| 11. |
- Shungin, Dmitry, et al.
(author)
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Ranking and characterization of established BMI and lipid associated loci as candidates for gene-environment interactions
- 2017
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In: PLOS Genetics. - : Public Library Science. - 1553-7390 .- 1553-7404. ; 13:6
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Journal article (peer-reviewed)abstract
- Phenotypic variance heterogeneity across genotypes at a single nucleotide polymorphism (SNP) may reflect underlying gene-environment (GxE) or gene-gene interactions. We modeled variance heterogeneity for blood lipids and BMI in up to 44,211 participants and investigated relationships between variance effects (P-v), GxE interaction effects (with smoking and physical activity), and marginal genetic effects (P-m). Correlations between P-v and P-m were stronger for SNPs with established marginal effects (Spearman's rho = 0.401 for triglycerides, and rho = 0.236 for BMI) compared to all SNPs. When P-v and P-m were compared for all pruned SNPs, only BMI was statistically significant (Spearman's rho = 0.010). Overall, SNPs with established marginal effects were overrepresented in the nominally significant part of the P-v distribution (P-binomial < 0.05). SNPs from the top 1% of the P-m distribution for BMI had more significant P-v values (Pmann-Whitney = 1.46x10(-5)), and the odds ratio of SNPs with nominally significant (< 0.05) P-m and P-v was 1.33 (95% CI: 1.12, 1.57) for BMI. Moreover, BMI SNPs with nominally significant GxE interaction P-values (Pint < 0.05) were enriched with nominally significant P-v values (P-binomial = 8.63x10(-9) and 8.52x10(-7) for SNP x smoking and SNP x physical activity, respectively). We conclude that some loci with strong marginal effects may be good candidates for GxE, and variance-based prioritization can be used to identify them.
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| 12. |
- Cardona, Alexia, et al.
(author)
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Epigenome-wide association study of incident type 2 diabetes in a British population : EPIC-Norfolk study
- 2019
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In: Diabetes. - : American Diabetes Association. - 0012-1797 .- 1939-327X. ; 68:12, s. 2315-2326
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Journal article (peer-reviewed)abstract
- Epigenetic changes may contribute substantially to risks of diseases of aging. Previous studies reported seven methylation variable positions (MVPs) robustly associated with incident type 2 diabetes mellitus (T2DM). However, their causal roles in T2DM are unclear. In an incident T2DM case-cohort study nested within the populationbased European Prospective Investigation into Cancer and Nutrition (EPIC)-Norfolk cohort, we used whole blood DNA collected at baseline, up to 11 years before T2DM onset, to investigate the role of methylation in the etiology of T2DM. We identified 15 novel MVPs with robust associations with incident T2DM and robustly confirmed three MVPs identified previously (near to TXNIP, ABCG1, and SREBF1). All 18 MVPs showed directionally consistent associations with incident and prevalent T2DM in independent studies. Further conditional analyses suggested that the identified epigenetic signals appear related to T2DM via glucose and obesityrelated pathways acting before the collection of baseline samples.We integrated genome-wide genetic data to identify methylation-associated quantitative trait loci robustly associated with 16 of the 18 MVPs and found one MVP, cg00574958 at CPT1A, with a possible direct causal role in T2DM. None of the implicated genes were previously highlighted by genetic association studies, suggesting that DNA methylation studies may reveal novel biological mechanisms involved in tissue responses to glycemia.
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| 13. |
- Jensen, Rikke Beck, et al.
(author)
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Genetic Markers of Insulin Sensitivity and Insulin Secretion Are Associated With Spontaneous Postnatal Growth and Response to Growth Hormone Treatment in Short SGA Children: the North European SGA Study (NESGAS)
- 2015
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In: Journal of Clinical Endocrinology and Metabolism. - : The Endocrine Society. - 1945-7197 .- 0021-972X. ; 100:3, s. 503-507
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Journal article (peer-reviewed)abstract
- Purpose: The wide heterogeneity in the early growth and metabolism of children born small for gestational age (SGA), both before and during GH therapy, may reflect common genetic variations related to insulin secretion or sensitivity. Method: Combined multiallele single nucleotide polymorphism scores with known associations with insulin sensitivity or insulin secretion were analyzed for their relationships with spontaneous postnatal growth and first-year responses to GH therapy in 96 short SGA children. Results: The insulin sensitivity allele score (GS-InSens) was positively associated with spontaneous postnatal weight gain (regression coefficient [B]: 0.12 SD scores per allele; 95% confidence interval [CI], 0.01-0.23; P = .03) and also in response to GH therapy with first-year height velocity (B: 0.18 cm/y per allele; 95% CI, 0.02-0.35; P = .03) and change in IGF-1 (B: 0.17 SD scores per allele; 95% CI, 0.00-0.32; P = .03). The association with first-year height velocity was independent of reported predictors of response to GH therapy (adjusted P = .04). The insulin secretion allele score (GS-InSec) was positively associated with spontaneous postnatal height gain (B: 0.15; 95% CI, 0.01-0.30; P = .03) and disposition index both before (B: 0.02; 95% CI, 0.00-0.04; P = .04) and after 1 year of GH therapy (B: 0.03; 95% CI, 0.01-0.05; P = .002), but not with growth and IGF-1 responses to GH therapy. Neither of the allele scores was associated with size at birth. Conclusion: Genetic allele scores indicative of insulin sensitivity and insulin secretion were associated with spontaneous postnatal growth and responses to GH therapy in short SGA children. Further pharmacogenetic studies may support the rationale for adjuvant therapies by informing the mechanisms of treatment response.
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| 14. |
- Lunetta, Kathryn L., et al.
(author)
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Rare coding variants and X-linked loci associated with age at menarche
- 2015
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In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 6
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Journal article (peer-reviewed)abstract
- More than 100 loci have been identified for age at menarche by genome-wide association studies; however, collectively these explain only similar to 3% of the trait variance. Here we test two overlooked sources of variation in 192,974 European ancestry women: low-frequency proteincoding variants and X-chromosome variants. Five missense/nonsense variants (in ALMS1/LAMB2/TNRC6A/TACR3/PRKAG1) are associated with age at menarche (minor allele frequencies 0.08-4.6%; effect sizes 0.08-1.25 years per allele; P<5 x 10(-8)). In addition, we identify common X-chromosome loci at IGSF1 (rs762080, P = 9.4 x 10(-13)) and FAAH2 (rs5914101, P = 4.9 x 10(-10)). Highlighted genes implicate cellular energy homeostasis, post-transcriptional gene silencing and fatty-acid amide signalling. A frequently reported mutation in TACR3 for idiopathic hypogonatrophic hypogonadism (p.W275X) is associated with 1.25-year-later menarche (P = 2.8 x 10(-11)), illustrating the utility of population studies to estimate the penetrance of reportedly pathogenic mutations. Collectively, these novel variants explain similar to 0.5% variance, indicating that these overlooked sources of variation do not substantially explain the 'missing heritability' of this complex trait.
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| 15. |
- Perrier, Flavie, et al.
(author)
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Identifying and correcting epigenetics measurements for systematic sources of variation
- 2018
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In: Clinical Epigenetics. - London : BioMed Central. - 1868-7083 .- 1868-7075. ; 10
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Journal article (peer-reviewed)abstract
- Background: Methylation measures quantified by microarray techniques can be affected by systematic variation due to the technical processing of samples, which may compromise the accuracy of the measurement process and contribute to bias the estimate of the association under investigation. The quantification of the contribution of the systematic source of variation is challenging in datasets characterized by hundreds of thousands of features.In this study, we introduce a method previously developed for the analysis of metabolomics data to evaluate the performance of existing normalizing techniques to correct for unwanted variation. Illumina Infinium HumanMethylation450K was used to acquire methylation levels in over 421,000 CpG sites for 902 study participants of a case-control study on breast cancer nested within the EPIC cohort. The principal component partial R-square (PC-PR2) analysis was used to identify and quantify the variability attributable to potential systematic sources of variation. Three correcting techniques, namely ComBat, surrogate variables analysis (SVA) and a linear regression model to compute residuals were applied. The impact of each correcting method on the association between smoking status and DNA methylation levels was evaluated, and results were compared with findings from a large meta-analysis.Results: A sizeable proportion of systematic variability due to variables expressing 'batch' and 'sample position' within 'chip' was identified, with values of the partial R-2 statistics equal to 9.5 and 11.4% of total variation, respectively. After application of ComBat or the residuals' methods, the contribution was 1.3 and 0.2%, respectively. The SVA technique resulted in a reduced variability due to 'batch' (1.3%) and 'sample position' (0.6%), and in a diminished variability attributable to 'chip' within a batch (0.9%). After ComBat or the residuals' corrections, a larger number of significant sites (k = 600 and k = 427, respectively) were associated to smoking status than the SVA correction (k = 96).Conclusions: The three correction methods removed systematic variation in DNA methylation data, as assessed by the PC-PR2, which lent itself as a useful tool to explore variability in large dimension data. SVA produced more conservative findings than ComBat in the association between smoking and DNA methylation.
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| 16. |
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| 17. |
- Thompson, Deborah J, et al.
(author)
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Genetic predisposition to mosaic Y chromosome loss in blood
- 2019
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In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 575, s. 652-657
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Journal article (peer-reviewed)abstract
- Mosaic loss of chromosome Y (LOY) in circulating white blood cells is the most common form of clonal mosaicism1-5, yet our knowledge of the causes and consequences of this is limited. Here, using a computational approach, we estimate that 20% of the male population represented in the UK Biobank study (n = 205,011) has detectable LOY. We identify 156 autosomal genetic determinants of LOY, which we replicate in 757,114 men of European and Japanese ancestry. These loci highlight genes that are involved in cell-cycle regulation and cancer susceptibility, as well as somatic drivers of tumour growth and targets of cancer therapy. We demonstrate that genetic susceptibility to LOY is associated with non-haematological effects on health in both men and women, which supports the hypothesis that clonal haematopoiesis is a biomarker of genomic instability in other tissues. Single-cell RNA sequencing identifies dysregulated expression of autosomal genes in leukocytes with LOY and provides insights into why clonal expansion of these cells may occur. Collectively, these data highlight the value of studying clonal mosaicism to uncover fundamental mechanisms that underlie cancer and other ageing-related diseases.
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