Differential associations of core and non-core plasma biomarkers with cognitive performance in Black adults

Abstract

Background

Black adults experience disproportionately higher rates of Alzheimer's disease and related dementias (ADRD), yet remain underrepresented in blood-based biomarker research. Understanding how plasma biomarkers relate to cognitive performance is essential for equitable detection and monitoring of ADRD.

Objective

We examined cross-sectional and longitudinal associations of both core and non-core plasma biomarkers and cognition in a community-based cohort of Black adults.

Methods

Participants from the ARCHES study completed baseline plasma biomarker assessments and neuropsychological testing, including a Preclinical Alzheimer Cognitive Composite (PACC) score and the Montreal Cognitive Assessment (MoCA). Plasma biomarkers reflecting amyloid, tau, neurodegeneration, and astrocytic activation were quantified using immunoprecipitation–mass spectrometry and ultrasensitive immunoassay platforms. Linear regression was used to evaluate cross-sectional associations between biomarkers and cognition. Linear mixed-effects models examined whether baseline biomarker levels were associated with cognitive change over one year, adjusting for age, sex, and education.

Results

The sample included 334 participants with a mean baseline age of 64.6 years (SD = 10.1; range, 45–92.9). Cross-sectionally, higher brain-derived phosphorylated tau₁₈₁ was associated with poorer MoCA score (p = 0.04), and neurofilament light chain (NfL) level was also associated with lower PACC score (p = 0.04). Longitudinally, higher baseline NfL and glial fibrillary acidic protein (GFAP) were associated with faster cognitive decline (p < 0.001 and p = 0.018).

Conclusions

Non-core NfL and GFAP biomarkers are associated with both cross-sectional and longitudinal cognitive performance. These findings highlight the importance of inclusive biomarker research and suggest non-core biomarkers may be particularly informative for characterizing cognitive aging and decline in this population.

Keywords

Alzheimer's disease amyloid-beta dementia GFAP neurodegeneration neurofilaments plasma racial disparities tau

Introduction

Black older adults are twice as likely to develop Alzheimer's disease and related dementia (ADRD) as their non-Hispanic White (nHWs) counterparts.^1,2 AD is biologically defined as a neurodegenerative disorder characterized by the accumulation of amyloid-β (Aβ) plaques, tau neurofibrillary tangles, and progressive brain atrophy.² Biomarkers are essential for detecting and monitoring AD progression, yet most biomarker studies have been conducted in predominantly nHW, highly educated samples.³ With the growing proportion of older adults from minoritized racial groups, improving diversity in biomarker research is critical for closing persistent gaps in healthcare access in AD detection and treatment.⁴

The A/T/N framework was developed to biologically stage AD using three biomarker categories: amyloid pathology (A), tau pathology (T), and neurodegeneration (N).⁵ Amyloid and tau biomarkers are considered the core indicators of AD and often begin to change 10–20 years before symptom onset. In contrast, markers of neurodegeneration, such as neurofilament light chain (NfL), and markers of astrocytic activation, such as glial fibrillary acidic protein (GFAP), are nonspecific indicators of neuronal injury and inflammation that tend to increase later in the disease course as downstream consequences of accumulating pathology.⁵ Sensitive and scalable biomarkers are essential for the early detection of AD, a need that has become increasingly urgent with recent advances in disease-modifying therapies.⁶ Positron emission tomography (PET) and cerebrospinal fluid (CSF) biomarkers are recognized as gold standards for detecting and staging AD and have been consistently associated with cognitive performance in cross-sectional studies and with the longitudinal risk of AD.² However, these approaches are invasive, costly, and difficult to implement at scale.⁷

The development of blood-based biomarkers has enabled minimally invasive and scalable quantification of AD–related pathology, including amyloid-β 1-42/amyloid-β 1-40 (Aβ_42/40) ratios, phosphorylated tau isoforms (ptau), and markers of axonal injury and neurodegeneration.² Systematic reviews indicate that plasma biomarkers such as pTau₂₁₇, pTau₁₈₁, total tau, Aβ_42/40, NfL, and GFAP have good diagnostic accuracy for distinguishing individuals with prodromal AD or mild cognitive impairment (MCI) from cognitively unimpaired controls and are associated with cognitive performance.^8–13 However, biomarker performance varies across assays, analytical platforms, and populations.¹⁴

The extant cadre of biomarker studies has included limited representation of minoritized populations, constraining inferences about ethnoracial differences.^2,12 Among the few studies examining diverse cohorts, differential plasma biomarker performance has been observed between nHW and Black individuals with MCI or AD.^15,16 In the Health and Aging Brain Study–Health Disparities (HABS-HD) cohort, plasma Aβ_42/40 and pTau₁₈₁ showed stronger and more consistent associations with PET pathology and clinical diagnosis in nHW participants, whereas in Black participants, Aβ_42/40 performed less reliably, and pTau₁₈₁ and NfL showed more consistent associations with dementia and neurodegeneration.¹⁷ Similarly, a study based on three longitudinal cohorts from the Rush Alzheimer's Disease Center found that associations between plasma biomarkers and cognitive decline were generally comparable across racial groups; however, higher pTau₂₁₇ levels were specifically associated with greater global and semantic memory decline among Black adults.¹⁰

The Aging Research Characterizing Health Exposome via Social drivers (ARCHES) was designed to increase the diversity of AD research by integrating plasma-based AD biomarkers with comprehensive neuropsychological assessments among Black participants residing in communities across the St Louis metropolitan area.¹⁸ In this study, we examine the cross-sectional and longitudinal associations between plasma biomarkers and cognitive performance among ARCHES participants. We hypothesize that participants with elevated A/T/N biomarker levels have lower cognitive performance and experience a faster decline in cognitive performance.

Methods

Participants

The ARCHES study is a prospective, community-engaged cohort designed to characterize cognitive aging among middle-aged and older Black adults living in the Greater St Louis region, spanning Missouri and Illinois. Individuals were eligible if they self-identified as Black or African American, were at least 45 years of age, and resided within the area. Participants were cognitively unimpaired at study entry, as determined by a telephone-administered Montreal Cognitive Assessment (MoCA)-BLIND score greater than 17, a threshold selected to account for lower average educational attainment related to historical structural and educational inequities that minoritized groups face.¹⁸ The study protocol received approval from the Washington University Human Research Protection Office, and written informed consent was obtained from all participants before any study procedures.¹⁸ By December 1, 2025, the cohort included 360 enrolled participants.

Cognitive performance

Cognitive performance was assessed using a Preclinical Alzheimer Cognitive Composite (PACC) score and the MoCA Version 8.3 English.^19–21 All assessments are conducted annually in person, primarily at the study office, and administered one-on-one by trained study coordinators in a quiet, private room following standardized testing protocols. Coordinators complete a rigorous, in-house training, supervised practice, and testing out before conducting visits independently. All coordinators administering the MoCA hold official MoCA certification. Basic accommodations are available for sensory limitations; participants are asked about hearing and vision impairments, where reading glasses and hearing aids are provided during testing if needed.

The PACC integrated function across multiple cognitive domains by averaging standardized scores from semantic fluency (animal naming),²² the free-recall component of the Free and Cued Selective Reminding Test,²⁰ and inverse-scored completion times from the Trail Making Tests A and B, thereby capturing memory, processing speed, and executive function.²³ Scores at both baseline and follow-up were standardized using the baseline mean and standard deviation for each component measure. This approach preserves a common metric across waves and minimizes bias in longitudinal comparisons arising from differential attrition or changes in sample composition over time.⁸ The MoCA assesses attention, language, visuospatial skills, memory, and executive function. In the present analyses, both PACC and MoCA scores were modeled as continuous indicators of cognitive performance.²¹

Plasma A/T/N biomarkers

At baseline study visits, 60 milliliters of blood was collected by a trained and certified phlebotomist using standard clinical venipuncture protocols to ensure participant comfort and sample integrity. Following plasma collection, the tubes were placed on wet ice for approximately 30 min before laboratory processing. Plasma was separated by spinning EDTA tubes at 2000 g for 10 min at 4°C, with any samples showing evidence of hemolysis excluded from further analysis. The resulting plasma aliquots, along with buffy coat fractions, were initially stored at −20°C and later transferred to long-term storage at −80°C.²⁴

Plasma aliquots (2.5 mL each) were sent to two external laboratories for biomarker quantification: C₂N Diagnostics for immunoprecipitation–mass spectrometry (IP-MS) analysis and Alamar Biosciences for measurement using the NULISA™ (Nanoparticle-Enhanced Ultrasensitive Immunoassay) platform. The C₂N IP-MS assay isolates amyloid-β peptides via immunoprecipitation followed by high-resolution mass spectrometric detection, providing highly accurate quantification of Aβ₄₂, Aβ₄₀, and the Aβ_42/40 ratio.²⁴ In contrast, the NULISA platform utilizes magnetic nanoparticle–based capture in conjunction with DNA-barcoded detection antibodies, enabling digital, ultrasensitive quantification of low-abundance plasma proteins.^25,26 Both platforms measured Aβ₄₂, Aβ₄₀, pTau₁₈₁, and pTau₂₁₇; however, NULISA additionally quantified brain-derived (BD) pTau₁₈₁, pTau₂₁₇, and total tau, as well as NfL and GFAP. BD tau refers to tau isoforms and fragments originating predominantly from neuronal tissue that enter peripheral circulation following axonal injury or neurodegeneration.^25,26

Individual plasma biomarker levels (Aβ₄₂, Aβ₄₀, pTau₁₈₁, pTau₂₁₇, BD-pTau₁₈₁, BD-pTau₂₁₇, NfL, and GFAP), as well as plasma biomarker ratios (Aβ₄₂/Aβ₄₀, pTau₁₈₁/npTau₁₈₁, pTau₂₁₇/npTau₂₁₇), were standardized (z-score transferred) and included as continuous explanatory variables.²⁴ In this study, we analyzed the A/T/N biomarkers available from each platform to provide a comprehensive characterization of plasma biomarker and cognition associations; direct cross-platform comparison or formal evaluation of relative assay performance was not an objective.

Data analyses

Cross-sectional associations between cognitive performance, as measured by the PACC and MoCA, and plasma A/T/N biomarker concentrations and ratios were evaluated using linear regression models. All cross-sectional analyses were implemented in R (version 4.5.2) using the stats package.²⁷

To examine longitudinal associations, linear mixed-effects (LME) models with random intercepts accounted for within-person repeated measurements over time. Baseline biomarker levels and ratios were entered separately into each model as continuous predictors, and study wave (Wave 1; Wave 2) was included as a categorical time variable. We included biomarker × wave interaction terms to test whether baseline biomarker levels were associated with differential change in cognitive performance across waves. LME models were conducted using the lme4 package.²⁸ To address potential attrition bias, we conducted a sensitivity analysis using inverse probability weighting (IPW). Stabilized weights were generated based on baseline age, sex, and education level. Overall, 18 cross-sectional linear regression models and 18 longitudinal LME models were performed. Benjamini–Hochberg false discovery rate correction was applied to the cross-sectional and longitudinal tests to adjust for multiple comparisons.

All the models adjusted for sex, baseline age, and education level. APOE ε4 status was not included as a covariate because prior studies have reported that the association between APOE ε4 and AD risk is weaker and less consistent among Black populations than non-Hispanic Whites. Additionally, APOE genotype is also highly associated with AD biomarkers, particularly amyloid measures, which may introduce overadjustment when modeling biomarker–cognition associations.^29,30

Results

Of the 360 currently enrolled, 334 (80 men, 254 women) had plasma biomarkers analyzed. Women were slightly older than men (mean age 65.3 ± 10.1 versus 62.2 ± 9.69 years, p = 0.014) and had higher educational attainment (15.3 ± 2.67 versus 13.6 ± 2.41 years, p < 0.001). Most participants were generally healthy, yet resided in marginalized communities within the Greater St Louis area, as indicated by a low Charlson Comorbidity Index (mean 0.2 ± 0.5) and high Area Deprivation Index national rank (mean 74.8 ± 22.2). Women demonstrated significantly higher PACC scores than men (mean 0.09 ± 0.67 versus −0.20 ± 0.78, p = 0.004). There was no statistical difference in the MoCA score.

For plasma biomarkers measured by C₂N (n = 332), Aβ_42/40 was missing for 2 participants, pTau₁₈₁ for 22 participants, and pTau₂₁₇ for 20 participants, primarily due to technical issues, such as undetectable tau levels. No sex differences were observed for the Aβ_42/40 and percentage of pTau₂₁₇ over non-pTau₂₁₇ (% pTau₂₁₇). Men exhibited significantly higher pTau₁₈₁ ratios compared with women (24.9 ± 8.69 versus 21.0 ± 6.38, p < 0.001). Alamar Aβ_42/40 brain-derived (BD) tau biomarkers (pTau₁₈₁, pTau₂₁₇, total tau) and GFAP showed no significant sex differences. Women had significantly higher plasma NfL levels than men (773 ± 737 versus 622 ± 315, p = 0.010) (Table 1).

Table 1.

Participant demographics.

	Men (N = 80)		Women (N = 254)		p
	Mean (SD)	Median [Min, Max]	Mean (SD)	Median [Min, Max]	p
Age (years)	62.2 (9.69)	62.6 [45.0, 85.8]	65.3 (10.1)	66.3 [45.0, 92.9]	0.014
Education (years)	13.6 (2.41)	13.0 [8.00, 21.0]	15.3 (2.67)	16.0 [8.00, 29.0]	<0.001
Charlson Comorbidity Index	0.24 (0.60)	0 [0, 2.00]	0.138 (0.511)	0 [0, 5.00]	0.183
Area Deprivation Index	76.1 (21.7)	82.0 [27.0, 100]	74.4 (22.4)	80.0 [10.0, 100]	0.526
PACC	−0.20 (0.79)	−0.10 [−2.71, 1.20]	0.09 (0.67)	0.10 [−2.11, 1.59]	0.004
Change of PACC (N = 272)	−0.36 (3.19)	0.259 [−10.8, 4.97]	0.68 (2.24)	0.65 [−7.35, 6.09]	0.0256
MoCA	23.7 (3.74)	24.0 [12.0, 30.0]	24.5 (3.26)	25.0 [10.0, 30.0]	0.095
Change of MoCA	0.18 (3.03)	0 [−7.00, 8.00]	−0.028 (2.52)	0 [−9.00, 7.00]	0.637
C₂N: Aβ₄₂ /Aβ₄₀ (N = 332)	0.10 (0.02)	0.10 [0.08, 0.19]	0.105 (0.0159)	0.10 [0.06, 0.20]	0.635
C₂N: pTau₁₈₁ ratio (N = 312)	24.9 (8.69)	24.7 [1.79, 50.3]	21.0 (6.28)	20.5 [5.85, 45.6]	<0.001
C₂N: pTau₂₁₇ ratio (N = 314)	2.42 (2.46)	1.54 [0.72, 15.9]	1.91 (1.53)	1.43 [0.33, 15.6]	0.095
Alamar: Aβ₄₂ /Aβ₄₀	8.11 (2.43)	8.11 [2.75, 14.8]	8.70 (11.5)	7.62 [1.41, 185]	0.445
Alamar: BD pTau₁₈₁	377 (227)	315 [130, 1750]	417 (401)	317 [89.0, 3680]	0.27
Alamar: BD pTau₂₁₇	300 (134)	276 [139, 1110]	315 (192)	266 [107, 1810]	0.444
Alamar: BD total Tau	568 (185)	499 [286, 992]	575 (284)	495 [221, 3180]	0.789
Alamar: NfL	622 (315)	534 [230, 2050]	773 (737)	560 [138, 6180]	0.010
Alamar: GFAP	407 (501)	333 [103, 4390]	496 (299)	424 [94.0, 2360]	0.133

PACC: Preclinical Alzheimer's Cognitive Composite; MoCA: Montreal Cognitive Assessment; BD: Brain Derived.

A second wave of cognitive functioning data was available from 272 (81.43%) participants. Participants with follow-up data had a higher proportion of women, significantly more years of education, and higher cognitive performance as measured by both PACC and MoCA, but showed no significant differences in biomarker levels compared with those lost to follow-up (Supplemental Table 1).

Correlations among biomarkers measured by the C₂N and Alamar platforms are presented in Figure 1 . The correlation between C₂N- and Alamar-measured Aβ_42/40 was weak (r = 0.089). Correlations between C₂N pTau ratios and Alamar brain-derived (BD) pTau levels were moderate to strong (r = 0.80–0.95). Within the C₂N platform, correlations between Aβ_42/40 and pTau ratios were weak. In contrast, within the Alamar platform, correlations among A/T/N biomarkers ranged from moderate to strong (r = 0.27–0.93).

Cross-sectionally, after controlling for age, sex, and education, significant associations were observed between plasma biomarkers measured on the Alamar platform and cognitive performance. A 1-SD increase in BD pTau₁₈₁ was associated with −0.50 (95% CI: −0.83 to −0.16) points lower MoCA score, respectively, and a 1-SD increase in NfL was associated with a −0.10-point lower PACC score (95% CI: −0.17 to −0.03) (Table 2).

Table 2.

Cross-sectional associations between plasma biomarkers and cognitive performance.

Biomarkers (standardized [z-scored])	MoCA	PACC
C2N
Aβ₄₂ /Aβ₄₀ (N = 332)	0.19 (−0.15–0.54)	−0.01 (−0.08–0.05)
C2N: pTau181 ratio (N = 312)	0.28 (−0.08–0.64)	0.05 (−0.03–0.12)
pTau₂₁₇ ratio (N = 314)	−0.29 (−0.66–0.07)	0.01 (−0.06–0.08)
Alamar (N = 334)
Aβ₄₂ /Aβ₄₀	0.28 (−0.06–0.61)	0.06 (−0.00–0.13)
Brain Derived (BD) pTau ₁₈₁	−0.50^** (−0.83 – −0.16)	−0.04 (−0.11–0.03)
BD pTau ₂₁₇	−0.45 (−0.79 – −0.10)	−0.03 (−0.10–0.04)
BD total Tau	−0.03 (−0.37–0.31)	−0.00 (−0.07–0.06)
NfL	−0.41 (−0.75 – −0.07)	−0.10^** (−0.17 – −0.03)
GFAP	−0.14 (−0.51–0.23)	0.01 (−0.06–0.09)

*p < 0.05 **p < 0.01 ***p < 0.001. P values were adjusted for multiple testing using the Benjamini–Hochberg false discovery rate (FDR) procedure across 18 cross-sectional tests. Models controlled for sex, age, and education.

Longitudinally, after controlling for age, sex, and education, baseline C₂N Aβ_42/40 was significantly positively associated with PACC scores, whereas baseline Alamar NfL and GFAP were significantly negatively associated with PACC scores (Figure 2). A 1-SD increase in NfL and GFAP was associated with −0.55-point (95% CI: −0.80 to −0.29) and −0.50-point (95% CI: −0.82 to −0.18) decreases in PACC score, respectively (Supplemental Table 2). After applying IPW, the associations remained statistically significant (Supplemental Table 21–23).

Discussion

This study is one of the first to examine associations between plasma biomarkers and cognitive performance in an exclusively Black cohort. This study identified significant associations between plasma biomarkers and cognitive performance among Black participants and observed differential associations across biomarker analytes.

We observed significant cross-sectional associations between plasma biomarkers measured on the Alamar platform with cognitive performance, revealing distinct patterns across core AD biomarkers and non-core markers of neurodegeneration. A higher plasma BD pTau₁₈₁ level was associated with worse cognitive performance, as measured by the MoCA. These findings align with a growing body of evidence demonstrating stronger and more consistent associations between plasma pTau biomarkers and cognitive impairment than with Aβ_42/40 across racial groups.³¹ Plasma pTau₁₈₁ appears to be more tightly coupled to neurodegeneration and the clinical expression of AD, as tau phosphorylation and tangle formation occur more closely in time to synaptic dysfunction and neuronal loss.³¹ In contrast, plasma Aβ_42/40 primarily reflects early amyloid deposition, which may precede overt cognitive decline by many years and therefore be less informative cross-sectionally once cognitive decline is present.⁵

Among the non-core biomarkers, plasma NfL was significantly associated with cognitive performance both cross-sectionally and longitudinally, whereas GFAP showed a significant longitudinal association with PACC. Biologically, plasma NfL is a structural component of large, myelinated axons that is released into circulation following neuroaxonal injury and reflects nonspecific neuronal damage arising from both central and peripheral nervous system, whereas GFAP reflects astrocytic activation and astrogliosis, indexing neuroinflammatory processes that may occur early in AD pathophysiology.^31,32 In our study, both NfL and GFAP were more consistently associated with cognitive performance within this cohort. One plausible explanation is the higher burden of mixed dementia pathology among Black adults. Autopsy findings from the Rush Alzheimer's Disease Clinical Core found that Black decedents are less likely than White decedents to exhibit AD pathology as the main etiology and were more likely to display mixed dementia.³³ Consistent with these neuropathological observations, biomarker evidence from the HABS-HD and the Study of Race to Understand Alzheimer Biomarker further demonstrated a lower prevalence of amyloid PET positivity among Black participants compared to nHWs.³⁴

The associations between non-core biomarkers and cognitive decline also highlight the role of structural and social risk determinants of health. Plasma NfL and GFAP have been linked to cardiovascular disease and related conditions, including traumatic brain injury, seizures, cardiac disease, hypertension, hypercholesterolemia, and diabetes—conditions that are disproportionately prevalent among Black populations.³⁵ Among our samples, even though participants had a minimal comorbidity index, 66.7% of participants had hypertension, while 48.7% had hypercholesterolemia. Vascular risk factors may represent biological pathways linking systemic health to neurodegeneration-related biomarkers; these variables were not included as covariates in the primary models to avoid potential overadjustment or multicollinearity when examining biomarker–cognition associations. Future studies using mediation or structural equation modeling approaches may better disentangle the complex relationships among vascular health, plasma biomarkers, and cognitive decline.

Beyond biomedical risk, chronic exposure to discrimination, particularly institutionalized discrimination, represents a cumulative stressor. Previous studies found that discrimination is a significant contributor to cognitive decline, especially among Black men,^36,37 and other studies have reported associations between experiences of discrimination and elevated levels of NfL and GFAP.³² Although prior research has generally not identified consistent sex differences in plasma AD biomarkers, gender-related social exposures may influence both cognitive outcomes and biomarker profiles.³⁸ In our cohort, men exhibited lower baseline cognitive performance and higher levels of pTau₁₈₁, NfL, and GFAP, suggesting that the combined effects of social stressors, health disparities, and structural inequities may contribute to biomarker elevations and cognitive vulnerability among Black men.^39,40

Biomarkers in this study were derived from two different analytical platforms and yielded distinct patterns of association with cognitive outcomes. Cross-platform comparison was not an explicit aim of this study; however, the observed differences may reflect assay-specific analytical characteristics, biomarker targets, or cohort-specific factors rather than inherent differences in assay performance or sensitivity. C₂N-measured Aβ_42/40 and pTau₁₈₁ and pTau₂₁₇ ratios are primarily designed to reflect AD pathological status, rather than downstream cognitive consequences, especially in samples without advanced tau burden.⁴¹ In contrast, the Alamar NULISA platform is optimized for multibiomarker phenotyping, which may be more sensitive to capturing heterogeneity in biomarker profiles across disease stages and population subgroups.⁴² To date, few studies have systematically evaluated the validity or performance of plasma biomarker assays across different ethnoracial groups. The differential findings observed here may therefore reflect both biological heterogeneity and gaps in existing validation efforts, further highlighting the critical need to increase diversity and inclusion in biomarker research to ensure equitable and generalizable applications of blood-based biomarkers.

This study examined associations between A/T/N plasma biomarkers and cognitive change among Black participants, contributing to efforts to increase diversity in biomarker research. Several limitations should be noted. The modest sample size and relatively short follow-up duration may have influenced the results through potential practice effects and limited sensitivity for detecting clinically meaningful cognitive change. Differential attrition between baseline and follow-up may have introduced potential bias in the longitudinal analyses. In addition, women comprised approximately three-quarters of the analytic cohort, which may influence generalizability. In our sample, men were younger, had fewer years of education, and had lower baseline PACC scores than women. Although sex-stratified analyses suggested some differences in biomarker–cognition associations, the smaller number of male participants limited statistical power and precluded firm conclusions regarding sex-specific effects; thus, the analyses and results are not included in the main text (Supplemental Table 9–20). Future studies with larger and more balanced samples will be essential to clarify potential sex-related differences in plasma biomarker performance among Black adults. Despite these limitations, the observed biomarker–cognition associations underscore the importance of inclusive research to ensure accurate characterization of disease processes and equitable advances in AD detection and monitoring.

Supplemental Material

sj-docx-1-alz-10.1177_13872877261450646 - Supplemental material for Differential associations of core and non-core plasma biomarkers with cognitive performance in Black adults

Supplemental material, sj-docx-1-alz-10.1177_13872877261450646 for Differential associations of core and non-core plasma biomarkers with cognitive performance in Black adults by Yiqi Zhu, Jean-François Trani, Alexis I.B. Walker, Semere Bekena, Ramkrishna K. Singh and Ganesh M. Babulal in Journal of Alzheimer's Disease

Footnotes

Acknowledgements

We would like to thank the respondents for sharing their voices, lived experiences, and time in this research, and the staff members of ARCHES for their support in completing the data collection.

ORCID iDs

Yiqi Zhu

Jean-François Trani

Alexis I.B. Walker

Semere Bekena

Ramkrishna K. Singh

Ganesh M. Babulal

Ethical considerations

The study protocol was approved by the Washington University Human Research Protection Office.

Consent to participate

All human subjects provided informed consent.

Consent for publication

Not applicable.

Author contribution(s)

Yiqi Zhu: Conceptualization; Formal analysis; Investigation; Methodology; Visualization; Writing – original draft.

Jean-François Trani: Conceptualization; Writing – review & editing.

Alexis I.B. Walker: Data curation; Project administration; Supervision; Writing – review & editing.

Semere Bekena: Data curation; Writing – review & editing.

Ramkrishna K. Singh: Data curation; Writing – review & editing.

Ganesh M. Babulal: Conceptualization; Data curation; Funding acquisition; Investigation; Methodology; Project administration; Supervision; Writing – review & editing.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: National Institutes of Health (NIH); National Institute on Aging (NIH/NIA), Grant/Award Number: R01AG074302; Alzheimer's Association, Grant/Award Number: SG-22-968620-ARCHES.

Declaration of conflicting interests

The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Semere Bekena and Ganesh Babulal are Editorial Board Members of this journal but were not involved in the peer-review process of this article nor had access to any information regarding its peer-review.

Data availability statement

De-identified data from the ARCHES cohort may be made available upon reasonable request to the corresponding author, subject to institutional approvals and data use agreements. All requests must comply with participant consent and ethical guidelines to protect participant privacy.

Supplemental material

Supplemental material for this article is available online.

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