101
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Patowary A, Purkanti R, Singh M, Chauhan RK, Bhartiya D, Dwivedi OP, Chauhan G, Bharadwaj D, Sivasubbu S, Scaria V. Systematic analysis and functional annotation of variations in the genome of an Indian individual. Hum Mutat 2012; 33:1133-40. [PMID: 22461382 DOI: 10.1002/humu.22091] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2011] [Accepted: 03/05/2012] [Indexed: 01/02/2023]
Abstract
Whole genome sequencing of personal genomes has revealed a large repertoire of genomic variations and has provided a rich template for identification of common and rare variants in genomes in addition to understanding the genetic basis of diseases. The widespread application of personal genome sequencing in clinical settings for predictive and preventive medicine has been limited due to the lack of comprehensive computational analysis pipelines. We have used next-generation sequencing technology to sequence the whole genome of a self-declared healthy male of Indian origin. We have generated around 28X of the reference human genome with over 99% coverage. Analysis revealed over 3 million single nucleotide variations and about 490,000 small insertion-deletion events including several novel variants. Using this dataset as a template, we designed a comprehensive computational analysis pipeline for the systematic analysis and annotation of functionally relevant variants in the genome. This study follows a systematic and intuitive data analysis workflow to annotate genome variations and its potential functional effects. Moreover, we integrate predictive analysis of pharmacogenomic traits with emphasis on drugs for which pharmacogenomic testing has been recommended. This study thus provides the template for genome-scale analysis of personal genomes for personalized medicine.
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Affiliation(s)
- Ashok Patowary
- Genomics and Molecular Medicine, CSIR Institute of Genomics and IntegrativeBiology, Council of Scientific and Industrial Research, Delhi, India
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102
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Hodoğlugil U, Mahley RW. Turkish population structure and genetic ancestry reveal relatedness among Eurasian populations. Ann Hum Genet 2012; 76:128-41. [PMID: 22332727 DOI: 10.1111/j.1469-1809.2011.00701.x] [Citation(s) in RCA: 45] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Turkey has experienced major population movements. Population structure and genetic relatedness of samples from three regions of Turkey, using over 500,000 SNP genotypes, were compared together with Human Genome Diversity Panel (HGDP) data. To obtain a more representative sampling from Central Asia, Kyrgyz samples (Bishkek, Kyrgyzstan) were genotyped and analysed. Principal component (PC) analysis reveals a significant overlap between Turks and Middle Easterners and a relationship with Europeans and South and Central Asians; however, the Turkish genetic structure is unique. FRAPPE, STRUCTURE, and phylogenetic analyses support the PC analysis depending upon the number of parental ancestry components chosen. For example, supervised STRUCTURE (K=3) illustrates a genetic ancestry for the Turks of 45% Middle Eastern (95% CI, 42-49), 40% European (95% CI, 36-44) and 15% Central Asian (95% CI, 13-16), whereas at K=4 the genetic ancestry of the Turks was 38% European (95% CI, 35-42), 35% Middle Eastern (95% CI, 33-38), 18% South Asian (95% CI, 16-19) and 9% Central Asian (95% CI, 7-11). PC analysis and FRAPPE/STRUCTURE results from three regions in Turkey (Aydin, Istanbul and Kayseri) were superimposed, without clear subpopulation structure, suggesting sample homogeneity. Thus, this study demonstrates admixture of Turkish people reflecting the population migration patterns.
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Affiliation(s)
- Uğur Hodoğlugil
- Gladstone Institute of Cardiovascular Disease, San Francisco, CA 94158, USA
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103
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Salm MPA, Horswell SD, Hutchison CE, Speedy HE, Yang X, Liang L, Schadt EE, Cookson WO, Wierzbicki AS, Naoumova RP, Shoulders CC. The origin, global distribution, and functional impact of the human 8p23 inversion polymorphism. Genome Res 2012; 22:1144-53. [PMID: 22399572 PMCID: PMC3371712 DOI: 10.1101/gr.126037.111] [Citation(s) in RCA: 56] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Genomic inversions are an increasingly recognized source of genetic variation. However, a lack of reliable high-throughput genotyping assays for these structures has precluded a full understanding of an inversion's phylogenetic, phenotypic, and population genetic properties. We characterize these properties for one of the largest polymorphic inversions in man (the ∼4.5-Mb 8p23.1 inversion), a structure that encompasses numerous signals of natural selection and disease association. We developed and validated a flexible bioinformatics tool that utilizes SNP data to enable accurate, high-throughput genotyping of the 8p23.1 inversion. This tool was applied retrospectively to diverse genome-wide data sets, revealing significant population stratification that largely follows a clinal “serial founder effect” distribution model. Phylogenetic analyses establish the inversion's ancestral origin within the Homo lineage, indicating that 8p23.1 inversion has occurred independently in the Pan lineage. The human inversion breakpoint was localized to an inverted pair of human endogenous retrovirus elements within the large, flanking low-copy repeats; experimental validation of this breakpoint confirmed these elements as the likely intermediary substrates that sponsored inversion formation. In five data sets, mRNA levels of disease-associated genes were robustly associated with inversion genotype. Moreover, a haplotype associated with systemic lupus erythematosus was restricted to the derived inversion state. We conclude that the 8p23.1 inversion is an evolutionarily dynamic structure that can now be accommodated into the understanding of human genetic and phenotypic diversity.
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Affiliation(s)
- Maximilian P A Salm
- Centre for Endocrinology, Barts & the London School of Medicine & Dentistry, Queen Mary University of London, London, United Kingdom.
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104
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Sung C, Lee PL, Tan LL, Toh DS. Pharmacogenetic Risk for Adverse Reactions to Irinotecan in the Major Ethnic Populations of Singapore. Drug Saf 2011; 34:1167-75. [DOI: 10.2165/11594440-000000000-00000] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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105
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Fan Q, Zhou X, Khor CC, Cheng CY, Goh LK, Sim X, Tay WT, Li YJ, Ong RTH, Suo C, Cornes B, Ikram MK, Chia KS, Seielstad M, Liu J, Vithana E, Young TL, Tai ES, Wong TY, Aung T, Teo YY, Saw SM. Genome-wide meta-analysis of five Asian cohorts identifies PDGFRA as a susceptibility locus for corneal astigmatism. PLoS Genet 2011; 7:e1002402. [PMID: 22144915 PMCID: PMC3228826 DOI: 10.1371/journal.pgen.1002402] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2011] [Accepted: 10/17/2011] [Indexed: 12/21/2022] Open
Abstract
Corneal astigmatism refers to refractive abnormalities and irregularities in the curvature of the cornea, and this interferes with light being accurately focused at a single point in the eye. This ametropic condition is highly prevalent, influences visual acuity, and is a highly heritable trait. There is currently a paucity of research in the genetic etiology of corneal astigmatism. Here we report the results from five genome-wide association studies of corneal astigmatism across three Asian populations, with an initial discovery set of 4,254 Chinese and Malay individuals consisting of 2,249 cases and 2,005 controls. Replication was obtained from three surveys comprising of 2,139 Indians, an additional 929 Chinese children, and an independent 397 Chinese family trios. Variants in PDGFRA on chromosome 4q12 (lead SNP: rs7677751, allelic odds ratio = 1.26 (95% CI: 1.16-1.36), P(meta) = 7.87×10(-9)) were identified to be significantly associated with corneal astigmatism, exhibiting consistent effect sizes across all five cohorts. This highlights the potential role of variants in PDGFRA in the genetic etiology of corneal astigmatism across diverse Asian populations.
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Affiliation(s)
- Qiao Fan
- School of Public Health, National University of Singapore, Singapore, Singapore
| | - Xin Zhou
- School of Public Health, National University of Singapore, Singapore, Singapore
| | - Chiea-Chuen Khor
- Genome Institute of Singapore, Agency for Science, Technology, and Research, Singapore, Singapore
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Centre for Molecular Epidemiology, National University of Singapore, Singapore, Singapore
- Department of Pediatrics, National University of Singapore, Singapore, Singapore
| | - Ching-Yu Cheng
- School of Public Health, National University of Singapore, Singapore, Singapore
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Department of Ophthalmology, National University of Singapore, Singapore, Singapore
| | - Liang-Kee Goh
- School of Public Health, National University of Singapore, Singapore, Singapore
- Duke–National University of Singapore Graduate Medical School, Singapore, Singapore
- Department of Medical Oncology, National Cancer Centre Singapore, Singapore, Singapore
| | - Xueling Sim
- Centre for Molecular Epidemiology, National University of Singapore, Singapore, Singapore
| | - Wan-Ting Tay
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Yi-Ju Li
- Center for Human Genetics, Duke University Medical Center, Durham, North Carolina, United States of America
- Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, North Carolina, United States of America
| | - Rick Twee-Hee Ong
- School of Public Health, National University of Singapore, Singapore, Singapore
- NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore, Singapore
| | - Chen Suo
- Centre for Molecular Epidemiology, National University of Singapore, Singapore, Singapore
| | - Belinda Cornes
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Mohammad Kamran Ikram
- School of Public Health, National University of Singapore, Singapore, Singapore
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Duke–National University of Singapore Graduate Medical School, Singapore, Singapore
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Kee-Seng Chia
- School of Public Health, National University of Singapore, Singapore, Singapore
- Centre for Molecular Epidemiology, National University of Singapore, Singapore, Singapore
- NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore, Singapore
| | - Mark Seielstad
- Institute for Human Genetics and Department of Laboratory Medicine, University of California San Francisco, San Francisco, California, United States of America
| | - Jianjun Liu
- Genome Institute of Singapore, Agency for Science, Technology, and Research, Singapore, Singapore
| | - Eranga Vithana
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Department of Ophthalmology, National University of Singapore, Singapore, Singapore
| | - Terri L. Young
- Center for Human Genetics, Duke University Medical Center, Durham, North Carolina, United States of America
| | - E.-Shyong Tai
- School of Public Health, National University of Singapore, Singapore, Singapore
- Department of Medicine, National University of Singapore, Singapore, Singapore
| | - Tien-Yin Wong
- School of Public Health, National University of Singapore, Singapore, Singapore
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Department of Ophthalmology, National University of Singapore, Singapore, Singapore
- Centre for Eye Research Australia, University of Melbourne, Melbourne, Australia
| | - Tin Aung
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Department of Ophthalmology, National University of Singapore, Singapore, Singapore
| | - Yik-Ying Teo
- School of Public Health, National University of Singapore, Singapore, Singapore
- Genome Institute of Singapore, Agency for Science, Technology, and Research, Singapore, Singapore
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore, Singapore
- Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore
| | - Seang-Mei Saw
- School of Public Health, National University of Singapore, Singapore, Singapore
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Department of Ophthalmology, National University of Singapore, Singapore, Singapore
- NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore, Singapore
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106
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Teo SM, Ku CS, Salim A, Naidoo N, Chia KS, Pawitan Y. Regions of homozygosity in three Southeast Asian populations. J Hum Genet 2011; 57:101-8. [PMID: 22129560 DOI: 10.1038/jhg.2011.132] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The genomes of outbred populations were first shown in 2006 to contain regions of homozygosity (ROHs) of several megabases. Further studies have also investigated the characteristics of ROHs in healthy individuals in various populations but there are no studies on Singapore populations to date. This study aims to identify and investigate the characteristics of ROHs in three Singapore populations. A total of 268 samples (96 Chinese, 89 Malays and 83 Indians) are genotyped on Illumina Human 1 M Beadchip and Affymetrix Genome-Wide Human SNP Array 6.0. We use the PennCNV algorithm to detect ROHs. We report an abundance of ROHs (≥500 kb), with an average of more than one hundred regions per individual. On average, the Indian population has the lowest number of ROHs and smallest total length of ROHs per individual compared with the Chinese and Malay populations. We further investigate the relationship between the occurrence of ROHs and haplotype frequency, regional linkage disequilibrium (LD) and positive selection. Based on the results of this data set, we find that the frequency of occurrence of ROHs is positively associated with haplotype frequency and regional LD. The majority of regions detected for recent positive selection and regions with differential LD between populations overlap with the ROH loci. When we consider both the location of the ROHs and the allelic form of the ROHs, we are able to separate the populations by principal component analysis, demonstrating that ROHs contain information on population structure and the demographic history of a population.
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Affiliation(s)
- Shu-Mei Teo
- Centre for Molecular Epidemiology, National University of Singapore, Singapore.
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107
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Wang X, Liu X, Sim X, Xu H, Khor CC, Ong RTH, Tay WT, Suo C, Poh WT, Ng DPK, Liu J, Aung T, Chia KS, Wong TY, Tai ES, Teo YY. A statistical method for region-based meta-analysis of genome-wide association studies in genetically diverse populations. Eur J Hum Genet 2011; 20:469-75. [PMID: 22126751 PMCID: PMC3306862 DOI: 10.1038/ejhg.2011.219] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
Genome-wide association studies (GWAS) have become the preferred experimental design in exploring the genetic etiology of complex human traits and diseases. Standard SNP-based meta-analytic approaches have been utilized to integrate the results from multiple experiments. This fundamentally assumes that the patterns of linkage disequilibrium (LD) between the underlying causal variants and the directly genotyped SNPs are similar across the populations for the same SNPs to emerge with surrogate evidence of disease association. We introduce a novel strategy for assessing regional evidence of phenotypic association that explicitly incorporates the extent of LD in the region. This provides a natural framework for combining evidence from multi-ethnic studies of both dichotomous and quantitative traits that (i) accommodates different patterns of LD, (ii) integrates different genotyping platforms and (iii) allows for the presence of allelic heterogeneity between the populations. Our method can also be generalized to perform gene-based or pathway-based analyses. Applying this method on real GWAS data in type 2 diabetes (T2D) boosted the association evidence in regions well-established for T2D etiology in three diverse South-East Asian populations, as well as identified two novel gene regions and a biologically convincing pathway that are subsequently validated with data from the Wellcome Trust Case Control Consortium.
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Affiliation(s)
- Xu Wang
- Department of Epidemiology and Public Health, National University of Singapore, Singapore
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108
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Novembre J, Ramachandran S. Perspectives on human population structure at the cusp of the sequencing era. Annu Rev Genomics Hum Genet 2011; 12:245-74. [PMID: 21801023 DOI: 10.1146/annurev-genom-090810-183123] [Citation(s) in RCA: 62] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Human groups show structured levels of genetic similarity as a consequence of factors such as geographical subdivision and genetic drift. Surveying this structure gives us a scientific perspective on human origins, sheds light on evolutionary processes that shape both human adaptation and disease, and is integral to effectively carrying out the mission of global medical genetics and personalized medicine. Surveys of population structure have been ongoing for decades, but in the past three years, single-nucleotide-polymorphism (SNP) array technology has provided unprecedented detail on human population structure at global and regional scales. These studies have confirmed well-known relationships between distantly related populations and uncovered previously unresolvable relationships among closely related human groups. SNPs represent the first dense genome-wide markers, and as such, their analysis has raised many challenges and insights relevant to the study of population genetics with whole-genome sequences. Here we draw on the lessons from these studies to anticipate the directions that will be most fruitful to pursue during the emerging whole-genome sequencing era.
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Affiliation(s)
- John Novembre
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California 90403, USA.
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109
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Xu H, Poh WT, Sim X, Ong RTH, Suo C, Tay WT, Khor CC, Seielstad M, Liu J, Aung T, Tai ES, Wong TY, Chia KS, Teo YY. SgD-CNV, a database for common and rare copy number variants in three Asian populations. Hum Mutat 2011; 32:1341-9. [PMID: 21882294 DOI: 10.1002/humu.21601] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2011] [Accepted: 08/11/2011] [Indexed: 01/02/2023]
Abstract
Copy number variants (CNVs) extend our understanding of the genetic diversity in humans. However, the distribution and characteristics of CNVs in Asian populations remain largely unexplored, especially for rare CNVs that have emerged as important genetic factors for complex traits. In the present study, we performed an in-depth investigation of common and rare CNVs across 8,148 individuals from the three major Asian ethnic groups: Chinese (n = 1,945), Malays (n = 2,399), and Indians (n = 2,217) in Singapore, making this investigation the most comprehensive genome-wide survey of CNVs outside the European-ancestry populations to date. We detected about 16 CNVs per individual and the ratio of loss to gain events is ∼2:1. The majority of the CNVs are of low frequency (<10%), and 40% are rare (<1%). In each population, ∼20% of the CNVs are not previously catalogued in the Database of Genomic Variants (DGV). Contrary to findings from European studies, the common CNVs (>5%) in our populations are not well tagged by SNPs in Illumina 1M and 610K arrays, and most disease-associated common CNVs previously reported in Caucasians are rare in our populations. We also report noticeable population differentiation in the CNV landscape of these Asian populations, with the greatest diversity seen between the Indians and the Chinese.
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Affiliation(s)
- Haiyan Xu
- Centre for Molecular Epidemiology, National University of Singapore, Singapore
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110
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Kooner JS, Saleheen D, Sim X, Sehmi J, Zhang W, Frossard P, Been LF, Chia KS, Dimas AS, Hassanali N, Jafar T, Jowett JBM, Li X, Radha V, Rees SD, Takeuchi F, Young R, Aung T, Basit A, Chidambaram M, Das D, Grunberg E, Hedman ÅK, Hydrie ZI, Islam M, Khor CC, Kowlessur S, Kristensen MM, Liju S, Lim WY, Matthews DR, Liu J, Morris AP, Nica AC, Pinidiyapathirage JM, Prokopenko I, Rasheed A, Samuel M, Shah N, Shera AS, Small KS, Suo C, Wickremasinghe AR, Wong TY, Yang M, Zhang F, Abecasis GR, Barnett AH, Caulfield M, Deloukas P, Frayling T, Froguel P, Kato N, Katulanda P, Kelly MA, Liang J, Mohan V, Sanghera DK, Scott J, Seielstad M, Zimmet PZ, Elliott P, Teo YY, McCarthy MI, Danesh J, Tai ES, Chambers JC. Genome-wide association study in individuals of South Asian ancestry identifies six new type 2 diabetes susceptibility loci. Nat Genet 2011; 43:984-9. [PMID: 21874001 PMCID: PMC3773920 DOI: 10.1038/ng.921] [Citation(s) in RCA: 387] [Impact Index Per Article: 29.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2011] [Accepted: 08/03/2011] [Indexed: 12/16/2022]
Abstract
We carried out a genome-wide association study of type-2 diabetes (T2D) in individuals of South Asian ancestry. Our discovery set included 5,561 individuals with T2D (cases) and 14,458 controls drawn from studies in London, Pakistan and Singapore. We identified 20 independent SNPs associated with T2D at P < 10(-4) for testing in a replication sample of 13,170 cases and 25,398 controls, also all of South Asian ancestry. In the combined analysis, we identified common genetic variants at six loci (GRB14, ST6GAL1, VPS26A, HMG20A, AP3S2 and HNF4A) newly associated with T2D (P = 4.1 × 10(-8) to P = 1.9 × 10(-11)). SNPs at GRB14 were also associated with insulin sensitivity (P = 5.0 × 10(-4)), and SNPs at ST6GAL1 and HNF4A were also associated with pancreatic beta-cell function (P = 0.02 and P = 0.001, respectively). Our findings provide additional insight into mechanisms underlying T2D and show the potential for new discovery from genetic association studies in South Asians, a population with increased susceptibility to T2D.
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Affiliation(s)
- Jaspal S Kooner
- NHLI, Imperial College London, Hammersmith Hospital, Ducane Road, London, W12 0NN, UK
- Ealing Hospital NHS Trust, Uxbridge Road, Middlesex, UB1 3HW, UK
- Imperial College Healthcare NHS Trust, DuCane Road, London, W12 0HS
| | - Danish Saleheen
- Center for Non-Communicable Diseases Pakistan, Karachi, 75300, Pakistan
- Department of Public Health and Primary Care, University of Cambridge, worts causeway, Cambridge CB1 8RN, UK
| | - Xueling Sim
- Centre for Molecular Epidemiology, National University of Singapore, Singapore
| | - Joban Sehmi
- NHLI, Imperial College London, Hammersmith Hospital, Ducane Road, London, W12 0NN, UK
- Ealing Hospital NHS Trust, Uxbridge Road, Middlesex, UB1 3HW, UK
| | - Weihua Zhang
- Epidemiology and Biostatistics, Imperial College London, Norfolk Place, London, W2 1PG, UK
| | - Philippe Frossard
- Center for Non-Communicable Diseases Pakistan, Karachi, 75300, Pakistan
| | - Latonya F Been
- Department of Pediatrics, Section of Genetics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
| | - Kee-Seng Chia
- Centre for Molecular Epidemiology, National University of Singapore, Singapore
- Department of Epidemiology and Public Health, National University of Singapore, Singapore
| | - Antigone S Dimas
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Neelam Hassanali
- Oxford Centre for Diabetes, Endocrinology & Metabolism, University of Oxford, Churchill Hospital, Oxford, UK
| | - Tazeen Jafar
- Department of Community Health Sciences, Aga Khan University, Stadium Road, P.O. Box 3500, Karachi-74800, Pakistan
- Department of Medicine, Aga Khan University, Stadium Road, P.O. Box 3500, Karachi-74800, Pakistan
| | - Jeremy BM Jowett
- Baker IDI Heart and Diabetes Institute, Melbourne, Victoria, 3004, Australia
| | - Xinzhing Li
- NHLI, Imperial College London, Hammersmith Hospital, Ducane Road, London, W12 0NN, UK
| | - Venkatesan Radha
- Department of Molecular Genetics, Madras Diabetes Research Foundation-ICMR Advanced Centre for Genomics of Diabetes, Chennai 603 103, India
| | - Simon D Rees
- College of Medical and Dental Sciences, University of Birmingham
- BioMedical Research Centre, Heart of England NHS Foundation Trust, Birmingham
| | - Fumihiko Takeuchi
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan, 162-8655
| | - Robin Young
- Department of Public Health and Primary Care, University of Cambridge, worts causeway, Cambridge CB1 8RN, UK
| | - Tin Aung
- Department of Ophthalomolgy, National University of Singapore, Singapore
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
| | - Abdul Basit
- Baqai Institute of Diabetology and Endocrinology, Karachi, Pakistan
| | - Manickam Chidambaram
- Department of Molecular Genetics, Madras Diabetes Research Foundation-ICMR Advanced Centre for Genomics of Diabetes, Chennai 603 103, India
| | - Debashish Das
- Ealing Hospital NHS Trust, Uxbridge Road, Middlesex, UB1 3HW, UK
| | - Elin Grunberg
- Department of Twin Research and Genetic Epidemiology, King’s College London, London, UK
| | - Åsa K Hedman
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Zafar I Hydrie
- Baqai Institute of Diabetology and Endocrinology, Karachi, Pakistan
| | - Muhammed Islam
- Department of Community Health Sciences, Aga Khan University, Stadium Road, P.O. Box 3500, Karachi-74800, Pakistan
| | - Chiea-Chuen Khor
- Centre for Molecular Epidemiology, National University of Singapore, Singapore
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore
| | | | - Malene M Kristensen
- Baker IDI Heart and Diabetes Institute, Melbourne, Victoria, 3004, Australia
| | - Samuel Liju
- Department of Molecular Genetics, Madras Diabetes Research Foundation-ICMR Advanced Centre for Genomics of Diabetes, Chennai 603 103, India
| | - Wei-Yen Lim
- Centre for Molecular Epidemiology, National University of Singapore, Singapore
| | - David R Matthews
- Oxford Centre for Diabetes, Endocrinology & Metabolism, University of Oxford, Churchill Hospital, Oxford, UK
| | - Jianjun Liu
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore
| | - Andrew P Morris
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Alexandra C Nica
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | | | - Inga Prokopenko
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Asif Rasheed
- Center for Non-Communicable Diseases Pakistan, Karachi, 75300, Pakistan
| | - Maria Samuel
- Center for Non-Communicable Diseases Pakistan, Karachi, 75300, Pakistan
| | - Nabi Shah
- Center for Non-Communicable Diseases Pakistan, Karachi, 75300, Pakistan
| | | | - Kerrin S Small
- Department of Twin Research and Genetic Epidemiology, King’s College London, London, UK
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK
| | - Chen Suo
- Centre for Molecular Epidemiology, National University of Singapore, Singapore
| | - Ananda R Wickremasinghe
- Department of Public Health, Faculty of Medicine, University of Kelaniya, Ragama, Sri Lanka, 11010
| | - Tien Yin Wong
- Department of Ophthalomolgy, National University of Singapore, Singapore
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
- Center for Eye Research Australia, University of Melbourne, Australia
| | - Mingyu Yang
- Beijing Genomics Institute, Shenzhen 518083, China
| | - Fan Zhang
- Beijing Genomics Institute, Shenzhen 518083, China
| | - DIAGRAM
- Members of the DIAGRAM and MuTHER study are listed in the Supplementary Online Material
| | - MuTHER
- Members of the DIAGRAM and MuTHER study are listed in the Supplementary Online Material
| | - Goncalo R Abecasis
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan
| | - Anthony H Barnett
- College of Medical and Dental Sciences, University of Birmingham
- BioMedical Research Centre, Heart of England NHS Foundation Trust, Birmingham
| | - Mark Caulfield
- Clinical Pharmacology and Barts and the London Genome Centre, William Harvey Research Institute, Barts and the London School of Medicine, Queen Mary University of London, London, UK
| | - Panos Deloukas
- Human Genetics, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SA UK
| | - Tim Frayling
- Genetics of Complex Traits, Institute of Biomedical and Clinical Science, Peninsula Medical School, University of Exeter, Exeter, UK
| | - Philippe Froguel
- Genomics of Common Diseases, School of Public Health, Imperial College London, Hammersmith Hospital, Du Cane Road, London W12 0NN
| | - Norihiro Kato
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan, 162-8655
| | - Prasad Katulanda
- Oxford Centre for Diabetes, Endocrinology & Metabolism, University of Oxford, Churchill Hospital, Oxford, UK
- Diabetes Research Unit, Dept of Clinical Medicine, Univ of Colombo, Sri Lanka
| | - M Ann Kelly
- College of Medical and Dental Sciences, University of Birmingham
- BioMedical Research Centre, Heart of England NHS Foundation Trust, Birmingham
| | - Junbin Liang
- Beijing Genomics Institute, Shenzhen 518083, China
| | - Viswanathan Mohan
- Department of Molecular Genetics, Madras Diabetes Research Foundation-ICMR Advanced Centre for Genomics of Diabetes, Chennai 603 103, India
- Dr Mohan’s Diabetes Specialties Centre, Chennai 600086, India
| | - Dharambir K Sanghera
- Department of Pediatrics, Section of Genetics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
| | - James Scott
- NHLI, Imperial College London, Hammersmith Hospital, Ducane Road, London, W12 0NN, UK
| | - Mark Seielstad
- Institure of Human Genetics, University of California, San Francisco
| | - Paul Z Zimmet
- Baker IDI Heart and Diabetes Institute, Melbourne, Victoria, 3004, Australia
| | - Paul Elliott
- Epidemiology and Biostatistics, Imperial College London, Norfolk Place, London, W2 1PG, UK
- MRC-HPA Centre for Environment and Health, Imperial College London, Norfolk Place, London, W2 1PG, UK
| | - Yik Ying Teo
- Centre for Molecular Epidemiology, National University of Singapore, Singapore
- Department of Epidemiology and Public Health, National University of Singapore, Singapore
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore
- Department of Statistics and Applied Probability, National University of Singapore, Singapore
- NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore
| | - Mark I McCarthy
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology & Metabolism, University of Oxford, Churchill Hospital, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford, UK
| | - John Danesh
- Department of Public Health and Primary Care, University of Cambridge, worts causeway, Cambridge CB1 8RN, UK
| | - E Shyong Tai
- Department of Epidemiology and Public Health, National University of Singapore, Singapore
- Department of Medicine, National University of Singapore, Singapore
- Duke-National University of Singapore Graduate Medical School, Singapore 169857,Singapore
| | - John C Chambers
- Ealing Hospital NHS Trust, Uxbridge Road, Middlesex, UB1 3HW, UK
- Imperial College Healthcare NHS Trust, DuCane Road, London, W12 0HS
- Epidemiology and Biostatistics, Imperial College London, Norfolk Place, London, W2 1PG, UK
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111
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Suo C, Xu H, Khor CC, Ong RT, Sim X, Chen J, Tay WT, Sim KS, Zeng YX, Zhang X, Liu J, Tai ES, Wong TY, Chia KS, Teo YY. Natural positive selection and north-south genetic diversity in East Asia. Eur J Hum Genet 2011; 20:102-10. [PMID: 21792231 DOI: 10.1038/ejhg.2011.139] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
Recent reports have identified a north-south cline in genetic variation in East and South-East Asia, but these studies have not formally explored the basis of these clinical differences. Understanding the origins of these variations may provide valuable insights in tracking down the functional variants in genomic regions identified by genetic association studies. Here we investigate the genetic basis of these differences with genome-wide data from the HapMap, the Human Genome Diversity Project and the Singapore Genome Variation Project. We implemented four bioinformatic measures to discover genomic regions that are considerably differentiated either between two Han Chinese populations in the north and south of China, or across 22 populations in East and South-East Asia. These measures prioritized genomic stretches with: (i) regional differences in the allelic spectrum for SNPs common to the two Han Chinese populations; (ii) differential evidence of positive selection between the two populations as quantified by integrated haplotype score (iHS) and cross-population extended haplotype homozygosity (XP-EHH); (iii) significant correlation between allele frequencies and geographical latitudes of the 22 populations. We also explored the extent of linkage disequilibrium variations in these regions, which is important in combining genetic association studies from North and South Chinese. Two of the regions that emerged are found in HLA class I and II, suggesting that the HLA imputation panel from the HapMap may not be directly applicable to every Chinese sample. This has important implications to autoimmune studies that plan to impute the classical HLA alleles to fine map the SNP association signals.
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Affiliation(s)
- Chen Suo
- Centre for Molecular Epidemiology, National University of Singapore, Singapore, Singapore
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112
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Abstract
Copy number variations can be identified using newer genotyping arrays with higher single nucleotide polymorphisms (SNPs) density and copy number probes accompanied by newer algorithms. McCarroll et al. (2008) applied these to the HapMap II samples and identified 1316 copy number polymorphisms (CNPs). In our study, we applied the same approach to 859 samples from three Singapore populations and seven HapMap III populations. Approximately 50% of the 1291 autosomal CNPs were found to be polymorphic only in populations of non-African ancestry. Pairwise comparisons among the 10 populations showed substantial differences in the CNPs frequencies. Additionally, 698 CNPs showed significant differences with false discovery rate (FDR)<0.01 among the 10 populations and these loci overlap with known disease-associated or pharmacogenetic-related genes such as CFHR3 and CFHR1 (age related macular degeneration), GSTTI (metabolism of various carcinogenic compounds and cancers) and UGT2B17 (prostate cancer and graft-versus-host disease). The correlations between CNPs and genome-wide association studies-SNPs were investigated and several loci, which were previously unreported, that may potentially be implicated in complex diseases and traits were found; for example, childhood acute lymphoblastic leukaemia, age-related macular degeneration, breast cancer, response to antipsychotic treatment, rheumatoid arthritis and type-1 diabetes. Additionally, we also found 5014 novel copy number loci that have not been reported previously by McCarroll et al. (2008) in the 10 populations.
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113
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Listman JB, Malison RT, Sanichwankul K, Ittiwut C, Mutirangura A, Gelernter J. Southeast Asian origins of five Hill Tribe populations and correlation of genetic to linguistic relationships inferred with genome-wide SNP data. AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 2011; 144:300-8. [PMID: 20979205 DOI: 10.1002/ajpa.21408] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
In Thailand, the term Hill Tribe is used to describe populations whose members traditionally practice slash and burn agriculture and reside in the mountains. These tribes are thought to have migrated throughout Asia for up to 5,000 years, including migrations through Southern China and/or Southeast Asia. There have been continuous migrations southward from China into Thailand for approximately the past thousand years and the present geographic range of any given tribe straddles multiple political borders. As none of these populations have autochthonous scripts, written histories have until recently, been externally produced. Northern Asian, Tibetan, and Siberian origins of Hill Tribes have been proposed. All purport endogamy and have nonmutually intelligible languages. To test hypotheses regarding the geographic origins of these populations, relatedness and migrations among them and neighboring populations, and whether their genetic relationships correspond with their linguistic relationships, we analyzed 2,445 genome-wide SNP markers in 118 individuals from five Thai Hill Tribe populations (Akha, Hmong, Karen, Lahu, and Lisu), 90 individuals from majority Thai populations, and 826 individuals from Asian and Oceanean HGDP and HapMap populations using a Bayesian clustering method. Considering these results within the context of results ofrecent large-scale studies of Asian geographic genetic variation allows us to infer a shared Southeast Asian origin of these five Hill Tribe populations as well ancestry components that distinguish among them seen in successive levels of clustering. In addition, the inferred level of shared ancestry among the Hill Tribes corresponds well to relationships among their languages.
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Affiliation(s)
- J B Listman
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06510, USA
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114
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Sim X, Ong RTH, Suo C, Tay WT, Liu J, Ng DPK, Boehnke M, Chia KS, Wong TY, Seielstad M, Teo YY, Tai ES. Transferability of type 2 diabetes implicated loci in multi-ethnic cohorts from Southeast Asia. PLoS Genet 2011; 7:e1001363. [PMID: 21490949 PMCID: PMC3072366 DOI: 10.1371/journal.pgen.1001363] [Citation(s) in RCA: 123] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2010] [Accepted: 03/04/2011] [Indexed: 12/24/2022] Open
Abstract
Recent large genome-wide association studies (GWAS) have identified multiple loci
which harbor genetic variants associated with type 2 diabetes mellitus (T2D),
many of which encode proteins not previously suspected to be involved in the
pathogenesis of T2D. Most GWAS for T2D have focused on populations of European
descent, and GWAS conducted in other populations with different ancestry offer a
unique opportunity to study the genetic architecture of T2D. We performed
genome-wide association scans for T2D in 3,955 Chinese (2,010 cases, 1,945
controls), 2,034 Malays (794 cases, 1,240 controls), and 2,146 Asian Indians
(977 cases, 1,169 controls). In addition to the search for novel variants
implicated in T2D, these multi-ethnic cohorts serve to assess the
transferability and relevance of the previous findings from European descent
populations in the three major ethnic populations of Asia, comprising half of
the world's population. Of the SNPs associated with T2D in previous GWAS,
only variants at CDKAL1 and
HHEX/IDE/KIF11 showed the strongest
association with T2D in the meta-analysis including all three ethnic groups.
However, consistent direction of effect was observed for many of the other SNPs
in our study and in those carried out in European populations. Close examination
of the associations at both the CDKAL1 and
HHEX/IDE/KIF11 loci provided some evidence of locus and
allelic heterogeneity in relation to the associations with T2D. We also detected
variation in linkage disequilibrium between populations for most of these loci
that have been previously identified. These factors, combined with limited
statistical power, may contribute to the failure to detect associations across
populations of diverse ethnicity. These findings highlight the value of
surveying across diverse racial/ethnic groups towards the fine-mapping efforts
for the casual variants and also of the search for variants, which may be
population-specific. Type 2 diabetes mellitus (T2D) is a chronic disease which can lead to
complications such as heart disease, stroke, hypertension, blindness due to
diabetic retinopathy, amputations from peripheral vascular diseases, and kidney
disease from diabetic nephropathy. The increasing prevalence and complications
of T2D are likely to increase the health and economic burden of individuals,
families, health systems, and countries. Our study carried out in three major
Asian ethnic groups (Chinese, Malays, and Indians) in Singapore suggests that
the findings of studies carried out in populations of European ancestry (which
represents most studies to date) may be relevant to populations in Asia.
However, our study also raises the possibility that different genes, and within
the genes different variants, may confer susceptibility to T2D in these
populations. These findings are particularly relevant in Asia, where the
greatest growth of T2D is expected in the coming years, and emphasize the
importance of studying diverse populations when trying to localize the regions
of the genome associated with T2D. In addition, we may need to consider novel
methods for combining data across populations.
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Affiliation(s)
- Xueling Sim
- Centre for Molecular Epidemiology, National University of Singapore,
Singapore, Singapore
| | - Rick Twee-Hee Ong
- Centre for Molecular Epidemiology, National University of Singapore,
Singapore, Singapore
- NUS Graduate School for Integrative Science and Engineering, National
University of Singapore, Singapore, Singapore
- Genome Institute of Singapore, Agency for Science, Technology and
Research, Singapore, Singapore
| | - Chen Suo
- Centre for Molecular Epidemiology, National University of Singapore,
Singapore, Singapore
| | - Wan-Ting Tay
- Singapore Eye Research Institute, Singapore National Eye Centre,
Singapore, Singapore
| | - Jianjun Liu
- Genome Institute of Singapore, Agency for Science, Technology and
Research, Singapore, Singapore
| | - Daniel Peng-Keat Ng
- Department of Epidemiology and Public Health, National University of
Singapore, Singapore, Singapore
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, School
of Public Health, University of Michigan, Ann Arbor, Michigan, United States of
America
| | - Kee-Seng Chia
- Centre for Molecular Epidemiology, National University of Singapore,
Singapore, Singapore
- Department of Epidemiology and Public Health, National University of
Singapore, Singapore, Singapore
| | - Tien-Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Centre,
Singapore, Singapore
- Department of Epidemiology and Public Health, National University of
Singapore, Singapore, Singapore
- Department of Ophthalmology, National University of Singapore, Singapore,
Singapore
- Centre for Eye Research Australia, University of Melbourne, Melbourne,
Australia
| | - Mark Seielstad
- Genome Institute of Singapore, Agency for Science, Technology and
Research, Singapore, Singapore
| | - Yik-Ying Teo
- Centre for Molecular Epidemiology, National University of Singapore,
Singapore, Singapore
- NUS Graduate School for Integrative Science and Engineering, National
University of Singapore, Singapore, Singapore
- Genome Institute of Singapore, Agency for Science, Technology and
Research, Singapore, Singapore
- Department of Epidemiology and Public Health, National University of
Singapore, Singapore, Singapore
- Department of Statistics and Applied Probability, National University of
Singapore, Singapore, Singapore
- * E-mail: (E-ST); (Y-YT)
| | - E-Shyong Tai
- Department of Epidemiology and Public Health, National University of
Singapore, Singapore, Singapore
- Department of Medicine, National University of Singapore, Singapore,
Singapore
- Duke-National University of Singapore Graduate Medical School, Singapore,
Singapore
- * E-mail: (E-ST); (Y-YT)
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Translational aspects of genetic factors in the prediction of drug response variability: a case study of warfarin pharmacogenomics in a multi-ethnic cohort from Asia. THE PHARMACOGENOMICS JOURNAL 2011; 12:312-8. [PMID: 21383771 DOI: 10.1038/tpj.2011.7] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
Genetic markers displaying highly significant statistical associations with complex phenotypes may not necessarily possess sufficient clinical validity to be useful. Understanding the contribution of these markers beyond readily available clinical biomarkers is particularly important in pharmacogenetics. We demonstrate the utility of genetic testing using the example of warfarin in a multi-ethnic setting comprising of three Asian populations that are broadly representative of the genetic diversity for half of the population in the world, especially as distinct interethnic differences in warfarin dose requirements have been previously established. We confirmed the roles of three well-established loci (CYP2C9, VKORC1 and CYP4F2) in explaining warfarin dosage variation in the three Asian populations. In addition, we assessed the relationship between ethnicity and the genotypes of these loci, observing strong correlations at VKORC1 and CYP4F2. Subsequently, we established the additional utility of these genetic factors in predicting warfarin dose beyond ethnicity and clinical biomarkers through performing a series of systematic cross-validation analyses of the relative predictive accuracies of various fixed-dose regimen, clinical and genetic models. Through a pharmacogenetics model for warfarin, we show the importance of genetic testing beyond readily available clinical biomarkers in predicting dose requirements, confirming the role of genetic profiling in personalized medicine.
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Abstract
In this review, I describe how evolutionary genomics is uniquely suited to spearhead advances in understanding human disease risk, owing to the privileged position of genes as fundamental causes of phenotypic variation, and the ability of population genetic and phylogenetic methods to robustly infer processes of natural selection, drift, and mutation from genetic variation at the levels of family, population, species, and clade. I first provide an overview of models for the origins and maintenance of genetically based disease risk in humans. I then discuss how analyses of genetic disease risk can be dovetailed with studies of positive and balancing selection, to evaluate the degree to which the 'genes that make us human' also represent the genes that mediate risk of polygenic disease. Finally, I present four basic principles for the nascent field of human evolutionary medical genomics, each of which represents a process that is nonintuitive from a proximate perspective. Joint consideration of these principles compels novel forms of interdisciplinary analyses, most notably studies that (i) analyze tradeoffs at the level of molecular genetics, and (ii) identify genetic variants that are derived in the human lineage or in specific populations, and then compare individuals with derived versus ancestral alleles.
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Affiliation(s)
- Bernard J Crespi
- Department of Biosciences, Simon Fraser University Burnaby, BC, Canada
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117
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Teo YY, Ong RTH, Sim X, Tai ES, Chia KS. Identifying candidate causal variants via trans-population fine-mapping. Genet Epidemiol 2011; 34:653-64. [PMID: 20839287 DOI: 10.1002/gepi.20522] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Genome-wide association studies have discovered and confirmed a large number of loci that are implicated with disease susceptibility and severity. Polymorphisms that emerged from these studies are mostly indirectly associated to the phenotype, and the natural progression is to identify the causal variants that are functionally responsible for these association signals. Long stretches of high linkage disequilibrium (LD) benefitted the initial discovery phase in a genome-wide scan, allowing commercial genotyping products with imperfect coverage to detect genomic regions genuinely associated with the phenotype. However, regions of high LD confound the fine-mapping phase, as markers that are perfectly correlated to the causal variants display similar evidence of phenotypic association, hampering the process of differentiating the functional polymorphisms from neighboring surrogates. Here, we explore the potential of integrating information across different populations for narrowing the candidate region that a causal variant resides in, and compare the efficacy of this process of trans-population fine-mapping with the extent of variation in patterns of LD between the populations. In addition, we explore two different strategies for pooling data across multiple populations for the purpose of prioritizing the rankings of the causal variants. Our results clearly establish the benefits of trans-population analysis in reducing the number of possible candidates for the causal variants, particularly in genomic regions displaying strong evidence of inter-population LD variation. Directly integrating the statistical evidence by summing the test statistics outperforms the standard meta-analytic procedure. These findings have direct relevance to the design and analysis of ongoing fine-mapping studies.
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Affiliation(s)
- Yik-Ying Teo
- Department of Statistics and Applied Probability, National University of Singapore, Singapore.
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118
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Li YJ, Goh L, Khor CC, Fan Q, Yu M, Han S, Sim X, Ong RTH, Wong TY, Vithana EN, Yap E, Nakanishi H, Matsuda F, Ohno-Matsui K, Yoshimura N, Seielstad M, Tai ES, Young TL, Saw SM. Genome-wide association studies reveal genetic variants in CTNND2 for high myopia in Singapore Chinese. Ophthalmology 2011; 118:368-75. [PMID: 21095009 PMCID: PMC3052933 DOI: 10.1016/j.ophtha.2010.06.016] [Citation(s) in RCA: 96] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2010] [Revised: 06/03/2010] [Accepted: 06/03/2010] [Indexed: 02/03/2023] Open
Abstract
OBJECTIVE To determine susceptibility genes for high myopia in Singaporean Chinese. DESIGN A meta-analysis of 2 genome-wide association (GWA) datasets in Chinese and a follow-up replication cohort in Japanese. PARTICIPANTS AND CONTROLS Two independent datasets of Singaporean Chinese individuals aged 10 to 12 years (Singapore Cohort Study of the Risk factors for Myopia [SCORM]: cases = 65, controls = 238) and more than 21 years (Singapore Prospective Study Program [SP2]: cases = 222, controls = 435) for GWA studies, and a Japanese dataset aged more than 20 years (cases = 959, controls = 2128) for replication. METHODS Genomic DNA samples from SCORM and SP2 were genotyped using various Illumina Beadarray platforms (>HumanHap 500). Single-locus association tests were conducted for each dataset with meta-analysis using pooled z-scores. The top-ranked genetic markers were examined for replication in the Japanese dataset. Fisher P was calculated for the combined analysis of all 3 cohorts. MAIN OUTCOME MEASURES High myopia, defined by spherical equivalent (SE) ≤ -6.00 diopters (D); controls defined by SE between -0.50 and +1.00 D. RESULTS Two SNPs (rs12716080 and rs6885224) in the gene CTNND2 on chromosome 5p15 ranked top in the meta-analysis of our Chinese datasets (meta P = 1.14 × 10(-5) and meta P = 1.51 × 10(-5), respectively) with strong supporting evidence in each individual dataset analysis (max P = 1.85 × 10(-4) in SCORM: max P = 8.8 × 10(-3) in SP2). Evidence of replication was observed in the Japanese dataset for rs6885224 (P = 0.035, meta P of 3 datasets: 7.84 × 10(-6)). CONCLUSIONS This study identified a strong association of CTNND2 for high myopia in Asian datasets. The CTNND2 gene maps to a known high myopia linkage region on chromosome 5p15.
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Affiliation(s)
- Yi-Ju Li
- Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, North Carolina, USA
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119
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Ong RTH, Liu X, Poh WT, Sim X, Chia KS, Teo YY. A method for identifying haplotypes carrying the causative allele in positive natural selection and genome-wide association studies. Bioinformatics 2011; 27:822-8. [PMID: 21216773 DOI: 10.1093/bioinformatics/btr007] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
MOTIVATION Methods for detecting positive selection relied on finding evidence of long haplotypes to identify candidate regions under selection. However, these methods generally do not identify the length and form of the selected haplotype. RESULTS We present HapFinder, a method which can find the common longest haplotype under three different settings from a database, which is relevant in the analysis of positive selection in population genetics and also in medical genetics for finding the likely haplotype form carrying the causal allele at the functional polymorphism. AVAILABILITY A java program, implementing the methods described in HapFinder, together with R scripts and datasets for producing the figures presented in this article are publicly available at http://www.nus-cme.org.sg/sgvp/software/hapfinder.html. The site also hosts an online browser for finding haplotypes from the International HapMap Project and the Singapore Genome Variation Project.
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Affiliation(s)
- Rick Twee-Hee Ong
- Department of Epidemiology and Public Health, National University of Singapore, Singapore.
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120
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Chen J, Teo YY, Toh DSL, Sung C. Interethnic comparisons of important pharmacology genes using SNP databases: potential application to drug regulatory assessments. Pharmacogenomics 2010; 11:1077-94. [PMID: 20712526 DOI: 10.2217/pgs.10.79] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
Abstract
BACKGROUND The frequencies of alleles implicated in drug-response variability provide vital information for public health management. Differences in frequencies between genetically diverse groups of individuals can hamper drug assessments, particularly in populations where clinical data are not readily available. MATERIALS & METHODS Making use of large, publicly available population genotype databases and population genetics tools, we developed a quick and efficient methodology to assess population divergence, which could be integrated into drug assessment and regulatory processes. To showcase its effectiveness, we present an analysis of population differences in a set of 42 important pharmacogenomics genes (PharmGKB) by utilizing allele frequencies of SNPs shared among three ethnic groups in the recently completed Singapore Genome Variation Project (Chinese, Malay and Indian) and four populations in the International HapMap project. RESULTS The analyses facilitate comparisons across populations, such as identification of genes that exhibit moderate-to-high divergence between the main ethnic groups in Singapore and Caucasians, the dominant population in most drug-development programs. CONCLUSION A potential use of the analyses is for regulators to develop a decision tree based on the extent of population divergence in key drug targets, metabolizing enzymes or transporter pathways when reviewing foreign clinical trial data. The methodology can be readily extended to other genes and countries with diverse ethnic groups. We continue to explore ways of integrating the information from these population genetics tools into stratifying the risk that the drug response established in one population could be translated to another.
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121
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Hartman M, Suo C, Lim WY, Miao H, Teo YY, Chia KS. Ability to predict breast cancer in Asian women using a polygenic susceptibility model. Breast Cancer Res Treat 2010; 127:805-12. [DOI: 10.1007/s10549-010-1279-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2010] [Accepted: 11/18/2010] [Indexed: 01/14/2023]
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Kaput J, Evelo CT, Perozzi G, van Ommen B, Cotton R. Connecting the Human Variome Project to nutrigenomics. GENES & NUTRITION 2010; 5:275-283. [PMID: 28300226 PMCID: PMC2989367 DOI: 10.1007/s12263-010-0186-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/17/2010] [Accepted: 09/24/2010] [Indexed: 10/19/2022]
Abstract
Nutrigenomics is the science of analyzing and understanding gene-nutrient interactions, which because of the genetic heterogeneity, varying degrees of interaction among gene products, and the environmental diversity is a complex science. Although much knowledge of human diversity has been accumulated, estimates suggest that ~90% of genetic variation has not yet been characterized. Identification of the DNA sequence variants that contribute to nutrition-related disease risk is essential for developing a better understanding of the complex causes of disease in humans, including nutrition-related disease. The Human Variome Project (HVP; http://www.humanvariomeproject.org/) is an international effort to systematically identify genes, their mutations, and their variants associated with phenotypic variability and indications of human disease or phenotype. Since nutrigenomic research uses genetic information in the design and analysis of experiments, the HVP is an essential collaborator for ongoing studies of gene-nutrient interactions. With the advent of next generation sequencing methodologies and the understanding of the undiscovered variation in human genomes, the nutrigenomic community will be generating novel sequence data and results. The guidelines and practices of the HVP can guide and harmonize these efforts.
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Affiliation(s)
- Jim Kaput
- Division of Personalised Nutrition and Medicine, FDA/National Center for Toxicological Research, 3900 NCTR Road, Jefferson, AR 72079 USA
| | - Chris T. Evelo
- Department of Bioinformatics (BiGCaT), Maastricht University, Maastricht, The Netherlands
| | - Giuditta Perozzi
- INRAN—National Research Institute on Food & Nutrition, Via Ardeatina 546, 00178 Rome, Italy
| | - Ben van Ommen
- TNO Quality of Life, P.O. box 360, 3700 AJ Zeist, The Netherlands
| | - Richard Cotton
- Genomic Disorders Research Centre, Level 2, Alan Gilbert Building, 161 Barry Street, Melbourne, VIC 3053 Australia
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123
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Ku CS, Naidoo N, Teo SM, Pawitan Y. Regions of homozygosity and their impact on complex diseases and traits. Hum Genet 2010; 129:1-15. [PMID: 21104274 DOI: 10.1007/s00439-010-0920-6] [Citation(s) in RCA: 75] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2010] [Accepted: 11/04/2010] [Indexed: 12/23/2022]
Abstract
Regions of homozygosity (ROHs) are more abundant in the human genome than previously thought. These regions are without heterozygosity, i.e. all the genetic variations within the regions have two identical alleles. At present there are no standardized criteria for defining the ROHs resulting in the different studies using their own criteria in the analysis of homozygosity. Compared to the era of genotyping microsatellite markers, the advent of high-density single nucleotide polymorphism genotyping arrays has provided an unparalleled opportunity to comprehensively detect these regions in the whole genome in different populations. Several studies have identified ROHs which were associated with complex phenotypes such as schizophrenia, late-onset of Alzheimer's disease and height. Collectively, these studies have conclusively shown the abundance of ROHs larger than 1 Mb in outbred populations. The homozygosity association approach holds great promise in identifying genetic susceptibility loci harboring recessive variants for complex diseases and traits.
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Affiliation(s)
- Chee Seng Ku
- Department of Epidemiology and Public Health, Centre for Molecular Epidemiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
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124
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Ku CS, Pawitan Y, Sim X, Ong RTH, Seielstad M, Lee EJD, Teo YY, Chia KS, Salim A. Genomic copy number variations in three Southeast Asian populations. Hum Mutat 2010; 31:851-7. [PMID: 20506136 DOI: 10.1002/humu.21287] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Research on the role of copy number variations (CNVs) in the genetic risk of diseases in Asian populations has been hampered by a relative lack of reference CNV maps for Asian populations outside the East Asians. In this article, we report the population characteristics of CNVs in Chinese, Malay, and Asian Indian populations in Singapore. Using the Illumina Human 1M Beadchip array, we identify 1,174 CNV loci in these populations that corroborated with findings when the same samples were typed on the Affymetrix 6.0 platform. We identify 441 novel loci not previously reported in the Database of Genomic Variations (DGV). We observe a considerable number of loci that span all three populations and were previously unreported, as well as population-specific loci that are quite common in the respective populations. From this we observe the distribution of CNVs in the Asian Indian population to be considerably different from the Chinese and Malay populations. About half of the deletion loci and three-quarters of duplication loci overlap UCSC genes. Tens of loci show population differentiation and overlap with genes previously known to be associated with genetic risk of diseases. One of these loci is the CYP2A6 deletion, previously linked to reduced susceptibility to lung cancer.
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Affiliation(s)
- Chee-Seng Ku
- Centre for Molecular Epidemiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
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Dehwah MAS, Wang M, Huang QY. CDKAL1 and type 2 diabetes: a global meta-analysis. GENETICS AND MOLECULAR RESEARCH 2010; 9:1109-20. [PMID: 20568056 DOI: 10.4238/vol9-2gmr802] [Citation(s) in RCA: 60] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
CDKAL1 (cyckin-dependent kinase 5 regulatory subunit-associated protein 1-like 1) has been shown to be associated with type 2 diabetes in various ethnic groups; however, contradictory results have been reported. We performed a comprehensive meta-analysis of 21 studies for rs7756992, 17 studies for rs7754840 and 10 studies for rs10946398 variants of the CDKAL1 gene to evaluate the effect of CDKAL1 on genetic susceptibility for type 2 diabetes. We found a significant association of rs7756992, rs7754840 and rs10946398 in CDKAL1 with type 2 diabetes (odds ratio (OR) = 1.15, 95% confidence interval (CI) = 1.07-1.23, P < 0.0001; OR = 1.14, 95%CI = 1.06-1.24, P = 0.001, and OR = 1.12, 95%CI = 1.07-1.18, P < 0.0001, respectively). We conclude that there are significant associations between CDKAL1 polymorphisms and type 2 diabetes, but these associations vary in different ethnic populations.
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Affiliation(s)
- M A S Dehwah
- Hubei Key Lab of Genetic Regulation and Integrative Biology, College of Life Sciences, Huazhong Normal University, Wuhan, Hubei, China
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Andiappan AK, Anantharaman R, Nilkanth PP, Wang DY, Chew FT. Evaluating the transferability of Hapmap SNPs to a Singapore Chinese population. BMC Genet 2010; 11:36. [PMID: 20459637 PMCID: PMC2877651 DOI: 10.1186/1471-2156-11-36] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2009] [Accepted: 05/07/2010] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The International Hapmap project serves as a valuable resource for human genome variation data, however its applicability to other populations has yet to be exhaustively investigated. In this paper, we use high density genotyping chips and resequencing strategies to compare the Singapore Chinese population with the Hapmap populations. First we compared 1028 and 114 unrelated Singapore Chinese samples genotyped using the Illumina Human Hapmap 550 k chip and Affymetrix 500 k array respectively against the 270 samples from Hapmap. Secondly, data from 20 candidate genes on 5q31-33 resequenced for an asthma candidate gene based study was also used for the analysis. RESULTS A total of 237 SNPs were identified through resequencing of which only 95 SNPs (40%) were in Hapmap; however an additional 56 SNPs (24%) were not genotyped directly but had a proxy SNP in the Hapmap. At the genome-wide level, Singapore Chinese were highly correlated with Hapmap Han Chinese with correlation of 0.954 and 0.947 for the Illumina and Affymetrix platforms respectively with deviant SNPs randomly distributed within and across all chromosomes. CONCLUSIONS The high correlation between our population and Hapmap Han Chinese reaffirms the applicability of Hapmap based genome-wide chips for GWA studies. There is a clear population signature for the Singapore Chinese samples and they predominantly resemble the southern Han Chinese population; however when new migrants particularly those with northern Han Chinese background were included, population stratification issues may arise. Future studies needs to address population stratification within the sample collection while designing and interpreting GWAS in the Chinese population.
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Affiliation(s)
- Anand Kumar Andiappan
- Department of Biological Sciences, National University of Singapore, Science Drive 4, Singapore 117543
| | - Ramani Anantharaman
- Department of Biological Sciences, National University of Singapore, Science Drive 4, Singapore 117543
| | - Pallavi Parate Nilkanth
- Department of Biological Sciences, National University of Singapore, Science Drive 4, Singapore 117543
| | - De Yun Wang
- Department of Otolaryngology, National University of Singapore, 10 Lower Kent Ridge Road, Singapore 119260
| | - Fook Tim Chew
- Department of Biological Sciences, National University of Singapore, Science Drive 4, Singapore 117543
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Current world literature. Curr Opin Lipidol 2010; 21:148-52. [PMID: 20616627 DOI: 10.1097/mol.0b013e3283390e49] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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128
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Teo YY, Sim X. Patterns of linkage disequilibrium in different populations: implications and opportunities for lipid-associated loci identified from genome-wide association studies. Curr Opin Lipidol 2010; 21:104-15. [PMID: 20125009 DOI: 10.1097/mol.0b013e3283369e5b] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
PURPOSE OF REVIEW Genome-wide association studies across numerous populations have uncovered a remarkable number of loci implicated with lipid-related traits. The association signals at a number of these loci have been successfully replicated across multiple populations, but a fraction failed to be reproduced when tested in other populations. The present review examines the patterns of linkage disequilibrium at these lipid-associated loci and the implications to replication studies, meta-analyses and fine-mapping efforts across multiple populations. RECENT FINDINGS The extent of linkage disequilibrium has been well established to differ across populations, particularly between African and non-African groups. A novel strategy has been developed for assessing interpopulation variations in regional patterns of linkage disequilibrium. This approach has been applied to the genomes of populations in public databases, identifying regions where linkage disequilibrium is considerably different, some of which exist in regions associated with phenotypic variation. It has been shown that such diversity in linkage disequilibrium can challenge replication studies and meta-analyses while benefiting the pursuit for the functional variants in fine-mapping studies. SUMMARY The next phases in genome-wide studies aim to reproduce the emerging association signals across different populations and to identify the functional variants directly responsible for these signals. Recent publications are beginning to yield valuable insights into the unique challenges and opportunities presented by both consistent and varying patterns of linkage disequilibrium in these follow-up phases.
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Affiliation(s)
- Yik-Ying Teo
- Department of Statistics and Applied Probability, Singapore.
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Ong RTH, Teo YY. varLD: a program for quantifying variation in linkage disequilibrium patterns between populations. Bioinformatics 2010; 26:1269-70. [PMID: 20308177 DOI: 10.1093/bioinformatics/btq125] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
MOTIVATION Linkage disequilibrium (LD) differences between populations can potentially result in failure to replicate primary signals of trait association in independent genome-wide association studies (GWAS). However, such inter-population LD differences can be leveraged to narrow the search for common causal variants responsible for the association signals observed. The ability to assess and quantify LD variations among populations is thus expected to contribute to both replication and fine-mapping stages of GWAS. AVAILABILITY The program varLD is available for download from http://www.nus-cme.org.sg/software/varld.html.
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Affiliation(s)
- Rick Twee-Hee Ong
- NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore
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