ArticlemedRxiv : the preprint server for health sciences2025
Polygenic associations with clinical and neuropathological trait heterogeneity across TDP-43 proteinopathies.
Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
- Updated by
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: TDP-43 proteinopathies, including amyotrophic lateral sclerosis (ALS), frontotemporal lobar degeneration with TDP-43 (FTLD-TDP), and limbic-predominant age-related TDP-43 encephalopathy, encompass a spectrum of clinical and neuropathological traits. Despite mounting evidence for shared genetic risk across TDP-43 proteinopathies, the modifiers of individual-level traits are unknown. We aimed to identify polygenic contributions to trait heterogeneity across TDP-43 proteinopathies. Methods: We used weighted correlation analysis of GWAS summary statistics for ALS, FTLD-TDP, and hippocampal sclerosis of aging (HS-Aging) to identify data-driven clusters of highly correlated single nucleotide polymorphisms (SNPs). We performed gene ontology enrichment analysis for each identified cluster. We derived cluster-specific polygenic scores and evaluated their association with clinical and neuropathological traits in an independently evaluated sample of individuals who met neuropathological and/or genetic criteria for FTLD-TDP or ALS (n=260). Results: We identified 5 distinct data-driven clusters, including 3 GWAS phenotype-specific clusters (FTLD-TDP, ALS, HS-Aging) and 2 clusters representing the overlap between a pair of GWAS phenotypes (ALS-FTLD and FTLD-HS). Pathway analysis revealed biologically meaningful associations including distinct GWAS phenotype-specific processes within clusters. Cluster-specific ALS and FTLD-TDP polygenic risk each associated with individual-level clinical traits, even within the context of autosomal dominant mutation carriers, where higher ALS polygenic risk associated with neuromuscular impairment and higher FTLD-TDP polygenic risk associated with cognitive-behavioral impairment. Moreover, higher FTLD-TDP polygenic risk associated with higher TDP-43 burden within characteristic FTLD-TDP brain regions. Interpretation: We suggest that there are polygenic modifiers of clinical and neuropathological traits across TDP-43 proteinopathies that may contribute to individual-level differences, including likelihood for developing FTLD or ALS.
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.