1
|
Garzón Rodríguez N, Briceño-Balcázar I, Nicolini H, Martínez-Magaña JJ, Genis-Mendoza AD, Flores-Lázaro JC, Villatoro Velázquez JA, Bustos Gamiño M, Medina-Mora ME, Quiroz-Padilla MF. Exploring the relationship between admixture and genetic susceptibility to attention deficit hyperactivity disorder in two Latin American cohorts. J Hum Genet 2024; 69:373-380. [PMID: 38714835 PMCID: PMC11269173 DOI: 10.1038/s10038-024-01246-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 03/11/2024] [Accepted: 03/18/2024] [Indexed: 07/13/2024]
Abstract
Contemporary research on the genomics of Attention Deficit Hyperactivity Disorder (ADHD) often underrepresents admixed populations of diverse genomic ancestries, such as Latin Americans. This study explores the relationship between admixture and genetic associations for ADHD in Colombian and Mexican cohorts. Some 546 participants in two groups, ADHD and Control, were genotyped with Infinium PsychArray®. Global ancestry levels were estimated using overall admixture proportions and principal component analysis, while local ancestry was determined using a method to estimate ancestral components along the genome. Genome-wide association analysis (GWAS) was conducted to identify significant associations. Differences between Colombia and Mexico were evaluated using appropriate statistical tests. 354 Single-nucleotide polymorphisms (SNPs) and Single-nucleotide variants (SNVs) related to some genes and intergenic regions exhibited suggestive significance (p-value < 5*10e-5) in the GWAS. None of the variants revealed genome-wide significance (p-value < 5*10e-8). The study identified a significant relationship between risk SNPs and the European component of admixture, notably observed in the LOC105379109 gene. Despite differences in risk association loci, such as FOXP2, our findings suggest a possible homogeneity in genetic variation's impact on ADHD between Colombian and Mexican populations. Current reference datasets for ADHD predominantly consist of samples with high European ancestry, underscoring the need for further research to enhance the representation of reference populations and improve the identification of ADHD risk traits in Latin Americans.
Collapse
Affiliation(s)
- Nicolás Garzón Rodríguez
- Laboratorio de Bases Biológicas del Comportamiento, Facultad de Psicología, Universidad de La Sabana, Chía, Colombia
- Doctorado en Biociencias, Facultad de Ingeniería, Universidad de La Sabana, Chía, Colombia
| | | | - Humberto Nicolini
- Laboratorio de Enfermedades Psiquiátricas, Neurodegenerativas y Adicciones, Instituto Nacional de Medicina Genómica, Secretaría de Salud, Mexico City, México
| | - José Jaime Martínez-Magaña
- Laboratorio de Enfermedades Psiquiátricas, Neurodegenerativas y Adicciones, Instituto Nacional de Medicina Genómica, Secretaría de Salud, Mexico City, México
| | - Alma D Genis-Mendoza
- Laboratorio de Enfermedades Psiquiátricas, Neurodegenerativas y Adicciones, Instituto Nacional de Medicina Genómica, Secretaría de Salud, Mexico City, México
- Hospital Psiquiátrico Infantil Dr Juan N. Navarro, Mexico City, México
| | - Julio C Flores-Lázaro
- Facultad de Psicología, Universidad Nacional Autónoma de México - UNAM, Mexico City, México
| | | | - Marycarmen Bustos Gamiño
- Instituto Nacional de Psiquiatría Ramon de la Fuente Muñiz, Secretaría de Salud, Mexico City, México
| | - Maria Elena Medina-Mora
- Facultad de Psicología, Universidad Nacional Autónoma de México - UNAM, Mexico City, México
- Instituto Nacional de Psiquiatría Ramon de la Fuente Muñiz, Secretaría de Salud, Mexico City, México
| | - Maria Fernanda Quiroz-Padilla
- Laboratorio de Bases Biológicas del Comportamiento, Facultad de Psicología, Universidad de La Sabana, Chía, Colombia.
| |
Collapse
|
2
|
Yang Y, Wang Q, Wang C, Buxbaum J, Ionita-Laza I. KnockoffHybrid: A knockoff framework for hybrid analysis of trio and population designs in genome-wide association studies. Am J Hum Genet 2024; 111:1448-1461. [PMID: 38821058 PMCID: PMC11267528 DOI: 10.1016/j.ajhg.2024.05.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Revised: 05/02/2024] [Accepted: 05/06/2024] [Indexed: 06/02/2024] Open
Abstract
Both trio and population designs are popular study designs for identifying risk genetic variants in genome-wide association studies (GWASs). The trio design, as a family-based design, is robust to confounding due to population structure, whereas the population design is often more powerful due to larger sample sizes. Here, we propose KnockoffHybrid, a knockoff-based statistical method for hybrid analysis of both the trio and population designs. KnockoffHybrid provides a unified framework that brings together the advantages of both designs and produces powerful hybrid analysis while controlling the false discovery rate (FDR) in the presence of linkage disequilibrium and population structure. Furthermore, KnockoffHybrid has the flexibility to leverage different types of summary statistics for hybrid analyses, including expression quantitative trait loci (eQTL) and GWAS summary statistics. We demonstrate in simulations that KnockoffHybrid offers power gains over non-hybrid methods for the trio and population designs with the same number of cases while controlling the FDR with complex correlation among variants and population structure among subjects. In hybrid analyses of three trio cohorts for autism spectrum disorders (ASDs) from the Autism Speaks MSSNG, Autism Sequencing Consortium, and Autism Genome Project with GWAS summary statistics from the iPSYCH project and eQTL summary statistics from the MetaBrain project, KnockoffHybrid outperforms conventional methods by replicating several known risk genes for ASDs and identifying additional associations with variants in other genes, including the PRAME family genes involved in axon guidance and which may act as common targets for human speech/language evolution and related disorders.
Collapse
Affiliation(s)
- Yi Yang
- Department of Biostatistics, City University of Hong Kong, Hong Kong SAR, China; School of Data Science, City University of Hong Kong, Hong Kong SAR, China.
| | - Qi Wang
- School of Data Science, City University of Hong Kong, Hong Kong SAR, China
| | - Chen Wang
- Department of Biostatistics, Columbia University, New York, NY 10032, USA
| | - Joseph Buxbaum
- Departments of Psychiatry, Neuroscience, and Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Iuliana Ionita-Laza
- Department of Biostatistics, Columbia University, New York, NY 10032, USA; Department of Statistics, Lund University, Lund, Sweden
| |
Collapse
|
3
|
Kendall C, Robinson J, Debortoli G, Nooranikhojasteh A, Christian D, Newman D, Sayers K, Cole S, Parra E, Schillaci M, Viola B. Global and local ancestry estimation in a captive baboon colony. PLoS One 2024; 19:e0305157. [PMID: 38959276 PMCID: PMC11221750 DOI: 10.1371/journal.pone.0305157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Accepted: 05/24/2024] [Indexed: 07/05/2024] Open
Abstract
The last couple of decades have highlighted the importance of studying hybridization, particularly among primate species, as it allows us to better understand our own evolutionary trajectory. Here, we report on genetic ancestry estimates using dense, full genome data from 881 olive (Papio anubus), yellow (Papio cynocephalus), or olive-yellow crossed captive baboons from the Southwest National Primate Research Center. We calculated global and local ancestry information, imputed low coverage genomes (n = 830) to improve marker quality, and updated the genetic resources of baboons available to assist future studies. We found evidence of historical admixture in some putatively purebred animals and identified errors within the Southwest National Primate Research Center pedigree. We also compared the outputs between two different phasing and imputation pipelines along with two different global ancestry estimation software. There was good agreement between the global ancestry estimation software, with R2 > 0.88, while evidence of phase switch errors increased depending on what phasing and imputation pipeline was used. We also generated updated genetic maps and created a concise set of ancestry informative markers (n = 1,747) to accurately obtain global ancestry estimates.
Collapse
Affiliation(s)
| | - Jacqueline Robinson
- Institute for Human Genetics, University of California, San Francisco, San Francisco, California, United States of America
| | - Guilherme Debortoli
- Department of Anthropology, University of Toronto Mississauga, Mississauga, Ontario, Canada
| | - Amin Nooranikhojasteh
- Epigenomics Lab, Princess Margaret Cancer Center, University Health Network, Toronto, Ontario, Canada
| | - Debbie Christian
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, Texas, United States of America
| | - Deborah Newman
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, Texas, United States of America
| | - Kenneth Sayers
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, Texas, United States of America
| | - Shelley Cole
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, Texas, United States of America
| | - Esteban Parra
- Department of Anthropology, University of Toronto Mississauga, Mississauga, Ontario, Canada
| | - Michael Schillaci
- Department of Anthropology, University of Toronto Scarborough, Scarborough, Ontario, Canada
| | - Bence Viola
- Department of Anthropology, University of Toronto, Toronto, Ontario, Canada
| |
Collapse
|
4
|
Roberts MC, Holt KE, Del Fiol G, Baccarelli AA, Allen CG. Precision public health in the era of genomics and big data. Nat Med 2024; 30:1865-1873. [PMID: 38992127 DOI: 10.1038/s41591-024-03098-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Accepted: 05/29/2024] [Indexed: 07/13/2024]
Abstract
Precision public health (PPH) considers the interplay between genetics, lifestyle and the environment to improve disease prevention, diagnosis and treatment on a population level-thereby delivering the right interventions to the right populations at the right time. In this Review, we explore the concept of PPH as the next generation of public health. We discuss the historical context of using individual-level data in public health interventions and examine recent advancements in how data from human and pathogen genomics and social, behavioral and environmental research, as well as artificial intelligence, have transformed public health. Real-world examples of PPH are discussed, emphasizing how these approaches are becoming a mainstay in public health, as well as outstanding challenges in their development, implementation and sustainability. Data sciences, ethical, legal and social implications research, capacity building, equity research and implementation science will have a crucial role in realizing the potential for 'precision' to enhance traditional public health approaches.
Collapse
Affiliation(s)
- Megan C Roberts
- Division of Pharmaceutical Outcomes and Policy, University of North Carolina Eshelman School of Pharmacy, Chapel Hill, NC, USA.
| | - Kathryn E Holt
- Department of Infection Biology, London School of Hygiene & Tropical Medicine, London, UK
- Department of Infectious Diseases, School of Translational Medicine, Monash University, Melbourne, Victoria, Australia
| | - Guilherme Del Fiol
- Biomedical Informatics, School of Medicine, University of Utah, Salt Lake City, UT, USA
| | - Andrea A Baccarelli
- Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Caitlin G Allen
- Department of Public Health Sciences, College of Medicine, Medical University of South Carolina, Charleston, SC, USA
| |
Collapse
|
5
|
Crowley JJ, Cappi C, Ochoa-Panaifo ME, Frederick RM, Kook M, Wiese AD, Rancourt D, Atkinson EG, Giusti-Rodriguez P, Anderberg JL, Abramowitz JS, Adorno VR, Aguirre C, Alves GS, Alves GS, Ancalade N, Arellano Espinosa AA, Arnold PD, Ayton DM, Barbosa IG, Castano LMB, Barrera CN, Berardo MC, Berrones D, Best JR, Bigdeli TB, Burton CL, Buxbaum JD, Callahan JL, Carneiro MCB, Cepeda SL, Chazelle E, Chire JM, Munoz MC, Quiroz PC, Cobite J, Comer JS, Costa DL, Crosbie J, Cruz VO, Dager G, Daza LF, de la Rosa-Gómez A, Del Río D, Delage FZ, Dreher CB, Fay L, Fazio T, Ferrão YA, Ferreira GM, Figueroa EG, Fontenelle LF, Forero DA, Fragoso DTH, Gadad BS, Garrison SR, González A, Gonzalez LD, González MA, Gonzalez-Barrios P, Goodman WK, Grice DE, Guintivano J, Guttfreund DG, Guzick AG, Halvorsen MW, Hovey JD, Huang H, Irreño-Sotomonte J, Janssen-Aguilar R, Jensen M, Jimenez Reynolds AZ, Lujambio JAJ, Khalfe N, Knutsen MA, Lack C, Lanzagorta N, Lima MO, Longhurst MO, Lozada Martinez DA, Luna ES, Marques AH, Martinez MS, de Los Angeles Matos M, Maye CE, McGuire JF, Menezes G, Minaya C, Miño T, Mithani SM, de Oca CM, Morales-Rivero A, Moreira-de-Oliveira ME, Morris OJ, Muñoz SI, Naqqash Z, Núñez Bracho AA, Núñez Bracho BE, Rojas MCO, Olavarria Castaman LA, Balmaceda TO, Ortega I, Patel DI, Patrick AK, Paz Y Mino M, Perales Orellana JL, Stumpf BP, Peregrina T, Duarte TP, Piacsek KL, Placencia M, Prieto MB, Quarantini LC, Quarantini-Alvim Y, Ramos RT, Ramos IC, Ramos VR, Ramsey KA, Ray EV, Richter MA, Riemann BC, Rivas JC, Rosario MC, Ruggero CJ, Ruiz-Chow AA, Ruiz-Velasco A, Sagarnaga MN, Sampaio AS, Saraiva LC, Schachar RJ, Schneider SC, Schweissing EJ, Seligman LD, Shavitt RG, Soileau KJ, Stewart SE, Storch SB, Strouphauer ER, Cuevas VT, Timpano KR, la Garza BTD, Vallejo-Silva A, Vargas-Medrano J, Vásquez MI, Martinez GV, Weinzimmer SA, Yanez MA, Zai G, Zapata-Restrepo LM, Zappa LM, Zepeda-Burgos RM, Zoghbi AW, Miguel EC, Rodriguez CI, Martinez Mallen MC, Moya PR, Borda T, Moyano MB, Mattheisen M, Pereira S, Lázaro-Muñoz G, Martinez-Gonzalez KG, Pato MT, Nicolini H, Storch EA. Latin American Trans-ancestry INitiative for OCD genomics (LATINO): Study protocol. Am J Med Genet B Neuropsychiatr Genet 2024; 195:e32962. [PMID: 37946624 PMCID: PMC11076176 DOI: 10.1002/ajmg.b.32962] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 09/26/2023] [Accepted: 10/06/2023] [Indexed: 11/12/2023]
Abstract
Obsessive-compulsive disorder (OCD) is a debilitating psychiatric disorder. Worldwide, its prevalence is ~2% and its etiology is mostly unknown. Identifying biological factors contributing to OCD will elucidate underlying mechanisms and might contribute to improved treatment outcomes. Genomic studies of OCD are beginning to reveal long-sought risk loci, but >95% of the cases currently in analysis are of homogenous European ancestry. If not addressed, this Eurocentric bias will result in OCD genomic findings being more accurate for individuals of European ancestry than other ancestries, thereby contributing to health disparities in potential future applications of genomics. In this study protocol paper, we describe the Latin American Trans-ancestry INitiative for OCD genomics (LATINO, https://www.latinostudy.org). LATINO is a new network of investigators from across Latin America, the United States, and Canada who have begun to collect DNA and clinical data from 5000 richly phenotyped OCD cases of Latin American ancestry in a culturally sensitive and ethical manner. In this project, we will utilize trans-ancestry genomic analyses to accelerate the identification of OCD risk loci, fine-map putative causal variants, and improve the performance of polygenic risk scores in diverse populations. We will also capitalize on rich clinical data to examine the genetics of treatment response, biologically plausible OCD subtypes, and symptom dimensions. Additionally, LATINO will help elucidate the diversity of the clinical presentations of OCD across cultures through various trainings developed and offered in collaboration with Latin American investigators. We believe this study will advance the important goal of global mental health discovery and equity.
Collapse
Affiliation(s)
- James J Crowley
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Carolina Cappi
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Departamento de Psiquiatria, Universidade de São Paulo, São Paulo, São Paulo, Brazil
| | | | - Renee M Frederick
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Minjee Kook
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Andrew D Wiese
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Diana Rancourt
- Department of Psychology, University of South Florida, Tampa, Florida, USA
| | - Elizabeth G Atkinson
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
| | - Paola Giusti-Rodriguez
- Department of Psychiatry, University of Florida College of Medicine, Gainesville, Florida, USA
| | - Jacey L Anderberg
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Jonathan S Abramowitz
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Victor R Adorno
- Hospital Psiquiátrico de Asunción, Direccion General, Asuncion, Central, Paraguay
| | - Cinthia Aguirre
- Departamento de Psiquiatría, Hospital Psiquiátrico de Asunción, Asuncion, Central, Paraguay
| | - Gilberto S Alves
- Hospital Nina Rodrigues/Universidade Federal do Maranhão (UFMA), Sao Luis do Maranhao, Maranhao, Brazil
| | - Gustavo S Alves
- Hospital Universitário Professor Edgard Santos, Serviço de Psiquiatria, Laboratório de Neuropsicofarmacologia-LANP, Universidade Federal da Bahia, Salvador, Bahia, Brazil
- Faculdade de Medicina da Bahia, Universidade Federal da Bahia, Pós-Graduação em Medicina e Saúde, Salvador, Bahia, Brazil
| | - NaEshia Ancalade
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | | | - Paul D Arnold
- The Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Daphne M Ayton
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Izabela G Barbosa
- Departamento de Saúde Mental da Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | | | | | - María Celeste Berardo
- Centro Interdisciplinario de Tourette, TOC, TDAH y Trastornos Asociados (CITA), Buenos Aires, Buenos Aires, Argentina
| | - Dayan Berrones
- Department of Psychology, Rice University, Houston, Texas, USA
| | - John R Best
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Tim B Bigdeli
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, New York, USA
- VA New York Harbor Healthcare System, Brooklyn, New York, USA
| | - Christie L Burton
- Department of Neurosciences and Mental Health, Hospital for Sick Children, Toronto, Ontario, Canada
| | - Joseph D Buxbaum
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | | | - Maria Cecília B Carneiro
- Departamento de Psiquiatria e Medicina Legal, Universidade Federal do Paraná, Curitiba, Parana, Brazil
| | - Sandra L Cepeda
- Department of Psychology, University of Miami, Coral Gables, Florida, USA
| | - Evelyn Chazelle
- Centro Interdisciplinario de Tourette, TOC, TDAH y Trastornos Asociados (CITA), Buenos Aires, Buenos Aires, Argentina
| | - Jessica M Chire
- Instituto Nacional de Salud Mental "Honorio Delgado-Hideyo Noguchi", Dirección de Niños y Adolescentes Lima, Lima, Peru
| | | | | | - Journa Cobite
- Department of Counseling Psychology, University of Houston, Houston, Texas, USA
| | - Jonathan S Comer
- Department of Psychology, Florida International University, Miami, Florida, USA
| | - Daniel L Costa
- Departamento de Psiquiatria, Universidade de São Paulo, São Paulo, São Paulo, Brazil
| | - Jennifer Crosbie
- Department of Neurosciences and Mental Health, Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Victor O Cruz
- Instituto Nacional de Salud Mental "Honorio Delgado-Hideyo Noguchi", Oficina Ejecutiva de Investigación, Lima, Lima, Peru
- School of Medicine, Universidad San Martin de Porres, Lima, Lima, Peru
| | - Guillermo Dager
- Corporación Universitaria Rafael Nuñez, Cartagena, Bolivar, Colombia
| | - Luisa F Daza
- Hospital Psiquiátrico Universitario Del Valle, Cali, Valle del Cauca, Colombia
| | - Anabel de la Rosa-Gómez
- Facultad de Estudios Superiores Iztacala, Tlalnepantla de Baz, Universidad Nacional Autónoma de México, Ciudad de Mexico, Mexico
| | | | - Fernanda Z Delage
- Departamento de Medicina Forense e Psiquiatria, Universidade Federal do Paraná, Curitiba, Parana, Brazil
| | - Carolina B Dreher
- Departamento de Psiquiatria, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
- Departamento de Psiquiatria, Clínica Médica, Porto Alegre, Rio Grande do Sul, Brazil
| | - Lucila Fay
- Centro Interdisciplinario de Tourette, TOC, TDAH y Trastornos Asociados (CITA), Buenos Aires, Buenos Aires, Argentina
| | - Tomas Fazio
- Centro Interdisciplinario de Tourette, TOC, TDAH y Trastornos Asociados (CITA), Buenos Aires, Buenos Aires, Argentina
| | - Ygor A Ferrão
- Departamento de Psiquiatria, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil
| | - Gabriela M Ferreira
- Departamento de Medicina Forense e Psiquiatria, Universidade Federal do Paraná, Curitiba, Parana, Brazil
- Hospital de Clínicas da Universidade Federal do Paraná, Curitiba, Parana, Brazil
| | - Edith G Figueroa
- Departamento de Psiquiatría de Adultos, Instituto Nacional de Salud Mental "Honorio Delgado-Hideyo Noguchi", Lima, Lima, Peru
| | - Leonardo F Fontenelle
- Departamento de Psiquiatria e Medicina Legal, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Rio de Janeiro, Brazil
- Departamento de Psiquiatria, Instituto D'Or de Pesquisa e Ensino, Rio de Janeiro, Rio de Janeiro, Brazil
| | - Diego A Forero
- Fundación Universitaria del Área Andina, Escuela de Salud y Ciencias del Deporte, Bogota, Bogota, Colombia
| | - Daniele T H Fragoso
- Departamento de Medicina Forense e Psiquiatria, Universidade Federal do Paraná, Curitiba, Parana, Brazil
| | - Bharathi S Gadad
- Department of Psychiatry, Texas Tech University Health Sciences Center El Paso, El Paso, Texas, USA
| | | | | | - Laura D Gonzalez
- Centro Interdisciplinario de Tourette, TOC, TDAH y Trastornos Asociados (CITA), Buenos Aires, Buenos Aires, Argentina
| | - Marco A González
- Facultad de Estudios Superiores Iztacala, Tlalnepantla de Baz, Universidad Nacional Autónoma de México, Ciudad de Mexico, Mexico
| | - Polaris Gonzalez-Barrios
- Departamento de Psiquiatría, Universidad de Puerto Rico, San Juan, Puerto Rico, USA
- Universidad de Puerto Rico Campus de Ciências Médicas, San Juan, Puerto Rico, USA
| | - Wayne K Goodman
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Dorothy E Grice
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Jerry Guintivano
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | | | - Andrew G Guzick
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Matthew W Halvorsen
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Joseph D Hovey
- Department of Psychological Science, The University of Texas Rio Grande Valley, Edinburg, Texas, USA
| | - Hailiang Huang
- Broad Institute of MIT and Harvard, Stanley Center for Psychiatric Research, Cambridge, Massachusetts, USA
| | - Jonathan Irreño-Sotomonte
- Center for Mental Health-Cersame, School of Medicine and Health Sciences, Universidad del Rosario, Bogota, District of Colombia, Colombia
| | - Reinhard Janssen-Aguilar
- Instituto Nacional de Neurología y Neurocirugía Manuel Velasco Suarez, Subdirección de Psiquiatría, Ciudad de México, Ciudad de Mexico, Mexico
| | - Matias Jensen
- Centro de Neurociencias, Universidad de Valparaíso, Valparaiso, Chile
| | | | | | - Nasim Khalfe
- Baylor College of Medicine, School of Medicine, Houston, Texas, USA
| | - Madison A Knutsen
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
- Department of Psychology, Augustana College, Rock Island, Illinois, USA
| | - Caleb Lack
- Department of Psychology, University of Central Oklahoma, Edmond, Oklahoma, USA
| | - Nuria Lanzagorta
- Departamento de Investigación Clínica, Grupo Médico Carracci, Ciudad de México, Ciudad de Mexico, Mexico
| | - Monicke O Lima
- Departamento de Psiquiatria, Universidade de São Paulo, São Paulo, São Paulo, Brazil
| | - Melanie O Longhurst
- Department of Psychiatry, Texas Tech University Health Sciences Center El Paso, El Paso, Texas, USA
| | | | - Elba S Luna
- Instituto Nacional de Salud Mental "Honorio Delgado-Hideyo Noguchi", Oficina Ejecutiva de Investigación, Lima, Lima, Peru
| | - Andrea H Marques
- National Institute of Mental Heatlh (NIMH), Bethesda, Maryland, USA
| | - Molly S Martinez
- DFW OCD Treatment Specialists, Richardson, Texas, USA
- Specialists in OCD and Anxiety Recovery (SOAR), Richardson, Texas, USA
| | - Maria de Los Angeles Matos
- Centro Interdisciplinario de Tourette, TOC, TDAH y Trastornos Asociados (CITA), Buenos Aires, Buenos Aires, Argentina
| | - Caitlyn E Maye
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Joseph F McGuire
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Gabriela Menezes
- Programa de Ansiedade, Obsessões e Compulsões, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Charlene Minaya
- Department of Psychology, Fordham University, New York, New York, USA
| | - Tomás Miño
- Centro de Neurociencias, Universidad de Valparaíso, Valparaiso, Chile
| | - Sara M Mithani
- School of Nursing, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | | | | | - Maria E Moreira-de-Oliveira
- Programa de Ansiedade, Obsessões e Compulsões, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Olivia J Morris
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Sandra I Muñoz
- Facultad de Estudios Superiores Iztacala, Tlalnepantla de Baz, Universidad Nacional Autónoma de México, Ciudad de Mexico, Mexico
| | - Zainab Naqqash
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | | | | | | | | | - Trinidad Olivos Balmaceda
- Centro Interdisciplinario de Neurociencia de Valparaíso, Universidad de Valparaíso, Valparaiso, Valparaiso, Chile
| | - Iliana Ortega
- The Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Darpan I Patel
- School of Nursing, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - Ainsley K Patrick
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Mariel Paz Y Mino
- Clínica de Salud Mental USFQ, Universidad San Francisco de Quito, Quito, Pichincha, Ecuador
- Universidad San Francisco de Quito, Quito, Pichincha, Ecuador
| | - Jose L Perales Orellana
- Universidad Tegnológica Privada de Santa Cruz (UTEPSA), Santa Cruz de la Sierra, Andres Ibañez, Bolivia
| | - Bárbara Perdigão Stumpf
- Departamento de Saúde Mental da Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | | | | | | | - Maritza Placencia
- Departamento Académico de Ciencias Dinámicas, Universidad Nacional Mayor de San Marcos, Lima, Lima, Peru
| | - María Belén Prieto
- Centro Interdisciplinario de Tourette, TOC, TDAH y Trastornos Asociados (CITA), Buenos Aires, Buenos Aires, Argentina
| | - Lucas C Quarantini
- Hospital Universitário Professor Edgard Santos, Serviço de Psiquiatria, Laboratório de Neuropsicofarmacologia-LANP, Universidade Federal da Bahia, Salvador, Bahia, Brazil
- Departamento de Neurociências e Saúde Mental, Faculdade de Medicina da Bahia, Universidade Federal da Bahia, Salvador, Bahia, Brazil
| | - Yana Quarantini-Alvim
- Hospital Universitário Professor Edgard Santos, Serviço de Psiquiatria, Laboratório de Neuropsicofarmacologia-LANP, Universidade Federal da Bahia, Salvador, Bahia, Brazil
- Faculdade Santa Casa, Faculdade de Psicologia, Salvador, Bahia, Brazil
| | - Renato T Ramos
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
- Department of Psychiatry, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Iaroslava C Ramos
- Department of Psychiatry, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
- Department of Psychiatry, Frederick Thompson Anxiety Disorders Centre, Toronto, Ontario, Canada
| | - Vanessa R Ramos
- Departamento de Psiquiatria, Universidade de São Paulo, São Paulo, São Paulo, Brazil
| | - Kesley A Ramsey
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Elise V Ray
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Margaret A Richter
- Department of Psychiatry, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | | | - Juan C Rivas
- Hospital Psiquiátrico Universitario Del Valle, Cali, Valle del Cauca, Colombia
- Departamento de Psiquiatría, Universidad del Valle, Cali, Valle del Cauca, Colombia
- Departamento de Psiquiatria, Universidad ICESI, Cali, Valle del Cauca, Colombia
- Departamento de Psiquiatria, Fundación Valle del Lili, Cali, Valle del Cauca, Colombia
| | - Maria C Rosario
- Departamento de Psiquiatria da, Universidade Federal de São Paulo (UNIFESP), Sao Paulo, Sao Paulo, Brazil
| | - Camilo J Ruggero
- Department of Psychology, University of North Texas, Denton, Texas, USA
| | | | - Alejandra Ruiz-Velasco
- Department of Psychiatry, Texas Tech University Health Sciences Center El Paso, El Paso, Texas, USA
| | - Melisa N Sagarnaga
- Facultad de Psicología, Universidad de Buenos Aires, Buenos Aires, Buenos Aires, Argentina
| | - Aline S Sampaio
- Hospital Universitário Professor Edgard Santos, Serviço de Psiquiatria, Laboratório de Neuropsicofarmacologia-LANP, Universidade Federal da Bahia, Salvador, Bahia, Brazil
- Faculdade de Medicina da Bahia, Universidade Federal da Bahia, Pós-Graduação em Medicina e Saúde, Salvador, Bahia, Brazil
- Departamento de Neurociências e Saúde Mental, Faculdade de Medicina da Bahia, Universidade Federal da Bahia, Salvador, Bahia, Brazil
| | - Leonardo C Saraiva
- Departamento de Psiquiatria, Universidade de São Paulo, São Paulo, São Paulo, Brazil
| | - Russell J Schachar
- Department of Neurosciences and Mental Health, Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Sophie C Schneider
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Ethan J Schweissing
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Laura D Seligman
- Department of Psychological Science, The University of Texas Rio Grande Valley, Edinburg, Texas, USA
| | - Roseli G Shavitt
- Departamento de Psiquiatria, Universidade de São Paulo, São Paulo, São Paulo, Brazil
| | - Keaton J Soileau
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - S Evelyn Stewart
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
- BC Mental Health and Substance Use Services, Vancouver, British Columbia, Canada
- BC Children's Hospital Research Institute, Vancouver, British Columbia, Canada
| | - Shaina B Storch
- Washington University in St. Louis, St. Louis, Missouri, USA
| | | | - Vissente Tapia Cuevas
- Centro Interdisciplinario de Neurociencia de Valparaíso, Universidad de Valparaíso, Valparaiso, Valparaiso, Chile
| | - Kiara R Timpano
- Department of Psychology, University of Miami, Coral Gables, Florida, USA
| | | | - Alexie Vallejo-Silva
- Center for Mental Health-Cersame, School of Medicine and Health Sciences, Universidad del Rosario, Bogota, District of Colombia, Colombia
| | - Javier Vargas-Medrano
- Department of Psychiatry, Texas Tech University Health Sciences Center El Paso, El Paso, Texas, USA
| | - María I Vásquez
- Hospital Nacional Arzobispo Loayza, Servicio de Salud Mental, Lima, Lima, Peru
| | - Guadalupe Vidal Martinez
- Department of Psychiatry, Texas Tech University Health Sciences Center El Paso, El Paso, Texas, USA
| | - Saira A Weinzimmer
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Mauricio A Yanez
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Gwyneth Zai
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Department of Molecular Brain Sciences, Centre for Addiction and Mental Health, Neurogenetics Section, Toronto, Ontario, Canada
| | - Lina M Zapata-Restrepo
- Departamento de Psiquiatria, Fundación Valle del Lili, Cali, Valle del Cauca, Colombia
- Facultad de Ciencias de la Salud, Universidad ICESI, Cali, Valle, Colombia
- Department of Neurology, Global Brain Health Institute-University of California San Francisco, San Francisco, California, USA
| | - Luz M Zappa
- Centro Interdisciplinario de Tourette, TOC, TDAH y Trastornos Asociados (CITA), Buenos Aires, Buenos Aires, Argentina
- Departamento de Salud Mental, Hospital de Niños Ricardo Gutierrez, Buenos Aires, Buenos Aires, Argentina
- Hospital Universitario Austral, Materno Infantil, Buenos Aires, Buenos Aires, Argentina
| | - Raquel M Zepeda-Burgos
- Centro de Investigación en Ciencias y Humanidades, Universidad Dr. José Matías Delgado, Santa Tecla, La Libertad, El Salvador
| | - Anthony W Zoghbi
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
- Department of Psychiatry, New York State Psychiatric Institute, New York, New York, USA
| | - Euripedes C Miguel
- Departamento de Psiquiatria, Universidade de São Paulo, São Paulo, São Paulo, Brazil
| | - Carolyn I Rodriguez
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California, USA
- Department of Psychiatry, Temerty Faculty of Medicine, Veterans Affairs Palo Alto Health Care System, Palo Alto, California, USA
| | | | - Pablo R Moya
- Universidad de Valparaíso, Instituto de Fisiología Valparaiso, Valparaiso, Chile
- Centro Interdisciplinario de Neurociencia de Valparaiso (CINV), Valparaiso, Chile
| | - Tania Borda
- Instituto Realize, Buenos Aires, Buenos Aires, Argentina
- Facultad de Psicología, Universidad Catolica Argentina, Buenos Aires, Buenos Aires, Argentina
| | - María Beatriz Moyano
- Centro Interdisciplinario de Tourette, TOC, TDAH y Trastornos Asociados (CITA), Buenos Aires, Buenos Aires, Argentina
- Asociación de Psiquiatras Argentinos (APSA), Buenos Aires, Buenos Aires, Argentina
- Asociación de Psiquiatras Argentinos (APSA), Presidente del Capítulo de Investigacion en Psiquiatria, Buenos Aires, Buenos Aires, Argentina
| | - Manuel Mattheisen
- Department of Community Health and Epidemiology & Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada
- LMU Munich, Institute of Psychiatric Phenomics and Genomics (IPPG), Munich, Germany
| | - Stacey Pereira
- Baylor College of Medicine, Center for Medical Ethics and Health Policy, Houston, Texas, USA
| | - Gabriel Lázaro-Muñoz
- Center for Bioethics, Harvard University School of Medicine, Boston, Massachusetts, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA
| | | | - Michele T Pato
- Department of Psychiatry, Rutgers University-Robert Wood Johnson Medical School, Piscataway, New Jersey, USA
| | - Humberto Nicolini
- Departamento de Psiquiatría, Ciudad de México, Grupo Médico Carracci, Ciudad de Mexico, Mexico
- Laboratorio de Genómica de Enfermedades Psiquiátricas y Neurodegenerativas, Ciudad de México, Instituto Nacional de Medicina Genómica, Ciudad de Mexico, Mexico
| | - Eric A Storch
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| |
Collapse
|
6
|
Smith JL, Tcheandjieu C, Dikilitas O, Iyer K, Miyazawa K, Hilliard A, Lynch J, Rotter JI, Chen YDI, Sheu WHH, Chang KM, Kanoni S, Tsao PS, Ito K, Kosel M, Clarke SL, Schaid DJ, Assimes TL, Kullo IJ. Multi-Ancestry Polygenic Risk Score for Coronary Heart Disease Based on an Ancestrally Diverse Genome-Wide Association Study and Population-Specific Optimization. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2024; 17:e004272. [PMID: 38380516 DOI: 10.1161/circgen.123.004272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Accepted: 01/23/2024] [Indexed: 02/22/2024]
Abstract
BACKGROUND Predictive performance of polygenic risk scores (PRS) varies across populations. To facilitate equitable clinical use, we developed PRS for coronary heart disease (CHD; PRSCHD) for 5 genetic ancestry groups. METHODS We derived ancestry-specific and multi-ancestry PRSCHD based on pruning and thresholding (PRSPT) and ancestry-based continuous shrinkage priors (PRSCSx) applied to summary statistics from the largest multi-ancestry genome-wide association study meta-analysis for CHD to date, including 1.1 million participants from 5 major genetic ancestry groups. Following training and optimization in the Million Veteran Program, we evaluated the best-performing PRSCHD in 176,988 individuals across 9 diverse cohorts. RESULTS Multi-ancestry PRSPT and PRSCSx outperformed ancestry-specific PRSPT and PRSCSx across a range of tuning values. Two best-performing multi-ancestry PRSCHD (ie, PRSPTmult and PRSCSxmult) and 1 ancestry-specific (PRSCSxEUR) were taken forward for validation. PRSPTmult demonstrated the strongest association with CHD in individuals of South Asian ancestry and European ancestry (odds ratio per 1 SD [95% CI, 2.75 [2.41-3.14], 1.65 [1.59-1.72]), followed by East Asian ancestry (1.56 [1.50-1.61]), Hispanic/Latino ancestry (1.38 [1.24-1.54]), and African ancestry (1.16 [1.11-1.21]). PRSCSxmult showed the strongest associations in South Asian ancestry (2.67 [2.38-3.00]) and European ancestry (1.65 [1.59-1.71]), lower in East Asian ancestry (1.59 [1.54-1.64]), Hispanic/Latino ancestry (1.51 [1.35-1.69]), and the lowest in African ancestry (1.20 [1.15-1.26]). CONCLUSIONS The use of summary statistics from a large multi-ancestry genome-wide meta-analysis improved the performance of PRSCHD in most ancestry groups compared with single-ancestry methods. Despite the use of one of the largest and most diverse sets of training and validation cohorts to date, improvement of predictive performance was limited in African ancestry. This highlights the need for larger genome-wide association study datasets of underrepresented populations to enhance the performance of PRSCHD.
Collapse
Affiliation(s)
- Johanna L Smith
- Department of Cardiovascular Medicine (J.L.S., O.D., I.J.K.), Mayo Clinic, Rochester, MN
| | - Catherine Tcheandjieu
- Department of Epidemiology and Biostatistics, University of California San Francisco (C.T.)
- Gladstone Institute of Data Science and Biotechnology, Gladstone Institute, San Francisco, CA (C.T.)
- VA Palo Alto Health Care System (C.T., A.H., P.S.T., S.L.C.)
| | - Ozan Dikilitas
- Department of Cardiovascular Medicine (J.L.S., O.D., I.J.K.), Mayo Clinic, Rochester, MN
| | - Kruthika Iyer
- Stanford University School of Medicine, Palo Alto, CA (K. Iyer, A.H.)
| | - Kazuo Miyazawa
- Riken Center for Integrative Medical Sciences, Yokohama City, Japan (K.M., K. Ito)
| | - Austin Hilliard
- VA Palo Alto Health Care System (C.T., A.H., P.S.T., S.L.C.)
- Stanford University School of Medicine, Palo Alto, CA (K. Iyer, A.H.)
| | | | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA (J.I.R., Y.-D.I.C.)
| | - Yii-Der Ida Chen
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA (J.I.R., Y.-D.I.C.)
| | - Wayne Huey-Herng Sheu
- Institute of Molecular and Genomic Medicine, National Health Research Institute (W.H.-H.S.)
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taipei Veterans General Hospital (W.H.-H.S.)
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taiwan (W.H.-H.S.)
| | - Kyong-Mi Chang
- Corporal Michael J Crescenz VA Medical Center, Philadelphia, PA (K.-M.C.)
| | - Stavroula Kanoni
- Queen Mary University of London, Cambridge, United Kingdom (S.K.)
| | - Philip S Tsao
- VA Palo Alto Health Care System (C.T., A.H., P.S.T., S.L.C.)
- Stanford University, Stanford, CA (P.S.T., S.L.C., T.L.A.)
| | - Kaoru Ito
- Riken Center for Integrative Medical Sciences, Yokohama City, Japan (K.M., K. Ito)
| | - Matthew Kosel
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN (M.K., D.J.S.)
| | - Shoa L Clarke
- VA Palo Alto Health Care System (C.T., A.H., P.S.T., S.L.C.)
- Stanford University, Stanford, CA (P.S.T., S.L.C., T.L.A.)
| | - Daniel J Schaid
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN (M.K., D.J.S.)
| | | | - Iftikhar J Kullo
- Department of Cardiovascular Medicine (J.L.S., O.D., I.J.K.), Mayo Clinic, Rochester, MN
| |
Collapse
|
7
|
Step K, Ndong Sima CAA, Mata I, Bardien S. Exploring the role of underrepresented populations in polygenic risk scores for neurodegenerative disease risk prediction. Front Neurosci 2024; 18:1380860. [PMID: 38859922 PMCID: PMC11163124 DOI: 10.3389/fnins.2024.1380860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 05/14/2024] [Indexed: 06/12/2024] Open
Affiliation(s)
- Kathryn Step
- Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Carene Anne Alene Ndong Sima
- Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Ignacio Mata
- Genomic Medicine, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, United States
| | - Soraya Bardien
- Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
- South African Medical Research Council/Stellenbosch University Genomics of Brain Disorders Research Unit, Stellenbosch University, Cape Town, South Africa
| |
Collapse
|
8
|
Miranda JP, Pereira A, Corvalán C, Miquel JF, Alberti G, Gana JC, Santos JL. Genetic determinants of serum bilirubin using inferred native American gene variants in Chilean adolescents. Front Genet 2024; 15:1382103. [PMID: 38826804 PMCID: PMC11140026 DOI: 10.3389/fgene.2024.1382103] [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: 02/05/2024] [Accepted: 04/18/2024] [Indexed: 06/04/2024] Open
Abstract
Gene variants in the UGT1A1 gene are strongly associated with circulating bilirubin levels in several populations, as well as other variants of modest effect across the genome. However, the effects of such variants are unknown regarding the Native American ancestry of the admixed Latino population. Our objective was to assess the Native American genetic determinants of serum bilirubin in Chilean admixed adolescents using the local ancestry deconvolution approach. We measured total serum bilirubin levels in 707 adolescents of the Chilean Growth and Obesity Cohort Study (GOCS) and performed high-density genotyping using the Illumina-MEGA array (>1.7 million genotypes). We constructed a local ancestry reference panel with participants from the 1000 Genomes Project, the Human Genome Diversity Project, and our GOCS cohort. Then, we inferred and isolated haplotype tracts of Native American, European, or African origin to perform genome-wide association studies. In the whole cohort, the rs887829 variant and others near UGT1A1 were the unique signals achieving genome-wide statistical significance (b = 0.30; p = 3.34 × 10-57). After applying deconvolution methods, we found that significance is also maintained in Native American (b = 0.35; p = 3.29 × 10-17) and European (b = 0.28; p = 1.14 × 10-23) ancestry components. The rs887829 variant explained a higher percentage of the variance of bilirubin in the Native American (37.6%) compared to European ancestry (28.4%). In Native American ancestry, carriers of the TT genotype of this variant averaged 4-fold higher bilirubinemia compared to the CC genotype (p = 2.82 × 10-12). We showed for the first time that UGT1A1 variants are the primary determinant of bilirubin levels in Native American ancestry, confirming its pan-ethnic relevance. Our study illustrates the general value of the local ancestry deconvolution approach to assessing isolated ancestry effects in admixed populations.
Collapse
Affiliation(s)
- José P. Miranda
- Department of Nutrition, Diabetes, and Metabolism, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
- School of Medicine, PhD in Epidemiology Program, Pontificia Universidad Católica de Chile, Santiago, Chile
- Advanced Center for Chronic Diseases (ACCDiS), Pontificia Universidad Católica de Chile and Universidad de Chile, Santiago, Chile
| | - Ana Pereira
- Instituto de Nutrición y Tecnología de los Alimentos INTA, Universidad de Chile, Santiago, Chile
| | - Camila Corvalán
- Instituto de Nutrición y Tecnología de los Alimentos INTA, Universidad de Chile, Santiago, Chile
| | - Juan F. Miquel
- Department of Gastroenterology, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Gigliola Alberti
- Pediatrics Division, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
- Department of Gastroenterology and Pediatric Nutrition, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Juan C. Gana
- Pediatrics Division, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
- Department of Gastroenterology and Pediatric Nutrition, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - José L. Santos
- Department of Nutrition, Diabetes, and Metabolism, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
- School of Medicine, PhD in Epidemiology Program, Pontificia Universidad Católica de Chile, Santiago, Chile
| |
Collapse
|
9
|
Saffie Awad P, Makarious MB, Elsayed I, Sanyaolu A, Wild Crea P, Schumacher Schuh AF, Levine KS, Vitale D, Korestky MJ, Kim J, Peixoto Leal T, Perinan MT, Dey S, Noyce AJ, Reyes-Palomares A, Rodriguez-Losada N, Foo JN, Mohamed W, Heilbron K, Norcliffe-Kaufmann L, Rizig M, Okubadejo N, Nalls M, Blauwendraat C, Singleton A, Leonard H, Mata IF, Bandres Ciga S. Insights into Ancestral Diversity in Parkinsons Disease Risk: A Comparative Assessment of Polygenic Risk Scores. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.11.28.23299090. [PMID: 38076954 PMCID: PMC10705647 DOI: 10.1101/2023.11.28.23299090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
Objectives To evaluate and compare different polygenic risk score (PRS) models in predicting Parkinsons disease (PD) across diverse ancestries, focusing on identifying the most suitable approach for each population and potentially contributing to equitable advancements in precision medicine. Methods We constructed a total of 105 PRS across individual level data from seven diverse ancestries. First, a cross-ancestry conventional PRS comparison was implemented by utilizing the 90 known European risk loci with weighted effects from four independent summary statistics including European, East Asian, Latino/Admixed American, and African/Admixed. These models were adjusted by sex, age, and principal components (28 PRS) and by sex, age, and percentage of admixture (28 PRS) for comparison. Secondly, a novel and refined multi-ancestry best-fit PRS approach was then applied across the seven ancestries by leveraging multi-ancestry meta-analyzed summary statistics and using a p-value thresholding approach (49 PRS) to enhance prediction applicability in a global setting. Results European-based PRS models predicted disease status across all ancestries to differing degrees of accuracy. Ashkenazi Jewish had the highest Odds Ratio (OR): 1.96 (95% CI: 1.69-2.25, p < 0.0001) with an AUC (Area Under the Curve) of 68%. Conversely, the East Asian population, despite having fewer predictive variants (84 out of 90), had an OR of 1.37 (95% CI: 1.32-1.42) and an AUC of 62%, illustrating the cross-ancestry transferability of this model. Lower OR alongside broader confidence intervals were observed in other populations, including Africans (OR =1.38, 95% CI: 1.12-1.63, p=0.001). Adjustment by percentage of admixture did not outperform principal components. Multi-ancestry best-fit PRS models improved risk prediction in European, Ashkenazi Jewish, and African ancestries, yet didn't surpass conventional PRS in admixed populations such as Latino/American admixed and African admixed populations. Interpretation The present study represents a novel and comprehensive assessment of PRS performance across seven ancestries in PD, highlighting the inadequacy of a 'one size fits all' approach in genetic risk prediction. We demonstrated that European based PD PRS models are partially transferable to other ancestries and could be improved by a novel best-fit multi-ancestry PRS, especially in non-admixed populations.
Collapse
|
10
|
Verhoef E, Allegrini AG, Jansen PR, Lange K, Wang CA, Morgan AT, Ahluwalia TS, Symeonides C, Eising E, Franken MC, Hypponen E, Mansell T, Olislagers M, Omerovic E, Rimfeld K, Schlag F, Selzam S, Shapland CY, Tiemeier H, Whitehouse AJO, Saffery R, Bønnelykke K, Reilly S, Pennell CE, Wake M, Cecil CAM, Plomin R, Fisher SE, St Pourcain B. Genome-Wide Analyses of Vocabulary Size in Infancy and Toddlerhood: Associations With Attention-Deficit/Hyperactivity Disorder, Literacy, and Cognition-Related Traits. Biol Psychiatry 2024; 95:859-869. [PMID: 38070845 DOI: 10.1016/j.biopsych.2023.11.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 11/26/2023] [Accepted: 11/29/2023] [Indexed: 02/17/2024]
Abstract
BACKGROUND The number of words children produce (expressive vocabulary) and understand (receptive vocabulary) changes rapidly during early development, partially due to genetic factors. Here, we performed a meta-genome-wide association study of vocabulary acquisition and investigated polygenic overlap with literacy, cognition, developmental phenotypes, and neurodevelopmental conditions, including attention-deficit/hyperactivity disorder (ADHD). METHODS We studied 37,913 parent-reported vocabulary size measures (English, Dutch, Danish) for 17,298 children of European descent. Meta-analyses were performed for early-phase expressive (infancy, 15-18 months), late-phase expressive (toddlerhood, 24-38 months), and late-phase receptive (toddlerhood, 24-38 months) vocabulary. Subsequently, we estimated single nucleotide polymorphism-based heritability (SNP-h2) and genetic correlations (rg) and modeled underlying factor structures with multivariate models. RESULTS Early-life vocabulary size was modestly heritable (SNP-h2 = 0.08-0.24). Genetic overlap between infant expressive and toddler receptive vocabulary was negligible (rg = 0.07), although each measure was moderately related to toddler expressive vocabulary (rg = 0.69 and rg = 0.67, respectively), suggesting a multifactorial genetic architecture. Both infant and toddler expressive vocabulary were genetically linked to literacy (e.g., spelling: rg = 0.58 and rg = 0.79, respectively), underlining genetic similarity. However, a genetic association of early-life vocabulary with educational attainment and intelligence emerged only during toddlerhood (e.g., receptive vocabulary and intelligence: rg = 0.36). Increased ADHD risk was genetically associated with larger infant expressive vocabulary (rg = 0.23). Multivariate genetic models in the ALSPAC (Avon Longitudinal Study of Parents and Children) cohort confirmed this finding for ADHD symptoms (e.g., at age 13; rg = 0.54) but showed that the association effect reversed for toddler receptive vocabulary (rg = -0.74), highlighting developmental heterogeneity. CONCLUSIONS The genetic architecture of early-life vocabulary changes during development, shaping polygenic association patterns with later-life ADHD, literacy, and cognition-related traits.
Collapse
Affiliation(s)
- Ellen Verhoef
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands.
| | - Andrea G Allegrini
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Philip R Jansen
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center, Rotterdam, the Netherlands; Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit, Amsterdam, the Netherlands; Section Clinical Genetics, Department Human Genetics, Amsterdam University Medical Centers, Amsterdam, the Netherlands
| | - Katherine Lange
- Murdoch Children's Research Institute, Parkville, Victoria, Australia; Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia
| | - Carol A Wang
- School of Medicine and Public Health, The University of Newcastle, Newcastle, New South Wales, Australia; Mothers and Babies Research Program, Hunter Medical Research Institute, Newcastle, New South Wales, Australia
| | - Angela T Morgan
- Murdoch Children's Research Institute, Parkville, Victoria, Australia; Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia; Department of Audiology and Speech Pathology, University of Melbourne, Parkville, Victoria, Australia; Royal Children's Hospital, Melbourne, Victoria, Australia
| | - Tarunveer S Ahluwalia
- Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark; Steno Diabetes Center Copenhagen, Herlev, Denmark; Bioinformatics Center, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Christos Symeonides
- Murdoch Children's Research Institute, Parkville, Victoria, Australia; Royal Children's Hospital, Melbourne, Victoria, Australia; Minderoo Foundation, Perth, Western Australia, Australia
| | - Else Eising
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands
| | - Marie-Christine Franken
- Erasmus University Medical Center, Sophia Children's Hospital, Department of Otorhinolaryngology and Head and Neck Surgery, Rotterdam, the Netherlands
| | - Elina Hypponen
- Australian Centre for Precision Health, Unit of Clinical and Health Sciences, University of South Australia, Adelaide, South Australia, Australia; South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
| | - Toby Mansell
- Murdoch Children's Research Institute, Parkville, Victoria, Australia; Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia
| | - Mitchell Olislagers
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands; Department of Urology, Erasmus University Medical Center, Erasmus University Medical Center Cancer Institute, Rotterdam, the Netherlands
| | - Emina Omerovic
- Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Kaili Rimfeld
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; Department of Psychology, Royal Holloway University of London, London, UK
| | - Fenja Schlag
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands
| | - Saskia Selzam
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Chin Yang Shapland
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK; Population Health Sciences, University of Bristol, Bristol, UK
| | - Henning Tiemeier
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center, Rotterdam, the Netherlands; Harvard, T.H. Chan School of Public Health, Boston, Massachusetts
| | - Andrew J O Whitehouse
- Telethon Kids Institute, The University of Western Australia, Perth, Western Australia, Australia
| | - Richard Saffery
- Murdoch Children's Research Institute, Parkville, Victoria, Australia; Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia; Chongqing Medical University, Chongqing, China
| | - Klaus Bønnelykke
- Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Sheena Reilly
- Murdoch Children's Research Institute, Parkville, Victoria, Australia; Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia; Menzies Health Institute Queensland, Griffith University, Brisbane, Queensland, Australia
| | - Craig E Pennell
- School of Medicine and Public Health, The University of Newcastle, Newcastle, New South Wales, Australia; Mothers and Babies Research Program, Hunter Medical Research Institute, Newcastle, New South Wales, Australia; Maternity and Gynaecology John Hunter Hospital, Newcastle, New South Wales, Australia
| | - Melissa Wake
- Murdoch Children's Research Institute, Parkville, Victoria, Australia; Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia; Liggins Institute, The University of Auckland, Grafton, New Zealand
| | - Charlotte A M Cecil
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center, Rotterdam, the Netherlands; Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands; Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - Robert Plomin
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Simon E Fisher
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands; Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Beate St Pourcain
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands; Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK; Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands.
| |
Collapse
|
11
|
Kronzer VL, Sparks JA, Raychaudhuri S, Cerhan JR. Low-frequency and rare genetic variants associated with rheumatoid arthritis risk. Nat Rev Rheumatol 2024; 20:290-300. [PMID: 38538758 DOI: 10.1038/s41584-024-01096-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/20/2024] [Indexed: 04/28/2024]
Abstract
Rheumatoid arthritis (RA) has an estimated heritability of nearly 50%, which is particularly high in seropositive RA. HLA alleles account for a large proportion of this heritability, in addition to many common single-nucleotide polymorphisms with smaller individual effects. Low-frequency and rare variants, such as those captured by next-generation sequencing, can also have a large role in heritability in some individuals. Rare variant discovery has informed the development of drugs such as inhibitors of PCSK9 and Janus kinases. Some 34 low-frequency and rare variants are currently associated with RA risk. One variant (19:10352442G>C in TYK2) was identified in five separate studies, and might therefore represent a promising therapeutic target. Following a set of best practices in future studies, including studying diverse populations, using large sample sizes, validating RA and serostatus, replicating findings, adjusting for other variants and performing functional assessment, could help to ensure the relevance of identified variants. Exciting opportunities are now on the horizon for genetics in RA, including larger datasets and consortia, whole-genome sequencing and direct applications of findings in the management, and especially treatment, of RA.
Collapse
Affiliation(s)
| | - Jeffrey A Sparks
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Soumya Raychaudhuri
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - James R Cerhan
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| |
Collapse
|
12
|
Troubat L, Fettahoglu D, Henches L, Aschard H, Julienne H. Multi-trait GWAS for diverse ancestries: mapping the knowledge gap. BMC Genomics 2024; 25:375. [PMID: 38627641 PMCID: PMC11022331 DOI: 10.1186/s12864-024-10293-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 04/09/2024] [Indexed: 04/19/2024] Open
Abstract
BACKGROUND Approximately 95% of samples analyzed in univariate genome-wide association studies (GWAS) are of European ancestry. This bias toward European ancestry populations in association screening also exists for other analyses and methods that are often developed and tested on European ancestry only. However, existing data in non-European populations, which are often of modest sample size, could benefit from innovative approaches as recently illustrated in the context of polygenic risk scores. METHODS Here, we extend and assess the potential limitations and gains of our multi-trait GWAS pipeline, JASS (Joint Analysis of Summary Statistics), for the analysis of non-European ancestries. To this end, we conducted the joint GWAS of 19 hematological traits and glycemic traits across five ancestries (European (EUR), admixed American (AMR), African (AFR), East Asian (EAS), and South-East Asian (SAS)). RESULTS We detected 367 new genome-wide significant associations in non-European populations (15 in Admixed American (AMR), 72 in African (AFR) and 280 in East Asian (EAS)). New associations detected represent 5%, 17% and 13% of associations in the AFR, AMR and EAS populations, respectively. Overall, multi-trait testing increases the replication of European associated loci in non-European ancestry by 15%. Pleiotropic effects were highly similar at significant loci across ancestries (e.g. the mean correlation between multi-trait genetic effects of EUR and EAS ancestries was 0.88). For hematological traits, strong discrepancies in multi-trait genetic effects are tied to known evolutionary divergences: the ARKC1 loci, which is adaptive to overcome p.vivax induced malaria. CONCLUSIONS Multi-trait GWAS can be a valuable tool to narrow the genetic knowledge gap between European and non-European populations.
Collapse
Affiliation(s)
- Lucie Troubat
- Department of Computational Biology, Institut Pasteur, Université Paris Cité, Paris, F-75015, France
| | - Deniz Fettahoglu
- Department of Computational Biology, Institut Pasteur, Université Paris Cité, Paris, F-75015, France
| | - Léo Henches
- Department of Computational Biology, Institut Pasteur, Université Paris Cité, Paris, F-75015, France
| | - Hugues Aschard
- Department of Computational Biology, Institut Pasteur, Université Paris Cité, Paris, F-75015, France
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Hanna Julienne
- Department of Computational Biology, Institut Pasteur, Université Paris Cité, Paris, F-75015, France.
- Institut Pasteur, Université Paris Cité, Bioinformatics and Biostatistics Hub, Paris, F-75015, France.
| |
Collapse
|
13
|
Lu Z, Wang X, Carr M, Kim A, Gazal S, Mohammadi P, Wu L, Gusev A, Pirruccello J, Kachuri L, Mancuso N. Improved multi-ancestry fine-mapping identifies cis-regulatory variants underlying molecular traits and disease risk. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.15.24305836. [PMID: 38699369 PMCID: PMC11065034 DOI: 10.1101/2024.04.15.24305836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
Multi-ancestry statistical fine-mapping of cis-molecular quantitative trait loci (cis-molQTL) aims to improve the precision of distinguishing causal cis-molQTLs from tagging variants. However, existing approaches fail to reflect shared genetic architectures. To solve this limitation, we present the Sum of Shared Single Effects (SuShiE) model, which leverages LD heterogeneity to improve fine-mapping precision, infer cross-ancestry effect size correlations, and estimate ancestry-specific expression prediction weights. We apply SuShiE to mRNA expression measured in PBMCs (n=956) and LCLs (n=814) together with plasma protein levels (n=854) from individuals of diverse ancestries in the TOPMed MESA and GENOA studies. We find SuShiE fine-maps cis-molQTLs for 16% more genes compared with baselines while prioritizing fewer variants with greater functional enrichment. SuShiE infers highly consistent cis-molQTL architectures across ancestries on average; however, we also find evidence of heterogeneity at genes with predicted loss-of-function intolerance, suggesting that environmental interactions may partially explain differences in cis-molQTL effect sizes across ancestries. Lastly, we leverage estimated cis-molQTL effect-sizes to perform individual-level TWAS and PWAS on six white blood cell-related traits in AOU Biobank individuals (n=86k), and identify 44 more genes compared with baselines, further highlighting its benefits in identifying genes relevant for complex disease risk. Overall, SuShiE provides new insights into the cis-genetic architecture of molecular traits.
Collapse
Affiliation(s)
- Zeyun Lu
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Xinran Wang
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Matthew Carr
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Artem Kim
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Steven Gazal
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA
| | - Pejman Mohammadi
- Center for Immunity and Immunotherapies, Seattle Children’s Research Institute, Seattle, WA, USA
- Department of Pediatrics, University of Washington School of Medicine, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Lang Wu
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaiʻi Cancer Center, University of Hawaiʻi at Mānoa, Honolulu, HI, USA
| | - Alexander Gusev
- Harvard Medical School and Dana-Farber Cancer Institute, Boston, MA, USA
| | - James Pirruccello
- Division of Cardiology, University of California San Francisco, San Francisco, CA, USA
| | - Linda Kachuri
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Nicholas Mancuso
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA
| |
Collapse
|
14
|
Hou K, Gogarten S, Kim J, Hua X, Dias JA, Sun Q, Wang Y, Tan T, Atkinson EG, Martin A, Shortt J, Hirbo J, Li Y, Pasaniuc B, Zhang H. Admix-kit: an integrated toolkit and pipeline for genetic analyses of admixed populations. Bioinformatics 2024; 40:btae148. [PMID: 38490256 PMCID: PMC10980565 DOI: 10.1093/bioinformatics/btae148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 02/08/2024] [Accepted: 03/13/2024] [Indexed: 03/17/2024] Open
Abstract
SUMMARY Admixed populations, with their unique and diverse genetic backgrounds, are often underrepresented in genetic studies. This oversight not only limits our understanding but also exacerbates existing health disparities. One major barrier has been the lack of efficient tools tailored for the special challenges of genetic studies of admixed populations. Here, we present admix-kit, an integrated toolkit and pipeline for genetic analyses of admixed populations. Admix-kit implements a suite of methods to facilitate genotype and phenotype simulation, association testing, genetic architecture inference, and polygenic scoring in admixed populations. AVAILABILITY AND IMPLEMENTATION Admix-kit package is open-source and available at https://github.com/KangchengHou/admix-kit. Additionally, users can use the pipeline designed for admixed genotype simulation available at https://github.com/UW-GAC/admix-kit_workflow.
Collapse
Affiliation(s)
- Kangcheng Hou
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, United States
| | - Stephanie Gogarten
- Department of Biostatistics, University of Washington, Seattle, WA, 98195, United States
| | - Joohyun Kim
- Vanderbilt Genetics Institute and Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, 37232, United States
| | - Xing Hua
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, 20892, United States
| | - Julie-Alexia Dias
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02120, United States
| | - Quan Sun
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, United States
| | - Ying Wang
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, United States
| | - Taotao Tan
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, United States
| | - Elizabeth G Atkinson
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, United States
| | - Alicia Martin
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, United States
| | - Jonathan Shortt
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, United States
| | - Jibril Hirbo
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, 37232, United States
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, United States
| | - Bogdan Pasaniuc
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, United States
| | - Haoyu Zhang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, 20892, United States
| |
Collapse
|
15
|
Tissink EP, Shadrin AA, van der Meer D, Parker N, Hindley G, Roelfs D, Frei O, Fan CC, Nagel M, Nærland T, Budisteanu M, Djurovic S, Westlye LT, van den Heuvel MP, Posthuma D, Kaufmann T, Dale AM, Andreassen OA. Abundant pleiotropy across neuroimaging modalities identified through a multivariate genome-wide association study. Nat Commun 2024; 15:2655. [PMID: 38531894 DOI: 10.1038/s41467-024-46817-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 03/12/2024] [Indexed: 03/28/2024] Open
Abstract
Genetic pleiotropy is abundant across spatially distributed brain characteristics derived from one neuroimaging modality (e.g. structural, functional or diffusion magnetic resonance imaging [MRI]). A better understanding of pleiotropy across modalities could inform us on the integration of brain function, micro- and macrostructure. Here we show extensive genetic overlap across neuroimaging modalities at a locus and gene level in the UK Biobank (N = 34,029) and ABCD Study (N = 8607). When jointly analysing phenotypes derived from structural, functional and diffusion MRI in a genome-wide association study (GWAS) with the Multivariate Omnibus Statistical Test (MOSTest), we boost the discovery of loci and genes beyond previously identified effects for each modality individually. Cross-modality genes are involved in fundamental biological processes and predominantly expressed during prenatal brain development. We additionally boost prediction of psychiatric disorders by conditioning independent GWAS on our multimodal multivariate GWAS. These findings shed light on the shared genetic mechanisms underlying variation in brain morphology, functional connectivity, and tissue composition.
Collapse
Affiliation(s)
- E P Tissink
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, The Netherlands.
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience, an institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands.
| | - A A Shadrin
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Building 48, Oslo, Norway
| | - D van der Meer
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Building 48, Oslo, Norway
- School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - N Parker
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Building 48, Oslo, Norway
| | - G Hindley
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Building 48, Oslo, Norway
- Psychosis Studies, Institute of Psychiatry, Psychology and Neurosciences, King's College London, 16 De Crespigny Park, London, SE5 8AB, United Kingdom
| | - D Roelfs
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Building 48, Oslo, Norway
| | - O Frei
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Building 48, Oslo, Norway
| | - C C Fan
- Laureate Institute for Brain Research, Tulsa, OK, USA
- Department of Radiology, University of California San Diego, La Jolla, CA, 92037, USA
| | - M Nagel
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, The Netherlands
| | - T Nærland
- K.G. Jebsen Centre for Neurodevelopmental disorders, Division of Paediatric Medicine, Institute of Clinical Medicine, University of Oslo, Building 31, Oslo, Norway
| | - M Budisteanu
- Prof. Dr. Alex Obregia Clinical Hospital of Psychiatry, Bucharest, Romania
- "Victor Babes" National Institute of Pathology, Bucharest, Romania
| | - S Djurovic
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Building 48, Oslo, Norway
- K.G. Jebsen Centre for Neurodevelopmental disorders, Division of Paediatric Medicine, Institute of Clinical Medicine, University of Oslo, Building 31, Oslo, Norway
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - L T Westlye
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Building 48, Oslo, Norway
- K.G. Jebsen Centre for Neurodevelopmental disorders, Division of Paediatric Medicine, Institute of Clinical Medicine, University of Oslo, Building 31, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - M P van den Heuvel
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, The Netherlands
- Department of Child and Adolescent Psychology and Psychiatry, section Complex Trait Genetics, Amsterdam Neuroscience, VU University Medical Centre, Amsterdam, The Netherlands
| | - D Posthuma
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, The Netherlands
- Department of Child and Adolescent Psychology and Psychiatry, section Complex Trait Genetics, Amsterdam Neuroscience, VU University Medical Centre, Amsterdam, The Netherlands
| | - T Kaufmann
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Building 48, Oslo, Norway
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health, University of Tübingen, Tübingen, Germany
| | - A M Dale
- Department of Radiology, University of California San Diego, La Jolla, CA, 92037, USA
- Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, 92037, USA
- Department of Neurosciences, University of California San Diego, La Jolla, CA, 92037, USA
| | - O A Andreassen
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Building 48, Oslo, Norway.
- K.G. Jebsen Centre for Neurodevelopmental disorders, Division of Paediatric Medicine, Institute of Clinical Medicine, University of Oslo, Building 31, Oslo, Norway.
| |
Collapse
|
16
|
McAusland L, Burton CL, Bagnell A, Boylan K, Hatchard T, Lingley-Pottie P, Al Maruf A, McGrath P, Newton AS, Rowa K, Schachar RJ, Shaheen SM, Stewart S, Arnold PD, Crosbie J, Mattheisen M, Soreni N, Stewart SE, Meier S. The genetic architecture of youth anxiety: a study protocol. BMC Psychiatry 2024; 24:159. [PMID: 38395805 PMCID: PMC10885620 DOI: 10.1186/s12888-024-05583-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Accepted: 02/03/2024] [Indexed: 02/25/2024] Open
Abstract
BACKGROUND Anxiety disorders are the most common psychiatric problems among Canadian youth and typically have an onset in childhood or adolescence. They are characterized by high rates of relapse and chronicity, often resulting in substantial impairment across the lifespan. Genetic factors play an important role in the vulnerability toward anxiety disorders. However, genetic contribution to anxiety in youth is not well understood and can change across developmental stages. Large-scale genetic studies of youth are needed with detailed assessments of symptoms of anxiety disorders and their major comorbidities to inform early intervention or preventative strategies and suggest novel targets for therapeutics and personalization of care. METHODS The Genetic Architecture of Youth Anxiety (GAYA) study is a Pan-Canadian effort of clinical and genetic experts with specific recruitment sites in Calgary, Halifax, Hamilton, Toronto, and Vancouver. Youth aged 10-19 (n = 13,000) will be recruited from both clinical and community settings and will provide saliva samples, complete online questionnaires on demographics, symptoms of mental health concerns, and behavioural inhibition, and complete neurocognitive tasks. A subset of youth will be offered access to a self-managed Internet-based cognitive behavioral therapy resource. Analyses will focus on the identification of novel genetic risk loci for anxiety disorders in youth and assess how much of the genetic risk for anxiety disorders is unique or shared across the life span. DISCUSSION Results will substantially inform early intervention or preventative strategies and suggest novel targets for therapeutics and personalization of care. Given that the GAYA study will be the biggest genomic study of anxiety disorders in youth in Canada, this project will further foster collaborations nationally and across the world.
Collapse
Affiliation(s)
- Laina McAusland
- The Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada.
- Department of Medical Genetics, University of Calgary, Calgary, AB, Canada.
| | - Christie L Burton
- Neurosciences & Mental Health, Hospital for Sick Children, Toronto, ON, Canada
| | - Alexa Bagnell
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Khrista Boylan
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
- Offord Center for Child Studies, Hamilton, ON, Canada
- Child and Youth Mental Health Program, Hamilton Health Sciences, Hamilton, ON, Canada
| | - Taylor Hatchard
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
- Youth Wellness Center, St. Joseph's Healthcare, Hamilton, ON, Canada
| | - Patricia Lingley-Pottie
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
- Department of Psychiatry, IWK Health Centre, Halifax, NS, Canada
| | - Abdullah Al Maruf
- The Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada
- College of Pharmacy, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Patrick McGrath
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Amanda S Newton
- Department of Pediatrics, University of Alberta, Edmonton, AB, Canada
| | - Karen Rowa
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
- Anxiety Treatment and Research Clinic, St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada
- Department of Psychology, Neuroscience, and Behaviour, McMaster University, Hamilton, ON, Canada
| | - Russell J Schachar
- Neurosciences & Mental Health, Hospital for Sick Children, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - S-M Shaheen
- The Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada
| | - Sam Stewart
- Department of Epidemiology and Community Health, Dalhousie University, Halifax, NS, Canada
| | - Paul D Arnold
- The Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada
- Department of Medical Genetics, University of Calgary, Calgary, AB, Canada
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada
| | - Jennifer Crosbie
- Neurosciences & Mental Health, Hospital for Sick Children, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Manuel Mattheisen
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
- Department of Epidemiology and Community Health, Dalhousie University, Halifax, NS, Canada
- Department of Computer Science, Dalhousie University, Halifax, NS, Canada
| | - Noam Soreni
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
- Offord Center for Child Studies, Hamilton, ON, Canada
- Anxiety Treatment and Research Clinic, St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada
- Pediatric OCD Consultation Service, St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada
| | - S Evelyn Stewart
- British Columbia Children's Hospital Research Institute, Vancouver, BC, Canada
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Sandra Meier
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
- Department of Epidemiology and Community Health, Dalhousie University, Halifax, NS, Canada
- Department of Computer Science, Dalhousie University, Halifax, NS, Canada
| |
Collapse
|
17
|
Sun Q, Rowland BT, Chen J, Mikhaylova AV, Avery C, Peters U, Lundin J, Matise T, Buyske S, Tao R, Mathias RA, Reiner AP, Auer PL, Cox NJ, Kooperberg C, Thornton TA, Raffield LM, Li Y. Improving polygenic risk prediction in admixed populations by explicitly modeling ancestral-differential effects via GAUDI. Nat Commun 2024; 15:1016. [PMID: 38310129 PMCID: PMC10838303 DOI: 10.1038/s41467-024-45135-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 01/16/2024] [Indexed: 02/05/2024] Open
Abstract
Polygenic risk scores (PRS) have shown successes in clinics, but most PRS methods focus only on participants with distinct primary continental ancestry without accommodating recently-admixed individuals with mosaic continental ancestry backgrounds for different segments of their genomes. Here, we develop GAUDI, a novel penalized-regression-based method specifically designed for admixed individuals. GAUDI explicitly models ancestry-differential effects while borrowing information across segments with shared ancestry in admixed genomes. We demonstrate marked advantages of GAUDI over other methods through comprehensive simulation and real data analyses for traits with associated variants exhibiting ancestral-differential effects. Leveraging data from the Women's Health Initiative study, we show that GAUDI improves PRS prediction of white blood cell count and C-reactive protein in African Americans by > 64% compared to alternative methods, and even outperforms PRS-CSx with large European GWAS for some scenarios. We believe GAUDI will be a valuable tool to mitigate disparities in PRS performance in admixed individuals.
Collapse
Affiliation(s)
- Quan Sun
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Bryce T Rowland
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Jiawen Chen
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Anna V Mikhaylova
- Department of Biostatistics, University of Washington, Seattle, WA, 98195, USA
| | - Christy Avery
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Ulrike Peters
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Jessica Lundin
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Tara Matise
- Department of Genetics, Rutgers University, New Brunswick, NJ, 08901, USA
| | - Steve Buyske
- Department of Statistics, Rutgers University, New Brunswick, NJ, 08901, USA
| | - Ran Tao
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Rasika A Mathias
- Department of Medicine, Johns Hopkins University, Baltimore, MD, 21287, USA
| | - Alexander P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA, 98195, USA
| | - Paul L Auer
- Division of Biostatistics, Institute for Health and Equity, and Cancer Center, Medical College of Wisconsin, Milwaukee, WI, 53226, USA
| | - Nancy J Cox
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Timothy A Thornton
- Department of Biostatistics, University of Washington, Seattle, WA, 98195, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
| |
Collapse
|
18
|
Kolpakov S, Yashkin A, Ukraintseva S, Yashin A, Akushevich I. Genome-Related Mechanisms Contributing to Differences in Alzheimer's Disease Incidence Between White and Black Older US Adults. J Racial Ethn Health Disparities 2024:10.1007/s40615-024-01907-3. [PMID: 38273182 PMCID: PMC11269527 DOI: 10.1007/s40615-024-01907-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 12/31/2023] [Accepted: 01/04/2024] [Indexed: 01/27/2024]
Abstract
In this manuscript, we leverage a modified GWAS algorithm adapted for use with multidimensional Cox models and data from the Health and Retirement Study to explore how genetic variation influences the size of the disparity in Alzheimer's disease (AD) incidence between older Black and White US adults. We identified four loci that were associated with higher AD incidence levels in older Black adults: (1) rs11077034 (hazard ratio (HR), 4.98) from the RBFOX1 gene; (2) rs7144494 (HR, 1.68) from the HISLA gene; (3) rs7660552 (HR, 3.07) from the SLC25A4 gene; and (4) rs12599485 (HR, 3.181) from the NIP30 gene. The RBFOX1, HISLA, SLC25A4, and NIP30 genes are known to be associated with AD (RBFOX1, NIP30) directly, and also influence the risk of AD risk-related morbidities such as hypertension (RBFOX1, SLC25A4), depression (SLC25A4), and certain cancers (HISLA, SLC25A4). A likely disparity-generating mechanism may lie in endocytosis and abnormal tissue growing mechanisms, depending on inherited gene mutations and the structure of proxies as well as gene-environment interactions with other risk factors such as lifestyle, education level, and access to adequate medical services.
Collapse
Affiliation(s)
- Stanislav Kolpakov
- Social Science Research Institute, Duke University, Durham, NC, 27710, USA.
| | - Arseniy Yashkin
- Social Science Research Institute, Duke University, Durham, NC, 27710, USA
| | | | - Anatoliy Yashin
- Social Science Research Institute, Duke University, Durham, NC, 27710, USA
| | - Igor Akushevich
- Social Science Research Institute, Duke University, Durham, NC, 27710, USA
| |
Collapse
|
19
|
Clifford RE, Maihofer AX, Chatzinakos C, Coleman JRI, Daskalakis NP, Gasperi M, Hogan K, Mikita EA, Stein MB, Tcheandjieu C, Telese F, Zuo Y, Ryan AF, Nievergelt CM. Genetic architecture distinguishes tinnitus from hearing loss. Nat Commun 2024; 15:614. [PMID: 38242899 PMCID: PMC10799010 DOI: 10.1038/s41467-024-44842-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 01/04/2024] [Indexed: 01/21/2024] Open
Abstract
Tinnitus is a heritable, highly prevalent auditory disorder treated by multiple medical specialties. Previous GWAS indicated high genetic correlations between tinnitus and hearing loss, with little indication of differentiating signals. We present a GWAS meta-analysis, triple previous sample sizes, and expand to non-European ancestries. GWAS in 596,905 Million Veteran Program subjects identified 39 tinnitus loci, and identified genes related to neuronal synapses and cochlear structural support. Applying state-of-the-art analytic tools, we confirm a large number of shared variants, but also a distinct genetic architecture of tinnitus, with higher polygenicity and large proportion of variants not shared with hearing difficulty. Tissue-expression analysis for tinnitus infers broad enrichment across most brain tissues, in contrast to hearing difficulty. Finally, tinnitus is not only correlated with hearing loss, but also with a spectrum of psychiatric disorders, providing potential new avenues for treatment. This study establishes tinnitus as a distinct disorder separate from hearing difficulties.
Collapse
Affiliation(s)
- Royce E Clifford
- Veterans Affairs San Diego Healthcare System, Research Service, San Diego, CA, USA.
- University of California San Diego, Division of Otolaryngology - Head and Neck Surgery, La Jolla, CA, USA.
| | - Adam X Maihofer
- Veterans Affairs San Diego Healthcare System, Research Service, San Diego, CA, USA
- University of California San Diego, Department of Psychiatry, La Jolla, CA, USA
| | - Chris Chatzinakos
- Harvard Medical School, Department of Psychiatry, Boston, MA, USA
- McLean Hospital, Center of Excellence in Depression and Anxiety Disorders, Belmont, MA, USA
| | - Jonathan R I Coleman
- King's College London, NIHR Maudsley BRC, London, UK
- King's College London, Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, London, UK
| | - Nikolaos P Daskalakis
- Harvard Medical School, Department of Psychiatry, Boston, MA, USA
- McLean Hospital, Center of Excellence in Depression and Anxiety Disorders, Belmont, MA, USA
| | - Marianna Gasperi
- Veterans Affairs San Diego Healthcare System, Research Service, San Diego, CA, USA
- University of California San Diego, Department of Psychiatry, La Jolla, CA, USA
| | - Kelleigh Hogan
- Veterans Affairs San Diego Healthcare System, Research Service, San Diego, CA, USA
- University of California San Diego, Department of Psychiatry, La Jolla, CA, USA
| | - Elizabeth A Mikita
- Veterans Affairs San Diego Healthcare System, Research Service, San Diego, CA, USA
- University of California San Diego, Department of Psychiatry, La Jolla, CA, USA
| | - Murray B Stein
- University of California San Diego, Department of Psychiatry, La Jolla, CA, USA
- Veterans Affairs San Diego Healthcare System, Psychiatry Service, San Diego, CA, USA
- University of California San Diego, School of Public Health, La Jolla, CA, USA
| | | | - Francesca Telese
- University of California San Diego, Department of Psychiatry, La Jolla, CA, USA
| | - Yanning Zuo
- University of California San Diego, Department of Psychiatry, La Jolla, CA, USA
| | - Allen F Ryan
- Veterans Affairs San Diego Healthcare System, Research Service, San Diego, CA, USA
- University of California San Diego, Division of Otolaryngology - Head and Neck Surgery, La Jolla, CA, USA
| | - Caroline M Nievergelt
- Veterans Affairs San Diego Healthcare System, Research Service, San Diego, CA, USA.
- University of California San Diego, Department of Psychiatry, La Jolla, CA, USA.
| |
Collapse
|
20
|
Schraw JM, Jaime E, Shumate CJ, Canfield MA, Lupo PJ. Prevalence of congenital anomalies according to maternal race and ethnicity, Texas, 1999-2018. Birth Defects Res 2024; 116:e2274. [PMID: 38014617 PMCID: PMC10872311 DOI: 10.1002/bdr2.2274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 10/05/2023] [Accepted: 11/08/2023] [Indexed: 11/29/2023]
Abstract
BACKGROUND Few studies of congenital anomalies provide prevalence estimates stratified by maternal race/ethnicity. We sought to determine whether the prevalence of a broad spectrum of anomalies varies among offspring of women from different race/ethnic groups. METHODS We obtained information on cases with anomalies from the population-based Texas Birth Defects Registry, and denominator data on livebirths among Texas residents during 1999-2018 from the Texas Center for Health Statistics. We estimated the prevalence ratio (PR) and 95% confidence interval (CI) of N = 145 anomalies among offspring of Hispanic and non-Hispanic Black relative to non-Hispanic White women using Poisson regression, adjusting for maternal age, education, body mass index, and previous livebirths. We performed a two-stage analysis with a Bonferroni-adjusted p < 1.7 × 10-4 in the initial screening phase to identify anomalies with statistically significant variation. RESULTS There were 7,698,768 livebirths and 1,187,385 anomalies diagnosed in 368,393 cases. The prevalence of any monitored congenital anomaly was similar among offspring of non-Hispanic White (referent), non-Hispanic Black (PR 0.98, CI 0.96-1.00), and Hispanic (PR 0.95, CI 0.93-0.96) women. We observed statistically significant racial/ethnic variation for 42 anomalies. Marked differences were observed when comparing offspring of non-Hispanic Black to non-Hispanic White women with respect to polydactyly (PR 4.38, CI 4.07-4.72), pyloric stenosis (PR 0.34, CI 0.29-0.40), and aortic valve atresia/stenosis (PR 0.51, CI 0.36-0.72). CONCLUSIONS Birth prevalence of many major congenital anomalies varies by maternal race and ethnicity. While the reasons for these differences are likely multifactorial, a thorough understanding of racial and ethnic disparities is useful to stimulate etiologic research.
Collapse
Affiliation(s)
- Jeremy M Schraw
- Center for Epidemiology and Population Health, Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA
| | - Elwin Jaime
- Center for Epidemiology and Population Health, Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA
| | - Charles J Shumate
- Birth Defects Epidemiology and Surveillance Branch, Texas Department of State Health Services, Austin, Texas, USA
| | - Mark A Canfield
- Division of Epidemiology, Human Genetics and Environmental Sciences, University of Texas School of Public Health, Austin, Texas, USA
| | - Philip J Lupo
- Center for Epidemiology and Population Health, Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA
| |
Collapse
|
21
|
Kachuri L, Chatterjee N, Hirbo J, Schaid DJ, Martin I, Kullo IJ, Kenny EE, Pasaniuc B, Witte JS, Ge T. Principles and methods for transferring polygenic risk scores across global populations. Nat Rev Genet 2024; 25:8-25. [PMID: 37620596 PMCID: PMC10961971 DOI: 10.1038/s41576-023-00637-2] [Citation(s) in RCA: 32] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/11/2023] [Indexed: 08/26/2023]
Abstract
Polygenic risk scores (PRSs) summarize the genetic predisposition of a complex human trait or disease and may become a valuable tool for advancing precision medicine. However, PRSs that are developed in populations of predominantly European genetic ancestries can increase health disparities due to poor predictive performance in individuals of diverse and complex genetic ancestries. We describe genetic and modifiable risk factors that limit the transferability of PRSs across populations and review the strengths and weaknesses of existing PRS construction methods for diverse ancestries. Developing PRSs that benefit global populations in research and clinical settings provides an opportunity for innovation and is essential for health equity.
Collapse
Affiliation(s)
- Linda Kachuri
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Nilanjan Chatterjee
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Jibril Hirbo
- Department of Medicine Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Daniel J Schaid
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Iman Martin
- Division of Genomic Medicine, National Human Genome Research Institute, Bethesda, MD, USA
| | - Iftikhar J Kullo
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Eimear E Kenny
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bogdan Pasaniuc
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - John S Witte
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA.
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA.
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.
- Department of Genetics, Stanford University, Stanford, CA, USA.
| | - Tian Ge
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Center for Precision Psychiatry, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| |
Collapse
|
22
|
Yang G, Alarcon C, Chanfreau C, Lee NH, Friedman P, Nutescu E, Tuck M, O'Brien T, Gong L, Klein TE, Chang KM, Tsao PS, Meltzer DO, Tuteja S, Perera MA. Investigation of genomic and transcriptomic risk factors in clopidogrel response in African Americans. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.05.23299140. [PMID: 38106031 PMCID: PMC10723512 DOI: 10.1101/2023.12.05.23299140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Clopidogrel, an anti-platelet drug, used to prevent thrombosis after percutaneous coronary intervention. Clopidogrel resistance results in recurring ischemic episodes, with African Americans suffering disproportionately. The aim of this study was to identify biomarkers of clopidogrel resistance in African American patients. We conducted a genome-wide association study, including local ancestry adjustment, in 141 African Americans on clopidogrel to identify associations with high on-treatment platelet reactivity (HTPR). We validated genome-wide and suggestive hits in an independent cohort of African American clopidogrel patients (N = 823) from the Million Veteran's Program (MVP) along with in vitro functional follow up. We performed differential gene expression (DGE) analysis in whole blood with functional follow-up in MEG-01 cells. We identified rs7807369, within thrombospondin 7A (THSD7A), as significantly associated with increasing risk of HTPR (p = 4.56 × 10-9). Higher THSD7A expression was associated with HTPR in an independent gene expression cohort of clopidogrel treated patients (p = 0.004) and supported by increased gene expression on THSD7A in primary human endothelial cells carrying the risk haplotype. Two SNPs (rs1149515 and rs191786) were validated in the MVP cohort. DGE analysis identified an association with decreased LAIR1 expression to HTPR. LAIR1 knockdown in a MEG-01 cells resulted in increased expression of SYK and AKT1, suggesting an inhibitory role of LAIR1 in the Glycoprotein VI pathway. Notably, the CYP2C19 variants showed no association with clopidogrel response in the discovery or MVP cohorts. In summary, these finding suggest that other variants outside of CYP2C19 star alleles play an important role in clopidogrel response in African Americans.
Collapse
Affiliation(s)
- Guang Yang
- Department of Pharmacology, Center for Pharmacogenomics, Fienberg School of Medicine, Northwestern University, Chicago IL
| | - Cristina Alarcon
- Department of Pharmacology, Center for Pharmacogenomics, Fienberg School of Medicine, Northwestern University, Chicago IL
| | | | - Norman H Lee
- Department of Pharmacology and Physiology, George Washington University, 2300 I Street NW, Washington, DC, 20037, USA
| | - Paula Friedman
- Department of Pharmacology, Center for Pharmacogenomics, Fienberg School of Medicine, Northwestern University, Chicago IL
| | - Edith Nutescu
- Department of Pharmacy Practice and Center for Pharmacoepidemiology and Pharmacoeconomic Research, University of Illinois Chicago, College of Pharmacy, Chicago, IL
| | - Matthew Tuck
- Washington DC VA Medical Center, Washington, DC and The George Washington University, Washington, DC
| | - Travis O'Brien
- Department of Pharmacology and Physiology, George Washington University, 2300 I Street NW, Washington, DC, 20037, USA
| | - Li Gong
- Department of Biomedical Data Science, Stanford University, Stanford, CA
| | - Teri E Klein
- Department of Biomedical Data Science and Department of Medicine, Stanford University, Stanford, CA
| | - Kyong-Mi Chang
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Philip S Tsao
- VA Palo Alto Healthcare System and Stanford University, Palo Alto, CA
| | - David O Meltzer
- Section of Hospital Medicine, Department of Medicine, University of Chicago, Chicago, IL
| | - Sony Tuteja
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Minoli A Perera
- Department of Pharmacology, Center for Pharmacogenomics, Fienberg School of Medicine, Northwestern University, Chicago IL
| |
Collapse
|
23
|
Avadhanam S, Williams AL. Phase-free local ancestry inference mitigates the impact of switch errors on phase-based methods. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.02.569669. [PMID: 38106003 PMCID: PMC10723336 DOI: 10.1101/2023.12.02.569669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Local ancestry inference (LAI) is an indispensable component of a variety of analyses in medical and population genetics, from admixture mapping to characterizing demographic history. However, the accuracy of LAI depends on a number of factors such as phase quality (for phase-based LAI methods), time since admixture of the population under study, and other factors. Here we present an empirical analysis of four LAI methods using simulated individuals of mixed African and European ancestry, examining the impact of variable phase quality and a range of demographic scenarios. We found that regardless of phasing options, calls from LAI methods that operate on unphased genotypes (phase-free LAI) have 2.6-4.6% higher Pearson correlation with the ground truth than methods that operate on phased genotypes (phase-based LAI). Applying the TRACTOR phase-correction algorithm led to modest improvements in phase-based LAI, but despite this, the Pearson correlation of phase-free LAI remained 2.4-3.8% higher than phase-corrected phase-based approaches (considering the best performing methods in each category). Phase-free and phase-based LAI accuracy differences can dramatically impact downstream analyses: estimates of the time since admixture using phase-based LAI tracts are upwardly biased by ≈10 generations using our highest quality phased data but have virtually no bias using phase-free LAI calls. Our study underscores the strong dependence of phase-based LAI accuracy on phase quality and highlights the merits of LAI approaches that analyze unphased genetic data.
Collapse
|
24
|
Gupta Y, Friedman DJ, McNulty MT, Khan A, Lane B, Wang C, Ke J, Jin G, Wooden B, Knob AL, Lim TY, Appel GB, Huggins K, Liu L, Mitrotti A, Stangl MC, Bomback A, Westland R, Bodria M, Marasa M, Shang N, Cohen DJ, Crew RJ, Morello W, Canetta P, Radhakrishnan J, Martino J, Liu Q, Chung WK, Espinoza A, Luo Y, Wei WQ, Feng Q, Weng C, Fang Y, Kullo IJ, Naderian M, Limdi N, Irvin MR, Tiwari H, Mohan S, Rao M, Dube GK, Chaudhary NS, Gutiérrez OM, Judd SE, Cushman M, Lange LA, Lange EM, Bivona DL, Verbitsky M, Winkler CA, Kopp JB, Santoriello D, Batal I, Pinheiro SVB, Oliveira EA, Simoes E Silva AC, Pisani I, Fiaccadori E, Lin F, Gesualdo L, Amoroso A, Ghiggeri GM, D'Agati VD, Magistroni R, Kenny EE, Loos RJF, Montini G, Hildebrandt F, Paul DS, Petrovski S, Goldstein DB, Kretzler M, Gbadegesin R, Gharavi AG, Kiryluk K, Sampson MG, Pollak MR, Sanna-Cherchi S. Strong protective effect of the APOL1 p.N264K variant against G2-associated focal segmental glomerulosclerosis and kidney disease. Nat Commun 2023; 14:7836. [PMID: 38036523 PMCID: PMC10689833 DOI: 10.1038/s41467-023-43020-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 10/30/2023] [Indexed: 12/02/2023] Open
Abstract
African Americans have a significantly higher risk of developing chronic kidney disease, especially focal segmental glomerulosclerosis -, than European Americans. Two coding variants (G1 and G2) in the APOL1 gene play a major role in this disparity. While 13% of African Americans carry the high-risk recessive genotypes, only a fraction of these individuals develops FSGS or kidney failure, indicating the involvement of additional disease modifiers. Here, we show that the presence of the APOL1 p.N264K missense variant, when co-inherited with the G2 APOL1 risk allele, substantially reduces the penetrance of the G1G2 and G2G2 high-risk genotypes by rendering these genotypes low-risk. These results align with prior functional evidence showing that the p.N264K variant reduces the toxicity of the APOL1 high-risk alleles. These findings have important implications for our understanding of the mechanisms of APOL1-associated nephropathy, as well as for the clinical management of individuals with high-risk genotypes that include the G2 allele.
Collapse
Affiliation(s)
- Yask Gupta
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
- Institute for Inflammation Medicine, University of Lubeck, Lübeck, Germany
| | - David J Friedman
- Nephrology Division, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Michelle T McNulty
- Division of Pediatric Nephrology, Boston Children's Hospital, Boston, MA, USA
- Kidney Disease Initiative and Medical and Population Genetics Program, Broad Institute, Boston, MA, USA
| | - Atlas Khan
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Brandon Lane
- Division of Nephrology, Department of Pediatrics, Duke University School of Medicine, Durham, NC, USA
| | - Chen Wang
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Juntao Ke
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Gina Jin
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Benjamin Wooden
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Andrea L Knob
- Nephrology Division, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Tze Y Lim
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
- Unit of Genomic Variability and Complex Diseases, Department of Medical Sciences, University of Turin, Turin, Italy
| | - Gerald B Appel
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Kinsie Huggins
- Division of Nephrology, Department of Pediatrics, Duke University School of Medicine, Durham, NC, USA
| | - Lili Liu
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Adele Mitrotti
- Department of Precision and Regenerative Medicine and Ionian Area (DiMePre-J) Nephrology, Dialysis and Transplantation Unit, University of Bari Aldo Moro, Bari, Italy
| | - Megan C Stangl
- Division of Nephrology, Department of Pediatrics, Duke University School of Medicine, Durham, NC, USA
| | - Andrew Bomback
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Rik Westland
- Department of Pediatric Nephrology, Emma Children's Hospital, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
| | - Monica Bodria
- Division of Nephrology and Renal Transplantation, IRCCS Istituto Giannina Gaslini, Genoa, Italy
- Laboratory on Molecular Nephrology, IRCCS Istituto Giannina Gaslini, Genoa, Italy
| | - Maddalena Marasa
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Ning Shang
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - David J Cohen
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Russell J Crew
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - William Morello
- Pediatric Nephrology, Dialysis and Transplant Unit, Fondazione IRCCS Ca' Granda-Ospedale Maggiore Policlinico, Milano, Italy
| | - Pietro Canetta
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Jai Radhakrishnan
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Jeremiah Martino
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Qingxue Liu
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Wendy K Chung
- Departments of Pediatrics and Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Angelica Espinoza
- Center for Genetic Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Yuan Luo
- Center for Genetic Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Wei-Qi Wei
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Qiping Feng
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Chunhua Weng
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Yilu Fang
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Iftikhar J Kullo
- Atherosclerosis and Lipid Genomics Laboratory, Mayo Clinic, Rochester, MN, USA
| | | | - Nita Limdi
- Department of Neurology, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Marguerite R Irvin
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Hemant Tiwari
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Sumit Mohan
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Maya Rao
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Geoffrey K Dube
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Ninad S Chaudhary
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Orlando M Gutiérrez
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
- Division of Nephrology, Department of Medicine, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Suzanne E Judd
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Mary Cushman
- Department of Medicine and Pathology and Laboratory Medicine, University of Vermont, Burlington, VT, USA
| | - Leslie A Lange
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Ethan M Lange
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Daniel L Bivona
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Miguel Verbitsky
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Cheryl A Winkler
- Cancer Innovation Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health and Basic Research Program, Frederick National Laboratory, Frederick, MD, USA
| | - Jeffrey B Kopp
- Kidney Disease Section, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), NIH, Bethesda, MD, USA
| | - Dominick Santoriello
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Ibrahim Batal
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Sérgio Veloso Brant Pinheiro
- Universidade Federal de Minas Gerais (UFMG), Faculdade de Medicina, Laboratório Interdisciplinar de Investigação Médica, Departamento de Pediatria, Unidade de Nefrologia Pediátrica, Belo Horizonte, MG, Brazil
| | - Eduardo Araújo Oliveira
- Universidade Federal de Minas Gerais (UFMG), Faculdade de Medicina, Laboratório Interdisciplinar de Investigação Médica, Departamento de Pediatria, Unidade de Nefrologia Pediátrica, Belo Horizonte, MG, Brazil
| | - Ana Cristina Simoes E Silva
- Universidade Federal de Minas Gerais (UFMG), Faculdade de Medicina, Laboratório Interdisciplinar de Investigação Médica, Departamento de Pediatria, Unidade de Nefrologia Pediátrica, Belo Horizonte, MG, Brazil
| | - Isabella Pisani
- Nephrology Unit, Parma University Hospital, and Department of Medicine and Surgery, University of Parma, Parma, Italy
| | - Enrico Fiaccadori
- Nephrology Unit, Parma University Hospital, and Department of Medicine and Surgery, University of Parma, Parma, Italy
| | - Fangming Lin
- Division of Pediatric Nephrology, Department of Pediatrics, Columbia University, New York, NY, USA
| | - Loreto Gesualdo
- Department of Precision and Regenerative Medicine and Ionian Area (DiMePre-J) Nephrology, Dialysis and Transplantation Unit, University of Bari Aldo Moro, Bari, Italy
| | - Antonio Amoroso
- Immunogenetics and Transplant Biology Service, University Hospital "Città della Salute e della Scienza di Torino", Department of Medical Sciences, University of Turin, Turin, Italy
| | - Gian Marco Ghiggeri
- Division of Nephrology and Renal Transplantation, IRCCS Istituto Giannina Gaslini, Genoa, Italy
- Laboratory on Molecular Nephrology, IRCCS Istituto Giannina Gaslini, Genoa, Italy
| | - Vivette D D'Agati
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Riccardo Magistroni
- Surgical, Medical and Dental Department of Morphological Sciences, Section of Nephrology, University of Modena and Reggio Emilia, Modena, Italy
| | - Eimear E Kenny
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Translational Genomics, Icahn School of Medicine, New York, NY, 10027, USA
- Division of Genomic Medicine, Department of Medicine, Icahn School of Medicine, New York, NY, 10027, USA
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Giovanni Montini
- Pediatric Nephrology, Dialysis and Transplant Unit, Fondazione IRCCS Ca' Granda-Ospedale Maggiore Policlinico, Milano, Italy
- Department of Clinical Sciences and Community Health, Giuliana and Bernardo Caprotti Chair of Pediatrics, University of Milano, Milano, Italy
| | - Friedhelm Hildebrandt
- Harvard Medical School, Boston, MA, USA
- Division of Pediatric Nephrology, Boston Children's Hospital, Boston, MA, USA
| | - Dirk S Paul
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Slavé Petrovski
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - David B Goldstein
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Matthias Kretzler
- Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI, USA
| | - Rasheed Gbadegesin
- Division of Nephrology, Department of Pediatrics, Duke University School of Medicine, Durham, NC, USA
| | - Ali G Gharavi
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Krzysztof Kiryluk
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Matthew G Sampson
- Harvard Medical School, Boston, MA, USA
- Division of Pediatric Nephrology, Boston Children's Hospital, Boston, MA, USA
- Kidney Disease Initiative and Medical and Population Genetics Program, Broad Institute, Boston, MA, USA
| | - Martin R Pollak
- Nephrology Division, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Simone Sanna-Cherchi
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA.
| |
Collapse
|
25
|
Arora A, Jack K, Kumar AV, Borad M, Girardo ME, De Filippis E, Yang P, Dinu V. Genome-Wide Association Study of Gallstone Disease Identifies Novel Candidate Genomic Variants in a Latino Community of Southwest USA. J Racial Ethn Health Disparities 2023:10.1007/s40615-023-01867-0. [PMID: 38015333 DOI: 10.1007/s40615-023-01867-0] [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: 04/06/2023] [Revised: 11/05/2023] [Accepted: 11/06/2023] [Indexed: 11/29/2023]
Abstract
Gallstone disease (GSD) is a prevalent health condition that impacts many adults and is associated with presence of stones in gallbladder cavity that results in inflammation, pain, fever, nausea and vomiting. Several genome-wide association studies (GWAS) in the past have identified genes associated with GSD but only a few were focused on Latino population. To identify genetic risk factors for GSD in Latino population living in the Southwest USA we used self-reported clinical history, physical and lab measurements data in Sangre Por Salud (SPS) cohort and identified participants with and without diagnosis of GSD. We performed a GWAS on this phenotype using GSD cases matched to normal controls based on a tight criterion. We identified several novel loci associated with GSD as well as loci that were previously identified in past GWAS studies. The top 3 loci (MATN2, GPRIN3, GPC6) were strongly associated with GSD phenotype in our combined analysis and a sex stratified analysis results in females were closest to the overall results reflecting a general higher disease prevalence in females. The top identified variants in MATN2, GPRIN3, and GPC6 remain unchanged after local ancestry adjustment in SPS Latino population. Follow-up pathway enrichment analysis suggests enrichment of GO terms that are associated with immunological pathways; enzymatic processes in gallbladder, liver, and gastrointestinal tract; and GSD pathology. Our findings suggest an initial starting point towards better and deeper understanding of differences in gallstone disease pathology, biological mechanisms, and disease progression among Southwest US Latino population.
Collapse
Affiliation(s)
- Amit Arora
- College of Health Solutions, Arizona State University, Phoenix, AZ, 85004, USA.
| | - Khadijah Jack
- College of Health Solutions, Arizona State University, Phoenix, AZ, 85004, USA
| | - Ashok V Kumar
- Department of Quantitative Health Science, Mayo Clinic, Scottsdale, AZ, 85259, USA
| | - Mitesh Borad
- Division of Hematology and Medical Oncology, Mayo Clinic, Scottsdale, AZ, 85259, USA
| | - Marlene E Girardo
- Department of Quantitative Health Science, Mayo Clinic, Scottsdale, AZ, 85259, USA
| | | | - Ping Yang
- Department of Quantitative Health Science, Mayo Clinic, Scottsdale, AZ, 85259, USA
| | - Valentin Dinu
- College of Health Solutions, Arizona State University, Phoenix, AZ, 85004, USA
| |
Collapse
|
26
|
Moore A, Marks JA, Quach BC, Guo Y, Bierut LJ, Gaddis NC, Hancock DB, Page GP, Johnson EO. Evaluating 17 methods incorporating biological function with GWAS summary statistics to accelerate discovery demonstrates a tradeoff between high sensitivity and high positive predictive value. Commun Biol 2023; 6:1199. [PMID: 38001305 PMCID: PMC10673847 DOI: 10.1038/s42003-023-05413-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 10/03/2023] [Indexed: 11/26/2023] Open
Abstract
Where sufficiently large genome-wide association study (GWAS) samples are not currently available or feasible, methods that leverage increasing knowledge of the biological function of variants may illuminate discoveries without increasing sample size. We comprehensively evaluated 17 functional weighting methods for identifying novel associations. We assessed the performance of these methods using published results from multiple GWAS waves across each of five complex traits. Although no method achieved both high sensitivity and positive predictive value (PPV) for any trait, a subset of methods utilizing pleiotropy and expression quantitative trait loci nominated variants with high PPV (>75%) for multiple traits. Application of functionally weighting methods to enhance GWAS power for locus discovery is unlikely to circumvent the need for larger sample sizes in truly underpowered GWAS, but these results suggest that applying functional weighting to GWAS can accurately nominate additional novel loci from available samples for follow-up studies.
Collapse
Affiliation(s)
- Amy Moore
- Genomics and Translational Research Center, RTI International, Research Triangle Park, NC, 27709, USA.
| | - Jesse A Marks
- Genomics and Translational Research Center, RTI International, Research Triangle Park, NC, 27709, USA
| | - Bryan C Quach
- Genomics and Translational Research Center, RTI International, Research Triangle Park, NC, 27709, USA
| | - Yuelong Guo
- GeneCentric Therapeutics, Inc., Cary, NC, USA
| | - Laura J Bierut
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Nathan C Gaddis
- Genomics and Translational Research Center, RTI International, Research Triangle Park, NC, 27709, USA
| | - Dana B Hancock
- Genomics and Translational Research Center, RTI International, Research Triangle Park, NC, 27709, USA
| | - Grier P Page
- Genomics and Translational Research Center, RTI International, Research Triangle Park, NC, 27709, USA
- Fellow Program, RTI International, Research Triangle Park, NC, 27709, USA
| | - Eric O Johnson
- Genomics and Translational Research Center, RTI International, Research Triangle Park, NC, 27709, USA.
- Fellow Program, RTI International, Research Triangle Park, NC, 27709, USA.
| |
Collapse
|
27
|
Yang Z, Cieza B, Reyes-Dumeyer D, Montesinos R, Soto-Añari M, Custodio N, Tosto G. A benchmark study on current GWAS models in admixed populations. Brief Bioinform 2023; 25:bbad437. [PMID: 38037235 PMCID: PMC10689347 DOI: 10.1093/bib/bbad437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 10/30/2023] [Accepted: 11/08/2023] [Indexed: 12/02/2023] Open
Abstract
OBJECTIVE The performances of popular genome-wide association study (GWAS) models have not been examined yet in a consistent manner under the scenario of genetic admixture, which introduces several challenging aspects: heterogeneity of minor allele frequency (MAF), wide spectrum of case-control ratio, varying effect sizes, etc. METHODS We generated a cohort of synthetic individuals (N = 19 234) that simulates (i) a large sample size; (ii) two-way admixture (Native American and European ancestry) and (iii) a binary phenotype. We then benchmarked three popular GWAS tools [generalized linear mixed model associated test (GMMAT), scalable and accurate implementation of generalized mixed model (SAIGE) and Tractor] by computing inflation factors and power calculations under different MAFs, case-control ratios, sample sizes and varying ancestry proportions. We also employed a cohort of Peruvians (N = 249) to further examine the performances of the testing models on (i) real genetic and phenotype data and (ii) small sample sizes. RESULTS In the synthetic cohort, SAIGE performed better than GMMAT and Tractor in terms of type-I error rate, especially under severe unbalanced case-control ratio. On the contrary, power analysis identified Tractor as the best method to pinpoint ancestry-specific causal variants but showed decreased power when the effect size displayed limited heterogeneity between ancestries. In the Peruvian cohort, only Tractor identified two suggestive loci (P-value $\le 1\ast{10}^{-5}$) associated with Native American ancestry. DISCUSSION The current study illustrates best practice and limitations for available GWAS tools under the scenario of genetic admixture. Incorporating local ancestry in GWAS analyses boosts power, although careful consideration of complex scenarios (small sample sizes, imbalance case-control ratio, MAF heterogeneity) is needed.
Collapse
Affiliation(s)
- Zikun Yang
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY 10032, USA
- The Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY 10032, USA
| | - Basilio Cieza
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY 10032, USA
- The Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY 10032, USA
| | - Dolly Reyes-Dumeyer
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY 10032, USA
- The Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY 10032, USA
- Department of Neurology, College of Physicians and Surgeons, Columbia University and the New York Presbyterian Hospital, 710 West 168th Street, New York, NY 10032, USA
| | - Rosa Montesinos
- Unidad de diagnóstico de deterioro cognitivo y prevención de demencia, Instituto Peruano de Neurociencias, Lima, Perú
| | - Marcio Soto-Añari
- Instituto de Neurociencia Cognitiva, Arequipa, Perú
- Laboratorio de Neurociencia, Universidad Católica San Pablo, Arequipa, Perú
| | - Nilton Custodio
- Unidad de diagnóstico de deterioro cognitivo y prevención de demencia, Instituto Peruano de Neurociencias, Lima, Perú
| | - Giuseppe Tosto
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY 10032, USA
- The Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY 10032, USA
- Department of Neurology, College of Physicians and Surgeons, Columbia University and the New York Presbyterian Hospital, 710 West 168th Street, New York, NY 10032, USA
| |
Collapse
|
28
|
Wei Y, Zhi D, Zhang S. Fast and accurate local ancestry inference with Recomb-Mix. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.17.567650. [PMID: 38014185 PMCID: PMC10680832 DOI: 10.1101/2023.11.17.567650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
The availability of large genotyped cohorts brings new opportunities for revealing high-resolution genetic structure of admixed populations, via local ancestry inference (LAI), the process of identifying the ancestry of each segment of an individual haplotype. Though current methods achieve high accuracy in standard cases, LAI is still challenging when reference populations are more similar (e.g., intra-continental), when the number of reference populations is too numerous, or when the admixture events are deep in time, all of which are increasingly unavoidable in large biobanks. Here, we present a new LAI method, Recomb-Mix. Adopting the commonly used site-based formulation based on the classic Li and Stephens' model, Recomb-Mix integrates the elements of existing methods and introduces a new graph collapsing to simplify counting paths with the same ancestry label readout. Through comprehensive benchmarking on various simulated datasets, we show that Recomb-Mix is more accurate than existing methods in diverse sets of scenarios while being competitive in terms of resource efficiency. We expect that Recomb-Mix will be a useful method for advancing genetics studies of admixed populations.
Collapse
Affiliation(s)
- Yuan Wei
- Department of Computer Science, University of Central Florida, Orlando, FL, USA
| | - Degui Zhi
- McWilliams School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Shaojie Zhang
- Department of Computer Science, University of Central Florida, Orlando, FL, USA
| |
Collapse
|
29
|
Goovaerts S, Hoskens H, Eller RJ, Herrick N, Musolf AM, Justice CM, Yuan M, Naqvi S, Lee MK, Vandermeulen D, Szabo-Rogers HL, Romitti PA, Boyadjiev SA, Marazita ML, Shaffer JR, Shriver MD, Wysocka J, Walsh S, Weinberg SM, Claes P. Joint multi-ancestry and admixed GWAS reveals the complex genetics behind human cranial vault shape. Nat Commun 2023; 14:7436. [PMID: 37973980 PMCID: PMC10654897 DOI: 10.1038/s41467-023-43237-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 11/01/2023] [Indexed: 11/19/2023] Open
Abstract
The cranial vault in humans is highly variable, clinically relevant, and heritable, yet its genetic architecture remains poorly understood. Here, we conduct a joint multi-ancestry and admixed multivariate genome-wide association study on 3D cranial vault shape extracted from magnetic resonance images of 6772 children from the ABCD study cohort yielding 30 genome-wide significant loci. Follow-up analyses indicate that these loci overlap with genomic risk loci for sagittal craniosynostosis, show elevated activity cranial neural crest cells, are enriched for processes related to skeletal development, and are shared with the face and brain. We present supporting evidence of regional localization for several of the identified genes based on expression patterns in the cranial vault bones of E15.5 mice. Overall, our study provides a comprehensive overview of the genetics underlying normal-range cranial vault shape and its relevance for understanding modern human craniofacial diversity and the etiology of congenital malformations.
Collapse
Affiliation(s)
- Seppe Goovaerts
- Department of Human Genetics, KU Leuven, Leuven, Belgium.
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium.
| | - Hanne Hoskens
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
| | - Ryan J Eller
- Department of Biology, Indiana University Indianapolis, Indianapolis, IN, USA
| | - Noah Herrick
- Department of Biology, Indiana University Indianapolis, Indianapolis, IN, USA
| | - Anthony M Musolf
- Statistical Genetics Section, Computational and Statistical Genomics Branch, NHGRI, NIH, MD, Baltimore, USA
| | - Cristina M Justice
- Genometrics Section, Computational and Statistical Genomics Branch, Division of Intramural Research, NHGRI, NIH, Baltimore, MD, USA
- Neurobehavioral Clinical Research Section, Social and Behavioral Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Meng Yuan
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
| | - Sahin Naqvi
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA, USA
- Departments of Genetics and Biology, Stanford University School of Medicine, Stanford, CA, USA
| | - Myoung Keun Lee
- Department of Oral and Craniofacial Sciences, Center for Craniofacial and Dental Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Dirk Vandermeulen
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
| | - Heather L Szabo-Rogers
- Department of Anatomy, Physiology and Pharmacology, University of Saskatchewan, Saskatchewan, Canada
| | - Paul A Romitti
- Department of Epidemiology, College of Public Health, The University of Iowa, Iowa City, IA, USA
| | - Simeon A Boyadjiev
- Department of Pediatrics, University of California Davis, Sacramento, CA, USA
| | - Mary L Marazita
- Department of Oral and Craniofacial Sciences, Center for Craniofacial and Dental Genetics, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - John R Shaffer
- Department of Oral and Craniofacial Sciences, Center for Craniofacial and Dental Genetics, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Mark D Shriver
- Department of Anthropology, Pennsylvania State University, State College, PA, USA
| | - Joanna Wysocka
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Susan Walsh
- Department of Biology, Indiana University Indianapolis, Indianapolis, IN, USA
| | - Seth M Weinberg
- Department of Oral and Craniofacial Sciences, Center for Craniofacial and Dental Genetics, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Anthropology, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Peter Claes
- Department of Human Genetics, KU Leuven, Leuven, Belgium.
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium.
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium.
- Murdoch Children's Research Institute, Melbourne, VIC, Australia.
| |
Collapse
|
30
|
Gouveia MH, Bentley AR, Leal TP, Tarazona-Santos E, Bustamante CD, Adeyemo AA, Rotimi CN, Shriner D. Unappreciated subcontinental admixture in Europeans and European Americans and implications for genetic epidemiology studies. Nat Commun 2023; 14:6802. [PMID: 37935687 PMCID: PMC10630423 DOI: 10.1038/s41467-023-42491-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 10/12/2023] [Indexed: 11/09/2023] Open
Abstract
European-ancestry populations are recognized as stratified but not as admixed, implying that residual confounding by locus-specific ancestry can affect studies of association, polygenic adaptation, and polygenic risk scores. We integrate individual-level genome-wide data from ~19,000 European-ancestry individuals across 79 European populations and five European American cohorts. We generate a new reference panel that captures ancestral diversity missed by both the 1000 Genomes and Human Genome Diversity Projects. Both Europeans and European Americans are admixed at the subcontinental level, with admixture dates differing among subgroups of European Americans. After adjustment for both genome-wide and locus-specific ancestry, associations between a highly differentiated variant in LCT (rs4988235) and height or LDL-cholesterol were confirmed to be false positives whereas the association between LCT and body mass index was genuine. We provide formal evidence of subcontinental admixture in individuals with European ancestry, which, if not properly accounted for, can produce spurious results in genetic epidemiology studies.
Collapse
Affiliation(s)
- Mateus H Gouveia
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Thiago P Leal
- Department of Genomic Medicine, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, 44197, USA
| | - Eduardo Tarazona-Santos
- Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, 31270-910, Brazil
| | - Carlos D Bustamante
- Center for Computational, Evolutionary and Human Genomics (CEHG), Stanford University, Stanford, CA, 94305, USA
| | - Adebowale A Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Charles N Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
| | - Daniel Shriner
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
| |
Collapse
|
31
|
Tanigawa Y, Kellis M. Power of inclusion: Enhancing polygenic prediction with admixed individuals. Am J Hum Genet 2023; 110:1888-1902. [PMID: 37890495 PMCID: PMC10645553 DOI: 10.1016/j.ajhg.2023.09.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 09/22/2023] [Accepted: 09/22/2023] [Indexed: 10/29/2023] Open
Abstract
Admixed individuals offer unique opportunities for addressing limited transferability in polygenic scores (PGSs), given the substantial trans-ancestry genetic correlation in many complex traits. However, they are rarely considered in PGS training, given the challenges in representing ancestry-matched linkage-disequilibrium reference panels for admixed individuals. Here we present inclusive PGS (iPGS), which captures ancestry-shared genetic effects by finding the exact solution for penalized regression on individual-level data and is thus naturally applicable to admixed individuals. We validate our approach in a simulation study across 33 configurations with varying heritability, polygenicity, and ancestry composition in the training set. When iPGS is applied to n = 237,055 ancestry-diverse individuals in the UK Biobank, it shows the greatest improvements in Africans by 48.9% on average across 60 quantitative traits and up to 50-fold improvements for some traits (neutrophil count, R2 = 0.058) over the baseline model trained on the same number of European individuals. When we allowed iPGS to use n = 284,661 individuals, we observed an average improvement of 60.8% for African, 11.6% for South Asian, 7.3% for non-British White, 4.8% for White British, and 17.8% for the other individuals. We further developed iPGS+refit to jointly model the ancestry-shared and -dependent genetic effects when heterogeneous genetic associations were present. For neutrophil count, for example, iPGS+refit showed the highest predictive performance in the African group (R2 = 0.115), which exceeds the best predictive performance for the White British group (R2 = 0.090 in the iPGS model), even though only 1.49% of individuals used in the iPGS training are of African ancestry. Our results indicate the power of including diverse individuals for developing more equitable PGS models.
Collapse
Affiliation(s)
- Yosuke Tanigawa
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Manolis Kellis
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| |
Collapse
|
32
|
Mbatchou J, Abney M, McPeek MS. BRASS: Permutation methods for binary traits in genetic association studies with structured samples. PLoS Genet 2023; 19:e1011020. [PMID: 37934792 PMCID: PMC10656004 DOI: 10.1371/journal.pgen.1011020] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Revised: 11/17/2023] [Accepted: 10/16/2023] [Indexed: 11/09/2023] Open
Abstract
In genetic association analysis of complex traits, permutation testing can be a valuable tool for assessing significance when the distribution of the test statistic is unknown or not well-approximated. This commonly arises, e.g, in tests of gene-set, pathway or genome-wide significance, or when the statistic is formed by machine learning or data adaptive methods. Existing applications include eQTL mapping, association testing with rare variants, inclusion of admixed individuals in genetic association analysis, and epistasis detection among many others. For genetic association testing in samples with population structure and/or relatedness, use of naive permutation can lead to inflated type 1 error. To address this in quantitative traits, the MVNpermute method was developed. However, for association mapping of a binary trait, the relationship between the mean and variance makes both naive permutation and the MVNpermute method invalid. We propose BRASS, a permutation method for binary traits, for use in association mapping in structured samples. In addition to modeling structure in the sample, BRASS allows for covariates, ascertainment and simultaneous testing of multiple markers, and it accommodates a wide range of test statistics. In simulation studies, we compare BRASS to other permutation and resampling-based methods in a range of scenarios that include population structure, familial relatedness, ascertainment and phenotype model misspecification. In these settings, we demonstrate the superior control of type 1 error by BRASS compared to the other 6 methods considered. We apply BRASS to assess genome-wide significance for association analyses in domestic dog for elbow dysplasia (ED) and idiopathic epilepsy (IE). For both traits we detect previously identified associations, and in addition, for ED, we detect significant association with a SNP on chromosome 35 that was not detected by previous analyses, demonstrating the potential of the method.
Collapse
Affiliation(s)
- Joelle Mbatchou
- Regeneron Genetics Center, Tarrytown, New York, United States of America
- Department of Statistics, The University of Chicago, Chicago, Illinois, United States of America
| | - Mark Abney
- Department of Human Genetics, The University of Chicago, Chicago, Illinois, United States of America
| | - Mary Sara McPeek
- Department of Statistics, The University of Chicago, Chicago, Illinois, United States of America
- Department of Human Genetics, The University of Chicago, Chicago, Illinois, United States of America
| |
Collapse
|
33
|
Shriner D, Bentley AR, Gouveia MH, Heuston EF, Doumatey AP, Chen G, Zhou J, Adeyemo A, Rotimi CN. Universal genome-wide association studies: Powerful joint ancestry and association testing. HGG ADVANCES 2023; 4:100235. [PMID: 37653728 PMCID: PMC10507155 DOI: 10.1016/j.xhgg.2023.100235] [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: 12/01/2022] [Revised: 08/28/2023] [Accepted: 08/28/2023] [Indexed: 09/02/2023] Open
Abstract
The vast majority of human populations and individuals have mixed ancestry. Consequently, adjustment for locus-specific ancestry is essential for genetic association studies. To empower association studies for all populations, it is necessary to integrate effects of locus-specific ancestry and genotype. We developed a joint test of ancestry and association that can be performed with summary statistics, is independent of study design, can take advantage of locus-specific ancestry effects to boost power in association testing, and can utilize association effects to fine map admixture peaks. We illustrate the test using the association between serum triglycerides and LPL. By combining data from African Americans, European Americans, and West Africans, we identify three conditionally independent variants with varying amounts of ancestrally differentiated allele frequencies. Using out-of-sample data, we demonstrate improved prediction achievable by accounting for multiple causal variants and locus-specific ancestry effects at a single locus.
Collapse
Affiliation(s)
- Daniel Shriner
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Mateus H Gouveia
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Elisabeth F Heuston
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Ayo P Doumatey
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Jie Zhou
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Adebowale Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Charles N Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA.
| |
Collapse
|
34
|
Wang Y, Kanai M, Tan T, Kamariza M, Tsuo K, Yuan K, Zhou W, Okada Y, Huang H, Turley P, Atkinson EG, Martin AR. Polygenic prediction across populations is influenced by ancestry, genetic architecture, and methodology. CELL GENOMICS 2023; 3:100408. [PMID: 37868036 PMCID: PMC10589629 DOI: 10.1016/j.xgen.2023.100408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 06/21/2023] [Accepted: 08/22/2023] [Indexed: 10/24/2023]
Abstract
Polygenic risk scores (PRSs) developed from multi-ancestry genome-wide association studies (GWASs), PRSmulti, hold promise for improving PRS accuracy and generalizability across populations. To establish best practices for leveraging the increasing diversity of genomic studies, we investigated how various factors affect the performance of PRSmulti compared with PRSs constructed from single-ancestry GWASs (PRSsingle). Through extensive simulations and empirical analyses, we showed that PRSmulti overall outperformed PRSsingle in understudied populations, except when the understudied population represented a small proportion of the multi-ancestry GWAS. Furthermore, integrating PRSs based on local ancestry-informed GWASs and large-scale, European-based PRSs improved predictive performance in understudied African populations, especially for less polygenic traits with large-effect ancestry-enriched variants. Our work highlights the importance of diversifying genomic studies to achieve equitable PRS performance across ancestral populations and provides guidance for developing PRSs from multiple studies.
Collapse
Affiliation(s)
- Ying Wang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Masahiro Kanai
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Taotao Tan
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | | | - Kristin Tsuo
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Kai Yuan
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Wei Zhou
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Center for Infectious Disease Education and Research (CiDER), and Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita 565-0871, Japan
- Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo 113-0033, Japan
| | - the BioBank Japan Project
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Society of Fellows, Harvard University, Cambridge, MA 02138, USA
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Center for Infectious Disease Education and Research (CiDER), and Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita 565-0871, Japan
- Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo 113-0033, Japan
- Department of Economics, and Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA
| | - Hailiang Huang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Patrick Turley
- Department of Economics, and Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA
| | - Elizabeth G. Atkinson
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Alicia R. Martin
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| |
Collapse
|
35
|
Medina-Muñoz SG, Ortega-Del Vecchyo D, Cruz-Hervert LP, Ferreyra-Reyes L, García-García L, Moreno-Estrada A, Ragsdale AP. Demographic modeling of admixed Latin American populations from whole genomes. Am J Hum Genet 2023; 110:1804-1816. [PMID: 37725976 PMCID: PMC10577084 DOI: 10.1016/j.ajhg.2023.08.015] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 08/17/2023] [Accepted: 08/23/2023] [Indexed: 09/21/2023] Open
Abstract
Demographic models of Latin American populations often fail to fully capture their complex evolutionary history, which has been shaped by both recent admixture and deeper-in-time demographic events. To address this gap, we used high-coverage whole-genome data from Indigenous American ancestries in present-day Mexico and existing genomes from across Latin America to infer multiple demographic models that capture the impact of different timescales on genetic diversity. Our approach, which combines analyses of allele frequencies and ancestry tract length distributions, represents a significant improvement over current models in predicting patterns of genetic variation in admixed Latin American populations. We jointly modeled the contribution of European, African, East Asian, and Indigenous American ancestries into present-day Latin American populations. We infer that the ancestors of Indigenous Americans and East Asians diverged ∼30 thousand years ago, and we characterize genetic contributions of recent migrations from East and Southeast Asia to Peru and Mexico. Our inferred demographic histories are consistent across different genomic regions and annotations, suggesting that our inferences are robust to the potential effects of linked selection. In conjunction with published distributions of fitness effects for new nonsynonymous mutations in humans, we show in large-scale simulations that our models recover important features of both neutral and deleterious variation. By providing a more realistic framework for understanding the evolutionary history of Latin American populations, our models can help address the historical under-representation of admixed groups in genomics research and can be a valuable resource for future studies of populations with complex admixture and demographic histories.
Collapse
Affiliation(s)
- Santiago G Medina-Muñoz
- National Laboratory of Genomics for Biodiversity (LANGEBIO), Advanced Genomics Unit (UGA), CINVESTAV, Irapuato, Guanajuato 36824, Mexico
| | - Diego Ortega-Del Vecchyo
- Laboratorio Internacional de Investigación sobre el Genoma Humano, Universidad Nacional Autónoma de Mexico, Juriquilla, Querétaro 76230, Mexico
| | | | | | | | - Andrés Moreno-Estrada
- National Laboratory of Genomics for Biodiversity (LANGEBIO), Advanced Genomics Unit (UGA), CINVESTAV, Irapuato, Guanajuato 36824, Mexico.
| | - Aaron P Ragsdale
- National Laboratory of Genomics for Biodiversity (LANGEBIO), Advanced Genomics Unit (UGA), CINVESTAV, Irapuato, Guanajuato 36824, Mexico; Department of Integrative Biology, University of Wisconsin-Madison, Madison, WI 53706, USA.
| |
Collapse
|
36
|
Hou K, Gogarten S, Kim J, Hua X, Dias JA, Sun Q, Wang Y, Tan T, Atkinson EG, Martin A, Shortt J, Hirbo J, Li Y, Pasaniuc B, Zhang H. Admix-kit: An Integrated Toolkit and Pipeline for Genetic Analyses of Admixed Populations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.30.560263. [PMID: 37873338 PMCID: PMC10592849 DOI: 10.1101/2023.09.30.560263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Admixed populations, with their unique and diverse genetic backgrounds, are often underrepresented in genetic studies. This oversight not only limits our understanding but also exacerbates existing health disparities. One major barrier has been the lack of efficient tools tailored for the special challenges of genetic study of admixed populations. Here, we present admix-kit, an integrated toolkit and pipeline for genetic analyses of admixed populations. Admix-kit implements a suite of methods to facilitate genotype and phenotype simulation, association testing, genetic architecture inference, and polygenic scoring in admixed populations.
Collapse
Affiliation(s)
- Kangcheng Hou
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA
| | | | - Joohyun Kim
- Vanderbilt Genetics Institute and Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Xing Hua
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Julie-Alexia Dias
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Quan Sun
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ying Wang
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Taotao Tan
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | | | - Elizabeth G. Atkinson
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Alicia Martin
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jonathan Shortt
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Jibril Hirbo
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Bogdan Pasaniuc
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA
| | - Haoyu Zhang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| |
Collapse
|
37
|
Yang G, González P, Moneró M, Carrasquillo K, Renta JY, Hernandez-Suarez DF, Botton MR, Melin K, Scott SA, Ruaño G, Roche-Lima A, Alarcon C, Ritchie MD, Perera MA, Duconge J. Discovery of Ancestry-specific Variants Associated with Clopidogrel Response among Caribbean Hispanics. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.09.29.23296372. [PMID: 37873439 PMCID: PMC10593031 DOI: 10.1101/2023.09.29.23296372] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Background High on-treatment platelet reactivity (HTPR) with clopidogrel is predictive of ischemic events in adults with coronary artery disease. Despite strong data suggesting HTPR varies with ethnicity, including clinical and genetic variables, no genome-wide association study (GWAS) of clopidogrel response has been performed among Caribbean Hispanics. This study aimed to identify genetic predictors of HTPR in a cohort of Caribbean Hispanic cardiovascular patients from Puerto Rico. Methods Local Ancestry inference (LAI) and traditional GWASs were performed on a cohort of 511 clopidogrel-treated patients, stratified based on their P2Y12 reaction units (PRU) into responders and non-responders (HTPR). Results The LAI GWAS identified variants within the CYP2C19 region associated with HTPR, predominantly driven by individuals of European ancestry and absent in those with native ancestry. Incorporating local ancestry adjustment notably enhanced our ability to detect associations. While no loci reached traditional GWAS significance, three variants showed suggestive significance at chromosomes 3, 14 and 22 (OSBPL10 rs1376606, DERL3 rs5030613, and RGS6 rs9323567). In addition, a variant in the UNC5C gene on chromosome 4 was associated with an increased risk of HTPR. These findings were not identified in other cohorts, highlighting the unique genetic landscape of Caribbean Hispanics. Conclusion This is the first GWAS of clopidogrel response in Hispanics, confirming the relevance of the CYP2C19 cluster, particularly among those with European ancestry, and also identifying novel markers in a diverse patient population. Further studies are warranted to replicate our findings in other diverse cohorts and meta-analyses.
Collapse
Affiliation(s)
- Guang Yang
- Department of Pharmacology, Center for Pharmacogenomics, Feinberg School of Medicine, Northwestern University, Chicago IL 60611, United States
| | - Pablo González
- Department of Pharmacology, School of Medicine, University of Puerto Rico - Medical Sciences Campus, San Juan, Puerto Rico, 00936, United States
| | - Mariangeli Moneró
- Department of Pharmacology, School of Medicine, University of Puerto Rico - Medical Sciences Campus, San Juan, Puerto Rico, 00936, United States
| | - Kelvin Carrasquillo
- Research Centers in Minority Institutions (RCMI) Program, Center for Collaborative Research in Health Disparities (CCRHD), Academic Affairs Deanship, University of Puerto Rico - Medical Sciences Campus, San Juan, Puerto Rico, 00936, United States
| | - Jessicca Y. Renta
- Research Centers in Minority Institutions (RCMI) Program, Center for Collaborative Research in Health Disparities (CCRHD), Academic Affairs Deanship, University of Puerto Rico - Medical Sciences Campus, San Juan, Puerto Rico, 00936, United States
| | - Dagmar F. Hernandez-Suarez
- Department of Translational Medicine, Herbert Wertheim College of Medicine, Florida International University, Miami, FL 33199, United States
| | - Mariana R. Botton
- Transplant Immunology and Personalized Medicine Unit, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
| | - Kyle Melin
- Department of Pharmacy Practice, School of Pharmacy, University of Puerto Rico - Medical Sciences Campus, San Juan, Puerto Rico, 00936, United States
| | - Stuart A. Scott
- Department of Pathology, Stanford University, Palo Alto, CA 94304, United States
| | - Gualberto Ruaño
- Institute of Living at Hartford Hospital, Hartford, CT 06102, United States
| | - Abiel Roche-Lima
- Research Centers in Minority Institutions (RCMI) Program, Center for Collaborative Research in Health Disparities (CCRHD), Academic Affairs Deanship, University of Puerto Rico - Medical Sciences Campus, San Juan, Puerto Rico, 00936, United States
| | - Cristina Alarcon
- Department of Pharmacology, Center for Pharmacogenomics, Feinberg School of Medicine, Northwestern University, Chicago IL 60611, United States
| | - Marylyn D. Ritchie
- Department of Genetics and Institute for Biomedical Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, United States
| | - Minoli A. Perera
- Department of Pharmacology, Center for Pharmacogenomics, Feinberg School of Medicine, Northwestern University, Chicago IL 60611, United States
| | - Jorge Duconge
- Research Centers in Minority Institutions (RCMI) Program, Center for Collaborative Research in Health Disparities (CCRHD), Academic Affairs Deanship, University of Puerto Rico - Medical Sciences Campus, San Juan, Puerto Rico, 00936, United States
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Puerto Rico - Medical Sciences Campus, San Juan, Puerto Rico, 00936, United States
| |
Collapse
|
38
|
Housini M, Zhou Z, Gutierrez J, Rao S, Jomaa R, Subasinghe K, Reid DM, Silzer T, Phillips N, O'Bryant S, Barber RC. Top Alzheimer's disease risk allele frequencies differ in HABS-HD Mexican- versus Non-Hispanic White Americans. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12518. [PMID: 38155914 PMCID: PMC10752755 DOI: 10.1002/dad2.12518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 11/13/2023] [Accepted: 11/25/2023] [Indexed: 12/30/2023]
Abstract
INTRODUCTION: Here we evaluate frequencies of the top 10 Alzheimer's disease (AD) risk alleles for late-onset AD in Mexican American (MA) and non-Hispanic White (NHW) American participants enrolled in the Health and Aging Brain Study-Health Disparities Study cohort. METHODS: Using DNA extracted from this community-based diverse population, we calculated the genotype frequencies in each population to determine whether a significant difference is detected between the different ethnicities. DNA genotyping was performed per manufacturers' protocols. RESULTS: Allele and genotype frequencies for 9 of the 11 single nucleotide polymorphisms (two apolipoprotein E variants, CR1, BIN1, DRB1, NYAP1, PTK2B, FERMT2, and ABCA7) differed significantly between MAs and NHWs. DISCUSSION: The significant differences in frequencies of top AD risk alleles observed here across MAs and NHWs suggest that ethnicity-specific genetic risks for AD exist. Given our results, we are advancing additional projects to further elucidate ethnicity-specific differences in AD.
Collapse
Affiliation(s)
- Mohammad Housini
- Department of Pharmacology and NeuroscienceSchool of Biomedical SciencesUniversity of North Texas Health Science CenterFort WorthTexasUSA
- Department of Family Medicine & Manipulative MedicineTexas College of Osteopathic MedicineUniversity of North Texas Health Science CenterFort WorthTexasUSA
| | - Zhengyang Zhou
- Department of Biostatistics and EpidemiologySchool of Public HealthUniversity of North Texas Health Science CenterFort WorthTexasUSA
- Institute for Translational ResearchUNT Health Science CenterFort WorthTexasUSA
| | - John Gutierrez
- Department of Internal MedicineTexas Institute for Graduate Medical Education and ResearchSan AntonioTexasUSA
| | - Sumedha Rao
- Department of Family Medicine & Manipulative MedicineTexas College of Osteopathic MedicineUniversity of North Texas Health Science CenterFort WorthTexasUSA
| | - Rodwan Jomaa
- Department of Family Medicine & Manipulative MedicineTexas College of Osteopathic MedicineUniversity of North Texas Health Science CenterFort WorthTexasUSA
| | - Kumudu Subasinghe
- Department of MicrobiologyImmunology and GeneticsSchool of Biomedical SciencesUniversity of North Texas Health Science CenterFort WorthTexasUSA
| | - Danielle Marie Reid
- Department of MicrobiologyImmunology and GeneticsSchool of Biomedical SciencesUniversity of North Texas Health Science CenterFort WorthTexasUSA
| | - Talisa Silzer
- Department of MicrobiologyImmunology and GeneticsSchool of Biomedical SciencesUniversity of North Texas Health Science CenterFort WorthTexasUSA
| | - Nicole Phillips
- Institute for Translational ResearchUNT Health Science CenterFort WorthTexasUSA
- Department of MicrobiologyImmunology and GeneticsSchool of Biomedical SciencesUniversity of North Texas Health Science CenterFort WorthTexasUSA
| | - Sid O'Bryant
- Department of Family Medicine & Manipulative MedicineTexas College of Osteopathic MedicineUniversity of North Texas Health Science CenterFort WorthTexasUSA
- Institute for Translational ResearchUNT Health Science CenterFort WorthTexasUSA
| | - Robert Clinton Barber
- Department of Family Medicine & Manipulative MedicineTexas College of Osteopathic MedicineUniversity of North Texas Health Science CenterFort WorthTexasUSA
- Institute for Translational ResearchUNT Health Science CenterFort WorthTexasUSA
| | | |
Collapse
|
39
|
Cheng X, Du F, Long X, Huang J. Genetic Inheritance Models of Non-Syndromic Cleft Lip with or without Palate: From Monogenic to Polygenic. Genes (Basel) 2023; 14:1859. [PMID: 37895208 PMCID: PMC10606748 DOI: 10.3390/genes14101859] [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: 08/14/2023] [Revised: 09/18/2023] [Accepted: 09/21/2023] [Indexed: 10/29/2023] Open
Abstract
Non-syndromic cleft lip with or without palate (NSCL/P) is a prevalent birth defect that affects 1/500-1/1400 live births globally. The genetic basis of NSCL/P is intricate and involves both genetic and environmental factors. In the past few years, various genetic inheritance models have been proposed to elucidate the underlying mechanisms of NSCL/P. These models range from simple monogenic inheritance to more complex polygenic inheritance. Here, we present a comprehensive overview of the genetic inheritance model of NSCL/P exemplified by representative genes and regions from both monogenic and polygenic perspectives. We also summarize existing association studies and corresponding loci of NSCL/P within the Chinese population and highlight the potential of utilizing polygenic risk scores for risk stratification of NSCL/P. The potential application of polygenic models offers promising avenues for improved risk assessment and personalized approaches in the prevention and management of NSCL/P individuals.
Collapse
Affiliation(s)
- Xi Cheng
- Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China; (X.C.); (F.D.); (X.L.)
| | - Fengzhou Du
- Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China; (X.C.); (F.D.); (X.L.)
- Department of Plastic Surgery, Peking Union Medical College Hospital, Beijing 100730, China
| | - Xiao Long
- Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China; (X.C.); (F.D.); (X.L.)
- Department of Plastic Surgery, Peking Union Medical College Hospital, Beijing 100730, China
| | - Jiuzuo Huang
- Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China; (X.C.); (F.D.); (X.L.)
- Department of Plastic Surgery, Peking Union Medical College Hospital, Beijing 100730, China
| |
Collapse
|
40
|
Gyawali PK, Le Guen Y, Liu X, Belloy ME, Tang H, Zou J, He Z. Improving genetic risk prediction across diverse population by disentangling ancestry representations. Commun Biol 2023; 6:964. [PMID: 37736834 PMCID: PMC10517023 DOI: 10.1038/s42003-023-05352-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Accepted: 09/12/2023] [Indexed: 09/23/2023] Open
Abstract
Risk prediction models using genetic data have seen increasing traction in genomics. However, most of the polygenic risk models were developed using data from participants with similar (mostly European) ancestry. This can lead to biases in the risk predictors resulting in poor generalization when applied to minority populations and admixed individuals such as African Americans. To address this issue, largely due to the prediction models being biased by the underlying population structure, we propose a deep-learning framework that leverages data from diverse population and disentangles ancestry from the phenotype-relevant information in its representation. The ancestry disentangled representation can be used to build risk predictors that perform better across minority populations. We applied the proposed method to the analysis of Alzheimer's disease genetics. Comparing with standard linear and nonlinear risk prediction methods, the proposed method substantially improves risk prediction in minority populations, including admixed individuals, without needing self-reported ancestry information.
Collapse
Affiliation(s)
- Prashnna K Gyawali
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA.
| | - Yann Le Guen
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
- Institut du Cerveau-Paris Brain Institute-ICM, Paris, France
| | - Xiaoxia Liu
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Michael E Belloy
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Hua Tang
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - James Zou
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.
| | - Zihuai He
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA.
- Quantitative Sciences Unit, Department of Medicine (Biomedical Informatics Research), Stanford University, Stanford, CA, USA.
| |
Collapse
|
41
|
Salehi Nowbandegani P, Wohns AW, Ballard JL, Lander ES, Bloemendal A, Neale BM, O'Connor LJ. Extremely sparse models of linkage disequilibrium in ancestrally diverse association studies. Nat Genet 2023; 55:1494-1502. [PMID: 37640881 DOI: 10.1038/s41588-023-01487-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Accepted: 07/24/2023] [Indexed: 08/31/2023]
Abstract
Linkage disequilibrium (LD) is the correlation among nearby genetic variants. In genetic association studies, LD is often modeled using large correlation matrices, but this approach is inefficient, especially in ancestrally diverse studies. In the present study, we introduce LD graphical models (LDGMs), which are an extremely sparse and efficient representation of LD. LDGMs are derived from genome-wide genealogies; statistical relationships among alleles in the LDGM correspond to genealogical relationships among haplotypes. We published LDGMs and ancestry-specific LDGM precision matrices for 18 million common variants (minor allele frequency >1%) in five ancestry groups, validated their accuracy and demonstrated order-of-magnitude improvements in runtime for commonly used LD matrix computations. We implemented an extremely fast multiancestry polygenic prediction method, BLUPx-ldgm, which performs better than a similar method based on the reference LD correlation matrix. LDGMs will enable sophisticated methods that scale to ancestrally diverse genetic association data across millions of variants and individuals.
Collapse
Affiliation(s)
- Pouria Salehi Nowbandegani
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
| | - Anthony Wilder Wohns
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
- Stanford University School of Medicine, Stanford, CA, USA.
| | - Jenna L Ballard
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Graduate Group in Genomics and Computational Biology, University of Pennsylvania, Philadelphia, PA, USA
| | - Eric S Lander
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biology, MIT, Cambridge, MA, USA
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
| | - Alex Bloemendal
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Benjamin M Neale
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Luke J O'Connor
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
| |
Collapse
|
42
|
Moorjani P, Hellenthal G. Methods for Assessing Population Relationships and History Using Genomic Data. Annu Rev Genomics Hum Genet 2023; 24:305-332. [PMID: 37220313 PMCID: PMC11040641 DOI: 10.1146/annurev-genom-111422-025117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
Genetic data contain a record of our evolutionary history. The availability of large-scale datasets of human populations from various geographic areas and timescales, coupled with advances in the computational methods to analyze these data, has transformed our ability to use genetic data to learn about our evolutionary past. Here, we review some of the widely used statistical methods to explore and characterize population relationships and history using genomic data. We describe the intuition behind commonly used approaches, their interpretation, and important limitations. For illustration, we apply some of these techniques to genome-wide autosomal data from 929 individuals representing 53 worldwide populations that are part of the Human Genome Diversity Project. Finally, we discuss the new frontiers in genomic methods to learn about population history. In sum, this review highlights the power (and limitations) of DNA to infer features of human evolutionary history, complementing the knowledge gleaned from other disciplines, such as archaeology, anthropology, and linguistics.
Collapse
Affiliation(s)
- Priya Moorjani
- Department of Molecular and Cell Biology and Center for Computational Biology, University of California, Berkeley, California, USA;
| | - Garrett Hellenthal
- UCL Genetics Institute and Research Department of Genetics, Evolution, and Environment, University College London, London, United Kingdom;
| |
Collapse
|
43
|
Felsky D, Cannitelli A, Pipitone J. Whole Person Modeling: a transdisciplinary approach to mental health research. DISCOVER MENTAL HEALTH 2023; 3:16. [PMID: 37638348 PMCID: PMC10449734 DOI: 10.1007/s44192-023-00041-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Accepted: 08/10/2023] [Indexed: 08/29/2023]
Abstract
The growing global burden of mental illness has prompted calls for innovative research strategies. Theoretical models of mental health include complex contributions of biological, psychosocial, experiential, and other environmental influences. Accordingly, neuropsychiatric research has self-organized into largely isolated disciplines working to decode each individual contribution. However, research directly modeling objective biological measurements in combination with cognitive, psychological, demographic, or other environmental measurements is only now beginning to proliferate. This review aims to (1) to describe the landscape of modern mental health research and current movement towards integrative study, (2) to provide a concrete framework for quantitative integrative research, which we call Whole Person Modeling, (3) to explore existing and emerging techniques and methods used in Whole Person Modeling, and (4) to discuss our observations about the scarcity, potential value, and untested aspects of highly transdisciplinary research in general. Whole Person Modeling studies have the potential to provide a better understanding of multilevel phenomena, deliver more accurate diagnostic and prognostic tests to aid in clinical decision making, and test long standing theoretical models of mental illness. Some current barriers to progress include challenges with interdisciplinary communication and collaboration, systemic cultural barriers to transdisciplinary career paths, technical challenges in model specification, bias, and data harmonization, and gaps in transdisciplinary educational programs. We hope to ease anxiety in the field surrounding the often mysterious and intimidating world of transdisciplinary, data-driven mental health research and provide a useful orientation for students or highly specialized researchers who are new to this area.
Collapse
Affiliation(s)
- Daniel Felsky
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, 250 College Street, Toronto, ON M5T 1R8 Canada
- Department of Psychiatry, Faculty of Medicine, University of Toronto, Toronto, ON Canada
- Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON Canada
- Rotman Research Institute, Baycrest Hospital, Toronto, ON Canada
- Faculty of Medicine, McMaster University, Hamilton, ON Canada
| | - Alyssa Cannitelli
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, 250 College Street, Toronto, ON M5T 1R8 Canada
- Faculty of Medicine, McMaster University, Hamilton, ON Canada
| | - Jon Pipitone
- Department of Psychiatry, Queen’s University, Kingston, ON Canada
| |
Collapse
|
44
|
Tan T, Atkinson EG. Strategies for the Genomic Analysis of Admixed Populations. Annu Rev Biomed Data Sci 2023; 6:105-127. [PMID: 37127050 PMCID: PMC10871708 DOI: 10.1146/annurev-biodatasci-020722-014310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Admixed populations constitute a large portion of global human genetic diversity, yet they are often left out of genomics analyses. This exclusion is problematic, as it leads to disparities in the understanding of the genetic structure and history of diverse cohorts and the performance of genomic medicine across populations. Admixed populations have particular statistical challenges, as they inherit genomic segments from multiple source populations-the primary reason they have historically been excluded from genetic studies. In recent years, however, an increasing number of statistical methods and software tools have been developed to account for and leverage admixture in the context of genomics analyses. Here, we provide a survey of such computational strategies for the informed consideration of admixture to allow for the well-calibrated inclusion of mixed ancestry populations in large-scale genomics studies, and we detail persisting gaps in existing tools.
Collapse
Affiliation(s)
- Taotao Tan
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA;
| | - Elizabeth G Atkinson
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA;
| |
Collapse
|
45
|
Gupta Y, Friedman DJ, McNulty M, Khan A, Lane B, Wang C, Ke J, Jin G, Wooden B, Knob AL, Lim TY, Appel GB, Huggins K, Liu L, Mitrotti A, Stangl MC, Bomback A, Westland R, Bodria M, Marasa M, Shang N, Cohen DJ, Crew RJ, Morello W, Canetta P, Radhakrishnan J, Martino J, Liu Q, Chung WK, Espinoza A, Luo Y, Wei WQ, Feng Q, Weng C, Fang Y, Kullo IJ, Naderian M, Limdi N, Irvin MR, Tiwari H, Mohan S, Rao M, Dube G, Chaudhary NS, Gutiérrez OM, Judd SE, Cushman M, Lange LA, Lange EM, Bivona DL, Verbitsky M, Winkler CA, Kopp JB, Santoriello D, Batal I, Brant Pinheiro SV, Araújo Oliveira E, E Silva ACS, Pisani I, Fiaccadori E, Lin F, Gesualdo L, Amoroso A, Ghiggeri GM, D'Agati VD, Magistroni R, Kenny EE, Loos RJF, Montini G, Hildebrandt F, Paul DS, Petrovski S, Goldstein DB, Kretzler M, Gbadegesin R, Gharavi AG, Kiryluk K, Sampson MG, Pollak MR, Sanna-Cherchi S. Strong protective effect of the APOL1 p.N264K variant against G2-associated focal segmental glomerulosclerosis and kidney disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.08.02.23293554. [PMID: 37577628 PMCID: PMC10418582 DOI: 10.1101/2023.08.02.23293554] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
Black Americans have a significantly higher risk of developing chronic kidney disease (CKD), especially focal segmental glomerulosclerosis (FSGS), than European Americans. Two coding variants (G1 and G2) in the APOL1 gene play a major role in this disparity. While 13% of Black Americans carry the high-risk recessive genotypes, only a fraction of these individuals develops FSGS or kidney failure, indicating the involvement of additional disease modifiers. Here, we show that the presence of the APOL1 p.N264K missense variant, when co-inherited with the G2 APOL1 risk allele, substantially reduces the penetrance of the G1G2 and G2G2 high-risk genotypes by rendering these genotypes low-risk. These results align with prior functional evidence showing that the p.N264K variant reduces the toxicity of the APOL1 high-risk alleles. These findings have important implications for our understanding of the mechanisms of APOL1 -associated nephropathy, as well as for the clinical management of individuals with high-risk genotypes that include the G2 allele.
Collapse
|
46
|
Smith JL, Tcheandjieu C, Dikilitas O, lyer K, Miyazawa K, Hilliard A, Lynch J, Rotter JI, Chen YDI, Sheu WHH, Chang KM, Kanoni S, Tsao P, Ito K, Kosel M, Clarke SL, Schaid DJ, Assimes TL, Kullo IJ. A Multi-Ancestry Polygenic Risk Score for Coronary Heart Disease Based on an Ancestrally Diverse Genome-Wide Association Study and Population-Specific Optimization. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.02.23290896. [PMID: 37609230 PMCID: PMC10441485 DOI: 10.1101/2023.06.02.23290896] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
Background Predictive performance of polygenic risk scores (PRS) varies across populations. To facilitate equitable clinical use, we developed PRS for coronary heart disease (PRSCHD) for 5 genetic ancestry groups. Methods We derived ancestry-specific and multi-ancestry PRSCHD based on pruning and thresholding (PRSP+T) and continuous shrinkage priors (PRSCSx) applied on summary statistics from the largest multi-ancestry genome-wide meta-analysis for CHD to date, including 1.1 million participants from 5 continental populations. Following training and optimization of PRSCHD in the Million Veteran Program, we evaluated predictive performance of the best performing PRSCHD in 176,988 individuals across 9 cohorts of diverse genetic ancestry. Results Multi-ancestry PRSP+T outperformed ancestry specific PRSP+T across a range of tuning values. In training stage, for all ancestry groups, PRSCSx performed better than PRSP+T and multi-ancestry PRS outperformed ancestry-specific PRS. In independent validation cohorts, the selected multi-ancestry PRSP+T demonstrated the strongest association with CHD in individuals of South Asian (SAS) and European (EUR) ancestry (OR per 1SD[95% CI]; 2.75[2.41-3.14], 1.65[1.59-1.72]), followed by East Asian (EAS) (1.56[1.50-1.61]), Hispanic/Latino (HIS) (1.38[1.24-1.54]), and weakest in African (AFR) ancestry (1.16[1.11-1.21]). The selected multi-ancestry PRSCSx showed stronger associacion with CHD in comparison within each ancestry group where the association was strongest in SAS (2.67[2.38-3.00]) and EUR (1.65[1.59-1.71]), progressively decreasing in EAS (1.59[1.54-1.64]), HIS (1.51[1.35-1.69]), and lowest in AFR (1.20[1.15-1.26]). Conclusions Utilizing diverse summary statistics from a large multi-ancestry genome-wide meta-analysis led to improved performance of PRSCHD in most ancestry groups compared to single-ancestry methods. Improvement of predictive performance was limited, specifically in AFR and HIS, despite use of one of the largest and most diverse set of training and validation cohorts to date. This highlights the need for larger GWAS datasets of AFR and HIS individuals to enhance performance of PRSCHD.
Collapse
Affiliation(s)
- Johanna L. Smith
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Catherine Tcheandjieu
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
- Gladstone Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA, USA
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Ozan Dikilitas
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Kruthika lyer
- Stanford University School of Medicine, Palo Alto, CA, USA
| | - Kazuo Miyazawa
- Riken Ctr. for Integrative Medical Sciences, Yokohama City, Japan
| | - Austin Hilliard
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Stanford University School of Medicine, Palo Alto, CA, USA
| | - Julie Lynch
- Salt Lake City VA Met CTR., Salt Lake City, UT, USA
| | - Jerome I. Rotter
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Yii-Der Ida Chen
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Wayne Huey-Herng Sheu
- Institute of Molecular and Genomic Medicine, National Health Research Institutes, Taiwan
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Kyong-Mi Chang
- Corporal Michael J Crescenz VA Medical Ctr. Philadelphia, PA, USA
| | | | - Phil Tsao
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Stanford University, Stanford, CA, USA
| | - Kaoru Ito
- Riken Ctr. for Integrative Medical Sciences, Yokohama City, Japan
| | - Matthew Kosel
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Shoa L. Clarke
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Stanford University, Stanford, CA, USA
| | - Daniel J. Schaid
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | | | - Iftikhar J. Kullo
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| |
Collapse
|
47
|
Wendt FR, Pathak GA, Vahey J, Qin X, Koller D, Cabrera-Mendoza B, Haeny A, Harrington KM, Rajeevan N, Duong LM, Levey DF, De Angelis F, De Lillo A, Bigdeli TB, Pyarajan S, Gaziano JM, Gelernter J, Aslan M, Provenzale D, Helmer DA, Hauser ER, Polimanti R. Modeling the longitudinal changes of ancestry diversity in the Million Veteran Program. Hum Genomics 2023; 17:46. [PMID: 37268996 PMCID: PMC10239111 DOI: 10.1186/s40246-023-00487-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 05/05/2023] [Indexed: 06/04/2023] Open
Abstract
BACKGROUND The Million Veteran Program (MVP) participants represent 100 years of US history, including significant social and demographic changes over time. Our study assessed two aspects of the MVP: (i) longitudinal changes in population diversity and (ii) how these changes can be accounted for in genome-wide association studies (GWAS). To investigate these aspects, we divided MVP participants into five birth cohorts (N-range = 123,888 [born from 1943 to 1947] to 136,699 [born from 1948 to 1953]). RESULTS Ancestry groups were defined by (i) HARE (harmonized ancestry and race/ethnicity) and (ii) a random-forest clustering approach using the 1000 Genomes Project and the Human Genome Diversity Project (1kGP + HGDP) reference panels (77 world populations representing six continental groups). In these groups, we performed GWASs of height, a trait potentially affected by population stratification. Birth cohorts demonstrate important trends in ancestry diversity over time. More recent HARE-assigned Europeans, Africans, and Hispanics had lower European ancestry proportions than older birth cohorts (0.010 < Cohen's d < 0.259, p < 7.80 × 10-4). Conversely, HARE-assigned East Asians showed an increase in European ancestry proportion over time. In GWAS of height using HARE assignments, genomic inflation due to population stratification was prevalent across all birth cohorts (linkage disequilibrium score regression intercept = 1.08 ± 0.042). The 1kGP + HGDP-based ancestry assignment significantly reduced the population stratification (mean intercept reduction = 0.045 ± 0.007, p < 0.05) confounding in the GWAS statistics. CONCLUSIONS This study provides a characterization of ancestry diversity of the MVP cohort over time and compares two strategies to infer genetically defined ancestry groups by assessing differences in controlling population stratification in genome-wide association studies.
Collapse
Affiliation(s)
- Frank R Wendt
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- VA Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA CT Healthcare System, VA CT 116A2, 950 Campbell Avenue, West Haven, CT, 06516, USA
| | - Gita A Pathak
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- VA Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA CT Healthcare System, VA CT 116A2, 950 Campbell Avenue, West Haven, CT, 06516, USA
| | - Jacqueline Vahey
- Durham VA Medical Center, Durham, NC, USA
- Duke University, Carmichael Building, 300 N Duke St, Durham, NC, 27701, USA
| | - Xuejun Qin
- Durham VA Medical Center, Durham, NC, USA
- Duke University, Carmichael Building, 300 N Duke St, Durham, NC, 27701, USA
| | - Dora Koller
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- VA Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA CT Healthcare System, VA CT 116A2, 950 Campbell Avenue, West Haven, CT, 06516, USA
| | - Brenda Cabrera-Mendoza
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- VA Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA CT Healthcare System, VA CT 116A2, 950 Campbell Avenue, West Haven, CT, 06516, USA
| | - Angela Haeny
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Kelly M Harrington
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA, USA
- Department of Psychiatry, Boston University School of Medicine, Boston, MA, USA
| | - Nallakkandi Rajeevan
- VA Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA CT Healthcare System, VA CT 116A2, 950 Campbell Avenue, West Haven, CT, 06516, USA
- Yale Center for Medical Informatics, Yale School of Medicine, New Haven, CT, USA
| | - Linh M Duong
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- VA Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA CT Healthcare System, VA CT 116A2, 950 Campbell Avenue, West Haven, CT, 06516, USA
| | - Daniel F Levey
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- VA Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA CT Healthcare System, VA CT 116A2, 950 Campbell Avenue, West Haven, CT, 06516, USA
| | - Flavio De Angelis
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- VA Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA CT Healthcare System, VA CT 116A2, 950 Campbell Avenue, West Haven, CT, 06516, USA
| | | | - Tim B Bigdeli
- SUNY Downstate Health Sciences University, Brooklyn, NY, USA
- VA New York Harbor Healthcare System, Brooklyn, NY, USA
| | - Saiju Pyarajan
- Massachusetts Area Veterans Epidemiology, Research, and Information Center (MAVERIC), Jamaica Plain, MA, USA
- VA Cooperative Studies Program, VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital and Harvard School of Medicine, Boston, MA, USA
| | - John Michael Gaziano
- VA Cooperative Studies Program, VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital and Harvard School of Medicine, Boston, MA, USA
| | - Joel Gelernter
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
- Department of Psychiatry, VA CT Healthcare System, West Haven, CT, USA
| | - Mihaela Aslan
- VA Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA CT Healthcare System, VA CT 116A2, 950 Campbell Avenue, West Haven, CT, 06516, USA
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Dawn Provenzale
- Durham VA Medical Center, Durham, NC, USA
- Duke University, Carmichael Building, 300 N Duke St, Durham, NC, 27701, USA
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Drew A Helmer
- Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey VA Medical Center, Houston, TX, USA
- Department of Medicine, Baylor College of Medicine, Houston, TX, USA
| | - Elizabeth R Hauser
- Durham VA Medical Center, Durham, NC, USA.
- Duke University, Carmichael Building, 300 N Duke St, Durham, NC, 27701, USA.
| | - Renato Polimanti
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA.
- VA Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA CT Healthcare System, VA CT 116A2, 950 Campbell Avenue, West Haven, CT, 06516, USA.
| |
Collapse
|
48
|
Mester R, Hou K, Ding Y, Meeks G, Burch KS, Bhattacharya A, Henn BM, Pasaniuc B. Impact of cross-ancestry genetic architecture on GWASs in admixed populations. Am J Hum Genet 2023; 110:927-939. [PMID: 37224807 PMCID: PMC10257009 DOI: 10.1016/j.ajhg.2023.05.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 05/04/2023] [Accepted: 05/04/2023] [Indexed: 05/26/2023] Open
Abstract
Genome-wide association studies (GWASs) have identified thousands of variants for disease risk. These studies have predominantly been conducted in individuals of European ancestries, which raises questions about their transferability to individuals of other ancestries. Of particular interest are admixed populations, usually defined as populations with recent ancestry from two or more continental sources. Admixed genomes contain segments of distinct ancestries that vary in composition across individuals in the population, allowing for the same allele to induce risk for disease on different ancestral backgrounds. This mosaicism raises unique challenges for GWASs in admixed populations, such as the need to correctly adjust for population stratification. In this work we quantify the impact of differences in estimated allelic effect sizes for risk variants between ancestry backgrounds on association statistics. Specifically, while the possibility of estimated allelic effect-size heterogeneity by ancestry (HetLanc) can be modeled when performing a GWAS in admixed populations, the extent of HetLanc needed to overcome the penalty from an additional degree of freedom in the association statistic has not been thoroughly quantified. Using extensive simulations of admixed genotypes and phenotypes, we find that controlling for and conditioning effect sizes on local ancestry can reduce statistical power by up to 72%. This finding is especially pronounced in the presence of allele frequency differentiation. We replicate simulation results using 4,327 African-European admixed genomes from the UK Biobank for 12 traits to find that for most significant SNPs, HetLanc is not large enough for GWASs to benefit from modeling heterogeneity in this way.
Collapse
Affiliation(s)
- Rachel Mester
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA.
| | - Kangcheng Hou
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Yi Ding
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Gillian Meeks
- Integrative Genetics and Genomics Graduate Group, University of California, Davis, Davis, CA 95616, USA
| | - Kathryn S Burch
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Arjun Bhattacharya
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Brenna M Henn
- Department of Anthropology, Center for Population Biology and the Genome Center, University of California, Davis, Davis, CA 95616, USA
| | - Bogdan Pasaniuc
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Bioinformatics Interdepartmental Program, 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; Institute of Precision Health, David Geffen School of Medicine, 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.
| |
Collapse
|
49
|
Li Q, Chen J, Faux P, Delgado ME, Bonfante B, Fuentes-Guajardo M, Mendoza-Revilla J, Chacón-Duque JC, Hurtado M, Villegas V, Granja V, Jaramillo C, Arias W, Barquera R, Everardo-Martínez P, Sánchez-Quinto M, Gómez-Valdés J, Villamil-Ramírez H, Silva de Cerqueira CC, Hünemeier T, Ramallo V, Wu S, Du S, Giardina A, Paria SS, Khokan MR, Gonzalez-José R, Schüler-Faccini L, Bortolini MC, Acuña-Alonzo V, Canizales-Quinteros S, Gallo C, Poletti G, Rojas W, Rothhammer F, Navarro N, Wang S, Adhikari K, Ruiz-Linares A. Automatic landmarking identifies new loci associated with face morphology and implicates Neanderthal introgression in human nasal shape. Commun Biol 2023; 6:481. [PMID: 37156940 PMCID: PMC10167347 DOI: 10.1038/s42003-023-04838-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 04/12/2023] [Indexed: 05/10/2023] Open
Abstract
We report a genome-wide association study of facial features in >6000 Latin Americans based on automatic landmarking of 2D portraits and testing for association with inter-landmark distances. We detected significant associations (P-value <5 × 10-8) at 42 genome regions, nine of which have been previously reported. In follow-up analyses, 26 of the 33 novel regions replicate in East Asians, Europeans, or Africans, and one mouse homologous region influences craniofacial morphology in mice. The novel region in 1q32.3 shows introgression from Neanderthals and we find that the introgressed tract increases nasal height (consistent with the differentiation between Neanderthals and modern humans). Novel regions include candidate genes and genome regulatory elements previously implicated in craniofacial development, and show preferential transcription in cranial neural crest cells. The automated approach used here should simplify the collection of large study samples from across the world, facilitating a cosmopolitan characterization of the genetics of facial features.
Collapse
Affiliation(s)
- Qing Li
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, 200438, China
| | - Jieyi Chen
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, 200438, China
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Pierre Faux
- Aix-Marseille Université, CNRS, EFS, ADES, Marseille, 13005, France
| | - Miguel Eduardo Delgado
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, 200438, China
- División Antropología, Facultad de Ciencias Naturales y Museo, Universidad Nacional de La Plata, La Plata, República Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas, CONICET, Buenos Aires, República Argentina
| | - Betty Bonfante
- Aix-Marseille Université, CNRS, EFS, ADES, Marseille, 13005, France
| | - Macarena Fuentes-Guajardo
- Departamento de Tecnología Médica, Facultad de Ciencias de la Salud, Universidad de Tarapacá, Arica, 1000000, Chile
| | - Javier Mendoza-Revilla
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, 31, Perú
- Unit of Human Evolutionary Genetics, Institut Pasteur, Paris, 75015, France
| | - J Camilo Chacón-Duque
- Division of Vertebrates and Anthropology, Department of Earth Sciences, Natural History Museum, London, SW7 5BD, UK
| | - Malena Hurtado
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, 31, Perú
| | - Valeria Villegas
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, 31, Perú
| | - Vanessa Granja
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, 31, Perú
| | - Claudia Jaramillo
- GENMOL (Genética Molecular), Universidad de Antioquia, Medellín, 5001000, Colombia
| | - William Arias
- GENMOL (Genética Molecular), Universidad de Antioquia, Medellín, 5001000, Colombia
| | - Rodrigo Barquera
- Molecular Genetics Laboratory, National School of Anthropology and History, Mexico City, 14050, Mexico, 6600, Mexico
- Department of Archaeogenetics, Max Planck Institute for the Science of Human History (MPI-SHH), Jena, 07745, Germany
| | - Paola Everardo-Martínez
- Molecular Genetics Laboratory, National School of Anthropology and History, Mexico City, 14050, Mexico, 6600, Mexico
| | - Mirsha Sánchez-Quinto
- Forensic Science, Faculty of Medicine, UNAM (Universidad Nacional Autónoma de México), Mexico City, 06320, Mexico
| | - Jorge Gómez-Valdés
- Molecular Genetics Laboratory, National School of Anthropology and History, Mexico City, 14050, Mexico, 6600, Mexico
| | - Hugo Villamil-Ramírez
- Unidad de Genomica de Poblaciones Aplicada a la Salud, Facultad de Química, UNAM-Instituto Nacional de Medicina Genómica, Mexico City, 4510, Mexico
| | | | - Tábita Hünemeier
- Departamento de Genética e Biologia Evolutiva, Instituto de Biociências, Universidade de São Paulo, São Paulo, SP, 05508-090, Brazil
| | - Virginia Ramallo
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre, 90040-060, Brazil
- Instituto Patagónico de Ciencias Sociales y Humanas, Centro Nacional Patagónico, CONICET, Puerto Madryn, U9129ACD, Argentina
| | - Sijie Wu
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, 200438, China
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Siyuan Du
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Andrea Giardina
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, MK7 6AA, United Kingdom
| | - Soumya Subhra Paria
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, MK7 6AA, United Kingdom
| | - Mahfuzur Rahman Khokan
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, MK7 6AA, United Kingdom
| | - Rolando Gonzalez-José
- Instituto Patagónico de Ciencias Sociales y Humanas, Centro Nacional Patagónico, CONICET, Puerto Madryn, U9129ACD, Argentina
| | - Lavinia Schüler-Faccini
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre, 90040-060, Brazil
| | - Maria-Cátira Bortolini
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre, 90040-060, Brazil
| | - Victor Acuña-Alonzo
- Molecular Genetics Laboratory, National School of Anthropology and History, Mexico City, 14050, Mexico, 6600, Mexico
| | - Samuel Canizales-Quinteros
- Unidad de Genomica de Poblaciones Aplicada a la Salud, Facultad de Química, UNAM-Instituto Nacional de Medicina Genómica, Mexico City, 4510, Mexico
| | - Carla Gallo
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, 31, Perú
| | - Giovanni Poletti
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, 31, Perú
| | - Winston Rojas
- GENMOL (Genética Molecular), Universidad de Antioquia, Medellín, 5001000, Colombia
| | - Francisco Rothhammer
- Instituto de Alta Investigación, Universidad de Tarapacá, Arica, Arica, 1000000, Chile
| | - Nicolas Navarro
- Biogéosciences, UMR 6282 CNRS, Université de Bourgogne, Dijon, 21000, France
- EPHE, PSL University, Paris, 75014, France
| | - Sijia Wang
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, 200438, China
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Kaustubh Adhikari
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, MK7 6AA, United Kingdom.
- Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, London, WC1E 6BT, UK.
| | - Andrés Ruiz-Linares
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, 200438, China.
- Aix-Marseille Université, CNRS, EFS, ADES, Marseille, 13005, France.
- Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, London, WC1E 6BT, UK.
| |
Collapse
|
50
|
Yang Z, Huaman BC, Reyes-Dumeyer D, Montesinos R, Soto-Añari M, Custodio N, Tosto G. A benchmark study on current GWAS models in admixed populations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.27.538299. [PMID: 37163101 PMCID: PMC10168347 DOI: 10.1101/2023.04.27.538299] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Objective The performances of popular Genome-wide association study (GWAS) models haven't been examined yet in a consistent manner under the scenario of genetic admixture, which introduces several challenging aspects such as heterogeneity of minor allele frequency (MAF), a wide spectrum of case-control ratio, and varying effect sizes etc. Methods We generated a cohort of synthetic individuals (N=19,234) that simulates 1) a large sample size; 2) two-way admixture [Native American-European ancestry] and 3) a binary phenotype. We then examined the inflation factors produced by three popular GWAS tools: GMMAT, SAIGE, and Tractor. We also computed power calculations under different MAFs, case-control ratios, and varying ancestry percentages. Then, we employed a cohort of Peruvians (N=249) to further examine the performances of the testing models on 1) real genetic data and 2) small sample sizes. Finally, we validated these findings using an independent Peruvian cohort (N=109) included in 1000 Genome project (1000G). Results In the synthetic cohort, SAIGE performed better than GMMAT and Tractor in terms of type-I error rate, especially under severe unbalanced case-control ratio. On the contrary, power analysis identified Tractor as the best method to pinpoint ancestry-specific causal variants, but showed decreased power when no adequate heterogeneity of the true effect sizes was simulated between ancestries. The real Peruvian data showed that Tractor is severely affected by small sample sizes, and produced severely inflated statistics, which we replicated in the 1000G Peruvian cohort. Discussion The current study illustrates the limitations of available GWAS tools under different scenarios of genetic admixture. We urge caution when interpreting results under complex population scenarios.
Collapse
Affiliation(s)
- Zikun Yang
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University. 630 West 168 Street, New York, NY 10032, USA
- The Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University. 630 West 168 Street, New York, NY 10032, USA
| | - Basilio Cieza Huaman
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University. 630 West 168 Street, New York, NY 10032, USA
- The Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University. 630 West 168 Street, New York, NY 10032, USA
| | - Dolly Reyes-Dumeyer
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University. 630 West 168 Street, New York, NY 10032, USA
- The Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University. 630 West 168 Street, New York, NY 10032, USA
- Department of Neurology, College of Physicians and Surgeons, Columbia University and the New York Presbyterian Hospital. 710 West 168 Street, New York, NY 10032, USA
| | - Rosa Montesinos
- Unidad de diagnóstico de deterioro cognitivo y prevención de demencia, Instituto Peruano de Neurociencias, Lima, Perú
| | - Marcio Soto-Añari
- Instituto de Neurociencia Cognitiva, Arequipa, Perú
- Laboratorio de Neurociencia, Universidad Católica San Pablo, Arequipa, Perú
| | - Nilton Custodio
- Unidad de diagnóstico de deterioro cognitivo y prevención de demencia, Instituto Peruano de Neurociencias, Lima, Perú
| | - Giuseppe Tosto
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University. 630 West 168 Street, New York, NY 10032, USA
- The Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University. 630 West 168 Street, New York, NY 10032, USA
- Department of Neurology, College of Physicians and Surgeons, Columbia University and the New York Presbyterian Hospital. 710 West 168 Street, New York, NY 10032, USA
| |
Collapse
|