Ancestral diversity in lipoprotein(a) studies helps address evidence gaps

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  • Moa P. Lee
  • Sofia F. Dimos
  • Laura M. Raffield
  • Zhe Wang
  • Anna F. Ballou
  • Carolina G. Downie
  • Christopher H. Arehart
  • Adolfo Correa
  • Paul S. De Vries
  • Zhaohui Du
  • Christopher R. Gignoux
  • Penny Gordon-Larsen
  • Xiuqing Guo
  • Jeffrey Haessler
  • Annie Green Howard
  • Yao Hu
  • Helina Kassahun
  • Shia T. Kent
  • J. Antonio G. Lopez
  • Keri L. Monda
  • Kari E. North
  • Ulrike Peters
  • Michael H. Preuss
  • Stephen S. Rich
  • Shannon L. Rhodes
  • Jie Yao
  • Rina Yarosh
  • Michael Y. Tsai
  • Jerome I. Rotter
  • Charles L. Kooperberg
  • Christie Ballantyne
  • Christy L. Avery
  • Mariaelisa Graff
Introduction The independent and causal cardiovascular disease risk factor lipoprotein(a) (Lp(a)) is elevated in >1.5 billion individuals worldwide, but studies have prioritised European populations. Methods Here, we examined how ancestrally diverse
studies could clarify Lp(a)’s genetic architecture, inform efforts examining application of Lp(a) polygenic risk scores (PRS), enable causal inference and identify unexpected Lp(a) phenotypic effects using data from African (n=25 208), East Asian (n=2895), European (n=362 558), South Asian (n=8192) and Hispanic/Latino (n=8946) populations.
Results Fourteen genome-wide significant loci with numerous population specific signals of large effect were identified that enabled construction of Lp(a) PRS of moderate (R2=15% in East Asians) to high (R2=50% in Europeans) accuracy. For all populations, PRS showed promise as a ‘rule out’ for elevated Lp(a) because certainty of assignment to the low-risk threshold was high (88.0%–
99.9%) across PRS thresholds (80th–99th percentile).
Causal effects of increased Lp(a) with increased glycated haemoglobin were estimated for Europeans (p value =1.4×10−6), although inverse effects in Africans and East Asians suggested the potential for heterogeneous causal effects. Finally, Hispanic/Latinos were the only population in which known associations with coronary atherosclerosis and ischaemic heart disease were identified in external testing of Lp(a) PRS phenotypic effects.
Conclusions Our results emphasise the merits of prioritising ancestral diversity when addressing Lp(a) evidence gaps.
OriginalsprogEngelsk
Artikelnummere002382
TidsskriftOpen Heart
Vol/bind10
Udgave nummer2
Antal sider11
ISSN2398-595X
DOI
StatusUdgivet - 2023

Bibliografisk note

Funding Information:
This work was supported by UK Biobank application 25953. The following grants supported this study: R01HL152828 (Avery, Ballou, Howard, North), R01HL151152 (Avery, Gignoux, Graff, North), R01HG010297, R01HG011345 (Avery, Gignoux, Graff, North), T32HL007055 (Lee) and F32HL149256 (Lee). Amgen Inc (Thousand Oaks, California) partially funded this study. The PAGE (Population Architecture Using Genomics and Epidemiology) programme is funded by the National Human Genome Research Institute with cofunding from the National Institute on Minority Health and Health Disparities and the National Heart, Lung, and Blood Institute. Assistance with data management, data integration, data dissemination, genotype imputation, ancestry deconvolution, population genetics, analysis pipelines and general study coordination was provided by the PAGE Coordinating Center (NI-HU01HG007419). Genotyping services were provided by the Center for Inherited Disease Research, which is fully funded through a federal contract from the National Institutes of Health (NIH) to The Johns Hopkins University, contract number HHSN268201200008I. Genotype data quality control and quality assurance services were provided by the Genetic Analysis Center in the Biostatistics Department of the University of Washington, through support provided by the Center for Inherited Disease Research contract. PAGE data and materials included in this report were funded through the following studies and organisations: (1) The Atherosclerosis Risk in Communities study (ARIC): The Atherosclerosis Risk in Communities study has been funded in whole or in part with Federal funds from the National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services (contract numbers HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700004I and HHSN268201700005I), R01HL087641, R01HL059367 and R01HL086694; National Human Genome Research Institute contract U01HG004402; and National Institutes of Health contract HHSN268200625226C. Measurement of Lp(a) was supported by Denka Seiken. The authors thank the staff and participants of the ARIC study for their important contributions. Infrastructure was partly supported by Grant Number UL1RR025005, a component of the National Institutes of Health and NIH Roadmap for Medical Research. (2) The Coronary Artery Risk Development in Young Adults Study (CARDIA): The Coronary Artery Risk Development in Young Adults Study (CARDIA) is supported by contracts HHSN268201800003I, HHSN268201800004I, HHSN268201800005I, HHSN268201800006I and HHSN268201800007I from the National Heart, Lung, and Blood Institute (NHLBI). CARDIA is also partially supported by the Intramural Research Program of the National Institute on Aging (NIA) and an intra-agency agreement between NIA and NHLBI (AG0005). GWAS genotyping and data analyses were funded in part by grants U01-HG004729 and R01-HL093029 from the National Institutes of Health to Dr Myriam Fornage. (3) Women’s Health Initiative (WHI): The WHI programme is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, US Department of Health and Human Services through contracts 75N92021D00001, 75N92021D00002, 75N92021D00003, 75N92021D00004, 75N92021D00005. (4) The Jackson Heart Study (JHS) is supported and conducted in collaboration with Jackson State University (HHSN268201800013I), Tougaloo College (HHSN268201800014I), the Mississippi State Department of Health (HHSN268201800015I) and the University of Mississippi Medical Center (HHSN268201800010I, HHSN268201800011I and HHSN268201800012I) contracts from the National Heart, Lung, and Blood Institute (NHLBI) and the National Institute on Minority Health and Health Disparities (NIMHD). The authors also wish to thank the staffs and participants of the JHS. (5) The MESA project is conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with MESA investigators. Support for MESA is provided by contracts 75N92020D00001, HHSN268201500003I, N01-HC-95159, 75N92020D00005, N01-HC-95160, 75N92020D00002, N01-HC-95161, 75N92020D00003, N01-HC-95162, 75N92020D00006, N01-HC-95163, 75N92020D00004, N01-HC-95164, 75N92020D00007, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, N01-HC-95169, UL1-TR-000040, UL1-TR-001079, UL1-TR-001420. Also supported in part by the National Center for Advancing Translational Sciences, CTSI grant UL1TR001881, and the National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center (DRC) grant DK063491 to the Southern California Diabetes Endocrinology Research Center. Infrastructure for the CHARGE Consortium is supported in part by the National Heart, Lung, and Blood Institute (NHLBI) grant R01HL105756. (6) BioMe: The Mount Sinai BioMe Biobank is supported by The Andrea and Charles Bronfman Philanthropies. We thank all participants and all our recruiters who have assisted and continue to assist in data collection and management. We are grateful for the computational resources and staff expertise provided by Scientific Computing at the Icahn School of Medicine at Mount Sinai. Whole genome sequencing (WGS) for the Trans-Omics in Precision Medicine (TOPMed) programme was supported by the National Heart, Lung and Blood Institute (NHLBI). WGS for 'NHLBI TOPMed: Jackson Heart Study' (phs000964) was performed at the Northwest Genomics Center (HHSN268201100037C). Core support including centralised genomic read mapping and genotype calling, along with variant quality metrics and filtering were provided by the TOPMed Informatics Research Center (3R01HL-117626-02S1; contract HHSN268201800002I). Core support including phenotype harmonisation, data management, sample-identity QC and general programme coordination were provided by the TOPMed Data Coordinating Center (R01HL-120393; U01HL-120393; contract HHSN268201800001I). We gratefully acknowledge the studies and participants who provided biological samples and data for TOPMed. The project described was supported by the National Center for Advancing Translational Sciences, National Institutes of Health, through Grant KL2TR002490 (LMR). The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the US Department of Health and Human Services.

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