Empirically validate cognitive abilities as an RDoC transdiagnostic domain for mental health across neural and genetic units of analysis: a population-based cohort study in adolescents

Background: A 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 genetic units 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. Methods: We 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. Findings: Mental health predicted cognitive abilities of unseen children (i.e., those who were not part of the modelling process) at r=.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. Interpretation: Consistent 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 view of cognitive abilities as an integrative-functional domain for the aetiology of mental health. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement Data used in the preparation of this article were obtained from the Adolescent Brain Cognitive Development (ABCD) Study (https://abcdstudy.org), held in the NIMH Data Archive (NDA). This is a multisite, longitudinal study designed to recruit more than 10,000 children age 9 to 10 and follow them over 10 years into early adulthood. The ABCD Study is supported by the National Institutes of Health and additional federal partners under award numbers U01DA041022, U01DA041028, U01DA041048, U01DA041089, U01DA041106, U01DA041117, U01DA041120, U01DA041134, U01DA041148, U01DA041156, U01DA041174, U24DA041123, U24DA041147, U01DA041093 and U01DA041025. A full list of supporters is available at https://abcdstudy.org/federal-partners.html. A listing of participating sites and a complete listing of the study investigators can be found at https://abcdstudy.org/scientists/workgroups/. ABCD consortium investigators designed and implemented the study and/or provided data but did not necessarily participate in the analysis or writing of this report. This manuscript reflects the views of the authors and may not reflect the opinions or views of the NIH or ABCD consortium investigators. We thank the ABCD team. The authors wish to acknowledge the use of New Zealand eScience Infrastructure (NeSI) high performance computing facilities, consulting support and/or training services as part of this research. New Zealand national facilities are provided by NeSI and funded jointly by NeSI collaborator institutions and through the Ministry of Business, Innovation & Employment Research Infrastructure programme. URL https://www.nesi.org.nz. Yue Wang and Narun Pat were supported by Health Research Council Funding (21/618) and by University of Otago. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: We used publicly available ABCD 4.0 data provided by the ABCD study (https://abcdstudy.org), held in the NIMH Data Archive (https://nda.nih.gov/abcd/). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes We used publicly available ABCD 4.0 data provided by the ABCD study (https://abcdstudy.org), held in the NIMH Data Archive (https://nda.nih.gov/abcd/). We uploaded the R analysis script and detailed outputs here: https://github.com/HAM-lab-Otago-University/Commonality-analysis-ABCD4.0