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Yang Z, Hu L, Zhen J, Gu Y, Liu Y, Huang S, Wei Y, Zheng H, Guo X, Chen GB, Yang Y, Xiong L, Wei F, Liu S. Genetic basis of pregnancy-associated decreased platelet counts and gestational thrombocytopenia. Blood 2024; 143:1528-1538. [PMID: 38064665 PMCID: PMC11033587 DOI: 10.1182/blood.2023021925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 12/01/2023] [Accepted: 12/01/2023] [Indexed: 02/29/2024] Open
Abstract
ABSTRACT Platelet count reduction occurs throughout pregnancy, with 5% to 12% of pregnant women being diagnosed with gestational thrombocytopenia (GT), characterized by a more marked decrease in platelet count during pregnancy. However, the underlying biological mechanism behind these phenomena remains unclear. Here, we used sequencing data from noninvasive prenatal testing of 100 186 Chinese pregnant individuals and conducted, to our knowledge, the hitherto largest-scale genome-wide association studies on platelet counts during 5 periods of pregnancy (the first, second, and third trimesters, delivery, and the postpartum period) as well as 2 GT statuses (GT platelet count < 150 × 109/L and severe GT platelet count < 100 × 109/L). Our analysis revealed 138 genome-wide significant loci, explaining 10.4% to 12.1% of the observed variation. Interestingly, we identified previously unknown changes in genetic effects on platelet counts during pregnancy for variants present in PEAR1 and CBL, with PEAR1 variants specifically associated with a faster decline in platelet counts. Furthermore, we found that variants present in PEAR1 and TUBB1 increased susceptibility to GT and severe GT. Our study provides insight into the genetic basis of platelet counts and GT in pregnancy, highlighting the critical role of PEAR1 in decreasing platelet counts during pregnancy and the occurrence of GT. Those with pregnancies carrying specific variants associated with declining platelet counts may experience a more pronounced decrease, thereby elevating the risk of GT. These findings lay the groundwork for further investigation into the biological mechanisms and causal implications of GT.
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Affiliation(s)
- Zijing Yang
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
- The Genetics Laboratory, Longgang District Maternity and Child Healthcare Hospital of Shenzhen City, Shenzhen, Guangdong, China
| | - Liang Hu
- The Genetics Laboratory, Longgang District Maternity and Child Healthcare Hospital of Shenzhen City, Shenzhen, Guangdong, China
| | - Jianxin Zhen
- Central Laboratory, Shenzhen Baoan Women's and Children's Hospital, Shenzhen, Guangdong, China
| | - Yuqin Gu
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Yanhong Liu
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Shang Huang
- The Genetics Laboratory, Longgang District Maternity and Child Healthcare Hospital of Shenzhen City, Shenzhen, Guangdong, China
- Shenzhen Children's Hospital of China Medical University, Shenzhen, Guangdong, China
| | - Yuandan Wei
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
- Central Laboratory, Shenzhen Baoan Women's and Children's Hospital, Shenzhen, Guangdong, China
| | - Hao Zheng
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Xinxin Guo
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Guo-Bo Chen
- Department of Genetic and Genomic Medicine, Center for Productive Medicine, Clinical Research Institute, Zhejiang Provincial People’s Hospital, People’s Hospital of Hangzhou Medical College, Hangzhou, Zhejiang, China
- Key Laboratory of Endocrine Gland Diseases of Zhejiang Province, Hangzhou, Zhejiang, China
| | - Yan Yang
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Likuan Xiong
- Central Laboratory, Shenzhen Baoan Women's and Children's Hospital, Shenzhen, Guangdong, China
- Shenzhen Key Laboratory of Birth Defects Research, Shenzhen, Guangdong, China
| | - Fengxiang Wei
- The Genetics Laboratory, Longgang District Maternity and Child Healthcare Hospital of Shenzhen City, Shenzhen, Guangdong, China
- Longgang Maternity and Child Institute of Shantou University Medical College, Shenzhen, Guangdong, China
| | - Siyang Liu
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
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Ludhiadch A, Sulena, Singh S, Chakraborty S, Sharma D, Kulharia M, Singh P, Munshi A. Genomic Variation Affecting MPV and PLT Count in Association with Development of Ischemic Stroke and Its Subtypes. Mol Neurobiol 2023; 60:6424-6440. [PMID: 37453995 DOI: 10.1007/s12035-023-03460-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 06/22/2023] [Indexed: 07/18/2023]
Abstract
Platelets play a significant role in the pathophysiology of ischemic stroke since they are involved in the formation of intravascular thrombus after erosion or rupture of the atherosclerotic plaques. Platelet (PLT) count and mean platelet volume (MPV) are the two significant parameters that affect the functions of platelets. In the current study, MPV and PLT count was evaluated using flow cytometry and a cell counter. SonoClot analysis was carried out to evaluate activated clot timing (ACT), clot rate (CR), and platelet function (PF). Genotyping was carried out using GSA and Sanger sequencing, and expression analysis was performed using RT-PCR. In silico analysis was carried out using the GROMACS tool and UNAFold. The interaction of significant proteins with other proteins was predicted using the STRING database. Ninety-six genes were analyzed, and a significant association of THPO (rs6141) and ARHGEF3 (rs1354034) was observed with the disease and its subtypes. Altered genotypes were associated significantly with increased MPV, decreased PLT count, and CR. Expression analysis revealed a higher expression in patients bearing the variant genotypes of both genes. In silico analysis revealed that mutation in the THPO gene leads to the reduced compactness of protein structure. mRNA encoded by mutated ARHGEF3 gene increases the half-life of mRNA. The two significant proteins interact with many other proteins, especially the ones involved in platelet activation, aggregation, erythropoiesis, megakaryocyte maturation, and cytoskeleton rearrangements, suggesting that they could be important players in the determination of MPV values. In conclusion, the current study demonstrated the role of higher MPV affected by genetic variation in the development of IS and its subtypes. The results of the current study also indicate that higher MPV can be used as a biomarker for the disease and altered genotypes, and higher MPV can be targeted for better therapeutic outcomes.
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Affiliation(s)
- Abhilash Ludhiadch
- Complex Disease Genomics and Precision Medicine Laboratory, Department of Human Genetics and Molecular Medicine, Central University of Punjab, Ghudda, Bathinda, Punjab, 151401, India
| | - Sulena
- Department of Neurology, Guru Gobind Singh Medical College and Hospital, Sadiq Road, Faridkot, Punjab, 151203, India
| | | | - Sudip Chakraborty
- Department of Computational Sciences, School of Basic and Applied Sciences, Central University of Punjab, Ghudda, Bathinda, Punjab, 151401, India
| | - Dixit Sharma
- Department of Animal Sciences, School of Life Sciences, Central University of Himachal Pradesh, Kangra, Himachal Pradesh, 176206, India
| | - Mahesh Kulharia
- Centre for Computational Biology and Bioinformatics, School of Life Sciences, Central University of Himachal Pradesh, Kangra, Himachal Pradesh, 176206, India
| | - Paramdeep Singh
- Department of Radiodiagnosis, All India Institute of Medical Sciences, Bathinda, Punjab, 151001, India
| | - Anjana Munshi
- Complex Disease Genomics and Precision Medicine Laboratory, Department of Human Genetics and Molecular Medicine, Central University of Punjab, Ghudda, Bathinda, Punjab, 151401, India.
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Burley K, Fitzgibbon L, van Heel D, Vuckovic D, Mumford AD. PIK3R3 is a candidate regulator of platelet count in people of Bangladeshi ancestry. Res Pract Thromb Haemost 2023; 7:100175. [PMID: 37538507 PMCID: PMC10394561 DOI: 10.1016/j.rpth.2023.100175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Revised: 04/27/2023] [Accepted: 05/05/2023] [Indexed: 08/05/2023] Open
Abstract
Background Blood platelets are mediators of atherothrombotic disease and are regulated by complex sets of genes. Association studies in European ancestry populations have already detected informative platelet regulatory loci. Studies in other ancestries can potentially reveal new associations because of different allele frequencies, linkage structures, and variant effects. Objectives To reveal new regulatory genes for platelet count (PLT). Methods Genome-wide association studies (GWAS) were performed in 20,218 Bangladeshi and 9198 Pakistani individuals from the Genes & Health study. Loci significantly associated with PLT underwent fine-mapping to identify candidate genes. Results Of 1588 significantly associated variants (P < 5 × 10-8) at 20 loci in the Bangladeshi analysis, most replicated findings in prior transancestry GWAS and in the Pakistani analysis. However, the Bangladeshi locus defined by rs946528 (chr1:46019890) did not associate with PLT in the Pakistani analysis but was in the same linkage disequilibrium block (r2 ≥ 0.5) as PLT-associated variants in prior East Asian GWAS. The single independent association signal was refined to a 95% credible set of 343 variants spanning 8 coding genes. Functional annotation, mapping to megakaryocyte regulatory regions, and colocalization with blood expression quantitative trait loci identified the likely mediator of the PLT phenotype to be PIK3R3 encoding a regulator of phosphoinositol 3-kinase (PI3K). Conclusion Abnormal PI3K activity in the vessel wall is already implicated in the pathogenesis of atherothrombosis. Our identification of a new association between PIK3R3 and PLT provides further mechanistic insights into the contribution of the PI3K pathway to platelet biology.
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Affiliation(s)
- Kate Burley
- School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, UK
| | - Lucy Fitzgibbon
- School of Cellular and Molecular Medicine, University of Bristol, Bristol, UK
| | - David van Heel
- Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | | | - Dragana Vuckovic
- Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, London, UK
| | - Andrew D. Mumford
- School of Cellular and Molecular Medicine, University of Bristol, Bristol, UK
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Browning SR, Waples RK, Browning BL. Fast, accurate local ancestry inference with FLARE. Am J Hum Genet 2023; 110:326-335. [PMID: 36610402 PMCID: PMC9943733 DOI: 10.1016/j.ajhg.2022.12.010] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Accepted: 12/13/2022] [Indexed: 01/09/2023] Open
Abstract
Local ancestry is the source ancestry at each point in the genome of an admixed individual. Inferred local ancestry is used for admixture mapping and population genetic analyses. We present FLARE (fast local ancestry estimation), a method for local ancestry inference. FLARE achieves high accuracy through the use of an extended Li and Stephens model, and it achieves exceptional computational performance through incorporation of computational techniques developed for genotype imputation. Memory requirements are reduced through on-the-fly compression of reference haplotypes and stored checkpoints. Computation time is reduced through the use of composite reference haplotypes. These techniques allow FLARE to scale to datasets with hundreds of thousands of sequenced individuals and to provide superior accuracy on large-scale data. FLARE is open source and available at https://github.com/browning-lab/flare.
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Affiliation(s)
- Sharon R Browning
- Department of Biostatistics, University of Washington, Seattle, WA, USA.
| | - Ryan K Waples
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Brian L Browning
- Department of Biostatistics, University of Washington, Seattle, WA, USA; Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA, USA.
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Genetic Polymorphisms Associated with Prothrombin Time and Activated Partial Thromboplastin Time in Chinese Healthy Population. Genes (Basel) 2022; 13:genes13101867. [PMID: 36292752 PMCID: PMC9602091 DOI: 10.3390/genes13101867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 09/30/2022] [Accepted: 10/12/2022] [Indexed: 11/04/2022] Open
Abstract
(1) Background: The purpose of this study was to evaluate the effect of gene polymorphisms on prothrombin time (PT) and activated partial thromboplastin time (APTT) in a healthy Chinese population. (2) Methods: A total of 403 healthy volunteers from a series of novel oral anticoagulants (NOACs) bioequivalence trials in China were included. Coagulation tests for PT and APTT were performed in the central lab at Peking University First Hospital. Whole-exome sequencing (WES) and genome-wide association analysis were performed. (3) Results: In the correlation analysis of PT, 105 SNPs from 84 genes reached the genome-wide significance threshold (p < 1 × 10−5). Zinc Finger Protein 594 (ZNF594) rs184838268 (p = 4.50 × 10−19) was most significantly related to PT, and Actinin Alpha 1 (ACTN1) was found to interact most with other candidate genes. Significant associations with previously reported candidate genes Aurora Kinase B (AURKB), Complement C5(C5), Clock Circadian Regulator (CLOCK), and Histone Deacetylase 9(HDAC9) were detected in our dataset (p < 1 × 10−5). PiggyBac Transposable Element Derived 2(PGBD2) rs75935520 (p = 4.49 × 10−6), Bromodomain Adjacent To Zinc Finger Domain 2A(BAZ2A) rs199970765 (p = 5.69 × 10−6) and Protogenin (PRTG) rs80064850 (p = 8.69 × 10−6) were significantly correlated with APTT (p < 1 × 10−5). The heritability values of PT and APTT were 0.83 and 0.64, respectively; (4) Conclusion: The PT and APTT of healthy populations are affected by genetic polymorphisms. ZNF594 and ACTN1 variants could be novel genetic markers of PT, while PRTG polymorphisms might be associated with APTT levels. The findings could be attributed to ethnic differences, and need further investigation.
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Genetic pleiotropy underpinning adiposity and inflammation in self-identified Hispanic/Latino populations. BMC Med Genomics 2022; 15:192. [PMID: 36088317 PMCID: PMC9464371 DOI: 10.1186/s12920-022-01352-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2022] [Accepted: 09/02/2022] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND Concurrent variation in adiposity and inflammation suggests potential shared functional pathways and pleiotropic disease underpinning. Yet, exploration of pleiotropy in the context of adiposity-inflammation has been scarce, and none has included self-identified Hispanic/Latino populations. Given the high level of ancestral diversity in Hispanic American population, genetic studies may reveal variants that are infrequent/monomorphic in more homogeneous populations. METHODS Using multi-trait Adaptive Sum of Powered Score (aSPU) method, we examined individual and shared genetic effects underlying inflammatory (CRP) and adiposity-related traits (Body Mass Index [BMI]), and central adiposity (Waist to Hip Ratio [WHR]) in HLA participating in the Population Architecture Using Genomics and Epidemiology (PAGE) cohort (N = 35,871) with replication of effects in the Cameron County Hispanic Cohort (CCHC) which consists of Mexican American individuals. RESULTS Of the > 16 million SNPs tested, variants representing 7 independent loci were found to illustrate significant association with multiple traits. Two out of 7 variants were replicated at statistically significant level in multi-trait analyses in CCHC. The lead variant on APOE (rs439401) and rs11208712 were found to harbor multi-trait associations with adiposity and inflammation. CONCLUSIONS Results from this study demonstrate the importance of considering pleiotropy for improving our understanding of the etiology of the various metabolic pathways that regulate cardiovascular disease development.
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Granot-Hershkovitz E, Sun Q, Argos M, Zhou H, Lin X, Browning SR, Sofer T. AFA: Ancestry-specific allele frequency estimation in admixed populations: The Hispanic Community Health Study/Study of Latinos. HGG ADVANCES 2022; 3:100096. [PMID: 35300209 PMCID: PMC8920934 DOI: 10.1016/j.xhgg.2022.100096] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Accepted: 02/18/2022] [Indexed: 11/22/2022] Open
Abstract
Allele frequency estimates in admixed populations, such as Hispanics and Latinos, rely on the sample's specific admixture composition and thus may differ between two seemingly similar populations. However, ancestry-specific allele frequencies, i.e., pertaining to the ancestral populations of an admixed group, may be particularly useful for prioritizing genetic variants for genetic discovery and personalized genomic health. We developed a method, ancestry-specific allele frequency estimation in admixed populations (AFA), to estimate the frequencies of biallelic variants in admixed populations with an unlimited number of ancestries. AFA uses maximum-likelihood estimation by modeling the conditional probability of having an allele given proportions of genetic ancestries. It can be applied using either local ancestry interval proportions encompassing the variant (local-ancestry-specific allele frequency estimations in admixed populations [LAFAs]) or global proportions of genetic ancestries (global-ancestry-specific allele frequency estimations in admixed populations [GAFAs]), which are easier to compute and are more widely available. Simulations and comparisons to existing software demonstrated the high accuracy of the method. We implemented AFA on high-quality imputed data of ∼9,000 Hispanics and Latinos from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), an understudied, admixed population with three predominant continental ancestries: Amerindian, European, and African. Comparison of the European and African estimated frequencies to the respective gnomAD frequencies demonstrated high correlations (Pearson R2 = 0.97-0.99). We provide a genome-wide dataset of the estimated ancestry-specific allele frequencies for available variants with allele frequency between 5% and 95% in at least one of the three ancestral populations. Association analysis of Amerindian-enriched variants with cardiometabolic traits identified five loci associated with lipid traits in Hispanics and Latinos, demonstrating the utility of ancestry-specific allele frequencies in admixed populations.
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Affiliation(s)
- Einat Granot-Hershkovitz
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA 02115, USA,Department of Medicine, Harvard Medical School, Boston, MA 02115, USA,Corresponding author
| | - Quan Sun
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Maria Argos
- School of Public Health, The University of Illinois, Chicago, Chicago, IL 60612, USA
| | - Hufeng Zhou
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Xihong Lin
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Sharon R. Browning
- Department of Biostatistics, University of Washington, Seattle, WA 98105, USA
| | - Tamar Sofer
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA 02115, USA,Department of Medicine, Harvard Medical School, Boston, MA 02115, USA,Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA,Corresponding author
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8
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Little A, Hu Y, Sun Q, Jain D, Broome J, Chen MH, Thibord F, McHugh C, Surendran P, Blackwell TW, Brody JA, Bhan A, Chami N, de Vries PS, Ekunwe L, Heard-Costa N, Hobbs BD, Manichaikul A, Moon JY, Preuss MH, Ryan K, Wang Z, Wheeler M, Yanek LR, Abecasis GR, Almasy L, Beaty TH, Becker LC, Blangero J, Boerwinkle E, Butterworth AS, Choquet H, Correa A, Curran JE, Faraday N, Fornage M, Glahn DC, Hou L, Jorgenson E, Kooperberg C, Lewis JP, Lloyd-Jones DM, Loos RJF, Min YI, Mitchell BD, Morrison AC, Nickerson DA, North KE, O'Connell JR, Pankratz N, Psaty BM, Vasan RS, Rich SS, Rotter JI, Smith AV, Smith NL, Tang H, Tracy RP, Conomos MP, Laurie CA, Mathias RA, Li Y, Auer PL, Thornton T, Reiner AP, Johnson AD, Raffield LM. Whole genome sequence analysis of platelet traits in the NHLBI Trans-Omics for Precision Medicine (TOPMed) initiative. Hum Mol Genet 2022; 31:347-361. [PMID: 34553764 PMCID: PMC8825339 DOI: 10.1093/hmg/ddab252] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 08/23/2021] [Accepted: 08/24/2021] [Indexed: 12/15/2022] Open
Abstract
Platelets play a key role in thrombosis and hemostasis. Platelet count (PLT) and mean platelet volume (MPV) are highly heritable quantitative traits, with hundreds of genetic signals previously identified, mostly in European ancestry populations. We here utilize whole genome sequencing (WGS) from NHLBI's Trans-Omics for Precision Medicine initiative (TOPMed) in a large multi-ethnic sample to further explore common and rare variation contributing to PLT (n = 61 200) and MPV (n = 23 485). We identified and replicated secondary signals at MPL (rs532784633) and PECAM1 (rs73345162), both more common in African ancestry populations. We also observed rare variation in Mendelian platelet-related disorder genes influencing variation in platelet traits in TOPMed cohorts (not enriched for blood disorders). For example, association of GP9 with lower PLT and higher MPV was partly driven by a pathogenic Bernard-Soulier syndrome variant (rs5030764, p.Asn61Ser), and the signals at TUBB1 and CD36 were partly driven by loss of function variants not annotated as pathogenic in ClinVar (rs199948010 and rs571975065). However, residual signal remained for these gene-based signals after adjusting for lead variants, suggesting that additional variants in Mendelian genes with impacts in general population cohorts remain to be identified. Gene-based signals were also identified at several genome-wide association study identified loci for genes not annotated for Mendelian platelet disorders (PTPRH, TET2, CHEK2), with somatic variation driving the result at TET2. These results highlight the value of WGS in populations of diverse genetic ancestry to identify novel regulatory and coding signals, even for well-studied traits like platelet traits.
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Affiliation(s)
- Amarise Little
- Department of Biostatistics, University of Washington, Seattle, WA 98105, USA
| | - Yao Hu
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Quan Sun
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Deepti Jain
- Department of Biostatistics, University of Washington, Seattle, WA 98105, USA
| | - Jai Broome
- Department of Biostatistics, University of Washington, Seattle, WA 98105, USA
| | - Ming-Huei Chen
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Bethesda, MD 20892, USA
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA 01702, USA
| | - Florian Thibord
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Bethesda, MD 20892, USA
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA 01702, USA
| | - Caitlin McHugh
- Department of Biostatistics, University of Washington, Seattle, WA 98105, USA
| | - Praveen Surendran
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge CB1 8RN, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge CB1 8RN, UK
- Rutherford Fund Fellow, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - Thomas W Blackwell
- TOPMed Informatics Research Center, University of Michigan, Department of Biostatistics, Ann Arbor, MI 48109, USA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 98101, USA
| | | | - Nathalie Chami
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, USA
| | - Paul S de Vries
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, Human Genetics Center, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Lynette Ekunwe
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Nancy Heard-Costa
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA 01702, USA
| | - Brian D Hobbs
- Channing Division of Network Medicine and Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Ani Manichaikul
- Department of Public Health Sciences, Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
| | - Jee-Young Moon
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Michael H Preuss
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, USA
| | - Kathleen Ryan
- Department of Medicine, Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Zhe Wang
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, USA
| | - Marsha Wheeler
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Lisa R Yanek
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Goncalo R Abecasis
- TOPMed Informatics Research Center, University of Michigan, Department of Biostatistics, Ann Arbor, MI 48109, USA
| | - Laura Almasy
- Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | | | - Lewis C Becker
- Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville, TX 78520, USA
| | - Eric Boerwinkle
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, Human Genetics Center, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Adam S Butterworth
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge CB1 8RN, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge CB1 8RN, UK
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge CB1 8RN, UK
- National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge CB1 8RN, UK
| | - Hélène Choquet
- Division of Research, Kaiser Permanente Northern California, Oakland, CA 94612, USA
| | - Adolfo Correa
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Joanne E Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville, TX 78520, USA
| | - Nauder Faraday
- Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Myriam Fornage
- University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - David C Glahn
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Eric Jorgenson
- Division of Research, Kaiser Permanente Northern California, Oakland, CA 94612, USA
| | - Charles Kooperberg
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Joshua P Lewis
- Department of Medicine, Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Donald M Lloyd-Jones
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, USA
| | - Yuan-I Min
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Braxton D Mitchell
- Department of Medicine, Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Alanna C Morrison
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, Human Genetics Center, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Deborah A Nickerson
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Kari E North
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Jeffrey R O'Connell
- Department of Medicine, Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Nathan Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN 55455, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 98101, USA
- Department of Epidemiology, University of Washington, Seattle, WA 98195, USA
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle WA 98101, USA
| | - Ramachandran S Vasan
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA 01702, USA
- Departments of Cardiology and Preventive Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA 02118, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA 02118, USA
| | - Stephen S Rich
- Department of Public Health Sciences, Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
| | - Jerome I Rotter
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Albert V Smith
- TOPMed Informatics Research Center, University of Michigan, Department of Biostatistics, Ann Arbor, MI 48109, USA
| | - Nicholas L Smith
- Department of Epidemiology, University of Washington, Seattle, WA 98195, USA
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle WA 98101, USA
- Department of Veterans Affairs Office of Research and Development, Seattle Epidemiologic Research and Information Center, Seattle, WA 98108, USA
| | - Hua Tang
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Russell P Tracy
- Department of Pathology and Laboratory Medicine and Biochemistry, University of Vermont Larner College of Medicine, Colchester, VT 05446, USA
| | - Matthew P Conomos
- Department of Biostatistics, University of Washington, Seattle, WA 98105, USA
| | - Cecelia A Laurie
- Department of Biostatistics, University of Washington, Seattle, WA 98105, USA
| | - Rasika A Mathias
- Division of Allergy and Clinical Immunology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Yun Li
- Departments of Biostatistics, Genetics, Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Paul L Auer
- Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI 53201, USA
| | | | - Timothy Thornton
- Department of Biostatistics, University of Washington, Seattle, WA 98105, USA
| | - Alexander P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA 98195, USA
| | - Andrew D Johnson
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Bethesda, MD 20892, USA
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA 01702, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
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9
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Horimoto AR, Xue D, Cai J, Lash JP, Daviglus ML, Franceschini N, Thornton TA. Genome-Wide Admixture Mapping of Estimated Glomerular Filtration Rate and Chronic Kidney Disease Identifies European and African Ancestry-of-Origin Loci in Hispanic and Latino Individuals in the United States. J Am Soc Nephrol 2022; 33:77-87. [PMID: 34670813 PMCID: PMC8763178 DOI: 10.1681/asn.2021050617] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Accepted: 09/08/2021] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND Admixture mapping is a powerful approach for gene mapping of complex traits that leverages the diverse genetic ancestry in populations with recent admixture, such as Hispanic or Latino individuals in the United States. These individuals have an increased risk of CKD. METHODS We performed genome-wide admixture mapping for both CKD and eGFR in a sample of 12,601 participants from the Hispanic Community Health Study/Study of Latinos, with validation in a sample of 8191 Black participants from the Women's Health Initiative (WHI). We also compared the findings with those from a conventional genome-wide association study. RESULTS Three novel ancestry-of-origin loci were identified on chromosomes 2, 14, and 15 for CKD and eGFR. The chromosome 2 locus comprises two European ancestry regions encompassing the FSHR and NRXN1 genes, with European ancestry at this locus associated with increased CKD risk. The chromosome 14 locus, found within the DLK1-DIO3 imprinted domain, was associated with lower eGFR and driven by European ancestry. The eGFR-associated locus on chromosome 15 included intronic variants of RYR3 and was within an African-specific genomic region associated with higher eGFR. The genome-wide association study failed to identify significant associations in these regions. We validated the chromosome 14 and 15 loci associated with eGFR in the WHI Black participants. CONCLUSIONS This study provides evidence of shared ancestry-specific genomic regions influencing eGFR in Hispanic or Latino individuals and Black individuals and illustrates the potential for leveraging genetic ancestry in recently admixed populations for the discovery of novel candidate loci for kidney phenotypes.
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Affiliation(s)
| | - Diane Xue
- Institute for Public Health Genetics, University of Washington, Seattle, Washington
| | - Jianwen Cai
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina
| | - James P. Lash
- Department of Medicine, University of Illinois at Chicago, Chicago, Illinois
| | - Martha L. Daviglus
- Institute for Minority Health Research, University of Illinois at Chicago, Chicago, Illinois
| | - Nora Franceschini
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina
| | - Timothy A. Thornton
- Department of Biostatistics, University of Washington, Seattle, Washington
- Department of Statistics, University of Washington, Seattle, Washington
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10
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Ngwa JS, Yanek LR, Kammers K, Kanchan K, Taub MA, Scharpf RB, Faraday N, Becker LC, Mathias RA, Ruczinski I. Secondary analyses for genome-wide association studies using expression quantitative trait loci. Genet Epidemiol 2022; 46:170-181. [PMID: 35312098 PMCID: PMC9086181 DOI: 10.1002/gepi.22448] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 11/19/2021] [Accepted: 01/20/2022] [Indexed: 01/01/2023]
Abstract
Genome-wide association studies (GWAS) have successfully identified thousands of single nucleotide polymorphisms (SNPs) associated with complex traits; however, the identified SNPs account for a fraction of trait heritability, and identifying the functional elements through which genetic variants exert their effects remains a challenge. Recent evidence suggests that SNPs associated with complex traits are more likely to be expression quantitative trait loci (eQTL). Thus, incorporating eQTL information can potentially improve power to detect causal variants missed by traditional GWAS approaches. Using genomic, transcriptomic, and platelet phenotype data from the Genetic Study of Atherosclerosis Risk family-based study, we investigated the potential to detect novel genomic risk loci by incorporating information from eQTL in the relevant target tissues (i.e., platelets and megakaryocytes) using established statistical principles in a novel way. Permutation analyses were performed to obtain family-wise error rates for eQTL associations, substantially lowering the genome-wide significance threshold for SNP-phenotype associations. In addition to confirming the well known association between PEAR1 and platelet aggregation, our eQTL-focused approach identified a novel locus (rs1354034) and gene (ARHGEF3) not previously identified in a GWAS of platelet aggregation phenotypes. A colocalization analysis showed strong evidence for a functional role of this eQTL.
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Affiliation(s)
- Julius S. Ngwa
- Department of BiostatisticsJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
| | - Lisa R. Yanek
- Department of MedicineJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Kai Kammers
- Department of OncologyJohns Hopkins University, School of MedicineBaltimoreMarylandUSA
| | - Kanika Kanchan
- Department of MedicineJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Margaret A. Taub
- Department of BiostatisticsJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
| | - Robert B. Scharpf
- Department of OncologyJohns Hopkins University, School of MedicineBaltimoreMarylandUSA
| | - Nauder Faraday
- Department of Anesthesiology and Critical Care MedicineJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Lewis C. Becker
- Department of MedicineJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Rasika A. Mathias
- Department of MedicineJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Ingo Ruczinski
- Department of BiostatisticsJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
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11
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Gorenjak V, Petrelis AM, Stathopoulou MG, Toupance S, Kumar S, Labat C, Masson C, Murray H, Lamont J, Fitzgerald P, Benetos A, Visvikis-Siest S. A genetic determinant of VEGF-A levels is associated with telomere attrition. Aging (Albany NY) 2021; 13:23517-23526. [PMID: 34661551 PMCID: PMC8580333 DOI: 10.18632/aging.203636] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Accepted: 10/03/2021] [Indexed: 12/19/2022]
Abstract
Telomere length (TL) is a hallmark of cellular aging and is associated with chronic diseases development. The vascular endothelial growth factor A (VEGF-A), a potent angiogenesis factor, is implicated in the pathophysiology of many chronic diseases. The aim of the present study was to investigate the associations between VEGF-A and TL. TL in leukocytes (LTL) and skeletal muscle (MTL) were measured, 10 VEGF-related polymorphisms genotyped, and VEGF-A plasma concentrations determined in 402 individuals from the TELARTA cohort. LTL/MTL ratio was calculated as an estimate of lifelong TL attrition. Associations between VEGF-A variants and levels, and TL parameters were investigated. We identified one significant association between the minor allele (T) of rs6993770 variant and LTL/MTL ratio (P=0.001143, β=0.0148, SE=0.004516). The rs6993770 is an intronic variant of the ZFPM2 gene, which is involved in haematopoiesis and the identified association with increased telomere attrition could be due to increased haematopoiesis. No significant epistatic interaction was identified, and no association was found between levels of VEGF-A and any of assessed phenotypes. We identified a potential common genetic regulation between VEGF-A and telomere length attrition that could be explained by mechanisms of increased hematopoiesis and production of platelets. VEGF-A and TL could play an important role in personalized medicine of chronic diseases and identification of molecular links between them can promote the understanding of their complex implications.
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Affiliation(s)
| | | | | | - Simon Toupance
- Université de Lorraine, Inserm, DCAC, Nancy F-54000, France
| | - Satish Kumar
- Université de Lorraine, IGE-PCV, Nancy F-54000, France
| | - Carlos Labat
- Université de Lorraine, Inserm, DCAC, Nancy F-54000, France
| | | | - Helena Murray
- Randox Laboratories Limited, Crumlin, Co. Antrim BT29 4QY, Northern Ireland, United Kingdom
| | - John Lamont
- Randox Laboratories Limited, Crumlin, Co. Antrim BT29 4QY, Northern Ireland, United Kingdom
| | - Peter Fitzgerald
- Randox Laboratories Limited, Crumlin, Co. Antrim BT29 4QY, Northern Ireland, United Kingdom
| | - Athanase Benetos
- Université de Lorraine, Inserm, DCAC, Nancy F-54000, France.,Université de Lorraine, CHRU-Nancy, Pôle "Maladies du Vieillissement, Gérontologie et Soins Palliatifs", Nancy F-54000, France
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12
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Mikaelsdottir E, Thorleifsson G, Stefansdottir L, Halldorsson G, Sigurdsson JK, Lund SH, Tragante V, Melsted P, Rognvaldsson S, Norland K, Helgadottir A, Magnusson MK, Ragnarsson GB, Kristinsson SY, Reykdal S, Vidarsson B, Gudmundsdottir IJ, Olafsson I, Onundarson PT, Sigurdardottir O, Sigurdsson EL, Grondal G, Geirsson AJ, Geirsson G, Gudmundsson J, Holm H, Saevarsdottir S, Jonsdottir I, Thorgeirsson G, Gudbjartsson DF, Thorsteinsdottir U, Rafnar T, Stefansson K. Genetic variants associated with platelet count are predictive of human disease and physiological markers. Commun Biol 2021; 4:1132. [PMID: 34580418 PMCID: PMC8476563 DOI: 10.1038/s42003-021-02642-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Accepted: 09/07/2021] [Indexed: 12/13/2022] Open
Abstract
Platelets play an important role in hemostasis and other aspects of vascular biology. We conducted a meta-analysis of platelet count GWAS using data on 536,974 Europeans and identified 577 independent associations. To search for mechanisms through which these variants affect platelets, we applied cis-expression quantitative trait locus, DEPICT and IPA analyses and assessed genetic sharing between platelet count and various traits using polygenic risk scoring. We found genetic sharing between platelet count and counts of other blood cells (except red blood cells), in addition to several other quantitative traits, including markers of cardiovascular, liver and kidney functions, height, and weight. Platelet count polygenic risk score was predictive of myeloproliferative neoplasms, rheumatoid arthritis, ankylosing spondylitis, hypertension, and benign prostate hyperplasia. Taken together, these results advance understanding of diverse aspects of platelet biology and how they affect biological processes in health and disease. Evgenia Mikaelsdottir et al. report a study of variants associated with platelet count among European individuals where they identify 577 associations. They also report a genetic overlap between platelet count and human diseases, including myeloproliferative neoplasms, rheumatoid arthritis, and hypertension, as well as a genetic overlap between platelet count and various physiological markers.
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Affiliation(s)
| | | | | | | | | | - Sigrun H Lund
- deCODE Genetics/Amgen, Sturlugata 8, 101, Reykjavik, Iceland
| | | | - Pall Melsted
- deCODE Genetics/Amgen, Sturlugata 8, 101, Reykjavik, Iceland.,School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | | | - Magnus K Magnusson
- deCODE Genetics/Amgen, Sturlugata 8, 101, Reykjavik, Iceland.,Faculty of Medicine, University of Iceland, 101, Reykjavik, Iceland
| | - Gunnar B Ragnarsson
- Department of Oncology, Landspitali-University Hospital, 101, Reykjavik, Iceland
| | - Sigurdur Y Kristinsson
- Faculty of Medicine, University of Iceland, 101, Reykjavik, Iceland.,Department of Hematology, Landspitali-University Hospital, 101, Reykjavik, Iceland
| | - Sigrun Reykdal
- Department of Hematology, Landspitali-University Hospital, 101, Reykjavik, Iceland
| | - Brynjar Vidarsson
- Department of Hematology, Landspitali-University Hospital, 101, Reykjavik, Iceland
| | | | - Isleifur Olafsson
- Department of Clinical Biochemistry, Landspitali-University Hospital, 101, Reykjavik, Iceland
| | - Pall T Onundarson
- Faculty of Medicine, University of Iceland, 101, Reykjavik, Iceland.,Laboratory Hematology, Landspitali-University Hospital, 101, Reykjavik, Iceland
| | - Olof Sigurdardottir
- Department of Clinical Biochemistry, Akureyri Hospital, 600, Akureyri, Iceland
| | | | - Gerdur Grondal
- Department of Rheumatology, Landspitali-University Hospital, 101, Reykjavik, Iceland
| | - Arni J Geirsson
- Department of Rheumatology, Landspitali-University Hospital, 101, Reykjavik, Iceland
| | - Gudmundur Geirsson
- Department of Urology, Landspitali-University Hospital, 101, Reykjavik, Iceland
| | | | - Hilma Holm
- deCODE Genetics/Amgen, Sturlugata 8, 101, Reykjavik, Iceland
| | - Saedis Saevarsdottir
- deCODE Genetics/Amgen, Sturlugata 8, 101, Reykjavik, Iceland.,Faculty of Medicine, University of Iceland, 101, Reykjavik, Iceland.,Department of Rheumatology, Landspitali-University Hospital, 101, Reykjavik, Iceland
| | - Ingileif Jonsdottir
- deCODE Genetics/Amgen, Sturlugata 8, 101, Reykjavik, Iceland.,Faculty of Medicine, University of Iceland, 101, Reykjavik, Iceland
| | - Gudmundur Thorgeirsson
- deCODE Genetics/Amgen, Sturlugata 8, 101, Reykjavik, Iceland.,Department of Cardiology, Landspitali-University Hospital, 101, Reykjavik, Iceland
| | - Daniel F Gudbjartsson
- deCODE Genetics/Amgen, Sturlugata 8, 101, Reykjavik, Iceland.,School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Unnur Thorsteinsdottir
- deCODE Genetics/Amgen, Sturlugata 8, 101, Reykjavik, Iceland.,Faculty of Medicine, University of Iceland, 101, Reykjavik, Iceland
| | - Thorunn Rafnar
- deCODE Genetics/Amgen, Sturlugata 8, 101, Reykjavik, Iceland
| | - Kari Stefansson
- deCODE Genetics/Amgen, Sturlugata 8, 101, Reykjavik, Iceland. .,Faculty of Medicine, University of Iceland, 101, Reykjavik, Iceland.
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13
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O’Sullivan LR, Cahill MR, Young PW. The Importance of Alpha-Actinin Proteins in Platelet Formation and Function, and Their Causative Role in Congenital Macrothrombocytopenia. Int J Mol Sci 2021; 22:9363. [PMID: 34502272 PMCID: PMC8431150 DOI: 10.3390/ijms22179363] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 08/25/2021] [Accepted: 08/26/2021] [Indexed: 12/04/2022] Open
Abstract
The actin cytoskeleton plays a central role in platelet formation and function. Alpha-actinins (actinins) are actin filament crosslinking proteins that are prominently expressed in platelets and have been studied in relation to their role in platelet activation since the 1970s. However, within the past decade, several groups have described mutations in ACTN1/actinin-1 that cause congenital macrothrombocytopenia (CMTP)-accounting for approximately 5% of all cases of this condition. These findings are suggestive of potentially novel functions for actinins in platelet formation from megakaryocytes in the bone marrow and/or platelet maturation in circulation. Here, we review some recent insights into the well-known functions of actinins in platelet activation before considering possible roles for actinins in platelet formation that could explain their association with CMTP. We describe what is known about the consequences of CMTP-linked mutations on actinin-1 function at a molecular and cellular level and speculate how these changes might lead to the alterations in platelet count and morphology observed in CMTP patients. Finally, we outline some unanswered questions in this area and how they might be addressed in future studies.
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Affiliation(s)
- Leanne R. O’Sullivan
- School of Biochemistry & Cell Biology, University College Cork, T12 XF62 Cork, Ireland;
| | - Mary R. Cahill
- Department of Haematology and CancerResearch@UCC, Cork University Hospital, University College Cork, T12 XF62 Cork, Ireland;
| | - Paul W. Young
- School of Biochemistry & Cell Biology, University College Cork, T12 XF62 Cork, Ireland;
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14
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Hu Y, Bien SA, Nishimura KK, Haessler J, Hodonsky CJ, Baldassari AR, Highland HM, Wang Z, Preuss M, Sitlani CM, Wojcik GL, Tao R, Graff M, Huckins LM, Sun Q, Chen MH, Mousas A, Auer PL, Lettre G, Tang W, Qi L, Thyagarajan B, Buyske S, Fornage M, Hindorff LA, Li Y, Lin D, Reiner AP, North KE, Loos RJF, Raffield LM, Peters U, Avery CL, Kooperberg C. Multi-ethnic genome-wide association analyses of white blood cell and platelet traits in the Population Architecture using Genomics and Epidemiology (PAGE) study. BMC Genomics 2021; 22:432. [PMID: 34107879 PMCID: PMC8191001 DOI: 10.1186/s12864-021-07745-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Accepted: 05/26/2021] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Circulating white blood cell and platelet traits are clinically linked to various disease outcomes and differ across individuals and ancestry groups. Genetic factors play an important role in determining these traits and many loci have been identified. However, most of these findings were identified in populations of European ancestry (EA), with African Americans (AA), Hispanics/Latinos (HL), and other races/ethnicities being severely underrepresented. RESULTS We performed ancestry-combined and ancestry-specific genome-wide association studies (GWAS) for white blood cell and platelet traits in the ancestrally diverse Population Architecture using Genomics and Epidemiology (PAGE) Study, including 16,201 AA, 21,347 HL, and 27,236 EA participants. We identified six novel findings at suggestive significance (P < 5E-8), which need confirmation, and independent signals at six previously established regions at genome-wide significance (P < 2E-9). We confirmed multiple previously reported genome-wide significant variants in the single variant association analysis and multiple genes using PrediXcan. Evaluation of loci reported from a Euro-centric GWAS indicated attenuation of effect estimates in AA and HL compared to EA populations. CONCLUSIONS Our results highlighted the potential to identify ancestry-specific and ancestry-agnostic variants in participants with diverse backgrounds and advocate for continued efforts in improving inclusion of racially/ethnically diverse populations in genetic association studies for complex traits.
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Affiliation(s)
- Yao Hu
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Stephanie A Bien
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Katherine K Nishimura
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Jeffrey Haessler
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Chani J Hodonsky
- Department of Epidemiology, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Antoine R Baldassari
- Department of Epidemiology, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Heather M Highland
- Department of Epidemiology, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Zhe Wang
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Michael Preuss
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Colleen M Sitlani
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
| | | | - Ran Tao
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
- The Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Mariaelisa Graff
- Department of Epidemiology, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Laura M Huckins
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Quan Sun
- Department of Biostatistics, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ming-Huei Chen
- The Framingham Heart Study, National Heart, Lung and Blood Institute, Framingham, MA, USA
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Framingham, MA, USA
| | - Abdou Mousas
- Montreal Heart Institute, Montreal, Quebec, Canada
| | - Paul L Auer
- School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI, USA
| | - Guillaume Lettre
- Montreal Heart Institute, Montreal, Quebec, Canada
- Department of Medicine, Faculty of Medicine, Université de Montréal, Montreal, Quebec, Canada
| | - Weihong Tang
- School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Lihong Qi
- School of Medicine, University of California Davis, Davis, CA, USA
| | | | - Steve Buyske
- Department of Statistics and Biostatistics, Rutgers University, Piscataway, NJ, USA
| | - Myriam Fornage
- Brown Foundation Institute for Molecular Medicine, the University of Texas Health Science Center, Houston, TX, USA
| | - Lucia A Hindorff
- Division of Genomic Medicine, NIH National Human Genome Research Institute, Bethesda, MD, USA
| | - Yun Li
- Department of Biostatistics, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Genetics, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Danyu Lin
- Department of Biostatistics, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Alexander P Reiner
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
| | - Kari E North
- Department of Epidemiology, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Laura M Raffield
- Department of Genetics, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ulrike Peters
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Christy L Avery
- Department of Epidemiology, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Charles Kooperberg
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
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15
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Sun P, Zhou W, Fu Y, Cheung CYY, Dong Y, Yang ML, Zhang H, Jia J, Huo Y, Willer CJ, Chen YE, Tang CS, Tse HF, Lam KSL, Gao W, Xu M, Yu H, Sham PC, Zhang Y, Ganesh SK. An Asian-specific MPL genetic variant alters JAK-STAT signaling and influences platelet count in the population. Hum Mol Genet 2021; 30:836-842. [PMID: 33693786 DOI: 10.1093/hmg/ddab062] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 02/20/2021] [Accepted: 02/23/2021] [Indexed: 12/27/2022] Open
Abstract
Genomic discovery efforts for hematological traits have been successfully conducted through genome-wide association study on samples of predominantly European ancestry. We sought to conduct unbiased genetic discovery for coding variants that influence hematological traits in a Han Chinese population. A total of 5257 Han Chinese subjects from Beijing, China were included in the discovery cohort and analyzed by an Illumina ExomeChip array. Replication analyses were conducted in 3827 independent Chinese subjects. We analyzed 12 hematological traits and identified 22 exome-wide significant single-nucleotide polymorphisms (SNP)-trait associations with 15 independent SNPs. Our study provides replication for two associations previously reported but not replicated. Further, one association was identified and replicated in the current study, of a coding variant in the myeloproliferative leukemia (MPL) gene, c.793C > T, p.Leu265Phe (L265F) with increased platelet count (β = 20.6 109 cells/l, Pmeta-analysis = 2.6 × 10-13). This variant is observed at ~2% population frequency in East Asians, whereas it has not been reported in gnomAD European or African populations. Functional analysis demonstrated that expression of MPL L265F in Ba/F3 cells resulted in enhanced phosphorylation of Stat3 and ERK1/2 as compared with the reference MPL allele, supporting altered activation of the JAK-STAT signal transduction pathway as the mechanism underlying the novel association between MPL L265F and platelet count.
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Affiliation(s)
- Pengfei Sun
- Department of Cardiology, Peking University First Hospital, Beijing 100034, China
| | - Wei Zhou
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI 48109, USA.,Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI 48109, USA.,Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Yi Fu
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Peking University, Beijing 100191, China.,Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Beijing 100191, China
| | - Chloe Y Y Cheung
- Department of Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong 999077, China
| | - Yujun Dong
- Department of Hematology, Peking University First Hospital, Beijing 100034, China
| | - Min-Lee Yang
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI 48109, USA.,Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI 48109, USA
| | - He Zhang
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI 48109, USA.,Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI 48109, USA.,Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Jia Jia
- Department of Cardiology, Peking University First Hospital, Beijing 100034, China
| | - Yong Huo
- Department of Cardiology, Peking University First Hospital, Beijing 100034, China
| | - Cristen J Willer
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI 48109, USA.,Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI 48109, USA.,Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Y Eugene Chen
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI 48109, USA
| | - Clara S Tang
- Department of Surgery, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong 999077, China
| | - Hung-Fat Tse
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Peking University, Beijing 100191, China
| | - Karen S L Lam
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Peking University, Beijing 100191, China
| | - Wei Gao
- Department of Cardiology, Peking University Third Hospital, Beijing 100083, China
| | - Ming Xu
- Department of Cardiology, Peking University Third Hospital, Beijing 100083, China
| | - Haiyi Yu
- Department of Cardiology, Peking University Third Hospital, Beijing 100083, China
| | - Pak Chung Sham
- Department of Psychiatry and Centre for PanorOmic Sciences, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong 999077, China
| | - Yan Zhang
- Department of Cardiology, Peking University First Hospital, Beijing 100034, China.,Institute of Cardiovascular Disease?Peking University First Hospital, Beijing, 100034, China
| | - Santhi K Ganesh
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI 48109, USA.,Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI 48109, USA
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16
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Whole genome sequence analyses of eGFR in 23,732 people representing multiple ancestries in the NHLBI trans-omics for precision medicine (TOPMed) consortium. EBioMedicine 2021; 63:103157. [PMID: 33418499 PMCID: PMC7804602 DOI: 10.1016/j.ebiom.2020.103157] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Revised: 11/10/2020] [Accepted: 11/18/2020] [Indexed: 01/05/2023] Open
Abstract
Background Genetic factors that influence kidney traits have been understudied for low frequency and ancestry-specific variants. Methods We combined whole genome sequencing (WGS) data from 23,732 participants from 10 NHLBI Trans-Omics for Precision Medicine (TOPMed) Program multi-ethnic studies to identify novel loci for estimated glomerular filtration rate (eGFR). Participants included European, African, East Asian, and Hispanic ancestries. We applied linear mixed models using a genetic relationship matrix estimated from the WGS data and adjusted for age, sex, study, and ethnicity. Findings When testing single variants, we identified three novel loci driven by low frequency variants more commonly observed in non-European ancestry (PRKAA2, rs180996919, minor allele frequency [MAF] 0.04%, P = 6.1 × 10−11; METTL8, rs116951054, MAF 0.09%, P = 4.5 × 10−9; and MATK, rs539182790, MAF 0.05%, P = 3.4 × 10−9). We also replicated two known loci for common variants (rs2461702, MAF=0.49, P = 1.2 × 10−9, nearest gene GATM, and rs71147340, MAF=0.34, P = 3.3 × 10−9, CDK12). Testing aggregated variants within a gene identified the MAF gene. A statistical approach based on local ancestry helped to identify replication samples for ancestry-specific variants. Interpretation This study highlights challenges in studying variants influencing kidney traits that are low frequency in populations and more common in non-European ancestry.
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17
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Chen MH, Raffield LM, Mousas A, Sakaue S, Huffman JE, Moscati A, Trivedi B, Jiang T, Akbari P, Vuckovic D, Bao EL, Zhong X, Manansala R, Laplante V, Chen M, Lo KS, Qian H, Lareau CA, Beaudoin M, Hunt KA, Akiyama M, Bartz TM, Ben-Shlomo Y, Beswick A, Bork-Jensen J, Bottinger EP, Brody JA, van Rooij FJA, Chitrala K, Cho K, Choquet H, Correa A, Danesh J, Di Angelantonio E, Dimou N, Ding J, Elliott P, Esko T, Evans MK, Floyd JS, Broer L, Grarup N, Guo MH, Greinacher A, Haessler J, Hansen T, Howson JMM, Huang QQ, Huang W, Jorgenson E, Kacprowski T, Kähönen M, Kamatani Y, Kanai M, Karthikeyan S, Koskeridis F, Lange LA, Lehtimäki T, Lerch MM, Linneberg A, Liu Y, Lyytikäinen LP, Manichaikul A, Martin HC, Matsuda K, Mohlke KL, Mononen N, Murakami Y, Nadkarni GN, Nauck M, Nikus K, Ouwehand WH, Pankratz N, Pedersen O, Preuss M, Psaty BM, Raitakari OT, Roberts DJ, Rich SS, Rodriguez BAT, Rosen JD, Rotter JI, Schubert P, Spracklen CN, Surendran P, Tang H, Tardif JC, Trembath RC, Ghanbari M, Völker U, Völzke H, Watkins NA, Zonderman AB, Wilson PWF, Li Y, Butterworth AS, Gauchat JF, Chiang CWK, Li B, Loos RJF, Astle WJ, Evangelou E, van Heel DA, Sankaran VG, Okada Y, Soranzo N, Johnson AD, Reiner AP, Auer PL, Lettre G. Trans-ethnic and Ancestry-Specific Blood-Cell Genetics in 746,667 Individuals from 5 Global Populations. Cell 2020; 182:1198-1213.e14. [PMID: 32888493 PMCID: PMC7480402 DOI: 10.1016/j.cell.2020.06.045] [Citation(s) in RCA: 308] [Impact Index Per Article: 77.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2019] [Revised: 04/16/2020] [Accepted: 06/29/2020] [Indexed: 12/14/2022]
Abstract
Most loci identified by GWASs have been found in populations of European ancestry (EUR). In trans-ethnic meta-analyses for 15 hematological traits in 746,667 participants, including 184,535 non-EUR individuals, we identified 5,552 trait-variant associations at p < 5 × 10-9, including 71 novel associations not found in EUR populations. We also identified 28 additional novel variants in ancestry-specific, non-EUR meta-analyses, including an IL7 missense variant in South Asians associated with lymphocyte count in vivo and IL-7 secretion levels in vitro. Fine-mapping prioritized variants annotated as functional and generated 95% credible sets that were 30% smaller when using the trans-ethnic as opposed to the EUR-only results. We explored the clinical significance and predictive value of trans-ethnic variants in multiple populations and compared genetic architecture and the effect of natural selection on these blood phenotypes between populations. Altogether, our results for hematological traits highlight the value of a more global representation of populations in genetic studies.
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Affiliation(s)
- Ming-Huei Chen
- The Framingham Heart Study, National Heart, Lung and Blood Institute, Framingham, MA 01702, USA; Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Framingham, MA 01702, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Abdou Mousas
- Montreal Heart Institute, Montreal, QC H1T 1C8, Canada
| | - Saori Sakaue
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Osaka 565-0871, Japan; Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa 230-0045, Japan
| | - Jennifer E Huffman
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA 02130, USA
| | - Arden Moscati
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Bhavi Trivedi
- Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, UK
| | - Tao Jiang
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - Parsa Akbari
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; MRC Biostatistics Unit, University of Cambridge, Cambridge CB2 0SR, UK; Human Genetics, Wellcome Sanger Institute, Hinxton CB10 1SA, UK; The National Institute for Health Research Blood and Transplant Unit (NIHR BTRU) in Donor Health and Genomics, University of Cambridge, Cambridge CB2 0QQ, UK
| | | | - Erik L Bao
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of Harvard and MIT, Cambridge, MA 02446, USA
| | - Xue Zhong
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University, Nashville, TN 37232, USA
| | - Regina Manansala
- Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI 53201, USA
| | - Véronique Laplante
- Département de Pharmacologie et Physiologie, Faculty of Medicine, Université de Montréal, Montreal, QC H3T 1J4, Canada
| | - Minhui Chen
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA
| | - Ken Sin Lo
- Montreal Heart Institute, Montreal, QC H1T 1C8, Canada
| | - Huijun Qian
- Department of Statistics and Operation Research, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Caleb A Lareau
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of Harvard and MIT, Cambridge, MA 02446, USA
| | | | - Karen A Hunt
- Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, UK
| | - Masato Akiyama
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa 230-0045, Japan; Department of Ocular Pathology and Imaging Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8581, Japan
| | - Traci M Bartz
- Department of Biostatistics, University of Washington, Seattle, WA 98101, USA
| | - Yoav Ben-Shlomo
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2PS, UK
| | - Andrew Beswick
- Translational Health Sciences, Musculoskeletal Research Unit, Bristol Medical School, University of Bristol, Bristol BS10 5NB, UK
| | - Jette Bork-Jensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Erwin P Bottinger
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Hasso-Plattner-Institut, Universität Potsdam, Potsdam 14469, Germany
| | - Jennifer A Brody
- Department of Medicine, University of Washington, Seattle, WA 98101, USA
| | - Frank J A van Rooij
- Department of Epidemiology, Erasmus University Medical Center Rotterdam, Rotterdam 3015, the Netherlands
| | - Kumaraswamynaidu Chitrala
- Laboratory of Epidemiology and Population Science, National Institute on Aging/NIH, Baltimore, MD 21224, USA
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA 02130, USA; Department of Medicine, Division on Aging, Brigham and Women's Hospital, Boston, MA 02115, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Hélène Choquet
- Division of Research, Kaiser Permanente Northern California, Oakland, CA 94612, USA
| | - Adolfo Correa
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - John Danesh
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; Human Genetics, Wellcome Sanger Institute, Hinxton CB10 1SA, UK; The National Institute for Health Research Blood and Transplant Unit (NIHR BTRU) in Donor Health and Genomics, University of Cambridge, Cambridge CB2 0QQ, UK; Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge CB10 1SA, UK; National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge University Hospitals, Cambridge CB2 0QQ, UK; British Heart Foundation Centre of Research Excellence, Division of Cardiovascular Medicine, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK
| | - Emanuele Di Angelantonio
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; The National Institute for Health Research Blood and Transplant Unit (NIHR BTRU) in Donor Health and Genomics, University of Cambridge, Cambridge CB2 0QQ, UK; Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge CB10 1SA, UK; National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge University Hospitals, Cambridge CB2 0QQ, UK; British Heart Foundation Centre of Research Excellence, Division of Cardiovascular Medicine, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK
| | - Niki Dimou
- Section of Nutrition and Metabolism, International Agency for Research on Cancer, Lyon 69008, France; Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina 45110, Greece
| | - Jingzhong Ding
- Department of Internal Medicine, Section of Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, NC 27101, USA
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK; Imperial Biomedical Research Centre, Imperial College London and Imperial College NHS Healthcare Trust, London SW7 2AZ, UK; Medical Research Council-Public Health England Centre for Environment, Imperial College London, London SW7 2AZ, UK; UK Dementia Research Institute, Imperial College London, London SW7 2AZ, UK; Health Data Research UK - London, London SW7 2AZ, UK
| | - Tõnu Esko
- Broad Institute of Harvard and MIT, Cambridge, MA 02446, USA
| | - Michele K Evans
- Laboratory of Epidemiology and Population Science, National Institute on Aging/NIH, Baltimore, MD 21224, USA
| | - James S Floyd
- Department of Medicine, University of Washington, Seattle, WA 98101, USA; Department of Epidemiology, University of Washington, Seattle, WA 98101, USA
| | - Linda Broer
- Department of Internal Medicine, Erasmus University Medical Center Rotterdam, Rotterdam 3015, the Netherlands
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Michael H Guo
- Broad Institute of Harvard and MIT, Cambridge, MA 02446, USA; Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Andreas Greinacher
- Institute for Immunology and Transfusion Medicine, University Medicine Greifswald, Greifswald 17475, Germany
| | - Jeff Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Joanna M M Howson
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; Novo Nordisk Research Centre Oxford, Innovation Building, Old Road Campus, Oxford OX3 7FZ, UK
| | - Qin Qin Huang
- Human Genetics, Wellcome Sanger Institute, Hinxton CB10 1SA, UK
| | - Wei Huang
- Department of Genetics, Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center and Shanghai Industrial Technology Institute (SITI), Shanghai 201203, China
| | - Eric Jorgenson
- Division of Research, Kaiser Permanente Northern California, Oakland, CA 94612, USA
| | - Tim Kacprowski
- Interfaculty Institute of Genetics and Functional Genomics, University Medicine Greifswald, Greifswald 17475, Germany; Chair of Experimental Bioinformatics, Research Group Computational Systems Medicine, Technical University of Munich, Freising-Weihenstephan 85354, Germany; German Center for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald 17475, Germany
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, Tampere 33521, Finland; Department of Clinical Physiology, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33014, Finland
| | - Yoichiro Kamatani
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa 230-0045, Japan; Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo 108-8639, Japan
| | - Masahiro Kanai
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa 230-0045, Japan; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Savita Karthikeyan
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - Fotis Koskeridis
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina 45110, Greece
| | - Leslie A Lange
- Department of Medicine, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere 33520, Finland; Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33014, Finland
| | - Markus M Lerch
- Department of Internal Medicine, University Medicine Greifswald, Greifswald 17475, Germany
| | - Allan Linneberg
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Frederiksberg 2000, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Yongmei Liu
- Duke Molecular Physiology Institute, Department of Medicine, Division of Cardiology, Duke University Medical Center, Durham, NC 27701, USA
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere 33520, Finland; Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33014, Finland
| | - Ani Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22903, USA
| | - Hilary C Martin
- Human Genetics, Wellcome Sanger Institute, Hinxton CB10 1SA, UK
| | - Koichi Matsuda
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo 108-8639, Japan
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Nina Mononen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere 33520, Finland; Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33014, Finland
| | - Yoshinori Murakami
- Division of Molecular Pathology, The Institute of Medical Sciences, The University of Tokyo, Tokyo 108-8639, Japan
| | - Girish N Nadkarni
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Matthias Nauck
- German Center for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald 17475, Germany; Institue of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald 17475, Germany
| | - Kjell Nikus
- Department of Cardiology, Heart Center, Tampere University Hospital, Tampere 33521, Finland; Department of Cardiology, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33014, Finland
| | - Willem H Ouwehand
- Human Genetics, Wellcome Sanger Institute, Hinxton CB10 1SA, UK; British Heart Foundation Centre of Research Excellence, Division of Cardiovascular Medicine, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK; Department of Hematology, University of Cambridge, Cambridge CB2 0PT, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Cambridge CB2 0PT, UK
| | - Nathan Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN 55455, USA
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Michael Preuss
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Bruce M Psaty
- Department of Medicine, University of Washington, Seattle, WA 98101, USA; Department of Epidemiology, University of Washington, Seattle, WA 98101, USA; Department of Health Services, University of Washington, Seattle, WA 98101, USA; Kaiser Permanente Washington Health Research Institute, Seattle, WA 98101, USA
| | - Olli T Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku 20521, Finland; Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku 20521, Finland; Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku 20521, Finland
| | - David J Roberts
- The National Institute for Health Research Blood and Transplant Unit (NIHR BTRU) in Donor Health and Genomics, University of Cambridge, Cambridge CB2 0QQ, UK; Radcliffe Department of Medicine, John Radcliffe Hospital, University of Oxford, Oxford OX3 9DU, UK; Department of Haematology, Churchill Hospital, Oxford OX3 7LE, UK; NHS Blood and Transplant - Oxford Centre, John Radcliffe Hospital, Oxford OX3 9DU, UK
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22903, USA
| | - Benjamin A T Rodriguez
- The Framingham Heart Study, National Heart, Lung and Blood Institute, Framingham, MA 01702, USA; Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Framingham, MA 01702, USA
| | - Jonathan D Rosen
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Petra Schubert
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA 02130, USA
| | - Cassandra N Spracklen
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA; Department of Biostatistics and Epidemiology, University of Massachusetts, Amherst, MA 01002, USA
| | - Praveen Surendran
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; Rutherford Fund Fellow, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - Hua Tang
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Jean-Claude Tardif
- Montreal Heart Institute, Montreal, QC H1T 1C8, Canada; Department of Medicine, Faculty of Medicine, Université de Montréal, Montreal, QC H3T 1J4, Canada
| | - Richard C Trembath
- School of Basic and Medical Biosciences, Faculty of Life Sciences and Medicine, King's College London, London SE1 1UL, UK
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus University Medical Center Rotterdam, Rotterdam 3015, the Netherlands; Department of Genetics, School of Medicine, Mashhad University of Medical Sciences, Mashhad 9177948564, Iran
| | - Uwe Völker
- Interfaculty Institute of Genetics and Functional Genomics, University Medicine Greifswald, Greifswald 17475, Germany; German Center for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald 17475, Germany
| | - Henry Völzke
- German Center for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald 17475, Germany; Institute for Community Medicine, University Medicine Greifswald, Greifswald 17475, Germany
| | - Nicholas A Watkins
- National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Cambridge CB2 0PT, UK
| | - Alan B Zonderman
- Laboratory of Epidemiology and Population Science, National Institute on Aging/NIH, Baltimore, MD 21224, USA
| | | | - Yun Li
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA; Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA; Department of Computer Science, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Adam S Butterworth
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; The National Institute for Health Research Blood and Transplant Unit (NIHR BTRU) in Donor Health and Genomics, University of Cambridge, Cambridge CB2 0QQ, UK; Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge CB10 1SA, UK
| | - Jean-François Gauchat
- Département de Pharmacologie et Physiologie, Faculty of Medicine, Université de Montréal, Montreal, QC H3T 1J4, Canada
| | - Charleston W K Chiang
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA; Quantitative and Computational Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA
| | - Bingshan Li
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 37232, USA
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - William J Astle
- MRC Biostatistics Unit, University of Cambridge, Cambridge CB2 0SR, UK; The National Institute for Health Research Blood and Transplant Unit (NIHR BTRU) in Donor Health and Genomics, University of Cambridge, Cambridge CB2 0QQ, UK; NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Strangeways Laboratory, Cambridge CB1 8RN, UK
| | - Evangelos Evangelou
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina 45110, Greece; Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK
| | - David A van Heel
- Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, UK
| | - Vijay G Sankaran
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of Harvard and MIT, Cambridge, MA 02446, USA
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Osaka 565-0871, Japan; Laboratory of Statistical Immunology, Osaka University Graduate School of Medicine, Suita, Osaka 565-0871, Japan
| | - Nicole Soranzo
- Human Genetics, Wellcome Sanger Institute, Hinxton CB10 1SA, UK; Department of Hematology, University of Cambridge, Cambridge CB2 0PT, UK
| | - Andrew D Johnson
- The Framingham Heart Study, National Heart, Lung and Blood Institute, Framingham, MA 01702, USA; Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Framingham, MA 01702, USA
| | - Alexander P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA 98109, USA
| | - Paul L Auer
- Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI 53201, USA.
| | - Guillaume Lettre
- Montreal Heart Institute, Montreal, QC H1T 1C8, Canada; Department of Medicine, Faculty of Medicine, Université de Montréal, Montreal, QC H3T 1J4, Canada.
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18
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Kessler T, Schunkert H, von Hundelshausen P. Novel Approaches to Fine-Tune Therapeutic Targeting of Platelets in Atherosclerosis: A Critical Appraisal. Thromb Haemost 2020; 120:1492-1504. [PMID: 32772352 DOI: 10.1055/s-0040-1714352] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
The pathogenesis of atherosclerotic vascular disease is driven by a multitude of risk factors intertwining metabolic and inflammatory pathways. Increasing knowledge about platelet biology sheds light on how platelets take part in these processes from early to later stages of plaque development. Recent insights from experimental studies and mouse models substantiate platelets as initiators and amplifiers in atherogenic leukocyte recruitment. These studies are complemented by results from genetics studies shedding light on novel molecular mechanisms which provide an interesting prospect as novel targets. For instance, experimental studies provide further details how platelet-decorated von Willebrand factor tethered to activated endothelial cells plays a role in atherogenic monocyte recruitment. Novel aspects of platelets as atherogenic inductors of neutrophil extracellular traps and particularities in signaling pathways such as cyclic guanosine monophosphate and the inhibitory adaptor molecule SHB23/LNK associating platelets with atherogenesis are shared. In summary, it was our intention to balance insights from recent experimental data that support a plausible role for platelets in atherogenesis against a paucity of clinical evidence needed to validate this concept in humans.
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Affiliation(s)
- Thorsten Kessler
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, Munich, Germany.,Deutsches Zentrum für Herz-Kreislauf-Forschung (DZHK) e.V., Partner Site Munich Heart Alliance, Munich, Germany
| | - Heribert Schunkert
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, Munich, Germany.,Deutsches Zentrum für Herz-Kreislauf-Forschung (DZHK) e.V., Partner Site Munich Heart Alliance, Munich, Germany
| | - Philipp von Hundelshausen
- Deutsches Zentrum für Herz-Kreislauf-Forschung (DZHK) e.V., Partner Site Munich Heart Alliance, Munich, Germany.,Institut für Prophylaxe und Epidemiologie der Kreislaufkrankheiten, Klinikum der Universität, Ludwig-Maximilians-Universität, Partner Site Munich Heart Alliance, Munich, Germany
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19
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Cho H, Kang J, Kim HS, Park KW. Ethnic Differences in Oral Antithrombotic Therapy. Korean Circ J 2020; 50:645-657. [PMID: 32725974 PMCID: PMC7390713 DOI: 10.4070/kcj.2020.0098] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Accepted: 03/22/2020] [Indexed: 02/04/2023] Open
Abstract
Oral antithrombotic therapy (antiplatelet therapy and anticoagulation therapy) is a key element of pharmacotherapy in patients with cardiovascular (CV) disease. Several reports of ethnic differences have suggested that there may be difference therapeutic requirements and response to therapy for antithrombotic therapy. In particular for East Asians, there seems to be a lower incidence of ischemic outcomes and a higher incidence of bleeding outcomes compared to Westerners. The purpose of this review is to describe the ethnicity-related differences in antithrombotic therapy for CV disease and to discuss the need to establish a more effective and targeted antithrombotic treatment strategy in East Asians.
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Affiliation(s)
- Haechan Cho
- Department of Internal Medicine, Cardiovascular Center, Seoul National University Hospital, Seoul, Korea
| | - Jeehoon Kang
- Department of Internal Medicine, Cardiovascular Center, Seoul National University Hospital, Seoul, Korea
| | - Hyo Soo Kim
- Department of Internal Medicine, Cardiovascular Center, Seoul National University Hospital, Seoul, Korea
| | - Kyung Woo Park
- Department of Internal Medicine, Cardiovascular Center, Seoul National University Hospital, Seoul, Korea.
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20
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Shi H, Burch KS, Johnson R, Freund MK, Kichaev G, Mancuso N, Manuel AM, Dong N, Pasaniuc B. Localizing Components of Shared Transethnic Genetic Architecture of Complex Traits from GWAS Summary Data. Am J Hum Genet 2020; 106:805-817. [PMID: 32442408 PMCID: PMC7273527 DOI: 10.1016/j.ajhg.2020.04.012] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Accepted: 04/20/2020] [Indexed: 12/19/2022] Open
Abstract
Despite strong transethnic genetic correlations reported in the literature for many complex traits, the non-transferability of polygenic risk scores across populations suggests the presence of population-specific components of genetic architecture. We propose an approach that models GWAS summary data for one trait in two populations to estimate genome-wide proportions of population-specific/shared causal SNPs. In simulations across various genetic architectures, we show that our approach yields approximately unbiased estimates with in-sample LD and slight upward-bias with out-of-sample LD. We analyze nine complex traits in individuals of East Asian and European ancestry, restricting to common SNPs (MAF > 5%), and find that most common causal SNPs are shared by both populations. Using the genome-wide estimates as priors in an empirical Bayes framework, we perform fine-mapping and observe that high-posterior SNPs (for both the population-specific and shared causal configurations) have highly correlated effects in East Asians and Europeans. In population-specific GWAS risk regions, we observe a 2.8× enrichment of shared high-posterior SNPs, suggesting that population-specific GWAS risk regions harbor shared causal SNPs that are undetected in the other GWASs due to differences in LD, allele frequencies, and/or sample size. Finally, we report enrichments of shared high-posterior SNPs in 53 tissue-specific functional categories and find evidence that SNP-heritability enrichments are driven largely by many low-effect common SNPs.
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Affiliation(s)
- Huwenbo Shi
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
| | - Kathryn S Burch
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA.
| | - Ruth Johnson
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Malika K Freund
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Gleb Kichaev
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Nicholas Mancuso
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Astrid M Manuel
- Department of Biological Sciences, Florida International University, Miami, FL 33199, USA
| | - Natalie Dong
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Bogdan Pasaniuc
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
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21
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A positively selected FBN1 missense variant reduces height in Peruvian individuals. Nature 2020; 582:234-239. [PMID: 32499652 PMCID: PMC7410362 DOI: 10.1038/s41586-020-2302-0] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Accepted: 03/10/2020] [Indexed: 01/21/2023]
Abstract
On average, Peruvian individuals are among the shortest in the world1. Here we show that Native American ancestry is associated with reduced height in an ethnically diverse group of Peruvian individuals, and identify a population-specific, missense variant in the FBN1 gene (E1297G) that is significantly associated with lower height. Each copy of the minor allele (frequency of 4.7%) reduces height by 2.2 cm (4.4 cm in homozygous individuals). To our knowledge, this is the largest effect size known for a common height-associated variant. FBN1 encodes the extracellular matrix protein fibrillin 1, which is a major structural component of microfibrils. We observed less densely packed fibrillin-1-rich microfibrils with irregular edges in the skin of individuals who were homozygous for G1297 compared with individuals who were homozygous for E1297. Moreover, we show that the E1297G locus is under positive selection in non-African populations, and that the E1297 variant shows subtle evidence of positive selection specifically within the Peruvian population. This variant is also significantly more frequent in coastal Peruvian populations than in populations from the Andes or the Amazon, which suggests that short stature might be the result of adaptation to factors that are associated with the coastal environment in Peru.
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22
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Hodonsky CJ, Baldassari AR, Bien SA, Raffield LM, Highland HM, Sitlani CM, Wojcik GL, Tao R, Graff M, Tang W, Thyagarajan B, Buyske S, Fornage M, Hindorff LA, Li Y, Lin D, Reiner AP, North KE, Loos RJF, Kooperberg C, Avery CL. Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics. BMC Genomics 2020; 21:228. [PMID: 32171239 PMCID: PMC7071748 DOI: 10.1186/s12864-020-6626-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Accepted: 02/26/2020] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Quantitative red blood cell (RBC) traits are highly polygenic clinically relevant traits, with approximately 500 reported GWAS loci. The majority of RBC trait GWAS have been performed in European- or East Asian-ancestry populations, despite evidence that rare or ancestry-specific variation contributes substantially to RBC trait heritability. Recently developed combined-phenotype methods which leverage genetic trait correlation to improve statistical power have not yet been applied to these traits. Here we leveraged correlation of seven quantitative RBC traits in performing a combined-phenotype analysis in a multi-ethnic study population. RESULTS We used the adaptive sum of powered scores (aSPU) test to assess combined-phenotype associations between ~ 21 million SNPs and seven RBC traits in a multi-ethnic population (maximum n = 67,885 participants; 24% African American, 30% Hispanic/Latino, and 43% European American; 76% female). Thirty-nine loci in our multi-ethnic population contained at least one significant association signal (p < 5E-9), with lead SNPs at nine loci significantly associated with three or more RBC traits. A majority of the lead SNPs were common (MAF > 5%) across all ancestral populations. Nineteen additional independent association signals were identified at seven known loci (HFE, KIT, HBS1L/MYB, CITED2/FILNC1, ABO, HBA1/2, and PLIN4/5). For example, the HBA1/2 locus contained 14 conditionally independent association signals, 11 of which were previously unreported and are specific to African and Amerindian ancestries. One variant in this region was common in all ancestries, but exhibited a narrower LD block in African Americans than European Americans or Hispanics/Latinos. GTEx eQTL analysis of all independent lead SNPs yielded 31 significant associations in relevant tissues, over half of which were not at the gene immediately proximal to the lead SNP. CONCLUSION This work identified seven loci containing multiple independent association signals for RBC traits using a combined-phenotype approach, which may improve discovery in genetically correlated traits. Highly complex genetic architecture at the HBA1/2 locus was only revealed by the inclusion of African Americans and Hispanics/Latinos, underscoring the continued importance of expanding large GWAS to include ancestrally diverse populations.
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Affiliation(s)
- Chani J. Hodonsky
- University of North Carolina Gillings School of Public Health, 135 Dauer Dr, Chapel Hill, NC 27599 USA
- University of Virginia Center for Public Health Genomics, 1355 Lee St, Charlottesville, VA 22908 USA
| | - Antoine R. Baldassari
- University of North Carolina Gillings School of Public Health, 135 Dauer Dr, Chapel Hill, NC 27599 USA
| | - Stephanie A. Bien
- Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA 98109 USA
| | - Laura M. Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC 27599 USA
| | - Heather M. Highland
- University of North Carolina Gillings School of Public Health, 135 Dauer Dr, Chapel Hill, NC 27599 USA
| | - Colleen M. Sitlani
- University of Washington, 1730 Minor Ave, Ste 1360, Seattle, WA 98101 USA
| | - Genevieve L. Wojcik
- Stanford University School of Medicine, 291 Campus Dr, Stanford, CA 94305 USA
| | - Ran Tao
- Vanderbilt University, 2525 West End Ave #1100, Nashville, TN 37203 USA
| | - Marielisa Graff
- University of North Carolina Gillings School of Public Health, 135 Dauer Dr, Chapel Hill, NC 27599 USA
| | - Weihong Tang
- University of Minnesota, 420 Delaware St SE, Minneapolis, MN 55455 USA
| | | | - Steve Buyske
- Rutgers University, 683 Hoes Ln W, Piscataway, NJ 08854 USA
| | - Myriam Fornage
- University of Texas Houston, 7000 Fannin Street, Houston, TX 77030 USA
| | - Lucia A. Hindorff
- National Human Genome Research Institute, 31 Center Dr, Bethesda, MD 20894 USA
| | - Yun Li
- University of North Carolina Gillings School of Public Health, 135 Dauer Dr, Chapel Hill, NC 27599 USA
| | - Danyu Lin
- University of North Carolina Gillings School of Public Health, 135 Dauer Dr, Chapel Hill, NC 27599 USA
| | - Alex P. Reiner
- Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA 98109 USA
- University of Washington, 1705 NE Pacific St, Seattle, WA 98195 USA
| | - Kari E. North
- University of North Carolina Gillings School of Public Health, 135 Dauer Dr, Chapel Hill, NC 27599 USA
- Department of Genetics, University of North Carolina at Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC 27599 USA
| | - Ruth J. F. Loos
- Icahn School of Medicine at Mount Sinai, 1468 Madison Ave, New York, NY 10029 USA
| | | | - Christy L. Avery
- University of North Carolina Gillings School of Public Health, 135 Dauer Dr, Chapel Hill, NC 27599 USA
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23
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Lin SH, Loftfield E, Sampson JN, Zhou W, Yeager M, Freedman ND, Chanock SJ, Machiela MJ. Mosaic chromosome Y loss is associated with alterations in blood cell counts in UK Biobank men. Sci Rep 2020; 10:3655. [PMID: 32108144 PMCID: PMC7046668 DOI: 10.1038/s41598-020-59963-8] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Accepted: 02/04/2020] [Indexed: 12/31/2022] Open
Abstract
Mosaic loss of Y chromosome (mLOY) is the most frequently detected somatic copy number alteration in leukocytes of men. In this study, we investigate blood cell counts as a potential mechanism linking mLOY to disease risk in 206,353 UK males. Associations between mLOY, detected by genotyping arrays, and blood cell counts were assessed by multivariable linear models adjusted for relevant risk factors. Among the participants, mLOY was detected in 39,809 men. We observed associations between mLOY and reduced erythrocyte count (−0.009 [−0.014, −0.005] × 1012 cells/L, p = 2.75 × 10−5) and elevated thrombocyte count (5.523 [4.862, 6.183] × 109 cells/L, p = 2.32 × 10−60) and leukocyte count (0.218 [0.198, 0.239] × 109 cells/L, p = 9.22 × 10−95), particularly for neutrophil count (0.174 × [0.158, 0.190]109 cells/L, p = 1.24 × 10−99) and monocyte count (0.021 [0.018 to 0.024] × 109 cells/L, p = 6.93 × 10−57), but lymphocyte count was less consistent (0.016 [0.007, 0.025] × 109 cells/L, p = 8.52 × 10−4). Stratified analyses indicate these associations are independent of the effects of aging and smoking. Our findings provide population-based evidence for associations between mLOY and blood cell counts that should stimulate investigation of the underlying biological mechanisms linking mLOY to cancer and chronic disease risk.
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Affiliation(s)
- Shu-Hong Lin
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, 9609 Medical Center Drive MSC 9776, Bethesda, Maryland, 20892, USA
| | - Erikka Loftfield
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, 9609 Medical Center Drive MSC 9776, Bethesda, Maryland, 20892, USA
| | - Josh N Sampson
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, 9609 Medical Center Drive MSC 9776, Bethesda, Maryland, 20892, USA
| | - Weiyin Zhou
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, 9609 Medical Center Drive MSC 9776, Bethesda, Maryland, 20892, USA.,Cancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Frederick, Maryland, 8717 Grovemont Circle, Gaithersburg, MD, 20877, USA
| | - Meredith Yeager
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, 9609 Medical Center Drive MSC 9776, Bethesda, Maryland, 20892, USA.,Cancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Frederick, Maryland, 8717 Grovemont Circle, Gaithersburg, MD, 20877, USA
| | - Neal D Freedman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, 9609 Medical Center Drive MSC 9776, Bethesda, Maryland, 20892, USA
| | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, 9609 Medical Center Drive MSC 9776, Bethesda, Maryland, 20892, USA
| | - Mitchell J Machiela
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, 9609 Medical Center Drive MSC 9776, Bethesda, Maryland, 20892, USA.
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24
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Moon JY, Louie TL, Jain D, Sofer T, Schurmann C, Below JE, Lai CQ, Aviles-Santa ML, Talavera GA, Smith CE, Petty LE, Bottinger EP, Chen YDI, Taylor KD, Daviglus ML, Cai J, Wang T, Tucker KL, Ordovás JM, Hanis CL, Loos RJF, Schneiderman N, Rotter JI, Kaplan RC, Qi Q. A Genome-Wide Association Study Identifies Blood Disorder-Related Variants Influencing Hemoglobin A 1c With Implications for Glycemic Status in U.S. Hispanics/Latinos. Diabetes Care 2019; 42:1784-1791. [PMID: 31213470 PMCID: PMC6702612 DOI: 10.2337/dc19-0168] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Accepted: 05/24/2019] [Indexed: 02/03/2023]
Abstract
OBJECTIVE We aimed to identify hemoglobin A1c (HbA1c)-associated genetic variants and examine their implications for glycemic status evaluated by HbA1c in U.S. Hispanics/Latinos with diverse genetic ancestries. RESEARCH DESIGN AND METHODS We conducted a genome-wide association study (GWAS) of HbA1c in 9,636 U.S. Hispanics/Latinos without diabetes from the Hispanic Community Health Study/Study of Latinos, followed by a replication among 4,729 U.S. Hispanics/Latinos from three independent studies. RESULTS Our GWAS and replication analyses showed 10 previously known and novel loci associated with HbA1c at genome-wide significance levels (P < 5.0 × 10-8). In particular, two African ancestry-specific variants, HBB-rs334 and G6PD-rs1050828, which are causal mutations for sickle cell disease and G6PD deficiency, respectively, had ∼10 times larger effect sizes on HbA1c levels (β = -0.31% [-3.4 mmol/mol]) and -0.35% [-3.8 mmol/mol] per minor allele, respectively) compared with other HbA1c-associated variants (0.03-0.04% [0.3-0.4 mmol/mol] per allele). A novel Amerindian ancestry-specific variant, HBM-rs145546625, was associated with HbA1c and hematologic traits but not with fasting glucose. The prevalence of hyperglycemia (prediabetes and diabetes) defined using fasting glucose or oral glucose tolerance test 2-h glucose was similar between carriers of HBB-rs334 or G6PD-rs1050828 HbA1c-lowering alleles and noncarriers, whereas the prevalence of hyperglycemia defined using HbA1c was significantly lower in carriers than in noncarriers (12.2% vs. 28.4%, P < 0.001). After recalibration of the HbA1c level taking HBB-rs334 and G6PD-rs1050828 into account, the prevalence of hyperglycemia in carriers was similar to noncarriers (31.3% vs. 28.4%, P = 0.28). CONCLUSIONS This study in U.S. Hispanics/Latinos found several ancestry-specific alleles associated with HbA1c through erythrocyte-related rather than glycemic-related pathways. The potential influences of these nonglycemic-related variants need to be considered when the HbA1c test is performed.
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Affiliation(s)
- Jee-Young Moon
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY
| | - Tin L Louie
- Department of Biostatistics, University of Washington, Seattle, WA
| | - Deepti Jain
- Department of Biostatistics, University of Washington, Seattle, WA
| | - Tamar Sofer
- Department of Biostatistics, University of Washington, Seattle, WA
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA
| | - Claudia Schurmann
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Jennifer E Below
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX
| | - Chao-Qiang Lai
- Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA
| | | | - Gregory A Talavera
- Graduate School of Public Health, San Diego State University, San Diego, CA
| | - Caren E Smith
- Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA
| | - Lauren E Petty
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX
| | - Erwin P Bottinger
- Department of Preventive Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Yii-Der Ida Chen
- Institute for Translational Genomics and Population Sciences, Harbor-UCLA Medical Center, Torrance, CA
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, Harbor-UCLA Medical Center, Torrance, CA
| | - Martha L Daviglus
- Institute for Minority Health Research, University of Illinois at Chicago, Chicago, IL
| | - Jianwen Cai
- Department of Biostatistics and Collaborative Studies Coordinating Center, University of North Carolina, Chapel Hill, NC
| | - Tao Wang
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY
| | - Katherine L Tucker
- Department of Biomedical and Nutritional Sciences, University of Massachusetts Lowell, Lowell, MA
| | - José M Ordovás
- Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA
- IMDEA Food Institute, Campus de Excelencia Internacional Universidad Autónoma de Madrid-Consejo Superior de Investigaciones Científicas, Madrid, Spain
| | - Craig L Hanis
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | | | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Harbor-UCLA Medical Center, Torrance, CA
| | - Robert C Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Qibin Qi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY
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25
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Open Chromatin Profiling in Adipose Tissue Marks Genomic Regions with Functional Roles in Cardiometabolic Traits. G3-GENES GENOMES GENETICS 2019; 9:2521-2533. [PMID: 31186305 PMCID: PMC6686932 DOI: 10.1534/g3.119.400294] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Identifying the regulatory mechanisms of genome-wide association study (GWAS) loci affecting adipose tissue has been restricted due to limited characterization of adipose transcriptional regulatory elements. We profiled chromatin accessibility in three frozen human subcutaneous adipose tissue needle biopsies and preadipocytes and adipocytes from the Simpson Golabi-Behmel Syndrome (SGBS) cell strain using an assay for transposase-accessible chromatin (ATAC-seq). We identified 68,571 representative accessible chromatin regions (peaks) across adipose tissue samples (FDR < 5%). GWAS loci for eight cardiometabolic traits were enriched in these peaks (P < 0.005), with the strongest enrichment for waist-hip ratio. Of 110 recently described cardiometabolic GWAS loci colocalized with adipose tissue eQTLs, 59 loci had one or more variants overlapping an adipose tissue peak. Annotated variants at the SNX10 waist-hip ratio locus and the ATP2A1-SH2B1 body mass index locus showed allelic differences in regulatory assays. These adipose tissue accessible chromatin regions elucidate genetic variants that may alter adipose tissue function to impact cardiometabolic traits.
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26
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O'Sullivan LR, Ajaykumar AP, Dembicka KM, Murphy A, Grennan EP, Young PW. Investigation of calmodulin-like and rod domain mutations suggests common molecular mechanism for α-actinin-1-linked congenital macrothrombocytopenia. FEBS Lett 2019; 594:161-174. [PMID: 31365757 DOI: 10.1002/1873-3468.13562] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2019] [Revised: 07/22/2019] [Accepted: 07/29/2019] [Indexed: 11/11/2022]
Abstract
Actinin-1 mutations cause dominantly inherited congenital macrothrombocytopenia (CMTP), with mutations in the actin-binding domain increasing actinin's affinity for F-actin. In this study, we examined nine CMTP-causing mutations in the calmodulin-like and rod domains of actinin-1. These mutations increase, to varying degrees, actinin's ability to bundle actin filaments in vitro. Mutations within the calmodulin-like domain decrease its thermal stability slightly but do not dramatically affect calcium binding, with mutant proteins retaining calcium-dependent regulation of filament bundling in vitro. The G764S and E769K mutations increase cytoskeletal association of actinin in cells, and all mutant proteins colocalize with F-actin in cultured HeLa cells. Thus, CMTP-causing actinin-1 mutations outside the actin-binding domain also increase actin association, suggesting a common molecular mechanism underlying actinin-1 related CMTP.
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Affiliation(s)
- Leanne Rose O'Sullivan
- School of Biochemistry and Cell Biology, Western Gateway Building, University College Cork, Cork, Ireland
| | | | - Kornelia Maria Dembicka
- School of Biochemistry and Cell Biology, Western Gateway Building, University College Cork, Cork, Ireland
| | - Aidan Murphy
- School of Biochemistry and Cell Biology, Western Gateway Building, University College Cork, Cork, Ireland
| | - Eamonn Paul Grennan
- School of Biochemistry and Cell Biology, Western Gateway Building, University College Cork, Cork, Ireland
| | - Paul William Young
- School of Biochemistry and Cell Biology, Western Gateway Building, University College Cork, Cork, Ireland
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27
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Wang H, Cade BE, Sofer T, Sands SA, Chen H, Browning SR, Stilp AM, Louie TL, Thornton TA, Johnson WC, Below JE, Conomos MP, Evans DS, Gharib SA, Guo X, Wood AC, Mei H, Yaffe K, Loredo JS, Ramos AR, Barrett-Connor E, Ancoli-Israel S, Zee PC, Arens R, Shah NA, Taylor KD, Tranah GJ, Stone KL, Hanis CL, Wilson JG, Gottlieb DJ, Patel SR, Rice K, Post WS, Rotter JI, Sunyaev SR, Cai J, Lin X, Purcell SM, Laurie CC, Saxena R, Redline S, Zhu X. Admixture mapping identifies novel loci for obstructive sleep apnea in Hispanic/Latino Americans. Hum Mol Genet 2019; 28:675-687. [PMID: 30403821 DOI: 10.1093/hmg/ddy387] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2018] [Accepted: 11/05/2018] [Indexed: 01/11/2023] Open
Abstract
Obstructive sleep apnea (OSA) is a common disorder associated with increased risk of cardiovascular disease and mortality. Its prevalence and severity vary across ancestral background. Although OSA traits are heritable, few genetic associations have been identified. To identify genetic regions associated with OSA and improve statistical power, we applied admixture mapping on three primary OSA traits [the apnea hypopnea index (AHI), overnight average oxyhemoglobin saturation (SaO2) and percentage time SaO2 < 90%] and a secondary trait (respiratory event duration) in a Hispanic/Latino American population study of 11 575 individuals with significant variation in ancestral background. Linear mixed models were performed using previously inferred African, European and Amerindian local genetic ancestry markers. Global African ancestry was associated with a lower AHI, higher SaO2 and shorter event duration. Admixture mapping analysis of the primary OSA traits identified local African ancestry at the chromosomal region 2q37 as genome-wide significantly associated with AHI (P < 5.7 × 10-5), and European and Amerindian ancestries at 18q21 suggestively associated with both AHI and percentage time SaO2 < 90% (P < 10-3). Follow-up joint ancestry-SNP association analyses identified novel variants in ferrochelatase (FECH), significantly associated with AHI and percentage time SaO2 < 90% after adjusting for multiple tests (P < 8 × 10-6). These signals contributed to the admixture mapping associations and were replicated in independent cohorts. In this first admixture mapping study of OSA, novel associations with variants in the iron/heme metabolism pathway suggest a role for iron in influencing respiratory traits underlying OSA.
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Affiliation(s)
- Heming Wang
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA.,Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA.,Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA.,Broad Institute, Cambridge, MA 02142, USA
| | - Brian E Cade
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA.,Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA.,Broad Institute, Cambridge, MA 02142, USA
| | - Tamar Sofer
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA.,Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA.,Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Scott A Sands
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA.,Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Han Chen
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.,Center for Precision Health, School of Public Health & School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Sharon R Browning
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Adrienne M Stilp
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Tin L Louie
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | | | - W Craig Johnson
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Jennifer E Below
- Vanderbilt Genetics Institute, Department of Medical Genetics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Matthew P Conomos
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Daniel S Evans
- California Pacific Medical Center Research Institute, San Francisco, CA, USA
| | - Sina A Gharib
- Computational Medicine Core, Center for Lung Biology, UW Medicine Sleep Center, Division of Pulmonary, Critical Care and Sleep Medicine, University of Washington, Seattle, WA, USA
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute and Department of Pediatrics at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Alexis C Wood
- USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, USA
| | - Hao Mei
- Department of Data Science, University of Mississippi Medical Center, Jackson, MS, USA
| | - Kristine Yaffe
- Departments of Psychiatry and Neurology, University of California, San Francisco, San Francisco, CA, USA.,Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
| | - Jose S Loredo
- Division of Pulmonary Critical Care and Sleep Medicine, Department of Medicine, UC San Diego School of Medicine, La Jolla, CA, USA
| | - Alberto R Ramos
- Department of Neurology, University of Miami Miller School of Medicine, Miami, FL, USA
| | | | - Sonia Ancoli-Israel
- Departments of Medicine and Psychiatry, University of California, San Diego, CA, USA.,Department of Veterans Affairs, San Diego Center of Excellence for Stress and Mental Health, San Diego, CA, USA
| | - Phyllis C Zee
- Department of Neurology and Sleep Medicine Center, Northwestern University, Chicago, IL, USA
| | - Raanan Arens
- The Children's Hospital at Montefiore, Division of Respiratory and Sleep Medicine, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Neomi A Shah
- Division of Pulmonary, Critical Care and Sleep Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute and Department of Pediatrics at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Gregory J Tranah
- California Pacific Medical Center Research Institute, San Francisco, CA, USA
| | - Katie L Stone
- California Pacific Medical Center Research Institute, San Francisco, CA, USA
| | - Craig L Hanis
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - James G Wilson
- Physiology and Biophysics, University of Mississippi, Jackson, MS, USA
| | - Daniel J Gottlieb
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA.,Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA.,VA Boston Healthcare System, Boston, MA, USA
| | - Sanjay R Patel
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Ken Rice
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Wendy S Post
- Division of Cardiology, Johns Hopkins University, Baltimore, MD, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute and Department of Pediatrics at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Shamil R Sunyaev
- Broad Institute, Cambridge, MA 02142, USA.,Division of Genetics, Brigham and Women's Hospital, Boston, MA, USA.,Division of Medical Sciences, Harvard Medical School, Boston, MA, USA
| | - Jianwen Cai
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA
| | - Xihong Lin
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Shaun M Purcell
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA.,Broad Institute, Cambridge, MA 02142, USA.,Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Cathy C Laurie
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Richa Saxena
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA.,Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA.,Broad Institute, Cambridge, MA 02142, USA.,Center for Genomic Medicine and Department of Anesthesia, Pain, and Critical Care Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA.,Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA.,Division of Pulmonary, Critical Care, and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Xiaofeng Zhu
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA
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28
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Iantorno M, Weintraub WS, Garcia-Garcia HM, Attaran S, Gajanana D, Buchanan KD, Rogers T, Torguson R, Waksman R. Genetic and Nongenetic Implications of Racial Variation in Response to Antiplatelet Therapy. Am J Cardiol 2019; 123:1878-1883. [PMID: 30967284 DOI: 10.1016/j.amjcard.2019.02.047] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2018] [Revised: 02/18/2019] [Accepted: 02/20/2019] [Indexed: 12/17/2022]
Abstract
Race has been identified as an independent risk factor for poor prognosis and an independent predictor of survival in coronary artery disease. Race-related dissimilarities have been identified in cardiovascular patients in terms of age of presentation, co-morbidities, socioeconomic status, and treatment approach as well as genetically driven race-related disparities in responsiveness to medications. Antiplatelet therapy represents a fundamental component of therapy in cardiovascular patients, especially in patients presenting with acute coronary syndromes. It has been argued that the different level of platelet reactivity and varying response to antiplatelet therapy among races may account in part for worse outcomes in certain populations. The purpose of this review is to describe genotypic and phenotypic race-related differences in platelet reactivity and responsiveness to cardiovascular treatment, focusing on antiplatelet therapy to highlight the need establish a more effective and targeted antithrombotic strategy.
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Affiliation(s)
- Micaela Iantorno
- Section of Interventional Cardiology, MedStar Washington Hospital Center, Washington, District of Columbia
| | - William S Weintraub
- Section of Interventional Cardiology, MedStar Washington Hospital Center, Washington, District of Columbia
| | - Hector M Garcia-Garcia
- Section of Interventional Cardiology, MedStar Washington Hospital Center, Washington, District of Columbia
| | - Saina Attaran
- Section of Interventional Cardiology, MedStar Washington Hospital Center, Washington, District of Columbia
| | - Deepakraj Gajanana
- Section of Interventional Cardiology, MedStar Washington Hospital Center, Washington, District of Columbia
| | - Kyle D Buchanan
- Section of Interventional Cardiology, MedStar Washington Hospital Center, Washington, District of Columbia
| | - Toby Rogers
- Section of Interventional Cardiology, MedStar Washington Hospital Center, Washington, District of Columbia; Cardiovascular Branch, Division of Intramural Research, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland
| | - Rebecca Torguson
- Section of Interventional Cardiology, MedStar Washington Hospital Center, Washington, District of Columbia
| | - Ron Waksman
- Section of Interventional Cardiology, MedStar Washington Hospital Center, Washington, District of Columbia.
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29
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Kong X, Ma L, Chen E, Shaw CA, Edelstein LC. Identification of the Regulatory Elements and Target Genes of Megakaryopoietic Transcription Factor MEF2C. Thromb Haemost 2019; 119:716-725. [PMID: 30731491 PMCID: PMC6932631 DOI: 10.1055/s-0039-1678694] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Megakaryopoiesis produces specialized haematopoietic stem cells in the bone marrow that give rise to megakaryocytes which ultimately produce platelets. Defects in megakaryopoiesis can result in altered platelet counts and physiology, leading to dysfunctional haemostasis and thrombosis. Additionally, dysregulated megakaryopoiesis is also associated with myeloid pathologies. Transcription factors play critical roles in cell differentiation by regulating the temporal and spatial patterns of gene expression which ultimately decide cell fate. Several transcription factors have been described as regulating megakaryopoiesis including myocyte enhancer factor 2C (MEF2C); however, the genes regulated by MEF2C that influence megakaryopoiesis have not been reported. Using chromatin immunoprecipitation-sequencing and Gene Ontology data we identified five candidate genes that are bound by MEF2C and regulate megakaryopoiesis: MOV10, AGO3, HDAC1, RBBP5 and WASF2. To study expression of these genes, we silenced MEF2C gene expression in the Meg01 megakaryocytic cell line and in induced pluripotent stem cells by CRISPR/Cas9 editing. We also knocked down MEF2C expression in cord blood-derived haematopoietic stem cells by siRNA. We found that absent or reduced MEF2C expression resulted in defects in megakaryocytic differentiation and reduced levels of the candidate target genes. Luciferase assays confirmed that genomic sequences within the target genes are regulated by MEF2C levels. Finally, we demonstrate that small deletions linked to a platelet count-associated single nucleotide polymorphism alter transcriptional activity, suggesting a mechanism by which genetic variation in MEF2C alters platelet production. These data help elucidate the mechanism behind MEF2C regulation of megakaryopoiesis and genetic variation driving platelet production.
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Affiliation(s)
- Xianguo Kong
- Cardeza Foundation for Hematologic Research and Department of Medicine, Sidney Kimmel Medical School at Thomas Jefferson University, Philadelphia, PA
| | - Lin Ma
- Cardeza Foundation for Hematologic Research and Department of Medicine, Sidney Kimmel Medical School at Thomas Jefferson University, Philadelphia, PA
| | - Edward Chen
- Department of Human & Molecular Genetics, Baylor College of Medicine, Houston, TX
| | - Chad A. Shaw
- Department of Human & Molecular Genetics, Baylor College of Medicine, Houston, TX
- Department of Statistics, Rice University, Houston, TX
| | - Leonard C. Edelstein
- Cardeza Foundation for Hematologic Research and Department of Medicine, Sidney Kimmel Medical School at Thomas Jefferson University, Philadelphia, PA
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30
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Grinde KE, Brown LA, Reiner AP, Thornton TA, Browning SR. Genome-wide Significance Thresholds for Admixture Mapping Studies. Am J Hum Genet 2019; 104:454-465. [PMID: 30773276 PMCID: PMC6407497 DOI: 10.1016/j.ajhg.2019.01.008] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2018] [Accepted: 01/17/2019] [Indexed: 01/25/2023] Open
Abstract
Admixture mapping studies have become more common in recent years, due in part to technological advances and growing international efforts to increase the diversity of genetic studies. However, many open questions remain about appropriate implementation of admixture mapping studies, including how best to control for multiple testing, particularly in the presence of population structure. In this study, we develop a theoretical framework to characterize the correlation of local ancestry and admixture mapping test statistics in admixed populations with contributions from any number of ancestral populations and arbitrary population structure. Based on this framework, we develop an analytical approach for obtaining genome-wide significance thresholds for admixture mapping studies. We validate our approach via analysis of simulated traits with real genotype data for 8,064 unrelated African American and 3,425 Hispanic/Latina women from the Women's Health Initiative SNP Health Association Resource (WHI SHARe). In an application to these WHI SHARe data, our approach yields genome-wide significant p value thresholds of 2.1 × 10-5 and 4.5 × 10-6 for admixture mapping studies in the African American and Hispanic/Latina cohorts, respectively. Compared to other commonly used multiple testing correction procedures, our method is fast, easy to implement (using our publicly available R package), and controls the family-wise error rate even in structured populations. Importantly, we note that the appropriate admixture mapping significance threshold depends on the number of ancestral populations, generations since admixture, and population structure of the sample; as a result, significance thresholds are not, in general, transferable across studies.
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Affiliation(s)
- Kelsey E Grinde
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA.
| | - Lisa A Brown
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA; Seattle Genetics, Bothell, WA 98021, USA
| | - Alexander P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA 98195, USA; Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Timothy A Thornton
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Sharon R Browning
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
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31
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Grinde KE, Qi Q, Thornton TA, Liu S, Shadyab AH, Chan KHK, Reiner AP, Sofer T. Generalizing polygenic risk scores from Europeans to Hispanics/Latinos. Genet Epidemiol 2019; 43:50-62. [PMID: 30368908 PMCID: PMC6330129 DOI: 10.1002/gepi.22166] [Citation(s) in RCA: 67] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2018] [Revised: 08/12/2018] [Accepted: 08/28/2018] [Indexed: 12/17/2022]
Abstract
Polygenic risk scores (PRSs) are weighted sums of risk allele counts of single-nucleotide polymorphisms (SNPs) associated with a disease or trait. PRSs are typically constructed based on published results from Genome-Wide Association Studies (GWASs), and the majority of which has been performed in large populations of European ancestry (EA) individuals. Although many genotype-trait associations have generalized across populations, the optimal choice of SNPs and weights for PRSs may differ between populations due to different linkage disequilibrium (LD) and allele frequency patterns. We compare various approaches for PRS construction, using GWAS results from both large EA studies and a smaller study in Hispanics/Latinos: The Hispanic Community Health Study/Study of Latinos (HCHS/SOL, n = 12 , 803 ). We consider multiple approaches for selecting SNPs and for computing SNP weights. We study the performance of the resulting PRSs in an independent study of Hispanics/Latinos from the Women's Health Initiative (WHI, n = 3 , 582 ). We support our investigation with simulation studies of potential genetic architectures in a single locus. We observed that selecting variants based on EA GWASs generally performs well, except for blood pressure trait. However, the use of EA GWASs for weight estimation was suboptimal. Using non-EA GWAS results to estimate weights improved results.
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Affiliation(s)
- Kelsey E. Grinde
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Qibin Qi
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | | | - Simin Liu
- Department of Epidemiology, Brown University, Providence, RI, USA
| | - Aladdin H. Shadyab
- Department of Family Medicine and Public Health, University of California San Diego, San Diego, CA, USA
| | - Kei Hang K. Chan
- Department of Epidemiology, Brown University, Providence, RI, USA
- Departments of Biomedical Sciences and Electronic Engineering, City University of Hong Kong, HKSAR
| | - Alexander P. Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Tamar Sofer
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
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32
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Reiner AP, Johnson AD. Platelet Genomics. Platelets 2019. [DOI: 10.1016/b978-0-12-813456-6.00005-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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33
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Kanhai D, Mulder R, Ploos van Amstel HK, Schutgens R, Lukens M, Tamminga RYJ. Familial macrothrombocytopenia due to a double mutation in cis in the alpha-actinin 1 gene (ACTN1), previously considered to be chronic immune thrombocytopenic purpura. Pediatr Blood Cancer 2018; 65:e27418. [PMID: 30124235 DOI: 10.1002/pbc.27418] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2018] [Revised: 07/10/2018] [Accepted: 07/29/2018] [Indexed: 11/07/2022]
Abstract
Congenital thrombocytopenia can easily be misdiagnosed as immune thrombocytopenic purpura, as is illustrated by this case of a woman and her two children. Doubts arose when steroid/IVIG therapy failed in the mother and the thrombocytopenia in the children persisted. By means of next-generation sequencing, two missense variants in cis in the ACTN1 gene of the affected family members were identified, both of unknown significance. We conclude, after further analysis of these mutations with, among others, in silico prediction tools, that the thrombocytopenia has a genetic cause, in particular the ACTN1 mutations, and is not immune mediated.
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Affiliation(s)
- Danny Kanhai
- Department of Pediatric Hematology, Beatrix Children's Hospital, University Medical Center Groningen, Groningen, the Netherlands
| | - René Mulder
- Department of Laboratory Medicine, University Medical Center Groningen, Groningen, the Netherlands
| | | | - Roger Schutgens
- Department of Hematology, Van Creveldkliniek, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Michael Lukens
- Department of Laboratory Medicine, University Medical Center Groningen, Groningen, the Netherlands
| | - Rienk Y J Tamminga
- Department of Pediatric Hematology, Beatrix Children's Hospital, University Medical Center Groningen, Groningen, the Netherlands
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34
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Vasudeva K, Munshi A. Genetics of platelet traits in ischaemic stroke: focus on mean platelet volume and platelet count. Int J Neurosci 2018; 129:511-522. [PMID: 30371123 DOI: 10.1080/00207454.2018.1538991] [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] [Indexed: 12/11/2022]
Abstract
Purpose/Aim of the study: The aim of this review is to summarize the role of genetic variants affecting mean platelet volume (MPV) and platelet count (PLT) leading to higher platelet reactivity and in turn to thrombotic events like stroke and cardiovascular diseases. MATERIALS AND METHODS A search was conducted in PUBMED, MEDLINE, EMBASE, PROQUEST, Science Direct, Cochrane Library, and Google Scholar related to the studies focussing on genome-wide association studies (GWAS), whole exome sequencing (WES), whole genome sequencing (WGS), phenome-wide association studies (PheWAS) and multi-omic analysis that have been employed to identify the genetic variants influencing MPV and PLT. RESULTS Antiplatelet agents underscore the crucial role of platelets in the pathogenesis of stroke. Higher platelet reactivity in terms of mean platelet volume (MPV) and platelet count (PLT) contributes significantly to the interindividual variation in platelet reaction at the site of vessel wall injury. Some individuals encounter thrombotic events as platelets get occluded at the site of vessel wall injury whereas others heal the injury without occluding the circulation. Evidence suggests that MPV and PLT have a strong genetic component. High throughput techniques including genome-wide association studies (GWAS), whole exome sequencing (WES), whole genome sequencing (WGS), phenome-wide association studies (PheWAS) and multi-omic analysis have identified different genetic variants influencing MPV and PLT. CONCLUSIONS Identification of complex genetic cross talks affecting PLT and MPV might help to develop novel treatment strategies in treating neurovascular diseases like stroke.
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Affiliation(s)
- Kanika Vasudeva
- a Department of Human Genetics and Molecular Medicine , Central University of Punjab Bathinda , Punjab , India
| | - Anjana Munshi
- a Department of Human Genetics and Molecular Medicine , Central University of Punjab Bathinda , Punjab , India
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35
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Origin and age of the causative mutations in KLC2, IMPA1, MED25 and WNT7A unravelled through Brazilian admixed populations. Sci Rep 2018; 8:16552. [PMID: 30410084 PMCID: PMC6224410 DOI: 10.1038/s41598-018-35022-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2018] [Accepted: 10/23/2018] [Indexed: 12/13/2022] Open
Abstract
The mutation age and local ancestry of chromosomal segments harbouring mutations associated with autosomal recessive (AR) disorders in Brazilian admixed populations remain unknown; additionally, inbreeding levels for these affected individuals continue to be estimated based on genealogical information. Here, we calculated inbreeding levels using a runs of homozygosity approach, mutation age and local ancestry to infer the origin of each chromosomal segments containing disorder-causing mutations in KLC2, IMPA1, MED25 and WNT7A. Genotyped data were generated from 18 patients affected by AR diseases and combined to the 1000 genome project (1KGP) and Simons genome diversity project (SGDP) databases to infer local ancestry. We found a major European contribution for mutated haplotypes with recent mutation age and inbreeding values found only in Native American and Middle East individuals. These results contribute to identifying the origin of and to understanding how these diseases are maintained and spread in Brazilian and world populations.
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36
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Soares-Souza G, Borda V, Kehdy F, Tarazona-Santos E. Admixture, Genetics and Complex Diseases in Latin Americans and US Hispanics. CURRENT GENETIC MEDICINE REPORTS 2018. [DOI: 10.1007/s40142-018-0151-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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37
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Izzi B, Bonaccio M, de Gaetano G, Cerletti C. Learning by counting blood platelets in population studies: survey and perspective a long way after Bizzozero. J Thromb Haemost 2018; 16:1711-1721. [PMID: 29888860 DOI: 10.1111/jth.14202] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2017] [Indexed: 01/13/2023]
Abstract
Platelet count represents a useful tool in clinical practice to discriminate individuals at higher risk of bleeding. Less obvious is the role of platelet count variability within the normal range of distribution in shaping the individual's disease risk profile. Epidemiological studies have shown that platelet count in the adult general population is associated with a number of health outcomes related to hemostasis and thrombosis. However, recent studies are suggesting a possible role of this platelet index also as an independent risk factor. In this review of adult population studies, we will first focus on known genetic and non-genetic determinants of platelet number variability. Next, we will evaluate platelet count as a marker and/or a predictor of disease risk and its interaction with other risk factors. We will then discuss the role of platelet count variability within the normal distribution range as a contribution to disease and mortality risk. The possibility of considering platelet count as a simple, inexpensive indicator of increased risk of disease and death in general populations could open new opportunities to investigate novel platelet pathophysiological roles as well as therapeutic opportunities. Future studies should also consider platelet count, not only platelet function, as a modulator of disease and mortality risk.
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Affiliation(s)
- B Izzi
- Department of Epidemiology and Prevention, IRCCS Istituto Neurologico Mediterraneo Neuromed, Pozzilli (IS), Italy
| | - M Bonaccio
- Department of Epidemiology and Prevention, IRCCS Istituto Neurologico Mediterraneo Neuromed, Pozzilli (IS), Italy
| | - G de Gaetano
- Department of Epidemiology and Prevention, IRCCS Istituto Neurologico Mediterraneo Neuromed, Pozzilli (IS), Italy
| | - C Cerletti
- Department of Epidemiology and Prevention, IRCCS Istituto Neurologico Mediterraneo Neuromed, Pozzilli (IS), Italy
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38
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Yasukochi Y, Sakuma J, Takeuchi I, Kato K, Oguri M, Fujimaki T, Horibe H, Yamada Y. Identification of nine novel loci related to hematological traits in a Japanese population. Physiol Genomics 2018; 50:758-769. [PMID: 29958078 PMCID: PMC6172615 DOI: 10.1152/physiolgenomics.00088.2017] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
Recent genome-wide association studies have identified various genetic variants associated with hematological traits. Although it is possible that quantitative data of hematological traits are varied among the years examined, conventional genome-wide association studies have been conducted in a cross-sectional manner that measures traits at a single point in time. To address this issue, we have traced blood profiles in 4,884 Japanese individuals who underwent annual health check-ups for several years. In the present study, longitudinal exome-wide association studies were conducted to identify genetic variants related to 13 hematological phenotypes. The generalized estimating equation model showed that a total of 67 single nucleotide polymorphisms (SNPs) were significantly [false discovery rate (FDR) of <0.01] associated with hematological phenotypes. Of the 67 SNPs, nine SNPs were identified as novel hematological markers: rs4686683 of SENP2 for red blood cell count (FDR = 0.008, P = 5.5 × 10−6); rs3917688 of SELP for mean corpuscular volume (FDR = 0.005, P = 2.4 × 10−6); rs3133745 of C8orf37-AS1 for white blood cell count (FDR = 0.003, P = 1.3 × 10−6); rs13121954 at 4q31.2 for basophil count (FDR = 0.007, P = 3.1 × 10−5); rs7584099 at 2q22.3 (FDR = 2.6 × 10−5, P = 8.8 × 10−8), rs1579219 of HCG17 (FDR = 0.003, P = 2.0 × 10−5), and rs10757049 of DENND4C (FDR = 0.008, P = 5.6 × 10−5) for eosinophil count; rs12338 of CTSB for neutrophil count (FDR = 0.007, P = 2.9 × 10−5); and rs395967 of OSMR-AS1 for monocyte count (FDR = 0.008, P = 3.2 × 10−5).
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Affiliation(s)
- Yoshiki Yasukochi
- Department of Human Functional Genomics, Advanced Science Research Promotion Center, Mie University, Tsu, Mie , Japan.,CREST, Japan Science and Technology Agency, Kawaguchi, Saitama , Japan
| | - Jun Sakuma
- CREST, Japan Science and Technology Agency, Kawaguchi, Saitama , Japan.,Computer Science Department, College of Information Science, University of Tsukuba, Tsukuba, Ibaraki , Japan.,RIKEN Center for Advanced Intelligence Project , Tokyo , Japan
| | - Ichiro Takeuchi
- CREST, Japan Science and Technology Agency, Kawaguchi, Saitama , Japan.,RIKEN Center for Advanced Intelligence Project , Tokyo , Japan.,Department of Computer Science, Nagoya Institute of Technology, Nagoya, Aichi , Japan
| | - Kimihiko Kato
- Department of Human Functional Genomics, Advanced Science Research Promotion Center, Mie University, Tsu, Mie , Japan.,Department of Internal Medicine, Meitoh Hospital, Nagoya, Aichi , Japan
| | - Mitsutoshi Oguri
- Department of Human Functional Genomics, Advanced Science Research Promotion Center, Mie University, Tsu, Mie , Japan.,Department of Cardiology, Kasugai Municipal Hospital, Kasugai, Aichi , Japan
| | - Tetsuo Fujimaki
- Department of Cardiovascular Medicine, Inabe General Hospital, Inabe, Mie , Japan
| | - Hideki Horibe
- Department of Cardiovascular Medicine, Gifu Prefectural Tajimi Hospital, Tajimi, Gifu , Japan
| | - Yoshiji Yamada
- Department of Human Functional Genomics, Advanced Science Research Promotion Center, Mie University, Tsu, Mie , Japan.,CREST, Japan Science and Technology Agency, Kawaguchi, Saitama , Japan
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Jo Hodonsky C, Schurmann C, Schick UM, Kocarnik J, Tao R, van Rooij FJ, Wassel C, Buyske S, Fornage M, Hindorff LA, Floyd JS, Ganesh SK, Lin DY, North KE, Reiner AP, Loos RJ, Kooperberg C, Avery CL. Generalization and fine mapping of red blood cell trait genetic associations to multi-ethnic populations: The PAGE Study. Am J Hematol 2018; 93:10.1002/ajh.25161. [PMID: 29905378 PMCID: PMC6300146 DOI: 10.1002/ajh.25161] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2018] [Revised: 05/29/2018] [Accepted: 05/29/2018] [Indexed: 12/17/2022]
Abstract
Red blood cell (RBC) traits provide insight into a wide range of physiological states and exhibit moderate to high heritability, making them excellent candidates for genetic studies to inform underlying biologic mechanisms. Previous RBC trait genome-wide association studies were performed primarily in European- or Asian-ancestry populations, missing opportunities to inform understanding of RBC genetic architecture in diverse populations and reduce intervals surrounding putative functional SNPs through fine-mapping. Here, we report the first fine-mapping of six correlated (Pearson's r range: |0.04 - 0.92|) RBC traits in up to 19,036 African Americans and 19,562 Hispanic/Latinos participants of the Population Architecture using Genomics and Epidemiology (PAGE) consortium. Trans-ethnic meta-analysis of race/ethnic- and study-specific estimates for approximately 11,000 SNPs flanking 13 previously identified association signals as well as 150,000 additional array-wide SNPs was performed using inverse-variance meta-analysis after adjusting for study and clinical covariates. Approximately half of previously reported index SNP-RBC trait associations generalized to the trans-ethnic study population (p<1.7x10-4 ); previously unreported independent association signals within the ABO region reinforce the potential for multiple functional variants affecting the same locus. Trans-ethnic fine-mapping did not reveal additional signals at the HFE locus independent of the known functional variants. Finally, we identified a potential novel association in the Hispanic/Latino study population at the HECTD4/RPL6 locus for RBC count (p=1.9x10-7 ). The identification of a previously unknown association, generalization of a large proportion of known association signals, and refinement of known association signals all exemplify the benefits of genetic studies in diverse populations. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Chani Jo Hodonsky
- Department of Epidemiology, University of North Carolina Gillings School of Public Health, Chapel Hill, NC
| | - Claudia Schurmann
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
- The Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Ursula M Schick
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
- The Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, NY
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Jonathan Kocarnik
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Ran Tao
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN
| | - Frank Ja van Rooij
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3000, the Netherlands
| | - Christina Wassel
- Department of Pathology and Laboratory Medicine, College of Medicine, University of Vermont, Burlington, VT
| | - Steve Buyske
- Department of Statistics and Biostatistics, Hill Center, Rutgers, The State University of New Jersey, 110 Frelinghuysen Rd. Piscataway, NY
| | - Myriam Fornage
- Institute of Molecular Medicine and Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX
| | - Lucia A Hindorff
- Division of Genomic Medicine, National Human Genome Research Institute, National institutes of Health, Bethesda, MD
| | - James S Floyd
- Departments of Medicine, University of Washington, Seattle, WA
- Department of Epidemiology, University of Washington, Seattle, WA
| | - Santhi K Ganesh
- Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI
| | - Dan-Yu Lin
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC
| | - Kari E North
- Department of Epidemiology, University of North Carolina Gillings School of Public Health, Chapel Hill, NC
| | - Alex P Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA
- Department of Epidemiology, University of Washington, Seattle, WA
| | - Ruth Jf Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
- The Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Christy L Avery
- Department of Epidemiology, University of North Carolina Gillings School of Public Health, Chapel Hill, NC
- Carolina Population Center, University of North Carolina, Chapel Hill, NC
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40
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Population-specific genetic modification of Huntington's disease in Venezuela. PLoS Genet 2018; 14:e1007274. [PMID: 29750799 PMCID: PMC5965898 DOI: 10.1371/journal.pgen.1007274] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2017] [Revised: 05/23/2018] [Accepted: 02/23/2018] [Indexed: 12/21/2022] Open
Abstract
Modifiers of Mendelian disorders can provide insights into disease mechanisms and guide therapeutic strategies. A recent genome-wide association (GWA) study discovered genetic modifiers of Huntington's disease (HD) onset in Europeans. Here, we performed whole genome sequencing and GWA analysis of a Venezuelan HD cluster whose families were crucial for the original mapping of the HD gene defect. The Venezuelan HD subjects develop motor symptoms earlier than their European counterparts, implying the potential for population-specific modifiers. The main Venezuelan HD family inherits HTT haplotype hap.03, which differs subtly at the sequence level from European HD hap.03, suggesting a different ancestral origin but not explaining the earlier age at onset in these Venezuelans. GWA analysis of the Venezuelan HD cluster suggests both population-specific and population-shared genetic modifiers. Genome-wide significant signals at 7p21.2-21.1 and suggestive association signals at 4p14 and 17q21.2 are evident only in Venezuelan HD, but genome-wide significant association signals at the established European chromosome 15 modifier locus are improved when Venezuelan HD data are included in the meta-analysis. Venezuelan-specific association signals on chromosome 7 center on SOSTDC1, which encodes a bone morphogenetic protein antagonist. The corresponding SNPs are associated with reduced expression of SOSTDC1 in non-Venezuelan tissue samples, suggesting that interaction of reduced SOSTDC1 expression with a population-specific genetic or environmental factor may be responsible for modification of HD onset in Venezuela. Detection of population-specific modification in Venezuelan HD supports the value of distinct disease populations in revealing novel aspects of a disease and population-relevant therapeutic strategies.
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Dunn EC, Sofer T, Wang MJ, Soare TW, Gallo LC, Gogarten SM, Kerr KF, Chen CY, Stein MB, Ursano RJ, Guo X, Jia Y, Yao J, Rotter JI, Argos M, Cai J, Perreira K, Wassertheil-Smoller S, Smoller JW. Genome-wide association study of depressive symptoms in the Hispanic Community Health Study/Study of Latinos. J Psychiatr Res 2018; 99:167-176. [PMID: 29505938 PMCID: PMC6192675 DOI: 10.1016/j.jpsychires.2017.12.010] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/25/2017] [Revised: 11/28/2017] [Accepted: 12/14/2017] [Indexed: 12/12/2022]
Abstract
Although genome-wide association studies (GWAS) have identified several variants linked to depression, few GWAS of non-European populations have been performed. We conducted a genome-wide analysis of depression in a large, population-based sample of Hispanics/Latinos. Data came from 12,310 adults in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Past-week depressive symptoms were assessed using the 10-item Center for Epidemiological Studies of Depression Scale. Three phenotypes were examined: a total depression score, a total score modified to account for psychiatric medication use, and a score excluding anti-depressant medication users. We estimated heritability due to common variants (h2SNP), and performed a GWAS of the three phenotypes. Replication was attempted in three independent Hispanic/Latino cohorts. We also performed sex-stratified analyses, analyzed a binary trait indicating probable depression, and conducted three trans-ethnic analyses. The three phenotypes exhibited significant heritability (h2SNP = 6.3-6.9%; p = .002) in the total sample. No SNPs were genome-wide significant in analyses of the three phenotypes or the binary indicator of probable depression. In sex-stratified analyses, seven genome-wide significant SNPs (one in females; six in males) were identified, though none were supported through replication. Four out of 24 loci identified in prior GWAS were nominally associated in HCHS/SOL. There was no evidence of overlap in genetic risk factors across ancestry groups, though this may have been due to low power. We conducted the largest GWAS of depression-related phenotypes in Hispanic/Latino adults. Results underscore the genetic complexity of depressive symptoms as a phenotype in this population and suggest the need for much larger samples.
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Affiliation(s)
- Erin C Dunn
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, United States; Department of Psychiatry, Harvard Medical School, Boston, MA, United States; Stanley Center for Psychiatric Research, The Broad Institute of Harvard and MIT, Cambridge, MA, United States.
| | - Tamar Sofer
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, United States; Department of Medicine, Harvard Medical School, Boston, MA, United States
| | - Min-Jung Wang
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, United States
| | - Thomas W Soare
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, United States; Department of Psychiatry, Harvard Medical School, Boston, MA, United States; Stanley Center for Psychiatric Research, The Broad Institute of Harvard and MIT, Cambridge, MA, United States
| | - Linda C Gallo
- Department of Psychology, San Diego State University, San Diego, CA, United States
| | - Stephanie M Gogarten
- Department of Biostatistics, University of Washington, Seattle, WA, United States
| | - Kathleen F Kerr
- Department of Biostatistics, University of Washington, Seattle, WA, United States
| | - Chia-Yen Chen
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, United States; Department of Psychiatry, Harvard Medical School, Boston, MA, United States; Stanley Center for Psychiatric Research, The Broad Institute of Harvard and MIT, Cambridge, MA, United States; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, United States
| | - Murray B Stein
- Department of Psychiatry, University of California San Diego, La Jolla, CA, United States
| | - Robert J Ursano
- Department of Psychiatry, Uniformed Services University of the Health Sciences, Bethesda, MD, United States
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, United States
| | - Yucheng Jia
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, United States
| | - Jie Yao
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, United States
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, United States
| | - Maria Argos
- School of Public Health, University of Illinois at Chicago, Chicago, IL, United States
| | - Jianwen Cai
- Department of Biostatistics, The University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Krista Perreira
- College of Arts and Sciences, The University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Sylvia Wassertheil-Smoller
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Jordan W Smoller
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, United States; Department of Psychiatry, Harvard Medical School, Boston, MA, United States; Stanley Center for Psychiatric Research, The Broad Institute of Harvard and MIT, Cambridge, MA, United States
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42
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Handtke S, Steil L, Greinacher A, Thiele T. Toward the Relevance of Platelet Subpopulations for Transfusion Medicine. Front Med (Lausanne) 2018; 5:17. [PMID: 29459897 PMCID: PMC5807390 DOI: 10.3389/fmed.2018.00017] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2017] [Accepted: 01/18/2018] [Indexed: 12/11/2022] Open
Abstract
Circulating platelets consist of subpopulations with different age, maturation state and size. In this review, we address the association between platelet size and platelet function and summarize the current knowledge on platelet subpopulations including reticulated platelets, procoagulant platelets and platelets exposing signals to mediate their clearance. Thereby, we emphasize the impact of platelet turnover as an important condition for platelet production in vivo. Understanding of the features that characterize platelet subpopulations is very relevant for the methods of platelet concentrate production, which may enrich or deplete particular platelet subpopulations. Moreover, the concept of platelet size being associated with platelet function may be attractive for transfusion medicine as it holds the perspective to separate platelet subpopulations with specific functional capabilities.
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Affiliation(s)
- Stefan Handtke
- Institut für Immunologie und Transfusionsmedizin, Greifswald, Germany
| | - Leif Steil
- Interfakultäres Institut für Funktionelle Genomforschung, Greifswald, Germany
| | | | - Thomas Thiele
- Institut für Immunologie und Transfusionsmedizin, Greifswald, Germany
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43
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Lin BD, Carnero Montoro E, Bell JT, Boomsma DI, de Geus EJ, Jansen R, Kluft C, Mangino M, Penninx B, Spector TD, Willemsen G, Hottenga JJ. 2SNP heritability and effects of genetic variants for neutrophil-to-lymphocyte and platelet-to-lymphocyte ratio. J Hum Genet 2017; 62:979-988. [PMID: 29066854 PMCID: PMC5669488 DOI: 10.1038/jhg.2017.76] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2017] [Revised: 05/24/2017] [Accepted: 06/13/2017] [Indexed: 01/13/2023]
Abstract
Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) are important biomarkers for disease development and progression. To gain insight into the genetic causes of variance in NLR and PLR in the general population, we conducted genome-wide association (GWA) analyses and estimated SNP heritability in a sample of 5901 related healthy Dutch individuals. GWA analyses identified a new genome-wide significant locus on the HBS1L-MYB intergenic region for PLR, which replicated in a sample of 2538 British twins. For platelet count, we replicated three known genome-wide significant loci in our cohort (at CCDC71L-PIK3CG, BAK1 and ARHGEF3). For neutrophil count, we replicated the PSMD3 locus. For the identified top SNPs, we found significant cis and trans expression quantitative trait loci effects for several loci involved in hematological and immunological pathways. Linkage Disequilibrium score (LD) regression analyses for PLR and NLR confirmed that both traits are heritable, with a polygenetic SNP heritability for PLR of 14.1%, and for NLR of 2.4%. Genetic correlations were present between ratios and the constituent counts, with the genetic correlation (r=0.45) of PLR with platelet count reaching statistical significance. In conclusion, we established that two important biomarkers have a significant heritable SNP component, and identified the first genome-wide locus for PLR.
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Affiliation(s)
- Bochao Danae Lin
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Elena Carnero Montoro
- Department of Twin Research and Genetic Epidemiology, Kings College London, London SE1 7EH, UK
| | - Jordana T. Bell
- Department of Twin Research and Genetic Epidemiology, Kings College London, London SE1 7EH, UK
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Eco J. de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- EMGO+ Institute for Health & Care Research, VU Medical Center, Amsterdam, The Netherlands
| | - Rick Jansen
- Department of Psychiatry, VU Medical Center, Amsterdam, The Netherlands
| | | | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, Kings College London, London SE1 7EH, UK
- NIHR Biomedical Research Centre at Guy’s and St Thomas’ Foundation Trust, London SE1 9RT, UK
| | - Brenda Penninx
- Department of Psychiatry, VU Medical Center, Amsterdam, The Netherlands
| | - Tim D. Spector
- Department of Twin Research and Genetic Epidemiology, Kings College London, London SE1 7EH, UK
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- EMGO+ Institute for Health & Care Research, VU Medical Center, Amsterdam, The Netherlands
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Abstract
PURPOSE OF REVIEW Inherited thrombocytopenias are a heterogeneous group of diseases caused by mutations in many genes. They account for approximately only 50% of cases, suggesting that novel genes have yet to be identified for a comprehensive understanding of platelet biogenesis defects. This review provides an update of the last year of discoveries on inherited thrombocytopenias focusing on the molecular basis and potential pathogenic mechanisms affecting megakaryopoiesis and platelet production. RECENT FINDINGS Most of the novel discoveries are related to identification of mutations in novel inherited thrombocytopenia genes using a next-generation sequencing approach. They include MECOM, DIAPH1, TRPM7, SRC, FYB, and SLFN14, playing different roles in megakaryopoiesis and platelet production. Moreover, it is worth mentioning data on hypomorphic mutations of FLI1 and the association of single nucleotide polymorphisms, such as that identified in ACTN1, with thrombocytopenia. SUMMARY Thanks to the application of next-generation sequencing, the number of inherited thrombocytopenia genes is going to increase rapidly. Considering the wide genetic heterogeneity (more than 30 genes), these technologies can also be used for diagnostic purpose. Whatever is the aim, extreme caution should be taken in interpreting data, as inherited thrombocytopenias are mainly autosomal dominant diseases caused by variants of apparent unknown significance.
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45
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Affiliation(s)
- Sarah K Westbury
- a School of Clinical Sciences, University of Bristol , Bristol , UK
| | | | - Andrew D Mumford
- c School of Cellular and Molecular Medicine, University of Bristol , Bristol , UK
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Brown LA, Sofer T, Stilp AM, Baier LJ, Kramer HJ, Masindova I, Levy D, Hanson RL, Moncrieft AE, Redline S, Rosas SE, Lash JP, Cai J, Laurie CC, Browning S, Thornton T, Franceschini N. Admixture Mapping Identifies an Amerindian Ancestry Locus Associated with Albuminuria in Hispanics in the United States. J Am Soc Nephrol 2017; 28:2211-2220. [PMID: 28137830 PMCID: PMC5491288 DOI: 10.1681/asn.2016091010] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2016] [Accepted: 12/29/2016] [Indexed: 11/03/2022] Open
Abstract
Increased urine albumin excretion is highly prevalent in Hispanics/Latinos. Previous studies have found an association between urine albumin excretion and Amerindian ancestry in Hispanic/Latino populations. Admixture between racial/ethnic groups creates long-range linkage disequilibrium between variants with different allelic frequencies in the founding populations and it can be used to localize genes. Hispanic/Latino genomes are an admixture of European, African, and Amerindian ancestries. We leveraged this admixture to identify associations between urine albumin excretion (urine albumin-to-creatinine ratio [UACR]) and genomic regions harboring variants with highly differentiated allele frequencies among the ancestral populations. Admixture mapping analysis of 12,212 Hispanic Community Health Study/Study of Latinos participants, using a linear mixed model, identified three novel genome-wide significant signals on chromosomes 2, 11, and 16. The admixture mapping signal identified on chromosome 2, spanning q11.2-14.1 and not previously reported for UACR, is driven by a difference between Amerindian ancestry and the other two ancestries (P<5.7 × 10-5). Within this locus, two common variants located at the proapoptotic BCL2L11 gene associated with UACR: rs116907128 (allele frequency =0.14; P=1.5 × 10-7) and rs586283 (C allele frequency =0.35; P=4.2 × 10-7). In a secondary analysis, rs116907128 accounted for most of the admixture mapping signal observed in the region. The rs116907128 variant is common among full-heritage Pima Indians (A allele frequency =0.54) but is monomorphic in the 1000 Genomes European and African populations. In a replication analysis using a sample of full-heritage Pima Indians, rs116907128 significantly associated with UACR (P=0.01; n=1568). Our findings provide evidence for the presence of Amerindian-specific variants influencing the variation of urine albumin excretion in Hispanics/Latinos.
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Affiliation(s)
- Lisa A Brown
- Department of Biostatistics, University of Washington School of Public Health, Seattle, Washington
| | - Tamar Sofer
- Department of Biostatistics, University of Washington School of Public Health, Seattle, Washington
| | - Adrienne M Stilp
- Department of Biostatistics, University of Washington School of Public Health, Seattle, Washington
| | - Leslie J Baier
- Epidemiology and Clinical Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona
| | - Holly J Kramer
- Department of Public Health Sciences and Medicine, Division of Nephrology and Hypertension, Loyola University Chicago, Maywood, Illinois
| | - Ivica Masindova
- Epidemiology and Clinical Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona
| | - Daniel Levy
- The Framingham Heart Study, Framingham, Massachusetts, and Population Sciences Branch, National Heart, Lung, and Blood Institute, US National Institutes of Health, Bethesda, Maryland
| | - Robert L Hanson
- Epidemiology and Clinical Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona
| | | | - Susan Redline
- Department of Medicine, Brigham and Women's Hospital and Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts
| | - Sylvia E Rosas
- Department of Medicine, Division of Nephrology, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - James P Lash
- Department of Medicine, Division of Nephrology and Institute for Minority Health Research, University of Illinois at Chicago, Chicago, Illinois
| | - Jianwen Cai
- Collaborative Studies Coordinating Center, Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina; and
| | - Cathy C Laurie
- Department of Biostatistics, University of Washington School of Public Health, Seattle, Washington
| | - Sharon Browning
- Department of Biostatistics, University of Washington School of Public Health, Seattle, Washington
| | - Timothy Thornton
- Department of Biostatistics, University of Washington School of Public Health, Seattle, Washington
| | - Nora Franceschini
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina
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Abstract
The last decade has witnessed an explosion in the depth, variety, and amount of human genetic data that can be generated. This revolution in technical and analytical capacities has enabled the genetic investigation of human traits and disease in thousands to now millions of participants. Investigators have taken advantage of these advancements to gain insight into platelet biology and the platelet's role in human disease. To do so, large human genetics studies have examined the association of genetic variation with two quantitative traits measured in many population and patient based cohorts: platelet count (PLT) and mean platelet volume (MPV). This article will review the many human genetic strategies-ranging from genome-wide association study (GWAS), Exomechip, whole exome sequencing (WES), to whole genome sequencing (WGS)-employed to identify genes and variants that contribute to platelet traits. Additionally, we will discuss how these investigations have examined and interpreted the functional implications of these newly identified genetic factors and whether they also impart risk to human disease. The depth and size of genetic, phenotypic, and other -omic data are primed to continue their growth in the coming years and provide unprecedented opportunities to gain critical insights into platelet biology and how platelets contribute to disease.
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Affiliation(s)
- John D Eicher
- a Population Sciences Branch , National Heart Lung and Blood Institute, The Framingham Heart Study , Framingham , MA , USA
| | - Guillaume Lettre
- b Department of Medicine , Université de Montréal , Montréal , Québec , Canada.,c Montreal Heart Institute , Montréal , Québec , Canada
| | - Andrew D Johnson
- a Population Sciences Branch , National Heart Lung and Blood Institute, The Framingham Heart Study , Framingham , MA , USA
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Qi Q, Stilp AM, Sofer T, Moon JY, Hidalgo B, Szpiro AA, Wang T, Ng MCY, Guo X, Chen YDI, Taylor KD, Aviles-Santa ML, Papanicolaou G, Pankow JS, Schneiderman N, Laurie CC, Rotter JI, Kaplan RC. Genetics of Type 2 Diabetes in U.S. Hispanic/Latino Individuals: Results From the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Diabetes 2017; 66:1419-1425. [PMID: 28254843 PMCID: PMC5399610 DOI: 10.2337/db16-1150] [Citation(s) in RCA: 49] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2016] [Accepted: 02/23/2017] [Indexed: 12/15/2022]
Abstract
Few genome-wide association studies (GWAS) of type 2 diabetes (T2D) have been conducted in U.S. Hispanics/Latinos of diverse backgrounds who are disproportionately affected by diabetes. We conducted a GWAS in 2,499 T2D case subjects and 5,247 control subjects from six Hispanic/Latino background groups in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Our GWAS identified two known loci (TCF7L2 and KCNQ1) reaching genome-wide significance levels. Conditional analysis on known index single nucleotide polymorphisms (SNPs) indicated an additional independent signal at KCNQ1, represented by an African ancestry-specific variant, rs1049549 (odds ratio 1.49 [95% CI 1.27-1.75]). This association was consistent across Hispanic/Latino background groups and replicated in the MEta-analysis of type 2 DIabetes in African Americans (MEDIA) Consortium. Among 80 previously known index SNPs at T2D loci, 66 SNPs showed consistency with the reported direction of associations and 14 SNPs significantly generalized to the HCHS/SOL. A genetic risk score based on these 80 index SNPs was significantly associated with T2D (odds ratio 1.07 [1.06-1.09] per risk allele), with a stronger effect observed in nonobese than in obese individuals. Our study identified a novel independent signal suggesting an African ancestry-specific allele at KCNQ1 for T2D. Associations between previously identified loci and T2D were generally shown in a large cohort of U.S. Hispanics/Latinos.
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Affiliation(s)
- Qibin Qi
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY
| | - Adrienne M Stilp
- Department of Biostatistics, University of Washington, Seattle, WA
| | - Tamar Sofer
- Department of Biostatistics, University of Washington, Seattle, WA
| | - Jee-Young Moon
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY
| | - Bertha Hidalgo
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL
| | - Adam A Szpiro
- Department of Biostatistics, University of Washington, Seattle, WA
| | - Tao Wang
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY
| | - Maggie C Y Ng
- Center for Genomics and Personalized Medicine Research and Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, and Department of Pediatrics, Harbor-UCLA Medical Center, Los Angeles, CA
| | | | - Yii-Der Ida Chen
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, and Department of Pediatrics, Harbor-UCLA Medical Center, Los Angeles, CA
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, and Department of Pediatrics, Harbor-UCLA Medical Center, Los Angeles, CA
| | - M Larissa Aviles-Santa
- Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - George Papanicolaou
- Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - James S Pankow
- Division of Epidemiology & Community Health, University of Minnesota, Minneapolis, MN
| | | | - Cathy C Laurie
- Department of Biostatistics, University of Washington, Seattle, WA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, and Department of Pediatrics, Harbor-UCLA Medical Center, Los Angeles, CA
| | - Robert C Kaplan
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY
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49
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Hodonsky CJ, Jain D, Schick UM, Morrison JV, Brown L, McHugh CP, Schurmann C, Chen DD, Liu YM, Auer PL, Laurie CA, Taylor KD, Browning BL, Li Y, Papanicolaou G, Rotter JI, Kurita R, Nakamura Y, Browning SR, Loos RJF, North KE, Laurie CC, Thornton TA, Pankratz N, Bauer DE, Sofer T, Reiner AP. Genome-wide association study of red blood cell traits in Hispanics/Latinos: The Hispanic Community Health Study/Study of Latinos. PLoS Genet 2017; 13:e1006760. [PMID: 28453575 PMCID: PMC5428979 DOI: 10.1371/journal.pgen.1006760] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2016] [Revised: 05/12/2017] [Accepted: 04/12/2017] [Indexed: 01/13/2023] Open
Abstract
Prior GWAS have identified loci associated with red blood cell (RBC) traits in populations of European, African, and Asian ancestry. These studies have not included individuals with an Amerindian ancestral background, such as Hispanics/Latinos, nor evaluated the full spectrum of genomic variation beyond single nucleotide variants. Using a custom genotyping array enriched for Amerindian ancestral content and 1000 Genomes imputation, we performed GWAS in 12,502 participants of Hispanic Community Health Study and Study of Latinos (HCHS/SOL) for hematocrit, hemoglobin, RBC count, RBC distribution width (RDW), and RBC indices. Approximately 60% of previously reported RBC trait loci generalized to HCHS/SOL Hispanics/Latinos, including African ancestral alpha- and beta-globin gene variants. In addition to the known 3.8kb alpha-globin copy number variant, we identified an Amerindian ancestral association in an alpha-globin regulatory region on chromosome 16p13.3 for mean corpuscular volume and mean corpuscular hemoglobin. We also discovered and replicated three genome-wide significant variants in previously unreported loci for RDW (SLC12A2 rs17764730, PSMB5 rs941718), and hematocrit (PROX1 rs3754140). Among the proxy variants at the SLC12A2 locus we identified rs3812049, located in a bi-directional promoter between SLC12A2 (which encodes a red cell membrane ion-transport protein) and an upstream anti-sense long-noncoding RNA, LINC01184, as the likely causal variant. We further demonstrate that disruption of the regulatory element harboring rs3812049 affects transcription of SLC12A2 and LINC01184 in human erythroid progenitor cells. Together, these results reinforce the importance of genetic study of diverse ancestral populations, in particular Hispanics/Latinos.
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Affiliation(s)
- Chani J. Hodonsky
- Department of Epidemiology, University of North Carolina Gillings School of Public Health, Chapel Hill, NC, United States of America
| | - Deepti Jain
- Department of Biostatistics, University of Washington, Seattle, WA, United States of America
| | - Ursula M. Schick
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- The Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America
| | - Jean V. Morrison
- Department of Biostatistics, University of Washington, Seattle, WA, United States of America
| | - Lisa Brown
- Department of Biostatistics, University of Washington, Seattle, WA, United States of America
| | - Caitlin P. McHugh
- Department of Biostatistics, University of Washington, Seattle, WA, United States of America
- New York Genome Center, New York, NY, United States of America
| | - Claudia Schurmann
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- The Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Diane D. Chen
- Division of Hematology/Oncology, Boston Children's Hospital, Boston, MA, United States of America
| | - Yong Mei Liu
- School of Medicine, Wake Forest University, Winston-Salem, NC, United States of America
| | - Paul L. Auer
- Joseph J. Zilber School of Public Health, University of Wisconsin Milwaukee, Milwaukee, WI, United States of America
| | - Cecilia A. Laurie
- Department of Biostatistics, University of Washington, Seattle, WA, United States of America
| | - Kent D. Taylor
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA United States of America
- Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA United States of America
| | - Brian L. Browning
- Department of Medicine, University of Washington, Seattle, WA United States of America
| | - Yun Li
- Department of Genetics, University of North Carolina, Chapel Hill, NC, United States of America
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC, United States of America
- Department of Computer Science, University of North Carolina, Chapel Hill, NC, United States of America
| | - George Papanicolaou
- Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD, United States of America
| | - Jerome I. Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA United States of America
- Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA United States of America
| | - Ryo Kurita
- Research and Development Department, Central Blood Institute, Blood Service Headquarters, Japanese Red Cross Society, Tokyo, Japan
| | - Yukio Nakamura
- Cell Engineering Division, RIKEN BioResource Center, Tsukuba, Ibaraki, Japan
- Comprehensive Human Sciences, Tsukuba University, Tsukuba, Ibaraki, Japan
| | - Sharon R. Browning
- Department of Biostatistics, University of Washington, Seattle, WA, United States of America
| | - Ruth J. F. Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- The Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Kari E. North
- Department of Epidemiology, University of North Carolina Gillings School of Public Health, Chapel Hill, NC, United States of America
- Department of Genetics, University of North Carolina, Chapel Hill, NC, United States of America
| | - Cathy C. Laurie
- Department of Biostatistics, University of Washington, Seattle, WA, United States of America
| | - Timothy A. Thornton
- Department of Biostatistics, University of Washington, Seattle, WA, United States of America
| | - Nathan Pankratz
- Division of Laboratory Medicine & Pathology, University of Minnesota, Minneapolis, MN, United States of America
| | - Daniel E. Bauer
- Division of Hematology/Oncology, Boston Children's Hospital, Boston, MA, United States of America
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA, United States of America
- Department of Pediatrics, Harvard Medical School and Harvard Stem Cell Institute, Harvard University, Boston, MA, United States of America
| | - Tamar Sofer
- Department of Biostatistics, University of Washington, Seattle, WA, United States of America
| | - Alex P. Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America
- * E-mail:
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50
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Dunn EC, Sofer T, Gallo LC, Gogarten SM, Kerr KF, Chen CY, Stein MB, Ursano RJ, Guo X, Jia Y, Qi Q, Rotter JI, Argos M, Cai J, Penedo FJ, Perreira K, Wassertheil-Smoller S, Smoller JW. Genome-wide association study of generalized anxiety symptoms in the Hispanic Community Health Study/Study of Latinos. Am J Med Genet B Neuropsychiatr Genet 2017; 174:132-143. [PMID: 27159506 PMCID: PMC5501086 DOI: 10.1002/ajmg.b.32448] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2015] [Accepted: 03/14/2016] [Indexed: 01/25/2023]
Abstract
Although generalized anxiety disorder (GAD) is heritable and aggregates in families, no genomic loci associated with GAD have been reported. We aimed to discover potential loci by conducting a genome-wide analysis of GAD symptoms in a large, population-based sample of Hispanic/Latino adults. Data came from 12,282 participants (aged 18-74) in the Hispanic Community Health Study/Study of Latinos. Using a shortened Spielberger Trait Anxiety measure, we analyzed the following: (i) a GAD symptoms score restricted to the three items tapping diagnostic features of GAD as defined by DSM-V; and (ii) a total trait anxiety score based on summing responses to all ten items. We first calculated the heritability due to common variants (h2SNP ) and then conducted a genome-wide association study (GWAS) of GAD symptoms. Replication was attempted in three independent Hispanic cohorts (Multi-Ethnic Study of Atherosclerosis, Women's Health Initiative, Army STARRS). The GAD symptoms score showed evidence of modest heritability (7.2%; P = 0.03), while the total trait anxiety score did not (4.97%; P = 0.20). One genotyped SNP (rs78602344) intronic to thrombospondin 2 (THBS2) was nominally associated (P = 5.28 × 10-8 ) in the primary analysis adjusting for psychiatric medication use and significantly associated with the GAD symptoms score in the analysis excluding medication users (P = 4.18 × 10-8 ). However, meta-analysis of the replication samples did not support this association. Although we identified a genome-wide significant locus in this sample, we were unable to replicate this finding. Evidence for heritability was also only detected for GAD symptoms, and not the trait anxiety measure, suggesting differential genetic influences within the domain of trait anxiety. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Erin C. Dunn
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
- Stanley Center for Psychiatric Research, The Broad Institute of Harvard and MIT, Cambridge, Massachusetts
| | - Tamar Sofer
- Department of Biostatistics, University of Washington, Seattle, Washington
| | - Linda C. Gallo
- Department of Psychology, San Diego State University, La Jolla, California
| | | | - Kathleen F. Kerr
- Department of Biostatistics, University of Washington, Seattle, Washington
| | - Chia-Yen Chen
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
- Stanley Center for Psychiatric Research, The Broad Institute of Harvard and MIT, Cambridge, Massachusetts
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts
| | - Murray B. Stein
- Department of Psychiatry, University of California San Diego, San Diego, California
| | - Robert J. Ursano
- Department of Psychiatry, Uniformed Services University of the Health Sciences, Bethesda Maryland
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, California
| | - Yucheng Jia
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, California
| | - Qibin Qi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx New York, New York
| | - Jerome I. Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, California
| | - Maria Argos
- School of Public Health, University of Illinois at Chicago, Chicago, Illinois
| | - Jianwen Cai
- Department of Biostatistics, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Frank J Penedo
- Department of Medical Social Sciences, Northwestern University, Chicago, Illinois
| | - Krista Perreira
- College and Arts and Sciences, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Sylvia Wassertheil-Smoller
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx New York, New York
| | - Jordan W. Smoller
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
- Stanley Center for Psychiatric Research, The Broad Institute of Harvard and MIT, Cambridge, Massachusetts
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