Showing papers in "npj Genomic Medicine in 2018"

Meta-analysis of the diagnostic and clinical utility of genome and exome sequencing and chromosomal microarray in children with suspected genetic diseases

Abstract: Genetic diseases are leading causes of childhood mortality. Whole-genome sequencing (WGS) and whole-exome sequencing (WES) are relatively new methods for diagnosing genetic diseases, whereas chromosomal microarray (CMA) is well established. Here we compared the diagnostic utility (rate of causative, pathogenic, or likely pathogenic genotypes in known disease genes) and clinical utility (proportion in whom medical or surgical management was changed by diagnosis) of WGS, WES, and CMA in children with suspected genetic diseases by systematic review of the literature (January 2011–August 2017) and meta-analysis, following MOOSE/PRISMA guidelines. In 37 studies, comprising 20,068 children, diagnostic utility of WGS (0.41, 95% CI 0.34–0.48, I2 = 44%) and WES (0.36, 95% CI 0.33–0.40, I2 = 83%) were qualitatively greater than CMA (0.10, 95% CI 0.08–0.12, I2 = 81%). Among studies published in 2017, the diagnostic utility of WGS was significantly greater than CMA (P < 0.0001, I2 = 13% and I2 = 40%, respectively). Among studies featuring within-cohort comparisons, the diagnostic utility of WES was significantly greater than CMA (P < 0.001, I2 = 36%). The diagnostic utility of WGS and WES were not significantly different. In studies featuring within-cohort comparisons of WGS/WES, the likelihood of diagnosis was significantly greater for trios than singletons (odds ratio 2.04, 95% CI 1.62–2.56, I2 = 12%; P < 0.0001). Diagnostic utility of WGS/WES with hospital-based interpretation (0.42, 95% CI 0.38–0.45, I2 = 48%) was qualitatively higher than that of reference laboratories (0.29, 95% CI 0.27–0.31, I2 = 49%); this difference was significant among studies published in 2017 (P < .0001, I2 = 22% and I2 = 26%, respectively). The clinical utility of WGS (0.27, 95% CI 0.17–0.40, I2 = 54%) and WES (0.17, 95% CI 0.12–0.24, I2 = 76%) were higher than CMA (0.06, 95% CI 0.05–0.07, I2 = 42%); this difference was significant for WGS vs CMA (P < 0.0001). In conclusion, in children with suspected genetic diseases, the diagnostic and clinical utility of WGS/WES were greater than CMA. Subgroups with higher WGS/WES diagnostic utility were trios and those receiving hospital-based interpretation. WGS/WES should be considered a first-line genomic test for children with suspected genetic diseases.

Rapid whole-genome sequencing decreases infant morbidity and cost of hospitalization.

Abstract: Genetic disorders are a leading cause of morbidity and mortality in infants. Rapid whole-genome sequencing (rWGS) can diagnose genetic disorders in time to change acute medical or surgical management (clinical utility) and improve outcomes in acutely ill infants. We report a retrospective cohort study of acutely ill inpatient infants in a regional children’s hospital from July 2016–March 2017. Forty-two families received rWGS for etiologic diagnosis of genetic disorders. Probands also received standard genetic testing as clinically indicated. Primary end-points were rate of diagnosis, clinical utility, and healthcare utilization. The latter was modelled in six infants by comparing actual utilization with matched historical controls and/or counterfactual utilization had rWGS been performed at different time points. The diagnostic sensitivity of rWGS was 43% (eighteen of 42 infants) and 10% (four of 42 infants) for standard genetic tests (P = .0005). The rate of clinical utility of rWGS (31%, thirteen of 42 infants) was significantly greater than for standard genetic tests (2%, one of 42; P = .0015). Eleven (26%) infants with diagnostic rWGS avoided morbidity, one had a 43% reduction in likelihood of mortality, and one started palliative care. In six of the eleven infants, the changes in management reduced inpatient cost by $800,000–$2,000,000. These findings replicate a prior study of the clinical utility of rWGS in acutely ill inpatient infants, and demonstrate improved outcomes and net healthcare savings. rWGS merits consideration as a first tier test in this setting.

The NSIGHT1-randomized controlled trial: rapid whole-genome sequencing for accelerated etiologic diagnosis in critically ill infants.

Abstract: Genetic disorders are a leading cause of morbidity and mortality in infants in neonatal and pediatric intensive care units (NICU/PICU). While genomic sequencing is useful for genetic disease diagnosis, results are usually reported too late to guide inpatient management. We performed an investigator-initiated, partially blinded, pragmatic, randomized, controlled trial to test the hypothesis that rapid whole-genome sequencing (rWGS) increased the proportion of NICU/PICU infants receiving a genetic diagnosis within 28 days. The participants were families with infants aged <4 months in a regional NICU and PICU, with illnesses of unknown etiology. The intervention was trio rWGS. Enrollment from October 2014 to June 2016, and follow-up until November 2016. Of all, 26 female infants, 37 male infants, and 2 infants of undetermined sex were randomized to receive rWGS plus standard genetic tests (n = 32, cases) or standard genetic tests alone (n = 33, controls). The study was terminated early due to loss of equipoise: 73% (24) controls received genomic sequencing as standard tests, and 15% (five) controls underwent compassionate cross-over to receive rWGS. Nevertheless, intention to treat analysis showed the rate of genetic diagnosis within 28 days of enrollment (the primary end-point) to be higher in cases (31%, 10 of 32) than controls (3%, 1 of 33; difference, 28% [95% CI, 10–46%]; p = 0.003). Among infants enrolled in the first 25 days of life, the rate of neonatal diagnosis was higher in cases (32%, 7 of 22) than controls (0%, 0 of 23; difference, 32% [95% CI, 11–53%];p = 0.004). Median age at diagnosis (25 days [range 14–90] in cases vs. 130 days [range 37–451] in controls) and median time to diagnosis (13 days [range 1–84] in cases, vs. 107 days [range 21–429] in controls) were significantly less in cases than controls (p = 0.04). In conclusion, rWGS increased the proportion of NICU/PICU infants who received timely diagnoses of genetic diseases. Genetic disorders in critically ill infants can be diagnosed in as little as 26 h by rapid whole genome sequencing (rWGS). A study led by Stephen F. Kingsmore at the Rady Children’s Institute for Genomic Medicine in San Diego and Children’s Mercy Hospital in Kansas City compared the time to genetic diagnosis in 65 infants with inherited diseases of unknown cause using rWGS, clinical confirmatory testing and standard genetic tests or standard genetic tests alone. They found that the addition of rWGS including confirmatory testing significantly decreased the time to diagnosis, which in newborns can mean the difference between life and death. Because of the increasing accessibility and decreasing costs of the technology and the critical need for timely and effective intervention in infants with suspected genetic diseases, the authors advocate the use of rWGS as a first-line diagnostic test.

Cytogenomic identification and long-read single molecule real-time (SMRT) sequencing of a Bardet-Biedl Syndrome 9 (BBS9) deletion.

Abstract: Bardet–Biedl syndrome (BBS) is a recessive disorder characterized by heterogeneous clinical manifestations, including truncal obesity, rod-cone dystrophy, renal anomalies, postaxial polydactyly, and variable developmental delays. At least 20 genes have been implicated in BBS, and all are involved in primary cilia function. We report a 1-year-old male child from Guyana with obesity, postaxial polydactyly on his right foot, hypotonia, ophthalmologic abnormalities, and developmental delay, which together indicated a clinical diagnosis of BBS. Clinical chromosomal microarray (CMA) testing and high-throughput BBS gene panel sequencing detected a homozygous 7p14.3 deletion of exons 1–4 of BBS9 that was encompassed by a 17.5 Mb region of homozygosity at chromosome 7p14.2–p21.1. The precise breakpoints of the deletion were delineated to a 72.8 kb region in the proband and carrier parents by third-generation long-read single molecule real-time (SMRT) sequencing (Pacific Biosciences), which suggested non-homologous end joining as a likely mechanism of formation. Long-read SMRT sequencing of the deletion breakpoints also determined that the aberration included the neighboring RP9 gene implicated in retinitis pigmentosa; however, the clinical significance of this was considered uncertain given the paucity of reported cases with unambiguous RP9 mutations. Taken together, our study characterized a BBS9 deletion, and the identification of this shared haplotype in the parents suggests that this pathogenic aberration may be a BBS founder mutation in the Guyanese population. Importantly, this informative case also highlights the utility of long-read SMRT sequencing to map nucleotide breakpoints of clinically relevant structural variants.

New insights into structural features and optimal detection of circulating tumor DNA determined by single-strand DNA analysis.

Abstract: Circulating cell-free DNA (cfDNA) has received increasing interest as an apparent breakthrough approach in diagnostics, personalized medicine, and tumor biology. However, the structural features of cfDNA are poorly characterized. Specifically, the literature has discrepancies with regards to cfDNA size profile. We performed a blinded study of the distribution of cfDNA fragment sizes in cancer patient plasma (n = 11), by various ultra-deep-sequencing approaches and quantitative PCR (Q-PCR). Whole-genome sequencing of single-stranded DNA library preparation (SSP-S) revealed that nearly half of the total cfDNA fragment number are below 120 nucleotides, which are not readily detectable by standard double-stranded DNA library preparation (DSP) protocols. Fractional size distribution of cancer patient circulating DNA was very similar using both SSP-S-based or Q-PCR-based methods also revealing that high molecular weight (over 350 bp) cfDNA is a minor component (~2%). These extra small detected cfDNA fragments may mostly result from nicks occurring in blood circulation in one or both DNA strands, which are subsequently revealed through the denaturation step of the SSP and Q-PCR procedures. Detailed analysis of the data suggested that most of the detectable cfDNA in blood has a nucleosome footprint (∼10-bp periodicity repeats). The nucleosome is thus the most stabilizing structure of DNA in the circulation. cfDNA molecules, which are initially packed in chromatin, are released from cells and are then dynamically degraded in blood both within and between nucleosomes or transcription factor-associated subcomplexes. While this study provides new insights into cfDNA size profiles harmonizing sequencing and Q-PCR findings, our data validate the use of a specific Q-PCR method and SSP-S for obtaining an optimal qualitative and quantitative analytical signal. Around half of all tumor-derived DNA strands found in the bloodstream of cancer patients are too short for detection by the most commonly used diagnostic sequencing methods. Alain R. Thierry from the Montpellier Cancer Research Institute, France, and colleagues quantified the size distribution of circulating cell-free DNA (cfDNA) using two genomic protocols that analyze single-stranded DNA—and can thus pick up small DNA fragments that are missed by conventional double-stranded approaches. Looking in the blood of patients with tumors of the colon, lung, breast and liver, the researchers showed that nearly half of all stretches of cfDNA are shorter than 120 nucleotides long. These sequences likely result from tightly packed DNA that’s dynamically degraded into smaller and smaller fragments. The findings highlight the need for whole-genome sequencing or other single-stranded methods to get an accurate read on cfDNA profiles.

Pan-cancer screen for mutations in non-coding elements with conservation and cancer specificity reveals correlations with expression and survival.

Abstract: Cancer develops by accumulation of somatic driver mutations, which impact cellular function. Mutations in non-coding regulatory regions can now be studied genome-wide and further characterized by correlation with gene expression and clinical outcome to identify driver candidates. Using a new two-stage procedure, called ncDriver, we first screened 507 ICGC whole-genomes from 10 cancer types for non-coding elements, in which mutations are both recurrent and have elevated conservation or cancer specificity. This identified 160 significant non-coding elements, including the TERT promoter, a well-known non-coding driver element, as well as elements associated with known cancer genes and regulatory genes (e.g., PAX5, TOX3, PCF11, MAPRE3). However, in some significant elements, mutations appear to stem from localized mutational processes rather than recurrent positive selection in some cases. To further characterize the driver potential of the identified elements and shortlist candidates, we identified elements where presence of mutations correlated significantly with expression levels (e.g., TERT and CDH10) and survival (e.g., CDH9 and CDH10) in an independent set of 505 TCGA whole-genome samples. In a larger pan-cancer set of 4128 TCGA exomes with expression profiling, we identified mutational correlation with expression for additional elements (e.g., near GATA3, CDC6, ZNF217, and CTCF transcription factor binding sites). Survival analysis further pointed to MIR122, a known marker of poor prognosis in liver cancer. In conclusion, the screen for significant mutation patterns coupled with correlative mutational analysis identified new individual driver candidates and suggest that some non-coding mutations recurrently affect expression and play a role in cancer development.

Whole-genome analysis for effective clinical diagnosis and gene discovery in early infantile epileptic encephalopathy.

Abstract: Early infantile epileptic encephalopathy (EIEE) is a devastating epilepsy syndrome with onset in the first months of life. Although mutations in more than 50 different genes are known to cause EIEE, current diagnostic yields with gene panel tests or whole-exome sequencing are below 60%. We applied whole-genome analysis (WGA) consisting of whole-genome sequencing and comprehensive variant discovery approaches to a cohort of 14 EIEE subjects for whom prior genetic tests had not yielded a diagnosis. We identified both de novo point and INDEL mutations and de novo structural rearrangements in known EIEE genes, as well as mutations in genes not previously associated with EIEE. The detection of a pathogenic or likely pathogenic mutation in all 14 subjects demonstrates the utility of WGA to reduce the time and costs of clinical diagnosis of EIEE. While exome sequencing may have detected 12 of the 14 causal mutations, 3 of the 12 patients received non-diagnostic exome panel tests prior to genome sequencing. Thus, given the continued decline of sequencing costs, our results support the use of WGA with comprehensive variant discovery as an efficient strategy for the clinical diagnosis of EIEE and other genetic conditions.

Mutation load estimation model as a predictor of the response to cancer immunotherapy.

Abstract: The determination of the mutation load, a total number of nonsynonymous point mutations, by whole-exome sequencing was shown to be useful in predicting the treatment responses to cancer immunotherapy. However, this technique is expensive and time-consuming, which hampers its application in clinical practice. Therefore, the objective of this study was to construct a mutation load estimation model for lung adenocarcinoma, using a small set of genes, as a predictor of the immunotherapy treatment response. Using the somatic mutation data downloaded from The Cancer Genome Atlas (TCGA) database, a computational framework was developed. The estimation model consisted of only 24 genes, used to estimate the mutation load in the independent validation cohort precisely (R2 = 0.7626). Additionally, the estimated mutation load can be used to identify the patients with durable clinical benefits, with 85% sensitivity, 93% specificity, and 89% accuracy, indicating that the model can serve as a predictive biomarker for cancer immunotherapy treatment response. Furthermore, our analyses demonstrated the necessity of the cancer-specific models by the constructed melanoma and colorectal models. Since most genes in the lung adenocarcinoma model are not currently included in the sequencing panels, a customized targeted sequencing panel can be designed with the selected model genes to assess the mutation load, instead of whole-exome sequencing or the currently used panel-based methods. Consequently, the cost and time required for the assessment of mutation load may be considerably decreased, which indicates that the presented model is a more cost-effective approach to cancer immunotherapy response prediction in clinical practice. Estimating patients’ mutation load from a small set of genes can accurately predict their response to cancer immunotherapy. Harnessing patients’ immune response to target tumor cells is an effective treatment approach in some cases but not others. A patient’s number of deleterious genetic mutations across all their protein-coding genes has been shown to correlate with their responsiveness to immunotherapy. However, whole-exome sequencing is time-consuming and costly. Yu-Chao Wang at the National Yang-Ming University, Taiwan, and colleagues have developed cancer-specific mutation load estimation models for adenocarcinoma, melanoma and colorectal cancer that require sequencing only a small number of genes. They show that the mutation load in lung adenocarcinoma patients can be estimated from 24 genes and that they can predict immunotherapy responsiveness with similar accuracy to that obtained using whole-exome sequencing.

Cardiac arrhythmia and neuroexcitability gene variants in resected brain tissue from patients with sudden unexpected death in epilepsy (SUDEP).

Abstract: Sudden unexpected death in epilepsy (SUDEP) is the leading cause of epilepsy-related mortality in young adults. The exact mechanisms are unknown but death often follows a generalized tonic-clonic seizure. Proposed mechanisms include seizure-related respiratory, cardiac, autonomic, and arousal dysfunction. Genetic drivers underlying SUDEP risk are largely unknown. To identify potential SUDEP risk genes, we compared whole-exome sequences (WES) derived from formalin-fixed paraffin embedded surgical brain specimens of eight epilepsy patients who died from SUDEP with seven living controls matched for age at surgery, sex, year of surgery and lobe of resection. We compared identified variants from both groups filtering known polymorphisms from publicly available data as well as scanned for epilepsy and candidate SUDEP genes. In the SUDEP cohort, we identified mutually exclusive variants in genes involved in µ-opiod signaling, gamma-aminobutyric acid (GABA) and glutamate-mediated synaptic signaling, including ARRB2, ITPR1, GABRR2, SSTR5, GRIK1, CTNAP2, GRM8, GNAI2 and GRIK5. In SUDEP patients we also identified variants in genes associated with cardiac arrhythmia, including KCNMB1, KCNIP1, DPP6, JUP, F2, and TUBA3D, which were not present in living epilepsy controls. Our data shows that genomic analysis of brain tissue resected for seizure control can identify potential genetic biomarkers of SUDEP risk.

Complex genetics of female fertility.

Abstract: Variation in reproductive lifespan and female fertility have implications for health, population size and ageing. Fertility declines well before general signs of menopause and is also adversely affected by common reproductive diseases, including polycystic ovarian syndrome (PCOS) and endometriosis. Understanding the factors that regulate the timing of puberty and menopause, and the relationships with fertility are important for individuals and for policy. Substantial genetic variation exists for common traits associated with reproductive lifespan and for common diseases influencing female fertility. Genetic studies have identified mutations in genes contributing to disorders of reproduction, and in the last ten years, genome-wide association studies (GWAS) have transformed our understanding of common genetic contributions to these complex traits and diseases. These studies have made great progress towards understanding the genetic factors contributing to variation in traits and diseases influencing female fertility. The data emerging from GWAS demonstrate the utility of genetics to explain epidemiological observations, revealing shared biological pathways linking puberty timing, fertility, reproductive ageing and health outcomes. Many variants implicate DNA damage/repair genes in variation in the age at menopause with implications for follicle health and ageing. In addition to the discovery of individual genes and pathways, the increasingly powerful studies on common genetic risk factors help interpret the underlying relationships and direction of causation in the regulation of reproductive lifespan, fertility and related traits.

Incorporating epilepsy genetics into clinical practice: a 360°evaluation.

Abstract: We evaluated a new epilepsy genetic diagnostic and counseling service covering a UK population of 3.5 million. We calculated diagnostic yield, estimated clinical impact, and surveyed referring clinicians and families. We costed alternative investigational pathways for neonatal onset epilepsy. Patients with epilepsy of unknown aetiology onset 2 years, with turnaround time of 21 days. Pathogenic variants were seen in SCN8A, SCN2A, SCN1A, KCNQ2, HNRNPU, GRIN2A, SYNGAP1, STXBP1, STX1B, CDKL5, CHRNA4, PCDH19 and PIGT. Clinician prediction was poor. Clinicians and families rated the service highly. In neonates, the cost of investigations could be reduced from £9362 to £2838 by performing gene panel earlier and the median diagnostic delay of 3.43 years reduced to 21 days. Panel testing for epilepsy has a high yield among children with onset < 2 years, and an appreciable clinical and financial impact. Parallel gene testing supersedes single gene testing in most early onset cases that do not show a clear genotype-phenotype correlation. Clinical interpretation of laboratory results, and in-depth discussion of implications for patients and their families, necessitate multidisciplinary input and skilled genetic counseling. Screening for epilepsy-related gene variants can lead to effective, personalized treatment plans while reducing costs. UK and Danish scientists, led by Deb Pal, King’s College London, evaluated a new service within the UK that searches for genetic variants in patients that cause epilepsy. The authors assessed the impact of next-generation gene panel tests, as well as the necessary resources to make such a service effective. Genetic testing was most effective in patients with seizure onset under 2 years old (21% diagnosed) and yield even higher in neonatal-onset epilepsy (63% diagnosed). For many patients with pathogenic variants, the diagnoses allowed for recommendations on treatment or enrolment in clinical trials. The researchers found that diagnostic delay and financial burden in neonatal epilepsy could be drastically reduced with gene panel testing. The scheme was highly rated by users and patients alike.

Clinical testing of BRCA1 and BRCA2: a worldwide snapshot of technological practices.

Abstract: Clinical testing of BRCA1 and BRCA2 began over 20 years ago. With the expiration and overturning of the BRCA patents, limitations on which laboratories could offer commercial testing were lifted. These legal changes occurred approximately the same time as the widespread adoption of massively parallel sequencing (MPS) technologies. Little is known about how these changes impacted laboratory practices for detecting genetic alterations in hereditary breast and ovarian cancer genes. Therefore, we sought to examine current laboratory genetic testing practices for BRCA1/BRCA2. We employed an online survey of 65 questions covering four areas: laboratory characteristics, details on technological methods, variant classification, and client-support information. Eight United States (US) laboratories and 78 non-US laboratories completed the survey. Most laboratories (93%; 80/86) used MPS platforms to identify variants. Laboratories differed widely on: (1) technologies used for large rearrangement detection; (2) criteria for minimum read depths; (3) non-coding regions sequenced; (4) variant classification criteria and approaches; (5) testing volume ranging from 2 to 2.5 × 105 tests annually; and (6) deposition of variants into public databases. These data may be useful for national and international agencies to set recommendations for quality standards for BRCA1/BRCA2 clinical testing. These standards could also be applied to testing of other disease genes.

Responsible sharing of biomedical data and biospecimens via the "Automatable Discovery and Access Matrix" (ADA-M).

Abstract: Given the data-rich nature of modern biomedical research, there is a pressing need for a systematic, structured, computer-readable way to capture, communicate, and manage sharing rules that apply to biomedical resources. This is essential for responsible recording, versioning, communication, querying, and actioning of resource sharing plans. However, lack of a common “information model” for rules and conditions that govern the sharing of materials, methods, software, data, and knowledge creates a fundamental barrier. Without this, it can be virtually impossible for Research Ethics Committees (RECs), Institutional Review Boards (IRBs), Data Access Committees (DACs), biobanks, and end users to confidently track, manage, and interpret applicable legal and ethical requirements. This raises costs and burdens of data stewardship and decreases efficient and responsible access to data, biospecimens, and other resources. To address this, the GA4GH and IRDiRC organizations sponsored the creation of the Automatable Discovery and Access Matrix (ADA-M, read simply as “Adam”). ADA-M is a comprehensive information model that provides the basis for producing structured metadata “Profiles” of regulatory conditions, thereby enabling efficient application of those conditions across regulatory spheres. Widespread use of ADA-M will aid researchers in globally searching and prescreening potential data and/or biospecimen resources for compatibility with their research plans in a responsible and efficient manner, increasing likelihood of timely DAC approvals while also significantly reducing time and effort DACs, RECs, and IRBs spend evaluating resource requests and research proposals. Extensive online documentation, software support, video guides, and an Application Programming Interface (API) for ADA-M have been made available.

Recurrent loss of heterozygosity correlates with clinical outcome in pancreatic neuroendocrine cancer.

Abstract: Pancreatic neuroendocrine tumors (pNETs) are uncommon cancers arising from pancreatic islet cells. Here we report the analysis of gene mutation, copy number, and RNA expression of 57 sporadic well-differentiated pNETs. pNET genomes are dominated by aneuploidy, leading to concordant changes in RNA expression at the level of whole chromosomes and chromosome segments. We observed two distinct patterns of somatic pNET aneuploidy that are associated with tumor pathology and patient prognosis. Approximately 26% of the patients in this series had pNETs with genomes characterized by recurrent loss of heterozygosity (LoH) of 10 specific chromosomes, accompanied by bi-allelic MEN1 inactivation and generally poor clinical outcome. Another ~40% of patients had pNETs that lacked this recurrent LoH pattern but had chromosome 11 LoH, bi-allelic MEN1 inactivation, and universally good clinical outcome. The somatic aneuploidy allowed pathogenic germline variants (e.g., ATM) to be expressed unopposed, with RNA expression patterns showing inactivation of downstream tumor suppressor pathways. No prognostic associations were found with tumor morphology, single gene mutation, or expression of RNAs reflecting the activity of immune, differentiation, proliferative or tumor suppressor pathways. In pNETs, single gene mutations appear to be less important than aneuploidy, with MEN1 the only statistically significant recurrently mutated driver gene. In addition, only one pNET in the series had clearly actionable single nucleotide variants (SNVs) (in PTEN and FLCN) confirmed by corroborating RNA expression changes. The two clinically relevant patterns of LoH described here define a novel oncogenic mechanism and a plausible route to genomic precision oncology for this tumor type.

User considerations in assessing pharmacogenomic tests and their clinical support tools.

Abstract: Pharmacogenomic (PGx) testing is gaining recognition from physicians, pharmacists and patients as a tool for evidence-based medication management However, seemingly similar PGx testing panels (and PGx-based decision support tools) can diverge in their technological specifications, as well as the genetic factors that determine test specificity and sensitivity, and hence offer different values for users Reluctance to embrace PGx testing is often the result of unfamiliarity with PGx technology, a lack of knowledge about the availability of curated guidelines/evidence for drug dosing recommendations, and an absence of wide-spread institutional implementation efforts and educational support Demystifying an often confusing and variable PGx marketplace can lead to greater acceptance of PGx as a standard-of-care practice that improves drug outcomes and provides a lifetime value for patients Here, we highlight the key underlying factors of a PGx test that should be considered, and discuss the current progress of PGx implementation

A phenotype centric benchmark of variant prioritisation tools

Abstract: Next generation sequencing is a standard tool used in clinical diagnostics. In Mendelian diseases the challenge is to discover the single etiological variant among thousands of benign or functionally unrelated variants. After calling variants from aligned sequencing reads, variant prioritisation tools are used to examine the conservation or potential functional consequences of variants. We hypothesised that the performance of variant prioritisation tools may vary by disease phenotype. To test this we created benchmark data sets for variants associated with different disease phenotypes. We found that performance of 24 tested tools is highly variable and differs by disease phenotype. The task of identifying a causative variant amongst a large number of benign variants is challenging for all tools, highlighting the need for further development in the field. Based on our observations, we recommend use of five top performers found in this study (FATHMM, M-CAP, MetaLR, MetaSVM and VEST3). In addition we provide tables indicating which analytical approach works best in which disease context. Variant prioritisation tools are best suited to investigate variants associated with well-studied genetic diseases, as these variants are more readily available during algorithm development than variants associated with rare diseases. We anticipate that further development into disease focussed tools will lead to significant improvements.

Pathogenic copy number variants that affect gene expression contribute to genomic burden in cerebral palsy.

Abstract: Cerebral palsy (CP) is the most frequent movement disorder of childhood affecting 1 in 500 live births in developed countries. We previously identified likely pathogenic de novo or inherited single nucleotide variants (SNV) in 14% (14/98) of trios by exome sequencing and a further 5% (9/182) from evidence of outlier gene expression using RNA sequencing. Here, we detected copy number variants (CNV) from exomes of 186 unrelated individuals with CP (including our original 98 trios) using the CoNIFER algorithm. CNV were validated with Illumina 850 K SNP arrays and compared with RNA-Seq outlier gene expression analysis from lymphoblastoid cell lines (LCL). Gene expression was highly correlated with gene dosage effect. We resolved an additional 3.7% (7/186) of this cohort with pathogenic or likely pathogenic CNV while a further 7.7% (14/186) had CNV of uncertain significance. We identified recurrent genomic rearrangements previously associated with CP due to 2p25.3 deletion, 22q11.2 deletions and duplications and Xp monosomy. We also discovered a deletion of a single gene, PDCD6IP, and performed additional zebrafish model studies to support its single allele loss in CP aetiology. Combined SNV and CNV analysis revealed pathogenic and likely pathogenic variants in 22.7% of unselected individuals with CP. At least 23% of cerebral palsy has a genetic basis, due to either point mutations or large chromosomal abnormalities. Using sequence data from 186 unrelated patients, a team led by Mark Corbett from the University of Adelaide, Australia, searched the protein-coding portion of the genome for disease-causing duplications or deletions, types of mutations collectively known as copy number variants, or CNVs. The researchers singled out 7 pathogenic CNVs that they corroborated through microarray profiling and gene expression analyses. Using a zebrafish model, the researchers identified a new gene “PDCD6IP” associated with cerebral palsy and epilepsy. They also flagged another 14 CNVs that were likely pathogenic but could not be confirmed. The work highlights the need for comprehensive genetic testing to be considered early in the diagnosis of cerebral palsy.

Identification of an immune gene expression signature associated with favorable clinical features in Treg-enriched patient tumor samples.

Abstract: Immune heterogeneity within the tumor microenvironment undoubtedly adds several layers of complexity to our understanding of drug sensitivity and patient prognosis across various cancer types. Within the tumor microenvironment, immunogenicity is a favorable clinical feature in part driven by the antitumor activity of CD8+ T cells. However, tumors often inhibit this antitumor activity by exploiting the suppressive function of regulatory T cells (Tregs), thus suppressing the adaptive immune response. Despite the seemingly intuitive immunosuppressive biology of Tregs, prognostic studies have produced contradictory results regarding the relationship between Treg enrichment and survival. We therefore analyzed RNA-seq data of Treg-enriched tumor samples to derive a pan-cancer gene signature able to help reconcile the inconsistent results of Treg studies, by better understanding the variable clinical association of Tregs across alternative tumor contexts. We show that increased expression of a 32-gene signature in Treg-enriched tumor samples (n = 135) is able to distinguish a cohort of patients associated with chemosensitivity and overall survival. This cohort is also enriched for CD8+ T cell abundance, as well as the antitumor M1 macrophage subtype. With a subsequent validation in a larger TCGA pool of Treg-enriched patients (n = 626), our results reveal a gene signature able to produce unsupervised clusters of Treg-enriched patients, with one cluster of patients uniquely representative of an immunogenic tumor microenvironment. Ultimately, these results support the proposed gene signature as a putative biomarker to identify certain Treg-enriched patients with immunogenic tumors that are more likely to be associated with features of favorable clinical outcome.

An integrated clinical program and crowdsourcing strategy for genomic sequencing and Mendelian disease gene discovery.

Abstract: Despite major progress in defining the genetic basis of Mendelian disorders, the molecular etiology of many cases remains unknown. Patients with these undiagnosed disorders often have complex presentations and require treatment by multiple health care specialists. Here, we describe an integrated clinical diagnostic and research program using whole-exome and whole-genome sequencing (WES/WGS) for Mendelian disease gene discovery. This program employs specific case ascertainment parameters, a WES/WGS computational analysis pipeline that is optimized for Mendelian disease gene discovery with variant callers tuned to specific inheritance modes, an interdisciplinary crowdsourcing strategy for genomic sequence analysis, matchmaking for additional cases, and integration of the findings regarding gene causality with the clinical management plan. The interdisciplinary gene discovery team includes clinical, computational, and experimental biomedical specialists who interact to identify the genetic etiology of the disease, and when so warranted, to devise improved or novel treatments for affected patients. This program effectively integrates the clinical and research missions of an academic medical center and affords both diagnostic and therapeutic options for patients suffering from genetic disease. It may therefore be germane to other academic medical institutions engaged in implementing genomic medicine programs.

HHV-6 encoded small non-coding RNAs define an intermediate and early stage in viral reactivation.

Abstract: Human herpesvirus 6A and 6B frequently acquires latency. HHV-6 activation has been associated with various human diseases. Germ line inheritance of chromosomally integrated HHV-6 makes viral DNA-based analysis difficult for determination of early stages of viral activation. We characterized early stages of HHV-6 activation using high throughput transcriptomics studies and applied the results to understand virus activation under clinical conditions. Using a latent HHV-6A cell culture model in U2OS cells, we identified an early stage of viral reactivation, which we define as transactivation that is marked by transcription of several viral small non-coding RNAs (sncRNAs) in the absence of detectable increase in viral replication and proteome. Using deep sequencing approaches, we detected previously known as well as a new viral sncRNAs that characterized viral transactivation and differentiated it from latency. Here we show changes in human transcriptome upon viral transactivation that reflect multiple alterations in mitochondria-associated pathways, which was supported by observation of increased mitochondrial fragmentation in virus reactivated cells. Furthermore, we present here a unique clinical case of DIHS/DRESS associated death where HHV-6 sncRNA-U14 was abundantly detected throughout the body of the patient in the presence of low viral DNA. In this study, we have identified a unique and early stage of viral activation that is characterized by abundant transcription of viral sncRNAs, which can serve as an ideal biomarker under clinical conditions.

FDA guidance for next generation sequencing-based testing: balancing regulation and innovation in precision medicine

Abstract: On 12 April 2018, the Food and Drug Administration (FDA) finalized a guidance document, Considerations for Design, Development, and Analytical Validation of Next Generation Sequencing (NGS)-Based In Vitro Diagnostics (IVDs) Intended to Aid in the Diagnosis of Suspected Germline Diseases, in efforts to accelerate the establishment of a regulatory approach for next generation sequencing (NGS) testing. While the FDA’s guidance is a step forward towards integrating NGS into clinical practice, the document has rekindled the debate about the FDA’s authority despite existing rules already enforced by Centers for Medicare and Medicaid Services (CMS). The FDA’s proposed framework also raises concerns as to whether it effectively protects consumer safety or threatens scientific discovery and innovation. As questions about regulation, statutory power, and legislation reform remain, the FDA and healthcare leaders must consider logistical and stakeholder challenges, if they seek to transform clinical care with NGS technology.

TAC-seq: targeted DNA and RNA sequencing for precise biomarker molecule counting

Abstract: Targeted next-generation sequencing (NGS) methods have become essential in medical research and diagnostics. In addition to NGS sensitivity and high-throughput capacity, precise biomolecule counting based on unique molecular identifier (UMI) has potential to increase biomolecule detection accuracy. Although UMIs are widely used in basic research its introduction to clinical assays is still in progress. Here, we present a robust and cost-effective TAC-seq (Targeted Allele Counting by sequencing) method that uses UMIs to estimate the original molecule counts of mRNAs, microRNAs, and cell-free DNA. We applied TAC-seq in three different clinical applications and compared the results with standard NGS. RNA samples extracted from human endometrial biopsies were analyzed using previously described 57 mRNA-based receptivity biomarkers and 49 selected microRNAs at different expression levels. Cell-free DNA aneuploidy testing was based on cell line (47,XX, +21) genomic DNA. TAC-seq mRNA profiling showed identical clustering results to transcriptome RNA sequencing, and microRNA detection demonstrated significant reduction in amplification bias, allowing to determine minor expression changes between different samples that remained undetermined by standard NGS. The mimicking experiment for cell-free DNA fetal aneuploidy analysis showed that TAC-seq can be applied to count highly fragmented DNA, detecting significant (p = 7.6 × 10−4) excess of chromosome 21 molecules at 10% fetal fraction level. Based on three proof-of-principle applications we demonstrate that TAC-seq is an accurate and highly potential biomarker profiling method for advanced medical research and diagnostics.

Heterogeneity in clinical sequencing tests marketed for autism spectrum disorders.

Abstract: Autism spectrum disorders (ASD) is now a high profile and common concern in the population. Diagnosis has long been based on clinical findings, but with increased recognition of a strong genetic contribution and a subset of cases with an underlying genetic syndrome, clinical laboratory testing to search for genomic risk variants is now an important component of the diagnostic work-up. Chromosomal microarray is currently the recommended first-tier genetic test for ASD, revealing deleted and duplicated segments of DNA. These relatively large copy number variations (CNVs), often affecting several genes, can account for 5–25% of ASD cases, depending on the cohort examined. The introduction of next-generation sequencing (NGS) now allows for a more in-depth look at ASD’s genetic landscape. Besides CNVs, genomic risk factors for ASD can include singlenucleotide variants, insertion/deletions, and complex structural variations, contained in potentially hundreds of different genes, which may be involved in complex interactions. The NGS technology may be targeted to a selection of genes of interest, or to the coding portions of all genes (exome sequencing), or for entire genome sequencing. Such sequencing approaches are now being marketed for use as second-tier tests for ASD, particularly when chromosomal microarray analysis has not revealed any explanation for the clinical presentation. We undertook to survey the scope of sequencing tests for ASD (or including ASD) that are primarily being marketed by commercial laboratories as adjuncts or follow-up to chromosomal microarrays. Perhaps not surprisingly, because this is a new territory and guidelines are not yet developed, we found significant heterogeneity among such laboratories with respect to the tests they offer. The most striking finding was the variable number of genes being tested for on panels marketed for ASD (range, 11–2562), with little content overlap, albeit, these encompassed ASD-specific as well as much larger ASD-inclusive panels (Table 1). Our search began in 2017, using the former GeneTests and current Genetic Testing Registry as resources, supplemented by an internet search (terms: “autism panel”, “autism lab sequencing”, “autism genetic test”). To focus on gene panels, we excluded biochemical assays, chromosomal microarrays, and sequencing tests involving fewer than three genes. To focus on ASD, we excluded tests targeted for general neurodevelopmental disorders, seizure disorders, and intellectual disability, unless they specified autism. That search resulted in 20 DNA testing laboratories offering an ASD gene panel. Updating the survey in June 2018 (adding use of a new resource, Concert Genetics— www.concertgenetics.com), we found that four panels were no longer offered, but five were newly available, for an updated total of 21 laboratories (Table 1). We then went to the individual laboratory websites for further information. We compared ASD gene lists from panels of the 21 laboratories. Each entire panel is listed in Supplementary Table S1. Supplementary Table S2 shows the 178 genes included in at least five lab panels (“shared genes”) in order of listing frequency. Table 2 summarizes the top 16 most commonly listed genes, along with their associated genetic disorders according to the Online Mendelian Inheritance in Man (OMIM). The latter shows that most (12/16) of these genes are associated with genetic syndromes, where the primary phenotype involves physical/ systemic features and not ASD. Almost half of these genes (7/ 16) were located on the X chromosome. Only one gene was included on all panels offered by the 21 labs: MECP2, which is associated with Rett syndrome (previously considered part of the ASD spectrum, but no longer so under criteria of the Diagnostic and statistical manual of mental disorders (5th edn)). There were 63 genes shared among at least 10 lists, but the vast majority of the cumulative list of 2928 unique genes were included by fewer than five laboratories. There were, nonetheless, some pockets of significant overlap. Two pairs of laboratories each posted identical ASD gene lists. Two other laboratories had lists that encompassed those of separate labs, but with additional genes to create their own collection. We then compared the gene lists ascertained here to four lists from academic research projects that identify genes with strong association to ASD: Simons Foundation Autism Risk Initiative (SFARI), Simons Foundation Powering Autism Research for Knowledge (SPARK), Autism Speaks – MSSNG, and Autism Sequencing Consortium (ASC) (Supplementary Table S2). Comparing these lists, we found 15 genes to be shared by all, and an additional 24 genes were common to 3 of the 4 lists (Supplementary Table S3). We noted that 39 ASD risk genes identified by at least two of these research sources were not included among the top 178 genes listed by the commercial labs (Supplementary Table S4). Moreover, seven well-studied genes (ADNP, ARID1B, CHD8, POGZ, SCN2A, SLC6A1, and SYNGAP1) identified to be important for ASD by the SFARI, SPARK, MSSNG, and ASC research projects, are not found among the commercial list of the top 47 shared genes (Supplementary Table S2).

A robust targeted sequencing approach for low input and variable quality DNA from clinical samples.

Abstract: Next-generation deep sequencing of gene panels is being adopted as a diagnostic test to identify actionable mutations in cancer patient samples. However, clinical samples, such as formalin-fixed, paraffin-embedded specimens, frequently provide low quantities of degraded, poor quality DNA. To overcome these issues, many sequencing assays rely on extensive PCR amplification leading to an accumulation of bias and artifacts. Thus, there is a need for a targeted sequencing assay that performs well with DNA of low quality and quantity without relying on extensive PCR amplification. We evaluate the performance of a targeted sequencing assay based on Oligonucleotide Selective Sequencing, which permits the enrichment of genes and regions of interest and the identification of sequence variants from low amounts of damaged DNA. This assay utilizes a repair process adapted to clinical FFPE samples, followed by adaptor ligation to single stranded DNA and a primer-based capture technique. Our approach generates sequence libraries of high fidelity with reduced reliance on extensive PCR amplification-this facilitates the accurate assessment of copy number alterations in addition to delivering accurate single nucleotide variant and insertion/deletion detection. We apply this method to capture and sequence the exons of a panel of 130 cancer-related genes, from which we obtain high read coverage uniformity across the targeted regions at starting input DNA amounts as low as 10 ng per sample. We demonstrate the performance using a series of reference DNA samples, and by identifying sequence variants in DNA from matched clinical samples originating from different tissue types.

Two different STAT1 gain-of-function mutations lead to diverse IFN-γ-mediated gene expression

Abstract: Signal transducer and activator of transcription 1 (STAT1) regulates multiple biological processes downstream of a variety of cytokine receptors in many cell types. Heterozygous gain-of-function (GOF) mutations in STAT1 have been associated with a diverse phenotype encompassing chronic mucocutaneous candidiasis (CMCC) and declining immunity. There is no clear correlation between STAT1 domain-specific mutations and phenotype, and it remains unclear why GOF mutations in STAT1 result in such a wide spectrum of clinical presentations. To begin exploring this dilemma, we have studied the patterns of gene expression mediated by two different GOF mutations. Analysis of IFN-γ response elements using RNA microarrays in cells transfected with the rare H629Y mutant or the common R274G mutant showed distinct patterns of gene expression. We show here that the impact of GOF mutations in STAT1 is variant-specific. This difference in gene expression may explain the diversity in clinical manifestations experienced by these patients.

Clinical relevance of screening checklists for detecting cancer predisposition syndromes in Asian childhood tumours.

Abstract: Assessment of cancer predisposition syndromes (CPS) in childhood tumours is challenging to paediatric oncologists due to inconsistent recognizable clinical phenotypes and family histories, especially in cohorts with unknown prevalence of germline mutations. Screening checklists were developed to facilitate CPS detection in paediatric patients; however, their clinical value have yet been validated. Our study aims to assess the utility of clinical screening checklists validated by genetic sequencing in an Asian cohort of childhood tumours. We evaluated 102 patients under age 18 years recruited over a period of 31 months. Patient records were reviewed against two published checklists and germline mutations in 100 cancer-associated genes were profiled through a combination of whole-exome sequencing and multiplex ligation-dependent probe amplification on blood-derived genomic DNA. Pathogenic germline mutations were identified in ten (10%) patients across six known cancer predisposition genes: TP53, DICER1, NF1, FH, SDHD and VHL. Fifty-four (53%) patients screened positive on both checklists, including all ten pathogenic germline carriers. TP53 was most frequently mutated, affecting five children with adrenocortical carcinoma, sarcomas and diffuse astrocytoma. Disparity in prevalence of germline mutations across tumour types suggested variable genetic susceptibility and implied potential contribution of novel susceptibility genes. Only five (50%) children with pathogenic germline mutations had a family history of cancer. We conclude that CPS screening checklists are adequately sensitive to detect at-risk children and are relevant for clinical application. In addition, our study showed that 10% of Asian paediatric solid tumours have a heritable component, consistent with other populations.

Predictors of next-generation sequencing panel selection using a shared decision-making approach

Abstract: The introduction of next-generation sequencing panels has transformed the approach for genetic testing in cancer patients, however, established guidelines for their use are lacking. A shared decision-making approach has been adopted by our service, where patients play an active role in panel selection and we sought to identify factors associated with panel selection and report testing outcomes. Demographic and clinical data were gathered for female breast and/or ovarian cancer patients aged 21 and over who underwent panel testing. Panel type was classified as 'breast cancer panel' (BCP) or 'multi-cancer panel' (MCP). Stepwise multiple logistic regression analysis was used to identify clinical factors most predictive of panel selection. Of the 265 included subjects, the vast majority selected a broader MCP (81.5%). Subjects who chose MCPs were significantly more likely to be ≥50 years of age (49 vs. 31%; p < 0.05), Chinese (76 vs. 47%; p < 0.001) and have a personal history of ovarian cancer (41 vs. 8%; p < 0.001) with the latter two identified as the best predictors of panel selection. Family history of cancer was not significantly associated with panel selection. There were no statistically significant differences in result outcomes between the two groups. In summary, our findings demonstrate that the majority of patients have a preference for interrogating a larger number of genes beyond those with established testing guidelines, despite the additional likelihood of uncertainty. Individual factors, including cancer history and ethnicity, are the best predictors of panel selection.

Improving imputation in disease-relevant regions: lessons from cystic fibrosis.

Abstract: Does genotype imputation with public reference panels identify variants contributing to disease? Genotype imputation using the 1000 Genomes Project (1KG; 2504 individuals) displayed poor coverage at the causal cystic fibrosis (CF) transmembrane conductance regulator (CFTR) locus for the International CF Gene Modifier Consortium. Imputation with the larger Haplotype Reference Consortium (HRC; 32,470 individuals) displayed improved coverage but low sensitivity of variants clinically relevant for CF. A hybrid reference that combined whole genome sequencing (WGS) from 101 CF individuals with the 1KG imputed a greater number of single-nucleotide variants (SNVs) that would be analyzed in a genetic association study (r2 ≥ 0.3 and MAF ≥ 0.5%) than imputation with the HRC, while the HRC excelled in the lower frequency spectrum. Using the 1KG or HRC as reference panels missed the most common CF-causing variants or displayed low imputation accuracy. Designs that incorporate population-specific WGS can improve imputation accuracy at disease-specific loci, while imputation using public data sets can omit disease-relevant genotypes.

Exome sequencing for paediatric-onset diseases: impact of the extensive involvement of medical geneticists in the diagnostic odyssey.

Abstract: Currently, offering whole-exome sequencing (WES) via collaboration with an external laboratory is increasingly common. However, the receipt of a WES report can be merely the beginning of a continuing exploration process rather than the end of the diagnostic odyssey. The laboratory often does not have the information the physician has, and any discrepancies in variant interpretation must be addressed by a medical geneticist. In this study, we performed diagnostic WES of 104 patients with paediatric-onset genetic diseases. The post-exome review of WES reports by the clinical geneticist led to a more comprehensive assessment of variant pathogenicity in 16 cases. The overall diagnostic yield was 41% (n = 43). Among these 43 diagnoses, 51% (22/43) of the pathogenic variants were nucleotide changes that have not been previously reported. The time required for the post-exome review of the WES reports varied, and 26% (n = 27) of the reports required an extensive amount of time (>3 h) for the geneticist to review. In this predominantly Chinese cohort, we highlight the importance of discrepancies between global and ethnic-specific frequencies of a genetic variant that complicate variant interpretation and the significance of post-exome diagnostic modalities in genetic diagnosis using WES. The challenges faced by geneticists in interpreting WES reports are also discussed.

Chemical genetic-based phenotypic screen reveals novel regulators of gluconeogenesis in human primary hepatocytes.

Abstract: Insulin resistance is a pathophysiological hallmark of type 2 diabetes and nonalcoholic fatty liver disease. Under the condition of fat accumulation in the liver, suppression of hepatic glucose production by insulin is diminished. In order to gain deeper understanding of dysregulation of glucose production in metabolic diseases, in the present study, we performed an unbiased phenotypic screening in primary human hepatocytes to discover novel mechanisms that regulate gluconeogenesis in the presence of insulin. To optimize phenotypic screening process, we used a chemical genetic screening approach by building a small-molecule library with prior knowledge of activity-based protein profiling. The "positive hits" result from the screen will be small molecules with known protein targets. This makes downstream deconvolution process (i.e., determining the relevant biological targets) less time-consuming. To unbiasedly decipher the molecular targets, we developed a novel statistical method and discovered a set of genes, including DDR3 and CACNA1E that suppressed gluconeogenesis in human hepatocytes. Further investigation, including transcriptional profiling and gene network analysis, was performed to understand the molecular functions of DRD3 and CACNA1E in human hepatocytes.