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Gene Discovery Using Twins
- David Duffy, Rick Sturm, Gu Zhu, Stuart MacGregor
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- Journal:
- Twin Research and Human Genetics / Volume 23 / Issue 2 / April 2020
- Published online by Cambridge University Press:
- 24 June 2020, pp. 90-93
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One of Nick’s key early achievements at QIMR was to establish a twin study on melanoma risk factors. The Brisbane Twin Nevus Study (BTNS) had an initial focus on nevus (mole) count in adolescents but, reflecting Nick’s broad interests, expanded in scope enormously over the decades. In the skin cancer arena, BTNS was essential to genetic discoveries in melanoma, eye color and pigmentation. Later studies amassed data on thousands of phenotypes, ranging from molecular phenotypes such as gene expression to studies where gene mapping findings in adolescents turned out to have translational potential in late-onset diseases. Nick’s twin data have formed the basis for an enormous range of discoveries, with Nick and his colleagues continuing to capitalize on these data.
Genetic heterogeneity in self-reported depressive symptoms identified through genetic analyses of the PHQ-9
- Jackson G. Thorp, Andries T. Marees, Jue-Sheng Ong, Jiyuan An, Stuart MacGregor, Eske M. Derks
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- Journal:
- Psychological Medicine / Volume 50 / Issue 14 / October 2020
- Published online by Cambridge University Press:
- 18 September 2019, pp. 2385-2396
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Background
Depression is a clinically heterogeneous disorder. Previous large-scale genetic studies of depression have explored genetic risk factors of depression case–control status or aggregated sums of depressive symptoms, ignoring possible clinical or genetic heterogeneity.
MethodsWe analyse data from 148 752 subjects of white British ancestry in the UK Biobank who completed nine items of a self-rated measure of current depressive symptoms: the Patient Health Questionnaire (PHQ-9). Genome-Wide Association analyses were conducted for nine symptoms and two composite measures. LD Score Regression was used to calculate SNP-based heritability (h2SNP) and genetic correlations (rg) across symptoms and to investigate genetic correlations with 25 external phenotypes. Genomic structural equation modelling was used to test the genetic factor structure across the nine symptoms.
ResultsWe identified nine genome-wide significant genomic loci (8 novel), with no overlap in loci across symptoms. h2SNP ranged from 6% (concentration problems) to 9% (appetite changes). Genetic correlations ranged from 0.54 to 0.96 (all p < 1.39 × 10−3) with 30 of 36 correlations being significantly smaller than one. A two-factor model provided the best fit to the genetic covariance matrix, with factors representing ‘psychological’ and ‘somatic’ symptoms. The genetic correlations with external phenotypes showed large variation across the nine symptoms.
ConclusionsPatterns of SNP associations and genetic correlations differ across the nine symptoms, suggesting that current depressive symptoms are genetically heterogeneous. Our study highlights the value of symptom-level analyses in understanding the genetic architecture of a psychiatric trait. Future studies should investigate whether genetic heterogeneity is recapitulated in clinical symptoms of major depression.
Evidence of causal effect of major depression on alcohol dependence: findings from the psychiatric genomics consortium
- Renato Polimanti, Roseann E. Peterson, Jue-Sheng Ong, Stuart MacGregor, Alexis C. Edwards, Toni-Kim Clarke, Josef Frank, Zachary Gerring, Nathan A. Gillespie, Penelope A. Lind, Hermine H. Maes, Nicholas G. Martin, Hamdi Mbarek, Sarah E. Medland, Fabian Streit, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Substance Use Disorder Working Group of the Psychiatric Genomics Consortium, 23andMe Research Team, Arpana Agrawal, Howard J. Edenberg, Kenneth S. Kendler, Cathryn M. Lewis, Patrick F. Sullivan, Naomi R. Wray, Joel Gelernter, Eske M. Derks
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- Journal:
- Psychological Medicine / Volume 49 / Issue 7 / May 2019
- Published online by Cambridge University Press:
- 01 April 2019, pp. 1218-1226
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Background
Despite established clinical associations among major depression (MD), alcohol dependence (AD), and alcohol consumption (AC), the nature of the causal relationship between them is not completely understood. We leveraged genome-wide data from the Psychiatric Genomics Consortium (PGC) and UK Biobank to test for the presence of shared genetic mechanisms and causal relationships among MD, AD, and AC.
MethodsLinkage disequilibrium score regression and Mendelian randomization (MR) were performed using genome-wide data from the PGC (MD: 135 458 cases and 344 901 controls; AD: 10 206 cases and 28 480 controls) and UK Biobank (AC-frequency: 438 308 individuals; AC-quantity: 307 098 individuals).
ResultsPositive genetic correlation was observed between MD and AD (rgMD−AD = + 0.47, P = 6.6 × 10−10). AC-quantity showed positive genetic correlation with both AD (rgAD−AC quantity = + 0.75, P = 1.8 × 10−14) and MD (rgMD−AC quantity = + 0.14, P = 2.9 × 10−7), while there was negative correlation of AC-frequency with MD (rgMD−AC frequency = −0.17, P = 1.5 × 10−10) and a non-significant result with AD. MR analyses confirmed the presence of pleiotropy among these four traits. However, the MD-AD results reflect a mediated-pleiotropy mechanism (i.e. causal relationship) with an effect of MD on AD (beta = 0.28, P = 1.29 × 10−6). There was no evidence for reverse causation.
ConclusionThis study supports a causal role for genetic liability of MD on AD based on genetic datasets including thousands of individuals. Understanding mechanisms underlying MD-AD comorbidity addresses important public health concerns and has the potential to facilitate prevention and intervention efforts.
Potential influence of socioeconomic status on genetic correlations between alcohol consumption measures and mental health
- Andries T. Marees, Dirk J. A. Smit, Jue-Sheng Ong, Stuart MacGregor, Jiyuan An, Damiaan Denys, Florence Vorspan, Wim van den Brink, Eske M. Derks
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- Journal:
- Psychological Medicine / Volume 50 / Issue 3 / February 2020
- Published online by Cambridge University Press:
- 15 March 2019, pp. 484-498
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Background. Frequency and quantity of alcohol consumption are metrics commonly used to measure alcohol consumption behaviors. Epidemiological studies indicate that these alcohol consumption measures are differentially associated with (mental) health outcomes and socioeconomic status (SES). The current study aims to elucidate to what extent genetic risk factors are shared between frequency and quantity of alcohol consumption, and how these alcohol consumption measures are genetically associated with four broad phenotypic categories: (i) SES; (ii) substance use disorders; (iii) other psychiatric disorders; and (iv) psychological/personality traits.
Methods. Genome-Wide Association analyses were conducted to test genetic associations with alcohol consumption frequency (N = 438 308) and alcohol consumption quantity (N = 307 098 regular alcohol drinkers) within UK Biobank. For the other phenotypes, we used genome-wide association studies summary statistics. Genetic correlations (rg) between the alcohol measures and other phenotypes were estimated using LD score regression.
Results. We found a substantial genetic correlation between the frequency and quantity of alcohol consumption (rg = 0.52). Nevertheless, both measures consistently showed opposite genetic correlations with SES traits, and many substance use, psychiatric, and psychological/personality traits. High alcohol consumption frequency was genetically associated with high SES and low risk of substance use disorders and other psychiatric disorders, whereas the opposite applies for high alcohol consumption quantity.
Conclusions. Although the frequency and quantity of alcohol consumption show substantial genetic overlap, they consistently show opposite patterns of genetic associations with SES-related phenotypes. Future studies should carefully consider the potential influence of SES on the shared genetic etiology between alcohol and adverse (mental) health outcomes.
A Novel Approach for Pathway Analysis of GWAS Data Highlights Role of BMP Signaling and Muscle Cell Differentiation in Colorectal Cancer Susceptibility – Erratum
- Aniket Mishra, Stuart MacGregor
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- Twin Research and Human Genetics / Volume 20 / Issue 2 / April 2017
- Published online by Cambridge University Press:
- 23 February 2017, p. 186
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The publishers regret to announce that the affiliation for the above paper was incorrectly inserted. The correct affiliation is below:
Aniket Mishra1, Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) and the Colorectal Cancer Family Registry (CCFR), and Stuart MacGregor1
1 Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
A Novel Approach for Pathway Analysis of GWAS Data Highlights Role of BMP Signaling and Muscle Cell Differentiation in Colorectal Cancer Susceptibility
- Aniket Mishra, Stuart MacGregor
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- Journal:
- Twin Research and Human Genetics / Volume 20 / Issue 1 / February 2017
- Published online by Cambridge University Press:
- 20 January 2017, pp. 1-9
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Genome-wide association studies (GWAS) have revolutionized the field of gene mapping. As the GWAS field matures, it is becoming clear that for many complex traits, a proportion of the missing heritability is attributable to common variants of individually small effect. Detecting these small effects individually can be difficult, and statistical power would be increased if relevant variants could be grouped together for testing. Here, we propose a VEGAS2Pathway approach that aggregates association strength of individual markers into pre-specified biological pathways. It accounts for gene size and linkage disequilibrium between markers using simulations from the multivariate normal distribution. Pathway size is taken into account via a resampling approach. Importantly, since the approach only requires summary data, the method can easily be applied in all GWASs, including meta-analysis, singleton-based, family-based, and DNA-pooling-based designs. This approach is implemented in a user-friendly web page https://vegas2.qimrberghofer.edu.au and a command line tool. The web implementation uses gene-sets from the gene ontology (GO), curated gene-sets from MSigDB (containing canonical pathways and gene-sets from BIOCARTA, REACTOME, KEGG databases), PANTHER, and pathway commons databases, enabling analysis of a wide range of complex traits. We applied this method on a colorectal cancer GWAS meta-analysis data set (10,934 cases, 12,328 controls) from the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO). We report statistically significant enrichment of association signal for the ‘BMP signaling’ and ‘muscle cell differentiation’ pathways, suggesting a possible role for these pathways onto the risk of colorectal cancer.
Sweet Taste Perception is Associated with Body Mass Index at the Phenotypic and Genotypic Level
- Liang-Dar Hwang, Gabriel Cuellar-Partida, Jue-Sheng Ong, Paul A. S. Breslin, Danielle R. Reed, Stuart MacGregor, Puya Gharahkhani, Nicholas G. Martin, Miguel E. Rentería
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- Journal:
- Twin Research and Human Genetics / Volume 19 / Issue 5 / October 2016
- Published online by Cambridge University Press:
- 05 August 2016, pp. 465-471
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Investigations on the relationship between sweet taste perception and body mass index (BMI) have been inconclusive. Here, we report a longitudinal analysis using a genetically informative sample of 1,576 adolescent Australian twins to explore the relationship between BMI and sweet taste. First, we estimated the phenotypic correlations between perception scores for four different sweet compounds (glucose, fructose, neohesperidine dihydrochalcone (NHDC), and aspartame) and BMI. Then, we computed the association between adolescent taste perception and BMI in early adulthood (reported 9 years later). Finally, we used twin modeling and polygenic risk prediction analysis to investigate the genetic overlap between BMI and sweet taste perception. Our findings revealed that BMI in early adulthood was significantly associated with each of the sweet perception scores, with the strongest correlation observed in aspartame with r = 0.09 (p = .007). However, only limited evidence of association was observed between sweet taste perception and BMI that was measured at the same time (in adolescence), with the strongest evidence of association observed for glucose with a correlation coefficient of r = 0.06 (p = .029) and for aspartame with r = 0.06 (p = .035). We found a significant (p < .05) genetic correlation between glucose and NHDC perception and BMI. Our analyses suggest that sweet taste perception in adolescence can be a potential indicator of BMI in early adulthood. This association is further supported by evidence of genetic overlap between the traits, suggesting that some BMI genes may be acting through biological pathways of taste perception.
A Genomewide Association Study of Nicotine and Alcohol Dependence in Australian and Dutch Populations
- Penelope A. Lind, Stuart Macgregor, Jacqueline M. Vink, Michele L Pergadia, Narelle K. Hansell, Marleen H. M. de Moor, August B. Smit, Jouke-Jan Hottenga, Melinda M. Richter, Andrew C. Heath, Nicholas G. Martin, Gonneke Willemsen, Eco J. C. de Geus, Nicole Vogelzangs, Brenda W. Penninx, John B. Whitfield, Grant W. Montgomery, Dorret I. Boomsma, Pamela A. F. Madden
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- Journal:
- Twin Research and Human Genetics / Volume 13 / Issue 1 / February 2010
- Published online by Cambridge University Press:
- 21 January 2016, pp. 11-29
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Persistent tobacco use and excessive alcohol consumption are major public health concerns worldwide. Both alcohol and nicotine dependence (AD, ND) are genetically influenced complex disorders that exhibit a high degree of comorbidity. To identify gene variants contributing to one or both of these addictions, we first conducted a pooling-based genomewide association study (GWAS) in an Australian population, using Illumina Infinium 1M arrays. Allele frequency differences were compared between pooled DNA from case and control groups for: (1) AD, 1224 cases and 1162 controls; (2) ND, 1273 cases and 1113 controls; and (3) comorbid AD and ND, 599 cases and 488 controls. Secondly, we carried out a GWAS in independent samples from the Netherlands for AD and for ND. Thirdly, we performed a meta-analysis of the 10, 000 most significant AD- and ND-related SNPs from the Australian and Dutch samples. In the Australian GWAS, one SNP achieved genomewide significance (p < 5 x 10-8) for ND (rs964170 in ARHGAPlOon chromosome 4, p = 4.43 x 10”8) and three others for comorbid AD/ND (rs7530302 near MARK1 on chromosome 1 (p = 1.90 x 10-9), rs1784300 near DDX6 on chromosome 11 (p = 2.60 x 10-9) and rs12882384 in KIAA1409 on chromosome 14 (p = 4.86 x 10-8)). None of the SNPs achieved genomewide significance in the Australian/Dutch meta-analysis, but a gene network diagram based on the top-results revealed overrepre-sentation of genes coding for ion-channels and cell adhesion molecules. Further studies will be requirec before the detailed causes of comorbidity between AC and ND are understood.
VEGAS2: Software for More Flexible Gene-Based Testing
- Aniket Mishra, Stuart Macgregor
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- Twin Research and Human Genetics / Volume 18 / Issue 1 / February 2015
- Published online by Cambridge University Press:
- 18 December 2014, pp. 86-91
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Gene-based tests such as versatile gene-based association study (VEGAS) are commonly used following per-single nucleotide polymorphism (SNP) GWAS (genome-wide association studies) analysis. Two limitations of VEGAS were that the HapMap2 reference set was used to model the correlation between SNPs and only autosomal genes were considered. HapMap2 has now been superseded by the 1,000 Genomes reference set, and whereas early GWASs frequently ignored the X chromosome, it is now commonly included. Here we have developed VEGAS2, an extension that uses 1,000 Genomes data to model SNP correlations across the autosomes and chromosome X. VEGAS2 allows greater flexibility when defining gene boundaries. VEGAS2 offers both a user-friendly, web-based front end and a command line Linux version. The online version of VEGAS2 can be accessed through https://vegas2.qimrberghofer.edu.au/. The command line version can be downloaded from https://vegas2.qimrberghofer.edu.au/zVEGAS2offline.tgz. The command line version is developed in Perl, R and shell scripting languages; source code is available for further development.
Genome-Wide Association Study for Ovarian Cancer Susceptibility Using Pooled DNA
- Yi Lu, Xiaoqing Chen, Jonathan Beesley, Sharon E. Johnatty, Anna deFazio, Australian Ovarian Cancer Study (AOCS) Study Group, Sandrina Lambrechts, Diether Lambrechts, Evelyn Despierre, Ignace Vergotes, Jenny Chang-Claude, Rebecca Hein, Stefan Nickels, Shan Wang-Gohrke, Thilo Dörk, Matthias Dürst, Natalia Antonenkova, Natalia Bogdanova, Marc T. Goodman, Galina Lurie, Lynne R. Wilkens, Michael E. Carney, Ralf Butzow, Heli Nevanlinna, Tuomas Heikkinen, Arto Leminen, Lambertus A. Kiemeney, Leon F.A.G. Massuger, Anne M. van Altena, Katja K. Aben, Susanne Krüger Kjaer, Estrid Høgdall, Allan Jensen, Angela Brooks-Wilson, Nhu Le, Linda Cook, Madalene Earp, Linda Kelemen, Douglas Easton, Paul Pharoah, Honglin Song, Jonathan Tyrer, Susan Ramus, Usha Menon, Alexandra Gentry-Maharaj, Simon A. Gayther, Elisa V. Bandera, Sara H. Olson, Irene Orlow, Lorna Rodriguez-Rodriguez, Stuart Macgregor, Georgia Chenevix-Trench
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- Journal:
- Twin Research and Human Genetics / Volume 15 / Issue 5 / October 2012
- Published online by Cambridge University Press:
- 13 July 2012, pp. 615-623
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Recent Genome-Wide Association Studies (GWAS) have identified four low-penetrance ovarian cancer susceptibility loci. We hypothesized that further moderate- or low-penetrance variants exist among the subset of single-nucleotide polymorphisms (SNPs) not well tagged by the genotyping arrays used in the previous studies, which would account for some of the remaining risk. We therefore conducted a time- and cost-effective stage 1 GWAS on 342 invasive serous cases and 643 controls genotyped on pooled DNA using the high-density Illumina 1M-Duo array. We followed up 20 of the most significantly associated SNPs, which are not well tagged by the lower density arrays used by the published GWAS, and genotyping them on individual DNA. Most of the top 20 SNPs were clearly validated by individually genotyping the samples used in the pools. However, none of the 20 SNPs replicated when tested for association in a much larger stage 2 set of 4,651 cases and 6,966 controls from the Ovarian Cancer Association Consortium. Given that most of the top 20 SNPs from pooling were validated in the same samples by individual genotyping, the lack of replication is likely to be due to the relatively small sample size in our stage 1 GWAS rather than due to problems with the pooling approach. We conclude that there are unlikely to be any moderate or large effects on ovarian cancer risk untagged by less dense arrays. However, our study lacked power to make clear statements on the existence of hitherto untagged small-effect variants.
Effects of GABRA2 Variation on Physiological, Psychomotor and Subjective Responses in the Alcohol Challenge Twin Study
- Penelope A. Lind, Stuart MacGregor, Grant W. Montgomery, Andrew C. Heath, Nicholas G. Martin, John B. Whitfield
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- Twin Research and Human Genetics / Volume 11 / Issue 2 / 01 April 2008
- Published online by Cambridge University Press:
- 21 February 2012, pp. 174-182
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Multiple reports have identified variation in the GABRA2 gene as contributing to the genetic susceptibility to alcohol dependence. However, both the mechanism behind this association, and the range of alcohol-related phenotypes affected by variation in this gene, are currently undefined. Other data suggest that the risk of alcohol dependence is increased by relative insensitivity to alcohol's intoxicating effects. We have therefore tested whether GABRA2 variation is associated with variation in the subjective and objective effects of a standard dose of alcohol in humans. Data on responses to alcohol from the Alcohol Challenge Twin Study (Martin et al., 1985) have been tested against allelic and haplotype information obtained by typing 41 single-nucleotide polymorphisms in or close to the GABRA2 gene. Nominally significant allelic associations (p < .05, without correction for multiple testing) were found for body sway, motor coordination, pursuit rotor and arithmetical computation tasks, and for the personality dimension of Neuroticism. Because of the large number of phenotypes tested, these possibly significant findings will need to be confirmed in further studies.
Vitamin D Receptor Gene Polymorphisms Have Negligible Effect on Human Height
- Stuart Macgregor, Jouke-Jan Hottenga, Penelope A. Lind, H. Eka D. Suchiman, Gonneke Willemsen, P. Eline Slagboom, Grant W. Montgomery, Nicholas G. Martin, Peter M. Visscher, Dorret I. Boomsma
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- Twin Research and Human Genetics / Volume 11 / Issue 5 / 01 October 2008
- Published online by Cambridge University Press:
- 21 February 2012, pp. 488-494
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Human height is a highly heritable trait, with genetic factors explaining up to 90% of phenotypic variation. Vitamin D levels are known to influence several physiological processes, including skeletal growth. The vitamin D receptor (VDR) gene has been reported as contributing to variation in height. A meta-analysis of 13607 adult individuals found a small but significant association with the rs1544410 (BsmI) polymorphism. In contrast, the meta-analysis found no effect in a sample of 550 children. Two recent studies reported variants with large effect on height elsewhere in VDR (rs10735810 [FokI] and rs7139166 [-1521] polymorphisms). We genotyped large Caucasian samples from Australia (N = 3906) and the Netherlands (N = 1689) for polymorphisms in VDR. The Australian samples were twin families with height measures from 3 time points throughout adolescence. The Dutch samples were adult twins. We use the available family data to perform both within and between family tests of association. We found no significant associations for any of the genotyped variants after multiple testing correction. The (non-significant) effect of rs1544410 in the Australian adolescent cohort was in the same direction and of similar magnitude (additive effect 0.3cm) to the effect observed in the published adult meta-analysis. An effect of this size explains ~0.1% of the phenotypic variance in height — this implies that many, probably hundreds, of such variants are responsible for the observed genetic variation. Our results did not support any role for two other regions (rs10735810, rs7139166) of VDR in explaining variation in height.
False Disease Region Identification From Identity-By-Descent Haplotype Sharing in the Presence of Phenocopies
- Stuart Macgregor, Sara A. Knott, Peter M. Visscher
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- Journal:
- Twin Research and Human Genetics / Volume 9 / Issue 1 / 01 February 2006
- Published online by Cambridge University Press:
- 21 February 2012, pp. 9-16
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Linkage analysis (either parametric or nonparametric) is commonly applied to identify chromosomal regions using related individuals affected by disease. In complex disease the incomplete relationship between phenotype and genotype can be modeled using a phenocopy parameter, the probability that an individual is affected given they do not carry the disease mutation of interest, and a nonpenetrance parameter, the probability that an individual is not affected given they do carry the disease mutation of interest. If the linkage phase between multiple markers and a putative disease locus is known, then haplotypes carrying the mutation can, in principle, be identified by comparing the chromosome segments that are shared identical-by-descent (IBD) across affected individuals. We consider here the effect of a nonzero phenocopy rate on the linkage peak and hence upon the identification of disease haplotypes that are shared IBD between affected individuals. We show, by theory and computer simulation, that in diseases for which there is a nonzero phenocopy rate, the chromosomal regions identified may not include the true disease locus. We utilize a LOD-1 confidence interval for a widely used nonparametric linkage statistic. We find that in small/moderate samples this confidence interval may be inappropriate. We give specific examples where the phenocopy rates are nonnegligible in some complex diseases. The success of further work to identify the causal mutations underlying the linkage peaks in these diseases will depend on researchers allowing for the presence of phenocopies by examining appropriately wide regions around the initial positive linkage finding.
Contributors
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- By Rose Teteki Abbey, K. C. Abraham, David Tuesday Adamo, LeRoy H. Aden, Efrain Agosto, Victor Aguilan, Gillian T. W. Ahlgren, Charanjit Kaur AjitSingh, Dorothy B E A Akoto, Giuseppe Alberigo, Daniel E. Albrecht, Ruth Albrecht, Daniel O. Aleshire, Urs Altermatt, Anand Amaladass, Michael Amaladoss, James N. Amanze, Lesley G. Anderson, Thomas C. Anderson, Victor Anderson, Hope S. Antone, María Pilar Aquino, Paula Arai, Victorio Araya Guillén, S. Wesley Ariarajah, Ellen T. Armour, Brett Gregory Armstrong, Atsuhiro Asano, Naim Stifan Ateek, Mahmoud Ayoub, John Alembillah Azumah, Mercedes L. García Bachmann, Irena Backus, J. Wayne Baker, Mieke Bal, Lewis V. Baldwin, William Barbieri, António Barbosa da Silva, David Basinger, Bolaji Olukemi Bateye, Oswald Bayer, Daniel H. Bays, Rosalie Beck, Nancy Elizabeth Bedford, Guy-Thomas Bedouelle, Chorbishop Seely Beggiani, Wolfgang Behringer, Christopher M. Bellitto, Byard Bennett, Harold V. Bennett, Teresa Berger, Miguel A. Bernad, Henley Bernard, Alan E. Bernstein, Jon L. Berquist, Johannes Beutler, Ana María Bidegain, Matthew P. Binkewicz, Jennifer Bird, Joseph Blenkinsopp, Dmytro Bondarenko, Paulo Bonfatti, Riet en Pim Bons-Storm, Jessica A. Boon, Marcus J. Borg, Mark Bosco, Peter C. Bouteneff, François Bovon, William D. Bowman, Paul S. Boyer, David Brakke, Richard E. Brantley, Marcus Braybrooke, Ian Breward, Ênio José da Costa Brito, Jewel Spears Brooker, Johannes Brosseder, Nicholas Canfield Read Brown, Robert F. Brown, Pamela K. Brubaker, Walter Brueggemann, Bishop Colin O. Buchanan, Stanley M. Burgess, Amy Nelson Burnett, J. Patout Burns, David B. Burrell, David Buttrick, James P. Byrd, Lavinia Byrne, Gerado Caetano, Marcos Caldas, Alkiviadis Calivas, William J. Callahan, Salvatore Calomino, Euan K. Cameron, William S. Campbell, Marcelo Ayres Camurça, Daniel F. Caner, Paul E. Capetz, Carlos F. Cardoza-Orlandi, Patrick W. Carey, Barbara Carvill, Hal Cauthron, Subhadra Mitra Channa, Mark D. Chapman, James H. Charlesworth, Kenneth R. Chase, Chen Zemin, Luciano Chianeque, Philip Chia Phin Yin, Francisca H. Chimhanda, Daniel Chiquete, John T. Chirban, Soobin Choi, Robert Choquette, Mita Choudhury, Gerald Christianson, John Chryssavgis, Sejong Chun, Esther Chung-Kim, Charles M. A. Clark, Elizabeth A. Clark, Sathianathan Clarke, Fred Cloud, John B. Cobb, W. Owen Cole, John A Coleman, John J. Collins, Sylvia Collins-Mayo, Paul K. Conkin, Beth A. Conklin, Sean Connolly, Demetrios J. Constantelos, Michael A. Conway, Paula M. Cooey, Austin Cooper, Michael L. Cooper-White, Pamela Cooper-White, L. William Countryman, Sérgio Coutinho, Pamela Couture, Shannon Craigo-Snell, James L. Crenshaw, David Crowner, Humberto Horacio Cucchetti, Lawrence S. Cunningham, Elizabeth Mason Currier, Emmanuel Cutrone, Mary L. Daniel, David D. Daniels, Robert Darden, Rolf Darge, Isaiah Dau, Jeffry C. Davis, Jane Dawson, Valentin Dedji, John W. de Gruchy, Paul DeHart, Wendy J. Deichmann Edwards, Miguel A. De La Torre, George E. Demacopoulos, Thomas de Mayo, Leah DeVun, Beatriz de Vasconcellos Dias, Dennis C. Dickerson, John M. Dillon, Luis Miguel Donatello, Igor Dorfmann-Lazarev, Susanna Drake, Jonathan A. Draper, N. Dreher Martin, Otto Dreydoppel, Angelyn Dries, A. J. Droge, Francis X. D'Sa, Marilyn Dunn, Nicole Wilkinson Duran, Rifaat Ebied, Mark J. Edwards, William H. Edwards, Leonard H. Ehrlich, Nancy L. Eiesland, Martin Elbel, J. Harold Ellens, Stephen Ellingson, Marvin M. Ellison, Robert Ellsberg, Jean Bethke Elshtain, Eldon Jay Epp, Peter C. Erb, Tassilo Erhardt, Maria Erling, Noel Leo Erskine, Gillian R. Evans, Virginia Fabella, Michael A. Fahey, Edward Farley, Margaret A. Farley, Wendy Farley, Robert Fastiggi, Seena Fazel, Duncan S. Ferguson, Helwar Figueroa, Paul Corby Finney, Kyriaki Karidoyanes FitzGerald, Thomas E. FitzGerald, John R. Fitzmier, Marie Therese Flanagan, Sabina Flanagan, Claude Flipo, Ronald B. Flowers, Carole Fontaine, David Ford, Mary Ford, Stephanie A. Ford, Jim Forest, William Franke, Robert M. Franklin, Ruth Franzén, Edward H. Friedman, Samuel Frouisou, Lorelei F. Fuchs, Jojo M. Fung, Inger Furseth, Richard R. Gaillardetz, Brandon Gallaher, China Galland, Mark Galli, Ismael García, Tharscisse Gatwa, Jean-Marie Gaudeul, Luis María Gavilanes del Castillo, Pavel L. Gavrilyuk, Volney P. Gay, Metropolitan Athanasios Geevargis, Kondothra M. George, Mary Gerhart, Simon Gikandi, Maurice Gilbert, Michael J. Gillgannon, Verónica Giménez Beliveau, Terryl Givens, Beth Glazier-McDonald, Philip Gleason, Menghun Goh, Brian Golding, Bishop Hilario M. Gomez, Michelle A. Gonzalez, Donald K. Gorrell, Roy Gottfried, Tamara Grdzelidze, Joel B. Green, Niels Henrik Gregersen, Cristina Grenholm, Herbert Griffiths, Eric W. Gritsch, Erich S. Gruen, Christoffer H. Grundmann, Paul H. Gundani, Jon P. Gunnemann, Petre Guran, Vidar L. Haanes, Jeremiah M. Hackett, Getatchew Haile, Douglas John Hall, Nicholas Hammond, Daphne Hampson, Jehu J. Hanciles, Barry Hankins, Jennifer Haraguchi, Stanley S. Harakas, Anthony John Harding, Conrad L. Harkins, J. William Harmless, Marjory Harper, Amir Harrak, Joel F. Harrington, Mark W. Harris, Susan Ashbrook Harvey, Van A. Harvey, R. Chris Hassel, Jione Havea, Daniel Hawk, Diana L. Hayes, Leslie Hayes, Priscilla Hayner, S. Mark Heim, Simo Heininen, Richard P. Heitzenrater, Eila Helander, David Hempton, Scott H. Hendrix, Jan-Olav Henriksen, Gina Hens-Piazza, Carter Heyward, Nicholas J. Higham, David Hilliard, Norman A. Hjelm, Peter C. Hodgson, Arthur Holder, M. Jan Holton, Dwight N. Hopkins, Ronnie Po-chia Hsia, Po-Ho Huang, James Hudnut-Beumler, Jennifer S. Hughes, Leonard M. Hummel, Mary E. Hunt, Laennec Hurbon, Mark Hutchinson, Susan E. Hylen, Mary Beth Ingham, H. Larry Ingle, Dale T. Irvin, Jon Isaak, Paul John Isaak, Ada María Isasi-Díaz, Hans Raun Iversen, Margaret C. 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Yee, Viktor Yelensky, Yeo Khiok-Khng, Gustav K. K. Yeung, Angela Yiu, Amos Yong, Yong Ting Jin, You Bin, Youhanna Nessim Youssef, Eliana Yunes, Robert Michael Zaller, Valarie H. Ziegler, Barbara Brown Zikmund, Joyce Ann Zimmerman, Aurora Zlotnik, Zhuo Xinping
- Edited by Daniel Patte, Vanderbilt University, Tennessee
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- Book:
- The Cambridge Dictionary of Christianity
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- 05 August 2012
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- 20 September 2010, pp xi-xliv
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Genetic variation of brain-derived neurotrophic factor (BDNF) in bipolar disorder: Case-control study of over 3000 individuals from the UK
- Elaine K. Green, Rachel Raybould, Stuart Macgregor, Sally Hyde, Allan H. Young, Michael C. O'Donovan, Michael J. Owen, George Kirov, Lisa Jones, Ian Jones, Nick Craddock
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- Journal:
- The British Journal of Psychiatry / Volume 188 / Issue 1 / January 2006
- Published online by Cambridge University Press:
- 02 January 2018, pp. 21-25
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- January 2006
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Background
Brain-derived neurotrophic factor (BDNF) influences neuronal survival, proliferation and plasticity Three family-based studies have shown association of the common Valine (Val) allele of the Val66Met polymorphism of the BDNF gene with susceptibility to bipolar disorder.
AimsTo replicate this finding.
MethodWe genotyped the Val66Met polymorphism in our UK White bipolar case-control sample (n=3062).
ResultsWe found no overall evidence of allele or genotype association. However, we found association with disease status in the subset of 131 individuals that had experienced rapid cycling at some time (P=0.004). We found a similar association on re-analysis of our previously reported family-based association sample (P<0.03, one-tailed test).
ConclusionsVariation at the Val66Met polymorphism of BDNF does not play a major role in influencing susceptibility to bipolar disorder as a whole, but is associated with susceptibility to the rapid-cycling subset of the disorder.