| 41. |
- Varga, Tibor V., et al.
(författare)
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Association is not prediction : A landscape of confused reporting in diabetes – A systematic review
- 2020
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Ingår i: Diabetes Research and Clinical Practice. - : Elsevier BV. - 0168-8227. ; 170
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Tidskriftsartikel (refereegranskat)abstract
- Aims: Appropriate analysis of big data is fundamental to precision medicine. While statistical analyses often uncover numerous associations, associations themselves do not convey predictive value. Confusion between association and prediction harms clinicians, scientists, and ultimately, the patients. We analyzed published papers in the field of diabetes that refer to “prediction” in their titles. We assessed whether these articles report metrics relevant to prediction. Methods: A systematic search was undertaken using NCBI PubMed. Articles with the terms “diabetes” and “prediction” were selected. All abstracts of original research articles, within the field of diabetes epidemiology, were searched for metrics pertaining to predictive statistics. Simulated data was generated to visually convey the differences between association and prediction. Results: The search-term yielded 2,182 results. After discarding non-relevant articles, 1,910 abstracts were evaluated. Of these, 39% (n = 745) reported metrics of predictive statistics, while 61% (n = 1,165) did not. The top reported metrics of prediction were ROC AUC, sensitivity and specificity. Using the simulated data, we demonstrated that biomarkers with large effect sizes and low P values can still offer poor discriminative utility. Conclusions: We demonstrate a landscape of confused reporting within the field of diabetes epidemiology where the term “prediction” is often incorrectly used to refer to association statistics. We propose guidelines for future reporting, and two major routes forward in terms of main analytic procedures and research goals: the explanatory route, which contributes to precision medicine, and the prediction route which contributes to personalized medicine.
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| 42. |
- Varga, Tibor V., et al.
(författare)
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Comprehensive Analysis of Established Dyslipidemia-Associated Loci in the Diabetes Prevention Program
- 2016
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Ingår i: Circulation. - : Lippincott Williams & Wilkins. - 1942-325X .- 1942-3268. ; 9:6, s. 495-503
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Tidskriftsartikel (refereegranskat)abstract
- Background: We assessed whether 234 established dyslipidemia-associated loci modify the effects of metformin treatment and lifestyle intervention (versus placebo control) on lipid and lipid subfraction levels in the Diabetes Prevention Program randomized controlled trial. Methods and Results: We tested gene treatment interactions in relation to baseline-adjusted follow-up blood lipid concentrations (high-density lipoprotein [HDL] and low-density lipoprotein-cholesterol, total cholesterol, and triglycerides) and lipoprotein subfraction particle concentrations and size in 2993 participants with pre-diabetes. Of the previously reported single-nucleotide polymorphism associations, 32.5% replicated at P<0.05 with baseline lipid traits. Trait-specific genetic risk scores were robustly associated (3x10(-4)>P>1.1x10(-16)) with their respective baseline traits for all but 2 traits. Lifestyle modified the effect of the genetic risk score for large HDL particle numbers, such that each risk allele of the genetic risk scores was associated with lower concentrations of large HDL particles at follow-up in the lifestyle arm (beta=-0.11 mu mol/L per genetic risk scores risk allele; 95% confidence interval, -0.188 to -0.033; P=5x10(-3); P-interaction=1x10(-3) for lifestyle versus placebo), but not in the metformin or placebo arms (P>0.05). In the lifestyle arm, participants with high genetic risk had more favorable or similar trait levels at 1-year compared with participants at lower genetic risk at baseline for 17 of the 20 traits. Conclusions: Improvements in large HDL particle concentrations conferred by lifestyle may be diminished by genetic factors. Lifestyle intervention, however, was successful in offsetting unfavorable genetic loading for most lipid traits.
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| 43. |
- Varga, Tibor V, et al.
(författare)
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Lipidomic profiles, lipid trajectories and clinical biomarkers in female elite endurance athletes
- 2020
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 10, s. 1-9
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Tidskriftsartikel (refereegranskat)abstract
- We assessed whether blood lipid metabolites and their changes associate with various cardiometabolic, endocrine, bone- and energy-related comorbidities of Relative Energy Deficiency in Sport (RED-S) in female elite endurance athletes. Thirty-eight Scandinavian female elite athletes underwent a day-long exercise test. Five blood samples were obtained during the day - at fasting state and before and after two standardized exercise tests. Clinical biomarkers were assessed at fasting state, while untargeted lipidomics was undertaken using all blood samples. Linear and logistic regression was used to assess associations between lipidomic features and clinical biomarkers. Overrepresentations of findings with P < 0.05 from these association tests were assessed using Fisher's exact tests. Self-organizing maps and a trajectory clustering algorithm were utilized to identify informative clusters in the population. Twenty associations PFDR < 0.05 were detected between lipidomic features and clinical biomarkers. Notably, cortisol demonstrated an overrepresentation of associations with P < 0.05 compared to other traits (PFisher = 1.9×10-14). Mean lipid trajectories were created for 201 named features for the cohort and subsequently by stratifying participants by their energy availability and menstrual dysfunction status. This exploratory analysis of lipid trajectories indicates that participants with menstrual dysfunction might have decreased adaptive response to exercise interventions.
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| 44. |
- Varga, Tibor V., et al.
(författare)
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Novel genetic loci associated with long-term deterioration in blood lipid concentrations and coronary artery disease in European adults
- 2017
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Ingår i: International Journal of Epidemiology. - : Oxford University Press (OUP). - 0300-5771 .- 1464-3685. ; 46:4, s. 1211-1222
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Tidskriftsartikel (refereegranskat)abstract
- Background: Cross-sectional genome-wide association studies have identified hundreds of loci associated with blood lipids and related cardiovascular traits, but few genetic association studies have focused on long-term changes in blood lipids.Methods: Participants from the GLACIER Study (N-max = 3492) were genotyped with the MetaboChip array, from which 29 387 SNPs (single nucleotide polymorphisms;replication, fine-mapping regions and wildcard SNPs for lipid traits) were extracted for association tests with 10-year change in total cholesterol (Delta TC) and triglycerides (Delta TG). Four additional prospective cohort studies (MDC, PIVUS, ULSAM, MRC Ely; N-max = 8263 participants) were used for replication. We conducted an in silico look-up for association with coronary artery disease (CAD) in the Coronary ARtery DIsease Genome-wide Replication and Meta-analysis (CARDIoGRAMplusC4D) Consortium (N similar to 190 000) and functional annotation for the top ranking variants.Results: In total, 956 variants were associated (P < 0.01) with either Delta TC or Delta TG in GLACIER. In GLACIER, chr19:50121999 at APOE was associated with Delta TG and multiple SNPs in the APOA1/A4/C3/A5 region at genome-wide significance (P < 5 x 10(-8)), whereas variants in four loci, DOCK7, BRE, SYNE1 and KCNIP1, reached study-wide significance (P < 1.7 x 10(-6)). The rs7412 variant at APOE was associated with DTC in GLACIER (P < 1.7 x 10(-6)). In pooled analyses of all cohorts, 139 SNPs at six and five loci were associated with Delta TC and for Delta TG, respectively (P < 10(-3)). Of these, a variant at CAPN3 (P = 1.2 x 10(-4)), multiple variants at HPR (P-min = 1.5 x 10(-6)) and a variant at SIX5 (P = 1.9 x 10(-4)) showed evidence for association with CAD.Conclusions: We identified seven novel genomic regions associated with long-term changes in blood lipids, of which three also raise CAD risk.
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| 45. |
- Varga, Tibor V., et al.
(författare)
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Organizational Justice and Long-term Metabolic Trajectories : A 25-Year Follow-up of the Whitehall II Cohort
- 2022
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Ingår i: Journal of Clinical Endocrinology and Metabolism. - : The Endocrine Society. - 0021-972X .- 1945-7197. ; 107:2, s. 398-409
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Tidskriftsartikel (refereegranskat)abstract
- Context: Organizational justice has been linked to lower risk of several chronic conditions among employees, but less is known about the long-term mechanisms underlying this risk reduction.Objective: To assess whether self-reported organizational justice is associated with individual and composite long-term metabolic trajectories.Design: Twenty-five-year follow-up of the Whitehall II prospective cohort study.Setting: Middle-aged public servants from the United Kingdom.Participants: Data on 8182 participants were used.Main Outcome Measures: Levels of 11 anthropometric, glycemic, lipid, and blood pressure biomarkers were measured at 5 timepoints (1991–2013). We used generalized estimating equations and group-based trajectory modeling to investigate the relationship between organizational justice and biomarker trajectories.Results: High vs low organizational justice were associated with lower waist (−1.7 cm) and hip (−1 cm) circumference, body mass index (−0.6 kg/m2), triglycerides (−1.07 mmol/L), and fasting insulin (−1.08 µIU/mL) trajectories. Two latent metabolic trajectory clusters were identified: a high- and a low-risk cluster. High organizational justice (vs low) were associated with belonging to the low-risk cluster (pooled odds ratio = 1.47). The low-risk cluster demonstrated lower baseline levels of most biomarkers and better glycemic control, whereas the high-risk cluster showed higher baseline levels of most biomarkers, glycemic deterioration, but also greater improvements in lipid levels over time.Conclusions: People with high organizational justice had more favorable long-term cardiometabolic biomarker patterns than those with low organizational justice, indicating a potential mechanism contributing to the lower risk of chronic diseases in the first group. Further intervention studies are warranted to determine whether improvement of organizational justice might improve long-term health.
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| 46. |
- Varga, Tibor V., et al.
(författare)
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Predictive utilities of lipid traits, lipoprotein subfractions and other risk factors for incident diabetes : A machine learning approach in the Diabetes Prevention Program
- 2021
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Ingår i: BMJ Open Diabetes Research and Care. - : BMJ. - 2052-4897. ; 9:1
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Tidskriftsartikel (refereegranskat)abstract
- Introduction Although various lipid and non-lipid analytes measured by nuclear magnetic resonance (NMR) spectroscopy have been associated with type 2 diabetes, a structured comparison of the ability of NMR-derived biomarkers and standard lipids to predict individual diabetes risk has not been undertaken in larger studies nor among individuals at high risk of diabetes. Research design and methods Cumulative discriminative utilities of various groups of biomarkers including NMR lipoproteins, related non-lipid biomarkers, standard lipids, and demographic and glycemic traits were compared for short-term (3.2 years) and long-term (15 years) diabetes development in the Diabetes Prevention Program, a multiethnic, placebo-controlled, randomized controlled trial of individuals with pre-diabetes in the USA (N=2590). Logistic regression, Cox proportional hazards model and six different hyperparameter-tuned machine learning algorithms were compared. The Matthews Correlation Coefficient (MCC) was used as the primary measure of discriminative utility. Results Models with baseline NMR analytes and their changes did not improve the discriminative utility of simpler models including standard lipids or demographic and glycemic traits. Across all algorithms, models with baseline 2-hour glucose performed the best (max MCC=0.36). Sophisticated machine learning algorithms performed similarly to logistic regression in this study. Conclusions NMR lipoproteins and related non-lipid biomarkers were associated but did not augment discrimination of diabetes risk beyond traditional diabetes risk factors except for 2-hour glucose. Machine learning algorithms provided no meaningful improvement for discrimination compared with logistic regression, which suggests a lack of influential latent interactions among the analytes assessed in this study. Trial registration number Diabetes Prevention Program: NCT00004992; Diabetes Prevention Program Outcomes Study: NCT00038727.
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| 47. |
- Webb, Thomas R., et al.
(författare)
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Systematic Evaluation of Pleiotropy Identifies 6 Further Loci Associated With Coronary Artery Disease
- 2017
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Ingår i: Journal of the American College of Cardiology. - : Elsevier BV. - 0735-1097 .- 1558-3597. ; 69:7, s. 823-836
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND Genome-wide association studies have so far identified 56 loci associated with risk of coronary artery disease (CAD). Many CAD loci show pleiotropy; that is, they are also associated with other diseases or traits.OBJECTIVES This study sought to systematically test if genetic variants identified for non-CAD diseases/traits also associate with CAD and to undertake a comprehensive analysis of the extent of pleiotropy of all CAD loci.METHODS In discovery analyses involving 42,335 CAD cases and 78,240 control subjects we tested the association of 29,383 common (minor allele frequency >5%) single nucleotide polymorphisms available on the exome array, which included a substantial proportion of known or suspected single nucleotide polymorphisms associated with common diseases or traits as of 2011. Suggestive association signals were replicated in an additional 30,533 cases and 42,530 control subjects. To evaluate pleiotropy, we tested CAD loci for association with cardiovascular risk factors (lipid traits, blood pressure phenotypes, body mass index, diabetes, and smoking behavior), as well as with other diseases/traits through interrogation of currently available genome-wide association study catalogs.RESULTS We identified 6 new loci associated with CAD at genome-wide significance: on 2q37 (KCNJ13-GIGYF2), 6p21 (C2), 11p15 (MRVI1-CTR9), 12q13 (LRP1), 12q24 (SCARB1), and 16q13 (CETP). Risk allele frequencies ranged from 0.15 to 0.86, and odds ratio per copy of the risk allele ranged from 1.04 to 1.09. Of 62 new and known CAD loci, 24 (38.7%) showed statistical association with a traditional cardiovascular risk factor, with some showing multiple associations, and 29 (47%) showed associations at p < 1 x 10(-4) with a range of other diseases/traits.CONCLUSIONS We identified 6 loci associated with CAD at genome-wide significance. Several CAD loci show substantial pleiotropy, which may help us understand the mechanisms by which these loci affect CAD risk.
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| 48. |
- Zheng, Yan, et al.
(författare)
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Mendelian randomization analysis does not support causal associations of birth weight with hypertension risk and blood pressure in adulthood
- 2020
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Ingår i: European Journal of Epidemiology. - : Springer Science and Business Media LLC. - 1573-7284 .- 0393-2990. ; 35:7, s. 685-697
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Tidskriftsartikel (refereegranskat)abstract
- Epidemiology studies suggested that low birthweight was associated with a higher risk of hypertension in later life. However, little is known about the causality of such associations. In our study, we evaluated the causal association of low birthweight with adulthood hypertension following a standard analytic protocol using the study-level data of 183,433 participants from 60 studies (CHARGE-BIG consortium), as well as that with blood pressure using publicly available summary-level genome-wide association data from EGG consortium of 153,781 participants, ICBP consortium and UK Biobank cohort together of 757,601 participants. We used seven SNPs as the instrumental variable in the study-level analysis and 47 SNPs in the summary-level analysis. In the study-level analyses, decreased birthweight was associated with a higher risk of hypertension in adults (the odds ratio per 1 standard deviation (SD) lower birthweight, 1.22; 95% CI 1.16 to 1.28), while no association was found between genetically instrumented birthweight and hypertension risk (instrumental odds ratio for causal effect per 1 SD lower birthweight, 0.97; 95% CI 0.68 to 1.41). Such results were consistent with that from the summary-level analyses, where the genetically determined low birthweight was not associated with blood pressure measurements either. One SD lower genetically determined birthweight was not associated with systolic blood pressure (β = − 0.76, 95% CI − 2.45 to 1.08 mmHg), 0.06 mmHg lower diastolic blood pressure (β = − 0.06, 95% CI − 0.93 to 0.87 mmHg), or pulse pressure (β = − 0.65, 95% CI − 1.38 to 0.69 mmHg, all p > 0.05). Our findings suggest that the inverse association of birthweight with hypertension risk from observational studies was not supported by large Mendelian randomization analyses. © 2020, Springer Nature B.V.
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