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- Andersson, Jonas, 1977-, et al.
(författare)
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C-reactive protein is a determinant of first-ever stroke: prospective nested case-referent study.
- 2009
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Ingår i: Cerebrovascular diseases (Basel, Switzerland). - : S. Karger AG. - 1421-9786 .- 1015-9770. ; 27:6, s. 544-51
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND AND PURPOSE: C-reactive protein (CRP) is a determinant of stroke, but there are no prospective studies on CRP and first ischemic stroke divided into etiologic subtypes. Our primary aim was to study CRP as a determinant of ischemic stroke, classified according to Trial of ORG 10172 in Acute Stroke Treatment (TOAST) criteria, and intracerebral hemorrhage (ICH) in a prospective study. A secondary aim was to study the relationship between the 1444C>T polymorphism, plasma levels of CRP and stroke. METHODS: The study was a prospective population-based case-referent study nested within the Northern Sweden Cohorts. We defined 308 cases of ischemic stroke and 61 ICH. Two controls for each case were defined from the same cohort. RESULTS: The OR for the highest (>3 mg/l) versus lowest group (<1 mg/l) of CRP was 2.58 (95% CI 1.74-3.84) for ischemic stroke and 1.63 (95% CI 0.67-3.93) for ICH. In a multivariate model including traditional risk factors, CRP remained associated with ischemic stroke (OR 2.06; 95% CI 1.29-3.29). Small-vessel disease was associated with CRP in the multivariate model (OR 3.88; 95% CI 1.10-13.7). The CRP 1444 (CC/CT vs. TT) polymorphism was associated with plasma levels of CRP but neither with ischemic stroke nor with ICH. CONCLUSIONS: This prospective population-based study shows that CRP is significantly associated with the risk of having a first ischemic stroke, especially for small-vessel disease. No significant associations were found between the CRP 1444C>T polymorphism and any stroke subtype.
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| 3. |
- Burgess, S., et al.
(författare)
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Bayesian methods for meta-analysis of causal relationships estimated using genetic instrumental variables
- 2010
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Ingår i: Statistics in medicine. - : Wiley. - 1097-0258 .- 0277-6715. ; 29:12, s. 1298-311
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Tidskriftsartikel (refereegranskat)abstract
- Genetic markers can be used as instrumental variables, in an analogous way to randomization in a clinical trial, to estimate the causal relationship between a phenotype and an outcome variable. Our purpose is to extend the existing methods for such Mendelian randomization studies to the context of multiple genetic markers measured in multiple studies, based on the analysis of individual participant data. First, for a single genetic marker in one study, we show that the usual ratio of coefficients approach can be reformulated as a regression with heterogeneous error in the explanatory variable. This can be implemented using a Bayesian approach, which is next extended to include multiple genetic markers. We then propose a hierarchical model for undertaking a meta-analysis of multiple studies, in which it is not necessary that the same genetic markers are measured in each study. This provides an overall estimate of the causal relationship between the phenotype and the outcome, and an assessment of its heterogeneity across studies. As an example, we estimate the causal relationship of blood concentrations of C-reactive protein on fibrinogen levels using data from 11 studies. These methods provide a flexible framework for efficient estimation of causal relationships derived from multiple studies. Issues discussed include weak instrument bias, analysis of binary outcome data such as disease risk, missing genetic data, and the use of haplotypes.
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| 5. |
- Sandholm, Niina, et al.
(författare)
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New susceptibility loci associated with kidney disease in type 1 diabetes
- 2012
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Ingår i: PLOS Genetics. - San Francisco, USA : Public Library of Science, PLOS. - 1553-7390 .- 1553-7404. ; 8:9, s. e1002921-
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Tidskriftsartikel (refereegranskat)abstract
- Diabetic kidney disease, or diabetic nephropathy (DN), is a major complication of diabetes and the leading cause of end-stage renal disease (ESRD) that requires dialysis treatment or kidney transplantation. In addition to the decrease in the quality of life, DN accounts for a large proportion of the excess mortality associated with type 1 diabetes (T1D). Whereas the degree of glycemia plays a pivotal role in DN, a subset of individuals with poorly controlled T1D do not develop DN. Furthermore, strong familial aggregation supports genetic susceptibility to DN. However, the genes and the molecular mechanisms behind the disease remain poorly understood, and current therapeutic strategies rarely result in reversal of DN. In the GEnetics of Nephropathy: an International Effort (GENIE) consortium, we have undertaken a meta-analysis of genomewide association studies (GWAS) of T1D DN comprising similar to 2.4 million single nucleotide polymorphisms (SNPs) imputed in 6,691 individuals. After additional genotyping of 41 top ranked SNPs representing 24 independent signals in 5,873 individuals, combined meta-analysis revealed association of two SNPs with ESRD: rs7583877 in the AFF3 gene (P = 1.2 x 10(-8)) and an intergenic SNP on chromosome 15q26 between the genes RGMA and MCTP2, rs12437854 (P = 2.0 x 10(-9)). Functional data suggest that AFF3 influences renal tubule fibrosis via the transforming growth factor-beta (TGF-beta 1) pathway. The strongest association with DN as a primary phenotype was seen for an intronic SNP in the ERBB4 gene (rs7588550, P = 2.1 x 10(-7)), a gene with type 2 diabetes DN differential expression and in the same intron as a variant with cis-eQTL expression of ERBB4. All these detected associations represent new signals in the pathogenesis of DN.
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