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Troubat L, Fettahoglu D, Henches L, Aschard H, Julienne H. Multi-trait GWAS for diverse ancestries: mapping the knowledge gap. BMC Genomics 2024; 25:375. [PMID: 38627641 PMCID: PMC11022331 DOI: 10.1186/s12864-024-10293-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 04/09/2024] [Indexed: 04/19/2024] Open
Abstract
BACKGROUND Approximately 95% of samples analyzed in univariate genome-wide association studies (GWAS) are of European ancestry. This bias toward European ancestry populations in association screening also exists for other analyses and methods that are often developed and tested on European ancestry only. However, existing data in non-European populations, which are often of modest sample size, could benefit from innovative approaches as recently illustrated in the context of polygenic risk scores. METHODS Here, we extend and assess the potential limitations and gains of our multi-trait GWAS pipeline, JASS (Joint Analysis of Summary Statistics), for the analysis of non-European ancestries. To this end, we conducted the joint GWAS of 19 hematological traits and glycemic traits across five ancestries (European (EUR), admixed American (AMR), African (AFR), East Asian (EAS), and South-East Asian (SAS)). RESULTS We detected 367 new genome-wide significant associations in non-European populations (15 in Admixed American (AMR), 72 in African (AFR) and 280 in East Asian (EAS)). New associations detected represent 5%, 17% and 13% of associations in the AFR, AMR and EAS populations, respectively. Overall, multi-trait testing increases the replication of European associated loci in non-European ancestry by 15%. Pleiotropic effects were highly similar at significant loci across ancestries (e.g. the mean correlation between multi-trait genetic effects of EUR and EAS ancestries was 0.88). For hematological traits, strong discrepancies in multi-trait genetic effects are tied to known evolutionary divergences: the ARKC1 loci, which is adaptive to overcome p.vivax induced malaria. CONCLUSIONS Multi-trait GWAS can be a valuable tool to narrow the genetic knowledge gap between European and non-European populations.
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Affiliation(s)
- Lucie Troubat
- Department of Computational Biology, Institut Pasteur, Université Paris Cité, Paris, F-75015, France
| | - Deniz Fettahoglu
- Department of Computational Biology, Institut Pasteur, Université Paris Cité, Paris, F-75015, France
| | - Léo Henches
- Department of Computational Biology, Institut Pasteur, Université Paris Cité, Paris, F-75015, France
| | - Hugues Aschard
- Department of Computational Biology, Institut Pasteur, Université Paris Cité, Paris, F-75015, France
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Hanna Julienne
- Department of Computational Biology, Institut Pasteur, Université Paris Cité, Paris, F-75015, France.
- Institut Pasteur, Université Paris Cité, Bioinformatics and Biostatistics Hub, Paris, F-75015, France.
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2
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Beugnot A, Mary-Huard T, Bauland C, Combes V, Madur D, Lagardère B, Palaffre C, Charcosset A, Moreau L, Fievet JB. Identifying QTLs involved in hybrid performance and heterotic group complementarity: new GWAS models applied to factorial and admixed diallel maize hybrid panels. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:219. [PMID: 37816986 PMCID: PMC10564676 DOI: 10.1007/s00122-023-04431-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Accepted: 07/25/2023] [Indexed: 10/12/2023]
Abstract
KEY MESSAGE An original GWAS model integrating the ancestry of alleles was proposed and allowed the detection of background specific additive and dominance QTLs involved in heterotic group complementarity and hybrid performance. Maize genetic diversity is structured into genetic groups selected and improved relative to each other. This process increases group complementarity and differentiation over time and ensures that the hybrids produced from inter-group crosses exhibit high performances and heterosis. To identify loci involved in hybrid performance and heterotic group complementarity, we introduced an original association study model that disentangles allelic effects from the heterotic group origin of the alleles and compared it with a conventional additive/dominance model. This new model was applied on a factorial between Dent and Flint lines and a diallel between Dent-Flint admixed lines with two different layers of analysis: within each environment and in a multiple-environment context. We identified several strong additive QTLs for all traits, including some well-known additive QTLs for flowering time (in the region of Vgt1/2 on chromosome 8). Yield trait displayed significant non-additive effects in the diallel panel. Most of the detected Yield QTLs exhibited overdominance or, more likely, pseudo-overdominance effects. Apparent overdominance at these QTLs contributed to a part of the genetic group complementarity. The comparison between environments revealed a higher stability of additive QTL effects than non-additive ones. Several QTLs showed variations of effects according to the local heterotic group origin. We also revealed large chromosomic regions that display genetic group origin effects. Altogether, our results illustrate how admixed panels combined with dedicated GWAS modeling allow the identification of new QTLs that could not be revealed by a classical hybrid panel analyzed with traditional modeling.
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Affiliation(s)
- Aurélien Beugnot
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, UMR GQE-Le Moulon, 91272, Gif-Sur-Yvette, France
| | - Tristan Mary-Huard
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, UMR GQE-Le Moulon, 91272, Gif-Sur-Yvette, France
- Université Paris-Saclay, AgroParisTech, INRAE, UMR MIA Paris-Saclay, 91120, Palaiseau, France
| | - Cyril Bauland
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, UMR GQE-Le Moulon, 91272, Gif-Sur-Yvette, France
| | - Valerie Combes
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, UMR GQE-Le Moulon, 91272, Gif-Sur-Yvette, France
| | - Delphine Madur
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, UMR GQE-Le Moulon, 91272, Gif-Sur-Yvette, France
| | | | | | - Alain Charcosset
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, UMR GQE-Le Moulon, 91272, Gif-Sur-Yvette, France
| | - Laurence Moreau
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, UMR GQE-Le Moulon, 91272, Gif-Sur-Yvette, France
| | - Julie B Fievet
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, UMR GQE-Le Moulon, 91272, Gif-Sur-Yvette, France.
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3
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Abstract
Since the publication of the first genome-wide association study for cancer in 2007, thousands of common alleles that are associated with the risk of cancer have been identified. The relative risk associated with individual variants is small and of limited clinical significance. However, the combined effect of multiple risk variants as captured by polygenic scores (PGSs) may be much greater and therefore provide risk discrimination that is clinically useful. We review the considerable research efforts over the past 15 years for developing statistical methods for PGSs and their application in large-scale genome-wide association studies to develop PGSs for various cancers. We review the predictive performance of these PGSs and the multiple challenges currently limiting the clinical application of PGSs. Despite this, PGSs are beginning to be incorporated into clinical multifactorial risk prediction models to stratify risk in both clinical trials and clinical implementation studies.
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Affiliation(s)
- Xin Yang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Siddhartha Kar
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Early Cancer Institute, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Antonis C Antoniou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Paul D P Pharoah
- Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
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4
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Downie ML, Gupta S, Voinescu C, Levine AP, Sadeghi-Alavijeh O, Dufek-Kamperis S, Cao J, Christian M, Kari JA, Thalgahagoda S, Ranawaka R, Abeyagunawardena A, Gbadegesin R, Parekh R, Kleta R, Bockenhauer D, Stanescu HC, Gale DP. Common Risk Variants in AHI1 Are Associated With Childhood Steroid Sensitive Nephrotic Syndrome. Kidney Int Rep 2023; 8:1562-1574. [PMID: 37547536 PMCID: PMC10403666 DOI: 10.1016/j.ekir.2023.05.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 04/21/2023] [Accepted: 05/22/2023] [Indexed: 08/08/2023] Open
Abstract
Introduction Steroid-sensitive nephrotic syndrome (SSNS) is the most common form of kidney disease in children worldwide. Genome-wide association studies (GWAS) have demonstrated the association of SSNS with genetic variation at HLA-DQ/DR and have identified several non-HLA loci that aid in further understanding of disease pathophysiology. We sought to identify additional genetic loci associated with SSNS in children of Sri Lankan and European ancestry. Methods We conducted a GWAS in a cohort of Sri Lankan individuals comprising 420 pediatric patients with SSNS and 2339 genetic ancestry matched controls obtained from the UK Biobank. We then performed a transethnic meta-analysis with a previously reported European cohort of 422 pediatric patients and 5642 controls. Results Our GWAS confirmed the previously reported association of SSNS with HLA-DR/DQ (rs9271602, P = 1.12 × 10-27, odds ratio [OR] = 2.75). Transethnic meta-analysis replicated these findings and identified a novel association at AHI1 (rs2746432, P = 2.79 × 10-8, OR = 1.37), which was also replicated in an independent South Asian cohort. AHI1 is implicated in ciliary protein transport and immune dysregulation, with rare variation in this gene contributing to Joubert syndrome type 3. Conclusions Common variation in AHI1 confers risk of the development of SSNS in both Sri Lankan and European populations. The association with common variation in AHI1 further supports the role of immune dysregulation in the pathogenesis of SSNS and demonstrates that variation across the allele frequency spectrum in a gene can contribute to disparate monogenic and polygenic diseases.
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Affiliation(s)
- Mallory L. Downie
- Department of Renal Medicine, University College London, London, UK
- Paediatric Nephrology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
| | - Sanjana Gupta
- Department of Renal Medicine, University College London, London, UK
| | - Catalin Voinescu
- Department of Renal Medicine, University College London, London, UK
| | - Adam P. Levine
- Department of Pathology, University College London, London, UK
| | | | | | - Jingjing Cao
- Division of Nephrology, Department of Pediatrics, The Hospital for Sick Children, Toronto, Canada
| | | | - Jameela A. Kari
- Pediatric Nephrology Centre of Excellence, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia
| | | | - Randula Ranawaka
- Department of Pediatrics, University of Peradeniya, Peradeniya, Sri Lanka
| | | | - Rasheed Gbadegesin
- Department of Pediatrics, Duke University School of Medicine, Durham, North Carolina, USA
| | - Rulan Parekh
- Division of Nephrology, Department of Pediatrics, The Hospital for Sick Children, Toronto, Canada
- Department of Medicine, Women’s College Hospital, Toronto, Canada
| | - Robert Kleta
- Department of Renal Medicine, University College London, London, UK
- Paediatric Nephrology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
| | - Detlef Bockenhauer
- Department of Renal Medicine, University College London, London, UK
- Paediatric Nephrology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
| | | | - Daniel P. Gale
- Department of Renal Medicine, University College London, London, UK
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5
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Qiao J, Wu Y, Zhang S, Xu Y, Zhang J, Zeng P, Wang T. Evaluating significance of European-associated index SNPs in the East Asian population for 31 complex phenotypes. BMC Genomics 2023; 24:324. [PMID: 37312035 DOI: 10.1186/s12864-023-09425-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 06/01/2023] [Indexed: 06/15/2023] Open
Abstract
BACKGROUND Genome-wide association studies (GWASs) have identified many single-nucleotide polymorphisms (SNPs) associated with complex phenotypes in the European (EUR) population; however, the extent to which EUR-associated SNPs can be generalized to other populations such as East Asian (EAS) is not clear. RESULTS By leveraging summary statistics of 31 phenotypes in the EUR and EAS populations, we first evaluated the difference in heritability between the two populations and calculated the trans-ethnic genetic correlation. We observed the heritability estimates of some phenotypes varied substantially across populations and 53.3% of trans-ethnic genetic correlations were significantly smaller than one. Next, we examined whether EUR-associated SNPs of these phenotypes could be identified in EAS using the trans-ethnic false discovery rate method while accounting for winner's curse for SNP effect in EUR and difference of sample sizes in EAS. We found on average 54.5% of EUR-associated SNPs were also significant in EAS. Furthermore, we discovered non-significant SNPs had higher effect heterogeneity, and significant SNPs showed more consistent linkage disequilibrium and allele frequency patterns between the two populations. We also demonstrated non-significant SNPs were more likely to undergo natural selection. CONCLUSIONS Our study revealed the extent to which EUR-associated SNPs could be significant in the EAS population and offered deep insights into the similarity and diversity of genetic architectures underlying phenotypes in distinct ancestral groups.
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Affiliation(s)
- Jiahao Qiao
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Yuxuan Wu
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Shuo Zhang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Yue Xu
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Jinhui Zhang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Ping Zeng
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
- Center for Medical Statistics and Data Analysis, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
- Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
- Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
- Engineering Research Innovation Center of Biological Data Mining and Healthcare Transformation, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
| | - Ting Wang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
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6
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Jia G, Li Y, Zhong X, Wang K, Pividori M, Alomairy R, Esposito A, Ltaief H, Terao C, Akiyama M, Matsuda K, Keyes DE, Im HK, Gojobori T, Kamatani Y, Kubo M, Cox NJ, Evans J, Gao X, Rzhetsky A. The high-dimensional space of human diseases built from diagnosis records and mapped to genetic loci. NATURE COMPUTATIONAL SCIENCE 2023; 3:403-417. [PMID: 38177845 PMCID: PMC10766526 DOI: 10.1038/s43588-023-00453-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Accepted: 04/13/2023] [Indexed: 01/06/2024]
Abstract
Human diseases are traditionally studied as singular, independent entities, limiting researchers' capacity to view human illnesses as dependent states in a complex, homeostatic system. Here, using time-stamped clinical records of over 151 million unique Americans, we construct a disease representation as points in a continuous, high-dimensional space, where diseases with similar etiology and manifestations lie near one another. We use the UK Biobank cohort, with half a million participants, to perform a genome-wide association study of newly defined human quantitative traits reflecting individuals' health states, corresponding to patient positions in our disease space. We discover 116 genetic associations involving 108 genetic loci and then use ten disease constellations resulting from clustering analysis of diseases in the embedding space, as well as 30 common diseases, to demonstrate that these genetic associations can be used to robustly predict various morbidities.
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Affiliation(s)
- Gengjie Jia
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China.
| | - Yu Li
- Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
- Computer Science Program, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
- Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong, People's Republic of China
| | - Xue Zhong
- Department of Medicine and Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, US
| | - Kanix Wang
- Department of Medicine, Institute of Genomics and Systems Biology, Committee on Genomics, Genetics, and Systems Biology, University of Chicago, Chicago, IL, US
- Department of Operations, Business Analytics, and Information Systems, University of Cincinnati, Cincinnati, OH, US
| | - Milton Pividori
- Department of Medicine, Institute of Genomics and Systems Biology, Committee on Genomics, Genetics, and Systems Biology, University of Chicago, Chicago, IL, US
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, US
| | - Rabab Alomairy
- Extreme Computing Research Center, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
- College of Computer Science and Engineering, University of Jeddah, Jeddah, Saudi Arabia
| | | | - Hatem Ltaief
- Extreme Computing Research Center, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Chikashi Terao
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
- Department of Applied Genetics, The School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
| | - Masato Akiyama
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Ophthalmology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Koichi Matsuda
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - David E Keyes
- Extreme Computing Research Center, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Hae Kyung Im
- Department of Medicine, Institute of Genomics and Systems Biology, Committee on Genomics, Genetics, and Systems Biology, University of Chicago, Chicago, IL, US
| | - Takashi Gojobori
- Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
- Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Yoichiro Kamatani
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Nancy J Cox
- Department of Medicine and Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, US
| | - James Evans
- Department of Sociology, University of Chicago, Chicago, IL, US
| | - Xin Gao
- Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.
- Computer Science Program, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.
| | - Andrey Rzhetsky
- Department of Medicine, Institute of Genomics and Systems Biology, Committee on Genomics, Genetics, and Systems Biology, University of Chicago, Chicago, IL, US.
- Department of Human Genetics, University of Chicago, Chicago, IL, US.
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7
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Risk factors for acute encephalitis and early seizure recurrence in complex febrile seizures. Eur J Pediatr 2022; 181:3103-3110. [PMID: 35713689 DOI: 10.1007/s00431-022-04529-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 06/01/2022] [Accepted: 06/09/2022] [Indexed: 11/03/2022]
Abstract
The purpose of this study is to elucidate risk factors for central nervous system infection and early seizure recurrence in children with febrile seizures (FSs) and thus facilitate outpatient management of complex FS. This single-center, retrospective cohort study investigated 688 children (6-60 months old) with FSs in Japan during 2011-2021. We investigated the incidence and clinical manifestations of children with acute encephalitis or bacterial meningitis. Logistic regression modeling was used to examine risk factors for seizure recurrence within 24 h. Among children with recurrent FSs, the distribution of intervals between first and second FS was assessed. Among 145 children with complex FSs, 2 patients (1.4%) had acute viral encephalitis and none had bacterial meningitis. Acute encephalitis was found in 2 of 8 patients (25%) with FSs prolonged ≥30 min and 2 of 3 patients (67%) requiring ≥2 intravenous anticonvulsants to stop seizures. Seizure recurrence within 24 h was observed in 16% of participants and was independently associated with preceding use of diazepam and family history of FS. In 82% of patients with FS recurrence within 24 h, early recurrences occurred within 8 h of the first seizure. Conclusion: Patients with prolonged or refractory FSs are still indicated for hospital admission due to the risk of acute encephalitis. FS patients with a family history of FS may be managed safely by 8-h observation or single-dose rectal diazepam as prophylaxis against early recurrent seizure. What is Known: • Hospitalization has been recommended for children with complex febrile seizures due to the increased risk of central nervous infections. • Recent studies showed low incidences of bacterial meningitis (<1%) in children with complex febrile seizures in the presence of routine immunization. What is New: • Acute encephalitis was identified in 1.4% of children with complex febrile seizures, characterized by prolonged seizures ≥30 min and refractory seizures. • Early recurrent seizures may be safely managed by prophylactic diazepam or 8-h expectant observation.
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8
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Significant interpopulation differentiation at candidate loci may underlie ethnic disparities in the prevalence of uterine fibroids. J Genet 2021. [DOI: 10.1007/s12041-021-01342-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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9
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Yau MS, Kuipers AL, Price R, Nicolas A, Tajuddin SM, Handelman SK, Arbeeva L, Chesi A, Hsu YH, Liu CT, Karasik D, Zemel BS, Grant SFA, Jordan JM, Jackson RD, Evans MK, Harris TB, Zmuda JM, Kiel DP. A Meta-Analysis of the Transferability of Bone Mineral Density Genetic Loci Associations From European to African Ancestry Populations. J Bone Miner Res 2021; 36:469-479. [PMID: 33249669 PMCID: PMC8353846 DOI: 10.1002/jbmr.4220] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 11/09/2020] [Accepted: 11/19/2020] [Indexed: 12/17/2022]
Abstract
Genetic studies of bone mineral density (BMD) largely have been conducted in European populations. We therefore conducted a meta-analysis of six independent African ancestry cohorts to determine whether previously reported BMD loci identified in European populations were transferable to African ancestry populations. We included nearly 5000 individuals with both genetic data and assessments of BMD. Genotype imputation was conducted using the 1000G reference panel. We assessed single-nucleotide polymorphism (SNP) associations with femoral neck and lumbar spine BMD in each cohort separately, then combined results in fixed effects (or random effects if study heterogeneity was high, I2 index >60) inverse variance weighted meta-analyses. In secondary analyses, we conducted locus-based analyses of rare variants using SKAT-O. Mean age ranged from 12 to 68 years. One cohort included only men and another cohort included only women; the proportion of women in the other four cohorts ranged from 52% to 63%. Of 56 BMD loci tested, one locus, 6q25 (C6orf97, p = 8.87 × 10-4 ), was associated with lumbar spine BMD and two loci, 7q21 (SLC25A13, p = 2.84 × 10-4 ) and 7q31 (WNT16, p = 2.96 × 10-5 ), were associated with femoral neck BMD. Effects were in the same direction as previously reported in European ancestry studies and met a Bonferroni-adjusted p value threshold, the criteria for transferability to African ancestry populations. We also found associations that met locus-specific Bonferroni-adjusted p value thresholds in 11q13 (LRP5, p < 2.23 × 10-4 ), 11q14 (DCDC5, p < 5.35 × 10-5 ), and 17p13 (SMG6, p < 6.78 × 10-5 ) that were not tagged by European ancestry index SNPs. Rare single-nucleotide variants in AKAP11 (p = 2.32 × 10-2 ), MBL2 (p = 4.09 × 10-2 ), MEPE (p = 3.15 × 10-2 ), SLC25A13 (p = 3.03 × 10-2 ), STARD3NL (p = 3.35 × 10-2 ), and TNFRSF11A (p = 3.18 × 10-3 ) were also associated with BMD. The majority of known BMD loci were not transferable. Larger genetic studies of BMD in African ancestry populations will be needed to overcome limitations in statistical power and to identify both other loci that are transferable across populations and novel population-specific variants. © 2020 American Society for Bone and Mineral Research (ASBMR).
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Affiliation(s)
- Michelle S Yau
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Allison L Kuipers
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ryan Price
- Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - Aude Nicolas
- Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - Salman M Tajuddin
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Baltimore, MD, USA
| | - Samuel K Handelman
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Liubov Arbeeva
- Thurston Arthritis Research Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Alessandra Chesi
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Yi-Hsiang Hsu
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - David Karasik
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, MA, USA
- Azrieli Faculty of Medicine, Bar Ilan University, Safed, Israel
| | - Babette S Zemel
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Division of Gastroenterology, Hepatology, and Nutrition, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Struan FA Grant
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Division of Endocrinology and Diabetes, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Joanne M Jordan
- Thurston Arthritis Research Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Rebecca D Jackson
- Department of Internal Medicine, The Ohio State University, Columbus, OH, USA
| | - Michele K Evans
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Baltimore, MD, USA
| | - Tamara B Harris
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Baltimore, MD, USA
| | - Joseph M Zmuda
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Douglas P Kiel
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
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10
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Atkinson EG, Maihofer AX, Kanai M, Martin AR, Karczewski KJ, Santoro ML, Ulirsch JC, Kamatani Y, Okada Y, Finucane HK, Koenen KC, Nievergelt CM, Daly MJ, Neale BM. Tractor uses local ancestry to enable the inclusion of admixed individuals in GWAS and to boost power. Nat Genet 2021; 53:195-204. [PMID: 33462486 PMCID: PMC7867648 DOI: 10.1038/s41588-020-00766-y] [Citation(s) in RCA: 106] [Impact Index Per Article: 35.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Accepted: 12/15/2020] [Indexed: 12/26/2022]
Abstract
Admixed populations are routinely excluded from genomic studies due to concerns over population structure. Here, we present a statistical framework and software package, Tractor, to facilitate the inclusion of admixed individuals in association studies by leveraging local ancestry. We test Tractor with simulated and empirical two-way admixed African-European cohorts. Tractor generates accurate ancestry-specific effect-size estimates and P values, can boost genome-wide association study (GWAS) power and improves the resolution of association signals. Using a local ancestry-aware regression model, we replicate known hits for blood lipids, discover novel hits missed by standard GWAS and localize signals closer to putative causal variants.
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Affiliation(s)
- Elizabeth G Atkinson
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Adam X Maihofer
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Masahiro Kanai
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Bioinformatics and Integrative Genomics, Harvard Medical School, Boston, MA, USA
- Department of Statistical Genetics, Graduate School of Medicine, Osaka University, Suita, Japan
| | - Alicia R Martin
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Konrad J Karczewski
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Marcos L Santoro
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Departamento de Psiquiatria, Universidade Federal de São Paulo, São Paulo, Brazil
- Departamento de Morfologia e Genética, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Jacob C Ulirsch
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, MA, USA
| | - Yoichiro Kamatani
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yukinori Okada
- Department of Statistical Genetics, Graduate School of Medicine, Osaka University, Suita, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Japan
| | - Hilary K Finucane
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Karestan C Koenen
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | | | - Mark J Daly
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Benjamin M Neale
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
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11
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Gill PK, Dron JS, Dilliott AA, McIntyre AD, Cao H, Wang J, Movsesyan IG, Malloy MJ, Pullinger CR, Kane JP, Hegele RA. Ancestry-specific profiles of genetic determinants of severe hypertriglyceridemia. J Clin Lipidol 2021; 15:88-96. [PMID: 33303403 DOI: 10.1016/j.jacl.2020.11.007] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2020] [Revised: 10/31/2020] [Accepted: 11/17/2020] [Indexed: 12/01/2022]
Abstract
BACKGROUND Susceptibility to severe hypertriglyceridemia (HTG), defined as plasma triglyceride (TG) levels ≥10 mmol/L (880 mg/dL), is conferred by both heterozygous rare variants in five genes involved in TG metabolism and numerous common single-nucleotide polymorphisms (SNPs) associated with TG levels. OBJECTIVE To date, these genetic susceptibility factors have been comprehensively assessed primarily in severe HTG patients of European ancestry. Here, we expand our analysis to HTG patients of East Asian and Hispanic ancestry. METHODS The genomic DNA of 336, 63 and 199 severe HTG patients of European, East Asian and Hispanic ancestry, respectively, was evaluated using a targeted next-generation sequencing panel to screen for: 1) rare variants in LPL, APOA5, APOC2, GPIHBP1 and LMF1; 2) common, small-to-moderate effect SNPs, quantified using a polygenic score; and 3) common, large-effect polymorphisms, APOA5 p.G185C and p.S19W. RESULTS While the proportion of individuals with high polygenic scores was similar, frequency of rare variant carriers varied across ancestries. Compared with ancestry-matched controls, Hispanic patients were the most likely to have a rare variant (OR = 5.02; 95% CI 3.07-8.21; p < 0.001), while European patients were the least likely (OR = 2.56; 95% CI 1.58-4.13; p < 0.001). The APOA5 p.G185C polymorphism, exclusive to East Asians, was significantly enriched in patients compared with controls (OR = 10.1; 95% CI 5.6-18.3; p < 0.001), showing the highest enrichment among the measured genetic factors. CONCLUSION While TG-associated rare variants and common SNPs are both found in statistical excess in severe HTG patients of different ancestral backgrounds, the overall genetic profiles of each ancestry group were distinct.
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Affiliation(s)
- Praneet K Gill
- Department of Biochemistry, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada; Blackburn Cardiovascular Genetics Laboratory, Robarts Research Institute, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada
| | - Jacqueline S Dron
- Department of Biochemistry, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada; Blackburn Cardiovascular Genetics Laboratory, Robarts Research Institute, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada
| | - Allison A Dilliott
- Department of Biochemistry, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada; Blackburn Cardiovascular Genetics Laboratory, Robarts Research Institute, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada
| | - Adam D McIntyre
- Blackburn Cardiovascular Genetics Laboratory, Robarts Research Institute, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada
| | - Henian Cao
- Blackburn Cardiovascular Genetics Laboratory, Robarts Research Institute, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada
| | - Jian Wang
- Blackburn Cardiovascular Genetics Laboratory, Robarts Research Institute, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada
| | - Irina G Movsesyan
- Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, USA
| | - Mary J Malloy
- Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, USA
| | - Clive R Pullinger
- Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, USA
| | - John P Kane
- Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, USA
| | - Robert A Hegele
- Department of Biochemistry, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada; Blackburn Cardiovascular Genetics Laboratory, Robarts Research Institute, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada.
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12
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Cui J, Raychaudhuri S, Karlson EW, Speyer C, Malspeis S, Guan H, Sparks JA, Ni H, Liu X, Stevens E, Williams JN, Davenport EE, Knevel R, Costenbader KH. Interactions Between Genome-Wide Genetic Factors and Smoking Influencing Risk of Systemic Lupus Erythematosus. Arthritis Rheumatol 2020; 72:1863-1871. [PMID: 32969204 DOI: 10.1002/art.41414] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Accepted: 06/12/2020] [Indexed: 12/16/2022]
Abstract
OBJECTIVE To identify interactions between genetic factors and current or recent smoking in relation to risk of developing systemic lupus erythematosus (SLE). METHODS For the study, 673 patients with SLE (diagnosed according to the American College of Rheumatology 1997 updated classification criteria) were matched by age, sex, and race (first 3 genetic principal components) to 3,272 control subjects without a history of connective tissue disease. Smoking status was classified as current smoking/having recently quit smoking within 4 years before diagnosis (or matched index date for controls) versus distant past/never smoking. In total, 86 single-nucleotide polymorphisms and 10 classic HLA alleles previously associated with SLE were included in a weighted genetic risk score (wGRS), with scores dichotomized as either low or high based on the median value in control subjects (low wGRS being defined as less than or equal to the control median; high wGRS being defined as greater than the control median). Conditional logistic regression models were used to estimate both the risk of SLE and risk of anti-double-stranded DNA autoantibody-positive (dsDNA+) SLE. Additive interactions were assessed using the attributable proportion (AP) due to interaction, and multiplicative interactions were assessed using a chi-square test (with 1 degree of freedom) for the wGRS and for individual risk alleles. Separate repeated analyses were carried out among subjects of European ancestry only. RESULTS The mean ± SD age of the SLE patients at the time of diagnosis was 36.4 ± 15.3 years. Among the 673 SLE patients included, 92.3% were female and 59.3% were dsDNA+. Ethnic distributions were as follows: 75.6% of European ancestry, 4.5% of Asian ancestry, 11.7% of African ancestry, and 8.2% classified as other ancestry. A high wGRS (odds ratio [OR] 2.0, P = 1.0 × 10-51 versus low wGRS) and a status of current/recent smoking (OR 1.5, P = 0.0003 versus distant past/never smoking) were strongly associated with SLE risk, with significant additive interaction (AP 0.33, P = 0.0012), and associations with the risk of anti-dsDNA+ SLE were even stronger. No significant multiplicative interactions with the total wGRS (P = 0.58) or with the HLA-only wGRS (P = 0.06) were found. Findings were similar in analyses restricted to only subjects of European ancestry. CONCLUSION The strong additive interaction between an updated SLE genetic risk score and current/recent smoking suggests that smoking may influence specific genes in the pathogenesis of SLE.
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Affiliation(s)
- Jing Cui
- Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Soumya Raychaudhuri
- Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Elizabeth W Karlson
- Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Cameron Speyer
- Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Susan Malspeis
- Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Hongshu Guan
- Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Jeffrey A Sparks
- Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Hongru Ni
- Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Xinyi Liu
- Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Emma Stevens
- Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Jessica N Williams
- Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Emma E Davenport
- Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Rachel Knevel
- Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, and Leiden University Medical Center, Leiden, The Netherlands
| | - Karen H Costenbader
- Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
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13
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Hebbar P, Abubaker JA, Abu-Farha M, Alsmadi O, Elkum N, Alkayal F, John SE, Channanath A, Iqbal R, Pitkaniemi J, Tuomilehto J, Sladek R, Al-Mulla F, Thanaraj TA. Genome-wide landscape establishes novel association signals for metabolic traits in the Arab population. Hum Genet 2020; 140:505-528. [PMID: 32902719 PMCID: PMC7889551 DOI: 10.1007/s00439-020-02222-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Accepted: 09/01/2020] [Indexed: 02/07/2023]
Abstract
While the Arabian population has a high prevalence of metabolic disorders, it has not been included in global studies that identify genetic risk loci for metabolic traits. Determining the transferability of such largely Euro-centric established risk loci is essential to transfer the research tools/resources, and drug targets generated by global studies to a broad range of ethnic populations. Further, consideration of populations such as Arabs, that are characterized by consanguinity and a high level of inbreeding, can lead to identification of novel risk loci. We imputed published GWAS data from two Kuwaiti Arab cohorts (n = 1434 and 1298) to the 1000 Genomes Project haplotypes and performed meta-analysis for associations with 13 metabolic traits. We compared the observed association signals with those established for metabolic traits. Our study highlighted 70 variants from 9 different genes, some of which have established links to metabolic disorders. By relaxing the genome-wide significance threshold, we identified ‘novel’ risk variants from 11 genes for metabolic traits. Many novel risk variant association signals were observed at or borderline to genome-wide significance. Furthermore, 349 previously established variants from 187 genes were validated in our study. Pleiotropic effect of risk variants on multiple metabolic traits were observed. Fine-mapping illuminated rs7838666/CSMD1 rs1864163/CETP and rs112861901/[INTS10,LPL] as candidate causal variants influencing fasting plasma glucose and high-density lipoprotein levels. Computational functional analysis identified a variety of gene regulatory signals around several variants. This study enlarges the population ancestry diversity of available GWAS and elucidates new variants in an ethnic group burdened with metabolic disorders.
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Affiliation(s)
- Prashantha Hebbar
- Dasman Diabetes Institute, P.O. Box 1180, 15462, Dasman, Kuwait.,Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | | | | | | | - Naser Elkum
- Sidra Medical and Research Center, Doha, Qatar
| | - Fadi Alkayal
- Dasman Diabetes Institute, P.O. Box 1180, 15462, Dasman, Kuwait
| | - Sumi Elsa John
- Dasman Diabetes Institute, P.O. Box 1180, 15462, Dasman, Kuwait
| | | | - Rasheeba Iqbal
- Dasman Diabetes Institute, P.O. Box 1180, 15462, Dasman, Kuwait
| | - Janne Pitkaniemi
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Jaakko Tuomilehto
- Department of Public Health, University of Helsinki, Helsinki, Finland.,Department of Public Health Solutions, National Institute for Health and Welfare, Helsinki, Finland
| | - Robert Sladek
- McGill University and Genome Quebec Innovation Centre, Montreal, Canada
| | - Fahd Al-Mulla
- Dasman Diabetes Institute, P.O. Box 1180, 15462, Dasman, Kuwait.
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14
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Abstract
Canalization refers to the evolution of populations such that the number of individuals who deviate from the optimum trait, or experience disease, is minimized. In the presence of rapid cultural, environmental, or genetic change, the reverse process of decanalization may contribute to observed increases in disease prevalence. This review starts by defining relevant concepts, drawing distinctions between the canalization of populations and robustness of individuals. It then considers evidence pertaining to three continuous traits and six domains of disease. In each case, existing genetic evidence for genotype-by-environment interactions is insufficient to support a strong inference of decanalization, but we argue that the advent of genome-wide polygenic risk assessment now makes an empirical evaluation of the role of canalization in preventing disease possible. Finally, the contributions of both rare and common variants to congenital abnormality and adult onset disease are considered in light of a new kerplunk model of genetic effects.
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Affiliation(s)
- Greg Gibson
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia 30332, USA;
| | - Kristine A Lacek
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia 30332, USA;
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15
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Kho M, Smith JA, Verweij N, Shang L, Ryan KA, Zhao W, Ware EB, Gansevoort RT, Irvin MR, Lee JE, Turner ST, Sung J, van der Harst P, Arnett DK, Baylin A, Park SK, Seo YA, Kelly KM, Chang YPC, Zhou X, Lieske JC, Kardia SLR. Genome-Wide Association Meta-Analysis of Individuals of European Ancestry Identifies Suggestive Loci for Sodium Intake, Potassium Intake, and Their Ratio Measured from 24-Hour or Half-Day Urine Samples. J Nutr 2020; 150:2635-2645. [PMID: 32840624 PMCID: PMC7549298 DOI: 10.1093/jn/nxaa241] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2020] [Revised: 05/19/2020] [Accepted: 07/17/2020] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Excess sodium intake and insufficient potassium intake are risk factors for hypertension, but there is limited knowledge regarding genetic factors that influence intake. Twenty-hour or half-day urine samples provide robust estimates of sodium and potassium intake, outperforming other measures such as spot urine samples and dietary self-reporting. OBJECTIVE The aim of this study was to investigate genomic regions associated with sodium intake, potassium intake, and sodium-to-potassium ratio measured from 24-h or half-day urine samples. METHODS Using samples of European ancestry (mean age: 54.2 y; 52.3% women), we conducted a meta-analysis of genome-wide association studies in 4 cohorts with 24-h or half-day urine samples (n = 6,519), followed by gene-based analysis. Suggestive loci (P < 10-6) were examined in additional European (n = 844), African (n = 1,246), and Asian (n = 2,475) ancestry samples. RESULTS We found suggestive loci (P < 10-6) for all 3 traits, including 7 for 24-h sodium excretion, 4 for 24-h potassium excretion, and 4 for sodium-to-potassium ratio. The most significant locus was rs77958157 near cocaine- and amphetamine-regulated transcript prepropeptide (CARTPT) , a gene involved in eating behavior and appetite regulation (P = 2.3 × 10-8 with sodium-to-potassium ratio). Two suggestive loci were replicated in additional samples: for sodium excretion, rs12094702 near zinc finger SWIM-type containing 5 (ZSWIM5) was replicated in the Asian ancestry sample reaching Bonferroni-corrected significance (P = 0.007), and for potassium excretion rs34473523 near sodium leak channel (NALCN) was associated at a nominal P value with potassium excretion both in European (P = 0.043) and African (P = 0.043) ancestry cohorts. Gene-based tests identified 1 significant gene for sodium excretion, CDC42 small effector 1 (CDC42SE1), which is associated with blood pressure regulation. CONCLUSIONS We identified multiple suggestive loci for sodium and potassium intake near genes associated with eating behavior, nervous system development and function, and blood pressure regulation in individuals of European ancestry. Further research is needed to replicate these findings and to provide insight into the underlying genetic mechanisms by which these genomic regions influence sodium and potassium intake.
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Affiliation(s)
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA,Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Niek Verweij
- Department of Cardiology, Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Lulu Shang
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Kathleen A Ryan
- Department of Medicine, School of Medicine, University of Maryland Baltimore, Baltimore, MD, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Erin B Ware
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Ron T Gansevoort
- Department of Nephrology, Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Marguerite R Irvin
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Jung Eun Lee
- Department of Food and Nutrition, Seoul National University, Seoul, Republic of Korea
| | - Stephen T Turner
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA
| | - Joohon Sung
- Department of Epidemiology, School of Public Health, Seoul National University, Seoul, Republic of Korea,Institute of Environment and Health, Seoul National University, Seoul, Republic of Korea
| | - Pim van der Harst
- Department of Cardiology, Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Donna K Arnett
- College of Public Health, University of Kentucky, Lexington, KY, USA
| | - Ana Baylin
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA,Department of Nutritional Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Sung Kyun Park
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA,Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Young Ah Seo
- Department of Nutritional Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Kristen M Kelly
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Yen Pei C Chang
- Department of Medicine, School of Medicine, University of Maryland Baltimore, Baltimore, MD, USA
| | - Xiang Zhou
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - John C Lieske
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA,Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
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16
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Rio S, Mary-Huard T, Moreau L, Bauland C, Palaffre C, Madur D, Combes V, Charcosset A. Disentangling group specific QTL allele effects from genetic background epistasis using admixed individuals in GWAS: An application to maize flowering. PLoS Genet 2020; 16:e1008241. [PMID: 32130208 PMCID: PMC7075643 DOI: 10.1371/journal.pgen.1008241] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2019] [Revised: 03/16/2020] [Accepted: 01/29/2020] [Indexed: 12/21/2022] Open
Abstract
When handling a structured population in association mapping, group-specific allele effects may be observed at quantitative trait loci (QTLs) for several reasons: (i) a different linkage disequilibrium (LD) between SNPs and QTLs across groups, (ii) group-specific genetic mutations in QTL regions, and/or (iii) epistatic interactions between QTLs and other loci that have differentiated allele frequencies between groups. We present here a new genome-wide association (GWAS) approach to identify QTLs exhibiting such group-specific allele effects. We developed genetic materials including admixed progeny from different genetic groups with known genome-wide ancestries (local admixture). A dedicated statistical methodology was developed to analyze pure and admixed individuals jointly, allowing one to disentangle the factors causing the heterogeneity of allele effects across groups. This approach was applied to maize by developing an inbred "Flint-Dent" panel including admixed individuals that was evaluated for flowering time. Several associations were detected revealing a wide range of configurations of allele effects, both at known flowering QTLs (Vgt1, Vgt2 and Vgt3) and new loci. We found several QTLs whose effect depended on the group ancestry of alleles while others interacted with the genetic background. Our GWAS approach provides useful information on the stability of QTL effects across genetic groups and can be applied to a wide range of species.
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Affiliation(s)
- Simon Rio
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190, Gif-sur-Yvette, France
| | - Tristan Mary-Huard
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190, Gif-sur-Yvette, France
- MIA, INRAE, AgroParisTech, Université Paris-Saclay, 75005, Paris, France
| | - Laurence Moreau
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190, Gif-sur-Yvette, France
| | - Cyril Bauland
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190, Gif-sur-Yvette, France
| | - Carine Palaffre
- UE 0394 SMH, INRAE, 2297 Route de l’INRA, 40390, Saint-Martin-de-Hinx, France
| | - Delphine Madur
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190, Gif-sur-Yvette, France
| | - Valérie Combes
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190, Gif-sur-Yvette, France
| | - Alain Charcosset
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190, Gif-sur-Yvette, France
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17
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Lupo PJ, Mitchell LE, Jenkins MM. Genome-wide association studies of structural birth defects: A review and commentary. Birth Defects Res 2019; 111:1329-1342. [PMID: 31654503 DOI: 10.1002/bdr2.1606] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2019] [Revised: 09/21/2019] [Accepted: 10/02/2019] [Indexed: 12/14/2022]
Abstract
BACKGROUND While there is strong evidence that genetic risk factors play an important role in the etiologies of structural birth defects, compared to other diseases, there have been relatively few genome-wide association studies (GWAS) of these conditions. We reviewed the current landscape of GWAS conducted for birth defects, noting novel insights, and future directions. METHODS This article reviews the literature with regard to GWAS of structural birth defects. Key defects included in this review include oral clefts, congenital heart defects (CHDs), biliary atresia, pyloric stenosis, hypospadias, craniosynostosis, and clubfoot. Additionally, other issues related to GWAS are considered, including the assessment of polygenic risk scores and issues related to genetic ancestry, as well as utilizing genome-wide single nucleotide polymorphism array data to evaluate gene-environment interactions and Mendelian randomization. RESULTS For some birth defects, including oral clefts and CHDs, several novel susceptibility loci have been identified and replicated through GWAS, including 8q24 for oral clefts, DGKK for hypospadias, and 4p16 for CHDs. Relatively common birth defects for which there are currently no published GWAS include neural tube defects, anotia/microtia, anophthalmia/microphthalmia, gastroschisis, and omphalocele. CONCLUSIONS Overall, GWAS have been successful in identifying several novel susceptibility genes and genomic regions for structural birth defects. These findings have provided new insights into the etiologies of these phenotypes. However, GWAS have been underutilized for understanding the genetic etiologies of several birth defects.
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Affiliation(s)
- Philip J Lupo
- Department of Pediatrics, Section of Hematology-Oncology, Baylor College of Medicine, Houston, Texas
| | - Laura E Mitchell
- Department of Epidemiology, Human Genetics and Environmental Sciences, UTHealth School of Public Health, Houston, Texas
| | - Mary M Jenkins
- National Center on Birth Defects and Developmental Disabilities, Centers for Disease Control and Prevention, Atlanta, Georgia
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18
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Oliynyk RT. Future Preventive Gene Therapy of Polygenic Diseases from a Population Genetics Perspective. Int J Mol Sci 2019; 20:E5013. [PMID: 31658652 PMCID: PMC6834143 DOI: 10.3390/ijms20205013] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2019] [Revised: 10/01/2019] [Accepted: 10/08/2019] [Indexed: 12/15/2022] Open
Abstract
With the accumulation of scientific knowledge of the genetic causes of common diseases and continuous advancement of gene-editing technologies, gene therapies to prevent polygenic diseases may soon become possible. This study endeavored to assess population genetics consequences of such therapies. Computer simulations were used to evaluate the heterogeneity in causal alleles for polygenic diseases that could exist among geographically distinct populations. The results show that although heterogeneity would not be easily detectable by epidemiological studies following population admixture, even significant heterogeneity would not impede the outcomes of preventive gene therapies. Preventive gene therapies designed to correct causal alleles to a naturally-occurring neutral state of nucleotides would lower the prevalence of polygenic early- to middle-age-onset diseases in proportion to the decreased population relative risk attributable to the edited alleles. The outcome would manifest differently for late-onset diseases, for which the therapies would result in a delayed disease onset and decreased lifetime risk; however, the lifetime risk would increase again with prolonging population life expectancy, which is a likely consequence of such therapies. If the preventive heritable gene therapies were to be applied on a large scale, the decreasing frequency of risk alleles in populations would reduce the disease risk or delay the age of onset, even with a fraction of the population receiving such therapies. With ongoing population admixture, all groups would benefit over generations.
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Affiliation(s)
- Roman Teo Oliynyk
- Centre for Computational Evolution, University of Auckland, Auckland 1010, New Zealand.
- Department of Computer Science, University of Auckland, Auckland 1010, New Zealand.
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Muhamed B, Parks T, Sliwa K. Genetics of rheumatic fever and rheumatic heart disease. Nat Rev Cardiol 2019; 17:145-154. [PMID: 31519994 DOI: 10.1038/s41569-019-0258-2] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/09/2019] [Indexed: 12/13/2022]
Abstract
Rheumatic heart disease (RHD) is a complication of group A streptococcal infection that results from a complex interaction between the genetic make-up of the host, the infection itself and several other environmental factors, largely reflecting poverty. RHD is estimated to affect 33.4 million people and results in 10.5 million disability-adjusted life-years lost globally. The disease has long been considered heritable but still little is known about the host genetic factors that increase or reduce the risk of developing RHD. In the 1980s and 1990s, several reports linked the disease to the human leukocyte antigen (HLA) locus on chromosome 6, followed in the 2000s by reports implicating additional candidate regions elsewhere in the genome. Subsequently, the search for susceptibility loci has been reinvigorated by the use of genome-wide association studies (GWAS) through which millions of variants can be tested for association in thousands of individuals. Early findings implicate not only HLA, particularly the HLA-DQA1 to HLA-DQB1 region, but also the immunoglobulin heavy chain locus, including the IGHV4-61 gene segment, on chromosome 14. In this Review, we assess the emerging role of GWAS in assessing RHD, outlining both the advantages and disadvantages of this approach. We also highlight the potential use of large-scale, publicly available data and the value of international collaboration to facilitate comprehensive studies that produce findings that have implications for clinical practice.
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Affiliation(s)
- Babu Muhamed
- Hatter Institute for Cardiovascular Diseases Research in Africa, Department of Medicine, University of Cape Town, Cape Town, South Africa
| | - Tom Parks
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK.,Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Karen Sliwa
- Hatter Institute for Cardiovascular Diseases Research in Africa, Department of Medicine, University of Cape Town, Cape Town, South Africa.
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Abstract
Risk of disease is multifactorial and can be shaped by socio-economic, demographic, cultural, environmental and genetic factors. Our understanding of the genetic determinants of disease risk has greatly advanced with the advent of genome-wide association studies (GWAS), which detect associations between genetic variants and complex traits or diseases by comparing populations of cases and controls. However, much of this discovery has occurred through GWAS of individuals of European ancestry, with limited representation of other populations, including from Africa, The Americas, Asia and Oceania. Population demography, genetic drift and adaptation to environments over thousands of years have led globally to the diversification of populations. This global genomic diversity can provide new opportunities for discovery and translation into therapies, as well as a better understanding of population disease risk. Large-scale multi-ethnic and representative biobanks and population health resources provide unprecedented opportunities to understand the genetic determinants of disease on a global scale.
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Evidence for Recent Polygenic Selection on Educational Attainment and Intelligence Inferred from Gwas Hits: A Replication of Previous Findings Using Recent Data. PSYCH 2019. [DOI: 10.3390/psych1010005] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
Genetic variants identified by three large genome-wide association studies (GWAS) of educational attainment (EA) were used to test a polygenic selection model. Weighted and unweighted polygenic scores (PGS) were calculated and compared across populations using data from the 1000 Genomes (n = 26), HGDP-CEPH (n = 52) and gnomAD (n = 8) datasets. The PGS from the largest EA GWAS was highly correlated to two previously published PGSs (r = 0.96–0.97, N = 26). These factors are both highly predictive of average population IQ (r = 0.9, N = 23) and Learning index (r = 0.8, N = 22) and are robust to tests of spatial autocorrelation. Monte Carlo simulations yielded highly significant p values. In the gnomAD samples, the correlation between PGS and IQ was almost perfect (r = 0.98, N = 8), and ANOVA showed significant population differences in allele frequencies with positive effect. Socioeconomic variables slightly improved the prediction accuracy of the model (from 78–80% to 85–89%), but the PGS explained twice as much of the variance in IQ compared to socioeconomic variables. In both 1000 Genomes and gnomAD, there was a weak trend for lower GWAS significance SNPs to be less predictive of population IQ. Additionally, a subset of SNPs were found in the HGDP-CEPH sample (N = 127). The analysis of this sample yielded a positive correlation with latitude and a low negative correlation with distance from East Africa. This study provides robust results after accounting for spatial autocorrelation with Fst distances and random noise via an empirical Monte Carlo simulation using null SNPs.
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22
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Torres JB. Race, Rare Genetic Variants, and the Science of Human Difference in the Post‐Genomic Age. TRANSFORMING ANTHROPOLOGY 2019. [DOI: 10.1111/traa.12144] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Affiliation(s)
- Jada Benn Torres
- Genetic Anthropology and Biocultural Studies Laboratory Department of Anthropology Vanderbilt University Nashville TN 37235
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23
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Modeling Heterogeneity in the Genetic Architecture of Ethnically Diverse Groups Using Random Effect Interaction Models. Genetics 2019; 211:1395-1407. [PMID: 30796011 PMCID: PMC6456318 DOI: 10.1534/genetics.119.301909] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2018] [Accepted: 01/24/2019] [Indexed: 01/08/2023] Open
Abstract
In humans, most genome-wide association studies have been conducted using data from Caucasians and many of the reported findings have not replicated in other populations. This lack of replication may be due to statistical issues (small sample sizes or confounding) or perhaps more fundamentally to differences in the genetic architecture of traits between ethnically diverse subpopulations. What aspects of the genetic architecture of traits vary between subpopulations and how can this be quantified? We consider studying effect heterogeneity using Bayesian random effect interaction models. The proposed methodology can be applied using shrinkage and variable selection methods, and produces useful information about effect heterogeneity in the form of whole-genome summaries (e.g., the proportions of variance of a complex trait explained by a set of SNPs and the average correlation of effects) as well as SNP-specific attributes. Using simulations, we show that the proposed methodology yields (nearly) unbiased estimates when the sample size is not too small relative to the number of SNPs used. Subsequently, we used the methodology for the analyses of four complex human traits (standing height, high-density lipoprotein, low-density lipoprotein, and serum urate levels) in European-Americans (EAs) and African-Americans (AAs). The estimated correlations of effects between the two subpopulations were well below unity for all the traits, ranging from 0.73 to 0.50. The extent of effect heterogeneity varied between traits and SNP sets. Height showed less differences in SNP effects between AAs and EAs whereas HDL, a trait highly influenced by lifestyle, exhibited a greater extent of effect heterogeneity. For all the traits, we observed substantial variability in effect heterogeneity across SNPs, suggesting that effect heterogeneity varies between regions of the genome.
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Abstract
The cause(s) of ubiquitous cognitive differences between American self-identified racial/ethnic groups (SIREs) is uncertain. Evolutionary-genetic models posit that ancestral genetic selection pressures are the ultimate source of these differences. Conversely, sociological models posit that these differences result from racial discrimination. To examine predictions based on these models, we conducted a global admixture analysis using data from the Pediatric Imaging, Neurocognition, and Genetics Study (PING; N = 1,369 American children). Specifically, we employed a standard methodology of genetic epidemiology to determine whether genetic ancestry significantly predicts cognitive ability, independent of SIRE. In regression models using four different codings for SIRE as a covariate, we found incremental relationships between genetic ancestry and both general cognitive ability and parental socioeconomic status (SES). The relationships between global ancestry and cognitive ability were partially attenuated when parental SES was added as a predictor and when cognitive ability was the outcome. Moreover, these associations generally held when subgroups were analyzed separately. Our results are congruent with evolutionary-genetic models of group differences and with certain environmental models that mimic the predictions of evolutionary-genetic ones. Implications for research on race/ethnic differences in the Americas are discussed, as are methods for further exploring the matter.
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Abstract
The cause(s) of ubiquitous cognitive differences between American self-identified racial/ethnic groups (SIREs) is uncertain. Evolutionary-genetic models posit that ancestral genetic selection pressures are the ultimate source of these differences. Conversely, sociological models posit that these differences result from racial discrimination. To examine predictions based on these models, we conducted a global admixture analysis using data from the Pediatric Imaging, Neurocognition, and Genetics Study (PING; N = 1,369 American children). Specifically, we employed a standard methodology of genetic epidemiology to determine whether genetic ancestry significantly predicts cognitive ability, independent of SIRE. In regression models using four different codings for SIRE as a covariate, we found incremental relationships between genetic ancestry and both general cognitive ability and parental socioeconomic status (SES). The relationships between global ancestry and cognitive ability were partially attenuated when parental SES was added as a predictor and when cognitive ability was the outcome. Moreover, these associations generally held when subgroups were analyzed separately. Our results are congruent with evolutionary-genetic models of group differences and with certain environmental models that mimic the predictions of evolutionary-genetic ones. Implications for research on race/ethnic differences in the Americas are discussed, as are methods for further exploring the matter.
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Schaid DJ, Chen W, Larson NB. From genome-wide associations to candidate causal variants by statistical fine-mapping. Nat Rev Genet 2018; 19:491-504. [PMID: 29844615 PMCID: PMC6050137 DOI: 10.1038/s41576-018-0016-z] [Citation(s) in RCA: 490] [Impact Index Per Article: 81.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Advancing from statistical associations of complex traits with genetic markers to understanding the functional genetic variants that influence traits is often a complex process. Fine-mapping can select and prioritize genetic variants for further study, yet the multitude of analytical strategies and study designs makes it challenging to choose an optimal approach. We review the strengths and weaknesses of different fine-mapping approaches, emphasizing the main factors that affect performance. Topics include interpreting results from genome-wide association studies (GWAS), the role of linkage disequilibrium, statistical fine-mapping approaches, trans-ethnic studies, genomic annotation and data integration, and other analysis and design issues.
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Affiliation(s)
- Daniel J Schaid
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA.
| | - Wenan Chen
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Nicholas B Larson
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA
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27
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Bogomolov M, Heller R. Assessing replicability of findings across two studies of multiple features. Biometrika 2018. [DOI: 10.1093/biomet/asy029] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Affiliation(s)
- Marina Bogomolov
- The William Davidson Faculty of Industrial Engineering and Management, Technion–Israel Institute of Technology, Technion City, Haifa 3200003, Israel
| | - Ruth Heller
- Department of Statistics and Operations Research, Tel-Aviv University, P.O. Box 39040, Tel-Aviv 6997801, Israel
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28
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Zanetti D, Weale ME. Transethnic differences in GWAS signals: A simulation study. Ann Hum Genet 2018; 82:280-286. [PMID: 29733446 DOI: 10.1111/ahg.12251] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2017] [Revised: 01/15/2018] [Accepted: 03/14/2018] [Indexed: 02/01/2023]
Abstract
Genome-wide association studies (GWASs) have allowed researchers to identify thousands of single nucleotide polymorphisms (SNPs) and other variants associated with particular complex traits. Previous studies have reported differences in the strength and even the direction of GWAS signals across different populations. These differences could be due to a combination of (1) lack of power, (2) allele frequency differences, (3) linkage disequilibrium (LD) differences, and (4) true differences in causal variant effect sizes. To determine whether properties (1)-(3) on their own might be sufficient to explain the patterns previously noted in strong GWAS signals, we simulated case-control data of European, Asian and African ancestry, applying realistic allele frequencies and LD from 1000 Genomes data but enforcing equal causal effect sizes across populations. Much of the observed differences in strong GWAS signals could indeed be accounted for by allele frequency and LD differences, enhanced by the Euro-centric SNP bias and lower SNP coverage found in older GWAS panels. While we cannot rule out a role for true transethnic effect size differences, our results suggest that strong causal effects may be largely shared among human populations, motivating the use of transethnic data for fine-mapping.
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Affiliation(s)
- Daniela Zanetti
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, CA, USA.,Department of Animal Biology-Anthropology, University of Barcelona, Barcelona, Spain
| | - Michael E Weale
- Department of Medical & Molecular Genetics, King's College London, London, UK
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29
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Schielzeth H, Rios Villamil A, Burri R. Success and failure in replication of genotype-phenotype associations: How does replication help in understanding the genetic basis of phenotypic variation in outbred populations? Mol Ecol Resour 2018; 18:739-754. [PMID: 29575806 DOI: 10.1111/1755-0998.12780] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2017] [Revised: 03/09/2018] [Accepted: 03/09/2018] [Indexed: 12/29/2022]
Abstract
Recent developments in sequencing technologies have facilitated genomewide mapping of phenotypic variation in natural populations. Such mapping efforts face a number of challenges potentially leading to low reproducibility. However, reproducible research forms the basis of scientific progress. We here discuss the options for replication and the reasons for potential nonreproducibility. We then review the evidence for reproducible quantitative trait loci (QTL) with a focus on natural animal populations. Existing case studies of replication fall into three categories: (i) traits that have been mapped to major effect loci (including chromosomal inversion and supergenes) by independent research teams; (ii) QTL fine-mapped in discovery populations; and (iii) attempts to replicate QTL across multiple populations. Major effect loci, in particular those associated with inversions, have been successfully replicated in several cases within and across populations. Beyond such major effect variants, replication has been more successful within than across populations, suggesting that QTL discovered in natural populations may often be population-specific. This suggests that biological causes (differences in linkage patterns, allele frequencies or context-dependencies of QTL) contribute to nonreproducibility. Evidence from other fields, notably animal breeding and QTL mapping in humans, suggests that a significant fraction of QTL is indeed reproducible in direction and magnitude at least within populations. However, there is also a large number of QTL that cannot be easily reproduced. We put forward that more studies should explicitly address the causes and context-dependencies of QTL signals, in particular to disentangle linkage differences, allele frequency differences and gene-by-environment interactions as biological causes of nonreproducibility of QTL, especially between populations.
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Affiliation(s)
- Holger Schielzeth
- Population Ecology Group, Institute of Ecology and Evolution, Friedrich Schiller University, Jena, Germany
| | - Alejandro Rios Villamil
- Population Ecology Group, Institute of Ecology and Evolution, Friedrich Schiller University, Jena, Germany
| | - Reto Burri
- Population Ecology Group, Institute of Ecology and Evolution, Friedrich Schiller University, Jena, Germany
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30
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Oliveira M, Saraiva DP, Cavadas B, Fernandes V, Pedro N, Casademont I, Koeth F, Alshamali F, Harich N, Cherni L, Sierra B, Guzman MG, Sakuntabhai A, Pereira L. Population genetics-informed meta-analysis in seven genes associated with risk to dengue fever disease. INFECTION GENETICS AND EVOLUTION 2018; 62:60-72. [PMID: 29673983 DOI: 10.1016/j.meegid.2018.04.018] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2018] [Revised: 04/02/2018] [Accepted: 04/13/2018] [Indexed: 12/30/2022]
Abstract
Population genetics theory predicted that rare frequent markers would be the main contributors for heritability of complex diseases, but meta-analyses of genome-wide association studies are revealing otherwise common markers, present in all population groups, as the identified candidate genes. In this work, we applied a population-genetics informed meta-analysis to 10 markers located in seven genes said to be associated with dengue fever disease. Seven markers (in PLCE1, CD32, CD209, OAS1 and OAS3 genes) have high-frequency and the other three (in MICB and TNFA genes) have intermediate frequency. Most of these markers have high discriminatory power between population groups, but their frequencies follow the rules of genetic drift, and seem to have not been under strong selective pressure. There was a good agreement in directional consistency across trans-ethnic association signals, in East Asian and Latin American cohorts, with heterogeneity generated by randomness between studies and especially by low sample sizes. This led to confirm the following significant associations: with DF, odds ratio of 0.67 for TNFA-rs1800629-A; with DHF, 0.82 for CD32-rs1801274-G; with DSS, 0.55 for OAS3-rs2285933-G, 0.80 for PLCE1-rs2274223-G and 1.32 for MICB-rs3132468-C. The overall genetic risks confirmed sub-Saharan African populations and descendants as the best protected against the severer forms of the disease, while Southeast and Northeast Asians are the least protected ones. European and close neighbours are the best protected against dengue fever, while, again, Southeast and Northeast Asians are the least protected ones. These risk scores provide important predictive information for the largely naïve European and North American regions, as well as for Africa where misdiagnosis with other hemorrhagic diseases is of concern.
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Affiliation(s)
- Marisa Oliveira
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal; Instituto de Patologia e Imunologia Molecular da Universidade do Porto (IPATIMUP), 4200-135 Porto, Portugal; Instituto de Ciências Biomédicas Abel Salazar (ICBAS), Universidade do Porto, 4050-313 Porto, Portugal; Institut Pasteur, Functional Genetics of Infectious Diseases Unit, 75724 Paris Cedex 15, France
| | - Diana P Saraiva
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal; Instituto de Patologia e Imunologia Molecular da Universidade do Porto (IPATIMUP), 4200-135 Porto, Portugal; Institut Pasteur, Functional Genetics of Infectious Diseases Unit, 75724 Paris Cedex 15, France
| | - Bruno Cavadas
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal; Instituto de Patologia e Imunologia Molecular da Universidade do Porto (IPATIMUP), 4200-135 Porto, Portugal; Instituto de Ciências Biomédicas Abel Salazar (ICBAS), Universidade do Porto, 4050-313 Porto, Portugal
| | - Verónica Fernandes
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal; Instituto de Patologia e Imunologia Molecular da Universidade do Porto (IPATIMUP), 4200-135 Porto, Portugal
| | - Nicole Pedro
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal; Instituto de Patologia e Imunologia Molecular da Universidade do Porto (IPATIMUP), 4200-135 Porto, Portugal
| | - Isabelle Casademont
- Institut Pasteur, Functional Genetics of Infectious Diseases Unit, 75724 Paris Cedex 15, France; Pasteur Kyoto International Joint Research Unit for Integrative Vaccinomics, Kyoto, Japan
| | - Fanny Koeth
- Institut Pasteur, Functional Genetics of Infectious Diseases Unit, 75724 Paris Cedex 15, France; Pasteur Kyoto International Joint Research Unit for Integrative Vaccinomics, Kyoto, Japan
| | - Farida Alshamali
- General Department of Forensic Sciences and Criminology, Dubai Police General Headquarters, PO Box 1493, Dubai, United Arab Emirates
| | - Nourdin Harich
- Laboratoire des Sciences Anthropogénétiques et Biotechnologies, Départment de Biologie, Université Chouaïb Doukkali, El Jadida 24000, Morocco
| | - Lotfi Cherni
- Laboratory of Genetics, Immunology and Human Pathology, Faculté de Sciences de Tunis, Université de Tunis El Manar, Tunis 2092, Tunisia; Tunis and High Institute of Biotechnology, University of Monastir, 5000 Monastir, Tunisia
| | - Beatriz Sierra
- Virology Department, PAHO/WHO Collaborating Center for the Study of Dengue and its Vector, Pedro Kourí Institute of Tropical Medicine (IPK), 601 Havana, Cuba
| | - Maria G Guzman
- Virology Department, PAHO/WHO Collaborating Center for the Study of Dengue and its Vector, Pedro Kourí Institute of Tropical Medicine (IPK), 601 Havana, Cuba
| | - Anavaj Sakuntabhai
- Institut Pasteur, Functional Genetics of Infectious Diseases Unit, 75724 Paris Cedex 15, France; Pasteur Kyoto International Joint Research Unit for Integrative Vaccinomics, Kyoto, Japan; CNRS UMR2000: Génomique évolutive, modélisation et santé (GEMS), Paris, France
| | - Luisa Pereira
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal; Instituto de Patologia e Imunologia Molecular da Universidade do Porto (IPATIMUP), 4200-135 Porto, Portugal; Faculdade de Medicina da Universidade do Porto, Portugal.
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Mufarrih SH, Malik AT, Qureshi NQ, Lakdawala RH, Rabbani MU, Ali A, Noordin S. The effect of tranexamic acid in unilateral and bilateral total knee arthroplasty in the South Asian population: A retrospective cohort study. Int J Surg 2018; 52:25-29. [PMID: 29438816 DOI: 10.1016/j.ijsu.2018.02.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2017] [Revised: 01/26/2018] [Accepted: 02/04/2018] [Indexed: 11/27/2022]
Abstract
INTRODUCTION Together with evidence of higher bleeding tendencies, the vulnerability of the South-Asian population to anemia secondary to a higher prevalence of hemoglobinopathies and micronutrient deficiencies merits further exploration of the effects of tranexamic acid on this population. Additionally, limited access to self-care facilities and certain sociocultural beliefs and practices may not be conducive to a speedy recovery from surgical complications. The aim of this study is to investigate the effects of intraoperative administration of tranexamic acid during total knee arthroplasty when considering the South-Asian population. METHODOLOGY Medical record files of 355 patients who underwent total knee arthroplasty (2007-2015) were reviewed to collect data regarding patient characteristics, surgical variables and post-operative complications. Unilateral and Bilateral total knee arthroplasty were studied separately. Analysis was done using t-test, Mann-Whitney U test, chi-square and Fisher's exact square where appropriate. The threshold for significance was p < 0.05. RESULTS The study showed that for unilateral surgery, tranexamic acid caused a significant reduction in estimated blood loss (p-value=0.011), total operative time, calculated blood loss, and hemoglobin change (p-value<0.001) whereas in bilateral surgery, tranexamic acid only caused a significant reduction in calculated blood loss (p-value < 0.001) and hemoglobin change (p-value=0.001). Interestingly, in those who received tranexamic acid vs. those who did not, there was a significant increase in length of hospital stay (p<0.001) and special care unit admissions (p-value=0.033) in unilateral and bilateral surgery respectively. CONCLUSIONS Although tranexamic acid effectively reduces intraoperative blood loss, it does not have an effect on the need for post-operative blood transfusions. The increased length of stay and special care unit admissions associated with tranexamic acid use should be explored further to reveal the complete safety profile of tranexamic acid administration in the South-Asian population during total knee arthroplasty.
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Affiliation(s)
| | | | | | | | | | - Arif Ali
- Orthopedic Surgery, Aga Khan University Hospital, Pakistan
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32
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Tsui NBY, Cheng G, Chung T, Lam CWK, Yee A, Chung PKC, Kwan TK, Ko E, He D, Wong WT, Lau JYN, Lau LT, Fok M. Population-Wide Genetic Risk Prediction of Complex Diseases: A Pilot Feasibility Study in Macau Population for Precision Public Healthcare Planning. Sci Rep 2018; 8:1853. [PMID: 29382849 PMCID: PMC5789865 DOI: 10.1038/s41598-017-19017-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2017] [Accepted: 12/20/2017] [Indexed: 02/01/2023] Open
Abstract
The genetic bases of many common diseases have been identified through genome-wide association studies in the past decade. However, the application of this approach on public healthcare planning has not been well established. Using Macau with population of around 650,000 as a basis, we conducted a pilot study to evaluate the feasibility of population genomic research and its potential on public health decisions. By performing genome-wide SNP genotyping of over a thousand Macau individuals, we evaluated the population genetic risk profiles of 47 non-communicable diseases and traits, as well as two traits associated with influenza infection. We found that for most of the diseases, the genetic risks of Macau population were different from those of Caucasian, but with similar profile with mainland Chinese. We also identified a panel of diseases that Macau population may have a high or elevated genetic risks. This pilot study showed that (1) population genomic study is feasible in Asian regions like Macau; (2) Macau may have different profile of population-based genetic risks than Caucasians, (3) the different prevalence of genetic risk profile indicates the importance of Asian-specific studies for Asian populations; and (4) the results generated may have an impact for going forward healthcare planning.
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Affiliation(s)
- Nancy B Y Tsui
- Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hung Hom, Hong Kong.,Avalon Genomics (Hong Kong) Limited, Shatin, Hong Kong
| | - Gregory Cheng
- Faculty of Health Sciences, Macau University of Science and Technology, Taipa, Macau
| | - Teresa Chung
- Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hung Hom, Hong Kong
| | - Christopher W K Lam
- Faculty of Health Sciences, Macau University of Science and Technology, Taipa, Macau
| | - Anita Yee
- Avalon Genomics (Hong Kong) Limited, Shatin, Hong Kong
| | | | - Tsz-Ki Kwan
- Avalon Genomics (Hong Kong) Limited, Shatin, Hong Kong
| | - Elaine Ko
- Avalon Genomics (Hong Kong) Limited, Shatin, Hong Kong
| | - Daihai He
- Department of Applied Mathematics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong
| | - Wing-Tak Wong
- Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hung Hom, Hong Kong
| | - Johnson Y N Lau
- Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hung Hom, Hong Kong
| | - Lok Ting Lau
- Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hung Hom, Hong Kong.
| | - Manson Fok
- Faculty of Health Sciences, Macau University of Science and Technology, Taipa, Macau.
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Mägi R, Horikoshi M, Sofer T, Mahajan A, Kitajima H, Franceschini N, McCarthy MI, Morris AP. Trans-ethnic meta-regression of genome-wide association studies accounting for ancestry increases power for discovery and improves fine-mapping resolution. Hum Mol Genet 2018; 26:3639-3650. [PMID: 28911207 PMCID: PMC5755684 DOI: 10.1093/hmg/ddx280] [Citation(s) in RCA: 132] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2017] [Accepted: 07/13/2017] [Indexed: 01/08/2023] Open
Abstract
Trans-ethnic meta-analysis of genome-wide association studies (GWAS) across diverse populations can increase power to detect complex trait loci when the underlying causal variants are shared between ancestry groups. However, heterogeneity in allelic effects between GWAS at these loci can occur that is correlated with ancestry. Here, a novel approach is presented to detect SNP association and quantify the extent of heterogeneity in allelic effects that is correlated with ancestry. We employ trans-ethnic meta-regression to model allelic effects as a function of axes of genetic variation, derived from a matrix of mean pairwise allele frequency differences between GWAS, and implemented in the MR-MEGA software. Through detailed simulations, we demonstrate increased power to detect association for MR-MEGA over fixed- and random-effects meta-analysis across a range of scenarios of heterogeneity in allelic effects between ethnic groups. We also demonstrate improved fine-mapping resolution, in loci containing a single causal variant, compared to these meta-analysis approaches and PAINTOR, and equivalent performance to MANTRA at reduced computational cost. Application of MR-MEGA to trans-ethnic GWAS of kidney function in 71,461 individuals indicates stronger signals of association than fixed-effects meta-analysis when heterogeneity in allelic effects is correlated with ancestry. Application of MR-MEGA to fine-mapping four type 2 diabetes susceptibility loci in 22,086 cases and 42,539 controls highlights: (i) strong evidence for heterogeneity in allelic effects that is correlated with ancestry only at the index SNP for the association signal at the CDKAL1 locus; and (ii) 99% credible sets with six or fewer variants for five distinct association signals.
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Affiliation(s)
- Reedik Mägi
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Momoko Horikoshi
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.,Laboratory for Endocrinology, Metabolism and Kidney Diseases, RIKEN, Center for Integrative Medical Sciences, Yokohama, Japan
| | - Tamar Sofer
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Anubha Mahajan
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Hidetoshi Kitajima
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Mark I McCarthy
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.,Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.,Oxford NIHR Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, UK
| | | | - Andrew P Morris
- Estonian Genome Center, University of Tartu, Tartu, Estonia.,Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.,Department of Biostatistics.,Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK
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Wang S, Qian F, Zheng Y, Ogundiran T, Ojengbede O, Zheng W, Blot W, Nathanson KL, Hennis A, Nemesure B, Ambs S, Olopade OI, Huo D. Genetic variants demonstrating flip-flop phenomenon and breast cancer risk prediction among women of African ancestry. Breast Cancer Res Treat 2018; 168:703-712. [PMID: 29302764 DOI: 10.1007/s10549-017-4638-1] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2017] [Accepted: 12/23/2017] [Indexed: 01/19/2023]
Abstract
BACKGROUND Few studies have evaluated the performance of existing breast cancer risk prediction models among women of African ancestry. In replication studies of genetic variants, a change in direction of the risk association is a common phenomenon. Termed flip-flop, it means that a variant is risk factor in one population but protective in another, affecting the performance of risk prediction models. METHODS We used data from the genome-wide association study (GWAS) of breast cancer in the African diaspora (The Root consortium), which included 3686 participants of African ancestry from Nigeria, USA, and Barbados. Polygenic risk scores (PRSs) were constructed from the published odds ratios (ORs) of four sets of susceptibility loci for breast cancer. Discrimination capacity was measured using the area under the receiver operating characteristic curve (AUC). RESULTS Flip-flop phenomenon was observed among 30~40% of variants across studies. Using the 34 variants with consistent directionality among previous studies, we constructed a PRS with AUC of 0.531 (95% confidence interval [CI]: 0.512-0.550), which is similar to the PRS using 93 variants and ORs from European ancestry populations (AUC = 0.525, 95% CI: 0.506-0.544). Additionally, we found the 34-variant PRS has good discriminative accuracy in women with family history of breast cancer (AUC = 0.586, 95% CI: 0.532-0.640). CONCLUSIONS We found that PRS based on variants identified from prior GWASs conducted in women of European and Asian ancestries did not provide a comparable degree of risk stratification for women of African ancestry. Further large-scale fine-mapping studies in African ancestry populations are desirable to discover population-specific genetic risk variants.
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Affiliation(s)
- Shengfeng Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.,Center for Clinical Cancer Genetics & Global Health, Department of Medicine, University of Chicago, 5841 S. Maryland Ave., MC 2020, Chicago, IL, 60637, USA
| | - Frank Qian
- Department of Medicine, University of Chicago, Chicago, USA
| | - Yonglan Zheng
- Center for Clinical Cancer Genetics & Global Health, Department of Medicine, University of Chicago, 5841 S. Maryland Ave., MC 2020, Chicago, IL, 60637, USA
| | - Temidayo Ogundiran
- Department of Surgery, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Oladosu Ojengbede
- Center for Population and Reproductive Health, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, USA
| | - William Blot
- Division of Epidemiology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, USA
| | | | - Anselm Hennis
- Chronic Disease Research Centre, Tropical Medicine Research Institute, University of the West Indies, Bridgetown, Barbados
| | - Barbara Nemesure
- Department of Preventive Medicine, State University of New York, Stony Brook, USA
| | - Stefan Ambs
- Laboratory of Human Carcinogenesis, National Cancer Institute, Rockville, USA
| | - Olufunmilayo I Olopade
- Center for Clinical Cancer Genetics & Global Health, Department of Medicine, University of Chicago, 5841 S. Maryland Ave., MC 2020, Chicago, IL, 60637, USA.
| | - Dezheng Huo
- Department of Public Health Sciences, University of Chicago, 5841 S. Maryland Ave, MC 2007, Chicago, IL, 60637, USA.
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35
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Mufarrih SH, Qureshi NQ, Ali A, Malik AT, Naim H, Noordin S. Total knee Arthroplasty: risk factors for allogeneic blood transfusions in the South Asian population. BMC Musculoskelet Disord 2017; 18:359. [PMID: 28830388 PMCID: PMC5568396 DOI: 10.1186/s12891-017-1728-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2017] [Accepted: 08/16/2017] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Total knee arthroplasty (TKA) is the recommended treatment for end-stage knee osteoarthritis. Considering the various risks associated with intra and postoperative blood transfusions, better understanding is required with respect to the risk factors contributing to a greater possibility of blood transfusion during or after surgery. Although literature highlights several such factors, our study is among the first to identify these risk factors in the South Asian population which differs from other populations in several ways. METHODS The study consists of a review of 658 patients undergoing TKA from 2005 to 2015. Data was obtained from patient medical records and was analysed using logistic regression analysis. The relationship between each predictor and the outcome variable was calculated as an Odds ratio (OR), the threshold of significance for which was p = 0.25 and p = 0.05 for univariate and multivariable analysis respectively. RESULTS The mean age of the patient population was 63 years (78% female), 25% of whom received one or more blood transfusions. Multivariable analysis revealed 5 significant independent predictors for increased risk of blood transfusions including bilateral knee surgery (OR:5.51), preoperative anemia (OR:4.15), higher ASA (American Society of Anaesthesiologists) status (3-4) (OR:1.92), female sex (OR:3.44) and BMI (Body mass index) ≤30 (OR:1.79) while increasing co-morbidities and age (>60) were found to be insignificant. CONCLUSIONS The factors identified for the South Asian population are largely similar to those for other populations. Identification of high risk patients will permit the application of an international multipronged approach which not only targets the modifiable risk factors but also the decision making process and blood management protocols in order to minimize the transfusion associated risks for a patient undergoing a TKA.
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Affiliation(s)
| | | | - Arif Ali
- Aga Khan University Hospital, Karachi, Pakistan
| | | | - Huda Naim
- Dow International Medical College, Karachi, Pakistan
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36
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Palmer C, Pe’er I. Statistical correction of the Winner's Curse explains replication variability in quantitative trait genome-wide association studies. PLoS Genet 2017; 13:e1006916. [PMID: 28715421 PMCID: PMC5536394 DOI: 10.1371/journal.pgen.1006916] [Citation(s) in RCA: 73] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2017] [Revised: 07/31/2017] [Accepted: 07/10/2017] [Indexed: 12/11/2022] Open
Abstract
Genome-wide association studies (GWAS) have identified hundreds of SNPs responsible for variation in human quantitative traits. However, genome-wide-significant associations often fail to replicate across independent cohorts, in apparent inconsistency with their apparent strong effects in discovery cohorts. This limited success of replication raises pervasive questions about the utility of the GWAS field. We identify all 332 studies of quantitative traits from the NHGRI-EBI GWAS Database with attempted replication. We find that the majority of studies provide insufficient data to evaluate replication rates. The remaining papers replicate significantly worse than expected (p < 10-14), even when adjusting for regression-to-the-mean of effect size between discovery- and replication-cohorts termed the Winner's Curse (p < 10-16). We show this is due in part to misreporting replication cohort-size as a maximum number, rather than per-locus one. In 39 studies accurately reporting per-locus cohort-size for attempted replication of 707 loci in samples with similar ancestry, replication rate matched expectation (predicted 458, observed 457, p = 0.94). In contrast, ancestry differences between replication and discovery (13 studies, 385 loci) cause the most highly-powered decile of loci to replicate worse than expected, due to difference in linkage disequilibrium.
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Affiliation(s)
- Cameron Palmer
- Department of Systems Biology, Columbia University Medical Center, New York, New York, United States of America
- Department of Computer Science, Columbia University, New York, New York, United States of America
| | - Itsik Pe’er
- Department of Computer Science, Columbia University, New York, New York, United States of America
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37
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Faruque MU, Chen G, Doumatey AP, Zhou J, Huang H, Shriner D, Adeyemo AA, Rotimi CN, Dunston GM. Transferability of genome-wide associated loci for asthma in African Americans. J Asthma 2017; 54:1-8. [PMID: 27177148 PMCID: PMC5300042 DOI: 10.1080/02770903.2016.1188941] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2015] [Revised: 05/05/2016] [Accepted: 05/08/2016] [Indexed: 01/11/2023]
Abstract
OBJECTIVE Transferability of significantly associated loci or GWAS "hits" adds credibility to genotype-disease associations and provides evidence for generalizability across different ancestral populations. We sought evidence of association of known asthma-associated single nucleotide polymorphisms (SNPs) in an African American population. METHODS Subjects comprised 661 participants (261 asthma cases and 400 controls) from the Howard University Family Study. Forty-eight SNPs previously reported to be associated with asthma by GWAS were selected for testing. We adopted a combined strategy by first adopting an "exact" approach where we looked-up only the reported index SNP. For those index SNPs missing form our dataset, we used a "local" approach that examined all the regional SNPs in LD with the index SNP. RESULTS Out of the 48 SNPs, our cohort had genotype data available for 27, which were examined for exact replication. Of these, two SNPs were found positively associated with asthma. These included: rs10508372 (OR = 1.567 [95%CI, 1.133-2.167], P = 0.0066) and rs2378383 (OR = 2.147 [95%CI, 1.149-4.013], P = 0.0166), located on chromosomal bands 10p14 and 9q21.31, respectively. Local replication of the remaining 21 loci showed association at two chromosomal loci (9p24.1-rs2381413 and 6p21.32-rs3132947; Bonferroni-corrected P values: 0.0033 and 0.0197, respectively). Of note, multiple SNPs in LD with rs2381413 located upstream of IL33 were significantly associated with asthma. CONCLUSIONS This study has successfully transferred four reported asthma-associated loci in an independent African American population. Identification of several asthma-associated SNPs in the upstream of the IL33, a gene previously implicated in allergic inflammation of asthmatic airway, supports the generalizability of this finding.
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Affiliation(s)
- Mezbah U. Faruque
- National Human Genome Center, Howard University College of Medicine, Washington, DC, USA
| | - Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Ayo P. Doumatey
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jie Zhou
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Hanxia Huang
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Daniel Shriner
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Adebowale A. Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Charles N. Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Georgia M. Dunston
- National Human Genome Center, Howard University College of Medicine, Washington, DC, USA
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38
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Pharmacogenomic implications of the evolutionary history of infectious diseases in Africa. THE PHARMACOGENOMICS JOURNAL 2016; 17:112-120. [PMID: 27779243 PMCID: PMC5380847 DOI: 10.1038/tpj.2016.78] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/17/2016] [Revised: 07/06/2016] [Accepted: 07/19/2016] [Indexed: 12/20/2022]
Abstract
As the common birthplace of all human populations, modern humans have lived longer on the African continent than in any other geographical region of the world. This long history, along with the evolutionary need to adapt to environmental challenges such as exposure to infectious agents, has led to greater genetic variation in Africans. The vast genetic variation in Africans also extends to genes involved in the absorption, distribution, metabolism and excretion of pharmaceuticals. Ongoing cataloging of these clinically relevant variants reveals huge allele-frequency differences within and between African populations. Here, we examine Africa's large burden of infectious disease, discuss key examples of known genetic variation modulating disease risk, and provide examples of clinically relevant variants critical for establishing dosing guidelines. We propose that a more systematic characterization of the genetic diversity of African ancestry populations is required if the current benefits of precision medicine are to be extended to these populations.
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39
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Spector SA, Brummel SS, Nievergelt CM, Maihofer AX, Singh KK, Purswani MU, Williams PL, Hazra R, Van Dyke R, Seage GR. Genetically determined ancestry is more informative than self-reported race in HIV-infected and -exposed children. Medicine (Baltimore) 2016; 95:e4733. [PMID: 27603370 PMCID: PMC5023893 DOI: 10.1097/md.0000000000004733] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
The Pediatric HIV/AIDS Cohort Study (PHACS), the largest ongoing longitudinal study of perinatal HIV-infected (PHIV) and HIV-exposed, uninfected (PHEU) children in the United States, comprises the Surveillance Monitoring of Antiretroviral Therapy [ART] Toxicities (SMARTT) Study in PHEU children and the Adolescent Master Protocol (AMP) that includes PHIV and PHEU children ≥7 years. Although race/ethnicity is often used to assess health outcomes, this approach remains controversial and may fail to accurately reflect the backgrounds of ancestry-diverse populations as represented in the PHACS participants.In this study, we compared genetically determined ancestry (GDA) and self-reported race/ethnicity (SRR) in the PHACS cohort. GDA was estimated using a highly discriminative panel of 41 single nucleotide polymorphisms and compared to SRR. Because SRR was similar between the PHIV and PHEU, and between the AMP and SMARTT cohorts, data for all unique 1958 participants were combined.According to SRR, 63% of study participants identified as Black/African-American, 27% White, and 34% Hispanic. Using the highest percentage of ancestry/ethnicity to identify GDA, 9.5% of subjects were placed in the incorrect superpopulation based on SRR. When ≥50% or ≥75% GDA of a given superpopulation was required, 12% and 25%, respectively, of subjects were placed in the incorrect superpopulation based on SRR, and the percent of subjects classified as multiracial increased. Of 126 participants with unidentified SRR, 71% were genetically identified as Eurasian.GDA provides a more robust assessment of race/ethnicity when compared to self-report, and study participants with unidentified SRR could be assigned GDA using genetic markers. In addition, identification of continental ancestry removes the taxonomic identification of race as a variable when identifying risk for clinical outcomes.
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Affiliation(s)
- Stephen A. Spector
- University of California, San Diego, La Jolla
- Rady Children's Hospital-San Diego, San Diego, CA
- Correspondence: Stephen A. Spector, University of California, San Diego, 9500 Gilman Drive, Stein Clinical Research Building, MC 0672, La Jolla, CA 92093-0672 (e-mail: )
| | - Sean S. Brummel
- Center for Biostatistics in AIDS Research, Harvard T.H. Chan School of Public Health, Boston, MA
| | | | | | | | - Murli U. Purswani
- Albert Einstein College of Medicine, Bronx Lebanon Hospital, Bronx, New York, NY
| | - Paige L. Williams
- Center for Biostatistics in AIDS Research, Harvard T.H. Chan School of Public Health, Boston, MA
- Departments of Biostatistics
- Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Rohan Hazra
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD
| | | | - George R. Seage
- Center for Biostatistics in AIDS Research, Harvard T.H. Chan School of Public Health, Boston, MA
- Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
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40
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Kiranmayi M, Chirasani VR, Allu PKR, Subramanian L, Martelli EE, Sahu BS, Vishnuprabu D, Kumaragurubaran R, Sharma S, Bodhini D, Dixit M, Munirajan AK, Khullar M, Radha V, Mohan V, Mullasari AS, Naga Prasad SV, Senapati S, Mahapatra NR. Catestatin Gly364Ser Variant Alters Systemic Blood Pressure and the Risk for Hypertension in Human Populations via Endothelial Nitric Oxide Pathway. Hypertension 2016; 68:334-47. [PMID: 27324226 DOI: 10.1161/hypertensionaha.116.06568] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2016] [Accepted: 05/17/2016] [Indexed: 12/13/2022]
Abstract
Catestatin (CST), an endogenous antihypertensive/antiadrenergic peptide, is a novel regulator of cardiovascular physiology. Here, we report case-control studies in 2 geographically/ethnically distinct Indian populations (n≈4000) that showed association of the naturally-occurring human CST-Gly364Ser variant with increased risk for hypertension (age-adjusted odds ratios: 1.483; P=0.009 and 2.951; P=0.005). Consistently, 364Ser allele carriers displayed elevated systolic (up to ≈8 mm Hg; P=0.004) and diastolic (up to ≈6 mm Hg; P=0.001) blood pressure. The variant allele was also found to be in linkage disequilibrium with other functional single-nucleotide polymorphisms in the CHGA promoter and nearby coding region. Functional characterization of the Gly364Ser variant was performed using cellular/molecular biological experiments (viz peptide-receptor binding assays, nitric oxide [NO], phosphorylated extracellular regulated kinase, and phosphorylated endothelial NO synthase estimations) and computational approaches (molecular dynamics simulations for structural analysis of wild-type [CST-WT] and variant [CST-364Ser] peptides and docking of peptide/ligand with β-adrenergic receptors [ADRB1/2]). CST-WT and CST-364Ser peptides differed profoundly in their secondary structures and showed differential interactions with ADRB2; although CST-WT displaced the ligand bound to ADRB2, CST-364Ser failed to do the same. Furthermore, CST-WT significantly inhibited ADRB2-stimulated extracellular regulated kinase activation, suggesting an antagonistic role towards ADRB2 unlike CST-364Ser. Consequently, CST-WT was more potent in NO production in human umbilical vein endothelial cells as compared with CST-364Ser. This NO-producing ability of CST-WT was abrogated by ADRB2 antagonist ICI 118551. In conclusion, CST-364Ser allele enhanced the risk for hypertension in human populations, possibly via diminished endothelial NO production because of altered interactions of CST-364Ser peptide with ADRB2 as compared with CST-WT.
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Affiliation(s)
- Malapaka Kiranmayi
- From the Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India (M.Kiranmayi, V.R.C., P.K.R.A., L.S., B.S.S., R.K., M.D., S.Senapati, N.R.M.); Department of Molecular Cardiology, Lerner Research Institute, Cleveland Clinic, OH (E.E.M., S.V.N.P.); Department of Genetics, Dr. ALM PG Institute of Basic Medical Sciences, University of Madras, Taramani Campus, Chennai, Tamil Nadu, India (D.V., A.K.M.); Department of Experimental Medicine and Biotechnology, Postgraduate Institute of Medical Education and Research, Chandigarh, India (S.Sharma, M.Khullar); Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, Tamil Nadu, India (D.B., V.R., V.M.); Institute of Cardiovascular Diseases, Madras Medical Mission, Chennai, Tamil Nadu, India (A.S.M.); Department of Medicine, University of California San Francisco (P.K.R.A.); and Department of Clinical Biochemistry, University of Cambridge, Cambridge, United Kingdom (B.S.S.)
| | - Venkat R Chirasani
- From the Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India (M.Kiranmayi, V.R.C., P.K.R.A., L.S., B.S.S., R.K., M.D., S.Senapati, N.R.M.); Department of Molecular Cardiology, Lerner Research Institute, Cleveland Clinic, OH (E.E.M., S.V.N.P.); Department of Genetics, Dr. ALM PG Institute of Basic Medical Sciences, University of Madras, Taramani Campus, Chennai, Tamil Nadu, India (D.V., A.K.M.); Department of Experimental Medicine and Biotechnology, Postgraduate Institute of Medical Education and Research, Chandigarh, India (S.Sharma, M.Khullar); Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, Tamil Nadu, India (D.B., V.R., V.M.); Institute of Cardiovascular Diseases, Madras Medical Mission, Chennai, Tamil Nadu, India (A.S.M.); Department of Medicine, University of California San Francisco (P.K.R.A.); and Department of Clinical Biochemistry, University of Cambridge, Cambridge, United Kingdom (B.S.S.)
| | - Prasanna K R Allu
- From the Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India (M.Kiranmayi, V.R.C., P.K.R.A., L.S., B.S.S., R.K., M.D., S.Senapati, N.R.M.); Department of Molecular Cardiology, Lerner Research Institute, Cleveland Clinic, OH (E.E.M., S.V.N.P.); Department of Genetics, Dr. ALM PG Institute of Basic Medical Sciences, University of Madras, Taramani Campus, Chennai, Tamil Nadu, India (D.V., A.K.M.); Department of Experimental Medicine and Biotechnology, Postgraduate Institute of Medical Education and Research, Chandigarh, India (S.Sharma, M.Khullar); Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, Tamil Nadu, India (D.B., V.R., V.M.); Institute of Cardiovascular Diseases, Madras Medical Mission, Chennai, Tamil Nadu, India (A.S.M.); Department of Medicine, University of California San Francisco (P.K.R.A.); and Department of Clinical Biochemistry, University of Cambridge, Cambridge, United Kingdom (B.S.S.)
| | - Lakshmi Subramanian
- From the Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India (M.Kiranmayi, V.R.C., P.K.R.A., L.S., B.S.S., R.K., M.D., S.Senapati, N.R.M.); Department of Molecular Cardiology, Lerner Research Institute, Cleveland Clinic, OH (E.E.M., S.V.N.P.); Department of Genetics, Dr. ALM PG Institute of Basic Medical Sciences, University of Madras, Taramani Campus, Chennai, Tamil Nadu, India (D.V., A.K.M.); Department of Experimental Medicine and Biotechnology, Postgraduate Institute of Medical Education and Research, Chandigarh, India (S.Sharma, M.Khullar); Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, Tamil Nadu, India (D.B., V.R., V.M.); Institute of Cardiovascular Diseases, Madras Medical Mission, Chennai, Tamil Nadu, India (A.S.M.); Department of Medicine, University of California San Francisco (P.K.R.A.); and Department of Clinical Biochemistry, University of Cambridge, Cambridge, United Kingdom (B.S.S.)
| | - Elizabeth E Martelli
- From the Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India (M.Kiranmayi, V.R.C., P.K.R.A., L.S., B.S.S., R.K., M.D., S.Senapati, N.R.M.); Department of Molecular Cardiology, Lerner Research Institute, Cleveland Clinic, OH (E.E.M., S.V.N.P.); Department of Genetics, Dr. ALM PG Institute of Basic Medical Sciences, University of Madras, Taramani Campus, Chennai, Tamil Nadu, India (D.V., A.K.M.); Department of Experimental Medicine and Biotechnology, Postgraduate Institute of Medical Education and Research, Chandigarh, India (S.Sharma, M.Khullar); Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, Tamil Nadu, India (D.B., V.R., V.M.); Institute of Cardiovascular Diseases, Madras Medical Mission, Chennai, Tamil Nadu, India (A.S.M.); Department of Medicine, University of California San Francisco (P.K.R.A.); and Department of Clinical Biochemistry, University of Cambridge, Cambridge, United Kingdom (B.S.S.)
| | - Bhavani S Sahu
- From the Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India (M.Kiranmayi, V.R.C., P.K.R.A., L.S., B.S.S., R.K., M.D., S.Senapati, N.R.M.); Department of Molecular Cardiology, Lerner Research Institute, Cleveland Clinic, OH (E.E.M., S.V.N.P.); Department of Genetics, Dr. ALM PG Institute of Basic Medical Sciences, University of Madras, Taramani Campus, Chennai, Tamil Nadu, India (D.V., A.K.M.); Department of Experimental Medicine and Biotechnology, Postgraduate Institute of Medical Education and Research, Chandigarh, India (S.Sharma, M.Khullar); Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, Tamil Nadu, India (D.B., V.R., V.M.); Institute of Cardiovascular Diseases, Madras Medical Mission, Chennai, Tamil Nadu, India (A.S.M.); Department of Medicine, University of California San Francisco (P.K.R.A.); and Department of Clinical Biochemistry, University of Cambridge, Cambridge, United Kingdom (B.S.S.)
| | - Durairajpandian Vishnuprabu
- From the Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India (M.Kiranmayi, V.R.C., P.K.R.A., L.S., B.S.S., R.K., M.D., S.Senapati, N.R.M.); Department of Molecular Cardiology, Lerner Research Institute, Cleveland Clinic, OH (E.E.M., S.V.N.P.); Department of Genetics, Dr. ALM PG Institute of Basic Medical Sciences, University of Madras, Taramani Campus, Chennai, Tamil Nadu, India (D.V., A.K.M.); Department of Experimental Medicine and Biotechnology, Postgraduate Institute of Medical Education and Research, Chandigarh, India (S.Sharma, M.Khullar); Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, Tamil Nadu, India (D.B., V.R., V.M.); Institute of Cardiovascular Diseases, Madras Medical Mission, Chennai, Tamil Nadu, India (A.S.M.); Department of Medicine, University of California San Francisco (P.K.R.A.); and Department of Clinical Biochemistry, University of Cambridge, Cambridge, United Kingdom (B.S.S.)
| | - Rathnakumar Kumaragurubaran
- From the Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India (M.Kiranmayi, V.R.C., P.K.R.A., L.S., B.S.S., R.K., M.D., S.Senapati, N.R.M.); Department of Molecular Cardiology, Lerner Research Institute, Cleveland Clinic, OH (E.E.M., S.V.N.P.); Department of Genetics, Dr. ALM PG Institute of Basic Medical Sciences, University of Madras, Taramani Campus, Chennai, Tamil Nadu, India (D.V., A.K.M.); Department of Experimental Medicine and Biotechnology, Postgraduate Institute of Medical Education and Research, Chandigarh, India (S.Sharma, M.Khullar); Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, Tamil Nadu, India (D.B., V.R., V.M.); Institute of Cardiovascular Diseases, Madras Medical Mission, Chennai, Tamil Nadu, India (A.S.M.); Department of Medicine, University of California San Francisco (P.K.R.A.); and Department of Clinical Biochemistry, University of Cambridge, Cambridge, United Kingdom (B.S.S.)
| | - Saurabh Sharma
- From the Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India (M.Kiranmayi, V.R.C., P.K.R.A., L.S., B.S.S., R.K., M.D., S.Senapati, N.R.M.); Department of Molecular Cardiology, Lerner Research Institute, Cleveland Clinic, OH (E.E.M., S.V.N.P.); Department of Genetics, Dr. ALM PG Institute of Basic Medical Sciences, University of Madras, Taramani Campus, Chennai, Tamil Nadu, India (D.V., A.K.M.); Department of Experimental Medicine and Biotechnology, Postgraduate Institute of Medical Education and Research, Chandigarh, India (S.Sharma, M.Khullar); Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, Tamil Nadu, India (D.B., V.R., V.M.); Institute of Cardiovascular Diseases, Madras Medical Mission, Chennai, Tamil Nadu, India (A.S.M.); Department of Medicine, University of California San Francisco (P.K.R.A.); and Department of Clinical Biochemistry, University of Cambridge, Cambridge, United Kingdom (B.S.S.)
| | - Dhanasekaran Bodhini
- From the Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India (M.Kiranmayi, V.R.C., P.K.R.A., L.S., B.S.S., R.K., M.D., S.Senapati, N.R.M.); Department of Molecular Cardiology, Lerner Research Institute, Cleveland Clinic, OH (E.E.M., S.V.N.P.); Department of Genetics, Dr. ALM PG Institute of Basic Medical Sciences, University of Madras, Taramani Campus, Chennai, Tamil Nadu, India (D.V., A.K.M.); Department of Experimental Medicine and Biotechnology, Postgraduate Institute of Medical Education and Research, Chandigarh, India (S.Sharma, M.Khullar); Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, Tamil Nadu, India (D.B., V.R., V.M.); Institute of Cardiovascular Diseases, Madras Medical Mission, Chennai, Tamil Nadu, India (A.S.M.); Department of Medicine, University of California San Francisco (P.K.R.A.); and Department of Clinical Biochemistry, University of Cambridge, Cambridge, United Kingdom (B.S.S.)
| | - Madhulika Dixit
- From the Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India (M.Kiranmayi, V.R.C., P.K.R.A., L.S., B.S.S., R.K., M.D., S.Senapati, N.R.M.); Department of Molecular Cardiology, Lerner Research Institute, Cleveland Clinic, OH (E.E.M., S.V.N.P.); Department of Genetics, Dr. ALM PG Institute of Basic Medical Sciences, University of Madras, Taramani Campus, Chennai, Tamil Nadu, India (D.V., A.K.M.); Department of Experimental Medicine and Biotechnology, Postgraduate Institute of Medical Education and Research, Chandigarh, India (S.Sharma, M.Khullar); Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, Tamil Nadu, India (D.B., V.R., V.M.); Institute of Cardiovascular Diseases, Madras Medical Mission, Chennai, Tamil Nadu, India (A.S.M.); Department of Medicine, University of California San Francisco (P.K.R.A.); and Department of Clinical Biochemistry, University of Cambridge, Cambridge, United Kingdom (B.S.S.)
| | - Arasambattu K Munirajan
- From the Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India (M.Kiranmayi, V.R.C., P.K.R.A., L.S., B.S.S., R.K., M.D., S.Senapati, N.R.M.); Department of Molecular Cardiology, Lerner Research Institute, Cleveland Clinic, OH (E.E.M., S.V.N.P.); Department of Genetics, Dr. ALM PG Institute of Basic Medical Sciences, University of Madras, Taramani Campus, Chennai, Tamil Nadu, India (D.V., A.K.M.); Department of Experimental Medicine and Biotechnology, Postgraduate Institute of Medical Education and Research, Chandigarh, India (S.Sharma, M.Khullar); Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, Tamil Nadu, India (D.B., V.R., V.M.); Institute of Cardiovascular Diseases, Madras Medical Mission, Chennai, Tamil Nadu, India (A.S.M.); Department of Medicine, University of California San Francisco (P.K.R.A.); and Department of Clinical Biochemistry, University of Cambridge, Cambridge, United Kingdom (B.S.S.)
| | - Madhu Khullar
- From the Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India (M.Kiranmayi, V.R.C., P.K.R.A., L.S., B.S.S., R.K., M.D., S.Senapati, N.R.M.); Department of Molecular Cardiology, Lerner Research Institute, Cleveland Clinic, OH (E.E.M., S.V.N.P.); Department of Genetics, Dr. ALM PG Institute of Basic Medical Sciences, University of Madras, Taramani Campus, Chennai, Tamil Nadu, India (D.V., A.K.M.); Department of Experimental Medicine and Biotechnology, Postgraduate Institute of Medical Education and Research, Chandigarh, India (S.Sharma, M.Khullar); Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, Tamil Nadu, India (D.B., V.R., V.M.); Institute of Cardiovascular Diseases, Madras Medical Mission, Chennai, Tamil Nadu, India (A.S.M.); Department of Medicine, University of California San Francisco (P.K.R.A.); and Department of Clinical Biochemistry, University of Cambridge, Cambridge, United Kingdom (B.S.S.)
| | - Venkatesan Radha
- From the Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India (M.Kiranmayi, V.R.C., P.K.R.A., L.S., B.S.S., R.K., M.D., S.Senapati, N.R.M.); Department of Molecular Cardiology, Lerner Research Institute, Cleveland Clinic, OH (E.E.M., S.V.N.P.); Department of Genetics, Dr. ALM PG Institute of Basic Medical Sciences, University of Madras, Taramani Campus, Chennai, Tamil Nadu, India (D.V., A.K.M.); Department of Experimental Medicine and Biotechnology, Postgraduate Institute of Medical Education and Research, Chandigarh, India (S.Sharma, M.Khullar); Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, Tamil Nadu, India (D.B., V.R., V.M.); Institute of Cardiovascular Diseases, Madras Medical Mission, Chennai, Tamil Nadu, India (A.S.M.); Department of Medicine, University of California San Francisco (P.K.R.A.); and Department of Clinical Biochemistry, University of Cambridge, Cambridge, United Kingdom (B.S.S.)
| | - Viswanathan Mohan
- From the Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India (M.Kiranmayi, V.R.C., P.K.R.A., L.S., B.S.S., R.K., M.D., S.Senapati, N.R.M.); Department of Molecular Cardiology, Lerner Research Institute, Cleveland Clinic, OH (E.E.M., S.V.N.P.); Department of Genetics, Dr. ALM PG Institute of Basic Medical Sciences, University of Madras, Taramani Campus, Chennai, Tamil Nadu, India (D.V., A.K.M.); Department of Experimental Medicine and Biotechnology, Postgraduate Institute of Medical Education and Research, Chandigarh, India (S.Sharma, M.Khullar); Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, Tamil Nadu, India (D.B., V.R., V.M.); Institute of Cardiovascular Diseases, Madras Medical Mission, Chennai, Tamil Nadu, India (A.S.M.); Department of Medicine, University of California San Francisco (P.K.R.A.); and Department of Clinical Biochemistry, University of Cambridge, Cambridge, United Kingdom (B.S.S.)
| | - Ajit S Mullasari
- From the Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India (M.Kiranmayi, V.R.C., P.K.R.A., L.S., B.S.S., R.K., M.D., S.Senapati, N.R.M.); Department of Molecular Cardiology, Lerner Research Institute, Cleveland Clinic, OH (E.E.M., S.V.N.P.); Department of Genetics, Dr. ALM PG Institute of Basic Medical Sciences, University of Madras, Taramani Campus, Chennai, Tamil Nadu, India (D.V., A.K.M.); Department of Experimental Medicine and Biotechnology, Postgraduate Institute of Medical Education and Research, Chandigarh, India (S.Sharma, M.Khullar); Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, Tamil Nadu, India (D.B., V.R., V.M.); Institute of Cardiovascular Diseases, Madras Medical Mission, Chennai, Tamil Nadu, India (A.S.M.); Department of Medicine, University of California San Francisco (P.K.R.A.); and Department of Clinical Biochemistry, University of Cambridge, Cambridge, United Kingdom (B.S.S.)
| | - Sathyamangla V Naga Prasad
- From the Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India (M.Kiranmayi, V.R.C., P.K.R.A., L.S., B.S.S., R.K., M.D., S.Senapati, N.R.M.); Department of Molecular Cardiology, Lerner Research Institute, Cleveland Clinic, OH (E.E.M., S.V.N.P.); Department of Genetics, Dr. ALM PG Institute of Basic Medical Sciences, University of Madras, Taramani Campus, Chennai, Tamil Nadu, India (D.V., A.K.M.); Department of Experimental Medicine and Biotechnology, Postgraduate Institute of Medical Education and Research, Chandigarh, India (S.Sharma, M.Khullar); Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, Tamil Nadu, India (D.B., V.R., V.M.); Institute of Cardiovascular Diseases, Madras Medical Mission, Chennai, Tamil Nadu, India (A.S.M.); Department of Medicine, University of California San Francisco (P.K.R.A.); and Department of Clinical Biochemistry, University of Cambridge, Cambridge, United Kingdom (B.S.S.)
| | - Sanjib Senapati
- From the Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India (M.Kiranmayi, V.R.C., P.K.R.A., L.S., B.S.S., R.K., M.D., S.Senapati, N.R.M.); Department of Molecular Cardiology, Lerner Research Institute, Cleveland Clinic, OH (E.E.M., S.V.N.P.); Department of Genetics, Dr. ALM PG Institute of Basic Medical Sciences, University of Madras, Taramani Campus, Chennai, Tamil Nadu, India (D.V., A.K.M.); Department of Experimental Medicine and Biotechnology, Postgraduate Institute of Medical Education and Research, Chandigarh, India (S.Sharma, M.Khullar); Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, Tamil Nadu, India (D.B., V.R., V.M.); Institute of Cardiovascular Diseases, Madras Medical Mission, Chennai, Tamil Nadu, India (A.S.M.); Department of Medicine, University of California San Francisco (P.K.R.A.); and Department of Clinical Biochemistry, University of Cambridge, Cambridge, United Kingdom (B.S.S.)
| | - Nitish R Mahapatra
- From the Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India (M.Kiranmayi, V.R.C., P.K.R.A., L.S., B.S.S., R.K., M.D., S.Senapati, N.R.M.); Department of Molecular Cardiology, Lerner Research Institute, Cleveland Clinic, OH (E.E.M., S.V.N.P.); Department of Genetics, Dr. ALM PG Institute of Basic Medical Sciences, University of Madras, Taramani Campus, Chennai, Tamil Nadu, India (D.V., A.K.M.); Department of Experimental Medicine and Biotechnology, Postgraduate Institute of Medical Education and Research, Chandigarh, India (S.Sharma, M.Khullar); Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, Tamil Nadu, India (D.B., V.R., V.M.); Institute of Cardiovascular Diseases, Madras Medical Mission, Chennai, Tamil Nadu, India (A.S.M.); Department of Medicine, University of California San Francisco (P.K.R.A.); and Department of Clinical Biochemistry, University of Cambridge, Cambridge, United Kingdom (B.S.S.).
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Cook JP, Morris AP. Multi-ethnic genome-wide association study identifies novel locus for type 2 diabetes susceptibility. Eur J Hum Genet 2016; 24:1175-80. [PMID: 27189021 PMCID: PMC4947384 DOI: 10.1038/ejhg.2016.17] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2015] [Revised: 12/21/2015] [Accepted: 02/01/2016] [Indexed: 12/16/2022] Open
Abstract
Genome-wide association studies (GWAS) have traditionally been undertaken in homogeneous populations from the same ancestry group. However, with the increasing availability of GWAS in large-scale multi-ethnic cohorts, we have evaluated a framework for detecting association of genetic variants with complex traits, allowing for population structure, and developed a powerful test of heterogeneity in allelic effects between ancestry groups. We have applied the methodology to identify and characterise loci associated with susceptibility to type 2 diabetes (T2D) using GWAS data from the Resource for Genetic Epidemiology on Adult Health and Aging, a large multi-ethnic population-based cohort, created for investigating the genetic and environmental basis of age-related diseases. We identified a novel locus for T2D susceptibility at genome-wide significance (P<5 × 10−8) that maps to TOMM40-APOE, a region previously implicated in lipid metabolism and Alzheimer's disease. We have also confirmed previous reports that single-nucleotide polymorphisms at the TCF7L2 locus demonstrate the greatest extent of heterogeneity in allelic effects between ethnic groups, with the lowest risk observed in populations of East Asian ancestry.
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Affiliation(s)
- James P Cook
- Department of Biostatistics, University of Liverpool, Liverpool, UK
| | - Andrew P Morris
- Department of Biostatistics, University of Liverpool, Liverpool, UK.,Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
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Zanetti D, Via M, Carreras-Torres R, Esteban E, Chaabani H, Anaibar F, Harich N, Habbal R, Ghalim N, Moral P. Analysis of Genomic Regions Associated With Coronary Artery Disease Reveals Continent-Specific Single Nucleotide Polymorphisms in North African Populations. J Epidemiol 2016; 26:264-71. [PMID: 26780859 PMCID: PMC4848325 DOI: 10.2188/jea.je20150034] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Background In recent years, several genomic regions have been robustly associated with coronary artery disease (CAD) in different genome-wide association studies (GWASs) conducted mainly in people of European descent. These kinds of data are lacking in African populations, even though heart diseases are a major cause of premature death and disability. Methods Here, 384 single nucleotide polymorphisms (SNPs) in the top four CAD risk regions (1p13, 1q41, 9p21, and 10q11) were genotyped in 274 case-control samples from Morocco and Tunisia, with the aim of analyzing for the first time if the associations found in European populations were transferable to North Africans. Results The results indicate that, as in Europe, these four genetic regions are also important for CAD risk in North Africa. However, the individual SNPs associated with CAD in Africa are different from those identified in Europe in most cases (1p13, 1q41, and 9p21). Moreover, the seven risk variants identified in North Africans are efficient in discriminating between cases and controls in North African populations, but not in European populations. Conclusions This study indicates a disparity in markers associated to CAD susceptibility between North Africans and Europeans that may be related to population differences in the chromosomal architecture of these risk regions.
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Affiliation(s)
- Daniela Zanetti
- Department of Animal Biology-Anthropology, University of Barcelona
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43
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Shriner D. Mixed Ancestry and Disease Risk Transferability. CURRENT GENETIC MEDICINE REPORTS 2015. [DOI: 10.1007/s40142-015-0080-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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A genome-wide association study of antidepressant response in Koreans. Transl Psychiatry 2015; 5:e633. [PMID: 26348319 PMCID: PMC5068817 DOI: 10.1038/tp.2015.127] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/26/2015] [Revised: 06/20/2015] [Accepted: 07/08/2015] [Indexed: 12/11/2022] Open
Abstract
We conducted a three-stage genome-wide association study (GWAS) of response to antidepressant drugs in an ethnically homogeneous sample of Korean patients in untreated episodes of nonpsychotic unipolar depression, mostly of mature onset. Strict quality control was maintained in case selection, diagnosis, verification of adherence and outcome assessments. Analyzed cases completed 6 weeks of treatment with adequate plasma drug concentrations. The overall successful completion rate was 85.5%. Four candidate single-nucleotide polymorphisms (SNPs) on three chromosomes were identified by genome-wide search in the discovery sample of 481 patients who received one of four allowed selective serotonin reuptake inhibitor (SSRI) antidepressant drugs (Stage 1). In a focused replication study of 230 SSRI-treated patients, two of these four SNP candidates were confirmed (Stage 2). Analysis of the Stage 1 and Stage 2 samples combined (n = 711) revealed GWAS significance (P = 1.60 × 10(-8)) for these two SNP candidates, which were in perfect linkage disequilibrium. These two significant SNPs were confirmed also in a focused cross-replication study of 159 patients treated with the non-SSRI antidepressant drug mirtazapine (Stage 3). Analysis of the Stage 1, Stage 2 and Stage 3 samples combined (n = 870) also revealed GWAS significance for these two SNPs, which was sustained after controlling for gender, age, number of previous episodes, age at onset and baseline severity (P = 3.57 × 10(-8)). For each SNP, the response rate decreased (odds ratio=0.31, 95% confidence interval: 0.20-0.47) as a function of the number of minor alleles (non-response alleles). The two SNPs significantly associated with antidepressant response are rs7785360 and rs12698828 of the AUTS2 gene, located on chromosome 7 in 7q11.22. This gene has multiple known linkages to human psychological functions and neurobehavioral disorders. Rigorous replication efforts in other ethnic populations are recommended.
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Tomei S, Mamtani R, Al Ali R, Elkum N, Abdulmalik M, Ismail A, Cheema S, Rouh HA, Aigha II, Hani F, Al-Samraye S, Taher Aseel M, El Emadi N, Al Mujalli A, Abdelkerim A, Youssif S, Worschech A, El Sebakhy E, Temanni R, Khanna V, Wang E, Kizhakayil D, Al-Thani AA, Al-Thani M, Lowenfels A, Marincola FM, Sheikh J, Chouchane L. Obesity susceptibility loci in Qataris, a highly consanguineous Arabian population. J Transl Med 2015; 13:119. [PMID: 25890290 PMCID: PMC4422146 DOI: 10.1186/s12967-015-0459-3] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2015] [Accepted: 03/10/2015] [Indexed: 12/26/2022] Open
Abstract
OBJECTIVES In Qataris, a population characterized by a small size and a high rate of consanguinity, between two-thirds to three-quarters of adults are overweight or obese. We investigated the relevance of 23 obesity-related loci in the Qatari population. METHODS Eight-hundred-four individuals assessed to be third generation Qataris were included in the study and assigned to 3 groups according to their body mass index (BMI): 190 lean (BMI < 25 kg/m(2)); 131 overweight (25 kg/m(2) ≤ BMI < 30 kg/m(2)) and 483 obese (BMI ≥ 30 kg/m(2)). Genomic DNA was isolated from peripheral blood and genotyped by TaqMan. RESULTS Two loci significantly associated with obesity in Qataris: the TFAP2B variation (rs987237) (A allele versus G allele: chi-square = 10.3; P = 0.0013) and GNPDA2 variation (rs10938397) (A allele versus G allele: chi-square = 6.15; P = 0.013). The TFAP2B GG genotype negatively associated with obesity (OR = 0.21; P = 0.0031). Conversely, the GNDPA2 GG homozygous genotype associated with higher risk of obesity in subjects of age < 32 years (P = 0.0358). CONCLUSION We showed a different genetic profile associated with obesity in the Qatari population compared to Western populations. Studying the genetic background of Qataris is of primary importance as the etiology of a given disease might be population-specific.
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Affiliation(s)
- Sara Tomei
- Department of Genetic Medicine, Laboratory of Genetic Medicine & Immunology, Weill Cornell Medical College in Qatar, Al Luqta Street, Qatar Foundation, Education City, Doha, Qatar, PO 24144. .,Sidra Medical and Research Center, Research Branch, Al Nasr Tower, Al Corniche Street, Qatar Foundation, Doha, Qatar, PO 26999.
| | - Ravinder Mamtani
- Global and Public Health Department, Weill Cornell Medical College in Qatar, Doha, Qatar.
| | - Rashid Al Ali
- Sidra Medical and Research Center, Research Branch, Al Nasr Tower, Al Corniche Street, Qatar Foundation, Doha, Qatar, PO 26999.
| | - Naser Elkum
- Sidra Medical and Research Center, Research Branch, Al Nasr Tower, Al Corniche Street, Qatar Foundation, Doha, Qatar, PO 26999.
| | | | - Awatef Ismail
- Global and Public Health Department, Weill Cornell Medical College in Qatar, Doha, Qatar.
| | - Sohaila Cheema
- Global and Public Health Department, Weill Cornell Medical College in Qatar, Doha, Qatar.
| | - Hekmat A Rouh
- Global and Public Health Department, Weill Cornell Medical College in Qatar, Doha, Qatar.
| | - Idil I Aigha
- Department of Genetic Medicine, Laboratory of Genetic Medicine & Immunology, Weill Cornell Medical College in Qatar, Al Luqta Street, Qatar Foundation, Education City, Doha, Qatar, PO 24144.
| | - Fatima Hani
- Department of Genetic Medicine, Laboratory of Genetic Medicine & Immunology, Weill Cornell Medical College in Qatar, Al Luqta Street, Qatar Foundation, Education City, Doha, Qatar, PO 24144.
| | - Sura Al-Samraye
- Global and Public Health Department, Weill Cornell Medical College in Qatar, Doha, Qatar.
| | | | | | | | | | | | - Andrea Worschech
- Department of Genetic Medicine, Laboratory of Genetic Medicine & Immunology, Weill Cornell Medical College in Qatar, Al Luqta Street, Qatar Foundation, Education City, Doha, Qatar, PO 24144.
| | - Emad El Sebakhy
- Sidra Medical and Research Center, Research Branch, Al Nasr Tower, Al Corniche Street, Qatar Foundation, Doha, Qatar, PO 26999.
| | - Ramzi Temanni
- Sidra Medical and Research Center, Research Branch, Al Nasr Tower, Al Corniche Street, Qatar Foundation, Doha, Qatar, PO 26999.
| | - Vineesh Khanna
- Sidra Medical and Research Center, Research Branch, Al Nasr Tower, Al Corniche Street, Qatar Foundation, Doha, Qatar, PO 26999.
| | - Ena Wang
- Sidra Medical and Research Center, Research Branch, Al Nasr Tower, Al Corniche Street, Qatar Foundation, Doha, Qatar, PO 26999.
| | - Dhanya Kizhakayil
- Department of Genetic Medicine, Laboratory of Genetic Medicine & Immunology, Weill Cornell Medical College in Qatar, Al Luqta Street, Qatar Foundation, Education City, Doha, Qatar, PO 24144.
| | | | | | | | - Francesco M Marincola
- Sidra Medical and Research Center, Research Branch, Al Nasr Tower, Al Corniche Street, Qatar Foundation, Doha, Qatar, PO 26999.
| | - Javaid Sheikh
- Dean's Office, Weill Cornell Medical College in Qatar, Doha, Qatar.
| | - Lotfi Chouchane
- Department of Genetic Medicine, Laboratory of Genetic Medicine & Immunology, Weill Cornell Medical College in Qatar, Al Luqta Street, Qatar Foundation, Education City, Doha, Qatar, PO 24144.
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Kaufman JS, Dolman L, Rushani D, Cooper RS. The contribution of genomic research to explaining racial disparities in cardiovascular disease: a systematic review. Am J Epidemiol 2015; 181:464-72. [PMID: 25731887 DOI: 10.1093/aje/kwu319] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
After nearly a decade of genome-wide association studies, no assessment has yet been made of their contribution toward an explanation of the most prominent racial health disparities observed at the population level. We examined populations of African and European ancestry and focused on cardiovascular diseases, which are collectively the largest contributor to the racial mortality gap. We conducted a systematic search for review articles and meta-analyses published in 2007-2013 in which genetic data from both populations were available. We identified 68 articles relevant to this question; however, few reported significant associations in both racial groups, with just 3 variants meeting study-specific significance criteria. For most outcomes, there were too few estimates for quantitative summarization, but when summarization was possible, racial group did not contribute to heterogeneity. Most associations reported from genome-wide searches were small, difficult to replicate, and in no consistent direction that favored one racial group or another. Although the substantial investment in this technology might have produced clinical advances, it has thus far made little or no contribution to our understanding of population-level racial health disparities in cardiovascular disease.
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Bashinskaya VV, Kulakova OG, Kiselev IS, Baulina NM, Favorov AV, Boyko AN, Tsareva EY, Favorova OO. GWAS-identified multiple sclerosis risk loci involved in immune response: validation in Russians. J Neuroimmunol 2015; 282:85-91. [PMID: 25903733 DOI: 10.1016/j.jneuroim.2015.03.015] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2014] [Revised: 03/15/2015] [Accepted: 03/16/2015] [Indexed: 01/01/2023]
Abstract
Multiple sclerosis (MS) is a chronic neuro-inflammatory disease of complex etiology. The results of GWAS, a high-throughput method to discover genetic architecture of MS, require replication in independent ethnic groups. We performed a replication study of nine GWAS-identified SNPs in immune response in Russians. Associations of CLEC16A and IL2RA with MS were validated. Besides, we observed the associations of CLEC16A and IRF8 in women, and IL7RA and CD58 in men. With multi-locus association analysis two protective biallelic combinations: (TNFRSF1A*T+CLEC16A*A) and (TNFRSF1A*T+IRF8*A) were identified in women. Associations of CLEC16A*G/G and both biallelic combinations in women with MS survived the permutation test.
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Affiliation(s)
- V V Bashinskaya
- Pirogov Russian National Research Medical University, Ostrovitianov str. 1, 117997 Moscow, Russia; Russian Cardiology Scientific and Production Center, 3-d Cherepkovskaya str, 15A, Moscow 121552 Russia.
| | - O G Kulakova
- Pirogov Russian National Research Medical University, Ostrovitianov str. 1, 117997 Moscow, Russia; Russian Cardiology Scientific and Production Center, 3-d Cherepkovskaya str, 15A, Moscow 121552 Russia
| | - I S Kiselev
- Pirogov Russian National Research Medical University, Ostrovitianov str. 1, 117997 Moscow, Russia
| | - N M Baulina
- Pirogov Russian National Research Medical University, Ostrovitianov str. 1, 117997 Moscow, Russia
| | - A V Favorov
- Johns Hopkins School of Medicine, 550 North Broadway, Baltimore, MD 21205, USA; Vavilov Institute of General Genetics, Russian Academy of Sciences, Gubkina str. 3, 119333 Moscow, Russia
| | - A N Boyko
- Pirogov Russian National Research Medical University, Ostrovitianov str. 1, 117997 Moscow, Russia
| | - E Yu Tsareva
- Pirogov Russian National Research Medical University, Ostrovitianov str. 1, 117997 Moscow, Russia; Russian Cardiology Scientific and Production Center, 3-d Cherepkovskaya str, 15A, Moscow 121552 Russia
| | - O O Favorova
- Pirogov Russian National Research Medical University, Ostrovitianov str. 1, 117997 Moscow, Russia; Russian Cardiology Scientific and Production Center, 3-d Cherepkovskaya str, 15A, Moscow 121552 Russia
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48
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Li YR, Keating BJ. Trans-ethnic genome-wide association studies: advantages and challenges of mapping in diverse populations. Genome Med 2014; 6:91. [PMID: 25473427 PMCID: PMC4254423 DOI: 10.1186/s13073-014-0091-5] [Citation(s) in RCA: 124] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Genome-wide association studies (GWASs) are the method most often used by geneticists to interrogate the human genome, and they provide a cost-effective way to identify the genetic variants underpinning complex traits and diseases. Most initial GWASs have focused on genetically homogeneous cohorts from European populations given the limited availability of ethnic minority samples and so as to limit population stratification effects. Transethnic studies have been invaluable in explaining the heritability of common quantitative traits, such as height, and in examining the genetic architecture of complex diseases, such as type 2 diabetes. They provide an opportunity for large-scale signal replication in independent populations and for cross-population meta-analyses to boost statistical power. In addition, transethnic GWASs enable prioritization of candidate genes, fine-mapping of functional variants, and potentially identification of SNPs associated with disease risk in admixed populations, by taking advantage of natural differences in genomic linkage disequilibrium across ethnically diverse populations. Recent efforts to assess the biological function of variants identified by GWAS have highlighted the need for large-scale replication, meta-analyses and fine-mapping across worldwide populations of ethnically diverse genetic ancestries. Here, we review recent advances and new approaches that are important to consider when performing, designing or interpreting transethnic GWASs, and we highlight existing challenges, such as the limited ability to handle heterogeneity in linkage disequilibrium across populations and limitations in dissecting complex architectures, such as those found in recently admixed populations.
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Affiliation(s)
- Yun R Li
- />The Center for Applied Genomics, 1,016 Abramson Building, The Children’s Hospital of Philadelphia, Philadelphia, 19104 PA USA
- />Medical Scientist Training Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, 19104 PA USA
| | - Brendan J Keating
- />The Center for Applied Genomics, 1,016 Abramson Building, The Children’s Hospital of Philadelphia, Philadelphia, 19104 PA USA
- />Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, 19104 PA USA
- />Department of Surgery, Division of Transplantation, Perelman School of Medicine, University of Pennsylvania, Philadelphia, 19104 PA USA
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49
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Goldstein BA, Knowles JW, Salfati E, Ioannidis JPA, Assimes TL. Simple, standardized incorporation of genetic risk into non-genetic risk prediction tools for complex traits: coronary heart disease as an example. Front Genet 2014; 5:254. [PMID: 25136350 PMCID: PMC4117937 DOI: 10.3389/fgene.2014.00254] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2014] [Accepted: 07/10/2014] [Indexed: 01/09/2023] Open
Abstract
Purpose: Genetic risk assessment is becoming an important component of clinical decision-making. Genetic Risk Scores (GRSs) allow the composite assessment of genetic risk in complex traits. A technically and clinically pertinent question is how to most easily and effectively combine a GRS with an assessment of clinical risk derived from established non-genetic risk factors as well as to clearly present this information to patient and health care providers. Materials and Methods: We illustrate a means to combine a GRS with an independent assessment of clinical risk using a log-link function. We apply the method to the prediction of coronary heart disease (CHD) in the Atherosclerosis Risk in Communities (ARIC) cohort. We evaluate different constructions based on metrics of effect change, discrimination, and calibration. Results: The addition of a GRS to a clinical risk score (CRS) improves both discrimination and calibration for CHD in ARIC. Results are similar regardless of whether external vs. internal coefficients are used for the CRS, risk factor single nucleotide polymorphisms (SNPs) are included in the GRS, or subjects with diabetes at baseline are excluded. We outline how to report the construction and the performance of a GRS using our method and illustrate a means to present genetic risk information to subjects and/or their health care provider. Conclusion: The proposed method facilitates the standardized incorporation of a GRS in risk assessment.
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Affiliation(s)
- Benjamin A Goldstein
- Department of Medicine, Stanford University School of Medicine Stanford, CA, USA
| | - Joshua W Knowles
- Department of Medicine, Stanford University School of Medicine Stanford, CA, USA
| | - Elias Salfati
- Department of Medicine, Stanford University School of Medicine Stanford, CA, USA
| | - John P A Ioannidis
- Department of Medicine, Stanford University School of Medicine Stanford, CA, USA ; Department of Health Research and Policy, Stanford University School of Medicine Stanford, CA, USA ; Department of Statistics, Stanford University School of Humanities and Sciences Stanford, CA, USA
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50
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Ethnic background and genetic variation in the evaluation of cancer risk: a systematic review. PLoS One 2014; 9:e97522. [PMID: 24901479 PMCID: PMC4046957 DOI: 10.1371/journal.pone.0097522] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2013] [Accepted: 04/21/2014] [Indexed: 11/19/2022] Open
Abstract
The clinical use of genetic variation in the evaluation of cancer risk is expanding, and thus understanding how determinants of cancer susceptibility identified in one population can be applied to another is of growing importance. However there is considerable debate on the relevance of ethnic background in clinical genetics, reflecting both the significance and complexity of genetic heritage. We address this via a systematic review of reported associations with cancer risk for 82 markers in 68 studies across six different cancer types, comparing association results between ethnic groups and examining linkage disequilibrium between risk alleles and nearby genetic loci. We find that the relevance of ethnic background depends on the question. If asked whether the association of variants with disease risk is conserved across ethnic boundaries, we find that the answer is yes, the majority of markers show insignificant variability in association with cancer risk across ethnic groups. However if the question is whether a significant association between a variant and cancer risk is likely to reproduce, the answer is no, most markers do not validate in an ethnic group other than the discovery cohort's ancestry. This lack of reproducibility is not attributable to studies being inadequately populated due to low allele frequency in other ethnic groups. Instead, differences in local genomic structure between ethnic groups are associated with the strength of association with cancer risk and therefore confound interpretation of the implied physiologic association tracked by the disease allele. This suggest that a biological association for cancer risk alleles may be broadly consistent across ethnic boundaries, but reproduction of a clinical study in another ethnic group is uncommon, in part due to confounding genomic architecture. As clinical studies are increasingly performed globally this has important implications for how cancer risk stratifiers should be studied and employed.
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