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Genetic analyses of diverse populations improves discovery for complex traits
by
Moreno-Estrada, Andres
, Sabatti, Chiara
, Patel, Yesha M.
, Lim, Unhee
, Poisner, Hannah
, Vishnu, Abhishek
, Fernández-Rhodes, Lindsay
, Lin, Dan-Yu
, Canizales-Quinteros, Samuel
, Park, Sung-Shim L.
, Young, Kristin L.
, Hailu, Benyam
, Jackson, Rebecca D.
, Huckins, Laura M.
, Fornage, Myriam
, Schurmann, Claudia
, Richard, Melissa A.
, Loos, Ruth J. F.
, Verbanck, Marie
, Graff, Mariaelisa
, Hu, Yao
, Vahi, Karan
, Romm, Jane
, Nishimura, Katherine K.
, Belbin, Gillian M.
, Wilkens, Lynne R.
, Zubair, Niha
, Kocarnik, Jonathan M.
, Jeff, Janina
, Conomos, Matthew P.
, Stram, Daniel O.
, Doheny, Kimberly
, Bottinger, Erwin P.
, Laurie, Cecelia A.
, Kenny, Eimear E.
, Laurie, Cathy C.
, Sockell, Alexandra
, Sheng, Xin
, Li, Yuqing
, Lu, Yingchang
, Walker, Ryan W.
, Norman, Paul J.
, Matise, Tara C.
, Heiss, Gerardo
, Acuña-Alonso, Victor
, Tao, Ran
, Hindorff, Lucia A.
, Sandoval, Karla
, Stahl, Eli A.
, Wojcik, Genevieve L.
, Boerwinkle, Eric
, Winkler, Cheryl A.
, Buyske, Steven
, Ambite, Jose Luis
, Deelman, Ewa
, Pooler, Loreall C.
, Peters, Ulrike
, Justice, Anne E.
, Haessler, Jeffrey
, Haiman, Christopher A.
, Bustamante, Carlos D.
, Henn, Brenna M.
, Gigno
in
45/43
/ 631/208/205/2138
/ 631/208/457/649
/ Analysis
/ Architecture
/ Asian People - genetics
/ Bioinformatics
/ Black or African American
/ Black People - genetics
/ Body Height - genetics
/ Chronic conditions
/ Chronic illnesses
/ Cohort Studies
/ Disease
/ Drug development
/ Economic indicators
/ Ecosystems
/ Epidemiology
/ Ethnic factors
/ Ethnic groups
/ Ethnicity
/ Female
/ Gene mapping
/ Genetic analysis
/ Genetic aspects
/ Genetic diversity
/ Genetic research
/ Genetics, Medical - methods
/ Genome-wide association studies
/ Genome-Wide Association Study - methods
/ Genomes
/ Genomics
/ Health disparities
/ Health Equity - trends
/ Health Status Disparities
/ Hemoglobin
/ Heterogeneity
/ Hispanic Americans
/ Hispanic or Latino - genetics
/ Humanities and Social Sciences
/ Humans
/ Letter
/ Loci
/ Male
/ Mapping
/ Minority & ethnic groups
/ Minority Groups
/ multidisciplinary
/ Multifactorial Inheritance - genetics
/ Phenotypes
/ Population
/ Population genetics
/ Population studies
/ Populations
/ Precision medicine
/ Principal components analysis
/ Representations
/ Science
/ Science (multidisciplinary)
/ United States
/ Women's Health
/ Womens health
2019
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Genetic analyses of diverse populations improves discovery for complex traits
by
Moreno-Estrada, Andres
, Sabatti, Chiara
, Patel, Yesha M.
, Lim, Unhee
, Poisner, Hannah
, Vishnu, Abhishek
, Fernández-Rhodes, Lindsay
, Lin, Dan-Yu
, Canizales-Quinteros, Samuel
, Park, Sung-Shim L.
, Young, Kristin L.
, Hailu, Benyam
, Jackson, Rebecca D.
, Huckins, Laura M.
, Fornage, Myriam
, Schurmann, Claudia
, Richard, Melissa A.
, Loos, Ruth J. F.
, Verbanck, Marie
, Graff, Mariaelisa
, Hu, Yao
, Vahi, Karan
, Romm, Jane
, Nishimura, Katherine K.
, Belbin, Gillian M.
, Wilkens, Lynne R.
, Zubair, Niha
, Kocarnik, Jonathan M.
, Jeff, Janina
, Conomos, Matthew P.
, Stram, Daniel O.
, Doheny, Kimberly
, Bottinger, Erwin P.
, Laurie, Cecelia A.
, Kenny, Eimear E.
, Laurie, Cathy C.
, Sockell, Alexandra
, Sheng, Xin
, Li, Yuqing
, Lu, Yingchang
, Walker, Ryan W.
, Norman, Paul J.
, Matise, Tara C.
, Heiss, Gerardo
, Acuña-Alonso, Victor
, Tao, Ran
, Hindorff, Lucia A.
, Sandoval, Karla
, Stahl, Eli A.
, Wojcik, Genevieve L.
, Boerwinkle, Eric
, Winkler, Cheryl A.
, Buyske, Steven
, Ambite, Jose Luis
, Deelman, Ewa
, Pooler, Loreall C.
, Peters, Ulrike
, Justice, Anne E.
, Haessler, Jeffrey
, Haiman, Christopher A.
, Bustamante, Carlos D.
, Henn, Brenna M.
, Gigno
in
45/43
/ 631/208/205/2138
/ 631/208/457/649
/ Analysis
/ Architecture
/ Asian People - genetics
/ Bioinformatics
/ Black or African American
/ Black People - genetics
/ Body Height - genetics
/ Chronic conditions
/ Chronic illnesses
/ Cohort Studies
/ Disease
/ Drug development
/ Economic indicators
/ Ecosystems
/ Epidemiology
/ Ethnic factors
/ Ethnic groups
/ Ethnicity
/ Female
/ Gene mapping
/ Genetic analysis
/ Genetic aspects
/ Genetic diversity
/ Genetic research
/ Genetics, Medical - methods
/ Genome-wide association studies
/ Genome-Wide Association Study - methods
/ Genomes
/ Genomics
/ Health disparities
/ Health Equity - trends
/ Health Status Disparities
/ Hemoglobin
/ Heterogeneity
/ Hispanic Americans
/ Hispanic or Latino - genetics
/ Humanities and Social Sciences
/ Humans
/ Letter
/ Loci
/ Male
/ Mapping
/ Minority & ethnic groups
/ Minority Groups
/ multidisciplinary
/ Multifactorial Inheritance - genetics
/ Phenotypes
/ Population
/ Population genetics
/ Population studies
/ Populations
/ Precision medicine
/ Principal components analysis
/ Representations
/ Science
/ Science (multidisciplinary)
/ United States
/ Women's Health
/ Womens health
2019
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Do you wish to request the book?
Genetic analyses of diverse populations improves discovery for complex traits
by
Moreno-Estrada, Andres
, Sabatti, Chiara
, Patel, Yesha M.
, Lim, Unhee
, Poisner, Hannah
, Vishnu, Abhishek
, Fernández-Rhodes, Lindsay
, Lin, Dan-Yu
, Canizales-Quinteros, Samuel
, Park, Sung-Shim L.
, Young, Kristin L.
, Hailu, Benyam
, Jackson, Rebecca D.
, Huckins, Laura M.
, Fornage, Myriam
, Schurmann, Claudia
, Richard, Melissa A.
, Loos, Ruth J. F.
, Verbanck, Marie
, Graff, Mariaelisa
, Hu, Yao
, Vahi, Karan
, Romm, Jane
, Nishimura, Katherine K.
, Belbin, Gillian M.
, Wilkens, Lynne R.
, Zubair, Niha
, Kocarnik, Jonathan M.
, Jeff, Janina
, Conomos, Matthew P.
, Stram, Daniel O.
, Doheny, Kimberly
, Bottinger, Erwin P.
, Laurie, Cecelia A.
, Kenny, Eimear E.
, Laurie, Cathy C.
, Sockell, Alexandra
, Sheng, Xin
, Li, Yuqing
, Lu, Yingchang
, Walker, Ryan W.
, Norman, Paul J.
, Matise, Tara C.
, Heiss, Gerardo
, Acuña-Alonso, Victor
, Tao, Ran
, Hindorff, Lucia A.
, Sandoval, Karla
, Stahl, Eli A.
, Wojcik, Genevieve L.
, Boerwinkle, Eric
, Winkler, Cheryl A.
, Buyske, Steven
, Ambite, Jose Luis
, Deelman, Ewa
, Pooler, Loreall C.
, Peters, Ulrike
, Justice, Anne E.
, Haessler, Jeffrey
, Haiman, Christopher A.
, Bustamante, Carlos D.
, Henn, Brenna M.
, Gigno
in
45/43
/ 631/208/205/2138
/ 631/208/457/649
/ Analysis
/ Architecture
/ Asian People - genetics
/ Bioinformatics
/ Black or African American
/ Black People - genetics
/ Body Height - genetics
/ Chronic conditions
/ Chronic illnesses
/ Cohort Studies
/ Disease
/ Drug development
/ Economic indicators
/ Ecosystems
/ Epidemiology
/ Ethnic factors
/ Ethnic groups
/ Ethnicity
/ Female
/ Gene mapping
/ Genetic analysis
/ Genetic aspects
/ Genetic diversity
/ Genetic research
/ Genetics, Medical - methods
/ Genome-wide association studies
/ Genome-Wide Association Study - methods
/ Genomes
/ Genomics
/ Health disparities
/ Health Equity - trends
/ Health Status Disparities
/ Hemoglobin
/ Heterogeneity
/ Hispanic Americans
/ Hispanic or Latino - genetics
/ Humanities and Social Sciences
/ Humans
/ Letter
/ Loci
/ Male
/ Mapping
/ Minority & ethnic groups
/ Minority Groups
/ multidisciplinary
/ Multifactorial Inheritance - genetics
/ Phenotypes
/ Population
/ Population genetics
/ Population studies
/ Populations
/ Precision medicine
/ Principal components analysis
/ Representations
/ Science
/ Science (multidisciplinary)
/ United States
/ Women's Health
/ Womens health
2019
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Genetic analyses of diverse populations improves discovery for complex traits
Journal Article
Genetic analyses of diverse populations improves discovery for complex traits
2019
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Overview
Genome-wide association studies (GWAS) have laid the foundation for investigations into the biology of complex traits, drug development and clinical guidelines. However, the majority of discovery efforts are based on data from populations of European ancestry
1
–
3
. In light of the differential genetic architecture that is known to exist between populations, bias in representation can exacerbate existing disease and healthcare disparities. Critical variants may be missed if they have a low frequency or are completely absent in European populations, especially as the field shifts its attention towards rare variants, which are more likely to be population-specific
4
–
10
. Additionally, effect sizes and their derived risk prediction scores derived in one population may not accurately extrapolate to other populations
11
,
12
. Here we demonstrate the value of diverse, multi-ethnic participants in large-scale genomic studies. The Population Architecture using Genomics and Epidemiology (PAGE) study conducted a GWAS of 26 clinical and behavioural phenotypes in 49,839 non-European individuals. Using strategies tailored for analysis of multi-ethnic and admixed populations, we describe a framework for analysing diverse populations, identify 27 novel loci and 38 secondary signals at known loci, as well as replicate 1,444 GWAS catalogue associations across these traits. Our data show evidence of effect-size heterogeneity across ancestries for published GWAS associations, substantial benefits for fine-mapping using diverse cohorts and insights into clinical implications. In the United States—where minority populations have a disproportionately higher burden of chronic conditions
13
—the lack of representation of diverse populations in genetic research will result in inequitable access to precision medicine for those with the highest burden of disease. We strongly advocate for continued, large genome-wide efforts in diverse populations to maximize genetic discovery and reduce health disparities.
Genetic analyses of ancestrally diverse populations show evidence of heterogeneity across ancestries and provide insights into clinical implications, highlighting the importance of including ancestrally diverse populations to maximize genetic discovery and reduce health disparities.
Publisher
Nature Publishing Group UK,Nature Publishing Group
Subject
/ Analysis
/ Disease
/ Female
/ Genome-wide association studies
/ Genome-Wide Association Study - methods
/ Genomes
/ Genomics
/ Hispanic or Latino - genetics
/ Humanities and Social Sciences
/ Humans
/ Letter
/ Loci
/ Male
/ Mapping
/ Multifactorial Inheritance - genetics
/ Principal components analysis
/ Science
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