Bioinformatics Approach to Identify Significant Biomarkers, Drug Targets Shared Between Parkinson's Disease and Bipolar Disorder: A Pilot Study.
Md Bipul HossainMd Kobirul IslamApurba AdhikaryAbidur RahamanMd Zahidul IslamPublished in: Bioinformatics and biology insights (2022)
Parkinson's disease (PD) is a neurodegenerative disorder responsible for shaking, rigidity, and trouble in walking and patients' coordination ability and physical stability deteriorate day by day. Bipolar disorder (BD) is a psychiatric disorder which is the reason behind extreme shiftiness in mood, and frequent mood inversion may reach too high called mania. People with BD have a greater chance of developing PD during the follow-up period. A lot of work has been done to understand the key factors for developing these 2 diseases. But the molecular functionalities that trigger the development of PD in people with BD are not clear yet. In our study, we are intended to identify the molecular biomarkers and pathways shared between BD and PD. We have investigated the RNA-Seq gene expression data sets of PD and BD. A total of 45 common unique genes (32 up-regulated and 13 down-regulated) abnormally expressed in both PD and BD were identified by applying statistical methods on the GEO data sets. Gene ontology (GO) and BioCarta, KEGG, and Reactome pathways analysis of these 45 common dysregulated genes identified numerous altered molecular pathways such as mineral absorption, Epstein-Barr virus infection, HTLV-I infection, antigen processing, and presentation. Analysis of protein-protein interactions revealed 9 significant hub-proteins, namely RPL21, RPL34, CKS2, B2M, TNFRSF10A, DTX2, HLA-B, ATP2A3, and TAPBP. Significant transcription factors (IRF8, SPI1, RUNX1, and FOXA1) and posttranscriptional regulator microRNAs (hsa-miR-491-3p and hsa-miR-1246) are also found by analyzing gene-transcription factors and gene-miRNAs interactions, respectively. Protein-drug interaction analysis revealed hub-protein B2M's interaction with molecular drug candidates like N -formylmethionine, 3-indolebutyric acid, and doxycycline. Finally, a link between pathological processes of PD and BD is identified at transcriptional level. This study may help us to predict the development of PD among the people suffering from BD and gives some clue to understand significant pathological mechanisms.
Keyphrases
- bipolar disorder
- transcription factor
- genome wide identification
- gene expression
- epstein barr virus
- rna seq
- genome wide
- major depressive disorder
- single cell
- copy number
- end stage renal disease
- dna methylation
- magnetic resonance imaging
- mental health
- long non coding rna
- diffuse large b cell lymphoma
- cell proliferation
- electronic health record
- climate change
- bioinformatics analysis
- magnetic resonance
- oxidative stress
- newly diagnosed
- peritoneal dialysis
- computed tomography
- long noncoding rna
- deep learning
- immune response
- amino acid
- data analysis
- heat shock