INS NYC 2024 Program

Poster	Poster Session 06 Program Schedule 02/15/2024 04:00 pm - 05:15 pm Room: Majestic Complex (Posters 61-120) Poster Session 06: Aging \| MCI \| Neurodegenerative Disease - PART 2 Final Abstract #100 Identifying Rates and Neurocognitive Drivers of Clinical-Neuropathology Diagnostic Discordance in Alzheimer’s Disease Rita Taylor, University of Missouri, Columbia, United States Andrew Kiselica, University of Missouri, Columbia, United States Category: Dementia (Alzheimer's Disease) Keyword 1: neurocognition Keyword 2: executive functions Keyword 3: dementia - Alzheimer's disease Objective: The National Institute on Aging and Alzheimer’s Association (NIA-AA) are currently revising clinical criteria for Alzheimer’s disease diagnosis. Proposed criteria indicate a shift away from clinical-neuropathological correlation to a focus on in vivo biomarker diagnosis. One criticism of the clinical-neuropathological diagnostic process has been that these diagnoses can be discordant. However, rates and drivers of discordance are understudied. This goal is important to inform the current NIA-AA criteria revision process and update clinician knowledge about in-life indicators of possible presence of pathology for purposes of biomarker referral. Thus, the aim of the current study was to describe rates of clinical-neuropathological/diagnostic discordance in AD and examine neurocognitive drivers of concordance and discordance. Participants and Methods: The sample consisted of participants from the National Alzheimer’s Coordinating Center (NACC) Uniform Dataset (UDS) and Neuropathology (NP) Datasets. Participants were included if they completed the neuropsychological battery for at least one timepoint and had neuropathology data available. The final sample consisted of 919 participants (Male=54%). Clinical diagnoses of suspected AD etiology were determined by clinicians according to contemporary diagnostic criteria. Neuropathology diagnoses were determined using the NIA-AA AD neuropathologic change variable. The sample was divided into four groups: concordant AD, concordant non-AD, discordant AD-clinical (clinical diagnosis, no neuropathology diagnosis), and discordant AD-neuropathology (neuropathology diagnosis, no clinical diagnosis). Between-subjects ANOVAs were used to evaluate group performance differences across domains of memory, language, attention, and executive functioning (EF). Results: The sample broke down as follows: 52% concordant AD, 30% concordant non-AD, 7% discordant AD-clinical, 15% discordant AD-neuropath. There were no significant differences in attention [F(3, 919) = 2.11, p = 0.98, η²= 0.01] or language [F(3, 919) = 2.42, p = 0.06, η²= 0.01] performance. There were significant differences in memory [F(3, 919) = 31.71, p < 0.001, η²= 0.11] and EF [F(3, 919) = 7.37, p < 0 .001, η²= 0.04] performance between groups. Post hoc tests revealed that for memory, performance was worst in the concordant AD group, followed by the concordant non-AD group, discordant AD-neuropathology group, and discordant AD-clinical group. For EF, performance was worst in the concordant AD group, followed by the discordant AD-neuropathology group, discordant AD-clinical group, and concordant non-AD group. Follow-up analyses revealed that lower EF performance was related to lower memory performance, but the strength of this relationship was significantly attenuated in concordant AD. Conclusions: Unsurprisingly, given historical importance of memory dysfunction in AD, findings indicate that memory performance was worst in concordant AD. On the other hand, given the role of EF in diagnosing non-AD pathology, it was unexpected that those in concordant non-AD and discordant AD-clinical groups performed better on EF compared to concordant AD. However, EF deficits in non-AD and discordant AD-clinical were more strongly related to poor memory performance, suggesting that EF could be having a greater influence on memory performance in these groups. Results suggest that NIA-AA criteria can incorporate cognitive findings (e.g., poor memory) that point to a need for biomarker testing but that careful attention should be paid to possible confounds (e.g., executive deficits).

Poster

02/15/2024
04:00 pm - 05:15 pm
Room: Majestic Complex (Posters 61-120)

Poster Session 06: Aging | MCI | Neurodegenerative Disease - PART 2

Final Abstract #100

Identifying Rates and Neurocognitive Drivers of Clinical-Neuropathology Diagnostic Discordance in Alzheimer’s Disease

Rita Taylor, University of Missouri, Columbia, United States
Andrew Kiselica, University of Missouri, Columbia, United States

Category: Dementia (Alzheimer's Disease)

Keyword 1: neurocognition
Keyword 2: executive functions
Keyword 3: dementia - Alzheimer's disease

Objective:

The National Institute on Aging and Alzheimer’s Association (NIA-AA) are currently revising clinical criteria for Alzheimer’s disease diagnosis. Proposed criteria indicate a shift away from clinical-neuropathological correlation to a focus on in vivo biomarker diagnosis. One criticism of the clinical-neuropathological diagnostic process has been that these diagnoses can be discordant. However, rates and drivers of discordance are understudied. This goal is important to inform the current NIA-AA criteria revision process and update clinician knowledge about in-life indicators of possible presence of pathology for purposes of biomarker referral. Thus, the aim of the current study was to describe rates of clinical-neuropathological/diagnostic discordance in AD and examine neurocognitive drivers of concordance and discordance.

Participants and Methods:

The sample consisted of participants from the National Alzheimer’s Coordinating Center (NACC) Uniform Dataset (UDS) and Neuropathology (NP) Datasets. Participants were included if they completed the neuropsychological battery for at least one timepoint and had neuropathology data available. The final sample consisted of 919 participants (Male=54%). Clinical diagnoses of suspected AD etiology were determined by clinicians according to contemporary diagnostic criteria. Neuropathology diagnoses were determined using the NIA-AA AD neuropathologic change variable. The sample was divided into four groups: concordant AD, concordant non-AD, discordant AD-clinical (clinical diagnosis, no neuropathology diagnosis), and discordant AD-neuropathology (neuropathology diagnosis, no clinical diagnosis). Between-subjects ANOVAs were used to evaluate group performance differences across domains of memory, language, attention, and executive functioning (EF).

Results:

The sample broke down as follows: 52% concordant AD, 30% concordant non-AD, 7% discordant AD-clinical, 15% discordant AD-neuropath. There were no significant differences in attention [F(3, 919) = 2.11, p = 0.98, η²= 0.01] or language [F(3, 919) = 2.42, p = 0.06, η²= 0.01] performance. There were significant differences in memory [F(3, 919) = 31.71, p < 0.001, η²= 0.11] and EF [F(3, 919) = 7.37, p < 0 .001, η²= 0.04] performance between groups. Post hoc tests revealed that for memory, performance was worst in the concordant AD group, followed by the concordant non-AD group, discordant AD-neuropathology group, and discordant AD-clinical group. For EF, performance was worst in the concordant AD group, followed by the discordant AD-neuropathology group, discordant AD-clinical group, and concordant non-AD group. Follow-up analyses revealed that lower EF performance was related to lower memory performance, but the strength of this relationship was significantly attenuated in concordant AD.

Conclusions:

Unsurprisingly, given historical importance of memory dysfunction in AD, findings indicate that memory performance was worst in concordant AD. On the other hand, given the role of EF in diagnosing non-AD pathology, it was unexpected that those in concordant non-AD and discordant AD-clinical groups performed better on EF compared to concordant AD. However, EF deficits in non-AD and discordant AD-clinical were more strongly related to poor memory performance, suggesting that EF could be having a greater influence on memory performance in these groups. Results suggest that NIA-AA criteria can incorporate cognitive findings (e.g., poor memory) that point to a need for biomarker testing but that careful attention should be paid to possible confounds (e.g., executive deficits).