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We performed a genome-wide association study (GWAS) and a multistage meta-analysis of type 2 diabetes (T2D) in Punjabi Sikhs from India. Our discovery GWAS in 1,616 individuals (842 case subjects) was followed by in silico replication of the top 513 independent SNPs (P < 10(-3)) in Punjabi Sikhs (n = 2,819; 801 case subjects). We further replicated...
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... Sikh discovery GWAS. Clinical characteristics of the stage 1 Punjabi Sikh T2D GWAS cohort and stage 2a and 2b (replication) cohorts are described in Supplemen- tary Table 3. Principal components analysis revealed little population structure ( Supplementary Fig. 1). After quality control, 524,216 directly genotyped SNPs in 1,616 subjects (842 case and 774 control subjects) from 1,850 total sub- jects were available for association testing after removing samples showing cryptic relatedness through identity- by-descent sharing. ...
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... reason for choosing a more cosmopolitan panel and not restricting to the GIH was based on our own data showing equal diversity of the Sikhs from GIH and CEU, and based on previously described advantages of using a worldwide reference panel (39). We performed a GWAS for T2D adjusted for covariates age, sex, BMI, and five principal components ( Supplementary Fig. 1); no evi- dence of inflation was observed (Supplementary Fig. 2A and B) (see RESEARCH DESIGN AND METHODS). Replication and meta-analyses in Punjabi Sikh participants. ...
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... age, sex, BMI, and five principal components ( Supplementary Fig. 1); no evi- dence of inflation was observed (Supplementary Fig. 2A and B) (see RESEARCH DESIGN AND METHODS). Replication and meta-analyses in Punjabi Sikh participants. We undertook a two-stage replication in T2D case-control samples of Punjabi Sikh ancestry (stages 2a and 3a in Fig. 1). Lead SNPs representing 513 novel, independent (r 2 ,0.25) association signals with P , 10 23 in the discovery GWAS (including only two previously known GWAS SNPs from TCF7L2 and IGF2BP2 and excluding 62 SNPs with P , 10 23 from other known T2D loci) were tested for in silico replication in the Punjabi Sikh sub- component of the ...
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... 801 T2D case and 2,018 control subjects (Supplementary Table 1). Top SNPs representing 66 putatively novel signals with P , 10 24 after stage 1 and 2a meta-analysis using a fixed effects, inverse-variance approach were directly geno- typed in the stage 3a sample of 2,894 Punjabi Sikh indi- viduals (1,711 T2D case and 1,183 control subjects) ( Fig. 1 and Supplementary Table ...
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... Asians. In order to identify T2D association sig- nals common to Punjabi and other South Asian pop- ulations, we tested the association of the 513 top independent signals (P , 10 23 ) derived from the discovery cohort in GWAS from the LOLIPOP, PROMIS, and RACE studies as part of stage 2b replication (10,971 T2D case and 18,186 control subjects) ( Fig. 1 and Supplementary Table 1). Thirty-one signals (P , 10 24 from an interim analysis with stage 2b) were further genotyped in 10,817 South Asians (5,157 T2D and 5,660 control subjects) (Fig. 1) as part of stage 3b replication. Clinical characteristics of the stage 3 replication cohorts are described in Supplementary Table 4. Combined ...
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... from the discovery cohort in GWAS from the LOLIPOP, PROMIS, and RACE studies as part of stage 2b replication (10,971 T2D case and 18,186 control subjects) ( Fig. 1 and Supplementary Table 1). Thirty-one signals (P , 10 24 from an interim analysis with stage 2b) were further genotyped in 10,817 South Asians (5,157 T2D and 5,660 control subjects) (Fig. 1) as part of stage 3b replication. Clinical characteristics of the stage 3 replication cohorts are described in Supplementary Table 4. Combined South Asian meta-analysis revealed nominally significant association in six SNPs with MAF .5% (P # 10 24 ), but only the two previously known SNPs in TCF7L2 and IGF2BP2 reached genome-wide ...
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... required to val- idate these results and identify causal variants at these loci. Multiethnic replication and meta-analysis. To identify T2D signals spanning ethnicities, we extended the repli- cation of 31 SNPs with P , 10 24 in Punjabis and South Asians (stage 3b) to East Asians (AGEN+) and Europeans (DIAGRAM+) in stages 3c and 3d, respectively (Fig. 1). Upon meta-analysis of 31 loci in Asians (South Asians and AGEN+), genome-wide associations were only seen in TCF7L2 (rs7903146, P = 1.93 3 10 238 ) and IGF2BP2 (rs1470579, P = 1.54 3 10 213 ) (Supplementary Table 9). In joint multiethnic meta-analysis on 128,127 individuals from 27 studies, only two previously known loci, TCF7L2 ...
Citations
... The study was performed under the Declaration of Helsinki guidelines. All participating studies were reviewed and approved by the respective Universities or Institutional Review Boards, including the primary institute of the University of Oklahoma Health Sciences Center's Institutional Review Board and the Human Subject Protection Committees at the participating hospitals and institutes in India [16,17]. All participants provided written informed consent for investigations. ...
... The majority of the CAD patients were recruited from the Dayanand Medical College and Hospital following their admission for the coronary artery bypass graft (CABG) or angioplasty based on the date of admission or surgery and the use of medicines obtained from patient records as mentioned previously [20,21]. Demographic and anthropometric measurements, lipid and glucose panels, and blood pressure measures are described elsewhere [16,18,22]. Body mass index (BMI) was calculated as the ratio of weight (kg) to height (m) 2 . ...
... The diagnosis of type 2 diabetes (T2D) was confirmed by referral to the medical records for symptoms and medications as well as measuring fasting glucose levels following American Diabetes Association [23] guidelines as described previously [24]. Subjects with type 1 diabetes, family history of type 1 diabetes or any other co-morbidities were excluded [16]. ...
We evaluated the performance of various polygenic risk score (PRS) models derived from European (EU), South Asian (SA), and Punjabi Asian Indians (AI) studies on 13,974 subjects from AI ancestry. While all models successfully predicted Coronary artery disease (CAD) risk, the AI, SA, and EU + AI were superior predictors and more transportable than the EU model; the predictive performance in training and test sets was 18% and 22% higher in AI and EU + AI models, respectively than in EU. Comparing individuals with extreme PRS quartiles, the AI and EU + AI captured individuals with high CAD risk showed 2.6 to 4.6 times higher efficiency than the EU. Interestingly, including the clinical risk score did not significantly change the performance of any genetic model. The enrichment of diversity variants in EU PRS improves risk prediction and transportability. Establishing population-specific normative and risk factors and inclusion into genetic models would refine the risk stratification and improve the clinical utility of CAD PRS.
Graphical abstract
... Thus far, only a handful of T2D GWAS has been published on South AIs, who comprise more than a quarter of the world population. [12][13][14] Most of the genetic studies on South Asians have been performed on immigrants, such as Indians living in the UK or on Pakistani populations. These studies do not putatively reflect the underlying genetic architecture of phenotypic traits and their interactions with other clinical and lifestyle factors of native AIs. ...
... 31,32 In this study, we constructed an ancestry-specific PRS (PRS AI ) for T2D using candidate variants derived from our Asian Indian Diabetic Heart Study/Sikh Diabetes Study (AIDHS/SDS). 13,[33][34][35][36] We also built a PRS (PRS EU ) using summary statistics from GWAS meta-analyses from seven European cohorts. 37 We compared the predictive efficacy and transferability between PRS derived from AIDHS/SDS and Europeans using validation datasets-1 and 2, including data from South Asians from the UK Biobank (UKBB). ...
... All study participants of AIDHS/SDS were from the Northern part of India and were recruited from 2003 to 2009. 13,36,38,39 Study protocol and consent documents were reviewed and approved by the University of Oklahoma Health Sciences Center's Institutional Review Board (IRB #: 2911). Clinical characteristics and demographic details of the studied subjects are presented in Table 1. ...
Background
Genome-wide polygenic risk scores (PRS) have shown high specificity and sensitivity in predicting type 2 diabetes (T2D) risk in Europeans. However, the PRS-driven information and its clinical significance in non-Europeans are underrepresented. We examined the predictive efficacy and transferability of PRS models using variant information derived from genome-wide studies of Asian Indians (AIs) (PRSAI) and Europeans (PRSEU) using 13,974 AI individuals.
Methods
Weighted PRS models were constructed and analyzed on 4602 individuals from the Asian Indian Diabetes Heart Study/Sikh Diabetes Study (AIDHS/SDS) as discovery/training and test/validation datasets. The results were further replicated in 9372 South Asian individuals from UK Biobank (UKBB). We also assessed the performance of each PRS model by combining data of the clinical risk score (CRS).
Results
Both genetic models (PRSAI and PRSEU) successfully predicted the T2D risk. However, the PRSAI revealed 13.2% odds ratio (OR) 1.80 [95% confidence interval (CI) 1.63–1.97; p = 1.6 × 10⁻¹⁵²] and 12.2% OR 1.38 (95% CI 1.30–1.46; p = 7.1 × 10⁻²³⁷) superior performance in AIDHS/SDS and UKBB validation sets, respectively. Comparing individuals of extreme PRS (ninth decile) with the average PRS (fifth decile), PRSAI showed about two-fold OR 20.73 (95% CI 10.27–41.83; p = 2.7 × 10⁻¹⁷) and 1.4-fold OR 3.19 (95% CI 2.51–4.06; p = 4.8 × 10⁻²¹) higher predictability to identify subgroups with higher genetic risk than the PRSEU. Combining PRS and CRS improved the area under the curve from 0.74 to 0.79 in PRSAI and 0.72 to 0.75 in PRSEU.
Conclusion
Our data suggest the need for extending genetic and clinical studies in varied ethnic groups to exploit the full clinical potential of PRS as a risk prediction tool in diverse study populations.
... The TCF7L2 variation has led to an upsurge risk of early-onset T2D among African Americans (38). It is worth highlighting that the current study reinforces earlier studies on South Asian T2D genetics (39). In addition, WDR11 has previously been associated with fasting glucose (32), T2D susceptibility (32), and youth-onset T2D (33). ...
OBJECTIVE
South Asians are diagnosed with type 2 diabetes (T2D) more than a decade earlier in life than seen in European populations. We hypothesized that studying the genomics of age of diagnosis in these populations may give insight into the earlier age diagnosis of T2D among individuals of South Asian descent.
RESEARCH DESIGN AND METHODS
We conducted a meta-analysis of genome-wide association studies (GWAS) of age at diagnosis of T2D in 34,001 individuals from four independent cohorts of European and South Asian Indians.
RESULTS
We identified two signals near the TCF7L2 and CDKAL1 genes associated with age at the onset of T2D. The strongest genome-wide significant variants at chromosome 10q25.3 in TCF7L2 (rs7903146; P = 2.4 × 10−12, β = −0.436; SE 0.02) and chromosome 6p22.3 in CDKAL1 (rs9368219; P = 2.29 × 10−8; β = −0.053; SE 0.01) were directionally consistent across ethnic groups and present at similar frequencies; however, both loci harbored additional independent signals that were only present in the South Indian cohorts. A genome-wide signal was also obtained at chromosome 10q26.12 in WDR11 (rs3011366; P = 3.255 × 10−8; β = 1.44; SE 0.25), specifically in the South Indian cohorts. Heritability estimates for the age at diagnosis were much stronger in South Indians than Europeans, and a polygenic risk score constructed based on South Indian GWAS explained ∼2% trait variance.
CONCLUSIONS
Our findings provide a better understanding of ethnic differences in the age at diagnosis and indicate the potential importance of ethnic differences in the genetic architecture underpinning T2D.
... 6,7 This early onset of diabetes and lower BMI of Indian people with T2D may be partly because of genetic differences; some of which have been previously described. [8][9][10][11][12] However, a major contribution may be due to early life undernutrition in Indians. [13][14][15] A substantial variation was also reported in the prevalence and clinical characteristics of people with T2D in different states of India in the Indian Council for Medical Research-India Diabetes (ICMR-INDIAB) study. ...
... Previous studies reported the association of rs9552911 SNP at the SGCG locus and rs998451 at the TMEM163 locus with T2D in India but not in other populations. 9, 10 We did not find any association of these variants with any of the subgroups in WellGen (Table 4). ...
Background:
A machine-learning approach identified five subgroups of diabetes in Europeans which included severe autoimmune diabetes (SAID), severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD), mild obesity-related diabetes (MOD) and mild age-related diabetes (MARD) with partially distinct genetic aetiologies. We previously validated four of the non-autoimmune subgroups in people with young-onset type 2 diabetes (T2D) from the Indian WellGen study. Here, we aimed to apply European-derived centroids and genetic risk scores (GRSs) to the unselected (for age) WellGen to test their applicability and investigate the genetic aetiology of the Indian T2D subgroups.
Methods:
We applied European derived centroids and GRSs to T2D participants of Indian ancestry (WellGen, n = 2217, 821 genotyped) and compared them with normal glucose tolerant controls (Pune Maternal Nutrition Study, n = 461).
Findings:
SIDD was the predominant subgroup followed by MOD, whereas SIRD and MARD were less frequent. Weighted-GRS for T2D, obesity and lipid-related traits associated with T2D. We replicated some of the previous associations of GRS for T2D, insulin secretion, and BMI with SIDD and MOD. Unique to Indian subgroups was the association of GRS for (a) proinsulin with MOD and MARD, (b) liver-lipids with SIDD, SIRD and MOD, and (c) opposite effect of beta-cell GRS with SIDD and MARD, obesity GRS with MARD compared to Europeans. Genetic variants of fucosyltransferases were associated with T2D and MOD in Indians but not Europeans.
Interpretation:
The similarities emphasise the applicability of some of the European-derived GRSs to T2D and its subgroups in India while the differences highlight the need for large-scale studies to identify aetiologies in diverse ancestries. The data provide robust evidence for genetically distinct aetiologies for the T2D subgroups and at least partly mirror those seen in Europeans.
Funding:
Vetenskapsrådet, Diabetes Wellness, and Hjärt-Lungfonden (Sweden), DST (India), Wellcome Trust, Crafoord Foundation and Albert Påhlsson Foundation.
... Furthermore, large meta-analyses of GWAS were performed [10,129] and identified 2284 SNPs associated with T2D, but only 183 and 38 loci were successfully replicated as T2D susceptibility markers once and twice, respectively [130]. Thus, a large portion of the originally discovered SNP-disease associations were poorly replicated by independent studies [131][132][133]. TCF7L2, HHEX, KCNJ11, CENTD2, ARAP1, FTO, HNF1B, PPARG, IGF2BP2, CDKAL1, VEGFA, SLC30A8, CDKN2A, CDKN2B, KCNQ1, UBE2E2, ANK1, ABCC8, IRS1, and GLP2R are the genes whose polymorphic variants showed strong associations with susceptibility to T2D and related phenotypes [134][135][136]. ...
Numerous studies have shown that oxidative stress resulting from an imbalance between the production of free radicals and their neutralization by antioxidant enzymes is one of the major pathological disorders underlying the development and progression of type 2 diabetes (T2D). The present review summarizes the current state of the art advances in understanding the role of abnormal redox homeostasis in the molecular mechanisms of T2D and provides comprehensive information on the characteristics and biological functions of antioxidant and oxidative enzymes, as well as discusses genetic studies conducted so far in order to investigate the contribution of polymorphisms in genes encoding redox state-regulating enzymes to the disease pathogenesis.
... Among the T2D-associated signals found in our study, the rs7903146 variant at the TCF7L2 locus is the most well-established genetic marker for T2D and the largest-effect common-variant signal for T2D in Europeans [29], first identified in 2007 in a French population [30]. The association between rs7903146 and T2D transcends ancestry and has been replicated across numerous populations including Finnish [31], Icelandic [32], Danish [33], Japanese [34], Indian [35], Punjabi Sikh [36], Mexican and Latin American [37,38], African American [39], Sub-Saharan African [40] populations as well as in multiple multi-ancestral meta-analyses [41][42][43][44]. Most recently, a meta-analysis combining the data from 122 GWAS for 180,834 individuals with T2D and 1,159,055 controls of European, East Asian, South Asian, African, African American, and Hispanic individuals with recent admixture of American, African and European ancestry [45] confirmed the association of rs7903146 with T2D. ...
We tested associations between 13 established genetic variants and type 2 diabetes (T2D) in 1371 study participants from the Volga-Ural region of the Eurasian continent, and evaluated the predictive ability of the model containing polygenic scores for the variants associated with T2D in our dataset, alone and in combination with other risk factors such as age and sex. Using logistic regression analysis, we found associations with T2D for the CCL20 rs6749704 (OR = 1.68, PFDR = 3.40 × 10−5), CCR5 rs333 (OR = 1.99, PFDR = 0.033), ADIPOQ rs17366743 (OR = 3.17, PFDR = 2.64 × 10−4), TCF7L2 rs114758349 (OR = 1.77, PFDR = 9.37 × 10−5), and CCL2 rs1024611 (OR = 1.38, PFDR = 0.033) polymorphisms. We showed that the most informative prognostic model included weighted polygenic scores for these five loci, and non-genetic factors such as age and sex (AUC 85.8%, 95%CI 83.7%–87.8%). Compared to the model containing only non-genetic parameters, adding the polygenic score for the five T2D-associated loci showed improved net reclassification (NRI = 37.62%, 1.39 × 10−6). Inclusion of all 13 tested SNPs to the model with age and sex did not improve the predictive ability compared to the model containing five T2D-associated variants (NRI = −17.86, p = 0.093). The five variants associated with T2D in people from the Volga-Ural region are linked to inflammation (CCR5, CCL2, CCL20) and glucose metabolism regulation (TCF7L, ADIPOQ2). Further studies in independent groups of T2D patients should validate the prognostic value of the model and elucidate the molecular mechanisms of the disease development.
... Studies conducted among European communities have identified 41 SNPs associated with T2DM and found that genes associated with glucose homeostasis, insulin pathway and pancreatic development pathways were the candidate genes associated with T2DM [19]. SNPs at high mobility group box 1 pseudogene 1 (HMG1L1)/ CCCTC-binding-like factor (CTCFL), paired box 4 A4 (PLXNA4), cleavage-activating protein (SCAP), chr5p11 and a novel locus at 13q12 at sarcoglycan gamma (SGCG) were associated with T2DM [20]. Table 1 provides a comprehensive list of marker-trait association of T2DM, and includes significant findings related to the genes of T2DM in the global population, including India. ...
... Genome-wide studies have mapped a susceptibility locus for T2DM to 3q27, where ADIPOQ gene is situated. SNPs of this gene have been studied, and two SNPs, a silent T to G substitution in exon 2 and a G to T substitution in intron 2, were found to be associated in the Japanese population [20]. A study identified that + 10211T/G polymorphism in the adiponectin gene was associated with T2DM in the Asian Indian population [23]. ...
Background
Non-communicable diseases such as cardiovascular diseases, respiratory diseases and diabetes contribute to the majority of deaths in India. Public health programmes on non-communicable diseases (NCD) prevention primarily target the behavioural risk factors of the population. Hereditary is known as a risk factor for most NCDs, specifically, type 2 diabetes mellitus (T2DM), and hence, understanding of the genetic markers of T2DM may facilitate prevention, early case detection and management.
Main body
We reviewed the studies that explored marker–trait association with type 2 diabetes mellitus globally, with emphasis on India. Globally, single nucleotide polymorphisms (SNPs) rs7903146 of Transcription Factor 7-like 2 (TCF7L2) gene was common, though there were alleles that were unique to specific populations. Within India, the state-wise data were also taken to foresee the distribution of risk/susceptible alleles. The findings from India showcased the common and unique alleles for each region.
Conclusion
Exploring the known and unknown genetic determinants might assist in risk prediction before the onset of behavioural risk factors and deploy prevention measures. Most studies were conducted in non-representative groups with inherent limitations such as smaller sample size or looking into only specific marker–trait associations. Genome-wide association studies using data from extensive prospective studies are required in highly prevalent regions worldwide. Further research is required to understand the singular effect and the interaction of genes in predicting diabetes mellitus and other comorbidities.
... Tabassum et al. [43] published a GWAS largely based on the Indo-European and Dravidian population with the strongest association signal around the TMEM163 gene. In the same year, Saxena et al. [44] published a study on the Punjabi Sikh population with a novel signal at the SGCG gene. Recently, a study [45] published on the genetic basis of T2D in three ethnically endogamous Indian populations based in Tamil Nadu, Rajasthan and Andhra Pradesh states (the INDIGENIUS Consortium) also demonstrated substantial population-specificity in the genetic basis of T2D within Indian populations. ...
Type 2 diabetes (T2D) is a complex metabolic derangement that has a strong genetic basis. There is substantial population-specificity in the association of genetic variants with T2D. The Indian urban Sindhi population is at a high risk of T2D. The genetic basis of T2D in this population is unknown. We interrogated 28 pooled whole blood genomes of 1402 participants from the Diabetes In Sindhi Families In Nagpur (DISFIN) study using Illumina’s Global Screening Array. From a total of 608,550 biallelic variants, 140 were significantly associated with T2D after adjusting for comorbidities, batch effects, pooling error, kinship status and pooling variation in a random effects multivariable logistic regression framework. Of the 102 well-characterized genes that these variants mapped onto, 70 genes have been previously reported to be associated with T2D to varying degrees with known functional relevance. Excluding open reading frames, intergenic non-coding elements and pseudogenes, our study identified 22 novel candidate genes in the Sindhi population studied. Our study thus points to the potential, interesting candidate genes associated with T2D in an ethnically endogamous population. These candidate genes need to be fully investigated in future studies.
... These two phenotypes are highly associated with diabetes (40). In addition, another gene SGCG encoding protein in the sarcoglycan complex has been identified for diabetes among Punjabi Sikhs population in India (41). Animal studies have provided further evidence for the involvement of the SGCZ gene in diabetes development. ...
We conducted the first genome-wide association study of prediabetes status change (to diabetes or normal glycaemia) among 900 White participants of the Atherosclerosis Risk in Communities (ARIC) study. Single nucleotide polymorphism (SNP)-based analysis was performed by logistic regression models, controlling for age, gender, body mass index, and the first 3 genetic principal components. Gene-based analysis was conducted by combining SNP-based p values using effective Chi-square test method. Promising SNPs (p < 1×10-5) and genes (p < 1×10-4) were further evaluated for replication among 514 White participants of the Framingham Heart Study (FHS). To accommodate familial correlations, generalized estimation equation models were applied for SNP-based analyses in the FHS. Analysis results across ARIC and FHS were combined using inverse-variance-weighted meta-analysis method for SNPs and Fisher’s method for genes. We robustly identified 5 novel genes that are associated with prediabetes status change using gene-based analyses, including SGCZ (ARIC p = 9.93×10-6, FHS p = 2.00×10-3, Meta p = 3.72×10-7) at 8p22, HPSE2 (ARIC p = 8.26×10-19, FHS p = 5.85×10-3, Meta p < 8.26×10-19) at 10q24.2, ADGRA1 (ARIC p = 1.34×10-5, FHS p = 1.13×10-3, Meta p = 2.88×10-7) at 10q26.3, GLB1L3 (ARIC p = 3.71×10-6, FHS p = 4.51×10-3, Meta p = 3.16×10-7) at 11q25, and PCSK6 (ARIC p = 6.51×10-6, FHS p = 1.10×10-2, Meta p = 1.25×10-6) at 15q26.3. eQTL analysis indicated that these genes were highly expressed in tissues related to diabetes development. However, we were not able to identify any novel locus in single SNP-based analysis. Future large scale genomic studies of prediabetes status change are warranted.
... Although India represents nearly one fifth of the global population, there have only been a few genome-wide association studies (GWASs) of T2D involving populations in India including our own study of the Punjabi Sikh population or immigrant populations of Indian ancestry, which localized a few T2D susceptibility loci (28)(29)(30)(31)(32). In addition, there is a paucity of data on EEG specific family-based genetic epidemiological studies (26,(33)(34)(35)(36)(37). ...
... Through NIH support, over 4,700 individuals were recruited as part of the Asian Indian Diabetic Heart Study/Sikh Diabetes Study [AIDHS/ SDS], and the details of these studies were reported previously (34,36,48). Briefly, the Sikh Khatri EEG family study (Phase I of the AIDHS/SDS) was comprised of 1,260 individuals distributed across 340 families (mostly nuclear in nature) for whom demographic, phenotypic/covariate data, and blood samples were already available (30,34,36,49,50). The Agarwal and Sikh EEGs are speakers of Indo-Europeans languages, and the Reddy and Chettiar EEGs are speakers of Dravidian languages. ...
To assess the burden of type 2 diabetes (T2D) and its genetic profile in endogamous populations of India given the paucity of data, we aimed to determine the prevalence of T2D and estimate its heritability using family-based cohorts from three distinct Endogamous Ethnic Groups (EEGs) representing Northern (Rajasthan [Agarwals: AG]) and Southern (Tamil Nadu [Chettiars: CH] and Andhra Pradesh [Reddys: RE]) states of India. For comparison, family-based data collected previously from another North Indian Punjabi Sikh (SI) EEG was used. In addition, we examined various T2D-related cardiometabolic traits and determined their heritabilities. These studies were conducted as part of the Indian Diabetes Genetic Studies in collaboration with US (INDIGENIUS) Consortium. The pedigree, demographic, phenotypic, covariate data and samples were collected from the CH, AG, and RE EEGs. The status of T2D was defined by ADA guidelines (fasting glucose ≥ 126 mg/dl or HbA1c ≥ 6.5% and/or use of diabetes medication/history). The prevalence of T2D in CH (N = 517, families = 21, mean age = 47y, mean BMI = 27), AG (N = 530, Families = 25, mean age = 43y, mean BMI = 27), and RE (N = 500, Families = 22, mean age = 46y, mean BMI = 27) was found to be 33%, 37%, and 36%, respectively, Also, the study participants from these EEGs were found to be at increased cardiometabolic risk (e.g., obesity and prediabetes). Similar characteristics for the SI EEG (N = 1,260, Families = 324, Age = 51y, BMI = 27, T2D = 75%) were obtained previously. We used the variance components approach to carry out genetic analyses after adjusting for covariate effects. The heritability (h2) estimates of T2D in the CH, RE, SI, and AG were found to be 30%, 46%, 54%, and 82% respectively, and statistically significant (P ≤ 0.05). Other T2D related traits (e.g., BMI, lipids, blood pressure) in AG, CH, and RE EEGs exhibited strong additive genetic influences (h2 range: 17% [triglycerides/AG and hs-CRP/RE] - 86% [glucose/non-T2D/AG]). Our findings highlight the high burden of T2D in Indian EEGs with significant and differential additive genetic influences on T2D and related traits.
