Recent Publications

Jason D Merker, Aaron M Wenger, Tam Sneddon, Megan Grove, Zachary Zappala, Laure Fresard, Daryl Waggott, Sowmi Utiramerur, Yanli Hou, Kevin S Smith, Stephen B Montgomery, Matthew Wheeler, Jillian G Buchan, Christine C Lambert, Kevin S Eng, Luke Hickey, Jonas Korlach, James Ford & Euan A Ashley

2017 Jun 22 (epub ahead of print)

ABSTRACT PurposeCurrent clinical genomics assays primarily utilize short-read sequencing (SRS), but SRS has limited ability to evaluate repetitive regions and structural variants. Long-read sequencing (LRS) has complementary strengths, and we aimed to determine whether LRS could offer a means to identify overlooked genetic variation in patients undiagnosed by SRS.MethodsWe performed low-coverage genome LRS to identify structural variants in a patient who presented with multiple neoplasia and cardiac myxomata, in whom the results of targeted clinical testing and genome SRS were negative.ResultsThis LRS approach yielded 6,971 deletions and 6,821 insertions > 50 bp. Filtering for variants that are absent in an unrelated control and overlap a disease gene coding exon identified three deletions and three insertions. One of these, a heterozygous 2,184 bp deletion, overlaps the first coding exon of PRKAR1A, which is implicated in autosomal dominant Carney complex. RNA sequencing demonstrated decreased PRKAR1A expression. The deletion was classified as pathogenic based on guidelines for interpretation of sequence variants.ConclusionThis first successful application of genome LRS to identify a pathogenic variant in a patient suggests that LRS has significant potential for the identification of disease-causing structural variation.

Christine Grady, R.N., Ph.D., Steven R. Cummings, M.D., Michael C. Rowbotham, M.D., Michael V. McConnell, M.D., M.S.E.E., Euan A. Ashley, F.R.C.P., D.Phil., and Gagandeep Kang, M.D., Ph.D.

2017; 376: 856-867

ABSTRACT This multipart review provides an overview of innovative approaches to improving and expanding the informed consent process for researchers and participants, along with short essays covering specific areas of innovation.

Michael V. McConnell, MD, MSEE; Anna Shcherbina, MEng; Aleksandra Pavlovic, BS; Julian R. Homburger, BS; Rachel L. Goldfeder, MS; Daryl Waggot, MSc; Mildred K. Cho, PhD; Mary E. Rosenberger, PhD; William L. Haskell, PhD; Jonathan Myers, PhD; Mary Ann Champagne, RN, MS; Emmanuel Mignot, MD, PhD; Martin Landray, MB, ChB, PhD; Lionel Tarassenko, MA, DPhil; Robert A. Harrington, MD; Alan C. Yeung, MD; Euan A. Ashley, MB, ChB, DPhil

2017; 2(1): 67-76

ABSTRACT Studies have established the importance of physical activity and fitness, yet limited data exist on the associations between objective, real-world physical activity patterns, fitness, sleep, and cardiovascular health.

Shcherbina, A., Mattsson, C. M., Waggott, D., Salisbury, H., Christle, J. W., Hastie, T., Wheeler, M. T., Ashley, E. A.

2017; 7 (2)

ABSTRACT The ability to measure physical activity through wrist-worn devices provides an opportunity for cardiovascular medicine. However, the accuracy of commercial devices is largely unknown. The aim of this work is to assess the accuracy of seven commercially available wrist-worn devices in estimating heart rate (HR) and energy expenditure (EE) and to propose a wearable sensor evaluation framework. We evaluated the Apple Watch, Basis Peak, Fitbit Surge, Microsoft Band, Mio Alpha 2, PulseOn, and Samsung Gear S2. Participants wore devices while being simultaneously assessed with continuous telemetry and indirect calorimetry while sitting, walking, running, and cycling. Sixty volunteers (29 male, 31 female, age 38 ± 11 years) of diverse age, height, weight, skin tone, and fitness level were selected. Error in HR and EE was computed for each subject/device/activity combination. Devices reported the lowest error for cycling and the highest for walking. Device error was higher for males, greater body mass index, darker skin tone, and walking. Six of the devices achieved a median error for HR below 5% during cycling. No device achieved an error in EE below 20 percent. The Apple Watch achieved the lowest overall error in both HR and EE, while the Samsung Gear S2 reported the highest. In conclusion, most wrist-worn devices adequately measure HR in laboratory-based activities, but poorly estimate EE, suggesting caution in the use of EE measurements as part of health improvement programs. We propose reference standards for the validation of consumer health devices (http://precision.stanford.edu/).

Sara Saberi, MD, MS; Matthew Wheeler, MD, PhD; Jennifer Bragg-Gresham, MS, PhD; Whitney Hornsby, PhD; Prachi P. Agarwal, MD, MS; Anil Attili, MD; Maryann Concannon, MSW; Annika M. Dries, BA; Yael Shmargad, BS; Heidi Salisbury, RN, MSN, CNS; Suwen Kumar, MBBS; Jonathan J. Herrera, MS; Jonathan Myers, PhD; Adam S. Helms, MD, MS; Euan A. Ashley, FRCP, DPhil; Sharlene M. Day, MD

2017;317(13):1349-1357

ABSTRACT Importance: Formulating exercise recommendations for patients with hypertrophic cardiomyopathy is challenging because of concern about triggering ventricular arrhythmias and because a clinical benefit has not been previously established in this population. Objective: To determine whether moderate-intensity exercise training improves exercise capacity in adults with hypertrophic cardiomyopathy. Design, Setting, and Participants: A randomized clinical trial involving 136 patients with hypertrophic cardiomyopathy was conducted between April 2010 and October 2015 at 2 academic medical centers in the United States (University of Michigan Health System and Stanford University Medical Center). Date of last follow-up was November 2016. Interventions: Participants were randomly assigned to 16 weeks of moderate-intensity exercise training (n = 67) or usual activity (n = 69). Main Outcomes and Measures: The primary outcome measure was change in peak oxygen consumption from baseline to 16 weeks. Results: Among the 136 randomized participants (mean age, 50.4 [SD, 13.3] years; 42% women), 113 (83%) completed the study. At 16 weeks, the change in mean peak oxygen consumption was +1.35 (95% CI, 0.50 to 2.21) mL/kg/min among participants in the exercise training group and +0.08 (95% CI, −0.62 to 0.79) mL/kg/min among participants in the usual-activity group (between-group difference, 1.27 [95% CI, 0.17 to 2.37]; P = .02). There were no occurrences of sustained ventricular arrhythmia, sudden cardiac arrest, appropriate defibrillator shock, or death in either group. Conclusions and Relevance: In this preliminary study involving patients with hypertrophic cardiomyopathy, moderate-intensity exercise compared with usual activity resulted in a statistically significant but small increase in exercise capacity at 16 weeks. Further research is needed to understand the clinical importance of this finding in patients with hypertrophic cardiomyopathy, as well as the long-term safety of exercise at moderate and higher levels of intensity.

Priest, J. R., Gawad, C., Kahlig, K. M., Yu, J. K., O'Hara, T., Boyle, P. M., Rajamani, S., Clark, M. J., Garcia, S. T., Ceresnak, S., Harris, J., Boyle, S., Dewey, F. E., Malloy-Walton, L., Dunn, K., Grove, M., Perez, M. V., Neff, N. F., Chen, R., Maeda, K., Dubin, A., Belardinelli, L., West, J., Antolik, C., Macaya, D., Quertermous, T., Trayanova, N. A., Quake, S. R., Ashley, E. A.

2016; 113 (41): 11555-11560

ABSTRACT Somatic mosaicism, the occurrence and propagation of genetic variation in cell lineages after fertilization, is increasingly recognized to play a causal role in a variety of human diseases. We investigated the case of life-threatening arrhythmia in a 10-day-old infant with long QT syndrome (LQTS). Rapid genome sequencing suggested a variant in the sodium channel NaV1.5 encoded by SCN5A, NM_000335:c.5284G > T predicting p.(V1762L), but read depth was insufficient to be diagnostic. Exome sequencing of the trio confirmed read ratios inconsistent with Mendelian inheritance only in the proband. Genotyping of single circulating leukocytes demonstrated the mutation in the genomes of 8% of patient cells, and RNA sequencing of cardiac tissue from the infant confirmed the expression of the mutant allele at mosaic ratios. Heterologous expression of the mutant channel revealed significantly delayed sodium current with a dominant negative effect. To investigate the mechanism by which mosaicism might cause arrhythmia, we built a finite element simulation model incorporating Purkinje fiber activation. This model confirmed the pathogenic consequences of cardiac cellular mosaicism and, under the presenting conditions of this case, recapitulated 2:1 AV block and arrhythmia. To investigate the extent to which mosaicism might explain undiagnosed arrhythmia, we studied 7,500 affected probands undergoing commercial gene-panel testing. Four individuals with pathogenic variants arising from early somatic mutation events were found. Here we establish cardiac mosaicism as a causal mechanism for LQTS and present methods by which the general phenomenon, likely to be relevant for all genetic diseases, can be detected through single-cell analysis and next-generation sequencing.

Ashley, E. A.

2016; 17 (9): 507-522

ABSTRACT There is great potential for genome sequencing to enhance patient care through improved diagnostic sensitivity and more precise therapeutic targeting. To maximize this potential, genomics strategies that have been developed for genetic discovery - including DNA-sequencing technologies and analysis algorithms - need to be adapted to fit clinical needs. This will require the optimization of alignment algorithms, attention to quality-coverage metrics, tailored solutions for paralogous or low-complexity areas of the genome, and the adoption of consensus standards for variant calling and interpretation. Global sharing of this more accurate genotypic and phenotypic data will accelerate the determination of causality for novel genes or variants. Thus, a deeper understanding of disease will be realized that will allow its targeting with much greater therapeutic precision.

Homburger, J. R., Green, E. M., Caleshu, C., Sunitha, M. S., Taylor, R. E., Ruppel, K. M., Metpally, R. P., Colan, S. D., Michels, M., Day, S. M., Olivotto, I., Bustamante, C. D., Dewey, F. E., Ho, C. Y., Spudich, J. A., Ashley, E. A.

2016; 113 (24): 6701-6706

ABSTRACT Myosin motors are the fundamental force-generating elements of muscle contraction. Variation in the human β-cardiac myosin heavy chain gene (MYH7) can lead to hypertrophic cardiomyopathy (HCM), a heritable disease characterized by cardiac hypertrophy, heart failure, and sudden cardiac death. How specific myosin variants alter motor function or clinical expression of disease remains incompletely understood. Here, we combine structural models of myosin from multiple stages of its chemomechanical cycle, exome sequencing data from two population cohorts of 60,706 and 42,930 individuals, and genetic and phenotypic data from 2,913 patients with HCM to identify regions of disease enrichment within β-cardiac myosin. We first developed computational models of the human β-cardiac myosin protein before and after the myosin power stroke. Then, using a spatial scan statistic modified to analyze genetic variation in protein 3D space, we found significant enrichment of disease-associated variants in the converter, a kinetic domain that transduces force from the catalytic domain to the lever arm to accomplish the power stroke. Focusing our analysis on surface-exposed residues, we identified a larger region significantly enriched for disease-associated variants that contains both the converter domain and residues on a single flat surface on the myosin head described as the myosin mesa. Notably, patients with HCM with variants in the enriched regions have earlier disease onset than patients who have HCM with variants elsewhere. Our study provides a model for integrating protein structure, large-scale genetic sequencing, and detailed phenotypic data to reveal insight into time-shifted protein structures and genetic disease.

Priest, J. R., Osoegawa, K., Mohammed, N., Nanda, V., Kundu, R., Schultz, K., Lammer, E. J., Girirajan, S., Scheetz, T., Waggott, D., Haddad, F., Reddy, S., Bernstein, D., Burns, T., Steimle, J. D., Yang, X. H., Moskowitz, I. P., Hurles, M., Lifton, R. P., Nickerson, D., Bamshad, M., Eichler, E. E., Mital, S., Sheffield, V., Quertermous, T., Gelb, B. D., Portman, M., Ashley, E. A.

All Authors

2016; 12 (4)

ABSTRACT Congenital heart disease (CHD) has a complex genetic etiology, and recent studies suggest that high penetrance de novo mutations may account for only a small fraction of disease. In a multi-institutional cohort surveyed by exome sequencing, combining analysis of 987 individuals (discovery cohort of 59 affected trios and 59 control trios, and a replication cohort of 100 affected singletons and 533 unaffected singletons) we observe variation at novel and known loci related to a specific cardiac malformation the atrioventricular septal defect (AVSD). In a primary analysis, by combining developmental coexpression networks with inheritance modeling, we identify a de novo mutation in the DNA binding domain of NR1D2 (p.R175W). We show that p.R175W changes the transcriptional activity of Nr1d2 using an in vitro transactivation model in HUVEC cells. Finally, we demonstrate previously unrecognized cardiovascular malformations in the Nr1d2tm1-Dgen knockout mouse. In secondary analyses we map genetic variation to protein-interaction networks suggesting a role for two collagen genes in AVSD, which we corroborate by burden testing in a second replication cohort of 100 AVSDs and 533 controls (p = 8.37e-08). Finally, we apply a rare-disease inheritance model to identify variation in genes previously associated with CHD (ZFPM2, NSD1, NOTCH1, VCAN, and MYH6), cardiac malformations in mouse models (ADAM17, CHRD, IFT140, PTPRJ, RYR1 and ATE1), and hypomorphic alleles of genes causing syndromic CHD (EHMT1, SRCAP, BBS2, NOTCH2, and KMT2D) in 14 of 59 trios, greatly exceeding variation in control trios without CHD (p = 9.60e-06). In total, 32% of trios carried at least one putatively disease-associated variant across 19 loci,suggesting that inherited and de novo variation across a heterogeneous group of loci may contribute to disease risk.

View details for DOI 10.1371/journal.pgen.1005963

View details for PubMedID 27058611