The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
CD33: increased inclusion of exon 2 implicates the Ig V-set domain in Alzheimer’s disease susceptibility
Open accessAbstract
We previously demonstrated that the Alzheimer's disease (AD) associated risk allele, rs3865444(C), results in a higher surface density of CD33 on monocytes. Here, we find alternative splicing of exon 2 to be the primary mechanism of the genetically driven differential expression of CD33 protein. We report that the risk allele, rs3865444(C), is associated with greater cell surface expression of CD33 in both subjects of European and African-American ancestry and that there is a single haplotype influencing CD33 surface expression. A meta-analysis of the two populations narrowed the number of significant SNPs in high linkage disequilibrium (LD) (r(2) > 0.8) with rs3865444 to just five putative causal variants associated with increased protein expression. Using gene expression data from flow-sorted CD14(+)CD16(-) monocytes from 398 healthy subjects of three populations, we show that the rs3865444(C) risk allele is strongly associated with greater expression of CD33 exon 2 (pMETA = 2.36 × 10(-60)). Western blotting confirms increased protein expression of the full-length CD33 isoform containing exon 2 relative to the rs3865444(C) allele (P < 0.0001). Of the variants in strong LD with rs3865444, rs12459419, which is located in a putative SRSF2 splice site of exon 2, is the most likely candidate to mediate the altered alternative splicing of CD33's Immunoglobulin V-set domain 2 and ultimately influence AD susceptibility.
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“In addition, it is becoming increasingly clear that genetic risk can also be mediated through mRNA splicing28,29.”
From Genetic analysis of the human microglial transcriptome across brain regions, aging and disease pathologies (2022) · cites this paper as [29]
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“For instance, the CD33 locus in AD influences CD33 splicing, resulting in isoforms with different biological and likely pathological functions29.”
From Genetic analysis of the human microglial transcriptome across brain regions, aging and disease pathologies (2022) · cites this paper as [29]
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“The protective SNP alters CD33 mRNA splicing such that the extracellular sialic acid–binding domain is lost from the final protein (Malik et al., 2013, 2015; Raj et al., 2014).”
From Microglia in Alzheimer’s disease (2018) · cites this paper as Raj et al., 2014
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Cites
Browning, S. R., & Browning, B. L. (2007) · The American Journal of Human Genetics · doi:10.1086/521987 · Cited by 3,217
TREM2 Variants in Alzheimer's Disease
Guerreiro, R., Wojtas, A., Bras, J., Carrasquillo, M., Rogaeva, E., Majounie, E., Cruchaga, C., Sassi, C., Kauwe, J. S. K., Younkin, S., et al. (2013) · New England Journal of Medicine · doi:10.1056/nejmoa1211851 · Cited by 3,020
LocusZoom: regional visualization of genome-wide association scan results
Pruim, R. J., Welch, R. P., Sanna, S., Teslovich, T. M., Chines, P. S., Gliedt, T. P., Boehnke, M., Abecasis, G. R., & Willer, C. J. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq419 · Cited by 2,707
Variant of TREM2 Associated with the Risk of Alzheimer's Disease
Jonsson, T., Stefansson, H., Steinberg, S., Jonsdottir, I., Jonsson, P. V., Snaedal, J., Bjornsson, S., Huttenlocher, J., Levey, A. I., Lah, J. J., et al. (2013) · New England Journal of Medicine · doi:10.1056/nejmoa1211103 · Cited by 2,558
Siglecs and their roles in the immune system
Crocker, P. R., Paulson, J. C., & Varki, A. P. (2007) · Nature reviews. Immunology · doi:10.1038/nri2056 · Cited by 2,032
Initiative, T. A. D. N., Hollingworth, P., CHARGE consortium, EADI1 consortium, Harold, D., Sims, R., Gerrish, A., Lambert, J.-C., Carrasquillo, M. M., Abraham, R., et al. (2011) · Nature Genetics · doi:10.1038/ng.803 · Cited by 1,997
Naj, A. C., Jun, G., Beecham, G. W., Wang, L.-S., Vardarajan, B. N., Buros, J., Gallins, P. J., Buxbaum, J. D., Jarvik, G. P., Crane, P. K., et al. (2011) · Nature Genetics · doi:10.1038/ng.801 · Cited by 1,901
Self-citationIntegrated Systems Approach Identifies Genetic Nodes and Networks in Late-Onset Alzheimer’s Disease
Zhang, B., Gaiteri, C., Bodea, L.-G., Wang, Z., McElwee, J., Podtelezhnikov, A. A., Zhang, C., Xie, T., Tran, L., Dobrin, R., et al. (2013) · Cell · doi:10.1016/j.cell.2013.03.030 · Cited by 1,657
Self-citationBouchon, A., Dietrich, J., & Colonna, M. (2000) · The Journal of Immunology · doi:10.4049/jimmunol.164.10.4991 · Cited by 1,284 · cited 6×
“Our exon-level analysis of CD33 expression highlights an emerging role for an infiltrating macrophage and/or microglial activation network (including the genes TYROBP, CD33 and TREM2) in modulating AD susceptibility and pathology.”
BackgroundInfluentialAlzheimer’s Disease Risk Gene CD33 Inhibits Microglial Uptake of Amyloid Beta
Griciuc, A., Serrano-Pozo, A., Parrado, A. R., Lesinski, A. N., Asselin, C. N., Mullin, K., Hooli, B., Choi, S. H., Hyman, B. T., & Tanzi, R. E. (2013) · Neuron · doi:10.1016/j.neuron.2013.04.014 · Cited by 1,004
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Items 101–145 of 145
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Shaw, B. C., Katsumata, Y., Simpson, J. F., Fardo, D. W., & Estus, S. (2021) · Genes · doi:10.3390/genes12071008 · Cited by 16
Transgenic mouse models to study the physiological and pathophysiological roles of human Siglecs
McCord, K. A., & Macauley, M. S. (2022) · Biochemical Society Transactions · doi:10.1042/bst20211203 · Cited by 12
Matuszewska, M., Cieślik, M., Wilkaniec, A., Strawski, M., & Czapski, G. A. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms24010013 · Cited by 13
Lamba, J. K., Voigt, A. P., Chauhan, L., Shin, M., Aplenc, R., Brodersen, L. E., Gamis, A. S., Meshinchi, S., & Loken, M. R. (2018) · Leukemia & lymphoma/Leukemia and lymphoma · doi:10.1080/10428194.2017.1421756 · Cited by 10
Evolution of Human-Specific Alleles Protecting Cognitive Function of Grandmothers
Saha, S., Khan, N., Comi, T. J., Verhagen, A., Sasmal, A., Diaz, S. L., Yu, H., Chen, X., Akey, J. M., Frank, M., et al. (2022) · Molecular Biology and Evolution · doi:10.1093/molbev/msac151 · Cited by 9
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Hooli, B. V., & Tanzi, R. E. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-800105-9.00034-2 · Cited by 9
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Alzheimer’s diseases in America, Europe, and Asian regions: a global genetic variation
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Javor, J., Bucová, M., Ďurmanová, V., Radošinská, D., Párnická, Z., Čierný, D., Kurča, E., Čopíková‐Cudráková, D., Gmitterová, K., & Shawkatová, I. (2022) · Life · doi:10.3390/life12071094 · Cited by 7
Javor, J., Ďurmanová, V., Párnická, Z., Minárik, G., Králová, M., Pečeňák, J., Vašečková, B., Režnáková, V., Šutovský, S., Gmitterová, K., et al. (2020) · International Journal of Immunogenetics · doi:10.1111/iji.12489 · Cited by 7
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Humphrey, J., Brophy, E., Kosoy, R., Zeng, B., Coccia, E., Mattei, D., Ravi, A., Efthymiou, A. G., Navarro, E., Muller, B. Z., et al. (2023) · medRxiv · doi:10.1101/2023.12.01.23299073 · Cited by 5
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Li, X., Zhao, Y., Kong, H., Song, C., Liu, J., & Xia, J. (2023) · iScience · doi:10.1016/j.isci.2023.107958 · Cited by 3
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Czapski, G. A., Matuszewska, M., Cieślik, M., & Strosznajder, J. B. (2024) · Folia Neuropathologica · doi:10.5114/fn.2024.138140 · Cited by 2
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Association of CD33 genetic variants with neurocognitive profiles in chronic viral hepatitis
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Fioretto, L., Ziaco, M., Nuzzo, G., Albiani, F., Saponaro, M., Carbone, D., Barra, G., dell’Isola, M., Follero, O., Esercizio, N., et al. (2025) · Frontiers in Immunology · doi:10.3389/fimmu.2025.1648691 · Cited by 1
Clement, N. S., Braae, A., Turton, J. C., Lord, J., & Guetta‐Baranes, T. (2016) · Journal of Alzheimer’s Disease & Parkinsonism · doi:10.4172/2161-0460.1000276
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Role of the Slingshot-Cofilin and RanBP9 pathways in Alzheimer's Disease Pathogenesis
Woo, J. A. (2015) · Digital Commons - University of South Florida (University of South Florida)
Kargar, M., Jamali, H., & Sadeghi, M. (2019) · Medical Laboratory Journal · doi:10.29252/mlj.13.5.19
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Park, J., Tao, X., & Zhai, R. G. (2020) · OBM Genetics · doi:10.21926/obm.genet.2001106
Bahlo, M. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.735227305.793565249
Mubeen, H., Masood, A., Zafar, A., Khan, Z. Q., Khan, M. Q., Nisa, A. U., & Naveed, Z. A. (2022) · Research Square · doi:10.21203/rs.3.rs-2060964/v1
Philippi, S. M., Kailash, B. P., Raj, T., & Castellano, J. M. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.12.28.522119
Eskandari‐Sedighi, G., Crichton, M. C., Zia, S., Gomez, E., Laurent, C. D. S., Cortez, L. M., Patel, Z. H., Sidhu, G., Sarkar, S., Aghanya, V., et al. (2023) · Research Square · doi:10.21203/rs.3.rs-3147035/v1
Novel combinations of CD33-targeted immunotherapies
Xue, T., Chen, M. L., Gong, J., Li, L., & Cao, C. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-23932-8.00013-3
Eskandari‐Sedighi, G., Crichton, M. C., Zia, S., Gomez‐Cardona, E., Cortez, L. M., Patel, Z. H., Takahashi, K., St. Laurent, C. D., Sidhu, G., Sarkar, S., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26725883
Bhattacherjee, A., Jung, J., Zia, S., Ho, M. F. S., Eskandari‐Sedighi, G., St. Laurent, C. D., McCord, K. A., Bains, A., Sidhu, G., Sarkar, S., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14314649
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Qing, W., Xie, Y., Wu, X., Jin, S., Zhen, W., Yu, S., Sun, Y., Sun, W., Xu, J., & Zhang, H. (2026) · Journal of Pain Research · doi:10.2147/jpr.s603587
Li, J., Yue, D., Xie, W., Xiong, Z., & Wang, X. (2026) · Gene · doi:10.1016/j.gene.2026.150397
BindingDB Entry 50014978: Discovery of Small-Molecule CD33 Pre-mRNA Splicing Modulators.
BindingDB (2023) · UC San Diego · doi:10.7270/q2xd15jr
Metadata
- Authors
- Raj, T., Ryan, K. J., Replogle, J. M., Chibnik, L. B., Rosenkrantz, L., Tang, A., Rothamel, K., Stranger, B. E., Bennett, D. A., Evans, D. A., De Jager, P. L., & Bradshaw, E. M.
- Affiliations
- Broad Institute (US)
- Brigham and Women's Hospital (US)
- University of Chicago (US)
- Rush University Medical Center (US)
- Corresponding author
- Bradshaw, E. M.
- ORCID
- Venue
- Human Molecular Genetics
- Publisher
- Oxford University Press (OUP)
- Published
- 2013-12-30
- Volume
- 23
- Issue
- 10
- Pages
- 2729-2736
- ISSN
- 0964-6906 (ISSN-L)
- 1460-2083
- PMC
- PMC3990171
- OpenAlex
- W2161428211
- Cited by
- 144
- References
- 27
- Citations by year
- 2026: 3 · 2025: 7 · 2024: 13 · 2023: 10 · 2022: 18 · 2021: 20 · 2020: 18 · 2019: 13 · 2018: 9 · 2017: 9 · 2016: 9 · 2015: 7 · 2014: 8
- FWCI
- 5.56
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Human Molecular Genetics (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health
- National Institute on Aging (R01AG017917, P30-AG 10161, K25AG041906, R01AG030146, R01 AG30146, R01‐AG17917, R01 AG15819, R01AG11101, R01AG011101, R01AG043617, R01AG015819, P30AG010161, F32AG043267, R01AG031553)
- National Institute of General Medical Sciences (RC2GM093080)
- National Institute of Neurological Disorders and Stroke (R01NS067305)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Keywords
- CD33, Alzheimer's disease, alternative splicing, exon 2, monocytes, cell surface expression, haplotypes, linkage disequilibrium, SRSF2, genetic susceptibility, CD14+CD16+ monocytes
- MeSH terms
- Alzheimer Disease, Black or African American, Exons, Humans, Linkage Disequilibrium, Case-Control Studies, Alternative Splicing, Sequence Analysis, DNA, Protein Structure, Tertiary, Genetic Predisposition to Disease, Protein Isoforms, Polymorphism, Single Nucleotide, White People, Genetic Association Studies, Sialic Acid Binding Ig-like Lectin 3
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