Biology subjects

Hide, W.

Publications and source records attributed to Hide, W..

10 recordsLinked to original sources

bioRxiv2026

Genedex: Contextualizing gene signatures across Alzheimer's disease pathology, cell types, and brain regions

Systematic prioritization of candidate Alzheimer's disease (AD) genes and their target functions for therapeutic intervention requires a consistent understanding of their brain location, cell-type-specific expression, relationships with pathology, and direction of change. Defining the role of a gene in AD requires interrogation of multiple publications, each providing a different context. Often, it is also unclear whether a gene is up- or downregulated across these contexts. However, the narrow diversity of contexts in which they have been assayed and described limits interpretation. We integrated 1,562 gene signatures from 34 studies, annotated for pathological process, cell type, brain region, and direction of change, and showed that Genedex recovers established AD biology. Genedex addresses cellular and regional unexplained directional contradictions from 10,657 discordant genes in the published AD literature. We investigated the role of heat-shock chaperones and neurotrophic signaling in cognitive resilience using Genedex. Heat-shock chaperone genes are broadly upregulated with tau burden; but, in the presence of amyloid pathology, their expression diverges, showing upregulation in excitatory neurons and downregulation in glia and during A{beta} clearance. LINGO1, a regulator of BDNF, is upregulated with neuritic plaque load, tau burden, and selective vulnerability in cortical regions. Notably, in tau-affected RORB excitatory neurons, LINGO1 expression is inversely correlated with neurotrophic genes BDNF and NTRK2. A prioritized interneuronal resilience signature shows correlated pathway co-expression with somatostatin and parvalbumin interneuronal signatures. Vulnerability-associated signatures separate by cellular context: neuronal programs are positively correlated with vulnerable interneurons, while glial and vascular cells are predominantly anti-correlated. By systematically mapping genes across functional, cellular, spatial, and directional axes, Genedex provides a platform for discovery of contextualized targets and mechanistic hypotheses. Genedex is freely available at hidelab.github.io/genedex-app.

neuroscience↗

bioRxiv2026

MicroRNA correlates of resilience to Alzheimer's disease identify candidate therapeutic targets for neuroprotection

Many aged individuals accumulate advanced Alzheimers disease (AD) neuropathology without cognitive decline, signifying potent endogenous resilience mechanisms. Mimicking resilience to AD may offer new therapeutic opportunities by emulating endogenous neuroprotection, but the molecular pathways that underpin resilience remain largely unknown. MicroRNAs (miRNAs)--small noncoding RNA molecules that post-transcriptionally regulate gene expression--influence neuronal and glial processes associated with development, aging, and AD neurodegeneration but their role in resilience has not been characterized. We investigated resilience-associated miRNAs and their targeted programs in the dorsolateral prefrontal cortex of post-mortem human brains. We analyzed matched miRNA and messenger RNA (mRNA) expression across resilient, AD, and control subjects from the Religious Order Study and Memory and Aging Project (ROSMAP) cohort. Nine miRNAs were differentially expressed in resilience compared with AD, including previously unreported miR-362-3p and miR-433-3p and new resilience-associated roles for known AD-related miRNAs, including neuronal miR-132-3p and miR-129-5p. By analyzing miRNA activity across AD progression, we found additional cognitive-associated miRNAs (e.g., miR-335-5p and miR-19b) and one plaque-restricted miRNA (miR-199a-5p). Sex-specific miRNA dysregulation was observed: miR-7-5p showed male-specific upregulation in AD versus resilience and suggested sex-specific differences in AD patients. Integrated co-expression and target-enrichment analyses linked resilience-associated miRNAs to pathways that were associated with cognitive decline, including transforming growth factor {beta}, Rho guanosine triphosphatases, and neurotransmitter receptor regulation. We also report restricted co-activity in AD subjects for miR-362-3p with inflammatory pathways, including tumor necrosis factor and Toll-like receptor signaling. These results demonstrate systematic involvement of miRNAs across neuronal and glial programs of AD resilience, cognitive decline, and sex-specific regulation. Our study provides an important resource for discovery of actionable regulatory programs that could lead to new therapies, based on endogenous molecules, that emulate natural resilience to AD. Key pointsO_LINine distinct cortical microRNA (miRNA) signatures correlate with resilience to Alzheimers disease (AD)-related cognitive decline, pointing to endogenous regulatory programs that may help preserve cognitive function. C_LIO_LIAt the miRNA level, resilient brains show minimal or no detectable differences to healthy individuals, despite the profound pathological differences, supporting the idea that resilience reflects preserved molecular homeostasis rather than a separate disease state. C_LIO_LISome miRNA signatures are specific to a certain pathology (e.g., one linked to amyloid-{beta} plaques independently of tau pathology and cognitive decline), helping to disentangle the regulation of these processes. C_LIO_LISex-specific miRNA dysregulation in AD suggests that resilience-linked pathways may be regulated differently in males and females, reinforcing the value of sex-stratified analyses and the potential for differential therapeutic strategies. C_LIO_LIIntegrative miRNA-pathway analysis highlights candidate regulatory networks involved in inflammation, matrisome, and cellular stress responses, providing a framework for resilience-linked therapeutic targets. C_LI

neuroscience↗

bioRxiv2026

A microRNA atlas of the human prefrontal cortex across the adult lifespan

Aging of the human brain is characterized by widespread changes in gene expression regulated in part by microRNAs (miRNAs). We present a lifespan miRNA atlas of the human dorsolateral prefrontal cortex generated from small RNA sequencing of 113 postmortem samples spanning 18 to 100 years of age. Differential expression analysis revealed progressive age-associated remodeling of miRNA expression, with the strongest differences observed between old and young individuals. Among the significantly altered miRNAs, miR-34a-5p emerged as one of the most robustly upregulated miRNAs in the aged cortex, alongside additional aging-associated miRNAs including miR-155-5p, miR-132-3p, miR-212-3p, miR-449a, and members of the miR-302 family. This atlas provides a resource for investigating miRNA dysregulation and small RNA regulatory networks during human cortical aging.

neuroscience↗

bioRxiv2026

Aging-related Transcriptomic Changes with Spatial Resolution in the Human Prefrontal Cortex

The human prefrontal cortex (PFC), whose laminar organization is essential for cognitive function, is among the first regions to show age-related functional decline1,2. Single-cell sequencing studies revealed cell type-dependent aging effects but lacked spatial specificity3-6. Spatial transcriptomics (ST) advanced our molecular understanding of the human PFC7, yet whether aging-driven changes differ across PFC layers remains unclear. Here, we performed whole-transcriptome ST on postmortem PFC from 37 individuals across the adult lifespan. We mapped cortical layers and revealed aging mechanisms across layers. This represents one of the largest and most comprehensive lifespan ST analysis of the human PFC brain, offering crucial insight into how the brain ages and identifying potential molecular targets to mitigate cognitive aging and extend healthspan.

neuroscience↗

bioRxiv2025

Systemic infections alter cortical transcriptional signatures in Alzheimer's disease

Alzheimers disease (AD) is characterized by neuroinflammation, yet the impact of concurrent systemic infections on the AD brain remains poorly understood. We investigated the molecular mechanisms underlying the central nervous system response to systemic infections in AD by analyzing RNA sequencing data generated in the prefrontal cortex from 202 post-mortem donors (113 AD, 89 controls), where we stratified by the presence of a respiratory infection at the time of death. We identified 763 significantly differentially expressed genes (DEGs) between AD and controls without infection, which were enriched for oxidative phosphorylation and neurodegenerative pathways. In contrast, 122 DEGs distinguished AD from controls during infection, with 57 genes uniquely altered in AD in the presence of infection, including MAPK4, VAV3, and POU3F4, implicating infection-dependent mechanisms of vascular and immune regulation. Pathway activity analysis revealed that infection in AD suppresses some immune and vascular pathways, while enhancing transcriptional and developmental programs. Weighted gene co-expression network analysis uncovered three key modules: one module strongly associated with AD, enriched for aging and signal transduction; one module linked to both AD and infection, highlighting cytoskeletal remodelling and host-pathogen interactions; and one module specific to infection, enriched in astrocytes, pericytes, and endothelial cells, implicating blood-brain barrier dysfunction. These findings suggest that systemic respiratory infections reshape transcriptional programs in the AD brain, dampening immune effector pathways and engaging vascular and host-pathogen processes in blood-brain-barrier-associated cell types. Our results highlight the complex interplay between systemic infection, neuroinflammation, and vascular responses in AD.

neuroscience↗

bioRxiv2025

Context-dependent regulatory variants in Alzheimer's disease

Noncoding genetic variants underlie many complex diseases, yet identifying and interpreting their functional impacts remains challenging. Late-onset Alzheimers disease (LOAD), a polygenic neurodegenerative disorder, exemplifies this challenge. The disease is strongly associated with noncoding variation, including common variants enriched in microglial enhancers and rare variants nominated at loci implicated in neurodevelopment and synaptic function. These variants may perturb regulatory sequences by disrupting transcription factor (TF) motifs or altering local regulatory sequence context, with potential consequences for gene expression and chromatin accessibility. However, assessing their impact is complicated by the context-dependent functions of regulatory sequences, underscoring the need to systematically examine variant effects across diverse tissues, cell types, and cellular states. Here, we combined in vitro and in vivo massively parallel reporter assays (MPRAs) with interpretable machine-learning models to systematically characterize common and rare variants across myeloid and neuron-enriched neural contexts. Parallel profiling of variants in four immune states in vitro and three mouse brain regions in vivo revealed that individual variants can differentially and even oppositely modulate reporter activity across cellular contexts, while a subset showed immune-state-dependent effects. Within the assayed candidate set, the relative effect sizes of common and rare variants reversed between contexts, with common variants showing larger effects in THP-1 macrophages and rare variants in brain tissue. Interpretable sequence-to-function models prioritized context-biased variants and generated motif-level hypotheses, including predicted transcription-factor motif disruption and subtler changes in local motif context. To probe endogenous consequences at a prioritized locus, we used CRISPR interference to perturb a rare-variant-containing enhancer at the SEC63-OSTM1 locus, revealing metabolic and biosynthetic transcriptional programs resembling those induced by SEC63 promoter perturbation, together with a stimulation-specific interferon response. These findings show that LOAD-associated noncoding variants exhibit context-dependent effects on reporter activity and predicted chromatin accessibility, and provide a framework for linking genetic association to regulatory activity, sequence grammar and endogenous transcriptional state.

genomics↗

bioRxiv2025

Molecular hallmarks of excitatory and inhibitory neuronal resilience and resistance to Alzheimer's disease

BackgroundA significant proportion of individuals maintain healthy cognitive function despite having extensive Alzheimers disease (AD) pathology, known as cognitive resilience. Understanding the molecular mechanisms that protect these individuals can identify therapeutic targets for AD dementia. This study aims to define molecular and cellular signatures of cognitive resilience, protection and resistance, by integrating genetics, bulk RNA, and single-nucleus RNA sequencing data across multiple brain regions from AD, resilient, and control individuals. MethodsWe analyzed data from the Religious Order Study and the Rush Memory and Aging Project (ROSMAP), including bulk (n=631) and multi-regional single nucleus (n=48) RNA sequencing. Subjects were categorized into AD, resilient, and control based on {beta}-amyloid and tau pathology, and cognitive status. We identified and prioritized protected cell populations using whole genome sequencing-derived genetic variants, transcriptomic profiling, and cellular composition distribution. ResultsTranscriptomic results, supported by GWAS-derived polygenic risk scores, place cognitive resilience as an intermediate state in the AD continuum. Tissue-level analysis revealed 43 genes enriched in nucleic acid metabolism and signaling that were differentially expressed between AD and resilience. Only GFAP (upregulated) and KLF4 (downregulated) showed differential expression in resilience compared to controls. Cellular resilience involved reorganization of protein folding and degradation pathways, with downregulation of Hsp90 and selective upregulation of Hsp40, Hsp70, and Hsp110 families in excitatory neurons. Excitatory neuronal subpopulations in the entorhinal cortex (ATP8B1+ and MEF2Chigh) exhibited unique resilience signaling through neurotrophin (modulated by LINGO1) and angiopoietin (ANGPT2/TEK) pathways. We identified MEF2C, ATP8B1, and RELN as key markers of resilient excitatory neuronal populations, characterized by selective vulnerability in AD. Protective rare variant enrichment highlighted vulnerable populations, including somatostatin (SST) inhibitory interneurons, validated through immunofluorescence showing co-expression of rare variant associated RBFOX1 and KIF26B in SST+ neurons in the dorsolateral prefrontal cortex. The maintenance of excitatory-inhibitory balance emerges as a key characteristic of resilience. ConclusionsWe identified molecular and cellular hallmarks of cognitive resilience, an intermediate state in the AD continuum. Resilience mechanisms include preservation of neuronal function, maintenance of excitatory/inhibitory balance, and activation of protective signaling pathways. Specific excitatory neuronal populations appear to play a central role in mediating cognitive resilience, while a subset of vulnerable SST interneurons likely provide compensation against AD-associated dysregulation. This study offers a framework to leverage natural protective mechanisms to mitigate neurodegeneration and preserve cognition in AD.

neuroscience↗

bioRxiv2022

PanomiR: A systems biology framework for analysis of multi-pathway targeting by miRNAs

Charting microRNA (miRNA) regulation across pathways is central to characterizing their role in disease. Yet, current methods reveal only individual miRNA-pathway interactions. We have developed a systems biology approach, Pathway networks of miRNA Regulation (PanomiR), that overcomes these limitations to identify miRNA targeting of groups of interacting pathways using gene expression. The approach does not depend on statistically significant enrichment of miRNA target genes in individual pathways or significant differentially expressed genes. Rather, it directly captures differential activity of pathways between states, determining their up-or-down regulation while sensitively detecting biologically-meaningful signals. PanomiR analyzes the co-activity of differentially regulated pathways to determine coordinate functional groups and uses these co-activated grouped pathways to uncover miRNAs that target them. Incorporating both experimentally-supported or predicted miRNA-mRNA interactions, PanomiR robustly identifies miRNAs central to the regulation of disease functions. We applied PanomiR to a liver cancer dataset and showed that it can organize liver cancer pathways and their regulating miRNAs into coordinated transcriptional programs, reflecting the pathogenic mechanisms of hepatocellular carcinoma. PanomiR recapitulated known central miRNAs in liver cancer with a biologically meaningful assignment of pathways under their regulation, unbiased by the number of genes targeted by each miRNA. PanomiR is a granular framework for detecting broad-scale multi-pathway programs under miRNA regulation. It is accessible as an open-source R/Bioconductor package: .

systems biology↗

bioRxiv2019

Meta-analysis of the human brain transcriptome identifies heterogeneity across human AD coexpression modules robust to sample collection and methodological approach

Alzheimers disease (AD) is a complex and heterogenous brain disease that affects multiple inter-related biological processes. This complexity contributes, in part, to existing difficulties in the identification of successful disease-modifying therapeutic strategies. To address this, systems approaches are being used to characterize AD-related disruption in molecular state. To evaluate the consistency across these molecular models, a consensus atlas of the human brain transcriptome was developed through coexpression meta-analysis across the AMP-AD consortium. Consensus analysis was performed across five coexpression methods used to analyze RNA-seq data collected from 2114 samples across 7 brain regions and 3 research studies. From this analysis, five consensus clusters were identified that described the major sources of AD-related alterations in transcriptional state that were consistent across studies, methods, and samples. AD genetic associations, previously studied AD-related biological processes, and AD targets under active investigation were enriched in only three of these five clusters. The remaining two clusters demonstrated strong heterogeneity between males and females in AD-related expression that was consistently observed across studies. AD transcriptional modules identified by systems analysis of individual AMP-AD teams were all represented in one of these five consensus clusters except ROS/MAP-identified Module 109, which was specific for genes that showed the strongest association with changes in AD-related gene expression across consensus clusters. The other two AMP-AD transcriptional analyses reported modules that were enriched in one of the two sex-specific Consensus Clusters. The fifth cluster has not been previously identified and was enriched for genes related to proteostasis. This study provides an atlas to map across biological inquiries of AD with the goal of supporting an expansion in AD target discovery efforts.

systems biology↗

bioRxiv2017

Project MinE: study design and pilot analyses of a large-scale whole-genome sequencing study in amyotrophic lateral sclerosis

The most recent genome-wide association study in amyotrophic lateral sclerosis (ALS) demonstrates a disproportionate contribution from low-frequency variants to genetic susceptibility of disease. We have therefore begun Project MinE, an international collaboration that seeks to analyse whole-genome sequence data of at least 15,000 ALS patients and 7,500 controls. Here, we report on the design of Project MinE and pilot analyses of newly whole-genome sequenced 1,264 ALS patients and 611 controls drawn from the Netherlands. As has become characteristic of sequencing studies, we find an abundance of rare genetic variation (minor allele frequency < 0.1 %), the vast majority of which is absent in public data sets. Principal component analysis reveals local geographical clustering of these variants within The Netherlands. We use the whole-genome sequence data to explore the implications of poor geographical matching of cases and controls in a sequence-based disease study and to investigate how ancestry-matched, externally sequenced controls can induce false positive associations. Also, we have publicly released genome-wide minor allele counts in cases and controls, as well as results from genic burden tests.

genetics↗