Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale

doi:10.1038/s41588-020-0676-4

Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale

,

Producción científica: Article › revisión exhaustiva

186 Citas (Scopus)

Resumen

Large-scale whole-genome sequencing studies have enabled the analysis of rare variants (RVs) associated with complex phenotypes. Commonly used RV association tests have limited scope to leverage variant functions. We propose STAAR (variant-set test for association using annotation information), a scalable and powerful RV association test method that effectively incorporates both variant categories and multiple complementary annotations using a dynamic weighting scheme. For the latter, we introduce ‘annotation principal components’, multidimensional summaries of in silico variant annotations. STAAR accounts for population structure and relatedness and is scalable for analyzing very large cohort and biobank whole-genome sequencing studies of continuous and dichotomous traits. We applied STAAR to identify RVs associated with four lipid traits in 12,316 discovery and 17,822 replication samples from the Trans-Omics for Precision Medicine Program. We discovered and replicated new RV associations, including disruptive missense RVs of NPC1L1 and an intergenic region near APOC1P1 associated with low-density lipoprotein cholesterol.

Idioma original	English
Páginas (desde-hasta)	969-983
Número de páginas	15
Publicación	Nature Genetics
Volumen	52
N.º	9
DOI	https://doi.org/10.1038/s41588-020-0676-4
Estado	Published - sept 1 2020

Nota bibliográfica

Publisher Copyright:
© 2020, The Author(s), under exclusive licence to Springer Nature America, Inc.

Financiación

This work was supported by grant nos. R35-CA197449, P01-CA134294, U19-CA203654 and R01-HL113338 (to X. Lin), U01-HG009088 (to X. Lin, S.R.S. and B.M.N.), R01-HL142711 (to P.N. and G.M.P.), K01-HL125751 and R03-HL141439 (to G.M.P.), R35-HL135824 (to C.J.W.), 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, UL1TR001881 and DK063491 (to J.I.R. and X.G.), HHSN268201800002I (to G.R.A.), R35-GM127131 and R01-MH101244 (to S.R.S.), U01-HL72518, HL087698, HL49762, HL59684, HL58625, HL071025, HL112064, NR0224103 and M01-RR000052 (to the Johns Hopkins General Clinical Research Center), R01-HL093093, R01-HL133040 (to D.E.W.), NO1-HC-25195, HHSN268201500001I, 75N92019D00031 and R01-HL092577-06S1 (to R.S.V. and L.A.C.), the Evans Medical Foundation and the Jay and Louis Coffman Endowment from the Department of Medicine, Boston University School of Medicine (to R.S.V.), HHSN268201800001I (to K.M.R., A.T.K., M.P.C. and J.G.B.), U01-HL137162 (to K.M.R. and M.P.C.), R35-HL135818 and R01-HL113338 (to S.R.), R01-HL113323, U01-DK085524, R01-HL045522, R01-MH078143, R01-MH078111 and R01-MH083824 (to J.M.P., M.C.M., J.E.C. and J.B.), R01-HL92301, R01-HL67348, R01-NS058700, R01-AR48797 and R01-AG058921 (to N.D.P. and D.W.B.), R01-DK071891 (to N.D.P., B.I.F. and D.W.B.), M01-RR07122 and F32-HL085989 (to the General Clinical Research Center of the Wake Forest University School of Medicine), the American Diabetes Association, P60-AG10484 (to the Claude Pepper Older Americans Independence Center of Wake Forest University Health Sciences), U01-HL137181 (to J.R.O.), R01-HL093093 (to S.T.M.), 1U24CA237617 and 5U24HG009446 (to X.S.L.), HHSN268201600018C, HHSN268201600001C, HHSN268201600002C, HHSN268201600003C and HHSN268201600004C (to C.L.K.), U01-HL072524, R01-HL104135-04S1, U01-HL054472, U01-HL054473, U01-HL054495, U01-HL054509 and R01-HL055673-18S1 (to M.R.I., S.A. and D.K.A.), Swedish Research Council grant no. 201606830 (to G.H.), grant nos. HHSN268201800010I, HHSN268201800011I, HHSN268201800012I, HHSN268201800013I, HHSN268201800014I and HHSN268201800015I (to A.C.), HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700005I and HHSN268201700004I (to E.B.), and R01-HL134320 (to C.M.B.). WGS for the TOPMed program was supported by the NHLBI. Centralized read mapping and genotype calling, along with variant quality metrics and filtering were provided by the TOPMed Informatics Research Center (no. 3R01HL-117626-02S1; contract no. HHSN268201800002I). Phenotype harmonization, data management, sample identity quality control and general study coordination were provided by the TOPMed Data Coordinating Center (no. 3R01HL-120393-02S1; 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 Note. S.A. reports equity and employment by 23andMe. L.A.C. spends part of her time consulting for the Dyslipidemia Foundation, a nonprofit company, as a statistical consultant. X.S.L. is cofounder, board member and scientific advisory board of GV20 Oncotherapy, board member of the scientific advisory board of 3DMedCare, consultant of Genentech and is a recipient of research grants from Sanofi and Takeda, all unrelated to the present work. For The Amish Research Program receives partial support from Regeneron Pharmaceuticals for B.D.M. M.E.M reports a grant from Regeneron Pharmaceuticals that is unrelated to the present work. B.M.P. serves on the steering committee of the Yale Open Data Access Project funded by Johnson & Johnson. S.R. reports interests in Jazz Pharmaceuticals, Eisai and Respircardia, all unrelated to the present work. Z.W. cofounded Rgenta Therapeutics and directs its scientific advisory board. B.M.N. is on the scientific advisory board of Deep Genomics, and is a consultant for CAMP4 Therapeutics, Takeda and Biogen. S.R.S. is a consultant to NGM Biopharmaceuticals and Inari Agriculture. He is also on the scientific advisory board of Veritas Genetics. G.R.A. is an employee of Regeneron Pharmaceuticals and owns stock and stock options for Regeneron Pharmaceuticals. The spouse of C.J.W. works at Regeneron Pharmaceuticals. P.N. reports grants from Amgen, Apple and Boston Scientific, and consulting income from Apple and Blackstone Life Sciences, all unrelated to the present work. X. Lin is a consultant to AbbVie Pharmaceuticals.

Financiadores	Número del financiador
Institute of Neurological Disorders and Stroke National Advisory Neurological Disorders and Stroke Council
Margaret M. and Albert B. Alkek Department of Medicine
1 Laboratory for Complex Brain Networks, Wake Forest University School of Medicine
Sanofi and Takeda
National Institute of Arthritis and Musculoskeletal and Skin Diseases
Vetenskapsrådet
Evans Medical Foundation
National Institute on Aging
National Heart, Lung, and Blood Institute (NHLBI)	R01HL142711, R01HL133040, R01HL112064, U01HL072518, R01HL113338, R01HL059684, R01HL095163, U01HL054509, U01HL137181, R01HL105756, U01HL137162, R01HL092301, R43HL095161, R01HL071025, P50HL118006, R43HL095160, R01HL120393, R13HL095166, R43HL095167, P01HL045522, R44HL095169, R01HL049762, F32HL085989, U01HL054473, U01HL054495, U01HL054472, K08HL141601, U01HL130114, R01HL055673, R01HL134320, R35HL135818, U01HL072524, R01HL093093, R01HL119443, K01HL125751, R01HL113323, R01HL117626, R03HL141439, R01HL092577, R01HL067348, R01HL087698, R21HL095165, R01HL104135, R35HL135824
National Heart, Lung, and Blood Institute (NHLBI)
National Childhood Cancer Registry – National Cancer Institute	R35CA197449, P30CA016672, P01CA134294, U19CA203654, U24CA237617
National Childhood Cancer Registry – National Cancer Institute
National Institute of Health National Institute of Nursing Research	NR0224103
National Institute of Health National Institute of Nursing Research
National Heart, Lung, and Blood Institute (NHLBI)	R35-HL135824, HL58625, N01-HC-95161, N01-HC-95162, N01-HC-95163, N01-HC-95164, K01-HL125751, N01-HC-95160, HL087698, N01-HC-95169, N01-HC-95159, U01-HL72518, N01-HC-95165, N01-HC-95166, N01-HC-95167, HHSN268201800002I, R01-HL113338, N01-HC-95168, R01-HL142711, R03-HL141439, HL071025, HHSN268201500003I
National Heart, Lung, and Blood Institute (NHLBI)
National Human Genome Research Institute	U24HG009446, U01HG009088
National Human Genome Research Institute
National Institute of General Medical Sciences	T32GM074897, R35GM127131, T32GM135117
National Institute of General Medical Sciences
National Institute of Diabetes and Digestive and Kidney Diseases	U01DK085524, P30DK063491, R01DK071891
National Institute of Diabetes and Digestive and Kidney Diseases
National Institute of Mental Health	R01MH078143, R01MH078111, R01MH083824, R01MH101244
National Institute of Mental Health
National Institutes of Health/National Institute of Environmental Health Sciences	P42ES016454, P30ES000002
National Institutes of Health/National Institute of Environmental Health Sciences
National Center for Advancing Translational Sciences (NCATS)	UL1TR001420, UL1TR001079, UL1TR001881, UL1TR000040
National Center for Advancing Translational Sciences (NCATS)
National Human Genome Research Institute	U01-HG009088
National Human Genome Research Institute
National Institutes of Health (NIH)	75N92020D00007, 75N92020D00001, 75N92020D00002, 75N92020D00005, 75N92020D00006, 75N92020D00003, 75N92020D00004
National Institutes of Health (NIH)
National Center for Research Resources	M01RR000052, M01RR007122
National Center for Research Resources
National Institute on Drug Abuse	Z01DA000004
National Institute on Drug Abuse
Department of Family Medicine School of Medicine Boston University School of Medicine and Boston Medical Center Boston University Institute for Health Systems Innovation and Policy	R01-HL67348, U01-DK085524, R01-AR48797, R01-HL045522, R01-MH083824, R01-HL113323, R35-HL135818, M01-RR07122, R01-NS058700, R01-DK071891, HHSN268201800001I, U01-HL137162, R01-AG058921, R01-MH078111, R01-MH078143, R01-HL92301, F32-HL085989
Department of Family Medicine School of Medicine Boston University School of Medicine and Boston Medical Center Boston University Institute for Health Systems Innovation and Policy
National Institute of Mental Health	R01-MH101244
National Institute of Mental Health
Johns Hopkins General Clinical Research Center	NO1-HC-25195, R01-HL092577-06S1, 75N92019D00031, R01-HL133040, HHSN268201500001I, R01-HL093093
National Childhood Cancer Registry – National Cancer Institute	R35-CA197449, P01-CA134294, U19-CA203654
National Childhood Cancer Registry – National Cancer Institute
Institute of Neurological Disorders and Stroke National Advisory Neurological Disorders and Stroke Council	R01NS058700
Institute of Neurological Disorders and Stroke National Advisory Neurological Disorders and Stroke Council
American Diabetes Association Inc	P60-AG10484
American Diabetes Association Inc
National Center for Research Resources	M01-RR000052
National Center for Research Resources
National Institute on Aging	K01AG059898, R01AG058921
National Institute on Aging
National Institute of General Medical Sciences	R35-GM127131
National Institute of General Medical Sciences
Claude Pepper Older Americans Independence Center of Wake Forest University Health Sciences	1U24CA237617, U01-HL054509, U01-HL072524, U01-HL054495, U01-HL054473, 5U24HG009446, R01-HL104135-04S1, U01-HL054472, R01-HL055673-18S1, U01-HL137181, HHSN268201600002C, HHSN268201600003C, HHSN268201600001C, HHSN268201600018C, HHSN268201600004C
Vetenskapsrådet	201606830, HHSN268201700003I, HHSN268201700004I, HHSN268201700005I, R01-HL134320, HHSN268201700001I, HHSN268201700002I, HHSN268201800015I, HHSN268201800012I, HHSN268201800011I, HHSN268201800014I, HHSN268201800013I, HHSN268201800010I
Vetenskapsrådet
National Institute of Diabetes and Digestive and Kidney Diseases	DK063491
National Institute of Diabetes and Digestive and Kidney Diseases
National Institute of Arthritis and Musculoskeletal and Skin Diseases	R01AR048797
National Institute of Arthritis and Musculoskeletal and Skin Diseases
National Center for Advancing Translational Sciences (NCATS)	UL1-TR-001420, UL1-TR-001079, UL1TR001881, UL1-TR-000040
National Center for Advancing Translational Sciences (NCATS)

ASJC Scopus subject areas

Genetics

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10.1038/s41588-020-0676-4

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@article{c144b52dddaa47d8aae975b189a4f116,

title = "Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale",

abstract = "Large-scale whole-genome sequencing studies have enabled the analysis of rare variants (RVs) associated with complex phenotypes. Commonly used RV association tests have limited scope to leverage variant functions. We propose STAAR (variant-set test for association using annotation information), a scalable and powerful RV association test method that effectively incorporates both variant categories and multiple complementary annotations using a dynamic weighting scheme. For the latter, we introduce {\textquoteleft}annotation principal components{\textquoteright}, multidimensional summaries of in silico variant annotations. STAAR accounts for population structure and relatedness and is scalable for analyzing very large cohort and biobank whole-genome sequencing studies of continuous and dichotomous traits. We applied STAAR to identify RVs associated with four lipid traits in 12,316 discovery and 17,822 replication samples from the Trans-Omics for Precision Medicine Program. We discovered and replicated new RV associations, including disruptive missense RVs of NPC1L1 and an intergenic region near APOC1P1 associated with low-density lipoprotein cholesterol.",

author = "Xihao Li and Zilin Li and Hufeng Zhou and Gaynor, \{Sheila M.\} and Yaowu Liu and Han Chen and Ryan Sun and Rounak Dey and Arnett, \{Donna K.\} and Stella Aslibekyan and Ballantyne, \{Christie M.\} and Bielak, \{Lawrence F.\} and John Blangero and Eric Boerwinkle and Bowden, \{Donald W.\} and Broome, \{Jai G.\} and Conomos, \{Matthew P.\} and Adolfo Correa and Cupples, \{L. Adrienne\} and Curran, \{Joanne E.\} and Freedman, \{Barry I.\} and Xiuqing Guo and George Hindy and Irvin, \{Marguerite R.\} and Kardia, \{Sharon L.R.\} and Sekar Kathiresan and Khan, \{Alyna T.\} and Kooperberg, \{Charles L.\} and Laurie, \{Cathy C.\} and Liu, \{X. Shirley\} and Mahaney, \{Michael C.\} and Manichaikul, \{Ani W.\} and Martin, \{Lisa W.\} and Mathias, \{Rasika A.\} and McGarvey, \{Stephen T.\} and Mitchell, \{Braxton D.\} and Montasser, \{May E.\} and Moore, \{Jill E.\} and Morrison, \{Alanna C.\} and O{\textquoteright}Connell, \{Jeffrey R.\} and Palmer, \{Nicholette D.\} and Akhil Pampana and Peralta, \{Juan M.\} and Peyser, \{Patricia A.\} and Psaty, \{Bruce M.\} and Susan Redline and Rice, \{Kenneth M.\} and Rich, \{Stephen S.\} and Smith, \{Jennifer A.\} and Arnett, \{Donna K.\}",

note = "Publisher Copyright: {\textcopyright} 2020, The Author(s), under exclusive licence to Springer Nature America, Inc.",

year = "2020",

month = sep,

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doi = "10.1038/s41588-020-0676-4",

language = "English",

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T1 - Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale

AU - Li, Xihao

AU - Li, Zilin

AU - Zhou, Hufeng

AU - Gaynor, Sheila M.

AU - Liu, Yaowu

AU - Chen, Han

AU - Sun, Ryan

AU - Dey, Rounak

AU - Arnett, Donna K.

AU - Aslibekyan, Stella

AU - Ballantyne, Christie M.

AU - Bielak, Lawrence F.

AU - Blangero, John

AU - Boerwinkle, Eric

AU - Bowden, Donald W.

AU - Broome, Jai G.

AU - Conomos, Matthew P.

AU - Correa, Adolfo

AU - Cupples, L. Adrienne

AU - Curran, Joanne E.

AU - Freedman, Barry I.

AU - Guo, Xiuqing

AU - Hindy, George

AU - Irvin, Marguerite R.

AU - Kardia, Sharon L.R.

AU - Kathiresan, Sekar

AU - Khan, Alyna T.

AU - Kooperberg, Charles L.

AU - Laurie, Cathy C.

AU - Liu, X. Shirley

AU - Mahaney, Michael C.

AU - Manichaikul, Ani W.

AU - Martin, Lisa W.

AU - Mathias, Rasika A.

AU - McGarvey, Stephen T.

AU - Mitchell, Braxton D.

AU - Montasser, May E.

AU - Moore, Jill E.

AU - Morrison, Alanna C.

AU - O’Connell, Jeffrey R.

AU - Palmer, Nicholette D.

AU - Pampana, Akhil

AU - Peralta, Juan M.

AU - Peyser, Patricia A.

AU - Psaty, Bruce M.

AU - Redline, Susan

AU - Rice, Kenneth M.

AU - Rich, Stephen S.

AU - Smith, Jennifer A.

AU - Arnett, Donna K.

PY - 2020/9/1

Y1 - 2020/9/1

N2 - Large-scale whole-genome sequencing studies have enabled the analysis of rare variants (RVs) associated with complex phenotypes. Commonly used RV association tests have limited scope to leverage variant functions. We propose STAAR (variant-set test for association using annotation information), a scalable and powerful RV association test method that effectively incorporates both variant categories and multiple complementary annotations using a dynamic weighting scheme. For the latter, we introduce ‘annotation principal components’, multidimensional summaries of in silico variant annotations. STAAR accounts for population structure and relatedness and is scalable for analyzing very large cohort and biobank whole-genome sequencing studies of continuous and dichotomous traits. We applied STAAR to identify RVs associated with four lipid traits in 12,316 discovery and 17,822 replication samples from the Trans-Omics for Precision Medicine Program. We discovered and replicated new RV associations, including disruptive missense RVs of NPC1L1 and an intergenic region near APOC1P1 associated with low-density lipoprotein cholesterol.

AB - Large-scale whole-genome sequencing studies have enabled the analysis of rare variants (RVs) associated with complex phenotypes. Commonly used RV association tests have limited scope to leverage variant functions. We propose STAAR (variant-set test for association using annotation information), a scalable and powerful RV association test method that effectively incorporates both variant categories and multiple complementary annotations using a dynamic weighting scheme. For the latter, we introduce ‘annotation principal components’, multidimensional summaries of in silico variant annotations. STAAR accounts for population structure and relatedness and is scalable for analyzing very large cohort and biobank whole-genome sequencing studies of continuous and dichotomous traits. We applied STAAR to identify RVs associated with four lipid traits in 12,316 discovery and 17,822 replication samples from the Trans-Omics for Precision Medicine Program. We discovered and replicated new RV associations, including disruptive missense RVs of NPC1L1 and an intergenic region near APOC1P1 associated with low-density lipoprotein cholesterol.

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Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale

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Financiación

ASJC Scopus subject areas

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