ArticleScientific reports2019
Genetic variation across RNA metabolism and cell death gene networks is implicated in the semantic variant of primary progressive aphasia.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 16 citations in OpenAlex.
- The Genetics of TDP-43 Type C Neurodegeneration: A Whole-Genome Sequencing Study and Literature Review.Neurology. Genetics · 2026Article
- Analysis of the splicing landscape of the frontal cortex in FTLD-TDP reveals subtype specific patterns and cryptic splicing.Acta neuropathologica · 2025Article
- Deciphering distinct genetic risk factors for FTLD-TDP pathological subtypes via whole-genome sequencing.Nature communications · 2025Article
- Frontotemporal Degeneration with Transactive Response DNA-Binding Protein Type C at the Anterior Temporal Lobe.Annals of neurology · 2023Review
- Temporopolar regions of the human brain.Brain : a journal of neurology · 2023Article
- Neuroinflammation is highest in areas of disease progression in semantic dementia.Brain : a journal of neurology · 2021Article
- Integrating protein networks and machine learning for disease stratification in the Hereditary Spastic Paraplegias.iScience · 2021Article
- Mendelian and Sporadic FTD: Disease Risk and Avenues from Genetics to Disease Pathways Through In Silico Modelling.Advances in experimental medicine and biology · 2021Article
- The Right Temporal Variant of Frontotemporal Dementia Is Not Genetically Sporadic: A Case Series.Journal of Alzheimer's disease : JAD · 2021Article
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Authors and funding
20 authors at 20 institutions in 13 countries.
Funding
Abstract
The semantic variant of primary progressive aphasia (svPPA) is a clinical syndrome characterized by neurodegeneration and progressive loss of semantic knowledge. Unlike many other forms of frontotemporal lobar degeneration (FTLD), svPPA has a highly consistent underlying pathology composed of TDP-43 (a regulator of RNA and DNA transcription metabolism). Previous genetic studies of svPPA are limited by small sample sizes and a paucity of common risk variants. Despite this, svPPA's relatively homogenous clinicopathologic phenotype makes it an ideal investigative model to examine genetic processes that may drive neurodegenerative disease. In this study, we used GWAS metadata, tissue samples from pathologically confirmed frontotemporal lobar degeneration, and in silico techniques to identify and characterize protein interaction networks associated with svPPA risk. We identified 64 svPPA risk genes that interact at the protein level. The protein pathways represented in this svPPA gene network are critical regulators of RNA metabolism and cell death, such as SMAD proteins and NOTCH1. Many of the genes in this network are involved in TDP-43 metabolism. Contrary to the conventional notion that svPPA is a clinical syndrome with few genetic risk factors, our analyses show that svPPA risk is complex and polygenic in nature. Risk for svPPA is likely driven by multiple common variants in genes interacting with TDP-43, along with cell death,x` working in combination to promote neurodegeneration.
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