Smith-Magenis Syndrome (SMS) Cell Models for Research
Disease Burden and Research Significance
Smith-Magenis Syndrome (SMS) is a rare neurodevelopmental disorder with an estimated prevalence of 1 in 15,000 to 1 in 25,000 live births (WHO, 2023). It is caused by a microdeletion on chromosome 17p11.2 or by pathogenic variants in the RAI1 gene. The syndrome is characterized by intellectual disability, sleep disturbances, behavioral problems (including self-hugging), and distinctive facial features. There is no cure, and management is symptomatic. The clinical impact is significant, with patients requiring lifelong support. Research into SMS is crucial for understanding the molecular mechanisms and developing targeted therapies.
SMS is an ideal model for studying gene dosage effects, chromatin remodeling, and neurodevelopmental pathways. The RAI1 gene encodes a transcription factor involved in circadian rhythm regulation and neuronal differentiation. Public datasets, such as those from NCBI GEO, provide transcriptomic and epigenetic data from patient-derived cells. Open questions include the precise role of RAI1 in sleep-wake cycles and the development of targeted interventions. Gene-edited cell models are essential for functional validation and drug screening.
Core Molecular Pathogenesis
- • Although SMS is not a cancer syndrome, the molecular pathways affected are relevant to cell growth and differentiation. Key pathways include:
- • Circadian rhythm regulation: RAI1 interacts with CLOCK and BMAL1, influencing the expression of clock genes.
- • Chromatin remodeling: RAI1 is involved in histone acetylation and methylation, affecting gene expression.
- • Neuronal differentiation: RAI1 regulates genes involved in synaptic plasticity and neuronal maturation.
- • Apoptosis and cell survival: Dysregulation of RAI1 may affect cell survival pathways, though not directly oncogenic.
| Gene | Frequency (%) | Mutation Type | Functional Effect |
|---|---|---|---|
| RAI1 | ~90% | Deletion or loss-of-function | Haploinsufficiency, reduced transcription factor activity |
| SREBF1 | ~10% | Deletion | Lipid metabolism dysregulation |
| DRG2 | ~10% | Deletion | Neuronal development impairment |
| MYO15A | ~5% | Deletion | Hearing loss |
| TOP3A | ~5% | Deletion | DNA replication stress |
Data from ClinVar and DECIPHER.
- • RAI1 is a transcription factor that regulates multiple signaling networks:
- • Circadian clock network: RAI1 activates CLOCK and BMAL1, leading to expression of PER and CRY genes.
- • Neurotrophin signaling: RAI1 modulates BDNF and NGF pathways, affecting neuronal survival.
- • Wnt signaling: RAI1 may influence beta-catenin activity, impacting cell proliferation.
- • Dopaminergic signaling: RAI1 regulates dopamine receptor expression, relevant to behavioral symptoms.
Key nodes: CLOCK, BMAL1, PER1, CRY1, BDNF, DRD1.
Experimental Model Systems
| Cell Line | Origin | Key Mutations |
|---|---|---|
| SH-SY5Y | Human neuroblastoma | RAI1 wild-type; can be edited |
| HEK293 | Human embryonic kidney | RAI1 wild-type; easy to edit |
| iPSC-derived neurons | Patient-derived | RAI1 deletion or mutation |
| Cerebral organoids | iPSC-derived | RAI1 haploinsufficiency |
Organoids offer a 3D model of brain development and are valuable for studying neuronal migration and synaptic defects.
- • RAI1 knockout mice: Show behavioral and sleep abnormalities similar to SMS.
- • RAI1 haploinsufficient mice: Model the 17p11.2 deletion.
- • Zebrafish with rai1 knockdown: Used for high-throughput drug screening.
- • Patient-derived xenografts (PDX): Not common for SMS, but iPSC-derived organoids can be transplanted into mice for in vivo studies.
- • CRISPR-Cas9 technology enables the creation of isogenic cell lines with precise RAI1 mutations. For example:
- • RAI1 knockout cell lines: Complete loss of function, useful for studying haploinsufficiency effects.
- • RAI1 point mutation knock-in lines: Mimic specific pathogenic variants, such as p.Arg1085Ter.
- • Reporter lines: RAI1 promoter-driven fluorescent reporters to monitor transcriptional activity.
These models are commercially available from various sources and are sequence-verified to ensure accuracy. They accelerate research by providing consistent, reproducible systems for mechanistic studies and drug screening.
Related Disease
| Disease name | Disease type |
|---|
Related Services
Related Products
| Product name | Cat.No. | Species | Gene ID | |
|---|---|---|---|---|
| MFAP4 Knockout HEK293 Cell Line | EDJ-KQ234 | Human | 4239 | Details Get a Quote |
| GRIN2B Knockout HEK293 Cell Line | EDJ-KQ668 | Human | 2904 | Details Get a Quote |
| PCK1 Knockout HEK293 Cell Line | EDJ-KQ841 | Human | 5105 | Details Get a Quote |
| CLOCK Knockout HEK293 Cell Line | EDJ-KQ990 | Human | 9575 | Details Get a Quote |
| FLCN Knockout HEK293 Cell Line | EDJ-KQ1150 | Human | 201163 | Details Get a Quote |
| LLGL1 Knockout HEK293 Cell Line | EDJ-KQ1383 | Human | 3996 | Details Get a Quote |
| SREBF1 Knockout HEK293 Cell Line | EDJ-KQ1869 | Human | 6720 | Details Get a Quote |
| KCNJ12 Knockout HEK293 Cell Line | EDJ-KQ1932 | Human | 3768 | Details Get a Quote |
| TNFRSF13B Knockout HEK293 Cell Line | EDJ-KQ1965 | Human | 23495 | Details Get a Quote |
| PER2 Knockout HEK293 Cell Line | EDJ-KQ2265 | Human | 8864 | Details Get a Quote |
| SHMT1 Knockout HEK293 Cell Line | EDJ-KQ2588 | Human | 6470 | Details Get a Quote |
| CRY1 Knockout HEK293 Cell Line | EDJ-KQ3045 | Human | 1407 | Details Get a Quote |
| BMAL1 Knockout HEK293 Cell Line | EDJ-KQ3060 | Human | 406 | Details Get a Quote |
| DRG2 Knockout HEK293 Cell Line | EDJ-KQ4477 | Human | 1819 | Details Get a Quote |
| FLII Knockout HEK293 Cell Line | EDJ-KQ4610 | Human | 2314 | Details Get a Quote |
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Applications of Gene-Edited Cells
- • Gene-edited cell lines allow researchers to validate the functional impact of RAI1 variants. For example:
- • Knockout of RAI1 in SH-SY5Y cells leads to altered expression of circadian genes, confirming its role.
- • Knock-in of a pathogenic mutation can be used to study the molecular consequences in a controlled background.
- • CRISPR screens can identify genetic modifiers that rescue RAI1 deficiency.
- • Isogenic pairs (wild-type vs. RAI1 knockout) are powerful for drug screening. For instance:
- • Screening compounds that restore circadian rhythm in RAI1-deficient cells.
- • Testing drugs that modulate histone acetylation to compensate for RAI1 loss.
- • Resistance modeling: Not directly applicable, but can be adapted for neurodevelopmental phenotypes.
CRISPR synthetic lethality screens can identify genes that are essential in RAI1-deficient cells but not in wild-type cells. These genes may serve as biomarkers or therapeutic targets. For example, targeting the circadian regulator CK1δ has been shown to rescue sleep defects in SMS models.
Public Data Resources
| Database | URL | Description |
|---|---|---|
| TCGA | https://www.cancer.gov/tcga | Not directly relevant, but provides genomic data for comparison. |
| cBioPortal | https://www.cbioportal.org | Contains cancer genomics data; may include SMS-related genes. |
| DepMap | https://depmap.org | Provides CRISPR screens and dependency data for cancer cell lines; useful for identifying vulnerabilities. |
| GEO | https://www.ncbi.nlm.nih.gov/geo/ | Gene expression datasets from SMS patient samples and models. |
| ClinVar | https://www.ncbi.nlm.nih.gov/clinvar/ | Curated information on RAI1 variants. |
| UniProt | https://www.uniprot.org | Protein information for RAI1. |
Frequently Asked Research Questions
What is the best cell line for studying SMS?
How can I create a RAI1 knockout cell line?
Are there commercially available SMS cell models?
What assays are used to assess circadian rhythm in SMS cells?
Can I use organoids for drug screening?
Key References and Database URLs
| WHO | https://www.who.int |
|---|---|
| NCI | https://www.cancer.gov |
| NCBI Gene | https://www.ncbi.nlm.nih.gov/gene/10743 |
| ClinVar | https://www.ncbi.nlm.nih.gov/clinvar/ |
| DepMap | https://depmap.org |
| GEO | https://www.ncbi.nlm.nih.gov/geo/ |
| UniProt | https://www.uniprot.org/uniprot/Q9Y2S1 |
| DECIPHER | https://www.deciphergenomics.org |