Molecular remodeling of adipose tissue is associated with metabolic recovery after weight loss surgery.

BACKGROUND: Bariatric surgery is an effective therapy for individuals with severe obesity to achieve sustainable weight loss and to reduce comorbidities. Examining the molecular signature of subcutaneous adipose tissue (SAT) following different types of bariatric surgery may help in gaining further insight into their distinct metabolic impact. RESULTS: Subjects undergoing biliopancreatic diversion with duodenal switch (BPD-DS) showed a significantly higher percentage of total weight loss than those undergoing gastric bypass or sleeve gastrectomy (RYGB + SG) (41.7 ± 4.6 vs 28.2 ± 6.8%; p = 0.00005). Individuals losing more weight were also significantly more prone to achieve both type 2 diabetes and dyslipidemia remission (OR = 0.75; 95%CI = 0.51-0.91; p = 0.03). Whole transcriptome and methylome profiling showed that bariatric surgery induced a profound molecular remodeling of SAT at 12 months postoperative, mainly through gene down-regulation and hypermethylation. The extent of changes observed was greater following BPD-DS, with 61.1% and 49.8% of up- and down-regulated genes, as well as 85.7% and 70.4% of hyper- and hypomethylated genes being exclusive to this procedure, and mostly associated with a marked decrease of immune and inflammatory responses. Weight loss was strongly associated with genes being simultaneously differentially expressed and methylated in BPD-DS, with the strongest association being observed for GPD1L (r2 = 0.83; p = 1.4 × 10-6). CONCLUSIONS: Present findings point to the greater SAT molecular remodeling following BPD-DS as potentially linked with higher metabolic remission rates. These results will contribute to a better understanding of the metabolic pathways involved in the response to bariatric surgery and will eventually lead to the development of gene targets for the treatment of obesity. Trial registration ClinicalTrials.gov NCT02390973.

DNA methylation changes in association with trauma-focused psychotherapy efficacy in treatment-resistant depression patients: a prospective longitudinal study.

Background: Stressful events increase the risk for treatment-resistant depression (TRD), and trauma-focused psychotherapy can be useful for TRD patients exposed to early life stress (ELS). Epigenetic processes are known to be related to depression and ELS, but there is no evidence of the effects of trauma-focused psychotherapy on methylation alterations.Objective: We performed the first epigenome-wide association study to investigate methylation changes related to trauma-focused psychotherapies effects in TRD patients.Method: Thirty TRD patients assessed for ELS underwent trauma-focused psychotherapy, of those, 12 received trauma-focused cognitive behavioural therapy, and 18 Eye Movement Desensitization and Reprocessing (EMDR). DNA methylation was profiled with Illumina Infinium EPIC array at T0 (baseline), after 8 weeks (T8, end of psychotherapy) and after 12 weeks (T12 - follow-up). We examined differentially methylated CpG sites and regions, as well as pathways analysis in association with the treatment.Results: Main results obtained have shown 110 differentially methylated regions (DMRs) with a significant adjusted p-value area associated with the effects of trauma-focused psychotherapies in the entire cohort. Several annotated genes are related to inflammatory processes and psychiatric disorders, such as LTA, GFI1, ARID5B, TNFSF13, and LST1. Gene enrichment analyses revealed statistically significant processes related to tumour necrosis factor (TNF) receptor and TNF signalling pathway. Stratified analyses by type of trauma-focused psychotherapy showed statistically significant adjusted p-value area in 141 DMRs only for the group of patients receiving EMDR, with annotated genes related to inflammation and psychiatric disorders, including LTA, GFI1, and S100A8. Gene set enrichment analyses in the EMDR group indicated biological processes related to inflammatory response, particularly the TNF signalling pathway.Conclusion: We provide preliminary valuable insights into global DNA methylation changes associated with trauma-focused psychotherapies effects, in particular with EMDR treatment.

Stressful events increase treatment-resistant depression, and trauma-focused psychotherapy can be useful for these patients.Epigenome-wide data shows changes associated with trauma-focused psychotherapies, especially eye movement desensitization and reprocessing therapy, in treatment-resistant depression patients.Genes and biological pathways related to inflammatory and immune systems are among the most statistically significant results.

AgeGuess, a Methylomic Prediction Model for Human Ages.

Aging was a biological process under regulations from both inherited genetic factors and various molecular modifications within cells during the lifespan. Multiple studies demonstrated that the chronological age may be accurately predicted using the methylomic data. This study proposed a three-step feature selection algorithm AgeGuess for the age regression problem. AgeGuess selected 107 methylomic features as the gender-independent age biomarkers and the Support Vector Regressor (SVR) model using these biomarkers achieved 2.0267 in the mean absolute deviation (MAD) compared with the real chronological ages. Another regression algorithm Ridge achieved a slightly better MAD 1.9859 using the same biomarkers. The gender-independent age prediction models may be further improved by establishing two gender-specific models. And it's interesting to observe that there were only two methylation biomarkers shared by the two gender-specific biomarker sets and these two biomarkers were within the two known age-associated biomarker genes CALB1 and KLF14.

FeSTwo, a two-step feature selection algorithm based on feature engineering and sampling for the chronological age regression problem.

Accurate determination of the sample's chronological age is an important forensic problem. This regression problem may be improved by selecting appropriate methylomic features. Most of the existing feature selection algorithms, however, optimize the regression performance by considering only the original features. This study proposed four feature engineering strategies to transform the original methylomic features. The regression performance of the age regression model was improved by the resampling-based feature selection algorithm FeSTwo proposed in this study. FeSTwo outperformed the parallel algorithms used in the previous studies even with the electronic health record data. The age prediction performance of the FeSTwo-detected features was also confirmed for another independent dataset. The study results demonstrated that the proposed model, FeSTwo, led to a more than 8% reduction in root-mean-square error (RMSE) on the test dataset with only 70 features.

Detecting Methylomic Biomarkers of Pediatric Autism in the Peripheral Blood Leukocytes.

Autism was a spectrum of multiple complex diseases that required an interdisciplinary group of experts to make a diagnostic decision. Both genetic and environmental factors play essential roles in causing the onset of Autism. Therefore, this study hypothesized that methylomic biomarkers may facilitate the accurate Autism detection. A comprehensive series of biomarker detection algorithms were utilized to find the best methylomic biomarkers for the Autism detection using the methylomic data of the peripheral blood samples. The best model achieved 99.70% in accuracy with 678 methylomic biomarkers and a tenfold cross validation strategy. Some of the methylomic biomarkers were experimentally confirmed to be associated with the onset or development of Autism.

Assessing DNA Methylation in Cancer Stem Cells.

Many cancer-associated epigenetic signatures are also commonly observed in stem cells, just as epigenetic stem cell patterns are in cancer cells. DNA methylation is recognized as a hallmark of cancer development and progression. Herein, we describe two approaches to analyze DNA methylation, which can be applied to study or discover DNA methylation aberrations throughout the genome, as well as a more targeted investigation of regions of interest in cancer stem cells.