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Hypersexual disorder (HD) was proposed as a diagnosis in the DSM-5 and the classification ?Compulsive Sexual Behavior Disorder? is now presented as an impulse-control disorder in ICD-11. HD incorporates several pathophysiological mechanisms; including impulsivity, compulsivity, sexual desire dysregulation and sexual addiction. No previous study investigated HD in a methylation analysis limited to microRNA (miRNA) associated CpG-sites. The genome wide methylation pattern was measured in whole blood from 60 subjects with HD and 33 healthy volunteers using the Illumina EPIC BeadChip. 8,852 miRNA associated CpG-sites were investigated in multiple linear regression analyses of methylation M-values to a binary independent variable of disease state (HD or healthy volunteer), adjusting for optimally determined covariates. Expression levels of candidate miRNAs were investigated in the same individuals for differential expression analysis. Candidate methylation loci were further studied for an association with alcohol dependence in an independent cohort of 107 subjects. Two CpG-sites were borderline significant in HD ? cg18222192 (MIR708)(p < 10E-05,p(FDR) = 5.81E-02) and cg01299774 (MIR4456)(p < 10E-06, p(FDR) = 5.81E-02). MIR4456 was significantly lower expressed in HD in both univariate (p < 0.0001) and multivariate (p < 0.05) analyses. Cg01299774 methylation levels were inversely correlated with expression levels of MIR4456 (p < 0.01) and were also differentially methylated in alcohol dependence (p = 0.026). Gene target prediction and pathway analysis revealed that MIR4456 putatively targets genes preferentially expressed in brain and that are involved in major neuronal molecular mechanisms thought to be relevant for HD, e.g., the oxytocin signalling pathway. In summary, our study implicates a potential contribution of MIR4456 in the pathophysiology of HD by putatively influencing oxytocin signalling.

Hypersexual disorder (HD) was proposed as a diagnosis in the DSM-5 and the classification ‘Compulsive Sexual Behavior Disorder’ is now presented as an impulse-control disorder in ICD-11. HD incorporates several pathophysiological mechanisms; including impulsivity, compulsivity, sexual desire dysregulation and sexual addiction. No previous study investigated HD in a methylation analysis limited to microRNA (miRNA) associated CpG-sites. The genome wide methylation pattern was measured in whole blood from 60 subjects with HD and 33 healthy volunteers using the Illumina EPIC BeadChip. 8,852 miRNA associated CpG-sites were investigated in multiple linear regression analyses of methylation M-values to a binary independent variable of disease state (HD or healthy volunteer), adjusting for optimally determined covariates. Expression levels of candidate miRNAs were investigated in the same individuals for differential expression analysis. Candidate methylation loci were further studied for an association with alcohol dependence in an independent cohort of 107 subjects. Two CpG-sites were borderline significant in HD – cg18222192 (MIR708)(p < 10E-05,pFDR = 5.81E-02) and cg01299774 (MIR4456)(p < 10E-06, pFDR = 5.81E-02). MIR4456 was significantly lower expressed in HD in both univariate (p < 0.0001) and multivariate (p < 0.05) analyses. Cg01299774 methylation levels were inversely correlated with expression levels of MIR4456 (p < 0.01) and were also differentially methylated in alcohol dependence (p = 0.026). Gene target prediction and pathway analysis revealed that MIR4456 putatively targets genes preferentially expressed in brain and that are involved in major neuronal molecular mechanisms thought to be relevant for HD, e.g., the oxytocin signalling pathway. In summary, our study implicates a potential contribution of MIR4456 in the pathophysiology of HD by putatively influencing oxytocin signalling.

Genome-wide association studies have identified a number of single-nucleotide polymorphisms (SNPs) that are associated with psychiatric diseases. Increasing body of evidence suggests a complex connection of SNPs and the transcriptional and epigenetic regulation of gene expression, which is poorly understood. In the current study, we investigated the interplay between genetic risk variants, shifts in methylation and mRNA levels in whole blood from 223 adolescents distinguished by a risk for developing psychiatric disorders. We analyzed 37 SNPs previously associated with psychiatric diseases in relation to genome-wide DNA methylation levels using linear models, with Bonferroni correction and adjusting for cell-type composition. Associations between DNA methylation, mRNA levels and psychiatric disease risk evaluated by the Development and Well-Being Assessment (DAWBA) score were identified by robust linear models, Pearson's correlations and binary regression models. We detected five SNPs (in HCRTR1, GAD1, HADC3 and FKBP5) that were associated with eight CpG sites, validating five of these SNP-CpG pairs. Three of these CpG sites, that is, cg01089319 (GAD1), cg01089249 (GAD1) and cg24137543 (DIAPH1), manifest in significant gene expression changes and overlap with active regulatory regions in chromatin states of brain tissues. Importantly, methylation levels at cg01089319 were associated with the DAWBA score in the discovery group. These results show how distinct SNPs linked with psychiatric diseases are associated with epigenetic shifts with relevance for gene expression. Our findings give a novel insight on how genetic variants may modulate risks for the development of psychiatric diseases.

We investigated five methylation markers recently linked to body-mass index, for their role in the neuropathology of obesity. In neuroimaging experiments, our analysis involving 23 participants showed that methylation levels for the cg07814318 site, which lies within the KLF13 gene, correlated with brain activity in the claustrum, putamen, cingulate gyrus, and frontal gyri, some of which have been previously associated to food signaling, obesity, or reward. Methylation levels at cg07814318 also positively correlated with ghrelin levels. Moreover, expression of KLF13 was augmented in the brains of obese and starved mice. Our results suggest the cg07814318 site could be involved in orexigenic processes, and also implicate KLF13 in obesity. Our findings are the first to associate methylation levels in blood with brain activity in obesity-related regions, and further support previous findings between ghrelin, brain activity, and genetic differences.

The ability of statins to strongly reduce low-density lipoprotein cholesterol (LDL-C) varies interindividually and is partially influenced by genetic variants. Based on a comprehensive analysis of 23 single nucleotide polymorphisms (SNPs) known to be associated with pharmacokinetics and dynamics of statins, we developed a genetic risk score to study its impact on the therapy outcome in elderly individuals under at least 5 years statin therapy. The study was performed in a population-based cohort of 1016 elderly individuals, which comprised 168 statin users investigated at age 75 and 80. Using random forest models, the major variants influencing LDL-C levels were summarized in a weighted GRS (wGRS). The wGRS was tested with lipid and glucose outcomes and validated in an independent population-based cohort including 221 statin users. Four SNPs within the APOE cluster (rs7412, rs4420638), ABCC2 (rs2002042) and CELSR/SORT1/PSRC1 (rs646776), displayed a major impact on statin efficacy. The wGRS was significantly associated with lower LDL-C at age 75 and 80. This association was replicated displaying similar results. GRS analysis is a powerful tool to evaluate the additive effects of genetic variants on statin response and to estimate the magnitude of LDL-C reduction to a considerable extent in the older population.

Single-nucleotide polymorphisms (SNPs) of the fat mass and obesity associated (FTO) gene are linked to obesity, but how these SNPs influence resting-state neural activation is unknown. Few brain-imaging studies have investigated the influence of obesity-related SNPs on neural activity, and no study has investigated resting-state connectivity patterns. We tested connectivity within three, main resting-state networks: default mode (DMN), sensorimotor (SMN), and salience network (SN) in 30 male participants, grouped based on genotype for the rs9939609 FTO SNP, as well as punishment and reward sensitivity measured by the Behavioral Inhibition (BIS) and Behavioral Activation System (BAS) questionnaires. Because obesity is associated with anomalies in both systems, we calculated a BIS/BAS ratio (BBr) accounting for features of both scores. A prominence of BIS over BAS (higher BBr) resulted in increased connectivity in frontal and paralimbic regions. These alterations were more evident in the obesity-associated AA genotype, where a high BBr was also associated with increased SN connectivity in dopaminergic circuitries, and in a subnetwork involved in somatosensory integration regarding food. Participants with AA genotype and high BBr, compared to corresponding participants in the TT genotype, also showed greater DMN connectivity in regions involved in the processing of food cues, and in the SMN for regions involved in visceral perception and reward-based learning. These findings suggest that neural connectivity patterns influence the sensitivity toward punishment and reward more closely in the AA carriers, predisposing them to developing obesity. Our work explains a complex interaction between genetics, neural patterns, and behavioral measures in determining the risk for obesity and may help develop individually-tailored strategies for obesity prevention., De två första författarna delar förstaförfattarskapet.

Currently, Roux-en Y gastric bypass (RYGB) is the most efficient therapy for severe obesity. Weight loss after surgery is, however, highly variable and genetically influenced. Genome-wide association studies have identified several single nucleotide polymorphisms (SNP) associated with body mass index (BMI) and waist-hip ratio (WHR). We aimed to identify two genetic risk scores (GRS) composed of weighted BMI and WHR-associated SNPs to estimate their impact on excess BMI loss (EBMIL) after RYGB surgery. Two hundred and thirty-eight obese patients (BMI 45.1 +/- 6.2 kg/m(2), 74 % women), who underwent RYGB, were genotyped for 35 BMI and WHR-associated SNPs and were followed up after 2 years. SNPs with high impact on post-surgical weight loss were filtered out using a random forest model. The filtered SNPs were combined into a GRS and analyzed in a linear regression model. An up to 11 % lower EBMIL with higher risk score was estimated for two GRS models (P = 0.026 resp. P = 0.021) composed of seven BMI-associated SNPs (closest genes: MC4R, TMEM160, PTBP2, NUDT3, TFAP2B, ZNF608, MAP2K5, GNPDA2, and MTCH2) and of three WHR-associated SNPs (closest genes: HOXC13, LYPLAL1, and DNM3-PIGC). Patients within the lowest GRS quartile had higher EBMIL compared to patients within the other three quartiles in both models. We identified two GRSs composed of BMI and WHR-associated SNPs with significant impact on weight loss after RYGB surgery using random forest analysis as a SNP selection tool. The GRS may be useful to pre-surgically evaluate the risks for patients undergoing RYGB surgery.

Background: DNA methylation is an essential nuclear process associated with genomic functions such as transcription factor binding and the regulation of gene expression. DNA methylation patterns can also serve as potential biomarkers for disease progression and response to therapy. However, the full dynamics of DNA methylation across daily physiologic events have not been fully elucidated. Objective: We sought to study how ingesting a standardized meal acutely affects peripheral blood DNA methylation. Design: We performed an observational study in healthy men (n = 26) on DNA methylation and gene expression in whole blood before and 160 min after the ingestion of a standardized meal. Cytosine-phosphate-guanine (CpG) methylation was assayed on the HumanMethylation450k microarray, and gene expression was measured with the Human Gene 2.1 ST Array. Results: Differential methylation after food intake was detected in 13% of the analyzed probes (63,207 CpG probes) at a 5% false discovery rate (FDR). This effect was driven by changes in leukocyte fractions as estimated from comparisons against methylation datasets generated from sorted leukocytes. When methylation values were adjusted for estimated leukocyte fractions, 541 probes were observed to be altered in the postprandial state (5% FDR). Conclusions: Apparent alterations in DNA methylation 160 min after meal ingestion mainly reflect changes in the estimated leukocyte population in whole blood. These results have major methodologic implications for genome-wide methylation studies because they highlight the strong underlying effects of changes in leukocyte fractions on CpG methylation patterns as well as the potential importance of meal-standardized sampling procedures for future investigations when alterations in white blood cell fractions are unavailable.