Recent studies have demonstrated the use of genomic data, particularly gene expression signatures, as clinical prognostic factors in complex diseases. Such studies herald the future for genomic medicine and the opportunity for personalized prognosis in a variety of clinical contexts that utilize genomescale molecular information. Several key areas represent logical and critical next steps in the use of complex genomic profiling data towards the goal of personalized medicine. First, analyses should be geared toward the development of molecular profiles that predict future events – such as major clinical events or the response, resistance, or adverse reaction to therapy. Secondly, these must move into actual clinical practice by forming the basis for the next generation of clinical trials that will employ these methodologies to stratify patients. Lastly, there remain formidable challenges is in the translation of genomic technologies into clinical medicine that will need to be addressed: professional and public education, health outcomes research, reimbursement, regulatory oversight and privacy protection.
genomic medicine, personalized medicine, human genome.
The prevailing view in therapeutic clinical research today is that observational studies are useful for generating new hypotheses and that controlled experiments (i.e., randomized clinical trials, RCTs) are the most appropriate method for assessing and confirming the efficacy of interventions.
The current trend towards patient-centered medicine calls for alternative ways of reasoning, and in particular for a shift towards hypothetico-deductive logic, in which theory is adjusted in light of individual facts. A new model of this kind should change our approach to drug research and development, and regulation. The assessment of new therapeutic agents would be viewed as a continuous process, and regulatory approval would no longer be regarded as the final step in the testing of a hypothesis, but rather, as the hypothesis-generating step.
The main role of RCTs in this patient-centered research paradigm would be to generate hypotheses, while observations would serve primarily to test their validity for different types of patients. Under hypothetico-deductive logic, RCTs are considered "exploratory" and observations, "confirmatory".
In this era of tailored therapeutics, the answers to therapeutic questions cannot come exclusively from methods that rely on data aggregation, the analysis of similarities, controlled experiments, and a search for the best outcome for the average patient; they must also come from methods based on data disaggregation, analysis of subgroups and individuals, an integration of research and clinical practice, systematic observations, and a search for the best outcome for the individual patient. We must look not only to evidence-based medicine, but also to medicine-based evidence, in seeking the knowledge that we need.
The recent explosion of genomic data and technology points to opportunities to redefine lung diseases at the molecular level; to apply integrated genomic approaches to elucidate mechanisms of lung pathophysiology; and to improve early detection, diagnosis, and treatment of lung diseases. Research is needed to translate genomic discoveries into clinical applications, such as detecting preclinical disease, predicting patient outcomes, guiding treatment choices, and most of all identifying potential therapeutic targets for lung diseases. The Division of Lung Diseases in the National Heart, Lung, and Blood Institute convened a workshop, “Genomic Medicine and Lung Diseases,” to discuss the potential for integrated genomics and systems approaches to advance 21st century pulmonary medicine and to evaluate the most promising opportunities for this next phase of genomics research to yield clinical benefit. Workshop sessions included (1) molecular phenotypes, molecular biomarkers, and therapeutics; (2) new technology and opportunity; (3) integrative genomics; (4) molecular anatomy of the lung; (5) novel data and information platforms; and (6) recommendations for exceptional research opportunities in lung genomics research.
molecular phenotypes; molecular networks; drug repurposing; epigenetics; data sharing
The development and application of systems strategies to biology and disease are transforming medical research and clinical practice in an unprecedented rate. In the foreseeable future, clinicians, medical researchers, and ultimately the consumers and patients will be increasingly equipped with a deluge of personal health information, e.g., whole genome sequences, molecular profiling of diseased tissues, and periodic multi-analyte blood testing of biomarker panels for disease and wellness. The convergence of these practices will enable accurate prediction of disease susceptibility and early diagnosis for actionable preventive schema and personalized treatment regimes tailored to each individual. It will also entail proactive participation from all major stakeholders in the health care system. We are at the dawn of predictive, preventive, personalized, and participatory (P4) medicine, the fully implementation of which requires marrying basic and clinical researches through advanced systems thinking and the employment of high-throughput technologies in genomics, proteomics, nanofluidics, single-cell analysis, and computation strategies in a highly-orchestrated discipline we termed translational systems medicine.
Systems biology; P4 Medicine; Family genome sequencing; Targeted proteomics; Single-cell analysis
Genome-wide expression microarray studies have revealed that the biological and clinical heterogeneity of breast cancer can be partly explained by information embedded within a complex but ordered transcriptional architecture. Comprising this architecture are gene expression networks, or signatures, reflecting biochemical and behavioral properties of tumors that might be harnessed to improve disease subtyping, patient prognosis and prediction of therapeutic response. Emerging 'hypothesis-driven' strategies that incorporate knowledge of pathways and other biological phenomena in the signature discovery process are linking prognosis and therapy prediction with transcriptional readouts of tumorigenic mechanisms that better inform therapeutic options.
The pace of exome and genome sequencing is accelerating, with the identification of many new disease-causing mutations in research settings, and it is likely that whole exome or genome sequencing could have a major impact in the clinical arena in the relatively near future. However, the human genomics community is currently facing several challenges, including phenotyping, sample collection, sequencing strategies, bioinformatics analysis, biological validation of variant function, clinical interpretation and validity of variant data, and delivery of genomic information to various constituents. Here we review these challenges and summarize the bottlenecks for the clinical application of exome and genome sequencing, and we discuss ways for moving the field forward. In particular, we urge the need for clinical-grade sample collection, high-quality sequencing data acquisition, digitalized phenotyping, rigorous generation of variant calls, and comprehensive functional annotation of variants. Additionally, we suggest that a 'networking of science' model that encourages much more collaboration and online sharing of medical history, genomic data and biological knowledge, including among research participants and consumers/patients, will help establish causation and penetrance for disease causal variants and genes. As we enter this new era of genomic medicine, we envision that consumer-driven and consumer-oriented efforts will take center stage, thus allowing insights from the human genome project to translate directly back into individualized medicine.
Despite stunning advances in our understanding of the genetics and the molecular basis for cancer, many patients with cancer are not yet receiving therapy tailored specifically to their tumor biology. The translation of these advances into clinical practice has been hindered, in part, by the lack of evidence for biomarkers supporting the personalized medicine approach. Most stakeholders agree that the translation of biomarkers into clinical care requires evidence of clinical utility. The highest level of evidence comes from randomized controlled clinical trials (RCTs). However, in many instances, there may be no RCTs that are feasible for assessing the clinical utility of potentially valuable genomic biomarkers. In the absence of RCTs, evidence generation will require well-designed cohort studies for comparative effectiveness research (CER) that link detailed clinical information to tumor biology and genomic data. CER also uses systematic reviews, evidence-quality appraisal, and health outcomes research to provide a methodologic framework for assessing biologic patient subgroups. Rapid learning health care (RLHC) is a model in which diverse data are made available, ideally in a robust and real-time fashion, potentially facilitating CER and personalized medicine. Nonetheless, to realize the full potential of personalized care using RLHC requires advances in CER and biostatistics methodology and the development of interoperable informatics systems, which has been recognized by the National Cancer Institute's program for CER and personalized medicine. The integration of CER methodology and genomics linked to RLHC should enhance, expedite, and expand the evidence generation required for fully realizing personalized cancer care.
The clinical utility is uncertain for many cancer genomic applications. Comparative effectiveness research (CER) can provide evidence to clarify this uncertainty.
To identify approaches to help stakeholders make evidence-based decisions, and to describe potential challenges and opportunities using CER to produce evidence-based guidance.
We identified general CER approaches for genomic applications through literature review, the authors’ experiences, and lessons learned from a recent, seven-site CER initiative in cancer genomic medicine. Case studies illustrate the use of CER approaches.
Evidence generation and synthesis approaches include comparative observational and randomized trials, patient reported outcomes, decision modeling, and economic analysis. We identified significant challenges to conducting CER in cancer genomics: the rapid pace of innovation, the lack of regulation, the limited evidence for clinical utility, and the beliefs that genomic tests could have personal utility without having clinical utility. Opportunities to capitalize on CER methods in cancer genomics include improvements in the conduct of evidence synthesis, stakeholder engagement, increasing the number of comparative studies, and developing approaches to inform clinical guidelines and research prioritization.
CER offers a variety of methodological approaches to address stakeholders’ needs. Innovative approaches are needed to ensure an effective translation of genomic discoveries.
evidence synthesis; evidence generation; stakeholder; clinical utility
In order to establish systems medicine, based on the results and insights from basic biological research applicable for a medical and a clinical patient care, it is essential to measure patient-based data that represent the molecular and cellular state of the patient's pathology. In this paper, we discuss potential limitations of the sole usage of static genotype data, e.g., from next-generation sequencing, for translational research. The hypothesis advocated in this paper is that dynOmics data, i.e., high-throughput data that are capable of capturing dynamic aspects of the activity of samples from patients, are important for enabling personalized medicine by complementing genotype data.
genome medicine; personalized medicine; next-generation sequencing data; dynOmics data; high-throughput data
Recent advances in human genomics and biotechnologies have profound impacts on medical research and clinical practice. Individual genomic information, including DNA sequences and gene expression profiles, can be used for prediction, prevention, diagnosis, and treatment for many complex diseases. Personalized medicine attempts to tailor medical care to individual patients by incorporating their genomic information. In a case of pancreatic cancer, the fourth leading cause of cancer death in the United States, alteration in many genes as well as molecular profiles in blood, pancreas tissue, and pancreas juice has recently been discovered to be closely associated with tumorigenesis or prognosis of the cancer. This review aims to summarize recent advances of important genes, proteins, and microRNAs that play a critical role in the pathogenesis of pancreatic cancer, and to provide implications for personalized medicine in pancreatic cancer.
pancreatic cancer; genomics; genetics; biomarker; molecular target; personalized medicine
Prior clinical studies have demonstrated that a family history of coronary artery disease (CAD) is associated with future cardiovascular events. Although there are several Mendelian disorders that are associated with CAD, most common forms of CAD are believed to be multifactorial and the result of many genes with small individual effects. The identification of these genes and their variation would be very helpful for the prediction, prevention, and management of CAD; linkage analysis or candidate gene case-control studies have been largely unsuccessful. On the contrary, recent advances in genomic techniques have generated a large amount of deoxyribonucleic acid (DNA)-based information. The link between CAD and inflammation and biological pathways has been highlighted. In particular, several genome-wide association studies have replicated a novel gene marker on chromosome 9p21. The information gained from genomic studies, in combination with clinical data, is expected to refine personalized approaches to assess risk and guide management for CAD. Genetic risk scores derived from several functional single nucleotide polymorphisms (SNPs) or haplotypes in multiple genes may improve the prediction of CAD. Despite the complexity of CAD genetics, steady progress is expected.
Coronary artery disease; Genomics; Genes; Risk; Polymorphism, single nucleotide
In this review, we discuss some of the most recent developments in genomics research and their relevance to the field of pediatrics. In particular, we examine 3 major approaches that are being used to identify genetic correlates of disease: genome-wide association studies, copy number variation studies, and next-generation sequencing. In the past few years, these approaches have yielded major insights into the causes and pathophysiology of a wide range of diseases but are also constrained by certain limitations. This review provides an overview of the genomic landscape in complex pediatric disorders and sets the stage for translating new discoveries into clinical practice, the future of genomic medicine.
CNV; genome; genomics; GWAS; NGS
Predictive models that generate individualized estimates for medically relevant outcomes are playing increasing roles in clinical care and translational research. However, current methods for calibrating these estimates lose valuable information. Our goal is to develop a new calibration method to conserve as much information as possible, and would compare favorably to existing methods in terms of important performance measures: discrimination and calibration.
Material and methods
We propose an adaptive technique that utilizes individualized confidence intervals (CIs) to calibrate predictions. We evaluate this new method, adaptive calibration of predictions (ACP), in artificial and real-world medical classification problems, in terms of areas under the ROC curves, the Hosmer-Lemeshow goodness-of-fit test, mean squared error, and computational complexity.
ACP compared favorably to other calibration methods such as binning, Platt scaling, and isotonic regression. In several experiments, binning, isotonic regression, and Platt scaling failed to improve the calibration of a logistic regression model, whereas ACP consistently improved the calibration while maintaining the same discrimination or even improving it in some experiments. In addition, the ACP algorithm is not computationally expensive.
The calculation of CIs for individual predictions may be cumbersome for certain predictive models. ACP is not completely parameter-free: the length of the CI employed may affect its results.
ACP can generate estimates that may be more suitable for individualized predictions than estimates that are calibrated using existing methods. Further studies are necessary to explore the limitations of ACP.
Background. In recent years, there has been an explosion in the number of technical and medical diagnostic platforms being developed. This has greatly improved our ability to more accurately, and more comprehensively, explore and characterize human biological systems on the individual level. Large quantities of biomedical data are now being generated and archived in many separate research and clinical activities, but there exists a paucity of studies that integrate the areas of clinical neuropsychiatry, personal genomics and brain-machine interfaces.
Methods. A single person with severe mental illness was implanted with the Medtronic Reclaim® Deep Brain Stimulation (DBS) Therapy device for Obsessive Compulsive Disorder (OCD), targeting his nucleus accumbens/anterior limb of the internal capsule. Programming of the device and psychiatric assessments occurred in an outpatient setting for over two years. His genome was sequenced and variants were detected in the Illumina Whole Genome Sequencing Clinical Laboratory Improvement Amendments (CLIA)-certified laboratory.
Results. We report here the detailed phenotypic characterization, clinical-grade whole genome sequencing (WGS), and two-year outcome of a man with severe OCD treated with DBS. Since implantation, this man has reported steady improvement, highlighted by a steady decline in his Yale-Brown Obsessive Compulsive Scale (YBOCS) score from ∼38 to a score of ∼25. A rechargeable Activa RC neurostimulator battery has been of major benefit in terms of facilitating a degree of stability and control over the stimulation. His psychiatric symptoms reliably worsen within hours of the battery becoming depleted, thus providing confirmatory evidence for the efficacy of DBS for OCD in this person. WGS revealed that he is a heterozygote for the p.Val66Met variant in BDNF, encoding a member of the nerve growth factor family, and which has been found to predispose carriers to various psychiatric illnesses. He carries the p.Glu429Ala allele in methylenetetrahydrofolate reductase (MTHFR) and the p.Asp7Asn allele in ChAT, encoding choline O-acetyltransferase, with both alleles having been shown to confer an elevated susceptibility to psychoses. We have found thousands of other variants in his genome, including pharmacogenetic and copy number variants. This information has been archived and offered to this person alongside the clinical sequencing data, so that he and others can re-analyze his genome for years to come.
Conclusions. To our knowledge, this is the first study in the clinical neurosciences that integrates detailed neuropsychiatric phenotyping, deep brain stimulation for OCD and clinical-grade WGS with management of genetic results in the medical treatment of one person with severe mental illness. We offer this as an example of precision medicine in neuropsychiatry including brain-implantable devices and genomics-guided preventive health care.
Genomics; Deep brain stimulation; Whole genome sequencing; Ethics; Neurosurgery; Obsessive compulsive disorder
Response to specific depression treatments varies widely among individuals. Understanding and predicting that variation could have great benefits for people living with depression.
The authors describe a conceptual model for identifying and evaluating evidence relevant to personalizing treatment for depression. They review evidence related to three specific treatment decisions: choice between antidepressant medication and psychotherapy, selection of a specific antidepressant medication, and selection of a specific psychotherapy. They then discuss potential explanations for negative findings as well as implications for research and clinical practice.
Many previous studies have examined general predictors of outcome, but few have examined true moderators (predictors of differential response to alternative treatments). The limited evidence indicates that some specific clinical characteristics may inform the choice between antidepressant medication and psychotherapy and the choice of specific antidepressant medication. Research to date does not identify any biologic or genetic predictors of sufficient clinical utility to inform the choice between medication and psychotherapy, the selection of specific medication, or the selection of a specific psychotherapy.
While individuals vary widely in response to specific depression treatments, that variability remains largely unpredictable. Future research should focus on identifying true moderator effects and should consider how response to treatments varies across episodes. At this time, our inability to match patients with treatments implies that systematic follow-up and adjustment of treatment is more important than initial treatment selection.
We propose A step-by-step roadmap to integrate genetics in the Electronic Patient Record in Family Medicine and clinical research. This could make urgent operationalization of readily available genetic knowledge feasible in clinical research and consequently improved medical care.
Improving genomic literacy by training and education is needed first. The second step is the improvement of the possibilities to register the family history in such a way that queries can identify patients at risk. Adding codes to the ICPC chapters “A21 Personal/family history of malignancy” and “A99 Disease carrier not described further” is proposed. Multidisciplinary guidelines for referral must be unambiguous. Electronical patient records need possibilities to add (new) family history information, including links between individuals who are family members. Automatic alerts should help general practitioners to recognize patients at risk who satisfy referral criteria. We present a familial breast cancer case with a BRCA1 mutation as an example.
Genetics registration; Family history; Electronic patient record; General practice/family medicine; Clinical research
This report is the collective product of word-leading experts working in the branches of integrative medicine by predictive, preventive and personalised medicine (PPPM) under the coordination of the European Association for Predictive, Preventive and Personalised Medicine. The general report has been prepared as the consortium document proposed at the EPMA World Congress 2011 which took place in Bonn, Germany. This forum analyzed the overall deficits and trends relevant for the top-science and daily practice in PPPM focused on the patient. Follow-up consultations resulted in a package of recommendations for consideration by research units, educators, healthcare industry, policy-makers, and funding bodies to cover the current knowledge deficit in the field and to introduce integrative approaches for advanced diagnostics, targeted prevention, treatments tailored to the person and cost-effective healthcare.
predictive; preventive and personalised medicine; integrative medicine; common/rare disease; diabetes/cancer/cardiovascular/neurodegenerative diseases; co-morbidities; well-being concept; research; education; healthcare; ethics; economy
Cancers are complex multifactorial diseases. For centuries, conventional organ-based classification system (i.e., breast cancer, lung cancer, colon cancer, colorectal cancer, prostate cancer, lymphoma, leukemia, and so on) has been utilized. Recently, molecular diagnostics has become an essential component in clinical decision-making. However, tumor evolution and behavior cannot accurately be predicted, despite numerous research studies reporting promising tumor biomarkers. To advance molecular diagnostics, a better understanding of intratumor and intertumor heterogeneity is essential. Tumor cells interact with the extracellular matrix and host non-neoplastic cells in the tumor microenvironment, which is influenced by genomic variation, hormones, and dietary, lifestyle and environmental exposures, implicated by molecular pathological epidemiology. Essentially, each tumor possesses its own unique characteristics in terms of molecular make-up, tumor microenvironment and interactomes within and between neoplastic and host cells. Starting from the unique tumor concept and paradigm, we can better classify tumors by molecular methods, and move closer toward personalized cancer medicine and prevention.
genomics; holistic; intratumor heterogeneity; molecular classification; molecular pathological epidemiology; MPE; neoplasia; phenome; systems biology; tumor–host interaction; unique tumor paradigm
BCM faculty members spearheaded development of a first generation Personal Genome Profile (Baylor PGP) assay to assist physicians in diagnosing and managing patients in this new era of medicine. The principles that are guiding the design and implementation of the Baylor PGP are high quality, robustness, low expense, flexibility, practical clinical utility and the ability to facilitate broad areas of clinical research. The single most distinctive feature of the approach taken is an emphasis on extensive screening for rare disease causing mutations rather than common risk-increasing polymorphisms. Because these variants have very large direct effects, the ability to inexpensively screen for them could have major immediate clinical impact in disease diagnosis, carrier detection, pre-symptomatic detection of late onset disease and even prenatal diagnosis. In addition to creating a counseling tool for individual ‘consumers’ this system will fit into the established medical record and be used by physicians involved in direct patient care. This paper describes an overall framework for clinical diagnostic array genotyping, and the available technologies as well as highlights the opportunities and challenges for implementation.
Translational medicine requires the integration of knowledge using heterogeneous data from health care to the life sciences. Here, we describe a collaborative effort to produce a prototype Translational Medicine Knowledge Base (TMKB) capable of answering questions relating to clinical practice and pharmaceutical drug discovery.
We developed the Translational Medicine Ontology (TMO) as a unifying ontology to integrate chemical, genomic and proteomic data with disease, treatment, and electronic health records. We demonstrate the use of Semantic Web technologies in the integration of patient and biomedical data, and reveal how such a knowledge base can aid physicians in providing tailored patient care and facilitate the recruitment of patients into active clinical trials. Thus, patients, physicians and researchers may explore the knowledge base to better understand therapeutic options, efficacy, and mechanisms of action.
This work takes an important step in using Semantic Web technologies to facilitate integration of relevant, distributed, external sources and progress towards a computational platform to support personalized medicine.
TMO can be downloaded from http://code.google.com/p/translationalmedicineontology and TMKB can be accessed at http://tm.semanticscience.org/sparql.
The Scientific Board of the California Medical Association presents the following inventory of items of progress in physical medicine and rehabilitation. Each item, in the judgment of a panel of knowledgeable physicians, has recently become reasonably firmly established, both as to scientific fact and important clinical significance. The items are presented in simple epitome and an authoritative reference, both to the item itself and to the subject as a whole, is generally given for those who may be unfamiliar with a particular item. The purpose is to assist busy practitioners, students, research workers or scholars to stay abreast of these items of progress in physical medicine and rehabilitation that have recently achieved a substantial degree of authoritative acceptance, whether in their own field of special interest or another.
The items of progress listed below were selected by the Advisory Panel to the Section on Physical Medicine and Rehabilitation of the California Medical Association and the summaries were prepared under its direction.
The Scientific Board of the California Medical Association presents the following inventory of items of progress in preventive medicine and public health. Each item, in the judgment of a panel of knowledgeable physicians, has recently become reasonably firmly established, both as to scientific fact and important clinical significance. The items are presented in simple epitome and an authoritative reference, both to the item itself and to the subject as a whole, is generally given for those who may be unfamiliar with a particular item. The purpose is to assist busy practitioners, students, research workers or scholars to stay abreast of these items of progress in preventive medicine and public health that have recently achieved a substantial degree of authoritative acceptance, whether in their own field of special interest or another.
The items of progress listed below were selected by the Advisory Panel to the Section on Preventive Medicine and Public Health of the California Medical Association and the summaries were prepared under its direction.
The Scientific Board of the California Medical Association presents the following inventory of items of progress in nuclear medicine. Each item, in the judgment of a panel of knowledgeable physicians, has recently become reasonably firmly established, both as to scientific fact and important clinical significance. The items are presented in simple epitome and an authoritative reference, both to the item itself and to the subject as a whole, is generally given for those who may be unfamiliar with a particular item. The purpose is to assist busy practitioners, students, research workers or scholars to stay abreast of these items of progress in nuclear medicine that have recently achieved a substantial degree of authoritative acceptance, whether in their own field of special interest or another.
The items of progress listed below were selected by the Advisory Panel to the Section on Nuclear Medicine of the California Medical Association and the summaries were prepared under its direction.
The Scientific Board of the California Medical Association presents the following inventory of items of progress in occupational medicine. Each item, in the judgment of a panel of knowledgeable physicians, has recently become reasonably firmly established, both as to scientific fact and important clinical significance. The items are presented in simple epitome and an authoritative reference, both to the item itself and to the subject as a whole, is generally given for those who may be unfamiliar with a particular item. The purpose is to assist busy practitioners, students, research workers or scholars to stay abreast of these items of progress in occupational medicine that have recently achieved a substantial degree of authoritative acceptance, whether in their own field of special interest or another.
The items of progress listed below were selected by the Advisory Panel to the Section on Occupational Medicine of the California Medical Association and the summaries were prepared under its direction.
The Scientific Board of the California Medical Association presents the following inventory of items of progress in internal medicine. Each item, in the judgment of a panel of knowledgeable physicians, has recently become reasonably firmly established, both as to scientific fact and important clinical significance. The items are presented in simple epitome and an authoritative reference, both to the item itself and to the subject as a whole, is generally given for those who may be unfamiliar with a particular item. The purpose is to assist busy practitioners, students, research workers or scholars to stay abreast of these items of progress in internal medicine that have recently achieved a substantial degree of authoritative acceptance, whether in their own field of special interest or another.
The items of progress listed below were selected by the Advisory Panel to the Section on Internal Medicine of the California Medical Association and the summaries were prepared under its direction.