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A statistical framework for multi-trait rare variant analysis in large-scale whole-genome sequencing studies

Nature Computational Science volume 5, pages 125–143 (2025)Cite this article

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A preprint version of the article is available at bioRxiv.

Abstract

Large-scale whole-genome sequencing (WGS) studies have improved our understanding of the contributions of coding and noncoding rare variants to complex human traits. Leveraging association effect sizes across multiple traits in WGS rare variant association analysis can improve statistical power over single-trait analysis, and also detect pleiotropic genes and regions. Existing multi-trait methods have limited ability to perform rare variant analysis of large-scale WGS data. We propose MultiSTAAR, a statistical framework and computationally scalable analytical pipeline for functionally informed multi-trait rare variant analysis in large-scale WGS studies. MultiSTAAR accounts for relatedness, population structure and correlation among phenotypes by jointly analyzing multiple traits, and further empowers rare variant association analysis by incorporating multiple functional annotations. We applied MultiSTAAR to jointly analyze three lipid traits in 61,838 multi-ethnic samples from the Trans-Omics for Precision Medicine (TOPMed) Program. We discovered and replicated new associations with lipid traits missed by single-trait analysis.

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Fig. 1: MultiSTAAR framework and pipeline.
Fig. 2: Manhattan plots and Q–Q plots for unconditional gene-centric coding, noncoding and ncRNA multi-trait analysis of LDL-C, HDL-C and TG using TOPMed data (n = 61,838).
Fig. 3: TOPMed genetic-region (2-kb sliding window) unconditional multi-trait analysis results for LDL-C, HDL-C and TG using TOPMed data (n = 61,838).

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Data availability

This Article used TOPMed Freeze 8 WGS data and lipids phenotype data. Genotype and phenotype data are both available in the database of Genotypes and Phenotypes. The TOPMed WGS data were from the following 20 study cohorts (accession numbers provided in parentheses): Old Order Amish (phs000956.v1.p1), Atherosclerosis Risk in Communities Study (phs001211), Mt Sinai BioMe Biobank (phs001644), Coronary Artery Risk Development in Young Adults (phs001612), Cleveland Family Study (phs000954), Cardiovascular Health Study (phs001368), Diabetes Heart Study (phs001412), Framingham Heart Study (phs000974), Genetic Study of Atherosclerosis Risk (phs001218), Genetic Epidemiology Network of Arteriopathy (phs001345), Genetic Epidemiology Network of Salt Sensitivity (phs001217), Genetics of Lipid Lowering Drugs and Diet Network (phs001359), Hispanic Community Health Study—Study of Latinos (phs001395), Hypertension Genetic Epidemiology Network and Genetic Epidemiology Network of Arteriopathy (phs001293), Jackson Heart Study (phs000964), Multi-Ethnic Study of Atherosclerosis (phs001416), San Antonio Family Heart Study (phs001215), Genome-Wide Association Study of Adiposity in Samoans (phs000972), Taiwan Study of Hypertension using Rare Variants (phs001387) and Women’s Health Initiative (phs001237). The sample sizes, ancestry and phenotype summary statistics of these cohorts are provided in Supplementary Table 2. Source data for Figs. 2 and 3 and Extended Data Figs. 1 and 2 are available via Zenodo (https://doi.org/10.5281/zenodo.14213842)58. The UK Biobank analyses were conducted using the UK Biobank resource under application 52008. The functional annotation data are publicly available and can be downloaded from the following links: GRCh38 CADD v1.4 (https://cadd.gs.washington.edu/download); ANNOVAR dbNSFP v3.3a (https://annovar.openbioinformatics.org/en/latest/user-guide/download); LINSIGHT (https://github.com/CshlSiepelLab/LINSIGHT); FATHMM-XF (http://fathmm.biocompute.org.uk/fathmm-xf); FANTOM5 CAGE (https://fantom.gsc.riken.jp/5/data); GeneCards (https://www.genecards.org; v4.7 for hg38); and Umap/Bismap (https://bismap.hoffmanlab.org; ‘before March 2020’ version). In addition, recombination rate and nucleotide diversity were obtained from ref. 59. The whole-genome individual functional annotation data were assembled from a variety of sources, and the computed annotation PCs are available at the Functional Annotation of Variant-Online Resource (FAVOR) site (https://favor.genohub.org)60 and the FAVOR database (https://doi.org/10.7910/DVN/1VGTJI)61.

Code availability

MultiSTAAR is implemented as an open-source R package available at https://github.com/xihaoli/MultiSTAAR and https://hsph.harvard.edu/research/lin-lab/software. Data analysis was performed in R (4.1.0). STAAR v0.9.7 and MultiSTAAR v0.9.7 were used in simulation and real data analysis and implemented as open-source R packages available at https://github.com/xihaoli/STAAR (ref. 56) and https://github.com/xihaoli/MultiSTAAR (ref. 54). The assembled functional annotation data were downloaded from FAVOR using Wget (https://www.gnu.org/software/wget/wget.html).

Change history

  • 05 March 2025

    In the version of the article initially published, DOIs were missing from refs. 54–58 and have now been added to the HTML and PDF versions of the article.

References

  1. Taliun, D. et al. Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program. Nature 590, 290–299 (2021).

    Google Scholar 

  2. The All of Us Research Program Investigators. The ‘All of Us’ research program. New Engl. J. Med. 381, 668–676 (2019).

    Google Scholar 

  3. Halldorsson, B. V. et al. The sequences of 150,119 genomes in the UK Biobank. Nature 607, 732–740 (2022).

    MATH  Google Scholar 

  4. Lee, S., Abecasis, G. R., Boehnke, M. & Lin, X. Rare-variant association analysis: study designs and statistical tests. Am. J. Human Genet. 95, 5–23 (2014).

    Google Scholar 

  5. Li, B. & Leal, S. M. Methods for detecting associations with rare variants for common diseases: application to analysis of sequence data. Am. J. Human Genet. 83, 311–321 (2008).

    MATH  Google Scholar 

  6. Madsen, B. E. & Browning, S. R. A groupwise association test for rare mutations using a weighted sum statistic. PLoS Genet. 5, e1000384 (2009).

    Google Scholar 

  7. Morris, A. P. & Zeggini, E. An evaluation of statistical approaches to rare variant analysis in genetic association studies. Genet. Epidemiol. 34, 188–193 (2010).

    MATH  Google Scholar 

  8. Wu, M. C. et al. Rare-variant association testing for sequencing data with the sequence kernel association test. Am. J. Human Genet. 89, 82–93 (2011).

    MATH  Google Scholar 

  9. Liu, Y. et al. ACAT: a fast and powerful P value combination method for rare-variant analysis in sequencing studies. Am. J. Human Genet. 104, 410–421 (2019).

    MATH  Google Scholar 

  10. Solovieff, N., Cotsapas, C., Lee, P. H., Purcell, S. M. & Smoller, J. W. Pleiotropy in complex traits: challenges and strategies. Nat. Rev. Genet. 14, 483–495 (2013).

    Google Scholar 

  11. Sivakumaran, S. et al. Abundant pleiotropy in human complex diseases and traits. Am. J. Human Genet. 89, 607–618 (2011).

    MATH  Google Scholar 

  12. Abdellaoui, A., Yengo, L., Verweij, K. J. H. & Visscher, P. M. 15 years of GWAS discovery: realizing the promise. Am. J. Human Genet 110, 179–194 (2023).

    MATH  Google Scholar 

  13. Watanabe, K. et al. A global overview of pleiotropy and genetic architecture in complex traits. Nat. Genet. 51, 1339–1348 (2019).

    MATH  Google Scholar 

  14. Wu, B. & Pankow, J. S. Sequence kernel association test of multiple continuous phenotypes. Genet. Epidemiol. 40, 91–100 (2016).

    MATH  Google Scholar 

  15. Dutta, D., Scott, L., Boehnke, M. & Lee, S. Multi-SKAT: general framework to test for rare-variant association with multiple phenotypes. Genet. Epidemiol. 43, 4–23 (2019).

    Google Scholar 

  16. Luo, L. et al. Multi-trait analysis of rare-variant association summary statistics using MTAR. Nat. Commun. 11, 2850 (2020).

    MATH  Google Scholar 

  17. Broadaway, K. A. et al. A statistical approach for testing cross-phenotype effects of rare variants. Am. J. Human Genet. 98, 525–540 (2016).

    MATH  Google Scholar 

  18. Li, X. et al. Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale. Nat. Genet. 52, 969–983 (2020).

    MATH  Google Scholar 

  19. Sammel, M., Lin, X. & Ryan, L. Multivariate linear mixed models for multiple outcomes. Stat. Med. 18, 2479–2492 (1999).

    MATH  Google Scholar 

  20. Conomos, M. P., Miller, M. B. & Thornton, T. A. Robust inference of population structure for ancestry prediction and correction of stratification in the presence of relatedness. Genet. Epidemiol. 39, 276–293 (2015).

    MATH  Google Scholar 

  21. Conomos, M. P., Reiner, A. P., Weir, B. S. & Thornton, T. A. Model-free estimation of recent genetic relatedness. Am. J. Human Genet. 98, 127–148 (2016).

    MATH  Google Scholar 

  22. Gogarten, S. M. et al. Genetic association testing using the GENESIS R/Bioconductor package. Bioinformatics 35, 5346–5348 (2019).

    MATH  Google Scholar 

  23. Lee, P. H. et al. Principles and methods of in silico prioritization of noncoding regulatory variants. Human Genet. 137, 15–30 (2018).

  24. Li, Z. et al. A framework for detecting noncoding rare-variant associations of large-scale whole-genome sequencing studies. Nat. Methods 19, 1599–1611 (2022).

  25. Morrison, A. C. et al. Practical approaches for whole-genome sequence analysis of heart-and blood-related traits. Am. J. Human Genet. 100, 205–215 (2017).

    MATH  Google Scholar 

  26. Selvaraj, M. S. et al. Whole genome sequence analysis of blood lipid levels in >66,000 individuals. Nat. Commun. 13, 5995 (2022).

    MATH  Google Scholar 

  27. Liu, Z. & Lin, X. Multiple phenotype association tests using summary statistics in genome-wide association studies. Biometrics 74, 165–175 (2018).

    MathSciNet  MATH  Google Scholar 

  28. Teslovich, T. M. et al. Biological, clinical and population relevance of 95 loci for blood lipids. Nature 466, 707–713 (2010).

    MATH  Google Scholar 

  29. Schaffner, S. F. et al. Calibrating a coalescent simulation of human genome sequence variation. Genome Res. 15, 1576–1583 (2005).

    MATH  Google Scholar 

  30. Natarajan, P. et al. Deep-coverage whole genome sequences and blood lipids among 16,324 individuals. Nat. Commun. 9, 3391 (2018).

    MATH  Google Scholar 

  31. Stilp, A. M. et al. A system for phenotype harmonization in the National Heart, Lung and Blood Institute Trans-Omics for Precision Medicine (TOPMed) program. Am. J. Epidemiol. 190, 1977–1992 (2021).

    MATH  Google Scholar 

  32. Frankish, A. et al. GENCODE reference annotation for the human and mouse genomes. Nucleic Acids Res. 47, D766–D773 (2019).

    MATH  Google Scholar 

  33. Dong, C. et al. Comparison and integration of deleteriousness prediction methods for non-synonymous SNVs in whole exome sequencing studies. Human Mol. Genet. 24, 2125–2137 (2014).

  34. Kircher, M. et al. A general framework for estimating the relative pathogenicity of human genetic variants. Nat. Genet. 46, 310–315 (2014).

    MATH  Google Scholar 

  35. Huang, Y.-F., Gulko, B. & Siepel, A. Fast, scalable prediction of deleterious noncoding variants from functional and population genomic data. Nat. Genet. 49, 618–624 (2017).

  36. Rogers, M. F. et al. FATHMM-XF: accurate prediction of pathogenic point mutations via extended features. Bioinformatics 34, 511–513 (2017).

    MATH  Google Scholar 

  37. Buniello, A. et al. The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019. Nucleic Acids Res. 47, D1005–D1012 (2019).

    Google Scholar 

  38. Klarin, D. et al. Genetics of blood lipids among ~300,000 multi-ethnic participants of the Million Veteran Program. Nat. Genet. 50, 1514–1523 (2018).

    MATH  Google Scholar 

  39. Forrest, A. R. et al. A promoter-level mammalian expression atlas. Nature 507, 462–470 (2014).

    MATH  Google Scholar 

  40. Abascal, F. et al. Expanded encyclopaedias of DNA elements in the human and mouse genomes. Nature 583, 699–710 (2020).

    MATH  Google Scholar 

  41. Andersson, R. et al. An atlas of active enhancers across human cell types and tissues. Nature 507, 455–461 (2014).

    MATH  Google Scholar 

  42. Fishilevich, S. et al. GeneHancer: genome-wide integration of enhancers and target genes in GeneCards. Database 2017, bax028 (2017).

    Google Scholar 

  43. DiCorpo, D. et al. Whole genome sequence association analysis of fasting glucose and fasting insulin levels in diverse cohorts from the NHLBI TOPMed program. Commun. Biol. 5, 756 (2022).

    Google Scholar 

  44. Jiang, M.-Z. et al. Whole genome sequencing based analysis of inflammation biomarkers in the Trans-Omics for Precision Medicine (TOPMed) consortium. Human Mol. Genet 33, 1429–1441 (2024).

    MATH  Google Scholar 

  45. Dijk, W. et al. Identification of a gain-of-function LIPC variant as a novel cause of familial combined hypocholesterolemia. Circulation 146, 724–739 (2022).

    MATH  Google Scholar 

  46. Ottensmann, L. et al. Genome-wide association analysis of plasma lipidome identifies 495 genetic associations. Nat. Commun. 14, 6934 (2023).

    MATH  Google Scholar 

  47. Guo, T. et al. Association between the DOCK7, PCSK9 and GALNT2 gene polymorphisms and serum lipid levels. Sci. Rep. 6, 19079 (2016).

    Google Scholar 

  48. Li, Z. et al. Dynamic scan procedure for detecting rare-variant association regions in whole-genome sequencing studies. Am. J. Human Genet. 104, 802–814 (2019).

    MATH  Google Scholar 

  49. McCaw, Z. R., Gao, J., Lin, X. & Gronsbell, J. Synthetic surrogates improve power for genome-wide association studies of partially missing phenotypes in population biobanks. Nat. Genet. 56, 1527–1536 (2024).

    Google Scholar 

  50. Li, X. et al. Powerful, scalable and resource-efficient meta-analysis of rare variant associations in large whole genome sequencing studies. Nat. Genet. 55, 154–164 (2023).

    MATH  Google Scholar 

  51. Chen, H. et al. Control for population structure and relatedness for binary traits in genetic association studies via logistic mixed models. Am. J. Human Genet. 98, 653–666 (2016).

    MATH  Google Scholar 

  52. Chen, H. et al. Efficient variant set mixed model association tests for continuous and binary traits in large-scale whole-genome sequencing studies. Am. J. Human Genet. 104, 260–274 (2019).

    MATH  Google Scholar 

  53. Liu, Y. & Xie, J. Cauchy combination test: a powerful test with analytic P-value calculation under arbitrary dependency structures. J. Am. Stat. Assoc. 115, 393–402 (2020).

    MathSciNet  MATH  Google Scholar 

  54. Li, X. xihaoli/MultiSTAAR: MultiSTAAR_v0.9.7 (v0.9.7). Zenodo. https://doi.org/10.5281/zenodo.13955413 (2024).

  55. Li, X. & Li, Z. xihaoli/STAARpipeline: STAARpipeline_v0.9.7 (v0.9.7). Zenodo. https://doi.org/10.5281/zenodo.10098313 (2023).

  56. Li, X. xihaoli/STAAR: STAAR_v0.9.7 (v0.9.7). Zenodo. https://doi.org/10.5281/zenodo.10060210 (2023).

  57. Li, X. & Li, Z. xihaoli/STAARpipelineSummary: STAARpipelineSummary_v0.9.7 (v0.9.7). Zenodo. https://doi.org/10.5281/zenodo.10113310 (2023).

  58. Li, X. et al. Source data of the MultiSTAAR manuscript “A statistical framework for multi-trait rare variant analysis in large-scale whole-genome sequencing studies”. [Data set]. Zenodo. https://doi.org/10.5281/zenodo.14213842 (2024).

  59. Gazal, S. et al. Linkage disequilibrium–dependent architecture of human complex traits shows action of negative selection. Nat. Genet. 49, 1421–1427 (2017).

    MATH  Google Scholar 

  60. Zhou, H. et al. FAVOR: functional annotation of variants online resource and annotator for variation across the human genome. Nucleic Acids Res. 51, D1300–D1311 (2023).

    Google Scholar 

  61. Zhou, H., Arapoglou, T., Li, X., Li, Z. & Lin, X. FAVOR Essential Database. V1 edn (Harvard Dataverse, 2022).

  62. Moors, J. et al. A Polynesian-specific missense CETP variant alters the lipid profile. Human Genet. Genomics Adv. 4, 100204 (2023).

    MATH  Google Scholar 

Download references

Acknowledgements

This work was supported by grants R35-CA197449, U19-CA203654, U01-HG012064 and U01-HG009088 (X. Lin), NHLBI TOPMed Fellowship 75N92021F00229 (X. Li and M.S.S.), 1R01AG086379-01 (Z. Liu), R01-HL142711 and R01-HL127564 (P.N. and G.M.P.), R00HG012956-02 (Z.Y.), 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, UL1-TR001881, DK063491, R01-HL071051, R01-HL071205, R01-HL071250, R01-HL071251, R01-HL071258, R01-HL071259 and UL1-RR033176 (J.I.R.), HHSN268201800001I and U01-HL137162 (K.M.R.), DK078616 and HL151855 (J.B.M.), 1R35-HL135818, R01-HL113338 and HL046389 (S.R.), HL105756 (B.M.P.), HHSN268201600018C, HHSN268201600001C, HHSN268201600002C, HHSN268201600003C and HHSN268201600004C (C.K.), R01-MD012765 and R01-DK117445 (N.F.), R01-HL153805 and R03-HL154284 (B.E.C.), HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700005I and HHSN268201700004I (E.B.), U01-HL072524, R01-HL104135-04S1, U01-HL054472, U01-HL054473, U01-HL054495, U01-HL054509 and R01-HL055673-18S1 (D.K.A.) and U01-HL72518, HL087698, HL49762, HL59684, HL58625, HL071025, HL112064, NR0224103 and M01-RR000052 (to the Johns Hopkins General Clinical Research Center). The Diabetes Heart Study (DHS) was supported by R01 HL92301, R01 HL67348, R01 NS058700, R01 AR48797, R01 DK071891 and R01 AG058921, the General Clinical Research Center of the Wake Forest University School of Medicine (M01 RR07122, F32 HL085989), the American Diabetes Association and a pilot grant from the Claude Pepper Older Americans Independence Center of Wake Forest University Health Sciences (P60 AG10484). The Framingham Heart Study (FHS) acknowledges the support of contracts NO1-HC-25195, HHSN268201500001I, 75N92019D00031, 1R01HL064753, R01HL076784 and 1R01AG028321 from the National Heart, Lung and Blood Institute and grant supplement R01 HL092577-06S1 for this research. We also acknowledge the dedication of the FHS study participants, without whom this research would not be possible. R.S.V. is supported in part by the Evans Medical Foundation and the Jay and Louis Coffman Endowment from the Department of Medicine, Boston University Chobanian & Avedisian School of Medicine. 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). We also thank the staff and participants of the JHS. Support for GENOA was provided by the NHLBI (U01HL054457, U01HL054464, U01HL054481, R01HL119443 and R01HL087660) of the National Institutes of Health (NIH). Collection of the San Antonio Family Study data was supported in part by NIH grants P01 HL045522, MH078143, MH078111 and MH083824, and whole-genome sequencing of SAFS subjects was supported by U01 DK085524 and R01 HL113323. Molecular data for the Trans-Omics in Precision Medicine (TOPMed) program was supported by the NHLBI. Core support, including centralized 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 no. HHSN268201800002I). Core support, including phenotype harmonization, data management, sample-identity quality control and general program coordination were provided by the TOPMed Data Coordinating Center (R01HL-120393; U01HL-120393; contract no. HHSN268201800001I). We gratefully acknowledge the studies and participants who provided biological samples and data for TOPMed. The full study-specific acknowledgements are detailed in the Supplementary Information.

Author information

Authors and Affiliations

  1. Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Xihao Li, Zachary R. McCaw & Yun Li

  2. Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Xihao Li, Min-Zhi Jiang, Yun Li & Laura M. Raffield

  3. Human Genetics Center, Department of Epidemiology, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA

    Han Chen, Eric Boerwinkle, Paul S. de Vries, Myriam Fornage, Alanna C. Morrison & Bing Yu

  4. Center for Genomic Medicine and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA

    Margaret Sunitha Selvaraj, Zhi Yu & Pradeep Natarajan

  5. Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA

    Margaret Sunitha Selvaraj, Zhi Yu, Brian E. Cade, James B. Meigs, Pradeep Natarajan & Xihong Lin

  6. Department of Medicine, Harvard Medical School, Boston, MA, USA

    Margaret Sunitha Selvaraj, James B. Meigs, Alisa K. Manning & Pradeep Natarajan

  7. Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA

    Eric Van Buren, Hufeng Zhou, Sheila M. Gaynor, Rounak Dey, Zilin Li & Xihong Lin

  8. Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA

    Yuxuan Wang, Daniel DiCorpo, Ching-Ti Liu, Josée Dupuis & Gina M. Peloso

  9. Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Ryan Sun

  10. Clinical and Translational Epidemiology Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA

    Zhi Yu

  11. Department of Biostatistics, The Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA

    Min-Zhi Jiang

  12. Provost Office, University of South Carolina, Columbia, SC, USA

    Donna K. Arnett

  13. Section of Cardiovascular Medicine, Boston Medical Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA

    Emelia J. Benjamin

  14. Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA

    Emelia J. Benjamin

  15. Framingham Heart Study, Framingham, MA, USA

    Emelia J. Benjamin, Nancy L. Heard-Costa & Ramachandran S. Vasan

  16. Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA

    Joshua C. Bis, Jennifer A. Brody, Bruce M. Psaty & Colleen M. Sitlani

  17. Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, TX, USA

    John Blangero, Joanne E. Curran & Michael C. Mahaney

  18. Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA

    Eric Boerwinkle, Adithya Balasubramanian, Huyen Dinh, Harsha Doddapaneni, Shannon Dugan-Perez, Jesse Farek, Richard Gibbs, Yi Han, Jianhong Hu, Ziad Khan, Sandra Lee, Vipin Menon, Ginger Metcalf, Zeineen Momin, Donna Muzny, Caitlin Nessner, Osuji Nkechinyere, Geoffrey Okwuonu, Mahitha Rajendran, Sejal Salvi, Jireh Santibanez & Jennifer Watt

  19. Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC, USA

    Donald W. Bowden & Nicholette D. Palmer

  20. Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA

    Brian E. Cade & Susan Redline

  21. Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA

    Brian E. Cade & Susan Redline

  22. Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA

    April P. Carson

  23. Department of Human Genetics and Department of Biostatistics and Health Data Science, University of Pittsburgh, Pittsburgh, PA, USA

    Jenna C. Carlson

  24. The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Nathalie Chami, Ruth J. F. Loos & Zhe Wang

  25. The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Nathalie Chami

  26. The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA

    Yii-Der Ida Chen, Kent D. Taylor & Jerome I. Rotter

  27. Brown Foundation Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA

    Myriam Fornage

  28. Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Nora Franceschini & Kari E. North

  29. Department of Internal Medicine, Nephrology, Wake Forest University School of Medicine, Winston-Salem, NC, USA

    Barry I. Freedman

  30. Division of Biology & Biomedical Sciences, Washington University School of Medicine, St. Louis, MO, USA

    Charles Gu

  31. Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA

    Nancy L. Heard-Costa

  32. Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA

    Jiang He & Changwei Li

  33. Translational Science Institute, Tulane University, New Orleans, LA, USA

    Jiang He & Changwei Li

  34. Department of Preventive Medicine, Northwestern University, Chicago, IL, USA

    Lifang Hou

  35. Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan

    Yi-Jen Hung

  36. Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA

    Marguerite R. Irvin

  37. Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA

    Robert C. Kaplan

  38. Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA

    Robert C. Kaplan & Alexander P. Reiner

  39. Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA

    Sharon L. R. Kardia, Patricia A. Peyser & Jennifer A. Smith

  40. Department of Medicine, Division of Nephrology, University of Illinois Chicago, Chicago, IL, USA

    Tanika N. Kelly & Charles Kooperberg

  41. Department of Biomedical Informatics, University of Colorado, Aurora, CO, USA

    Iain Konigsberg

  42. Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Brian G. Kral, Rasika A. Mathias & Lisa R. Yanek

  43. Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA

    Honghuang Lin

  44. Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark

    Ruth J. F. Loos

  45. School of Medicine and Health Sciences, George Washington University, Washington, DC, USA

    Lisa W. Martin

  46. Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA

    Braxton D. Mitchell & May E. Montasser

  47. Naseri & Associates Public Health Consultancy Firm and Family Health Clinic, Apia, Samoa

    Take Naseri

  48. Department of Epidemiology, Brown University, Providence, RI, USA

    Take Naseri & Stephen McGarvey

  49. Departments of Epidemiology, University of Washington, Seattle, WA, USA

    Bruce M. Psaty & Alexander P. Reiner

  50. Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA

    Bruce M. Psaty

  51. Department of Genome Sciences, University of Virginia, Charlottesville, VA, USA

    Stephen S. Rich

  52. Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA

    Hemant K. Tiwari

  53. Department of Quantitative and Qualitative Health Sciences, UT Health San Antonio School of Public Health, San Antonia, TX, USA

    Ramachandran S. Vasan

  54. School of Medicine, National University of Samoa, Apia, Samoa

    Satupa’itea Viali

  55. Department of Chronic Disease Epidemiology, Yale University School of Public Health, New Haven, CT, USA

    Satupa’itea Viali

  56. Oceania University of Medicine, Apia, Samoa

    Satupa’itea Viali

  57. Department of Epidemiology, Fairbanks School of Public Health, Indiana University, Indianapolis, IN, USA

    Jennifer Wessel

  58. Diabetes Translational Research Center, Indiana University, Indianapolis, IN, USA

    Jennifer Wessel

  59. Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada

    Josée Dupuis

  60. Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA

    James B. Meigs

  61. Division of Biostatistics, Data Science Institute, and Cancer Center, Medical College of Wisconsin, Milwaukee, WI, USA

    Paul L. Auer

  62. Metabolism Program, The Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Alisa K. Manning

  63. Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, MA, USA

    Alisa K. Manning

  64. Department of Biostatistics, University of Washington, Seattle, WA, USA

    Erin Buth, Matthew Conomos,  Ben Heavner, Susanne May, Caitlin McHugh, Sarah C. Nelson, Catherine Tong, Kayleen Williams & Kenneth M. Rice

  65. Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA

    Zhonghua Liu

  66. Department of Statistics, Harvard University, Cambridge, MA, USA

    Xihong Lin

  67. New York Genome Center, New York, NY, USA

    Namiko Abe, Karen Bunting, Bo-Juen Chen, Soren Germer, Tanja Smith & Michael Zody

  68. University of Michigan, Ann Arbor, MI, USA

    Gonçalo Abecasis, Larry Bielak, Thomas Blackwell, Matthew Flickinger, Colin Gross, Jonathon LeFaive, Jacob Pleiness, Albert Vernon Smith, Daniel Taliun, Peter VandeHaar, Jiongming Wang, Ketian Yu & Sebastian Zoellner

  69. Broad Institute, Cambridge, MA, USA

    Francois Aguet, Kristin Ardlie, Mark Chaffin, Seung Hoan Choi, Stacey Gabriel, Namrata Gupta, Carolina Roselli & Seyedeh Maryam Zekavat

  70. Cedars-Sinai Medical Center, Boston, MA, USA

    Christine Albert

  71. Children’s Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, USA

    Laura Almasy

  72. Emory University, Atlanta, GA, USA

    Alvaro Alonso, Rich Johnston, Lawrence S. Phillips & Zhaohui Qin

  73. University of Maryland, Baltimore, MD, USA

    Seth Ament, Amber Beitelshees, Christy Chang, Coleen Damcott, Scott Devine, Mao Fu, Da-Wei Gong, Yue Guan, Elliott Hong, Michael Kessler, Joshua Lewis, Patrick McArdle, Tim O’Connor, James Perry, Toni Pollin, Robert Reed, Kathleen Ryan, Amol Shetty, Elizabeth Streeten, Simeon Taylor & Huichun Xu

  74. University of Washington, Seattle, WA, USA

    Peter Anderson, Jai Broome, Colleen Davis, Leslie Emery, Chris Frazar, Stephanie M. Fullerton, Stephanie Gogarten, Deepti Jain, Craig Johnson, Alyna Khan, Cathy Laurie, Cecelia Laurie, David Levine, Sarah Ruuska, Josh Smith, Nona Sotoodehnia, Adrienne M. Stilp, Adam Szpiro, Timothy A. Thornton, David Tirschwell, Fei Fei Wang, Bruce Weir & Quenna Wong

  75. University of Mississippi, Jackson, MS, USA

    Pramod Anugu, Lynette Ekunwe, Yan Gao, Hao Mei & Nancy Min

  76. National Institutes of Health, Bethesda, MD, USA

    Deborah Applebaum-Bowden

  77. Johns Hopkins University, Baltimore, MD, USA

    Dan Arking, Dimitrios Avramopoulos, Emily Barron-Casella, Terri Beaty, Lewis Becker, James Casella, Kimberly Jones, Barry Make, Rakhi Naik, Ingo Ruczinski, Steven Salzberg, Margaret Taub & Dhananjay Vaidya

  78. Duke University, Durham, NC, USA

    Allison Ashley-Koch & Marilyn Telen

  79. University of Alabama, Birmingham, AL, USA

    Stella Aslibekyan & Bertha Hidalgo

  80. Stanford University, Stanford, CA, USA

    Tim Assimes, Chris Gignoux & Marco Perez

  81. Department of Medicine, Providence Health Care, Vancouver, British Columbia, Canada

    Najib Ayas

  82. Cleveland Clinic, Cleveland, OH, USA

    John Barnard & Mina Chung

  83. Tempus, University of Colorado Anschutz Medical Campus, Aurora, CO, USA

    Kathleen Barnes

  84. Columbia University, New York, NY, USA

    R. Graham Barr & Danish Saleheen

  85. The Emmes Corporation, LTRC, Rockville, MD, USA

    Lucas Barwick

  86. Cleveland Clinic, Quantitative Health Sciences, Cleveland, OH, USA

    Gerald Beck

  87. Department of Medicine, Johns Hopkins University, Baltimore, MD, USA

    Diane Becker

  88. National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA

    Rebecca Beer, Weiniu Gan, Cashell Jaquish, Andrew Johnson, Daniel Levy, James Luo, Julie Mikulla, George Papanicolaou & Pankaj Qasba

  89. Department of Epidemiology, University of Florida, Gainesville, FL, USA

    Takis Benos

  90. Fundação de Hematologia e Hemoterapia de PernambucoHemope, Recife, Brazil

    Marcos Bezerra

  91. Department of Obstetrics and Gynecology, University of Utah, Salt Lake City, UT, USA

    Nathan Blue

  92. National Jewish Health, National Jewish Health, Denver, CO, USA

    Russell Bowler

  93. Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI, USA

    Ulrich Broeckel

  94. Department of Pediatrics, University of Texas Health at Houston, Houston, TX, USA

    Deborah Brown

  95. University of California at San Francisco, San Francisco, CA, USA

    Esteban Burchard, Ryan Hernandez & Shannon Kelly

  96. Department of Biomedical Data Science, Stanford University, Stanford, CA, USA

    Carlos Bustamante

  97. University of Colorado at Denver, Denver, CO, USA

    Jonathan Cardwell, Sameer Chavan, Michelle Daya, Shanshan Gao, Daniel Grine, John Hokanson, Ethan Lange, Susan Mathai, Bonnie Neltner, Meher Preethi Boorgula, Pamela Russell, David Schwartz, Aniket Shetty, Tarik Walker, Avram Walts & Ivana Yang

  98. Brigham & Women’s Hospital, Boston, MA, USA

    Vincent Carey, Juan P. Casas Romero, Michael Cho, Dawn DeMeo, Auyon Ghosh, Meryl LeBoff, Jiwon Lee, JoAnn Manson, Dandi Qiao, Edwin Silverman, Jody Sylvia & Carla Wilson

  99. University of Montreal, Montreal, Canada

    Julie Carrier

  100. Washington State University at Pullman, Pullman, WA, USA

    Cara Carty

  101. University of California at Los Angeles, Los Angeles, CA, USA

    Richard Casaburi, Carolyn Crandall & Karol Watson

  102. Department of Medicine, Brigham & Women’s Hospital, Boston, MA, USA

    Peter Castaldi & Matt Moll

  103. National Taiwan University, Taipei, Taiwan

    Yi-Cheng Chang

  104. Division of Preventive Medicine, Brigham & Women’s Hospital, Boston, MA, USA

    Daniel Chasman

  105. University of Virginia, Charlottesville, VA, USA

    Wei-Min Chen, Charles Farber, Ani Manichaikul, Josyf C. Mychaleckyj & Aakrosh Ratan

  106. National Taiwan University Hospital, National Taiwan University, Taipei, Taiwan

    Lee-Ming Chuang

  107. National Health Research Institute Taiwan, Miaoli County, Taiwan

    Ren-Hua Chung

  108. Metabolomics Platform, Broad Institute, Cambridge, MA, USA

    Clary Clish

  109. Department of Immunity and Immunology, Cleveland Clinic, Cleveland, OH, USA

    Suzy Comhair

  110. University of Vermont, Burlington, VT, USA

    Elaine Cornell

  111. Department of Population Health Science, University of Mississippi, Jackson, MS, USA

    Adolfo Correa

  112. National Jewish Health, Denver, CO, USA

    James Crapo & Snow Xueyan Zhao

  113. Department of Biostatistics, Boston University, Boston, MA, USA

    L. Adrienne Cupples

  114. Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA

    Jeffrey Curtis & Cristen Willer

  115. Vitalant Research Institute, San Francisco, CA, USA

    Brian Custer

  116. University of Illinois at Chicago, Chicago, IL, USA

    Dawood Darbar

  117. University of Chicago, Chicago, IL, USA

    Sean David

  118. Vanderbilt University, Nashville, TN, USA

    Michael DeBaun

  119. University of Cincinnati, Cincinnati, OH, USA

    Ranjan Deka

  120. University of North Carolina, Chapel Hill, NC, USA

    Qing Duan

  121. University of Texas Rio Grande Valley School of Medicine, Edinburg, TX, USA

    Ravi Duggirala & Juan Manuel Peralta

  122. Department of Pathology and Laboratory Medicine, University of Vermont, Burlington, VT, USA

    Jon Peter Durda & Russell Tracy

  123. Department of Genetics, Washington University in St Louis, St Louis, MO, USA

    Susan K. Dutcher

  124. Brown University, Providence, RI, USA

    Charles Eaton

  125. Channing Division of Network Medicine, Harvard University, Cambridge, MA, USA

    Adel El Boueiz

  126. Massachusetts General Hospital, Boston, MA, USA

    Patrick T. Ellinor, Steven A. Lubitz & Lu-Chen Weng

  127. Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA

    Serpil Erzurum

  128. Center for Genes, Environment and Health, National Jewish Health, Denver, CO, USA

    Tasha Fingerlin

  129. Washington University in St Louis, St Louis, MO, USA

    Lucinda Fulton, D. C. Rao, Karen Schwander & Yun Ju Sung

  130. Fred Hutchinson Cancer Research Center, Seattle, WA, USA

    Margery Gass & Jeff Haessler

  131. New York Genome Center, New York City, NY, USA

    Heather Geiger, Melissa Marton, Catherine Reeves, Nicolas Robine, Alexi Runnels & Lara Winterkorn

  132. Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Bruce Gelb, Eimear Kenny, Girish Nadkarni & Michael Preuss

  133. University of Pittsburgh, Pittsburgh, PA, USA

    Mark Geraci, Mark Gladwin, Ryan L. Minster & Frank Sciurba

  134. Beth Israel Deaconess Medical Center, Boston, MA, USA

    Robert Gerszten & Tamar Sofer

  135. Department of Psychiatry, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA

    David Glahn

  136. University of Texas Rio Grande Valley School of Medicine, San Antonio, TX, USA

    Harald Goring

  137. University of Colorado Anschutz Medical Campus, Aurora, CO, USA

    Sharon Graw, Luisa Mestroni & Matthew Taylor

  138. Department of Obstetrics and Gynecology, Mass General Brigham, Boston, MA, USA

    Kathryn J. Gray

  139. Lundquist Institute, Torrance, CA, USA

    Xiuqing Guo, Xiaohui Li & Henry Lin

  140. Department of Cardiology, University of Mississippi, Jackson, MS, USA

    Michael Hall

  141. Department of Medicine, University of Calgary, Calgary, Canada

    Patrick Hanly

  142. Department of Genetics, University of Maryland, Philadelphia, PA, USA

    Daniel Harris

  143. Department of Chronic Disease Epidemiology, Yale University, New Haven, CT, USA

    Nicola L. Hawley

  144. Department of Epidemiology, University of Washington, Seattle, WA, USA

    Susan Heckbert & Nicholas Smith

  145. Wake Forest Baptist Health, Winston-Salem, NC, USA

    David Herrington

  146. Channing Division of Network Medicine, Brigham & Women’s Hospital, Boston, MA, USA

    Craig Hersh

  147. University of Texas Health at Houston, Houston, TX, USA

    James Hixson

  148. Regeneron Genetics Center, Boston, MA, USA

    Brian Hobbs

  149. University of Iowa, Iowa City, IO, USA

    Karin Hoth & Robert Wallace

  150. Institute of Population Health Sciences, National Health Research Institute Taiwan, Miaoli County, Taiwan

    Chao Agnes Hsiung

  151. Blood Works Northwest, Seattle, WA, USA

    Haley Huston

  152. Taichung Veterans General Hospital Taiwan, Taichung City, Taiwan

    Chii Min Hwu, Wen-Jane Lee & Wayne Hui-Heng Sheu

  153. Divisions of Endocrinology, Diabetes and Metabolism and Internal Medicine, Oklahoma State University Medical Center, Columbus, OH, USA

    Rebecca Jackson

  154. Department of Medicine, University of Washington, Seattle, WA, USA

    Jill Johnsen

  155. Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA

    Hyun Min Kang & Joshua Weinstock

  156. Harvard University, Cambridge, MA, USA

    Wonji Kim & Sean McFarland

  157. McGill University, Montréal, Quebec, Canada

    John Kimoff

  158. Department of Epidemiology, University of Colorado at Denver, Aurora, CO, USA

    Greg Kinney

  159. Department of Medicine, Blood Works Northwest, Seattle, WA, USA

    Barbara Konkle

  160. Department of Public Health Sciences, Loyola University, Maywood, IL, USA

    Holly Kramer

  161. Department of Biostatistics, Harvard School of Public Health, Boston, MA, USA

    Christoph Lange

  162. Department of Medicine, University of Colorado at Denver, Aurora, CO, USA

    Leslie Lange

  163. Department of Epidemiology and Medicine, Brown University, Providence, RI, USA

    Simin Liu

  164. Department of Cardiology, Duke University, Durham, NC, USA

    Yongmei Liu

  165. Cardiovascular Institute, Stanford University, Stanford, CA, USA

    Yu Liu

  166. Boston University, Boston, MA, USA

    Kathryn L. Lunetta

  167. Department of Critical Care and Sleep Medicine, Division of Pulmonary, The Ohio State University, Columbus, OH, USA

    Ulysses Magalang

  168. University of Alabama at Birmingham, Birmingham, AL, USA

    Merry-Lynn McDonald

  169. Department of Genome Sciences, University of Washington, Seattle, WA, USA

    Daniel McGoldrick, Deborah Nickerson & Machiko Threlkeld

  170. RTI International, Research Triangle Park, NC, USA

    Becky McNeil

  171. University of Arizona, Tucson, AZ, USA

    Deborah A. Meyers

  172. Center For Sleep Sciences and Medicine, Stanford University, Palo Alto, CA, USA

    Emmanuel Mignot

  173. National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA

    Mollie Minear

  174. Department of Genes and Human Disease, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA

    Courtney Montgomery

  175. Howard University, Washington, DC, USA

    Sergei Nekhai

  176. University of Maryland, Balitmore, MD, USA

    Jeff O’Connell

  177. University at Buffalo, Buffalo, NY, USA

    Heather Ochs-Balcom

  178. Division of Sleep Medicine/Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Allan Pack

  179. Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA

    David T. Paik & Joseph Wu

  180. University of Minnesota, Minneapolis, MN, USA

    James Pankow, Michael Tsai & Scott Vrieze

  181. Biostatistics and Epidemiology Division, RTI International, Research Triangle Park, NC, USA

    Cora Parker

  182. Fred Hutchinson Cancer Research Center and UW Medicine, Seattle, WA, USA

    Ulrike Peters

  183. Departments of Cardiology and Medicine, Johns Hopkins University, Baltimore, MD, USA

    Wendy Post

  184. Department of Medicine, University of Colorado at Denver, Denver, CO, USA

    Julia Powers Becker

  185. Colorado Center for Personalized Medicine, University of Colorado at Denver, Denver, CO, USA

    Nicholas Rafaels

  186. Northwestern University, Chicago, IL, USA

    Laura Rasmussen-Torvik

  187. Department of Medicine, National Jewish Health, Denver, CO, USA

    Elizabeth Regan

  188. Lutia I Puava Ae Mapu I Fagalele, Apia, Samoa

    Muagututi’a Sefuiva Reupena

  189. Sleep Research Unit and Institute for Mental Health Research, University of Ottawa, Ottawa, Ontario, Canada

    Rebecca Robillard

  190. Departments of Medicine, Pharmacology and Biomedical Informatics, Vanderbilt University, Nashville, TN, USA

    Dan Roden

  191. Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil

    Ester Cerdeira Sabino

  192. Department of Pathology, University of Maryland, Seattle, WA, USA

    Shabnam Salimi

  193. Lundquist Institute, TGPS, Torrance, CA, USA

    Kevin Sandow

  194. Division of Hematology and Oncology, Harvard University, Boston, MA, USA

    Vijay G. Sankaran

  195. Department of Genetics, Harvard Medical School, Boston, MA, USA

    Christine Seidman

  196. Harvard Medical School, Boston, MA, USA

    Jonathan Seidman

  197. Department of Pediatrics, Emory University, Atlanta, GA, USA

    Vivien Sheehan

  198. Department of Human Genetics, Emory University, Atlanta, GA, USA

    Stephanie L. Sherman

  199. Departments of Medicine and Cardiology, Vanderbilt University, Nashville, TN, USA

    M. Benjamin Shoemaker

  200. UMass Memorial Medical Center, Worcester, MA, USA

    Brian Silver

  201. University of Saskatchewan, Saskatoon, Saskatchewan, Canada

    Robert Skomro

  202. Albert Einstein College of Medicine, New York, NY, USA

    Sylvia Smoller

  203. Department of Biostatistical Sciences, Wake Forest Baptist Health, Winston-Salem, NC, USA

    Beverly Snively

  204. Department of Genetics, Stanford University, Stanford, CA, USA

    Michael Snyder & Hua Tang

  205. Department of Genomic Cardiology, University of Colorado at Denver, Aurora, CO, USA

    Garrett Storm

  206. Channing Department of Medicine, Brigham & Women’s Hospital, Boston, MA, USA

    Jessica Lasky Su

  207. Université Laval, Quebec City, Quebec, Canada

    Frédéric Sériès

  208. Cancer Prevention Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA

    Lesley Tinker

  209. Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA

    Sarah Tishkoff

  210. USC Methylation Characterization Center, University of Southern California, Los Angeles, CA, USA

    David Van Den Berg

  211. Brigham & Women’s Hospital, Mass General Brigham, Boston, MA, USA

    Heming Wang

  212. Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA

    Daniel E. Weeks

  213. Department of Medicine and Channing Division of Network Medicine, Brigham & Women’s Hospital, Boston, MA, USA

    Scott T. Weiss

  214. Henry Ford Health System, Detroit, MI, USA

    L. Keoki Williams

  215. Case Western Reserve University, Cleveland, OH, USA

    Scott Williams

  216. Department of Cardiology, Beth Israel Deaconess Medical Center, Cambridge, MA, USA

    James Wilson

  217. Department of Medicine, Henry Ford Health System, Detroit, MA, USA

    Baojun Wu

  218. Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA

    Yingze Zhang

  219. Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA

    Wei Zhao

  220. Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA

    Xiaofeng Zhu

  221. Department of Medicine, University of California at San Francisco, San Francisco, CA, USA

    Elad Ziv

  222. Health Quantitative Sciences Research, Mayo Clinic, Rochester, MI, USA

    Mariza de Andrade

  223. Cardiovascular Division, Department of Medicine, Washington University in St Louis, St Louis, MO, USA

    Lisa de las Fuentes

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Contributions

X. Li, H.C., Z. Li, Z. Liu and X. Lin designed the experiments. X. Li, H.C., Z. Li and X. Lin performed the experiments. X. Li, H.C., M.S.S., E.V.B., Y.W., R.S., Z.R.M., Z.Y., M.-Z.J., D.D., S.M.G., R.D., D.K.A., E.J.B., J.C.B., J.B., E.B., D.W.B., J.A.B., B.E.C., A.P.C., J.C.C., N.C., Y.-D.I.C., J.E.C., P.S.d.V., M.F., N.F., B.I.F., C.G., N.L.H.C., J.H., L.H., Y.-J.H., M.R.I., R.C.K., S.L.R.K., T.N.K., I.K., C.K., B.G.K., C.L., Y.L., H.L., C.-T.L. R.J.F.L., M.C.M., L.W.M., R.A.M., B.D.M., M.E.M., A.C.M., T.N., K.E.N., N.D.P., P.A.P., B.M.P., S.R., A.P.R., S.S.R., C.M.S., J.A.S., K.D.T., H.K.T., R.S.V., S.V., Z.W., J.W., L.R.Y., B.Y., J.D., J.B.M., P.L.A., L.M.R., A.K.M., K.M.R., J.I.R., G.M.P., P.N., Z. Li, H.Z., Z. Liu and X. Lin acquired, analyzed or interpreted data. G.M.P., P.N. and the NHLBI TOPMed Lipids Working Group provided administrative, technical or material support. X. Li, Z. Li, Z. Liu and X. Lin drafted the paper and revised it according to suggestions by the coauthors. All authors critically reviewed the paper, suggested revisions as needed, and approved the final version.

Corresponding authors

Correspondence to Zilin Li, Zhonghua Liu or Xihong Lin.

Ethics declarations

Competing interests

Z.R.M. and R.D. are employees of Insitro. S.M.G. is an employee of Regeneron Genetics Center. M.E.M. receives research funding from Regeneron Pharmaceutical Inc., unrelated to this project. B.M.P. serves on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson. L.M.R. and S.S.R. are consultants for the TOPMed Administrative Coordinating Center (via Westat). P.N. reports research grants from Allelica, Amgen, Apple, Boston Scientific, Genentech/Roche and Novartis, personal fees from Allelica, Apple, AstraZeneca, Blackstone Life Sciences, Creative Education Concepts, CRISPR Therapeutics, Eli Lilly & Co, Esperion Therapeutics, Foresite Capital, Foresite Labs, Genentech/Roche, GV, HeartFlow, Magnet Biomedicine, Merck, Novartis, TenSixteen Bio and Tourmaline Bio, equity in Bolt, Candela, Mercury, MyOme, Parameter Health, Preciseli and TenSixteen Bio, and spousal employment at Vertex Pharmaceuticals, all unrelated to the present work. X. Lin is a consultant of AbbVie Pharmaceuticals and Verily Life Sciences. The other authors declare no competing interests.

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Nature Computational Science thanks Yuehua Cui, Yukinori Okada and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Ananya Rastogi, in collaboration with the Nature Computational Science team. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Manhattan plots and Q-Q plots for unconditional gene-centric coding, noncoding and genetic region (2-kb sliding window) multi-trait analysis of fasting glucose (FG) and fasting insulin (FI) using TOPMed data (n = 21,731).

a, Manhattan plots for unconditional gene-centric coding analysis of protein-coding genes. The horizontal line indicates a genome-wide MultiSTAAR-O P value threshold of \(5.00\times {10}^{-7}\). The significant threshold is defined by multiple comparisons using the Bonferroni correction (\(0.05/\left(\mathrm{20,000}\times 5\right)=5.00\times {10}^{-7}\)). Different symbols represent the MultiSTAAR-O P value of the protein-coding gene using different functional categories (putative loss-of-function, putative loss-of-function and disruptive missense, missense, disruptive missense, synonymous). b, Quantile-quantile plots for unconditional gene-centric coding analysis of protein-coding genes. Different symbols represent the MultiSTAAR-O P-value of the gene using different functional categories. c, Manhattan plots for unconditional gene-centric noncoding analysis of protein-coding genes. The horizontal line indicates a genome-wide MultiSTAAR-O P value threshold of \(3.57\times {10}^{-7}\). The significant threshold is defined by multiple comparisons using the Bonferroni correction (\(0.05/\left(\mathrm{20,000}\times 7\right)=3.57\times {10}^{-7}\)). Different symbols represent the MultiSTAAR-O P value of the protein-coding gene using different functional categories (upstream, downstream, UTR, promoter_CAGE, promoter_DHS, enhancer_CAGE, enhancer_DHS). Promoter_CAGE and promoter_DHS are the promoters with overlap of Cap Analysis of Gene Expression (CAGE) sites and DNase hypersensitivity (DHS) sites for a given gene, respectively. Enhancer_CAGE and enhancer_DHS are the enhancers in GeneHancer-predicted regions with the overlap of CAGE sites and DHS sites for a given gene, respectively. d, Quantile-quantile plots for unconditional gene-centric noncoding analysis of protein-coding genes. Different symbols represent the MultiSTAAR-O P-value of the gene using different functional categories. e, Manhattan plot showing the associations of 2.68 million 2-kb sliding windows versus \(-{\log }_{10}(P)\) of MultiSTAAR-O. The horizontal line indicates a genome-wide P value threshold of \(1.86\times {10}^{-8}\). f, Quantile-quantile plot of 2-kb sliding window MultiSTAAR-O P values. In panels, a, c and e, the chromosome number are indicated by the colors of dots. In all panels, MultiSTAAR-O is a two-sided test.

Extended Data Fig. 2 Manhattan plots and Q-Q plots for unconditional gene-centric coding, noncoding and genetic region (2-kb sliding window) multi-trait analysis of C-reactive protein (CRP), interleukin-6 (IL-6), lipoprotein-associated phospholipase A2 (Lp-PLA2) activity, and lipoprotein-associated phospholipase A2 (Lp-PLA2) mass using TOPMed data (n = 9,380).

a, Manhattan plots for unconditional gene-centric coding analysis of protein-coding genes. The horizontal line indicates a genome-wide MultiSTAAR-O P value threshold of \(5.00\times {10}^{-7}\). The significant threshold is defined by multiple comparisons using the Bonferroni correction (\(0.05/\left(\mathrm{20,000}\times 5\right)=5.00\times {10}^{-7}\)). Different symbols represent the MultiSTAAR-O P value of the protein-coding gene using different functional categories (putative loss-of-function, putative loss-of-function and disruptive missense, missense, disruptive missense, synonymous). b, Quantile-quantile plots for unconditional gene-centric coding analysis of protein-coding genes. Different symbols represent the MultiSTAAR-O P-value of the gene using different functional categories. c, Manhattan plots for unconditional gene-centric noncoding analysis of protein-coding genes. The horizontal line indicates a genome-wide MultiSTAAR-O P value threshold of \(3.57\times {10}^{-7}\). The significant threshold is defined by multiple comparisons using the Bonferroni correction (\(0.05/\left(\mathrm{20,000}\times 7\right)=3.57\times {10}^{-7}\)). Different symbols represent the MultiSTAAR-O P value of the protein-coding gene using different functional categories (upstream, downstream, UTR, promoter_CAGE, promoter_DHS, enhancer_CAGE, enhancer_DHS). Promoter_CAGE and promoter_DHS are the promoters with overlap of Cap Analysis of Gene Expression (CAGE) sites and DNase hypersensitivity (DHS) sites for a given gene, respectively. Enhancer_CAGE and enhancer_DHS are the enhancers in GeneHancer predicted regions with the overlap of CAGE sites and DHS sites for a given gene, respectively. d, Quantile-quantile plots for unconditional gene-centric noncoding analysis of protein-coding genes. Different symbols represent the MultiSTAAR-O P-value of the gene using different functional categories. e, Manhattan plot showing the associations of 2.67 million 2-kb sliding windows versus \(-{\log }_{10}(P)\) of MultiSTAAR-O. The horizontal line indicates a genome-wide P value threshold of \(1.87\times {10}^{-8}\). f, Quantile-quantile plot of 2-kb sliding window MultiSTAAR-O P values. In panels, a, c and e, the chromosome number are indicated by the colors of dots. In all panels, MultiSTAAR-O is a two-sided test.

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Li, X., Chen, H., Selvaraj, M.S. et al. A statistical framework for multi-trait rare variant analysis in large-scale whole-genome sequencing studies. Nat Comput Sci 5, 125–143 (2025). https://doi.org/10.1038/s43588-024-00764-8

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