Self-organized metabotyping of obese individuals identifies clusters responding differently to bariatric surgery.

Weight loss through bariatric surgery is efficient for treatment or prevention of obesity related diseases such as type 2 diabetes and cardiovascular disease. Long term weight loss response does, however, vary among patients undergoing surgery. Thus, it is difficult to identify predictive markers while most obese individuals have one or more comorbidities. To overcome such challenges, an in-depth multiple omics analyses including fasting peripheral plasma metabolome, fecal metagenome as well as liver, jejunum, and adipose tissue transcriptome were performed for 106 individuals undergoing bariatric surgery. Machine leaning was applied to explore the metabolic differences in individuals and evaluate if metabolism-based patients' stratification is related to their weight loss responses to bariatric surgery. Using Self-Organizing Maps (SOMs) to analyze the plasma metabolome, we identified five distinct metabotypes, which were differentially enriched for KEGG pathways related to immune functions, fatty acid metabolism, protein-signaling, and obesity pathogenesis. The gut metagenome of the most heavily medicated metabotypes, treated simultaneously for multiple cardiometabolic comorbidities, was significantly enriched in Prevotella and Lactobacillus species. This unbiased stratification into SOM-defined metabotypes identified signatures for each metabolic phenotype and we found that the different metabotypes respond differently to bariatric surgery in terms of weight loss after 12 months. An integrative framework that utilizes SOMs and omics integration was developed for stratifying a heterogeneous bariatric surgery cohort. The multiple omics datasets described in this study reveal that the metabotypes are characterized by a concrete metabolic status and different responses in weight loss and adipose tissue reduction over time. Our study thus opens a path to enable patient stratification and hereby allow for improved clinical treatments.

A systems biology approach to study non-alcoholic fatty liver (NAFL) in women with obesity.

Non-alcoholic fatty liver disease (NAFLD) is now the most frequent global chronic liver disease. Individuals with NAFLD exhibited an increased risk of all-cause mortality driven by extrahepatic cancers and liver and cardiovascular disease. Once the disease is established, women have a higher risk of disease progression and worse outcome. It is therefore critical to deepen the current knowledge on the pathophysiology of NAFLD in women. Here, we used a systems biology approach to investigate the contribution of different organs to this disease. We analyzed transcriptomics profiles of liver and adipose tissues, fecal metagenomes, and plasma metabolomes of 55 women with and without NAFLD. We observed differences in metabolites, expression of human genes, and gut microbial features between the groups and revealed that there is substantial crosstalk between these different omics sets. Multi-omics analysis of individuals with NAFLD may provide novel strategies to study the pathophysiology of NAFLD in humans.

Hyperinsulinemia Is Highly Associated With Markers of Hepatocytic Senescence in Two Independent Cohorts.

Cellular senescence is an essentially irreversible growth arrest that occurs in response to various cellular stressors and may contribute to development of type 2 diabetes mellitus and nonalcoholic fatty liver disease (NAFLD). In this article, we investigated whether chronically elevated insulin levels are associated with cellular senescence in the human liver. In 107 individuals undergoing bariatric surgery, hepatic senescence markers were assessed by immunohistochemistry as well as transcriptomics. A subset of 180 participants from the ongoing Finnish Kuopio OBesity Surgery (KOBS) study was used as validation cohort. We found plasma insulin to be highly associated with various markers of cellular senescence in liver tissue. The liver transcriptome of individuals with high insulin revealed significant upregulation of several genes associated with senescence: p21, TGFß, PI3K, HLA-G, IL8, p38, Ras, and E2F. Insulin associated with hepatic senescence independently of NAFLD and plasma glucose. By using transcriptomic data from the KOBS study, we could validate the association of insulin with p21 in the liver. Our results support a potential role for hyperinsulinemia in induction of cellular senescence in the liver. These findings suggest possible benefits of lowering insulin levels in obese individuals with insulin resistance.