SNP (single nucleotide polymorphism) testing is a core technology for revealing individual genetic differences, predicting disease risk, and guiding precision medicine. It is particularly crucial for early screening of complex diseases such as breast cancer and Alzheimer's disease. However, its development faces multiple challenges: how to select clinically valuable sites from a vast array of mutations? How to balance testing throughput, cost, and accuracy? How to overcome the high barriers of clinical sample validation and regulatory submission?
To assist in the development of precision medicine SNP products, this article systematically reviews the entire process of SNP detection kit development: from disease target screening and technical route optimization to clinical compliance declaration, and deeply analyzes the key steps and technical points.
1. Determine target disease and SNP site
1. Disease selection
▲ Choose diseases with high incidence or clear genetic associations (such as breast cancer, Alzheimer's disease, cardiovascular disease, etc.).
▲ Give priority to diseases for which genetic screening is supported by existing clinical guidelines (such as BRCA1/2 genes and breast cancer).
2. SNP screening and verification
Literature and database mining:
▲ Use GWAS databases (such as the NHGRI-EBI GWAS Catalog), ClinVar, dbSNP, etc. to screen SNPs that are significantly associated with the disease.
▲ Focus on functional sites: such as missense mutations in coding regions (rsID), regulatory regions (promoters, enhancers) or non-coding RNA-related sites.
Functional verification:
Predict the biological impact of SNPs through in vitro experiments (such as luciferase reporter gene) or bioinformatics tools (PolyPhen-2, SIFT).
-Crowd Applicability:
- Confirm the allele frequency of SNP in the target population (refer to the 1000 Genomes Project, gnomAD database), and avoid selecting rare sites (MAF<1%可能影响检测意义）。
2. Technical route selection
1. Detection method selection
▲ A small number of SNPs (<10个）：
- qPCR method: TaqMan probe (specific primers and probes need to be designed), ARMS-PCR (allele-specific amplification).
- HRM (High Resolution Melting): Suitable for known mutation sites, low cost but limited resolution.
▲ Medium throughput (10-100):
-Microfluidic chip: Customized SNP typing chip, suitable for known panels.
- MMCA (Multi-color Melting Curve Analysis): Specific primers and probes need to be designed, and multiple fluorescence channels are used to detect 10 to dozens of SNPs.
-Multiplex PCR+NGS: High flexibility through target region capture combined with next-generation sequencing.
▲ High throughput (>100):
- Whole genome arrays (such as the Illumina Global Screening Array): These are more expensive but can cover multiple disease loci.
2. Technology verification and optimization
▲ Specificity and sensitivity:
Verify typing accuracy using standards of known genotype (e.g., Coriell cell line).
Test for cross-reactivity (e.g., adjacent SNPs or homologous sequence interference).
▲ Anti-interference ability:
Simulate clinical sample conditions (e.g., inhibitors in blood, varying DNA concentrations/purities).
Repeatability:
Repeat the test within the same batch and between different batches and calculate the CV value (generally required<5%）。
3. Kit Design and Production (qPCR Method)
1. Core component development
▲ Primer/probe design:
Use tools such as Primer-BLAST and Beacon Designer to avoid primer dimers or nonspecific binding.
▲ Internal control system:
Endogenous pair: Test sample quality (such as human β-globin gene).
Positive/Negative Controls: Contains homozygous/heterozygous genotype standards.
2. Kit Composition
Master reaction mix (premixed enzyme, dNTPs, buffer), primer/probe mix, controls, DNA extraction reagent (optional), instruction manual (including data analysis thresholds).
IV. Clinical Validation and Performance Evaluation
1. Sample Collection
Cooperate with hospitals to obtain clinical samples (ethical approval required), covering different genotypes (wild type, heterozygous, homozygous variants), with a sample size of at least 200 cases.
2. Performance index test
- Accuracy: Comparison with the gold standard method (such as Sanger sequencing) and calculation of the coincidence rate (>99%).
- Limit of Detection (LoD): Determine the lowest DNA input amount (e.g. 1 ng/μL).
- Anti-interference test: Add common inhibitors (such as heparin, hemoglobin).
3. Data Analysis and Reporting
- Develop automated analysis software that outputs easily readable results (e.g., “high risk/medium risk/low risk”) that comply with CLIA or ISO standards.
V. Regulatory Declaration and Quality Control
1. Regulatory Path
China: For Class III medical devices (high risk), performance evaluation, clinical data, and GMP certification must be submitted.
2. Manufacturing Quality Control (GMP)
- Establish ISO 13485 quality management system, audit raw material suppliers, and batch testing (such as sterility and sensitivity).
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