Biology subjects

Kenna, K.

Publications and source records attributed to Kenna, K..

4 recordsLinked to original sources

bioRxiv2024

Sex-specific DNA methylation differences in Amyotrophic lateral sclerosis

Sex is an important covariate in all genetic and epigenetic research due to its role in the incidence, progression and outcome of many phenotypic characteristics and human diseases. Amyotrophic lateral sclerosis (ALS) is a motor neuron disease with a sex bias towards higher incidence in males. Here, we report for the first time a blood-based epigenome-wide association study meta-analysis in 9274 individuals after stringent quality control (5529 males and 3975 females). We identified a total of 226 ALS saDMPs (sex-associated DMPs) annotated to a total of 159 unique genes. These ALS saDMPs were depleted at transposable elements yet significantly enriched at enhancers and slightly enriched at 3UTRs. These ALS saDMPs were enriched for transcription factor motifs such as ESR1 and REST. Moreover, we identified an additional 10 genes associated with ALS saDMPs through chromatin loop interactions, suggesting a potential regulatory role for these saDMPs on distant genes. Furthermore, we investigated the relationship between DNA methylation at specific CpG sites and overall survival in ALS using Cox proportional hazards models. We identified two ALS saDMPs, cg14380013 and cg06729676, that showed significant associations with survival. Overall, our study reports a reliable catalogue of sex-associated ALS saDMPs in ALS and elucidates several characteristics of these sites using a large-scale dataset. This resource will benefit future studies aiming to investigate the role of sex in the incidence, progression and risk for ALS.

genomics↗

bioRxiv2024

predicTTE: An accessible and optimal tool for time-to-event prediction in neurological diseases

Time-to-event prediction is a key task for biological discovery, experimental medicine, and clinical care. This is particularly true for neurological diseases where development of reliable biomarkers is often limited by difficulty visualising and sampling relevant cell and molecular pathobiology. To date, much work has relied on Cox regression because of ease-of-use, despite evidence that this model includes incorrect assumptions. We have implemented a set of deep learning and spline models for time-to-event modelling within a fully customizable app and accompanying online portal, both of which can be used for any time-to-event analysis in any disease by a non-expert user. Our online portal includes capacity for end-users including patients, Neurology clinicians, and researchers, to access and perform predictions using a trained model, and to contribute new data for model improvement, all within a data-secure environment. We demonstrate a pipeline for use of our app with three use-cases including imputation of missing data, hyperparameter tuning, model training and independent validation. We show that predictions are optimal for use in downstream applications such as genetic discovery, biomarker interpretation, and personalised choice of medication. We demonstrate the efficiency of an ensemble configuration, including focused training of a deep learning model. We have optimised a pipeline for imputation of missing data in combination with time-to-event prediction models. Overall, we provide a powerful and accessible tool to develop, access and share time-to-event prediction models; all software and tutorials are available at www.predictte.org.

neuroscience↗

bioRxiv2023

Genomewide paired DNA-RNAseq analyses to discover intronic splice mutation hotspots in neurological disorders

Explaining missing heritability in rare disorders requires effective methods to interpret genetic variants. Sequence-to-function models such as SpliceAI support discovery of splice altering variants but filtering their output to identify pathogenic mutations remains challenging. We developed SpliPath to address 2 unmet needs in this process. First, SpliPath links the output of SpliceAI with reference transcriptomics data. This allows users to identify genetic variants that induce unannotated splice isoforms selectively expressed in disease models or patient tissue. Second, SpliPath aggregates variants with similar functional consequences into collapsed splicing quantitative trait loci (csQTLs) for more powerful genetic association analyses. We first used SpliPath to annotate whole genome sequencing (WGS) of 9,467 ALS patients and controls using RNAseq data from an iPSC model of TDP-43 dysfunction. Through this, SpliPath identified 53 variants predicted to enhance cryptic exon (CE) retention events associated with a core ALS pathomechanism. We then applied SpliPath to 294 ALS patients where both WGS and RNAseq were available and discovered missing genetic risk in the known ALS gene KIF5A. This revealed a first of kind intronic mutation hotspot that was validated using minigene reporter assays. Finally, using the same RNAseq data we then predicted 754 candidate csQTL for an independent WGS cohort of 6,625 ALS patients and 2,472 controls. Unbiased genomewide csQTL association testing successfully recovered KIF5A and nominated EPG5 as a potential pathogenic gene. These effects were undetectable using simplistic SpliceAI gene burden tests. Collectively, our study demonstrates the utility of SpliPath for uncovering missing heritability in rare disorders.

bioinformatics↗

bioRxiv2022

Aeration Strategy at Birth Does Not Impact Carotid Blood Flow and Oxygen Delivery in Preterm Lambs

BackgroundThe impact of different respiratory strategies at birth on the preterm lung is well understood, however, concerns have been raised that lung recruitment may impede cerebral haemodynamics. This study aims to examine the effect of three different ventilation strategies on cerebral haemodynamics and oxygenation. Methods124-127 day gestation apnoeic intubated preterm lambs (n=68) being studied as part of a larger program primarily assessing lung injury were randomised to positive pressure ventilation with positive end-expiratory pressure (PEEP) 8 cmH2O (No-RM; n=12), sustained inflation (SI; n=15) or dynamic PEEP strategy (DynPEEP; maximum PEEP 14 or 20 cmH2O, n=41) at birth, followed by 90 minutes of standardised ventilation. Haemodynamic data was continuously recorded, with intermittent arterial blood gas analysis. Main outcome measures for this study included carotid blood flow, carotid artery oxygen content and carotid oxygen delivery. ResultsOverall carotid blood flow measures were comparable between strategies, with the exception of mean carotid blood flow which was significantly lower for the SI group compared to the No-RM and DynPEEP groups respectively over the first 3 minutes (p<0.0001, mixed-effects model). Carotid oxygen content and oxygen delivery were similar between strategies. Maximum PEEP did not alter cerebral haemodynamic measures. ConclusionAlthough there were some short-term variations in cerebral haemodynamics between different PEEP strategies and SI, these were not sustained. ImpactO_LIDifferent pressure strategies to facilitate lung aeration at birth in preterm infants have been proposed. There is minimal information on the effect of lung recruitment on cerebral haemodynamics. C_LIO_LIThis is the first study that compares the effect of sustained lung inflation, and dynamic and static positive end-expiratory pressure on cerebral haemodynamics. C_LIO_LIWe found that the different ventilation strategies did not alter carotid blood flow, carotid oxygen content or carotid oxygen delivery. C_LIO_LIThis preclinical study provides some reassurance that respiratory strategies designed to focus on lung aeration at birth may not impact cerebral haemodynamics in preterm neonates. C_LI

physiology↗