Major depressive disorder (MDD) is a common illness that often has chronic or recurring course. Prevention is believed to be the key to reducing the burden of this disorder. However, an effective prevention program requires thorough knowledge of predisposing factors and mechanisms by which they convey risk. Personality characteristics are powerful predictors of MDD onset, but it is not yet clear which traits are the best markers of vulnerability. Also, the mechanisms underlying these links are not well understood. This project aims to identify main personality risk factors for depression onset and elucidate relevant etiologic processes, including interactions with life stress as well as neural and endocrinal mechanisms. Another objective is to learn how much concomitant depression distorts scores on personality measures, thus informing basic personality research and clinical assessment. We propose to recruit 575 14- and 15-year-old females (demographic stratum at highest risk for incident depression) who have never experienced a major depressive episode. Participants will be assessed in person three times: at baseline, month 18, and month 36. They will complete a thorough diagnostic interview, a battery of personality scales, as well as measures of negative life events, daily functioning, cortisol levels, and brain activity. They also will participate in brief phone interviews between assessments to minimize biases in recall of depressive episodes and stressful life events. Family psychiatric history and informant-ratings of personality will be obtained from a parent. We will use Structural Equation Modeling (SEM) to estimate trait scores with high precision, and growth modeling to remove distortions in these ratings induced by concomitant depression. We expect these analytic strategies to substantially enhance power of our analyses and will develop formulas for correcting personality scores in future studies. Next, we will examine the dynamic interplay between personality and environment in development of vulnerability to MDD. We also will test two promising biomarkers of pathological developmental trajectories. Furthermore, we will develop a personality screen to identify adolescents at risk well before they experienced depression. This multidisciplinary project will form the basis for a program of research that ultimately seeks to design and target new preventive interventions for adolescent depression.

Public Health Relevance

The goal of this project is to identify adolescent women at risk for major depression and find new opportunities to prevent development of depression. To achieve this aim we will follow a sample of 575 healthy 14- and 15-year-old girls and will try to predict who becomes depressed over the next 3 years. Our findings will help researchers to develop and target new preventive measures.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Research Project (R01)
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Study Section
Child Psychopathology and Developmental Disabilities Study Section (CPDD)
Program Officer
Garriock, Holly A
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State University New York Stony Brook
Schools of Medicine
Stony Brook
United States
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Meyer, Alexandria; Nelson, Brady; Perlman, Greg et al. (2018) A neural biomarker, the error-related negativity, predicts the first onset of generalized anxiety disorder in a large sample of adolescent females. J Child Psychol Psychiatry 59:1162-1170
Nelson, Brady D; Infantolino, Zachary P; Klein, Daniel N et al. (2018) Time-Frequency Reward-Related Delta Prospectively Predicts the Development of Adolescent-Onset Depression. Biol Psychiatry Cogn Neurosci Neuroimaging 3:41-49
Hausman, Estee M; Kotov, Roman; Perlman, Greg et al. (2018) Prospective predictors of first-onset depressive disorders in adolescent females with anxiety disorders. J Affect Disord 235:176-183
Jin, Jingwen; Narayanan, Ananth; Perlman, Greg et al. (2017) Orbitofrontal cortex activity and connectivity predict future depression symptoms in adolescence. Biol Psychiatry Cogn Neurosci Neuroimaging 2:610-618
Kopala-Sibley, Daniel C; Klein, Daniel N; Perlman, Greg et al. (2017) Self-criticism and dependency in female adolescents: Prediction of first onsets and disentangling the relationships between personality, stressful life events, and internalizing psychopathology. J Abnorm Psychol 126:1029-1043
Schuler, Keke L; Ruggero, Camilo J; Goldstein, Brandon L et al. (2017) Diurnal Cortisol Interacts With Stressful Events to Prospectively Predict Depressive Symptoms in Adolescent Girls. J Adolesc Health 61:767-772
Goldstein, Brandon L; Perlman, Greg; Kotov, Roman et al. (2017) Etiologic specificity of waking Cortisol: Links with maternal history of depression and anxiety in adolescent girls. J Affect Disord 208:103-109
Gromatsky, Molly A; Waszczuk, Monika A; Perlman, Greg et al. (2017) The role of parental psychopathology and personality in adolescent non-suicidal self-injury. J Psychiatr Res 85:15-23
Liu, Keke; Ruggero, Camilo J; Goldstein, Brandon et al. (2016) Elevated cortisol in healthy female adolescent offspring of mothers with posttraumatic stress disorder. J Anxiety Disord 40:37-43
Kopala-Sibley, Daniel C; Danzig, Allison P; Kotov, Roman et al. (2016) Negative emotionality and its facets moderate the effects of exposure to Hurricane Sandy on children's postdisaster depression and anxiety symptoms. J Abnorm Psychol 125:471-81

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