Impact of next-generation sequencing on diagnosis and management of neurometabolic disorders: current advances and future perspectives

Comprehensive genome analysis and variant detection at scale using DRAGEN

Research and medical genomics require comprehensive, scalable methods for the discovery of novel disease targets, evolutionary drivers and genetic markers with clinical significance. This necessitates a framework to identify all types of variants independent of their size or location. Here we present DRAGEN, which uses multigenome mapping with pangenome references, hardware acceleration and machine learning-based variant detection to provide insights into individual genomes, with ~30 min of computation time from raw reads to variant detection. DRAGEN outperforms current state-of-the-art methods in speed and accuracy across all variant types (single-nucleotide variations, insertions or deletions, short tandem repeats, structural variations and copy number variations) and incorporates specialized methods for analysis of medically relevant genes. We demonstrate the performance of DRAGEN across 3,202 whole-genome sequencing datasets by generating fully genotyped multisample variant call format files and demonstrate its scalability, accuracy and innovation to further advance the integration of comprehensive genomics. Overall, DRAGEN marks a major milestone in sequencing data analysis and will provide insights across various diseases, including Mendelian and rare diseases, with a highly comprehensive and scalable platform.

Leaving no patient behind! Expert recommendation in the use of innovative technologies for diagnosing rare diseases

Genetic diagnosis plays a crucial role in rare diseases, particularly with the increasing availability of emerging and accessible treatments. The International Rare Diseases Research Consortium (IRDiRC) has set its primary goal as: "Ensuring that all patients who present with a suspected rare disease receive a diagnosis within one year if their disorder is documented in the medical literature". Despite significant advances in genomic sequencing technologies, more than half of the patients with suspected Mendelian disorders remain undiagnosed. In response, IRDiRC proposes the establishment of "a globally coordinated diagnostic and research pipeline". To help facilitate this, IRDiRC formed the Task Force on Integrating New Technologies for Rare Disease Diagnosis. This multi-stakeholder Task Force aims to provide an overview of the current state of innovative diagnostic technologies for clinicians and researchers, focusing on the patient's diagnostic journey. Herein, we provide an overview of a broad spectrum of emerging diagnostic technologies involving genomics, epigenomics and multi-omics, functional testing and model systems, data sharing, bioinformatics, and Artificial Intelligence (AI), highlighting their advantages, limitations, and the current state of clinical adaption. We provide expert recommendations outlining the stepwise application of these innovative technologies in the diagnostic pathways while considering global differences in accessibility. The importance of FAIR (Findability, Accessibility, Interoperability, and Reusability) and CARE (Collective benefit, Authority to control, Responsibility, and Ethics) data management is emphasized, along with the need for enhanced and continuing education in medical genomics. We provide a perspective on future technological developments in genome diagnostics and their integration into clinical practice. Lastly, we summarize the challenges related to genomic diversity and accessibility, highlighting the significance of innovative diagnostic technologies, global collaboration, and equitable access to diagnosis and treatment for people living with rare disease.

Comprehensive and accurate genome analysis at scale using DRAGEN accelerated algorithms

Research and medical genomics require comprehensive and scalable solutions to drive the discovery of novel disease targets, evolutionary drivers, and genetic markers with clinical significance. This necessitates a framework to identify all types of variants independent of their size (e.g., SNV/SV) or location (e.g., repeats). Here we present DRAGEN that utilizes novel methods based on multigenomes, hardware acceleration, and machine learning based variant detection to provide novel insights into individual genomes with ~30min computation time (from raw reads to variant detection). DRAGEN outperforms all other state-of-the-art methods in speed and accuracy across all variant types (SNV, indel, STR, SV, CNV) and further incorporates specialized methods to obtain key insights in medically relevant genes (e.g., HLA, SMN, GBA). We showcase DRAGEN across 3,202 genomes and demonstrate its scalability, accuracy, and innovations to further advance the integration of comprehensive genomics for research and medical applications.

The diagnostic rate of inherited metabolic disorders by exome sequencing in a cohort of 547 individuals with developmental disorders

Considering that some Inherited Metabolic Disorders (IMDs) can be diagnosed in patients with no distinctive clinical features of IMDs, we aimed to evaluate the power of exome sequencing (ES) to diagnose IMDs within a cohort of 547 patients with unspecific developmental disorders (DD). IMDs were diagnosed in 12% of individuals with causative diagnosis (177/547). There are clear benefits of using ES in DD to diagnose IMD, particularly in cases where biochemical studies are unavailable.

Synopsis

Exome sequencing and diagnostic rate of Inherited Metabolic Disorders in individuals with developmental disorders.

Genetic Modifiers and Rare Mendelian Disease

Despite advances in high-throughput sequencing that have revolutionized the discovery of gene defects in rare Mendelian diseases, there are still gaps in translating individual genome variation to observed phenotypic outcomes. While we continue to improve genomics approaches to identify primary disease-causing variants, it is evident that no genetic variant acts alone. In other words, some other variants in the genome (genetic modifiers) may alleviate (suppress) or exacerbate (enhance) the severity of the disease, resulting in the variability of phenotypic outcomes. Thus, to truly understand the disease, we need to consider how the disease-causing variants interact with the rest of the genome in an individual. Here, we review the current state-of-the-field in the identification of genetic modifiers in rare Mendelian diseases and discuss the potential for future approaches that could bridge the existing gap.

De novo pathogenic DNM1L variant in a patient diagnosed with atypical hereditary sensory and autonomic neuropathy

Background

Profiling the entire genome at base pair resolution in a single test offers novel insights into disease by means of dissection of genetic contributors to phenotypic features.

Methods

We performed genome sequencing for a patient who presented with atypical hereditary sensory and autonomic neuropathy, severe epileptic encephalopathy, global developmental delay, and growth hormone deficiency.

Results

Assessment of the variants detected by mapped sequencing reads followed by Sanger confirmation revealed that the proband is a compound heterozygote for rare variants within RETREG1 (FAM134B), a gene associated with a recessive form of hereditary sensory and autonomic neuropathy, but not with epileptic encephalopathy or global developmental delay. Further analysis of the data also revealed a heterozygous missense variant in DNM1L, a gene previously implicated in an autosomal dominant encephalopathy, epilepsy, and global developmental delay and confirmed by Sanger sequencing to be a de novo variant not present in parental genomes.

Conclusions

Our findings emphasize the importance of genome‐wide sequencing in patients with a well‐characterized genetic disease with atypical presentation. This approach reduces the potential for misdiagnoses.

Changes in pediatric plasma acylcarnitines upon fasting for refined interpretation of metabolic stress

BACKGROUND

Childhood fasting intolerance is a life-threatening problem associated with various inborn errors of metabolism. Plasma acylcarnitines reflect fatty acid oxidation and help determine fasting intolerance etiology. Pediatric reference values of plasma acylcarnitines upon fasting are not available, complicating interpretation of stress samples.

METHODS

Retrospective analysis of supervised clinical fasting studies between 01/2005-09/2012. Exclusion criteria involved patients with (suspected) disorders, repeated tests or incomplete results. Remaining children were grouped according to age: group A (≤24 months), B (25-84 months) and C (≥85 months). Median and 2.5^th to 97.5^th percentiles of basic metabolic parameters and acylcarnitines were determined at start and end of testing on the ward and analyzed for significant differences (p<0.05).

RESULTS

Out of 127 fasting studies, 48 were included: group A (n=13), B (n=23) and C (n=12). Hypoglycemia occurred in 21%. Children from group C demonstrated significantly higher end glucose concentrations while end ketone body concentrations were significantly lower compared to younger children. In all groups, free carnitine and C3-carnitine significantly decreased upon fasting, while C2-, C6-, C12:1-, C12-, C14:1-, C14-, C16:1- and C16-carnitine significantly increased. End concentrations of C6-, C12:1-, C12-, C14:1-, C14-, C16:1-, C16- and C18:1-carnitine were significantly lower in children ≥85 months compared to younger children.

CONCLUSIONS

Fasting-induced counter-regulatory mechanisms to maintain energy homeostasis are age-dependent. This influences the changes in basic metabolic parameters and acylcarnitine profiles. Our data enable improved interpretation of the individual fasting response and may support assessment of minimal safe fasting times or treatment responses in patients.

Biochemical Screening of Intellectually Disabled Patients: A Stepping Stone to Initiate a Newborn Screening Program in Pakistan

Inborn errors of metabolism (IEMs) are rare group of genetic disorders comprising of more than 1,000 different types. Around 200 of IEMs are potentially treatable through diet, pharmacological and other therapies, if diagnosed earlier in life. IEMs can be diagnosed early through newborn screening (NBS) programs, which are in place in most of the developed countries. However, establishing a NBS in a developing country is a challenging task due to scarcity of disease related data, large population size, poor economy, and burden of other common disorders. Since, not enough data is available for the prevalence of IEMs in Pakistan; therefore, in this study, we set out to find the prevalence of various treatable IEMs in a cohort of intellectually disabled patients suspected for IEMs, which will help us to initiate a NBS program for the most frequent IEMs in Pakistan. Therefore, a total of 429 intellectually disabled (IQ <70) patient samples were collected from Pakistan. A subset of 113 patient samples was selected based on the clinical information for the detailed biochemical screening. Advance analytical techniques like, Amino Acid Analyzer, GC-MS, UHPLC-MS, and MS/MS were used to screen for different treatable IEMs like aminoacidopathies, fatty acid β-oxidation disorders and mucopolysaccharidoses (MPS) etc. A total of 14 patients were diagnosed with an IEM i.e., 9 with homocystinuria, 2 with MPS, 2 with Guanidinoacetate methyltransferase (GAMT) deficiency and 1 with sitosterolemia. These IEMs are found frequent in the collected patient samples from Pakistan. Thus, present study can help to take an initiative step to start a NBS program in Pakistan, especially for the homocystinuria having highest incidence among aminoacidopathies in the studied patients, and which is amenable to treatment. This endeavor will pave the way for a healthier life of affected patients and will lessen the burden on their families and society.

Uncovering Missing Heritability in Rare Diseases

The problem of 'missing heritability' affects both common and rare diseases hindering: discovery, diagnosis, and patient care. The 'missing heritability' concept has been mainly associated with common and complex diseases where promising modern technological advances, like genome-wide association studies (GWAS), were unable to uncover the complete genetic mechanism of the disease/trait. Although rare diseases (RDs) have low prevalence individually, collectively they are common. Furthermore, multi-level genetic and phenotypic complexity when combined with the individual rarity of these conditions poses an important challenge in the quest to identify causative genetic changes in RD patients. In recent years, high throughput sequencing has accelerated discovery and diagnosis in RDs. However, despite the several-fold increase (from ~10% using traditional to ~40% using genome-wide genetic testing) in finding genetic causes of these diseases in RD patients, as is the case in common diseases-the majority of RDs are also facing the 'missing heritability' problem. This review outlines the key role of high throughput sequencing in uncovering genetics behind RDs, with a particular focus on genome sequencing. We review current advances and challenges of sequencing technologies, bioinformatics approaches, and resources.

Identification of human D lactate dehydrogenase deficiency

Phenotypic and biochemical categorization of humans with detrimental variants can provide valuable information on gene function. We illustrate this with the identification of two different homozygous variants resulting in enzymatic loss-of-function in LDHD, encoding lactate dehydrogenase D, in two unrelated patients with elevated D-lactate urinary excretion and plasma concentrations. We establish the role of LDHD by demonstrating that LDHD loss-of-function in zebrafish results in increased concentrations of D-lactate. D-lactate levels are rescued by wildtype LDHD but not by patients’ variant LDHD, confirming these variants’ loss-of-function effect. This work provides the first in vivo evidence that LDHD is responsible for human D-lactate metabolism. This broadens the differential diagnosis of D-lactic acidosis, an increasingly recognized complication of short bowel syndrome with unpredictable onset and severity. With the expanding incidence of intestinal resection for disease or obesity, the elucidation of this metabolic pathway may have relevance for those patients with D-lactic acidosis.

D-lactic acidosis typically occurs in the context of short bowel syndrome; excess D-lactate is produced by intestinal bacteria. Here, the authors identify two point mutations in the human lactate dehydrogenase D (LDHD) gene that cause enzymatic loss of function and are associated with elevated plasma D-lactate.

The role of the clinician in the multi-omics era: are you ready?

Since Garrod's first description of alkaptonuria in 1902, and newborn screening for phenylketonuria introduced in the 1960s, P4 medicine (preventive, predictive, personalized, and participatory) has been a reality for the clinician serving patients with inherited metabolic diseases. The era of high-throughput technologies promises to accelerate its scale dramatically. Genomics, transcriptomics, epigenomics, proteomics, glycomics, metabolomics, and lipidomics offer an amazing opportunity for holistic investigation and contextual pathophysiologic understanding of inherited metabolic diseases for precise diagnosis and tailored treatment. While each of the -omics technologies is important to systems biology, some are more mature than others. Exome sequencing is emerging as a reimbursed test in clinics around the world, and untargeted metabolomics has the potential to serve as a single biochemical testing platform. The challenge lies in the integration and cautious interpretation of these big data, with translation into clinically meaningful information and/or action for our patients. A daunting but exciting task for the clinician; we provide clinical cases to illustrate the importance of his/her role as the connector between physicians, laboratory experts and researchers in the basic, computer, and clinical sciences. Open collaborations, data sharing, functional assays, and model organisms play a key role in the validation of -omics discoveries. Having all the right expertise at the table when discussing the diagnostic approach and individualized management plan according to the information yielded by -omics investigations (e.g., actionable mutations, novel therapeutic interventions), is the stepping stone of P4 medicine. Patient participation and the adjustment of the medical team's plan to his/her and the family's wishes most certainly is the capstone. Are you ready?