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At least 19 recordsLinked to original sources

PubMed2026

Protective TMEM106B-rs3173615 delays age at onset in GRN mutation carriers.

One of the major causative genes involved in Frontotemporal dementia (FTD) is Granulin (GRN), encoding for Progranulin (PGRN). GRN mutation carriers show a substantial heterogeneity with high variability in age at onset and pathological presentation, even within the same family or identical mutations, suggesting the presence of additional genetic factors. Single nucleotide polymorphisms in the Transmembrane protein 106B (TMEM106B) locus were identified as a genetic risk-associated factor for FTD. The top variant identified was the non-coding rs1990622, with the major allele (T) associated with an increased risk to develop FTD, while subjects with the minor allele (C) were less likely to develop disease, suggesting a protective effect. In this study, we investigate in a large Italian cohort of GRN mutation carriers, how the coding variant TMEM106B-rs3173615, in linkage disequilibrium with rs1990622, modulates age at onset, survival, and PGRN levels, including, up to date, the highest sample size of homozygous protective allele carriers. Genetic screening for TMEM106B-rs3173615 was performed on a total of 187 GRN mutation carriers, comprising 131 FTD patients and 56 pre-symptomatic subjects. Individuals with the protective genotype (GG) had a risk of FTD onset reduced by 80%, with a median age at onset of 77 years compared to a median age at onset of 63 years for individuals without the protective genotype. TMEM106B-rs3173615 acts as a genetic modifier of age at onset in the presence of GRN mutations and could be considered in clinical practice to optimize risk stratification for FTD.

Humans↗

PubMed2026

GRN rs5848 variant associates with TDP-43 pathology and cancer in opposite directions.

Epidemiologic studies have reported that cancer survivors have a relatively low risk of developing dementia, but the mechanisms underlying that inverse relationship are mostly unknown. The Granulin (GRN) gene single nucleotide variant rs5848 T allele is associated with increased risk of limbic-predominant age-related TDP-43 encephalopathy neuropathologic change (LATE-NC) and hippocampal sclerosis of aging (HS-Aging). The T allele is also associated with lower expression of the cognate protein progranulin (PGRN), which is a mitogen implicated in neoplasia. We examined whether the rs5848 variant associated with LATE-NC/HS-Aging pathology and cancer in the same cohort. This study leveraged genotype data from the Alzheimer's Disease Genomics Consortium (n = 8121) and the Alzheimer's Disease Sequencing Project (n = 3231), with cancer history and neuropathology data drawn from the National Alzheimer's Coordinating Center. The rs5848 T allele was associated with higher odds of LATE-NC (p < 0.001) and was also associated with lower odds of cancer (p = 0.012). Established TMEM106B, APOE, and BIN1 risk alleles for Alzheimer's disease showed no associations with cancer, implying that the GRN-related associations could not be completely explained by selection bias in the study sample. The finding of a specific allele with opposite correlative impact on cancer risk and dementia-related pathology has potential therapeutic implications.

Humans↗

PubMed1979

Cardio-inhibitory mechanism in the gigantocellular reticular nucleus of the medulla oblongata.

A cardio-inhibitory mechanism was localized in the ventral part of the medullary gigantocellular reticular nucleus (GRN) in chloralose--urethane anesthetized cats. Stimulation of this mechanism produced an average 58.9% reduction of the heart rate (calculated from 55 responsive points having more than 40% reduction) associated mostly with hypotension, or no change or occasionally a slight increase of the arterial blood pressure. Midcollicular decerebration did not affect this bradycardia. The bradycardia following GRN stimulation of either side by a pair of symmetrically placed electrodes was reduced slightly but equally by: (1) sectioning either side of the vagus nerve; (2) hemisection at a level 4 mm rostral of the obex on either side; or (3) partial destruction of the dorsal motor (DM) and solitary (SN) nuclei on either side. Additional section of the vagus nerve on the opposite side completely abolished the bradycardiac response. Besides, the GRN bradycardia was also slightly but equally attenuated by making a midline bisection in a length extending from 10 to 4 mm rostral of the obex. Additional section of the vagus nerve on either side abolished completely only the bradycardia following electrical stimulation of the GRN on the same side, while that following electrical stimulation of the GRN on the opposite side remained unaffected. On the other hand, the GRN bradycardia was not affected by simply making a caudal midline bisection in a length extending from 3 or 4 mm rostral to 2 mm caudal of the obex. The results suggest: (1) the ventral part of the GRN is a cardio-inhibitory mechanism independent of the higher center; (2) the efferent pathway descends both ipsilaterally and contralaterally and makes synaptic relay in the areas of DM and/or SN and finally exits via the vagus nerves; (3) the fibers decussate rostral to the level 4 mm rostral of the obex; and (4) both ipsilateral and contralateral descending fibers appeared to exert the same degree of suppressive influence in the heart rate.

Animals↗

PubMed1979

Sigma subunit of Escherichia coli RNA polymerase affects the function of lambda N gene.

A new class of Escherichia coli mutants, referred to as grn, has been isolated by localized mutagenesis. These mutations affect the sigma subunit of DNA-dependent RNA polymerase (ribonucleoside 5'-triphosphate:RNA nucleotidyltransferase, EC 2.7.7.6) by abolishing the expression of the lambda N gene, and they are closely lniked to dnaG in the order dnaG-grn-uxaA. Detailed study of one such mutant, grn1, yielded the following results: (i) grn1 is a single mutation and the mutant cell shows cold-sensitivity in growth; (ii) the Grn phenotype of the mutant can easily be suppressed by secondary mutations in the beta subunit gene of RNA polymerase; (iii) purified holoenzyme of RNA polymerase isolated from the mutant showed an altered salt-dependency in vitro, and the mixed reconstitution of the mutant with the wild-type subunits showed that the sigma subunit of the grn1 mutant is altered; (iv) lambda phage mutants (lambda grg), which overcome the grn mutation, can be classified into two groups, the "nin-deletion" and the "N-mutant" groups (both of these are also able to grow on the previously described groN mutant of Georgopoulos and nusAB of Friedman); (iv) the mutant polymerase transcribed 12S as well as 7S RNA from lambda DNA in the presence of the rho factor in vitro. These results indicate that the grn mutation alters the sigma subunit of RNA polymerase and that the sigma subunit participates in activating the N-mediated antitermination mode of lambda phage transcription.

Bacteriophage lambda↗

PubMed2026

Neurodegeneration risk variants promote lysosomal TMEM106B fibril accumulation.

Variants in TMEM106B and GRN, which encode lysosomal proteins, interact through unknown mechanisms to increase the risk of age-related cognitive decline and neurodegeneration. Here, we show that these variants converge on a single molecular intermediate: the cleaved intra-lysosomal fibril core of TMEM106B, a precursor to amyloid fibrils that accumulate in the aging brain. A protein-coding TMEM106B risk variant (p.T185) drives fibril core accumulation by impairing its degradation and GRN risk variants amplify this effect. Mice over-expressing the fibril core develop hallmarks of neurodegeneration, and cryo-electron tomography reveals intra-lysosomal fibrils in cultured neurons, mice, and diseased human brain. In GRN-mutation carriers, in whom fibril burden is greatest, fibrils extrude through ruptured lysosomal membranes. These findings identify intra-lysosomal TMEM106B fibrillization as a convergent neurodegeneration mechanism and potential therapeutic target.

Journal Article↗

PubMed2027

Inferring Gene Regulatory Networks in Stem Cells: Methods and Applications.

Gene regulatory networks (GRNs) represent the complex interplay of transcription factors, regulatory elements, and target genes that orchestrate cellular identity and function, playing a crucial role in the differentiation and maintenance of stem cells. This chapter provides an overview of experimental and computational methodologies for inferring GRNs, with particular emphasis on single-cell approaches. We first review key experimental techniques for detecting transcription factor binding sites, chromatin accessibility, and DNA motifs, alongside essential databases that support GRN reconstruction. We then introduce computational inference methods that can be categorized into four principal frameworks: correlation-based approaches, regression and machine learning models, probabilistic and deep learning methods, and integrative or message-passing frameworks. To illustrate practical application, we present a case study applying the pySCENIC workflow to a peripheral blood mononuclear cell single-cell RNA sequencing dataset from mouse, demonstrating how regulon-based analysis can reveal cell-type-specific regulatory programs. This chapter aims to serve as a practical guide for researchers seeking to understand and implement GRN inference methodologies in stem cell biology and related fields.

Gene Regulatory Networks↗

PubMed2026

Modelling the effects of biological intervention in a dynamical gene network.

Cellular response to environmental and internal signals can be modeled by dynamical gene regulatory networks (GRN). In the literature, three main classes of gene network models can be distinguished: (1) non-quantitative (or data-based) models which do not describe the probability distribution of gene expressions; (2) quantitative models which fully describe the probability distribution of all genes co-expression; and (3) mechanistic models which allow for a causal interpretation of gene interactions. We propose two rigorous frameworks to model gene alteration in a dynamical GRN, depending on whether the network model is quantitative or mechanistic. We explain how these models can be used for design of experiment, or, if additional alteration data are available, for validation purposes or to improve the parameter estimation of the original model. We apply these methods to the Gaussian graphical model, which is quantitative but non-mechanistic, and to mechanistic models of Bayesian networks and penalized linear regression.

Gene Regulatory Networks↗

PubMed2026

Protamine gene expression is associated with sperm motility in rams: An integrative experimental and gene network analysis.

Protamine 1 (PRM1) and protamine 2 (PRM2) are essential regulators of sperm chromatin condensation and genome integrity, and their dysregulation has been associated with impaired male fertility. However, their role in rams remains insufficiently characterized. This study investigated the relationship between protamine gene expression and semen quality in rams and explored their potential upstream regulatory mechanisms using gene regulatory network (GRN) analysis. Fifteen ejaculates from five rams were analyzed. Based on total sperm motility using computer-assisted sperm analysis (CASA), ejaculates were classified into a high-motility group (n = 8) and a low-motility group (n = 7). PRM1 and PRM2 expression levels were quantified by RT-qPCR. Following normality confirmation (p > 0.05), parametric tests were applied using the ejaculate as the biological experimental unit. Samples with reduced motility showed significantly lower expression of both protamines (p < 0.01). Moreover, progressive sperm motility was strongly correlated with both PRM1 (r = 0.71, p = 0.019) and PRM2 (r = 0.69, p = 0.03) transcript levels. Cross-species GRN inference using scGeneRAI and a reference human spermatogenesis dataset identified several hypothesis-generating candidate transcription factors, including HMGB4, HMGB1, H2AFZ, NKX6-1, and SMC3, consistently supported across multiple bootstrap resampling runs. These findings demonstrate a strong association between protamine expression and sperm motility in rams. While the identified candidate regulators provide a valuable framework for future species-specific validation, they also highlight promising candidate molecular biomarkers of male fertility in livestock.

Gene regulatory networks↗

PubMed2024

A time-resolved single-cell roadmap of the logic driving anterior neural crest diversification from neural border to migration stages.

Neural crest cells exemplify cellular diversification from a multipotent progenitor population. However, the full sequence of early molecular choices orchestrating the emergence of neural crest heterogeneity from the embryonic ectoderm remains elusive. Gene-regulatory-networks (GRN) govern early development and cell specification toward definitive neural crest. Here, we combine ultradense single-cell transcriptomes with machine-learning and large-scale transcriptomic and epigenomic experimental validation of selected trajectories, to provide the general principles and highlight specific features of the GRN underlying neural crest fate diversification from induction to early migration stages using Xenopus frog embryos as a model. During gastrulation, a transient neural border zone state precedes the choice between neural crest and placodes which includes multiple converging gene programs. During neurulation, transcription factor connectome, and bifurcation analyses demonstrate the early emergence of neural crest fates at the neural plate stage, alongside an unbiased multipotent-like lineage persisting until epithelial-mesenchymal transition stage. We also decipher circuits driving cranial and vagal neural crest formation and provide a broadly applicable high-throughput validation strategy for investigating single-cell transcriptomes in vertebrate GRNs in development, evolution, and disease.

Animals↗

PubMed2026

GRNContext: an interactive web platform for contextualized gene regulatory networks visualization across human cancers.

SUMMARY: While current Gene Regulatory Network (GRN) databases provide comprehensive reference maps of potential interactions between transcription factors and target genes, they do not specify which regulatory interactions are active within specific biological contexts. This limitation is particularly critical in cancer, where transcriptional programs are inherently tissue-specific. To address this gap, we developed GRNContext, an interactive web platform designed for the visualization, exploration, and comparative analysis of gene regulatory networks contextualized across 33 cancer types from The Cancer Genome Atlas (TCGA). Our approach uses the TFLink human reference GRN as a starting point and integrates TCGA transcriptomic profiles to infer cancer-specific regulatory activity. Regulatory relevance was assessed using complementary machine learning and statistical methods, which were unified into a consensus score to prioritize and filter the most relevant candidate regulators for each target gene. By providing both curated context-specific GRNs and a user-friendly platform, GRNContext constitutes a comprehensive and accessible resource that supports mechanistic investigations, hypothesis generation, and translational research focused on transcriptional regulation in cancer. AVAILABILITY AND IMPLEMENTATION: GRNContext is supported by all major browsers and freely available on the web at https://apps.cienciavida.org/grncontext. It is implemented as a client-server web application featuring a FastAPI backend and a React frontend utilizing Cytoscape.js for interactive network visualization, all containerized via Docker for cross-platform compatibility.

Humans↗

PubMed2026

transfactor: transcription factor activity estimation via probabilistic gene expression deconvolution.

Gene expression is a primary modality being studied to differentiate between biological cells. Contemporary single-cell studies simultaneously measure genome-wide transcription levels for thousands of individual cells in a single experiment. While the characterization of cell population differences has often occurred through differential gene expression analysis, tiny effect sizes become statistically significant when thousands of cells are available for each population, compromising biological interpretation. Moreover, these large studies have spurred the development of methods to infer gene regulatory networks (GRNs) directly from the data, and GRN databases are becoming more comprehensive. In this work, we propose a statistical model for gene expression measures and an inference method that leverage GRNs to deconvolve transcription factor (TF) activity from gene expression, by probabilistically assigning mRNA molecules to TFs. This shifts the paradigm from investigating gene expression differences to regulatory differences at the level of TF activity, aiding interpretation and allowing prioritization of a limited number of TFs responsible for significant contributions to the observed gene expression differences. The inferred TF activities result in intuitive prioritization of TFs in terms of the (difference in) estimated number of molecules they produce, in contrast to other widely used methods relying on arbitrary enrichment scores. Our model allows the incorporation of prior information on the regulatory potential between each TF and target gene and is able to deal with both repressing and activating interactions. We compare our approach to other TF activity estimation methods using two simulation experiments and two case studies. Single-cell RNA-sequencing; TF activity; bioinformatics; GRN.

Transcription Factors↗

PubMed2025

Redundant and Singular Regulatory Elements Underlie the Rapidly Evolving Pigmentation of Drosophila.

A major hurdle in understanding the molecular changes responsible for metazoan diversity is the characterization of cis-regulatory elements (CREs) for gene regulatory networks (GRNs). CRE changes are suspected to be commonplace in trait evolution, since such changes circumvent the deleterious effects of pleiotropy. A growing list of genes, though, is known to be regulated by redundant CREs. Such redundant CRE architectures complicate the characterization of GRN evolution, as they compound the effort to characterize each locus, and raise the questions of how and whether genes with redundant architectures evolve expression. Here, we used the evolution of sexually dimorphic abdomen pigmentation of Drosophila (D.) melanogaster as a model to study the function and evolution of CREs. Numerous sequences were evaluated that were previously predicted as potential abdomen CREs. Most of these predictions were validated, including two, four, and ten that, respectively, reside in the homothorax, grainy head, and Eip74EF transcription factor loci. The homothorax CREs were found to be partially redundant for this gene's pigmentation function, and pupal-stage Homothorax expression and the CRE activities were conserved among Drosophila species with the derived dimorphic and ancestral monomorphic phenotypes. Similarly, the Eip74EF CREs were conserved in the monomorphic D. willistoni. Thus, this gene's extensive CRE spatiotemporal redundancy has been conserved for over 30 million years, predating the dimorphic trait. Pigmentation evolution has been connected elsewhere to changes in nonredundant CREs. When these traits evolve, GRN changes may be biased towards the genes with singular nonredundant CREs, while the expression of redundantly regulated genes remains conserved.

Animals↗

PubMed2025

Integrative proteomic analysis provides novel therapeutic insights for etiological subtypes of diabetes.

AIMS: Type 2 diabetes (T2D) is a highly heterogeneous disease characterised by subtypes with variations in aetiology, disease progression, and risk of complications. However, potential drug targets for these subtypes have not been explored. This study aims to investigate potential drug targets by integrating proteomics. MATERIALS AND METHODS: Summary-level data of circulating proteins were extracted from the UK Biobank and the deCODE Health Study. Genetic associations with five diabetes subtypes were obtained from Swedish All New Diabetics in Scania and Malmö Diet and Cancer cohort, including severe autoimmune diabetes (SAID), severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD), mild obesity-related diabetes (MOD), and mild age-related diabetes (MARD). The associations between circulating proteins and diabetes subtypes were assessed through Mendelian randomisation, followed by multiple sensitivity and colocalization analyses. Additionally, tissue-specific, pathway and functional enrichment analysis, assessment of protein druggability, and the protein-protein interaction (PPI) networks were used to further explore biological mechanisms and therapeutic potential. RESULTS: Genetically predicted levels of 2, 2, 9, 3, and 5 circulating proteins were associated with SIRD, SIDD, MARD, MOD, and SAID, respectively. Colocalization analyses further revealed links between GRN with MARD/SIRD, LILRB5 with SIDD/MARD, CR1 with MARD, TNFSF12 with MOD, and DAPK2 with SAID. Enrichment analysis suggested that these proteins were mainly enriched in blood and adipose tissues and involved in immune and inflammatory related pathways. PPI analysis revealed GRN, TNFSF12, and DAPK2 are associated with known T2D targets. CONCLUSIONS: Our study identified several potential drug targets for different subtypes of diabetes using an integrated genetic approach, yielding new insights for precision medicine of diabetes.

Humans↗

PubMed2025

Decoding nitrogen uptake efficiency in maize and sorghum: insights from comparative gene regulatory networks.

Nitrogen (N) is an essential macronutrient for plant growth and yield, yet optimizing nitrogen use efficiency remains a challenge in agriculture. To better understand the regulatory basis of plant responses to N availability, we constructed a maize-specific nitrogen uptake efficiency gene regulatory network (mNUEGRN) comprising 1625 protein-DNA interactions (PDI) between 70 promoters and 301 transcription factors using enhanced yeast one-hybrid assays. We also projected a sorghum NUE GRN (spNUEGRN) based on maize orthologs and analyzed N-responsive subnetworks in both species using transcriptome profiling under N stress of early deprivation and recovery. Cross-species comparison with an existing Arabidopsis GRN revealed about 18% conserved interaction, corresponding to 11% of the mNUEGRN, particularly within the nitrate assimilation pathways. Notably, bZIP18 and bZIP30 emerged as central regulators in mNUEGRN, forming highly connected feed-forward loops (FFLs). From our time series data, we identified 19 236 and 23 864 differentially expressed genes in maize and sorghum, respectively. Gini correlation analysis uncovered 764 and 638 FFLs in mNUEGRN and spNUEGRN, respectively, of which 22 FFLs in maize and 35 in sorghum were identified in both leaf and root for each species. These FFLs may represent candidate regulatory motifs that contribute to modulating transcriptional responses under fluctuating N conditions, but their potential roles require further investigation. Together, our findings reveal evolutionarily conserved and species-specific regulatory strategies that mediate early N responsiveness, offering a foundation for engineering crops with improved NUE.

Sorghum↗

PubMed2026

Insights into glandular trichome biology from analysis of organ-specific gene expression programmes in cannabis, hop and tomato.

Glandular trichomes (GTs) are epidermal outgrowths in which diverse specialised (secondary) metabolites are synthesised and stored. Cannabis (Cannabis sativa L.) and its close relative hop (Humulus lupulus L.) have pharmaceutical and industrial significance due to the presence of these metabolites in their GTs. We examined the conservation or divergence of the specific transcriptional programmes underlying GT biology. To achieve this, we generated transcriptome atlases of trichomes, flower, leaf, stem and root for cannabis, hop and tomato. We found that 12.9, 10.1 and 16.8% of cannabis, hop and tomato genes, respectively, were expressed organ/tissue specifically across all organs/tissues. Transcription factors (TFs) on average accounted for 7.5% of the organ-specific transcriptome and likely regulate organ-specific functions. We also conducted weighted gene co-expression network analysis and gene regulatory network (GRN) analysis to identify key regulators of GT function across the species and validated our predictions by DNA affinity purification sequencing for a subset of the cannabis and tomato GT TFs. The GRNs specific to cannabis or hop GTs were enriched for TFs and target genes associated with specialised metabolism, reflecting their species-specific nature. Conversely, the shared GRN components (identified via orthology analysis) were involved in highly conserved processes, such as flavonoid biosynthesis, solute transport and metabolite storage. Together, these GRNs and the associated transcriptome atlases are valuable resources to improve our knowledge of GT function and organ-specific genome regulation.

Solanum lycopersicum↗

PubMed2025

Proteomic analysis reveals distinct cerebrospinal fluid signatures across genetic frontotemporal dementia subtypes.

We used an untargeted mass spectrometric approach, tandem mass tag proteomics, for the identification of proteomic signatures in genetic frontotemporal dementia (FTD). A total of 238 cerebrospinal fluid (CSF) samples from the Genetic FTD Initiative were analyzed, including samples from 107 presymptomatic (44 C9orf72, 38 GRN, and 25 MAPT) and 55 symptomatic (27 C9orf72, 17 GRN, and 11 MAPT) mutation carriers as well as 76 mutation-negative controls ("noncarriers"). We found shared and distinct proteomic alterations in each genetic form of FTD. Among the proteins significantly altered in symptomatic mutation carriers compared with noncarriers, we found that a set of proteins including neuronal pentraxin 2 and fatty acid binding protein 3 changed across all three genetic forms of FTD and patients with Alzheimer's disease from previously published datasets. We observed differential changes in lysosomal proteins among symptomatic mutation carriers with marked abundance decreases in MAPT carriers but not other carriers. Further, we identified mutation-associated proteomic changes already evident in presymptomatic mutation carriers. Weighted gene coexpression network analysis combined with gene ontology annotation revealed clusters of proteins enriched in neurodegeneration and glial responses as well as synapse- or lysosome-related proteins indicating that these are the central biological processes affected in genetic FTD. These clusters correlated with measures of disease severity and were associated with cognitive decline. This study revealed distinct proteomic changes in the CSF of patients with genetic FTD, providing insights into the pathological processes involved in the disease. In addition, we identified proteins that warrant further exploration as diagnostic and prognostic biomarker candidates.

Humans↗

PubMed2024

Further description of the phenotypic spectrum of neuronal ceroid lipofuscinosis type 11.

PURPOSE: Ceroid lipofuscinosis type 11 (CLN11) is a very rare disease, being reported in only 13 unrelated families so far. Further reports are necessary to comprehend the clinical phenotype of this condition. This article aims to report 9 additional cases of CLN11 from 9 unrelated Latin American families presenting with relatively slow disease progression. METHODS: This was a retrospective observational study including patients with CLN11. Patients were identified through an active search for granulin precursor gene (GRN) pathogenic variants across the entire database of next-generation sequencing of a commercial laboratory and by contacting attending physicians to check for clinical and radiologic findings compatible with a neuronal ceroid lipofuscinosis phenotype. RESULTS: Nine CLN11 patients from unrelated families were evaluated. Age of onset varied between 3 to 17 years. The most common findings were visual impairment, cerebellar ataxia, seizures, myoclonus, and cognitive decline. One patient had a previously unreported finding of cervical, perioral, and tongue myoclonus. Most of the patients were able to walk unassisted after an average of 14.2 years (SD 4.76 y) from disease onset. CONCLUSION: We describe 9 new cases of a very rare type of neuronal ceroid lipofuscinosis (CLN11) from Latin America with a recurrent p.(Gln257ProfsTer27) and a novel p.(Cys83Ter) nonsense variant. Our findings suggest that a slowly progressive neuronal ceroid lipofuscinosis might be a clue for the diagnosis of CLN11.

Humans↗

PubMed2026

Microglial PICALM: A novel genetic driver and therapeutic target in vascular dementia.

BACKGROUND: Vascular dementia (VaD) lacks well-defined genetic mechanisms. Cell-type-specific effects of GWAS loci remain unexplored. METHODS: We integrated single‑cell eQTL data (183 donors, eight cell types) with VaD GWAS (3624 cases, 475,484 controls) using Mendelian randomization and Bayesian colocalization, replicated in an independent cohort (2074 cases, 456,366 controls). Subtype, snRNA‑seq, cell‑cell communication, PheWAS, expression profiling, and drug prediction with BBB permeability assessment were performed. RESULTS: Microglial PICALM was the only robustly replicated signal (OR = 0.8334, p = 5.3 × 10⁻⁴; colocalization PP.H4 > 0.75). The effect was strongest in multiple infarctions dementia (OR = 0.7746). Exploratory snRNA-seq analysis (4 VaD vs. 4 controls; GSE282111) provided supporting evidence for microglial PICALM enrichment and downregulation (p < 0.001). PICALM‑high microglia showed enhanced neurovascular‑ and phagocytosis‑related communication (e.g., SPP1, GAS6, GRN). PheWAS revealed no pleiotropy. In silico drug repurposing prioritised three FDA-approved BBB-penetrant compounds (disopyramide, benzocaine, amantadine) as candidates warranting further mechanistic validation. CONCLUSIONS: Microglial PICALM is identified as a likely genetic determinant of VaD, especially in the multiple infarctions subtype. Upregulating PICALM may be associated with a neuroprotective microglial phenotype, highlighting PICALM as a candidate therapeutic target warranting further experimental validation.

Humans↗