Assessing the joint effects of mitochondrial genes and physical activity on the psychiatric phenotype of subjective well-being based on the UK Biobank data.

Subjective well-being (SWB) is an important measure for mental health status. Previous research has shown that physical activity can affect an individual's well-being, yet the underlying molecular mechanism remains to be clarified. In this study, we aim to evaluate the potential interactions between mitochondrial genes and physical activity (PA) as well as their combined effects on individual well-being. SWB phenotype data in UK Biobank were enrolled for this study including nine aspects such as work/job satisfaction, health satisfaction, family relationship satisfaction, friendships satisfaction, financial situation satisfaction, ever depressed for a whole week, general happiness, general happiness with own health and belief that own life is meaningful. We made analysis for each aspects separately. Firstly, mitochondria-wide association studies (MiWAS) was conducted to assess the association of mitochondrial Single Nucleotide Polymorphisms SNP with each aspect of SWB. Then an interaction analysis of mitochondrial DNA (mtDNA) mutation and PA was performed to evaluate their joint effect on SWB status. Meanwhile, these two analysis were made for female and male group separately as well as the total samples, all under the control of possible confounding factors including gender, age, Townsend Deprivation Index (TDI), education, alcohol consumption, smoking habits, and 10 principal components. MiWAS analysis identified 45 mtSNPs associated with 9 phenotypes of SWB. For example, m.15218A > G on MT-CYB in the health satisfaction phenotype of the total subjects. Gender-specific analyses found 30 mtSNPs in females and 58 in males, involving 13 mtGenes. In mtDNA-PA interaction analysis, we also identified 10 significant mtDNA-PA interaction sets for SWB. For instance, m.13020 T > C (MT-ND5) was associated with the SWB financial situation satisfaction phenotype in all subjects (P = 0.00577). In addition, MiWAS analysis identified 12 mtGene variants associated with SWB, as MT-ND1 and MT-ND2. However, in mtDNA-PA interactions we detected 7 mtDNA affecting psychiatric disorders occurring, as in the friendships satisfaction phenotype (m.3394 T > C on MT-ND1). Our study results suggest an implication of the interaction between mitochondrial function and physical activity in the risk of psychiatric disorder development.

Assessing the interaction effects of mitochondrial DNA polymorphisms and lifestyle on heel bone mineral density.

BACKGROUND: Bone mineral density (BMD) is a major predictor of osteoporotic fractures, and previous studies have reported the effects of mitochondrial dysfunction and lifestyle on BMD, respectively. However, their interaction effects on BMD are still unclear. Therefore, we aimed to investigate the possible interaction of mitochondrial DNA (mtDNA) and common lifestyles contributing to osteoporosis. METHODS: Our analysis included 119,120 white participants (Nfemale=65,949 and Nmale=53,171) from the UK Biobank with heel BMD phenotype data. A generalized linear regression model of PLINK was performed to assess the interaction effects of mtDNA and five life environmental factors on heel BMD, including smoking, drinking, physical activity, dietary diversity score, and vitamin D. In addition, we also performed linear regression analysis for total body BMD. Finally, we assessed the potential causal relationships between mtDNA copy number (mtDNA-CN) and life environmental factors using Mendelian randomization (MR) analysis. RESULTS: Our study identified four mtDNA loci showing suggestive evidence of heel BMD, such as m.16356T>C (MT-DLOOP; P =1.50×10-3) in total samples. Multiple candidate mtDNA×lifetsyle interactions were also detected for heel BMD, such as MT-ND2×physical activity (P = 2.88×10-3) in total samples and MT-ND1×smoking (P = 8.54×10-4) in males. Notably, MT-CYB was a common candidate mtDNA loci for heel BMD to interact with five life environmental factors. Multivariable MR analysis indicated a causal effect of physical activity on heel BMD when mtDNA-CN was considered (P =1.13×10-3). CONCLUSIONS: Our study suggests the candidate interaction between mitochondria and lifestyles on heel BMD, providing novel clues for exploring the pathogenesis of osteoporosis.

Identifying novel chemical-related susceptibility genes for five psychiatric disorders through integrating genome-wide association study and tissue-specific 3'aQTL annotation datasets.

The establishment of 3'aQTLs comprehensive database provides an opportunity to help explore the functional interpretation from the genome-wide association study (GWAS) data of psychiatric disorders. In this study, we aim to search novel susceptibility genes, pathways, and related chemicals of five psychiatric disorders via GWAS and 3'aQTLs datasets. The GWAS datasets of five psychiatric disorders were collected from the open platform of Psychiatric Genomics Consortium (PGC, https://www.med.unc.edu/pgc/ ) and iPSYCH ( https://ipsych.dk/ ) (Demontis et al. in Nat Genet 51(1):63-75, 2019; Grove et al. in Nat Genet 51:431-444, 2019; Genomic Dissection of Bipolar Disorder and Schizophrenia in Cell 173: 1705-1715.e1716, 2018; Mullins et al. in Nat Genet 53: 817-829; Howard et al. in Nat Neurosci 22: 343-352, 2019). The 3'untranslated region (3'UTR) alternative polyadenylation (APA) quantitative trait loci (3'aQTLs) summary datasets of 12 brain regions were obtained from another public platform ( https://wlcb.oit.uci.edu/3aQTLatlas/ ) (Cui et al. in Nucleic Acids Res 50: D39-D45, 2022). First, we aligned the GWAS-associated SNPs of psychiatric disorders and datasets of 3'aQTLs, and then, the GWAS-associated 3'aQTLs were identified from the overlap. Second, gene ontology (GO) and pathway analysis was applied to investigate the potential biological functions of matching genes based on the methods provided by MAGMA. Finally, chemical-related gene-set analysis (GSA) was also conducted by MAGMA to explore the potential interaction of GWAS-associated 3'aQTLs and multiple chemicals in the mechanism of psychiatric disorders. A number of susceptibility genes with 3'aQTLs were found to be associated with psychiatric disorders and some of them had brain-region specificity. For schizophrenia (SCZ), HLA-A showed associated with psychiatric disorders in all 12 brain regions, such as cerebellar hemisphere (P = 1.58 × 10-36) and cortex (P = 1.58 × 10-36). GO and pathway analysis identified several associated pathways, such as Phenylpropanoid Metabolic Process (GO:0009698, P = 6.24 × 10-7 for SCZ). Chemical-related GSA detected several chemical-related gene sets associated with psychiatric disorders. For example, gene sets of Ferulic Acid (P = 6.24 × 10-7), Morin (P = 4.47 × 10-2) and Vanillic Acid (P = 6.24 × 10-7) were found to be associated with SCZ. By integrating the functional information from 3'aQTLs, we identified several susceptibility genes and associated pathways especially chemical-related gene sets for five psychiatric disorders. Our results provided new insights to understand the etiology and mechanism of psychiatric disorders.

Assessing the association of coffee consumption on the relationship of chronic pain with depression and anxiety.

BACKGROUND: A bidirectional relationship between chronic pain (CP) and mental disorders has been reported, and coffee was believed to be associated with both. However, the association of coffee in this bidirectional relationship remains unclear. We aim to analyze the association of coffee consumption on the relationship of CP with depression and anxiety. METHODS: A total of 376,813 participants from UK Biobank were included. We collected data on anxiety, depression and CP from objects of our study population. The association of coffee consumption on the relationship of CP with depression and anxiety was assessed through logistic/linear regression models. Moreover, seemingly unrelated estimation test (SUEST) was used to compare whether the coefficients differed in two different groups. RESULTS: We observed significant associations of coffee consumption in the interaction of CP with depression and anxiety, such as the association of multisite chronic pain (MCP) on self-reported depression (ßcoffee = 0.421, ßnon-coffee = 0.488, PSUEST = 0.001), and the association of MCP on generalized anxiety disorder-7 (GAD-7) scores (ßcoffee = 0.561, ßnon-coffee = 0.678, PSUEST = 0.004) were significantly different between coffee drinking and non-coffee drinking groups. Furthermore, in analysis stratified by gender, we found headache (ßmale = 0.392, ßfemale = 0.214, PSUEST = 0.022) and hip pain (ßmale = 0.480, ßfemale = 0.191, PSUEST = 0.021) had significant associations with self-reported depression between males and females groups in coffee drinkers. CONCLUSIONS: Our results suggested that coffee consumption has a significant association on the relationship of CP with depression and anxiety.

A Metabolomics Study of Feces Revealed That a Disturbance of Selenium-Centered Metabolic Bioprocess Was Involved in Kashin-Beck Disease, an Osteoarthropathy Endemic to China.

Background: Kashin-Beck disease (KBD) is a distinct osteoarthropathy in China with an unclear pathogenesis. This study aims to explore whether perturbations in the intestine metabolome could be linked to KBD individuals. Methods: An investigation was conducted in KBD endemic villages and fecal samples were collected. After applying inclusion and exclusion criteria, a total of 75 subjects were enrolled for this study, including 46 KBD (including 19 Grade I KBD and 27 Grade II KBD) and 29 controls. Untargeted metabolomics analysis was performed on the platform of UHPLC-MS. PLS-DA and OPLS-DA were conducted to compare the groups and identify the differential metabolites (DMs). Pathway analysis was conducted on MPaLA platform to explore the functional implication of the DMs. Results: Metabolomics analysis showed that compared with the control group, KBD individuals have a total of 584 differential metabolites with dysregulated levels such as adrenic acid (log2FC = -1.87, VIP = 4.84, p = 7.63 × 10-7), hydrogen phosphate (log2FC = -2.57, VIP = 1.27, p = 1.02 × 10-3), taurochenodeoxycholic acid (VIP = 1.16, log2FC = -3.24, p = 0.03), prostaglandin E3 (VIP = 1.17, log2FC = 2.67, p = 5.61 × 10-4), etc. Pathway analysis revealed several significantly perturbed pathways associated with KBD such as selenium micronutrient network (Q value = 3.11 × 10-3, Wikipathways), metabolism of lipids (Q value = 8.43 × 10-4, Reactome), free fatty acid receptors (Q value = 3.99 × 10-3, Reactome), and recycling of bile acids and salts (Q value = 2.98 × 10-3, Reactome). Subgroup comparisons found a total of 267 differential metabolites were shared by KBD vs. control, KBD II vs. control, and KBD I vs. control, while little difference was found between KBD II and KBD I (only one differential metabolite detected). Conclusions: KBD individuals showed distinct metabolic features characterized by perturbations in lipid metabolism and selenium-related bioprocesses. Our findings suggest that the loss of nutrients metabolism balance in intestine was involved in KBD pathogenesis. Linking the nutrients metabolism (especially selenium and lipid) to KBD cartilage damage should be a future direction of KBD study.

A longitudinal genome-wide association study of bone mineral density mean and variability in the UK Biobank.

Bone mineral density (BMD) is an essential predictor of osteoporosis and fracture. We conducted a genome-wide trajectory analysis of BMD and analyzed the BMD change. PURPOSE: This study aimed to identify the genetic architecture and potential biomarkers of BMD. METHODS: Our analysis included 141,261 white participants from the UK Biobank with heel BMD phenotype data. We used a genome-wide trajectory analysis tool, TrajGWAS, to conduct a genome-wide association study (GWAS) of BMD. Then, we validated our findings in previously reported BMD genetic associations and performed replication analysis in the Asian participants. Finally, gene-set enrichment analysis (GSEA) of the identified candidate genes was conducted using the FUMA platform. RESULTS: A total of 52 genes associated with BMD trajectory mean were identified, of which the top three significant genes were WNT16 (P = 1.31 × 10-126), FAM3C (P = 4.18 × 10-108), and CPED1 (P = 8.48 × 10-106). In addition, 114 genes associated with BMD within-subject variability were also identified, such as AC092079.1 (P = 2.72 × 10-13) and RGS7 (P = 4.72 × 10-10). The associations for these candidate genes were confirmed in the previous GWASs and replicated successfully in the Asian participants. GSEA results of BMD change identified multiple GO terms related to skeletal development, such as SKELETAL SYSTEM DEVELOPMENT (Padjusted = 2.45 × 10-3) and REGULATION OF OSSIFICATION (Padjusted = 2.45 × 10-3). KEGG enrichment analysis showed that these genes were mainly enriched in WNT SIGNALING PATHWAY. CONCLUSIONS: Our findings indicated that the CPED1-WNT16-FAM3C locus plays a significant role in BMD mean trajectories and identified several novel candidate genes contributing to BMD within-subject variability, facilitating the understanding of the genetic architecture of BMD.

A systematical association analysis of 25 common virus infection and genetic susceptibility of COVID-19 infection.

OBJECTIVES: Previous studies identified a number of diseases were associated with 2019 coronavirus disease (COVID-19). However, the associations between these diseases related viral infections and COVID-19 remains unknown now. METHODS: In this study, we utilized single nucleotide polymorphisms (SNPs) related to COVID-19 from genome-wide association study (GWAS) and individual-level genotype data from the UK biobank to calculate polygenic risk scores (PRS) of 487,409 subjects for eight COVID-19 clinical phenotypes. Then, multiple logistic regression models were established to assess the correlation between serological measurements (positive/negative) of 25 viruses and the PRS of eight COVID-19 clinical phenotypes. And we performed stratified analyses by age and gender. RESULTS: In whole population, we identified 12 viruses associated with the PRS of COVID-19 clinical phenotypes, such as VZV seropositivity for Varicella Zoster Virus (Unscreened/Exposed_Negative: ß = 0.1361, P = 0.0142; Hospitalized/Unscreened: ß = 0.1167, P = 0.0385) and MCV seropositivity for Merkel Cell Polyomavirus (Unscreened/Exposed_Negative: ß = -0.0614, P = 0.0478). After age stratification, we identified seven viruses associated with the PRS of eight COVID-19 clinical phenotypes in the age < 65 years group. After gender stratification, we identified five viruses associated with the PRS of eight COVID-19 clinical phenotypes in the women group. CONCLUSION: Our study findings suggest that the genetic susceptibility to different COVID-19 clinical phenotypes is associated with the infection status of various common viruses.

Evaluating the interaction between 3'aQTL and alcohol consumption/smoking on anxiety and depression: 3'aQTL-by-environment interaction study in UK Biobank cohort.

BACKGROUND: Smoking and alcohol consumption were associated with the development of depression and anxiety. 3'UTR APA quantitative trait loci (3'aQTLs) have been associated with multiple health states and conditions. Our aim is to evaluate the interactive effects of 3'aQTLs-alcohol consumption/tobacco smoking on the risk of anxiety and depression. METHODS: The 3'aQTL data of 13 brain regions were extracted from the large-scale 3'aQTL atlas. The phenotype data (frequency of cigarette smoking and alcohol drinking, anxiety score, self-reported anxiety, depression score and self-reported depression) of 90,399-103,011 adults aged 40-69 years living in the UK and contributing to the UK Biobank during 2006-2010, were obtained from the UK Biobank cohort. The frequency of cigarette smoking and alcohol drinking of each subject were defined by the amount of smoking and alcohol drinking of self-reported, respectively. The continuous alcohol consumption/smoking terms were further categorized in tertiles. 3'aQTL-by-environmental interaction analysis was then performed to evaluate the associations of gene-smoking/alcohol consumption interactions with anxiety and depression using generalized linear model (GLM) of PLINK 2.0 with an additive mode of inheritance. Furthermore, GLM was also used to explore the relationship between alcohol consumption/smoking with hazard of anxiety/depression stratified by allele for the significant genotyped SNPs that modified the alcohol consumption/smoking-anxiety/depression association. RESULTS: The interaction analysis identified several candidate 3'aQTLs-alcohol consumption interactions, such as rs7602638 located in PPP3R1 (ß = 0.08, P = 6.50 × 10-6) for anxiety score; rs10925518 located in RYR2 (OR = 0.95, P = 3.06 × 10-5) for self-reported depression. Interestingly, we also observed that the interactions between TMOD1 (ß = 0.18, P = 3.30 × 10-8 for anxiety score; ß = 0.17, P = 1.42 × 10-6 for depression score), ZNF407 (ß = 0.17, P = 2.11 × 10-6 for anxiety score; ß = 0.15, P = 4.26 × 10-5 for depression score) and alcohol consumption was not only associated with anxiety, but related to depression. Besides, we found that relationship between alcohol consumption and hazard of anxiety/depression was significantly different for different SNPs genotypes, such as rs34505550 in TMOD1 (AA: OR = 1.03, P = 1.79 × 10-6; AG: OR = 1.00, P = 0.94; GG: OR = 1.00, P = 0.21) for self-reported anxiety. LIMITATIONS: The identified 3'aQTLs-alcohol consumption/smoking interactions were associated with depression and anxiety, and its potential biological mechanisms need to be further revealed. CONCLUSIONS: Our study identified important interactions between candidate 3'aQTL and alcohol consumption/smoking on depression and anxiety, and found that the 3'aQTL may modify the associations between consumption/smoking with depression and anxiety. These findings may help to further explore the pathogenesis of depression and anxiety.

Association between electronic device use and health status among a middle-aged and elderly population: a cross-sectional analysis in the UK Biobank.

Aim: Few previous studies have investigated the impact of multiple types of electronic devices on health status, and the moderating effects of gender, age, and BMI. Our aim is to examine the relationships between the use of four types of electronics and three health status indicators in a middle-aged and elderly population, and how these relationships varied by gender, age, and BMI. Subject and methods: Using data from 376,806 participants aged 40-69 years in the UK Biobank, we conducted a multivariate linear regression to estimate the association between electronic device use and health status. Electronics use was categorized as TV watching, computer use, computer gaming, and mobile phone use, and health status included self-rated health (SRH), multisite chronic pain (MCP), and total physical activity (TPA). Interaction terms were utilized to assess whether the above associations were modified by BMI, gender, and age. Further stratified analysis was performed to explore the role of gender, age, and BMI. Results: Higher levels of TV watching (BSRH = 0.056, BMCP = 0.044, BTPA= -1.795), computer use (BSRH = 0.007, BTPA= -3.469), and computer gaming (BSRH = 0.055, BMCP = 0.058, BTPA= -6.076) were consistently associated with poorer health status (all P < 0.05). Contrastingly, earlier exposure to mobile phones (BSRH = -0.048, BTPA= 0.933, BMCP = 0.056) was inconsistent with health (all P < 0.05). Additionally, BMI (Bcomputer use-SRH= 0.0026, Bphone-SRH= 0.0049, BTV-MCP= 0.0031, and BTV-TPA= -0.0584) exacerbated the negative effects of electronics use, and male (Bphone-SRH = -0.0414, Bphone-MCP = -0.0537, Bphone-TPA= 2.8873) were healthier with earlier exposure to mobile phones (all P < 0.05). Conclusion: Our findings suggest that the adverse health effects associated with watching TV, computer use, and computer gaming were consistent and were moderated by BMI, gender, and age, which advances a comprehensive understanding of the association between multiple types of electronic devices and health status, and provides new perspectives for future research. Supplementary Information: The online version contains supplementary material available at 10.1007/s10389-023-01886-5.

Combined effects of inflammation and coronavirus disease 2019 (COVID-19) on the risks of anxiety and depression: A cross-sectional study based on UK Biobank.

Infection-induced perturbation of immune homeostasis could promote psychopathology. Psychiatric sequelae have been observed after previous coronavirus outbreaks. However, limited studies were conducted to explore the potential interaction effects of inflammation and coronavirus disease 2019 (COVID-19) on the risks of anxiety and depression. In this study, first, polygenic risk scores (PRS) were calculated for eight COVID-19 clinical phenotypes using individual-level genotype data from the UK Biobank. Then, linear regression models were developed to assess the effects of COVID-19 PRS, C-reactive protein (CRP), systemic immune inflammation index (SII), and their interaction effects on the Generalized Anxiety Disorder-7 (GAD-7, 104 783 individuals) score and the Patient Health Questionnaire-9 (PHQ-9, 104 346 individuals) score. Several suggestive interactions between inflammation factors and COVID-19 clinical phenotypes were detected for PHQ-9 score, such as CRP/SII × Hospitalized/Not_Hospitalized in women group and CRP × Hospitalized/Unscreened in age >65 years group. For GAD-7 score, we also found several suggestive interactions, such as CRP × Positive/Unscreened in the age ≤65 years group. Our results suggest that not only COVID-19 and inflammation have important effects on anxiety and depression but also the interactions of COVID-19 and inflammation have serious risks for anxiety and depression.

Evaluating the role of anxiety on the association between irritable bowel syndrome and brain volumes: a mediation analysis in the UK Biobank cohort.

There is a strong link between irritable bowel syndrome and brain volumes, yet, to date, research examining the mediators of this association has been little. Based on the phenotypic data of 15 248 participants from the UK Biobank, a two-stage mediation analysis was performed to assess the association among brain volumes, anxiety, and irritable bowel syndrome. In the first stage, we identified the candidate mediating role of anxiety for irritable bowel syndrome associated with brain volumes using regression models. Then, we quantified the magnitude of the mediation effects by evaluating the average causal-mediated effect and proportion of mediation through performing mediation analyses in the R package in the second stage. In the first stage, we identified the partly mediating role of anxiety in the association between irritable bowel syndrome and the volume of thalamus (P left = 1.16 × 10-4, P right = 2.41 × 10-4), and grey matter (P left = 3.22 × 10-2, P right = 1.18 × 10-2) in the VIIIa cerebellum. In the second stage, we observed that the proportion of the total effect of irritable bowel syndrome on volume of thalamus mediated by anxiety was 14.3% for the left region (ß Average causal-mediated effect = -0.008, P Average causal-mediated effect = 0.004) and 14.6% for the right region (ß Average causal-mediated effect = -0.007, P Average causal-mediated effect = 0.006). Anxiety mediated 30.8% for the left region (ß Average causal-mediated effect = -0.013, P Average causal-mediated effect = 0.002) and 21.6% for the right region (ß Average causal-mediated effect = -0.010, P Average causal-mediated effect x= 0.018) of the total effect of irritable bowel syndrome on the volume of grey matter in the VIIIa cerebellum. Our study revealed the indirect mediating role of anxiety in the association between irritable bowel syndrome and brain volumes, promoting our understanding of the functional mechanisms of irritable bowel syndrome and its related psychosocial factors.

Identification of novel functional brain proteins for treatment-resistant schizophrenia: Based on a proteome-wide association study.

OBJECTIVE: Genetic approaches are increasingly advantageous in characterizing treatment-resistant schizophrenia (TRS). We aimed to identify TRS-associated functional brain proteins, providing a potential pathway for improving psychiatric classification and developing better-tailored therapeutic targets. METHODS: TRS-related proteome-wide association studies (PWAS) were conducted on genome-wide association studies (GWAS) from CLOZUK and the Psychiatric Genomics Consortium (PGC), which provided TRS individuals (n = 10,501) and non-TRS individuals (n = 20,325), respectively. The reference datasets for the human brain proteome were obtained from ROS/MAP and Banner, with 8,356 and 11,518 proteins collected, respectively. We then performed colocalization analysis and functional enrichment analysis to further explore the biological functions of the proteins identified by PWAS. RESULTS: In PWAS, two statistically significant proteins were identified using the ROS/MAP and then replicated using the Banner reference dataset, including CPT2 (PPWAS-ROS/MAP = 4.15 × 10-2 and PPWAS-Banner = 3.38 × 10-3) and APOL2 (PPWAS-ROS/MAP = 4.49 × 10-3 and PPWAS-Banner = 8.26 × 10-3). Colocalization analysis identified three variants that were causally related to protein expression in the human brain, including CCDC91 (PP4 = 0.981), PRDX1 (PP4 = 0.894), and WARS2 (PP4 = 0.757). We extended PWAS results from gene-based analysis to pathway-based analysis, identifying 14 gene ontology (GO) terms and the only candidate pathway for TRS, metabolic pathways (all P < 0.05). CONCLUSIONS: Our results identified two protein biomarkers, and cautiously support that the pathological mechanism of TRS is linked to lipid oxidation and inflammation, where mitochondria-related functions may play a role.

Assessing the effect of interaction between lifestyle and longitudinal changes in brain structure on sleep phenotypes.

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 × longitudinal changes in brain structure interactions were detected for 5 sleep phenotypes, such as physical activity×caudate_age2 for daytime dozing (OR = 1.0389, P = 8.84 × 10-3) in total samples, coffee intake×cerebellar white matter volume_age2 for daytime dozing (OR = 0.9652, P = 1.13 × 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.

Assessing the effect of interaction between gut microbiome and inflammatory bowel disease on the risks of depression.

Background: Gut microbiome and inflammatory bowel disease (IBD) are implicated in the development of depression, but the effect of their interactions on the risk of depression remains unclear. We aim to analyze the effect of interactions between gut microbiome and IBD on the risk of depression, and explore candidate genes involving the interactions. Methods: Using the individual genotype and depression traits data from the UK Biobank, we calculated the polygenetic risk scores (PRS) of 114 gut microbiome, ulcerative colitis (UC), Crohn's disease (CD), and total IBD (CD + UC) respectively. The effects of interactions between gut microbiome and IBD on depression were assessed through a linear regression model. Moreover, for observed significant interactions between gut microbiome PRS and IBD PRS, PLINK software was used to test pair-wise single nucleotide polymorphisms (SNPs) interaction of corresponding gut microbiome PRS and IBD PRS on depression. Results: We found 64 candidate interactions between gut microbiome and IBD on four phenotypes of depression, such as F_Lachnospiraceae (RNT) × (CD + UC) for patient health questionnaire-9 (PHQ-9) score (P = 1.48 × 10-3), F_Veillonellaceae (HB) × UC for self-reported depression (P = 2.83 × 10-3) and P_Firmicutes (RNT) × CD for age at first episode of depression (P = 8.50 × 10-3). We observed interactions of gut-microbiome-associated SNPs × IBD-associated SNPs, such as G_Alloprevotella (HB)-associated rs147650986 (GPM6A) × IBD-associated rs114471990 (QRICH1) (P = 2.26 × 10-4). Conclusion: Our results support the effects of interactions between gut microbiome and IBD on depression risk, and reported several novel candidate genes for depression.

Association between telomere length and insomnia: A mendelian randomization and colocalization study.

BACKGROUND: Previous studies have suggested a potential association between sleep and telomere length (TL), but its genetic basis remains unclear. In this study, we aimed to explore the genetic correlation and potential causal association between TL and insomnia. METHODS: The genome-wide association study (GWAS) datasets of TL and insomnia-related traits were used, including insomnia, snoring, daytime dozing and napping. Based on the polygenic risk scores (PRS) of TL, linear regression and linkage disequilibrium score (LDSC) regression were used to preliminarily explore the association between TL and insomnia parameters in the UK Biobank cohort. Then, we investigated the causal association between TL and insomnia by mendelian randomization (MR) analysis and colocalization analysis. RESULTS: In the UK Biobank cohort, the association between TL and insomnia was observed in the female samples (t = 2.968, P = 3.00 × 10-3). LDSC detected a genetic correlation between short TL and insomnia (Rg = -9.27 × 10-2, P = 8.00 × 10-4). We found no evidence supporting significant causal association between insomnia and TL in IVW method (b = -5.95 × 10-3, P = 0.57), with horizontal pleiotropy and heterogeneity tests indicating the validity of our MR study. Finally, rs12638862 was classified as colocalized by COLOC (PP4 = 0.99), and TERC may be involved in regulating the association between insomnia and TL. CONCLUSIONS: Our study found no evidence for causal association between insomnia and TL in individuals of European ancestry. We detected a candidate gene associated with both insomnia and TL, providing novel clues for understanding the roles of this association.

[The TCR repertoire diversity and its application in the prevention and treatment of lung cancer].

Immune checkpoint inhibitors have become the standard for advanced lung cancer treatment, but their effect on the prevention of lung cancer metastasis is still unclear. T-cell receptors (TCRs) are key "signal sensors" that recognize neoantigens on the surface of cancer cells. This review summarizes the research progress of TCR-T cell therapy in the prevention and treatment of lung cancer from the perspective of the diversity of TCR repertoire and the mechanism of tumor antigen recognition, in order to improve the efficacy of the prevention and treatment of lung cancer metastasis.

Fluorine impairs carboxylesterase 1-mediated hydrolysis of T-2 toxin and increases its chondrocyte toxicity.

Background: T-2 toxin is recognized as one of the high-risk environmental factors for etiology and pathogenesis of Kashin-Beck disease (KBD). Previous evidence indicates decreased serum fluorine level in KBD patients. However, whether fluoride could regulate carboxylesterase 1 (CES1)-mediated T-2 toxin hydrolysis and alter its chondrocyte toxicity remains largely unknown. Methods: In this study, in vitro hydrolytic kinetics were explored using recombinant human CES1. HPLC-MS/MS was used to quantitative determination of hydrolytic metabolites of T-2 toxin. HepG2 cells were treated with different concentration of sodium fluoride (NaF). qRT-PCR and western blot analysis were used to compare the mRNA and protein expression levels of CES1. C28/I2 cells were treated with T-2 toxin, HT-2 toxin, and neosolaniol (NEO), and then cell viability was determined by MTT assay, cell apoptosis was determined by Annexin V-FITC/PI, Hoechst 33258 staining, and cleaved caspase-3, and cell cycle was monitored by flow cytometry assay, CKD4 and CDK6. Results: We identified that recombinant human CES1 was involved in T-2 toxin hydrolysis to generate HT-2 toxin, but not NEO, and NaF repressed the formation of HT-2 toxin. Both mRNA and protein expression of CES1 were significantly down-regulated in a dose-dependent manner after NaF treatment in HepG2 cells. Moreover, we evaluated the chondrocyte toxicity of T-2 toxin and its hydrolytic metabolites. Results showed that T-2 toxin induced strongest cell apoptosis, followed by HT-2 toxin and NEO. The decreased the proportion of cells in G0/G1 phase was observed with the descending order of T-2 toxin, HT-2 toxin, and NEO. Conclusions: This study reveals that CES1 is responsible for the hydrolysis of T-2 toxin, and that fluoride impairs CES1-mediated T-2 toxin detoxification to increase its chondrocyte toxicity. This study provides novel insight into understanding the relationship between fluoride and T-2 toxin in the etiology of KBD.

Identification of Human Brain Proteins for Bitter-Sweet Taste Perception: A Joint Proteome-Wide and Transcriptome-Wide Association Study.

Objective: Bitter or sweet beverage perception is associated with alterations in brain structure and function. Our aim is to analyze the genetic association between bitter or sweet beverage perception and human brain proteins. Materials and methods: In our study, 8356 and 11,518 proteins were first collected from two reference datasets of human brain proteomes, the ROS/MAP and Banner. The bitter or sweet beverage perception-related proteome-wide association studies (PWAS) were then conducted by integrating recent genome-wide association study (GWAS) data (n = 422,300) of taste perception with human brain proteomes. The human brain gene expression profiles were collected from two reference datasets, including the brain RNA-seq (CBR) and brain RNA-seq splicing (CBRS). The taste perception-related transcriptome-wide association studies (TWAS) were finally performed by integrating the same GWAS data with human brain gene expression profiles to validate the PWAS findings. Results: In PWAS, four statistically significant proteins were identified using the ROS/MAP and then replicated using the Banner reference dataset (all permutated p < 0.05), including ABCG2 for total bitter beverages and tea, CPNE1 for total bitter beverage, ACTR1B for artificially sweetened beverages, FLOT2 for alcoholic bitter beverages and total sweet beverages. In TWAS analysis, six statistically significant genes were detected by CBR and confirmed by the CBRS reference dataset (all permutated p < 0.05), including PIGG for total bitter beverages and non-alcoholic bitter beverages, C3orf18 for total bitter beverages, ZSWIM7 for non-alcoholic bitter beverages, PEX7 for coffee, PKP4 for tea and RPLP2 for grape juice. Further comparison of the PWAS and TWAS found three common statistically significant proteins/genes identified from the Banner and CBR reference datasets, including THBS4 for total bitter beverages, CA4 for non-alcoholic bitter beverages, LIAS for non-grape juices. Conclusions: Our results support the potential effect of bitter or sweet beverage perception on brain function and identify several candidate brain proteins for bitter or sweet beverage perception.