Project description:Population-attributable risk models estimate that up to one-third of Alzheimer's disease (AD) cases may be preventable through risk factor modification. The field of AD prevention has largely focused on addressing these factors through universal risk reduction strategies for the general population. However, targeting these strategies in a clinical precision medicine fashion, including the use of genetic risk factors, allows for potentially greater impact on AD risk reduction. Apolipoprotein E (APOE), and specifically the APOE ?4 variant, is one of the most well-established genetic influencers on late-onset AD risk. In this review, we evaluate the impact of APOE ?4 carrier status on AD prevention interventions, including lifestyle, nutrigenomic, pharmacogenomic, AD comorbidities, and other biological and behavioral considerations. Using a clinical precision medicine strategy that incorporates APOE ?4 carrier status may provide a highly targeted and distinct approach to AD prevention with greater potential for success.
Project description:Precision medicine is an emerging approach to disease treatment and prevention that considers variability in patient genes, environment, and lifestyle. However, little has been written about how such research impacts emergency care. Recent advances in analytical techniques have made it possible to characterize patients in a more comprehensive and sophisticated fashion at the molecular level, promising highly individualized diagnosis and treatment. Among these techniques are various systematic molecular phenotyping analyses (e.g., genomics, transcriptomics, proteomics, and metabolomics). Although a number of emergency physicians use such techniques in their research, widespread discussion of these approaches has been lacking in the emergency care literature and many emergency physicians may be unfamiliar with them. In this article, we briefly review the underpinnings of such studies, note how they already impact acute care, discuss areas in which they might soon be applied, and identify challenges in translation to the emergency department (ED). While such techniques hold much promise, it is unclear whether the obstacles to translating their findings to the ED will be overcome in the near future. Such obstacles include validation, cost, turnaround time, user interface, decision support, standardization, and adoption by end-users.
Project description:ObjectiveA key component for precision medicine is a good prediction algorithm for patients' response to treatments. We aim to implement machine learning (ML) algorithms into the response-adaptive randomization (RAR) design and improve the treatment outcomes.Materials and methodsWe incorporated 9 ML algorithms to model the relationship of patient responses and biomarkers in clinical trial design. Such a model predicted the response rate of each treatment for each new patient and provide guidance for treatment assignment. Realizing that no single method may fit all trials well, we also built an ensemble of these 9 methods. We evaluated their performance through quantifying the benefits for trial participants, such as the overall response rate and the percentage of patients who receive their optimal treatments.ResultsSimulation studies showed that the adoption of ML methods resulted in more personalized optimal treatment assignments and higher overall response rates among trial participants. Compared with each individual ML method, the ensemble approach achieved the highest response rate and assigned the largest percentage of patients to their optimal treatments. For the real-world study, we successfully showed the potential improvements if the proposed design had been implemented in the study.ConclusionIn summary, the ML-based RAR design is a promising approach for assigning more patients to their personalized effective treatments, which makes the clinical trial more ethical and appealing. These features are especially desirable for late-stage cancer patients who have failed all the Food and Drug Administration (FDA)-approved treatment options and only can get new treatments through clinical trials.
Project description:Precision medicine is revolutionising patient care in cancer. As more knowledge is gained about the impact of specific genetic lesions on diagnosis, prognosis and treatment response, diagnostic precision and the possibility for optimal individual treatment choice have improved. Identification of hallmark genetic aberrations such as the BCR::ABL1 gene fusion in chronic myeloid leukaemia (CML) led to the rapid development of efficient targeted therapy and molecular follow-up, vastly improving survival for patients with CML during recent decades. The assessment of translocations, copy number changes and point mutations are crucial for the diagnosis and risk stratification of acute myeloid leukaemia and myelodysplastic syndromes. Still, the often heterogeneous and complex genetic landscape of haematological malignancies presents several challenges for the implementation of precision medicine to guide diagnosis, prognosis and treatment choice. This review provides an introduction and overview of the important molecular characteristics and methods currently applied in clinical practice to guide clinical decision making in haematological malignancies of myeloid and lymphoid origin. Further, experimental ways to guide the choice of targeted therapy for refractory patients are reviewed, such as functional precision medicine using drug profiling. An example of the use of pipeline studies where the treatment is chosen according to the molecular characteristics in rare solid malignancies is also provided. Finally, the future opportunities and remaining challenges of precision medicine in the real world are discussed.
Project description:AimDevelop and apply a comprehensive and accurate next-generation sequencing based assay to help clinicians to match oncology patients to therapies.Materials & methodsThe performance of the CANCERPLEX® assay was assessed using DNA from well-characterized routine clinical formalin-fixed paraffin-embedded (FFPE) specimens and cell lines.ResultsThe maximum sensitivity of the assay is 99.5% and its accuracy is virtually 100% for detecting somatic alterations with an allele fraction of as low as 10%. Clinically actionable variants were identified in 93% of patients (930 of 1000) who underwent testing.ConclusionThe test's capacity to determine all of the critical genetic changes, tumor mutation burden, microsatellite instability status and viral associations has important ramifications on clinical decision support strategies, including identification of patients who are likely to benefit from immune checkpoint blockage therapies.
Project description:One of the main challenges for healthcare systems is the increasing prevalence of neurodegenerative pathologies together with the rapidly aging populations. The enormous progresses made in the field of biomedical research and informatics have been crucial for improving the knowledge of how genes, epigenetic modifications, aging, nutrition, drugs and microbiome impact health and disease. In fact, the availability of high technology and computational facilities for large-scale analysis enabled a deeper investigation of neurodegenerative disorders, providing a more comprehensive overview of disease and encouraging the development of a precision medicine approach for these pathologies. On this subject, the creation of collaborative networks among medical centers, research institutes and highly qualified specialists can be decisive for moving the precision medicine from the bench to the bedside. To this purpose, the present review has been thought to discuss the main components which may be part of precise and personalized treatment programs applied to neurodegenerative disorders. Parkinson Disease will be taken as an example to understand how precision medicine approach can be clinically useful and provide substantial benefit to patients. In this perspective, the realization of web-based networks can be decisive for the implementation of precision medicine strategies across different specialized centers as well as for supporting clinical/therapeutical decisions and promoting a more preventive and participative medicine for neurodegenerative disorders. These collaborative networks are essentially addressed to find innovative, sustainable and effective strategies able to provide optimal and safer therapies, discriminate at risk individuals, identify patients at preclinical or early stage of disease, set-up individualized and preventative strategies for improving prognosis and patient's quality of life.
Project description:Stroke remains one of the leading causes of long-term disability and mortality despite recent advances in acute thrombolytic therapies. In fact, the global lifetime risk of stroke in adults over the age of 25 is approximately 25%, with 24.9 million cases of ischemic stroke and 18.7 million cases of hemorrhagic stroke reported in 2015. One of the main challenges in developing effective new acute therapeutics and enhanced long-term interventions for stroke recovery is the heterogeneity of stroke, including etiology, comorbidities, and lifestyle factors that uniquely affect each individual stroke survivor. In this comprehensive review, we propose that future biomarker studies can be designed to support precision medicine therapeutic interventions after stroke. The current challenges in defining ideal biomarkers for stroke are highlighted, including consideration of disease course, age, lifestyle factors, and subtypes of stroke. This overview of current clinical trials includes biomarker collection, and concludes with an example of biomarker design for aneurysmal subarachnoid hemorrhage. With the advent of "-omics" studies, neuroimaging, big data, and precision medicine, well-designed stroke biomarker trials will greatly advance the treatment of a disease that affects millions globally every year.
Project description:Precision Medicine emerges from the genomic paradigm of health and disease. For precise molecular diagnoses of genetic diseases, we must analyze the Whole Exome (WES) or the Whole Genome (WGS). By not needing exon capture, WGS is more powerful to detect single nucleotide variants and copy number variants. In healthy individuals, we can observe monogenic highly penetrant variants, which may be causally responsible for diseases, and also susceptibility variants, associated with common polygenic diseases. But there is the major problem of penetrance. Thus, there is the question of whether it is worthwhile to perform WGS in all healthy individuals as a step towards Precision Medicine. The genetic architecture of disease is consistent with the fact that they are all polygenic. Moreover, ancestry adds another layer of complexity. We are now capable of obtaining Polygenic Risk Scores for all complex diseases using only data from new generation sequencing. Yet, review of available evidence does not at present favor the idea that WGS analyses are sufficiently developed to allow reliable predictions of the risk components for monogenic and polygenic hereditary diseases in healthy individuals. Probably, it is still better for WGS to remain reserved for the diagnosis of pathogenic variants of Mendelian diseases.
Project description:Despite the progress made in understanding the biology of autism spectrum disorder (ASD), effective biological interventions for the core symptoms remain elusive. Because of the etiological heterogeneity of ASD, identification of a "one-size-fits-all" treatment approach will likely continue to be challenging. A meeting was convened at the University of Missouri and the Thompson Center to discuss strategies for stratifying patients with ASD for the purpose of moving toward precision medicine. The "white paper" presented here articulates the challenges involved and provides suggestions for future solutions.
Project description:BackgroundAngiotensin-converting enzyme (ACE) metabolizes a number of important peptides participating in blood pressure regulation and vascular remodeling. Elevated ACE expression in tissues (which is generally reflected by ACE in blood) is associated with increased risk of cardiovascular diseases. Elevated ACE in blood is also a marker for granulomatous diseases.MethodsWe applied our novel approach-ACE phenotyping-to characterize serum ACE in 300 unrelated patients and to establish normal values for ACE levels. ACE phenotyping includes (a) determination of ACE activity with 2 substrates (Z-Phe-His-Leu [ZPHL] and Hip-His-Leu [HHL]), (b) calculation of a ratio for hydrolysis of ZPHL and HHL, and (c) quantification of ACE immunoreactive protein levels and ACE conformation with a set of monoclonal antibodies (mAbs) to ACE.ResultsOnly a combination of ACE activity determination with 2 substrates and quantification of the amount of ACE immunoreactive protein with mAbs 1G12 and 9B9 allows for the unequivocal detection of the presence of ACE inhibitors in the blood. After excluding such subjects, we were able to establish normal values of ACE in healthy populations: 50%-150% from control pooled serum. This ACE phenotyping approach in screening format with special attention to outliers can also identify patients with various mutations in ACE and may help to identify the as yet unknown ACE secretase or other mechanistic details of precise regulation of ACE expression.ConclusionsACE phenotyping is a promising new approach with potential clinical significance to advance precision medicine screening techniques by establishing different risk groups based on ACE phenotype.