Massively parallel sequencing is emerging from research settings into clinical practice, helping the vision of precision medicine to become a reality. The most successful applications are using the ...tools of implementation science within the framework of the learning health-care system. This article examines the application of massively parallel sequencing to four clinical scenarios: pharmacogenomics, diagnostic testing, somatic testing for molecular tumor characterization, and population screening. For each application, it highlights an exemplar program to illustrate the enablers and challenges of implementation. International examples are also presented. These early lessons will allow other programs to account for these factors, helping to accelerate the implementation of precision medicine and health.
Applications of genomics to population screening are expanding in the United States and internationally. Many of these programs are being implemented in the context of healthcare systems, mostly in a ...clinical research setting, but there are some emerging examples of clinical models. This review examines these genomic population screening programs to identify common features and differences in screened conditions, genomic technology employed, approach to results disclosure, health outcomes, financial models, and sustainability. The diversity of approaches provides opportunities to learn and better understand the optimal approach to implementation based on the contextual setting.
Burnout is a long-term stress reaction marked by emotional exhaustion, depersonalization, and a lack of sense of personal accomplishment. Burnout in clinicians is receiving significant attention. ...Some have proposed that clinicians are experiencing symptoms of moral injury, defined as "perpetrating, failing to prevent, bearing witness to, or learning about acts that transgress deeply held moral beliefs and expectations." Current efforts to improve the electronic health record (EHR) have focused on improving the user experience to reduce burden that has been identified as a contributing factor to provider burnout. However, if EHRs are contributing to moral injury, improvements to user experience will not eliminate the effects on providers. Current research has not evaluated the risk for moral injury resulting from the use of EHRs. This Perspective reviews the differences between burnout and moral injury, discusses the implications for clinicians using EHRs, and highlights the need for research to better define the problem.
Big data, coupled with the use of advanced analytical approaches, such as artificial intelligence (AI), have the potential to improve medical outcomes and population health. Data that are routinely ...generated from, for example, electronic medical records and smart devices have become progressively easier and cheaper to collect, process, and analyze. In recent decades, this has prompted a substantial increase in biomedical research efforts outside traditional clinical trial settings. Despite the apparent enthusiasm of researchers, funders, and the media, evidence is scarce for successful implementation of products, algorithms, and services arising that make a real difference to clinical care. This article collection provides concrete examples of how "big data" can be used to advance healthcare and discusses some of the limitations and challenges encountered with this type of research. It primarily focuses on real-world data, such as electronic medical records and genomic medicine, considers new developments in AI and digital health, and discusses ethical considerations and issues related to data sharing. Overall, we remain positive that big data studies and associated new technologies will continue to guide novel, exciting research that will ultimately improve healthcare and medicine-but we are also realistic that concerns remain about privacy, equity, security, and benefit to all.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Reporting and sharing pharmacogenetic test results across clinical laboratories and electronic health records is a crucial step toward the implementation of clinical pharmacogenetics, but allele ...function and phenotype terms are not standardized. Our goal was to develop terms that can be broadly applied to characterize pharmacogenetic allele function and inferred phenotypes.
Terms currently used by genetic testing laboratories and in the literature were identified. The Clinical Pharmacogenetics Implementation Consortium (CPIC) used the Delphi method to obtain a consensus and agree on uniform terms among pharmacogenetic experts.
Experts with diverse involvement in at least one area of pharmacogenetics (clinicians, researchers, genetic testing laboratorians, pharmacogenetics implementers, and clinical informaticians; n = 58) participated. After completion of five surveys, a consensus (>70%) was reached with 90% of experts agreeing to the final sets of pharmacogenetic terms.
The proposed standardized pharmacogenetic terms will improve the understanding and interpretation of pharmacogenetic tests and reduce confusion by maintaining consistent nomenclature. These standard terms can also facilitate pharmacogenetic data sharing across diverse electronic health care record systems with clinical decision support.
In clinical exome and genome sequencing, there is a potential for the recognition and reporting of incidental or secondary findings unrelated to the indication for ordering the sequencing but of ...medical value for patient care. The American College of Medical Genetics and Genomics (ACMG) recently published a policy statement on clinical sequencing that emphasized the importance of alerting the patient to the possibility of such results in pretest patient discussions, clinical testing, and reporting of results. The ACMG appointed a Working Group on Incidental Findings in Clinical Exome and Genome Sequencing to make recommendations about responsible management of incidental findings when patients undergo exome or genome sequencing. This Working Group conducted a year-long consensus process, including an open forum at the 2012 Annual Meeting and review by outside experts, and produced recommendations that have been approved by the ACMG Board. Specific and detailed recommendations, and the background and rationale for these recommendations, are described herein. The ACMG recommends that laboratories performing clinical sequencing seek and report mutations of the specified classes or types in the genes listed here. This evaluation and reporting should be performed for all clinical germline (constitutional) exome and genome sequencing, including the "normal" of tumor-normal subtractive analyses in all subjects, irrespective of age but excluding fetal samples. We recognize that there are insufficient data on penetrance and clinical utility to fully support these recommendations, and we encourage the creation of an ongoing process for updating these recommendations at least annually as further data are collected.
Animal traits develop through the expression and action of numerous regulatory and realizator genes that comprise a gene regulatory network (GRN). For each GRN, its underlying patterns of gene ...expression are controlled by cis-regulatory elements (CREs) that bind activating and repressing transcription factors. These interactions drive cell-type and developmental stage-specific transcriptional activation or repression. Most GRNs remain incompletely mapped, and a major barrier to this daunting task is CRE identification. Here, we used an in silico method to identify predicted CREs (pCREs) that comprise the GRN which governs sex-specific pigmentation of Drosophila melanogaster. Through in vivo assays, we demonstrate that many pCREs activate expression in the correct cell-type and developmental stage. We employed genome editing to demonstrate that two CREs control the pupal abdomen expression of trithorax, whose function is required for the dimorphic phenotype. Surprisingly, trithorax had no detectable effect on this GRN's key trans-regulators, but shapes the sex-specific expression of two realizator genes. Comparison of sequences orthologous to these CREs supports an evolutionary scenario where these trithorax CREs predated the origin of the dimorphic trait. Collectively, this study demonstrates how in silico approaches can shed novel insights on the GRN basis for a trait's development and evolution.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
8.
Pharmacogenomics Roden, Dan M; McLeod, Howard L; Relling, Mary V ...
Lancet,
08/2019, Letnik:
394, Številka:
10197
Journal Article
Recenzirano
Odprti dostop
Genomic medicine, which uses DNA variation to individualise and improve human health, is the subject of this Series of papers. The idea that genetic variation can be used to individualise drug ...therapy—the topic addressed here—is often viewed as within reach for genomic medicine. We have reviewed general mechanisms underlying variability in drug action, the role of genetic variation in mediating beneficial and adverse effects through variable drug concentrations (pharmacokinetics) and drug actions (pharmacodynamics), available data from clinical trials, and ongoing efforts to implement pharmacogenetics in clinical practice.
The epidemiology and natural history of pediatric primary sclerosing cholangitis (PSC), autoimmune sclerosing cholangitis (ASC), and autoimmune hepatitis (AIH) are not well characterized. Using ...multiple, overlapping search strategies followed by a detailed records review, we identified all cases of pediatric PSC, ASC, AIH, and inflammatory bowel disease (IBD) in a geographically isolated region of the United States. We identified 607 cases of IBD, 29 cases of PSC, 12 cases of ASC, and 44 cases of AIH. The mean age at diagnosis was 13.0 years for PSC, 11.3 years for ASC, and 9.8 years for AIH. The incidence and prevalence of PSC, ASC, and AIH were 0.2 and 1.5 cases, 0.1 and 0.6 cases, and 0.4 and 3.0 cases per 100,000 children, respectively. The mean duration of follow‐up was 5.9 years. The probability of developing complicated liver disease within 5 years of the diagnosis of liver disease was 37% 95% confidence interval (CI) = 21%‐58% for PSC, 25% (95% CI = 7%‐70%) for ASC, and 15% (95% CI = 7%‐33%) for AIH. The 5‐year survival rates with the native liver were 78% (95% CI = 54%‐91%) for PSC, 90% (95% CI = 47%‐99%) for ASC, and 87% (95% CI = 71%‐95%) for AIH. Cholangiocarcinoma developed in 2 of the 29 PSC patients (6.9%). PSC occurred in 9.9% of patients with ulcerative colitis (UC) and in 0.6% of patients with Crohn's disease (CD). ASC occurred in 2.3% of UC patients and 0.9% of CD patients. AIH occurred in 0.4% of UC patients and in 0.3% of CD patients. Liver disease occurred in 39 of 607 IBD patients (6.4%) overall. Conclusion: Immune‐mediated liver diseases are important sources of morbidity in children. Using a population‐based design, this study quantifies the burden and natural history of immune‐mediated liver disease in children. (Hepatology 2013;58:1392–1400)
Health care delivery is increasingly influenced by the emerging concepts of precision health and the learning health care system. Although not synonymous with precision health, genomics is a key ...enabler of individualized care. Delivering patient-centered, genomics-informed care based on individual-level data in the current national landscape of health care delivery is a daunting challenge. Problems to overcome include data generation, analysis, storage, and transfer; knowledge management and representation for patients and providers at the point of care; process management; and outcomes definition, collection, and analysis. Development, testing, and implementation of a genomics-informed program requires multidisciplinary collaboration and building the concepts of precision health into a multilevel implementation framework. Using the principles of a learning health care system provides a promising solution. This article describes the implementation of population-based genomic medicine in an integrated learning health care system-a working example of a precision health program.
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