The use of genomic sequence data in a clinical setting is truly a new phenomenon in this 21st century. In the year 1999, no human ever had their genome sequenced; by 2009 there were seven individuals who had their genome sequenced [ref Wade NYT], and it has been predicted by some that the millionth person will have their genome sequenced in calendar year 2014. Although it is not clear if or when the remarkable uptake of this technology might level off, it is clear that this technology will increasingly affect the way medicine is practiced. All healthcare practitioners will be increasingly asked to put this data into an appropriate clinical context, and this book is designed to assist you in this effort.

Genomics has the potential to improve our approach to care in almost every aspect of medicine from cancer to infectious diseases. This book is organized according to the standard medical and surgical subspecialties of clinical care and, in addition, has dedicated sections to areas that are not classic clinical subspecialties in adult care such as metabolomics and pharmacogenomics. The pharmacogenomics section describes the use of genetic sequence information to guide the choice and dosage of therapeutic agents. We expect that the knowledge base for all of the book’s sections will continue to grow.

We are moving into an increasingly DNA-first world of clinical medicine, where the DNA sequence data will be available for decision making prior to the patient’s visit to your office or hospital. In this DNA-first world, we will all need point-of-care decision support and we hope in these early years of genomic medicine that you find this book to be useful in your decision support needs. In addition to the detailed information in this book, several online resources including annotated genomic glossaries are available and listed in the supplementary materials.

Importantly, enthusiasm about genomic medicine should not lead to an abandonment of the classic tools of clinical medicine that are needed to inform care. First and foremost among these tools are the history and physical examination. The importance of environmental influences on health must not be overlooked [ref Willett]. While this text gives great attention to the “nature” side of the nature versus nurture equation, there are many other sources of important information on the role of environment in all diseases including that which is considered as “genetic” [ref Harrisons].

Family health history has been used in clinical medicine for generations as a proxy for genetic information in efforts to predict disease risk in patients. In contrast to its previous application, in the era of DNA-first genomic medicine, family health history will increasingly be used to add context to the DNA sequence data. Since every patient will be revealed to have rare genetic changes, so rare that they may only exist within their immediate family, the health history of others in the family who share these changes will be necessary in order to gain insight into how these changes will affect health. It will only be through knowing how these changes played out for the patient’s immediate relatives that we will be able to interpret some sequence variations in the patient who is being seen. It is because of this “interpretative need” that we will ultimately require detailed family health histories that are annotated with DNA sequence variant information.

At the current time, patients can be engaged in the gathering of detailed family health history to maximize the time of busy providers. The US Surgeon General’s My Family Health Portrait (available at https://familyhistory.hhs.gov) provides a web-based tool that allows patients to enter data regarding their own personal medical history as well as that of relatives. This data can be analyzed as a pedigree image or in a table format providing valuable information to care providers. In this interim time, before we arrive at “genomically annotated” family health history tools, we can use such currently available tools to guide disease risk interpretation via classical methodologies.