Multi-INTACT: integrative analysis of the genome, transcriptome, and proteome identifies causal mechanisms of complex traits

We present multi-integration of transcriptome-wide association studies and colocalization (Multi-INTACT), an algorithm that models multiple "gene products" (e.g., encoded RNA transcript and protein levels) to implicate causal genes and relevant gene products. In simulations, Multi-INTACT achieves higher power than existing methods, maintains calibrated false discovery rates, and detects the true causal gene product(s). We apply Multi-INTACT to GWAS on 1408 metabolites, integrating the GTEx expression and UK Biobank protein QTL datasets. Multi-INTACT infers 52 to 109% more metabolite causal genes than protein-alone or expression-alone analyses and indicates both gene products are relevant for most gene nominations.

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Publication Details

Journal
Genome biology
Published
2025-02-03
DOI
https://doi.org/10.1186/s13059-025-03480-2
Citations
8
Primary Topic
Bioinformatics and Genomic Networks
Type
article
Field-Weighted Citation Impact
6.45

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Multi-INTACT: integrative analysis of the genome, transcriptome, and proteome identifies causal mechanisms of complex traits

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8 citations
Genome biology
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Multi-INTACT: integrative analysis of the genome, transcriptome, and proteome identifies causal mechanisms of complex traits

Michael Boehnke, Joshua Chiou, Roger Piqué-Regi, Francesca Luca, Hae Kyung Im, Charles Burant, Jean Morrison, Jeffrey Okamoto, Brady Ryan, Xiaoquan Wen, Eric B. Fauman, Xianyong Yin, Markku Laakso
article en
8 citations

Abstract

We present multi-integration of transcriptome-wide association studies and colocalization (Multi-INTACT), an algorithm that models multiple "gene products" (e.g., encoded RNA transcript and protein levels) to implicate causal genes and relevant gene products. In simulations, Multi-INTACT achieves higher power than existing methods, maintains calibrated false discovery rates, and detects the true causal gene product(s). We apply Multi-INTACT to GWAS on 1408 metabolites, integrating the GTEx expression and UK Biobank protein QTL datasets. Multi-INTACT infers 52 to 109% more metabolite causal genes than protein-alone or expression-alone analyses and indicates both gene products are relevant for most gene nominations.

Genome biologyVol. 26(1)
University of Eastern Finland (FI), Pfizer (United States) (US), Wayne State University (US), University of Michigan (US), University of Chicago (US), Kuopio University Hospital (FI), Statistical Service (CY), Nanjing Medical University (CN)
National Institutes of Health
Openalex Percentile: Top 3%
Bioinformatics and Genomic Networks
6.45
DOIOpen Access PDFOpenAlex
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