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PubMed2026

Longitudinal multiorgan transcriptomic atlas of salt-induced hypertension.

High dietary salt intake elevates blood pressure and drives multiorgan damage. However, the molecular programs underlying progressive organ injury remain poorly defined. Here, we present a longitudinal multiorgan transcriptomic atlas of salt-induced hypertensive injury. We profiled kidney cortex, kidney medulla, heart, and liver across 4 stages, spanning early hypertension to advanced pathology in Dahl salt-sensitive rats. We identified dynamic and tissue-specific molecular trajectories, including a shared early proliferative response that converges on proinflammatory and fibrotic remodeling. Notably, we uncovered compartment-specific renal responses, showing that the cortex and medulla, despite their proximity, follow distinct molecular trajectories during disease progression. We further identified 79 stage- and tissue-specific transcription factors that drive gene expression dynamics in salt-induced hypertensive injury. Integration with human genome-wide association studies revealed conserved pathways in endocrine signaling, ion transport, lipid metabolism, and detoxification, establishing cross-species relevance and highlighting mechanistic targets of clinical importance. Compound-transcriptome analysis revealed stage- and organ-specific therapeutic opportunities, prioritizing kinase and epigenetic modulators as candidates to rebalance maladaptive gene programs. Overall, this study provides a resource for understanding molecular mechanisms from early salt-induced hypertension to tissue-specific injury and underscores the need for precision interventions.

Animals↗

PubMed2026

Deciphering the prodrome of inflammatory bowel disease up to 10 years before disease onset by massively parallel serology.

BACKGROUND: Defining immune dysregulation during the asymptomatic prodrome of immune-mediated diseases offers opportunities for early disease detection and interception. In inflammatory bowel disease (IBD), prodromal immune changes remain poorly characterised. OBJECTIVE: To define preclinical immunological alterations by characterising longitudinal serum antibody repertoires using high-throughput phage-display immunoprecipitation sequencing (PhIP-Seq). DESIGN: We applied PhIP-Seq to profile antibody responses in 2000 longitudinal serum samples from 200 individuals who developed Crohn's disease (CD), 200 who developed ulcerative colitis (UC) and 100 matched healthy controls within the US military Proteomic Evaluation and Discovery in an IBD Cohort of Tri-service Subjects cohort, collected up to 10 years before diagnosis. Antibody repertoires were profiled against 357 000 microbial-associated, viral-associated, food-associated and immune-associated peptides. RESULTS: Antibody repertoire variability was increased up to ~4 years prediagnosis in pre-CD and pre-UC individuals. Differential analyses revealed elevated herpesvirus-directed responses (notably Epstein-Barr virus) and anti-flagellin antibodies up to 10 years prediagnosis in CD, particularly in individuals who later developed complicated or ileal disease. In contrast, responses to encapsulated bacteria (eg, Streptococcus pneumoniae, Haemophilus, Neisseria) progressively declined towards diagnosis. Pre-UC was characterised by combined antimicrobial, antiviral and autoantibody signatures, including antibodies against the MAP kinase-activating death domain protein. CONCLUSIONS: Large-scale serological profiling of archived prediagnostic samples identified disease-specific immune trajectories years before IBD onset, providing novel insights into disease pathogenesis in its prodromal phase.

ANTIGENS↗

PubMed2026

From genes to trajectories: mapping genetic influences on Huntington's disease progression.

MOTIVATION: There are many diseases with established genetic factors, such as Huntington's disease (HD), that are characterized by variable rates of progression. However, beyond the contribution of the known genetic factors - in this case the Huntingtin (HTT) gene - the impact of the full human genome on the natural progression of such diseases throughout a patient's life remains largely unknown. The increased availability of genome wide association (GWA) data in HD gene expansion carriers (HDGECs), combined with the clinical assessment scores on the same set of patients, has provided a perfect opportunity to assess the potentially broader genetic impact on the natural progression of HD. RESULTS: We present a genetics-driven, probabilistic disease progression model designed to identify and investigate the ways in which a range of genetic factors affect the natural progression of HD. When applied to a clinico-genomic HD dataset, our model identified several single nucleotide polymorphisms (SNPs) with previously unreported effects on disease progression that act at distinct stages and with varying magnitudes. This discovery may shed light on the potential mechanistic impact of previously unidentified genes on HD that may have implications for clinical management. As increasing amounts of GWA data become available more generally, we anticipate that this modeling framework will be broadly applicable to other diseases with strong genetic components. AVAILABILITY AND IMPLEMENTATION: The source code for IHDPM is available at https://github.com/BiomedSciAI/IHDPM.

Huntington Disease↗

PubMed2025

The cost and cost trajectory of genome sequencing and bioinformatics analysis for Indigenous children with suspected rare diseases.

PURPOSE: Indigenous peoples are underrepresented in reference genome libraries. Consequently, rare disease diagnosis may require bespoke bioinformatics analyses of genome sequences. Establishing diagnostic cost is crucial to support policy development for equitable diagnosis of rare diseases. We estimated the cost and cost trajectory of diagnostic genome sequencing and bioinformatics for Indigenous participants with suspected rare diseases. METHODS: We conducted a microcosting study of Indigenous children and their families receiving genome sequencing through Canada's Silent Genomes Project. Invoice data informed the costs of genome sequencing. We conducted a time-and-motion study for bioinformatics analyses, including labor, computing, and data storage costs. RESULTS: With standard bioinformatics, costs ranged from C$3645 (SD: 455) for singletons to C$7402 (SD: 566) for trios. With advanced, bespoke bioinformatics, costs ranged from C$5344 (SD: 634) for singletons to C$9760 (SD: 822) for trios. Genome sequencing was a primary cost driver; however, sequencing costs decreased by 61% over 4 years. Bioinformatics costs ranged from 21.3% to 58.3% of the total costs. The time required for bioinformatics ranged from 71 hours to 215 hours for standard and advanced analyses, respectively. CONCLUSION: Genome sequencing costs decreased over time. Bioinformatics is a significant cost driver, particularly for bespoke analyses arising from nonrepresentative reference libraries.

Humans↗

PubMed2026

Accurately Deciphering Tissue Heterogeneity From Spatial Multi-Modal and Multi-Omics With STransformer.

Advances in spatially resolved technologies enable the simultaneous acquisition of diverse data modalities within a tissue slice while preserving critical spatial context, which presents unprecedented opportunities to decipher intricate tissue heterogeneity. However, existing computational approaches lack the intrinsic flexibility to universally process both spatial multi-modal and multi-omics data. Here, we introduce STransformer, a unified deep learning framework designed to seamlessly accommodate a comprehensive landscape of spatial data. By simultaneously capturing short-range cellular interactions and tissue-wide semantic patterns, it extracts robust representations to accurately dissect complex tissue heterogeneity. Systematic evaluations across diverse species, tissue types, and data modalities highlight its profound versatility. For spatial multi-modal data, STransformer delineates intricate anatomical structures in the human cortex, uncovers pathological mechanisms in Alzheimer's disease, and characterizes dynamic spatiotemporal developmental trajectories during chicken cardiogenesis. Scaling to spatial multi-omics data, STransformer synergizes spatial transcriptomic and proteomic profiles to decipher intricate immune microenvironments within the human tonsil, and jointly analyzes spatial epigenomic and transcriptomic data to infer regulatory mechanisms in the mouse embryonic brain. Consequently, STransformer serves as a highly versatile and robust analytical framework for advancing our understanding of tissue heterogeneity and disease pathogenesis.

Multiomics↗

PubMed2026

TACR3 variant confers resilience to aging and Alzheimer's disease.

BACKGROUND: While genetic factors strongly influence brain aging trajectories, variants conferring cognitive resilience remain poorly characterized. The neurokinin-3 receptor (NK3-R), encoded by Tachykinin Receptor 3 (TACR3), modulates cholinergic signaling in memory circuits vulnerable to aging. Previous studies linked the non-WT expression of the TACR3 variant rs2765 with cognitive decline and reduced volume of the hippocampus and basal forebrain, but systematic replication and mechanistic validation were lacking. METHODS: We investigated rs2765 in the preregistered AgeGain cohort of cognitively healthy older adults (n=188) with independent validation in the ADNI cohort (n=809) which includes persons with and without Alzheimer's Disease (AD) that show healthy cognition, mild cognitive impairment or dementia. Analyses integrated structural neuroimaging, longitudinal cognitive assessments, epigenetic aging (PhenoAge), genome-wide methylation profiling, and mechanistic validation through luciferase assays and cross-species protein expression studies. RESULTS: The infrequent protective rs2765 WT variant, found in 12.8% of Europeans, conferred 49% slower cognitive decline (p = 0.002) for amyloid-positive individuals of the ADNI cohort and 3.7 years younger epigenetic age (p = 0.013, 95% CI: 0.79-6.67 years) in the cognitively healthy AgeGain cohort. WT carriers showed larger hippocampal and basal forebrain volumes across cohorts, with Allen Brain Atlas integration revealing these outcomes to occur exclusively in regions where TACR3 expression positively correlated with gray matter volume. Mechanistically, the non-WT variant ameliorated RBMX-mediated post-transcriptional regulation, reducing NK3-R protein expression by 25-40% in vitro and ex vivo murine brain slice models. Senescence-accelerated mice exhibited reduced endogenous NK3-R expression, phenocopying the predicted functional consequences of the variant. In AgeGain participants, genome-wide methylation profiling identified 2,313 differentially methylated CpGs affecting 228 pathways spanning glutamatergic signaling, acetylcholine receptor pathways, chromatin remodeling, and angiogenesis, suggesting coordinated molecular reprogramming from synaptic function to systemic aging. CONCLUSIONS: rs2765 WT confers resilience to age- and AD-related cognitive decline through RBMX-dependent regulation of NK3-R expression, with effects of remarkable size cascading from memory to systemic aging. rs2765 genotyping could stratify individuals for NK3-R modulator therapy (e.g., fezolinetant or senktides) and identify those maintaining function despite pathological burden, complementing APOE-based risk assessment in precision geromedicine.

Journal Article↗

PubMed2026

Modelling time-varying genetic effects on binary disease risk via functional Mendelian randomization.

MOTIVATION: Genome-wide association studies have identified thousands of genetic variants associated with complex traits, establishing Mendelian randomization (MR) as a powerful framework for causal inference using variants as natural experiments. However, existing MR methods treat causal effects as static, relying on cross-sectional exposure measurements and ignoring how genetic predispositions to disease operate dynamically across the life course. Recovering age-specific causal effect functions from longitudinal data requires combining functional data representations of exposure trajectories with instrumental variable estimation strategies suitable for binary disease endpoints, a methodological gap that has remained unaddressed. RESULTS: We develop a functional MR framework for binary outcomes that integrates functional principal component analysis with two-stage residual inclusion (2SRI), ensuring consistent estimation under the nonlinear logistic link function that renders standard instrumental variable estimators inconsistent. Simulations across different causal effect trajectory shapes, varying measurement densities, and varying instrument strengths demonstrate accurate recovery of time-varying genetically predicted effects with minimal bias. Applied to UK Biobank data, the framework identifies an age-specific causal effect of genetically predicted body mass index on type 2 diabetes risk concentrated in early mid-adulthood and progressively attenuating thereafter. Concordance between the proposed 2SRI estimator applied to type 2 diabetes and the established continuous-outcome functional MR estimator applied to the paired glycated haemoglobin marker in the same cohort provides indirect empirical support for the validity of the proposed approach. AVAILABILITY AND IMPLEMENTATION: The method is implemented in the R package mvfmr, with a full tutorial vignette.

Mendelian Randomization Analysis↗

PubMed2026

Cumulative microscopy reveals cellular states in fibroblasts from patients with genetic disorders.

Analysis of cellular states and signaling trajectories can provide insights into causes of disease. We developed cumulative microscopy, a method to perform cyclical imaging without elution or quenching steps. Cumulative microscopy computationally extracts individual signals from accumulating fluorescence during sequential imaging. We use cumulative microscopy to quantitatively assess cell cycle and stress markers in individual primary fibroblasts from patients with rare genetic proliferative disorders with increased cancer risk. Neural network-based analysis of cumulative microscopy data suggests that cells from patients with Cartilage-hair hypoplasia (CHH), but not Mulibrey Nanism (MUL), show replication stress. We analyze cell states and cell trajectories and find that a subset of cells from patients with CHH show spontaneous replication stress, followed by cell cycle exit in both G1 and G2 phases. We note that replication stress potentially could underlie both proliferative defects and increased cancer risk in CHH patients and conclude that cumulative microscopy is an efficient, quantitative, and generalizable approach to multiplex microscopy.

Humans↗

PubMed2026

Blood Metabolomic Signatures of 1-Hour Glucose Predict Cardiometabolic Risk.

BACKGROUND: Elevated 1-hour glucose levels during an oral glucose tolerance test strongly predict type 2 diabetes (T2D) and cardiovascular disease. We investigated whether the fasting blood metabolome predicting 1-hour glucose could be a target for improving β-cell function, long-term glycemic trajectories, and reducing the risks of T2D and coronary heart disease. We also investigated whether plasma microRNAs derived from key metabolic organs regulate changes in a metabolomic risk score (MRS) for predicting 1-hour glucose. METHODS: Untargeted blood metabolomics and a frequently sampled 75-g oral glucose tolerance test were performed in participants from the OmniCarb trial (n=162). In an independent weight-loss dietary intervention trial (POUNDS Lost [Preventing Overweight Using Novel Dietary Strategies]), temporal changes in MRS and plasma microRNAs measured by genome-wide sequencing were analyzed. In addition, associations of MRS at baseline and its 10-year changes with long-term risk of incident T2D and coronary heart disease were prospectively investigated in the NHS (Nurses' Health Study). RESULTS: We created a fasting blood MRS for predicting 1-hour glucose (Pearson r=0.8) and found significant associations with half-day (diurnal) postprandial glucose excursions and insulin secretion after 5-week controlled feeding interventions varying in carbohydrate amount and glycemic index. In the POUNDS Lost trial, diet-induced changes in MRSs were related to 2-year trajectories of glucose metabolism; circulating microRNAs regulating cardiometabolic abnormalities were pivotal factors influencing these changes. In the NHS, women in the top 20% of MRS had a multivariate-adjusted relative risk of 3.80 (95% CI, 2.22-6.51) for T2D and 1.48 (95% CI, 1.04-2.12) for coronary heart disease compared with those in the lowest 20%. In addition, 10-year increases in plasma metabolites related to 1-hour glucose were linearly associated with a higher risk of T2D. CONCLUSIONS: Our findings indicate that fasting blood metabolomic signatures predicting elevated 1-hour glucose reflect disease pathophysiology and could be targets for preventing T2D and coronary heart disease.

blood glucose↗

PubMed2025

Multi-omic underpinnings of heterogeneous aging across multiple organ systems.

Aging is the main determinant of chronic diseases and mortality, yet organ-specific aging trajectories vary, and the molecular basis underlying this heterogeneity remains unclear. To elucidate this, we integrated genomic, epigenomic, transcriptomic, proteomic, and metabolomic data, employing post-genome-wide association study methodologies to systematically investigate the molecular mechanisms of nine organ-specific aging clocks and four blood-based epigenetic clocks. We uncovered genetic correlations and specific phenotypic clusters among these aging-related traits, identified prioritized genetic drug targets for heterogeneous aging, and elucidated downstream proteomic and metabolomic effects mediated by heterogeneous aging. We constructed a cross-layer molecular interaction network of heterogeneous aging across multiple organ systems and characterized detectable biomarkers of this heterogeneity. Integrating these findings, we developed an R/Shiny-based framework that provides a comprehensive multi-omic molecular landscape of heterogeneous aging, thereby advancing the understanding of aging heterogeneity and informing precision medicine strategies to delay organ-specific aging and prevent or treat its associated chronic diseases.

Aging↗

PubMed2026

Single-cell analysis of the human retina reveals stage-linked microglial states and neural-immune circuit rewiring in diabetic retinopathy.

Diabetic retinopathy (DR) is a major cause of vision loss worldwide. Here, we conduct single-cell RNA sequencing of twenty human retina samples (from living and post-mortem donors) across non-diabetic, diabetic, and DR states to create a comprehensive transcriptomic atlas. We identify two stable microglial populations-homeostatic and inflammatory-that exist along a functional continuum, plus a neutrophil cluster within C1QA+ myeloid cells with dynamic transitions occurring throughout disease progression. Module-level analysis reveals divergent transcriptional trajectories: homeostatic microglia maintain energetic programs while selectively upregulating stress elements, whereas inflammatory microglia layer additional pro-inflammatory programs onto preserved biosynthetic foundations. Eleven co-expression modules organize into two major axes: an inflammatory-stress axis, and a regulatory/metabolic-motility axis, with a stable translation module persisting across disease stages. Cell communication analysis further highlights sophisticated neural-immune interactions, particularly between photoreceptors and microglia. Our findings provide insights into the complex cellular dynamics of DR progression and suggest potential therapeutic targets for early intervention.

Humans↗

PubMed2025

An integrative network approach for longitudinal stratification in Parkinson's disease.

Parkinson's disease (PD) is a neurodegenerative disorder characterized by motor symptoms resulting from the loss of dopamine-producing neurons in the brain. Currently, there is no cure for the disease which is in part due to the heterogeneity in patient symptoms, trajectories and manifestations. There is a known genetic component of PD and genomic datasets have helped to uncover some aspects of the disease. Understanding the longitudinal variability of PD is essential as it has been theorised that there are different triggers and underlying disease mechanisms at different points during disease progression. In this paper, we perform longitudinal and cross-sectional experiments to identify which data modalities or combinations of modalities are informative at different time points. We use clinical, genomic, and proteomic data from the Parkinson's Progression Markers Initiative. We validate the importance of flexible data integration by highlighting the varying combinations of data modalities for optimal stratification at different disease stages in idiopathic PD. We show there is a shared signal in the DNAm signatures of participants with a mutation in a causal gene of PD and participants with idiopathic PD. We also show that integration of SNPs and DNAm data modalities has potential for use as an early diagnostic tool for individuals with a genetic cause of PD.

Parkinson Disease↗

PubMed2026

Adverse pregnancy outcomes and long-term cardiovascular disease risk.

Pregnancy provides a unique physiological stress test for the cardiovascular system, during which, adverse pregnancy outcomes (APOs) can unmask latent susceptibility to future disease. Common complications, including hypertensive disorders of pregnancy (HDP), gestational diabetes, and preterm birth (delivery before 37 weeks' gestation), identify women at substantially higher long-term risk of cardiovascular morbidity and mortality compared with women without a history of APOs. These excess risks likely reflect the combined effects of pre-existing cardiometabolic and genetic susceptibility, as well as the haemodynamic and metabolic stressors of pregnancy, heralding accelerated risk factor trajectories, relative impairment in endothelial and microvascular function, and early disease onset. This final Review in the Series extends the focus from cardiovascular disease during pregnancy and HDP to the long-term cardiovascular implications of APOs after delivery. We synthesise epidemiological data quantifying cardiovascular risk across major APO phenotypes and emerging evidence linking maternal APO history with cardiometabolic risk trajectories in offspring. We also delineate putative mechanistic pathways and summarise guidelines and consensus-informed recommendations for short-term and long-term follow-up after APOs. Finally, we propose practical approaches for integrating APO history into cardiovascular disease risk assessment and guideline-directed prevention across the female life course. We highlight key knowledge gaps, including uncertainty about optimal follow-up models, the limitations of current risk-stratification tools, and the absence of APO-specific prevention trials. We also outline priorities for mechanistic and implementation research. Positioning APOs as early, sex-specific indicators of cardiovascular risk offers a key window of opportunity to shift prevention upstream and improve cardiovascular health outcomes for women.

Humans↗

PubMed2026

Subjective cognition trajectories, Alzheimer biomarkers, and incident mild cognitive impairment.

BACKGROUND: Subjective cognitive decline is common in older adults and may represent an early clinical signal along the Alzheimer's disease continuum. The clinical relevance of longitudinal changes in subjective cognitive decline remains unclear. OBJECTIVES: To determine whether trajectories of self- or study partner-reported cognitive decline predict progression to mild cognitive impairment and reflect Alzheimer's disease-specific biological patterns. DESIGN, SETTING, PARTICIPANTS: Data were pooled from two observational cohorts. Cognitively unimpaired participants with baseline amyloid status, repeated assessments of subjective cognitive decline, and clinical follow-up were included. The study included 770 participants with a median follow-up of 5.0 years (interquartile range 4.0-7.0). MEASUREMENTS: Subjective cognitive decline was assessed using the Everyday Cognition questionnaire completed by participants and study partners. Linear mixed-effects models examined associations with amyloid status and progression to mild cognitive impairment. Cox proportional hazards models tested whether one-year changes predicted progression. RESULTS: Amyloid-positive participants and those who progressed to mild cognitive impairment showed steeper increases in self- and study partner-reported cognitive difficulties over time. Among amyloid-positive participants, only increases in study partner-report differentiated progressors from non-progressors. One-year increases in study partner-report predicted a higher risk of mild cognitive impairment compared with unchanged scores (hazard ratio 3.24; 95% confidence interval 1.73-6.07]), with effects confined to amyloid-positive participants. CONCLUSIONS: Short-term increases in study partner-reported cognitive difficulties identify amyloid-positive cognitively unimpaired older adults at increased risk of near-term progression to mild cognitive impairment. Longitudinal monitoring using study partner reports may provide a low-burden and clinically relevant approach for early risk stratification and surveillance in aging populations.

Humans↗

PubMed2026

Global disparities in COVID-19 vaccine coverage associated with trajectories of SARS-CoV-2 adaptation.

BACKGROUND: Vaccination serves as an effective intervention for health promotion and disease prevention across the socioecological systems and has played an important role during the COVID-19 pandemic. However, global disparities in vaccine coverage have increased uncertainty about the trajectories of viral adaptation, and the potential interplay between SARS-CoV-2 adaptation and vaccine rollout warrants further quantification. METHODS: Using over 13 million SARS-CoV-2 genomes across 86 countries from March 2020 to September 2022, we analyzed nonlinear associations between SARS-CoV-2 adaptation and vaccination coverage, considering public health and social measures, international travel, and infection dynamics, before and after the emergence of Omicron. Additionally, we examined the relationship between SARS-CoV-2 adaptation and COVID-19 mortality. RESULTS: During the pre-Omicron period, we found positive associations between nonsynonymous to synonymous divergence (dN/dS) ratios in the S1 subunit and medium levels of adjusted vaccine coverage (effect size: 0.96 [95% CI 0.47, 1.45]), while the association became insignificant at high levels (effect size: -1.89 [95% CI -4.20, 0.43]). However, no significant associations were found when Omicron dominated, possibly due to the immune escape ability of Omicron variants and the complex immune landscape shaped by mass hybrid immunity. Moreover, we observed evidence of dynamic interdependence and positive correlations between COVID-19 mortality and SARS-CoV-2 adaptation, with COVID-19 mortality interpreted as a proxy for uncontrolled viral spread. CONCLUSIONS: Our findings suggest a complex nonlinear relationship between vaccine-induced immunity and SARS-CoV-2 adaptation, with high vaccine coverage potentially linked to lower positive selection. We also observed directional coupling between COVID-19 mortality and SARS-CoV-2 adaptation. This may have implications for fair and fast vaccination in pandemic preparedness and response. CLINICAL TRIAL NUMBER: Not applicable.

Humans↗

PubMed2026

Parallel evolutionary trajectories rewire enteropathogenic Escherichia coli adhesion to restore host attachment.

Enteropathogenic Escherichia coli (EPEC) causes disease in children, presenting as chronic diarrhea that can impair physical and cognitive development. The attachment of typical EPEC (tEPEC) to the gut epithelium via bundle-forming pili (BFP) is a key factor in its virulence. Yet, infections by atypical EPEC (aEPEC), which lack BFP, have become increasingly common. To investigate how aEPEC recover host-attachment in the absence of BFP, we performed experimental evolution using a non-adherent E. coli, constructed to mimic the ancestor of aEPEC, and selected adherent progeny. Highly adherent variants evolved through phase-variable activation of type I fimbriae (T1F), followed by two alternative trajectories: bacterial filamentation, which increases T1F avidity, or point mutations in the T1F adhesin FimH that enhance ligand affinity. Extending our analysis to the genomes of 327 aEPEC strains isolated from infected patients revealed that similar FimH mutations are common. We further demonstrated experimentally that these naturally occurring variants often increase epithelial-attachment. Our findings implicate T1F in aEPEC pathogenesis and suggest it may be clinically relevant for anti-adhesion therapy. More broadly, these results indicate that impaired host-attachment can be rapidly compensated by upregulating and optimizing an alternative adhesin, and that combining experimental evolution with comparative genomics can reveal evolutionary trajectories occurring in nature.

Bacterial Adhesion↗

PubMed2026

Multimodal computational framework resolves B cell maturation in autoimmunity and ageing.

Identification of the origin of pathogenic immune cells is crucial for therapeutic interventions and diagnosis but pseudotime methods struggle to trace immune cells accurately. Current trajectory inference methods for B cell development and response in health and disease either ignore or underutilize antigen receptor sequence information, limiting their ability to resolve developmental pathways, particularly for pathogenic populations. Widely used methods such as Monocle 3 reconstruct developmental paths from transcriptomic similarity alone, discarding the features from immune receptors. Dandelion has combined the immune receptor features with transcriptomics but it struggles to simulate the trajectory path of B cells. Here we present ClonoTrace, a computational framework that integrates BCR sequence features with transcriptomic trajectory inference through gated fusion of multimodal embeddings. In fetal B cell development and germinal centre development, ClonoTrace demonstrates closer concordance with the canonical reference ordering than Monocle 3 and Dandelion. Applied to systemic lupus erythematosus, ClonoTrace indicates a memory B cell extrafollicular maturation route alongside the naïve B cell route, accompanied by induction of ZEB2 with a concomitant decline of BACH2 along the trajectory, as a candidate alternative route to pathogenic double negative 2 B cells (DN2) in systemic lupus erythematosus (SLE) patients. In healthy ageing, ClonoTrace resolved three candidate age-related B cell maturation routes, from naïve, IgM+ memory and switched-memory B cells, each passing through a DN2-associated transcriptional state that is ordered before age-associated B cells along the inferred trajectory. ClonoTrace's fate probability algorithm indicated that IgM+ memory B cell to ABC transition as the leading candidate age-associated transition, which may be distinct from SLE DN2 maturation. ClonoTrace provides a generalizable framework for receptor-informed trajectory inference, describing candidate developmental routes of pathogenic B cell populations in autoimmunity and ageing.

Humans↗

PubMed2026

Development and external validation of an explainable machine learning model for predicting chronic kidney disease progression in the Korean population.

BACKGROUND: Current risk stratification models, such as the Kidney Failure Risk Equation (KFRE), exhibit variable performance across ethnic groups and fail to capture dynamic clinical trajectories. This study aimed to develop and validate a Korean-specific machine learning (ML) model for predicting chronic kidney disease (CKD) progression using an ensemble approach. METHODS: We used electronic health records from Seoul National University Hospital for model development (n = 28,209) and the Korean Genome and Epidemiology Study (KoGES) CKD cohort for external validation (n = 3,960). The primary outcome was a composite of ≥40% decline in estimated glomerular filtration rate (eGFR) or progression to end-stage renal disease within 2 years. A soft-voting ensemble of four ML algorithms (XGBoost, LightGBM, CatBoost, and Random Forest) was developed. RESULTS: The ensemble model demonstrated robust discrimination in internal validation (area under the receiver operating characteristic curve [AUROC], 0.939; 95% confidence interval [CI], 0.934-0.944), significantly exceeding the KFRE (AUROC, 0.879-0.884). External validation in the KoGES cohort showed comparable discrimination (AUROC, 0.859; 95% CI, 0.798-0.914) versus KFRE (four-variable AUROC, 0.882; 95% CI, 0.818-0.935). Shapley Additive exPlanations (SHAP) analysis identified baseline eGFR, serum creatinine, eGFR slope, albumin, and hemoglobin as key prognostic features, supporting a complementary framework using KFRE for community screening and the ML model for hospital-based risk stratification. CONCLUSION: The ensemble ML model accurately predicts short-term CKD progression in Korean patients. By incorporating longitudinal features and ensemble learning, it provides a precise alternative to Western-derived equations, particularly in tertiary care settings.

Chronic kidney failure↗