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Tan CCS, Ko KKK, Chen H, Liu J, Loh M, Chia M, Nagarajan N. No evidence for a common blood microbiome based on a population study of 9,770 healthy humans. Nat Microbiol 2023; 8:973-985. [PMID: 36997797 PMCID: PMC10159858 DOI: 10.1038/s41564-023-01350-w] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Accepted: 03/02/2023] [Indexed: 04/01/2023]
Abstract
Human blood is conventionally considered sterile but recent studies suggest the presence of a blood microbiome in healthy individuals. Here we characterized the DNA signatures of microbes in the blood of 9,770 healthy individuals using sequencing data from multiple cohorts. After filtering for contaminants, we identified 117 microbial species in blood, some of which had DNA signatures of microbial replication. They were primarily commensals associated with the gut (n = 40), mouth (n = 32) and genitourinary tract (n = 18), and were distinct from pathogens detected in hospital blood cultures. No species were detected in 84% of individuals, while the remainder only had a median of one species. Less than 5% of individuals shared the same species, no co-occurrence patterns between different species were observed and no associations between host phenotypes and microbes were found. Overall, these results do not support the hypothesis of a consistent core microbiome endogenous to human blood. Rather, our findings support the transient and sporadic translocation of commensal microbes from other body sites into the bloodstream.
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Affiliation(s)
- Cedric C S Tan
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore.
- UCL Genetics Institute, University College London, London, UK.
| | - Karrie K K Ko
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
- Department of Microbiology, Singapore General Hospital, Singapore, Republic of Singapore
- Department of Molecular Pathology, Singapore General Hospital, Singapore, Republic of Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Republic of Singapore
| | - Hui Chen
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Jianjun Liu
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Marie Loh
- Population and Global Health, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Republic of Singapore
- Department of Epidemiology and Biostatistics, Imperial College London, South Kensington, London, UK
- National Skin Centre, Singapore, Republic of Singapore
| | - Minghao Chia
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Niranjan Nagarajan
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore.
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Republic of Singapore.
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2
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Alva O, Leroy A, Heiske M, Pereda-Loth V, Tisseyre L, Boland A, Deleuze JF, Rocha J, Schlebusch C, Fortes-Lima C, Stoneking M, Radimilahy C, Rakotoarisoa JA, Letellier T, Pierron D. The loss of biodiversity in Madagascar is contemporaneous with major demographic events. Curr Biol 2022; 32:4997-5007.e5. [PMID: 36334586 DOI: 10.1016/j.cub.2022.09.060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 07/13/2022] [Accepted: 09/28/2022] [Indexed: 11/06/2022]
Abstract
Only 400 km off the coast of East Africa, the island of Madagascar is one of the last large land masses to have been colonized by humans. While many questions surround the human occupation of Madagascar, recent studies raise the question of human impact on endemic biodiversity and landscape transformation. Previous genetic and linguistic analyses have shown that the Malagasy population has emerged from an admixture that happened during the last millennium, between Bantu-speaking African populations and Austronesian-speaking Asian populations. By studying the sharing of chromosome segments between individuals (IBD determination), local ancestry information, and simulated genetic data, we inferred that the Malagasy ancestral Asian population was isolated for more than 1,000 years with an effective size of just a few hundred individuals. This isolation ended around 1,000 years before present (BP) by admixture with a small African population. Around the admixture time, there was a rapid demographic expansion due to intrinsic population growth of the newly admixed population, which coincides with extensive changes in Madagascar's landscape and the extinction of all endemic large-bodied vertebrates. Therefore, our approach can provide new insights into past human demography and associated impacts on ecosystems.
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Affiliation(s)
- Omar Alva
- Équipe de Médecine Evolutive, EVOLSAN faculté de chirurgie dentaire, Université Toulouse III, Toulouse, France
| | - Anaïs Leroy
- Équipe de Médecine Evolutive, EVOLSAN faculté de chirurgie dentaire, Université Toulouse III, Toulouse, France
| | - Margit Heiske
- Équipe de Médecine Evolutive, EVOLSAN faculté de chirurgie dentaire, Université Toulouse III, Toulouse, France
| | - Veronica Pereda-Loth
- Équipe de Médecine Evolutive, EVOLSAN faculté de chirurgie dentaire, Université Toulouse III, Toulouse, France
| | - Lenka Tisseyre
- Équipe de Médecine Evolutive, EVOLSAN faculté de chirurgie dentaire, Université Toulouse III, Toulouse, France
| | - Anne Boland
- Commissariat à l'Energie Atomique, Institut Génomique, Centre National de Génotypage, 91000 Evry, France
| | - Jean-François Deleuze
- Commissariat à l'Energie Atomique, Institut Génomique, Centre National de Génotypage, 91000 Evry, France
| | - Jorge Rocha
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, Universidade do Porto, 4485-661 Vairão, Portugal; Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, 4099-002 Porto, Portugal; BIOPOLIS Program in Genomics, Biodiversity and Land Planning, CIBIO, Campus de Vairão, 4485-661 Vairão, Portugal
| | - Carina Schlebusch
- Human Evolution, Department of Organismal Biology, Evolutionary Biology Centre, Uppsala University, Norbyvägen 18C, 75236 Uppsala, Sweden
| | - Cesar Fortes-Lima
- Human Evolution, Department of Organismal Biology, Evolutionary Biology Centre, Uppsala University, Norbyvägen 18C, 75236 Uppsala, Sweden
| | - Mark Stoneking
- Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, D-04103 Leipzig, Germany; Université Lyon 1, CNRS, Laboratoire de Biométrie et Biologie Evolutive, UMR 5558, Villeurbanne, France
| | - Chantal Radimilahy
- Musée d'Art et d'Archéologie, University of Antananarivo, Antananarivo, Madagascar
| | | | - Thierry Letellier
- Équipe de Médecine Evolutive, EVOLSAN faculté de chirurgie dentaire, Université Toulouse III, Toulouse, France
| | - Denis Pierron
- Équipe de Médecine Evolutive, EVOLSAN faculté de chirurgie dentaire, Université Toulouse III, Toulouse, France.
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3
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Halim-Fikri H, Syed-Hassan SNRK, Wan-Juhari WK, Assyuhada MGSN, Hernaningsih Y, Yusoff NM, Merican AF, Zilfalil BA. Central resources of variant discovery and annotation and its role in precision medicine. ASIAN BIOMED 2022; 16:285-298. [PMID: 37551357 PMCID: PMC10392146 DOI: 10.2478/abm-2022-0032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/09/2023]
Abstract
Rapid technological advancement in high-throughput genomics, microarray, and deep sequencing technologies has accelerated the possibility of more complex precision medicine research using large amounts of heterogeneous health-related data from patients, including genomic variants. Genomic variants can be identified and annotated based on the reference human genome either within the sequence as a whole or in a putative functional genomic element. The American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) mutually created standards and guidelines for the appraisal of proof to expand consistency and straightforwardness in clinical variation interpretations. Various efforts toward precision medicine have been facilitated by many national and international public databases that classify and annotate genomic variation. In the present study, several resources are highlighted with recognition and data spreading of clinically important genetic variations.
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Affiliation(s)
- Hashim Halim-Fikri
- Malaysian Node of the Human Variome Project, School of Medical Sciences, Universiti Sains Malaysia, Kelantan16150, Malaysia
| | | | - Wan-Khairunnisa Wan-Juhari
- Malaysian Node of the Human Variome Project, School of Medical Sciences, Universiti Sains Malaysia, Kelantan16150, Malaysia
- Human Genome Centre, School of Medical Sciences, Universiti Sains Malaysia, Kelantan16150, Malaysia
| | - Mat Ghani Siti Nor Assyuhada
- Malaysian Node of the Human Variome Project, School of Medical Sciences, Universiti Sains Malaysia, Kelantan16150, Malaysia
| | - Yetti Hernaningsih
- Department of Clinical Pathology, Faculty of Medicine Universitas Airlangga, Dr. Soetomo Academic General Hospital, Surabaya, Indonesia
| | - Narazah Mohd Yusoff
- Department of Clinical Pathology, Faculty of Medicine Universitas Airlangga, Dr. Soetomo Academic General Hospital, Surabaya, Indonesia
- Clinical Diagnostic Laboratory, Advanced Medical and Dental Institute, Universiti Sains Malaysia, Penang13200, Malaysia
| | - Amir Feisal Merican
- Institute of Biological Sciences, Faculty of Science, University of Malaya, Kuala Lumpur50603, Malaysia
- Center of Research for Computational Sciences and Informatics in Biology, Bio Industry, Environment, Agriculture and Healthcare (CRYSTAL), University of Malaya, Kuala Lumpur50603, Malaysia
| | - Bin Alwi Zilfalil
- Malaysian Node of the Human Variome Project, School of Medical Sciences, Universiti Sains Malaysia, Kelantan16150, Malaysia
- Human Genome Centre, School of Medical Sciences, Universiti Sains Malaysia, Kelantan16150, Malaysia
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4
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New Drug Development and Clinical Trial Design by Applying Genomic Information Management. Pharmaceutics 2022; 14:pharmaceutics14081539. [PMID: 35893795 PMCID: PMC9330622 DOI: 10.3390/pharmaceutics14081539] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 07/19/2022] [Accepted: 07/22/2022] [Indexed: 02/04/2023] Open
Abstract
Depending on the patients’ genotype, the same drug may have different efficacies or side effects. With the cost of genomic analysis decreasing and reliability of analysis methods improving, vast amount of genomic information has been made available. Several studies in pharmacology have been based on genomic information to select the optimal drug, determine the dose, predict efficacy, and prevent side effects. This paper reviews the tissue specificity and genomic information of cancer. If the tissue specificity of cancer is low, cancer is induced in various organs based on a single gene mutation. Basket trials can be performed for carcinomas with low tissue specificity, confirming the efficacy of one drug for a single gene mutation in various carcinomas. Conversely, if the tissue specificity of cancer is high, cancer is induced in only one organ based on a single gene mutation. An umbrella trial can be performed for carcinomas with a high tissue specificity. Some drugs are effective for patients with a specific genotype. A companion diagnostic strategy that prescribes a specific drug for patients selected with a specific genotype is also reviewed. Genomic information is used in pharmacometrics to identify the relationship among pharmacokinetics, pharmacodynamics, and biomarkers of disease treatment effects. Utilizing genomic information, sophisticated clinical trials can be designed that will be better suited to the patients of specific genotypes. Genomic information also provides prospects for innovative drug development. Through proper genomic information management, factors relating to drug response and effects can be determined by selecting the appropriate data for analysis and by understanding the structure of the data. Selecting pre-processing and appropriate machine-learning libraries for use as machine-learning input features is also necessary. Professional curation of the output result is also required. Personalized medicine can be realized using a genome-based customized clinical trial design.
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5
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Eph and Ephrin Variants in Malaysian Neural Tube Defect Families. Genes (Basel) 2022; 13:genes13060952. [PMID: 35741713 PMCID: PMC9222557 DOI: 10.3390/genes13060952] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 05/20/2022] [Accepted: 05/23/2022] [Indexed: 02/01/2023] Open
Abstract
Neural tube defects (NTDs) are common birth defects with a complex genetic etiology. Mouse genetic models have indicated a number of candidate genes, of which functional mutations in some have been found in human NTDs, usually in a heterozygous state. This study focuses on Ephs-ephrins as candidate genes of interest owing to growing evidence of the role of this gene family during neural tube closure in mouse models. Eph-ephrin genes were analyzed in 31 Malaysian individuals comprising seven individuals with sporadic spina bifida, 13 parents, one twin-sibling and 10 unrelated controls. Whole exome sequencing analysis and bioinformatic analysis were performed to identify variants in 22 known Eph-ephrin genes. We reported that three out of seven spina bifida probands and three out of thirteen family members carried a variant in either EPHA2 (rs147977279), EPHB6 (rs780569137) or EFNB1 (rs772228172). Analysis of public databases shows that these variants are rare. In exome datasets of the probands and parents of the probands with Eph-ephrin variants, the genotypes of spina bifida-related genes were compared to investigate the probability of the gene–gene interaction in relation to environmental risk factors. We report the presence of Eph-ephrin gene variants that are prevalent in a small cohort of spina bifida patients in Malaysian families.
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Göllner T, Larena M, Kutanan W, Lukas H, Fieder M, Schaschl H. Unveiling the Genetic History of the Maniq, a primary hunter-gatherer society. Genome Biol Evol 2022; 14:6526392. [PMID: 35143674 PMCID: PMC9005329 DOI: 10.1093/gbe/evac021] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/01/2022] [Indexed: 11/17/2022] Open
Abstract
The Maniq of southern Thailand is one of the last remaining practicing hunter-gatherer communities in the world. However, our knowledge on their genetic origins and demographic history is still largely limited. We present here the genotype data covering ∼2.3 million single nucleotide polymorphisms of 11 unrelated Maniq individuals. Our analyses reveal the Maniq to be closely related to the Semang populations of Malaysia (Malay Negritos), who altogether carry an Andamanese-related ancestry linked to the ancient Hòabìnhian hunter-gatherers of Mainland Southeast Asia (MSEA). Moreover, the Maniq possess ∼35% East Asian-related ancestry, likely brought about by recent admixture with surrounding agriculturist communities in the region. In addition, the Maniq exhibit one of the highest levels of genetic differentiation found among living human populations, indicative of their small population size and historical practice of endogamy. Similar to other hunter-gatherer populations of MSEA, we also find the Maniq to possess low levels of Neanderthal ancestry and undetectable levels of Denisovan ancestry. Altogether, we reveal the Maniq to be a Semang group that experienced intense genetic drift and exhibits signs of ancient Hòabìnhian ancestry.
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Affiliation(s)
- Tobias Göllner
- Department of Evolutionary Anthropology, Faculty of Life Sciences, University of Vienna, Vienna, Austria
| | - Maximilian Larena
- Human Evolution, Department of Organismal Biology, Uppsala University, Norbyvägen, Uppsala, 18C, 75236, Sweden
| | - Wibhu Kutanan
- Department of Biology, Faculty of Science, Khon Kaen University, Khon Kaen, 40002, Thailand
| | - Helmut Lukas
- Institute for Social Anthropology, Austrian Academy of Sciences, Vienna, Austria
| | - Martin Fieder
- Department of Evolutionary Anthropology, Faculty of Life Sciences, University of Vienna, Vienna, Austria
| | - Helmut Schaschl
- Department of Evolutionary Anthropology, Faculty of Life Sciences, University of Vienna, Vienna, Austria
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7
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Hoh BP, Deng L, Xu S. The Peopling and Migration History of the Natives in Peninsular Malaysia and Borneo: A Glimpse on the Studies Over the Past 100 years. Front Genet 2022; 13:767018. [PMID: 35154269 PMCID: PMC8829068 DOI: 10.3389/fgene.2022.767018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Accepted: 01/07/2022] [Indexed: 12/05/2022] Open
Abstract
Southeast Asia (SEA) has one of the longest records of modern human habitation out-of-Africa. Located at the crossroad of the mainland and islands of SEA, Peninsular Malaysia is an important piece of puzzle to the map of peopling and migration history in Asia, a question that is of interest to many anthropologists, archeologists, and population geneticists. This review aims to revisit our understanding to the population genetics of the natives from Peninsular Malaysia and Borneo over the past century based on the chronology of the technology advancement: 1) Anthropological and Physical Characterization; 2) Blood Group Markers; 3) Protein Markers; 4) Mitochondrial and Autosomal DNA Markers; and 5) Whole Genome Analysis. Subsequently some missing gaps of the study are identified. In the later part of this review, challenges of studying the population genetics of natives will be elaborated. Finally, we conclude our review by reiterating the importance of unveiling migration history and genetic diversity of the indigenous populations as a steppingstone towards comprehending disease evolution and etiology.
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Affiliation(s)
- Boon-Peng Hoh
- Faculty of Medicine and Health Sciences, UCSI University, UCSI Hospital, Port Dickson, Malaysia
- *Correspondence: Boon-Peng Hoh,
| | - Lian Deng
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
- Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, China
- Jiangsu Key Laboratory of Phylogenomics and Comparative Genomics, School of Life Sciences, Jiangsu Normal University, Xuzhou, China
- Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
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8
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Liu Y, Lv Y, Zarrei M, Dong R, Yang X, Higginbotham EJ, Li Y, Zhao D, Song F, Yang Y, Zhang H, Wang Y, Scherer SW, Gai Z. Chromosomal microarray analysis of 410 Han Chinese patients with autism spectrum disorder or unexplained intellectual disability and developmental delay. NPJ Genom Med 2022; 7:1. [PMID: 35022430 PMCID: PMC8755789 DOI: 10.1038/s41525-021-00271-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2019] [Accepted: 11/09/2021] [Indexed: 12/20/2022] Open
Abstract
Copy number variants (CNVs) are recognized as a crucial genetic cause of neurodevelopmental disorders (NDDs). Chromosomal microarray analysis (CMA), the first-tier diagnostic test for individuals with NDDs, has been utilized to detect CNVs in clinical practice, but most reports are still from populations of European ancestry. To contribute more worldwide clinical genomics data, we investigated the genetic etiology of 410 Han Chinese patients with NDDs (151 with autism and 259 with unexplained intellectual disability (ID) and developmental delay (DD)) using CMA (Affymetrix) after G-banding karyotyping. Among all the NDD patients, 109 (26.6%) carried clinically relevant CNVs or uniparental disomies (UPDs), and 8 (2.0%) had aneuploidies (6 with trisomy 21 syndrome, 1 with 47,XXY, 1 with 47,XYY). In total, we found 129 clinically relevant CNVs and UPDs, including 32 CNVs in 30 ASD patients, and 92 CNVs and 5 UPDs in 79 ID/DD cases. When excluding the eight patients with aneuploidies, the diagnostic yield of pathogenic and likely pathogenic CNVs and UPDs was 20.9% for all NDDs (84/402), 3.3% in ASD (5/151), and 31.5% in ID/DD (79/251). When aneuploidies were included, the diagnostic yield increased to 22.4% for all NDDs (92/410), and 33.6% for ID/DD (87/259). We identified a de novo CNV in 14.9% (60/402) of subjects with NDDs. Interestingly, a higher diagnostic yield was observed in females (31.3%, 40/128) compared to males (16.1%, 44/274) for all NDDs (P = 4.8 × 10-4), suggesting that a female protective mechanism exists for deleterious CNVs and UPDs.
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Affiliation(s)
- Yi Liu
- Pediatric Research Institute, Qilu Children's Hospital of Shandong University, Ji'nan, 250022, China
| | - Yuqiang Lv
- Pediatric Research Institute, Qilu Children's Hospital of Shandong University, Ji'nan, 250022, China
| | - Mehdi Zarrei
- The Centre for Applied Genomics and Department of Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
| | - Rui Dong
- Pediatric Research Institute, Qilu Children's Hospital of Shandong University, Ji'nan, 250022, China
| | - Xiaomeng Yang
- Pediatric Research Institute, Qilu Children's Hospital of Shandong University, Ji'nan, 250022, China
| | - Edward J Higginbotham
- The Centre for Applied Genomics and Department of Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
| | - Yue Li
- Pediatric Research Institute, Qilu Children's Hospital of Shandong University, Ji'nan, 250022, China
| | - Dongmei Zhao
- Pediatric Health Care Institute, Qilu Children's Hospital of Shandong University, Ji'nan, 250022, China
| | - Fengling Song
- Pediatric Health Care Institute, Qilu Children's Hospital of Shandong University, Ji'nan, 250022, China
| | - Yali Yang
- Rehabilitation Center, Qilu Children's Hospital of Shandong University, Ji'nan, 250022, China
| | - Haiyan Zhang
- Pediatric Research Institute, Qilu Children's Hospital of Shandong University, Ji'nan, 250022, China
| | - Ying Wang
- Pediatric Research Institute, Qilu Children's Hospital of Shandong University, Ji'nan, 250022, China
| | - Stephen W Scherer
- The Centre for Applied Genomics and Department of Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada. .,McLaughlin Centre and Department of Molecular Genetics, University of Toronto, Toronto, ON, M5S 1A1, Canada.
| | - Zhongtao Gai
- Pediatric Research Institute, Qilu Children's Hospital of Shandong University, Ji'nan, 250022, China.
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9
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Wahyudi F, Aghakhanian F, Rahman S, Teo YY, Szpak M, Dhaliwal J, Ayub Q. Prioritising positively selected variants in whole-genome sequencing data using FineMAV. BMC Bioinformatics 2021; 22:604. [PMID: 34922440 PMCID: PMC8684245 DOI: 10.1186/s12859-021-04506-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 11/30/2021] [Indexed: 11/17/2022] Open
Abstract
Background In population genomics, polymorphisms that are highly differentiated between geographically separated populations are often suggestive of Darwinian positive selection. Genomic scans have highlighted several such regions in African and non-African populations, but only a handful of these have functional data that clearly associates candidate variations driving the selection process. Fine-Mapping of Adaptive Variation (FineMAV) was developed to address this in a high-throughput manner using population based whole-genome sequences generated by the 1000 Genomes Project. It pinpoints positively selected genetic variants in sequencing data by prioritizing high frequency, population-specific and functional derived alleles. Results We developed a stand-alone software that implements the FineMAV statistic. To graphically visualise the FineMAV scores, it outputs the statistics as bigWig files, which is a common file format supported by many genome browsers. It is available as a command-line and graphical user interface. The software was tested by replicating the FineMAV scores obtained using 1000 Genomes Project African, European, East and South Asian populations and subsequently applied to whole-genome sequencing datasets from Singapore and China to highlight population specific variants that can be subsequently modelled. The software tool is publicly available at https://github.com/fadilla-wahyudi/finemav. Conclusions The software tool described here determines genome-wide FineMAV scores, using low or high-coverage whole-genome sequencing datasets, that can be used to prioritize a list of population specific, highly differentiated candidate variants for in vitro or in vivo functional screens. The tool displays these scores on the human genome browsers for easy visualisation, annotation and comparison between different genomic regions in worldwide human populations. Supplementary Information The online version contains supplementary material available at 10.1186/s12859-021-04506-9.
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Affiliation(s)
- Fadilla Wahyudi
- School of Science, Monash University Malaysia, 47500, Bandar Sunway, Selangor Darul Ehsan, Malaysia
| | - Farhang Aghakhanian
- Monash University Malaysia Genomics Facility, 47500, Bandar Sunway, Selangor Darul Ehsan, Malaysia.,Genes and Human Disease Research Program, Oklahoma Medical Research Foundation,, Oklahoma City, OK, 73104, USA
| | - Sadequr Rahman
- School of Science, Monash University Malaysia, 47500, Bandar Sunway, Selangor Darul Ehsan, Malaysia.,Tropical Medicine and Biology Multidisciplinary Platform, Monash University Malaysia, 47500, Bandar Sunway, Selangor Darul Ehsan, Malaysia
| | - Yik-Ying Teo
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Michał Szpak
- European Bioinformatics Institute, Hinxton, CB10 1SA, UK.,Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA, UK
| | - Jasbir Dhaliwal
- School of Information Technology, Monash University Malaysia, 47500, Bandar Sunway, Selangor Darul Ehsan, Malaysia.
| | - Qasim Ayub
- School of Science, Monash University Malaysia, 47500, Bandar Sunway, Selangor Darul Ehsan, Malaysia. .,Monash University Malaysia Genomics Facility, 47500, Bandar Sunway, Selangor Darul Ehsan, Malaysia. .,Tropical Medicine and Biology Multidisciplinary Platform, Monash University Malaysia, 47500, Bandar Sunway, Selangor Darul Ehsan, Malaysia.
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10
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African Gene Flow Reduces Beta-Ionone Anosmia/Hyposmia Prevalence in Admixed Malagasy Populations. Brain Sci 2021; 11:brainsci11111405. [PMID: 34827404 PMCID: PMC8615941 DOI: 10.3390/brainsci11111405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Revised: 10/19/2021] [Accepted: 10/20/2021] [Indexed: 11/23/2022] Open
Abstract
While recent advances in genetics make it possible to follow the genetic exchanges between populations and their phenotypic consequences, the impact of the genetic exchanges on the sensory perception of populations has yet to be explored. From this perspective, the present study investigated the consequences of African gene flow on odor perception in a Malagasy population with a predominantly East Asian genetic background. To this end, we combined psychophysical tests with genotype data of 235 individuals who were asked to smell the odorant molecule beta-ionone (βI). Results showed that in this population the ancestry of the OR5A1 gene significantly influences the ability to detect βI. At the individual level, African ancestry significantly protects against specific anosmia/hyposmia due to the higher frequency of the functional gene (OR ratios = 14, CI: 1.8–110, p-value = 0.012). At the population level, African introgression decreased the prevalence of specific anosmia/hyposmia to this odorous compound. Taken together, these findings validate the conjecture that in addition to cultural exchanges, genetic transfer may also influence the sensory perception of the population in contact.
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11
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M R, Nanda N, Sagili H, Rani JM, A Naga S. Association of osteoprotegerin gene T950C polymorphism with cardiometabolic risk factors in gestational diabetes mellitus in South Indian Tamilian women. Diabetes Metab Syndr 2021; 15:102157. [PMID: 34186363 DOI: 10.1016/j.dsx.2021.05.030] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Revised: 05/25/2021] [Accepted: 05/26/2021] [Indexed: 12/13/2022]
Abstract
BACKGROUND & AIMS This study was designed to explore the relevance of Osteoprotegerin (OPG) and its polymorphism in the cardiometabolic risk in gestational diabetes mellitus patients before diet-therapy (GDMA1). METHODS South Indian Tamilian pregnant women were screened and 145 were grouped as GDMA1 (n = 73) and normal pregnancy (n = 72). Serum OPG, TNF α, lipid profile, insulin and blood pressure was compared. Genomic DNA was analysed for rs2073617 T950C polymorphism. Chi square test was done to analyze the frequency distribution of alleles. Multiple regression analysis was done to assess the association among cardiometabolic parameters. RESULTS TNF α (p < 0.01), Osteoprotegerin (p < 0.01), lipid profile (p < 0.01), atherogenic indices (p < 0.01), systolic and diastolic and blood pressure (<0.001) levels were higher in GDMA1 patients. TNF α (p < 0.01) and osteoprotegerin (p < 0.01) were higher in women with CT allele. Osteoprotegerin was independently contributed by BMI in all GDMA1 cases and diastolic blood pressure (DBP) in CT allele cases. There was significantly higher odd (OR = 3.63) in the distribution of CT genotype among the multiparous women. CONCLUSIONS Osteoprotegerin, atherogenic lipid risk factor and inflammation are higher in GDMA1 women. Rise in OPG is contributed by high BMI in GDMA1 women. Higher odds of CT allele distribution in multiparous women suggests that TT allele women are at higher risk of developing GDM in their first pregnancy. Further analysis of T950C polymorphism in a larger cohort is warranted to confirm its role.
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Affiliation(s)
- Rakchna M
- Department of Biochemistry, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India
| | - Nivedita Nanda
- Department of Biochemistry, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India.
| | - Haritha Sagili
- Department of Obstetrics & Gynaecology, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India
| | - Jasmine Manna Rani
- Department of Biochemistry, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India
| | - Sailaja A Naga
- Department of Biochemistry, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India
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12
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Wu D, Li PY, Pan B, Tiang Z, Dou J, Williantarra I, Pribowo AY, Nurdiansyah R, Foo RSY, Wang C. Genetic admixture in the culturally unique Peranakan Chinese population in Southeast Asia. Mol Biol Evol 2021; 38:4463-4474. [PMID: 34152401 PMCID: PMC8476152 DOI: 10.1093/molbev/msab187] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
The Peranakan Chinese are culturally unique descendants of immigrants from China who settled in the Malay Archipelago ∼300-500 years ago. Today, among large communities in Southeast Asia, the Peranakans have preserved Chinese traditions with strong influence from the local indigenous Malays. Yet, whether or to what extent genetic admixture co-occurred with the cultural mixture has been a topic of ongoing debate. We performed whole-genome sequencing (WGS) on 177 Singapore (SG) Peranakans and analyzed the data jointly with WGS data of Asian and European populations. We estimated that Peranakan Chinese inherited ∼5.62% (95% confidence interval [CI]: 4.75-6.46%) Malay ancestry, much higher than that in SG Chinese (1.08%, 0.69-1.53%), southern Chinese (0.86%, 0.57-1.31%), and northern Chinese (0.25%, 0.18-0.33%). A sex-biased admixture history, in which the Malay ancestry was contributed primarily by females, was supported by X chromosomal variants, and mitochondrial (MT) and Y haplogroups. Finally, we identified an ancient admixture event shared by Peranakan Chinese and SG Chinese ∼1,612 (95% CI: 1,345-1,923) years ago, coinciding with the settlement history of Han Chinese in southern China, apart from the recent admixture event with Malays unique to Peranakan Chinese ∼190 (159-213) years ago. These findings greatly advance our understanding of the dispersal history of Chinese and their interaction with indigenous populations in Southeast Asia.
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Affiliation(s)
- Degang Wu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Peter Yiqing Li
- Cardiovascular Research Institute, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- NUHS Cardiovascular Diseases Translational Research Program, National University Health System, Singapore, Singapore
| | - Bangfen Pan
- Cardiovascular Research Institute, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- NUHS Cardiovascular Diseases Translational Research Program, National University Health System, Singapore, Singapore
- Genome Institute of Singapore, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Zenia Tiang
- Cardiovascular Research Institute, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- NUHS Cardiovascular Diseases Translational Research Program, National University Health System, Singapore, Singapore
- Genome Institute of Singapore, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Jinzhuang Dou
- Genome Institute of Singapore, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Ivanna Williantarra
- Department of Anatomy and Medical Imaging, School of Medical Science, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand
- Department of Biotechnology, Indonesia International Institute for Life Sciences (i3L), Jakarta, Indonesia
| | - Amadeus Yeremia Pribowo
- Department of Biotechnology, Indonesia International Institute for Life Sciences (i3L), Jakarta, Indonesia
| | - Rizky Nurdiansyah
- Department of Bioinformatics, Indonesia International Institute for Life Sciences (i3L), Jakarta, Indonesia
| | | | - Roger S Y Foo
- Cardiovascular Research Institute, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- NUHS Cardiovascular Diseases Translational Research Program, National University Health System, Singapore, Singapore
- Genome Institute of Singapore, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
- Corresponding authors: E-mails: ;
| | - Chaolong Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Corresponding authors: E-mails: ;
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13
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Zhu Q, Cao Y, Zhang S, Huang Y, Hu Y, Zhou Y, Wang H, Wang Y, Zhang J. A targeted ancestry informative InDels panel on capillary electrophoresis for ancestry inference in Asian populations. Electrophoresis 2021; 42:1605-1613. [PMID: 34081340 DOI: 10.1002/elps.202100016] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2021] [Revised: 04/12/2021] [Accepted: 05/30/2021] [Indexed: 11/09/2022]
Abstract
CE is the primary methodology used in forensic DNA typing. Alleles of commonly used types of genetic markers could be separated and detected via CE based on dye color and migration time. Insertion/deletion (InDel) is an ideal genetic marker for forensic DNA analysis due to their abundance in the human genome, low mutation rate, availability of their allele types via CE, and elimination of stutter peaks. Moreover, InDels could be used as ancestry informative markers since allele frequencies of InDels is different among geographically separated populations. Several ancestry informative insertion/deletion panels have been established based on CE platform to achieve the intercontinental populations distinction. However, improvements to differentiate intracontinental populations is few. In this study, 21 InDels with fixation index (FST ) > 0.15 were selected and assembled into one ancestry informative insertion/deletion panel. Using well-designed primers, those 21 InDels could be amplified successfully and genotyped on the CE platform accurately and completely. The panel showed a large FST distance distinction among the ten Asian populations. Using clustering analysis, ten Asian populations were classified into three subgroups: East Asian, Southeast Asian, and South Asian subgroups. To evaluate the panel's capability in ancestry inference, a validation experiment was undertaken with 319 individuals from four geographically separated populations in China. Four Chinese populations were classified into different ancestry subgroups and 81.8% test individuals' ancestry could be inferred correctly. Our result showed that development of high ancestry informative InDels panel based on CE platform is a potential for individual ancestry inference among intracontinental populations.
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Affiliation(s)
- Qiang Zhu
- West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, P. R. China
| | - Yueyan Cao
- West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, P. R. China
| | - Shu Zhang
- Basic Medicine Colleges, Chengdu University of Traditional Chinese Medicine, Chengdu, P. R. China
| | - Yuguo Huang
- West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, P. R. China
| | - Yuhan Hu
- West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, P. R. China
| | - Yijun Zhou
- West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, P. R. China
| | - Haoyu Wang
- West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, P. R. China
| | - Yufang Wang
- West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, P. R. China
| | - Ji Zhang
- West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, P. R. China
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14
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Huang X, Wang S, Jin L, He Y. Dissecting dynamics and differences of selective pressures in the evolution of human pigmentation. Biol Open 2021; 10:bio056523. [PMID: 33495209 PMCID: PMC7888712 DOI: 10.1242/bio.056523] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2020] [Accepted: 12/21/2020] [Indexed: 01/05/2023] Open
Abstract
Human pigmentation is a highly diverse and complex trait among populations and has drawn particular attention from both academic and non-academic investigators for thousands of years. Previous studies detected selection signals in several human pigmentation genes, but few studies have integrated contribution from multiple genes to the evolution of human pigmentation. Moreover, none has quantified selective pressures on human pigmentation over epochs and between populations. Here, we dissect dynamics and differences of selective pressures during different periods and between distinct populations with new approaches. We use genotype data of 19 genes associated with human pigmentation from 17 publicly available datasets and obtain data for 2346 individuals of six representative population groups from across the world. Our results quantify the strength of natural selection on light pigmentation not only in modern Europeans (0.0259/generation) but also in proto-Eurasians (0.00650/generation). Our results also suggest that several derived alleles associated with human dark pigmentation may be under positive directional selection in some African populations. Our study provides the first attempt to quantitatively investigate the dynamics of selective pressures during different time periods in the evolution of human pigmentation.This article has an associated First Person interview with the first author of the article.
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Affiliation(s)
- Xin Huang
- Chinese Academy of Sciences Key Laboratory of Computational Biology, Chinese Academy of Sciences-Max Planck Society Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Sijia Wang
- Chinese Academy of Sciences Key Laboratory of Computational Biology, Chinese Academy of Sciences-Max Planck Society Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
- State Key Laboratory of Genetic Engineering and Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Li Jin
- Chinese Academy of Sciences Key Laboratory of Computational Biology, Chinese Academy of Sciences-Max Planck Society Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
- State Key Laboratory of Genetic Engineering and Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Yungang He
- Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
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15
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Hoh BP, Zhang X, Deng L, Yuan K, Yew CW, Saw WY, Hoque MZ, Aghakhanian F, Phipps ME, Teo YY, Subbiah VK, Xu S. Shared Signature of Recent Positive Selection on the TSBP1-BTNL2-HLA-DRA Genes in Five Native Populations from North Borneo. Genome Biol Evol 2020; 12:2245-2257. [PMID: 33022050 PMCID: PMC7738747 DOI: 10.1093/gbe/evaa207] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/28/2020] [Indexed: 11/17/2022] Open
Abstract
North Borneo (NB) is home to more than 40 native populations. These natives are believed to have undergone local adaptation in response to environmental challenges such as the mosquito-abundant tropical rainforest. We attempted to trace the footprints of natural selection from the genomic data of NB native populations using a panel of ∼2.2 million genome-wide single nucleotide polymorphisms. As a result, an ∼13-kb haplotype in the Major Histocompatibility Complex Class II region encompassing candidate genes TSBP1–BTNL2–HLA-DRA was identified to be undergoing natural selection. This putative signature of positive selection is shared among the five NB populations and is estimated to have arisen ∼5.5 thousand years (∼220 generations) ago, which coincides with the period of Austronesian expansion. Owing to the long history of endemic malaria in NB, the putative signature of positive selection is postulated to be driven by Plasmodium parasite infection. The findings of this study imply that despite high levels of genetic differentiation, the NB populations might have experienced similar local genetic adaptation resulting from stresses of the shared environment.
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Affiliation(s)
- Boon-Peng Hoh
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,Faculty of Medicine and Health Sciences, UCSI University, Jalan Menara Gading, Taman Connaught, Malaysia Cheras, Kuala Lumpur
| | - Xiaoxi Zhang
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,School of Life Science and Technology, ShanghaiTech University, Shanghai, China
| | - Lian Deng
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Kai Yuan
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Chee-Wei Yew
- Biotechnology Research Institute, Universiti Malaysia Sabah, Jalan UMS, Kota Kinabalu, Sabah, Malaysia
| | - Woei-Yuh Saw
- Department of Statistics and Applied Probability, Faculty of Science, National University of Singapore, Singapore
| | - Mohammad Zahirul Hoque
- Faculty of Medicine and Health Sciences, Universiti Malaysia Sabah, Jalan UMS, Kota Kinabalu, Sabah, Malaysia
| | - Farhang Aghakhanian
- Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Selangor, Malaysia
| | - Maude E Phipps
- Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Selangor, Malaysia
| | - Yik-Ying Teo
- Department of Statistics and Applied Probability, Faculty of Science, National University of Singapore, Singapore.,Saw Swee Hock School of Public Health, National University of Singapore, Singapore.,NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore.,Life Sciences Institute, National University of Singapore, Singapore.,Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore
| | - Vijay Kumar Subbiah
- Biotechnology Research Institute, Universiti Malaysia Sabah, Jalan UMS, Kota Kinabalu, Sabah, Malaysia
| | - Shuhua Xu
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,School of Life Science and Technology, ShanghaiTech University, Shanghai, China.,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China.,Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China.,Collaborative Innovation Centre of Genetics and Development, Shanghai, China
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16
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Lim K, Lam M, Huang H, Liu J, Lee J. Genetic liability in individuals at ultra-high risk of psychosis: A comparison study of 9 psychiatric traits. PLoS One 2020; 15:e0243104. [PMID: 33264322 PMCID: PMC7710117 DOI: 10.1371/journal.pone.0243104] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Accepted: 11/14/2020] [Indexed: 11/19/2022] Open
Abstract
Individuals at ultra-high risk (UHR) of psychosis are characterised by the emergence of attenuated psychotic symptoms and deterioration in functioning. In view of the high non-psychotic comorbidity and low rates of transition to psychosis, the specificity of the UHR status has been called into question. This study aims to (i) investigate if the UHR construct is associated with the genetic liability of schizophrenia or other psychiatric conditions; (ii) examine the ability of polygenic risk scores (PRS) to discriminate healthy controls from UHR, remission and conversion status. PRS was calculated for 210 youths (nUHR = 102, nControl = 108) recruited as part of the Longitudinal Youth at Risk Study (LYRIKS) using nine psychiatric traits derived from twelve large-scale psychiatric genome-wide association studies as discovery datasets. PRS was also examined to discriminate UHR-Healthy control status, and healthy controls from UHR remission and conversion status. Result indicated that schizophrenia PRS appears to best index the genetic liability of UHR, while trend level associations were observed for depression and cross-disorder PRS. Schizophrenia PRS discriminated healthy controls from UHR (R2 = 7.9%, p = 2.59 x 10-3, OR = 1.82), healthy controls from non-remitters (R2 = 8.1%, p = 4.90 x 10-4, OR = 1.90), and converters (R2 = 7.6%, p = 1.61 x 10-3, OR = 1.82), with modest predictive ability. A trend gradient increase in schizophrenia PRS was observed across categories. The association between schizophrenia PRS and UHR status supports the hypothesis that the schizophrenia polygenic liability indexes the risk for developing psychosis.
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Affiliation(s)
- Keane Lim
- Research Division, Institute of Mental Health, Singapore, Singapore
| | - Max Lam
- Research Division, Institute of Mental Health, Singapore, Singapore
- Feinstein Institute of Medical Research, The Zucker Hillside Hospital, New York, New York, United States of America
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- Genome Institute of Singapore, Singapore, Singapore
| | - Hailiang Huang
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America
| | - Jianjun Liu
- Genome Institute of Singapore, Singapore, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Jimmy Lee
- Research Division, Institute of Mental Health, Singapore, Singapore
- Department of Psychosis, Institute of Mental Health, Singapore, Singapore
- Neuroscience and Mental Health, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
- * E-mail:
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17
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Chai JF, Kao SL, Wang C, Lim VJY, Khor IW, Dou J, Podgornaia AI, Chothani S, Cheng CY, Sabanayagam C, Wong TY, van Dam RM, Liu J, Reilly DF, Paterson AD, Sim X. Genome-Wide Association for HbA1c in Malay Identified Deletion on SLC4A1 that Influences HbA1c Independent of Glycemia. J Clin Endocrinol Metab 2020; 105:5906591. [PMID: 32936915 DOI: 10.1210/clinem/dgaa658] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Accepted: 09/15/2020] [Indexed: 12/30/2022]
Abstract
CONTEXT Glycated hemoglobin A1c (HbA1c) level is used to screen and diagnose diabetes. Genetic determinants of HbA1c can vary across populations and many of the genetic variants influencing HbA1c level were specific to populations. OBJECTIVE To discover genetic variants associated with HbA1c level in nondiabetic Malay individuals. DESIGN AND PARTICIPANTS We conducted a genome-wide association study (GWAS) analysis for HbA1c using 2 Malay studies, the Singapore Malay Eye Study (SiMES, N = 1721 on GWAS array) and the Living Biobank study (N = 983 on GWAS array and whole-exome sequenced). We built a Malay-specific reference panel to impute ethnic-specific variants and validate the associations with HbA1c at ethnic-specific variants. RESULTS Meta-analysis of the 1000 Genomes imputed array data identified 4 loci at genome-wide significance (P < 5 × 10-8). Of the 4 loci, 3 (ADAM15, LINC02226, JUP) were novel for HbA1c associations. At the previously reported HbA1c locus ATXN7L3-G6PC3, association analysis using the exome data fine-mapped the HbA1c associations to a 27-bp deletion (rs769664228) at SLC4A1 that reduced HbA1c by 0.38 ± 0.06% (P = 3.5 × 10-10). Further imputation of this variant in SiMES confirmed the association with HbA1c at SLC4A1. We also showed that these genetic variants influence HbA1c level independent of glucose level. CONCLUSION We identified a deletion at SLC4A1 associated with HbA1c in Malay. The nonglycemic lowering of HbA1c at rs769664228 might cause individuals carrying this variant to be underdiagnosed for diabetes or prediabetes when HbA1c is used as the only diagnostic test for diabetes.
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Affiliation(s)
- Jin-Fang Chai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Shih-Ling Kao
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Chaolong Wang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore
| | - Victor Jun-Yu Lim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Ing Wei Khor
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Jinzhuang Dou
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore
| | | | - Sonia Chothani
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Charumathi Sabanayagam
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
| | - Tien-Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Rob M van Dam
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
- Department of Nutrition, Harvard T.H Chan School of Public Health, Boston, Massachusetts
| | - Jianjun Liu
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore
| | - Dermot F Reilly
- Merck Research Laboratories, Kenilworth, New Jersey
- Janssen Pharmaceuticals Inc, Titusville, New Jersey
| | - Andrew D Paterson
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Canada
- Divisions of Epidemiology and Biostatistics, Dalla Lana School of Public Health, University of Toronto, Canada
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
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18
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Koh JQS, Mohamed Rahim NB, Sng EL, Yap J, Zhong L, Thiagarajan N, Lim ST, Ewe SH, Chao V, Ho KW. Five-Meter Walk Test as a Predictor of Prolonged Index Hospitalization After Transcatheter Aortic Valve Implantation. Am J Cardiol 2020; 132:100-105. [PMID: 32762962 DOI: 10.1016/j.amjcard.2020.07.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2020] [Revised: 07/01/2020] [Accepted: 07/03/2020] [Indexed: 10/23/2022]
Abstract
There are no studies evaluating comprehensive predictors of transcatheter aortic valve implantation (TAVI) outcomes encompassing frailty assessments in a South-East Asian cohort. In this longitudinal single-center cohort, all patients who underwent TAVI in a tertiary cardiac center and comprehensively assessed for frailty at baseline were included in a registry. The primary outcome was to investigate frailty indices predictive of prolonged index hospitalization after TAVI. Seventy-six patients with a mean age of 77.6 ± 8.5 years were included. Mean Society of Thoracic Society Predicted Risk of Mortality score was 5.2 ± 3.0, with 11 (14.5%) patients classified as high-risk (Society of Thoracic Society Predicted Risk of Mortality >8). Mean and median index hospitalization duration were 9.2 ± 5.6 and 7 [4.5 to 9.5] days, respectively. Univariate analysis demonstrated that lower hemoglobin (Hb) (p <0.01), longer 5-meter walk test (5MWT) (p <0.01), lower dominant hand grip strength (p <0.01), the use of transaortic access (p = 0.01), new atrial fibrillation post-TAVI (p <0.01), and lower postprocedural Hb (p <0.01) were associated with longer index hospitalization duration. Multivariate linear regression demonstrated preoperative Hb, preoperative atrial fibrillation and 5MWT were independent baseline predictors of index hospitalization duration (p <0.05). Additionally, a 5MWT cutoff of 11 seconds (0.45 m/s) had a high specificity (88.6%) in predicting prolonged index hospitalization duration. In conclusion, this is the first comprehensive frailty assessment in a South-East Asian cohort demonstrating 5MWT to be a significant predictor of prolonged index hospitalization. This simple and effective frailty assessment index may be considered to optimize patient selection for TAVI.
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19
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Dou J, Wu D, Ding L, Wang K, Jiang M, Chai X, Reilly DF, Tai ES, Liu J, Sim X, Cheng S, Wang C. Using off-target data from whole-exome sequencing to improve genotyping accuracy, association analysis and polygenic risk prediction. Brief Bioinform 2020; 22:5857014. [PMID: 32591784 DOI: 10.1093/bib/bbaa084] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2020] [Revised: 04/09/2020] [Accepted: 04/21/2020] [Indexed: 12/12/2022] Open
Abstract
Whole-exome sequencing (WES) has been widely used to study the role of protein-coding variants in genetic diseases. Non-coding regions, typically covered by sparse off-target data, are often discarded by conventional WES analyses. Here, we develop a genotype calling pipeline named WEScall to analyse both target and off-target data. We leverage linkage disequilibrium shared within study samples and from an external reference panel to improve genotyping accuracy. In an application to WES of 2527 Chinese and Malays, WEScall can reduce the genotype discordance rate from 0.26% (SE= 6.4 × 10-6) to 0.08% (SE = 3.6 × 10-6) across 1.1 million single nucleotide polymorphisms (SNPs) in the deeply sequenced target regions. Furthermore, we obtain genotypes at 0.70% (SE = 3.0 × 10-6) discordance rate across 5.2 million off-target SNPs, which had ~1.2× mean sequencing depth. Using this dataset, we perform genome-wide association studies of 10 metabolic traits. Despite of our small sample size, we identify 10 loci at genome-wide significance (P < 5 × 10-8), including eight well-established loci. The two novel loci, both associated with glycated haemoglobin levels, are GPATCH8-SLC4A1 (rs369762319, P = 2.56 × 10-12) and ROR2 (rs1201042, P = 3.24 × 10-8). Finally, using summary statistics from UK Biobank and Biobank Japan, we show that polygenic risk prediction can be significantly improved for six out of nine traits by incorporating off-target data (P < 0.01). These results demonstrate WEScall as a useful tool to facilitate WES studies with decent amounts of off-target data.
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Affiliation(s)
- Jinzhuang Dou
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Degang Wu
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lin Ding
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Kai Wang
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Minghui Jiang
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | | | | | - E Shyong Tai
- Saw Swee Hock School of Public Health, Duke-NUS Medical School, and Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Jianjun Liu
- Genome Institute of Singapore and a professor at Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Shanshan Cheng
- Ministry of Education Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Chaolong Wang
- Ministry of Education Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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20
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Maliepaard M, Taams AC, Sung C, Poh J, Yu Y. Ethnicity-Specific Drug Safety Data in European Medicines Agency Registration Dossiers, European Public Assessment Reports, and European and Singapore Drug Labels: Lost in Translation? Pharmaceut Med 2020; 33:407-416. [PMID: 31933229 DOI: 10.1007/s40290-019-00302-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
BACKGROUND Information on drug safety in different ethnic populations reported in public documents such as the European Public Assessment Reports (EPARs), European Summary of Product Characteristics (SmPCs) or Singapore Package Inserts (SGPIs) generally appears limited. OBJECTIVE This study aimed to clarify the extent of drug safety data in ethnic populations that is available in drug registration dossiers used for registration in the European Union (EU) and Singapore, and how much of this information is then included in the EPARs and SmPCs or SGPIs. METHODS For this purpose, drug registration dossiers and these public documents for a selection of 25 drugs authorized both in the EU and Singapore were compared (note, the number of available full registration dossiers was only 24 due to a technical issue). RESULTS Detailed safety data in ethnic groups were present in 23/24 (96%) of the drug registration dossiers, but was only present in 12/25 (48%) of the EPARs, 8/25 (32%) of the SmPCs, and 9/25 (36%) of the SGPIs. Furthermore, in many cases where ethnicity-specific safety information was provided in the SmPC or SGPIs, details on the ethnic subpopulations was not provided. CONCLUSIONS Despite the fact that safety data analyzed with respect to ethnic populations are available in almost all screened registration dossiers, this information is often unknown to patients or prescribers as it was often not included in the EPARs, EU SmPCs or SGPIs. In order to increase the availability of such potentially important safety information, it is recommended to at least provide ethnic populations and group size in these public documents. In this way, trust in the registered drugs in different ethnic populations may be increased, and more robust treatment decisions may be obtained in clinical practice.
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Affiliation(s)
- Marc Maliepaard
- Medicines Evaluation Board, Utrecht, The Netherlands.
- Department of Pharmacology and Toxicology, Radboud University Medical Centre, Nijmegen, The Netherlands.
| | - Anne C Taams
- Medicines Evaluation Board, Utrecht, The Netherlands
| | - Cynthia Sung
- Vigilance and Compliance Branch, Health Sciences Authority, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Jalene Poh
- Vigilance and Compliance Branch, Health Sciences Authority, Singapore, Singapore
| | - Yang Yu
- Medicines Evaluation Board, Utrecht, The Netherlands
- Department of Pharmacology and Toxicology, Radboud University Medical Centre, Nijmegen, The Netherlands
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21
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Reddy G, van Dam RM. Food, culture, and identity in multicultural societies: Insights from Singapore. Appetite 2020; 149:104633. [PMID: 32084519 DOI: 10.1016/j.appet.2020.104633] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2019] [Revised: 01/20/2020] [Accepted: 02/13/2020] [Indexed: 10/25/2022]
Abstract
The choice of food practices can be influenced by one's identity in many societies, but has mostly been evaluated in light of the maintenance of cultural identity in migrant populations. This study focused on understanding the influence of identity on food practices among individuals in multicultural societies. We conducted 18 focus group discussions (n = 130) among Indian, Chinese and Malay women in Singapore. Focus group transcripts were analysed using Thematic Analysis both inductively and deductively. Deductive analysis was framed within a Social Representations Approach, a social psychological theory that allows a deeper understanding of the contextual aspects of identity. Participants highlighted the central position of food in social events, cultural celebrations, and persistent traditional beliefs about health (such as 'hot-cold balance'). These beliefs extended to the perception of certain traditional foods possessing medicinal properties. Importantly, the consumption of these traditional foods was accepted as necessary for the maintenance of health by the women. We propose that while cultural food practices are integral to identity preservation and identity continuity for Singaporean women from all three racial groups, this is different to other multicultural societies such as Canada where communities preserve their cultural food practices, in part, due to fear of cultural identity loss. In addition, cross-cultural food practices are readily adopted in participants' daily lives for a number of reasons such as the promotion of health, convenience, and variety. At times, this adoption blurred boundaries between different cultural cuisines. Food practices in multicultural societies like Singapore are thus a reflection of everyday multiculturalism, multicultural social policies, and attitudes towards traditional healthful food practices, and these aspects need to be considered in the development of public health policies and interventions.
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Affiliation(s)
- Geetha Reddy
- University of Groningen, Grote Kruisstraat 2/1, the Netherlands.
| | - Rob M van Dam
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
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22
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Yahya P, Sulong S, Harun A, Wangkumhang P, Wilantho A, Ngamphiw C, Tongsima S, Zilfalil BA. Ancestry-informative marker (AIM) SNP panel for the Malay population. Int J Legal Med 2019; 134:123-134. [PMID: 31760471 DOI: 10.1007/s00414-019-02184-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2019] [Accepted: 10/15/2019] [Indexed: 10/25/2022]
Abstract
Ancestry-informative markers (AIMs) can be used to infer the ancestry of an individual to minimize the inaccuracy of self-reported ethnicity in biomedical research. In this study, we describe three methods for selecting AIM SNPs for the Malay population (Malay AIM panel) using different approaches based on pairwise FST, informativeness for assignment (In), and PCA-correlated SNPs (PCAIMs). These Malay AIM panels were extracted from genotype data stored in SNP arrays hosted by the Malaysian node of the Human Variome Project (MyHVP) and the Singapore Genome Variation Project (SGVP). In particular, genotype data from a total of 165 Malay individuals were analyzed, comprising data on 117 individual genotypes from the Affymetrix SNP-6 SNP array platform and data on 48 individual genotypes from the OMNI 2.5 Illumina SNP array platform. The HapMap phase 3 database (1397 individuals from 11 populations) was used as a reference for comparison with the Malay genotype data. The accuracy of each resulting Malay AIM panel was evaluated using a machine learning "ancestry-predictive model" constructed by using WEKA, a comprehensive machine learning platform written in Java. A total of 1250 SNPs were finally selected, which successfully identified Malay individuals from other world populations with an accuracy of 90%, but the accuracy decreased to 80% using 157 SNPs according to the pairwise FST method, while a panel of 200 SNPs selected using In and PCAIMs could be used to identify Malay individuals with an accuracy of approximately 80%.
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Affiliation(s)
- Padillah Yahya
- Department of Paediatrics, School of Medical Sciences, Universiti Sains Malaysia, 16150, Kubang Kerian, Kelantan, Malaysia
| | - Sarina Sulong
- Human Genome Centre, School of Medical Sciences, Universiti Sains Malaysia, 16150, Kubang Kerian, Kelantan, Malaysia
| | - Azian Harun
- Department of Medical Microbiology and Parasitology, School of Medical Sciences, Universiti Sains Malaysia, 16150, Kubang Kerian, Kelantan, Malaysia
| | - Pongsakorn Wangkumhang
- National Center for Genetic Engineering and Biotechnology (BIOTEC), Thailand Science Park, Khlong Luang District, Pathum Thani, 12120, Thailand
| | - Alisa Wilantho
- National Center for Genetic Engineering and Biotechnology (BIOTEC), Thailand Science Park, Khlong Luang District, Pathum Thani, 12120, Thailand
| | - Chumpol Ngamphiw
- National Center for Genetic Engineering and Biotechnology (BIOTEC), Thailand Science Park, Khlong Luang District, Pathum Thani, 12120, Thailand
| | - Sissades Tongsima
- National Center for Genetic Engineering and Biotechnology (BIOTEC), Thailand Science Park, Khlong Luang District, Pathum Thani, 12120, Thailand
| | - Bin Alwi Zilfalil
- Department of Paediatrics, School of Medical Sciences, Universiti Sains Malaysia, 16150, Kubang Kerian, Kelantan, Malaysia.
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23
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Large-Scale Whole-Genome Sequencing of Three Diverse Asian Populations in Singapore. Cell 2019; 179:736-749.e15. [DOI: 10.1016/j.cell.2019.09.019] [Citation(s) in RCA: 76] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2019] [Revised: 06/24/2019] [Accepted: 09/19/2019] [Indexed: 12/19/2022]
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24
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Complement Receptor 1 availability on red blood cell surface modulates Plasmodium vivax invasion of human reticulocytes. Sci Rep 2019; 9:8943. [PMID: 31221984 PMCID: PMC6586822 DOI: 10.1038/s41598-019-45228-6] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2017] [Accepted: 06/03/2019] [Indexed: 01/01/2023] Open
Abstract
Plasmodium vivax parasites preferentially invade reticulocyte cells in a multistep process that is still poorly understood. In this study, we used ex vivo invasion assays and population genetic analyses to investigate the involvement of complement receptor 1 (CR1) in P. vivax invasion. First, we observed that P. vivax invasion of reticulocytes was consistently reduced when CR1 surface expression was reduced through enzymatic cleavage, in the presence of naturally low-CR1-expressing cells compared with high-CR1-expressing cells, and with the addition of soluble CR1, a known inhibitor of P. falciparum invasion. Immuno-precipitation experiments with P. vivax Reticulocyte Binding Proteins showed no evidence of complex formation. In addition, analysis of CR1 genetic data for worldwide human populations with different exposure to malaria parasites show significantly higher frequency of CR1 alleles associated with low receptor expression on the surface of RBCs and higher linkage disequilibrium in human populations exposed to P. vivax malaria compared with unexposed populations. These results are consistent with a positive selection of low-CR1-expressing alleles in vivax-endemic areas. Collectively, our findings demonstrate that CR1 availability on the surface of RBCs modulates P. vivax invasion. The identification of new molecular interactions is crucial to guiding the rational development of new therapeutic interventions against vivax malaria.
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25
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Tan ALM, Langley SR, Tan CF, Chai JF, Khoo CM, Leow MKS, Khoo EYH, Moreno-Moral A, Pravenec M, Rotival M, Sadananthan SA, Velan SS, Venkataraman K, Chong YS, Lee YS, Sim X, Stunkel W, Liu MH, Tai ES, Petretto E. Ethnicity-Specific Skeletal Muscle Transcriptional Signatures and Their Relevance to Insulin Resistance in Singapore. J Clin Endocrinol Metab 2019; 104:465-486. [PMID: 30137523 DOI: 10.1210/jc.2018-00309] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2018] [Accepted: 08/14/2018] [Indexed: 11/19/2022]
Abstract
CONTEXT Insulin resistance (IR) and obesity differ among ethnic groups in Singapore, with the Malays more obese yet less IR than Asian-Indians. However, the molecular basis underlying these differences is not clear. OBJECTIVE As the skeletal muscle (SM) is metabolically relevant to IR, we investigated molecular pathways in SM that are associated with ethnic differences in IR, obesity, and related traits. DESIGN, SETTING, AND MAIN OUTCOME MEASURES We integrated transcriptomic, genomic, and phenotypic analyses in 156 healthy subjects representing three major ethnicities in the Singapore Adult Metabolism Study. PATIENTS This study contains Chinese (n = 63), Malay (n = 51), and Asian-Indian (n = 42) men, aged 21 to 40 years, without systemic diseases. RESULTS We found remarkable diversity in the SM transcriptome among the three ethnicities, with >8000 differentially expressed genes (40% of all genes expressed in SM). Comparison with blood transcriptome from a separate Singaporean cohort showed that >95% of SM expression differences among ethnicities were unique to SM. We identified a network of 46 genes that were specifically downregulated in Malays, suggesting dysregulation of components of cellular respiration in SM of Malay individuals. We also report 28 differentially expressed gene clusters, four of which were also enriched for genes that were found in genome-wide association studies of metabolic traits and disease and correlated with variation in IR, obesity, and related traits. CONCLUSION We identified extensive gene-expression changes in SM among the three Singaporean ethnicities and report specific genes and molecular pathways that might underpin and explain the differences in IR among these ethnic groups.
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Affiliation(s)
- Amelia Li Min Tan
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Duke-National University of Singapore Medical School, Singapore
| | - Sarah R Langley
- Duke-National University of Singapore Medical School, Singapore
- National Heart Centre Singapore, Singapore
| | - Chee Fan Tan
- Nanyang Institute of Technology in Health and Medicine, Nanyang Technological University, Singapore
- School of Biological Sciences, Nanyang Technological University, Singapore
| | - Jin Fang Chai
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Chin Meng Khoo
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Duke-National University of Singapore Medical School, Singapore
- Division of Endocrinology, Department of Medicine, National University Health System, Singapore
| | - Melvin Khee-Shing Leow
- Duke-National University of Singapore Medical School, Singapore
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (A*STAR), Singapore
- Department of Endocrinology, Tan Tock Seng Hospital, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
| | - Eric Yin Hao Khoo
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Division of Endocrinology, Department of Medicine, National University Health System, Singapore
| | | | - Michal Pravenec
- Institute Of Physiology, Czech Academy Of Sciences, Prague, Czech Republic
| | - Maxime Rotival
- Unit of Human Evolutionary Genetics, Institut Pasteur, Paris, France
| | - Suresh Anand Sadananthan
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (A*STAR), Singapore
| | - S Sendhil Velan
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (A*STAR), Singapore
- Singapore Bioimaging Consortium, Agency for Science, Technology and Research (A*STAR), Singapore
| | - Kavita Venkataraman
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Yap Seng Chong
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (A*STAR), Singapore
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Yung Seng Lee
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (A*STAR), Singapore
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Division of Paediatrics Endocrinology, Khoo Teck Puat-National University Children's Medical Institute, National University Hospital, National University Health System, Singapore
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Walter Stunkel
- Experimental Biotherapeutics Centre, Agency for Science, Technology and Research (A*STAR), Singapore
| | - Mei Hui Liu
- Department of Chemistry, Food Science & Technology Programme, National University of Singapore, Singapore
| | - E Shyong Tai
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Duke-National University of Singapore Medical School, Singapore
- Division of Endocrinology, Department of Medicine, National University Health System, Singapore
| | - Enrico Petretto
- Duke-National University of Singapore Medical School, Singapore
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26
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Sivadas A, Scaria V. Population-scale genomics-Enabling precision public health. ADVANCES IN GENETICS 2018; 103:119-161. [PMID: 30904093 DOI: 10.1016/bs.adgen.2018.09.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
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.
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Affiliation(s)
- Ambily Sivadas
- GN Ramachandran Knowledge Center for Genome Informatics, CSIR Institute of Genomics and Integrative Biology (CSIR-IGIB), New Delhi, India; Academy of Scientific and Innovative Research (AcSIR), New Delhi, India
| | - Vinod Scaria
- GN Ramachandran Knowledge Center for Genome Informatics, CSIR Institute of Genomics and Integrative Biology (CSIR-IGIB), New Delhi, India; Academy of Scientific and Innovative Research (AcSIR), New Delhi, India.
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27
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Real-Time Tumor Gene Expression Profiling to Direct Gastric Cancer Chemotherapy: Proof-of-Concept “3G” Trial. Clin Cancer Res 2018; 24:5272-5281. [DOI: 10.1158/1078-0432.ccr-18-0193] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2018] [Revised: 05/28/2018] [Accepted: 07/12/2018] [Indexed: 11/16/2022]
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28
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Lin Y, Liu L, Yang S, Li Y, Lin D, Zhang X, Yin X. Genotype imputation for Han Chinese population using Haplotype Reference Consortium as reference. Hum Genet 2018; 137:431-436. [DOI: 10.1007/s00439-018-1894-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2018] [Accepted: 05/26/2018] [Indexed: 11/30/2022]
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29
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Volgman AS, Palaniappan LS, Aggarwal NT, Gupta M, Khandelwal A, Krishnan AV, Lichtman JH, Mehta LS, Patel HN, Shah KS, Shah SH, Watson KE. Atherosclerotic Cardiovascular Disease in South Asians in the United States: Epidemiology, Risk Factors, and Treatments: A Scientific Statement From the American Heart Association. Circulation 2018; 138:e1-e34. [PMID: 29794080 DOI: 10.1161/cir.0000000000000580] [Citation(s) in RCA: 287] [Impact Index Per Article: 47.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
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.
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Limviphuvadh V, Tan CS, Konishi F, Jenjaroenpun P, Xiang JS, Kremenska Y, Mu YS, Syn N, Lee SC, Soo RA, Eisenhaber F, Maurer-Stroh S, Yong WP. Discovering novel SNPs that are correlated with patient outcome in a Singaporean cancer patient cohort treated with gemcitabine-based chemotherapy. BMC Cancer 2018; 18:555. [PMID: 29751792 PMCID: PMC5948914 DOI: 10.1186/s12885-018-4471-x] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2017] [Accepted: 05/01/2018] [Indexed: 12/20/2022] Open
Abstract
Background Single Nucleotide Polymorphisms (SNPs) can influence patient outcome such as drug response and toxicity after drug intervention. The purpose of this study is to develop a systematic pathway approach to accurately and efficiently predict novel non-synonymous SNPs (nsSNPs) that could be causative to gemcitabine-based chemotherapy treatment outcome in Singaporean non-small cell lung cancer (NSCLC) patients. Methods Using a pathway approach that incorporates comprehensive protein-protein interaction data to systematically extend the gemcitabine pharmacologic pathway, we identified 77 related nsSNPs, common in the Singaporean population. After that, we used five computational criteria to prioritize the SNPs based on their importance for protein function. We specifically selected and screened six candidate SNPs in a patient cohort with NSCLC treated with gemcitabine-based chemotherapy. Result We performed survival analysis followed by hematologic toxicity analyses and found that three of six candidate SNPs are significantly correlated with the patient outcome (P < 0.05) i.e. ABCG2 Q141K (rs2231142), SLC29A3 S158F (rs780668) and POLR2A N764K (rs2228130). Conclusions Our computational SNP candidate enrichment workflow approach was able to identify several high confidence biomarkers predictive for personalized drug treatment outcome while providing a rationale for a molecular mechanism of the SNP effect. Trial registration NCT00695994. Registered 10 June, 2008 ‘retrospectively registered’. Electronic supplementary material The online version of this article (10.1186/s12885-018-4471-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Vachiranee Limviphuvadh
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01 Matrix, Singapore, 138671, Singapore
| | - Chee Seng Tan
- Department of Haematology-Oncology, National University Health System, 5 Lower Kent Ridge Road, Singapore, 119074, Singapore
| | - Fumikazu Konishi
- Education Academy of Computational Life Sciences, Tokyo Institute of Technology, Tokyo, Japan
| | - Piroon Jenjaroenpun
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01 Matrix, Singapore, 138671, Singapore
| | - Joy Shengnan Xiang
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01 Matrix, Singapore, 138671, Singapore
| | - Yuliya Kremenska
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01 Matrix, Singapore, 138671, Singapore
| | - Yar Soe Mu
- Department of Haematology-Oncology, National University Health System, 5 Lower Kent Ridge Road, Singapore, 119074, Singapore
| | - Nicholas Syn
- Department of Haematology-Oncology, National University Health System, 5 Lower Kent Ridge Road, Singapore, 119074, Singapore.,Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Soo Chin Lee
- Department of Haematology-Oncology, National University Health System, 5 Lower Kent Ridge Road, Singapore, 119074, Singapore
| | - Ross A Soo
- Department of Haematology-Oncology, National University Health System, 5 Lower Kent Ridge Road, Singapore, 119074, Singapore.,Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Frank Eisenhaber
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01 Matrix, Singapore, 138671, Singapore.,Department of Biological Sciences, National University of Singapore (NUS), 14 Science Drive 4, Singapore, 117543, Singapore.,School of Computer Engineering (SCE), Nanyang Technological University (NTU), 50 Nanyang Drive, Singapore, 637553, Singapore
| | - Sebastian Maurer-Stroh
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01 Matrix, Singapore, 138671, Singapore.,Department of Biological Sciences, National University of Singapore (NUS), 14 Science Drive 4, Singapore, 117543, Singapore
| | - Wei Peng Yong
- Department of Haematology-Oncology, National University Health System, 5 Lower Kent Ridge Road, Singapore, 119074, Singapore.
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31
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Taliun D, Chothani SP, Schönherr S, Forer L, Boehnke M, Abecasis GR, Wang C. LASER server: ancestry tracing with genotypes or sequence reads. Bioinformatics 2018; 33:2056-2058. [PMID: 28200055 PMCID: PMC5870850 DOI: 10.1093/bioinformatics/btx075] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2016] [Accepted: 02/09/2017] [Indexed: 01/22/2023] Open
Abstract
Summary To enable direct comparison of ancestry background in different studies, we developed LASER to estimate individual ancestry by placing either sezquenced or genotyped samples in a common ancestry space, regardless of the sequencing strategy or genotyping array used to characterize each sample. Here we describe the LASER server to facilitate application of the method to a wide range of genetic studies. The server provides genetic ancestry estimation for different geographic regions and user-friendly interactive visualization of the results. Availability and Implementation The LASER server is freely accessible at http://laser.sph.umich.edu/ Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Daniel Taliun
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- To whom correspondence should be addressed. or
| | - Sonia P Chothani
- Computational and Systems Biology, Genome Institute of Singapore, Singapore, Singapore
| | - Sebastian Schönherr
- Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Lukas Forer
- Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Gonçalo R Abecasis
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Chaolong Wang
- Computational and Systems Biology, Genome Institute of Singapore, Singapore, Singapore
- To whom correspondence should be addressed. or
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32
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Yew CW, Hoque MZ, Pugh-Kitingan J, Minsong A, Voo CLY, Ransangan J, Lau STY, Wang X, Saw WY, Ong RTH, Teo YY, Xu S, Hoh BP, Phipps ME, Kumar SV. Genetic relatedness of indigenous ethnic groups in northern Borneo to neighboring populations from Southeast Asia, as inferred from genome-wide SNP data. Ann Hum Genet 2018. [PMID: 29521412 DOI: 10.1111/ahg.12246] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
The region of northern Borneo is home to the current state of Sabah, Malaysia. It is located closest to the southern Philippine islands and may have served as a viaduct for ancient human migration onto or off of Borneo Island. In this study, five indigenous ethnic groups from Sabah were subjected to genome-wide SNP genotyping. These individuals represent the "North Borneo"-speaking group of the great Austronesian family. They have traditionally resided in the inland region of Sabah. The dataset was merged with public datasets, and the genetic relatedness of these groups to neighboring populations from the islands of Southeast Asia, mainland Southeast Asia and southern China was inferred. Genetic structure analysis revealed that these groups formed a genetic cluster that was independent of the clusters of neighboring populations. Additionally, these groups exhibited near-absolute proportions of a genetic component that is also common among Austronesians from Taiwan and the Philippines. They showed no genetic admixture with Austro-Melanesian populations. Furthermore, phylogenetic analysis showed that they are closely related to non-Austro-Melansian Filipinos as well as to Taiwan natives but are distantly related to populations from mainland Southeast Asia. Relatively lower heterozygosity and higher pairwise genetic differentiation index (FST ) values than those of nearby populations indicate that these groups might have experienced genetic drift in the past, resulting in their differentiation from other Austronesians. Subsequent formal testing suggested that these populations have received no gene flow from neighboring populations. Taken together, these results imply that the indigenous ethnic groups of northern Borneo shared a common ancestor with Taiwan natives and non-Austro-Melanesian Filipinos and then isolated themselves on the inland of Sabah. This isolation presumably led to no admixture with other populations, and these individuals therefore underwent strong genetic differentiation. This report contributes to addressing the paucity of genetic data on representatives from this strategic region of ancient human migration event(s).
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Affiliation(s)
- Chee Wei Yew
- Biotechnology Research Institute, Universiti Malaysia Sabah, Jalan UMS, Sabah, Malaysia
| | - Mohd Zahirul Hoque
- Faculty of Medicine and Health Sciences, Universiti Malaysia Sabah, Jalan UMS, Sabah, Malaysia
| | | | - Alexander Minsong
- Faculty of Humanities, Arts & Heritage, Universiti Malaysia Sabah, Jalan UMS, Sabah, Malaysia
| | | | - Julian Ransangan
- Borneo Marine Research Institute, Universiti Malaysia Sabah, Jalan UMS, Sabah, Malaysia
| | - Sophia Tiek Ying Lau
- Biotechnology Research Institute, Universiti Malaysia Sabah, Jalan UMS, Sabah, Malaysia
| | - Xu Wang
- Department of Statistics and Applied Probability, Faculty of Science, National University of Singapore, Singapore
| | - Woei Yuh Saw
- Department of Statistics and Applied Probability, Faculty of Science, National University of Singapore, Singapore
| | - Rick Twee-Hee Ong
- Department of Statistics and Applied Probability, Faculty of Science, National University of Singapore, Singapore.,Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Yik-Ying Teo
- Department of Statistics and Applied Probability, Faculty of Science, National University of Singapore, Singapore.,Saw Swee Hock School of Public Health, National University of Singapore, Singapore.,NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore.,Life Sciences Institute, National University of Singapore, Singapore.,Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore
| | - Shuhua Xu
- Max Planck Independent Research Group on Population Genomics, Chinese Academy of Sciences and Max Planck Society Partner Institute for Computational Biology (PICB), Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.,School of Life Science and Technology, ShanghaiTec University, Shanghai, China.,Collaborative Innovation Centre of Genetics and Development, Shanghai, China
| | - Boon-Peng Hoh
- Institute for Molecular Medical Biotechnology, Universiti Teknologi MARA, Selangor, Malaysia.,Faculty of Medicine and Health Sciences, UCSI University, Kuala Lumpur, Malaysia
| | - Maude E Phipps
- Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Selangor, Malaysia
| | - S Vijay Kumar
- Biotechnology Research Institute, Universiti Malaysia Sabah, Jalan UMS, Sabah, Malaysia
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33
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Han Y, Dorajoo R, Chang X, Wang L, Khor CC, Sim X, Cheng CY, Shi Y, Tham YC, Zhao W, Chee ML, Sabanayagam C, Chee ML, Tan N, Wong TY, Tai ES, Liu J, Goh DYT, Yuan JM, Koh WP, van Dam RM, Low AF, Chan MYY, Friedlander Y, Heng CK. Genome-wide association study identifies a missense variant at APOA5 for coronary artery disease in Multi-Ethnic Cohorts from Southeast Asia. Sci Rep 2017; 7:17921. [PMID: 29263402 PMCID: PMC5738399 DOI: 10.1038/s41598-017-18214-z] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2017] [Accepted: 12/01/2017] [Indexed: 12/19/2022] Open
Abstract
Recent genome-wide association studies (GWAS) have identified multiple loci associated with coronary artery disease (CAD) among predominantly Europeans. However, their relevance to multi-ethnic populations from Southeast Asia is largely unknown. We performed a meta-analysis of four GWAS comprising three Chinese studies and one Malay study (Total N = 2,169 CAD cases and 7,376 controls). Top hits (P < 5 × 10-8) were further evaluated in 291 CAD cases and 1,848 controls of Asian Indians. Using all datasets, we validated recently identified loci associated with CAD. The involvement of known canonical pathways in CAD was tested by Ingenuity Pathway Analysis. We identified a missense SNP (rs2075291, G > T, G185C) in APOA5 for CAD that reached robust genome-wide significance (Meta P = 7.09 × 10-10, OR = 1.636). Conditional probability analysis indicated that the association at rs2075291 was independent of previously reported index SNP rs964184 in APOA5. We further replicated 10 loci previously identified among predominantly Europeans (P: 1.33 × 10-7-0.047). Seven pathways (P: 1.10 × 10-5-0.019) were identified. We identified a missense SNP, rs2075291, in APOA5 associated with CAD at a genome-wide significance level and provided new insights into pathways contributing to the susceptibility to CAD in the multi-ethnic populations from Southeast Asia.
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Affiliation(s)
- Yi Han
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore; and Khoo Teck Puat - National University Children's Medical Institute, National University Health System, Singapore, Singapore
| | - Rajkumar Dorajoo
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Xuling Chang
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore; and Khoo Teck Puat - National University Children's Medical Institute, National University Health System, Singapore, Singapore
| | - Ling Wang
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Chiea-Chuen Khor
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Yuan Shi
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Yih Chung Tham
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Wanting Zhao
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Miao Ling Chee
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Charumathi Sabanayagam
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Centre for Quantitative Medicine, Duke-NUS Graduate Medical School, Singapore, Singapore
| | - Miao Li Chee
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Nicholas Tan
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Department of Ophthalmology, National University Hospital, Singapore, Singapore
| | - Tien Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - E-Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, National University Health System, Singapore, Singapore
| | - Jianjun Liu
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Daniel Y T Goh
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore; and Khoo Teck Puat - National University Children's Medical Institute, National University Health System, Singapore, Singapore
| | - Jian-Min Yuan
- Department of Epidemiology, Graduate School of Public Health; and University of Pittsburgh Cancer Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Woon-Puay Koh
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Duke-NUS Graduate Medical School Singapore, Singapore, Singapore
| | - Rob M van Dam
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, National University Health System, Singapore, Singapore
| | - Adrian F Low
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- National University Heart Centre, National University Health System, Singapore, Singapore
| | - Mark Yan-Yee Chan
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Yechiel Friedlander
- School of Public Health and Community Medicine, Hebrew University of Jerusalem, Jerusalem, Israel.
| | - Chew-Kiat Heng
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore; and Khoo Teck Puat - National University Children's Medical Institute, National University Health System, Singapore, Singapore.
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34
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Lipidomic profiling of plasma in a healthy Singaporean population to identify ethnic specific differences in lipid levels and associations with disease risk factors. CLINICAL MASS SPECTROMETRY 2017. [DOI: 10.1016/j.clinms.2017.11.002] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
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35
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Takeuchi F, Katsuya T, Kimura R, Nabika T, Isomura M, Ohkubo T, Tabara Y, Yamamoto K, Yokota M, Liu X, Saw WY, Mamatyusupu D, Yang W, Xu S, Teo YY, Kato N. The fine-scale genetic structure and evolution of the Japanese population. PLoS One 2017; 12:e0185487. [PMID: 29091727 PMCID: PMC5665431 DOI: 10.1371/journal.pone.0185487] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2016] [Accepted: 09/13/2017] [Indexed: 11/21/2022] Open
Abstract
The contemporary Japanese populations largely consist of three genetically distinct groups—Hondo, Ryukyu and Ainu. By principal-component analysis, while the three groups can be clearly separated, the Hondo people, comprising 99% of the Japanese, form one almost indistinguishable cluster. To understand fine-scale genetic structure, we applied powerful haplotype-based statistical methods to genome-wide single nucleotide polymorphism data from 1600 Japanese individuals, sampled from eight distinct regions in Japan. We then combined the Japanese data with 26 other Asian populations data to analyze the shared ancestry and genetic differentiation. We found that the Japanese could be separated into nine genetic clusters in our dataset, showing a marked concordance with geography; and that major components of ancestry profile of Japanese were from the Korean and Han Chinese clusters. We also detected and dated admixture in the Japanese. While genetic differentiation between Ryukyu and Hondo was suggested to be caused in part by positive selection, genetic differentiation among the Hondo clusters appeared to result principally from genetic drift. Notably, in Asians, we found the possibility that positive selection accentuated genetic differentiation among distant populations but attenuated genetic differentiation among close populations. These findings are significant for studies of human evolution and medical genetics.
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Affiliation(s)
- Fumihiko Takeuchi
- Department of Gene Diagnostics and Therapeutics, National Center for Global Health and Medicine, Tokyo, Japan
- * E-mail: (FT); (NK)
| | - Tomohiro Katsuya
- Department of Clinical Gene Therapy, Osaka University Graduate School of Medicine, Suita, Japan
| | - Ryosuke Kimura
- Department of Human Biology and Anatomy, Graduate School of Medicine, University of the Ryukyus, Nishihara-cho, Japan
| | - Toru Nabika
- Department of Functional Pathology, Shimane University School of Medicine, Izumo, Japan
| | - Minoru Isomura
- Department of Functional Pathology, Shimane University School of Medicine, Izumo, Japan
| | - Takayoshi Ohkubo
- Department of Hygiene and Public Health, Teikyo University School of Medicine, Tokyo, Japan
| | - Yasuharu Tabara
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Ken Yamamoto
- Department of Medical Chemistry, Kurume University School of Medicine, Kurume, Japan
| | - Mitsuhiro Yokota
- Department of Genome Science, School of Dentistry, Aichi Gakuin University, Nagoya, Japan
| | - Xuanyao Liu
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
- NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore, Singapore
| | - Woei-Yuh Saw
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
- Life Sciences Institute, National University of Singapore, Singapore, Singapore
| | - Dolikun Mamatyusupu
- College of the Life Sciences and Technology, Xinjiang University, Urumqi, China
| | - Wenjun Yang
- Key Laboratory of Reproduction and Heredity of Ningxia Region, Ningxia Medical University, Yinchuan, Ningxia, China
| | - Shuhua Xu
- Max Planck Independent Research Group on Population Genomics, Chinese Academy of Sciences and Max Planck Society Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences Shanghai, China
- School of Life Sciences and Technology, ShanghaiTech University, Shanghai, China
- Collaborative Innovation Center of Genetics and Development, Shanghai, China
| | | | - Yik-Ying Teo
- Department of Gene Diagnostics and Therapeutics, National Center for Global Health and Medicine, Tokyo, Japan
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
- NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore, Singapore
- Life Sciences Institute, National University of Singapore, Singapore, Singapore
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
- Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore
| | - Norihiro Kato
- Department of Gene Diagnostics and Therapeutics, National Center for Global Health and Medicine, Tokyo, Japan
- * E-mail: (FT); (NK)
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36
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Chan SL, Chua APG, Aminkeng F, Chee CBE, Jin S, Loh M, Gan SH, Wang YT, Brunham LR. Association and clinical utility of NAT2 in the prediction of isoniazid-induced liver injury in Singaporean patients. PLoS One 2017; 12:e0186200. [PMID: 29036176 PMCID: PMC5642896 DOI: 10.1371/journal.pone.0186200] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2017] [Accepted: 09/27/2017] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND AND AIMS Isoniazid (INH) is part of the first-line-therapy for tuberculosis (TB) but can cause drug-induced liver injury (DILI). Several candidate single nucleotide polymorphisms (SNPs) have been previously identified but the clinical utility of these SNPs in the prediction of INH-DILI remains uncertain. The aim of this study was to assess the association between selected candidate SNPs and the risk of INH-DILI and to assess the clinical validity of associated variants in a Singaporean population. METHODS This was a case-control study where 24 INH-DILI cases and 79 controls were recruited from the TB control unit in a tertiary hospital. Logistic regression was used to test for the association between candidate SNPs and INH-DILI. NAT2 acetylator status was inferred from genotypes and tested for association with INH-DILI. Finally, clinical validity measures were estimated for significant variants. RESULTS Two SNPs in NAT2 (rs1041983 and rs1495741) and NAT2 slow acetylators (SA) were significantly associated with INH-DILI (OR (95% CI) = 13.86 (4.30-44.70), 0.10 (0.03-0.33) and 9.98 (3.32-33.80), respectively). Based on an INH-DILI prevalence of 10%, the sensitivity, specificity, positive and negative predictive values of NAT2 SA were 75%, 78%, 28% and 97%, respectively. The population attributable fraction (PAF) and number needed to test (NNT) for NAT2 SA were estimated to be 0.67 and 4.08, respectively. A model with clinical and NAT2 acetylator status provided significantly better prediction for INH-DILI than a clinical model alone (area under receiver operating characteristic curve = 0.863 vs. 0.766, respectively, p = 0.027). CONCLUSIONS We show the association between NAT2 SA and INH-DILI in a Singaporean population and demonstrated its clinical utility in the prediction of INH-DILI.
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Affiliation(s)
- Sze Ling Chan
- Translational Laboratory in Genetic Medicine, Agency for Science, Technology and Research, Singapore and the National University of Singapore, Singapore
| | | | - Folefac Aminkeng
- Translational Laboratory in Genetic Medicine, Agency for Science, Technology and Research, Singapore and the National University of Singapore, Singapore
| | | | - Shengnan Jin
- School of Laboratory Medicine and Life Science, Wenzhou Medical University, Wenzhou, China
| | - Marie Loh
- Translational Laboratory in Genetic Medicine, Agency for Science, Technology and Research, Singapore and the National University of Singapore, Singapore
| | - Suay Hong Gan
- Department of Respiratory Medicine, Tan Tock Seng Hospital, Singapore
| | - Yee Tang Wang
- Department of Respiratory Medicine, Tan Tock Seng Hospital, Singapore
| | - Liam R. Brunham
- Translational Laboratory in Genetic Medicine, Agency for Science, Technology and Research, Singapore and the National University of Singapore, Singapore
- Department of Medicine, Centre for Heart Lung Innovation, University of British Columbia, Vancouver, Canada
- * E-mail:
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37
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Dou J, Sun B, Sim X, Hughes JD, Reilly DF, Tai ES, Liu J, Wang C. Estimation of kinship coefficient in structured and admixed populations using sparse sequencing data. PLoS Genet 2017; 13:e1007021. [PMID: 28961250 PMCID: PMC5636172 DOI: 10.1371/journal.pgen.1007021] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2017] [Revised: 10/11/2017] [Accepted: 09/14/2017] [Indexed: 12/15/2022] Open
Abstract
Knowledge of biological relatedness between samples is important for many genetic studies. In large-scale human genetic association studies, the estimated kinship is used to remove cryptic relatedness, control for family structure, and estimate trait heritability. However, estimation of kinship is challenging for sparse sequencing data, such as those from off-target regions in target sequencing studies, where genotypes are largely uncertain or missing. Existing methods often assume accurate genotypes at a large number of markers across the genome. We show that these methods, without accounting for the genotype uncertainty in sparse sequencing data, can yield a strong downward bias in kinship estimation. We develop a computationally efficient method called SEEKIN to estimate kinship for both homogeneous samples and heterogeneous samples with population structure and admixture. Our method models genotype uncertainty and leverages linkage disequilibrium through imputation. We test SEEKIN on a whole exome sequencing dataset (WES) of Singapore Chinese and Malays, which involves substantial population structure and admixture. We show that SEEKIN can accurately estimate kinship coefficient and classify genetic relatedness using off-target sequencing data down sampled to ~0.15X depth. In application to the full WES dataset without down sampling, SEEKIN also outperforms existing methods by properly analyzing shallow off-target data (~0.75X). Using both simulated and real phenotypes, we further illustrate how our method improves estimation of trait heritability for WES studies. Inference of genetic relatedness from molecular markers has broad applications in many areas, including quantitative genetics, forensics, evolution and ecology. Classic estimators, however, are not suitable for low-coverage sequencing data, which have high levels of genotype uncertainty and missing data. We evaluate existing methods and describe a new method for kinship estimation using sparse sequencing data. Our method leverages correlations between neighboring markers and models genotype uncertainty in kinship estimators for both homogeneous populations and admixed populations. We show that our method can accurately estimate kinship coefficient even when the sequencing depth is as low as ~0.15X, while existing methods have strong downward bias. Our method can be applied to estimate kinship using sparse off-target data and thus enables control of family structure and estimation of heritability in target sequencing studies, in which the deeply sequenced target regions are often too small to infer genetic relatedness. Even for whole exome sequencing, we show that our method can improve kinship and heritability estimation by including off-target data, compared to conventional analyses solely based on the target regions.
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Affiliation(s)
- Jinzhuang Dou
- Computational and Systems Biology, Genome Institute of Singapore, Singapore, Singapore
| | - Baoluo Sun
- Computational and Systems Biology, Genome Institute of Singapore, Singapore, Singapore
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Jason D. Hughes
- Genetics, Merck Sharp & Dohme Corp., Kenilworth, New Jersey, United States of America
| | - Dermot F. Reilly
- Genetics, Merck Sharp & Dohme Corp., Kenilworth, New Jersey, United States of America
| | - E. Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
- Duke-NUS Medical School, National University of Singapore, Singapore, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Jianjun Liu
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Human Genetics, Genome Institute of Singapore, Singapore, Singapore
| | - Chaolong Wang
- Computational and Systems Biology, Genome Institute of Singapore, Singapore, Singapore
- Duke-NUS Medical School, National University of Singapore, Singapore, Singapore
- * E-mail:
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38
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Saw WY, Tantoso E, Begum H, Zhou L, Zou R, He C, Chan SL, Tan LWL, Wong LP, Xu W, Moong DKN, Lim Y, Li B, Pillai NE, Peterson TA, Bielawny T, Meikle PJ, Mundra PA, Lim WY, Luo M, Chia KS, Ong RTH, Brunham LR, Khor CC, Too HP, Soong R, Wenk MR, Little P, Teo YY. Establishing multiple omics baselines for three Southeast Asian populations in the Singapore Integrative Omics Study. Nat Commun 2017; 8:653. [PMID: 28935855 PMCID: PMC5608948 DOI: 10.1038/s41467-017-00413-x] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2017] [Accepted: 06/28/2017] [Indexed: 11/09/2022] Open
Abstract
The Singapore Integrative Omics Study provides valuable insights on establishing population reference measurement in 364 Chinese, Malay, and Indian individuals. These measurements include > 2.5 millions genetic variants, 21,649 transcripts expression, 282 lipid species quantification, and 284 clinical, lifestyle, and dietary variables. This concept paper introduces the depth of the data resource, and investigates the extent of ethnic variation at these omics and non-omics biomarkers. It is evident that there are specific biomarkers in each of these platforms to differentiate between the ethnicities, and intra-population analyses suggest that Chinese and Indians are the most biologically homogeneous and heterogeneous, respectively, of the three groups. Consistent patterns of correlations between lipid species also suggest the possibility of lipid tagging to simplify future lipidomics assays. The Singapore Integrative Omics Study is expected to allow the characterization of intra-omic and inter-omic correlations within and across all three ethnic groups through a systems biology approach.The Singapore Genome Variation projects characterized the genetics of Singapore's Chinese, Malay, and Indian populations. The Singapore Integrative Omics Study introduced here goes further in providing multi-omic measurements in individuals from these populations, including genetic, transcriptome, lipidome, and lifestyle data, and will facilitate the study of common diseases in Asian communities.
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Affiliation(s)
- Woei-Yuh Saw
- Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive, Singapore, 117549, Singapore.,Life Sciences Institute, National University of Singapore, 28 Medical Drive, Singapore, 117456, Singapore
| | - Erwin Tantoso
- Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive, Singapore, 117549, Singapore
| | - Husna Begum
- Life Sciences Institute, National University of Singapore, 28 Medical Drive, Singapore, 117456, Singapore.,Baker IDI Heart and Diabetes Institute, 75 Commercial Road, Melbourne, VIC, 3004, Australia
| | - Lihan Zhou
- MiRXES, Agency for Science, Technology and Research Singapore, 10 Biopolis Road, Chromos, Singapore, 138670, Singapore
| | - Ruiyang Zou
- MiRXES, Agency for Science, Technology and Research Singapore, 10 Biopolis Road, Chromos, Singapore, 138670, Singapore
| | - Cheng He
- MiRXES, Agency for Science, Technology and Research Singapore, 10 Biopolis Road, Chromos, Singapore, 138670, Singapore
| | - Sze Ling Chan
- Translational Laboratory in Genetic Medicine, Agency for Science, Technology and Research Singapore, 8A Biomedical Grove, Immunos, Singapore, 138648, Singapore
| | - Linda Wei-Lin Tan
- Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive, Singapore, 117549, Singapore
| | - Lai-Ping Wong
- Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive, Singapore, 117549, Singapore
| | - Wenting Xu
- Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive, Singapore, 117549, Singapore
| | - Don Kyin Nwe Moong
- Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive, Singapore, 117549, Singapore
| | - Yenly Lim
- Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive, Singapore, 117549, Singapore
| | - Bowen Li
- Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive, Singapore, 117549, Singapore
| | - Nisha Esakimuthu Pillai
- Life Sciences Institute, National University of Singapore, 28 Medical Drive, Singapore, 117456, Singapore
| | - Trevor A Peterson
- Department of Medical Microbiology, University of Manitoba, 730 William Avenue, Winnipeg, MB, Canada, R3E 0Z2.,National Microbiology Laboratory, 1015 Arlington St, Winnipeg, MB, Canada, R3E
| | - Tomasz Bielawny
- Department of Medical Microbiology, University of Manitoba, 730 William Avenue, Winnipeg, MB, Canada, R3E 0Z2.,National Microbiology Laboratory, 1015 Arlington St, Winnipeg, MB, Canada, R3E
| | - Peter J Meikle
- Baker IDI Heart and Diabetes Institute, 75 Commercial Road, Melbourne, VIC, 3004, Australia.,Department of Biochemistry and Molecular Biology, The University of Melbourne, Bio21, 30 Flemington Road, Melbourne, VIC, 3010, Australia
| | - Piyushkumar A Mundra
- Baker IDI Heart and Diabetes Institute, 75 Commercial Road, Melbourne, VIC, 3004, Australia
| | - Wei-Yen Lim
- Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive, Singapore, 117549, Singapore
| | - Ma Luo
- Department of Medical Microbiology, University of Manitoba, 730 William Avenue, Winnipeg, MB, Canada, R3E 0Z2.,National Microbiology Laboratory, 1015 Arlington St, Winnipeg, MB, Canada, R3E
| | - Kee-Seng Chia
- Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive, Singapore, 117549, Singapore
| | - Rick Twee-Hee Ong
- Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive, Singapore, 117549, Singapore
| | - Liam R Brunham
- Translational Laboratory in Genetic Medicine, Agency for Science, Technology and Research Singapore, 8A Biomedical Grove, Immunos, Singapore, 138648, Singapore
| | - Chiea-Chuen Khor
- Genome Institute of Singapore, Agency for Science, Technology and Research Singapore, 60 Biopolis St, Singapore, 138672, Singapore.,Singapore Eye Research Institute, 20 College Road, Singapore, 169856, Singapore
| | - Heng Phon Too
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore, 117597, Singapore.,Molecular Engineering of Biological and Chemical System/Chemical Pharmaceutical Engineering, Singapore-Massachusetts Institute of Technology Alliance, 4 Engineering Drive 3, Singapore, 117576, Singapore.,Bioprocessing Technology Institute, A*STAR (Agency for Science, Technology and Research, Singapore), 20 Biopolis Way, Singapore, 138668, Singapore
| | - Richie Soong
- Cancer Science Institute of Singapore, National University of Singapore, 14 Medical Drive, Singapore, 117599, Singapore
| | - Markus R Wenk
- Life Sciences Institute, National University of Singapore, 28 Medical Drive, Singapore, 117456, Singapore.,Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore, 117597, Singapore.,NUS Graduate School for Integrative Science and Engineering, National University of Singapore, 28 Medical Drive, Singapore, 117456, Singapore.,State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, No.1 West Beichen Road, Chaoyang District, Beijing, 100101, China.,Department of Biological Sciences, National University of Singapore, 16 Science Drive 4, Singapore, 117543, Singapore
| | - Peter Little
- Life Sciences Institute, National University of Singapore, 28 Medical Drive, Singapore, 117456, Singapore
| | - Yik-Ying Teo
- Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive, Singapore, 117549, Singapore. .,Life Sciences Institute, National University of Singapore, 28 Medical Drive, Singapore, 117456, Singapore. .,Genome Institute of Singapore, Agency for Science, Technology and Research Singapore, 60 Biopolis St, Singapore, 138672, Singapore. .,NUS Graduate School for Integrative Science and Engineering, National University of Singapore, 28 Medical Drive, Singapore, 117456, Singapore. .,Department of Statistics and Applied Probability, National University of Singapore, 6 Science Drive 2, Singapore, 117546, Singapore.
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39
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Enane FO, Shuen WH, Gu X, Quteba E, Przychodzen B, Makishima H, Bodo J, Ng J, Chee CL, Ba R, Seng Koh L, Lim J, Cheong R, Teo M, Hu Z, Ng KP, Maciejewski J, Radivoyevitch T, Chung A, Ooi LL, Tan YM, Cheow PC, Chow P, Chan CY, Lim KH, Yerian L, Hsi E, Toh HC, Saunthararajah Y. GATA4 loss of function in liver cancer impedes precursor to hepatocyte transition. J Clin Invest 2017; 127:3527-3542. [PMID: 28758902 DOI: 10.1172/jci93488] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2017] [Accepted: 06/08/2017] [Indexed: 12/18/2022] Open
Abstract
The most frequent chromosomal structural loss in hepatocellular carcinoma (HCC) is of the short arm of chromosome 8 (8p). Genes on the remaining homologous chromosome, however, are not recurrently mutated, and the identity of key 8p tumor-suppressor genes (TSG) is unknown. In this work, analysis of minimal commonly deleted 8p segments to identify candidate TSG implicated GATA4, a master transcription factor driver of hepatocyte epithelial lineage fate. In a murine model, liver-conditional deletion of 1 Gata4 allele to model the haploinsufficiency seen in HCC produced enlarged livers with a gene expression profile of persistent precursor proliferation and failed hepatocyte epithelial differentiation. HCC mimicked this gene expression profile, even in cases that were morphologically classified as well differentiated. HCC with intact chromosome 8p also featured GATA4 loss of function via GATA4 germline mutations that abrogated GATA4 interactions with a coactivator, MED12, or by inactivating mutations directly in GATA4 coactivators, including ARID1A. GATA4 reintroduction into GATA4-haploinsufficient HCC cells or ARID1A reintroduction into ARID1A-mutant/GATA4-intact HCC cells activated hundreds of hepatocyte genes and quenched the proliferative precursor program. Thus, disruption of GATA4-mediated transactivation in HCC suppresses hepatocyte epithelial differentiation to sustain replicative precursor phenotype.
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Affiliation(s)
- Francis O Enane
- Translational Hematology and Oncology Research, Taussig Cancer Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Wai Ho Shuen
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore
| | - Xiaorong Gu
- Translational Hematology and Oncology Research, Taussig Cancer Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Ebrahem Quteba
- Translational Hematology and Oncology Research, Taussig Cancer Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Bartlomiej Przychodzen
- Translational Hematology and Oncology Research, Taussig Cancer Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Hideki Makishima
- Translational Hematology and Oncology Research, Taussig Cancer Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Juraj Bodo
- Translational Hematology and Oncology Research, Taussig Cancer Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Joanna Ng
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore
| | - Chit Lai Chee
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore
| | - Rebecca Ba
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore
| | - Lip Seng Koh
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore
| | - Janice Lim
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore
| | - Rachael Cheong
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore
| | - Marissa Teo
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore
| | - Zhenbo Hu
- Translational Hematology and Oncology Research, Taussig Cancer Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Kwok Peng Ng
- Translational Hematology and Oncology Research, Taussig Cancer Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Jaroslaw Maciejewski
- Translational Hematology and Oncology Research, Taussig Cancer Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Tomas Radivoyevitch
- Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio, USA
| | - Alexander Chung
- Department of Hepato-pancreato-biliary and Transplant Surgery and
| | | | - Yu Meng Tan
- Department of Hepato-pancreato-biliary and Transplant Surgery and
| | - Peng-Chung Cheow
- Department of Hepato-pancreato-biliary and Transplant Surgery and
| | - Pierce Chow
- Department of Hepato-pancreato-biliary and Transplant Surgery and
| | - Chung Yip Chan
- Department of Hepato-pancreato-biliary and Transplant Surgery and
| | - Kiat Hon Lim
- Department of Pathology, Singapore General Hospital, Singapore
| | - Lisa Yerian
- Clinical Pathology, Pathology Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Eric Hsi
- Clinical Pathology, Pathology Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Han Chong Toh
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore
| | - Yogen Saunthararajah
- Translational Hematology and Oncology Research, Taussig Cancer Institute, Cleveland Clinic, Cleveland, Ohio, USA
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40
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Tan-Koi WC, Sung C, Chong YY, Lateef A, Pang SM, Vasudevan A, Aw D, Lui NL, Lee SX, Ren EC, Koay ES, Tay YK, Lim YL, Lee HY, Dong D, Loke C, Tan L, Limenta M, Lee EJ, Toh D, Chan CL. Tailoring of recommendations to reduce serious cutaneous adverse drug reactions: a pharmacogenomics approach. Pharmacogenomics 2017; 18:881-890. [PMID: 28594314 DOI: 10.2217/pgs-2017-0016] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
The Health Sciences Authority launched a pharmacogenetics initiative in 2008 to facilitate evaluation of pharmacogenetics associations pertinent for Chinese, Malays and Indians in Singapore. The aim was to reduce the incidence and unpredictability of serious adverse drug reactions, with a focus on serious skin adverse drug reactions. This paper describes the gathering of evidence and weighing of factors that led to different genotyping recommendations for HLA-B*15:02 with carbamazepine and HLA-B*58:01 with allopurinol, despite both having strong genetic associations. Translation of pharmacogenomics at a national level requires careful deliberation of the prevalence of at-risk allele, strength of genetic associations, positive predictive value, cost-effectiveness and availability of alternative therapies. Our experience provides a perspective on translating genomic discoveries in advancing drug safety.
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Affiliation(s)
- Wei Chuen Tan-Koi
- Health Products Regulation Group, Health Sciences Authority, 11 Biopolis Way, 11-03, Helios, Singapore 138667, Singapore.,Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Cynthia Sung
- Health Products Regulation Group, Health Sciences Authority, 11 Biopolis Way, 11-03, Helios, Singapore 138667, Singapore.,Health Services & Systems Research Programme, Duke-NUS Medical School, Singapore, Singapore
| | - Yong Yeow Chong
- Department of Rheumatology and Immunology, Singapore General Hospital, Singapore, Singapore.,Internal Medicine Centre, Raffles Hospital, Singapore, Singapore
| | - Aisha Lateef
- Division of Rheumatology, National University Hospital, Singapore, Singapore
| | - Shiu Ming Pang
- Department of Dermatology, Singapore General Hospital, Singapore, Singapore
| | - Archana Vasudevan
- Department of Rheumatology, Changi General Hospital, Singapore, Singapore
| | - Derrick Aw
- Division of Dermatology, National University Hospital, Singapore, Singapore
| | - Nai Lee Lui
- Department of Rheumatology and Immunology, Singapore General Hospital, Singapore, Singapore
| | - Shan Xian Lee
- Department of Dermatology, Changi General Hospital, Singapore, Singapore
| | - Ee Chee Ren
- Singapore Immunology Network, Agency for Science, Technology and Research, Singapore, Singapore
| | - Evelyn Sc Koay
- Molecular Diagnosis Centre, National University Hospital, Singapore, Singapore.,Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Yong Kwang Tay
- Department of Dermatology, Changi General Hospital, Singapore, Singapore
| | | | - Haur Yueh Lee
- Department of Dermatology, Singapore General Hospital, Singapore, Singapore
| | - Di Dong
- Health Services & Systems Research Programme, Duke-NUS Medical School, Singapore, Singapore.,Global Health Research Center, Duke-Kunshan University, Kunshan, China
| | - Celine Loke
- Health Products Regulation Group, Health Sciences Authority, 11 Biopolis Way, 11-03, Helios, Singapore 138667, Singapore
| | - Liesbet Tan
- Health Products Regulation Group, Health Sciences Authority, 11 Biopolis Way, 11-03, Helios, Singapore 138667, Singapore
| | - Michael Limenta
- Health Products Regulation Group, Health Sciences Authority, 11 Biopolis Way, 11-03, Helios, Singapore 138667, Singapore
| | - Edmund Jd Lee
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Dorothy Toh
- Health Products Regulation Group, Health Sciences Authority, 11 Biopolis Way, 11-03, Helios, Singapore 138667, Singapore
| | - Cheng Leng Chan
- Health Products Regulation Group, Health Sciences Authority, 11 Biopolis Way, 11-03, Helios, Singapore 138667, Singapore
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41
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Abdullah N, Abdul Murad NA, Mohd Haniff EA, Syafruddin SE, Attia J, Oldmeadow C, Kamaruddin MA, Abd Jalal N, Ismail N, Ishak M, Jamal R, Scott RJ, Holliday EG. Predicting type 2 diabetes using genetic and environmental risk factors in a multi-ethnic Malaysian cohort. Public Health 2017; 149:31-38. [PMID: 28528225 DOI: 10.1016/j.puhe.2017.04.003] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2016] [Revised: 03/17/2017] [Accepted: 04/05/2017] [Indexed: 12/22/2022]
Abstract
OBJECTIVE Malaysia has a high and rising prevalence of type 2 diabetes (T2D). While environmental (non-genetic) risk factors for the disease are well established, the role of genetic variations and gene-environment interactions remain understudied in this population. This study aimed to estimate the relative contributions of environmental and genetic risk factors to T2D in Malaysia and also to assess evidence for gene-environment interactions that may explain additional risk variation. STUDY DESIGN This was a case-control study including 1604 Malays, 1654 Chinese and 1728 Indians from the Malaysian Cohort Project. METHODS The proportion of T2D risk variance explained by known genetic and environmental factors was assessed by fitting multivariable logistic regression models and evaluating McFadden's pseudo R2 and the area under the receiver-operating characteristic curve (AUC). Models with and without the genetic risk score (GRS) were compared using the log likelihood ratio Chi-squared test and AUCs. Multiplicative interaction between genetic and environmental risk factors was assessed via logistic regression within and across ancestral groups. Interactions were assessed for the GRS and its 62 constituent variants. RESULTS The models including environmental risk factors only had pseudo R2 values of 16.5-28.3% and AUC of 0.75-0.83. Incorporating a genetic score aggregating 62 T2D-associated risk variants significantly increased the model fit (likelihood ratio P-value of 2.50 × 10-4-4.83 × 10-12) and increased the pseudo R2 by about 1-2% and AUC by 1-3%. None of the gene-environment interactions reached significance after multiple testing adjustment, either for the GRS or individual variants. For individual variants, 33 out of 310 tested associations showed nominal statistical significance with 0.001 < P < 0.05. CONCLUSION This study suggests that known genetic risk variants contribute a significant but small amount to overall T2D risk variation in Malaysian population groups. If gene-environment interactions involving common genetic variants exist, they are likely of small effect, requiring substantially larger samples for detection.
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Affiliation(s)
- N Abdullah
- School of Biomedical Sciences and Pharmacy, Faculty of Health, University of Newcastle, Newcastle, NSW, Australia; UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - N A Abdul Murad
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - E A Mohd Haniff
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - S E Syafruddin
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - J Attia
- Clinical Research Design, IT and Statistical Support (CReDITSS) Unit, Hunter Medical Research Institute, Newcastle, NSW, Australia; Centre for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, Faculty of Health, University of Newcastle, Newcastle, NSW, Australia
| | - C Oldmeadow
- Clinical Research Design, IT and Statistical Support (CReDITSS) Unit, Hunter Medical Research Institute, Newcastle, NSW, Australia; Centre for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, Faculty of Health, University of Newcastle, Newcastle, NSW, Australia
| | - M A Kamaruddin
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - N Abd Jalal
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - N Ismail
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - M Ishak
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - R Jamal
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia.
| | - R J Scott
- School of Biomedical Sciences and Pharmacy, Faculty of Health, University of Newcastle, Newcastle, NSW, Australia; Hunter Area Pathology Service, John Hunter Hospital, Newcastle, NSW, Australia
| | - E G Holliday
- Clinical Research Design, IT and Statistical Support (CReDITSS) Unit, Hunter Medical Research Institute, Newcastle, NSW, Australia; Centre for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, Faculty of Health, University of Newcastle, Newcastle, NSW, Australia.
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42
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Baker JL, Rotimi CN, Shriner D. Human ancestry correlates with language and reveals that race is not an objective genomic classifier. Sci Rep 2017; 7:1572. [PMID: 28484253 PMCID: PMC5431528 DOI: 10.1038/s41598-017-01837-7] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2017] [Accepted: 04/04/2017] [Indexed: 12/22/2022] Open
Abstract
Genetic and archaeological studies have established a sub-Saharan African origin for anatomically modern humans with subsequent migrations out of Africa. Using the largest multi-locus data set known to date, we investigated genetic differentiation of early modern humans, human admixture and migration events, and relationships among ancestries and language groups. We compiled publicly available genome-wide genotype data on 5,966 individuals from 282 global samples, representing 30 primary language families. The best evidence supports 21 ancestries that delineate genetic structure of present-day human populations. Independent of self-identified ethno-linguistic labels, the vast majority (97.3%) of individuals have mixed ancestry, with evidence of multiple ancestries in 96.8% of samples and on all continents. The data indicate that continents, ethno-linguistic groups, races, ethnicities, and individuals all show substantial ancestral heterogeneity. We estimated correlation coefficients ranging from 0.522 to 0.962 between ancestries and language families or branches. Ancestry data support the grouping of Kwadi-Khoe, Kx’a, and Tuu languages, support the exclusion of Omotic languages from the Afroasiatic language family, and do not support the proposed Dené-Yeniseian language family as a genetically valid grouping. Ancestry data yield insight into a deeper past than linguistic data can, while linguistic data provide clarity to ancestry data.
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Affiliation(s)
- Jennifer L Baker
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Building 12A, Room 4047, 12 South Drive, Bethesda, Maryland, 20892, USA
| | - Charles N Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Building 12A, Room 4047, 12 South Drive, Bethesda, Maryland, 20892, USA.
| | - Daniel Shriner
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Building 12A, Room 4047, 12 South Drive, Bethesda, Maryland, 20892, USA.
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43
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Liu X, Lu D, Saw WY, Shaw PJ, Wangkumhang P, Ngamphiw C, Fucharoen S, Lert-Itthiporn W, Chin-Inmanu K, Chau TNB, Anders K, Kasturiratne A, de Silva HJ, Katsuya T, Kimura R, Nabika T, Ohkubo T, Tabara Y, Takeuchi F, Yamamoto K, Yokota M, Mamatyusupu D, Yang W, Chung YJ, Jin L, Hoh BP, Wickremasinghe AR, Ong RH, Khor CC, Dunstan SJ, Simmons C, Tongsima S, Suriyaphol P, Kato N, Xu S, Teo YY. Characterising private and shared signatures of positive selection in 37 Asian populations. Eur J Hum Genet 2017; 25:499-508. [PMID: 28098149 DOI: 10.1038/ejhg.2016.181] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2016] [Revised: 10/22/2016] [Accepted: 11/01/2016] [Indexed: 11/09/2022] Open
Abstract
The Asian Diversity Project (ADP) assembled 37 cosmopolitan and ethnic minority populations in Asia that have been densely genotyped across over half a million markers to study patterns of genetic diversity and positive natural selection. We performed population structure analyses of the ADP populations and divided these populations into four major groups based on their genographic information. By applying a highly sensitive algorithm haploPS to locate genomic signatures of positive selection, 140 distinct genomic regions exhibiting evidence of positive selection in at least one population were identified. We examined the extent of signal sharing for regions that were selected in multiple populations and observed that populations clustered in a similar fashion to that of how the ancestry clades were phylogenetically defined. In particular, populations predominantly located in South Asia underwent considerably different adaptation as compared with populations from the other geographical regions. Signatures of positive selection present in multiple geographical regions were predicted to be older and have emerged prior to the separation of the populations in the different regions. In contrast, selection signals present in a single population group tended to be of lower frequencies and thus can be attributed to recent evolutionary events.
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Affiliation(s)
- Xuanyao Liu
- NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore, Singapore.,Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Dongsheng Lu
- Max Planck Independent Research Group on Population Genomics, Chinese Academy of Sciences and Max Planck Society Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Woei-Yuh Saw
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.,Life Sciences Institute, National University of Singapore, Singapore, Singapore
| | - Philip J Shaw
- National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Pathum Thani, Thailand
| | - Pongsakorn Wangkumhang
- National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Pathum Thani, Thailand
| | - Chumpol Ngamphiw
- National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Pathum Thani, Thailand
| | - Suthat Fucharoen
- Institute of Molecular Biosciences, Mahidol University, Nakhon Pathom, Thailand
| | - Worachart Lert-Itthiporn
- Faculty of Science, Molecular Medicine Graduate Programme, Mahidol University, Bangkok, Thailand.,Division of Bioinformatics and Data Management for Research, Department of Research and Development, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Kwanrutai Chin-Inmanu
- Division of Bioinformatics and Data Management for Research, Department of Research and Development, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Tran Nguyen Bich Chau
- Oxford University Clinical Research Unit, Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam
| | - Katie Anders
- Oxford University Clinical Research Unit, Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam.,Nuffield Department of Clinical Medicine, Centre for Tropical Medicine, University of Oxford, Oxford, UK
| | | | - H Janaka de Silva
- Department of Medicine, Faculty of Medicine, University of Kelaniya, Ragama, Sri Lanka
| | - Tomohiro Katsuya
- Department of Clinical Gene Therapy, Osaka University Graduate School of Medicine, Suita, Japan
| | - Ryosuke Kimura
- Department of Human Biology and Anatomy, Graduate School of Medicine, University of the Ryukyus, Nishihara-cho, Japan
| | - Toru Nabika
- Department of Functional Pathology, Shimane University School of Medicine, Izumo, Japan
| | - Takayoshi Ohkubo
- Department of Hygiene and Public Health, Teikyo University School of Medicine, Tokyo, Japan
| | - Yasuharu Tabara
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Fumihiko Takeuchi
- Department of Gene Diagnostics and Therapeutics, National Center for Global Health and Medicine, Tokyo, Japan
| | - Ken Yamamoto
- Department of Medical Chemistry, Kurume University School of Medicine, Kurume, Japan
| | - Mitsuhiro Yokota
- Department of Genome Science, School of Dentistry, Aichi Gakuin University, Nagoya, Japan
| | - Dolikun Mamatyusupu
- College of the Life Sciences and Technology, Xinjiang University, Urumqi, China
| | - Wenjun Yang
- Key Laboratory of Reproduction and Heredity of Ningxia Region, Ningxia Medical University, YinchuanChina
| | - Yeun-Jun Chung
- Department of Microbiology, Integrated Research Center for Genome Polymorphism, The Catholic University Medical College, Seoul, Korea
| | - Li Jin
- State Key Laboratory of Genetic Engineering and Ministry of Education (MOE), Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai, China
| | - Boon-Peng Hoh
- Faculty of Medicine and Health Sciences, UCSI University, Kuala Lumpur, Malaysia
| | | | - RickTwee-Hee Ong
- Saw Swee Hock 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
| | - Sarah J Dunstan
- Oxford University Clinical Research Unit, Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam.,Nuffield Department of Clinical Medicine, Centre for Tropical Medicine, University of Oxford, Oxford, UK.,The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Victoria, Australia
| | - Cameron Simmons
- Oxford University Clinical Research Unit, Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam.,Nuffield Department of Clinical Medicine, Centre for Tropical Medicine, University of Oxford, Oxford, UK.,Department of Microbiology and Immunology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Sissades Tongsima
- National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Pathum Thani, Thailand
| | - Prapat Suriyaphol
- Division of Bioinformatics and Data Management for Research, Department of Research and Development, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.,Institute of Personalized Genomics and Gene Therapy (IPGG), Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Norihiro Kato
- Department of Gene Diagnostics and Therapeutics, National Center for Global Health and Medicine, Tokyo, Japan
| | - Shuhua Xu
- Max Planck Independent Research Group on Population Genomics, Chinese Academy of Sciences and Max Planck Society Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.,School of Life Sciences and Technology, ShanghaiTech University, Shanghai, China.,Collaborative Innovation Center of Genetics and Development, Shanghai, China
| | - Yik-Ying Teo
- NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore, Singapore.,Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.,Life Sciences Institute, National University of Singapore, Singapore, Singapore.,Department of Gene Diagnostics and Therapeutics, National Center for Global Health and Medicine, Tokyo, Japan.,Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore.,Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore
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44
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Tan M, Ng IKS, Chen Z, Ban K, Ng C, Chiu L, Seah E, Lin M, Tai BC, Yan B, Ng CH, Chng WJ. Clinical implications ofDNMT3Amutations in a Southeast Asian cohort of acute myeloid leukaemia patients. J Clin Pathol 2017; 70:669-676. [DOI: 10.1136/jclinpath-2016-204195] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2016] [Revised: 12/15/2016] [Accepted: 12/16/2016] [Indexed: 02/03/2023]
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45
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Ibrahim WN, Sabri MAB, Musa NAM, Ahmad NNFN, Abdullah NZB, Talib NB. Endothelial Nitric Oxide Synthase Gene Polymorphism and Coronary Artery Disease in Asian Populations. JOURNAL OF MEDICAL SCIENCES 2016. [DOI: 10.3923/jms.2017.38.45] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
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46
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Harrison RW, Radhakrishnan V, Lam PS, Allocco DJ, Brar S, Fahy M, Fisher R, Ikeno F, Généreux P, Kimura T, Liu M, Lye WK, Mintz GS, Nagai H, Suzuki Y, White R, Allen JC, Krucoff MW. Rationale and design of the East-West late lumen loss study: Comparison of late lumen loss between Eastern and Western drug-eluting stent study cohorts. Am Heart J 2016; 182:103-110. [PMID: 27914489 DOI: 10.1016/j.ahj.2016.07.011] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2016] [Accepted: 07/31/2016] [Indexed: 01/09/2023]
Abstract
BACKGROUND The contemporary evaluation of novel drug-eluting stents (DES) includes mechanistic observations that characterize postdeployment stent behavior. Quantification of late lumen loss due to neointimal hyperplasia 8-13 months after stent implantation, via quantitative coronary angiography (QCA), constitutes such an observation and is required by most regulatory authorities. Late lumen loss, as determined by QCA, has been validated as a surrogate for clinical endpoints such as target vessel revascularization. The mechanistic response to DES has not been directly compared across predominantly Asian or Western populations, whereas understanding their comparability across geographic populations could enhance global DES evaluation. OBJECTIVE The East-West late lumen loss study is designed to demonstrate whether the residual differences in late lumen loss, as assessed by QCA, is different between Eastern and Western DES recipients from studies with protocol angiography at 8-13 months of follow-up. METHODS Data from independent core laboratories that have characterized angiographic late lumen loss in DES clinical trials with protocol follow-up angiography will be compiled and dichotomized into Eastern and Western populations. A prospectively developed propensity score model incorporating clinical and anatomic variables affecting late lumen loss will be used to adjust comparisons of QCA measurements. CONCLUSION Documentation of whether there are clinically meaningful differences in mechanistic response to DES implantation across genetically unique geographies could facilitate both the quality and efficiency of global device evaluation requiring invasive follow-up for novel stent designs.
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Affiliation(s)
- Robert W Harrison
- Duke University Medical Center/Duke Clinical Research Institute, Durham, NC.
| | | | | | | | | | | | - Rebecca Fisher
- Duke University Medical Center/Duke Clinical Research Institute, Durham, NC
| | | | | | | | | | - Weng Kit Lye
- Duke-NUS Graduate Medical School Singapore, Singapore
| | - Gary S Mintz
- Cardiovascular Research Foundation, New York, NY
| | | | - Yuka Suzuki
- Pharmaceuticals and Medical Devices Agency, Tokyo, Japan
| | | | - John C Allen
- Duke-NUS Graduate Medical School Singapore, Singapore
| | - Mitchell W Krucoff
- Duke University Medical Center/Duke Clinical Research Institute, Durham, NC
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Liu J, Li M, Su B. GWAS-identified schizophrenia risk SNPs at TSPAN18 are highly diverged between Europeans and East Asians. Am J Med Genet B Neuropsychiatr Genet 2016; 171:1032-1040. [PMID: 27312590 DOI: 10.1002/ajmg.b.32471] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2016] [Accepted: 06/03/2016] [Indexed: 12/21/2022]
Abstract
Genome-wide association studies (GWASs) have identified multiple schizophrenia (SCZ) risk variants for samples of European and East Asian descent, but most of the identified susceptibility variants are population-specific to either Europeans or East Asians. This strong genetic heterogeneity suggests that differential population histories may play a role in SCZ susceptibility. Here, we explored this possibility by examining the allele frequency divergence of 136 previously reported genome-wide SCZ risk SNPs between European and East Asian populations. Our results showed that two SNPs (rs11038167 and rs11038172) at TSPAN18, reported as genome-wide significant SCZ risk variants in Han Chinese, were entirely monomorphic in Europeans, indicating a deep between-population divergence at this gene locus. To explore the evolutionary history of TSPAN18 in East Asians, we conducted population genetic analyses including multiple neutrality tests, the haplotype-based iHS and EHH tests, as well as haplotype bifurcation map and network constructions. We found that the protective allele of rs11038172 (G allele) had a long extended haplotype with much slower decay compared to the A allele. The star-like shape of the G-allele-carrying haplotypes indicates a recent enrichment in East Asians. Together, the evidences suggest that the protective allele of rs11038172 has experienced recent Darwinian positive selection in East Asians. These findings provide new insights that may help explain the strong genetic heterogeneity in SCZ risk and previous inconsistent association results for SCZ among both Europeans and East Asians. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Jiewei Liu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Ming Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Kunming, Yunnan, China
| | - Bing Su
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
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48
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Genetic diversity of variants involved in drug response and metabolism in Sri Lankan populations: implications for clinical implementation of pharmacogenomics. Pharmacogenet Genomics 2016; 26:28-39. [PMID: 26444257 PMCID: PMC4890825 DOI: 10.1097/fpc.0000000000000182] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Supplemental Digital Content is available in the text. Background Interpopulation differences in drug responses are well documented, and in some cases they correspond to differences in the frequency of associated genetic markers. Understanding the diversity of genetic markers associated with drug response across different global populations is essential to infer population rates of drug response or risk for adverse drug reactions, and to guide implementation of pharmacogenomic testing. Sri Lanka is a culturally and linguistically diverse nation, but little is known about the population genetics of the major Sri Lankan ethnic groups. The objective of this study was to investigate the diversity of pharmacogenomic variants in the major Sri Lankan ethnic groups. Methods We examined the allelic diversity of more than 7000 variants in genes involved in drug biotransformation and response in the three major ethnic populations of Sri Lanka (Sinhalese, Sri Lankan Tamils, and Moors), and compared them with other South Asian, South East Asian, and European populations using Wright’s Fixation Index, principal component analysis, and STRUCTURE analysis. Results We observed overall high levels of similarity within the Sri Lankan populations (median FST=0.0034), and between Sri Lankan and other South Asian populations (median FST=0.0064). Notably, we observed substantial differentiation between Sri Lankan and European populations for important pharmacogenomic variants related to warfarin (VKORC1 rs9923231) and clopidogrel (CYP2C19 rs4986893) response. Conclusion These data expand our understanding of the population structure of Sri Lanka, provide a resource for pharmacogenomic research, and have implications for the clinical use of genetic testing of pharmacogenomic variants in these populations.
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49
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Alperet DJ, Lim WY, Mok-Kwee Heng D, Ma S, van Dam RM. Optimal anthropometric measures and thresholds to identify undiagnosed type 2 diabetes in three major Asian ethnic groups. Obesity (Silver Spring) 2016; 24:2185-93. [PMID: 27558457 DOI: 10.1002/oby.21609] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2016] [Revised: 06/02/2016] [Accepted: 06/03/2016] [Indexed: 12/28/2022]
Abstract
OBJECTIVE To identify optimal anthropometric measures and cutoffs to identify undiagnosed diabetes mellitus (UDM) in three major Asian ethnic groups (Chinese, Malays, and Asian-Indians). METHODS Cross-sectional data were analyzed from 14,815 ethnic Chinese, Malay, and Asian-Indian participants of the Singapore National Health Surveys, which included anthropometric measures and an oral glucose tolerance test. Receiver operating characteristic curve analyses were used with calculation of the area under the curve (AUC) to evaluate the performance of body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHTR) for the identification of UDM. RESULTS BMI performed significantly worse (AUCMEN = 0.70; AUCWOMEN = 0.75) than abdominal measures, whereas WHTR (AUCMEN = 0.76; AUCWOMEN = 0.79) was among the best performing measures in both sexes and all ethnic groups. Anthropometric measures performed better in Chinese than in Asian-Indian participants for the identification of UDM. A WHTR cutoff of 0.52 appeared optimal with a sensitivity of 76% in men and 73% in women and a specificity of 63% in men and 70% in women. CONCLUSIONS Although ethnic differences were observed in the performance of anthropometric measures for the identification of UDM, abdominal adiposity measures generally performed better than BMI, and WHTR performed best in all Asian ethnic groups.
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Affiliation(s)
- Derrick Johnston Alperet
- NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Wei-Yen Lim
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
- Epidemiology and Disease Control Division, Public Health Group, Ministry of Health, Singapore
| | - Derrick Mok-Kwee Heng
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
- Epidemiology and Disease Control Division, Public Health Group, Ministry of Health, Singapore
| | - Stefan Ma
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
- Epidemiology and Disease Control Division, Public Health Group, Ministry of Health, Singapore
| | - Rob M van Dam
- NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore.
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore.
- Department of Medicine, Yong Loo Lin School of Medicine, National University Health System, Singapore.
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50
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Djuardi Y, Supali T, Wibowo H, Heijmans BT, Deelen J, Slagboom EP, Houwing-Duistermaat JJ, Sartono E, Yazdanbakhsh M. Maternal and child cytokine relationship in early life is not altered by cytokine gene polymorphisms. Genes Immun 2016; 17:380-385. [PMID: 27581100 PMCID: PMC5223084 DOI: 10.1038/gene.2016.35] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2015] [Revised: 06/21/2016] [Accepted: 07/06/2016] [Indexed: 01/22/2023]
Abstract
The development of immune responses is influenced by the interaction between environmental and genetic factors. Our previous study showed a close association between maternal and young infant's cytokine responses. The question is how this association evolves over time and the contribution of genetic polymorphisms to this association. Five cytokines in mitogen-stimulated whole blood culture were measured from pregnant mothers and their children aged 2, 5, 12, 24 and 48 months. Cytokine gene polymorphisms were determined in both mothers and children. High production of maternal interleukin (IL)-10, tumour necrosis factor-α (TNF-α) and interferon-γ (IFN-γ) was significantly associated with higher levels of the corresponding cytokines in their children at 2 months (T2), but the association decreased over time. Maternal single-nucleotide polymorphism (SNP) in IFN-γ gene, rs3181032, was found to be associated with child's IFN-γ levels at T2 only, whereas maternal IL-10 rs4579758 and child's TNF-α rs13215091 were associated with child's corresponding cytokines at later ages but not at T2. In the final models including the gene polymorphisms, maternal cytokines were still the strongest determinant of child cytokines. Maternal cytokine during pregnancy, which could be a proxy for child's environmental factors, showed its highest impact at early age, with no or little influence from genetic factors.
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Affiliation(s)
- Y Djuardi
- Department of Parasitology, Universitas Indonesia, Jakarta, Indonesia.,Department of Parasitology, Leiden University Medical Center, Leiden, The Netherlands
| | - T Supali
- Department of Parasitology, Universitas Indonesia, Jakarta, Indonesia
| | - H Wibowo
- Department of Parasitology, Universitas Indonesia, Jakarta, Indonesia
| | - B T Heijmans
- Molecular Epidemiology, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands
| | - J Deelen
- Molecular Epidemiology, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands
| | - E P Slagboom
- Molecular Epidemiology, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands
| | - J J Houwing-Duistermaat
- Medical Statistics, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands
| | - E Sartono
- Department of Parasitology, Leiden University Medical Center, Leiden, The Netherlands
| | - M Yazdanbakhsh
- Department of Parasitology, Leiden University Medical Center, Leiden, The Netherlands
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