Protein prediction for trait mapping in diverse populations

Genetically regulated gene expression has helped elucidate the biological mechanisms underlying complex traits. Improved high-throughput technology allows similar interrogation of the genetically regulated proteome for understanding complex trait mechanisms. Here, we used the Trans-omics for Precisi...

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Vydáno v:	PloS one Ročník 17; číslo 2; s. e0264341
Hlavní autoři:	Schubert, Ryan, Geoffroy, Elyse, Gregga, Isabelle, Mulford, Ashley J., Aguet, Francois, Ardlie, Kristin, Gerszten, Robert, Clish, Clary, Van Den Berg, David, Taylor, Kent D., Durda, Peter, Johnson, W. Craig, Cornell, Elaine, Guo, Xiuqing, Liu, Yongmei, Tracy, Russell, Conomos, Matthew, Blackwell, Tom, Papanicolaou, George, Lappalainen, Tuuli, Mikhaylova, Anna V., Thornton, Timothy A., Cho, Michael H., Gignoux, Christopher R., Lange, Leslie, Lange, Ethan, Rich, Stephen S., Rotter, Jerome I., Manichaikul, Ani, Im, Hae Kyung, Wheeler, Heather E.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States Public Library of Science 24.02.2022 Public Library of Science (PLoS)
Témata:	Arteriosclerosis Atherosclerosis Atherosclerosis - ethnology Atherosclerosis - genetics Biochemistry Bioinformatics Biology C-reactive protein Chromosome mapping Epidemiology Female Gene expression Gene Frequency Gene mapping Genetic aspects Genetic Association Studies Genetic research Genomes Genomics Health aspects Hispanic Americans Humans Indigenous peoples Interrogation Laboratories Male Medical genetics Methods Minority & ethnic groups Modelling Models, Genetic Native Americans Pediatrics Peptide mapping Pilot Projects Polymorphism, Single Nucleotide Population Population (statistical) Population genetics Population statistics Population studies Precision medicine Prediction models Predictions Proteins Proteins - genetics Proteome - genetics Proteomes Proteomics Public health Quantitative Trait Loci Race Regression analysis Single-nucleotide polymorphism Training United States New York United States > US Chicago Illinois
ISSN:	1932-6203, 1932-6203
On-line přístup:	Získat plný text
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Popis
Shrnutí:	Genetically regulated gene expression has helped elucidate the biological mechanisms underlying complex traits. Improved high-throughput technology allows similar interrogation of the genetically regulated proteome for understanding complex trait mechanisms. Here, we used the Trans-omics for Precision Medicine (TOPMed) Multi-omics pilot study, which comprises data from Multi-Ethnic Study of Atherosclerosis (MESA), to optimize genetic predictors of the plasma proteome for genetically regulated proteome-wide association studies (PWAS) in diverse populations. We built predictive models for protein abundances using data collected in TOPMed MESA, for which we have measured 1,305 proteins by a SOMAscan assay. We compared predictive models built via elastic net regression to models integrating posterior inclusion probabilities estimated by fine-mapping SNPs prior to elastic net. In order to investigate the transferability of predictive models across ancestries, we built protein prediction models in all four of the TOPMed MESA populations, African American (n = 183), Chinese (n = 71), European (n = 416), and Hispanic/Latino (n = 301), as well as in all populations combined. As expected, fine-mapping produced more significant protein prediction models, especially in African ancestries populations, potentially increasing opportunity for discovery. When we tested our TOPMed MESA models in the independent European INTERVAL study, fine-mapping improved cross-ancestries prediction for some proteins. Using GWAS summary statistics from the Population Architecture using Genomics and Epidemiology (PAGE) study, which comprises ∼50,000 Hispanic/Latinos, African Americans, Asians, Native Hawaiians, and Native Americans, we applied S-PrediXcan to perform PWAS for 28 complex traits. The most protein-trait associations were discovered, colocalized, and replicated in large independent GWAS using proteome prediction model training populations with similar ancestries to PAGE. At current training population sample sizes, performance between baseline and fine-mapped protein prediction models in PWAS was similar, highlighting the utility of elastic net. Our predictive models in diverse populations are publicly available for use in proteome mapping methods at https://doi.org/10.5281/zenodo.4837327 .
Bibliografie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Membership list can be found in the S8 Table. Competing Interests: The authors have declared that no competing interests exist.
ISSN:	1932-6203 1932-6203
DOI:	10.1371/journal.pone.0264341