Lipidomic profiling at the interface of metabolic surgery and cardiovascular disease

Multi-omics approaches in psychoneuroimmunology and health research: Conceptual considerations and methodological recommendations

The field of psychoneuroimmunology (PNI) has grown substantially in both relevance and prominence over the past 40 years. Notwithstanding its impressive trajectory, a majority of PNI studies are still based on a relatively small number of analytes. To advance this work, we suggest that PNI, and health research in general, can benefit greatly from adopting a multi-omics approach, which involves integrating data across multiple biological levels (e.g., the genome, proteome, transcriptome, metabolome, lipidome, and microbiome/metagenome) to more comprehensively profile biological functions and relate these profiles to clinical and behavioral outcomes. To assist investigators in this endeavor, we provide an overview of multi-omics research, highlight recent landmark multi-omics studies investigating human health and disease risk, and discuss how multi-omics can be applied to better elucidate links between psychological, nervous system, and immune system activity. In doing so, we describe how to design high-quality multi-omics studies, decide which biological samples (e.g., blood, stool, urine, saliva, solid tissue) are most relevant, incorporate behavioral and wearable sensing data into multi-omics research, and understand key data quality, integration, analysis, and interpretation issues. PNI researchers are addressing some of the most interesting and important questions at the intersection of psychology, neuroscience, and immunology. Applying a multi-omics approach to this work will greatly expand the horizon of what is possible in PNI and has the potential to revolutionize our understanding of mind-body medicine.

Bariatric Surgery-Induced Cardiac and Lipidomic Changes in Obesity-Related Heart Failure with Preserved Ejection Fraction

OBJECTIVE

To determine the effects of gastric bypass on myocardial lipid deposition and function and the plasma lipidome in women with obesity and heart failure with preserved ejection fraction (HFpEF).

METHODS

A primary cohort (N = 12) with HFpEF and obesity underwent echocardiography and magnetic resonance spectroscopy both before and 3 months and 6 months after bariatric surgery. Plasma lipidomic analysis was performed before surgery and 3 months after surgery in the primary cohort and were confirmed in a validation cohort (N = 22).

RESULTS

After surgery-induced weight loss, Minnesota Living with Heart Failure questionnaire scores, cardiac mass, and liver fat decreased (P < 0.02, P < 0.001, and P = 0.007, respectively); echo-derived e' increased (P = 0.03), but cardiac fat was unchanged. Although weight loss was associated with decreases in many plasma ceramide and sphingolipid species, plasma lipid and cardiac function changes did not correlate.

CONCLUSIONS

Surgery-induced weight loss in women with HFpEF and obesity was associated with improved symptoms, reverse cardiac remodeling, and improved relaxation. Although weight loss was associated with plasma sphingolipidome changes, cardiac function improvement was not associated with lipidomic or myocardial triglyceride changes. The results of this study suggest that gastric bypass ameliorates obesity-related HFpEF and that cardiac fat deposition and lipidomic changes may not be critical to its pathogenesis.

Defining and Using Preoperative Predictors of Diabetic Remission Following Bariatric Surgery

BACKGROUND

Diabetes remission is defined as the return of glycemic control in the absence of medication or insulin use after bariatric surgery. We sought to identify and assess the clinical utility of a predictive model for remission of type 2 diabetes mellitus in a population seeking bariatric surgery.

METHOD

A retrospective cohort design was applied to presurgical data on patients referred for Roux-en-Y gastric bypass (RYGB) or vertical sleeve gastrectomy (VSG). The model developed from logistic regression was compared with a published model through receiver operating characteristic analyses.

RESULTS

At 12 months postoperatively, 59.7% of the cohort was remitted, with no differences between RYGB and VSG. Logistic regression analyses yielded a model in which 4 preoperative variables reliably predicted remission. A Hosmer-Lemeshow goodness-of-fit test result of 0.204 indicated good fit of the developed prediction model to our outcome data. The predictive accuracy of this prediction model was compared with a published model, and an associated variation with diabetes years was substituted for age in our patient population. Our model was the most accurate.

CONCLUSIONS

Using these predictors, healthcare providers may be able to better counsel patients who are living with diabetes and considering bariatric surgery on the likelihood of achieving remission from the intervention. This refined prediction model requires further testing in a larger sample to evaluate its external validity.

Urinary Lipidomics: evidence for multiple sources and sexual dimorphism in healthy individuals

Urinary lipidomics may add new valuable biomarkers to the diagnostic armamentarium for early detection of metabolic and kidney diseases. Sources and composition of urinary lipids in healthy individuals, however, have not been investigated in detail. Shotgun lipidomics was used to quantify lipidomic profiles in native urine samples from 16 individuals (eight men, eight women) collected in five fractions over 24 h. All probands were comprehensively characterized by urinary and clinical indices. The mean total urinary lipid concentration per sample was 0.84 μM in men and 1.03 μM in women. We observed significant intra- and interindividual variations of lipid concentrations over time, but failed to detect a clear circadian pattern. Based on quantity and subclass composition it seems very unlikely that plasma serves as major source for the urinary lipidome. Considering lipid metabolites occurring in at least 20% of all samples 38 lipid species from 7 lipid classes were identified. Four phosphatidylserine and one phosphatidylethanolamine ether species (PE-O 36:5) were detectable in almost all urine samples. Sexual dimorphism has been found mainly for phosphatidylcholines and phosphatidylethanolamines. In men and in women urinary lipid species were highly correlated with urinary creatinine and albumin excretion, reflecting glomerular filtration and tubular transport processes. In women, however, lipid species deriving from urinary cells and cellular constituents of the lower genitourinary tract considerably contributed to the urinary lipidome. In conclusion, our study revealed the potential of urinary lipidomics but also the complexity of methodological challenges which have to be overcome for its implementation as a routine diagnostic tool for renal, urological and metabolic diseases.

Lipidomics: Techniques, Applications, and Outcomes Related to Biomedical Sciences

Lipidomics is a newly emerged discipline that studies cellular lipids on a large scale based on analytical chemistry principles and technological tools, particularly mass spectrometry. Recently, techniques have greatly advanced and novel applications of lipidomics in the biomedical sciences have emerged. This review provides a timely update on these aspects. After briefly introducing the lipidomics discipline, we compare mass spectrometry-based techniques for analysis of lipids and summarize very recent applications of lipidomics in health and disease. Finally, we discuss the status of the field, future directions, and advantages and limitations of the field.

Nutrigenomics, the Microbiome, and Gene-Environment Interactions: New Directions in Cardiovascular Disease Research, Prevention, and Treatment: A Scientific Statement From the American Heart Association

Cardiometabolic diseases are the leading cause of death worldwide and are strongly linked to both genetic and nutritional factors. The field of nutrigenomics encompasses multiple approaches aimed at understanding the effects of diet on health or disease development, including nutrigenetic studies investigating the relationship between genetic variants and diet in modulating cardiometabolic risk, as well as the effects of dietary components on multiple "omic" measures, including transcriptomics, metabolomics, proteomics, lipidomics, epigenetic modifications, and the microbiome. Here, we describe the current state of the field of nutrigenomics with respect to cardiometabolic disease research and outline a direction for the integration of multiple omics techniques in future nutrigenomic studies aimed at understanding mechanisms and developing new therapeutic options for cardiometabolic disease treatment and prevention.