Genome ResearchGenetic & Genomic MedicinePeer-reviewed journal article
PWAS Hub: Exploring Gene-Based Associations of Common Complex Diseases
Guy KelmaniD, Roei ZuckeriD, Nadav BrandesiD, Michal Linial BiD
Abstract
PWAS (Proteome-Wide Association Study) is an innovative genetic association approach that complements widely-used methods like GWAS (Genome-Wide Association Study). The PWAS platform involves consecutive phases. Initially, machine learning modeling and probabilistic considerations quantified the impact of genetic variants on protein-coding genes biochemical functions. Secondly, aggregating the variants per gene for each individual determines a gene-damaging score. Finally, standard statistical tests are activated in the case-control setting to yield statistically significant genes per phenotype. The PWAS Hub offers a user-friendly interface for an in-depth exploration of gene-disease associations from the UK Biobank (UKB). Results from PWAS cover 99 common diseases and conditions, each with over 10,000 diagnosed individuals per phenotype. Users can explore genes associated with these diseases, with separate analyses conducted for males and females. The PWAS Hub lists statistically significant genes associated with common diseases. It also indicates whether the analyzed damaged gene is associated with an increased or decreased risk. For each phenotype, the analyses account for sex-based genetic effects, inheritance modes (dominant and recessive), and the pleiotropic nature of associated genes. The PWAS Hub showcases its usefulness by navigating through such proteomic-genetic application for asthma. Graphical tools facilitate comparing genetic effects between the results of PWAS and coding GWAS, aiding in understanding the sex-specific genetic impact on common diseases. This adaptable platform is attractive for clinicians, researchers, and individuals interested in delving into gene-disease associations and sex-specific genetic effects. The PWAS Hub is accessible at http://pwas.huji.ac.il.
- organism: human
- assay: GWAS summary statistics
- research focus: database / resource
- approach: statistical model
- Citations
- 4
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- PWAS: Proteome-Wide Association Study
Nadav Brandes, Nathan Linial, Michal Linial B·Genome biologyPeer-reviewed·Jul 14, 2020
- Functionally informed cis and trans proteome-wide association studies prioritize disease-critical genes
Kangcheng Hou, Ali Pazokitoroudi, … Alkes L. Price·medRxiv·Apr 27, 2026
- Co-expression-wide association studies link genetically regulated interactions with complex traits
Mykhaylo M. Malakhov, Wei Pan·Nature CommunicationsPeer-reviewed·Dec 11, 2025
- Recessive and sex-dependent genetic effects in primary hypertension
Roei Zucker, Michal Linial B·medRxiv·May 31, 2022
- Investigation of Autosomal Genetic Sex Differences in Parkinsons disease
Cornelis Blauwendraat, Hirotaka Iwaki, … Andrew Singleton·Annals of NeurologyPeer-reviewed·Apr 26, 2021
- XWAS: a software toolset for genetic data analysis and association studies of the X chromosome
Feng Gao, Diana Chang, … Alon Keinan·Journal of HeredityPeer-reviewed·Aug 12, 2015