Application of next generation sequencing in the screening of monogenic diseases in China, 2021: a consensus among Chinese newborn screening experts

Guan

et al. 2022

Orphanet J Rare Dis

Purpose Newborn screening (NBS) applications are limited as they can only cover a few genetic diseases and may have false positive or false negative rates. A new detection program called newborn genetic screening (NBGS) has been designed to address the potential defects of NBS. This study aimed to investigate the perceptions, acceptance, and expectations of childbearing people related to NBGS to provide the basis for the targeted improvement in the NBGS program carried out in Hospitals. Methods A questionnaire with 20 items was designed on www.wjx.cn. Individuals who came to the Nanjing maternity and child health care Hospital for consultation from June 2021 to August 2021 participated in the survey. The data of the study was arranged properly and analyzed after the investigation. Results A total of 1141 valid questionnaires were collected in the survey, in which the average age of the participants was 31 (± 4) years, and a 1:4 ratio of males to females. Additionally, 65.12% of the participants possessed a bachelor's degree or above qualification. Overall, 50.57% of participants had an annual household income of 100,000–250,000 RMB, while about 86.68% of the participants supported the development of NBGS. The participation cost to pay for NBGS depended on the family incomes; about 59.42% of them were willing to pay a participation fee of 1000–2000 RMB. Conclusion Our research provisionally demonstrated that the residents generally supported the use of NBGS, especially those with higher educational degrees, but the understanding of the genetic diseases and NBGS among the low-educated population still needs to be strengthened.

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Current attitudes and preconceptions on newborn genetic screening in the Chinese reproductive-aged population

Guan

et al. 2022

Orphanet J Rare Dis

“…Recently, NGS has also been applied in newborn screening (NBS) programs in regions of high prevalence ( 31 ). Due to the rapid nature of disease progression in neonates, diagnostic yield and speed are fundamental aspects of obtaining a high clinical impact ( 32 ).…”

Section: Introductionmentioning

confidence: 99%

Applications of next generation sequencing in the screening and diagnosis of thalassemia: A mini-review

et al. 2022

Thalassemias are a group of inherited blood disorders that affects 5–7% of the world population. Comprehensive screening strategies are essential for the management and prevention of this disorder. Today, many clinical and research laboratories have widely utilized next-generation sequencing (NGS) technologies to identify diseases, from germline and somatic disorders to infectious diseases. Yet, NGS application in thalassemia is limited and has just recently surfaced due to current demands in seeking alternative DNA screening tools that are more efficient, versatile, and cost-effective. This review aims to understand the several aspects of NGS technology, including its most current and expanding uses, advantages, and limitations, along with the issues and solutions related to its integration into routine screening and diagnosis of thalassemias. Hitherto, NGS has been a groundbreaking technology that offers tremendous improvements as a diagnostic tool for thalassemia in terms of its higher throughput, accuracy, and adaptability. The superiority of NGS in detecting rare variants, solving complex hematological problems, and providing non-invasive alternatives to neonatal diagnosis cannot be overlooked. However, several pitfalls still preclude its use as a stand-alone technique over conventional methods.

Computational Intelligence and Neuroscience

“…With the development of next-generation gene-sequencing technology [ 9 ], the accuracy of the sequencing results has been greatly improved and the types of sequenced genes have become more comprehensive. The use of machine learning methods to establish a survival model and a prognosis model for patients with osteosarcoma can be used as a means of adjuvant therapy to help doctors formulate a more effective and targeted diagnosis and treatment plans and ultimately achieve the purpose of precise treatment [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

A Survival Status Classification Model for Osteosarcoma Patients Based on E-CNN-SVM and Multisource Data Fusion

Zhang

Peng

2022

Traditional algorithms have the following drawbacks: (1) they only focus on a certain aspect of genetic data or local feature data of osteosarcoma patients, and the extracted feature information is not considered as a whole; (2) they do not equalize the sample data between categories; (3) the generalization ability of the model is weak, and it is difficult to perform the task of classifying the survival status of osteosarcoma patients better. In this context, this paper designs a survival status prediction model for osteosarcoma patients based on E-CNN-SVM and multisource data fusion, taking into full consideration the characteristics of the small number of samples, high dimensionality, and interclass imbalance of osteosarcoma patients’ genetic data. The model fuses four gene sequencing data highly correlated with bone tumors using the random forest algorithm in a dimensionality reduction and then equalizes the data using a hybrid sampling method combining the SMOTE algorithm and the TomekLink algorithm; secondly, the CNN model with the incentive module is used to further extract features from the data for more accurate extraction of characteristic information; finally, the data are passed to the SVM model to further improve the stability and classification performance of the model. The model has been demonstrated to be more effective in improving the accuracy of the classification of patients with osteosarcoma.