Different effects of maternal homocysteine concentration, MTHFR and MTRR genetic polymorphisms on the occurrence of fetal aneuploidy.

RESEARCH QUESTION: Do maternal homocysteine (Hcy) concentrations, MTHFR and MTRR genes have effects on the occurrence of fetal aneuploidy? DESIGN: A total of 619 aneuploidy mothers and 192 control mothers were recruited in this study. Differences in distributions of maternal MTHFR 677C>T, MTHFR 1298A>C and MTRR 66A>G genetic polymorphisms and maternal Hcy concentrations between aneuploidy mothers and control mothers were analysed. RESULTS: The maternal MTHFR 677C>T polymorphism was found to be a risk factor for the occurrence of many fetal non-mosaic aneuploidies studied here, including trisomies 13, 15, 16, 18, 21, 22, TRA and TS. The maternal MTHFR 1298A>C polymorphism was found to be a risk factor specifically associated with the occurrence of fetal trisomy 15 and fetal TS. The maternal MTRR 66A>G polymorphism was found to be a risk factor only specifically associated with the occurrence of fetal trisomy 21. The Hcy concentrations of mothers of trisomies 22, 21, 18, 16, 15 and TS fetuses were significantly higher than the Hcy concentrations of control mothers. CONCLUSIONS: Overall, data suggested an association between these maternal polymorphisms and the susceptibility of fetal non-mosaic trisomy and Turner syndrome. However, these three maternal polymorphisms had different associations with the susceptibility of different fetal aneuploidies, and the elevated maternal Hcy concentration appeared to be a likely risk factor for fetal Turner syndrome and fetal trisomies.

Partial least squares based identification of Duchenne muscular dystrophy specific genes.

Large-scale parallel gene expression analysis has provided a greater ease for investigating the underlying mechanisms of Duchenne muscular dystrophy (DMD). Previous studies typically implemented variance/regression analysis, which would be fundamentally flawed when unaccounted sources of variability in the arrays existed. Here we aim to identify genes that contribute to the pathology of DMD using partial least squares (PLS) based analysis. We carried out PLS-based analysis with two datasets downloaded from the Gene Expression Omnibus (GEO) database to identify genes contributing to the pathology of DMD. Except for the genes related to inflammation, muscle regeneration and extracellular matrix (ECM) modeling, we found some genes with high fold change, which have not been identified by previous studies, such as SRPX, GPNMB, SAT1, and LYZ. In addition, downregulation of the fatty acid metabolism pathway was found, which may be related to the progressive muscle wasting process. Our results provide a better understanding for the downstream mechanisms of DMD.