Matthew T Wheeler

Stanford University, Palo Alto, California, United States

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Publications (31)371.25 Total impact

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    Journal of the American College of Cardiology 06/2015; 65(22). DOI:10.1016/j.jacc.2015.03.559 · 15.34 Impact Factor
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    ABSTRACT: To examine the prevalence of athletes who screen positive with the preparticipation examination guidelines from the American Heart Association, the AHA 12-elements, in combination with 3 screening electrocardiogram (ECG) criteria. Observational cross-sectional study. Stanford University Sports Medicine Clinic. Total of 1596 participants, including 297 (167 male; mean age, 16.2 years) high school athletes, 1016 (541 male; mean age, 18.8 years) collegiate athletes, and 283 (mean age, 26.3 years) male professional athletes. Athletes were screened using the 8 personal and family history questions from the AHA 12-elements. Electrocardiograms were obtained for all participants and interpreted using Seattle criteria, Stanford criteria, and European Society of Cardiology (ESC) recommendations. Approximately one-quarter of all athletes (23.8%) had at least 1 positive response to the AHA personal and family history elements. High school and college athletes had similar rates of having at least 1 positive response (25.9% vs 27.4%), whereas professional athletes had a significantly lower rate of having at least 1 positive response (8.8%, P < 0.05). Females reported more episodes of unexplained syncope (11.4% vs 7.5%, P = 0.017) and excessive exertional dyspnea with exercise (11.1% vs 6.1%, P = 0.001) than males. High school athletes had more positive responses to the family history elements when compared with college athletes (P < 0.05). The percentage of athletes who had an abnormal ECG varied between Seattle criteria (6.0%), Stanford criteria (8.8%), and ESC recommendations (26.8%). Many athletes screen positive under current screening recommendations, and ECG results vary widely by interpretation criteria. In a patient population without any adverse cardiovascular events, the currently recommended AHA 12-elements have an unacceptably high rate of false positives. Newer screening guidelines are needed, with fewer false positives and evidence-based updates.
    Clinical journal of sport medicine: official journal of the Canadian Academy of Sport Medicine 04/2015; DOI:10.1097/JSM.0000000000000203 · 2.01 Impact Factor
  • The Journal of Heart and Lung Transplantation 04/2015; 34(4):S186. DOI:10.1016/j.healun.2015.01.509 · 5.61 Impact Factor
  • Journal of the American College of Cardiology 03/2015; 65(10):A1408. DOI:10.1016/S0735-1097(15)61408-5 · 15.34 Impact Factor
  • Matthew T Wheeler, Euan A Ashley
    Journal of the American College of Cardiology 02/2015; 65(6):570-572. DOI:10.1016/j.jacc.2014.12.004 · 15.34 Impact Factor
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    ABSTRACT: There is controversy regarding Q wave criteria for assessing risk for hypertrophic cardiomyopathy (HCM) in young athletes. The 12-lead ECGs from Preparticipation screening in healthy athletes and patients with HCM were studied retrospectively. All 12 leads were measured using the same automated ECG analysis program. There were a total of 225 HCM patients and 1124 athletes with 12-lead electrocardiograms available for analysis. Athletes were on average 20years of age, 65% were male and 24% were African-American. Patients with HCM were on average 51years of age, 56% were male and 5.8% were African-American. Q waves by either amplitude, duration or area criteria were more prevalent in males than females, in lateral leads than inferior and in HCM patients than athletes. The most striking difference in Q waves between the groups was in Limb lead I and in the females. Tall, skinny Q waves were rare in athletes and had the highest prevalence of only 3.7% in male HCM patients. Q waves are more common in males compared to females and in patients with HCM compared to athletes. Q waves of 30ms or more in limb lead I appear to offer the greatest discriminatory value for separating patients with HCM from athletes. Copyright © 2015 Elsevier Inc. All rights reserved.
    Journal of Electrocardiology 02/2015; DOI:10.1016/j.jelectrocard.2015.01.009 · 1.36 Impact Factor
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    ABSTRACT: Current guidelines for interpretation of the ECGs of athletes recommend that isolated R and S wave amplitudes that exceed traditional criteria for left ventricular hypertrophy be accepted as a physiological response to exercise training. This is based on training and echocardiographic studies but not on long term follow up. Demonstration of the prognostic characteristics of the amplitude criteria in a non-athletic population could support the current guidelines. To evaluate the prognostic value of the R and S wave voltage criteria for electrocardiographic left ventricular hypertrophy (ECG-LVH) in an ambulatory clinical population. The target population consisted of 20,903 ambulatory subjects who had ECGs recorded between 1987 and 1999 and were followed for cardiovascular death until 2013. During the mean follow up of 17years, there were 881 cardiovascular deaths. The mean age was 43±10, 91% were male and 16% were African American. Of the 2482 (12%) subjects who met the Sokolow-Lyon criteria, 241 (1.2%) subjects with left ventricular (LV) strain had an HR of 5.4 (95% CI 4.1-7.2, p<0.001), while 2241 (11%) subjects without strain had an HR of 1.4 (95% CI 1.2-1.8, p<0.001). Of the 4836 (23%) subjects who met the Framingham voltage criteria, 350 (2%) subjects with LV strain had an HR of 5.1 (95% CI 4.0-6.5, p<0.001), while 4486 (22%) subjects without strain had an HR of 1.1 (95% CI 0.9-1.3, p=0.26). The individual components of the Romhilt-Estes had HRs ranging from 1.4 to 3.6, with only the voltage component not being significant (HR 1.1, 95% CI 0.9-1.5, p=0.35). This study demonstrates that the R and S wave voltage criteria components of most of the original classification schema for electrocardiographic left ventricular hypertrophy are not predictive of CV mortality. Our findings support the current guidelines for electrocardiographic screening of athletes. Copyright © 2014 Elsevier Inc. All rights reserved.
    Journal of Electrocardiology 12/2014; 48(3). DOI:10.1016/j.jelectrocard.2014.12.012 · 1.36 Impact Factor
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    ABSTRACT: Regular exercise and a physically active lifestyle have favorable effects on health. Several issues related to this theme are addressed in this report. A comment on the requirements of personalized exercise medicine and in-depth biological profiling along with the opportunities that they offer is presented. This is followed by a brief overview of the evidence for the contributions of genetic differences to the ability to benefit from regular exercise. Subsequently, studies showing that mutations in TP53 influence exercise capacity in mice and humans are succinctly described. The evidence for effects of exercise on endothelial function in health and disease also is covered. Finally, changes in cardiac and skeletal muscle in response to exercise and their implications for patients with cardiac disease are summarized. Innovative research strategies are needed to define the molecular mechanisms involved in adaptation to exercise and to translate them into useful clinical and public health applications.
    Progress in Cardiovascular Diseases 08/2014; 57(4). DOI:10.1016/j.pcad.2014.08.005 · 2.44 Impact Factor
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    ABSTRACT: Whole-genome sequencing (WGS) is increasingly applied in clinical medicine and is expected to uncover clinically significant findings regardless of sequencing indication. To examine coverage and concordance of clinically relevant genetic variation provided by WGS technologies; to quantitate inherited disease risk and pharmacogenomic findings in WGS data and resources required for their discovery and interpretation; and to evaluate clinical action prompted by WGS findings. An exploratory study of 12 adult participants recruited at Stanford University Medical Center who underwent WGS between November 2011 and March 2012. A multidisciplinary team reviewed all potentially reportable genetic findings. Five physicians proposed initial clinical follow-up based on the genetic findings. Genome coverage and sequencing platform concordance in different categories of genetic disease risk, person-hours spent curating candidate disease-risk variants, interpretation agreement between trained curators and disease genetics databases, burden of inherited disease risk and pharmacogenomic findings, and burden and interrater agreement of proposed clinical follow-up. Depending on sequencing platform, 10% to 19% of inherited disease genes were not covered to accepted standards for single nucleotide variant discovery. Genotype concordance was high for previously described single nucleotide genetic variants (99%-100%) but low for small insertion/deletion variants (53%-59%). Curation of 90 to 127 genetic variants in each participant required a median of 54 minutes (range, 5-223 minutes) per genetic variant, resulted in moderate classification agreement between professionals (Gross κ, 0.52; 95% CI, 0.40-0.64), and reclassified 69% of genetic variants cataloged as disease causing in mutation databases to variants of uncertain or lesser significance. Two to 6 personal disease-risk findings were discovered in each participant, including 1 frameshift deletion in the BRCA1 gene implicated in hereditary breast and ovarian cancer. Physician review of sequencing findings prompted consideration of a median of 1 to 3 initial diagnostic tests and referrals per participant, with fair interrater agreement about the suitability of WGS findings for clinical follow-up (Fleiss κ, 0.24; P < 001). In this exploratory study of 12 volunteer adults, the use of WGS was associated with incomplete coverage of inherited disease genes, low reproducibility of detection of genetic variation with the highest potential clinical effects, and uncertainty about clinically reportable findings. In certain cases, WGS will identify clinically actionable genetic variants warranting early medical intervention. These issues should be considered when determining the role of WGS in clinical medicine.
    JAMA The Journal of the American Medical Association 03/2014; 311(10):1035-45. DOI:10.1001/jama.2014.1717 · 30.39 Impact Factor
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    ABSTRACT: The clinical expression of hypertrophic cardiomyopathy (HC) is undoubtedly influenced by modifying genetic and environmental factors. Lifestyle practices such as tobacco and alcohol use, poor nutritional intake, and physical inactivity are strongly associated with adverse cardiovascular outcomes and increased mortality in the general population. Before addressing the direct effect of such modifiable factors on the natural history of HC, it is critical to define their prevalence in this population. A voluntary survey, drawing questions in part from the 2007 to 2008 National Health and Nutrition Examination Survey (NHANES), was posted on the HC Association website and administered to patients with HC at the University of Michigan. Propensity score matching to NHANES participants was used. Dichotomous and continuous health behaviors were analyzed using logistic and linear regression, respectively, and adjusted for body mass index and propensity score quintile. Compared to the matched NHANES participants, the patients with HC reported significantly less alcohol and tobacco use but also less time engaged in physical activity at work and for leisure. Time spent participating in vigorous or moderate activity was a strong predictor of self-reported exercise capacity. The body mass index was greater in the HC cohort than in the NHANES cohort. Exercise restrictions negatively affected emotional well-being in most surveyed subjects. In conclusion, patients with HC are less active than the general United States population. The well-established relation of inactivity, obesity, and cardiovascular mortality might be exaggerated in patients with HC. More data are needed on exercise in those with HC to strike a balance between acute risks and the long-term health benefits of exercise.
    The American journal of cardiology 01/2013; 111(7). DOI:10.1016/j.amjcard.2012.12.018 · 3.43 Impact Factor
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    ABSTRACT: Familial hypertrophic cardiomyopathy (HCM) is a prevalent hereditary cardiac disorder linked to arrhythmia and sudden cardiac death. While the causes of HCM have been identified as genetic mutations in the cardiac sarcomere, the pathways by which sarcomeric mutations engender myocyte hypertrophy and electrophysiological abnormalities are not understood. To elucidate the mechanisms underlying HCM development, we generated patient-specific induced pluripotent stem cell cardiomyocytes (iPSC-CMs) from a ten-member family cohort carrying a hereditary HCM missense mutation (Arg663His) in the MYH7 gene. Diseased iPSC-CMs recapitulated numerous aspects of the HCM phenotype including cellular enlargement and contractile arrhythmia at the single-cell level. Calcium (Ca(2+)) imaging indicated dysregulation of Ca(2+) cycling and elevation in intracellular Ca(2+) ([Ca(2+)](i)) are central mechanisms for disease pathogenesis. Pharmacological restoration of Ca(2+) homeostasis prevented development of hypertrophy and electrophysiological irregularities. We anticipate that these findings will help elucidate the mechanisms underlying HCM development and identify novel therapies for the disease.
    Cell stem cell 01/2013; 12(1):101-13. DOI:10.1016/j.stem.2012.10.010 · 22.15 Impact Factor
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    ABSTRACT: Rapid advances in DNA sequencing promise to enable new diagnostics and individualized therapies. Achieving personalized medicine, however, will require extensive research on highly reidentifiable, integrated datasets of genomic and health information. To assist with this, participants in the Personal Genome Project choose to forgo privacy via our institutional review board- approved "open consent" process. The contribution of public data and samples facilitates both scientific discovery and standardization of methods. We present our findings after enrollment of more than 1,800 participants, including whole-genome sequencing of 10 pilot participant genomes (the PGP-10). We introduce the Genome-Environment-Trait Evidence (GET-Evidence) system. This tool automatically processes genomes and prioritizes both published and novel variants for interpretation. In the process of reviewing the presumed healthy PGP-10 genomes, we find numerous literature references implying serious disease. Although it is sometimes impossible to rule out a late-onset effect, stringent evidence requirements can address the high rate of incidental findings. To that end we develop a peer production system for recording and organizing variant evaluations according to standard evidence guidelines, creating a public forum for reaching consensus on interpretation of clinically relevant variants. Genome analysis becomes a two-step process: using a prioritized list to record variant evaluations, then automatically sorting reviewed variants using these annotations. Genome data, health and trait information, participant samples, and variant interpretations are all shared in the public domain-we invite others to review our results using our participant samples and contribute to our interpretations. We offer our public resource and methods to further personalized medical research.
    Proceedings of the National Academy of Sciences 07/2012; 109(30):11920-7. DOI:10.1073/pnas.1201904109 · 9.81 Impact Factor
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    Circulation 02/2012; 125(7):931-44. DOI:10.1161/CIRCULATIONAHA.110.972828 · 14.95 Impact Factor
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    ABSTRACT: Whole-genome sequencing harbors unprecedented potential for characterization of individual and family genetic variation. Here, we develop a novel synthetic human reference sequence that is ethnically concordant and use it for the analysis of genomes from a nuclear family with history of familial thrombophilia. We demonstrate that the use of the major allele reference sequence results in improved genotype accuracy for disease-associated variant loci. We infer recombination sites to the lowest median resolution demonstrated to date (< 1,000 base pairs). We use family inheritance state analysis to control sequencing error and inform family-wide haplotype phasing, allowing quantification of genome-wide compound heterozygosity. We develop a sequence-based methodology for Human Leukocyte Antigen typing that contributes to disease risk prediction. Finally, we advance methods for analysis of disease and pharmacogenomic risk across the coding and non-coding genome that incorporate phased variant data. We show these methods are capable of identifying multigenic risk for inherited thrombophilia and informing the appropriate pharmacological therapy. These ethnicity-specific, family-based approaches to interpretation of genetic variation are emblematic of the next generation of genetic risk assessment using whole-genome sequencing.
    PLoS Genetics 09/2011; 7(9):e1002280. DOI:10.1371/journal.pgen.1002280 · 8.17 Impact Factor
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    Circulation 08/2011; 124(6):746-57. DOI:10.1161/CIRCULATIONAHA.110.013078 · 14.95 Impact Factor
  • Frederick E Dewey, Matthew T Wheeler, Euan A Ashley
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    ABSTRACT: Heart failure remains a leading cause of morbidity and mortality in developed nations. Our current understanding of molecular pathways involved in heart failure reveals little of the multiscale biological systems at work. Here we consider recent advances in understanding the integrative multiscale biology, or systems biology, of heart failure and present a framework for future work in the area. Multiplexed assays of gene expression and the complex dynamics of protein-protein interactions in heart failure have illuminated key pathways important to myocardial adaptation. Modeling of complex systems has advanced to incorporate these dynamic data sources into networks that capture fundamental interactions on different biological scales. The complex syndrome of heart failure, like other complex disease syndromes, can be viewed as an emergent property of these multiscale systems. A comprehensive understanding of adaptive mechanisms in heart failure requires integration of multiple data sources on several biological scales. A combination of holistic systems biology approaches and traditional reductionist experimentation will be required for a nuanced understanding of this multifaceted disease process.
    Current opinion in cardiology 07/2011; 26(4):314-21. DOI:10.1097/HCO.0b013e328346597d · 2.59 Impact Factor
  • Journal of the American College of Cardiology 04/2011; 57(14). DOI:10.1016/S0735-1097(11)62041-X · 15.34 Impact Factor
  • Journal of the American College of Cardiology 04/2011; 57(14). DOI:10.1016/S0735-1097(11)61159-5 · 15.34 Impact Factor
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    ABSTRACT: Network analysis techniques allow a more accurate reflection of underlying systems biology to be realized than traditional unidimensional molecular biology approaches. Using gene coexpression network analysis, we define the gene expression network topology of cardiac hypertrophy and failure and the extent of recapitulation of fetal gene expression programs in failing and hypertrophied adult myocardium. We assembled all myocardial transcript data in the Gene Expression Omnibus (n=1617). Because hierarchical analysis revealed species had primacy over disease clustering, we focused this analysis on the most complete (murine) dataset (n=478). Using gene coexpression network analysis, we derived functional modules, regulatory mediators, and higher-order topological relationships between genes and identified 50 gene coexpression modules in developing myocardium that were not present in normal adult tissue. We found that known gene expression markers of myocardial adaptation were members of upregulated modules but not hub genes. We identified ZIC2 as a novel transcription factor associated with coexpression modules common to developing and failing myocardium. Of 50 fetal gene coexpression modules, 3 (6%) were reproduced in hypertrophied myocardium and 7 (14%) were reproduced in failing myocardium. One fetal module was common to both failing and hypertrophied myocardium. Network modeling allows systems analysis of cardiovascular development and disease. Although we did not find evidence for a global coordinated program of fetal gene expression in adult myocardial adaptation, our analysis revealed specific gene expression modules active during both development and disease and specific candidates for their regulation.
    Circulation Cardiovascular Genetics 02/2011; 4(1):26-35. DOI:10.1161/CIRCGENETICS.110.941757 · 5.34 Impact Factor

Publication Stats

1k Citations
371.25 Total Impact Points

Institutions

  • 2008–2015
    • Stanford University
      • • Stanford Center for Inherited Cardiovascular Disease
      • • Division of Cardiovascular Medicine
      • • Department of Medicine
      Palo Alto, California, United States
  • 2009–2014
    • Stanford Medicine
      • Division of Cardiovascular Medicine
      Stanford, California, United States
  • 2010
    • Harvard Medical School
      • Department of Genetics
      Boston, Massachusetts, United States