Biology subjects

Day, G. S.

Publications and source records attributed to Day, G. S..

8 recordsLinked to original sources

bioRxiv2026

Targeted proteomics of postmortem human brain reveals neurobiologic heterogeneity in Alzheimer's disease using NULISA technology

BackgroundAlzheimers disease (AD) is clinicopathologically heterogeneous. A proportion of patients living with AD present clinically at a younger onset of cognitive symptoms before 65 years old and/or non-amnestic clinical syndromes. Neuropathologically, corticolimbic distribution of neurofibrillary tangle pathology occurs on a continuum with some cases having greater cortical tau pathology relative to limbic regions and others with relatively restricted accumulation in limbic structures. These patterns of corticolimbic tangle distribution are associated with clinical presentation and age at onset. This study sought to examine protein expression differences across the spectrum of clinicopathologic heterogeneity using the NULISA targeted proteomics platform. MethodsA series of thirteen neuropathologically diagnosed AD cases from Mayo Clinic prospectively followed research studies were selected to reflect heterogeneity of clinical syndromes and corticolimbic distribution of tangle pathology. Frozen postmortem brain tissue samples were isolated from inferior parietal cortex and homogenized in RIPA buffer for analysis using Alamar Biosciences NULISA CNS disease 120 panel. Applying a conservative detection threshold of 75% level of detection for the novel application of NULISA in human brain, we evaluated levels of 69 of 129 protein targets across samples. We examined associations between age at onset cognitive symptoms and corticolimbic distribution of tangles (CLix) separately with individual protein targets using linear regression analysis. ResultsAD cases with a younger age at onset had higher measured levels of ubiquitin, while older age was associated with higher levels of total tau, CRH, and NPTX2. Investigations of corticolimbic heterogeneity revealed AD cases with lower CLix score (i.e., cortical predominant distribution of tau) had higher measured p-tau181, p-tau231, ubiquitin, and p62. AD cases with higher CLix (i.e., relative cortical sparing) had higher levels of total tau, CRH, NPTX2, MDH1, and HBA1. Brain-derived total tau consistently showed a stronger association in both models. ConclusionThis work demonstrates the utility of postmortem proteomics for investigating biomarkers associated with AD clinicopathologic heterogeneity. We observed proteomic differences in synapse integrity, tau post-translational modification, and ubiquitination associated with age at symptomatic onset and corticolimbic distribution of tangle pathology.

neuroscience↗

bioRxiv2026

TDP-43 subtypes shape transcriptomic signatures in Alzheimer's disease

TAR DNA-binding protein 43 (TDP-43) pathology frequently co-occurs with Tau neurofibrillary tangles (NFTs) and amyloid {beta} plaques in Alzheimers disease (AD), driving significant clinical heterogeneity. Whether TDP-43 engages autonomous molecular programs or instead amplifies Tau-driven neurodegeneration remains difficult to resolve, largely because these pathologies often co-occur. To separate these overlapping signatures, we generated regionally resolved transcriptomic profiles from cognitively normal controls (Controls), neuropathologically defined cohorts of AD, AD with limbic-predominant age-related TDP-43 encephalopathy (AD/LATE), and frontotemporal lobar degeneration (FTLD-TDP), categorizing them by their distinct TDP-43 subtypes (types and {beta} for AD/LATE; types A and B for FTLD-TDP). By integrating transcriptomic profiles with quantitative measures of phosphorylated TDP-43 (pTDP-43) and Tau (pTau), we separated pathology-associated signals within mixed disease contexts. We found that TDP-43 is linked to distinct transcriptomic programs in AD/LATE that are largely uncoupled from Tau burden and diverge from those observed in FTLD-TDP. These signatures showed regional specificity, with transcriptomic remodeling occurring in the amygdala across both diseases, whereas frontal cortex alterations were largely restricted to FTLD-TDP. Furthermore, by stratifying cases by TDP-43 morphological subtype, we unmasked specific biological trajectories, from immune activation to unique cellular vulnerabilities, that are not apparent in unstratified cohorts. Together, our findings provide a framework for decoupling mixed proteinopathies and demonstrate that TDP-43 shapes autonomous, subtype-dependent transcriptional landscapes in AD.

neuroscience↗

bioRxiv2026

Neurodegeneration risk variants promote lysosomal TMEM106B fibrilaccumulation

Variants in TMEM106B and GRN, which encode lysosomal proteins, interact through unknown mechanisms to increase the risk of age-related cognitive decline and neurodegeneration. Here, we show that these variants converge on a single molecular intermediate: the cleaved intra-lysosomal fibril core of TMEM106B, a precursor to amyloid fibrils that accumulate in the aging brain. A protein-coding TMEM106B risk variant (p.T185) drives fibril core accumulation by impairing its degradation and GRN risk variants amplify this effect. Mice over-expressing the fibril core develop hallmarks of neurodegeneration, and cryo-electron tomography reveals intra-lysosomal fibrils in cultured neurons, mice, and diseased human brain. In GRN-mutation carriers, in whom fibril burden is greatest, fibrils extrude through ruptured lysosomal membranes. These findings identify intra-lysosomal TMEM106B fibrillization as a convergent neurodegeneration mechanism and potential therapeutic target.

cell biology↗

bioRxiv2024

Nomination of a novel plasma protein biomarker panel capable of classifying Alzheimer's disease dementia with high accuracy in an African American cohort

IntroductionAfrican Americans (AA) are widely underrepresented in plasma biomarker studies for Alzheimers disease (AD) and current diagnostic biomarker candidates do not reflect the heterogeneity of AD. MethodsUntargeted proteome measurements were obtained using the SomaScan 7k platform to identify novel plasma biomarkers for AD in a cohort of AA clinically diagnosed as AD dementia (n=183) or cognitively unimpaired (CU, n=145). Machine learning approaches were implemented to identify the set of plasma proteins that yields the best classification accuracy. ResultsA plasma protein panel achieved an area under the curve (AUC) of 0.91 to classify AD dementia vs CU. The reproducibility of this finding was observed in the ANMerge plasma and AMP-AD Diversity brain datasets (AUC=0.83; AUC=0.94). DiscussionThis study demonstrates the potential of biomarker discovery through untargeted plasma proteomics and machine learning approaches. Our findings also highlight the potential importance of the matrisome and cerebrovascular dysfunction in AD pathophysiology.

neuroscience↗

bioRxiv2023

Increasing hub disruption parallels dementia severity in autosomal dominant Alzheimer disease

Hub regions in the brain, recognized for their roles in ensuring efficient information transfer, are vulnerable to pathological alterations in neurodegenerative conditions, including Alzheimer Disease (AD). Given their essential role in neural communication, disruptions to these hubs have profound implications for overall brain network integrity and functionality. Hub disruption, or targeted impairment of functional connectivity at the hubs, is recognized in AD patients. Computational models paired with evidence from animal experiments hint at a mechanistic explanation, suggesting that these hubs may be preferentially targeted in neurodegeneration, due to their high neuronal activity levels--a phenomenon termed "activity-dependent degeneration". Yet, two critical issues were unresolved. First, past research hasnt definitively shown whether hub regions face a higher likelihood of impairment (targeted attack) compared to other regions or if impairment likelihood is uniformly distributed (random attack). Second, human studies offering support for activity-dependent explanations remain scarce. We applied a refined hub disruption index to determine the presence of targeted attacks in AD. Furthermore, we explored potential evidence for activity-dependent degeneration by evaluating if hub vulnerability is better explained by global connectivity or connectivity variations across functional systems, as well as comparing its timing relative to amyloid beta deposition in the brain. Our unique cohort of participants with autosomal dominant Alzheimer Disease (ADAD) allowed us to probe into the preclinical stages of AD to determine the hub disruption timeline in relation to expected symptom emergence. Our findings reveal a hub disruption pattern in ADAD aligned with targeted attacks, detectable even in pre-clinical stages. Notably, the disruptions severity amplified alongside symptomatic progression. Moreover, since excessive local neuronal activity has been shown to increase amyloid deposition and high connectivity regions show high level of neuronal activity, our observation that hub disruption was primarily tied to regional differences in global connectivity and sequentially followed changes observed in A{beta} PET cortical markers is consistent with the activity-dependent degeneration model. Intriguingly, these disruptions were discernible 8 years before the expected age of symptom onset. Taken together, our findings not only align with the targeted attack on hubs model but also suggest that activity-dependent degeneration might be the cause of hub vulnerability. This deepened understanding could be instrumental in refining diagnostic techniques and developing targeted therapeutic strategies for AD in the future.

neuroscience↗

bioRxiv2023

PNMA2 forms non-enveloped virus-like capsids that trigger paraneoplastic neurological syndrome

The paraneoplastic Ma antigen (PNMA) genes are associated with cancer-induced paraneoplastic syndromes that present with neurological symptoms and autoantibody production. How PNMA proteins trigger a severe autoimmune disease is unclear. PNMA genes are predominately expressed in the central nervous system with little known functions but are ectopically expressed in some tumors. Here, we show that PNMA2 is derived from a Ty3 retrotransposon that encodes a protein which forms virus-like capsids released from cells as non-enveloped particles. Recombinant PNMA2 capsids injected into mice induce a robust autoimmune reaction with significant generation of autoantibodies that preferentially bind external "spike" PNMA2 capsid epitopes, while capsid-assembly-defective PNMA2 protein is not immunogenic. PNMA2 autoantibodies present in cerebrospinal fluid of patients with anti-Ma2 paraneoplastic neurologic disease show similar preferential binding to PNMA2 "spike" capsid epitopes. These observations suggest that PNMA2 capsids released from tumors trigger an autoimmune response that underlies Ma2 paraneoplastic neurological syndrome.

neuroscience↗

bioRxiv2022

Multimodal brain age estimates relate to Alzheimer disease biomarkers and cognition in early stages: a cross-sectional observational study

BackgroundEstimates of "brain-predicted age" quantify apparent brain age compared to normative trajectories of neuroimaging features. The brain age gap (BAG) between predicted and chronological age is elevated in symptomatic Alzheimer disease (AD), but has not been well explored in preclinical AD. Prior studies have typically modeled BAG with structural magnetic resonance imaging (MRI), but more recently other modalities, including functional connectivity (FC) and multimodal MRI, have been explored. MethodsWe trained three models to predict age from FC, volumetric (Vol), or multimodal MRI (Vol+FC) in 390 control participants (18-89 years old). In independent samples of 144 older adult controls, 154 preclinical AD participants, and 154 cognitively impaired (CI; CDR > 0) participants, we tested relationships between BAG and AD biomarkers of amyloid, tau, and neurodegeneration, as well as a global cognitive composite. ResultsAll models predicted age in the control training set, with the multimodal model outperforming the unimodal models. All three BAG estimates were significantly elevated in CI compared to controls. FC-BAG and Vol+FC-BAG were marginally reduced in preclinical AD participants compared to controls. In CI participants only, elevated Vol-BAG and Vol+FC-BAG were associated with more advanced AD pathology and lower cognitive performance. ConclusionsBoth FC-BAG and Vol-BAG are elevated in CI participants. However, FC and volumetric MRI also capture complementary signals. Specifically, FC-BAG may capture a unique biphasic response to preclinical AD pathology, while Vol-BAG may capture pathological progression and cognitive decline in the symptomatic stage. A multimodal age-prediction model captures these modality-specific patterns, and further, improves sensitivity to healthy age differences. FundingThis work was supported by the National Institutes of Health (P01-AG026276, P01-AG03991, P30-AG066444, 5-R01-AG052550, 5-R01-AG057680, 1-R01-AG067505, 1S10RR022984-01A1, U19-AG032438), the BrightFocus Foundation (A2022014F), and the Alzheimers Association (SG-20-690363-DIAN).

neuroscience↗

bioRxiv2022

Neuroimaging within the Dominantly Inherited Alzheimer's Network (DIAN): PET and MRI

The Dominantly Inherited Alzheimer Network (DIAN) Observational Study is an international collaboration studying autosomal dominant Alzheimer disease (ADAD). This rare form of Alzheimer disease (AD) is caused by mutations in the presenilin 1 (PSEN1), presenilin 2 (PSEN2), or amyloid precursor protein (APP) genes. As individuals from these families have a 50% chance of inheriting the familial mutation, this provides researchers with a well-matched cohort of carriers vs non-carriers for case-control studies. An important trait of ADAD is that the age at symptom onset is highly predictable and consistent for each specific mutation, allowing researchers to estimate an individuals point in their disease time course prior to symptom onset. Although ADAD represents only a small proportion (approximately 0.1%) of all AD cases, studying this form of AD allows researchers to investigate preclinical AD and the progression of changes that occur within the brain prior to AD symptom onset. Furthermore, the young age at symptom onset (typically 30-60 years) means age-related comorbidities are much less prevalent than in sporadic AD, thereby allowing AD pathophysiology to be studied independent of these confounds. A major goal of the DIAN Observational Study is to create a global resource for AD researchers. To that end, the current manuscript provides an overview of the DIAN magnetic resonance imaging (MRI) and positron emission tomography (PET) protocols and highlights the key imaging results of this study to date.

neuroscience↗