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. 2023 Aug 23;14(1):5120.
doi: 10.1038/s41467-023-40775-z.

Effect of apolipoprotein genotype and educational attainment on cognitive function in autosomal dominant Alzheimer's disease

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Effect of apolipoprotein genotype and educational attainment on cognitive function in autosomal dominant Alzheimer's disease

Stephanie Langella et al. Nat Commun. .

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.

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Conflict of interest statement

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.

Figures

Fig. 1
Fig. 1. Age-related trajectories of cognitive impairment in PSEN1 E280A mutation carriers and non-carriers.
a Cross-sectional MMSE scores of PSEN1 E280A mutation carriers (red) and non-carriers (black) as a function of age. b Differences in MMSE score between PSEN1 E280A mutation carriers and non-carriers as a function of age. MMSE score declines in mutation carriers begins to differ from non-carriers at 31.5 years. The shaded areas of each plot represent the 99% credible intervals around the model estimates drawn from the distributions of model fits derived by the Hamiltonian Markov chain Monte Carlo analyses. MMSE Mini Mental State Examination. Source data are provided as a Source Data file.
Fig. 2
Fig. 2. Age-related trajectories of cognitive impairment in PSEN1 E280A mutation carriers and non-carriers stratified by presence or absence of APOE e4.
a Cross-sectional MMSE scores of PSEN1 E280A mutation carriers who are APOE e4+ (red) and APOE e4- (black) as a function of age. b Differences in MMSE score between APOE e4+ and e4− PSEN1 E280A mutation carriers as a function of age. MMSE score declines in APOE e4+ PSEN1 E280A mutation carriers begins to differ from APOE e4− PSEN1 E280A mutation carriers at 44.3 years. c Cross-sectional MMSE scores of PSEN1 E280A mutation non-carriers who are APOE e4+ (red) and APOE e4− (black) as a function of age. d Differences in MMSE score between APOE e4+ and e4- PSEN1 E280A mutation non-carriers as a function of age. MMSE score does not differ between APOE e4+ and e4− PSEN1 E280A mutation non-carriers in this age range. The shaded areas of each plot represent the 99% credible intervals around the model estimates drawn from the distributions of model fits derived by the Hamiltonian Markov chain Monte Carlo analyses. MMSE = Mini Mental State Examination. Source data are provided as a Source Data file.
Fig. 3
Fig. 3. Cognitive function by years of educational attainment in PSEN1 E280A mutation carriers stratified by APOE genotype.
Mini Mental State Examination scores plotted by years of formal educational attainment in PSEN1 E280A mutation carriers stratified by a APOE e4 genotype (red: APOE e4+; black: APOE e4−) and b APOE e2 genotype (red: APOE e2−; black: APOE e2+). Plots show regression line with shaded standard error bands. MMSE = Mini Mental State Examination. Source data are provided as a Source Data file.

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