Type 2 Diabetes Partitioned Polygenic Scores Associate With Disease Outcomes in 454,193 Individuals Across 13 Cohorts

Daniel Dicorpo; Jessica Leclair; Joanne B. Cole; Chloe Sarnowski; Fariba Ahmadizar; Lawrence F. Bielak; Anneke Blokstra; Erwin P. Bottinger; Layal Chaker; Yii Der I. Chen; Ye Chen; Paul S. de Vries; Tariq Faquih; Mohsen Ghanbari; Valborg Gudmundsdottir; Xiuqing Guo; Natalie R. Hasbani; Dorina Ibi; M. Arfan Ikram; Maryam Kavousi; Hampton L. Leonard; Aaron Leong; Josep M. Mercader; Alanna C. Morrison; Girish N. Nadkarni; Mike A. Nalls; Raymond Noordam; Michael Preuss; Jennifer A. Smith; Stella Trompet; Petra Vissink; Jie Yao; Wei Zhao; Eric Boerwinkle; Mark O. Goodarzi; Vilmundur Gudnason; J. Wouter Jukema; Sharon L.R. Kardia; Ruth J.F. Loos; Ching Ti Liu; Alisa K. Manning; Dennis Mook-Kanamori; James S. Pankow; H. Susan J. Picavet; Naveed Sattar; Eleanor M. Simonsick; W. M.Monique Verschuren; Ko Willems van Dijk; Jose C. Florez; Jerome I. Rotter; James B. Meigs; Josee Dupuis; Miriam S. Udler

doi:10.2337/dc21-1395

Type 2 Diabetes Partitioned Polygenic Scores Associate With Disease Outcomes in 454,193 Individuals Across 13 Cohorts

Daniel Dicorpo, Jessica Leclair, Joanne B. Cole, Chloe Sarnowski, Fariba Ahmadizar, Lawrence F. Bielak, Anneke Blokstra, Erwin P. Bottinger, Layal Chaker, Yii Der I. Chen, Ye Chen, Paul S. de Vries, Tariq Faquih, Mohsen Ghanbari, Valborg Gudmundsdottir, Xiuqing Guo, Natalie R. Hasbani, Dorina Ibi, M. Arfan Ikram, Maryam KavousiHampton L. Leonard, Aaron Leong, Josep M. Mercader, Alanna C. Morrison, Girish N. Nadkarni, Mike A. Nalls, Raymond Noordam, Michael Preuss, Jennifer A. Smith, Stella Trompet, Petra Vissink, Jie Yao, Wei Zhao, Eric Boerwinkle, Mark O. Goodarzi, Vilmundur Gudnason, J. Wouter Jukema, Sharon L.R. Kardia, Ruth J.F. Loos, Ching Ti Liu, Alisa K. Manning, Dennis Mook-Kanamori, James S. Pankow, H. Susan J. Picavet, Naveed Sattar, Eleanor M. Simonsick, W. M.Monique Verschuren, Ko Willems van Dijk, Jose C. Florez, Jerome I. Rotter, James B. Meigs, Josee Dupuis, Miriam S. Udler

Epidemiology

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Abstract

OBJECTIVE Type 2 diabetes (T2D) has heterogeneous patient clinical characteristics and out-comes. 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 b-cell, proinsulin, obesity, lipodystro-phy, 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 hyperten-sion. 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 predis-pose differentially to clinical outcomes.

Original language	English (US)
Pages (from-to)	674-683
Number of pages	10
Journal	Diabetes care
Volume	45
Issue number	3
DOIs	https://doi.org/10.2337/dc21-1395
State	Published - Mar 2022

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Publisher Copyright:
© 2022 by the American Diabetes Association.

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Dicorpo, D., Leclair, J., Cole, J. B., Sarnowski, C., Ahmadizar, F., Bielak, L. F., Blokstra, A., Bottinger, E. P., Chaker, L., Chen, Y. D. I., Chen, Y., de Vries, P. S., Faquih, T., Ghanbari, M., Gudmundsdottir, V., Guo, X., Hasbani, N. R., Ibi, D., Ikram, M. A., ... Udler, M. S. (2022). Type 2 Diabetes Partitioned Polygenic Scores Associate With Disease Outcomes in 454,193 Individuals Across 13 Cohorts. Diabetes care, 45(3), 674-683. https://doi.org/10.2337/dc21-1395

Dicorpo, D, Leclair, J, Cole, JB, Sarnowski, C, Ahmadizar, F, Bielak, LF, Blokstra, A, Bottinger, EP, Chaker, L, Chen, YDI, Chen, Y, de Vries, PS, Faquih, T, Ghanbari, M, Gudmundsdottir, V, Guo, X, Hasbani, NR, Ibi, D, Ikram, MA, Kavousi, M, Leonard, HL, Leong, A, Mercader, JM, Morrison, AC, Nadkarni, GN, Nalls, MA, Noordam, R, Preuss, M, Smith, JA, Trompet, S, Vissink, P, Yao, J, Zhao, W, Boerwinkle, E, Goodarzi, MO, Gudnason, V, Wouter Jukema, J, Kardia, SLR, Loos, RJF, Liu, CT, Manning, AK, Mook-Kanamori, D, Pankow, JS, Picavet, HSJ, Sattar, N, Simonsick, EM, Verschuren, WMM, van Dijk, KW, Florez, JC, Rotter, JI, Meigs, JB, Dupuis, J & Udler, MS 2022, 'Type 2 Diabetes Partitioned Polygenic Scores Associate With Disease Outcomes in 454,193 Individuals Across 13 Cohorts', Diabetes care, vol. 45, no. 3, pp. 674-683. https://doi.org/10.2337/dc21-1395

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title = "Type 2 Diabetes Partitioned Polygenic Scores Associate With Disease Outcomes in 454,193 Individuals Across 13 Cohorts",

abstract = "OBJECTIVE Type 2 diabetes (T2D) has heterogeneous patient clinical characteristics and out-comes. 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 b-cell, proinsulin, obesity, lipodystro-phy, 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 hyperten-sion. 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 predis-pose differentially to clinical outcomes.",

author = "Daniel Dicorpo and Jessica Leclair and Cole, {Joanne B.} and Chloe Sarnowski and Fariba Ahmadizar and Bielak, {Lawrence F.} and Anneke Blokstra and Bottinger, {Erwin P.} and Layal Chaker and Chen, {Yii Der I.} and Ye Chen and {de Vries}, {Paul S.} and Tariq Faquih and Mohsen Ghanbari and Valborg Gudmundsdottir and Xiuqing Guo and Hasbani, {Natalie R.} and Dorina Ibi and Ikram, {M. Arfan} and Maryam Kavousi and Leonard, {Hampton L.} and Aaron Leong and Mercader, {Josep M.} and Morrison, {Alanna C.} and Nadkarni, {Girish N.} and Nalls, {Mike A.} and Raymond Noordam and Michael Preuss and Smith, {Jennifer A.} and Stella Trompet and Petra Vissink and Jie Yao and Wei Zhao and Eric Boerwinkle and Goodarzi, {Mark O.} and Vilmundur Gudnason and {Wouter Jukema}, J. and Kardia, {Sharon L.R.} and Loos, {Ruth J.F.} and Liu, {Ching Ti} and Manning, {Alisa K.} and Dennis Mook-Kanamori and Pankow, {James S.} and Picavet, {H. Susan J.} and Naveed Sattar and Simonsick, {Eleanor M.} and Verschuren, {W. M.Monique} and {van Dijk}, {Ko Willems} and Florez, {Jose C.} and Rotter, {Jerome I.} and Meigs, {James B.} and Josee Dupuis and Udler, {Miriam S.}",

note = "Publisher Copyright: {\textcopyright} 2022 by the American Diabetes Association.",

year = "2022",

month = mar,

doi = "10.2337/dc21-1395",

language = "English (US)",

volume = "45",

pages = "674--683",

journal = "Diabetes care",

issn = "0149-5992",

publisher = "American Diabetes Association Inc.",

number = "3",

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TY - JOUR

T1 - Type 2 Diabetes Partitioned Polygenic Scores Associate With Disease Outcomes in 454,193 Individuals Across 13 Cohorts

AU - Dicorpo, Daniel

AU - Leclair, Jessica

AU - Cole, Joanne B.

AU - Sarnowski, Chloe

AU - Ahmadizar, Fariba

AU - Bielak, Lawrence F.

AU - Blokstra, Anneke

AU - Bottinger, Erwin P.

AU - Chaker, Layal

AU - Chen, Yii Der I.

AU - Chen, Ye

AU - de Vries, Paul S.

AU - Faquih, Tariq

AU - Ghanbari, Mohsen

AU - Gudmundsdottir, Valborg

AU - Guo, Xiuqing

AU - Hasbani, Natalie R.

AU - Ibi, Dorina

AU - Ikram, M. Arfan

AU - Kavousi, Maryam

AU - Leonard, Hampton L.

AU - Leong, Aaron

AU - Mercader, Josep M.

AU - Morrison, Alanna C.

AU - Nadkarni, Girish N.

AU - Nalls, Mike A.

AU - Noordam, Raymond

AU - Preuss, Michael

AU - Smith, Jennifer A.

AU - Trompet, Stella

AU - Vissink, Petra

AU - Yao, Jie

AU - Zhao, Wei

AU - Boerwinkle, Eric

AU - Goodarzi, Mark O.

AU - Gudnason, Vilmundur

AU - Wouter Jukema, J.

AU - Kardia, Sharon L.R.

AU - Loos, Ruth J.F.

AU - Liu, Ching Ti

AU - Manning, Alisa K.

AU - Mook-Kanamori, Dennis

AU - Pankow, James S.

AU - Picavet, H. Susan J.

AU - Sattar, Naveed

AU - Simonsick, Eleanor M.

AU - Verschuren, W. M.Monique

AU - van Dijk, Ko Willems

AU - Florez, Jose C.

AU - Rotter, Jerome I.

AU - Meigs, James B.

AU - Dupuis, Josee

AU - Udler, Miriam S.

PY - 2022/3

Y1 - 2022/3

N2 - OBJECTIVE Type 2 diabetes (T2D) has heterogeneous patient clinical characteristics and out-comes. 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 b-cell, proinsulin, obesity, lipodystro-phy, 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 hyperten-sion. 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 predis-pose differentially to clinical outcomes.

AB - OBJECTIVE Type 2 diabetes (T2D) has heterogeneous patient clinical characteristics and out-comes. 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 b-cell, proinsulin, obesity, lipodystro-phy, 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 hyperten-sion. 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 predis-pose differentially to clinical outcomes.

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DO - 10.2337/dc21-1395

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SN - 0149-5992

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JO - Diabetes care

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Type 2 Diabetes Partitioned Polygenic Scores Associate With Disease Outcomes in 454,193 Individuals Across 13 Cohorts

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