Multivariate network-based analytic methods such as weighted gene co-expression network analysis are frequently applied to human and animal gene-expression data to estimate the first principal component of a module, or module eigengene (ME). MEs are interpreted as multivariate summaries of correlated gene-expression patterns and network connectivity across genes within a module. As such, they have the potential to elucidate the mechanisms by which molecular genomic variation contributes to individual differences in complex traits. Although increasingly used to test for associations between modules and complex traits, the genetic and environmental etiology of MEs has not been empirically established. It is unclear if, and to what degree, individual differences in blood-derived MEs reflect random variation versus familial aggregation arising from heritable or shared environmental influences. We used biometrical genetic analyses to estimate the contribution of genetic and environmental influences on MEs derived from blood lymphocytes collected on a sample of N = 661 older male twins from the Vietnam Era Twin Study of Aging (VETSA) whose mean age at assessment was 67.7 years (SD = 2.6 years, range = 62-74 years). Of the 26 detected MEs, 14 (56%) had statistically significant additive genetic variation with an average heritability of 44% (SD = 0.08, range = 35%-64%). Despite the relatively small sample size, this demonstration of significant family aggregation including estimates of heritability in 14 of the 26 MEs suggests that blood-based MEs are reliable and merit further exploration in terms of their associations with complex traits and diseases.

The Finkel-Biskis-Jinkins Osteosarcoma (c-Fos; encoded by FOS) plays an important role in several cardiovascular diseases, including atherosclerosis and stroke. However, the relationship between FOS and venous thromboembolism (VTE) remains unknown. We identified differentially expressed genes in Gene Expression Omnibus dataset, GSE48000, comprising VTE patients and healthy individuals, and analysed them using CIBERSORT and weighted co-expression network analysis (WGCNA). FOS and CD46 expressions were significantly downregulated (FOS p = 2.26E-05, CD64 p = 8.83E-05) and strongly linked to neutrophil activity in VTE. We used GSE19151 and performed PCR to confirm that FOS and CD46 had diagnostic potential for VTE; however, only FOS showed differential expression by PCR and ELISA in whole blood samples. Moreover, we found that hsa-miR-144 which regulates FOS expression was significantly upregulated in VTE. Furthermore, FOS expression was significantly downregulated in neutrophils of VTE patients (p = 0.03). RNA sequencing performed on whole blood samples of VTE patients showed that FOS exerted its effects in VTE via the leptin-mediated adipokine signalling pathway. Our results suggest that FOS and related genes or proteins can outperform traditional clinical markers and may be used as diagnostic biomarkers for VTE.

OBJECTIVE: Obsessive-compulsive disorder (OCD) is a complex psychiatric disorder. Genetic and broad environmental factors are common risk factors for OCD. The purpose of this study is to explore the molecular mechanism of OCD and to find new molecular targets for the diagnosis and management of OCD.
METHODS: All data were downloaded from public dataset. Key modules and candidate key mRNAs were identified based on weighted gene co-expression network analysis (WGCNA). The \"limma\" R package was used for differential expression analysis of mRNAs. Subsequently, functional enrichment analysis of differentially expressed mRNAs (DEmRNAs) was also carried out. In addition, a diagnostic model was constructed. Finally, the infiltration level of immune cells in OCD and its correlation with multicentric key DEmRNAs were analyzed.
RESULTS: Green and red modules were selected as the hub modules. A total of 447 mRNAs were considered candidate key mRNAs according to GS > 0.2 and MM > 0.3. A total of 26 DEmRNAs in the same direction were identified in the GSE60190 and GSE78104 datasets. A total of 26 DEmRNAs were intersected with candidate key mRNAs in WGCNA to obtain 10 intersection DEmRNAs (HSPB1, ITPK1, CBX7, PPP1R10, TAOK1, PISD, MKNK2, RWDD1, PPA1, and RELN). However, only four DEmRNAs (HSPB1, TAOK1, MKNK2, and PPA1) predicted related drugs. Subsequently, receiver operating characteristic analysis shows that the diagnostic model has high diagnostic value. Moreover, six multicentric key DEmRNAs (SNRPF, SNRNP70, PRPF8, NOP56, EPRS, and CCT2) were screened by UpSet package. Finally, six multicentric key DEmRNAs were found to be associated with immune cells.
CONCLUSIONS: The key molecules obtained in this study lay a foundation for further research on the molecular mechanism of OCD.

BACKGROUND: FRMD5 variants were recently identified in patients with developmental delay, ataxia, and eye movement abnormalities.
OBJECTIVE: We describe 2 patients presenting with childhood-onset ataxia, nystagmus, and seizures carrying pathogenic de novo FRMD5 variants. Weighted gene co-expression network analysis (WGCNA) was performed to gain insights into the function of FRMD5 in the brain.
METHODS: Trio-based whole-exome sequencing was performed in both patients, and CoExp web tool was used to conduct WGCNA.
RESULTS: Both patients presented with developmental delay, childhood-onset ataxia, nystagmus, and seizures. Previously unreported findings were diffuse choreoathetosis and dystonia of the hands (patient 1) and areas of abnormal magnetic resonance imaging signal in the white matter (patient 2). WGCNA showed that FRMD5 belongs to gene networks involved in neurodevelopment and oligodendrocyte function.
CONCLUSIONS: We expanded the phenotype of FRMD5-related disease and shed light on its role in brain function and development. We recommend including FRMD5 in the genetic workup of childhood-onset ataxia and nystagmus. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Incomplete Kawasaki Disease is a complex disease that often occurs in infants and has substantial coronary artery damage. Its pathogenesis is unclear and lacks specific diagnostic markers. The purpose of our study is to research the mechanism of incomplete Kawasaki Disease use of bioinformatic methods and identify potential biomarkers. We performed weighted gene co-expression network analysis to analyze the data set GSE68004 and identified modules and genes which were correlated with the disease. Through functional annotation and enrichment analysis, we determined the biological function and signal pathway of these genes. We further used lasso regression and ROC curve to screen genes and determined that the final candidate gene was HSPB11and hsa-miR-155-5p that regulates its expression. Finally, we validated the screened gene using an independent dataset and construct a TF-miRNA network. Through the relationships of TFs and hsa-miR-155-5p, we found is hsa-miR-155-5p closely related to hypoxia-related transcription factors, which may be a new direction in the research of Kawasaki disease.

Identifying critical pathways governing disease progression is essential for accurate prognosis and effective therapy. We developed a broadly applicable and novel systems-level gene discovery strategy. This approach focused on constitutively active androgen receptor (AR) splice variant-driven pathways as representative of an intractable mechanism of prostate cancer (PC) therapeutic resistance. We performed a meta-analysis of human prostate samples using weighted gene co-expression network analysis combined with experimental AR variant transcriptome analyses. An AR variant-driven gene module that is upregulated during human PC progression was identified. We filtered this module by identifying genes that functionally interacted with AR variants using a high-throughput synthetic genetic array screen in Schizosaccharomyces pombe This strategy identified seven AR variant-regulated genes that also enhance AR activity and drive cancer progression. Expression of the seven genes predicted poor disease-free survival in large independent PC patient cohorts. Pharmacologic inhibition of interacting members of the gene set potently and synergistically decreased PC cell proliferation. This unbiased and novel gene discovery strategy identified a clinically relevant, oncogenic, interacting gene hub with strong prognostic and therapeutic potential in PC.