We propose to utilize a factor-based approach to classify Neuropsychiatric Symptoms (NPS) in a data-driven manner, and to determine the brain networks associated with different NPS factors, in 200 participants with mild Alzheimer?s disease (AD). There is a crucial need to develop improved treatments for NPS in ADRD. Current pharmacological treatments for NPS were developed 50 years ago, are often inefficacious, and can have serious adverse effects including increased mortality. Neuroanatomically-based treatments such as TMS and transcranial direct current stimulation (tDCS) for NPS are promising, but their development has been hampered by our lack of knowledge about the neuroanatomical bases of NPS in ADRD. The proposed project attempts to leverage current NIH-funded research programs and assessment tools developed in psychiatric settings to address this knowledge gap by: 1. Measuring and classifying NPS in a data-driven manner; 2. Determining the associations between empirically-determined NPS factors and specific brain networks; 3. Comparing a novel brief data-driven measure of NPS to two commonly used NPS measures using a neuro- anatomic gold-standard. These investigations have not been previously performed. Our subjects will be recruited from one ongoing NIH-funded study of a community-based cohort, the Predictors of Severity in AD study (AG007370), and the Columbia Memory and Behavioral Disorders Clinic. For the proposed project, we will perform the following measures in a single cross-sectional administration: Structural, DTI, and resting BOLD MRI; The Structured Clinical Interview for DSM-5 Research Version or SCID-5-RV; And the self- and informant-based DSM 5 Cross-Cutting Psychiatric Symptom Measure or ?Cross-Cutting Measure?. The SCID- 5-RV is a standardized clinical psychiatric interview developed over decades to assess a very large range of psychiatric symptoms in a reliable, valid, and psychometrically sound manner. The Cross-Cutting Measure is a valid, reliable, brief, adaptive instrument designed to assess all major domains of psychopathology with good psychometric properties. It can be administered on-line. A small number of factors have been found to underlie psychiatric diagnoses detected by the SCID, including Internalizing, Externalizing, and Psychosis factors. Damage to networks involving the ventromedial prefrontal cortex (vmPFC) and amydgala is associated with the Internalizing factor, the ventrolateral PFC (vlPFC) with the Externalizing factor, and the posterior cingulate cortex (PCC) with the Psychosis factor. We will assess the factor structure of NPS on the SCID-5-RV and determine the brain networks associated with these factors on sMRI, DTI, and fMRI. We will compare the Cross-Cutting Measure to the Neuropsychiatric Inventory and Geriatric Depression Scale using a neuroanatomic gold standard. These investigations could improve our measurement and understanding of the neuroanatomical bases of NPS and provide novel data-driven measures of NPS and treatment targets for use in clinical trials of neuroanatomically-based treatments for NPS in ADRD such as TMS and tDCS.
Neuropsychiatric symptoms in Alzheimer's disease and related dementias are a major public health problem as they are common, greatly increase the cost of and difficulty of care, and our pharmacological treatments are inadequate. We propose to use a data-driven approach to determine the factors underlying neuropsychiatric symptoms in participants with Alzheimer's disease, the brain networks associated with these factors, and test a novel brief global measure of neuropsychiatric symptoms. The goals are to improve the measurement and classification of neuropsychiatric symptoms in studies of participants with Alzheimer's disease and related dementias, and to identify measures to use and brain networks to target with anatomically-based treatments of neuropsychiatric symptoms, including Transcranial Magnetic Stimulation (TMS).
|Fieo, Robert A; Silverman, Hannah; O'Shea, Deirdre et al. (2018) Establishing dimensionality of sexual behaviours in patients with regional brain dysfunction. Brain Inj 32:1455-1464|