125 research outputs found

    What life course theoretical models best explain the relationship between exposure to childhood adversity and psychopathology symptoms: Recency, accumulation, or sensitive periods?

    Get PDF
    Copyright © Cambridge University Press 2018Â. Background Although childhood adversity is a potent determinant of psychopathology, relatively little is known about how the characteristics of adversity exposure, including its developmental timing or duration, influence subsequent mental health outcomes. This study compared three models from life course theory (recency, accumulation, sensitive period) to determine which one(s) best explained this relationship.Methods Prospective data came from the Avon Longitudinal Study of Parents and Children (n = 7476). Four adversities commonly linked to psychopathology (caregiver physical/emotional abuse; sexual/physical abuse; financial stress; parent legal problems) were measured repeatedly from birth to age 8. Using a statistical modeling approach grounded in least angle regression, we determined the theoretical model(s) explaining the most variability (r2) in psychopathology symptoms measured at age 8 using the Strengths and Difficulties Questionnaire and evaluated the magnitude of each association.Results Recency was the best fitting theoretical model for the effect of physical/sexual abuse (girls r2 = 2.35%; boys r2 = 1.68%). Both recency (girls r2 = 1.55%) and accumulation (boys r2 = 1.71%) were the best fitting models for caregiver physical/emotional abuse. Sensitive period models were chosen alone (parent legal problems in boys r2 = 0.29%) and with accumulation (financial stress in girls r2 = 3.08%) more rarely. Substantial effect sizes were observed (standardized mean differences = 0.22-1.18).Conclusions Child psychopathology symptoms are primarily explained by recency and accumulation models. Evidence for sensitive periods did not emerge strongly in these data. These findings underscore the need to measure the characteristics of adversity, which can aid in understanding disease mechanisms and determining how best to reduce the consequences of exposure to adversity

    Dopamine Genetic Risk Score Predicts Depressive Symptoms in Healthy Adults and Adults with Depression

    Get PDF
    Background: Depression is a common source of human disability for which etiologic insights remain limited. Although abnormalities of monoamine neurotransmission, including dopamine, are theorized to contribute to the pathophysiology of depression, evidence linking dopamine-related genes to depression has been mixed. The current study sought to address this knowledge-gap by examining whether the combined effect of dopamine polymorphisms was associated with depressive symptomatology in both healthy individuals and individuals with depression. Methods: Data were drawn from three independent samples: (1) a discovery sample of healthy adult participants (n = 273); (2) a replication sample of adults with depression (n = 1,267); and (3) a replication sample of healthy adult participants (n = 382). A genetic risk score was created by combining functional polymorphisms from five genes involved in synaptic dopamine availability (COMT and DAT) and dopamine receptor binding (DRD1, DRD2, DRD3). Results: In the discovery sample, the genetic risk score was associated with depressive symptomatology (β = −0.80, p = 0.003), with lower dopamine genetic risk scores (indicating lower dopaminergic neurotransmission) predicting higher levels of depression. This result was replicated with a similar genetic risk score based on imputed genetic data from adults with depression (β = −0.51, p = 0.04). Results were of similar magnitude and in the expected direction in a cohort of healthy adult participants (β = −0.86, p = 0.15). Conclusions: Sequence variation in multiple genes regulating dopamine neurotransmission may influence depressive symptoms, in a manner that appears to be additive. Further studies are required to confirm the role of genetic variation in dopamine metabolism and depression