Development of a blood-based ferroptosis driver scoring system for Parkinson's disease using public datasets and machine learning.

Antipsychotics drugs are to varying degrees associated with hematological side-effects and peripheral metabolic and immunological changes. Here, we aimed to characterize the initial transcriptional changes in peripheral leukocytes from individuals with schizophrenia spectrum disorder (SSD) after starting antipsychotic treatment with amisulpride, aripiprazole, or olanzapine. We analyzed RNA sequencing data obtained from peripheral whole blood samples from 100 individuals with SSD (41 antipsychotic-naïve, 10 antipsychotic-free and 49 antipsychotic-switching at inclusion) collected at baseline and after one week and three weeks of antipsychotic drug use. Data from 36 healthy controls (HC) collected at baseline and after three weeks without any intervention were included. We analyzed age- and sex-adjusted differentially expressed genes between SSD and HC before and after treatment and stratified by previous antipsychotic use. A linear mixed model was applied to study longitudinal gene expression changes associated with the antipsychotic drug that was used. After three weeks of antipsychotic use, the antipsychotic-switching group had the most significant transcriptional changes, characterized by increased expression of genes typically transcribed by immature erythroid cells and immature neutrophil cells. This gene profile showed no correlation with symptoms score. Interestingly, the immature neutrophil-associated gene signature was more pronounced in participants receiving olanzapine, and partly also amisulpride, but not aripiprazole. In contrast, only minor transcriptional changes were observed in the antipsychotic-naïve participants. These findings suggest that prior antipsychotic exposure may have a priming effect on leukocyte gene expression, which results in a transcriptional response indicative of stress erythropoiesis and neutropoiesis when switching to a new antipsychotic drug. This response appears to be independent of psychosis symptom severity.

Background:Extreme-phenotype comparisons allowed the discovery of novel asthma genetic risk loci. However, this approach remains unexplored in epigenome-wide association studies (EWAS). We aimed to identify bulk and cell-specific methylation markers of asthma with severe exacerbations across diverse ancestry groups.Methods:We conducted a meta-EWAS of 739,543 CpGs in whole blood among 1,192 African American and Latino pediatric populations, comparing non-asthmatics and asthma exacerbators. Genome-wide CpGs were followed up for replication in a meta-analysis across 1,516 ethnically diverse participants and in a cross-tissue evaluation of 393 nasal samples. We conducted differentially methylated region (DMRs), cell-type-deconvoluted, and quantitative trait loci analyses (whole-genome sequencing n=1,668; RNA-seq n=1,209). We examined enrichment in traits, pathways, and druggable genes, and analyzed DNAm predictors of plasma proteins and aging.Results:DNAm at 505 CpGs and 119 DMRs in whole blood were associated with asthma exacerbations (p <9x10−8, λ=1.05). We replicated 25 CpGs in blood cells, cross-validated 7 in nasal samples, and detected 42 cell-specific DNAm markers mainly driven by T cells. DNAm at 134 CpGs was associated with gene expression in whole blood, including 118 associations with T-cell receptor genes, and 446 CpGs were regulated by > 1 genetic variant. We found enrichment for previous associations with environmental exposures, immune disorders, immune and inflammatory pathways, and druggable genes by developmental drugs. 21 methylation-predicted plasma proteins, involved in host defense, and one lung aging clock were associated with asthma exacerbations.Conclusions:The first meta-EWAS of extreme asthma phenotypes identified hundreds of novel DNAm markers, suggesting novel methylation biomarkers and candidate drugs for asthma and supporting the role of T cells.

Acute myocardial infarction (AMI) is one of the leading causes of mortality worldwide. Despite extensive research, only a limited number of genes have been identified as reliable biomarkers for the diagnosis and treatment of AMI. This study aims to identify novel biomarkers and therapeutic targets for AMI by integrating multi-omics data and machine learning. We obtained the GWAS dataset I9_MI_STRICT from the FinnGen database and the eQTL dataset of peripheral blood from the GTEx database. Using these datasets, we identified genes significantly associated with AMI through transcriptome-wide association studies (TWAS). Functional enrichment analysis was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Additionally, we downloaded three AMI peripheral blood gene expression microarray datasets (GSE66360, GSE48060, GSE60993) from the Gene Expression Omnibus (GEO) database. Key genes were further identified by combining the risk prediction model constructed by 12 machine learning methods(dataset GSE66360 as the training set, dataset GSE48060 and dataset GSE60993 as the validation set) and Bayesian colocalization analysis. To explore the potential mechanisms of these key genes in AMI, we conducted immunoinfiltration analysis, single-gene Gene Set Enrichment Analysis (GSEA), and Gene Set Variation Analysis (GSVA). Finally, the expression of key genes was validated using real-time quantitative PCR (RT-qPCR) and western blot. We identified several key genes: LIPA, PECAM1, SMARCA4, HP, RTN2, CFDP1, XPO6, and FES. Receiver operating characteristic (ROC) analysis demonstrated that these genes exhibited excellent diagnostic performance. Enrichment analysis revealed their primary involvement in lipid metabolism, immune system processes, gene transcription regulation, and ion channel regulation. Furthermore, immunoinfiltration analysis showed that PECAM1, HP, RTN2, CFDP1, and FES were significantly correlated with various immune cell types. qRT-PCR and western blot analysis revealed that the mRNA expression of LIPA, RTN2, and PECAM1 was upregulated in the AMI group, while CFDP1 and XPO6 showed downregulation compared to the control group. This study identified nine key genes as potential novel targets for the diagnosis and treatment of AMI.

Maternal nutrition during late gestation is critical for fetal development, neonatal resilience, and postnatal adaptation in beef cattle. This study aimed to evaluate the effects of nutritional restriction and supplementation of hydroxytyrosol (HT) in late pregnancy on behavioural, circadian, stress-related, and inflammatory responses in cows and their restricted nursed offspring. Pregnant cows were allocated to a 2 × 2 factorial experimental design (feeding level: T100% vs. T60% of nutrient requirements; HT: 0 vs. 180 mg/kg of diet). Cow behaviours were recorded during meals (from week −12 prepartum to term), and calf activities, body temperature, and mother–offspring interactions were assessed at 5 weeks postpartum. Nutritional restriction accelerated feed intake in cows and increased stress-related behaviours, while HT partially mitigated these effects. Molecular analyses in blood samples revealed dynamic prepartum upregulation of glucocorticoid-receptor NR3C1 in week −6, and downregulation of circadian (BMAL1, PER1, CRY1) gene expression in week 5 after parturition, both in T60%-HT cows. In calves, maternal HT supplementation promoted active exploratory behaviour, and counteracted behavioural and circadian (CRY1 and PER1) and inflammatory markers (IL8) gene expression resulting from prenatal nutrient restriction, leading to behavioural profiles and blood gene expression comparable to those observed in calves born to adequately fed dams.

Host gene expression profiling holds great potential in improving the differential diagnostics of bacterial and viral infections. We investigated its discriminative value in children with suspected serious infections. Peripheral blood gene expression profiles were analyzed by RNA sequencing in 268 children aged between 4 weeks and 16 years: 211 hospitalized due to a suspected severe infection, 15 with a confirmed viral respiratory tract infection managed as outpatients, and 42 healthy control children. We classified children according to the bacterial, viral, or other etiology of their final diagnosis, and determined expression profiles. We derived 2-transcript signatures discriminating bacterial infections and viral-bacterial co-infections from viral infections in a discovery group (n = 101) of children with respiratory tract infections and validated them in children (n = 109) with non-respiratory infections, including cases with probable and mixed etiologies in the analyses. Here, we show that clustering of blood transcriptome cannot be unequivocally explained by the etiology of infection. A 2-transcript signature comprising TSPO and SECISBP2 genes differentiates bacterial and viral-bacterial co-infections from viral infections with an area under the curve of 0.93 and 0.87 (95% confidence interval, 0.88-0.98 and 0.82-0.92) in the discovery and discovery plus validation groups, respectively. Both groups combined, the sensitivity is 77%, and specificity 87%. The identified 2-transcript signature demonstrates good accuracy in distinguishing between bacterial and viral infections in a complex population of children hospitalized for suspected severe infection. Heterogeneity of clinical manifestations needs to be considered in diagnostic gene expression studies.

Recent studies have shown that from the 23rd week of gestation onward, the fetus becomes progressively more hypoxic, with oxygenation levels rising again after 33-34 weeks. The biological significance of this biphasic oxygenation pattern has remained unclear. Umbilical cord blood samples from 100 preterm and 100 full-term neonates were analyzed for blood gas parameters and for HIF1A, ADRB3 (β3-adrenoceptor), and VEGFA gene expression. A progressive increase in mRNA expression of all three genes was observed with advancing gestational age, followed by a decline during the final weeks of pregnancy. This gene expression trend was inversely correlated with fetal oxygenation status. This study demonstrates that β3-adrenoceptor expression progressively increases with gestational age, supporting the concept that this receptor plays a key role in fetal development and well-being. These findings strengthen the evidence from animal models showing that pharmacological activation of β3-adrenoceptors can reproduce, even after birth, some of the beneficial effects normally provided by the intrauterine environment. Collectively, this work supports the conceptual framework for developing a "pharmacological artificial placenta" aimed at mimicking intrauterine conditions to promote physiological neonatal adaptation. Recent studies have shown that from the 23rd week of gestation onward, the fetus becomes progressively more hypoxic, with oxygenation levels rising again after 33-34 weeks. However, the biological significance of this biphasic oxygenation pattern had remained unclear. This study demonstrates for the first time that fetal oxygen fluctuations are accompanied by a synchronous and coordinated increase in the mRNA expression of HIF1A, ADRB3 (β3-adrenoceptor), and VEGFA genes. These findings support a mechanistic link between intrauterine hypoxia, β3-adrenergic signaling, and fetal maturation. This work contributes to ongoing research suggesting that pharmacological β3-adrenoceptor activation may help recreate intrauterine-like conditions, potentially promoting physiological fetal development in adverse environments.

Acute respiratory exacerbations in bronchiectasis are important as they impair quality of life and are associated with accelerated lung function decline. Yet, no validated methods exist to identify children at increased risk of exacerbations. We therefore determined if peripheral blood gene expression (GE) signatures can identify those at risk of an impending exacerbation. Thirty-one children with bronchiectasis had RNA extracted from peripheral blood collected whilst they were clinically stable, with 22 having an exacerbation during the next 3 months. Microarray assays using the HumanHT-12 v4.0 Expression BeadChip identified differentially expressed genes (p value ≤ 0.05, fold change > 1.5). The top targets were verified using real-time quantitative polymerase chain reaction (rt-qPCR) assays, and receiver operating characteristics and area under the curve (AUC) were assessed. Functional analysis of these genes was performed using Ingenuity Pathway Analysis. Overall, 647 entities were significantly dysregulated (p < 0.05) in the exacerbation group (n = 22), and pathway analysis identified neutrophil degranulation as the dominant affected pathway, which was also significantly inhibited (p < 0.001). Forty entities (32 genes) were associated with a future exacerbation (p ≤ 0.05, fold change ≥ 1.5) and six genes (ANXA3, ALAS2, DEFA1, ALPL, SNCA, PROK2) were verified using RT-qPCR (all p < 0.04) as the most discriminatory. DEFA1 and ANXA3 had the highest AUC (0.92, 95% confidence interval [CI] 0.82-1.00, and 0.87, 95% CI 0.73-1.00, respectively). We identified neutrophil-associated genes from peripheral blood that could be potential biomarkers for children with bronchiectasis at increased risk of exacerbations during the next 3 months. These GE signatures warrant further investigation and validation in larger, independent cohorts. KEY MESSAGES: Exacerbations in paediatric bronchiectasis are important. Peripheral blood gene expression may help identify children at risk of exacerbations. Six neutrophil-associated genes were associated with a future exacerbation. Identifying predictive gene expression signatures warrants further investigation.

Whole blood gene expression to assess disease severity of omicron-associated acute encephalitis and croup in children: A transcriptomic and immune profiling study.

Autophagy dysregulation has been implicated in the toxic protein aggregates of amyotrophic lateral sclerosis (ALS). However, the causal relationship between impaired autophagy and ALS remains ambiguous, necessitating further elucidation. This Mendelian randomization (MR) study employs a two-sample design, utilizing genetic instruments to proxy autophagy dysregulation as the exposure and ALS as the outcome. It incorporates summary statistics of ALS (27,205 cases, 110,881 controls), along with data on DNA methylation, RNA splicing, gene expression, and protein abundance quantitative trait loci (QTLs) in both blood and brain tissues (mQTL, sQTL, eQTL, and pQTL, respectively) sourced from European cohorts. Cis-variants situated proximal to or within the 604 autophagy-related genes, exhibiting robust associations with molecular alterations in autophagy, are employed as instrumental variables. Their causal links with ALS are assessed via summary-data-based MR (SMR) analyses, followed by Bayesian colocalization, sensitivity analyses, brain cell-specific MR analyses, protein-protein interaction (PPI), and druggable analyses. Consistent evidence supported the causal effects of two lysosome genes (FNBP1 and IDUA), one autophagy core gene (C9orf72), and one mitophagy gene (USP35) on ALS risk. Specifically, brain FNBP1 splicing level (OR = 1.18, p = 3.38E-5) and blood USP35 expression level (OR = 1.17, p = 5.94E-5) were positively associated with higher ALS risk. In contrast, we found strong causal evidence of brain IDUA methylation level (OR = 0.96, p = 8.36E-6) and blood C9orf72 methylation level (OR = 0.55, p = 7.59E-12) with lower ALS risk. Cell-type-specific MR analyses, PPI, and druggable analyses further nominated the key brain cell type (astrocytes), potential interaction with known causative genes (SQSTM1 and PFN1), and promising druggability for FNBP1 in ALS. This multi-omics MR study identified causal associations between the regulation of four autophagy-related genes and ALS risk, shedding light on autophagy-mediated mechanisms and offering early evidence of novel therapeutic targets for ALS.

Social cognition is essential for forming and maintaining intimate relationships. Individuals with a history of childhood maltreatment (CM) often show impairments in interpersonal functioning, including trust and romantic attachment. The oxytocin system has been implicated in social behavior, yet the role of oxytocin receptor (OXTR) gene expression in CM-related social functioning remains insufficiently understood. This study examined the impact of CM on social cognition in a large web-based sample and explored the association between CM and OXTR gene expression in a well-characterized clinical cohort. Both studies were preregistered (https://doi.org/10.17605/OSF.IO/KNC2X), and data and code are available at OSF (https://doi.org/10.17605/OSF.IO/4DZWK). Study 1 assessed the relationship between CM severity, interpersonal trust, and romantic attachment in a web-based sample (N = 252). Participants completed the Childhood Trauma Questionnaire, the Generalized Trust Scale, a behavioral distrust game, and the Experiences in Close Relationships Questionnaire. Study 2 analyzed OXTR gene expression in peripheral blood samples from N = 92 CM-exposed individuals and examined associations with self-reported CM severity. Exploratory analyses additionally included measures of interpersonal sensitivity, social functioning, and maladaptive personality traits. In Study 1, greater CM severity was significantly associated with lower interpersonal trust (both self-reported and behavioral), and with higher levels of attachment-related anxiety and avoidance. In Study 2, no significant association was found between CM severity and OXTR gene expression in blood. However, exploratory analyses revealed that CM severity was associated with social interaction difficulties, while OXTR gene expression was associated with the maladaptive personality trait of detachment. The findings highlight robust associations between CM and impairments in trust as well as insecure romantic attachment. Although no direct link was found between CM and OXTR expression, future research should investigate gene–environment interactions using larger samples and alternative tissue sources. Interventions targeting trust and attachment processes may offer promising avenues to improve relational functioning in individuals with a history of CM.

Alcohol-associated liver disease (ALD) is a significant global health concern that is characterized by hepatic triglyceride accumulation and dysregulation with impairment of oxygen homeostasis. This study investigated the time-dependent effects of ethanol exposure on liver disease progression in 2-month-old male C57/BL6 mice. Mice were treated with ethanol (20% ethanol at 5gm/kg.b.wt/day) for 2, 4, and 6months, and blood biochemical markers, liver histopathology, and gene expression were evaluated. Results showed that ethanol exposure led to significant increases in thiobarbituric acid reactive substances (TBARS), protein carbonyls, plasma nitric oxide (NOx), C-reactive protein, and homocysteine, liver enzymes, such as aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), gamma-glutamyl transferase (γ-GT), lactate dehydrogenase (LDH) indicating oxidative stress and liver injury. Lipid profile analysis revealed increased total cholesterol and triglycerides, with decreased HDL-cholesterol. Moreover, reduced mitochondrial enzyme activity indicates dysfunction. Histopathology and qRT-PCR analysis showed increased CYP2E1, Bax, Bcl2, p53, caspase-3, caspase-9, and inducible nitric oxide synthase (iNOS) gene expression, leading to ROS/RNS generation. The miR-21 was upregulated, while miR-26a was downregulated, contributing to lipid metabolism dysregulation, pro-inflammation, and pro-fibrosis. These findings suggest that ethanol exposure causes triglyceride accumulation and cholesterol dysregulation, leading to oxidative stress, mitochondrial dysfunction, and hepatocellular injury. The dysregulation of miR-21 and miR-26a contributes to ALD progression. Markers of oxidative stress, miRNAs, and disrupted metabolic pathways may serve as potential biomarkers or therapeutic targets for early detection and intervention in ALD.

Gulf War Illness is a chronic multi-symptom disorder experienced by over 30% of veterans from the 1990–1991 Gulf War and is increasingly recognized to be driven by underlying persistent neuroinflammation resulting from chemical and physiological exposures experienced during deployment. Despite significant advances in identifying Gulf War-relevant exposures and underlying pathobiology, effective treatment strategies for Gulf War Illness are still largely lacking. Many studies that have evaluated potential therapies for Gulf War Illness have primarily focused on a single treatment. However, through a mechanistically informed computational evaluation of blood biomarkers and gene expression in veterans with Gulf War Illness, we identified that a combination of anti-inflammatory and anti-glucocorticoid treatment may prove effective in treating Gulf War Illness. Here, we have evaluated combined treatment with the anti-TNFα drug, etanercept, and anti-glucocorticoid, mifepristone, in an established long-term mouse model of Gulf War Illness of combined physiological stress and nerve agent exposure. Supporting results from the computational modeling of this treatment, we found that this drug combination significantly alleviates the underlying neuroinflammation associated with Gulf War Illness. The fusion of computational and in vivo preclinical treatment evaluation may provide a highly useful and translationally relevant means by which to identify successful treatment paradigms for Gulf War Illness.

Azithromycin is a widely used antibiotic and was frequently used to treat hospitalized patients during the COVID-19 pandemic. The impact of empiric azithromycin use on the respiratory microbiome in patients with viral respiratory infections is unclear. Here we used longitudinal metatranscriptomics on nasal swabs from a prospective multicentre cohort of 1,164 patients hospitalized for COVID-19. We compared the upper respiratory microbiome, resistome and systemic immune response in patients treated with azithromycin (n = 366) with those who received no antibiotics (n = 474) or other antibiotics (n = 324). We found that azithromycin altered microbiome composition and increased the expression and relative proportion of macrolide/lincosamide/streptogramin (MLS) resistance genes. These changes occurred after 1 day of exposure and persisted for over a week. MLS resistance gene expression was associated with commensals and potential pathogens, while there were no differences in host inflammatory gene expression in blood and airways. This demonstrates that empiric azithromycin treatment impacts the upper respiratory microbiome and resistome without apparent anti-inflammatory benefit.

Effects of dietary lyophilized Rhodotorula mucilaginosa on the growth performance, proximate composition, blood biochemical parameters, gene expression and microbiome of gilthead seabream (Sparus aurata)

Subcutaneous immunotherapy (SCIT) is a well-established treatment for inducing immune tolerance in patients with allergic rhinitis (AR). However, the precise molecular mechanisms by which SCIT induces immune tolerance, particularly at the transcriptomic level over the treatment course, have not been fully elucidated. This study aimed to investigate the molecular mechanisms of SCIT by analysing changes in peripheral blood gene expression profiles in AR patients over time. Whole blood samples were prospectively collected from 30 AR patients (16 paediatric, 14 adult) and 10 healthy controls. RNA sequencing was performed at baseline and at 3, 6 and 12 months of SCIT. Differentially expressed genes (DEGs) were identified, and pathway enrichment, immune cell deconvolution and weighted gene co-expression network analysis were conducted to explore immune regulation and tolerance mechanisms. AR patients showed 1180 DEGs compared to healthy controls, with upregulated genes related to B-cell activation and downregulated genes linked to Th1 differentiation. Both paediatric and adult cohorts exhibited consistent transcriptomic changes, characterised by progressive normalisation of gene expression, with the number of DEGs decreasing over time and significant convergence towards healthy control profiles by 12 months. SCIT enhanced type I interferon responses and antiviral pathways while reducing B-cell activation and inflammatory responses. Immune cell analysis revealed increased regulatory T cells and dendritic cells by 6 months and reduced Th2 cells and eosinophils by 12 months. Key immune-related hub genes, including CD19, CD79A, CD79B, CD22, IFIH1, STAT1, DHX58, TLR4, IL1B and TLR1, were identified as central to SCIT efficacy. SCIT dynamically modulates blood gene expression profiles in AR patients, inducing immune tolerance and reducing inflammatory responses. These findings enhance understanding of the molecular mechanisms of SCIT and highlight potential biomarkers for predicting and monitoring treatment efficacy.

Introduction: The increasing incidence of endometrial cancer (EC) requires an extensive search for novel preventive tools and early intervention approaches. However, the development of reliable predictive models is impossible without knowledge of genetic alterations prior to diagnosis. In this work, we aimed to establish whether known EC risk factors are associated with peripheral blood gene expression changes in a prospective design and whether such associations differ between women who later developed EC and matched controls. Methods: First, we selected variables (parity status, lifetime number of years of menstruation, coffee consumption, body mass index (BMI), age at menopause, use of oral contraceptives) that were shown to have an impact on EC risk in a large prospective cohort (165,000 women). Next, using BeadChip microarray technology, we tested the association between these variables and gene expression profiles in RNA extracted from mixed circulating immune cells in a nested case-control study (79 case-control pairs) of women from the NOWAC postgenome cohort. Lastly, we undertook a gene set enrichment analysis (GSEA). Results: At overall gene expression level, we found no difference between the EC cases and controls. The introduction of parity status into the statistical model revealed changes in the expression of 1,379 genes in the controls, while we did not observe any expression changes in the cases. Twenty-seven genes were associated with BMI increase in the controls, whereas there was no association observed between changes in BMI and gene expression in women with EC. In GSEA, 2,407 significantly enriched gene sets were attributed to a parity increase among cancer-free women. Conclusion: In this study, we found that an increased number of parities has a life-long effect on the gene expression profile in the peripheral blood of women who never developed cancer. In contrast, in women who were diagnosed with EC later in life, neither multiparity nor elevated BMI showed a significant association with gene expression patterns. However, given the modest sample size and exploratory nature of the study, these findings should be verified in larger cohorts.

To characterize clinical and transcriptomic differences in juvenile scleromyositis overlap (jOverlap) compared to juvenile systemic sclerosis (jSSc) and juvenile dermatomyositis (JDM), focusing on autoantibody profiles, organ involvement, treatment, and peripheral blood gene expression. Peripheral blood bulk RNA sequencing was performed on children with jSSc (n=25), JDM (n=25), and jOverlap (n=26), and healthy controls (HCs; n=21) from two tertiary referral centers. Disease category was assigned by treating physicians. Clinical data and autoantibody profiles were collected. RNA was sequenced using the Illumina NextSeq 500 platform. Differentially expressed genes (DEGs) were identified using Partek Flow and DESeq2, applying a log2 fold change cutoff of ±1.5 and a false discovery rate of <0.1. Patients with jOverlap, predominantly White girls, had distinct autoantibody patterns enriched for PM-Scl, U1-RNP, and U3-RNP. Compared to HCs, patients with jSSc, JDM, and jOverlap demonstrated a unique gene expression profile, with up-regulation of type-1 interferon-related genes, specifically SIGLEC1 and IFI27. Compared to patients with JDM, patients with jOverlap showed higher expression of RAB13 (linked to sclerosing neurodegenerative disease), MMEL1 (inflammatory arthritis), and MMP19 (pulmonary fibrosis). t-distributed stochastic neighbor embedding clustering revealed that although HC, jSSc, and JDM samples each formed distinct clusters, jOverlap samples were distributed across all clusters, highlighting their heterogeneity. Patients with jOverlap exhibited a distinct immunophenotype and clinical profile compared to patients with jSSc and JDM. Their broad transcriptional heterogeneity suggests disease category alone does not explain gene expression patterns. Further analysis correlating DEGs with autoantibodies, age, and clinical features is warranted to better define this overlapping disease entity.

Dietary effect of nano-encapsulated probiotics and alpha-lipoic acid in improving blood parameters, immunity, gut health, gene expression, and growth performance in heat-stressed broilers

Selective serotonin reuptake inhibitors (SSRIs) are a recommended first line medication for the treatment of major depressive disorder, due to higher tolerability and lower risk of adverse effects than other antidepressants. The mechanisms by which SSRIs reduce depressive symptoms are not well understood, but are hypothesised to include direct effects on serotonin signalling and synaptic remodelling, and indirect effects on inflammation. Indirect or off-target effects may be detectable in blood and can be investigated using methylome- and transcriptome-wide approaches. The Staged Treatment in Early Psychosis (STEP) clinical trial included a 6-month long randomised, placebo-controlled trial of the SSRI fluoxetine in a cohort of young people at ultra-high risk for psychosis. A methylome-wide association study (MWAS; NTotal (before/after/both)=104 (52/52/44), NSSRI (before/after/both)=45 (21/24/18)) and differential expression analysis were performed on longitudinal blood samples collected at the start and end of the 6months to identify changes in DNA-methylation and gene expression associated with medium-term SSRI exposure. Four methylation CpGs (cg26253898, cg09719563, cg22216017, cg26017656) were significantly associated with SSRI exposure (FDR < 0.1, 2 CpGs at FDR < 0.05) and annotated to genes involved in glucose metabolism, synaptic remodelling and inflammation (GCG, COL23A1, PEG10, SGCE, MFGE8). Gene-set enrichment analyses of genes annotated to the top 100 CpGs identified significant tissue-specific enrichments in artery, adipose and spleen tissues, and in the 'postsynaptic density' GO term. No genes were differentially expressed, including genes annotated to the significant methylation CpGs. Medium-term SSRI use during the STEP trial was associated with changes in DNA-methylation that may partially explain the potential antidepressant mechanisms and adverse effects of SSRIs, however replication in other cohorts is necessary to establish if these changes are generalisable to SSRI use more broadly.