The applications of big data in molecular diagnostics

The clinical application of metagenomic next-generation sequencing for detecting pathogens in bronchoalveolar lavage fluid: case reports and literature review

INTRODUCTION

Clinical metagenomic next-generation sequencing (mNGS) allows a comprehensive genetic analysis of microbial materials. Different from other traditional target-driven molecular diagnostic tests, such as PCR, mNGS is a hypothesis-free diagnostic approach that allows a comprehensive genetic analysis of the clinical specimens that cover nearly any common, rare, and new pathogens ranging broadly from viruses, bacteria, fungi to parasites.

AREAS COVERED

In this article, we discussed the clinical application of the mNGS using two clinical cases as examples and described the use of mNGS to assist the diagnosis of parasitic pulmonary infection. The advantages and challenges in implementing mNGS in clinical microbiology are also discussed.

EXPERT OPINION

mNGS is a promising technology that allows quick diagnosis of infectious diseases. Currently, a plethora of sequencing and analysis methods exists for mNGS, each with individual merits and pitfalls. While standards and best practices were proposed by various metagenomics working groups, they are yet to be widely adopted in the community. The development of a consensus set of guidelines is necessary to guide the usage of this new technology and the interpretation of NGS results before clinical adoption of mNGS testing.

Interest in technology among medical students early in their clinical experience

BACKGROUND

The world is in the midst of the "digital" revolution characterized by the ascendency of computerization, information systems and artificial intelligence with an emphasis on innovation and creativity. This revolution has affected current medical practice and promises to significantly impact it in the future. This requires physician's understanding and participation in adopting such technology. This study aimed to explore the role technology plays in the future career plans of medical students.

METHODS

A questionnaire examining selection criteria for medical specialty choice, criteria for choosing a post-residency job and demographic data was completed by a convenience sample of 5th-year Israeli medical students.

RESULTS

Two-hundred forty-two students (51 % men) completed the questionnaire, an 84 % response rate. Only a third (35 %) rated the specialty selection criterion "provides mechanical/ technological challenges" as important, while only 7% considered as important that a specialty requires skills in computer science. Few students were interested in post-residency positions requiring much technological knowledge (25 %) and requiring much skill with computerized information systems (13 %). Male students were significantly more interested than females in such positions and these students more often reported that they were considering careers in surgery and its subspecialties. This surgical bent was confirmed by the 42 % of students interested in post-residency positions that include time in the operating room having more interest in positions requiring much technological knowledge than the students not interested in operating room time.

CONCLUSIONS

This preliminary study demonstrated that as a group the students' expressed relatively little interest in medical specialties and post-residency positions involving technological challenges and knowledge of information (computer) science. Yet, the sub-group interested in the surgical specialties had such interests. These findings were perplexing since the students belong to Generations Y and Z who are steeped in the use of smartphones and social media. Therefore, we failed to support our hypothesis that Generation Y and Z students would be attracted to specialties and positions that provide them with technological challenges. Furthermore, medical educators need to explore this apparent lack of interest in technology in order to insure that the future physician workforce is ready to face future "digital" challenges.

Current scenario of the genetic testing for rare neurological disorders exploiting next generation sequencing

Next generation sequencing is currently a cornerstone of genetic testing in routine diagnostics, allowing for the detection of sequence variants with so far unprecedented large scale, mainly in genetically heterogenous diseases, such as neurological disorders. It is a fast-moving field, where new wet enrichment protocols and bioinformatics tools are constantly being developed to overcome initial limitations. Despite the as yet undiscussed advantages, however, there are still some challenges in data analysis and the interpretation of variants. In this review, we address the current state of next generation sequencing diagnostic testing for inherited human disorders, particularly giving an overview of the available high-throughput sequencing approaches; including targeted, whole-exome and whole-genome sequencing; and discussing the main critical aspects of the bioinformatic process, from raw data analysis to molecular diagnosis.