PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “niche models”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 recordsLinked to original sources
PubMed2025

Climatic data sources and limitations of ecological niche models impact the estimations of historical ranges and niche overlaps in distantly related Korean salamanders.

BACKGROUND: Ecological niche models (ENMs) and analyses of niche overlap/divergence have become popular methods in ecology and evolutionary biology. These analyses rely on environmental data available from several databases. However, the influence of data sources on these analyses is rarely tested. Here, we test the impact of climatic data choice on the prediction of current and Plio-Pleistocene suitable habitats for two distantly related, but broadly sympatric, salamanders endemic to the Korean Peninsula. We ran MaxEnt separately on WorldClim and CHELSA climate data. We then hindcasted ENMs to five time periods of the Plio-Pleistocene, bracketing the estimated intraspecific divergence times for these species. We then quantified the differences in predictions between WorldClim- and CHELSA-based models. Also, given the sympatry and similar habitat requirements of the two species, we tested for niche overlaps using niche identity and background tests and tested the sensitivity of the results to climatic data choice. RESULTS: The ENMs successfully predicted contemporary suitable habitats for the two species. However, the predictions were highly sensitive to climatic data choice as well as variable combinations. The hindcasted ENMs produced contrasting predictions depending on the choice of climatic dataset and failed to predict suitable habitats for some Pleistocene time periods regardless of the climatic data choice. The niche analyses were also sensitive to climatic data choice, with results suggesting either niche overlaps or divergence depending on the climatic dataset used for the analyses. CONCLUSIONS: Our study highlights the influence of climatic data choice on the outcomes of ENMs and niche analyses. Our results also underscore the limitations of macroclimate-based ENMs, especially when the species is likely buffered from macroclimatic changes by microhabitat. We argue for the need for additional ecological, ecophysiological, and population genomic studies to better understand the range formation of these enigmatic species.

Animals↗
PubMed2026

The evolutionary origins of the parthenogenetic lizard Aspidoscelis tesselatus.

Most vertebrate species reproduce sexually. The whiptail lizards (Aspidoscelis) are a notable exception; at least 11 of the 45 recognized species are parthenogenetic. Here, we focus on one such species (Aspidoscelis tesselatus) as a case study to understand how parthenogenetic species originate and evolve. Using genome-wide sequence data and ecological niche modelling, we find that A. tesselatus likely arose from a single hybrid speciation event between A. scalaris and A. marmoratus less than 500,000 years ago. The geographic ranges of A. tesselatus and its parental species overlap currently, and niche modelling shows this zone of sympatry was even broader during the period when A. tesselatus likely formed. We additionally show evidence that A. tesselatus has a dynamic genome post-formation, with de novo mutations, introgression, and double-strand break associated events all contributing to variation within the species. These results show that asexual lineages can continue to be shaped by ongoing genomic and ecological dynamics, illuminating the processes that influence transitions in reproductive mode.

asexuality↗
PubMed2025

Conservation genomics of a threatened subtropical Rhododendron species highlights the distinct conservation actions required in marginal and admixed populations.

With the impact of climate change and anthropogenic activities, the underlying threats facing populations with different evolutionary histories and distributions, and the associated conservation strategies necessary to ensure their survival, may vary within a species. This is particularly true for marginal populations and/or those showing admixture. Here, we re-sequence genomes of 102 individuals from 21 locations for Rhododendron vialii, a threatened species distributed in the subtropical forests of southwestern China that has suffered from habitat fragmentation due to deforestation. Population structure results revealed that R. vialii can be divided into five genetic lineages using neutral single-nucleotide polymorphisms (SNPs), whereas selected SNPs divide the species into six lineages. This is due to the Guigu (GG) population, which is identified as admixed using neutral SNPs, but is assigned to a distinct genetic cluster using non-neutral loci. R. vialii has experienced multiple genetic bottlenecks, and different demographic histories have been suggested among populations. Ecological niche modeling combined with genomic offset analysis suggests that the marginal population (Northeast, NE) harboring the highest genetic diversity is likely to have the highest risk of maladaptation in the future. The marginal population therefore needs urgent ex situ conservation in areas where the influence of future climate change is predicted to be well buffered. Alternatively, the GG population may have the potential for local adaptation, and will need in situ conservation. The Puer population, which carries the heaviest genetic load, needs genetic rescue. Our findings highlight how population genomics, genomic offset analysis, and ecological niche modeling can be integrated to inform targeted conservation.

Rhododendron↗
PubMed2026

Have we entered a 'post-model' era in plant biology?

Models such as arabidopsis (Arabidopsis thaliana) have underpinned genomic and physiological research in plant science. Advances in genome sequencing, pangenomics, and genome editing have prompted claims of a 'post-model' era, with model-crops and crops such as rice and bread wheat combining agricultural relevance with experimental tractability. We argue that the 'simplicity-to-complexity' approach remains valid, although model systems have evolved. Arabidopsis remains indispensable for interpreting multi-omics data, testing developmental hypotheses, and generating mechanistic insights difficult to obtain in crops. Linking these strengths to model-crops adds translational value by bridging discovery and breeding, while niche models such as Brachypodium distachyon and legumes address grass cell wall biology and nitrogen fixation. Future progress depends on diverse species with complementary strengths across fundamental and applied plant biology.

arabidopsis↗
PubMed2026

Genetically diverse populations hold the keys to climatic adaptation in the Western barn owl (Tyto alba).

Although local adaptation influences species distributions, its role in driving evolutionary resilience under climate change remains unclear. Current predictive models focus on genetic adaptation to present climates, providing limited insight into future adaptive capacity. We hypothesise that historical responses to climatic shifts can reveal candidate loci for local adaptation in the future. Combining ecological niche modelling and genomic analyses, we investigate spatiotemporal patterns and mechanisms of local adaptation of the Western Palearctic barn owl (Tyto alba). Ecological modelling reveals that barn owls now occupy a broader climatic niche than during the Last Glacial Maximum. Genomic analyses indicate ongoing adaptation, with regions under selection linked to environmental factors across all populations. We find that local adaptation drives evolutionary changes across populations, enabling colonisation of new habitats and shaping responses to climate change in resident populations. We show that standing genetic diversity plays a crucial role in adaptation to past, present, and future environmental shifts.

Animals↗
PubMed2026

Genomic-Environmental Integration Predicts Climate Vulnerability and Adaptive Potential of Tibetan Plateau Herpetofauna.

The herpetofauna of the Tibetan Plateau, home to Earth's highest-elevation ectothermic vertebrates, face escalating threats from rapid climate change. However, conventional conservation strategies often overlook intraspecific genetic variation and adaptive potential, limiting their predictive accuracy and effectiveness. Here, we integrate whole-genome resequencing data with environmental modeling to assess climate vulnerability in two endemic species: Nanorana parkeri (Tibetan frog) and Thermophis baileyi (hot-spring snake). Results suggest that the western populations of the two species exhibit higher genomic offsets under future climate, while some eastern populations of the Tibetan frog face a decrease in niche suitability, and the hot-spring snake will experience varying degrees of loss of suitable habitats. Furthermore, heterozygosity, genetic diversity, and genetic load demonstrate significant correlations with genomic offsets, suggesting that low genetic diversity and high genetic load may weaken the potential to adapt to environmental changes. Based on a genome-niche index that combines genomic offsets with niche suitability change, we identified evolutionary rescue populations that are potentially tolerant to climate change. Our findings underscore the importance of integrating genomic and environmental data to forecast the adaptive potential and enable effective conservation management of high-altitude herpetofauna under rapid climate change.

Animals↗
PubMed2025

Environmental Stresses Constrain Soil Microbial Community Functions by Regulating Deterministic Assembly and Niche Width.

Increasing evidence indicates that the loss of soil microbial α-diversity triggered by environmental stress negatively impacts microbial functions; however, the effects of microbial α-diversity on community functions under environmental stress are poorly understood. Here, we investigated the changes in bacterial and fungal α- diversity along gradients of five natural stressors (temperature, precipitation, plant diversity, soil organic C and pH) across 45 grasslands in China and evaluated their connection with microbial functional traits. By quantifying the five environmental stresses into an integrated stress index, we found that the bacterial and fungal α-diversity declined under high environmental stress across three soil layers (0-20 cm, 20-40 cm and 40-60 cm). Metagenomic-based analyses showed that the diversity of functional genes decreased along the stress gradients. High stress enhanced the abundance of genes associated with broad functional categories (e.g., glycolysis/gluconeogenesis, TCA cycle, DNA replication/repair and cell growth/death) but reduced the abundance of genes linked to specialised functional categories (e.g., C, N, S and methane metabolism). Phylogenetic null models and niche analyses indicated that stochastic assembly processes predominated in high-diversity communities, in which bacterial and fungal taxa had a narrow ecological niche. However, in low-diversity communities, deterministic assembly processes were dominant, and taxa had wide niches, correlating with the reduction in gene abundance observed for broad and specialised functional categories. Given the essential role of the microbiome in regulating ecosystem functions, our findings suggest that low-diversity-induced deterministic community assembly processes and a wide niche under high environmental stress may regulate microbial functions. These findings emphasise the ecological mechanisms through which microbial biodiversity regulates terrestrial ecosystem functioning.

Soil Microbiology↗
PubMed2026

Genomic insights into local adaptation of indigenous chickens.

Indigenous chickens are an essential part of biodiversity and a vital protein resource to humans, yet global warming and environmental changes pose serious threats to their survival and productivity. Therefore, assessing population adaptive capacity under shifting environments is crucial for breeding resilient animals, and guiding conservation strategies. Here, we integrated ecological and whole-genome resequencing data from 1 022 chickens from 44 Chinese indigenous populations to reveal genomic signatures of local adaptation. From 87 agroclimatic variables, we identified eight dominant environmental factors including solar radiation, precipitation, diurnal temperature range, and five landcover variables (cropland areas, water areas, trees coverage, bare ground and shrubs coverage) that shape ecological niches of indigenous chickens. Landscape and comparative genomics analyses revealed both known and novel candidate genes, such as UNC80, PTPRO, NCOR2, CSF2RB, NXT2 and PALLD for the solar radiation, precipitation, diurnal temperature range, cropland areas, trees coverage and bare ground, respectively. Particularly, adaptive non-coding variants harbored in these genes exhibited spatial allelic changes across populations and acted as regulatory elements via chromatin accessibility and DNA methylation, influencing adaptation in a tissue-specific manner. Our findings underscore the rich genetic diversity of Chinese indigenous chickens and provide new insights into genomic mechanisms of local adaptation, offering valuable references for domestic animal breeding, conservation, and climate resilience.

Animals↗
PubMed2025

Tumors hijack macrophages for iron supply to promote bone metastasis and anemia.

Bone marrow is both a primary site for hematopoiesis and a fertile niche for metastasis. The mechanism of the common occurrence of anemia among patients with bone metastasis remains poorly understood. Here, we show that a specialized population of VCAM1+CD163+CCR3+ macrophages, normally essential for erythropoiesis by transporting iron to erythroblasts, are highly enriched in the bone metastatic niche in mouse models. Tumor cells hijack these macrophages for iron supply, reducing iron availability for erythroblasts, impairing erythropoiesis, and contributing to anemia. Increased iron supply enables tumor cells to produce hemoglobin in response to hypoxia, mimicking erythroblasts. We identify macrophages with similar iron-transporting features in human bone metastases and show that elevated HBB expression correlates with increased risk of bone metastasis. These findings establish iron-transporting macrophages as an essential component of the metastatic bone niche, revealing a critical interplay between immune cells, metal metabolism, and tumor cell plasticity in driving metastasis and anemia.

Animals↗
PubMed2025

Novel Predictive Spatial Biomarker in Non-Small Cell Lung Carcinoma: The Diversity of Niches Unlocking Treatment Sensitivity (DONUTS).

Probabilistic spatial modelling techniques developed on large-scale tumor-immune Atlases (~35M individually mapped cells; 50,000 high power fields) were used to characterize predictive features of treatment-responsive lung cancer. We identified CD8+FoxP3+ cell density as a robust pre-treatment biomarker for outcomes across disease stages and therapy types. In parallel, single-cell RNAseq studies of CD8+FoxP3+ T-cells revealed an activated, early effector phenotype, substantiating an anti-tumor role, and contrasting with CD4+FoxP3+ T-regulatory cells. A spatial biomarker was developed using an empirical probabilistic model to define the immediate cell neighbors or niche surrounding CD8+FoxP3+ cells and proximity to the tumor-stromal boundary. The resultant 'Diversity of Niches Unlocking Treatment Sensitivity (DONUTS)' are more prevalent than the CD8+FoxP3+ cells themselves, mitigating sampling error in small biopsies. Further, the DONUTS only require four markers, are additive to PD-L1, and associate with tertiary lymphoid structure counts. Taken together, the DONUTS represent a next-generation predictive biomarker poised for clinical implementation.

AstroPath↗
PubMed2026

Metagenome-scale modeling to assess microbiome metabolic complementarity for precision microbiota transplantation therapies.

Fecal microbiota transplantation (FMT) holds therapeutic promise beyond recurrent Clostridioides difficile infection, but clinical outcomes remain unpredictable and donor-selection strategies remain limited, in part because the role of donor‒recipient metabolic interactions in shaping the post-FMT community remains poorly understood. Here, we leverage metagenome-scale metabolic modeling to quantify metabolic niche complementarity between donor and recipient microbiomes and predict post-FMT community composition. Using MICOM-derived metabolic models, we show that donor genomes whose metabolic flux profiles are more dissimilar from the recipient community colonize at significantly higher rates in a murine FMT model. In a human IBS trial, the same metric predicted post-FMT community composition via leave-one-out cross-validation and captured known disease-associated alterations in short-chain fatty acid, sulfur, and gas metabolism. We then performed 2,548 in silico FMT simulations between IBS-D/M patients and donors from the OpenBiome biobank to evaluate personalized donor screening, identifying super-donors characterized by high taxonomic diversity, broad metabolic niche coverage, and community interaction networks dominated by cross-feeding rather than competition. Together, these results support metabolic niche complementarity as a potential determinant of post-FMT community composition and provide a mechanistic basis for evaluating donor-recipient metabolic compatibility. This framework offers a scalable approach for generating testable hypotheses for personalized donor selection.

Fecal Microbiota Transplantation↗
PubMed2026

Multi-omics identification and functional validation of signal regulatory protein gamma as a prognostic biomarker and immune regulator in head and neck squamous cell carcinoma.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) comprises biologically diverse tumors, and durable responses to immune-checkpoint blockade are achieved by only a subset of patients. There remains a need for markers that connect clinical outcome with malignant-cell phenotypes and tissue-level immune organization. METHODS: We integrated The Cancer Genome Atlas HNSCC cohort (TCGA-HNSC), five Gene Expression Omnibus (GEO) validation cohorts, single-cell RNA sequencing, Visium spatial transcriptomics, cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq)-informed protein-potential inference, pharmacogenomic screening, genetic-risk analysis and experimental validation. A reconstructed 296-pipeline survival modelling framework was used to prioritize prognostic hub genes across validation-cohort-specific analyses. RESULTS: SIRPG was repeatedly ranked among the top ten selected genes in all five validation cohorts. At single-cell resolution, SIRPG-high tumor cells showed stronger malignant-cell features, immune-inhibitory and metabolic programs, Scissor-positive risk association, CLCA2/P53-related perturbation signals and inferred SIRPG-CD47/signal regulatory protein (SIRP) communication. Spatial analyses placed this axis within an immune-checkpoint-coupled niche, supported by Maxspin/multiview intercellular spatial modelling (MISTy) spatial coupling, communication analysis by optimal transport (COMMOT)-inferred CD47-SIRPG communication and scProTrans-inferred CD47/SIRPG protein-potential overlap. Functionally, SIRPG knockdown reduced HNSCC cell viability and increased apoptosis, whereas re-expression of short hairpin RNA (shRNA)-resistant SIRPG restored the CLCA2-BAX/BCL2 protein response. CONCLUSION: Together, these findings identify SIRPG as an immune-related prognostic hub and context-dependent tumor-cell regulator associated with apoptosis, immune communication and spatial microenvironmental organization in HNSCC.

Humans↗
PubMed2026

Patient-derived models of prostate cancer: Capturing tumour complexity from initiation to metastasis.

Prostate cancer is a growing global health challenge. To identify new ways to improve patient care, researchers need a variety of preclinical models that faithfully recapitulate human tumours across the disease continuum, from initiation to metastasis. These complementary models include primary cultures of prostate epithelial cells (PrECs), co-cultures, patient-derived explants (PDEs), patient-derived organoids (PDOs) and patient-derived xenografts (PDXs). Collectively, these models enable researchers to study tumour biology and therapeutic responses in clinically relevant contexts. Yet, there is still a need to improve the fidelity of preclinical models to human tumours by integrating diverse cell types from the tumour microenvironment and mimicking biomechanical features. By improving culture methods with matrix components that resemble the tumour microenvironment and new formulations of media that imitate human plasma, in vitro models will more accurately reflect human physiology, nutrient availability, and metabolism. In time this may reduce the reliance on animal testing through organ-on-chip and related techniques. These more complex models are suited to more detailed experimental readouts, including single-cell and spatial analyses. Intravital imaging also enables dynamic visualisation of cell-cell interactions and treatment responses in vivo. Collectively, these approaches are facilitating a shift towards sophisticated models that capture patients' tumour heterogeneity, different cellular niches, and provide opportunities to carefully study tumorigenesis, metastasis, lineage plasticity, and therapy resistance. In this review, we discuss the current progress and future directions for patient-derived models of prostate cancer, highlighting how they can be generated, refined, characterised and shared to accelerate the worldwide effort in translational research.

Humans↗
PubMed2025

Understanding proneural-mesenchymal transition using patient-derived glioma stem-like cell (GSC) organoids and engineered extracellular matrix.

Glioblastoma multiforme (GBM) is a highly aggressive, angiogenic WHO grade IV glioma marked by rapid progression, therapeutic resistance, and poor prognosis. A defining feature of GBM is the presence of glioma stem-like cells (GSCs), which reside in specialized perivascular niches and drive tumor progression, recurrence, and therapeutic resistance. The blood-brain barrier, coupled with the complex and dynamic tumor microenvironment, poses significant challenges for both treatment and mechanistic investigation. Current in vitro GBM models inadequately recapitulate the structural and biochemical cues of the native perivascular niche due to the absence of functional vasculature and brain-mimetic extracellular matrix (ECM), limiting their physiological relevance and predictive power. To address the limitations of existing in vitro GBM models, we developed a patient-derived glioma stem cells (GSC) derived Matrigel spheroid system that transitions into organoids and enables integration into engineered microenvironments. Our model incorporates GSC organoids representing proneural and mesenchymal GBM subtypes, a synthetic engineered extracellular matrix (eECM), and endothelial cells (ECs) seeded on the matrix surface. We evaluated the expression of subtype-specific, pro-angiogenic, stemness, and differentiation markers under increasingly complex co-culture conditions. Our results show that Matrigel-derived GSC spheroids progressively differentiate into organoids over two weeks, with significantly enhanced expression of cell-specific markers in the presence of ECs. Encapsulation of these organoids within eECM, combined with EC co-culture, further promoted cellular invasion and induction of GBM associated genes. This in situ encapsulation strategy enables real-time observation of GSC behavior in a tunable microenvironment that mimics key features of the native tumor niche. Together, this platform provides a physiologically relevant and modular in vitro system for investigating GBM pathophysiology. It holds promise for uncovering tumor-specific cellular dependencies, studying GSC-vascular interactions, and conducting high-throughput drug screening under controlled, biomimetic conditions.

Engineered extracellular matrix↗
PubMed2025

Biomathematical enzyme kinetics model of prebiotic autocatalytic RNA networks: degenerating parasite-specific hyperparasite catalysts confer parasite resistance and herald the birth of molecular immunity.

Catalysis and specifically autocatalysis are the quintessential building blocks of life. Yet, although autocatalytic networks are necessary, they are not sufficient for the emergence of life-like properties, such as replication and adaptation. The ultimate and potentially fatal threat faced by molecular replicators is parasitism; if the polymerase error rate exceeds a critical threshold, even the fittest molecular species will disappear. Here we have developed an autocatalytic RNA early life mathematical network model based on enzyme kinetics, specifically the steady-state approximation. We confirm previous models showing that these second-order autocatalytic cycles are sustainable, provided there is a sufficient nucleotide pool. However, molecular parasites become untenable unless they sequentially degenerate to hyperparasites (i.e. parasites of parasites). Parasite resistance-a parasite-specific host response decreasing parasite fitness-is acquired gradually, and eventually involves an increased binding affinity of hyperparasites for parasites. Our model is supported at three levels; firstly, ribozyme polymerases display Michaelis-Menten saturation kinetics and comply with the steady-state approximation. Secondly, ribozyme polymerases are capable of sustainable auto-amplification and of surmounting the fatal error threshold. Thirdly, with growing sequence divergence of host and parasite catalysts, the probability of self-binding is expected to increase and the trend towards cross-reactivity to diminish. Our model predicts that primordial host-RNA populations evolved via an arms race towards a host-parasite-hyperparasite catalyst trio that conferred parasite resistance within an RNA replicator niche. While molecular parasites have traditionally been viewed as a nuisance, our model argues for their integration into the host habitat rather than their separation. It adds another mechanism-with biochemical precision-by which parasitism can be tamed and offers an attractive explanation for the universal coexistence of catalyst trios within prokaryotes and the virosphere, heralding the birth of a primitive molecular immunity.

Kinetics↗
PubMed2025

Reducing redundancy and enhancing accuracy through a phylogenetically-informed microbial community metabolic modeling approach.

MOTIVATION: Metabolic modeling has emerged as a powerful tool for predicting community functions. However, current modeling approaches face significant challenges in balancing the metabolic trade-offs between individual and community-level growth. In this study, we investigated the effect of metabolic relatedness among taxa on growth rate calculations by merging related taxa based on their metabolic similarity, introducing this approach as PhyloCOBRA. RESULTS: This approach enhanced the accuracy and efficiency of microbial community simulations by combining genome-scale metabolic models (GEMs) of closely related organisms, aligning with the concepts of niche differentiation and nestedness theory. To validate our approach, we implemented PhyloCOBRA within the MICOM and OptCom package (creating PhyloMICOM and PhyloOptCom, respectively), and applied it to metagenomic data from 186 individuals and four-species synthetic community (SynCom). Our results demonstrated significant improvement in the accuracy and reliability of growth rate predictions compared to the standard methods. Sensitivity analysis revealed that PhyloMICOM models were more robust to random noise, while Jaccard index calculations showed a reduction in redundancy, highlighting the enhanced specificity of the generated community models. Furthermore, PhyloMICOM reduced the computational complexity, addressing a key concern in microbial community simulations. This approach marks a significant advancement in community-scale metabolic modeling, offering a more stable, efficient, and ecologically relevant tool for simulating and understanding the intricate dynamics of microbial ecosystems. AVAILABILITY AND IMPLEMENTATION: PhyloCOBRA implementations are available as extensions to the MICOM packages and can be accessed at https://github.com/sepideh-mofidifar/PhyloCOBRA.

Phylogeny↗
PubMed2026

Spatially Contextualized Integrative Genomics Highlights Neuronal and Glial Regulatory Programs in Low Back Pain.

PURPOSE: Low back pain (LBP) is a heterogeneous pain condition with a measurable genetic contribution, but the genes, brain cell types, and spatial tissue contexts through which inherited risk is expressed remain unclear. We aimed to define cell-type-specific and spatially contextualized genetic mechanisms underlying LBP. METHODS: FinnGen R12 LBP GWAS summary statistics (42,521 cases and 353,224 controls) were integrated with brain single-nuclei eQTL data across eight major brain cell classes. We evaluated genome-wide polygenic signal using LDSC, prioritized genes using MAGMA and PoPS, and performed brain cell-type-specific eQTL-anchored Mendelian randomization, primarily based on single-instrument Wald ratio estimates, followed by Bayesian colocalization. Spatial genetic mapping was conducted using gsMap in an E16.5 murine embryonic atlas and two adult human lumbar spinal cord Visium sections. Selected candidates were assessed by RT-qPCR in neuronal-like and astroglial-like inflammatory cell models. RESULTS: LDSC supported interpretable polygenic signal for LBP. MAGMA and PoPS showed partial gene-level convergence, with TCF4 and TMEFF2 supported by both approaches. Across 1641 tested gene-cell type exposures, significant eQTL-anchored MR associations were concentrated in excitatory neurons, oligodendrocytes, inhibitory neurons, and astrocytes. Integrated eQTL-anchored MR, colocalization, and gene-prioritization evidence highlighted CLEC18A, QPRT, and GMPPB as higher-priority non-MHC candidates with moderate, but not strong, colocalization support. gsMap localized LBP-associated enrichment to neuroaxis-related embryonic regions, including brain, spinal cord, sympathetic nerve, and dorsal root ganglion, and to neuronal-like niches in adult lumbar spinal cord. RT-qPCR showed model-dependent expression changes, with QPRT and LGI4 preferentially responsive in neuronal-like SH-SY5Y cells and GMPPB and DPYSL5 responsive in astroglial-like U251 cells. CONCLUSION: These findings support neuronal and glial regulatory programs as plausible contributors to LBP genetic susceptibility and highlight CLEC18A, QPRT, and GMPPB as higher-priority non-MHC candidates with moderate colocalization support. The results provide a spatially contextualized framework for candidate prioritization in LBP, while emphasizing the need for larger cell-type-specific eQTL resources and functional validation before therapeutic or mechanistic conclusions can be drawn.

Mendelian randomization↗