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Dive into the research topics where Marcus A. Tuke is active.

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Featured researches published by Marcus A. Tuke.


Nature | 2014

Another explanation for apparent epistasis

Andrew R. Wood; Marcus A. Tuke; Michael A. Nalls; Dena Hernandez; Stefania Bandinelli; Andrew Singleton; David Melzer; Luigi Ferrucci; Timothy M. Frayling; Michael N. Weedon

Arising from G. Hemani et al. 508, 249–253 (2014); doi:10.1038/nature1300510.1038/nature13005Epistasis occurs when the effect of a genetic variant on a trait is dependent on genotypes of other variants elsewhere in the genome. Hemani et al. recently reported the detection and replication of many instances of epistasis between pairs of variants influencing gene expression levels in humans. Using whole-genome sequencing data from 450 individuals we strongly replicated many of the reported interactions but, in each case, a single third variant captured by our sequencing data could explain all of the apparent epistasis. Our results provide an alternative explanation for the apparent epistasis observed for gene expression in humans. There is a Reply to this Brief Communication Arising by Hemani, G. et al. Nature 514, http://dx.doi.org/10.1038/nature13692 (2014).


PLOS Genetics | 2016

Genome-Wide Association Analyses in 128,266 Individuals Identifies New Morningness and Sleep Duration Loci

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.


Nature Genetics | 2015

Structural forms of the human amylase locus and their relationships to SNPs, haplotypes and obesity

Christina L. Usher; Robert E. Handsaker; Tonu Esko; Marcus A. Tuke; Michael N. Weedon; Alex Hastie; Jennifer E. Moon; Seva Kashin; Christian Fuchsberger; Andres Metspalu; Carlos N. Pato; Michele T. Pato; Mark I. McCarthy; Michael Boehnke; David Altshuler; Timothy M. Frayling; Joel N. Hirschhorn; Steven A. McCarroll

Hundreds of genes reside in structurally complex, poorly understood regions of the human genome. One such region contains the three amylase genes (AMY2B, AMY2A and AMY1) responsible for digesting starch into sugar. Copy number of AMY1 is reported to be the largest genomic influence on obesity, although genome-wide association studies for obesity have found this locus unremarkable. Using whole-genome sequence analysis, droplet digital PCR and genome mapping, we identified eight common structural haplotypes of the amylase locus that suggest its mutational history. We found that the AMY1 copy number in an individuals genome is generally even (rather than odd) and partially correlates with nearby SNPs, which do not associate with body mass index (BMI). We measured amylase gene copy number in 1,000 obese or lean Estonians and in 2 other cohorts totaling ∼3,500 individuals. We had 99% power to detect the lower bound of the reported effects on BMI, yet found no association.


BMJ | 2016

Height, body mass index, and socioeconomic status: mendelian randomisation study in UK Biobank

Jessica Tyrrell; Samuel E. Jones; Robin N. Beaumont; Christina M. Astley; Rebecca Lovell; Hanieh Yaghootkar; Marcus A. Tuke; Katherine S. Ruth; Rachel M. Freathy; Joel N. Hirschhorn; Andrew R. Wood; Anna Murray; Michael N. Weedon; Timothy M. Frayling

Objective To determine whether height and body mass index (BMI) have a causal role in five measures of socioeconomic status. Design Mendelian randomisation study to test for causal effects of differences in stature and BMI on five measures of socioeconomic status. Mendelian randomisation exploits the fact that genotypes are randomly assigned at conception and thus not confounded by non-genetic factors. Setting UK Biobank. Participants 119 669 men and women of British ancestry, aged between 37 and 73 years. Main outcome measures Age completed full time education, degree level education, job class, annual household income, and Townsend deprivation index. Results In the UK Biobank study, shorter stature and higher BMI were observationally associated with several measures of lower socioeconomic status. The associations between shorter stature and lower socioeconomic status tended to be stronger in men, and the associations between higher BMI and lower socioeconomic status tended to be stronger in women. For example, a 1 standard deviation (SD) higher BMI was associated with a £210 (€276;


International Journal of Epidemiology | 2017

Gene–obesogenic environment interactions in the UK Biobank study

Jessica Tyrrell; Andrew R. Wood; Ryan M. Ames; Hanieh Yaghootkar; Robin N. Beaumont; Samuel E. Jones; Marcus A. Tuke; Katherine S. Ruth; Rachel M. Freathy; George Davey Smith; Stéphane Joost; Idris Guessous; Anna Murray; David P. Strachan; Zoltán Kutalik; Michael N. Weedon; Timothy M. Frayling

300; 95% confidence interval £84 to £420; P=6×10−3) lower annual household income in men and a £1890 (£1680 to £2100; P=6×10−15) lower annual household income in women. Genetic analysis provided evidence that these associations were partly causal. A genetically determined 1 SD (6.3 cm) taller stature caused a 0.06 (0.02 to 0.09) year older age of completing full time education (P=0.01), a 1.12 (1.07 to 1.18) times higher odds of working in a skilled profession (P=6×10−7), and a £1130 (£680 to £1580) higher annual household income (P=4×10−8). Associations were stronger in men. A genetically determined 1 SD higher BMI (4.6 kg/m2) caused a £2940 (£1680 to £4200; P=1×10−5) lower annual household income and a 0.10 (0.04 to 0.16) SD (P=0.001) higher level of deprivation in women only. Conclusions These data support evidence that height and BMI play an important partial role in determining several aspects of a person’s socioeconomic status, especially women’s BMI for income and deprivation and men’s height for education, income, and job class. These findings have important social and health implications, supporting evidence that overweight people, especially women, are at a disadvantage and that taller people, especially men, are at an advantage.


Diabetes | 2016

Genetic Evidence for a Link Between Favorable Adiposity and Lower Risk of Type 2 Diabetes, Hypertension, and Heart Disease.

Hanieh Yaghootkar; Luca A. Lotta; Jessica Tyrrell; Roelof A.J. Smit; Samuel E. Jones; Louise A. Donnelly; Robin N. Beaumont; Archie Campbell; Marcus A. Tuke; Caroline Hayward; Katherine S. Ruth; Sandosh Padmanabhan; J. Wouter Jukema; Colin Palmer; Andrew T. Hattersley; Rachel M. Freathy; Claudia Langenberg; Nicholas J. Wareham; Andrew R. Wood; Anna Murray; Michael N. Weedon; Naveed Sattar; Ewan R. Pearson; Robert A. Scott; Timothy M. Frayling

Abstract Background: Previous studies have suggested that modern obesogenic environments accentuate the genetic risk of obesity. However, these studies have proven controversial as to which, if any, measures of the environment accentuate genetic susceptibility to high body mass index (BMI). Methods: We used up to 120 000 adults from the UK Biobank study to test the hypothesis that high-risk obesogenic environments and behaviours accentuate genetic susceptibility to obesity. We used BMI as the outcome and a 69-variant genetic risk score (GRS) for obesity and 12 measures of the obesogenic environment as exposures. These measures included Townsend deprivation index (TDI) as a measure of socio-economic position, TV watching, a ‘Westernized’ diet and physical activity. We performed several negative control tests, including randomly selecting groups of different average BMIs, using a simulated environment and including sun-protection use as an environment. Results: We found gene–environment interactions with TDI (Pinteraction = 3 × 10–10), self-reported TV watching (Pinteraction = 7 × 10–5) and self-reported physical activity (Pinteraction = 5 × 10–6). Within the group of 50% living in the most relatively deprived situations, carrying 10 additional BMI-raising alleles was associated with approximately 3.8 kg extra weight in someone 1.73 m tall. In contrast, within the group of 50% living in the least deprivation, carrying 10 additional BMI-raising alleles was associated with approximately 2.9 kg extra weight. The interactions were weaker, but present, with the negative controls, including sun-protection use, indicating that residual confounding is likely. Conclusions: Our findings suggest that the obesogenic environment accentuates the risk of obesity in genetically susceptible adults. Of the factors we tested, relative social deprivation best captures the aspects of the obesogenic environment responsible.


Human Reproduction | 2016

Genetic evidence that lower circulating FSH levels lengthen menstrual cycle, increase age at menopause and impact female reproductive health

Katherine S. Ruth; Robin N. Beaumont; Jessica Tyrrell; Samuel E. Jones; Marcus A. Tuke; Hanieh Yaghootkar; Andrew R. Wood; Rachel M. Freathy; Michael N. Weedon; Timothy M. Frayling; Anna Murray

Recent genetic studies have identified some alleles that are associated with higher BMI but lower risk of type 2 diabetes, hypertension, and heart disease. These “favorable adiposity” alleles are collectively associated with lower insulin levels and higher subcutaneous–to–visceral adipose tissue ratio and may protect from disease through higher adipose storage capacity. We aimed to use data from 164,609 individuals from the UK Biobank and five other studies to replicate associations between a genetic score of 11 favorable adiposity variants and adiposity and risk of disease, to test for interactions between BMI and favorable adiposity genetics, and to test effects separately in men and women. In the UK Biobank, the 50% of individuals carrying the most favorable adiposity alleles had higher BMIs (0.120 kg/m2 [95% CI 0.066, 0.174]; P = 1E-5) and higher body fat percentage (0.301% [0.230, 0.372]; P = 1E-16) compared with the 50% of individuals carrying the fewest alleles. For a given BMI, the 50% of individuals carrying the most favorable adiposity alleles were at lower risk of type 2 diabetes (odds ratio [OR] 0.837 [0.784, 0.894]; P = 1E-7), hypertension (OR 0.935 [0.911, 0.958]; P = 1E-7), and heart disease (OR 0.921 [0.872, 0.973]; P = 0.003) and had lower blood pressure (systolic −0.859 mmHg [−1.099, −0.618]; P = 3E-12 and diastolic −0.394 mmHg [−0.534, −0.254]; P = 4E-8). In women, these associations could be explained by the observation that the alleles associated with higher BMI but lower risk of disease were also associated with a favorable body fat distribution, with a lower waist-to-hip ratio (−0.004 cm [95% CI −0.005, −0.003] 50% vs. 50%; P = 3E-14), but in men, the favorable adiposity alleles were associated with higher waist circumference (0.454 cm [0.267, 0.641] 50% vs. 50%; P = 2E-6) and higher waist-to-hip ratio (0.0013 [0.0003, 0.0024] 50% vs. 50%; P = 0.01). Results were strengthened when a meta-analysis with five additional studies was conducted. There was no evidence of interaction between a genetic score consisting of known BMI variants and the favorable adiposity genetic score. In conclusion, different molecular mechanisms that lead to higher body fat percentage (with greater subcutaneous storage capacity) can have different impacts on cardiometabolic disease risk. Although higher BMI is associated with higher risk of diseases, better fat storage capacity could reduce the risk.


Diabetologia | 2016

Variants in the FTO and CDKAL1 loci have recessive effects on risk of obesity and type 2 diabetes, respectively

Andrew R. Wood; Jessica Tyrrell; Robin N. Beaumont; Samuel E. Jones; Marcus A. Tuke; Katherine S. Ruth; Hanieh Yaghootkar; Rachel M. Freathy; Anna Murray; Timothy M. Frayling; Michael N. Weedon

STUDY QUESTION How does a genetic variant in the FSHB promoter, known to alter FSH levels, impact female reproductive health? SUMMARY ANSWER The T allele of the FSHB promoter polymorphism (rs10835638; c.-211G>T) results in longer menstrual cycles and later menopause and, while having detrimental effects on fertility, is protective against endometriosis. WHAT IS KNOWN ALREADY The FSHB promoter polymorphism (rs10835638; c.-211G>T) affects levels of FSHB transcription and, as a result, circulating levels of FSH. FSH is required for normal fertility and genetic variants at the FSHB locus are associated with age at menopause and polycystic ovary syndrome (PCOS). STUDY DESIGN, SIZE, DURATION We used cross-sectional data from the UK Biobank to look at associations between the FSHB promoter polymorphism and reproductive traits, and performed a genome-wide association study (GWAS) for length of menstrual cycle. PARTICIPANTS/MATERIALS, SETTING, METHODS We included white British individuals aged 40–69 years in 2006–2010, in the May 2015 release of genetic data from UK Biobank. We tested the FSH-lowering T allele of the FSHB promoter polymorphism (rs10835638; c.-211G>T) for associations with 29, mainly female, reproductive phenotypes in up to 63 350 women and 56 608 men. We conducted a GWAS in 9534 individuals to identify genetic variants associated with length of menstrual cycle. MAIN RESULTS AND THE ROLE OF CHANCE The FSH-lowering T allele of the FSHB promoter polymorphism (rs10835638; MAF 0.16) was associated with longer menstrual cycles [0.16 SD (c. 1 day) per minor allele; 95% confidence interval (CI) 0.12–0.20; P = 6 × 10−16], later age at menopause (0.13 years per minor allele; 95% CI 0.04–0.22; P = 5.7 × 10−3), greater female nulliparity [odds ratio (OR) = 1.06; 95% CI 1.02–1.11; P = 4.8 × 10−3] and lower risk of endometriosis (OR = 0.79; 95% CI 0.69–0.90; P = 4.1 × 10−4). The FSH-lowering T allele was not associated with other female reproductive illnesses or conditions in our study and we did not replicate associations with male infertility or PCOS. In the GWAS for menstrual cycle length, only variants near the FSHB gene reached genome-wide significance (P < 5 × 10−9). LIMITATIONS, REASONS FOR CAUTION The data included might be affected by recall bias. Cycle length was not available for 25% of women still cycling (1% did not answer, 6% did not know and for 18% cycle length was recorded as ‘irregular’). Women with a cycle length recorded were aged over 40 and were approaching menopause; however, we did not find evidence that this affected the results. Many of the groups with illnesses had relatively small sample sizes and so the study may have been under-powered to detect an effect. WIDER IMPLICATIONS OF THE FINDINGS We found a strong novel association between a genetic variant that lowers FSH levels and longer menstrual cycles, at a locus previously robustly associated with age at menopause. The variant was also associated with nulliparity and endometriosis risk. These findings should now be verified in a second independent group of patients. We conclude that lifetime differences in circulating levels of FSH between individuals can influence menstrual cycle length and a range of reproductive outcomes, including menopause timing, infertility, endometriosis and PCOS. STUDY FUNDING/COMPETING INTEREST(S) None. TRIAL REGISTRATION NUMBER Not applicable.


Human Molecular Genetics | 2018

Genome-wide association study of offspring birth weight in 86 577 women identifies five novel loci and highlights maternal genetic effects that are independent of fetal genetics

Robin N. Beaumont; Nicole M. Warrington; Alana Cavadino; Jessica Tyrrell; Michael Nodzenski; Momoko Horikoshi; Frank Geller; Ronny Myhre; Rebecca C Richmond; Lavinia Paternoster; Jonathan P. Bradfield; Eskil Kreiner-Møller; Ville Huikari; Sarah Metrustry; Kathryn L. Lunetta; Jodie N. Painter; Jouke-Jan Hottenga; Catherine Allard; Sheila J. Barton; Ana Espinosa; Julie A. Marsh; Catherine Potter; Ge Zhang; Wei Ang; Diane J. Berry; Luigi Bouchard; Shikta Das; Hakon Hakonarson; Jani Heikkinen; Øyvind Helgeland

Aims/hypothesisGenome-wide association (GWA) studies have identified hundreds of common genetic variants associated with obesity and type 2 diabetes. These studies have usually focused on additive association tests. Identifying deviations from additivity may provide new biological insights and explain some of the missing heritability for these diseases.MethodsWe performed a GWA study using a dominance deviation model for BMI, obesity (29,925 cases) and type 2 diabetes (4,040 cases) in 120,286 individuals of British ancestry from the UK Biobank study. We also investigated whether single nucleotide polymorphisms previously shown to be associated with these traits showed any enrichment for departures from additivity.ResultsKnown obesity-associated variants in FTO showed strong evidence of deviation from additivity (pDOMDEV = 3 × 10−5) through a recessive effect of the allele associated with higher BMI. The average BMI of individuals carrying zero, one or two BMI-raising alleles was 27.27 (95% CI 27.22, 27.31) kg/m2, 27.54 (95% CI 27.50, 27.58) kg/m2 and 28.07 (95% CI 28.00, 28.14) kg/m2, respectively. A similar effect was observed in 105,643 individuals from the GIANT Consortium (pDOMDEV = 0.003; meta-analysis pDOMDEV = 1 × 10−7). For type 2 diabetes, we detected a recessive effect (pDOMDEV = 5 × 10−4) at CDKAL1. Relative to homozygous non-risk allele carriers, homozygous risk allele carriers had an OR of 1.48 (95% CI 1.32, 1.65), while the heterozygous group had an OR of 1.06 (95% CI 0.99, 1.14), a result consistent with that of a previous study. We did not identify any novel associations at genome-wide significance.Conclusions/interpretationAlthough we found no evidence of widespread non-additive genetic effects contributing to obesity and type 2 diabetes risk, we did find robust examples of recessive effects at the FTO and CDKAL1 loci.Access to research materialsSummary statistics are available at www.t2diabetesgenes.org and by request ([email protected]). All underlying data are available on application from the UK Biobank.


Human Molecular Genetics | 2016

Quantifying the extent to which index event biases influence large genetic association studies.

Hanieh Yaghootkar; Michael P. Bancks; Samuel E. Jones; Aaron McDaid; Robin N. Beaumont; Louise A. Donnelly; Andrew R. Wood; Archie Campbell; Jessica Tyrrell; Lynne J. Hocking; Marcus A. Tuke; Katherine S. Ruth; Ewan R. Pearson; Anna Murray; Rachel M. Freathy; Patricia B. Munroe; Caroline Hayward; Colin N. A. Palmer; Michael N. Weedon; James S. Pankow; Timothy M. Frayling; Zoltán Kutalik

Abstract Genome-wide association studies of birth weight have focused on fetal genetics, whereas relatively little is known about the role of maternal genetic variation. We aimed to identify maternal genetic variants associated with birth weight that could highlight potentially relevant maternal determinants of fetal growth. We meta-analysed data on up to 8.7 million SNPs in up to 86 577 women of European descent from the Early Growth Genetics (EGG) Consortium and the UK Biobank. We used structural equation modelling (SEM) and analyses of mother–child pairs to quantify the separate maternal and fetal genetic effects. Maternal SNPs at 10 loci (MTNR1B, HMGA2, SH2B3, KCNAB1, L3MBTL3, GCK, EBF1, TCF7L2, ACTL9, CYP3A7) were associated with offspring birth weight at P < 5 × 10−8. In SEM analyses, at least 7 of the 10 associations were consistent with effects of the maternal genotype acting via the intrauterine environment, rather than via effects of shared alleles with the fetus. Variants, or correlated proxies, at many of the loci had been previously associated with adult traits, including fasting glucose (MTNR1B, GCK and TCF7L2) and sex hormone levels (CYP3A7), and one (EBF1) with gestational duration. The identified associations indicate that genetic effects on maternal glucose, cytochrome P450 activity and gestational duration, and potentially on maternal blood pressure and immune function, are relevant for fetal growth. Further characterization of these associations in mechanistic and causal analyses will enhance understanding of the potentially modifiable maternal determinants of fetal growth, with the goal of reducing the morbidity and mortality associated with low and high birth weights.

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Michael N. Weedon

National Institute for Health Research

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