Perspective: a systems approach to diabetes research

Candidate composite biomarker to inform drug treatments for diabetic kidney disease

Introduction

Current guidelines recommend renin angiotensin system inhibitors (RASi) as key components of treatment of diabetic kidney disease (DKD). Additional options include sodium-glucose cotransporter-2 inhibitors (SGLT2i), glucagon-like peptide 1 receptor agonists (GLP1a), and mineralocorticoid receptor antagonists (MCRa). The identification of the optimum drug combination for an individual is difficult because of the inter-, and longitudinal intra-individual heterogeneity of response to therapy.

Results

Using data from a large observational study (PROVALID), we identified a set of parameters that can be combined into a meaningful composite biomarker that appears to be able to identify which of the various treatment options is clinically beneficial for an individual. It uses machine-earning techniques to estimate under what conditions a treatment of RASi plus an additional treatment is different from the treatment with RASi alone. The measure of difference is the annual percent change (ΔeGFR) in the estimated glomerular filtration rate (ΔeGFR). The 1eGFR is estimated for both the RASi-alone treatment and the add-on treatment.

Discussion

Higher estimated increase of eGFR for add-on patients compared with RASi-alone patients indicates that prognosis may be improved with the add-on treatment. The personalized biomarker value thus identifies which patients may benefit from the additional treatment.

Genetic glucocorticoid receptor variants differ between ethnic groups but do not explain variation in age of diabetes onset, metabolic and inflammation parameters in patients with type 2 diabetes

Aims

The effect of excess glucocorticoid receptor (GR) stimulation through glucocorticoid medication or cortisol on glucose metabolism is well established. There are genetic GR variants that result in increased or decreased GR stimulation. We aimed to determine the prevalence of genetic GR variants in different ethnic groups in a cohort of patients with type 2 diabetes, and we aimed to determine their association with age of diabetes onset and metabolic and inflammation parameters.

Methods

A cross-sectional analysis was performed in a multiethnic cohort (n = 602) of patients with established type 2 diabetes. Polymorphisms in the GR gene that have previously been associated with altered glucocorticoid sensitivity (TthIIII, ER22/23EK N363S, BclI and 9β) were determined and combined into 6 haplotypes. Associations with age of diabetes onset, HbA1c, hs-CRP and lipid values were evaluated in multivariate regression models.

Results

The prevalence of the SNPs of N363S and BclI was higher in Dutch than in non-Dutch patients. We observed a lower prevalence of the SNP 9β in Dutch, South(East) Asian and Black African patients versus Turkish and Moroccan patients. We did not detect an association between SNPs and diabetes age of onset or metabolic parameters. We only found a trend for lower age of onset and higher HbA1c in patients with 1 or 2 copies of haplotype 3 (TthIIII + 9β).

Conclusions

The prevalence of genetic GR variants differs between patients of different ethnic origins. We did not find a clear association between genetic GR variants and age of diabetes onset or metabolic and inflammation parameters. This indicates that the clinical relevance of GR variants in patients with established type 2 diabetes is limited.

Precision nutrition: Maintaining scientific integrity while realizing market potential

Precision Nutrition (PN) is an approach to developing comprehensive and dynamic nutritional recommendations based on individual variables, including genetics, microbiome, metabolic profile, health status, physical activity, dietary pattern, food environment as well as socioeconomic and psychosocial characteristics. PN can help answer the question “What should I eat to be healthy?”, recognizing that what is healthful for one individual may not be the same for another, and understanding that health and responses to diet change over time. The growth of the PN market has been driven by increasing consumer interest in individualized products and services coupled with advances in technology, analytics, and omic sciences. However, important concerns are evident regarding the adequacy of scientific substantiation supporting claims for current products and services. An additional limitation to accessing PN is the current cost of diagnostic tests and wearable devices. Despite these challenges, PN holds great promise as a tool to improve healthspan and reduce healthcare costs. Accelerating advancement in PN will require: (a) investment in multidisciplinary collaborations to enable the development of user-friendly tools applying technological advances in omics, sensors, artificial intelligence, big data management, and analytics; (b) engagement of healthcare professionals and payers to support equitable and broader adoption of PN as medicine shifts toward preventive and personalized approaches; and (c) system-wide collaboration between stakeholders to advocate for continued support for evidence-based PN, develop a regulatory framework to maintain consumer trust and engagement, and allow PN to reach its full potential.

Oxidative Stress in Type 2 Diabetes: The Case for Future Pediatric Redoxomics Studies

Considerable evidence supports the role of oxidative stress in adult type 2 diabetes (T2D). Due to increasing rates of pediatric obesity, lack of physical activity, and consumption of excess food calories, it is projected that the number of children living with insulin resistance, prediabetes, and T2D will markedly increase with enormous worldwide economic costs. Understanding the factors contributing to oxidative stress and T2D risk may help develop optimal early intervention strategies. Evidence suggests that oxidative stress, triggered by excess dietary fat consumption, causes excess mitochondrial hydrogen peroxide emission in skeletal muscle, alters redox status, and promotes insulin resistance leading to T2D. The pathophysiological events arising from excess calorie-induced mitochondrial reactive oxygen species production are complex and not yet investigated in children. Systems medicine is an integrative approach leveraging conventional medical information and environmental factors with data obtained from “omics” technologies such as genomics, proteomics, and metabolomics. In adults with T2D, systems medicine shows promise in risk assessment and predicting drug response. Redoxomics is a branch of systems medicine focusing on “omics” data related to redox status. Systems medicine with a complementary emphasis on redoxomics can potentially optimize future healthcare strategies for adults and children with T2D.

Associations of Nutritional, Environmental, and Metabolic Biomarkers with Diabetes-Related Mortality in U.S. Adults: The Third National Health and Nutrition Examination Surveys between 1988-1994 and 2016

Background: Nutritional, environmental, and metabolic status may play a role in affecting the progression and prognosis of type 2 diabetes. However, results in identifying prognostic biomarkers among diabetic patients have been inconsistent and inconclusive. We aimed to evaluate the associations of nutritional, environmental, and metabolic status with disease progression and prognosis among diabetic patients. Methods: In a nationally representative sample in the NHANES III (The Third National Health and Nutrition Examination Survey, 1988−1994), we analyzed available data on 44 biomarkers among 2113 diabetic patients aged 20 to 90 years (mean age: 58.2 years) with mortality data followed up through 2016. A panel of 44 biomarkers from blood and urine specimens available from NHANES III were included in this study and the main outcomes as well as the measures are mortalities from all-causes. We performed weighted logistic regression analyses after controlling potential confounders. To assess incremental prognostic values of promising biomarkers beyond traditional risk factors, we compared c-statistics of the adjusted models with and without biomarkers, separately. Results: In total, 1387 (65.2%) deaths were documented between 1988 and 2016. We observed an increased risk of all-cause mortality associated with higher levels of serum C-reactive protein (p for trend = 0.0004), thyroid stimulating hormone (p for trend = 0.04), lactate dehydrogenase (p for trend = 0.02), gamma glutamyl transferase (p for trend = 0.02), and plasma fibrinogen (p for trend = 0.03), and urine albumin (p for trend < 0.0001). In contrast, higher levels of serum sodium (p for trend = 0.005), alpha carotene (p for trend = 0.006), and albumin (p for trend = 0.005) were associated with a decreased risk of all-cause mortality. In addition, these significant associations were not modified by age, sex, or race. Inclusion of thyroid stimulating hormone (p = 0.03), fibrinogen (p = 0.01), and urine albumin (p < 0.0001), separately, modestly improved the discriminatory ability for predicting all-cause mortality among diabetic patients. Conclusions: Our nationwide study findings provide strong evidence that some nutritional, environmental, and metabolic biomarkers were significant predictors of all-cause mortality among diabetic patients and may have potential clinical value for improving stratification of mortality risk.

Remodeling the Epigenetic Landscape of Cancer-Application Potential of Flavonoids in the Prevention and Treatment of Cancer

Epigenetics, including DNA methylation, histone modification, and noncoding RNA regulation, are physiological regulatory changes that affect gene expression without modifying the DNA sequence. Although epigenetic disorders are considered a sign of cell carcinogenesis and malignant events that affect tumor progression and drug resistance, in view of the reversible nature of epigenetic modifications, clinicians believe that associated mechanisms can be a key target for cancer prevention and treatment. In contrast, epidemiological and preclinical studies indicated that the epigenome is constantly reprogrammed by intake of natural organic compounds and the environment, suggesting the possibility of utilizing natural compounds to influence epigenetics in cancer therapy. Flavonoids, although not synthesized in the human body, can be consumed daily and are common in medicinal plants, vegetables, fruits, and tea. Recently, numerous reports provided evidence for the regulation of cancer epigenetics by flavonoids. Considering their origin in natural and food sources, few side effects, and remarkable biological activity, the epigenetic antitumor effects of flavonoids warrant further investigation. In this article, we summarized and analyzed the multi-dimensional epigenetic effects of all 6 subtypes of flavonoids (including flavonols, flavones, isoflavones, flavanones, flavanols, and anthocyanidin) in different cancer types. Additionally, our report also provides new insights and a promising direction for future research and development of flavonoids in tumor prevention and treatment via epigenetic modification, in order to realize their potential as cancer therapeutic agents.

SYSTEMIC FACTORS AND EARLY TREATMENT RESPONSE TO INTRAVITREAL INJECTION FOR DIABETIC MACULAR EDEMA: The Role of Renal Function

PURPOSE

To investigate the effect of systemic factors on early treatment response to intravitreal bevacizumab injection (IVBI) and intravitreal dexamethasone implant (IVDI) in patients with diabetic macular edema (DME).

METHODS

We reviewed the medical records of 117 treatment naïve DME patients who underwent IVBI. We divided the patients according to their IVBI response. An IVDI was performed in patients with poor response to IVBIs. We investigated the various systemic factors of diabetic patients and examined the relationship between systemic factors and the treatment response to IVBI and IVDI.

RESULTS

In a total of 117 treatment naïve DME eyes, 61 eyes (52.14%) were classified as IVBI responders. An IVDI was performed in 23 of 56 eyes with poor response to IVBI, and 17 eyes (73.91%) had a good response. Among various systemic factors of patients with diabetes, renal function (blood urea nitrogen, creatinine, and estimated glomerular filtration rate) showed a significant negative correlation with central subfield retinal thickness improvement after treatment (P < 0.05). However, there was no difference in HbA1C levels regarding the treatment response to IVBI and IVDI.

CONCLUSION

Renal function was significantly worse in patients with a poor response to IVBI and IVDI. Renal function could be used as a possible predictor for treatment response in certain patients with DME. Furthermore, for patients with DME with poor responses to anti-vascular endothelial growth factor or steroid treatments, assessment of renal function could help explain the poor treatment response.

Relationship between Clinical Features of Diabetic Retinopathy and Systemic Factors in Patients with Newly Diagnosed Type II Diabetes Mellitus

BACKGROUND

We investigated the relationship between clinical features of diabetic retinopathy (DR) and systemic factors in patients with newly diagnosed type II diabetes mellitus (T2DM).

METHODS

Retrospective review of newly diagnosed T2DM-patients who underwent complete ophthalmic examinations at the time of T2DM diagnosis were conducted. We reviewed DM related systemic factor data and investigated systemic factors related to the presence of DR at T2DM diagnosis. In DR patients, the relationship between DR severity and systemic factors was analyzed.

RESULTS

Of 380 patients, forty (10.53%) patients had DR at the initial ophthalmologic examination. Glycated hemoglobin (HbA_1C), fasting plasma glucose (FPG), urine albumin to creatinine ratio (UACR), and urine microalbumin level were significantly higher in DR patients than in patients without DR. In the multivariate logistic regression analysis, high HbA_1C was a significant risk factor for the presence of DR at new T2DM diagnosis (odds ratio, 2.372; P < 0.001). HbA_1C, FPG, UACR, and urine microalbumin level showed significantly positive correlations with DR severity .

CONCLUSION

In patients with newly diagnosed T2DM, 10.53% have DR at initial ophthalmologic examination and high HbA_1C, FPG, UACR and urine microalbumin levels. These factors are significantly positively correlated with DR severity. Therefore, more careful fundus examination is needed for newly diagnosed T2DM patients with high HbA_1C, FPG, UACR, and urine microalbumin levels.

Working Towards Eye Health Equity for Indigenous Australians with Diabetes

Type 2 diabetes mellitus (T2DM) poses significant challenges to individuals and broader society, much of which is borne by disadvantaged and marginalised population groups including Indigenous people. The increasing prevalence of T2DM among Indigenous people has meant that rates of diabetes-related complications such as blindness from end-stage diabetic retinopathy (DR) continue to be important health concerns. Australia, a high-income and resource-rich country, continues to struggle to adequately respond to the health needs of its Indigenous people living with T2DM. Trends among Indigenous Australians highlight that the prevalence of DR has almost doubled over two decades, and the prevalence of diabetes-related vision impairment is consistently reported to be higher among Indigenous Australians (5.2%–26.5%) compared to non-Indigenous Australians (1.7%). While Australia has collated reliable estimates of the eye health burden owing to T2DM in its Indigenous population, there is fragmentation of existing data and limited knowledge on the underlying risk factors. Taking a systems approach that investigates the social, environmental, clinical, biological and genetic risk factors, and—importantly—integrates these data, may give valuable insights into the most important determinants contributing to the development of diabetes-related blindness. This knowledge is a crucial initial step to reducing the human and societal impacts of blindness on Indigenous Australians, other priority populations and society at large.

Effect of Steviol Glycosides on Human Health with Emphasis on Type 2 Diabetic Biomarkers: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

The natural sweetener from Stevia rebaudiana Bertoni, steviol glycoside (SG), has been proposed to exhibit a range of antidiabetic properties. The objective of this systematic review was to critically evaluate evidence for the effectiveness of SGs on human health, particularly type 2 diabetic (T2D) biomarkers, collecting data from randomized controlled trials (RCTs). Electronic searches were performed in PubMed and EMBASE and the bibliography of retrieved full-texts was hand searched. Using the Cochrane criteria, the reporting quality of included studies was assessed. Seven studies, nine RCTs, including a total of 462 participants were included. A meta-analysis was performed to assess the effect of SGs on following outcomes: BMI, blood pressure (BP), fasting blood glucose (FBG), lipids, and glycated hemoglobin (HbA1c). The meta-analysis revealed an overall significant reduction in systolic BP in favour of SGs between SG and placebo, mean difference (MD): -6.32 mm Hg (-7.69 to 0.46). The overall effect of BMI, diastolic BP, FBG, total cholesterol, and high-density lipoprotein cholesterol (HDL-C) was a non-significant reduction in favour of SGs, and a non-significant increase in low-density lipoprotein cholesterol and triglyceride, while no significant effect of HbA1c was found. Heterogeneity was significant for several analyses. More studies investigating the effect of SGs on human health, particularly T2D biomarkers, are warranted.

A Data Integration Multi-Omics Approach to Study Calorie Restriction-Induced Changes in Insulin Sensitivity

Background: The mechanisms responsible for calorie restriction (CR)-induced improvement in insulin sensitivity (IS) have not been fully elucidated. Greater insight can be achieved through deep biological phenotyping of subjects undergoing CR, and integration of big data. Materials and Methods: An integrative approach was applied to investigate associations between change in IS and factors from host, microbiota, and lifestyle after a 6-week CR period in 27 overweight or obese adults (ClinicalTrials.gov: NCT01314690). Partial least squares regression was used to determine associations of change (week 6 - baseline) between IS markers and lifestyle factors (diet and physical activity), subcutaneous adipose tissue (sAT) gene expression, metabolomics of serum, urine and feces, and gut microbiota composition. ScaleNet, a network learning approach based on spectral consensus strategy (SCS, developed by us) was used for reconstruction of biological networks. Results: A spectrum of variables from lifestyle factors (10 nutrients), gut microbiota (10 metagenomics species), and host multi-omics (metabolic features: 84 from serum, 73 from urine, and 131 from feces; and 257 sAT gene probes) most associated with IS were identified. Biological network reconstruction using SCS, highlighted links between changes in IS, serum branched chain amino acids, sAT genes involved in endoplasmic reticulum stress and ubiquitination, and gut metagenomic species (MGS). Linear regression analysis to model how changes of select variables over the CR period contribute to changes in IS, showed greatest contributions from gut MGS and fiber intake. Conclusion: This work has enhanced previous knowledge on links between host glucose homeostasis, lifestyle factors and the gut microbiota, and has identified potential biomarkers that may be used in future studies to predict and improve individual response to weight-loss interventions. Furthermore, this is the first study showing integration of the wide range of data presented herein, identifying 115 variables of interest with respect to IS from the initial input, consisting of 9,986 variables. Clinical Trial Registration: clinicaltrials.gov (NCT01314690).

Differential proteome analysis of diabetes mellitus type 2 and its pathophysiological complications

The prevalence of Diabetes Mellitus Type 2 (DM 2) is increasing every passing year due to some global changes in lifestyles of people. The exact underlying mechanisms of the progression of this disease are not yet known. However recent advances in the combined omics more particularly in proteomics and genomics have opened a gateway towards the understanding of predetermined genetic factors, progression, complications and treatment of this disease. Here we shall review the recent advances in proteomics that have led to an early and better diagnostic approaches in controlling DM 2 more importantly the comparison of structural and functional protein biomarkers that are modified in the diseased state. By applying these advanced and promising proteomic strategies with bioinformatics applications and bio-statistical tools the prevalence of DM 2 and its associated disorders i-e nephropathy and retinopathy are expected to be controlled.

Predictive biomarkers for type 2 of diabetes mellitus: Bridging the gap between systems research and personalized medicine

The global incidence of metabolic disorders like type 2 diabetes mellitus (DM2) has assumed epidemic proportions, leading to adverse health and socio-economic impacts. It is therefore of critical importance the early diagnosis of DM2 patients and the detection of those at increased risk of disease. In this respect, Precision Medicine (PM) is an emerging approach that includes practices, tests, decisions and treatments adapted to the characteristics of each patient. With regard to DM2, PM manages a wealth of "omics" data (genomic, metabolic, proteomic, environmental, clinical and paraclinical) to increase the number of clinically validated biomarkers in order to identify patients in early stage even before the prediabetic phase.

SIGNIFICANCE

In this paper, we discuss the epidemic dimension of metabolic disorders like type 2 diabetes mellitus (DM2) and the urgent demand for novel biomarkers to reduce the incidence or even delay the onset of DM2. Recent research data produced by "multi-omics" technologies (genomics/epigenomics, transcriptomics, proteomics and metabolomics), suggest that many potential biomarkers might be helpful in the prediction and early diagnosis of DM2. Predictive, Preventive and Personalized Medicine (PPPM) manages and integrates these data to apply personalized, preventive, and therapeutic approaches. This is significant because there is an emerging need for establishing channels for communication and personalized consultation between systems research and precision medicine, as the medicine of the future.

Metabolomics as a Tool to Understand Pathophysiological Processes

Multiple diseases have a strong metabolic component, and metabolomics as a powerful phenotyping technology, in combination with orthogonal biological and clinical approaches, will undoubtedly play a determinant role in accelerating the understanding of mechanisms that underlie these complex diseases determined by a set of genetic, lifestyle, and environmental exposure factors. Here, we provide several examples of valuable findings from metabolomics-led studies in diabetes and obesity metabolism, neurodegenerative disorders, and cancer metabolism and offer a longer term vision toward personalized approach to medicine, from population-based studies to pharmacometabolomics.

Features of Long-Standing Korean Type 2 Diabetes Mellitus Patients with Diabetic Retinopathy: A Study Based on Standardized Clinical Data

BACKGROUND

This is part of a prospective study carried out as a national project to secure standardized public resources for type 2 diabetes mellitus (T2DM) patients in Korea. We compared various characteristics of long-standing T2DM patients with diabetic retinopathy (DR) and macular edema (ME).

METHODS

From September 2014 to July 2015, T2DM patients with disease duration of at least 15 years were recruited at a single university hospital. Clinical data and samples were collected according to the common data elements and standards of procedure developed by the Korean Diabetes Association Research Council. Each participant was assessed by ophthalmologists for DR and ME.

RESULTS

Among 220 registered patients, 183 completed the ophthalmologic assessment. DR was associated with longer disease duration (odds ratio [OR], 1.071; 95% confidence interval [CI], 1.001 to 1.147 for non-proliferative diabetic retinopathy [NPDR]) (OR, 1.142; 95% CI, 1.051 to 1.242 for proliferative diabetic retinopathy [PDR]) and the use of long-acting insulin (OR, 4.559; 95% CI, 1.672 to 12.427 for NPDR) (OR, 4.783; 95% CI, 1.581 to 14.474 for PDR), but a lower prevalence of a family history of cancer (OR, 0.310; 95% CI, 0.119 to 0.809 for NPDR) (OR, 0.206; 95% CI, 0.063 to 0.673 for PDR). ME was associated with higher glycosylated hemoglobin levels (OR, 1.380; 95% CI, 1.032 to 1.845) and the use of rapid-acting insulin (OR, 5.211; 95% CI, 1.445 to 18.794).

CONCLUSION

Various clinical features were associated with DR and ME. Additional epidemiological and biorepository-based studies using this cohort are being conducted to deepen our understanding of diabetic complications in Korea.

Informatics for Nutritional Genetics and Genomics

While traditional nutrition science is focusing on nourishing population, modern nutrition is aiming at benefiting individual people. The goal of modern nutritional research is to promote health, prevent diseases, and improve performance. With the development of modern technologies like bioinformatics, metabolomics, and molecular genetics, this goal is becoming more attainable. In this chapter, we will discuss the new concepts and technologies especially in informatics and molecular genetics and genomics, and how they have been implemented to change the nutrition science and lead to the emergence of new branches like nutrigenomics, nutrigenetics, and nutritional metabolomics.

PECAM-1 Leu125Val (rs688) Polymorphism and Diabetic Nephropathy in Caucasians with Type 2 Diabetes Mellitus

Objectives. Platelet endothelial cell adhesion molecule-1 (PECAM-1) plays a key role in the transendothelial migration of circulating leukocytes during inflammation and in the maintenance of vascular endothelial integrity. We hypothesized that genetic variation in PECAM-1 gene could be associated with diabetic nephropathy (DN) and with the level of soluble PECAM-1 in Caucasians with type 2 diabetes mellitus (T2DM). Design and Methods. We analyzed the rs688 single nucleotide polymorphism of PECAM-1 gene C373G (Leu125Val) at exon 3, which encodes the first extracellular Ig-like domain that mediates the homophilic binding of PECAM-1, in 276 T2DM subjects with documented DN (cases) and 375 T2DM subjects without DN (controls), using a polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) strategy. Level of plasma soluble PECAM-1 (sPECAM-1) was measured by ELISA in a subpopulation of 120 diabetics with DN. Results. We found no association between the Leu125Val polymorphism and DN in subjects with T2DM. Likewise, the Leu125Val polymorphism was not associated with serum sPECAM-1 levels in a subpopulation of 120 diabetics with DN. Conclusion. The Leu125Val polymorphism of PECAM-1 and the level of sPECAM-1 are not associated with DN in T2DM subjects of Slovenian origin.

Novel tuberculosis susceptibility candidate genes revealed by the reconstruction and analysis of associative networks

Tuberculosis (TB) is a common infectious disease caused by M. tuberculosis. The risk of the disease is dependent on complex interactions between host genetics and environmental factors. Accumulated genomic data, along with novel methodological approaches such as associative networks, facilitate studies into the inherited basis of TB. In the current study, we carried out the reconstruction and analysis of an associative network representing molecular interactions between proteins and genes associated with TB. The network predominantly comprises of well-studied key proteins and genes which are able to govern the immune response against M. tuberculosis. However, this approach also allowed us to reveal 12 proteins encoded by genes, the polymorphisms of which have never been studied in relation to M. tuberculosis infection. These proteins include surface antigens (CD4, CD69, CD79, CD80, MUC16) and other important components of the immune response, inflammation, pathogen recognition, cell migration and activation (HCST, ADA, CP, SPP1, CXCR4, AGER, PACRG). Thus, the associative network approach enables the discovery of new candidate genes for TB susceptibility.

Losing weight for a better health: Role for the gut microbiota

In recent years, there have been several reviews on gut microbiota, obesity and cardiometabolism summarizing interventions that may impact the gut microbiota and have beneficial effects on the host (some examples include [1–3]). In this review we discuss how the gut microbiota changes with weight loss (WL) interventions in relation to clinical and dietary parameters. We also evaluate available evidence on the heterogeneity of response to these interventions. Two important questions were generated in this regard: 1) Can response to an intervention be predicted? 2) Could pre-intervention modifications to the gut microbiota optimize WL and metabolic improvement? Finally, we have delineated some recommendations for future research, such as the importance of assessment of diet and other environmental exposures in WL intervention studies, and the need to shift to more integrative approaches of data analysis.

Genetics, genomics and personalized medicine in Type 2 diabetes: a perspective on the Arab region

Type 2 diabetes (T2D) is a wide-spread, chronic metabolic disorder, affecting millions of people worldwide. The epidemic of diabetes has placed a huge strain on public health, longevity and economy. T2D occurs as a result of both genetic and environmental factors and is heterogeneous in its presentation across individuals. This review gives an overview of the genetic variations identified by genome-wide association studies which predispose individuals to T2D and those which are responsible for variable drug response across patients, and the necessity to adopt a personalized approach to diabetes management. We also include a perspective on diabetes in Arabs, given the high incidence of T2D and consanguineous marriages, and the need to understand associated genetic components in this vulnerable population.

The genomics of micronutrient requirements

Healthy nutrition is accepted as a cornerstone of public health strategies for reducing the risk of noncommunicable conditions such as obesity, cardiovascular disease, and related morbidities. However, many research studies continue to focus on single or at most a few factors that may elicit a metabolic effect. These reductionist approaches resulted in: (1) exaggerated claims for nutrition as a cure or prevention of disease; (2) the wide use of empirically based dietary regimens, as if one fits all; and (3) frequent disappointment of consumers, patients, and healthcare providers about the real impact nutrition can make on medicine and health. Multiple factors including environment, host and microbiome genetics, social context, the chemical form of the nutrient, its (bio)availability, and chemical and metabolic interactions among nutrients all interact to result in nutrient requirement and in health outcomes. Advances in laboratory methodologies, especially in analytical and separation techniques, are making the chemical dissection of foods and their availability in physiological tissues possible in an unprecedented manner. These omics technologies have opened opportunities for extending knowledge of micronutrients and of their metabolic and endocrine roles. While these technologies are crucial, more holistic approaches to the analysis of physiology and environment, novel experimental designs, and more sophisticated computational methods are needed to advance our understanding of how nutrition influences health of individuals.

A proteomic approach to obesity and type 2 diabetes

The incidence of obesity and type diabetes 2 has increased dramatically resulting in an increased interest in its biomedical relevance. However, the mechanisms that trigger the development of diabetes type 2 in obese patients remain largely unknown. Scientific, clinical and pharmaceutical communities are dedicating vast resources to unravel this issue by applying different omics tools. During the last decade, the advances in proteomic approaches and the Human Proteome Organization have opened and are opening a new door that may be helpful in the identification of patients at risk and to improve current therapies. Here, we briefly review some of the advances in our understanding of type 2 diabetes that have occurred through the application of proteomics. We also review, in detail, the current improvements in proteomic methodologies and new strategies that could be employed to further advance our understanding of this pathology. By applying these new proteomic advances, novel therapeutic and/or diagnostic protein targets will be discovered in the obesity/Type 2 diabetes area.

Enabling nutrient security and sustainability through systems research

Human and companion animal health depends upon nutritional quality of foods. Seed varieties, seasonal and local growing conditions, transportation, food processing, and storage, and local food customs can influence the nutrient content of food. A new and intensive area of investigation is emerging that recognizes many factors in these agri-food systems that influence the maintenance of nutrient quality which is fundamental to ensure nutrient security for world populations. Modeling how these systems function requires data from different sectors including agricultural, environmental, social, and economic, but also must incorporate basic nutrition and other biomedical sciences. Improving the agri-food system through advances in pre- and post-harvest processing methods, biofortification, or fortifying processed foods will aid in targeting nutrition for populations and individuals. The challenge to maintain and improve nutrient quality is magnified by the need to produce food locally and globally in a sustainable and consumer-acceptable manner for current and future populations. An unmet requirement for assessing how to improve nutrient quality, however, is the basic knowledge of how to define health. That is, health cannot be maintained or improved by altering nutrient quality without an adequate definition of what health means for individuals and populations. Defining and measuring health therefore becomes a critical objective for basic nutritional and other biomedical sciences.

MicroRNAs are potential prognostic and therapeutic targets in diabetic osteoarthritis

Osteoarthritis is an aging-related degenerative disease that severely influences the elders' life quality. However, there have been few clinical approaches available until now. Currently, more knowledge of the pathology of osteoarthritis has been illustrated. Especially, diabetes can be the only predictor of osteoarthritis. Due to its outstanding characteristics, MicroRNA has been considered as an efficient target in treating diseases. In this review, we will discuss a new insight focusing on the roles of microRNA in the progression of osteoarthritis-induced by diabetes, especially type II diabetes mellitus.

Amelioration of mitochondrial dysfunction-induced insulin resistance in differentiated 3T3-L1 adipocytes via inhibition of NF-κB pathways

A growing body of evidence suggests that activation of nuclear factor kappa B (NF-κB) signaling pathways is among the inflammatory mechanism involved in the development of insulin resistance and chronic low-grade inflammation in adipose tissues derived from obese animal and human subjects. Nevertheless, little is known about the roles of NF-κB pathways in regulating mitochondrial function of the adipose tissues. In the present study, we sought to investigate the direct effects of celastrol (potent NF-κB inhibitor) upon mitochondrial dysfunction-induced insulin resistance in 3T3-L1 adipocytes. Celastrol ameliorates mitochondrial dysfunction by altering mitochondrial fusion and fission in adipocytes. The levels of oxidative DNA damage, protein carbonylation and lipid peroxidation were down-regulated. Further, the morphology and quantification of intracellular lipid droplets revealed the decrease of intracellular lipid accumulation with reduced lipolysis. Moreover, massive production of the pro-inflammatory mediators tumor necrosis factor-α (TNF-α) and interleukin-1β (IL-1β) were markedly depleted. Insulin-stimulated glucose uptake activity was restored with the enhancement of insulin signaling pathways. This study signified that the treatments modulated towards knockdown of NF-κB transcription factor may counteract these metabolic insults exacerbated in our model of synergy between mitochondrial dysfunction and inflammation. These results demonstrate for the first time that NF-κB inhibition modulates mitochondrial dysfunction induced insulin resistance in 3T3-L1 adipocytes.

Translational genomics

The term "Translational Genomics" reflects both title and mission of this new journal. "Translational" has traditionally been understood as "applied research" or "development", different from or even opposed to "basic research". Recent scientific and societal developments have triggered a re-assessment of the connotation that "translational" and "basic" are either/or activities: translational research nowadays aims at feeding the best science into applications and solutions for human society. We therefore argue here basic science to be challenged and leveraged for its relevance to human health and societal benefits. This more recent approach and attitude are catalyzed by four trends or developments: evidence-based solutions; large-scale, high dimensional data; consumer/patient empowerment; and systems-level understanding.

Decreased global DNA methylation in the white blood cells of high fat diet fed vervet monkeys (Chlorocebus aethiops)

Epigenetic mechanisms are associated with the development of many chronic diseases and due to their reversible nature offer a unique window of opportunity to reverse the disease phenotype. This study investigated whether global DNA methylation correlates with dysglycemia in the vervet monkey (Chlorocebus aethiops). Diet-induced changes in DNA methylation were observed where global DNA methylation was twofold lower in monkeys fed a high fat diet (n = 10) compared to monkeys fed a standard diet (n = 15). An inverse correlation was observed between DNA methylation, blood glucose concentrations, bodyweight, and age, although the association was not statistically significant. Consumption of a high fat diet is associated with the development of metabolic disease; thus, these results suggest the use of global DNA methylation as a biomarker to assess the risk for metabolic disease. Moreover, this study provides further support for the use of the vervet monkey as a model system to study metabolic diseases such as type 2 diabetes. Integration of altered DNA methylation profiles into predictive models could facilitate risk stratification and enable intervention strategies to inhibit disease progression. Such interventions could include lifestyle modifications, for example, the increased consumption of functional foods with the capacity to modulate DNA methylation, thus potentially reversing the disease phenotype and preventing disease.