bioRxiv Science⌕ Search

Biology subjects

Heron, J.

Publications and source records attributed to Heron, J..

5 recordsLinked to original sources

Body-part specificity for learning of multiple prior distributions in human coincidence timing

During timing tasks, the brain learns the statistical distribution of target intervals and integrates this prior knowledge with sensory inputs to optimise task performance. Daily events can have different temporal statistics (e.g. fastball/slowball in baseball batting), making it important to learn and retain multiple priors. However, the rules governing this process are not yet understood. Here, we demonstrate that the learning of multiple prior distributions in a coincidence timing task is characterised by body-part specificity. In our experiments, two prior distributions (short and long intervals) were imposed on participants. When using only one body part for timing responses, regardless of the priors, participants learned a single prior by generalising over the two distributions. However, when the two priors were assigned to different body parts, participants concurrently learned the two independent priors. Moreover, body-part specific prior acquisition was faster when the priors were assigned to anatomically distant body parts (e.g. hand/foot) than when they were assigned to close body parts (e.g. index/middle fingers). This suggests that the body-part specific learning of priors is organised according to somatotopy.

neuroscience↗

Mendelian randomisation for mediation analysis: current methods and challenges for implementation

Mediation analysis seeks to explain the pathway(s) through which an exposure affects an outcome. Mediation analysis experiences a number of methodological difficulties, including bias due to confounding and measurement error. Mendelian randomisation (MR) can be used to improve causal inference for mediation analysis. We describe two approaches that can be used for estimating mediation analysis with MR: multivariable Mendelian randomisation (MVMR) and two-step Mendelian randomisation. We outline the approaches and provide code to demonstrate how they can be used in mediation analysis. We review issues that can affect analyses, including confounding, measurement error, weak instrument bias, and analysis of multiple mediators. Description of the methods is supplemented by simulated and real data examples. Although Mendelian randomisation relies on large sample sizes and strong assumptions, such as having strong instruments and no horizontally pleiotropic pathways, our examples demonstrate that it is unlikely to be affected by confounders of the exposure or mediator and the outcome, reverse causality and non-differential measurement error of the exposure or mediator. Both MVMR and two-step MR can be implemented in both individual-level MR and summary data MR, and can improve causal inference in mediation analysis.

genetics↗

Adverse childhood experiences: associations with educational attainment and adolescent health, and the role of family and socioeconomic factors. Analysis of a prospective cohort study.

BackgroundExperiencing multiple adverse childhood experiences (ACE) is a risk factor for many adverse outcomes. However, the role of family and socioeconomic factors in these associations is often overlooked.\n\nMethods and findingsUsing data from the Avon Longitudinal Study of Parents and Children, we assess associations of ACE between birth and 16 years (sexual, physical or emotional abuse, emotional neglect, parental substance abuse, parental mental illness or suicide attempt, violence between parents, parental separation, bullying, and parental criminal conviction) with educational attainment at 16 years (n=9,959) and health at age 17 years (depression, obesity, harmful alcohol use, smoking and illicit drug use, n=4,917). We explore the extent to which associations are robust to adjustment for family and socioeconomic factors, whether associations differ according to socioeconomic factors, and estimate the proportion of adverse educational and health outcomes attributable to ACE, family or socioeconomic measures.\n\nThere were strong associations of ACE with lower educational attainment and higher risk of depression, drug use and smoking. Associations with educational attainment attenuated after adjustment but remained strong. Associations with depression, drug use and smoking were not altered by adjustment. Associations of ACE with harmful alcohol use and obesity were weak. We found no evidence that associations differed by socioeconomic factors. Between 5-15% of the cases of adverse educational and health outcomes occur amongst people experiencing 4+ ACE, and between 1-19% occur in people whose mothers have a low level of education.\n\nConclusionsThis study demonstrates strong associations between ACE and lower educational attainment and worse health that are independent of family and socioeconomic factors. Our findings imply that interventions that focus solely on ACE or solely on socioeconomic deprivation, whilst beneficial, would miss most cases of adverse educational and health outcomes. Intervention strategies should therefore target a wide range of relevant factors, including ACE, socioeconomic deprivation, parental substance use and mental health.

epidemiology↗

Identifying Critical Points of Trajectories of Depressive Symptoms From Childhood to Young Adulthood: Evidence of Sex Differences from the Avon Longitudinal Study of Parents and Children (ALSPAC)

Depression is a common mental illness associated with increased substance misuse and risk of suicide. Potential risk factors for depression include sex and depressive symptoms in early life, however the mechanisms responsible are not yet understood. Research has focused on late childhood and adolescence as this developmental period may be a modifiable risk factor that prevents or reduces depression at a later stage. It is also important to establish at what ages the level of depression is changing as this will help identify critical points to intervene with treatment. We used multilevel growth-curve models to explore adolescent trajectories of depressive symptoms in the Avon Longitudinal Study of Parents and Children, a UK based pregnancy cohort. Using data from 9301 individuals, trajectories of depressive symptoms were constructed for males and females between 10.6 and 22.8 years old. We calculated the age of peak velocity for depressive symptoms (the age at which depressive symptoms increases most rapidly) and the age of maximum depressive symptoms. Adjusted results suggested that being female was associated with a steeper trajectory compared to being male (per 1 year increase in relation to depressive symptoms: 0.128, SE = 0.035, [95% CI: 0.059, 0.198]; p <0.001). We found evidence suggesting that females had an earlier age of peak velocity of depressive symptoms (females 13.7 years old, SE = 0.321, [95% CI: 12.9, 14.4] and males 16.4 years old, SE = 0.096, [95% CI: 16.2, 16.6]; p <0.001), but weak evidence of an earlier age of maximum depressive symptoms (p = 0.125). Possible mechanisms that underlie this sex difference include the roles of pubertal development and timing. Using multilevel growth curve models to estimate the age of peak velocity and maximum depressive symptoms for different population subgroups may provide useful knowledge for treating and preventing later depression.

epidemiology↗

Autistic traits and suicidal thoughts, plans and self-harm in late adolescence: population based cohort study

ImportanceThere have been recent concerns about a higher incidence of mortality by suicide in people with autism spectrum disorder (ASD). To our knowledge, no large cohort studies have examined which features of autism may lead to suicidal ideation and behaviour, and whether there are any potential modifiable mechanisms.\n\nObjectiveTo examine the hypothesis that ASD diagnosis and traits in childhood are associated with suicidal thoughts, plans and self-harm at 16 years, and that any of the observed associations are explained by depression in adolescence at 12 years.\n\nDesign, setting and participantsProspective investigation of associations between ASD diagnosis and autistic traits with suicidal ideation and behaviour and a potential risk pathway via depression in early adolescence in 5,031 members of the Avon Longitudinal Study of Parents and Children.\n\nMain outcomes and measuresHistory of self-harm with and without suicidal intent, suicidal thoughts and plans at 16 years assessed using a detailed self-report questionnaire. Exposures were ASD diagnosis and four measures (the coherence subscale of the Childrens Communication Checklist, the Social and Communication Disorders Checklist, a repetitive behaviour measure, and the sociability temperament subscale of the Emotionality, Activity and Sociability scale) dichotomised to represent the autism trait groups. Depressive symptoms in early adolescence were measured by the Short Moods and Feelings Questionnaire at 12 years.\n\nResultsChildren with impaired social communication had a higher risk of self-harm with suicidal intent (RR 2.10, 95% CI 1.28, 3.34), suicidal thoughts (1.42 times (95% CI 1.06, 1.91) and suicidal plans (RR 1.95, 95% CI 1.09, 3.47) by the age of 16 years as compared to those without. There was no evidence for an association between ASD diagnosis and the outcomes although these analyses were imprecise due to small numbers. There was also no evidence of an association between other autism trait measures and the outcomes. Approximately 32% of the total estimated association between social communication impairment and self-harm was explained by depressive symptoms at age 12 years.\n\nConclusionsImpairments in social communication are important in relation to suicidality. Early identification and management of depression may be a preventative mechanism and future research identifying other modifiable mechanisms may lead to preventative action or interventions against suicidal behaviour in this high-risk group.

epidemiology↗