ReviewBriefings in bioinformatics2025
The integration of genome-wide and transcriptome-wide association studies in neurodegenerative diseases: opportunities, challenges, and current methodological innovations.
Review in Briefings in bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- A Cross-Tissue Transcriptome Association Study Revealed Novel Susceptibility Genes for Chronic Obstructive Pulmonary Disease.International journal of chronic obstructive pulmonary disease · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Neurodegenerative diseases (NDs) such as Alzheimer's and Parkinson's disease are characterized by complex genetic and regulatory landscapes. Genome-wide association studies (GWAS) and transcriptome-wide association studies (TWAS) have become two essential and complementary methods for investigating the genetic basis of these disorders. GWAS systematically identifies genetic variants associated with disease risk, while TWAS provides functional insight by integrating expression quantitative trait loci to infer the effects of genetically regulated gene expression on complex traits. The aim of this review was to provide a comprehensive overview of methodological developments and integrative applications of GWAS and TWAS in the context of NDs research. We first conducted a bibliometric analysis that delineates evolving research trends and identifies emerging focal areas in the field. We then compared the underlying assumptions, strengths, and analytical frameworks of GWAS and TWAS. Subsequently, we highlighted recent advances in TWAS methodology, including fine-mapping strategies, multi-tissue and single-cell modeling, integration of multi-omic data layers, and applications of machine learning and artificial intelligence. Finally, current challenges related to ancestry representation, reference panel diversity, and translational generalizability were also presented. By synthesizing these perspectives, this review clarified the methodological landscape, guided future integrative analyses, and supported the broader application of transcriptome-informed genetic approaches in understanding and treating NDs.
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.