Unveiling promising drug targets for autism spectrum disorder: insights from genetics, transcriptomics, and proteomics.

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder for which current treatments are limited and drug development costs are prohibitive. Identifying drug targets for ASD is crucial for the development of targeted therapies. Summary-level data of expression quantitative trait loci obtained from GTEx, protein quantitative trait loci data from the ROSMAP project, and two ASD genome-wide association studies datasets were utilized for discovery and replication. We conducted a combined analysis using Mendelian randomization (MR), transcriptome-wide association studies, Bayesian colocalization, and summary-data-based MR to identify potential therapeutic targets associated with ASD and examine whether there are shared causal variants among them. Furthermore, pathway and drug enrichment analyses were performed to further explore the underlying mechanisms and summarize the current status of pharmacological targets for developing drugs to treat ASD. The protein-protein interaction (PPI) network and mouse knockout models were performed to estimate the effect of therapeutic targets. A total of 17 genes revealed causal associations with ASD and were identified as potential targets for ASD patients. Cathepsin B (CTSB) [odd ratio (OR) = 2.66 95, confidence interval (CI): 1.28-5.52, P = 8.84 × 10-3], gamma-aminobutyric acid type B receptor subunit 1 (GABBR1) (OR = 1.99, 95CI: 1.06-3.75, P = 3.24 × 10-2), and formin like 1 (FMNL1) (OR = 0.15, 95CI: 0.04-0.58, P = 5.59 × 10-3) were replicated in the proteome-wide MR analyses. In Drugbank, two potential therapeutic drugs, Acamprosate (GABBR1 inhibitor) and Bryostatin 1 (CASP8 inhibitor), were inferred as potential influencers of autism. Knockout mouse models suggested the involvement of the CASP8, GABBR1, and PLEKHM1 genes in neurological processes. Our findings suggest 17 candidate therapeutic targets for ASD and provide novel drug targets for therapy development and critical drug repurposing opportunities.

Lack of Causal Associations of Inflammatory Bowel Disease with Parkinson's Disease and Other Neurodegenerative Disorders.

BACKGROUND: Observational studies have indicated associations between inflammatory bowel disease (IBD) and neurodegenerative diseases, including Parkinson's disease (PD). OBJECTIVE: To evaluate the causal associations of IBD with PD and other selected neurodegenerative disorders using updated data. METHODS: Bidirectional two-sample Mendelian randomization studies using genome-wide association studies summary statistics of IBD and PD. RESULTS: We found a lack of evidence for the causal association of IBD on PD (odds ratio [OR], 1.014; 95% confidence interval [CI], 0.967-1.063; P = 0.573). Reverse analysis also indicated no evidence of a causal effect for PD on IBD (OR, 0.978; 95% CI, 0.910-1.052; P = 0.549). The causality between IBD and Alzheimer's disease, amyotrophic lateral sclerosis, and multiple sclerosis was unfounded (all P > 0.05). CONCLUSIONS: The updated analyses provide no clear evidence for causal associations of IBD with PD or the other three neurodegenerative diseases. Potential confounders might contribute to the previously observed associations, and further investigations are warranted. © 2023 International Parkinson and Movement Disorder Society.

Diagnostic consistency between admission and discharge of pediatric cases in a tertiary teaching hospital in China.

BACKGROUND: Patient-centered, high-quality health care relies on accurate and timely diagnosis. Diagnosis is a complex, error-prone process. Prevention of errors involves understanding the cause of errors. This study investigated diagnostic discordance between admission and discharge in pediatric cases. METHODS: We retrospectively reviewed the electronic medical records of 5381 pediatric inpatients during 2017-2018 in a tertiary teaching hospital. We analyzed diagnostic consistency by comparing the first 4 digits of admission and discharge ICD-10 codes of the cases and classified them as concordant for "complete and partial match" or discordant for "no match". RESULTS: Diagnostic discordance was observed in 49.2% with the highest prevalence in infections of the nervous and respiratory systems (Ps < 0.001). Multiple (multivariable) logistic regression analysis predicted a lower risk of diagnostic discordance with older children (aOR, 95%CI: 0.94, 0.93-0.96) and a higher risk with infectious diseases (aOR, 95%CI: 1.49, 1.33-1.66) and admission by resident and attending pediatricians (aOR, 95%CI: 1.41, 1.30-1.54). Discordant cases had a higher rate of antibiotic prescription (OR, 95%CI: 2.09, 1.87-2.33), a longer duration of antibiotic use (P = 0.02), a longer length of hospital stay (P < 0.001), and higher medical expenses (P < 0.001). CONCLUSIONS: This study denotes a considerably high rate of discordance between admission and discharge diagnoses with an associated higher and longer prescription of antibiotics, a longer length of stay, and higher medical expenses among Chinese pediatric inpatient cases. Infectious diseases were identified as high-risk clinical conditions for discordance. Considering potential diagnostic and coding errors, departmental investigation of preventable diagnostic discordance is suggested for quality health care and preventing potential medicolegal consequences.

Investigating shared genetic architecture between inflammatory bowel diseases and primary biliary cholangitis.

Background & Aims: Inflammatory bowel disease (IBD) is commonly associated with extraintestinal complications, including autoimmune liver disease. The co-occurrence of IBD and primary biliary cholangitis (PBC) has been increasingly observed, but the underlying relationship between these conditions remains unclear. Methods: Using summary statistics from genome-wide association studies (GWAS), we investigated the causal effects between PBC and IBD, including Crohn's disease (CD) and ulcerative colitis (UC). We also analyzed the shared genetic architecture between IBD and PBC using data from GWAS, bulk-tissue RNA sequencing, and single cell RNA sequencing, and explored potential functional genes. Result: There was a strong positive genetic correlation between PBC and IBD (linkage disequilibrium score regression: rg = 0.2249, p = 3.38 × 10-5). Cross-trait analysis yielded 10 shared-risk single nucleotide polymorphisms (SNPs), as well as nine novel SNPs, which were associated with both traits. Using Mendelian randomization, a stable causal effect was established of PBC on IBD. Genetically predicted PBC was found to have a risk effect on IBD (1.105; 95% CI: 1.058-1.15; p = 1.16 × 10-10), but not vice versa. Shared tissue-specific heritability enrichment was identified for PBC and IBD (including CD and UC) in lung, spleen, and whole-blood samples. Furthermore, shared enrichment was observed of specific cell types (T cells, B cells, and natural killer cells) and their subtypes. Nine functional genes were identified based on summary statistics-based Mendelian randomization. Conclusions: This study detected shared genetic architecture between IBD and PBC and demonstrated a stable causal relationship of genetically predicted PBC on the risk of IBD. These findings shed light on the biological basis of comorbidity between IBD and PBC, and have important implications for intervention and treatment targets of these two diseases simultaneously. Impact and Implications: The discovery of novel shared single nucleotide polymorphisms (SNPs) and functional genes provides insights into the common targets between inflammatory bowel disease (IBD) and primary biliary cholangitis (PBC), serving as a basis for new drug development and contributing to the study of disease pathogenesis. Additionally, the established significant causality and genetic correlation underscore the importance of clinical intervention in preventing the comorbidity of IBD and PBC. The enrichment of SNP heritability in specific tissues and cell types reveals the role of immune factors in the potential disease mechanisms shared between IBD and PBC. This stimulates further research on potential interventions and could lead to the development of new targets for immune-based therapies.

Genetically predicted causal associations between periodontitis and psychiatric disorders.

BACKGROUND: Psychiatric disorders have serious harm to individuals' lives with high disease burden. Observational studies reported inconsistent associations between periodontitis and some psychiatric disorders, and the causal correlations between them remain unknown. OBJECTIVE: This study aims to explore the causal associations between periodontitis and psychiatric disorders. METHODS: A series of two-sample Mendelian randomisation (MR) analyses were employed using genome-wide association study summary statistics for periodontitis in adults from Gene-Lifestyle Interactions in Dental Endpoints Consortium and 10 psychiatric disorders from Psychiatric Genomics Consortium. Causal effects were primarily estimated using the inverse-variance weighted (IVW) method. Various sensitivity analyses were also conducted to assess the robustness of our results. FINDINGS: The MR analysis suggested that genetically determined periodontitis was not causally associated with 10 psychiatric disorders (IVW, all p>0.089). Furthermore, the reverse MR analysis revealed that 10 psychiatric disorders had no causal effect on periodontitis (IVW, all p>0.068). We discovered that all the results were consistent in the four MR analytical methods, including the IVW, MR-Egger, weighted median and weighted mode. Besides, we did not identify any heterogeneity or horizontal pleiotropy in the sensitivity analysis. CONCLUSIONS: These results do not support bidirectional causal associations between genetically predicted periodontitis and 10 common psychiatric disorders. Potential confounders might contribute to the previously observed associations. CLINICAL IMPLICATIONS: Our findings might alleviate the concerns of patients with periodontitis or psychiatric disorders. However, further research was warranted to delve into the intricate relationship between dental health and mental illnesses.

HIPPO signaling-related signature for predicting prognosis and therapeutic response in gastric cancer.

Background: Gastric cancer (GC) is a multifactorial progressive disease with high mortality and heterogeneous prognosis. Effective prognostic biomarkers for GC were critically needed. Hippo signaling pathway is one of the critical mechanisms regulating the occurrence and development of GC, and has potential clinical application value for the prognosis and treatment of GC patients. However, there is no effective signature based on Hippo signaling pathway-related genes (HSPRGs) to predict the prognosis and treatment response of GC patients. Our study aimed to build a HSPRGs signature and explore its performance in improving prognostic assessment and drug therapeutic response in GC. Methods: Based on gene expression profiles obtained from The Cancer Genome Atlas (TCGA) database, we identified differentially expressed HSPRGs and conducted univariate and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis to construct a multigene risk signature. Subsequently, the Kaplan-Meier curve and receiver operating characteristic (ROC) were performed to evaluate the predictive value of the risk signature in both training and validation cohort. Furthermore, we carried out univariate and multivariate Cox regression analysis to investigate the independent prognostic factors and establish a predictive nomogram. The enriched signaling pathways in risk signature were analyzed by gene set enrichment analysis (GSEA). Tumor immune dysfunction and exclusion (TIDE) and drug sensitivity analysis were performed to depict therapeutic response in GC. Results: In total, 38 differentially expressed HSPRGs were identified, and final four genes (DLG3, TGFB3, TGFBR1, FZD6) were incorporated to build the signature. The ROC curve with average 1-, 3-, and 5-year areas under the curve (AUC) equal to .609, .634, and .639. Clinical ROC curve revealed that risk signature was superior to other clinicopathological factors in predicting prognosis. Calibration curves and C-index (.655) of nomogram showed excellent consistency. Besides, in the immunotherapy analysis, exclusion (p < 2.22 × 10-16) and microsatellite instability (p = .0058) performed significantly differences. Finally, our results suggested that patients in the high-risk group were more sensitive to specific chemotherapeutic agents. Conclusion: Results support the hypothesis that Hippo-related signature is a novel prognostic biomarker and predictor, which could help optimize GC prognostic stratification and inform clinical medication decisions.