Differential HLA Association of GAD65 and IA2 Autoantibodies in North Indian Type 1 Diabetes Patients

The human leucocyte antigen (HLA) association with type 1 diabetes (T1D) is well known but there are limited studies investigating the association between β-cell autoantibodies and HLA genes. We evaluated the prevalence of GAD65 and IA-2 autoantibodies (GADA and IA2A) in 252 T1D patients from North India and investigated the genetic association of GADA and IA2A with HLA class I and class II genes/haplotypes. GADA and IA2A were detected in 50.79% and 15.87% of T1D patients, respectively, while only 8.73% had both GADA and IA2A. HLA-DRB1 ∗ 03 was observed to be significantly higher in GADA+ T1D patients as compared to GADA– (91.41% vs. 66.13%, Bonferroni- corrected P P c = 1.11 × 10 − 5 ; OR = 5.45 ; 95% CI: 2.67-11.08). Similarly, HLA-DQB1 ∗ 02 was found to be significantly increased in GADA+ patients (94.53%, P c = 2.19 × 10 − 5 ; OR = 6.27 ; 95% CI: 2.7-14.49) as compared to GADA– (73.39%). The frequencies of HLA-DRB1 ∗ 04 and DQB1 ∗ 03 were increased in IA2A+ patients (45.0% and 52.5%, respectively) as compared to that in IA2A– (25.94% and 33.96%, respectively). Further, the frequency of DRB1 ∗ 03-DQB1 ∗ 02 haplotype was found to be significantly increased in GADA+ T1D patients as compared to GADA- (60.55% vs. 41.94%, P = 3.94 × 10 − 5 ; OR = 2.13 ; 95 % CI = 1.49 -3.03). Similarly, HLA-DRB1 ∗ 04-DQB1 ∗ 03 haplotype was found to be significantly increased in IA2A+ T1D patients compared to IA2A– patients (22.5% vs. 12.97%; P = 0.041 ; OR = 1.95 ; 95 % CI = 1.08 -3.52). None of the HLA class I genes (HLA-A, B, and Cw) was found to be associated with GADA or IA2A in people with T1D. Our findings suggest that HLA-DRB1 ∗ 03/DQB1 ∗ 02 and HLA-DRB1 ∗ 04/DQB1 ∗ 03 might play an important role in the development of GADA and IA2A, respectively.

COVID-19 and Indian population: a comparative genetic analysis

Background Major risk factors of COVID-19 include older age, male gender, and comorbidities. In addition, host genetic makeup is also known to play a major role in COVID-19 susceptibility and severity. To assess the genetic predisposition of the Indian population to COVID-19, a comparative analysis of the frequencies of polymorphisms directly or potentially associated with COVID-19 susceptibility, severity, immune response, and fatal outcomes was done between the Indian population and other major populations (European, African, East Asian, South Asian, and American). Materials and methods Polymorphisms directly or potentially associated with COVID-19 susceptibility, severity, immune response, and mortality were mined from genetic association studies, comparative genetic studies, expression quantitative trait loci studies among others. Genotype data of these polymorphisms were either sourced from the GenomegaDB database of Mapmygenome India Ltd. (sample size = 3054; Indian origin) or were imputed. Polymorphisms with minor allele frequency >= 0.05 and that are in Hardy-Weinberg equilibrium in the Indian population were considered for allele frequency comparison between the Indian population and 1000 Genome population groups. Results Allele frequencies of 421 polymorphisms were found to be significantly different in the Indian population compared to European, African, East Asian, South Asian, and American populations. 128 polymorphisms were shortlisted based on linkage disequilibrium and were analyzed in detail. Apart from well-studied genes, like ACE2, TMPRSS2, ADAM17, and FURIN, variants from AHSG, IFITM3, PTPN2, CD209, CCL5, HEATR9, SELENBP9, AGO1, HLA-G, MX1, ICAM3, MUC5B, CRP, C1GALT1, and other genes were also found to be significantly different in Indian population. These variants might be implicated in COVID-19 susceptibility and progression. Conclusion Our comparative study unraveled multiple genetic variants whose allele frequencies were significantly different in the Indian population and might have a potential role in COVID-19 susceptibility, its severity, and fatal outcomes. This study can be very useful for selecting candidate genes/variants for future COVID-19 related genetic association studies.

Genetic Architecture of Heart Failure with Preserved versus Reduced Ejection Fraction

BackgroundPharmacologic clinical trials for heart failure (HF) with preserved ejection fraction (HFpEF) have been largely unsuccessful as compared to those for heart failure with reduced ejection fraction (HFrEF). Whether differences in the genetic underpinnings of these HF subtypes may provide insights into the disparate outcomes of these clinical trials remains unknown.ObjectivesWe pursued genetic association analyses to compare the genetic architecture of HFpEF with that of HFrEF.MethodsWe created a non-Hispanic White cohort including 19,495 HFrEF and 19,589 HFpEF cases among 43,344 unclassified HF cases, and 258,943 controls without HF in the Veterans Health Administration Million Veteran Program. We then conducted genome-wide association studies of unclassified HF, HFrEF and HFpEF, followed by genetic correlation analyses and Mendelian randomization analyses of established HF risk factors with HFrEF and HFpEF.ResultsWe found 13 loci associated with HFrEF at genome-wide significance, but only one associated with HFpEF. Among genome-wide significant loci for HFrEF, four loci were not associated with any HF risk factor. The single locus identified for HFpEF (FTO) is a known marker for obesity. Genetically determined associations were widely different between HFrEF and HFpEF for several risk factors including coronary artery disease, lipid levels, and pulse pressure.ConclusionsThe modest genetic discovery for HFpEF compared to HFrEF despite a robust sample size indicates that HFpEF, as currently defined, likely represents the amalgamation of several, distinct pathobiological entities. Development of consensus sub-phenotyping of HFpEF is paramount to better dissect the underlying genetic signals and contributors to HFpEF.Condensed AbstractWe utilized a large, uniformly phenotyped, single cohort of heart failure sub-classified into heart failure with reduced (HFrEF) and preserved ejection fraction (HFpEF) based on current clinical definitions, to conduct detailed genetic analyses of the two HF sub-types. We found different genetic architectures and distinct genetic association profiles of HFrEF and HFpEF suggesting differences in underlying pathobiology. Furthermore, the low yield of HFpEF genome-wide association study (GWAS) compared to similarly powered HFrEF GWAS underscores the heterogeneity of HFpEF and the urgent need for developing consensus sub-phenotyping of HFpEF to improve the discovery in genetic mechanisms and therapeutic interventions.