Biology subjects

Grieve, S. M.

Publications and source records attributed to Grieve, S. M..

3 recordsLinked to original sources

bioRxiv2024

Exploring Differences in Functional Connectivity in Australian Rules Football Players : A Resting-State fMRI Study on the Default Mode Network

The effects of non-concussive impacts in contact-sports such as in Australian rules football (ARF) are still largely unexplored. These impacts are often but not always lower in intensity, but occur more frequently than actual concussions. Since non-concussive impacts are often asymptomatic, their significance may be underestimated. Acute or subacute measurement of non-concussive injury is challenging as the pathological response and injury is poorly described. There is therefore a need for a greater understanding of the pathological consequences of exposure. Growing evidence indicates that resting-state functional connectivity (rs-fMRI) changes in the Default Mode Network (DMN) may be an important biomarker that is sensitive to characterize these impacts. In this work, we examined functional connectivity changes within the DMN of ARF players to evaluate its potential as an early biomarker for non-concussive impacts. Based on rs-fMRI, we compare the DMN of 47 sub-elite ARF players (mean age 21.5{+/-}2.7 years [SD], males 57%) and 42 age-matched healthy controls (mean age 23.2{+/-}2.3 years [SD], males 48%) using Independent Component Analysis (ICA) and Dual Regression. This approach permits an unbiased decomposition of brain activity into networks with principled handling of statistical error. An 83% increase in DMN connectivity (as measured by the Strictly Standardized Mean Difference on values derived from Dual Regression) was observed in ARF players in the left retrosplenial cingulate cortex compared to healthy controls (FDR-corrected p-value from dual regression = 0.03, 95% CI computed via bootstrapping was 58% to 116%). The AUC for distinguishing ARF players from controls was 0.80 (95% CI; [0.71, 0.89]), equating to a PPV of 78% and a NPV of 74%. These results are preliminary; future work could investigate robustness to different random initializations of ICA and validate the findings on an independent testing set, as well as investigate longitudinal changes in ARF players over the course of a playing season.

neuroscience↗

bioRxiv2024

Towards Principled Modeling Of Coronary Artery Calcium Scores With Zero-Inflated Regression

AO_SCPLOWBSTRACTC_SCPLOWThe Coronary Artery Calcium Score (CACS) is a widely-used measure of Coronary Artery Disease (CAD). The primary use of CACS is to identify subclinical CAD and estimate risk of future cardiovascular events such as acute myocardial infarction. The development of coronary atherosclerosis is well known to be accelerated in response to risk factors such as age, hypertension, hypercholeterolaemia and smoking. However, there is substantial variability in an individuals susceptibility or resistance to CAD against these risk factors. Quantifiying the deviation from "expected" CACS provides an novel opportunity to inform multi-omic and similar unbiased discovery of new markers and mechanisms of CAD trained against CT imaging. Standard linear regression struggles to model CACS due to the high prevalence of zeros (which reflect the absence of measurable coronary plaque). Prior works have variously handled this by discarding measurements with CACS of zero or by binning the CACS into broad categorical groups. Such approaches discard meaningful data, motivating the need for a more principled approach to handling the data distribution. In this work, we explored zero-inflated regression as a possible approach to modeling CACS using a cohort of patients from the BioHEART-CT study, and devised metrics to validate performance. We identified zero-inflated negative binomial regression, zero-inflated gamma regression and zero-inflated lognormal regression as promising approaches for handling the distributional properties of CACS, where the best method to use can vary depending on the dataset considered. A key contribution of our work is to demonstrate how these models can also estimate the percentile of the observed CACS relative to the distribution that would be expected after controlling for the inputs, thereby avoiding the need for data-hungry binning-based approaches.

bioinformatics↗

bioRxiv2022

Cellular Heterogeneity of Pluripotent Stem Cell Derived Cardiomyocyte Grafts is Mechanistically Linked to Treatable Arrhythmias

BackgroundExciting pre-clinical data have confirmed that human pluripotent stem cell derived cardiomyocytes (PSC-CMs) can remuscularise the injured or diseased heart, with several clinical trials now in planning or recruitment stages worldwide. However, ventricular arrhythmias are a predictable complication following engraftment of intramyocardially injected PSC-CMs. Therefore, there is an urgent unmet need to gain mechanistic insights and treatment strategies to control or prevent these engraftment arrhythmias (EAs). MethodsWe used a porcine model of myocardial infarction and PSC-CM transplantation to investigate efficacy of pharmacologic and catheter based anti-arrhythmic strategies in mitigating EAs. Furthermore, cell doses were robustly phenotyped using single cell ribonucleic acid sequencing and high parameter flow cytometry to identify cellular characteristics predictive of arrhythmogenesis. ResultsCombination therapy with amiodarone and ivabradine significantly reduced EA rate and burden following PSC-CM transplantation. Catheter ablation was also a feasible and effective treatment strategy which could be considered in the case of pharmacologically refractory arrhythmias. In addition, we show that EAs are mechanistically linked to cellular heterogeneity in the input PSC-CM and resultant graft. Specifically, we identify atrial and pacemaker-like cardiomyocytes as culprit arrhythmogenic subpopulations. We further describe two unique surface marker signatures, SIRPA+/CD90-/CD200+ and SIRPA+/CD90-/CD200-, which identify arrhythmogenic and non-arrhythmogenic cardiomyocytes respectively. ConclusionOur data deepens mechanistic understanding of EAs and suggests that modifications to current PSC-CM production and/or selection protocols could ameliorate this problem. We further show that current clinical pharmacologic and interventional anti-arrhythmic strategies can control and potentially abolish these arrhythmias, an important safety consideration given several impending clinical trials.

cell biology↗