Genome-wide DNA methylation pattern in visceral adipose tissue differentiates insulin-resistant from insulin-sensitive obese subject

Elucidating the potential mechanisms involved in the detrimental effect of excess body weight on insulin action is an important priority in counteracting obesity-associated diseases. The present study aimed to disentangle the epigenetic basis of insulin resistance by performing a genome-wide epigenetic analysis in visceral adipose tissue (VAT) from morbidly obese patients depending on the insulin sensitivity evaluated by the clamp technique. The global human methylome screening performed in VAT from 7 insulin-resistant (IR) and 5 insulin-sensitive (IS) morbidly obese patients (discovery cohort) analyzed using the Infinium HumanMethylation450 BeadChip array identified 982 CpG sites able to perfectly separate the IR and IS samples. The identified sites represented 538 unique genes, 10% of which were diabetes-associated genes. The current work identified novel IR-related genes epigenetically regulated in VAT, such as COL9A1, COL11A2, CD44, MUC4, ADAM2, IGF2BP1, GATA4, TET1, ZNF714, ADCY9, TBX5, and HDACM. The gene with the largest methylation fold-change and mapped by 5 differentially methylated CpG sites located in island/shore and promoter region was ZNF714. This gene presented lower methylation levels in IR than in IS patients in association with increased transcription levels, as further reflected in a validation cohort (n = 24; 11 IR and 13 IS). This study reveals, for the first time, a potential epigenetic regulation involved in the dysregulation of VAT that could predispose patients to insulin resistance and future type 2 diabetes in morbid obesity, providing a potential therapeutic target and biomarkers for counteracting this process

DNA methylation map in circulating leukocytes mirrors subcutaneous adipose tissue methylation pattern: a genome-wide analysis from non-obese and obese patients

The characterization of the epigenetic changes within the obesity-related adipose tissue will provide new insights to understand this metabolic disorder, but adipose tissue is not easy to sample in population-based studies. We aimed to evaluate the capacity of circulating leukocytes to reflect the adipose tissue-specific DNA methylation status of obesity susceptibility. DNA samples isolated from subcutaneous adipose tissue and circulating leukocytes were hybridized in the Infinium HumanMethylation 450 BeadChip. Data were compared between samples from obese (n = 45) and non-obese (n = 8-10) patients by Wilcoxon-rank test, unadjusted for cell type distributions. A global hypomethylation of the differentially methylated CpG sites (DMCpGs) was observed in the obese subcutaneous adipose tissue and leukocytes. The overlap analysis yielded a number of genes mapped by the common DMCpGs that were identified to reflect the obesity state in the leukocytes. Specifically, the methylation levels of FGFRL1, NCAPH2, PNKD and SMAD3 exhibited excellent and statistically significant efficiencies in the discrimination of obesity from non-obesity status (AUC > 0.80; p < 0.05) and a great correlation between both tissues. Therefore, the current study provided new and valuable DNA methylation biomarkers of obesity-related adipose tissue pathogenesis through peripheral blood analysis, an easily accessible and minimally invasive biological material instead of adipose tissue

A novel epigenetic signature for early diagnosis in lung cancer

Purpose: lung cancer remains as the leading cause of cancer-related death worldwide, mainly due to late diagnosis. Cytology is the gold-standard method for lung cancer diagnosis in minimally invasive respiratory samples, despite its low sensitivity. We aimed to identify epigenetic biomarkers with clinical utility for cancer diagnosis in minimally/noninvasive specimens to improve accuracy of current technologies. Experimental design: the identification of novel epigenetic biomarkers in stage I lung tumors was accomplished using an integrative genome-wide restrictive analysis of two different large public databases. DNA methylation levels for the selected biomarkers were validated by pyrosequencing in paraffin-embedded tissues and minimally invasive and noninvasive respiratory samples in independent cohorts. Results: we identified nine cancer-specific hypermethylated genes in early-stage lung primary tumors. Four of these genes presented consistent CpG island hypermethylation compared with nonmalignant lung and were associated with transcriptional silencing. A diagnostic signature was built using multivariate logistic regression model based on the combination of four genes: BCAT1, CDO1, TRIM58, and ZNF177. Clinical diagnostic value was also validated in multiple independent cohorts and yielded a remarkable diagnostic accuracy in all cohorts tested. Calibrated and cross-validated epigenetic model predicts with high accuracy the probability to detect cancer in minimally and noninvasive samples. We demonstrated that this epigenetic signature achieved higher diagnostic efficacy in bronchial fluids as compared with conventional cytology for lung cancer diagnosis. Conclusions: minimally invasive epigenetic biomarkers have emerged as promising tools for cancer diagnosis. The herein obtained epigenetic model in combination with current diagnostic protocols may improve early diagnosis and outcome of lung cancer patients

Super Resolution Fluorescence Microscopy and Tracking of Bacterial Flotillin (Reggie) Paralogs Provide Evidence for Defined-Sized Protein Microdomains within the Bacterial Membrane but Absence of Clusters Containing Detergent-Resistant Proteins

Biological membranes have been proposed to contain microdomains of a specific lipid composition, in which distinct groups of proteins are clustered. Flotillin-like proteins are conserved between pro—and eukaryotes, play an important function in several eukaryotic and bacterial cells, and define in vertebrates a type of so-called detergent-resistant microdomains. Using STED microscopy, we show that two bacterial flotillins, FloA and FloT, form defined assemblies with an average diameter of 85 to 110 nm in the model bacterium Bacillus subtilis. Interestingly, flotillin microdomains are of similar size in eukaryotic cells. The soluble domains of FloA form higher order oligomers of up to several hundred kDa in vitro, showing that like eukaryotic flotillins, bacterial assemblies are based in part on their ability to self-oligomerize. However, B. subtilis paralogs show significantly different diffusion rates, and consequently do not colocalize into a common microdomain. Dual colour time lapse experiments of flotillins together with other detergent-resistant proteins in bacteria show that proteins colocalize for no longer than a few hundred milliseconds, and do not move together. Our data reveal that the bacterial membrane contains defined-sized protein domains rather than functional microdomains dependent on flotillins. Based on their distinct dynamics, FloA and FloT confer spatially distinguishable activities, but do not serve as molecular scaffolds

DNA methylation map in circulating leukocytes mirrors subcutaneous adipose tissue methylation pattern: a genome-wide analysis from non-obese and obese patients

The characterization of the epigenetic changes within the obesity-related adipose tissue will provide new insights to understand this metabolic disorder, but adipose tissue is not easy to sample in population-based studies. We aimed to evaluate the capacity of circulating leukocytes to reflect the adipose tissue-specific DNA methylation status of obesity susceptibility. DNA samples isolated from subcutaneous adipose tissue and circulating leukocytes were hybridized in the Infinium HumanMethylation 450 BeadChip. Data were compared between samples from obese (n = 45) and non-obese (n = 8-10) patients by Wilcoxon-rank test, unadjusted for cell type distributions. A global hypomethylation of the differentially methylated CpG sites (DMCpGs) was observed in the obese subcutaneous adipose tissue and leukocytes. The overlap analysis yielded a number of genes mapped by the common DMCpGs that were identified to reflect the obesity state in the leukocytes. Specifically, the methylation levels of FGFRL1, NCAPH2, PNKD and SMAD3 exhibited excellent and statistically significant efficiencies in the discrimination of obesity from non-obesity status (AUC > 0.80; p < 0.05) and a great correlation between both tissues. Therefore, the current study provided new and valuable DNA methylation biomarkers of obesity-related adipose tissue pathogenesis through peripheral blood analysis, an easily accessible and minimally invasive biological material instead of adipose tissue

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

A genetic investigation of sex bias in the prevalence of attention-deficit/hyperactivity disorder

Background Attention-deficit/hyperactivity disorder (ADHD) shows substantial heritability and is 2-7 times more common in males than females. We examined two putative genetic mechanisms underlying this sex bias: sex-specific heterogeneity and higher burden of risk in female cases. Methods We analyzed genome-wide autosomal common variants from the Psychiatric Genomics Consortium and iPSYCH Project (20,183 cases, 35,191 controls) and Swedish populationregister data (N=77,905 cases, N=1,874,637 population controls). Results Genetic correlation analyses using two methods suggested near complete sharing of common variant effects across sexes, with rg estimates close to 1. Analyses of population data, however, indicated that females with ADHD may be at especially high risk of certain comorbid developmental conditions (i.e. autism spectrum disorder and congenital malformations), potentially indicating some clinical and etiological heterogeneity. Polygenic risk score (PRS) analysis did not support a higher burden of ADHD common risk variants in female cases (OR=1.02 [0.98-1.06], p=0.28). In contrast, epidemiological sibling analyses revealed that the siblings of females with ADHD are at higher familial risk of ADHD than siblings of affected males (OR=1.14, [95% CI: 1.11-1.18], p=1.5E-15). Conclusions Overall, this study supports a greater familial burden of risk in females with ADHD and some clinical and etiological heterogeneity, based on epidemiological analyses. However, molecular genetic analyses suggest that autosomal common variants largely do not explain the sex bias in ADHD prevalence