# Neuroanatomical associations with the factor structure underlying neuropsychiatric symptoms in Alzheimer's disease

> **NIH NIH R01** · COLUMBIA UNIVERSITY HEALTH SCIENCES · 2021 · $530,267

## Abstract

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-...

## Key facts

- **NIH application ID:** 10172821
- **Project number:** 5R01AG062268-04
- **Recipient organization:** COLUMBIA UNIVERSITY HEALTH SCIENCES
- **Principal Investigator:** Edward D Huey
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $530,267
- **Award type:** 5
- **Project period:** 2018-09-30 → 2023-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10172821

## Citation

> US National Institutes of Health, RePORTER application 10172821, Neuroanatomical associations with the factor structure underlying neuropsychiatric symptoms in Alzheimer's disease (5R01AG062268-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10172821. Licensed CC0.

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