Background Previous studies on European (EUR) samples have obtained inconsistent results regarding the genetic correlation between type 2 diabetes mellitus (T2DM) and Schizophrenia (SCZ). A large-scale trans-ethnic genetic analysis may provide additional evidence with enhanced power. Objective We aimed to explore the genetic basis for both T2DM and SCZ based on large-scale genetic analyses of genome-wide association study (GWAS) data from both East Asian (EAS) and EUR subjects. Methods A range of complementary approaches were employed to cross-validate the genetic correlation between T2DM and SCZ at the whole genome, autosomes (linkage disequilibrium score regression, LDSC), loci (Heritability Estimation from Summary Statistics, HESS), and causal variants (MiXeR and Mendelian randomization, MR) levels. Then, genome-wide and transcriptome-wide cross-trait/ethnic meta-analyses were performed separately to explore the effective shared organs, cells and molecular pathways. Results A weak genome-wide negative genetic correlation between SCZ and T2DM was found for the EUR (rg = − 0.098, P = 0.009) and EAS (rg =- 0.053 and P = 0.032) populations, which showed no significant difference between the EUR and EAS populations (P = 0.22). After Bonferroni correction, the rg remained significant only in the EUR population. Similar results were obtained from analyses at the levels of autosomes, loci and causal variants. 25 independent variants were firstly identified as being responsible for both SCZ and T2DM. The variants associated with the two disorders were significantly correlated to the gene expression profiles in the brain (P = 1.1E-9) and pituitary gland (P = 1.9E-6). Then, 61 protein-coding and non-coding genes were identified as effective genes in the pituitary gland (P < 9.23E-6) and were enriched in metabolic pathways related to glutathione mediated arsenate detoxification and to D-myo-inositol-trisphosphate. Conclusion Here, we show that a negative genetic correlation exists between SCZ and T2DM at the whole genome, autosome, locus and causal variant levels. We identify pituitary gland as a common effective organ for both diseases, in which non-protein-coding effective genes, such as lncRNAs, may be responsible for the negative genetic correlation. This highlights the importance of molecular metabolism and neuroendocrine modulation in the pituitary gland, which may be responsible for the initiation of T2DM in SCZ patients.
Objectives: To explore the connection of hypertension and severe COVID-19 outcomes.Methods: A total of 68 observational studies recording mortality and/or general severity of COVID-19 were pooled for meta-analyses of the relationship of severe COVID-19 outcomes with hypertension as well as systolic and diastolic blood pressure. Genome-wide cross-trait meta-analysis (GWCTM) was performed to explore the genes linking between hypertension and COVID-19 severity.Results: The results of meta-analysis with the random effect model indicated that pooled risk ratios of hypertension on mortality and severity of COVID-19 were 1.80 [95% confidence interval (CI) 1.54–2.1] and 1.78 (95% confidence interval 1.56–2.04), respectively, although the apparent heterogeneity of the included studies was detected. In subgroup analysis, cohorts of severe and mild patients of COVID-19 assessed in Europe had a significant pooled weighted mean difference of 6.61 mmHg (95% CI 3.66–9.55) with no heterogeneity found (p = 0.26). The genes in the shared signature of hypertension and the COVID-19 severity were mostly expressed in lungs. Analysis of molecular networks commonly affected both by hypertension and by severe COVID-19 highlighted CCR1/CCR5 and IL10RB signaling, as well as Th1 and Th2 activation pathways, and also a potential for a shared regulation with multiple sclerosis.Conclusion: Hypertension is significantly associated with the severe course of COVID-19. Genetic variants within inflammation- and immunity-related genes may affect their expression in lungs and confer liability to both elevated blood pressure and to severe COVID-19.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.