Mutation spectrum of thalassemia among pre-pregnant adults in the Jiangsu Province by capillary electrophoresis-based multiplex PCR assay

BACKGROUND

Thalassemia is a common genetic disorder in southwestern China, and an increasing number of cases from eastern China have been recently reported. Here, we developed a rapid, convenient, and accurate assay to evaluate the mutation spectrum of thalassemia in eastern China.

METHODS

A carrier screening assay for 61 hotspot variants among HBA1/HBA2 and HBB (OMIM: 141800, 141850, and 141900) genes was developed by SNaPshot/high-throughput ligation-dependent probe amplification (HLPA) technology. We used this assay to detect the mutation spectrum of thalassemia in individuals from eastern China and compared with the data collected from literatures focused on southern and northern China for variant distribution.

RESULTS

Among 4276 tested individuals, 2.62% (112/4276) were α-thalassemia carriers, with 90 carrying one deletion or mutation and 22 carrying two deletions. 0.40% (17/4276) were β-thalassemia carriers, and the most common variant of β-thalassemia was c.126_129delCTTT (29.41%) followed by c.316-197C>T (23.53%). The genotype distribution in our study was similar to those from southern China populations.

CONCLUSION

The Chinese population from different regions presented comparable mutation spectrum of thalassemia, and the SNaPshot/HLPA technique may serve as a capable assay for a routine genetic test in clinical practice with its accurate, rapid, and inexpensive advantage.

Improving the malignancy prediction of breast cancer based on the integration of radiomics features from dual-view mammography and clinical parameters

Radiomics has been a promising imaging biomarker for many malignant diseases. We developed a novel radiomics strategy that incorporating radiomics features extracted from dual-view mammograms and clinical parameters for identifying benign and malignant breast lesions, and validated whether the radiomics assessment could improve the accurate diagnosis of breast cancer. A total of 380 patients (mean age, 52 ± 7 years) with 621 breast lesions utilizing mammograms on craniocaudal (CC) and mediolateral oblique (MLO) views were randomly allocated into the training (n = 486) and testing (n = 135) sets in this retrospective study. A total of 1184 and 2368 radiomics features were extracted from single-position region of interest (ROI) and position-paired ROI, separately. Clinical parameters were then combined for better prediction. Recursive feature elimination and least absolute shrinkage and selection operator methods were applied to select optimal predictive features. Random forest was used to conduct the predictive model. Intraclass correlation coefficient test was used to assess repeatability and reproducibility of features. After preprocessing, 467 radiomics features and clinical parameters remained in the single-view and dual-view models. The performance and significance of models were quantified by the area under the curve (AUC), sensitivity, specificity, and accuracy. The correlation analysis between variables was evaluated using the correlation ratio and Pearson correlation coefficient. The model using a combination of dual-view radiomics and clinical parameters achieved a favorable performance (AUC: 0.804, 95% CI: 0.668-0.916), outperformed single-view model and model without clinical parameters. Incorporating with radiomics features of dual-view (CC&MLO) mammogram, age, breast density, and type of suspicious lesions can provide a noninvasive approach to evaluate the malignancy of breast lesions and facilitate clinical decision-making.