Dimensional clinical phenotyping using post‐mortem brain donor medical records: post‐mortem RDoC profiling is associated with Alzheimer's disease neuropathology

Abstract

Abstract Introduction Transdiagnostic dimensional phenotypes are essential to investigate the relationship between continuous symptom dimensions and pathological changes. This is a fundamental challenge to post‐mortem work, as assessments of phenotypic concepts need to rely on existing records. Methods We adapted well‐validated methodologies to compute National Institute of Mental Health Research Domain Criteria (RDoC) scores using natural language processing (NLP) from electronic health records (EHRs) obtained from post‐mortem brain donors and tested whether cognitive domain scores were associated with Alzheimer's disease neuropathological measures. Results Our results confirm an association of EHR‐derived cognitive scores with neuropathological findings. Notably, higher neuropathological load, particularly neuritic plaques, was associated with higher cognitive burden scores in the frontal (ß = 0.38, P = 0.0004), parietal (ß = 0.35, P = 0.0008), temporal (ß = 0.37, P = 0.0004) and occipital (ß = 0.37, P = 0.0003) lobes. Discussion This proof‐of‐concept study supports the validity of NLP‐based methodologies to obtain quantitative measures of RDoC clinical domains from post‐mortem EHR. The associations may accelerate post‐mortem brain research beyond classical case–control designs.

Keywords

• biological specimen banks
• dementia
• medical informatics
• natural language processing
• neuropathology