Abstract ：

Introduction: Observational studies highlight associations of common diseases with individual schizophrenia symptoms. However, it is unclear whether these diseases are associated with individual treatment-resistant schizophrenia (TRS). We aimed to explore the genetic associations between common immune diseases, metabolic diseases, psychiatric disorders, gut microbiota and TRS. Methods: Genome-wide association study (GWAS) summary data of European participants (n = similar to 456,327) included TRS, 11 psychiatric disorders, 23 immune and metabolic diseases, body mass index, height, and 211 gut microbiota. In this genetic correlation and two-sample Mendelian randomization (MR) study, linkage disequilibrium score (LDSC) regression was applied to infer genetic correlation estimates. Two-sample MR tested potential causal associations of genetic variants associated with common immune diseases, metabolic diseases, psychiatric disorders, and gut microbiota with TRS. Results: LDSC revealed candidate associations between attention deficit/hyperactivity disorder (ADHD), schizophrenia, intestinal infectious diseases, obesity and TRS (genetic correlation range, 0.230-0.702; p < 0.05). Two-sample MR analyses suggested that ADHD was positively associated with TRS (estimate [SE] = 0.204 [0.073], p = 0.005), a finding that remained stable across statistical models. Besides, schizophrenia and genus Barnesiella levels were causally associated with TRS but not consistent across MR approaches. Conclusion: This study reports genetic correlations between ADHD, schizophrenia, intestinal infectious diseases, obesity and TRS. The study also found that genus Barnesiella was associated with TRS. These findings may have clinical implications, highlighting the possible strategy for TRS prevention.

Keyword ：

Attention deficit hyperactivity disorder Intestinal infectious diseases Obesity Treatment-resistant schizophrenia Two-sample Mendelian randomization

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Limited efforts have been invested in exploring the interaction effects between genetic factors and gut microbiota on neuroticism and general happiness. The polygenic risk scores (PRS) of gut microbiota were calculated from individual-level genotype data of the UK Biobank cohort. Linear regression models were then used to assess the associations between individual PRS of gut microbiota and mental traits and interaction analysis was performed by PLINK2.0. KOBAS-i was used to conduct gene ontology (GO) enrichment analysis of the identified genes. We observed suggestive significant associations between neuroticism and PRS for the genus Bifidobacterium (rank-normal transformation, RNT) (beta = -1.10, P = 4.16 x 10(-3)) and the genus Desulfovibrio (RNT) (beta = 0.54, P = 7.46 x 10(-3)). PRS for the genus Bifidobacterium (hurdle binary, HB) (beta = 1.99, P = 5.24 x 10(-3)) and the genus Clostridium (RNT) (beta = 1.26, P = 9.27 x 10(-3)) were found to be suggestive positively associated with general happiness. Interaction analysis identified several significant genes that interacted with gut microbiota, such as RORA (rs575949009, beta = -45.00, P = 1.82 x 10(-9)) for neuroticism and ASTN2 (rs36005728, beta = 19.15, P = 3.37 x 10(-8)) for general happiness. Our study results support the genetic effects of gut microbiota on the development of neuroticism and general happiness.

Keyword ：

general happiness gut microbiota neuroticism polygenic risk scores

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Longitudinal changes in brain structure and lifestyle can affect sleep phenotypes. However, the influence of the interaction between longitudinal changes in brain structure and lifestyle on sleep phenotypes remains unclear. Genome-wide association study dataset of longitudinal changes in brain structure was obtained from published study. Phenotypic data of lifestyles and sleep phenotypes were obtained from UK Biobank cohort. Using genotype data from UK Biobank, we calculated polygenetic risk scores of longitudinal changes in brain structure phenotypes. Linear/logistic regression analysis was conducted to evaluate interactions between longitudinal changes in brain structure and lifestyles on sleep duration, chronotype, insomnia, snoring and daytime dozing. Multiple lifestyle x longitudinal changes in brain structure interactions were detected for 5 sleep phenotypes, such as physical activityxcaudate_age2 for daytime dozing (OR = 1.0389, P = 8.84 x 10(-3)) in total samples, coffee intakexcerebellar white matter volume_age2 for daytime dozing (OR = 0.9652, P = 1.13 x 10(-4)) in females. Besides, we found 4 overlapping interactions in different sleep phenotypes. We conducted sex stratification analysis and identified one overlapping interaction between female and male. Our results support the moderate effects of interaction between lifestyle and longitudinal changes in brain structure on sleep phenotypes, and deepen our understanding of the pathogenesis of sleep disorders.

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Cerebellar white matter coffee intake hippocampus insomnia sleep duration

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ObjectiveCardiac fibroblasts (CFs) proliferation and extracellular matrix deposition are important features of cardiac fibrosis. Various studies have indicated that vitamin D displays an anti-fibrotic property in chronic heart diseases. This study explored the role of vitamin D in the growth of CFs via an integrin signaling pathway.MethodsMTT and 5-ethynyl-2 '-deoxyuridine assays were performed to determine cell viability. Western blotting was performed to detect the expression of proliferating cell nuclear antigen (PCNA) and integrin signaling pathway. The fibronectin was observed by ELISA. Immunohistochemical staining was employed to evaluate the expression of integrin beta 3.ResultsThe PCNA expression in the CFs was enhanced after isoproterenol (ISO) stimulation accompanied by an elevated expression of integrin beta-3 (beta 3). The blockade of the integrin beta 3 with a specific integrin beta 3 antibody reduced the PCNA expression induced by the ISO. Decreasing the integrin beta 3 by siRNA reduced the ISO-triggered phosphorylation of FAK and Akt. Both the FAK inhibitor and Akt inhibitor suppressed the PCNA expression induced by the ISO in the CFs. Calcitriol (CAL), an active form of vitamin D, attenuated the ISO-induced CFs proliferation by downregulating the integrin beta 3 expression, and phosphorylation of FAK and Akt. Moreover, CAL reduced the increased levels of fibronectin and hydroxyproline in the CFs culture medium triggered by the ISO. The administration of calcitriol decreased the integrin beta 3 expression in the ISO-induced myocardial injury model.ConclusionThese findings revealed a novel role for CAL in suppressing the CFs growth by the downregulation of the integrin beta 3/FAK/Akt pathway.

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cardiac fibroblast integrin myocardial fibrosis proliferation vitamin D

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Background: Sleep behaviors were believed to be associated with mental disorders (MD). However, the underlying mechanism of such association relationship, especially the role of multiple lifestyle factors in it remains unclear. Methods: A total of 402,290 participants from UK Biobank who don't have MD at baseline were included. They were divided into poor, intermediate and healthy sleep patterns according to the sleep score, which was calculated based on the data collecting from five sleep behaviors. Cox proportional hazard model was used to estimate the associations between sleep behaviors and MD. The associations were further estimated when taking lifestyle factors such as physical activity, coffee intake, tea intake and genetic susceptibility into account. Results: Healthy sleep pattern was associated with lower risk of overall MD status (HR,0.41, 95%CI,0.39-0.43), depressive disorders (HR,0.34, 95%CI,0.31-0.37) and anxiety disorders (HR,0.46, 95%CI,0.41-0.79), compared with poor sleep pattern. And in each subgroup of physical activity, tea intake, coffee intake, age and genetic risk scores (GRS), healthy sleep pattern could partly offset the risk of diseases. Conclusions: Our study suggested healthy sleep behaviors could diminish the negative effect from genetic predisposition and lifestyle factors on the risk of MD, highlighting the benefit of healthy sleep pattern.

Keyword ：

Genetic predisposition to disease Mental disorders Physical activity Sleep behavior

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Disrupted brain structures and several life environmental factors have been shown to influence depression and anxiety, but their interactions with anxiety and depression remain elusive. Genome-wide association study datasets of 15 brain structure longitudinal changes (N = 15,640) were obtained from the published study. Genotype and phenotype-related data of depression, anxiety, and life environmental factors (including smoking, alcohol drinking, coffee intake, maternal smoking, physical activity, vitamin D, insomnia, sleep duration, and family satisfaction) were collected from UK Biobank. We calculated the polygenic risk scores (PRS) of 15 brain structure changes and then conducted linear regression analyses to explore the interactions of brain structure changes and life environmental factors on depression and anxiety using 15 brain structure change-related PRS, life environmental factors and interactions of them as instrumental variables, and depression score or anxiety score as outcomes. Sex stratification in all analyses was performed to reveal sex-specific differences in the interactions. We found 14 shared interactions related to both depression and anxiety in total sample, such as alcohol drinking x cerebellum white matter 3 (WM; beta = -.003, p = .018 for depression; beta = -003, p = .008 for anxiety) and maternal smoking x nucleus accumbens 2 (beta = .088, p = .002 for depression; beta = .070, p = .008 for anxiety). We also observed sex-specific differences in the interactions, for instance, alcohol drinking x cerebellum WM 3 was negatively associated with depression and anxiety in males (beta = -.004, p = .020 for depression; beta = -.005, p = .002 for anxiety). Our study results reveal the important interactions between brain structure changes and several life environmental factors on depression and anxiety, which may help to explore the pathogenesis of depression and anxiety.

Keyword ：

anxiety brain structure changes depression interaction life environmental factor

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The mechanism of environmental factors in Kashin-Beck disease (KBD) remains unknown. We aimed to identify single nucleotide polymorphisms (SNPs) and protein alterations of selenium- and T-2 toxin-responsive genes to provide new evidence of chondrocytic damage in KBD. This study sampled the cubital venous blood of 258 subjects including 129 sex-matched KBD patients and 129 healthy controls for SNP detection. We applied an additive model, a dominant model, and a recessive model to identify significant SNPs. We then used the Comparative Toxicogenomics Database (CTD) to select selenium- and T-2 toxin-responsive genes with the candidate SNP loci. Finally, immunohistochemistry was applied to verify the protein expression of candidate genes in knee cartilage obtained from 15 subjects including 5 KBD, 5 osteoarthritis (OA), and 5 healthy controls. Forty-nine SNPs were genotyped in the current study. The C allele of rs6494629 was less frequent in KBD than in the controls (OR = 0.63, p = 0.011). Based on the CTD database, PPARG, ADAM12, IL6, SMAD3, and TIMP2 were identified to interact with selenium, sodium selenite, and T-2 toxin. KBD was found to be significantly associated with rs12629751 of PPARG (additive model: OR = 0.46, p = 0.012; dominant model: OR = 0.45, p = 0.049; recessive model: OR = 0.18, p = 0.018), rs1871054 of ADAM12 (dominant model: OR = 2.19, p = 0.022), rs1800796 of IL6 (dominant model: OR = 0.30, p = 0.003), rs6494629 of SMAD3 (additive model: OR = 0.65, p = 0.019; dominant model: OR = 0.52, p = 0.012), and rs4789936 of TIMP2 (recessive model: OR = 5.90, p = 0.024). Immunohistochemistry verified significantly upregulated PPARG, ADAM12, SMAD3, and TIMP2 in KBD compared with OA and normal controls (p < 0.05). Genetic polymorphisms of PPARG, ADAM12, SMAD3, and TIMP2 may contribute to the risk of KBD. These genes could promote the pathogenesis of KBD by disturbing ECM homeostasis.

Keyword ：

chondrocyte damage Kashin-Beck disease selenium single nucleotide polymorphism T-2 toxin

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Background DNA methylation has long been known as an epigenetic gene silencing mechanism. For a motivating example, the methylomes of cancer and non-cancer cells show a number of methylation differences, indicating that certain features characteristics of cancer cells may be related to methylation characteristics. Robust methods for detecting differentially methylated regions (DMRs) could help scientists narrow down genome regions and even find biologically important regions. Although some statistical methods were developed for detecting DMR, there is no default or strongest method. Fisher's exact test is direct, but not suitable for data with multiple replications, while regression-based methods usually come with a large number of assumptions. More complicated methods have been proposed, but those methods are often difficult to interpret. Results In this paper, we propose a three-step nonparametric kernel smoothing method that is both flexible and straightforward to implement and interpret. The proposed method relies on local quadratic fitting to find the set of equilibrium points (points at which the first derivative is 0) and the corresponding set of confidence windows. Potential regions are further refined using biological criteria, and finally selected based on a Bonferroni adjusted t-test cutoff. Using a comparison of three senescent and three proliferating cell lines to illustrate our method, we were able to identify a total of 1077 DMRs on chromosome 21. Conclusions We proposed a completely nonparametric, statistically straightforward, and interpretable method for detecting differentially methylated regions. Compared with existing methods, the non-reliance on model assumptions and the straightforward nature of our method makes it one competitive alternative to the existing statistical methods for defining DMRs.

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Background T-2 toxin is thought to induce the growth plate and articular cartilage damage of Kashin-Beck disease (KBD), an endemic osteochondropathy in China. This study aims to explore the potential underlying mechanism of such toxic effects by integrating DNA methylation and gene expression profiles. Methods In this study, C28/I2 chondrocytes were treated with T-2 toxin (5 ng/mL) for 24 h and 72 h. Global DNA methylation level of chondrocyte was tested by Enzyme-Linked Immuno Sorbent Assay. Genome-wide DNA methylation and expression profiles were detected using Illumina Infinium HumanMethylation850 BeadChip and RNA-seq technique, respectively. Differentially methylated genes (DMGs) and differentially expressed genes (DEGs) were identified mainly for two stages including 24 h group versus Control group and 72 h group versus 24 h group. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed by Metascape. DMGs and DEGs were further validated by Sequenom MassARRAY system and quantitative real-time polymerase chain reaction. Results The global DNA methylation levels of chondrocytes exposed to T-2 toxin were significantly increased (P < 0.05). For 24 h group versus Control group (24 VS C), 189 DEGs and 590 DMGs were identified, and 4 of them were overlapping. For 72 h group versus 24 h group (72 VS 24), 1671 DEGs and 637 DMGs were identified, and 45 of them were overlapping. The enrichment analysis results of DMGs and DEGs both showed that MAPK was the one of the mainly involved signaling pathways in the regulation of chondrocytes after T-2 toxin exposure (DEGs: P-24VSc = 1.62 x 10(- 7); P-72VS24 = 1.20 x 10(- 7); DMGs: P-24VSc = 0.0056; P-72VS24 = 3.80 x 10(- 5)). Conclusions The findings depicted a landscape of genomic methylation and transcriptome changes of chondrocytes after T-2 toxin exposure and suggested that dysfunction of MAPK pathway may play important roles in the chondrocytes damage induced by T-2 toxin, which could provide new clues for understanding the potential biological mechanism of KBD cartilage damage induced by T-2 toxin.

Keyword ：

Chondrocyte damage DNA methylation Kashin-Beck disease RNA-seq T-2 toxin

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