Biology subjects

Montine, T. J.

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

16 recordsLinked to original sources

bioRxiv2026

Novel LRRK2 Kinase Inhibitors Enhance Phosphorylation and Restore Adapter Protein Binding in LRRK2 Variants

Autosomal dominant mutations in LRRK2 that increase kinase activity significantly increase the risk of developing Parkinson's disease (PD). Efforts to reduce the resulting hyperphosphorylation have focused mainly on small-molecule type I kinase inhibitors (KIs); however, these bind the active, closed conformation of the LRRK2 kinase domain, which affects protein tertiary structure and can alter other functions of this multi-domain protein. Because disruption of these functions may contribute to pathogenesis independently of, or in addition to, augmented kinase activity, inhibitors that engage LRRK2 differently may offer an advantage. We hypothesize that KIs, which bind distinct conformations of LRRK2 and modulate non-kinase functions differently than type I inhibitors, may be beneficial. Here we tested two series of LRRK2 inhibitors, based on hesperadin (series A) and GNF-7 (series B), which each inhibited LRRK2 kinase activity in biochemical and cellular assays while differing in effects on other LRRK2 functions. Interestingly, series B compounds enhanced phosphorylation of interdomain heterologous phosphosites and restored 14-3-3 binding in LRRK2 variants with suppressed phosphorylation. These chemotypes provide tools for dissecting the consequences of different inhibitor-bound LRRK2 conformations and support conformation-selective inhibition as a therapeutic strategy for PD.

biochemistry↗

bioRxiv2026

APOE4 Drives Uniquely Dysfunctional Human Microglial States in Alzheimer's Disease

Variation in APOE, notably the {varepsilon}4 allele, profoundly shapes risk and severity of late-onset Alzheimers disease (AD), yet how it remodels human microglial states remains unresolved. We combine spatially resolved proteomic profiling with single-nuclear multiomic analyses to define microglial organization across APOE3/3 and APOE4/4 genotypes in AD. Quantifying condition-associated variation across the cellular manifold reveals a continuous landscape of microglial states. APOE4/4 shifts cells toward terminal states marked by loss of homeostatic identity, metabolic disruption, and incomplete acquisition of disease-associated programs. We identify an APOE4/4-enriched population in AD that exhibits inflammatory signaling without effective metabolic or phagocytic engagement, localizing to niches of gliosis and senescence, and coupled to chronic stress adaptation programs. Together with evidence that APOE4/4 potentiates the activation threshold of nascent microglia, these findings establish a unified framework for human microglial state change, linking genetic risk to spatial and molecular organization of immune responses in the AD brain. Graphical Abstract.APOE4/4 in Alzheimers disease reshapes microglial fate along continuous trajectories characterized by proteomic, transcriptional, and epigenetic programs consistent with chronic stress adaptation, alongside distinct composite spatial niches comprised of astrocytic gliosis and cellular senescence. O_FIG O_LINKSMALLFIG WIDTH=168 HEIGHT=200 SRC="FIGDIR/small/733295v1_ufig1.gif" ALT="Figure 1"> View larger version (75K): org.highwire.dtl.DTLVardef@b2afa4org.highwire.dtl.DTLVardef@12978f8org.highwire.dtl.DTLVardef@1c4e46dorg.highwire.dtl.DTLVardef@170e44d_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2026

Predicting Autopsy-Confirmed Neuropathology across Clinical, Neuroimaging, and CSF Biomarkers using Machine Learning

Accurate in vivo prediction of neuropathology is critical for advancing diagnosis and treatment of Alzheimers disease and related dementias (ADRDs). As many individuals with ADRDs have mixed pathologies ({beta}-amyloid, pathologic tau, cerebrovascular disease, vascular brain injury, pathologic TDP-43, hippocampal sclerosis, Lewy bodies), there is interest in determining how accurately we can infer these pathologic changes from clinical data, biofluid assays (e.g., CSF), and neuroimaging. Here we evaluated automated machine learning models trained on data curated by the AD Sequencing Project Phenotype Harmonization Consortium (N=7,894 individuals), to predict 26 autopsy-confirmed neuropathological outcomes. Predictors included in vivo clinical and cognitive composite scores, brain measures from 3D structural MRI and diffusion tensor imaging, image-derived measures of white matter hyperintensities (WMH), and CSF biomarkers. Predictive models were trained using ensemble learning with stratified cross-validation. We assessed performance using Spearmans rank correlation and Matthews correlation coefficient, to accommodate co-occurring pathologic changes. The added value of neuroimaging and CSF versus clinical features alone was quantified. Braak stage was among the most consistently predicted outcomes. CSF biomarkers best predicted {beta}-amyloid and tau pathology, but diffusion MRI metrics best captured vascular brain injury and white matter injury, and outperformed clinical and cognitive measures and anatomical MRI in predicting Lewy body disease. Anatomical measures from structural MRI outperformed standard clinical assessments in assessing neurodegeneration and hippocampal sclerosis, and WMH complemented cognitive measures in predicting TDP-43 pathology. These results establish a baseline for comparing modalities for inferring neuropathology.

neuroscience↗

bioRxiv2026

Massive-scale single-nucleus multi-omics identifies novel rare noncoding drivers of Parkinson's disease

Most genetic variants contributing to complex diseases reside in the noncoding genome. While common variants uncovered by genome-wide association studies often fail to explain much of the observed heritability of these diseases, rare variants often have higher effect sizes and cumulatively explain a larger portion of heritability. However, rare variants, particularly rare noncoding variants, have remained under-characterized largely due to the difficulties of accurately predicting variant functionality at scale, given that each individual carries an average of [~]10,000 rare variants. Here, we generated multi-omic data from >3.3 million nuclei sampled from five brain regions across a cohort of 80 individuals with Parkinsons disease (PD) and 21 neurologically normal control individuals with matched 30x whole-genome sequencing. We use this data to identify cell type-specific features of PD, map cell type-specific chromatin accessibility and expression quantitative trait loci, and train machine learning models to predict the effect of variants on gene regulation. We identify rare noncoding variants statistically associated with sporadic PD and extend our approaches to predict drivers of familial PD of unknown genetic origin. Our results underscore the significance of rare noncoding variants in complex diseases and provide a roadmap for applying similar approaches in other disease systems.

genetics↗

bioRxiv2024

regionalpcs: improved discovery of DNA methylation associations with complex traits

We have developed the regional principal components (rPCs) method, a novel approach for summarizing gene-level methylation. rPCs address the challenge of deciphering complex epigenetic mechanisms in diseases like Alzheimers disease (AD). In contrast to traditional averaging, rPCs leverage principal components analysis to capture complex methylation patterns across gene regions. Our method demonstrated a 54% improvement in sensitivity over averaging in simulations, offering a robust framework for identifying subtle epigenetic variations. Applying rPCs to the AD brain methylation data in ROSMAP, combined with cell type deconvolution, we uncovered 838 differentially methylated genes associated with neuritic plaque burden--significantly outperforming conventional methods. Integrating methylation quantitative trait loci (meQTL) with genome-wide association studies (GWAS) identified 17 genes with potential causal roles in AD, including MS4A4A and PI-CALM. Our approach is available in the Bioconductor package regionalpcs, opening avenues for research and facilitating a deeper understanding of the epigenetic landscape in complex diseases.

genomics↗

bioRxiv2024

Single-Cell Peripheral Immunoprofiling of Lewy Body Disease in a Multi-site Cohort

Studies implicated peripheral organs involvement in the development of Lewy body disease (LBD), a spectrum of neurodegenerative diagnoses that include Parkinsons Disease (PD) without or with dementia (PDD) and dementia with Lewy bodies (DLB). This study characterized peripheral immune responses unique to LBD at single-cell resolution. Peripheral mononuclear cell (PBMC) samples were collected from sites across the U.S. The diagnosis groups comprise healthy controls (HC, n=164), LBD (n=132), Alzheimers disease dementia (ADD, n=98), other neurodegenerative disease controls (NDC, n=21), and immune disease controls (IDC, n=14). PBMCs were activated with three stimulants, stained by surface and intracellular signal markers, and analyzed by flow cytometry, generating 1,184 immune features. Our model classified LBD from HC with an AUROC of 0.90{+/-}0.06. The same model distinguished LBD from ADD, NDC, IDC, or other common conditions associated with LBD. Model predictions were driven by pPLC{gamma}2, p38, and pSTAT5 signals from specific cell populations and activations.

neuroscience↗

bioRxiv2023

Human cerebrospinal fluid single exosomes in Parkinson and Alzheimer diseases

Exosomes are proposed to be important in the pathogenesis of prevalent neurodegenerative diseases. We report the first application of solid-state technology to perform multiplex analysis of single exosomes in human cerebrospinal fluid (CSF) obtained from the lumbar sac of people diagnosed with Alzheimers disease dementia (ADD, n=30) or Parkinsons disease dementia (PDD, n=30), as well as age-matched health controls (HCN, n=30). Single events were captured with mouse monoclonal antibodies to one of three different tetraspanins (CD9, CD63, or CD81) or with mouse (M) IgG control, and then probed with fluorescently labeled antibodies to prion protein (PrP) or CD47 to mark neuronal or presynaptic origin, as well as ADD- and PDD-related proteins: amyloid beta (A{beta}), tau, -synuclein, and Apolipoprotein (Apo) E. Data were collected only from captured events that were within the size range of 50 to 200 nm. Exosomes were present at approximately 100 billion per mL human CSF and were similarly abundant for CD9+ and CD81+ events, but CD63+ were only 22% to 25% of CD9+ (P<0.0001) or CD81+ (P<0.0001) events. Approximately 24% of CSF exosomes were PrP+, while only 2% were CD47+. The vast majority of exosomes were surface ApoE+, and the number of PrP-ApoE+ (P<0.001) and PrP+ApoE+ (P<0.01) exosomes were significantly reduced in ADD vs. HCN for CD9+ events only. A{beta}, tau, and -synuclein were not detected on the exosome surface or in permeabilized cargo. These data provide new insights into single exosome molecular features and highlight reduction in the CSF concentration of ApoE+ exosomes in patients with ADD.

neuroscience↗

bioRxiv2022

Proteomics of resilience to Alzheimer's disease identifies brain regional soluble Aβ levels, actin filament processes, and response to injury

Resilience to Alzheimers disease (RAD) is an uncommon combination of high disease burden without dementia that may provide critical insights into limiting the clinical impact of this incurable disease. In this study, we used mass spectrometry-based proteomics to quantify regional protein differences that characterize RAD. Starting with over 700 brain donations, we identified 43 extensively annotated research participants who met stringent inclusion exclusion criteria and analyzed matched isocortical regions, hippocampus, and caudate nucleus. Differential expression analysis of 7,115 soluble proteins identified lower isocortical and hippocampal soluble A{beta} peptide levels as a significant feature of RAD. Protein co-expression analysis revealed a group of 181 densely-interacting proteins significantly associated with RAD that were enriched for actin filament-based process, cellular detoxification, and wound healing in isocortex and hippocampus. We further support our findings using data from 689 human isocortical samples from four independent external cohorts that were the closest approximations of our clinico-pathologic groups. The molecular basis of RAD, a widely replicated state in older adults for which there is no experimental model, likely holds important insights into therapeutic interventions for Alzheimers disease.

neuroscience↗

bioRxiv2021

Single-synapse analyses of Alzheimers disease implicate pathologic tau, DJ1, CD47, and ApoE

Synaptic molecular characterization is limited for Alzheimers disease (AD). We used mass cytometry to quantify 38 probes in approximately 17 million single synaptic events from human brains without pathologic change or with pure AD or Lewy body disease (LBD), non-human primates (NHP), and PS/APP mice. Synaptic molecular integrity in humans and NHP was similar. Although not detected in human synapses, A{beta} was in PS/APP mice synaptic events. Clustering and pattern identification of human synapses showed expected disease-specific differences, like increased hippocampal pathologic tau in AD and reduced caudate dopamine transporter in LBD, and revealed novel findings including increased hippocampal CD47 and lowered DJ1 in AD and higher ApoE in AD dementia. Our results were independently supported by multiplex ion beam imaging of intact tissue.

neuroscience↗

bioRxiv2021

Spontaneous Isomerization of Asp387 in Tau is Diagnostic for Alzheimer's Disease: An Endogenous Indicator of Reduced Autophagic Flux

Amino acid isomerization is a spontaneous chemical modification potentially related to the underlying causes of Alzheimers disease (AD). We demonstrate that data-independent acquisition mass spectrometry can be used to characterize isomerization in complex protein mixtures. Examination of a large cohort of brain tissue samples revealed a striking relationship between isomerization of tau and AD status. Surprisingly, isomerization was found to be more abundant in both autosomal dominant and sporadic AD samples relative to controls. We hypothesize that lower autophagic flux in AD brains accounts for these results. Additional data, including quantitative analysis of proteins related to autophagy, strongly support this hypothesis. For example, isomerization of tau is positively correlated with levels of p62, a recognized indicator of autophagic inhibition. In sum, the data suggest strong ties between isomerization and autophagic flux, which may therefore represent a promising target for future investigations into the therapy and prevention of AD.

neuroscience↗

bioRxiv2021

An aging clock using metabolomic CSF

Quantifying the physiology of aging is essential for improving our understanding of age-related disease and the heterogeneity of healthy aging. Recent studies have shown that in regression models using "-omic" platforms to predict chronological age, residual variation in predicted age is correlated with health outcomes, and suggest that these "omic clocks" provide measures of biological age. This paper presents predictive models for age using metabolomic profiles of cerebrospinal fluid from healthy human subjects, and finds that metabolite and lipid data are generally able to predict chronological age within 10 years. We use these models to predict the age of a cohort of subjects with Alzheimers and Parkinsons disease and find an increase in prediction error, potentially indicating that the relationship between the metabolome and chronological age differs with these diseases. In our analysis of control subjects, we find the carnitine shuttle, sucrose, biopterin, vitamin E metabolism, tryptophan, and tyrosine to be the most associated with age. We showcase the potential usefulness of age prediction models in a small dataset (n = 85), and discuss techniques for drift correction, missing data imputation, and regularized regression which can be used to help mitigate the statistical challenges that commonly arise in this setting. To our knowledge, this work presents the first multivariate predictive metabolomic and lipidomic models for age using mass spectrometry analysis of cerebrospinal fluid.

systems biology↗

bioRxiv2021

Can we put Humpty Dumpty back together again? What does protein quantification mean in bottom-up proteomics?

Bottom-up proteomics provides peptide measurements and has been invaluable for moving proteomics into large-scale analyses. In bottom-up proteomics, protein parsimony and protein inference derived from these measured peptides are important for determining which protein coding genes are present. However, given the complexity of RNA splicing processes, and how proteins can be modified post-translationally, it is overly simplistic to assume that all peptides that map to a singular protein coding gene will demonstrate the same quantitative response. Accordingly, by assuming all peptides from a protein coding sequence are representative of the same protein we may be missing out on detecting important biological differences. To better account for the complexity of the proteome we need to think of new or better ways of handling peptide data.

biochemistry↗

bioRxiv2020

Single-cell epigenomic identification of inherited risk loci in Alzheimer's and Parkinson's disease

Genome-wide association studies (GWAS) have identified thousands of variants associated with disease phenotypes. However, the majority of these variants do not alter coding sequences, making it difficult to assign their function. To this end, we present a multi-omic epigenetic atlas of the adult human brain through profiling of the chromatin accessibility landscapes and three-dimensional chromatin interactions of seven brain regions across a cohort of 39 cognitively healthy individuals. Single-cell chromatin accessibility profiling of 70,631 cells from six of these brain regions identifies 24 distinct cell clusters and 359,022 cell type-specific regulatory elements, capturing the regulatory diversity of the adult brain. We develop a machine learning classifier to integrate this multi-omic framework and predict dozens of functional single nucleotide polymorphisms (SNPs), nominating gene and cellular targets for previously orphaned GWAS loci. These predictions both inform well-studied disease-relevant genes, such as BIN1 in microglia for Alzheimers disease (AD) and reveal novel gene-disease associations, such as STAB1 in microglia and MAL in oligodendrocytes for Parkinsons disease (PD). Moreover, we dissect the complex inverted haplotype of the MAPT (encoding tau) PD risk locus, identifying ectopic enhancer-gene contacts in neurons that increase MAPT expression and may mediate this disease association. This work greatly expands our understanding of inherited variation in AD and PD and provides a roadmap for the epigenomic dissection of noncoding regulatory variation in disease.

genomics↗

bioRxiv2019

A Consensus Proteomic Analysis of Alzheimer’s Disease Brain and Cerebrospinal Fluid Reveals Early Changes in Energy Metabolism Associated with Microglia and Astrocyte Activation

Our understanding of the biological changes in the brain associated with Alzheimers disease (AD) pathology and cognitive impairment remains incomplete. To increase our understanding of these changes, we analyzed dorsolateral prefrontal cortex of control, asymptomatic AD, and AD brains from four different centers by label-free quantitative mass spectrometry and weighted protein co-expression analysis to obtain a consensus protein co-expression network of AD brain. This network consisted of 13 protein co-expression modules. Six of these modules correlated with amyloid-{beta} plaque burden, tau neurofibrillary tangle burden, cognitive function, and clinical functional status, and were altered in asymptomatic AD, AD, or in both disease states. These six modules reflected synaptic, mitochondrial, sugar metabolism, extracellular matrix, cytoskeletal, and RNA binding/splicing biological functions. The identified protein network modules were preserved in a community-based cohort analyzed by a different quantitative mass spectrometry approach. They were also preserved in temporal lobe and precuneus brain regions. Some of the modules were influenced by aging, and showed changes in other neurodegenerative diseases such as frontotemporal dementia and corticobasal degeneration. The module most strongly associated with AD pathology and cognitive impairment was the sugar metabolism module. This module was enriched in AD genetic risk factors, and was also highly enriched in microglia and astrocyte protein markers associated with an anti-inflammatory state, suggesting that the biological functions it represents serve a protective role in AD. Proteins from the sugar metabolism module were increased in cerebrospinal fluid from asymptomatic AD and AD cases, highlighting their potential as biomarkers of the altered brain network. In this study of >2000 brains and nearly 400 cerebrospinal fluid samples by quantitative proteomics, we identify proteins and biological processes in AD brain that may serve as therapeutic targets and fluid biomarkers for the disease.

systems biology↗

bioRxiv2019

CSF sTREM2 correlates with CSF tau in advancing Parkinson’s disease

Parkinsons disease (PD) is the second most common neurodegenerative disease after Alzheimers disease (AD) and affects 1% of the population above 60 years old. Although PD commonly manifests with motor symptoms, a majority of patients with PD subsequently develop cognitive impairment which often progresses to dementia, a major cause of morbidity and disability. PD is characterized by -synuclein accumulation that frequently associates with amyloid beta (A{beta}) and tau fibrils, the hallmarks of AD neuropathologic changes; this co-occurrence suggests that onset of cognitive decline in PD may be associated with appearance of pathologic A{beta} and/or tau. Recent studies have highlighted the appearance of the soluble form of the Triggering Receptor Expressed on Myeloid cells 2 (sTREM2) receptor in CSF during development of AD. Given the known association of microglial activation with advancing PD, we investigated whether CSF and/or plasma sTREM2 increased with progression to PD dementia. We examined 165 participants consisting of 17 cognitively normal elderly, 45 PD patients with no cognitive impairment, 86 with mild cognitive impairment, and 17 with dementia. Stratification of subjects by CSF A{beta} and tau levels revealed that CSF sTREM2 concentrations were elevated in PD subgroups with abnormal tau, but not A{beta}, CSF concentration. These findings indicate that CSF sTREM2 could serve as a surrogate immune biomarker of neuronal injury in PD that is associated with cognitive decline.\n\nOne sentence summaryCSF sTREM2 correlates with CSF tau in PD

neuroscience↗

bioRxiv2017

An improved ATAC-seq protocol reduces background and enables interrogation of frozen tissues

We present Omni-ATAC, an improved ATAC-seq protocol for chromatin accessibility profiling that works across multiple applications with substantial improvement of signal-to-background ratio and information content. The Omni-ATAC protocol enables chromatin accessibility profiling from archival frozen tissue samples and 50 m sections, revealing the activities of disease-associated DNA elements in distinct human brain structures. The Omni-ATAC protocol enables the interrogation of personal regulomes in tissue context and translational studies.

genomics↗