ABSTRACT
BACKGROUND: Menstrual blood (MB) is a convenient specimen type that can be self-collected easily and non-invasively by women. This study assessed the potential application of MB as a diagnostic specimen to detect genital tract infections (GTIs) and human papillomavirus (HPV) infections in women. METHOD: Genomic DNA was extracted from MB samples. Pacific Bioscience (Pacbio) 16S ribosomal DNA (rDNA) high-fidelity (HiFi) long-read sequencing and HPV PCR were performed. RESULTS: MB samples were collected from women with a pathological diagnosis of CIN1, CIN2, CIN3 or HPV infection. The sensitivity and positive predictive value (PPV) of high-risk HPV detection using MB were found to be 66.7%. A shift in vaginal flora and a significant depletion in Lactobacillus spp. in the vaginal microbiota communities were observed in the MB samples using 16S rDNA sequencing. CONCLUSIONS: In this study, we demonstrated that MB is a proper diagnostic specimen of consideration for non-invasive detection of HPV DNA and genotyping using PCR and the diagnosis of GTIs using metagenomic next-generation sequencing (mNGS). MB testing is suitable for all women who menstruate and this study has opened up the possibility of the use of MB as a diagnostic specimen to maintain women's health.
ABSTRACT
Introduction: Big Data technologies instilled an informational perspective to our understanding of the world. However, fundamental issues such as the management and storage of data can create privacy concerns. Heterogeneous types of data pose challenges in reproducibility and standardization. It is now an opportunity for us to help the health-care professionals, educators, and policy-makers understand the impact of Big Data, and steer the development roadmap to positively impact the molecular diagnostic industry. Area covered: In this review, we discuss the latest trends in applying Big Data to several key areas of molecular diagnostics: metagenomics, Mendelian disease screening, personalized medicine, and metabolomics. The limitations of utilizing bioinformatics and Big Data analytic tools are also summarized. We further propose an action plan on how to prepare a new generation of health-care professionals to step into the age of Big Data through a tailor-made bioinformatics training program. Expert opinion: In order to cope with the development of these powerful technologies, issues of ethics, regulations, and data format standardization are urgently needed. Besides, a long-term planning to train medical scientists, pathologists, and specialists on bioinformatics is necessary. It is an appropriate time to review all these issues before implementing these tests for patients' diagnosis, prognosis and treatment efficacy.
