MATERIALS AND METHODS: Eight hundred and twenty-eight subjects (404 PD patients, and 424 age and gender-matched control subjects without neurological disorders) were recruited. Genotyping was done by Taqman® allelic discrimination assay on an Applied Biosystems 7500 Fast Real-Time PCR machine.
RESULTS: The heterozygous A419V genotype was found in only 1 patient with PD, compared to 3 in the control group (0.4% vs 1.3%), giving an odds ratio of 0.35 (95% confidence interval (CI), 0.01 to 3.79; P = 0.624).
CONCLUSION: A419V is not an important LRRK2 risk variant in our Asian cohort of patients with PD. Our data are further supported by a literature review which showed that 4 out of 6 published studies reported a negative association of this variant in PD.
METHOD: Targeted sequencing of fourteen genes panel was performed to identify the mutations in 29 OI patients with type I, III, IV and V disease. The mutations were determined using Ion Torrent Suite software version 5 and variant annotation was conducted using ANNOVAR. The identified mutations were confirmed using Sanger sequencing and in silico analysis was performed to evaluate the effects of the candidate mutations at protein level.
RESULTS: Majority of patients had mutations in collagen genes, 48% (n = 14) in COL1A1 and 14% (n = 4) in COL1A2. Type I OI was caused by quantitative mutations in COL1A1 whereas most of type III and IV were due to qualitative mutations in both of the collagen genes. Those with quantitative mutations had milder clinical severity compared to qualitative mutations in terms of dentinogenesis imperfecta (DI), bone deformity and the ability to walk with aid. Furthermore, a few patients (28%, n = 8) had mutations in IFITM5, BMP1, P3H1 and SERPINF1.
CONCLUSION: Majority of our OI patients have mutations in collagen genes, similar to other OI populations worldwide. Genotype-phenotype analysis revealed that qualitative mutations had more severe clinical characteristics compared to quantitative mutations. It is crucial to identify the causative mutations and the clinical severity of OI patients may be predicted based on the types of mutations.