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Combining xQTL and Genome-Wide Association Studies from Ethnically Diverse Populations Improves Druggable Gene Discovery

68 Pages Posted: 3 Jan 2025 Publication Status: Review Complete

See all articles by Noah Lorincz-Comi

Noah Lorincz-Comi

Cleveland Clinic

Wenqiang Song

Cleveland Clinic

Xin Chen

Cleveland Clinic

Isabela Rivera Paz

Cleveland Clinic

Yuan Hou

Cleveland Clinic

Yadi Zhou

Cleveland Clinic - Genomic Medicine Institute

Jielin Xu

Cleveland Clinic

William Martin

Cleveland Clinic

John Barnard

Cleveland Clinic

Andrew A. Pieper

Case Western Reserve University

Jonathan L. Haines

Case Western Reserve University

Mina Chung

Cleveland Clinic - Department of Cardiovascular and Metabolic Sciences; Case Western Reserve University - Cleveland Clinic Foundation and the Lerner College of Medicine

Feixiong Cheng

Cleveland Clinic - Genomic Medicine Institute; Cleveland Clinic, Lerner College of Medicine, Department of Molecular Medicine; Case Western Reserve University, School of Medicine, Case Comprehensive Cancer Center

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Abstract

Repurposing existing medicines to target disease-associated genes represents a promising strategy for developing new treatments for complex diseases. However, progress has been hindered by a lack of viable candidate drug targets identified through genome-wide association studies (GWAS). Gene-based association tests provide a more powerful alternative to traditional single nucleotide polymorphism (SNP)-based methods, yet current approaches often fail to leverage shared heritability across populations and to effectively integrate functional genomic data. To address these challenges, we developed GenT and its various extensions, comprising a framework of gene-based tests utilizing summary-level GWAS data. Using GenT, we identified 16, 15, 35, and 83 druggable genes linked to Alzheimer’s disease (AD), amyotrophic lateral sclerosis, major depression, and schizophrenia, respectively. Additionally, our multi-ancestry gene-based test (MuGenT) uncovered 28 druggable genes associated with type 2 diabetes that previous trans-ancestry or ancestry-specific GWAS had missed. By integrating brain expression and protein quantitative trait loci (e/pQTLs) into our analysis, we identified 43 druggable and potentially causal genes (e.g., RIPK2, NTRK1, RIOK1) associated with AD. Notably, experimental assays demonstrated that the NTRK1 protein inhibitor GW441756 significantly reduced tau hyper-phosphorylation (including p-tau181 and p-tau217) in AD patient-derived iPSC neurons, thus providing mechanistic support for our predictions. Overall, our findings underscore the power of gene-based association testing as a strategic tool for informed drug target discovery and validation based on human genetic and genomic data for complex diseases.

Note:
Funding Information: This work was primarily supported by the National Institute on Aging (NIA) under Award Number R01AG084250, U01AG073323, R01AG066707, R01AG076448, R01AG082118, RF1AG082211, R56AG074001, and R21AG083003, and the National Institute of Neurological Disorders and Stroke (NINDS) under Award Number RF1NS133812 to F.C. This work was partly supported by the Alzheimer's Association award (ALZDISCOVERY-1051936) and the funds from the Alzheimer's Drug Discovery Foundation to F.C. This work was supported in part by the Rebecca E. Barchas, MD, Professorship in Translational Psychiatry, the Valour Foundation, Project 19PABH134580006-AHA/Allen Initiative in Brain Health and Cognitive Impairment, the Elizabeth Ring Mather & William Gwinn Mather Fund, S. Livingston Samuel Mather Trust, and the Louis Stokes VA Medical Center resources and facilities to A.A.P.

Declaration of Interests: The authors declare no competing interests.

Keywords: Druggable gene, genome-wide association studies (GWAS), gene-based testing, neurodegenerative disease, and expression quantitative trait loci (eQTL)

Suggested Citation

Lorincz-Comi, Noah and Song, Wenqiang and Chen, Xin and Rivera Paz, Isabela and Hou, Yuan and Zhou, Yadi and Xu, Jielin and Martin, William and Barnard, John and Pieper, Andrew A. and Haines, Jonathan L. and Chung, Mina and Cheng, Feixiong and Administrator, Sneak Peek, Combining xQTL and Genome-Wide Association Studies from Ethnically Diverse Populations Improves Druggable Gene Discovery. Available at SSRN: https://ssrn.com/abstract=5080346 or http://dx.doi.org/10.2139/ssrn.5080346
This version of the paper has not been formally peer reviewed.

Noah Lorincz-Comi

Cleveland Clinic ( email )

Wenqiang Song

Cleveland Clinic ( email )

Xin Chen

Cleveland Clinic ( email )

Isabela Rivera Paz

Cleveland Clinic ( email )

Yuan Hou

Cleveland Clinic ( email )

9500 Euclid Ave.
Cleveland, OH 44195
United States

Yadi Zhou

Cleveland Clinic - Genomic Medicine Institute ( email )

Cleveland, OH 44106
United States

Jielin Xu

Cleveland Clinic ( email )

9500 Euclid Ave.
Cleveland, OH 44195
United States

William Martin

Cleveland Clinic ( email )

9500 Euclid Ave.
Cleveland, OH 44195
United States

John Barnard

Cleveland Clinic ( email )

Andrew A. Pieper

Case Western Reserve University ( email )

10900 Euclid Ave.
Cleveland, OH 44106
United States

Jonathan L. Haines

Case Western Reserve University ( email )

10900 Euclid Ave.
Cleveland, OH 44106
United States

Mina Chung

Cleveland Clinic - Department of Cardiovascular and Metabolic Sciences ( email )

United States

Case Western Reserve University - Cleveland Clinic Foundation and the Lerner College of Medicine

9980 Carnegie Ave
Cleveland, OH 44195
United States

Feixiong Cheng (Contact Author)

Cleveland Clinic - Genomic Medicine Institute ( email )

Cleveland, OH 44106
United States

Cleveland Clinic, Lerner College of Medicine, Department of Molecular Medicine ( email )

9500 Euclid Avenue
Cleveland, OH 44195
United States

Case Western Reserve University, School of Medicine, Case Comprehensive Cancer Center ( email )

2511 Overlook Road
Cleveland Heights, OH 44195
United States

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