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Chen HH, Petty LE, Bush W, et al. GWAS and Beyond: Using Omics Approaches to Interpret SNP Associations. Curr Genet Med Rep. 2019;7(1):30-40doi: 10.1007/s40142-019-0159-z.
Chen, H. H., Petty, L. E., Bush, W., Naj, A. C., & Below, J. E. (2019). GWAS and Beyond: Using Omics Approaches to Interpret SNP Associations. Current genetic medicine reports, 7(1), 30-40. https://doi.org/10.1007/s40142-019-0159-z
Chen, Hung-Hsin, et al. "GWAS and Beyond: Using Omics Approaches to Interpret SNP Associations." Current genetic medicine reports vol. 7,1 (2019): 30-40. doi: https://doi.org/10.1007/s40142-019-0159-z
Chen HH, Petty LE, Bush W, Naj AC, Below JE. GWAS and Beyond: Using Omics Approaches to Interpret SNP Associations. Curr Genet Med Rep. 2019 Mar;7(1):30-40. doi: 10.1007/s40142-019-0159-z. Epub 2019 Feb 14. PMID: 33312764; PMCID: PMC7731888.
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Curr Genet Med Rep. 2019 Mar;7(1):30-40. doi: 10.1007/s40142-019-0159-z. Epub 2019 Feb 14.

GWAS and Beyond: Using Omics Approaches to Interpret SNP Associations.

Current genetic medicine reports

Hung-Hsin Chen, Lauren E Petty, William Bush, Adam C Naj, Jennifer E Below

Affiliations

  1. Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA.
  2. Institute for Computational Biology, Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA.
  3. Department of Biostatistics, Epidemiology, and Informatics; Department of Pathology and Laboratory Medicine; Center for Clinical Epidemiology and Biostatistics; Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.

PMID: 33312764 PMCID: PMC7731888 DOI: 10.1007/s40142-019-0159-z

Abstract

PURPOSE OF REVIEW: Neurodegenerative diseases, neuropsychiatric disorders, and related traits have highly complex etiologies but are also highly heritable and identifying the causal genes and biological pathways underlying these traits may advance the development of treatments and preventive strategies. While many genome-wide association studies (GWAS) have successfully identified variants contributing to polygenic neurodegenerative and neuropsychiatric phenotypes including Alzheimer's disease (AD), schizophrenia (SCZ), and bipolar disorder (BPD) amongst others, interpreting the biological roles of significantly-associated variants in the genetic architecture of these traits remains a significant challenge. Here we review several 'omics' approaches which attempt to bridge the gap from associated genetic variants to phenotype by helping define the functional roles of GWAS loci in the development of neuropsychiatric disorders and traits.

RECENT FINDINGS: Several common 'omics' approaches have been applied to examine neuropsychiatric traits, such as nearest-gene mapping, trans-ethnic fine mapping, annotation enrichment analysis, transcriptomic analysis, and pathway analysis, and each of these approaches has strengths and limitations in providing insight into biological mechanisms. One popular emerging method is the examination of tissue-specific genetically-regulated gene expression (GReX), which aggregates the genetic variants' effects at the gene-level. Furthermore, proteomic, metabolomic, and microbiomic studies and phenome-wide association studies will further enhance our understanding of neuropsychiatric traits.

SUMMARY: GWAS has been applied to neuropsychiatric traits for a decade, but our understanding about the biological function of identified variants remains limited. Today, technological advancements have created analytical approaches for integrating transcriptomics, metabolomics, proteomics, pharmacology and toxicology as tools for understanding the functional roles of genetics variants. These data, as well as the broader clinical information provided by electronic health records, can provide additional insight and complement genomic analyses.

Keywords: Functional Annotation; Functional Interpretation; Genetically Regulated Expression; Genome-Wide Association Studies; Omics

Conflict of interest statement

Conflict of Interest Hung-Hsin Chen, Lauren E. Petty, Adam C. Naj, and Jennifer E. Below each declare no potential conflicts of interest.

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