Biology subjects

Priest, J.

Publications and source records attributed to Priest, J..

9 recordsLinked to original sources

bioRxiv2025

Persistent Classical and Atypical Memory B Cells Underlie Heterogeneous Vaccine Responses in Ocrelizumab-Treated Multiple Sclerosis

Background and ObjectivesPatients with multiple sclerosis (pwMS) treated with ocrelizumab (OCR), a B-cell-depleting therapy, exhibit heterogeneous humoral responses to SARS-CoV-2 mRNA vaccination. The mechanisms underlying this variability remain incompletely understood. We performed a longitudinal analysis of B-cell subset dynamics and antigen-specific T cell responses in OCR-treated pwMS and healthy controls to determine how immune cell composition, timing of OCR infusion, and lymphocyte dynamics influence humoral response outcomes. MethodsBased on post-vaccination anti-Spike IgG titers measured by multiplex bead immunoassay, pwMS were categorized as super-responders (SR), responders (R), or non-responders (NR). A 35-marker spectral flow cytometry panel was used to characterize T- and B-cell subsets longitudinally, at baseline and following stimulation with a SARS-CoV-2 peptide pool. ResultsCD4+ and CD8+ T cell populations were preserved across OCR-treated pwMS, and SARS-CoV-2-specific T cells remained detectable for more than 6 months after vaccination. In contrast, residual B-cell subset composition distinguished responders from non-responders. DN2-like B cells (CD19+CD27-IgD-T-bet+CD11c+CXCR5-) persisted despite repeated OCR infusions and were enriched in SR compared with NR. Repletion of mature naive B cells in peripheral blood correlated with time since last OCR infusion and with stronger humoral immune responses. ConclusionsB-cell subsets that resist OCR-mediated depletion may contribute to vaccine responsiveness in OCR-treated pwMS. Altered repletion kinetics of naive B cell subsets in non-responders suggest that specific B-cell populations may serve as predictive biomarkers of vaccine-induced humoral immunity, despite preserved T-cell responses.

immunology↗

bioRxiv2025

Plakophilin-2 Coordinates Energy Metabolism and Contractility in Cardiomyocytes, Revealing Its Roles beyond Desmosomes

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a familial cardiac disease associated with ventricular arrhythmias and an increased risk of sudden cardiac death. Mutations in the desmosome gene Plakophilin-2, PKP2, lead to reduction in PKP2 protein and collapse of desmosomes that is known to compromise contractility and electrical stability of cardiomyocytes. Our previous studies demonstrated the efficacy of adeno-associated virus 9 (AAV9)-mediated restoration of PKP2 expression in a cardiac specific knock-out mouse model of Pkp2 and revealed profound changes in mRNA signatures of metabolic enzymes that were reversed by the gene replacement approach. In this study, we used PKP2-deficient mouse hearts and human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) to identify changes in steady-state metabolite levels associated with impaired lipid homeostasis, glycolysis, and glucose oxidation. These metabolic phenotypes align with human ARVC metabolic data and reflect an intrinsic impairment of cellular energy metabolism. Here we showed for the first time that these intracellular metabolic defects were associated specifically with poor contractility of cardiomyocytes. AAV9:PKP2 restored contractility, improved electrophysiological properties and Ca2+ transients. In contrast, we observed that treating PKP2-deficient cardiomyocytes pharmacologically with small molecule metabolic enhancers improved contractility but not electrophysiological properties and Ca2+ transients, suggesting differential sensitivity of structure-mediated functions in response to metabolic perturbance. Our study modeled and revealed a direct intracellular connection between compromised PKP2 function and metabolic impairment. We proposed that an increased risk of decoupling energy-responsive contractility from less energy-responsive electrical activities can be a new arrhythmogenic mechanism, potentially responsible for exercise-triggered cardiac adversity in ARVC disease development and progression.

cell biology↗

bioRxiv2020

Genome-wide association study in European patients with congenital heart disease identifies risk loci for transposition of the great arteries and anomalies of the thoracic arteries and veins and expression of discovered candidate genes in the developing heart

RationaleGenetic factors undoubtedly contribute to the development of congenital heart disease (CHD), but still remain mostly ill-defined. ObjectiveIdentification of genetic risk factors associated with CHD and functional analysis of SNP-carrying genes. Methods and ResultsGenetic association study of 1,440 Caucasian CHD patients from the German Heart Center Munich collected from March 2009 to June 2016, 2,594 patients of previous studies provided by the Newcastle University and 8,486 controls underwent meta-analysis to detect single nucleotide polymorphisms (SNPs) associated with CHD. Results4,034 Caucasian CHD patients strictly classified according to the Society of Thoracic Surgeons nomenclature and 8,486 controls were included. One SNP on chromosome 5 reached genome-wide significance across all CHD phenotypes (rs185531658,OR:2.16, p=5.28x10-9) and was also indicative for septal defects (OR:2.16, p=6.15x10-8). One region on chromosome 20 pointing to the MACROD2 locus, identified four SNPs (rs150246290,OR:3.78, p=1.27x10-10; rs149890280,OR:3.74, p=1.8x10-10; rs149467721,OR:3.53; p=1.39x10-9, rs77094733,OR:3.53, p=1.73x10-9) in patients with transposition of the great arteries (TGA). A second region was detected on chromosome 8 located at ZBTB10 (rs148563140,OR:3.42, p=3.28x10-8; rs143638934,OR:3.42, p=3.51x10-8) in the same subgroup. Three highly significant risk variants on chromosome 17 (rs76774446,OR:1.60, p=9.95x10-8; rs11874,OR:1.60, p=6.64x10-8; rs17677363,OR:1.60, p=9.81x10-8) within the GOSR2 locus were identified in patients with anomalies of thoracic arteries and veins (ATAV). Genetic variants associated with ATAV are suggested to influence expression of WNT3, and variant rs870142 related to septal defects is proposed to influence expression of MSX1. Cardiac differentiation of human and murine induced pluripotent stem cells and single cell RNAseq analyses of developing murine and human hearts show essential functional roles for MACROD2, GOSR2, WNT3 and MSX1 at all developmental stages. ConclusionsFor the first time genetic risk factors in CHD patients with TGA and ATAV were identified. Several candidate genes play an essential functional role in heart development at the embryonic, newborn and adult stage.

genomics↗

bioRxiv2019

Association between the 4p16 genomic locus and different types of congenital heart disease: results from adult survivors in the UK Biobank

Congenital heart disease is the most common birth defect in newborns and the leading cause of death in infancy, affecting nearly 1% of live births. A locus in chromosome 4p16, adjacent to MSX1 and STX18, has been associated with atrial septal defects (ASD) in multiple European and Chinese cohorts. Here, genotyping data from the UK Biobank was used to test for associations between this locus and congenital heart disease in adult survivors of left ventricular outflow tract obstruction (n=164) and ASD (n=223), with a control sample of 332,788 individuals, and a meta-analysis of the new and existing ASD data was performed.\n\nThe results show an association between the previously reported markers at 4p16 and risk for either ASD or left ventricular outflow tract obstruction, with effect sizes similar to the published data (OR between 1.27-1.45; all p<0.05). Differences in allele frequencies remained constant through the studied age range (40-70 years), indicating that the variants themselves do not drive lethal genetic defects. Meta-analysis shows an OR of 1.35 (95% CI: 1.25-1.46; p<10-4) for the association with ASD.\n\nThe findings show that the genetic associations with ASD can be generalized to adult survivors of both ASD and left ventricular lesions. Although the 4p16 associations are statistically compelling, the mentioned alleles confer only a small risk for disease and their frequencies in this adult sample are the same as in children, likely limiting their clinical significance. Further epidemiological and functional studies may elicit factors triggering disease in interaction with the risk alleles.

genetics↗

bioRxiv2019

Large-scale examination of neuropsychiatric, cognitive and cardiovascular phenotypic associations with 15q11.2 BP1-BP2 deletion in ~500,000 UK Biobank individuals

BackgroundDeletion of a non-imprinted 500Kb genomic region at chromosome 15q11.2, between breakpoints 1 and 2 of the Prader-Willi/Angelman locus (BP1-BP2 deletion) has been associated in previous studies with phenotypes including developmental delay, autism, schizophrenia and congenital cardiovascular malformations (CVM). The deletion has a low baseline population prevalence and large-scale data regarding the magnitude of these associations and any milder effects on cognition phenotypes, in populations not selected for disease, are limited.\n\nMethodsUsing the UK Biobank (UKB) cohort of [~]500,000 individuals, we identified individuals with neuropsychiatric and CVM diagnoses and investigated their association with deletions at the BP1-BP2 locus. In addition we assessed the association of BP1-BP2 deletions with cognitive function and academic achievement in individuals with no previous diagnosis.\n\nResultsCases of neurodevelopmental and CVM disease had an increased prevalence of the deletion compared to controls (0.68%; OR=1.84 [95% CI 1.23 - 2.75]; p=0.004 and 0.64%; OR=1.73 [95% CI 1.08 - 2.75]; p=0.03 respectively). Excluding participants diagnosed with neurodevelopmental or neuropsychiatric disease, deletion carriers had worse scores in four tests of cognitive function, and while 32.8% of UKB participants without BP1-BP2 deletion had a university or college degree as their highest educational qualification, only 22.8% of deletion carriers achieved this (OR 0.57 [95% CI 0.51-0.64]; p=5.60E-22).\n\nConclusionsWe conclude that BP1-BP2 deletion has an appreciable population prevalence with important life-course impacts on undiagnosed carriers. These data are of potential utility in deciding the circumstances under which clinical testing for BP1-BP2 deletion may be helpful.\n\nKey messagesO_LIDeletions at chromosome 15q11.2 between breakpoints 1 and 2 (BP1-BP2), which encompass four genes, have been associated with developmental delay, autism, schizophrenia and congenital cardiovascular malformations.\nC_LIO_LIHere, we use the largest cohort studied to date: the UK Biobank cohort of [~]500,000 individuals, to explore the association of this deletion with neuropsychiatric and cardiovascular phenotypes as well as its effects on cognitive function and academic achievement.\nC_LIO_LIWe find an appreciable population prevalence of the deletion with these phenotypes and demonstrate reduced cognitive function and lower academic achievements in those individuals with no prior diagnosis.\nC_LI

genetics↗

bioRxiv2019

A new method for inferring timetrees from temporally sampled molecular sequences

Pathogen timetrees are phylogenies scaled to time. They reveal the temporal history of a pathogen spread through the populations as captured in the evolutionary history of strains. These timetrees are inferred by using molecular sequences of pathogenic strains sampled at different times. That is, temporally sampled sequences enable the inference of sequence divergence times. Here, we present a new approach (RelTime with Dated Tips [RTDT]) to estimating pathogen timetrees based on the relative rate framework underlying the RelTime approach. RTDT does not require many of the priors demanded by Bayesian approaches, and it has light computing requirements. We found RTDT to be accurate on simulated datasets evolved under a variety of branch rates models. Interestingly, we found two non-Bayesian methods (RTDT and Least Squares Dating [LSD]) to perform similar to or better than the Bayesian approaches available in BEAST and MCMCTree programs. RTDT method was found to generally outperform all other methods for phylogenies in with autocorrelated evolutionary rates. In analyses of empirical datasets, RTDT produced dates that were similar to those from Bayesian analyses. Speed and accuracy of the new method, as compared to the alternatives, makes it appealing for analyzing growing datasets of pathogenic strains. Cross-platform MEGA X software, freely available from http://www.megasoftware.net, now contains the new method for use through a friendly graphical user interface and in high-throughput settings.\n\nAUTHOR SUMMARYPathogen timetrees trace the origins and evolutionary histories of strains in populations, hosts, and outbreaks. The tips of these molecular phylogenies often contain sampling time information because the sequences were generally obtained at different times during the disease outbreaks and propagation. We have developed a new method for inferring timetrees for phylogenies with tip dates, which improves on widely-used Bayesian methods (e.g., BEAST) in computational efficiency and does not require prior specification of population parameters, branch rate model, or clock model. We performed extensive computer simulation and found that RTDT performed better than the other methods for the estimation of divergence times at deep node in phylogenies where evolutionary rates were autocorrelated. The new method is available in the cross-platform MEGA software package that provides a graphical user interface, and allows use via a command line in scripting and high throughput analysis (www.megasoftware.net).

evolutionary biology↗

bioRxiv2019

Phenome-wide burden of copy number variation in UK Biobank

Copy number variations (CNV) represent a significant proportion of the genetic differences between individuals and many CNVs associate causally with syndromic disease and clinical outcomes. Here, we characterize the landscape of copy number variation and their phenome-wide effects in a sample of 472,228 array-genotyped individuals from the UK Biobank. In addition to population-level selection effects against genic loci conferring high-mortality, we describe genetic burden from syndromic and previously uncharacterized CNV loci across nearly 2,000 quantitative and dichotomous traits, with separate analyses for common and rare classes of variation. Specifically, we highlight the effects of CNVs at two well-known syndromic loci 16p11.2 and 22q11.2, as well as novel associations at 9p23, in the context of acute coronary artery disease and high body mass index. Our data constitute a deeply contextualized portrait of population-wide burden of copy number variation, as well as a series of known and novel dosage-mediated genic associations across the medical phenome.

genomics↗

bioRxiv2018

Weakly supervised classification of rare aortic valve malformations using unlabeled cardiac MRI sequences

Biomedical repositories such as the UK Biobank provide increasing access to prospectively collected cardiac imaging, however these data are unlabeled which creates barriers to their use in supervised machine learning. We develop a weakly supervised deep learning model for classification of aortic valve malformations using up to 4,000 unlabeled cardiac MRI sequences. Instead of requiring highly curated training data, weak supervision relies on noisy heuristics defined by domain experts to programmatically generate large-scale, imperfect training labels. For aortic valve classification, models trained with imperfect labels substantially outperform a supervised model trained on hand-labeled MRIs. In an orthogonal validation experiment using health outcomes data, our model identifies individuals with a 1.8-fold increase in risk of a major adverse cardiac event. This work formalizes a learning baseline for aortic valve classification and outlines a general strategy for using weak supervision to train machine learning models using unlabeled medical images at scale.

bioinformatics↗

bioRxiv2017

Does tobacco abstinence decrease reward sensitivity? A human laboratory test

IntroductionAnimal studies report abstinence from nicotine makes rewards less rewarding; however, the results of human tests of the effects of cessation on reward sensitivity are mixed. The current study tested reward sensitivity in abstinent smokers using more rigorous methods than most prior studies.\n\nMethodsA human laboratory study compared outcomes for 1 week prior to quitting to those during 4 weeks post-quit. The study used smokers trying to quit, objective and subjective measures, multiple measures during smoking and abstinence, and monetary rewards to increase the prevalence of abstinence. Current daily smokers (n = 211) who were trying to quit completed an operant measure of reward sensitivity and a survey of pleasure from various rewards as well as self-reports of anhedonia, delay discounting, positive affect and tobacco withdrawal twice each week. A comparison group of long-term former smokers (n = 67) also completed the tasks weekly for 4 weeks. Primary analyses were based on the 61 current smokers who abstained for all 4 weeks.\n\nResultsStopping smoking decreased self-reported pleasure from rewards but did not decrease reward sensitivity on the operant task. Abstinence also decreased self-reported reward frequency and increased the two anhedonia measures. However, the changes with abstinence were small for all outcomes (6-14%) and most lasted less than a week.\n\nConclusionAbstinence from tobacco decreased most self-report measures of reward sensitivity; however, it did not change the objective measure. The self-report effects were small.\n\nImplicationsO_LIAnimal research suggests that nicotine withdrawal decreases reward sensitivity. Replication tests of this in humans have produced inconsistent results.\nC_LIO_LIWe report what we believe is a more rigorous test\nC_LIO_LIWe found smoking abstinence slightly decreases self-reports of reward sensitivity but does not do so for behavioral measures of reward sensitivity\nC_LI

neuroscience↗