| 41. |
- Carland, Corinne, et al.
(author)
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Proteomic analysis of 92 circulating proteins and their effects in cardiometabolic diseases
- 2023
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In: Clinical Proteomics. - : BMC. - 1542-6416 .- 1559-0275. ; 20:1
-
Journal article (peer-reviewed)abstract
- Background: Human plasma contains a wide variety of circulating proteins. These proteins can be important clinical biomarkers in disease and also possible drug targets. Large scale genomics studies of circulating proteins can identify genetic variants that lead to relative protein abundance.Methods: We conducted a meta-analysis on genome-wide association studies of autosomal chromosomes in 22,997 individuals of primarily European ancestry across 12 cohorts to identify protein quantitative trait loci (pQTL) for 92 cardiometabolic associated plasma proteins.Results: We identified 503 (337 cis and 166 trans) conditionally independent pQTLs, including several novel variants not reported in the literature. We conducted a sex-stratified analysis and found that 118 (23.5%) of pQTLs demonstrated heterogeneity between sexes. The direction of effect was preserved but there were differences in effect size and significance. Additionally, we annotate trans-pQTLs with nearest genes and report plausible biological relationships. Using Mendelian randomization, we identified causal associations for 18 proteins across 19 phenotypes, of which 10 have additional genetic colocalization evidence. We highlight proteins associated with a constellation of cardiometabolic traits including angiopoietin-related protein 7 (ANGPTL7) and Semaphorin 3F (SEMA3F).Conclusion: Through large-scale analysis of protein quantitative trait loci, we provide a comprehensive overview of common variants associated with plasma proteins. We highlight possible biological relationships which may serve as a basis for further investigation into possible causal roles in cardiometabolic diseases.
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| 42. |
- Dam, Veerle, et al.
(author)
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Association of menopausal characteristics and risk of coronary heart disease : A pan-European case-cohort analysis
- 2019
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In: International Journal of Epidemiology. - : Oxford University Press. - 0300-5771 .- 1464-3685. ; 48:4, s. 1275-1285
-
Journal article (peer-reviewed)abstract
- Background: Earlier age at menopause has been associated with increased risk of coronary heart disease (CHD), but the shape of association and role of established cardiovascular risk factors remain unclear. Therefore, we examined the associations between menopausal characteristics and CHD risk; the shape of the association between age at menopause and CHD risk; and the extent to which these associations are explained by established cardiovascular risk factors.Methods: We used data from EPIC-CVD, a case-cohort study, which includes data from 23 centres from 10 European countries. We included only women, of whom 10 880 comprise the randomly selected sub-cohort, supplemented with 4522 cases outside the sub-cohort. We conducted Prentice-weighted Cox proportional hazards regressions with age as the underlying time scale, stratified by country and adjusted for relevant confounders.Results: After confounder and intermediate adjustment, post-menopausal women were not at higher CHD risk compared with pre-menopausal women. Among post-menopausal women, earlier menopause was linearly associated with higher CHD risk [HRconfounder and intermediate adjusted per-year decrease = 1.02, 95% confidence interval (CI) = 1.01-1.03, p = 0.001]. Women with a surgical menopause were at higher risk of CHD compared with those with natural menopause (HRconfounder-adjusted = 1.25, 95% CI = 1.10-1.42, p < 0.001), but this attenuated after additional adjustment for age at menopause and intermediates (HR = 1.12, 95% CI = 0.96-1.29, p = 0.15). A proportion of the association was explained by cardiovascular risk factors.Conclusions: Earlier and surgical menopause were associated with higher CHD risk. These associations could partially be explained by differences in conventional cardiovascular risk factors. These women might benefit from close monitoring of cardiovascular risk factors and disease.
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| 43. |
- Dam, Veerle, et al.
(author)
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Genetically Determined Reproductive Aging and Coronary Heart Disease : A Bidirectional 2-sample Mendelian Randomization
- 2022
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In: Journal of Clinical Endocrinology and Metabolism. - : The Endocrine Society. - 0021-972X .- 1945-7197. ; 107:7, s. E2952-E2961
-
Journal article (peer-reviewed)abstract
- Background: Accelerated reproductive aging, in women indicated by early natural menopause, is associated with increased coronary heart disease (CHD) risk in observational studies. Conversely, an adverse CHD risk profile has been suggested to accelerate menopause. Objectives: To study the direction and evidence for causality of the relationship between reproductive aging and (non-)fatal CHD and CHD risk factors in a bidirectional Mendelian randomization (MR) approach, using age at natural menopause (ANM) genetic variants as a measure for genetically determined reproductive aging in women. We also studied the association of these variants with CHD risk (factors) in men. Design: Two-sample MR, using both cohort data as well as summary statistics, with 4 methods: simple and weighted median-based, standard inverse-variance weighted (IVW) regression, and MR-Egger regression. Participants: Data from EPIC-CVD and summary statistics from UK Biobank and publicly available genome-wide association studies were pooled for the different analyses. Main Outcome Measures: CHD, CHD risk factors, and ANM. Results: Across different methods of MR, no association was found between genetically determined reproductive aging and CHD risk in women (relative risk estimateIVW = 0.99; 95% confidence interval (CI), 0.97-1.01), or any of the CHD risk factors. Similarly, no associations were found in men. Neither did the reversed analyses show evidence for an association between CHD (risk factors) and reproductive aging. Conclusion: Genetically determined reproductive aging is not causally associated with CHD risk (factors) in women, nor were the genetic variants associated in men. We found no evidence for a reverse association in a combined sample of women and men.
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| 44. |
- de Vries, Paul S., et al.
(author)
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Multiancestry Genome-Wide Association Study of Lipid Levels Incorporating Gene-Alcohol Interactions
- 2019
-
In: American Journal of Epidemiology. - : Oxford University Press. - 0002-9262 .- 1476-6256. ; 188:6, s. 1033-1054
-
Journal article (peer-reviewed)abstract
- A person's lipid profile is influenced by genetic variants and alcohol consumption, but the contribution of interactions between these exposures has not been studied. We therefore incorporated gene-alcohol interactions into a multiancestry genome-wide association study of levels of high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides. We included 45 studies in stage 1 (genome-wide discovery) and 66 studies in stage 2 (focused follow-up), for a total of 394,584 individuals from 5 ancestry groups. Analyses covered the period July 2014-November 2017. Genetic main effects and interaction effects were jointly assessed by means of a 2-degrees-of-freedom (df) test, and a 1-df test was used to assess the interaction effects alone. Variants at 495 loci were at least suggestively associated (P < 1 x 10(-6)) with lipid levels in stage 1 and were evaluated in stage 2, followed by combined analyses of stage 1 and stage 2. In the combined analysis of stages 1 and 2, a total of 147 independent loci were associated with lipid levels at P < 5 x 10(-8) using 2-df tests, of which 18 were novel. No genome-wide-significant associations were found testing the interaction effect alone. The novel loci included several genes (proprotein convertase subtilisin/kexin type 5 (PCSK5), vascular endothelial growth factor B (VEGFB), and apolipoprotein B mRNA editing enzyme, catalytic polypeptide 1 (APOBEC1) complementation factor (A1CF)) that have a putative role in lipid metabolism on the basis of existing evidence from cellular and experimental models.
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| 45. |
- Desai, Trishna A., et al.
(author)
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Identifying proteomic risk factors for overall, aggressive, and early onset prostate cancer using Mendelian Randomisation and tumour spatial transcriptomics
- 2024
-
In: EBioMedicine. - : Elsevier. - 2352-3964. ; 105
-
Journal article (peer-reviewed)abstract
- Background Understanding the role of circulating proteins in prostate cancer risk can reveal key biological pathways and identify novel targets for cancer prevention. Methods We investigated the association of 2002 genetically predicted circulating protein levels with risk of prostate cancer overall, and of aggressive and early onset disease, using cis- pQTL Mendelian randomisation (MR) and colocalisation. Findings for proteins with support from both MR, after correction for multiple -testing, and colocalisation were replicated using two independent cancer GWAS, one of European and one of African ancestry. Proteins with evidence of prostate -speci fi c tissue expression were additionally investigated using spatial transcriptomic data in prostate tumour tissue to assess their role in tumour aggressiveness. Finally, we mapped risk proteins to drug and ongoing clinical trials targets. Findings We identi fi ed 20 proteins genetically linked to prostate cancer risk (14 for overall [8 speci fi c], 7 for aggressive [3 speci fi c], and 8 for early onset disease [2 speci fi c]), of which the majority replicated where data were available. Among these were proteins associated with aggressive disease, such as PPA2 [Odds Ratio (OR) per 1 SD increment = 2.13, 95% CI: 1.54 - 2.93], PYY [OR = 1.87, 95% CI: 1.43 - 2.44] and PRSS3 [OR = 0.80, 95% CI: 0.73 - 0.89], and those associated with early onset disease, including EHPB1 [OR = 2.89, 95% CI: 1.99 - 4.21], POGLUT3 [OR = 0.76, 95% CI: 0.67 - 0.86] and TPM3 [OR = 0.47, 95% CI: 0.34 - 0.64]. We con fi rmed an inverse association of MSMB with prostate cancer overall [OR = 0.81, 95% CI: 0.80 - 0.82], and also found an inverse association with both aggressive [OR = 0.84, 95% CI: 0.82 - 0.86] and early onset disease [OR = 0.71, 95% CI: 0.68 - 0.74]. Using spatial transcriptomics data, we identi fi ed MSMB as the genome-wide top -most predictive gene to distinguish benign regions from high grade cancer regions that comparatively had fi ve -fold lower MSMB expression. Additionally, ten proteins that were associated with prostate cancer risk also mapped to existing therapeutic interventions. Interpretation Our fi ndings emphasise the importance of proteomics for improving our understanding of prostate cancer aetiology and of opportunities for novel therapeutic interventions. Additionally, we demonstrate the added bene fi t of in-depth functional analyses to triangulate the role of risk proteins in the clinical aggressiveness of prostate tumours. Using these integrated methods, we identify a subset of risk proteins associated with aggressive and early onset disease as priorities for investigation for the future prevention and treatment of prostate cancer.
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| 46. |
- Dimas, Antigone S, et al.
(author)
-
Impact of type 2 diabetes susceptibility variants on quantitative glycemic traits reveals mechanistic heterogeneity.
- 2014
-
In: Diabetes. - : American Diabetes Association. - 1939-327X .- 0012-1797. ; 63:6, s. 2158-2171
-
Journal article (peer-reviewed)abstract
- Patients with established type 2 diabetes display both beta-cell dysfunction and insulin resistance. To define fundamental processes leading to the diabetic state, we examined the relationship between type 2 diabetes risk variants at 37 established susceptibility loci and indices of proinsulin processing, insulin secretion and insulin sensitivity. We included data from up to 58,614 non-diabetic subjects with basal measures, and 17,327 with dynamic measures. We employed additive genetic models with adjustment for sex, age and BMI, followed by fixed-effects inverse variance meta-analyses. Cluster analyses grouped risk loci into five major categories based on their relationship to these continuous glycemic phenotypes. The first cluster (PPARG, KLF14, IRS1, GCKR) was characterized by primary effects on insulin sensitivity. The second (MTNR1B, GCK) featured risk alleles associated with reduced insulin secretion and fasting hyperglycemia. ARAP1 constituted a third cluster characterized by defects in insulin processing. A fourth cluster (including TCF7L2, SLC30A8, HHEX/IDE, CDKAL1, CDKN2A/2B) was defined by loci influencing insulin processing and secretion without detectable change in fasting glucose. The final group contained twenty risk loci with no clear-cut associations to continuous glycemic traits. By assembling extensive data on continuous glycemic traits, we have exposed the diverse mechanisms whereby type 2 diabetes risk variants impact disease predisposition.
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| 47. |
- Do, Ron, et al.
(author)
-
Common variants associated with plasma triglycerides and risk for coronary artery disease
- 2013
-
In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 45:11, s. 1345-
-
Journal article (peer-reviewed)abstract
- Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiological studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids (P < 5 x 10(-8) for each) to examine the role of triglycerides in risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglyceride levels, and we show that the direction and magnitude of the associations with both traits are factors in determining CAD risk. Second, we consider loci with only a strong association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol (HDL-C) levels, the strength of a polymorphism's effect on triglyceride levels is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD.
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| 48. |
- Drogan, Dagmar, et al.
(author)
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Untargeted Metabolic Profiling Identifies Altered Serum Metabolites of Type 2 Diabetes Mellitus in a Prospective, Nested Case Control Study
- 2015
-
In: Clinical Chemistry. - : Oxford University Press (OUP). - 0009-9147 .- 1530-8561. ; 61:3, s. 487-497
-
Journal article (peer-reviewed)abstract
- BACKGROUND:Application of metabolite profiling could expand the etiological knowledge of type 2 diabetes mellitus (T2D). However, few prospective studies apply broad untargeted metabolite profiling to reveal the comprehensive metabolic alterations preceding the onset of T2D. METHODS: We applied untargeted metabolite profiling in serum samples obtained from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort comprising 300 individuals who developed T2D after a median follow-up time of 6 years and 300 matched controls. For that purpose, we used ultraperformance LC-MS with a protocol specifically designed for large-scale metabolomics studies with regard to robustness and repeatability. After multivariate classification to select metabolites with the strongest contribution to disease classification, we applied multivariable-adjusted conditional logistic regression to assess the association of these metabolites with T2D.RESULTS: Among several alterations in lipid metabolism, there was an inverse association with T2D for metabolites chemically annotated as lysophosphatidylcholine(dm16:0) and phosphatidylcholine(O-20:0/O-20:0). Hexose sugars were positively associated with T2D, whereas higher concentrations of a sugar alcohol and a deoxyhexose sugar reduced the odds of diabetes by approximately 60% and 70%, respectively. Furthermore, there was suggestive evidence for a positive association of the circulating purine nucleotide isopentenyladenosine-5' -monophosphate with incident T2D.CONCLUSIONS: This study constitutes one of the largest metabolite profiling approaches of T2D biomarkers in a prospective study population. The findings might help generate new hypotheses about diabetes etiology and develop further targeted studies of a smaller number of potentially important metabolites. (C) 2014 American Association for Clinical Chemistry
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| 49. |
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| 50. |
- Elks, Cathy E., et al.
(author)
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Age at Menarche and Type 2 Diabetes Risk The EPIC-InterAct study
- 2013
-
In: Diabetes Care. - : American Diabetes Association. - 1935-5548 .- 0149-5992. ; 36:11, s. 3526-3534
-
Journal article (peer-reviewed)abstract
- OBJECTIVEYounger age at menarche, a marker of pubertal timing in girls, is associated with higher risk of later type 2 diabetes. We aimed to confirm this association and to examine whether it is explained by adiposity.RESEARCH DESIGN AND METHODSThe prospective European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct case-cohort study consists of 12,403 incident type 2 diabetes cases and a stratified subcohort of 16,154 individuals from 26 research centers across eight European countries. We tested the association between age at menarche and incident type 2 diabetes using Prentice-weighted Cox regression in 15,168 women (n = 5,995 cases). Models were adjusted in a sequential manner for potential confounding and mediating factors, including adult BMI.RESULTSMean menarcheal age ranged from 12.6 to 13.6 years across InterAct countries. Each year later menarche was associated with 0.32 kg/m(2) lower adult BMI. Women in the earliest menarche quintile (8-11 years, n = 2,418) had 70% higher incidence of type 2 diabetes compared with those in the middle quintile (13 years, n = 3,634), adjusting for age at recruitment, research center, and a range of lifestyle and reproductive factors (hazard ratio [HR], 1.70; 95% CI, 1.49-1.94; P < 0.001). Adjustment for BMI partially attenuated this association (HR, 1.42; 95% CI, 1.18-1.71; P < 0.001). Later menarche beyond the median age was not protective against type 2 diabetes.CONCLUSIONSWomen with history of early menarche have higher risk of type 2 diabetes in adulthood. Less than half of this association appears to be mediated by higher adult BMI, suggesting that early pubertal development also may directly increase type 2 diabetes risk.
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