PURPOSE: We developed and validated a fetal trisomy detection method for use as a noninvasive prenatal test (NIPT) including a Clinical Laboratory Improvement Amendments (CLIA)-certified bioinformatics pipeline on a cloud-based computing system using both Illumina and Life Technology sequencing platforms for 221 Korean clinical samples. We determined the necessary proportions of the fetal fraction in the cell-free DNA (cfDNA) sample for NIPT of trisomies 13, 18, and 21 through a limit of quantification (LOQ) test. MATERIALS AND METHODS: Next-generation sequencing libraries from 221 clinical samples and three positive controls were generated using Illumina and Life Technology chemistries. Sequencing results were uploaded to a cloud and mapped on the human reference genome (GRCh37/hg19) using bioinformatics tools. Based on Z-scores calculated by normalization of the mapped read counts, final aneuploidy reports were automatically generated for fetal aneuploidy determination. RESULTS: We identified in total 29 aneuploid samples, and additional analytical methods performed to confirm the results showed that one of these was a false-positive. The LOQ test showed that the proportion of fetal fraction in the cfDNA sample would affect the interpretation of the aneuploidy results. CONCLUSION: Noninvasive chromosome examination (NICE), a CLIA-certified NIPT with a cloud-based bioinformatics platform, showed unambiguous success in fetus aneuploidy detection.
Aneuploidy* ; Computational Biology ; DNA ; Fetus* ; Genome ; High-Throughput Nucleotide Sequencing ; Humans ; Prenatal Diagnosis ; Trisomy

Aged people are challenged by serious complications from chronic diseases, such as mood disorder, diabetes, heart disease, and infectious diseases, which are also the most common causes of death in older people. Therefore, elderly care facilities are more important than ever. The most common causes of death in elderly care facilities were reported to be diabetes, cardiovascular disease, and pneumonia. Recently, the coronavirus disease 2019 (COVID-19) pandemic have a great impact on blind spots of safety where aged people were isolated from society. Elderly care facilities were one of the blind spots in the midst of the pandemic, where major casualties were reported from COVID-19 complications because most people had one or two mortality risk factors, such as diabetes or cardiovascular disease. Therefore, medical governance of public health center and hospital, and elderly care facility is becoming important issue of priority. Thus, remote health monitoring service by the Internet of Medical Things (IoMT) sensors is more important than ever. Recently, technological breakthroughs have enabled healthcare professionals to have easy access to patients in medical blind spots through the use of IoT sensors. These sensors can detect medically urgent situations in a timely fashion and make medical decisions for aged people in elderly care facilities. Real-time electrocardiograms and blood sugar monitoring sensors are approved by the medical insurance service. Real-time monitoring services in medical blind spots, such as elderly care facilities, has been suggested. Heart rhythm monitoring could play a role in detecting early cardiovascular disease events and monitoring blood glucose levels in the management of chronic diseases, such as diabetes, in aged people in elderly care facilities. This review presents the potential usefulness of remote monitoring with IoMT sensors in medical blind spots and clinical suggestions for applications.