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Brain Differences in Infants at Differential Genetic Risk for Late-Onset Alzheimer Disease: A Cross-sectional Imaging Study
Open accessAbstract
IMPORTANCE: Converging evidence suggests brain structure alterations may precede overt cognitive impairment in Alzheimer disease by several decades. Early detection of these alterations holds inherent value for the development and evaluation of preventive treatment therapies. OBJECTIVE: To compare magnetic resonance imaging measurements of white matter myelin water fraction (MWF) and gray matter volume (GMV) in healthy infant carriers and noncarriers of the apolipoprotein E (APOE) ε4 allele, the major susceptibility gene for late-onset AD. DESIGN, SETTING, AND PARTICIPANTS: Quiet magnetic resonance imaging was performed at an academic research imaging center on 162 healthy, typically developing 2- to 25-month-old infants with no family history of Alzheimer disease or other neurological or psychiatric disorders. Cross-sectional measurements were compared in the APOE ε4 carrier and noncarrier groups. White matter MWF was compared in one hundred sixty-two 2- to 25-month-old sleeping infants (60 ε4 carriers and 102 noncarriers). Gray matter volume was compared in a subset of fifty-nine 6- to 25-month-old infants (23 ε4 carriers and 36 noncarriers), who remained asleep during the scanning session. The carrier and noncarrier groups were matched for age, gestational duration, birth weight, sex ratio, maternal age, education, and socioeconomic status. MAIN OUTCOMES AND MEASURES: Automated algorithms compared regional white matter MWF and GMV in the carrier and noncarrier groups and characterized their associations with age. RESULTS: Infant ε4 carriers had lower MWF and GMV measurements than noncarriers in precuneus, posterior/middle cingulate, lateral temporal, and medial occipitotemporal regions, areas preferentially affected by AD, and greater MWF and GMV measurements in extensive frontal regions and measurements were also significant in the subset of 2- to 6-month-old infants (MWF differences, P < .05, after correction for multiple comparisons; GMV differences, P < .001, uncorrected for multiple comparisons). Infant ε4 carriers also exhibited an attenuated relationship between MWF and age in posterior white matter regions. CONCLUSIONS AND RELEVANCE: While our findings should be considered preliminary, this study demonstrates some of the earliest brain changes associated with the genetic predisposition to AD. It raises new questions about the role of APOE in normal human brain development, the extent to which these processes are related to subsequent AD pathology, and whether they could be targeted by AD prevention therapies.
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“Infant APOE4-carriers exhibit alterations in myelin volume and cognitive maturation trajectories relative to APOE3/3-carriers34,35.”
From APOE4 impairs myelination via cholesterol dysregulation in oligodendrocytes (2022) · cites this paper as [34]
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“Indeed, ApoE4-specific alterations in brain structure have been found in <2 year old children (Dean et al., 2014; Shaw et al., 2007).”
From Reversal of ApoE4-induced recycling block as a novel prevention approach for Alzheimer’s disease (2018) · cites this paper as Dean et al., 2014
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“some of these changes are present much earlier in life [16]”
From ApoE, ApoE Receptors, and the Synapse in Alzheimer's Disease (2017) · cites this paper as [16]
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“Genetic mutations are associated with various brain abnormalities that are evident on MRI (see REF. 158 for review).”
From Imaging structural and functional brain development in early childhood (2018) · cites this paper as [158]
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Additional file 4 of Exploring the ATN classification system using brain morphology
Heinzinger, N., Maaß, A., Berron, D., Yakupov, R., Peters, O., Fiebach, J. B., Villringer, K., Preis, L., Priller, J., Spruth, E. J., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26574865
Additional file 5 of Exploring the ATN classification system using brain morphology
Heinzinger, N., Maaß, A., Berron, D., Yakupov, R., Peters, O., Fiebach, J. B., Villringer, K., Preis, L., Priller, J., Spruth, E. J., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26574868
Additional file 3 of Exploring the ATN classification system using brain morphology
Heinzinger, N., Maass, A., Berron, D., Yakupov, R., Peters, O., Fiebach, J. B., Villringer, K., Preis, L., Priller, J., Spruth, E. J., et al. (2023) · Figshare · doi:10.6084/m9.figshare.26574862
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Additional file 6 of Exploring the ATN classification system using brain morphology
Heinzinger, N., Maaß, A., Berron, D., Yakupov, R., Peters, O., Fiebach, J. B., Villringer, K., Preis, L., Priller, J., Spruth, E. J., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26574871
Additional file 10 of Exploring the ATN classification system using brain morphology
Heinzinger, N., Maass, A., Berron, D., Yakupov, R., Peters, O., Fiebach, J. B., Villringer, K., Preis, L., Priller, J., Spruth, E. J., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26574883
Additional file 8 of Exploring the ATN classification system using brain morphology
Heinzinger, N., Maaß, A., Berron, D., Yakupov, R., Peters, O., Fiebach, J. B., Villringer, K., Preis, L., Priller, J., Spruth, E. J., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26574877
Additional file 1 of Exploring the ATN classification system using brain morphology
Heinzinger, N., Maaß, A., Berron, D., Yakupov, R., Peters, O., Fiebach, J. B., Villringer, K., Preis, L., Priller, J., Spruth, E. J., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26574856
Additional file 2 of Exploring the ATN classification system using brain morphology
Heinzinger, N., Maass, A., Berron, D., Yakupov, R., Peters, O., Fiebach, J. B., Villringer, K., Preis, L., Priller, J., Spruth, E. J., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26574859
Additional file 9 of Exploring the ATN classification system using brain morphology
Heinzinger, N., Maaß, A., Berron, D., Yakupov, R., Peters, O., Fiebach, J. B., Villringer, K., Preis, L., Priller, J., Spruth, E. J., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26574880
Additional file 7 of Exploring the ATN classification system using brain morphology
Heinzinger, N., Maaß, A., Berron, D., Yakupov, R., Peters, O., Fiebach, J. B., Villringer, K., Preis, L., Priller, J., Spruth, E. J., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26574874
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Metadata
- Authors
- Dean, D. C., Jerskey, B. A., Chen, K., Protas, H., Thiyyagura, P., Roontiva, A., O'Muircheartaigh, J., Dirks, H., Waskiewicz, N., Lehman, K., Siniard, A. L., Turk, M. N., Hua, X., Madsen, S. K., Thompson, P. M., Fleisher, A. S., Huentelman, M. J., Deoni, S. C. L., & Reiman, E. M.
- Affiliations
- Brown University (US)
- University of Arizona (US)
- Banner Alzheimer’s Institute (US)
- Advanced Baby Imaging Lab, School of Engineering, Brown University, Providence, Rhode Island7Department of Neuroimaging, King’s College London, Institute of Psychiatry, London, England
- Translational Genomics Research Institute (US)
- University of California, Los Angeles (US)
- University of California San Diego (US)
- Corresponding author
- Deoni, Sean C. L.
- ORCID
- Venue
- JAMA Neurology
- Publisher
- American Medical Association (AMA)
- Published
- 2014-01-01
- Volume
- 71
- Issue
- 1
- Pages
- 11
- ISSN
- 2168-6149 (ISSN-L)
- PMC
- PMC4056558
- OpenAlex
- W2160816909
- Cited by
- 263
- References
- 41
- Citations by year
- 2026: 10 · 2025: 15 · 2024: 18 · 2023: 24 · 2022: 14 · 2021: 15 · 2020: 20 · 2019: 27 · 2018: 19 · 2017: 19 · 2016: 25 · 2015: 25 · 2014: 29
- FWCI
- 19.13
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- JAMA Neurology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Research Portal (King's College London) (submittedVersion)
- Funders
- Wellcome Trust (096195)
- National Institute on Aging (P30-AG-19610, R01AG031581, P30AG019610)
- National Institute of Mental Health (R01MH087510)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Cognitive Abilities and Testing
- Keywords
- late-onset Alzheimer's disease, APOE ε4, genetic risk, infants, myelin water fraction, white matter, gray matter volume, brain development, precuneus, cingulate cortex, lateral temporal cortex, occipitotemporal cortex, frontal lobe, early detection, Alzheimer's disease prevention
- MeSH terms
- Alleles, Alzheimer Disease, Child, Preschool, Cross-Sectional Studies, Heterozygote, Humans, Infant, Magnetic Resonance Imaging, Genetic Variation, Age of Onset, Genetic Predisposition to Disease, Early Diagnosis, Apolipoprotein E4, Cerebrum
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