Family history has always been one of the most powerful and inexpensive tools for assessing a patient’s genetic risks.
In the case of rare single-gene (Mendelian) syndromes , such as Marfan syndrome, cystic fibrosis, or a cancer syndrome, knowledge of the family history can alert the patient and his/her physicians of the potential need for testing, surveillance and/or preventive measures. For common multifactorial disorders, such as diabetes, asthma, or non-Mendelian cancer predisposition, this is even more important, because a single genetic test result is less likely to drastically change an individual’s overall risk assessment.
Obstacles to widespread utilization of family history among primary care physicians have included the time required to gather the data; storage and retrieval of the data; and uncertainty about how to interpret it, especially in the era of evidence-based medicine.
Genetic testing provides another source of data, which shares many of the same obstacles to widespread adoption as family history: choosing and ordering appropriate tests; data storage and retrieval; evidence-based application of these data.
These challenges are not too difficult to solve when dealing with a single mutation or just one or two genes. But we are now in an era of easily accessible genome-wide mapping, with 1 million or more pieces of data in each test result. And clinical-grade sequencing of entire genomes, containing several billion pieces of data, is coming soon.
With specialty training, a human can learn to interpret moderately complicated family histories with a high degree of scientific accuracy. But global assessment of an entire genome, either for identification of the cause of a Mendelian syndrome or for recognition of factors contributing to common disease, is beyond reasonable human capacity.
Realistically, neither family history nor genetic testing is sufficient for robust risk assessment. Combining both sources of genetic information, together with environmental and other personal factors, is the ultimate goal, and is the essence of individualized medicine.
Much work is yet to be done to fully develop the evidence and refine the algorithms that will drive this type of medical care. But for many conditions, there is already sufficient qualitative and quantitative evidence to justify clinical application today. Consider, for example, the inclusion of family history in assessment of coronary artery disease risk or likelihood of carrying a mutation in one of the BRCA genes. So, the third obstacle, evidence-based interpretation, is not really the rate-limiting step today.
The biggest current barriers to integration of family history and genetic (or genomic) data in actual clinical care are data acquisition, storage, and retrieval.
The solution to this problem is obvious: computers.
More specifically, despite all of the grumbling and complaints they generate, electronic health records (EHRs) hold great promise for simplifying our lives while simultaneously improving patient care.
To be maximally useful, a family history should include data on three to four generations: children, siblings, parents/aunts/uncles, and grandparents. Depending upon the specific question at hand, children or grandparents may be more or less relevant to the risk assessment; cousins, nieces, and nephews may sometimes be important, too. For each relative, useful data include age, age of death, cause of death, and the diagnosis and approximate age of onset of each health problem. In many cases, presence or absence of common environmental risk factors is also important (for example, lung cancer without exposure to tobacco, asbestos, or radon suggests a greater likelihood of genetic predisposition). The ancestral origin on each side of the family is also sometimes informative.
Add to that the increasing availability of single-gene and whole-genome testing results, and the task of assembling all of this data becomes overwhelming.
EHRs have the ability to simplify all of this.
Just as is done today when collecting medical information about an individual patient, the family history and genetic testing elements discussed above can be stored as discrete pieces of data for each of that patient’s relatives. Studies have already shown that patients’ recall of their family history is generally pretty reliable. And if they’re encouraged to discuss that history with family members, the quality of the data improves further.
Patient portals, an integral component of meaningful use of EHRs, empower patients to collect and input this information from home, solving the problem of inadequate time during a clinical encounter.
With appropriate informed consent, it is also technically feasible to link EHR data of related individuals to increase the quantity and accuracy of family history data. Genomic sequencing data, from the patient and his/her relatives, can also be electronically linked to the family history.
Once gathered and stored, those discrete elements still need to be displayed in a logical way. People in general and physicians in particular, value flexibility and individuality in how they view data. Some prefer a graphical display of family history in a genogram or pedigree; others prefer tabular representation. Sometimes, it is helpful to see which relatives have a specific condition or group of conditions. Other times, it is useful to view the medical history of each relative individually. One may wish to view the entire family history all at once, but often a filtered view of only certain conditions or relatives of interest is more relevant.