Abstract
INTRODUCTION
Consistent predictive performance across racial and ethnic groups is essential to the use of plasma biomarkers as screening tools in preclinical Alzheimer's disease trials.
METHODS
Logistic regression examined racial and ethnic group differences in plasma eligibility using an algorithm that included Phosphorylated tau217 to non‐phosphorylated tau217 ratio, amyloid beta 42/40, age, and apolipoprotein E to predict > 18 Centiloids on amyloid imaging in cognitively unimpaired individuals.
RESULTS
Among 6437 participants screened, with non‐Hispanic (NH) White as the reference group, odds ratios of plasma ineligibility were 2.88 (95% confidence interval [CI]: 1.40–6.96) for Hispanic Black, 1.60 (95% CI: 1.33–1.92) for Hispanic White, 2.10 (95% CI: 1.37–3.38) for NH Asian, and 1.59 (95% CI: 1.27–2.0) for NH Black participants. Positron emission tomography (PET) eligibility rates did not differ among those who were plasma eligible.
DISCUSSION
Differential rates of plasma eligibility, but consistent PET eligibility among plasma‐eligible participants, were observed, supporting the use of universal biomarker cutpoints across race and ethnic groups.
Highlights
Underrepresented racial and ethnic groups had lower rates of plasma eligibility compared to non‐Hispanic White individuals based on a plasma screening algorithm that included the phosphorylated tau 217 ratio.
Among plasma‐eligible participants, amyloid positron emission tomography eligibility rates did not differ by racial and ethnic group.
Plasma biomarker tests may provide equivalent effectiveness for identifying imaging biomarker eligible, cognitively unimpaired individuals across racial and ethnic groups.
Keywords: amyloid biomarkers, ethnicity, plasma biomarkers, predictive cutpoints, race, trial eligibility, underrepresented
1. INTRODUCTION
In many Alzheimer's disease (AD) clinical trials, individuals from some racial and ethnic backgrounds are severely underrepresented. This underrepresentation poses critical challenges to addressing the public health needs of an aging population, especially given the disproportionate risk of dementia among individuals from Black or African American and Hispanic or Latino communities. 1 , 2 , 3 , 4 Differential eligibility based on trial inclusion and exclusion criteria may contribute to underrepresentation of some groups. 5 For instance, lower rates of amyloid eligibility have been observed on positron emission tomography (PET) and cerebrospinal fluid (CSF) markers among underrepresented groups screening for recent trials of amyloid‐lowering therapies. 5 , 6 , 7 , 8
Plasma biomarkers can serve as accurate predictors of more established biomarkers such as amyloid PET 9 , 10 , 11 and have emerged as critical tools to accelerate screening in preclinical AD trials. Their use reduces cost, saves time, and reduces burden on clinical trial sites and participants. The minimal invasiveness of blood tests may also facilitate willingness to screen for trials among groups historically underrepresented in AD trials. In the AHEAD Study, a preclinical AD study testing lecanemab in cognitively unimpaired adults with evidence of intermediate and elevated amyloid on PET, plasma screening was initially introduced using an algorithm that included the ratio of amyloid beta (Aβ) 42 to 40 (Aβ42/40), age, and apolipoprotein E (apoE). 12 Previously, we reported differences in eligibility rates by race and ethnicity among individuals screened for the AHEAD Study using a study‐specific algorithm based on a model of amyloid PET that included predictors Aβ42/40, age and apoE proteotype. Individuals identifying as Hispanic Black, Hispanic White, non‐Hispanic (NH) Asian, and NH Black were 2 to 4 times less likely to be plasma eligible compared to NH Whites. PET eligibility rates among individuals who were plasma eligible did not differ by group. 12 Phosphorylated tau217 to non‐phosphorylated tau217 ratio (p‐tau217r) was subsequently included in the model based on new evidence of increased sensitivity and specificity. 13 , 14 Here, we build on our previous findings and report eligibility rates by race and ethnicity of individuals screened using the model that included p‐tau217r, Aβ42/40, age, and apoE.
2. METHODS
2.1. The AHEAD 3‐45 study
The AHEAD 3‐45 Study is a public–private partnership between the Alzheimer's Clinical Trials Consortium (ACTC) and Eisai Inc., funded by the National Institute on Aging (NIA), Eisai Inc., the Alzheimer's Association, GHR Foundation, and other philanthropic donors. This ongoing multi‐center, double‐blind, placebo‐controlled clinical trials program is designed to assess the safety and efficacy of lecanemab in preclinical AD. 15 The study, comprising two sister trials with a common screening process, recently completed randomization, enrolling participants without cognitive impairment but with biomarker evidence of AD. The “A3” study enrolled cognitively unimpaired participants with intermediate brain amyloid levels; the “A45” study enrolled cognitively unimpaired participants with elevated brain amyloid. The screening process for the study has been delineated in detail elsewhere. 12 , 15 Briefly, it included two main stages. Stage 1 included plasma biomarker testing at screening visit 1a (ScV1a) and subsequent cognitive and functional evaluations at screening visit 1b (ScV1b). During Stage 2, Stage 1–eligible participants underwent amyloid PET scan at screening visits 2 and 3. Participants with intermediate or elevated brain amyloid were eligible for randomization in the A3 and A45 trials, respectively.
RESEARCH IN CONTEXT
Systematic review: We reviewed the literature using traditional sources (e.g., PubMed), meeting abstracts, and presentations. Some racial and ethnic groups are underrepresented in Alzheimer's disease (AD) trials. We evaluate eligibility rates based on a model that predicted amyloid positron emission tomography (PET) Centiloid based on plasma measures including predictors phosphorylated tau 217 ratio, amyloid beta 42/40, age, and apolipoprotein E proteotype, and subsequent PET eligibility in the AHEAD 3‐45 preclinical AD program.
Interpretation: In this sample of cognitively unimpaired individuals, underrepresented racial and ethnic groups were less likely to meet the plasma prediction cutpoint, but among those meeting the plasma prediction cutpoint PET eligibility did not differ by group.
Future directions: Larger scale screening approaches should be considered in future trials to ensure inclusive trial cohorts. Future studies should examine underlying reasons for lower biomarker eligibility in racially and ethnically underrepresented groups, including differences in amyloid prevalence and other contributors to dementia risk.
2.2. Study sample
Interested, cognitively unimpaired participants aged 55 to 80 with an available study partner were screened at 75 North American clinical study sites. The study used a variety of methods to facilitate the recruitment of historically underrepresented groups. More detailed discussions of these efforts are forthcoming in separate articles.
In the AHEAD Study, participants’ self‐reported race was captured as “American Indian or Alaskan Native,” “Asian,” “Black” or “African American,” “Hawaiian or other Pacific Islander,” “White,” “Other,” “More than One Race,” “Unknown,” or “Not Reported.” Ethnicity was captured as “Hispanic or Latino,” “non‐Hispanic or Latino,” “Unknown,” or “Not Reported”.
2.3. Biomarker eligibility
Plasma assays were used to measure p‐tau217r, Aβ42/40, and apoE proteotype using liquid chromatography tandem mass spectrometry performed by C2N Diagnostics. 16 , 17 , 18 , 19 , 20 Participants were screened using a pre‐specified, study‐specific algorithm based on a model that used plasma to predict amyloid PET burden and included predictors p‐tau217r, Aβ42/40, age, and apoE proteotype. Individuals who met the cutpoint of > 18 Centiloids (CL) were considered “plasma eligible” and could proceed to cognitive and clinical testing at the second screening visit (ScV1b). Eligibility for clinical and cognitive criteria at ScV1b were as follows: Global Clinical Dementia Rating (CDR) score of 0, Mini‐Mental State Examination (MMSE) of ≥ 27 (with educational adjustments: 6 , 21 specifically, ≤ 12 years of education, MMSE ≥ 25; 13–15 years of education, MMSE ≥ 26; ≥ 16 years of education, MMSE ≥ 27), and Wechsler Memory Scale‐Revised Logical Memory Subscale II (WMSR‐LMS II) score of ≥ 6 at the time of screening as described by Rafii et al. 15 Participants eligible at ScV1b underwent PET imaging in Stage 2 with [18F] NAV4694 for detecting cerebral amyloid (ScV2/3). Those within 20 to 40 CL were eligible for randomization to A3 and those > 40 CL were eligible for randomization to A45 pending safety magnetic resonance imaging (MRI) eligibility.
2.4. Statistical analysis
For these analyses, all participants screened between May 2023 and March 2024, in North America, with plasma results at ScV1a determined based on the algorithm comprised of p‐tau217r, Aβ42/40, age, and apoE were included (Figure 1). Race and ethnicity were combined to derive a single variable (race and ethnicity) that included five mutually exclusive categories: Hispanic Black, Hispanic White, NH Asian, NH Black, NH White. Participants who identified as “More than one Race” (N = 86), “Other Race” (N = 83), “American Indian or Alaskan Native” (N = 22), “Native Hawaiian or other Pacific Islander” (N = 8), missing (N = 35), or unknown race and ethnicity (N = 2) were not included in the analysis (n = 236) given the small numbers of those participants in each group. All groups, except NH White participants, were considered members of underrepresented racial and ethnic groups. Participants who were approved to move forward from ScV1a to ScV1b through manual overrides by the Coordinating Center, due to prior knowledge of amyloid status from results acquired outside the AHEAD Study screening process (n = 12), were not included in the analysis (Figure 1).
FIGURE 1.
Consort diagram of the consented participants included in this analysis who underwent plasma screening between May 2023 and March 2024 using a model that predicted amyloid PET CL using plasma including predictors p‐tau217r, Aβ42/40, age, and apoE proteotype to identify individuals above > 18 CL on NAV4694 amyloid PET imaging. Aβ, amyloid beta; apoE, apolipoprotein E; CL, Centiloids; PET, positron emission tomography; p‐tau217r, phosphorylated tau217 to non‐phosphorylated tau217 ratio.
We summarized participant characteristics across the groups using means and standard deviations for continuous variables and using counts and percentages for categorical variables. To compare the effect of race and ethnicity on plasma eligibility, we used logistic regression analyses to model ineligibility rates. Due to small sample sizes, we used Fisher exact test to compare eligibility on amyloid PET. Results are reported using odds ratios (ORs) and corresponding 95% confidence intervals (CIs). Moreover, given previous reports of differential apoE4 carrier risk of AD across racial and ethnic groups, 22 we evaluated p‐tau217r by apoE4 carrier status across groups. All statistical analyses were performed in R version 4.2.0.
3. RESULTS
Enrollment for the AHEAD Study concluded in October 2024. Sox thousand six hundred eighty‐five participants consented in North America underwent plasma screening using a study‐specific algorithm based on a model that predicted amyloid PET including predictors p‐tau217r, Aβ42/40, age, and apoE proteotype. Demographic characteristics of the 6437 individuals included in this analysis are reported in Table 1. The average age of the cohort was 68.2 (± 6.3) years, 35.3% of individuals were apoE4 carriers, and 66.4% were female. The self‐reported racial and ethnic makeup of the sample included: 155 (2.4%) participants who were NH Asian, 62 (1%) who were Hispanic Black, 511 (7.9%) who were NH Black, 877 (13.6%) who were Hispanic White, and 4832 (75%) who were NH White. Though age and residential status were similar, the groups differed on several important demographics. Years of education were highest among NH Asian followed by NH White, NH Black, Hispanic White, and lowest among Hispanic Black groups. The NH Black and Hispanic Black participant groups had higher proportions of females (75.3% and 72.6%, respectively) than the other groups. The proportion of apoE4 carriers differed significantly across groups (P ≤ 0.01). Participants identifying as NH Black (38.6%) and NH White (37.5%) demonstrated the highest proportions of apoE4 carriage, followed by participants identifying as Hispanic Black (27.4%) and Hispanic White (24.3%). NH Asian participants had the lowest proportion of apoE4 carriers (21.3%). The proportion of married individuals varied significantly across groups (P < 0.01). More NH White and NH Asian participants were married than the other groups. We detected a significant difference in Hollingshead scores across racial and ethnic groups (P < 0.01). Although most participants had scores reflecting upper‐middle socioeconomic status, individuals who identified as Hispanic Black had a greater proportion of scores reflective of lower socioeconomic status (46.8%).
TABLE 1.
Demographic characteristics of participants who underwent plasma screening using p‐tau217r in the plasma algorithm across race and ethnicity.
| Hispanic Black (n = 62) | Hispanic White (n = 877) | NH Asian (n = 155) | NH Black (n = 511) | NH White (N = 4832) | Total (N = 6437) | |
|---|---|---|---|---|---|---|
| Age (years) | ||||||
| Mean (SD) | 67.5 (6.3) | 68.2 (6.2) | 68.2 (6.3) | 68.8 (5.8) | 68.1 (6.4) | 68.2 (6.3) |
| Sex (%) | ||||||
| Female | 45 (72.6) | 604 (68.9) | 82 (52.9) | 385 (75.3) | 3155 (65.3) | 4271 (66.4) |
| ApoE4 (%) | ||||||
| Carrier | 17 (27.4) | 213 (24.3) | 33 (21.3) | 197 (38.6) | 1814 (37.5) | 2274 (35.3) |
| Non‐carrier | 45 (72.6) | 664 (75.7) | 122 (78.7) | 314 (61.4) | 3017 (62.5) | 4162 (64.7) |
| Education (years) | ||||||
| Mean (SD) | 12.27 (3.12) | 14.07 (3.51) | 17.25 (3.02) | 15.42 (2.94) | 16.46 (2.75) | 16.03 (3.03) |
| Hollingshead (%) | ||||||
| 11–17 | 7 (11.3) | 120 (13.7) | 47 (31.1) | 74 (14.5) | 1096 (22.8) | 1344 (20.9) |
| 18–31 | 6 (9.7) | 220 (25.1) | 66 (43.7) | 206 (40.5) | 2309 (47.9) | 2807 (43.8) |
| 32–47 | 8 (12.9) | 189 (21.6) | 25 (16.6) | 118 (23.2) | 905 (18.8) | 1245 (19.4) |
| 48–62 | 12 (19.4) | 170 (19.4) | 12 (7.9) | 87 (17.1) | 426 (8.8) | 707 (11.0) |
| 63–77 | 29 (46.8) | 178 (20.3) | 1 (0.7) | 24 (4.7) | 81 (1.7) | 313 (4.9) |
| Marital status (%) | ||||||
| Married | 17 (27.4) | 394 (44.9) | 108 (69.7) | 233 (45.6) | 3254 (67.3) | 4006 (62.2) |
| Divorced | 29 (46.8) | 291 (33.2) | 28 (18.1) | 131 (25.6) | 797 (16.5) | 1276 (19.8) |
| Single | 10 (16.1) | 69 (7.9) | 5 (3.2) | 71 (13.9) | 283 (5.9) | 438 (6.8) |
| Widowed | 5 (8.1) | 115 (13.1) | 10 (6.5) | 63 (12.3) | 411 (8.5) | 604 (9.4) |
| Other | 1 (1.6) | 8 (0.9) | 4 (2.6) | 13 (2.5) | 87 (1.8) | 113 (1.8) |
| Residence (%) | ||||||
| Assisted | 0 (0.0) | 1 (0.1) | 0 (0.0) | 0 (0.0) | 1 (0.0) | 2 (0.0) |
| Independent | 36 (94.7) | 659 (97.6) | 142 (99.3) | 466 (96.9) | 4621 (98.8) | 5924 (98.5) |
| Senior | 2 (5.3) | 14 (2.1) | 1 (0.7) | 12 (2.5) | 47 (1.0) | 76 (1.3) |
| Other | 0 (0.0) | 1 (0.1) | 0 (0.0) | 3 (0.6) | 10 (0.2) | 14 (0.2) |
Note: Race and ethnic categories are mutually exclusive derived categories based on participant self‐reported race and ethnicity. Discrepancies in number may be attributed to missing data.
Abbreviations: ApoE4, apolipoprotein E4; H, Hispanic; NH, non‐Hispanic; p‐tau217r, phosphorylated tau217 to non‐phosphorylated tau217 ratio SD, standard deviation.
We examined levels of p‐tau217r by race and ethnicity and by apoE4 carrier status. A significant effect of race and ethnicity on p‐tau217r was observed in both carriers (P < 0.01) and non‐carriers (P < 0.01), with highest ratios observed among NH White carriers (Figure 2; Table S1 in supporting information). Based on the plasma screening algorithm, 4750 participants did not meet the predicted amyloid PET cutpoint of 18 CL and were “plasma ineligible.” Rates of plasma ineligibility differed by group (Figure 3, P < 0.01). Participants from underrepresented racial and ethnic groups had higher rates of plasma ineligibility compared to the NH White group. In logistic regression models, participants self‐identifying as Hispanic Black (OR = 2.88 [95% CI: 1.40, 6.96], P < 0.01), Hispanic White (OR = 1.60 [95% CI: 1.33, 1.92], P < 0.01), NH Black (OR = 1.59 [95% CI: 1.27, 2.0], P < 0.01), and NH Asian (OR = 2.10 [95% CI: 1.37, 3.38], P < 0.01), were more likely to be plasma ineligible compared to those self‐identifying as NH White (Figure S1 in supporting information).
FIGURE 2.
Unadjusted log p‐tau217r by apoE4 status (carriers vs. non‐carriers) across race and ethnic group. A significant effect of race and ethnicity is observed in both carriers and non‐carriers. ApoE4, apolipoprotein E4; H, Hispanic; NH, non‐Hispanic; p‐tau217r, phosphorylated tau217 to non‐phosphorylated tau217 ratio.
FIGURE 3.
Proportion of plasma‐ineligible individuals by racial and ethnic group with 95% confidence intervals (Fisher exact test, not adjusting for any covariates, P < 0.01). Dashed line denotes overall mean. NH, non‐Hispanic.
One thousand five hundred eighty‐seven participants met the predicted amyloid PET > 18 CL cutpoint and were deemed “plasma eligible.” Plasma eligibility, ineligibility to undergo PET imaging, and PET eligibility by group can be observed in Table 2. Of the plasma‐eligible individuals, 49% were ineligible to undergo amyloid PET imaging based on clinical and cognitive screening assessments, unstable medical conditions, or exclusionary medications. Among the 808 plasma‐eligible individuals who underwent PET imaging 63.8% had amyloid PET CL values > 20 CL, the threshold for randomization. Figure 4 depicts PET ineligibility rates by group of individuals who underwent PET imaging. The proportions of those who were PET ineligible did not differ by race and ethnicity (P = 0.406; although there were few Hispanic Black [N = 1] and NH Asian [N = 3] participants who met PET eligibility).
TABLE 2.
Plasma and subsequent eligibility of participants.
| Eligibility |
Hispanic White (n = 877) |
Hispanic Black (n = 62) |
NH Asian (n = 155) | NH Black (n = 511) | NH White (N = 4832) | Total (N = 6437) |
|---|---|---|---|---|---|---|
|
Plasma eligible N (% of plasma screened) |
164 (18.7) | 7 (11.3) | 23 (14.8) | 96 (18.7) | 1297 (26.8) | 1587 |
|
Plasma eligible but not eligible to undergo PET a N (% of plasma eligible) |
87 (53.0) | 3 (42.9) | 17 (73.9) | 69 (71.9) | 603 (46.5) | 779 |
|
PET eligible N (% of PET individuals who underwent imaging) |
48 (63.2) | 3 (75%) | 3 (50.0%) | 17 (68.0%) | 481 (71.5%) | 808 |
Note: PET eligibility proportions are based on participants who underwent NAV 4694 amyloid PET imaging.
Reasons for ineligibility after plasma determination include exclusionary medical conditions, exclusionary medications, exclusionary performance on cognitive testing or Clinical Dementia Rating scale.
Abbreviations: NH, non‐Hispanic; PET, positron emission tomography.
FIGURE 4.
Proportion of PET‐ineligible individuals by racial and ethnic group with 95% confidence intervals that underwent PET screening (Fisher exact test, not adjusting for any covariates, P = 0.4). Dashed line denotes overall mean. NH, non‐Hispanic; PET, positron emission tomography.
4. DISCUSSION
Despite their reported higher risk of dementia and cognitive impairment, some racial and ethnic groups remain severely underrepresented in AD clinical trials, including preclinical AD trials like the AHEAD Study. Ineligibility due to amyloid biomarker criteria may be an important contributor to underrepresentation of these groups. In the AHEAD Study, the use of plasma screening contributed to the screening of 16,815 individuals in North America, including 4534 (27%) who were from historically underrepresented racial and ethnic groups. In this analysis, we examined a subset of these individuals evaluated with a study‐specific plasma algorithm that included p‐tau217r, Aβ42/40, age, and apoE to predict > 18 CL on amyloid PET imaging (N = 6437). We observed significant differences in plasma eligibility rates, with participants who self‐identified as Hispanic Black, Hispanic White, NH Asian, and NH Black qualifying less frequently compared to participants self‐reporting as NH White. Despite the observed racial and ethnic differences in plasma eligibility, among those who went on to PET imaging, no group differences were observed in PET eligibility.
In the AHEAD Study, the introduction of plasma screening was initially determined using the Aβ42/40, age, and apoE4 status algorithm with a cutpoint favoring sensitivity. 12 Recent observational studies have demonstrated that p‐tau217 levels measured by mass spectrometry are strongly correlated with amyloid CSF and PET measures. 13 , 23 , 24 , 25 In the AHEAD Study, the addition of p‐tau217r to the plasma algorithm, implemented at the earliest screening visit, prior to cognitive and clinical assessments, contributed to a more accurate prediction of PET amyloid eligibility. 14 Given that biomarker cutoffs are often defined based on cohorts largely comprised of individuals identifying as NH White, evaluating the screening performance of these biomarkers across other racial and ethnic groups is critical for AD trials aiming to enroll more inclusive study cohorts. While we observed differences in plasma eligibility rates in our analyses, PET eligibility among those who were plasma eligible did not differ by group. This suggests that in this study, a prespecified plasma prediction cutpoint was appropriately applied across racial and ethnic groups. A more thorough understanding of the differential eligibility based on plasma measures and other eligibility criteria among these groups will require substantial further investigation.
Our findings are consistent with our previous report and align with findings from other studies. In the AHEAD Study, we previously observed very similar racial and ethnic differences in eligibility using an algorithm based on a model that included Aβ42/40, age, and apoE proteotype with a (plasma predictive cutpoint > 11 CL). 12 Although the initial algorithm favored sensitivity, rather than specificity, we observed similar ability of that plasma algorithm to predict PET eligibility across racial and ethnic groups, such that no differences were observed among plasma‐eligible participants. In the Anti‐Amyloid Treatment in Asymptomatic Alzheimer's (A4) Study, another preclinical trial, evaluation of the screened population demonstrated higher likelihood of biomarker ineligibility among underrepresented racial and ethnic groups based on amyloid PET. 6 , 8 The ongoing double‐blind placebo‐controlled Phase 3 TRAILBLAZER‐ALZ 3 trial testing donanemab in preclinical AD has recently reported similar lower eligibility rates among racial and ethnic underrepresented groups on a plasma p‐tau217 screening assay. 26 Moreover, similar observations have been made in studies of symptomatic populations. Differential trial eligibility has been reported among 10,804 screened participants across four Phase 2 and Phase 3 placebo‐controlled, double‐blind randomized trials of amyloid‐lowering treatments in early AD. Consistent with our results, in this report racial and ethnic groups underrepresented in trials had higher probability of ineligibility on amyloid PET imaging. 7 Findings from the Imaging Dementia‐Evidence for Amyloid Scanning Cohort Study evaluation of PET positivity among 17,107 Medicare beneficiaries with mild cognitive impairment or dementia, suggest lower likelihood of an amyloid PET–positive scan among self‐reported Asian, Black, and Hispanic participants compared to White participants. 27 Moreover, Xiong et al. suggested lower amyloid PET levels, trends toward lower levels of CSF p‐tau181, and slower rates of longitudinal accumulation in Black adults compared to White individuals. 28 Altogether, these findings may suggest that differential prevalence of brain amyloid among underrepresented racial and ethnic groups, rather than biomarker performance or cutpoints, is the key contributor to differential eligibility rates in trials of amyloid‐lowering treatments. These findings have important implications for future AD trials and underscore the need for large‐scale screening efforts leveraging plasma biomarkers to identify and oversample individuals from underrepresented groups.
4.1. Limitations
Clinical trials are subject to selection bias often due to study‐specific requirements including exclusionary medical conditions, willingness to participate, or the way in which participants may be enrolled in the study among other reasons. In the AHEAD Study, while we were able to engage greater numbers of individuals from underrepresented racial and ethnic groups, the randomized sample was predominantly NH White and highly educated, inadequately representing the full range of key sociodemographic factors among the population at highest risk for dementia.
Some studies suggest that comorbidities, such as chronic kidney disease and body mass index (BMI), may influence biomarker levels in some racial and ethnic groups. 29 , 30 In this study we controlled for some of these potential confounding factors by using the ratio of p‐tau217 to non‐phosphorylated tau as recommended by others. 31 Further evaluating these and other comorbidities in cohorts that oversample racial and ethnic groups will be critical to further understand intersectionality of these covariates.
While this analysis reflects rates of plasma eligibility and PET eligibility among plasma‐eligible participants, 49% of plasma‐eligible individuals did not undergo PET imaging due to not meeting cognitive, functional, or medical criteria. Future analyses will examine other potential contributors to differential eligibility, including criteria that may disproportionately exclude individuals from communities of color.
Last, in this analysis, we cannot be certain that longitudinal rates of amyloid accumulation across racial and ethnic groups are similar over time. Future studies, such as the Amyloid Plasma Extension (APEX) Study, will enable longitudinal evaluation of AD plasma and other biomarkers. The study will enroll participants who consented to the AHEAD Study but were not eligible for randomization and will oversample individuals from racial and ethnic underrepresented groups to better understand differences in these and other underrepresented populations helping to address this gap and other important questions.
5. CONCLUSION
Similar to previous observations using a plasma eligibility algorithm based on Aβ42/40, an algorithm using p‐tau217r combined with Aβ42/40 was able to accurately predict amyloid PET pathology across racial and ethnic groups. The plasma eligibility findings continue to raise the possibility that amyloid pathology may be less prevalent among unimpaired individuals from some communities of color. Our findings also suggest that a consistent plasma‐predictive cutpoint can and should be implemented across racial and ethnic groups to detect amyloid levels appropriate for a given interventional target and that doing so does not bias toward inappropriate exclusion of underrepresented racial and ethnic groups. Our results have important implications for future AD trials using plasma screening, but more studies are needed to better understand the underlying reasons for differential plasma eligibility and potential differences in prevalence of amyloid pathology across racial and ethnic populations.
CONFLICT OF INTEREST STATEMENT
Doris Molina‐Henry has received funding from the American Heart Association and the Alzheimer's Association. Rema Raman has received research support from NIH, Eisai, Eli Lilly, the Alzheimer's Association, and the American Heart Association. Andy Liu and Oliver Langford are employees of the Keck School of Medicine of USC. Joel B. Braunstein, Philip B. Verghese, and Venky Venkatesh are paid employees of C2N Diagnostics, and collectively have research support from the NIH, BrightFocus Foundation, GHR Foundation, Alzheimer's Drug Discovery Foundation, and the Michael J. Fox Foundation. Shobha Dhadda and Michael Irizarry are paid employees of Eisai. Joshua D. Grill has received research support from NIA, Alzheimer's Association, BrightFocus Foundation, Eli Lilly, Genentech, Biogen, and Eisai, and has served as a consultant for SiteRx. Keith A. Johnson has received research from the NIH and GHR Foundation, and has consulted for Novartis, Janssen, and Merck. Robert A. Rissman has received research support from the National Institute on Aging, the Alzheimer's Association, and is a consultant for Amydis Inc, Bioivt, Lexeo, Keystone Bio, Allyx, DiamiR, Ionis and PrecisionMed. Paul S. Aisen has received grants from NIH, Lilly, and the Alzheimer's Association; has research collaborations with Eisai and CogRx; and serves as a consultant for Merck, Roche, Genentech, Abbvie, Biogen, Checkpoint, Immunobrain, and Arrowhead. Reisa A. Sperling has received research support from the NIH, the Alzheimer's Association, the GHR Foundation, Eli Lilly, and Eisai, and has consulted for Abbvie, AC Immune, Acumen, Alector, Apellis, Biohaven, Bristol Myers Squibb, Genentech, Janssen, Nervgen, Oligomerix, Prothena, Vigil Neuroscience, Ionis, and Vaxxinity. The AHEAD Study team has received research support from the NIH, NIA, Alzheimer's Association, and Eisai. Author disclosures are available in the supporting information.
CONSENT STATEMENT
Informed consent was obtained from all participants and their study partners.
Supporting information
Supporting Information
Supporting Information
ACKNOWLEDGMENTS
The authors would like to thank the site principal investigators, staff, participants, and their study partners for their involvement in this study. The AHEAD 3‐45 Study is conducted as a public–private partnership of the Alzheimer's Clinical Trial Consortium (ACTC), funded by the National Institute on Aging, National Institutes of Health (NIH), Eisai Inc., the GHR Foundation, and other philanthropists.
Molina‐Henry DP, Raman R, Liu A, et al. Racial and ethnic differences in plasma p‐tau217 ratio biomarker eligibility rates in a preclinical AD trial with lecanemab. Alzheimer's Dement. 2025;e70164. 10.1002/dad2.70164
AHEAD 3‐45 Study Team
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