Measurement of Cardiometabolic Risk in Antipsychotic-Treated Children

Washington University, Saint Louis MO

Investigators

Linked publications, trials & patents

Abstract

DESCRIPTION (provided by applicant): This K23 award application is relevant to multiple topic areas in the recent IOM research priority list, as well as the recent IOM report brief and White House Let's Move Campaign focused on childhood obesity. The award will support mentoring, didactic training and additional career development activities for a candidate uniquely suited to develop expertise in the area of obesity and metabolic risk in children with mental health disorders. The applicant's immediate career goals are to further develop expertise in the measurement of metabolic mechanisms underlying obesity and cardiometabolic risk. The applicant's long-term career goal is to establish herself as an independent investigator studying childhood obesity and cardiometabolic risk in psychiatric populations. The specialized combined expertise that will emerge from the planned activities will be unique in the field of child psychiatry and will provide a resource for needed research in this high-priority, underserved topic area for decades to come. The US prevalence of childhood-onset obesity and type 2 diabetes, both predictors of cardiovascular risk, have increased to epidemic proportions in recent decades. Children with mental illness, especially those treated with antipsychotic medications, are at additional risk for obesity and related risk conditions. Despite known increases in obesity-related outcomes, including premature mortality, associated with childhood-onset versus adult-onset obesity, there remains an under-appreciation of these risks in children. A variety of noninvasive techniques to assess cardiometabolic risk have begun to be applied in children, including carotid intima media thickness (IMT) measured by ultrasound, and hepatic and cardiac triglyceride content measured by 1H Magnetic Resonance Spectroscopy (MRS). These measures allow for the early, noninvasive study of metabolic risk. Unfortunately, none of these promising methods have been applied to the high-risk population of children with psychiatric disorders, and cardiac triglyceride content has not been evaluated in children at all, preventing accurate characterization of risk or the effectiveness of interventions the reduce risk in this vulnerable population. The research portion of this application focuses on the use of sensitive, early biomarkers of disease risk, including hepatic triglyceride content (HTGC), as well as cardiac triglyceride content (CTGC) and carotid IMT, directly relevant to diabetes and cardiovascular disease risk, respectively. The overall aim of this two-study research plan is to characterize the level of measurable risk using these sensitive markers in treated and untreated children with mental health disorders, and to evaluate the magnitude of change in risk that can be observed using these biomarkers in children receiving a well- established behavioral weight-loss intervention. This will be accomplished using two studies: 1) A case control cross sectional comparison of CTGC, HTCG and IMT values in three groups of overweight/obese children who are age-, gender- and body mass index (BMI) percentile-matched: antipsychotic treated mentally ill children; mentally ill children not treated with antipsychotics and untreated children with no mental illness (a small reference group of lean healthy participants will also be included) and 2) A randomized controlled test of the effects of a 12-week behavioral weight loss intervention (versus diet and exercise education) on CTGC, HTGC and IMT in overweight/obese antipsychotic-treated children (a small reference group of healthy overweight/obese children will receive the active intervention only). The primary analytic plan will utilize ANOVA and ANCOVA, respectively, to test a focused set of hypotheses concerning the level of cardiometabolic risk in the study samples and the extent to which known weight loss interventions can modify these sensitive risk biomarkers. )