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PubMed2026

Circulating tumor cells identify a disseminated genomic high-risk phenotype within IMS-IMWG 2025 staging in newly diagnosed multiple myeloma.

The 2025 IMS-IMWG consensus genomic staging (CGS) system has improved genomic risk stratification in newly diagnosed multiple myeloma (NDMM), yet does not capture whether high-risk clones have acquired a disseminated phenotype. We investigated whether circulating tumor cells (CTC) refine CGS and enable longitudinal residual disease monitoring. We retrospectively analyzed 631 MM patients from the NICHE cohort (NCT04645199) who underwent CTC assessment across disease phases. Among 410 patients assessed at diagnosis, CTC were detectable in 63.9% and correlated with both bone marrow plasma cell infiltration and accumulation of high-risk cytogenetic abnormalities. In 359 NDMM patients with adequate follow-up, a cohort-derived CTC threshold of 0.38% independently predicted inferior progression-free survival (PFS) after multivariable adjustment. Importantly, CTC refined prognostic stratification specifically within the CGS high-risk subgroup. Patients with CGS high-risk/CTC-high disease had the shortest PFS, thereby defining a disseminated genomic high-risk phenotype comprising 12.4% (39/314) of evaluable NDMM patients. In follow-up cohorts, detectable CTC were associated with inferior outcomes in 127 patients assessed during non-progressive disease states, whereas combined CTC and bone marrow minimal residual disease assessment stratified outcomes in 120 patients with paired measurements. Overall, CTC-integrated CGS supports minimally invasive baseline risk stratification and longitudinal disease monitoring.

Journal Article↗
PubMed2026

Systemic Comorbidities of Keloid and Hypertrophic Scars: A Phenome-Wide Association Study in a Multiethnic U.S. Pediatric Cohort.

BACKGROUND: Excessive scarring (ES), including keloids and hypertrophic scars, impairs function, appearance, and quality of life in children. Its pediatric comorbidity spectrum is not well defined, limiting anticipatory guidance and multidisciplinary care. This research aims to investigate comorbidities of ES in a diverse pediatric cohort using a phenome-wide association study (PheWAS). METHODS: This population-based study leveraged longitudinal electronic health record (EHR) data from participants enrolled in the Children's Hospital of Philadelphia (CHOP) from 2006. Diagnosis codes (International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] and Tenth Revision [ICD-10-CM]) were mapped to 3109 phenotype codes (PheCodes). PheWAS analyses were conducted using logistic regression, with Bonferroni correction applied to account for multiple testing. RESULTS: Among 86,092 pediatric participants, 662 (0.77%) were identified with ES; the remaining served as controls. Multivariable PheWAS screening identified 154 significant associations across 16 disease categories, of which 105 were not reported previously to our knowledge. Dermatologic phenotypes (n = 28; 18%) were most enriched, including acne and other follicular disorders, eczema, pigmentary changes, papulosquamous and granulomatous disorders, and cutaneous infections. Respiratory phenotypes (n = 21; 14%) included respiratory failure, pneumonia, asthma, allergic rhinitis, pharyngitis, and tonsillar hypertrophy. Sense organ disorders (n = 19; 12%) comprised conjunctivitis, refractive errors, otitis, and hearing impairment. Infection-related phenotypes (n = 14; 9%) highlighted susceptibility to viral (influenza, human papillomavirus [HPV], molluscum contagiosum), fungal (candidiasis, dermatophytosis), and bacterial infections. CONCLUSIONS: These findings suggest that ES in children indicates not only localized wound-healing impairment, but also systemic immune, developmental, and proliferative dysregulations, emphasizing the need for genetic and mechanistic studies to clarify causal pathways and multidisciplinary surveillance beyond dermatologic care.

Humans↗
PubMed2026

Proteomic signatures for sudden cardiac death and related intermediate phenotypes.

BACKGROUND: Novel markers for sudden cardiac death (SCD) are needed. OBJECTIVE: This study aimed to explore whether a protein risk score derived from a large-scale proteomics dataset improves risk prediction of SCD in the general population. METHODS: A total of 52,705 individuals with 1459 unique plasma protein measurements were included from the UK Biobank Pharma Proteomics Project. A protein risk score was developed using lasso-penalized Cox regression on 40,722 participants enrolled at the English centers and validated on 11,983 participants enrolled at the remaining centers. RESULTS: The protein risk score formula developed from the derivation set comprised 64 unique plasma proteins including latent-transforming growth factor beta-binding protein 2, protein tyrosine phosphatase receptor sigma, and spondin-1. In the test set, a per standard deviation increase in protein risk score was associated with a hazard ratio of 2.60 (95% confidence interval [CI] 2.12-3.18) for SCD. Adding a protein risk score to SCD clinical risk factors resulted in a concordance index increase of 0.063 (95% CI 0.037-0.105) for SCD. For ventricular arrhythmia-mediated SCDs, an increase in concordance index when a protein risk score was added to SCD clinical risk factors was 0.070 (95% CI 0.010-0.188). A protein risk score added to SCD clinical risk factors resulted in a risk reclassification of 16.9% (95% CI 9.0-24.7) at a 10-year risk threshold of 5%. A protein risk score was significantly associated with intermediate phenotypes of SCD including corrected QT prolongation, an increase in left ventricular mean myocardial thickness, and a decrease in left ventricular global longitudinal strain. CONCLUSION: A protein risk score derived from a single plasma sample significantly improved risk prediction of SCD and related intermediate phenotypes.

Humans↗
PubMed2025

Influence of genetic factors of humans, mosquitoes and parasites, on the evolution of Plasmodium falciparum infections, malaria transmission and genetic control methods: a review of the literature.

Despite significant progress, malaria remains a public health problem in many regions, particularly in sub-Saharan Africa. This situation is partly explained by the mosquito's resistance to insecticides and the emergence of parasite resistance to antimalarial drugs. Indeed, in spite of the various vectors' controls, insecticide resistance emerges from multi-generational selection and poses worldwide concern. In parallel, artemisinin resistance unfortunately emerged independently in multiple countries in eastern Africa. Since 2014, artemisinin resistance has been observed in 6 countries in Africa and, more concerningly, the evidence from longitudinal molecular surveys in these countries suggests that it is spreading. While phenotypic evidence of treatment failure is still limited, the increasing reports of validated artemisinin resistance mutations are alarming. Unlike the emergence of artemisinin resistance in South-East Asia, our understanding of the genetic determinants of artemisinin resistance and our ability to sequence and map the spread of resistance are significantly greater. In addition to mosquito and parasite genetics affecting malaria evolution, many human individual variants have been identified that are associated with malaria protection, but the most important of all relates to the structure or function of red blood cells, the classical polymorphisms that causes sickle cell trait, α-thalassaemia, G6PD deficiency, and the major red cell blood group variants. In that biological complex context, there is a need to characterize the various genetic factors in Plasmodium falciparum, humans and mosquitoes that are potentially associated with resistance to antimalarial drugs and insecticides, and their involvement in the evolution, severity and transmission of malaria. In this direction, A comprehensive literature review was conducted to capture the objectives highlighted above. The advances in genomic surveillance and emerging genetic control strategies, such as gene drive technology were also considered in this review. We used search engines such as PubMed and Google scholar to retrieve articles useful to the objective of this paper and information on the knowledge of genetic factors and methods that contributed to malaria control were synthesized.

Humans↗
PubMed2026

Clinical and molecular characterization of TCF12 variants in an Asian pediatric cohort with craniosynostosis.

BACKGROUND: Craniosynostosis is a genetically heterogeneous craniofacial disorder caused by the premature fusion of one or more cranial sutures. Pathogenic variants in TCF12, encoding a basic helix-loop-helix (bHLH) transcription factor, represent a major cause of autosomal dominant coronal craniosynostosis and are characterized by incomplete penetrance and marked phenotypic variability. However, clinical and molecular data from Asian pediatric populations remain limited. METHODS: Trio-based whole-exome sequencing was performed on ten pediatric patients with cranial deformities and their parents. The identified TCF12 variants were classified according to the American College of Medical Genetics and Genomics (ACMG) guidelines and validated by Sanger sequencing. Detailed clinical and radiological data were collected. In addition, a comprehensive literature review was conducted to summarize previously reported TCF12 variants and associated phenotypes. RESULTS: Ten distinct heterozygous TCF12 variants were identified in ten unrelated pediatric patients, all of which were classified as pathogenic or likely pathogenic according to ACMG criteria. Six variants were inherited, and four occurred de novo. Seven patients had imaging-confirmed craniosynostosis, predominantly involving the coronal sutures (five bilateral and one unilateral), while one patient presented with multisuture craniosynostosis (left coronal and sagittal sutures). Three patients showed cranial deformities without radiographic evidence of suture fusion. Phenotypic heterogeneity and incomplete penetrance were observed, including a mildly affected parent. Most pathogenic variants were truncating variants distributed mainly across exons 14-19 and predicted to induce loss of function, either through nonsense-mediated mRNA decay or the production of truncated proteins lacking the entire C-terminal bHLH domain. Structural modeling analysis further indicated that the bHLH-domain-located missense variant p.Arg603Trp alters the local DNA-binding conformation of TCF12 and impairs its binding affinity to the E-box DNA motif. CONCLUSIONS: This study provides additional clinical and molecular data on TCF12-related craniosynostosis in a pediatric cohort from an Asian population. Our findings support haploinsufficiency as the central pathogenic mechanism, primarily driven by truncating variants affecting the C-terminal bHLH domain. The marked clinical heterogeneity, the presence of mild or evolving phenotypes, and incomplete penetrance observed in our cohort underscore the importance of early diagnosis and longitudinal clinical surveillance in affected families.

Humans↗
PubMed2026

Dolichocolon May Differentially Associate with Ulcerative Colitis Phenotype in Children.

BACKGROUND: Dolichocolon (DC) is an underrecognized anatomic variant associated with constipation; its association with ulcerative colitis (UC) is unknown. METHODS: We retrospectively reviewed abdominal MRI and CT scans in children with UC, Crohn's disease (CD), and non-inflammatory bowel disease (non-IBD) controls, classifying DC subtypes. RESULTS: A total of 111 cases (66 with UC) were examined. DC was similarly common (p = 0.4436) in patients with constipated (69%) or non-constipated (NC-UC: 57%) UC. In non-constipated (NC) patients, DC prevalence was higher in children with UC than those with CD or controls. Type 1 DC predominated in NC children with proctitis/left-sided UC (E1/E2), while Type 2 DC was enriched in children with extensive/pancolitis (E3/E4). DISCUSSION: DC may be associated with different phenotypes of UC and may influence disease distribution independent of constipation. However, given the cross-sectional design of this study, these associations should be interpreted cautiously and require confirmation in longitudinal studies.

Humans↗
PubMed2026

Human brown fat metabolism associates with systemic branched-chain amino acids homeostasis.

Circulating branched-chain amino acids (BCAAs) are linked with insulin resistance, but the human tissues contributing to systemic BCAA homeostasis remain incompletely defined. Brown adipose tissue (BAT) is a metabolically active adipose depot associated with favourable insulin sensitivity, yet its role in BCAA metabolism in humans remains unclear. We tested whether human BAT metabolism is associated with circulating BCAA levels, BAT-resident BCAA-catabolic signatures, and longitudinal changes in systemic BCAA homeostasis. We studied 83 adults who underwent metabolic phenotyping, PET-CT assessment of cold-stimulated BAT metabolism, and serum metabolomic profiling at room temperature and during acute mild cold exposure. Supraclavicular BAT biopsies from 25 participants were analysed by transcriptomics and metabolomics, and 40 participants were re-examined for circulating BCAA profiles after approximately five years. Participants with high BAT metabolism had lower circulating BCAA levels than those with low BAT metabolism. Within BAT, metabolically active individuals exhibited lower relative BCAA abundance together with higher expression of genes involved in BCAA catabolism. These BAT BCAA-catabolic signatures aligned with thermogenic capacity and indices of systemic insulin sensitivity. In contrast, individuals with low BAT metabolism showed increases in circulating BCAAs over five years. Integrative analyses further linked circulating lipopolysaccharide, a marker of metabolic endotoxemia, with higher BAT BCAA and aminomalonate abundance, together with transcriptional patterns involving inflammatory and mitochondrial pathways. Together, these findings identify human BAT metabolism as a tissue phenotype linked to systemic BCAA homeostasis and extend the role of human BAT beyond thermogenesis, suggesting that BAT-associated BCAA handling may contribute to systemic metabolic health.

Humans↗
PubMed2026

Effects of Fecal Microbiota Transplantation on Intestinal Microbial Characteristics and Clinical Phenotypes in Patients with Parkinson's Disease.

Alterations in the gut microbiota have been associated with Parkinson's disease (PD), but longitudinal microbial changes after fecal microbiota transplantation (FMT) and their clinical associations remain poorly understood. This single-center retrospective observational study included 6 patients with PD, stratified into high- and low-severity subgroups based on disease duration (>6 years vs ≤6 years). Thirty-six fecal samples were collected before FMT and monthly for five months afterward. Microbial diversity, community structure, taxonomic composition, and predicted functional profiles were assessed using 16S ribosomal RNA gene sequencing. Analyses included alpha and beta diversity, taxonomic abundance, linear discriminant analysis effect size, Tax4Fun2-based functional prediction, and Spearman rank correlations between microbial features and clinical indicators. Descriptive analyses indicated differences in microbial richness, diversity, community structure, and predicted functions between severity subgroups and across post-FMT time points. At baseline, the low-severity subgroup had greater microbial richness and diversity than the high-severity subgroup, with relatively higher abundances of taxa including Bifidobacterium and Lactobacillus. One month after FMT, richness and diversity increased from baseline in the high-severity subgroup, accompanied by changes in taxonomic composition. Both subgroups showed time-associated variation in microbial diversity and predicted Kyoto Encyclopedia of Genes and Genomes pathway enrichment after FMT. Predicted functions included carbohydrate and amino acid metabolism, secondary metabolite biosynthesis, membrane transport, and signal transduction. Several operational taxonomic units correlated with indicators of motor impairment, constipation, sleep quality, functional status, and neuropsychiatric symptoms. FMT was therefore associated with longitudinal changes in gut microbial diversity, composition, and predicted functions, and specific microbial features were associated with motor and non-motor indicators. Given the small retrospective cohort, these findings are preliminary and warrant confirmation in larger controlled studies. Future studies should determine whether these microbial alterations are reproducible, persist beyond five months, reflect donor engraftment, and correspond to measurable clinical improvement after transplantation in PD.

Humans↗
PubMed2026

Genetic evidence that advanced COVID-19 accelerates longitudinal brain atrophy: A Mendelian randomization study.

Coronavirus disease 2019 (COVID-19) was reported to persist long-term in the brain and leave several long-term neurologic sequelae. However, the causal relationship between COVID-19 and brain aging is still unknown. The genome-wide association study (GWAS) data on COVID-19 phenotypes (susceptibility, hospitalization, and severity), involving a total of 5,779,391 participants, were collected from the COVID-19 Host Genetics Initiative. In addition, GWAS data on longitudinal changes in 15 brain structures, assessed via magnetic resonance imaging across the lifespan, were sourced from the ENIGMA Consortium and involved 15,640 participants. Two-sample Mendelian randomization was conducted to infer the causal relationship between COVID-19 and longitudinal brain changes. Multi-trait GWAS meta-analysis, colocalization, and fine-mapping analyses were performed to identify shared genetic etiologies. H3K27me3 ChIP-seq was used to evaluate the regulatory effect of colocalized loci. Two-step Mendelian randomization was applied to explore potential mediating mechanisms across multi-omics layers, including proteomics, metabolomics, and immunomics. Our results showed that COVID-19 hospitalization (β = -262.405, P = .041) and severity (β = -177.676, P = .049) were genetically associated with atrophied volume of total brain during longitudinal change. This suggests that individuals with advanced COVID-19 may be more susceptible to accelerated global brain aging. Caudate was genetically affected by all COVID-19 phenotypes. Seven variants were shared between advanced COVID-19 and global brain aging. rs117169628 was colocalized between advanced COVID-19 and global brain aging, and exerted an inhibitory effect on CDH15 expression, further strengthening the causality. Six metabolites, 1 protein, and 1 immune trait were identified as potential mediators. Our study indicates that advanced COVID-19 might be genetically associated with accelerated brain aging. Brain health should be paid more attention in long COVID-19.

Humans↗
PubMed2024

Algorithms for the identification of prevalent diabetes in the All of Us Research Program validated using polygenic scores.

The All of Us Research Program (AoU) is an initiative designed to gather a comprehensive and diverse dataset from at least one million individuals across the USA. This longitudinal cohort study aims to advance research by providing a rich resource of genetic and phenotypic information, enabling powerful studies on the epidemiology and genetics of human diseases. One critical challenge to maximizing its use is the development of accurate algorithms that can efficiently and accurately identify well-defined disease and disease-free participants for case-control studies. This study aimed to develop and validate type 1 (T1D) and type 2 diabetes (T2D) algorithms in the AoU cohort, using electronic health record (EHR) and survey data. Building on existing algorithms and using diagnosis codes, medications, laboratory results, and survey data, we developed and implemented algorithms for identifying prevalent cases of type 1 and type 2 diabetes. The first set of algorithms used only EHR data (EHR-only), and the second set used a combination of EHR and survey data (EHR+). A universal algorithm was also developed to identify individuals without diabetes. The performance of each algorithm was evaluated by testing its association with polygenic scores (PSs) for type 1 and type 2 diabetes. We demonstrated the feasibility and utility of using AoU EHR and survey data to employ diabetes algorithms. For T1D, the EHR-only algorithm showed a stronger association with T1D-PS compared to the EHR + algorithm (DeLong p-value = 3 × 10-5). For T2D, the EHR + algorithm outperformed both the EHR-only and the existing T2D definition provided in the AoU Phenotyping Library (DeLong p-values = 0.03 and 1 × 10-4, respectively), identifying 25.79% and 22.57% more cases, respectively, and providing an improved association with T2D PS. We provide a new validated type 1 diabetes definition and an improved type 2 diabetes definition in AoU, which are freely available for diabetes research in the AoU. These algorithms ensure consistency of diabetes definitions in the cohort, facilitating high-quality diabetes research.

Humans↗
PubMed2025

A SuperLearner-based pipeline for the development of DNA methylation-derived predictors of phenotypic traits.

BACKGROUND: DNA methylation (DNAm) provides a window to characterize the impacts of environmental exposures and the biological aging process. Epigenetic clocks are often trained on DNAm using penalized regression of CpG sites, but recent evidence suggests potential benefits of training epigenetic predictors on principal components. METHODOLOGY/FINDINGS: We developed a pipeline to simultaneously train three epigenetic predictors; a traditional CpG Clock, a PCA Clock, and a SuperLearner PCA Clock (SL PCA). We gathered publicly available DNAm datasets to generate i) a novel childhood epigenetic clock, ii) a reconstructed Hannum adult blood clock, and iii) as a proof of concept, a predictor of polybrominated biphenyl exposure using the three developmental methodologies. We used correlation coefficients and median absolute error to assess fit between predicted and observed measures, as well as agreement between duplicates. The SL PCA clocks improved fit with observed phenotypes relative to the PCA clocks or CpG clocks across several datasets. We found evidence for higher agreement between duplicate samples run on alternate DNAm arrays when using SL PCA clocks relative to traditional methods. Analyses examining associations between relevant exposures and epigenetic age acceleration (EAA) produced more precise effect estimates when using predictions derived from SL PCA clocks. CONCLUSIONS: We introduce a novel method for the development of DNAm-based predictors that combines the improved reliability conferred by training on principal components with advanced ensemble-based machine learning. Coupling SuperLearner with PCA in the predictor development process may be especially relevant for studies with longitudinal designs utilizing multiple array types, as well as for the development of predictors of more complex phenotypic traits.

DNA Methylation↗
PubMed2026

Epigenetics and childhood obesity: DNA methylation coordinates environment and gene regulation.

Childhood obesity is a complex disorder which results from the combined contribution of genetics, the environment, and development, which is programmed and coordinated by epigenetic mechanisms. Of them, DNA methylation has emerged as an important molecular interface between environmental inputs and changes in gene expression. In this review, we provide an overview of the role of DNA methylation in childhood obesity during the key developmental stages, from prenatal life and childhood to adolescence. We also highlight the available evidence from candidate genes and genome-wide association studies implicating critical loci involved in energy homeostasis and adipogenesis, where DNA methylation is altered. Further, we also provide an overview of how maternal obesity, nutritional status, and bariatric surgery shape offspring's methylation profiles and contribute to the increased risk of programming obesity across generations. Although aberrant methylation patterns are consistently associated with altered metabolic phenotypes, disentangling causality remains a significant challenge. Herein, we highlight emerging approaches, such as rigorous longitudinal cohorts, epigenetic Mendelian randomization, and CRISPR-based epigenome editing, that are beginning to provide the analytical clarity needed to move beyond association. Finally, we examine the potential of DNA methylation signatures to inform early risk stratification and prevention possibilities. Although yet to be clinically validated, whole-genome methylation profiling is increasingly integrated with systems biology and multi-omics frameworks, making the identification of robust, clinically actionable markers more promising. A more precise understanding of how epigenetic processes shape susceptibility to childhood obesity could ultimately support strategies capable of altering lifelong metabolic trajectories.

Humans↗
PubMed2025

Novel approaches and applications in identifying DNA methylation markers of cardio-kidney-metabolic disease.

Cardio-kidney-metabolic (CKM) diseases represent a major public health challenge, accounting for a large proportion of global burden of morbidity and mortality. These conditions share risk factors, including genetic predisposition, environmental exposures, and lifestyle influences, which collectively drive disease development and progression. Epigenetic modifications, particularly DNA methylation (DNAm), serve as key mediators and biomarkers between these risk factors and disease phenotypes by regulating gene expression without altering the DNA sequence. Epigenome-wide association studies have identified DNAm markers associated with CKM diseases and related phenotypes, highlighting both shared pathways and disease-specific epigenetic signatures in inflammation, metabolic dysfunction, and aging-related processes. Longitudinal studies further demonstrate the dynamic nature of DNAm changes over time, offering insights into disease trajectories. Additionally, methylation risk scores integrating multiple epigenetic markers show promise in improving disease prediction and risk stratification beyond traditional clinical factors. To synthesize the current evidence, we conducted a targeted literature search in PubMed for English-language, peer-reviewed articles published between 2014 and the present. Future research leveraging large, well-phenotyped cohorts, advanced statistical methods, and innovative study designs will be critical for uncovering novel biomarkers, refining risk prediction models, and developing targeted epigenetic therapies to mitigate the global burden.

Humans↗
PubMed2026

Downregulation of Trpv4 and Klf2 in brain microvessels is associated with the progression of neurovascular dysfunction and cognitive impairment in a model of heart failure with preserved ejection fraction.

Vascular cognitive impairment (VCI) shares major risk factors with heart failure with preserved ejection fraction (HFpEF), including obesity, diabetes and hypertension. Yet VCI research often relies on single-stimulus models, whereas patients experience combined risk factors. We therefore assessed cerebrovascular and cognitive phenotypes in an HFpEF model and investigated underlying mechanisms. Male Lean and Obese ZSF1 rats underwent longitudinal assessments of blood pressure, glucose, cardiac function and behavioural performance. Cerebral blood flow and neurovascular coupling were assessed by laser speckle contrast imaging. White matter integrity, blood-brain barrier (BBB) permeability and vascular density were analyzed by (immuno)histochemistry. Cortical microvessels were isolated for transcriptomic profiling, and selected targets were validated using multiplex in-situ hybridization. Obese rats exhibited neurovascular uncoupling and impaired short- and long-term memory and spatial learning, accompanied by brain atrophy and reduced myelin. BBB permeability increased at 22-23 weeks and vascular density at 34-35 weeks in Obese versus Lean rats. Transcriptomic analysis of brain microvessels revealed altered processes related to angiogenesis, vasoreactivity, immune mechanisms and vascular remodelling, with consistent downregulation of Trpv4 and Klf2. Obese ZSF1 rats develop progressive neurovascular dysfunction associated with HFpEF onset and reduced Trpv4 and Klf2 expression in cerebral microvessels, two key vasoprotective genes.

Diastolic dysfunction↗
PubMed2026

Integrating Radiogenomics and CSF-Based Liquid Biopsy Sequencing for Precision Neuro-Oncology.

Glioblastoma and diffuse gliomas pose major therapeutic challenges due to marked intratumoral heterogeneity, limited tissue accessibility, and the blood-brain barrier. Tissue-based next-generation sequencing (NGS) remains essential for WHO CNS5 molecular classification, yet it is invasive and poorly suited to serial monitoring. Two complementary non- or minimally invasive approaches have advanced rapidly: radiogenomics, which correlates multiparametric MRI features with genomic alterations, and cerebrospinal fluid (CSF) liquid biopsy sequencing, which detects circulating tumor DNA with high tissue concordance. This review examines the independent progress and synergistic integration of radiogenomics and CSF-NGS. Imaging signatures can non-invasively predict key drivers (IDH1/2, EGFR, TERT, PTEN, TP53) and molecular subtypes, while CSF-ctDNA sequencing enables real-time assessment of clonal evolution, therapy resistance (including post-temozolomide hypermutation), and residual disease. We discuss technical considerations, performance metrics, multimodal artificial-intelligence fusion, and emerging clinical applications for diagnosis, prognosis, treatment selection, and longitudinal surveillance. Critical challenges, standardization, prospective validation, and workflow integration are highlighted. By combining the spatial phenotypic information of radiogenomics with the temporal genomic resolution of CSF sequencing, this multimodal strategy offers a promising path toward precision neuro-oncology and reduced reliance on repeated invasive sampling.

Humans↗
PubMed2026

Spatiotemporal single-cell profiling reveals T cell clonal dynamics and phenotypic plasticity in human graft-versus-host disease.

Allogeneic hematopoietic cell transplantation cures hematologic diseases but is limited by acute graft‑versus‑host disease. How human T cell clones drive epithelial injury remains poorly mapped. We studied 31 transplant recipients, integrating longitudinal T cell antigen receptor (TCR) profiling with single-cell RNA sequencing/TCR sequencing and spatial transcriptomics to track T cell clonal dynamics. We developed DecompTCR to resolve temporal dynamics and adapted computational tools to map clone phenotypes and niches in tissue. Our analyses revealed that cyclophosphamide selectively depletes alloreactive clones, although insufficient early expansion leads to incomplete depletion and severe disease. Severe graft‑versus‑host disease is marked by persistent expansion of alloreactive clones, rewiring of homeostatic cell types and diversification of donor-derived CD8+ clonotypes that acquire Hobit (ZNF683)+ tissue‑resident memory T (TRM) cell programs during migration to epithelium. Spatial deconvolution identified CD8+ effector/Hobit+ TRM hubs near intestinal stem‑cell-rich crypt bases and crypt‑loss regions. This clonotype‑resolved framework links tissue‑instructed TRM cell remodeling to localized epithelial injury, nominating early-repertoire dynamics and spatial hub burden as biomarkers.

Journal Article↗
PubMed2026

Metagenomic profiling of blood-associated microbial DNA signatures in leukemia-associated febrile neutropenia.

Febrile neutropenia (FN) is a life-threatening complication of chemotherapy, but the low microbial biomass of blood makes shotgun metagenomic profiles highly sensitive to technical background. We reanalyzed 47 publicly available patient sequencing runs representing 43 unique patient-timepoint samples from 19 SRA-labeled patients, together with 23 no-template-control (NTC) runs spanning 21 sequencing batches. To distinguish reference-catalogue content from progressively stronger evidence of patient-associated signal, we applied batch-matched NTC correction together with nested abundance thresholds and a feature-specific global NTC envelope. CheckM2 evaluated 1,013 bins; 13 met completeness &#x2265;50% and contamination <10%, and dereplication yielded 11 draft MAG representatives. Ten representatives showed positive patient-to-control abundance excess, but only four showed recurrent support above both threefold matched-control abundance and the global NTC envelope. Functional annotations were therefore interpreted as reference-genome homologs rather than evidence of expression, phenotype, viability or bloodstream origin. Matched-control correction retained 19 read-level ARG types, but only seven subjects contributed complete longitudinal ARG-profile contrasts, limiting reliable temporal inference. The resulting run-resolved, nested evidence framework identified a subset of microbial DNA and ARG signals that remained detectable under increasingly stringent control criteria while distinguishing them from catalogue-level or background-sensitive signals. These findings support cautious reporting of patient-enriched microbial DNA and ARG signals rather than inference of a resident blood microbiome or clinical resistance phenotype.

antimicrobial resistance genes↗
PubMed2026

Single-section multiplex spatial proteomics of immune microenvironments in kidney transplantation.

Characterizing kidney disease is challenged by marked cellular heterogeneity and limited tissue availability from renal biopsies. Conventional diagnostic workflows rely on multiple serial sections for parallel staining, increasing tissue consumption, sampling bias, and loss of spatial information, thereby constraining molecular characterization within intact tissue architecture. High-plex spatial proteomics may overcome these limitations by enabling comprehensive molecular profiling on a single section. Here, we present and evaluate a high-plex cyclic immunofluorescence imaging workflow (MACSima&#x2122;, Miltenyi Biotec) applied to kidney transplant biopsies, including BK virus nephropathy (BKVN) and focal segmental glomerulosclerosis (FSGS), to characterize spatial immune organization with a focus on complement system components. Feasibility and subcellular resolution were first assessed in a lupus nephritis section, demonstrating compatibility with diagnostic immune panels and preservation of tissue morphology. A 48-marker multiplex panel interrogating immunity, oxidative stress, senescence, and fibrosis was then applied to BKVN samples, including paired pre- and post-treatment biopsies, revealing distinct proteomic patterns and dynamic changes following therapy. In FSGS, a glomerulus-focused panel identified spatially resolved innate and adaptive immune signatures, including complement-related patterns supporting exploratory analysis of glomerular immune architecture. Structural, nuclear, membrane, and phosphorylated signaling markers enabled precise delineation of renal compartments and assessment of cellular states such as proliferation, DNA damage, and pathway activation. The workflow also supported detection of extracellular vesicles in cultured renal cells, highlighting its versatility. Overall, this approach provides a robust, tissue-sparing platform for integrated spatial and molecular profiling of renal biopsies, reducing sampling bias while enabling discovery-level phenotyping from a single section. This unified strategy is particularly suited to kidney transplantation, where diagnosis, therapeutic decision-making, and longitudinal monitoring are closely interconnected.

Kidney Transplantation↗