Multi-ancestry transcriptome-wide association analyses yield insights into tobacco use biology and drug repurposing

被引：16

作者：

Chen, Fang ^{[1
]}

Wang, Xingyan ^{[1
]}

Jang, Seon-Kyeong ^{[2
]}

Quach, Bryan C. ^{[3
]}

Weissenkampen, J. Dylan ^{[4
,5
]}

Khunsriraksakul, Chachrit ^{[6
]}

Yang, Lina ^{[1
]}

Sauteraud, Renan ^{[1
]}

Albert, Christine M. ^{[7
,8
]}

Allred, Nicholette D. D. ^{[9
]}

Arnett, Donna K. ^{[10
]}

Ashley-Koch, Allison E. ^{[11
,12
,13
]}

Barnes, Kathleen C. ^{[14
]}

Barr, R. Graham ^{[15
]}

Becker, Diane M. ^{[16
,21
]}

Bielak, Lawrence F. ^{[17
]}

Bis, Joshua C. ^{[18
]}

Blangero, John ^{[19
,20
]}

Boorgula, Meher Preethi ^{[14
]}

Chasman, Daniel I.

Chavan, Sameer ^{[14
]}

Chen, Yii-Der I. ^{[22
]}

Chuang, Lee-Ming ^{[23
]}

Correa, Adolfo ^{[24
]}

Curran, Joanne E. ^{[19
]}

David, Sean P. ^{[25
,26
]}

de las Fuentes, Lisa ^{[27
,28
]}

Deka, Ranjan ^{[29
]}

Duggirala, Ravindranath ^{[19
,20
]}

Faul, Jessica D. ^{[30
]}

Garrett, Melanie E. ^{[11
,12
]}

Gharib, Sina A. ^{[18
,31
]}

Guo, Xiuqing ^{[22
]}

Hall, Michael E. ^{[32
]}

Hawley, Nicola L. ^{[33
]}

He, Jiang ^{[34
]}

Hobbs, Brian D. ^{[21
,35
,36
]}

Hokanson, John E. ^{[37
]}

Hsiung, Chao A. ^{[38
]}

Hwang, Shih-Jen ^{[39
,40
]}

Hyde, Thomas M. ^{[41
,42
,43
]}

Irvin, Marguerite R. ^{[44
]}

Jaffe, Andrew E. ^{[41
,42
,45
,46
,47
,48
]}

Johnson, Eric O. ^{[3
]}

Kaplan, Robert ^{[49
,50
]}

Kardia, Sharon L. R.

Kaufman, Joel D. ^{[41
,51
,52
,53
,54
]}

Kelly, Tanika N. ^{[34
]}

Kleinman, Joel E. ^{[42
]}

Kooperberg, Charles ^{[55
]}

机构：

[1] Penn State Coll Med, Dept Publ Hlth Sci, Hershey, PA 17033 USA

[2] Univ Minnesota, Dept Psychol, Minneapolis, MN 55455 USA

[3] RTI Int, Res Triangle Pk, NC USA

[4] Univ Penn, Dept Genet, Philadelphia, PA 19104 USA

[5] Penn State Coll Med, Dept Psychol, Hershey, PA USA

[6] Penn State Coll Med, Dept Bioinformat & Genom, Hershey, PA USA

[7] Cedars Sinai Med Ctr, Dept Cardiol, Los Angeles, CA USA

[8] Brigham & Womens Hosp, Div Prevent Med, Boston, MA USA

[9] Wake Forest Sch Med, Dept Biochem, Winston Salem, NC USA

[10] Univ Kentucky, Coll Publ Hlth, Lexington, KY USA

[11] Duke Univ, Duke Mol Physiol Inst, Med Ctr, Durham, NC USA

[12] Duke Univ, Dept Med, Med Ctr, Durham, NC USA

[13] Duke Univ, Duke Comprehens Sickle Cell Ctr, Med Ctr, Durham, NC USA

[14] Univ Colorado, Colorado Ctr Personalized Med, Anschutz Med Ctr, Aurora, CO USA

[15] Columbia Univ, Dept Med, Med Ctr, New York, NY USA

[16] Johns Hopkins Univ, Dept Med, Sch Med, Baltimore, MD USA

[17] Univ Michigan, Sch Publ Hlth, Dept Epidemiol, Ann Arbor, MI USA

[18] Univ Washington, Cardiovasc Hlth Res Unit, Dept Med, Seattle, WA USA

[19] Univ Texas Rio Grande Valley, Dept Human Genet, Sch Med, Brownsville, TX USA

[20] Univ Texas Rio Grande Valley Sch Med, South Texas Diabet & Obes Inst, Brownsville, TX USA

[21] Harvard Med Sch, Boston, MA USA

[22] Harbor UCLA Med Ctr, Lundquist Inst Biomed Innovat, Inst Translat Genom & Populat Sci, Dept Pediat, Torrance, CA USA

[23] Natl Taiwan Univ Hosp, Dept Internal Med, Taipei, Taiwan

[24] Univ Mississippi, Med Ctr, Jackson Heart Study, Dept Med, Jackson, MS USA

[25] Univ Chicago, Chicago, IL USA

[26] NorthShore Univ Hlth Syst, Evanston, IL USA

[27] Washington Univ, Sch Med, Dept Med, Div Biostat, St Louis, MO USA

[28] Washington Univ, Cardiovasc Div, Sch Med, St Louis, MO USA

[29] Univ Cincinnati, Coll Med, Dept Environm & Publ Hlth Sci, Cincinnati, OH USA

[30] Univ Michigan, Survey Res Ctr, Inst Social Res, Ann Arbor, MI USA

[31] Univ Washington, Comp Med Core Ctr Lung Biol, Div Pulm Crit Care & Sleep Med, Seattle, WA USA

[32] Univ Mississippi, Med Ctr, Dept Med, Jackson, MS USA

[33] Yale Univ, Sch Publ Hlth, Dept Epidemiol Chron Dis, New Haven, CT USA

[34] Tulane Univ, Dept Epidemiol, Sch Publ Hlth & Trop Med, New Orleans, LA USA

[35] Brigham & Womens Hosp, Channing Div Network Med, Boston, MA USA

[36] Brigham & Womens Hosp, Div Pulm & Crit Care Med, Boston, MA USA

[37] Univ Colorado, Colorado Sch Publ Hlth, Dept Epidemiol, Anschutz Med Campus, Aurora, CO USA

[38] Natl Hlth Res Inst, Colorado Sch Publ Hlth, Dept Epidemiol, Anschutz Med Campus, Aurora, CO USA

[39] NIH, Natl Heart Lung & Blood Inst, Div Intramural Res, Populat Sci Branch, Bethesda, MD USA

[40] Framingham Heart Dis Epidemiol Study, Framingham, MA USA

[41] Lieber Inst Brain Dev, Baltimore, MD USA

[42] Johns Hopkins Univ, Dept Psychiat & Behav Sci, Sch Med, Baltimore, MD USA

[43] Johns Hopkins Univ, Dept Neurol, Sch Med, Baltimore, MD USA

[44] Univ Alabama Birmingham, Dept Epidemiol, Birmingham, AL USA

[45] Johns Hopkins Bloomberg Sch Publ Hlth, Dept Mental Hlth, Baltimore, MD USA

[46] Johns Hopkins Bloomberg Sch Publ Hlth, Dept Biostat, Baltimore, MD USA

[47] Johns Hopkins Univ, Sch Med, Dept Human Genet, Baltimore, MD USA

[48] Johns Hopkins Univ, Sch Med, Dept Neurosci, Baltimore, MD USA

[49] Albert Einstein Coll Med, Dept Epidemiol & Populat Hlth, The Bronx, NY USA

[50] Fred Hutchinson Canc Res Ctr, Publ Hlth Sci Div, Seattle, WA USA

来源：

NATURE GENETICS | 2023年 / 55卷 / 02期

基金：

美国国家卫生研究院;

关键词：

GENERAL FRAMEWORK; RARE VARIANTS; CEREBELLUM; NICOTINE;

D O I：

10.1038/s41588-022-01282-x

中图分类号：

Q3 [遗传学];

学科分类号：

071007 ; 090102 ;

摘要：

Most transcriptome-wide association studies (TWASs) so far focus on European ancestry and lack diversity. To overcome this limitation, we aggregated genome-wide association study (GWAS) summary statistics, whole-genome sequences and expression quantitative trait locus (eQTL) data from diverse ancestries. We developed a new approach, TESLA (multi-ancestry integrative study using an optimal linear combination of association statistics), to integrate an eQTL dataset with a multi-ancestry GWAS. By exploiting shared phenotypic effects between ancestries and accommodating potential effect heterogeneities, TESLA improves power over other TWAS methods. When applied to tobacco use phenotypes, TESLA identified 273 new genes, up to 55% more compared with alternative TWAS methods. These hits and subsequent fine mapping using TESLA point to target genes with biological relevance. In silico drug-repurposing analyses highlight several drugs with known efficacy, including dextromethorphan and galantamine, and new drugs such as muscle relaxants that may be repurposed for treating nicotine addiction.

引用

页码：291 / +

页数：15

共 28 条

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Guy Brusselle
Andre G. Uitterlinden
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Elizabeth C. Oelsner
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Michael R. Brown
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Medea Imboden
Ayoung Jeong
Traci M. Bartz
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Claudia Flexeder
Stefan Karrasch
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