Genetic Variations and Precision Medicine

The time and costs associated with the sequencing of a human genome have decreased significantly in recent years. Many people have chosen to have their genomes sequenced to receive genomics-based personalized healthcare services. To reach the goal of genomics-based precision medicine, health information management (HIM) professionals need to manage and analyze patients' genomic data. Two important pieces of information from the genome sequence are the risk of genetic diseases and the specific medication or pharmacogenomic results for the individual patient, both of which are linked to a patient's genetic variations. In this review article, we introduce genetic variations, including their data types, relevant databases, and some currently available analysis methods and systems. HIM professionals can choose to use these databases, methods, and systems in the management and analysis of patients' genomic data.

A prognostic model based on readily available clinical data enriched a pre-emptive pharmacogenetic testing program

OBJECTIVES

We describe the development, implementation, and evaluation of a model to pre-emptively select patients for genotyping based on medication exposure risk.

STUDY DESIGN AND SETTING

Using deidentified electronic health records, we derived a prognostic model for the prescription of statins, warfarin, or clopidogrel. The model was implemented into a clinical decision support (CDS) tool to recommend pre-emptive genotyping for patients exceeding a prescription risk threshold. We evaluated the rule on an independent validation cohort and on an implementation cohort, representing the population in which the CDS tool was deployed.

RESULTS

The model exhibited moderate discrimination with area under the receiver operator characteristic curves ranging from 0.68 to 0.75 at 1 and 2 years after index dates. Risk estimates tended to underestimate true risk. The cumulative incidences of medication prescriptions at 1 and 2 years were 0.35 and 0.48, respectively, among 1,673 patients flagged by the model. The cumulative incidences in the same number of randomly sampled subjects were 0.12 and 0.19, and in patients over 50 years with the highest body mass indices, they were 0.22 and 0.34.

CONCLUSION

We demonstrate that prognostic algorithms can guide pre-emptive pharmacogenetic testing toward those likely to benefit from it.

Pharmacogenetics in cancer therapy - 8 years of experience at the Institute for Oncology and Radiology of Serbia

PURPOSE

Pharmacogenetics is a study of possible mechanism by which an individual's response to drugs is genetically determined by variations in their DNA sequence. The aim of pharmacogenetics is to identify the optimal drug and dose for each individual based on their genetic constitution, i.e. to individualize drug treatment. This leads to achieving the maximal therapeutic response for each patient, while reducing adverse side effects of therapy and the cost of treatment. A centralized pharmacogenetics service was formed at the Institute for Oncology and Radiology of Serbia (IORS) with the aim to provide a personalized approach to cancer treatment of Serbian patients.

METHODS

Analyses of KRAS mutations in metastatic colorectal cancer, EGFR mutations in advanced non-small cell lung cancer, CYP2D6 polymorphism in breast cancer, DPD polymorphism in colorectal cancer and MTHFR polymorphism in osteosarcoma have been performed by real time polymerase chain reaction (PCR) and PCR-restriction fragment length polymorphism (PCR-RFLP).

RESULTS

Mutation testing analyses were successful for 1694 KRAS samples and 1821 EGFR samples, while polymorphism testing was successful for 9 CYP2D6 samples, 65 DPD samples and 35 MTHFR samples.

CONCLUSIONS

Pharmacogenetic methods presented in this paper provide cancer patients in Serbia the best possible choice of treatment at the moment.

Using Workflow Modeling to Identify Areas to Improve Genetic Test Processes in the University of Maryland Translational Pharmacogenomics Project

Delivering genetic test results to clinicians is a complex process. It involves many actors and multiple steps, requiring all of these to work together in order to create an optimal course of treatment for the patient. We used information gained from focus groups in order to illustrate the current process of delivering genetic test results to clinicians. We propose a business process model and notation (BPMN) representation of this process for a Translational Pharmacogenomics Project being implemented at the University of Maryland Medical Center, so that personalized medicine program implementers can identify areas to improve genetic testing processes. We found that the current process could be improved to reduce input errors, better inform and notify clinicians about the implications of certain genetic tests, and make results more easily understood. We demonstrate our use of BPMN to improve this important clinical process for CYP2C19 genetic testing in patients undergoing invasive treatment of coronary heart disease.

Using EHR-Linked Biobank Data to Study Metformin Pharmacogenomics

Metformin is a commonly prescribed diabetes medication whose mechanism of action is poorly understood. In this study we utilized EHR-linked biobank data to elucidate the impact of genomic variation on glycemic response to metformin. Our study found significant gene- and SNP-level associations within the beta-2 subunit of the heterotrimeric adenosine monophosphate-activated protein kinase complex. Using EHR phenotypes where were able to add additional clarity to ongoing metformin pharmacogenomic dialogue.

Prerequisites to implementing a pharmacogenomics program in a large health-care system

Pharmacogenomics (PGx) technology is advancing rapidly; however, clinical adoption is lagging. The Indiana Institute of Personalized Medicine (IIPM) places a strong focus on translating PGx research into clinical practice. We describe what have been found to be the key requirements that must be delivered in order to ensure a successful and enduring PGx implementation within a large health-care system.

Towards a global IT system for personalized medicine: the Medicine Safety Code initiative

The availability of pharmacogenomic data of individual patients can significantly improve physicians' prescribing behavior, lead to a reduced incidence of adverse drug events and an improvement of effectiveness of treatment. The Medicine Safety Code (MSC) initiative is an effort to improve the ability of clinicians and patients to share pharmacogenomic data and to use it at the point of care. The MSC is a standardized two-dimensional barcode that captures individual pharmacogenomic data. The system is backed by a web service that allows the decoding and interpretation of anonymous MSCs without requiring the installation of dedicated software. The system is based on a curated, ontology-based knowledge base representing pharmacogenomic definitions and clinical guidelines. The MSC system performed well in preliminary tests. To evaluate the system in realistic health care settings and to translate it into practical applications, the future participation of stakeholders in clinical institutions, medical researchers, pharmaceutical companies, genetic testing providers, health IT companies and health insurance organizations will be essential.

Molecular Medicine: How, What, and When?

Integrating molecular medicine into clinical practice will create many challenges. But the existing genetic testing paradigm may not be the right model for introducing these new technologies.

Integrating molecular medicine into the US health-care system: opportunities, barriers, and policy challenges

Scientific support about the concept of using molecular data for risk stratification and tailoring health-care interventions to the individual--a strategy broadly defined as molecular medicine (MM)--is accumulating. Molecular-based health-care technologies are beginning to enter clinical practice, but their use has revealed many scientific, economic, and organizational barriers to the effective delivery of targeted health care. We conducted a qualitative interview study to describe the MM landscape, with an emphasis on eliciting policy recommendations for the field from a broad range of stakeholders in MM and health care. Molecular medicine has widespread support but will require changes in how molecular-based technologies are evaluated, how health care is financed and delivered, and how clinicians and consumers are trained and prepared for its use. In particular, researchers and developers need to become active participants in a variety of clinical integration strategies to realize the promise of MM.

The PharmGKB: integration, aggregation, and annotation of pharmacogenomic data and knowledge

The Pharmacogenetics and Pharmacogenomics Knowledge Base, PharmGKB (http://www.pharmgkb.org), curates pharmacogenetic and pharmacogenomic information to generate knowledge concerning the relationships among genes, drugs, and diseases, and the effects of gene variation on these relationships. PharmGKB curators collect information on genotype-phenotype relationships both from the literature and from the deposition of primary research data into our database. Their goal is to catalyze pharmacogenetic and pharmacogenomic research.

Genomics and proteomics methodologies for vulnerable populations research

This chapter describes common genomic and proteomic methods and their application to the study of vulnerable population groups. The International HapMap project is discussed in relation to unique Haplotype single nucleotide polymorphisms (htSNPs) in population groups. In addition, studies, which have used these methods to investigate aging, ethnic, and racial specific conditions, as well as psychiatric diseases, are reviewed. Advantages and limitations of various genomic and proteomic approaches are discussed in relation to population admixture and sample selection.

Pharmacogenetics and uncertainty: implications for policy makers

Uncertainty for policy makers is not new but the pressure to make decisions under conditions of uncertainty is perhaps greater than ever. The arrival of new scientific developments such as pharmacogenetics offers potentially great benefits (as well as significant risks). They have passionate supporters as well as doubters. The evidence is often extensive but unclear and policy makers may find themselves under pressure to make decisions before they feel that the evidence is compelling. The UK is particularly well placed to play a leading role in the development of pharmacogenetics and is equally well placed to derive the benefits to both health and wealth that could flow from this. However, the uncertainties threaten to overwhelm the capacity of policy makers to act effectively. The uncertainties are both about the context within which the science and delivery of pharmacogenetics is being developed and about the interests that could be served. This paper maps these uncertainties and concludes with some suggestions, drawing on deliberative democracy and futures thinking, as to how policy makers might manage the tensions and dilemmas they face by moving from an unstable, emergent policy arena to a more stable one.

Putting pharmacogenetics into practice

Genetics is slowly explaining variations in drug response, but applying this knowledge depends on implementation of a host of policies that provide long-term support to the field, from translational research and regulation to professional education.

Pharmacogenetic challenges for the health care system

Pharmacogenetics--the effect of genotype on drug response--holds the promise of safer and more effective drug therapy. Genetic tests would be routinely given to patients prior to prescription of a drug, with therapeutic decisions based on the patient's drug-response profile. This paper examines the operational changes and the ethical, legal, and policy challenges that pharmacogenetic medicine poses for key actors in the health care system. Adaptation by drug companies, regulatory agencies, physicians, patients, insurers, and public funding agencies will be necessary to integrate pharmacogenetic medicine into health care.

Multicenter epidemiologic and health services research on therapeutics in the HMO Research Network Center for Education and Research on Therapeutics

Research and education programs in therapeutics that combine the data, organizational capabilities, and expertise of several managed care organizations working in concert can serve an important role when a single organization is not large enough to address a question of interest, when diversity in populations or delivery systems is required, and when it is necessary to establish consistency of results in different settings. Nine members of the HMO Research Network, a consortium of health maintenance organizations (HMOs) that perform public domain research, have formed a Center for Education and Research on Therapeutics (CERT), sponsored by the Agency for Healthcare Research and Quality, to conduct multicenter research in therapeutics. The CERT uses a distributed organizational model with shared leadership, in which data reside at the originating organization until they are needed to support a specific study. Extraction of data from the host computer systems, and some manipulation of data, is typically accomplished through computer programs that are developed centrally, then modified for use at each site. For complex studies, pooled analysis files are created by a coordinating center, and then analysed by investigators throughout the HMOs. It is also possible to contact HMO members when necessary. This multicenter environment has several benefits, addressing: (1) a wide array of questions about the safety and effectiveness of therapeutics, (2) the impact of efforts to change clinicians' and patients' behavior, and (3) pharmacoeconomic and pharmacogenetic questions.

The interface of genetics and public health: research and educational challenges

As the target date for the sequencing of the human genome approaches, there is growing recognition that public health practice, research, and education will be impacted by new genetic technologies and information and that a multidisciplinary approach is required. Research in the emerging field of public health genetics encompasses a broad range of disciplines and will increasingly involve the interactions among the investigators in these fields. An overview of these areas of research is provided, with illustrative examples. Education in public health genetics needs to address a variety of audiences, including public health graduate students and practitioners, students from related disciplines, and health care professionals. Two new graduate programs at the Universities of Michigan and Washington and training opportunities for public health professionals are described. These educational efforts must be ongoing so that the potential of genetic technology and information can be appropriately used to benefit the health of all.