Targeted NGS meets expert clinical characterization: Efficient diagnosis of spastic paraplegia type 11

Identification and analyses of exonic and copy number variants in spastic paraplegia

Hereditary spastic paraplegias are a diverse group of degenerative disorders that are clinically categorized as isolated; with involvement of lower limb spasticity, or symptomatic, where spastic paraplegia is complicated by further neurological features. We sought to identify the underlying genetic causes of these disorders in the participating patients. Three consanguineous families with multiple affected members were identified by visiting special schools in the Punjab Province. DNA was extracted from blood samples of the participants. Exome sequencing was performed for selected patients from the three families, and the data were filtered to identify rare homozygous variants. ExomeDepth was used for the delineation of the copy number variants. All patients had varying degrees of intellectual disabilities, poor speech development, spasticity, a wide-based gait or an inability to walk and hypertonia. In family RDHR07, a homozygous deletion involving multiple exons and introns of SPG11 (NC000015.9:g.44894055_449028del) was found and correlated with the phenotype of the patients who had spasticity and other complex movement disorders, but not those who exhibited ataxic or indeterminate symptoms as well. In families ANMD03 and RDFA06, a nonsense variant, c.985C > T;(p.Arg329Ter) in DDHD2 and a frameshift insertion‒deletion variant of AP4B1, c.965-967delACTinsC;p.(Tyr322SerfsTer14), were identified which were homozygous in the patients while the obligate carriers in the respective pedigrees were heterozygous. All variants were ultra-rare with none, or very few carriers identified in the public databases. The three loss of function variants are likely to cause nonsense-mediated decay of the respective transcripts. Our research adds to the genetic variability associated with the SPG11 and AP4B1 variants and emphasizes the genetic heterogeneity of hereditary spastic paraplegia.

Gut microbiome, T cell subsets, and cytokine analysis identify differential biomarkers in tuberculosis

Introduction

The gut microbiota, T cell subsets, and cytokines participate in tuberculosis (TB) pathogenesis. To date, the mechanisms by which these factors interactively promote TB development at different time points remain largely unclear. In the context of this study, We looked into the microorganisms in the digestive tract, T cell types, and cytokines related to tuberculosis.

Methods

According to QIIME2, we analyzed 16SrDNA sequencing of the gut microbiome on the Illumina MiSeq. Enzyme-linked immunosorbent assay was used to measure the concentrations of cytokines.

Results

We showed the presence of 26 identifiable differential microbiomes in the gut and 44 metabolic pathways between healthy controls and the different time points in the development of TB in patients. Five bacterial genera (Bacteroides, Bifidobacterium, Faecalibacterium, Collinsella, and Clostridium) were most closely associated with CD4/CD8, whereas three bacterial taxa (Faecalibacterium, Collinsella, and Clostridium) were most closely associated with CD4. Three bacterial taxa (Faecalibacterium, Ruminococcus, and Dorea) were most closely associated with IL-4. Ruminococcus was most closely associated with IL-2 and IL-10.

Conclusion

Diverse microorganisms, subsets of T cells, and cytokines, exhibiting varying relative abundances and structural compositions, were observed in both healthy controls and patients throughout distinct phases of tuberculosis. Gaining insight into the function of the gut microbiome, T cell subsets, and cytokines may help modulate therapeutic strategies for TB.

Chinese families with autosomal recessive hereditary spastic paraplegia caused by mutations in SPG11

Background

Spastic paraplegia type 11 (SPG11) mutations are the most frequent cause of autosomal recessive hereditary spastic paraplegia (ARHSP). We are aiming to identify the causative mutations in SPG11 among families referred to our center with ARHSP in a Chinese population.

Methods

Targeted next-generation sequencing was performed on the patients to identify disease-causing mutations. Variants were analyzed according to their predicted pathogenicity and their relevance to the clinical phenotypes. The segregation in the family members was validated by Sanger sequencing.

Results

A total of 12 mutations in SPG11 gene from 9 index cases were identified, including 6 frameshift mutations, 3 missense mutations, 1 nonsense mutation, 1 splicing mutation, and 1 intron deletion mutation. In 6 of these patients, the mutations were homozygous, and the other 3 patients carried two compound heterozygous mutations. Six mutations were novel; 2 were classified as pathogenic, 1 were considered as likely pathogenic, and the other 3 were variants of unknown significance. Additionally, 1 missense heterozygous variant we found was also carried by amyotrophic lateral sclerosis (ALS) patient. Clinically and electrophysiologically, some of our ARHSP patients partially shared various features of autosomal-recessive juvenile amyotrophic lateral sclerosis (ARJALS), including combination of both UMN and LMN degeneration.

Conclusions

The results contribute to extending of the SPG11 gene mutation spectrum and emphasizing a putative link between ARHSP and ARJALS.

Expect the unexpected: screening for secondary findings in clinical genomics research

BACKGROUND

Due to decreasing cost, and increasing speed and precision, genomic sequencing in research is resulting in the generation of vast amounts of genetic data. The question of how to manage that information has been an area of significant debate. In particular, there has been much discussion around the issue of 'secondary findings' (SF)-findings unrelated to the research that have diagnostic significance.

SOURCES OF DATA

The following includes ethical commentaries, guidelines and policies in respect to large-scale clinical genomics studies.

AREAS OF AGREEMENT

Research participant autonomy and their informed consent are paramount-policies around SF must be made clear and participants must have the choice as to which results they wish to receive, if any.

AREAS OF CONTROVERSY

While many agree that clinically 'actionable' findings should be returned, some question whether they should be actively sought within a research protocol.

GROWING POINTS

SF present challenges to a growing field; diverse policies around their management have the potential to hinder collaboration and future research.

AREAS TIMELY FOR DEVELOPING RESEARCH

The impact of returning SF and accurate estimates of their clinical utility are needed to inform future protocol design.

Next-generation sequencing in neuromuscular diseases

PURPOSE OF REVIEW

Neuromuscular diseases are clinically and genetically heterogeneous and probably contain the greatest proportion of causative Mendelian defects than any other group of conditions. These disorders affect muscle and/or nerves with neonatal, childhood or adulthood onset, with significant disability and early mortality. Along with heterogeneity, unidentified and often very large genes require complementary and comprehensive methods in routine molecular diagnosis. Inevitably, this leads to increased diagnostic delays and challenges in the interpretation of genetic variants.

RECENT FINDINGS

The application of next-generation sequencing, as a research and diagnostic strategy, has made significant progress into solving many of these problems. The analysis of these data is by no means simple, and the clinical input is essential to interpret results.

SUMMARY

In this review, we describe using examples the recent advances in the genetic diagnosis of neuromuscular disorders, in research and clinical practice and the latest developments that are underway in next-generation sequencing. We also discuss the latest collaborative initiatives such as the Genomics England (Department of Health, UK) genome sequencing project that combine rare disease clinical phenotyping with genomics, with the aim of defining the vast majority of rare disease genes in patients as well as modifying risks and pharmacogenomics factors.