Intratumor tertiary lymphatic structure evaluation predicts the prognosis and immunotherapy response of patients with colorectal cancer.

Background: Immune checkpoint therapy, involving the programmed cell death 1 (PD-1) monoclonal antibody, has revolutionized the treatment of cancer. Tertiary lymphatic structure (TLS) serves as an immune indicator to predict the efficacy of PD-1 antibody therapy. However, there is no clear result whether the distribution, quantity, and maturity of TLS can be effective indicators for predicting the clinical efficacy of anti-PD1 immunotherapy in patients with colorectal cancer (CRC). Methods: Fifty-seven patients who underwent surgical resection and thirty-nine patients who received anti-PD-1 immunotherapy were enrolled in this retrospective study. Immunohistochemical staining and multiple fluorescence immunohistochemistry were used to evaluate the mismatch repair (MMR) subtypes and TLS distribution, quantity, and maturity, respectively. Results: A comprehensive patient score system was built based on TLS quantity and maturity. We found that the proportion of patients with score >1 was much higher in the deficient mismatch repair(dMMR) group than in the proficient mismatch repair(pMMR) group, and this difference was mainly due to intratumoral TLS. Patient score, based on the TLS evaluation of whole tumor, peritumor, or intratumor, was used to evaluate the efficacy of anti-PD1 immunotherapy. Based only on the intratumor TLS evaluation, the proportion of patients with a score >1 was higher in the response (PR + CR) group than in the non-response (PD) group. Multivariate analysis revealed that patient scores were positively correlated with the clinical efficacy of immunotherapy. Further analysis of immune-related progression-free survival was performed in patients with CRC who received anti-PD-1 immunotherapy. Patients with score >1 based on the intratumor TLS evaluation had significantly better survival. Conclusions: These results suggest that the patient score based on intratumor TLS evaluation may be a good immune predictive indicator for PD-1 antibody therapy in patients with CRC.

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.

Mendelian randomization study of the relationship between blood and urine biomarkers and schizophrenia in the UK Biobank cohort.

BACKGROUND: The identification of suitable biomarkers is of crucial clinical importance for the early diagnosis of treatment-resistant schizophrenia (TRS). This study aims to comprehensively analyze the association between TRS and blood and urine biomarkers. METHODS: Candidate TRS-related single nucleotide polymorphisms (SNPs) were obtained from a recent genome-wide association study. The UK Biobank cohort, comprising 376,807 subjects with blood and urine biomarker testing data, was used to calculate the polygenic risk score (PRS) for TRS. Pearson correlation analyses were performed to evaluate the correlation between TRS PRS and each of the biomarkers, using calculated TRS PRS as the instrumental variables. Bidirectional two-sample Mendelian randomization (MR) was used to assess potential causal associations between candidate biomarkers with TRS. RESULTS: Here we identify a significant association between TRS PRS and phosphate (r = 0.007, P = 1.96 × 10-4). Sex subgroup analyses identify seven and three candidate biomarkers associated with TRS PRS in male and female participants, respectively. For example, total protein and phosphate for males, creatinine and phosphate for females. Bidirectional two-sample MR analyses indicate that TRS is negatively associated with cholesterol (estimate = -0.363, P = 0.008). Conversely, TRS is positively associated with total protein (estimate = 0.137, P = 0.027), mean corpuscular volume (estimate = 0.032, P = 2.25 × 10-5), and mean corpuscular hemoglobin (estimate = 0.018, P = 0.007). CONCLUSIONS: Our findings provide insights into the roles of blood and urine biomarkers in the early detection and treatment of TRS.

People with schizophrenia experience periods of time during which they misperceive reality. Some people with schizophrenia do not respond well to the usual drugs that are used to relieve their symptoms. This type of schizophrenia is known as treatment-resistant schizophrenia (TRS). We looked at differences in the genes (inherited characteristics), blood and urine of a group of people in the UK with schizophrenia to see if people with TRS have particular characteristics that would enable them to be distinguished from patients with schizophrenia who tend to respond to usual treatment. We found several differences in the blood that could be used to predict which people might get TRS, including some that were specific to men or women. These discoveries are important because they can help doctors identify people who are more likely to develop TRS earlier, enabling them to avoid using treatments that might not work well for them.

Effects of immunogenic cell death-inducing chemotherapeutics on the immune cell activation and tertiary lymphoid structure formation in melanoma.

Background: The infiltration and activation of immune cells in the tumor microenvironment (TIME) affect the prognosis of patients with cancer. Tertiary lymphoid structure (TLS) formation favors tumour- infiltrating-lymphocyte (TIL) recruitment and is regarded as an important indicator of good prognosis associated with immunotherapy in patients with tumors. Chemotherapy is currently one of the most commonly used clinical treatment methods. However, there have been no clear report to explore the effects of different types of chemotherapy on TLS formation in the TIME. This study examined the effects of immunogenic cell death (ICD)-inducing chemotherapeutics on immune cells, high-endothelial venules (HEV), and TLSs in mouse melanomas. Methods: Doxorubicin (an ICD inducer), gemcitabine (non-ICD inducer), and a combination of the two drugs was delivered intra-peritoneally to B16F1-loaded C57BL/6 mice. The infiltration of immune cells into tumor tissues was evaluated using flow cytometry. HEV and TLS formation was assessed using immunohistochemistry and multiple fluorescent immunohistochemical staining. Results: Doxorubicin alone, gemcitabine alone, and the two-drug combination all slowed tumor growth, with the combined treatment demonstrating a more pronounced effect. Compared with the control group, the doxorubicin group showed a higher infiltration of CD8+ T cells and tissue-resident memory T cells (TRM) and an increase in the secretion of interferon-γ, granzyme B, and perforin in CD8+ T subsets and activation of B cells and dendritic cells. Doxorubicin alone and in combination with gemcitabine decreased regulatory T cells in the TIME. Moreover, doxorubicin treatment promoted the formation of HEV and TLS. Doxorubicin treatment also upregulated the expression of programmed cell death protein (PD)-1 in CD8+ T cells and programmed cell death protein ligand (PD-L)1 in tumor cells. Conclusions: These results indicate that doxorubicin with an ICD reaction promotes TLS formation and increases PD-1/PD-L1 expression in tumor tissues. The results demonstrate the development of a therapeutic avenue using combined immune checkpoint therapy.

Immune checkpoint ligands expressed on mature high endothelial venules predict poor prognosis of NSCLC: have a relationship with CD8+ T lymphocytes infiltration.

Background: An insufficient number of intratumoral CD8+ T lymphocytes is a major barrier to antitumor immunity and immunotherapy. High endothelial venules (HEVs) are the major sites through which lymphocytes enter tumors; however, the molecular mechanism through which HEVs mediate CD8+ T lymphocyte infiltration remains poorly understood. Methods: Forty-two patients with stage IIIA lung adenocarcinoma, who underwent surgery, were recruited. Multiplex immunohistochemical staining was conducted on tumor tissues to detect the immune checkpoint ligands (ICLs) expressed in the HEVs, blood vessels, and lymphatics. A new ICL score model was constructed to evaluate ligand expression. The relationship between ICL score, tumor-infiltrating CD8+ T cell frequency, and survival of patients was investigated. Results: Mature HEVs, but not blood vessels or lymphatics, mediated CD8+ T cell infiltration. However, the ICLs expressed on mature HEVs could negatively regulate CD8+ T cell entry into tertiary lymphoid structures (TLSs). In addition, according to the results obtained using our ICLtotal score model, the expression of ICLs on HEVs was observed to be a predictor of both CD8+ T cell infiltration and survival, in which a high ICLtotal score > 1 represent a weak CD8+ T cell infiltration and a high ICLtotal score > 2 predicts poor survival. Conclusion: Using the ICL score model, we discovered that ICLs expressed on HEVs are indicative of CD8+ T cell subset infiltration in TLSs, as well as of patient survival with lung cancer.

Long-term ambient air pollution and the risk of musculoskeletal diseases: A prospective cohort study.

Evidence of the associations of air pollution and musculoskeletal diseases is inconsistent. This study aimed to examine the associations between air pollutants and the risk of incident musculoskeletal diseases, such as degenerative joint diseases (n = 38,850) and inflammatory arthropathies (n = 20,108). An air pollution score was constructed to assess the combined effect of PM2.5, PM2.5-10, NO2, and NOX. Cox proportional hazard model was applied to assess the relationships between air pollutants and the incidence of each musculoskeletal disease. The air pollution scores exhibited the modest association with an increased risk of osteoporosis (HR = 1.006, 95% CI: 1.002-1.011). Among the individual air pollutants, PM2.5 and PM2.5-10 exhibited the most significant effect on elevated risk of musculoskeletal diseases, such as PM2.5 on osteoporosis (HR = 1.064, 95% CI: 1.020-1.110), PM2.5-10 on inflammatory arthropathies (HR = 1.059, 95% CI: 1.037-1.081). Females were found to have a higher risk of incident musculoskeletal diseases when exposed to air pollutants. Individuals with extreme BMI or lower socioeconomic status had a higher risk of developing musculoskeletal diseases. Our findings reveal that long-term exposure to ambient air pollutants may contribute to an increased risk of musculoskeletal diseases.

Associations of classical HLA alleles with depression and anxiety.

Immune dysregulation has been widely observed in patients with psychiatric disorders. This study aims to examine the association between HLA alleles and depression and anxiety. Using data from the UK Biobank, we performed regression analyses to assess the association of 359 HLA alleles with depression and anxiety, as determined by Patient Health Questionnaire (PHQ) score (n = 120,033), self-reported depression (n = 121,685), general anxiety disorder (GAD-7) score (n = 120,590), and self-reported anxiety (n = 108,310). Subsequently, we conducted gene environmental interaction study (GEIS) to evaluate the potential effects of interactions between HLA alleles and environmental factors on the risk of depression and anxiety. Sex stratification was implemented in all analysis. Our study identified two significant HLA alleles associated with self-reported depression, including HLA-C*07:01 (ß = -0.015, p = 5.54 × 10-5 ) and HLA-B*08:01 (ß = -0.015, p = 7.78 × 10-5 ). Additionally, we identified four significant HLA alleles associated with anxiety score, such as HLA-DRB1*07:01 (ß = 0.084, p = 9.28 × 10-5 ) and HLA-B*57:01 (ß = 0.139, p = 1.22 × 10-4 ). GEIS revealed that certain HLA alleles interacted with environmental factors to influence mental health outcomes. For instance, HLA-A*02:07 × cigarette smoking was associated with depression score (ß = 0.976, p = 1.88 × 10-6 ). Moreover, sex stratification analysis revealed significant sex-based differences in the interaction effects of certain HLA alleles with environmental factors. Our findings indicate the considerable impact of HLA alleles on the risks of depression and anxiety, providing valuable insights into the functional relevance of immune dysfunction in these conditions.

Interplay of IL-33 and IL-35 Modulates Th2/Th17 Responses in Cigarette Smoke Exposure HDM-Induced Asthma.

Cigarette smoke (CS) facilitates adverse effects on the airway inflammation and treatment of asthma. Here, we investigated the mechanisms by which CS exacerbates asthma. The roles of IL-33 and IL-35 in asthma development were examined by treatment with IL-33 knockout (IL-33 KO) or transfection of adenovirus encoding IL-35 (Ad-IL-35) in a murine model of cigarette smoke-exposure asthma. Furthermore, the involvement of IL-33 and IL-35 in regulating DCs and Th2/Th17 cells was examined in a coculture system of DCs with CD4+ T cells. Additionally, we observed the effect of CpG-ODNs on the balance of IL-33 and IL-35. We show that CS and house dust mite (HDM) exposure induced IL-33 and suppressed IL-35 levels in cigarette smoke-exposure asthma in vivo and in vitro. Treatment with IL-33 KO or Ad-IL-35 significantly attenuated airway hyperreactivity, goblet hyperplasia, airway remodelling, and eosinophil and neutrophil infiltration in the lung tissues from asthmatic mice. Furthermore, we demonstrated reciprocal regulation between CS and HDM-modulated IL-33 and IL-35. Mechanistically, IL-33 KO (or anti-ST2) and Ad-IL-35 attenuated Th2- and Th17-associated inflammation by downregulating TSLP-DC signalling. Finally, administration of CpG-ODNs suppressed the expression of IL-33/ST2 and elevated the levels of IL-35, which is mainly derived from CD4+Foxp+ Tregs, to alleviate Th2- and Th17-associated inflammation by inhibiting the activation of BMDCs. Taken together, the IL-33/ST2 pathway drives the DC-Th2 and Th17 responses of cigarette smoke-exposure asthma, while IL-35 has the opposite effect. CpG-ODNs represent a potential therapeutic strategy for modulating the balance of IL-33 and IL-35 to suppress allergic airway inflammation.

Identification of novel rare variants for anxiety: an exome-wide association study in the UK Biobank.

BACKGROUND: Rare variants are believed to play a substantial role in the genetic architecture of mental disorders, particularly in coding regions. However, limited evidence supports the impact of rare variants on anxiety. METHODS: Using whole-exome sequencing data from 200,643 participants in the UK Biobank, we investigated the contribution of rare variants to anxiety. Firstly, we computed genetic risk score (GRS) of anxiety utilizing genotype data and summary data from a genome-wide association study (GWAS) on anxiety disorder. Subsequently, we identified individuals within the lowest 50% GRS, a subgroup more likely to carry pathogenic rare variants. Within this subgroup, we classified individuals with the highest 10% 7-item Generalized Anxiety Disorder scale (GAD-7) score as cases (N = 1869), and those with the lowest 10% GAD-7 score were designated as controls (N = 1869). Finally, we conducted gene-based burden tests and single-variant association analyses to assess the relationship between rare variants and anxiety. RESULTS: Totally, 47,800 variants with MAF ≤0.01 were annotated as non-benign coding variants, consisting of 42,698 nonsynonymous SNVs, 489 nonframeshift substitution, 236 frameshift substitution, 617 stop-gain and 40 stop-loss variants. After variation aggregation, 5066 genes were included in gene-based association analysis. Totally, 11 candidate genes were detected in burden test, such as RNF123 (PBonferroni adjusted = 3.40 × 10-6), MOAP1(PBonferroni adjusted = 4.35 × 10-4), CCDC110 (PBonferroni adjusted = 5.83 × 10-4). Single-variant test detected 9 rare variants, such as rs35726701(RNF123)(PBonferroni adjusted = 3.16 × 10-10) and rs16942615(CAMTA2) (PBonferroni adjusted = 4.04 × 10-4). Notably, RNF123, CCDC110, DNAH2, and CSKMT gene were identified in both tests. CONCLUSIONS: Our study identified novel candidate genes for anxiety in protein-coding regions, revealing the contribution of rare variants to anxiety.

A multidimensional social risk atlas of depression and anxiety: An observational and genome-wide environmental interaction study.

Background: Mental disorders are largely socially determined, yet the combined impact of multidimensional social factors on the two most common mental disorders, depression and anxiety, remains unclear. Methods: We constructed a polysocial risk score (PsRS), a multidimensional social risk indicator including components from three domains: socioeconomic status, neighborhood and living environment and psychosocial factors. Supported by the UK Biobank cohort, we randomly divided 110 332 participants into the discovery cohort (60%; n = 66 200) and the replication cohort (40%; n = 44 134). We tested the associations between 13 single social factors with Patient Health Questionnaire (PHQ) score, Generalized Anxiety Disorder Scale (GAD) score and self-reported depression and anxiety. The significant social factors were used to calculate PsRS for each mental disorder by considering weights from the multivariable linear model. Generalized linear models were applied to explore the association between PsRS and depression and anxiety. Genome-wide environmental interaction study (GWEIS) was further performed to test the effect of interactions between PsRS and SNPs on the risk of mental phenotypes. Results: In the discovery cohort, PsRS was positively associated with PHQ score (ß = 0.37; 95% CI = 0.35-0.38), GAD score (ß = 0.27; 95% CI = 0.25-0.28), risk of self-reported depression (OR = 1.29; 95% CI = 1.28-1.31) and anxiety (OR = 1.19; 95% CI = 1.19-1.23). Similar results were observed in the replication cohort. Emotional stress, lack of social support and low household income were significantly associated with the development of depression and anxiety. GWEIS identified multiple candidate loci for PHQ score, such as rs149137169 (ST18) (Pdiscovery = 1.08 × 10-8, Preplication = 3.25 × 10-6) and rs3759812 (MYO9A) (Pdiscovery = 3.87 × 10-9, Preplication = 6.21 × 10-5). Additionally, seven loci were detected for GAD score, such as rs114006170 (TMPRSS11D) (Pdiscovery = 1.14 × 10-9, Preplication = 7.36 × 10-5) and rs77927903 (PIP4K2A) (Pdiscovery = 2.40 × 10-9, Preplication = 0.002). Conclusions: Our findings reveal the positive effects of multidimensional social factors on the risk of depression and anxiety. It is important to address key social disadvantage in mental health promotion and treatment.

Insight into the Causal Relationship between Gut Microbiota and Back Pain: A Two Sample Bidirectional Mendelian Randomization Study.

Observational studies have shown that alterations in gut microbiota composition are associated with low back pain. However, it remains unclear whether the association is causal. To reveal the causal association between gut microbiota and low back pain, a two-sample bidirectional Mendelian randomization (MR) analysis is performed. The inverse variance weighted regression (IVW) is performed as the principal MR analysis. MR-Egger and Weighted Median is further conducted as complementary analysis to validate the robustness of the results. Finally, a reverse MR analysis is performed to evaluate the possibility of reverse causation. The inverse variance weighted (IVW) method suggests that Peptostreptococcaceae (odds ratio [OR] 1.056, 95% confidence interval [CI] [1.015-1.098], P IVW = 0.010), and Lactobacillaceae (OR 1.070, 95% CI [1.026-1.115], P IVW = 0.003) are positively associated with back pain. The Ruminococcaceae (OR 0.923, 95% CI [0.849-0.997], P IVW = 0.033), Butyricicoccus (OR 0.920, 95% CI [0.868 - 0.972], P IVW = 0.002), and Lachnospiraceae (OR 0.948, 95% CI [0.903-0.994], P IVW = 0.022) are negatively associated with back pain. In this study, underlying causal relationships are identified among gut microbiota and low back pain. Notably, further research is needed on the biological mechanisms by which gut microbiota influences low back pain.

Single-cell transcriptomics reveals tumor-infiltrating B cell function after neoadjuvant pembrolizumab and chemotherapy in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is the most pervasive lung cancer subtype. Recent studies have shown that immune checkpoint inhibitors achieved favorable clinical benefits in resectable NSCLC; however, the associated mechanism remains unclear. The role of T cells in antitumor immunity has received considerable attention, while the antitumor effects of tumor-infiltrating B cells (TIBs) in NSCLC remain poorly understood. Here, we conducted a single-cell RNA-seq analysis of immune cells isolated from 12 patients with IIIA NSCLC to investigate B cell subtypes and their functions following neoadjuvant chemoimmunotherapy. We confirmed the simultaneous existence of the four B cell subtypes. Among them, memory B cells were found to be associated with a positive therapeutic effect to neoadjuvant chemoimmunotherapy. Furthermore, we found that G Protein-Coupled Receptor 183 (GPR183) was most prevalent in memory B cells and associated with a positive therapeutic response. Multiplex immunofluorescence and flow cytometry experiments in an additional cohort of 22 treatment-naïve and 30 IIIA/IIIB NSCLC patients treated with neoadjuvant chemoimmunotherapy verified these findings. Overall, our analysis revealed the functions of TIBs and their potential effect on clinical treatment in NSCLC.

Dissecting the Association between Gut Microbiota and Brain Structure Change Rate: A Two-Sample Bidirectional Mendelian Randomization Study.

The connection between the gut microbiota and brain structure changes is still unclear. We conducted a Mendelian randomization (MR) study to examine the bidirectional causality between the gut microbiota (211 taxa, including 131 genera, 35 families, 20 orders, 16 classes and 9 phyla; N = 18,340 individuals) and age-independent/dependent longitudinal changes in brain structure across the lifespan (N = 15,640 individuals aged 4~99 years). We identified causal associations between the gut microbiota and age-independent/dependent longitudinal changes in brain structure, such as family Peptostreptococcaceae with age-independent longitudinal changes of cortical gray matter (GM) volume and genus Faecalibacterium with age-independent average cortical thickness and cortical GM volume. Taking age-independent longitudinal changes in brain structure across the lifespan as exposures, there were causal relationships between the surface area and genus Lachnospiraceae. Our findings may serve as fundamentals for further research on the genetic mechanisms and biological treatment of complex traits and diseases associated with the gut microbiota and the brain structure change rate.

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.

Integrative Analysis of Proteome-wide Association Studies and Functional Enrichment Analysis to Identify Genes and Chemicals Associated with Alcohol Dependence.

OBJECTIVES: Alcohol dependence accounts for a large proportion of the global burden of disease and disability. This study aims to investigate the candidate genes and chemicals associated with alcohol dependence. METHODS: Using data from published alcohol dependence genome-wide association studies, we first conducted a proteome-wide association study of alcohol dependence by integrating alcohol dependence genome-wide association studies with 2 human brain reference proteomes of dorsolateral prefrontal cortex from the Religious Order Study and Rush Memory and Aging Project and the Banner Sun Health Research Institute. Then, based on the identified genes in proteome-wide association study, we conducted functional enrichment analysis and chemical-related functional enrichment analysis to detect the related Gene Ontology terms and chemicals. RESULTS: Proteome-wide association study identified several potential candidate genes for alcohol dependence, such as GOT2 ( P = 7.59 × 10 -6 ) and C3orf33 ( P = 5.00 × 10 -3 ). Furthermore, functional enrichment analysis identified multiple candidate Gene Ontology terms associated with alcohol dependence, such as glyoxylate metabolic process (adjusted P = 2.99 × 10 -6 ) and oxoglutarate metabolic process (adjusted P = 9.95 × 10 -6 ). Chemical-related functional enrichment analysis detected several alcohol dependence-related candidate chemicals, such as pitavastatin ( P = 2.00 × 10 -4 ), cannabinoids ( P = 4.00 × 10 -4 ), 11-nor-Δ(9)-tetrahydrocannabinol-9-carboxylic acid ( P = 4.00 × 10 -4 ), and gabapentin ( P = 2.00 × 10 -3 ). CONCLUSIONS: Our study reports multiple candidate genes and chemicals associated with alcohol dependence, providing novel clues for understanding the biological mechanism of alcohol dependence.

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.

Mitochondria-wide association study observed significant interactions of mitochondrial respiratory and the inflammatory in the development of anxiety and depression.

The aim of this study was to investigate the possible interaction of mitochondrial dysfunction and inflammatory cytokines in the risk of anxiety and depression. We utilized the UK Biobank for the sample of this study. A mitochondria-wide association(MiWAS) and interaction analysis was performed to investigate the interaction effects of mitochondrial DNA (mtDNA)×C-reactive protein (CRP) on the risks of self-reported anxiety (N = 72,476), general anxiety disorder (GAD-7) scores (N = 80,853), self-reported depression (N = 80,778), Patient Health Questionnaire (PHQ-9) scores (N = 80,520) in total samples, females and males, respectively, adjusting for sex, age, Townsend deprivation index (TDI), education score, alcohol intake, smoking and 10 principal components. In all, 25 mtSNPs and 10 mtSNPs showed significant level of association with self-reported anxiety and GAD-7 score respectively. A total of seven significant mtDNA × CRP interactions were found for anxiety, such as m.3915G>A(MT-ND1) for self-reported anxiety in total subjects (P = 6.59 × 10-3), m.4561T>C(MT-ND2) (P = 3.04 × 10-3) for GAD-7 score in total subjects. For depression, MiWAS identified 17 significant mtSNPs for self-reported depression and 14 significant mtSNPs for PHQ-9 scores. 17 significant mtDNA associations (2 for self-reported depression and 15 for PHQ-9 score) was identified, such as m.14869G>A(MT-CYB; P = 2.22 × 10-3) associated with self-reported depression and m.4561T>C (MT-ND2; P value = 3.02 × 10-8) associated with PHQ-9 score in all subjects. In addition, 5 common mtDNA shared with anxiety and depression were found in MiWAS, and 4 common mtDNA variants were detected to interact with CRP for anxiety and depression, such as m.9899T>C(MT-CO3). Our study suggests the important interaction effects of mitochondrial function and CRP on the risks of anxiety and depression.

Exploratory factor analysis of shared and specific genetic associations in depression and anxiety.

BACKGROUND: Previous genetic studies of anxiety and depression were mostly based on independent phenotypes. This study aims to investigate the shared and specific genetic structure between anxiety and depression. METHOD: To identify the underlying factors of Generalized Anxiety Disorder-7 (GAD-7), Patient Health Questionnaire-9 (PHQ-9), and their combined scale (joint scale), we employed exploratory factor analysis (EFA) using the eigenvalue of parallel analysis. Subsequently, we conducted a genome-wide association study (GWAS) for these factors. In addition, we utilized LD Score Regression (LDSC) to determine the genetic correlations between the identified factors and four common mental disorders, three sleep phenotypes, and other traits that have been previously linked to anxiety and depression. RESULTS: The EFA uncovered two factors for the GAD-7 scale, namely nervousness and disturbance, two factors for the PHQ-9 scale, namely negative affect and sleep/appetite disturbance, and four factors for the joint scale, specifically nervousness, anhedonia, sleep/appetite disturbance, and fidget. We identified two genome-wide significant genomic loci, with overlap across GAD-7 factor 1 and joint scale factor 1: rs148579586 (PGAD-7 = 1.365 × 10-09, PJoint scale = 1.434 × 10-09) and rs201074060 (PGAD-7 = 3.672 × 10-09, PJoint scale = 3.824 × 10-09). Genetic correlations in factors ranged from 0.722 to 1.000 (all p < 1.786 × 10-03) with 27 of 28 correlations being significantly smaller than one. The genetic correlations with external phenotypes showed small variation across the eight factors. CONCLUSION: Unidimensional structures can provide more precise scores, which can aid in identifying the shared and specific genetic associations between anxiety and depression. This is a crucial step in characterizing the genetic structure of these conditions and their co-occurrence.

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.

Evaluating the genetic interaction effects of gut microbiome and diet on the risk of neuroticism in the UK Biobank cohort.

OBJECTIVES: In this study designed to investigate the effect of diet and gut microbiome on neuropsychiatric disorders, we explored the mechanisms of the interaction between diet and gut microbiome on the risk of neuroticism. METHODS: First, using the individual genotype data from the UK Biobank cohort (N = 306 165), we calculated the polygenic risk score (PRS) based on 814 dietary habits single nucleotide polymorphisms (SNPs), 21 diet compositions SNPs and 1001 gut microbiome SNPs, respectively. Gut microbiome and diet-associated SNPs were collected from three genome-wide association studies (GWAS), including the gut microbiome (N = 3890), diet compositions (over 235 000 subjects) and dietary habits (N = 449 210). The neuroticism score was calculated by 12 questions from the Eysenck Personality Inventory Neuroticism scale. Then, regression analysis was performed to evaluate the interaction effects between diet and the gut microbiome on the risk of neuroticism. RESULTS: Our studies demonstrated multiple candidate interactions between diet and gut microbiome, such as protein vs. Bifidobacterium (ß = 4.59 × 10-3; P = 9.45 × 10-3) and fat vs. Clostridia (ß = 3.67 × 10-3; P = 3.90 × 10-2). In addition, pieces of fresh fruit per day vs. Ruminococcus (ß = -5.79 × 10-3, P = 1.10 × 10-3) and pieces of dried fruit per day vs. Clostridiales (ß = -5.63 × 10-3, P = 1.49 × 10-3) were found to be negatively associated with neuroticism in fruit types. We also identified several positive interactions, such as tablespoons of raw vegetables per day vs. Veillonella (ß = 5.92 × 10-3, P = 9.21 × 10-4) and cooked vegetables per day vs. Acidaminococcaceae (ß = 5.69 × 10-3, P = 1.24 × 10-3). CONCLUSIONS: Our results provide novel clues for understanding the roles of diet and gut microbiome in the development of neuroticism.