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Western Psychiatric Institute & Clinic

Healthy Bodies, Healthy Minds: Helping Adolescents with Polycystic Ovary Syndrome. Dana L Rofey PhD University of Pittsburgh Department of Pediatrics (Children’s Hospital), Psychiatry (Western Psychiatric Institute), and Psychology Division of Weight Management and Wellness.

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Western Psychiatric Institute & Clinic

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  1. Healthy Bodies, Healthy Minds: Helping Adolescents with Polycystic Ovary Syndrome Dana L Rofey PhDUniversity of PittsburghDepartment of Pediatrics (Children’s Hospital), Psychiatry (Western Psychiatric Institute), and PsychologyDivision of Weight Management and Wellness Western Psychiatric Institute & Clinic

  2. Reviewed Articles • Rofey, D.L., Szigethy, E., Noll, R., Iobst, E., Dahl, R., & Arslanian, S. (2008). Cognitive Behavioral Therapy for adolescents with Polycystic Ovary Syndrome: A pilot study. Journal of Pediatric Psychology. • Rofey, D.L.,Hull, E.E., Phillips, J., Vogt, K., Silk, J.S., & Dahl, R.E. (in press). Utilizing EMA in pediatric obesity to quantify behavior, emotion, and sleep. Obesity.

  3. Overview • Brief background and rationale • Present studies • Future directions • Questions/thoughts from the group

  4. Background: PCOS • 10% of women • Comorbidities • Obesity • Depression • Sleep • PCOS: A model physical illness

  5. Behavioral Intervention: Why • Obesity • Depression • Sleep • Endocrine/Metabolic Functioning • Role of puberty

  6. CBT and Functioning • Weight • Family-based • Different approach • Depression • Multiple sources of information • New technology • Sleep (future direction) • Diaries • Actigraphy

  7. Aims • Aim 1: Behavioral • Change in weight (kg) • Increase in energy expenditure • Aim 2: Emotional • Change in depression (CDI; KSADS) • Aim 3: Physiological • Sleep • Metabolic parameters

  8. Screening Process Step 1 Participants are screened for depression (≥10 on the CDI) ↓ Step 2a Participants meet other inclusion criteria: PCOS (hyperandrogenism; oligo-ovulation; exclusion of other endocrine disorders) and are between the ages of 11 and 21 ↓ ↓ Step 2b Participants complete a semi-structured clinical interview, K-SADS ↓ Step 2c Participants meet DSM-IV criteria for minor/major depressive disorder ↓ Step 3 Participants sign the consent to participate in the intervention (11 sessions)

  9. Method Weight Management Solution: Armband and Feedback Device Answer-only cellular phone Total caloric intake Total physical activity Number of steps Sleep duration/efficiency

  10. Results Paired T-Tests Documenting Behavioral, Emotional, and Physiological Parameters in Adolescents with PCOS Pre- and Post-Intervention ________________________________________________________ Variables Pre-Tx Post-Tx t Value Effect Mean (SD) Mean (SD) Size ________________________________________________________ Depressive Symptoms CDI 14.1(8) 8.3(7) 4.5** .39 Weight Kilograms 106(26) 99(29) 2.5* .13 Sleep PSQ 1.24(.77) .62(.74) 2.9** .30 ________________________________________________________ Note: N=~44; CDI – Children’s Depression Inventory; PSQ – Pediatric Sleep Questionnaire, Sleepiness; *p < .05, ** p < .01 ________________________________________________________

  11. Behavioral, Emotional, and Physiological Outcomes Over Time

  12. EMA Results • Ecological Momentary Assessment Pilot Data • Compliance rate for armband: 74.7±.3% • Compliance rate for phone calls: 64.2 ±.3% • Higher BMIs were more likely to be compliant with EMA methods, rho=.78, p<.01. • No association between compliance rates for EMA and level of depressive symptoms.

  13. EMA Results • Mixed effect model • Significant interaction between group and physical activity, F (1,111) = 6.17; p < .05 in predicting positive mood. • For obese, depressed girls, physical activity predicts positive affect, mean = 3.1 • For controls, physical activity does not significantly predict positive affect, mean = 2.8. • SIDENOTE: For controls, physical activity does not affect positive affect.

  14. EMA Output Sample: Participant

  15. EMA Output Sample: Scientific

  16. Discussion • Similar underlying processes maintaining these changes • Targeting overlapping regulatory processes • Underlying neurobiological and genetic factors

  17. Discussion • Neurobiological underpinnings • Sleep as an effective “window into the brain” • Cognitive functioning (Hannon/Rofey, Hull, Kolko, Chakravorty, & Arslanian, to be submitted) • fMRI BRAINIMPLICATIONS Hypothalamus Regulating intake and homeostasis Anterior (amygdala, Initiation of eating striatum, insula) Anterior cortex (orbito- Termination of eating frontal, dorsolateral)

  18. Discussion • Genetic (chromosomes 2p, 3q, 5p, 6p, 7q, 10p, 11q, 17p and 20q) GENEASSOCIATED PHENOTYPE Leptin Satiation, metabolism Ghrelin Appetite stimulation PROP Taste preference PPAR Fat metabolism Mitochondrial uncoupling proteins Energy expenditure

  19. Future Directions • Temporal relationship: Eating, physical activity, mood, and sleep • Role of physiology in depression • Remaining sleep disturbances • Behavioral impact of intervention on: • Activation areas of the brain • Physiological data

  20. Thank you Mentors Ronald Dahl, MD Silva Arslanian, MD Thank you Collaborators Robert Noll, PhD Eva Szigethy, MD, PhD Ronette Blake, MS Ethan Hull, PhD Tamara Hannon, MD Pamela Murray, MD Hala Tfayli, MD Julie Byrne, CRNP Marsha Marcus, PhD Anne Marie Kuchera, RD, MA Joseph Sanfilippo, MD, MBA Jennifer Silk, PhD KayLoni Olson, Angela Vincent, Kelly Rabenstein, Katherine Belendiuk, Britney Brinkman, Emily Hogan, Erica Stein, Glory Ojiere, Amy Gillio, Jenn Jones, Jill Matlock, Brittany Musselman, Meaghan Beckner, Rachel Metz, Megan Barna, Ashley Rowden, Brian Thoma Weight Management & Wellness Center Polycystic Ovary Syndrome Center *These data were collected under NIH grants T32-HD049354-01, K12-HD043441-06, PMBC/HL076852/076858, and K23-HD061598

  21. Questions to the group • Is an 11-session intervention enough? • What about weight maintenance? • Are children who are obese with a medical diagnosis qualitatively different than obese adolescents without a medical diagnosis? • Challenges with actigraphy data • Data analysis • Participant and laboratory burden • Is it worthwhile to scan?

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