Objective To investigate the genotype and phenotype in patients with leber congenital amaurosis (LCA), and offer accurate genetic counseling and prenatal diagnosis for those families. Methods Three LCA patients and their parents were recruited for this study and received detailed collection of medical history and family history from March to August 2016. The three patients received fundus fluorescein angiography examination and their parents received slit-lamp microscope and indirect ophthalmoscopy examinations. DNA was extracted from the patients and their family members. Whole-exome sequencing method was used for genetic diagnosis and typing of the three LCA patients and their parents. Results The three patients with different clinical features had a definite clinical diagnosis of LCA. Patient 1 showed pale disc, attenuated vessels aroud the optic disc and the salt-and-pepper appearance of the retina, had the homozygous c.744.745insT (p.249, L>Ffs4) mutation inSPATA7. Patient 2 showed optic disc pallor and attenuated retinal vessels, had the heterozygous c.535G>A, p.A179T mutation inWFS1. Patient 3 showed pale disc, atrophic macular and retinal and choroidal degeneration, had the heterozygous mutation in CRB1, RPGRIP1, SPATA7. Conclusion LCA has characteristics of genetic heterogeneity and clinical and phenotypic diversity.
Adverse drug reaction (ADR) signal detection serves as a core component of pharmacovigilance, with its methodological framework continuously enriched by advancements in data science and artificial intelligence. This article systematically reviews and elaborates on the principles, implementation pathways, and application scenarios of mainstream ADR signal detection methods, including traditional frequentist methods such as the proportional reporting ratio (PRR), reporting odds ratio (ROR), and the comprehensive standard method; Bayesian probabilistic models such as the Bayesian confidence propagation neural network (BCPNN) and the multi-item gamma-Poisson Shrinker (MGPS); as well as machine learning and data mining techniques such as association rules, random forest, and zero-inflated models. By systematically comparing the advantages, limitations, applicable conditions, and empirical studies of these methods in the monitoring of both traditional Chinese medicine and chemical drugs, this study aims to provide researchers and regulatory agencies with a comprehensive methodological reference framework to facilitate the selection, optimization, and integrated application of detection approaches. Moving forward, improving data quality and promoting multi-technology collaboration will be crucial directions for enhancing the sensitivity and specificity of ADR signal detection, thereby supporting more precise decision-making in clinical medication safety.