Enhanced polygenic risk score incorporating gene-environment interaction suggests the association of major depressive disorder with cardiac and lung function.

BACKGROUND: Depression has been linked to an increased risk of cardiovascular and respiratory diseases; however, its impact on cardiac and lung function remains unclear, especially when accounting for potential gene-environment interactions. METHODS: We developed a novel polygenic and gene-environment interaction risk score (PGIRS) integrating the major genetic effect and gene-environment interaction effect of depression-associated loci. The single nucleotide polymorphisms (SNPs) demonstrating major genetic effect or environmental interaction effect were obtained from genome-wide SNP association and SNP-environment interaction analyses of depression. We then calculated the depression PGIRS for non-depressed individuals, using smoking and alcohol consumption as environmental factors. Using linear regression analysis, we assessed the associations of PGIRS and conventional polygenic risk score (PRS) with lung function (N = 42 886) and cardiac function (N = 1791) in the subjects with or without exposing to smoking and alcohol drinking. RESULTS: We detected significant associations of depression PGIRS with cardiac and lung function, contrary to conventional depression PRS. Among smokers, forced vital capacity exhibited a negative association with PGIRS (ß = -0.037, FDR = 1.00 × 10-8), contrasting with no significant association with PRS (ß = -0.002, FDR = 0.943). In drinkers, we observed a positive association between cardiac index with PGIRS (ß = 0.088, FDR = 0.010), whereas no such association was found with PRS (ß = 0.040, FDR = 0.265). Notably, in individuals who both smoked and drank, forced expiratory volume in 1-second demonstrated a negative association with PGIRS (ß = -0.042, FDR = 6.30 × 10-9), but not with PRS (ß = -0.003, FDR = 0.857). CONCLUSIONS: Our findings underscore the profound impact of depression on cardiac and lung function, highlighting the enhanced efficacy of considering gene-environment interactions in PRS-based studies.

A genome-wide association study identifies candidate genes for sleep disturbances in depressed individuals.

OBJECTIVE: This study aimed to identify candidate loci and genes related to sleep disturbances in depressed individuals and clarify the co-occurrence of sleep disturbances and depression from the genetic perspective. METHODS: The study subjects (including 58,256 self-reported depressed individuals and 6,576 participants with PHQ-9 score ≥ 10, respectively) were collected from the UK Biobank, which were determined based on the Patient Health Questionnaire (PHQ-9) and self-reported depression status, respectively. Sleep related traits included chronotype, insomnia, snoring and daytime dozing. Genome-wide association studies (GWASs) of sleep related traits in depressed individuals were conducted by PLINK 2.0 adjusting age, sex, Townsend deprivation index and 10 principal components as covariates. The CAUSALdb database was used to explore the mental traits associated with the candidate genes identified by the GWAS. RESULTS: GWAS detected 15 loci significantly associated with chronotype in the subjects with self-reported depression, such as rs12736689 at RNASEL (P = 1.00 × 10- 09), rs509476 at RGS16 (P = 1.58 × 10- 09) and rs1006751 at RFX4 (P = 1.54 × 10- 08). 9 candidate loci were identified in the subjects with PHQ-9 ≥ 10, of which 2 loci were associated with insomnia such as rs115379847 at EVC2 (P = 3.50 × 10- 08), and 7 loci were associated with daytime dozing, such as rs140876133 at SMYD3 (P = 3.88 × 10- 08) and rs139156969 at ROBO2 (P = 3.58 × 10- 08). Multiple identified genes, such as RNASEL, RGS16, RFX4 and ROBO2 were reported to be associated with chronotype, depression or cognition in previous studies. CONCLUSION: Our study identified several candidate genes related to sleep disturbances in depressed individuals, which provided new clues for understanding the biological mechanism underlying the co-occurrence of depression and sleep disorders.

Epigenetic analysis suggests aberrant cerebellum brain aging in old-aged adults with autism spectrum disorder and schizophrenia.

The aberrant aging hypothesis of schizophrenia (SCZ) and autism spectrum disorder (ASD) has been proposed, and the DNA methylation (DNAm) clock, which is a cumulative evaluation of DNAm levels at age-related CpGs, could serve as a biological aging indicator. This study evaluated epigenetic brain aging of ASD and SCZ using Horvath's epigenetic clock, based on two public genome-wide DNA methylation datasets of post-mortem brain samples (NASD = 222; NSCZ = 142). Total subjects were further divided into subgroups by gender and age. The epigenetic age acceleration (AgeAccel) for each sample was calculated as the residual value resulting from the regression model and compared between groups. Results showed DNAm age has a strong correlation with chronological age in both datasets across multiple brain regions (P < 0.05). When divided into equally sized age groups, the AgeAccel of the cerebellum (CB) region from people over 45 years of age was greater compared to the control sample (AgeAccel of ASD vs control: 5.069 vs -6.249; P < 0.001). And a decelerated epigenetic aging process was observed in the CB region of individuals with SCZ aged 50-70 years (AgeAccel of SCZ vs control: -3.171 vs 2.418; P < 0.05). However, our results showed no significant difference in AgeAccel between ASD and control groups, and between SCZ and control groups in the total and gender-specific groups (P > 0.05). This study's results revealed some evidence for aberrant epigenetic CB brain aging in old-aged patients with ASD and SCZ, indicating a different pattern of CB aging in older adults with these two diseases. However, further studies of larger ASD and SCZ cohorts are necessary to make definitive conclusions on this observation.

Whole-Transcriptome Sequencing of Knee Joint Cartilage from Kashin-Beck Disease and Osteoarthritis Patients.

The aim of this study was to provide a comprehensive understanding of similarities and differences in mRNAs, lncRNAs, and circRNAs within cartilage for Kashin-Beck disease (KBD) compared to osteoarthritis (OA). We conducted a comparison of the expression profiles of mRNAs, lncRNAs, and circRNAs via whole-transcriptome sequencing in eight KBD and ten OA individuals. To facilitate functional annotation-enriched analysis for differentially expressed (DE) genes, DE lncRNAs, and DE circRNAs, we employed bioinformatic analysis utilizing Gene Ontology (GO) and KEGG. Additionally, using quantitative reverse transcriptase polymerase chain reaction (qRT-PCR), we validated the expression levels of four cartilage-related genes in chondrocytes. We identified a total of 43 DE mRNAs, 1451 DE lncRNAs, and 305 DE circRNAs in KBD cartilage tissue compared to OA (q value < 0.05; |log2FC| > 1). We also performed competing endogenous RNA network analysis, which identified a total of 65 lncRNA-mRNA interactions and 4714 miRNA-circRNA interactions. In particular, we observed that circRNA12218 had binding sites for three miRNAs targeting ACAN, while circRNA12487 had binding sites for seven miRNAs targeting COL2A1. Our results add a novel set of genes and non-coding RNAs that could potentially serve as candidate diagnostic biomarkers or therapeutic targets for KBD patients.

Involvement of Yes-Associated Protein 1 Activation in the Matrix Degradation of Human-Induced-Pluripotent-Stem-Cell-Derived Chondrocytes Induced by T-2 Toxin and Deoxynivalenol Alone and in Combination.

T-2 toxin and deoxynivalenol (DON) are two prevalent mycotoxins that cause cartilage damage in Kashin-Beck disease (KBD). Cartilage extracellular matrix (ECM) degradation in chondrocytes is a significant pathological feature of KBD. It has been shown that the Hippo pathway is involved in cartilage ECM degradation. This study aimed to examine the effect of YAP, a major regulator of the Hippo pathway, on the ECM degradation in the hiPS-derived chondrocytes (hiPS-Ch) model of KBD. The hiPS-Ch injury models were established via treatment with T-2 toxin/DON alone or in combination. We found that T-2 toxin and DON inhibited the proliferation of hiPS-Ch in a dose-dependent manner; significantly increased the levels of YAP, SOX9, and MMP13; and decreased the levels of COL2A1 and ACAN (all p values < 0.05). Immunofluorescence revealed that YAP was primarily located in the nuclei of hiPS-Ch, and its expression level increased with toxin concentrations. The inhibition of YAP resulted in the dysregulated expression of chondrogenic markers (all p values < 0.05). These findings suggest that T-2 toxin and DON may inhibit the proliferation of, and induce the ECM degradation, of hiPS-Ch mediated by YAP, providing further insight into the cellular and molecular mechanisms contributing to cartilage damage caused by toxins.

Assessing the interaction effects of brain structure longitudinal changes and life environmental factors on depression and anxiety.

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 × cerebellum white matter 3 (WM; beta = -.003, p = .018 for depression; beta = -003, p = .008 for anxiety) and maternal smoking × 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 × 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.

Evaluating the interactive effects of dietary habits and human gut microbiome on the risks of depression and anxiety.

BACKGROUND: Gut microbiome and dietary patterns have been suggested to be associated with depression/anxiety. However, limited effort has been made to explore the effects of possible interactions between diet and microbiome on the risks of depression and anxiety. METHODS: Using the latest genome-wide association studies findings in gut microbiome and dietary habits, polygenic risk scores (PRSs) analysis of gut microbiome and dietary habits was conducted in the UK Biobank cohort. Logistic/linear regression models were applied for evaluating the associations for gut microbiome-PRS, dietary habits-PRS, and their interactions with depression/anxiety status and Patient Health Questionnaire (PHQ-9)/Generalized Anxiety Disorder-7 (GAD-7) score by R software. RESULTS: We observed 51 common diet-gut microbiome interactions shared by both PHQ score and depression status, such as overall beef intake × genus Sporobacter [hurdle binary (HB)] (PPHQ = 7.88 × 10-4, Pdepression status = 5.86 × 10-4); carbohydrate × genus Lactococcus (HB) (PPHQ = 0.0295, Pdepression status = 0.0150). We detected 41 common diet-gut microbiome interactions shared by GAD score and anxiety status, such as sugar × genus Parasutterella (rank normal transformed) (PGAD = 5.15 × 10-3, Panxiety status = 0.0347); tablespoons of raw vegetables per day × family Coriobacteriaceae (HB) (PGAD = 6.02 × 10-4, Panxiety status = 0.0345). Some common significant interactions shared by depression and anxiety were identified, such as overall beef intake × genus Sporobacter (HB). CONCLUSIONS: Our study results expanded our understanding of how to comprehensively consider the relationships for dietary habits-gut microbiome interactions with depression and anxiety.

Identifying Candidate Genes Associated with Sporadic Amyotrophic Lateral Sclerosis via Integrative Analysis of Transcriptome-Wide Association Study and Messenger RNA Expression Profile.

Amyotrophic lateral sclerosis, a fatal neurodegeneration disease affecting motor neurons in the brain and spinal cord, is difficult to diagnose and treat. The objective of this study is to identify novel candidate genes related to ALS. Transcriptome-wide association study of ALS was conducted by integrating the genome-wide association study summary data (including 1234 ALS patients and 2850 controls) and pre-computed gene expression weights of different tissues. The ALS-associated genes identified by TWAS were further compared with the differentially expressed genes detected by the mRNA expression profiles of the sporadic ALS. Functional enrichment and annotation analysis of identified genes were performed by an R package and the functional mapping and annotation software. TWAS identified 761 significant genes (PTWAS < 0.05), 627 Gene ontology terms, and 8 Kyoto Encyclopedia of Genes and Genomes pathways for ALS, such as C9orf72, with three expression quantitative trait loci were found significantly: rs2453554 (PTWAS CBRS = 4.68 × 10-10, PTWAS CBRS = 2.54 × 10-9), rs10967976 (PTWAS CBRS = 7.85 × 10-10, PTWAS CBRS = 8.91 × 10-9, PTWAS CBRS = 1.49 × 10-7, PTWAS CBRS = 5.59 × 10-7), rs3849946 (PTWAS CBRS = 7.69 × 10-4, PTWAS YBL = 4.02 × 10-2), Mitochondrion (Padj = 4.22 × 10-16), and Cell cycle (Padj = 2.04 × 10-3). Moreover, 107 common genes, 4 KEGG pathways and 41 GO terms were detected by integrating mRNA expression profiles of sALS, such as CPVL (FC = 2.06, PmRNA = 6.99 × 10-6, PTWAS CBR = 2.88 × 10-2, PTWAS CBR = 4.37 × 10-2), Pyrimidine Metabolism (Padj = 2.43 × 10-2), and Cell Activation (Padj = 5.54 × 10-3). Multiple candidate genes and pathways were detected for ALS. Our findings may provide novel clues for understanding the genetic mechanism of ALS.

Exome-wide screening identifies novel rare risk variants for major depression disorder.

Despite thousands of common genetic loci of major depression disorders (MDD) have been identified by GWAS to date, a large proportion of genetic variation predisposing to MDD remains unaccounted for. By utilizing the newly released UK Biobank 200,643 exome dataset, we conducted an exome-wide association study to identify rare risk variants contributing to MDD. After quality control, 120,033 participants with MDD polygenic risk scores (PRS) values were included. The individuals with lower 30% quantile of the PRS value were filtered for case and control selecting. Then the cases were set as the individuals with upper 10% quantile of the PHQ depression score and lower 10% quantile were set as controls. Finally, 1612 cases and 1612 controls were included in this study. The variants were annotated by ANNOVRA software. After exclusions, 34,761 qualifying variants, including 148 frameshift variant, 335 non-frameshift variant, 33,758 nonsynonymous, 91 start-loss, 393 stop-gain, 36 stop-loss variants were imported into the SKAT R-package to perform single variants, gene-based burden and robust burden tests with minor allele frequency (MAF) < 0.01. Single variant association testing identified one variant, rs4057749 (P = 5.39 × 10-9), within OR8B4 gene at an exome-wide significance level. The gene-based burden test of the exonic variants identified genome-wide significant associations in OR8B4 (PSKAT = 6.23 × 10-5, PSKAT Robust = 4.49 × 10-5), TRAPPC11 (PSKAT = 0.014, PSKAT Robust = 0.015), SBK3 (PSKAT = 0.020, PSKAT Robust = 0.025) and TNRC6B (PSKAT = 0.026, PSKAT Robust = 0.036). We identified multiple novel rare risk variants contributing to MDD in the individuals with lower PRS of MDD. The findings can help to broaden the genetic insights of the MDD pathogenesis.

Treatment Resistance in Schizophrenia Is Associated with Attention Deficit/Hyperactivity Disorder and Gut Microbiota: A Genetic Correlation and Mendelian Randomization Study.

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 = ∼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.

Maternal smoking around birth may lower the protective effects of breastfeeding on anxiety, depression and neuroticism in adult offspring: a UK biobank study.

We aim to explore the combined effects of the smoking and breastfeeding on offspring mental health outcomes. We used data from UK biobank (N = 342,846) to evaluate joint effect of breastfeeding and maternal smoke during pregnancy (MSDP) on seven adult offspring mental health outcomes (self-reported depression, depression score, self-reported anxiety, anxiety score, neuroticism score, self-harm, suicide). We stratified individuals to MSDP group and non-MSDP group as well as breastfeeding group and non-breastfeeding group. Multiple linear regression and logistic regressions analysis were performed between independent variables (MSDP or breastfeeding) and dependent variables separately (seven mental health outcomes) in each stratum. Effect estimates were expressed as ß values and OR values. Sex, age, 10 principle components of population structure, smoking, alcohol use, and Townsend deprivation index were examined as covariates. At MSDP grouping level, coefficients (odds ratio [OR]) for association of breastfed as a baby with self-reported anxiety (category variable) were 0.87 (95%CI, (0.82-0.93), P = 1.74 × 10-5) in the MSDP group and 0.83 (95%CI, (0.79-0.87), P = 2.76 × 10-17) in the non-MSDP group. At breastfeeding grouping level, OR for association of MSDP and self-reported anxiety were 1.15 (95%CI, (1.10-1.20), P = 5.36 × 10-11) in breastfeeding group and 1.12(95%CI, (1.06-1.20), P = 2.02 × 10-4) in non-breastfeeding group. At MSDP grouping level, negatively associations were found for breastfeeding and anxiety score (continuable variable) in MSDP group (-0.04 SD change per SD change in MSDP, 95% CI, (- 0.06, - 0.02), P = 2.42 × 10-3) and non-MSDP group (-0.06 SD change per SD change in MSDP, 95%CI, (- 0.07, - 0.04), P = 1.70 × 10-11). At breastfeeding grouping level, positive association was found for MSDP and anxiety score in the breastfeeding group (0.07 SD change per SD change in MSDP, 95%CI, (0.06-0.09), P = 1.49 × 10-20) and non-breastfeeding group (0.07 SD change per SD change in MSDP, 95%CI, (0.05-0.09), P = 7.19 × 10-8). Compared with non-MSDP group, the protective effect (reflected by coefficients) of breastfeeding on anxiety in the MSDP decreased. Our preliminary study found MSDP may lower the protective effect of breastfeeding on the adult offspring anxiety, depression and neuroticism, providing useful recommendations for health care service via quitting smoking during pregnancy and encouraging prolonged breastfeeding.

Association between birth by caesarian section and anxiety, self-harm: a gene-environment interaction study using UK Biobank data.

BACKGROUND: Limited efforts have been paid to explore the underlying genetic mechanisms of birth by caesarian section (CS) affecting the risks of adult anxiety and self-harm. METHODS: Using UK Biobank cohort, the logistic regression model was first applied to evaluate the associations of adult anxiety and self-harm with birth by CS. Using birth by CS as exposure variables, genome-wide by environment interaction study (GWEIS) was then applied by PLINK2.0 to identify associated genes interacting with birth by CS for anxiety and self-harm. RESULTS: In the observational study, significant associations were observed between birth by CS and anxiety (odds ratio (OR) = 1.24; 95% confidence interval (CI), 1.12-1.38; P = 4.86 × 10- 5), and self-harm (OR = 1.12; 95% CI, 1.01-1.24; P = 2.90 × 10- 2). GWEIS revealed multiple suggestive genes interacted with birth by CS for anxiety, such as DKK2 (rs13137764, P = 1.24 × 10- 9, adjusted P = 2.68 × 10- 7) and ATXN1 (rs62389045, P = 4.38 × 10- 8, adjusted P = 3.55 × 10- 6). For self-harm, significant gene-environment interactions of birth by CS on self-harm were detected, such as ALDH1A2 (rs77828167, P = 1.62 × 10- 8; rs116899929, P = 1.92 × 10- 8) and DAB1 (rs116124269, P = 3.20 × 10- 8; rs191070006, P = 3.63 × 10- 8). CONCLUSIONS: Our results suggested that birth by CS was associated with the risk of adult anxiety and self-harm. We also discovered some genes interacted with birth by CS might influence the risk of anxiety and self-harm, which may provide novel clues for the pathogenesis of those mental disorders.

WISP1 Is Involved in the Pathogenesis of Kashin-Beck Disease via the Autophagy Pathway.

OBJECTIVE: Kashin-Beck disease (KBD) is a kind of endemic and chronic osteochondropathy in China. This study aims to explore the functional relevance and potential mechanism of Wnt-inducible signaling pathway protein 1 (WISP1) in the pathogenesis of KBD. DESIGN: KBD and control cartilage specimens were collected for tissue section observation and primary chondrocyte culture. Firstly, the morphological and histopathological observations were made under a light and electron microscope. Then, the expression levels of WISP1 as well as molecular markers related to the autophagy pathway and extracellular matrix (ECM) synthesis were detected in KBD and control chondrocytes by qRT-PCR, Western blot, and immunohistochemistry. Furthermore, the lentiviral transfection technique was applied to make a WISP1 knockdown cell model based on KBD chondrocytes. In vitro intervention experiments were conducted on the C28/I2 human chondrocyte cell line using human recombinant WISP1 (rWISP1). RESULTS: The results showed that the autolysosome appeared in the KBD chondrocytes. The expression of WISP1 was significantly higher in KBD chondrocytes. Additionally, T-2 toxin, a risk factor for KBD onset, could up-regulate the expression of WISP1 in C28/I2. The autophagy markers ATG4C and LC3II were upregulated after the low-concentration treatment of T-2 toxin and downregulated after the high-concentration treatment. After knocking down WISP1 expression in KBD chondrocytes, MAP1LC3B decreased while ATG4C and COL2A1 increased. Moreover, the rWISP1 protein treatment in C28/I2 chondrocytes could upregulate the expression of ATG4C and LC3II at the beginning and downregulate them then. CONCLUSIONS: Our study suggested that WISP1 might play a role in the pathogenesis of KBD through autophagy.

Identifying psychiatric disorder-associated gut microbiota using microbiota-related gene set enrichment analysis.

Psychiatric disorders are a group of complex psychological syndromes with high prevalence. It has been reported that gut microbiota has a dominant influence on the risks of psychiatric disorders through gut microbiota-brain axis. We extended the classic gene set enrichment analysis (GSEA) approach to detect the association between gut microbiota and complex diseases using published genome-wide association study (GWAS) and GWAS of gut microbiota summary data. We applied our approach to real GWAS data sets of five psychiatric disorders, including attention deficiency/hyperactive disorder (ADHD), autism spectrum disorder (AUT), bipolar disorder (BD), schizophrenia (SCZ) and major depressive disorder (MDD). To evaluate the performance of our approach, we also tested the genetic correlations of obesity and type 2 diabetes with gut microbiota. We identified several significant associations between psychiatric disorders and gut microbiota, such as ADHD and genus Desulfovibrio (P = 0.031), order Clostridiales (P = 0.034). For AUT, association signals were observed for genera Bacteroides (P = 0.012) and Desulfovibrio (P = 0.033). Genus Desulfovibrio (P = 0.005) appeared to be associated with BD. For MDD, association signals were observed for genus Desulfovibrio (P = 0.003), order Clostridiales (P = 0.004), family Lachnospiraceae (P = 0.007) and genus Bacteroides (P = 0.007). Genus Desulfovibrio (P = 0.012) and genus Bacteroides (P = 0.038) appeared to be associated with SCZ. Our study results provide novel clues for revealing the roles of gut microbiota in psychiatric disorders. This study also illustrated the good performance of GSEA approach for exploring the relationships between gut microbiota and complex diseases.

Associations between electronic devices use and common mental traits: A gene-environment interaction model using the UK Biobank data.

BACKGROUND: Electronic devices use has been reported to be associated with depression. However, limited effort has been provided to elucidate the associations between electronic devices use and mental traits in interaction with genetic factors. METHODS: We first conducted an observational study consisting of 138 976-383 742 participants for TV watching, 29 636-38 599 participants for computer using and 118 61-330 985 participants for computer playing in the UK Biobank cohort. A linear regression model was used to evaluate the associations between common mental traits and electronic devices use. Subsequently, a genome-wide gene-environment interaction study (GWEIS) was performed by PLINK2.0 to estimate the interaction effects of genes and electronic devices use on the risks of the four mental traits. RESULTS: In the UK Biobank cohort, significant associations were observed between electronic devices use and mental traits (all P < 1.0 × 10-9 ), including depression score (B = 0.094 for TV watching), anxiety score (B = 0.051 for TV watching), cigarette smoking (B = 0.046 for computer using) and alcohol drinking (B = 0.010 for computer playing). GWEIS identified multiple mental traits associated loci, interacting with electronic devices use, such as DCDC2 (rs115986722, P = 4.10 × 10-10 ) for anxiety score and TV watching, PRKCE (rs56181965, P = 9.64 × 10-10 ) for smoking and computer using and FRMD4A (rs56227933, P = 7.42 × 10-11 ) for depression score and computer playing. CONCLUSIONS: Our findings suggested that electronic devices use was associated with common mental traits and provided new clues for understanding genetic architecture of mental traits.

Dissecting the association between psychiatric disorders and neurological proteins: a genetic correlation and two-sample bidirectional Mendelian randomization study.

OBJECTIVES: The role of neurological proteins in the development of bipolar disorder (BD) and schizophrenia (SCZ) remains elusive now. The current study aims to explore the potential genetic correlations of plasma neurological proteins with BD and SCZ. METHODS: By using the latest genome-wide association study (GWAS) summary data of BD and SCZ (including 41,917 BD cases, 11,260 SCZ cases, and 396,091 controls) derived from the Psychiatric GWAS Consortium website (PGC) and a recently released GWAS of neurological proteins (including 750 individuals), we performed a linkage disequilibrium score regression (LDSC) analysis to detect the potential genetic correlations between the two common psychiatric disorders and each of the 92 neurological proteins. Two-sample Mendelian randomisation (MR) analysis was then applied to assess the bidirectional causal relationship between the neurological proteins identified by LDSC, BD and SCZ. RESULTS: LDSC analysis identified one neurological protein, NEP, which shows suggestive genetic correlation signals for both BD (coefficient = -0.165, p value = 0.035) and SCZ (coefficient = -0.235, p value = 0.020). However, those association did not remain significant after strict Bonferroni correction. Two sample MR analysis found that there was an association between genetically predicted level of NEP protein, BD (odd ratio [OR] = 0.87, p value = 1.61 × 10-6) and SCZ (OR = 0.90, p value = 4.04 × 10-6). However, in the opposite direction, there is no genetically predicted association between BD, SCZ, and NEP protein level. CONCLUSION: This study provided novel clues for understanding the genetic effects of neurological proteins on BD and SCZ.

PCA-based GRS analysis enhances the effectiveness for genetic correlation detection.

Genetic risk score (GRS, also known as polygenic risk score) analysis is an increasingly popular method for exploring genetic architectures and relationships of complex diseases. However, complex diseases are usually measured by multiple correlated phenotypes. Analyzing each disease phenotype individually is likely to reduce statistical power due to multiple testing correction. In order to conquer the disadvantage, we proposed a principal component analysis (PCA)-based GRS analysis approach. Extensive simulation studies were conducted to compare the performance of PCA-based GRS analysis and traditional GRS analysis approach. Simulation results observed significantly improved performance of PCA-based GRS analysis compared to traditional GRS analysis under various scenarios. For the sake of verification, we also applied both PCA-based GRS analysis and traditional GRS analysis to a real Caucasian genome-wide association study (GWAS) data of bone geometry. Real data analysis results further confirmed the improved performance of PCA-based GRS analysis. Given that GWAS have flourished in the past decades, our approach may help researchers to explore the genetic architectures and relationships of complex diseases or traits.

Integrative Genomic Enrichment Analysis Identified the Brain Regions and Development Stages Related to Anorexia Nervosa and Obsessive-Compulsive Disorder.

Our aim is to explore the spatial and temporal features of anorexia nervosa (AN) and obsessive-compulsive disorder (OCD) considering different brain regions and development stages. The gene sets related to 16 brain regions and nine development stages were obtained from a brain spatial and temporal transcriptomic dataset. Using the genome-wide association study data, transcriptome-wide association study (TWAS) was conducted to identify the genes whose imputed expressions were associated with AN and OCD, respectively. The mRNA expression profiles were analyzed by GEO2R to obtain differentially expressed genes. Gene set enrichment analysis was conducted to detect the spatial and temporal features related to AN and OCD using the TWAS and mRNA expression analysis results. We observed multiple common association signals shared by TWAS and mRNA expression analysis of AN, such as the primary auditory cortex vs. cerebellar cortex in fetal development and earlier vs. later fetal development in the somatosensory cortex. For OCD, we also detected multiple common association signals, such as medial prefrontal cortex vs. amygdala in adulthood and fetal development vs. infancy in mediodorsal nucleus of thalamus. Our study provides novel clues for describing the spatial and temporal features of brain development in the pathogenesis of AN and OCD.

A Large-Scale Genetic Correlation Scan Between Intelligence and Brain Imaging Phenotypes.

Limited efforts have been paid to evaluate the potential relationships between structural and functional brain imaging and intelligence until now. We performed a two-stage analysis to systematically explore the relationships between 3144 brain image-derived phenotypes (IDPs) and intelligence. First, by integrating genome-wide association studies (GWAS) summaries data of brain IDPs and two GWAS summary datasets of intelligence, we systematically scanned the relationship between each of the 3144 brain IDPs and intelligence through linkage disequilibrium score regression (LDSC) analysis. Second, using the individual-level genotype and intelligence data of 160 124 subjects derived from UK Biobank datasets, polygenetic risk scoring (PRS) analysis was performed to replicate the common significant associations of the first stage. In the first stage, LDSC identified 6 and 2 significant brain IDPs significantly associated with intelligence dataset1 and dataset2, respectively. It is interesting that NET100_0624 showed genetic correlations with intelligence in the two datasets of intelligence. After adjusted for age and sex as the covariates, NET100_0624 (P = 5.26 × 10-20, Pearson correlation coefficients = -0.02) appeared to be associated with intelligence by PRS analysis of UK Biobank samples. Our findings may help to understand the genetic mechanisms of the effects of brain structure and function on the development of intelligence.

Genetic Correlation Analysis and Transcriptome-wide Association Study Suggest the Overlapped Genetic Mechanism between Gout and Attention-deficit Hyperactivity Disorder.

OBJECTIVES: Gout is a common inflammatory arthritis, which is caused by hyperuricemia. Limited efforts have been paid to systematically explore the relationships between gout and common psychiatric disorders. METHODS: Genome-wide association study summary data of gout were obtained from the GeneATLAS, which contained 452,264 participants including 3,528 gout cases. Linkage disequilibrium score regression (LDSC) was first conducted to evaluate the genetic relationships between gout and 5 common psychiatric disorders. Transcriptome-wide association studies (TWAS) was then conducted to explore the potential biological mechanism underlying the observed genetic correlation between gout and attention-deficit hyperactivity disorder (ADHD). The Database for Annotation, Visualization and Integrated Discovery online functional annotation system was applied for pathway enrichment analysis and gene ontology enrichment analysis. RESULTS: LDSC analysis observed significant genetic correlation between gout and ADHD (genetic correlation coefficients = 0.29, standard error = 0.09 and P value = 0.0015). Further TWAS of gout identified 105 genes with P value < 0.05 in muscle skeleton and 228 genes with P value < 0.05 in blood. TWAS of ADHD also detected 300 genes with P value < 0.05 in blood. Further comparing the TWAS results identified 9 common candidate genes shared by gout and ADHD, such as CD300C (Pgout = 0.0040; PADHD = 0.0226), KDM6B (Pgout = 0.0074; PADHD = 0.0460), and BST1 (Pgout = 0.0349; PADHD = 0.03560). CONCLUSION: We observed genetic correlation between gout and ADHD and identified multiple candidate genes for gout and ADHD.