Document text
Principal Investigator: Nadia Micali
Organization: UNIV OF NORTH CAROLINA CHAPEL HILL
Fiscal Year: 2024
Award: $587,548
Funding agency: National Institute of Mental Health
PROJECT SUMMARY
Eating disorders (ED) and non-eating disorders internalizing-spectrum disorders (nonED-INT; e.g., major
depressive disorder, generalized anxiety disorder, social phobia, obsessive-compulsive disorder, posttraumatic
stress disorder) have major public health importance due to their prevalence and significant personal and
societal costs. These disorders often onset during adolescence and co-occur. Despite years of psychiatric
research, detection and prevention strategies for ED and nonED-INT are not optimal. Little is understood about
the developmental course of ED and nonED-INT symptoms, particularly their co-development, and the degree
to which shared vs. unique genetic and phenotypic factors underlie ED and nonED-INT risk. In this study, we
will elucidate the taxonomy of ED and nonED-INT symptoms: clarifying their joint (i.e., as an overarching
internalizing dimension) and specific developmental course and identifying genetic and environmental
predictors. We will leverage the rich genomic and phenotypic data from two large and well-characterized
cohorts - the Adolescent Brain and Cognitive Development (ABCD) and the Avon Longitudinal Study of
Parents and Children (ALSPAC) cohorts. We will deliver developmental models of ED and nonED-INT
symptom course, explicate their joint and specific risk (genetic and environmental), and assess differences in
models across samples and race/ethnicities.
We propose three specific aims: First, using ABCD and ALSPAC data, we will empirically identify trajectories
of ED and nonED-INT symptoms across development for each cohort and assess stability of the models
across sex, race, and ethnicity. Second, using multi-trait genomic methods, we identify unique and common
genetic risk across ED and nonED-INT phenotypes. Finally, we will determine genetic and phenotypic
longitudinal predictors of ED and nonED-INT trajectories in each cohort and elucidate the stability and
robustness of a predictive model based on both genetic and early-life risk indicators.
In the short-term, our results will lend clarity to the taxonomy of ED and nonED-INT. In the long-term, improved
understanding of developmental pathways will aid early intervention and identification of high-risk youth.
Terms: <0-11 years old><12-20 years old><21+ years old><Adolescence><Adolescent><Adolescent Development><Adolescent Youth><Adult><Adult Human><Age><Anorexia Nervosa><Anthropometry><Anxiety Disorders><Binge eating disorder><Biological><Birth><Brain><Brain Nervous System><Bulimia><Bulimia Nervosa><Child><Child Youth><Childhood><Children (0-21)><Chronic><Classification><Cognition Disorders><Computing Methodologies><Crystallization><Data><Detection><Development><Developmental Course><Diagnosis><Dimensions><Disease><Disorder><Dysfunction><Early Intervention><Early identification><Eating><Eating Disorders><Encephalon><Equation><Ethnic Origin><Ethnicity><Factor Analyses><Factor Analysis><Food Intake><Functional disorder><Funding Opportunities><GWA study><GWAS><Gender><General Taxonomy><Generalized Anxiety Disorder><Generations><Genetic><Genetic Diseases><Genetic Risk><Genomic approach><Genomics><Joints><Life><Long-term cohort><Longitudinal Studies><Longitudinal cohort><Longterm cohort><Machine Learning><Major Depressive Disorder><Measurement><Mental disorders><Mental health disorders><Metabolic><Methods><Modeling><Moods><NIMH><National Institute of Mental Health><Nationalities><Obsessive-Compulsive Disorder><Obsessive-Compulsive Neurosis><Onset of illness><Outcome><PTSD><Parents><Parturition><Pathway interactions><Pattern><Phenotype><Physiopathology><Post-Traumatic Neuroses><Post-Traumatic Stress Disorders><Posttraumatic Neuroses><Predicting Risk><Prevalence><Preventative strategy><Prevention><Prevention strategy><Preventive strategy><Psychiatric Disease><Psychiatric Disorder><Public Health><Race><Races><Research><Risk><Sampling><Site><Social Phobia><Statistical Methods><Structure><Subgroup><Symptoms><Systematics><Taxonomy><Techniques><Testing><Work><Youth><Youth 10-21><adolescence (12-20)><adulthood><ages><biologic><bulimic><clinical depression><co-morbid><co-morbidity><co-occurring disorders><cognitive development><cognitive disease><cognitive disorder><cognitive syndrome><cohort><comorbidity><computational methodology><computational methods><computer based method><computer based prediction><computer methods><computing method><cost><developmental><differences due to race><differences in race><differs by race><differs in race><disease classification><disease onset><disease risk><disorder classification><disorder onset><disorder risk><dual diagnosis><early adulthood><effective therapy><effective treatment><emerging adult><emerging adulthood><forecasting risk><gender assigned><genetic condition><genetic disorder><genome wide association><genome wide association scan><genome wide association studies><genome wide association study><genomewide association scan><genomewide association studies><genomewide association study><genomic data><genomic data-set><genomic dataset><genomic effort><genomic strategy><girls><high risk><high risk group><high risk individual><high risk people><high risk population><improved><juvenile><juvenile human><kids><long-term study><longitudinal outcome studies><longterm study><machine based learning><major depression><major depression disorder><mental illness><multidisciplinary><nosology><novel><parent><pathophysiology><pathway><pediatric><phenotypic data><polygenic risk score><population based><post-COVID><post-COVID-19><post-coronavirus disease 2019><post-trauma stress disorder><posttrauma stress disorder><predict risk><predict risks><predicted risk><predicted risks><predicting risks><predictive modeling><predictive risk><predicts risk><psychiatric illness><psychological disorder><race based differences><race differences><race related differences><racial><racial background><racial difference><racial origin><racially different><risk prediction><risk prediction algorithm><risk prediction model><risk predictions><sex><sex assigned><societal costs><statistic methods><statistics><symptom cluster><trait><traumatic neurosis><whole genome association analysis><whole genome association studies><whole genome association study><youngster>