Long Noncoding RNA VLDLR-AS1 Levels in Serum Correlate with Combat-Related Chronic Mild Traumatic Brain Injury and Depression Symptoms in US Veterans

More than 75% of traumatic brain injuries (TBIs) are mild (mTBI) and military service members often experience repeated combat-related mTBI. The chronic comorbidities concomitant with repetitive mTBI (rmTBI) include depression, post-traumatic stress disorder or neurological dysfunction. This study sought to determine a long noncoding RNA (lncRNA) expression signature in serum samples that correlated with rmTBI years after the incidences. Serum samples were obtained from Long-Term Impact of Military-Relevant Brain-Injury Consortium Chronic Effects of Neurotrauma Consortium (LIMBIC CENC) repository, from participants unexposed to TBI or who had rmTBI. Four lncRNAs were identified as consistently present in all samples, as detected via droplet digital PCR and packaged in exosomes enriched for CNS origin. The results, using qPCR, demonstrated that the lncRNA VLDLR-AS1 levels were significantly lower among individuals with rmTBI compared to those with no lifetime TBI. ROC analysis determined an AUC of 0.74 (95% CI: 0.6124 to 0.8741; p = 0.0012). The optimal cutoff for VLDLR-AS1 was ≤153.8 ng. A secondary analysis of clinical data from LIMBIC CENC was conducted to evaluate the psychological symptom burden, and the results show that lncRNAs VLDLR-AS1 and MALAT1 are correlated with symptoms of depression. In conclusion, lncRNA VLDLR-AS1 may serve as a blood biomarker for identifying chronic rmTBI and depression in patients.

Identification and functional analysis of a potential key lncRNA involved in fat loss of cancer cachexia

Cancer cachexia is a devastating, multifactorial, and irreversible syndrome characterized by skeletal muscle reduction with or without fat loss. Although much attention has been focused on muscle wasting, fat loss may occur earlier and accelerate muscle wasting in cachexia. The cause of 20% of cancer related death makes it urgent to discover molecular mechanisms behind cancer cachexia. Here we applied weighted gene co-expression network analysis (WGCNA) to identify cachexia related gene modules using differentially expressed 3289 genes and 59 long non-coding RNAs based on microarray data of cachectic and non-cachectic subcutaneous adipose tissue. Subsequently, 16 independent modules were acquired and GSAASeqSP Toolset confirmed that black module was significantly associated with fat loss in cancer cachexia. Top 50 hub-genes in black module contained only one lncRNA, VLDLR antisense RNA 1 (VLDLR-AS1). We then explored the function of black module from the view of VLDLR-AS1-connected genes in the network. GO enrichment and KEGG pathways analysis revealed LDLR-AS1-connected genes were involved in Wnt signaling pathway, small GTPase mediated signal transduction, epithelial-mesenchymal transition and so on. Through construction of competing endogenous RNAs (ceRNAs) regulation network, we showed that VLDLR-AS1 may function with hsa-miR-600 to regulate gene GOLGA3, DUSP14, and UCHL1, or interact with hsa-miR-1224-3p to modulate the expression of gene GOLGA3, ZNF219, RNF141, and CALU. After literature validation, we predicted that VLDLR-AS1 most likely interacted with miR-600 to regulate UCH-L1 through Wnt/β-catenin signaling pathway. However, further experiments are still required to validate mechanisms of VLDLR-AS1 in fat reduction of cancer cachexia.