| 1. |
- Quell, Jan D., et al.
(författare)
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Automated pathway and reaction prediction facilitates in silico identification of unknown metabolites in human cohort studies
- 2017
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Ingår i: Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences. - : Elsevier BV. - 1570-0232 .- 1873-376X. ; 1071, s. 58-67
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Tidskriftsartikel (refereegranskat)abstract
- Identification of metabolites in non-targeted metabolomics continues to be a bottleneck in metabolomics studies in large human cohorts. Unidentified metabolites frequently emerge in the results of association studies linking metabolite levels to, for example, clinical phenotypes. For further analyses these unknown metabolites must be identified. Current approaches utilize chemical information, such as spectral details and fragmentation characteristics to determine components of unknown metabolites. Here, we propose a systems biology model exploiting the internal correlation structure of metabolite levels in combination with existing biochemical and genetic information to characterize properties of unknown molecules.Levels of 758 metabolites (439 known, 319 unknown) in human blood samples of 2279 subjects were measured using a non-targeted metabolomics platform (LC-MS and GC-MS). We reconstructed the structure of biochemical pathways that are imprinted in these metabolomics data by building an empirical network model based on 1040 significant partial correlations between metabolites. We further added associations of these metabolites to 134 genes from genome-wide association studies as well as reactions and functional relations to genes from the public database Recon 2 to the network model. From the local neighborhood in the network, we were able to predict the pathway annotation of 180 unknown metabolites. Furthermore, we classified 100 pairs of known and unknown and 45 pairs of unknown metabolites to 21 types of reactions based on their mass differences. As a proof of concept, we then looked further into the special case of predicted dehydrogenation reactions leading us to the selection of 39 candidate molecules for 5 unknown metabolites. Finally, we could verify 2 of those candidates by applying LC-MS analyses of commercially available candidate substances. The formerly unknown metabolites X-13891 and X-13069 were shown to be 2-dodecendioic acid and 9-tetradecenoic acid, respectively.Our data-driven approach based on measured metabolite levels and genetic associations as well as information from public resources can be used alone or together with methods utilizing spectral patterns as a complementary, automated and powerful method to characterize unknown metabolites.
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| 2. |
- Sandholm, Niina, et al.
(författare)
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The genetic landscape of renal complications in type 1 diabetes
- 2017
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Ingår i: Journal of the American Society of Nephrology. - 1046-6673. ; 28:2, s. 557-574
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Tidskriftsartikel (refereegranskat)abstract
- Diabetes is the leading cause of ESRD. Despite evidence for a substantial heritability of diabetic kidney disease, efforts to identify genetic susceptibility variants have had limited success. We extended previous efforts in three dimensions, examining a more comprehensive set of genetic variants in larger numbers of subjects with type 1 diabetes characterized for a wider range of cross-sectional diabetic kidney disease phenotypes. In 2843 subjects, we estimated that the heritability of diabetic kidney disease was 35% (P=6.4310-3). Genome-wide association analysis and replication in 12,540 individuals identified no single variants reaching stringent levels of significance and, despite excellent power, provided little independent confirmation of previously published associatedvariants.Whole-exome sequencing in 997 subjects failed to identify any large-effect coding alleles of lower frequency influencing the risk of diabetic kidney disease. However, sets of alleles increasing body mass index (P=2.2310-5) and the risk of type 2 diabetes (P=6.1310-4) associated with the risk of diabetic kidney disease.Wealso found genome-wide genetic correlation between diabetic kidney disease and failure at smoking cessation (P=1.1310-4). Pathway analysis implicated ascorbate and aldarate metabolism (P=9.0310-6), and pentose and glucuronate interconversions (P=3.0310-6) in pathogenesis of diabetic kidney disease. These data provide further evidence for the role of genetic factors influencing diabetic kidney disease in those with type 1 diabetes and highlight some key pathways that may be responsible. Altogether these results reveal important biology behind the major cause of kidney disease.
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| 3. |
- Colombo, Marco, et al.
(författare)
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Serum kidney injury molecule 1 and β2-microglobulin perform as well as larger biomarker panels for prediction of rapid decline in renal function in type 2 diabetes
- 2019
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Ingår i: Diabetologia. - : Springer Science and Business Media LLC. - 0012-186X .- 1432-0428. ; 62:1, s. 156-168
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Tidskriftsartikel (refereegranskat)abstract
- Aims/hypothesis: As part of the Surrogate Markers for Micro- and Macrovascular Hard Endpoints for Innovative Diabetes Tools (SUMMIT) programme we previously reported that large panels of biomarkers derived from three analytical platforms maximised prediction of progression of renal decline in type 2 diabetes. Here, we hypothesised that smaller (n ≤ 5), platform-specific combinations of biomarkers selected from these larger panels might achieve similar prediction performance when tested in three additional type 2 diabetes cohorts. Methods: We used 657 serum samples, held under differing storage conditions, from the Scania Diabetes Registry (SDR) and Genetics of Diabetes Audit and Research Tayside (GoDARTS), and a further 183 nested case–control sample set from the Collaborative Atorvastatin in Diabetes Study (CARDS). We analysed 42 biomarkers measured on the SDR and GoDARTS samples by a variety of methods including standard ELISA, multiplexed ELISA (Luminex) and mass spectrometry. The subset of 21 Luminex biomarkers was also measured on the CARDS samples. We used the event definition of loss of >20% of baseline eGFR during follow-up from a baseline eGFR of 30–75 ml min−1 [1.73 m]−2. A total of 403 individuals experienced an event during a median follow-up of 7 years. We used discrete-time logistic regression models with tenfold cross-validation to assess association of biomarker panels with loss of kidney function. Results: Twelve biomarkers showed significant association with eGFR decline adjusted for covariates in one or more of the sample sets when evaluated singly. Kidney injury molecule 1 (KIM-1) and β2-microglobulin (B2M) showed the most consistent effects, with standardised odds ratios for progression of at least 1.4 (p < 0.0003) in all cohorts. A combination of B2M and KIM-1 added to clinical covariates, including baseline eGFR and albuminuria, modestly improved prediction, increasing the area under the curve in the SDR, Go-DARTS and CARDS by 0.079, 0.073 and 0.239, respectively. Neither the inclusion of additional Luminex biomarkers on top of B2M and KIM-1 nor a sparse mass spectrometry panel, nor the larger multiplatform panels previously identified, consistently improved prediction further across all validation sets. Conclusions/interpretation: Serum KIM-1 and B2M independently improve prediction of renal decline from an eGFR of 30–75 ml min−1 [1.73 m]−2 in type 2 diabetes beyond clinical factors and prior eGFR and are robust to varying sample storage conditions. Larger panels of biomarkers did not improve prediction beyond these two biomarkers.
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| 4. |
- Looker, Helen C, et al.
(författare)
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Biomarkers of rapid chronic kidney disease progression in type 2 diabetes.
- 2015
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Ingår i: Kidney International. - : Elsevier BV. - 1523-1755 .- 0085-2538. ; 88:4, s. 888-896
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Tidskriftsartikel (refereegranskat)abstract
- Here we evaluated the performance of a large set of serum biomarkers for the prediction of rapid progression of chronic kidney disease (CKD) in patients with type 2 diabetes. We used a case-control design nested within a prospective cohort of patients with baseline eGFR 30-60 ml/min per 1.73 m(2). Within a 3.5-year period of Go-DARTS study patients, 154 had over a 40% eGFR decline and 153 controls maintained over 95% of baseline eGFR. A total of 207 serum biomarkers were measured and logistic regression was used with forward selection to choose a subset that were maximized on top of clinical variables including age, gender, hemoglobin A1c, eGFR, and albuminuria. Nested cross-validation determined the best number of biomarkers to retain and evaluate for predictive performance. Ultimately, 30 biomarkers showed significant associations with rapid progression and adjusted for clinical characteristics. A panel of 14 biomarkers increased the area under the ROC curve from 0.706 (clinical data alone) to 0.868. Biomarkers selected included fibroblast growth factor-21, the symmetric to asymmetric dimethylarginine ratio, β2-microglobulin, C16-acylcarnitine, and kidney injury molecule-1. Use of more extensive clinical data including prebaseline eGFR slope improved prediction but to a lesser extent than biomarkers (area under the ROC curve of 0.793). Thus we identified several novel associations of biomarkers with CKD progression and the utility of a small panel of biomarkers to improve prediction.Kidney International advance online publication, 22 July 2015; doi:10.1038/ki.2015.199.
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| 5. |
- Looker, Helen C., et al.
(författare)
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Protein biomarkers for the prediction of cardiovascular disease in type 2 diabetes
- 2015
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Ingår i: Diabetologia. - : Springer Science and Business Media LLC. - 1432-0428 .- 0012-186X. ; 58:6, s. 1363-1371
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Tidskriftsartikel (refereegranskat)abstract
- Aims/hypothesis We selected the most informative protein biomarkers for the prediction of incident cardiovascular disease (CVD) in people with type 2 diabetes. Methods In this nested case-control study we measured 42 candidate CVD biomarkers in 1,123 incident CVD cases and 1,187 controls with type 2 diabetes selected from five European centres. Combinations of biomarkers were selected using cross-validated logistic regression models. Model prediction was assessed using the area under the receiver operating characteristic curve (AUROC). Results Sixteen biomarkers showed univariate associations with incident CVD. The most predictive subset selected by forward selection methods contained six biomarkers: N-terminal pro-B-type natriuretic peptide (OR 1.69 per 1 SD, 95% CI 1.47, 1.95), high-sensitivity troponin T (OR 1.29, 95% CI 1.11, 1.51), IL-6 (OR 1.13, 95% CI 1.02, 1.25), IL-15 (OR 1.15, 95% CI 1.01, 1.31), apolipoprotein C-III (OR 0.79, 95% CI 0.70, 0.88) and soluble receptor for AGE (OR 0.84, 95% CI 0.76, 0.94). The prediction of CVD beyond clinical covariates improved from an AUROC of 0.66 to 0.72 (AUROC for Framingham Risk Score covariates 0.59). In addition to the biomarkers, the most important clinical covariates for improving prediction beyond the Framingham covariates were estimated GFR, insulin therapy and HbA(1c). Conclusions/interpretation We identified six protein biomarkers that in combination with clinical covariates improved the prediction of our model beyond the Framingham Score covariates. Biomarkers can contribute to improved prediction of CVD in diabetes but clinical data including measures of renal function and diabetes-specific factors not included in the Framingham Risk Score are also needed.
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| 6. |
- Willeit, Peter, et al.
(författare)
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Baseline and on-statin treatment lipoprotein(a) levels for prediction of cardiovascular events: individual patient-data meta-analysis of statin outcome trials
- 2018
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Ingår i: The Lancet. - : ELSEVIER SCIENCE INC. - 0140-6736 .- 1474-547X. ; 392:10155, s. 1311-1320
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Tidskriftsartikel (refereegranskat)abstract
- Background Elevated lipoprotein(a) is a genetic risk factor for cardiovascular disease in general population studies. However, its contribution to risk for cardiovascular events in patients with established cardiovascular disease or on statin therapy is uncertain. Methods Patient-level data from seven randomised, placebo-controlled, statin outcomes trials were collated and harmonised to calculate hazard ratios (HRs) for cardiovascular events, defined as fatal or non-fatal coronary heart disease, stroke, or revascularisation procedures. HRs for cardiovascular events were estimated within each trial across predefined lipoprotein(a) groups (15 to amp;lt;30 mg/dL, 30 to amp;lt;50 mg/dL, and amp;gt;= 50 mg/dL, vs amp;lt;15 mg/dL), before pooling estimates using multivariate random-effects meta-analysis. Findings Analyses included data for 29 069 patients with repeat lipoprotein(a) measurements (mean age 62 years [SD 8]; 8064 [28%] women; 5751 events during 95 576 person-years at risk). Initiation of statin therapy reduced LDL cholesterol (mean change -39% [95% CI -43 to -35]) without a significant change in lipoprotein(a). Associations of baseline and on-statin treatment lipoprotein(a) with cardiovascular disease risk were approximately linear, with increased risk at lipoprotein(a) values of 30 mg/dL or greater for baseline lipoprotein(a) and 50 mg/dL or greater for on-statin lipoprotein(a). For baseline lipoprotein(a), HRs adjusted for age and sex (vs amp;lt;15 mg/dL) were 1.04 (95% CI 0.91-1.18) for 15 mg/dL to less than 30 mg/dL, 1.11 (1.00-1.22) for 30 mg/dL to less than 50 mg/dL, and 1.31 (1.08-1.58) for 50 mg/dL or higher; respective HRs for on-statin lipoprotein(a) were 0.94 (0.81-1.10), 1.06 (0. 94-1.21), and 1.43 (1.15-1.76). HRs were almost identical after further adjustment for previous cardiovascular disease, diabetes, smoking, systolic blood pressure, LDL cholesterol, and HDL cholesterol. The association of on-statin lipoprotein(a) with cardiovascular disease risk was stronger than for on-placebo lipoprotein(a) (interaction p=0.010) and was more pronounced at younger ages (interaction p=0.008) without effect-modification by any other patient-level or study-level characteristics. Interpretation In this individual-patient data meta-analysis of statin-treated patients, elevated baseline and on-statin lipoprotein(a) showed an independent approximately linear relation with cardiovascular disease risk. This study provides a rationale for testing the lipoprotein(a) lowering hypothesis in cardiovascular disease outcomes trials. Copyright (C) 2018 Elsevier Ltd. All rights reserved.
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| 7. |
- Gonçalves, Isabel, et al.
(författare)
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Association between renin and atherosclerotic burden in subjects with and without type 2 diabetes
- 2016
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Ingår i: BMC Cardiovascular Disorders. - : Springer Science and Business Media LLC. - 1471-2261. ; 16:1, s. 1-10
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Tidskriftsartikel (refereegranskat)abstract
- Background: Activation of the renin-angiotensin-aldosterone-system (RAAS) has been proposed to contribute to development of vascular complications in type 2 diabetes (T2D). The aim of the present study was to determine if plasma renin levels are associated with the severity of vascular changes in subjects with and without T2D. Methods: Renin was analyzed by the Proximity Extension Assay in subjects with (n = 985) and without (n = 515) T2D participating in the SUMMIT (SUrrogate markers for Micro- and Macro-vascular hard endpoints for Innovative diabetes Tools) study and in 205 carotid endarterectomy patients. Vascular changes were assessed by determining ankle-brachial pressure index (ABPI), carotid intima-media thickness (IMT), carotid plaque area, pulse wave velocity (PWV) and the reactivity hyperemia index (RHI). Results: Plasma renin was elevated in subjects with T2D and demonstrated risk factor-independent association with prevalent cardiovascular disease both in subjects with and without T2D. Renin levels increased with age, body mass index, HbA1c and correlated inversely with HDL. Subjects with T2D had more severe carotid disease, increased arterial stiffness, and impaired endothelial function. Risk factor-independent associations between renin and APBI, bulb IMT, carotid plaque area were observed in both T2D and non-T2D subjects. These associations were independent of treatment with RAAS inhibitors. Only weak associations existed between plasma renin and the expression of pro-inflammatory and fibrous components in plaques from 205 endarterectomy patients. Conclusions: Our findings provide clinical evidence for associations between systemic RAAS activation and atherosclerotic burden and suggest that this association is of particular importance in T2D.
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| 8. |
- Goncalves, Isabel, et al.
(författare)
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Elevated Plasma Levels of MMP-12 Are Associated With Atherosclerotic Burden and Symptomatic Cardiovascular Disease in Subjects With Type 2 Diabetes.
- 2015
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Ingår i: Arteriosclerosis, Thrombosis and Vascular Biology. - 1524-4636. ; 35:7, s. 1723-1731
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Tidskriftsartikel (refereegranskat)abstract
- Matrix metalloproteinases (MMPs) degrade extracellular matrix proteins and play important roles in development and tissue repair. They have also been shown to have both protective and pathogenic effects in atherosclerosis, and experimental studies have suggested that MMP-12 contributes to plaque growth and destabilization. The objective of this study was to investigate the associations between circulating MMPs, atherosclerosis burden, and incidence of cardiovascular disease with a particular focus on type 2 diabetes mellitus.
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| 9. |
- Shore, Angela C, et al.
(författare)
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Use of Vascular Assessments and Novel Biomarkers to Predict Cardiovascular Events in Type 2 Diabetes : The SUMMIT VIP Study
- 2018
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Ingår i: Diabetes Care. - : American Diabetes Association. - 1935-5548 .- 0149-5992. ; 41:10, s. 2212-2219
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: Cardiovascular disease (CVD) risk prediction represents an increasing clinical challenge in the treatment of diabetes. We used a panel of vascular imaging, functional assessments, and biomarkers reflecting different disease mechanisms to identify clinically useful markers of risk for cardiovascular (CV) events in subjects with type 2 diabetes (T2D) with or without manifest CVD.RESEARCH DESIGN AND METHODS: The study cohort consisted of 936 subjects with T2D recruited at four European centers. Carotid intima-media thickness and plaque area, ankle-brachial pressure index, arterial stiffness, endothelial function, and circulating biomarkers were analyzed at baseline, and CV events were monitored during a 3-year follow-up period.RESULTS: The CV event rate in subjects with T2D was higher in those with (n = 440) than in those without (n = 496) manifest CVD at baseline (5.53 vs. 2.15/100 life-years, P < 0.0001). New CV events in subjects with T2D with manifest CVD were associated with higher baseline levels of inflammatory biomarkers (interleukin 6, chemokine ligand 3, pentraxin 3, and hs-CRP) and endothelial mitogens (hepatocyte growth factor and vascular endothelial growth factor A), whereas CV events in subjects with T2D without manifest CVD were associated with more severe baseline atherosclerosis (median carotid plaque area 30.4 mm2 [16.1-92.2] vs. 19.5 mm2 [9.5-40.5], P = 0.01). Conventional risk factors, as well as measurements of arterial stiffness and endothelial reactivity, were not associated with CV events.CONCLUSIONS: Our observations demonstrate that markers of inflammation and endothelial stress reflect CV risk in subjects with T2D with manifest CVD, whereas the risk for CV events in subjects with T2D without manifest CVD is primarily related to the severity of atherosclerosis.
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| 10. |
- Siddiqui, Moneeza K., et al.
(författare)
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A common missense variant of LILRB5 is associated with statin intolerance and myalgia
- 2017
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Ingår i: European Heart Journal. - : Oxford University Press (OUP). - 0195-668X .- 1522-9645. ; 38:48, s. 3569-U31
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Tidskriftsartikel (refereegranskat)abstract
- Aims: A genetic variant in LILRB5 (leukocyte immunoglobulin-like receptor subfamily-B) (rs12975366: T > C: Asp247Gly) has been reported to be associated with lower creatine phosphokinase (CK) and lactate dehydrogenase (LDH) levels. Both biomarkers are released from injured muscle tissue, making this variant a potential candidate for susceptibility to muscle-related symptoms. We examined the association of this variant with statin intolerance ascertained from electronic medical records in the GoDARTS study.Methods and results: In the GoDARTS cohort, the LILRB5 Asp247 variant was associated with statin intolerance (SI) phenotypes; one defined as having raised CK and being non-adherent to therapy [odds ratio (OR) 1.81; 95% confidence interval (CI): 1.34–2.45] and the other as being intolerant to the lowest approved dose of a statin before being switched to two or more other statins (OR 1.36; 95% CI: 1.07–1.73). Those homozygous for Asp247 had increased odds of developing both definitions of intolerance. Importantly the second definition did not rely on CK elevations. These results were replicated in adjudicated cases of statin-induced myopathy in the PREDICTION-ADR consortium (OR1.48; 95% CI: 1.05–2.10) and for the development of myalgia in the JUPITER randomized clinical trial of rosuvastatin (OR1.35, 95% CI: 1.10–1.68). A meta-analysis across the studies showed a consistent association between Asp247Gly and outcomes associated with SI (OR1.34; 95% CI: 1.16–1.54).Conclusion: This study presents a novel immunogenetic factor associated with statin intolerance, an important risk factor for cardiovascular outcomes. The results suggest that true statin-induced myalgia and non-specific myalgia are distinct, with a potential role for the immune system in their development. We identify a genetic group that is more likely to be intolerant to their statins.
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