Personomics: The Missing Link in the Evolution from Precision Medicine to Personalized Medicine

Integrating the assessment of quality of life in care and research in pulmonary fibrosis

PURPOSE OF REVIEW

Pulmonary fibrosis (PF) negatively influences health-related quality of life (HRQOL). Patients living with PF have voiced the desire for a focus on symptoms and HRQOL in both disease monitoring and treatment decisions.

RECENT FINDINGS

Currently available disease modifying treatments do little to impact HRQOL. Newer studies evaluating pharmacologic and nonpharmacologic therapies targeting symptoms and HRQOL in PF have been conducted with some promising results. There is increasing recognition of the importance of incorporating HRQOL as a higher tier endpoint in clinical trials. Disease-specific measure of HRQOL have been developed for those living with PF, and there is ongoing work to better understand the validity and reliability characteristics of these tools. In addition to research, there is recognition of the potential benefits of measuring HRQOL and symptoms in clinical practice in facilitate integrating patient perspective into care and allow for more personalized treatment approaches.

SUMMARY

There is increased momentum to discover treatments that impact HRQOL in PF. More work is desperately needed to identify better treatment targets, and to incorporate HRQOL and symptoms as higher tier endpoints in clinical trials. Further work is also needed to address the practicalities of integrating HRQOL measurement into clinical care.

Discordances in patients' and physicians' perspectives on which contextual factors should be accounted for during smoking cessation

BACKGROUND

Smoking cessation interventions requires attending to the circumstances and needs of individual patients. We aimed at highlighting the discordances between patients' and physicians' perspectives on contextual factors that should be considered during smoking cessation.

METHODS

We identified 36 contextual factors identified that should be considered during smoking cessation using PubMed and interviewing general practitioners. Physicians recruited through social networks campaigns and smoker or former smoker patients from the ComPaRe cohort selected the factors they considered most relevant in two online paired comparison experiment. Bradley Terry Luce models estimated the ability of each factor (i.e. the probability to be preferred). We calculated the Pearson's correlation and the intraclass correlation coefficients for the contextual factor from each perspective and compared the ranking of the 10 contextual factors with the highest abilities.

RESULTS

Seven hundred and ninety-three patients' and 795 physicians' perspectives estimated the ability (i.e., importance) of the contextual factors in 11 963 paired comparisons. We found a high correlation between physicians' and patients' perspectives of the contextual factors to be considered for smoking cessation (r = 0.76, P < 0.0001). However, the agreement between the abilities of contextual factors was poor (ICC = 0.42 [-0.10; 0.75]; P = 0.09). Fine-grain analysis of participants' answers revealed many discrepancies. For example, 40% factors ranked in the top 10 most important for physicians were not in patients' top 10 ranking.

CONCLUSION

Our results highlight the importance of patient-centered care, the need to engage discussions about patients' values, beyond what is thought to be important, to avoid overlooking their real context.

Precision prevention in worksite health-A scoping review on research trends and gaps

OBJECTIVES

To map the current state of precision prevention research in the workplace setting, specifically to study contexts and characteristics, and to analyze the precision prevention approach in the stages of risk assessment/data monitoring, data analytics, and the health promotion interventions implemented.

METHODS

Six international databases were searched for studies published between January 2010 and May 2023, using the term "precision prevention" or its synonyms in the context of worksite health promotion.

RESULTS

After screening 3,249 articles, 129 studies were reviewed. Around three-quarters of the studies addressed an intervention (95/129, 74%). Only 14% (18/129) of the articles primarily focused on risk assessment and data monitoring, and 12% of the articles (16/129) mainly included data analytics studies. Most of the studies focused on behavioral outcomes (61/160, 38%), followed by psychological (37/160, 23%) and physiological (31/160, 19%) outcomes of health (multiple answers were possible). In terms of study designs, randomized controlled trials were used in more than a third of all studies (39%), followed by cross-sectional studies (18%), while newer designs (e.g., just-in-time-adaptive-interventions) are currently rarely used. The main data analyses of all studies were regression analyses (44% with analyses of variance or linear mixed models), whereas machine learning methods (e.g., Algorithms, Markov Models) were conducted only in 8% of the articles.

DISCUSSION

Although there is a growing number of precision prevention studies in the workplace, there are still research gaps in applying new data analysis methods (e.g., machine learning) and implementing innovative study designs. In the future, it is desirable to take a holistic approach to precision prevention in the workplace that encompasses all the stages of precision prevention (risk assessment/data monitoring, data analytics and interventions) and links them together as a cycle.

Personalized laboratory medicine in the digital health era: recent developments and future challenges

Interpretation of laboratory data is a comparative procedure and requires reliable reference data, which are mostly derived from population data but used for individuals in conventional laboratory medicine. Using population data as a "reference" for individuals has generated several problems related to diagnosing, monitoring, and treating single individuals. This issue can be resolved by using data from individuals' repeated samples, as their personal reference, thus needing that laboratory data be personalized. The modern laboratory information system (LIS) can store the results of repeated measurements from millions of individuals. These data can then be analyzed to generate a variety of personalized reference data sets for numerous comparisons. In this manuscript, we redefine the term "personalized laboratory medicine" as the practices based on individual-specific samples and data. These reflect their unique biological characteristics, encompassing omics data, clinical chemistry, endocrinology, hematology, coagulation, and within-person biological variation of all laboratory data. It also includes information about individuals' health behavior, chronotypes, and all statistical algorithms used to make precise decisions. This approach facilitates more accurate diagnosis, monitoring, and treatment of diseases for each individual. Furthermore, we explore recent advancements and future challenges of personalized laboratory medicine in the context of the digital health era.

Lifeworlds in pain: a principled method for investigation and intervention

The experience of pain spans biological, psychological and sociocultural realms, both basic and complex, it is by turns necessary and devastating. Despite an extensive knowledge of the constituents of pain, the ability to translate this into effective intervention remains limited. It is suggested that current, multiscale, medical approaches, largely informed by the biopsychosocial (BPS) model, attempt to integrate knowledge but are undermined by an epistemological obligation, one that necessitates a prior isolation of the constituent parts. To overcome this impasse, we propose that an anthropological stance needs to be taken, underpinned by a Bayesian apparatus situated in computational psychiatry. Here, pain is presented within the context of lifeworlds, where attention is shifted away from the constituents of experience (e.g. nociception, reward processing and fear-avoidance), towards the dynamic affiliation that occurs between these processes over time. We argue that one can derive a principled method of investigation and intervention for pain from modelling approaches in computational psychiatry. We suggest that these modelling methods provide the necessary apparatus to navigate multiscale ontology and epistemology of pain. Finally, a unified approach to the experience of pain is presented, where the relational, inter-subjective phenomenology of pain is brought into contact with a principled method of translation; in so doing, revealing the conditions and possibilities of lifeworlds in pain.

Diagnosis and management of bipolar disorders

Bipolar disorders (BDs) are recurrent and sometimes chronic disorders of mood that affect around 2% of the world's population and encompass a spectrum between severe elevated and excitable mood states (mania) to the dysphoria, low energy, and despondency of depressive episodes. The illness commonly starts in young adults and is a leading cause of disability and premature mortality. The clinical manifestations of bipolar disorder can be markedly varied between and within individuals across their lifespan. Early diagnosis is challenging and misdiagnoses are frequent, potentially resulting in missed early intervention and increasing the risk of iatrogenic harm. Over 15 approved treatments exist for the various phases of bipolar disorder, but outcomes are often suboptimal owing to insufficient efficacy, side effects, or lack of availability. Lithium, the first approved treatment for bipolar disorder, continues to be the most effective drug overall, although full remission is only seen in a subset of patients. Newer atypical antipsychotics are increasingly being found to be effective in the treatment of bipolar depression; however, their long term tolerability and safety are uncertain. For many with bipolar disorder, combination therapy and adjunctive psychotherapy might be necessary to treat symptoms across different phases of illness. Several classes of medications exist for treating bipolar disorder but predicting which medication is likely to be most effective or tolerable is not yet possible. As pathophysiological insights into the causes of bipolar disorders are revealed, a new era of targeted treatments aimed at causal mechanisms, be they pharmacological or psychosocial, will hopefully be developed. For the time being, however, clinical judgment, shared decision making, and empirical follow-up remain essential elements of clinical care. This review provides an overview of the clinical features, diagnostic subtypes, and major treatment modalities available to treat people with bipolar disorder, highlighting recent advances and ongoing therapeutic challenges.

Precision and personalized medicine: What their current definition says and silences about the model of health they promote. Implication for the development of personalized health

The US National Human Genome Research Institute defines precision medicine as follows: "Precision medicine (generally considered analogous to personalized medicine or individualized medicine) is an innovative approach that uses information about an individual's genomic, environmental, and lifestyle information to guide decisions related to their medical management. The goal of precision medicine is to provide a more precise approach for the prevention, diagnosis, and treatment of disease." In this perspective article, we question this definition of precision medicine and the risks linked to its current practice and development. We highlight that in practice, precision medicine is based on the use of large volumes of biological data for individual purposes mostly in line with the biomedical model of health, which carries the risk of the biological reductionism of the person. A more comprehensive, precise, and even "personal" approach to health would require taking into account environmental, socio-economic, psychological, and biological determinants, an approach more in line with the biopsychosocial model of health. The role of environmental exposures, in a broad sense, is highlighted more and more, notably in the field of exposome research. Not considering the conceptual framework in which precision medicine is deployed leads to the concealment of the different responsibilities that can be mobilized within the health system. Anchoring precision medicine in a model that does not limit its definition to its biological and technical components makes it possible to envisage a personalized and more precise medicine, integrating a greater share of interventions centered on the skills and life contexts of individuals.

Personalized reference intervals: from theory to practice

Using laboratory test results for diagnosis and monitoring requires a reliable reference to which the results can be compared. Currently, most reference data is derived from the population, and patients in this context are considered members of a population group rather than individuals. However, such reference data has limitations when used as the reference for an individual. A patient's test results preferably should be compared with their own, individualized reference intervals (RI), i.e. a personalized RI (prRI).The prRI is based on the homeostatic model and can be calculated using an individual's previous test results obtained in a steady-state situation and estimates of analytical (CV_A) and biological variation (BV). BV used to calculate the prRI can be obtained from the population (within-subject biological variation, CV_I) or an individual's own data (within-person biological variation, CV_P). Statistically, the prediction interval provides a useful tool to calculate the interval (i.e. prRI) for future observation based on previous measurements. With the development of information technology, the data of millions of patients is stored and processed in medical laboratories, allowing the implementation of personalized laboratory medicine. PrRI for each individual should be made available as part of the laboratory information system and should be continually updated as new test results become available.In this review, we summarize the limitations of population-based RI for the diagnosis and monitoring of disease, provide an outline of the prRI concept and different approaches to its determination, including statistical considerations for deriving prRI, and discuss aspects which must be further investigated prior to implementation of prRI in clinical practice.

A Nonparametric Weighted Cognitive Diagnosis Model and Its Application on Remedial Instruction in a Small-Class Situation

CDMs can provide a discrete classification of mastery skills to diagnose relevant conceptions immediately for Education Sustainable Development. Due to the problem of parametric CDMs with only a few training sample sizes in small classroom teaching situations and the lack of a nonparametric model for classifying error patterns, two nonparametric weighted cognitive diagnosis models, NWSD and NWBD, for classifying mastery skills and knowledge bugs were proposed, respectively. In both, the variances of items with respect to the ideal responses were considered for computing the weighted Hamming distance, and the inverse distances between the observed and ideal responses were used as weights to obtain the probabilities of the mastering attributes of a student. Conversely, NWBD can classify students’ “bugs”, so teachers can provide suitable examples for precision assistance before teaching non-mastery skills. According to the experimental results on simulated and real datasets, the proposed methods outperform some standard methods in a small-class situation. The results also demonstrate that a remedial course with NWSD and NWBD is better than one with traditional group remedial teaching.

The biopsychosociotechnical model: a systems-based framework for human-centered health improvement

The biopsychosocial model is among the most influential frameworks for human-centered health improvement but has faced significant criticism- both conceptual and pragmatic. This paper extends and fundamentally re-structures the biopsychosocial model by combining it with sociotechnical systems theory. The resulting biopsychosociotechnical model addresses key critiques of the biopsychosocial model, providing a more "practical theory" for human-centered health improvement. It depicts the determinants of health as complex adaptive system of systems; includes the the artificial world (technology); and provides a roadmap for systems improvement by: differentiating between "health status" and "health and needs assessment", [promoting problem framing]; explaining health as an emergent property of the biopsychosociotechnical context [imposing a systems orientation]; focusing on "interventions" vs. "treatments" to modify the biopsychosociotechnical determinants of health, [expanding the solution space]; calling for a participatory design process [supporting systems awareness and goal-orientation]; and including intervention management to support the full lifecycle of health improvement.

Personality network neuroscience: Promises and challenges on the way toward a unifying framework of individual variability

We propose that the application of network theory to established psychological personality conceptions has great potential to advance a biologically plausible model of human personality. Stable behavioral tendencies are conceived as personality “traits.” Such traits demonstrate considerable variability between individuals, and extreme expressions represent risk factors for psychological disorders. Although the psychometric assessment of personality has more than hundred years tradition, it is not yet clear whether traits indeed represent “biophysical entities” with specific and dissociable neural substrates. For instance, it is an open question whether there exists a correspondence between the multilayer structure of psychometrically derived personality factors and the organizational properties of traitlike brain systems. After a short introduction into fundamental personality conceptions, this article will point out how network neuroscience can enhance our understanding about human personality. We will examine the importance of intrinsic (task-independent) brain connectivity networks and show means to link brain features to stable behavioral tendencies. Questions and challenges arising from each discipline itself and their combination are discussed and potential solutions are developed. We close by outlining future trends and by discussing how further developments of network neuroscience can be applied to personality research.

Effectiveness of health education in the self-care and adherence of patients with heart failure: a meta-analysis

OBJECTIVE

to evaluate in the literature the effectiveness of the health education interventions in self-care and adherence to treatment of patients with Chronic Heart Failure.

METHOD

a systematic review with meta-analysis. Studies were selected that compared health education interventions with the usual care to assess the outcomes of adherence and self-care. The quality of the methodological evidence was assessed by the Grading of Recommendations, Assessment, Development and Evaluation system.

RESULTS

the educational interventions were more effective in relation to the usual care in the outcome of adherence (fixed effect=0-3841; p-value <0.001). There was no statistical difference in the outcome of self-care (fixed effect=0.0063; p-value=0.898).

CONCLUSION

the educational interventions improved the outcome of adherence, though not self-care in the patient with Heart Failure.

Digital Twins for Multiple Sclerosis

An individualized innovative disease management is of great importance for people with multiple sclerosis (pwMS) to cope with the complexity of this chronic, multidimensional disease. However, an individual state of the art strategy, with precise adjustment to the patient's characteristics, is still far from being part of the everyday care of pwMS. The development of digital twins could decisively advance the necessary implementation of an individualized innovative management of MS. Through artificial intelligence-based analysis of several disease parameters - including clinical and para-clinical outcomes, multi-omics, biomarkers, patient-related data, information about the patient's life circumstances and plans, and medical procedures - a digital twin paired to the patient's characteristic can be created, enabling healthcare professionals to handle large amounts of patient data. This can contribute to a more personalized and effective care by integrating data from multiple sources in a standardized manner, implementing individualized clinical pathways, supporting physician-patient communication and facilitating a shared decision-making. With a clear display of pre-analyzed patient data on a dashboard, patient participation and individualized clinical decisions as well as the prediction of disease progression and treatment simulation could become possible. In this review, we focus on the advantages, challenges and practical aspects of digital twins in the management of MS. We discuss the use of digital twins for MS as a revolutionary tool to improve diagnosis, monitoring and therapy refining patients' well-being, saving economic costs, and enabling prevention of disease progression. Digital twins will help make precision medicine and patient-centered care a reality in everyday life.

Artificial Intelligence in the Healthcare System: An Overview

This chapter aims to present insights into the influence of artificial intelligence (AI) on medicine, public health, and the economy. PubMed and Google Scholar databases were used for the identification and collection of articles with search commands of "artificial intelligence" AND "public health" and "artificial intelligence" AND "medicine". A total of 273 articles specifically handling the issue of artificial intelligence, dating ten years back, in three major medical journals: Science, The Lancet, and The New England Journal of Medicine, were analyzed. Computational power gets stronger by the day, giving us new solutions and possibilities. Current medicine problems like personalized medicine, storage of data, and documentation overload will likely be replaced by AI shortly. The application of AI may also bring substantial benefits to other areas of medicine like the diagnostic and therapeutic processes. The development and spread of AI are inescapable as it lowers healthcare and administrative costs, improves medical efficiency, and predicts and prevents major disease complications. The use of AI in medicine seems destined to carry the day.

Delivering Personalized Care at a Distance: How Telemedicine Can Foster Getting to Know the Patient as a Person

The promise of precision medicine is based on the use of new technologies to better characterize patients by defining individuals in the areas of genomics, proteomics, metabolomics and other aspects of biologic variability. Wise application of modern technology can similarly transform health visits with patients, allowing for better characterization of the patient's individual life circumstances than possible in a traditional office visit. The use of, and experience with, telemedicine have increased significantly during the COVID-19 pandemic. Patients and clinicians report high satisfaction with telemedicine, and the quality of communication and patient-centeredness experienced in this setting are both rated highly. In this article, we explore the benefits offered by telemedicine in facilitating personalized care with particular focus on telemedicine delivered by video platforms. We propose strategies and skills specific to the effective implementation of personalized telemedicine, drawing on literature in patient-centered communication and home visits. While traditional in-person office visits continue to offer important opportunities such as thorough physical examination and the potential for enhanced non-verbal communication, telemedicine offers many important advantages that can facilitate the process of getting to know the patient as a person.

The Need of Personalized Medicine in Coping with Stress during Infertility Treatment

The term personalized medicine was created for oncological patients, but due to its positive clinical results it is now used in many other fields of medicine, including reproductive medicine. The aim of the study was to determine the level of stress and strategies of coping with stress in patients treated for infertility. The study—using a questionnaire developed by the authors, the Perceived Stress Scale-10 (PSS-10), and the Coping Orientation to Problems Experienced Inventory (Mini-COPE)—was conducted among 456 people from infertile couples. Conclusions: More than half of the studied patients demonstrated a high level of stress. The choice of coping strategies was related to the respondents’ gender and level of stress as well as their experience with assisted reproductive technology.

The impact of twenty-first century personalized medicine versus twenty-first century medicine's impact on personalization

BACKGROUND

Over the past decade, the exponential growth of the literature devoted to personalized medicine has been paralleled by an ever louder chorus of epistemic and ethical criticisms. Their differences notwithstanding, both advocates and critics share an outdated philosophical understanding of the concept of personhood and hence tend to assume too simplistic an understanding of personalization in health care.

METHODS

In this article, we question this philosophical understanding of personhood and personalization, as these concepts shape the field of personalized medicine. We establish a dialogue with phenomenology and hermeneutics (especially with E. Husserl, M. Merleau-Ponty and P. Ricoeur) in order to achieve a more sophisticated understanding of the meaning of these concepts We particularly focus on the relationship between personal subjectivity and objective data.

RESULTS

We first explore the gap between the ideal of personalized healthcare and the reality of today's personalized medicine. We show that the nearly exclusive focus of personalized medicine on the objective part of personhood leads to a flawed ethical debate that needs to be reframed. Second, we seek to contribute to this reframing by drawing on the phenomenological-hermeneutical movement in philosophy. Third, we show that these admittedly theoretical analyses open up new conceptual possibilities to tackle the very practical ethical challenges that personalized medicine faces.

CONCLUSION

Finally, we propose a reversal: if personalization is a continuous process by which the person reappropriates all manner of objective data, giving them meaning and thereby shaping his or her own way of being human, then personalized medicine, rather than being personalized itself, can facilitate personalization of those it serves through the data it provides.

Genomics and Pharmacogenomics Knowledge, Attitude and Practice of Pharmacists Working in United Arab Emirates: Findings from Focus Group Discussions-A Qualitative Study

(1) Background: Genomics and pharmacogenomics are relatively new fields in medicine in the United Arab Emirates (UAE). Understanding the knowledge, attitudes and current practices among pharmacists is an important pillar to establish the roadmap for implementing genomic medicine and pharmacogenomics; (2) Methods: A qualitative method was used, with focus group discussions (FGDs) being conducted among pharmacists working in public and private hospitals in Abu Dhabi Emirate. Snowball sampling was used. Thematic inductive analysis was performed by two researchers independently. NVIVO software was used to establish the themes; (3) Results: Lack of knowledge of genomics and pharmacogenomics among pharmacists was one of the most prominent findings. Therefore, the role of pharmacist in making the right decisions was highlighted to be a barrier for pharmacogenomics implementation in the UAE. Pharmacists have a positive attitude toward pharmacogenomics, but they are preoccupied with concern of confidentiality. In addition, religion and culture shadowed their attitudes toward genetic testing; (4) Conclusions: It is highly recommended to introduce new courses and training workshops for healthcare providers to improve the opportunities for genomics and pharmacogenomics application in the UAE. Pharmacists agreed that the health authorities should take the lead for improving trust and confidence in the system for a better future in the era of genomics and pharmacogenomics.

Depressive and Anxiety Symptoms Screening in Cardiac Inpatients: A Virtuous Italian Approach to Psychocardiology

Despite the fact that American Heart Association (AHA) recommended a systematic screening for depression in cardiovascular inpatients, poor attention has been given to this issue. Furthermore, no specific guidelines exist for anxiety screening in cardiovascular inpatients. Thus, the aims of this study were to verify the feasibility of a depressive and anxiety symptoms screening protocol in an Italian hospital specializing in cardiovascular diseases and to evaluate both anxiety and depressive symptoms prevalence. A group of 2009 consecutive inpatients completed the 9-item Patient Health Questionnaire (PHQ-9) and the 7-item Generalized Anxiety Disorder (GAD-7). The rates of depressive and anxiety symptoms were almost 9% and 16% respectively. Men were less likely than women to experience both depressive and anxiety symptoms. Patients who were admitted to the heart failure unit reported higher risk of experiencing both symptoms compared to patients in other wards. Similarly, patients admitted to the cardiac surgery unit showed a higher risk of experiencing anxiety symptoms compared to other patients. The proposed screening procedure showed a good feasibility and acceptance. This study highlighted the importance of implementing a short screening procedure in hospitals dealing with cardiovascular inpatients to identify those individuals who require specific attention and interventions.

Health and Aging: Unifying Concepts, Scores, Biomarkers and Pathways

Despite increasing research efforts, there is a lack of consensus on defining aging or health. To understand the underlying processes, and to foster the development of targeted interventions towards increasing one's health, there is an urgent need to find a broadly acceptable and useful definition of health, based on a list of (molecular) features; to operationalize features of health so that it can be measured; to identify predictive biomarkers and (molecular) pathways of health; and to suggest interventions, such as nutrition and exercise, targeted at putative causal pathways and processes. Based on a survey of the literature, we propose to define health as a state of an individual characterized by the core features of physiological, cognitive, physical and reproductive function, and a lack of disease. We further define aging as the aggregate of all processes in an individual that reduce its wellbeing, that is, its health or survival or both. We define biomarkers of health by their attribute of predicting future health better than chronological age. We define healthspan pathways as molecular features of health that relate to each other by belonging to the same molecular pathway. Our conceptual framework may integrate diverse operationalizations of health and guide precision prevention efforts.

Using What We Already Have: Uncovering New Drug Repurposing Strategies in Existing Omics Data

The promise of drug repurposing is to accelerate the translation of knowledge to treatment of human disease, bypassing common challenges associated with drug development to be more time- and cost-efficient. Repurposing has an increased chance of success due to the previous validation of drug safety and allows for the incorporation of omics. Hypothesis-generating omics processes inform drug repurposing decision-making methods on drug efficacy and toxicity. This review summarizes drug repurposing strategies and methodologies in the context of the following omics fields: genomics, epigenomics, transcriptomics, proteomics, metabolomics, microbiomics, phenomics, pregomics, and personomics. While each omics field has specific strengths and limitations, incorporating omics into the drug repurposing landscape is integral to its success.

Prehabilitation is better than cure

PURPOSE OF REVIEW

With a continuously growing number of older patients undergoing major surgical procedures, reliable parameters practicable in perioperative routine revealing those patients at risk are urgently needed. Recently, the concept of 'prehabilitation' with its key elements exercise, nutrition and psychological stress reduction especially in frail patients is attracting increasing attention.

RECENT FINDINGS

Literature search revealed a huge amount of publications in particular within the last 12 months. Although a single definition of both frailty and prehabilitation is still to be made, various players in the perioperative setting obviously are becoming increasingly convinced about a possible benefit of the program - referring to different components and measures performed. Although physiologically advantages seem obvious, there is hardly any reliable data on clinical outcomes resulting from properly performed studies. This applies especially to octogenarians; thus those at risk for adverse events the concept originally addresses.

SUMMARY

Identifying high-risk patients at the earliest possible stage and increasing their physiological reserve prior to surgery is a promising approach that seems to result in remarkable improvements for older patients. However, further studies on effectiveness in a highly heterogeneous population and agreement on a common concept are mandatory before a final judgement can be given.

Multi-Omics Research Trends in Sepsis: A Bibliometric, Comparative Analysis Between the United States, the European Union 28 Member States, and China

"-Omics" research is in transition with the recent rise of multi-omics technology platforms. Integration of "-omics" and multi-omics research is of high priority in sepsis, a heterogeneous syndrome that is widely recognized as a global health burden and a priority biomedical funding field. We report here an original study on bibliometric trends in the use of "-omics" technologies, and multi-omics approaches in particular, in sepsis research in three (supra)national settings, the United States, the European Union 28 Member States (EU-28), and China. Using a 5-year longitudinal bibliometric study design from 2011 to 2015, we analyzed the sepsis-related research articles in English language that included at least one or multi-omics technologies in publicly available form in Medline (free full texts). We found that the United States has had the lead (almost one-third of publications) in the inclusion of an "-omics" or multi-omics technology in sepsis within the study period. However, both China and the EU-28 displayed a significant increase in the number of publications that employed one or more types of "-omics" research (p < 0.005), while the EU-28 displayed a significant increase especially in multi-omics research articles in sepsis (p < 0.05). Notably, more than half of the multi-omics research studies in the sepsis knowledge domain had a university or government/state funding source. Among the multi-omics research publications in sepsis, the combination of genomics and transcriptomics was the most frequent (40.5%), followed by genomics and proteomics (20.4%). We suggest that the lead of the United States in the field of "-omics" and multi-omics research in sepsis is likely at stake, with both the EU-28 and China rapidly increasing their research capacity. Moreover, "triple omics" that combine genomics, proteomics, and metabolomics analyses appear to be uncommon in sepsis, and yet much needed for triangulation of systems science data. These observations have implications for "-omics" technology policy and global research funding strategic foresight.

The Effect of a Personalized Approach to Patient Education on Heart Failure Self-Management

Personalized tools relevant to an individual patient’s unique characteristics may be an important component of personalized health care. We randomized 97 patients hospitalized with acute decompensated heart failure to receive a printout of an ultrasound image of their inferior vena cava (IVC) with an explanation of how the image is related to their fluid status (n = 50) or to receive no image and only generic heart failure information (n = 47). Adherence to medications, low-sodium diet, and daily weight measurement at baseline and 30 days after discharge were assessed using the Medical Outcomes Study Specific Adherence Scale, modified to a three-item version for heart failure (HF), (MOSSAS-3HF, maximum score = 15, indicating adherence all of the time). The baseline MOSSAS-3HF scores (mean ± standard deviation (SD)) were similar for intervention and control groups (7.4 ± 3.4 vs. 6.4 ± 3.7, p = 0.91). The MOSSAS-3HF scores improved for both groups but were not different at 30 days (11.8 ± 2.8 vs. 11.7 ± 3.0, p = 0.90). Survival without readmission or emergency department (ED) visit at 30 days was similar (82.6% vs. 84.1%, p = 0.85). A personalized HF tool did not affect rates of self-reported HF treatment adherence or survival without readmission or ED visit.

Metabolomics in the study of retinal health and disease

Metabolomics is the qualitative and quantitative assessment of the metabolites (small molecules < 1.5 kDa) in body fluids. The metabolites are the downstream of the genetic transcription and translation processes and also downstream of the interactions with environmental exposures; thus, they are thought to closely relate to the phenotype, especially for multifactorial diseases. In the last decade, metabolomics has been increasingly used to identify biomarkers in disease, and it is currently recognized as a very powerful tool with great potential for clinical translation. The metabolome and the associated pathways also help improve our understanding of the pathophysiology and mechanisms of disease. While there has been increasing interest and research in metabolomics of the eye, the application of metabolomics to retinal diseases has been limited, even though these are leading causes of blindness. In this manuscript, we perform a comprehensive summary of the tools and knowledge required to perform a metabolomics study, and we highlight essential statistical methods for rigorous study design and data analysis. We review available protocols, summarize the best approaches, and address the current unmet need for information on collection and processing of tissues and biofluids that can be used for metabolomics of retinal diseases. Additionally, we critically analyze recent work in this field, both in animal models and in human clinical disease, including diabetic retinopathy and age-related macular degeneration. Finally, we identify opportunities for future research applying metabolomics to improve our current assessment and understanding of mechanisms of vitreoretinal diseases, and to hence improve patient assessment and care.

Fully-automated systems and the need for global approaches should exhort clinical labs to reinvent routine MS analysis?

Today, many LC–high-resolution MS instruments have become affordable, easy-to-use, sensitive and quantitative. Meanwhile, there is an increased need for more comprehensive approaches. However, omics analyses are still restricted to specialists whereas, in hospitals, routine analyses are targeted and quantitative and represent the main and heavy tasks. But the availability of fully automated LC–MS instruments that can handle independently from sample extraction to result reporting, as well as the increasing biomedical interest for global approaches, clinical analytical workflow should be reorganized. Bioanalysts are now in the position to develop/implement clinical metabolomics or proteomics as routine analyses. In this article, this coming evolution and the reasons to implement global/omics determinations as routine analysis, is described.

LC-HRMS Metabolomics for Untargeted Diagnostic Screening in Clinical Laboratories: A Feasibility Study

Today’s high-resolution mass spectrometers (HRMS) allow bioanalysts to perform untargeted/global determinations that can reveal unexpected compounds or concentrations in a patient’s sample. This could be performed for preliminary diagnosis attempts when usual diagnostic processes and targeted determinations fail. We have evaluated an untargeted diagnostic screening (UDS) procedure. UDS is a metabolome analysis that compares one sample (e.g., a patient) with control samples (a healthy population). Using liquid chromatography (LC)-HRMS full-scan analysis of human serum extracts and unsupervised data treatment, we have compared individual samples that were spiked with one xenobiotic or a higher level of one endogenous compound with control samples. After the use of different filters that drastically reduced the number of metabolites detected, the spiked compound was eventually revealed in each test sample and ranked. The proposed UDS procedure appears feasible and reliable to reveal unexpected xenobiotics (toxicology) or higher concentrations of endogenous metabolites. HRMS-based untargeted approaches could be useful as preliminary diagnostic screening when canonical processes do not reveal disease etiology nor establish a clear diagnosis and could reduce misdiagnosis. On the other hand, the risk of overdiagnosis of this approach should be reduced with mandatory biomedical interpretation of the patient’s UDS results and with confirmatory targeted and quantitative determinations.

Untangling Waist Circumference and Hip Circumference from Body Mass Index with a Body Shape Index, Hip Index, and Anthropometric Risk Indicator

Body mass index (BMI) corrects body weight for height and is well established for diagnosing overweight and obesity and correlating with many medical conditions. Waist circumference (WC) is used to diagnose abdominal obesity. However, the correlation of BMI and WC is high, around 0.9, making the use of BMI and WC in concert challenging. A body shape index (ABSI) is a new measure of risk associated with abdominal size. Derived in 2012, ABSI is analogous to BMI in that it normalizes WC for weight and height (and thus to BMI). A similar derivation led to hip index (HI), normalizing hip circumference for BMI. Hazard ratios (HRs) for univariate risk associations of the independent measures height, BMI, ABSI, and HI can be multiplied to give a combined HR, the anthropometric risk indicator (ARI). Compared to any one anthropometric factor, including BMI and WC, ARI more accurately estimates personalized mortality hazard. Published work on ABSI, HI, and ARI supports their association with many aspects of health, including cardiometabolic conditions related to the metabolic syndrome.

Male Infertility, Precision Medicine and Systems Proteomics

Precision medicine (PM) is an approach that has the power to create the best effect and safety of medicine and treatment with the least side effects for each person. PM is very helpful as sometimes due to inaccurate or late diagnosis or toxicities of the drugs irreversible side effect for patient's health are generated. This seemingly new and emerging science is also effective in preventing disease, due to differences in the genes, environment, and lifestyles of any particular person. PM can be a prominent criterion in infertility research. To achieve this goal, there should be information from a healthy human body, including genetic and molecular information. A PM is an evolution in health care, which is very helpful even economically. The guarantor of the PM success is the examination of the molecular profile of the patient, including genes, proteins, metabolites, etc. Therefore, genomics, proteomics, and metabolomics-based techniques are very important in this regard. Unfortunately, despite extensive studies on PM practice in various fields, male infertility has remained unresponsive. Given that around 20% of couples around the world suffer from infertility, and almost half of them are related to men's problems, the PM approach has a high potential for male infertility. In this study, with the help of proteomics and metabolomics, PM information on male infertility was explored.