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Cited by 57Alzheimer's disease research and treatmentsDementia and Cognitive Impairment ResearchGenetic Associations and Epidemiology

Population-based analysis of Alzheimer’s disease risk alleles implicates genetic interactions.

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Ebbert, Mark T.W., Ridge, Perry G., Wilson, Andrew R., Sharp, Aaron R., Bailey, Matthew, Norton, Maria C., Tschanz, JoAnn T., Munger, Ronald G. +2 more·2014·Biological Psychiatry
DOI 10.1016/j.biopsych.2013.07.008PMC PMC3867586
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Abstract

Background Reported odds ratios and population attributable fractions (PAF) for late-onset Alzheimer's disease (LOAD) risk loci (BIN1, ABCA7, CR1, MS4A4E, CD2AP, PICALM, MS4A6A, CD33, and CLU) come from clinically ascertained samples. Little is known about the combined PAF for these LOAD risk alleles and the utility of these combined markers for case-control prediction. Here we evaluate these loci in a large population-based sample to estimate PAF and explore the effects of additive and nonadditive interactions on LOAD status prediction performance. Methods 2419 samples from the Cache County Memory Study were genotyped for APOE and nine LOAD risk loci from AlzGene.org. We used logistic regression and receiver operator characteristic analysis to assess the LOAD status prediction performance of these loci using additive and nonadditive models and compared odds ratios and PAFs between AlzGene.org and Cache County. Results Odds ratios were comparable between Cache County and AlzGene.org when identical single nucleotide polymorphisms were genotyped. PAFs from AlzGene.org ranged from 2.25% to 37%; those from Cache County ranged from .05% to 20%. Including non-APOE alleles significantly improved LOAD status prediction performance (area under the curve = .80) over APOE alone (area under the curve = .78) when not constrained to an additive relationship (p < .03). We identified potential allelic interactions (p values uncorrected): CD33-MS4A4E (synergy factor = 5.31; p < .003) and CLU-MS4A4E (synergy factor = 3.81; p < .016). Conclusions Although nonadditive interactions between loci significantly improve diagnostic ability, the improvement does not reach the desired sensitivity or specificity for clinical use. Nevertheless, these results suggest that understanding gene-gene interactions may be important in resolving Alzheimer's disease etiology.

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  • Obesity increases the risk for late-onset Alzheimer's disease (LOAD) and other dementias.

    “Studies have shown that diet, obesity, cardiovascular diseases, hypertension, physical activity, diabetes, educational attainment, smoking, and traumatic brain injury increase the risk for LOAD and other dementias (Ebbert et al., 2014; Baumgart et al., 2015; Xu et al., 2015; Wajman et al., 2018).”

    From Plcg2M28L Interacts With High Fat/High Sugar Diet to Accelerate Alzheimer’s Disease-Relevant Phenotypes in Mice (2022) · cites this paper as Ebbert et al., 2014

    The Introduction and Abstract > Methods describe genetic risk alleles and LOAD prediction, not obesity. A search for obesity, body mass index, and lifestyle risk factors found no passage in our copy linking obesity to LOAD or other dementias. (LLM, conf=0.72)

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Authors
Ebbert, M. T. W., Ridge, P. G., Wilson, A. R., Sharp, A. R., Bailey, M., Norton, M. C., Tschanz, J. T., Munger, R. G., Corcoran, C. D., & Kauwe, J. S. K.
Affiliations
  • Brigham Young University (US)
  • Utah State University (US)
ORCID
Venue
Biological Psychiatry
Publisher
Elsevier BV
Published
2014-05
Volume
75
Issue
9
Pages
732-737
ISSN
0006-3223 (ISSN-L)
DOI
10.1016/j.biopsych.2013.07.008
PMC
PMC3867586
OpenAlex
W2159734538
Cited by
57
References
2
Citations by year
2026: 1 · 2025: 2 · 2024: 2 · 2023: 1 · 2022: 4 · 2021: 3 · 2020: 5 · 2019: 6 · 2018: 6 · 2017: 8 · 2016: 9 · 2015: 3 · 2014: 6 · 2013: 1
FWCI
4.41
Type
journal article
Language
en
Open access
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations
  • Biological Psychiatry (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
Funders
National Institute on Aging (R01 AG 11380, R01AG031272, R01AG042611, R01AG31272, R01AG011380, R01AG021136, R01 AG 21136)
Topics
  • Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
Keywords
late-onset Alzheimer's disease, genetic susceptibility loci, population attributable fraction, gene-gene interaction, epistasis, apolipoprotein E, CD33, clusterin, BIN1, ABCA7, complement receptor 1, MS4A6A, PICALM, CD2AP, diagnostic prediction, synergy factor
MeSH terms
Aged, Alleles, Alzheimer Disease, Apolipoproteins E, Female, Humans, Male, Models, Genetic, Risk, ROC Curve, Cohort Studies, Logistic Models, Odds Ratio, Age of Onset, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Genotyping Techniques

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