Plasma protein profiling reveals protein clusters related to BMI and insulin levels in middle-aged overweight subjects

Mass spectrometry as a lens into molecular human nutrition and health

Mass spectrometry (MS) has developed over the last decades into the most informative and versatile analytical technology in molecular and structural biology (). The platform enables discovery, identification, and characterisation of non-volatile biomolecules, such as proteins, peptides, DNA, RNA, nutrients, metabolites, and lipids at both speed and scale and can elucidate their interactions and effects. The versatility, robustness, and throughput have rendered MS a major research and development platform in molecular human health and biomedical science. More recently, MS has also been established as the central tool for 'Molecular Nutrition', enabling comprehensive and rapid identification and characterisation of macro- and micronutrients, bioactives, and other food compounds. 'Molecular Nutrition' thereby helps understand bioaccessibility, bioavailability, and bioefficacy of macro- and micronutrients and related health effects. Hence, MS provides a lens through which the fate of nutrients can be monitored along digestion via absorption to metabolism. This in turn provides the bioanalytical foundation for 'Personalised Nutrition' or 'Precision Nutrition' in which design and development of diets and nutritional products is tailored towards consumer and patient groups sharing similar genetic and environmental predisposition, health/disease conditions and lifestyles, and/or objectives of performance and wellbeing. The next level of integrated nutrition science is now being built as 'Systems Nutrition' where public and personal health data are correlated with life condition and lifestyle factors, to establish directional relationships between nutrition, lifestyle, environment, and health, eventually translating into science-based public and personal heath recommendations and actions. This account provides a condensed summary of the contributions of MS to a precise, quantitative, and comprehensive nutrition and health science and sketches an outlook on its future role in this fascinating and relevant field.

Cardiovascular Biomarkers of Obesity and Overlap With Cardiometabolic Dysfunction

Background Obesity may be associated with a range of cardiometabolic manifestations. We hypothesized that proteomic profiling may provide insights into the biological pathways that contribute to various obesity-associated cardiometabolic traits. We sought to identify proteomic signatures of obesity and examine overlap with related cardiometabolic traits, including abdominal adiposity, insulin resistance, and adipose depots. Methods and Results We measured 71 circulating cardiovascular disease protein biomarkers in 6981 participants (54% women; mean age, 49 years). We examined the associations of obesity, computed tomography measures of adiposity, cardiometabolic traits, and incident metabolic syndrome with biomarkers using multivariable regression models. Of the 71 biomarkers examined, 45 were significantly associated with obesity, of which 32 were positively associated and 13 were negatively associated with obesity (false discovery rate q<0.05 for all). There was significant overlap of biomarker profiles of obesity and cardiometabolic traits, but 23 biomarkers, including melanoma cell adhesion molecule (MCAM), growth differentiation factor-15 (GDF15), and lipoprotein(a) (LPA) were unique to metabolic traits only. Using hierarchical clustering, we found that the protein biomarkers clustered along 3 main trait axes: adipose, metabolic, and lipid traits. In longitudinal analyses, 6 biomarkers were significantly associated with incident metabolic syndrome: apolipoprotein B (apoB), insulin-like growth factor-binding protein 2 (IGFBP2), plasma kallikrein (KLKB1), complement C2 (C2), fibrinogen (FBN), and N-terminal pro-B-type natriuretic peptide (NT-proBNP); false discovery rate q<0.05 for all. Conclusions We found that the proteomic architecture of obesity overlaps considerably with associated cardiometabolic traits, implying shared pathways. Despite overlap, hierarchical clustering of proteomic profiles identified 3 distinct clusters of cardiometabolic traits: adipose, metabolic, and lipid. Further exploration of these novel protein targets and associated pathways may provide insight into the mechanisms responsible for the progression from obesity to cardiometabolic disease.

Serum Amyloid P and a Dendritic Cell-Specific Intercellular Adhesion Molecule-3-Grabbing Nonintegrin Ligand Inhibit High-Fat Diet-Induced Adipose Tissue and Liver Inflammation and Steatosis in Mice

High-fat diet (HFD)-induced inflammation is associated with a variety of health risks. The systemic pentraxin serum amyloid P (SAP) inhibits inflammation. SAP activates the high-affinity IgG receptor Fcγ receptor I (FcγRI; CD64) and the lectin receptor dendritic cell-specific intercellular adhesion molecule-3-grabbing nonintegrin (DC-SIGN; CD209). Herein, we show that for mice on an HFD, injections of SAP and a synthetic CD209 ligand (1866) reduced HFD-increased adipose and liver tissue inflammation, adipocyte differentiation, and lipid accumulation in adipose tissue. HFD worsened glucose tolerance test results and caused increased adipocyte size; for mice on an HFD, SAP improved glucose tolerance test results and reduced adipocyte size. Mice on an HFD had elevated serum levels of IL-1β, IL-23, interferon (IFN)-β, IFN-γ, monocyte chemoattractant protein 1 [MCP-1; chemokine (C-C motif) ligand 2 (CCL2)], and tumor necrosis factor-α. SAP reduced serum levels of IL-23, IFN-β, MCP-1, and tumor necrosis factor-α, whereas 1866 reduced IFN-γ. In vitro, SAP, but not 1866, treated cells isolated from white fat tissue (stromal vesicular fraction) produced the anti-inflammatory cytokine IL-10. HFD causes steatosis, and both SAP and 1866 reduced it. Conversely, compared with control mice, SAP knockout mice fed on a normal diet had increased white adipocyte cell sizes, increased numbers of inflammatory cells in adipose and liver tissue, and steatosis; and these effects were exacerbated on an HFD. SAP and 1866 may inhibit some, but not all, of the effects of a high-fat diet.

Altered serum levels of interleukin-3 in first-episode drug-naive and chronic medicated schizophrenia

Elevated serum levels of Interleukin-3 (IL-3), a major component of the cytokines, have been observed in chronic and medicated patients with schizophrenia, but this elevation may reflect either or both medication and illness chronicity effects. Thus, we compared serum IL-3 levels in first-episode drug-naive (FEDN) to chronic medicated patients with schizophrenia and examined the association of IL-3 with their psychopathological symptoms. Serum IL-3 levels were assessed in 55 FEDN patients, 52 chronic medicated patients and 43 healthy controls. Schizophrenia symptomatology was assessed with the Positive and Negative Syndrome Scale (PANSS). Serum IL-3 levels were measured by sandwich enzyme-linked immunosorbent assay (ELISA). We found significantly lower IL-3 levels in FEDN patients than both chronic patients and healthy controls (both p<0.001), while IL-3 levels in chronic patients were markedly higher than in healthy controls. No significant association was observed between IL-3 and any clinical psychopathology in FEDN patients; however, we found a significant correlation between serum IL-3 levels and the PANSS general psychopathology subscore in chronic medicated patients (p<0.05). Decreased IL-3 levels in FEDN patients suggest that suppressed immune function may be associated with developing schizophrenia, but as the disease progresses IL-3 levels increase perhaps related to medication treatment or other factors that occur during chronic illness.

Obese dogs with and without obesity-related metabolic dysfunction - a proteomic approach

Background

Approximately 20 % of obese dogs have metabolic disturbances similar to those observed in human metabolic syndrome, a condition known as obesity-related metabolic dysfunction. This condition is associated with insulin resistance and decreased circulating adiponectin concentrations, but clinical consequences have not been reported. In order to define better the metabolic changes associated with obesity-related metabolic dysfunction (ORMD), we compared the plasma proteomes of obese dogs with and without ORMD.

A proteomic analysis was conducted on plasma samples from 8 obese male dogs, 4 with ORMD and 4 without ORMD. The samples were first treated for the depletion of high-abundance proteins and subsequently analysed by using 2-DE DIGE methodology.

Results

Using mass spectrometry, 12 proteins were identified: albumin, apoliprotein A-I, C2, C3, C5, C4BPA, A2M, Uncharacterised protein (Fragment) OS = Canis familiaris, fibrinogen, IGJ, ITIH2, and glutathione peroxidase. In obese dogs with ORMD, the relative amounts of ten proteins (albumin, apoliprotein A-I, C2, C3, C5, C4BPA, A2M, Uncharacterised protein (Fragment) OS = Canis familiaris, fibrinogen, and ITIH2) were increased and two proteins (IGJ and glutathione peroxidase) were decreased, compared with obese dogs without ORMD. Specific assays were then used to confirm differences in serum albumin, apoliprotein A-I and glutathione peroxidase in a separate group of 20 overweight dogs, 8 with ORMD and 12 without ORMD.

Conclusions

The current study provides evidence that, in obese dogs with ORMD, there are changes in expression of proteins involved in lipid metabolism, immune response, and antioxidant status. The clinical significance of these changes remains to be defined.

The complement system in human cardiometabolic disease

The complement system has been implicated in obesity, fatty liver, diabetes and cardiovascular disease (CVD). Complement factors are produced in adipose tissue and appear to be involved in adipose tissue metabolism and local inflammation. Thereby complement links adipose tissue inflammation to systemic metabolic derangements, such as low-grade inflammation, insulin resistance and dyslipidaemia. Furthermore, complement has been implicated in pathophysiological mechanisms of diet- and alcohol induced liver damage, hyperglycaemia, endothelial dysfunction, atherosclerosis and fibrinolysis. In this review, we summarize current evidence on the role of the complement system in several processes of human cardiometabolic disease. C3 is the central component in complement activation, and has most widely been studied in humans. C3 concentrations are associated with insulin resistance, liver dysfunction, risk of the metabolic syndrome, type 2 diabetes and CVD. C3 can be activated by the classical, the lectin and the alternative pathway of complement activation; and downstream activation of C3 activates the terminal pathway. Complement may also be activated via extrinsic proteases of the coagulation, fibrinolysis and the kinin systems. Studies on the different complement activation pathways in human cardiometabolic disease are limited, but available evidence suggests that they may have distinct roles in processes underlying cardiometabolic disease. The lectin pathway appeared beneficial in some studies on type 2 diabetes and CVD, while factors of the classical and the alternative pathway were related to unfavourable cardiometabolic traits. The terminal complement pathway was also implicated in insulin resistance and liver disease, and appears to have a prominent role in acute and advanced CVD. The available human data suggest a complex and potentially causal role for the complement system in human cardiometabolic disease. Further, preferably longitudinal studies are needed to disentangle which aspects of the complement system and complement activation affect the different processes in human cardiometabolic disease.

Can bariatric surgery reduce risk of Alzheimer's disease?

Recent studies demonstrate that obesity is independently associated with poor neurocognitive outcomes, including cognitive impairment, increased risk for dementia, and regional alterations in brain structure. Bariatric surgery is an effective treatment for obesity and initial findings suggest that it may result in cognitive improvements. The current paper reviews and integrates recent research in this area, with a focus on potential mediators and moderators of neuropsychological outcome in bariatric surgery patients, including anesthetic and nutritional complications, and proposes novel avenues for continued study in this area.

A consideration of biomarkers to be used for evaluation of inflammation in human nutritional studies

To monitor inflammation in a meaningful way, the markers used must be valid: they must reflect the inflammatory process under study and they must be predictive of future health status. In 2009, the Nutrition and Immunity Task Force of the International Life Sciences Institute, European Branch, organized an expert group to attempt to identify robust and predictive markers, or patterns or clusters of markers, which can be used to assess inflammation in human nutrition studies in the general population. Inflammation is a normal process and there are a number of cells and mediators involved. These markers are involved in, or are produced as a result of, the inflammatory process irrespective of its trigger and its location and are common to all inflammatory situations. Currently, there is no consensus as to which markers of inflammation best represent low-grade inflammation or differentiate between acute and chronic inflammation or between the various phases of inflammatory responses. There are a number of modifying factors that affect the concentration of an inflammatory marker at a given time, including age, diet and body fatness, among others. Measuring the concentration of inflammatory markers in the bloodstream under basal conditions is probably less informative compared with data related to the concentration change in response to a challenge. A number of inflammatory challenges have been described. However, many of these challenges are poorly standardised. Patterns and clusters may be important as robust biomarkers of inflammation. Therefore, it is likely that a combination of multiple inflammatory markers and integrated readouts based upon kinetic analysis following defined challenges will be the most informative biomarker of inflammation.

Challenges in Biomarker Discovery: Combining Expert Insights with Statistical Analysis of Complex Omics Data

INTRODUCTION: The advent of high throughput technologies capable of comprehensive analysis of genes, transcripts, proteins and other significant biological molecules has provided an unprecedented opportunity for the identification of molecular markers of disease processes. However, it has simultaneously complicated the problem of extracting meaningful molecular signatures of biological processes from these complex datasets. The process of biomarker discovery and characterization provides opportunities for more sophisticated approaches to integrating purely statistical and expert knowledge-based approaches. AREAS COVERED: In this review we will present examples of current practices for biomarker discovery from complex omic datasets and the challenges that have been encountered in deriving valid and useful signatures of disease. We will then present a high-level review of data-driven (statistical) and knowledge-based methods applied to biomarker discovery, highlighting some current efforts to combine the two distinct approaches. EXPERT OPINION: Effective, reproducible and objective tools for combining data-driven and knowledge-based approaches to identify predictive signatures of disease are key to future success in the biomarker field. We will describe our recommendations for possible approaches to this problem including metrics for the evaluation of biomarkers.

Predicting total, abdominal, visceral and hepatic adiposity with circulating biomarkers in Caucasian and Japanese American women

Background

Characterization of abdominal and intra-abdominal fat requires imaging, and thus is not feasible in large epidemiologic studies.

Objective

We investigated whether biomarkers may complement anthropometry (body mass index [BMI], waist circumference [WC], and waist-hip ratio [WHR]) in predicting the size of the body fat compartments by analyzing blood biomarkers, including adipocytokines, insulin resistance markers, sex steroid hormones, lipids, liver enzymes and gastro-neuropeptides.

Methods

Fasting levels of 58 blood markers were analyzed in 60 healthy, Caucasian or Japanese American postmenopausal women who underwent anthropometric measurements, dual energy X-ray absorptiometry (DXA), and abdominal magnetic resonance imaging. Total, abdominal, visceral and hepatic adiposity were predicted based on anthropometry and the biomarkers using Random Forest models.

Results

Total body fat was well predicted by anthropometry alone (R² = 0.85), by the 5 best predictors from the biomarker model alone (leptin, leptin-adiponectin ratio [LAR], free estradiol, plasminogen activator inhibitor-1 [PAI1], alanine transaminase [ALT]; R² = 0.69), or by combining these 5 biomarkers with anthropometry (R² = 0.91). Abdominal adiposity (DXA trunk-to-periphery fat ratio) was better predicted by combining the two types of predictors (R² = 0.58) than by anthropometry alone (R² = 0.53) or the 5 best biomarkers alone (25(OH)-vitamin D₃, insulin-like growth factor binding protein-1 [IGFBP1], uric acid, soluble leptin receptor [sLEPR], Coenzyme Q10; R² = 0.35). Similarly, visceral fat was slightly better predicted by combining the predictors (R² = 0.68) than by anthropometry alone (R² = 0.65) or the 5 best biomarker predictors alone (leptin, C-reactive protein [CRP], LAR, lycopene, vitamin D₃; R² = 0.58). Percent liver fat was predicted better by the 5 best biomarker predictors (insulin, sex hormone binding globulin [SHBG], LAR, alpha-tocopherol, PAI1; R² = 0.42) or by combining the predictors (R² = 0.44) than by anthropometry alone (R² = 0.29).

Conclusion

The predictive ability of anthropometry for body fat distribution may be enhanced by measuring a small number of biomarkers. Studies to replicate these data in men and other ethnic groups are warranted.

Responses to high-fat challenges varying in fat type in subjects with different metabolic risk phenotypes: a randomized trial

Background

The ability of subjects to respond to nutritional challenges can reflect the flexibility of their biological system. Nutritional challenge tests could be used as an indicator of health status but more knowledge on metabolic and immune responses of different subjects to nutritional challenges is needed. The aim of this study was to compare the responses to high-fat challenges varying in fat type in subjects with different metabolic risk phenotypes.

Methodology/Principal Findings

In a cross-over design 42 men (age 50–70 y) consumed three high-fat shakes containing saturated fat (SFA), monounsaturated fat (MUFA) or n-3 polyunsaturated (PUFA). Men were selected on BMI and health status (lean, obese or obese diabetic) and phenotyped with MRI for adipose tissue distribution. Before and 2 and 4 h after shake consumption blood was drawn for measurement of expression of metabolic and inflammation-related genes in peripheral blood mononuclear cells (PBMCs), plasma triglycerides (TAG), glucose, insulin, cytokines and ex vivo PBMC immune response capacity. The MUFA and n-3 PUFA challenge, compared to the SFA challenge, induced higher changes in expression of inflammation genes MCP1 and IL1β in PBMCs. Obese and obese diabetic subjects had different PBMC gene expression and metabolic responses to high-fat challenges compared to lean subjects. The MUFA challenge induced the most pronounced TAG response, mainly in obese and obese diabetic subjects.

Conclusion/Significance

The PBMC gene expression response and metabolic response to high-fat challenges were affected by fat type and metabolic risk phenotype. Based on our results we suggest using a MUFA challenge to reveal differences in response capacity of subjects.

Trial Registration

ClinicalTrials.gov NCT00977262

Increased plasma VEGF levels in major depressive or manic episodes in patients with mood disorders

BACKGROUND

The neurotrophic hypothesis suggests that mood disorders are associated with dysfunction of neuronal networks under the influence of neurotrophic factors. Vascular endothelial growth factor (VEGF) is a neurotrophic factor as well as an angiogenic cytokine.

METHODS

We examined plasma VEGF levels in 35 unipolar patients who were diagnosed with current major depressive disorder (MDD), 35 bipolar patients who were diagnosed with bipolar I disorder, manic episode (BM), and 60 healthy controls. The severity of depressive or manic symptoms was measured using the Hamilton Depression Rating Scale (HDRS) or the Young Mania rating scale (YMRS), respectively.

RESULTS

Plasma VEGF levels were 163.28±135.33 pg/mL in MDD patients, 199.82±182.59 pg/mL in BM patients, and 110.05±109.57 pg/mL in healthy controls. Both MDD and BM patients had significantly higher VEGF levels than healthy controls when controlling for BMI as a covariate (p=0.010). Patients' VEGF levels were not correlated with either HDRS or YMRS scores.

LIMITATIONS

We assessed plasma VEGF levels at one time point, and we did not determine the source of VEGF in our samples.

CONCLUSIONS

Plasma VEGF levels were elevated in patients with acute episodes of major depressive disorder and bipolar disorder. Such an alteration of VEGF in acute episode, mood disorders may be associated with a neuroprotective role for VEGF.