Empirically validate cognitive abilities as an RDoC transdiagnostic domain for mental health across neural and genetic units of analysis

Abstract

SummaryBackgroundA leading transdiagnostic framework for psychiatry, NIMH Research Domain Criteria (RDoC), posits that cognitive abilities are a major factor (known as functional domain) underlying mental health across various diagnoses. Specifically, RDoC assumes the relationship between cognitive abilities and mental health to be 1) manifested across neural and geneticunits of analysis, 2) environmentally situated, and 3) reliable. These central assumptions have not been empirically validated. To address this, we used data from the Adolescent Brain Cognitive Development (ABCD) Study, which included 11,876 participants (5,680 females). The study spanned two years and focused on children aged 9-10 and 11-12.MethodsWe applied machine learning to make out-of-sample predictions of cognitive abilities based on measures of mental health (emotional/behavioural problems, at-risk personalities), neuroimaging (45 types of brain MRI), polygenic scores (three definitions), and socio-demographics, lifestyles and developments (44 variables e.g., parental income, screen use). Using linear-mixed-model commonality analyses, we then examined the extent to which the relationship between cognitive abilities and mental health was explained by the other measures.FindingsMental health predicted cognitive abilities of unseen children (i.e., those who were not part of the modelling process) atr=.39. At baseline, this cognitive-abilities-mental-health relationship was accounted for by neuroimaging (69%), by polygenic scores (18%) and by socio-demographics, lifestyles and developments (70%). Moreover, the variance in the relationship between cognitive abilities and mental health that was captured by socio-demographics, lifestyles and developments was explained by neuroimaging (66%) and polygenic scores (22%). These patterns were consistent across the two-time points.InterpretationConsistent with RDoC, the cognitive abilities and mental health relationship was 1) manifested in both neuroimaging and polygenic scores, 2) explained by socio-demographics, lifestyles and developments and 3) reliable across two years. This supports RDoC’s view of cognitive abilities as an integrative-functional domain for the aetiology of mental health.FundingHealth Research Council Funding of New Zealand (21/618) and University of OtagoResearch in ContextEvidence before this studyIt has been over a decade since the initiation of Research Domain Criteria (RDoC) by the US National Institute of Mental Health. The first article outlining its framework (Insel et al., 2010,AJP) has been cited over 6,650 times according to Google Scholar as of September 25th, 2023. In one estimate (Pacheco et al., 2022,JCPP), 644 RDoC-themed grants were funded between 2008-19 in the US. RDoC has also asserted its impact on psychiatric research outside of the US, as seen in frameworks such as the Psychiatric Ratings using Intermediate Stratified Markers (PRISM) funded by EU-Innovative Medicine Initiative (Kas et al., 2019,Neuroscience and Biobehavioral Reviews). Accordingly, RDoC has had a great influence on the landscape of modern psychiatric research. Yet, most RDoC-themed studies have focused on applying the framework (e.g., to improve the aetiology of certain mental illnesses), but few, if any, have tested its central assumptions regarding the properties of its functional domains. These assumptions were largely expert-drivenNY. Here, we focused on empirically validating the properties of one of the six major functional domains, cognitive systems (note we called them cognitive abilities here to map closer to a term used in cognitive literature).Added value of this studyDuring the time when RDoC was first developed, there was no large-scale neuroimaging and genetic data appropriate to validate the framework. The emergence of studies such as the Adolescent Brain Cognitive Development (ABCD) offers not only neuroimaging and genetic data but also high-quality data on phenotypes (e.g., mental health and cognitive abilities) along with socio-demographics and lifestyles which allows us to validate the RDoC framework. Using machine learning, we were able to quantify the extent to which the relationship between cognitive abilities and mental health was 1) manifested in both neuroimaging and polygenic scores, 2) explained by socio-demographics, lifestyles, and developments and 3) reliable across two years. Accordingly, our study validated the role of cognitive abilities as a functional domain according to RDoC.Implications of all of the available evidenceWe provide empirical evidence to support RDoC’s view of cognitive abilities as a transdiagnostic domain for mental health. By doing so, we laid a foundation to achieve the four goals set by RdoC (Pacheco et al., 2022,JCPP). First, we have addressed the aetiology of mental health by showing the reliable and predictable transdiagnostic relationship between cognitive abilities and mental health. Second, we also identified neuroimaging and genetic biomarkers that explain this relationship. Third, with our findings on the socio-demographics, lifestyles and developments, we touched on target identification. Finally, our use of machine learning to make out-of-sample predictions on individual children could lead to further development of personalised interventions. Overall, our findings lend credibility to RDoC research focusing on cognitive abilities.