The value of combined MRI, enhanced CT and 18F-FDG PET/CT in the diagnosis of recurrence and metastasis after surgery for ovarian cancer.

OBJECTIVE: The purpose of this article was to investigate the value of combined MRI, enhanced CT and 18F-FDG PET/CT in the diagnosis of recurrence and metastasis after surgery for ovarian cancer. METHODS: Ninety-five ovarian cancer patients were selected as the study subjects, all of them underwent surgical treatment, and MRI, enhanced CT and 18F-FDG PET/CT were performed on all of them in the postoperative follow-up, and the pathological results after the second operation were used as the diagnostic "gold standard". The diagnostic value (sensitivity, specificity, accuracy, negative predictive value and positive predictive value) of the three examination methods alone or in combination for the diagnosis of postoperative recurrence and metastasis of ovarian cancer was compared, and the detection rate was calculated when the lesion was the unit of study, so as to compare the efficacy of the three methods in the diagnosis of postoperative recurrent metastatic lesions of ovarian cancer. RESULTS: The sensitivity, specificity, accuracy, positive predictive value and negative predictive value of the combined group were higher than those of MRI and enhanced CT for recurrence and metastasis of ovarian cancer after surgery, and the specificity, accuracy and positive predictive value of the combined group were higher than those of the 18F-FDG PET/CT group, and those of the 18F-FDG PET/CT group were higher than those of the enhanced CT group (all P < 0.05). When the postoperative recurrent metastatic lesions of ovarian cancer were used as the study unit, the detection rate of lesions in the combined group was higher than that of the three examinations detected individually, and the detection rate of lesions in 18F-FDG PET/CT was higher than that of enhanced CT and MRI (P < 0.05). CONCLUSION: The combination of MRI, enhanced CT and 18F-FDG PET/CT can accurately diagnose recurrence and metastasis of ovarian cancer after surgery, detect recurrent metastatic lesions as early as possible, and improve patients' prognosis.

Hyperactive lateral habenula mediates the comorbidity between rheumatoid arthritis and depression-like behaviors.

Rheumatoid arthritis (RA) patients have a high prevalence for depression. On the other hand, comorbid with depression is associated with worse prognosis for RA. However, little is known about the underlying mechanisms for the comorbidity between RA and depression. It remains to be elucidated which brain region is critically involved in the development of depression in RA, and whether alterations in the brain may affect pathological development of RA symptoms. Here, by combining clinical and animal model studies, we show that in RA patients, the level of depression is significantly correlated with the severity of RA disease activity and affects patients' quality of life. The collagen antibody-induced arthritis (CAIA) mouse model of RA also develops depression-like behaviors, accompanied by hyperactivity and alterations in gene expression reflecting cerebrovascular disruption in the lateral habenula (LHb), a brain region critical for processing negative valence. Importantly, inhibition of the LHb not only alleviates depression-like behaviors, but also results in rapid remission of RA symptoms and amelioration of RA-related pathological changes. Together, our study highlights a critical but previously overlooked contribution of hyperactive LHb to the comorbidity between RA and depression, suggesting that targeting LHb in conjunction with RA treatments may be a promising strategy for RA patients comorbid with depression.

Phenome-wide analyses identify an association between the parent-of-origin effects dependent methylome and the rate of aging in humans.

BACKGROUND: The variation in the rate at which humans age may be rooted in early events acting through the genomic regions that are influenced by such events and subsequently are related to health phenotypes in later life. The parent-of-origin-effect (POE)-regulated methylome includes regions enriched for genetically controlled imprinting effects (the typical type of POE) and regions influenced by environmental effects associated with parents (the atypical POE). This part of the methylome is heavily influenced by early events, making it a potential route connecting early exposures, the epigenome, and aging. We aim to test the association of POE-CpGs with early and later exposures and subsequently with health-related phenotypes and adult aging. RESULTS: We perform a phenome-wide association analysis for the POE-influenced methylome using GS:SFHS (Ndiscovery = 5087, Nreplication = 4450). We identify and replicate 92 POE-CpG-phenotype associations. Most of the associations are contributed by the POE-CpGs belonging to the atypical class where the most strongly enriched associations are with aging (DNAmTL acceleration), intelligence, and parental (maternal) smoking exposure phenotypes. A proportion of the atypical POE-CpGs form co-methylation networks (modules) which are associated with these phenotypes, with one of the aging-associated modules displaying increased within-module methylation connectivity with age. The atypical POE-CpGs also display high levels of methylation heterogeneity, fast information loss with age, and a strong correlation with CpGs contained within epigenetic clocks. CONCLUSIONS: These results identify the association between the atypical POE-influenced methylome and aging and provide new evidence for the "early development of origin" hypothesis for aging in humans.

Phenome-wide analysis identifies parent-of-origin effects on the human methylome associated with changes in the rate of aging.

Variation in the rate at which humans age may be rooted in early life events acting through genomic regions that are influenced by such events and subsequently are related to health phenotypes in later life. The parent-of-origin-effect (POE)-regulated methylome includes regions either enriched for genetically controlled imprinting effects (the typical type of POE) or atypical POE introduced by environmental effects associated with parents. This part of the methylome is heavily influenced by early life events, making it a potential route connecting early environmental exposures, the epigenome and the rate of aging. Here, we aim to test the association of POE-influenced methylation of CpG dinucleotides (POE-CpG sites) with early and later environmental exposures and subsequently with health-related phenotypes and adult aging phenotypes. We do this by performing phenome-wide association analyses of the POE-influenced methylome using a large family-based population cohort (GS:SFHS, Ndiscovery=5,087, Nreplication=4,450). At the single CpG level, 92 associations of POE-CpGs with phenotypic variation were identified and replicated. Most of the associations were contributed by POE-CpGs belonging to the atypical class and the most strongly enriched associations were with aging (DNAmTL acceleration), intelligence and parental (maternal) smoking exposure phenotypes. We further found that a proportion of the atypical-POE-CpGs formed co-methylation networks (modules) which are associated with these phenotypes, with one of the aging-associated modules displaying increased internal module connectivity (strength of methylation correlation across constituent CpGs) with age. Atypical POE-CpGs also displayed high levels of methylation heterogeneity and epigenetic drift (i.e. information loss with age) and a strong correlation with CpGs contained within epigenetic clocks. These results identified associations between the atypical-POE-influenced methylome and aging and provided new evidence for the "early development of origin" hypothesis for aging in humans.

The clinical value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) semi-quantitative parameters in monitoring neoadjuvant chemotherapy response of osteosarcoma.

BACKGROUND: Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a non-invasive technique which could monitor tumor morphology, blood vessel dynamics, and micro-environmental changes. PURPOSE: To evaluate the value of DCE-MRI semi-quantitative parameters in monitoring the neoadjuvant chemotherapy (NAC) response of osteosarcoma. MATERIAL AND METHODS: Twenty-five patients pathologically confirmed as osteosarcoma received four cycles of NAC followed by surgery. All patients underwent conventional and dynamic MRI twice, before starting chemotherapy and before surgical treatment. With a reference standard of histological response (tumor necrosis rate), semi-quantitative parameters were compared between good response group (TNR ≥ 90%) and non-response group (TNR < 90%). The differences between intra- and inter-group parameters before and after NAC were analyzed by Mann-Whitney U test. Receiver operating characteristic (ROC) analysis was generated to assess the parameters' efficacy in predicting the outcome of NAC. RESULTS: The changes were statistically significant on slope, maximum signal intensity (SImax), time to peak (TTP), signal enhanced extent (SEE), peak percent enhancement (PPE), washout rate (WOR), and enhancement rate (ER) in the good response group (P < 0.05), while only SImax and SEE were different in the non-response group after NAC. The changes in Slope, SImax, TTP, SEE, WOR, and ER were markedly different (P < 0.05) between the two groups after NAC. Also, at the threshold values of 3.2%/s, 175 s, and 5.4% (slope, TTP, and ER), the sensitivity and specificity for predicting good response to chemotherapy were 83.3% and 92.3%, 91.7% and 69.2%, 84.6% and 75.0%, respectively. CONCLUSION: Slope, TTP, and ER values could be used to evaluate and predict the response to NAC in osteosarcoma.

Lifestyle and Genetic Factors Modify Parent-of-Origin Effects on the Human Methylome.

BACKGROUND: parent-of-origin effects (POE) play important roles in complex disease and thus understanding their regulation and associated molecular and phenotypic variation are warranted. Previous studies mainly focused on the detection of genomic regions or phenotypes regulated by POE. Understanding whether POE may be modified by environmental or genetic exposures is important for understanding of the source of POE-associated variation, but only a few case studies addressing modifiable POE exist. METHODS: in order to understand this high order of POE regulation, we screened 101 genetic and environmental factors such as 'predicted mRNA expression levels' of DNA methylation/imprinting machinery genes and environmental exposures. POE-mQTL-modifier interaction models were proposed to test the potential of these factors to modify POE at DNA methylation using data from Generation Scotland: The Scottish Family Health Study(N=2315). FINDINGS: a set of vulnerable/modifiable POE-CpGs were identified (modifiable-POE-regulated CpGs, N=3). Four factors, 'lifetime smoking status' and 'predicted mRNA expression levels' of TET2, SIRT1 and KDM1A, were found to significantly modify the POE on the three CpGs in both discovery and replication datasets. We further identified plasma protein and health-related phenotypes associated with the methylation level of one of the identified CpGs. INTERPRETATION: the modifiable POE identified here revealed an important yet indirect path through which genetic background and environmental exposures introduce their effect on DNA methylation, motivating future comprehensive evaluation of the role of these modifiers in complex diseases. FUNDING: NSFC (81971270),H2020-MSCA-ITN(721815), Wellcome (204979/Z/16/Z,104036/Z/14/Z), MRC (MC_UU_00007/10, MC_PC_U127592696), CSO (CZD/16/6,CZB/4/276, CZB/4/710), SFC (HR03006), EUROSPAN (LSHG-CT-2006-018947), BBSRC (BBS/E/D/30002276), SYSU, Arthritis Research UK, NHLBI, NIH.

Genome-wide methylation data improves dissection of the effect of smoking on body mass index.

Variation in obesity-related traits has a genetic basis with heritabilities between 40 and 70%. While the global obesity pandemic is usually associated with environmental changes related to lifestyle and socioeconomic changes, most genetic studies do not include all relevant environmental covariates, so the genetic contribution to variation in obesity-related traits cannot be accurately assessed. Some studies have described interactions between a few individual genes linked to obesity and environmental variables but there is no agreement on their total contribution to differences between individuals. Here we compared self-reported smoking data and a methylation-based proxy to explore the effect of smoking and genome-by-smoking interactions on obesity related traits from a genome-wide perspective to estimate the amount of variance they explain. Our results indicate that exploiting omic measures can improve models for complex traits such as obesity and can be used as a substitute for, or jointly with, environmental records to better understand causes of disease.

Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation.

Characterizing genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. In the present study, we describe results of DNAm quantitative trait locus (mQTL) analyses on 32,851 participants, identifying genetic variants associated with DNAm at 420,509 DNAm sites in blood. We present a database of >270,000 independent mQTLs, of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15-17% of the additive genetic variance of DNAm. We show that the genetic architecture of DNAm levels is highly polygenic. Using shared genetic control between distal DNAm sites, we constructed networks, identifying 405 discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic variants are associated with both DNAm levels and complex diseases, but only in a minority of cases do these associations reflect causal relationships from DNAm to trait or vice versa, indicating a more complex genotype-phenotype map than previously anticipated.

Magnetic resonance elastography can predict the development of hepatocellular carcinoma: a meta-analysis and systematic review.

BACKGROUND: Hepatocellular carcinoma (HCC) has become the third leading cause of cancer-related death worldwide, and its incidence rate is increasing. Magnetic resonance elastography (MRE) can indirectly realize the accurate non-invasive evaluation of liver reserve function in HCC patients. In this study, we aimed to evaluate the effectiveness of MRE in the diagnosis of HCC patients. METHODS: We searched globally-recognized electronic databases, such as PubMed, EMBASE, China National Knowledge Infrastructure, and Cochrane Central, for relevant literature on MRE prediction of HCC. The diagnostic performance of all studies was quantitatively summarized using a bivariate random effects model including heterogeneity analysis, receiver operating characteristic (ROC) curve, and bias determination. RESULTS: The diagnostic accuracy of MRE for HCC was based on 1,735 patients. The sensitivity (31-100%) was lower than the specificity (81-94%). The overall sensitivity was 64% [95% confidence interval (CI): 46-79%; I2=92.44%], and the overall specificity was 85% (95% CI: 82-88%; I2=67.86%). Limited publication bias was observed in this study, and the sensitivity analysis showed that the study was robust. DISCUSSION: The results of our meta-analysis show that MRE has moderate sensitivity and excellent specificity in the detection of HCC. MRE can be an effective diagnostic tool for HCC and can provide strong support for the selection of clinical treatment methods and prognostic judgment.

Assessing the role of genome-wide DNA methylation between smoking and risk of lung cancer using repeated measurements: the HUNT study.

BACKGROUND: It is unclear if smoking-related DNA methylation represents a causal pathway between smoking and risk of lung cancer. We sought to identify novel smoking-related DNA methylation sites in blood, with repeated measurements, and to appraise the putative role of DNA methylation in the pathway between smoking and lung cancer development. METHODS: We derived a nested case-control study from the Trøndelag Health Study (HUNT), including 140 incident patients who developed lung cancer during 2009-13 and 140 controls. We profiled 850 K DNA methylation sites (Illumina Infinium EPIC array) in DNA extracted from blood that was collected in HUNT2 (1995-97) and HUNT3 (2006-08) for the same individuals. Epigenome-wide association studies (EWAS) were performed for a detailed smoking phenotype and for lung cancer. Two-step Mendelian randomization (MR) analyses were performed to assess the potential causal effect of smoking on DNA methylation as well as of DNA methylation (13 sites as putative mediators) on risk of lung cancer. RESULTS: The EWAS for smoking in HUNT2 identified associations at 76 DNA methylation sites (P < 5 × 10-8), including 16 novel sites. Smoking was associated with DNA hypomethylation in a dose-response relationship among 83% of the 76 sites, which was confirmed by analyses using repeated measurements from blood that was collected at 11 years apart for the same individuals. Two-step MR analyses showed evidence for a causal effect of smoking on DNA methylation but no evidence for a causal link between DNA methylation and the risk of lung cancer. CONCLUSIONS: DNA methylation modifications in blood did not seem to represent a causal pathway linking smoking and the lung cancer risk.

Identification of epigenome-wide DNA methylation differences between carriers of APOE ε4 and APOE ε2 alleles.

BACKGROUND: The apolipoprotein E (APOE) ε4 allele is the strongest genetic risk factor for late onset Alzheimer's disease, whilst the ε2 allele confers protection. Previous studies report differential DNA methylation of APOE between ε4 and ε2 carriers, but associations with epigenome-wide methylation have not previously been characterised. METHODS: Using the EPIC array, we investigated epigenome-wide differences in whole blood DNA methylation patterns between Alzheimer's disease-free APOE ε4 (n = 2469) and ε2 (n = 1118) carriers from the two largest single-cohort DNA methylation samples profiled to date. Using a discovery, replication and meta-analysis study design, methylation differences were identified using epigenome-wide association analysis and differentially methylated region (DMR) approaches. Results were explored using pathway and methylation quantitative trait loci (meQTL) analyses. RESULTS: We obtained replicated evidence for DNA methylation differences in a ~ 169 kb region, which encompasses part of APOE and several upstream genes. Meta-analytic approaches identified DNA methylation differences outside of APOE: differentially methylated positions were identified in DHCR24, LDLR and ABCG1 (2.59 × 10-100 ≤ P ≤ 2.44 × 10-8) and DMRs were identified in SREBF2 and LDLR (1.63 × 10-4 ≤ P ≤ 3.01 × 10-2). Pathway and meQTL analyses implicated lipid-related processes and high-density lipoprotein cholesterol was identified as a partial mediator of the methylation differences in ABCG1 and DHCR24. CONCLUSIONS: APOE ε4 vs. ε2 carrier status is associated with epigenome-wide methylation differences in the blood. The loci identified are located in trans as well as cis to APOE and implicate genes involved in lipid homeostasis.

Epigenetic prediction of major depressive disorder.

Variation in DNA methylation (DNAm) is associated with lifestyle factors such as smoking and body mass index (BMI) but there has been little research exploring its ability to identify individuals with major depressive disorder (MDD). Using penalised regression on genome-wide CpG methylation, we tested whether DNAm risk scores (MRS), trained on 1223 MDD cases and 1824 controls, could discriminate between cases (n = 363) and controls (n = 1417) in an independent sample, comparing their predictive accuracy to polygenic risk scores (PRS). The MRS explained 1.75% of the variance in MDD (ß = 0.338, p = 1.17 × 10-7) and remained associated after adjustment for lifestyle factors (ß = 0.219, p = 0.001, R2 = 0.68%). When modelled alongside PRS (ß = 0.384, p = 4.69 × 10-9) the MRS remained associated with MDD (ß = 0.327, p = 5.66 × 10-7). The MRS was also associated with incident cases of MDD who were well at recruitment but went on to develop MDD at a later assessment (ß = 0.193, p = 0.016, R2 = 0.52%). Heritability analyses found additive genetic effects explained 22% of variance in the MRS, with a further 19% explained by pedigree-associated genetic effects and 16% by the shared couple environment. Smoking status was also strongly associated with MRS (ß = 0.440, p ≤ 2 × 10-16). After removing smokers from the training set, the MRS strongly associated with BMI (ß = 0.053, p = 0.021). We tested the association of MRS with 61 behavioural phenotypes and found that whilst PRS were associated with psychosocial and mental health phenotypes, MRS were more strongly associated with lifestyle and sociodemographic factors. DNAm-based risk scores of MDD significantly discriminated MDD cases from controls in an independent dataset and may represent an archive of exposures to lifestyle factors that are relevant to the prediction of MDD.

Application of Multi-Modal Imaging Mediated by Iron Carbon Nanoparticles Based on Reinforcement Learning in the Diagnosis of Breast Nodules.

Breast cancer has become the first malignant tumor in women. Early detection and early treatment are the key to improve the prognosis of breast cancer patients. The key to the screening and diagnosis of breast cancer lies in the qualitative differential diagnosis of breast nodules. With the rapid development of MRI technology, especially the application of high field strength and ultra-high field strength, the role of breast MRI is increasingly prominent. MRI has the advantages of safety, no ionizing radiation, high resolution of soft tissue, high sensitivity and specificity for the diagnosis of early breast cancer. Multimodal imaging based on reinforcement learning and iron carbon nanoparticles plays an important role in the diagnosis of breast nodules. This paper first discusses the application of iron carbon nanoparticles and breast MRI multimodal imaging technology in tumor treatment, and then studies the application of iron carbon nanoparticles mediated multimodal imaging in the diagnosis of breast nodules through experimental methods. The experimental results show that multimodal imaging has a good effect in the diagnosis of breast nodules, which is helpful for the prevention and treatment of breast nodules.

Epigenome-wide analyses identify DNA methylation signatures of dementia risk.

INTRODUCTION: Dementia pathogenesis begins years before clinical symptom onset, necessitating the understanding of premorbid risk mechanisms. Here we investigated potential pathogenic mechanisms by assessing DNA methylation associations with dementia risk factors in Alzheimer's disease (AD)-free participants. METHODS: Associations between dementia risk measures (family history, AD genetic risk score [GRS], and dementia risk scores [combining lifestyle, demographic, and genetic factors]) and whole-blood DNA methylation were assessed in discovery and replication samples (n = ~400 to ~5000) from Generation Scotland. RESULTS: AD genetic risk and two dementia risk scores were associated with differential methylation. The GRS associated predominantly with methylation differences in cis but also identified a genomic region implicated in Parkinson disease. Loci associated with dementia risk scores were enriched for those previously associated with body mass index and alcohol consumption. DISCUSSION: Dementia risk measures show widespread association with blood-based methylation, generating several hypotheses for assessment by future studies.

Linking protein to phenotype with Mendelian Randomization detects 38 proteins with causal roles in human diseases and traits.

To efficiently transform genetic associations into drug targets requires evidence that a particular gene, and its encoded protein, contribute causally to a disease. To achieve this, we employ a three-step proteome-by-phenome Mendelian Randomization (MR) approach. In step one, 154 protein quantitative trait loci (pQTLs) were identified and independently replicated. From these pQTLs, 64 replicated locally-acting variants were used as instrumental variables for proteome-by-phenome MR across 846 traits (step two). When its assumptions are met, proteome-by-phenome MR, is equivalent to simultaneously running many randomized controlled trials. Step 2 yielded 38 proteins that significantly predicted variation in traits and diseases in 509 instances. Step 3 revealed that amongst the 271 instances from GeneAtlas (UK Biobank), 77 showed little evidence of pleiotropy (HEIDI), and 92 evidence of colocalization (eCAVIAR). Results were wide ranging: including, for example, new evidence for a causal role of tyrosine-protein phosphatase non-receptor type substrate 1 (SHPS1; SIRPA) in schizophrenia, and a new finding that intestinal fatty acid binding protein (FABP2) abundance contributes to the pathogenesis of cardiovascular disease. We also demonstrated confirmatory evidence for the causal role of four further proteins (FGF5, IL6R, LPL, LTA) in cardiovascular disease risk.

Identifying epigenetic biomarkers of established prognostic factors and survival in a clinical cohort of individuals with oropharyngeal cancer.

BACKGROUND: Smoking status, alcohol consumption and HPV infection (acquired through sexual activity) are the predominant risk factors for oropharyngeal cancer and are thought to alter the prognosis of the disease. Here, we conducted single-site and differentially methylated region (DMR) epigenome-wide association studies (EWAS) of these factors, in addition to ∼ 3-year survival, using Illumina Methylation EPIC DNA methylation profiles from whole blood in 409 individuals as part of the Head and Neck 5000 (HN5000) study. Overlapping sites between each factor and survival were then assessed using two-step Mendelian randomization to assess whether methylation at these positions causally affected survival. RESULTS: Using the MethylationEPIC array in an OPC dataset, we found novel CpG associations with smoking, alcohol consumption and ~ 3-year survival. We found no CpG associations below our multiple testing threshold associated with HPV16 E6 serological response (used as a proxy for HPV infection). CpG site associations below our multiple-testing threshold (PBonferroni < 0.05) for both a prognostic factor and survival were observed at four gene regions: SPEG (smoking), GFI1 (smoking), PPT2 (smoking) and KHDC3L (alcohol consumption). Evidence for a causal effect of DNA methylation on survival was only observed in the SPEG gene region (HR per SD increase in methylation score 1.28, 95% CI 1.14 to 1.43, P 2.12 × 10-05). CONCLUSIONS: Part of the effect of smoking on survival in those with oropharyngeal cancer may be mediated by methylation at the SPEG gene locus. Replication in data from independent datasets and data from HN5000 with longer follow-up times is needed to confirm these findings.

Germline Polymorphisms and Length of Survival of Nasopharyngeal Carcinoma: An Exome-Wide Association Study in Multiple Cohorts.

Germline polymorphisms are linked with differential survival outcomes in cancers but are not well studied in nasopharyngeal carcinoma (NPC). Here, a two-phase association study is conducted to discover germline polymorphisms that are associated with the prognosis of NPC. The discovery phase includes two consecutive hospital cohorts of patients with NPC from Southern China. Exome-wide genotypes at 246 173 single nucleotide polymorphisms (SNPs) are determined, followed by survival analysis for each SNP under Cox proportional hazard regression model. Candidate SNP is replicated in another two independent cohorts from Southern China and Singapore. Meta-analysis of all samples (n = 5553) confirms that the presence of rs1131636-T, located in the 3'-UTR of RPA1, confers an inferior overall survival (HR = 1.33, 95% CI = 1.20-1.47, P = 6.31 × 10-8). Bioinformatics and biological assays show that rs1131636 has regulatory effects on upstream RPA1. Functional studies further demonstrate that RPA1 promotes the growth, invasion, migration, and radioresistance of NPC cells. Additionally, miR-1253 is identified as a suppressor for RPA1 expression, likely through regulation of its binding affinity to rs1131636 locus. Collectively, these findings provide a promising biomarker aiding in stratifying patients with poor survival, as well as a potential drug target for NPC.

Genome-wide association study of antidepressant treatment resistance in a population-based cohort using health service prescription data and meta-analysis with GENDEP.

Antidepressants demonstrate modest response rates in the treatment of major depressive disorder (MDD). Despite previous genome-wide association studies (GWAS) of antidepressant treatment response, the underlying genetic factors are unknown. Using prescription data in a population and family-based cohort (Generation Scotland: Scottish Family Health Study; GS:SFHS), we sought to define a measure of (a) antidepressant treatment resistance and (b) stages of antidepressant resistance by inferring antidepressant switching as non-response to treatment. GWAS were conducted separately for antidepressant treatment resistance in GS:SFHS and the Genome-based Therapeutic Drugs for Depression (GENDEP) study and then meta-analysed (meta-analysis n = 4213, cases = 358). For stages of antidepressant resistance, a GWAS on GS:SFHS only was performed (n = 3452). Additionally, we conducted gene-set enrichment, polygenic risk scoring (PRS) and genetic correlation analysis. We did not identify any significant loci, genes or gene sets associated with antidepressant treatment resistance or stages of resistance. Significant positive genetic correlations of antidepressant treatment resistance and stages of resistance with neuroticism, psychological distress, schizotypy and mood disorder traits were identified. These findings suggest that larger sample sizes are needed to identify the genetic architecture of antidepressant treatment response, and that population-based observational studies may provide a tractable approach to achieving the necessary statistical power.

Publisher Correction: Parent of origin genetic effects on methylation in humans are common and influence complex trait variation.

In the original version of this Article, the legend in the upper panel of Figure 2 incorrectly read 'paternal imprinting' and should have read 'maternal imprinting'. This has been corrected in both the PDF and HTML versions of the Article.

Identification of novel differentially methylated sites with potential as clinical predictors of impaired respiratory function and COPD.

BACKGROUND: The causes of poor respiratory function and COPD are incompletely understood, but it is clear that genes and the environment play a role. As DNA methylation is under both genetic and environmental control, we hypothesised that investigation of differential methylation associated with these phenotypes would permit mechanistic insights, and improve prediction of COPD. We investigated genome-wide differential DNA methylation patterns using the recently released 850 K Illumina EPIC array. This is the largest single population, whole-genome epigenetic study to date. METHODS: Epigenome-wide association studies (EWASs) of respiratory function and COPD were performed in peripheral blood samples from the Generation Scotland: Scottish Family Health Study (GS:SFHS) cohort (n = 3781; 274 COPD cases and 2919 controls). In independent COPD incidence data (n = 149), significantly differentially methylated sites (DMSs; p < 3.6 × 10-8) were evaluated for their added predictive power when added to a model including clinical variables, age, sex, height and smoking history using receiver operating characteristic analysis. The Lothian Birth Cohort 1936 (LBC1936) was used to replicate association (n = 895) and prediction (n = 178) results. FINDINGS: We identified 28 respiratory function and/or COPD associated DMSs, which mapped to genes involved in alternative splicing, JAK-STAT signalling, and axon guidance. In prediction analyses, we observed significant improvement in discrimination between COPD cases and controls (p < .05) in independent GS:SFHS (p = .016) and LBC1936 (p = .010) datasets by adding DMSs to a clinical model. INTERPRETATION: Identification of novel DMSs has provided insight into the molecular mechanisms regulating respiratory function and aided prediction of COPD risk. Further studies are needed to assess the causality and clinical utility of identified associations. FUND: Wellcome Trust Strategic Award 10436/Z/14/Z.