The Identifying Depression Early in Adolescence Risk Stratified Cohort (IDEA-RiSCo): Rationale, Methods, and Baseline Characteristics

Abstract

Background: The characterization of adolescents at high risk for developing depression has traditionally relied on the presence or absence of single risk factors. More recently, the use of composite risk scores combining information from multiple variables has gained attention in prognostic research in the field of mental health. We previously developed a sociodemographic composite score to estimate the individual level probability of depression occurrence in adolescence, the Identifying Depression Early in Adolescence Risk Score (IDEA-RS).Objectives: In this report, we present the rationale, methods, and baseline characteristics of the Identifying Depression Early in Adolescence Risk Stratified Cohort (IDEA-RiSCo), a study designed for in-depth examination of multiple neurobiological, psychological, and environmental measures associated with the risk of developing and with the presence of depression in adolescence, with a focus on immune/inflammatory and neuroimaging markers.Methods: Using the IDEA-RS as a tool for risk stratification, we recruited a new sample of adolescents enriched for low (LR) and high (HR) depression risk, as well as a group of adolescents with a currently untreated major depressive episode (MDD). Methods for phenotypic, peripheral biological samples, and neuroimaging assessments are described, as well as baseline clinical characteristics of the IDEA-RiSCo sample.Results: A total of 7,720 adolescents aged 14–16 years were screened in public state schools in Porto Alegre, Brazil. We were able to identify individuals at low and high risk for developing depression in adolescence: in each group, 50 participants (25 boys, 25 girls) were included and successfully completed the detailed phenotypic assessment with ascertainment of risk/MDD status, blood and saliva collections, and magnetic resonance imaging (MRI) scans. Across a variety of measures of psychopathology and exposure to negative events, there was a clear pattern in which either the MDD group or both the HR and the MDD groups exhibited worse indicators in comparison to the LR group.Conclusion: The use of an empirically-derived composite score to stratify risk for developing depression represents a promising strategy to establish a risk-enriched cohort that will contribute to the understanding of the neurobiological correlates of risk and onset of depression in adolescence.

The experience of receiving a diagnosis of depression in adolescence: A pilot qualitative study in Brazil

“…The Identifying Depression Early in Adolescence Risk Stratified Cohort (IDEA RiSCo) study (Kieling et al, 2021) included a sample of 150 adolescents aged 14–16 years from schools in Porto Alegre, Rio Grande do Sul, Brazil, who had undergone screening for risk factors associated with MDD (see Table 1 for the list of factors). Additional information on the study setting is provided in Supplemental Appendix A.…”

Social isolation as a core feature of adolescent depression: a qualitative study in Porto Alegre, Brazil

“…They were also asked to suggest other professionals in their network that could take part in the interviews. Parents and adolescents were recruited from a group involved in a research project on adolescent depression (Kieling et al, 2021 ).…”

Cortisol and development of depression in adolescence and young adulthood – a systematic review and meta-analysis

“…Our findings further highlight the importance of longitudinal studies in adolescence, considering that this period and early adulthood constitute the peak for new cases, in many cross-sectional designs the individuals at-risk might be inadvertently classified as “healthy controls”, whilst some of them might develop depression which is not depicted. Therefore, a more comprehensive way of understanding depression and the risk factors associated with depression onset, is crucial to more accurately identify who is at-risk of developing this condition which would allow designing better prevention strategies ( Kieling et al, 2021 ).…”