A common microbial signature is present in the lower airways of interstitial lung diseases including sarcoidosis

Background: The etiology of pulmonary sarcoidosis is not well established. Although the mechanism triggering pulmonary sarcoidosis remains to be established, inflammatory reactions seem to play an important role in this process. Objectives: The aim of this study was to define the composition of the lower airway microbiota in the bronchoalveolar lavage (BAL) of patients affected by interstitial lung diseases, including sarcoidosis, to determine whether the bacterial signature differs among these diseases. Methods: Ten patients affected by pulmonary sarcoidosis and 9 patients affected by other interstitial lung diseases were enrolled. 16S rRNA next-generation sequencing was used to study BAL microbial composition of these patients, and were also compared with already published microbial content in higher airways of such diseases. Results: Four phyla dominated the lower airway microbiota, Bacteroidetes being the most abundant phylum in both groups (56.9%). Diversity analysis showed no significant differences between the various diseases, particularly between pulmonary sarcoidosis and other interstitial lung diseases affecting lower airways. Conclusions: Our data indicate that the bacterial lower airways microbiota share the same signature and, therefore, cannot be used as a diagnostic tool to discriminate among different interstitial lung diseases, including sarcoidosis, while microbial diversity is present when considering lower or higher respiratory airways

Quality assurance of genetic laboratories and the EBTNA practice certification, a simple standardization assurance system for a laboratory network

Abstract Analytical laboratory results greatly influence medical diagnosis, about 70% of medical decisions are based on laboratory results. Quality assurance and quality control are designed to detect and correct errors in a laboratory's analytical process to ensure both the reliability and accuracy of test results. Unreliable performance can result in misdiagnosis and delayed treatment. Furthermore, improved quality guarantees increased productivity at a lower cost. Quality assurance programmes include internal quality control, external quality assessment, proficiency surveillance and standardization. It is necessary to try to ensure compliance with the requirements of the standards at all levels of the process. The sources of these standards are the International Standards Organization (ISO), national standards bodies, guidelines from professional organisations, accreditation bodies and governmental regulations. Laboratory networks increase the performance of laboratories in support of diagnostic screening programme. It is essential that genetic laboratories of a network have procedures underpinned by a robust quality assurance system to minimize errors and to reassure the clinicians and the patients that international standards are being met. This article provides an overview of the bases of quality assurance and its importance in genetic tests and it reports the EBTNA quality assurance system which is a clear and simple system available for access to adequate standardization of a genetic laboratory's network

Cracking the Code of Human Diseases Using Next-Generation Sequencing: Applications, Challenges, and Perspectives

Next-generation sequencing (NGS) technologies have greatly impacted on every field of molecular research mainly because they reduce costs and increase throughput of DNA sequencing. These features, together with the technology's flexibility, have opened the way to a variety of applications including the study of the molecular basis of human diseases. Several analytical approaches have been developed to selectively enrich regions of interest from the whole genome in order to identify germinal and/or somatic sequence variants and to study DNA methylation. These approaches are now widely used in research, and they are already being used in routine molecular diagnostics. However, some issues are still controversial, namely, standardization of methods, data analysis and storage, and ethical aspects. Besides providing an overview of the NGS-based approaches most frequently used to study the molecular basis of human diseases at DNA level, we discuss the principal challenges and applications of NGS in the field of human genomics

Clinical Evaluation of a Custom Gene Panel as a Tool for Precision Male Infertility Diagnosis by Next-Generation Sequencing

Background: Up to 15% of couples are infertile and male factor infertility accounts for approximately 50% of these cases. Male infertility is a multifactorial pathological condition. The genetic of male infertility is very complex and at least 2000 genes are involved in its etiology. Genetic testing by next-generation sequencing (NGS) technologies can be relevant for its diagnostic value in male infertile patients. Therefore, the aim of this study was to implement the diagnostic offer with the use of an NGS panel for the identification of genetic variants. Methods: We developed an NGS gene panel that we used in 22 male infertile patients. The panel consisted of 110 genes exploring the genetic causes of male infertility; namely spermatogenesis failure due to single-gene mutations, central hypogonadism, androgen insensitivity syndrome, congenital hypopituitarism, and primary ciliary dyskinesia. Results: NGS and a subsequent sequencing of the positive pathogenic or likely pathogenic variants, 5 patients (23%) were found to have a molecular defect. In particular, pathogenic variants were identified in TEX11, CCDC39, CHD7, and NR5A1 genes. Moreover, 14 variants of unknown significance and 7 novel variants were found that require further functional studies and family segregation. Conclusion: This extended NGS-based diagnostic approach may represent a useful tool for the diagnosis of male infertility. The development of a custom-made gene panel by NGS seems capable of reducing the proportion of male idiopathic infertility

Male Infertility Diagnosis: Improvement of Genetic Analysis Performance by the Introduction of Pre-Diagnostic Genes in a Next-Generation Sequencing Custom-Made Panel

Background: Infertility affects about 7% of the general male population. The underlying cause of male infertility is undefined in about 50% of cases (idiopathic infertility). The number of genes involved in human spermatogenesis is over two thousand. Therefore, it is essential to analyze a large number of genes that may be involved in male infertility. This study aimed to test idiopathic male infertile patients negative for a validated panel of “diagnostic” genes, for a wide panel of genes that we have defined as “pre-diagnostic.” Methods: We developed a next-generation sequencing (NGS) gene panel including 65 pre-diagnostic genes that were used in 12 patients who were negative to a diagnostic genetic test for male infertility disorders, including primary spermatogenic failure and central hypogonadism, consisting of 110 genes. Results: After NGS sequencing, variants in pre-diagnostic genes were identified in 10/12 patients who were negative to a diagnostic test for primary spermatogenic failure (n = 9) or central hypogonadism (n = 1) due to mutations of single genes. Two pathogenic variants of DNAH5 and CFTR genes and three uncertain significance variants of DNAI1, DNAH11, and CCDC40 genes were found. Moreover, three variants with high impact were found in AMELY, CATSPER 2, and ADCY10 genes. Conclusion: This study suggests that searching for pre-diagnostic genes may be of relevance to find the cause of infertility in patients with apparently idiopathic primary spermatogenic failure due to mutations of single genes and central hypogonadism

Gene variants in Eating Disorders. Focus on Anorexia Nervosa Bulimia Nervosa and Binge-eating Disorder

Eating disorders such as anorexia nervosa, bulimia nervosa and binge-eating disorder, have a deep social impact, concluding with death in cases of severe disease. Eating disorders affect up to 5% of the population in the industrialized countries, but probably the phenomenon is under-detection and under-diagnosis. Eating disorders are multifactorial disorders, resulting from the interaction between environmental triggers, psychological factors, but there is also a strong genetic component. In fact, genetic factors predispose for approximately 33-84% to anorexia nervosa, 28-83% to bulimia nervosa, and 41-57% to binge eating disorder. Twins and family studies have provided an unassailable proof on the heritability of these disorders. Other types of genetic studies, including genome-wide association studies, whole genome sequencing and linkage analysis, allowed to identify the genes and their variants associated with eating disorders and moreover global collaborative efforts have led to delineate the etiology of these disorders. Next Generation Sequencing technologies can be considered as an ideal diagnostic approach to identify not only the common variants, such as single nucleotide polymorphism, but also rare variants. Here we summarize the present knowledge on the molecular etiology and genetic determinants of eating disorders including serotonergic genes, dopaminergic genes, opioid genes, appetite regulation genes, endocannabinoid genes and vitamin D3

The molecular analysis of BRCA1 and BRCA2: Next-generation sequencing supersedes conventional approaches

Abstract Background Accurate and sensitive detection of BRCA 1/2 germ-line mutations is crucial for the clinical management of women affected by breast cancer, for prevention and, notably, also for the identification of at-risk healthy relatives. The most widely used methods for BRCA1 / 2 molecular analysis are Sanger sequencing, and denaturing high performance liquid chromatography (dHPLC) followed by the Sanger method. However, recent findings suggest that next-generation sequencing (NGS)-based approaches may be an efficient tool for diagnostic purposes. In this context, we evaluated the effectiveness of NGS for BRCA gene analysis compared with dHPLC/Sanger sequencing. Methods Seventy women were screened for BRCA1/2 mutations by both dHPLC/Sanger sequencing and NGS, and the data were analyzed using a bioinformatic pipeline. Results Sequence data analysis showed that NGS is more sensitive in detecting BRCA 1/2 variants than the conventional procedure, namely, dHPLC/Sanger. Conclusion Next-generation sequencing is more sensitive, faster, easier to use and less expensive than the conventional Sanger method. Consequently, it is a reliable procedure for the routine molecular screening of the BRCA 1/2 genes

An Information Filtering System for e-Health: the Health-on-Net

This paper describes a work performed in the framework of the HealthOnNet project purposed to define and implement an Internet-based repository of diagnostic exams and medical reports connecting several Italian hospitals. The repository, which will be used as an historical and legal archive of clinical data, offers second opinion teleconsulting features as well as advanced categorization and filtering services. The paper is focused on this latter point and describes the process and the algorithms we defined to automatically classify medical documents (with respect to the widely adopted International Classification of Diseases and Related Health Problems of the World Health Organization) and to filter them on the basis of a user defined profile. Then it describes the developed prototype and some experimentation results

Comparative Metagenomic Analysis of Human Gut Microbiome Composition Using Two Different Bioinformatic Pipelines

Technological advances in next-generation sequencing-based approaches have greatly impacted the analysis of microbial community composition. In particular, 16S rRNA-based methods have been widely used to analyze the whole set of bacteria present in a target environment. As a consequence, several specific bioinformatic pipelines have been developed to manage these data. MetaGenome Rapid Annotation using Subsystem Technology (MG-RAST) and Quantitative Insights Into Microbial Ecology (QIIME) are two freely available tools for metagenomic analyses that have been used in a wide range of studies. Here, we report the comparative analysis of the same dataset with both QIIME and MG-RAST in order to evaluate their accuracy in taxonomic assignment and in diversity analysis. We found that taxonomic assignment was more accurate with QIIME which, at family level, assigned a significantly higher number of reads. Thus, QIIME generated a more accurate BIOM file, which in turn improved the diversity analysis output. Finally, although informatics skills are needed to install QIIME, it offers a wide range of metrics that are useful for downstream applications and, not less important, it is not dependent on server times