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Alzheimer’s Disease: Analyzing the Missing Heritability
Open accessAbstract
Alzheimer's disease (AD) is a complex disorder influenced by environmental and genetic factors. Recent work has identified 11 AD markers in 10 loci. We used Genome-wide Complex Trait Analysis to analyze >2 million SNPs for 10,922 individuals from the Alzheimer's Disease Genetics Consortium to assess the phenotypic variance explained first by known late-onset AD loci, and then by all SNPs in the Alzheimer's Disease Genetics Consortium dataset. In all, 33% of total phenotypic variance is explained by all common SNPs. APOE alone explained 6% and other known markers 2%, meaning more than 25% of phenotypic variance remains unexplained by known markers, but is tagged by common SNPs included on genotyping arrays or imputed with HapMap genotypes. Novel AD markers that explain large amounts of phenotypic variance are likely to be rare and unidentifiable using genome-wide association studies. Based on our findings and the current direction of human genetics research, we suggest specific study designs for future studies to identify the remaining heritability of Alzheimer's disease.
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“a majority of remaining AD variants are likely to be rare [6, 8]”
From Linkage, whole genome sequence, and biological data implicate variants in RAB10 in Alzheimer’s disease resilience (2017) · cites this paper as [8]
Experimental — accuracy not yet measuredIn the citing paper
“variation at this locus is estimated to explain only a portion of the heritability of LOAD [76]”
From Genetic architecture of Alzheimer's disease (2020) · cites this paper as [76]
In the citing paper
“Interestingly, estimates suggest common variants identified by GWAS explain only 30% of the heritability of AD [76]”
From Genetic architecture of Alzheimer's disease (2020) · cites this paper as [76]
In the citing paper
“Current estimates suggest only about 30–40% of the heritability of AD is explained by identified GWAS variants, leaving over 25% of the variance unexplained by known genetic factors [76]”
From Genetic architecture of Alzheimer's disease (2020) · cites this paper as [76]
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PLINK: a tool set for whole-genome association and population-based linkage analyses.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089
Corder, E. H., Saunders, A. M., Strittmatter, W. J., Schmechel, D. E., Gaskell, P. C., Small, G. W., Roses, A. D., Haines, J. L., & Pericak-Vance, M. A. (1993) · Science · doi:10.1126/science.8346443 · Cited by 9,429
GCTA: a tool for genome-wide complex trait analysis
Yang, J., Lee, S. H., Goddard, M. E., & Visscher, P. M. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2010.11.011 · Cited by 8,279
The International HapMap Project
†The International HapMap Consortium, Genotyping centres: Baylor College of Medicine and ParAllele BioScience, Gibbs, R. A., Belmont, J. W., Hardenbol, P., Willis, T. D., Yu, F., Chinese HapMap Consortium, Yang, H., Ch'ang, L.-Y., et al. (2003) · Nature · doi:10.1038/nature02168 · Cited by 6,057
Host–microbe interactions have shaped the genetic architecture of inflammatory bowel disease
The International IBD Genetics Consortium (IIBDGC), Jostins, L., Ripke, S., Weersma, R. K., Duerr, R. H., McGovern, D. P., Hui, K. Y., Lee, J. C., Philip Schumm, L., Sharma, Y., et al. (2012) · Nature · doi:10.1038/nature11582 · Cited by 4,722
Goate, A., Chartier-Harlin, M.-C., Mullan, M., Brown, J., Crawford, F., Fidani, L., Giuffra, L., Haynes, A., Irving, N., James, L., et al. (1991) · Nature · doi:10.1038/349704a0 · Cited by 4,659
Querfurth, H. W., & LaFerla, F. M. (2010) · New England Journal of Medicine · doi:10.1056/nejmra0909142 · Cited by 4,569
Common SNPs explain a large proportion of the heritability for human height
Yang, J., Benyamin, B., McEvoy, B. P., Gordon, S., Henders, A. K., Nyholt, D. R., Madden, P. A., Heath, A. C., Martin, N. G., Montgomery, G. W., et al. (2010) · Nature Genetics · doi:10.1038/ng.608 · Cited by 4,446
Cloning of a gene bearing missense mutations in early-onset familial Alzheimer's disease
Sherrington, R., Rogaev, E. I., Liang, Y., Rogaeva, E. A., Levesque, G., Ikeda, M., Chi, H., Lin, C., Li, G., Holman, K., et al. (1995) · Nature · doi:10.1038/375754a0 · Cited by 4,051
Robust relationship inference in genome-wide association studies
Manichaikul, A., Mychaleckyj, J. C., Rich, S. S., Daly, K., Sale, M., & Chen, W.-M. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq559 · Cited by 3,541
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- C Ballard, 2011, Alzheimer's disease, Lancet
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Ávila, J., Gómez‐Ramos, A., & Soriano, E. (2014) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2014.00323 · Cited by 7
Machine learning in brain imaging genomics
Yan, J., Du, L., Yao, X., & Shen, L. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-804076-8.00014-1 · Cited by 7
N’Songo, A., Carrasquillo, M. M., Wang, X., Nguyen, T., Asmann, Y. W., Younkin, S. G., Allen, M., Duara, R., Custo, M. T. G., Graff‐Radford, N. R., et al. (2017) · Journal of Alzheimer s Disease · doi:10.3233/jad-161185 · Cited by 6
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Wang, M., Li, A., Sekiya, M., Beckmann, N. D., Quan, X., Schrode, N., Fernando, M. B., Yu, A., Zhu, L., Cao, J., et al. (2019) · doi:10.1101/788323 · Cited by 6
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Sun, N., Akay, L. A., Murdock, M. H., Park, Y., Bubnys, A., Galani, K., Mathys, H., Jiang, X., Ng, A. P., Bennett, D. A., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.02.09.479797 · Cited by 6
Bond, M. L., Quiroga, I. Y., D’Costa, S., Wu, Y., Bell, J. L., McAfee, J. C., Kramer, N. E., Lee, S., Patrucco, M., Phanstiel, D. H., et al. (2024) · medRxiv · doi:10.1101/2024.09.13.24313654 · Cited by 5
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D’Argenio, V., Tomaiuolo, R., Bargeri, S., & Sancesario, G. M. (2026) · Genes · doi:10.3390/genes17020233 · Cited by 5
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Osterman, M. D., Song, Y. E., Lynn, A., Miskimen, K. L. S., Adams, L. D., Laux, R. A., Caywood, L. J., Prough, M. B., Clouse, J. E., Herington, S. D., et al. (2023) · Human Genetics and Genomics Advances · doi:10.1016/j.xhgg.2023.100241 · Cited by 5
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Francis, E., Cadar, D., Steptoe, A., & Ajnakina, O. (2022) · BMC Psychiatry · doi:10.1186/s12888-022-03717-5 · Cited by 4
Heal, M., McFall, G. P., Vergote, D., Jhamandas, J. H., Westaway, D. A., & Dixon, R. A. (2022) · Journal of Alzheimer s Disease · doi:10.3233/jad-220334 · Cited by 4
Han, S., Cho, S.-A., Choi, W., Eilbeck, K. L., Coon, H. H., Nho, K. T., & Lee, Y. (2025) · BMC Genomics · doi:10.1186/s12864-025-11362-x · Cited by 6
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Osterman, M. D., Song, Y. E., Lynn, A., Miskimen, K. L. S., Wheeler, N. R., Bartlett, J., Farrer, L. A., Schellenberg, G. D., Martin, E. R., Pericak‐Vance, M. A., et al. (2024) · Neurology Genetics · doi:10.1212/nxg.0000000000200198 · Cited by 3
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Oviya, I. R., Sankar, D., Manoharan, S., Prabahar, A., & Raja, K. (2024) · Genes · doi:10.3390/genes15050614 · Cited by 2
Hartin, P. J., Cleland, I., Nugent, C., McClean, S. I., Patterson, T. J., Tschanz, J. T., Clark, C. J., & Norton, M. C. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-19312-0_32 · Cited by 2
Clark, C. J. (2016) · Digital Commons - USU (Utah State University) · doi:10.26076/0337-6f81 · Cited by 2
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Zhou, J., Qiu, Y., Chen, S., Liu, L., Liao, H., Chen, H., Lv, S., & Li, X. (2020) · Frontiers in Genetics · doi:10.3389/fgene.2020.572350 · Cited by 2
Schenker-Ahmed, N. M., Bulsara, N., Yang, L., Huang, L., Iranmehr, A., Wu, J., Graff, A. M., Dadakova, T., Chung, H.-K., Tkach, D., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/731661 · Cited by 2
Lin, C., Li, H., Deng, C., Liu, W., Erhardt, S., Wu, F., Zhao, X., Wang, J., Wang, D., Hu, B., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.02.09.430536 · Cited by 2
Vogt, H. (2021) · transcript Verlag eBooks · doi:10.14361/9783839455784 · Cited by 2
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Housini, M., Zhou, Z., Abdullah, L. B., Pathak, G. A., Ayoub, R., Gutierrez, J., Andrews, S. J., Phillips, N., O’Bryant, S. E., Barber, R. C., et al. (2025) · Alzheimer s & Dementia Translational Research & Clinical Interventions · doi:10.1002/trc2.70124 · Cited by 1
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Wang, P., Song, Y. E., Lynn, A., Miskimen, K. L. S., Gulyayev, A. V., Prough, M. B., Dorfsman, D. A., Laux, R. A., Fuzzell, S. L., Hochstetler, S. D., et al. (2026) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1002/dad2.70388 · Cited by 1
Haplotype-centered mapping for improved alignments and genetic association studies
Bodily, P., Clement, M., Snell, Q. O., Fujimoto, M., & Ridge, P. G. (2014) · ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB) · doi:10.1145/2649387.2649435 · Cited by 1
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Koenig, H. G., VanderWeele, T. J., & Peteet, J. R. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780190088859.003.0027 · Cited by 1
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Potier, M. (2021) · Bulletin de l Académie Nationale de Médecine · doi:10.1016/j.banm.2021.02.003 · Cited by 1
Nicolas, G., Charbonnier, C., & de Oliveira, J. R. M. (2015) · Journal of Molecular Neuroscience · doi:10.1007/s12031-015-0557-y · Cited by 1
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Voyle, N., Jansen, W. J., Keohane, A., Patel, H., Folarin, A., Newhouse, S., Johnston, C., Lin, K., Visser, P. J., Hodges, A., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/174995 · Cited by 1
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Iatrou (2018) · Research Publications (Maastricht University) · doi:10.26481/dis.20180712ai · Cited by 1
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Li, Y., Kang, J., Wu, C., Dinov, I. D., Hu, J., Chalise, P., Mahnken, J. D., & Initiative, A. D. N. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.07.29.454368 · Cited by 1
Shade, L. M. P., Katsumata, Y., Claas, S. A., Ebbert, M., Abner, E. L., Hohman, T. J., Mukherjee, S., Nho, K. T., Saykin, A. J., Bennett, D. A., et al. (2022) · medRxiv · doi:10.1101/2022.12.13.22282475 · Cited by 1
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Bellenguez, C., & Lambert, J. (2018) · Springer eBooks · doi:10.1007/978-3-319-72938-1_4
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Ayat, M., & Domaratzki, M. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/489245
Patel, S. (2019) · TSpace (University of Toronto)
Rajabli, F., Feliciano‐Astacio, B. E., Cukier, H. N., Wang, L., Griswold, A. J., Hamilton‐Nelson, K. L., Adams, L. D., Rodríguez, V., Mena, P. R., Tejada, S. J., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.03.10.986083
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Agrahari, M., Megha, K., Dahiya, K., Sharma, I., Sharma, A., Jha, N. K., Goswami, V. K., Raj, R., Kesari, K. K., & Jha, S. K. (2021) · NeuroPharmac Journal · doi:10.37881/1.617
Vogt, H. (2021) · transcript Verlag eBooks · doi:10.1515/9783839455784-006
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Koenig, H. G., VanderWeele, T. J., & Peteet, J. R. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780190088859.003.0005 · Cited by 1
Koenig, H. G., VanderWeele, T. J., & Peteet, J. R. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780190088859.003.0029
Levin, J. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780190088859.002.0007
Koenig, H. G., VanderWeele, T. J., & Peteet, J. R. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780190088859.003.0033
Koenig, H. G., VanderWeele, T. J., & Peteet, J. R. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780190088859.002.0009
Alzheimer’s Disease and Other Dementias
Koenig, H. G., VanderWeele, T. J., & Peteet, J. R. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780190088859.003.0023
Koenig, H. G., VanderWeele, T. J., & Peteet, J. R. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780190088859.003.0024
Koenig, H. G., VanderWeele, T. J., & Peteet, J. R. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780190088859.003.0020
Koenig, H. G., VanderWeele, T. J., & Peteet, J. R. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780190088859.003.0026
Disease Prevention, Detection, and Treatment
Koenig, H. G., VanderWeele, T. J., & Peteet, J. R. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780190088859.003.0030 · Cited by 1
Koenig, H. G., VanderWeele, T. J., & Peteet, J. R. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780190088859.003.0019
Koenig, H. G., VanderWeele, T. J., & Peteet, J. R. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780190088859.002.0004
Personality Traits and Disorders
Koenig, H. G., VanderWeele, T. J., & Peteet, J. R. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780190088859.003.0011
Schizophrenia and Other Psychoses
Koenig, H. G., VanderWeele, T. J., & Peteet, J. R. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780190088859.003.0009
Metadata
- Authors
- Ridge, P. G., Mukherjee, S., Crane, P. K., Kauwe, J. S. K., & Alzheimer’s Disease Genetics Consortium
- Affiliations
- Brigham Young University (US)
- University of Washington (US)
- Corresponding author
- Kauwe, John S. K.
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2013-11-07
- Volume
- 8
- Issue
- 11
- Pages
- e79771
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC3820606
- OpenAlex
- W2010192073
- Cited by
- 328
- References
- 64
- Citations by year
- 2026: 8 · 2025: 13 · 2024: 18 · 2023: 60 · 2022: 26 · 2021: 31 · 2020: 29 · 2019: 24 · 2018: 29 · 2017: 26 · 2016: 30 · 2015: 22 · 2014: 12
- FWCI
- 14.70
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Howard Hughes Medical Institute
- U.S. Department of Veterans Affairs (U01 AG024904)
- Alzheimer's Association (IIRG-05–14147, K01 AG030514, U01 AG016976, R01AG042611, U01 AG032984, IIRG-08-89720, U01 AG024904, U24AG021886, MNIRG-11-205368)
- Dana Foundation (K01 AG030514, U01 AG024904)
- Bristol-Myers Squibb (U01 AG024904, AG024904)
- Eli Lilly and Company (U01 AG024904, AG024904)
- Pfizer (AG024904, U01 AG024904)
- AstraZeneca
- GlaxoSmithKline
- Novartis
- Office of Research and Development
- Brigham Young University (MNIRG-11-205368, R01AG042611)
- University of Pennsylvania (U24 AG026395, U24 AG026390)
- F. Hoffmann-La Roche (AG024904, U01 AG024904)
- Medpace (U01 AG024904)
- Synarc (U01 AG024904, K01 AG030514)
- Northern California Institute for Research and Education (U01 AG024904, K01 AG030514)
- Wellcome Trust
- Alzheimer's Research Trust
- Newcastle University
- Stichting MS Research
- Elan (U01 AG024904)
- Eisai (U01 AG024904, AG024904)
- North Bristol NHS Trust
- Universitat de Barcelona
- Hersenstichting
- National Institutes of Health (5rc2ag036502-02, MNIRG-11-205368, 5r01ag027944-05, 5u01ag024904-10, 7r01ag019757-06, 5r37ag015473-15, AG016976, U01-AG024904, AG024904, MH60451)
- Genentech (AG024904, U01 AG024904)
- Canadian Institutes of Health Research
- Medical Research Council (U01 AG024904, K01 AG030514)
- National Institute on Aging (U01-AG-024904, R01AG017917, AG 10483, P01AG010491, P50 AG016575, AG 016976, AG05 128, P30AG010129, P30AG010133, R01AG019085, P50AG005144, R01AG042611, P50 AG016576, R01AG030146, AG021547, AG036535, AG010491, AG-05144, U24 AG026390, P30AG028383, P30AG012300, AG 025688, P50AG016577, P50AG005133, R01-AG027944, AG 024904, AG 030,514, AG-034504, P30AG028377, U01AG006781, U01AG016976, P50AG005131, R01-AG019757, R01AG034504, R37-AG015473, P50AG005138, R01AG026390, R01AG022374, P50AG016570, AG019610, K01AG030514, R01AG040770, AG036528, P50AG005128, P30AG010124, P50AG016573, AG019757, R01AG021547, R01AG041232, R01AG030653, U01AG010483, R01AG015819, P30AG008017, P30AG010161, U01AG032984, R01AG012101, R01AG031581, P30AG008051, R01AG041797, RC2-AG036502, P50AG016582, P50AG008702, AG032984, AG013846, P50AG005681, P50AG005142, P50AG008671, P30AG019610, R01AG026916, P50AG005146, P01AG003991, 1RC2AG036502, U24AG026395, P30AG013846, P50AG005136, P50AG005134, RC2AG036535, P30AG013854, R01AG025259, P50AG025688, AG026395, R01AG017173, RC2AG036528, R01AG033193, P01AG002219, AG021886, R01AG013616, U24AG056270, P01AG019724, U24AG021886, P30AG062421, P50AG023501, AG027944, R01AG020688, AG 030653, P50AG016574, R01AG035137, UO1-AG06781)
- National Institute of Mental Health (U01 AG024904, MH60451, R01MH080295, P50MH060451)
- National Human Genome Research Institute (UO1 HG004610, U01HG004610, U01HG006375)
- National Cancer Institute (R01CA129769, U54CA137788, U54CA132378)
- National Institute of Neurological Disorders and Stroke (NS3 9764, R01NS080820, R01NS059873, MH60451, NIMH MH60451, P50NS039764)
- National Institute of Biomedical Imaging and Bioengineering (U01 AG024904, AG024904)
- National Center for Research Resources (MO1 RR000-96, UL1RR02777, UL1RR029893, M01RR000096, M01RR000645)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Keywords
- Alzheimer's disease, missing heritability, phenotypic variance explained, GCTA, common SNPs, apolipoprotein E, genetic markers
- MeSH terms
- Aged, Alzheimer Disease, Apolipoproteins E, Female, Genetic Markers, Humans, Male, Case-Control Studies, Age of Onset, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Genome-Wide Association Study
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