ViroFind: A novel target-enrichment deep-sequencing platform reveals a complex JC virus population in the brain of PML patients

Deep nucleotide sequencing enables the unbiased, broad-spectrum detection of viruses in clinical samples without requiring an a priori hypothesis for the source of infection. However, its use in clinical research applications is limited by low cost-effectiveness given that most of the sequencing information from clinical samples is related to the human genome, which renders the analysis of viral genomes challenging. To overcome this limitation we developed ViroFind, an in-solution target-enrichment platform for virus detection and discovery in clinical samples. ViroFind comprises 165,433 viral probes that cover the genomes of 535 selected DNA and RNA viruses that infect humans or could cause zoonosis. The ViroFind probes are used in a hybridization reaction to enrich viral sequences and therefore enhance the detection of viral genomes via deep sequencing. We used ViroFind to detect and analyze all viral populations in the brain of 5 patients with progressive multifocal leukoencephalopathy (PML) and of 18 control subjects with no known neurological disease. Compared to direct deep sequencing, by using ViroFind we enriched viral sequences present in the clinical samples up to 127-fold. We discovered highly complex polyoma virus JC populations in the PML brain samples with a remarkable degree of genetic divergence among the JC virus variants of each PML brain sample. Specifically for the viral capsid protein VP1 gene, we identified 24 single nucleotide substitutions, 12 of which were associated with amino acid changes. The most frequent (4 of 5 samples, 80%) amino acid change was D66H, which is associated with enhanced tissue tropism, and hence likely a viral fitness advantage, compared to other variants. Lastly, we also detected sparse JC virus sequences in 10 of 18 (55.5%) of control samples and sparse human herpes virus 6B (HHV6B) sequences in the brain of 11 of 18 (61.1%) control subjects. In sum, ViroFind enabled the in-depth analysis of all viral genomes in PML and control brain samples and allowed us to demonstrate a high degree of JC virus genetic divergence in vivo that has been previously underappreciated. ViroFind can be used to investigate the structure of the virome with unprecedented depth in health and disease state

The Long Noncoding RNA Landscape of the Ischemic Human Left Ventricle

Background—The discovery of functional classes of long noncoding RNAs (lncRNAs) has expanded our understanding of the variety of RNA species that exist in cells. In the heart, lncRNAs have been implicated in the regulation of development, ischemic and dilated cardiomyopathy, and myocardial infarction. Nevertheless, there is a limited description of expression profiles for these transcripts in human subjects. Methods and Results—We obtained left ventricular tissue from human patients undergoing cardiac surgery and used RNA sequencing to describe a lncRNA profile. We then identified a list of lncRNAs that were differentially expressed between pairs of samples before and after the ischemic insult of cardiopulmonary bypass. The expression of some of these lncRNAs correlates with ischemic time. Coding genes in close proximity to differentially expressed lncRNAs as well as coding genes that have coordinated expression with these lncRNAs are enriched in functional categories related to myocardial infarction including: heart function, metabolism, the stress response, and the immune system. Conclusions—We describe a list of lncRNAs that are differentially expressed after ischemia in the human heart. These genes are predicted to function in pathways consistent with myocardial injury. As a result, lncRNAs may serve as novel diagnostic and therapeutic targets for ischemic heart disease

Genetic Variants Associated With Cancer Therapy-Induced Cardiomyopathy

BACKGROUND: Cancer therapy-induced cardiomyopathy (CCM) is associated with cumulative drug exposures and preexisting cardiovascular disorders. These parameters incompletely account for substantial interindividual susceptibility to CCM. We hypothesized that rare variants in cardiomyopathy genes contribute to CCM. METHODS: We studied 213 patients with CCM from 3 cohorts: retrospectively recruited adults with diverse cancers (n=99), prospectively phenotyped adults with breast cancer (n=73), and prospectively phenotyped children with acute myeloid leukemia (n=41). Cardiomyopathy genes, including 9 prespecified genes, were sequenced. The prevalence of rare variants was compared between CCM cohorts and The Cancer Genome Atlas participants (n=2053), healthy volunteers (n=445), and an ancestry-matched reference population. Clinical characteristics and outcomes were assessed and stratified by genotypes. A prevalent CCM genotype was modeled in anthracycline-treated mice. RESULTS: CCM was diagnosed 0.4 to 9 years after chemotherapy; 90% of these patients received anthracyclines. Adult patients with CCM had cardiovascular risk factors similar to the US population. Among 9 prioritized genes, patients with CCM had more rare protein-altering variants than comparative cohorts ( P≤1.98e-04). Titin-truncating variants (TTNtvs) predominated, occurring in 7.5% of patients with CCM versus 1.1% of The Cancer Genome Atlas participants ( P=7.36e-08), 0.7% of healthy volunteers ( P=3.42e-06), and 0.6% of the reference population ( P=5.87e-14). Adult patients who had CCM with TTNtvs experienced more heart failure and atrial fibrillation ( P=0.003) and impaired myocardial recovery ( P=0.03) than those without. Consistent with human data, anthracycline-treated TTNtv mice and isolated TTNtv cardiomyocytes showed sustained contractile dysfunction unlike wild-type ( P=0.0004 and P<0.002, respectively). CONCLUSIONS: Unrecognized rare variants in cardiomyopathy-associated genes, particularly TTNtvs, increased the risk for CCM in children and adults, and adverse cardiac events in adults. Genotype, along with cumulative chemotherapy dosage and traditional cardiovascular risk factors, improves the identification of patients who have cancer at highest risk for CCM. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov . Unique identifiers: NCT01173341; AAML1031; NCT01371981.This work was supported in part by grants from the Instituto de Salud Carlos III (ISCIII) (PI15/01551, PI17/01941 and CB16/11/00432 to P.G-P. and L.A-P.), the Spanish Ministry of Economy and Competitiveness (SAF2015-71863-REDT to P.G-P.), the John S. LaDue Memorial Fellowship at Harvard Medical School (Y.K.), Wellcome Trust (107469/Z/15/Z to J.S.W.), Medical Research Council (intramural awards to S.A.C. and J.S.W; MR/M003191/1 to U.T), National Institute for Health Research Biomedical Research Unit at the Royal Brompton and Harefield National Health Service Foundation Trust and Imperial College London (P.J.B., S.A.C., J.S.W.), National Institute for Health Research Biomedical Research Centre at Imperial College London Healthcare National Health Service Trust and Imperial College London (D.O.R., S.A.C., S.P., J.S.W.), Sir Henry Wellcome Postdoctoral Fellowship (C.N.T.), Rosetrees and Stoneygate Imperial College Research Fellowship (N.W.), Fondation Leducq (S.A.C., C.E.S., J.G.S.), Health Innovation Challenge Fund award from the Wellcome Trust and Department of Health (UK; HICF-R6-373; S.A.C., P.J.B., J.S. W.), the British Heart Foundation (NH/17/1/32725 to D.O.R.; SP/10/10/28431 to S.A.C), Alex’s Lemonade Stand Foundation (K.G.), National Institutes of Health (R.A.: U01CA097452, R01CA133881, and U01CA097452; Z.A.: R01 HL126797; B.K.: R01 HL118018 and K23-HL095661; J.G.S. and C.E.S.: 5R01HL080494, R01HL084553), and the Howard Hughes Medical Institute (C.E.S.). The Universitario Puerta de Hierro and Virgen de la Arrixaca Hospitals are members of the European Reference Network on Rare and Complex Diseases of the Heart (Guard-Heart; http://guard-heart.ern-net.eu). This publication includes independent research commissioned by the Health Innovation Challenge Fund (HICF), a parallel funding partnership between the Department of Health and Wellcome Trust. The Centro Nacional de Investigaciones Cardiovasculares (CNIC) is supported by the Ministry of Economy, Industry and Competitiveness and the Pro CNIC Foundation, and is a Severo Ochoa Center of Excellence (SEV-2015-0505). Grants from ISCIII and the Spanish Ministry of Economy and Competitiveness are supported by the Plan Estatal de I+D+I 2013-2016 – European Regional Development Fund (FEDER) “A way of making Europe”.S

Disease-specific variant pathogenicity prediction significantly improves variant interpretation in inherited cardiac conditions

Funder: Science and Technology Development Fund; doi: https://doi.org/10.13039/Funder: Al-Alfi FoundationFunder: Magdi Yacoub Heart FoundationFunder: Rosetrees and Stoneygate Imperial College Research FellowshipFunder: National Health and Medical Research Council (Australia)Abstract: Purpose: Accurate discrimination of benign and pathogenic rare variation remains a priority for clinical genome interpretation. State-of-the-art machine learning variant prioritization tools are imprecise and ignore important parameters defining gene–disease relationships, e.g., distinct consequences of gain-of-function versus loss-of-function variants. We hypothesized that incorporating disease-specific information would improve tool performance. Methods: We developed a disease-specific variant classifier, CardioBoost, that estimates the probability of pathogenicity for rare missense variants in inherited cardiomyopathies and arrhythmias. We assessed CardioBoost’s ability to discriminate known pathogenic from benign variants, prioritize disease-associated variants, and stratify patient outcomes. Results: CardioBoost has high global discrimination accuracy (precision recall area under the curve [AUC] 0.91 for cardiomyopathies; 0.96 for arrhythmias), outperforming existing tools (4–24% improvement). CardioBoost obtains excellent accuracy (cardiomyopathies 90.2%; arrhythmias 91.9%) for variants classified with >90% confidence, and increases the proportion of variants classified with high confidence more than twofold compared with existing tools. Variants classified as disease-causing are associated with both disease status and clinical severity, including a 21% increased risk (95% confidence interval [CI] 11–29%) of severe adverse outcomes by age 60 in patients with hypertrophic cardiomyopathy. Conclusions: A disease-specific variant classifier outperforms state-of-the-art genome-wide tools for rare missense variants in inherited cardiac conditions (https://www.cardiodb.org/cardioboost/), highlighting broad opportunities for improved pathogenicity prediction through disease specificity

Disease-specific variant pathogenicity prediction significantly improves variant interpretation in inherited cardiac conditions

Funder: Science and Technology Development Fund; doi: https://doi.org/10.13039/Funder: Al-Alfi FoundationFunder: Magdi Yacoub Heart FoundationFunder: Rosetrees and Stoneygate Imperial College Research FellowshipFunder: National Health and Medical Research Council (Australia)Abstract: Purpose: Accurate discrimination of benign and pathogenic rare variation remains a priority for clinical genome interpretation. State-of-the-art machine learning variant prioritization tools are imprecise and ignore important parameters defining gene–disease relationships, e.g., distinct consequences of gain-of-function versus loss-of-function variants. We hypothesized that incorporating disease-specific information would improve tool performance. Methods: We developed a disease-specific variant classifier, CardioBoost, that estimates the probability of pathogenicity for rare missense variants in inherited cardiomyopathies and arrhythmias. We assessed CardioBoost’s ability to discriminate known pathogenic from benign variants, prioritize disease-associated variants, and stratify patient outcomes. Results: CardioBoost has high global discrimination accuracy (precision recall area under the curve [AUC] 0.91 for cardiomyopathies; 0.96 for arrhythmias), outperforming existing tools (4–24% improvement). CardioBoost obtains excellent accuracy (cardiomyopathies 90.2%; arrhythmias 91.9%) for variants classified with >90% confidence, and increases the proportion of variants classified with high confidence more than twofold compared with existing tools. Variants classified as disease-causing are associated with both disease status and clinical severity, including a 21% increased risk (95% confidence interval [CI] 11–29%) of severe adverse outcomes by age 60 in patients with hypertrophic cardiomyopathy. Conclusions: A disease-specific variant classifier outperforms state-of-the-art genome-wide tools for rare missense variants in inherited cardiac conditions (https://www.cardiodb.org/cardioboost/), highlighting broad opportunities for improved pathogenicity prediction through disease specificity

Shared genetic predisposition in peripartum and dilated cardiomyopathies

Background: Peripartum cardiomyopathy shares some clinical features with idiopathic dilated cardiomyopathy, a disorder caused by mutations in more than 40 genes, including TTN, which encodes the sarcomere protein titin. Methods: In 172 women with peripartum cardiomyopathy, we sequenced 43 genes with variants that have been associated with dilated cardiomyopathy. We compared the prevalence of different variant types (nonsense, frameshift, and splicing) in these women with the prevalence of such variants in persons with dilated cardiomyopathy and with population controls. Results: We identified 26 distinct, rare truncating variants in eight genes among women with peripartum cardiomyopathy. The prevalence of truncating variants (26 in 172 [15%]) was significantly higher than that in a reference population of 60,706 persons (4.7%, P=1.3×10(-7)) but was similar to that in a cohort of patients with dilated cardiomyopathy (55 of 332 patients [17%], P=0.81). Two thirds of identified truncating variants were in TTN, as seen in 10% of the patients and in 1.4% of the reference population (P=2.7×10(-10)); almost all TTN variants were located in the titin A-band. Seven of the TTN truncating variants were previously reported in patients with idiopathic dilated cardiomyopathy. In a clinically well-characterized cohort of 83 women with peripartum cardiomyopathy, the presence of TTN truncating variants was significantly correlated with a lower ejection fraction at 1-year follow-up (P=0.005). Conclusions: The distribution of truncating variants in a large series of women with peripartum cardiomyopathy was remarkably similar to that found in patients with idiopathic dilated cardiomyopathy. TTN truncating variants were the most prevalent genetic predisposition in each disorder

Genetic distance between the JC virus sequences of each brain sample and MAD-1 sequence.

<p>The figure illustrates the genetic divergence between the JC virus sequences found in each PML brain and MAD-1 (red bar), the JC virus prototype sequence associated with PML. Each chord corresponds to a single nucleotide polymorphism. The presence of multiple JCV variants within each PML brain accounts for a remarkable degree of genetic variation and suggests that the genetic complexity of JC virus in the brain compartment has previously been underestimated.</p

A Nationwide Study on Hypertrophic Cardiomyopathy in Iceland: Evidence of a MYBPC3 Founder Mutation.

To access publisher's full text version of this article click on the hyperlink at the bottom of the page-The geographic isolation and homogeneous population of Iceland is ideally suited to ascertain clinical and genetic characteristics of hypertrophic cardiomyopathy (HCM) at the population level.-Medical records and cardiac imaging studies obtained between 1997 and 2010 were reviewed to identify Icelandic patients with HCM. Surviving patients were recruited for clinical and genetic studies. A previously identified Icelandic mutation, MYBPC3 c.927-2A>G, was genotyped, and mutation-negative samples were sequenced for HCM genes and other hypertrophic genes. Record review identified 180 HCM patients. Genetic analyses of 151 patients defined pathogenic mutations in 101 (67%), including MYBPC3 c.927-2A>G (88 patients; 58%), 4 other MYBPC3 or MYH7 mutations (5 patients; 3.3%), and 2 GLA mutations (8 patients; 5.3%). Haplotype and genetic genealogical data defined MYBPC3 c.927-2A>G as a founder mutation, introduced into the Icelandic population in the 15(th) century, with a current population prevalence of 0.36%. MYBPC3 c.927-2A>G mutation carriers exhibited phenotypic diversity but were younger at diagnosis (42 vs. 49 years, p=0.001) and sustained more adverse events (15% vs. 2%, p=0.02) than mutation-negative patients. All-cause mortality for HCM patients was similar to an age-matched Icelandic population (Hazard Ratio 0.98, p=0.9). HCM-related mortality (0.78%/year) occurred at a mean age of 68 compared to 81 years for non-HCM related mortality (p=0.02).-A founder MYBPC3 mutation that arose over 550 years ago is the predominant cause of HCM in Iceland. The MYBPC3 c.927-2A>G mutation is associated with low adverse event rates but earlier cardiovascular mortality, illustrating the impact of genotype on outcomes in HCM.Akureyri Hospital Research Fund (G.G.), Landspitali – The National University Hospital of Iceland (Research Fund project A-2013-011; B.A.), the National Institutes of Health (C.E.S. and J.G.S; HL084553), the Fondation Leducq (C.E.S. and J.G.S.; 11CVD01), the Howard Hughes Medical Institute (C.E.S.) and the LaDue Foundation (M.B.

Multiple JC virus variants within the same PML brain sample.

<p>Visual inspection of the JC virus 75 base-pair nucleotide reads reveals multiple single nucleotide polymorphisms (SNP). Each read is represented by a single horizontal arrow. SNPs in positions 3,122, 3,178 and 3,185 of the JC virus genome occur independently, which is consistent with the presence of at least three distinct viral variants in the same PML brain.</p