Abstract
Migraine and glucose-related (glycaemic) traits (fasting glucose, fasting insulin, and type 2 diabetes) are common and complex comorbid disorders that cause major economic and social burdens on patients and their families. Studies on the relationship between migraine and glucose-related traits have yielded inconsistent results. The purpose of this review is to synthesise and discuss the information from the available literature on the relationship between fasting glucose, fasting insulin, and type 2 diabetes (T2D) with migraine. Publications on migraine and fasting glucose, migraine and fasting insulin, and migraine and T2D were identified from a PubMed and Google Scholar database search and reviewed for this article. Multiple publications have suggested that the comorbidity of migraine and glucose-related traits may have a similar complex pathogenic mechanism, including impaired glucose homeostasis, insulin resistance, reduced cerebrovascular reactivity, abnormal brain metabolism, shared genetic factors, neurotransmitters, and sex hormones. Furthermore, several studies have found a bi-directional link between migraine with insulin resistance and T2D. There is strong evidence for a biological association between migraine headache and glucose-related traits, and burgeoning evidence for shared genetic influences. Therefore, genetic research into these comorbid traits has the potential to identify new biomarkers and therapeutic targets and provide biological insight into their relationships. We encourage healthcare professionals to consider the co-occurrence of migraine with glucose-related traits in the evaluation and treatment of their patients.
Keywords: migraine, glycaemic traits, glucose, insulin, type 2 diabetes, genetic
1. Introduction
Migraine is a chronic neurological disease with repeated attacks of headache lasting between 4 and 72 h often accompanied by nausea, vomiting, photophobia, and phonophobia [1,2]. Migraine is considered a complex neurovascular brain disorder [2,3], and generally affects people during their most productive years (age 25–50) [4,5]. Migraine has a lifetime prevalence of 15–20%, and worldwide, it is the third most common medical disease and second most disabling neurological disease. In women, the lifetime and yearly prevalence of migraine is 33% and 18%, respectively, whereas it is 13% and 6% in men [6]. Studies conducted in the United States and Europe have shown that the rates of migraine in women (15–18%) are around three times higher in comparison to men (6–8%) [7]. Migraine is associated with a significant economic strain on patients, their families, and the community due to the loss of productivity and healthcare resource utilization [8]. Migraine, with a considerable annual expense of US $20 billion in the United States and €111 billion in the European Union, is a substantial cause for societal and economic concerns [6,9]. The International Headache Society (IHS) classifies approximately 95% of migraine headaches into two major clinical subclasses, migraine without aura (MO), affecting 70–80% of migraineurs, and migraine with aura (MA), where affected patients experience auditory, visual, and sensory hallucinations [10,11]. MA is also split into three main subtypes: migraine with brainstem aura, hemiplegic, and retinal migraine. Migraine can be categorised as episodic (EM) or chronic migraine (CM) according to the frequency of headache [12].
Furthermore, the complexity of migraine is increased by environmental factors that have been reported to play a significant role in triggering and continuing migraine in some sufferers. Environmental factors which may precipitate migraine include skipped or delayed meals, dehydration, hormonal changes, bright light, loud noise, oral contraceptives, and hormonal replacement therapies [13]. Different comorbidities like neurological, cardiovascular, psychological, and endocrine are strongly associated with migraine that can substantially affect disease progression and therapeutic and preventive approaches. In terms of cardiovascular comorbidities, the incidence of stroke [14], angina, and myocardial infarction [15], is increased in migraine (especially MA) patients, compared with non-migraine patients. The elevated risk in migraineurs for several cardiovascular diseases suggested that these pathologies are underpinned by a specific metabolic risk factor(s) and prompted numerous studies to detect common metabolic anomalies. Many studies have examined traits related to glucose metabolism (glycaemic traits). For almost a century, migraine has been associated with hypoglycaemia [16,17]. Reduced blood glucose levels have long been known to trigger or worsen migraine attacks in some patients [16,18,19,20]. Early experimental research suggests that the metabolic alterations produced by fasting or glucose or insulin administration can precipitate migraine attacks [21]. Insulin is also a vital regulator of brain glucose metabolism, and hypoglycaemia can induce migraine attacks in CM patients following prolonged fasting [22]. Other migraine studies have observed interictal impairments in glucose tolerance and insulin resistance [23,24]. Insulin is the key regulator of glucose homoeostasis, promoting glucose absorption from the blood into primarily fat and muscle cells via insulin-sensitive glucose transporters (GLUTs), in particular GLUT4 [17].
Although there are inconsistent results concerning the incidence of metabolic complications in migraine, CM patients have been reported with higher resistance to insulin [25]. Insulin resistance (IR) was found to be considerably greater compared to non-migraineurs in a study conducted in young, non-obese, and non-diabetic migraine sufferers [26]. However, IR is a key pathogenetic factor in developing type 2 diabetes (T2D). Conflicting results in various studies have been reported about the incidence of T2D in migraineurs [27,28,29]. In those patients, IR associated with CM can increase the risk of T2D that is more likely to occur when additional T2D related pathogenetic abnormalities are present [30,31,32]. Therefore, CM patients with higher IR may be more likely to develop T2D if related impairment occurs in the secretion of β-cell insulin [30,31,33]. A variety of illnesses, including dyslipidaemia, obesity, diabetes, high blood pressure, stroke, and coronary artery disease, are all associated with IR [34]. Since migraine and glucose-related traits are common disorders and often coexist, shared aetiologies can induce their comorbidity, and the combination of both conditions adds significant burdens upon society. Therefore, this narrative review will examine the relationship between migraine and glucose-related traits by focusing on observational epidemiological and genetic studies.
The most relevant observational epidemiological studies that support the shared biological mechanisms between migraine and glucose-related traits have been summarised in the first part of this study. The second section highlights shared genetics, including candidate genes and genetic variants involved in the pathophysiology of migraine and glucose-related traits. Finally, we highlight key findings and recommend future investigations on the comorbidity of migraines and glucose-related traits.
2. Methods
This narrative review used PubMed and Google Scholar databases to find English-language publications published up to March 2022, including original research and reviews articles. The goal of our study was to compile information from all studies (observational epidemiological studies, candidate gene association studies, and genome-wide association studies) that investigated the relationship between migraine and glucose-related traits. Search terms used “migraine” and “hypoglycaemia,” “migraine” and “blood glucose,” “migraine” and “glucose metabolism,” “migraine” and “insulin resistance,” “migraine” and “insulin metabolism,” “migraine” and “metabolic syndrome,” and “migraine” and “diabetes.” In addition, relevant articles were selected for the review according to specific headings. We also conducted an in-depth review of candidate gene association studies (CGAS) for migraine in this article (i.e., PubMed was searched using the terms “migraine” and “candidate gene study”). We then searched PubMed for overlapping CGAS for glucose-related traits (using the terms “diabetes” and “one migraine potential gene [e.g., “MTHFR”], and “candidate gene study”).
3. Results
3.1. Migraine and Hypoglycaemia
Hypoglycaemia (low blood sugar/glucose) is a medical condition that can trigger or exacerbate migraines and other headaches [16,35,36]. Blood glucose levels may drop too low when food intake is insufficient for the body’s needs. A similar condition can occur if someone avoids meals, maintains diet, and fasting condition. One of the first hypotheses is that hypoglycaemia possibly plays a causative role in fasting headaches. In general, serum glucose levels can be a significant and specific precipitating factor for certain migraine patients. It is widely known that lower blood glucose levels can trigger or deteriorate migraine attacks [18,20,37]. Fasting is one of the most well-known and frequently reported migraine triggers with a percentage range from 39% to 66% [13,38,39,40], and is very common in migraine patients during longer fasting [35]. In particular, some experts reported that small alterations of blood glucose might change pain receptors in the brain for some genetically predisposed individuals, which contribute to fasting headache [41]. Numerous clinical studies [13,42,43,44,45] endorse there is a well-documented link between fasting and migraine, including the studies related to fasting for religious purposes like Ramadan [46] or Yom Kippur [47]. An overnight fasting condition can trigger migraines in certain people [48]. Indeed, fasting, and missing meals can contribute to the development of migraines. For example, one study reported that migraine attacks had improved following correction of hypoglycaemia with intakes of orange juice for a 38-year-old obese woman with migraine [16]. The researchers showed the same results in four other individuals and concluded that decreased blood glucose was linked with headaches. These observations indicate that glucose deficit can trigger fasting-induced headaches directly or indirectly. Likewise, Blau and Cumings [18] noted that six of 12 patients suffered migraine headaches when fasting. Thus, the attacks might be induced by hypoglycaemia, and the ingestion of food was a simple way of preventing headaches. Furthermore, Blau and Pyke [49] once again pointed out that a significant reduction of migraine occurred due to the hypoglycaemia correction in T2D and migraine patients. Five of the 36 patients with migraine and T2D investigated by the authors resolved or reduced their migraine attacks after correction of blood glucose, and four were affected by migraine attacks by nocturnal hypoglycaemia. The migraine attack in six of the remaining 27 patients was associated with fasting or food skipping.
Clinical studies have shown that fasting result in activation of the insulin receptor. Surprisingly, intravenous insulin infusion is effective in causing migraine aura. Studies reported insulin-induced hypoglycaemia could lead to migraine-like pain since blood glucose levels dropped suddenly [19]. However, further evidence was provided a decade later with the finding that sucrose-induced reactive hypoglycaemia could trigger migraines [23]. Reactive hypoglycaemia refers to low blood sugar that is relatively uncommon, where a high-sugar meal induces hypoglycaemia, due to a rapid increase in blood sugar levels (hyperglycaemia), causing an insulin overproduction and triggering a rapid drop in blood sugar levels. Insulin is also a key regulator for brain glucose metabolism [24], and hypoglycaemia can lead to a migraine attack in migraine patients after prolonged fasting [35]. Dalkara and Kilic [41] wrote a review of the metabolism of brain glycogen during migraines. In astrocytes, the plasma glucose is stored as glycogen and quickly digested for glutamate and potassium uptake during the intensive synaptic activity of headache attacks. The authors proposed that extended periods of low blood glucose and sustained sympathetic activity in long-term fasting could diminish existing glucose derived from glycogen generated in presynaptic astrocytes and trigger aura and headache [41]. Magnetic Resonance Spectroscopy (MRS) investigations in migraines, for example, consistently demonstrate hypometabolism or reduced ATP levels due to anomalies of mitochondrial oxidative phosphorylation (OXPHOS) [50]. In addition, early investigations supporting these results indicated metabolic alterations resulting from fasting or administration of glucose or insulin can lead to migraine attacks in susceptible patients [23,24,26]. However, contrary arguments are made in ICHD-3beta [12] that state headache is not a common complaint in individuals with symptomatic hypoglycaemia. For example, insulin-induced hypoglycaemia did not produce headaches in most migraineurs studied [19]. In this study, Pearce et al. reported that headache occurred in two of the 20 individuals with migraines included in his research due to insulin-induced hypoglycaemia during a 2-h observational period. Thus, he concluded that migraine attacks might be caused by a rapid decrease in blood glucose and metabolic events [19]. Therefore, the assumption is that a sudden reduction of blood glucose levels could be attributed to migraine attacks and other metabolic events.
A hereditary state of altered glucose transport into the brain, GLUT1 (glucose transport protein type 1) deficient syndrome, is associated with hemiplegic migraine and migraine with auras [51]. Several heterozygous mutations have been found in the SLC2A1 encoding GLUT1 gene. These patients have a glucose transportation deficiency across the blood-brain barrier and have different neurological abnormalities [41]. This deficient syndrome of GLUT1 supports that glucose insufficiency can trigger migraine headaches. In addition, hyperglycaemia makes the cortex more resistant to the start of cortical spreading depression (CSD) and accelerates CSD recovery, while hypoglycaemia has the inverse effect on CSD lengths [52]. Insulin-induced hypoglycaemia dramatically prolongs the duration of CSD in experimental mice, which is thought to induce migraine aura and lead to headaches [52]. One experimental study published in 2017 found that the administration of insulin, glucagon, or leptin dramatically modulates the trigeminovascular system’s neuronal activity because of metabolic changes, which is a critical system in the pathogenesis of migraine headaches [53]. This reveals a possible neurobiological relationship between migraine and alterations in glucose homoeostasis [53]. Furthermore, recent bioinformatics analysis identified one of these single nucleotide polymorphisms (SNPs) (rs1024905, minor allele G), which is associated with increased migraine risk, is also associated with decreased expression of the C12orf5 gene in whole blood [54], cerebellum, and temporal cortex [55]. The C12orf5 gene was recently found to encode the TP53-inducible glycolysis and apoptosis regulator (TIGAR), which primarily acts as an inhibitory regulator of glucose breakdown (glycolysis) in human cells. Thus, decreased expression of TIGAR will result in increased glucose breakdown due to decreased blocking of glycolysis [56]. Hence, migraine sufferers carrying the rs1024905-G risk allele may also have increased glucose breakdown.
3.2. Migraine and Insulin Resistance
Migraine and metabolic syndrome are both prevalent and expensive conditions. Both disorders coexist, but there is an unclear relationship between the two processes. IR is one aspect of metabolic syndrome [57]. It is becoming apparent that the metabolism of insulin and glucose in migraine patients are affected and can play a pathophysiological function [57]. Furthermore, the 1-year migraine prevalence in metabolic syndrome was found to be increased to 11.9% of men and 22.5% of women who had higher body mass index (BMI), waist circumference, and a high proportion of diabetes mellitus [57]. Bic et al. [58] have proposed that biological conditions such as insulin resistance that increased free fatty acids and blood lipids could be an underlying cause of migraine headaches.
Two investigations have found that insulin sensitivity is reduced in patients with migraines, suggesting a role for insulin resistance in migraine and vascular disease comorbidity [24,26]. Clinical and epidemiological research has repeatedly linked migraine to depression, T2D, cerebrovascular diseases, and obesity, where insulin resistance is involved [59,60]. Furthermore, multiple investigations [60,61,62] have found that impaired glucose metabolism and insulin resistance are frequent pathophysiological aspects in T2D, obesity, depression, and dementia. Thus, insulin resistance may play a significant metabolic role in associating migraine and various comorbidities. When comparing the lowest to the highest quartile of homeostatic model assessment (HOMA), hyperinsulinemia is related to 5.67 times greater risk of migraine [63]. The plasma concentration of glucose in migraineurs was substantially more significant during the oral glucose tolerance test (OGTT) than in the controls. Several insulin sensitivity measures, such as ISI Stumvoll and OGIS-180, demonstrated an insulin resistance condition in migraineurs [26]. Cavestro et al. reported that both glucose and insulin were considerably higher (p < 0.001) in patients than in healthy controls after OGTT in a larger group of 84 migraine patients [24]. More recently, several clinical trials confirmed the incidence of insulin resistance in patients suffering from both episodic and chronic migraines [22,64,65]. Another study indicates that episodic migraine patients were normal in terms of insulin sensitivity, but chronic migraine subjects have been significantly linked to increased insulin resistance [22,66]. The risk of physical and mental illnesses such as hypertension, depression, and diabetes has increased in people with chronic migraines compared with those with episodic headaches [28]. Contrary to the results of most published studies, a few studies have not supported a relationship between migraine and IR [67,68]. However, these studies examined IR in migraineurs using fasting glucose and insulin levels rather than during a dynamic test such as OGTT. For example, one study by Sacco et al. [68] investigated 50 migraineurs with aura, 50 migraineurs without aura, and 50 controls and reported that migraine was not associated with IR.
The precise pathophysiological changes that could cause an association of migraine with IR are unclear. Brain metabolism and cerebral blood flow [69,70] are regulated by insulin through insulin receptors located in many brain parts; however, how these receptors transmit signals and exert resistance on its function remains uncertain. New research has revealed that insulin significantly influences glucose and energy homeostasis within the brain, even though the brain was long considered an insulin-independent organ [71]. According to some experts [60], peripheral insulin resistance (IR) can spread to the brain, resulting in brain insulin resistance. During times of high metabolic demand, this condition has been shown to lower insulin receptor levels in neurones and astrocytes, resulting in a decrease in glucose absorption and glycogen formation, which could trigger the neuronal cell stress associated with migraine chronification [60]. Two genetic studies have identified an important link between insulin receptor (INSR) gene polymorphisms and migraine [72,73]. These polymorphic gene-coded receptors, assessed in mononuclear cells, did not demonstrate in vitro functional problems but could be potentially dysfunctional in vivo, particularly in the hypothalamus and limbic areas where many receptors are expressed [74]. However, it is not clear whether the associated polymorphism in the INSR gene causes loss or increased function. Furthermore, insulin may be implicated in migraine pathophysiology because it is linked with glucose metabolism and directly impacts gonadotropin secretion through the hypothalamus [69]. Studies in laboratory rats have demonstrated that insulin induces the secretions of gonadotropins from the hypothalamic and pituitary glands [75]. The hypothalamus’ central involvement in autonomic function and homoeostasis indicates that it may contribute to some autonomic symptoms linked with migraine [76,77,78] or its prodromal phase [77,78]. Activating the brainstem regions and hypothalamus before the onset of pain shows that these structures play an important role in migraine’s pathophysiology [79,80]. Positron emission tomography (PET) showed for the first time that spontaneous migraine attacks activate the hypothalamus and demonstrate that the hypothalamus is implicated relatively early in a migraine attack [80]. Estroprogestin medications also cause hyperinsulinism and hypoglycaemia, aggravating migraines in individuals who receive these medicines [81]. This connection may explain the strong links between insulin and female sex hormones and the deterioration of migraines due to estroprogestins, and it could support the theory of menstrual migraines [24].
Calcitonin gene-related peptide (CGRP) is well known to be involved in migraine pathophysiology [82,83], with serum concentrations of CGRP being shown to be increased during migraine attacks [84], resulting in sensitivity of the trigeminal system [85]. Besides its role in migraines, animal studies revealed an association between CGRP and the modulation of insulin and glucagon production [86,87]. Therefore, higher plasma insulin levels in migraine patients can also be caused by CGRP, a neuropeptide expressed in sensory nerves associated with glucose metabolism and plays a vital role in migraine pathogenesis [88]. Furthermore, CGRP antagonism via receptor antagonists or by monoclonal antibodies reduces and prevents migraines [89]. CGRP is known to induce resistance to insulin and obesity [90] by decreasing the release of insulin from β-cells [91]. One study reported that CGRP is higher in obese and diabetic Zucker rats, and administration of capsaicin, a sensory nerve blockade, reduces blood glucose following an oral glucose tolerance test and enhances the sensitivity to insulin [92]. These authors later revealed that the sensory neurons of the pancreatic islets carrying CGRP are sensitive to capsaicin. Capsaicin inhibits them with a consequent positive effect on the secretion of insulin and glucose tolerance [86].
3.3. Migraine and Diabetes Mellitus
Diabetes mellitus (DM), usually referred to as diabetes, is a chronic lifelong disorder caused by reduced pancreatic production of insulin or the inefficiency of the generated insulin, referred to as insulin resistance. This deficiency leads to increased glucose concentrations in the blood, damaging many systems of the body. There are two primary forms of diabetes: type 1 diabetes (T1D), an autoimmune disease that occurs most often in children and adolescents, and T2D due to the body’s failure to respond adequately to insulin triggered by the pancreas. T2D impacts all ages, with a global prevalence of 9.3% [93]. The possible association between migraine and diabetes remains unknown due to conflicting findings. Some studies reported diabetes to have a protective effect for migraine, some studies suggest diabetes increased the risk for migraines, while other studies report no association between the two conditions.
Migraine is also linked to insulin resistance, suggesting a relationship between migraine and T2D. Several studies have shown that disabled insulin sensitivity in migraines contributes to the possibility of increasing the risk of T2D for migraine patients [29,94,95]. Population-based cross-sectional analyses were conducted by Bigal et al. [27], which was included in the American Migraine Prevalence and Prevention (AMPP) study demonstrated that people who had a migraine in the previous year were more likely than headache-free controls to have T2D (12.6% versus 9.4%; odds ratio (OR) = 1.4, confidence interval [95% CI: 1.2–1.6]). However, the prevalence of diabetes among patients with episodic and chronic migraines did not differ in the same populations [28].
In contrast, some studies have documented an opposite association between diabetes and migraine [96,97,98,99,100]. For example, Nord–Trøndelag Health Surveys [99] indicated that type 1 diabetes (T1D) is associated with decreased migraine prevalence (OR = 0.47, confidence interval [95% CI: 0.26–0.96]), and any other type of headaches (OR = 0.55, [95% CI: 0.34–0.88]) compared to a patient without DM. While many studies did not distinguish between T1D and T2D, a cross-sectional analysis of the HUNT study data [96] indicated that the prevalence of migraine in both types 1 and 2 DM is less likely to be reported than individuals without DM in the last year (multivariable-adjusted OR = 0.4, confidence interval [95% CI: 0.2–0.9] for T1D and migraine and multivariable-adjusted OR = 0.7, [95% CI: 0.5–0.9] for T2D and migraine). In addition, the Norwegian cohort study [100], consisting of men and women under 80 years of age, demonstrated that both types 1 and 2 DM were related significantly with reduced risk of migraine (OR = 0.74, confidence interval [95% CI: 0.62–0.89]) and (OR = 0.86, confidence interval [95% CI: 0.80–0.92]). This result is in line with other findings from an old clinical survey [49] by Blau and Pyke that shows that the onset of diabetes greatly reduces the incidence of migraine attacks in migraine patients.
Likewise, analysis of data from the Women’s Health Study (WHS) cohort [29] of women without DM at baseline revealed that individuals with a history of migraine, active MA, or active MO were at reduced risk (OR = 0.79, confidence interval [95% CI: 0.67 to 0.94]) of acquiring T2D as compared to non-migraineurs women. In addition, Fagherazzi et al. [101] examined the association between migraine and drug-treated T2D in French prospective cohort research. This study has shown a lowered risk for developing T2D for women with active migraines and a decrease in the prevalence of migraines in patients with T2D. Notably, the prevalence of migraine in this cohort reduced from 22 to 11 percent during the 24 years prior to T2D diagnosis, which implies that diabetes may protect against migraine. Early case-control research [98] similarly revealed a reduced migraine frequency in people with DM compared to individuals without DM. A cross-sectional study [97] in Norway based on an analysis of data on the prescription of medicines produced similar conclusions. Compared to the non-diabetic group, the study found that people with DM had an overall reduced prevalence of medically-treated migraines and the pattern became more evident with increasing age. Age may also be a significant effect modifier in the relationship between T2D and migraine, indicating an opposite association among older people [100]. However, large-scale population-based investigations have revealed no statistically significant difference in migraine incidence between children with T1D versus controls [102]. Similarly, studies by López-de-Andrés et al. [103] and Haghighi [94] showed that migraine prevalence between those with and without diabetes is not significantly differentiated. It is particularly interesting to see the relationship between headache and DM, as the DM has an impact on vascular reactivity [104,105], and causes diabetic neuropathy [106], and contributes to changes in the style of life that can all be significant in migraine pathophysiology. Migraine and diabetes both have lifestyle-related factors that play a role in their aetiology and pathophysiology [107]. Lifestyle changes can alter the functioning of both central and autonomic nerve systems, which can lead to migraine attacks or diabetes. A higher incidence of migraine attacks is associated with smoking, alcohol consumption, and sedentary life in people with diabetes [107]. Several studies have found that migraine sufferers may benefit from weight loss and lifestyle slimming techniques, including physical activity, exercise, and sports [107,108]. At present, the specific biological mechanisms behind this apparent protective effect of diabetes on the risk of developing migraine attacks are unknown. Considering the preceding discussion, the probable biological mechanisms of comorbidity between migraine and glucose-related traits can be found in Figure 1.
Figure 1.
Possible mechanisms describing the relationship between migraine and glucose-related traits. Cortical spreading depression (CSD) in migraine stimulates pain pathways originating in the parasympathetic trigeminal nerve fibres, resulting in the production of calcitonin gene-related peptide (CGRP) [52,84,85]. It is suggested that CGRP expressed in sensory nerves associated with glucose metabolism and plays a vital role in migraine pathogenesis [88]. A change in blood glucose level is another significant aspect in this association where hyperglycaemia makes the cortex more resistant to the start of CSD and accelerates CSD recovery. At the same time, hypoglycaemia has an inverse effect on CSD length [52]. Low blood glucose and sustained sympathetic activity in long-term fasting could diminish existing glucose derived from glycogen generated in presynaptic astrocytes and trigger aura and headache [41]. In migraine, magnetic resonance spectroscopy (MRS) investigations demonstrate hypometabolism or reduced ATP levels due to mitochondrial oxidative phosphorylation (OXPHOS) anomalies, which can lead to migraine attacks [50]. In diabetes, sensory nerve damage due to lower CGRP expression may have diminished CGRP-induced vasodilation and nociceptive effects, which can explain the decreased prevalence of active migraine [101].
3.4. Migraine and Glucose-Related Traits: Lifestyle Changes and Treatment
A low-glycaemic diet may be a beneficial and effective approach in treating migraine headaches [109]. This diet has been suggested as a way to reduce inflammation [110]. A diet high in fat and low in carbohydrate (ketogenic diet) works similarly to fasting, where ketone bodies are raised and can be utilised as an alternate energy source to repair anomalies in glucose metabolism observed in migraines [111]. The idea that migraines result from insufficient brain energy or uncompensated oxidative stress has reintroduced the ketogenic diet into the spotlight. A low-calorie ketogenic nutritional plan is widely used for weight loss, as well as for the treatment of various pathologies, including neurological conditions [112]. This diet has recently demonstrated encouraging results in migraine prevention, potentially influencing numerous pathophysiological systems [113]. For instance, the ketogenic diet can improve mitochondrial function, reduce oxidative stress, lower cerebral excitability, suppress inflammation and decrease cortical spreading depression [111]. A recent double-blind, crossover study by Di Lorenzo et al. compared the preventative effects of a very-low-calorie ketogenic and non-ketogenic diet for one month in 35 overweight migraine sufferers. The ketogenic diet was significantly more effective than the non-ketogenic diet in lowering monthly migraine days. For example, the 50% responder rate for monthly migraine days was 74.28% (26/35 patients) during the ketogenic diet, but only 8.57% (3/35 patients) during the non-ketogenic diet [114]. In addition, a longitudinal study found that following nutritional advice based on the Healthy Eating Plate (HEP), especially reducing carbohydrate, red and processed meat consumption, was associated with a reduction in migraine frequency and disability [115]. Given lifestyle modifications can be effective in migraine therapy, especially when migraine is associated with other diseases such as glucose-related traits, primary care physicians have developed SEEDS (Sleep, Exercise, Eat, Diary, and Stress) guidelines to assist migraine patients change their lifestyle components [111].
3.5. Shared Genetic Basis
Twin and family studies provide numerous approaches to determine familial aggregation, environmental contributions, and genetic influences on disease. Classical twin research compares the similarities between monozygotic (MZ) twins to dizygotic (DZ) twins, whereas familial studies normally include parent-offspring pairs or sibling pairs. Genetically linked individuals (for example, twins) can increase the power of genetic research to detect the genetic variations potentially related to complex diseases [116]. Family and twin studies have shown that migraine tends to occur in families, and there are robust genetic components that can lead to the development of migraine in an individual, familial hemiplegic migraine (FHM) is the best example because it is a severe and rare monogenic form of MA which follows an autosomal dominant pattern of inheritance [117]. Higher concordance of disease rate in monozygotic twins than dizygotic twins have been consistently found in twin studies, indicating a significant genetic contribution to migraine [118,119,120,121,122,123]. The estimated heritability of migraine is 33–65% (depending on migraine-type—MA or MO) [118,124,125]. The heritability estimate describes how much of the phenotypic variation of migraine in a population is due to genetic factors. Even when twins have grown apart, the increased concordance of migraine among MZ twins continued [126,127,128,129,130], undermining the possible effects of common (shared) environmental factors and thus supporting the prominent roles of genetics and non-shared environmental factors in the aetiology of the disease.
Intense genetic research has also been performed on glucose-related traits such as fasting glucose, insulin measures, and glycated haemoglobin (HbA1c), used to diagnose, and control T2D, which are also important risk factors for migraine even in the non-diabetic range. Genetic and environmental factors influence the fasting blood glucose (FPG) level. Higher than optimal levels of FBG can also result in increased morbidity and death, even if less than the diagnostic diabetes threshold (FBG ≥ 7.0 mmol/L is the diagnostic criterion for diabetes) [116]. The chance of developing microvascular illness, such as heart attack or stroke, starts to rise long before this diagnostic threshold [129]. Diabetes and higher than optimal FPG levels combined resulted in 3.7 million deaths worldwide between 1980 and 2014 [116]. The heritability for fasting glucose ranges from 10–75%, and for fasting insulin, it is 20–55% [130]. Twin and family research have long indicated the genetic components to the susceptibility of T2D. T2D runs in families, and genetic as well as environmental factors affect the likelihood of developing T2D disease [131]. Heritability estimates of T2D range from 25% to 80% [131]. These differences in heritability may be linked to the study designs and/or reflect significant variations as heritability can depend on gender, age, or background [130]. Furthermore, twin studies show very strong concordance (70%) for MZ twin pairs, whereas the concordance in DZ twins is only 20–30% [131].
Migraine and glucose-related traits can have a shared genetic basis. Several migraine comorbidities are explained by common genetic risk factors [132,133,134]. This concept can explain some of the associations between migraine and glucose-related traits. A range of metabolic and nociceptive processes are modulated by certain neurochemicals, including nitric oxide and CGRP. Genetic risk factors that contribute to insulin resistance and impaired glucose metabolism may also lead to migraine headaches.
Although twin and family studies indicate substantial evidence for genetic components in migraine and glucose-related traits, no twin studies have examined their shared heritability (genetic correlation). However, in 2020 Siewert and colleagues [135] performed cross-trait linkage disequilibrium score regression (LDSC)—an approach to estimate trait heritability and genetic correlation from genome-wide association study (GWAS) results [136]—between migraine and multiple traits and reported a significant study-wide genetic correlation (p < 1.06 × 10−3) between migraine and T2D. Although subsequent Mendelian randomisation analysis did not indicate a causal effect of T2D on migraine, the observed genetic correlation suggests shared genetically determined mechanisms contribute to their co-occurrence—e.g., neurovascular mechanisms associated with T2D may contribute to migraine risk. Thus, identifying specific shared genetic risk factors for migraine and glucose-related traits has potential to advance our understanding of the comorbid pathophysiology between them and can be accomplished using two fundamental approaches: candidate gene association studies and genome-wide association studies.
3.6. Candidate Gene Association Studies
In genetic association research, candidate gene studies have identified risk variants related to a specific disease. CGAS are comparatively cheap and easy to perform, focusing on selecting genes that have previously been linked to the disease somehow. The candidate gene approach starts with selecting a putative candidate gene based on its relevance to the known or hypothesised disease mechanism under investigation. For example, the study of candidate gene associations found that about 200 genetic variations in around 100 genes can be related to a more common form of migraine [137]. These findings, however, have been inconsistent and proven difficult to replicate. Researchers have worked over decades to uncover the role of genetics in glucose-related traits using epidemiology research, candidate gene investigations, and family linkage studies. CGAS also identified genes associated with glucose-related traits before genome-wide association studies (GWAS), but many of these findings were not replicated [138,139,140,141]. Nonetheless, several candidate genes have been thoroughly examined, including those involved in the pathways hypothesised to be pathophysiology related to both disorders. Interesting overlapping candidate genes for migraine and glucose-related traits are MTHFR, INSR, TNF, ESR1, NOS3, and PON1. The overlapping candidate genes suggest potential common biological mechanisms behind migraine and glucose-related traits. Table 1 outlines some of the candidate genes that are associated with migraine and glucose-related traits.
Table 1.
A summary of candidate genes commonly associated with both migraine and glucose-related traits.
| Candidate Genes | Function of Relative Protein | Polymorphisms | Migraine | Glucose-Related Traits | ||
|---|---|---|---|---|---|---|
| Supporting Association (Reference) | Not Supporting Association (Reference) |
Supporting Association (Reference) | Not Supporting Association (Reference) |
|||
| Methylenetetrahydrofolate reductase (MTHFR) | MTHFR enzyme transforms 5, 10-methylene tetrahydrofolate to 5-methyl tetrahydrofolate, an essential part of folate and homocysteine metabolism | C677T | [142,143,144] | [145,146] | [147,148,149] | [150,151] |
| Insulin receptor (INSR) | INSR mediates insulin’s activity on target cells and plays an important function in the regulation of glucose homeostasis | Val985Met, other polymorphisms | [72,73] | [152,153] | [154,155] | [156] |
| Tumour necrosis factor (TNF) | TNF initiates and regulates the chain of events that leads to an inflammatory response | −308 (G/A) | [142,157] | [158,159,160] | [161] | |
| −238 (A/G) | [162] | [163,164] | ||||
| Estrogen receptor 1 (ESR1) | ESR1 has expressed variety of different tissues and organs, including vascular endothelial cells and trigeminal neurones with the linked with hormone system | Pvull (−397 T>C, rs2234693) and Xbal (−351 A>G, rs9340799) | [165] | [166,167] | ||
| G594A | [168,169,170] | [171] | ||||
| Nitric oxide synthase 3 (NOS3) | NOS3 synthesise nitric oxide from L-arginine, a crucial endogenous endothelial-derived relaxing factor | VNTR (27 bp) in intron 4 | [172,173] | [174] | [175,176,177] | |
| Glu298Asp | [178,179] | [172] | [180,181] | |||
| Paraoxonase 1 (PON1) | Enzyme involved in preventing LDL oxidation and endothelial dysfunction | Gln192Arg | [182] | [183,184] | [185,186,187,188] | |
3.6.1. Methylenetetrahydrofolate Reductase
Methylenetetrahydrofolate reductase (MTHFR) transforms 5, 10-methylene tetrahydrofolate to 5-methyl tetrahydrofolate, an essential part of folate and homocysteine metabolism. The most important genetic variant is the MTHFR C677T polymorphism that causes hyperhomocysteinemia. The C677T polymorphism is a C to T transition at base pair 677, linked to reduced MTHFR activity as this transformation leads to an amino acid change from alanine to valine. The MTHFR C677T polymorphism can reduce enzyme activity by 65% and raise plasma total homocysteine levels, especially in the presence of low dietary folate. Homocysteine levels were found to be higher in migraine patients with aura [189]. Hyperhomocysteinemia (high level of plasma homocysteine) can lead to endothelial dysfunction, which in turn could contribute to the development of cortical spreading depression (a process involved in migraine aura pathogenesis) [189]. High homocysteine levels are linked with T2D via insulin resistance as homocysteine was found to have adverse effects on β-cell glucose metabolism and cell viability, thereby impairing insulin secretory activity [147]. Previous epidemiological research also indicates that migraine [190,191] and T2D [147,148] can be related to the C677T genetic polymorphism of MTHFR.
Rubino et al. [142] performed a meta-analysis comprising 2961 migraineurs (2170 patients with MA and 791 patients with MO), linking the MTHFR C677T polymorphism to migraine, and found evidence that MTHFR was associated with MA only (OR = 1.30, 95% CI [1.06–1.58]). Likewise, the meta-analysis carried out by Schurks et al. [143] found a similar observation that an elevated risk of MA (OR = 1.48, 95% CI [1.02–2.13]) was linked to the MTHFR 677TT genotype among non-Caucasians. Furthermore, Samaan et al. carried out a meta-analysis [144], which included five Caucasian datasets, showing that the TT genotype was associated with both MA and MO in non-Caucasians, whereas for the Caucasians, this variant was associated only with MA. In contrast, several investigations have reported the TT genotype to be associated with a reduced risk for MA [192,193]. However, a German study [145] with 656 MA patients and 625 controls did not supported the association between MTHFR TT genotype and MA, and similar results were observed in a Finnish study [146] comprising 898 MA and 900 controls.
According to recent research, there is a link between C677T and T2D susceptibility. A meta-analysis by Zhu et al. [147] was undertaken in 2014 in China better to identify the function of C677T polymorphism in T2D. This meta-analysis comprised 4656 T2D cases and 2127 controls from 29 studies, and they identified a significant relationship between the polymorphism of MTHFR C677T and T2D. Wang et al. [148] also observed in a study carried out in China in 2014 that C677T polymorphism in MTHFR can contribute to the risk of T2D. A further study by Khalid et al. [149] noticed that the relationship of MTHFR C677T and T2D was significant with the Arab population. However, Errera et al. [150] found no evidence for an association between the 677TT polymorphism of MTHFR and T2D in Brazilian populations in 2006. Similarly, no association was found for MTHFR C677T polymorphism in T2D development in case-control research in the Brazilian population with 47 T2D cases and 78 controls [151].
3.6.2. Insulin Receptor
The insulin receptor (INSR) is a membrane protein on every cell’s surface and part of the tyrosine kinase receptor family [194]. The insulin receptor gene consists of 22 exons and 21 introns and spans about 120 kilobases, which maps to the short arm of 19p13.3–p13.2 chromosomes. The mature INSR is a hetero-tetramer that consists of two α-subunits and two β-subunits. Exons 1–11 code for the receptor’s α-subunits, while exons 12–22 code for the receptor’s β-subunits. Exon 2 codes the insulin-binding domain of the insulin receptor protein, while the protein tyrosine kinase domain needed for the insulin action is encoded by exons 17–21 [194]. INSR regulates insulin’s activity on target cells. Insulin’s metabolic function is governed by a series of chemical events that begin with insulin attaching to its receptor [195]. When the insulin signalling pathway is activated, the glucose transporter 4 (GLUT4) is translocated to the cell surface, allowing glucose to enter the cell. Thus, genes in the insulin signalling pathway, such as the insulin receptor (INSR), insulin receptor substrates 1 and 2 (IRS1 and IRS2), and GLUT4, are attractive candidates for insulin resistance [196]. However, the precise mechanisms for mediating insulin resistance remain unclear. Any defect in INSR might lower the insulin’s action and lead to resistance to insulin, resulting in T2D [197].
In many different populations, the function of the INSR Val985Met variant in the predisposition to disease has been investigated. However, the findings remain inconclusive, with some research showing relevance for this variant [154,155], while others do not support this finding [156,198]. One study conducted in a Danish population found no significant association between Met985 polymorphism and T2D [156]. In contrast, the Met985 polymorphism was found at a higher frequency in T2D people (5.6%) compared to control (1.3%) participants (OR = 4.49, 95% CI [1.65–12.26]; p = 0.005) in a Dutch population sample recruited in Rotterdam [155]. Another study in the Netherlands, comprised of a sample gathered from Hoorn, found that the occurrence of the Met985 polymorphism in T2D patients (3.7%) and control subjects (2.7%) were similar [154]. However, a joint analysis of data from Hoorn and Rotterdam indicated a significant association between the Met985 polymorphism and T2D with a frequency of 4.4% in T2D cases compared to 1.8% in controls [154].
Factors contributing to insulin resistance and T2D have also been linked to migraine. McCarthy et al. identified polymorphism of five single-nucleotides in the insulin receptor gene in 16 North American families that were significantly associated with typical migraines, implying that the insulin receptor may play a role in the disease’s pathogenesis [72]. In addition, they have reproduced a few of their findings in an independent Australian study of 255 patients with MO and MA and 237 controls. In this investigation, 16 polymorphisms in the insulin receptor gene were genotyped in two Caucasian samples comprising a total 827 North American MA and MO patients and 765 controls. MA was most strongly linked to one exonic and two intronic variants (rs1799817, rs2860172, and rs2860174, with allelic p-values of 0.008, 0.002, and 0.007, respectively) in one of the samples of North American origin. In the combined study of both American samples, rs2860174 that was the only variant which was significant regardless of sex. Similar results from a large sample in a German population were reported by Netzer and colleagues [73], in which one of the five SNPs (rs2860174) showed allelic association at a significant level (p = 0.005). However, an Australian study [154] on one large family and a Finnish linkage study [153] on 72 families found no linkage between the region of INSR and migraine with aura.
3.6.3. Tumour Necrosis Factor
Tumour necrosis factor (TNF) is a major pro-inflammatory cytokine that initiates and regulates the chain of events that leads to an inflammatory response [199]. TNF (previously called TNF-α) and lymphotoxin-α or LT-α (previously called TNF-β) are members of the same TNF superfamily and are coded by the same gene cluster [200]. The promoter variants −308 A/G and −238 G/A in the TNF-α gene (TNF) influence transcriptional regulation of the gene coding for LT-α (LTA) [200]. TNF has a polymorphism at position −308 in the promoter region, with either a G (TNFα1) allele or an A (TNFα2) allele [199]. The TNFα2 allele has been associated with several autoimmune diseases as it is a stronger transcriptional activator relative to the TNFα1 allele, resulting in higher levels of TNF [199].
An Italian study, for example, Rainero et al. [199], discovered an association between migraine and the −308 (G/A) polymorphism in TNF, located in the human leucocyte antigen (HLA) class III region. In MO patients (OR = 3.30, p < 0.001) the TNF −308 (G/A) polymorphism has been linked to the migraine occurrence, with individuals homozygous for the G allele have an increased risk for migraine. In a similar study from Iran, Mazaheri et al. [157] found that MO patients had a higher frequency of the −308 A allele than the control subjects (40.6% versus 22.3%, OR: 3.73, confidence interval: [95% CI 2.4–5.82], p < 0.0001), and thus suggest that TNF or a locus in linkage disequilibrium (LD) with TNF could be involved in the risk of migraine.
Increased TNF-α concentrations are closely associated with hyperinsulinemia and body mass index (BMI) [163]. TNF-α can disrupt insulin release and the insulin effect by interfering with insulin signalling pathways and affecting the synthesis, secretion, and activities of other cytokines. TNF-α expression in adipose tissue has been linked to insulin resistance, which is considered a key pathogenic mechanism in the development of T2D [163]. Several research investigating the relationship between TNF polymorphism with insulin resistance and T2D risk have been published in various countries [158,159,161]. The conclusions of these investigations, however, are mostly inconsistent. For example, Day et al. [162], found a significant association between the TNF-238G/A polymorphism and a decrease in insulin resistance in UK populations. At the same time, Valenti et al. [201] reported that patients with the TNF −238 A allele had higher levels of insulin resistance and higher incidence of impaired glucose tolerance. In response to a fat-rich meal, the −308 G/A TNF polymorphism is independently associated with fasting glucose concentration, postprandial triacylglycerol levels, and BMI [202]. In 2014, a meta-analysis carried out by Zhao et al. [158] showed that the polymorphism TNF −308 A allele in T2D increased by around 21%. Similarly, Golshani and his colleagues [174] discovered, in Iranian populations, a greater risk of T2D development associated with TNF −308 G/A genotype. A further study found that the TNF −308 A/G polymorphism was significantly associated with a higher risk of T2D in the Chinese Han population [160]. In contrast, Feng et al. [161] conducted a meta-analysis and found no significant association between the TNF −308 G/A polymorphism with T2D risk in Caucasian and Asian populations. In the same context, the findings of two small-sample meta-analyses have revealed that TNF −238 G/A was not associated with T2D [163,164].
3.6.4. Oestrogen Receptor 1
In humans, there are two oestrogen receptor (ESR) isoforms: oestrogen receptor α (ESR1) and oestrogen receptor β (ESR2) [165]. ESR1 appears to be the dominant oestrogen receptor. Apart from the reproductive system, Oestrogen receptor 1 (ESR1) is a gene found on chromosome 6q25.1 that is expressed in numerous tissues and organs, including bone, intestinal tract, macrophages, and vascular endothelial cells. The most widely studied polymorphisms of the ESR1 gene are Pvull (−397 T>C, rs2234693) and Xbal (−351 A>G, rs9340799) [165]. Recent research has suggested that the genetic variants of ESR1 gene have a role in the development of migraine [168]. In two separate Australian case-control populations [168], the G594A SNP in exon 8 of ESR1 was positively associated with to migraine. In the same populations, an investigation of the progesterone receptor (PGR) also revealed an association. Moreover, a combined study of both hormonal genes revealed that the insertion of the Alu allele in intron 7 (PROGINS) combined with the 594A ESR1 allele increased the risk of migraine by 3.2 fold [169]. However, follow-up investigations of two other ESR1 polymorphisms in intron 1 and exon 4 (G325C) by the same group, found no association [203]. This is contrasted with research in a Spanish population [171] that found an association with the G325C polymorphism but not with the original G594A polymorphism. A bigger Finnish cohort study [146], examining 26 SNPs across the ESR1 gene, found no correlation with migraine, as did another Spanish study that looked at three SNPs and found no association.
Findings from several studies indicate migraine is more common in women during adolescence [204] and can be altered in different reproductive stages such as pregnancy, menopause, menstrual cycle, and hormone therapy [205,206]. This strongly suggests that fluctuating hormone levels, especially oestrogen, may play a role in precipitating a migraine attack. Previously, it has been assumed that prolonged exposure to high oestrogen levels before reducing in concentrations (oestrogen withdrawal) can cause migraine occurrence [207]. Furthermore, vascular effects of steroid hormones, like the modulation of nitric oxide generation and, hence changing vascular tone [208]. This all can be related to the pathophysiology of migraines. Schurks and colleagues [170] reported association between migraine and G594A and C325G polymorphisms of ESR1, which were shown to be dominant and recessive, respectively. Oterino et al. [209] conducted a study involving a multi-locus investigation of five polymorphisms related to oestrogen to resolve some of the contradicting results on ESR1, finding ESR1 and ESR2 polymorphisms association with MA/MO, but FSHR polymorphisms association with only MA at a nominal significance level (p < 0.05). These findings support the idea that hormones and/or hormone-related genes may play a role in migraine risk.
Recent research has reported that variants in ESR1 have a significant role in developing T2D and metabolic syndromes; however, the results were conflicting [210]. The ESR1 gene has a critical role in metabolic homeostasis. In animal studies, male and female ESR1 gene knock-out mice have acquired metabolic syndrome characteristics including obesity due to decreased fatty acid oxidation, impaired glucose tolerance, and reduced insulin sensitivity [210]. Although a study of 47 Caucasians [166] with T2D reported no substantial difference in the allelic frequency of Pvull polymorphism of ESR1 between type 2 diabetic and control groups, there was, however, a significant association between Pvull polymorphisms and T2D in African-Americans, European-Americans [166,167], Hungarians [211] and Egyptian women [212]. In 2018, a meta-analysis of eight studies found that T2D was associated with Pvull (OR = 0.673, 95% CI: [0.550–0.823]) but not the Xbal polymorphism. In this study, the Pvull C allele was associated with a decreased risk of T2D in Chinese, whereas the Xbal G allele was associated with a decreased risk of T2D in Caucasians [165]. Wei et al. [138] reported that the rs722208 variant of ESR1 was associated with fasting plasma glucose (FPG) (p = 0.045) in Han Chinese T2D patients by analysing the association between candidate gene mutations and quantitative traits related to metabolic syndrome. Another study [213] reported that the rs2207396 ESR1 polymorphism was associated with an increased risk for T2D in hypogonadal men.
3.6.5. Nitric Oxide Synthase 3
Genes encoding for endothelial function are interesting candidate genes for T2D and migraine. Nitric oxide (NO) is a crucial endogenous endothelial-derived relaxing factor produced from L-arginine by a group of enzymes known as neuronal synthase (NOS1), inducible synthase (NOS2), and endothelial synthase (NOS3) [180]. NOS1 and NOS3 are most likely to contribute to whole-body NO generation [180]. The NOS3 gene, located on 7q35–36, is primarily expressed in endothelial cells [180]. Many studies recently linked NOS3 gene polymorphisms with an increased risk of migraine, insulin resistance, and T2D; however, the findings were not always conclusive.
DM and its consequences were also linked to impaired NO production [214]. Among the several functions of NO, Pieper [215] concluded that NO alterations play a major part in developing insulin resistance and T2D by showing its capability to modulate peripheral and hepatic glucose metabolism and insulin production. Several investigations have been performed to identify the relationship between T2D and NOS3 polymorphism [175,176,180]. The research found that the 4a allele for the 4b/4a VNTR increases the risk of developing type 1 and type 2 DM [175,176,177]. Furthermore, this allele was related to endothelial dysfunction in diabetic individuals, implying that the 4a allele reduces NO bioavailability and contributes to diabetes susceptibility [214]. In addition to the 4a allele, the Asp allele for polymorphism Glu298Asp related to diabetes risk [176,180], and it appears that this association is especially important for obese individuals [181]. The NOS3 −786 T>C and Glu298Asp polymorphisms were also linked with diabetic nephropathy [216].
Genetic susceptibility to migraine has been linked to the polymorphism in the NOS3 gene. Despite diverse pathogenetic processes in migraine, there is compelling evidence that NO plays a critical role in migraine pathogenesis [217]. NO is a key mediator in modulating cerebral blood flow and leads to the activation of nociceptors in the trigeminovascular system during a migraine episode [217]. In this context, migraine risk was associated with the variant genotypes for −786 T>C polymorphisms [178]. In comparison to the controls, the Asp/Asp genotype for the Glu298Asp polymorphism was related to a 2-fold increase in migraine risk and a 3-fold increase in migraine with aura risk compared to migraine without aura patients [179]. Furthermore, the Glu298Asp polymorphism was associated with headache pain intensity and the age at which migraines begin [178]. Other research, however, found no association between NOS3 polymorphisms and migraine [147,172]. While one study found no link between NOS3 haplotypes and migraine [174], another more extensive analysis included variants for the −786 T>C, −665 C>T, 4b/4a VNTR, and Glu298Asp polymorphisms, as well as the tagSNP rs743506, found interesting results [173]. This study observed that NOS3 rs743506 and NOS2 2087G/A interact significantly in patients with migraine compared to control (p < 0.05), and this combination impacts the susceptibility to migraine [173]. The haplotypes C-C-4a-Glu-G and C-C-4b-Glu-G were identified more commonly in women with MA than for women with MO [172]. Thus, this study suggests that NOS3 haplotypes may influence the sensitivity to aura in migraine patients despite the lack of associations between NOS3 haplotypes and migraines [172].
3.6.6. Paraoxonase 1
Paraoxonase 1 (PON1), a polymorphic enzyme coded for the PON1 gene on chromosome 7q21.3, has a vital function in the metabolism of many organophosphorus products, such as pesticides, neurotoxins, and aryl esters, and is mainly generated in the liver [182]. Two nonsynonymous polymorphisms, 8638 bp apart, were shown to influence PON1 activities: substitutions of leucine to methionine at position 55 (55L/M, rs854560, c.220 T>A as per GenBank accession number NM 000446) and substitution of glutamine to arginine at position 192 (Q192R, rs662, c.632 A>G at GenBank accession number NM 000446). At position 192, the R allele was associated with rapid hydrolysis of paraoxon, while the Q allele was associated with slow hydrolysis [182]. The PON1 gene contains many polymorphisms both in the gene’s coding regions and promoter regions, some of which (e.g., PON1 192Q/R and 55L/M) can alter the activity of PON1’s enzymes and peptide concentration [183]. In addition, PON protein possesses PON1 and arylesterase (ARE) activity and is involved in preventing LDL oxidation and endothelial dysfunction, both of which have been linked to the pathogenesis of migraine [183]. Garcia-Martin et al. investigated PON1 polymorphisms (PON1 192Q/R and 55L/M) and their association with migraine risk in 197 Spanish Caucasian migraine patients [182]. They observed that the risk of migraine in those patients is not associated with PON1 polymorphisms, however, the genotype PON1 192Q/Q and allelic variant PON1 192Q were significantly more common in patients who had a migraine earlier in life [182]. In a subsequent investigation, biochemical assays were used to analyse PON1 enzyme activity levels in a Turkish population of 104 migraine patients and 86 healthy participants to determine the risk of acquiring migraine [183]. The PON1 serum activity has shown a significant drop in migraine patients. In this example, the authors genotyped PON1 55L/M and 192Q/R polymorphisms but found no significant differences in allele frequencies between patients and controls [183]. Similarly, an Italian study [184] demonstrated no association for PON1 55L/M and 192Q/R polymorphisms in 96 patients with chronic migraines.
It has been suggested that oxidative stress is responsible for impaired insulin action [218]. In the PON1 gene locus, Met-Leu 54 polymorphism is associated with insulin resistance in healthy persons and is strongly LD with the PON1 192 polymorphism [219]. Barbieri et al. [219] concluded that the genotype L/L PON’s presence is associated with a higher degree of insulin resistance (IR). Insulin resistance is well documented to play a key role in the pathogenesis of T2D [197]. In various investigations, decreased PON1 levels were identified in DM [220,221]. In one study, together with 110 healthy volunteers, a total of 86 T1D and 246 T2D patients were investigated by Flekac et al. [185]. They found that having the PON1-55 MM and PON1-192 Q/Q genotypes in diabetic patients instead of L/L and R/R genotypes, respectively, were related to poorer diabetes control. In contrast, better control of diabetes was identified in patients with L/L and R/R genotypes [185]. Several other investigations have found similar results [186,187]. For diabetic patients, Flekac et al. reported that paraoxonase levels are low in individuals with comorbidities like nephropathy, neuropathy, and retinopathy [185]. A further study conducted by Van den Berg et al. analysed 566 members of the Cohort study of Diabetes and Atherosclerosis Maastricht (CoDAM) and discovered that the R/R-phenotype was significantly more common in newly diagnosed T2D patients than in subjects with normal glucose tolerance [188].
3.7. Genome-Wide Association Studies
GWAS is an agnostic strategy to examine genetic variants (most often SNPs) spread across the genome for association to a particular disease or trait [222]. GWAS have revealed distinct genomic risk loci containing genetic variants associated with migraine [223,224,225] and glucose-related traits [226,227]; and the list of loci associated with each specific disorder grows with each subsequent study, mainly due to the increase in power of GWAS when performed in larger GWAS samples. So far, at least 170 genetic variants (123 genomic loci) have been associated with migraine (36), 403 genetic variants (243 genomic loci) to T2D [226], 41 genetic variants to fasting glucose [227], and 17 genetic variants to fasting insulin [227].
GWAS have made substantial progress in identifying genetic risk factors and understanding the mechanisms underlying T2D. Several genetic loci highly influence the risk of T2D. Large-scale GWAS have been highly effective in identifying of over 400 T2D-associated genetic variants, explaining the heritability of the disease by up to 20% [226,228,229], which offer mechanistic insights into T2D pathophysiology. Initially, most T2D-associated loci in populations of European ancestry were revealed back in 2007 [230,231]. Following efforts to identify additional T2D loci in the populations of Europe’s ancestry, large-scale meta-analyses of single studies [232,233,234] were carried out. For example, the DIAGRAM-DIAMANTE (Diabetes Genetics Replication and Meta-Analysis Consortium-Diabetes, Meta-Analysis Trans-Ethnic) consortium has meta-analysed 32 T2D GWAS of European descent participants (74,124 T2D cases and 824,006 controls) and discovered 243 T2D risk-associated genomic loci containing a total of 403 distinct (LD-independent) genetic risk variants [226]. The sample size was more than three times larger than in any previous T2D GWAS. Large-scale investigations increased our understanding of the genetic basis of T2D. With the emergence of the T2D genetic association dataset in a non-European ancestry group, trans-ancestry meta-analysis demonstrated a higher common susceptibility among worldwide populations. Most of the T2D loci are associated mainly with insulin production and the β-cell function with a significantly smaller number of genetic variants which seemingly affect insulin resistance. A large-scale meta-analysis of GWAS has been carried out using several cohorts with insulin sensitivity, processing, and secretion measurements to detect novel genetic variants related to insulin resistance. This technique has confirmed that several loci have been associated with certain glucose-related traits while also identifying novel loci. The Meta-Analyses of Glucose and Insulin-related Traits Consortium (MAGIC) conducted meta-analyses on GWAS from nondiabetic cohorts, including 151,188 individuals with fasting glucose (FG) measurements and 105,056 individuals with fasting insulin (FI) measurements, where they reported 41 genetic variants significantly associated with fasting glucose and 17 genetic variants significantly associated with fasting insulin [227].
Several GWAS studies on migraine have been conducted [223,224,225,235,236]. Between 2013 and 2016, the number of migraine risk loci increased from 13 [224] to 44 [223] as the number of samples and worldwide collaboration expanded. The 2016 meta-analysis of 22 GWAS studies included 59,674 cases and 316,078 controls, and identified 38 genome loci containing 44 independent genetic variants (SNPs) significantly associated with the risk of migraine [223]. Most of these common SNPs discovered were either intronic or intergenic, which is consistent with the assumption that most GWAS risk variants have regulatory impacts on gene expression rather than protein structure disruption. Analyses of the genes at the migraine risk loci indicated that the genes were enriched in vascular tissues and suggested a possible vascular mechanism of migraine [223]. Nitric oxide signalling and oxidative stress with the contribution of loci near REST, GJA1, YAP1, PRDM16, LRP1, and MRVI1 also seem to be other significant pathways [223]. In the latest IHGC GWAS [225], 102,084 migraine cases and 771,257 controls were analysed to identify 170 index variants which map into 123 specific genomic risk loci, 86 of which have not been published previously. This latest GWAS performed multiple and more extensive tissue enrichment analyses and found genetic evidence for the function of both vascular and neuronal tissue types in migraine that refined earlier studies on smaller GWAS and tissue datasets. Identifying risk loci that encode migraine-specific targets were particularly fascinating findings in their GWAS. For example, a new GWAS locus on chromosome 11 contains the CALCA and CALCB genes which encode the alpha and beta calcitonin gene-related peptide (CGRP) isoforms, respectively [225].
CGRP is an extremely powerful vasodilator with a possible involvement in the pathophysiology of migraine headache [225]. Several biological migraine treatments against CGRP or its receptor were recently developed. CGRP-based monoclonal antibodies have notably been used to prevent migraines, and they have been seen as a significant achievement in migraine-specific therapy [225]. Interestingly, CGRP and related peptide amylin are located in the pancreas, where their role is to influence insulin secretion from the β-cells [237]. This process is significant as insulin regulates blood sugar levels by helping other body cells absorb or use glucose for energy. This procedure is disrupted in T2D when cells become insulin resistant, resulting in reduced absorption of insulin and higher blood sugar levels. The relationship between CGRP and glucose homeostasis is complicated. Research studies performed in rats with obesity and T2D revealed that the infusion of pharmaceutical doses of CGRP caused insulin resistance and lowered peripheral glucose clearance [101]. These findings all emphasise potential links between CGRP, the pathophysiology of migraines and glucose metabolism [238]. However, further research is needed to explain the effects of peptides on migraine and glucose-related traits.
In a recent GWAS studies of 102,084 migraineurs [225] and 74,124 T2D patients [226], the SNP rs1472662 [nearest coding gene MACF1 (microtubule actin crosslinking factor 1)] and rs42854 (nearest coding gene ANKDD1B (ankyrin repeat and death domain containing 1B)] were found to be significantly associated (p < 5 × 10−8) with migraine and T2D and four SNPs were associated with migraine and T2D at genome-wide suggestive level. At the gene level, two genome-wide significant genes [MACF1 and THADA (thyroid adenoma associated)] were associated with migraine and T2D. In addition, from the same migraine GWAS study, eight migraine risk loci (rs12598836, rs7618883, rs1472662, rs10894756, rs6693567, rs7916911, rs10866704, and rs843215) were also associated with fasting glucose [227], and six migraine loci (rs11165300, rs6668908, rs28455731, rs13235543, rs4739105, and rs4814864) were associated with fasting insulin [227] at a nominal p-value level (p < 0.05) (Table 2). The genetic risk loci for migraine and glucose-related traits implicated by GWAS are both new and recent and have not previously been examined via CGAS. However, our inquiry of the publicly available glucose-related traits GWAS summary data of European descent suggests that some of the migraine risk loci identified in the 2022 IHGC migraine GWAS [225] are also associated with FG [227], FI [227], and T2D [226] (Table 2). Table 2 summaries the genome-wide significant loci of migraine associated with glucose-related traits.
Table 2.
Genome-wide significant migraine risk loci and their associations with FG, FI, and T2D.
| 2022 IHGC Migraine | 2018 DIAGRAM T2D | 2021 MAGIC FG | 2021 MAGIC FI | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Genes | SNP | CHR | BP | EA | NEA | OR | p-Value | OR | p-Value | OR | p-Value | OR | p-Value |
| PRDM16 | rs10218452 | 1 | 3,075,597 | G | A | 1.12 | 7.26 × 10−71 | 0.99 | 0.27 | 1.00 | 0.450 | 1.00 | 0.985 |
| CAMTA1 | rs10128028 | 1 | 7,055,843 | T | C | 1.03 | 7.66 × 10−9 | 0.99 | 0.047 | 1.00 | 0.118 | 1.00 | 0.625 |
| TMEM51 | rs12057629 | 1 | 15,538,493 | C | T | 1.04 | 9.38 × 10−14 | 0.99 | 0.4 | 1.00 | 0.666 | 1.00 | 0.999 |
| INPP5B | rs28739509 | 1 | 38,366,907 | C | T | 1.04 | 2.64 × 10−10 | 1.00 | 0.6 | 1.00 | 0.381 | 1.00 | 0.446 |
| C1orf87 | rs11578492 | 1 | 60,529,980 | C | A | 1.03 | 6.25 × 10−9 | - | - | 1.00 | 0.920 | 1.00 | 0.814 |
| near LEPR | rs7511672 | 1 | 66,178,918 | G | A | 1.03 | 1.43 × 10−9 | 0.99 | 0.17 | 1.00 | 0.681 | 1.00 | 0.388 |
| near RP4-598G3.1 | rs56019088 | 1 | 73,891,226 | I | D | 1.05 | 7.32 × 10−13 | - | - | 1.00 | 0.765 | 1.00 | 0.708 |
| TGFBR3 | rs11165300 | 1 | 92,177,663 | G | T | 1.03 | 4.72 × 10−8 | 1.00 | 0.84 | 1.00 | 0.344 | 0.99 | 0.035 |
| near TSPAN2 | rs2078371 | 1 | 115,677,183 | C | T | 1.11 | 5.87 × 10−42 | 0.97 | 0.0025 | 1.01 | 0.130 | 0.99 | 0.230 |
| MEF2D | rs2274319 | 1 | 156,450,873 | T | C | 1.08 | 2.74 × 10−41 | 1.01 | 0.42 | 1.00 | 0.562 | 0.99 | 0.052 |
| RABGAP1L | rs11487328 | 1 | 174,601,659 | G | C | 1.05 | 1.70 × 10−8 | - | - | 1.00 | 0.633 | 1.00 | 0.689 |
| PLA2G4A | rs6668908 | 1 | 186,913,055 | G | T | 1.03 | 2.22 × 10−8 | 1.01 | 0.22 | 1.00 | 0.629 | 1.01 | 0.045 |
| near MAPKAPK2 | rs56140113 | 1 | 206,843,108 | C | T | 1.04 | 7.76 × 10−9 | 1.00 | 0.95 | 0.99 | 0.195 | 1.00 | 0.638 |
| KIF26B | rs72764846 | 1 | 245,847,455 | G | A | 1.04 | 5.41 × 10−9 | 1.01 | 0.14 | - | - | - | - |
| MACF1 | rs1472662 | 1 | 39,590,409 | T | G | 1.04 | 1.75 × 10−8 | 1.08 | 1.60 × 10−22 | 1.01 | 0.011 | 1.01 | 0.075 |
| near ADAMTSL4 | rs6693567 | 1 | 150,510,660 | C | T | 1.04 | 1.25 × 10−13 | 0.98 | 0.011 | 1.01 | 0.032 | 1.00 | 0.510 |
| THADA | rs12712881 | 2 | 43,649,780 | A | C | 1.03 | 3.50 × 10−10 | 1.03 | 1.50 × 10−7 | 1.01 | 0.131 | 1.00 | 0.865 |
| ANKRD36C | rs4907224 | 2 | 96,576,609 | A | T | 1.04 | 1.63 × 10−9 | 1.00 | 0.86 | 1.00 | 0.877 | 1.00 | 0.410 |
| ZEB2 | rs7564469 | 2 | 145,258,445 | C | T | 1.04 | 5.06 × 10−9 | 1.03 | 0.00064 | 1.00 | 0.360 | 1.00 | 0.247 |
| near AC064865.1 | rs895219 | 2 | 146,037,564 | C | T | 1.04 | 3.74 × 10−11 | 0.99 | 0.065 | 1.00 | 0.260 | 0.99 | 0.097 |
| MYO3B | rs4668251 | 2 | 171,234,235 | G | C | 1.03 | 7.58 × 10−9 | 1.01 | 0.26 | 1.00 | 0.901 | 1.00 | 0.505 |
| near HOXD10 | rs72923449 | 2 | 176,978,383 | C | A | 1.08 | 4.66 × 10−8 | 1.02 | 0.23 | - | - | - | - |
| CARF | rs138556413 | 2 | 203,832,867 | C | T | 1.14 | 4.15 × 10−16 | 1.03 | 0.12 | - | - | - | - |
| near TRPM8 | rs10166942 | 2 | 234,825,093 | T | C | 1.10 | 9.35 × 10−51 | 0.99 | 0.26 | 1.00 | 0.273 | 1.00 | 0.754 |
| near RNU6-546P | rs843215 | 2 | 156,416,638 | G | A | 1.03 | 2.61 × 10−8 | 1.01 | 0.058 | 1.01 | 0.042 | 1.00 | 0.719 |
| ATRIP | rs7618883 | 3 | 48,498,456 | T | A | 1.03 | 4.16 × 10−8 | 0.99 | 0.13 | 0.99 | 0.010 | 0.99 | 0.074 |
| near TGFBR2 | rs7371912 | 3 | 30,472,786 | A | G | 1.04 | 1.06 × 10−14 | - | - | 1.00 | 0.800 | 1.00 | 0.746 |
| near HNRNPA3P8 | rs950570 | 3 | 80,302,512 | T | C | 1.06 | 1.30 × 10−8 | 0.98 | 0.14 | 1.00 | 0.704 | 1.00 | 0.984 |
| near CADM2 | rs73138150 | 3 | 86,149,109 | T | A | 1.03 | 1.95 × 10−8 | 0.99 | 0.041 | 1.00 | 0.349 | 1.00 | 0.609 |
| near C3orf38 | rs6795209 | 3 | 88,210,464 | A | G | 1.04 | 1.23 × 10−8 | - | - | 1.00 | 0.458 | 0.99 | 0.123 |
| ITGB5 | rs1499963 | 3 | 124,607,055 | C | T | 1.03 | 7.48 × 10−9 | 0.99 | 0.059 | 1.00 | 0.293 | 1.00 | 0.770 |
| near GPR149 | rs13078967 | 3 | 154,289,946 | A | C | 1.16 | 2.16 × 10−16 | 1.00 | 0.95 | - | - | - | - |
| near SEC63P2 | rs73805934 | 4 | 35,469,918 | G | C | 1.04 | 1.11 × 10−9 | 1.00 | 0.93 | 1.00 | 0.708 | 1.00 | 0.975 |
| near SPINK2 | rs7684253 | 4 | 57,727,311 | T | C | 1.04 | 4.21 × 10−14 | 1.00 | 0.79 | 1.00 | 0.404 | 1.01 | 0.318 |
| ANKDD1B | rs42854 | 5 | 74,963,277 | G | C | 1.04 | 9.40 × 10−13 | 0.95 | 3.80 × 10−13 | 1.01 | 0.221 | 0.99 | 0.057 |
| near SSBP2 | rs12653216 | 5 | 81,129,663 | T | C | 1.04 | 8.08 × 10−9 | 0.99 | 0.12 | 1.00 | 0.760 | 1.00 | 0.672 |
| near ZNF474 | rs11957829 | 5 | 121,515,195 | G | A | 1.04 | 1.58 × 10−9 | 0.99 | 0.41 | 1.00 | 0.839 | 1.00 | 0.885 |
| SNX24 | rs246326 | 5 | 122,306,398 | T | C | 1.05 | 6.80 × 10−10 | 1.01 | 0.15 | 1.00 | 0.807 | 1.00 | 0.617 |
| near POU4F3 | rs10038882 | 5 | 145,752,008 | T | C | 1.04 | 1.33 × 10−12 | 0.99 | 0.084 | 1.00 | 0.618 | 1.01 | 0.284 |
| TIGD6|HMGXB3 | rs4705403 | 5 | 149,380,493 | A | G | 1.05 | 1.18 × 10−8 | 1.00 | 0.68 | 1.00 | 0.354 | 1.00 | 0.877 |
| near NKX2-5 | rs6556059 | 5 | 172,645,766 | T | C | 1.03 | 8.16 × 10−10 | 1.00 | 0.48 | 0.99 | 0.158 | 1.01 | 0.286 |
| NSD1 | rs10866704 | 5 | 176,676,461 | A | T | 1.04 | 2.10 × 10−8 | - | - | 1.01 | 0.039 | 1.00 | 0.800 |
| PHACTR1 | rs9349379 | 6 | 12,903,957 | A | G | 1.08 | 1.41 × 10−47 | 1.00 | 0.83 | 1.00 | 0.415 | 1.00 | 0.132 |
| near PRL | rs9295536 | 6 | 22,131,929 | C | A | 1.04 | 7.75 × 10−12 | 1.01 | 0.34 | 1.00 | 0.812 | 1.00 | 0.126 |
| near IER3 | rs9468830 | 6 | 30,749,712 | T | G | 1.04 | 2.38 × 10−8 | 1.00 | 0.97 | 1.00 | 0.909 | 1.00 | 0.227 |
| EHMT2 | rs74434374 | 6 | 31,850,308 | C | A | 1.08 | 4.52 × 10−9 | 0.99 | 0.55 | - | - | - | - |
| KCNK5 | rs10456100 | 6 | 39,183,470 | T | C | 1.05 | 9.16 × 10−19 | 0.97 | 8.90 × 10−5 | 1.00 | 0.970 | 1.00 | 0.427 |
| near KRT19P1 | rs34273564 | 6 | 72,321,017 | T | C | 1.03 | 1.00 × 10−10 | 1.00 | 0.48 | 0.99 | 0.178 | 1.00 | 0.658 |
| FHL5 | rs11153082 | 6 | 97,059,666 | G | A | 1.09 | 7.26 × 10−54 | 1.00 | 0.68 | 1.00 | 0.689 | 1.00 | 0.974 |
| REV3L | rs6568677 | 6 | 111,713,302 | A | G | 1.04 | 2.09 × 10−8 | 1.02 | 0.0047 | 1.00 | 0.559 | 1.00 | 0.783 |
| near GJA1 | rs28455731 | 6 | 121,846,038 | T | G | 1.07 | 8.82 × 10−23 | 1.00 | 0.75 | 1.00 | 0.614 | 0.98 | 0.027 |
| near PCMT1 | rs9383843 | 6 | 150,133,954 | C | A | 1.03 | 1.35 × 10−9 | 1.01 | 0.047 | 1.00 | 0.355 | 1.00 | 0.983 |
| SUGCT | rs10234636 | 7 | 40,427,617 | T | C | 1.09 | 4.43 × 10−28 | 0.99 | 0.33 | 1.00 | 0.743 | 1.00 | 0.413 |
| MLXIPL | rs13235543 | 7 | 73,013,901 | C | T | 1.06 | 3.06 × 10−13 | 0.97 | 0.00038 | 1.00 | 0.419 | 0.98 | 0.003 |
| TSPAN12 | rs56067931 | 7 | 120,481,569 | C | T | 1.04 | 4.83 × 10−8 | 1.00 | 0.67 | 1.00 | 0.479 | 1.00 | 0.858 |
| PTK2B | rs11782789 | 8 | 27,266,287 | A | T | 1.04 | 3.03 × 10−9 | 0.99 | 0.18 | 1.00 | 0.139 | 1.00 | 0.510 |
| near RP11-573J24.1 | rs4739105 | 8 | 64,496,159 | T | C | 1.04 | 2.85 × 10−8 | 1.01 | 0.11 | 1.00 | 0.542 | 0.99 | 0.023 |
| NFIB | rs580845 | 9 | 14,103,618 | A | C | 1.03 | 4.30 × 10−8 | 0.99 | 0.31 | 1.00 | 0.778 | 1.00 | 0.226 |
| near RP11-373A6.1 | rs10156578 | 9 | 29,372,501 | C | G | 1.04 | 3.34 × 10−12 | 1.01 | 0.026 | 1.00 | 0.430 | 1.00 | 0.822 |
| TJP2 | rs7034179 | 9 | 71,746,838 | T | C | 1.04 | 1.60 × 10−16 | 1.00 | 0.77 | 0.99 | 0.496 | 1.01 | 0.684 |
| ZNF462 | rs17723637 | 9 | 109,687,403 | G | A | 1.04 | 8.63 × 10−9 | 1.00 | 0.63 | 1.00 | 0.427 | 1.00 | 0.226 |
| ASTN2 | rs3891689 | 9 | 119,258,583 | C | T | 1.06 | 2.28 × 10−21 | 1.00 | 0.88 | 1.01 | 0.087 | 1.00 | 0.887 |
| near EHMT1 | rs4278223 | 9 | 140,743,200 | T | A | 1.05 | 6.24 × 10−10 | 1.02 | 0.036 | - | - | - | - |
| near R-5SP299 | rs7916911 | 10 | 8,722,944 | T | G | 1.04 | 3.18 × 10−12 | 1.00 | 0.81 | 0.99 | 0.035 | 1.00 | 0.472 |
| near MLLT10 | rs10828247 | 10 | 21,822,856 | G | A | 1.03 | 7.51 × 10−9 | 1.00 | 0.87 | 1.00 | 0.834 | 1.00 | 0.561 |
| PLCE1 | rs2274224 | 10 | 96039597 | G | C | 1.06 | 3.28 × 10−26 | 1.00 | 0.76 | 1.00 | 0.648 | 1.00 | 0.113 |
| HPSE2 | rs12260159 | 10 | 100,702,737 | G | A | 1.09 | 7.33 × 10−16 | - | - | 1.00 | 0.459 | 1.00 | 0.846 |
| CNNM2 | rs12260436 | 10 | 104,741,114 | C | A | 1.04 | 7.29 × 10−10 | 0.99 | 0.12 | 1.00 | 0.786 | 1.00 | 0.581 |
| RBM20 | rs869432 | 10 | 112,502,662 | A | C | 1.03 | 3.54 × 10−8 | 1.02 | 0.0059 | - | - | - | - |
| HTRA1 | rs2672592 | 10 | 124,230,750 | T | G | 1.04 | 1.22 × 10−12 | 1.00 | 0.9 | 1.00 | 0.567 | 0.99 | 0.272 |
| near GPR26 | rs11248546 | 10 | 125,242,283 | C | T | 1.04 | 1.59 × 10−12 | 1.01 | 0.19 | 1.00 | 0.338 | 1.00 | 0.435 |
| INPP5A | rs200314499 | 10 | 134,479,675 | - | - | - | - | - | - | - | - | - | - |
| near SPATA19 | rs10894756 | 11 | 133,745,852 | G | A | 1.03 | 2.83 × 10−8 | 1.00 | 0.51 | 1.01 | 0.018 | 1.00 | 0.890 |
| MRGPRE | rs12295710 | 11 | 3,249,984 | T | C | 1.05 | 2.86 × 10−16 | 1.00 | 0.89 | - | - | - | - |
| MRVI1 | rs4910165 | 11 | 10,674,044 | G | C | 1.06 | 1.09 × 10−24 | 1.02 | 0.00094 | 1.00 | 0.363 | 1.00 | 0.370 |
| near INSC | rs1003194 | 11 | 15,126,085 | A | G | 1.03 | 2.43 × 10−10 | 0.99 | 0.13 | 1.00 | 0.792 | 1.00 | 0.393 |
| MPPED2 | rs11031122 | 11 | 30,547,438 | C | T | 1.04 | 6.91 × 10−10 | 1.02 | 0.0031 | 1.00 | 0.122 | 1.00 | 0.669 |
| AMBRA1 | rs7932866 | 11 | 46,548,094 | A | G | 1.04 | 2.38 × 10−9 | 1.00 | 0.58 | 0.99 | 0.151 | 1.00 | 0.435 |
| near RAB3IL1 | rs12787928 | 11 | 61,697,078 | A | T | 1.03 | 6.85 × 10−9 | 0.99 | 0.11 | 1.00 | 0.615 | 0.99 | 0.084 |
| RBM14-RBM4|RBM4 | rs566673 | 11 | 66,401,373 | G | T | 1.03 | 9.07 × 10−9 | 1.01 | 0.1 | 1.00 | 0.955 | 1.00 | 0.713 |
| YAP1 | rs12226331 | 11 | 102,070,976 | T | A | 1.04 | 1.92 × 10−13 | 1.01 | 0.37 | 1.00 | 0.090 | 1.00 | 0.472 |
| near FGF6 | rs2160875 | 12 | 4,527,322 | C | T | 1.07 | 2.72 × 10−36 | 1.00 | 0.91 | 1.00 | 0.316 | 1.00 | 0.413 |
| PDZRN4 | rs1458170 | 12 | 41,901,277 | C | T | 1.04 | 5.75 × 10−9 | 0.98 | 0.016 | 1.00 | 0.187 | 1.00 | 0.929 |
| LRP1 | rs11172113 | 12 | 57,527,283 | T | C | 1.11 | 1.38 × 10−90 | 0.99 | 0.15 | 1.00 | 0.219 | 1.00 | 0.469 |
| ATP2B1 | rs4842676 | 12 | 90,091,782 | C | G | 1.04 | 2.26 × 10−9 | 0.99 | 0.34 | 1.00 | 0.391 | 1.00 | 0.380 |
| near RP11-690J15.1 | rs10777902 | 12 | 98,498,223 | A | C | 1.03 | 1.25 × 10−10 | 0.99 | 0.12 | 1.00 | 0.914 | 1.00 | 0.483 |
| NCOR2 | rs1271309 | 12 | 124,820,705 | G | A | 1.04 | 3.74 × 10−8 | 1.03 | 0.0035 | 0.99 | 0.246 | 1.00 | 0.851 |
| LRCH1 | rs7335684 | 13 | 47,193,696 | G | A | 1.03 | 1.05 × 10−8 | 0.99 | 0.035 | 1.00 | 0.845 | 1.00 | 0.810 |
| RNF219-AS1 | rs7996252 | 13 | 78,876,537 | T | C | 1.03 | 4.11 × 10−8 | 1.01 | 0.11 | 1.00 | 0.984 | 1.00 | 0.834 |
| near COL4A1 | rs2000660 | 13 | 110,788,441 | A | G | 1.05 | 4.95 × 10−8 | 1.00 | 0.77 | - | - | - | - |
| near RP11-384J4.2 | rs1245463 | 14 | 27,661,650 | A | G | 1.04 | 5.72 × 10−14 | 1.02 | 0.02 | 1.00 | 0.261 | 1.00 | 0.321 |
| near LRFN5 | rs1542668 | 14 | 42,548,912 | G | A | 1.03 | 2.53 × 10−8 | 1.01 | 0.46 | 1.00 | 0.450 | 1.01 | 0.095 |
| near ARID4A | rs28756401 | 14 | 58,761,912 | G | A | 1.03 | 6.40 × 10−9 | 0.97 | 9.70 × 10−7 | 1.00 | 0.699 | 1.00 | 0.551 |
| DLST | rs55707505 | 14 | 75,362,552 | T | C | 1.03 | 2.48 × 10−8 | 1.00 | 0.88 | 1.00 | 0.558 | 1.00 | 0.321 |
| IFT43 | rs75002882 | 14 | 76,496,477 | G | T | 1.17 | 9.22 × 10−9 | 0.97 | 0.25 | - | - | - | - |
| near ITPK1 | rs11624776 | 14 | 93,595,591 | A | C | 1.05 | 9.75 × 10−19 | 1.00 | 0.73 | 1.00 | 0.898 | 1.00 | 0.674 |
| SERPI-1 | rs28929474 | 14 | 94,844,947 | T | C | 1.12 | 2.54 × 10−9 | 0.90 | 5.90 × 10−6 | - | - | - | - |
| ABHD17C | rs12708529 | 15 | 81,022,364 | A | G | 1.04 | 8.11 × 10−10 | 1.02 | 0.022 | 0.99 | 0.185 | 1.01 | 0.162 |
| HMOX2 | rs12598836 | 16 | 4,534,482 | G | A | 1.04 | 2.21 × 10−10 | - | - | 1.01 | 0.008 | 1.00 | 0.787 |
| CFDP1 | rs8046696 | 16 | 75,442,143 | T | G | 1.04 | 4.76 × 10−14 | 1.00 | 0.62 | 1.00 | 0.398 | 1.00 | 0.919 |
| near ZCCHC14 | rs8052831 | 16 | 87,578,039 | G | A | 1.04 | 8.25 × 10−15 | 1.01 | 0.07 | 1.00 | 0.792 | 1.01 | 0.123 |
| SMG6 | rs9894634 | 17 | 1,967,501 | C | T | 1.03 | 9.64 × 10−11 | 1.02 | 0.0041 | 1.00 | 0.921 | 1.00 | 0.454 |
| ZBTB4 | rs34914463 | 17 | 7,366,619 | T | C | 1.05 | 2.41 × 10−9 | 0.99 | 0.14 | - | - | - | - |
| HOXB3 | rs11652860 | 17 | 46,632,679 | G | C | 1.03 | 1.07 × 10−8 | 1.01 | 0.15 | - | - | - | - |
| RP11-81K2.1 | rs2119930 | 17 | 47,514,039 | G | T | 1.04 | 6.69 × 10−15 | 1.00 | 0.48 | 1.00 | 0.910 | 1.00 | 0.782 |
| MRC2 | rs12452590 | 17 | 60,720,058 | G | T | 1.04 | 2.03 × 10−10 | 0.97 | 2.50 × 10−6 | - | - | - | - |
| TBC1D16 | rs1285294 | 17 | 77,925,681 | C | T | 1.03 | 4.32 × 10−8 | 1.02 | 0.0064 | 1.01 | 0.075 | 1.00 | 0.289 |
| RNF213 | rs8077768 | 17 | 78,256,432 | C | T | 1.04 | 9.32 × 10−13 | 1.00 | 0.52 | - | - | - | - |
| near RBBP8 | rs7506921 | 18 | 20,201,527 | A | T | 1.04 | 1.17 × 10−11 | - | - | 1.00 | 0.546 | 1.00 | 0.748 |
| near SKOR2 | rs1019990 | 18 | 44,866,736 | C | T | 1.04 | 1.00 × 10−11 | 1.00 | 0.66 | 1.00 | 0.181 | 1.00 | 0.716 |
| near FECH | rs8087942 | 18 | 55,192,245 | A | G | 1.04 | 9.71 × 10−13 | 1.00 | 0.8 | 1.00 | 0.906 | 1.00 | 0.946 |
| CAC-1A | rs10405121 | 19 | 13,339,128 | G | A | 1.03 | 4.74 × 10−10 | 1.00 | 0.58 | 1.00 | 0.865 | 1.00 | 0.758 |
| SUGP1 | rs74182632 | 19 | 19,406,126 | A | G | 1.07 | 1.43 × 10−8 | 1.01 | 0.36 | 1.01 | 0.410 | 0.98 | 0.054 |
| B9D2/TMEM91 | rs1982072 | 19 | 41,864,509 | A | T | 1.04 | 4.22 × 10−11 | 1.01 | 0.22 | 1.00 | 0.773 | 1.00 | 0.279 |
| near JAG1 | rs111404218 | 20 | 10,684,159 | - | - | - | - | - | - | - | - | - | - |
| SLC24A3 | rs4814864 | 20 | 19,469,817 | C | G | 1.07 | 1.44 × 10−28 | 0.99 | 0.47 | 1.00 | 0.638 | 1.01 | 0.031 |
| C20orf112 | rs6057599 | 20 | 31,168,439 | T | C | 1.04 | 8.73 × 10−14 | 1.01 | 0.4 | 1.01 | 0.178 | 1.01 | 0.149 |
| ZMYND8 | rs910187 | 20 | 45,841,052 | G | A | 1.04 | 1.14 × 10−10 | 0.98 | 0.001 | 1.00 | 0.211 | 1.00 | 0.574 |
| near MRPS6 | rs28451064 | 21 | 35,593,827 | G | A | 1.07 | 3.52 × 10−15 | 1.02 | 0.031 | - | - | - | - |
| RUNX1 | rs764508 | 21 | 36,935,896 | C | T | 1.03 | 3.28 × 10−9 | 0.99 | 0.16 | 1.00 | 0.632 | 1.00 | 0.139 |
| near AC006547.14 | rs625686 | 22 | 20,142,932 | C | T | 1.03 | 8.26 × 10−9 | 0.99 | 0.042 | 1.00 | 0.430 | 1.00 | 0.720 |
| near FAM47A | rs1507220 | X | 34,102,712 | A | C | 1.03 | 2.67 × 10−8 | - | - | 0.99 | 0.665 | 1.02 | 0.262 |
| near MED14 | rs4403550 | X | 40,746,484 | - | - | - | - | - | - | - | - | - | - |
Odds ratio (OR) and p-value associated with effect allele (EA); Non-effect allele (NEA); Chromosome (CHR), Base pair position (BP); Single nucleotide polymorphism (SNP).
4. Conclusions
Our review of previous studies highlighted several genes and biochemical pathways that could be shared between migraine and glucose-related traits. Candidate gene association studies of strong biological candidate genes have reported suggestive but inconsistent evidence for association with migraine and glucose-related traits. Impaired glucose metabolism, reduced insulin sensitivity, and fluctuation of blood glucose levels have all been associated with the comorbidity of migraine and glucose-related traits. Twin and family studies have demonstrated a strong genetic component for migraine and glucose-related traits. Two genome-wide significant loci associated with migraine (rs1472662 near MACF1 and rs42854 near ANKDD1B) have also been associated with T2D at the genome-wide significant level, and two genes (MACF1 and THADA) have been associated with both migraine and T2D at the gene-based genome-wide significant level. It is worth mentioning that GWAS has found MACF1 to be associated with vascular diseases like hypertension and peripheral artery disease [239], further supporting the idea that headaches may somehow be linked to the vascular system. Additional migraine GWAS risk loci have been associated with fasting glucose and fasting insulin at (p < 0.05). These observations warrant further examination.
Among the investigated candidate gene polymorphisms, the MTHFR C677T, TNF −308(G/A), NOS3 Glu298Asp, and NOS3 [VNTR (27 bp) in intron 4] provided the most consistent evidence for association with both migraine and glucose-related traits, whereas genetic variants in the INSR, ESR1, and PON1 candidate genes were less consistent. Both GWAS and candidate gene approaches have identified genes involved in the aetiology of migraine and glucose-related traits. For example, a recent GWAS study identified SNP rs17175860 within INSR significantly (p = 3 × 10−14) associated with T2D (www.ebi.ac.uk/gwas/, accessed on 13 March 2022) [229]. Additionally, SNP rs3845843 15,508 bp upstream of the TNF alpha-induced protein 6 gene (TNFAIP6) was significantly (p = 3 × 10−11) associated with an increased risk of T2D (www.ebi.ac.uk/gwas/, accessed on 13 March 2022) [229]. Notably, the TNF gene is involved in obesity-related insulin resistance [240] and was also associated with T1D at genome-wide suggestive level (rs3093664, p = 3.0 × 10−7) (www.ebi.ac.uk/gwas/, accessed on 13 March 2022) [241]. Studies have suggested that the link between migraine and diabetes may be caused by insulin resistance, which plays a vital role in developing metabolic syndrome and is also a risk factor for migraine [26,107]. A GWAS study conducted in 715 patients with Han Chinese ethnicity in Taiwan discovered that one SNP (rs146094041) in the Oestrogen related receptor gamma gene (ESRRG) was genome-wide significantly associated (p = 3.40 × 10−9) with migraine onset before the age of 12 years (www.ebi.ac.uk/gwas/, accessed on 13 March 2022) [242]. Given the involvement of sex hormones, especially oestrogen, in migraine pathophysiology [107,243], the link between migraine and diabetes may be partially explained by sex hormones. However, it is important to note that the remaining candidate genes reviewed here were not found to be associated with migraine or glucose-related traits in GWAS at the genome-wide significant level or genome-wide suggestive level. A similar finding was reached by de Vries et al. [244], who reported no experiment-wide significant results for the identified candidate genes previously associated with migraine. The most plausible explanations for GWAS findings not supporting previously implicated candidate genes relates to the large multiple test burden in GWAS, and the often small sample sizes utilised in CGAS—which increases the likelihood of producing both false-positive and false-negative results. In addition, over 90% of the genetic variants discovered by GWAS are in the non-coding regions and hence cannot be easily linked to a probable candidate gene [245].
This review provides insight into potential pleiotropic genes and shared biological mechanisms that may contribute to migraine and glucose-related traits; however, comprehensive cross-disorder investigations, utilising large and powerful genetic datasets, are required to understand how genetic risk factors mediate the relationship between migraine and glucose-related traits. Moreover, identifying shared genetic factors, and characterising their relationship in migraine risk and glucose-related traits, will enhance our understanding of their underlying biological mechanisms and enable the development of new biomarkers, new therapeutic targets, and tailor treatment strategies (e.g., glucose-related) in migraine patients.
Acknowledgments
The first author would like to thank the Queensland University of Technology (QUT) and the Australian Government’s Research Training Program (RTP) for providing a scholarship.
Author Contributions
Conceptualisation: M.R.I. and D.R.N.; analysis and writing—original draft preparation: M.R.I.; writing—critical review and editing: D.R.N.; supervision: D.R.N. All authors have read and agreed to the published version of the manuscript.
Funding
The authors received no financial support for the research, authorship, and/or publication of this article.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
No new data were generated or analysed in this study. Data sharing was not applicable.
Conflicts of Interest
The authors declared no potential conflict of interest with respect to the research, authorship and/or publication of this article.
Footnotes
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Gerring Z.F., Powell J.E., Montgomery G.W., Nyholt D.R. Genome-wide analysis of blood gene expression in migraine implicates immune-inflammatory pathways. Cephalalgia. 2018;38:292–303. doi: 10.1177/0333102416686769. [DOI] [PubMed] [Google Scholar]
- 2.Vos T., Allen C., Arora M., Barber R.M., Bhutta Z.A., Brown A., Carter A., Casey D.C., Charlson F.J., Chen A.Z., et al. Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990–2015: A systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016;388:1545–1602. doi: 10.1016/S0140-6736(16)31678-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Feigin V.L., Abajobir A.A., Abate K.H., Abd-Allah F., Abdulle A.M., Abera S.F., Abyu G.Y., Ahmed M.B., Aichour A.N., Aichour I., et al. Global, regional, and national burden of neurological disorders during 1990–2015: A systematic analysis for the Global Burden of Disease Study 2015. Lancet Neurol. 2017;16:877–897. doi: 10.1016/S1474-4422(17)30299-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Vos T., Barber R.M., Bell B., Bertozzi-Villa A., Biryukov S., Bolliger I., Charlson F., Davis A., Degenhardt L., Dicker D., et al. Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990–2013: A systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2015;386:743–800. doi: 10.1016/S0140-6736(15)60692-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Vos T., Flaxman A.D., Naghavi M., Lozano R., Michaud C., Ezzati M., Shibuya K., Salomon J.A., Abdalla S., Aboyans V., et al. Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990–2010: A systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380:2163–2196. doi: 10.1016/S0140-6736(12)61729-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Dodick D.W. Migraine. Lancet. 2018;391:1315–1330. doi: 10.1016/S0140-6736(18)30478-1. [DOI] [PubMed] [Google Scholar]
- 7.Kowalska M., Prendecki M., Kozubski W., Lianeri M., Dorszewska J. Molecular factors in migraine. Oncotarget. 2016;7:50708–50718. doi: 10.18632/oncotarget.9367. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Bloudek L.M., Stokes M., Buse D.C., Wilcox T.K., Lipton R.B., Goadsby P.J., Varon S.F., Blumenfeld A.M., Katsarava Z., Pascual J., et al. Cost of healthcare for patients with migraine in five European countries: Results from the International Burden of Migraine Study (IBMS) J. Headache Pain. 2012;13:361–378. doi: 10.1007/s10194-012-0460-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Linde M., Gustavsson A., Stovner L.J., Steiner T.J., Barré J., Katsarava Z., Lainez J.M., Lampl C., Lantéri-Minet M., Rastenyte D., et al. The cost of headache disorders in Europe: The Eurolight project. Eur. J. Neurol. 2012;19:703–711. doi: 10.1111/j.1468-1331.2011.03612.x. [DOI] [PubMed] [Google Scholar]
- 10.Nyholt D.R., Borsook D., Griffiths L.R. Migrainomics—Identifying brain and genetic markers of migraine. Nat. Rev. Neurol. 2017;13:725–741. doi: 10.1038/nrneurol.2017.151. [DOI] [PubMed] [Google Scholar]
- 11.Launer L.J., Terwindt G.M., Ferrari M.D. The prevalence and characteristics of migraine in a population-based cohort: The GEM study. Neurology. 1999;53:537–542. doi: 10.1212/WNL.53.3.537. [DOI] [PubMed] [Google Scholar]
- 12.The International Classification of Headache Disorders, 3rd edition (beta version) Cephalalgia. 2013;33:629–808. doi: 10.1177/0333102413485658. [DOI] [PubMed] [Google Scholar]
- 13.Kelman L. The triggers or precipitants of the acute migraine attack. Cephalalgia. 2007;27:394–402. doi: 10.1111/j.1468-2982.2007.01303.x. [DOI] [PubMed] [Google Scholar]
- 14.Li L., Schulz U.G., Kuker W., Rothwell P.M. Age-specific association of migraine with cryptogenic TIA and stroke: Population-based study. Neurology. 2015;85:1444–1451. doi: 10.1212/WNL.0000000000002059. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Kurth T., Winter A.C., Eliassen A.H., Dushkes R., Mukamal K.J., Rimm E.B., Willett W.C., Manson J.E., Rexrode K.M. Migraine and risk of cardiovascular disease in women: Prospective cohort study. BMJ. 2016;353:i2610. doi: 10.1136/bmj.i2610. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Gray P.A., Burtness H.I. Hypoglycemic headache. Endocrinology. 1935;19:549–560. doi: 10.1210/endo-19-5-549. [DOI] [Google Scholar]
- 17.Gross E.C., Lisicki M., Fischer D., Sándor P.S., Schoenen J. The metabolic face of migraine—From pathophysiology to treatment. Nat. Rev. Neurol. 2019;15:627–643. doi: 10.1038/s41582-019-0255-4. [DOI] [PubMed] [Google Scholar]
- 18.Blau J.N., Cumings C.J. Method of precipitating and preventing some migraine attacks. Br. Med. J. 1966;2:1242–1243. doi: 10.1136/bmj.2.5524.1242. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Pearce J. Insulin induced hypoglycaemia in migraine. J. Neurol. Neurosurg. Psychiatry. 1971;34:154–156. doi: 10.1136/jnnp.34.2.154. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Jacome D.E. Hypoglycemia rebound migraine. Headache. 2001;41:895–898. doi: 10.1111/j.1526-4610.2001.01163.x. [DOI] [PubMed] [Google Scholar]
- 21.Goadsby P.J., Holland P.R., Martins-Oliveira M., Hoffmann J., Schankin C., Akerman S. Pathophysiology of Migraine: A Disorder of Sensory Processing. Physiol. Rev. 2017;97:553–622. doi: 10.1152/physrev.00034.2015. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Fava A., Pirritano D., Consoli D., Plastino M., Casalinuovo F., Cristofaro S., Colica C., Ermio C., De Bartolo M., Opipari C., et al. Chronic migraine in women is associated with insulin resistance: A cross-sectional study. Eur. J. Neurol. 2014;21:267–272. doi: 10.1111/ene.12289. [DOI] [PubMed] [Google Scholar]
- 23.Dexter J.D., Roberts J., Byer J.A. The five hour glucose tolerance test and effect of low sucrose diet in migraine. Headache. 1978;18:91–94. doi: 10.1111/j.1526-4610.1978.hed1802091.x. [DOI] [PubMed] [Google Scholar]
- 24.Cavestro C., Rosatello A., Micca G., Ravotto M., Marino M.P., Asteggiano G., Beghi E. Insulin metabolism is altered in migraineurs: A new pathogenic mechanism for migraine? Headache. 2007;47:1436–1442. doi: 10.1111/j.1526-4610.2007.00719.x. [DOI] [PubMed] [Google Scholar]
- 25.Casucci G., Villani V., Cologno D., D’Onofrio F. Migraine and metabolism. Neurol. Sci. 2012;33:81–85. doi: 10.1007/s10072-012-1047-4. [DOI] [PubMed] [Google Scholar]
- 26.Rainero I., Limone P., Ferrero M., Valfre W., Pelissetto C., Rubino E., Gentile S., Lo Giudice R., Pinessi L. Insulin sensitivity is impaired in patients with migraine. Cephalalgia. 2005;25:593–597. doi: 10.1111/j.1468-2982.2005.00928.x. [DOI] [PubMed] [Google Scholar]
- 27.Bigal M.E., Kurth T., Hu H., Santanello N., Lipton R.B. Migraine and cardiovascular disease: Possible mechanisms of interaction. Neurology. 2009;72:1864–1871. doi: 10.1212/WNL.0b013e3181a71220. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Buse D.C., Manack A., Serrano D., Turkel C., Lipton R.B. Sociodemographic and comorbidity profiles of chronic migraine and episodic migraine sufferers. J. Neurol. Neurosurg. Psychiatry. 2010;81:428–432. doi: 10.1136/jnnp.2009.192492. [DOI] [PubMed] [Google Scholar]
- 29.Burch R.C., Rist P.M., Winter A.C., Buring J.E., Pradhan A.D., Loder E.W., Kurth T. Migraine and risk of incident diabetes in women: A prospective study. Cephalalgia. 2012;32:991–997. doi: 10.1177/0333102412453954. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Hamed S.A., Hamed E.A., Ezz Eldin A.M., Mahmoud N.M. Vascular Risk Factors, Endothelial Function, and Carotid Thickness in Patients with Migraine: Relationship to Atherosclerosis. J. Stroke Cerebrovasc. Dis. 2010;19:92–103. doi: 10.1016/j.jstrokecerebrovasdis.2009.04.007. [DOI] [PubMed] [Google Scholar]
- 31.Scher A.I., Terwindt G.M., Picavet H.S.J., Verschuren W.M.M., Ferrari M.D., Launer L.J. Cardiovascular risk factors and migraine. Neurology. 2005;64:614. doi: 10.1212/01.WNL.0000151857.43225.49. [DOI] [PubMed] [Google Scholar]
- 32.Etminan M., Takkouche B., Isorna F.C., Samii A. Risk of ischaemic stroke in people with migraine: Systematic review and meta-analysis of observational studies. BMJ. 2005;330:63. doi: 10.1136/bmj.38302.504063.8F. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Merikangas K.R., Fenton B.T., Cheng S.H., Stolar M.J., Risch N. Association between migraine and stroke in a large-scale epidemiological study of the United States. Arch. Neurol. 1997;54:362–368. doi: 10.1001/archneur.1997.00550160012009. [DOI] [PubMed] [Google Scholar]
- 34.Sacco S., Pistoia F., Degan D., Carolei A. Conventional vascular risk factors: Their role in the association between migraine and cardiovascular diseases. Cephalalgia. 2015;35:146–164. doi: 10.1177/0333102414559551. [DOI] [PubMed] [Google Scholar]
- 35.Torelli P., Evangelista A., Bini A., Castellini P., Lambru G., Manzoni G.C. Fasting Headache: A Review of the Literature and New Hypotheses. Headache J. Head Face Pain. 2009;49:744–752. doi: 10.1111/j.1526-4610.2009.01390.x. [DOI] [PubMed] [Google Scholar]
- 36.Hufnagl K.N., Peroutka S.J. Glucose regulation in headache: Implications for dietary management. Expert Rev. Neurother. 2014;2:311–317. doi: 10.1586/14737175.2.3.311. [DOI] [PubMed] [Google Scholar]
- 37.Macdonald C. Migraine. Lancet. 1933;1:123–126. [Google Scholar]
- 38.Finocchi C., Sivori G. Food as trigger and aggravating factor of migraine. Neurol. Sci. 2012;33:77–80. doi: 10.1007/s10072-012-1046-5. [DOI] [PubMed] [Google Scholar]
- 39.Spierings E.L., Ranke A.H., Honkoop P.C. Precipitating and aggravating factors of migraine versus tension-type headache. Headache. 2001;41:554–558. doi: 10.1046/j.1526-4610.2001.041006554.x. [DOI] [PubMed] [Google Scholar]
- 40.Rose F.C. Trigger factors and natural history of migraine. Funct. Neurol. 1986;1:379–384. [PubMed] [Google Scholar]
- 41.Dalkara T., Kiliç K. How does fasting trigger migraine? A hypothesis. Curr. Pain Headache Rep. 2013;17:368. doi: 10.1007/s11916-013-0368-1. [DOI] [PubMed] [Google Scholar]
- 42.Robbins L. Precipitating factors in migraine: A retrospective review of 494 patients. Headache. 1994;34:214–216. doi: 10.1111/j.1526-4610.1994.hed3404214.x. [DOI] [PubMed] [Google Scholar]
- 43.Turner L.C., Molgaard C.A., Gardner C.H., Rothrock J.F., Stang P.E. Migraine trigger factors in non-clinical Mexican-American population in San Diego county: Implications for etiology. Cephalalgia. 1995;15:523–530. doi: 10.1046/j.1468-2982.1995.1506523.x. [DOI] [PubMed] [Google Scholar]
- 44.Scharff L., Turk D.C., Marcus D.A. Triggers of headache episodes and coping responses of headache diagnostic groups. Headache. 1995;35:397–403. doi: 10.1111/j.1526-4610.1995.hed3507397.x. [DOI] [PubMed] [Google Scholar]
- 45.Peroutka S.J. What Turns on a Migraine? A Systematic Review of Migraine Precipitating Factors. Curr. Pain Headache Rep. 2014;18:454. doi: 10.1007/s11916-014-0454-z. [DOI] [PubMed] [Google Scholar]
- 46.Abu-Salameh I., Plakht Y., Ifergane G. Migraine exacerbation during Ramadan fasting. J. Headache Pain. 2010;11:513–517. doi: 10.1007/s10194-010-0242-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Drescher M.J., Elstein Y. Prophylactic COX2 inhibitor: An end to the Yom Kippur headache. Headache. 2006;46:1487–1491. doi: 10.1111/j.1526-4610.2006.00609.x. [DOI] [PubMed] [Google Scholar]
- 48.Peroutka S.J. Serum glucose regulation and headache. Headache. 2002;42:303–308. doi: 10.1046/j.1526-4610.2002.02083.x. [DOI] [PubMed] [Google Scholar]
- 49.Blau J.N., Pyke D.A. Effect of diabetes on migraine. Lancet. 1970;2:241–243. doi: 10.1016/S0140-6736(70)92588-2. [DOI] [PubMed] [Google Scholar]
- 50.Gross E.C., Putananickal N., Orsini A.-L., Vogt D.R., Sandor P.S., Schoenen J., Fischer D. Mitochondrial function and oxidative stress markers in higher-frequency episodic migraine. Sci. Rep. 2021;11:4543. doi: 10.1038/s41598-021-84102-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.Mohammad S.S., Coman D., Calvert S. Glucose transporter 1 deficiency syndrome and hemiplegic migraines as a dominant presenting clinical feature. J. Paediatr. Child Health. 2014;50:1025–1026. doi: 10.1111/jpc.12613. [DOI] [PubMed] [Google Scholar]
- 52.Hoffmann U., Sukhotinsky I., Eikermann-Haerter K., Ayata C. Glucose modulation of spreading depression susceptibility. J. Cereb. Blood Flow Metab. 2013;33:191–195. doi: 10.1038/jcbfm.2012.132. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.Martins-Oliveira M., Akerman S., Holland P.R., Hoffmann J.R., Tavares I., Goadsby P.J. Neuroendocrine signaling modulates specific neural networks relevant to migraine. Neurobiol. Dis. 2017;101:16–26. doi: 10.1016/j.nbd.2017.01.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Westra H.J., Peters M.J., Esko T., Yaghootkar H., Schurmann C., Kettunen J., Christiansen M.W., Fairfax B.P., Schramm K., Powell J.E., et al. Systematic identification of trans eQTLs as putative drivers of known disease associations. Nat. Genet. 2013;45:1238–1243. doi: 10.1038/ng.2756. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55.Zou F., Chai H.S., Younkin C.S., Allen M., Crook J., Pankratz V.S., Carrasquillo M.M., Rowley C.N., Nair A.A., Middha S., et al. Brain expression genome-wide association study (eGWAS) identifies human disease-associated variants. PLoS Genet. 2012;8:e1002707. doi: 10.1371/journal.pgen.1002707. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 56.Bensaad K., Tsuruta A., Selak M.A., Vidal M.N., Nakano K., Bartrons R., Gottlieb E., Vousden K.H. TIGAR, a p53-inducible regulator of glycolysis and apoptosis. Cell. 2006;126:107–120. doi: 10.1016/j.cell.2006.05.036. [DOI] [PubMed] [Google Scholar]
- 57.Guldiken B., Guldiken S., Taskiran B., Koc G., Turgut N., Kabayel L., Tugrul A. Migraine in metabolic syndrome. Neurologist. 2009;15:55–58. doi: 10.1097/NRL.0b013e31817781b6. [DOI] [PubMed] [Google Scholar]
- 58.Bic Z., Blix G., Hopp H., Leslie F. In search of the ideal treatment for migraine headache. Med. Hypotheses. 1998;50:1–7. doi: 10.1016/S0306-9877(98)90170-0. [DOI] [PubMed] [Google Scholar]
- 59.Altamura C., Corbelli I., de Tommaso M., Di Lorenzo C., Di Lorenzo G., Di Renzo A., Filippi M., Jannini T.B., Messina R., Parisi P., et al. Pathophysiological Bases of Comorbidity in Migraine. Front. Hum. Neurosci. 2021;15:640574. doi: 10.3389/fnhum.2021.640574. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 60.Del Moro L., Rota E., Pirovano E., Rainero I. Migraine, Brain Glucose Metabolism and the “Neuroenergetic” Hypothesis: A Scoping Review. J. Pain. 2022;102:23–29. doi: 10.1016/j.jpain.2022.02.006. [DOI] [PubMed] [Google Scholar]
- 61.Arnold S.E., Arvanitakis Z., Macauley-Rambach S.L., Koenig A.M., Wang H.-Y., Ahima R.S., Craft S., Gandy S., Buettner C., Stoeckel L.E., et al. Brain insulin resistance in type 2 diabetes and Alzheimer disease: Concepts and conundrums. Nat. Rev. Neurol. 2018;14:168–181. doi: 10.1038/nrneurol.2017.185. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 62.Hamer J.A., Testani D., Mansur R.B., Lee Y., Subramaniapillai M., McIntyre R.S. Brain insulin resistance: A treatment target for cognitive impairment and anhedonia in depression. Exp. Neurol. 2019;315:1–8. doi: 10.1016/j.expneurol.2019.01.016. [DOI] [PubMed] [Google Scholar]
- 63.Gruber H.J., Bernecker C., Pailer S., Fauler G., Horejsi R., Möller R., Lechner A., Fazekas F., Truschnig-Wilders M. Hyperinsulinaemia in migraineurs is associated with nitric oxide stress. Cephalalgia. 2009;30:593–598. doi: 10.1111/j.1468-2982.2009.02012.x. [DOI] [PubMed] [Google Scholar]
- 64.Wang X., Li X., Diao Y., Meng S., Xing Y., Zhou H., Yang D., Sun J., Chen H., Zhao Y. Are Glucose and Insulin Metabolism and Diabetes Associated with Migraine? A Community-Based, Case-Control Study. J. Oral Facial Pain Headache. 2017;31:240–250. doi: 10.11607/ofph.1843. [DOI] [PubMed] [Google Scholar]
- 65.Bernecker C., Pailer S., Kieslinger P., Horejsi R., Möller R., Lechner A., Wallner-Blazek M., Weiss S., Fazekas F., Truschnig-Wilders M., et al. GLP-2 and leptin are associated with hyperinsulinemia in non-obese female migraineurs. Cephalalgia. 2010;30:1366–1374. doi: 10.1177/0333102410364674. [DOI] [PubMed] [Google Scholar]
- 66.Sachdev A., Marmura M.J. Metabolic syndrome and migraine. Front. Neurol. 2012;3:161. doi: 10.3389/fneur.2012.00161. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 67.Bhoi S.K., Kalita J., Misra U.K. Metabolic syndrome and insulin resistance in migraine. J. Headache Pain. 2012;13:321–326. doi: 10.1007/s10194-012-0416-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 68.Sacco S., Altobelli E., Ornello R., Ripa P., Pistoia F., Carolei A. Insulin resistance in migraineurs: Results from a case-control study. Cephalalgia. 2014;34:349–356. doi: 10.1177/0333102413511155. [DOI] [PubMed] [Google Scholar]
- 69.Porte D., Jr., Baskin D.G., Schwartz M.W. Insulin signaling in the central nervous system: A critical role in metabolic homeostasis and disease from C. elegans to humans. Diabetes. 2005;54:1264–1276. doi: 10.2337/diabetes.54.5.1264. [DOI] [PubMed] [Google Scholar]
- 70.Schwartz M.W., Figlewicz D.P., Baskin D.G., Woods S.C., Porte D., Jr. Insulin in the brain: A hormonal regulator of energy balance. Endocr. Rev. 1992;13:387–414. doi: 10.1210/edrv-13-3-387. [DOI] [PubMed] [Google Scholar]
- 71.Cetinkalp S., Simsir I.Y., Ertek S. Insulin resistance in brain and possible therapeutic approaches. Curr. Vasc. Pharmacol. 2014;12:553–564. doi: 10.2174/1570161112999140206130426. [DOI] [PubMed] [Google Scholar]
- 72.McCarthy L.C., Hosford D.A., Riley J.H., Bird M.I., White N.J., Hewett D.R., Peroutka S.J., Griffiths L.R., Boyd P.R., Lea R.A., et al. Single-nucleotide polymorphism alleles in the insulin receptor gene are associated with typical migraine. Genomics. 2001;78:135–149. doi: 10.1006/geno.2001.6647. [DOI] [PubMed] [Google Scholar]
- 73.Netzer C., Freudenberg J., Heinze A., Heinze-Kuhn K., Goebel I., McCarthy L.C., Roses A.D., Gobel H., Todt U., Kubisch C. Replication study of the insulin receptor gene in migraine with aura. Genomics. 2008;91:503–507. doi: 10.1016/j.ygeno.2008.03.006. [DOI] [PubMed] [Google Scholar]
- 74.Lee J., Pilch P.F. The insulin receptor: Structure, function, and signaling. Am. J. Physiol. 1994;266:C319–C334. doi: 10.1152/ajpcell.1994.266.2.C319. [DOI] [PubMed] [Google Scholar]
- 75.Adashi E.Y., Hsueh A.J., Bambino T.H., Yen S.S. Disparate effect of clomiphene and tamoxifen on pituitary gonadotropin release in vitro. Am. J. Physiol. 1981;240:E125–E130. doi: 10.1152/ajpendo.1981.240.2.E125. [DOI] [PubMed] [Google Scholar]
- 76.Cortelli P., Pierangeli G. Hypothalamus and headaches. Neurol. Sci. 2007;28:S198–S202. doi: 10.1007/s10072-007-0776-2. [DOI] [PubMed] [Google Scholar]
- 77.Holland P., Goadsby P.J. The hypothalamic orexinergic system: Pain and primary headaches. Headache. 2007;47:951–962. doi: 10.1111/j.1526-4610.2007.00842.x. [DOI] [PubMed] [Google Scholar]
- 78.Alstadhaug K.B. Migraine and the hypothalamus. Cephalalgia. 2009;29:809–817. doi: 10.1111/j.1468-2982.2008.01814.x. [DOI] [PubMed] [Google Scholar]
- 79.Schulte L.H., Allers A., May A. Hypothalamus as a mediator of chronic migraine. Neurology. 2017;88:2011. doi: 10.1212/WNL.0000000000003963. [DOI] [PubMed] [Google Scholar]
- 80.Denuelle M., Fabre N., Payoux P., Chollet F., Geraud G. Hypothalamic activation in spontaneous migraine attacks. Headache. 2007;47:1418–1426. doi: 10.1111/j.1526-4610.2007.00776.x. [DOI] [PubMed] [Google Scholar]
- 81.Kim C., Siscovick D.S., Sidney S., Lewis C.E., Kiefe C.I., Koepsell T.D. Oral contraceptive use and association with glucose, insulin, and diabetes in young adult women: The CARDIA Study. Coronary Artery Risk Development in Young Adults. Diabetes Care. 2002;25:1027–1032. doi: 10.2337/diacare.25.6.1027. [DOI] [PubMed] [Google Scholar]
- 82.Favoni V., Giani L., Al-Hassany L., Asioli G.M., Butera C., de Boer I., Guglielmetti M., Koniari C., Mavridis T., Vaikjärv M., et al. CGRP and migraine from a cardiovascular point of view: What do we expect from blocking CGRP? J. Headache Pain. 2019;20:27. doi: 10.1186/s10194-019-0979-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 83.Edvinsson L. The Trigeminovascular Pathway: Role of CGRP and CGRP Receptors in Migraine. Headache. 2017;57:47–55. doi: 10.1111/head.13081. [DOI] [PubMed] [Google Scholar]
- 84.Lassen L.H., Haderslev P.A., Jacobsen V.B., Iversen H.K., Sperling B., Olesen J. CGRP may play a causative role in migraine. Cephalalgia. 2002;22:54–61. doi: 10.1046/j.1468-2982.2002.00310.x. [DOI] [PubMed] [Google Scholar]
- 85.Iyengar S., Johnson K.W., Ossipov M.H., Aurora S.K. CGRP and the Trigeminal System in Migraine. Headache. 2019;59:659–681. doi: 10.1111/head.13529. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 86.Gram D.X., Ahrén B., Nagy I., Olsen U.B., Brand C.L., Sundler F., Tabanera R., Svendsen O., Carr R.D., Santha P., et al. Capsaicin-sensitive sensory fibers in the islets of Langerhans contribute to defective insulin secretion in Zucker diabetic rat, an animal model for some aspects of human type 2 diabetes. Eur. J. Neurosci. 2007;25:213–223. doi: 10.1111/j.1460-9568.2006.05261.x. [DOI] [PubMed] [Google Scholar]
- 87.Walker C.S., Li X., Whiting L., Glyn-Jones S., Zhang S., Hickey A.J., Sewell M.A., Ruggiero K., Phillips A.R., Kraegen E.W., et al. Mice lacking the neuropeptide alpha-calcitonin gene-related peptide are protected against diet-induced obesity. Endocrinology. 2010;151:4257–4269. doi: 10.1210/en.2010-0284. [DOI] [PubMed] [Google Scholar]
- 88.Hosseinpour M., Maleki F., Khoramdad M., Sullman M.J.M., Nejadghaderi S.A., Kolahi A.-A., Safiri S. A systematic literature review of observational studies of the bilateral association between diabetes and migraine. Diabetes Metab. Syndr. Clin. Res. Rev. 2021;15:673–678. doi: 10.1016/j.dsx.2021.03.018. [DOI] [PubMed] [Google Scholar]
- 89.Dodick D.W., Goadsby P.J., Spierings E.L., Scherer J.C., Sweeney S.P., Grayzel D.S. Safety and efficacy of LY2951742, a monoclonal antibody to calcitonin gene-related peptide, for the prevention of migraine: A phase 2, randomised, double-blind, placebo-controlled study. Lancet Neurol. 2014;13:885–892. doi: 10.1016/S1474-4422(14)70128-0. [DOI] [PubMed] [Google Scholar]
- 90.Melnyk A., Himms-Hagen J. Resistance to aging-associated obesity in capsaicin-desensitized rats one year after treatment. Obes. Res. 1995;3:337–344. doi: 10.1002/j.1550-8528.1995.tb00159.x. [DOI] [PubMed] [Google Scholar]
- 91.Pettersson M., Ahrén B., Böttcher G., Sundler F. Calcitonin gene-related peptide: Occurrence in pancreatic islets in the mouse and the rat and inhibition of insulin secretion in the mouse. Endocrinology. 1986;119:865–869. doi: 10.1210/endo-119-2-865. [DOI] [PubMed] [Google Scholar]
- 92.Gram D.X., Hansen A.J., Wilken M., Elm T., Svendsen O., Carr R.D., Ahrén B., Brand C.L. Plasma calcitonin gene-related peptide is increased prior to obesity, and sensory nerve desensitization by capsaicin improves oral glucose tolerance in obese Zucker rats. Eur. J. Endocrinol. 2005;153:963–969. doi: 10.1530/eje.1.02046. [DOI] [PubMed] [Google Scholar]
- 93.Saeedi P., Petersohn I., Salpea P., Malanda B., Karuranga S., Unwin N., Colagiuri S., Guariguata L., Motala A.A., Ogurtsova K., et al. Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes Atlas, 9th edition. Diabetes Res. Clin. Pract. 2019;157:107843. doi: 10.1016/j.diabres.2019.107843. [DOI] [PubMed] [Google Scholar]
- 94.Haghighi F.S., Rahmanian M., Namiranian N., Arzaghi S.M., Dehghan F., Chavoshzade F., Sepehri F. Migraine and type 2 diabetes; is there any association? J. Diabetes Metab. Disord. 2015;15:37. doi: 10.1186/s40200-016-0241-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 95.Split W., Szydlowska M. Headaches in non insulin-dependent diabetes mellitus. Funct. Neurol. 1997;12:327–332. [PubMed] [Google Scholar]
- 96.Aamodt A.H., Stovner L.J., Midthjell K., Hagen K., Zwart J.A. Headache prevalence related to diabetes mellitus. The Head-HUNT study. Eur. J. Neurol. 2007;14:738–744. doi: 10.1111/j.1468-1331.2007.01765.x. [DOI] [PubMed] [Google Scholar]
- 97.Berge L.I., Riise T., Fasmer O.B., Hundal O., Oedegaard K.J., Midthjell K., Lund A. Does diabetes have a protective effect on migraine? Epidemiology. 2013;24:129–134. doi: 10.1097/EDE.0b013e31827623d0. [DOI] [PubMed] [Google Scholar]
- 98.Burn W.K., Machin D., Waters W.E. Prevalence of migraine in patients with diabetes. Br. Med. J. 1984;289:1579–1580. doi: 10.1136/bmj.289.6458.1579-a. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 99.Hagen K., Åsvold B.O., Midthjell K., Stovner L.J., Zwart J.A., Linde M. Inverse relationship between type 1 diabetes mellitus and migraine. Data from the Nord-Trøndelag Health Surveys 1995–1997 and 2006–2008. Cephalalgia. 2018;38:417–426. doi: 10.1177/0333102417690488. [DOI] [PubMed] [Google Scholar]
- 100.Antonazzo I.C., Riise T., Cortese M., Berge L.I., Engeland A., Bernt Fasmer O., Lund A., Joachim Ødegaard K., Poluzzi E., Bjornevik K. Diabetes is associated with decreased migraine risk: A nationwide cohort study. Cephalalgia. 2018;38:1759–1764. doi: 10.1177/0333102417748573. [DOI] [PubMed] [Google Scholar]
- 101.Fagherazzi G., El Fatouhi D., Fournier A., Gusto G., Mancini F.R., Balkau B., Boutron-Ruault M.C., Kurth T., Bonnet F. Associations Between Migraine and Type 2 Diabetes in Women: Findings From the E3N Cohort Study. JAMA Neurol. 2019;76:257–263. doi: 10.1001/jamaneurol.2018.3960. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 102.Fazeli Farsani S., Souverein P.C., van der Vorst M.M., Knibbe C.A., de Boer A., Mantel-Teeuwisse A.K. Chronic comorbidities in children with type 1 diabetes: A population-based cohort study. Arch. Dis. Child. 2015;100:763–768. doi: 10.1136/archdischild-2014-307654. [DOI] [PubMed] [Google Scholar]
- 103.López-de-Andrés A., Del Barrio J.L., Hernández-Barrera V., de Miguel-Díez J., Jimenez-Trujillo I., Martinez-Huedo M.A., Jimenez-García R. Migraine in adults with diabetes; is there an association? Results of a population-based study. Diabetes Metab. Syndr. Obes. Targets. 2018;11:367. doi: 10.2147/DMSO.S170253. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 104.Tantucci C., Bottini P., Fiorani C., Dottorini M.L., Santeusanio F., Provinciali L., Sorbini C.A., Casucci G. Cerebrovascular reactivity and hypercapnic respiratory drive in diabetic autonomic neuropathy. J. Appl. Physiol. 2001;90:889–896. doi: 10.1152/jappl.2001.90.3.889. [DOI] [PubMed] [Google Scholar]
- 105.Wijnhoud A.D., Koudstaal P.J., Dippel D.W. Relationships of transcranial blood flow Doppler parameters with major vascular risk factors: TCD study in patients with a recent TIA or nondisabling ischemic stroke. J. Clin. Ultrasound. 2006;34:70–76. doi: 10.1002/jcu.20193. [DOI] [PubMed] [Google Scholar]
- 106.Ziegler D. Treatment of diabetic polyneuropathy: Update 2006. Ann. N. Y. Acad. Sci. 2006;1084:250–266. doi: 10.1196/annals.1372.008. [DOI] [PubMed] [Google Scholar]
- 107.Rivera-Mancilla E., Al-Hassany L., Villalón C.M., MaassenVanDenBrink A. Metabolic Aspects of Migraine: Association With Obesity and Diabetes Mellitus. Front. Neurol. 2021;12:686398. doi: 10.3389/fneur.2021.686398. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 108.Amin F.M., Aristeidou S., Baraldi C., Czapinska-Ciepiela E.K., Ariadni D.D., Di Lenola D., Fenech C., Kampouris K., Karagiorgis G., Braschinsky M., et al. The association between migraine and physical exercise. J. Headache. 2018;19:1–9. doi: 10.1186/s10194-018-0902-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 109.Evcili G., Utku U., Öğün M.N., Özdemir G. Early and long period follow-up results of low glycemic index diet for migraine prophylaxis. J. Turk. Soc. Algol. 2018;30:8–11. doi: 10.5505/agri.2017.62443. [DOI] [PubMed] [Google Scholar]
- 110.Razeghi Jahromi S., Ghorbani Z., Martelletti P., Lampl C., Togha M., On behalf of the School of Advanced Studies of the European Headache Federation (EHF-SAS) Association of diet and headache. J. Headache Pain. 2019;20:106. doi: 10.1186/s10194-019-1057-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 111.Gazerani P. Migraine and Diet. Nutrients. 2020;12:1658. doi: 10.3390/nu12061658. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 112.Cervenka M.C., Wood S., Bagary M., Balabanov A., Bercovici E., Brown M.G., Devinsky O., Di Lorenzo C., Doherty C.P., Felton E., et al. International Recommendations for the Management of Adults Treated with Ketogenic Diet Therapies. Neurol. Clin. Pract. 2021;11:385–397. doi: 10.1212/CPJ.0000000000001007. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 113.Di Lorenzo C., Ballerini G., Barbanti P., Bernardini A., D’Arrigo G., Egeo G., Frediani F., Garbo R., Pierangeli G., Prudenzano M.P., et al. Applications of Ketogenic Diets in Patients with Headache: Clinical Recommendations. Nutrients. 2021;13:2307. doi: 10.3390/nu13072307. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 114.Di Lorenzo C., Pinto A., Ienca R., Coppola G., Sirianni G., Di Lorenzo G., Parisi V., Serrao M., Spagnoli A., Vestri A., et al. A Randomized Double-Blind, Cross-Over Trial of very Low-Calorie Diet in Overweight Migraine Patients: A Possible Role for Ketones? Nutrients. 2019;11:1742. doi: 10.3390/nu11081742. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 115.Altamura C., Cecchi G., Bravo M., Brunelli N., Laudisio A., Caprio P.D., Botti G., Paolucci M., Khazrai Y.M., Vernieri F. The Healthy Eating Plate Advice for Migraine Prevention: An Interventional Study. Nutrients. 2020;12:1579. doi: 10.3390/nu12061579. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 116.Wang W., Zhang C., Liu H., Xu C., Duan H., Tian X., Zhang D. Heritability and genome-wide association analyses of fasting plasma glucose in Chinese adult twins. BMC Genom. 2020;21:491. doi: 10.1186/s12864-020-06898-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 117.Peck K.R., Johnson Y.L., Smitherman T.A. Migraine. Handb. Clin. Neurol. 2016;138:283–293. doi: 10.1016/b978-0-12-802973-2.00016-1. [DOI] [PubMed] [Google Scholar]
- 118.Ulrich V., Gervil M., Kyvik K.O., Olesen J., Russell M.B. The inheritance of migraine with aura estimated by means of structural equation modelling. J. Med. Genet. 1999;36:225–227. [PMC free article] [PubMed] [Google Scholar]
- 119.Merikangas K., Tierney C., Martin N., Heath A., Risch N. Genetics of migraine in the Australian Twin Registry. New Adv. Headache Res. 1994;4:27–28. [Google Scholar]
- 120.Larsson B., Bille B., Pedersen N.L. Genetic influence in headaches: A Swedish twin study. Headache J. Head Face Pain. 1995;35:513–519. doi: 10.1111/j.1526-4610.1995.hed3509513.x. [DOI] [PubMed] [Google Scholar]
- 121.Honkasalo M.L., Kaprio J., Winter T., Heikkilä K., Sillanpää M., Koskenvuo M. Migraine and concomitant symptoms among 8167 adult twin pairs. Headache J. Head Face Pain. 1995;35:70–78. doi: 10.1111/j.1526-4610.1995.hed3502070.x. [DOI] [PubMed] [Google Scholar]
- 122.Gervil M., Ulrich V., Kaprio J., Olesen J., Russell M. The relative role of genetic and environmental factors in migraine without aura. Neurology. 1999;53:995. doi: 10.1212/WNL.53.5.995. [DOI] [PubMed] [Google Scholar]
- 123.Wessman M., Kaunisto M.A., Kallela M., Palotie A. The molecular genetics of migraine. Ann. Med. 2004;36:462–473. doi: 10.1080/07853890410018060. [DOI] [PubMed] [Google Scholar]
- 124.Mulder E.J., Van Baal C., Gaist D., Kallela M., Kaprio J., Svensson D.A., Nyholt D.R., Martin N.G., MacGregor A.J., Cherkas L.F. Genetic and environmental influences on migraine: A twin study across six countries. Twin Res. Hum. Genet. 2003;6:422–431. doi: 10.1375/136905203770326420. [DOI] [PubMed] [Google Scholar]
- 125.Nyholt D.R., Gillespie N.G., Heath A.C., Merikangas K.R., Duffy D.L., Martin N.G. Latent class and genetic analysis does not support migraine with aura and migraine without aura as separate entities. Genet. Epidemiol. 2004;26:231–244. doi: 10.1002/gepi.10311. [DOI] [PubMed] [Google Scholar]
- 126.Ziegler D.K., Hur Y.M., Bouchard T.J., Jr., Hassanein R.S., Barter R. Migraine in twins raised together and apart. Headache J. Head Face Pain. 1998;38:417–422. doi: 10.1046/j.1526-4610.1998.3806417.x. [DOI] [PubMed] [Google Scholar]
- 127.Svensson D.A., Larsson B., Waldenlind E., Pedersen N.L. Shared rearing environment in migraine: Results from twins reared apart and twins reared together. Headache J. Head Face Pain. 2003;43:235–244. doi: 10.1046/j.1526-4610.2003.03047.x. [DOI] [PubMed] [Google Scholar]
- 128.Gardner K.L. Genetics of migraine: An update. Headache J. Head Face Pain. 2006;46:S19–S24. doi: 10.1111/j.1526-4610.2006.00486.x. [DOI] [PubMed] [Google Scholar]
- 129.WHO . Global Report on Diabetes. World Health Organization; Geneva, Switzerland: 2016. [Google Scholar]
- 130.van Dongen J., Willemsen G., Chen W.-M., de Geus E.J.C., Boomsma D.I. Heritability of metabolic syndrome traits in a large population-based sample. J. Lipid Res. 2013;54:2914–2923. doi: 10.1194/jlr.P041673. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 131.Prasad R.B., Groop L. Genetics of type 2 diabetes-pitfalls and possibilities. Genes. 2015;6:87–123. doi: 10.3390/genes6010087. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 132.Øie L.R., Kurth T., Gulati S., Dodick D.W. Migraine and risk of stroke. J. Neurol. Neurosurg. Psychiatry. 2020;91:593–604. doi: 10.1136/jnnp-2018-318254. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 133.Yang Y., Zhao H., Heath A.C., Madden P.A.F., Martin N.G., Nyholt D.R. Shared Genetic Factors Underlie Migraine and Depression. Twin Res. Hum. Genet. 2016;19:341–350. doi: 10.1017/thg.2016.46. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 134.Adewuyi E.O., Sapkota Y., Auta A., Yoshihara K., Nyegaard M., Griffiths L.R., Montgomery G.W., International Endogene Consortium IEC. andMe Research Team. International Headache Genetics Consortium IHGH et al. Shared Molecular Genetic Mechanisms Underlie Endometriosis and Migraine Comorbidity. Genes. 2020;11:268. doi: 10.3390/genes11030268. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 135.Siewert K.M., Klarin D., Damrauer S.M., Chang K.-M., Tsao P.S., Assimes T.L., Davey Smith G., Voight B.F., The International Headache Genetics C. Cross-trait analyses with migraine reveal widespread pleiotropy and suggest a vascular component to migraine headache. Int. J. Epidemiol. 2020;49:1022–1031. doi: 10.1093/ije/dyaa050. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 136.Bulik-Sullivan B., Finucane H.K., Anttila V., Gusev A., Day F.R., Loh P.R., Duncan L., Perry J.R., Patterson N., Robinson E.B., et al. An atlas of genetic correlations across human diseases and traits. Nat. Genet. 2015;47:1236–1241. doi: 10.1038/ng.3406. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 137.Rainero I., Roveta F., Vacca A., Noviello C., Rubino E. Migraine pathways and the identification of novel therapeutic targets. Expert Opin. Ther. Targets. 2020;24:245–253. doi: 10.1080/14728222.2020.1728255. [DOI] [PubMed] [Google Scholar]
- 138.Wei F.J., Cai C.Y., Yu P., Lv J., Ling C., Shi W.T., Jiao H.X., Chang B.C., Yang F.H., Tian Y., et al. Quantitative candidate gene association studies of metabolic traits in Han Chinese type 2 diabetes patients. Genet. Mol. Res. 2015;14:15471–15481. doi: 10.4238/2015.November.30.25. [DOI] [PubMed] [Google Scholar]
- 139.Barroso I., Luan J.a., Middelberg R.P.S., Harding A.-H., Franks P.W., Jakes R.W., Clayton D., Schafer A.J., O’Rahilly S., Wareham N.J. Candidate gene association study in type 2 diabetes indicates a role for genes involved in β-cell function as well as insulin action. PLoS Biol. 2003;1:e20. doi: 10.1371/journal.pbio.0000020. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 140.Brown A.E., Walker M. Genetics of Insulin Resistance and the Metabolic Syndrome. Curr. Cardiol. Rep. 2016;18:75. doi: 10.1007/s11886-016-0755-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 141.Barroso I. Genetics of Type 2 diabetes. Diabet. Med. J. Br. Diabet. Assoc. 2005;22:517–535. doi: 10.1111/j.1464-5491.2005.01550.x. [DOI] [PubMed] [Google Scholar]
- 142.Rubino E., Ferrero M., Rainero I., Binello E., Vaula G., Pinessi L. Association of the C677T polymorphism in the MTHFR gene with migraine: A meta-analysis. Cephalalgia. 2009;29:818–825. doi: 10.1111/j.1468-2982.2007.01400.x. [DOI] [PubMed] [Google Scholar]
- 143.Schürks M., Rist P.M., Kurth T. MTHFR 677C>T and ACE D/I polymorphisms in migraine: A systematic review and meta-analysis. Headache. 2010;50:588–599. doi: 10.1111/j.1526-4610.2009.01570.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 144.Samaan Z., Gaysina D., Cohen-Woods S., Craddock N., Jones L., Korszun A., Owen M., Mente A., McGuffin P., Farmer A. Methylenetetrahydrofolate Reductase Gene Variant (MTHFR C677T) and Migraine: A Case Control Study and Meta-analysis. BMC Neurol. 2011;11:66. doi: 10.1186/1471-2377-11-66. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 145.Todt U., Freudenberg J., Goebel I., Netzer C., Heinze A., Heinze-Kuhn K., Göbel H., Kubisch C. MTHFR C677T polymorphism and migraine with aura. Ann. Neurol. 2006;60:621–622. doi: 10.1002/ana.20911. [DOI] [PubMed] [Google Scholar]
- 146.Kaunisto M.A., Kallela M., Hämäläinen E., Kilpikari R., Havanka H., Harno H., Nissilä M., Säkö E., Ilmavirta M., Liukkonen J., et al. Testing of variants of the MTHFR and ESR1 genes in 1798 Finnish individuals fails to confirm the association with migraine with aura. Cephalalgia. 2006;26:1462–1472. doi: 10.1111/j.1468-2982.2006.01228.x. [DOI] [PubMed] [Google Scholar]
- 147.Zhu B., Wu X., Zhi X., Liu L., Zheng Q., Sun G. Methylenetetrahydrofolate reductase C677T polymorphism and type 2 diabetes mellitus in Chinese population: A meta-analysis of 29 case-control studies. PLoS ONE. 2014;9:e102443. doi: 10.1371/journal.pone.0102443. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 148.Wang H., Hu C., Xiao S.H., Wan B. Association of tagging SNPs in the MTHFR gene with risk of type 2 diabetes mellitus and serum homocysteine levels in a Chinese population. Dis. Markers. 2014;2014:725731. doi: 10.1155/2014/725731. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 149.Al-Rubeaan K., Siddiqui K., Saeb A.T.M., Nazir N., Al-Naqeb D., Al-Qasim S. ACE I/D and MTHFR C677T polymorphisms are significantly associated with type 2 diabetes in Arab ethnicity: A meta-analysis. Gene. 2013;520:166–177. doi: 10.1016/j.gene.2013.02.017. [DOI] [PubMed] [Google Scholar]
- 150.Errera F.I., Silva M.E., Yeh E., Maranduba C.M., Folco B., Takahashi W., Pereira A.C., Krieger J.E., Passos-Bueno M.R. Effect of polymorphisms of the MTHFR and APOE genes on susceptibility to diabetes and severity of diabetic retinopathy in Brazilian patients. Braz. J. Med. Biol. Res. 2006;39:883–888. doi: 10.1590/S0100-879X2006000700005. [DOI] [PubMed] [Google Scholar]
- 151.Pirozzi F.F., Belini Junior E., Okumura J.V., Salvarani M., Bonini-Domingos C.R., Ruiz M.A. The relationship between of ACE I/D and the MTHFR C677T polymorphisms in the pathophysiology of type 2 diabetes mellitus in a population of Brazilian obese patients. Arch. Endocrinol. Metab. 2018;62:21–26. doi: 10.20945/2359-3997000000005. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 152.Curtain R., Tajouri L., Lea R., MacMillan J., Griffiths L. No mutations detected in the INSR gene in a chromosome 19p13 linked migraine pedigree. Eur. J. Med. Genet. 2006;49:57–62. doi: 10.1016/j.ejmg.2005.01.015. [DOI] [PubMed] [Google Scholar]
- 153.Kaunisto M.A., Tikka P.J., Kallela M., Leal S.M., Papp J.C., Korhonen A., Hämäläinen E., Harno H., Havanka H., Nissilä M., et al. Chromosome 19p13 loci in Finnish migraine with aura families. Am. J. Med. Genet. Part B Neuropsychiatr. Genet. 2005;132B:85–89. doi: 10.1002/ajmg.b.30082. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 154.’t Hart L.M., Stolk R.P., Dekker J.M., Nijpels G., Grobbee D.E., Heine R.J., Maassen J.A. Prevalence of variants in candidate genes for type 2 diabetes mellitus in The Netherlands: The Rotterdam study and the Hoorn study. J. Clin. Endocrinol. Metab. 1999;84:1002–1006. doi: 10.1210/jcem.84.3.5563. [DOI] [PubMed] [Google Scholar]
- 155.Hart L.T., Stolk R., Heine R., Grobbee D., Van Der Does F., Maassen J. Association of the insulin-receptor variant Met-985 with hyperglycemia and non-insulin-dependent diabetes mellitus in the Netherlands: A population-based study. Am. J. Hum. Genet. 1996;59:1119. [PMC free article] [PubMed] [Google Scholar]
- 156.Hansen L., Hansen T., Clausen J.O., Echwald S.M., Urhammer S.A., Rasmussen S.K., Pedersen O. The Val985Met insulin-receptor variant in the Danish Caucasian population: Lack of associations with non-insulin-dependent diabetes mellitus or insulin resistance. Am. J. Hum. Genet. 1997;60:1532. doi: 10.1086/515464. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 157.Mazaheri S., Hajilooi M., Rafiei A. The G-308A promoter variant of the tumor necrosis factor-alpha gene is associated with migraine without aura. J. Neurol. 2006;253:1589–1593. doi: 10.1007/s00415-006-0270-4. [DOI] [PubMed] [Google Scholar]
- 158.Zhao Y., Li Z., Zhang L., Zhang Y., Yang Y., Tang Y., Fu P. The TNF-alpha-308 G/A polymorphism is associated with type 2 diabetes mellitus: An updated meta-analysis. Mol. Biol. Rep. 2014;41:73–83. doi: 10.1007/s11033-013-2839-1. [DOI] [PubMed] [Google Scholar]
- 159.Golshani H., Haghani K., Dousti M., Bakhtiyari S. Association of TNF-α 308 G/A Polymorphism With Type 2 Diabetes: A Case–Control Study in the Iranian Kurdish Ethnic Group. Osong Public Health Res. Perspect. 2015;6:94–99. doi: 10.1016/j.phrp.2015.01.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 160.Liu Z.H., Ding Y.L., Xiu L.C., Pan H.Y., Liang Y., Zhong S.Q., Liu W.W., Rao S.Q., Kong D.L. A meta-analysis of the association between TNF-α-308 G>A polymorphism and type 2 diabetes mellitus in Han Chinese population. PLoS ONE. 2013;8:e59421. doi: 10.1371/journal.pone.0059421. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 161.Feng R.-N., Zhao C., Sun C.-H., Li Y. Meta-Analysis of TNF 308 G/A Polymorphism and Type 2 Diabetes Mellitus. PLoS ONE. 2011;6:e18480. doi: 10.1371/journal.pone.0018480. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 162.Day C.P., Grove J., Daly A.K., Stewart M.W., Avery P.J., Walker M. Tumour necrosis factor-alpha gene promoter polymorphism and decreased insulin resistance. Diabetologia. 1998;41:430–434. doi: 10.1007/s001250050926. [DOI] [PubMed] [Google Scholar]
- 163.Feng R., Li Y., Zhao D., Wang C., Niu Y., Sun C. Lack of association between TNF 238 G/A polymorphism and type 2 diabetes: A meta-analysis. Acta Diabetol. 2009;46:339. doi: 10.1007/s00592-009-0118-3. [DOI] [PubMed] [Google Scholar]
- 164.Meng N., Zhang Y., Li H., Ma J., Qu Y. Association of tumor necrosis factor alpha promoter polymorphism (TNF-α 238 G/A and TNF-α 308 G/A) with diabetic mellitus, diabetic retinopathy and diabetic nephropathy: A meta-analysis. Curr. Eye Res. 2014;39:194–203. doi: 10.3109/02713683.2013.834942. [DOI] [PubMed] [Google Scholar]
- 165.Yang J., Han R., Chen M., Yuan Y., Hu X., Ma Y., Wu M., Zhang X., Wang M., Jiang S. Associations of estrogen receptor alpha gene polymorphisms with type 2 diabetes mellitus and metabolic syndrome: A systematic review and meta-analysis. Horm. Metab. Res. 2018;50:469–477. doi: 10.1055/a-0620-8553. [DOI] [PubMed] [Google Scholar]
- 166.Huang Q., Wang T.-H., Lu W.-H., Mu P.-W., Yang Y.-F., Liang W.-W., Li C.-X., Lin G.-P. Estrogen receptor alpha gene polymorphism associated with type 2 diabetes mellitus and the serum lipid concentration in Chinese women in Guangzhou. Chin. Med. J. 2006;119:1794–1801. doi: 10.1097/00029330-200611010-00006. [DOI] [PubMed] [Google Scholar]
- 167.Sale M.M., Freedman B.I., Langefeld C.D., Williams A.H., Hicks P.J., Colicigno C.J., Beck S.R., Brown W.M., Rich S.S., Bowden D.W. A genome-wide scan for type 2 diabetes in African-American families reveals evidence for a locus on chromosome 6q. Diabetes. 2004;53:830–837. doi: 10.2337/diabetes.53.3.830. [DOI] [PubMed] [Google Scholar]
- 168.Colson N.J., Lea R.A., Quinlan S., MacMillan J., Griffiths L.R. The estrogen receptor 1 G594A polymorphism is associated with migraine susceptibility in two independent case/control groups. Neurogenetics. 2004;5:129–133. doi: 10.1007/s10048-004-0181-4. [DOI] [PubMed] [Google Scholar]
- 169.Colson N.J., Lea R.A., Quinlan S., MacMillan J., Griffiths L.R. Investigation of hormone receptor genes in migraine. Neurogenetics. 2005;6:17–23. doi: 10.1007/s10048-004-0205-0. [DOI] [PubMed] [Google Scholar]
- 170.Schürks M., Rist P.M., Kurth T. Sex hormone receptor gene polymorphisms and migraine: A systematic review and meta-analysis. Cephalalgia. 2010;30:1306–1328. doi: 10.1177/0333102410364155. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 171.Oterino A., Pascual J., de Alegría C.R., Valle N., Castillo J., Bravo Y., González F., Sánchez-Velasco P., Cayón A., Leyva-Cobián F. Association of migraine and ESR1 G325C polymorphism. Neuroreport. 2006;17:61–64. doi: 10.1097/01.wnr.0000192735.85287.f4. [DOI] [PubMed] [Google Scholar]
- 172.Gonçalves F.M., Martins-Oliveira A., Speciali J.G., Luizon M.R., Izidoro-Toledo T.C., Silva P.S., Dach F., Tanus-Santos J.E. Endothelial nitric oxide synthase haplotypes associated with aura in patients with migraine. DNA Cell Biol. 2011;30:363–369. doi: 10.1089/dna.2010.1152. [DOI] [PubMed] [Google Scholar]
- 173.Gonçalves F.M., Luizon M.R., Speciali J.G., Martins-Oliveira A., Dach F., Tanus-Santos J.E. Interaction among nitric oxide (NO)-related genes in migraine susceptibility. Mol. Cell. Biochem. 2012;370:183–189. doi: 10.1007/s11010-012-1409-5. [DOI] [PubMed] [Google Scholar]
- 174.Toriello M., Oterino A., Pascual J., Castillo J., Colás R., Alonso-Arranz A., Ruiz-Alegría C., Quintela E., Montón F., Ruiz-Lavilla N. Lack of association of endothelial nitric oxide synthase polymorphisms and migraine. Headache J. Head Face Pain. 2008;48:1115–1119. doi: 10.1111/j.1526-4610.2008.01181.x. [DOI] [PubMed] [Google Scholar]
- 175.Galanakis E., Kofteridis D., Stratigi K., Petraki E., Vazgiourakis V., Fragouli E., Mamoulakis D., Boumpas D.T., Goulielmos G.N. Intron 4 a/b polymorphism of the endothelial nitric oxide synthase gene is associated with both type 1 and type 2 diabetes in a genetically homogeneous population. Hum. Immunol. 2008;69:279–283. doi: 10.1016/j.humimm.2008.03.001. [DOI] [PubMed] [Google Scholar]
- 176.Jia Z., Zhang X., Kang S., Wu Y. Association of endothelial nitric oxide synthase gene polymorphisms with type 2 diabetes mellitus: A meta-analysis. Endocr. J. 2013;60:893–901. doi: 10.1507/endocrj.EJ12-0463. [DOI] [PubMed] [Google Scholar]
- 177.Mehrab-Mohseni M., Tabatabaei-Malazy O., Hasani-Ranjbar S., Amiri P., Kouroshnia A., Bazzaz J.T., Farahani-Shrhabi M., Larijani B., Amoli M.M. Endothelial nitric oxide synthase VNTR (intron 4 a/b) polymorphism association with type 2 diabetes and its chronic complications. Diabetes Res. Clin. Pract. 2011;91:348–352. doi: 10.1016/j.diabres.2010.12.030. [DOI] [PubMed] [Google Scholar]
- 178.Eröz R., Bahadir A., Dikici S., Tasdemir S. Association of endothelial nitric oxide synthase gene polymorphisms (894G/T,−786T/C, G10T) and clinical findings in patients with migraine. Neuromol. Med. 2014;16:587–593. doi: 10.1007/s12017-014-8311-0. [DOI] [PubMed] [Google Scholar]
- 179.Borroni B., Rao R., Liberini P., Venturelli E., Cossandi M., Archetti S., Caimi L., Padovani A. Endothelial nitric oxide synthase (Glu298Asp) polymorphism is an independent risk factor for migraine with aura. Headache J. Head Face Pain. 2006;46:1575–1579. doi: 10.1111/j.1526-4610.2006.00614.x. [DOI] [PubMed] [Google Scholar]
- 180.Monti L.D., Barlassina C., Citterio L., Galluccio E., Berzuini C., Setola E., Valsecchi G., Lucotti P., Pozza G., Bernardinelli L., et al. Endothelial nitric oxide synthase polymorphisms are associated with type 2 diabetes and the insulin resistance syndrome. Diabetes. 2003;52:1270–1275. doi: 10.2337/diabetes.52.5.1270. [DOI] [PubMed] [Google Scholar]
- 181.Bressler J., Pankow J.S., Coresh J., Boerwinkle E. Interaction between the NOS3 gene and obesity as a determinant of risk of type 2 diabetes: The atherosclerosis risk in communities study. PLoS ONE. 2013;8:e79466. doi: 10.1371/journal.pone.0079466. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 182.García-Martín E., Martínez C., Serrador M., Alonso-Navarro H., Navacerrada F., Agúndez J.A.G., Jiménez-Jiménez F.J. Paraoxonase 1 (PON1) polymorphisms and risk for migraine. J. Neurol. 2010;257:1482–1485. doi: 10.1007/s00415-010-5551-2. [DOI] [PubMed] [Google Scholar]
- 183.Yıldırım S., Akar S., Kuyucu M., Yıldırım A., Dane S., Aygül R. Paraoxonase 1 gene polymorphisms, paraoxonase/arylesterase activities and oxidized low-density lipoprotein levels in patients with migraine. Cell Biochem. Funct. 2011;29:549–554. doi: 10.1002/cbf.1785. [DOI] [PubMed] [Google Scholar]
- 184.Gentile G., Negro A., D’Alonzo L., Aimati L., Simmaco M., Martelletti P., Borro M. Lack of association between oxidative stress-related gene polymorphisms and chronic migraine in an Italian population. Expert Rev. Neurother. 2015;15:215–225. doi: 10.1586/14737175.2015.1001748. [DOI] [PubMed] [Google Scholar]
- 185.Flekač M., Škrha J., Zidkova K., Lacinova Z., Hilgertova J. Paraoxonase 1 gene polymorphisms and enzyme activities in diabetes mellitus. Physiol. Res. 2008;57:717–726. doi: 10.33549/physiolres.931285. [DOI] [PubMed] [Google Scholar]
- 186.Agachan B., Yilmaz H., Karaali Z., İsbir T. Paraoxonase 55 and 192 polymorphism and its relationship to serum paraoxonase activity and serum lipids in Turkish patients with non-insulin dependent diabetes mellitus. Cell Biochem. Funct. Cell. Biochem. Modul. Act. Agents Dis. 2004;22:163–168. doi: 10.1002/cbf.1070. [DOI] [PubMed] [Google Scholar]
- 187.Karabina S.-A.P., Lehner A.N., Frank E., Parthasarathy S., Santanam N. Oxidative inactivation of paraoxonase—Implications in diabetes mellitus and atherosclerosis. Biochim. Biophys. Acta Gen. Subj. 2005;1725:213–221. doi: 10.1016/j.bbagen.2005.07.005. [DOI] [PubMed] [Google Scholar]
- 188.Van den Berg S., Jansen E., Kruijshoop M., Beekhof P., Blaak E., Van Der Kallen C., Van Greevenbroek M., Feskens E. Paraoxonase 1 phenotype distribution and activity differs in subjects with newly diagnosed Type 2 diabetes (the CODAM Study) Diabet. Med. 2008;25:186–193. doi: 10.1111/j.1464-5491.2007.02328.x. [DOI] [PubMed] [Google Scholar]
- 189.Zhang Q., Shao A., Jiang Z., Tsai H., Liu W. The exploration of mechanisms of comorbidity between migraine and depression. J. Cell. Mol. Med. 2019;23:4505–4513. doi: 10.1111/jcmm.14390. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 190.Stuart S., Cox H.C., Lea R.A., Griffiths L.R. The role of the MTHFR gene in migraine. Headache. 2012;52:515–520. doi: 10.1111/j.1526-4610.2012.02106.x. [DOI] [PubMed] [Google Scholar]
- 191.Liu R., Geng P., Ma M., Yu S., Yang M., He M., Dong Z., Zhang W. MTHFR C677T polymorphism and migraine risk: A meta-analysis. J. Neurol. Sci. 2014;336:68–73. doi: 10.1016/j.jns.2013.10.008. [DOI] [PubMed] [Google Scholar]
- 192.Joshi G., Pradhan S., Mittal B. Role of the ACE ID and MTHFR C677T polymorphisms in genetic susceptibility of migraine in a north Indian population. J. Neurol. Sci. 2009;277:133–137. doi: 10.1016/j.jns.2008.11.002. [DOI] [PubMed] [Google Scholar]
- 193.Schürks M., Zee R.Y., Buring J.E., Kurth T. MTHFR 677C->T and ACE D/I polymorphisms and migraine attack frequency in women. Cephalalgia. 2010;30:447–456. doi: 10.1111/j.1468-2982.2009.01980.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 194.Bodhini D., Sandhiya M., Ghosh S., Majumder P.P., Rao M.R., Mohan V., Radha V. Association of His1085His INSR gene polymorphism with type 2 diabetes in South Indians. Diabetes Technol. Ther. 2012;14:696–700. doi: 10.1089/dia.2012.0009. [DOI] [PubMed] [Google Scholar]
- 195.Masternak M.M., Al-Regaiey K.A., Lim M.M.D.R., Jimenez-Ortega V., Panici J.A., Bonkowski M.S., Bartke A. Effects of caloric restriction on insulin pathway gene expression in the skeletal muscle and liver of normal and long-lived GHR-KO mice. Exp. Gerontol. 2005;40:679–684. doi: 10.1016/j.exger.2005.06.003. [DOI] [PubMed] [Google Scholar]
- 196.Villegas R., Delahanty R., Williams S., Li H., O’Brian R., Shi J., Cai Q., Xiang Y.B., Shu X.O. Genetic Variation and Insulin Resistance in Middle-Aged Chinese Men. Ann. Hum. Genet. 2015;79:357–365. doi: 10.1111/ahg.12124. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 197.Batista T.M., Haider N., Kahn C.R. Defining the underlying defect in insulin action in type 2 diabetes. Diabetologia. 2021;64:994–1006. doi: 10.1007/s00125-021-05415-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 198.O’Rahilly S., Krook A., Morgan R., Reese A., Flier J., Moller D. Insulin receptor and insulin-responsive glucose transporter (GLUT 4) mutations and polymorphisms in a Welsh type 2 (non-insulin-dependent) diabetic population. Diabetologia. 1992;35:486–489. doi: 10.1007/BF02342449. [DOI] [PubMed] [Google Scholar]
- 199.Rainero I., Grimaldi L., Salani G., Valfre W., Rivoiro C., Savi L., Pinessi L. Association between the tumor necrosis factor-α−308 G/A gene polymorphism and migraine. Neurology. 2004;62:141–143. doi: 10.1212/01.WNL.0000101717.16799.8F. [DOI] [PubMed] [Google Scholar]
- 200.Lindholm E., Bakhtadze E., Cilio C., Agardh E., Groop L., Agardh C.-D. Association between LTA, TNF and AGER polymorphisms and late diabetic complications. PLoS ONE. 2008;3:e2546. doi: 10.1371/journal.pone.0002546. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 201.Valenti L., Fracanzani A.L., Dongiovanni P., Santorelli G., Branchi A., Taioli E., Fiorelli G., Fargion S. Tumor necrosis factor α promoter polymorphisms and insulin resistance in nonalcoholic fatty liver disease. Gastroenterology. 2002;122:274–280. doi: 10.1053/gast.2002.31065. [DOI] [PubMed] [Google Scholar]
- 202.Jackson K.G., Li Y., Ryan M.F., Gibney E.R., Brennan L., Roche H.M., Williams C.M., Lovegrove J.A., Vimaleswaran K.S. Association of the tumor necrosis factor-alpha promoter polymorphism with change in triacylglycerol response to sequential meals. Nutr. J. 2015;15:70. doi: 10.1186/s12937-016-0190-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 203.Colson N.J., Lea R.A., Quinlan S., Griffiths L.R. No role for estrogen receptor 1 gene intron 1 Pvu II and exon 4 C325G polymorphisms in migraine susceptibility. BMC Med. Genet. 2006;7:12. doi: 10.1186/1471-2350-7-12. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 204.Lipton R.B., Diamond S., Reed M., Diamond M.L., Stewart W.F. Migraine diagnosis and treatment: Results from the American Migraine Study II. Headache J. Head Face Pain. 2001;41:638–645. doi: 10.1046/j.1526-4610.2001.041007638.x. [DOI] [PubMed] [Google Scholar]
- 205.Maggioni F., Alessi C., Maggino T., Zanchin G. Headache during pregnancy. Cephalalgia. 1997;17:765–769. doi: 10.1046/j.1468-2982.1997.1707765.x. [DOI] [PubMed] [Google Scholar]
- 206.MacGregor E.A. Headache and hormone replacement therapy in the postmenopausal woman. Curr. Treat. Options Neurol. 2009;11:10–17. doi: 10.1007/s11940-009-0002-z. [DOI] [PubMed] [Google Scholar]
- 207.MacGregor E.A. Oestrogen and attacks of migraine with and without aura. Lancet Neurol. 2004;3:354–361. doi: 10.1016/S1474-4422(04)00768-9. [DOI] [PubMed] [Google Scholar]
- 208.Gupta S., Mehrotra S., Villalón C.M., Perusquía M., Saxena P.R., MaassenVanDenBrink A. Potential role of female sex hormones in the pathophysiology of migraine. Pharmacology. 2007;113:321–340. doi: 10.1016/j.pharmthera.2006.08.009. [DOI] [PubMed] [Google Scholar]
- 209.Oterino A., Toriello M., Cayón A., Castillo J., Colas R., Alonson-Arranz A., Ruiz-Alegria C., Quintela E., Monton F., Ruiz-Lavilla N., et al. Multilocus analyses reveal involvement of the ESR1, ESR2, and FSHR genes in migraine. Headache. 2008;48:1438–1450. doi: 10.1111/j.1526-4610.2008.01294.x. [DOI] [PubMed] [Google Scholar]
- 210.Ereqat S., Cauchi S., Eweidat K., Elqadi M., Nasereddin A. Estrogen receptor 1 gene polymorphisms (PvuII and XbaI) are associated with type 2 diabetes in Palestinian women. PeerJ. 2019;7:e7164. doi: 10.7717/peerj.7164. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 211.Speer G., Cseh K., Winkler G., Vargha P., Braun E., Takács I., Lakatos P. Vitamin D and estrogen receptor gene polymorphisms in type 2 diabetes mellitus and in android type obesity. Eur. J. Endocrinol. 2001;144:385–389. doi: 10.1530/eje.0.1440385. [DOI] [PubMed] [Google Scholar]
- 212.Motawi T.M., El-Rehany M.A., Rizk S.M., Ramzy M.M., El-Roby D.M. Genetic polymorphism of estrogen receptor alpha gene in Egyptian women with type II diabetes mellitus. Meta Gene. 2015;6:36–41. doi: 10.1016/j.mgene.2015.08.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 213.Linnér C., Svartberg J., Giwercman A., Giwercman Y.L. Estrogen receptor alpha single nucleotide polymorphism as predictor of diabetes type 2 risk in hypogonadal men. Aging Male. 2013;16:52–57. doi: 10.3109/13685538.2013.772134. [DOI] [PubMed] [Google Scholar]
- 214.Oliveira-Paula G.H., Lacchini R., Tanus-Santos J.E. Endothelial nitric oxide synthase: From biochemistry and gene structure to clinical implications of NOS3 polymorphisms. Gene. 2016;575:584–599. doi: 10.1016/j.gene.2015.09.061. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 215.Pieper G. Enhanced, unaltered and impaired nitric oxide-mediated endothelium-dependent relaxation in experimental diabetes mellitus: Importance of disease duration. Diabetologia. 1999;42:204–213. doi: 10.1007/s001250051140. [DOI] [PubMed] [Google Scholar]
- 216.Shoukry A., Shalaby S.M., Abdelazim S., Abdelazim M., Ramadan A., Ismail M.I., Fouad M. Endothelial nitric oxide synthase gene polymorphisms and the risk of diabetic nephropathy in type 2 diabetes mellitus. Genet. Test. Mol. Biomark. 2012;16:574–579. doi: 10.1089/gtmb.2011.0218. [DOI] [PubMed] [Google Scholar]
- 217.Olesen J. Nitric oxide-related drag targets in headache. Neurotherapeutics. 2010;7:183–190. doi: 10.1016/j.nurt.2010.03.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 218.Paolisso G., Tagliamonte M., Rizzo M., Giugliano D. Advancing age and insulin resistance: New facts about an ancient history. Eur. J. Clin. Investig. 1999;29:758–769. doi: 10.1046/j.1365-2362.1999.00522.x. [DOI] [PubMed] [Google Scholar]
- 219.Barbieri M., Bonafé M., Marfella R., Ragno E., Giugliano D., Franceschi C., Paolisso G. LL-paraoxonase genotype is associated with a more severe degree of homeostasis model assessment IR in healthy subjects. J. Clin. Endocrinol. Metab. 2002;87:222–225. doi: 10.1210/jcem.87.1.8183. [DOI] [PubMed] [Google Scholar]
- 220.Abbott C.A., Mackness M.I., Kumar S., Boulton A.J., Durrington P.N. Serum paraoxonase activity, concentration, and phenotype distribution in diabetes mellitus and its relationship to serum lipids and lipoproteins. Arterioscler. Thromb. Vasc. Biol. 1995;15:1812–1818. doi: 10.1161/01.ATV.15.11.1812. [DOI] [PubMed] [Google Scholar]
- 221.Ikeda Y., Suehiro T., Inoue M., Nakauchi Y., Morita T., Arii K., Ito H., Kumon Y., Hashimoto K. Serum paraoxonase activity and its relationship to diabetic complications in patients with non—Insulin-dependent diabetes mellitus. Metabolism. 1998;47:598–602. doi: 10.1016/S0026-0495(98)90246-3. [DOI] [PubMed] [Google Scholar]
- 222.Guo X., Rotter J.I. Genome-wide association studies. JAMA. 2019;322:1705–1706. doi: 10.1001/jama.2019.16479. [DOI] [PubMed] [Google Scholar]
- 223.Gormley P., Anttila V., Winsvold B.S., Palta P., Esko T., Pers T.H., Farh K.-H., Cuenca-Leon E., Muona M., Furlotte N.A. Meta-analysis of 375,000 individuals identifies 38 susceptibility loci for migraine. Nat. Genet. 2016;48:856–866. doi: 10.1038/ng.3598. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 224.Anttila V., Winsvold B.S., Gormley P., Kurth T., Bettella F., McMahon G., Kallela M., Malik R., de Vries B., Terwindt G., et al. Genome-wide meta-analysis identifies new susceptibility loci for migraine. Nat. Genet. 2013;45:912–917. doi: 10.1038/ng.2676. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 225.Hautakangas H., Winsvold B.S., Ruotsalainen S.E., Bjornsdottir G., Harder A.V.E., Kogelman L.J.A., Thomas L.F., Noordam R., Benner C., Gormley P., et al. Genome-wide analysis of 102,084 migraine cases identifies 123 risk loci and subtype-specific risk alleles. Nat. Genet. 2022;54:152–160. doi: 10.1038/s41588-021-00990-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 226.Mahajan A., Taliun D., Thurner M., Robertson N.R., Torres J.M., Rayner N.W., Payne A.J., Steinthorsdottir V., Scott R.A., Grarup N., et al. Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps. Nat. Genet. 2018;50:1505–1513. doi: 10.1038/s41588-018-0241-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 227.Lagou V., Mägi R., Hottenga J.-J., Grallert H., Perry J.R., Bouatia-Naji N., Marullo L., Rybin D., Jansen R., Min J.L. Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability. Nat. Commun. 2021;12:24. doi: 10.1038/s41467-020-19366-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 228.Mahajan A., Spracklen C.N., Zhang W., Ng M.C.Y., Petty L.E., Kitajima H., Yu G.Z., Rüeger S., Speidel L., Kim Y.J., et al. Trans-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation. medRxiv. 2020 doi: 10.1101/2020.09.22.20198937. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 229.Vujkovic M., Keaton J.M., Lynch J.A., Miller D.R., Zhou J., Tcheandjieu C., Huffman J.E., Assimes T.L., Lorenz K., Zhu X., et al. Discovery of 318 new risk loci for type 2 diabetes and related vascular outcomes among 1.4 million participants in a multi-ancestry meta-analysis. Nat. Genet. 2020;52:680–691. doi: 10.1038/s41588-020-0637-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 230.Saxena R., Voight B.F., Lyssenko V., Burtt N.P., de Bakker P.I., Chen H., Roix J.J., Kathiresan S., Hirschhorn J.N., Daly M.J. Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science. 2007;316:1331–1336. doi: 10.1126/science.1142358. [DOI] [PubMed] [Google Scholar]
- 231.Scott L.J., Mohlke K.L., Bonnycastle L.L., Willer C.J., Li Y., Duren W.L., Erdos M.R., Stringham H.M., Chines P.S., Jackson A.U. A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants. Science. 2007;316:1341–1345. doi: 10.1126/science.1142382. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 232.Morris A.P., Voight B.F., Teslovich T.M., Ferreira T., Segrè A.V., Steinthorsdottir V., Strawbridge R.J., Khan H., Grallert H., Mahajan A., et al. Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Nat. Genet. 2012;44:981–990. doi: 10.1038/ng.2383. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 233.Mahajan A., Wessel J., Willems S.M., Zhao W., Robertson N.R., Chu A.Y., Gan W., Kitajima H., Taliun D., Rayner N.W., et al. Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes. Nat. Genet. 2018;50:559–571. doi: 10.1038/s41588-018-0084-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 234.Voight B.F., Scott L.J., Steinthorsdottir V., Morris A.P., Dina C., Welch R.P., Zeggini E., Huth C., Aulchenko Y.S., Thorleifsson G., et al. Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis. Nat. Genet. 2010;42:579–589. doi: 10.1038/ng.609. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 235.Anttila V., Stefansson H., Kallela M., Todt U., Terwindt G.M., Calafato M.S., Nyholt D.R., Dimas A.S., Freilinger T., Müller-Myhsok B., et al. Genome-wide association study of migraine implicates a common susceptibility variant on 8q22.1. Nat. Genet. 2010;42:869–873. doi: 10.1038/ng.652. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 236.Chasman D.I., Schürks M., Anttila V., de Vries B., Schminke U., Launer L.J., Terwindt G.M., van den Maagdenberg A.M., Fendrich K., Völzke H. Genome-wide association study reveals three susceptibility loci for common migraine in the general population. Nat. Genet. 2011;43:695. doi: 10.1038/ng.856. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 237.Gray A.L.H., Antevska A., Link B.A., Bogin B., Burke S.J., Dupuy S.D., Collier J.J., Levine Z.A., Karlstad M.D., Do T.D. α-CGRP disrupts amylin fibrillization and regulates insulin secretion: Implications on diabetes and migraine. Chem. Sci. 2021;12:5853–5864. doi: 10.1039/D1SC01167G. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 238.Siva Z.O., Uluduz D., Keskin F.E., Erenler F., Balcı H., Uygunoğlu U., Saip S., Göksan B., Siva A. Determinants of glucose metabolism and the role of NPY in the progression of insulin resistance in chronic migraine. Cephalalgia. 2018;38:1773–1781. doi: 10.1177/0333102417748928. [DOI] [PubMed] [Google Scholar]
- 239.Ward-Caviness C.K., Neas L.M., Blach C., Haynes C.S., LaRocque-Abramson K., Grass E., Dowdy E., Devlin R.B., Diaz-Sanchez D., Cascio W.E. Genetic variants in the bone morphogenic protein gene family modify the association between residential exposure to traffic and peripheral arterial disease. PLoS ONE. 2016;11:e0152670. doi: 10.1371/journal.pone.0152670. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 240.Nieto-Vazquez I., Fernández-Veledo S., Krämer D.K., Vila-Bedmar R., Garcia-Guerra L., Lorenzo M. Insulin resistance associated to obesity: The link TNF-alpha. Arch. Physiol. Biochem. 2008;114:183–194. doi: 10.1080/13813450802181047. [DOI] [PubMed] [Google Scholar]
- 241.Syreeni A., Sandholm N., Sidore C., Cucca F., Haukka J., Harjutsalo V., Groop P.H. Genome-wide search for genes affecting the age at diagnosis of type 1 diabetes. Intern. Med. 2021;289:662–674. doi: 10.1111/joim.13187. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 242.Tsai C.-K., Liang C.-S., Lin G.-Y., Tsai C.-L., Lee J.-T., Sung Y.-F., Lin Y.-K., Hung K.-S., Chen W.-L., Yang F.-C. Identifying genetic variants for age of migraine onset in a Han Chinese population in Taiwan. J. Headache Pain. 2021;22:89. doi: 10.1186/s10194-021-01301-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 243.Al-Hassany L., Haas J., Piccininni M., Kurth T., Maassen Van Den Brink A., Rohmann J.L. Giving Researchers a Headache—Sex and Gender Differences in Migraine. Front. Neurol. 2020;11:549038. doi: 10.3389/fneur.2020.549038. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 244.de Vries B., Anttila V., Freilinger T., Wessman M., Kaunisto M.A., Kallela M., Artto V., Vijfhuizen L.S., Göbel H., Dichgans M., et al. Systematic re-evaluation of genes from candidate gene association studies in migraine using a large genome-wide association data set. Cephalalgia. 2016;36:604–614. doi: 10.1177/0333102414566820. [DOI] [PubMed] [Google Scholar]
- 245.Cano-Gamez E., Trynka G. From GWAS to Function: Using Functional Genomics to Identify the Mechanisms Underlying Complex Diseases. Front. Genet. 2020;11:424. doi: 10.3389/fgene.2020.00424. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
No new data were generated or analysed in this study. Data sharing was not applicable.