Integrative and Collaborative Approach in the Chronic Management of Obesity in Primary and Tertiary Care Setting: Vall Hebron-SAP Muntanya Healthcare Route

Integrative approach; Obesity; Primary careEnfoque integrador; Obesidad; Atención primariaEnfocament integrador; Obesitat; Atenció primàriaIntroduction: In the context of obesity pandemic, the health care providers involved in the primary care should have a significant role. Several guidelines for the management of obesity in primary care were proposed recently. In general lines, these guidelines include recommendation on the baseline assessment, therapy, and algorithm for referral to specialized obesity clinic and follow-up. Nevertheless, at present, there is no guideline or protocol that continuously and bidirectionally links the two settings: primary care and specialized obesity clinic. Methods: We present a model of continuous, bilateral, and integrative interaction between primary care units and reference tertiary care setting in the chronic management of obesity that is already implemented in a public health system. Results: The novelty of our algorithm is that incorporates the support and continuous communication with the specialized obesity clinic of the tertiary care setting from the beginning in the management of a patient with obesity, in a bidirectional manner. Conclusion: This kind of bidirectional and continuous collaboration will help engage health care providers in the management of obesity, optimize efforts, shorten the time until proper intervention, personalize the approach and, finally, save costs for the health system

A polygenic and phenotypic risk prediction for polycystic ovary syndrome evaluated by phenomewide association studies

Context: As many as 75% of patients with polycystic ovary syndrome (PCOS) are estimated tobe unidentified in clinical practice. Objective: Utilizing polygenic risk prediction, we aim to identify the phenome-widecomorbidity patterns characteristic of PCOS to improve accurate diagnosis and preventivetreatment.Design, Patients, and Methods: Leveraging the electronic health records (EHRs) of 124 852individuals, we developed a PCOS risk prediction algorithm by combining polygenic risk scores(PRS) with PCOS component phenotypes into a polygenic and phenotypic risk score (PPRS). Weevaluated its predictive capability across different ancestries and perform a PRS-based phenomewide association study (PheWAS) to assess the phenomic expression of the heightened risk ofPCOS.Results: The integrated polygenic prediction improved the average performance (pseudo-R2)for PCOS detection by 0.228 (61.5-fold), 0.224 (58.8-fold), 0.211 (57.0-fold) over the null modelacross European, African, and multi-ancestry participants respectively. The subsequent PRSpowered PheWAS identified a high level of shared biology between PCOS and a range ofmetabolic and endocrine outcomes, especially with obesity and diabetes: "morbid obesity","type 2 diabetes", "hypercholesterolemia", "disorders of lipid metabolism", "hypertension",and "sleep apnea" reaching phenome-wide significance.Conclusions: Our study has expanded the methodological utility of PRS in patient stratificationand risk prediction, especially in a multifactorial condition like PCOS, across different geneticorigins. By utilizing the individual genome-phenome data available from the EHR, our approachalso demonstrates that polygenic prediction by PRS can provide valuable opportunities todiscover the pleiotropic phenomic network associated with PCOS pathogenesis.Abbreviations: AA, African ancestry; ANOVA, analysis of variance; BMI, body mass index; EA,European ancestry; EHR, electronic health records; eMERGE, electronic Medical Records andGenomics Network; GWAS, genome-wide association study; IBD, identity-by-descent; ICDCM, International Classification of Diseases, Clinical Modification; LD, linkage disequilibrium;MA, multi-ancestry; MAF, minor allele frequency; NIH, National Institutes of Health; PCA,principal component analysis; PheWAS, phenome-wide association study; PCOS, polycysticovary syndrome; PPRS, polygenic and phenotypic risk score; PRS, polygenic risk sc

Medicine in the early twenty-first century: Paradigm and anticipation - EPMA position paper 2016

Challenges of “standardisation” and “individualisation” have always been characteristic for medical services. In terms of individualisation, the best possible individual care is the ethical imperative of medicine, and it is a good right of any patient to receive it. However, in terms of standardisation, all the available treatments are based on guideline recommendations derived from large multi-centre trials with many thousands of patients involved. In the most optimal way, the standardisation and individualisation should go hand-in-hand, in order to identify the right patient treating him/her with the right medication and the right dose at the right time point! Further, in paradigm and anticipation, there is a big discrepancy between “disease care” and “health care” which dramatically impacts ethical and economical aspects of medical services. Several approaches have been suggested in ancient and modern medicine to conduct medical services in a possibly optimal way. What is the difference amongst all of them and how big is the potential beyond corresponding approach to satisfy the needs of the individual, the patient, professional groups involved and society at large? On behalf of the “European Association for Predictive, Preventive and Personalised Medicine,” the dedicated EPMA working group provides a deep analysis in the issue followed by the expert recommendations considering the multifaceted aspects of both “disease care” and “health care” practices including ethics and economy, life quality of individuals and patients, interests of professional groups involved, benefits of subpopulations, health care system(s) and society as a whole

Comorbidities in the diseasome are more apparent than real: What Bayesian filtering reveals about the comorbidities of depression

Comorbidity patterns have become a major source of information to explore shared mechanisms of pathogenesis between disorders. In hypothesis-free exploration of comorbid conditions, disease-disease networks are usually identified by pairwise methods. However, interpretation of the results is hindered by several confounders. In particular a very large number of pairwise associations can arise indirectly through other comorbidity associations and they increase exponentially with the increasing breadth of the investigated diseases. To investigate and filter this effect, we computed and compared pairwise approaches with a systems-based method, which constructs a sparse Bayesian direct multimorbidity map (BDMM) by systematically eliminating disease-mediated comorbidity relations. Additionally, focusing on depression-related parts of the BDMM, we evaluated correspondence with results from logistic regression, text-mining and molecular-level measures for comorbidities such as genetic overlap and the interactome-based association score. We used a subset of the UK Biobank Resource, a cross-sectional dataset including 247 diseases and 117,392 participants who filled out a detailed questionnaire about mental health. The sparse comorbidity map confirmed that depressed patients frequently suffer from both psychiatric and somatic comorbid disorders. Notably, anxiety and obesity show strong and direct relationships with depression. The BDMM identified further directly co-morbid somatic disorders, e.g. irritable bowel syndrome, fibromyalgia, or migraine. Using the subnetwork of depression and metabolic disorders for functional analysis, the interactome-based system-level score showed the best agreement with the sparse disease network. This indicates that these epidemiologically strong disease-disease relations have improved correspondence with expected molecular-level mechanisms. The substantially fewer number of comorbidity relations in the BDMM compared to pairwise methods implies that biologically meaningful comorbid relations may be less frequent than earlier pairwise methods suggested. The computed interactive comprehensive multimorbidity views over the diseasome are available on the web at Co=MorNet: bioinformatics.mit.bme.hu/UKBNetworks

Stable Patterns of Gene Expression Regulating Carbohydrate Metabolism Determined by Geographic Ancestry

Background: Individuals of African descent in the United States suffer disproportionately from diseases with a metabolic etiology (obesity, metabolic syndrome, and diabetes), and from the pathological consequences of these disorders (hypertension and cardiovascular disease). Methodology/Principal Findings: Using a combination of genetic/genomic and bioinformatics approaches, we identified a large number of genes that were both differentially expressed between American subjects self-identified to be of either African or European ancestry and that also contained single nucleotide polymorphisms that distinguish distantly related ancestral populations. Several of these genes control the metabolism of simple carbohydrates and are direct targets for the SREBP1, a metabolic transcription factor also differentially expressed between our study populations. Conclusions/Significance: These data support the concept of stable patterns of gene transcription unique to a geographic ancestral lineage. Differences in expression of several carbohydrate metabolism genes suggest both genetic and transcriptional mechanisms contribute to these patterns and may play a role in exacerbating the disproportionate levels o

Nutrition and physical activity programs for obesity treatment (PRONAF study). methodological approach of the project

Este trabajo aborda la metodología seguida para llevar a cabo el proyecto de investigación PRONAF (Clinical Trials Gov.: number NCT01116856.) Background: At present, scientific consensus exists on the multifactorial etiopatogenia of obesity. Both professionals and researchers agree that treatment must also have a multifactorial approach, including diet, physical activity, pharmacology and/or surgical treatment. These two last ones should be reserved for those cases of morbid obesities or in case of failure of the previous ones. The aim of the PRONAF study is to determine what type of exercise combined with caloric restriction is the most appropriate to be included in overweigth and obesity intervention programs, and the aim of this paper is to describe the design and the evaluation methods used to carry out the PRONAF study. Methods/design: One-hundred nineteen overweight (46 males) and 120 obese (61 males) subjects aged 18–50 years were randomly assigned to a strength training group, an endurance training group, a combined strength + endurance training group or a diet and physical activity recommendations group. The intervention period was 22 weeks (in all cases 3 times/wk of training for 22 weeks and 2 weeks for pre and post evaluation). All subjects followed a hypocaloric diet (25-30% less energy intake than the daily energy expenditure estimated by accelerometry). 29–34% of the total energy intake came from fat, 14–20% from protein, and 50–55% from carbohydrates. The mayor outcome variables assesed were, biochemical and inflamatory markers, body composition, energy balance, physical fitness, nutritional habits, genetic profile and quality of life. 180 (75.3%) subjects finished the study, with a dropout rate of 24.7%. Dropout reasons included: personal reasons 17 (28.8%), low adherence to exercise 3 (5.1%), low adherence to diet 6 (10.2%), job change 6 (10.2%), and lost interest 27 (45.8%). Discussion: Feasibility of the study has been proven, with a low dropout rate which corresponds to the estimated sample size. Transfer of knowledge is foreseen as a spin-off, in order that overweight and obese subjects can benefit from the results. The aim is to transfer it to sports centres. Effectiveness on individual health-related parameter in order to determine the most effective training programme will be analysed in forthcoming publications

PERSPECTIVE APPROACH TO PSYCHO-SOMATIC DISORDERS IN ELDERLY PATIENTS WITH CERTAIN MEDICINAL PLANTS IN COVID PANDEMIC

Psychosomatic disorders have now become a common disease in present global scenario due to Covid pandemic. People are always in panic due to morbidity of the disease whereas the livelihood has become a secondary morbid condition due to economic slowdown. Under the above global scenario almost every person is undergoing certain psychosomatic problems either one or both of the factors.  Apart from this, the present trend of competitive and conservative life-style has made young and old person to panic mental situations. The egoistic attitude of the human being and his inability to compromise his desire/demands tends to imbalance of temperament resulting into essential hypertension, insomnia, irritability etc. Ultimately such person becomes addicted to anxiolytic, anti-depressant and tranquilising drugs of modern medicine. Psychiatric disorders are commonly encountered by clinical medicine and the management includes psychotherapy, behavioural therapy, physical treatment with antipsychotic drugs, but the post management leads to addiction or drug dependence along with morbid withdrawal symptoms in patients. In view of problems of dependence specific approach of Ayurvedic concept like Satwavajaya and Daivavyapasraya have provided the light of protection but the practices are still limited due to orthodox beliefs. Some psychotropic drugs like Medhyarasayana etc. in single and compound form are described in classical texts for the management of different mental disorders. The use of herbs to offset these antecedents and outcome has greatly increased in recent years. Not only it is helpful for psychosomatic issues rather it would be helpful at least in such Covid pandemic as because the anti-psychotic drugs are scarce in market due to heavy personal demands. Ayurvedic approach can also create a trend of revitalising herbal preparations keeping behind the hazardous post drug complication. It is an attempt for mainstreaming the Ayurveda in present scenario

The Dark side of Obesity: Multi-omics analysis of the dysmetabolic morbidities spectrum

Obesity is one of the most prevalent clinical conditions worldwide and is associated with a wide spectrum of dysmetabolic comorbidities. Complex cardio-metabolic disease cohorts, such as obesity cohorts are characterised by population heterogeneity, multiple underlying diseases status and different comorbidities’ treatment regiments. The systematic collection of multiple types of clinical and biological data from such cohorts and the data-analysis in an integrative manner is a challenging task due to the variables’ dimensionality and the lack of standardised know-how of post-processing.The main resource of this thesis has been the BARIA cohort, a detailed collection over time of multiple omics and demographic data from participants in bariatric surgery. BARIA datasets included plasma metabolites, RNA from hepatic, jejunal, mesenteric and subcutaneous adipose tissues and gut microbial metagenome, besides biometric data. The work presented in this thesis included the development of a systems biology integrative framework based on BARIA that (i) utilised unsupervised machine learning algorithms, self-organizing maps in particular, and multi-omics integrative frameworks, the DIABLO library, in order to stratify the BARIA heterogeneous obesity cohort and predict the bariatric surgery’s outcome. The thesis covered how BARIA can be the onset for (ii) studying molecular mechanisms related to type 2 diabetes (T2D) and G-protein coupled receptors (GPCRs) and for identifying a minimal set of biomarkers for obesity’s comorbidities such as (iii) non-alcoholic fatty liver disease (NAFL) and (iv) gallstones formation after bariatric surgery.The results indicated that the metabotypes comprising a bariatric surgery cohort exhibited a concrete metabolic status and different responses over time after the bariatric surgery. It has been demonstrated how obesity and T2D associated metabolites, such as 3-hydroxydecanoate, can increase inflammatory responses via GPCRs molecular activation and signalling. Last but not least, minimal sets of both evasive and non-evasive multi-omic discriminatory biomarkers for obesity’s dysmetabolic morbidities (NAFLD and gallstones after bariatric surgery) were obtained. Taking into consideration all the findings, this thesis presented how data-driven approaches can be used for studying in-depth heterogeneous cohorts, hereby facilitating early diagnosis and enabling potential preventive actions