"Vulnerability to Drug Abuse: Pathways to Recovery" is an application for a competing continuation of R01 DA-11301. The application responds to PA-08-124, Epidemiology of Drug Abuse. The increase in rates of drug use and substance use disorders (SUD) across the teens and early 20s has been extensively studied at the level of epidemiology, theory, and intervention. In contrast, the decrease in drug use and SUD that begins in the later 20s (Figure A1) has received little scientific attention. Yet there are both scientific and public health reasons to pay close attention to this phenomenon. Scientifically, recovery from SUD is hard to explain within a simplistic model of gene-driven brain structure or function, or within current risk models. A more multifaceted, developmental understanding is needed. The public health implications arise from the possibility of developing ways to support natural recovery. Barriers to progress include the following: (1) Most research on natural (untreated) recovery uses samples of convenience;(2) representative population studies are largely cross-sectional, and so (a) rely on retrospective recall and (b) lack the ability to address mechanisms. The goals of the present application are (1) to distinguish stable recovery (recovery at age 26 and 30) from unstable patterns of SUD (e.g., relapse at age 30, new onsets at 26 or 30);and (2) to identify predictors and potential mechanisms that lead to stable recovery. The data will come from the Great Smoky Mountains Study (GSMS), a longitudinal, population-based study of 1,420 youth (70% Anglo, 25% American Indian, 5% African American, 50% female) recruited in 1993 at age 9-13 and assessed on average 8 times since then. Like the cross-sectional studies in Figure A1, the longitudinal GSMS data also shows SUD peaking in the early 20s and declining at the last assessment at age 26 (Figure B1). Data collection will include (as at every preceding wave) a full interview-based assessment of 18 DSM-IV substance use disorders and most psychiatric disorders, treatments and medications, level of functioning, health, family structure and functioning, education, employment, income, recent life events and quality of life. In addition we shall complete on all participants the CANTAB neurocognitive assessment battery that we are currently using with a subgroup of 160 who are participating in an fMRI study of adolescent-limited and persistent SUD. We will address these hypotheses: H1. Stable recovery at age 30 will be predicted by fewer comorbid psychiatric disorders, a higher level of functioning, better health and fewer traumatic life events by age 26, compared with relapse or persistence. H2. High levels of stress biomarkers (EBV, DHEAS, CRP, cortisol reactivity) in response to stressors at age 26 will predict relapse at age 30. H3. Stable recovery vs. relapse will be associated with poor delay of gratification and high sensation seeking. H4. Despite higher levels of SUD in Indians and males, neurocognitive mechanisms of risk will not differ.
Following high levels of adolescent/young adult substance use disorders (SUD), most individuals recover despite lack of treatment. The public health challenge is to ensure stable recovery and to prevent residual impairment. This phase of a longitudinal, population-based study (N=1,420, 70% Anglo, 25% American Indian, 5% African American, 50% female) seeks to understand the prevalence and mechanisms of stable recovery from SUD, vs. relapse and adult onset. Predictors include history of SUD, psychiatric disorders, treatment, level of functioning, health, family structure and functioning, education, employment, income, recent life events and quality of life. Mechanisms of stable recovery include stress biomarkers and neurocognitive style.
|Copeland, William E; Angold, Adrian; Shanahan, Lilly et al. (2014) Longitudinal patterns of anxiety from childhood to adulthood: the Great Smoky Mountains Study. J Am Acad Child Adolesc Psychiatry 53:21-33|
|Shanahan, Lilly; Zucker, Nancy; Copeland, William E et al. (2014) Are children and adolescents with food allergies at increased risk for psychopathology? J Psychosom Res 77:468-73|
|Sung, Minje; Erkanli, Al; Costello, E Jane (2014) Estimating the causal effect of conduct disorder on the time from first substance use to substance use disorders using g-estimation. Subst Abus 35:141-6|
|Towe-Goodman, Nissa R; Franz, Lauren; Copeland, William et al. (2014) Perceived family impact of preschool anxiety disorders. J Am Acad Child Adolesc Psychiatry 53:437-46|
|Copeland, William E; Shanahan, Lilly; Egger, Helen et al. (2014) Adult diagnostic and functional outcomes of DSM-5 disruptive mood dysregulation disorder. Am J Psychiatry 171:668-74|
|Shanahan, Lilly; Copeland, William E; Angold, Adrian et al. (2014) Sleep problems predict and are predicted by generalized anxiety/depression and oppositional defiant disorder. J Am Acad Child Adolesc Psychiatry 53:550-8|
|Shanahan, Lilly; Copeland, William E; Worthman, Carol M et al. (2013) Children with both asthma and depression are at risk for heightened inflammation. J Pediatr 163:1443-7|
|Copeland, William E; Shanahan, Lilly; Erkanli, Alaattin et al. (2013) Indirect comorbidity in childhood and adolescence. Front Psychiatry 4:144|
|Shanahan, Lilly; Copeland, William E; Worthman, Carol M et al. (2013) Sex-differentiated changes in C-reactive protein from ages 9 to 21: the contributions of BMI and physical/sexual maturation. Psychoneuroendocrinology 38:2209-17|
|Costello, E Jane; Eaves, Lindon; Sullivan, Patrick et al. (2013) Genes, environments, and developmental research: methods for a multi-site study of early substance abuse. Twin Res Hum Genet 16:505-15|
Showing the most recent 10 out of 38 publications