Biology subjects

Peters, A.

Publications and source records attributed to Peters, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Pathogenicity of autoreactive TH17 cells is modulated by the TRPM7 kinase

The melastatin-like transient receptor potential channel, TRPM7, is crucial for signaling in leukocytes. It harbors a channel domain, permeable to divalent cations as well as a serine/threonine -kinase, phosphorylating inter alia SMAD2. TRPM7 kinase activity is essential for the differentiation of non-pathogenic T helper 17 (TH17) cells as well as for T cell colonization and alloreactivity in the gut. As pathogenic TH17 (pTH17) cells drive autoimmune diseases, we studied TRPM7 kinase involvement in pTH17 polarization and function as well as in the development of multiple sclerosis (MS), using human T cells and established murine experimental autoimmune encephalomyelitis (EAE) models. Our results reveal an elevated TRPM7 activity in T effector cells derived from the cerebrospinal fluid (CSF) of MS patients, in line with higher functional TRPM7 expression on human TH17 cells. Utilizing a mouse line with disrupted kinase activity (Trpm7R/R), we uncovered both impaired differentiation of pathogenic TH17 cells as well as a significantly milder course of TH17-mediated transfer EAE in Trpm7R/R mice compared to Trpm7+/+ controls. In the CNS of Trpm7R/R mice, the number of FOXP3+ T cells (Tregs) was increased, while fewer TH17 cells infiltrated the CNS due to a migration defect of transferred pTH17 cells in the Trpm7R/R hosts and a failure to reactivate in the intestine, due to reduced MHCII signaling. Thus, inactivation of TRPM7 kinase may represent a promising therapeutic strategy targeting both differentiation and reactivation of pTH17 cells while preserving Tregs function and thereby dampening CNS inflammation in MS.

immunology↗

bioRxiv2026

Exposure to childhood adversity and adult alcohol, nicotine, and illicit drug use in Germany: a cross-sectional analysis of the German National Cohort (NAKO)

Rationale: Exposure to adversity in childhood and adolescence (i.e., "early-life stress"; ELS) is a well-established risk factor for substance use. Objectives: The aim of this study was to investigate associations between ELS exposure and substance use across subtypes of ELS, different substance classes, and behavioral profiles of substance use. Methods: In this cross-sectional study, we examined associations between ELS exposure and substance use in a population-based sample of 172,173 adults aged 19-74 years from the German National Cohort (NAKO). ELS exposure was assessed using the Childhood Trauma Screener. Substance use included nicotine, alcohol, and illicit drug use. Associations were examined using regression models evaluating overall ELS exposure, cumulative trauma load, and ELS subtypes. Latent class analysis (LCA) was conducted to identify substance use profiles. Results: ELS exposure was associated with higher odds of smoking, greater smoking severity, heavier alcohol consumption among drinkers, and higher odds of lifetime illicit drug use. Overall, the strongest associations were observed for opioid and stimulant use. Dose-response analyses revealed higher risk with increasing numbers of ELS subtypes. Abuse-related subtypes, particularly exposure to physical and sexual abuse, consistently showed strongest independent associations across substances, whereas neglect exhibited weaker, more variable associations. LCA identified four substance use profiles, with ELS exposure predicting membership in more severe polysubstance classes. Conclusions: ELS emerged as a robust risk factor for adult substance use, underscoring the need for trauma-informed approaches in clinical practice, public health, and policy to mitigate the long-term consequences of early adversity.

neuroscience↗

bioRxiv2026

Intraindividual longitudinal changes of the proteome reveal dynamic markers of biological aging

Proteomic aging clocks have emerged as biomarkers of aging, but most rely on cross-sectional data. Here, we present a proteomic aging clock based on longitudinal measurements of liquid chromatography-mass spectrometry plasma proteomics at up to three time points in the population-based KORA cohort, comprising 9,105 samples from 4,100 individuals in the final dataset aged 25-88 years. The model predicts chronological age and yields a measure of proteomic age acceleration associated with lifestyle and clinical risk factors. Risk factor-stratified analyses reveal shared proteomic signatures among cardiometabolic exposures and distinct signatures for smoking and physical activity. Within individuals, dyslipidemia and impaired kidney function track transitions to increases in age acceleration, while higher age acceleration is associated with increased all-cause mortality. Mediation analysis suggests that risk factors are linked to mortality indirectly through age acceleration. Affected proteins and pathways highlight extracellular matrix remodeling, complement and coagulation pathways, and liver-derived plasma proteins as key contributors to aging. Mendelian randomization identifies proteins with evidence consistent with a causal role in aging-related traits. Together, these findings are consistent with biological aging being dynamically responsive to changes in modifiable risk factors.

bioinformatics↗

bioRxiv2026

Continent-wide calibration of camera-trap metrics reveals low population densities in the European wildcat

Effective conservation depends on demographic metrics that reliably reflect species status, particularly population abundance. For elusive species occurring at low densities, however, such metrics remain difficult to obtain. Spatial capture-recapture (SCR) models are the standardized approach for estimating density in marked populations, but their data requirements, especially the need for multiple spatial recaptures across individuals, often limit applicability in small or data-poor populations. This constraint has resulted in knowledge gaps for some of the most vulnerable species, undermining evidence-based conservation planning and management. Using camera-trap data and SCR-derived density estimates from data-rich populations, we evaluated alternative, less data-demanding metrics and tested the hypothesis: Space to Event (STE), Mean Local Abundance (MLA), and Relative Abundance Index (RAI) exhibit predictable relationships with SCR-derived density; if supported, these metrics can reliably estimate density in populations where SCR models cannot be implemented. We applied this framework to the European wildcat (Felis silvestris), an elusive small felid with highly fragmented populations across Europe, for which density estimates are largely lacking despite growing conservation concern. Across 21 study areas spanning most of the species range, our results indicate that European wildcats generally occur at lower densities than previously reported. SCR-derived estimates (n=10) averaged 10.32 {+/-} 11.56 inds/100km2, while STE enabled density estimation in five additional data-poor areas (mean 5.52 {+/-} 5.33 inds/100km2). STE showed a strong linear relationship with SCR-derived density (R2=0.98), supporting its use as a viable alternative when SCR is infeasible, although it tended to underestimate compared to SCR, especially at higher densities. In contrast, MLA and RAI showed weaker and non-linear relationships with SCR-derived density (R2=0.65), indicating substantially lower explanatory power and suggesting their estimates are more strongly influenced by confounding processes. By explicitly calibrating alternative metrics across a wide density gradient throughout most of the species distribution, this study provides a transferable methodological framework for estimating density in low-density wildlife populations and the first continent-wide, standardized density assessment of a carnivore species. From a management perspective, our findings identify populations that may be most vulnerable, particularly those with the lowest densities, and highlight the need to prioritize absolute abundance monitoring.

ecology↗

bioRxiv2026

The role of IgE patterns and their link to the gut microbiome in allergic sensitization

Allergic diseases are heterogeneous conditions shaped by immune pathways and environmental influences, including the gut microbiome. Using cross-sectional data from 508 adults in the KORA FF4 cohort (275 with IgE sensitization, 233 without), we provide a multimodal statistical analysis of deep IgE profiles and concomitant gut microbial amplicon sequencing variant (ASV) data. We identified three latent allergy components in the cohorts IgE profiles that reflects food, pollen, and house dust mite markers and enables interpretable stratification of the cohort. Contrary to prior studies, microbial diversity did not differ between sensitized and non-sensitized individuals across all cohort strata. Differential abundance analysis identified 61 ASVs, with enrichment in Bacteroidaceae, Oscillospiraceae, and Veillonellaceae families, and depletion in the Lachnospiraceae family. Microbial network analysis further identified altered family-level associations in pollen- and food-sensitized individuals. Taxon set enrichment highlighted folic acid- and vitamin A-producing taxa, with consistent signals from Prevotella copri (depleted) and Bacteroides massiliensis (enriched). Together, our analysis points toward specific microbial families and metabolic groups as correlates of IgE sensitization in an adult population. HIGHLIGHTSO_LIIgE sensitization clusters reflect allergen sources and cross-reactive proteins C_LIO_LIThree latent allergy components capture the IgE profile structure of the entire cohort C_LIO_LIDistinct IgE patterns are linked to changes in taxa compositions and associations C_LIO_LIFolic acid- and vitamin A-producing taxa are enriched in IgE-sensitized individuals C_LI GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=84 SRC="FIGDIR/small/714318v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@1d1c8fborg.highwire.dtl.DTLVardef@1e1fea7org.highwire.dtl.DTLVardef@1589fcorg.highwire.dtl.DTLVardef@160282_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2025

Stable coexistence of Citrobacter rodentium with a lytic bacteriophage during in vivo murine infection

Bacteriophages are ubiquitously present in bacterial communities, yet phage-bacteria interactions in complex environments like the gut remain poorly understood. While antibiotic resistance is driving a renewed interest in phage therapy, most studies have been conducted in in vitro systems, offering limited insight into the complexity of such dynamics in physiological contexts. Here, we use Citrobacter rodentium (CR), a natural mouse-restricted enteric pathogen and well-established model for human enteropathogenic and enterohaemorrhagic Escherichia coli (EPEC and EHEC) infections, to investigate phage-pathogen interactions in vivo. We isolate and characterise Eifel2, a novel lytic phage infecting CR, and generate anti-phage specific antibodies that enable the visualisation of phage infections in vitro. In a murine model of CR infection, oral administration of Eifel2 led to robust phage replication in the gut without reducing the bacterial burden or infection-associated inflammation, confirming the establishment of a stable coexistence in the gut. Despite the emergence of a sub-population of phage-resistant CR mutants in vivo, they did not undergo clonal expansion, indicating that additional selective pressures impaired their widespread dissemination in the gut. Together, our findings demonstrate that imaging approaches can capture key infection stages in vitro, while in vivo models are essential for capturing the complexity of phage-bacteria interactions. This work highlights the importance of studying phage therapy in host-pathogen contexts that include a normal microbiota and a suitable host environment, where dynamic co-existence rather than eradication may define therapeutic outcomes. ImportanceBacteriophages, or phages, are viruses which can either kill or persist inside bacteria. Current interests in phage biology are in part ignited by the fact that they could be used to treat infections caused by antibiotic-resistant bacteria. However, most of our understanding of phage-bacterial interactions comes from in vitro models and/or in vivo gut models relying on altering the endogenous microbiota. Here we report the finding of a novel phage, Eifel2, which specifically targets Citrobacter rodentium (CR), the mouse equivalent of human diarrhoeagenic E. coli pathogens. Despite effectively killing CR in vitro, CR and Eifel2 develop a coexistence relationship in mice with an intact microbiota. While CR phage-resistant mutants emerge, host and microbial factors constrain their expansion. This work highlights the importance of studying phage therapy in host-pathogen contexts that include the complete microbiota, where therapeutic outcomes may rely on dynamic co-existence and containment rather than eradication.

microbiology↗

bioRxiv2025

A statistical model for quantitative analysis of single-molecule footprinting data

The binding of sequence-specific TFs (TF) to genomic DNA is fundamental to gene regulation. Emerging single-molecule footprinting (SMF) technologies such as the NOMe-seq and Fiber-seq assays offer unique opportunities for acquiring quantitative information about binding states of TFs and nucleosomes at single-DNA-molecule resolution. Contrasting bulk epigenomic profiling methodologies, SMF enables better molecular characterization of inherently stochastic processes of protein-DNA interactions. Despite the many advantages that SMF technologies bring for studying mechanisms of gene regulation, rigorous statistical models for the analysis of datasets generated using these technologies are still missing. Here, we introduce a novel statistical framework designed for inference of footprint lengths and predictions of footprint positions for unbiased quantitative analysis and interpretation of SMF datasets. We carried out comprehensive computational simulations of SMF experiments and identified experimental parameters that are critical to footprint detection. Finally, we demonstrate the power of this statistical approach for the analysis of genome-wide and amplicon-based NOMe-seq datasets generated for mouse embryonic stem cells.

bioinformatics↗

bioRxiv2025

Theobromine is Associated with Slower Epigenetic Ageing

Theobromine, a commonly consumed dietary alkaloid derived from cocoa, has been linked to extended lifespan in model organisms and to health benefits in humans. We examined associations between circulating theobromine intake, measured using serum metabolomics, and blood-based epigenetic markers of biological ageing in two European human population-based cohorts. Serum theobromine levels were significantly associated with reduced epigenetic age acceleration, as measured by GrimAge (p<2e-7) and DNAmTL (p<0.001) in over 500 individuals from the TwinsUK cohort, and both signals replicated in 1,160 individuals from the KORA cohort (p = 7.2e-08 and p = 0.007, respectively). Sensitivity analyses including covariates of other cocoa and coffee metabolites suggest that the effect is specific to theobromine. Our findings indicate that the reported beneficial links between theobromine intake on health and ageing extend to the molecular epigenetic level in humans.

genetics↗

bioRxiv2024

Comparative genomics of the sexually transmitted parasite Trichomonas vaginalis reveals relaxed and convergent evolution and genes involved in spillover from birds to humans

Trichomonas vaginalis is the causative agent of the venereal disease trichomoniasis which infects men and women globally and is associated with serious outcomes during pregnancy and cancers of the human reproductive tract. Trichomonads parasitize a range of hosts in addition to humans including birds, livestock, and domesticated animals. Recent genetic analysis of trichomonads recovered from columbid birds has provided evidence that these parasite species undergo frequent host-switching, and that a current epoch spillover event from columbids likely gave rise to T. vaginalis in humans. We undertook a comparative evolutionary genomics study of seven trichomonad species, generating chromosome-scale reference genomes for T. vaginalis and its avian sister species Trichomonas stableri, and assemblies of five other species that infect birds and mammals. Human-infecting trichomonad lineages have undergone recent and convergent genome size expansions compared to their avian sister species, and the major contributor to their increased genome size is increased repeat expansions, especially multicopy gene families and transposable elements, with genetic drift likely a driver due to relaxed selection. Trichomonads have independently host-switched twice from birds to humans, and genes implicated in the transition to the human host include those associated with host tissue adherence and phagocytosis, extracellular vesicles, and CAZyme virulence factors.

microbiology↗

bioRxiv2024

Spatio-temporal interaction of immune and renal cells determines glomerular crescent formation in autoimmune kidney disease

Rapidly progressive glomerulonephritis (RPGN) is the most aggressive group of autoimmune kidney disease with the worst prognosis. Anti-neutrophil cytoplasmic antibody (ANCA) associated vasculitis, anti-glomerular basement membrane (anti-GBM) and lupus nephritis are the most common causes of RPGN and are characterized by the formation of glomerular crescents and infiltration of leukocytes that eventually lead to glomerulosclerosis and kidney failure. In this work, we used high-resolution spatial transcriptomics of 32 ANCA, 19 lupus nephritis, 6 anti-GBM, and 6 control patients to understand how intercellular signaling between immune and renal tissue cells leads to renal inflammation and glomerular injury. Using 3,218,210 immune and kidney cells, we observed that the biological pathways involved in the sequence of glomerular crescent formation are similar across the diseases. While innate immune cells infiltrated the glomerular compartment relatively early, later increases in adaptive immune cells were largely restricted to the periglomerular regions. These changes in immune cells temporally correlated with increases in glomerular parietal epithelial (PEC) and fibrotic mesangial cells, suggesting disease-relevant functional signaling between these immune and renal cells. Cell communication analysis revealed early disease PDGF signaling from epithelial and mesangial cells to PECs, causing their activation and proliferation. At later stages, TGF-{beta} signaling from macrophages, T cells, epithelial cells, and mesangial cells to PECs triggered the expression of extracellular matrix components resulting in glomerulosclerosis. Our results highlight a spatio-temporally conserved progression into glomerular crescents and sclerosis for ANCA, lupus nephritis, and anti-GBM disease, which is driven by consecutive PDGF and TGF-{beta} signaling to PECs.

immunology↗

bioRxiv2024

A CRISPRi Library Screen in Group B Streptococcus Identifies Surface Immunogenic Protein (Sip) as a Mediator of Multiple Host Interactions

Group B Streptococcus (GBS; Streptococcus agalactiae) is an important pathobiont capable of colonizing various host environments, contributing to severe perinatal infections. Surface proteins play critical roles in GBS-host interactions, yet comprehensive studies of these proteins functions have been limited by genetic manipulation challenges. This study leveraged a CRISPR interference (CRISPRi) library to target genes encoding surface-trafficked proteins in GBS, identifying their roles in modulating macrophage cytokine responses. Bioinformatic analysis of 654 GBS genomes revealed 66 conserved surface protein genes. Using a GBS strain expressing chromosomally integrated dCas9, we generated and validated CRISPRi strains targeting these genes. THP-1 macrophage-like cells were exposed to ethanol-killed GBS variants, and pro-inflammatory cytokines TNF- and IL-1{beta} were measured. Notably, knockdown of the sip gene, encoding the Surface Immunogenic Protein (Sip), significantly increased IL-1{beta} secretion, implicating Sip in caspase-1-dependent regulation. Further, {Delta}sip mutants demonstrated impaired biofilm formation, reduced adherence to human fetal membranes, and diminished uterine persistence in a mouse colonization model. These findings suggest Sip modulates GBS- host interactions critical for pathogenesis, underscoring its potential as a therapeutic target or vaccine component.

microbiology↗

bioRxiv2024

Prey attracting but not repelled by predators suggests an asymmetric investment in the encounter-avoid-escape sequence.

Understanding predator-prey interactions, particularly how species use space and time to influence encounter rates, is fundamental in community and behavioural ecology. However, for large, free-ranging animals, encounter rates are rarely quantified directly, because of logistical and methodological challenges associated with tracking both predators and prey simultaneously. Instead, studies commonly rely on proxies such as spatial or temporal overlap. While informative, these proxies provide only incomplete estimates of encounter rates because they typically consider only one dimension of the interaction process (spatial or temporal). Although camera traps cannot directly measure encounters among large free-roaming species, they offer the opportunity to quantify the proximal co-occurrence, i.e., the extent to which species tolerate or avoid one anothers proximity in space and time. We analysed data from a one-year study conducted across four German protected areas using 283 camera traps and applying recurrent event analysis to investigate interactions among three prey species, red deer (Cervus elaphus), roe deer (Capreolus capreolus), wild boar (Sus scrofa) and two large predators grey wolf (Canis lupus), and Eurasian lynx (Lynx lynx). Prey visitation rates were unaffected by predator presence, whereas wolves exhibited a strong attraction to prey, with visitation rates four to six times higher immediately after prey detections. The limited sample size prevented robust conclusions regarding Eurasian lynx responses. These findings point towards an asymmetry in the predation sequence (i.e., spatio-temporal proximity, encounter, ignorance or avoidance post-encounter, capture or escape from attack): Predators must succeed at every stage of the sequence to capture prey, while prey can avoid predation by disrupting the process at any single stage. Our results suggest that prey species do not necessarily reduce large-scale spatio-temporal proximity to predators and may instead rely on anti-predator responses occurring later in the predation sequence.

ecology↗

bioRxiv2024

Individual variation in red deer responsiveness towards human disturbance: A prospect for wildlife viewing in Europes national parks.

Animals adjust behavior to changes in perceived predation risk, even when risk is non-consumptive, as is the case for human recreation. However, individuals within populations can differ greatly in their plasticity towards perceived risk, especially when antipredator responses incur fitness costs via lost foraging opportunities. Therefore, risk-benefit trade-offs are usually made at the individual level. We test whether red deer (Cervus elaphus) inhabiting the Bavarian Forest National Park show individual variation in behavioral plasticity towards human disturbance. We measured human disturbance as the number of recreationists on the closest trail on a given day and used random regression to dissolve movement responses, measured as hourly step-length, of 63 GPS-collared red deer females to fine scale spatio-temporal variation in disturbance. We quantified behavioral state specific between-individual variation along the disturbance gradient. At the population level, red deer responded to recreational disturbance during the middle of the day only, and reduced movement in response to recreation. However, population patterns masked strong between-individual variation in plasticity to recreation activity during the morning, midday, and evening, such that some deer reacted with flight while others responded little. Behavioral responses were mediated by vegetation cover with stronger responses in more open areas. Flight responses are costly due to lost foraging opportunities. A shift in risk-benefit trade-offs when risk is non-lethal, as is the case for recreation in many national parks, may favor more human-tolerant individuals over time. Lay summaryWe assessed the individual response of red deer towards recreational activities in the Bavarian Forest National Park, using GPS-telemetry data and modelled daily numbers of tourists on trails. Red deer varied in their fear of humans, most red deer adjusted movement on days with many park visitors, but some individuals did not respond to human disturbance. Individual variation in movement increased with human disturbance. Foraging-risk trade-offs may promote behavioral variation of red deer and their tolerance of humans.

animal behavior and cognition↗

bioRxiv2024

CODI: Enhancing machine learning-based molecular profiling through contextual out-of-distribution integration

Molecular analytics increasingly utilize machine learning (ML) for predictive modeling based on data acquired through molecular profiling technologies. However, developing robust models that accurately capture physiological phenotypes is challenged by a multitude of factors. These include the dynamics inherent to biological systems, variability stemming from analytical procedures, and the resource-intensive nature of obtaining sufficiently representative datasets. Here, we propose and evaluate a new method: Contextual Out-of-Distribution Integration (CODI). Based on experimental observations, CODI generates synthetic data that integrate unrepresented sources of variation encountered in real-world applications into a given molecular fingerprint dataset. By augmenting a dataset with out-of-distribution variance, CODI enables an ML model to better generalize to samples beyond the initial training data. Using three independent longitudinal clinical studies and a case-control study, we demonstrate CODIs application to several classification scenarios involving vibrational spectroscopy of human blood. We showcase our approachs ability to enable personalized fingerprinting for multi-year longitudinal molecular monitoring and enhance the robustness of trained ML models for improved disease detection. Our comparative analyses revealed that incorporating CODI into the classification workflow consistently led to significantly improved classification accuracy while minimizing the requirement of collecting extensive experimental observations. SIGNIFICANCE STATEMENTAnalyzing molecular fingerprint data is challenging due to multiple sources of biological and analytical variability. This variability hinders the capacity to collect sufficiently large and representative datasets that encompass realistic data distributions. Consequently, the development of machine learning models that generalize to unseen, independently collected samples is often compromised. Here, we introduce CODI, a versatile framework that enhances traditional classifier training methodologies. CODI is a general framework that incorporates information about possible out-of-distribution variations into a given training dataset, augmenting it with simulated samples that better capture the true distribution of the data. This allows the classification to achieve improved predictive performance on samples beyond the original distribution of the training data.

bioinformatics↗

bioRxiv2024

The integrated stress response/eIF2α pathway controls cytokine production in tissue-resident memory CD4+ T cells

Tissue-resident memory T (Trm) cells are a specialized T cell population that resides in tissues and can play both a protective and pathogenic role. The mechanism that enables Trm cells to provide a rapid protective response while restricting their function in homeostasis remains unclear. Here, we show that human and mouse CD4+ Trm cells exist in a poised state, characterized by storage of proinflammatory type-1 and type-3 cytokine mRNAs without protein production. In steady-state conditions, cytokine mRNA translation in Trm cells is suppressed by the integrated stress response (ISR)/eIF2 pathway, whereas Trm-cell activation under inflammatory conditions results in eIF2 dephosphorylation, leading to derepression and rapid translation of the cytokine mRNAs stored in stress granules. Pharmacological inhibition of eIF2 dephosphorylation resulted in reduced cytokine production from Trm cells, and ameliorated autoimmune kidney disease in mice. Consistent with these results, the ISR pathway in Trm cells was downregulated in patients with immune-mediated diseases of the kidney and the intestine. Our results identify ISR/eIF2-mediated control of cytokine mRNA translation as an underlying mechanism that restricts Trm cell activity in homeostasis but also promotes rapid response upon local infection or autoimmune reaction.

immunology↗

bioRxiv2024

The Interpretable Multimodal Machine Learning (IMML) framework reveals pathological signatures of distal sensorimotor polyneuropathy

Distal sensorimotor polyneuropathy (DSPN) is a common neurological disorder in elderly adults and people with obesity, prediabetes and diabetes and is associated with high morbidity and premature mortality. DSPN is a multifactorial disease and not fully understood yet. Here, we developed the Interpretable Multimodal Machine Learning (IMML) framework for predicting DSPN prevalence and incidence based on sparse multimodal data. Exploiting IMMLs interpretability further empowered biomarker identification. We leveraged the population-based KORA F4/FF4 cohort including 1,091 participants and their deep multimodal characterisation, i.e. clinical data, genomics, methylomics, transcriptomics, proteomics, inflammatory proteins and metabolomics. Clinical data alone is sufficient to stratify individuals with and without DSPN (AUROC = 0.752), whilst predicting DSPN incidence 6.5{+/-}0.2 years later strongly benefits from clinical data complemented with two or more molecular modalities (improved {Delta}AUROC >0.1, achieved AUROC of 0.714). Important and interpretable features of incident DSPN prediction include up-regulation of proinflammatory cytokines, down-regulation of SUMOylation pathway and essential fatty acids, thus yielding novel insights in the disease pathophysiology. These may become biomarkers for incident DSPN, guide prevention strategies and serve as proof of concept for the utility of IMML in studying complex diseases.

bioinformatics↗

bioRxiv2023

Missing view completion for multi-timepoints omics data via representation disentanglement and temporal knowledge transfer

Longitudinal multi-view omics data offer unique insights into the temporal dynamics of individual-level physiology, which provides opportunities to advance personalized healthcare. However, the common occurrence of incomplete views makes extrapolation tasks difficult, and there is a lack of tailored methods for this critical issue. Here, we introduce LEOPARD, an innovative approach specifically designed to complete missing views in multi-timepoint omics data. By disentangling longitudinal omics data into content and temporal representations, LEOPARD transfers the temporal knowledge to the omics-specific content, thereby completing missing views. The effectiveness of LEOPARD is validated on three benchmark datasets constructed with data from the MGH COVID study and the KORA cohort, spanning periods from 3 days to 14 years. Compared to conventional imputation methods, such as missForest, PMM, GLMM, and cGAN, LEOPARD yields the most robust results across the benchmark datasets. LEOPARD-imputed data also achieve the highest agreement with observed data in our analyses for age-associated metabolites detection, estimated glomerular filtration rate-associated proteins identification, and chronic kidney disease prediction. Our work takes the first step toward a generalized treatment of missing views in longitudinal omics data, enabling comprehensive exploration of temporal dynamics and providing valuable insights into personalized healthcare.

bioinformatics↗

bioRxiv2023

T:B cell communication in ectopic lymphoid follicles in CNS autoimmunity

Meningeal ectopic lymphoid follicle-like structures (eLFs) have been described in multiple sclerosis (MS) and its animal model experimental autoimmune encephalomyelitis (EAE), but their role in CNS autoimmunity is unclear. To analyze the cellular phenotypes and interactions within these structures, we employed a Th17 adoptive transfer EAE model featuring formation of large, numerous eLFs. Single-cell transcriptomic analysis revealed that clusters of activated B cells and B1/Marginal Zone-like B cells are overrepresented in the CNS and identified B cells poised for undergoing antigen-driven germinal center (GC) reactions and clonal expansion in the CNS. Furthermore, CNS B cells showed enhanced capacity for antigen presentation and immunological synapse formation compared to peripheral B cells. To directly visualize Th17:B cell cooperation in eLFs, we labeled Th17 cells with a ratiometric calcium sensor, and tracked their interactions with tdTomato-labeled B cells in real-time. Thereby, we demonstrated for the first time that T and B cells form long-lasting antigen-specific contacts in meningeal eLFs that result in reactivation of autoreactive T cells. Consistent with these findings, autoreactive T cells depended on CNS B cells to maintain a pro-inflammatory cytokine profile in the CNS. Collectively, our study reveals that extensive T:B cell cooperation occurs in meningeal eLFs in our model promoting differentiation and clonal expansion of B cells, as well as reactivation of CNS T cells and thereby supporting smoldering inflammatory processes within the CNS compartment. Our results provide valuable insights into the function of eLFs and may provide a direction for future research in MS.

immunology↗