SynthesisAmerican journal of human genetics2013
Network-based multiple sclerosis pathway analysis with GWAS data from 15,000 cases and 30,000 controls.
Synthesis in American journal of human genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 90 papers, 4 of them syntheses that pooled it.
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
90 citing papers in PubMed, 4 syntheses or guidelines pooled it, 163 citations in OpenAlex.
- A systems biology approach uncovers cell-specific gene regulatory effects of genetic associations in multiple sclerosis.Nature communications · 2019Pooled it
- Meta-analysis of genome-wide association studies reveals genetic overlap between Hodgkin lymphoma and multiple sclerosis.International journal of epidemiology · 2016Pooled it
- Pooled it
- Pathway-based analysis of GWAs data identifies association of sex determination genes with susceptibility to testicular germ cell tumors.Human molecular genetics · 2014Pooled it
- Multimodal Integration of Protein Interactomes With Genomic and Molecular Data Discovers Distinct Rheumatoid Arthritis Endotypes.Arthritis & rheumatology (Hoboken, N.J.) · 2026Article
- In vivo mapping of protein-protein interactions of schizophrenia risk factors generates an interconnected disease network.Schizophrenia (Heidelberg, Germany) · 2026Article
- Article
- Exploring the role of EBV in multiple sclerosis pathogenesis through EBV interactome.Frontiers in immunology · 2025Article
- Multiscale networks in multiple sclerosis.PLoS computational biology · 2024Article
- Association between glioma and neurodegenerative diseases risk: a two-sample bi-directional Mendelian randomization analysis.Frontiers in neurology · 2024Article
- Twenty-Five Years of AI in Neurology: The Journey of Predictive Medicine and Biological Breakthroughs.JMIR neurotechnology · 2024Article
- Review
- Subtypes of relapsing-remitting multiple sclerosis identified by network analysis.Frontiers in digital health · 2022Article
- Article
- An integrative study of genetic variants with brain tissue expression identifies viral etiology and potential drug targets of multiple sclerosis.Molecular and cellular neurosciences · 2021Article
- Obesity and the risk of Multiple Sclerosis. The role of Leptin.Annals of clinical and translational neurology · 2021Article
- Genome-Wide Association Identifies Risk Pathways for SAPHO Syndrome.Frontiers in cell and developmental biology · 2021Article
- Genomic, proteomic, and systems biology approaches in biomarker discovery for multiple sclerosis.Cellular immunology · 2020Review
- Vitamin D genes influence MS relapses in children.Multiple sclerosis (Houndmills, Basingstoke, England) · 2020Article
- Fyn Tyrosine Kinase as Harmonizing Factor in Neuronal Functions and Dysfunctions.International journal of molecular sciences · 2020Review
30 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
Abstract
Multiple sclerosis (MS) is an inflammatory CNS disease with a substantial genetic component, originally mapped to only the human leukocyte antigen (HLA) region. In the last 5 years, a total of seven genome-wide association studies and one meta-analysis successfully identified 57 non-HLA susceptibility loci. Here, we merged nominal statistical evidence of association and physical evidence of interaction to conduct a protein-interaction-network-based pathway analysis (PINBPA) on two large genetic MS studies comprising a total of 15,317 cases and 29,529 controls. The distribution of nominally significant loci at the gene level matched the patterns of extended linkage disequilibrium in regions of interest. We found that products of genome-wide significantly associated genes are more likely to interact physically and belong to the same or related pathways. We next searched for subnetworks (modules) of genes (and their encoded proteins) enriched with nominally associated loci within each study and identified those modules in common between the two studies. We demonstrate that these modules are more likely to contain genes with bona fide susceptibility variants and, in addition, identify several high-confidence candidates (including BCL10, CD48, REL, TRAF3, and TEC). PINBPA is a powerful approach to gaining further insights into the biology of associated genes and to prioritizing candidates for subsequent genetic studies of complex traits.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.