Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics
Background Quantitative red blood cell (RBC) traits are highly polygenic clinically relevant traits, with approximately 500 reported GWAS loci. The majority of RBC trait GWAS have been performed in European- or East Asian-ancestry populations, despite evidence that rare or ancestry-specific variatio...
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| Autor*in: |
Hodonsky, Chani J. [verfasserIn] Baldassari, Antoine R. [verfasserIn] Bien, Stephanie A. [verfasserIn] Raffield, Laura M. [verfasserIn] Highland, Heather M. [verfasserIn] Sitlani, Colleen M. [verfasserIn] Wojcik, Genevieve L. [verfasserIn] Tao, Ran [verfasserIn] Graff, Marielisa [verfasserIn] Tang, Weihong [verfasserIn] Thyagarajan, Bharat [verfasserIn] Buyske, Steve [verfasserIn] Fornage, Myriam [verfasserIn] Hindorff, Lucia A. [verfasserIn] Li, Yun [verfasserIn] Lin, Danyu [verfasserIn] Reiner, Alex P. [verfasserIn] North, Kari E. [verfasserIn] Loos, Ruth J. F. [verfasserIn] Kooperberg, Charles [verfasserIn] Avery, Christy L. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2020 |
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| Übergeordnetes Werk: |
Enthalten in: BMC genomics - London : BioMed Central, 2000, 21(2020), 1 vom: 14. März |
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| Übergeordnetes Werk: |
volume:21 ; year:2020 ; number:1 ; day:14 ; month:03 |
| Links: |
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| DOI / URN: |
10.1186/s12864-020-6626-9 |
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| Katalog-ID: |
SPR039101150 |
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| 100 | 1 | |a Hodonsky, Chani J. |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics |
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| 520 | |a Background Quantitative red blood cell (RBC) traits are highly polygenic clinically relevant traits, with approximately 500 reported GWAS loci. The majority of RBC trait GWAS have been performed in European- or East Asian-ancestry populations, despite evidence that rare or ancestry-specific variation contributes substantially to RBC trait heritability. Recently developed combined-phenotype methods which leverage genetic trait correlation to improve statistical power have not yet been applied to these traits. Here we leveraged correlation of seven quantitative RBC traits in performing a combined-phenotype analysis in a multi-ethnic study population. Results We used the adaptive sum of powered scores (aSPU) test to assess combined-phenotype associations between ~ 21 million SNPs and seven RBC traits in a multi-ethnic population (maximum n = 67,885 participants; 24% African American, 30% Hispanic/Latino, and 43% European American; 76% female). Thirty-nine loci in our multi-ethnic population contained at least one significant association signal (p < 5E-9), with lead SNPs at nine loci significantly associated with three or more RBC traits. A majority of the lead SNPs were common (MAF > 5%) across all ancestral populations. Nineteen additional independent association signals were identified at seven known loci (HFE, KIT, HBS1L/MYB, CITED2/FILNC1, ABO, HBA1/2, and PLIN4/5). For example, the HBA1/2 locus contained 14 conditionally independent association signals, 11 of which were previously unreported and are specific to African and Amerindian ancestries. One variant in this region was common in all ancestries, but exhibited a narrower LD block in African Americans than European Americans or Hispanics/Latinos. GTEx eQTL analysis of all independent lead SNPs yielded 31 significant associations in relevant tissues, over half of which were not at the gene immediately proximal to the lead SNP. Conclusion This work identified seven loci containing multiple independent association signals for RBC traits using a combined-phenotype approach, which may improve discovery in genetically correlated traits. Highly complex genetic architecture at the HBA1/2 locus was only revealed by the inclusion of African Americans and Hispanics/Latinos, underscoring the continued importance of expanding large GWAS to include ancestrally diverse populations. | ||
| 650 | 4 | |a Blood cell traits |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Combined-phenotype analysis |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Pleiotropy |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Diversity |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Multi-ethnic |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a GWAS |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Baldassari, Antoine R. |e verfasserin |4 aut | |
| 700 | 1 | |a Bien, Stephanie A. |e verfasserin |4 aut | |
| 700 | 1 | |a Raffield, Laura M. |e verfasserin |4 aut | |
| 700 | 1 | |a Highland, Heather M. |e verfasserin |4 aut | |
| 700 | 1 | |a Sitlani, Colleen M. |e verfasserin |4 aut | |
| 700 | 1 | |a Wojcik, Genevieve L. |e verfasserin |4 aut | |
| 700 | 1 | |a Tao, Ran |e verfasserin |4 aut | |
| 700 | 1 | |a Graff, Marielisa |e verfasserin |4 aut | |
| 700 | 1 | |a Tang, Weihong |e verfasserin |4 aut | |
| 700 | 1 | |a Thyagarajan, Bharat |e verfasserin |4 aut | |
| 700 | 1 | |a Buyske, Steve |e verfasserin |4 aut | |
| 700 | 1 | |a Fornage, Myriam |e verfasserin |4 aut | |
| 700 | 1 | |a Hindorff, Lucia A. |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Yun |e verfasserin |4 aut | |
| 700 | 1 | |a Lin, Danyu |e verfasserin |4 aut | |
| 700 | 1 | |a Reiner, Alex P. |e verfasserin |4 aut | |
| 700 | 1 | |a North, Kari E. |e verfasserin |4 aut | |
| 700 | 1 | |a Loos, Ruth J. F. |e verfasserin |4 aut | |
| 700 | 1 | |a Kooperberg, Charles |e verfasserin |4 aut | |
| 700 | 1 | |a Avery, Christy L. |e verfasserin |4 aut | |
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10.1186/s12864-020-6626-9 doi (DE-627)SPR039101150 (SPR)s12864-020-6626-9-e DE-627 ger DE-627 rakwb eng 570 610 ASE 42.20 bkl 44.48 bkl Hodonsky, Chani J. verfasserin aut Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background Quantitative red blood cell (RBC) traits are highly polygenic clinically relevant traits, with approximately 500 reported GWAS loci. The majority of RBC trait GWAS have been performed in European- or East Asian-ancestry populations, despite evidence that rare or ancestry-specific variation contributes substantially to RBC trait heritability. Recently developed combined-phenotype methods which leverage genetic trait correlation to improve statistical power have not yet been applied to these traits. Here we leveraged correlation of seven quantitative RBC traits in performing a combined-phenotype analysis in a multi-ethnic study population. Results We used the adaptive sum of powered scores (aSPU) test to assess combined-phenotype associations between ~ 21 million SNPs and seven RBC traits in a multi-ethnic population (maximum n = 67,885 participants; 24% African American, 30% Hispanic/Latino, and 43% European American; 76% female). Thirty-nine loci in our multi-ethnic population contained at least one significant association signal (p < 5E-9), with lead SNPs at nine loci significantly associated with three or more RBC traits. A majority of the lead SNPs were common (MAF > 5%) across all ancestral populations. Nineteen additional independent association signals were identified at seven known loci (HFE, KIT, HBS1L/MYB, CITED2/FILNC1, ABO, HBA1/2, and PLIN4/5). For example, the HBA1/2 locus contained 14 conditionally independent association signals, 11 of which were previously unreported and are specific to African and Amerindian ancestries. One variant in this region was common in all ancestries, but exhibited a narrower LD block in African Americans than European Americans or Hispanics/Latinos. GTEx eQTL analysis of all independent lead SNPs yielded 31 significant associations in relevant tissues, over half of which were not at the gene immediately proximal to the lead SNP. Conclusion This work identified seven loci containing multiple independent association signals for RBC traits using a combined-phenotype approach, which may improve discovery in genetically correlated traits. Highly complex genetic architecture at the HBA1/2 locus was only revealed by the inclusion of African Americans and Hispanics/Latinos, underscoring the continued importance of expanding large GWAS to include ancestrally diverse populations. Blood cell traits (dpeaa)DE-He213 Combined-phenotype analysis (dpeaa)DE-He213 Pleiotropy (dpeaa)DE-He213 Diversity (dpeaa)DE-He213 Multi-ethnic (dpeaa)DE-He213 GWAS (dpeaa)DE-He213 Baldassari, Antoine R. verfasserin aut Bien, Stephanie A. verfasserin aut Raffield, Laura M. verfasserin aut Highland, Heather M. verfasserin aut Sitlani, Colleen M. verfasserin aut Wojcik, Genevieve L. verfasserin aut Tao, Ran verfasserin aut Graff, Marielisa verfasserin aut Tang, Weihong verfasserin aut Thyagarajan, Bharat verfasserin aut Buyske, Steve verfasserin aut Fornage, Myriam verfasserin aut Hindorff, Lucia A. verfasserin aut Li, Yun verfasserin aut Lin, Danyu verfasserin aut Reiner, Alex P. verfasserin aut North, Kari E. verfasserin aut Loos, Ruth J. F. verfasserin aut Kooperberg, Charles verfasserin aut Avery, Christy L. verfasserin aut Enthalten in BMC genomics London : BioMed Central, 2000 21(2020), 1 vom: 14. März (DE-627)326644954 (DE-600)2041499-7 1471-2164 nnns volume:21 year:2020 number:1 day:14 month:03 https://dx.doi.org/10.1186/s12864-020-6626-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 42.20 ASE 44.48 ASE AR 21 2020 1 14 03 |
| spelling |
10.1186/s12864-020-6626-9 doi (DE-627)SPR039101150 (SPR)s12864-020-6626-9-e DE-627 ger DE-627 rakwb eng 570 610 ASE 42.20 bkl 44.48 bkl Hodonsky, Chani J. verfasserin aut Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background Quantitative red blood cell (RBC) traits are highly polygenic clinically relevant traits, with approximately 500 reported GWAS loci. The majority of RBC trait GWAS have been performed in European- or East Asian-ancestry populations, despite evidence that rare or ancestry-specific variation contributes substantially to RBC trait heritability. Recently developed combined-phenotype methods which leverage genetic trait correlation to improve statistical power have not yet been applied to these traits. Here we leveraged correlation of seven quantitative RBC traits in performing a combined-phenotype analysis in a multi-ethnic study population. Results We used the adaptive sum of powered scores (aSPU) test to assess combined-phenotype associations between ~ 21 million SNPs and seven RBC traits in a multi-ethnic population (maximum n = 67,885 participants; 24% African American, 30% Hispanic/Latino, and 43% European American; 76% female). Thirty-nine loci in our multi-ethnic population contained at least one significant association signal (p < 5E-9), with lead SNPs at nine loci significantly associated with three or more RBC traits. A majority of the lead SNPs were common (MAF > 5%) across all ancestral populations. Nineteen additional independent association signals were identified at seven known loci (HFE, KIT, HBS1L/MYB, CITED2/FILNC1, ABO, HBA1/2, and PLIN4/5). For example, the HBA1/2 locus contained 14 conditionally independent association signals, 11 of which were previously unreported and are specific to African and Amerindian ancestries. One variant in this region was common in all ancestries, but exhibited a narrower LD block in African Americans than European Americans or Hispanics/Latinos. GTEx eQTL analysis of all independent lead SNPs yielded 31 significant associations in relevant tissues, over half of which were not at the gene immediately proximal to the lead SNP. Conclusion This work identified seven loci containing multiple independent association signals for RBC traits using a combined-phenotype approach, which may improve discovery in genetically correlated traits. Highly complex genetic architecture at the HBA1/2 locus was only revealed by the inclusion of African Americans and Hispanics/Latinos, underscoring the continued importance of expanding large GWAS to include ancestrally diverse populations. Blood cell traits (dpeaa)DE-He213 Combined-phenotype analysis (dpeaa)DE-He213 Pleiotropy (dpeaa)DE-He213 Diversity (dpeaa)DE-He213 Multi-ethnic (dpeaa)DE-He213 GWAS (dpeaa)DE-He213 Baldassari, Antoine R. verfasserin aut Bien, Stephanie A. verfasserin aut Raffield, Laura M. verfasserin aut Highland, Heather M. verfasserin aut Sitlani, Colleen M. verfasserin aut Wojcik, Genevieve L. verfasserin aut Tao, Ran verfasserin aut Graff, Marielisa verfasserin aut Tang, Weihong verfasserin aut Thyagarajan, Bharat verfasserin aut Buyske, Steve verfasserin aut Fornage, Myriam verfasserin aut Hindorff, Lucia A. verfasserin aut Li, Yun verfasserin aut Lin, Danyu verfasserin aut Reiner, Alex P. verfasserin aut North, Kari E. verfasserin aut Loos, Ruth J. F. verfasserin aut Kooperberg, Charles verfasserin aut Avery, Christy L. verfasserin aut Enthalten in BMC genomics London : BioMed Central, 2000 21(2020), 1 vom: 14. März (DE-627)326644954 (DE-600)2041499-7 1471-2164 nnns volume:21 year:2020 number:1 day:14 month:03 https://dx.doi.org/10.1186/s12864-020-6626-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 42.20 ASE 44.48 ASE AR 21 2020 1 14 03 |
| allfields_unstemmed |
10.1186/s12864-020-6626-9 doi (DE-627)SPR039101150 (SPR)s12864-020-6626-9-e DE-627 ger DE-627 rakwb eng 570 610 ASE 42.20 bkl 44.48 bkl Hodonsky, Chani J. verfasserin aut Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background Quantitative red blood cell (RBC) traits are highly polygenic clinically relevant traits, with approximately 500 reported GWAS loci. The majority of RBC trait GWAS have been performed in European- or East Asian-ancestry populations, despite evidence that rare or ancestry-specific variation contributes substantially to RBC trait heritability. Recently developed combined-phenotype methods which leverage genetic trait correlation to improve statistical power have not yet been applied to these traits. Here we leveraged correlation of seven quantitative RBC traits in performing a combined-phenotype analysis in a multi-ethnic study population. Results We used the adaptive sum of powered scores (aSPU) test to assess combined-phenotype associations between ~ 21 million SNPs and seven RBC traits in a multi-ethnic population (maximum n = 67,885 participants; 24% African American, 30% Hispanic/Latino, and 43% European American; 76% female). Thirty-nine loci in our multi-ethnic population contained at least one significant association signal (p < 5E-9), with lead SNPs at nine loci significantly associated with three or more RBC traits. A majority of the lead SNPs were common (MAF > 5%) across all ancestral populations. Nineteen additional independent association signals were identified at seven known loci (HFE, KIT, HBS1L/MYB, CITED2/FILNC1, ABO, HBA1/2, and PLIN4/5). For example, the HBA1/2 locus contained 14 conditionally independent association signals, 11 of which were previously unreported and are specific to African and Amerindian ancestries. One variant in this region was common in all ancestries, but exhibited a narrower LD block in African Americans than European Americans or Hispanics/Latinos. GTEx eQTL analysis of all independent lead SNPs yielded 31 significant associations in relevant tissues, over half of which were not at the gene immediately proximal to the lead SNP. Conclusion This work identified seven loci containing multiple independent association signals for RBC traits using a combined-phenotype approach, which may improve discovery in genetically correlated traits. Highly complex genetic architecture at the HBA1/2 locus was only revealed by the inclusion of African Americans and Hispanics/Latinos, underscoring the continued importance of expanding large GWAS to include ancestrally diverse populations. Blood cell traits (dpeaa)DE-He213 Combined-phenotype analysis (dpeaa)DE-He213 Pleiotropy (dpeaa)DE-He213 Diversity (dpeaa)DE-He213 Multi-ethnic (dpeaa)DE-He213 GWAS (dpeaa)DE-He213 Baldassari, Antoine R. verfasserin aut Bien, Stephanie A. verfasserin aut Raffield, Laura M. verfasserin aut Highland, Heather M. verfasserin aut Sitlani, Colleen M. verfasserin aut Wojcik, Genevieve L. verfasserin aut Tao, Ran verfasserin aut Graff, Marielisa verfasserin aut Tang, Weihong verfasserin aut Thyagarajan, Bharat verfasserin aut Buyske, Steve verfasserin aut Fornage, Myriam verfasserin aut Hindorff, Lucia A. verfasserin aut Li, Yun verfasserin aut Lin, Danyu verfasserin aut Reiner, Alex P. verfasserin aut North, Kari E. verfasserin aut Loos, Ruth J. F. verfasserin aut Kooperberg, Charles verfasserin aut Avery, Christy L. verfasserin aut Enthalten in BMC genomics London : BioMed Central, 2000 21(2020), 1 vom: 14. März (DE-627)326644954 (DE-600)2041499-7 1471-2164 nnns volume:21 year:2020 number:1 day:14 month:03 https://dx.doi.org/10.1186/s12864-020-6626-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 42.20 ASE 44.48 ASE AR 21 2020 1 14 03 |
| allfieldsGer |
10.1186/s12864-020-6626-9 doi (DE-627)SPR039101150 (SPR)s12864-020-6626-9-e DE-627 ger DE-627 rakwb eng 570 610 ASE 42.20 bkl 44.48 bkl Hodonsky, Chani J. verfasserin aut Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background Quantitative red blood cell (RBC) traits are highly polygenic clinically relevant traits, with approximately 500 reported GWAS loci. The majority of RBC trait GWAS have been performed in European- or East Asian-ancestry populations, despite evidence that rare or ancestry-specific variation contributes substantially to RBC trait heritability. Recently developed combined-phenotype methods which leverage genetic trait correlation to improve statistical power have not yet been applied to these traits. Here we leveraged correlation of seven quantitative RBC traits in performing a combined-phenotype analysis in a multi-ethnic study population. Results We used the adaptive sum of powered scores (aSPU) test to assess combined-phenotype associations between ~ 21 million SNPs and seven RBC traits in a multi-ethnic population (maximum n = 67,885 participants; 24% African American, 30% Hispanic/Latino, and 43% European American; 76% female). Thirty-nine loci in our multi-ethnic population contained at least one significant association signal (p < 5E-9), with lead SNPs at nine loci significantly associated with three or more RBC traits. A majority of the lead SNPs were common (MAF > 5%) across all ancestral populations. Nineteen additional independent association signals were identified at seven known loci (HFE, KIT, HBS1L/MYB, CITED2/FILNC1, ABO, HBA1/2, and PLIN4/5). For example, the HBA1/2 locus contained 14 conditionally independent association signals, 11 of which were previously unreported and are specific to African and Amerindian ancestries. One variant in this region was common in all ancestries, but exhibited a narrower LD block in African Americans than European Americans or Hispanics/Latinos. GTEx eQTL analysis of all independent lead SNPs yielded 31 significant associations in relevant tissues, over half of which were not at the gene immediately proximal to the lead SNP. Conclusion This work identified seven loci containing multiple independent association signals for RBC traits using a combined-phenotype approach, which may improve discovery in genetically correlated traits. Highly complex genetic architecture at the HBA1/2 locus was only revealed by the inclusion of African Americans and Hispanics/Latinos, underscoring the continued importance of expanding large GWAS to include ancestrally diverse populations. Blood cell traits (dpeaa)DE-He213 Combined-phenotype analysis (dpeaa)DE-He213 Pleiotropy (dpeaa)DE-He213 Diversity (dpeaa)DE-He213 Multi-ethnic (dpeaa)DE-He213 GWAS (dpeaa)DE-He213 Baldassari, Antoine R. verfasserin aut Bien, Stephanie A. verfasserin aut Raffield, Laura M. verfasserin aut Highland, Heather M. verfasserin aut Sitlani, Colleen M. verfasserin aut Wojcik, Genevieve L. verfasserin aut Tao, Ran verfasserin aut Graff, Marielisa verfasserin aut Tang, Weihong verfasserin aut Thyagarajan, Bharat verfasserin aut Buyske, Steve verfasserin aut Fornage, Myriam verfasserin aut Hindorff, Lucia A. verfasserin aut Li, Yun verfasserin aut Lin, Danyu verfasserin aut Reiner, Alex P. verfasserin aut North, Kari E. verfasserin aut Loos, Ruth J. F. verfasserin aut Kooperberg, Charles verfasserin aut Avery, Christy L. verfasserin aut Enthalten in BMC genomics London : BioMed Central, 2000 21(2020), 1 vom: 14. März (DE-627)326644954 (DE-600)2041499-7 1471-2164 nnns volume:21 year:2020 number:1 day:14 month:03 https://dx.doi.org/10.1186/s12864-020-6626-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 42.20 ASE 44.48 ASE AR 21 2020 1 14 03 |
| allfieldsSound |
10.1186/s12864-020-6626-9 doi (DE-627)SPR039101150 (SPR)s12864-020-6626-9-e DE-627 ger DE-627 rakwb eng 570 610 ASE 42.20 bkl 44.48 bkl Hodonsky, Chani J. verfasserin aut Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background Quantitative red blood cell (RBC) traits are highly polygenic clinically relevant traits, with approximately 500 reported GWAS loci. The majority of RBC trait GWAS have been performed in European- or East Asian-ancestry populations, despite evidence that rare or ancestry-specific variation contributes substantially to RBC trait heritability. Recently developed combined-phenotype methods which leverage genetic trait correlation to improve statistical power have not yet been applied to these traits. Here we leveraged correlation of seven quantitative RBC traits in performing a combined-phenotype analysis in a multi-ethnic study population. Results We used the adaptive sum of powered scores (aSPU) test to assess combined-phenotype associations between ~ 21 million SNPs and seven RBC traits in a multi-ethnic population (maximum n = 67,885 participants; 24% African American, 30% Hispanic/Latino, and 43% European American; 76% female). Thirty-nine loci in our multi-ethnic population contained at least one significant association signal (p < 5E-9), with lead SNPs at nine loci significantly associated with three or more RBC traits. A majority of the lead SNPs were common (MAF > 5%) across all ancestral populations. Nineteen additional independent association signals were identified at seven known loci (HFE, KIT, HBS1L/MYB, CITED2/FILNC1, ABO, HBA1/2, and PLIN4/5). For example, the HBA1/2 locus contained 14 conditionally independent association signals, 11 of which were previously unreported and are specific to African and Amerindian ancestries. One variant in this region was common in all ancestries, but exhibited a narrower LD block in African Americans than European Americans or Hispanics/Latinos. GTEx eQTL analysis of all independent lead SNPs yielded 31 significant associations in relevant tissues, over half of which were not at the gene immediately proximal to the lead SNP. Conclusion This work identified seven loci containing multiple independent association signals for RBC traits using a combined-phenotype approach, which may improve discovery in genetically correlated traits. Highly complex genetic architecture at the HBA1/2 locus was only revealed by the inclusion of African Americans and Hispanics/Latinos, underscoring the continued importance of expanding large GWAS to include ancestrally diverse populations. Blood cell traits (dpeaa)DE-He213 Combined-phenotype analysis (dpeaa)DE-He213 Pleiotropy (dpeaa)DE-He213 Diversity (dpeaa)DE-He213 Multi-ethnic (dpeaa)DE-He213 GWAS (dpeaa)DE-He213 Baldassari, Antoine R. verfasserin aut Bien, Stephanie A. verfasserin aut Raffield, Laura M. verfasserin aut Highland, Heather M. verfasserin aut Sitlani, Colleen M. verfasserin aut Wojcik, Genevieve L. verfasserin aut Tao, Ran verfasserin aut Graff, Marielisa verfasserin aut Tang, Weihong verfasserin aut Thyagarajan, Bharat verfasserin aut Buyske, Steve verfasserin aut Fornage, Myriam verfasserin aut Hindorff, Lucia A. verfasserin aut Li, Yun verfasserin aut Lin, Danyu verfasserin aut Reiner, Alex P. verfasserin aut North, Kari E. verfasserin aut Loos, Ruth J. F. verfasserin aut Kooperberg, Charles verfasserin aut Avery, Christy L. verfasserin aut Enthalten in BMC genomics London : BioMed Central, 2000 21(2020), 1 vom: 14. März (DE-627)326644954 (DE-600)2041499-7 1471-2164 nnns volume:21 year:2020 number:1 day:14 month:03 https://dx.doi.org/10.1186/s12864-020-6626-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 42.20 ASE 44.48 ASE AR 21 2020 1 14 03 |
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Enthalten in BMC genomics 21(2020), 1 vom: 14. März volume:21 year:2020 number:1 day:14 month:03 |
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Blood cell traits Combined-phenotype analysis Pleiotropy Diversity Multi-ethnic GWAS |
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Hodonsky, Chani J. @@aut@@ Baldassari, Antoine R. @@aut@@ Bien, Stephanie A. @@aut@@ Raffield, Laura M. @@aut@@ Highland, Heather M. @@aut@@ Sitlani, Colleen M. @@aut@@ Wojcik, Genevieve L. @@aut@@ Tao, Ran @@aut@@ Graff, Marielisa @@aut@@ Tang, Weihong @@aut@@ Thyagarajan, Bharat @@aut@@ Buyske, Steve @@aut@@ Fornage, Myriam @@aut@@ Hindorff, Lucia A. @@aut@@ Li, Yun @@aut@@ Lin, Danyu @@aut@@ Reiner, Alex P. @@aut@@ North, Kari E. @@aut@@ Loos, Ruth J. F. @@aut@@ Kooperberg, Charles @@aut@@ Avery, Christy L. @@aut@@ |
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The majority of RBC trait GWAS have been performed in European- or East Asian-ancestry populations, despite evidence that rare or ancestry-specific variation contributes substantially to RBC trait heritability. Recently developed combined-phenotype methods which leverage genetic trait correlation to improve statistical power have not yet been applied to these traits. Here we leveraged correlation of seven quantitative RBC traits in performing a combined-phenotype analysis in a multi-ethnic study population. Results We used the adaptive sum of powered scores (aSPU) test to assess combined-phenotype associations between ~ 21 million SNPs and seven RBC traits in a multi-ethnic population (maximum n = 67,885 participants; 24% African American, 30% Hispanic/Latino, and 43% European American; 76% female). Thirty-nine loci in our multi-ethnic population contained at least one significant association signal (p < 5E-9), with lead SNPs at nine loci significantly associated with three or more RBC traits. A majority of the lead SNPs were common (MAF > 5%) across all ancestral populations. Nineteen additional independent association signals were identified at seven known loci (HFE, KIT, HBS1L/MYB, CITED2/FILNC1, ABO, HBA1/2, and PLIN4/5). For example, the HBA1/2 locus contained 14 conditionally independent association signals, 11 of which were previously unreported and are specific to African and Amerindian ancestries. One variant in this region was common in all ancestries, but exhibited a narrower LD block in African Americans than European Americans or Hispanics/Latinos. GTEx eQTL analysis of all independent lead SNPs yielded 31 significant associations in relevant tissues, over half of which were not at the gene immediately proximal to the lead SNP. Conclusion This work identified seven loci containing multiple independent association signals for RBC traits using a combined-phenotype approach, which may improve discovery in genetically correlated traits. 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Hodonsky, Chani J. |
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Hodonsky, Chani J. ddc 570 bkl 42.20 bkl 44.48 misc Blood cell traits misc Combined-phenotype analysis misc Pleiotropy misc Diversity misc Multi-ethnic misc GWAS Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics |
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570 610 ASE 42.20 bkl 44.48 bkl Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics Blood cell traits (dpeaa)DE-He213 Combined-phenotype analysis (dpeaa)DE-He213 Pleiotropy (dpeaa)DE-He213 Diversity (dpeaa)DE-He213 Multi-ethnic (dpeaa)DE-He213 GWAS (dpeaa)DE-He213 |
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ddc 570 bkl 42.20 bkl 44.48 misc Blood cell traits misc Combined-phenotype analysis misc Pleiotropy misc Diversity misc Multi-ethnic misc GWAS |
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Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics |
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Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics |
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Hodonsky, Chani J. |
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BMC genomics |
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Hodonsky, Chani J. Baldassari, Antoine R. Bien, Stephanie A. Raffield, Laura M. Highland, Heather M. Sitlani, Colleen M. Wojcik, Genevieve L. Tao, Ran Graff, Marielisa Tang, Weihong Thyagarajan, Bharat Buyske, Steve Fornage, Myriam Hindorff, Lucia A. Li, Yun Lin, Danyu Reiner, Alex P. North, Kari E. Loos, Ruth J. F. Kooperberg, Charles Avery, Christy L. |
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570 610 ASE 42.20 bkl 44.48 bkl |
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Elektronische Aufsätze |
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Hodonsky, Chani J. |
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10.1186/s12864-020-6626-9 |
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verfasserin |
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ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics |
| title_auth |
Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics |
| abstract |
Background Quantitative red blood cell (RBC) traits are highly polygenic clinically relevant traits, with approximately 500 reported GWAS loci. The majority of RBC trait GWAS have been performed in European- or East Asian-ancestry populations, despite evidence that rare or ancestry-specific variation contributes substantially to RBC trait heritability. Recently developed combined-phenotype methods which leverage genetic trait correlation to improve statistical power have not yet been applied to these traits. Here we leveraged correlation of seven quantitative RBC traits in performing a combined-phenotype analysis in a multi-ethnic study population. Results We used the adaptive sum of powered scores (aSPU) test to assess combined-phenotype associations between ~ 21 million SNPs and seven RBC traits in a multi-ethnic population (maximum n = 67,885 participants; 24% African American, 30% Hispanic/Latino, and 43% European American; 76% female). Thirty-nine loci in our multi-ethnic population contained at least one significant association signal (p < 5E-9), with lead SNPs at nine loci significantly associated with three or more RBC traits. A majority of the lead SNPs were common (MAF > 5%) across all ancestral populations. Nineteen additional independent association signals were identified at seven known loci (HFE, KIT, HBS1L/MYB, CITED2/FILNC1, ABO, HBA1/2, and PLIN4/5). For example, the HBA1/2 locus contained 14 conditionally independent association signals, 11 of which were previously unreported and are specific to African and Amerindian ancestries. One variant in this region was common in all ancestries, but exhibited a narrower LD block in African Americans than European Americans or Hispanics/Latinos. GTEx eQTL analysis of all independent lead SNPs yielded 31 significant associations in relevant tissues, over half of which were not at the gene immediately proximal to the lead SNP. Conclusion This work identified seven loci containing multiple independent association signals for RBC traits using a combined-phenotype approach, which may improve discovery in genetically correlated traits. Highly complex genetic architecture at the HBA1/2 locus was only revealed by the inclusion of African Americans and Hispanics/Latinos, underscoring the continued importance of expanding large GWAS to include ancestrally diverse populations. |
| abstractGer |
Background Quantitative red blood cell (RBC) traits are highly polygenic clinically relevant traits, with approximately 500 reported GWAS loci. The majority of RBC trait GWAS have been performed in European- or East Asian-ancestry populations, despite evidence that rare or ancestry-specific variation contributes substantially to RBC trait heritability. Recently developed combined-phenotype methods which leverage genetic trait correlation to improve statistical power have not yet been applied to these traits. Here we leveraged correlation of seven quantitative RBC traits in performing a combined-phenotype analysis in a multi-ethnic study population. Results We used the adaptive sum of powered scores (aSPU) test to assess combined-phenotype associations between ~ 21 million SNPs and seven RBC traits in a multi-ethnic population (maximum n = 67,885 participants; 24% African American, 30% Hispanic/Latino, and 43% European American; 76% female). Thirty-nine loci in our multi-ethnic population contained at least one significant association signal (p < 5E-9), with lead SNPs at nine loci significantly associated with three or more RBC traits. A majority of the lead SNPs were common (MAF > 5%) across all ancestral populations. Nineteen additional independent association signals were identified at seven known loci (HFE, KIT, HBS1L/MYB, CITED2/FILNC1, ABO, HBA1/2, and PLIN4/5). For example, the HBA1/2 locus contained 14 conditionally independent association signals, 11 of which were previously unreported and are specific to African and Amerindian ancestries. One variant in this region was common in all ancestries, but exhibited a narrower LD block in African Americans than European Americans or Hispanics/Latinos. GTEx eQTL analysis of all independent lead SNPs yielded 31 significant associations in relevant tissues, over half of which were not at the gene immediately proximal to the lead SNP. Conclusion This work identified seven loci containing multiple independent association signals for RBC traits using a combined-phenotype approach, which may improve discovery in genetically correlated traits. Highly complex genetic architecture at the HBA1/2 locus was only revealed by the inclusion of African Americans and Hispanics/Latinos, underscoring the continued importance of expanding large GWAS to include ancestrally diverse populations. |
| abstract_unstemmed |
Background Quantitative red blood cell (RBC) traits are highly polygenic clinically relevant traits, with approximately 500 reported GWAS loci. The majority of RBC trait GWAS have been performed in European- or East Asian-ancestry populations, despite evidence that rare or ancestry-specific variation contributes substantially to RBC trait heritability. Recently developed combined-phenotype methods which leverage genetic trait correlation to improve statistical power have not yet been applied to these traits. Here we leveraged correlation of seven quantitative RBC traits in performing a combined-phenotype analysis in a multi-ethnic study population. Results We used the adaptive sum of powered scores (aSPU) test to assess combined-phenotype associations between ~ 21 million SNPs and seven RBC traits in a multi-ethnic population (maximum n = 67,885 participants; 24% African American, 30% Hispanic/Latino, and 43% European American; 76% female). Thirty-nine loci in our multi-ethnic population contained at least one significant association signal (p < 5E-9), with lead SNPs at nine loci significantly associated with three or more RBC traits. A majority of the lead SNPs were common (MAF > 5%) across all ancestral populations. Nineteen additional independent association signals were identified at seven known loci (HFE, KIT, HBS1L/MYB, CITED2/FILNC1, ABO, HBA1/2, and PLIN4/5). For example, the HBA1/2 locus contained 14 conditionally independent association signals, 11 of which were previously unreported and are specific to African and Amerindian ancestries. One variant in this region was common in all ancestries, but exhibited a narrower LD block in African Americans than European Americans or Hispanics/Latinos. GTEx eQTL analysis of all independent lead SNPs yielded 31 significant associations in relevant tissues, over half of which were not at the gene immediately proximal to the lead SNP. Conclusion This work identified seven loci containing multiple independent association signals for RBC traits using a combined-phenotype approach, which may improve discovery in genetically correlated traits. Highly complex genetic architecture at the HBA1/2 locus was only revealed by the inclusion of African Americans and Hispanics/Latinos, underscoring the continued importance of expanding large GWAS to include ancestrally diverse populations. |
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Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics |
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https://dx.doi.org/10.1186/s12864-020-6626-9 |
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Baldassari, Antoine R. Bien, Stephanie A. Raffield, Laura M. Highland, Heather M. Sitlani, Colleen M. Wojcik, Genevieve L. Tao, Ran Graff, Marielisa Tang, Weihong Thyagarajan, Bharat Buyske, Steve Fornage, Myriam Hindorff, Lucia A. Li, Yun Lin, Danyu Reiner, Alex P. North, Kari E. Loos, Ruth J. F. Kooperberg, Charles Avery, Christy L. |
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Baldassari, Antoine R. Bien, Stephanie A. Raffield, Laura M. Highland, Heather M. Sitlani, Colleen M. Wojcik, Genevieve L. Tao, Ran Graff, Marielisa Tang, Weihong Thyagarajan, Bharat Buyske, Steve Fornage, Myriam Hindorff, Lucia A. Li, Yun Lin, Danyu Reiner, Alex P. North, Kari E. Loos, Ruth J. F. Kooperberg, Charles Avery, Christy L. |
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10.1186/s12864-020-6626-9 |
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2024-07-03T22:00:15.318Z |
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