ArticleMolecular medicine reports2016
Deciphering the genetic and modular connections between coronary heart disease, idiopathic pulmonary arterial hypertension and pulmonary heart disease.
Article in Molecular medicine reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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
4 citing papers in PubMed, 8 citations in OpenAlex.
- Baseline triglyceride-glucose, body mass index, end-diastolic internal diameter of the left atria and creatinine are independent predictors for pulmonary hypertension in coronary artery disease patients after percutaneous coronary intervention treatments.Biomarkers in medicine · 2024Article
- Deciphering the Protein, Modular Connections and Precision Medicine for Heart Failure With Preserved Ejection Fraction and Hypertension Based on TMT Quantitative Proteomics and Molecular Docking.Frontiers in physiology · 2021Article
- Deciphering the scalene association among type-2 diabetes mellitus, prostate cancer, and chronic myeloid leukemia via enrichment analysis of disease-gene network.Cancer medicine · 2019Article
- Association between a Single Nucleotide Polymorphism in the 3'-UTR ofDisease markers · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Coronary heart disease (CHD), idiopathic pulmonary arterial hypertension (IPAH) and pulmonary heart disease (PHD) are circulatory system diseases that may simultaneously emerge in a patient and they are often treated together in clinical practice. However, the molecular mechanisms connecting these three diseases remain unclear. In order to determine the multidimensional characteristic correlations between these three diseases based on genomic networks to aid in medical decision-making, genes from the Online Mendelian Inheritance in Man database were obtained, and applied network construction and modularized analysis were conducted. Functional enrichment analysis was conducted to explore the associations between overlapping genes, modules and pathways. A total of 29 overlapping genes and 3 common modules were identifed for the 3 diseases. Glycosphingolipid biosynthesis and the arachidonic acid metabolism are common pathways, and the biosynthetic process is suggested to be the major function involved in the three diseases. The current study reported, to the best of our knowledge for the first time, the role of glycosphingolipid biosynthesis in IPAH and PHD. The present study provided an improved understanding of the pathological mechanisms underlying CHD, IPAH and PHD. The overlapping genes, modules and pathways suggest novel areas for further research, and drug targets. The observations of the current study additionally suggest that drug indications can be broadened because of the presence of common targets.
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.