Biopsychosocial frailty and mild cognitive impairment subtypes: Findings from the Italian project on the epidemiology of Alzheimer's disease (IPREA).

INTRODUCTION: Frailty is a critical intermediate status of the aging process including physical, cognitive, and psychosocial phenotypes. We operationalized a biopsychosocial frailty construct, estimating its association with mild cognitive impairment (MCI) and its subtypes. METHODS: In 1980, older individuals from the population-based Italian PRoject on the Epidemiology of Alzheimer's disease (IPREA), we investigated cross-sectional associations among biopsychosocial frailty, MCI, and its subtypes. RESULTS: Participants with biopsychosocial frailty showed an increased odds ratio (OR) of MCI [OR: 4.36; 95% confidence interval (CI): 2.60-7.29; Fisher's exact p < 0.01], particularly for nonamnestic MCI single domain (naMCI-SD, OR:3.28; 95% CI: 1.35-7.97; Fisher's exact p = 0.02) and for nonamnestic MCI multiple domain (naMCI-MD, OR:6.92; 95% CI: 3.37-14.21; Fisher's exact p < 0.01). No statistically significant associations between amnestic MCI single or multiple domain and biopsychosocial frailty were observed. DISCUSSION: In a large, older Italian cohort, a biopsychosocial frailty phenotype was associated with MCI, in particular, could be associated with some of its subtypes, that is, naMCI-SD, and naMCI-MD.

Associations of a biopsychosocial frailty phenotype with all-cause dementia, Alzheimer's disease, vascular dementia, and other dementias: the Italian PRoject on the Epidemiology of Alzheimer's disease (IPREA).

Frailty is a critical intermediate status of the aging process including physical, cognitive, and psychosocial domains/phenotypes. We operationalized a new biopsychosocial frailty construct, estimating its impact on the odds of all-cause dementia, Alzheimer's disease (AD), vascular dementia (VaD), and other dementias in 2838 older individuals from the population-based Italian PRoject on the Epidemiology of Alzheimer's disease (IPREA). Biopsychosocial frailty operationalization was based on the results of a previous comprehensive geriatric assessment and the presence of physical frailty. In this cross-sectional study, participants with biopsychosocial frailty showed an increased odds ratio of all-cause dementia [odds ratio (OR): 5.55, 95% confidence interval (CI): 3.72-8.28, p < 0.001], in particular for probable AD (OR: 3.62, 95% CI: 1.55-8.45, p < 0.001), probable VaD (OR: 10.05, 95% CI: 5.05-19.97, p < 0.001), and possible VaD (OR: 17.61, 95% CI: 6.42-48.32, p < 0.001). No statistically significant association was found between this biopsychosocial frailty phenotype and possible AD (OR: 2.84, 95% CI: 0.81-9.97, p = 0.09) or other dementias (OR: 1.77, 95% CI: 0.75-0.21, p = 0.19). In conclusion, in a large cohort of Italian older individuals, a biopsychosocial frailty model was associated to all-cause dementia, probable AD, and probable and possible VaD. In the next future, other large and prospective population-based studies evaluating the association between the biopsychosocial frailty phenotype and incident all-cause dementia, AD, and VaD are needed, addressing also potential bias and confounding sources.

Bariatric surgery and T2DM improvement mechanisms: a mathematical model.

BACKGROUND: Consensus exists that several bariatric surgery procedures produce a rapid improvement of glucose homeostasis in obese diabetic patients, improvement apparently uncorrelated with the degree of eventual weight loss after surgery. Several hypotheses have been suggested to account for these results: among these, the anti-incretin, the ghrelin and the lower-intestinal dumping hypotheses have been discussed in the literature. Since no clear-cut experimental results are so far available to confirm or disprove any of these hypotheses, in the present work a mathematical model of the glucose-insulin-incretin system has been built, capable of expressing these three postulated mechanisms. The model has been populated with critically evaluated parameter values from the literature, and simulations under the three scenarios have been compared. RESULTS: The modeling results seem to indicate that the suppression of ghrelin release is unlikely to determine major changes in short-term glucose control. The possible existence of an anti-incretin hormone would be supported if an experimental increase of GIP concentrations were evident post-surgery. Given that, on the contrary, collected evidence suggests that GIP concentrations decrease post-surgery, the lower-intestinal dumping hypothesis would seem to describe the mechanism most likely to produce the observed normalization of Type 2 Diabetes Mellitus (T2DM) after bariatric surgery. CONCLUSIONS: The proposed model can help discriminate among competing hypotheses in a context where definitive data are not available and mechanisms are still not clear.

Modeling rejection immunity.

BACKGROUND: Transplantation is often the only way to treat a number of diseases leading to organ failure. To overcome rejection towards the transplanted organ (graft), immunosuppression therapies are used, which have considerable side-effects and expose patients to opportunistic infections. The development of a model to complement the physician's experience in specifying therapeutic regimens is therefore desirable. The present work proposes an Ordinary Differential Equations model accounting for immune cell proliferation in response to the sudden entry of graft antigens, through different activation mechanisms. The model considers the effect of a single immunosuppressive medication (e.g. cyclosporine), subject to first-order linear kinetics and acting by modifying, in a saturable concentration-dependent fashion, the proliferation coefficient. The latter has been determined experimentally. All other model parameter values have been set so as to reproduce reported state variable time-courses, and to maintain consistency with one another and with the experimentally derived proliferation coefficient. RESULTS: The proposed model substantially simplifies the chain of events potentially leading to organ rejection. It is however able to simulate quantitatively the time course of graft-related antigen and competent immunoreactive cell populations, showing the long-term alternative outcomes of rejection, tolerance or tolerance at a reduced functional tissue mass. In particular, the model shows that it may be difficult to attain tolerance at full tissue mass with acceptably low doses of a single immunosuppressant, in accord with clinical experience. CONCLUSIONS: The introduced model is mathematically consistent with known physiology and can reproduce variations in immune status and allograft survival after transplantation. The model can be adapted to represent different therapeutic schemes and may offer useful indications for the optimization of therapy protocols in the transplanted patient.

Alcohol consumption and COVID-19 in Europe: how the pandemic hit the weak.

INTRODUCTION: The COVID-19 pandemic came along with several health and social unprecedented emergencies, among which handling people with substance use disorder issues. METHODS: In this work, data from a cross-sectional online survey conducted among more than 40,000 adults in 21 European countries during the spring of 2020 are analyzed. The survey recorded participants drinking habits during the year preceding the survey and the changes in alcohol consumption during lockdown. The analyses focused on alcohol consumers' type, investigating on the behavioral change in people who already had a problematic alcohol consumption attitude. RESULTS AND CONCLUSION: The results show how subjects with risky or hazardous use of alcohol increased both drinking quantity and frequency in most European countries, underlining the urge to establish regulations on online and home delivered alcoholic beverages availability and reinforcing and restructuring health care services.

Alcohol and Substance Use Disorders Diagnostic Criteria Changes and Innovations in ICD-11: An Overview.

Background: The new revision of the ICD came into effect on January 1st, 2022, and significant changes have been introduced in the section related to substance use disorders. Method: In the present work we describe the new ICD-11 section "Disorders due to Substance Use and Addictive Behaviors" and outline the innovations in classification and diagnosis introduced, with a view to addressing the most important issues in terms of new opportunities for identifying and caring for people in need of treatment. Results: The main innovations introduced in the ICD-11 chapter of interest are the expanded classes of psychoactive substances, the introduction of single episodes of substance use, the introduction of harmful patterns of substance use and severity qualifiers for substance intoxication. Furthermore, the new category "Disorders due to addictive behaviors" has been added, including "Gambling disorder" and the new diagnostic category "Gaming disorder". Conclusions: ICD-11 calls for renewed public health response and policies fostering the multi-professional and multidisciplinary management of alcohol and substance abuse treatment, giving to these forms of addiction new chances also towards the reaching of the UN 2030 Agenda Sustainable Development Goals.

Alcohol, youth and sport: recommendation and good practice examples from the FYFA European project.

Focus on Youth Football and Alcohol (FYFA) is a European project (EC, 3rd Health Program, HP-PJ-2016) involving research institutions from Belgium, Finland, Italy, Poland, Slovenia and the UK. The Istituto Superiore di Sanità (ISS), was the project leader of Work Package 5: "Review of national policies and practice in six Member States related to alcohol, young people, sport, marketing and football." The aim of WP5 was to determine the status quo of the policies and practices to reduce heavy episodic drinking related to young people, alcohol and sport at national level. This work investigates knowledge, attitudes and perceptions of experts from sport settings and from the prevention area giving insights on the perceived obstacles and facilitators, whenever available, to promote strategies to reduce alcohol related harm in youth within sport contexts. The presented work describes laws, regulations and attitudes. Furthermore, the results help identifying areas requiring development, highlighting examples of good practices. It emerges that prevention of alcohol-related harm to youth is important within sport settings and should be a priority for all FYFA countries. Despite the presence of regulations, there is a low level of knowledge and enforcement at national level and in the sport contexts; and there is the need of cooperation across organizations to implement alcohol policies for youth within sport settings. More efforts and resources are needed to overcome the main obstacles for effective implementation of alcohol policies, such as regulations on advertising and sponsorship, and alcohol selling, serving and consumption for young players. It is necessary to implement information strategies, prevention initiatives, training programs and to support the dialogue between sporting and prevention settings.

Correction: Identification of an early transcriptomic signature of insulin resistance and related diseases in lymphomonocytes of healthy subjects.

[This corrects the article DOI: 10.1371/journal.pone.0182559.].

Persistent low body weight in humans is associated with higher mitochondrial activity in white adipose tissue.

BACKGROUND: Constitutional thinness (CT) is a state of low but stable body weight (BMI ≤18 kg/m2). CT subjects have normal-range hormonal profiles and food intake but exhibit resistance to weight gain despite living in the modern world's obesogenic environment. OBJECTIVE: The goal of this study is to identify molecular mechanisms underlying this protective phenotype against weight gain. METHODS: We conducted a clinical overfeeding study on 30 CT subjects and 30 controls (BMI 20-25 kg/m2) matched for age and sex. We performed clinical and integrative molecular and transcriptomic analyses on white adipose and muscle tissues. RESULTS: Our results demonstrate that adipocytes were markedly smaller in CT individuals (mean ± SEM: 2174 ± 142 µm 2) compared with controls (3586 ± 216 µm2) (P < 0.01). The mitochondrial respiratory capacity was higher in CT adipose tissue, particularly at the level of complex II of the electron transport chain (2.2-fold increase; P < 0.01). This higher activity was paralleled by an increase in mitochondrial number (CT compared with control: 784 ± 27 compared with 675 ± 30 mitochondrial DNA molecules per cell; P < 0.05). No evidence for uncoupled respiration or "browning" of the white adipose tissue was found. In accordance with the mitochondrial differences, CT subjects had a distinct adipose transcriptomic profile [62 differentially expressed genes (false discovery rate of 0.1 and log fold change >0.75)], with many differentially expressed genes associating with positive metabolic outcomes. Pathway analyses revealed an increase in fatty acid oxidation ( P = 3 × 10-04) but also triglyceride biosynthesis (P = 3.6 × 10-04). No differential response to the overfeeding was observed in the 2 groups. CONCLUSIONS: The distinct molecular signature of the adipose tissue in CT individuals suggests the presence of augm ented futile lipid cycling, rather than mitochondrial uncoupling, as a way to increase energy expenditure in CT individuals. We propose that increased mitochondrial function in adipose tissue is an important mediator in sustaining the low body weight in CT individuals. This knowledge could ultimately allow more targeted approaches for weight management treatment strategies. This trial was registered at clinicaltrials.gov as NCT02004821.

A closed-loop multi-level model of glucose homeostasis.

BACKGROUND: The pathophysiologic processes underlying the regulation of glucose homeostasis are considerably complex at both cellular and systemic level. A comprehensive and structured specification for the several layers of abstraction of glucose metabolism is often elusive, an issue currently solvable with the hierarchical description provided by multi-level models. In this study we propose a multi-level closed-loop model of whole-body glucose homeostasis, coupled with the molecular specifications of the insulin signaling cascade in adipocytes, under the experimental conditions of normal glucose regulation and type 2 diabetes. METHODOLOGY/PRINCIPAL FINDINGS: The ordinary differential equations of the model, describing the dynamics of glucose and key regulatory hormones and their reciprocal interactions among gut, liver, muscle and adipose tissue, were designed for being embedded in a modular, hierarchical structure. The closed-loop model structure allowed self-sustained simulations to represent an ideal in silico subject that adjusts its own metabolism to the fasting and feeding states, depending on the hormonal context and invariant to circadian fluctuations. The cellular level of the model provided a seamless dynamic description of the molecular mechanisms downstream the insulin receptor in the adipocytes by accounting for variations in the surrounding metabolic context. CONCLUSIONS/SIGNIFICANCE: The combination of a multi-level and closed-loop modeling approach provided a fair dynamic description of the core determinants of glucose homeostasis at both cellular and systemic scales. This model architecture is intrinsically open to incorporate supplementary layers of specifications describing further individual components influencing glucose metabolism.

A reverse metabolic approach to weaning: in silico identification of immune-beneficial infant gut bacteria, mining their metabolism for prebiotic feeds and sourcing these feeds in the natural product space.

BACKGROUND: Weaning is a period of marked physiological change. The introduction of solid foods and the changes in milk consumption are accompanied by significant gastrointestinal, immune, developmental, and microbial adaptations. Defining a reduced number of infections as the desired health benefit for infants around weaning, we identified in silico (i.e., by advanced public domain mining) infant gut microbes as potential deliverers of this benefit. We then investigated the requirements of these bacteria for exogenous metabolites as potential prebiotic feeds that were subsequently searched for in the natural product space. RESULTS: Using public domain literature mining and an in silico reverse metabolic approach, we constructed probiotic-prebiotic-food associations, which can guide targeted feeding of immune health-beneficial microbes by weaning food; analyzed competition and synergy for (prebiotic) nutrients between selected microbes; and translated this information into designing an experimental complementary feed for infants enrolled in a pilot clinical trial ( http://www.nourishtoflourish.auckland.ac.nz/ ). CONCLUSIONS: In this study, we applied a benefit-oriented microbiome research strategy for enhanced early-life immune health. We extended from "classical" to molecular nutrition aiming to identify nutrients, bacteria, and mechanisms that point towards targeted feeding to improve immune health in infants around weaning. Here, we present the systems biology-based approach we used to inform us on the most promising prebiotic combinations known to support growth of beneficial gut bacteria ("probiotics") in the infant gut, thereby favorably promoting development of the immune system.

Consensus Clustering of temporal profiles for the identification of metabolic markers of pre-diabetes in childhood (EarlyBird 73).

In longitudinal clinical studies, methodologies available for the analysis of multivariate data with multivariate methods are relatively limited. Here, we present Consensus Clustering (CClust) a new computational method based on clustering of time profiles and posterior identification of correlation between clusters and predictors. Subjects are first clustered in groups according to a response variable temporal profile, using a robust consensus-based strategy. To discover which of the remaining variables are associated with the resulting groups, a non-parametric hypothesis test is performed between groups at every time point, and then the results are aggregated according to the Fisher method. Our approach is tested through its application to the EarlyBird cohort database, which contains temporal variations of clinical, metabolic, and anthropometric profiles in a population of 150 children followed-up annually from age 5 to age 16. Our results show that our consensus-based method is able to overcome the problem of the approach-dependent results produced by current clustering algorithms, producing groups defined according to Insulin Resistance (IR) and biological age (Tanner Score). Moreover, it provides meaningful biological results confirmed by hypothesis testing with most of the main clinical variables. These results position CClust as a valid alternative for the analysis of multivariate longitudinal data.

A computationally driven analysis of the polyphenol-protein interactome.

Polyphenol-rich foods are part of many nutritional interventions aimed at improving health and preventing cardiometabolic diseases (CMDs). Polyphenols have oxidative, inflammatory, and/or metabolic effects. Research into the chemistry and biology of polyphenol bioactives is prolific but knowledge of their molecular interactions with proteins is limited. We mined public data to (i) identify proteins that interact with or metabolize polyphenols, (ii) mapped these proteins to pathways and networks, and (iii) annotated functions enriched within the resulting polyphenol-protein interactome. A total of 1,395 polyphenols and their metabolites were retrieved (using Phenol-Explorer and Dictionary of Natural Products) of which 369 polyphenols interacted with 5,699 unique proteins in 11,987 interactions as annotated in STITCH, Pathway Commons, and BindingDB. Pathway enrichment analysis using the KEGG repository identified a broad coverage of significant pathways of low specificity to particular polyphenol (sub)classes. When compared to drugs or micronutrients, polyphenols have pleiotropic effects across many biological processes related to metabolism and CMDs. These systems-wide effects were also found in the protein interactome of the polyphenol-rich citrus fruits, used as a case study. In sum, these findings provide a knowledgebase for identifying polyphenol classes (and polyphenol-rich foods) that individually or in combination influence metabolism.

Identification of an early transcriptomic signature of insulin resistance and related diseases in lymphomonocytes of healthy subjects.

Insulin resistance is considered to be a pathogenetic mechanism in several and diverse diseases (e.g. type 2 diabetes, atherosclerosis) often antedating them in apparently healthy subjects. The aim of this study is to investigate with a microarray based approach whether IR per se is characterized by a specific pattern of gene expression. For this purpose we analyzed the transcriptomic profile of peripheral blood mononuclear cells in two groups (10 subjects each) of healthy individuals, with extreme insulin resistance or sensitivity, matched for BMI, age and gender, selected within the MultiKnowledge Study cohort (n = 148). Data were analyzed with an ad-hoc rank-based classification method. 321 genes composed the gene set distinguishing the insulin resistant and sensitive groups, within which the "Adrenergic signaling in cardiomyocytes" KEGG pathway was significantly represented, suggesting a pattern of increased intracellular cAMP and Ca2+, and apoptosis in the IR group. The same pathway allowed to discriminate between insulin resistance and insulin sensitive subjects with BMI >25, supporting his role as a biomarker of IR. Moreover, ASCM pathway harbored biomarkers able to distinguish healthy and diseased subjects (from publicly available data sets) in IR-related diseases involving excitable cells: type 2 diabetes, chronic heart failure, and Alzheimer's disease. The altered gene expression profile of the ASCM pathway is an early molecular signature of IR and could provide a common molecular pathogenetic platform for IR-related disorders, possibly representing an important aid in the efforts aiming at preventing, early detecting and optimally treating IR-related diseases.

Network Analysis of Metabolite GWAS Hits: Implication of CPS1 and the Urea Cycle in Weight Maintenance.

BACKGROUND AND SCOPE: Weight loss success is dependent on the ability to refrain from regaining the lost weight in time. This feature was shown to be largely variable among individuals, and these differences, with their underlying molecular processes, are diverse and not completely elucidated. Altered plasma metabolites concentration could partly explain weight loss maintenance mechanisms. In the present work, a systems biology approach has been applied to investigate the potential mechanisms involved in weight loss maintenance within the Diogenes weight-loss intervention study. METHODS AND RESULTS: A genome wide association study identified SNPs associated with plasma glycine levels within the CPS1 (Carbamoyl-Phosphate Synthase 1) gene (rs10206976, p-value = 4.709e-11 and rs12613336, p-value = 1.368e-08). Furthermore, gene expression in the adipose tissue showed that CPS1 expression levels were associated with successful weight maintenance and with several SNPs within CPS1 (cis-eQTL). In order to contextualize these results, a gene-metabolite interaction network of CPS1 and glycine has been built and analyzed, showing functional enrichment in genes involved in lipid metabolism and one carbon pool by folate pathways. CONCLUSIONS: CPS1 is the rate-limiting enzyme for the urea cycle, catalyzing carbamoyl phosphate from ammonia and bicarbonate in the mitochondria. Glycine and CPS1 are connected through the one-carbon pool by the folate pathway and the urea cycle. Furthermore, glycine could be linked to metabolic health and insulin sensitivity through the betaine osmolyte. These considerations, and the results from the present study, highlight a possible role of CPS1 and related pathways in weight loss maintenance, suggesting that it might be partly genetically determined in humans.

Body mass index mediates inflammatory response to acute dietary challenges.

SCOPE: Acute metabolic challenges provide an opportunity to identify mechanisms of metabolic and nutritional health. In this study, we assessed the transcriptomic response to oral glucose and lipid challenges in a cohort of individuals ranging in age and BMI. The main goal is to identify whether BMI can mediate the metabolic and transcriptional response to dietary challenges, and the differences between lipid and glucose tests. METHODS AND RESULTS: Two hundred fourteen healthy adults were assigned to the challenges and twenty-three individuals were selected for further transcriptomic proofing, using microarray analysis of peripheral blood mononuclear cells. Through linear-mixed models and network analysis, different sets of transcripts and pathways were identified that responded to the challenges depending on BMI. Different transcripts that responded to the lipid and glucose tests, independently of BMI, were also identified. In the network analysis, inflammatory and adhesion processes were strongly represented for both challenges. CONCLUSION: Our results indicate that BMI is strongly linked to the transcriptomic and metabolic response to acute challenges. The emerging biological processes are mainly inflammation-related pathways, highlighting an interconnection between obesity, inflammation/adhesion, and response to nutritional challenge. The comparison between lipid and glucose challenges shows how these trigger a substantially different molecular response.

Routine OGTT: a robust model including incretin effect for precise identification of insulin sensitivity and secretion in a single individual.

In order to provide a method for precise identification of insulin sensitivity from clinical Oral Glucose Tolerance Test (OGTT) observations, a relatively simple mathematical model (Simple Interdependent glucose/insulin MOdel SIMO) for the OGTT, which coherently incorporates commonly accepted physiological assumptions (incretin effect and saturating glucose-driven insulin secretion) has been developed. OGTT data from 78 patients in five different glucose tolerance groups were analyzed: normal glucose tolerance (NGT), impaired glucose tolerance (IGT), impaired fasting glucose (IFG), IFG+IGT, and Type 2 Diabetes Mellitus (T2DM). A comparison with the 2011 Salinari (COntinuos GI tract MOdel, COMO) and the 2002 Dalla Man (Dalla Man MOdel, DMMO) models was made with particular attention to insulin sensitivity indices ISCOMO, ISDMMO and kxgi (the insulin sensitivity index for SIMO). ANOVA on kxgi values across groups resulted significant overall (P<0.001), and post-hoc comparisons highlighted the presence of three different groups: NGT (8.62×10(-5)±9.36×10(-5) min(-1)pM(-1)), IFG (5.30×10(-5)±5.18×10(-5)) and combined IGT, IFG+IGT and T2DM (2.09×10(-5)±1.95×10(-5), 2.38×10(-5)±2.28×10(-5) and 2.38×10(-5)±2.09×10(-5) respectively). No significance was obtained when comparing ISCOMO or ISDMMO across groups. Moreover, kxgi presented the lowest sample average coefficient of variation over the five groups (25.43%), with average CVs for ISCOMO and ISDMMO of 70.32% and 57.75% respectively; kxgi also presented the strongest correlations with all considered empirical measures of insulin sensitivity. While COMO and DMMO appear over-parameterized for fitting single-subject clinical OGTT data, SIMO provides a robust, precise, physiologically plausible estimate of insulin sensitivity, with which habitual empirical insulin sensitivity indices correlate well. The kxgi index, reflecting insulin secretion dependency on glycemia, also significantly differentiates clinically diverse subject groups. The SIMO model may therefore be of value for the quantification of glucose homeostasis from clinical OGTT data.