Corticotropin-releasing hormone system polymorphisms are associated with children's cortisol reactivity.

The hypothalamic-pituitary-adrenal (HPA) axis underlies both adaptive and maladaptive responses to stress and may be an important marker of childhood vulnerability to psychopathology, although little is known about genetic variants that influence cortisol reactivity. We therefore examined associations between corticotrophin-releasing hormone (CRH) system gene (CRH, CRHR1 and CRHBP) variants and cortisol reactivity in preschoolers. A community sample of 409 three-year-old children completed a standardized stress task to elicit HPA axis activation. Salivary samples were obtained at the baseline and at 10-min intervals post-stress for a total of six samples. Salivary cortisol was measured using standard ELISA (enzyme-linked immunosorbent assay) protocols and cortisol reactivity was operationalized by calculating cortisol change scores ([baseline]-[peak cortisol post-stressor]). A single nucleotide polymorphism (SNP) marker panel containing 18 SNPs was used to tag the full-length CRH (4 SNPs), CRHR1 (7 SNPs) and CRHBP (7 SNPs) genes. Significant main effects on children's cortisol reactivity (all ps<0.05) were found for loci on CRHR1 and CRHBP. Haplotypes of the CRHR1 linkage region were also associated with cortisol reactivity (all ps<0.01). Additionally, we found multiple interactions between tag-SNPs in all three gene-coding regions predicting cortisol reactivity (all ps<0.05). Individual differences in children's cortisol reactivity are related to genetic variation in CRH system gene-coding regions. Our results have important implications for future research on the role of HPA axis function in the development of disorders such as anxiety and depression.

Additive effects of the dopamine D2 receptor and dopamine transporter genes on the error-related negativity in young children.

The error-related negativity (ERN) is a negative deflection in the event-related potential that occurs approximately 50 ms following the commission of an error at fronto-central electrode sites. Previous models suggest dopamine plays a role in the generation of the ERN. We recorded event-related potentials (ERPs) while 279 children aged 5-7 years completed a simple Go/No-Go task; the ERN was examined in relation to the dopamine D2 receptor (DRD2) and dopamine transporter (DAT1) genes. Results suggest an additive effect of the DRD2 and DAT1 genotype on ERN magnitude such that children with at least one DRD2 A1 allele and children with at least one DAT1 9 allele have an increased (i.e. more negative) ERN. These results provide further support for the involvement of dopamine in the generation of the ERN.

Molecular genetics of bipolar disorder.

Bipolar disorder (BPD) is an often devastating illness characterized by extreme mood dysregulation. Although family, twin and adoption studies consistently indicate a strong genetic component, specific genes that contribute to the illness remain unclear. This study gives an overview of linkage studies of BPD, concluding that the regions with the best evidence for linkage include areas on chromosomes 2p, 4p, 4q, 6q, 8q, 11p, 12q, 13q, 16p, 16q, 18p, 18q, 21q, 22q and Xq. Association studies are summarized, which support a possible role for numerous candidate genes in BPD including COMT, DAT, HTR4, DRD4, DRD2, HTR2A, 5-HTT, the G72/G30 complex, DISC1, P2RX7, MAOA and BDNF. Animal models related to bipolar illness are also reviewed, with special attention paid to those with clear genetic implications. We conclude with suggestions for strategies that may help clarify the genetic bases of this complex illness.

Outcome of dysthymic disorder at 5-year follow-up: the effect of familial psychopathology, early adversity, personality, comorbidity, and chronic stress.

OBJECTIVE: This study sought to identify predictors of course and outcome in dysthymic disorder. METHOD: Eighty-six outpatients with early-onset dysthymic disorder (before age 21) participated in a prospective 5-year follow-up study. Family history of psychopathology, early home environment, axis I and II comorbidity, social support, and chronic stress were assessed at baseline. The Longitudinal Interval Follow-up Evaluation and the Hamilton Depression Rating Scale were used in the follow-up assessments conducted at 30 and 60 months. RESULTS: Comorbid anxiety disorder, cluster C and depressive personality features, and chronic stress were associated with a lower rate of recovery from dysthymic disorder, while family history of bipolar disorder was associated with a higher probability of recovery. Family history of dysthymic disorder, poor childhood maternal and paternal relationships, childhood sexual abuse, cluster C features, neuroticism, a history of anxiety and eating disorders, and chronic stress predicted higher levels of depression at follow-up. Multivariate models indicated that almost all domains contributed to the prediction of course and outcome. CONCLUSIONS: The course and outcome of dysthymic disorder is best conceptualized within a multifactorial framework, with family history of psychopathology, early adversity, axis I and II comorbidity, and chronic stress all making important contributions.