Trans-ethnic genome-wide association study of blood metabolites in the Chronic Renal Insufficiency Cohort (CRIC) study
Metabolomics genome wide association study (GWAS) help outline the genetic contribution to human metabolism. However, studies to date have focused on relatively healthy, population-based samples of White individuals. Here, we conducted a GWAS of 537 blood metabolites measured in the Chronic Renal In...
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creator | Rhee, Eugene P. Surapaneni, Aditya Zheng, Zihe Zhou, Linda Dutta, Diptavo Arking, Dan E. Zhang, Jingning Duong, ThuyVy Chatterjee, Nilanjan Luo, Shengyuan Schlosser, Pascal Mehta, Rupal Waikar, Sushrut S. Saraf, Santosh L. Kelly, Tanika N. Hamm, Lee L. Rao, Panduranga S. Mathew, Anna V. Hsu, Chi-yuan Parsa, Afshin Vasan, Ramachandran S. Kimmel, Paul L. Clish, Clary B. Coresh, Josef Feldman, Harold I. Grams, Morgan E. |
description | Metabolomics genome wide association study (GWAS) help outline the genetic contribution to human metabolism. However, studies to date have focused on relatively healthy, population-based samples of White individuals. Here, we conducted a GWAS of 537 blood metabolites measured in the Chronic Renal Insufficiency Cohort (CRIC) Study, with separate analyses in 822 White and 687 Black study participants. Trans-ethnic meta-analysis was then applied to improve fine-mapping of potential causal variants. Mean estimated glomerular filtration rate was 44.4 and 41.5 mL/min/1.73m2 in the White and Black participants, respectively. There were 45 significant metabolite associations at 19 loci, including novel associations at PYROXD2, PHYHD1, FADS1-3, ACOT2, MYRF, FAAH, and LIPC. The strength of associations was unchanged in models additionally adjusted for estimated glomerular filtration rate and proteinuria, consistent with a direct biochemical effect of gene products on associated metabolites. At several loci, trans-ethnic meta-analysis, which leverages differences in linkage disequilibrium across populations, reduced the number and/or genomic interval spanned by potentially causal single nucleotide polymorphisms compared to fine-mapping in the White participant cohort alone. Across all validated associations, we found strong concordance in effect sizes of the potentially causal single nucleotide polymorphisms between White and Black study participants. Thus, our study identifies novel genetic determinants of blood metabolites in chronic kidney disease, demonstrates the value of diverse cohorts to improve causal inference in metabolomics GWAS, and underscores the shared genetic basis of metabolism across race.
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doi_str_mv | 10.1016/j.kint.2022.01.014 |
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[Display omitted]</description><identifier>ISSN: 0085-2538</identifier><identifier>ISSN: 1523-1755</identifier><identifier>EISSN: 1523-1755</identifier><identifier>DOI: 10.1016/j.kint.2022.01.014</identifier><identifier>PMID: 35120996</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Cohort Studies ; Ethnicity ; Female ; Genome-Wide Association Study ; GWAS ; Humans ; Linkage Disequilibrium ; Male ; metabolomics ; Polymorphism, Single Nucleotide ; Renal Insufficiency, Chronic - genetics ; trans-ethnic meta-analysis</subject><ispartof>Kidney international, 2022-04, Vol.101 (4), p.814-823</ispartof><rights>2022 International Society of Nephrology</rights><rights>Copyright © 2022 International Society of Nephrology. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c455t-a2f793d5217a544dcd715dca83efde32e66e3ea7282eebece0ef4e4f7cb360683</citedby><cites>FETCH-LOGICAL-c455t-a2f793d5217a544dcd715dca83efde32e66e3ea7282eebece0ef4e4f7cb360683</cites><orcidid>0000-0003-4004-326X ; 0000-0002-8584-4194 ; 0000-0002-3235-6832</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,315,781,785,886,27929,27930</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35120996$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Rhee, Eugene P.</creatorcontrib><creatorcontrib>Surapaneni, Aditya</creatorcontrib><creatorcontrib>Zheng, Zihe</creatorcontrib><creatorcontrib>Zhou, Linda</creatorcontrib><creatorcontrib>Dutta, Diptavo</creatorcontrib><creatorcontrib>Arking, Dan E.</creatorcontrib><creatorcontrib>Zhang, Jingning</creatorcontrib><creatorcontrib>Duong, ThuyVy</creatorcontrib><creatorcontrib>Chatterjee, Nilanjan</creatorcontrib><creatorcontrib>Luo, Shengyuan</creatorcontrib><creatorcontrib>Schlosser, Pascal</creatorcontrib><creatorcontrib>Mehta, Rupal</creatorcontrib><creatorcontrib>Waikar, Sushrut S.</creatorcontrib><creatorcontrib>Saraf, Santosh L.</creatorcontrib><creatorcontrib>Kelly, Tanika N.</creatorcontrib><creatorcontrib>Hamm, Lee L.</creatorcontrib><creatorcontrib>Rao, Panduranga S.</creatorcontrib><creatorcontrib>Mathew, Anna V.</creatorcontrib><creatorcontrib>Hsu, Chi-yuan</creatorcontrib><creatorcontrib>Parsa, Afshin</creatorcontrib><creatorcontrib>Vasan, Ramachandran S.</creatorcontrib><creatorcontrib>Kimmel, Paul L.</creatorcontrib><creatorcontrib>Clish, Clary B.</creatorcontrib><creatorcontrib>Coresh, Josef</creatorcontrib><creatorcontrib>Feldman, Harold I.</creatorcontrib><creatorcontrib>Grams, Morgan E.</creatorcontrib><creatorcontrib>CKD Biomarkers Consortium and the Chronic Renal Insufficiency Cohort (CRIC) Study Investigators</creatorcontrib><title>Trans-ethnic genome-wide association study of blood metabolites in the Chronic Renal Insufficiency Cohort (CRIC) study</title><title>Kidney international</title><addtitle>Kidney Int</addtitle><description>Metabolomics genome wide association study (GWAS) help outline the genetic contribution to human metabolism. However, studies to date have focused on relatively healthy, population-based samples of White individuals. Here, we conducted a GWAS of 537 blood metabolites measured in the Chronic Renal Insufficiency Cohort (CRIC) Study, with separate analyses in 822 White and 687 Black study participants. Trans-ethnic meta-analysis was then applied to improve fine-mapping of potential causal variants. Mean estimated glomerular filtration rate was 44.4 and 41.5 mL/min/1.73m2 in the White and Black participants, respectively. There were 45 significant metabolite associations at 19 loci, including novel associations at PYROXD2, PHYHD1, FADS1-3, ACOT2, MYRF, FAAH, and LIPC. The strength of associations was unchanged in models additionally adjusted for estimated glomerular filtration rate and proteinuria, consistent with a direct biochemical effect of gene products on associated metabolites. At several loci, trans-ethnic meta-analysis, which leverages differences in linkage disequilibrium across populations, reduced the number and/or genomic interval spanned by potentially causal single nucleotide polymorphisms compared to fine-mapping in the White participant cohort alone. Across all validated associations, we found strong concordance in effect sizes of the potentially causal single nucleotide polymorphisms between White and Black study participants. Thus, our study identifies novel genetic determinants of blood metabolites in chronic kidney disease, demonstrates the value of diverse cohorts to improve causal inference in metabolomics GWAS, and underscores the shared genetic basis of metabolism across race.
[Display omitted]</description><subject>Cohort Studies</subject><subject>Ethnicity</subject><subject>Female</subject><subject>Genome-Wide Association Study</subject><subject>GWAS</subject><subject>Humans</subject><subject>Linkage Disequilibrium</subject><subject>Male</subject><subject>metabolomics</subject><subject>Polymorphism, Single Nucleotide</subject><subject>Renal Insufficiency, Chronic - genetics</subject><subject>trans-ethnic meta-analysis</subject><issn>0085-2538</issn><issn>1523-1755</issn><issn>1523-1755</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kU1r3DAQhkVpaTZp_0APRcf04I0-LNmGUggmaRcChZCehSyNY21tKZXkLfvv482mob0UBoTQO8-IeRD6QMmaEiovtuufzuc1I4ytCV2qfIVWVDBe0EqI12hFSC0KJnh9gk5T2pLl3nDyFp1wQRlpGrlCu7uofSogD94ZfA8-TFD8dhawTikYp7MLHqc82z0OPe7GECyeIOsujC5Dws7jPABuhxgOhFvwesQbn-a-d8aBN3vchiHEjM_b20376ch6h970ekzw_vk8Qz-ur-7ab8XN96-b9vKmMKUQudCsrxpuBaOVFmVpja2osEbXHHoLnIGUwEFXrGYAHRgg0JdQ9pXpuCSy5mfoy5H7MHcTWAM-Rz2qh-gmHfcqaKf-ffFuUPdhp-qmJFI2C-D8GRDDrxlSVpNLBsZRewhzUkwyubioOV-i7Bg1MaQUoX8ZQ4k6CFNbdRCmDsIUoUuVS9PHvz_40vLH0BL4fAzAsqadg6jS01rBuggmKxvc__iPhNSqtQ</recordid><startdate>20220401</startdate><enddate>20220401</enddate><creator>Rhee, Eugene P.</creator><creator>Surapaneni, Aditya</creator><creator>Zheng, Zihe</creator><creator>Zhou, Linda</creator><creator>Dutta, Diptavo</creator><creator>Arking, Dan E.</creator><creator>Zhang, Jingning</creator><creator>Duong, ThuyVy</creator><creator>Chatterjee, Nilanjan</creator><creator>Luo, Shengyuan</creator><creator>Schlosser, Pascal</creator><creator>Mehta, Rupal</creator><creator>Waikar, Sushrut S.</creator><creator>Saraf, Santosh L.</creator><creator>Kelly, Tanika N.</creator><creator>Hamm, Lee L.</creator><creator>Rao, Panduranga S.</creator><creator>Mathew, Anna V.</creator><creator>Hsu, Chi-yuan</creator><creator>Parsa, Afshin</creator><creator>Vasan, Ramachandran S.</creator><creator>Kimmel, Paul L.</creator><creator>Clish, Clary B.</creator><creator>Coresh, Josef</creator><creator>Feldman, Harold I.</creator><creator>Grams, Morgan E.</creator><general>Elsevier Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0003-4004-326X</orcidid><orcidid>https://orcid.org/0000-0002-8584-4194</orcidid><orcidid>https://orcid.org/0000-0002-3235-6832</orcidid></search><sort><creationdate>20220401</creationdate><title>Trans-ethnic genome-wide association study of blood metabolites in the Chronic Renal Insufficiency Cohort (CRIC) study</title><author>Rhee, Eugene P. ; Surapaneni, Aditya ; Zheng, Zihe ; Zhou, Linda ; Dutta, Diptavo ; Arking, Dan E. ; Zhang, Jingning ; Duong, ThuyVy ; Chatterjee, Nilanjan ; Luo, Shengyuan ; Schlosser, Pascal ; Mehta, Rupal ; Waikar, Sushrut S. ; Saraf, Santosh L. ; Kelly, Tanika N. ; Hamm, Lee L. ; Rao, Panduranga S. ; Mathew, Anna V. ; Hsu, Chi-yuan ; Parsa, Afshin ; Vasan, Ramachandran S. ; Kimmel, Paul L. ; Clish, Clary B. ; Coresh, Josef ; Feldman, Harold I. ; Grams, Morgan E.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c455t-a2f793d5217a544dcd715dca83efde32e66e3ea7282eebece0ef4e4f7cb360683</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Cohort Studies</topic><topic>Ethnicity</topic><topic>Female</topic><topic>Genome-Wide Association Study</topic><topic>GWAS</topic><topic>Humans</topic><topic>Linkage Disequilibrium</topic><topic>Male</topic><topic>metabolomics</topic><topic>Polymorphism, Single Nucleotide</topic><topic>Renal Insufficiency, Chronic - genetics</topic><topic>trans-ethnic meta-analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Rhee, Eugene P.</creatorcontrib><creatorcontrib>Surapaneni, Aditya</creatorcontrib><creatorcontrib>Zheng, Zihe</creatorcontrib><creatorcontrib>Zhou, Linda</creatorcontrib><creatorcontrib>Dutta, Diptavo</creatorcontrib><creatorcontrib>Arking, Dan E.</creatorcontrib><creatorcontrib>Zhang, Jingning</creatorcontrib><creatorcontrib>Duong, ThuyVy</creatorcontrib><creatorcontrib>Chatterjee, Nilanjan</creatorcontrib><creatorcontrib>Luo, Shengyuan</creatorcontrib><creatorcontrib>Schlosser, Pascal</creatorcontrib><creatorcontrib>Mehta, Rupal</creatorcontrib><creatorcontrib>Waikar, Sushrut S.</creatorcontrib><creatorcontrib>Saraf, Santosh L.</creatorcontrib><creatorcontrib>Kelly, Tanika N.</creatorcontrib><creatorcontrib>Hamm, Lee L.</creatorcontrib><creatorcontrib>Rao, Panduranga S.</creatorcontrib><creatorcontrib>Mathew, Anna V.</creatorcontrib><creatorcontrib>Hsu, Chi-yuan</creatorcontrib><creatorcontrib>Parsa, Afshin</creatorcontrib><creatorcontrib>Vasan, Ramachandran S.</creatorcontrib><creatorcontrib>Kimmel, Paul L.</creatorcontrib><creatorcontrib>Clish, Clary B.</creatorcontrib><creatorcontrib>Coresh, Josef</creatorcontrib><creatorcontrib>Feldman, Harold I.</creatorcontrib><creatorcontrib>Grams, Morgan E.</creatorcontrib><creatorcontrib>CKD Biomarkers Consortium and the Chronic Renal Insufficiency Cohort (CRIC) Study Investigators</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Kidney international</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Rhee, Eugene P.</au><au>Surapaneni, Aditya</au><au>Zheng, Zihe</au><au>Zhou, Linda</au><au>Dutta, Diptavo</au><au>Arking, Dan E.</au><au>Zhang, Jingning</au><au>Duong, ThuyVy</au><au>Chatterjee, Nilanjan</au><au>Luo, Shengyuan</au><au>Schlosser, Pascal</au><au>Mehta, Rupal</au><au>Waikar, Sushrut S.</au><au>Saraf, Santosh L.</au><au>Kelly, Tanika N.</au><au>Hamm, Lee L.</au><au>Rao, Panduranga S.</au><au>Mathew, Anna V.</au><au>Hsu, Chi-yuan</au><au>Parsa, Afshin</au><au>Vasan, Ramachandran S.</au><au>Kimmel, Paul L.</au><au>Clish, Clary B.</au><au>Coresh, Josef</au><au>Feldman, Harold I.</au><au>Grams, Morgan E.</au><aucorp>CKD Biomarkers Consortium and the Chronic Renal Insufficiency Cohort (CRIC) Study Investigators</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Trans-ethnic genome-wide association study of blood metabolites in the Chronic Renal Insufficiency Cohort (CRIC) study</atitle><jtitle>Kidney international</jtitle><addtitle>Kidney Int</addtitle><date>2022-04-01</date><risdate>2022</risdate><volume>101</volume><issue>4</issue><spage>814</spage><epage>823</epage><pages>814-823</pages><issn>0085-2538</issn><issn>1523-1755</issn><eissn>1523-1755</eissn><abstract>Metabolomics genome wide association study (GWAS) help outline the genetic contribution to human metabolism. However, studies to date have focused on relatively healthy, population-based samples of White individuals. Here, we conducted a GWAS of 537 blood metabolites measured in the Chronic Renal Insufficiency Cohort (CRIC) Study, with separate analyses in 822 White and 687 Black study participants. Trans-ethnic meta-analysis was then applied to improve fine-mapping of potential causal variants. Mean estimated glomerular filtration rate was 44.4 and 41.5 mL/min/1.73m2 in the White and Black participants, respectively. There were 45 significant metabolite associations at 19 loci, including novel associations at PYROXD2, PHYHD1, FADS1-3, ACOT2, MYRF, FAAH, and LIPC. The strength of associations was unchanged in models additionally adjusted for estimated glomerular filtration rate and proteinuria, consistent with a direct biochemical effect of gene products on associated metabolites. At several loci, trans-ethnic meta-analysis, which leverages differences in linkage disequilibrium across populations, reduced the number and/or genomic interval spanned by potentially causal single nucleotide polymorphisms compared to fine-mapping in the White participant cohort alone. Across all validated associations, we found strong concordance in effect sizes of the potentially causal single nucleotide polymorphisms between White and Black study participants. Thus, our study identifies novel genetic determinants of blood metabolites in chronic kidney disease, demonstrates the value of diverse cohorts to improve causal inference in metabolomics GWAS, and underscores the shared genetic basis of metabolism across race.
[Display omitted]</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>35120996</pmid><doi>10.1016/j.kint.2022.01.014</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0003-4004-326X</orcidid><orcidid>https://orcid.org/0000-0002-8584-4194</orcidid><orcidid>https://orcid.org/0000-0002-3235-6832</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Cohort Studies Ethnicity Female Genome-Wide Association Study GWAS Humans Linkage Disequilibrium Male metabolomics Polymorphism, Single Nucleotide Renal Insufficiency, Chronic - genetics trans-ethnic meta-analysis |
title | Trans-ethnic genome-wide association study of blood metabolites in the Chronic Renal Insufficiency Cohort (CRIC) study |
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