Objective: To explore the association between the HLA antibody positivity rate in female blood donors and pregnancy history, number of pregnancies, interval from the last pregnancy to blood donation, and age, to identify associated variables using a univariate generalized additive model (GAM), and to further analyze the predictive role of characteristic variables for HLA antibody positivity using a random forest model. Methods: HLA antibody detection was performed on 391 female blood donors using the Luminex immunomagnetic bead method. The correlation between pregnancy-related factors and HLA antibodies was analyzed using the Chi-square test. Based on R software, a univariate GAM was first constructed to analyze the association types between characteristic variables and the HLA antibody positivity rate, followed by the construction of a random forest model to evaluate the predictive value of the variables. Results: Among the 391 female blood donors without a transfusion history, the overall HLA antibody positivity rate was 26.34%. The positivity rate in donors with a pregnancy history was significantly higher than that in those without (30.09% vs 9.72%, P<0.05), and HLA antibody positivity rate increased linearly with the number of pregnancies (P<0.05). In the univariate GAM, age and number of deliveries exhibited a non-linear association with the HLA antibody positivity rate (the positivity rate increased sharply between 25-35 years of age and stabilized after 3 deliveries). Besides, the interval from the last pregnancy to blood donation showed a linear association with the HLA antibody positivity rate, and the positivity rate decreased as the interval prolonged (P<0.05). In the random forest model, age (mean decrease gini=29.26) and interval from the last pregnancy to blood donation (mean decrease gini=22.02) were core predictive variables: age was more conducive to identifying positive samples, while the interval from the last pregnancy to blood donation was more helpful for excluding negative samples. The number of deliveries (mean decrease accuracy=16.98) made a significant contribution to predicting positive samples, whereas the number of abortions had no impact. The model had an AUC of 0.583 (95% CI: 0.593 8-0.770 2), indicating a certain predictive value. Conclusion: The associated variables identified by the univariate GAM model, including age, interval from the last pregnancy to blood donation, and number of deliveries, provide a basis for key variables in the random forest model. All three variables have predictive value for HLA antibody positivity, which can provide evidence-based support for personalized transfusion management and stratified screening of female blood donors in this region.

OBJECTIVE: To explore the genetic etiology of 46 Chinese pedigrees affected with Hereditary multiple exostoses (HME) and provide genetic counseling and reproductive intervention. METHODS: Whole-exome sequencing and Sanger sequencing were carried out on 87 patients from the 46 pedigrees to analyze the variants of EXT1 and EXT2 genes. Pathogenicity of the variants was assessed based on the guidelines from the American College of Medical Genetics and Genomics and Association for Molecular Pathology (ACMG/AMP). Prenatal diagnosis and preimplantation genetic testing (PGT) were provided for couples with identified pathogenic mutations. This study was approved by the Medical Ethics Committee of the hospital (Ethics No.: LL-SC-SG-2014-010). RESULTS: In total 17 and 22 pathogenic variants were respectively identified in the EXT1 and EXT2 genes, among which 5 EXT1 and 12 EXT2 variants were unreported previously. Three patients with no family history were found to harbor de novo variants of the EXT1 gene. Twenty nine couples had opted for PGT or underwent prenatal diagnosis following natural conception, and 17 healthy babies were born. CONCLUSION This study has clarified the genetic etiology of 45 HME pedigrees and identified 17 novel variants, which has enriched the mutational spectrum of the EXT1 and EXT2 genes. Reproductive intervention through PGT and prenatal diagnosis have prevented the recurrence of HME in these families.
Humans ; Female ; Male ; Pedigree ; Exostoses, Multiple Hereditary/diagnosis* ; N-Acetylglucosaminyltransferases/genetics* ; Adult ; Exostosin 1 ; Asian People/genetics* ; Genetic Testing ; Exostosin 2 ; Mutation ; China ; Prenatal Diagnosis ; Pregnancy ; Genetic Counseling ; Preimplantation Diagnosis ; Exome Sequencing ; East Asian People

ObjectiveTo observe the pharmacodynamic effects of Cinnamomi Cortex on the incretin effect in the rat model of diabetes mellites （DM） induced by streptozotocin （STZ） and explore the underlying mechanism from glucagon-like peptide-1 （GLP-1） and dipeptidyl peptidase-4 （DPP-4）. MethodForty SD rats were randomly assigned into blank， model， sitagliptin （0.1 g·kg^-1）， and low- and high-dose Cinnamomi Cortex （0.45 and 0.9 g·kg^-1， respectively） groups. The DM rat model was established by a high-fat diet combined with intraperitoneal injection of 40 mg·kg^-1 STZ in other groups except the blank group. The intervention lasted for 8 weeks. The status， body weight， water intake， food intake， and fasting blood glucose （FBG） of the rats were observed and determined. Hematoxylin-eosin staining was employed to reveal the pathological changes of the pancreas， and immunohistochemistry to detect the expression of glucagon in the pancreas. Biochemical assay was employed to measure the serum levels of lipid metabolism indexes such as total cholesterol （TC）， triglyceride （TG）， low-density lipoprotein （LDL）， and high-density lipoprotein （HDL）. Enzyme-linked immunosorbent assay was employed to determine the levels of glycosylated hemoglobin， insulin， glucagon， GLP-1， and glucose-dependent insulinotropic polypeptide （GIP） in rat serum， and Western blot to determine the protein levels of GLP-1 and DPP-4 in the pancreas. ResultAfter 8 weeks of intervention， the model group showed higher body weight， FBG， TC， TG， LDL， glycosylated hemoglobin， glucagon， insulin， and insulin resistance index and lower HDL， GLP-1， and GIP than the blank group （P<0.05， P<0.01）. The Cinnamomi Cortex groups showed lower body weight， FBG， TC， TG， LDL， glycosylated hemoglobin， glucagon， insulin， and insulin resistance index and higher HDL， GLP-1， and GIP than the model group （P<0.05， P<0.01）. The Cinnamomi Cortex groups showed recovered morphology of islet cells and no nucleus aggregation. Compared with the model group， the Cinnamomi Cortex groups showed declined levels of glucagon in the center of islet cells. Compared with the blank group， the model group showed up-regulated protein level of DPP-4 and down-regulated protein level of GLP-1 （P<0.01）. Compared with the model group， the high-dose Cinnamomi Cortex groups showed down-regulated protein level of DPP-4 and up-regulated protein level of GLP-1 （P<0.05）. ConclusionCinnamomi Cortex may reduce blood glucose and improve incretin effect to lower the blood glucose level by regulating DPP-4 and GLP-1 in DM rats.