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Adams, M. J.

Publications and source records attributed to Adams, M. J..

At least 19 recordsLinked to original sources

The effects of CYP2C19 metaboliser status on DNA methylation

CYP2C19 metabolises many medications e.g., antidepressants, proton pump inhibitors and its enzymatic activity can be inferred from genetic variants within its encoding gene, linking to the efficacy of drug treatments and their side effects. It is however unclear if enzymatic activity is associated with local or widespread differences in DNA methylation. DNA methylation differences associated with CYP2C19 metabolising status may also have the potential to reveal interacting genes and pathways that underly CYP2C19 effects on drug response and health consequences. A methylome-wide association study was conducted in the Generation Scotland cohort (n=18,396) to investigate the linear and non-linear effects of CYP2C19 metaboliser status on genome-wide DNA methylation. Pathway enrichment analysis was conducted for the cytosine-guanine dinucleotide (CpG) probes significantly associated with CYP2C19 metaboliser status. We examined whether the associations between CYP2C19 metaboliser status and DNA methylation were independent of theuse of drugs that are inducers, inhibitors, or substrates of the CYP2C19 enzyme by interaction analysis. Forty-eight CpG probes were significantly associated with both linear and quadratic terms of CYP2C19 metaboliser status (PBonferroni < 0.05). These CpG are annotated to genes involving drug metabolism, inflammation, lipid level, and Type 2 diabetes. Pathway enrichment analysis showed enrichment in biological processes involving metabolic activities and the Cytochrome P450 pathway. However, DNA methylation signals associated with CYP2C19 metaboliser statusdid not vary by CYP2C19-related medication use. This research suggests that genetically-determined CYP2C19 metaboliser status is associated with both local and distal DNA methylation. These associations are independent of whether individuals were receiving drugs that are related to this enzyme.

pharmacology and toxicology↗

Methodological Considerations When Using Polygenic Scores to Explore Parent-Offspring Genetic Nurturing Effects

BackgroundResearch has begun to explore the effects of parental genetic nurturing on offspring outcomes using polygenic scores (PGSs). However, there are concerns regarding potential biases due to confounding when mediating parental phenotypes are included. MethodsDepression, educational attainment and height PGSs were generated for 2680 biological parent-offspring trios using genome-wide association study (GWAS) meta-analysis summary statistics in a large population study: Generation Scotland. Regression and pathway models were estimated incorporating PGSs for both parents and offspring to explore direct (offspring PGS) and genetic nurturing (parental PGS) effects on psychological distress, educational attainment and height. Genetic nurturing via parental phenotypes were incorporated into the models. To explore sources of bias we conducted simulation analyses of 10,000 trios using combinations of PGS predictive accuracy and accounted variance. ResultsModels incorporating both offspring and parental PGSs suggested positive parental genetic nurturing effects on offspring educational attainment, but not psychological distress or height. In contrast, models additionally incorporating parental phenotypic information suggested positive parent phenotype mediated genetic nurturing effects were at play for all phenotypes explored as well as negative residual genetic nurturing effects for height. 10,000 parent-offspring trio effects (without genetic nurturing effects) were simulated. Simulations demonstrated that models incorporating parent and offspring PGSs resulted in genetic nurturing effects that were unbiased. However, adding parental phenotypes as mediating variables results in biased positive estimates of parent phenotype mediated genetic nurturing effects and negative estimates of residual genetic nurturing effects. Biased effects increased in magnitude as PGS accuracy and accounted variance decreased. These biases were only eliminated when PGSs were simulated to capture the entirety of trait genetic variance. ConclusionResults suggest that in the absence of PGSs that capture all genetic variance, parental phenotypes act as colliders in the same way as heritable environments. Relatively simple models combining parental and offspring PGSs can be used to detect genetic nurturing effects in complex traits. However, our findings suggest alternative methods should be utilised when aiming to identify mediating phenotypes and potentially modifiable parental nurturing effects.

genomics↗

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.

genetics↗

Characterisation and Genetic Architecture of Major Depressive Disorder Subgroups Defined by Weight and Sleep Changes

Major depressive disorder, MDD, is highly heterogeneous and thus subgroups with different underlying aetiologies have been postulated. The aim of this work is to further characterise depression subgroups defined using sleep and weight changes. Probable lifetime MDD cases (n = 26,662) from the UK Biobank were stratified into three subgroups defined by self-reported weight and sleep changes during worst episode: (i) increased weight and sleep ({uparrow}WS), (ii) decreased weight and sleep ({downarrow}WS) and (iii) the remaining uncategorised individuals. Analyses compared the depression characteristics, mental health scores, neurological and inflammatory comorbidities and genetic architecture between subgroups and with 50,147 controls from UK Biobank. In contrast to {uparrow}WS depression, {downarrow}WS depression had a higher age of onset and lower proportion reporting countless or continuous episodes compared to uncategorised individuals. The {downarrow}WS depression also had a higher wellbeing score than the other subgroups. Analyses of subgroup comorbidities identified a novel association between {uparrow}WS depression and epilepsy. Subgroup-specific GWAS identified three genome-wide significant loci associated with {uparrow}WS in genes previously associated with immunometabolic traits and response to anticonvulsants. The effect of BMI adjustment in the genetic analyses of the subgroups and using broader weight-only definitions were also examined. The findings provide further evidence for differences in the characteristics and genetic architecture of depression subgroups defined by sleep and weight change and highlight the importance of dividing non-{uparrow}WS individuals into {downarrow}WS and uncategorised subgroups in analyses, as {downarrow}WS symptoms may identify a more acute depression subgroup.

genomics↗

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

Backgroundparent-of-origin effects (POE) play important roles in development and complex disease and thus understanding their regulation and associated molecular and phenotypic variation are warranted. Previous studies have 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 these modifiable POE exist. Methodsin 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 early/late lifestyle/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). Resultsa 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. Importantly, the POE on one of the CpGs were modified by both genetic and environmental factors. We further identified plasma protein and health-related phenotypes associated with the methylation level of one of the identified CpGs. Conclusionsthe 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. Key MessagesO_LIPrevious population studies showed that parent-origin-effects(POE) on human methylome can be widespread and affect health-related traits and diseases. C_LIO_LIWhether the POE remained stable throughout the life or can be modified by genetic or environmental factors were largely unknown. C_LIO_LIBy systematically screening 101 genetic and environmental factors in a large cohort(GS:SFHS) we provided the first population-level replicated evidence that those measuring lifestyle (smoking) and predicted expression of DNA methylation- or imprinting-machinery genes are amongst the factors that can modulate the POE of mQTLs for a set of CpG sites. C_LIO_LIWe found those modifiable-POE-regulated CpGs are also phenotypically relevant - one is associated with the plasma levels of CLEC4C and health-related phenotypes such as HDL levels. C_LIO_LIThe modifiable POE identified here revealed an important yet indirect path through which genetic background and environmental exposures introduce their effect on DNA methylation and their potential phenotypic consequences. This also provided a paradigm for further studies to explore how environmental and genetic effects can be integrated at methylation level. C_LI

genetics↗

DNA methylation signatures of aggression and closely related constructs: A meta-analysis of epigenome-wide studies across the lifespan

DNA methylation profiles of aggressive behavior may capture lifetime cumulative effects of genetic, stochastic, and environmental influences associated with aggression. Here, we report the first large meta-analysis of epigenome-wide association studies (EWAS) of aggressive behavior (N=15,324 participants). In peripheral blood samples of 14,434 participants from 18 cohorts with mean ages ranging from 7 to 68 years, 13 methylation sites were significantly associated with aggression (alpha=1.2x10-7; Bonferroni correction). In cord blood samples of 2,425 children from five cohorts with aggression assessed at mean ages ranging from 4 to 7 years, 83% of these sites showed the same direction of association with childhood aggression (r=0.74, p=0.006) but no epigenome-wide significant sites were found. Top-sites (48 at a false discovery rate of 5% in the peripherl blood meta-analysis or in a combined meta-analysis of peripheral blood and cord blood) have been associated with chemical exposures, smoking, cognition, metabolic traits, and genetic variation (mQTLs). Three genes whose expression levels were associated with top-sites were previously linked to schizophrenia and general risk tolerance. At six CpGs, DNA methylation variation in blood mirrors variation in the brain. On average 44% (range=3-82%) of the aggression-methylation association was explained by current and former smoking and BMI. These findings point at loci that are sensitive to chemical exposures with potential implications for neuronal functions. We hope these results to be a starting point for studies leading to applications as peripheral biomarkers and to reveal causal relationships with aggression and related traits.

genetics↗

A genome-wide association study finds genetic variants associated with neck or shoulder pain in UK Biobank

BackgroundCommon types of musculoskeletal conditions include pain in the neck and shoulder areas. This study seeks to identify the genetic variants associated with neck or shoulder pain based on a genome-wide association approach using 203,309 subjects from the UK Biobank cohort and look for replication evidence from the Generation Scotland: Scottish Family Health Study (GS:SFHS) and TwinsUK. MethodsCases in the UK Biobank were determined by a question which asked the participants if they had experienced pain in the neck or shoulder in the previous month influencing daily activities. Controls were the UK Biobank participants who reported no pain anywhere in the last month. A genome-wide association study was performed adjusting for age, sex, BMI and 9 population principal components. Significant and independent genetic variants were then sent to GS:SFHS and TwinsUK for replication. ResultsWe identified 3 genetic loci that were associated with neck or shoulder pain in the UK Biobank samples. The most significant locus was in an intergenic region in chromosome 17, rs12453010, having P = 1.66 x 10-11. The second most significant locus was located in the FOXP2 gene in chromosome 7 with P = 2.38 x 10-10 for rs34291892. The third locus was located in the LINC01572 gene in chromosome 16 with P = 4.50 x 10-8 for rs62053992. In the replication stage, among 4 significant and independent genetic variants, rs2049604 in the FOXP2 gene and rs62053992 in the LINC01572 gene were weakly replicated in GS:SFHS (P = 0.0240 and P = 0.0202, respectively). None of the single nucleotide polymorphisms (SNPs) were replicated in the TwinsUK cohort (P > 0.05). ConclusionsWe have identified 3 loci associated with neck or shoulder pain in the UK Biobank cohort, two of which were weakly supported in a replication cohort. Further evidence is needed to confirm their roles in neck or shoulder pain. SignificanceThis is the first genome-wide association study on neck or shoulder pain. We have identified 3 genetic loci (an intergenic region in chromosome 17, the FOXP2 gene in chromosome 7, and the LINC01572 gene in chromosome 16) that are associated with neck or shoulder pain using the UK Biobank cohort, among which the FOXP2 gene and the LINC01572 gene were weakly replicated by the Generation Scotland: Scottish Family Health Study (P < 0.05). The SNP heritability was 0.11, indicating neck or shoulder pain is a heritable trait. The tissue expression analysis suggested that neck or shoulder pain was related to multiple brain tissues, indicating the involvement of neuron function. The results will inform further research in the characterisation of the mechanisms of neck or shoulder pain.

genetics↗

Stratifying major depressive disorder by polygenic risk for schizophrenia in relation to structural brain measures

BackgroundSubstantial clinical heterogeneity of major depressive disorder (MDD) suggests it may group together individuals with diverse aetiologies. Identifying distinct subtypes should lead to more effective diagnosis and treatment, while providing more useful targets for further research. Genetic and clinical overlap between MDD and schizophrenia (SCZ) suggests an MDD subtype may share underlying mechanisms with SCZ.\n\nMethodsThe present study investigated whether a neurobiologically distinct subtype of MDD could be identified by SCZ polygenic risk score (PRS). We explored interactive effects between SCZ PRS and MDD case/control status on a range of cortical, subcortical and white matter metrics among 2,370 male and 2,574 female UK Biobank participants.\n\nResultsThere was a significant SCZ PRS by MDD interaction for rostral anterior cingulate cortex (RACC) thickness ({beta}=.191, q=.043). This was driven by a positive association between SCZ PRS and RACC thickness among MDD cases ({beta}=.098, p=.026), compared to a negative association among controls ({beta}=-.087, p=.002). MDD cases with low SCZ PRS showed thinner RACC, although the opposite difference for high-SCZ-PRS cases was not significant. There were nominal interactions for other brain metrics, but none remained significant after correcting for multiple comparisons.\n\nConclusionsOur significant results indicate that MDD case-control differences in RACC thickness vary as a function of SCZ PRS. Although this was not the case for most other brain measures assessed, our specific findings still provide some further evidence that MDD in the presence of high genetic risk for SCZ is subtly neurobiologically distinct from MDD in general.

neuroscience↗

Genetic comorbidity between major depression and cardio-metabolic disease, stratified by age at onset of major depression.

IntroductionIts imperative to understand the specific and shared aetiologies of major depression and cardio-metabolic disease, as both traits are frequently comorbid and each represents a major burden to society. This study examined whether there is a genetic association between major depression and cardio-metabolic traits and if this association is stratified by age at onset for major depression.\n\nMethodsPolygenic risk scores analysis and linkage disequilibrium score regression was performed to examine whether differences in shared genetic aetiology exist between depression case control status (N cases = 40,940, N controls = 67,532), earlier (N = 15,844), and later onset depression (N = 15,800) with body mass index, coronary artery disease, stroke, and type 2 diabetes in eleven data sets from the Psychiatric Genomics Consortium, Generation Scotland, and UK Biobank.\n\nResultsAll cardio-metabolic polygenic risk scores were associated with depression status. Significant genetic correlations were found between depression and body mass index, coronary artery disease, and type 2 diabetes. Higher polygenic risk for body mass index, coronary artery disease and type 2 diabetes was associated with both early and later onset depression, while higher polygenic risk for stroke was associated with later onset depression only. Significant genetic correlations were found between body mass index and later onset depression, and between coronary artery disease and both early and late onset depression.\n\nConclusionsThe phenotypic associations between major depression and cardio-metabolic traits may partly reflect their overlapping genetic aetiology irrespective of the age depression first presents.

genetics↗

Expression quantitative trait loci-derived scores and white matter microstructure in UK Biobank: a novel approach to integrating genetics and neuroimaging

BackgroundExpression quantitative trait loci (eQTL) are genetic variants associated with gene expression. Using genome-wide genotype data, it is now possible to impute gene expression using eQTL mapping efforts. This approach can be used to analyse previously unexplored relationships between gene expression and heritable in vivo measures of human brain structural connectivity.\n\nMethodsUsing large-scale eQTL mapping studies, we computed 6,457 gene expression scores (eQTL scores) using genome-wide genotype data in UK Biobank, where each score represents a genetic proxy measure of gene expression. These scores were then tested for associations with two diffusion tensor imaging measures, fractional anisotropy (NFA=14,518) and mean diffusivity (NMD=14,485), representing white matter structural integrity.\n\nResultsWe found FDR-corrected significant associations between 8 eQTL scores and structural connectivity phenotypes, including global and regional measures ({beta}absolute FA=0.0339-0.0453; MD=0.0308-0.0381) and individual tracts ({beta}absolute FA=0.0320-0.0561; MD=0.0295-0.0480). The loci within these eQTL scores have been reported to regulate expression of genes involved in various brain-related processes and disorders, such as neurite outgrowth and Parkinsons disease (DCAKD, SLC35A4, SEC14L4, SRA1, NMT1, CPNE1, PLEKHM1, UBE3C).\n\nDiscussionOur findings indicate that eQTL scores are associated with measures of in vivo brain connectivity and provide novel information not previously found by conventional genome-wide association studies. Although the role of expression of these genes regarding white matter microstructural integrity is not yet clear, these findings suggest it may be possible, in future, to map potential trait- and disease-associated eQTL to in vivo brain connectivity and better understand the mechanisms of psychiatric disorders and brain traits, and their associated imaging findings.

bioinformatics↗

White matter microstructure and its relation to longitudinal measures of depressive symptoms in mid-late life

BackgroundStudies of white matter microstructure in depression typically show alterations in depressed individuals, but they are frequently limited by small sample sizes and the absence of longitudinal measures of depressive symptoms. Depressive symptoms are however dynamic, and understanding the neurobiology of different trajectories could have important clinical implications.\n\nMethodsWe examined associations between current and longitudinal measures of depressive symptoms and white matter microstructure (Fractional Anisotropy, FA; Mean Diffusivity; MD) in the UK Biobank Imaging study. Depressive symptoms were assessed on 2-4 occasions over 5.9 to 10.7 years (on N=18,959 individuals on at least two occasions, N=4,444 on four occasions) from which we derived four measures of depressive symptomatology; (i) cross-sectional measure at the time of scan (imaging was conducted at a single time point), and three longitudinal measures, (ii) trajectory (iii) mean and (iv) intra-subject variance over time.\n\nResultsDecreased white matter microstructure in the anterior thalamic radiation demonstrated significant associations across all four measures of depressive symptoms (for MD: {beta}=0.020 to 0.029, pcorr<0.030). The greatest effect sizes were however seen between decreasing white matter integrity and increasing longitudinal progression of symptoms (for MD: {beta}=0.030 to 0.040, pcorr<0.049). Cross-sectional symptom severity was particularly associated with decreased white matter integrity in association fibres and thalamic radiations (MD: {beta}=0.015 to 0.039, pcorr<0.041). While greater mean and within subject variance of depressive symptoms were mainly associated with decreased white matter microstructure within projection fibres (MD: {beta}=0.019 to 0.029, pcorr<0.044).\n\nConclusionsThese findings indicate shared and differential neurobiological associations with severity, course and intra-subject variability of depressive symptoms. This enriches our understanding of the neurobiology underlying dynamic features of the disorder.

neuroscience↗

A phenome-wide association and Mendelian Randomisation study of polygenic risk for depression in UK Biobank

Depression is the leading cause of worldwide disability but there remains considerable uncertainty regarding its neural and behavioural associations. Depression is known to be heritable with a polygenic architecture, and results from genome-wide associations studies are providing summary statistics with increasing polygenic signal that can be used to estimate genetic risk scores for prediction in independent samples. This provides a timely opportunity to identify traits that are associated with polygenic risk of depression in the large and consistently phenotyped UK Biobank sample. Using the Psychiatric Genomics Consortium (PGC), 23andMe and non-imaging UK Biobank datasets as reference samples, we estimated polygenic risk scores for depression (depression-PRS) in a discovery sample of 10,674 people and a replication sample of 11,214 people from the UK Biobank Imaging Study, testing for associations with 210 behavioural and 278 neuroimaging phenotypes. In the discovery sample, 93 traits were significantly associated with depression-PRS after multiple testing correction. Among these, 92 traits were in the same direction, and 69 were significant in the replication analysis. For imaging traits that replicated across samples, higher depression-PRS was associated with lower global white matter microstructure, association-fibre and thalamic-radiation microstructural integrity (absolute {beta}: 0.023 to 0.040, PFDR: 0.045 to 3.92x10-4). Mendelian Randomisation analysis showed a causal effect of liability to depression on these structural brain measures ({beta}: 0.125 to 0.707, pFDR<0.048). Replicated behavioural traits that positively associated with depression-PRS included sleep problems, smoking status, measures of pain and stressful life experiences, and those negatively associated with depression-PRS included subjective ratings of physical health (absolute {beta}: 0.014 to 0.180, PFDR: 0.046 to 8.54x10-15). Effect of depression PRS on mental health in the presence of reported childhood trauma, stressful life events and those living in more socially deprived areas showed increased variance explained by 1.42 - 4.08 times (pFDR for their interaction with depression-PRS: 0.049 to 0.003). Overall, the present study revealed replicable associations between depression-PRS and white matter microstructure that appeared to be a causal consequence of liability to depression. Analyses provided further evidence that greater effects of polygenic risk of depression are found in individuals exposed to risk-conferring environments.

genetics↗

CRISPR disruption and UK Biobank analysis of a highly conserved polymorphic enhancer suggests its role in anxiety and male alcohol intake.

Excessive alcohol intake is associated with 5.9% of global deaths. However, this figure is especially acute in men such that 7.6% of deaths can be attributed to alcohol intake. Previous studies identified a significant interaction between genotypes of the galanin (GAL) gene with anxiety and alcohol abuse in different male populations but were unable to define a mechanism. To address these issues the current study analysed the human UK Biobank cohort and identified a significant interaction (n=115,865; p=0.0007) between allelic variation (GG or CA genotypes) in the highly conserved human GAL5.1 enhancer, alcohol intake (AUDIT questionnaire scores) and anxiety in men that was consistent with these previous studies. Critically, disruption of GAL5.1 in mice using CRISPR genome editing significantly reduced GAL expression in the amygdala and hypothalamus whilst producing a corresponding reduction in ethanol intake in KO mice. Intriguingly, we also found evidence of reduced anxiety-like behaviour in male GAL5.1KO animals mirroring that seen in humans. Using bioinformatic analysis and co-transfection studies we further identified the EGR1 transcription factor, that is co expressed with GAL in amygdala and hypothalamus, as being important in the protein kinase C (PKC) supported activity of the GG genotype of GAL5.1 but less so in the CA genotype. Our unique study uses a novel combination of human association analysis, CRISPR genome editing in mice, animal behavioural analysis and cell culture studies to identify a highly conserved regulatory mechanism linking anxiety and alcohol intake that might contribute to increased susceptibility to anxiety and alcohol abuse in men.

genetics↗

Stratifying depression by neuroticism: revisiting a diagnostic tradition using GWAS data

Major depressive disorder and neuroticism share a large genetic basis. We sought to determine whether this shared basis could be decomposed to identify genetic factors that are specific to depression. We analysed two sets of summary statistics from genome-wide association studies of depression (from the Psychiatric Genomics Consortium and 23andMe) and compared them to GWAS of neuroticism (from UK Biobank). First, we used a pairwise GWAS analysis to classify variants as associated with only depression, with only neuroticism, or with both. Second, we estimated partial genetic correlations to test whether the depressions genetic link with other phenotypes was explained by shared overlap with neuroticism. We found evidence that most genetic variants associated with depression are likely to be shared with neuroticism. The overlapping common genetic variance of depression and neuroticism was negatively genetically correlated with cognitive function and positively genetically correlated with several psychiatric disorders. We found that the genetic contributions unique to depression, and not shared with neuroticism, were correlated with inflammation, cardiovascular disease, and sleep patterns. Our findings demonstrate that, while genetic risk factors for depression are largely shared with neuroticism, there are also non-neuroticism related features of depression that may be useful for further patient or phenotypic stratification.

genetics↗

Identification of novel common variants associated with chronic pain using conditional false discovery rate analysis with major depressive disorder and assessment of pleiotropic effects of LRFN5.

Chronic pain is highly prevalent worldwide, with a significant socioeconomic burden, and also contributes to excess mortality. Chronic pain is a complex trait that is moderately heritable and genetically, as well as phenotypically, correlated with major depressive disorder (MDD). Use of the Conditional False Discovery Rate (cFDR) approach, which leverages pleiotropy identified from existing GWAS outputs, has been successful in discovering novel associated variants in related phenotypes. Here, genome-wide association study outputs for both von Korff chronic pain grade as a quasi-quantitative trait and for MDD were used to identify variants meeting a cFDR threshold for each outcome phenotype separately, as well as a conjunctional cFDR (ccFDR) threshold for both phenotypes together. Using a moderately conservative threshold, we identified a total of 11 novel single nucleotide polymorphisms (SNPs), six of which were associated with chronic pain grade and nine of which were associated with MDD. Four SNPs on chromosome 14 were associated with both chronic pain grade and MDD. SNPs associated only with chronic pain grade were located within SLC16A7 on chromosome 12. SNPs associated only with MDD were located either in a gene-dense region on chromosome 1 harbouring LINC01360, LRRIQ3, FPGT and FPGT-TNNI3K, or within/close to LRFN5 on chromosome 14. The SNPs associated with both outcomes were also located within LRFN5. Several of the SNPs on chromosomes 1 and 14 were identified as being associated with expression levels of nearby genes in the brain and central nervous system. Overall, using the cFDR approach, we identified several novel genetic loci associated with chronic pain and we describe likely pleiotropic effects of a recently identified MDD locus on chronic pain.\n\nAuthor SummaryGenetic variants explaining variation in complex traits can often be associated with more than one trait at once ( pleiotropy). Taking account of this pleiotropy in genetic studies can increase power to find sites in the genome harbouring trait-associated variants. In this study we used the suspected underlying pleiotropy between chronic pain and major depressive disorder to discover novel variants associated with chronic pain, and to investigate genetic variation that may be shared between the two disorders.

genetics↗

Genome-wide Association Study of Multisite Chronic Pain in UK Biobank

Chronic pain is highly prevalent worldwide, contributing a significant socioeconomic and public health burden. Several aspects of chronic pain, for example back pain and a severity-related phenotype, chronic pain grade, have been shown to be complex, heritable traits with a polygenic component. Additional pain-related phenotypes capturing aspects of an individuals overall sensitivity to experiencing and reporting chronic pain have also been suggested. We have here made use of a measure of the number of sites of chronic pain in individuals within the general UK population. This measure, termed Multisite Chronic Pain (MCP), is also a complex trait, but its genetic architecture has not previously been investigated. To address this, a large-scale genome-wide association study (GWAS) of MCP was carried out in ~380,000 UK Biobank participants to identify associated genetic variants. Findings were consistent with MCP having a significant polygenic component with a SNP heritability of 10.2%, and 76 independent lead single nucleotide polymorphisms (SNPs) at 39 risk loci were identified. Additional gene-level association analyses identified neurogenesis, synaptic plasticity, nervous system development, cell-cycle progression and apoptosis genes as being enriched for genetic association with MCP. Genetic correlations were observed between MCP and a range of psychiatric, autoimmune and anthropometric traits including major depressive disorder (MDD), asthma and BMI. Furthermore, in Mendelian randomisation (MR) analyses a bi-directional causal relationship was observed between MCP and MDD. A polygenic risk score (PRS) for MCP was found to significantly predict chronic widespread pain (pain all over the body), indicating the existence of genetic variants contributing to both of these pain phenotypes. These findings support the proposition that chronic pain involves a strong nervous system component and have implications for our understanding of the physiology of chronic pain and for the development of novel treatment strategies.

genetics↗

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

BackgroundThe 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 850K Illumina EPIC array in the largest single population sample to date.\n\nMethodsEpigenome-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=3,791; 274 COPD cases and 2,928 controls). In independent COPD incidence data (N=150), significantly differentially methylated sites (DMSs; p<3.6x10-8) 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.\n\nFindingsWe identified 29 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<0.05) in independent GS:SFHS (p=0.014) and LBC1936 (p=0.018) datasets by adding DMSs to a clinical model.\n\nInterpretationIdentification of novel DMSs has provided insight into the molecular mechanisms regulating respiratory function and aided prediction of COPD risk.\n\nFundingWellcome Trust Strategic Award 10436/Z/14/Z.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched for articles in PubMed published in English up to July 25, 2018, with the search terms \"DNA methylation\" and \"respiratory function\", or \"COPD\". We found some evidence for association between differential DNA methylation and both respiratory function and COPD. Of the twelve previous studies identified, eight used peripheral blood samples (sample size [N] range = 100-1,085) and four used lung tissue samples (N range = 24-160). The number of CpG loci analysed range from 27,578 to 485,512. These studies have not identified consistent changes in methylation, most likely due to a combination of factors including small sample sizes, technical issues, phenotypic definitions, and study design. In addition, no previous study has: analysed a sample from a large single cohort; used the recently released Illumina EPIC array (which assesses ~850,000 CpG loci); adjusted methylation data and phenotype for smoking history, or used both prevalent and incident COPD electronic health record data.\n\nAdded value of this studyTo our knowledge, this is the largest single cohort epigenome-wide association study (EWAS) of respiratory function and COPD to date (N=3,791). After applying stringent genome-wide significance criteria (P <3.6x10-8), we found that DNA methylation levels at 29 CpG sites in peripheral blood were associated with respiratory function or COPD. Of these 29, seven were testable in an independent population sample: all seven showed consistent direction of effect between the two samples and three showed replication (p<0.007 [0.05/7 CpG sites tested]). Our results suggest that adjustment of both the phenotypic and the DNA methylation probe data for smoking history, which has not been carried out in previous studies, reduces the confounding effects of smoking, identifies larger numbers of associations, and reduces the heterogeneity of effects across smoking strata. We used gene set enrichment and pathway analyses, together with an approach that combines DNA methylation results with gene expression data to provide evidence for enrichment of differentially methylated sites in genes linked to alternative splicing, and JAK-STAT signalling and axon guidance. Finally, we demonstrated that the inclusion of DNA methylation data improves COPD risk prediction over established clinical variables alone in two independent datasets.\n\nImplications of all the available evidenceThere is now accumulating evidence that DNA methylation in peripheral blood is associated with respiratory function and COPD.\n\nOur study has shown that DNA methylation levels at 29 CpG sites are robustly associated with respiratory function and COPD, provide mechanistic insights, and can improve prediction of COPD risk. Further studies are warranted to improve understanding of the aetiology of COPD and to assess the utility of DNA methylation profiling in the clinical management of this condition.

genomics↗

Genome-wide meta-analysis of depression in 807,553 individuals identifies 102 independent variants with replication in a further 1,507,153 individuals

Major depression is a debilitating psychiatric illness that is typically associated with low mood, anhedonia and a range of comorbidities. Depression has a heritable component that has remained difficult to elucidate with current sample sizes due to the polygenic nature of the disorder. To maximise sample size, we meta-analysed data on 807,553 individuals (246,363 cases and 561,190 controls) from the three largest genome-wide association studies of depression. We identified 102 independent variants, 269 genes, and 15 gene-sets associated with depression, including both genes and gene-pathways associated with synaptic structure and neurotransmission. Further evidence of the importance of prefrontal brain regions in depression was provided by an enrichment analysis. In an independent replication sample of 1,306,354 individuals (414,055 cases and 892,299 controls), 87 of the 102 associated variants were significant following multiple testing correction. Based on the putative genes associated with depression this work also highlights several potential drug repositioning opportunities. These findings advance our understanding of the complex genetic architecture of depression and provide several future avenues for understanding aetiology and developing new treatment approaches.

genetics↗