Detecting Cognitive Impairment in African American Older Adults Using the LASSI-L and Plasma P-Tau 217

Background: Alzheimer’s disease (AD) disproportionately affects Black/African American (B/AA) older adults, yet this group remains underrepresented in research. Traditional neuropsychological assessments, often developed on predominantly White populations, may not be reliable for B/AA individuals. The Loewenstein-Acevedo Scales for Semantic Interference and Learning (LASSI-L) have been shown to effectively differentiate individuals with amnestic mild cognitive impairment (aMCI) from cognitively unimpaired (CU) individuals. This study examines the relationship between LASSI-L performance and plasma p-tau ₂₁₇ levels to explore early detection methods for AD in B/AA populations. Methods: Fifty-six older adults received clinical and cognitive evaluations and were deemed cognitively unimpaired (CU) and p-tau ₂₁₇ negative (n = 35) or met criteria for amnestic mild cognitive impairment (aMCI) and p-tau ₂₁₇ positive (n = 21). All participants were administered the LASSI-L to compare groups, but it was not used for group allocation to avoid circularity. Results: After adjusting for age and MMSE score, the aMCI p-tau ₂₁₇+ group performed significantly worse than the CU p-tau ₂₁₇- group on both free recall on List B (Free B1 Recall) and frPSI (correct responses on Cued B2). These differences remained statistically significant after covariate adjustment (p < 0.001). In addition, four other outcomes remained statistically significant following covariate adjustment: the aMCI p-tau ₂₁₇+ group exhibited a higher percentage of intrusion errors (PIE) on both Cued B1 and Cued B2, along with poorer performance on maximal learning ability (Cued A2) and PSI (correct responses on Cued B1). However, after applying the Bonferroni correction, only PIE on Cued B2 remained statistically significant among these measures. Notably, performance on LASSI-L Free B1 Recall and PIE for List Cued B2 were significant predictors distinguishing aMCI p-tau ₂₁₇+ from CU p-tau ₂₁₇- groups, with high sensitivity (80%) and specificity (91.7%). ROC analysis of these predictors yielded an area under the curve of 0.872 (SE = 0.055; p < 0.001), with a 95% confidence interval ranging from 0.765 to 0.979. Conclusion: The study highlights the utility of the LASSI-L in conjunction with plasma biomarkers, particularly p-tau ₂₁₇, for early AD detection in B/AA older adults. The LASSI-L demonstrated strong sensitivity to cognitive impairment, effectively differentiating between CU and aMCI groups based on plasma p-tau ₂₁₇ levels. These findings suggest that combining cognitive assessments with plasma biomarkers can enhance early diagnosis and improve timely interventions, addressing health disparities in AD diagnosis and care.

• Alzheimer’s Disease
• Mild Cognitive Impairment
• P-Tau217
• LASSI-L

1. Introduction

Alzheimer’s disease (AD) is one of the most prevalent conditions impacting older adults, with Black/African American (B/AA) older adults being disproportionately impacted. Specifically, among B/AA older adults, approximately 20% are living with AD, nearly double the prevalence seen in their white counterparts (11.5%), despite often experiencing delayed or missed diagnoses altogether [1] - [3] . Despite being heavily impacted, B/AA older adults remain one of the most underrepresented groups in AD research [2] . This underrepresentation poses a critical issue, especially since many neuropsychological assessments were developed and normed primarily on White populations, often failing to account for cultural differences. As a result, these assessments may lead to inaccurate diagnoses for B/AA individuals. The lack of reliable and culturally relevant assessments for B/AA older adults is particularly troubling given that existing literature highlights lower baseline global cognition, poorer performance on cognitive assessments, and a slower rate of cognitive decline associated with AD [4] [5] . This further emphasizes the need for more accurate and culturally sensitive assessments for B/AA older adults to ensure these individuals can receive timely and appropriate interventions.

Although traditional neuropsychological assessments may lack reliability in B/AA populations, the Loewenstein-Acevedo Scales for Semantic Interference and Learning (LASSI-L) is an innovative cognitive challenge test that is sensitive to early cognitive changes in preclinical and prodromal AD and other neurodegenerative conditions [6] - [10] , while also being culturally fair and effective at differentiating individuals with amnestic mild cognitive impairment (aMCI) from cognitively unimpaired (CU) individuals across a number of ethnic and cultural groups including B/AA populations which is an outcome not consistently achieved with traditional neuropsychological assessments [11] - [13] .

In addition to these novel cognitive assessments, advances in plasma-based biomarkers, particularly p-tau₂₁₇, demonstrate excellent promise for the early detection of AD [14] . P-tau₂₁₇ consistently demonstrates high sensitivity and specificity to Aβ PET positivity and tau PET results [15] [16] . Research has shown that p-tau₂₁₇ levels correlate with both current AD brain pathology and future cognitive performance. Additionally, a recent study with plasma p-tau₂₁₇ has indicated that this measure is equally effective as amyloid PET imaging in identifying various stages of AD progression [17] . These findings suggest p-tau₂₁₇ may serve as a strong predictor for detecting AD even before clinical symptoms appear and may serve as a valuable indicator during the different stages of AD [18] . There is increasing interest in the use of plasma-based biomarkers like p-tau₂₁₇ which has been heralded as an extremely promising approach to use for screening purposes in primary care settings. However, a limitation of this approach is that abnormal amyloid accumulation may occur many years before clinical symptoms [19] - [21] . Thus, elevated plasma p-tau₂₁₇ does not necessarily mean that cognitive or functional impairment is present or even unfolding. To that end, blood-based biomarkers in the absence of sensitive cognitive measures may not have clinical relevance in primary care or community health settings. Of particular concern is the underrepresentation of B/AA older adults in much of the rapidly evolving research related to plasma biomarkers, as well as their decreased likelihood of seeking cognitive evaluations despite having twice the prevalence of AD and AD-Related Dementias (ADRD) relative to the general population [22] - [25] .

The LASSI-L has been found to be related to PET amyloid burden as well as elevated levels of plasma p-tau₁₈₁ and Aβ 42/40 [26] - [29] and has shown good generalizability to older Hispanic and non-Hispanic populations. Unfortunately, the LASSI-L has not yet been related to p-tau₂₁₇ or any other plasma biomarkers of AD in a B/AA cohort. Therefore, the current investigation represents the first systematic attempt to examine differences in LASSI-L performance among cognitively impaired B/AA older adults with suspected underlying AD pathology (elevated plasma p-tau₂₁₇) and CU B/AA older adults without elevated plasma p-tau₂₁₇. Based on previous research, it was hypothesized that SIEs and other cognitive deficits measured by the LASSI-L could discriminate between B/AAs who were cognitively impaired likely due to underlying AD and controls.

2. Methods

2.1. Study Population

Fifty-six participants aged 60 and above from two IRB-approved studies with identical clinical and neuropsychological profiles were included from the following two studies: Florida Alzheimer’s Disease Research Center (ADRC) and Innovative Deep Phenotyping of African Americans at Risk for Alzheimer’s disease. Both studies were IRB approved (i.e., AG047726602/ AG066506 and AG077677).

All participants were community dwellers who were independent in completing basic and instrumental activities of daily living and did not meet DSM-5-TR criteria for Major Neurocognitive Disorder or any other significant neuropsychiatric disorder that could preclude reliable cognitive assessments [30] .

The standardized protocol consisted of neuropsychological battery and annual clinical assessment protocol which was administered at the same time the Hopkins Verbal Learning Test-Revised [31] , a measure of episodic memory including a single paragraph using recall of the passage [32] , Category Fluency [33] , Stroop Color Word Test [34] , and Trail Making Test Part A and B [35] . The neuropsychological assessments and clinical interviews were completed separately by experienced clinicians to avoid criterion contamination. All participants were evaluated in English. Diagnostic determination was made by a multidisciplinary consensus panel and independent of the LASSI-L to avoid diagnostic circularity.

2.2. Cut-Offs for p-tau 217 Positivity

Venous blood was collected using 10mL Purple Top tubes containing EDTA as an anticoagulant, mixed by inversion ten times, and centrifuged at room temperature for 12 minutes at 1700 RPM within one hour of collection. Aliquots of 500 microliters of plasma were then frozen and stored at -80 degrees Celsius (C). Prior to analysis, the samples were thawed (1 freeze-thaw cycle) at room temperature, vortexed for 30 seconds, and placed on ice until centrifuging at 10,000g for five minutes at 4C. Single molecule array (SIMOA) technology for p-tau₂₁₇ (ALZpath; Quanterix, Billerica, MA) was employed. Duplicate samples were analyzed. We only included samples with a coefficient of variation (CV) 20% or less. It is common practice in our laboratories and others to exclude p-tau₂₁₇ values that have a duplicate covariation of greater than 20%. This is because the reliability of the findings with such a high coefficient of variability is unreliable.

Internally derived cutoffs for “positive” plasma p-tau₂₁₇ were based on correspondence with the visual read of an Aβ-PET scan contiguous with the blood draw from our ADRC (N = 239). A cutoff value of > 0.55 pg/ml representing a positive plasma p-tau₂₁₇ value was derived from the receiver operating characteristic (ROC) curve and Youden’s index. The cutoff value of 0.55 pg/ml, representing a “positive” plasma p-tau₂₁₇ test had a sensitivity of 89% and a specificity of 82% [36] . In a series of several datasets across the globe, Ashton and colleagues [14] found a correspondence with amyloid PET scans at the 95th percentile at plasma p-tau₂₁₇ > 0.63 pg/ml, but acknowledged that p-tau₂₁₇ scores at our cut-off of > 0.55 pg/ml likely reflected AD pathology accumulation. As such, our cut off of > 0.55 pg/ml was maintained to represent amyloid positivity. However, Ashton and colleagues [14] argued that p-tau₂₁₇ as low as 0.43-0.55 pg/ml may still represent amyloid accumulation. Thus, to be conservative, we employed Ashton’s cut-off of < 0.40 pg/ml as representing the absence of significant abnormal plasma amyloid accumulation.

2.3. Diagnostic Classification

Based on the participants comprehensive clinical interview and performance on the neuropsychological testing battery, diagnostic groups were classified utilizing the following criteria:

2.4. Cognitively Unimpaired p-tau 217 Negative Group (CU p-tau 217 -; n = 35)

Participants were classified as CU p-tau₂₁₇- if the following criteria were met: a) no subjective cognitive complaints by the participant and/or informant; b) Global Clinical Dementia Scale (CDR) of 0; c) performance across measures demonstrated scores less than 1.0 SD below the mean accounting for age and education, d) P-tau₂₁₇ was deemed negative if below the p-tau₂₁₇ cutoff of < 0.40 pg/ml as described above.

2.5. Amnestic Mild Cognitive Impairment p-tau 217 Positive Group (aMCI p-tau 217 +; n = 21)

Participants were classified as aMCI p-tau₂₁₇+ if the following criteria were met: a) subjective cognitive complaints by the participant and/or informant; b) Global CDR of 0.5; c) one or more memory measures on the standardized battery listed above demonstrated scores at least 1.5 SD or more below the mean accounting for age, education, and language; d) p-tau₂₁₇ was deemed positive if above the p-tau₂₁₇ cutoff of > 0.55 pg/ml.

2.6. Loewenstein-Acevedo Scales for Semantic Interference and Learning (LASSI-L)

All participants were administered the LASSI-L; however, it was not utilized in diagnosis to avoid circularity. The LASSI-L is a well-established cognitive stress test validated in both English and multiple other languages. It has demonstrated strong test-retest reliability as well as high discriminative and concurrent validity [11] [37] - [40] . Furthermore, a preliminary study with the LASSI-L suggested it is culturally fair and effective in distinguishing individuals with aMCI from CU individuals in B/AA populations [13] .

During administration of the LASSI-L, the participant uses controlled learning and cued recall to maximize storage of an initial list of 15 target words (List A) representing one of the three semantic categories (i.e., fruits, clothing, musical instruments). After the 15 words from List A have been presented, there is a free recall trial and then cued recall trials for each of the three categories consisting of five words per category. List A is presented again along with the cued recall trials for each of the three categories. Afterwards, a second list of different words for free recall (List B) from the same semantic categories is presented immediately after the second trial of List A. The presence of shared semantic categories between Lists A and B leads to a significant amount of proactive semantic interference (PSI), which is measured during Cued B (Cued B1 recall). Compared to conventional memory assessments, the re-presentation and subsequent recall of this second word list evaluates an individual’s capacity to recover from the effects of PSI (frPSI) (Cued B2 recall). Of note, the participant is later provided with category cues to determine how many words they are able to recall from List A to measure retroactive semantic interference and the later recovery from PSI is not assessed by any other memory paradigm. For more information regarding LASSI-L, refer to Curiel and colleagues [37] [38] .

In the current study, we examined the LASSI-L variables including maximal learning ability (Cued A2), PSI (correct responses on Cued B1), frPSI (correct responses on Cued B2), and semantic intrusion errors (SIE) that occurred during both Cued B1 and Cued B2. To assess SIEs, a method was developed using the percentage of intrusion errors (PIE) relative to total correct responses, accounting for the relationship between errors and total responses which provides more information compared to the absolute number of intrusions alone which is calculated by the formula: Intrusion Errors/(Intrusion Errors + Correct Responses) [41] . PIE was utilized in the current study and has previously demonstrated to be highly sensitive to early cognitive impairment [41] [42] .

3. Statistical Analyses

For initial comparisons between diagnostic groups, a one-way analysis of variance (ANOVA) and analysis of covariance (ANCOVAs) controlling for age and performance on the MMSE were employed. Based on obtained findings, a stepwise binary logistic regression analysis was performed to determine the extent to which LASSI-L variables could distinguish between CU p-tau₂₁₇- and aMCI p-tau₂₁₇+ groups. Afterwards, a receiver operative characteristic (ROC) analysis was conducted to examine the sensitivity and specificity in the LASSI-L variables’ ability to differentiate between groups.

4. Results

As demonstrated in Table 1 , the CU p-tau₂₁₇- and aMCI p-tau₂₁₇+ groups were found to have similar educational backgrounds and similar gender distribution with no statistically significant differences. Age and performance on the MMSE, a global cognitive screener, were statistically significant indicating those who are aMCI p-tau₂₁₇+ were older and presented with worsening performance on the MMSE compared to those who were deemed CU p-tau₂₁₇. Performance across the LASSI-L demonstrated B/AA aMCI p-tau₂₁₇+ participants presented with worsening performance compared to the CU p-tau₂₁₇- participants across all LASSI-L variables. After controlling for age and performance on the MMSE, performance on the LASSI-L subtests across aMCI p-tau₂₁₇+ and CU p-tau₂₁₇- were subsequently examined.

Table 1

Table 1. Diagnostic groups, demographic, lassi-l performance, and plasma biomarkers in B/AA older adults.

	Cognitively Unimpaired p−tau217- (n = 35)	aMCI p−tau217+ (n = 21)	F-or X2 Value	p-value	Eta Squared
Age	65.94 (SD = 5.1) (range 56 - 78)	69.81 (SD = 6.1) (range 56 - 81)	6.12	p = 0.016	0.100
Education	14.31 (SD = 2.7) (range = 10 - 20)	14.52 (SD = 3.0) (range = 11 - 20)	0.08	p = 0.78	NA
MMSE Score (range 23 - 30)	28.71 (SD = 1.5) (range = 24 - 30)	26.05 (SD = 2.5) (range = 21 - 30)	16.88	p < 0.001	0.235
Female (%)	62.9%	52.4%	0.24	p = 0.411	NA
P-tau217 (Range = 0.180 - 3.15)	0.225 (SD = 0.07) range (0.100 - 0.370 pg/ml)	1.01 (SD = 0.55) range (0.560 - 2.710 pg/ml)	73.40	p < 0.001	0.572
LASSI-L Cued A2 Recall	13.53 (SD = 1.6) (range = 8 - 15)	10.97 (SD = 2.4) (range = 6 - 15)	18.60	p < 0.001	0.253
LASSI-L Free B1 Recall	7.14 (SD = 0.24) Range (2 - 12)	3.76 (SD = 2.5) (range 0 - 10)	22.70	p < 0.001	0.292
LASSI-L Free B1 Intrusions	0.83 (SD = 1.1) Range (0 - 4)	1.95 (SD = 2.1) (range 0 - 6)	22.70	p < 0.001	0.292
LASSI-L Cued B1 Recall	7.26 (SD = 2.7) (range 1 - 12)	4.76 (SD = 2.5) (range 0 - 10)	14.11	p < 0.001	0.204
LASSI-L Cued B1 Intrusions	1.97 (SD = 2.1) (range 0 - 11)	4.05 (SD = 3.0) (range 0 - 0)	9.93	p = 0.002	0.153
LASSI-L Cued B2 Recall	10.97 (SD = 1.5) (range 3 - 14)	7.57 (SD = 2.6) (range 3 - 12)	23.29	p < 0.001	0.297
LASSI-L Cued B2 Intrusions	1.57 (SD = 1.7) (range 0 - 7)	3.38 (SD = 2.3) (range 0 - 8)	10.24	p = 0.002	0.157
Percentage Intrusion Errors (PIE Cued B1)	0.204 (SD = 0.20) (range 0 - 0.85)	0.468 (SD = 0.27) (range 0 - 1.00)	18.11	p < 0.001	0.251
Percentage Intrusion Errors (PIE Cued B2)	0.118 (SD = 0.13) (range 0 - 0.64)	0.295 (SD = 0.17) (range 0 - 0.57)	18.52	p < 0.001	0.252

An inspection of Table 2 after adjustment for covariates allowed for us to determine both changes in LASSI-L p-values and effect sizes could be compared to unadjusted values in Table 1 (all p< 0.002). Since the inclusion of covariates reduced degrees of freedom and statistical power, we first present unadjusted values since performing Bonferroni measures across so many tests would likely result in family-wise type 2 errors (accepting a false null hypothesis). Performance across the LASSI-L demonstrated that B/AA aMCI p-tau₂₁₇ + group performed significantly worse than the CU p-tau₂₁₇- group on Free B1 Recall and Cued B2 Recall. These differences remained statistically significant after covariate adjustment (p< 0.001). In addition, four other outcomes remained statistically significant following covariate adjustment: the aMCI p-tau₂₁₇+ group exhibited a higher percentage of intrusion errors on both Cued B1 and Cued B2, along with poorer performance on Cued A2 and Cued B1 Recall. However, after applying the Bonferroni correction, only PIE on Cued B2 remained statistically significant among these measures.

Table 2

Table 2. African American diagnostic groups demographic, LASSI-L indices and plasma biomarkers after adjustment for age and MMSE scores.

	Cognitively Unimpaired p-tau217- (n = 35)	aMCI p-tau217 + (n = 21)	F-or X2 Value	p-value	Partial Eta Squared
LASSI-L Cued A2 Recall	13.21 (SE = 0.34)	11.84 (SE = 0.46)	4.82	p = 0.033	8.5%
LASSI-L Free B1 Recall	7.00 (SE = 0.46)	4.00 (SE = 0.62)	12.67	p < 0.001	19.6%
LASSI-L Free B1 Intrusions	1.05 (SE = 0.26)	1.68 (SE = 0.36)	1.65	p = 0.205	3.1%
LASSI-L Cued B1 Recall	7.14 (SE = 0.49)	4.96 (SE = 0.67)	5.88	p = 0.019	10.2%
LASSI-L Cued B1 Intrusions	2.48 (SE = 0.42)	3.21 (SE = 0.57)	0.890	p = 0.350	1.7%
LASSI-L Cued B2 Recall	10.75 (SE = 0.47)	7.94 (SE = 0.64)	10.53	p < 0.001	16.8%
LASSI-L Cued B2 Intrusions	1.77 (SE = 0.36)	3.05 (SE = 0.48)	3.82	p = 0.056	6.8%
Percentage Intrusion Errors (PIE Cued B1)	0.243 (SE = 0.04)	0.401 (SE = 0.06)	4.45	p = 0.04	8.0%
Percentage Intrusion Errors (PIE Cued B2)	0.135 (SE = 0.03)	0.267 (SE = 0.04)	6.87	p = 0.011	11.7%

Table 3 demonstrated performance on LASSI-L Free B1 Recall and PIE for List Cued B2 are significant predictors of aMCI p-tau₂₁₇+ and able to distinguish between those who were aMCI p-tau₂₁₇+ versus CU p-tau₂₁₇- with high sensitivity (80%) and specificity (91.7%). These two variables yielded a single predicted probability score, which was then employed in ROC analysis which yielded an area under the curve of 0.872 (SE = 0.055); p < 0.001. At the 95th percentile, the lower bound was 0.765 while the upper bound was 0.079 ( Figure 1 ).

Table 3

Table 3. Predicting group membership (CU p-tau 217 - vs. aMCI p-tau 217 +) Using performance on LASSI-L.

	B	S.E.	Wald	df	Sig.
Pie Cued B2	5.80	2.5	5.47	1	0.019
LASSI Free Recall B	−0.497	0.717	9.05	1	0.002
Constant	1.038	1.011	1.054	1	0.305

Note: Sensitivity of Joint Predictors is 80.0% and specificity is 97.1%.

Figure 1

Figure 1. Area under the ROC curve.

5. Discussion

This is the first study to examine differences in LASSI-L performance between aMCI B/AA older adults with suspected underlying AD pathology (high p-tau₂₁₇ load) and CU B/AA older adults without suspicion of underlying AD (low p-tau₂₁₇ load). Results demonstrated that LASSI-L variables, specifically PIE for Cued B2, Free B1 Recall, and Cued B2 Recall were able to effectively discriminate between aMCI and CU B/AA groups, and that the LASSI-L could distinguish between groups with differing p-tau₂₁₇ levels. This study highlights the utilization of the LASSI-L in combination with plasma biomarkers to enhance early detection of AD/ADRD, marking a significant finding as this is the first time the LASSI-L correct recall responses and SIEs have been linked to p-tau₂₁₇ in a B/AA cohort. This suggests that the LASSI-L cognitive challenge test is indicative of cognitive deficits which may reflect difficulties in the participant’s ability to maintain accurate memory and an increased vulnerability to inaccurate recall. This finding aligns with previous literature showing that the LASSI-L could be a useful predictor of clinical progression over time in at-risk older adults since the LASSI-L was able to accurately depict those patients who progressed from Pre-MCI to aMCI [42] .

As expected, the aMCI p-tau₂₁₇+ group exhibited inferior performance on free recall across PSI (correct responses on Cued B1) and frPSI (correct responses on Cued B2). These findings suggest the LASSI-L remains sensitive to cognitive changes and can effectively discriminate between B/AA older adults who are cognitively impaired versus CU. This aligns with previous studies [29] [41] [42] , highlighting the potential of the LASSI-L as a reliable tool for assessing cognitive function in B/AA populations and underscores the importance of utilizing cognitive assessments in early detection. While plasma biomarkers, particularly p-tau₂₁₇, have shown sensitivity and predictive value for AD, these may be elevated in the absence of clinical symptoms. Thus, for clinical screening and evaluation, these exciting emerging biomarkers can best be used in conjunction with cognitive assessments, such as the LASSI-L, as biomarkers alone do not indicate the presence of current cognitive impairment. Early access to plasma biomarkers, even before clinical symptoms emerge, may allow for timely referrals for cognitive evaluations, helping to assess the extent of cognitive impairment and inform appropriate interventions. These findings are particularly significant for the B/AA population, given the high prevalence of AD and their lower likelihood of seeking cognitive evaluations. A p-tau₂₁₇ assay, combined with the brief LASSI-L (a shortened version of the full LASSI-L), could provide valuable information in primary care or remote community settings, where access to specialty memory disorder centers or amyloid/tau neuroimaging may be limited.

There are several strengths of the current study. The study design allowed for participants to be carefully diagnosed utilizing identical clinical and neuropsychological protocols to place individuals into CU and aMCI groups. The LASSI-L was also not utilized when diagnosing the CU and aMCI groups which is a strength as it avoided circularity. Additional strengths include adjustments being employed in statistical methods for age and performance on a global cognitive screener (i.e., MMSE). While the relationship between plasma biomarkers and cognitive decline in B/AA populations remains underexplored, our study adds to a growing body of evidence supporting the use of culturally fair cognitive assessments and easily accessible biomarkers in these communities. This evidence is valuable as it not only bridges the gap in the literature but also provides practical and non-invasive methods for early detection of AD/ADRD which may help address disparities in AD diagnosis and care among this underrepresented population. Limitations of the current study include the modest total sample size of 56 participants. Increasing the participant pool would strengthen the generalizability of the findings, enabling a more thorough analysis and a more accurate reflection of the diverse characteristics within the population. Further studies with aMCI participants with low p-tau and different etiologies will also provide meaningful information that would be valuable for assessing B/AA populations.

Although beyond the scope of the current investigation, future research should aim to examine medical comorbidities that might be related to both cognitive impairment and trajectories of cognitive and functional decline longitudinally to further assess the LASSI-L’s predictive abilities. This will enhance our knowledge of early detection of AD/ADRD in our underserved B/AA older adult populations.

Acknowledgments

This research was funded by the National Institute of Health Grant R01 AG077677 (David Loewenstein, PI) and National Institute of Aging Grant R01 AG047649 (David Loewenstein, PI). Funding was also provided by the 1Florida Alzheimer’s Disease Research Center 5 P50 AG047726602 and 1P30AG066506-01 (Glenn Smith, Ranjan Duara and David Loewenstein MPIs). The sponsors had no role in the design and conduct of the study; in the collection analysis, and interpretation of data; in the preparation of the manuscript; or in the review or approval of the manuscript.

References

1. Kornblith, E., Bahorik, A., Boscardin, W.J., Xia, F., Barnes, D.E. and Yaffe, K. (2022) Association of Race and Ethnicity with Incidence of Dementia among Older Adults. JAMA, 327, 1488-1495. >https://doi.org/10.1001/jama.2022.3550

2. Rosselli, M., Uribe, I.V., Ahne, E. and Shihadeh, L. (2022) Culture, Ethnicity, and Level of Education in Alzheimer’s Disease. Neurotherapeutics, 19, 26-54. >https://doi.org/10.1007/s13311-022-01193-z

3. Rigby, T., Gregoire, A.M., Reader, J., Kahsay, Y., Fisher, J., Kairys, A., et al. (2024) Identification of Amnestic Mild Cognitive Impairment among Black and White Community-Dwelling Older Adults Using NIH Toolbox Cognition Tablet Battery. Journal of the International Neuropsychological Society, 30, 689-696. >https://doi.org/10.1017/s1355617724000213

4. Barnes, L.L., Wilson, R.S., Li, Y., Aggarwal, N.T., Gilley, D.W., McCann, J.J., et al. (2005) Racial Differences in the Progression of Cognitive Decline in Alzheimer Disease. The American Journal of Geriatric Psychiatry, 13, 959-967. >https://doi.org/10.1097/00019442-200511000-00006

5. Barnes, L.L. and Bennett, D.A. (2014) Alzheimer’s Disease in African Americans: Risk Factors and Challenges for the Future. Health Affairs, 33, 580-586. >https://doi.org/10.1377/hlthaff.2013.1353

6. Loewenstein, D.A., Curiel, R.E., Duara, R. and Buschke, H. (2017) Novel Cognitive Paradigms for the Detection of Memory Impairment in Preclinical Alzheimer’s Disease. Assessment, 25, 348-359. >https://doi.org/10.1177/1073191117691608

7. Crocco, E.A., Loewenstein, D.A., Curiel, R.E., Alperin, N., Czaja, S.J., Harvey, P.D., et al. (2018) A Novel Cognitive Assessment Paradigm to Detect Pre-Mild Cognitive Impairment (PreMCI) and the Relationship to Biological Markers of Alzheimer’s Disease. Journal of Psychiatric Research, 96, 33-38. >https://doi.org/10.1016/j.jpsychires.2017.08.015

8. Cid, R.E.C. and Loewenstein, D.A. (2022) Salient Cognitive Paradigms to Assess Preclinical Alzheimer’s Disease. Neurotherapeutics, 19, 89-98. >https://doi.org/10.1007/s13311-022-01192-0

9. Sierra, L.A., Hughes, S.B., Ullman, C.J., Hall, A., Pandeya, S.R., Schubert, R., et al. (2023) LASSI-L Detects Early Cognitive Changes in Pre-Motor Manifest Huntington’s Disease: A Replication and Validation Study. Frontiers in Neurology, 14, Article 1191718. >https://doi.org/10.3389/fneur.2023.1191718

10. Loewenstein, D.A., Curiel, R.E., Wright, C., Sun, X., Alperin, N., Crocco, E., et al. (2017) Recovery from Proactive Semantic Interference in Mild Cognitive Impairment and Normal Aging: Relationship to Atrophy in Brain Regions Vulnerable to Alzheimer’s Disease. Journal of Alzheimer’s Disease, 56, 1119-1126. >https://doi.org/10.3233/jad-160881

11. Matías-Guiu, J.A., Curiel, R.E., Rognoni, T., Valles-Salgado, M., Fernández-Matarrubia, M., Hariramani, R., et al. (2016) Validation of the Spanish Version of the LASSI-L for Diagnosing Mild Cognitive Impairment and Alzheimer’s Disease. Journal of Alzheimer’s Disease, 56, 733-742. >https://doi.org/10.3233/jad-160866

12. Curiel Cid, R.E., Loewenstein, D.A., Rosselli, M., Matias‐Guiu, J.A., Piña, D., Adjouadi, M., et al. (2019) A Cognitive Stress Test for Prodromal Alzheimer’s Disease: Multiethnic Generalizability. Alzheimer’s&Dementia: Diagnosis, Assessment&Disease Monitoring, 11, 550-559. >https://doi.org/10.1016/j.dadm.2019.05.003

13. Capp, K.E., Curiel Cid, R.E., Crocco, E.A., Stripling, A., Kitaigorodsky, M., Sierra, L.A., et al. (2019) Semantic Intrusion Error Ratio Distinguishes between Cognitively Impaired and Cognitively Intact African American Older Adults. Journal of Alzheimer’s Disease, 73, 785-790. >https://doi.org/10.3233/jad-191022

14. Ashton, N.J., Brum, W.S., Di Molfetta, G., Benedet, A.L., Arslan, B., Jonaitis, E., et al. (2024) Diagnostic Accuracy of a Plasma Phosphorylated Tau 217 Immunoassay for Alzheimer Disease Pathology. JAMA Neurology, 81, 255-263. >https://doi.org/10.1001/jamaneurol.2023.5319

15. Doecke, J.D., Pérez-Grijalba, V., Fandos, N., Fowler, C., Villemagne, V.L., Masters, C.L., et al. (2020) Total Aβ ₄₂/Aβ ₄₀ Ratio in Plasma Predicts Amyloid-Pet Status, Independent of Clinical AD Diagnosis. Neurology, 94, e1580-e1591. >https://doi.org/10.1212/wnl.0000000000009240

16. Mundada, N.S., Rojas, J.C., Vandevrede, L., Thijssen, E.H., Iaccarino, L., Okoye, O.C., et al. (2023) Head-to-Head Comparison between Plasma P-Tau217 and Flortaucipir-PET in Amyloid-Positive Patients with Cognitive Impairment. Alzheimer’s Research&Therapy, 15, Article No. 157. >https://doi.org/10.1186/s13195-023-01302-w

17. Lehmann, S., Schraen-Maschke, S., Vidal, J., Delaby, C., Buee, L., Blanc, F., et al. (2024) Clinical Value of Plasma ALZpath pTau217 Immunoassay for Assessing Mild Cognitive Impairment. Journal of Neurology, Neurosurgery&Psychiatry, 95, 1046-1053. >https://doi.org/10.1136/jnnp-2024-333467

18. Jonaitis, E.M., et al. (2022) Plasma pTau-217 in Preclinical Alzheimer’s Disease. medRxiv 2022.06.09.22276206. >https://doi.org/10.1101/2022.06.09.22276206.

19. Bennett, D.A., Schneider, J.A., Arvanitakis, Z., Kelly, J.F., Aggarwal, N.T., Shah, R.C., et al. (2006) Neuropathology of Older Persons without Cognitive Impairment from Two Community-Based Studies. Neurology, 66, 1837-1844. >https://doi.org/10.1212/01.wnl.0000219668.47116.e6

20. Knopman, D.S., Parisi, J.E., Salviati, A., Floriach-Robert, M., Boeve, B.F., Ivnik, R.J., et al. (2003) Neuropathology of Cognitively Normal Elderly. Journal of Neuropathology&Experimental Neurology, 62, 1087-1095. >https://doi.org/10.1093/jnen/62.11.1087

21. Grøntvedt, G.R., Schröder, T.N., Sando, S.B., White, L., Bråthen, G. and Doeller, C.F. (2018) Alzheimer’s Disease. Current Biology, 28, R645-R649. >https://doi.org/10.1016/j.cub.2018.04.080

22. Gurland, B.J., Wilder, D.E., Lantigua, R., Stern, Y., Chen, J., Killeffer, E.H.P., et al. (1999) Rates of Dementia in Three Ethnoracial Groups. International Journal of Geriatric Psychiatry, 14, 481-493. >https://doi.org/10.1002/(sici)1099-1166(199906)14:6<481::aid-gps959>3.0.co;2-5

23. Potter, G.G., Plassman, B.L., Burke, J.R., Kabeto, M.U., Langa, K.M., Llewellyn, D.J., et al. (2009) Cognitive Performance and Informant Reports in the Diagnosis of Cognitive Impairment and Dementia in African Americans and Whites. Alzheimer’s&Dementia, 5, 445-453. >https://doi.org/10.1016/j.jalz.2009.04.1234

24. Reitan, R.M. (1958) Validity of the Trail Making Test as an Indicator of Organic Brain Damage. Perceptual and Motor Skills, 8, 271-276. >https://doi.org/10.2466/pms.1958.8.3.271

25. Manly, J.J., Jones, R.N., Langa, K.M., Ryan, L.H., Levine, D.A., McCammon, R., et al. (2022) Estimating the Prevalence of Dementia and Mild Cognitive Impairment in the US. The 2016 Health and Retirement Study Harmonized Cognitive Assessment Protocol Project. JAMA Neurology, 79, 1242-1249. >https://doi.org/10.1001/jamaneurol.2022.3543

26. Loewenstein, D.A., Curiel, R.E., Greig, M.T., Bauer, R.M., Rosado, M., Bowers, D., et al. (2016) A Novel Cognitive Stress Test for the Detection of Preclinical Alzheimer Disease: Discriminative Properties and Relation to Amyloid Load. The American Journal of Geriatric Psychiatry, 24, 804-813. >https://doi.org/10.1016/j.jagp.2016.02.056

27. Loewenstein, D.A., Curiel, R.E., DeKosky, S., Bauer, R.M., Rosselli, M., Guinjoan, S.M., et al. (2018) Utilizing Semantic Intrusions to Identify Amyloid Positivity in Mild Cognitive Impairment. Neurology, 91, e976-e984. >https://doi.org/10.1212/wnl.0000000000006128

28. Curiel, R.E., Loewenstein, D.A., Rosselli, M., Penate, A., Greig-Custo, M.T., Bauer, R.M., et al. (2018) Semantic Intrusions and Failure to Recover from Semantic Interference in Mild Cognitive Impairment: Relationship to Amyloid and Cortical Thickness. Current Alzheimer Research, 15, 848-855. >https://doi.org/10.2174/1567205015666180427122746

29. Kitaigorodsky, M., Curiel Cid, R.E., Crocco, E., Gorman, K.L., González-Jiménez, C.J., Greig-Custo, M., et al. (2021) Changes in LASSI-L Performance over Time among Older Adults with Amnestic MCI and Amyloid Positivity: A Preliminary Study. Journal of Psychiatric Research, 143, 98-105. >https://doi.org/10.1016/j.jpsychires.2021.08.033

30. American Psychiatric Association (2022) Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision (DSM-5-TR). American Psychiatric Association. >https://doi.org/10.1176/appi.books.9780890425787

31. Brandt, J. (1991) The Hopkins Verbal Learning Test: Development of a New Memory Test with Six Equivalent Forms. Clinical Neuropsychologist, 5, 125-142. >https://doi.org/10.1080/13854049108403297

32. Beekly, D.L., Ramos, E.M., Lee, W.W., Deitrich, W.D., Jacka, M.E., Wu, J., et al. (2007) The National Alzheimer’s Coordinating Center (NACC) Database: The Uniform Data Set. Alzheimer Disease&Associated Disorders, 21, 249-258. >https://doi.org/10.1097/wad.0b013e318142774e

33. Binetti, G., Magni, E., Cappa, S.F., Padovani, A., Bianchetti, A. and Trabucchi, M. (1995) Semantic Memory in Alzheimer’s Disease: An Analysis of Category Fluency. Journal of Clinical and Experimental Neuropsychology, 17, 82-89. >https://doi.org/10.1080/13803399508406584

34. Golden, C., Freshwater, S.M. and Golden, Z. (1978) Stroop Color and Word Test. >https://doi.org/10.1037/t06065-000

35. Reitan, R.M. (1958) Validity of the Trail Making Test as an Indicator of Organic Brain Damage. Perceptual and Motor Skills, 8, 271-276. >https://doi.org/10.2466/pms.1958.8.3.271

36. Asken, B.M., DeSimone, J.C., Wang, W., McFarland, K.N., Arias, F., Levy, S., et al. (2024) Plasma P‐Tau217 Concordance with Amyloid PET among Ethnically Diverse Older Adults. Alzheimer’s&Dementia: Diagnosis, Assessment&Disease Monitoring, 16, e12617. >https://doi.org/10.1002/dad2.12617

37. Crocco, E., Curiel, R.E., Acevedo, A., Czaja, S.J. and Loewenstein, D.A. (2014) An Evaluation of Deficits in Semantic Cueing and Proactive and Retroactive Interference as Early Features of Alzheimer’s Disease. The American Journal of Geriatric Psychiatry, 22, 889-897. >https://doi.org/10.1016/j.jagp.2013.01.066

38. Curiel, R.E., Crocco, E., Acevedo, A., Duara, R., Agron, J. and Loewenstein, D.A. (2013) A New Scale for the Evaluation of Proactive and Retroactive Interference in Mild Cognitive Impairment and Early Alzheimer’s Disease. Aging, 1, Article 1000102.

39. Matias-Guiu, J.A., Cabrera-Martín, M.N., Curiel, R.E., Valles-Salgado, M., Rognoni, T., Moreno-Ramos, T., et al. (2017) Comparison between FCSRT and LASSI-L to Detect Early Stage Alzheimer’s Disease. Journal of Alzheimer’s Disease, 61, 103-111. >https://doi.org/10.3233/jad-170604

40. Sánchez, S.M., Abulafia, C., Duarte-Abritta, B., de Guevara, M.S.L., Castro, M.N., Drucaroff, L., et al. (2017) Failure to Recover from Proactive Semantic Interference and Abnormal Limbic Connectivity in Asymptomatic, Middle-Aged Offspring of Patients with Late-Onset Alzheimer’s Disease. Journal of Alzheimer’s Disease, 60, 1183-1193. >https://doi.org/10.3233/jad-170491

41. Curiel Cid, R.E., Crocco, E.A., Duara, R., Garcia, J.M., Rosselli, M., DeKosky, S.T., et al. (2020) A Novel Method of Evaluating Semantic Intrusion Errors to Distinguish between Amyloid Positive and Negative Groups on the Alzheimer’s Disease Continuum. Journal of Psychiatric Research, 124, 131-136. >https://doi.org/10.1016/j.jpsychires.2020.02.008

42. Crocco, E.A., Curiel Cid, R., Kitaigorodsky, M., Grau, G.A., Garcia, J.M., Duara, R., et al. (2021) Intrusion Errors and Progression of Cognitive Deficits in Older Adults with Mild Cognitive Impairment and PreMCI States. Dementia and Geriatric Cognitive Disorders, 50, 135-142. >https://doi.org/10.1159/000512804