ArticleBMC genomics2018
Stratification of candidate genes for Parkinson's disease using weighted protein-protein interaction network analysis.
Article in BMC genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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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.
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Who cites it
18 citing papers in PubMed, 44 citations in OpenAlex.
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- G-cleave LC3B biosensor: monitoring autophagy and assessing resveratrol's synergistic impact on doxorubicin-induced apoptosis in breast cancer cells.Breast cancer research : BCR · 2024Article
- A genome-wide association study coupled with machine learning approaches to identify influential demographic and genomic factors underlying Parkinson's disease.Frontiers in genetics · 2023Article
- Regulation of mitophagy by the NSL complex underlies genetic risk for Parkinson's disease at 16q11.2 and MAPT H1 loci.Brain : a journal of neurology · 2022Article
- The Protein-Protein Interaction Network of Hereditary Parkinsonism Genes Is a Hierarchical Scale-Free Network.Yonsei medical journal · 2022Article
- Reduced expression of the psychiatric risk gene DLG2 (PSD93) impairs hippocampal synaptic integration and plasticity.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2022Article
- Analyzing host-viral interactome of SARS-CoV-2 for identifying vulnerable host proteins during COVID-19 pathogenesis.Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2021Article
- Alpha-synuclein research: defining strategic moves in the battle against Parkinson's disease.NPJ Parkinson's disease · 2021Review
- An integrated genomic approach to dissect the genetic landscape regulating the cell-to-cell transfer of α-synuclein.Cell reports · 2021Article
- Integrating protein networks and machine learning for disease stratification in the Hereditary Spastic Paraplegias.iScience · 2021Article
- Differences in MTHFR and LRRK2 variant's association with sporadic Parkinson's disease in Mexican Mestizos correlated to Native American ancestry.NPJ Parkinson's disease · 2021Article
- A Systematic Analysis on the Genes and Their Interaction Underlying the Comorbidity of Alzheimer's Disease and Major Depressive Disorder.Frontiers in aging neuroscience · 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
- PINOT: an intuitive resource for integrating protein-protein interactions.Cell communication and signaling : CCS · 2020Article
- Lysosomal Dysfunction at the Centre of Parkinson's Disease and Frontotemporal Dementia/Amyotrophic Lateral Sclerosis.Trends in neurosciences · 2019Review
- Neuropathology and pathogenesis of extrapyramidal movement disorders: a critical update-I. Hypokinetic-rigid movement disorders.Journal of neural transmission (Vienna, Austria : 1996) · 2019Review
- Genetic variation across RNA metabolism and cell death gene networks is implicated in the semantic variant of primary progressive aphasia.Scientific reports · 2019Article
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundGenome wide association studies (GWAS) have helped identify large numbers of genetic loci that significantly associate with increased risk of developing diseases. However, translating genetic knowledge into understanding of the molecular mechanisms underpinning disease (i.e. disease-specific impacted biological processes) has to date proved to be a major challenge. This is primarily due to difficulties in confidently defining candidate genes at GWAS-risk loci. The goal of this study was to better characterize candidate genes within GWAS loci using a protein interactome based approach and with Parkinson's disease (PD) data as a test case.
resultsWe applied a recently developed Weighted Protein-Protein Interaction Network Analysis (WPPINA) pipeline as a means to define impacted biological processes, risk pathways and therein key functional players. We used previously established Mendelian forms of PD to identify seed proteins, and to construct a protein network for genetic Parkinson's and carried out functional enrichment analyses. We isolated PD-specific processes indicating 'mitochondria stressors mediated cell death', 'immune response and signaling', and 'waste disposal' mediated through 'autophagy'. Merging the resulting protein network with data from Parkinson's GWAS we confirmed 10 candidate genes previously selected by pure proximity and were able to nominate 17 novel candidate genes for sporadic PD.
conclusionsWith this study, we were able to better characterize the underlying genetic and functional architecture of idiopathic PD, thus validating WPPINA as a robust pipeline for the in silico genetic and functional dissection of complex disorders.
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