False Discovery Rate Correction Research Articles

Causal role of 731 immune cells in diabetic nephropathy: a bi-directional two-sample Mendelian randomization study.

The primary cause of end-stage renal disease (ESRD) is diabetic nephropathy (DN), and a growing body of research indicates that immunology plays a part in how DN develops into ESRD. Our objective is to identify causal relationships between various immune invading cells and DN to identify possible targets for immunotherapy. This study used a complete Mendelian randomization (MR) analysis with two samples to identify the underlying mechanism linking immune cell characteristics with DN. Using publicly available genetic data, we investigated the causal link between 731 immune cell profiles and DN risk. Included were four different types of immune systems: morphological parameters (MP), absolute cell (AC), relative cell (RC), and median fluorescence intensities (MFI). The results' robustness, heterogeneity, and horizontal pleiotropy were confirmed through extensive sensitivity analysis. Following FDR (False Discovery Rate correction method) correction, no statistically significant differences were observed; however, six immunophenotypes were shown to be significantly associated with DN risk at the 0.25 level. Only CD28+ CD4- CD8- T cells were identified as the protective immunophenotype (OR = 0.588, 95% CI 0.437-0.792, P = 4.71 × 10-4). Moreover, DN had no discernible impact on immunophenotyping after FDR correction. Surprisingly, three unadjusted phenotypes with low P values were discovered to be positively correlated with the risk of DN: CD20 on IgD- CD27- B cells (OR = 1.263, 95% CI 1.076-1.482, P = 4.22 × 10-3), CD8 on naive CD8 + T cells with Effector Memory (OR = 1.107, 95% CI 1.013-1.209, P = 2.40 × 10-2), and CD8 on Effector Memory CD8 + T cells (OR = 1.126, 95% CI 1.024-1.239, P = 1.46 × 10-2). Our findings provide a genetic basis for the association between immune cells and DN and should inform future clinical research.

Exercise-Induced Proteomic Profile Changes in Patients with Advanced Heart Failure

Background/Objectives: The pathophysiological background of the processes activated by physical activity in patients with heart failure (HF) is not fully understood. Proteomic studies can help to preliminarily identify new protein markers for unknown or poorly defined physiological processes. We aimed to analyse the changes in the plasma proteomic profile of HF patients after a cardiopulmonary exercise test (CPET) to define pathways involved in the response to exercise. Methods: The study prospectively enrolled 20 male patients with advanced HF (aged 53.3 ± 8.3 years). Blood samples were taken from the patients before and immediately after the CPET to obtain plasma proteomic profiles. Two-sample t-tests (paired or non-paired) were performed with and without false discovery rate (FDR) correction for multiple testing. Enrichment analysis was performed to associate biological processes and pathways with the study results. Results: A total of 968 plasma proteins were identified, of which 722 underwent further statistical analysis. Of these, 236 proteins showed differential expression when comparing all plasma samples collected before and after CPT (p < 0.05), and for 86 of these the difference remained statistically significant after FDR correction. Proteins whose expression changed after exercise are mostly involved in immune response and inflammatory processes, coagulation, cell adhesion, regulation of cellular response to stimulus and regulation of programmed cell death. There were no differences in resting proteomics according to HF etiology (ischemic vs. non-ischemic). Conclusions: Changes in the proteomic profile revealed a complexity of exercise-induced processes in patients with HF, suggesting that few major physiological pathways are involved. Further studies focusing on specific pathways are needed.

Relationship of metabolites and metabolic ratios with schizophrenia: a mendelian randomization study

BackgroundThis study aims to investigate the causal relationship of human plasma metabolites and metabolic ratios with schizophrenia (SCZ).MethodsWe employed Mendelian Randomization (MR) approach to comprehensively analyze two large-scale metabolomics and schizophrenia Genome-Wide Association Study (GWAS) datasets, incorporating a total of 1091 metabolites and 309 metabolic ratios, with 52017 schizophrenia patients and 75889 healthy controls. The inverse variance-weighted (IVW) method was utilized to estimate the causal relationship between exposure and outcome. To provide a more comprehensive evaluation, additional Mendelian Randomization (MR) approaches were employed, including MR-Egger regression, weighted median, simple mode, and weighted mode methods. These analyses assessed the causal effects between blood metabolites, metabolic ratios, and schizophrenia. Tests for pleiotropy and heterogeneity were conducted. False Discovery Rate (FDR) correction was applied to account for multiple comparisons and heterogeneity, ensuring the robustness and reliability of our findings. Consistent with previous studies, an FDR threshold of < 0.2 was considered suggestive of a causal relationship, while an FDR of < 0.05 was considered to indicate a significant causal relationship.ResultsThe final results revealed that a significant causal association was found between the levels of two metabolites and schizophrenia, Alliin (OR = 0.915, 95%CI = 0.879–0.953, P = 1.93 × 10− 5, FDR = 0.013) was associated with a decreased risk of schizophrenia, N-actylcitrulline (OR = 1.058, 95%CI = 1.034–1.083, P = 1.4 × 10− 6, FDR = 0.002) was associated with increased risk of schizophrenia. When adjusting FDR to 0.2, the results showed that 4 metabolite levels and 2 metabolite ratios were suggestively causally associated with a reduced risk of schizophrenia including 2-aminooctanoate (OR = 0.904, 95%CI = 0.847–0.964, P = 0.002, FDR = 0.160), N-lactoylvaline (OR = 0.853, 95%CI = 0.775–0.938, P = 0.001,FDR = 0.122), X − 21310 (OR = 0.917, 95%CI = 0.866–0.971, P = 0.003,FDR = 0.195), X − 26111 (OR = 0.932, 95%CI = 0.890–0.976, P = 0.003,FDR = 0.189), Arachidonate (20:4n6) to oleate to vaccenate (18:1) ratio (OR = 0.945, 95%CI = 0.914–0.977, P = 8.2 × 10− 4, FDR = 0.104), and Citrulline to ornithine ratio (OR = 0.924, 95%CI = 0.881–0.969, P = 0.001, FDR = 0.122), while 4 metabolite levels and 2 metabolite ratios were suggestively causally associated with an increased risk of schizophrenia including N2, N5-diacetylornithine (OR = 1.090, 95%CI = 1.031–1.153, P = 0.003, FDR = 0.185), N − acetyl − 2−aminooctanoate (OR = 1.069, 95%CI=(1.027–1.114, P = 0.001, FDR = 0.127), N − acetyl − 2−aminoadipate (OR = 1.081, 95%CI = 1.030–1.133, P = 0.001, FDR = 0.128), X − 13844 (OR = 1.110, 95%CI = 1.036–1.190, P = 0.003, FDR = 0.196), X − 24556 (OR = 1.083, 95%CI = 1.036–1.132, P = 4.5 × 10− 4, FDR = 0.098), X − 24736 (OR = 1.065, 95%CI = 1.028–1.104, P = 5.6 × 10− 4, FDR = 0.098), N − acetylasparagine (OR = 1.048, 95%CI = 1.021–1.075, P = 4.5 × 10− 4, FDR = 0.098), N − acetylarginine (OR = 1.060, 95%CI = 1.028–1.092, P = 1.8 × 10− 4, FDR = 0.083), Cysteine to alanine ratio (OR = 1.086, 95%CI = 1.036–1.138, P = 6.5 × 10− 4, FDR = 0.101), and Benzoate to linoleoyl − arachidonoyl − glycerol (18:2 to 20:4) ratio (OR = 1.070, 95%CI = 1.025–1.117, P = 0.002, FDR = 0.158).ConclusionOur study results provide valuable insights for identifying diagnostic biomarkers related to schizophrenia and offer preliminary research findings for further exploration of the mechanisms linking schizophrenia and metabolism.

SNP Markers: Analysis of Genetic Diversity and Identification of Genomic Regions in Pantaneiro Sheep and Texel Sheep Under Natural Selection.

Sheep farming is growing substantially in Brazil, driven by the increasing demand for sheep meat. This rising demand has heightened the focus on sheep, making them the subject of numerous studies, including those centered on genetic analysis. A notable research area involves Pantaneiro sheep, which are indigenous to the Pantanal region of Mato Grosso do Sul and other locations. These sheep are of particular interest due to their adaptation to the unique environmental conditions of the Pantanal, a floodplain characterized by its distinctive climatic and ecological features. This study primarily aimed to conduct a comprehensive genomic analysis of Pantanal sheep subjected to natural selection within the Pantanal region and compare different sample herds using methodological approaches. Genomic analysis was performed to examine genetic diversity and structure via GGP50K single nucleotide polymorphism (SNP) analysis. A sample of 192 adult sheep over 4 years old was categorized into seven populations based on location: Six populations comprised Pantaneiro sheep with one Texel sheep population. Outlier SNPs were assessed to pinpoint regions under natural selection, with comparisons between the Pantaneiro and the commercial Texel breeds. All data analyses were conducted using the R programming language, employing specialized genetic analysis packages. These outlier SNPs were detected using three methodologies, PCAdapt, OutFLANK, and FDIST2/fsthet, with false discovery rate (FDR) corrections applied to ensure result accuracy. Each method was evaluated, and the genes associated with the identified SNPs were cross-referenced with the most recent sheep genome database, focusing specifically on genes with known phenotypic traits. Analysis of a sample comprising 192 adult individuals revealed greater genetic variability within the Pantaneiro breed than the Texel breed, highlighting the adaptation of the Pantaneiro breed to the unique Pantanal environment. Conversely, the Texel breed exhibited significantly higher levels of inbreeding, attributed to its controlled breeding practices. Outlier SNPs were detected with notable variation across different methodologies, underscoring the importance of FDR correction in ensuring the reliability and concentration of identified outliers. These outlier SNPs facilitated the identification of genes associated with key phenotypic traits, including hair growth, tissue regeneration, pigmentation regulation, and muscle capacity. The integrated analysis of methodologies demonstrated significant efficiency in elucidating the genomic landscape of Pantanal sheep, highlighting the genetic richness inherent in sheep from the Pantanal region of Mato Grosso do Sul. The techniques employed effectively identified outlier SNPs associated with phenotypically relevant genes. These findings, which reveal greater genetic variability and adaptability, underscore the potential of these animals for future research and their significance within Brazilian sheep farming. The Texel breed served as a valuable comparative group, illustrating the limited genetic variability in highly controlled breeding environments.

Unveiling the influence of circulating immune cells count on type 1 diabetes: Insight from bidirectional Mendelian randomization.

Observational studies have demonstrated an association between circulating immune cell and type 1 diabetes (T1D) risk. However, it is unknown whether this relationship is causal. Herein, we adopted a 2-sample bidirectional Mendelian randomization study to figure out whether circulating immune cell profiles causally impact T1D liability. Summary statistical data were obtained from genome-wide association study (GWAS) to investigate the causal relationship between white cell (WBC) count, 5 specific WBC count, and lymphocyte subtypes cell count and T1D risk. After false discovery rate (FDR) correction, the results indicated that lower lymphocyte cell count (odds ratio [OR] per 1 standard deviation [SD] decrease = 0.746, 95% confidence interval (CI): 0.673-0.828, PFDR = 0.036), and basophil cell count (OR per 1 SD decrease = 0.808, 95% CI: 0.700-0.932, PFDR = 0.010) were causally associated with T1D susceptibility. However, the absolute count of WBC, monocyte, neutrophil, eosinophil, and lymphocyte subtypes cell had no statistically significant effect on T1D risk. Taken together, this study indicates suggestive association between circulating immune cell count and T1D. Moreover, lower numbers of circulating lymphocyte and basophil cell were associated with the increased risk of T1D, which confirmed the immunity predisposition for T1D.

Investigating the uncertain causal link between gut microbiota and glaucoma: A genetic correlation and Mendelian randomisation study.

Glaucoma is the most common cause of irreversible blindness, and gut microbiota (GM) is associated with glaucoma. Whether this association represents a causal role remains unknown. This study aims to assess the potential association and causal link between GM and various forms of glaucoma, emphasising the need for cautious interpretation of the strength of these associations. Employing a two-sample bidirectional Mendelian randomisation (MR) framework with false discovery rate correction and various sensitivity analyses, supplemented by genetic correlation analysis via linkage disequilibrium score regression (LDSC) and colocalisation for European summary-level data between MiBioGen consortium and FinnGen Study, we sought to explore the relationship between GM and glaucoma. While certain microbial taxa showed potential associations with glaucoma subtypes (e.g., Erysipelotrichaceae with primary angle closure glaucoma, Senegalimassilia with exfoliation glaucoma), the overall findings suggest a complex and not definitively causal relationship between GM and glaucoma. Notably, reverse MR analysis did not establish a significant causal effect of glaucoma on GM composition, and no consistent genetic correlations were observed between GM and glaucoma. While our study provides some evidence of associations between specific GM taxa and glaucoma, the results underscore the complexity of these relationships and the need for further research to clarify the potential causal links. The findings highlight the importance of interpreting the gut-eye axis with caution and suggest that while GM may play a role in glaucoma, it is unlikely to be a predominant causal factor.

Causal relationship between gut microbiota and insulin-like growth factor 1: a bidirectional two-sample Mendelian randomization study.

The causal relationship between gut microbiota and insulin-like growth factor 1 (IGF-1) remains unclear. The purpose of this study was to explore the causal relationship between gut microbiota and IGF-1 in men and women. Single-nucleotide polymorphisms (SNPs) related to gut microbiota were derived from pooled statistics from large genome-wide association studies (GWASs) published by the MiBioGen consortium. Pooled data for IGF-1 were obtained from a large published GWAS. We conducted Mendelian randomization (MR) analysis, primarily using the inverse variance weighted (IVW) method. Additionally, we performed sensitivity analyses to enhance the robustness of our results, focusing on assessing heterogeneity and pleiotropy. In forward MR analysis, 11 bacterial taxa were found to have a causal effect on IGF-1 in men; 14 bacterial taxa were found to have a causal effect on IGF-1 in women (IVW, all P < 0.05). After false discovery rate (FDR) correction, all bacterial traits failed to pass the FDR correction. In reverse MR analysis, IGF-1 had a causal effect on nine bacterial taxa in men and two bacterial taxa in women respectively (IVW, all P < 0.05). After FDR correction, the causal effect of IGF-1 on order Actinomycetales (PFDR = 0.049) remains in men. The robustness of the IVW results was further confirmed after heterogeneity and pleiotropy analysis. Our study demonstrates a bidirectional causal link between the gut microbiota and IGF-1, in both men and women.

Differences in brain structure and cognitive performance between patients with long-COVID and those with normal recovery

BackgroundThe pathophysiology of protracted symptoms after COVID-19 is unclear. This study aimed to determine if long-COVID is associated with differences in baseline characteristics, markers of white matter diffusivity in the brain, and lower scores on objective cognitive testing. MethodsIndividuals who experienced COVID-19 symptoms for more than 60 days post-infection (long-COVID) (n = 56) were compared to individuals who recovered from COVID-19 within 60 days of infection (normal recovery) (n = 35). Information regarding physical and mental health, and COVID-19 illness was collected. The National Institute of Health Toolbox Cognition Battery was administered. Participants underwent magnetic resonance imaging (MRI) with diffusion tensor imaging (DTI). Tract-based spatial statistics were used to perform a whole-brain voxel-wise analysis on standard DTI metrics (fractional anisotropy, axial diffusivity, mean diffusivity, radial diffusivity), controlling for age and sex. NIH Toolbox Age-Adjusted Fluid Cognition Scores were used to compare long-COVID and normal recovery groups, covarying for Age-Adjusted Crystallized Cognition Scores and years of education. False discovery rate correction was applied for multiple comparisons. ResultsThere were no significant differences in age, sex, or history of neurovascular risk factors between the groups. The long-COVID group had significantly (p < 0.05) lower mean diffusivity than the normal recovery group across multiple white matter regions, including the internal capsule, anterior and superior corona radiata, corpus callosum, superior fronto-occiptal fasciculus, and posterior thalamic radiation. However, the effect sizes of these differences were small (all β<|0.3|) and no significant differences were found for the other DTI metrics. Fluid cognition composite scores did not differ significantly between the long-COVID and normal recovery groups (p > 0.05). ConclusionsDifferences in diffusivity between long-COVID and normal recovery groups were found on only one DTI metric. This could represent subtle areas of pathology such as gliosis or edema, but the small effect sizes and non-specific nature of the diffusion indices make pathological inference difficult. Although long-COVID patients reported many neuropsychiatric symptoms, significant differences in objective cognitive performance were not found.

Abnormal Structural–Functional Coupling and MRI Alterations of Brain Network Topology in Progressive Supranuclear Palsy

BackgroundProgressive supranuclear palsy (PSP) can cause structural and functional brain reconstruction. There is a lack of knowledge about the consistency between structural–functional (S–F) connection networks in PSP, despite growing evidence of anomalies in various single brain network parameters.PurposeTo study the changes in the structural and functional networks of PSP, network's topological properties including degree, and the consistency of S–F coupling. The relationship with clinical scales was examined including the assessment of PSP severity, and so on.Study TypeRetrospective.SubjectsA total of 51 PSP patients (70.04 ± 7.46, 25 females) and 101 healthy controls (64.58 ± 8.84, 58 females).Field Strength/Sequence3‐T, resting‐state functional MRI, diffusion tensor imaging, and T1‐weighted images.AssessmentA graph‐theoretic approach was used to evaluate structural and functional network topology metrics. We used the S–F coupling changes to explore the consistency of structural and functional networks.Statistical TestsIndependent samples t tests were employed for continuous variables, χ2 tests were used for categorical variables. For network analysis, two‐sample t tests was used and implied an false discovery rate (FDR) correction. Pearson correlation analysis was used to explore the correlations. A P‐value &lt;0.05 was considered statistically significant.ResultsPSP showed variations within and between modules. Specifically, PSP had decreased network properties changes (t = −2.0136; t = 2.5409; t = −2.5338; t = −2.4296; t = −2.5338; t = 2.8079). PSP showed a lower coupling in the thalamus and left putamen and a higher coupling in the visual, somatomotor, dorsal attention, and ventral attention network. S–F coupling was related to the number of network connections (r = 0.32, r = 0.22) and information transmission efficiency (r = 0.55, r = 0.28). S–F coupling was related to basic academic ability (r = 0.39) and disinhibition (r = 0.49).Data ConclusionPSP may show abnormal S–F coupling and intramodular and intermodular connectome in the structural and functional networks.Level of Evidence3Technical EfficacyStage 3

Causal influence of plasma metabolites on age-related macular degeneration: A Mendelian randomization study.

Using genome-wide association study data from European populations, this research clarifies the causal relationship between plasma metabolites and age-related macular degeneration (AMD) and employs Metabo Analyst 5.0 for enrichment analysis to investigate their metabolic pathways. Employing Mendelian randomization analysis, this study leveraged single nucleotide polymorphisms significantly associated with plasma metabolites as instrumental variables. This approach established a causal link between metabolites and AMD. Analytical methods such as inverse-variance weighted, Mendelian randomization-Egger, and weighted median were applied to validate causality. Mendelian Randomization Pleiotropy Residual Sum and Outlier was utilized for outlier detection and correction, and Cochran's Q test was conducted to assess heterogeneity. To delve deeper into the metabolic characteristics of AMD, metabolic enrichment analysis was performed using Metabo Analyst 5.0. These combined methods provided a robust framework for elucidating the metabolic underpinnings of AMD. The 2-sample MR analysis, after meticulous screening, identified causal relationships between 88 metabolites and AMD. Of these, 16 metabolites showed a significant causal association. Following false discovery rate correction, 3 metabolites remained significantly associated, with androstenediol (3 beta, 17 beta) disulfate (2) exhibiting the most potent protective effect against AMD. Further exploration using Metabo Analyst 5.0 highlighted 4 metabolic pathways potentially implicated in AMD pathogenesis. This pioneering MR study has unraveled the causal connections between plasma metabolites and AMD. It identified several metabolites with a causal impact on AMD, with 3 maintaining significance after FDR correction. These insights offer robust causal evidence for future clinical applications and underscore the potential of these metabolites as clinical biomarkers in AMD screening, treatment, and prevention strategies.

121 Copy number variation: From mapping to variance components in Holsteins

Abstract Copy number variations (CNVs) modify transcription levels mainly through changing genes and regulatory elements dosages. Hence, CNVs can contribute to the additive genetic variance of quantitative traits, which might not be fully captured by SNPs. Here, CNVs were mapped from 3,601 Holsteins and their contribution to complex traits was explored by i) quantitative trait loci (QTL) enrichment analysis, and ii) variance component analysis for metritis (1 = disease, 0 = no disease). The 4,113 CNVs derived from high-density (777k) genotypic information were compiled into 1,184 CNV regions (CNVRs) overlapping 7,832 QTLs reported in dairy cattle and available in the AnimalQTLdb. Fisher’s exact test was applied to perform the QTL enrichment analysis followed by False Discovery Rate (FDR) correction. Then, QTLs overlapping CNVRs were enriched for traits when the corrected P-value (PFDR) was lower than 0.05. For variance components estimation, genomic information from all CNVs loci was used to build the CNV-derived genomic relationship matrix (CNV_GRM). CNV loci showing double deletions, single deletions, and normal state in the population were coded as 0, 1, and 2, respectively, whereas CNV loci presenting normal state, single duplications, and double duplications were coded as 0, 1, and 2, respectively. Given that some CNVs presented both deletions and duplications at the same position in the population, these mixed-CNVs were treated as two distinct CNVs loci, one to represent deletions and the other to represent duplications. The variance components for metritis were estimated by fitting either only a SNP-derived GRM (SNP_GRM) or jointly SNP_GRM and CNV_GRM considering 3,272 cows in models that included the female category and farm-year-season as fixed effects. QTLs overlapped with CNVRs were enriched for milk (e.g., milk fat yield, milk yield, and milk protein percentage), reproduction (e.g., calving ease, non-return rate, and heat intensity), exterior (e.g., teat length, udder depth, and udder height), production (e.g., length of productive life, lifetime profit index, and net merit), and health traits (e.g., immune globulin G level, somatic cell, and bovine respiratory susceptibility). Regarding variance components, copy number variations were able to capture a fraction of the additive genetic variance not captured by SNPs alone, increasing the heritability estimate for metritis. In summary, our findings suggest that CNVs overlap QTLs associated with economically important traits more than only by chance and CNVs can capture additional additive genetic variance not fully captured by SNPs alone.

Identification of potential therapeutic targets for nonischemic cardiomyopathy in European ancestry: an integrated multiomics analysis

BackgroundNonischemic cardiomyopathy (NISCM) is a clinical challenge with limited therapeutic targets. This study aims to identify promising drug targets for NISCM.MethodsWe utilized cis-pQTLs from the deCODE study, which includes data from 35,559 Icelanders, and SNPs from the FinnGen study, which includes data from 1,754 NISCM cases and 340,815 controls of Finnish ancestry. Mendelian randomization (MR) analysis was performed to estimate the causal relationship between circulating plasma protein levels and NISCM risk. Proteins with significant associations underwent false discovery rate (FDR) correction, followed by Bayesian colocalization analysis. The expression of top two proteins, LILRA5 and NELL1, was further analyzed using various NISCM datasets. Descriptions from the Human Protein Atlas (HPA) validated protein expression. The impact of environmental exposures on LILRA5 was assessed using the Comparative Toxicogenomics Database (CTD), and molecular docking identified the potential small molecule interactions.ResultsMR analysis identified 255 circulating plasma proteins associated with NISCM, with 16 remaining significant after FDR correction. Bayesian colocalization analysis identified LILRA5 and NELL1 as significant, with PP.H4 > 0.8. LILRA5 has a protective effect (OR = 0.758, 95% CI, 0.670–0.857) while NELL1 displays the risk effect (OR = 1.290, 95% CI, 1.199–1.387) in NISCM. Decreased LILRA5 expression was found in NISCM such as diabetic, hypertrophic, dilated, and inflammatory cardiomyopathy, while NELL1 expression increased in hypertrophic cardiomyopathy. HPA data indicated high LILRA5 expression in neutrophils, macrophages and endothelial cells within normal heart and limited NELL1 expression. Immune infiltration analysis revealed decreased neutrophil in diabetic cardiomyopathy. CTD analysis identified several small molecules that affect LILRA5 mRNA expression. Among these, Estradiol, Estradiol-3-benzoate, Gadodiamide, Topotecan, and Testosterone were found to stably bind to the LILRA5 protein at the conserved VAL-15 or THR-133 residues in the Ig-like C2 domain.ConclusionBased on European Ancestry Cohort, this study reveals that LILRA5 and NELL1 are potential therapeutic targets for NISCM, with LILRA5 showing particularly promising prospects in diabetic cardiomyopathy. Several small molecules interact with LILRA5, implying potential clinical implication.

Structural brain characteristics of epilepsy patients with comorbid migraine without aura

Migraine is a common bi-directional comorbidity of epilepsy, indicating potential complex interactions between the two conditions. However, no previous studies have used brain morphology analysis to assess possible interactions between epilepsy and migraine. Voxel-based morphometry (VBM), surface-based morphometry (SBM), and structural covariance networks (SCNs) can be used to detect morphological changes with high accuracy. We recruited 30 individuals with epilepsy and comorbid migraine without aura (EM), along with 20 healthy controls (HC) and 30 epilepsy controls (EC) without migraine. We used VBM, SBM, and SCN analysis to compare differences in gray matter volume, cortical thickness, and global level and local level graph theory indexes between the EM, EC, and HC groups to investigate structural brain changes in the EM patients. VBM analysis showed that the EM group had gray matter atrophy in the right temporal pole compared with the HC group (p < 0.001, false discovery rate correction [FDR]). Furthermore, the headache duration in the EM group was negatively correlated with the gray matter volume of the right temporal pole (p < 0.05). SBM analysis showed cortical atrophy in the left insula, left posterior cingulate gyrus, left postcentral gyrus, left middle temporal gyrus, and left fusiform gyrus in the EM compared with the HC group (p < 0.001, family wise error correction). We found a positive correlation between headache frequency and the cortical thickness of the left middle temporal gyrus (p < 0.05). SCN analysis revealed no differences in global parameters between the three groups. The area under the curve (AUC) of the nodal betweenness centrality in the right postcentral gyrus was lower in the EM group compared with the HC group (p < 0.001, FDR correction), and the AUC of the nodal degree in the right fusiform gyrus was lower in the EM group compared with the EC group (p < 0.001, FDR correction). We found clear differences in brain structure in the EM patients compared with the HC group. Accordingly, migraine episodes may influence brain structure in epilepsy patients. Conversely, abnormal brain structure may be an important factor in the development of epilepsy with comorbid migraine without aura. Further studies are needed to investigate the role of brain structure in individuals with epilepsy and comorbid migraine without aura.

Causal association between mitochondrial function and psychiatric disorders: Insights from a bidirectional two-sample Mendelian randomization study

BackgroundPrevious observational studies have suggested that there appears to be a close association between mitochondrial function and psychiatric disorders, but whether a causal role exists remains unclear. MethodsWe extracted genetic instruments for 67 mitochondrial-related proteins and 10 psychiatric disorders from publicly available genome-wide association studies, and employed five distinct MR methods and false discovery rate correction to detect causal associations between them. Additionally, we conducted a series of sensitivity tests and additional model analysis to ensure the robustness of the results. For potential causal associations, we further performed reverse MR analyses to assess the impact of reverse causality. ResultsWe identified a total of 2 significant causal associations and 24 suggestive causal associations. Specifically, Phenylalanine-tRNA ligase was found to increase the risk of Alzheimer's disease, while Mitochondrial glutamate carrier 2 decreased the risk of autism spectrum disorder. Furthermore, there was no evidence of significant pleiotropy, heterogeneity, or reverse causality. LimitationsThis study was limited to individuals of European ancestry, and the conclusions drawn are merely revelatory. ConclusionThis study provides novel insights into the relationship between mitochondria and psychiatric disorders, as well as the pathogenesis and treatment strategies for psychiatric disorders.

Effect of the immune cells and plasma metabolites on rheumatoid arthritis: a mediated mendelian randomization study.

Increasing evidence indicates a close relationship between alterations in human immune cells and plasma metabolites with Rheumatoid Arthritis (RA). However, limited studies have left the causal relationships behind these links unclear. A bidirectional Mendelian Randomization (MR) study was conducted, combined with mediation analysis, using data from genome-wide association study database covering 731 immune cell phenotypes and 1,400 plasma metabolite traits to explore their causal relationships with RA and potential mediating effects. The primary method used for MR analysis was inverse-variance weighted and False Discovery Rate (FDR) correction was applied to verify the robustness of our results. HLA DR on CD33- HLA DR+ (myeloid cell group) (OR, 1.422; 95% CI, 1.194-1.694; P < 0.001; PFDR = 0.012) increased the risk of developing RA. CD19 on IgD+ CD38- naive (B cell group) (OR, 0.969; 95% CI, 0.954-0.985; P < 0.001; PFDR = 0.021) reduced the risk of developing RA. RA was a risk factor for HLA DR on CD14- CD16+ monocytes (monocyte group) (OR, 1.242; 95% CI, 1.102-1.401; P < 0.001; PFDR = 0.047). RA was a protective factor for memory B cell %lymphocyte (B cell group) (OR, 0.861; 95% CI, 0.795-0.933; P < 0.001; PFDR = 0.050), CD4+ CD8dim T cell %lymphocyte (TBNK group) (OR, 0.802; 95% CI, 0.711-0.904; P < 0.001; PFDR = 0.043), CD4+ CD8dim T cell %leukocyte (TBNK group) (OR, 0.814; 95% CI, 0.726-0.913; P < 0.001; PFDR = 0.046), CD24 on IgD+ CD24+ B cells (B cell group) (OR, 0.857; 95% CI, 0.793-0.927; P < 0.001; PFDR = 0.038), and CD24 on unswitched memory B cells (B cell group) (OR, 0.867; 95% CI, 0.797-0.942; P < 0.001; PFDR = 0.050). Increasing levels of docosatrienoate (22:3n3) (OR, 0.886; 95% CI, 0.838-0.936; P < 0.001; PFDR = 0.023) significantly reduced the risk of developing RA. The mediating effect of plasma metabolites in this context was not established. This study provides genetic evidence for the intricate relationships between immune cells, plasma metabolites, and RA, highlighting the potential mechanisms involved. This will contribute to future directions in precision medicine and research.

Investigating Neuroplasticity Changes Reflected by BDNF Levels in Astrocyte-Derived Extracellular Vesicles in Patients with Depression.

To investigate the neuroplasticity hypothesis of depression by measuring brain-derived neurotrophic factor (BDNF) levels in plasma astrocyte-derived extracellular vesicles (ADEVs) and to evaluate their potential as biomarkers for depression compared with plasma BDNF levels. Thirty-five patients with major depressive disorder (MDD) and 35 matched healthy controls (HCs) were enrolled. Plasma ADEVs were isolated using a combination of ultracentrifugation and immunoaffinity capture. Isolated ADEVs were validated using transmission electron microscopy, nanoparticle tracking analysis, and Western blotting. BDNF levels were quantified in both ADEVs and plasma. ALG-2-interacting protein X (Alix) and cluster of differentiation 81 (CD81) levels, two established extracellular vesicle markers, were measured in ADEVs. After false discovery rate correction, patients with MDD exhibited higher CD81 levels (P FDR = 0.040) and lower BDNF levels (P FDR = 0.043) in ADEVs than HCs at baseline. BDNF levels in ADEVs normalized to CD81 (P FDR = 0.002) and Alix (P FDR = 0.040) remained consistent with this finding. Following four weeks of selective serotonin reuptake inhibitor treatment (n=10), CD81 levels in ADEVs decreased (P FDR = 0.046), while BDNF levels normalized to CD81 increased (P FDR = 0.022). BDNF levels in ADEVs were more stable than in plasma. Exploratory analysis revealed no correlation between BDNF levels in ADEVs and plasma (ρ=0.117, P = 0.334). This study provides human in vivo evidence supporting the neuroplasticity hypothesis of depression by demonstrating altered BDNF levels in ADEVs. ADEVs may be more suitable for developing biomarkers of depression than plasma-derived biomarkers.

A Phenome-Wide Association Study (PheWAS) of Genetic Risk for C-Reactive Protein in Children of European Ancestry: Results From the ABCD Study.

C-reactive protein (CRP) is a moderately heritable marker of systemic inflammation that is associated with adverse physical and mental health outcomes. Identifying factors associated with genetic liability to elevated CRP in childhood may inform our understanding of variability in CRP that could be targeted to prevent and/or delay the onset of related health outcomes. We conducted a phenome-wide association study (PheWAS) of genetic risk for elevated CRP (i.e. CRP polygenic risk score [PRS]) among children genetically similar to European ancestry reference populations (median analytic n = 5,509) from the Adolescent Brain and Cognitive Development℠ (ABCD) Study. Associations between CRP PRS and 2,377 psychosocial and neuroimaging phenotypes were estimated using independent mixed effects models. Post hoc analyses examined whether: (1) covarying for measured body mass index (BMI) or removing the shared genetic architecture between CRP and BMI altered phenotypic associations, (2) sex moderated CRP PRS associations, and (3) associations are unconfounded by assortative mating or passive gene-environment correlations (using a within-family analyses). Multiple testing was adjusted for using Bonferroni and false discovery rate (FDR) correction. Nine phenotypes were positively associated with CRP PRS after multiple testing correction: five weight- and eating-related phenotypes (e.g. BMI, overeating), three phenotypes related to caregiver somatic problems (e.g. caregiver somatic complaints), as well as weekday video watching (all ps = 1.2 × 10-7 - 2.5 × 10-4, all p FDR s = 0.0002 - 0.05). No neuroimaging phenotypes were associated with CRP PRS (all ps = 0.0003 - 0.998; all p FDR s = 0.08 - 0.998) after correction for multiple testing. Eating and weight-related phenotypes remained associated with CRP PRS in within-family analyses. Covarying for BMI resulted in largely consistent results, and sex did not moderate any CRP PRS associations. Removing the shared genetic variance between CRP and BMI attenuated all relationships; associations with weekday video watching, caregiver somatic problems and caregiver report that the child is overweight remained significant while associations with waist circumference, weight, and caregiver report that child overeats did not. Genetic liability to elevated CRP is associated with higher weight, eating, and weekday video watching during childhood as well as caregiver somatic problems. These associations were consistent with direct genetic effects (i.e., not solely due to confounding factors like passive gene-environment correlations) and were independent of measured BMI. The majority of associations with weight and eating phenotypes were attributable to shared genetic architecture between BMI and inflammation. The relationship between genetics and heightened inflammation in later life may be partially attributable to modifiable behaviors (e.g. weight and activity levels) that are expressed as early as childhood.

Specific blood metabolite associations with Gout: a Mendelian randomization study.

Gout, common metabolic disorders, have poorly understood links with blood metabolites. Exploring these relationships could enhance clinical prevention and treatment strategies. We applied bidirectional two-sample Mendelian randomization (MR) analysis, using data from a genome-wide association (GWAS) study of 486 blood metabolites. Gout data was obtained from FinnGen R8 (7461 gout and 221,323 control cases). We implemented the inverse variance-weighted (IVW) method for main analytical approach. Extensive heterogeneity, pleiotropy tests, leave-one-out analysis, and reverse MR were conducted to validate the robustness of our findings. Both Bonferroni and False Discovery Rate (FDR) corrections were used to adjust for multiple comparisons, ensuring stringent validation of our results. Initial MR identified 31 candidate metabolites with potential genetic associations to gout. Following rigorous sensitivity analysis, 23 metabolites as potential statistical significance after final confirmation. These included metabolites enhancing gout risk such as X-11529 (OR = 1.225, 95% CI 1.112-1.350, P < 0.001), as well as others like piperine and stachydrine, which appeared to confer protective effects. The analysis was strengthened by reverse MR analysis. Additionally, an enrichment analysis was conducted, suggesting that 1-methylxanthine may be involved in the metabolic process of gout through the caffeine metabolism pathway. Identifying causal metabolites offers new insights into the mechanisms influencing gout, suggesting pathways for future research and potential therapeutic targets.

Topological properties of white matter network in first untreated children and adolescents with obsessive-compulsive disorder

Objective: To investigate the topological properties of the white matter network in the drug-naive first-episode children and adolescent with obsessive-compulsive disorder (OCD). Methods: This study was a case-control study. First-episode OCD childhren and adolescents(OCD group) who were treated in the outpatient or inpatient department of the Second Affiliated Hospital of Xinxiang Medical University from July 2018 to October 2023 were collected as the research subjects. Healthy controls (control group)matched by gender, age and education level were used as controls. Deterministic tractography technique was used to construct the whole brain white matter structural network, and graph theory analysis method was used to analyze the topological attributes of the whole brain white matter structure network in OCD children and adolescents. A network-based statistical method was used to examine the inter-group differences in the functional connectivity strength of the whole brain network. Results: Finally, 31 cases were included in the obsessive-compulsive disorder group, including 22 males and 9 females, with an age of (13.5±1.6) years; There were 34 cases in the control group, including 22 males and 12 females, with an age of (12.7±1.4) years. The global efficiency and local efficiency of the OCD group (0.62±0.03, 0.70±0.07) were significantly higher than those of the control group (0.50±0.06, 0.54±0.21) [both P<0.01, false discovery rate(FDR)correction]; while the characteristic path length (1.77±0.08) was significantly smaller than that of the control group (2.10±0.23) (P<0.01, FDR correction).The centrality comparison of nodal betweenness centrality showed that in the OCD group, the connections were enhanced in the left lateral orbitofrontal gyrus, right dorsal agranular insula, left dorsal granular insula, right granular insula, right posterior central gyrus main area of parietal lobe, left ventral granular insula, granular insula, left ventral granulosa, left granular insula, and left dorsal agranular insula [all P<0.001, family wise error (FWE) correction], while the connection of right thalamic was weakened (P<0.001, FWE correction), There were sub-networks characterized by significantly enhanced connection strength of relevant nodes in subcortical, visual network, and default mode network (P<0.05, permutation test 5 000 times). Conclusions: The topological properties of the brain's functional network in children and adolescents with OCD exhibit abnormalities, indicating an immature state of brain functional connectivity.

Understanding Factors That Cause Benign Paroxysmal Positional Vertigo, Ménière Disease, and Vestibular Neuritis: A Two-Sample Mendelian Randomization Study.

Vertigo is a prevalent clinical symptom, frequently associated with benign paroxysmal positional vertigo (BPPV), Ménière disease (MD), and vestibular neuritis (VN), which are three common peripheral vestibular disorders. However, there is a relative lack of research in epidemiology and etiology, with some existing studies presenting discrepancies in their conclusions. We conducted a two-sample Mendelian randomization (MR) analysis to explore potential risk and protective factors for these three peripheral vestibular disorders. Based on genome-wide association studies, we executed a univariable MR to investigate the potential associations between 38 phenotypes and MD, BPPV, and VN. We used the inverse variance weighted method as the primary MR result and conducted multiple sensitivity analyses. We used false discovery rate (FDR) correction to control for type I errors. For findings that were significant in the univariable MR, a multivariable MR analysis was implemented to ascertain direct effects. In addition, we replicated analyses of significant results from the univariable MR to enhance the robustness of our analyses. For BPPV, both alcohol consumption (odds ratio [OR] = 0.57, 95% confidence interval [CI] = 0.43 to 0.76, FDR Q = 0.004) and educational attainment (OR = 0.77, 95% CI = 0.68 to 0.88, FDR Q = 0.003) were found to decrease the risk. The genetic prediction analysis identified major depression (OR = 1.75, 95% CI = 1.28 to 2.39, FDR Q = 0.008) and anxiety (OR = 5.25, 95% CI = 1.79 to 15.42, FDR Q = 0.036) increased the risk of MD. However, the impact of major depression on MD could be influenced by potential horizontal pleiotropy. Systolic blood pressures (OR = 1.03, 95% CI = 1.02 to 1.04, FDR Q = 4.00 × 10 -7 ) and diastolic blood pressures (OR = 1.05, 95% CI = 1.03 to 1.07, FDR Q = 2.83 × 10 -6 ) were associated with an increased risk of VN, whereas high-density lipoprotein (OR = 0.77, 95% CI = 0.67 to 0.89, FDR Q = 0.009) and urate (OR = 0.75, 95% CI = 0.63 to 0.91, FDR Q = 0.041) reduces the risk of VN. Only the relationship between urate and VN was not replicated in the replication analysis. Multivariable MR showed that the protective effect of education on BPPV was independent of Townsend deprivation index. The protective effect of high-density lipoprotein against VN was independent of triglycerides and apolipoprotein A1. The risk impacts of systolic and diastolic blood pressures on VN exhibited collinearity, but both are independent of chronic kidney disease and estimated glomerular filtration rate. The impacts of anxiety and severe depression on MD demonstrated collinearity. Our study identified the risk association between systolic and diastolic blood pressure with VN and the protective influence of high-density lipoprotein on VN, which may support the vascular hypothesis underlying VN. Furthermore, we observed an elevated risk of MD associated with anxiety. The potential protective effects of education and alcohol consumption on BPPV need further exploration in subsequent studies to elucidate specific mechanistic pathways. In summary, our MR study offers novel insights into the etiology of three peripheral vestibular diseases from a genetic epidemiological standpoint.