Biology subjects

Emery, T.

Publications and source records attributed to Emery, T..

5 recordsLinked to original sources

bioRxiv2026

Leukocyte Immunoglobulin-Like Receptor B1 and its Interactions with Human Leukocyte Antigens

Interactions between Human Leukocyte Antigen (HLA) molecules and their cognate immunoreceptors are essential for regulating innate and adaptive immune cell functions. Leukocyte Immunoglobulin-like Receptors (LILRs) are key regulators of HLA-mediated immune responses, owing to their broad expression across immune cell populations and their ability to modulate both immune activation and tolerance. Among these, LILRB1-HLA interactions are increasingly recognised as important in transplantation, chronic infection and cancer therapies. Unlike other HLA-binding receptors, which recognise epitopes specific to HLA subsets, LILRB1 primarily engages the relatively conserved 3 and {beta}2-microglobulin components of HLA molecules, supporting its role as a broad regulator of pan-HLA class I-mediated functions. Nonetheless, there have been conflicting findings regarding the breadth of LILRB1-HLA-I interactions. While direct affinity studies on a limited subset of HLA-I molecules have revealed no significant differences in LILRB1 binding, broader analyses using single-antigen bead arrays suggest underlying variability. Here, we show through a broad binding assay that, while LILRB1 is a broad HLA-I-binding receptor, it exhibits differential preferences across HLA-I allotypes. Molecular dynamics analyses of the HLA-I-LILRB1 interface suggest that HLA-3 domain dynamism underlies these binding differences. We further determined the crystal structure of LILRB1 and used it to highlight intrinsic structural flexibility within its domains. Finally, these structural insights were leveraged to refine our understanding of the binding modalities of therapeutic monoclonal antibodies currently described. Together, our findings establish structural and mechanistic bases for differential HLA-I recognition by LILRB1 and provide insights into immunotherapeutic targeting of LILRB1.

immunology↗

bioRxiv2026

Longitudinal versus Cross-sectional effects of Age on MEG Power Spectra Parameters: Implications for Normative Models and Brain Ageing

Ageing produces changes in brain function. To map this process, researchers increasingly utilise Magnetoencephalography (MEG) to identify spectral shifts across large, age-diverse cohorts. However most such research has used cross-sectional designs, which may be confounded by generational differences and high inter-individual variability. To address these limitations, we analysed longitudinal resting-state MEG data from the Cam-CAN cohort, an adult lifespan cohort with a repeat MEG recording after approximately a decade. This design allowed us to contrast cross-sectional age differences between people (at baseline) with longitudinal age changes within people. Our analyses revealed four key findings. First, we observed consistency between baseline and longitudinal effects of increasing age on the slowing of the Alpha peak frequency. Second, we identified non-linear changes in Beta power, whereby power increased from youth to mid-life, but decreased from mid-life to late-life. These findings validate the use of normative charts for mapping these spectral components. Third, we detected some longitudinal effects, such as power reductions in Alpha and slowing of Beta peak frequency, that were not apparent cross-sectionally, underscoring the importance of intra-individual designs. Fourth, we did not find the commonly reported age-related flattening of the aperiodic exponent of the power spectrum, except in direct measures of cardiac activity. Together, these results demonstrate that while cross-sectional data capture major trends, longitudinal data are essential for isolating the true neurophysiological signatures of the ageing process.

neuroscience↗

bioRxiv2026

Dissociable contributions of cortical thickness and surface area to cognitive ageing: evidence from multiple longitudinal cohorts.

Cortical volume, a widely-used marker of brain ageing, is the product of two genetically and developmentally dissociable morphometric features: thickness and area. However, it remains unclear whether these two features have dissociable consequences for cognitive ageing. To address this, we analyse cross-sectional and longitudinal neuroimaging and cognitive data from one discovery cohort (Cam-CAN) and two independent, pre-registered replication cohorts (OASIS-3 and HABS-HD), leveraging wide age ranges across adulthood, different follow-up intervals and diverse population backgrounds. We show that thickness declines more steeply with age than does area, and shows stronger associations with longitudinal change in fluid cognitive abilities, fairly uniformly across the cortex. Cognitive change is also dependent on baseline thickness, independent of thickness change and independent of baseline cognitive ability. In contrast, area is comparatively stable across adulthood, at least until old age, and shows weaker and more heterogeneous associations with cognitive change. Together, these findings help to reconcile inconsistencies in the literature, and indicate that thickness provides a more sensitive marker of dynamic neurobiological processes underlying cognitive ageing, whereas area seems to reflect primarily stable, trait-like variation in cognitive ability.

neuroscience↗

bioRxiv2020

Safe linkage of cohort and population-based register data in a genome-wide association study on health care expenditure

BackgroundThere are research questions whose answers require record linkage of multiple databases which may be characterized by limited options for full data sharing. For this purpose, the Open Data Infrastructure for Social Science and Economic Innovations (ODISSEI) consortium has supported the development of the ODISSEI Secure Supercomputer (OSSC) platform that allows researchers to link cohort data to data from Statistics Netherlands and run analyses in a high performance computing (HPC) environment. MethodsAfter successful record linkage genome-wide association (GWA) analyses were carried out on expenditure for total health, mental health, primary and hospital care and medication. Record linkage for genotype data from 16,726 participants from the Netherlands Twin Register (NTR) with data from Statistics Netherlands was accomplished in the secure OSSC platform, followed by gene-based tests and estimation of total and SNP-based heritability. ResultsThe total heritability of expenditure ranged between 29.4 (SE 0.8) and 37.5 (SE 0.8) per cent, but GWA analyses did not identify single SNPs or genes that were genome-wide significantly associated with health care expenditure. SNP-based heritability was between 0.0 (SE 3.5) and 5.4 (SE 4.0) per cent and was different from zero for mental health care and primary care expenditure. ConclusionsWe successfully linked genotype data to administrative health care expenditure data from Statistics Netherlands and performed a series of analyses on health care expenditure. The OSSC platform offers secure possibilities for analysing linked data in large-scale and realizing sample sizes required for GWA studies, providing invaluable opportunities to answer many new research questions. Key messagesO_LICohort data of the Netherlands Twin Register were safely linked to population-based register data of Statistics Netherlands C_LIO_LIOn the ODISSEI Secure Supercomputer (OSSC) platform genome-wide association analyses were carried out on linked genotype and health care expenditure data C_LIO_LIVariation in health care expenditure was for approximately one third explained by family-based heritability, but SNP-heritability based on genetic similarity across unrelated individuals explained only a very small proportion of variance C_LIO_LIThe newly developed platform can serve as a prototype for realizing genome-wide association studies with sensitive data C_LI

genetics↗

bioRxiv2017

Symptoms of Depression in a Large Healthy Population Cohort are related to Subjective Memory Complaints and Memory Performance in Negative Contexts

Decades of research have investigated the impact of clinical depression on memory, which has revealed biases and in some cases impairments. However, little is understood about the effects of sub-clinical symptoms of depression on memory performance in the general population. Here we report the effects of symptoms of depression on memory problems in a large population-derived cohort (N = 2544), 87% of whom reported at least one symptom of depression. Specifically, we investigate the impact of depressive symptoms on subjective memory complaints, objective memory performance on a standard neuropsychological task and, in a subsample (n = 288), objective memory in affective contexts. There was a dissociation between subjective and objective memory performance, with depressive symptoms showing a robust relationship with self-reports of memory complaints, even after adjusting for age, gender, general cognitive ability and symptoms of anxiety, but not with performance on the standardised measure of verbal memory. Contrary to our expectations, hippocampal volume (assessed in a subsample, n = 592) did not account for significant variance in subjective memory, objective memory or depressive symptoms. Nonetheless, depressive symptoms were related to poorer memory for pictures presented in negative contexts, even after adjusting for memory for pictures in neutral contexts. Thus the symptoms of depression, associated with subjective memory complaints, appear better assessed by memory performance in affective contexts, rather than standardised memory measures. We discuss the implications of these findings for understanding the impact of depressive symptoms on memory functioning in the general population.

neuroscience↗