Ana Beatriz Ravagnani Salto, G. A. Salum, M. Hoffmann, Marcos L. Santoro, A. Zugman, Pedro M. Pan, S. Belangero, Lucas Toshio Ito, V. Doretto, M. S. Croci, Marcelo J A A Brañas, Carina de Giusti, Francisco Da Silva‐Jr, Sahâmia Martins Ribeiro, E. Miguel, J. Leckman
{"title":"The trajectory of anxiety symptoms during the transition from childhood to young adulthood is predicted by IQ and sex, but not polygenic risk scores","authors":"Ana Beatriz Ravagnani Salto, G. A. Salum, M. Hoffmann, Marcos L. Santoro, A. Zugman, Pedro M. Pan, S. Belangero, Lucas Toshio Ito, V. Doretto, M. S. Croci, Marcelo J A A Brañas, Carina de Giusti, Francisco Da Silva‐Jr, Sahâmia Martins Ribeiro, E. Miguel, J. Leckman","doi":"10.1002/jcv2.12268","DOIUrl":null,"url":null,"abstract":"Understanding the factors that determine distinct courses of anxiety symptoms throughout development will better guide interventions. There are scarce data‐driven longitudinal studies, using multi‐modal predictors, investigating the chronicity of anxiety symptoms from childhood to young adulthood, particularly in a middle‐income country.2033 youths (ages 6–14 years [Mean age = 10.4 ± 1.94) at Baseline] were enrolled in the Brazilian High‐Risk Cohort for Mental Conditions longitudinal study, and assessed at three timepoints, between 2010 and 2019, using the Screen for Child Anxiety Related Disorders. Confirmatory Factor Analysis provided input to Growth Mixture Models to identify the best fitting trajectory model. Multinomial logistic regression analyses tested the effects of intelligence quotient (IQ), environmental factors and polygenic risk scores on internalizing symptomatology within trajectory class membership.The best model solution identified three classes: high‐decreasing, moderate/low‐stable and low‐increasing symptoms over time. The high‐decreasing class showed a higher incidence of anxiety symptoms at the second time point (Mean age = 13.8 ± 1.93); while anxiety symptoms were highest in the low‐increasing class at the third timepoint (Mean age = 18.35 ± 2.03). Further, lower IQ predicted membership in the high‐decreasing trajectory class (OR = 0.68, 95% CI [0.55, 0.85]), while higher IQ predicted membership in the low‐increasing trajectory class (OR = 1.95, 95% CI [1.42, 2.67]). Finally, females were more likely than males to be in the low‐increasing trajectory class. Polygenic risk scores were not associated with anxiety trajectory class membership.Recognizing that anxiety symptoms follow diverse paths over time will allow for more effective intervention strategies. Specifically, interventions could accommodate children for greater anxiety risk in early childhood (i.e., lower IQ) versus late adolescence (i.e., higher IQ). That said, the emotional needs of girls in late adolescence should be monitored, regardless of their cognitive abilities or high achievements.","PeriodicalId":73542,"journal":{"name":"JCPP advances","volume":" 5","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JCPP advances","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/jcv2.12268","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Understanding the factors that determine distinct courses of anxiety symptoms throughout development will better guide interventions. There are scarce data‐driven longitudinal studies, using multi‐modal predictors, investigating the chronicity of anxiety symptoms from childhood to young adulthood, particularly in a middle‐income country.2033 youths (ages 6–14 years [Mean age = 10.4 ± 1.94) at Baseline] were enrolled in the Brazilian High‐Risk Cohort for Mental Conditions longitudinal study, and assessed at three timepoints, between 2010 and 2019, using the Screen for Child Anxiety Related Disorders. Confirmatory Factor Analysis provided input to Growth Mixture Models to identify the best fitting trajectory model. Multinomial logistic regression analyses tested the effects of intelligence quotient (IQ), environmental factors and polygenic risk scores on internalizing symptomatology within trajectory class membership.The best model solution identified three classes: high‐decreasing, moderate/low‐stable and low‐increasing symptoms over time. The high‐decreasing class showed a higher incidence of anxiety symptoms at the second time point (Mean age = 13.8 ± 1.93); while anxiety symptoms were highest in the low‐increasing class at the third timepoint (Mean age = 18.35 ± 2.03). Further, lower IQ predicted membership in the high‐decreasing trajectory class (OR = 0.68, 95% CI [0.55, 0.85]), while higher IQ predicted membership in the low‐increasing trajectory class (OR = 1.95, 95% CI [1.42, 2.67]). Finally, females were more likely than males to be in the low‐increasing trajectory class. Polygenic risk scores were not associated with anxiety trajectory class membership.Recognizing that anxiety symptoms follow diverse paths over time will allow for more effective intervention strategies. Specifically, interventions could accommodate children for greater anxiety risk in early childhood (i.e., lower IQ) versus late adolescence (i.e., higher IQ). That said, the emotional needs of girls in late adolescence should be monitored, regardless of their cognitive abilities or high achievements.