Search Results (253)

Disparities in the functional classification of secretory genes among aphid taxa may be attributed to variations in coding sequences and gene expression profiles. However, the driving factors that regulate sequence evolution remain unclear. This study aimed to investigate the differences in coding sequences and expression patterns of secretory genes between the rose grain aphid (Metopolophium dirhodum) and the pea aphid (Acrythosiphon pisum), with a particular focus on their roles in evolutionary adaptations and functional diversity. The study involved the rearing of aphids, RNA extraction, de novo transcriptome assembly, functional annotation, secretory protein prediction, and comparative analysis of coding sequences and expression patterns across various functional categories using bioinformatics tools. The results revealed that metabolic genes exhibited greater coding sequence divergence, indicating the influence of positive selection. Moreover, significant expression divergence was noted among functional categories, particularly in metabolic and genetic information processing genes, which exhibited higher variability. This study enhances our understanding of the molecular mechanisms that contribute to phenotypic and genetic diversity among aphid species. This study elucidates the relationship between variations in coding sequences and differences in gene expression among functional categories, thereby establishing a foundation for future studies on gene evolution in response to environmental pressures. Full article

Background: Rheumatoid arthritis (RA) is an autoimmune disease that remains incurable. An increasing number of proteomic genome-wide association studies (GWASs) are emerging, offering immense potential for identifying novel therapeutic targets for diseases. This study aims to identify potential therapeutic targets for RA based on human plasma proteome. Methods: Protein quantitative trait loci were extracted and integrated from eight large-scale proteomic GWASs. Proteome-wide Mendelian randomization (Pro-MR) was performed to prioritize proteins causally associated with RA. Further validation of the reliability and stratification of prioritized proteins was performed using MR meta-analysis, colocalization, and transcriptome-wide summary-data-based MR. Subsequently, prioritized proteins were characterized through protein–protein interaction and enrichment analyses, pleiotropy assessment, genetically engineered mouse models, cell-type-specific expression analysis, and druggability evaluation. Phenotypic expansion analyses were also conducted to explore the effects of the prioritized proteins on phenotypes such as endocrine disorders, cardiovascular diseases, and other immune-related diseases. Results: Pro-MR prioritized 32 unique proteins associated with RA risk. After validation, prioritized proteins were stratified into four reliability tiers. Prioritized proteins showed interactions with established RA drug targets and were enriched in an immune-related functional profile. Four trans-associated proteins exhibited vertical or horizontal pleiotropy with specific genes or proteins. Genetically engineered mouse models for 18 prioritized protein-coding genes displayed abnormal immune phenotypes. Single-cell RNA sequencing data were used to validate the enriched expression of several prioritized proteins in specific synovial cell types. Nine prioritized proteins were identified as targets of existing drugs in clinical trials or were already approved. Further phenome-wide MR and mediation analyses revealed the effects and potential mediating roles of some prioritized proteins on other phenotypes. Conclusions: This study identified 32 plasma proteins as potential therapeutic targets for RA, expanding the prospects for drug discovery and deepening insights into RA pathogenesis. Full article

Background/Objectives: Elevated serum uric acid levels are associated with the occurrence, development, and adverse events of coronary heart disease (CHD) and CHD risk factors. However, the extent of any pathogenic effect of the serum uric acid on CHD and whether CHD risk factors play a confounding or mediating role are still unclear. Methods: The potential causal associations of serum uric acid with CHD were evaluated via cross-trait linkage disequilibrium score regression analysis and Mendelian randomization. The pleiotropy of genetic tools was analyzed via a Bayesian colocalization approach. Moreover, we utilized two-step MR to identify risk factors mediating the relationship between uric acid and CHD. Results: Mendelian randomization results derived from two genetic instrument selection strategies support that serum uric acid levels have a significant causal relationship with coronary artery disease, stable angina pectoris, and myocardial infarction. This causal relationship was partially mediated by diastolic blood pressure, mean arterial pressure, and serum triglycerides. Transcriptomic analysis revealed that serum uric acid may directly contribute to the development of atherosclerosis by inducing transcriptomic changes in macrophages. Conclusions: Our findings highlight that the control of serum urate concentration in the long-term management of CHD patients may be necessary. Well-designed clinical trials and foundational research are presently required to furnish conclusive proof regarding the specific clinical scenarios in which adequate reduction in urate concentrations can confer cardiovascular advantages. Full article

Objective: Uncovering the renoprotective and anti-inflammatory effects of atorvastatin treatment in diabetic-and-obese rats by employing traditional renal function indicators (urea and creatinine) and four prototypical cytokines (IL-1β, il-6, IL-17α, TNFα). Method: Twenty-eight male Wistar rats, aged 6 months, 350–400 g, were randomized into four groups. The first group, G-I, the denominated control, were fed standard chow over the whole course of the experiments. The rodents in G-II were exposed to a High-Fat Diet. The last two groups were exposed to Streptozotocin peritoneal injection (35 mg/kg of body weight). A short biochemical assessment was performed before diabetes model induction to ensure appropriate glucose metabolism before experiments. Following model induction, only rodents in group G-IV were gradually introduced to the same High-Fat Diet as received by G-II. Model confirmation 10 days after injections marked the start of statin treatment in group G-IV, by daily gavage of atorvastatin 20 mg/kg of body weight/day for 21 days. At the end of the experiments, the biochemical profile of interest comprised typical renal retention byproducts (urea and creatinine) and the inflammatory profile described using plasma levels of TNFα, IL-17α, IL-6, and IL-1β. Results: Treatment with Atorvastatin was associated with a statistically significant improvement in renal function in G-IV compared to untreated diabetic rodents in G-III. Changes in inflammatory activity showed partial association with statin therapy, TNFα and IL-17α mirroring the trend in urea and creatinine values. Conclusions: Our results indicate that atorvastatin treatment yields a myriad of pleiotropic activities, among which renal protection was clearly demonstrated in this model of diabetic-and-obese rodents. The statin impact on inflammation regulation may not be as clear-cut, but the potential synergy of renal function preservation and partial tapering of inflammatory activity requires further research in severely metabolically challenged models. Full article

Background/Objectives: Epilepsy and sleep disturbances frequently co-occur, yet the causal nature of this relationship remains uncertain, particularly in relation to epilepsy subtypes and status epilepticus. We investigated potential bidirectional causal associations between sleep-related traits and epilepsy, including subtypes and status epilepticus, using Mendelian randomization (MR). Methods: We conducted two-sample MR using genome-wide association study (GWAS) summary statistics from European ancestry cohorts. Epilepsy, its subtypes, and status epilepticus were analyzed using data from the International League Against Epilepsy Consortium on Complex Epilepsies (ILAE) and the FinnGen study. Nine self-reported sleep-related traits were derived from the UK Biobank-based GWAS. Causal estimates were primarily obtained using inverse variance weighted models with additional MR analysis methods. Pleiotropy and heterogeneity were assessed to enhance the robustness of the finding. Results: Several subtype-specific associations were identified, with direction and statistical significance varying across cohorts and subtypes. After correction for multiple testing and filtering for tests with ≥10 instrumental variables to ensure robust and reliable MR estimates, several consistent and potentially mutually reinforcing associations emerged. In the ILAE cohort, focal epilepsy with hippocampal sclerosis was associated with an increased risk of insomnia, and juvenile myoclonic epilepsy with reduced sleep duration. In the FinnGen cohort, overall epilepsy was associated with increased risk of both insomnia and daytime sleepiness. In reverse MR, daytime sleepiness and napping were associated with increased risk of epilepsy, while daytime napping and frequent insomnia symptoms were linked to elevated risk of status epilepticus. Conclusions: Our findings reveal subtype-specific and bidirectional causal links between epilepsy and sleep-related traits. These results highlight the biological interplay between epileptic networks and sleep regulation and underscore the need for further clinical and mechanistic studies. Full article

Background: Huntington’s disease (HD) is a neurodegenerative disorder caused by a CAG repeat expansion in the HTT gene, with a rare juvenile-onset form (JoHD) marked by early, rigid motor symptoms. This study examined cortical and subcortical resting-state connectivity in JoHD, hypothesizing preserved cortical networks but altered striatal connectivity, in line with early subcortical atrophy despite relatively spared cortical volume. Methods: Participants included children and young adults with clinician-confirmed Juvenile-Onset Huntington’s Disease (JoHD; n = 19) and gene-non-expanded (GNE) controls (n = 64), both drawn from longitudinal studies at the University of Iowa. Resting-state functional MRI scans were analyzed to assess canonical cortical network and striatal connectivity, and linear mixed-effects models tested group differences and associations with motor, cognitive, and clinical outcomes. Results: JoHD participants showed reduced connectivity within the left somatomotor network and striatal circuits, despite largely typical cortical network connectivity. Striatal connectivity was associated with disease burden and cognitive ability, while left somatomotor connectivity was unrelated to clinical outcomes. Conclusions: These findings support the hypothesis of antagonistic pleiotropy in JoHD, where early neural advantages—such as relatively preserved or possibly enhanced cortical function—may contribute to later striatal vulnerability and degeneration. The observed left-lateralized somatomotor hypoconnectivity aligns with prior volumetric and gene expression research, highlighting the role of excitotoxic glutamatergic input and the selective vulnerability of high-functioning circuits in disease progression. Full article

Background: Intervertebral disc degeneration (IVDD) is caused by an imbalance between the catabolic and anabolic processes within intervertebral disc tissue. Several studies have suggested a potential association between cerebrospinal fluid metabolites (CFMs) and the development of IVDD. However, the existing evidence on the relationship between CFM and IVDD is limited and inconsistent. Methods: The data on 338 cerebrospinal fluid metabolites and intervertebral disc degeneration analyzed in this study were sourced from their respective genome-wide association studies (GWAS). MR analysis employed single nucleotide polymorphisms (SNPs) closely associated with disease as instrumental variables (IVs). The inverse variance weighted (IVW) method was employed as the primary statistical approach, complemented by MR-Egger, the Weighted median, Simple mode, and the Weighted mode for result validation. Comprehensive sensitivity analyses were performed to confirm the robustness of the results and assess for heterogeneity and horizontal pleiotropy. Results: Using the IVW method, this study revealed positive causal effects between 11 cerebrospinal fluid metabolites (CFMs) and intervertebral disc degeneration (IVDD), indicating that elevated levels of these 11 CFMs increase the risk of IVDD. Conversely, negative causal effects were identified for 6 CFMs, suggesting that higher levels of these CFMs have a protective effect against IVDD. Reverse MR analysis indicated 1 positive and 18 negative causal relationships between IVDD and CFMs. Conclusions: Our bidirectional Mendelian analysis provides compelling evidence of a causal relationship between CFMs and IVDD. These findings enhance our understanding of IVDD pathogenesis and highlight the potential for preventive therapies targeting CFMs. Further research is needed to clarify the mechanisms of these CFMs on IVDD. Full article

Rice tillering is an important trait that is genetically and environmentally co-regulated. Nitorgen is one of the key nutrients affecting tillering, and straw return further affects tiller development by altering soil heterogeneity. In order to analyze the genetic regulation mechanism of rice tillering and its interactions with the environment, 124 recombinant inbred line (RIL) populations derived from two superior Peijiu lines, 9311 and PA64s, were used as materials in this study, and the dynamic tillering phenotypes were measured under three treatments (no nitrogen application, nitrogen application, and nitrogen + straw return) for two consecutive years. Using an existing genetic map, we conducted single-environment, multi-environment, and meta-QTL analyses to systematically identify tiller-related genetic loci and their environmental interactions. The main findings were as follows: (1) A total of 57 QTLs were identified in the single-environment QTL analysis, of which 44 were unreported new QTLs. Four QTLs showed temporal pleiotropy, ten QTLs contributed more than 10% to the phenotypes under the no-N treatment, and five QTLs contributed more than 10% under the straw return treatment. Among them, the phenotypic contribution of mks1-355 (qD1tn1-3) and mks1-352 (qD2TN1-2) both exceeded 40%. (2) Multi-environmental QTL analysis detected 15 QTLs. Of these, qmD1TN1 (mks1-356) showed no environmental interaction effect, while qmD1TN12 (mks12-267), qmD2TN1 (mks1-334), qmD2TN3-1 (mks3-105), and qmD5TN6 (mks6-71) exhibited antagonistic pleiotropy, suggesting that these QTL need to be considered for environmental specificity in breeding. (3) Meta-QTL analysis localized 52 MQTLs, of which MQTL3.1 and MQTL6.8 contained 82 and 59 candidate genes, respectively, and no reported tiller-related genes were found. (4) mks1-355 (qD1tn1-3), mks1-352 (qD2TN1-2), and mks1-356 (qmD1TN1) may be located in the same genetic locus, and their phenotypic contributions were more than 40%. These QTLs were detected stably for two consecutive years, and they may be the main effector QTLs in tillering that are less affected by the environment. Further analysis revealed that these QTLs corresponded to MQTL1.6, which contains 56 candidate genes. Of these, the expression level of OsSPL2 gene in the parental line 9311 was significantly higher than that of PA64s, and there were polymorphic differences in the coding region. It was hypothesized that OsSPL2 was the main effector gene of this QTL. This study provides important genetic resources for mining candidate genes related to tillering and nitrogen efficiency in rice and lays a theoretical foundation for directional breeding and molecular marker development in specific environments. Full article

Sjögren’s disease (SjD) is a systemic autoimmune disorder primarily causing dry eyes and mouth. It frequently overlaps with other autoimmune diseases (AIDs), including rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). However, the genetic basis of SjD remains underexplored, limiting our understanding of its connections to other immune-mediated conditions. In this study, we aimed to identify gene networks associated with SjD through the integration of genetic, transcriptomic, and epigenomic data. We further compared the genetic factors of SjD with other immune-mediated diseases. We analyzed genome-wide association studies (GWAS) summary statistics, DNA methylation, and transcriptomic data using our in-house network-based methods, dmGWAS and EW_dmGWAS, to identify key gene modules associated with SjD. In dmGWAS analysis, discovery and evaluation datasets were used to identify consensus results. We conducted gene-set, cell-type, and disease-enrichment analyses on significant gene modules and explored potential drug targets. Genetic correlations and Mendelian randomization were applied to assess SjD’s link with 17 other AIDs and 16 cancer types. dmGWAS identified 207 and 211 gene modules in the discovery and evaluation phases, respectively, while EW_dmGWAS detected 886 modules. Key modules highlighted 55 genes (discovery), 52 genes (evaluation), and 59 genes (EW_dmGWAS), with at least 50 genes from each analysis linked to AIDs and cancer. Enrichment analyses confirmed their relevance to immune and oncogenic pathways. We pinpointed four candidate drug targets associated with AIDs. We developed a novel integrative omics approach to identify potential genetic markers of SjD and compared them with AIDs and cancers. Our approach can be similarly applied to other disease studies. Full article

Background and Objectives: Pre-eclampsia (PE) is a serious pregnancy complication defined by the onset of hypertension and multi-organ dysfunction occurring after 20 weeks of gestation. Studies have indicated the correlation between diabetes mellitus (DM) and PE, but the causal relationship remains unclear. Materials and Methods: The two-sample Mendelian randomization (MR) approach, including the inverse variance weighted random effects (IVW-RE) model and the traditional sensitivity model, was employed to assess the causal effects of pre-pregnancy type 1 diabetes (T1D) and type 2 diabetes (T2D) on PE using summary-level data obtained from genome-wide association studies. Additionally, diabetes-related factors, such as glycated hemoglobin (HbA1c) levels, fasting insulin levels, and body mass index (BMI), were evaluated for their potential causal effects on the risk of PE. Pleiotropy-robust and multivariable Mendelian randomization (MVMR) methods were further used because of the intricate associations among the traits. Insulin and metformin use was also assessed for their causal role in PE risk. Results: Our findings show that genetically predicted T1D (OR = 1.06, 95% CI: 1.03–1.09, p < 0.001), T2D (OR = 1.09, 95% CI: 1.04–1.14, p < 0.001), and BMI (OR = 1.64, 95% CI 1.49 to 1.80, p < 0.001) had causal effects on the incidence of PE, while the effects of HbA1c (OR = 0.77, 95% CI 0.59 to 1.02, p = 0.064) and fasting insulin levels (OR = 1.35, 95% CI 0.89 to 2.05, p = 0.153) on the occurrence of PE were not significant. The results were verified by MVMR analysis. Additionally, insulin use increased the risk of pre-eclampsia (OR = 1.11, 95% CI 1.05–1.17, p < 0.001). Conclusions: Our findings demonstrate a causal relationship between pre-pregnancy diabetes (DM) and obesity and the risk of PE from a genetic epidemiological perspective. Adverse maternal factors, including DM and obesity prior to pregnancy, should be considered in mechanistic studies of PE. In addition, comprehensive interventions for risk factors such as pre-pregnancy DM and obesity should be emphasized in clinical practice. Full article

Background/Objectives: Type 2 diabetes mellitus (T2DM) and Alzheimer’s disease (AD) are significant global health issues. Epidemiological studies suggest T2DM increases AD risk, though confounding factors and reverse causality complicate this association. This study aims to clarify the causal relationship between T2DM and AD through a systematic review and meta-analysis of Mendelian randomization (MR) studies and a new two-sample MR analysis. Methods: A literature search across major databases was conducted through May 2024 to identify MR studies linking T2DM and AD. Fixed/random-effect models provided pooled odds ratios (ORs) with 95% confidence intervals (CIs), and heterogeneity was assessed with the I² statistic. For our MR analysis, we pooled genetic variants from selected studies and analyzed AD outcomes using IGAP, EADB, and UKB databases. Multiple MR methods, including inverse variance weighted (IVW) and pleiotropy–robust approaches, were applied for validation. Results: Of 271 articles, 8 MR studies were included (sample sizes: 68,905 to 788,989), all from European ancestry. Our meta-analysis found no significant causal link between T2DM and AD (OR = 1.02, 95% CI: 1.00–1.04) with moderate heterogeneity (I² = 31.3%). Similarly, our MR analysis using 512 SNPs as instrumental variables showed no significant associations in IGAP, EADB, or UKB data, which is consistent across sensitivity analyses. Conclusions: This meta-MR and MR analysis revealed no significant causal association between T2DM and AD, indicating that genetic predisposition to T2DM does not appear to causally influence AD risk, though modifiable clinical or environmental aspects of T2DM may still contribute to neurodegenerative processes. Further research should explore other mechanisms linking these conditions. Full article

Background: Osteoporosis (OP) is a systemic bone disease often undiagnosed until fractures occur. Metabolites may influence OP, offering potential biomarkers or therapeutic targets. This study investigates the causal relationship between circulating metabolites and OP-related phenotypes using Mendelian Randomization (MR). Methods: GWAS data on 233 metabolic traits from 136,016 participants were analyzed through two-sample MR. Linkage disequilibrium score regression (LDCS) was used to estimate genetic correlations between metabolic traits and OP-related phenotypes, leveraging European ancestry linkage disequilibrium scores to account for polygenicity and stratification. MR employed the inverse-variance weighted (IVW) method, with sensitivity analyses via MR-Egger, MR-PRESSO, and weighted median methods to address pleiotropy and confounders. Results: LDCS identified significant genetic correlations between metabolites and bone mineral density (BMD) phenotypes, with total body BMD (toBMD) showing the strongest associations. Thirty-five metabolite traits, including apolipoprotein A-I, exhibited significant linkages. Among 79 metabolites influencing BMD, serum acetate levels were significantly associated with femoral neck BMD (OR: 1.28, 95% CI: 1.02–1.62), lumbar spine BMD (OR: 1.73, 95% CI: 1.32–2.27), and total body BMD (OR: 1.21, 95% CI: 1.04–1.42). Creatinine levels were consistently linked to reduced BMD, including lumbar spine BMD (OR: 0.88, 95% CI: 0.79–0.99). Triglycerides in IDL and VLDL particles also contributed to BMD variation. Conclusions: Significant genetic correlations and causal relationships were observed between specific metabolites and OP, highlighting key traits as potential biomarkers of bone health. These findings enhance the understanding of OP pathogenesis and suggest future preventive strategies. Full article

Background: Previous studies have demonstrated that the gut microbiota (GM) and rheumatoid arthritis (RA) are significantly associated, but the causal relationship has not been fully elucidated. Methods: We investigated the association between GM and RA using Mendelian randomization (MR) with two independent samples. Our study aimed to determine the causal relationship between gut microbiota and RA, including its seronegative and seropositive subtypes. Using data from a genome-wide association study (GWAS), we identified instrumental variables for 211 gut bacteria types. We then analyzed the FinnGen GWAS dataset, which included 3877 seronegative RA cases and 285,035 controls, along with 4290 seropositive RA cases and 368,362 controls, employing the inverse variance weighted (IVW) method and rigorous tests for pleiotropy and heterogeneity to ensure reliability. Results: The IVW results revealed that Prevotella 9, Sutterella, and Christensenellaceae R.7 exhibited an adverse correlation with seronegative RA (p < 0.05). Additionally, Lachnospira, Slackia, Roseburia, Barnesiella, and Prevotella 7 were associated with a reduced occurrence of seropositive RA (p < 0.05). Conversely, Ruminococcaceae UCG002 and Ruminococcus gauvreauii were linked to an increased susceptibility to seropositive RA (p < 0.05). Notably, no significant heterogeneity (p > 0.05) or pleiotropy (p > 0.05) was detected in the analysis of the significant MR estimates. Conclusions: Our study suggested significant associations between several gut bacteria and RA subtypes, indicating a potential microbial influence on RA development. These findings enhance our understanding of the gut-joint axis in RA and highlight promising targets for future microbiota-based therapies. Full article

Phytoalexins are specialized metabolites that are synthesized by plants in response to pathogens. A paradigm in transcription factor (TF) biology is that conserved TFs have dedicated roles across plant lineages in regulating specific branches of specialized metabolism. However, the Arabidopsis (Arabidopsis thaliana) NAC family TF ANAC042 (a.k.a. JUNGBRUNNEN1 or JUB1) regulates the synthesis of camalexin, a Trp-derived phytoalexin specifically produced by several Brassicaceae species, whereas its homolog in soybean (Glycine max) regulates the synthesis of glyceollins, which are Phe-derived phytoalexins specific to soybean. The question addressed by this research is whether ANAC042 broadly regulates phytoalexin biosynthetic pathways in Arabidopsis. Using a novel matrix-assisted laser desorption ionization high-resolution mass spectrometry (MALDI-HRMS) method, we found that the Arabidopsis loss-of-function mutant anac042–1 elicited with bacterial flagellin (Flg22) is deficient in lineage-specific Trp- and conserved Phe-derived phytoalexins—namely camalexin and 4-hydroxyindole-3-carbonyl nitrile (4OH-ICN), and pathogen-inducible monolignols and scopoletin, respectively. Overexpressing ANAC042 in the anac042-1 mutant restored or exceeded wildtype amounts of the metabolites. The expression of phytoalexin biosynthetic genes in mutant and overexpression lines mirrored the accumulation of metabolites. Yeast-one hybrid and promoter-reporter assays in Nicotiana benthamiana found that the ANAC042 protein directly binds and activates the promoters of CYP71B15, CYP71A12, and PAL1 genes for the synthesis of camalexin, 4OH-ICN, and pathogen-inducible monolignol/scopoletin, respectively. Our results demonstrate that ANAC042 regulates conserved and lineage-specific phytoalexin pathways in Arabidopsis. The latter suggests that it is an opportunistic TF that has coopted lineage-specific genes into phytoalexin metabolism, thus providing an exception to the current paradigm. Full article

Anorexia nervosa (AN) is a severe psychiatric disorder characterized by substantial heritability and a high mortality rate among psychiatric disorders. While cerebrospinal fluid (CSF) metabolomics has emerged as a novel approach to investigating central nervous system pathologies, its specific causal relationship with anorexia nervosa remains to be fully elucidated. Using genome-wide association study (GWAS) summary statistics for human CSF metabolites and AN information from publicly available datasets, we performed a two-sample Mendelian randomization (MR) analysis using the inverse-variance weighted (IVW) method as the primary approach, complemented by sensitivity analyses. Through a comprehensive analysis of 338 CSF metabolites, we identified six metabolites with significant causal relationships with AN risk. 1-stearoyl-2-linoleoyl-gpc (18:0/18:2) (OR = 1.09, 95% CI 1.00–1.18) and alpha-tocopherol (OR = 1.36, 95% CI 1.00–1.83) showed positive associations, increasing AN risk. Conversely, sphingomyelin (d18:1/20:0, d16:1/22:0) (OR = 0.86, 95% CI 0.77–0.95), 2,3-dihydroxy-2-methylbutyrate (OR = 0.92, 95% CI 0.86–0.98), N-acetylhistidine (OR = 0.92, 95% CI 0.86–0.98), and oxalate (ethanedioate) (OR = 0.83, 95% CI 0.73–0.94) had protective effects, reducing AN risk. Sensitivity analyses showed no evidence of horizontal pleiotropy or heterogeneity in the MR results. An MR directionality test and a Steiger filtering test confirmed the absence of reverse causality, thereby substantiating the robustness of our findings. These findings suggest that these CSF metabolites could serve as potential biomarkers for early AN detection and highlight novel therapeutic targets, potentially improving diagnosis and intervention strategies for this challenging disorder. Full article