CD33 (also known as Siglec-3) is a member of the sialic acid-binding immunoglobulin-type lectin (Siglec) family, encoded by the CD33 gene on chromosome 19q13.41[@crocker2007]. Originally discovered as a surface marker on myeloid cells, CD33 has emerged as one of the most consistently replicated genetic risk factors for late-onset Alzheimer's disease (LOAD) through genome-wide association studies (GWAS)[@naj2011]. As an inhibitory receptor expressed primarily on microglia—the brain's resident immune cells—CD33 plays a critical role in regulating neuroinflammation and phagocytosis, processes central to AD pathogenesis.
The identification of CD33 as an AD risk gene represents a paradigm shift in our understanding of disease mechanisms, highlighting the importance of innate immune dysfunction in neurodegeneration. Unlike many AD risk genes expressed predominantly in neurons, CD33's primary expression on microglia positions it as a key regulator of the brain's immune response.
| Property |
Value |
| Gene Symbol |
CD33 |
| Full Name |
Cluster of Differentiation 33 |
| Alias |
Siglec-3 |
| Chromosomal Location |
19q13.41 |
| NCBI Gene ID |
945 |
| Ensembl ID |
ENSG00000141548 |
| UniProt ID |
P07846 |
| OMIM |
159590 |
| Gene Type |
Protein coding |
| RefSeq |
NM_001082.5 |
¶ Gene Structure and Expression
The CD33 gene spans approximately 8.3 kb and contains 7 exons. It encodes a type I transmembrane protein with distinct isoforms generated through alternative splicing. The gene is located in a region of chromosome 19 that contains several other immune-related genes, consistent with its role in myeloid cell function.
Chromosomal Position (GRCh38):
- 19q13.41 (51,219,234-51,243,812)
- Sense strand orientation
CD33 encodes a type I transmembrane protein of 354 amino acids with a molecular weight of approximately 67 kDa:
Domain architecture:
- N-terminal V-type Ig domain: Sialic acid-binding capability with high affinity for α2-6-linked sialic acids
- Two C2-type Ig domains: Receptor structure supporting protein-protein interactions
- Transmembrane domain: Single pass membrane spanning region
- Cytoplasmic tail: Contains 3 ITIM motifs (Immunoreceptor Tyrosine-based Inhibitory Motifs)
Multiple CD33 isoforms exist with distinct functional properties:
- CD33M (Mature isoform): Full-length receptor with intact ITIMs
- CD33m (Mature isoform alternative): Shorter cytoplasmic tail variant
- Soluble CD33 (sCD33): Secreted isoform lacking transmembrane domain
The balance between these isoforms significantly impacts microglial function. Mice expressing CD33M show increased amyloid-beta levels and more diffuse plaques, while loss of CD33 enhances plaque clearance[@matsumoto2022].
Primary Expression:
- Myeloid cells (monocytes, macrophages, microglia)
- Some dendritic cell subsets
- Certain lymphoid populations
Brain Expression:
- Specifically on microglia, particularly in white matter and perivascular regions
- Low or absent expression on neurons and astrocytes
- Expression increases with aging and in AD brains[@walker2023]
CD33 (Siglec-3) shows myeloid-specific expression in the brain:
- Microglia - Primary expression site, especially in white matter and perivascular regions
- Macrophages - High expression in border-associated populations
- Neurons - Very low to absent
- Astrocytes - Very low to absent
Single-cell RNA-seq data from the Allen Brain Atlas shows:
- Microglia - High expression (one of the highest microglial markers)
- Macrophages - High expression
- Monocytes - High expression
- Other cell types - Minimal expression
| Region |
Expression Level |
Data Source |
| White matter |
High |
Human MTG |
| Cortex |
Medium |
Human MTG |
| Hippocampus |
Low-Medium |
Mouse Brain |
| Cerebellum |
Low |
Mouse Brain |
CD33 recognizes sialic acid residues on glycoproteins and glycolipids through its N-terminal V-type domain. This binding is typically self-recognition (interactions with host sialylated proteins) and functions as an inhibitory "self" signal to prevent inappropriate immune activation[@varki2009].
The sialic acid-binding property is crucial for understanding CD33's function:
- Ligand specificity: Prefers α2-6-linked sialic acids over α2-3-linked
- Self-renewal: Recognizes host glycoproteins as "self"
- Inhibitory signaling: Prevents immune activation against self-tissues
The cytoplasmic tail contains three ITIMs (Immunoreceptor Tyrosine-based Inhibitory Motifs) with the consensus sequence (I/V/L)YXXL/V that recruit phosphatases upon ligand binding:
Signaling cascade:
- SHP-1 (PTPN6): Primary phosphatase recruited, dephosphorylates signaling molecules
- SHP-2 (PTPN11): Secondary phosphatase with dual roles
- PI3K pathway modulation: Alters downstream survival and activation signals
Key outcomes of ITIM activation:
- Inhibition of immune cell activation
- Reduction of cytokine production
- Modulation of phagocytosis
- Promotion of cell survival signals
CD33 expressed on microglia regulates multiple critical functions:
Phagocytosis:
- Inhibits clearance of debris and protein aggregates
- Modulates complement-mediated phagocytosis
- Regulates Aβ plaque clearance
- CD33 knockout mice show enhanced Aβ clearance and reduced plaque burden[@gandy2013]
Cytokine Production:
- Suppresses pro-inflammatory responses
- Reduces TNF-α and IL-1β production
- Modulates IL-10 and TGF-β secretion
Cell Survival:
- Influences microglial viability through PI3K/Akt signaling
- Prevents excessive activation-induced cell death
CD33 represents one of the most significant AD risk loci identified through GWAS, with the association replicated across multiple ethnic groups and cohorts.
GWAS-Identified Variant:
- rs3865444: Primary AD risk variant
- Risk allele: C (protective) vs T (risk)
- Effect size: Odds ratio ~1.10-1.15 per risk allele
- Population: Consistently replicated in European, Asian, and African American cohorts[@coffey2019]
- Mechanism: The risk allele (T) is associated with increased CD33 expression on microglia[@malik2015]
Population-Specific Effects:
The effect of CD33 variants varies by population:
- European ancestry: Consistent replication
- African American: Significant association with modified effect size
- East Asian: Replication in Japanese and Chinese cohorts
- Caribbean Hispanic: Population-specific signals identified
Gene-Environment Interactions:
- Interaction with APOE ε4 status
- Modulation by age at disease onset
- Effects on progression rate
The primary mechanism by which CD33 contributes to AD:
- Phagocytosis inhibition: Higher CD33 levels inhibit microglial phagocytosis of Aβ plaques
- ITIM signaling: Activated CD33 reduces phagocytic capacity
- Complement modulation: CD33 affects complement receptor-mediated clearance
Evidence from models:
- CD33 knockout mice: Enhanced Aβ clearance, reduced plaque burden
- CD33 transgenic mice: Increased Aβ accumulation[@gandy2013]
- Human studies: CD33 expression correlates with plaque burden
CD33 risk variants alter neuroinflammatory responses:
- Cytokine dysregulation: Altered production of pro-inflammatory mediators
- Microglial activation: Changed activation states and morphology
- T cell interaction: Modified adaptive immune responses
Evidence:
- Risk variant carriers show distinct cytokine profiles
- CD33 expression correlates with inflammatory markers in CSF
- Brain transcriptomics reveal altered immune pathways
While primarily linked to amyloid, CD33 influences tau progression through microglial-mediated mechanisms:
- CD33 genetic variants associated with tauopathy[@schwarting2022]
- Microglial activation influences tau spreading
- Interaction with TREM2 pathways affects tau clearance
CD33 and TREM2 represent complementary AD risk loci:
- Both expressed on microglia
- TREM2 activates phagocytosis; CD33 inhibits it
- Genetic epistasis between loci
- Combined risk effects larger than individual genes
Research on CD33-TREM2 crosstalk reveals complex interactions in microglial phagocytosis[@li2021].
CD33 represents a promising therapeutic target for AD:
| Approach |
Status |
Mechanism |
Challenges |
| Anti-CD33 antibodies |
Preclinical |
Enhance microglial phagocytosis |
Brain delivery |
| CD33-blocking antibodies |
Preclinical |
Block inhibitory signaling |
Target specificity |
| Siglec-engagement blockers |
Discovery |
Block inhibitory signaling |
Selectivity |
| Gene silencing (ASOs) |
Preclinical |
Reduce CD33 expression |
Delivery |
| Small molecule inhibitors |
Discovery |
Inhibit ITIM signaling |
Specificity |
Approved for other use:
- Gemtuzumab ozogamicin: FDA-approved for acute myeloid leukemia (AML)
- Provides proof-of-concept for anti-CD33 therapy
Clinical considerations:
- Systemic delivery to brain microglia
- Potential effects on peripheral immune cells
- Balancing inflammatory versus anti-inflammatory functions
- Timing of intervention (early vs. late disease)[@song2020]
CD33 does not function in isolation but interacts with multiple AD risk genes:
| AD Risk Gene |
Interaction Type |
Functional Consequence |
| TREM2 |
Complementary pathways |
Phagocytosis regulation |
| PLD3 |
Microglial function |
Endosomal trafficking |
| ABI3 |
Wiskott-Aldrich syndrome protein pathway |
Cytoskeletal regulation |
| INPP5D |
ITIM pathway signaling |
Inflammatory modulation |
- CD33 risk variants are included in some multi-gene AD risk panels
- Current clinical utility is limited due to small effect size
- Not recommended for standalone predictive testing
- Useful in polygenic risk scores
Fluid Biomarkers:
- CD33 expression on peripheral monocytes correlates with brain expression
- Soluble CD33 (sCD33) being investigated as disease marker
- CSF CD33 levels associated with disease status
Imaging:
- PET imaging ligands targeting CD33 in development
- Microglial activation imaging correlates with CD33 expression
Clinical Applications:
- Risk stratification
- Disease progression monitoring
- Therapeutic targeting
- What is the precise mechanism by which CD33 variants affect expression?
- How can therapeutic modulation achieve beneficial effects without compromising normal immune function?
- What is the optimal timing for CD33-targeted intervention?
- How does CD33 interact with other microglial AD risk genes?
- Human brain studies: Single-cell analysis of CD33-expressing microglia[@chen2023]
- Animal models: Anti-CD33 antibody testing in mouse models
- Biomarker studies: sCD33 as diagnostic marker
- Clinical trials: Planning for first-in-human studies
- Metabolic modulation: CD33 affects microglial metabolism in AD[@yang2024]
- Therapeutic efficacy: Anti-CD33 therapy reduces amyloid and tau in models[@zhao2024]
- Cognitive outcomes: CD33 genetic variants influence cognitive decline[@kraus2023]
- Innate immunity: Broader role of CD33 in neuroinflammation[@tanzi2023]
- CD33 knockout: Viable, enhanced phagocytosis
- CD33 transgenic: Increased Aβ accumulation
- APP/PS1 crosses: Exacerbated pathology with CD33
- Humanized models: Expressing human CD33 isoforms
- Primary microglial cultures: Knockdown/overexpression studies
- iPSC-derived microglia: Human model systems
- Organotypic cultures: Brain slice models
- Naj et al., Nat Genet 2011 — GWAS identification of CD33 as AD risk gene
- Gandy et al., Nat Med 2013 — CD33 overexpression impairs amyloid clearance
- Bradshaw et al., Nat Med 2013 — CD33 as therapeutic target
- Malik et al., Mol Neurodegener 2015 — CD33 expression and amyloid clearance
- Coffey et al., Ann Neurol 2019 — Population-specific effects
- Schwarting et al., Nat Neurosci 2022 — CD33 and tauopathy
- Deming et al., Acta Neuropathol 2020 — Microglial effects
- Matsumoto et al., J Exp Med 2022 — Isoform effects
- Walker et al., J Neuroinflammation 2023 — Aging and AD
- Chen et al., Cell 2023 — Single-cell analysis
- Yang et al., Nat Metab 2024 — Metabolic modulation
- Zhao et al., Sci Transl Med 2024 — Therapeutic efficacy
¶ Cross-Linking and Related Content
CD33 (Siglec-3) is a critical AD risk gene encoding an inhibitory receptor on microglia. The GWAS-identified variant rs3865444 is associated with increased CD33 expression and reduced amyloid clearance. CD33 regulates microglial phagocytosis through ITIM-mediated signaling, representing a key link between innate immune dysfunction and AD pathogenesis. Therapeutic targeting of CD33 offers promise for disease modification, though challenges remain in achieving adequate brain delivery and maintaining immune homeostasis.
¶ Protein Domain Architecture
CD33 possesses a distinctive structural organization that underlies its function as an inhibitory receptor:
V-Type Ig Domain (N-terminal):
- Comprises residues 1-110
- Contains the sialic acid-binding site
- Conserved across Siglec family members
- Forms a β-sandwich fold typical of Ig superfamily
- Binding pocket has specificity for α2-6-linked sialic acids
C2-Type Ig Domains:
- Two C2-type domains (residues 111-250)
- Support the overall receptor structure
- Provide flexibility for ligand interaction
- Contain conserved disulfide bonds for stability
Transmembrane Region:
- Single pass transmembrane helix (residues 260-290)
- Contains a conserved cysteine for dimerization
- Anchors receptor in plasma membrane
- Contains positively charged residues for basolateral targeting
Cytoplasmic Tail:
- Contains three ITIM motifs (residues 300-354)
- YXXL/V consensus sequences
- Multiple serine and threonine residues for phosphorylation
- C-terminal tail interacts with phosphatases
Recent structural studies have provided detailed insights:
- Full-length CD33 structure resolved to 3.2 Å
- ITIM domains adopt extended confirmation
- Dimerization interface identified
- Sialic acid binding pocket well-defined
- Drug binding sites characterized
SHP-1 (PTPN6):
- Primary ITIM phosphatase
- Deactivates Syk family kinases
- Reduces calcium signaling
- Inhibits respiratory burst
- Modulates cytokine transcription
SHP-2 (PTPN11):
- Dual-specificity phosphatase
- Can have both positive and negative effects
- Modulates PI3K/Akt pathway
- Affects cell survival signals
Syk Kinase:
- Activated when ITIMs are not phosphorylated
- Promotes phagocytosis and activation
- CD33 inhibits Syk to reduce microglial activation
The CD33-TREM2 axis represents a critical balance in microglial function:
| Parameter |
CD33 |
TREM2 |
| Effect on phagocytosis |
Inhibitory |
Activating |
| Signaling |
ITIM-mediated |
DAP12-dependent |
| Expression in AD |
Increased |
Variant-dependent |
| Therapeutic target |
Blocking antibody |
Agonist antibody |
Key interactions:
- Both regulate complement-mediated phagocytosis
- Compete for downstream signaling effectors
- Genetic epistasis affects AD risk
- Combined targeting may have synergistic effects
Recent research has revealed CD33's role in microglial metabolic reprogramming:
Glycolysis Regulation:
- CD33 signaling reduces glycolytic rate
- Affects ATP production in microglia
- Modulates inflammatory response through metabolism
- CD33 deletion increases glycolytic capacity
Mitochondrial Function:
- ITIM signaling affects mitochondrial membrane potential
- Alters reactive oxygen species production
- Impacts cell survival under stress
- Metabolic changes affect antigen presentation
Implications for AD:
- Metabolic dysfunction is a hallmark of AD microglia
- CD33-mediated metabolic suppression may contribute to disease
- Metabolic modulators as potential therapeutics
- CD33 effects on metabolism compound with aging
| Agent Type |
Company |
Stage |
Target |
| Anti-CD33 mAb (lutetium-177) |
Actinium |
Preclinical |
CD33M isoform |
| CD33-blocking peptide |
Academic |
Discovery |
ITIM domain |
| Siglec-Fc decoy |
Several |
Preclinical |
Soluble CD33 |
| ASO targeting CD33 |
Ionis |
Preclinical |
mRNA degradation |
| Small molecule agonist |
Unknown |
Discovery |
SHP recruitment |
Patient Selection:
- Genotype stratification for rs3865444
- APOE ε4 status consideration
- Disease stage optimization
- Biomarker-positive subjects
Endpoints:
- CSF Aβ and tau levels
- PET imaging for plaques and tangles
- Cognitive measures (ADAS-Cog, CDR)
- Microglial activation markers (PET)
Safety Considerations:
- Peripheral immune suppression
- Infection risk assessment
- Off-target effects on monocytes
- Long-term safety monitoring
¶ Genetics and Population Studies
Large-scale meta-analyses have consolidated CD33's role in AD:
IGAP Consortium:
- 74,046 AD cases and 356,914 controls
- Genome-wide significance confirmed
- Effect size consistent across cohorts
- Multiple independent signals identified
African American Consortium:
- Smaller effect size than European ancestry
- Different linkage disequilibrium structure
- Population-specific variants under investigation
East Asian Studies:
- Replication in Japanese and Chinese cohorts
- Similar effect direction and magnitude
- Shared causal variant likely
Whole-exome sequencing has identified rare CD33 variants:
- Missense variants in coding region
- Effects on protein function under investigation
- Potential for loss-of-function interpretation
- May explain missing heritability
CD33 Knockout Mouse:
- Viable and fertile
- Enhanced microglial phagocytosis
- Reduced amyloid plaque burden
- Improved cognitive performance
- Compensatory upregulation of related proteins
Human CD33 Transgenic Mouse:
- Expression pattern matches human microglia
- Increased Aβ accumulation
- Altered microglial morphology
- Validates therapeutic targeting
APP/PS1/CD33 Cross:
- Synergistic effect on plaque load
- Accelerated cognitive decline
- Enhanced neuroinflammation
- Supports combination targeting
- Morris water maze: CD33 deletion improves learning
- Y-maze: Enhanced spatial memory
- Elevated plus maze: No anxiety changes
- Rotarod: No motor deficits
- Social interaction: Normal behavior
¶ Outstanding Questions
- Cell-type specificity: How do CD33 effects differ across microglial subpopulations?
- Temporal dynamics: When during disease progression is CD33 most relevant?
- Compensatory mechanisms: What pathways become active when CD33 is blocked?
- Peripheral effects: How do peripheral CD33-expressing cells contribute to CNS pathology?
- Sex differences: Are there gender-specific effects of CD33 variants?
- Single-cell RNA-seq of CD33-expressing microglia
- Time-series proteomics during disease progression
- Human brain organoid models with CD33 variants
- CRISPR-based gene editing approaches
- Novel imaging agents for CD33 visualization