Opportunities for the Cardiovascular Community in the Precision Medicine Initiative

Shah, Svati H.; Arnett, Donna K.; Houser, Steven R.; Ginsburg, Geoffrey S.; MacRae, Calum A.; Mital, Seema; Loscalzo, Joseph; Hall, Jennifer L.

doi:10.1161/circulationaha.115.019475

Cited by 55 publications

(38 citation statements)

References 12 publications

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“…Movement in this direction has begun with precision medicine initiatives moving forward. 13,18,[36][37][38] Large, dense, dynamic, personalized data clouds, such as the one being generated by the 100K wellness project 39 , is a specific example of a movement towards precision medicine.…”

Section: Accepted M Manuscriptmentioning

confidence: 99%

“…[68][69][70] In fact, the fields of genomics, epigenetics, transcriptomics, proteomics, metabolomics and gut microbiome analyses related to chronic disease risk prediction are continuing to evolve and future discovery will refine the identification of individuals in Stage B with these parameters. 36,71,72 It is important to note the 'omics' are usually thought of as providing a disease signature but they may be even more valuable in the transition from Stage A to Stage B, before there are clear underlying signs of allostatic load and clinical biomarkers of disease. Moreover, the importance of a lower than sex/age predicted level in cardiorespiratory fitness and muscle strength/endurance are important predictors of future chronic disease risk and adverse events.…”

Section: Stage B: the Emergence Of Chronic Disease Signsmentioning

confidence: 99%

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The P4 Health Spectrum – A Predictive, Preventive, Personalized and Participatory Continuum for Promoting Healthspan

Sagner

McNeil

Puska

et al. 2017

Progress in Cardiovascular Diseases

201

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Chronic diseases (i.e., Noncommunicable Diseases), mainly cardiovascular disease, cancer, respiratory diseases and type-2-diabetes, are now the leading cause of death, disability and diminished quality of life on the planet. Moreover, these diseases are also a major financial burden worldwide, significantly impacting the economy of many countries. Healthcare systems and medicine have progressively improved upon the ability to address infectious diseases and react to adverse health events through both surgical interventions and pharmacology; we have become efficient in delivering reactive care (i.e., initiating interventions once an individual is on the verge of or has actually suffered a negative health event). However, with slowly progressing and often 'silent' chronic diseases now being the main cause of illness, healthcare and medicine must evolve into a proactive system, moving away from a merely reactive approach to care. Minimal interactions among the specialists and limited information to the general practitioner and to the individual receiving care lead to a fragmented health approach, non-concerted prescriptions, a scattered follow-up and a suboptimal cost-effectiveness ratio. A new approach in medicine that is predictive, preventive, personalized and participatory, which we label here as "P4" holds great promise to reduce the burden of chronic diseases by harnessing technology and an increasingly better understanding of environment-biology interactions, evidence-based interventions and the underlying mechanisms of chronic diseases. In this concept paper, we propose a 'P4 Health Continuum' model as a framework to promote and facilitate multi-stakeholder collaboration with an orchestrated common language and an integrated care model to increase the healthspan.

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Section: Accepted M Manuscriptmentioning

confidence: 99%

Section: Stage B: the Emergence Of Chronic Disease Signsmentioning

confidence: 99%

The P4 Health Spectrum – A Predictive, Preventive, Personalized and Participatory Continuum for Promoting Healthspan

Sagner

McNeil

Puska

et al. 2017

Progress in Cardiovascular Diseases

201

View full text Add to dashboard Cite

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“…Extremely large sample sizes are needed for additional discoveries, given the distribution of effect sizes observed to date for both common and rare variants, as well as the estimated proportion of the heritability of CAD explained by these variants to date. In the coming years, this need should be fulfilled by megabiobanks involving at least a half-million participants, including, but not limited to, the UK Biobank, the China Kadoorie Biobank, the Million Veteran Program, and the soon-to-beestablished NIH Precision Medicine Initiative cohort (161)(162)(163)(164). Such biobanks will likely also be leveraged to gain a better understanding of the clinical utility of genetic risk scores, and to conduct additional, well-powered MR studies to complement studies published to date.…”

Section: Future Directionsmentioning

confidence: 99%

Genetics: Implications for Prevention and Management of Coronary Artery Disease

Assimes

Roberts

2016

Journal of the American College of Cardiology

103

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An exciting new era has dawned for the prevention and management of CAD utilizing genetic risk variants. The recent identification of over 60 susceptibility loci for coronary artery disease (CAD) confirm not only the importance of established risk factors, but also the existence of many novel causal pathways that are expected to improve our understanding of the genetic basis of CAD and facilitate the development of new therapeutic agents over time. Concurrently, Mendelian randomization studies have provided intriguing insights on the causal relationship between CAD-related traits, and highlight the potential benefits of long-term modifications of risk factors. Lastly, genetic risk scores of CAD may serve not only as prognostic, but also as predictive markers and carry the potential to considerably improve the delivery of established prevention strategies. This review will summarize the evolution and discovery of genetic risk variants for CAD and their current and future clinical applications. Key Words: genetic variation, Mendelian randomization, risk scores, sequencingAbbreviations and Acronyms CAD = coronary artery disease GRS = genetic risk score GWAS = genome-wide association study HDL = high-density lipoprotein LDL = low-density lipoprotein MI = myocardial infarction MR = Mendelian randomization SNP = single-nucleotide polymorphism WES = whole-exome sequencing WGS = whole-genome sequencing 3

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“…However, our estimates of the prevalence of somatic mosaicism are limited to ascertaining early mutation events detectable in blood or saliva; events occurring later in development that are detectable only within cardiac tissue may constitute additional, as yet unmeasured genetic risk for LQTS. More broadly, our findings exemplify how careful scrutiny of WGS data and computational modeling of a single patient may serve as the foundation for new insights into human pathophysiology; such deep explorations will form the heart of precision medicine as applied to cardiovascular disease (39).…”

Section: Discussionmentioning

confidence: 66%

Early somatic mosaicism is a rare cause of long-QT syndrome

Priest

Gawad

Kahlig

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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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 Na V 1.5 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 singlecell analysis and next-generation sequencing.here is growing recognition that somatic mosaicism, i.e., genetic variation within an individual that arises from errors in DNA replication during early development, may play a role in a variety of human diseases other than cancer (1). However, the extent to which cellular heterogeneity contributes to disease is minimally understood. One report suggests that 6.5% of de novo mutations presumed to be germline in origin may instead have arisen from postzygotic mosaic mutation events (2), and recent genetic investigations directly interrogating diseased tissues in brain malformations, breast cancer, and atrial fibrillation have revealed postzygotic causal mutations absent from germline DNA (3-6). Pathogenic mosaic structural variation is also detectable in children with neurodevelopmental disorders (7). However, a consequential category of genetic variation has not been surveyed systematically in clinical or research studies of other human diseases.The pathophysiological basis of long-QT syndrome (LQTS) is prolongation of cardiac ventricular repolarization by acquired factors such as drug exposure or genetic variation in the proteins controlling transmembrane ion-concentration gradients (8, 9); parental gonadal mosaicism is an infrequently described phenomenon in LQTS (10...

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Opportunities for the Cardiovascular Community in the Precision Medicine Initiative

Cited by 55 publications

References 12 publications

The P4 Health Spectrum – A Predictive, Preventive, Personalized and Participatory Continuum for Promoting Healthspan

The P4 Health Spectrum – A Predictive, Preventive, Personalized and Participatory Continuum for Promoting Healthspan

Genetics: Implications for Prevention and Management of Coronary Artery Disease

Early somatic mosaicism is a rare cause of long-QT syndrome

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