Biology subjects

Persohn, S. A.

Publications and source records attributed to Persohn, S. A..

5 recordsLinked to original sources

bioRxiv2026

Neuro-Metabolic and Vascular Dysregulation are Functional Biomarkers of Acquired Brain Injury

Emerging clinical and neuropathological evidence suggests a direct link between traumatic brain injury (TBI) and neurodegenerative diseases (ND), but the mechanisms by which TBI contributes to ND onset and progression remain unclear. To bridge this gap, the NINDS TBI-ADRD consortium developed a diagnostic framework to guide the design and evaluation of TBI-ADRD experiments using translational neuroimaging (DCE-MRI, 18F-FDG-PET) and advanced image-processing pipelines. Neuro-metabolic and vascular dysregulation (MVD) and metabolic functional connectomics (MFC) were evaluated in 8-month C57BL/6J mice at 30- and 60-days post-injury (DPI). Both MVD and MFC revealed significant changes at 30- and 60-DPI that were sex- and injury side-dependent. Female mice showed greater regional MVD alterations, while MFC identified sex-dependent changes at 30-DPI that diminished by 60-DPI. These findings suggest that a single mid-life closed-head injury induces sexually dimorphic MVD and brain network remodeling, supporting the potential of MVD as a sensitive biomarker for improved clinical monitoring post-TBI.

neuroscience↗

bioRxiv2026

Multidomain Analysis of Clinical Cognitive Assessments and Imaging Data in Alzheimer's Disease Accurately Predicts Disease Stage and Grade Independent of Amyloid and Tau

BackgroundIndividual clinical cognitive assessments (CCA) for Alzheimers disease (AD) provide broad disease stratification but are limited in sensitivity and specificity, requiring integration of multiple CCA for optimal disease staging. Recent work from our lab suggests that neuro-metabolic and vascular dysregulation (MVD) occurs early in AD, prior to clinical symptoms, and may provide higher sensitivity and specificity than CCA alone. In this study, we combined three widely accepted CCA with MVD readouts and developed a multimodal ensemble machine learning approach across the AD spectrum to predict disease stage and grade. MethodsAD subjects (N=372) across the disease spectrum with imaging (PET:18F-FDG, MRI:T1w, T2 FLAIR, ASL) and CCAs (ADAS-Cog, CDR, MoCA) data were analyzed from ADNI. Imaging data were registered to MNI152+, z-scored relative to cognitively normal controls, and processed for MVD. A clinical-set-enrichment analysis (CSEA) was developed to link regional brain changes with CCA scores, map changes to functional categories, project them into a 3D Cartesian space, and model trajectories, thus revealing at-risk and resilient regions. In addition, an ensemble machine-learning approach was utilized for disease stage classification, and a disease grading scheme across the AD spectrum was developed to further stratify within disease stages. FindingsRegional data followed an MVD pattern across AD stages stratified by CSEA scores. Females showed greater stage separation along the CCA axis within each region, indicating faster disease progression. Moreover, progression in at-risk brain regions (e.g., mid- and inf-temporal gyri, amygdala) was associated with longer disease path lengths, whereas progression in resilient brain regions (supramarginal gyrus) was not. Moreover, our classification and grading approach can predict AD stage and grade independent of amyloid-beta and tau with high precision and accuracy. InterpretationA framework was developed to evaluate MVD and CCA variations across the AD spectrum, thereby distinguishing at-risk and resilient brain regions. Distinct disease trajectories were identified, and a new data-driven grading scheme was proposed to highlight the potential for precision medicine and therapeutic evaluation. FundingNIH T32AG071444

neuroscience↗

bioRxiv2023

Assessment of Neurovascular Uncoupling: APOE Status is a Key Driver of Early Metabolic and Vascular Dysfunction

STRUCTURED ABSTRACTO_ST_ABSBACKGROUNDC_ST_ABSAlzheimers disease (AD) is the most common cause of dementia worldwide, with apolipoprotein {varepsilon}4 (APOE{varepsilon}4) being the strongest genetic risk factor. Current clinical diagnostic imaging focuses on amyloid and tau; however, new methods are needed for earlier detection. METHODSPET imaging was used to assess metabolism-perfusion in both sexes of aging C57BL/6J, and hAPOE mice, and were verified by transcriptomics, and immunopathology. RESULTSAll hAPOE strains showed AD phenotype progression by 8 mo, with females exhibiting the regional changes, which correlated with GO-term enrichments for glucose metabolism, perfusion, and immunity. Uncoupling analysis revealed APOE{varepsilon}4/{varepsilon}4 exhibited significant Type-1 uncoupling ({downarrow} glucose uptake, {uparrow} perfusion) at 8 and 12 mo, while APOE{varepsilon}3/{varepsilon}4 demonstrated Type-2 uncoupling ({uparrow} glucose uptake, {downarrow} perfusion), while immunopathology confirmed cell specific contributions. DISCUSSIONThis work highlights APOE{varepsilon}4 status in AD progression manifest as neurovascular uncoupling driven by immunological activation, and may serve as an early diagnostic biomarker.

neuroscience↗

bioRxiv2023

Levetiracetam Modulates Brain Metabolic Networks and Transcriptomic Signatures in the 5XFAD Mouse Model of Alzheimer's disease.

INTRODUCTIONSubcritical epileptiform activity is associated with impaired cognitive function and is commonly seen in patients with Alzheimers disease (AD). The anti-convulsant, levetiracetam (LEV), is currently being evaluated in clinical trials for its ability to reduce epileptiform activity and improve cognitive function in AD. The purpose of the current study was to apply pharmacokinetics (PK), network analysis of medical imaging, gene transcriptomics, and PK/PD modeling to a cohort of amyloidogenic mice to establish how LEV restores or drives alterations in the brain networks of mice in a dose-dependent basis using the rigorous preclinical pipeline of the MODEL-AD Preclinical Testing Core. METHODSChronic LEV was administered to 5XFAD mice of both sexes for 3 months based on allometrically scaled clinical dose levels from PK models. Data collection and analysis consisted of a multi-modal approach utilizing 18F-FDG PET/MRI imaging and analysis, transcriptomic analyses, and PK/PD modeling. RESULTSPharmacokinetics of LEV showed a sex and dose dependence in Cmax, CL/F, and AUC0-{infty}, with simulations used to estimate dose regimens. Chronic dosing at 10, 30, and 56 mg/kg, showed 18F-FDG specific regional differences in brain uptake, and in whole brain covariance measures such as clustering coefficient, degree, network density, and connection strength (i.e. positive and negative). In addition, transcriptomic analysis via nanoString showed dose-dependent changes in gene expression in pathways consistent 18F-FDG uptake and network changes, and PK/PD modeling showed a concentration dependence for key genes, but not for network covariance modeling. DISCUSSIONThis study represents the first report detailing the relationships of metabolic covariance and transcriptomic network changes resulting from LEV administration in 5XFAD mice. Overall, our results highlight non-linear kinetics based on dose and sex, where gene expression analysis demonstrated LEV dose- and concentration-dependent changes, along with cerebral metabolism, and/or cerebral homeostatic mechanisms relevant to human AD, which aligned closely with network covariance analysis of 18F-FDG images. Collectively, this study show cases the value of a multimodal connectomic, transcriptomic, and pharmacokinetic approach to further investigate dose dependent relationships in preclinical studies, with translational value towards informing clinical study design.

neuroscience↗

bioRxiv2021

The 677C>T variant in methylenetetrahydrofolate reductase causes morphological and functional cerebrovascular deficits in mice

Vascular contributions to cognitive impairment and dementia (VCID) particularly Alzheimers disease and related dementias (ADRDs) are increasing; however, mechanisms driving cerebrovascular decline are poorly understood. Methylenetetrahydrofolate reductase (MTHFR) is a critical enzyme in the folate and methionine cycles. Variants in MTHFR, notably 677C>T, are associated with dementias, but no mouse model existed to identify mechanisms by which MTHFR677C>T increases risk. Therefore, MODEL-AD created a novel knock-in (KI) strain carrying the Mthfr677C>T allele on the C57BL/6J background (Mthfr677C>T) to characterize morphology and function perturbed by the variant. Consistent with human clinical data, Mthfr677C>T mice have reduced enzyme activity in the liver and elevated plasma homocysteine levels. MTHFR enzyme activity as well as critical metabolites in the folate and methionine cycles are reduced in the Mthfr677C>T brain. Mice showed reduced tissue perfusion in numerous brain regions by PET/CT as well as significantly reduced vascular density and increased GFAP-expressing astrocytes in frontal cortex. Electron microscopy revealed cerebrovascular damage including endothelial and pericyte apoptosis, reduced luminal size, and increased astrocyte and microglial presence in the microenvironment. Collectively, these data suggest critical perturbations to cerebrovascular function in Mthfr677C>T mice supporting its use as a model for preclinical studies of VCID.

genetics↗