Biology subjects

Grabowski, T. J.

Publications and source records attributed to Grabowski, T. J..

5 recordsLinked to original sources

bioRxiv2026

Digital Atlases to Unlock the Potential of Brain Biorepository Tissues for Interdisciplinary Research

Human brain tissue preserved in biorepositories is foundational for the structural, cellular, and biomolecular research necessary for a mechanistic understanding of neurological diseases. Realizing the research potential of these valuable resources requires well-characterized research-relevant tissue that can be efficiently identified by investigators and incorporated into the conceptual and computational frameworks of interdisciplinary research. Several large-scale efforts to improve research reliability and reproducibility have sought to characterize and annotate the processes by which these samples are collected, yet limited progress has been made on standardizing spatial information for these samples. Biorepositories systematically collect brain tissue according to a brain sampling protocol (BSP) that differs between institutions, yet explicit spatial information regarding the samples may not be documented in standard operating procedures (SOPs). The amount of anatomical location details available to investigators are inconsistent across biorepositories and typically lack sufficient anatomical precision to ensure correspondence with samples from other biorepositories or research relevant brain regions specified by neuroimaging, functional, or disease-susceptibility criteria. Here, we introduce a pipeline for developing a Spatial Atlas for Mapping Protocol Locations of Ex vivo Samples (SAMPLES), which uses a neuroimaging framework to create a 3D representation of a BSP through a metrically precise digital instantiation of the procedures for brain extraction, segmentation, slicing, and sampling on a modern digital brain template. SAMPLES incorporates modern neuroinformatics conventions to create explicit 3D labels of BSP-defined samples that can be interactively visualized with freely available neuroimaging software. We illustrate the pipeline by developing an atlas for the protocol from the University of Washington BioRepository and Integrated Neuropathology laboratory (UW BRaIN SAMPLES). By providing an explicit, computable reference, SAMPLES atlases can support the efficient identification, referencing, and utilization of postmortem samples for interdisciplinary research. These capabilities enable biorepository workflows, data harmonization across biorepositories, and integration with antemortem neuroimaging.

neuroscience↗

bioRxiv2026

QNPtoVox: A methods pipeline for mapping 2D quantitative neuropathology to 3D MNI voxel space.

1.Quantitative neuropathology has advanced through whole-slide imaging and digital histology platforms. Yet, these measurements rarely align with neuroimaging coordinate frameworks that may be useful for spatial modeling and other applications. QNPtoVox, short for quantitative neuropathology to voxels, is a reproducible, modular pipeline that transforms quantitative metrics generated by digital pathology software (HALO) into voxel-based maps registered to a standard common coordinate (MNI) template. The workflow integrates digital histopathology, gross tissue photography, ex-vivo MRI, and nonlinear registration to generate spatially standardized 3D pathology representations. This Methods article provides a complete procedural description, including required materials, step-wise instructions, operator-dependent checkpoints, expected outputs, reproducibility evaluation, and troubleshooting. QNPtoVox enables voxel-level integration of neuropathology with neuroimaging tools, unlocking existing histopathology datasets for computational modeling and cross-cohort harmonization.

neuroscience↗

bioRxiv2026

The Caudate Nucleus Exhibits Distinct Pathology and Cell Type-Specific Responses Across Alzheimer's Disease

A{beta} presence in the caudate nucleus (Ca) partially defines Thal stage III in Alzheimers disease (AD), but little is known about ADs cellular impact on the region. Leveraging a public basal ganglia taxonomy of cellular populations, we generated a cellular resolution atlas of AD-associated pathological changes in Ca. Unlike cortex, we found that Ca AD pathology is dominated by two key features: phosphorylated tau (pTau)-containing neuropil threads enriched near oligodendrocytes in white matter tracts and amyloid-{beta} diffuse plaques enriched in gray matter. Although AD pathology in affected cortical regions results in neuronal loss, we find no AD-driven reductions in neuron proportions in Ca. However, there were observable changes in multiple cellular populations. Protoplasmic astrocytes and FLT1+/IL1B+ microglia increased in abundance with global pTau levels. We also observe gene expression changes in fast-spiking PTHLH-PVALB interneurons indicative of disrupted signaling pathways and altered intrinsic physiological properties. This work provides a cellular-resolution framework for understanding AD pathology in Ca.

neuroscience↗

bioRxiv2024

Unraveling Alzheimer's Disease: Investigating Dynamic Functional Connectivity in the Default Mode Network through DCC-GARCH Modeling

Alzheimers disease (AD) has a prolonged latent phase. Sensitive biomarkers of amyloid beta (A{beta}), in the absence of clinical symptoms, offer opportunities for early detection and identification of patients at risk. Current A{beta} biomarkers, such as CSF and PET biomarkers, are effective but face practical limitations due to high cost and limited availability. Recent blood plasma biomarkers, though accessible, still incur high costs and lack physiological significance in the Alzheimers process. This study explores the potential of brain functional connectivity (FC) alterations associated with AD pathology as a non-invasive avenue for A{beta} detection. While current stationary FC measurements lack sensitivity at the single-subject level, our investigation focuses on dynamic FC using resting-state functional MRI (rs-fMRI) and introduces the Generalized Auto-Regressive Conditional Heteroscedastic Dynamic Conditional Correlation (DCC-GARCH) model. Our findings demonstrate the superior sensitivity of DCC-GARCH to CSF A{beta} status, and offer key insights into dynamic functional connectivity analysis in AD.

neuroscience↗

bioRxiv2018

Genetic data and cognitively-defined late-onset Alzheimer’s disease subgroups

Categorizing people with late-onset Alzheimers disease into biologically coherent subgroups is important for personalized medicine. We evaluated data from five studies (total n=4 050, of whom 2 431 had genome-wide single nucleotide polymorphism (SNP) data). We assigned people to cognitively-defined subgroups on the basis of relative performance in memory, executive functioning, visuospatial functioning, and language at the time of Alzheimers disease diagnosis. We compared genotype frequencies for each subgroup to those from cognitively normal elderly controls. We focused on APOE and on SNPs with p<10-5 and odds ratios more extreme than those previously reported for Alzheimers disease (<0.77 or >1.30). There was substantial variation across studies in the proportions of people in each subgroup. In each study, higher proportions of people with isolated substantial relative memory impairment had [≥]1 APOE e4 allele than any other subgroup (overall p= 1.5 x 10-27). Across subgroups, there were 33 novel suggestive loci across the genome with p<10-5 and an extreme OR compared to controls, of which none had statistical evidence of heterogeneity and 30 had ORs in the same direction across all datasets. These data support the biological coherence of cognitively-defined subgroups and nominate novel genetic loci.

genetics↗