The DOI matches its Crossref record; 33 of the 34 references it cites were found in a registry or an index.
Mutations in ABCA7 in a Belgian cohort of Alzheimer's disease patients: a targeted resequencing study
Abstract
Background ABCA7 was identified as a risk gene for Alzheimer's disease in genome-wide association studies (GWAS). It was one of the genes most strongly associated with risk of Alzheimer's disease in a Belgian cohort. Using targeted resequencing, we investigated ABCA7 in this cohort with the aim to directly detect rare and common variations in this gene associated with Alzheimer's disease pathogenesis. Methods We did massive parallel resequencing of ABCA7 after HaloPlex target enrichment of the exons, introns, and regulatory regions in 772 unrelated patients with Alzheimer's disease (mean age at onset 74·6 years [SD 8·9]) recruited at two memory clinics in Flanders, Belgium, and 757 geographically matched community-dwelling controls (mean age at inclusion 73·9 years [8·0]). After bioinformatic processing, common variants were analysed with conditional logistic regression and rare variant association analysis was done in Variant Association Tools. To explore an observed founder effect, additional unrelated patients with Alzheimer's disease (n=183, mean age at onset 78·8 years [SD 6·0]) and control individuals (n=265, mean age at inclusion 56·9 years [10·8]) from the same cohort who had not been included in massive parallel resequencing because of insufficient biosamples were screened for the ABCA7 frameshift mutation Glu709fs with Sanger sequencing. The effect of loss-of-function mutations on ABCA7 expression was investigated with quantitative real-time PCR in post-mortem brains of patients (n=3) and control individuals (n=4); nonsense mediated mRNA decay was investigated in lymphoblast cell lines from three predicted loss-of-function mutation carriers from the cohort of 772 patients with Alzheimer's disease. Findings An intronic low-frequency variant rs78117248 (minor allele frequency 3·8% in 58 patients with Alzheimer's disease and in controls 1·8% in 28 controls) showed strongest association with Alzheimer's disease (odds ratio 2·07, 95% CI 1·31-3·27; p=0·0016), and remained significant after conditioning for the GWAS top single nucleotide polymorphisms rs3764650, rs4147929, and rs3752246 (2·00, 1·22-3·26; p=0·006). We identified an increased frequency of predicted loss-of-function mutations in the patients compared with the controls (relative risk 4·03, 95% CI 1·75-9·29; p=0·0002). One frameshift mutation (Glu709fs) showed a founder effect in the study population, and was found to segregate with disease in a family with autosomal dominant inheritance of Alzheimer's disease. Expression of ABCA7 was reduced in the two carriers of loss-of-function mutations found only in patients with Alzheimer's disease (Glu709fs and Trp1214*) compared with four non-carrier controls (relative expression 0·45, 95% CI 0·25-0·84; p=0·002) and in lymphoblast cell lines from three carriers of Glu709fs compared with those from two non-carrier controls. Interpretation We propose that a low-frequency variant can explain the association between ABCA7 and Alzheimer's disease, and the evidence of loss-of-function mutations in this risk gene suggests that partial loss-of-function of ABCA7 could be a potential pathogenetic mechanism of Alzheimer's disease. Funding Belgian Science Policy Office Interuniversity Attraction Poles program P7/16, Alzheimer Research Foundation, King Baudouin Foundation AB Fund, Methusalem Excellence Program initiative of the Flemish Government, Flanders Impulse Program on Networks for Dementia Research, Research Foundation Flanders, Agency for Innovation by Science and Technology Flanders, University of Antwerp Research Fund, and European Union's Seventh Framework Programme for Research, Technological development and Demonstration (AgedBrainSYSBIO).
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“loss-of-function mutations in ABCA7 have been identified as associated with disease risk in European populations [104–106]”
From Genetic architecture of Alzheimer's disease (2020) · cites this paper as [105]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975) · Journal of Psychiatric Research · doi:10.1016/0022-3956(75)90026-6 · Cited by 88,282
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
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
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
Meta-Analysis of 74,046 Individuals Identifies 11 New Susceptibility Loci for Alzheimer’s Disease
(EADI), E. A. D. I., Lambert, J.-C., (GERAD), G. A. E. R. I. A. D., Alzheimer's Disease Genetic Consortium (ADGC), (CHARGE), C. F. H. A. A. R. I. G. E., Ibrahim-Verbaas, C. A., Harold, D., Naj, A. C., Sims, R., Bellenguez, C., et al. (2013) · Nature Genetics · doi:10.1038/ng.2802 · Cited by 4,336
Self-citationHarold, D., Abraham, R., Hollingworth, P., Sims, R., Gerrish, A., Hamshere, M. L., Pahwa, J. S., Moskvina, V., Dowzell, K., Williams, A., et al. (2009) · Nature Genetics · doi:10.1038/ng.440 · Cited by 3,326
Self-citationHyman, B. T., Phelps, C. H., Beach, T. G., Bigio, E. H., Cairns, N. J., Carrillo, M. C., Dickson, D. W., Duyckaerts, C., Frosch, M. P., Masliah, E., et al. (2012) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2011.10.007 · Cited by 3,092
Genome-wide association studies for common diseases and complex traits
Hirschhorn, J. N., & Daly, M. J. (2005) · Nature Reviews Genetics · doi:10.1038/nrg1521 · Cited by 2,923
Annotation of functional variation in personal genomes using RegulomeDB
Boyle, A. P., Hong, E. L., Hariharan, M., Cheng, Y., Schaub, M. A., Kasowski, M., Karczewski, K. J., Park, J., Hitz, B. C., Weng, S., et al. (2012) · Genome Research · doi:10.1101/gr.137323.112 · Cited by 2,722
Genome-wide association study identifies variants at CLU and CR1 associated with Alzheimer's disease
the European Alzheimer's Disease Initiative Investigators, Lambert, J.-C., Heath, S., Even, G., Campion, D., Sleegers, K., Hiltunen, M., Combarros, O., Zelenika, D., Bullido, M. J., et al. (2009) · Nature Genetics · doi:10.1038/ng.439 · Cited by 2,234
Self-citation
Cited by
Sorted by citations
Scheltens, P., De Strooper, B., Kivipelto, M., Holstege, H., Chételat, G., Teunissen, C. E., Cummings, J., & van der Flier, W. M. (2021) · The Lancet · doi:10.1016/s0140-6736(20)32205-4 · Cited by 5,465
The genetic landscape of Alzheimer disease: clinical implications and perspectives
Van Cauwenberghe, C., Van Broeckhoven, C., & Sleegers, K. (2016) · Genetics in Medicine · doi:10.1038/gim.2015.117 · Cited by 863
Self-citationMolecular genetics of early-onset Alzheimer’s disease revisited
Cacace, R., Sleegers, K., & Van Broeckhoven, C. (2016) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2016.01.012 · Cited by 617
Self-citationLate onset Alzheimer’s disease genetics implicates microglial pathways in disease risk
Efthymiou, A. G., & Goate, A. M. (2017) · Molecular Neurodegeneration · doi:10.1186/s13024-017-0184-x · Cited by 562
Bisht, K., Sharma, K. P., & Tremblay, M. (2018) · Neurobiology of Stress · doi:10.1016/j.ynstr.2018.05.003 · Cited by 366
Metadata
- Authors
- Cuyvers, E., De Roeck, A., Van den Bossche, T., Van Cauwenberghe, C., Bettens, K., Vermeulen, S., Mattheijssens, M., Peeters, K., Engelborghs, S., Vandenbulcke, M., Vandenberghe, R., De Deyn, P. P., Van Broeckhoven, C., & Sleegers, K.
- Affiliations
- University of Antwerp (BE)
- Universitair Ziekenhuis Leuven (BE)
- Corresponding author
- Sleegers, Kristel
- Venue
- The Lancet Neurology
- Publisher
- Elsevier BV
- Published
- 2015-08
- Volume
- 14
- Issue
- 8
- Pages
- 814-822
- ISSN
- 1474-4422 (ISSN-L)
- OpenAlex
- W2168215272
- Cited by
- 152
- References
- 34
- Citations by year
- 2026: 3 · 2025: 8 · 2024: 15 · 2023: 8 · 2022: 17 · 2021: 11 · 2020: 15 · 2019: 12 · 2018: 16 · 2017: 20 · 2016: 22 · 2015: 4
- FWCI
- 15.20
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The Lancet Neurology (publishedVersion)
- PubMed (publishedVersion)
- Lirias (submittedVersion)
- VUBIR (Vrije Universiteit Brussel) (submittedVersion)
- 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
- ABCA7, Alzheimer's disease, genetic risk variants, rare variants, founder effect, loss-of-function mutations, nonsense-mediated mRNA decay, Flanders, Alzheimer's disease pathogenesis, targeted sequencing, intronic variants, postmortem brain
- MeSH terms
- Aged, Aged, 80 and over, Alzheimer Disease, Belgium, Female, Gene Frequency, Humans, Male, Middle Aged, Mutation, Cohort Studies, Sequence Analysis, DNA, ATP-Binding Cassette Transporters, Polymorphism, Single Nucleotide, Genome-Wide Association Study
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
