Shanghai Jiaotong University School of Medicine China
Title: Background:Conduct disorder (CD) is a mental disorder diagnosed in childhood or adolescence that presents antisocial behaviors, and is associated with structural alterations in brain. However, whether these structural alterations can distinguish CD from healthy controls (HCs) remains unknown. Here, we quantified these structural differences and explored the classification ability of these quantitative features based on machine learning (ML). Materials and Methods: High-resolution 3D structural m
Ailian Du is the professor in Shanghai Jiotong University School of Medicine, China.
To study the heteroplasmy and phenotype correlations of mtDNA 3243A>G mutation in 7 Han Chinese families using restrict fragment length polymorphism (RFLP) and pyrosequencing (Pyro). Methods Seven probands were pathologically and genetically diagnosed as mitochondrial diseases with 3243A>G mutation. The clinical phenotypes were studied in 39 maternal family members. 5 were diagnosed as mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes (MELAS), 2 with pure mitochondrial myopathy (MM), 1 with early neuropathy, ataxia, and retinitis pigmentosa (NARP) syndrome. Six with diabetes, 3 with hearing loss, and 20 family members are normal. Blood DNA from 37 members were detected with RFLP and pyrosequencing. mtDNA 3243A>G heterogeneity were analyzed. Results Mutation load in blood of 5 MELAS patients were 15.7% by RFLP (29% by Pyro), 12.8% (19% by Pyro), 40.1% (53% by Pyro), 25.8% (30% by Pyro), 28.3% (59% by Pyro). Mutation load in 2 MM patients were 13.7% (29% by Pyro) and 76.8% (79% by Pyro), and that in the NARP patient was 20.0% (57% by Pyro). Six family members with diabetes were range from 3.7%-7.6% (0%-14% by Pyro). Three family members with hearing loss were range from 4%-18.2% (6%-18%). The mutation load of 14 normal family members range from 2% to 12.5% (0%-5% by Pyro). Detection by Pyro is more accurate than RFLP when mutation load is lower than 10%. The mutation load is higher in those earlier age of onset. Conclusion Pyrosequencing is more reliable when mutation load is lower than 10%. The mutation load is negatively correlate to the age of onset in this research.