Whole genome sequencing of families diagnosed with cardiac channelopathies reveals structural variants missed by whole exome sequencing.

Cardiac channelopathies are a group of heritable disorders that affect the heart's electrical activity due to genetic variations present in genes coding for ion channels. With the advent of new sequencing technologies, molecular diagnosis of these disorders in patients has paved the way for early identification, therapeutic management and family screening. The objective of this retrospective study was to understand the efficacy of whole-genome sequencing in diagnosing patients with suspected cardiac channelopathies who were reported negative after whole exome sequencing and analysis. We employed a 3-tier analysis approach to identify nonsynonymous variations and loss-of-function variations missed by exome sequencing, and structural variations that are better resolved only by sequencing whole genomes. By performing whole genome sequencing and analyzing 25 exome-negative cardiac channelopathy patients, we identified 3 pathogenic variations. These include a heterozygous likely pathogenic nonsynonymous variation, CACNA1C:NM_000719:exon19:c.C2570G:p. P857R, which causes autosomal dominant long QT syndrome in the absence of Timothy syndrome, a heterozygous loss-of-function variation CASQ2:NM_001232.4:c.420+2T>C classified as pathogenic, and a 9.2 kb structural variation that spans exon 2 of the KCNQ1 gene, which is likely to cause Jervell-Lange-Nielssen syndrome. In addition, we also identified a loss-of-function variation and 16 structural variations of unknown significance (VUS). Further studies are required to elucidate the role of these identified VUS in gene regulation and decipher the underlying genetic and molecular mechanisms of these disorders. Our present study serves as a pilot for understanding the utility of WGS over clinical exomes in diagnosing cardiac channelopathy disorders.

Spatio-temporal dynamics of intra-host variability in SARS-CoV-2 genomes.

During the course of the COVID-19 pandemic, large-scale genome sequencing of SARS-CoV-2 has been useful in tracking its spread and in identifying variants of concern (VOC). Viral and host factors could contribute to variability within a host that can be captured in next-generation sequencing reads as intra-host single nucleotide variations (iSNVs). Analysing 1347 samples collected till June 2020, we recorded 16 410 iSNV sites throughout the SARS-CoV-2 genome. We found ∼42% of the iSNV sites to be reported as SNVs by 30 September 2020 in consensus sequences submitted to GISAID, which increased to ∼80% by 30th June 2021. Following this, analysis of another set of 1774 samples sequenced in India between November 2020 and May 2021 revealed that majority of the Delta (B.1.617.2) and Kappa (B.1.617.1) lineage-defining variations appeared as iSNVs before getting fixed in the population. Besides, mutations in RdRp as well as RNA-editing by APOBEC and ADAR deaminases seem to contribute to the differential prevalence of iSNVs in hosts. We also observe hyper-variability at functionally critical residues in Spike protein that could alter the antigenicity and may contribute to immune escape. Thus, tracking and functional annotation of iSNVs in ongoing genome surveillance programs could be important for early identification of potential variants of concern and actionable interventions.

Whole-genome sequencing of 1029 Indian individuals reveals unique and rare structural variants.

Structural variants contribute to genetic variability in human genomes and they can be presented in population-specific patterns. We aimed to understand the landscape of structural variants in the genomes of healthy Indian individuals and explore their potential implications in genetic disease conditions. For the identification of structural variants, a whole genome sequencing dataset of 1029 self-declared healthy Indian individuals from the IndiGen project was analysed. Further, these variants were evaluated for potential pathogenicity and their associations with genetic diseases. We also compared our identified variations with the existing global datasets. We generated a compendium of total 38,560 high-confident structural variants, comprising 28,393 deletions, 5030 duplications, 5038 insertions, and 99 inversions. Particularly, we identified around 55% of all these variants were found to be unique to the studied population. Further analysis revealed 134 deletions with predicted pathogenic/likely pathogenic effects and their affected genes were majorly enriched for neurological disease conditions, such as intellectual disability and neurodegenerative diseases. The IndiGenomes dataset helped us to understand the unique spectrum of structural variants in the Indian population. More than half of identified variants were not present in the publicly available global dataset on structural variants. Clinically important deletions identified in IndiGenomes might aid in improving the diagnosis of unsolved genetic diseases, particularly in neurological conditions. Along with basal allele frequency data and clinically important deletions, IndiGenomes data might serve as a baseline resource for future studies on genomic structural variant analysis in the Indian population.

1029 genomes of self-declared healthy individuals from India reveal prevalent and clinically relevant cardiac ion channelopathy variants.

BACKGROUND: The prevalence and genetic spectrum of cardiac channelopathies exhibit population-specific differences. We aimed to understand the spectrum of cardiac channelopathy-associated variations in India, which is characterised by a genetically diverse population and is largely understudied in the context of these disorders. RESULTS: We utilised the IndiGenomes dataset comprising 1029 whole genomes from self-declared healthy individuals as a template to filter variants in 36 genes known to cause cardiac channelopathies. Our analysis revealed 186,782 variants, of which we filtered 470 variants that were identified as possibly pathogenic (440 nonsynonymous, 30 high-confidence predicted loss of function ). About 26% (124 out of 470) of these variants were unique to the Indian population as they were not reported in the global population datasets and published literature. Classification of 470 variants by ACMG/AMP guidelines unveiled 13 pathogenic/likely pathogenic (P/LP) variants mapping to 19 out of the 1029 individuals. Further query of 53 probands in an independent cohort of cardiac channelopathy, using exome sequencing, revealed the presence of 3 out of the 13 P/LP variants. The identification of p.G179Sfs*62, p.R823W and c.420 + 2 T > C variants in KCNQ1, KCNH2 and CASQ2 genes, respectively, validate the significance of the P/LP variants in the context of clinical applicability as well as for large-scale population analysis. CONCLUSION: A compendium of ACMG/AMP classified cardiac channelopathy variants in 1029 self-declared healthy Indian population was created. A conservative genotypic prevalence was estimated to be 0.9-1.8% which poses a huge public health burden for a country with large population size like India. In the majority of cases, these disorders are manageable and the risk of sudden cardiac death can be alleviated by appropriate lifestyle modifications as well as treatment regimens/clinical interventions. Clinical utility of the obtained variants was demonstrated using a cardiac channelopathy patient cohort. Our study emphasises the need for large-scale population screening to identify at-risk individuals and take preventive measures. However, we suggest cautious clinical interpretation to be exercised by taking other cardiac channelopathy risk factors into account.

Genetic landscape of human platelet antigen variants in the Indian population analysed from 1029 whole genomes.

Genetic variants in human platelet antigens (HPAs) considered allo- or auto antigens are associated with various disorders, including neonatal alloimmune thrombocytopenia, platelet transfusion refractoriness and post-transfusion purpura. Although global differences in genotype frequencies were observed, the distributions of HPA variants in the Indian population are largely unknown. This study aims to explore the landscape of HPA variants in India to provide a basis for risk assessment and management of related complications. Population-specific frequencies of genetic variants associated with the 35 classes of HPAs (HPA-1 to HPA-35) were estimated by systematically analysing genomic variations of 1029 healthy Indian individuals as well as from global population genome datasets. Allele frequencies of the most clinically relevant HPA systems in the Indian population were found as follows, HPA-1a - 0.884, HPA-1b - 0.117, HPA-2a - 0.941, HPA-2b - 0.059, HPA-3a - 0.653, HPA-3b - 0.347, HPA-4a - 0.999, HPA-4b - 0.0010, HPA-5a - 0.923, HPA-5b - 0.077, HPA-6a - 0.998, HPA-6b - 0.002, HPA-15a - 0.582 and HPA-15b - 0.418. This study provides the first comprehensive analysis of HPA allele and genotype frequencies using large scale representative whole genome sequencing data of the Indian population.

IndiGenomes: a comprehensive resource of genetic variants from over 1000 Indian genomes.

With the advent of next-generation sequencing, large-scale initiatives for mining whole genomes and exomes have been employed to better understand global or population-level genetic architecture. India encompasses more than 17% of the world population with extensive genetic diversity, but is under-represented in the global sequencing datasets. This gave us the impetus to perform and analyze the whole genome sequencing of 1029 healthy Indian individuals under the pilot phase of the 'IndiGen' program. We generated a compendium of 55,898,122 single allelic genetic variants from geographically distinct Indian genomes and calculated the allele frequency, allele count, allele number, along with the number of heterozygous or homozygous individuals. In the present study, these variants were systematically annotated using publicly available population databases and can be accessed through a browsable online database named as 'IndiGenomes' http://clingen.igib.res.in/indigen/. The IndiGenomes database will help clinicians and researchers in exploring the genetic component underlying medical conditions. Till date, this is the most comprehensive genetic variant resource for the Indian population and is made freely available for academic utility. The resource has also been accessed extensively by the worldwide community since it's launch.

Spectrum of rare and common mitochondrial DNA variations from 1029 whole genomes of self-declared healthy individuals from India.

Mitochondrial disorders are a class of heterogeneous disorders caused by genetic variations in the mitochondrial genome (mtDNA) as well as the nuclear genome. The spectrum of mtDNA variants remains unexplored in the Indian population. In the present study, we have cataloged 2689 high confidence single nucleotide variants, small insertions and deletions in mtDNA in 1029 healthy Indian individuals. We found a major proportion (76.5 %) of the variants being rare (AF<=0.005) in the studied population. Intriguingly, we found two 'confirmed' pathogenic variants (m.1555 A>G and m.14484 T>C) with a frequency of ∼1 in 250 individuals in our dataset. The high carrier frequency underscores the need for screening of the mtDNA pathogenic mutations in newborns in India. Interestingly, our analysis also revealed 202 variants in our dataset which have been 'reported' in disease cases as per the MITOMAP database. Additionally, we found the frequency of haplogroup M (52.2 %) to be the highest among all the 18 top-level haplogroups found in our dataset. In comparison to the global population datasets, 20 unique mtDNA variants are found in the Indian population. We hope the whole genome sequencing based compendium of mtDNA variants along with their allele frequencies and heteroplasmy levels in the Indian population will drive additional genome scale studies for mtDNA. Furthermore, the identification of clinically relevant variants in our dataset will aid in better clinical interpretation of the variants in mitochondrial disorders.

Understanding the variant landscape, and genetic epidemiology of Multiple Endocrine Neoplasia in India.

PURPOSE: Multiple Endocrine Neoplasia (MEN) is a group of familial cancer syndromes that encompasses several types of endocrine tumors differentiated by genetic mutations in RET, MEN1 and CDKN1B genes. Accurate diagnosis of MEN subtypes can thus be performed through genetic testing. However, MEN variants remain largely understudied in Indian populations. Additionally, few dedicated resources to understand these disorders currently exist. METHODS: Using the gold-standard ACMG/AMP guidelines, we systematically classified variants reported across the three genes in the IndiGen dataset, and established the genetic epidemiology of MEN in the Indian population. We further classified ClinVar and Mastermind variants and compiled all into a database. Finally, we designed a multiplex primer panel for rapid variant identification. RESULTS: We have established the genetic prevalence of MEN as the following: 1 in 1026 individuals is likely to be afflicted with MEN linked with pathogenic RET mutations. We have further created the MAPVar database containing 3280 ACMG-classified variants freely accessible at: https://clingen.igib.res.in/MAPVar/ . Finally, our NGS primer panel covers 33 exonic regions across two pools through 38 amplicons with a total amplified region of 65 kb. CONCLUSION: Our work establishes that MEN is a prevalent disorder in India. The rare nature of Indian variants underscores the need of genomic and functional studies to establish a more comprehensive variant landscape. Additionally, our panel offers a means of cost-effective genetic testing, and the MAPVar database a ready reference to aid in a better understanding of variant pathogenicity in clinical as well as research settings.

The genomic landscape of CYP2D6 variation in the Indian population.

Aim: The CYP2D6 gene is highly polymorphic, causing large interindividual variability in the metabolism of several clinically important drugs. Materials & methods: The authors investigated the diversity and distribution of CYP2D6 alleles in Indians using whole genome sequences (N = 1518). Functional consequences were assessed using pathogenicity scores and molecular dynamics simulations. Results: The analysis revealed population-specific CYP2D6 alleles (*86, *7, *111, *112, *113, *99) and remarkable differences in variant and phenotype frequencies with global populations. The authors observed that one in three Indians could benefit from a dose alteration for psychiatric drugs with accurate CYP2D6 phenotyping. Molecular dynamics simulations revealed large conformational fluctuations, confirming the predicted reduced function of *86 and *113 alleles. Conclusion: The findings emphasize the utility of comprehensive CYP2D6 profiling for aiding precision public health.

Landscape of pharmacogenetic variants associated with non-insulin antidiabetic drugs in the Indian population.

INTRODUCTION: Genetic variants contribute to differential responses to non-insulin antidiabetic drugs (NIADs), and consequently to variable plasma glucose control. Optimal control of plasma glucose is paramount to minimizing type 2 diabetes-related long-term complications. India's distinct genetic architecture and its exploding burden of type 2 diabetes warrants a population-specific survey of NIAD-associated pharmacogenetic (PGx) variants. The recent availability of large-scale whole genomes from the Indian population provides a unique opportunity to generate a population-specific map of NIAD-associated PGx variants. RESEARCH DESIGN AND METHODS: We mined 1029 Indian whole genomes for PGx variants, drug-drug interaction (DDI) and drug-drug-gene interactions (DDGI) associated with 44 NIADs. Population-wise allele frequencies were estimated and compared using Fisher's exact test. RESULTS: Overall, we found 76 known and 52 predicted deleterious common PGx variants associated with response to type 2 diabetes therapy among Indians. We report remarkable interethnic differences in the relative cumulative counts of decreased and increased response-associated alleles across NIAD classes. Indians and South Asians showed a significant excess of decreased metformin response-associated alleles compared with other global populations. Network analysis of shared PGx genes predicts high DDI risk during coadministration of NIADs with other metabolic disease drugs. We also predict an increased CYP2C19-mediated DDGI risk for CYP3A4/3A5-metabolized NIADs, saxagliptin, linagliptin and glyburide when coadministered with proton-pump inhibitors (PPIs). CONCLUSIONS: Indians and South Asians have a distinct PGx profile for antidiabetes drugs, marked by an excess of poor treatment response-associated alleles for various NIAD classes. This suggests the possibility of a population-specific reduced drug response in atleast some NIADs. In addition, our findings provide an actionable resource for accelerating future diabetes PGx studies in Indians and South Asians and reconsidering NIAD dosing guidelines to ensure maximum efficacy and safety in the population.

Genetic landscape of human neutrophil antigen variants in India from population-scale genomes.

Antibodies against human neutrophil antigens (HNAs) play a significant role in various clinical conditions such as neonatal alloimmune neutropenia, transfusion-related acute lung injury, and other nonhemolytic transfusion reactions. This study aims to identify the genotype and allele frequencies of HNAs in the healthy Indian population. Ten genetic variants in four human genes encoding alleles of HNAs class I-V approved by the International Society of Blood Transfusion-Granulocyte Immunobiology Working Party were used in the analysis. Genetic variants from whole genome sequences of 1029 healthy Indian individuals corresponding to HNA alleles were analyzed. The frequencies of the variants were compared with global population datasets using an in-house computational pipeline. In HNA class I, allele frequencies of FCGR3B*01, FCGR3B*02, and FCGR3B*03 encoding HNA-1a, HNA-1b, and HNA-1c were 0.07, 0.8, and 0.13, respectively. HNA class 3 alleles namely SLC44A2*01 (encoding HNA-3a) and SLC44A2*02 (encoding HNA-3b) were found at allele frequencies of 0.78 and 0.22, respectively. The frequencies of ITGAM*01 encoding HNA-4a and ITGAM*02 encoding HNA-4a were 0.95 and 0.05, respectively. Furthermore, allele frequencies of HNA class 5 alleles were 0.32 for ITGAL*01 (encoding HNA-5a) and 0.68 for ITGAL*02 (encoding HNA-5b). Interestingly, it was also found that rs2230433 variant deciding the HNA class 5 alleles, was highly prevalent (78.2%) in the Indian population compared with other global populations. This study presents the first comprehensive report of HNA allele and genotype frequencies in the Indian population using population genome datasets of 1029 individuals. Significant difference was observed in the prevalence of HNA5a and HNA5b in India in comparison to other global populations.

Landscape of Variability in Chemosensory Genes Associated With Dietary Preferences in Indian Population: Analysis of 1029 Indian Genomes.

Perception and preferences for food and beverages determine dietary behaviour and health outcomes. Inherent differences in chemosensory genes, ethnicity, geo-climatic conditions, and sociocultural practices are other determinants. We aimed to study the variation landscape of chemosensory genes involved in perception of taste, texture, odour, temperature and burning sensations through analysis of 1,029 genomes of the IndiGen project and diverse continental populations. SNPs from 80 chemosensory genes were studied in whole genomes of 1,029 IndiGen samples and 2054 from the 1000 Genomes project. Population genetics approaches were used to infer ancestry of IndiGen individuals, gene divergence and extent of differentiation among studied populations. 137,760 SNPs including common and rare variants were identified in IndiGenomes with 62,950 novel (46%) and 48% shared with the 1,000 Genomes. Genes associated with olfaction harbored most SNPs followed by those associated with differences in perception of salt and pungent tastes. Across species, receptors for bitter taste were the most diverse compared to others. Three predominant ancestry groups within IndiGen were identified based on population structure analysis. We also identified 1,184 variants that exhibit differences in frequency of derived alleles and high population differentiation (FST ≥0.3) in Indian populations compared to European, East Asian and African populations. Examples include ADCY10, TRPV1, RGS6, OR7D4, ITPR3, OPRM1, TCF7L2, and RUNX1. This is a first of its kind of study on baseline variations in genes that could govern cuisine designs, dietary preferences and health outcomes. This would be of enormous utility in dietary recommendations for precision nutrition both at population and individual level.

Comprehensive Assessment of Indian Variations in the Druggable Kinome Landscape Highlights Distinct Insights at the Sequence, Structure and Pharmacogenomic Stratum.

India confines more than 17% of the world's population and has a diverse genetic makeup with several clinically relevant rare mutations belonging to many sub-group which are undervalued in global sequencing datasets like the 1000 Genome data (1KG) containing limited samples for Indian ethnicity. Such databases are critical for the pharmaceutical and drug development industry where diversity plays a crucial role in identifying genetic disposition towards adverse drug reactions. A qualitative and comparative sequence and structural study utilizing variant information present in the recently published, largest curated Indian genome database (IndiGen) and the 1000 Genome data was performed for variants belonging to the kinase coding genes, the second most targeted group of drug targets. The sequence-level analysis identified similarities and differences among different populations based on the nsSNVs and amino acid exchange frequencies whereas a comparative structural analysis of IndiGen variants was performed with pathogenic variants reported in UniProtKB Humsavar data. The influence of these variations on structural features of the protein, such as structural stability, solvent accessibility, hydrophobicity, and the hydrogen-bond network was investigated. In-silico screening of the known drugs to these Indian variation-containing proteins reveals critical differences imparted in the strength of binding due to the variations present in the Indian population. In conclusion, this study constitutes a comprehensive investigation into the understanding of common variations present in the second largest population in the world and investigating its implications in the sequence, structural and pharmacogenomic landscape. The preliminary investigation reported in this paper, supporting the screening and detection of ADRs specific to the Indian population could aid in the development of techniques for pre-clinical and post-market screening of drug-related adverse events in the Indian population.

An Alu insertion map of the Indian population: identification and analysis in 1021 genomes of the IndiGen project.

Actively retrotransposing primate-specific Alu repeats display insertion-deletion (InDel) polymorphism through their insertion at new loci. In the global datasets, Indian populations remain under-represented and so do their Alu InDels. Here, we report the genomic landscape of Alu InDels from the recently released 1021 Indian Genomes (IndiGen) (available at https://clingen.igib.res.in/indigen). We identified 9239 polymorphic Alu insertions that include private (3831), rare (3974) and common (1434) insertions with an average of 770 insertions per individual. We achieved an 89% PCR validation of the predicted genotypes in 94 samples tested. About 60% of identified InDels are unique to IndiGen when compared to other global datasets; 23% of sites were shared with both SGDP and HGSVC; among these, 58% (1289 sites) were common polymorphisms in IndiGen. The insertions not only show a bias for genic regions, with a preference for introns but also for the associated genes showing enrichment for processes like cell morphogenesis and neurogenesis (P-value < 0.05). Approximately, 60% of InDels mapped to genes present in the OMIM database. Finally, we show that 558 InDels can serve as ancestry informative markers to segregate global populations. This study provides a valuable resource for baseline Alu InDels that would be useful in population genomics.

An optimized, amplicon-based approach for sequencing of SARS-CoV-2 from patient samples using COVIDSeq assay on Illumina MiSeq sequencing platforms.

Sequencing of SARS-CoV-2 genomes is crucial for understanding the genetic epidemiology of the COVID-19 pandemic. It is also critical for understanding the evolution of the virus and also for the rapid development of diagnostic tools. The present protocol is a modification of the Illumina COVIDSeq test. We describe an amplicon-based next-generation sequencing approach with short turnaround time, adapted for bench-top sequencers like MiSeq, iSeq, and MiniSeq. For complete details on the use and execution of this protocol, please refer to Bhoyar et al. (2021).

Whole genome sequencing identifies novel structural variant in a large Indian family affected with X-linked agammaglobulinemia.

X-linked agammaglobulinemia (XLA, OMIM #300755) is a primary immunodeficiency disorder caused by pathogenic variations in the BTK gene, characterized by failure of development and maturation of B lymphocytes. The estimated prevalence worldwide is 1 in 190,000 male births. Recently, genome sequencing has been widely used in difficult to diagnose and familial cases. We report a large Indian family suffering from XLA with five affected individuals. We performed complete blood count, immunoglobulin assay, and lymphocyte subset analysis for all patients and analyzed Btk expression for one patient and his mother. Whole exome sequencing (WES) for four patients, and whole genome sequencing (WGS) for two patients have been performed. Carrier screening was done for 17 family members using Multiplex Ligation-dependent Probe Amplification (MLPA) and haplotype ancestry mapping using fineSTRUCTURE was performed. All patients had hypogammaglobulinemia and low CD19+ B cells. One patient who underwent Btk estimation had low expression and his mother showed a mosaic pattern. We could not identify any single nucleotide variants or small insertion/ deletions from the WES dataset that correlates with the clinical feature of the patient. Structural variant analysis through WGS data identifies a novel large deletion of 5,296 bp at loci chrX:100,624,323-100,629,619 encompassing exons 3-5 of the BTK gene. Family screening revealed seven carriers for the deletion. Two patients had a successful HSCT. Haplotype mapping revealed a South Asian ancestry. WGS led to identification of the accurate genetic mutation which could help in early diagnosis leading to improved outcomes, prevention of permanent organ damage and improved quality of life, as well as enabling genetic counselling and prenatal diagnosis in the family.

Initial Insights Into the Genetic Epidemiology of SARS-CoV-2 Isolates From Kerala Suggest Local Spread From Limited Introductions.

Coronavirus disease 2019 (COVID-19) rapidly spread from a city in China to almost every country in the world, affecting millions of individuals. The rapid increase in the COVID-19 cases in the state of Kerala in India has necessitated the understanding of SARS-CoV-2 genetic epidemiology. We sequenced 200 samples from patients in Kerala using COVIDSeq protocol amplicon-based sequencing. The analysis identified 166 high-quality single-nucleotide variants encompassing four novel variants and 89 new variants in the Indian isolated SARS-CoV-2. Phylogenetic and haplotype analysis revealed that the virus was dominated by three distinct introductions followed by local spread suggesting recent outbreaks and that it belongs to the A2a clade. Further analysis of the functional variants revealed that two variants in the S gene associated with increased infectivity and five variants mapped in primer binding sites affect the efficacy of RT-PCR. To the best of our knowledge, this is the first and most comprehensive report of SARS-CoV-2 genetic epidemiology from Kerala.

Pharmacogenomic landscape of COVID-19 therapies from Indian population genomes.

Aim: Numerous drugs are being widely prescribed for COVID-19 treatment without any direct evidence for the drug safety/efficacy in patients across diverse ethnic populations. Materials & methods: We analyzed whole genomes of 1029 Indian individuals (IndiGen) to understand the extent of drug-gene (pharmacogenetic), drug-drug and drug-drug-gene interactions associated with COVID-19 therapy in the Indian population. Results: We identified 30 clinically significant pharmacogenetic variants and 73 predicted deleterious pharmacogenetic variants. COVID-19-associated pharmacogenes were substantially overlapped with those of metabolic disorder therapeutics. CYP3A4, ABCB1 and ALB are the most shared pharmacogenes. Fifteen COVID-19 therapeutics were predicted as likely drug-drug interaction candidates when used with four CYP inhibitor drugs. Conclusion: Our findings provide actionable insights for future validation studies and improved clinical decisions for COVID-19 therapy in Indians.

Genetic epidemiology of autoinflammatory disease variants in Indian population from 1029 whole genomes.

BACKGROUND: Autoinflammatory disorders are the group of inherited inflammatory disorders caused due to the genetic defect in the genes that regulates innate immune systems. These have been clinically characterized based on the duration and occurrence of unprovoked fever, skin rash, and patient's ancestry. There are several autoinflammatory disorders that are found to be prevalent in a specific population and whose disease genetic epidemiology within the population has been well understood. However, India has a limited number of genetic studies reported for autoinflammatory disorders till date. The whole genome sequencing and analysis of 1029 Indian individuals performed under the IndiGen project persuaded us to perform the genetic epidemiology of the autoinflammatory disorders in India. RESULTS: We have systematically annotated the genetic variants of 56 genes implicated in autoinflammatory disorder. These genetic variants were reclassified into five categories (i.e., pathogenic, likely pathogenic, benign, likely benign, and variant of uncertain significance (VUS)) according to the American College of Medical Genetics and Association of Molecular pathology (ACMG-AMP) guidelines. Our analysis revealed 20 pathogenic and likely pathogenic variants with significant differences in the allele frequency compared with the global population. We also found six causal founder variants in the IndiGen dataset belonging to different ancestry. We have performed haplotype prediction analysis for founder mutations haplotype that reveals the admixture of the South Asian population with other populations. The cumulative carrier frequency of the autoinflammatory disorder in India was found to be 3.5% which is much higher than reported. CONCLUSION: With such frequency in the Indian population, there is a great need for awareness among clinicians as well as the general public regarding the autoinflammatory disorder. To the best of our knowledge, this is the first and most comprehensive population scale genetic epidemiological study being reported from India.