Search results
Found 62025 matches for
Prof Alan Stein and colleagues examined the impact of PTSD on children whose fathers had been in the armed forces.
Individual Mechanical Energy Expenditure Regimens Vary Seasonally with Weather, Sex, Age and Body Condition in a Generalist Carnivore Population: Support for Inter-Individual Tactical Diversity.
Diverse individual energy-budgeting tactics within wild populations provide resilience to natural fluctuations in food availability and expenditure costs. Although substantial heterogeneity in activity-related energy expenditure has been documented, few studies differentiate between responses to the environment and inter-individual differences stemming from life history, allometry, or somatic stores. Using tri-axial accelerometry, complemented by diet analysis, we investigated inter-individual within-season variation in overall dynamic body acceleration (ODBA; activity intensity measure) and "Activity" (above an ODBA threshold) in a high-density population of European badgers (Meles meles). Weather (including wind speed) affected ODBA and activity according to predictors of earthworm (food) availability and cooling potential. In spring, maximal ODBA expenditure at intermediate rainfall and temperature values suggested that badgers traded foraging success against thermoregulatory losses, where lower-condition badgers maintained higher spring ODBA irrespective of temperature while badgers in better body condition reduced ODBA at colder temperatures. Conversely, in summer, lower-condition badgers modulated ODBA according to temperature, likely in response to super-abundant food supply. Between 35% (spring, summer) and 57% (autumn) of residual total daily ODBA variance related to inter-individual differences unexplained by seasonal predictors, suggesting within-season tactical activity typologies. We propose that this heterogeneity among individual energy-expenditure profiles may contribute to population resilience under rapid environmental change.
Diagnostic and prognostic value of α-synuclein seed amplification assay kinetic measures in Parkinson's disease: a longitudinal cohort study
Background: α-synuclein seed amplification assay (SAA) positivity has been proposed as a diagnostic biomarker for Parkinson's disease. However, studies of the prognostic value of this biomarker have been limited to small, single-centre studies over short follow-up periods. We aimed to assess the diagnostic and prognostic value of quantitative CSF α-synuclein SAA kinetic measures in Parkinson's disease. Methods: In this longitudinal cohort study, we collected and analysed data from participants with Parkinson's disease, progressive supranuclear palsy, and healthy controls enrolled in three cohorts: the UK parkinsonism cohort, the Parkinson's Progression Markers Initiative (PPMI) international observational study, and the Tübingen Parkinson's disease cohort. Baseline CSF α-synuclein SAA data and longitudinal clinical data were collected between Jan 1, 2005, and Nov 1, 2023. The following seeding kinetic measures were calculated from the α-synuclein SAA curve for each SAA-positive sample: time to threshold (TTT) for a positive SAA result; maximum Thioflavin T fluorescence during the reaction time (MaxThT); and area under the fluorescence curve during the reaction time (AUC). We compared seeding kinetic measures between sporadic Parkinson's disease and progressive supranuclear palsy, and between sporadic Parkinson's disease and monogenic Parkinson's disease. We used time-to-event analyses to assess the ability of α-synuclein SAA kinetic measures to predict an unfavourable outcome in Parkinson's disease, adjusting for sex, age, and disease duration at SAA testing. Findings: We analysed data from 1631 participants: newly generated data from the UK parkinsonism cohort (Parkinson's disease, n=66; progressive supranuclear palsy, n=52; controls, n=9) and previously generated data from the PPMI (Parkinson's disease, n=1036; controls, n=239) and Tübingen (Parkinson's disease, n=229) cohorts. In the UK parkinsonism cohort, α-synuclein SAA was positive in 63 (96%) of 66 Parkinson's disease samples and eight (15%) of 52 progressive supranuclear palsy samples, with six (75%) of eight positive progressive supranuclear palsy samples having distinct low and slow seeding kinetics (low MaxThT and high TTT) as a marker of Lewy body co-pathology. TTT was faster in GBA1-associated Parkinson's disease compared with sporadic Parkinson's disease in both the PPMI (p=0·04) and Tübingen (p=0·01) cohorts. In the PPMI cohort, after excluding individuals who had an unfavourable outcome at the time of baseline SAA testing, an unfavourable outcome was observed in 593 (73%) of 810 participants with α-synuclein SAA-positive Parkinson's disease during a median follow-up period of 4·5 years (IQR 2–9). TTT at baseline predicted only cognitive decline (Montreal Cognitive Assessment score ≤21) as a component of an unfavourable outcome in Parkinson's disease in both the PPMI (n=824, hazard ratio [HR] 2·36 [95% CI 1·60–3·46], p=0·001) and Tübingen (n=135, 2·17 [1·07–4·41], p=0·03) cohorts. TTT also predicted cognitive decline in a subgroup of participants with Parkinson's disease in the PPMI cohort who were Alzheimer's disease biomarker negative (n=355, HR 1·80 [95% CI 1·03–3·18], p=0·04). Interpretation: Assessing α-synuclein SAA kinetic measures might aid in the diagnostic differentiation of Parkinson's disease from progressive supranuclear palsy with Lewy body co-pathology. Furthermore, faster seeding kinetics are found in GBA1-Parkinson's disease and predict cognitive decline in Parkinson's disease independently of Alzheimer's disease co-pathology. Funding: Medical Research Council, PSP Association. Copyright: © 2025 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.
Models of Cerebrovascular Reactivity in BOLD-fMRI and Transcranial Doppler Ultrasound.
The ability of cerebrovasculature to respond to meet tissue demands is vital for normal brain function and health. Cerebrovascular reactivity (CVR), a measure of the responsiveness of cerebrovasculature to vasoactive stimuli, is a valuable tool for evaluating cerebrovascular health. While CVR is commonly assessed using transcranial Doppler ultrasound (TCD), which measures blood velocity, or MRI-based techniques such as blood oxygenation level-dependent (BOLD) imaging, which reflect changes in blood oxygenation, direct comparisons between these modalities remain limited, particularly with stimuli that induce a large dynamic range. Because both methods capture hypercapnia-induced vascular changes, we hypothesised that their CVR metrics may be correlated. This study evaluates inter-modality correlations of CVR using TCD and BOLD-fMRI extracted from the MCA territory (parietal lobe) during a ramped hypercapnic protocol and different modelling strategies. Linear correlations across broad PETCO2 ranges validated the utility of linear CVR modelling in capturing repeatable metrics using TCD and MRI. A four-parameter sigmoid model revealed significant inter-modality variability in span and bound parameters, improved by fixing these parameters and focusing on slope and inflection point, which enhanced the correlations between modalities. These results support the reliability of linear CVR modelling within narrow vasoactive response ranges in healthy subjects and propose a simplified two-parameter sigmoid model as an effective framework for characterising non-linear CVR dynamics. This work adds to the sparse literature on inter-modality CVR comparisons and indicates which CVR metrics are comparable between TCD and BOLD-fMRI, emphasising CVR as a useful tool for assessing cerebrovascular health in research and clinical contexts.
Ultrahigh frequencies of peripherally matured LGI1- and CASPR2-reactive B cells characterize the cerebrospinal fluid in autoimmune encephalitis.
Intrathecal synthesis of central nervous system (CNS)-reactive autoantibodies is observed across patients with autoimmune encephalitis (AE), who show multiple residual neurobehavioral deficits and relapses despite immunotherapies. We leveraged two common forms of AE, mediated by leucine-rich glioma inactivated-1 (LGI1) and contactin-associated protein-like 2 (CASPR2) antibodies, as human models to comprehensively reconstruct and profile cerebrospinal fluid (CSF) B cell receptor (BCR) characteristics. We hypothesized that the resultant observations would both inform the observed therapeutic gap and determine the contribution of intrathecal maturation to pathogenic B cell lineages. From the CSF of three patients, 381 cognate-paired IgG BCRs were isolated by cell sorting and scRNA-seq, and 166 expressed as monoclonal antibodies (mAbs). Sixty-two percent of mAbs from singleton BCRs reacted with either LGI1 or CASPR2 and, strikingly, this rose to 100% of cells in clonal groups with ≥4 members. These autoantigen-reactivities were more concentrated within antibody-secreting cells (ASCs) versus B cells (P < 0.0001), and both these cell types were more differentiated than LGI1- and CASPR2-unreactive counterparts. Despite greater differentiation, autoantigen-reactive cells had acquired few mutations intrathecally and showed minimal variation in autoantigen affinities within clonal expansions. Also, limited CSF T cell receptor clonality was observed. In contrast, a comparison of germline-encoded BCRs versus the founder intrathecal clone revealed marked gains in both affinity and mutational distances (P = 0.004 and P < 0.0001, respectively). Taken together, in patients with LGI1 and CASPR2 antibody encephalitis, our results identify CSF as a compartment with a remarkably high frequency of clonally expanded autoantigen-reactive ASCs whose BCR maturity appears dominantly acquired outside the CNS.
Distress and neuroticism as mediators of the effect of childhood and adulthood adversity on cognitive performance in the UK Biobank study.
Childhood adversity and adulthood adversity affect cognition later in life. However, the mechanism through which adversity exerts these effects on cognition remains under-researched. We aimed to investigate if the effect of adversity on cognition was mediated by distress or neuroticism. The UK Biobank is a large, population-based, cohort study designed to investigate risk factors of cognitive health. Here, data were analysed using a cross-sectional design. Structural equation models were fitted to the data with childhood adversity or adulthood adversity as independent variables, distress and neuroticism as mediators and executive function and processing speed as latent dependent variables that were derived from the cognitive scores in the UK Biobank. Complete data were available for 64,051 participants in the childhood adversity model and 63,360 participants in the adulthood adversity model. Childhood adversity did not show a direct effect on processing speed. The effect of childhood adversity on executive function was partially mediated by distress and neuroticism. The effects of adulthood adversity on executive function and processing speed were both partially mediated by distress and neuroticism. In conclusion, distress and neuroticism mediated the deleterious effect of childhood and adulthood adversity on cognition and may provide a mechanism underlying the deleterious consequences of adversity.
Evaluating the harmonisation potential of diverse cohort datasets.
Data discovery, the ability to find datasets relevant to an analysis, increases scientific opportunity, improves rigour and accelerates activity. Rapid growth in the depth, breadth, quantity and availability of data provides unprecedented opportunities and challenges for data discovery. A potential tool for increasing the efficiency of data discovery, particularly across multiple datasets is data harmonisation.A set of 124 variables, identified as being of broad interest to neurodegeneration, were harmonised using the C-Surv data model. Harmonisation strategies used were simple calibration, algorithmic transformation and standardisation to the Z-distribution. Widely used data conventions, optimised for inclusiveness rather than aetiological precision, were used as harmonisation rules. The harmonisation scheme was applied to data from four diverse population cohorts.Of the 120 variables that were found in the datasets, correspondence between the harmonised data schema and cohort-specific data models was complete or close for 111 (93%). For the remainder, harmonisation was possible with a marginal a loss of granularity.Although harmonisation is not an exact science, sufficient comparability across datasets was achieved to enable data discovery with relatively little loss of informativeness. This provides a basis for further work extending harmonisation to a larger variable list, applying the harmonisation to further datasets, and incentivising the development of data discovery tools.
Neurodegenerative disease of the brain: a survey of interdisciplinary approaches.
Neurodegenerative diseases of the brain pose a major and increasing global health challenge, with only limited progress made in developing effective therapies over the last decade. Interdisciplinary research is improving understanding of these diseases and this article reviews such approaches, with particular emphasis on tools and techniques drawn from physics, chemistry, artificial intelligence and psychology.
Machine learning derived retinal pigment score from ophthalmic imaging shows ethnicity is not biology.
Few metrics exist to describe phenotypic diversity within ophthalmic imaging datasets, with researchers often using ethnicity as a surrogate marker for biological variability. We derived a continuous, measured metric, the retinal pigment score (RPS), that quantifies the degree of pigmentation from a colour fundus photograph of the eye. RPS was validated using two large epidemiological studies with demographic and genetic data (UK Biobank and EPIC-Norfolk Study) and reproduced in a Tanzanian, an Australian, and a Chinese dataset. A genome-wide association study (GWAS) of RPS from UK Biobank identified 20 loci with known associations with skin, iris and hair pigmentation, of which eight were replicated in the EPIC-Norfolk cohort. There was a strong association between RPS and ethnicity, however, there was substantial overlap between each ethnicity and the respective distributions of RPS scores. RPS decouples traditional demographic variables from clinical imaging characteristics. RPS may serve as a useful metric to quantify the diversity of the training, validation, and testing datasets used in the development of AI algorithms to ensure adequate inclusion and explainability of the model performance, critical in evaluating all currently deployed AI models. The code to derive RPS is publicly available at: https://github.com/uw-biomedical-ml/retinal-pigmentation-score .
Periodontitis and Outer Retinal Thickness: a Cross-Sectional Analysis of the United Kingdom Biobank Cohort.
PURPOSE: Periodontitis, a ubiquitous severe gum disease affecting the teeth and surrounding alveolar bone, can heighten systemic inflammation. We investigated the association between very severe periodontitis and early biomarkers of age-related macular degeneration (AMD), in individuals with no eye disease. DESIGN: Cross-sectional analysis of the prospective community-based cohort United Kingdom (UK) Biobank. PARTICIPANTS: Sixty-seven thousand three hundred eleven UK residents aged 40 to 70 years recruited between 2006 and 2010 underwent retinal imaging. METHODS: Macular-centered OCT images acquired at the baseline visit were segmented for retinal sublayer thicknesses. Very severe periodontitis was ascertained through a touchscreen questionnaire. Linear mixed effects regression modeled the association between very severe periodontitis and retinal sublayer thicknesses, adjusting for age, sex, ethnicity, socioeconomic status, alcohol consumption, smoking status, diabetes mellitus, hypertension, refractive error, and previous cataract surgery. MAIN OUTCOME MEASURES: Photoreceptor layer (PRL) and retinal pigment epithelium-Bruch's membrane (RPE-BM) thicknesses. RESULTS: Among 36 897 participants included in the analysis, 1571 (4.3%) reported very severe periodontitis. Affected individuals were older, lived in areas of greater socioeconomic deprivation, and were more likely to be hypertensive, diabetic, and current smokers (all P < 0.001). On average, those with very severe periodontitis were hyperopic (0.05 ± 2.27 diopters) while those unaffected were myopic (-0.29 ± 2.40 diopters, P < 0.001). Following adjusted analysis, very severe periodontitis was associated with thinner PRL (-0.55 μm, 95% confidence interval [CI], -0.97 to -0.12; P = 0.022) but there was no difference in RPE-BM thickness (0.00 μm, 95% CI, -0.12 to 0.13; P = 0.97). The association between PRL thickness and very severe periodontitis was modified by age (P < 0.001). Stratifying individuals by age, thinner PRL was seen among those aged 60 to 69 years with disease (-1.19 μm, 95% CI, -1.85 to -0.53; P < 0.001) but not among those aged < 60 years. CONCLUSIONS: Among those with no known eye disease, very severe periodontitis is statistically associated with a thinner PRL, consistent with incipient AMD. Optimizing oral hygiene may hold additional relevance for people at risk of degenerative retinal disease. FINANCIAL DISCLOSURES: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
Autoencoder-based phenotyping of ophthalmic images highlights genetic loci influencing retinal morphology and provides informative biomarkers.
MOTIVATION: Genome-wide association studies (GWAS) have been remarkably successful in identifying associations between genetic variants and imaging-derived phenotypes. To date, the main focus of these analyses has been on established, clinically-used imaging features. We sought to investigate if deep learning approaches can detect more nuanced patterns of image variability. RESULTS: We used an autoencoder to represent retinal optical coherence tomography (OCT) images from 31 135 UK Biobank participants. For each subject, we obtained a 64-dimensional vector representing features of retinal structure. GWAS of these autoencoder-derived imaging parameters identified 118 statistically significant loci; 41 of these associations were also significant in a replication study. These loci encompassed variants previously linked with retinal thickness measurements, ophthalmic disorders, and/or neurodegenerative conditions. Notably, the generated retinal phenotypes were found to contribute to predictive models for glaucoma and cardiovascular disorders. Overall, we demonstrate that self-supervised phenotyping of OCT images enhances the discoverability of genetic factors influencing retinal morphology and provides epidemiologically informative biomarkers. AVAILABILITY AND IMPLEMENTATION: Code and data links available at https://github.com/tf2/autoencoder-oct.