Consequences of Lipid Remodeling of Adipocyte Membranes Being Functionally Distinct from Lipid Storage in Obesity

Organ-Specific Responses to Chronic High-Fat Diets in Mice: Insights into Phospholipid Fatty Acid Distribution

Background/Objectives: This research aimed to investigate phospholipid fatty acid (PLFA) distribution in the brain, kidneys, and white adipose tissue (WAT) and lipid profiles in response to high-fat diets. Methods: Adult female C57BL/6 mice were fed high-fat diets containing 25% linseed, palm, or sunflower oil for 100 days. The fatty acid composition of dietary oils and tissue PL were analyzed using gas-liquid chromatography. Results: Linseed oil increased n-3 polyunsaturated fatty acids (PUFAs) with subsequent conversion into long-chain n-3 PUFAs in the brain and kidney PL, while only alpha-linolenic acid was elevated in WAT. Palm and sunflower oils resulted in unique PLFA distributions in the kidneys and WAT. Palm oil raised linoleic acid without conversion to pro-inflammatory n-6 PUFAs. Sunflower oil increased saturated palmitic acid, as opposed to the rise in monounsaturated oleic acid. Linseed oil also significantly improved lipid profiles, reducing LDL and increasing HDL levels while enhancing cardiovascular indices. Conclusions: This study demonstrates that dietary oils significantly impact organ-specific PLFA profiles, with linseed oil enriching brain and renal n-3 PUFAs, while palm and sunflower oils induce distinct modifications in the kidney and WAT. Moreover, linseed oil offers notable cardioprotective benefits due to the favorable lipid profile changes. These findings highlight the importance of dietary fat selection in achieving balanced lipid metabolism and suggest that diverse oil combinations may be essential for optimizing health outcomes.

Genome-wide DNA methylation analysis of body composition in Chinese monozygotic twins

BACKGROUND

Little is currently known about epigenetic alterations associated with body composition in obesity. Thus, we aimed to explore epigenetic relationships between genome-wide DNA methylation levels and three common traits of body composition as measured by body fat percentage (BF%), fat mass (FM) and lean body mass (LBM) among Chinese monozygotic twins.

METHODS

Generalized estimated equation model was used to regress the methylation level of CpG sites on body composition. Inference about Causation Through Examination Of Familial Confounding was used to explore the evidence of a causal relationship. Gene expression analysis was further performed to validate the results of differentially methylated genes.

RESULTS

We identified 32, 22 and 28 differentially methylated CpG sites (p < 10-5 ) as well as 20, 17 and eight differentially methylated regions (slk-corrected p < 0.05) significantly associated with BF%, FM and LBM which were annotated to 65 genes, showing partially overlapping. Causal inference demonstrated bidirectional causality between DNA methylation and body composition (p < 0.05). Gene expression analysis revealed significant correlations between expression levels of five differentially methylated genes and body composition (p < 0.05).

CONCLUSIONS

These DNA methylation signatures will contribute to increased knowledge about the epigenetic basis of body composition and provide new strategies for early prevention and treatment of obesity and its related diseases.

Precision nutrition for targeting pathophysiology of cardiometabolic phenotypes

Obesity is a heterogenous disease accompanied by a broad spectrum of cardiometabolic risk profiles. Traditional paradigms for dietary weight management do not address biological heterogeneity between individuals and have catastrophically failed to combat the global pandemic of obesity-related diseases. Nutritional strategies that extend beyond basic weight management to instead target patient-specific pathophysiology are warranted. In this narrative review, we provide an overview of the tissue-level pathophysiological processes that drive patient heterogeneity to shape distinct cardiometabolic phenotypes in obesity. Specifically, we discuss how divergent physiology and postprandial phenotypes can reveal key metabolic defects within adipose, liver, or skeletal muscle, as well as the integrative involvement of the gut microbiome and the innate immune system. Finally, we highlight potential precision nutritional approaches to target these pathways and discuss recent translational evidence concerning the efficacy of such tailored dietary interventions for different obesity phenotypes, to optimise cardiometabolic benefits.

Computer-Aided Imaging Analysis of Probe-Based Confocal Laser Endomicroscopy With Molecular Labeling and Gene Expression Identifies Markers of Response to Biological Therapy in IBD Patients: The Endo-Omics Study

BACKGROUND

We aimed to predict response to biologics in inflammatory bowel disease (IBD) using computerized image analysis of probe confocal laser endomicroscopy (pCLE) in vivo and assess the binding of fluorescent-labeled biologics ex vivo. Additionally, we investigated genes predictive of anti-tumor necrosis factor (TNF) response.

METHODS

Twenty-nine patients (15 with Crohn's disease [CD], 14 with ulcerative colitis [UC]) underwent colonoscopy with pCLE before and 12 to 14 weeks after starting anti-TNF or anti-integrin α4β7 therapy. Biopsies were taken for fluorescein isothiocyanate-labeled infliximab and vedolizumab staining and gene expression analysis. Computer-aided quantitative image analysis of pCLE was performed. Differentially expressed genes predictive of response were determined and validated in a public cohort.

RESULTS

In vivo, vessel tortuosity, crypt morphology, and fluorescein leakage predicted response in UC (area under the receiver-operating characteristic curve [AUROC], 0.93; accuracy 85%, positive predictive value [PPV] 89%; negative predictive value [NPV] 75%) and CD (AUROC, 0.79; accuracy 80%; PPV 75%; NPV 83%) patients. Ex vivo, increased binding of labeled biologic at baseline predicted response in UC (UC) (AUROC, 83%; accuracy 77%; PPV 89%; NPV 50%) but not in Crohn's disease (AUROC 58%). A total of 325 differentially expressed genes distinguished responders from nonresponders, 86 of which fell within the most enriched pathways. A panel including ACTN1, CXCL6, LAMA4, EMILIN1, CRIP2, CXCL13, and MAPKAPK2 showed good prediction of anti-TNF response (AUROC >0.7).

CONCLUSIONS

Higher mucosal binding of the drug target is associated with response to therapy in UC. In vivo, mucosal and microvascular changes detected by pCLE are associated with response to biologics in inflammatory bowel disease. Anti-TNF-responsive UC patients have a less inflamed and fibrotic state pretreatment. Chemotactic pathways involving CXCL6 or CXCL13 may be novel targets for therapy in nonresponders.

Integrative transcriptomic and metabolic analyses of the mammalian hibernating brain identifies a key role for succinate dehydrogenase in ischemic tolerance

Ischemic stroke results in a loss of tissue homeostasis and integrity, the underlying pathobiology of which stems primarily from the depletion of cellular energy stores and perturbation of available metabolites ¹ . Hibernation in thirteen-lined ground squirrels (TLGS), Ictidomys tridecemlineatus , provides a natural model of ischemic tolerance as these mammals undergo prolonged periods of critically low cerebral blood flow without evidence of central nervous system (CNS) damage ² . Studying the complex interplay of genes and metabolites that unfolds during hibernation may provide novel insights into key regulators of cellular homeostasis during brain ischemia. Herein, we interrogated the molecular profiles of TLGS brains at different time points within the hibernation cycle via RNA sequencing coupled with untargeted metabolomics. We demonstrate that hibernation in TLGS leads to major changes in the expression of genes involved in oxidative phosphorylation and this is correlated with an accumulation of the tricarboxylic acid (TCA) cycle intermediates citrate, cis-aconitate, and α-ketoglutarate-αKG. Integration of the gene expression and metabolomics datasets led to the identification of succinate dehydrogenase (SDH) as the critical enzyme during hibernation, uncovering a break in the TCA cycle at that level. Accordingly, the SDH inhibitor dimethyl malonate (DMM) was able to rescue the effects of hypoxia on human neuronal cells in vitro and in mice subjected to permanent ischemic stroke in vivo . Our findings indicate that studying the regulation of the controlled metabolic depression that occurs in hibernating mammals may lead to novel therapeutic approaches capable of increasing ischemic tolerance in the CNS.

Pathway-based integration of multi-omics data reveals lipidomics alterations validated in an Alzheimer's disease mouse model and risk loci carriers

Alzheimer's disease (AD) is a highly prevalent neurodegenerative disorder. Despite increasing evidence of the importance of metabolic dysregulation in AD, the underlying metabolic changes that may impact amyloid plaque formation are not understood, particularly for late-onset AD. This study analyzed genome-wide association studies (GWAS), transcriptomics, and proteomics data obtained from several data repositories to obtain differentially expressed (DE) multi-omics elements in mouse models of AD. We characterized the metabolic modulation in these data sets using gene ontology, transcription factor, pathway, and cell-type enrichment analyses. A predicted lipid signature was extracted from genome-scale metabolic networks (GSMN) and subsequently validated in a lipidomic data set derived from cortical tissue of ABCA-7 null mice, a mouse model of one of the genes associated with late-onset AD. Moreover, a metabolome-wide association study (MWAS) was performed to further characterize the association between dysregulated lipid metabolism in human blood serum and genes associated with AD risk. We found 203 DE transcripts, 164 DE proteins, and 58 DE GWAS-derived mouse orthologs associated with significantly enriched metabolic biological processes. Lipid and bioenergetic metabolic pathways were significantly over-represented across the AD multi-omics data sets. Microglia and astrocytes were significantly enriched in the lipid-predominant AD-metabolic transcriptome. We also extracted a predicted lipid signature that was validated and robustly modeled class separation in the ABCA7 mice cortical lipidome, with 11 of these lipid species exhibiting statistically significant modulations. MWAS revealed 298 AD single nucleotide polymorphisms-metabolite associations, of which 70% corresponded to lipid classes. These results support the importance of lipid metabolism dysregulation in AD and highlight the suitability of mapping AD multi-omics data into GSMNs to identify metabolic alterations.

RNA Sequencing of Intestinal Enterocytes Pre- and Post-Roux-en-Y Gastric Bypass Reveals Alteration in Gene Expression Related to Enterocyte Differentiation, Restitution, and Obesity with Regulation by Schlafen 12

BACKGROUND

The intestinal lining renews itself in a programmed fashion that can be affected by adaptation to surgical procedures such as gastric bypass.

METHODS

To assess adaptive mechanisms in the human intestine after Roux-en-Y gastric bypass (RYGB), we biopsied proximal jejunum at the anastomotic site during surgery to establish a baseline and endoscopically re-biopsied the same area 6-9 months after bypass for comparison. Laser microdissection was performed on pre- and post-RYGB biopsies to isolate enterocytes for RNA sequencing.

RESULTS

RNA sequencing suggested significant decreases in gene expression associated with G2/M DNA damage checkpoint regulation of the cell cycle pathway, and significant increases in gene expression associated with the CDP-diacylglycerol biosynthesis pathway TCA cycle II pathway, and pyrimidine ribonucleotide salvage pathway after RYGB. Since Schlafen 12 (SLFN12) is reported to influence enterocytic differentiation, we stained mucosa for SLFN12 and observed increased SLFN12 immunoreactivity. We investigated SLFN12 overexpression in HIEC-6 and FHs 74 Int intestinal epithelial cells and observed similar increased expression of the following genes that were also increased after RYGB: HES2, CARD9, SLC19A2, FBXW7, STXBP4, SPARCL1, and UTS.

CONCLUSIONS

Our data suggest that RYGB promotes SLFN12 protein expression, cellular mechanism and replication pathways, and genes associated with differentiation and restitution (HES2, CARD9, SLC19A2), as well as obesity-related genes (FBXW7, STXBP4, SPARCL1, UTS).

Heat-Killed Enterococcus faecalis EF-2001 Attenuate Lipid Accumulation in Diet-Induced Obese (DIO) Mice by Activating AMPK Signaling in Liver

To explore the inhibitory mechanism of heat-killed Enterococcus faecalis, EF-2001 on hepatic lipid deposition, a diet-induced obese (DIO) animal model was established by high-fat diet (HFD). The DIO C57BL/6 mice were divided into four groups: the normal group without HFD (ND, n = 8), obesity group (HFD, n = 8), experimental group (HFD + EF-2001, 200 mg/kg, n = 8), and positive control group (HFD + Orlistat, 60 mg/kg, n = 8). After 4 weeks, liver and adipose tissue were fixed in 10% paraformaldehyde, followed by embedding in paraffin for tissue sectioning. The differences in body mass, body fat ratio, fatty cell area, and lipid profiling of the liver (TC, LDL, and HDL) were also determined. Moreover, Western blot was performed to analyze the expression of lipid accumulation-related proteins, including AMPK, PPARγ, SREBP-1, ACC, and FAS. Compared with the HFD group, the HFD + EF-2001 group exhibited decreased fat mass, liver index, adipocyte area, TC, and LDL, and an increased level of HDL. The results of liver hematoxylin and eosin (H&E), and oil red O staining showed that the mice in each intervention group were improved on hepatic lipid accumulation, and the mice in the HFD + EF-2001 group were the most similar to those in the normal group when compared with the HFD group. From the Western blot results, we proved that EF-2001 activated the AMPK signaling pathway. EF-2001 significantly upregulated the expressions of p-AMPK and p-ACC and downregulated PPARγ, SREBP-1, and FAS in murine liver. Taken together, these results suggest that EF-2001 decrease lipid accumulation in the DIO model mice through the AMPK pathway and ameliorate liver damage by HFD.

The Insulin-Sensitizer Pioglitazone Remodels Adipose Tissue Phospholipids in Humans

The insulin-sensitizer pioglitazone exerts its cardiometabolic benefits in type 2 diabetes (T2D) through a redistribution of body fat, from ectopic and visceral areas to subcutaneous adipose depots. Whereas excessive weight gain and lipid storage in obesity promotes insulin resistance and chronic inflammation, the expansion of subcutaneous adipose by pioglitazone is associated with a reversal of these immunometabolic deficits. The precise events driving this beneficial remodeling of adipose tissue with pioglitazone remain unclear, and whether insulin-sensitizers alter the lipidomic composition of human adipose has not previously been investigated. Using shotgun lipidomics, we explored the molecular lipid responses in subcutaneous adipose tissue following 6months of pioglitazone treatment (45mg/day) in obese humans with T2D. Despite an expected increase in body weight following pioglitazone treatment, no robust effects were observed on the composition of storage lipids (i.e., triglycerides) or the content of lipotoxic lipid species (e.g., ceramides and diacylglycerides) in adipose tissue. Instead, pioglitazone caused a selective remodeling of the glycerophospholipid pool, characterized by a decrease in lipids enriched for arachidonic acid, such as plasmanylethanolamines and phosphatidylinositols. This contributed to a greater overall saturation and shortened chain length of fatty acyl groups within cell membrane lipids, changes that are consistent with the purported induction of adipogenesis by pioglitazone. The mechanism through which pioglitazone lowered adipose tissue arachidonic acid, a major modulator of inflammatory pathways, did not involve alterations in phospholipase gene expression but was associated with a reduction in its precursor linoleic acid, an effect that was also observed in skeletal muscle samples from the same subjects. These findings offer important insights into the biological mechanisms through which pioglitazone protects the immunometabolic health of adipocytes in the face of increased lipid storage.

Proteomic and Structural Manifestations of Cardiomyopathy in Rat Models of Obesity and Weight Loss

Obesity cardiomyopathy increases the risk of heart failure and death. Obesity is curable, leading to the restoration of the heart phenotype, but it is not clear if there are any after-effects of obesity present after weight loss. We characterize the proteomic landscape of obesity cardiomyopathy with an evaluation of whether the cardiac phenotype is still shaped after weight loss. Cardiomyopathy was validated by cardiac hypertrophy, fibrosis, oversized myocytes, and mTOR upregulation in a rat model of cafeteria diet-induced developmental obesity. By global proteomic techniques (LC-MS/MS) a plethora of molecular changes was observed in the heart and circulation of obese animals, suggesting abnormal utilization of metabolic substrates. This was confirmed by increased levels of cardiac ACSL-1, a key enzyme for fatty acid degradation and decreased GLUT-1, a glucose transporter in obese rats. Calorie restriction and weight loss led to the normalization of the heart's size, but fibrosis was still excessive. The proteomic compositions of cardiac tissue and plasma were different after weight loss as compared to control. In addition to morphological consequences, obesity cardiomyopathy involves many proteomic changes. Weight loss provides for a partial repair of the heart's architecture, but the trace of fibrotic deposition and proteomic alterations may occur.

A random forest based biomarker discovery and power analysis framework for diagnostics research

Background

Biomarker identification is one of the major and important goal of functional genomics and translational medicine studies. Large scale –omics data are increasingly being accumulated and can provide vital means for the identification of biomarkers for the early diagnosis of complex disease and/or for advanced patient/diseases stratification. These tasks are clearly interlinked, and it is essential that an unbiased and stable methodology is applied in order to address them. Although, recently, many, primarily machine learning based, biomarker identification approaches have been developed, the exploration of potential associations between biomarker identification and the design of future experiments remains a challenge.

Methods

In this study, using both simulated and published experimentally derived datasets, we assessed the performance of several state-of-the-art Random Forest (RF) based decision approaches, namely the Boruta method, the permutation based feature selection without correction method, the permutation based feature selection with correction method, and the backward elimination based feature selection method. Moreover, we conducted a power analysis to estimate the number of samples required for potential future studies.

Results

We present a number of different RF based stable feature selection methods and compare their performances using simulated, as well as published, experimentally derived, datasets. Across all of the scenarios considered, we found the Boruta method to be the most stable methodology, whilst the Permutation (Raw) approach offered the largest number of relevant features, when allowed to stabilise over a number of iterations. Finally, we developed and made available a web interface (https://joelarkman.shinyapps.io/PowerTools/) to streamline power calculations thereby aiding the design of potential future studies within a translational medicine context.

Conclusions

We developed a RF-based biomarker discovery framework and provide a web interface for our framework, termed PowerTools, that caters the design of appropriate and cost-effective subsequent future omics study.