Personalized Medicine for Diabetes: The Case for Personalized Medicine

Personalized medicine may be considered an extension of traditional approaches to understanding and treating disease, but with greater precision. Physicians may now use a patient''s genetic variation or expression profile as well as protein and metabolic markers to guide the selection of certain drugs or treatments. In many cases, the information provided by molecular markers predicts susceptibility to conditions. The added precision introduces the possibility of a more preventive, effective approach to clinical care and reductions in the duration and cost of clinical trials. Here, we make the case, through real-world examples, that personalized medicine is delivering significant value to individuals, to industry, and to the health care system overall and that it will continue to grow in importance if we can lift the barriers that impede its adoption and build incentives to encourage its practice.     

Personalized medicine in women's obesity prevention and treatment: implications for research,policy and practice

The prevalence of obesity in America has reached epidemic proportions, and obesity among women is particularly concerning. Severe obesity (body mass index ≥35 kg m^?2) is more prevalent in women than men. Further, women have sex‐specific risk factors that must be considered when developing preventive and therapeutic interventions. This review presents personalized medicine as a dynamic approach to obesity prevention, management and treatment for women. First, we review obesity as a complex health issue, with contributing sex‐specific, demographic, psychosocial, behavioural, environmental, epigenetic and genetic/genomic risk factors. Second, we present personalized medicine as a rapidly advancing field of health care that seeks to quantify these complex risk factors to develop more targeted and effective strategies that can improve disease management and/or better minimize an individual's likelihood of developing obesity. Third, we discuss how personalized medicine can be applied in a clinical setting with current and emerging tools, including health risk assessments, personalized health plans, and strategies for increasing patient engagement. Finally, we discuss the need for additional research, training and policy that can enhance the practice of personalized medicine in women's obesity, including further advancements in the ‘‐omics’ sciences, physician training in personalized medicine, and additional development and standardization of innovative targeted therapies and clinical tools.     

Personalized medicine in psychiatry: New technologies and approaches

Psychiatric patients tend to exhibit significant interindividual variability in their responses to psychoactive drugs, as well as an irregular clinical course. For these (and other) reasons, increasing numbers of psychiatrists are turning to genotyping for help in selecting the psychopharmacologic agents best suited to an individual patient's distinctive metabolic characteristics and clinical presentation. Fortunately, routine genotyping is already available for gene variations that code for proteins involved in neurotransmission, and for drug-metabolizing enzymes involved in the elimination of many medications. Thus, genotyping-based personalized psychiatry is now in sight. Increasing numbers of clinically useful DNA microarrays are in the development stage, including a simplified procedure for genotyping patients for CYP2D6, which metabolizes a high proportion of the currently prescribed antidepressants and antipsychotics. It has been pointed out that psychiatric disease is rarely a consequence of an abnormality in a single gene, but reflects the perturbations of complex intracellular networks in the brain. Thus, analysis of functional neuronal networks is becoming an essential component of drug development strategies. The integrated use of technologies such as electroencephalography, magnetoencephalography, functional magnetic resonance imaging (fMRI), and diffusion tensor imaging (DTI), in combination with pharmacogenetics, promises to transform our understanding of the mechanisms of psychiatric disorders and their treatment. The concept of network medicine envisions a time to come when drugs will be used to target a neural network rather than simply components within the network. Personalized medicine in psychiatry is still at an early stage, but it has a very promising future.     

Genome variation and personalized cancer medicine

Genomic variation, through effects on gene structure and expression, plays an important role in understanding disease predisposition, biology and clinical response to therapy. Transforming this knowledge into clinically relevant information that tailors interventions to an individual's specific genetic, physical, social and environmental profile is challenging. To illustrate how research initiatives at preclinical phases of development are attempting to address clinically important issues in oncology, six clinical problems related to cancers of the colon, prostate, breast, pancreas and brain (medulloblastoma) as well as metastatic disease of different origins are described. A unifying theme across applications is that healthy individuals previously indistinguishable in regards to cancer risk and patients with cancer previously categorized as similar with regard to prognosis or drug response are being stratified into more refined subgroups with different clinical profiles. Effective matching of a broad range of tests with more tailored strategies for prevention and/or treatment will require well‐designed clinical studies to evaluate benefits and costs.     

Personalized Medicine for Diabetes: Personalized Medicine in Diabetes: Regulatory Considerations

Personalized medicine has become a topic of great interest because of its potential to improve patient care and optimize therapeutic strategy. The U.S. Food and Drug Administration (FDA) is interested in promoting personalized medicine, whenever appropriate, to protect and promote the public health. The ability to better diagnose, screen, and manage patients with diabetes in order to individualize care should lead to better health outcomes and a large benefit to public health. This article describes FDA regulatory considerations for devices intended for use as personalized medicine tools for the diagnosis and treatment of patients with diabetes.     

Molecular classification of idiopathic pulmonary fibrosis: Personalized medicine,genetics and biomarkers

Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive fibrotic lung disease associated with high morbidity and poor survival. Characterized by substantial disease heterogeneity, the diagnostic considerations, clinical course and treatment response in individual patients can be variable. In the past decade, with the advent of high‐throughput proteomic and genomic technologies, our understanding of the pathogenesis of IPF has greatly improved and has led to the recognition of novel treatment targets and numerous putative biomarkers. Molecular biomarkers with mechanistic plausibility are highly desired in IPF, where they have the potential to accelerate drug development, facilitate early detection in susceptible individuals, improve prognostic accuracy and inform treatment recommendations. Although the search for candidate biomarkers remains in its infancy, attractive targets such as MUC5B and MPP7 have already been validated in large cohorts and have demonstrated their potential to improve clinical predictors beyond that of routine clinical practices. The discovery and implementation of future biomarkers will face many challenges, but with strong collaborative efforts among scientists, clinicians and the industry the ultimate goal of personalized medicine may be realized.     

Personalized Medicine for Diabetes: Circulating Biomarkers of Glycemia in Diabetes Management and Implications for Personalized Medicine

Personalized medicine represents a new model in how the medical community approaches disease management. Rather than managing those with a particular diagnosis according to an established guideline, the personalized medicine model seeks to identify unique characteristics within each patient that can serve as a basis for disease characterization and specialized treatment. This article reviews several circulating biomarkers of glycemia that are used in the medical management of diabetes, to include hemoglobin A1c, fructosamine, and 1,5-anhydroglucitol. Within the discussion, specific attention is paid to areas in which biomarker results do not correlate with anticipated results based on actual mean glycemia. Variability between actual and anticipated results of the various biomarker tests represents opportunities to identify previously undefined subcategories of diabetes and groups of patients that fit into these subcategories. Finally, research areas are proposed for these subcategories that would further promote the field of personalized medicine in diabetes.     

Systems medicine and metabolic modelling

Several complex diseases are caused by the malfunction of human metabolism, and deciphering the underlying molecular mechanisms can elucidate their aetiology. Systems biology is an integrative approach combining experimental and computational biology to identify and describe the molecular mechanisms of complex biological systems. Systems medicine has the potential to elucidate the onset and progression of complex metabolic diseases through the use of computational approaches. Advances in biotechnology have resulted in the provision of high-throughput data, which provide information about different metabolic processes. The systems medicine approach can utilize such data to reconstruct genome-scale metabolic models that can be used to study the function of specific enzymes and pathways in the context of the complete metabolic network. In this review, we outline the importance of genome-scale models in systems medicine and discuss how they may contribute towards the development of personalized medicine.     

Precision medicine in pheochromocytoma and paraganglioma: current and future concepts

Pheochromocytoma and paraganglioma (PPGL) are rare diseases but are also amongst the most characterized tumour types. Hence, patients with PPGL have greatly benefited from precision medicine for more than two decades. According to current molecular biology and genetics‐based taxonomy, PPGL can be divided into three different clusters characterized by: Krebs cycle reprogramming with oncometabolite accumulation or depletion (group 1a); activation of the (pseudo)hypoxia signalling pathway with increased tumour cell proliferation, invasiveness and migration (group 1b); and aberrant kinase signalling causing a pro‐mitogenic and anti‐apoptotic state (group 2). Categorization into these clusters is highly dependent on mutation subtypes. At least 12 different syndromes with distinct genetic causes, phenotypes and outcomes have been described. Genetic screening tests have a documented benefit, as different PPGL syndromes require specific approaches for optimal diagnosis and localization of various syndrome‐related tumours. Genotype‐tailored treatment options, follow‐up and preventive care are being investigated. Future new developments in precision medicine for PPGL will mainly focus on further identification of driver mechanisms behind both disease initiation and malignant progression. Identification of novel druggable targets and prospective validation of treatment options are eagerly awaited. To achieve these goals, we predict that collaborative large‐scale studies will be needed: Pheochromocytoma may provide an example for developing precision medicine in orphan diseases that could ultimately aid in similar efforts for other rare conditions.     

Personalized medicine: Present and future of breast cancer management

Breast cancer is the first cause of cancer in women worldwide. Recent molecular analyses have shown that it is not a single disease but a mixture of several diseases with different biological behaviors, which should lead to treatment customization for each patient. Personalized medicine is based on tumor and/or patient molecular profiles. This new way to think oncology is currently applied at different stages of breast cancer management, including prognosis, prediction of treatment efficacy, and development of new therapies via new kinds of clinical trials. These trials are not only based on tumor site but also on tumor genetic characterization using genomic tools such as gene expression profiling, array-CGH or next-generation sequencing technologies. The aim of personalized medicine is to tailor treatment according to the specificities of a single disease in a given patient. In this review, we present the advances in treatment personalization which are currently used in daily practice as well as the technologies and therapies under investigation in various clinical trials.     

Personalized medicine in neurosurgery

Personalized medicine (PM) in neurosurgery is possible today thanks to newly accessible imaging technologies, and to genomic, proteomic and epigenetic biomarkers capable of providing clinically useful information about individual patients. PM is becoming increasingly indispensable in neurosurgery because this specialty offers a wide range of therapeutic options such as surgery and/or radiotherapy and/or chemotherapy. Moreover, the effectiveness of these procedures varies from one patient to another, depending inter alia on the patients’ individual genomic traits. A prime example is glioblastoma multiforme, which exhibits at least five genomic biomarkers related to distinct therapeutic and prognostic outcomes. At least one of these biomarkers, the ω-6 methylguanine-DNA methyltransferase promoter of methylation status, has already been used in clinical trials. New functional imaging techniques allow the surgeon to circumvent crucial brain areas whose location may vary among patients, thus allowing the safe and complete excision of an adjacent tumor. Functional imaging, together with an increasing number of genomic and other 'omic' biomarkers, has also given rise to an improved classification based on molecular signatures of tumors like glioblastoma multiforme that will facilitate the correspondence between type of glioma and choice of biologically tailored-to-patient therapy.     

An epidemiological perspective of personalized medicine: the Estonian experience

The Estonian Biobank and several other biobanks established over a decade ago are now starting to yield valuable longitudinal follow‐up data for large numbers of individuals. These samples have been used in hundreds of different genome‐wide association studies, resulting in the identification of reliable disease‐associated variants. The focus of genomic research has started to shift from identifying genetic and nongenetic risk factors associated with common complex diseases to understanding the underlying mechanisms of the diseases and suggesting novel targets for therapy. However, translation of findings from genomic research into medical practice is still lagging, mainly due to insufficient evidence of clinical validity and utility. In this review, we examine the different elements required for the implementation of personalized medicine based on genomic information. First, biobanks and genome centres are required and have been established for the high‐throughput genomic screening of large numbers of samples. Secondly, the combination of susceptibility alleles into polygenic risk scores has improved risk prediction of cardiovascular disease, breast cancer and several other diseases. Finally, national health information systems are being developed internationally, to combine data from electronic medical records from different sources, and also to gradually incorporate genomic information. We focus on the experience in Estonia, one of several countries with national goals towards more personalized health care based on genomic information, where the unique combination of elements required to accomplish this goal are already in place.     

Personalized Medicine for Diabetes: The Personalized Medicine for Diabetes Meeting Summary Report

Personalized medicine for diabetes is a potential method to specifically identify people who are at high risk of developing type 2 diabetes based on a combination of personal history, family history, physical examination, circulating biomarkers, and genome. High-risk individuals can then be referred to lifestyle programs for risk reduction and disease prevention. Using a personalized medicine approach, a patient with already-diagnosed type 2 diabetes can be treated individually based on information specific to that individual. The field of personalized medicine for diabetes is rapidly exploding. Diabetes Technology Society convened the Personalized Medicine for Diabetes (PMFD) Meeting March 19–20, 2009 in San Francisco. The meeting was funded through a contract from the US Air Force. Diabetes experts from the military, government, academic, and industry communities participated. The purpose was to reach a consensus about PMFD in type 2 diabetes to (a) establish screening programs, (b) diagnose cases at an early stage, and (c) monitor and treat the disease with specific measures. The group defined what a PMFD program should encompass, what the benefits and drawbacks of such a PMFD program would be, and how to overcome barriers. The group reached six conclusions related to the power of PMFD to improve care of type 2 diabetes by resulting in (1) better prediction, (2) better prophylactic interventions, (3) better treatments, and (4) decreased cardiovascular disease burden. Additional research is needed to demonstrate the benefits of this approach. The US Air Force is well positioned to conduct research and develop clinical programs in PMFD.     

Genomic medicine in non-small cell lung cancer: paving the path to personalized care

Lung cancer is the commonest cause of cancer-related mortality and non-small cell lung cancer (NSCLC) accounts for 80% of all lung cancer. The prognosis of NSCLC remains poor across all stages, despite advances in staging techniques and treatments. The findings of recent high-throughput mRNA microarray studies have shown potential in refining current NSCLC diagnosis, classification, prognosis and treatment paradigms. Emerging microarray studies of microRNA, DNA copy number and methylation profiles are also providing novel insights into the biology of NSCLC. Currently there are several challenges, such as the reproducibility and cost of microarray platforms that will need to be addressed prior to the implementation of these genomic technologies to routine thoracic oncology practice. In addition, genomic tests (such as prognosis and prediction gene expression signatures) will need to be validated in well designed prospective studies that aim to answer clinically relevant questions. If successful, the integration of microarray-based genomic information with existing clinicopathological models may enhance the ability of clinicians to match the most effective treatment to an individual patient. Such a strategy may improve survival and reduce treatment-related morbidity in NSCLC patients.     

Personalized microbiome‐based approaches to metabolic syndrome management and prevention

Personalized or precision medicine is a novel clinical approach targeted to the individual patient and based on integration of clinical, genetic, and environmental factors that define a patient uniquely from other individuals featuring similar clinical symptoms. Such a personalized medicine approach is increasingly applied for diagnosis, clinical stratification, and treatment of metabolic syndrome (MetS)‐associated risks and diseases, including obesity, type 2 diabetes, non‐alcoholic fatty liver disease, and their complications. One emerging factor that governs MetS manifestations is the microbiome, the composition, function, growth dynamics, associated metabolite profile and diverse effects of which on host immune and metabolic systems can all significantly affect metabolic homeostasis. Interindividual differences in microbiome composition and function, as well as personal variations in microbial‐derived products, pave the way towards microbiome‐based personalized medicine in treating MetS‐related diseases.