PWAS: proteome-wide association study—linking genes and phenotypes by functional variation in proteins

Brandes, Nadav; Linial, Michal; Linial, Michal

doi:10.1186/s13059-020-02089-x

Cited by 75 publications

(99 citation statements)

References 62 publications

(75 reference statements)

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“…Recently, we developed Proteome-Wide Association Study (PWAS) 33 , a new gene-based method that addresses many of the shortcomings of GWAS. PWAS detects gene-phenotype associations that are mediated by alterations to protein function (Fig.…”

Section: Introductionmentioning

confidence: 99%

Genetic association studies of alterations in protein function expose recessive effects on cancer predisposition

Brandes

Linial

2021

Sci Rep

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The characterization of germline genetic variation affecting cancer risk, known as cancer predisposition, is fundamental to preventive and personalized medicine. Studies of genetic cancer predisposition typically identify significant genomic regions based on family-based cohorts or genome-wide association studies (GWAS). However, the results of such studies rarely provide biological insight or functional interpretation. In this study, we conducted a comprehensive analysis of cancer predisposition in the UK Biobank cohort using a new gene-based method for detecting protein-coding genes that are functionally interpretable. Specifically, we conducted proteome-wide association studies (PWAS) to identify genetic associations mediated by alterations to protein function. With PWAS, we identified 110 significant gene-cancer associations in 70 unique genomic regions across nine cancer types and pan-cancer. In 48 of the 110 PWAS associations (44%), estimated gene damage is associated with reduced rather than elevated cancer risk, suggesting a protective effect. Together with standard GWAS, we implicated 145 unique genomic loci with cancer risk. While most of these genomic regions are supported by external evidence, our results also highlight many novel loci. Based on the capacity of PWAS to detect non-additive genetic effects, we found that 46% of the PWAS-significant cancer regions exhibited exclusive recessive inheritance. These results highlight the importance of recessive genetic effects, without relying on familial studies. Finally, we show that many of the detected genes exert substantial cancer risk in the studied cohort determined by a quantitative functional description, suggesting their relevance for diagnosis and genetic consulting.

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Section: Introductionmentioning

confidence: 99%

Genetic association studies of alterations in protein function expose recessive effects on cancer predisposition

Brandes

Linial

2021

Sci Rep

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“…In this analysis we relied solely on genotyping of ~800K predefined genetic markers and ~600K variants in coding regions imputed from the original set of markers [32]. This limitation is particularly relevant for PWAS, which underestimates genetic damage when non-genotyped variants are involved, leading to diminished statistical power (but, critically, not to false discoveries) [29].…”

Section: Discussionmentioning

confidence: 99%

“…We used the PWAS software [29] (version 1.0.4; available at https://github.com/nadavbra/pwas) and executed the standard PWAS pipeline (specified in the GitHub page). We derived the dominant and recessive PWAS effect scores for the entire UKB cohort (which depend solely on the genetic information) and tested associations between 18,053 protein-coding genes and the ten cancer phenotypes.…”

Section: Pwasmentioning

confidence: 99%

Recessive effects in cancer predisposition exposed by genome-wide and proteome-wide association studies

Brandes

Linial

2020

Preprint

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The characterization of germline genetic variation affecting cancer risk, known as cancer predisposition, is fundamental to preventive and personalized medicine. Current attempts to detect cancer predisposition genomic regions are typically based on small-scale familial studies or genome-wide association studies (GWAS) over dedicated case-control cohorts. In this study, we utilized the UK Biobank as a large-scale prospective cohort to conduct a comprehensive analysis of cancer predisposition using both GWAS and proteome-wide association study (PWAS), a method that highlights genetic associations mediated by functional alterations to protein-coding genes. We discovered 137 unique genomic loci implicated with cancer risk in the white British population across nine cancer types and pan-cancer. While most of these genomic regions are supported by external evidence, our results highlight novel loci as well. We performed a comparative analysis of cancer predisposition between cancer types, finding that most of the implicated regions are cancer-type specific. We further analyzed the role of recessive genetic effects in cancer predisposition. We found that 30 of the 137 cancer regions were recovered only by a recessive model, highlighting the importance of recessive inheritance outside of familial studies. Finally, we show that many of the cancer associations exert substantial cancer risk in the studied cohort, suggesting their clinical relevance.

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“…More recently, the state-of-the-art PWAS, which aggregates the signal of all variants jointly impacting on a protein-coding gene and evaluates their overall effects on the protein's function using mathematical models, has entered the stage. It could assess whether the gene exhibits functional variability between individuals that correlates with the phenotype of interest, including tumors [3]. We could anticipate more of these central dogma-based omics strategies to help us better understand cancer.…”

Section: The Central Dogma-based Profilingmentioning

confidence: 99%

Multiomics kaleidoscope to visualize cancer hallmarks

Zhou

2020

Genome Biol

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PWAS: proteome-wide association study—linking genes and phenotypes by functional variation in proteins

Cited by 75 publications

References 62 publications

Genetic association studies of alterations in protein function expose recessive effects on cancer predisposition

Genetic association studies of alterations in protein function expose recessive effects on cancer predisposition

Recessive effects in cancer predisposition exposed by genome-wide and proteome-wide association studies

Multiomics kaleidoscope to visualize cancer hallmarks

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