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Type 2 Diabetes Partitioned Polygenic Scores Associate With Disease Outcomes in 454,193 Individuals Across 13 Cohorts
OBJECTIVE: Type 2 diabetes (T2D) has heterogeneous patient clinical characteristics and outcomes. In previous work, we investigated the genetic basis of this heterogeneity by clustering 94 T2D genetic loci using their associations with 47 diabetes-related traits and identified five clusters, termed...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Diabetes Association
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8918228/ https://www.ncbi.nlm.nih.gov/pubmed/35085396 http://dx.doi.org/10.2337/dc21-1395 |
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author | DiCorpo, Daniel LeClair, Jessica Cole, Joanne B. Sarnowski, Chloé Ahmadizar, Fariba Bielak, Lawrence F. Blokstra, Anneke Bottinger, Erwin P. Chaker, Layal Chen, Yii-Der I. Chen, Ye de Vries, Paul S. Faquih, Tariq Ghanbari, Mohsen Gudmundsdottir, Valborg Guo, Xiuqing Hasbani, Natalie R. Ibi, Dorina Ikram, M. Arfan Kavousi, Maryam Leonard, Hampton L. Leong, Aaron Mercader, Josep M. Morrison, Alanna C. Nadkarni, Girish N. Nalls, Mike A. Noordam, Raymond Preuss, Michael Smith, Jennifer A. Trompet, Stella Vissink, Petra Yao, Jie Zhao, Wei Boerwinkle, Eric Goodarzi, Mark O. Gudnason, Vilmundur Jukema, J. Wouter Kardia, Sharon L.R. Loos, Ruth J.F. Liu, Ching-Ti Manning, Alisa K. Mook-Kanamori, Dennis Pankow, James S. Picavet, H. Susan J. Sattar, Naveed Simonsick, Eleanor M. Verschuren, W.M. Monique Willems van Dijk, Ko Florez, Jose C. Rotter, Jerome I. Meigs, James B. Dupuis, Josée Udler, Miriam S. |
author_facet | DiCorpo, Daniel LeClair, Jessica Cole, Joanne B. Sarnowski, Chloé Ahmadizar, Fariba Bielak, Lawrence F. Blokstra, Anneke Bottinger, Erwin P. Chaker, Layal Chen, Yii-Der I. Chen, Ye de Vries, Paul S. Faquih, Tariq Ghanbari, Mohsen Gudmundsdottir, Valborg Guo, Xiuqing Hasbani, Natalie R. Ibi, Dorina Ikram, M. Arfan Kavousi, Maryam Leonard, Hampton L. Leong, Aaron Mercader, Josep M. Morrison, Alanna C. Nadkarni, Girish N. Nalls, Mike A. Noordam, Raymond Preuss, Michael Smith, Jennifer A. Trompet, Stella Vissink, Petra Yao, Jie Zhao, Wei Boerwinkle, Eric Goodarzi, Mark O. Gudnason, Vilmundur Jukema, J. Wouter Kardia, Sharon L.R. Loos, Ruth J.F. Liu, Ching-Ti Manning, Alisa K. Mook-Kanamori, Dennis Pankow, James S. Picavet, H. Susan J. Sattar, Naveed Simonsick, Eleanor M. Verschuren, W.M. Monique Willems van Dijk, Ko Florez, Jose C. Rotter, Jerome I. Meigs, James B. Dupuis, Josée Udler, Miriam S. |
author_sort | DiCorpo, Daniel |
collection | PubMed |
description | OBJECTIVE: Type 2 diabetes (T2D) has heterogeneous patient clinical characteristics and outcomes. In previous work, we investigated the genetic basis of this heterogeneity by clustering 94 T2D genetic loci using their associations with 47 diabetes-related traits and identified five clusters, termed β-cell, proinsulin, obesity, lipodystrophy, and liver/lipid. The relationship between these clusters and individual-level metabolic disease outcomes has not been assessed. RESEARCH DESIGN AND METHODS: Here we constructed individual-level partitioned polygenic scores (pPS) for these five clusters in 12 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank (n = 454,193) and tested for cross-sectional association with T2D-related outcomes, including blood pressure, renal function, insulin use, age at T2D diagnosis, and coronary artery disease (CAD). RESULTS: Despite all clusters containing T2D risk-increasing alleles, they had differential associations with metabolic outcomes. Increased obesity and lipodystrophy cluster pPS, which had opposite directions of association with measures of adiposity, were both significantly associated with increased blood pressure and hypertension. The lipodystrophy and liver/lipid cluster pPS were each associated with CAD, with increasing and decreasing effects, respectively. An increased liver/lipid cluster pPS was also significantly associated with reduced renal function. The liver/lipid cluster includes known loci linked to liver lipid metabolism (e.g., GCKR, PNPLA3, and TM6SF2), and these findings suggest that cardiovascular disease risk and renal function may be impacted by these loci through their shared disease pathway. CONCLUSIONS: Our findings support that genetically driven pathways leading to T2D also predispose differentially to clinical outcomes. |
format | Online Article Text |
id | pubmed-8918228 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Diabetes Association |
record_format | MEDLINE/PubMed |
spelling | pubmed-89182282022-03-17 Type 2 Diabetes Partitioned Polygenic Scores Associate With Disease Outcomes in 454,193 Individuals Across 13 Cohorts DiCorpo, Daniel LeClair, Jessica Cole, Joanne B. Sarnowski, Chloé Ahmadizar, Fariba Bielak, Lawrence F. Blokstra, Anneke Bottinger, Erwin P. Chaker, Layal Chen, Yii-Der I. Chen, Ye de Vries, Paul S. Faquih, Tariq Ghanbari, Mohsen Gudmundsdottir, Valborg Guo, Xiuqing Hasbani, Natalie R. Ibi, Dorina Ikram, M. Arfan Kavousi, Maryam Leonard, Hampton L. Leong, Aaron Mercader, Josep M. Morrison, Alanna C. Nadkarni, Girish N. Nalls, Mike A. Noordam, Raymond Preuss, Michael Smith, Jennifer A. Trompet, Stella Vissink, Petra Yao, Jie Zhao, Wei Boerwinkle, Eric Goodarzi, Mark O. Gudnason, Vilmundur Jukema, J. Wouter Kardia, Sharon L.R. Loos, Ruth J.F. Liu, Ching-Ti Manning, Alisa K. Mook-Kanamori, Dennis Pankow, James S. Picavet, H. Susan J. Sattar, Naveed Simonsick, Eleanor M. Verschuren, W.M. Monique Willems van Dijk, Ko Florez, Jose C. Rotter, Jerome I. Meigs, James B. Dupuis, Josée Udler, Miriam S. Diabetes Care Pathophysiology/Complications OBJECTIVE: Type 2 diabetes (T2D) has heterogeneous patient clinical characteristics and outcomes. In previous work, we investigated the genetic basis of this heterogeneity by clustering 94 T2D genetic loci using their associations with 47 diabetes-related traits and identified five clusters, termed β-cell, proinsulin, obesity, lipodystrophy, and liver/lipid. The relationship between these clusters and individual-level metabolic disease outcomes has not been assessed. RESEARCH DESIGN AND METHODS: Here we constructed individual-level partitioned polygenic scores (pPS) for these five clusters in 12 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank (n = 454,193) and tested for cross-sectional association with T2D-related outcomes, including blood pressure, renal function, insulin use, age at T2D diagnosis, and coronary artery disease (CAD). RESULTS: Despite all clusters containing T2D risk-increasing alleles, they had differential associations with metabolic outcomes. Increased obesity and lipodystrophy cluster pPS, which had opposite directions of association with measures of adiposity, were both significantly associated with increased blood pressure and hypertension. The lipodystrophy and liver/lipid cluster pPS were each associated with CAD, with increasing and decreasing effects, respectively. An increased liver/lipid cluster pPS was also significantly associated with reduced renal function. The liver/lipid cluster includes known loci linked to liver lipid metabolism (e.g., GCKR, PNPLA3, and TM6SF2), and these findings suggest that cardiovascular disease risk and renal function may be impacted by these loci through their shared disease pathway. CONCLUSIONS: Our findings support that genetically driven pathways leading to T2D also predispose differentially to clinical outcomes. American Diabetes Association 2022-03 2022-01-27 /pmc/articles/PMC8918228/ /pubmed/35085396 http://dx.doi.org/10.2337/dc21-1395 Text en © 2022 by the American Diabetes Association https://www.diabetesjournals.org/content/licenseReaders may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. More information is available at https://www.diabetesjournals.org/journals/pages/license. |
spellingShingle | Pathophysiology/Complications DiCorpo, Daniel LeClair, Jessica Cole, Joanne B. Sarnowski, Chloé Ahmadizar, Fariba Bielak, Lawrence F. Blokstra, Anneke Bottinger, Erwin P. Chaker, Layal Chen, Yii-Der I. Chen, Ye de Vries, Paul S. Faquih, Tariq Ghanbari, Mohsen Gudmundsdottir, Valborg Guo, Xiuqing Hasbani, Natalie R. Ibi, Dorina Ikram, M. Arfan Kavousi, Maryam Leonard, Hampton L. Leong, Aaron Mercader, Josep M. Morrison, Alanna C. Nadkarni, Girish N. Nalls, Mike A. Noordam, Raymond Preuss, Michael Smith, Jennifer A. Trompet, Stella Vissink, Petra Yao, Jie Zhao, Wei Boerwinkle, Eric Goodarzi, Mark O. Gudnason, Vilmundur Jukema, J. Wouter Kardia, Sharon L.R. Loos, Ruth J.F. Liu, Ching-Ti Manning, Alisa K. Mook-Kanamori, Dennis Pankow, James S. Picavet, H. Susan J. Sattar, Naveed Simonsick, Eleanor M. Verschuren, W.M. Monique Willems van Dijk, Ko Florez, Jose C. Rotter, Jerome I. Meigs, James B. Dupuis, Josée Udler, Miriam S. Type 2 Diabetes Partitioned Polygenic Scores Associate With Disease Outcomes in 454,193 Individuals Across 13 Cohorts |
title | Type 2 Diabetes Partitioned Polygenic Scores Associate With Disease Outcomes in 454,193 Individuals Across 13 Cohorts |
title_full | Type 2 Diabetes Partitioned Polygenic Scores Associate With Disease Outcomes in 454,193 Individuals Across 13 Cohorts |
title_fullStr | Type 2 Diabetes Partitioned Polygenic Scores Associate With Disease Outcomes in 454,193 Individuals Across 13 Cohorts |
title_full_unstemmed | Type 2 Diabetes Partitioned Polygenic Scores Associate With Disease Outcomes in 454,193 Individuals Across 13 Cohorts |
title_short | Type 2 Diabetes Partitioned Polygenic Scores Associate With Disease Outcomes in 454,193 Individuals Across 13 Cohorts |
title_sort | type 2 diabetes partitioned polygenic scores associate with disease outcomes in 454,193 individuals across 13 cohorts |
topic | Pathophysiology/Complications |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8918228/ https://www.ncbi.nlm.nih.gov/pubmed/35085396 http://dx.doi.org/10.2337/dc21-1395 |
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