ArticleProcedia computer science2017
A new approach to disentangle genetic and epigenetic components on disease comorbidities: studying correlation between genotypic and phenotypic disease networks.
Article in Procedia computer science, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
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Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Shared Genetic Architectures Between Lung Cancer and Multiple Polygenic Phenotypes in Genome-Wide Association Studies.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2021Pooled it
- Shared genetic architecture of non-viral cirrhosis with several pleiotropic traits: A nested case-control study in the UK Biobank.Liver international communications · 2024Article
- The shared genetic architecture between epidemiological and behavioral traits with lung cancer.Scientific reports · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Disease comorbidity is a result of complex epigenetic interplay. A disease is rarely a consequence of an abnormality in a single gene; complex pathways to disease patterns emerge from gene-gene interactions and gene-environment interactions. Understanding these mechanisms of disease and comorbidity development, breaking down them into clusters and disentangling the epigenetic - actionable - components, is of utter importance from a public health perspective. With the increase in the average life expectancy, healthy aging becomes a primary objective, from both an individual (i.e. quality of life) and a societal (i.e. healthcare costs) standpoint. Many studies have analyzed disease networks based on common altered genes, on protein-protein interactions, or on shared disease comorbidites, i.e. phenotypic disease networks. In this work we aim at studying the relations between genotypic and phenotypic disease networks, using a large statewide cohort of individuals (100, 000+ from California, USA) with linked clinical and genotypic information, the Genetic Epidemiology Research on Adult Health and Aging (GERA). By comparing their phenotypic and genotypic networks, we try to disentangle the epigenetic component of disease comorbidity.
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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.