Personalized medicine. Closing the gap between knowledge and clinical practice

Genetic Polymorphism in Angiotensinogen and Its Association with Cardiometabolic Diseases

Angiotensinogen (AGT) is one of the most significant enzymes of the renin-angiotensin-aldosterone system (RAAS) which is involved in the regulation and maintenance of blood pressure. AGT is involved in the production of angiotensin I which is then converted into angiotensin II that leads to renal homeostasis. However, various genetic polymorphisms in AGT have been discovered in recent times which have shown an association with various diseases. Genetic polymorphism increases the level of circulating AGT in blood which exaggerates the effects produced by AGT. The associated diseases occur due to various effects produced by increased AGT levels. Several cardiovascular diseases including myocardial infarction, coronary heart disease, heart failure, hypertrophy, etc. are associated with AGT polymorphism. Other diseases such as depression, obesity, diabetic nephropathy, pre-eclampsia, and liver injury are also associated with some variants of AGT gene. The most common variants of AGT polymorphism are M235T and T174M. The two variants are associated with many diseases. Some other variants such as G-217A, A-6G, A-20C and G-152A, are also present but they are not as significant as that of M235T and T174M variants. These variants increase the level of circulating AGT and are associated with prevalence of different diseases. These diseases occur through various pathological pathways, but the initial reason remains the same, i.e., increased level of AGT in the blood. In this article, we have majorly focused on how genetic polymorphism of different variants of AGT gene is associated with the prevalence of different diseases.

3D printed oral solid dosage form: Modified release and improved solubility

Oral solid dosage form is currently the most common used form of drug. 3D Printing, also known as additive manufacturing (AM), can quickly print customized and individualized oral solid dosage form on demand. Compared with the traditional tablet manufacturing process, 3D Printing has many advantages. By rationally selecting the formulation composition and cleverly designing the printing structure, 3D printing can improve the solubility of the drug and achieve precise modify of the drug release. 3D printed oral solid dosage form, however, still has problems such as limitations in formulation selection. And the selection process of the formulation lacks scientificity and standardization. Structural design of some 3D printing approaches is relatively scarce. This article reviews the formulation selection and structure design of 3D printed oral solid dosage form, providing more ideas for achieving modified drug release and solubility improvement of 3D printed oral solid dosage form through more scientific and extensive formulation selection and more sophisticated structural design.

Endothelial Damage in Sepsis: The Importance of Systems Biology

The early diagnosis and appropriate stratification of sepsis continues to be one of the most important challenges in modern medicine. Single isolated biomarkers have not been enough to improve diagnostic and prognostic strategies and to progress toward therapeutic goals. The information generated by the human genome project has allowed a more holistic approach to the problem. The integration of genomics, transcriptomics, proteomics and metabolomics in sepsis has allowed us to progress in the knowledge of new pathways which are pathophysiologically involved in this disease. Thus, we have understood the importance of and complex interaction between the inflammatory response and the endothelium. Understanding the role of important parts of the microcirculation, such as the endothelial glycocalyx and its interaction with the inflammatory response, has provided early recognition elements for clinical practice that allow the rational use of traditional medical interventions in sepsis. This comprehensive approach, which differs from the classical mechanistic approach, uses systems biology to increase the diagnostic and prognostic spectrum of endothelial damage biomarkers in sepsis, and to provide information on new pathways involved in the pathophysiology of the disease. This, in turn, provides tools for perfecting traditional medical interventions, using them at the appropriate times according to the disease's pathophysiological context, while at the same time discovering new and improved therapeutic alternatives. We have the challenge of transferring this ideal scenario to our daily clinical practice to improve our patients' care. The purpose of this article is to provide a general description of the importance of systems biology in integrating the complex interaction between the endothelium and the inflammatory response in sepsis.

New insights into the taxonomy of autoimmune diseases based on polyautoimmunity

OBJECTIVE

The clinical coexistence of two or more autoimmune diseases (ADs) fulfilling classification criteria is termed "overt polyautoimmunity" (PolyA), whereas the presence of autoantibodies unrelated to an index AD, without clinical criteria fulfillment, is known as "latent PolyA". We aimed to explore a new taxonomy of ADs based on PolyA.

METHODS

In a cross-sectional study of 292 subjects, we evaluated the presence of PolyA in 146, 45, 29, 17, and 17 patients with rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), Sjögren's syndrome (SS), autoimmune thyroid disease (AITD) and systemic sclerosis (SSc), respectively, and 38 healthy controls. Clinical assessment, autoantibody profile (by autoantigen array chip), lymphocytes immunophenotype and cytokine profile (by flow cytometry) were evaluated simultaneously. A mixed cluster methodology was used to classify ADs.

RESULTS

Latent PolyA was more frequent than overt PolyA, ranging from 69.9% in RA to 100% in SSc. Nevertheless, both latent and overt PolyA clustered together. Over-expressed IgG autoantibodies were found to be hallmarks for the identification of index ADs. The combination of autoantibodies allowed high accuracy in the classification of ADs. Three well-defined clusters based on PolyA were observed with distinctive clinical and immunological phenotypes.

CONCLUSIONS

This proof-of-concept study indicates that ADs can be classified according to PolyA. PolyA should be considered in all studies dealing with ADs, including epidemiological, genetic, and clinical trials.

Personalized, Predictive, Participatory, Precision, and Preventive (P5) Medicine in Rotator Cuff Tears

Rotator cuff (RC) disease is a common musculoskeletal disorder of the shoulder entailing pain, with reduced functionality and quality of life. The main objective of this study was to present a perspective of the current scientific evidence about personalized, predictive, participatory, precision, and preventive approaches in the management of RC diseases. The personalized, predictive, participatory, precision and preventive (P5) medicine model is an interdisciplinary and multidisciplinary approach that will provide researchers and clinicians with a comprehensive patrimony of knowledge in the management of RC diseases. The ability to define genetic predispositions in conjunction with the evaluation of lifestyle and environmental factors may boost the tailoring of diagnosis and therapy in patients suffering from RC diseases.

Personalized Healthcare: The Importance of Patients' Rights in Clinical Practice from the Perspective of Nursing Students in Poland, Spain and Slovakia-A Cross-Sectional Study

Background: This study aimed to define the role and importance of patients’ rights in personalized healthcare from the perspective of nursing students in Poland, Spain and Slovakia. Methods: The research was carried out by means of a diagnostic survey, using the survey technique, with the participation of 1002 nursing students attending a full-time undergraduate study program at three European countries. The “Patients’ rights” questionnaire was used as a research tool. The average age of students was 21.6 years (±3.4). The empirical material collected was subjected to a statistical analysis. Results: The study demonstrated that 72.1% of nursing students from Spain, 51.2% from Poland and 38.5% from Slovakia believe that patients’ rights are respected at a good level in their country. Significant intergroup differences (F = 67.43; p < 0.0001) were observed in the self-assessment of students’ knowledge of patients’ rights. The highest average values were obtained by students from Spain (3.54 ± 0.92), while 35.9% of students from Slovakia and 25.5% from Poland were quite critical and pointed to their low level of knowledge of patients’ rights in their self-assessment. When ranking patients’ rights related to respecting dignity, students from Spain obtained much higher average values (4.37 ± 0.92) than students from the other two countries. Conclusions: The level of students’ knowledge of patients’ rights and the respect for patients’ rights by medical personnel is, in the opinion of the respondents, quite diverse and requires in-depth educational activities among nursing students at the university level in respective countries.

Challenges and Future Prospects of Precision Medicine in Psychiatry

Precision medicine is increasingly recognized as a promising approach to improve disease treatment, taking into consideration the individual clinical and biological characteristics shared by specific subgroups of patients. In specific fields such as oncology and hematology, precision medicine has already started to be implemented in the clinical setting and molecular testing is routinely used to select treatments with higher efficacy and reduced adverse effects. The application of precision medicine in psychiatry is still in its early phases. However, there are already examples of predictive models based on clinical data or combinations of clinical, neuroimaging and biological data. While the power of single clinical predictors would remain inadequate if analyzed only with traditional statistical approaches, these predictors are now increasingly used to impute machine learning models that can have adequate accuracy even in the presence of relatively small sample size. These models have started to be applied to disentangle relevant clinical questions that could lead to a more effective management of psychiatric disorders, such as prediction of response to the mood stabilizer lithium, resistance to antidepressants in major depressive disorder or stratification of the risk and outcome prediction in schizophrenia. In this narrative review, we summarized the most important findings in precision medicine in psychiatry based on studies that constructed machine learning models using clinical, neuroimaging and/or biological data. Limitations and barriers to the implementation of precision psychiatry in the clinical setting, as well as possible solutions and future perspectives, will be presented.

Precision medicine in the care of rheumatoid arthritis: Focus on prediction and prevention of future clinically-apparent disease

There is an emerging understanding that an individual's risk for future rheumatoid arthritis (RA) can be determined using a combination of factors while they are still in a state where clinically-apparent inflammatory arthritis (IA) is not yet present. Indeed, this concept has underpinned several completed and ongoing prevention trials in RA. Importantly, risk factors can be divided into modifiable (e.g. smoking, exercise, dental care and diet) and non-modifiable factors (e.g. genetics, sex, age). In addition, there are now several biomarkers including autoantibodies, inflammatory markers and imaging techniques that are highly predictive of future clinically-apparent IA/RA. Although none of the prevention studies have yet provided major breakthroughs, several of them have provided valuable insights that can help to improve the design of future clinical trials and enable RA prevention. In aggregate, these findings suggest that the most accurate disease prediction models will require the combination of demographic and clinical information, biomarkers and potentially medical imaging data to identify individuals for intervention. This review summarizes some of the key aspects around precision medicine in RA with special focus on disease prediction and prevention.

How is the trade-off between adverse selection and discrimination risk affected by genetic testing? Theory and experiment

We develop a theoretical analysis of two widely used regulations of genetic tests, Disclosure Duty and Consent Law, and we run an experiment in order to shed light on both the take-up rate of genetic testing and on the comparison of policyholders' welfare under the two regulations. Disclosure duty forces individuals to reveal their test results to insurers, exposing them to a discrimination risk. Consent Law allows them to hide any detrimental information, resulting in adverse selection. The experiment results in much lower genetic tests take-up rates with Disclosure Duty than with Consent Law, showing that subjects are very sensitive to the discrimination risk. Under Consent Law, take-up rates increase with the adverse selection intensity. A decrease in the test cost, and in adverse selection intensity, both make it more likely that Consent Law is preferred to Disclosure Duty.

Metabolites of type I, II, III, and IV collagen may serve as markers of disease activity in axial spondyloarthritis

Local inflammation in axial spondyloarthritis (axSpA) leads to the release of collagen metabolites from the disease-affected tissue. We investigated whether collagen metabolites were associated with disease activity and could distinguish non-radiographic(nr)-axSpA from ankylosing spondylitis (AS). A total of 193 axSpA patients (nr-axSpA, n = 121 and AS, n = 72) and asymptomatic controls (n = 100) were included. Serum levels of metalloproteinase (MMP)-degraded collagen type I (C1M), type II (C2M), type III (C3M) and type IV (C4M2) were quantified by enzyme-linked immunosorbent assay (ELISA). All metabolites were higher in axSpA than in controls (all p < 0.001). Serum levels of C1M, C3M, and C4M2 were increased in AS compared to nr-axSpA (43.4 ng/mL vs. 34.6; p < 0.001, 15.4 vs. 12.8; p = 0.001, and 27.8 vs. 22.4; p < 0.001). The best metabolite to differentiate between axSpA and controls was C3M (AUC 0.95; specificity 92.0, sensitivity 83.4). C1M correlated with ASDAS-CRP in nr-axSpA (ρ = 0.37; p < 0.001) and AS (ρ = 0.57; p < 0.001). C1M, C3M, and C4M2 were associated with ASDAS-CRP in AS and nr-axSpA after adjustment for age, gender, and disease duration. Serum levels of collagen metabolites were significantly higher in AS and nr-axSpA than in controls. Moreover, the present study indicates that collagen metabolites reflect disease activity and are useful biomarkers of axSpA.

Predictive, Personalized, Preventive and Participatory (4P) Medicine Applied to Telemedicine and eHealth in the Literature

The main objective of this work is to provide a review of existing research work into predictive, personalized, preventive and participatory medicine in telemedicine and ehealth. The academic databases used for searches are IEEE Xplore, PubMed, Science Direct, Web of Science and ResearchGate, taking into account publication dates from 2010 up to the present day. These databases cover the greatest amount of information on scientific texts in multidisciplinary fields, from engineering to medicine. Various search criteria were established, such as ("Predictive" OR "Personalized" OR "Preventive" OR "Participatory") AND "Medicine" AND ("eHealth" OR "Telemedicine") selecting the articles of most interest. A total of 184 publications about predictive, personalized, preventive and participatory (4P) medicine in telemedicine and ehealth were found, of which 48 were identified as relevant. Many of the publications found show how the P4 medicine is being developed in the world and the benefits it provides for patients with different illnesses. After the revision that was undertaken, it can be said that P4 medicine is a vital factor for the improvement of medical services. It is hoped that one of the main contributions of this study is to provide an insight into how P4 medicine in telemedicine and ehealth is being applied, as well as proposing outlines for the future that contribute to the improvement of prevention and prediction of illnesses.

Manufacturing of Multi-drug Formulations with Customised Dose by Solvent Impregnation of Mesoporous Silica Tablets

The manufacture of personalised medicines where specific combinations of active pharmaceutical ingredients (APIs) and their dose within a tablet would be adjusted to the needs of individual patients, would require new manufacturing approaches compared to the established practice. In the case of low-dose formulations, the required precision of API content might not be achievable by traditional unit operations such as solid powder blending. The aim of the present work was to explore an alternative approach, based on the concept of pre-formulated placebo tablets containing mesoporous silica particles capable of absorbing APIs in the form of solutions, which can be precisely dosed at arbitrarily low quantities. The precision of the liquid dosing system has been validated; it was shown that the mechanical properties of the tablets were satisfactory even after multiple impregnation-drying cycles and that pharmacopoeia specifications on content uniformity could be met. Using model APIs, the spatial distribution of the API within the tablet after impregnation was investigated and shown to depend on the number and order of the impregnation-drying cycles. It was found that when an API was loaded to the tablet in a single step, a different dissolution profile was obtained compared to the same quantity dosed in multiple smaller steps. Overall, the approach of loading multiple API to a pre-formulated tablet at defined quantities using drop-on-demand liquid dosing was found to be feasible from the dose uniformity point of view. Further research should focus on potential API interactions and storage stability of tablets manufactured in this way.

Guidelines for biomarkers in autoimmune rheumatic diseases - evidence based analysis

Autoimmune rheumatic diseases are characterised by an abnormal immune system response, complement activation, cytokines dysregulation and inflammation. In last years, despite many progresses in managing these patients, it has been shown that clinical remission is reached in less than 50% of patients and a personalised and tailored therapeutic approach is still lacking resulting in a significant gap between guidelines and real-world practice. In this context, the need for biomarkers facilitating early diagnosis and profiling those individuals at the highest risk for a poor outcome has become of crucial interest. A biomarker generally refers to a measured characteristic which may be used as an indicator of some biological state or condition. Three different types of medical biomarkers has been suggested: i. mechanistic markers; ii. clinical disease markers; iii. therapeutic markers. A combination of biomarkers from these different groups could be used for an ideal more accurate diagnosis and treatment. However, although a growing body of evidence is focused on improving biomarkers, a significant amount of this information is not integrated on standard clinical care. The overarching aim of this work was to clarify the meaning of specific biomarkers during autoimmune diseases; their possible role in confirming diagnosis, predicting outcome and suggesting specific treatments.

Tocilizumab in the treatment of rheumatoid arthritis: an evidence-based review and patient selection

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by articular and systemic manifestations, such as anemia, fatigue, osteoporosis, and increased risk for cardiovascular diseases. The pathogenesis of RA is driven by a complex network of proinflammatory cytokines, with a pivotal role of IL-6 and tumor necrosis factor (TNF). The management of RA has been dramatically changed during the last years by the introduction of a treat-to-target approach aiming to achieve an acceptable disease control. Nowadays, TNF inhibitors (TNFis) are the most frequently prescribed class of biologic therapies, but the significant proportion of patients experiencing the failure of a TNFi led to the development of alternative therapeutic options targeted on different pathways. Considering the increasing number of targeted therapeutic options for RA, there is a growing interest in the identification of potential predictors of clinical response to each available mechanism of action, with the aim to drive the management of the disease toward a personalized approach according to the concept of precision medicine. Tocilizumab (TCZ) is the first humanized anti-IL-6 receptor subunit alpha (anti-IL-6R) monoclonal antibody approved for the treatment of RA refractory to methotrexate or TNFis. TCZ inhibits both the cis- and trans-signaling cascades involving the Janus kinase-signal transducer and the activator of transcription pathway, playing a crucial role in modulating not only joint inflammation but also the previously mentioned extra-articular manifestations and comorbidities of RA, such as fatigue, anemia, bone loss, depression, type 2 diabetes, and increased cardiovascular risk. In this review, moving from pathogenetic insights and evidence-based clinical data from randomized controlled trials and real-life observational studies, we will discuss the drivers for the selection of patient candidates to receive TCZ, in order to clarify the current positioning of this drug in the treatment algorithm of RA.

Towards precision medicine; a new biomedical cosmology

Precision Medicine has become a common label for data-intensive and patient-driven biomedical research. Its intended future is reflected in endeavours such as the Precision Medicine Initiative in the USA. This article addresses the question whether it is possible to discern a new 'medical cosmology' in Precision Medicine, a concept that was developed by Nicholas Jewson to describe comprehensive transformations involving various dimensions of biomedical knowledge and practice, such as vocabularies, the roles of patients and physicians and the conceptualisation of disease. Subsequently, I will elaborate my assessment of the features of Precision Medicine with the help of Michel Foucault, by exploring how precision medicine involves a transformation along three axes: the axis of biomedical knowledge, of biomedical power and of the patient as a self. Patients are encouraged to become the managers of their own health status, while the medical domain is reframed as a data-sharing community, characterised by changing power relationships between providers and patients, producers and consumers. While the emerging Precision Medicine cosmology may surpass existing knowledge frameworks; it obscures previous traditions and reduces research-subjects to mere data. This in turn, means that the individual is both subjected to the neoliberal demand to share personal information, and at the same time has acquired the positive 'right' to become a member of the data-sharing community. The subject has to constantly negotiate the meaning of his or her data, which can either enable self-expression, or function as a commanding Superego.

Monogenic polyautoimmunity in primary immunodeficiency diseases

Primary immunodeficiency diseases (PIDs) consist of a large group of genetic disorders that affect distinct components of the immune system. PID patients are susceptible to infection and non-infectious complications, particularly autoimmunity. A specific group of monogenic PIDs are due to mutations in genes that are critical for the regulation of immunological tolerance and immune responses. This group of monogenic PIDs is at high risk of developing polyautoimmunity (i.e., the presence of more than one autoimmune disease in a single patient) because of their impaired immunity. In this review, we discuss the mechanisms of autoimmunity in PIDs and the characteristics of polyautoimmunity in the following PIDs: IPEX; monogenic IPEX-like syndrome; LRBA deficiency; CTLA4 deficiency; APECED; ALPS; and PKCδ deficiency.

Novel therapeutic strategy for cancer and autoimmune conditions: Modulating cell metabolism and redox capacity

Dysregulation of cell metabolism and redox balance is implicated in the pathogenesis and progression of cancer and autoimmune diseases. Because the cell proliferation and apoptotic regulatory pathways are interconnected with metabolic and redox signalling pathways, the current mono-target treatment is ineffective, and multi-drug resistance remains common. Complex diseases are often implicated in a network-based context of pathology; therefore, a new holistic intervention approach is required to block multi-crosstalk in such complicated circumstances. The use of therapeutic agents isolated from herbs to holistically modulate metabolism and redox state has been shown to relieve carcinoma growth and the inflammatory response in autoimmune disorders. Multiple clinically applied or novel herbal chemicals with metabolic and redox modulatory capacity as well as low toxicity have recently been identified. Moreover, new metabolic targets and mechanisms of drug action have been discovered, leading to the exploration of new pathways for drug repositioning, clinical biomarker spectra, clinical treatment strategies and drug development. Taken together with multiple supporting examples, the modulation of cell metabolism and the redox capacity using herbal chemicals is emerging as a new, alternative strategy for the holistic treatment of cancer and autoimmune disorders. In the future, the development of new diagnostic tools based on the detection of metabolic and redox biomarkers, reformulation of optimized herbal compositions using artificial intelligence, and the combination of herbs with mono-targeting drugs will reveal new potential for clinical application.

Cytokine and autoantibody clusters interaction in systemic lupus erythematosus

Background

Evidence supports the existence of different subphenotypes in systemic lupus erythematosus (SLE) and the pivotal role of cytokines and autoantibodies, which interact in a highly complex network. Thus, understanding how these complex nonlinear processes are connected and observed in real-life settings is a major challenge. Cluster approaches may assist in the identification of these subphenotypes, which represent such a phenomenon, and may contribute to the development of personalized medicine. Therefore, the relationship between autoantibody and cytokine clusters in SLE was analyzed.

Methods

This was an exploratory study in which 67 consecutive women with established SLE were assessed. Clinical characteristics including disease activity, a 14-autoantibody profile, and a panel of 15 serum cytokines were measured simultaneously. Mixed-cluster methodology and bivariate analyses were used to define autoantibody and cytokine clusters and to identify associations between them and related variables.

Results

First, three clusters of autoantibodies were defined: (1) neutral, (2) antiphospholipid antibodies (APLA)-dominant, and (3) anti-dsDNA/ENA-dominant. Second, eight cytokines showed levels above the threshold thus making possible to find 4 clusters: (1) neutral, (2) chemotactic, (3) G-CSF dominant, and (4) IFNα/Pro-inflammatory. Furthermore, the disease activity was associated with cytokine clusters, which, in turn, were associated with autoantibody clusters. Finally, when all biomarkers were included, three clusters were found: (1) neutral, (2) chemotactic/APLA, and (3) IFN/dsDNA, which were also associated with disease activity.

Conclusion

These results support the existence of three SLE cytokine-autoantibody driven subphenotypes. They encourage the practice of personalized medicine, and support proof-of-concept studies.

Electronic supplementary material

The online version of this article (10.1186/s12967-017-1345-y) contains supplementary material, which is available to authorized users.

Future Horizons in Allergy

There are several advances in diagnosis and management for the otolaryngologist treating allergy. These include new technologies and the refinement of current techniques, and reflect overall trends in health care toward personalized medicine. Local immunoglobulin, urinary leukotriene E4, lipidomics, microRNA within extracellular vesicles, and optical rhinometry all offer to improve the diagnostic accuracy of allergy and related nonallergic conditions. New delivery systems for intranasal steroids and antihistamines, recombinant allergens, advances in allergen immunotherapy delivery, and biologics will improve current management options. These developments will aid the otolaryngologist in diagnosing and treating allergy and related diseases.

Challenges for learning health systems in the NHS. Case study: electronic health records in cardiology

Electronic health records (EHRs) are at the centre of advances in health informatics, but also many other innovations in healthcare. However, there are still obstacles to implementation and realisation of the full potential of EHRs as there are with learning health systems (LHS). Cardiovascular disease, in the UK and globally, carries greater morbidity and mortality than any other disease. Therefore, planning and delivery of health services represent major costs to individuals and populations. Both the scale of disease burden and the growing role of technology in cardiology practice make analysis of experiences with EHRs in cardiology a useful lens through which to view achievements and gaps to date. In this article regarding LHS, EHRs in cardiology are used as a case study of LHS in the NHS.

Autoimmunity in Guillain-Barré syndrome associated with Zika virus infection and beyond

Autoimmune diseases share common immunopathogenic mechanisms (i.e., the autoimmune tautology), which explain the clinical similarities among them as well as their familial clustering. Guillain-Barré syndrome (GBS), an autoimmune peripheral neuropathy, has been recently associated with Zika virus (ZIKV) infection. Based on a series of cases, this review article provides a comparative analysis of GBS associated with ZIKV infection, contrasted with the general characteristics of GBS in light of the autoimmune tautology, including gender differences in prevalence, subphenotypes, polyautoimmunity, familial autoimmunity, age at onset, pathophysiology, ecology, genetics, ancestry, and treatment.