Challenges of bringing next generation sequencing technologies to clinical molecular diagnostic laboratories

Challenges and opportunities to bridge translational to clinical research for personalized mitochondrial medicine

Mitochondrial disorders are a group of rare and heterogeneous genetic diseases characterized by dysfunctional mitochondria leading to deficient adenosine triphosphate synthesis and chronic energy deficit in patients. The majority of these patients exhibit a wide range of phenotypic manifestations targeting several organ systems, making their clinical diagnosis and management challenging. Bridging translational to clinical research is crucial for improving the early diagnosis and prognosis of these intractable mitochondrial disorders and for discovering novel therapeutic drug candidates and modalities. This review provides the current state of clinical testing in mitochondrial disorders, discusses the challenges and opportunities for converting basic discoveries into clinical settings, explores the most suited patient-centric approaches to harness the extraordinary heterogeneity among patients affected by the same primary mitochondrial disorder, and describes the current outlook of clinical trials.

Nanopore long-read next-generation sequencing for detection of mitochondrial DNA large-scale deletions

Primary mitochondrial diseases are progressive genetic disorders affecting multiple organs and characterized by mitochondrial dysfunction. These disorders can be caused by mutations in nuclear genes coding proteins with mitochondrial localization or by genetic defects in the mitochondrial genome (mtDNA). The latter include point pathogenic variants and large-scale deletions/rearrangements. MtDNA molecules with the wild type or a variant sequence can exist together in a single cell, a condition known as mtDNA heteroplasmy. MtDNA single point mutations are typically detected by means of Next-Generation Sequencing (NGS) based on short reads which, however, are limited for the identification of structural mtDNA alterations. Recently, new NGS technologies based on long reads have been released, allowing to obtain sequences of several kilobases in length; this approach is suitable for detection of structural alterations affecting the mitochondrial genome. In the present work we illustrate the optimization of two sequencing protocols based on long-read Oxford Nanopore Technology to detect mtDNA structural alterations. This approach presents strong advantages in the analysis of mtDNA compared to both short-read NGS and traditional techniques, potentially becoming the method of choice for genetic studies on mtDNA.

Current research status of blood biomarkers in Alzheimer's disease: Diagnosis and prognosis

Alzheimer's disease (AD), which mainly occurs in the elderly, is a neurodegenerative disease with a hidden onset, which leads to progressive cognitive and behavioral changes. The annually increasing prevalence rate and number of patients with AD exert great pressure on the society. No effective disease-modifying drug treatments are available; thus, there is no cure yet. The disease progression can only be delayed through early detection and drug assistance. Therefore, the importance of exploring associated biomarkers for the early diagnosis and prediction of the disease progress is highlighted. The National Institute on Aging- Alzheimer's Association (NIA-AA) proposed A/T/N diagnostic criteria in 2018, including Aβ42, p-tau, t-tau in cerebrospinal fluid (CSF), and positron emission tomography (PET). However, the invasiveness of lumbar puncture for CSF assessment and non-popularity of PET have prompted researchers to look for minimally invasive, easy to collect, and cost-effective biomarkers. Therefore, studies have largely focused on some novel molecules in the peripheral blood. This is an emerging research field, facing many obstacles and challenges while achieving some promising results.

Homoplasmy of the m. 8993 T>G variant in a patient without MRI findings of Leigh syndrome, ataxia or retinal abnormalities

Leigh syndrome is a progressive neurodegenerative syndrome caused by multiple mitochondrial DNA and nuclear DNA pathological variants. Patients with Leigh syndrome consistently have distinct brain lesions found on MRI scanning involving abnormal signal in the basal ganglia, brainstem and/or cerebellum. Other clinical findings vary depending on the genetic etiology and epigenetic factors. Mitochondrial DNA-derived Leigh syndrome phenotype is thought to be modulated by heteroplasmy level. The classic example is the clinical expression of the pathological variant, m. 8993 T>G. At heteroplasmy levels above 90%, the resulting phenotype is Leigh syndrome, but at levels 70-90% patients present with a syndrome of neuropathy, ataxia and retinitis pigmentosa. We describe a 15-year old girl with homoplasmic variant in m.8993 T>G and clinical and biochemical findings consistent with Leigh syndrome but with normal brain MRI findings and without retinal abnormalities or ataxia.

Clinical Insights into Mitochondrial Neurodevelopmental and Neurodegenerative Disorders: Their Biosignatures from Mass Spectrometry-Based Metabolomics

Mitochondria are dynamic multitask organelles that function as hubs for many metabolic pathways. They produce most ATP via the oxidative phosphorylation pathway, a critical pathway that the brain relies on its energy need associated with its numerous functions, such as synaptic homeostasis and plasticity. Therefore, mitochondrial dysfunction is a prevalent pathological hallmark of many neurodevelopmental and neurodegenerative disorders resulting in altered neurometabolic coupling. With the advent of mass spectrometry (MS) technology, MS-based metabolomics provides an emerging mechanistic understanding of their global and dynamic metabolic signatures. In this review, we discuss the pathogenetic causes of mitochondrial metabolic disorders and the recent MS-based metabolomic advances on their metabolomic remodeling. We conclude by exploring the MS-based metabolomic functional insights into their biosignatures to improve diagnostic platforms, stratify patients, and design novel targeted therapeutic strategies.

An innovative data analysis strategy for accurate next-generation sequencing detection of tumor mitochondrial DNA mutations

Next-generation sequencing technology has been commonly applied to detect mitochondrial DNA (mtDNA) mutations, which are reported to be strongly associated with cancers. However, several key challenges still exist regarding bioinformatics analysis of mtDNA sequencing data that greatly affect the detection accuracy of mtDNA mutations. Here we comprehensively evaluated several key analysis procedures in three different sample types. We found that a trimming procedure was essential for improving mtDNA mapping performance in plasma but not tissue samples. Mapping with a revised Cambridge reference sequence and human genome 19 reference was strongly suggested for mtDNA mutation detection in plasma samples because of the extreme abundance of nuclear DNA of mitochondrial origin. Moreover, our results showed that a setting of 3 mismatches was most appropriate for mtDNA mutation calling. Importantly, we revealed the presence of a negative logarithmic relationship between mtDNA site sequencing depth and minimum detectable mutation frequency and built an innovative and efficient filtering strategy to increase the accuracy and sensitivity of mutation detection. Finally, we verified that higher sequencing depth was required for a PCR-based compared with a capture-based enrichment strategy. We established an innovative data analysis strategy that is of great significance for improving the accuracy of mtDNA mutation detection for different types of tumor samples.

Maternally inherited mitochondrial respiratory disorders: from pathogenetic principles to therapeutic implications

Maternally inherited mitochondrial respiratory disorders are rare, progressive, and multi-systemic diseases that remain intractable, with no effective therapeutic interventions. Patients share a defective oxidative phosphorylation pathway responsible for mitochondrial ATP synthesis, in most cases due to pathogenic mitochondrial variants transmitted from mother to child or to a rare de novo mutation or large-scale deletion of the mitochondrial genome. The clinical diagnosis of these mitochondrial diseases is difficult due to exceptionally high clinical variability, while their genetic diagnosis has improved with the advent of next-generation sequencing. The mechanisms regulating the penetrance of the mitochondrial variants remain unresolved with the patient's nuclear background, epigenomic regulation, heteroplasmy, mitochondrial haplogroups, and environmental factors thought to act as rheostats. The lack of animal models mimicking the phenotypic manifestations of these disorders has hampered efforts toward curative therapies. Patient-derived cellular paradigms provide alternative models for elucidating the pathogenic mechanisms and screening pharmacological small molecules to enhance mitochondrial function. Recent progress has been made in designing promising approaches to curtail the negative impact of dysfunctional mitochondria and alleviate clinical symptoms: 1) boosting mitochondrial biogenesis; 2) shifting heteroplasmy; 3) reprogramming metabolism; and 4) administering hypoxia-based treatment. Here, we discuss their varying efficacies and limitations and provide an outlook on their therapeutic potential and clinical application.

Identification of unique and shared mitochondrial DNA mutations in neurodegeneration and cancer by single-cell mitochondrial DNA structural variation sequencing (MitoSV-seq)

Background

Point mutations and structural variations (SVs) in mitochondrial DNA (mtDNA) contribute to many neurodegenerative diseases. Technical limitations and heteroplasmy, however, have impeded their identification, preventing these changes from being examined in neurons in healthy and disease states.

Methods

We have developed a high-resolution technique—Mitochondrial DNA Structural Variation Sequencing (MitoSV-seq)—that identifies all types of mtDNA SVs and single-nucleotide variations (SNVs) in single neurons and novel variations that have been undetectable with conventional techniques.

Findings

Using MitoSV-seq, we discovered SVs/SNVs in dopaminergic neurons in the Ifnar1^−/− murine model of Parkinson disease. Further, MitoSV-seq was found to have broad applicability, delivering high-quality, full-length mtDNA sequences in a species-independent manner from human PBMCs, haematological cancers, and tumour cell lines, regardless of heteroplasmy. We characterised several common SVs in haematological cancers (AML and MDS) that were linked to the same mtDNA region, MT-ND5, using only 10 cells, indicating the power of MitoSV-seq in determining single-cancer-cell ontologies. Notably, the MT-ND5 hotspot, shared between all examined cancers and Ifnar1^−/− dopaminergic neurons, suggests that its mutations have clinical value as disease biomarkers.

Interpretation

MitoSV-seq identifies disease-relevant mtDNA mutations in single cells with high resolution, rendering it a potential drug screening platform in neurodegenerative diseases and cancers.

Funding

The Lundbeck Foundation, Danish Council for Independent Research-Medicine, and European Union Horizon 2020 Research and Innovation Programme.

Bioinformatics Tools and Databases to Assess the Pathogenicity of Mitochondrial DNA Variants in the Field of Next Generation Sequencing

The development of next generation sequencing (NGS) has greatly enhanced the diagnosis of mitochondrial disorders, with a systematic analysis of the whole mitochondrial DNA (mtDNA) sequence and better detection sensitivity. However, the exponential growth of sequencing data renders complex the interpretation of the identified variants, thereby posing new challenges for the molecular diagnosis of mitochondrial diseases. Indeed, mtDNA sequencing by NGS requires specific bioinformatics tools and the adaptation of those developed for nuclear DNA, for the detection and quantification of mtDNA variants from sequence alignment to the calling steps, in order to manage the specific features of the mitochondrial genome including heteroplasmy, i.e., coexistence of mutant and wildtype mtDNA copies. The prioritization of mtDNA variants remains difficult, relying on a limited number of specific resources: population and clinical databases, and in silico tools providing a prediction of the variant pathogenicity. An evaluation of the most prominent bioinformatics tools showed that their ability to predict the pathogenicity was highly variable indicating that special efforts should be directed at developing new bioinformatics tools dedicated to the mitochondrial genome. In addition, massive parallel sequencing raised several issues related to the interpretation of very low mtDNA mutational loads, discovery of variants of unknown significance, and mutations unrelated to patient phenotype or the co-occurrence of mtDNA variants. This review provides an overview of the current strategies and bioinformatics tools for accurate annotation, prioritization and reporting of mtDNA variations from NGS data, in order to carry out accurate genetic counseling in individuals with primary mitochondrial diseases.

Characterization of minority HIV-1 drug resistant variants in the United Kingdom following the verification of a deep sequencing-based HIV-1 genotyping and tropism assay

BACKGROUND

The widespread global access to antiretroviral drugs has led to considerable reductions in morbidity and mortality but, unfortunately, the risk of virologic failure increases with the emergence, and potential transmission, of drug resistant viruses. Detecting and quantifying HIV-1 drug resistance has therefore become the standard of care when designing new antiretroviral regimens. The sensitivity of Sanger sequencing-based HIV-1 genotypic assays is limited by its inability to identify minority members of the quasispecies, i.e., it only detects variants present above ~ 20% of the viral population, thus, failing to detect minority variants below this threshold. It is clear that deep sequencing-based HIV-1 genotyping assays are an important step change towards accurately monitoring HIV-infected individuals.

METHODS

We implemented and verified a clinically validated HIV-1 genotyping assay based on deep sequencing (DEEPGEN™) in two clinical laboratories in the United Kingdom: St. George's University Hospitals Healthcare NHS Foundation Trust (London) and at NHS Lothian (Edinburgh), to characterize minority HIV-1 variants in 109 plasma samples from ART-naïve or -experienced individuals.

RESULTS

Although subtype B HIV-1 strains were highly prevalent (44%, 48/109), most individuals were infected with non-B subtype viruses (i.e., A1, A2, C, D, F1, G, CRF02_AG, and CRF01_AE). DEEPGEN™ was able to accurately detect drug resistance-associated mutations not identified using standard Sanger sequencing-based tests, which correlated significantly with patient's antiretroviral treatment histories. A higher proportion of minority PI-, NRTI-, and NNRTI-resistance mutations was detected in NHS Lothian patients compared to individuals from St. George's, mainly M46I/L and I50 V (associated with PIs), D67 N, K65R, L74I, M184 V/I, and K219Q (NRTIs), and L100I (NNRTIs). Interestingly, we observed an inverse correlation between intra-patient HIV-1 diversity and CD4⁺ T cell counts in the NHS Lothian patients.

CONCLUSIONS

This is the first study evaluating the transition, training, and implementation of DEEPGEN™ between three clinical laboratories in two different countries. More importantly, we were able to characterize the HIV-1 drug resistance profile (including minority variants), coreceptor tropism, subtyping, and intra-patient viral diversity in patients from the United Kingdom, providing a rigorous foundation for basing clinical decisions on highly sensitive and cost-effective deep sequencing-based HIV-1 genotyping assays in the country.

eKLIPse: a sensitive tool for the detection and quantification of mitochondrial DNA deletions from next-generation sequencing data

PURPOSE

Accurate detection of mitochondrial DNA (mtDNA) alterations is essential for the diagnosis of mitochondrial diseases. The development of high-throughput sequencing technologies has enhanced the detection sensitivity of mtDNA pathogenic variants, but the detection of mtDNA rearrangements, especially multiple deletions, is still poorly processed. Here, we present eKLIPse, a sensitive and specific tool allowing the detection and quantification of large mtDNA rearrangements from single and paired-end sequencing data.

METHODS

The methodology was first validated using a set of simulated data to assess the detection sensitivity and specificity, and second with a series of sequencing data from mitochondrial disease patients carrying either single or multiple deletions, related to pathogenic variants in nuclear genes involved in mtDNA maintenance.

RESULTS

eKLIPse provides the precise breakpoint positions and the cumulated percentage of mtDNA rearrangements at a given gene location with a detection sensitivity lower than 0.5% mutant. eKLIPse software is available either as a script to be integrated in a bioinformatics pipeline, or as user-friendly graphical interface to visualize the results through a Circos representation ( https://github.com/dooguypapua/eKLIPse ).

CONCLUSION

Thus, eKLIPse represents a useful resource to study the causes and consequences of mtDNA rearrangements, for further genotype/phenotype correlations in mitochondrial disorders.

Molecular diagnosis of coenzyme Q10 deficiency: an update

INTRODUCTION

Coenzyme Q₁₀ (CoQ) deficiency syndromes comprise a growing number of genetic disorders. While primary CoQ deficiency syndromes are rare diseases, secondary deficiencies have been related to both genetic and environmental conditions, which are the main causes of biochemical CoQ deficiency. The diagnosis is the essential first step for planning future treatment strategies, as the potential treatability of CoQ deficiency is the most critical issue for the patients. Areas covered: While the quickest and most effective tool to define a CoQ-deficient status is its biochemical determination in biological fluids or tissues, this quantification does not provide a definite diagnosis of a CoQ-deficient status nor insight about the genetic etiology of the disease. The different laboratory tests to check for CoQ deficiency are evaluated in order to choose the best diagnostic pathway for the patient. Expert commentary: New insights are being discovered about the implication of new proteins in the intricate CoQ biosynthetic pathway. These insights reinforce the idea that next generation sequencing diagnostic strategies are the unique alternative in terms of rapid and accurate molecular diagnosis of CoQ deficiency.

Digital PCR methods improve detection sensitivity and measurement precision of low abundance mtDNA deletions

Mitochondrial DNA (mtDNA) mutations are a common cause of primary mitochondrial disorders, and have also been implicated in a broad collection of conditions, including aging, neurodegeneration, and cancer. Prevalent among these pathogenic variants are mtDNA deletions, which show a strong bias for the loss of sequence in the major arc between, but not including, the heavy and light strand origins of replication. Because individual mtDNA deletions can accumulate focally, occur with multiple mixed breakpoints, and in the presence of normal mtDNA sequences, methods that detect broad-spectrum mutations with enhanced sensitivity and limited costs have both research and clinical applications. In this study, we evaluated semi-quantitative and digital PCR-based methods of mtDNA deletion detection using double-stranded reference templates or biological samples. Our aim was to describe key experimental assay parameters that will enable the analysis of low levels or small differences in mtDNA deletion load during disease progression, with limited false-positive detection. We determined that the digital PCR method significantly improved mtDNA deletion detection sensitivity through absolute quantitation, improved precision and reduced assay standard error.

The heritable path of human physical performance: from single polymorphisms to the "next generation"

Human physical performance is a complex multifactorial trait. Historically, environmental factors (e.g., diet, training) alone have been unable to explain the basis of all prominent phenotypes for physical performance. Therefore, there has been an interest in the study of the contribution of genetic factors to the development of these phenotypes. Support for a genetic component is found with studies that shown that monozygotic twins were more similar than were dizygotic twins for many physiological traits. The evolution of molecular techniques and the ability to scan the entire human genome enabled association of several genetic polymorphisms with performance. However, some biases related to the selection of cohorts and inadequate definition of the study variables have complicated the already difficult task of studying such a large and polymorphic genome, often resulting in inconsistent results about the influence of candidate genes. This review aims to provide a critical overview of heritable genetic aspects. Novel molecular technologies, such as next-generation sequencing, are discussed and how they can contribute to improving understanding of the molecular basis for athletic performance. It is important to ensure that the large amount of data that can be generated using these tools will be used effectively by ensuring well-designed studies.

Molecular diagnosis of coenzyme Q10 deficiency

Coenzyme Q10 (CoQ) deficiency syndromes comprise a growing number of neurological and extraneurological disorders. Primary-genetic but also secondary CoQ deficiencies have been reported. The biochemical determination of CoQ is a good tool for the rapid identification of CoQ deficiencies but does not allow the selection of candidate genes for molecular diagnosis. Moreover, the metabolic pathway for CoQ synthesis is an intricate and not well-understood process, where a large number of genes are implicated. Thus, only next-generation sequencing techniques (either genetic panels of whole-exome and -genome sequencing) are at present appropriate for a rapid and realistic molecular diagnosis of these syndromes. The potential treatability of CoQ deficiency strongly supports the necessity of a rapid molecular characterization of patients, since primary CoQ deficiencies may respond well to CoQ treatment.

Understanding the limitations of next generation sequencing informatics, an approach to clinical pipeline validation using artificial data sets

The advantages of massively parallel sequencing are quickly being realized through the adoption of comprehensive genomic panels across the spectrum of genetic testing. Despite such widespread utilization of next generation sequencing (NGS), a major bottleneck in the implementation and capitalization of this technology remains in the data processing steps, or bioinformatics. Here we describe our approach to defining the limitations of each step in the data processing pipeline by utilizing artificial amplicon data sets to simulate a wide spectrum of genomic alterations. Through this process, we identified limitations of insertion, deletion (indel), and single nucleotide variant (SNV) detection using standard approaches and described novel strategies to improve overall somatic mutation detection. Using these artificial data sets, we were able to demonstrate that NGS assays can have robust mutation detection if the data can be processed in a way that does not lead to large genomic alterations landing in the unmapped data (i.e., trash). By using these pipeline modifications and a new variant caller, AbsoluteVar, we have been able to validate SNV mutation detection to 100% sensitivity and specificity with an allele frequency as low 4% and detection of indels as large as 90 bp. Clinical validation of NGS relies on the ability for mutation detection across a wide array of genetic anomalies, and the utility of artificial data sets demonstrates a mechanism to intelligently test a vast array of mutation types.

Massively parallel sequencing for diagnosing clinically and genetically heterogeneous disorders

Massively parallel sequencing technology has great potential to identify the precise molecular causes of human disorders, which were once considered difficult to diagnose for either inherited Mendelian or oncological diseases. Besides being a valuable tool for gene discovery, this technology has also gained tremendous momentum in clinical molecular diagnostic laboratories. There are a wide variety of clinical applications recently developed to meet the clinical demands for personalized medicine. This article discusses these up-to-date massively parallel sequencing clinical applications and emphasizes various disorders that can be targeted, as well as some challenges faced in the process of implementing these assays in the clinical setting.