Biology subjects

Adams, M.

Publications and source records attributed to Adams, M..

53 records · Page 3Linked to original sources

bioRxiv2019

A high-content screen profiles cytotoxic microRNAs in pediatric and adult glioblastoma cells and identifies miR-1300 as a potent inducer of cytokinesis failure

BackgroundMicroRNAs play an important role in the regulation of mRNA translation, and have therapeutic potential in cancer and other diseases.\n\nMethodsTo profile the landscape of microRNAs with significant cytotoxicity in the context of glioblastoma (GBM), we performed a high-throughput screen using a synthetic oligonucleotide library representing all known human microRNAs in adult and pediatric GBM cells. Bio-informatics analysis were used to refine this list and the top seven microRNAs were validated in a larger panel of cells by flow-cytometry, and RTqPCR. The downstream mechanism of the strongest and most consistent candidate was investigated by siRNAs, 3UTR luciferase assays and Western Blotting.\n\nResultsOur screen identified [~]100 significantly cytotoxic microRNAs with 70% concordance between cell lines. MicroRNA-1300 (miR-1300) was the most potent and robust candidate. We observed a striking binucleated phenotype in miR-1300 expressing cells and characterized the mechanism of action as cytokinesis failure followed by apoptosis, which was observed in an extended GBM cell panel including two stem-like patient-derived cultures. We identified the physiological role of miR-1300 as a regulator of endomitosis in megakaryocyte differentiation where blockade of cytokinesis is an essential step. In glioblastoma cells, the oncogene Epithelial Cell Transforming 2 (ECT2) was validated as a direct key target of miR-1300. ECT2 siRNA phenocopied the effects of miR-1300, and its overexpression led to a significant rescue of miR-1300 induced binucleation.\n\nConclusionMiR-1300 was identified as a novel regulator of endomitosis with translatable potential for therapeutic application. The datatasets will be a resource for the neuro-oncology community.\n\nKey points (2 or 3 key points 85 characters plus spaces each)70% of cytotoxic microRNAs were shared between adult and pediatric glioblastoma cells\n\nMiR-1300 expression is restricted to endomitosis within megakaryocyte differentiation\n\nMiR-1300s ectopic expression is a potent and promising therapeutic tool in cancer\n\nImportance of StudyPrevious functional studies of microRNAs involved in the regulation of glioblastoma cell proliferation and/or survival have focused on adult glioblastoma alone and are restricted to only a few microRNAs at a time. Our study provides the first encompassing landscape of potent cytotoxic microRNAs in pediatric and adult glioblastoma.\n\nNot only, does our data provide an invaluable resource for the research community but it also revealed that 70% of microRNAs with significant cytotoxicity were shared by adult and pediatric cells. Finally, we identified and characterized the previously undescribed role of microRNA-1300 in the tight regulation of megakaryocyte differentiation into platelets and how, when expressed outside of this context, miR-1300 consistently causes cytokinesis failure followed by apoptosis, and thus represents a powerful cytotoxic tool with potential for translation towards therapeutic applications.

cancer biology↗

bioRxiv2019

Complete characterization of the human immune cell transcriptome using accurate full-length cDNA sequencing

The human immune system relies on highly complex and diverse transcripts and the proteins they encode. These include transcripts for Human Leukocyte Antigen (HLA) class I and II receptors which are essential for self/non-self discrimination by the immune system as well as transcripts encoding B cell and T cell receptors (BCR and TCR) which recognize, bind, and help eliminate foreign antigens.\n\nHLA genes are highly diverse within the human population with each individual possessing two of thousands of different alleles in each of the 9 major HLA genes. Determining which combination of alleles an individual possesses for each HLA gene (high-resolution HLA-typing) is essential to establish donor-recipient compatibility in organ and bone-marrow transplantations. BCR and TCR genes in turn are generated by recombining a diverse set of gene segments on the DNA level in each maturing B and T cell, respectively. This process generates adaptive immune receptor repertoires (AIRR) of composed of unique transcripts expressed by each B and T cells. These repertoires carry a vast amount of health relevant information. Both short-read RNA-seq based HLA-typing1 and adaptive immune receptor repertoire sequencing2-5 currently rely heavily on our incomplete knowledge of the genetic diversity at HLA6 and BCR/TCR loci7,8.\n\nHere we used our nanopore sequencing based Rolling Circle to Concatemeric Consensus (R2C2) protocol9 to generate over 10,000,000 full-length cDNA sequences at a median accuracy of 97.9%. We used this dataset to demonstrate that deep and accurate full-length cDNA sequencing can - in addition to providing isoform-level transcriptome analysis for over 9,000 loci - be used to generate accurate sequences of HLA alleles for HLA allele typing and discovery as well as detailed AIRR data for the analysis of the adaptive immune system without requiring specific knowledge of the diversity at HLA and BCR/TCR loci.

genomics↗

bioRxiv2019

A custom genotyping array reveals population-level heterogeneity for the genetic risks of prostate cancer and other cancers in Africa

Although prostate cancer is the leading cause of cancer mortality for African men, the vast majority of known disease associations have been detected in European study cohorts. Furthermore, most genome-wide association studies have used genotyping arrays that are hindered by SNP ascertainment bias. To overcome these disparities in genomic medicine, the Men of African Descent and Carcinoma of the Prostate (MADCaP) Network has developed a genotyping array that is optimized for African populations. The MADCaP Array contains more than 1.5 million markers and an imputation backbone that successfully tags over 94% of common genetic variants in African populations. This array also has a high density of markers in genomic regions associated with cancer susceptibility, including 8q24. We assessed the effectiveness of the MADCaP Array by genotyping 399 prostate cancer cases and 403 controls from seven urban study sites in sub-Saharan Africa. We find that samples from Ghana and Nigeria cluster together, while samples from Senegal and South Africa yield distinct ancestry clusters. Using the MADCaP array, we identified cancer-associated loci that have large allele frequency differences across African populations. Polygenic risk scores were also generated for each genome in the MADCaP pilot dataset, and we found that predicted risks of CaP are lower in Senegal and higher in Nigeria.\n\nSignificanceWe have developed an Africa-specific genotyping array which enables investigators to identify novel disease associations and to fine-map genetic loci that are associated with prostate and other cancers.

genomics↗

bioRxiv2019

Strains used in whole organism Plasmodium falciparum vaccine trials differ in genome structure, sequence, and immunogenic potential

BackgroundPlasmodium falciparum (Pf) whole-organism sporozoite vaccines have provided excellent protection against controlled human malaria infection (CHMI) and naturally transmitted heterogeneous Pf in the field. Initial CHMI studies showed significantly higher durable protection against homologous than heterologous strains, suggesting the presence of strain-specific vaccine-induced protection. However, interpretation of these results and understanding of their relevance to vaccine efficacy (VE) have been hampered by the lack of knowledge on genetic differences between vaccine and CHMI strains, and how these strains are related to parasites in malaria endemic regions.\n\nMethodsWhole genome sequencing using long-read (Pacific Biosciences) and short-read (Illumina) sequencing platforms was conducted to generate de novo genome assemblies for the vaccine strain, NF54, and for strains used in heterologous CHMI (7G8 from Brazil, NF166.C8 from Guinea, and NF135.C10 from Cambodia). The assemblies were used to characterize sequence polymorphisms and structural variants in each strain relative to the reference Pf 3D7 (a clone of NF54) genome. Strains were compared to each other and to clinical isolates from South America, Sub-Saharan Africa, and Southeast Asia.\n\nResultsWhile few variants were detected between 3D7 and NF54, we identified tens of thousands of variants between NF54 and the three heterologous strains both genome-wide and within regulatory and immunologically important regions, including in pre-erythrocytic antigens that may be key for sporozoite vaccine-induced protection. Additionally, these variants directly contribute to diversity in immunologically important regions of the genomes as detected through in silico CD8+ T cell epitope predictions. Of all heterologous strains, NF135.C10 consistently had the highest number of unique predicted epitope sequences when compared to NF54, while NF166.C8 had the lowest. Comparison to global clinical isolates revealed that these four strains are representative of their geographic region of origin despite long-term culture adaptation; of note, NF135.C10 is from an admixed population, and not part of recently-formed drug resistant subpopulations present in the Greater Mekong Sub-region.\n\nConclusionsThese results are assisting the interpretation of VE of whole-organism vaccines against homologous and heterologous CHMI, and may be useful in informing the choice of strains for inclusion in region-specific or multi-strain vaccines.

genomics↗

bioRxiv2019

Genetic and shared couple environmental contributions to smoking and alcohol use in the UK population

Alcohol use and smoking are leading causes of death and disability worldwide. Both genetic and environmental factors have been shown to influence individual differences in the use of these substances. In the present study we tested whether genetic factors, modelled alongside common family environment, explained phenotypic variance in alcohol use and smoking behaviour in the Generation Scotland (GS) family sample of up to 19,377 individuals. SNP and pedigree-associated effects combined explained between 18% and 41% of the variance in substance use. Shared couple effects explained a significant amount of variance across all substance use traits, particularly alcohol intake, for which 38% of the phenotypic variance was explained. We tested whether the within-couple substance use correlations were due to assortative mating by testing the association between partner polygenic risk scores in 34,987 couple pairs from the UK Biobank (UKB). Only couples smoking status PRSs were significantly associated (b=0.01, S.E=0.005, p=0.02). However, an individuals alcohol PRS was associated with their partners phenotype (b=0.04, S.E=0.007, p < 2 x 10-7). In support of this, G carriers of a functional ADH1B polymorphism (rs1229984), known to be associated with greater alcohol intake, were found to consume less alcohol if they had a partner who carried an A allele at this SNP. Together these results show that the shared couple environment contributes significantly to patterns of substance use. It is unclear whether this is due to shared environmental factors, assortative mating, or indirect genetic effects. Future studies would benefit from longitudinal data and larger sample sizes to assess this further.

genetics↗

bioRxiv2019

A genome-wide association study identifies that the GDF5 and COL27A1 genes are associated with knee pain in UK Biobank (N = 171, 516)

ObjectiveKnee pain is one of the most common musculoskeletal complaints that brings people to medical attention. We sought to identify the genetic variants associated with knee pain in 171,516 subjects from the UK Biobank cohort and replicate them using cohorts from 23andMe, the Osteoarthritis Initiative (OAI), and the Johnston County Osteoarthritis Study (JoCo).\n\nMethodsWe performed a genome-wide association study of knee pain in the UK Biobank, where knee pain was ascertained through self-report and defined as \"knee pain in the last month interfering with usual activities\". A total of 22,204 cases and 149,312 controls were included in the discovery analysis. We tested our top and independent SNPs (P < 5 x 10-8) for replication in 23andMe, OAI, and JoCo, then performed a joint meta-analysis between discovery and replication cohorts using GWAMA. We calculated the narrow-sense heritability of knee pain using Genome-wide Complex Trait Analysis (GCTA).\n\nResultsWe identified 2 loci that reached genome-wide significance, rs143384 located in the GDF5 (P = 1.32 x 10-12), a gene previously implicated in osteoarthritis, and rs2808772, located near COL27A1 (P = 1.49 x 10-8). These findings were subsequently replicated in independent cohorts and increased in significance in the joint meta-analysis (rs143384: P = 4.64 x 10-18; rs2808772: P -11 = 2.56 x 10-1). The narrow sense heritability of knee pain was 0.08.\n\nConclusionIn this first reported genome-wide association meta-analysis of knee pain, we identified and replicated two loci in or near GDF5 and COL27A1 that are associated with knee pain.

genetics↗

bioRxiv2018

Genome-wide by environment interaction studies (GWEIS) of depressive symptoms and psychosocial stress in UK Biobank and Generation Scotland.

Stress is associated with poorer physical and mental health. To improve our understanding of this link, we performed genome-wide association studies (GWAS) of depressive symptoms and genome-wide by environment interaction studies (GWEIS) of depressive symptoms and stressful life events (SLE) in two UK population cohorts (Generation Scotland and UK Biobank). No SNP was individually significant in either GWAS, but gene-based tests identified six genes associated with depressive symptoms in UK Biobank (DCC, ACSS3, DRD2, STAG1, FOXP2 and KYNU; p < 2.77x10-6). Two SNPs with genome-wide significant GxE effects were identified by GWEIS in Generation Scotland: rs12789145 (53kb downstream PIWIL4; p = 4.95x10-9; total SLE) and rs17070072 (intronic to ZCCHC2; p = 1.46x10-8; dependent SLE). A third locus upstream CYLC2 (rs12000047 and rs12005200, p < 2.00x10-8; dependent SLE) when the joint effect of the SNP main and GxE effects was considered. GWEIS gene-based tests identified: MTNR1B with GxE effect with dependent SLE in Generation Scotland; and PHF2 with the joint effect in UK Biobank (p < 2.77x10-6). Polygenic risk scores (PRS) analyses incorporating GxE effects improved the prediction of depressive symptom scores, when using weights derived from either the UK Biobank GWAS of depressive symptoms (p = 0.01) or the PGC GWAS of major depressive disorder (p = 5.91x10-3). Using an independent sample, PRS derived using GWEIS GxE effects provided evidence of shared aetiologies between depressive symptoms and schizotypal personality, heart disease and COPD. Further such studies are required and may result in improved treatments for depression and other stress-related conditions.

genetics↗

bioRxiv2018

Factors associated with sharing email information and mental health survey participation in two large population cohorts

People who opt to participate in scientific studies tend to be healthier, wealthier, and more educated than the broader population. While selection bias does not always pose a problem for analysing the relationships between exposures and diseases or other outcomes, it can lead to biased effect size estimates. Biased estimates may weaken the utility of genetic findings because the goal is often to make inferences in a new sample (such as in polygenic risk score analysis). We used data from UK Biobank and Generation Scotland and conducted phenotypic and genome-wide association analyses on two phenotypes that reflected mental health data availability: (1) whether participants were contactable by email for follow-up) and (2) whether participants responded to a follow-up surveys of mental health. We identified nine genetic loci associated with email contact and 25 loci associated with mental health survey completion. Both phenotypes were positively genetically correlated with higher educational attainment and better health and negatively genetically correlated with psychological distress and schizophrenia. Recontact availability and follow-up participation can act as further genetic filters for data on mental health phenotypes.

genetics↗

bioRxiv2018

Spatial epidemiology of gestational age and birth weight in Switzerland: Census-based linkage study

BackgroundGestational age and birth weight are strong predictors of infant morbidity and mortality. Understanding spatial variation can inform policies to reduce health inequalities. We examined small-area variation in gestational age and birth weight in Switzerland.\n\nMethodsAll singleton live births recorded in the Swiss Live Birth Register 2011 to 2014 were eligible. We deterministically linked the Live Birth Register with census and survey data to create datasets including neonatal and pregnancy-related variables, parental characteristics and geographical variables. We produced maps of 705 areas and fitted linear mixed-effect models to assess to what extent spatial variation was explained by these variables.\n\nResultsWe analysed all 315,177 eligible live births. Area-level averages of gestational age varied between 272-279 days, and between 3138-3467g for birth weight. The fully adjusted models explained 31% and 87% of spatial variation of gestational age and birth weight, respectively. Language region explained most of the variation, with shorter gestational age and lower birth weight in French- and Italian- than in German-speaking areas. Other variables explaining variation were, for gestational age, the level of urbanisation, the parents nationality and missing father. For birth weight, they were gestational age, altitude, born out of wedlock, and parental nationality. In a subset of 69,463 live births with data on parental education, levels of education were only weakly associated with gestational age or birth weight.\n\nConclusionsIn Switzerland, small area variation in birth weight is largely explained, and variation in gestational age partially explained by geocultural, socio-demographic and pregnancy factors.\n\nStrengths and limitations of this studyO_LIThis study was based on a large sample with national coverage, with data on neonatal and pregnancy-related predictors of gestational age and birth weight, and precise spatial data.\nC_LIO_LINo data were available on the mode of delivery, maternal smoking, mothers weight and height or gestational diabetes.\nC_LIO_LIThe fully adjusted model explained about 80% of the regional variation in birth weight and about 40% of the variation in gestational age.\nC_LIO_LILanguage region, a proxy for cultural, social and behavioural factors, was a strong explanatory factor, with lower birth weight and shorter gestation in the French and Italian compared to the German language region.\nC_LIO_LIUnknown father was associated with shorter gestation and lower birth weight, indicating that children not recognised by their fathers may be at higher risk of poor outcomes.\nC_LI

epidemiology↗

bioRxiv2018

Integrated epigenome, exome and transcriptome analyses reveal molecular subtypes and homeotic transformation in uterine fibroids.

Uterine fibroids are benign myometrial smooth muscle tumors of unknown etiology that when symptomatic are the most common indication for hysterectomy in the USA. We conducted an integrated analysis of fibroids and adjacent normal myometria by whole exome sequencing, Infinium MethylationEPIC array, and RNA-sequencing. Unsupervised clustering by DNA methylation segregated normal myometria from fibroids, and further separated the fibroids into subtypes marked by MED12 mutation, HMGA2 activation (HMGA2hi) and HMGA1 activation (HMGA1hi). Upregulation of HMGA2 expression in HMGA2hi fibroids did not always appear to be dependent on translocation, as has been historically described, and was associated with hypomethylation in the HMGA2 gene body. Furthermore, we found that expression of HOXA13 was highly upregulated in fibroids and that overexpression of HOXA13 in a myometrial cell line induced expression of genes classically associated with uterine fibroids. Transcriptome analyses of the most differentially expressed genes between cervix and myometrium also showed that uterine fibroids and normal cervix clustered together and apart from normal myometria. Together, our integrated analysis shows a role for epigenetic modification in fibroid biology and strongly suggests that homeotic transformation of myometrium cells to a more cervical phenotype is important for the etiology of the disease.

physiology↗

bioRxiv2018

Replication of the diathesis-stress model for depression in Generation Scotland.

Depression has well-established influences from genetic and environmental risk factors. This has led to the diathesis-stress theory, which assumes a multiplicative gene-by-environment interaction (GxE) effect on risk. Recently, Colodro-Conde et al. empirically tested this theory, using the polygenic risk score for major depressive disorder (PRS, genes) and stressful life events (SLE, environment) effects on depressive symptoms, identifying significant GxE effects with an additive contribution to liability. We have tested the diathesis-stress theory on an independent sample of 4 919 individuals.\n\nWe identified nominally significant positive GxE effects in the full cohort (R2 = 0.08%, p = 0.049) and in women (R2 = 0.19%, p = 0.017), but not in men (R2 = 0.15%, p = 0.07). GxE effects were nominally significant, but only in women, when SLE were split into those in which the respondent plays an active or passive role (R2 = 0.15%, p = 0.038; R2 = 0.16%, p = 0.033, respectively). High PRS increased the risk of depression in participants reporting high numbers of SLE (p = 2.86 x 10-4). However, in those participants who reported no recent SLE, a higher PRS appeared to increase the risk of depressive symptoms in men ({beta} = 0.082, p = 0.016) but had a protective effect in women ({beta} = -0.061, p = 0.037). This difference was nominally significant (p = 0.017). Our study reinforces the evidence of additional risk in the aetiology of depression due to GxE effects. However, larger sample sizes are required to robustly validate these findings.

genomics↗

bioRxiv2018

Genetic correlations between pain phenotypes and depression and neuroticism

Correlations between pain phenotypes and psychiatric traits such as depression and the personality trait of neuroticism are not fully understood. The purpose of this study was to identify whether eight pain phenotypes, depressive symptoms, major depressive disorders, and neuroticism are correlated for genetic reasons. Eight pain phenotypes were defined by a specific pain-related question in the UK Biobank questionnaire. First we generated genome-wide association summary statistics on each pain phenotype, and estimated the common SNP-based heritability of each trait using GCTA. We then estimated the genetic correlation of each pain phenotype with depressive symptoms, major depressive disorders and neuroticism using the the cross-trait linkage disequilibrium score regression (LDSC) method integrated in the LD Hub. Third, we used the LDSC software to calculate genetic correlations among pain phenotypes. All pain phenotypes were heritable, with pain all over the body showing the highest heritability (h2=0.31, standard error=0.072). All pain phenotypes, except hip pain and knee pain, had significant and positive genetic correlations with depressive symptoms, major depressive disorders and neuroticism. The largest genetic correlations occurred between neuroticism and stomach or abdominal pain (rg=0.70, P=2.4 x 10-9). In contrast, hip pain and knee pain showed weaker evidence of shared genetic architecture with these negative emotional traits. In addition, many pain phenotypes had positive and significant genetic correlations with each other indicating shared genetic mechanisms. Pain at a variety of body sites is heritable and genetically correlated with depression and neuroticism. This suggests that pain, neuroticism and depression share partially overlapping genetic risk factors.

genetics↗

bioRxiv2018

Transcriptome assembly and annotation of johnsongrass (Sorghum halepense) rhizomes identifies candidate rhizome specific genes

Rhizomes facilitate the wintering and vegetative propagation of many perennial grasses. Sorghum halepense (johnsongrass) is an aggressive perennial grass that relies on a robust rhizome system to persist through winters and reproduce asexually from its rootstock nodes. This study aimed to sequence and assemble expressed transcripts within the johnsongrass rhizome. A de novo transcriptome assembly was generated from a single johnsongrass rhizome meristem tissue sample. A total of 141,176 probable protein-coding sequences from the assembly were identified and assigned gene ontology terms using Blast2GO. The johnsongrass assembly was compared to Sorghum bicolor, a related non-rhizomatous species, along with an assembly of similar rhizome tissue from the perennial grain crop Thinopyrum intermedium. The presence/absence analysis yielded a set of 259 johnsongrass contigs that are likely associated with rhizome development.

genomics↗

bioRxiv2017

A genome-wide association study finds novel genetic associations with broadly-defined headache in UK Biobank (N = 223,773)

Headache is the most common neurological symptom and a leading cause of years lived with disability. We sought to identify the genetic variants associated with a broadly-defined headache phenotype in 223,773 subjects from the UK Biobank cohort. We defined headache based on a specific question answered by the UK Biobank participants. We performed a genome-wide association study of headache as a single entity, using 74,461 cases and 149,312 controls. We identified 3,343 SNPs which reached the genome-wide significance level of P < 5 x 10-8. The SNPs were located in 28 loci, with the top SNP of rs11172113 in the LRP1 gene having a P value of 4.92 x 10-47. Of the 28 loci, 14 have previously been associated with migraine. Among 14 new loci, rs77804065 with a P value of 5.87 x 10-15 in the LINC02210-CRHR1 gene was the top SNP.\n\nPositive relationships (P < 0.001) between multiple brain tissues and genetic associations were identified through tissue expression analysis, whereas no vascular related tissues showed significant relationships. We identified several significant positive genetic correlations between headache and other psychological traits including neuroticism, depressive symptoms, insomnia, and major depressive disorder.\n\nOur results suggest that brain function is closely related to broadly-defined headache. In addition, we also found that many psychological traits have genetic correlations with headache.

genetics↗

bioRxiv2017

Cross-Site Comparison of Ribosomal Depletion Kits for Illumina RNAseq Library Construction

Ribosomal RNA (rRNA) comprises at least 90% of total RNA extracted from mammalian tissue or cell line samples. Informative transcriptional profiling using massively parallel sequencing technologies requires either enrichment of mature poly-adenylated transcripts or targeted depletion of the rRNA fraction. The latter method is of particular interest because it is compatible with degraded samples such as those extracted from FFPE and also captures transcripts that are not poly-adenylated such as some non-coding RNAs. Here we provide a cross-site study that evaluates the performance of ribosomal RNA removal kits from Illumina, Takara/Clontech, Kapa Biosystems, Lexogen, New England Biolabs and Qiagen on intact and degraded RNA samples. We find that all of the kits are capable of performing significant ribosomal depletion, though there are differences in their ease of use. All kits were able to remove ribosomal RNA to below 20% with intact RNA and identify [~]14,000 protein coding genes from the Universal Human Reference RNA sample at >1FPKM. Analysis of differentially detected genes between kits suggests that transcript length may be a key factor in library production efficiency. These results provide a roadmap for labs on the strengths of each of these methods and how best to utilize them.

genomics↗

bioRxiv2017

Genetic and environmental determinants of stressful life events and their overlap with depression and neuroticism

BackgroundStressful life events (SLEs) and neuroticism are risk factors for major depressive disorder (MDD). However, SLEs and neuroticism are heritable traits that are correlated with genetic risk for MDD. In the current study, we sought to investigate the genetic and environmental contributions to SLEs in a large family-based sample, and quantify any genetic overlap with MDD and neuroticism.\n\nMethodsA subset of Generation Scotland: the Scottish Family Health Study, consisting of 9618 individuals comprise the present study. We estimated the heritability of SLEs using pedigree-based and molecular genetic data. The environment was assessed by modelling familial, couple and sibling components. Using polygenic risk scores (PRS) and LD score regression we analysed the genetic overlap between MDD, neuroticism and SLEs.\n\nResultsPast 6-month life events were positively correlated with lifetime MDD status ({beta}=0.21, r2=1.1%, p=2.5 x 10-25) and neuroticism ({beta} =0.13, r2=1.9%, p=1.04 x 10-37). Common SNPs explained 8% of the variance in personal life events (those directly affecting the individual) (S.E.=0.03, p=9 x 10-4). A significant effect of couple environment accounted for 13% (S.E.=0.03, p=0.016) of variation in SLEs. PRS analyses found that individuals with higher PRS for MDD reported more SLEs ({beta} =0.05, r2=0.3%, p=3 x 10-5). LD score regression demonstrated genetic correlations between MDD and both SLEs (rG=0.33, S.E.=0.08) and neuroticism (rG=0.15, S.E.=0.07).\n\nConclusionsThese findings suggest that SLEs are partially heritable and this heritability is shared with risk for MDD and neuroticism. Further work should determine the causal direction and source of these associations.

genetics↗

bioRxiv2017

Genome-wide interaction study of stress-sensitivity and its prediction of major depressive disorder in UK Biobank and Generation Scotland

Individual response to stress is correlated with neuroticism and is an important predictor of both neuroticism and the onset of major depressive disorder (MDD). Identification of the genetics underpinning individual differences in response to negative events (stress-sensitivity) may improve our understanding of the molecular pathways involved, and its association with stress-related illnesses. We sought to generate a proxy for stress-sensitivity through modelling the interaction between SNP allele and MDD status on neuroticism score in order to identify genetic variants that contribute to the higher neuroticism seen in individuals with a lifetime diagnosis of depression compared to unaffected individuals. Meta-analysis of genome-wide interaction studies (GWIS) in UK Biobank (N = 23,092) and Generation Scotland: Scottish Family Health Study (N = 7,155) identified no genome-wide significance SNP interactions. However, gene-based tests identified a genome-wide significant gene, ZNF366, a negative regulator of glucocorticoid receptor function implicated in alcohol dependence (p = 1.48x10-7; Bonferroni-corrected significance threshold p < 2.79x10-6). Using summary statistics from the stress-sensitivity term of the GWIS, SNP heritability for stress-sensitivity was estimated at 5.0%. In models fitting polygenic risk scores of both MDD and neuroticism derived from independent GWAS, we show that polygenic risk scores derived from the UK Biobank stress-sensitivity GWIS significantly improved the prediction of MDD in Generation Scotland. This study may improve interpretation of larger genome-wide association studies of MDD and other stress-related illnesses, and the understanding of the etiological mechanisms underpinning stress-sensitivity.

genetics↗