Genomic and Precision Medicine

Cardiovascular Disease

Geoffrey S. Ginsburg, Huntington F Willard

• Publisher: Academic Press
• Year: 2017
• Print ISBN: 9780128018125
• eBook ISBN: 9780128018255
• Edition: 3
• Topic: Biological Sciences
• Subtopic: Pharmacology
• Index: Biological Sciences

Genomic and Precision Medicine: Cardiovascular Disease, Third Edition, focuses on the applications of genome discovery on the broad spectrum of cardiovascular disorders. Each chapter is organized for the application of genomics and personalized medicine tools and technologies to a) Risk Assessment and Susceptibility, b) Diagnosis and Prognosis, c) Pharmacogenomics and Precision Therapeutics, and d) Emerging and Future Opportunities in the field.- Presents a comprehensive volume written and edited by cardiovascular genomic specialists- Covers succinct commentary and key learning points that will assist providers with their local needs for the implementation of genomic and personalized medicine into practice- Provides an overview on major opportunities for genomic and personalized medicine in practice- Includes case studies that highlight the practical use of genomics in the management of patients

Chapter 1

Family Health History and Health Risk Assessment For Cardiovascular Disease in Health Care

Lori A. Orlando and Rebekah R. Wu, Center for Applied Genomics and Precision Medicine, Duke University, Durham, NC, United States

Abstract

Health risk assessments (HRAs) have the potential to play a key role in health promotion and disease prevention both at an individual and a population level. While the idea has been around since the 1950s and HRAs are commonly performed in the workplace, they have not been as readily adopted by the US health-care system. Several challenges must be addressed before broader uptake of HRAs in clinical care can occur: (1) usability for providers, (2) usability for patients, (3) quality of patient-entered data, and (4) impact on health outcomes. In this chapter, we describe recent developments in HRA design that are aimed at addressing these issues.

Keywords

Family health history; risk assessment; risk prediction; prevention; patient-entered data

Chapter Outline

Introduction 1

In the Beginning 3

Why Family Health History is Central to HRAs 3

An Implementation Crisis 5

Will Providers Use It? 6

Will the Patients Use It? 10

What About Patient-Entered Data? 11

Does It Make a Difference? 12

Conclusion 13

References 13

Introduction

In the continuum from health to disease, there are several key transition periods. The first is from healthy to presymptomatic, where an individual still feels well and is asymptomatic but has developed a disease. An example of this health state is the beginning of cardiovascular disease when an individual is developing plaque but they are unaware of it. The second is from presymptomatic to disease diagnosis and the third is from diagnosis to disease status, which can be either well controlled or uncontrolled. Health risk assessments (HRAs) are an essential component of the healthy period. Their purpose is to estimate an individual’s risk for developing common chronic diseases (see, e.g., Table 1.1) allowing clinicians to tailor preventive care, screening, and testing to each individual’s level of risk—with the goal of keeping healthy people healthy. Personalized care plans developed with the aid of HRAs balance effectiveness and harms with risk, in a way that maximizes benefit and minimizes harm not only for each individual, but when taken as a whole, for the population as well. Unfortunately, HRAs are not widely used in primary care, where they would be most effective, due to a number of constraints. This chapter discusses how HRAs were developed, their key aspects, and what needs to occur in order to integrate them into primary care settings.

Table 1.1

Examples of Conditions for Which Family Health History-Based Health Risk Assessment is Useful

	Risk Algorithm Based on Family Health History Only	Risk Algorithms Include Family Health History
Hereditary breast and ovarian cancer	×
Hereditary nonpolyposis colon cancer (Lynch syndrome)	×
Familial hypertrophic cardiomyopathy	×
Familial hypercholesterolemia	×
Alpha-1-antitrypsin deficiency	×
Diabetes mellitus type II		×
Abdominal aortic aneurysm		×
Coronary artery disease		×
Hemochromatosis	×
Maturity onset diabetes of the young		×
Osteoporosis		×
Arrhythmogenic right ventricular cardiomyopathy	×
Asthma		×
Melanoma		×
Prostate cancer		×
Age-related macular degeneration		×

In the Beginning

In 1948, Joseph Mountain, the Assistant Surgeon General, initiated the Framingham Heart Study, an innovative longitudinal study arising from the field of epidemiology. The goal, as devised by the director, Thomas Dawber, was to closely follow a group of individuals living in Framingham, Massachusetts, collecting as much data as possible over the course of many years in order to develop a risk prediction model for heart disease [1]. This was the first time the phrase “factor of risk,” more commonly termed risk factor today, was introduced [2]. Despite initial skepticism among both the research and medical communities, the trial was successful beyond expectations and the field of HRA was born. In 2009, when Clay Christensen coined the term “Precision Medicine,” he defined it as precisely predicting a medical outcome by combining a variety of data into rules [3]. By this definition, HRAs are simply the application of precision medicine to those who are healthy.

Today, most HRAs include the following components: data collection (either through a web-based or paper questionnaire), risk calculation, and report of risk results. This last component, the report, may or may not provide guidance about how to manage your risk. Some are exceptionally detailed and even indicate how much your risk can be lowered by initiating one or more recommended preventive actions, while others merely indicate that you are at increased risk for the specified condition. For the first component, data collection, the data collected varies depending upon which conditions are included in the risk assessment, but at a minimum they all include: demographics, lifestyle, personal health history, family health history, and biometrics (such as blood pressure, weight, cholesterol, etc.). Other types of data, such as genetic/genomic and individual preferences, are just now starting to be incorporated into some risk assessment models and have the potential to not only refine the accuracy of risk calculations but to also improve shared decision-making with medical providers [4,5].

Why Family Health History is Central to HRAs

Family health history is an unassuming and often overlooked, but essential data element in HRAs. For many conditions, family health history is the strongest predictor of disease risk and for some, such as hereditary cardiovascular syndromes, it is the only predictor (and thus the only component of the HRA) (see Table 1.1). An example of the impact of family health history on disease risk is type II diabetes, where a first degree relative (parent or child) with the disease increases an individual’s risk from an average of 3.2% to 14.3% [6]. In some cases, excluding a family health history can lead to missing those at highest risk for developing a condition. For example, many risk assessments for chronic obstructive pulmonary disease ask about environmental exposures (such as smoking and asbestos) but do not ask about family history; however, those with alpha-1-antitrypsin deficiency, a hereditary condition that runs in families, are at the highest risk of developing chronic obstructive pulmonary disease even without an environmental exposure [7]. Renal cell carcinoma, a tumor of the kidney, is another example. Almost all risk assessments include smoking, alcohol, and exercise, and some include fami...

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright
• List of Contributors
• Chapter 1. Family Health History and Health Risk Assessment For Cardiovascular Disease in Health Care
• Chapter 2. Personalized Lifestyle Medicine
• Chapter 3. Lipoprotein Disorders
• Chapter 4. Metabolic Syndrome
• Chapter 5. Hypertension
• Chapter 6. Novel Approaches to Cardiovascular Diagnostics: Focus on Coronary Artery Disease and Myocardial Infarction
• Chapter 7. Hypertrophic Cardiomyopathy in the Era of Genomic Medicine
• Chapter 8. Genomics to Predict Risk of Coronary Artery Disease
• Chapter 9. Genomics-Guided Antithrombotic Therapy for Acute Coronary Syndromes
• Chapter 10. Heart Failure: Impact of Genetics and Genomics
• Chapter 11. Arrhythmia Genomics
• Chapter 12. Genetics and Genomics of Peripheral Arterial Disease
• Chapter 13. Genetic Basis of Congenital Heart Disease
• Chapter 14. Perioperative Genomics
• Chapter 15. Genomics of Ischemic Stroke and Prospects for Clinical Applications
• Chapter 16. Cardiovascular Pharmacogenetics
• Glossary
• Abbreviations
• Index