Blood gene expression profiling in liver transplant recipients with hepatitis C virus and posttransplantation diabetes mellitus

Personalized medicine: progress and promise

Personalized medicine is a broad and rapidly advancing field of health care that is informed by each person's unique clinical, genetic, genomic, and environmental information. Personalized medicine depends on multidisciplinary health care teams and integrated technologies (e.g., clinical decision support) to utilize our molecular understanding of disease in order to optimize preventive health care strategies. Human genome information now allows providers to create optimized care plans at every stage of a disease, shifting the focus from reactive to preventive health care. The further integration of personalized medicine into the clinical workflow requires overcoming several barriers in education, accessibility, regulation, and reimbursement. This review focuses on providing a comprehensive understanding of personalized medicine, from scientific discovery at the laboratory bench to integration of these novel ways of understanding human biology at the bedside.

Collection and storage of human blood and adipose for genomic analysis of clinical samples

In this methods article, we describe collection and storage of clinically acquired blood and adipose samples for transcript analysis in an ongoing study exploring obesity in renal transplant recipients. Total ribonucleic acid (RNA) was isolated from whole blood using the LeukoLOCK™ Total RNA Isolation System (n = 4), and comparisons between fresh and frozen samples were made. Abdominal subcutaneous adipose samples (n = 4) were obtained during kidney transplantation, flash frozen, and stored at -80°C. Adipose RNA was extracted using either the STAT-60 method modified for lipids or Trizol plus RNeasy extraction. Affymetrix HG-U133 plus 2.0 arrays and Affymetrix Human Gene 1.0 ST arrays were used for both blood and adipose transcriptome analysis. Purity, quality, and quantity of RNA were high with comparable results using both array platforms.

IFN-stimulated gene expression is a useful potential molecular marker of response to antiviral treatment with Peg-IFNα 2b and ribavirin in patients with hepatitis C virus genotype 1

BACKGROUND AND AIMS

We undertook this study to determine the baseline gene expression of IFI27, IFIT1, IFI6, ISG15, IRF-1, IRF-3, OAS-2 and CXCL10 and its usefulness as molecular markers of response to antiviral treatment with peg-IFNα 2b/RBV in patients with hepatitis C virus genotype 1 (HCV-1).

METHODS

Gene expression was analyzed by RT-PCR in baseline liver biopsies from 42 HCV-1 patients who were treated with Peg-IFNα 2b/RBV for 48 weeks. In addition, we investigated gene expression of these genes in a second liver biopsy obtained 24 weeks post-treatment in sustained viral response (SVR) and relapser patients.

RESULTS

Thirteen patients achieved SVR, four were relapsers, four patients with viral response (VR) discontinued the following for 24 weeks post-treatment and 21 patients did not respond to antiviral therapy (NR). All patients with HCV-1 showed gene overexpression in baseline liver tissue, but only IFI27, IFIT1, IFI6, ISG15, and CXCL10 showed differential gene expression, which is inversely related to the response to antiviral therapy. Thus, liver tissue of NR patients showed upregulation of these genes, whereas patients with SVR gene expression level was significantly lower. Furthermore, 24 weeks afterwards treatment, SVR patients showed a significant downregulation of such genes, which was consistent with the RNA-HCV suppression. ISGs (IFI27, IFIT1, IFI6) and chemokine CXCL10 showed the best positive and negative predictive values on SVR to IFN/RBV therapy (range: 70.8-75% and 71.43-82.35%), respectively.

CONCLUSIONS

IFI27, IFIT1, IFI6, ISG15, and CXCL10 genes are potential biological markers useful for predicting response to Peg-IFNα 2b/RBV therapy in HCV-1 patients.

Integrating genomics into biobehavioral research: a transplantation exemplar

Biobehavioral research is becoming more established in nursing. This research paradigm includes a focus on the interactions of biological and behavioral variables and their impact on health outcomes. Nurse researchers have incorporated genomics as a research focus. However, biobehavioral and genomic approaches have often been viewed as separate paradigms. This article provides research exemplars from the liver transplantation population to illustrate how genomics can be integrated into a biobehavioral model of nursing research. Examples of how this integrated approach may be utilized to address gaps of knowledge are provided.

Genomic and personalized medicine: foundations and applications

The last decade has witnessed a steady embrace of genomic and personalized medicine by senior government officials, industry leadership, health care providers, and the public. Genomic medicine, which is the use of information from genomes and their derivatives (RNA, proteins, and metabolites) to guide medical decision making-is a key component of personalized medicine, which is a rapidly advancing field of health care that is informed by each person's unique clinical, genetic, genomic, and environmental information. As medicine begins to embrace genomic tools that enable more precise prediction and treatment disease, which include "whole genome" interrogation of sequence variation, transcription, proteins, and metabolites, the fundamentals of genomic and personalized medicine will require the development, standardization, and integration of several important tools into health systems and clinical workflows. These tools include health risk assessment, family health history, and clinical decision support for complex risk and predictive information. Together with genomic information, these tools will enable a paradigm shift to a comprehensive approach that will identify individual risks and guide clinical management and decision making, all of which form the basis for a more informed and effective approach to patient care. DNA-based risk assessment for common complex disease, molecular signatures for cancer diagnosis and prognosis, and genome-guided therapy and dose selection are just among the few important examples for which genome information has already enabled personalized health care along the continuum from health to disease. In addition, information from individual genomes, which is a fast-moving area of technological development, is spawning a social and information revolution among consumers that will undoubtedly affect health care decision making. Although these and other scientific findings are making their way from the genome to the clinic, the full application of genomic and personalized medicine in health care will require dramatic changes in regulatory and reimbursement policies as well as legislative protections for privacy for system-wide adoption. Thus, there are challenges from both a scientific and a policy perspective to personalized health care; however, they will be confronted and solved with the certainty that the science behind genomic medicine is sound and the practice of medicine that it informs is evidence based.

Peripheral blood gene expression profiling for cardiovascular disease assessment

Whole blood gene expression profiling has the potential to be informative about dynamic changes in disease states and to provide information on underlying disease mechanisms. Having demonstrated proof of concept in animal models, a number of studies have now tried to tackle the complexity of cardiovascular disease in human hosts to develop better diagnostic and prognostic indicators. These studies show that genomic signatures are capable of classifying patients with cardiovascular diseases into finer categories based on the molecular architecture of a patient's disease and more accurately predict the likelihood of a cardiovascular event than current techniques. To highlight the spectrum of potential applications of whole blood gene expression profiling approach in cardiovascular science, we have chosen to review the findings in a number of complex cardiovascular diseases such as atherosclerosis, hypertension and myocardial infarction as well as thromboembolism, aortic aneurysm, and heart transplant.