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PubMed2026

Multi‑omics approaches to decipher the molecular mechanisms of exercise‑mediated bone protection: From mechanistic insights to personalized exercise prescription (Review).

The global burden of bone metabolic disorders necessitates a shift from generic exercise recommendations toward personalized prescription strategies. Exercise confers skeletal protection through mechanotransduction, yet the underlying molecular networks remain incompletely understood. Multi‑omics technologies, including transcriptomics, proteomics, metabolomics and single‑cell spatial approaches, have revolutionized the capacity to decode exercise‑mediated bone adaptation at the systems level. The present review synthesizes current single‑omics landscapes and integrative multi‑omics analyses that elucidate the core regulatory networks, mechanobiological coupling mechanisms and multiorgan crosstalk that are implicated in the bone response to mechanical loading. Translational applications across clinical scenarios such as osteoporosis, osteoarthritis and disuse bone loss are evaluated, and the technical, analytical and translational challenges limiting clinical implementation are addressed. Finally, the present review provides a framework for translating multi‑omics molecular signatures into personalized exercise prescriptions for optimized skeletal health.

Humans↗

PubMed2026

Strategy for Simultaneous Multiomic Survey of N-Glycomic and Extracellular Matrix Proteome by Mass Spectrometry Imaging.

Recent advances in spatially resolved molecular profiling have positioned matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) as a powerful platform for multiomic tissue analyses. However, conventional workflows that sequentially target distinct molecular classes are time- and resource-intensive, requiring repeated sequential sample preparation, imaging, and data integration. Here, we evaluate streamlined strategies for simultaneous or combined acquisition of N-glycan and collagen-derived peptide information using PNGase F and collagenase. In-solution studies demonstrate that simultaneous enzymatic digestion yields comparable peptide identifications and glycan profiles relative to traditional sequential workflows, with minimal impact on enzymatic specificity. On the basis of these findings, we developed and optimized MALDI-MSI protocols enabling either simultaneous enzyme application or sequential enzyme treatment with unified matrix deposition and single-pass imaging. While direct coapplication reduced image uniformity, a hybrid approach that used sequential enzyme deposition with combined imaging preserved spatial fidelity and spectral quality while significantly reducing processing and computational demands. Application to human tissues, including vertebral bone and ocular samples, highlights the utility of this workflow for fragile specimens and exploratory multiomic surveys. Collectively, these results establish a framework for integrated glycomic and proteomic imaging targeting the extracellular microenvironment, expanding multiomic MALDI-MSI analyses.

Spectrometry, Mass, Matrix-Assisted Laser Desorpti↗

PubMed2026

Bridging genotype, phenotype, and clinical insight: the role of multi-omics in cardiovascular disease.

INTRODUCTION: It is increasingly evident that the multifactorial nature of cardiovascular disease requires the combination of different omics approaches for improving our mechanistic understanding, identifying novel drug targets, and developing accurate diagnostic, predictive, and prognostic biomarker panels. AREAS COVERED: We review the current state and the potential of multi-omics in cardiovascular disease, with a specific focus on plasma-, spatial-, and single-cell approaches. We discuss lipidomics as a genotype‑to‑phenotype bridge, the utility of remote longitudinal monitoring via microsampling/dried blood spots, and emerging clinical‑trial integrations of multi-omics approaches. We outline critical gaps in standardization and how to overcome these, pre‑analytical challenges and constraints that are often neglected, and data‑integration methods spanning from canonical correlation analysis to modern machine learning approaches. EXPERT OPINION: Multi‑omics can shape cardiovascular care by identifying drug targets in diseased tissue and by yielding small, usable biomarker panels.

Humans↗

PubMed2025

Widespread release of translational repression across Plasmodium's host-to-vector transmission event.

Malaria parasites must respond quickly to environmental changes, including during their transmission between mammalian and mosquito hosts. Therefore, female gametocytes proactively produce and translationally repress mRNAs that encode essential proteins that the zygote requires to establish a new infection. While the release of translational repression of individual mRNAs has been documented, the details of the global release of translational repression have not. Moreover, changes in the spatial arrangement and composition of the DOZI/CITH/ALBA complex that contribute to translational control are also not known. Therefore, we have conducted the first quantitative, comparative transcriptomics and DIA-MS proteomics of Plasmodium parasites across the host-to-vector transmission event to document the global release of translational repression. Using female gametocytes and zygotes of P. yoelii, we found that ~200 transcripts are released for translation soon after fertilization, including those encoding essential functions. Moreover, we identified that many transcripts remain repressed beyond this point. TurboID-based proximity proteomics of the DOZI/CITH/ALBA regulatory complex revealed substantial spatial and/or compositional changes across this transmission event, which are consistent with recent, paradigm-shifting models of translational control. Together, these data provide a model for the essential translational control mechanisms that promote Plasmodium's efficient transmission from mammalian host to mosquito vector.

Animals↗

PubMed2026

Lipid metabolism is a key central, systemic and gut microbial feature of the decline in rat hippocampal function during middle age.

Middle age is emerging as a turning point in brain ageing, prognostic of future cognitive health and amenable to intervention. Metabolic and proteomic differences during this period are not yet fully understood and may potentially influence functions of the hippocampus, a brain area that regulates memory and anxiety. While the gut microbiota is implicated in brain ageing, the relationship between the gut microbiota, the metabolic state, and hippocampal proteome in middle age has not been investigated. We hypothesise that peripheral metabolic or protein features are associated with hippocampal vulnerability in middle age. Therefore, young adult and middle-aged rats were assessed for behavioural, proteomic, metabolic, and gut microbiota differences. Proteomic profiling of the hippocampus revealed differential expression of proteins indicative of altered synaptic signalling. Concurrently, adult hippocampal neurogenesis was decreased in middle age. Hippocampal microglia exhibited a lipid rich, inflammatory phenotype in middle age which correlated with poorer memory performance. CSF and serum proteomic and metabolomic analyses identified dysregulated lipid-related pathways potentially contributing to hippocampal vulnerability in middle age. Furthermore, 16S rRNA sequencing revealed reduced abundance of bacteria involved in lipid metabolism regulation. However, faecal microbiota transfer from young to middle aged rats was not sufficient to robustly improve hippocampus-dependent spatial memory. Together, these findings highlight dysfunctional lipid metabolism as a key feature of middle age that may contribute to decline in hippocampal function. Given that the scope for intervention is limited during older age, targeting biomarkers involved in metabolic and lipid homeostasis may be pivotal for the development of pharmacological or lifestyle-based interventions during middle age which could ultimately delay future cognitive ageing.

Animals↗

PubMed2026

CRISPR-Enabled functional genomics in hPSCs-derived neural models for autism spectrum disorder.

Autism Spectrum Disorder (ASD) is a genetically heterogeneous neurodevelopmental condition in which hundreds of individually rare risk variants converge on a small number of shared biological pathways, including synaptic scaffolding, chromatin remodeling, excitation-inhibition balance, and cellular energy metabolism. Translating this genetic heterogeneity into mechanistic insight requires experimental systems capable of interrogating individual gene functions in human-relevant neural contexts at scale. CRISPR-enabled functional genomics in human pluripotent stem cell (hPSC)-derived neural models, spanning neural progenitors, cortical and inhibitory neurons, astrocytes, microglia, and brain organoids, provides precisely this capability. By integrating pooled perturbation screens with multimodal readouts including single-cell and spatial transcriptomics, chromatin accessibility profiling, proximity labeling proteomics, multi-electrode array electrophysiology, and metabolic flux analysis, these platforms enable systematic, causal mapping of ASD gene function at system resolution. Early applications have already revealed convergent mechanisms: BAF complex disruption expands the ventral progenitor pool and biases its fate toward oligodendrocyte and interneuron lineages; ADNP loss impairs microglial synaptic pruning through altered endocytic trafficking; and mTOR pathway dysregulation in PTEN- and TSC2-perturbed models links genetic risk directly to metabolic and mitochondrial dysfunction. Computational frameworks including MIMOSCA and SCEPTRE enable causal network reconstruction and pseudotime inference from these datasets, moving the field from gene lists toward pathway-level models of ASD pathobiology. Translational applications leverage isogenic iPSC panels and variant-level base and prime editing to stratify ASD variants by functional impact, informing gene therapy design for haploinsufficient targets such as CHD8 and SCN2A via AAV or antisense oligonucleotide delivery. Remaining challenges, including model developmental immaturity, batch variability, and the difficulty of modeling polygenic risk, are addressed by a roadmap integrating spatial perturbomics, AI-driven causal inference, and population-scale standardized biobanks. This review synthesizes the current state of CRISPR-based functional genomics in human stem cell neural models as a coherent experimental framework for converting ASD genetic associations into mechanistic understanding and therapeutic opportunity.

Humans↗

PubMed2026

Omics in optic neuropathies: From molecular landscapes to personalized therapeutics.

Optic neuropathies comprise a heterogeneous group of disorders involving transient or permanent injury to retinal ganglion cells (RGCs) and their axons. Clinically, these neurodegenerative conditions manifest as dyschromatopsia, decreased visual acuity, and visual field defects, and in severe cases may ultimately lead to blindness and disability. The marked heterogeneity across disease subtypes, incompletely understood etiologies, and complex pathogenic mechanisms pose substantial challenges to precise diagnosis and effective treatment. Recent advances in omics technologies - including genomics, transcriptomics, proteomics, metabolomics, lipidomics, single-cell and spatial sequencing, and integrative multi-omics approaches - have ushered optic nerve degenerative disease research into an era of high-resolution comprehensive investigation. In this review, we summarize representative applications of omics approaches to elucidate genetic alterations, signaling dysregulation, metabolic reprogramming, and immune responses in optic neuropathies. We further discuss the emerging potential of multi-omics in identifying early diagnostic biomarkers and informing individualized therapeutic strategies. Finally, we provide a forward-looking perspective on the future trajectory of omics technologies and their prospects in both fundamental research and clinical translation, with the overarching aim of accelerating the bench-to-bedside transition in this critical eye disease field.

biomarkers↗

PubMed2026

Proteomics as a theranostic compass in BCR::ABL1-negative myeloproliferative neoplasms: Integrating biomarker discovery with therapeutic stratification.

Classic BCR::ABL1-negative myeloproliferative neoplasms (MPNs)-polycythaemia vera, essential thrombocythaemia, and primary myelofibrosis-are clonal haematopoietic stem cell disorders with marked heterogeneity in clinical phenotype, disease trajectory, and therapeutic response. Genomic stratification by driver and cooperating mutations only partially accounts for this variability, leaving gaps in predicting thrombotic risk, fibrotic progression, leukaemic transformation, and treatment benefit. Proteomics bridges this gap by providing function-proximal readouts of protein abundance, post-translational modifications, pathway activity, and intercellular signalling that genomics and transcriptomics cannot capture, positioning it as a theranostic platform in which the same molecular readouts simultaneously inform diagnostic stratification and therapeutic decision-making. We propose a five-stage translational framework spanning from discovery-scale mass spectrometry and affinity-based plasma profiling to targeted validation, multicentre standardisation, and machine learning-integrated clinical panels. Proteomic evidence is synthesised across the following four disease axes: clonal fitness in haematopoietic stem and progenitor cells; bone marrow microenvironmental remodelling and fibrosis; chronic inflammation and thrombosis; and leukaemic transformation. We further describe how phosphoproteomics reveals resistance mechanisms to JAK inhibitors, including AXL-MAPK bypass and PP2A-autophagy-mediated tolerance, and how protein-level biomarkers (BCL2-BCL-XL, RAS-ERK, CAMK2G, and ROCK1/2) can guide individualised therapeutic selection. Affinity-based platforms (Olink PEA and SomaScan) and spatially resolved technologies (CODEX and single-cell proteomics) complement discovery proteomics. At present, however, this evidence base is constrained by small and heterogeneous cohorts, limited cross-platform reproducibility, and a scarcity of independent external validation for candidate protein panels. Realising this vision will require multicentre standardisation, analytically validated panel assays, and prospective clinical studies that translate molecular findings into decision-grade tools for patients with MPNs.

Humans↗

PubMed2026

Spatial multiomics in biomedical research: advances beyond transcriptomics.

Coordinated changes in gene expression, epigenetic regulation, protein and metabolic activities together drive disease progression and determine clinical outcomes. While spatially resolved transcriptomics has been widely adopted across biomedical fields, it offers an incomplete picture limited to transcriptomic levels. Here, we survey the latest developments in spatial multiomics technologies, with particular emphasis on platforms that extend beyond conventional transcriptomics and profile genomics, epigenomics, proteomics, or metabolomics within intact tissues. These approaches are rapidly becoming commercialized, and here we highlight major technical breakthroughs, enhanced sample compatibility, emerging applications, and computational tools for data analysis. This Review aims to equip researchers with a clear understanding of the current technological landscape and to accelerate the adoption of spatial multiomics methods in biomedical research.

Humans↗

PubMed2026

Multimodal Analysis Reveals Aberrant Expression of SUMO2 and Its Significant Association With Key Mechanisms of Metabolic Pathways in Hepatocellular Carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths worldwide. However, the role of small ubiquitin-like modifier 2 (SUMO2), a core member of the small ubiquitin-like modifier (SUMO) family, regarding its expression patterns and metabolism-related functions in HCC remains inadequately understood. METHODS: A multidimensional analytical framework was applied, integrating immunohistochemistry (153 HCC vs. 21 non-HCC samples), proteomics (159 paired samples), bulk transcriptomics (3240 HCC vs. 2267 non-HCC samples), single-cell RNA sequencing (RNA-seq) (10 HCC vs. 8 non-HCC samples), spatial transcriptomics, and external CRISPR/Cas9 functional genomics data. Systematic analyses included standardized mean difference (SMD), pathway enrichment, pseudotime trajectory inference, in silico knockout, cell-cell communication, metabolic flux scoring, immune infiltration, clinical correlation, drug sensitivity prediction, and molecular docking. RESULTS: At the protein level, immunohistochemistry (nuclear positivity) and external proteomic data collectively demonstrated consistent SUMO2 overexpression in HCC. Consistent upregulation was also observed at the mRNA level across large-scale cohorts. Single-cell RNA-seq and spatial transcriptomics localized SUMO2 enrichment to malignant hepatocytes and tumor-dominant regions. CRISPR-mediated SUMO2 knockout suppressed proliferation in multiple HCC cell lines. Mechanistically, high SUMO2 expression was significantly associated with metabolic reprogramming involving glycolysis/gluconeogenesis, pyruvate metabolism, and the tricarboxylic acid cycle. SUMO2-high malignant hepatocyte subpopulations exhibited enhanced activity of the macrophage migration inhibitory factor signaling axis and enhanced iron-sensor interactions. Further, the immune infiltration analysis revealed a negative correlation between SUMO2 expression and M1 macrophages and a positive correlation between follicular helper T cells and regulatory T cells. Clinically, elevated SUMO2 levels were found to be associated with adverse prognostic features. Furthermore, high SUMO2 expression was associated with increased sensitivity to dasatinib, and molecular docking simulations predicted potential binding between SUMO2 and dasatinib, with a Vina score of -8.5 kcal/mol. CONCLUSIONS: SUMO2 is aberrantly expressed at the protein, mRNA, single-cell, and spatial transcriptomic levels in HCC and is significantly associated with metabolic reprogramming and altered migration inhibitory factor (MIF)-mediated intercellular communication, suggesting its potential as a novel biomarker for diagnosis and treatment.

Humans↗

PubMed2026

DeepPlaque: a scalable multimodal platform for Aβ pathology and cell analysis in Alzheimer's disease.

Histological analysis is essential for understanding disease pathology and the microenvironment, particularly in Alzheimer's disease (AD), characterized by beta-amyloid (Aβ) plaques that exist as diffuse, fibrillar, and core species, with distinct toxicity levels. However, accurate classification of Aβ plaque types in postmortem brain tissues and profiling of surrounding cells present significant challenges. To address these challenges, we developed "DeepPlaque", an integrated system featuring "PlaqueNet", a deep learning model for automated classification of Aβ plaque species from diverse imaging platforms. DeepPlaque includes automated workflows for cellular phenotyping and proteomic profiling through targeted laser microdissection. PlaqueNet achieves expert-level accuracy (AUC > 90%) in classifying the 3 major Aβ plaque species, supporting consistent and large-scale annotation. By integrating spatial cellular phenotyping with laser microdissection, DeepPlaque enables high-throughput proteomic analysis of Aβ plaque niches, revealing that microglia are more abundant around core and fibrillar Aβ plaques, with increased expression of apolipoprotein E and amyloid precursor protein in core Aβ plaques. This customizable platform enhances the molecular and cellular characterization of Aβ plaque-associated environments, providing critical insights into AD pathology.

Alzheimer Disease↗

PubMed2026

Pathogenic role of serpin B3-positive neutrophils in reinforcing thrombus stiffening during ischemic stroke.

The contribution of immune cells to thrombus architecture and mechanical properties in acute ischemic stroke (AIS) remains poorly understood. Using 3-dimensional imaging and multiplex staining, we mapped immune cells in human stroke thrombi and identified neutrophils as the dominant population. Analysis of 19 thrombi confirmed their positive correlation with collagen, increased stiffness, and poorer clinical outcomes. To preserve spatial context, we developed a laser capture-based proteomic workflow and analyzed thrombus neutrophils from 34 patients with AIS stratified by 90-day outcomes, followed by validation in an independent cohort of 22 patients. Proteomic analysis revealed serpin B3 as a neutrophil-enriched protein strongly correlated with poor prognosis. In murine models of ferric chloride-induced carotid artery thrombosis and middle cerebral artery occlusion, experiments using wild-type, neutrophil-depleted, and Serpinb3a knockout mice demonstrated that neutrophil-derived serpin B3 promotes early thrombus formation, enhances collagen deposition, and contributes to progressive thrombus stiffening. Mechanistically, serpin B3 secreted by neutrophils amplifies thrombus stiffness through upregulation of transforming growth factor β1, neutrophil extracellular traps, and COL1A1. Targeted Serpinb3a knockdown delayed vascular occlusion, improved thrombolysis efficiency, and resulted in better neurological recovery. Collectively, these findings identify a neutrophil-driven mechanism underlying thrombus stiffening and establish SERPINB3 as both a prognostic biomarker and a promising therapeutic target in AIS. This project has been registered with the Chinese Clinical Trial Registration Platform (https://www.chictr.org.cn/index.html) and has successfully passed the review process (registration number: ChiCTR2300077911).

Animals↗

PubMed2026

Comprehensive transcriptomics and proteomics analysis of neointima formation in human saphenous vein: implications for bypass graft disease.

Human saphenous veins (SVs) are widely used as grafts in coronary artery bypass (CABG) surgery but often fail due to neointima formation. Little is known, however, regarding the cellular, transcriptomic, and proteomic dynamics of neointima formation in human veins. Here, we performed transcriptomics and proteomics analysis in an ex vivo tissue culture model of neointima formation in human SVs procured for CABG surgery. Histological examination demonstrated significant elastin degradation and neointima formation (indicated by increased neointima area and neointima-to-media ratio) in SVs subjected to tissue culture. Analysis of data from 72 patients suggests that the progression of SV remodeling and neointima formation differs according to sex and body mass index, which is negatively associated with neointima formation in males only. RNA sequencing demonstrated upregulation of proinflammatory and proliferation-related genes during neointima formation and identified novel processes, including increased cellular stress and DNA damage responses, reflecting tissue trauma associated with vein harvesting. Proteomic analysis identified upregulated extracellular matrix-related and coagulation/thrombosis proteins and downregulated metabolic proteins. Spatial transcriptomics, used to infer regionally enriched gene expression, suggested dynamic alterations in fibroblast and vascular smooth muscle cell (VSMC) states during neointima formation. Specifically, we identified the emergence of HES1+ and matrix metalloproteinase 2- and 14-positive (MMP2+/MMP14+) expression in VSMCs and fibroblasts, respectively, during neointima formation. Furthermore, our data suggest that MIR647, identified through screening, maintains VSMC contractile gene expression. Our findings suggest dynamic transcriptomic and proteomic changes during neointima formation in human veins and provide useful mechanistic information for the pathogenesis of SV graft disease.NEW & NOTEWORTHY Using multiomics and spatial transcriptomics, we uncover dynamic molecular and cellular changes driving neointima proliferation in human saphenous veins, the most common conduit for bypass surgery. Our study highlights sex- and body mass index-associated differences, novel fibroblast and smooth muscle cell states, and a role for microRNA-647 in preserving vascular contractile phenotype. These findings provide new insight into the mechanisms of vein graft failure and may guide future strategies to improve coronary bypass outcomes.

Humans↗

PubMed2025

Tribus: semi-automated discovery of cell identities and phenotypes from multiplexed imaging and proteomic data.

MOTIVATION: Multiplexed imaging and single-cell analysis are increasingly applied to investigate the tissue spatial ecosystems in cancer and other complex diseases. Accurate single-cell phenotyping based on marker combinations is a critical but challenging task due to (i) low reproducibility across experiments with manual thresholding, and, (ii) labor-intensive ground-truth expert annotation required for learning-based methods. RESULTS: We developed Tribus, an interactive knowledge-based classifier for multiplexed images and proteomic datasets that avoids hard-set thresholds and manual labeling. We demonstrated that Tribus recovers fine-grained cell types, matching the gold standard annotations by human experts. Additionally, Tribus can target ambiguous populations and discover phenotypically distinct cell subtypes. Through benchmarking against three similar methods in four public datasets with ground truth labels, we show that Tribus outperforms other methods in accuracy and computational efficiency, reducing runtime by an order of magnitude. Finally, we demonstrate the performance of Tribus in rapid and precise cell phenotyping with two large in-house whole-slide imaging datasets. AVAILABILITY AND IMPLEMENTATION: Tribus is available at https://github.com/farkkilab/tribus as an open-source Python package.

Proteomics↗

PubMed2001

Alternative RNA splicing in the nervous system.

Tissue-specific alternative splicing profoundly effects animal physiology, development and disease, and this is nowhere more evident than in the nervous system. Alternative splicing is a versatile form of genetic control whereby a common pre-mRNA is processed into multiple mRNA isoforms differing in their precise combination of exon sequences. In the nervous system, thousands of alternatively spliced mRNAs are translated into their protein counterparts where specific isoforms play roles in learning and memory, neuronal cell recognition, neurotransmission, ion channel function, and receptor specificity. The essential nature of this process is underscored by the finding that its misregulation is a common characteristic of human disease. This review highlights the current views of the biological phenomenon of alternative splicing, and describes evidence for its intricate underlying biochemical mechanisms. The roles of RNA binding proteins and their tissue-specific properties are discussed. Why does alternative splicing occur in cosmic proportions in the nervous system? How does it affect integrated cellular functions? How are region-specific, cell-specific and developmental differences in splicing directed? How are the control mechanisms that operate in the nervous system distinct from those of other tissues? Although there are many unanswered questions, substantial progress has been made in showing that alternative splicing is of major importance in generating proteomic diversity, and in modulating protein activities in a temporal and spatial manner. The relevance of alternative splicing to diseases of the nervous system is also discussed.

Alternative Splicing↗

PubMed2026

Integrated analysis of amide proton transfer weighted MRI and proteomics uncovers altered protein dynamics in glioblastoma.

PURPOSE: Elevated amide proton transfer-weighted (APTw) MRI signals in glioblastoma (GBM) are often linked to increased intracellular mobile proteins, but the associated molecular patterns in human tissue remain unclear. We examined the relationship between regional APTw features and cellular protein composition and profiled proteomic differences between tumor and peritumoral tissue. METHODS: In this single-center prospective study, preoperative MRI data were integrated with intraoperative neuronavigation for 12 image-guided tissue samples (8 tumor and 4 peritumoral). Total, cytoplasmic, and nuclear proteins were quantified using bicinchoninic acid (BCA) assay. Data-independent acquisition (DIA) proteomics identified exploratory differentially expressed proteins (DEPs), followed by functional enrichment and protein-protein interaction (PPI) network analyses. Transcript-level expression patterns and survival associations were queried in The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) datasets to provide indirect external clinical context. RESULTS: Tumor regions showed higher APTw signals than peritumoral regions (p < 0.001) and increased cytoplasmic protein concentration (p < 0.05), without a corresponding increase in total or nuclear protein levels. DIA identified 654 DEPs. Further analysis highlighted 36 higher-significance DEPs, and prioritized 12 hub proteins in the PPI network. In public transcriptomic datasets, ERBB2, RUNX1, and SHC1 showed higher expression in GBM and were associated with poorer overall survival. CONCLUSION: These findings suggest that elevated APTw signal in GBM may be associated with increased cytoplasmic protein content and distinct proteomic alterations. This imaging-proteomic framework provides exploratory regional context for future mechanistic and follow-up studies, but larger, spatially matched and independently validated cohorts are required to confirm the molecular contributors to APTw contrast.

Humans↗

PubMed2025

Unveiling the mechanism of micro-and-nano plastic phytotoxicity on terrestrial plants: A comprehensive review of omics approaches.

Micro-and-nano plastics (MNPs) are pervasive in terrestrial ecosystems and represent an increasing threat to plant health; however, the mechanisms underlying their phytotoxicity remain inadequately understood. MNPs can infiltrate plants through roots or leaves, causing a range of toxic effects, including inhibiting water and nutrient uptake, reducing seed germination rates, and impeding photosynthesis, resulting in oxidative damage within the plant system. The effects of MNPs are complex and influenced by various factors including size, shape, functional groups, and concentration. Recent advancements in omics technologies such as proteomics, metabolomics, transcriptomics, and microbiomics, coupled with emerging technologies like 4D omics, phenomics, spatial transcriptomics, and single-cell omics, offer unprecedented insight into the physiological, molecular, and cellular responses of terrestrial plants to MNPs exposure. This literature review synthesizes current findings regarding MNPs-induced phytotoxicity, emphasizing alterations in gene expression, protein synthesis, metabolic pathways, and physiological disruptions as revealed through omics analyses. We summarize how MNPs interact with plant cellular structures, disrupt metabolic processes, and induce oxidative stress, ultimately affecting plant growth and productivity. Furthermore, we have identified critical knowledge gaps and proposed future research directions, highlighting the necessity for integrative omics studies to elucidate the complex pathways of MNPs toxicity in terrestrial plants. In conclusion, this review underscores the potential of omics approaches to elucidate the mechanisms of MNPs-phytotoxicity and to develop strategies for mitigating the environmental impact of MNPs on plant health.

Plants↗

PubMed2026

A spatially resolved genomic-molecular atlas of human white-matter microstructure.

Human white matter has been linked to inherited variation, circulating molecular state and brain disease, but these layers have rarely been mapped onto the same tract anatomy. Here we measured genetic effects along 6,090 atlas-aligned fiber pathways sampled at 609,000 locations in 72,185 UK Biobank participants, and integrated proteomic and metabolomic profiles within the same anatomical frame. Genetic effects were not whole-tract properties: each locus formed a spatial footprint along fiber trajectories, ranging from single locations to broad multi-tract patterns and reflecting regional polygenicity rather than tract heritability. This map identified 258, 186 and 298 previously unreported loci for fractional anisotropy, mean diffusivity and axial diffusivity; spatial patterns replicated in adults and 157 of 315 FA loci replicated in adolescence in ABCD. Mendelian randomization linked localized genetic effects to neurodegenerative and psychiatric traits, with Alzheimer's disease showing directional effects across 12 of 17 tracts. Multi-omic analyses identified 97 proteomic and 161 metabolomic associations, with the broadest signals from lipid metabolites including linoleic acid and phosphatidylcholines. The strongest lipid-metabolite and genetic signals converged in the corpus callosum, placing inherited variation, disease risk and systemic lipid metabolism on the same localized tract segments.

Journal Article↗