Integrative analysis of loss-of-function variants in clinical and genomic data reveals novel genes associated with cardiovascular traits

Benjamin S. Glicksberg, Letizia Amadori, Nicholas K. Akers, Katyayani Sukhavasi, Oscar Franzén, Li Li, Gillian M. Belbin, Kristin L. Akers, Khader Shameer, Marcus A. Badgeley, Kipp W. Johnson, Ben Readhead, Bruce J. Darrow, Eimear E. Kenny, Christer Betsholtz, Raili Ermel, Josefin Skogsberg, Arno Ruusalepp, Eric E. Schadt, Joel T. DudleyHongxia Ren, Jason C. Kovacic, Chiara Giannarelli, Shuyu D. Li, Johan L.M. Björkegren, Rong Chen

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Background: Genetic loss-of-function variants (LoFs) associated with disease traits are increasingly recognized as critical evidence for the selection of therapeutic targets. We integrated the analysis of genetic and clinical data from 10,511 individuals in the Mount Sinai BioMe Biobank to identify genes with loss-of-function variants (LoFs) significantly associated with cardiovascular disease (CVD) traits, and used RNA-sequence data of seven metabolic and vascular tissues isolated from 600 CVD patients in the Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) study for validation. We also carried out in vitro functional studies of several candidate genes, and in vivo studies of one gene. Results: We identified LoFs in 433 genes significantly associated with at least one of 10 major CVD traits. Next, we used RNA-sequence data from the STARNET study to validate 115 of the 433 LoF harboring-genes in that their expression levels were concordantly associated with corresponding CVD traits. Together with the documented hepatic lipid-lowering gene, APOC3, the expression levels of six additional liver LoF-genes were positively associated with levels of plasma lipids in STARNET. Candidate LoF-genes were subjected to gene silencing in HepG2 cells with marked overall effects on cellular LDLR, levels of triglycerides and on secreted APOB100 and PCSK9. In addition, we identified novel LoFs in DGAT2 associated with lower plasma cholesterol and glucose levels in BioMe that were also confirmed in STARNET, and showed a selective DGAT2-inhibitor in C57BL/6 mice not only significantly lowered fasting glucose levels but also affected body weight. Conclusion: In sum, by integrating genetic and electronic medical record data, and leveraging one of the world's largest human RNA-sequence datasets (STARNET), we identified known and novel CVD-trait related genes that may serve as targets for CVD therapeutics and as such merit further investigation.

Original languageEnglish (US)
Article number108
JournalBMC Medical Genomics
Volume12
DOIs
StatePublished - Jul 25 2019
Externally publishedYes

Fingerprint

Cardiovascular Diseases
Atherosclerosis
Genes
Ecosystem
Lipids
Glucose
Electronic Health Records
Validation Studies
Liver
Hep G2 Cells
Gene Silencing
Inbred C57BL Mouse
Blood Vessels
Fasting
Triglycerides
Cholesterol
Body Weight
Gene Expression
Therapeutics

Keywords

  • Cardiovascular traits
  • Electronic Medical Records
  • Genetic association
  • Integrative data analysis
  • Loss-of-function variant
  • Target identification and validation

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)

Cite this

Integrative analysis of loss-of-function variants in clinical and genomic data reveals novel genes associated with cardiovascular traits. / Glicksberg, Benjamin S.; Amadori, Letizia; Akers, Nicholas K.; Sukhavasi, Katyayani; Franzén, Oscar; Li, Li; Belbin, Gillian M.; Akers, Kristin L.; Shameer, Khader; Badgeley, Marcus A.; Johnson, Kipp W.; Readhead, Ben; Darrow, Bruce J.; Kenny, Eimear E.; Betsholtz, Christer; Ermel, Raili; Skogsberg, Josefin; Ruusalepp, Arno; Schadt, Eric E.; Dudley, Joel T.; Ren, Hongxia; Kovacic, Jason C.; Giannarelli, Chiara; Li, Shuyu D.; Björkegren, Johan L.M.; Chen, Rong.

In: BMC Medical Genomics, Vol. 12, 108, 25.07.2019.

Research output: Contribution to journalArticle

Glicksberg, BS, Amadori, L, Akers, NK, Sukhavasi, K, Franzén, O, Li, L, Belbin, GM, Akers, KL, Shameer, K, Badgeley, MA, Johnson, KW, Readhead, B, Darrow, BJ, Kenny, EE, Betsholtz, C, Ermel, R, Skogsberg, J, Ruusalepp, A, Schadt, EE, Dudley, JT, Ren, H, Kovacic, JC, Giannarelli, C, Li, SD, Björkegren, JLM & Chen, R 2019, 'Integrative analysis of loss-of-function variants in clinical and genomic data reveals novel genes associated with cardiovascular traits', BMC Medical Genomics, vol. 12, 108. https://doi.org/10.1186/s12920-019-0542-3
Glicksberg, Benjamin S. ; Amadori, Letizia ; Akers, Nicholas K. ; Sukhavasi, Katyayani ; Franzén, Oscar ; Li, Li ; Belbin, Gillian M. ; Akers, Kristin L. ; Shameer, Khader ; Badgeley, Marcus A. ; Johnson, Kipp W. ; Readhead, Ben ; Darrow, Bruce J. ; Kenny, Eimear E. ; Betsholtz, Christer ; Ermel, Raili ; Skogsberg, Josefin ; Ruusalepp, Arno ; Schadt, Eric E. ; Dudley, Joel T. ; Ren, Hongxia ; Kovacic, Jason C. ; Giannarelli, Chiara ; Li, Shuyu D. ; Björkegren, Johan L.M. ; Chen, Rong. / Integrative analysis of loss-of-function variants in clinical and genomic data reveals novel genes associated with cardiovascular traits. In: BMC Medical Genomics. 2019 ; Vol. 12.
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abstract = "Background: Genetic loss-of-function variants (LoFs) associated with disease traits are increasingly recognized as critical evidence for the selection of therapeutic targets. We integrated the analysis of genetic and clinical data from 10,511 individuals in the Mount Sinai BioMe Biobank to identify genes with loss-of-function variants (LoFs) significantly associated with cardiovascular disease (CVD) traits, and used RNA-sequence data of seven metabolic and vascular tissues isolated from 600 CVD patients in the Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) study for validation. We also carried out in vitro functional studies of several candidate genes, and in vivo studies of one gene. Results: We identified LoFs in 433 genes significantly associated with at least one of 10 major CVD traits. Next, we used RNA-sequence data from the STARNET study to validate 115 of the 433 LoF harboring-genes in that their expression levels were concordantly associated with corresponding CVD traits. Together with the documented hepatic lipid-lowering gene, APOC3, the expression levels of six additional liver LoF-genes were positively associated with levels of plasma lipids in STARNET. Candidate LoF-genes were subjected to gene silencing in HepG2 cells with marked overall effects on cellular LDLR, levels of triglycerides and on secreted APOB100 and PCSK9. In addition, we identified novel LoFs in DGAT2 associated with lower plasma cholesterol and glucose levels in BioMe that were also confirmed in STARNET, and showed a selective DGAT2-inhibitor in C57BL/6 mice not only significantly lowered fasting glucose levels but also affected body weight. Conclusion: In sum, by integrating genetic and electronic medical record data, and leveraging one of the world's largest human RNA-sequence datasets (STARNET), we identified known and novel CVD-trait related genes that may serve as targets for CVD therapeutics and as such merit further investigation.",
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T1 - Integrative analysis of loss-of-function variants in clinical and genomic data reveals novel genes associated with cardiovascular traits

AU - Glicksberg, Benjamin S.

AU - Amadori, Letizia

AU - Akers, Nicholas K.

AU - Sukhavasi, Katyayani

AU - Franzén, Oscar

AU - Li, Li

AU - Belbin, Gillian M.

AU - Akers, Kristin L.

AU - Shameer, Khader

AU - Badgeley, Marcus A.

AU - Johnson, Kipp W.

AU - Readhead, Ben

AU - Darrow, Bruce J.

AU - Kenny, Eimear E.

AU - Betsholtz, Christer

AU - Ermel, Raili

AU - Skogsberg, Josefin

AU - Ruusalepp, Arno

AU - Schadt, Eric E.

AU - Dudley, Joel T.

AU - Ren, Hongxia

AU - Kovacic, Jason C.

AU - Giannarelli, Chiara

AU - Li, Shuyu D.

AU - Björkegren, Johan L.M.

AU - Chen, Rong

PY - 2019/7/25

Y1 - 2019/7/25

N2 - Background: Genetic loss-of-function variants (LoFs) associated with disease traits are increasingly recognized as critical evidence for the selection of therapeutic targets. We integrated the analysis of genetic and clinical data from 10,511 individuals in the Mount Sinai BioMe Biobank to identify genes with loss-of-function variants (LoFs) significantly associated with cardiovascular disease (CVD) traits, and used RNA-sequence data of seven metabolic and vascular tissues isolated from 600 CVD patients in the Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) study for validation. We also carried out in vitro functional studies of several candidate genes, and in vivo studies of one gene. Results: We identified LoFs in 433 genes significantly associated with at least one of 10 major CVD traits. Next, we used RNA-sequence data from the STARNET study to validate 115 of the 433 LoF harboring-genes in that their expression levels were concordantly associated with corresponding CVD traits. Together with the documented hepatic lipid-lowering gene, APOC3, the expression levels of six additional liver LoF-genes were positively associated with levels of plasma lipids in STARNET. Candidate LoF-genes were subjected to gene silencing in HepG2 cells with marked overall effects on cellular LDLR, levels of triglycerides and on secreted APOB100 and PCSK9. In addition, we identified novel LoFs in DGAT2 associated with lower plasma cholesterol and glucose levels in BioMe that were also confirmed in STARNET, and showed a selective DGAT2-inhibitor in C57BL/6 mice not only significantly lowered fasting glucose levels but also affected body weight. Conclusion: In sum, by integrating genetic and electronic medical record data, and leveraging one of the world's largest human RNA-sequence datasets (STARNET), we identified known and novel CVD-trait related genes that may serve as targets for CVD therapeutics and as such merit further investigation.

AB - Background: Genetic loss-of-function variants (LoFs) associated with disease traits are increasingly recognized as critical evidence for the selection of therapeutic targets. We integrated the analysis of genetic and clinical data from 10,511 individuals in the Mount Sinai BioMe Biobank to identify genes with loss-of-function variants (LoFs) significantly associated with cardiovascular disease (CVD) traits, and used RNA-sequence data of seven metabolic and vascular tissues isolated from 600 CVD patients in the Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) study for validation. We also carried out in vitro functional studies of several candidate genes, and in vivo studies of one gene. Results: We identified LoFs in 433 genes significantly associated with at least one of 10 major CVD traits. Next, we used RNA-sequence data from the STARNET study to validate 115 of the 433 LoF harboring-genes in that their expression levels were concordantly associated with corresponding CVD traits. Together with the documented hepatic lipid-lowering gene, APOC3, the expression levels of six additional liver LoF-genes were positively associated with levels of plasma lipids in STARNET. Candidate LoF-genes were subjected to gene silencing in HepG2 cells with marked overall effects on cellular LDLR, levels of triglycerides and on secreted APOB100 and PCSK9. In addition, we identified novel LoFs in DGAT2 associated with lower plasma cholesterol and glucose levels in BioMe that were also confirmed in STARNET, and showed a selective DGAT2-inhibitor in C57BL/6 mice not only significantly lowered fasting glucose levels but also affected body weight. Conclusion: In sum, by integrating genetic and electronic medical record data, and leveraging one of the world's largest human RNA-sequence datasets (STARNET), we identified known and novel CVD-trait related genes that may serve as targets for CVD therapeutics and as such merit further investigation.

KW - Cardiovascular traits

KW - Electronic Medical Records

KW - Genetic association

KW - Integrative data analysis

KW - Loss-of-function variant

KW - Target identification and validation

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