The South Asian genome

Genetic basis of early onset and progression of type 2 diabetes in South Asians

South Asians develop type 2 diabetes (T2D) early in life and often with normal body mass index (BMI). However, reasons for this are poorly understood because genetic research is largely focused on European ancestry groups. We used recently derived multi-ancestry partitioned polygenic scores (pPSs) to elucidate underlying etiological pathways British Pakistani and British Bangladeshi individuals with T2D (n = 11,678) and gestational diabetes mellitus (GDM) (n = 1,965) in the Genes & Health study (n = 50,556). Beta cell 2 (insulin deficiency) and Lipodystrophy 1 (unfavorable fat distribution) pPSs were most strongly associated with T2D, GDM and younger age at T2D diagnosis. Individuals at high genetic risk of both insulin deficiency and lipodystrophy were diagnosed with T2D 8.2 years earlier with BMI 3 kg m-2 lower compared to those at low genetic risk. The insulin deficiency pPS was associated with poorer HbA1c response to SGLT2 inhibitors. Insulin deficiency and lipodystrophy pPSs were associated with faster progression to insulin dependence and microvascular complications. South Asians had a greater genetic burden from both of these pPSs than white Europeans in the UK Biobank. In conclusion, genetic predisposition to insulin deficiency and lipodystrophy in British Pakistani and British Bangladeshi individuals is associated with earlier onset of T2D, faster progression to complications, insulin dependence and poorer response to medication.

An approach for developing a blood-based screening panel for lung cancer based on clonal hematopoietic mutations

Early detection can significantly reduce mortality due to lung cancer. Presented here is an approach for developing a blood-based screening panel based on clonal hematopoietic mutations. Animal model studies suggest that clonal hematopoietic mutations in tumor infiltrating immune cells can modulate cancer progression, representing potential predictive biomarkers. The goal of this study was to determine if the clonal expansion of these mutations in blood samples could predict the occurrence of lung cancer. A set of 98 potentially pathogenic clonal hematopoietic mutations in tumor infiltrating immune cells were identified using sequencing data from lung cancer samples. These mutations were used as predictors to develop a logistic regression machine learning model. The model was tested on sequencing data from a separate set of 578 lung cancer and 545 non-cancer samples from 18 different cohorts. The logistic regression model correctly classified lung cancer and non-cancer blood samples with 94.12% sensitivity (95% Confidence Interval: 92.20-96.04%) and 85.96% specificity (95% Confidence Interval: 82.98-88.95%). Our results suggest that it may be possible to develop an accurate blood-based lung cancer screening panel using this approach. Unlike most other "liquid biopsies" currently under development, the approach presented here is based on standard sequencing protocols and uses a relatively small number of rationally selected mutations as predictors.

South Asia: The Missing Diverse in Diversity

South Asia, making up around 25% of the world's population, encompasses a wide range of individuals with tremendous genetic and environmental diversity. This region, which spans eight countries, is home to over 4500 anthropologically defined groups that speak numerous languages and have an array of religious beliefs and cultures, making it one of the most diverse places in the world. Much of the region's rich genetic diversity and structure is the result of a complex combination of population history, migration patterns, and endogamous practices. Despite the overwhelming size and diversity, South Asians have often been underrepresented in genetic research, making up less than 2% of the participants in genetic studies. This has led to a lack of population specific understanding of genetic disease risks. We aim to raise awareness about underlying genetic diversity in this ancestry group, call attention to the lack of representation of the group, and to highlight strategies for future studies in South Asians.

In silico identification and functional prediction of differentially expressed genes in South Asian populations associated with type 2 diabetes

Type 2 diabetes (T2D) is one of the major metabolic disorders in humans caused by hyperglycemia and insulin resistance syndrome. Although significant genetic effects on T2D pathogenesis are experimentally proved, the molecular mechanism of T2D in South Asian Populations (SAPs) is still limited. Hence, the current research analyzed two Gene Expression Omnibus (GEO) and 17 Genome-Wide Association Studies (GWAS) datasets associated with T2D in SAP to identify DEGs (differentially expressed genes). The identified DEGs were further analyzed to explore the molecular mechanism of T2D pathogenesis following a series of bioinformatics approaches. Following PPI (Protein-Protein Interaction), 867 potential DEGs and nine hub genes were identified that might play significant roles in T2D pathogenesis. Interestingly, CTNNB1 and RUNX2 hub genes were found to be unique for T2D pathogenesis in SAPs. Then, the GO (Gene Ontology) showed the potential biological, molecular, and cellular functions of the DEGs. The target genes also interacted with different pathways of T2D pathogenesis. In fact, 118 genes (including HNF1A and TCF7L2 hub genes) were directly associated with T2D pathogenesis. Indeed, eight key miRNAs among 2582 significantly interacted with the target genes. Even 64 genes were downregulated by 367 FDA-approved drugs. Interestingly, 11 genes showed a wide range (9-43) of drug specificity. Hence, the identified DEGs may guide to elucidate the molecular mechanism of T2D pathogenesis in SAPs. Therefore, integrating the research findings of the potential roles of DEGs and candidate drug-mediated downregulation of marker genes, future drugs or treatments could be developed to treat T2D in SAPs.

A comprehensive analysis of genetic risk for metabolic syndrome in the Egyptian population via allele frequency investigation and Missense3D predictions

Diabetes mellitus (DM) represents a major health problem in Egypt and worldwide, with increasing numbers of patients with prediabetes every year. Numerous factors, such as obesity, hyperlipidemia, and hypertension, which have recently become serious concerns, affect the complex pathophysiology of diabetes. These metabolic syndrome diseases are highly linked to genetic variability that drives certain populations, such as Egypt, to be more susceptible to developing DM. Here we conduct a comprehensive analysis to pinpoint the similarities and uniqueness among the Egyptian genome reference and the 1000-genome subpopulations (Europeans, Ad-Mixed Americans, South Asians, East Asians, and Africans), aiming at defining the potential genetic risk of metabolic syndromes. Selected approaches incorporated the analysis of the allele frequency of the different populations' variations, supported by genotypes' principal component analysis. Results show that the Egyptian's reference metabolic genes were clustered together with the Europeans', Ad-Mixed Americans', and South-Asians'. Additionally, 8563 variants were uniquely identified in the Egyptian cohort, from those, two were predicted to cause structural damage, namely, CDKAL1: 6_21065070 (A > T) and PPARG: 3_12351660 (C > T) utilizing the Missense3D database. The former is a protein coding gene associated with Type 2 DM while the latter is a key regulator of adipocyte differentiation and glucose homeostasis. Both variants were detected heterozygous in two different Egyptian individuals from overall 110 sample. This analysis sheds light on the unique genetic traits of the Egyptian population that play a role in the DM high prevalence in Egypt. The proposed analysis pipeline -available through GitHub- could be used to conduct similar analysis for other diseases across populations.

A whole-genome reference panel of 14,393 individuals for East Asian populations accelerates discovery of rare functional variants

Underrepresentation of non-European (EUR) populations hinders growth of global precision medicine. Resources such as imputation reference panels that match the study population are necessary to find low-frequency variants with substantial effects. We created a reference panel consisting of 14,393 whole-genome sequences including more than 11,000 Asian individuals. Genome-wide association studies were conducted using the reference panel and a population-specific genotype array of 72,298 subjects for eight phenotypes. This panel yields improved imputation accuracy of rare and low-frequency variants within East Asian populations compared with the largest reference panel. Thirty-nine previously unidentified associations were found, and more than half of the variants were East Asian specific. We discovered genes with rare protein-altering variants, including LTBP1 for height and GPR75 for body mass index, as well as putative regulatory mechanisms for rare noncoding variants with cell type-specific effects. We suggest that this dataset will add to the potential value of Asian precision medicine.

Evaluation of Personalized Skincare Through in-silico Gene Interactive Networks and Cellular Responses to UVR and Oxidative Stress

Purpose

Personalized approaches in dermatology are designed to match the specific requirements based on the individual genetic makeup. One major factor accounting for the differences in skin phenotypes is single nucleotide polymorphism (SNP) within several genes with diverse roles that extend beyond skin tone and pigmentation. Therefore, the cellular sensitivities to the environmental stress and damage linked to extrinsic aging could also underlie the individual characteristics of the skin and dictate the unique skin care requirements. This study aimed to identify the likely biomarkers and molecular signatures expressed in skin cells of different ethnic backgrounds, which could aid further the design of personalized skin products based on specific demands.

Methods

Using data mining and in-silico modeling, the association of SNP-affected genes with three major skin types of European, Asian and African origin was analyzed and compared within the structure-function gene interaction networks. Cultured dermal fibroblasts were subsequently subjected to ultraviolet radiation and oxidative stress and analyzed for DNA damage and senescent markers. The protective applications of two cosmetic ingredients, Resveratrol and Quercetin, were validated in both cellular and in-silico models.

Results

Each skin type was characterized by the presence of SNPs in the genes controlling facultative and constitutive pigmentation, which could also underlie the major differences in responses to photodamage, such as oxidative stress, inflammation, and barrier homeostasis. Skin-type-specific dermal fibroblasts cultured in-vitro demonstrated distinctive sensitivities to ultraviolet radiation and oxidative stress, which could be modulated further by the bioactive compounds with the predicted capacities to interact with some of the genes in the in-silico models.

Conclusion

Evaluation of the SNP-affected gene networks and likely sensitivities of skin cells, defined as low threshold levels to extrinsic stress factors, can provide a valuable tool for the design and formulation of personalized skin products that match more accurately diverse ethnic backgrounds.

Cardiovascular Disease in South Asian Immigrants: a Review of Dysfunctional HDL as a Potential Marker

South Asians (SAs) account for a quarter of the world's population and are one of the fastest-growing immigrant groups in the United States (US). South Asian Immigrants (SAIs) are disproportionately more at risk of developing cardiovascular disease (CVD) than other ethnic/racial groups. Atherosclerosis is a chronic inflammatory disorder and is the major cause of CVD. Traditional CVD risk factors, though important, do not fully explain the elevated risk of CVD in SAIs. High-density lipoproteins (HDLs) are heterogeneous lipoproteins that modify their composition and functionality depending on physiological or pathological conditions. With its cholesterol efflux, anti-inflammatory, and antioxidant functions, HDL is traditionally considered a protective factor for CVD. However, its functions can be compromised under pathological conditions, such as chronic inflammation, making it dysfunctional (Dys-HDL). SAIs have a high prevalence of type 2 diabetes and metabolic syndrome, which may further promote Dys-HDL. This review explores the potential association between Dys-HDL and CVD in SAIs and presents current literature discussing the role of Dys-HDL in CVD.

Burden of Type 2 Diabetes and Associated Cardiometabolic Traits and Their Heritability Estimates in Endogamous Ethnic Groups of India: Findings From the INDIGENIUS Consortium

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.

Identification of genetic effects underlying type 2 diabetes in South Asian and European populations

South Asians are at high risk of developing type 2 diabetes (T2D). We carried out a genome-wide association meta-analysis with South Asian T2D cases (n = 16,677) and controls (n = 33,856), followed by combined analyses with Europeans (neff = 231,420). We identify 21 novel genetic loci for significant association with T2D (P = 4.7 × 10-8 to 5.2 × 10-12), to the best of our knowledge at the point of analysis. The loci are enriched for regulatory features, including DNA methylation and gene expression in relevant tissues, and highlight CHMP4B, PDHB, LRIG1 and other genes linked to adiposity and glucose metabolism. A polygenic risk score based on South Asian-derived summary statistics shows ~4-fold higher risk for T2D between the top and bottom quartile. Our results provide further insights into the genetic mechanisms underlying T2D, and highlight the opportunities for discovery from joint analysis of data from across ancestral populations.

Overview of the Americas’ First Peopling from a Patrilineal Perspective: New Evidence from the Southern Continent

Uniparental genetic systems are unique sex indicators and complement the study of autosomal diversity by providing landmarks of human migrations that repeatedly shaped the structure of extant populations. Our knowledge of the variation of the male-specific region of the Y chromosome in Native Americans is still rather scarce and scattered, but by merging sequence information from modern and ancient individuals, we here provide a comprehensive and updated phylogeny of the distinctive Native American branches of haplogroups C and Q. Our analyses confirm C-MPB373, C-P39, Q-Z780, Q-M848, and Q-Y4276 as the main founding haplogroups and identify traces of unsuccessful (pre-Q-F1096) or extinct (C-L1373*, Q-YP4010*) Y-chromosome lineages, indicating that haplogroup diversity of the founder populations that first entered the Americas was greater than that observed in the Indigenous component of modern populations. In addition, through a diachronic and phylogeographic dissection of newly identified Q-M848 branches, we provide the first Y-chromosome insights into the early peopling of the South American hinterland (Q-BY104773 and Q-BY15730) and on overlying inland migrations (Q-BY139813).

Type 2 diabetes risks and determinants in second-generation migrants and mixed ethnicity people of South Asian and African Caribbean descent in the UK

AIMS/HYPOTHESIS

Excess risks of type 2 diabetes in UK South Asians (SA) and African Caribbeans (AC) compared with Europeans remain unexplained. We studied risks and determinants of type 2 diabetes in first- and second-generation (born in the UK) migrants, and in those of mixed ethnicity.

METHODS

Data from the UK Biobank, a population-based cohort of ~500,000 participants aged 40-69 at recruitment, were used. Type 2 diabetes was assigned using self-report and HbA1c. Ethnicity was both self-reported and genetically assigned using admixture level scores. European, mixed European/South Asian (MixESA), mixed European/African Caribbean (MixEAC), SA and AC groups were analysed, matched for age and sex to enable comparison. In the frames of this cross-sectional study, we compared type 2 diabetes in second- vs first-generation migrants, and mixed ethnicity vs non-mixed groups. Risks and explanations were analysed using logistic regression and mediation analysis, respectively.

RESULTS

Type 2 diabetes prevalence was markedly elevated in SA (599/3317 = 18%) and AC (534/4180 = 13%) compared with Europeans (140/3324 = 4%). Prevalence was lower in second- vs first-generation SA (124/1115 = 11% vs 155/1115 = 14%) and AC (163/2200 = 7% vs 227/2200 = 10%). Favourable adiposity (i.e. lower waist/hip ratio or BMI) contributed to lower risk in second-generation migrants. Type 2 diabetes in mixed populations (MixESA: 52/831 = 6%, MixEAC: 70/1045 = 7%) was lower than in comparator ethnic groups (SA: 18%, AC: 13%) and higher than in Europeans (4%). Greater socioeconomic deprivation accounted for 17% and 42% of the excess type 2 diabetes risk in MixESA and MixEAC compared with Europeans, respectively. Replacing self-reported with genetically assigned ethnicity corroborated the mixed ethnicity analysis.

CONCLUSIONS/INTERPRETATION

Type 2 diabetes risks in second-generation SA and AC migrants are a fifth lower than in first-generation migrants. Mixed ethnicity risks were markedly lower than SA and AC groups, though remaining higher than in Europeans. Distribution of environmental risk factors, largely obesity and socioeconomic status, appears to play a key role in accounting for ethnic differences in type 2 diabetes risk.

Genotypes of informative loci from 1000 Genomes data allude evolution and mixing of human populations

Principal Component Analysis (PCA) projects high-dimensional genotype data into a few components that discern populations. Ancestry Informative Markers (AIMs) are a small subset of SNPs capable of distinguishing populations. We integrate these two approaches by proposing an algorithm to identify necessary informative loci whose removal from the data deteriorates the PCA structure. Unlike classical AIMs, necessary informative loci densely cover the genome, hence can illuminate the evolution and mixing history of populations. We conduct a comprehensive analysis to the genotype data of the 1000 Genomes Project using necessary informative loci. Projections along the top seven principal components demarcate populations at distinct geographic levels. Millions of necessary informative loci along each PC are identified. Population identities along each PC are approximately determined by weighted sums of minor (or major) alleles over the informative loci. Variations of allele frequencies are aligned with the history and direction of population evolution. The population distribution of projections along the top three PCs is recapitulated by a simple demographic model based on several waves of founder population separation and mixing. Informative loci possess locational concentration in the genome and functional enrichment. Genes at two hot spots encompassing dense PC 7 informative loci exhibit differential expressions among European populations. The mosaic of local ancestry in the genome of a mixed descendant from multiple populations can be inferred from partial PCA projections of informative loci. Finally, informative loci derived from the 1000 Genomes data well predict the projections of an independent genotype data of South Asians. These results demonstrate the utility and relevance of informative loci to investigate human evolution.

Sequencing and comparative genome analysis of three Indians

Remarkable advancement in DNA sequencing (NGS) technology has made personal genome analysis feasible and affordable. Here we present the whole genome sequencing and analysis of three individuals, two males and one female, from different parts of India. Comparison with the Reference Human Genome and the variant database showed a total of 4.0-4.85 million variants, primarily single nucleotide variants (SNVs), 350-600 K small insertions and deletions (INDELs), and previously unreported novel variants. The analysis of Y-chromosome and mitochondrial haplogroups revealed that the ancestors of the individual arrived on the subcontinent at very different times using distinctly different migration routes. Approximately, 500,000 novel SNPs and about 89,000 novel INDELs have been submitted to the NCBI as novel variants. PCA and Admix analysis revealed that the IHGP03, a Mizoram male from the Northeast region, is strikingly different from the other two Indian genomes. Collectively, the data suggest the complexity of the Indian population admix developed from several distinct waves of human migration over tens of thousands of years.

Do Diabetes Mellitus Differences Exist within Generations? Three Generations of Moluccans in the Netherlands

Background: Diabetes mellitus (DM) is known to be more prevalent among migrants compared to their host populations. It is unclear whether DM prevalence differs between generations among migrants. We investigated the differences in DM prevalence among three generations of Moluccans, who have been living for over 65 years in the Netherlands, compared to the Dutch population. Methods: In this cross-sectional study, data of a healthcare insurance database on hospital and medication use (Achmea Health Database) were used. The dataset contained 5394 Moluccans and 52,880 Dutch persons of all ages. DM differences were assessed by means of logistic regression, adjusting for age, sex, urbanization, and area socio-economic status. Results: The prevalence of DM was higher in all generations of Moluccans compared to the Dutch. The adjusted odds ratios (AORs) for DM were significantly higher in total group of Moluccans compared to the Dutch (AOR 1.60, 95% CI 1.42–1.80) and across the first and second generation of Moluccans compared to the Dutch (first generation (1.73, 1.47–2.04) and second generation (1.44, 1.19–1.75). Higher AOR were found for first generation men (1.55, 1.22–1.97) and first (1.90, 1.52–2.37) and second (1.63, 1.24–2.13) generation Moluccan women compared to the Dutch. AOR for the third generation Moluccans was increased to a similar extent (1.51, 0.97–2.34), although not statistical significant. Conclusions: Our findings show higher odds of DM across generations of Moluccans compared to the Dutch. DM prevention strategies for minorities should be targeted at all migrant generations in host countries.

The Burden of Atherosclerotic Cardiovascular Disease in South Asians Residing in Canada: A Reflection From the South Asian Heart Alliance

South Asians (SAs), originating from the Indian subcontinent (India, Pakistan, Sri Lanka, Bangladesh, Nepal, and Bhutan), represent one quarter of the global population and are the largest visible minority in Canada. SAs experience the highest rates of coronary artery disease in Canada. Although conventional cardiovascular risk factors remain predictive in SA, the excess risk is not fully explained by these risk factors alone. Abdominal obesity, metabolic syndrome, and insulin resistance likely contribute a greater risk in SAs than in other populations. The South Asian Heart Alliance has been recently formed to investigate and recommend the best strategies for the prevention of cardiometabolic disease in SAs in Canada. This topic review represents a comprehensive overview of the magnitude of cardiovascular disease in SAs in Canada, with a review of conventional and novel risk markers in the SA population. Both primary and secondary prevention strategies are suggested and when possible, adapted specifically for the SA population. The need for SAs and their healthcare professionals to be more aware of the problem and potential solutions, along with the need for population-specific research, is highlighted.

Sivasubbu S, Scaria V. Genomics of rare genetic diseases-experiences from India

Home to a culturally heterogeneous population, India is also a melting pot of genetic diversity. The population architecture characterized by multiple endogamous groups with specific marriage patterns, including the widely prevalent practice of consanguinity, not only makes the Indian population distinct from rest of the world but also provides a unique advantage and niche to understand genetic diseases. Centuries of genetic isolation of population groups have amplified the founder effects, contributing to high prevalence of recessive alleles, which translates into genetic diseases, including rare genetic diseases in India.Rare genetic diseases are becoming a public health concern in India because a large population size of close to a billion people would essentially translate to a huge disease burden for even the rarest of the rare diseases. Genomics-based approaches have been demonstrated to accelerate the diagnosis of rare genetic diseases and reduce the socio-economic burden. The Genomics for Understanding Rare Diseases: India Alliance Network (GUaRDIAN) stands for providing genomic solutions for rare diseases in India. The consortium aims to establish a unique collaborative framework in health care planning, implementation, and delivery in the specific area of rare genetic diseases. It is a nation-wide collaborative research initiative catering to rare diseases across multiple cohorts, with over 240 clinician/scientist collaborators across 70 major medical/research centers. Within the GUaRDIAN framework, clinicians refer rare disease patients, generate whole genome or exome datasets followed by computational analysis of the data for identifying the causal pathogenic variations. The outcomes of GUaRDIAN are being translated as community services through a suitable platform providing low-cost diagnostic assays in India. In addition to GUaRDIAN, several genomic investigations for diseased and healthy population are being undertaken in the country to solve the rare disease dilemma.In summary, rare diseases contribute to a significant disease burden in India. Genomics-based solutions can enable accelerated diagnosis and management of rare diseases. We discuss how a collaborative research initiative such as GUaRDIAN can provide a nation-wide framework to cater to the rare disease community of India.

Evaluation of a rare glucose-dependent insulinotropic polypeptide receptor variant in a patient with diabetes

AIMS

Glucose-dependent insulinotropic polypeptide (GIP) is an incretin hormone that augments insulin secretion in pancreatic β-cells via its glucose-dependent insulinotropic polypeptide receptor (GIPR). Recent genome-wide association studies identified a single nucleotide variant (SNV) in the GIPR encoding gene (GIPR), rs1800437, that is associated with obesity and insulin resistance. In the present study, we tested whether GIPR variants contribute to obesity and disturb glucose homeostasis or diabetes in specific patient populations.

MATERIALS AND METHODS

Exon sequencing of GIPR was performed in 164 children with obesity and insulin resistance and in 80 children with paediatric-onset diabetes of unknown origin. The Study of Health in Pomerania (SHIP) cohort, comprising 8320 adults, was screened for the GIPR variant Arg217Leu. GIPR variants were expressed in COS-7 cells and cAMP production was measured upon stimulation with GIP. Cell surface expression was determined by ELISA. Protein homology modelling of the GIPR variants was performed to extract three-dimensional information of the receptor.

RESULTS

A heterozygous missense GIPR variant Arg217Leu (rs200485112) was identified in a patient of Asian ancestry. Functional characterization of Arg217Leu revealed reduced surface expression and signalling after GIP challenge. The homology model of the GIPR structure supports the observed functional relevance of Arg217Leu.

CONCLUSION

In vitro functional studies and protein homology modelling indicate a potential relevance of the GIPR variant Arg217Leu in receptor function. The heterozygous variant displayed partial co-segregation with diabetes. Based on these findings, we suggest that GIPR variants may play a role in disturbed glucose homeostasis and may be of clinical relevance in homozygous patients.

Population-scale genomics-Enabling precision public health

The current excitement for affordable genomics technologies and national precision medicine initiatives marks a turning point in worldwide healthcare practices. The last decade of global population sequencing efforts has defined the enormous extent of genetic variation in the human population resulting in insights into differential disease burden and response to therapy within and between populations. Population-scale pharmacogenomics helps to provide insights into the choice of optimal therapies and an opportunity to estimate, predict and minimize adverse events. Such an approach can potentially empower countries to formulate national selection and dosing policies for therapeutic agents thereby promoting public health with precision. We review the breadth and depth of worldwide population-scale sequencing efforts and its implications for the implementation of clinical pharmacogenetics toward making precision medicine a reality.

Low quality cardiovascular care is important coronary risk factor in India

Global Burden of Disease study has reported that cardiovascular and ischemic heart disease (IHD) mortality has increased by 34% in last 25 years in India. It has also been reported that despite having lower coronary risk factors compared to developed countries, incident cardiovascular mortality, cardiovascular events and case-fatality are greater in India. Reasons for the increasing trends and high mortality have not been studied. There is evidence that social determinants of IHD risk factors are widely prevalent and increasing. Epidemiological studies have reported low control rates of hypertension, hypercholesterolemia, diabetes and smoking/tobacco. Registries have reported greater mortality of acute coronary syndrome in India compared to developed countries. Secondary prevention therapies have significant gaps. Low quality cardiovascular care is an important risk factor in India. Package of interventions focusing on fiscal, intersectoral and public health measures, improvement of health services at community, primary and secondary healthcare levels and appropriate referral systems to specialized hospitals is urgently required.

Atherosclerotic Cardiovascular Disease in South Asians in the United States: Epidemiology, Risk Factors, and Treatments: A Scientific Statement From the American Heart Association

South Asians (from Bangladesh, Bhutan, India, the Maldives, Nepal, Pakistan, and Sri Lanka) make up one quarter of the world's population and are one of the fastest-growing ethnic groups in the United States. Although native South Asians share genetic and cultural risk factors with South Asians abroad, South Asians in the United States can differ in socioeconomic status, education, healthcare behaviors, attitudes, and health insurance, which can affect their risk and the treatment and outcomes of atherosclerotic cardiovascular disease (ASCVD). South Asians have higher proportional mortality rates from ASCVD compared with other Asian groups and non-Hispanic whites, in contrast to the finding that Asian Americans (Asian Indian, Chinese, Filipino, Japanese, Korean, and Vietnamese) aggregated as a group are at lower risk of ASCVD, largely because of the lower risk observed in East Asian populations. Literature relevant to South Asian populations regarding demographics and risk factors, health behaviors, and interventions, including physical activity, diet, medications, and community strategies, is summarized. The evidence to date is that the biology of ASCVD is complex but is no different in South Asians than in any other racial/ethnic group. A majority of the risk in South Asians can be explained by the increased prevalence of known risk factors, especially those related to insulin resistance, and no unique risk factors in this population have been found. This scientific statement focuses on how ASCVD risk factors affect the South Asian population in order to make recommendations for clinical strategies to reduce disease and for directions for future research to reduce ASCVD in this population.

Obesity genetics: insights from the Pakistani population

The Pakistani population is extensively diverse, indicating a genetic admixture of European and Central/West Asian migrants with indigenous South Asian gene pools. Pakistanis are organized in different ethnicities/castes based on cultural, linguistic and geographical origin. While Pakistan is facing a rapid nutritional transition, the rising prevalence of obesity is driving a growing burden of health complications and mortality. This represents a unique opportunity for the research community to study the interplay between obesogenic environmental changes and obesity predisposing genes in the time frame of one generation. This review recapitulates the ancestral origins of Pakistani population, the societal determinants of the rise in obesity and its governmental management. We describe the contribution of syndromic, monogenic non-syndromic and polygenic obesity genes identified in the Pakistani population. We then discuss the utility of gene identification approaches based on large consanguineous families and original gene × environment interaction study designs in discovering new obesity genes and causal pathways. Elucidation of the genetic basis of obesity in the Pakistani population may result in improved methods of obesity prevention and treatment globally.

Whole genome variant analysis in three ethnically diverse Indians

India represents an amazing confluence of geographically, linguistically and socially disparate ethnic populations (Indian Genome Variation Consortium, J Genet 87:3-20, 2008). Understanding the genetic diversity of Indian population remains a daunting task. In this paper we present detailed analysis of genomic variations (high-depth coverage (~ 30×) using Illumina Hiseq 2000 platform) from three healthy Indian male individuals each belonging to three geographically delineated regions and linguistic phylum viz. high altitude region of Ladakh (Tibeto-Burman linguistic phylum), sub mountainous region of Kumaun (Indo-European linguistic phylum) and sea level region of Telangana (Dravidian linguistic phylum) for probing the extent of genetic diversity in our population. The sequencing analysis provided high quality data (~ 95% of the total reads aligned to the human reference genome for each sample) and very good alignment quality (> 80% of the filtered mapped reads had a quality score of 60). A total of 4.3, 3.7 and 4.3 million single nucleotide variations were identified in the genome of high altitude, sub mountainous and sea level respectively by comparing with human reference genome. Approximately 17.3, 18.2, 17.4% of the variants were unique in the three genomes. The study identified many novel variations in the three diverse genomes (132,970 in Ladakh, 112,317 in Kumaun and 128,881 in Telangana individual) and is an important resource for creating a baseline and a comprehensive catalogue of human genomic variation across the Indian as well as the Asian continent.

SAGE: a comprehensive resource of genetic variants integrating South Asian whole genomes and exomes

South Asia is home to \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$\sim $\end{document}20% of the world population and characterized by distinct ethnic, linguistic, cultural and genetic lineages. Only limited representative samples from the region have found its place in large population-scale international genome projects. The recent availability of genome scale data from multiple populations and datasets from South Asian countries in public domain motivated us to integrate the data into a comprehensive resource. In the present study, we have integrated a total of six datasets encompassing 1213 human exomes and genomes to create a compendium of 154 814 557 genetic variants and adding a total of 69 059 255 novel variants. The variants were systematically annotated using public resources and along with the allele frequencies are available as a browsable-online resource South Asian genomes and exomes. As a proof of principle application of the data and resource for genetic epidemiology, we have analyzed the pathogenic genetic variants causing retinitis pigmentosa. Our analysis reveals the genetic landscape of the disease and suggests subset of genetic variants to be highly prevalent in South Asia.

Pharmacogenetic landscape of DPYD variants in south Asian populations by integration of genome-scale data

AIM

Adverse drug reactions to 5-Fluorouracil(5-FU) is frequent and largely attributable to genetic variations in the DPYD gene, a rate limiting enzyme that clears 5-FU. The study aims at understanding the pharmacogenetic landscape of DPYD variants in south Asian populations.

MATERIALS & METHODS

Systematic analysis of population scale genome wide datasets of over 3000 south Asians was performed. Independent evaluation was performed in a small cohort of patients.

RESULTS

Our analysis revealed significant differences in the the allelic distribution of variants in different ethnicities.

CONCLUSIONS

This is the first and largest genetic map the DPYD variants associated with adverse drug reaction to 5-FU in south Asian population. Our study highlights ethnic differences in allelic frequencies.

Opportunities and challenges in phenotypic drug discovery: an industry perspective

Phenotypic drug discovery (PDD) approaches do not rely on knowledge of the identity of a specific drug target or a hypothesis about its role in disease, in contrast to the target-based strategies that have been widely used in the pharmaceutical industry in the past three decades. However, in recent years, there has been a resurgence in interest in PDD approaches based on their potential to address the incompletely understood complexity of diseases and their promise of delivering first-in-class drugs, as well as major advances in the tools for cell-based phenotypic screening. Nevertheless, PDD approaches also have considerable challenges, such as hit validation and target deconvolution. This article focuses on the lessons learned by researchers engaged in PDD in the pharmaceutical industry and considers the impact of 'omics' knowledge in defining a cellular disease phenotype in the era of precision medicine, introducing the concept of a chain of translatability. We particularly aim to identify features and areas in which PDD can best deliver value to drug discovery portfolios and can contribute to the identification and the development of novel medicines, and to illustrate the challenges and uncertainties that are associated with PDD in order to help set realistic expectations with regard to its benefits and costs.

Differentiated demographic histories and local adaptations between Sherpas and Tibetans

BACKGROUND

The genetic relationships reported by recent studies between Sherpas and Tibetans are controversial. To gain insights into the population history and the genetic basis of high-altitude adaptation of the two groups, we analyzed genome-wide data in 111 Sherpas (Tibet and Nepal) and 177 Tibetans (Tibet and Qinghai), together with available data from present-day human populations.

RESULTS

Sherpas and Tibetans show considerable genetic differences and can be distinguished as two distinct groups, even though the divergence between them (~3200-11,300 years ago) is much later than that between Han Chinese and either of the two groups (~6200-16,000 years ago). Sub-population structures exist in both Sherpas and Tibetans, corresponding to geographical or linguistic groups. Differentiation of genetic variants between Sherpas and Tibetans associated with adaptation to either high-altitude or ultraviolet radiation were identified and validated by genotyping additional Sherpa and Tibetan samples.

CONCLUSIONS

Our analyses indicate that both Sherpas and Tibetans are admixed populations, but the findings do not support the previous hypothesis that Tibetans derive their ancestry from Sherpas and Han Chinese. Compared to Tibetans, Sherpas show higher levels of South Asian ancestry, while Tibetans show higher levels of East Asian and Central Asian/Siberian ancestry. We propose a new model to elucidate the differentiated demographic histories and local adaptations of Sherpas and Tibetans.

Cardiometabolic disease in South Asians: A global health concern in an expanding population

Cardiovascular disease (CVD) is one of the main causes of mortality and morbidity worldwide. As an emerging population, South Asians (SAs) bear a disproportionately high burden of CVD relative to underlying classical risk factors, partly attributable to a greater prevalence of insulin resistance and diabetes and distinct genetic and epigenetic influences. While the phenotypic distinctions between SAs and other ethnicities in CVD risk are becoming increasingly clear, the biology of these conditions remains an area of active investigation, with emerging studies involving metabolism, genetic variation and epigenetic modifiers (e.g., extracellular RNA). In this review, we describe the current literature on prevalence, prognosis and CVD risk in SAs, and provide a landscape of translational research in this field toward ameliorating CVD risk in SAs.

Trends in Next-Generation Sequencing and a New Era for Whole Genome Sequencing

This article is a mini-review that provides a general overview for next-generation sequencing (NGS) and introduces one of the most popular NGS applications, whole genome sequencing (WGS), developed from the expansion of human genomics. NGS technology has brought massively high throughput sequencing data to bear on research questions, enabling a new era of genomic research. Development of bioinformatic software for NGS has provided more opportunities for researchers to use various applications in genomic fields. De novo genome assembly and large scale DNA resequencing to understand genomic variations are popular genomic research tools for processing a tremendous amount of data at low cost. Studies on transcriptomes are now available, from previous-hybridization based microarray methods. Epigenetic studies are also available with NGS applications such as whole genome methylation sequencing and chromatin immunoprecipitation followed by sequencing. Human genetics has faced a new paradigm of research and medical genomics by sequencing technologies since the Human Genome Project. The trend of NGS technologies in human genomics has brought a new era of WGS by enabling the building of human genomes databases and providing appropriate human reference genomes, which is a necessary component of personalized medicine and precision medicine.

Recent Advances in the Molecular Genetics of Familial Hypertrophic Cardiomyopathy in South Asian Descendants

The South Asian population, numbered at 1.8 billion, is estimated to comprise around 20% of the global population and 1% of the American population, and has one of the highest rates of cardiovascular disease. While South Asians show increased classical risk factors for developing heart failure, the role of population-specific genetic risk factors has not yet been examined for this group. Hypertrophic cardiomyopathy (HCM) is one of the major cardiac genetic disorders among South Asians, leading to contractile dysfunction, heart failure, and sudden cardiac death. This disease displays autosomal dominant inheritance, and it is associated with a large number of variants in both sarcomeric and non-sarcomeric proteins. The South Asians, a population with large ethnic diversity, potentially carries region-specific polymorphisms. There is high variability in disease penetrance and phenotypic expression of variants associated with HCM. Thus, extensive studies are required to decipher pathogenicity and the physiological mechanisms of these variants, as well as the contribution of modifier genes and environmental factors to disease phenotypes. Conducting genotype-phenotype correlation studies will lead to improved understanding of HCM and, consequently, improved treatment options for this high-risk population. The objective of this review is to report the history of cardiovascular disease and HCM in South Asians, present previously published pathogenic variants, and introduce current efforts to study HCM using induced pluripotent stem cell-derived cardiomyocytes, next-generation sequencing, and gene editing technologies. The authors ultimately hope that this review will stimulate further research, drive novel discoveries, and contribute to the development of personalized medicine with the aim of expanding therapeutic strategies for HCM.

Social and health epidemiology of immigrants in Germany: past, present and future

Germany has experienced different forms of immigration for many decades. At the end of and after the Second World War, refugees, displaced persons and German resettlers constituted the largest immigrant group. In the 1950s, labor migration started, followed by family reunification. There has been a constant migration of refugees and asylum seekers reaching peaks in the early 1990s as well as today. Epidemiological research has increasingly considered the health, and the access to health care, of immigrants and people with migration background. In this narrative review we discuss the current knowledge on health of immigrants in Germany. The paper is based on a selective literature research with a focus on studies using representative data from the health reporting system.

Our review shows that immigrants in Germany do not suffer from different diseases than non-immigrants, but they differ in their risk for certain diseases, in the resources to cope with theses risk and regarding access to treatment. We also identified the need for differentiation within the immigrant population, considering among others social and legal status, country of origin and duration of stay. Though most of the studies acknowledge the need for differentiation, the lack of data currently rules out analyses accounting for the existing diversity and thus a full understanding of health inequalities related to migration to Germany.

The Elevated Susceptibility to Diabetes in India: An Evolutionary Perspective

India has rapidly become a "diabetes capital" of the world, despite maintaining high rates of under-nutrition. Indians develop diabetes at younger age and at lower body weights than other populations. Here, we interpret these characteristics in terms of a "capacity-load" model of glucose homeostasis. Specifically, we assume that glycemic control depends on whether the body's "metabolic capacity," referring to traits, such as pancreatic insulin production and muscle glucose clearance, is able to resolve the "metabolic load" generated by high levels of body fat, high dietary glycemic load, and sedentary behavior. We employ data from modern cohorts to support the model and the interpretation that elevated diabetic risk among Indian populations results from the high metabolic load imposed by westernized lifestyles acting on a baseline of low metabolic capacity. We attribute this low metabolic capacity to the low birth weight characteristic of Indian populations, which is associated with short stature and low lean mass in adult life. Using stature as a marker of metabolic capacity, we review archeological and historical evidence to highlight long-term declines in Indian stature associated with adaptation to several ecological stresses. Underlying causes may include increasing population density following the emergence of agriculture, the spread of vegetarian diets, regular famines induced by monsoon failure, and the undermining of agricultural security during the colonial period. The reduced growth and thin physique that characterize Indian populations elevate susceptibility to truncal obesity, and increase the metabolic penalties arising from sedentary behavior and high glycemic diets. Improving metabolic capacity may require multiple generations; in the meantime, efforts to reduce the metabolic load will help ameliorate the situation.

Investigation of Genetic Variation Underlying Central Obesity amongst South Asians

South Asians are 1/4 of the world's population and have increased susceptibility to central obesity and related cardiometabolic disease. Knowledge of genetic variants affecting risk of central obesity is largely based on genome-wide association studies of common SNPs in Europeans. To evaluate the contribution of DNA sequence variation to the higher levels of central obesity (defined as waist hip ratio adjusted for body mass index, WHR) among South Asians compared to Europeans we carried out: i) a genome-wide association analysis of >6M genetic variants in 10,318 South Asians with focused analysis of population-specific SNPs; ii) an exome-wide association analysis of ~250K SNPs in protein-coding regions in 2,637 South Asians; iii) a comparison of risk allele frequencies and effect sizes of 48 known WHR SNPs in 12,240 South Asians compared to Europeans. In genome-wide analyses, we found no novel associations between common genetic variants and WHR in South Asians at P<5x10-8; variants showing equivocal association with WHR (P<1x10-5) did not replicate at P<0.05 in an independent cohort of South Asians (N = 1,922) or in published, predominantly European meta-analysis data. In the targeted analyses of 122,391 population-specific SNPs we also found no associations with WHR in South Asians at P<0.05 after multiple testing correction. Exome-wide analyses showed no new associations between genetic variants and WHR in South Asians, either individually at P<1.5x10-6 or grouped by gene locus at P<2.5x10-6. At known WHR loci, risk allele frequencies were not higher in South Asians compared to Europeans (P = 0.77), while effect sizes were unexpectedly smaller in South Asians than Europeans (P<5.0x10-8). Our findings argue against an important contribution for population-specific or cosmopolitan genetic variants underlying the increased risk of central obesity in South Asians compared to Europeans.

Conserved differences in protein sequence determine the human pathogenicity of Ebolaviruses

Reston viruses are the only Ebolaviruses that are not pathogenic in humans. We analyzed 196 Ebolavirus genomes and identified specificity determining positions (SDPs) in all nine Ebolavirus proteins that distinguish Reston viruses from the four human pathogenic Ebolaviruses. A subset of these SDPs will explain the differences in human pathogenicity between Reston and the other four ebolavirus species. Structural analysis was performed to identify those SDPs that are likely to have a functional effect. This analysis revealed novel functional insights in particular for Ebolavirus proteins VP40 and VP24. The VP40 SDP P85T interferes with VP40 function by altering octamer formation. The VP40 SDP Q245P affects the structure and hydrophobic core of the protein and consequently protein function. Three VP24 SDPs (T131S, M136L, Q139R) are likely to impair VP24 binding to human karyopherin alpha5 (KPNA5) and therefore inhibition of interferon signaling. Since VP24 is critical for Ebolavirus adaptation to novel hosts, and only a few SDPs distinguish Reston virus VP24 from VP24 of other Ebolaviruses, human pathogenic Reston viruses may emerge. This is of concern since Reston viruses circulate in domestic pigs and can infect humans, possibly via airborne transmission.

Association of genetic variants with skin pigmentation phenotype among populations of west Maharashtra, India

OBJECTIVES

South Asians exhibit extensive variation in skin melanin index (MI) which is observed across the broader region of South Asia as well as within restricted geographic regions. However, the genetic variants associated with variation in the skin pigmentation phenotype are poorly understood in these populations. The present study examines the association between MI measures and genetic variants from 5 candidate pigmentation genes among 533 individuals representing 6 populations of West Maharashtra.

METHODS

Associations between five single nucleotide polymorphisms (SNPs) known to play a role in pigmentation (rs1426654-SLC24A5, rs1042602-TYR, rs16891982-SLC45A2, rs6058017-ASIP, and rs642742-KITLG) and MI measures were tested using standard one-way analysis of variance (ANOVA) within each population. Multiple linear regression was used to test the effects of these SNPs in the full West Maharashtra sample using sex, age, and population or social group as covariates.

RESULTS

rs1426654 showed significant association with MI in all six study populations (P < 0.01). Association tests using sex, age, and population as covariates showed rs1426654 and rs1042602 to be significantly (P < 0.01) associated with lighter skin pigmentation in West Maharashtra as a whole. By contrast, when social group was added as a covariate instead of population, rs1426654, rs1042602, and rs16891982 were significantly (P < 0.01) associated with lighter skin pigmentation.

CONCLUSIONS

Only rs1426654 is significantly associated with MI in each individual population; however, rs1426654, rs1042602, and rs16891982 are significantly associated with pigmentation in the broader West Maharashtra region after controlling for population and social group, with rs1426654 (SLC24A5) explaining the majority of the observed variation. Am. J. Hum. Biol. 28:610-618, 2016. © 2016 Wiley Periodicals, Inc.

Quantitative trait association study for mean telomere length in the South Asian genomes

MOTIVATION

Mean telomere length (MTL) is associated with cancers and age-related diseases, which necessitates identification of genomic and environmental factors that impact telomere length dynamics. Here, we present a pilot genome wide association (GWA) study for MTL in South Asian population using publicly available next generation whole genome sequences (WGS), both for MTL and genotype calculations.

RESULTS

MTL in the studied population was not correlated with age, which is in accordance with previous reports. Further, we identified that individuals with Sikh religion had longer telomeres, which may be the result of complex interaction between genetic background and environmental factors. Finally, we identified 51 MTL-associated SNPs residing in five loci. The top ones were located in ADARB2 gene, which has previously been implicated with extreme old age.

CONCLUSION

Our results show that WGS data can be used in telomere length studies. In addition, we introduce novel loci implicated in MTL that may be worth considering in further telomere studies.

CONTACT

aarakelyan@sci.am

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Cardiovascular Disease in South Asian Migrants

Cardiovascular disease (CVD) represents a significant cause of global mortality and morbidity. South Asians (SAs) have a particularly high burden of coronary artery disease (CAD). This review describes current literature regarding the prevalence, incidence, etiology, and prognosis of CVD in SA migrants to high-income nations. We conducted a narrative review of CVD in the SA diaspora through a search of MEDLINE and PubMed. We included observational studies, randomized clinical trials, nonsystematic reviews, systematic reviews, and meta-analyses written in English. Of 15,231 articles identified, 827 articles were screened and 124 formed the basis for review. SA migrants have a 1.5-2 times greater prevalence of CAD than age- and sex-adjusted Europids. Increased abdominal obesity and body fat and increased burden of type 2 diabetes mellitus and dyslipidemia appear to be primary drivers of the excess CAD burden in SAs. Sedentary lifestyle and changes in diet after immigration are important contributors to weight gain and adiposity. Early life factors, physical activity patterns and, in some cases, reduced adherence to medical therapy may contribute to increased CVD risks in SAs. Novel biomarkers like leptin and adipokines may show distinct patterns in SAs and provide insights into cardiometabolic risk determinants. In conclusion, SAs have distinct CVD risk predispositions, with a complex relationship to cultural, innate, and acquired factors. Although CVD risk factor management and treatment among SAs is improving, opportunities exist for further advances.

Genome-wide insights into the genetic history of human populations

Although mtDNA and the non-recombining Y chromosome (NRY) studies continue to provide valuable insights into the genetic history of human populations, recent technical, methodological and computational advances and the increasing availability of large-scale, genome-wide data from contemporary human populations around the world promise to reveal new aspects, resolve finer points, and provide a more detailed look at our past demographic history. Genome-wide data are particularly useful for inferring migrations, admixture, and fine structure, as well as for estimating population divergence and admixture times and fluctuations in effective population sizes. In this review, we highlight some of the stories that have emerged from the analyses of genome-wide SNP genotyping data concerning the human history of Southern Africa, India, Oceania, Island South East Asia, Europe and the Americas and comment on possible future study directions. We also discuss advantages and drawbacks of using SNP-arrays, with a particular focus on the ascertainment bias, and ways to circumvent it.