Background: The revised guidelines for the management of medullary thyroid carcinoma recommend that genetic counseling regarding reproductive options, including preimplantation genetic diagnosis (PGD), be considered for all RET mutation carriers of reproductive age to avoid the transmission of multiple endocrine neoplasia type 2 (MEN2). However, the high complexity and cost of PGD have hindered its widespread use. Thus, it is necessary to establish a simple and relatively inexpensive method to facilitate the PGD of MEN2. Patients and Methods: A customized Nimblegen EZ sequence capture array was designed to capture the targeted regions, including the RET gene, and 1 Mb range on each side of the RET gene. Targeted, capture-based next generation sequencing of three members of one family with MEN2A (the couple and the paternal father) was conducted to identify the informative markers. The diagnosis of the embryos was achieved through haplotype analysis based on informative markers and causative mutation. Results: Based on the sequencing results, 173 informative markers were detected, which were sufficient for the subsequent use for PGD. Seven informative markers and the causative mutation (RET C634Y) were selected and subjected to Sanger sequencing. Through haplotype analysis, 4 embryos without inheritance of the mutation haplotype of the RET gene were diagnosed as unaffected. One unaffected embryo was transferred, with one healthy baby born at 38 gestational weeks. Conclusion: Targeted, capture-based next generation sequencing for identification of informative markers together with Sanger sequencing is an easy and efficient method for the PGD of monogenic diseases, such as MEN2.

Recent studies have suggested that sperm mitochondrial DNA copy number (mtDNA-CN), DNA fragmentation index (DFI), and reactive oxygen species (ROS) content are crucial to sperm function. However, the associations between these measurements and embryo development and pregnancy outcomes in assisted reproductive technology (ART) remain unclear. Semen samples were collected from 401 participants, and seminal quality, parameters of sperm concentration, motility, and morphology were analyzed by a computer-assisted sperm analysis system. DFI, mtDNA-CN, and ROS levels were measured using sperm chromatin structure assay, real-time quantitative polymerase chain reaction, and ROS assay, respectively. Among the participants, 126 couples underwent ART treatments, including in vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI), and 79 of the couples had embryos transferred. In 401 semen samples, elevated mtDNA-CN and DFI were associated with poor seminal quality. In 126 ART couples, only mtDNA-CN was negatively correlated with the fertilization rate, but this correlation was not significant after adjusting for male age, female age, seminal quality, ART strategy, number of retrieved oocytes, controlled stimulation protocols, and cycle rank. Regarding pregnancy outcomes, sperm mtDNA-CN, ROS, and DFI were not associated with the clinical pregnancy rate or live birth rate in 79 transferred cases. In conclusion, increased mtDNA-CN and DFI in sperm jointly contributed to poor seminal quality, but sperm mtDNA-CN, ROS, and DFI were not associated with clinical outcomes in ART.

Background: Polycystic ovary syndrome (PCOS) is a common endocrine disorder worldwide. We aimed to examine the associations of two mitochondrial DNA (mtDNA) biomarkers in the peripheral blood, mtDNA copy number (CN), and mtDNA⁴⁹⁷⁷ deletion rate (DR), with PCOS in a clinical setting.Methods: We performed a study involving 263 women with PCOS and 326 age-matched controls between June 2015 and June 2019. The mtDNA CN and mtDNA⁴⁹⁷⁷ DR were measured using multiplex probe-based qPCR. The associations of the mtDNA CN and mtDNA⁴⁹⁷⁷ DR with the risk of PCOS were estimated using logistic regression.Results: Analysis of the associations between mtDNA biomarkers and PCOS indicate that the mtDNA CN (P = 0.003) and mtDNA⁴⁹⁷⁷ DR (P < 0.001) in PCOS patients were significantly higher than those in the controls. After adjusting for the body mass index, luteinizing hormone/follicle-stimulating hormone ratio, and testosterone level, only higher mtDNA⁴⁹⁷⁷ DR was associated with PCOS (odds ratio 1.053, 95% confidence interval 1.024 to 1.083; P < 0.001). The linear dose-response trends of the mtDNA⁴⁹⁷⁷ DR were also supported by the quartile analysis.Conclusion: Multivariable models suggest that mtDNA⁴⁹⁷⁷ DR levels are strongly associated with PCOS and represent an independent risk factor for PCOS. Further investigation of the utility of mtDNA as a biomarker for PCOS is warranted.

This study was performed to characterize the relationship of various laboratory test indicators with clinical information and Preeclampsia (PE) development. Then, prediction models for early-onset preeclampsia (EOPE), late-onset preeclampsia (LOPE), and preterm preeclampsia (Preterm PE) were developed using maternal characteristics and laboratory data. Between January 2019 and December 2021, we retrospectively recruited 144 EOPE, 363 LOPE, 231 Preterm PE, and 1458 healthy participants from six hospitals. We utilized all available clinical and laboratory data obtained during routine prenatal visits in early pregnancy. The models for EOPE, LOPE, and Preterm PE were created using ensemble machine learning models with patient clinical and laboratory data. Results: By comparing laboratory variables between PE patients and healthy controls, we identified 7, 18, 8, 15, 7,29 laboratory markers for EOPE, LOPE, and Preterm PE, severe PE, superimposed PE, first-time PE respectively. The ensemble EOPE and LOPE models incorporating clinical and laboratory predictors outperformed the clinical factor models respectively. The ensemble EOPE model demonstrated good sensitivity (72.22%,95% confidence interval [CI]: 57.59%-86.85%) and specificity (85.25%,95% CI: 80.54%-89.97%) in distinguishing EOPE from controls in early pregnancy. Similarly, the ensemble LOPE model showed good accuracy in differentiating LOPE from healthy participants (sensitivity: 69.57%, 95% CI: 56.27%-82.86%; specificity: 85.25%, 95% CI: 80.54%-89.97%). The prediction scores demonstrated notable positive correlations with blood pressure at admission, while they showed inverse correlations with 24-hour urine protein levels and fetal growth restriction among PE patients. In conclusion, our study identified key laboratory indicators for forecasting PE. The developed models exhibited good predictive capability for assessing preeclampsia risk and severity based on clinical and laboratory data. Not applicable.