Human genome sequencing in health and disease

Alzheimer's as a Systems-Level Disease Involving the Interplay of Multiple Cellular Networks

Alzheimer's disease (AD), and many neurodegenerative disorders, are multifactorial in nature. They involve a combination of genomic, epigenomic, interactomic and environmental factors. Progress is being made, and these complex diseases are beginning to be understood as having their origin in altered states of biological networks at the cellular level. In the case of AD, genomic susceptibility and mechanisms leading to (or accompanying) the impairment of the central Amyloid Precursor Protein (APP) processing and tau networks are widely accepted as major contributors to the diseased state. The derangement of these networks may result in both the gain and loss of functions, increased generation of toxic species (e.g., toxic soluble oligomers and aggregates) and imbalances, whose effects can propagate to supra-cellular levels. Although well sustained by empirical data and widely accepted, this global perspective often overlooks the essential roles played by the main counteracting homeostatic networks (e.g., protein quality control/proteostasis, unfolded protein response, protein folding chaperone networks, disaggregases, ER-associated degradation/ubiquitin proteasome system, endolysosomal network, autophagy, and other stress-protective and clearance networks), whose relevance to AD is just beginning to be fully realized. In this chapter, an integrative perspective is presented. Alzheimer's disease is characterized to be a result of: (a) intrinsic genomic/epigenomic susceptibility and, (b) a continued dynamic interplay between the deranged networks and the central homeostatic networks of nerve cells. This interplay of networks will underlie both the onset and rate of progression of the disease in each individual. Integrative Systems Biology approaches are required to effect its elucidation. Comprehensive Systems Biology experiments at different 'omics levels in simple model organisms, engineered to recapitulate the basic features of AD may illuminate the onset and sequence of events underlying AD. Indeed, studies of models of AD in simple organisms, differentiated cells in culture and rodents are beginning to offer hope that the onset and progression of AD, if detected at an early stage, may be stopped, delayed, or even reversed, by activating or modulating networks involved in proteostasis and the clearance of toxic species. In practice, the incorporation of next-generation neuroimaging, high-throughput and computational approaches are opening the way towards early diagnosis well before irreversible cell death. Thus, the presence or co-occurrence of: (a) accumulation of toxic Aβ oligomers and tau species; (b) altered splicing and transcriptome patterns; (c) impaired redox, proteostatic, and metabolic networks together with, (d) compromised homeostatic capacities may constitute relevant 'AD hallmarks at the cellular level' towards reliable and early diagnosis. From here, preventive lifestyle changes and tailored therapies may be investigated, such as combined strategies aimed at both lowering the production of toxic species and potentiating homeostatic responses, in order to prevent or delay the onset, and arrest, alleviate, or even reverse the progression of the disease.

Assessing the Costs and Cost-Effectiveness of Genomic Sequencing

Despite dramatic drops in DNA sequencing costs, concerns are great that the integration of genomic sequencing into clinical settings will drastically increase health care expenditures. This commentary presents an overview of what is known about the costs and cost-effectiveness of genomic sequencing. We discuss the cost of germline genomic sequencing, addressing factors that have facilitated the decrease in sequencing costs to date and anticipating the factors that will drive sequencing costs in the future. We then address the cost-effectiveness of diagnostic and pharmacogenomic applications of genomic sequencing, with an emphasis on the implications for secondary findings disclosure and the integration of genomic sequencing into general patient care. Throughout, we ground the discussion by describing efforts in the MedSeq Project, an ongoing randomized controlled clinical trial, to understand the costs and cost-effectiveness of integrating whole genome sequencing into cardiology and primary care settings.

Next Generation Sequencing in the Clinic: a Patterns of Care Study in a Retrospective Cohort of Subjects Referred to a Genetic Medicine Clinic for Suspected Lynch Syndrome

Next generation sequencing (NGS) gene panels are increasingly used in medical genetics clinics for the evaluation of common inherited cancer syndromes, but the clinical efficacy of these tests, and the factors driving clinical providers to order them are unclear. We conducted a patterns-of-care study to compare patients evaluated with NGS gene panels with a reference group. We abstracted demographic, socioeconomic, and clinical information in a retrospective cohort of patients referred to a large medical genetics clinic for evaluation of inherited colorectal cancer and polyposis syndromes. Patients tested with NGS gene panels were more likely to be insured compared to the reference group (85.3 % vs. 69.2 %, p = 0.0068),less likely to have prior tumor tissue testing (29.4 % vs. 54.3 %, p = 0.0004), and less likely to have an abnormal tumor tissue test result (46.7 % vs. 74.5 %, p = 0.01). No significant differences were found between groups in age, gender, race, employment status, personal history of colorectal cancer, or proportion of patients fulfilling Lynch syndrome clinical criteria. Patients with NGS testing were less likely to have a pathogenic/likely pathogenic variant detected (13.7 % vs. 31.9 %, p = 0.002). Patients referred for NGS testing to evaluate inherited colorectal cancer/polyposis risk appear to undergo tumor tissue testing less frequently than non-NGS testing patients. Further studies are needed to assess the most effective and cost-effective approach to genomic diagnosis in this patient population.

A homozygous mutation in PEX16 identified by whole-exome sequencing ending a diagnostic odyssey

We present a patient with a unique neurological phenotype with a progressive neurodegenerative phenotype. An 18-year diagnostic odyssey for the patient ended when exome sequencing identified a homozygous PEX16 mutation suggesting an atypical peroxisomal biogenesis disorder (PBD). Interestingly, the patient's peroxisomal biochemical abnormalities were subtle, such that plasma very-long-chain fatty acids initially failed to provide a diagnosis. This case suggests next-generation sequencing may be diagnostic in some atypical peroxisomal biogenesis disorders.

Serum Levels of Stress Hormones and Oxidative Stress Biomarkers Differ according to Sasang Constitutional Type

Objectives. This study investigated whether Sasang constitutional type is associated with differences in the serum levels of stress hormones and oxidative stress. Methods. A total of 236 participants (77 males and 159 females) were enrolled. The serum levels of cortisol, adrenaline, reactive oxygen species (ROS), and malondialdehyde (MDA) were analyzed. Results. The distribution of Sasang constitutional types was as follows: Taeumin, 35.6%; Soumin, 33.0%; and Soyangin, 31.4%. The serum cortisol levels of Taeumin were significantly lower than Soumin (p < 0.1 in both sexes) and Soyangin (p < 0.05 in males and p < 0.1 in females). The adrenaline levels were also significantly lower in Taeumin than in Soumin (p < 0.05 in males and p < 0.1 in females) and Soyangin (p < 0.1 in males). Serum ROS levels were significantly higher in Soyangin than in Taeumin and Soumin (p < 0.05 in males), whereas MDA levels were significantly lower in Taeumin compared with Soumin and Soyangin (p < 0.05 in males and p < 0.1 in females). Conclusion. Taeumin type may tolerate psychological or oxidative stress better than other types, which suggests a biological mechanism to explain the different pathophysiological features of Sasang constitutional types.

Identification of susceptibility genes in non-syndromic cleft lip with or without cleft palate using whole-exome sequencing

Background

Non-syndromic cleft lip with or without cleft palate (NSCL/P) is among the most common congenital malformations. The etiology of NSCL/P remains poorly characterized owing to its complex genetic heterogeneity. The objective of this study was to identify genetic variants that increase susceptibility to NSCL/P.

Material and Methods

Whole-exome sequencing (WES) was performed in 8 fetuses with NSCL/P in China. Bioinformatics analysis was performed using commercially available software. Variants detected by WES were validated by Sanger sequencing.

Results

By filtering out synonymous variants in exons, we identified average 8575 nonsynonymous single nucleotide variants (SNVs). We subsequently compared the SNVs against public databases including NCBI dbSNP build 135 and 1000 Genomes Project and obtained an average of 203 SNVs. Total 12 reported candidate genes were verified by Sanger sequencing. Sanger sequencing also confirmed 16 novel SNVs shared by two or more samples.

Conclusions

We have found and confirmed 16 susceptibility genes responsible for NSCL/P, which may play important role in the etiology of NSCL/P. The susceptibility genes identified in this study will not only be useful in revealing the etiology of NSCL/P but also in diagnosis and treatment of the patients with NSCL/P.

Key words:Non-syndromic cleft lip with or without cleft palate, whole-exome sequencing, sanger sequencing, susceptibility gene, single nucleotide variants (SNVs).

Clinical and Genomic Approaches for the Diagnosis of Craniofacial Disorders

With the rapid development of readily accessible molecular diagnostic tools, a growing number of patients and families with craniofacial anomalies will have access to a confirmed molecular diagnosis. This chapter provides an overview to current clinical and molecular resources and approaches used by diagnostician today. Clarifying the underlying cause of a congenital defect is necessary to provide proper counseling, identify carrier/risk status of family members, inform prognosis and direct appropriate management, treatments, and surveillance recommendations. The use of molecular testing has evolved to confirm a suspected clinical diagnosis, establish a diagnosis in an unclear condition and end a diagnostic odyssey for many children with underlying syndromes, but the use of these techniques to understand common nonsyndromic malformations like clefts and craniosynostosis is still an active area of research that will contribute to clinical care in the future.

Management of Incidental Findings in Clinical Genomic Sequencing

Genomic sequencing is becoming accurate, fast, and increasingly inexpensive, and is rapidly being incorporated into clinical practice. Incidental or secondary findings, which can occur in large numbers from genomic sequencing, are a potential barrier to the utility of this new technology due to their relatively high prevalence and the lack of evidence or guidelines available to guide their clinical interpretation. This unit reviews the definition, classification, and management of incidental findings from genomic sequencing. The unit focuses on the clinical aspects of handling incidental findings, with an emphasis on the key role of clinical context in defining incidental findings and determining their clinical relevance and utility.

The role of combined SNV and CNV burden in patients with distal symmetric polyneuropathy

PURPOSE

Charcot-Marie-Tooth (CMT) disease is a heterogeneous group of genetic disorders of the peripheral nervous system. Copy-number variants (CNVs) contribute significantly to CMT, as duplication of PMP22 underlies the majority of CMT1 cases. We hypothesized that CNVs and/or single-nucleotide variants (SNVs) might exist in patients with CMT with an unknown molecular genetic etiology.

METHODS

Two hundred patients with CMT, negative for both SNV mutations in several CMT genes and for CNVs involving PMP22, were screened for CNVs by high-resolution oligonucleotide array comparative genomic hybridization. Whole-exome sequencing was conducted on individuals with rare, potentially pathogenic CNVs.

RESULTS

Putatively causative CNVs were identified in five subjects (~2.5%); four of the five map to known neuropathy genes. Breakpoint sequencing revealed Alu-Alu-mediated junctions as a predominant contributor. Exome sequencing identified MFN2 SNVs in two of the individuals.

CONCLUSION

Neuropathy-associated CNV outside of the PMP22 locus is rare in CMT. Nevertheless, there is potential clinical utility in testing for CNVs and exome sequencing in CMT cases negative for the CMT1A duplication. These findings suggest that complex phenotypes including neuropathy can potentially be caused by a combination of SNVs and CNVs affecting more than one disease-associated locus and contributing to a mutational burden.Genet Med 18 5, 443-451.

Review: High-performance computing to detect epistasis in genome scale data sets

It is becoming clear that most human diseases have a complex etiology that cannot be explained by single nucleotide polymorphisms (SNPs) or simple additive combinations; the general consensus is that they are caused by combinations of multiple genetic variations. The limited success of some genome-wide association studies is partly a result of this focus on single genetic markers. A more promising approach is to take into account epistasis, by considering the association of multiple SNP interactions with disease. However, as genomic data continues to grow in resolution, and genome and exome sequencing become more established, the number of combinations of variants to consider increases rapidly. Two potential solutions should be considered: the use of high-performance computing, which allows us to consider a larger number of variables, and heuristics to make the solution more tractable, essential in the case of genome sequencing. In this review, we look at different computational methods to analyse epistatic interactions within disease-related genetic data sets created by microarray technology. We also review efforts to use epistatic analysis results to produce biomarkers for diagnostic tests and give our views on future directions in this field in light of advances in sequencing technology and variants in non-coding regions.

Genome-Wide Sequencing for Prenatal Detection of Fetal Single-Gene Disorders

New sequencing methods capable of rapidly analyzing the genome at increasing resolution have transformed diagnosis of single-gene or oligogenic genetic disorders in pediatric and adult medicine. Targeted tests, consisting of disease-focused multigene panels and diagnostic exome sequencing to interrogate the sequence of the coding regions of nearly all genes, are now clinically offered when there is suspicion for an undiagnosed genetic disorder or cancer in children and adults. Implementation of diagnostic exome and genome sequencing tests on invasively and noninvasively obtained fetal DNA samples for prenatal genetic diagnosis is also being explored. We predict that they will become more widely integrated into prenatal care in the near future. Providers must prepare for the practical, ethical, and societal dilemmas that accompany the capacity to generate and analyze large amounts of genetic information about the fetus during pregnancy.

Decoding NF1 Intragenic Copy-Number Variations

Genomic rearrangements can cause both Mendelian and complex disorders. Currently, several major mechanisms causing genomic rearrangements, such as non-allelic homologous recombination (NAHR), non-homologous end joining (NHEJ), fork stalling and template switching (FoSTeS), and microhomology-mediated break-induced replication (MMBIR), have been proposed. However, to what extent these mechanisms contribute to gene-specific pathogenic copy-number variations (CNVs) remains understudied. Furthermore, few studies have resolved these pathogenic alterations at the nucleotide-level. Accordingly, our aim was to explore which mechanisms contribute to a large, unique set of locus-specific non-recurrent genomic rearrangements causing the genetic neurocutaneous disorder neurofibromatosis type 1 (NF1). Through breakpoint-spanning PCR as well as array comparative genomic hybridization, we have identified the breakpoints in 85 unrelated individuals carrying an NF1 intragenic CNV. Furthermore, we characterized the likely rearrangement mechanisms of these 85 CNVs, along with those of two additional previously published NF1 intragenic CNVs. Unlike the most typical recurrent rearrangements mediated by flanking low-copy repeats (LCRs), NF1 intragenic rearrangements vary in size, location, and rearrangement mechanisms. We propose the DNA-replication-based mechanisms comprising both FoSTeS and/or MMBIR and serial replication stalling to be the predominant mechanisms leading to NF1 intragenic CNVs. In addition to the loop within a 197-bp palindrome located in intron 40, four Alu elements located in introns 1, 2, 3, and 50 were also identified as intragenic-rearrangement hotspots within NF1.

The Genetic Basis of Mendelian Phenotypes: Discoveries, Challenges, and Opportunities

Discovering the genetic basis of a Mendelian phenotype establishes a causal link between genotype and phenotype, making possible carrier and population screening and direct diagnosis. Such discoveries also contribute to our knowledge of gene function, gene regulation, development, and biological mechanisms that can be used for developing new therapeutics. As of February 2015, 2,937 genes underlying 4,163 Mendelian phenotypes have been discovered, but the genes underlying ∼50% (i.e., 3,152) of all known Mendelian phenotypes are still unknown, and many more Mendelian conditions have yet to be recognized. This is a formidable gap in biomedical knowledge. Accordingly, in December 2011, the NIH established the Centers for Mendelian Genomics (CMGs) to provide the collaborative framework and infrastructure necessary for undertaking large-scale whole-exome sequencing and discovery of the genetic variants responsible for Mendelian phenotypes. In partnership with 529 investigators from 261 institutions in 36 countries, the CMGs assessed 18,863 samples from 8,838 families representing 579 known and 470 novel Mendelian phenotypes as of January 2015. This collaborative effort has identified 956 genes, including 375 not previously associated with human health, that underlie a Mendelian phenotype. These results provide insight into study design and analytical strategies, identify novel mechanisms of disease, and reveal the extensive clinical variability of Mendelian phenotypes. Discovering the gene underlying every Mendelian phenotype will require tackling challenges such as worldwide ascertainment and phenotypic characterization of families affected by Mendelian conditions, improvement in sequencing and analytical techniques, and pervasive sharing of phenotypic and genomic data among researchers, clinicians, and families.

Defining "mutation" and "polymorphism" in the era of personal genomics

BACKGROUND

The growing advances in DNA sequencing tools have made analyzing the human genome cheaper and faster. While such analyses are intended to identify complex variants, related to disease susceptibility and efficacy of drug responses, they have blurred the definitions of mutation and polymorphism.

DISCUSSION

In the era of personal genomics, it is critical to establish clear guidelines regarding the use of a reference genome. Nowadays DNA variants are called as differences in comparison to a reference. In a sequencing project Single Nucleotide Polymorphisms (SNPs) and DNA mutations are defined as DNA variants detectable in >1 % or <1 % of the population, respectively. The alternative use of the two terms mutation or polymorphism for the same event (a difference as compared with a reference) can lead to problems of classification. These problems can impact the accuracy of the interpretation and the functional relationship between a disease state and a genomic sequence. We propose to solve this nomenclature dilemma by defining mutations as DNA variants obtained in a paired sequencing project including the germline DNA of the same individual as a reference. Moreover, the term mutation should be accompanied by a qualifying prefix indicating whether the mutation occurs only in somatic cells (somatic mutation) or also in the germline (germline mutation). We believe this distinction in definition will help avoid confusion among researchers and support the practice of sequencing the germline and somatic tissues in parallel to classify the DNA variants thus defined as mutations.

Factors influencing success of clinical genome sequencing across a broad spectrum of disorders

To assess factors influencing the success of whole-genome sequencing for mainstream clinical diagnosis, we sequenced 217 individuals from 156 independent cases or families across a broad spectrum of disorders in whom previous screening had identified no pathogenic variants. We quantified the number of candidate variants identified using different strategies for variant calling, filtering, annotation and prioritization. We found that jointly calling variants across samples, filtering against both local and external databases, deploying multiple annotation tools and using familial transmission above biological plausibility contributed to accuracy. Overall, we identified disease-causing variants in 21% of cases, with the proportion increasing to 34% (23/68) for mendelian disorders and 57% (8/14) in family trios. We also discovered 32 potentially clinically actionable variants in 18 genes unrelated to the referral disorder, although only 4 were ultimately considered reportable. Our results demonstrate the value of genome sequencing for routine clinical diagnosis but also highlight many outstanding challenges.

Next-generation sequencing for the diagnosis of hereditary pheochromocytoma and paraganglioma syndromes

PURPOSE OF REVIEW

About 40% of the neuroendocrine tumors pheochromocytomas and paragangliomas (PPGLs) are caused by an inherited mutation. Diagnostic genetic screening is recommended for patients and their families. However, the number of susceptibility genes involved is high and continues to grow, making conventional sequencing costly and burdensome. Next-generation sequencing (NGS) enables accurate, thorough, and cost-effective identification of inherited mutations. Here we review recent successes, limitations, and the future of NGS for diagnosis of pheochromocytoma and paraganglioma syndromes.

RECENT FINDINGS

NGS-based screen of genetic disorders in the clinical setting shows improved diagnostic rates over conventional tests. Both broad, whole-exome sequencing, and targeted NGS approaches have been tested for screening of PPGLs, with accurate mutation detection, higher speed, and reduced costs compared with current assays. Flexibility to expand the targeted gene set is immediate in whole-exome sequencing, and adjustable in targeted NGS, but both methods have limitations.

SUMMARY

The high degree of genetic heterogeneity and heritability of PPGLs make NGS an ideal medium for their diagnostic screening. However, improved detection of large genomic defects and underrepresented gene areas are needed before NGS can fully realize its potential as the premier option for routine genetic testing of these syndromes.

Structural variation mutagenesis of the human genome: Impact on disease and evolution

Watson-Crick base-pair changes, or single-nucleotide variants (SNV), have long been known as a source of mutations. However, the extent to which DNA structural variation, including duplication and deletion copy number variants (CNV) and copy number neutral inversions and translocations, contribute to human genome variation and disease has been appreciated only recently. Moreover, the potential complexity of structural variants (SV) was not envisioned; thus, the frequency of complex genomic rearrangements and how such events form remained a mystery. The concept of genomic disorders, diseases due to genomic rearrangements and not sequence-based changes for which genomic architecture incite genomic instability, delineated a new category of conditions distinct from chromosomal syndromes and single-gene Mendelian diseases. Nevertheless, it is the mechanistic understanding of CNV/SV formation that has promoted further understanding of human biology and disease and provided insights into human genome and gene evolution. Environ. Mol. Mutagen. 56:419-436, 2015. © 2015 Wiley Periodicals, Inc.

Genetics and heart failure: a concise guide for the clinician

The pathogenesis of heart failure involves a complex interaction between genetic and environmental factors. Genetic factors may influence the susceptibility to the underlying etiology of heart failure, the rapidity of disease progression, or the response to pharmacologic therapy. The genetic contribution to heart failure is relatively minor in most multifactorial cases, but more direct and profound in the case of familial dilated cardiomyopathy. Early studies of genetic risk for heart failure focused on polymorphisms in genes integral to the adrenergic and renin-angiotensin-aldosterone system. Some of these variants were found to increase the risk of developing heart failure, and others appeared to affect the therapeutic response to neurohormonal antagonists. Regardless, each variant individually confers a relatively modest increase in risk and likely requires complex interaction with other variants and the environment for heart failure to develop. Dilated cardiomyopathy frequently leads to heart failure, and a genetic etiology increasingly has been recognized in cases previously considered to be "idiopathic". Up to 50% of dilated cardiomyopathy cases without other cause likely are due to a heritable genetic mutation. Such mutations typically are found in genes encoding sarcomeric proteins and are inherited in an autosomal dominant fashion. In recent years, rapid advances in sequencing technology have improved our ability to diagnose familial dilated cardiomyopathy and those diagnostic tests are available widely. Optimal care for the expanding population of patients with heritable heart failure involves counselors and physicians with specialized training in genetics, but numerous online genetics resources are available to practicing clinicians.

Whole-exome sequencing identifies novel homozygous mutation in NPAS2 in family with nonobstructive azoospermia

OBJECTIVE

To investigate the genetic cause of nonobstructive azoospermia (NOA) in a consanguineous Turkish family through homozygosity mapping followed by targeted exon/whole-exome sequencing to identify genetic variations.

DESIGN

Whole-exome sequencing (WES).

SETTING

Research laboratory.

PATIENT(S)

Two siblings in a consanguineous family with NOA.

INTERVENTION(S)

Validating all variants passing filter criteria with Sanger sequencing to confirm familial segregation and absence in the control population.

MAIN OUTCOME MEASURE(S)

Discovery of a mutation that could potentially cause NOA.

RESULT(S)

A novel nonsynonymous mutation in the neuronal PAS-2 domain (NPAS2) was identified in a consanguineous family from Turkey. This mutation in exon 14 (chr2: 101592000 C>G) of NPAS2 is likely a disease-causing mutation as it is predicted to be damaging, it is a novel variant, and it segregates with the disease. Family segregation of the variants showed the presence of the homozygous mutation in the three brothers with NOA and a heterozygous mutation in the mother as well as one brother and one sister who were both fertile. The mutation is not found in the single-nucleotide polymorphism database, the 1000 Genomes Project, the Baylor College of Medicine cohort of 500 Turkish patients (not a population-specific polymorphism), or the matching 50 fertile controls.

CONCLUSION(S)

With the use of WES we identified a novel homozygous mutation in NPAS2 as a likely disease-causing variant in a Turkish family diagnosed with NOA. Our data reinforce the clinical role of WES in the molecular diagnosis of highly heterogeneous genetic diseases for which conventional genetic approaches have previously failed to find a molecular diagnosis.

Next-Generation Sequencing Panels for the Diagnosis of Colorectal Cancer and Polyposis Syndromes: A Cost-Effectiveness Analysis

PURPOSE

To evaluate the cost effectiveness of next-generation sequencing (NGS) panels for the diagnosis of colorectal cancer and polyposis (CRCP) syndromes in patients referred to cancer genetics clinics.

PATIENTS AND METHODS

We developed a decision model to evaluate NGS panel testing compared with current standard of care in patients referred to a cancer genetics clinic. We obtained data on the prevalence of genetic variants from a large academic laboratory and calculated the costs and health benefits of identifying relatives with a pathogenic variant, in life-years and quality-adjusted life-years (QALYs). We classified the CRCP syndromes according to their type of inheritance and penetrance of colorectal cancer. One-way and probabilistic sensitivity analyses were conducted to assess uncertainty.

RESULTS

Evaluation with an NGS panel that included Lynch syndrome genes and other genes associated with highly penetrant CRCP syndromes led to an average increase of 0.151 year of life, 0.128 QALY, and $4,650 per patient, resulting in an incremental cost-effectiveness ratio of $36,500 per QALY compared with standard care and a 99% probability that this panel was cost effective at a threshold of $100,000 per QALY. When compared with this panel, the addition of genes with low colorectal cancer penetrance resulted in an incremental cost-effectiveness ratio of $77,300 per QALY.

CONCLUSION

The use of an NGS panel that includes genes associated with highly penetrant CRCP syndromes in addition to Lynch syndrome genes as a first-line test is likely to provide meaningful clinical benefits in a cost-effective manner at a $100,000 per QALY threshold.

Whole-genome sequencing for identification of Mendelian disorders in critically ill infants: a retrospective analysis of diagnostic and clinical findings

BACKGROUND

Genetic disorders and congenital anomalies are the leading causes of infant mortality. Diagnosis of most genetic diseases in neonatal and paediatric intensive care units (NICU and PICU) is not sufficiently timely to guide acute clinical management. We used rapid whole-genome sequencing (STATseq) in a level 4 NICU and PICU to assess the rate and types of molecular diagnoses, and the prevalence, types, and effect of diagnoses that are likely to change medical management in critically ill infants.

METHODS

We did a retrospective comparison of STATseq and standard genetic testing in a case series from the NICU and PICU of a large children's hospital between Nov 11, 2011, and Oct 1, 2014. The participants were families with an infant younger than 4 months with an acute illness of suspected genetic cause. The intervention was STATseq of trios (both parents and their affected infant). The main measures were the diagnostic rate, time to diagnosis, and rate of change in management after standard genetic testing and STATseq.

FINDINGS

20 (57%) of 35 infants were diagnosed with a genetic disease by use of STATseq and three (9%) of 32 by use of standard genetic testing (p=0·0002). Median time to genome analysis was 5 days (range 3-153) and median time to STATseq report was 23 days (5-912). 13 (65%) of 20 STATseq diagnoses were associated with de-novo mutations. Acute clinical usefulness was noted in 13 (65%) of 20 infants with a STATseq diagnosis, four (20%) had diagnoses with strongly favourable effects on management, and six (30%) were started on palliative care. 120-day mortality was 57% (12 of 21) in infants with a genetic diagnosis.

INTERPRETATION

In selected acutely ill infants, STATseq had a high rate of diagnosis of genetic disorders. Most diagnoses altered the management of infants in the NICU or PICU. The very high infant mortality rate indicates a substantial need for rapid genomic diagnoses to be allied with a novel framework for precision medicine for infants in NICU and PICU who are diagnosed with genetic diseases to improve outcomes.

FUNDING

Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Human Genome Research Institute, and National Center for Advancing Translational Sciences.

Somatic mosaicism: implications for disease and transmission genetics

Nearly all of the genetic material among cells within an organism is identical. However, single-nucleotide variants (SNVs), small insertions/deletions (indels), copy-number variants (CNVs), and other structural variants (SVs) continually accumulate as cells divide during development. This process results in an organism composed of countless cells, each with its own unique personal genome. Thus, every human is undoubtedly mosaic. Mosaic mutations can go unnoticed, underlie genetic disease or normal human variation, and may be transmitted to the next generation as constitutional variants. We review the influence of the developmental timing of mutations, the mechanisms by which they arise, methods for detecting mosaic variants, and the risk of passing these mutations on to the next generation.

Assessing the impact of mutations found in next generation sequencing data over human signaling pathways

Modern sequencing technologies produce increasingly detailed data on genomic variation. However, conventional methods for relating either individual variants or mutated genes to phenotypes present known limitations given the complex, multigenic nature of many diseases or traits. Here we present PATHiVar, a web-based tool that integrates genomic variation data with gene expression tissue information. PATHiVar constitutes a new generation of genomic data analysis methods that allow studying variants found in next generation sequencing experiment in the context of signaling pathways. Simple Boolean models of pathways provide detailed descriptions of the impact of mutations in cell functionality so as, recurrences in functionality failures can easily be related to diseases, even if they are produced by mutations in different genes. Patterns of changes in signal transmission circuits, often unpredictable from individual genes mutated, correspond to patterns of affected functionalities that can be related to complex traits such as disease progression, drug response, etc. PATHiVar is available at: http://pathivar.babelomics.org.

Assessing structural variation in a personal genome-towards a human reference diploid genome

Background

Characterizing large genomic variants is essential to expanding the research and clinical applications of genome sequencing. While multiple data types and methods are available to detect these structural variants (SVs), they remain less characterized than smaller variants because of SV diversity, complexity, and size. These challenges are exacerbated by the experimental and computational demands of SV analysis. Here, we characterize the SV content of a personal genome with Parliament, a publicly available consensus SV-calling infrastructure that merges multiple data types and SV detection methods.

Results

We demonstrate Parliament’s efficacy via integrated analyses of data from whole-genome array comparative genomic hybridization, short-read next-generation sequencing, long-read (Pacific BioSciences RSII), long-insert (Illumina Nextera), and whole-genome architecture (BioNano Irys) data from the personal genome of a single subject (HS1011). From this genome, Parliament identified 31,007 genomic loci between 100 bp and 1 Mbp that are inconsistent with the hg19 reference assembly. Of these loci, 9,777 are supported as putative SVs by hybrid local assembly, long-read PacBio data, or multi-source heuristics. These SVs span 59 Mbp of the reference genome (1.8%) and include 3,801 events identified only with long-read data. The HS1011 data and complete Parliament infrastructure, including a BAM-to-SV workflow, are available on the cloud-based service DNAnexus.

Conclusions

HS1011 SV analysis reveals the limits and advantages of multiple sequencing technologies, specifically the impact of long-read SV discovery. With the full Parliament infrastructure, the HS1011 data constitute a public resource for novel SV discovery, software calibration, and personal genome structural variation analysis.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1479-3) contains supplementary material, which is available to authorized users.

WHATIF: An open-source desktop application for extraction and management of the incidental findings from next-generation sequencing variant data

BACKGROUND

Identification and evaluation of incidental findings in patients following whole exome (WGS) or whole genome sequencing (WGS) is challenging for both practicing physicians and researchers. The American College of Medical Genetics and Genomics (ACMG) recently recommended a list of reportable incidental genetic findings. However, no informatics tools are currently available to support evaluation of incidental findings in next-generation sequencing data.

METHODS

The Wisconsin Hierarchical Analysis Tool for Incidental Findings (WHATIF), was developed as a stand-alone Windows-based desktop executable, to support the interactive analysis of incidental findings in the context of the ACMG recommendations. WHATIF integrates the European Bioinformatics Institute Variant Effect Predictor (VEP) tool for biological interpretation and the National Center for Biotechnology Information ClinVar tool for clinical interpretation.

RESULTS

An open-source desktop program was created to annotate incidental findings and present the results with a user-friendly interface. Further, a meaningful index (WHATIF Index) was devised for each gene to facilitate ranking of the relative importance of the variants and estimate the potential workload associated with further evaluation of the variants. Our WHATIF application is available at: http://tinyurl.com/WHATIF-SOFTWARE CONCLUSIONS: The WHATIF application offers a user-friendly interface and allows users to investigate the extracted variant information efficiently and intuitively while always accessing the up to date information on variants via application programming interfaces (API) connections. WHATIF׳s highly flexible design and straightforward implementation aids users in customizing the source code to meet their own special needs.

PMP22-Related neuropathies and other clinical manifestations in Chinese han patients with charcot-marie-tooth disease type 1

INTRODUCTION

Most cases of Charcot-Marie-Tooth (CMT) disease are caused by mutations in the peripheral myelin protein 22 gene (PMP22), including heterozygous duplications (CMT1A), deletions (HNPP), and point mutations (CMT1E).

METHODS

Single-nucleotide polymorphism (SNP) arrays were used to study PMP22 mutations based on the results of multiplex ligation-dependent probe amplification (MLPA) and polymerase chain reaction-restriction fragment length polymorphism methods in 77 Chinese Han families with CMT1. PMP22 sequencing was performed in MLPA-negative probands. Clinical characteristics were collected for all CMT1A/HNPP probands and their family members.

RESULTS

Twenty-one of 77 CMT1 probands (27.3%) carried duplication/deletion (dup/del) copynumber variants. No point mutations were detected. SNP array and MLPA seem to have similar sensitivity. Fifty-seven patients from 19 CMT1A families had the classical CMT phenotype, except for 1 with concomitant CIDP. Two HNPP probands presented with acute ulnar nerve palsy or recurrent sural nerve palsy, respectively.

CONCLUSIONS

The SNP array has wide coverage, high sensitivity, and high resolution and can be used as a screening tool to detect PMP22 dup/del as shown in this Chinese Han population.

New insights into the performance of human whole-exome capture platforms

Whole exome sequencing (WES) is increasingly used in research and diagnostics. WES users expect coverage of the entire coding region of known genes as well as sufficient read depth for the covered regions. It is, however, unknown which recent WES platform is most suitable to meet these expectations. We present insights into the performance of the most recent standard exome enrichment platforms from Agilent, NimbleGen and Illumina applied to six different DNA samples by two sequencing vendors per platform. Our results suggest that both Agilent and NimbleGen overall perform better than Illumina and that the high enrichment performance of Agilent is stable among samples and between vendors, whereas NimbleGen is only able to achieve vendor- and sample-specific best exome coverage. Moreover, the recent Agilent platform overall captures more coding exons with sufficient read depth than NimbleGen and Illumina. Due to considerable gaps in effective exome coverage, however, the three platforms cannot capture all known coding exons alone or in combination, requiring improvement. Our data emphasize the importance of evaluation of updated platform versions and suggest that enrichment-free whole genome sequencing can overcome the limitations of WES in sufficiently covering coding exons, especially GC-rich regions, and in characterizing structural variants.

The diagnostic pathway in complex paediatric neurology: a cost analysis

BACKGROUND

The diagnostic trajectory of complex paediatric neurology may be long, burdensome, and expensive while its diagnostic yield is frequently modest. Improvement in this trajectory is desirable and might be achieved by innovations such as whole exome sequencing. In order to explore the consequences of implementing them, it is important to map the current pathway. To that end, this study assessed the healthcare resource use and associated costs in this diagnostic trajectory in the Netherlands.

METHODS

Fifty patients presenting with complex paediatric neurological disorders of a suspected genetic origin were included between September 2011 and March 2012. Data on their healthcare resource utilization were collected from the hospital medical charts. Unit prices were obtained from the Dutch Healthcare Authority, the Dutch Healthcare Insurance Board, and the financial administration of the hospital. Bootstrap simulations were performed to determine mean quantities and costs.

RESULTS

The mean duration of the diagnostic trajectory was 40 months. A diagnosis was established in 6% of the patients. On average, patients made 16 physician visits, underwent four imaging and two neurophysiologic tests, and had eight genetic and 16 other tests. Mean bootstrapped costs per patient amounted to €12,475, of which 43% was for genetic tests (€5,321) and 25% for hospital visits (€3,112).

CONCLUSION

Currently, the diagnostic trajectories of paediatric patients who have complex neurological disease with a strong suspected genetic component are lengthy, resource-intensive, and low-yield. The data from this study provide a backdrop against which the introduction of novel techniques such as whole exome sequencing should be evaluated.

Fruit flies in biomedical research

Many scientists complain that the current funding situation is dire. Indeed, there has been an overall decline in support in funding for research from the National Institutes of Health and the National Science Foundation. Within the Drosophila field, some of us question how long this funding crunch will last as it demotivates principal investigators and perhaps more importantly affects the long-term career choice of many young scientists. Yet numerous very interesting biological processes and avenues remain to be investigated in Drosophila, and probing questions can be answered fast and efficiently in flies to reveal new biological phenomena. Moreover, Drosophila is an excellent model organism for studies that have translational impact for genetic disease and for other medical implications such as vector-borne illnesses. We would like to promote a better collaboration between Drosophila geneticists/biologists and human geneticists/bioinformaticians/clinicians, as it would benefit both fields and significantly impact the research on human diseases.

Affected kindred analysis of human X chromosome exomes to identify novel X-linked intellectual disability genes

X-linked Intellectual Disability (XLID) is a group of genetically heterogeneous disorders caused by mutations in genes on the X chromosome. Deleterious mutations in ~10% of X chromosome genes are implicated in causing XLID disorders in ~50% of known and suspected XLID families. The remaining XLID genes are expected to be rare and even private to individual families. To systematically identify these XLID genes, we sequenced the X chromosome exome (X-exome) in 56 well-established XLID families (a single affected male from 30 families and two affected males from 26 families) using an Agilent SureSelect X-exome kit and the Illumina HiSeq 2000 platform. To enrich for disease-causing mutations, we first utilized variant filters based on dbSNP, the male-restricted portions of the 1000 Genomes Project, or the Exome Variant Server datasets. However, these databases present limitations as automatic filters for enrichment of XLID genes. We therefore developed and optimized a strategy that uses a cohort of affected male kindred pairs and an additional small cohort of affected unrelated males to enrich for potentially pathological variants and to remove neutral variants. This strategy, which we refer to as Affected Kindred/Cross-Cohort Analysis, achieves a substantial enrichment for potentially pathological variants in known XLID genes compared to variant filters from public reference databases, and it has identified novel XLID candidate genes. We conclude that Affected Kindred/Cross-Cohort Analysis can effectively enrich for disease-causing genes in rare, Mendelian disorders, and that public reference databases can be used effectively, but cautiously, as automatic filters for X-linked disorders.

Multiple system atrophy: the application of genetics in understanding etiology

Classically defined phenotypically by a triad of cerebellar ataxia, parkinsonism, and autonomic dysfunction in conjunction with pyramidal signs, multiple system atrophy (MSA) is a rare and progressive neurodegenerative disease affecting an estimated 3-4 per every 100,000 individuals among adults 50-99 years of age. With a pathological hallmark of alpha-synuclein-immunoreactive glial cytoplasmic inclusions (GCIs; Papp-Lantos inclusions), MSA patients exhibit marked neurodegenerative changes in the striatonigral and/or olivopontocerebellar structures of the brain. As a member of the alpha-synucleinopathy family, which is defined by its well-demarcated alpha-synuclein-immunoreactive inclusions and aggregation, MSA's clinical presentation exhibits several overlapping features with other members including Parkinson's disease (PD) and dementia with Lewy bodies (DLB). Given the extensive fund of knowledge regarding the genetic etiology of PD revealed within the past several years, a genetic investigation of MSA is warranted. While a current genome-wide association study is underway for MSA to further clarify the role of associated genetic loci and single-nucleotide polymorphisms, several cases have presented solid preliminary evidence of a genetic etiology. Naturally, genes and variants manifesting known associations with PD (and other phenotypically similar neurodegenerative disorders), including SNCA and MAPT, have been comprehensively investigated in MSA patient cohorts. More recently variants in COQ2 have been linked to MSA in the Japanese population although this finding awaits replication. Nonetheless, significant positive associations with subsequent independent replication studies have been scarce. With very limited information regarding genetic mutations or alterations in gene dosage as a cause of MSA, the search for novel risk genes, which may be in the form of common variants or rare variants, is the logical nexus for MSA research. We believe that the application of next generation genetic methods to MSA will provide valuable insight into the underlying causes of this disease, and will be central to the identification of etiologic-based therapies.

Next-generation sequencing-based genome diagnostics across clinical genetics centers: implementation choices and their effects

Implementation of next-generation DNA sequencing (NGS) technology into routine diagnostic genome care requires strategic choices. Instead of theoretical discussions on the consequences of such choices, we compared NGS-based diagnostic practices in eight clinical genetic centers in the Netherlands, based on genetic testing of nine pre-selected patients with cardiomyopathy. We highlight critical implementation choices, including the specific contributions of laboratory and medical specialists, bioinformaticians and researchers to diagnostic genome care, and how these affect interpretation and reporting of variants. Reported pathogenic mutations were consistent for all but one patient. Of the two centers that were inconsistent in their diagnosis, one reported to have found 'no causal variant', thereby underdiagnosing this patient. The other provided an alternative diagnosis, identifying another variant as causal than the other centers. Ethical and legal analysis showed that informed consent procedures in all centers were generally adequate for diagnostic NGS applications that target a limited set of genes, but not for exome- and genome-based diagnosis. We propose changes to further improve and align these procedures, taking into account the blurring boundary between diagnostics and research, and specific counseling options for exome- and genome-based diagnostics. We conclude that alternative diagnoses may infer a certain level of 'greediness' to come to a positive diagnosis in interpreting sequencing results. Moreover, there is an increasing interdependence of clinic, diagnostics and research departments for comprehensive diagnostic genome care. Therefore, we invite clinical geneticists, physicians, researchers, bioinformatics experts and patients to reconsider their role and position in future diagnostic genome care.

Approaches for identifying germ cell mutagens: Report of the 2013 IWGT workshop on germ cell assays(☆)

This workshop reviewed the current science to inform and recommend the best evidence-based approaches on the use of germ cell genotoxicity tests. The workshop questions and key outcomes were as follows. (1) Do genotoxicity and mutagenicity assays in somatic cells predict germ cell effects? Limited data suggest that somatic cell tests detect most germ cell mutagens, but there are strong concerns that dictate caution in drawing conclusions. (2) Should germ cell tests be done, and when? If there is evidence that a chemical or its metabolite(s) will not reach target germ cells or gonadal tissue, it is not necessary to conduct germ cell tests, notwithstanding somatic outcomes. However, it was recommended that negative somatic cell mutagens with clear evidence for gonadal exposure and evidence of toxicity in germ cells could be considered for germ cell mutagenicity testing. For somatic mutagens that are known to reach the gonadal compartments and expose germ cells, the chemical could be assumed to be a germ cell mutagen without further testing. Nevertheless, germ cell mutagenicity testing would be needed for quantitative risk assessment. (3) What new assays should be implemented and how? There is an immediate need for research on the application of whole genome sequencing in heritable mutation analysis in humans and animals, and integration of germ cell assays with somatic cell genotoxicity tests. Focus should be on environmental exposures that can cause de novo mutations, particularly newly recognized types of genomic changes. Mutational events, which may occur by exposure of germ cells during embryonic development, should also be investigated. Finally, where there are indications of germ cell toxicity in repeat dose or reproductive toxicology tests, consideration should be given to leveraging those studies to inform of possible germ cell genotoxicity.

Churchill: an ultra-fast, deterministic, highly scalable and balanced parallelization strategy for the discovery of human genetic variation in clinical and population-scale genomics

While advances in genome sequencing technology make population-scale genomics a possibility, current approaches for analysis of these data rely upon parallelization strategies that have limited scalability, complex implementation and lack reproducibility. Churchill, a balanced regional parallelization strategy, overcomes these challenges, fully automating the multiple steps required to go from raw sequencing reads to variant discovery. Through implementation of novel deterministic parallelization techniques, Churchill allows computationally efficient analysis of a high-depth whole genome sample in less than two hours. The method is highly scalable, enabling full analysis of the 1000 Genomes raw sequence dataset in a week using cloud resources. http://churchill.nchri.org/.

Clinical Impact and Cost-Effectiveness of Whole Exome Sequencing as a Diagnostic Tool: A Pediatric Center's Experience

BACKGROUND

There are limited reports of the use of whole exome sequencing (WES) as a clinical diagnostic tool. Moreover, there are no reports addressing the cost burden associated with genetic tests performed prior to WES.

OBJECTIVE

We demonstrate the performance characteristics of WES in a pediatric setting by describing our patient cohort, calculating the diagnostic yield, and detailing the patients for whom clinical management was altered. Moreover, we examined the potential cost-effectiveness of WES by examining the cost burden of diagnostic workups.

METHODS

To determine the clinical utility of our hospital's clinical WES, we performed a retrospective review of the first 40 cases. We utilized dual bioinformatics analyses pipelines based on commercially available software and in-house tools.

RESULTS

Of the first 40 clinical cases, we identified genetic defects in 12 (30%) patients, of which 47% of the mutations were previously unreported in the literature. Among the 12 patients with positive findings, seven have autosomal dominant disease and five have autosomal recessive disease. Ninety percent of the cohort opted to receive secondary findings and of those, secondary medical actionable results were returned in three cases. Among these positive cases, there are a number of novel mutations that are being reported here. The diagnostic workup included a significant number of genetic tests with microarray and single-gene sequencing being the most popular tests. Significantly, genetic diagnosis from WES led to altered patient medical management in positive cases.

CONCLUSION

We demonstrate the clinical utility of WES by establishing the clinical diagnostic rate and its impact on medical management in a large pediatric center. The cost-effectiveness of WES was demonstrated by ending the diagnostic odyssey in positive cases. Also, in some cases it may be most cost-effective to directly perform WES. WES provides a unique glimpse into the complexity of genetic disorders.

Combinatorial approach to estimate copy number genotype using whole-exome sequencing data

Copy number variations (CNVs) are known risk factors in complex diseases. Array-based approaches have been widely used to detect CNVs, but limitations of array-based CNV detection methods, such as noisy signal and low resolution, have hindered detection of small CNVs. Recently, the development of next-generation sequencing techniques has increased rapidly owing to declines in cost. Particularly, whole-exome sequencing has proved useful for finding causal genes and variants in complex diseases. Because gene copy number may affect expression, CNV genotyping can be very valuable in disease association studies. However, almost all current CNV detection tools consider only two types of CNV genotypes. In this study, we propose a CNV genotype estimation approach using a combination of existing methods. Our approach was comprehensively compared with the customized Agilent array-comparative genomic hybridization. We found that our genotyping approach proved to be accurate, and reproducible, suggesting that it can complement existing CNV genotyping methods.

Copy number variation burden on asthma subgenome in normal cohorts identifies susceptibility markers

PURPOSE

Asthma is a complex disease caused by interplay of genes and environment on the genome of an individual. Copy number variations (CNVs) are more common compared to the other variations that disrupt genome organization. The effect of CNVs on asthma subgenome has been less studied compared to studies on the other variations. We report the assessments of CNV burden in asthma genes of normal cohorts carried out in different geographical areas of the world and discuss the relevance of the observation with respect to asthma pathogenesis.

METHODS

CNV analysis was performed using Affymerix high-resolution arrays, and various bioinformatics tools were used to understand the influence of genes on asthma pathogenesis.

RESULTS

This study identified 61 genes associated with asthma and provided various mechanisms and pathways underlying asthma pathogenesis. CCL3L1, ADAM8, and MUC5B were the most prevalent asthma genes. Among them, CCL3L1 was found across all 12 populations in varying copy number states. This study also identified the inheritance of asthma-CNVs from parents to offspring creating the latent period for manifestation of asthma.

CONCLUSIONS

This study revealed CNV burden with varying copy number states and identified susceptibility towards the disease manifestation. It can be hypothesized that primary CNVs may not be the initiating event in the pathogenesis of asthma and additional preceding mutations or CNVs may be required. The initiator or primary CNVs sensitize normal cohorts leading to an increased probability of accumulating mutations or exposure to allergic stimulating agents that can augment the development of asthma.

Genetic variation and RNA binding proteins: tools and techniques to detect functional polymorphisms

At its most fundamental level the goal of genetics is to connect genotype to phenotype. This question is asked at a basic level evaluating the role of genes and pathways in genetic model organism. Increasingly, this question is being asked in the clinic. Genomes of individuals and populations are being sequenced and compared. The challenge often comes at the stage of analysis. The variant positions are analyzed with the hope of understanding human disease. However after a genome or exome has been sequenced, the researcher is often deluged with hundreds of potentially relevant variations. Traditionally, amino-acid changing mutations were considered the tractable class of disease-causing mutations; however, mutations that disrupt noncoding elements are the subject of growing interest. These noncoding changes are a major avenue of disease (e.g., one in three hereditary disease alleles are predicted to affect splicing). Here, we review some current practices of medical genetics, the basic theory behind biochemical binding and functional assays, and then explore technical advances in how variations that alter RNA protein recognition events are detected and studied. These advances are advances in scale-high-throughput implementations of traditional biochemical assays that are feasible to perform in any molecular biology laboratory. This chapter utilizes a case study approach to illustrate some methods for analyzing polymorphisms. The first characterizes a functional intronic SNP that deletes a high affinity PTB site using traditional low-throughput biochemical and functional assays. From here we demonstrate the utility of high-throughput splicing and spliceosome assembly assays for screening large sets of SNPs and disease alleles for allelic differences in gene expression. Finally we perform three pilot drug screens with small molecules (G418, tetracycline, and valproic acid) that illustrate how compounds that rescue specific instances of differential pre-mRNA processing can be discovered.

Genetic testing in cardiovascular diseases

PURPOSE OF REVIEW

The review is designed to outline the major developments in genetic testing in the cardiovascular arena in the past year or so. This is an exciting time in genetic testing as whole exome and whole genome approaches finally reach the clinic. These new approaches offer insight into disease causation in families in which this might previously have been inaccessible, and also bring a wide range of interpretative challenges.

RECENT FINDINGS

Among the most significant recent findings has been the extent of physiologic rare coding variation in the human genome. New disease genes have been identified through whole exome studies in neonatal arrhythmia, congenital heart disease and coronary artery disease that were simply inaccessible with other techniques. This has not only shed light on the challenges of genetic testing at this scale, but has also sharply defined the limits of prior gene-panel focused testing. As novel therapies targeting specific genetic subsets of disease become available, genetic testing will become a part of routine clinical care.

SUMMARY

The pace of change in sequencing technologies has begun to transform clinical medicine, and cardiovascular disease is no exception. The complexity of such studies emphasizes the importance of real-time communication between the genetics laboratory and genetically informed clinicians. New efforts in data and knowledge management will be central to the continued advancement of genetic testing.

Next-generation sequencing for mitochondrial disorders

A great deal of our understanding of mitochondrial function has come from studies of inherited mitochondrial diseases, but still majority of the patients lack molecular diagnosis. Furthermore, effective treatments for mitochondrial disorders do not exist. Development of therapies has been complicated by the fact that the diseases are extremely heterogeneous, and collecting large enough cohorts of similarly affected individuals to assess new therapies properly has been difficult. Next-generation sequencing technologies have in the last few years been shown to be an effective method for the genetic diagnosis of inherited mitochondrial diseases. Here we review the strategies and findings from studies applying next-generation sequencing methods for the genetic diagnosis of mitochondrial disorders. Detailed knowledge of molecular causes also enables collection of homogenous cohorts of patients for therapy trials, and therefore boosts development of intervention.

Ethical considerations of research policy for personal genome analysis: the approach of the Genome Science Project in Japan

As evidenced by high-throughput sequencers, genomic technologies have recently undergone radical advances. These technologies enable comprehensive sequencing of personal genomes considerably more efficiently and less expensively than heretofore. These developments present a challenge to the conventional framework of biomedical ethics; under these changing circumstances, each research project has to develop a pragmatic research policy. Based on the experience with a new large-scale project-the Genome Science Project-this article presents a novel approach to conducting a specific policy for personal genome research in the Japanese context. In creating an original informed-consent form template for the project, we present a two-tiered process: making the draft of the template following an analysis of national and international policies; refining the draft template in conjunction with genome project researchers for practical application. Through practical use of the template, we have gained valuable experience in addressing challenges in the ethical review process, such as the importance of sharing details of the latest developments in genomics with members of research ethics committees. We discuss certain limitations of the conventional concept of informed consent and its governance system and suggest the potential of an alternative process using information technology.

Utility of next generation sequencing in clinical primary immunodeficiencies

Primary immunodeficiencies (PIDs) are a group of genetically heterogeneous disorders that present with very similar symptoms, complicating definitive diagnosis. More than 240 genes have hitherto been associated with PIDs, of which more than 30 have been identified in the last 3 years. Next generation sequencing (NGS) of genomes or exomes of informative families has played a central role in the discovery of novel PID genes. Furthermore, NGS has the potential to transform clinical molecular testing for established PIDs, allowing all PID differential diagnoses to be tested at once, leading to increased diagnostic yield, while decreasing both the time and cost of obtaining a molecular diagnosis. Given that treatment of PID varies by disease gene, early achievement of a molecular diagnosis is likely to enhance treatment decisions and improve patient outcomes.

The allelic spectrum of Charcot-Marie-Tooth disease in over 17,000 individuals with neuropathy

We report the frequency, positive rate, and type of mutations in 14 genes (PMP22, GJB1, MPZ, MFN2, SH3TC2, GDAP1, NEFL, LITAF, GARS, HSPB1, FIG4, EGR2, PRX, and RAB7A) associated with Charcot–Marie–Tooth disease (CMT) in a cohort of 17,880 individuals referred to a commercial genetic testing laboratory. Deidentified results from sequencing assays and multiplex ligation-dependent probe amplification (MLPA) were analyzed including 100,102 Sanger sequencing, 2338 next-generation sequencing (NGS), and 21,990 MLPA assays. Genetic abnormalities were identified in 18.5% (n = 3312) of all individuals. Testing by Sanger and MLPA (n = 3216) showed that duplications (dup) (56.7%) or deletions (del) (21.9%) in the PMP22 gene accounted for the majority of positive findings followed by mutations in the GJB1 (6.7%), MPZ (5.3%), and MFN2 (4.3%) genes. GJB1 del and mutations in the remaining genes explained 5.3% of the abnormalities. Pathogenic mutations were distributed as follows: missense (70.6%), nonsense (14.3%), frameshift (8.7%), splicing (3.3%), in-frame deletions/insertions (1.8%), initiator methionine mutations (0.8%), and nonstop changes (0.5%). Mutation frequencies, positive rates, and the types of mutations were similar between tests performed by either Sanger (n = 17,377) or NGS (n = 503). Among patients with a positive genetic finding in a CMT-related gene, 94.9% were positive in one of four genes (PMP22, GJB1, MPZ, or MFN2).

Validation of multiple single nucleotide variation calls by additional exome analysis with a semiconductor sequencer to supplement data of whole-genome sequencing of a human population

BACKGROUND

Validation of single nucleotide variations in whole-genome sequencing is critical for studying disease-related variations in large populations. A combination of different types of next-generation sequencers for analyzing individual genomes may be an efficient means of validating multiple single nucleotide variations calls simultaneously.

RESULTS

Here, we analyzed 12 independent Japanese genomes using two next-generation sequencing platforms: the Illumina HiSeq 2500 platform for whole-genome sequencing (average depth 32.4×), and the Ion Proton semiconductor sequencer for whole exome sequencing (average depth 109×). Single nucleotide polymorphism (SNP) calls based on the Illumina Human Omni 2.5-8 SNP chip data were used as the reference. We compared the variant calls for the 12 samples, and found that the concordance between the two next-generation sequencing platforms varied between 83% and 97%.

CONCLUSIONS

Our results show the versatility and usefulness of the combination of exome sequencing with whole-genome sequencing in studies of human population genetics and demonstrate that combining data from multiple sequencing platforms is an efficient approach to validate and supplement SNP calls.

Gene hunting in the genomic era: approaches to diagnostic dilemmas in patients with primary immunodeficiencies

There are more than 180 different genetic causes of primary immunodeficiencies identified to date. Approaches for identifying causative mutations can be broadly classified into 3 strategies: (1) educated guesses based on known signaling pathways essential for immune cell development and function, (2) similarity of clinical phenotypes to mouse models, and (3) unbiased genetic approaches. Next-generation DNA sequencing permits efficient sequencing of whole genomes or exomes but also requires strategies for filtering vast amounts of data. Recent studies have identified ways to solve difficult cases, such as diseases with autosomal dominant inheritance, incomplete penetrance, or mutations in noncoding regions. This review focuses on recently identified primary immunodeficiencies to illustrate the strategies, technologies, and potential pitfalls in finding novel causes of these diseases.