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Abstract The analysis of genomic variations in offspring after implantation has been infrequently studied. In this study, we aim to investigate the extent of de novo mutations in humans from developing fetus to birth. Using high-depth whole-genome sequencing, 443 parent-offspring trios were studied to compare the results of de novo mutations (DNMs) between different groups. The focus was on fetuses and newborns, with DNA samples obtained from the families’ blood and the aspirated embryonic tissues subjected to deep sequencing. It was observed that the average number of total DNMs in the newborns group was 56.26 (54.17–58.35), which appeared to be lower than that the multifetal reduction group, which was 76.05 (69.70–82.40) (F = 2.42, P = 0.12). However, after adjusting for parental age and maternal pre-pregnancy body mass index (BMI), significant differences were found between the two groups. The analysis was further divided into single nucleotide variants (SNVs) and insertion/deletion of a small number of bases (indels), and it was discovered that the average number of de novo SNVs associated with the multifetal reduction group and the newborn group was 49.89 (45.59–54.20) and 51.09 (49.22–52.96), respectively. No significant differences were noted between the groups (F = 1.01, P = 0.32). However, a significant difference was observed for de novo indels, with a higher average number found in the multifetal reduction group compared to the newborn group (F = 194.17, P

Abstract Background Chromosomal microarray analysis (CMA) has emerged as a critical instrument in prenatal diagnostic procedures, notably in assessing congenital heart diseases (CHD). Nonetheless, current research focuses solely on CHD, overlooking the necessity for thorough comparative investigations encompassing fetuses with varied structural abnormalities or those without apparent structural anomalies. Objective This study sought to assess the relation of single nucleotide polymorphism-based chromosomal microarray analysis (SNP-based CMA) in identifying the underlying causes of fetal cardiac ultrasound abnormalities. Methods A total of 2092 pregnant women who underwent prenatal diagnosis from 2017 to 2022 were included in the study and divided into four groups based on the presence of ultrasound structural abnormalities and the specific type of abnormality. The results of the SNP-Array test conducted on amniotic fluid samples from these groups were analyzed. Results Findings from the study revealed that the non-isolated CHD group exhibited the highest incidence of aneuploidy, overall chromosomal abnormalities, and trisomy 18, demonstrating statistically significant differences from the other groups (p 0.05). The occurrence rates of 22q11.2 and 15q11.2 were also not statistically different between the isolated CHD group and the non-isolated congenital heart defect group (p > 0.05). Conclusion SNP-based CMA enhances the capacity to detect abnormal CNVs in CHD fetuses, offering valuable insights for diagnosing chromosomal etiology and facilitating genetic counseling. This research contributes to the broader understanding of the utility of SNP-based CMA in the context of fetal cardiac ultrasound abnormalities.

BackgroundCurrent research offers limited clarity on the correlation between waist circumference and chronic pain prevalence.ObjectiveThis investigation seeks to elucidate the potential relationship between waist circumference and chronic pain and their causal association.MethodsAn observational study was conducted, leveraging data from the National Health and Nutrition Examination Survey (NHANES) collected between 2001 and 2004. The multivariable logistic regression was used to assess the relationship between waist circumference and chronic pain. Furthermore, a meta-analysis of Mendelian Randomization (MR) was applied to explore a causal relationship between waist circumference and pain.ResultsThe observational study, post multivariable adjustment, indicated that an increase in waist circumference by 1 dm (decimeter) correlates with a 14% elevation in chronic pain risk (Odds Ratio [OR] = 1.14, 95% Confidence Interval [CI]: 1.04–1.24, p = 0.01). Moreover, the meta-analysis of MR demonstrated that an increased waist circumference was associated with a genetic predisposition to pain risk (OR = 1.14, 95%CI: 1.06–1.23, p = 0.0007).ConclusionObservational analysis confirmed a significant relationship between increased waist circumference and the incidence of chronic pain, and results based on MR Study identified increased waist circumference as potentially causal for pain.

Abstract Introduction Hypoxia‐inducible factor‐2α (HIF‐2α) modulates the hypoxic response pathway in tumors; however, mutations in pathways (including SDHA, SDHB, SDHC, SDHD, FH, and VHL genes) that are suspected to activate HIF‐2α are poorly understood, with limited understanding of the prevalence and clinical prognosis. Methods This retrospective observational study used a de‐identified nationwide (US‐based) clinico‐genomic database (CGDB) across 15 available tumor types. Results Among the 9467 adult patients with advanced/metastatic solid tumors included in the analysis, any mutation at the above‐mentioned six genes was observed in 1.8% (95% CI: 1.5–2.1) of patients. The mutation prevalence ranged from 0.05% of SDHD to 0.93% of VHL. When further stratified by tumor type, the prevalence of gene mutation in each tumor type was well below 1%, except for VHL with 44% in renal cell carcinomas (RCC). Excluding RCC, the prevalence of any HIF‐2α gene mutations in the study population was 0.9% (95% CI: 0.8–1.2). The median overall survival (OS) from 1 and 2 L therapy among patients with any HIF‐2α gene mutation was 14.5 (95% CI: 11.5–24.2) and 9.3 (95% CI: 6.0–18.1) months, respectively, compared with 13.4 (95% CI: 12.9–13.9) and 9.8 (95% CI: 9.3–10.4) months among patients without HIF‐2α gene mutations. Discussion and Conclusions The prevalence of HIF‐2α related gene mutations was generally low (

Abstract Synthetic biology relies on the screening and quantification of genetic components to assemble sophisticated gene circuits with specific functions. Microscopy is a powerful tool for characterizing complex cellular phenotypes with increasing spatial and temporal resolution to library screening of genetic elements. Microscopy‐based assays are powerful tools for characterizing cellular phenotypes with spatial and temporal resolution and can be applied to large‐scale samples for library screening of genetic elements. However, strategies for high‐throughput microscopy experiments remain limited. Here, we present a high‐throughput, microscopy‐based platform that can simultaneously complete the preparation of an 8 × 12‐well agarose pad plate, allowing for the screening of 96 independent strains or experimental conditions in a single experiment. Using this platform, we screened a library of natural intrinsic promoters from Pseudomonas aeruginosa and identified a small subset of robust promoters that drives stable levels of gene expression under varying growth conditions. Additionally, the platform allowed for single‐cell measurement of genetic elements over time, enabling the identification of complex and dynamic phenotypes to map genotype in high throughput. We expected that the platform could be employed to accelerate the identification and characterization of genetic elements in various biological systems, as well as to understand the relationship between cellular phenotypes and internal states, including genotypes and gene expression programs.