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Abstract This study investigates the cellular origin and tissue heterogeneity in bipolar disorder (BD) by integrating multiomics data. Four distinct datasets were employed, including single-cell RNA sequencing (scRNA-seq) data (embryonic and fetal brain, n = 8, 1,266 cells), BD Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) data (adult brain, n = 210), BD bulk RNA-seq data (adult brain, n = 314), and BD genome-wide association study (GWAS) summary data (n = 413,466). The integration of scRNA-seq data with multiomics data relevant to BD was accomplished using the single-cell disease relevance score (scDRS) algorithm. We have identified a novel brain cell cluster named ADCY1, which exhibits distinct genetic characteristics. From a high-resolution genetic perspective, glial cells emerge as the primary cytopathology associated with BD. Specifically, astrocytes were significantly related to BD at the RNA-seq level, while microglia showed a strong association with BD across multiple panels, including the transcriptome-wide association study (TWAS), ATAC-seq, and RNA-seq. Additionally, oligodendrocyte precursor cells displayed a significant association with BD in both ATAC-seq and RNA-seq panel. Notably, our investigation of brain regions affected by BD revealed significant associations between BD and all three types of glial cells in the dorsolateral prefrontal cortex (DLPFC). Through comprehensive analyses, we identified several BD-associated genes, including CRMP1, SYT4, UCHL1, and ZBTB18. In conclusion, our findings suggest that glial cells, particularly in specific brain regions such as the DLPFC, may play a significant role in the pathogenesis of BD. The integration of multiomics data has provided valuable insights into the etiology of BD, shedding light on potential mechanisms underlying this complex psychiatric disorder.

Abstract 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.

While strides in cancer treatment continue to advance, the enduring challenges posed by cancer metastasis and recurrence persist as formidable contributors to the elevated mortality rates observed in cancer patients. Among the multifaceted factors implicated in tumor recurrence and metastasis, cancer stem cells (CSCs) emerge as noteworthy entities due to their inherent resistance to conventional therapies and heightened invasive capacities. Characterized by their notable abilities for self-renewal, differentiation, and initiation of tumorigenesis, the eradication of CSCs emerges as a paramount objective. Recent investigations increasingly emphasize the pivotal role of post-translational protein modifications (PTMs) in governing the self-renewal and replication capabilities of CSCs. This review accentuates the critical significance of several prevalent PTMs and the intricate interplay of PTM crosstalk in regulating CSC behavior. Furthermore, it posits that the manipulation of PTMs may offer a novel avenue for targeting and eliminating CSC populations, presenting a compelling perspective on cancer therapeutics with substantial potential for future applications.

Abstract 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.

BackgroundImmune 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).MethodsFifty-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.ResultsA 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.ConclusionsThese 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.

BackgroundAn 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.MethodsForty-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.ResultsMature 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.ConclusionUsing 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.

BackgroundThe 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.MethodsDoxorubicin (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.ResultsDoxorubicin 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.ConclusionsThese 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.

Purpose: Previous studies have demonstrated the link between micronutrients and mental health. However, it remains uncertain whether this connection is causal. We aim to investigate the potential causal effects of micronutrients on mental health based on linkage disequilibrium score (LDSC) regression and Mendelian randomization (MR) analysis. Methods: Utilizing publicly available genome-wide association study (GWAS) summary datasets, we performed LDSC and MR analysis to identify candidate micronutrients with potential causal effects on mental health. Single nucleotide polymorphisms (SNPs) significantly linked with candidate micronutrients with a genome-wide significance level (p < 5 × 10−8) were selected as instrumental variables (IVs). To estimate the causal effect of candidate micronutrients on mental health, we employed inverse variance weighted (IVW) regression. Additionally, two sensitivity analyses, MR-Egger and weighted median, were performed to validate our results. Results: We found evidence supporting significant causal associations between micronutrients and mental health. LDSC detected several candidate micronutrients, including serum iron (genetic correlation = −0.134, p = 0.032) and vitamin C (genetic correlation = −0.335, p < 0.001) for attention-deficit/hyperactivity disorder (ADHD), iron-binding capacity (genetic correlation = 0.210, p = 0.037) for Alzheimer’s disease (AD), and vitamin B12 (genetic correlation = −0.178, p = 0.044) for major depressive disorder (MDD). Further MR analysis suggested a potential causal relationship between vitamin B12 and MDD (b = −0.139, p = 0.009). There was no significant heterogeneity or pleiotropy, indicating the validity of the findings. Conclusion: In this study, we identified underlying causal relationships between micronutrients and mental health. Notably, more research is necessary to clarify the underlying biological mechanisms by which micronutrients affect mental health.

Abstract 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.

Abstract 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], PIVW = 0.010), and Lactobacillaceae (OR 1.070, 95% CI [1.026–1.115], PIVW = 0.003) are positively associated with back pain. The Ruminococcaceae (OR 0.923, 95% CI [0.849–0.997], PIVW = 0.033), Butyricicoccus (OR 0.920, 95% CI [0.868 ‐ 0.972], PIVW = 0.002), and Lachnospiraceae (OR 0.948, 95% CI [0.903–0.994], PIVW = 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.

Abstract Background Longevity is one of the most complex phenotypes, and its genetic basis remains unclear. This study aimed to explore the genetic correlation and potential causal association between gut microbiota and longevity. Results Linkage disequilibrium score (LDSC) regression analysis and a bi-directional two-sample Mendelian Randomization (MR) analysis were performed to analyze gut microbiota and longevity-related traits. LDSC analysis detected four candidate genetic correlations, including Veillonella (genetic correlation = 0.5578, P = 4.67 × 10− 2) and Roseburia (genetic correlation = 0.4491, P = 2.67 × 10− 2) for longevity, Collinsella (genetic correlation = 0.3144, P = 4.07 × 10− 2) for parental lifespan and Sporobacter (genetic correlation = 0.2092, P = 3.53 × 10− 2) for healthspan. Further MR analysis observed suggestive causation between Collinsella and parental longevity (father’s age at death) (weighted median: b = 1.79 × 10− 3, P = 3.52 × 10− 2). Reverse MR analysis also detected several causal effects of longevity-related traits on gut microbiota, such as longevity and Sporobacter (IVW: b = 7.02 × 10− 1, P = 4.21 × 10− 25). Statistical insignificance of the heterogeneity test and pleiotropy test supported the validity of the MR study. Conclusion Our study found evidence that gut microbiota is causally associated with longevity, or vice versa, providing novel clues for understanding the roles of gut microbiota in aging development.

Abstract Psychiatric disorders and neuroticism are closely associated with central nervous system, whose proper functioning depends on efficient protein renewal. This study aims to systematically analyze the association between anxiety / depression / neuroticism and each of the 439 proteins. 47,536 pQTLs of 439 proteins in brain, plasma and cerebrospinal fluid (CSF) were collected from recent genome-wide association study. Polygenic risk scores (PRS) of the 439 proteins were then calculated using the UK Biobank cohort, including 120,729 subjects of neuroticism, 255,354 subjects of anxiety and 316,513 subjects of depression. Pearson correlation analyses were performed to evaluate the correlation between each protein and each of the mental traits by using calculated PRSs as the instrumental variables of protein. In general population, six correlations were identified in plasma and CSF such as plasma protease C1 inhibitor (C1-INH) with neuroticism score (r = − 0.011, P = 2.56 × 10− 9) in plasma, C1-INH with neuroticism score (r = -0.010, P = 3.09 × 10− 8) in CSF, and ERBB1 with self-reported depression (r = − 0.012, P = 4.65 × 10− 5) in CSF. C1-INH and ERBB1 may induce neuroticism and depression by affecting brain function and synaptic development. Gender subgroup analyses found that BST1 was correlated with neuroticism score in male CSF (r = − 0.011, P = 1.80 × 10− 5), while CNTN2 was correlated with depression score in female brain (r = − 0.013, P = 6.43 × 10− 4). BST1 and CNTN2 may be involved in nervous system metabolism and brain health. Six common candidate proteins were associated with all three traits (P

Abstract Multiple previous studies explored the associations between early life factors and the age at onset of the depression. However, they only focused on the influence of environmental or genetic factors, without considering the interactions between them. Based on previous genome-wide association study (GWAS) data, we first calculated polygenic risk score (PRS) for depression. Regression analyses were conducted to assess the interacting effects of depression PRS and 5 early life factors, including felt hated by family member (N = 40,112), physically abused by family (N = 40,464), felt loved (N = 35633), and sexually molested (N = 41,595) in childhood and maternal smoking during pregnancy (N = 38,309), on the age at onset of the depression. Genome-wide environment interaction studies (GWEIS) were then performed to identify the genes interacting with early life factors for the age at onset of the depression. In regression analyses, we observed significant interacting effects of felt loved as a child and depression PRS on the age at onset of depression in total sample (β = 0.708, P = 5.03 × 10−3) and males (β = 1.421, P = 7.64 × 10−4). GWEIS identified a novel candidate loci interacting with felt loved as a child at GSAP (rs2068031, P = 4.24 × 10–8) and detected several genes with suggestive significance association, such as CMYA5 (rs7343, P = 2.03 × 10–6) and KIRREL3 (rs535603, P = 4.84 × 10–6) in males. Our results indicate emotional care in childhood may affect the age at onset of depression, especially in males, and GSAP plays an important role in their interaction.

Abstract It is well-accepted that both environment and genetic factors contribute to the development of mental disorders (MD). However, few genetic studies used time-to-event data analysis to identify the susceptibility genetic variants associated with MD and explore the role of environment factors in these associations. In order to detect novel genetic loci associated with MD based on the time-to-event data and identify the role of environmental factors in them, this study recruited 376,806 participants from the UK Biobank cohort. The MD outcomes (including overall MD status, anxiety, depression and substance use disorders (SUD)) were defined based on in-patient hospital, self-reported and death registry data collected in the UK Biobank. SPACOX approach was used to identify the susceptibility loci for MD using the time-to-event data of the UK Biobank cohort. And then we estimated the associations between identified candidate loci, fourteen environment factors and MD through a phenome-wide association study and mediation analysis. SPACOX identified multiple candidate loci for overall MD status, depression and SUD, such as rs139813674 (P value = 8.39 × 10–9, ZNF684) for overall MD status, rs7231178 (DCC, P value = 2.11 × 10–9) for depression, and rs10228494 (FOXP2, P value = 6.58 × 10–10) for SUD. Multiple environment factors could influence the associations between identified loci and MD, such as confide in others and felt hated. Our study identified novel candidate loci for MD, highlighting the strength of time-to-event data based genetic association studies. We also observed that multiple environment factors could influence the association between susceptibility loci and MD.

Abstract Background T-2 toxin is thought to induce the growth plate and articular cartilage damage of Kashin-Beck disease (KBD), an endemic osteochondropathy in China. This study aims to explore the potential underlying mechanism of such toxic effects by integrating DNA methylation and gene expression profiles. Methods In this study, C28/I2 chondrocytes were treated with T-2 toxin (5 ng/mL) for 24 h and 72 h. Global DNA methylation level of chondrocyte was tested by Enzyme-Linked Immuno Sorbent Assay. Genome-wide DNA methylation and expression profiles were detected using Illumina Infinium HumanMethylation850 BeadChip and RNA-seq technique, respectively. Differentially methylated genes (DMGs) and differentially expressed genes (DEGs) were identified mainly for two stages including 24 h group versus Control group and 72 h group versus 24 h group. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed by Metascape. DMGs and DEGs were further validated by Sequenom MassARRAY system and quantitative real-time polymerase chain reaction. Results The global DNA methylation levels of chondrocytes exposed to T-2 toxin were significantly increased (P

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.

Abstract Background Gut microbiota is closely associated with host health and disease occurrence. Host genetic factor plays an important role in shaping gut microbial communities. The specific mechanism of host-regulated gene expression affecting gut microbiota has not been elucidated yet. Here we conducted a transcriptome-wide association study (TWAS) for gut microbiota by leveraging expression imputation from large-scale GWAS data sets. Results TWAS detected multiple tissue-specific candidate genes for gut microbiota, such as FUT2 for genus Bifidobacterium in transverse colon (P PERM.ANL = 1.68 × 10–3) and SFTPD for an unclassified genus of Proteobacteria in transverse colon (P PERM.ANL = 5.69 × 10–3). Fine mapping replicated 3 candidate genes in TWAS, such as HELLS for Streptococcus (PIP = 0.685) in sigmoid colon, ANO7 for Erysipelotrichaceae (PIP = 0.449) in sigmoid colon. Functional analyses detected 94 significant GO terms and 11 pathways for various taxa in total, such as GO_NUCLEOSIDE_DIPHOSPHATASE_ACTIVITY for Butyrivibrio (FDR P = 1.30 × 10–4), KEGG_RENIN_ANGIOTENSIN_SYSTEM for Anaerostipes (FDR P = 3.16 × 10–2). Literature search results showed 12 genes prioritized by TWAS were associated with 12 diseases. For instance, SFTPD for an unclassified genus of Proteobacteria was related to atherosclerosis, and FUT2 for Bifidobacterium was associated with Crohn’s disease. Conclusions Our study results provided novel insights for understanding the genetic mechanism of gut microbiota, and attempted to provide clues for revealing the influence of genetic factors on gut microbiota for the occurrence and development of diseases.

Aims: Despite the interest in the association of gut microbiota with bone health, limited population-based studies of gut microbiota and bone mineral density (BMD) have been made. Our aim is to explore the possible association between gut microbiota and BMD. Methods: A total of 3,321 independent loci of gut microbiota were used to calculate the individual polygenic risk score (PRS) for 114 gut microbiota-related traits. The individual genotype data were obtained from UK Biobank cohort. Linear regressions were then conducted to evaluate the possible association of gut microbiota with L1-L4 BMD (n = 4,070), total BMD (n = 4,056), and femur total BMD (n = 4,054), respectively. PLINK 2.0 was used to detect the single-nucleotide polymorphism (SNP) × gut microbiota interaction effect on the risks of L1-L4 BMD, total BMD, and femur total BMD, respectively. Results: We detected five, three, and seven candidate gut microbiota-related traits for L1-L4 BMD, total BMD, and femur BMD, respectively, such as genus Dialister (p = 0.004) for L1-L4 BMD, and genus Eisenbergiella (p = 0.046) for total BMD. We also detected two common gut microbiota-related traits shared by L1-L4 BMD, total BMD, and femur total BMD, including genus Escherichia Shigella and genus Lactococcus. Interaction analysis of BMD detected several genes that interacted with gut microbiota, such as phospholipase D1 (PLD1) and endomucin (EMCN) interacting with genus Dialister in total BMD, and COL12A1 and Discs Large MAGUK Scaffold Protein 2 (DLG2) interacting with genus Lactococcus in femur BMD. Conclusion: Our results suggest associations between gut microbiota and BMD, which will be helpful to further explore the regulation mechanism and intervention gut microbiota of BMD. Cite this article: Bone Joint Res 2021;10(11):734–741.

BackgroundGrowing evidence supports that alterations in the gut microbiota play an essential role in the etiology of anxiety, depression, and other psychiatric disorders. However, the potential effect of oral microbiota on mental health has received little attention.MethodsUsing the latest genome-wide association study (GWAS) summary data of the oral microbiome, polygenic risk scores (PRSs) of 285 salivary microbiomes and 309 tongue dorsum microbiomes were conducted. Logistic and linear regression models were applied to evaluate the relationship between salivary-tongue dorsum microbiome interactions with anxiety and depression. Two-sample Mendelian randomization (MR) was utilized to compute the causal effects between the oral microbiome, anxiety, and depression.ResultsWe observed significant salivary-tongue dorsum microbiome interactions related to anxiety and depression traits. Significantly, one common interaction was observed to be associated with both anxiety score and depression score, Centipeda periodontii SGB 224 × Granulicatella uSGB 3289 (P depressionscore = 1.41 × 10−8, P anxietyscore = 5.10 × 10−8). Furthermore, we detected causal effects between the oral microbiome and anxiety and depression. Importantly, we identified one salivary microbiome associated with both anxiety and depression in both the UKB database and the Finngen public database, Eggerthia (P IVW − majordepression − UKB = 2.99 × 10−6, P IVW − Self − reportedanxiety/panicattacks − UKB = 3.06 × 10−59, P IVW − depression − Finngen = 3.16 × 10,-16 P IVW − anxiety − Finngen = 1.14 × 10−115).ConclusionThis study systematically explored the relationship between the oral microbiome and anxiety and depression, which could help improve our understanding of disease pathogenesis and propose new diagnostic targets and early intervention strategies.

Abstract Cumulative evidence shows that gut microbiome can influence brain function and behavior via the inflammatory processes. However, the role of interaction between gut dysbiosis and C-reactive protein (CRP) in the development of anxiety and depression remains to be elucidated. In this study, a total of 3321 independent single nucleotide polymorphism (SNP) loci associated with gut microbiome were driven from genome-wide association study (GWAS). Using individual level genotype data from UK Biobank, we then calculated the polygenetic risk scoring (PRS) of 114 gut microbiome related traits. Moreover, regression analysis was conducted to evaluate the possible effect of interaction between gut microbiome and CRP on the risks of Patient Health Questionnaire-9 (PHQ-9) (N = 113,693) and Generalized Anxiety Disorder-7 (GAD-7) (N = 114,219). At last, 11 candidate CRP × gut microbiome interaction with suggestive significance was detected for PHQ-9 score, such as F_Ruminococcaceae (β = − 0.009, P = 2.2 × 10–3), G_Akkermansia (β = − 0.008, P = 7.60 × 10–3), F_Acidaminococcaceae (β = 0.008, P = 1.22 × 10–2), G_Holdemanella (β = − 0.007, P = 1.39 × 10–2) and O_Lactobacillales (β = 0.006, P = 1.79× 10–2). 16 candidate CRP × gut microbiome interaction with suggestive significance was detected for GAD-7 score, such as O_Bacteroidales (β = 0.010, P = 4.00× 10–4), O_Selenomonadales (β = − 0.010, P = 1.20 × 10–3), O_Clostridiales (β = 0.009, P = 2.70 × 10–3) and G_Holdemanella (β = − 0.008, P = 4.20 × 10–3). Our results support the significant effect of interaction between CRP and gut microbiome on the risks of anxiety and depression, and identified several candidate gut microbiomes for them.

BackgroundT-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.MethodsIn 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.ResultsWe 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.ConclusionsThis 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.

Abstract Background Cigarette smoke (CS) exposure increases corticosteroid insensitive asthma related to increased Th17 phenotype, and new treatment strategies are needed for CS-associated asthma. Histone deacetylase 2 (HDAC2), found in the airway epithelium, is critical for ameliorating glucocorticoids insensitivity. We recently demonstrated the anti-inflammatory effects of CpG oligodeoxynucleotides (CpG-ODNs) on CS-exposure asthma. However, the effects of CpG-ODNs on HDAC2 expression and enzymatic activity remain unclear. This study aimed to assess whether CpG-ODNs protect against excessive Th17 immune responses in CS-induced asthma through HDAC2-dependent mechanisms and compared their effects with those of corticosteroids. Methods The effects of CpG-ODNs alone and in combination with budesonide (BUD) on airway inflammation and Th2/Th17-related airway immune responses were determined using an in vivo model of CS-induced asthma and in cultured bronchial epithelial (HBE) cells administered ovalbumin (OVA) and/or cigarette smoke extract (CSE). HDAC2 and retinoid-related orphan nuclear receptor γt (RORγt) expression were also assessed in mouse lung specimens and HBE cells. Results CpG-ODNs and BUD synergistically attenuated CS exposure asthmatic responses in vivo by modulating the influx of eosinophils and neutrophils, airway remodeling, Th2/Th17 associated cytokine and chemokine production, and airway hyperresponsiveness and blocking RORγt-mediated Th17 inflammation through induced HDAC2 expression/activity. In vitro, CpG-ODNs synergized with BUD to inhibit Th17 cytokine production in OVA- and CSE-challenged HBE cells while suppressing RORγt and increasing epithelial HDAC2 expression/activity. Conclusions CpG-ODNs reversed CS-induced HDAC2 downregulation and enhanced the sensitivity of CS-exposed asthmatic mice and CSE-induced HBE cells to glucocorticoid treatment. This effect may be associated with HDAC2 restoration via RORγt/IL-17 pathway regulation, suggesting that CpG-ODNs are potential corticosteroid-sparing agents for use in CS-induced asthma with Th17-biased immune conditions.

Tobacco smoke exposure is a major environmental risk factor that facilitates the development and progression of asthma. Our previous study showed that CpG oligodeoxynucleotide (CpG-ODN) inhibits thymic stromal lymphopoietin (TSLP)-dendritic cells (DCs) to reduce Th2/Th17-related inflammatory response in smoke-related asthma. However, the mechanism underlying CpG-ODN -downregulated TSLP remains unclear. A combined house dust mite (HDM)/cigarette smoke extract (CSE) model was used to assess the effects of CpG-ODN on airway inflammation, Th2/Th17 immune response, and amount of IL-33/ST2 and TSLP in mice with smoke-related asthma induced by adoptive transfer of bone-marrow-derived dendritic cells (BMDCs) and in the cultured human bronchial epithelium (HBE) cells administered anti-ST2, HDM, and/or CSE. In vivo, compared to the HDM alone model, the combined HDM/CSE model had aggravated inflammatory responses, while CpG-ODN attenuated airway inflammation, airway collagen deposition, and goblet cell hyperplasia and reduced the levels of IL-33/ST2, TSLP, and Th2/Th17-cytokines in the combined model. In vitro, IL-33/ST2 pathway activation promoted TSLP production in HBE cells, which could be inhibited by CpG-ODN. CpG-ODN administration alleviated Th2/Th17 inflammatory response, decreased the infiltration of inflammatory cells into the airway, and improved the remodeling of smoke-related asthma. The underlying mechanism may be that CpG-ODN inhibits the TSLP-DCs pathway by downregulating the IL-33/ST2 axis.

AbstractBackgroundDepression is a debilitating mental disorder that often coexists with anxiety. The genetic mechanisms of depression and anxiety have considerable overlap, and studying depression in non-anxiety samples could help to discover novel gene. We assess the genetic variation of depression in non-anxiety samples, using genome-wide association studies (GWAS) and linkage disequilibrium score regression (LDSC).MethodsThe GWAS of depression score and self-reported depression were conducted using the UK Biobank samples, comprising 99,178 non-anxiety participants with anxiety score

Rheumatoid arthritis (RA) is a multi-systemic inflammatory autoimmune disease involving peripheral joints, and the pathogenesis is not clear. Studies showed that DNA methylation and expression might also be involved in the pathogenesis of RA. This study integrated three expression profile datasets (GSE55235, GSE12021, and GSE55457) and one methylation profile dataset GSE111942 to elucidate the potential essential candidate genes and pathways in RA. Differentially expressed genes (DEGs) and differentially methylation genes (DMGs) were identified by R programming software, using Limma package and ChAMP package, respectively. DAVID performed gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs. Functional annotation and construction of a protein–protein interaction (PPI) network and the Molecular Complex Detection Algorithm (MCODE) were analysed by STRING and Cystoscope, respectively. Then the connection analysis of DEGs and DMGs was carried out, and further to analyse the relationship between methylation and gene expression, aiming to screen out the potential genes. In this study, 288 DEGs and 228 DMGs were identified, and the majority of DEGs were up-regulated. Enrichment analysis represented that DEGs mainly involved immune response and participated in the Cytokine–cytokine receptor interaction signal pathway. 282 nodes were identified from DEGs PPI network and MCODE, filtering the most significant 2 modules, 23 core node genes were identified and most of them are involved in the T cell receptor signalling pathway and chemokine-mediated signalling pathway. Cross-analysis revealed 4 genes [KNTC1 (cg 01277763), LRRC8D (cg 07600884), DHRS9 (cg 05961700), and UCP2 (cg 05205664)] that exhibited differential expression and methylation in RA simultaneously. Therefore, the four genes could be used as the target for RA.

Habitual coffee consumption is an addictive behavior with unknown genetic variations and has raised public health issues about its potential health-related outcomes. We performed exome-wide association studies to identify rare risk variants contributing to habitual coffee consumption utilizing the newly released UK Biobank exome dataset (n = 200,643). A total of 34,761 qualifying variants were imported into SKAT to conduct gene-based burden and robust tests with minor allele frequency OR2G2 (PSKAT = 1.88 × 10−9, PSKAT-Robust = 2.91 × 10−17), VEZT1 (PSKAT = 3.72 × 10−7, PSKAT-Robust = 1.41 × 10−7), and IRGC (PSKAT = 2.92 × 10−5, PSKAT-Robust = 1.07 × 10−7). These candidate genes were verified in the GWAS summary data of coffee intake, such as rs12737801 (p = 0.002) in OR2G2, and rs34439296 (p = 0.008) in IRGC. This study could help to extend genetic insights into the pathogenesis of coffee addiction, and may point to molecular mechanisms underlying health effects of habitual coffee consumption.

Although previous genome-wide association studies (GWASs) on post-traumatic stress disorder (PTSD) have identified multiple risk loci, how these loci confer risk of PTSD remains unclear. Through the FUSION pipeline, we integrated two human brain proteome reference datasets (ROS/MAP and Banner) with the PTSD GWAS dataset, respectively, to conduct a proteome-wide association study (PWAS) analysis. Then two transcriptome reference weights (Rnaseq and Splicing) were applied to a transcriptome-wide association study (TWAS) analysis. Finally, the PWAS and TWAS results were investigated through brain imaging analysis. In the PWAS analysis, 8 and 13 candidate genes were identified in the ROS/MAP and Banner reference weight groups, respectively. Examples included ADK (pPWAS-ROS/MAP = 3.00 × 10−5) and C3orf18 (pPWAS-Banner = 7.07 × 10−31). Moreover, the TWAS also detected multiple candidate genes associated with PTSD in two different reference weight groups, including RIMS2 (pTWAS-Splicing = 3.84 × 10−2), CHMP1A (pTWAS-Rnaseq = 5.09 × 10−4), and SIRT5 (pTWAS-Splicing = 4.81 × 10−3). Further comparison of the PWAS and TWAS results in different populations detected the overlapping genes: MADD (pPWAS-Banner = 4.90 × 10−2, pTWAS-Splicing = 1.23 × 10−2) in the total population and GLO1(pPWAS-Banner = 4.89 × 10−3, pTWAS-Rnaseq = 1.41 × 10−3) in females. Brain imaging analysis revealed several different brain imaging phenotypes associated with MADD and GLO1 genes. Our study identified multiple candidate genes associated with PTSD in the proteome and transcriptome levels, which may provide new clues to the pathogenesis of PTSD.

Previous studies have suggested that vitamin D (VD) was associated with psychiatric diseases, but efforts to elucidate the functional relevance of VD with depression and anxiety from genetic perspective have been limited. Based on the UK Biobank cohort, we first calculated polygenic risk score (PRS) for VD from genome-wide association study (GWAS) data of VD. Linear and logistic regression analysis were conducted to evaluate the associations of VD traits with depression and anxiety traits, respectively. Then, using individual genotype and phenotype data from the UK Biobank, genome-wide environment interaction studies (GWEIS) were performed to identify the potential effects of gene × VD interactions on the risks of depression and anxiety traits. In the UK Biobank cohort, we observed significant associations of blood VD level with depression and anxiety traits, as well as significant associations of VD PRS and depression and anxiety traits. GWEIS identified multiple candidate loci, such as rs114086183 (p = 4.11 × 10−8, LRRTM4) for self-reported depression status and rs149760119 (p = 3.88 × 10−8, GNB5) for self-reported anxiety status. Our study results suggested that VD was negatively associated with depression and anxiety. GWEIS identified multiple candidate genes interacting with VD, providing novel clues for understanding the biological mechanism potential associations between VD and psychiatric disorders.

Dietary habits have considerable impact on brain development and mental health. Despite long-standing interest in the association of dietary habits with mental health, few population-based studies of dietary habits have assessed depression and fluid intelligence. Our aim is to investigate the association of dietary habits with depression and fluid intelligence. In total, 814 independent loci were utilized to calculate the individual polygenic risk score (PRS) for 143 dietary habit-related traits. The individual genotype data were obtained from the UK Biobank cohort. Regression analyses were then conducted to evaluate the association of dietary habits with depression and fluid intelligence, respectively. PLINK 2.0 was utilized to detect the single nucleotide polymorphism (SNP) × dietary habit interaction effect on the risks of depression and fluid intelligence. We detected 22 common dietary habit-related traits shared by depression and fluid intelligence, such as red wine glasses per month, and overall alcohol intake. For interaction analysis, we detected that OLFM1 interacted with champagne/white wine in depression, while SYNPO2 interacted with coffee type in fluid intelligence. Our study results provide novel useful information for understanding how eating habits affect the fluid intelligence and depression.

Longan pericarp proanthocyanidins (LPPs) were extracted and examined by structural and bioactive analyses. By 1H and 13C NMR spectra, LPPs were identified for the first time containing dominant catechin/epicatechin units with a mean degree of polymerisation of 3.3. Consistent with this result, electron spray ionisation (ESI) mass spectra revealed that the predominant LPPs were poly(epi)catechin with abundant A-type and B-type linkages. Matrix-assisted laser desorption ionisation time of flight (MALDI-TOF) mass spectra of LPPs showed dominant [M + Na]+ peaks that corresponded to procyanidin trimers–octamers. The presence of galloyl group in monomeric units of LPPs was confirmed by FT-IR, NMR, ESI and MALDI-TOF mass spectrometry (MS). Moreover, LPPs had a strong antioxidant activity of 1.23 × 104 µmol TE/g as measured by oxygen radical scavenging capacity (ORAC), and α-amylase inhibitory activity with IC50 for uncompetitive α-amylase inhibition of 0.075 mg/mL. These results indicate LPPs are promising antioxidant which could be applied as potential functional food components.

Glyceollin I, an induced phytoalexin isolated from soybean, has been reported to have various bioactivities, including anti-bacterial, anti-nematode, anti-fungal, anti-estrogenic and anti-cancer, anti-oxidant, anti-inflammatory, insulin sensitivity enhancing, and attenuation of vascular contractions. Here we show that glyceollin I has hormesis and extends yeast life span at low (nM) doses in a calorie restriction (CR)-dependent manner, while it reduces life span and inhibits yeast cell proliferation at higher (μM) doses. In contrast, the other two isomers (glyceollin II and III) cannot extend yeast life span and only show life span reduction and antiproliferation at higher doses. Our results in anti-aging activity indicate that glyceollin I might be a promising calorie restriction mimetic candidate, and the high content of glyceollins could improve the bioactivity of soybean as functional food ingredients.

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. [ABSTRACT FROM AUTHOR]