Differences In Abundance Research Articles

Quantitative proteomics analysis of cerebrospinal fluid reveals putative protein biomarkers for canine non-infectious meningoencephalomyelitis.

Accurate ante-mortem diagnosis of non-infectious meningoencephalomyelitis (NIME) in dogs is challenging due to the similarity of clinical presentations, imaging findings, and cerebrospinal fluid (CSF) analysis results with other diseases. This study aimed to apply state-of-the-art quantitative proteomic technology to identify novel biomarkers for NIME. Serum and CSF samples from 11 dogs were included, with the control group consisting of patients presenting with intervertebral disc disease (IVDD, n = 6) and the study group consisting of dogs suffering from NIME (n = 5). Mass spectrometry-based quantitative proteomics revealed a set of 36 proteins with significant differential abundance in CSF samples. Up-regulated proteins in NIME CSF included immunoglobulins, inter-alpha-trypsin inhibitor heavy chain 2, acid sphingomyelinase-like phosphodiesterase, and chitinase 3-like protein 1, all associated with immune response and inflammation. Conversely, significantly down-regulated proteins included neural cell adhesion molecule, contactin-1, and procollagen C-endopeptidase enhancer, which are involved in neurodevelopment and synaptic plasticity. No differences in serum profiles were observed among the groups. This study identified a panel of CSF protein biomarker candidates for NIME and provided new insights into the pathogenesis of the disease, suggesting that neuronal dysfunction and immune dysregulation may be involved.

Characterization and comparison of fecal microbiota in horses with pituitary pars intermedia dysfunction and age-matched controls.

Altered gut microbiota has been associated with dopaminergic degenerative diseases in people, but studies on horses with pituitary pars intermedia dysfunction (PPID) are lacking. Investigate the effect of PPID on fecal microbiota in horses. Nine horses with PPID and 13 age-matched control horses. Prospective control study. Fecal samples were collected bimonthly. Microbial analysis used 16S rRNA sequencing to determine the relative abundance at genus and phylum levels, assess alpha and beta diversity and identify core microbiota. Horses with PPID had decreased relative abundances of Christensenellaceae R-7 group (median; 95% confidence interval [CI]: PPID, 2.04; 1.82-2.35 vs control, 2.54; 2.37-2.76; P = .02) and NK4A214 group (PPID, 2.21; 2.02-2.56 vs control, 2.62; 2.44-2.85; P = .05), and significant lower abundances of Romboutsia (log2FoldChange = -3.54; P = .04) and Peptococcaceae uncultured (log2FoldChange = -0.89; P = .04) by differential abundance analysis. However, the abundance of Fibrobacter (log2FoldChange = 0.74; P = .04) was significantly higher in the PPID group. A significant effect of PPID on beta diversity was observed (P = .004), whereas alpha diversity varied with months (P = .001). Seven unique genera were identified in horses with PPID and 12 in control horses. The fecal microbial composition is altered in horses with PPID. These findings support the potential role of the microbiota-gut-brain axis in the pathogenesis of PPID.

Extracellular vesicles in seminal plasma of Sahiwal cattle bulls carry a differential abundance of sperm fertility-associated proteins for augmenting the functional quality of low-fertile bull spermatozoa

Poor male fertility significantly affects dairy production, primarily due to low conception rates (CR) in bulls, even when cows are inseminated with morphologically normal sperm. Seminal plasma is a key factor in evaluating the fertilizing ability of bull semen. The extracellular vesicles (EVs) in seminal plasma contain fertility-associated proteins like SPAM1, ADAM7, and SP10, which influence sperm function and fertilizing potential. This study aimed to assess EV-associated fertility proteins in bulls with varying fertility levels and to investigate the effects of seminal plasma EVs (SPEVs) from high-fertility (HF) bulls on the spermatozoa of low-fertility (LF) Sahiwal bulls. Seminal plasma was isolated from the fresh semen of Sahiwal bulls, with four bulls classified as high fertility and three as low fertility. Fertility-associated proteins such as SP10, ADAM7, and SPAM 1 were highly expressed in SPEVs of high-fertility (HF) bulls. PKH26 dye-labeled SPEVs demonstrated significant uptake by spermatozoa at pH 6.8 with ≥ 4 h of co-incubation. Exposure of HF SPEVs to low-fertility (LF) spermatozoa reduced acrosome response, capacitation, and reactive oxygen species (ROS) formation. Our findings suggest that protein repertoires in SPEVs influence sperm activities such as motility, acrosome response, and ROS production. Supplementing LF spermatozoa with HF SPEVs could enhance their functional characteristics, highlighting these proteins as potential resources to modulate cattle bull sperm fertilizing ability.

Survival Disparity and the Unique Genomic and Microbiome Profiles of Colon Cancer in Appalachian Kentucky.

Colon cancer is a leading cause of mortality in Appalachian Kentucky. Studies suggest that the microbiome may influence cancer outcomes. We investigate differential gene expression, the tumor microbiome, and the association between the two as potential drivers of disparities in colon cancer outcomes. This study analyzed patients diagnosed with colon adenocarcinoma between 2010-2023. Demographic data were extracted from Kentucky Cancer Registry. Somatic mutations and significantly mutated genes were identified using Fischer's exact T-test. RNASeq data was processed for gene expression analysis and Holm-Bonferroni method was used to adjust p-values for multiple comparisons. The STAR aligner, (exotic)v2.1 pipeline, and KrakenUniq database were used to classify microbes in human samples. The R package (exotic) was then used to decontaminate the results. The final cohort included 2276 patients, 321 of which had available somatic mutation sequencing data. Demographic differences between Appalachian and non-Appalachian patients included marital status (P = 0.0005), race (P < 0.0001), insurance status, (P = 0.0005), BMI (P = 0.001), type 2 diabetes (P < 0.0001) and Charlson Comorbidity Index (CCI; P = 0.03). There was no difference in gene mutation frequency. There was differential expression of 228 genes. Differential abundance analysis revealed differences in 381 bacterial species. Importantly, 3 microbiota significantly correlated with survival disparities between Appalachian and non-Appalachian patients: C. cadaveris (adjusted P = 0.009), L. salivarius (adjusted P = 0.048), and S. wadsworthensis (adjusted P = 0.009). This is the first report of the distinct tumor microbiome in Appalachian Kentucky and its impact on survival. Further studies are needed to better characterize the unique tumor and gut microbiome of Appalachian patients with colon cancer.

Characterizing the omics landscape based on 10,000+ datasets

The characteristics of data produced by omics technologies are pivotal, as they critically influence the feasibility and effectiveness of computational methods applied in downstream analyses, such as data harmonization and differential abundance analyses. Furthermore, variability in these data characteristics across datasets plays a crucial role, leading to diverging outcomes in benchmarking studies, which are essential for guiding the selection of appropriate analysis methods in all omics fields. Additionally, downstream analysis tools are often developed and applied within specific omics communities due to the presumed differences in data characteristics attributed to each omics technology. In this study, we investigate over ten thousand datasets to understand how proteomics, metabolomics, lipidomics, transcriptomics, and microbiome data vary in specific data characteristics. We were able to show patterns of data characteristics specific to the investigated omics types and provide a tool that enables researchers to assess how representative a given omics dataset is for its respective discipline. Moreover, we illustrate how data characteristics can impact analyses at the example of normalization in the presence of sample-dependent proportions of missing values. Given the variability of omics data characteristics, we encourage the systematic inspection of these characteristics in benchmark studies and for downstream analyses to prevent suboptimal method selection and unintended bias.

Cardiac ATP production and contractility are favorably regulated by short-term S100A9 blockade after myocardial infarction.

The infarcted heart is energetically compromised exhibiting a deficient production of adenosine triphosphate (ATP) and the ensuing impaired contractile function. Short-term blockade of the protein S100A9 improves cardiac performance in mice after myocardial infarction (MI). The implications upon ATP production during this process are not known. This study evaluates whether S100A9 blockade effects ATP synthesis and cardiac contractility in C57BL/6 mice at seven days post-MI. Three experimental groups were used: (i) mice with MI, induced by permanent left coronary ligation, (ii) mice with MI, short-term treated with the S100A9 blocker ABR-238901, and (iii) sham (control) mice. After removing the left ventricle, mass spectrometry, pathway enrichment analysis, Western blot, RT-PCR and pharmacological network analysis were performed. A number of 600 differential abundance proteins (DAPs) was significantly altered by the S100A9 blocker in MI-treated mice compared with MI mice. Some of these proteins were associated with oxidative phosphorylation, citrate cycle (TCA), mitochondrial fatty acid beta-oxidation, glycolysis and cardiac muscle contraction pathways. In the ischemic ventricle, ABR-238901 treatment increased (1.8- to 38-fold) the abundance of proteins NDUFAB1, UQCRC1, HADHA, ACAA2, ALDOA, PKM1, DLD, DLAT, PDHX, ACO2, IDH3A, FH1, CKM, CKMT2, TNNC1, crucial for early cellular metabolic changes, ATP distribution and contractility. The cardiac level of ATP increased (1.8-fold, p < 0.05) in MI mice treated with ABR-238901 compared to MI mice. The network pharmacology analysis uncovered potential pharmacologic targets of ABR-238901 that may interact with DAPs related to ATP production and contractility. Short-term S100A9 blockade effectively regulates the proteins implicated in ATP production and cardiac contractility post-MI, providing a framework for future cardiac energy metabolism studies.

Positive sputum fungal culture, fungal sensitisation and airway microbial diversity in asthmatic children.

Sensitisation to thermotolerant fungi such as Aspergillus fumigatus and Candida albicans which can colonise the airways is associated with poor lung function in children with asthma. Dysbiosis of bacteria and fungi in the airway microbiome has been reported between health and asthma but has yet to be characterised for fungal sensitised asthmatic children. We investigated if microbial diversity of the airways is altered in fungal sensitised school-age asthmatic children. Sputum samples from children with asthma who were fungal sensitised (n=22) and non-fungal sensitised (n=17) along with children without asthma (n=15), aged 5-16 years were profiled by traditional microbiological culture, modified fungal culture, bacterial 16S and fungal ITS2 next generation sequencing. Microbiota were compared between groups using alpha/beta diversity and differential abundance analysis. Bacterial alpha diversity was significantly lower in asthma compared to disease controls and in stable compared to acute asthma. Fungal alpha and beta diversity did not change between asthma states and disease controls, but alpha diversity was significantly lower in asthma samples from patients with positive A. fumigatus culture. Children sensitised to fungi had similar microbial diversity compared to non-sensitised children. However, in children not sensitised to fungi, those with a positive airway fungal culture had significantly lower fungal alpha diversity and bacterial beta differences compared to children with negative fungal culture. Fungal sensitisation did not alter bacterial or fungal microbiota in the airways of asthmatic children. However, positive airway fungal culture was associated with significant changes in microbial diversity, particularly in non-fungal sensitised children with asthma.

Microbiome analysis in individuals with human papillomavirus oral infection

Microbiome gained attention as a cofactor in cancers originating from epithelial tissues. High-risk (hr)HPV infection causes oropharyngeal squamous cell carcinoma but only in a fraction of hrHPV+ individuals, suggesting that other factors play a role in cancer development. We investigated oral microbiome in cancer-free subjects harboring hrHPV oral infection (n = 33) and matched HPV− controls (n = 30). DNA purified from oral rinse-and-gargles of HIV-infected (HIV+) and HIV-uninfected (HIV−) individuals were used for 16S rRNA gene V3–V4 region amplification and sequencing. Analysis of differential microbial abundance and differential pathway abundance was performed, separately for HIV+ and HIV− individuals. Significant differences in alpha (Chao-1 and Shannon indices) and beta diversity (unweighted UniFrac distance) were observed between hrHPV+ and HPV-negative subjects, but only for the HIV− individuals. Infection by hrHPVs was associated with significant changes in the abundance of Saccharibacteria in HIV+ and Gracilibacteria in HIV− subjects. At the genus level, the greatest change in HIV+ individuals was observed for Bulleidia, which was significantly enriched in hrHPV+ subjects. In HIV− individuals, those hrHPV+ showed a significant enrichment of Parvimonas and depletion of Alloscardovia. Our data suggest a possible interplay between hrHPV infection and oral microbiome, which may vary with the HIV status.

DOP025 Subjects sharing bacterial amplicon sequence variants exhibit differences in their IgA and IgG coating of gut bacteria, with enrichment of IgG binding for bacteria typically found in the oral cavity

Abstract Background IgA is the predominant antibody in the gut, coating a larger proportion of intestinal bacteria. IgG is found in lower concentrations but tends to increase with gut inflammation. We aimed to characterize IgA- and IgG-coated gut microbial compositions in healthy controls and evaluate coating variations of shared bacteria across individuals. Methods We established a protocol for isolating IgA- and IgG-bound fecal bacteria, using magnetic streptavidin beads coated with biotin anti-human IgA or IgG (Fig. 1A). The initial stool, as well as the negative (unbound) and positive (IgG- or IgA-bound bacteria) fractions, were analyzed by 16S rRNA sequencing. For differential abundance, a non-parametric, permutation-based rank mean test was applied (dsFDR&amp;lt;0.25). Results Fecal samples from 13 healthy subjects (Mean age 40.6 years, 54% males) were simultaneously incubated with anti-human IgA- or IgG- coated beads. Within-sample variability was quantified using three different fecal aliquots per subject, and several controls were included throughout the process. Paired differential abundance between the positive and the negative IgA fractions identified 46 amplicon sequence variants (ASVs) bacteria significantly higher in the positive fraction (IgA bound) and 44 ASVs significantly higher in the negative fraction. To better characterize the bound and unbound ASVs, we calculated term enrichment f-scores using the dbBact knowledge base (PMID: 37326027). This indicated enrichment of bacteria consistently reported as IgA-bound in previous publications, implicating the validity of our separation of Ig-bound bacteria (Fig. 1B). Similar analysis for the IgG-bound bacteria, identified 58 and 49 differentially abundant ASVs in the positive and negative fractions, respectively, with significant enrichment of bacteria previously noted to show IgA-coating and of salivary/oral bacteria among IgG-bound bacteria (Fig. 1C). Using the Ig-coating index (ICI; PMID: 25171403) of each `shared` ASV (detected in more than two subjects), we noted large inter-individual variance among the controls, with 42.4% ASVs showing significant inter-individual variance in IgA-coating (FDR&amp;lt;0.1; Fig. 2A) and 30.3% ASVs with significant inter-individual variance in IgG-coating (FDR&amp;lt;0.1; Fig. 2B). Conclusion Healthy subjects show variations in the immunoglobulin coating of bacteria, even among shared ASVs, indicating a personalized immune-bacterial repertoire. However, it is still unclear if this variation contributes to the gut microbiome composition variations seen between subjects. In addition, we observed preferential enrichment for immunoglobulin coating of bacteria typically found in the oral cavity.

P1351 Microbiome Diversity and Taxonomic Differences in Quiescent Ulcerative Colitis: A Comparative Study of Proximal Extension

Abstract Background The gut microbiome plays a significant role in ulcerative colitis (UC) pathogenesis, but its contributions during clinical remission and in relation to disease extent remain underexplored. This study investigates the microbiome profiles of quiescent UC patients with proximal extension (Y) and those without proximal extension (N), aiming to identify microbiome-based differences and potential biomarkers for disease stratification. Methods Fecal microbiome samples were obtained from 30 quiescent UC patients: 17 without proximal extension (N) and 13 with proximal extension (Y). Sequencing data were processed to exclude human genome reads, and rarefaction curves were used to ensure data quality. Alpha- and beta-diversity metrics assessed microbial diversity within and between groups. Differentially abundant taxa were identified, and a random forest model was employed to classify patients based on microbial composition. Results: Diversity Analysis Alpha-diversity showed no significant differences between the N and Y groups.Beta-diversity analysis revealed no distinct clustering between groups (P = 0.44), indicating shared microbial community structures. Taxonomic Composition The Y group (proximal extension) showed higher abundances of taxa such as Bartonella birtlesii, Lactobacillus salivarius, Klebsiella sp. M5al, and Proteus vulgaris. The N group (no proximal extension) was enriched with taxa like Lactococcus lactis and Pediococcus acidilactici. Machine Learning Classification The random forest model successfully classified patients into N and Y groups based on microbial features. Key predictive taxa aligned with findings from differential abundance analyses, reinforcing their potential as biomarkers. Conclusion This study highlights distinct microbiome signatures between UC patients with and without proximal extension during remission. While diversity metrics were similar, specific taxa showed significant differences in abundance. These findings may inform microbiome-based diagnostic and therapeutic approaches tailored to disease extent. Further research is required to validate these results and explore the underlying mechanisms driving microbiome-disease interactions.

P0061 Guselkumab induction therapy results in molecular resolution of inflammation in moderately to severely active Ulcerative Colitis: results from the Phase 3 QUASAR induction study

Abstract Background Guselkumab (GUS) is a selective dual-acting IL-23p19 subunit inhibitor that potently neutralises interleukin 23 (IL-23) and binds to CD64, a receptor on cells that produce IL-23.1 GUS is now approved in the United States for treatment of moderately to severely active ulcerative colitis (UC). GUS has demonstrated efficacy in UC based on the results of the QUASAR Phase 2/3 programme.2,3 Mechanistic data from the Phase 2b induction study demonstrated a restoration of intestinal homeostasis and initiation of epithelial repair.4 These findings were confirmed in the larger Phase 3 QUASAR induction study presented here. Methods At induction baseline, 701 patients with moderately to severely active UC were randomized 3:2 to receive GUS 200mg IV induction or placebo (PBO) and clinical efficacy was assessed at Week 12 (WK12). Molecular analysis of the randomised population was performed comparing induction WK12 to baseline (WK0). Transcriptional profiling of colonic biopsies from 593 patients was performed with bulk RNA sequencing and gene modules were evaluated for differential expression. Serum proteomic profiling of 648 patients was conducted using a targeted O-Link Inflammation panel and differential protein abundance was assessed. Results Significantly higher proportions of patients treated with GUS 200mg IV achieved clinical remission, endoscopic improvement, histologic-endoscopic mucosal improvement (HEMI), and endoscopic remission at WK12 compared with PBO. GUS IV induction demonstrated significant downregulation of inflammatory transcriptional modules in colon tissue at WK12, representing Th17, plasma cell, neutrophil and inflammatory fibroblast biology, and an upregulation of healthy epithelium-related gene modules including goblet cells and healthy epithelium (all false discovery rate [FDR]&amp;lt;0.05). This response correlated with changes observed in the GUS 200mg IV arm of the Phase 2b induction study (r=0.97, p&amp;lt;0.0001). GUS treated patients who achieved HEMI at WK12 demonstrated the most robust changes in gene module expression at WK12 (p&amp;lt;0.0001), nearing non-IBD control levels. Inflammatory serum proteins were reduced as early as WK4, and continued to decline through WK12 (IFNγ, IL-17A, OSM, and IL-6, FDR&amp;lt;0.05). Changes in serum proteins were consistent with those observed in the GUS 200mg arm of the Phase 2b induction study (r=0.96, p&amp;lt;0.0001) (Figure 1). Conclusion Mechanistic observations in response to GUS 200mg IV induction were validated in the Phase 3 QUASAR induction study. These data demonstrate GUS IV induction reduced inflammatory biology towards normal while also increasing the healthy epithelium in patients who achieved HEMI at WK12.

DOP069 Guselkumab maintenance therapy mediates further improvements in intestinal immune homeostasis and mucosal healing in patients with ulcerative colitis

Abstract Background Guselkumab (GUS) is a dual-acting IL-23p19 subunit inhibitor that potently neutralises interleukin 23 (IL-23) and binds to CD64, a receptor on cells that produce IL-23.1 The QUASAR Phase 2b/3 studies have demonstrated efficacy and safety in induction and maintenance phases.2,3 The cellular and molecular mechanism of action of GUS induction was also previously reported.4 Here, the molecular changes that occur with maintenance treatment are presented. Methods At maintenance baseline, clinical responders to GUS induction treatment (n=568) were randomized 1:1:1 to GUS SC 200mg q4w, GUS SC 100mg q8w, or placebo (PBO; GUS withdrawal). Molecular analysis of the randomised population was performed comparing maintenance baseline (M0) to Week 44 (M44). Transcriptional profiling of colonic biopsies from 396 patients was performed using RNA sequencing and gene modules were evaluated for differential expression. Serum proteins were evaluated from 430 patients using a targeted inflammation panel and differential protein abundance was assessed. Results Clinically, both GUS SC maintenance dose regimens were highly efficacious and achieved the primary endpoint of clinical remission and all major secondary endpoints at M44 compared with PBO.2 Molecular analysis demonstrated a further significant downregulation of key inflammatory gene modules from M0 to M44 (all false discovery rate [FDR]&amp;lt;0.05) from that previously observed during induction.4 Unique to maintenance, gene modules related to intestinal mesenchymal biology (pericytes, fibroblasts and endothelium) showed even greater changes in maintenance compared to induction. An upregulation of gene modules representing healthy epithelial biology (crypt, goblet cells, M-cells) was also observed at M44 (Figure 1). Importantly, patients who achieved clinical remission at M44 demonstrated the most significant changes and gene module expression levels at M44 approximated those observed in non-IBD healthy controls, consistent with the profile of healthy colonic tissue. Serum analysis showed continued reductions in inflammatory proteins (e.g. IL-17A, IL-8, FDR &amp;lt;0.05) and several chemokines from M0 to M44, including CCL11 that has been linked to mesenchymal biology. By M44, GUS withdrawal demonstrated a reversal in the anti-inflammatory effects achieved at the end of induction. Conclusion GUS maintenance therapy for UC mediated further improvements in the anti-inflammatory and pro-healing effects achieved during induction. Moreover, this work provides evidence supporting a role for mesenchymal biology in tissue remodeling during maintenance. Together, these data provide molecular evidence supporting the robust clinical benefit of GUS maintenance therapy.

OP18 Multi-analytical Approaches Reveal Robust Gut Microbial Biomarkers for Inflammatory Bowel Disease Diagnosis: A Large-scale Cohort Study

Abstract Background Inflammatory bowel disease (IBD), encompassing Crohn's disease (CD) and ulcerative colitis (UC), is strongly associated with gut microbiota dysbiosis. While numerous association studies have identified potential diagnostic gut microbial markers, their clinical utility remains limited due to substantial variability across studies and lack of robust validation. Furthermore, despite the availability of multiple analytical approaches for identifying microbial biomarkers, their relative effectiveness remains unclear, and definitive biomarkers for IBD diagnosis are still lacking. This study aims to identify robust gut microbial biomarkers for IBD diagnosis through multiple analytical approaches. Methods We analysed 3,762 participants, including healthy controls (HC, n = 2,467) and patients with IBD (n = 1,293), stratified into CD (n = 879) and UC (n = 414). Gut microbiota profiles were analysed from stool samples using 16S rRNA gene sequencing. Four analytical approaches were employed: (1) differential abundance analyses (DA: LEfSe, ANCOM-BC, and MaAsLin2), (2) supervised random forest machine learning (ML), (3) unsupervised network analysis (NW), and (4) literature-based curation (LC). Biomarker candidates generated by these methods were compared for diagnostic performance using an ensemble ML model. Results Diversity analysis revealed distinct gut microbial community structures among HC, UC, and CD groups (unweighted UniFrac distance, PERMANOVA, p &amp;lt; 0.001, Fig. 1A). Dysbiosis scores, calculated based on these structural differences, were significantly higher in IBD groups compared to HC (Fig. 1B). Each analytical approach identified distinct microbial biomarkers associated with IBD and its subtypes. Supervised ML produced the most effective biomarker sets, achieving the highest diagnostic performance for distinguishing IBD from HC (AUC = 0.971), surpassing LC (AUC = 0.938), DA (AUC = 0.928), and NW (AUC = 0.912), Fig. 2. ML biomarker sets also demonstrated superior accuracy in distinguishing CD from HC (AUC = 0.933) and UC from CD (AUC = 0.892). These results highlight the superiority of ML in selecting robust biomarkers for IBD diagnostics across multiple classification tasks. Conclusion This study identifies robust gut microbial biomarkers for IBD diagnosis through multiple analytical approaches. The biomarker panel demonstrates high diagnostic accuracy in distinguishing both IBD from healthy controls and CD from UC. External validation of these findings is currently ongoing in an independent cohort. These findings provide a foundation for developing reliable microbiome-based diagnostic tools for IBD, potentially enabling more precise disease diagnosis and improved patient care.

P1324 Longitudinal Changes in Gut Microbiota During the First Year following diagnosis of Inflammatory Bowel Disease – the IBSEN III study

Abstract Background Despite the well-established involvement of the gut microbiota in inflammatory bowel disease (IBD), little is known about how the gut microbiota changes over time or how it varies with clinical disease activity and faecal calprotectin. To address this gap, we utilized the population-based inception cohort IBSEN III. Methods Stool samples from IBD patients and symptomatic controls (SC) were collected at diagnosis and after 3, 6, and 12 months. Comprehensive data collection was performed at baseline and the 12-month follow-up, while faecal calprotectin (f-calprotectin) and patient-reported clinical disease activity data were also gathered at 3 and 6 months. Stool microbiota profiling was performed targeting the V3-V4 region of the 16S rRNA gene, and a consensus-based approach utilizing mixed models was employed for the microbiota analysis. Results We included 761 subjects (median age 37, 48 % female) with ulcerative colitis (UC) and 448 subjects (median age 33, 55% female) with Crohn’ s disease (CD) who contributed at least one faecal sample, and respectively 79 and 58 provided samples at all four time points. A smaller proportion of our IBD population donated treatment naïve faecal samples (11% UC, 26% CD). In the IBD population, the patient-reported disease activity decreased over time, as did F-calprotectin levels (mixed model p &amp;lt; 0.001, median CD from 241 to 128, UC from 188 to 77). We used different thresholds of F-calprotectin for defining remission (50,150 and 250) and observed significant within-diagnosis differences (microbial diversity and consensus-based differential abundance analysis) depending on F-calprotectin status. Comparing F-calprotectin-defined inactive IBD (50,150 and 250) to symptomatic controls, there were significant differences between microbiota profiles from UC remission, but few/no differences to CD microbiota. Distinct changes in the gut microbiota of IBD subjects were observed throughout the first year, such as increased alpha diversity (Shannon, mixed model p &amp;lt; 0.001) and significant taxonomic changes (consensus-based differential abundance analysis, figure). There was a significant overlap between microbial patterns associated with F-calprotectin and patient-reported disease activity score (Fisher Exact test p &amp;lt; 0.001), and the changes in these scores were reflected in the microbial changes over time (Fisher Exact test p &amp;lt; 0.05). Significant changes comparing microbiota profiles in treatment naïve to post-treatment samples were found, both among subjects with CD and UC (consensus-based differential abundance analysis). Conclusion The gut microbiota during the first year after IBD diagnosis showed changes that paralleled inflammation and clinical disease activity.

P0189 Microbial and Molecular Profiling of the appendix of pediatric patients with inflammatory bowel diseases

Abstract Background Inflammatory bowel diseases (IBD), including Crohn disease (CD) and ulcerative colitis (UC), are chronic inflammatory conditions influenced by genetic, environmental, and microbial factors.1,2 Emerging evidence suggests a role for the appendix in IBD with immune and microbe impacts on the colon. Peri-appendicular patch (PAP) inflammation is observed in some UC patients; appendectomy has shown protective effects, reducing relapse and colectomy rates in UC.3,4 However, the mechanisms underlying these associations remain unclear. This study aims to explore these mechanisms by characterizing microbial species, molecular pathways, and host-microbiota interactions in the appendix of IBD patients. Methods Mucus from the appendix and non-inflamed colon of 10 pediatric IBD and 5 non-IBD patients undergoing elective surgical resection was collected for DNA and whole-genome sequencing. RNA and DNA from appendix tissues were used for RNA-seq and 16S rRNA sequencing, respectively. Metagenomic analysis was performed across all platforms. Fluorescence in-situ hybridization (FISH) and immunofluorescence defined localization. Results Proteobacteria were significantly enriched in IBD (mean = 27.23%±32%) compared to non-IBD mucus samples (mean = 1.6%±0.23%, p = 0.0052), with reduced bacterial diversity in the appendix of IBD patients. Differential abundance analysis revealed site-specific changes in MetaCyc pathways, notably in the IBD-appendix; for example, ABH and Lewis epitopes biosynthesis pathways were highly enriched in this organ. 38 of 50 MetaCyc pathways were linked to specific species, with E. coli contributing to 32 pathways. Immune and inflammatory pathways were significantly upregulated in the IBD-appendix. Strong correlations were observed between host tissue and microbial pathways in IBD mucus; for instance, Chondroitin Sulfate and Dermatan Sulfate Biosynthesis bacterial pathways were positively correlated with the upregulated host pathway Chemokine Receptors Bind Chemokines (Rho = 0.8851 and 0.88549, respectively), reflecting host-bacteria interaction in the appendix. Bacteria were observed in the mucus layer of IBD-appendix. Conclusion The appendix in IBD exhibits unique molecular and microbial features, offering key insights into its role in IBD pathogenesis and potential therapeutic avenues, reinforcing the efficacy of interventions such as appendectomy in UC.

P0203 Unique faecal &amp; oral microbiota signatures in first degree relatives of inflammatory bowel disease patients

Abstract Background While the aetiology of IBD is unknown, a range of genetic and environmental risk factors have been described. First-degree relatives (FDRs; siblings, parents and children) of IBD patients share many of these factors. To better understand the interplay between environmental and genetic risk factors, we evaluated the gut microbial profiles of an FDR cohort, their IBD probands and healthy controls (HC). The aim was to identify whether FDRs of IBD patients have healthy or IBD-like microbial features. Methods All participants were recruited as part of the Australian IBD Microbiome (AIM) study. Participants were selected based on self-reported first-degree relative status (n=68) and, where possible, affected IBD relatives (n=24) were included for comparison. All participants were antibiotic free for 3-months prior to baseline sampling. Oral and faecal samples underwent 16S rRNA sequencing. The Microbiome Research Centre 16S analysis pipeline and R studio were used for statistical analysis and data visualisation. Results The FDR group was predominantly female (63%) with a mean age of 49.7 years and BMI of 25.5 kg/m2. The IBD cohort was significantly different in age to FDR (mean 36.7; p &amp;lt; 0.05) but not controls (mean 40.4 years) and BMI was comparable between groups. European Australians were the most represented ethnic group (47.6%) and 98.6% of participants were non-smokers. Oral microbiota profiles showed no significant difference in alpha diversity across FDR, IBD and HC groups. Differential abundance analysis of the oral microbiota revealed FDRs had increased abundance of Oribacterium, Granulicatella, Lachnoanaerobaculum and Rothia compared to HC, and increased levels of Capnocytophaga, Tannerella and Abiotrophia compared to the IBD group. In agreement with other studies, faecal microbial profiles in the IBD group had significantly reduced alpha diversity compared to both FDR and HC groups. All groups were compositionally different by Bray-Curtis beta dissimilarity analysis (p&amp;lt;0.018). FDRs had higher abundance of Akkermansia, Alistipes and Monoglobus compared to IBD and HC groups. FDRs and IBD shared similar abundance of Butyricicoccus which was lower than the HCs. Conclusion FDR oral microbiome signatures had greater variance from HC than IBD groups. Faecal microbial analysis showed distinct differences with enrichment of key beneficial genera in the FDR group. FDR profiles however still shared significant gut microbial features with the IBD group, remaining distinct from healthy controls. FDRs oral microbiome was higher in opportunistic pathogens and IBD-like whereas faecal composition was protective, rich in beneficial metabolite producing genera.

P1330 The gut microbiome at the onset of inflammatory bowel disease: A systematic review of the literature and unified bioinformatic synthesis of sequencing data from &amp;gt;1000 treatment naïve patients

Abstract Background There are few studies of the gut microbiome in new-onset IBD. We present a novel secondary bioinformatic re-analysis (BA) of sequence outputs mapped to latest microbial taxonomy derived from systematic review. Methods MEDLINE and Embase searches were performed for microbiome studies in pre-treatment IBD. Appraisal was completed with ROBINS-E. Available 16S rRNA sequence datasets were downloaded and missing datasets requested. Integrated datasets were run through a unified pipeline based in QIIME2 supplemented by phyloseq and DESeq2. Results From 12,264 studies, 10,804 abstracts and 217 full texts were screened. 31 studies were eligible; 18 met the requirements for BA. Most were low risk for bias, except uncontrolled confounding. Methodology varied extensively. Considering only amplicon data; samples originated from 1,743 unique individuals (including 678 Crohn’s disease (CD), 399 ulcerative colitis (UC), 123 ‘other’ IBD, 130 healthy, 405 symptomatic, and 8 familial controls) derived from 15 countries. DNA was extracted using 15 different kits, sequencing performed on 4 separate platforms targeting 10 different 16S rRNA hypervariable regions. There was a paucity of adult data, particularly mucosal biopsies. Bacterial alpha diversity was reduced: in faeces in paediatric UC vs symptomatic controls (SC), in adult CD and UC vs HC and in paediatric SC vs HC (Figure 1). In paediatric biopsies in CD vs SC, CD vs UC, SC vs UC (Figure 2). Beta-diversity BA by Bray-Curtis demonstrated clear distinctions between faecal and mucosal biopsy communities, least evident in UC. Faecal communities separated by geography, though less evidently in biopsies. Differential abundance analysis revealed enrichment of oral genera across sample types (Fusobacterium, Peptostreptococcus, Neisseria in CD; Haemophilus, Aggregatibacter, Peptostreptococcus, Porphyromonas, Neisseria, Gemella in UC). Short-chain fatty acid (SCFA) producers were diminished but less consistently across IBD phenotype and sample type. Conclusion This work demonstrates the utility of a combined systematic review/secondary data analysis approach to published microbiome datasets. Whilst synthesis remains challenging due to the methodological inconsistencies within these studies, this approach better accounts for these variations and presents a new way to consider this data. A reduction in bacterial diversity remains core to the IBD microbiome, though with more complexity than previously considered (SC&amp;lt;UC in paediatric biopsies). Microbial community structure changes by sample type and geography. Enrichment of oral bacteria is consistent across IBD subtypes and sample types suggesting their importance in the disease. A deficit in SCFA producers may also be important.

Comparative analysis of bacterial microbiota in Aedes aegypti (Diptera: Culicidae): insights from field and laboratory populations in Colombia.

Comparative studies of the microbiota in whole-body mosquitoes from natural populations and laboratory-reared specimens are scarce, particularly in tropical countries like Colombia, where understanding microbial patterns is critical for effective disease control and vector management. This study examines the bacterial microbiota of Aedes aegypti by comparing field-collected mosquitoes from 3 Colombian regions (Southern Amazon, Central Andean region, and Northern Caribbean coast) with laboratory strains (Rockefeller, Otanche, and Tolima). These regions are highly endemic for dengue and are associated with lineage 1 of Ae. aegypti, known for its elevated vector competence. Using next-generation sequencing of the 16S rRNA gene with Illumina technology, we found that field-collected mosquitoes exhibited significantly higher alpha and beta diversity compared to laboratory-reared specimens. Field mosquitoes were enriched with bacterial families such as Acetobacteraceae, Lactobacillaceae, and Bacillaceae, while laboratory mosquitoes showed a greater abundance of Enterobacteriaceae. Differential abundance analysis revealed that Acetobacter and Bacillus predominated in field mosquitoes, whereas Asaia, Cedacea, and Chryseobacterium were more common in laboratory specimens. Notably, Pseudomonas and Acinetobacter were consistently abundant across all samples. Our findings suggest that environmental factors, such as habitat and diet, significantly influence the bacterial composition and diversity of Ae. aegypti in Colombia. Future research should further explore how these factors, alongside genetic components, shape mosquito-microbiota interactions and their implications for disease transmission and vector competence.

Compositional data analysis enables statistical rigor in comparative glycomics

Comparative glycomics data are compositional data, where measured glycans are parts of a whole, indicated by relative abundances. Applying traditional statistical analyses to these data often results in misleading conclusions, such as spurious “decreases” of glycans when other structures increase in abundance, or high false-positive rates for differential abundance. Our work introduces a compositional data analysis framework, tailored to comparative glycomics, to account for these data dependencies. We employ center log-ratio and additive log-ratio transformations, augmented with a scale uncertainty/information model, to introduce a statistically robust and sensitive data analysis pipeline. Applied to comparative glycomics datasets, including known glycan concentrations in defined mixtures, this approach controls false-positive rates and results in reproducible biological findings. Additionally, we present specialized analysis modalities: alpha- and beta-diversity analyze glycan distributions within and between samples, while cross-class glycan correlations shed light on previously undetected interdependencies. These approaches reveal insights into glycome variations that are critical to understanding roles of glycans in health and disease.

MAPPING THE CEREBROSPINAL FLUID PROTEOME IN BIPOLAR DISORDER.

Bipolar disorder (BD) is a severe psychiatric condition with unclear etiology and no established biomarkers. Here, we aimed to characterize the cerebrospinal fluid (CSF) proteome in euthymic BD individuals to identify potential protein biomarkers. We employed nano-flow liquid chromatography coupled to high-resolution mass spectrometry to quantify over 2,000 CSF proteins in 374 individuals from two independent clinical cohorts (n=164+89 and 66+55 cases and controls, respectively). A subset of the cases was followed longitudinally and reexamined after a median of 6.5 years. Differential abundance analysis revealed 41 proteins with robust case-control association in both cohorts. These included lower levels of synaptic proteins (e.g., APP, CLSTN1, NPTX2, NRXN1), axon guidance and cell adhesion molecules (e.g., NEO1, NCAM1, SEMA7A), higher levels of blood-brain-barrier integrity proteins (e.g., VTN, SERPIN3), and complement components (e.g., C1RL, C3, C5). The findings were consistently driven by the BD type 1 subtype. Comparing BD type 1 with controls increased discoverability, revealing 86 replicated associations despite a loss of statistical power. Moreover, longitudinal analyses of co-expression modules revealed dynamic changes in the CSF proteome composition that correlated with clinical outcomes, including disease severity, future manic episodes, and symptom improvement. Finally, we conducted association analyses of CSF proteins with genetic risk loci for bipolar disorder and schizophrenia. This study represents the first large-scale untargeted profiling of the CSF proteome in BD, unveiling potential biomarkers and providing in vivo support for altered synaptic and brain connectivity processes, impaired neurovascular integrity, and complement activation in the pathology of BD.