A recent genome wide associated study in European descent population identified the association of Atrial fibrillation (AF) risk with a single nucleotide polymorphism (SNP) in SCN10A. The aim of this study was to evaluate whether SCN10A polymorphisms are associated with AF risk in the Chinese Han population. A total of 2,300 individuals of Chinese Han origin were recruited and three potentially functional SNPs were genotyped. Logistic regression models were utilized to calculate odds ratios (ORs) at a 95% confidence intervals (CIs). Logistic regression analysis in an additive genetic model revealed that one SNP in SCN10A (rs6771157) was associated with an increased risk of AF (adjusted OR = 1.20, 95% CI: 1.06 - 1.36, P = 0.003). Stratification analysis of several main AF risk factors indicated that the risk associations with rs6771157 were not statistically different among different subgroups. In summary, our study suggests the possible involvement of the SCN10A variant in AF development in Chinese Han populations. Further biological function analyses are required to confirm our finding.

Background The association between free triiodothyronine (FT3) and long-term prognosis in dilated cardiomyopathy (DCM) patients has not been evaluated. The purpose of this study was to determine whether the level of FT3 could provide prognostic value in patients with DCM. Methods Data of consecutive patients diagnosed with DCM were collected from October 2009 to December 2014. FT3 was measured by fluoroimmunoassay. Other biochemical markers, such as free thyroxin (FT4), thyroid-stimulating hormone, red blood cell, hemoglobin, blood urea nitrogen, and serum creatinine, were tested at the same time. Follow-up was performed every 3 months. The primary endpoint was all-cause mortality. Pearson analysis was used to evaluate the correlation of FT3 and other lab metrics with DCM patients’ prognosis. The association of long-term mortality in DCM and FT3 was compared using Cox hazards model. Results Data of 176 patients diagnosed with DCM were collected. Of them, 24 patients missed FT3 values and six patients were lost to follow-up. Altogether, data of 146 patients were analyzed. During the median follow-up time of 79.9 (53.5–159.6) months, nine patients lost, 61 patients died (non-survival group), and 85 patients survived (survival group). FT3 was significantly lower in non-survival group than that in survival group (3.65 ± 0.83 pmol/L vs. 4.36 ± 1.91 pmol/L; P = 0.003). FT3 also showed a significantly positive correlation with red blood cell and hemoglobin, negatively correlated with age, blood urea nitrogen and serum creatinine ( P < 0.05), respectively. Patients in the group of lower FT3 levels (FT3 ≤3.49 pmol/L) suffered from a higher risk of all-cause mortality ( P for log-rank = 0.001). In multivariate Cox regression analysis, FT3 level was significantly associated with all-cause mortality (hazard ratio: 0.70, 95% confidence interval 0.52–0.95, P for trend = 0.021). Conclusion Low levels of FT3 were associated with increased all-cause mortality in patients with DCM.

Preimplantation genetic testing (PGT), the determination of an embryo's constituency before implantation, is becoming more and more common in clinic and there has been a gradual shift in technology towards next generation sequencing (NGS). Numerous biopsy samples such as a blastomere of cleavage stage embryo, trophectoderm of blastocyst and polar bodies as well as non-invasive or low-invasive samples such as blastocoele fluid and embryo's culture medium can be analyzed with different NGS platforms namely Roche, Illumina and Ion torrent. NGS technology has been validated and is now clinically applied to detect aneuploidies, partial or segmental aneuploidies, chromosomal aberrations including imbalanced translocations, inversion, deletion, duplication insertion and mosaicism, triploidy and single gene disorder which are often responsible for infertility and can be associated with spontaneous abortions and fetal malformations or diseases. Comprehensive chromosomal screening for all 24 chromosomes together with single gene disorder detection can be achieved at the same time in a single run using NGS and the analysis of multiple samples with different indication can be done on a single chip. NGS has the ability to detect numerical, structural and genetic abnormalities at a low cost with high efficiency and accuracy.

No abstract