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Contribution to Alzheimer's disease risk of rare variants in TREM2, SORL1, and ABCA7 in 1779 cases and 1273 controls
Open accessAbstract
We performed whole-exome and whole-genome sequencing in 927 late-onset Alzheimer disease (LOAD) cases, 852 early-onset AD (EOAD) cases, and 1273 controls from France. We assessed the evidence for gene-based association of rare variants with AD in 6 genes for which an association with such variants was previously claimed. When aggregating protein-truncating and missense-predicted damaging variants, we found exome-wide significant association between EOAD risk and rare variants in SORL1, TREM2, and ABCA7. No exome-wide significant signal was obtained in the LOAD sample, and significance of the order of 10-6 was observed in the whole AD group for TREM2. Our study confirms previous gene-level results for TREM2, SORL1, and ABCA7 and provides a clearer insight into the classes of rare variants involved. Despite different effect sizes and varying cumulative minor allele frequencies, the rare protein-truncating and missense-predicted damaging variants in TREM2, SORL1, and ABCA7 contribute similarly to the heritability of EOAD and explain between 1.1% and 1.5% of EOAD heritability each, compared with 9.12% for APOE ε4.
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“both SORL1 and ABCA7 genes—already detected by GWAS—carried numerous loss-of-function variants leading to strong increases in AD risk [9, 98, 128].”
From The new genetic landscape of Alzheimer’s disease: from amyloid cascade to genetically driven synaptic failure hypothesis? (2019) · cites this paper as [9]
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“SORL1 is now considered as a major AD risk factor gene, because of increased frequencies of rare coding variant carriers in cases as compared to cognitively-healthy controls [2, 22–24].”
From Impaired SorLA maturation and trafficking as a new mechanism for SORL1 missense variants in Alzheimer disease (2021) · cites this paper as [2]
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“Exome and genome sequencing recently allowed the identification of three genes harboring a higher burden of rare non-synonymous variants in AD cases as compared to controls: TREM2, SORL1, and ABCA7 [2].”
From Impaired SorLA maturation and trafficking as a new mechanism for SORL1 missense variants in Alzheimer disease (2021) · cites this paper as [2]
In the citing paper
“we also identified ten genes located in our genome-wide loci as having rare deleterious coding, splicing or LOF burden associations with LOAD (false discovery rate (FDR) P < 0.01), including previously implicated rare-variant signals in ABCA7, TREM2, and SORL1 (refs. 14,49–55), and additional associations with TREML4 in the TREM2 locus, TAP2 and PSMB8 in the HLA-DRB1 locus, PIP in the EPHA1 locus,”
From Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing (2019) · cites this paper as [52]
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Cites
R: A Language and Environment for Statistical Computing
R Core Team (2000) · doi:10.32614/r.manuals · Cited by 355,893
Fast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607
McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., & Stadlan, E. M. (1984) · Neurology · doi:10.1212/wnl.34.7.939 · Cited by 27,915
The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data
McKenna, A., Hanna, M., Banks, E., Sivachenko, A., Cibulskis, K., Kernytsky, A., Garimella, K., Altshuler, D., Gabriel, S., Daly, M., et al. (2010) · Genome Research · doi:10.1101/gr.107524.110 · Cited by 27,895
McKhann, G. M., Knopman, D. S., Chertkow, H., Hyman, B. T., Jack, C. R., Kawas, C. H., Klunk, W. E., Koroshetz, W. J., Manly, J. J., Mayeux, R., et al. (2011) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2011.03.005 · Cited by 18,657
A global reference for human genetic variation
The 1000 Genomes Project Consortium, authors, C., Auton, A., Abecasis, G. R., Steering committee, Altshuler, D. M., Durbin, R. M., Abecasis, G. R., Bentley, D. R., Chakravarti, A., et al. (2015) · Nature · doi:10.1038/nature15393 · Cited by 18,247
A method and server for predicting damaging missense mutations.
Adzhubei, I. A., Schmidt, S., Peshkin, L., Ramensky, V. E., Gerasimova, A., Bork, P., Kondrashov, A. S., & Sunyaev, S. R. (2010) · Nature Methods · doi:10.1038/nmeth0410-248 · Cited by 13,194
Second-generation PLINK: rising to the challenge of larger and richer datasets
Chang, C. C., Chow, C. C., Tellier, L. C., Vattikuti, S., Purcell, S. M., & Lee, J. J. (2015) · Gigascience · doi:10.1186/s13742-015-0047-8 · Cited by 12,709
Cingolani, P., Platts, A., Wang, L. L., Coon, M., Nguyen, T., Wang, L., Land, S. J., Lu, X., & Ruden, D. M. (2012) · Fly · doi:10.4161/fly.19695 · Cited by 11,816
Analysis of protein-coding genetic variation in 60,706 humans
Exome Aggregation Consortium, Lek, M., Karczewski, K. J., Minikel, E. V., Samocha, K. E., Banks, E., Fennell, T., O’Donnell-Luria, A. H., Ware, J. S., Hill, A. J., et al. (2016) · Nature · doi:10.1038/nature19057 · Cited by 9,587
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Alzheimer Disease Genetics Consortium (ADGC), Kunkle, B. W., The European Alzheimer’s Disease Initiative (EADI), Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (CHARGE), Genetic and Environmental Risk in AD/Defining Genetic, P. A. E. R. F. A. D. C. (., Grenier-Boley, B., Sims, R., Bis, J. C., Damotte, V., Naj, A. C., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0358-2 · Cited by 2,946
Self-citationKnopman, D. S., Amieva, H., Petersen, R. C., Chételat, G., Holtzman, D. M., Hyman, B. T., Nixon, R. A., & Jones, D. T. (2021) · Nature Reviews Disease Primers · doi:10.1038/s41572-021-00269-y · Cited by 2,606
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Hampel, H., Hardy, J., Blennow, K., Chen, C., Perry, G., Kim, S. H., Villemagne, V. L., Aisen, P., Vendruscolo, M., Iwatsubo, T., et al. (2021) · Molecular Psychiatry · doi:10.1038/s41380-021-01249-0 · Cited by 1,952
The multiplex model of the genetics of Alzheimer's disease
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Metadata
- Authors
- Bellenguez, C., Charbonnier, C., Grenier-Boley, B., Quenez, O., Le Guennec, K., Nicolas, G., Chauhan, G., Wallon, D., Rousseau, S., Richard, A. C., Boland, A., Bourque, G., Munter, H. M., Olaso, R., Meyer, V., Rollin-Sillaire, A., Pasquier, F., Letenneur, L., Redon, R., Dartigues, J.-F., Tzourio, C., Frebourg, T., Lathrop, M., Deleuze, J.-F., Hannequin, D., Genin, E., Amouyel, P., Debette, S., Lambert, J.-C., Campion, D., Hannequin, D., Campion, D., Wallon, D., Martinaud, O., Zarea, A., Nicolas, G., Rollin-Sillaire, A., Bombois, S., Mackowiak, M.-A., Deramecourt, V., Pasquier, F., Michon, A., Le Ber, I., Dubois, B., Godefroy, O., Etcharry-Bouyx, F., Chauviré, V., Chamard, L., Berger, E., Magnin, E., Dartigues, J.-F., Auriacombe, S., Tison, F., Sayette, V. D. L., Castan, D., Dionet, E., Sellal, F., Rouaud, O., Thauvin, C., Moreaud, O., Sauvée, M., Formaglio, M., Mollion, H., Roullet-Solignac, I., Vighetto, A., Croisile, B., Didic, M., Félician, O., Koric, L., Ceccaldi, M., Gabelle, A., Marelli, C., Labauge, P., Jonveaux, T., Vercelletto, M., Boutoleau-Bretonnière, C., Castelnovo, G., Paquet, C., Dumurgier, J., Hugon, J., De Boisgueheneuc, F., Belliard, S., Bakchine, S., Sarazin, M., Barrellon, M.-O., Laurent, B., Blanc, F., Pariente, J., & Jurici, S.
- Affiliations
- Inserm (FR)
- Université de Bordeaux (FR)
- Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR)
- McGill University and Génome Québec Innovation Centre (CA)
- Centre National de la Recherche Scientifique (FR)
- Centre Hospitalier Universitaire Amiens-Picardie (FR)
- Centre National de Recherche en Génomique Humaine (FR)
- Centre Hospitalier du Rouvray (FR)
- Centre Hospitalier Universitaire de Montpellier (FR)
- ORCID
- Bellenguez, Céline
- Charbonnier, Camille
- Quenez, Olivier
- Chauhan, Ganesh
- Boland, Anne
- Bourque, Guillaume
- Olaso, Robert
- Meyer, Vincent
- Letenneur, Luc
- Redon, Richard
- Tzourio, Christophe
- Lathrop, Mark
- Deleuze, Jean-François
- Amouyel, Philippe
- Debette, Stéphanie
- Lambert, Jean-Charles
- Bombois, Stéphanie
- Deramecourt, Vincent
- Dubois, Bruno
- Godefroy, Olivier
- Tison, François
- Sayette, Vincent de la
- Rouaud, Olivier
- Moreaud, Olivier
- Sauvée, Mathilde
- Croisile, Bernard
- Didic, Mira
- Félician, Olivier
- Koric, Lejla
- Ceccaldi, Mathieu
- Gabelle, Audrey
- Labauge, Pierre
- Jonveaux, Thérèse
- Castelnovo, Giovanni
- Paquet, Claire
- Dumurgier, Julien
- Hugon, Jacques
- Belliard, Serge
- Sarazin, Marie
- Laurent, Bernard
- Blanc, Frédéric
- Pariente, Jérémie
- Jurici, Snejana
- Venue
- Neurobiology of Aging
- Publisher
- Elsevier BV
- Published
- 2017-11
- Volume
- 59
- Pages
- 220.e1-220.e9
- ISSN
- 0197-4580 (ISSN-L)
- OpenAlex
- W2735794637
- Cited by
- 166
- References
- 56
- Citations by year
- 2026: 8 · 2025: 13 · 2024: 20 · 2023: 14 · 2022: 29 · 2021: 24 · 2020: 13 · 2019: 28 · 2018: 16
- FWCI
- 11.53
- Type
- journal article
- Language
- en
- Open access
- green
- hal.science
- Licence
- Locations
- Neurobiology of Aging (publishedVersion)
- PubMed (publishedVersion)
- HAL (submittedVersion, cc-by)
- HAL (submittedVersion)
- Funders
- France Génomique National infrastructure
- Centre National de Génotypage
- National Foundation for Alzheimer's disease and related disorders
- Institut Pasteur de Lille
- Inserm
- FRC
- Lille Métropole Communauté Urbaine council
- French government's LABEX
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › 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
- Alzheimer's disease, rare variants, TREM2, SORL1, ABCA7, early-onset Alzheimer's disease, late-onset Alzheimer's disease, truncating mutations, missense mutations, genetic risk, heritability, APOE ε4, gene-based association
- MeSH terms
- Whole Genome Sequencing, Adult, Aged, Aged, 80 and over, Alzheimer Disease, Female, Humans, Male, Membrane Glycoproteins, Middle Aged, Receptors, Immunologic, Genetic Variation, ATP-Binding Cassette Transporters, Genetic Predisposition to Disease, LDL-Receptor Related Proteins, Membrane Transport Proteins, Apolipoprotein E4, Genome-Wide Association Study, Young Adult, Genetic Association Studies
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