Biology subjects

Steele, J. D.

Publications and source records attributed to Steele, J. D..

3 recordsLinked to original sources

bioRxiv2021

Local CpG density affects the trajectory of age-associated epigenetic changes

DNA methylation is an epigenetic mark associated with gene repression and genome stability. Its pattern in the genome is disrupted with age and these changes can be used to statistically predict age with epigenetic clocks. Rates of aging inferred from these clocks correlate with human health. However, the molecular mechanisms underpinning age-associated DNA methylation changes are unknown. Local DNA sequence plays a strong role in programming DNA methylation levels at individual loci independently of age, but its influence on age-associated DNA methylation changes is unknown. We analysed longitudinal human DNA methylation trajectories at 345,895 CpGs from 600 individuals aged between 67 and 80 to understand the factors responsible for age-associated epigenetic changes at individual CpGs in the genome. We show that changes in methylation with age are especially apparent at 8,322 low CpG density loci. Using SNP data from the same individuals we demonstrate that DNA methylation trajectories are affected by local sequence polymorphisms at 1,487 loci with low CpG density. More generally, we find that local CpG density is a strong determinant of a CpGs methylation trajectory and that CpGs located in low CpG density regions are particularly prone to change. Overall, our results demonstrate that local DNA sequence influences age-associated DNA methylation changes in humans in vivo. We suggest that this occurs because interactions between CpGs reinforce maintenance of methylation patterns in CpG dense regions.

genetics↗

bioRxiv2019

Maladaptive striatal plasticity and abnormal reward-learning in cervical dystonia

In monogenetic generalized forms of dystonia, in vitro neurophysiological recordings have demonstrated direct evidence for abnormal plasticity at the level of the cortico-striatal synapse. It is unclear whether similar abnormalities contribute to the pathophysiology of cervical dystonia, the most common type of focal dystonia. We investigated whether abnormal cortico-striatal synaptic plasticity contributes to abnormal reward-learning behavior in patients with focal dystonia. Forty patients and forty controls performed a reward-gain and loss-avoidance reversal learning task. Participants behavior was fitted to a computational model of the basal ganglia incorporating detailed cortico-striatal synaptic learning rules. Model comparisons were performed to assess the ability of four hypothesised receptor specific abnormalities of cortico-striatal long term potentiation (LTP) and Long Term Depression (LTD): increased or decreased D1:LTP/LTD and increased or decreased D2: LTP/LTD to explain abnormal behavior in patients. Patients were selectively impaired in the post-reversal phase of the reward task. Individual learning rates in the reward reversal task correlated with the severity of the patients motor symptoms. A model of the striatum with decreased D2:LTP/ LTD best explained the patients behavior, suggesting excessive D2 cortico-striatal synaptic depotentiation could underpin biased reward learning in patients with cervical dystonia. Reversal learning impairment in cervical dystonia may be a behavioural correlate of D2 specific abnormalities in cortico-striatal synaptic plasticity. Reinforcement learning tasks with computational modeling could allow the identification of molecular targets for novel treatments based on their ability to restore normal reward-learning behavior in these patients.

neuroscience↗

bioRxiv2017

Dorsomedial prefrontal cortex activity during reinforcement learning discriminates response to Cognitive Behavioural Therapy in depression.

BACKGROUNDCognitive behavioural therapy (CBT) is an effective evidence based treatment for depression. At present there is no reliable predictor of CBT in depression. Although the key to successful CBT in depression lies in altering maladaptive information processing, no previous imaging study has probed predictors of CBT response using pre-treatment neural encoding of information processing. METHODS: Using functional magnetic resonance imaging we scanned 37 unmedicated depressed subjects before and after completing computerised CBT (cCBT). We model the trial-by-trial appraisal of feedback information during a probabilistic learning task by means of a dynamic learning rate. To discriminate response to cCBT we capitalise on the pre-treatment blood oxygen level dependent (BOLD) activity encoding the dynamic learning rate as a function of feedback congruence and valence. Additionally, we probe between-group differences in the learning style encoded in the models parameters.\n\nRESULTSWe show BOLD activity in the dorsomedial prefrontal cortex (dmPFC) to be encoding the dynamic learning rate. Crucially, responders exhibit greater BOLD activity in the dmPFC during incongruent negative trials but lower BOLD activity during congruent negative trials than non-responders. Additionally, on between-group comparisons of models parameter estimates we show responders take relatively greater account of previous feedback history and make comparatively smaller adjustments to the learning rate as a result of outcome surprisingness.\n\nCONCLUSIONSOur findings provide novel and important insights into the cognitive mechanisms underpinning response to cCBT and lend support to the feasibility and validity of neurocomputational approaches to treatment prediction research in psychiatry.

neuroscience↗