Lifestyle precision medicine: the next generation in type 2 diabetes prevention?

Genetic effects on gestational diabetes mellitus and their interactions with environmental factors among Japanese women

Gestational diabetes mellitus (GDM) is common in Japanese women, posing serious risks to mothers and offspring. This study investigated the influence of maternal genotypes on the risk of GDM and examined how these genotypes modify the effects of psychological and dietary factors during pregnancy. We analyzed data from 20,399 women in the Tohoku Medical Megabank Project Birth and Three-Generation Cohort. Utilizing two customized SNP arrays for the Japanese population (Affymetrix Axiom Japonica Array v2 and NEO), we performed a meta-analysis to combine the datasets. Gene-environment interactions were assessed by modeling interaction terms between genome-wide significant single nucleotide polymorphisms (SNPs) and psychological and dietary factors. Our analysis identified two SNP variants, rs7643571 (p = 9.14 × 10-9) and rs140353742 (p = 1.24 × 10-8), located in an intron of the MDFIC2 gene, as being associated with an increased risk of GDM. Additionally, although there were suggestive patterns for interactions between these SNPs and both dietary factors (e.g., carbohydrate and fruit intake) and psychological distress, none of the interaction terms remained significant after Bonferroni correction (p < 0.05/8). While nominal significance was observed in some models (e.g., psychological distress, p = 0.04), the data did not provide robust evidence of effect modification on GDM risk once adjusted for multiple comparisons. These findings reveal novel genetic associations with GDM in Japanese women and highlight the importance of gene-environment interactions in its etiology. Given that previous genome-wide association studies (GWAS) on GDM have primarily focused on Western populations, our study provides new insights by examining an Asian population using a population-specific array.

LSD600: the first corpus of biomedical abstracts annotated with lifestyle-disease relations

Lifestyle factors (LSFs) are increasingly recognized as instrumental in both the development and control of diseases. Despite their importance, there is a lack of methods to extract relations between LSFs and diseases from the literature, a step necessary to consolidate the currently available knowledge into a structured form. As simple co-occurrence-based relation extraction (RE) approaches are unable to distinguish between the different types of LSF-disease relations, context-aware models such as transformers are required to extract and classify these relations into specific relation types. However, no comprehensive LSF-disease RE system existed, nor a corpus suitable for developing one. We present LSD600 (available at https://zenodo.org/records/13952449), the first corpus specifically designed for LSF-disease RE, comprising 600 abstracts with 1900 relations of eight distinct types between 5027 diseases and 6930 LSF entities. We evaluated LSD600's quality by training a RoBERTa model on the corpus, achieving an F-score of 68.5% for the multilabel RE task on the held-out test set. We further validated LSD600 by using the trained model on the two Nutrition-Disease and FoodDisease datasets, where it achieved F-scores of 70.7% and 80.7%, respectively. Building on these performance results, LSD600 and the RE system trained on it can be valuable resources to fill the existing gap in this area and pave the way for downstream applications. Database URL: https://zenodo.org/records/13952449.

From molecular mechanisms of prostate cancer to translational applications: based on multi-omics fusion analysis and intelligent medicine

Prostate cancer is the most common cancer in men worldwide and has a high mortality rate. The complex and heterogeneous development of prostate cancer has become a core obstacle in the treatment of prostate cancer. Simultaneously, the issues of overtreatment in early-stage diagnosis, oligometastasis and dormant tumor recognition, as well as personalized drug utilization, are also specific concerns that require attention in the clinical management of prostate cancer. Some typical genetic mutations have been proved to be associated with prostate cancer's initiation and progression. However, single-omic studies usually are not able to explain the causal relationship between molecular alterations and clinical phenotypes. Exploration from a systems genetics perspective is also lacking in this field, that is, the impact of gene network, the environmental factors, and even lifestyle behaviors on disease progression. At the meantime, current trend emphasizes the utilization of artificial intelligence (AI) and machine learning techniques to process extensive multidimensional data, including multi-omics. These technologies unveil the potential patterns, correlations, and insights related to diseases, thereby aiding the interpretable clinical decision making and applications, namely intelligent medicine. Therefore, there is a pressing need to integrate multidimensional data for identification of molecular subtypes, prediction of cancer progression and aggressiveness, along with perosonalized treatment performing. In this review, we systematically elaborated the landscape from molecular mechanism discovery of prostate cancer to clinical translational applications. We discussed the molecular profiles and clinical manifestations of prostate cancer heterogeneity, the identification of different states of prostate cancer, as well as corresponding precision medicine practices. Taking multi-omics fusion, systems genetics, and intelligence medicine as the main perspectives, the current research results and knowledge-driven research path of prostate cancer were summarized.

Oleacein: A comprehensive review of its extraction, purification, absorption, metabolism, and health effects

Extra virgin olive oil (EVOO) consumption reduces the risk of cardiovascular disease in high-risk groups and the polyphenols in EVOO play an important health effect on it. As one of the most abundant polyphenols in EVOO, oleacein (OLEA) has many health benefits. However, there is no review article that focus comprehensively on OLEA, and most articles have limited data and information on OLEA. The purpose of this review is to summarize the results of all available studies, to present and compare the main traditional and novel techniques for the extraction and isolation and purification of OLEA, to elucidate the absorption and metabolic pathways of OLEA, and finally, to illustrate the health-promoting properties. Hopefully, this review can promote the use of OLEA in functional foods and therapeutic fields.

Impact of individual and environmental factors on dietary or lifestyle interventions to prevent type 2 diabetes development: a systematic review

BACKGROUND

The variability in the effectiveness of type 2 diabetes (T2D) preventive interventions highlights the potential to identify the factors that determine treatment responses and those that would benefit the most from a given intervention. We conducted a systematic review to synthesize the evidence to support whether sociodemographic, clinical, behavioral, and molecular factors modify the efficacy of dietary or lifestyle interventions to prevent T2D.

METHODS

We searched MEDLINE, Embase, and Cochrane databases for studies reporting on the effect of a lifestyle, dietary pattern, or dietary supplement interventions on the incidence of T2D and reporting the results stratified by any effect modifier. We extracted relevant statistical findings and qualitatively synthesized the evidence for each modifier based on the direction of findings reported in available studies. We used the Diabetes Canada Clinical Practice Scale to assess the certainty of the evidence for a given effect modifier.

RESULTS

The 81 publications that met our criteria for inclusion are from 33 unique trials. The evidence is low to very low to attribute variability in intervention effectiveness to individual characteristics such as age, sex, BMI, race/ethnicity, socioeconomic status, baseline behavioral factors, or genetic predisposition.

CONCLUSIONS

We report evidence, albeit low certainty, that those with poorer health status, particularly those with prediabetes at baseline, tend to benefit more from T2D prevention strategies compared to healthier counterparts. Our synthesis highlights the need for purposefully designed clinical trials to inform whether individual factors influence the success of T2D prevention strategies.

Role of sociodemographic, clinical, behavioral, and molecular factors in precision prevention of type 2 diabetes: a systematic review

The variability in the effectiveness of type 2 diabetes (T2D) preventive interventions highlights the potential to identify the factors that determine treatment responses and those that would benefit the most from a given intervention. We conducted a systematic review to synthesize the evidence to support whether sociodemographic, clinical, behavioral, and molecular characteristics modify the efficacy of dietary or lifestyle interventions to prevent T2D. Among the 80 publications that met our criteria for inclusion, the evidence was low to very low to attribute variability in intervention effectiveness to individual characteristics such as age, sex, BMI, race/ethnicity, socioeconomic status, baseline behavioral factors, or genetic predisposition. We found evidence, albeit low certainty, to support conclusions that those with poorer health status, particularly those with prediabetes at baseline, tend to benefit more from T2D prevention strategies compared to healthier counterparts. Our synthesis highlights the need for purposefully designed clinical trials to inform whether individual factors influence the success of T2D prevention strategies.

Health education via "empowerment" digital marketing of consumer products and services: Promoting therapeutic benefits of self-care for depression and chronic pain

Increasing health care costs and high economic burden exemplify the impact of chronic diseases on public health. Multifaceted approaches to treating chronic diseases include pharmaceutical drugs, digital therapeutics, and lifestyle medicine. Chronic diseases are largely preventable, and health promotion yields positive outcomes. However, despite positive return on investment (ROI) and cost-to-benefit ratio (CBR) for health promotion (median ROI 2.2, median CBR 14.4), commercial marketing of healthy lifestyles and self-care is limited. The objective of this perspective article is to discuss how digital marketing of consumer goods and services that support therapeutic self-care can also bridge public health and for-profit interests. We describe how "empowerment" marketing campaigns can provide evidence-based associations between products/services and self-care benefits for people living with chronic pain and depression. Such a "health education as marketing" strategy is illustrated by educational ads describing how contact with nature, music, and yoga can improve chronic pain and reduce depressive symptoms. Creating associations between health-related benefits of these activities with products (outdoor and yoga apparel, audio equipment) and services (music streaming services, music mobile apps, eco-tourism, yoga studios) that support them expand their value proposition, thus incentivizing profit-driven companies to engage in public health campaigns. Long-term success of companies that incorporate evidence-based health education as marketing and branding strategies will depend on following ethical considerations and advertising guidelines defined by consumer protection regulatory agencies, such as the Federal Trade Commission (FTC). In conclusion, integration of health education about self-care and commercial marketing can support health care outcomes and disease prevention.

Towards precision cardiometabolic prevention: results from a machine learning, semi-supervised clustering approach in the nationwide population-based ORISCAV-LUX 2 study

Given the rapid increase in the incidence of cardiometabolic conditions, there is an urgent need for better approaches to prevent as many cases as possible and move from a one-size-fits-all approach to a precision cardiometabolic prevention strategy in the general population. We used data from ORISCAV-LUX 2, a nationwide, cross-sectional, population-based study. On the 1356 participants, we used a machine learning semi-supervised cluster method guided by body mass index (BMI) and glycated hemoglobin (HbA1c), and a set of 29 cardiometabolic variables, to identify subgroups of interest for cardiometabolic health. Cluster stability was assessed with the Jaccard similarity index. We have observed 4 clusters with a very high stability (ranging between 92 and 100%). Based on distinctive features that deviate from the overall population distribution, we have labeled Cluster 1 (N = 729, 53.76%) as "Healthy", Cluster 2 (N = 508, 37.46%) as "Family history-Overweight-High Cholesterol ", Cluster 3 (N = 91, 6.71%) as "Severe Obesity-Prediabetes-Inflammation" and Cluster 4 (N = 28, 2.06%) as "Diabetes-Hypertension-Poor CV Health". Our work provides an in-depth characterization and thus, a better understanding of cardiometabolic health in the general population. Our data suggest that such a clustering approach could now be used to define more targeted and tailored strategies for the prevention of cardiometabolic diseases at a population level. This study provides a first step towards precision cardiometabolic prevention and should be externally validated in other contexts.

Using machine learning approaches for multi-omics data analysis: A review

With the development of modern high-throughput omic measurement platforms, it has become essential for biomedical studies to undertake an integrative (combined) approach to fully utilise these data to gain insights into biological systems. Data from various omics sources such as genetics, proteomics, and metabolomics can be integrated to unravel the intricate working of systems biology using machine learning-based predictive algorithms. Machine learning methods offer novel techniques to integrate and analyse the various omics data enabling the discovery of new biomarkers. These biomarkers have the potential to help in accurate disease prediction, patient stratification and delivery of precision medicine. This review paper explores different integrative machine learning methods which have been used to provide an in-depth understanding of biological systems during normal physiological functioning and in the presence of a disease. It provides insight and recommendations for interdisciplinary professionals who envisage employing machine learning skills in multi-omics studies.

Precision Health Care Elements, Definitions, and Strategies for Patients with Diabetes: A Literature Review

Diabetes is a prevalent disease with a high risk of complications. The number of people with diabetes worldwide was reported to increase every year. However, new integrated individualized health care related to diabetes is insufficiently developed. Purpose: The objective of this study was to conduct a literature review and discover precision health care elements, definitions, and strategies. Methods: This study involved a 2-stage process. The first stage comprised a systematic literature search, evidence evaluation, and article extraction. The second stage involved discovering precision health care elements and defining and developing strategies for the management of patients with diabetes. Results: Of 1337 articles, we selected 35 relevant articles for identifying elements and definitions of precision health care for diabetes, including personalized genetic or lifestyle factors, biodata- or evidence-based practice, glycemic target, patient preferences, glycemic control, interdisciplinary collaboration practice, self-management, and patient priority direct care. Moreover, strategies were developed to apply precision health care for diabetes treatment based on eight elements. Conclusions: We discovered precision health care elements and defined and developed strategies of precision health care for patients with diabetes. precision health care is based on team foundation, personalized glycemic target, and control as well as patient preferences and priority, thus providing references for future research and clinical practice.

Does the Impact of Intensive Lifestyle Intervention on Cardiovascular Disease Risk Vary According to Frailty as Measured via Deficit Accumulation?

BACKGROUND

Individuals are often counseled to use behavioral weight loss strategies to reduce risk for cardiovascular disease (CVD). We examined whether any benefits for CVD risk from weight loss intervention extend uniformly to individuals across a range of underlying health states.

METHODS

The time until first occurrence of a composite of fatal and nonfatal myocardial infarction and stroke, hospitalized angina, or CVD death was analyzed from 8 to 11 years of follow-up of 4,859 adults who were overweight or obese, aged 45-76 years with Type 2 diabetes. Individuals had been randomly assigned to either an intensive lifestyle intervention (ILI) or diabetes support and education (DSE). Participants were grouped by intervention assignment and a frailty index (FI) based on deficit accumulation, ordered from fewer (first tertile) to more (third tertile) deficits.

RESULTS

Baseline FI scores were unrelated to intervention-induced weight losses and increased physical activity. The relative effectiveness of ILI on CVD incidence was inversely related to baseline FI in a graded fashion (p = .01), with relative benefit (hazard ratio = 0.73 [95% CI 0.55,0.98]) for individuals in the first FI tertile to no benefit (hazard ratio = 1.15 [0.94,1.42]) among those in the third FI tertile. This graded relationship was not seen for individuals ordered by age tertile (p = .52), and was stronger among participants aged 45-59 years (three-way interaction p = .04).

CONCLUSIONS

In overweight/obese adults with diabetes, multidomain lifestyle interventions may be most effective in reducing CVD if administered before individuals have accrued many age-related health deficits. However, these exploratory analyses require confirmation by other studies.

CLINICAL TRIAL REGISTRATION

NCT00017953.

A pharmacological perspective of banana: implications relating to therapeutic benefits and molecular docking

Banana is one of the most nutritious fruits, as it is rich in carbohydrates, proteins, fatty acids, and minerals. Banana has been used in traditional medicines for managing coughs and colds, ulcers, burns, and diarrhea. Banana contains various bioactive compounds, such as alkaloids, phenols, flavonoids, tannins, and saponins, with reported therapeutic benefits, including antioxidant, anti-diabetic, anti-cancer, anti-inflammatory, and anti-microbial activities. The present review focuses on a comprehensive overview of the nutritional and biological properties and phytochemicals of different species of banana and its different parts. Although detailed characterization of the compounds that are present in many parts of the plant has been carried out, chemical profiling of the seed, pseudostem, and leaves of banana is lacking and requires further exploration. Moreover, the functions of the reported compounds were elucidated using computational tools, supporting their potential role in managing life-threatening diseases and physiological complications.

Next-generation epidemiology: the role of high-resolution molecular phenotyping in diabetes research

Epidemiologists have for many decades reported on the patterns and distributions of diabetes within and between populations and have helped to elucidate the aetiology of the disease. This has helped raise awareness of the tremendous burden the disease places on individuals and societies; it has also identified key risk factors that have become the focus of diabetes prevention trials and helped shape public health recommendations. Recent developments in affordable high-throughput genetic and molecular phenotyping technologies have driven the emergence of a new type of epidemiology with a more mechanistic focus than ever before. Studies employing these technologies have identified gene variants or causal loci, and linked these to other omics data that help define the molecular processes mediating the effects of genetic variation in the expression of clinical phenotypes. The scale of these epidemiological studies is rapidly growing; a trend that is set to continue as the public and private sectors invest heavily in omics data generation. Many are banking on this massive volume of diverse molecular data for breakthroughs in drug discovery and predicting sensitivity to risk factors, response to therapies and susceptibility to diabetes complications, as well as the development of disease-monitoring tools and surrogate outcomes. To realise these possibilities, it is essential that omics technologies are applied to well-designed epidemiological studies and that the emerging data are carefully analysed and interpreted. One might view this as next-generation epidemiology, where complex high-dimensionality data analysis approaches will need to be blended with many of the core principles of epidemiological research. In this article, we review the literature on omics in diabetes epidemiology and discuss how this field is evolving. Graphical abstract.

Response heterogeneity to lifestyle intervention among Latino adolescents

OBJECTIVE

To characterize the heterogeneity in response to lifestyle intervention among Latino adolescents with obesity.

METHODS

We conducted secondary data analysis of 90 Latino adolescents (age 15.4 ± 0.9 y, female 56.7%) with obesity (BMI% 98.1 ± 1.5%) that were enrolled in a 3 month lifestyle intervention and were followed for a year. Covariance pattern mixture models identified response phenotypes defined by changes in insulin sensitivity as measured using a 2 hour oral glucose tolerance test. Baseline characteristics were compared across response phenotypes using one-way ANOVA and chi-square test.

RESULTS

Three distinct response phenotypes (PH1, PH2, PH3) were identified. PH1 exhibited the most robust response defined by the greatest increase in insulin sensitivity over time (β ± SE, linear 0.52 ± 0.17, P < .001; quadratic -0.03 ± 0.01, P = .001). PH2 showed non-significant changes, while PH3 demonstrated modest short-term increases in insulin sensitivity which were not sustained over time (linear 0.08 ± 0.03, P = .002; quadratic -0.01 ± 0.002, P = .003). At baseline, PH3 (1.1 ± 0.4) was the most insulin resistant phenotype and exhibited the highest BMI% (98.5 ± 1.1%), 2 hours glucose concentrations (144.0 ± 27.5 mg/dL), and lowest beta-cell function as estimated by the oral disposition index (4.5 ± 2.8).

CONCLUSION

Response to lifestyle intervention varies among Latino youth with obesity and suggests that precision approaches are warranted to meet the prevention needs of high risk youth.

Management and Prevention Strategies for Non-communicable Diseases (NCDs) and Their Risk Factors

Non-communicable diseases (NCDs) are of increasing concern for society and national governments, as well as globally due to their high mortality rate. The main risk factors of NCDs can be classified into the categories of self-management, genetic factors, environmental factors, factors of medical conditions, and socio-demographic factors. The main focus is on the elements of self-management and to reach a consensus about the influence of food on risk management and actions toward the prevention of NCDs at all stages of life. Nutrition interventions are essential in managing the risk of NCDs. As they are of the utmost importance, this review highlights NCDs and their risk factors and outlines several common prevention strategies. We foresee that the best prevention management strategy will include individual (lifestyle management), societal (awareness management), national (health policy decisions), and global (health strategy) elements, with target actions, such as multi-sectoral partnership, knowledge and information management, and innovations. The most effective preventative strategy is the one that leads to changes in lifestyle with respect to diet, physical activities, cessation of smoking, and the control of metabolic disorders.

PCLiON: An Ontology for Data Standardization and Sharing of Prostate Cancer Associated Lifestyles

BACKGROUND

Researches on Lifestyle medicine (LM) have emerged in recent years to garner wide attention. Prostate cancer (PCa) could be prevented and treated by positive lifestyles, but the association between lifestyles and PCa is always personalized.

OBJECTIVES

In order to solve the heterogeneity and diversity of different data types related to PCa, establish a standardized lifestyle ontology, promote the exchange and sharing of disease lifestyle knowledge, and support text mining and knowledge discovery.

METHODS

The overall construction of PCLiON was created in accordance with the principles and methodology of ontology construction. Following the principles of evidence-based medicine, we screened and integrated the lifestyles and their related attributes. Protégé was used to construct and validate the semantic framework. All annotations in PCLiON were based on SNOMED CT, NCI Thesaurus, the Cochrane Library and FooDB, etc. HTML5 and ASP.NET was used to develop the independent Web page platform and corresponding intelligent terminal application. The PCLiON also uploaded to the National Center for Biomedical Ontology BioPortal.

RESULTS

PCLiON integrates 397 lifestyles and lifestyle-related factors associated with PCa, and is the first of its kind for a specific disease. It contains 320 attribute annotations and 11 object attributes. The logical relationship and completeness meet the ontology requirements. Qualitative analysis was carried out for 329 terms in PCLiON, including factors which are protective, risk or associated but functional unclear, etc. PCLiON is publicly available both at http://pcaontology.net/PCaLifeStyleDefault.aspx and https://bioportal.bioontology.org/ontologies/PCALION.

CONCLUSIONS

Through the bilingual online platforms, complex lifestyle research data can be transformed into standardized, reliable and responsive knowledge, which can promote the shared-decision making (SDM) on lifestyle intervention and assist patients in lifestyle self-management toward the goal of PCa targeted prevention.

Perception Among Diabetic Patients of Telescreening for Diabetic Retinopathy

Purpose: To evaluate the satisfaction of diabetic patients and its determinants of telescreening for diabetic retinopathy (DR) in Saudi Arabia. Methods: This cross-sectional survey was conducted in December 2018 in a diabetes center of Riyadh, Saudi Arabia. Ten questions were asked by the interviewer. A 5-point Likert scale was used to grade patient responses for each question. Rasch analysis was conducted to evaluate the response of the participants. The main outcome variable was the sum of the Logit values of the responses. The Rasch score was also compared among subgroups. Results: Two hundred (n = 200) diabetic patients were interviewed. The median Rasch score of client-perceived benefit of DR telescreening was +14.6 (25% quartile +3.09, minimum; -23.2, maximum; +35.7). A positive attitude of patients regarding DR telescreening was recorded in 159 (79.5%) participants. The perception of telescreening was better in younger diabetic patients than in older diabetic patients (Friedman p < 0.001). The perception was similar in both genders (Mann-Whitney p = 0.3). Diabetic patients from Riyadh and the southern region of Saudi Arabia had significantly more positive perception than those from north and eastern regions (Freedman p < 0.001). Conclusion: Diabetic patients have positive attitude toward tele-DR screening. Their cooperation is likely to be high if large scale tele-DR screening is implemented in the Kingdom.

Analysis of Diabetes Mellitus-Related Amputations in the State of Espírito Santo, Brazil

Background and objectives: Diabetes mellitus (DM) stands out among the most important public health problems worldwide since it represents a high burden on health systems and is associated with higher hospitalization rates, and a higher incidence of cardiovascular diseases. Amputations are among the most common complications, leading to disability and increasing care costs. This research aims to analyze the prevalence of DM-related amputations, comorbidities and associated risk factors in the diabetic population residing in the State of Espírito Santo, Brazil. Materials and Methods: This is a quantitative, exploratory, cross-sectional study with a time series design and the use of secondary data registered and followed by the system of Registration and Monitoring of Hypertension and Diabetes-SisHiperdia. Results: The sample consisted of 64,196 diabetic patients, out of them, 3.9% had type 1 DM, 10.9% with type 2 DM, and 85.2% with DM coexisting with hypertension. Most were female (66.6%), aged 40 to 59 years (45.6%), and 60 years and older (45.2%). The prevalence of DM-related amputations in the analyzed sample was 1.2% in type 1 DM, 1.5% in type 2 DM, and 2.2% in concomitant DM and hypertension. Higher amputation rates were observed in males in the age group above 60 years in type 1 DM and type 2 DM and were slightly higher in the age groups up to 29 years in DM with hypertension. A higher prevalence of amputation was related to smoking, physical inactivity, acute myocardial infarction (AMI), stroke, chronic kidney disease (CKD), and diabetic foot (DF) in all types of DM. Conclusions: The present study showed a significant prevalence of DM-related amputations. An increased prevalence was evidenced when correlated with smoking, physical inactivity, AMI, stroke, CKD, and DF with significant statistical associations, except for a sedentary lifestyle in type 1 DM.

The Impact of Education and Age on Metabolic Disorders

Metabolic disorders, such as obesity, elevated blood pressure, dyslipidemias, insulin resistance, hyperglycemia, and hyperuricemia have all been identified as risk factors for an epidemic of important and widespread chronic-degenerative diseases, such as type 2 diabetes and cardiovascular disease, that constitute some of the world's most important public health challenges. Their increasing prevalence can be associated with an aging population and to lifestyles within an obesogenic environment. Taking educational level as a proxy for lifestyle, and using both logistic and linear regressions, we study the relation between a wide set of metabolic biomarkers, and educational level, body mass index (BMI), age, and sex as correlates, in a population of 1,073 students, academic and non-academic staff at Mexico's largest university (UNAM). Controlling for BMI and sex, we consider educational level and age as complementary measures-degree and duration-of exposure to metabolic insults. Analyzing the role of education across a wide spectrum of educational levels (from primary school to doctoral degree), we show that higher education correlates to significantly better metabolic health when compared to lower levels, and is associated with significantly less risk for waist circumference, systolic blood pressure, glucose, glycosylated hemoglobin, triglycerides, high density lipoprotein and metabolic syndrome (all p < 0.05); but not for diastolic blood pressure, basal insulin, uric acid, low density lipoprotein, and total cholesterol. We classify each biomarker, and corresponding metabolic disorder, by its associated set of statistically significant correlates. Differences among the sets of significant correlates indicate various aetiologies and the need for targeted population-specific interventions. Thus, variables strongly linked to educational level are candidates for lifestyle change interventions. Hence, public policy efforts should be focused on those metabolic biomarkers strongly linked to education, while adopting a different approach for those biomarkers not linked as they may be poor targets for educational campaigns.

Big Data and diabetes: the applications of Big Data for diabetes care now and in the future

We review current applications of Big Data in diabetes care and consider the future potential by carrying out a scoping study of the academic literature on Big Data and diabetes care. Healthcare data are being produced at ever-increasing rates, and this information has the potential to transform the provision of diabetes care. Big Data is beginning to have an impact on diabetes care through data research. The use of Big Data for routine clinical care is still a future application. Vast amounts of healthcare data are already being produced, and the key is harnessing these to produce actionable insights. Considerable development work is required to achieve these goals.

Metabolically Healthy Obesity-Heterogeneity in Definitions and Unconventional Factors

The concept of heterogeneity among obese individuals in their risk for developing metabolic dysfunction and associated complications has been recognized for decades. At the origin of the heterogeneity idea is the acknowledgement that individuals with central obesity are more prone to developing type 2 diabetes and cardiovascular disease than those with peripheral obesity. There have been attempts to categorize subjects according to their metabolic health and degree of obesity giving rise to different obese and non-obese phenotypes that include metabolically unhealthy normal-weight (MUHNW), metabolically healthy obese (MHO), and metabolically unhealthy obese (MUO). Individuals belonging to the MHO phenotype are obese according to their body mass index although exhibiting fewer or none metabolic anomalies such as type 2 diabetes, dyslipidemia, hypertension, and/or unfavorable inflammatory and fribinolytic profiles. However, some authors claim that MHO is only transient in nature. Additionally, the phenotype categorization is controversial as it lacks standardized definitions possibly blurring the distinction between obesity phenotypes and confounding the associations with health outcomes. To add to the discussion, the factors underlying the origin or protection from metabolic deterioration and cardiometabolic risk for these subclasses are being intensely investigated and several hypotheses have been put forward. In the present review, we compare the different definitions of obesity phenotypes and present several possible factors underlying them (adipose tissue distribution and cellularity, contaminant accumulation on the adipose tissue, dysbiosis and metabolic endotoxemia imposing on to the endocannabinoid tone and inflammasome, and nutrient intake and dietary patterns) having inflammatory activation at the center.

PCaLiStDB: a lifestyle database for precision prevention of prostate cancer

The interaction between genes, lifestyles and environmental factors makes the genesis and progress of prostate cancer (PCa) very heterogeneous. Positive lifestyle is important to the prevention and controlling of PCa. To investigate the relationship between PCa and lifestyle at systems level, we established a PCa related lifestyle database (PCaLiStDB) and collected the PCa-related lifestyles including foods, nutrients, life habits and social and environmental factors as well as associated genes and physiological and biochemical indexes together with the disease phenotypes and drugs. Data format standardization was implemented for the future Lifestyle-Wide Association Studies of PCa (PCa_LWAS). Currently, 2290 single-factor lifestyles and 856 joint effects of two or more lifestyles were collected. Among these, 394 are protective factors, 556 are risk factors, 45 are no-influencing factors, 52 are factors with contradictory views and 1977 factors are lacking effective literatures support. PCaLiStDB is expected to facilitate the prevention and control of PCa, as well as the promotion of mechanistic study of lifestyles on PCa. Database URL: http://www.sysbio.org.cn/pcalistdb/.

Assessment of resistance vessel function in human skeletal muscle: guidelines for experimental design, Doppler ultrasound, and pharmacology

The introduction of duplex Doppler ultrasound almost half a century ago signified a revolutionary advance in the ability to assess limb blood flow in humans. It is now widely used to assess blood flow under a variety of experimental conditions to study skeletal muscle resistance vessel function. Despite its pervasive adoption, there is substantial variability between studies in relation to experimental protocols, procedures for data analysis, and interpretation of findings. This guideline results from a collegial discussion among physiologists and pharmacologists, with the goal of providing general as well as specific recommendations regarding the conduct of human studies involving Doppler ultrasound-based measures of resistance vessel function in skeletal muscle. Indeed, the focus is on methods used to assess resistance vessel function and not upstream conduit artery function (i.e., macrovasculature), which has been expertly reviewed elsewhere. In particular, we address topics related to experimental design, data collection, and signal processing as well as review common procedures used to assess resistance vessel function, including postocclusive reactive hyperemia, passive limb movement, acute single limb exercise, and pharmacological interventions.

Does diabetes influence the probability of experiencing chronic low back pain? A population-based cohort study: the Nord-Trøndelag Health Study

OBJECTIVE

Low back pain (LBP) is a major problem in modern society and it is important to study possible risk factors for this disorder. People with diabetes are often affected by LBP, but whether diabetes represents a risk factor for LBP has not been studied in detail. The aim of this study was to explore the association between diabetes and subsequent risk of chronic LBP.

DESIGN

An 11-year follow-up study.

SETTING

The Nord-Trøndelag Health Study (HUNT2; 1995-1997) and HUNT3 (2006-2008) surveys of Nord-Trøndelag County in Norway.

MAIN OUTCOME MEASURE

Chronic LBP, defined as LBP persisting at least 3 months continuously during the last year.

PARTICIPANTS

A total of 18 972 persons without chronic LBP at baseline in HUNT2, and 6802 persons who reported chronic LBP at baseline in HUNT2.

METHODS

Associations between diabetes and risk of chronic LBP among individuals aged 30-69 years were examined by generalised linear modelling.

RESULTS

Men without chronic LBP at baseline showed a significant association between diabetes and risk of chronic LBP (relative risk (RR) 1.43, 95% CI 1.04 to 1.96, p=0.043). In women, no association was found (RR 1.01, 95% CI 0.69 to 1.48, p=0.98). No association could be established between diabetes and recurrence or persistence of chronic LBP after 11 years in either sex.

CONCLUSIONS

Men with a diagnosis of diabetes may have a higher risk of subsequently experiencing chronic LBP.

Platelets as Potent Signaling Entities in Type 2 Diabetes Mellitus

Type 2 diabetes mellitus (T2DM) is a multifactorial disease with a dysregulated circulating inflammatory molecule tendency. T2DM is closely associated with systemic inflammation, endothelial dysfunction, cardiovascular risk, and increased clotting susceptibility. Platelets have fundamental roles in the development and propagation of inflammation and cardiovascular risk. They signal through membrane receptors, resulting in (hyper)activation and release of inflammatory molecules from platelet compartments. This review highlights how circulating inflammatory molecules, acting as platelet receptor ligands, interact with platelets, causing platelets to be potent drivers of systemic inflammation. We conclude by suggesting that focused platelet research in T2DM is an important avenue to pursue to identify novel therapeutic targets, and that platelets could be used as cellular activity sensors themselves.

Obesity and cardiovascular risk: a call for action from the European Society of Hypertension Working Group of Obesity, Diabetes and the High-risk Patient and European Association for the Study of Obesity: part A: mechanisms of obesity induced hypertension, diabetes and dyslipidemia and practice guidelines for treatment

: Obesity is a key factor for cardiovascular diseases and complications. Obesity is associated with hypertension, dyslipidemia and type II diabetes, which are the major predictors of cardiovascular disease in the future. It predisposes for atrial fibrillation, heart failure, sudden cardiac death, renal disease and ischemic stroke that are the main causes of cardiovascular hospitalization and mortality. As obesity and the cardiovascular effects on the vessels and the heart start early in life, even from childhood, it is important for health policies to prevent obesity very early before the disease manifestation emerge. Key roles in the prevention are strategies to increase physical exercise, reduce body weight and to prevent or treat hypertension, lipids disorders and diabetes earlier and efficiently to prevent cardiovascular complications.Epidemiology and mechanisms of obesity-induced hypertension, diabetes and dyslipidemia will be reviewed and the role of lifestyle modification and treatment strategies in obesity will be updated and analyzed. The best treatment options for people with obesity, hypertension, diabetes and dyslipidemia will discussed.

Inflammatory cytokines in type 2 diabetes mellitus as facilitators of hypercoagulation and abnormal clot formation

BACKGROUND

The global burden of type 2 diabetes mellitus (T2DM), together with the presence of cardiovascular risk in this population, is reaching pandemic levels. A prominent feature of T2DM is chronic and systemic inflammation, with the accompanying presence of circulating and dysregulated inflammatory biomarkers; which in turn is associated with abnormal clot formation.

METHODS

Here, we investigate the correlation between abnormal blood clotting, using thromboelastography (TEG), clot ultrastructure using scanning electron microscopy (SEM) and the presence of a dysregulated inflammatory cytokine profile, by examining various circulating biomarkers.

RESULTS

Our results show that many biomarkers, across TEG, cytokine and lipid groups, were greatly dysregulated in the T2DM sample. Furthermore, our T2DM sample's coagulation profiles were significantly more hypercoagulable when compared to our heathy sample, and ultrastructural analysis confirmed a matted and denser clot structure in the T2DM sample.

CONCLUSIONS

We suggest that dysregulated circulating molecules may in part be responsible for a hypercoagulable state and vascular dysfunction in the T2DM sample. We propose further that a personalized approach could be of great value when planning treatment and tracking the patient health status after embarking on a treatment regimes, and that looking to novel inflammatory and vascular biomarkers might be crucial.

Microbial Population Changes and Their Relationship with Human Health and Disease

Specific microbial profiles and changes in intestinal microbiota have been widely demonstrated to be associated with the pathogenesis of a number of extra-intestinal (obesity and metabolic syndrome) and intestinal (inflammatory bowel disease) diseases as well as other metabolic disorders, such as non-alcoholic fatty liver disease and type 2 diabetes. Thus, maintaining a healthy gut ecosystem could aid in avoiding the early onset and development of these diseases. Furthermore, it is mandatory to evaluate the alterations in the microbiota associated with pathophysiological conditions and how to counteract them to restore intestinal homeostasis. This review highlights and critically discusses recent literature focused on identifying changes in and developing gut microbiota-targeted interventions (probiotics, prebiotics, diet, and fecal microbiota transplantation, among others) for the above-mentioned pathologies. We also discuss future directions and promising approaches to counteract unhealthy alterations in the gut microbiota. Altogether, we conclude that research in this field is currently in its infancy, which may be due to the large number of factors that can elicit such alterations, the variety of related pathologies, and the heterogeneity of the population involved. Further research on the effects of probiotics, prebiotics, or fecal transplantations on the composition of the human gut microbiome is necessary.

The Continuing Evolution of Precision Health in Type 2 Diabetes: Achievements and Challenges

PURPOSE OF REVIEW

The purpose of this review was to summarize recent advances in the genomics of type 2 diabetes (T2D) and to highlight current initiatives to advance precision health.

RECENT FINDINGS

Generation of multi-omic data to measure each of the "biologic layers," developments in describing genomic function and annotation in T2D relevant tissue, along with the increasing recognition that T2D is a heterogeneous disease, and large-scale collaborations have all contributed to advancing our understanding of the molecular basis of T2D. Substantial advances have been made in understanding the molecular basis of T2D pathogenesis, such that precision health diabetes is increasingly becoming a reality. For precision diabetes to become a routine in clinical and public health, additional large-scale multi-omic initiatives are needed along with better assessment of our environment to delineate an individual's diabetes subtype for improved detection and management.

DNA methylation changes and improved sleep quality in adults with obstructive sleep apnea and diabetes

OBJECTIVE

Obstructive sleep apnea (OSA) is common among adults with diabetes. However, little is known about the impact of OSA treatment on DNA methylation levels. The purpose of this study is to explore changes in DNA methylation levels among adults with these conditions enrolled in a randomized controlled trial.

RESEARCH DESIGN AND METHODS

Participants were randomized to continuous positive airway pressure (CPAP) treatment or sham-CPAP placebo for 12 weeks. All participants received diabetes education and counseling. At baseline and 12 weeks, white blood cell DNA methylation levels for five candidate genes (ANGPTL4, DAPK3, KAT5, PER1, and TNFAIP3) and hemoglobin A1C (A1C) levels were obtained from blood. The Pittsburgh Sleep Quality Index (PSQI) and the Epworth Sleepiness Scale (ESS) assessed sleep quality and daytime sleepiness, respectively. T-tests examined within-subject changes from baseline to 12 weeks. Regression analyses explored associations between DNA methylation changes and baseline variables, minutes of therapeutic CPAP use, and changes in A1C levels, PSQI scores, and ESS scores.

RESULTS

Participants (n=10) were 70% female, 80% white, and 61.7±7.9 years old. Among all participants from baseline and 12 weeks, TNFAIP3 and PER1 DNA methylation levels decreased. At baseline, PER1 methylation levels were significantly higher in males and sex-based difference in methylation level changes was observed from baseline to 12 weeks. Changes in DNA methylation levels were not associated with minutes of therapeutic CPAP use or changes in A1C, PSQI scores, and ESS scores.

CONCLUSIONS

While DNA methylation level changes were observed in the study, the causal mechanism is unclear and additional work is needed. Although the methylation changes were small, the long-term effects are unknown.

GLP-1 receptor agonists and reduction of cardiometabolic risk: Potential underlying mechanisms

Type 2 diabetes mellitus (T2DM) is a metabolic condition with an elevated impact on cardiovascular (CV) risk. The innovative therapeutic approaches for T2DM - incretin-based therapies (IBTs), including glucagon-like peptide 1 (GLP-1) receptor agonists, have become popular and more widely used in recent years. The available scientific data from clinical studies and clinical practice highlights their beyond glucose-lowering effects, which is achieved without any increase in hypoglycaemia. The former effects include reduction in body weight, lipids, blood pressure, inflammatory markers, oxidative stress, endothelial dysfunction, and subclinical atherosclerosis, thus reducing and potentially preventing CV events. In fact, the introduction of IBTs is one of the key moments in the history of diabetes research and treatment. Such therapeutic strategies allow customization of antidiabetic treatment to each patient's need and therefore obtain better metabolic control with reduced CV risk. The aim of the present paper is to provide a comprehensive overview of the effects of GLP-1RA on various cardiometabolic markers and overall CV risk, with particular attention on recent CV outcome studies and potential mechanisms. In particular, the effects of liraglutide on formation and progression of atherosclerotic plaque and mechanisms explaining its cardioprotective effects are highlighted.

Gene-lifestyle interplay in type 2 diabetes

Type 2 diabetes (T2D) is widespread, affecting the health of hundreds of millions worldwide. The disease results from the complex interplay of lifestyle factors acting on a backdrop of inherited DNA risk variants. Detecting and understanding biomarkers, whether genotypes or other downstream biological features that dictate a person's phenotypic response to different lifestyle exposures, may have tremendous utility in the prevention of T2D. Here, we explore (i) evidence of how human genetic adaptation to diverse local environments might interact with lifestyle factors in T2D, (ii) the key challenges facing the research area of gene×lifestyle interactions in T2D, and (iii) the solutions that might be pursued in future studies. Overall, many preliminary examples of such interactions exist, but none is sufficient to have a major impact on clinical decision making. Future studies, integrating genetics and other biological markers into regulatory networks, are likely to be necessary to facilitate the integration of genomics into lifestyle medicine in T2D.

Effects of Oleacein on High-Fat Diet-Dependent Steatosis, Weight Gain, and Insulin Resistance in Mice

Many reports indicate that the protective action of nutraceuticals in the Mediterranean diet, against metabolic and cardiovascular diseases, can be attributed to the action of polyphenolic components of extra-virgin olive oil (EVOO). Here, we evaluated the protective effects of oleacein, one of the most abundant secoiridoids in EVOO, on the damages/metabolic alterations caused by high-fat diet (HFD) in male C57BL/6JolaHsd mice. After 5 weeks of treatment with 20 mg/kg of oleacein, body weight, glycemia, insulinemia, serum lipids, and histologic examination of liver tissue indicated a protective action of oleacein against abdominal fat accumulation, weight gain, and liver steatosis, with improvement of insulin-dependent glucose and lipid metabolism. Both serum parameters and hepatic histologic examination were altered in mice fed with HFD. By contrast, in the animals that received oleacein, plasma glucose, cholesterol and triglyceride serum levels, and liver histology were similar to controls fed with normocaloric diet. In addition, protein levels of FAS, SREBP-1, and phospho-ERK in liver were positively modulated by oleacein, indicating an improvement in liver insulin sensitivity. In a group of obese mice, treatment with oleacein determined a light, but still significant reduction of the increase in body weight, mainly due to lesser liver steatosis enlargement, associated with reduced levels of SREBP-1 and phospho-ERK and lower levels of total serum cholesterol; in these animals, altered plasma glucose and triglyceride serum levels were not reverted by oleacein. These results indicate that HFD-related hepatic insulin resistance may be partially prevented by oral administration of oleacein, suggesting a protective role of this nutraceutical against diet-dependent metabolic alterations. Additional studies are necessary to check whether oleacein can be used as an adjuvant to improve insulin sensitivity in humans.

Lack of association between glutathione s-transferase mu 1 (GSTM1) gene polymorphisms and obesity

Recent researches suggested that personal individual’s genetic background is contributed to the susceptibility to obesity. The present of this study is to investigate whether single nucleotide polymorphisms (SNPs) of glutathione s-transferase mu 1 (GSTM1) gene are susceptibility to obesity in Korean population. In present study, two SNPs (rs1056806 [Asp142Asp], rs3815029 [promoter]) of GSTM1 gene were genotyped in 117 overweight/obese subjects with a body mass index (BMI)≥23 kg/m² and 125 nonoverweight/obese with a BMI of 18.5–23.0 kg/m². Genotyping of two SNPs (rs1056806 and rs3815029) was determined by sequencing after polymerase chain reaction. Logistic regression models (codominant, dominant, recessive, and log-additive models) and allele analysis were used to calculate odds ratio, 95% confidence interval, and P-values. Significant association was considered at P<0.05. Tested two SNPs in GSTM1 genes did not show any significant association with obesity (rs1056806, P=0.24 in codominant 1 model; rs3815029, P=0.59 in codominant 1, P=0.09 in codominant 2, P=0.16 in dominant, P=0.09 in recessive, and P=0.07 in log-additive models). In summary, these results indicate that SNPs of GSTM1 gene did not associated with susceptibility of obesity in the Korean population.