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Article ; Online: Sex steroid hormones and risk of breast cancer: a two-sample Mendelian randomization study.

Nounu, Aayah / Kar, Siddhartha P / Relton, Caroline L / Richmond, Rebecca C

2022 Volume 24, Issue 1, Page(s) 66

Abstract: Background: Breast cancer (BC) has the highest cancer incidence and mortality in women worldwide. Observational epidemiological studies suggest a positive association between testosterone, estradiol, dehydroepiandrosterone sulphate (DHEAS) and other sex ...

Abstract	Background: Breast cancer (BC) has the highest cancer incidence and mortality in women worldwide. Observational epidemiological studies suggest a positive association between testosterone, estradiol, dehydroepiandrosterone sulphate (DHEAS) and other sex steroid hormones with postmenopausal BC. We used a two-sample Mendelian randomization analysis to investigate this association. Methods: Genetic instruments for nine sex steroid hormones and sex hormone-binding globulin (SHBG) were obtained from genome-wide association studies (GWAS) of UK Biobank (total testosterone (TT) N: 230,454, bioavailable testosterone (BT) N: 188,507 and SHBG N: 189,473), The United Kingdom Household Longitudinal Study (DHEAS N: 9722), the LIFE-Adult and LIFE-Heart cohorts (estradiol N: 2607, androstenedione N: 711, aldosterone N: 685, progesterone N: 1259 and 17-hydroxyprogesterone N: 711) and the CORtisol NETwork (CORNET) consortium (cortisol N: 25,314). Outcome GWAS summary statistics were obtained from the Breast Cancer Association Consortium (BCAC) for overall BC risk (N: 122,977 cases and 105,974 controls) and subtype-specific analyses. Results: We found that a standard deviation (SD) increase in TT, BT and estradiol increased the risk of overall BC (OR 1.14, 95% CI 1.09-1.21, OR 1.19, 95% CI 1.07-1.33 and OR 1.03, 95% CI 1.01-1.06, respectively) and ER + BC (OR 1.19, 95% CI 1.12-1.27, OR 1.25, 95% CI 1.11-1.40 and OR 1.06, 95% CI 1.03-1.09, respectively). An SD increase in DHEAS also increased ER + BC risk (OR 1.09, 95% CI 1.03-1.16). Subtype-specific analyses showed similar associations with ER+ expressing subtypes: luminal A-like BC, luminal B-like BC and luminal B/HER2-negative-like BC. Conclusions: TT, BT, DHEAS and estradiol increase the risk of ER+ type BCs similar to observational studies. Understanding the role of sex steroid hormones in BC risk, particularly subtype-specific risks, highlights the potential importance of attempts to modify and/or monitor hormone levels in order to prevent BC.
MeSH term(s)	17-alpha-Hydroxyprogesterone ; Adult ; Aldosterone ; Androstenedione ; Breast Neoplasms/epidemiology ; Breast Neoplasms/genetics ; Dehydroepiandrosterone Sulfate ; Estradiol ; Female ; Genome-Wide Association Study ; Gonadal Steroid Hormones ; Humans ; Hydrocortisone ; Longitudinal Studies ; Mendelian Randomization Analysis ; Progesterone ; Sex Hormone-Binding Globulin ; Testosterone
Chemical Substances	Gonadal Steroid Hormones ; Sex Hormone-Binding Globulin ; Testosterone (3XMK78S47O) ; Androstenedione (409J2J96VR) ; Aldosterone (4964P6T9RB) ; Progesterone (4G7DS2Q64Y) ; Estradiol (4TI98Z838E) ; Dehydroepiandrosterone Sulfate (57B09Q7FJR) ; 17-alpha-Hydroxyprogesterone (68-96-2) ; Hydrocortisone (WI4X0X7BPJ)
Language	English
Publishing date	2022-10-08
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2015059-3
ISSN	1465-542X ; 1465-5411
ISSN (online)	1465-542X
ISSN	1465-5411
DOI	10.1186/s13058-022-01553-9
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Article ; Online: Investigating causality in the association between DNA methylation and type 2 diabetes using bidirectional two-sample Mendelian randomisation.

Juvinao-Quintero, Diana L / Sharp, Gemma C / Sanderson, Eleanor C M / Relton, Caroline L / Elliott, Hannah R

Diabetologia

2023 Volume 66, Issue 7, Page(s) 1247–1259

Abstract: Aims/hypothesis: Several studies have identified associations between type 2 diabetes and DNA methylation (DNAm). However, the causal role of these associations remains unclear. This study aimed to provide evidence for a causal relationship between DNAm ...

Abstract	Aims/hypothesis: Several studies have identified associations between type 2 diabetes and DNA methylation (DNAm). However, the causal role of these associations remains unclear. This study aimed to provide evidence for a causal relationship between DNAm and type 2 diabetes. Methods: We used bidirectional two-sample Mendelian randomisation (2SMR) to evaluate causality at 58 CpG sites previously detected in a meta-analysis of epigenome-wide association studies (meta-EWAS) of prevalent type 2 diabetes in European populations. We retrieved genetic proxies for type 2 diabetes and DNAm from the largest genome-wide association study (GWAS) available. We also used data from the Avon Longitudinal Study of Parents and Children (ALSPAC, UK) when associations of interest were not available in the larger datasets. We identified 62 independent SNPs as proxies for type 2 diabetes, and 39 methylation quantitative trait loci as proxies for 30 of the 58 type 2 diabetes-related CpGs. We applied the Bonferroni correction for multiple testing and inferred causality based on p<0.001 for the type 2 diabetes to DNAm direction and p<0.002 for the opposing DNAm to type 2 diabetes direction in the 2SMR analysis. Results: We found strong evidence of a causal effect of DNAm at cg25536676 (DHCR24) on type 2 diabetes. An increase in transformed residuals of DNAm at this site was associated with a 43% (OR 1.43, 95% CI 1.15, 1.78, p=0.001) higher risk of type 2 diabetes. We inferred a likely causal direction for the remaining CpG sites assessed. In silico analyses showed that the CpGs analysed were enriched for expression quantitative trait methylation sites (eQTMs) and for specific traits, dependent on the direction of causality predicted by the 2SMR analysis. Conclusions/interpretation: We identified one CpG mapping to a gene related to the metabolism of lipids (DHCR24) as a novel causal biomarker for risk of type 2 diabetes. CpGs within the same gene region have previously been associated with type 2 diabetes-related traits in observational studies (BMI, waist circumference, HDL-cholesterol, insulin) and in Mendelian randomisation analyses (LDL-cholesterol). Thus, we hypothesise that our candidate CpG in DHCR24 may be a causal mediator of the association between known modifiable risk factors and type 2 diabetes. Formal causal mediation analysis should be implemented to further validate this assumption.
MeSH term(s)	Child ; Humans ; DNA Methylation/genetics ; Diabetes Mellitus, Type 2/genetics ; Diabetes Mellitus, Type 2/metabolism ; Longitudinal Studies ; Genome-Wide Association Study ; Cholesterol
Chemical Substances	Cholesterol (97C5T2UQ7J)
Language	English
Publishing date	2023-05-19
Publishing country	Germany
Document type	Meta-Analysis ; Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1694-9
ISSN	1432-0428 ; 0012-186X
ISSN (online)	1432-0428
ISSN	0012-186X
DOI	10.1007/s00125-023-05914-7
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Article ; Online: What is it about boys?

Relton, Caroline L

International journal of epidemiology

2014 Volume 43, Issue 1, Page(s) 5–7

MeSH term(s)	Chimerism ; Chromosomes, Human, Y ; DNA/blood ; Female ; Humans ; Male ; Pregnancy ; Survival
Chemical Substances	DNA (9007-49-2)
Language	English
Publishing date	2014-02-28
Publishing country	England
Document type	Editorial ; Research Support, Non-U.S. Gov't ; Comment
ZDB-ID	187909-1
ISSN	1464-3685 ; 0300-5771
ISSN (online)	1464-3685
ISSN	0300-5771
DOI	10.1093/ije/dyu017
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Zs.A 893: Show issues

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Article ; Online: Epigenetic modelling of former, current and never smokers.

Langdon, Ryan J / Yousefi, Paul / Relton, Caroline L / Suderman, Matthew J

Clinical epigenetics

2021 Volume 13, Issue 1, Page(s) 206

Abstract: Background: DNA methylation (DNAm) performs excellently in the discrimination of current and former smokers from never smokers, where AUCs > 0.9 are regularly reported using a single CpG site (cg05575921; AHRR). However, there is a paucity of DNAm ... ...

Abstract	Background: DNA methylation (DNAm) performs excellently in the discrimination of current and former smokers from never smokers, where AUCs > 0.9 are regularly reported using a single CpG site (cg05575921; AHRR). However, there is a paucity of DNAm models which attempt to distinguish current, former and never smokers as individual classes. Derivation of a robust DNAm model that accurately distinguishes between current, former and never smokers would be particularly valuable to epidemiological research (as a more accurate smoking definition vs. self-report) and could potentially translate to clinical settings. Therefore, we appraise 4 DNAm models of ternary smoking status (that is, current, former and never smokers): methylation at cg05575921 (AHRR model), weighted scores from 13 CpGs created by Maas et al. (Maas model), weighted scores from a LASSO model of candidate smoking CpGs from the literature (candidate CpG LASSO model), and weighted scores from a LASSO model supplied with genome-wide 450K data (agnostic LASSO model). Discrimination is assessed by AUC, whilst classification accuracy is assessed by accuracy and kappa, derived from confusion matrices. Results: We find that DNAm can classify ternary smoking status with reasonable accuracy, including when applied to external data. Ternary classification using only DNAm far exceeds the classification accuracy of simply assigning all classes as the most prevalent class (63.7% vs. 36.4%). Further, we develop a DNAm classifier which performs well in discriminating current from former smokers (agnostic LASSO model AUC in external validation data: 0.744). Finally, across our DNAm models, we show evidence of enrichment for biological pathways and human phenotype ontologies relevant to smoking, such as haemostasis, molybdenum cofactor synthesis, body fatness and social behaviours, providing evidence of the generalisability of our classifiers. Conclusions: Our findings suggest that DNAm can classify ternary smoking status with close to 65% accuracy. Both the ternary smoking status classifiers and current versus former smoking status classifiers address the present lack of former smoker classification in epigenetic literature; essential if DNAm classifiers are to adequately relate to real-world populations. To improve performance further, additional focus on improving discrimination of current from former smokers is necessary.
MeSH term(s)	Adult ; Cigarette Smoking/adverse effects ; Cigarette Smoking/epidemiology ; Cigarette Smoking/genetics ; DNA Methylation/genetics ; Epigenomics/methods ; Epigenomics/statistics & numerical data ; Female ; Humans ; Male ; Middle Aged ; Smokers/classification ; Smokers/statistics & numerical data
Language	English
Publishing date	2021-11-17
Publishing country	Germany
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2553921-8
ISSN	1868-7083 ; 1868-7075
ISSN (online)	1868-7083
ISSN	1868-7075
DOI	10.1186/s13148-021-01191-6
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Article ; Online: Epigenetic profiling of social communication trajectories and co-occurring mental health problems: a prospective, methylome-wide association study.

Rijlaarsdam, Jolien / Cecil, Charlotte A M / Relton, Caroline L / Barker, Edward D

Development and psychopathology

2021 Volume 34, Issue 3, Page(s) 854–863

Abstract: While previous studies suggest that both genetic and environmental factors play an important role in the development of autism-related traits, little is known about potential biological mechanisms underlying these associations. Using data from the Avon ... ...

Abstract	While previous studies suggest that both genetic and environmental factors play an important role in the development of autism-related traits, little is known about potential biological mechanisms underlying these associations. Using data from the Avon Longitudinal Study of Parents and Children (ALSPAC), we examined prospective associations between DNA methylation (DNAm:
MeSH term(s)	Adolescent ; Child ; Communication ; DNA Methylation ; Epigenesis, Genetic ; Epigenome ; Humans ; Infant, Newborn ; Longitudinal Studies ; Mental Health
Language	English
Publishing date	2021-01-26
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	1036173-x
ISSN	1469-2198 ; 0954-5794
ISSN (online)	1469-2198
ISSN	0954-5794
DOI	10.1017/S0954579420001662
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Zs.A 2601: Show issues

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Article ; Online: Harnessing Whole Genome Polygenic Risk Scores to Stratify Individuals Based on Cardiometabolic Risk Factors and Biomarkers at Age 10 in the Lifecourse-Brief Report.

Richardson, Tom G / O'Nunain, Katie / Relton, Caroline L / Davey Smith, George

Arteriosclerosis, thrombosis, and vascular biology

2022 Volume 42, Issue 3, Page(s) 362–365

Abstract: Background: In this study, we investigated the capability of polygenic risk scores to stratify a cohort of young individuals into risk deciles based on 10 different cardiovascular traits and circulating biomarkers.: Methods: We first conducted large- ... ...

Abstract	Background: In this study, we investigated the capability of polygenic risk scores to stratify a cohort of young individuals into risk deciles based on 10 different cardiovascular traits and circulating biomarkers. Methods: We first conducted large-scale genome-wide association studies using data on adults (mean age 56.5 years) enrolled in the UK Biobank study (n=393 193 to n=461 460). Traits and biomarkers analyzed were body mass index, systolic blood pressure, diastolic blood pressure, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides, apolipoprotein B, apolipoprotein A-I, C-reactive protein and vitamin D. Findings were then leveraged to build whole genome polygenic risk scores in participants from the Avon Longitudinal Study of Parents and Children (mean age, 9.9 years) which were used to stratify this cohort into deciles in turn and analyzed against their respective traits. Results: For each of the 10 different traits assessed, we found strong evidence of an incremental trend across deciles (all Conclusions: Although the use of polygenic prediction in a clinical setting may currently be premature, our findings suggest they are becoming increasingly powerful as a means of predicting complex trait variation at an early stage in the lifecourse.
MeSH term(s)	Biological Specimen Banks ; Biomarkers/blood ; Cardiometabolic Risk Factors ; Child ; Cohort Studies ; Female ; Genetic Variation ; Genome-Wide Association Study ; Humans ; Linear Models ; Linkage Disequilibrium ; Longitudinal Studies ; Male ; Multifactorial Inheritance ; United Kingdom
Chemical Substances	Biomarkers
Language	English
Publishing date	2022-01-20
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1221433-4
ISSN	1524-4636 ; 1079-5642
ISSN (online)	1524-4636
ISSN	1079-5642
DOI	10.1161/ATVBAHA.121.316650
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Article ; Online: DNA methylation-based predictors of health: applications and statistical considerations.

Yousefi, Paul D / Suderman, Matthew / Langdon, Ryan / Whitehurst, Oliver / Davey Smith, George / Relton, Caroline L

Nature reviews. Genetics

2022 Volume 23, Issue 6, Page(s) 369–383

Abstract: DNA methylation data have become a valuable source of information for biomarker development, because, unlike static genetic risk estimates, DNA methylation varies dynamically in relation to diverse exogenous and endogenous factors, including ... ...

Abstract	DNA methylation data have become a valuable source of information for biomarker development, because, unlike static genetic risk estimates, DNA methylation varies dynamically in relation to diverse exogenous and endogenous factors, including environmental risk factors and complex disease pathology. Reliable methods for genome-wide measurement at scale have led to the proliferation of epigenome-wide association studies and subsequently to the development of DNA methylation-based predictors across a wide range of health-related applications, from the identification of risk factors or exposures, such as age and smoking, to early detection of disease or progression in cancer, cardiovascular and neurological disease. This Review evaluates the progress of existing DNA methylation-based predictors, including the contribution of machine learning techniques, and assesses the uptake of key statistical best practices needed to ensure their reliable performance, such as data-driven feature selection, elimination of data leakage in performance estimates and use of generalizable, adequately powered training samples.
MeSH term(s)	Biomarkers ; DNA Methylation ; Epigenesis, Genetic ; Genome-Wide Association Study ; Humans ; Neoplasms/genetics
Chemical Substances	Biomarkers
Language	English
Publishing date	2022-03-18
Publishing country	England
Document type	Journal Article ; Review ; Research Support, Non-U.S. Gov't
ZDB-ID	2035157-4
ISSN	1471-0064 ; 1471-0056
ISSN (online)	1471-0064
ISSN	1471-0056
DOI	10.1038/s41576-022-00465-w
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Zs.A 5474: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (2.OG) ab Jg. 2022: Lesesaal (EG)
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Article ; Online: Vitamin D Levels and Risk of Juvenile Idiopathic Arthritis: A Mendelian Randomization Study.

Clarke, Sarah L N / Mitchell, Ruth E / Sharp, Gemma C / Ramanan, Athimalaipet V / Relton, Caroline L

Arthritis care & research

2022 Volume 75, Issue 3, Page(s) 674–681

Abstract: Objectives: Observational studies report mixed findings regarding the association between vitamin D and juvenile idiopathic arthritis (JIA) incidence or activity; however, such studies are susceptible to considerable bias. Because low vitamin D levels ... ...

Abstract	Objectives: Observational studies report mixed findings regarding the association between vitamin D and juvenile idiopathic arthritis (JIA) incidence or activity; however, such studies are susceptible to considerable bias. Because low vitamin D levels are common within the general population and easily corrected, there is potential public health benefit in identifying a causal association between vitamin D insufficiency and JIA incidence. To limit bias due to confounding and reverse causation, we examined the causal effect of the major circulating form of vitamin D, 25-hydroxy vitamin D (25-[OH]D), on JIA incidence using Mendelian randomization (MR). Methods: In this 2-sample MR analysis, we used summary level data from the largest and most recent genome-wide association study of 25-(OH)D levels (sample size 443,734), alongside summary data from 2 JIA genetic studies (sample sizes 15,872 and 12,501), all from European populations. To test and account for potential bias due to pleiotropy, we employed multiple MR methods and sensitivity analyses. Results: We found no evidence of a causal relationship between genetically predicted 25-(OH)D levels and JIA incidence (odds ratio 1.00 [95% confidence interval (95% CI) 0.76, 1.33] per SD increase in standardized natural-log transformed 25-[OH]D levels). This estimate was consistent across all methods tested. Additionally, there was no evidence that genetically predicted JIA causally influences 25-(OH)D levels (-0.002 SD change in standardized natural-log transformed 25-[OH]D levels per doubling odds in genetically predicted JIA [95% CI -0.006, 0.002]). Conclusion: Given the lack of a causal relationship between 25-(OH)D levels and JIA, population level vitamin D supplementation is unlikely to reduce JIA incidence.
MeSH term(s)	Humans ; Arthritis, Juvenile/diagnosis ; Arthritis, Juvenile/epidemiology ; Arthritis, Juvenile/genetics ; Mendelian Randomization Analysis/methods ; Genome-Wide Association Study ; Vitamin D ; Polymorphism, Single Nucleotide
Chemical Substances	Vitamin D (1406-16-2)
Language	English
Publishing date	2022-11-26
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	645059-3
ISSN	2151-4658 ; 0893-7524 ; 2151-464X
ISSN (online)	2151-4658
ISSN	0893-7524 ; 2151-464X
DOI	10.1002/acr.24815
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Article ; Online: Epigenetics and noncommunicable diseases.

Sharp, Gemma C / Relton, Caroline L

Epigenomics

2017 Volume 9, Issue 6, Page(s) 789–791

MeSH term(s)	Epigenesis, Genetic ; Epigenomics/methods ; Genetic Predisposition to Disease ; Humans ; Noncommunicable Diseases ; Prognosis
Language	English
Publishing date	2017-05-19
Publishing country	England
Document type	Editorial
ZDB-ID	2537199-X
ISSN	1750-192X ; 1750-1911
ISSN (online)	1750-192X
ISSN	1750-1911
DOI	10.2217/epi-2017-0045
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Article ; Online: Statistical and integrative system-level analysis of DNA methylation data.

Teschendorff, Andrew E / Relton, Caroline L

Nature reviews. Genetics

2017 Volume 19, Issue 3, Page(s) 129–147

Abstract: Epigenetics plays a key role in cellular development and function. Alterations to the epigenome are thought to capture and mediate the effects of genetic and environmental risk factors on complex disease. Currently, DNA methylation is the only epigenetic ...

Abstract	Epigenetics plays a key role in cellular development and function. Alterations to the epigenome are thought to capture and mediate the effects of genetic and environmental risk factors on complex disease. Currently, DNA methylation is the only epigenetic mark that can be measured reliably and genome-wide in large numbers of samples. This Review discusses some of the key statistical challenges and algorithms associated with drawing inferences from DNA methylation data, including cell-type heterogeneity, feature selection, reverse causation and system-level analyses that require integration with other data types such as gene expression, genotype, transcription factor binding and other epigenetic information.
MeSH term(s)	Animals ; DNA Methylation ; Databases, Genetic ; Epigenesis, Genetic ; Epigenomics/methods ; Humans
Language	English
Publishing date	2017-11-13
Publishing country	England
Document type	Journal Article ; Review
ZDB-ID	2035157-4
ISSN	1471-0064 ; 1471-0056
ISSN (online)	1471-0064
ISSN	1471-0056
DOI	10.1038/nrg.2017.86
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