Aim: Bipolar disorder is a multifactorial psychiatric condition characterized by mood dysregulation. Although its heritability is established, the underlying genetic mechanism still remains incomplete. Herein, the aim of this study was to integrate genome-wide association study data with functional analyses in order to nominate key genetic loci, and pathways and regulatory mechanisms involved in bipolar disorder.
Methodology: Public datasets for GWAS-identified bipolar disorder variants were downloaded and subjected to functional enrichment, protein-protein interaction mapping, and miRNA target prediction. The analyses focused on GO, Reactome, and KEGG pathway enrichment, as well as metabolomic and transcription factor analyses, to assess molecular dysregulation in bipolar disorder.
Results: Mitochondrial function, PALB2, RHOU; immune response, HLA-B, DPY19L3; synaptic signaling, KCNU1, DPP10; and metabolic processes. PPI analysis highlighted hub proteins such as PTK2 and PAK1, which might be regulatory proteins, while miRNA analysis revealed hsa-miR-126-3p and hsa-miR-452-5p as post-transcriptional regulators. Metabolomic assessment showed perturbations in GTP-binding proteins and magnesium homeostasis.
Interpretation: This integrative analysis enhances knowledge on the genetic and molecular architecture of bipolar disorder, reinforcing its polygenic nature and implicating mitochondrial dysfunction, immune dysregulation, and neurotransmitter imbalances. The identified pathways provide potential targets for therapeutic intervention, emphasizing the role of precision medicine in the management of bipolar disorder.
Key words: Bipolar disorder, GWAS, Bioinformatics, Genetic loci, Molecular mechanisms
J. Timmapuram, G. Baby Shalini, T. Poojasree et al.· Journal of environmental bio...· 0 citations
Aim: Coronary heart disease (CHD) is a leading cause of mortality worldwide, with a complex interplay of genetic and environmental factors influencing its development. Genome-wide association studies (GWAS) have identified multiple genetic loci associated with CHD, providing crucial insights into its pathophysiology. However, the full spectrum of genetic contributors and their biological mechanisms remains to be elucidated.
Methodology: This study integrates GWAS data with various ontology analyses to identify key genetic determinants of CHD. Variants associated with CHD were retrieved from public datasets and analysed using bioinformatics tools to explore their biological significance. Pathway enrichment, protein-protein interaction (PPI) networks, and clustering algorithms delineated functional relationships among candidate genes. Additionally, microRNA (miRNA) interactions were assessed to understand post-transcriptional regulatory mechanisms.
Results: These findings revealed novel insights into CHD genetics, confirming known loci such as 9p21.3 (CDKN2B-AS1), COL4A2 and PHACTR1, while uncovering their broader functional roles in vascular remodelling, inflammation, and lipid metabolism. Enrichment and miRNA analyses highlighted new regulatory layers involving TGF-beta and AGE-RAGE pathways, and miRNAs like hsa-miR-147b and hsa-miR-4790-5p, suggesting previously unrecognized mechanisms in CHD pathogenesis.
Interpretation: This study contributes to understanding CHD genetics by integrating multi-omic data to highlight relevant genetic factors and associated biological pathways.
Key words: Coronary heart disease, Functional enrichment analysis, Genome-wide association studies, Genetic risk factors, Precision medicine
T. Amulya, S. Vadlamudi, K. Farzia et al.· Journal of environmental bio...· 0 citations