Biology subjects

Lamar, M.

Publications and source records attributed to Lamar, M..

3 recordsLinked to original sources

bioRxiv2025

Aged brain multi-omic integration captures immunometabolic and sex variation

Resolving the molecular basis for heterogeneous ageing in the human brain requires integrating its diverse molecular layers. Here we applied a tensor-decomposition framework to jointly analyse single-nucleus RNA-seq, DNA methylation, H3K9ac histone acetylation and proteomic data from 276 post-mortem human cortices. The analysis uncovered two dominant, multi-omic themes. First, we identified an immunometabolic axis characterised by microglial activation, suppression of PI3K-Akt-mTOR signalling and epigenetic signatures that suggest repurposing of developmental transcription factors such as BARHL1. Second, we decomposed the effect of sex into a multi-omic program linked to cellular plasticity: although driven by canonical sex-chromosome genes, this axis was epigenetically enriched for pathways regulating stem-cell pluripotency and exhibited a female-biased shift toward precursor-like states in the oligodendrocyte lineage. Together, these findings deliver a high-resolution atlas of glial ageing and demonstrate that broad risk factors manifest as complex, cell-specific vulnerabilities; an insight critical for the development of targeted therapeutic strategies.

neuroscience↗

bioRxiv2023

Delayed primacy recall performance predicts post mortem Alzheimers disease pathology from unimpaired ante mortem cognitive baseline

INTRODUCTIONWe propose a novel method to assess delayed primacy in the CERAD memory test. We then examine whether this measure predicts post mortem Alzheimers disease (AD) neuropathology in individuals who were clinically unimpaired at baseline. METHODSA total of 1096 individuals were selected from the Rush Alzheimers Disease Center database registry. All participants were clinically unimpaired at baseline, and had subsequently undergone brain autopsy. Average age at baseline was 78.8 (6.92). A Bayesian regression analysis was carried out with global pathology as outcome; demographic, clinical and APOE data as covariates; and cognitive predictors, including delayed primacy. RESULTSGlobal AD pathology was best predicted by delayed primacy. Secondary analyses showed that delayed primacy was mostly associated with neuritic plaques, whereas total delayed recall was associated with neurofibrillary tangles. DISCUSSIONWe conclude that CERAD-derived delayed primacy is a useful metric for early detection and diagnosis of AD in unimpaired individuals.

neuroscience↗

bioRxiv2023

Interpretable deep learning approach for extracting cognitive features from hand-drawn images of intersecting pentagons in older adults

Hand drawing involves multiple neural systems for planning and precise control of sequential movements, making it a valuable cognitive test for older adults. However, conventional visual assessment of drawings may not capture intricate nuances that could help track cognitive states. To address this issue, we utilized a deep-learning model, PentaMind, to examine cognition-related features from hand-drawn images of intersecting pentagons. PentaMind, trained on 13,777 images from 3,111 participants in three aging cohorts, explained 23.3% of the variance in global cognitive scores, a comprehensive hour-long cognitive battery. The models performance, which was 1.92 times more accurate than conventional visual assessment, significantly improved the detection of cognitive decline. The improvement in accuracy was due to capturing additional drawing features that we found to be associated with motor impairments and cerebrovascular pathologies. By systematically modifying the input images, we discovered several important drawing attributes for cognition, including line waviness. Our results demonstrate that hand-drawn images can provide rich cognitive information, enabling rapid assessment of cognitive decline and suggesting potential clinical implications in dementia.

neuroscience↗