DIABETES, OBESITY AND DIAGNOSIS OF AMYOTROPHIC LATERAL SCLEROSIS: A POPULATION-BASED STUDY

Abstract

Importance

Although prior studies have suggested a role of cardiometabolic health on pathogenesis of amyotrophic lateral sclerosis (ALS), the association with diabetes has not been widely examined.

Objective

Amyotrophic lateral sclerosis is the most common motor neuron disorder. Several vascular risk factors have been associated with decreased risk for ALS. Although diabetes is also a risk factor for vascular disease, the few studies of diabetes and ALS have been inconsistent. We examined the association between diabetes and obesity, each identified through ICD-8 or 10 codes in a hospital registry, and ALS using data from the Danish National Registers.

Design and Setting

Population-based nested case-control study.

Participants

3,650 Danish residents diagnosed with ALS between 1982 and 2009, and 365,000 controls (100 for each ALS case), matched on age and sex.

Main Outcome Measure

Adjusted odds ratio (OR) for ALS associated with diabetes or obesity diagnoses at least three years prior to the ALS diagnosis date.

Results

When considering diabetes and our obesity indicator together, the estimated OR for ALS was 0.61 (95%CI: 0.46–0.80) for diabetes and 0.81 (95%CI: 0.57–1.16) for obesity. We observed no effect modification on the association with diabetes by gender, but a significant modification by age at first diabetes or age at ALS, with the protective association stronger with increasing age, consistent with different associations by diabetes type.

Conclusions and Relevance

We conducted a nationwide study to investigate the association between diabetes and ALS diagnosis. Our findings are in agreement with previous reports of a protective association between vascular risk factors and ALS, and suggest type 2 diabetes, but not type 1, is protective for ALS.

Introduction

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease, characterized by progressive degeneration of the upper and lower motor neurons,¹ with approximately half of the patients dying within 3 years of onset.² The ALS incidence rate is between 1.5 and 2.5 per 100,000 persons per year,³ with this rate increasing with increasing age, although incidence appears to decrease after 80 years of age.⁴ Although a recent study found ALS heritability to be higher than previously reported,⁵ the etiology of ALS pathogenesis is not completely understood, with environmental contributions likely contributing to the disease.² Because of the rarity of the disease, large scale cohort studies are difficult and so have not commonly been used to investigate potential risk factors, but the need for more such studies has been recognized.⁶

Recent reports have found a protective association between vascular risk factors, such as obesity or higher body mass index (BMI),⁷ higher cholesterol⁸ and hyperlipidemia^9,10 and ALS, and ALS survival.^11–14 These findings, coupled with reports that energy metabolism and homeostasis are also involved in ALS pathogenesis,⁹ suggest that the pathophysiology of ALS is multifactorial.¹⁵ Patients with type 2 diabetes have, on average, higher BMI, elevated blood lipid levels,¹⁶ and defective energy metabolism.¹⁷ Diabetes, moreover, is a metabolic disorder with increasing prevalence globally.¹⁸ The association, however, between diabetes and ALS has not been widely explored. Recently a case-control study in the Netherlands reported a protective, albeit insignificant, association between diabetes and ALS onset.⁸

To assess the potential link between diabetes and risk of ALS, we examined the association between hospital admissions for diabetes and ALS diagnosis between 1982 and 2009 in the entire Danish population. We used data obtained from the Danish Registers system, through which details of all Danish residents can be linked.¹⁹

Methods

Data Collection

Data were obtained from the Danish Registers system, through which details on e.g. demographics and certain health outcomes of all approximately 6 million Danish residents can be linked based on a 10-digit unique personal identifier. The Danish National Patient Register (NPR) was established in 1977 and is a comprehensive patient register, including nationwide clinical and administrative records for all somatic inpatient data. Since 1995 outpatient data have also been included in the NPR,²⁰ and are considered in our analyses.

ALS Case Ascertainment

We identified ALS cases based on their International Classification of Diseases (ICD; World Health Organization) discharge diagnoses, i.e. ICD-8 348.0 (ALS) until 1993 and ICD-10 G12.2 (Motor Neuron Disease) thereafter. As the diagnosis date (index date) we used the date of the first relevant code. We only included cases who were at least 20 years old when diagnosed and we restricted analyses to cases identified after 1982, to avoid inclusion of prevalent cases in the early years of the NPR. In a validation substudy, we obtained 173 medical records for ALS cases identified through the NPR. Of these, only 13 had no ALS (7.5%). The estimated PPV, including the clinically suspect ALS cases was 0.93 (95%CI: 0.88–0.96).²¹

Control Selection

Controls were selected through the Danish Civil Registration System, which was established in 1968 and includes administrative records (e.g date and place of birth, vital status and history of civil status and addresses) on all persons living in Denmark, and records are kept even when a person dies or emigrates.19 We selected 100 controls for each identified case, alive at the time of the matched case’s ALS diagnosis (the index date) and individually matched on sex and year of birth.

Diabetes Ascertainment

Diabetes is a disease occurring either due to insulin deficiency or a decreased responsiveness to insulin. Type 1 diabetes (formerly called juvenile or insulin-dependent), in most cases of autoimmune etiology, is associated with complete or almost complete insulin absence. Conversely, type 2 diabetes (non-insulin-dependent) is characterized by insulin resistance and occurs later in life as a syndrome of mainly overweight adults.²² We identified diabetes cases based on hospital discharge ICD codes for type 1 and type 2 diabetes in the NPR starting in 1977. Specifically, we used ICD-8 codes 249 and 250, respectively, and ICD-10 codes E10 and E11, respectively. Identification of diabetes patients using hospital data has been found to be highly reliable,²³ but misclassification between type 1 and 2 diabetes is likely,²⁴ and a complete classification by type is not possible.²⁵ This is also borne out in our own data, in which we found 74% of those with type 1 diabetes to also have a code for type 2. We, therefore, did not conduct separate analyses for type 1 and type 2 diabetes as distinguished by the ICD codes.

Our main analysis only considered diabetes discharges that occurred at least three years prior to the index date, to minimize the chance that any observed association with diabetes could be due to the effects of underlying, but not yet diagnosed, ALS. To assess the robustness of our results, we repeated our analyses using only diabetes discharges that occurred at least five and seven years prior to the index date.

Obesity and Lipid Metabolism Disorders

We used hospital discharge data to identify patients that had a diagnosis of obesity and lipid metabolism. Specifically, we considered obesity admissions using the ICD-8 code 277.99 and the ICD-10 codes E65.0–E66.9.²⁶ We refer to this throughout the paper as obesity for short hand, but it should be noted that this is not based on a BMI>30, the typical definition of obesity, but most likely reflects a much more elevated BMI. We also obtained hyperlipidemia and hypercholesterolemia data from the NPR (ICD-8: 279.00 and ICD-10: E78.0E78.5). As for diabetes, our main analyses used discharges that occurred at least three years prior to the index date.

Covariates

We additionally considered marital status (non-married, married, divorced, widowed), residence region at the index date (Copenhagen, i.e. the capital, Copenhagen suburbs, other large cities, provincial towns, rural areas, Greenland and unknown), and socio-economic status (SES) in our analyses. We coded SES as the highest level attained by either the subject or their spouse based on their job title. Job titles were categorized in five groups, according to the Danish Institute of Social Sciences, which reasonably captures SES variation in Denmark.²⁷ Group 1 includes e.g. corporate managers and subjects in academia; group 2 includes e.g. proprietors, managers of small businesses and teachers; group 3 e.g. includes technicians and nurses; group 4 includes skilled workers; and group 5 includes unskilled workers. We included a separate group for subjects with unknown job titles.

The NPR does not include data on potential individual-level confounders, such as smoking. We, therefore, used chronic obstructive pulmonary disease (COPD) codes (ICD-8:490–493, 518 and ICD-10: J40–J47), at least one year prior to the index date, as an indicator for smoking. In developed countries up to 70% of COPD cases are among tobacco smokers,²⁸ and is, thus, recognized as an indicator for smoking.

Data Analysis

For both diabetes and obesity, we ran conditional logistic regressions, with strata defined by the 1:100 case–control sets, adjusting for SES. We also ran models including COPD, marital status and region of residence at the index date as covariates. Finally, we considered obesity and diabetes together in a model and assessed the association with diabetes in models stratified by obesity levels.

We also assessed potential effect modification by sex and age. For the effect modification, we included an interaction term between our exposure variable (diabetes or obesity) and sex or age in separate models, adjusting for SES, and examined the statistical significance of the interaction term at the α=0.05 level.

Since misclassification in hospital diagnoses for type 1 and 2 diabetes is likely,^24,25 in an effort to separate potentially different effects, we attempted to separate types of diabetes based on the age at first mention of diabetes in the hospital registers. Those with diabetes onset at younger ages are more likely to have type 1 diabetes. We, therefore, conducted analyses considering separately diabetes with early and late first hospital discharge codes. We used a lower end cutoff of 40 (the decade closest to, but lower than, the first decile of the age distribution at first diabetes-related admission) and then also considered different cutoffs at older ages in 5-year increments.

This study was determined to be exempt by the HSPH IRB and was approved by the Danish Data Protection Agency. All statistical analyses were conducted using the R Statistical Software, version 3.0.3 (Foundation for Statistical Computing, Vienna, Austria).

Results

We identified 3,650 ALS cases in the NPR between 1982 and 2009 that satisfied our inclusion criteria. The mean age at diagnosis was 65.4 (SD = 11.6) years and 46.5% of all cases were female. The distributions of the SES groups, marital status, region of residence, obesity and COPD status are presented in Table 1 by sex and diabetes status.

Table 1.

Distribution of SES, marital status, region, obesity and COPD diagnoses by sex and diabetes status, among controls.

	Females				Males
	Diabetes		No Diabetes		Diabetes		No Diabetes
	N	(%)	N	(%)	N	(%)	N	(%)
Socio-Economic Status
Group 1 (high)	229	6.0	15,158	9.1	451	8.3	19,635	10.3
Group 2	270	7.1	17,899	10.8	549	10.1	21,609	11.4
Group 3	546	14.3	28,854	17.4	936	17.3	35,659	18.8
Group 4	923	24.1	42,172	25.4	1,563	28.9	54,722	28.8
Group 5 (low)	1,056	27.6	32,293	19.5	1,364	25.2	38,262	20.1
Unknown job title	802	21.0	29,398	17.7	550	10.2	20,100	10.6
Marital Status
Non-married	229	6.0	10,964	6.6	547	10.1	17,927	9.4
Married	1,126	29.4	56,063	33.8	3,135	57.9	115,704	60.9
Divorced	510	13.3	18,830	11.4	745	13.8	19,849	10.4
Widowed	1,961	51.3	79,917	48.2	986	18.2	36,507	19.2
Region of Residence at Diagnosis/Index Date
Copenhagen (Capital)	479	12.5	21,741	13.1	656	12.1	19,989	105
Copenhagen suburbs	713	18.6	35,804	21.6	1,235	22.8	40,980	21.6
Other cities (Aarhus, Odense)	474	12.4	18,816	11.4	642	11.9	20,518	10.8
Provincial towns	1,536	40.1	63,329	38.2	1,979	36.6	76,282	40.2
Rural areas	623	16.3	25,043	15.1	899	16.6	30,434	16.0
Greenland	0	0.0	598	0.4	1	0.0	1,029	0.5
Unknown	1	0.0	441	0.3	1	0.0	755	0.4
Obesity Hospital Discharge
No	3,066	80.1	163,766	98.8	4,730	87.4	188,933	99.4
Yes	760	19.9	2,008	1.2	683	12.6	1054	0.6
COPD
No	3,454	90.3	159,289	96.1	4,880	90.2	182,482	96.0
Yes	372	9.7	6,485	3.9	533	9.8	7505	4.0

Using NPR records, we identified 9,294 subjects with diabetes at least 3 years prior to the index date (date of ALS diagnosis or the same date for the matched controls) 55 of which were subsequently diagnosed with ALS. The average age of the first diabetes-related diagnosis was 59.7 (SD = 12.1) and there was no significant difference between cases and controls (p-value = 0.07). Among ALS cases with diabetes, the first diabetes-related admission occurred, on average, 9.8 (SD = 6.1) years before the ALS diagnosis.

We observed a strong protective association between prior diabetes-related admissions and ALS. The results are presented in Table 2. Adjusting for SES, marital status, region of residence or prior COPD admissions did not change the effect estimates, nor did adjusting for our obesity indicator. The ORs were similar when excluding diabetes in the 5 or 7 years before the index date (OR = 0.66; 95%CI: 0.50–0.88 and 0.69; 95%CI: 0.50–0.96, respectively).

Table 2.

Effect estimates (OR) and 95% confidence intervals for any diabetes or obesity admission at least 3 years prior to ALS.

	Cases	Controls	OR (95% CI)
			Unadjusted	Adjusted†	Mutually Adjusted‡
No Diabetes	3,595	355,761		ref
Diabetes	55	9,239	0.59 (0.45–0.77)	0.59 (0.45–0.77)	0.61 (0.46–0.80)
No Diabetes	3,619	360,495		ref
Diabetes	31	4,505	0.69 (0.48–0.98)	0.72 (0.50–1.02)	0.81 (0.57–1.16)

^†Adjusted for SES, prior COPD, marital status and residence at ALS diagnosis

^‡Same as adjusted, with diabetes and obesity simultaneously included in the model

We identified 4,536 subjects with a hospital record for obesity at least three years prior to the index date. Effect estimates for obesity in unadjusted models or adjusting for SES, COPD status, marital status, and residence at diagnosis were similar to those for diabetes, but when diabetes was included in the model the association was weakened and was no longer significant (Table 2). Further, we observed no effect modification by diabetes (p-value = 0.99). We identified 4,168 subjects with a discharge for either hyperlipidemia or hypercholesterolemia. We observed no association between these and ALS.

We found no evidence for effect modification by sex of either the diabetes (p-value = 0.84) or obesity (p-value = 0.72) association. We also found no effect modification by age at ALS diagnosis of the association with obesity (p-value = 0.42). Conversely, a significant effect modification by age at ALS on the association between diabetes and ALS was observed (p value = 0.012), with lower effect estimates observed at higher ages. Specifically, the effect of diabetes on ALS was increased until age 50, although this did not quite reach statistical significance, and became protective at older ages and at ages ≥61 this became statistically significant (Figure 1).

Figure 1.

Adjusted ORs (95%CI) for diabetes, by age at ALS onset

We also found a significant effect modification by age at first diabetes diagnosis, as a proxy to separate between type 1 and type 2 diabetes (Figure 2). The distribution of age at first diabetes-related diagnosis is presented in eFigure 1. When the cutoff for age at diabetes was 40 years old, the difference in effect estimates for diabetes among those older and younger than the cutoff was significant (p-value = 0.002), with a significantly protective association among subjects that were older than 40 years at first diabetes-related diagnosis and harmful effects for subjects that were younger than 40 years old, although the increased OR did not reach statistical significance (p-value = 0.14). For all examined cutoffs, the associations in the category of older age at diabetes diagnosis remained robust and similar to that in the main analysis. With decreasing cutoff age, however, we observed an upward trend in the association with diabetes among those in the younger age group.

Figure 2.

Adjusted ORs (95%CI) for association between diabetes and ALS, by age at first diabetes-related admission. For each of the seven age cutoffs presented in the x axis (40 to 70 by 5 years) we conducted a separate analysis for each cut-off age comparing those with an age at first diabetes-related diagnosis before (circles) and at or above (triangles) the cut-off age to those without a diabetes diagnosis

Discussion

We conducted a retrospective population-based study to examine the association between diabetes- and obesity-related hospital admissions and risk of ALS diagnosis. When including both in the same model, we observed a significantly protective association with diabetes, but not obesity, on risk of ALS. As we noted, however, a hospital discharge code for obesity likely reflects much more severe obesity than the typical definition of obesity as a BMI>30. The association with diabetes was modified by both age at ALS diagnosis and age at diabetes diagnosis, with older age at time of diagnosis for either disease associated with lower risk for ALS. Both earlier age at ALS and earlier age at first diabetes increase the likelihood that the diabetes is type 1. These results, thus, may suggest that the protective association is with type 2 diabetes, but not type 1, which may have the opposite association, i.e. an increased risk of ALS.

The association between diabetes and ALS has not been widely examined, with inconsistent findings initially.²⁹ A recent case-control study in the Netherlands reported a protective association that did not quite reach statistical significance; the use of self-reported diabetes diagnosis could have contributed to the attenuated the association.⁸ Our results, however, are consistent with a recent study in Sweden that reported an OR = 0.66 (95%CI: 0.45–0.80) for diabetes at least 3 years prior to ALS diagnosis.³⁰

Previous studies have found a protective association between vascular risk factors and ALS, and that obesity was uncommon among ALS patients.³¹ Scarmeas et al.³² found that subjects who had always been slim were at a significantly higher risk for ALS. O’Reilly et al.⁷ reported that ALS rates were significantly lower among obese subjects (RR = 0.73; 95%CI: 0.55–0.96). While the reasons for this association remain unclear, the protective association between higher BMI and ALS is consistently observed,^7,32,33 which has been suggested to be related to hypermetabolism that is also often observed with ALS.^9,15 Hyperlipidemia and elevated cholesterol levels have also been associated with lower ALS risk.^8,10,31

The underlying pathophysiological mechanisms of ALS are likely multifactorial, with defective energy metabolism and homeostasis likely playing an important role in pathogenesis.^9,15 Overweight and obese people are at higher risk of type 2 diabetes,³⁴ and those with type 2 diabetes are at higher risk for elevated cholesterol, hyperlipidemia and vascular disease.³⁵ Our findings, thus, are consistent with prior reports suggesting an inverse association between cardiometabolic health and ALS. In addition, higher levels of physical activity have been associated with increased risk of ALS,³² and are also generally associated with lower BMI, lower risk of diabetes, and generally better cardiometabolic health. It is possible that associations with BMI and diabetes are simply the result of their own association with physical activity. On the other hand, effects of physical activity on cardiometabolic health in general could be the reason for the association between physical activity and ALS. Studies with detailed data on all of these factors, including relevant timing, will be critical for sorting out the inter-relationships between these variables and risk of ALS. We also cannot rule out the possibility that genetic risk factors that give rise to ALS are protective for cardiometabolic disorders and, specifically, diabetes.

If the protective association with diabetes results from some causal association with an aspect of diabetes, rather than as a result of correlation with something else, then several possibilities could be surmised. Diabetes medications could be protective. A limited literature on a few compounds to date does not suggest such an effect,^36,37 but not all diabetic medications have been examined. Excitotoxicity or uric acid could also play a role. Glutamate excitotoxicity, a consequence of extracellular glutamate accumulation,³⁸ has been implicated in ALS pathogenesis.^39,40 The hyperglycemia that is characteristic of untreated type 2 diabetic subjects³⁵ (only 14–17% of type 2 diabetic subjects are treated with insulin⁴¹), through enhancing glutamate uptake,⁴² could protect against excitotoxicity. Diabetes has also been associated with high concentrations of uric acid,⁴³ which has been associated with reduced incidence of other neurodegenerative diseases,^44,45 and prolonged survival in ALS.⁴⁶

We found that the association between diabetes and ALS varied by age at ALS, trending towards a harmful association with earlier age at ALS. This could reflect different associations between type 1 vs. type 2 diabetes and ALS since earlier age at ALS would also imply earlier age at diabetes prior to ALS, which would therefore be more likely to be type 1 diabetes. However, ALS at earlier ages is likely more commonly genetic in origin, for example the presence of C9orf72 is more common among younger ALS patients.^47–49 Therefore, the variation by age at ALS could also suggest a different relation between diabetes and ALS when the ALS has a stronger genetic influence. We also found variation in the association with diabetes by the age at diabetes. This more strongly suggests a possible difference in the relation of type 1 and type 2 diabetes with ALS since it did not restrict the age at ALS. The trend towards an increased risk of ALS following type 1 diabetes is consistent with previous findings,^30,50 but more conclusive evidence will require data with more certain determination of diabetes type than what is available in the NPR.

An opposite association between type 1 diabetes and ALS could be expected based on uric acid or blood glucose. In contrast to those with type 2 diabetes, those with type 1 diabetes have lower uric acid levels,⁵¹ and are more prone to hypoglycemic excursions because they are all medicated and at risk for insulin treatment induced hypoglycemia.^52,53 Furthermore, most subjects with type 1 diabetes have type 1A diabetes, i.e. of autoimmune etiology,^35,53 and are at higher risk for presenting with additional autoimmune disorders.⁵⁴ Autoimmune mechanisms have also been implicated in ALS.^50,55

Neither outcome nor exposure misclassification can be excluded from our analysis. Both ALS²¹ and diabetes-related²³ hospital discharges, however, have been found to be highly reliable. Furthermore, using hospital diagnoses, we are likely only capturing the most severe cases of diabetes, obesity and disorders of lipid metabolism. Diabetics have reduced survival compared to non-diabetics so the possibility that survival differences could affect our results must be considered. However, if this was biasing our findings, we would likely expect to see stronger bias with diabetes that occurred earlier relative to ALS. But analyses restricting to diabetes at least 5 or 7 years prior to ALS showed similar results as for, or if anything slightly higher than, diabetes at least 3 years prior to ALS.

An additional limitation of our study is the lack of individual-level information on life-style factors, such as smoking. In Denmark, smoking has been shown to be very highly correlated with occupational status,⁵⁶ thus adjusting for occupation-based SES would partially also adjust for smoking status. More importantly, however, while the association between smoking and ALS is not completely consistent,⁵⁷ if anything it appears associated with an increased risk of ALS. Since smoking is a risk factor for diabetes, this would not account for a protective association.

In conclusion, we conducted a nationwide, population-based study and observed an overall protective association between diabetes and ALS diagnosis, with the suggestion that type 2 diabetes is protective and type 1 a risk factor. Although the mechanisms underlying this association remain unclear, our findings focus further attention on the role of energy metabolism in ALS pathogenesis.