Effect of apolipoprotein genotype and educational attainment on cognitive function in autosomal dominant alzheimer’s disease

ABSTRACT Autosomal dominant Alzheimer’s disease (ADAD) is genetically determined, but variability in age of symptom onset suggests additional factors may influence cognitive trajectories.

Although apolipoprotein E (_APOE_) genotype and educational attainment both influence dementia onset in sporadic AD, evidence for these effects in ADAD is limited. To investigate the effects

of _APOE_ and educational attainment on age-related cognitive trajectories in ADAD, we analyzed data from 675 Presenilin-1 E280A mutation carriers and 594 non-carriers. Here we show that

age-related cognitive decline is accelerated in ADAD mutation carriers who also have an _APOE_ e4 allele compared to those who do not and delayed in mutation carriers who also have an _APOE_

e2 allele compared to those who do not. Educational attainment is protective and moderates the effect of _APOE_ on cognition. Despite ADAD mutation carriers being genetically determined to

develop dementia, age-related cognitive decline may be influenced by other genetic and environmental factors. SIMILAR CONTENT BEING VIEWED BY OTHERS EFFECTS OF POLYGENIC RISK FOR ALZHEIMER’S

DISEASE ON RATE OF COGNITIVE DECLINE IN NORMAL AGING Article Open access 24 July 2020 GENETIC EFFECTS ON LONGITUDINAL COGNITIVE DECLINE DURING THE EARLY STAGES OF ALZHEIMER’S DISEASE

Article Open access 06 October 2021 ASSOCIATION OF GENETIC RISK OF ALZHEIMER’S DISEASE AND COGNITIVE FUNCTION IN TWO EUROPEAN POPULATIONS Article Open access 21 February 2025 INTRODUCTION

Presence of the e4 allele of the apolipoprotein E (_APOE_) gene is associated with increased risk for developing sporadic Alzheimer’s disease (AD) and an earlier age of clinical onset than

for individuals without an e4 allele1,2. However, evidence for an effect of _APOE_ e4 genotype on cognitive function in autosomal dominant AD (ADAD) has been limited and inconclusive. ADAD

is genetically determined by mutations on the amyloid precursor protein (_APP_), Presenilin-1 (_PSEN1_), and Presenilin-2 (_PSEN2_) genes3. The largest known kindred with ADAD due to a

single mutation (_PSEN1_ E280A) resides in Antioquia, Colombia. Carriers of this mutation have a median age of onset of mild cognitive impairment at 44 years and of dementia at 49 years4.

Despite the group’s well-characterized trajectory, there is individual variability in disease progression, highlighting the need to identify other genetic and environmental factors which may

influence age-related cognitive decline. The role of _APOE_ e4 in this kindred has been inconclusive. In a previous study of 109 _PSEN1_ E280A mutation carriers, those who had an _APOE_ e4

allele had an earlier age of dementia onset than those who did not5. A subsequent study of 71 carriers in the same kindred found no effect of _APOE_ e4, but found that the presence of the e2

allele was associated with delayed clinical onset by approximately eight years6. Broader investigations including ADAD carriers from multiple families have reported differences between

_APP_ and _PSEN1_ mutations, which may mask _APOE_ effects in combined analyses, but indicate detrimental effects on cognitive performance and decline in _PSEN1_ carriers7,8, demonstrating

the importance of additional investigation in a large single kindred. In addition, environmental factors (such as lifestyle, health, and socioeconomic conditions) may influence age-related

cognitive trajectories and mitigate genetic risk9,10,11. One such factor is education (often defined as years of formal educational attainment), which has been identified as an important

modifiable factor for dementia delay and prevention12. Higher educational attainment has been associated with slowed cognitive decline in older adults13 and lower dementia incidence14,

indicating educational attainment promotes cognitive resilience in the face of pathology15. The reported impact of educational attainment in ADAD, however, is inconsistent. Lower educational

attainment was a predictor of cognitive decline in ADAD due to various mutations7 and of earlier clinical onset in _PSEN1_ E280A carriers16. Unexpectedly, however, lower educational

attainment (less than three years) has also been associated with later onset of dementia in carriers of the _PSEN1_ E280A mutation5. Of note, ruralness was independently associated with both

lower educational attainment and later age of onset in that sample5, which may have contributed to the observed relationship. There have been no reported significant interactive effects

between _APOE_ genotype and educational attainment in ADAD to date. Additional investigation in this kindred is required to clarify these discrepant findings. The role of genetic and

environmental factors impacting age-related cognitive decline in ADAD are critical to further understand disease progression and to support future prevention and treatment goals. In this

study, we aimed to evaluate the influence of _APOE_ genotype on cognitive function in 675 _PSEN1_ E280A carriers and 594 non-carrier family members, and secondarily explore whether

educational attainment may be protective and moderate the relationship between _APOE_ and cognitive function. We hypothesized that presence of the e4 allele would be associated with

accelerated onset of cognitive impairment, presence of the e2 allele would be associated with delayed cognitive impairment, and that higher educational attainment would be protective against

cognitive impairment. Consistent with our hypotheses, in this work we show that the onset of age-related cognitive decline is accelerated in _PSEN1_ E280A mutation carriers who are also

_APOE_ e4+ compared to those who are _APOE_ e4− and delayed in those who are _APOE_ e2+ compared to _APOE_ e2−. Further, we find that educational attainment is protective and moderates the

effect of _APOE_ on cognition in _PSEN1_ carriers. RESULTS SAMPLE CHARACTERISTICS Sample characteristics are presented in Table 1. Of the 675 _PSEN1_ E280A mutation carriers, 141 were _APOE_

e4+ and 534 were _APOE_ e4−. The _APOE_ e4+ and e4− _PSEN1_ E280A mutation carriers did not differ in age (_p_ = 0.64) or sex (_p_ = 0.89), and they did not differ in MMSE score (_p_ = 

0.52) when collapsing across age. _PSEN1_ E280A mutation carriers who were also _APOE_ e4+ had on average more years of educational attainment than those who were _APOE_ e4− (_p_ = 0.02). Of

the 594 _PSEN1_ E280A mutation non-carriers, 148 were _APOE_ e4+ and 446 were _APOE_ e4−. Within these non-carriers, _APOE_ e4+ and e4− individuals did not differ in age (_p_ = 0.42), sex

(_p_ = 0.23), educational attainment (_p_ = 0.42), or MMSE score (_p_ = 0.82). AGE-RELATED COGNITIVE FUNCTION BY _PSEN1_ AND _APOE_ E4 GENOTYPE We first estimated the age-related trajectory

of cognitive impairment, measured through MMSE total score, using the Hamiltonian Markov chain Monte Carlo method in _PSEN1_ E280A mutation carriers and non-carriers, irrespective of APOE

genotype. MMSE was negatively associated with age in _PSEN1_ carriers and significantly differentiated carriers from non-carriers at 31.5 years (Fig. 1). We then estimated the age-related

trajectory of cognitive impairment as a function of _APOE_ e4 genotype separately in _PSEN1_ E280A mutation carriers and non-carriers. The cognitive trajectories of _APOE_ e4+ and e4−

_PSEN1_ E280A mutation carriers diverged at 44.3 years, approximately the median age of onset of mild cognitive impairment in this kindred4 (Fig. 2A, B). In contrast, the age-related

cognitive trajectories of _APOE_ e4+ and e4− _PSEN1_ E280A mutation non-carriers did not diverge (Fig. 2C, D). To supplement these analyses, age of clinical onset was compared in a subset of

_PSEN1_ mutation carriers who had converted to MCI or dementia. Consistent with the prior findings, _PSEN1_ mutation carriers who were also _APOE_ e4+ had earlier ages of clinical onset

compared to those who were _APOE_ e4− (Supplementary Table 1). ROLE OF EDUCATIONAL ATTAINMENT ON COGNITION IN _PSEN1_ E280A CARRIERS Years of educational attainment was examined as a

protective and potentially modifying factor of the relationship between _APOE_ e4 and cognitive function using separate linear regressions for _PSEN1_ E280A mutation carriers and

non-carriers. Within _PSEN1_ E280A mutation carriers, being _APOE_ e4+ was associated with lower MMSE scores compared to _APOE_ e4− (_β_ = −3.37, _p_ = 0.001). Irrespective of _APOE_

genotype, higher educational attainment was associated with higher MMSE scores (_β_ = 0.41, _p_ < 0.001). There was also a significant interaction between _APOE_ e4 and years of

educational attainment (_β_ = 0.32, _p_ = 0.005; Fig. 3a) such that the negative effect of _APOE_ e4+ was attenuated as years of educational attainment increased. In other words, higher

levels of educational attainment mitigated the additional risk conferred by the presence of at least one e4 allele in _PSEN1_ E280A carriers. In non-carriers of the _PSEN1_ E280A mutation,

there was no significant effect of _APOE_ e4 on MMSE score (_β_ = −0.17, _p_ = 0.66), but there was a significant main effect of educational attainment (_β_ = 0.16, _p_ < 0.001) such that

higher educational attainment was associated with higher MMSE scores. There was no interaction between _APOE_ e4 and educational attainment (_β_ = −0.003, _p_ = 0.94). AGE-RELATED COGNITIVE

FUNCTION BY _PSEN1_ AND _APOE_ E2 GENOTYPE Our findings suggest that within _PSEN1_ E280A carriers, age-related cognitive decline begins earlier in those who are _APOE_ e4+ than for those

with other _APOE_ genotypes, including those who are homozygous e3 and e2+. Because presence of the e2 allele has been associated with delayed clinical onset in this kindred6, we sought to

examine the association between _APOE_ e2 and cognition in our current sample. Of the 675 _PSEN1_ E280A mutation carriers, 102 were _APOE_ e2+ and 573 were _APOE_ e2− (Supplementary Table 

2). The _APOE_ e2+ and e2− _PSEN1_ E280A mutation carriers did not differ in age (_p_ = 0.20), sex (_p_ = 0.65), educational attainment (_p_ = 0.69), or MMSE score (_p_ = 0.37). Of the 594

_PSEN1_ E280A mutation non-carriers, 73 were _APOE_ e2+ and 521 were _APOE_ e2−, and _APOE_ e2+ and e2− individuals did not differ in age (_p_ = 0.47), sex (_p_ = 0.12), educational

attainment (_p_ = 0.70), or MMSE score (_p_ = 0.66). We first estimated the age-related trajectory of cognitive impairment as a function of _APOE_ e2 genotype separately in _PSEN1_ E280A

mutation carriers and non-carriers (Supplementary Fig. 1a, b). The cognitive trajectories of _APOE_ e2+ and e2− _PSEN1_ E280A mutation carriers diverged at 41.1 years, such that _APOE_ e2+

_PSEN1_ carriers had delayed age-related global cognitive decline. Age of clinical onset of the MCI and dementia converters did not significantly differ between _APOE_ e2+ and e2− genotypes,

but the trends were in the hypothesized direction such that _APOE_ e2+ mutation carriers had on average later clinical onset (Supplementary Table 1). In _PSEN1_ E280A mutation non-carriers,

the age-related cognitive trajectories of _APOE_ e2+ and e2− individuals did not diverge (Supplementary Fig. 1c, d). We then assessed the relationships between _APOE_ e2 genotype and

educational attainment on global cognitive function. Within _PSEN1_ E280A mutation carriers, there was a main effect of genotype, such that those who were _APOE_ e2− had lower MMSE scores

than those who were _APOE_ e2+ (_ß_ = −2.78, _p_ = 0.007). Across _APOE_ genotype, higher educational attainment was associated with higher MMSE scores (_ß_ = 0.26, _p_ = 0.018).

Additionally, there was a significant interaction between _APOE_ e2 genotype and educational attainment, ß = 0.24, _p_ = 0.046 (Fig. 3b), such that higher educational attainment attenuated

the negative effect of being _APOE_ e2−. DISCUSSION _APOE_ e4 has long been associated with increased risk and earlier age of onset for sporadic AD1,2,17,18,19,20. A rare variant on the

_APOE_ e3 allele was found to delay onset of MCI by three decades in a _PSEN1_ E280A carrier21, yet the evidence linking the more common e2 and e4 variants has been mixed5,6,22. Our findings

in over 1,000 participants from a single kindred show an added effect of _APOE_ genotype in carriers of the _PSEN1_ E280A mutation for ADAD, such that _APOE_ e4+ _PSEN1_ mutation carriers

had accelerated onset of age-related cognitive decline compared to _APOE_ e4− _PSEN1_ mutation carriers. The age-related trajectory of clinical impairment diverged between _APOE_ e4+ and e4−

_PSEN1_ mutation carriers around age 44, approximately the median age of onset of mild cognitive impairment in this kindred4. Our results are consistent with a prior study reporting a

detrimental effect of _APOE_ e4+ genotype in _PSEN1_ E280A mutation carriers5. A subsequent study of 71 _PSEN1_ E280A mutation carriers found no effect of _APOE_ e4 genotype, but the

relationship was in the expected negative direction6, suggesting the study may have been underpowered to detect an effect. Conversely, we found that _PSEN1_ E280A mutation carriers who were

_APOE_ e2+ had delayed onset of age-related cognitive decline, replicating a prior finding from this kindred6. The _APOE_ e2 allele has also been associated with delayed onset and protection

against cognitive decline in older adults20,23,24. More research is needed to determine how these genetic risk factors contribute to earlier cognitive decline in ADAD. Both _APOE_ e4 and

_PSEN1_ mutations influence accumulation of β-amyloid (Aβ) pathology in the brain25,26,27. This genetic combination may result in earlier or higher pathological burden, but future studies

will need to consider age-related trajectories of brain pathology in addition to clinical impairment. Since other mutations causing ADAD also alter Aβ production, similar results might be

expected in other ADAD mutations. However, the extent to which these results generalize to ADAD caused by other mutations is uncertain. A study of _APP_ and _PSEN1_ mutation carriers from

six families found no overall effect of _APOE_ e4 on cognitive decline, but in a direct comparison of age-related cognitive decline of _APOE_ e4+ _APP_ and _PSEN1_ carriers, the _APOE_ e4+

_PSEN1_ carriers had a steeper decline than the _APOE_ e4+ _APP_ carriers7. Additional questions remain about the nuances of _APOE_ genotype in ADAD. It is currently unknown whether the risk

is greater in homozygous _APOE_ e4 ADAD mutation carriers than in heterozygous _APOE_ e4 ADAD mutation carriers, as is observed in sporadic AD2. This question is particularly challenging to

answer in ADAD given the small percentage of homozygous _APOE_ e4 carriers coupled with the small population of ADAD mutation carriers. Observational evidence from a sample of 17 carriers

of an _APP_ mutation supports this notion, such that homozygous _APOE_ e4 mutation carriers had the earliest age of onset, followed by the heterozygous _APOE_ e4 mutation carriers, and

finally the _APOE_ e2 mutation carriers with the latest onset28. In a comparison of early- and late-onset AD, _APOE_ e4 genotype was associated with accelerated cognitive decline in both

groups29. Coupled with the current results, these findings provide converging evidence that _APOE_ may have similar effects in sporadic and autosomal dominant AD. Furthermore, in sporadic

AD, _APOE_ e4 has been associated with better cognitive performance and differing neural activity during young adulthood30,31,32, reflecting possible antagonistic pleiotropy of this genetic

risk factor33,34. Structurally, _APOE_ e4+ adults show greater parahippocampal thickness than _APOE_ e4− adults35 and differences in white matter integrity that may relate to observed

cognitive benefits36. Our study only considered age-related cognitive trajectories in adult carriers; however, it is possible that _APOE_ e4 may provide some biological or cognitive benefit

in younger _PSEN1_ carriers (i.e., childhood, akin to young adults in sporadic AD). In fact, _PSEN1_ carriers in this kindred have greater cortical thickness in childhood than non-carriers,

followed by atrophy in adulthood37. Studying the influence of both _APOE_ and _PSEN1_ across the lifespan will enhance our knowledge of the effects of these genes, and, hopefully, provide

mechanisms for disease prevention and treatment in the future. Despite the additional risk conferred by _APOE_ e4, our results suggest that educational attainment may be a critical mechanism

of cognitive reserve in ADAD, as previously shown in sporadic AD13,14,15. Higher educational attainment was related to higher global cognition in _PSEN1_ carriers and mitigated the

cognitive impairment associated with _APOE_ e4. Prior studies in this kindred have found opposing results, including one in which more years of educational attainment was associated with

delayed clinical onset16, and one in which higher educational attainment (defined categorically as greater than three years) was associated with lower cognition5 in _PSEN1_ mutation

carriers. The conflicting results may arise from differences in the samples’ average years of educational attainment, the treatment of educational attainment as a continuous versus

categorical variable, or from confounding variables influencing these relationships. In the prior study reporting a detrimental effect of educational attainment, low educational attainment

was highly correlated with ruralness, which similarly was associated with later clinical onset5. Ruralness, then, may reflect protective factors (e.g., physical activity, environment) that

explain the reported positive association of low educational attainment. We similarly found that ruralness was associated with fewer years of educational attainment in our sample, but we did

not find an association between ruralness and global cognition (see Supplementary Analysis). The _PSEN1_ carriers and non-carriers of our sample are members of the same families, providing

a high degree of environmental matching, although additional variables explaining quality rather than quantity of years of educational attainment may contribute to our findings and will be

important to consider in future work. Many studies examining education effects in sporadic AD include older adult populations with high levels of educational attainment, with averages often

greater than high school or college. This is not representative of the broader population, and there are many conflicting findings in the role of educational attainment on cognitive reserve

in older adults13,14,38,39. In contrast, our sample included a broad range of educational attainment. Our results indicate that low levels of formal educational attainment, in particular,

confers greater risk. As such, programs to increase early years of education may be particularly important as preventative measures, supported by the inclusion of education as one of the 12

modifiable risk factors for dementia in the most recent Lancet commission12. The factors contributing to higher versus lower educational attainment (e.g., socioeconomic status, occupational

attainment) as well as the underlying biological mechanisms of this _APOE_-educational attainment interaction require further study, particularly since higher levels of educational

attainment have been associated with lower Aβ in ADAD40. A primary limitation of this study is the reliance of single time-point data. Although our participants spanned a broad range of

ages, and age is highly linked to clinical progression in this kindred, we cannot speak to individual trajectories of decline with these data. Analysis of longitudinal cognitive decline will

further clarify whether _APOE_ influences age of onset, rate of decline, or both. Additionally, despite having one of the largest sample sizes compared to prior literature in ADAD, our

study was underpowered to assess potential gene dose-dependent effects of the _APOE_ e4 or e2 alleles (see Supplementary Fig. 2 for visualization of age-related cognitive trajectories).

Finally, educational attainment is not the sole environmental factor influencing cognition and clinical progression. More work is needed to further understand the impact of other lifestyle

and modifiable factors along with their interactions with genetic makeup. Together, our results highlight the importance of studying additional genetic and environmental risk factors in ADAD

populations, with critical implications for future disease prevention and interventions. Future studies can push these questions forward by investigating the biological basis for the

additive risk of _APOE_ e4 and _PSEN1_ mutations and for the protective role of _APOE_ e2, and for the aspects and length of educational attainment that can support cognitive function or

reduce the risk of dementia. Inclusion of blood-based biomarkers in such studies characterizing disease progression is necessary to increase access in these populations at risk and to

understand the biological mechanisms underlying these findings41,42,43. The answers to these questions will inform how to best implement educational interventions in various communities and

whether continuing late life education may provide additional protection. These answers are critical as Aβ- and _APOE_-based treatments for AD are being investigated44,45. In conclusion, our

results demonstrate that (1) age-related changes in global cognitive function may be accelerated in ADAD mutation carriers who are also _APOE_ e4+ compared to those who are _APOE_ e4−; (2)

age-related changes in global cognitive function may be delayed in ADAD mutation carriers who are also _APOE_ e2+ compared to those who are _APOE_ e2−; and (3) higher educational attainment

may have a protective effect against cognitive impairment, even in the presence of strong genetic risk factors. METHODS Study procedures were approved by the Institutional Review Board of

the University of Antioquia in Colombia (21-10-605) and were performed in accordance with the ethical standards of the Declaration of Helsinki. All participants provided informed consent

prior to the initiation of study procedures. Participants were compensated for their participation in accordance with the approved guidelines. STUDY DESIGN AND PARTICIPANTS This

cross-sectional study included participants over the age of 18 recruited from the Alzheimer’s Prevention Initiative (API) registry of ADAD, which includes more than 6000 living members of a

kindred with a high prevalence of carriers of the _PSEN1_ E280A mutation (approximately 1200 individuals)46. All members of the registry reside in Colombia and have a parent with the _PSEN1_

E280A mutation but are blind to their own genetic status. In total, 675 _PSEN1_ E280A mutation carriers (370 female, 305 male) and 594 mutation non-carriers (332 female, 262 male) were

included in these analyses. Neuropsychological assessments were performed at the University of Antioquia in Colombia. Participants completed a clinical interview and the Mini Mental State

Examination (MMSE), administered in Spanish, used as a proxy for cognitive impairment. Cognitive data were stored using REDCap (v. 13.1.29). Investigators were blind to participant genetic

status during data collection. GENOTYPING Genomic DNA was extracted from the blood by standard protocols, and _PSEN1_ E280A characterization was done at the University of Antioquia using

methods previously described47. Genomic DNA was amplified with the primers _PSEN1_-S 5′ AACAGCTCAGGAGAGGAATG 3′ and PSEN1-AS 5′ GATGAGACAAGTNCCNTGAA 3′. We used the restriction enzyme _Bsm_I

for restriction fragment length polymorphism analysis. Each participant was classified as a _PSEN1_ E280A carrier or non-carrier. _APOE_ genotyping was performed using a Kompetitive Allele

Specific PCR–KASPTM assay48 (LGV Genomics, Beverly, MA). Due to low numbers of homozygous e4 carriers and homozygous e2 carriers (see Table 2), each participant was classified based on the

presence of at least one e4 allele (e4+) or no e4 alleles (e4−), and separately, based on the presence of at least one e2 allele (e2+) or no e2 alleles (e2−). Twenty-nine participants (13

_PSEN1_ carriers and 16 non-carriers) were _APOE_ e2/e4 and, therefore, included in both _APOE_ e4+ and _APOE_ e2+ groups. STATISTICAL ANALYSIS All analyses were conducted in R version

4.2.0, modeled separately for _PSEN1_ E280A carriers and non-carriers. Group differences in continuous variables were assessed using Mann–Whitney _U_ tests due to non-normality, and

dichotomous variables were compared using chi-square tests. _APOE_ genotype was included in analyses as a dichotomous variable. Cognitive impairment was measured through MMSE total score

(maximum score = 30). Age-related trajectories were derived from cross-sectional MMSE scores modeled using a restricted cubic spline model. Model parameters were estimated using a

Hamiltonian Markov chain Monte Carlo method to compare group trajectories (prior = Cauchy distribution, chains = 8, iterations = 10,000, thin = 10). Linear regression was used to estimate

the effect of educational attainment on cognition, with MMSE total score as the dependent variable and _APOE_genotype, educational attainment, and their interaction term as predictors.

Educational attainment was included as a continuous variable, representing self-reported total years of formal educational attainment. Self-reported sex was collected for each participant

and is presented in demographic tables. Sex was not included in statistical analyses due to no a priori hypotheses about sex differences and sample size limitations of subdividing the

participants by _PSEN1_ genotype, _APOE_ genotype, and sex; however, the proportions of males and females were roughly similar, and there were no differences in sex distributions in the

comparison groups of interest, thus we believe results are generalizable to both males and females. REPORTING SUMMARY Further information on research design is available in the Nature

Portfolio Reporting Summary linked to this article. DATA AVAILABILITY Anonymized clinical, cognitive and genetic data are available upon request, subject to an internal review by F.L., and

Y.T.Q. to ensure that participant confidentiality and _PSEN1_ E280A carrier or non-carrier status are protected, completion of a data sharing agreement and in accordance with the University

of Antioquia’s and MGH’s institutional review board and institutional guidelines. Please submit requests for participant-related data to Y.T.Q. ([email protected]). Source data are

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D. & Whitford, R.) 75–86 (Springer New York, 2014). Download references ACKNOWLEDGEMENTS The authors thank the _PSEN1_ Colombian families for contributing their valuable time and effort,

without which this study would not have been possible. We thank the research staff of the Group of Neuroscience of Antioquia for their help coordinating study visits for the Colombian API

Registry. We thank Geidy Serrano from the Banner institute for her help quantifying DNA samples. This study was supported by grant DP5OD019833 from the National Institutes of Health Office

of the Director (Y.T.Q.), the Massachusetts General Hospital Executive Committee on Research (Y.T.Q.), and grant R01AG054671 from the National Institute on Aging (Y.T.Q.). The funders had no

role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the

manuscript for publication. AUTHOR INFORMATION Author notes * These authors jointly supervised this work: Eric M. Reiman, Francisco Lopera, Yakeel T. Quiroz. AUTHORS AND AFFILIATIONS *

Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA Stephanie Langella, N. Gil Barksdale, Gabriel Oliveira, Clara Vila-Castelar & Yakeel T. Quiroz * Grupo de

Neurociencias de Antioquia, Facultad de Medicina, Universidad de Antioquia, Medellin, Colombia Daniel Vasquez, David Aguillon, Natalia Acosta-Baena, Juliana Acosta-Uribe, Ana Y. Baena, 

Gloria Garcia-Ospina, Margarita Giraldo-Chica, Victoria Tirado, Claudia Muñoz, Silvia Ríos-Romenets, Claudia Guzman-Martínez, Francisco Lopera & Yakeel T. Quiroz * Banner Alzheimer’s

Institute, Phoenix, AZ, USA Yinghua Chen, Yi Su, Jeremy J. Pruzin, Valentina Ghisays & Eric M. Reiman * Neuroscience Research Institute and Department of Molecular, Cellular and

Developmental Biology, University of California Santa Barbara, Santa Barbara, CA, USA Juliana Acosta-Uribe & Kenneth S. Kosik * Brigham and Women’s Hospital, Harvard Medical School,

Boston, MA, USA Hyun-Sik Yang * Schepens Eye Research Institute of Mass Eye and Ear, Harvard Medical School, Boston, MA, USA Joseph F. Arboleda-Velasquez Authors * Stephanie Langella View

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E.M.R., F.L., and Y.T.Q. initiated this work, directed and supervised conduction of the study. S.L, N.G.B and Y.T.Q. drafted the manuscript. Clinical information was collected and analyzed

by F.L., D.V., D.A., N.A-B, A.B., M.G-C, V.T., C.M., S.R-R., and C.V.-C. Genetic data was collected and analyzed by G.G., C.G-M., J.A.-U., and K.K. Statistical analyses were conducted by

Y.C., V.G, and Y.S. All authors revised and contributed to finalize the manuscript. CORRESPONDING AUTHOR Correspondence to Yakeel T. Quiroz. ETHICS DECLARATIONS COMPETING INTERESTS S.L. is

supported by a grant from the Alzheimer’s Association (AARF-22-920754). Y.S. reports grants from The Alzheimer’s Association, The BrightFocus Foundation, NIH/NIA, State of Arizona, outside

the submitted work. C.V.-C. reports grants from the Alzheimer’s Association (AARF 2019A005859) and the National Institute on Aging (K99AG073452). K.S.K. is on the Board of Directors for the

Tau Consortium, receives funding from the NIA, the Alzheimer Association, and the Alzheimer’s Drug Discovery Foundation. H-S.Y. reports a grant from the National Institute of Aging (K23

AG062750). E.M.R. reports grants from National Institute on Aging (P30 AG072980, R01 AG069453, R01 AG055444), Banner Alzheimer’s Foundation and the NOMIS Foundation during the conduct of the

study. E.M.R. is a compensated scientific advisor for Alzheon, Aural Analytics, Denali, Retromer Therapeutics, and Vaxxinity, an uncompensated scientific advisor for Lilly, and a cofounder,

advisor and shareholder of AlzPATH, which is involved in the development of blood-based biomarkers for Alzheimer’s disease outside the scope of the submitted. In addition, E.M.R. is the

inventor of a patent issued to Banner Health, which involves the use of biomarker endpoints in at-risk persons to accelerate the evaluation of Alzheimer’s disease prevention therapies and is

outside the submitted work. F.L. was supported by an Anonymous Foundation, and the Administrative Department of Science, Technology and Innovation (Colciencias Colombia;111565741185).

E.M.R. and F.L. are principal investigators of the Alzheimer’s Prevention Initiative (API) Autosomal Dominant AD Trial, which is supported by NIA, philanthropy, Genentech, and Roche. Y.T.Q.

was supported by grants from the National Institute on Aging (R01 AG054671, RF1AG077627), the Alzheimer’s Association, and Massachusetts General Hospital ECOR. Y.T.Q. serves as consultant

for Biogen. The remaining authors declare no competing interests. PEER REVIEW PEER REVIEW INFORMATION _Nature Communications_ thanks Yadong Huang, and the other, anonymous, reviewer(s) for

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N.G., Vasquez, D. _et al._ Effect of apolipoprotein genotype and educational attainment on cognitive function in autosomal dominant Alzheimer’s disease. _Nat Commun_ 14, 5120 (2023).

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