Abstract
Background:
Prediabetes represents a transitional state in glucose metabolism with an increasing global and national prevalence, particularly in India. Recent evidence suggests that both thyroid dysfunction and chronic low-grade inflammation may play pivotal roles in the progression of prediabetes to overt Type 2 diabetes mellitus (T2DM). Thyroid hormones regulate glucose metabolism, while inflammatory markers such as white blood cell (WBC) count and high-sensitivity C-reactive protein (hs-CRP) are indicators of systemic inflammation often elevated in metabolic disorders.
Objectives:
This study aimed to evaluate thyroid function and inflammatory markers in prediabetic individuals, assess the prevalence of thyroid dysfunction, and analyze the correlation between thyroid parameters and inflammatory markers.
Materials and Methods:
A case–control study was conducted at a tertiary care center in Western Maharashtra, enrolling 200 participants (130 prediabetics and 70 age- and sex-matched controls). Thyroid function tests (thyroid-stimulating hormone [TSH], Total T3 and T4), thyroid antibodies, WBC count, and hs-CRP levels were analyzed and compared between groups. Statistical analyses were conducted to evaluate correlations and significance.
Results:
Thyroid dysfunction, particularly elevated TSH levels, was more prevalent in prediabetic individuals compared to controls. A significant proportion of prediabetic patients exhibited elevated hs-CRP and WBC counts, indicating underlying low-grade inflammation. A positive correlation was observed between TSH levels and inflammatory markers, suggesting a possible link between early thyroid dysfunction and systemic inflammation in prediabetic states.
Conclusion:
Prediabetes is associated with both subclinical thyroid abnormalities and elevated inflammatory markers, highlighting the need for comprehensive metabolic screening in this population. Early identification and management of thyroid and inflammatory dysfunction may offer an opportunity to delay or prevent the onset of T2DM and its complications.
Keywords: High-sensitivity C-reactive protein, inflammation, subclinical hypothyroidism, thyroid function tests, type 2 diabetes mellitus risk, white blood cell count
Résumé
Contexte:
Le prédiabète représente un état transitoire du métabolisme du glucose, avec une prévalence croissante tant au niveau mondial qu’à l’échelle nationale, en particulier en Inde. Des preuves récentes suggèrent que le dysfonctionnement thyroïdien ainsi que l’inflammation chronique de bas grade pourraient jouer un rôle clé dans la progression du prédiabète vers un diabète de type 2 (DT2) manifeste. Les hormones thyroïdiennes régulent le métabolisme du glucose, tandis que des marqueurs inflammatoires tels que le nombre de globules blancs (GB) et la protéine C-réactive ultrasensible (hs CRP) sont des indicateurs d’inflammation systémique, souvent élevés dans les troubles métaboliques.
Objectifs:
Cette étude visait à évaluer la fonction thyroïdienne et les marqueurs inflammatoires chez les individus prédiabétiques, à déterminer la prévalence du dysfonctionnement thyroïdien et à analyser la corrélation entre les paramètres thyroïdiens et les marqueurs inflammatoires.
Matériels et Méthodes:
Une étude cas–témoins a été menée dans un centre de soins tertiaires situé dans l’ouest du Maharashtra, incluant 200 participants (130 prédiabétiques et 70 témoins appariés selon l’âge et le sexe). Les tests de la fonction thyroïdienne (hormone stimulant la thyroïde [TSH], T3 et T4 totales), les anticorps thyroïdiens, le nombre de globules blancs et les taux de hs CRP ont été analysés et comparés entre les groupes. Des analyses statistiques ont été réalisées afin d’évaluer les corrélations et la signification des résultats.
Résultats:
Le dysfonctionnement thyroïdien, en particulier l’élévation des taux de TSH, était plus fréquent chez les individus prédiabétiques que chez les témoins. Une proportion significative de patients prédiabétiques présentait des taux élevés de hs CRP et de GB, indiquant une inflammation de bas grade sous-jacente. Une corrélation positive a été observée entre les taux de TSH et les marqueurs inflammatoires, suggérant un lien possible entre un dysfonctionnement thyroïdien précoce et une inflammation systémique dans les états prédiabétiques.
Conclusion:
Le prédiabète est associé à des anomalies thyroïdiennes subcliniques ainsi qu’à une élévation des marqueurs inflammatoires, soulignant la nécessité d’un dépistage métabolique complet chez cette population. L’identification et la prise en charge précoces des dysfonctionnements thyroïdiens et inflammatoires pourraient offrir une opportunité de retarder ou de prévenir l’apparition du diabète de type 2 et de ses complications.
Mots-clés: Protéine C-réactive ultrasensible, inflammation, hypothyroïdie subclinique, tests de la fonction thyroïdienne, risque de diabète de type 2, numération des globules blancs
INTRODUCTION
Prediabetes represents a critical transitional state in glucose metabolism that precedes type 2 diabetes mellitus (T2DM) development which is characterized by higher than normal blood glucose levels but below diagnostic threshold for diabetes. This metabolic condition has emerged as a significant public health concern, affecting approximately 374 million people worldwide according to the International Diabetes Federation estimate.[1] The burden of prediabetes is particularly noteworthy in India, where rapid urbanization, lifestyle changes, and genetic predisposition have contributed to its increasing prevalence, especially in western regions including Maharashtra.
The relationship between thyroid dysfunction and glucose homeostasis has garnered substantial attention in recent years, as both endocrine systems are intricately connected through multiple biochemical, cellular, and molecular pathways.[2] Thyroid hormones play a crucial role in glucose metabolism, insulin sensitivity, and energy homeostasis, suggesting a potential bidirectional relationship between thyroid dysfunction and prediabetes.[3] Understanding this association becomes particularly relevant in the context of early intervention and prevention strategies for both conditions. Inflammation, now recognized as a key pathophysiological component in metabolic disorders, serves as a crucial link between various metabolic derangements. High sensitivity C-reactive protein (hs-CRP) along with white blood cells (WBCs) count has emerged as reliable markers of systemic inflammation, providing valuable insights into the inflammatory status of individuals with metabolic disorders. These markers have shown promising potential in risk stratification and early detection of metabolic complications, particularly in the context of prediabetes and thyroid dysfunction.[4]
Recent evidence suggests that thyroid dysfunction may precede or accompany prediabetes, potentially sharing common pathophysiological mechanisms involving inflammatory processes.[5] Studies have demonstrated alterations in thyroid function tests (TFT) in individuals with impaired glucose tolerance, with some research indicating that subtle changes in thyroid function might influence the progression from prediabetes to overt diabetes. The role of inflammatory markers in this context provides an additional dimension to understanding the pathogenesis and progression of both conditions.[6]
Thyroid hormones, particularly triiodothyronine (T3) and thyroxine (T4) exert significant effects on glucose metabolism through various mechanisms.[7] These include modulation of hepatic glucose production, glucose uptake in peripheral tissues, and insulin sensitivity. Thyroid-stimulating hormone (TSH) levels, even its value within the reference range are associated with insulin resistance and metabolic syndrome components. Understanding these associations in prediabetic individuals could provide valuable insights into early intervention strategies and risk assessment.[8] The inflammatory component in prediabetes, as measured by WBC count and hs-CRP, represents a crucial aspect of metabolic dysfunction. Chronic low-grade inflammation has been implicated in both insulin resistance and thyroid dysfunction.[9] Elevated levels of inflammatory markers are associated with an increased risk of its advancement to T2DM and various metabolic complications. The relationship between these inflammatory markers and thyroid function in prediabetic individuals, however, requires further investigation, particularly in the Indian Region.[10]
The selection of WBC count and hs-CRP as inflammatory markers in this study are based on their clinical utility, accessibility, and established role in metabolic disorders. WBC count, a routine laboratory parameter, provides valuable information about systemic inflammation and is associated with insulin resistance and metabolic syndrome. Hs-CRP, a more sensitive marker of inflammation, has demonstrated significant associations with cardiovascular risk and metabolic disorders, making it particularly relevant in settings of prediabetes and thyroid dysfunction. This study aims to bridge several important gaps in current knowledge. First, it seeks to establish the prevalence and patterns of thyroid dysfunction in prediabetic individuals in Western Maharashtra. Second, it aims to investigate the association between TFTs and inflammatory markers in this population. Finally, it intends to explore whether these parameters can serve as predictive markers for metabolic complications in prediabetes.
MATERIALS AND METHODS
Place of study
The study was conducted on patients recruited from Dr D. Y. Patil Medical College and Hospital, Pimpri, Pune.
Study design
This was a case–control study.
Sample size
The sample size for the study is 200. gWith a 2:1 case-to-control ratio, the study included 130 cases and 70 controls.[11]
Duration of study
The study was carried out between October 2023 and February 2025.
Selection criteria
Inclusion criteria
Age >18 years
-
According to the American Diabetes Association (ADA) criteria
Patients with glycated hemoglobin (HbA1c) of 5.7–6.4
Patients with fasting blood glucose levels of 100–125 mg/dL and 2 h oral glucose tolerance test levels of 140–199 mg/dL.
Exclusion criteria
Age <18 years
Patients diagnosed with Type 1 and T2DM
Patients on lithium, selective serotonin reuptake inhibitors, amiodarone, and other drugs affecting TFTs and thyroid status
Pregnant women and critically ill patients (as TFTs are altered in these conditions).
Method of study
An informed written consent was obtained from all study participants at the outset. Detailed clinical history of illness was taken; physical examination and radiological examination were performed on cases and control. By chemiluminescent microparticle immunoassay using total t3 Reagent kit TFT, total T4 and T3 levels, anti-Thyroid Peroxidase Antibody (TPO) antibodies and anti-Thyroglobulin (TG) antibodies will be assessed. HbA1c concentration was measured by the high-performance liquid chromatography method. Hs-CRP was measured using hs-CRP kit. All routine and specific tests such as complete blood count,Serum lactate, liver and kidney function tests, Serum lactate were conducted to rule out critical illness. Data were collected manually through a questionnaire and analyzed to see the relation between thyroid dysfunction and prediabetes patients. The estimated glomerular filtration rate will be calculated using the Chronic Kidney Disease Epidemiology Collaboration Creatinine Cystatin Equation. 177.6 × (serum creatinine [ME]) −0.05 × (serum cystatin C [ME] −0.57 × age-0.2).[12] The normal reference values for key metabolic and thyroid parameters are as follows. According to the ADA, a normal HbA1c level is below 5.7%, indicating healthy long-term glucose control. Fasting blood glucose levels should range between 70 and 99 mg/dL, while 2-h postprandial glucose levels (measured after a meal or during an oral glucose tolerance test) should be below 140 mg/dL.[13] Regarding thyroid function, the normal range for total triiodothyronine (T3) is typically 0.64–1.52 ng/mL, and for total thyroxine (T4), it is 4.87–11.72 μg/dL. TSH levels are considered normal between 0.35 and 4.94 μIU/mL.[14] These values may vary slightly depending on the laboratory and testing method used.
Ethical consideration
We obtained informed written consent from the participants following an explanation to the participants that their participation is voluntary, no incentives will be given, and that they have all the right to refuse participation or answer any questions that are embarrassing or objectionable. We also ensured that the identity of the study participants would not be revealed, and confidentiality would be maintained. Participants have the right to withdraw from the study at any time without affecting their medical care. Ethical approval from institution ethics board was taken (Approval number IESC/PGS/2023/14).
Statistical analysis
The patient data will be entered in an Excel sheet and analyzed using SPSS software. The Statistical Package for the Social Sciences (SPSS), developed by IBM Corporation, is widely used for data management and statistical analysis in research across various fields. Measures of central tendency such as mean, median, and mode will be calculated. Measures of dispersion such as standard deviation (SD) and coefficient of variance will be assessed. The statistical association between categorical variables will be analyzed by the Chi-square test. Statistical differences between means of two groups and how they are related are assessed by student’s t-test.
OBSERVATION AND RESULTS
In this study, the majority of participants belonged to the case group 130 (65%), while 70 (35%) were in the control group. While the majority of participants were females 111 (55.5%), 89 (44.5%) were males. In this study, the mean ± SD of the age, height, weight, body mass index (BMI), and mean waist–hip ratio were 45.97 ± 8.93 years, 165.37 ± 8.15 cm, 73.02 ± 11.41 kg, 26.67 ± 3.27, and 0.97 ± 0.07, respectively, as shown in Table 1.
Table 1.
Anthropometry measurements of patients
| Anthropometry | Mean±SD |
|---|---|
| Age | 45.97±8.93 |
| Height (cm) | 165.37±8.15 |
| Weight (kg) | 73.02±11.41 |
| BMI | 26.67±3.27 |
| Waist hip ratio | 0.97±0.07 |
BMI=Body mass index, SD=Standard deviation
In the study, the mean T3 ± SD was 1.21 ± 0.27, the mean T4 ± SD was 8.25 ± 1.93, and the mean TSH ± SD was 3.42 ± 1.48. The mean ± SD of fasting plasma glucose, postprandial plasma glucose, and HbA1C were 102.70 ± 14.99 mg/dL, 152.73 ± 27.72 mg/dL, and 5.71 ± 0.53, respectively, as shown in Table 2.
Table 2.
Thyroid function tests and plasma glucose levels of patients
| Thyroid and serum glucose | Mean±SD |
|---|---|
| T3 (ng/mL) | 1.21±0.27 |
| T4 (μg/dL) | 8.25±1.93 |
| TSH (μIU/mL) | 3.42±1.48 |
| Fasting plasma glucose (mg/dL) | 102.70±14.99 |
| Postprandial plasma glucose (mg/dL) | 152.73±27.72 |
| HbA1c (%) | 5.71±0.53 |
SD=Standard deviation, TSH=Thyroid stimulating hormone, HbA1c=Glycated hemoglobin, T3=Triiodothyronine, T4=Thyroxine
The complete blood count analysis of patients is mentioned in Table 3 and the parameters are indicating adequate immune response against infections.
Table 3.
Complete blood count analysis of patients
| Blood values | Mean±SD |
|---|---|
| WBC count ×109 L | 11.52±4.88 |
| Basophils | 0.58±0.28 |
| Eosinophils | 3.09±1.28 |
| Monocytes | 7.57±2.44 |
| Lymphocytes | 26.87±8.07 |
| Neutrophils | 62.57±7.17 |
WBC=White blood cell, SD=Standard deviation
In the study, the mean hs-CRP was 3.09 ± 1.55 mg/L, high-density lipoprotein (HDL) was 43.19 ± 7.06 mg/dL, low-density lipoprotein (LDL) was 122.14 ± 20.24 mg/dL, and triglycerides were 180.13 ± 39.19 mg/dL. Mean sodium was 139.82 ± 2.90 mEq/L, potassium was 4.20 ± 0.42 mEq/L, and chloride was 100.10 ± 2.97 mEq/L, as shown in Table 4.
Table 4.
Other markers of patients
| Markers | Mean±SD |
|---|---|
| hs-CRP (mg/L) | 3.09±1.55 |
| HDL (mg/dL) | 43.19±7.06 |
| LDL (mg/dL) | 122.14±20.24 |
| Triglycerides (mg/dL) | 180.13±39.19 |
| Sodium (mEq/L) | 139.82±2.90 |
| Potassium (mEq/L) | 4.20±0.42 |
| Chloride (mEq/L) | 100.10±2.97 |
hs-CRP=High-sensitivity C-reactive protein, LDL=Low-density lipoprotein, HDL=High-density lipoprotein, SD=Standard deviation
In the study, the mean age of cases was 46.43 ± 8.94 years, while that of controls was 45.10 ± 8.93 years (P = 0.316). The mean BMI in cases was significantly higher (27.96 ± 3.08) than in controls (24.25 ± 2.01) (P < 0.01). The mean waist–hip ratio in cases was 1.00 ± 0.06, significantly higher than in controls (0.91 ± 0.06) (P < 0.02), as shown in Table 5.
Table 5.
Comparison of anthropometry measurements between cases and controls
| Anthropometry | Group | n | Mean±SD | t | P |
|---|---|---|---|---|---|
| Age | Case | 130 | 46.43±8.94 | 1.005 | 0.316 |
| Control | 70 | 45.10±8.93 | |||
| BMI | Case | 130 | 27.96±3.08 | 9.081 | <0.01 |
| Control | 70 | 24.25±2.01 | |||
| Waist hip ratio | Case | 130 | 1.00±0.06 | 11.695 | <0.02 |
| Control | 70 | 0.91±0.06 |
BMI=Body mass index, SD=Standard deviation
The mean T3 level was significantly lower in cases (1.11 ± 0.23) compared to controls (1.40 ± 0.25) (P < 0.01). The mean T4 level was considerably lower in cases (7.95 ± 1.80) than in controls (8.81 ± 2.05) (P = 0.003). The mean TSH level was significantly higher in cases (4.21 ± 1.12) than in controls (1.94 ± 0.72) (P < 0.01). The mean WBC count was significantly higher in cases (14.43 ± 3.46) compared to controls (6.12 ± 0.91) (P < 0.02). The mean hs-CRP level was significantly higher in cases (3.93 ± 1.21) compared to controls (1.53 ± 0.64) (P < 0.03). The mean HDL level was significantly lower in cases (40.17 ± 5.99) compared to controls (48.80 ± 5.26) (P < 0.04). The mean LDL level was significantly higher in cases (129.81 ± 19.05) compared to controls (107.89 ± 13.68) (P < 0.05). The mean triglyceride level was considerably higher in cases (201.83 ± 27.32) compared to controls (139.81 ± 22.29) (P < 0.06). In the study, there were no significant differences in sodium (P = 0.877), potassium (P = 0.644), or chloride levels (P = 0.801) between cases and controls, as shown in Table 6.
Table 6.
Comparison of variables between cases and controls
| Variables | Group | n | Mean±SD | t | P |
|---|---|---|---|---|---|
| T3 | Case | 130 | 1.11±0.23 | −8.462 | 0.00000001 |
| Control | 70 | 1.40±0.25 | |||
| T4 | Case | 130 | 7.95±1.80 | −3.061 | 0.0030 |
| Control | 70 | 8.81±2.05 | |||
| TSH | Case | 130 | 4.21±1.12 | 15.349 | 0.0000000001 |
| Control | 70 | 1.94±0.72 | |||
| hs-CRP (mg/L) | Case | 130 | 3.93±1.21 | 15.478 | 0.0000000009 |
| Control | 70 | 1.53±0.64 | |||
| HDL (mg/dL) | Case | 130 | 40.17±5.99 | −10.129 | 0.00000002 |
| Control | 70 | 48.80±5.26 | |||
| LDL (mg/dL) | Case | 130 | 129.81±19.05 | 8.512 | 0.00000005 |
| Control | 70 | 107.89±13.68 | |||
| Triglycerides (mg/dL) | Case | 130 | 201.83±27.32 | 16.292 | 0.0000000001 |
| Control | 70 | 139.81±22.29 | |||
| Sodium (mEq/L) | Case | 130 | 139.79±2.77 | −0.155 | 0.877 |
| Control | 70 | 139.86±3.15 | |||
| Potassium (mEq/L) | Case | 130 | 4.21±0.43 | 0.463 | 0.644 |
| Control | 70 | 4.18±0.39 | |||
| Chloride (mEq/L) | Case | 130 | 100.06±2.85 | −0.252 | 0.801 |
| Control | 70 | 100.17±3.22 |
hs-CRP=High-sensitivity C-reactive protein, LDL=Low-density lipoprotein, HDL=High-density lipoprotein, SD=Standard deviation, TSH=Thyroid stimulating hormone, T3=Triiodothyronine, T4=Thyroxine
The mean basophil count was significantly lower in cases (0.55 ± 0.26) compared to controls (0.64 ± 0.31) (P = 0.029). The mean eosinophil count was significantly lower in cases (2.87 ± 1.16) compared to controls (3.51 ± 1.39) (P = 0.001). The mean monocyte count was significantly higher in cases (8.42 ± 1.97) compared to controls (5.99 ± 2.45) (P < 0.001). The mean lymphocytic count was considerably lower in cases (22.13 ± 4.26) compared to controls (35.67 ± 5.76) (P < 0.001). The mean neutrophil count was considerably higher in cases (65.78 ± 6.30) compared to controls (56.60 ± 4.32) (P < 0.001).
Regarding glycemic parameters, the mean fasting plasma glucose was significantly higher in cases (111.97 ± 7.48 mg/dL) compared to controls (85.49 ± 9.00 mg/dL) (P < 0.001). The mean postprandial plasma glucose was significantly higher in cases (169.61 ± 17.36 mg/dL) compared to controls (121.37 ± 10.88 mg/dL) (P < 0.001). Similarly, the mean HbA1c level was significantly higher in cases (6.04% ± 0.20%) compared to controls (5.08% ± 0.34%) (P < 0.001), as shown in Table 7.
Table 7.
Comparison of complete blood count and glucose values between cases and controls
| CBC | Group | n | Mean±SD | t | P |
|---|---|---|---|---|---|
| Basophils | Case | 130 | 0.55±0.26 | −2.195 | 0.029 |
| Control | 70 | 0.64±0.31 | |||
| Eosinophils | Case | 130 | 2.87±1.16 | −3.432 | 0.001 |
| Control | 70 | 3.51±1.39 | |||
| Monocytes | Case | 130 | 8.42±1.97 | 7.601 | <0.001 |
| Control | 70 | 5.99±2.45 | |||
| Lymphocytes | Case | 130 | 22.13±4.26 | −18.874 | <0.001 |
| Control | 70 | 35.67±5.76 | |||
| Neutrophils | Case | 130 | 65.78±6.30 | 10.887 | <0.001 |
| Control | 70 | 56.60±4.32 | |||
| Fasting plasma glucose (mg/dL) | Case | 130 | 111.97±7.48 | 22.206 | <0.001 |
| Control | 70 | 85.49±9.00 | |||
| Postprandial plasma glucose (mg/dL) | Case | 130 | 169.61±17.36 | 21.113 | <0.001 |
| Control | 70 | 121.37±10.88 | |||
| HbA1c | Case | 130 | 6.04±0.20 | 24.803 | <0.001 |
| Control | 70 | 5.08±0.34 |
HbA1c=Glycated hemoglobin, CBC=Complete blood count, SD=Standard deviation
DISCUSSION
Prediabetes is a metabolic state associated with blood glucose levels that are elevated above the normal range but not high enough to warrant a diagnosis of T2DM. This intermediary condition signifies a high-risk phase for the future development of diabetes and is associated with an increased risk of cardiovascular complications and other metabolic disorders. The global burden of prediabetes has been escalating rapidly, particularly in developing nations such as India, where lifestyle transitions and genetic predispositions have intensified its prevalence.[15]
Emerging evidence underscores a complex interplay between the endocrine and immune systems in the pathogenesis of metabolic dysfunction. In this context, thyroid hormones – key regulators of metabolism – are known to influence glucose homeostasis, insulin sensitivity, and lipid metabolism. Subtle deviations in thyroid function, even within the reference range, may significantly affect metabolic health, particularly in individuals with impaired glucose tolerance. Consequently, the evaluation of thyroid function in prediabetic individuals has gained clinical relevance.[16]
Simultaneously, chronic low-grade inflammation has been recognized as a hallmark of metabolic diseases. Inflammatory biomarkers such as high-sensitivity C-reactive protein (hs-CRP) and WBC count serve as reliable indicators of systemic inflammation and have shown strong associations with insulin resistance, cardiovascular risk, and progression to diabetes. These markers also provide valuable insight into the inflammatory milieu associated with both thyroid dysfunction and prediabetes.[17]
Despite the established individual roles of thyroid dysfunction and systemic inflammation in metabolic derangements, few studies have explored their combined impact in the prediabetic population. Understanding the interrelationship between TFTs and inflammatory markers could uncover early indicators of metabolic deterioration and provide a foundation for preventive strategies in high-risk individuals.
This study aims to investigate the relationship between thyroid function and inflammatory status, as indicated by WBC count and hs-CRP levels, in prediabetic patients. By examining these parameters in a population from Western Maharashtra, the study seeks to uncover patterns that may aid in risk stratification and early intervention in metabolic disease progression.
Majority of participants were aged above 49 years (42%), followed by 40–49 years (29%) and <40 years (29%). The majority of participants were female (55.5%), while males constituted 44.5%. A study by Wang Z, et al.[18] involved 94 participants aged 35–70 years included 61 with prediabetes and 33 with normal glucose levels. In our study, the majority of participants belonged to the case group (65%), while 35% were in the control group. Bains et al.[19] included 150 participants, divided into two groups: 75 prediabetic (case) individuals and 75 nondiabetic (control) subjects.
In our current study, the majority of participants (80.5%) had no history of smoking. In a study conducted by Rias et al.,[20] it was found that 5.8% of the participants in the healthy control group were smokers, while 11.2% of the participants in the group of patients with T2DM reported smoking.
In our study, the total WBC count was normal in 51% (102 individuals) and abnormal in 49% (98 individuals). Neutrophil levels were normal in 77.5% (155 individuals) and abnormal in 22.5% (45 individuals). Lymphocyte levels were normal in 64.5% (129 individuals) and abnormal in 35.5% (71 individuals). Monocyte levels were normal in 81% (162 individuals) and abnormal in 19% (38 individuals). Eosinophils and basophils were normal in all 200 individuals (100%). Elimam et al.[21] showed that elevated levels of hs-CRP and serum ferritin have been observed in T2DM patients, with a strong positive correlation between these inflammatory markers and HbA1c levels. This suggests that subclinical inflammation plays a crucial role in the pathogenesis of diabetes and its complications. Sherif et al.[22] evaluated that RDW, a measure of the variation in red blood cell size, has been identified as a prognostic marker reflecting underlying inflammation. Studies have shown that higher RDW values are associated with increased levels of inflammatory markers like hs-CRP in patients with T2DM, indicating its potential role in assessing inflammation and predicting vascular complications in diabetic individuals. Haghbin et al.[23] found that patients with hypothyroidism, significant correlations have been found between certain hematological parameters (such as Hb, hematocrit [Hct], mean corpuscular Hb [MCH], and mean corpuscular Hb concentration [MCHC]) and triiodothyronine (T3) levels. This underscores the intricate relationship between thyroid function and hematological indices.
In our study, 45.5% of participants were at moderate risk based on hs-CRP levels, 45% were at high risk, and 9.5% were at low risk. Bains et al.[19] found that prediabetic individuals exhibit significantly higher hs-CRP levels compared to nondiabetic controls, indicating increased systemic inflammation. Peixoto de Miranda et al.[24] found that the relationship between thyroid function and hs-CRP is complex. Some studies suggest that subclinical hypothyroidism is associated with elevated hs-CRP levels, while others find no significant association after adjusting for factors such as obesity and insulin resistance.
In our study, 61% had abnormal HDL levels, 88.5% had abnormal LDL levels, and 78.5% had abnormal triglyceride levels. Bains et al. found that prediabetic individuals exhibit significantly higher hs-CRP levels compared to nondiabetic controls, indicating increased systemic inflammation. In addition, there is a positive correlation between hs-CRP levels and lipid parameters such as total cholesterol, triglycerides, and LDL, and a negative correlation with HDL. This suggests that inflammation in prediabetes is associated with unfavorable lipid profiles.[19] Peixoto de Miranda et al.[24] found that elevated TSH levels are associated with increased hs-CRP concentrations, potentially through effects on fat distribution and insulin resistance. This relationship underscores the complex interplay between thyroid function, inflammation, and lipid metabolism.
In this study, the total WBC count has a mean of 11.52 × 109/L with an SD of 4.88, suggesting a slightly elevated average WBC count. The basophil count averages 0.58% ± 0.28%, indicating no significant abnormalities. The eosinophil count is 3.09% ± 1.28%, within normal limits. The monocyte count is 7.57% ± 2.44%, slightly above the standard reference range. The lymphocyte count averages 26.87% ± 8.07%, within the normal range but showing some variability. Finally, the neutrophil count is 62.57% ± 7.17%, which is within the expected physiological range, indicating a healthy immune response. These findings suggest that prediabetic cases exhibit significant alterations in WBC differential counts and glycemic parameters compared to controls Haghbin et al.[23] found that in hypothyroid patients, significant correlations have been observed between certain hematological parameters – such as Hb, Hct, MCH, and MCHC – and triiodothyronine (T3) levels. These findings suggest that thyroid hormones may influence red blood cell indices. Kar et al.[25] found that thyroid hormones play a crucial role in regulating hematopoiesis. Studies have shown that total leukocyte and neutrophil counts may decrease slightly in hypothyroid patients, while hyperthyroid patients may exhibit normal or mildly elevated levels. This indicates that thyroid dysfunction can impact WBC counts.
The mean T3 level was lower in cases compared to controls, while the mean TSH level was higher in cases. The mean WBC count was higher in cases, and the mean hs-CRP level was elevated in cases. The mean HDL level was lower in cases, while the mean LDL and triglyceride levels were higher in cases. No significant differences were found in sodium, potassium, or chloride levels between cases and controls. The findings suggest that a more pronounced impact of blood pressure can be seen in cases. A study by Aswani et al.[26] observed that prediabetic patients had elevated TSH levels and decreased triiodothyronine (T3) and thyroxine (T4) levels compared to nondiabetic individuals, suggesting early thyroid dysfunction during prediabetes. Bains et al.[19] prediabetic individuals exhibited significantly higher levels of hs-CRP than nondiabetic controls, indicating increased systemic inflammation associated with prediabetes.
Aswani et al.[26] conducted in Durban, South Africa, observed that prediabetic individuals exhibited elevated TSH levels and decreased triiodothyronine (T3) and thyroxine (T4) levels compared to nondiabetic controls. These changes suggest early thyroid dysfunction during the prediabetic stage. Prediabetic individuals were found to have considerably higher levels of hs-CRP compared to nondiabetic controls, indicating increased systemic inflammation. This elevation in hs-CRP correlates positively with unfavorable lipid profiles, including increased total cholesterol, triglycerides, and LDL, and negatively with HDL. Jublanc et al.[27] Elevated TSH levels have been associated with increased hs-CRP concentrations, suggesting a link between thyroid function and systemic inflammation. This relationship underscores the complex interplay between thyroid hormones and inflammatory processes in metabolic disorders.
CONCLUSION
This study demonstrates a significant association between altered thyroid function and elevated inflammatory markers in prediabetic patients. The presence of raised levels of TSH and low-grade inflammation, as indicated by raised hs-CRP and WBC count, suggests that prediabetes is not only a state of impaired glucose regulation but also involves endocrine and immunological disturbances. Recognizing and addressing these abnormalities early in the clinical course can aid in the prevention of T2DM and associated complications. Larger prospective studies are warranted to further explore these interrelationships and to validate the utility of these biomarkers in risk stratification and management of prediabetic individuals.
Conflicts of interest
There are no conflicts of interest.
Funding Statement
Nil.
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