Biology subjects

Uyar, A.

Publications and source records attributed to Uyar, A..

8 recordsLinked to original sources

bioRxiv2026

Single-subject Proteomic Signatures in Alzheimers Disease Reflect Clinical Phenotypes and Distinguish Asymptomatic from Symptomatic Cases

INTRODUCTIONAlzheimers Disease (AD) exhibits considerable inter-individual variability in clinical presentation, neuropathological burden, and underlying molecular processes. Conventional cohort-based analyses of omics molecular data often mask individual-level heterogeneity, limiting insights into the precision therapeutic strategies. To address this challenge, we developed INDIGO (INdividual-level DIfferential GenOmics), a computational framework that quantifies molecular deviations for each individual relative to healthy controls, enabling subject-specific profiling of diseaseassociated alterations in proteomic data, with a framework that is readily applicable to other omics modalities. METHODSWe applied INDIGO to dorsolateral prefrontal cortex (DLPFC) proteomic data from ROSMAP cohort (N = 610). Protein level deviations were aggregated into gene set activity scores for KEGG pathways and curated AD Biodomain annotations. Functional alterations across AD and Asymptomatic AD (AsymAD) individuals were evaluated and correlated with clinical metrics including APOE4 genotype, Braak stage, CERAD and MMSE scores. Graph-based clustering was used to identify molecularly distinct subgroups based on shared patterns of functional dysregulation. RESULTSLimited overlap was observed between cohort-level differential expression analysis and INDIGO single-subject analyses. Individual deviations in various processes, including metabolic, immune and epigenetic pathways, exhibited sex- and disease stage-specific patterns. Amyloid clearance and immune activation were strongly associated with APOE4 dosage, higher amyloid and tau burden and cognitive decline, whereas upregulation of mitochondrial and synaptic modules correlated positively with preserved cognitive function. By linking individuals through concordant directional proteomic changes, we identified molecularly coherent subgroups that transcend conventional diagnostic boundaries and include both AD and AsymAD subjects. Each subgroup displayed distinct functional signatures and defined by a unique set of key regulatory proteins. DISCUSSIONThese results demonstrate that single-subject omics profiling can resolve individual molecular signatures aligned with clinical and neuropathological variation in AD. By linking molecular heterogeneity with disease phenotypes, INDIGO provides a scalable framework for precision modeling and novel therapeutic target discovery.

neuroscience↗

bioRxiv2025

WSB.APP/PS1 mice develop age-dependent cerebral amyloid angiopathy, cerebrovascular deficits, and white matter damage, which are modified by humanized APOE alleles.

INTRODUCTIONGrowing evidence suggests cerebrovascular deficits, including cerebral amyloid angiopathy (CAA), play a key role in Alzheimers disease (AD) pathogenesis. However, these facets of AD are not well understood, due in part to the lack of mouse models that develop robust vascular deficits and CAA. Here, we characterize human-relevant cerebrovascular phenotypes in WSB.APP/PS1 mice with and without humanized APOE alleles. METHODSAD-relevant cerebrovascular phenotypes in WSB, WSB.APP/PS1, WSB.APOE2/2APP/PS1, WSB.APOE3/3APP/PS1, and/or WSB.APOE4/4APP/PS1 mice were characterized using immunohistochemistry, transcriptomics, positron emission tomography/computed tomography, and ex-vivo analyses. RESULTSWSB.APP/PS1 mice exhibited age-related plaque deposition and CAA, significant transcriptomic overlap with human AD, myelin deficits, cerebrovascular/metabolic uncoupling, and altered cerebrovascular morphology. Aged WSB vasculature retained vasoreactivity, but exhibited increased stiffness. Compared to APOE2, APOE4 expression in WSB.APP/PS1 mice increased CAA and plaque-associated microglial area. DISCUSSIONThese data illustrate the utility of the WSB genetic context to model CAA and uncover vascular contributions to AD. HighlightsO_LIWSB.APP/PS1 mice developed CAA with age. C_LIO_LITranscriptomic profiling revealed significant molecular overlap between human AD and WSB.APP/PS1 brains. C_LIO_LITranscriptomics and immunofluorescence suggested age-related myelin deficits in WSB.APP/PS1 brains. C_LIO_LIWSB.APP/PS1 brains exhibited neurovascular uncoupling, changes in vascular volume and surface area, and increased permeability changes. C_LIO_LIWSB.APP/PS1 cerebrovasculature was resilient to loss of responsivity with age but exhibited increased vascular stiffness. C_LIO_LIHumanized APOE {varepsilon}4 alleles significantly increased CAA and parenchymal plaque-associated microglial area in WSB.APP/PS1 mice. C_LI Research in ContextO_LISystematic review: The authors characterized WSB.APP/PS1 as a unique human-relevant model of Alzheimers Disease and explored several facets of cerebrovascular deficits. C_LIO_LIInterpretation: WSB and/or WSB.APP/PS1 mice exhibited human-relevant vascular phenotypes, including CAA, neurovascular uncoupling, increased vascular tree volume, vascular stiffness, and resilience to age-related loss of responsivity. Furthermore, the transcriptomic profile of WSB.APP/PS1 brains significantly overlaps with signatures observed in human AD. WSB.APP/PS1 brains exhibited myelin deficits with age. Furthermore, humanized APOE {varepsilon}2, {varepsilon}3, and {varepsilon}4 alleles significantly modified WSB.APP/PS1 susceptibility to CAA, plaque deposition, and plaque-associated microglial area. C_LIO_LIFuture Directions: The WSB genetic context will be leveraged to identify specific molecular mechanisms associated with cerebrovascular deficits in AD. C_LI

neuroscience↗

bioRxiv2023

In vivo validation of late-onset Alzheimer's disease genetic risk factors

Structured AbstractO_ST_ABSIntroductionC_ST_ABSGenome-wide association studies have identified over 70 genetic loci associated with late-onset Alzheimers disease (LOAD), but few candidate polymorphisms have been functionally assessed for disease relevance and mechanism of action. MethodsCandidate genetic risk variants were informatically prioritized and individually engineered into a LOAD-sensitized mouse model that carries the AD risk variants APOE4 and Trem2*R47H. Potential disease relevance of each model was assessed by comparing brain transcriptomes measured with the Nanostring Mouse AD Panel at 4 and 12 months of age with human study cohorts. ResultsWe created new models for 11 coding and loss-of-function risk variants. Transcriptomic effects from multiple genetic variants recapitulated a variety of human gene expression patterns observed in LOAD study cohorts. Specific models matched to emerging molecular LOAD subtypes. DiscussionThese results provide an initial functionalization of 11 candidate risk variants and identify potential preclinical models for testing targeted therapeutics.

neuroscience↗

bioRxiv2021

Perturbation of ACE2 structural ensembles by SARS-CoV-2 spike protein binding

The human ACE2 enzyme serves as a critical first recognition point of coronaviruses, including SARS-CoV-2. In particular, the extracellular domain of ACE2 interacts directly with the S1 tailspike protein of the SARS-CoV-2 virion through a broad protein-protein interface. Although this interaction has been characterized by X-ray crystallography and Cryo-EM, these structures do not reveal significant differences in ACE2 structure upon S1 protein binding. In this work, using several all-atom molecular dynamics simulations, we show persistent differences in ACE2 structure upon binding. These differences are determined with the Linear Discriminant Analysis (LDA) machine learning method and validated using independent training and testing datasets, including long trajectories generated by D. E. Shaw Research on the Anton 2 supercomputer. In addition, long trajectories for 78 potent ACE2-binding compounds, also generated by D. E. Shaw Research, were projected onto the LDA classification vector in order to determine whether the ligand-bound ACE2 structures were compatible with S1 protein binding. This allows us to predict which compounds are "apo-like" vs "complex-like", as well as to pinpoint long-range ligand-induced allosteric changes of ACE2 structure.

biophysics↗

bioRxiv2020

Membrane-mediated ligand unbinding of the PK-11195 ligand from the translocator protein (TSPO)

The translocator protein (TSPO), previously known as the peripheral benzodiazepine receptor, is of longstanding medical interest as both a biomarker for neuroinjury and a potential drug target for neuroinflammation and other disorders. Recently it was shown that ligand residence time is a key factor determining steroidogenic efficacy of TSPO-binding compounds. This spurs interest in simulations of (un)binding pathways of TSPO ligands, which could reveal the molecular interactions governing ligand residence time. In this study, we use a weighted ensemble algorithm to determine the unbinding pathway for different poses of PK-11195, a TSPO ligand used in neuroimaging. In contrast with previous studies, our results show that PK-11195 does not dissociate directly into the solvent but instead dissociates via the lipid membrane by going between the transmembrane helices. We analyze this path ensemble in detail, constructing descriptors that can facilitate a general understanding of membrane-mediated ligand binding. We construct a Markov state model using additional straightforward simulations to determine pose stability and kinetics of ligand unbinding. Together we combine over 40 {micro}s of trajectory data to form a coherent picture of the ligand binding landscape. We find that all poses are able to interconvert before unbinding, leading to single mean first passage time estimate for all starting poses which roughly agrees with the experimental quantity. The ligand binding transition state predicted by our combined model occurs when PK-11195 is already in the membrane and does not involve direct ligand-protein interactions. This has implications for the design of new long residence-time TSPO ligands. SIGNIFICANCEKinetics-oriented drug design is an emerging objective in drug discovery. However, while ligand binding affinity (or the binding free energy) is purely a function of the bound and unbound states, the binding kinetics depends on the nature of the paths by which the (un)binding occurs. This underscores the importance of approaches that can reveal information about the ensemble of (un)binding paths. Here we used advanced molecular dynamics approaches to study the unbinding of PK-11195 from TSPO and find it dissociates from the protein by dissolving into the membrane, and that the transition state occurs after the PK-11195 molecule has already separated from TSPO. These results motivate the design of future long-residence time TSPO ligands that destabilize the membrane-solvated transition state.

biophysics↗

bioRxiv2019

Genetic perturbations of disease risk genes in mice capture transcriptomic signatures of late-onset Alzheimer’s disease

BackgroundNew genetic and genomic resources have identified multiple genetic risk factors for late-onset Alzheimers disease (LOAD) and characterized this common dementia at the molecular level. Experimental studies in model organisms can validate these associations and elucidate the links between specific genetic factors and transcriptomic signatures. Animal models based on LOAD-associated genes can potentially connect common genetic variation with LOAD transcriptomes, thereby providing novel insights into basic biological mechanisms underlying the disease.\n\nMethodsWe performed RNA-Seq on whole brain samples from a panel of six-month-old female mice, each carrying one of the following mutations: homozygous deletions of Apoe and Clu; hemizygous deletions of Bin1 and Cd2ap; and a transgenic APOE{varepsilon}4. Similar data from a transgenic APP/PS1 model was included for comparison to early-onset variant effects. Weighted gene co-expression network analysis (WGCNA) was used to identify modules of correlated genes and each module was tested for differential expression by strain. We then compared mouse modules with human postmortem brain modules from the Accelerating Medicines Partnership for AD (AMP-AD) to determine the LOAD-related processes affected by each genetic risk factor.\n\nResultsMouse modules were significantly enriched in multiple AD-related processes, including immune response, inflammation, lipid processing, endocytosis, and synaptic cell function. WGCNA modules were significantly associated with Apoe-/-, APOE{varepsilon}4, Clu-/-, and APP/PS1 mouse models. Apoe-/-, GFAP-driven APOE{varepsilon}4, and APP/PS1 driven modules overlapped with AMP-AD inflammation and microglial modules; Clu-/- driven modules overlapped with synaptic modules; and APP/PS1 modules separately overlapped with lipid-processing and metabolism modules.\n\nConclusionsThis study of genetic mouse models provides a basis to dissect the role of AD risk genes in relevant AD pathologies. We determined that different genetic perturbations affect different molecular mechanisms comprising AD, and mapped specific effects to each risk gene. Our approach provides a platform for further exploration into the causes and progression of AD by assessing animal models at different ages and/or with different combinations of LOAD risk variants.

neuroscience↗

bioRxiv2019

Staging Alzheimer’s disease in the brain and retina of B6.APP/PS1 mice by transcriptional profiling

Alzheimers disease (AD) is a common form of dementia characterized by amyloid plaque deposition, TAU pathology, neuroinflammation and neurodegeneration. Mouse models recapitulate some key features of AD. For instance, the B6.APP/PS1 model (carrying human transgenes for mutant forms of APP and PSEN1) shows plaque deposition and associated neuroinflammatory responses involving both astrocytes and microglia beginning around 6 months of age. However, in our colony, TAU pathology, significant neurodegeneration and cognitive decline are not apparent in this model even at older ages. Therefore, this model is ideal for studying neuroinflammatory responses to amyloid deposition. Here, RNA sequencing of brain and retinal tissue, generalized linear modeling (GLM), functional annotation followed by validation by immunofluorescence (IF) was performed in B6.APP/PS1 mice to determine the earliest molecular changes prior to and around the onset of plaque deposition (2-6 months of age). Multiple pathways were shown to be activated in response to amyloid deposition including the JAK/STAT and NALFD pathways. Putative, cell-specific targets of STAT3, a central component of the JAK/STAT pathway, were identified that we propose provide more precise options for assessing the potential for targeting activation of the JAK/STAT pathway as a treatment for human AD. In the retina, GLM predicted activation of vascular-related pathways. However, many of the gene expression changes comparing B6 with B6.APP/PS1 retina samples occurred prior to plaque onset (2 months of age). This suggests retinal changes in B6.APP/PS1 mice may be an artefact of overexpression of mutant forms of APP and PSEN1 providing limited translatability to human AD. Therefore, caution should be taken when using this mouse model to assess the potential of using the eye as a window to the brain for AD.

neuroscience↗

bioRxiv2019

A novel systems biology approach to evaluate mouse models of late-onset Alzheimer’s disease

BackgroundLate-onset Alzheimers disease (LOAD) is the most common form of dementia worldwide. To date, animal models of Alzheimers have focused on rare familial mutations, due to a lack of frank neuropathology from models based on common disease genes. Recent multi-cohort studies of postmortem human brain transcriptomes have identified a set of 30 gene co-expression modules associated with LOAD, providing a molecular catalog of relevant endophenotypes.\n\nResultsThis resource enables precise gene-based alignment between new animal models and human molecular signatures of disease. Here, we describe a new resource to efficiently screen mouse models for LOAD relevance. A new NanoString nCounter(R) Mouse AD panel was designed to correlate key human disease processes and pathways with mRNA from mouse brains. Analysis of three mouse models based on LOAD genetics, carrying APOE4 and TREM2*R47H alleles, demonstrated overlaps with distinct human AD modules that, in turn, are functionally enriched in key disease-associated pathways. Comprehensive comparison with full transcriptome data from same-sample RNA-Seq shows strong correlation between gene expression changes independent of experimental platform.\n\nConclusionsTaken together, we show that the nCounter Mouse AD panel offers a rapid, cost-effective and highly reproducible approach to assess disease relevance of potential LOAD mouse models.

neuroscience↗