Enda M. Byrne
University of Queensland
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Featured researches published by Enda M. Byrne.
The Journal of Politics | 2011
Peter K. Hatemi; Nathan A. Gillespie; Lindon J. Eaves; Brion S. Maher; Bradley T. Webb; Andrew C. Heath; Sarah E. Medland; David C. Smyth; Harry N. Beeby; Scott D. Gordon; Grant W. Montgomery; Ghu Zhu; Enda M. Byrne; Nicholas G. Martin
The assumption that the transmission of social behaviors and political preferences is purely cultural has been challenged repeatedly over the last 40 years by the combined evidence of large studies of adult twins and their relatives, adoption studies, and twins reared apart. Variance components and path modeling analyses using data from extended families quantified the overall genetic influence on political attitudes, but few studies have attempted to localize the parts of the genome which accounted for the heritability estimates found for political preferences. Here, we present the first genome-wide analysis of Conservative-Liberal attitudes from a sample of 13,000 respondents whose DNA was collected in conjunction with a 50-item sociopolitical attitude questionnaire. Several significant linkage peaks were identified and potential candidate genes discussed.
Molecular Psychiatry | 2012
Najaf Amin; Enda M. Byrne; Julie Johnson; Georgia Chenevix-Trench; Stefan Walter; Ilja M. Nolte; J. M. Vink; R. Rawal; Massimo Mangino; A. Teumer; J. C. Keers; Germaine C. Verwoert; S. Baumeister; Reiner Biffar; Astrid Petersmann; N. Dahmen; A. Doering; Aaron Isaacs; Linda Broer; Naomi R. Wray; Grant W. Montgomery; Daniel Levy; Bruce M. Psaty; V. Gudnason; Aravinda Chakravarti; P. Sulem; D. F. Gudbjartsson; Lambertus A. Kiemeney; U. Thorsteinsdottir; K. Stefansson
Coffee consumption is a model for addictive behavior. We performed a meta-analysis of genome-wide association studies (GWASs) on coffee intake from 8 Caucasian cohorts (N=18 176) and sought replication of our top findings in a further 7929 individuals. We also performed a gene expression analysis treating different cell lines with caffeine. Genome-wide significant association was observed for two single-nucleotide polymorphisms (SNPs) in the 15q24 region. The two SNPs rs2470893 and rs2472297 (P-values=1.6 × 10−11 and 2.7 × 10−11), which were also in strong linkage disequilibrium (r2=0.7) with each other, lie in the 23-kb long commonly shared 5′ flanking region between CYP1A1 and CYP1A2 genes. CYP1A1 was found to be downregulated in lymphoblastoid cell lines treated with caffeine. CYP1A1 is known to metabolize polycyclic aromatic hydrocarbons, which are important constituents of coffee, whereas CYP1A2 is involved in the primary metabolism of caffeine. Significant evidence of association was also detected at rs382140 (P-value=3.9 × 10−09) near NRCAM—a gene implicated in vulnerability to addiction, and at another independent hit rs6495122 (P-value=7.1 × 10−09)—an SNP associated with blood pressure—in the 15q24 region near the gene ULK3, in the meta-analysis of discovery and replication cohorts. Our results from GWASs and expression analysis also strongly implicate CAB39L in coffee drinking. Pathway analysis of differentially expressed genes revealed significantly enriched ubiquitin proteasome (P-value=2.2 × 10−05) and Parkinsons disease pathways (P-value=3.6 × 10−05).
Human Molecular Genetics | 2013
Diana L. Cousminer; Diane J. Berry; Nicholas J. Timpson; Wei Ang; Elisabeth Thiering; Enda M. Byrne; H. Rob Taal; Ville Huikari; Jonathan P. Bradfield; Marjan Kerkhof; Maria M. Groen-Blokhuis; Eskil Kreiner-Møller; Marcella Marinelli; Claus Holst; Jaakko Leinonen; John Perry; Ida Surakka; Olli Pietiläinen; Johannes Kettunen; Verneri Anttila; Marika Kaakinen; Ulla Sovio; Anneli Pouta; Shikta Das; Vasiliki Lagou; Chris Power; Inga Prokopenko; David Evans; John P. Kemp; Beate St Pourcain
The pubertal height growth spurt is a distinctive feature of childhood growth reflecting both the central onset of puberty and local growth factors. Although little is known about the underlying genetics, growth variability during puberty correlates with adult risks for hormone-dependent cancer and adverse cardiometabolic health. The only gene so far associated with pubertal height growth, LIN28B, pleiotropically influences childhood growth, puberty and cancer progression, pointing to shared underlying mechanisms. To discover genetic loci influencing pubertal height and growth and to place them in context of overall growth and maturation, we performed genome-wide association meta-analyses in 18 737 European samples utilizing longitudinally collected height measurements. We found significant associations (P < 1.67 × 10(-8)) at 10 loci, including LIN28B. Five loci associated with pubertal timing, all impacting multiple aspects of growth. In particular, a novel variant correlated with expression of MAPK3, and associated both with increased prepubertal growth and earlier menarche. Another variant near ADCY3-POMC associated with increased body mass index, reduced pubertal growth and earlier puberty. Whereas epidemiological correlations suggest that early puberty marks a pathway from rapid prepubertal growth to reduced final height and adult obesity, our study shows that individual loci associating with pubertal growth have variable longitudinal growth patterns that may differ from epidemiological observations. Overall, this study uncovers part of the complex genetic architecture linking pubertal height growth, the timing of puberty and childhood obesity and provides new information to pinpoint processes linking these traits.
PLOS Genetics | 2016
Samuel E. Jones; Jessica Tyrrell; Andrew R. Wood; Robin N. Beaumont; Katherine S. Ruth; Marcus A. Tuke; Hanieh Yaghootkar; Youna Hu; Maris Teder-Laving; Caroline Hayward; Till Roenneberg; James F. Wilson; Fabiola M. Del Greco; Andrew A. Hicks; Chol Shin; Chang Ho Yun; Seung Ku Lee; Andres Metspalu; Enda M. Byrne; Philip R. Gehrman; Henning Tiemeier; Karla V. Allebrandt; Rachel M. Freathy; Anna Murray; David A. Hinds; Timothy M. Frayling; Michael N. Weedon
Disrupted circadian rhythms and reduced sleep duration are associated with several human diseases, particularly obesity and type 2 diabetes, but until recently, little was known about the genetic factors influencing these heritable traits. We performed genome-wide association studies of self-reported chronotype (morning/evening person) and self-reported sleep duration in 128,266 white British individuals from the UK Biobank study. Sixteen variants were associated with chronotype (P<5x10-8), including variants near the known circadian rhythm genes RGS16 (1.21 odds of morningness, 95% CI [1.15, 1.27], P = 3x10-12) and PER2 (1.09 odds of morningness, 95% CI [1.06, 1.12], P = 4x10-10). The PER2 signal has previously been associated with iris function. We sought replication using self-reported data from 89,283 23andMe participants; thirteen of the chronotype signals remained associated at P<5x10-8 on meta-analysis and eleven of these reached P<0.05 in the same direction in the 23andMe study. We also replicated 9 additional variants identified when the 23andMe study was used as a discovery GWAS of chronotype (all P<0.05 and meta-analysis P<5x10-8). For sleep duration, we replicated one known signal in PAX8 (2.6 minutes per allele, 95% CI [1.9, 3.2], P = 5.7x10-16) and identified and replicated two novel associations at VRK2 (2.0 minutes per allele, 95% CI [1.3, 2.7], P = 1.2x10-9; and 1.6 minutes per allele, 95% CI [1.1, 2.2], P = 7.6x10-9). Although we found genetic correlation between chronotype and BMI (rG = 0.056, P = 0.05); undersleeping and BMI (rG = 0.147, P = 1x10-5) and oversleeping and BMI (rG = 0.097, P = 0.04), Mendelian Randomisation analyses, with limited power, provided no consistent evidence of causal associations between BMI or type 2 diabetes and chronotype or sleep duration. Our study brings the total number of loci associated with chronotype to 22 and with sleep duration to three, and provides new insights into the biology of sleep and circadian rhythms in humans.
American Journal of Medical Genetics | 2013
Enda M. Byrne; Philip R. Gehrman; Sarah E. Medland; Dale R. Nyholt; Andrew C. Heath; Pamela A. F. Madden; Ian B. Hickie; Cornelia van Duijn; Anjali K. Henders; Grant W. Montgomery; Nicholas G. Martin; Naomi R. Wray
Several aspects of sleep behavior such as timing, duration and quality have been demonstrated to be heritable. To identify common variants that influence sleep traits in the population, we conducted a genome‐wide association study of six sleep phenotypes assessed by questionnaire in a sample of 2,323 individuals from the Australian Twin Registry. Genotyping was performed on the Illumina 317, 370, and 610K arrays and the SNPs in common between platforms were used to impute non‐genotyped SNPs. We tested for association with more than 2,000,000 common polymorphisms across the genome. While no SNPs reached the genome‐wide significance threshold, we identified a number of associations in plausible candidate genes. Most notably, a group of SNPs in the third intron of the CACNA1C gene ranked as most significant in the analysis of sleep latency (P = 1.3 × 10−6). We attempted to replicate this association in an independent sample from the Chronogen Consortium (n = 2,034), but found no evidence of association (P = 0.73). We have identified several other suggestive associations that await replication in an independent sample. We did not replicate the results from previous genome‐wide analyses of self‐reported sleep phenotypes after correction for multiple testing.
Genome Biology | 2014
Matthew N. Davies; Lutz Krause; Jordana T. Bell; Fei Gao; Kirsten Ward; Honglong Wu; Hanlin Lu; Yuan Liu; Pei-Chein Tsai; David A. Collier; Therese M. Murphy; Emma Dempster; Jonathan Mill; Alexis Battle; Xiaowei Zhu; Anjali K. Henders; Enda M. Byrne; Naomi R. Wray; Nicholas G. Martin; Tim D. Spector; Jun Wang
BackgroundAlthough genetic variation is believed to contribute to an individual’s susceptibility to major depressive disorder, genome-wide association studies have not yet identified associations that could explain the full etiology of the disease. Epigenetics is increasingly believed to play a major role in the development of common clinical phenotypes, including major depressive disorder.ResultsGenome-wide MeDIP-Sequencing was carried out on a total of 50 monozygotic twin pairs from the UK and Australia that are discordant for depression. We show that major depressive disorder is associated with significant hypermethylation within the coding region of ZBTB20, and is replicated in an independent cohort of 356 unrelated case-control individuals. The twins with major depressive disorder also show increased global variation in methylation in comparison with their unaffected co-twins. ZBTB20 plays an essential role in the specification of the Cornu Ammonis-1 field identity in the developing hippocampus, a region previously implicated in the development of major depressive disorder.ConclusionsOur results suggest that aberrant methylation profiles affecting the hippocampus are associated with major depressive disorder and show the potential of the epigenetic twin model in neuro-psychiatric disease.
Translational Psychiatry | 2013
Enda M. Byrne; Tania Carrillo-Roa; Anjali K. Henders; Lisa Bowdler; Allan F. McRae; A. C. Heath; Nicholas G. Martin; Grant W. Montgomery; Lutz Krause; Naomi R. Wray
Our understanding of major depressive disorder (MDD) has focused on the influence of genetic variation and environmental risk factors. Growing evidence suggests the additional role of epigenetic mechanisms influencing susceptibility for complex traits. DNA sequence within discordant monozygotic twin (MZT) pairs is virtually identical; thus, they represent a powerful design for studying the contribution of epigenetic factors to disease liability. The aim of this study was to investigate whether specific methylation profiles in white blood cells could contribute to the aetiology of MDD. Participants were drawn from the Queensland Twin Registry and comprised 12 MZT pairs discordant for MDD and 12 MZT pairs concordant for no MDD and low neuroticism. Bisulphite treatment and genome-wide interrogation of differentially methylated CpG sites using the Illumina Human Methylation 450 BeadChip were performed in WBC-derived DNA. No overall difference in mean global methylation between cases and their unaffected co-twins was found; however, the differences in females was significant (P=0.005). The difference in variance across all probes between affected and unaffected twins was highly significant (P<2.2 × 10−16), with 52.4% of probes having higher variance in cases (binomial P-value<2.2 × 10−16). No significant differences in methylation were observed between discordant MZT pairs and their matched concordant MZT (permutation minimum P=0.11) at any individual probe. Larger samples are likely to be needed to identify true associations between methylation differences at specific CpG sites.
Molecular Psychiatry | 2016
Takeshi Otowa; Karin Hek; Misun Lee; Enda M. Byrne; Saira Saeed Mirza; Michel G. Nivard; Timothy B. Bigdeli; Steven H. Aggen; Daniel E. Adkins; Aaron R. Wolen; Ayman H. Fanous; Matthew C. Keller; Enrique Castelao; Zoltán Kutalik; S. V. der Auwera; Georg Homuth; Matthias Nauck; Alexander Teumer; Y. Milaneschi; J.J. Hottenga; Nese Direk; A. Hofman; A.G. Uitterlinden; Cornelis L. Mulder; Anjali K. Henders; Sarah E. Medland; S. D. Gordon; A. C. Heath; P. A. F. Madden; M. L. Pergadia
Anxiety disorders (ADs), namely generalized AD, panic disorder and phobias, are common, etiologically complex conditions with a partially genetic basis. Despite differing on diagnostic definitions based on clinical presentation, ADs likely represent various expressions of an underlying common diathesis of abnormal regulation of basic threat–response systems. We conducted genome-wide association analyses in nine samples of European ancestry from seven large, independent studies. To identify genetic variants contributing to genetic susceptibility shared across interview-generated DSM-based ADs, we applied two phenotypic approaches: (1) comparisons between categorical AD cases and supernormal controls, and (2) quantitative phenotypic factor scores (FS) derived from a multivariate analysis combining information across the clinical phenotypes. We used logistic and linear regression, respectively, to analyze the association between these phenotypes and genome-wide single nucleotide polymorphisms. Meta-analysis for each phenotype combined results across the nine samples for over 18 000 unrelated individuals. Each meta-analysis identified a different genome-wide significant region, with the following markers showing the strongest association: for case–control contrasts, rs1709393 located in an uncharacterized non-coding RNA locus on chromosomal band 3q12.3 (P=1.65 × 10−8); for FS, rs1067327 within CAMKMT encoding the calmodulin-lysine N-methyltransferase on chromosomal band 2p21 (P=2.86 × 10−9). Independent replication and further exploration of these findings are needed to more fully understand the role of these variants in risk and expression of ADs.
Sleep | 2012
Enda M. Byrne; Julie Johnson; Allan F. McRae; Dale R. Nyholt; Sarah E. Medland; Philip R. Gehrman; Andrew C. Heath; Pamela A. F. Madden; Grant W. Montgomery; Georgia Chenevix-Trench; Nicholas G. Martin
OBJECTIVES To identify common genetic variants that predispose to caffeine-induced insomnia and to test whether genes whose expression changes in the presence of caffeine are enriched for association with caffeine-induced insomnia. DESIGN A hypothesis-free, genome-wide association study. SETTING Community-based sample of Australian twins from the Australian Twin Registry. PARTICIPANTS After removal of individuals who said that they do not drink coffee, a total of 2,402 individuals from 1,470 families in the Australian Twin Registry provided both phenotype and genotype information. MEASUREMENTS AND RESULTS A dichotomized scale based on whether participants reported ever or never experiencing caffeine-induced insomnia. A factor score based on responses to a number of questions regarding normal sleep habits was included as a covariate in the analysis. More than 2 million common single nucleotide polymorphisms (SNPs) were tested for association with caffeine-induced insomnia. No SNPs reached the genome-wide significance threshold. In the analysis that did not include the insomnia factor score as a covariate, the most significant SNP identified was an intronic SNP in the PRIMA1 gene (P = 1.4 × 10⁻⁶, odds ratio = 0.68 [0.53 - 0.89]). An intergenic SNP near the GBP4 gene on chromosome 1 was the most significant upon inclusion of the insomnia factor score into the model (P = 1.9 × 10⁻⁶, odds ratio = 0.70 [0.62 - 0.78]). A previously identified association with a polymorphism in the ADORA2A gene was replicated. CONCLUSIONS Several genes have been identified in the study as potentially influencing caffeine-induced insomnia. They will require replication in another sample. The results may have implications for understanding the biologic mechanisms underlying insomnia.
Biological Psychiatry | 2017
Robert A. Power; Katherine E. Tansey; Henriette N. Buttenschøn; Sarah Cohen-Woods; Tim B. Bigdeli; Lynsey S. Hall; Zoltán Kutalik; S. Hong Lee; Stephan Ripke; Stacy Steinberg; Alexander Teumer; Alexander Viktorin; Naomi R. Wray; Volker Arolt; Bernard T. Baune; Dorret I. Boomsma; Anders D. Børglum; Enda M. Byrne; Enrique Castelao; Nicholas John Craddock; Ian Craig; Udo Dannlowski; Ian J. Deary; Franziska Degenhardt; Andreas J. Forstner; Scott D. Gordon; Hans J. Grabe; Jakob Grove; Steven P. Hamilton; Caroline Hayward
Background Major depressive disorder (MDD) is a disabling mood disorder, and despite a known heritable component, a large meta-analysis of genome-wide association studies revealed no replicable genetic risk variants. Given prior evidence of heterogeneity by age at onset in MDD, we tested whether genome-wide significant risk variants for MDD could be identified in cases subdivided by age at onset. Methods Discovery case-control genome-wide association studies were performed where cases were stratified using increasing/decreasing age-at-onset cutoffs; significant single nucleotide polymorphisms were tested in nine independent replication samples, giving a total sample of 22,158 cases and 133,749 control subjects for subsetting. Polygenic score analysis was used to examine whether differences in shared genetic risk exists between earlier and adult-onset MDD with commonly comorbid disorders of schizophrenia, bipolar disorder, Alzheimer’s disease, and coronary artery disease. Results We identified one replicated genome-wide significant locus associated with adult-onset (>27 years) MDD (rs7647854, odds ratio: 1.16, 95% confidence interval: 1.11–1.21, p = 5.2 × 10-11). Using polygenic score analyses, we show that earlier-onset MDD is genetically more similar to schizophrenia and bipolar disorder than adult-onset MDD. Conclusions We demonstrate that using additional phenotype data previously collected by genetic studies to tackle phenotypic heterogeneity in MDD can successfully lead to the discovery of genetic risk factor despite reduced sample size. Furthermore, our results suggest that the genetic susceptibility to MDD differs between adult- and earlier-onset MDD, with earlier-onset cases having a greater genetic overlap with schizophrenia and bipolar disorder.