Biology subjects

Buckley, R.

Publications and source records attributed to Buckley, R..

6 recordsLinked to original sources

bioRxiv2026

Continuous amyloid staging complements global amyloid burden in early Alzheimer's disease

Introduction: Early Alzheimer's disease (AD) staging remains challenging because clinical categories and global amyloid PET measures provide only coarse characterization of disease progression. We developed a continuous amyloid staging score from regional amyloid PET to complement global amyloid burden. Methods: Using longitudinal florbetapir PET from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we trained an end-to-end deep learning model to directly estimate a continuous amyloid staging score. We evaluated longitudinal consistency, its relationship with global amyloid burden, regional contributors to early-stage variation, and whether the staging score stratified subsequent memory decline among participants matched for baseline global amyloid burden. Cognitive analyses were replicated in A4+LEARN. Results: The staging score better preserved longitudinal visit order than existing amyloid staging approaches. During early disease stages, it captured regional amyloid variation despite relatively stable global amyloid burden. Among participants with similar baseline global amyloid burden, higher staging scores were associated with faster subsequent memory decline in both ADNI and A4+LEARN. Discussion: A continuous amyloid staging score complements global amyloid burden for early AD staging and cognitive risk stratification. Keywords: Alzheimer's disease; amyloid PET; disease staging; cognitive decline

neuroscience↗

bioRxiv2026

Mutagenic and carcinogenic potency determinations for NDMA support the cumulative dose assumption underpinning the less-than-lifetime Threshold of Toxicological Concern

The management of N-nitrosamine impurities challenges pharmaceutical development and regulation worldwide. Because most medicinal exposures are shorter than lifetime and absolute impurity exclusion is impossible, reliable approaches to define duration-specific intake limits are essential. On the premise that carcinogenic risk is proportional to cumulative dose, the Less-Than-Lifetime (LTL) Threshold of Toxicological Concern (TTC) framework defines progressively lower intake limits for mutagenic impurities over longer exposures. However, N-nitrosamines are currently treated as a cohort of concern, necessitating compound-specific evaluation placing reliance on in vivo mutagenicity assays for impurity qualifications. To better understand durational potency relationships and the application domain of the LTL-TTC, we apply benchmark dose (BMD) modelling to cumulative-dose-scaled transgenic rodent (TGR), error-corrected sequencing and rodent carcinogenicity datasets for N-nitrosodimethylamine (NDMA) obtained from the published literature. For TGR, cumulative-dose scaling better resolved liver as the most sensitive organ and reduced interstudy variability: liver BMDs spanned [~]80-fold in daily-dose units but only [~]20-fold when scaled to cumulative dose. Among closely-matched mouse liver gavage studies, cumulative-dose BMDs only varied by [~]2.5-fold across 1 to 28-day treatment regimens. Error-corrected sequencing also demonstrated parity, with acute-dose regimens producing mutation burdens near-identical (< 1.2-fold) to those cumulated from 28-day repeat-dose regimens. Comparable results were obtained from carcinogenicity datasets confirming proportionality-of-effect to cumulative dose. These findings empirically support the validity of the LTL-TTC concept. More broadly, they demonstrate that short-term in vivo mutagenicity assays can serve as reliable surrogates for lifetime carcinogenicity studies, strengthening the scientific and regulatory basis for duration-adjusted acceptable intakes for N-nitrosamine impurities.

pharmacology and toxicology↗

bioRxiv2024

A-Islands: A plant dataset for biodiversity research and species monitoring on Australian islands

Australias coastline is fringed by more than 8,000 continental islands. These islands feature a diverse array of landforms, rock and soil types and geological origins. Some of these islands are among the least invaded, most pristine habitats in Australia and support high plant diversity. Here, we present a new Australia-wide curated dataset for plant species occurrences on islands. Combining information from 1,349 species lists and floras, A-Islands includes data on >6,500 plant species from 844 islands ranging in size from 18 m2 to 4,400 km2, exhibiting different degrees of isolation from the mainland, and spanning all major Australian climate zones. Of these, 251 islands have been repeatedly sampled up to 11 times making it possible to investigate temporal compositional change. A-Islands is open access and will be continuously updated. Its simple data structure consisting of three comma separated files allows easy integration with other Australian and global plant-occurrence databases and can serve as a repository for island research in Australia. Knowing which species occur on Australia's islands will provide opportunities for future research, including studying changes in biodiversity and species-turnover within and among archipelagos, tests of classical island biogeography theory and as a baseline for ecological monitoring and conservation.

ecology↗

bioRxiv2021

Inter-laboratory automation of the in vitro micronucleus assay using imaging flow cytometry and deep learning

The in vitro micronucleus assay is a globally significant method for DNA damage quantification used for regulatory compound safety testing in addition to inter-individual monitoring of environmental, lifestyle and occupational factors. However it relies on time-consuming and user-subjective manual scoring. Here we show that imaging flow cytometry and deep learning image classification represents a capable platform for automated, inter-laboratory operation. Images were captured for the cytokinesis-block micronucleus (CBMN) assay across three laboratories using methyl methanesulphonate (1.25 - 5.0 {micro}g/mL) and/or carbendazim (0.8 - 1.6 {micro}g/mL) exposures to TK6 cells. Human-scored image sets were assembled and used to train and test the classification abilities of the "DeepFlow" neural network in both intra- and inter-laboratory contexts. Harnessing image diversity across laboratories yielded a network able to score unseen data from an entirely new laboratory without any user configuration. Image classification accuracies of 98%, 95%, 82% and 85% were achieved for mononucleates, binucleates, mononucleates with MN and binucleates with MN, respectively. Successful classifications of trinucleates (90%) and tetranucleates (88%) in addition to other or unscorable phenotypes (96%) were also achieved. Attempts to classify extremely rare, tri- and tetranucleated cells with micronuclei into their own categories were less successful ([≤] 57%). Benchmark dose analyses of human or automatically scored micronucleus frequency data yielded quantitation of the same equipotent dose regardless of scoring method. We conclude that this automated approach offers significant potential to broaden the practical utility of the CBMN method across industry, research and clinical domains. We share our strategy using openly-accessible frameworks.

pharmacology and toxicology↗

bioRxiv2020

Genetic Variants and Functional Pathways Associated with Resilience to Alzheimer's Disease

Approximately 30% of older adults exhibit the neuropathologic features of Alzheimers disease (AD) without signs of cognitive impairment. Yet, little is known about the genetic factors that allow these potentially resilient individuals to remain cognitively normal in the face of substantial neuropathology. We performed a large, genome-wide association study (GWAS) of two previously validated metrics of cognitive resilience quantified using a latent variable modeling approach and representing better-than-predicted cognitive performance for a given level of neuropathology. Data were harmonized across 5,108 participants from a clinical trial of AD and three longitudinal cohort studies of cognitive aging. All analyses were run across all participants and repeated restricting the sample to individuals with normal cognition to identify variants at the earliest stages of disease. As expected, all resilience metrics were genetically correlated with cognitive performance and education attainment traits (p-values<2.5x10-20), and we observed novel correlations with neuropsychiatric conditions (p-values<7.9x10-4). Notably, neither resilience metric was genetically correlated with clinical AD (p-values>0.42) nor associated with APOE (p-values>0.13). In single variant analyses, we observed a genome-wide significant locus among participants with normal cognition on chromosome 18 upstream of ATP8B1 (index SNP rs2571244, MAF=0.08, p=2.3x10-8). The top variant at this locus (rs2571244) was significantly associated with methylation in prefrontal cortex tissue at multiple CpG sites, including one just upstream of ATPB81 (cg19596477; p=2x10-13). Overall, this comprehensive genetic analysis of resilience implicates a putative role of vascular risk, metabolism, and mental health in protection from the cognitive consequences of neuropathology, while also providing evidence for a novel resilience gene along the bile acid metabolism pathway. Furthermore, the genetic architecture of resilience appears to be distinct from that of clinical AD, suggesting that a shift in focus to molecular contributors to resilience may identify novel pathways for therapeutic targets.

genetics↗

bioRxiv2019

A/T/N polygenic risk score for cognitive decline in old age

INTRODUCTIONWe developed a novel polygenic risk score (PRS) based on the A/T/N (amyloid plaques (A), phosphorylated tau tangles (T), and neurodegeneration (N)) framework and compared a PRS based on clinical AD diagnosis to assess which was a better predictor of cognitive decline. METHODSWe used summary statistics from genome wide association studies of cerebrospinal fluid amyloid-{beta} (A{beta}42) and phosphorylated-tau (ptau181), left hippocampal volume (LHIPV), and late-onset AD dementia to calculate PRS for 1181 participants in the Alzheimers Disease Neuroimaging Initiative (ADNI). Individual PRS were averaged to generate a composite A/T/N PRS. We assessed the association of PRS with baseline and longitudinal cognitive composites of executive function and memory. RESULTSThe A/T/N PRS showed superior predictive performance on AD biomarkers and executive function decline compared to the clinical AD PRS. DISCUSSIONResults suggest that integration of genetic risk across AD biomarkers may improve prediction of disease progression. Research in ContextO_ST_ABSSystematic ReviewC_ST_ABSAuthors reviewed relevant literature using PubMed and Google Scholar. Key studies that generated and validated polygenic risk scores (PRS) for clinical and pathologic AD were cited. PRS scores have been increasingly used in the literature but clinical utility continues to be questioned. InterpretationIn the current research landscape concerning PRS clinical utility in the AD space, there is room for model improvement and our hypothesis was that a PRS with integrated risk for AD biomarkers could yield a better model for cognitive decline. Future DirectionsThis study serves as proof-of-concept that encourages future study of integrated PRS across disease markers and utility in taking an A/T/N (amyloidosis, tauopathy and neurodegeneration) focused approach to genetic risk for cognitive decline and AD.

genomics↗