(1) Background: Increasing evidence shows that sedentary behaviors are associated with neuropsychiatric disorders (NPDs) and thus may be a modifiable factor to target for the prevention of NPDs. However, the direction and causality for the relationship remain unknown; sedentary behaviors could increase or decrease the risk of NPDs, and/or NPDs may increase or decrease engagement in sedentary behaviors. (2) Methods: This Mendelian randomization (MR) study with two samples included independent genetic variants related to sedentary behaviors (n = 408,815), Alzheimer’s disease (AD; n = 63,926), schizophrenia (SCZ; n = 105,318), and major depressive disorder (MDD; n = 500,199), which were extracted from several of the largest non-overlapping genome-wide association studies (GWASs), as instrumental variables. The summarized MR effect sizes from each instrumental variable were combined in an IVW (inverse-variance-weighted) approach, with various approaches (e.g., MR-Egger, weighted median, MR-pleiotropy residual sum and outlier), and sensitivity analyses were performed to identify and remove outliers and assess the horizontal pleiotropy. (3) Results: The MR evidence and linkage disequilibrium score regression revealed a consistent directional association between television watching and MDD (odds ratio (OR), 1.13 for MDD per one standard deviation (SD) increase in mean television watching time; 95% CI, 1.06–1.20; p = 6.80 × 10⁻⁵) and a consistent relationship between computer use and a decrease in the risk of AD (OR, 0.52 for AD per one SD increase in mean computer use time; 95% CI, 0.32–0.84; p = 8.20 × 10⁻³). In the reverse direction, MR showed a causal association between a reduced risk of SCZ and an increase in driving time (β, −0.016; 95% CI, −0.027–−0.004; p = 8.30 × 10⁻³). (4) Conclusions: Using genetic instrumental variables identified from large-scale GWASs, we found robust evidence for a causal relationship between long computer use time and a reduced risk of AD, and for a causal relationship between long television watching time and an increased risk of MDD. In reverse analyses, we found that SCZ was causally associated with reduced driving time. These findings fit in with our observations and prior knowledge as well as emphasizing the importance of distinguishing between different domains of sedentary behaviors in epidemiologic studies of NPDs.

Previous observational studies reported associations between non-steroidal anti-inflammatory drugs (NSAIDs) and major depressive disorder (MDD), however, these associations are often inconsistent and underlying biological mechanisms are still poorly understood. We conducted a two-sample Mendelian randomisation (MR) study to examine relationships between genetic variants and NSAID target gene expression or DNA methylation (DNAm) using publicly available expression, methylation quantitative trait loci (eQTL or mQTL) data and genetic variant-disease associations from genome-wide association studies (GWAS of MDD). We also assessed drug exposure using gene expression and DNAm levels of NSAID targets as proxies. Genetic variants were robustly adjusted for multiple comparisons related to gene expression, DNAm was used as MR instrumental variables and GWAS statistics of MDD as the outcome. A 1-standard deviation (SD) lower expression of NEU1 in blood was related to lower C-reactive protein (CRP) levels of −0.215 mg/L (95% confidence interval (CI): 0.128–0.426) and a decreased risk of MDD (odds ratio [OR] = 0.806; 95% CI: 0.735–0.885; p = 5.36 × 10⁻⁶). A concordant direction of association was also observed for NEU1 DNAm levels in blood and a risk of MDD (OR = 0.886; 95% CI: 0.836–0.939; p = 4.71 × 10⁻⁵). Further, the genetic variants associated with MDD were mediated by NEU1 expression via DNAm (β = −0.519; 95% CI: −0.717 to −0.320256; p = 3.16 × 10⁻⁷). We did not observe causal relationships between inflammatory genetic marker estimations and MDD risk. Yet, we identified a concordant association of NEU1 messenger RNA and an adverse direction of association of higher NEU1 DNAm with MDD risk. These results warrant increased pharmacovigilance and further in vivo or in vitro studies to investigate NEU1 inhibitors or supplements for MDD.

Background: Mild cognitive impairment (MCI) is the stage between cognitive decline due to physiological aging and the severity of decline seen in neurodegenerative disorders like Alzheimer disease (AD), which is among the most prevalent neurodegenerative disorders characterized by cognitive impairment. People with MCI are at increased risk of developing AD. Although MCI and AD are incurable, nutritional interventions can potentially delay or prevent their onset. Consequently, effective interventions used to decelerate or alleviate the progress of cognitive impairment in older people are a significant focus in geriatric care. Given the synergistic effects of nutrition on health, assessing the effectiveness of nutritional supplements or dietary composition in preventing MCI or AD is essential for developing interventional strategies. Objective: Our study aims to assess the effectiveness of various nutritional interventions, including special dietary types, dietary patterns, specific foods, nutritional intake, and nutritional supplements, in preventing cognitive decline among patients diagnosed with MCI or AD. To achieve this, we will use a comprehensive approach, including network meta-analysis, pairwise meta-analysis, and systematic review of randomized controlled trials (RCTs). Methods: The review will follow the Population, Intervention, Comparison, Outcome (PICO) model and the PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) guidelines. Two investigators will independently search PubMed electronically. Data extraction will follow the inclusion criteria, and data will be assessed for risk of bias using a revised tool. Additionally, evidence quality will be evaluated using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) framework. The outcomes of interest are assessing the cognitive outcomes in patients with MCI or AD. A systematic literature search will be conducted, identifying randomized controlled trials that investigate the impact of these nutritional interventions on cognitive function decline in individuals with MCI and AD. Network meta-analyses (random-effects model) and pairwise meta-analyses will then estimate the relative effectiveness of different nutritional interventions. Results: We included 51 studies, published between 1999 and 2023 (27 studies for AD and 24 studies for MCI) and involving 8420 participants. We completed data extraction for all 51 studies by December 2023. Currently, we are actively engaged in data analysis and manuscript preparation. We plan to finalize the manuscript and publish the comprehensive results by the end of 2024. Conclusions: Our study holds significant clinical relevance given the rising prevalence of AD and the potential influence of nutritional interventions on cognitive function in individuals with MCI and AD. By investigating this relationship, our research aims to inform evidence-based decision-making in the development of prevention strategies for MCI and AD. The outcomes are expected to contribute to the establishment of reliable recommendations for MCI or AD management, providing substantial support in the field. Trial Registration: PROSPERO CRD42022331173; http://tinyurl.com/3snjp7a4 International Registered Report Identifier (IRRID): PRR1-10.2196/47196

Background: Previous studies have demonstrated the value of re-analysing publicly available genetics data with recent analytical approaches. Publicly available datasets, such as the Women’s Health Initiative (WHI) offered by the database of genotypes and phenotypes (dbGaP), provide a wealthy resource for researchers to perform multiple analyses, including Genome-Wide Association Studies. Often, the genetic information of individuals in these datasets are stored in imputed dosage files output by MaCH; mldose and mlinfo files. In order for researchers to perform GWAS studies with this data, they must first be converted to a file format compatible with their tool of choice e.g., PLINK. Currently, there is no published tool which easily converts the datasets provided in MACH dosage files into PLINK-ready files. Results: Herein, we present Canary a singularity-based tool which converts MaCH dosage files into PLINK-compatible files with a single line of user input at the command line. Further, we provide a detailed tutorial on preparation of phenotype files. Moreover, Canary comes with preinstalled software often used during GWAS studies, to further increase the ease-of-use of HPC systems for researchers. Conclusions: Until now, conversion of imputed data in the form of MaCH mldose and mlinfo files needed to be completed manually. Canary uses singularity container technology to allow users to automatically convert these MaCH files into PLINK compatible files. Additionally, Canary provides researchers with a platform to conduct GWAS analysis more easily as it contains essential software needed for conducting GWAS studies, such as PLINK and Bioconductor. We hope that this tool will greatly increase the ease at which researchers can perform GWAS with imputed data, particularly on HPC environments.

Autism spectrum disorder (ASD) is a complex neurological condition marked by social, communication, and behavioral challenges. Current treatments are limited, with few approved drugs. This study used network analysis of key driver genes from blood and brain tissues to identify potential therapeutic drugs for ASD. We examined Gene Expression Omnibus (GEO) data from postmortem brain (GSE28521) and blood leukocyte (GSE42133) samples to find differentially expressed genes. Key driver genes were identified using weighted key driver analysis, supported by literature, knockout mouse model databases, and enrichment analysis. Drug repositioning was performed with PharmOmics and Connectivity Map (CMap) platforms. In blood samples, 204 key driver genes were discovered, associated with cell cycle regulation and stress response. In brain samples, 290 key driver genes focused on ribosomal activity and protein production. An integrated protein-protein interaction (PPI) network identified 16 shared key driver genes, demonstrating common disease signatures including RNA metabolism, protein regulation, SLIT and ROBO signaling, and antiviral pathways. Drug repositioning revealed 23 potential drugs for ASD, with sulpiride and everolimus demonstrating promise, and 19 drugs exhibiting neurological significance, including six with substantial blood-brain barrier permeability. Our study reveals both tissue-specific and shared molecular signatures of ASD in blood and brain tissues through PPI network analysis. We identified 16 key driver genes and 23 potential therapeutic drugs. Additionally, we discovered twelve novel key driver genes associated with ASD, emphasizing their roles in neurological and immune functions. These findings enhance our understanding of the molecular basis of ASD and suggest new therapeutic possibilities.

BACKGROUND Mild cognitive impairment (MCI) is the stage between cognitive decline due to physiological aging and the severity of decline seen in neurodegenerative disorders like Alzheimer disease (AD), which is among the most prevalent neurodegenerative disorders characterized by cognitive impairment. People with MCI are at increased risk of developing AD. Although MCI and AD are incurable, nutritional interventions can potentially delay or prevent their onset. Consequently, effective interventions used to decelerate or alleviate the progress of cognitive impairment in older people are a significant focus in geriatric care. Given the synergistic effects of nutrition on health, assessing the effectiveness of nutritional supplements or dietary composition in preventing MCI or AD is essential for developing interventional strategies. OBJECTIVE Our study aims to assess the effectiveness of various nutritional interventions, including special dietary types, dietary patterns, specific foods, nutritional intake, and nutritional supplements, in preventing cognitive decline among patients diagnosed with MCI or AD. To achieve this, we will use a comprehensive approach, including network meta-analysis, pairwise meta-analysis, and systematic review of randomized controlled trials (RCTs). METHODS The review will follow the Population, Intervention, Comparison, Outcome (PICO) model and the PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) guidelines. Two investigators will independently search PubMed electronically. Data extraction will follow the inclusion criteria, and data will be assessed for risk of bias using a revised tool. Additionally, evidence quality will be evaluated using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) framework. The outcomes of interest are assessing the cognitive outcomes in patients with MCI or AD. A systematic literature search will be conducted, identifying randomized controlled trials that investigate the impact of these nutritional interventions on cognitive function decline in individuals with MCI and AD. Network meta-analyses (random-effects model) and pairwise meta-analyses will then estimate the relative effectiveness of different nutritional interventions. RESULTS We included 51 studies, published between 1999 and 2023 (27 studies for AD and 24 studies for MCI) and involving 8420 participants. We completed data extraction for all 51 studies by December 2023. Currently, we are actively engaged in data analysis and manuscript preparation. We plan to finalize the manuscript and publish the comprehensive results by the end of 2024. CONCLUSIONS Our study holds significant clinical relevance given the rising prevalence of AD and the potential influence of nutritional interventions on cognitive function in individuals with MCI and AD. By investigating this relationship, our research aims to inform evidence-based decision-making in the development of prevention strategies for MCI and AD. The outcomes are expected to contribute to the establishment of reliable recommendations for MCI or AD management, providing substantial support in the field. CLINICALTRIAL PROSPERO CRD42022331173; http://tinyurl.com/3snjp7a4 INTERNATIONAL REGISTERED REPORT PRR1-10.2196/47196