Polygenic risk scores for cardiometabolic traits demonstrate importance of ancestry for predictive precision medicine

被引:0
作者
Kember, Rachel L. [1 ]
Verma, Shefali S. [2 ]
Verma, Anurag [3 ]
Xiao, Brenda [4 ]
Lucas, Anastasia [4 ]
Kripke, Colleen M. [5 ]
Judy, Renae [6 ]
Chen, Jinbo [7 ]
Damrauer, Scott M. [6 ]
Rader, Daniel J. [8 ]
Ritchie, Marylyn D. [9 ]
机构
[1] Univ Penn, Dept Psychiat, 3535 Market St, Philadelphia, PA 19104 USA
[2] Univ Penn, Dept Pathol & Lab Med, 3700 Hamilton Walk, Philadelphia, PA 19104 USA
[3] Univ Penn, Dept Med, 3700 Hamilton Walk, Philadelphia, PA 19104 USA
[4] Univ Penn, Grad Program Genom & Computat Biol, Philadelphia, PA 19104 USA
[5] Univ Penn, Inst Translat Med & Therapeut, Philadelphia, PA 19104 USA
[6] Univ Penn, Div Vasc Surg & Endovasc Therapy, Div Vasc Surg, Philadelphia, PA 19104 USA
[7] Univ Penn, Dept Biostat & Epidemiol, 203 Blockley Hall, Philadelphia, PA 19104 USA
[8] Univ Penn, Inst Translat Med & Therapeut, Dept Med & Genet, 3801 Filbert St, Philadelphia, PA 19104 USA
[9] Univ Penn, Perelman Sch Med, Dept Genet, Inst Biomed Informat, 3700 Hamilton Walk, Philadelphia, PA 19104 USA
来源
BIOCOMPUTING 2024, PSB 2024 | 2024年
基金
美国国家卫生研究院;
关键词
Polygenic risk scores; multi-ancestry GWAS; cardiometabolic phenotypes; precision medicine; BODY-MASS INDEX; BLOOD-PRESSURE; WIDE; COMPLICATIONS; METAANALYSIS; ASSOCIATION; GENOMICS; OBESITY; DISEASE; LOCI;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Polygenic risk scores (PRS) have predominantly been derived from genome-wide association studies (GWAS) conducted in European ancestry (EUR) individuals. In this study, we present an in-depth evaluation of PRS based on multi-ancestry GWAS for five cardiometabolic phenotypes in the Penn Medicine BioBank (PMBB) followed by a phenome-wide association study (PheWAS). We examine the PRS performance across all individuals and separately in African ancestry (AFR) and EUR ancestry groups. For AFR individuals, PRS derived using the multi-ancestry LD panel showed a higher effect size for four out of five PRSs (DBP, SBP, T2D, and BMI) than those derived from the AFR LD panel. In contrast, for EUR individuals, the multi-ancestry LD panel PRS demonstrated a higher effect size for two out of five PRSs (SBP and T2D) compared to the EUR LD panel. These findings underscore the potential benefits of utilizing a multi-ancestry LD panel for PRS derivation in diverse genetic backgrounds and demonstrate overall robustness in all individuals. Our results also revealed significant associations between PRS and various phenotypic categories. For instance, CAD PRS was linked with 18 phenotypes in AFR and 82 in EUR, while T2D PRS correlated with 84 phenotypes in AFR and 78 in EUR. Notably, associations like hyperlipidemia, renal failure, atrial fibrillation, coronary atherosclerosis, obesity, and hypertension were observed across different PRSs in both AFR and EUR groups, with varying effect sizes and significance levels. However, in AFR individuals, the strength and number of PRS associations with other phenotypes were generally reduced compared to EUR individuals. Our study underscores the need for future research to prioritize 1) conducting GWAS in diverse ancestry groups and 2) creating a cosmopolitan PRS methodology that is universally applicable across all genetic backgrounds. Such advances will foster a more equitable and personalized approach to precision medicine.
引用
收藏
页码:611 / 626
页数:16
相关论文
共 33 条
[21]   Principal components analysis corrects for stratification in genome-wide association studies [J].
Price, Alkes L. ;
Patterson, Nick J. ;
Plenge, Robert M. ;
Weinblatt, Michael E. ;
Shadick, Nancy A. ;
Reich, David .
NATURE GENETICS, 2006, 38 (08) :904-909
[22]   Common polygenic variation contributes to risk of schizophrenia and bipolar disorder [J].
Purcell, Shaun M. ;
Wray, Naomi R. ;
Stone, Jennifer L. ;
Visscher, Peter M. ;
O'Donovan, Michael C. ;
Sullivan, Patrick F. ;
Sklar, Pamela ;
Ruderfer, Douglas M. ;
McQuillin, Andrew ;
Morris, Derek W. ;
O'Dushlaine, Colm T. ;
Corvin, Aiden ;
Holmans, Peter A. ;
Macgregor, Stuart ;
Gurling, Hugh ;
Blackwood, Douglas H. R. ;
Craddock, Nick J. ;
Gill, Michael ;
Hultman, Christina M. ;
Kirov, George K. ;
Lichtenstein, Paul ;
Muir, Walter J. ;
Owen, Michael J. ;
Pato, Carlos N. ;
Scolnick, Edward M. ;
St Clair, David ;
Williams, Nigel M. ;
Georgieva, Lyudmila ;
Nikolov, Ivan ;
Norton, N. ;
Williams, H. ;
Toncheva, Draga ;
Milanova, Vihra ;
Thelander, Emma F. ;
Sullivan, Patrick ;
Kenny, Elaine ;
Quinn, Emma M. ;
Choudhury, Khalid ;
Datta, Susmita ;
Pimm, Jonathan ;
Thirumalai, Srinivasa ;
Puri, Vinay ;
Krasucki, Robert ;
Lawrence, Jacob ;
Quested, Digby ;
Bass, Nicholas ;
Crombie, Caroline ;
Fraser, Gillian ;
Kuan, Soh Leh ;
Walker, Nicholas .
NATURE, 2009, 460 (7256) :748-752
[23]   Cardiorenal Syndrome: Classification, Pathophysiology, Diagnosis, and Treatment Strategies A Scientific Statement From the American Heart Association [J].
Rangaswami, Janani ;
Bhalla, Vivek ;
Blair, John E. A. ;
Chang, Tara, I ;
Costa, Salvatore ;
Lentine, Krista L. ;
Lerma, Edgar, V ;
Mezue, Kenechukwu ;
Molitch, Mark ;
Mullens, Wilfried ;
Ronco, Claudio ;
Tang, W. H. Wilson ;
McCullough, Peter A. .
CIRCULATION, 2019, 139 (16) :E840-E878
[24]   Genome-wide studies to identify risk factors for kidney disease with a focus on patients with diabetes [J].
Regele, Florina ;
Jelencsics, Kira ;
Shiffman, Dov ;
Pare, Guillaume ;
McQueen, Matthew J. ;
Mann, Johannes F. E. ;
Oberbauer, Rainer .
NEPHROLOGY DIALYSIS TRANSPLANTATION, 2015, 30 :26-34
[25]   Interactions Between Obesity and Obstructive Sleep Apnea Implications for Treatment [J].
Romero-Corral, Abel ;
Caples, Sean M. ;
Lopez-Jimenez, Francisco ;
Somers, Virend K. .
CHEST, 2010, 137 (03) :711-719
[26]   Type 2 Diabetes and Hypertension A Study on Bidirectional Causality [J].
Sun, Dianjianyi ;
Zhou, Tao ;
Heianza, Yoriko ;
Li, Xiang ;
Fan, Mengyu ;
Fonseca, Vivian A. ;
Qi, Lu .
CIRCULATION RESEARCH, 2019, 124 (06) :930-937
[27]   Risk prediction by genetic risk scores for coronary heart disease is independent of self-reported family history [J].
Tada, Hayato ;
Melander, Olle ;
Louie, Judy Z. ;
Catanese, Joseph J. ;
Rowland, Charles M. ;
Devlin, James J. ;
Kathiresan, Sekar ;
Shiffman, Dov .
EUROPEAN HEART JOURNAL, 2016, 37 (06) :561-567
[28]   Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program [J].
Taliun, Daniel ;
Harris, Daniel N. ;
Kessler, Michael D. ;
Carlson, Jedidiah ;
Szpiech, Zachary A. ;
Torres, Raul ;
Taliun, Sarah A. Gagliano ;
Corvelo, Andre ;
Gogarten, Stephanie M. ;
Kang, Hyun Min ;
Pitsillides, Achilleas N. ;
LeFaive, Jonathon ;
Lee, Seung-been ;
Tian, Xiaowen ;
Browning, Brian L. ;
Das, Sayantan ;
Emde, Anne-Katrin ;
Clarke, Wayne E. ;
Loesch, Douglas P. ;
Shetty, Amol C. ;
Blackwell, Thomas W. ;
Smith, Albert, V ;
Wong, Quenna ;
Liu, Xiaoming ;
Conomos, Matthew P. ;
Bobo, Dean M. ;
Aguet, Francois ;
Albert, Christine ;
Alonso, Alvaro ;
Ardlie, Kristin G. ;
Arking, Dan E. ;
Aslibekyan, Stella ;
Auer, Paul L. ;
Barnard, John ;
Barr, R. Graham ;
Barwick, Lucas ;
Becker, Lewis C. ;
Beer, Rebecca L. ;
Benjamin, Emelia J. ;
Bielak, Lawrence F. ;
Blangero, John ;
Boehnke, Michael ;
Bowden, Donald W. ;
Brody, Jennifer A. ;
Burchard, Esteban G. ;
Cade, Brian E. ;
Casella, James F. ;
Chalazan, Brandon ;
Chasman, Daniel, I ;
Chen, Yii-Der Ida .
NATURE, 2021, 590 (7845) :290-299
[29]  
van der Harst P, 2018, CIRC RES, V122, P433, DOI [10.1161/CIRCRESAHA.117.312086, 10.1161/circresaha.117.312086]
[30]   The Penn Medicine BioBank: Towards a Genomics-Enabled Learning Healthcare System to Accelerate Precision Medicine in a Diverse Population [J].
Verma, Anurag ;
Damrauer, Scott M. ;
Naseer, Nawar ;
Weaver, JoEllen ;
Kripke, Colleen M. ;
Guare, Lindsay ;
Sirugo, Giorgio ;
Kember, Rachel L. ;
Drivas, Theodore G. ;
Dudek, Scott M. ;
Bradford, Yuki ;
Lucas, Anastasia ;
Judy, Renae ;
Verma, Shefali S. ;
Meagher, Emma ;
Nathanson, Katherine L. ;
Feldman, Michael ;
Ritchie, Marylyn D. ;
Rader, Daniel J. .
JOURNAL OF PERSONALIZED MEDICINE, 2022, 12 (12)