ReviewGenomics, proteomics & bioinformatics2024
Multiome-wide Association Studies: Novel Approaches for Understanding Diseases.
Review in Genomics, proteomics & bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Integrated Elementomics-Genomics-Metabolomics Analysis Reveals Plasma Biomarker Networks and Diagnostic Potential for Gastric Cancer.Metabolites · 2026Article
- Novel Susceptibility Genes for Sepsis Revealed by a Cross-Tissue Transcriptome-Wide Association Study.Shock (Augusta, Ga.) · 2026Article
- Molecular systems, human noncoding sequence variants, and blood pressure.Physiological reviews · 2026Review
- Enhancer-based gene therapy: a new path for precision medicine.Hereditas · 2026Review
- GENEasso: a curated resource of credible disease-gene associations across complex diseases from GWAS summary statistics.Nucleic acids research · 2026Article
- EWAS Open Platform 2026: a deeply integrated resource for epigenome-wide association studies.Nucleic acids research · 2026Article
- An Integrative Genetic Strategy for Identifying Causal Genes at Quantitative Trait Loci in Chickens.Animals : an open access journal from MDPI · 2026Review
- Integrative Multi-Omics Analysis Unveils Candidate Genes and Functional Variants for Growth and Reproductive Traits in Duroc Pigs.Animals : an open access journal from MDPI · 2025Article
- Exploring the Cellular and Molecular Landscape of Idiopathic Pulmonary Fibrosis: Integrative Multi-Omics and Single-Cell Analysis.Biomedicines · 2025Article
- Integrating plasma circulating protein-centered multi-omics to identify potential therapeutic targets for Parkinsonian cognitive disorders.Journal of translational medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The rapid development of multiome (transcriptome, proteome, cistrome, imaging, and regulome)-wide association study methods have opened new avenues for biologists to understand the susceptibility genes underlying complex diseases. Thorough comparisons of these methods are essential for selecting the most appropriate tool for a given research objective. This review provides a detailed categorization and summary of the statistical models, use cases, and advantages of recent multiome-wide association studies. In addition, to illustrate gene-disease association studies based on transcriptome-wide association study (TWAS), we collected 478 disease entries across 22 categories from 235 manually reviewed publications. Our analysis reveals that mental disorders are the most frequently studied diseases by TWAS, indicating its potential to deepen our understanding of the genetic architecture of complex diseases. In summary, this review underscores the importance of multiome-wide association studies in elucidating complex diseases and highlights the significance of selecting the appropriate method for each study.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.