Project description:Alzheimer's disease (AD) is the leading cause of dementia and sixth cause of death in elderly adults. AD poses a huge economic burden on society and constitutes an unprecedented challenge for caregivers and families affected. Aging of the population is projected to drastically aggravate the situation in the near future. To date, no therapy is available to prevent or ameliorate the disease. Moreover, several clinical trials for promising therapeutic agents have failed. Lack of supporting biomarker data for pre-symptomatic enrollment and inaccurate stratification of patients based on genetic heterogeneity appear to be contributing factors to this lack of success. Recently, the treatment of cancer has seen enormous advances based on the personalized genetics and biomarkers of the individual patient, forming the foundation of precision medicine for cancer. Likewise, technological progress in AD biomarker research promises the availability of reliable assays for pathology staging on a routine basis relatively soon. Moreover, tremendous achievements in AD genetics and high-throughput genotyping technology allow identification of predisposing risk alleles accurately and on a large scale. Finally, availability of electronic health records (EHR) promises the opportunity to integrate biomarker, genomic and clinical data efficiently. Together, these advances will form the basis of precision medicine for AD.
Project description:Early identification of coronary atherosclerotic pathogenic mechanisms is useful for predicting the risk of coronary heart disease (CHD) and future cardiac events. Epigenome changes may clarify a significant fraction of this "missing hereditability", thus offering novel potential biomarkers for prevention and care of CHD. The rapidly growing disciplines of systems biology and network science are now poised to meet the fields of precision medicine and personalized therapy. Network medicine integrates standard clinical recording and non-invasive, advanced cardiac imaging tools with epigenetics into deep learning for in-depth CHD molecular phenotyping. This approach could potentially explore developing novel drugs from natural compounds (i.e. polyphenols, folic acid) and repurposing current drugs, such as statins and metformin. Several clinical trials have exploited epigenetic tags and epigenetic sensitive drugs both in primary and secondary prevention. Due to their stability in plasma and easiness of detection, many ongoing clinical trials are focused on the evaluation of circulating miRNAs (e.g. miR-8059 and miR-320a) in blood, in association with imaging parameters such as coronary calcifications and stenosis degree detected by coronary computed tomography angiography (CCTA), or functional parameters provided by FFR/CT and PET/CT. Although epigenetic modifications have also been prioritized through network based approaches, the whole set of molecular interactions (interactome) in CHD is still under investigation for primary prevention strategies.
Project description:A large fraction of early-onset chronic kidney disease (CKD) is known to be monogenic in origin. To date, ∼450 monogenic (synonymous with single-gene disorders) genes, if mutated, are known to cause CKD, explaining ∼30% of cases in pediatric cohorts and ∼5-30% in adult cohorts. However, there are likely hundreds of additional monogenic nephropathy genes that may be revealed by whole-exome or -genome sequencing. Although the discovery of novel CKD-causing genes has accelerated, significant challenges in adult populations remain due to broad phenotypic heterogeneity together with variable expressivity, incomplete penetrance or age-related penetrance of these genes. Here we give an overview of the currently known monogenic causes for human CKD. We also describe how next-generation sequencing facilitates rapid molecular genetic diagnostics in individuals with suspected genetic kidney disease. In an era of precision medicine, understanding the utility of genetic testing in individuals with a suspected inherited nephropathy has important diagnostic and prognostic implications. Detection of monogenic causes of CKD permits molecular genetic diagnosis for patients and families and opens avenues for personalized treatment strategies for CKD. As an example, detection of a pathogenic mutation in the gene HNF1B not only allows for the formal diagnosis of CKD, but can also facilitate screening for additional extrarenal manifestations of disease, such as maturity-onset diabetes of youth, subclinical abnormal liver function tests, neonatal cholestasis and pancreatic hypoplasia. It also provides the driving force towards a better understanding of disease pathogenesis, potentially facilitating targeted new therapies for individuals with CKD.
Project description:Most physicians believe they practiced personalized medicine prior to the genomics era that followed the sequencing of the human genome. The focus of personalized medicine has been primarily genomic medicine, wherein it is hoped that the nucleotide dissimilarities among different individuals would provide clinicians with more precise understanding of physiology, more refined diagnoses, better disease risk assessment, earlier detection and monitoring, and tailored treatments to the individual patient. However, to date, the "genomic bench" has not worked itself to the clinical thrombosis bedside. In fact, traditional plasma-based hemostasis-thrombosis laboratory testing, by assessing functional pathways of coagulation, may better help manage venous thrombotic disease than a single DNA variant with a small effect size. There are some new and exciting discoveries in the genetics of platelet reactivity pertaining to atherothrombotic disease. Despite a plethora of genetic/genomic data on platelet reactivity, there are relatively little actionable pharmacogenetic data with antiplatelet agents. Nevertheless, it is crucial for genome-wide DNA/RNA sequencing to continue in research settings for causal gene discovery, pharmacogenetic purposes, and gene-gene and gene-environment interactions. The potential of genomics to advance medicine will require integration of personal data that are obtained in the patient history: environmental exposures, diet, social data, etc. Furthermore, without the ritual of obtaining this information, we will have depersonalized medicine, which lacks the precision needed for the research required to eventually incorporate genomics into routine, optimal, and value-added clinical care.
Project description:Chronic lymphocytic leukemia (CLL) is the most common hematologic malignancy in the Western Hemisphere. Despite advances in research and the development of effective treatment regimens, CLL is still largely an incurable disease. Although several prognostic factors have been identified in recent years, most of the new prognostic factors are not utilized, and treatment decisions are still based on clinical staging and limited use of cytogenetic analysis. Patients with advanced disease are treated at diagnosis, whereas others, regardless of their prognostic indicators, are offered treatment only at disease progression. Furthermore, treatment guidelines for elderly or "unfit" patients are unavailable because most CLL trials have included mostly younger, healthier patients. Given theheterogeneity of the clinical manifestations and prognosis of CLL, patients are likely to benefit from a personalized therapeutic approach. Recent advances in CLL pathobiology research, the use of high-throughput technologies, and most importantly, the introduction of novel targeted therapies with high efficacy and low toxicity are currently transforming the treatment of CLL. A personalized approach that includes early intervention in selected patients with CLL is likely to bring physicians closer to the goal of attaining cures in most patients with CLL.
Project description:Pancreatic cancer (PC) is a recalcitrant disease characterized by high incidence and poor prognosis. The extremely complex genomic landscape of PC has a deep influence on cultivating a tumor microenvironment, resulting in the promotion of tumor growth, drug resistance, and immune escape mechanisms. Despite outstanding progress in personalized medicine achieved for many types of cancer, chemotherapy still represents the mainstay of treatment for PC. Olaparib was the first agent to demonstrate a significant benefit in a biomarker-selected population, opening the doors for a personalized approach. Despite the failure of a large number of studies testing targeted agents or immunotherapy to demonstrate benefits over standard chemotherapy regimens, some interesting agents, alone or in combination with other drugs, have achieved promising results. A wide spectrum of therapeutic strategies, including immune-checkpoint inhibitors tyrosine kinase inhibitors and agents targeting metabolic pathways or the tumor microenvironment, is currently under investigation. In this review, we aim to provide a comprehensive overview of the current landscape and future directions of personalized medicine for patients affected by PC.
Project description:Alzheimer’s disease (AD) is a major problem of health and disability, with a relevant economic impact on society (e.g., €177 billion in Europe). Despite important advances in pathogenesis, diagnosis, and treatment, The primary causes of AD remain elusive, accurate biomarkers are not well characterized, and available pharmacological treatments are not cost-effective. As a complex disorder, AD is polygenic and multifactorial: hundreds of defective genes distributed across the human genome may contribute to its pathogenesis (with the participation of diverse environmental factors, cerebrovascular dysfunction, and epigenetic phenomena) and lead to amyloid deposition, neurofibrillary tangle formation, and premature neuronal death. Future perspectives for the global management of AD predict that structural and functional genomics and proteomics may help in the search for reliable biomarkers, and that pharmacogenomics may be an option in optimizing drug development and therapeutics.
Project description:Diabetes mellitus affects approximately 382 million individuals worldwide and is a leading cause of morbidity and mortality. Over 40 and nearly 80 genetic loci influencing susceptibility to type 1 and type 2 diabetes, respectively, have been identified. In addition, there is emerging evidence that some genetic variants help to predict response to treatment. Other variants confer apparent protection from diabetes or its complications and may lead to development of novel treatment approaches. Currently, there is clear clinical utility to genetic testing to find the at least 1% of diabetic individuals who have monogenic diabetes (e.g., maturity-onset diabetes of the young and KATP channel neonatal diabetes). Diagnosing many of these currently underdiagnosed types of diabetes enables personalized treatment, resulting in improved and less invasive glucose control, better prediction of prognosis, and enhanced familial risk assessment. Efforts to enhance the rate of detection, diagnosis, and personalized treatment of individuals with monogenic diabetes should set the stage for effective clinical translation of current genetic, pharmacogenetic, and pharmacogenomic research of more complex forms of diabetes.
Project description:The devastating consequences of tobacco smoking for individuals and societies motivate studies to identify and understand the biological pathways that drive smoking behaviors, so that more effective preventions and treatments can be developed. Cigarette smokers respond to nicotine in different ways, with a small number of smokers remaining lifelong low-level smokers who never exhibit any symptoms of dependence, and a larger group becoming nicotine dependent. Whether or not a smoker transitions to nicotine dependence has clear genetic contributions, and variants in the genes encoding the α5-α3-β4 nicotinic receptor subunits most strongly contribute to differences in the risk for developing nicotine dependence among smokers. More recent work reveals a differential response to pharmacologic treatment for smoking cessation based on these same genetic variants in the α5-α3-β4 nicotinic receptor gene cluster. We anticipate a continuing acceleration of the translation of genetic discoveries into more successful treatment for smoking cessation. Given that over 400,000 people in the United States and over 5 million people world-wide die each year from smoking related illnesses, an improved understanding of the mechanisms underlying smoking behavior and smoking cessation must be a high public health priority so we can best intervene at both the public health level and the individual level. This article is part of a Special Issue entitled 'NIDA 40th Anniversary Issue'.
Project description:Ménière's disease (MD) represents a heterogeneous group of relatively rare disorders with three core symptoms: episodic vertigo, tinnitus, and sensorineural hearing loss involving 125 to 2,000 Hz frequencies. The majority of cases are considered sporadic, although familial aggregation has been recognized in European and Korean populations, and the search for familial MD genes has been elusive until the last few years. Detailed phenotyping and cluster analyses have found several clinical predictors for different subgroups of patients, which may indicate different mechanisms, including genetic and immune factors. The genes associated with familial MD are COCH, FAM136A, DTNA, PRKCB, SEMA3D, and DPT. At least two mechanisms have been involved in MD: (a) a pro-inflammatory immune response mediated by interleukin-1 beta (IL-1?), tumor necrosis factor alpha (TNF?), and IL-6, and (b) a nuclear factor-kappa B (NF-?B)-mediated inflammation in the carriers of the single-nucleotide variant rs4947296. It is conceivable that microbial antigens trigger inflammation with release of pro-inflammatory cytokines at different sites within the cochlea, such as the endolymphatic sac, the stria vascularis, or the spiral ligament, leading to fluid imbalance with an accumulation of endolymph. Computational integration of clinical and "omics" data eventually should transform the management of MD from "one pill fits all" to precise patient stratification and a personalized approach. This article lays out a proposal for an algorithm for the genetic diagnosis of MD. This approach will facilitate the identification of new molecular targets for individualized treatment, including immunosuppressant and gene therapy, in the near future.