Publications by authors named "Mervi Alanne"

The natural anti-inflammatory protein interleukin-1 receptor antagonist (IL-1Ra) inhibits the activity of IL-1 and is associated with vascular injury and metabolic disorders. We analyzed genetic and nongenetic determinants of the IL-1Ra phenotype. Fifteen haplotype-tagging single nucleotide polymorphisms (SNPs) in the IL-1α (IL1A), IL-1β (IL1B), and IL-1 receptor antagonist (IL-1RN) genes were determined in the Health 2000 survey (n = 6771) and European myocardial infarction (MI) survivors (n = 972).

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Objective: Proinflammatory cytokine IL-1beta is capable of decreasing insulin-induced glucose transport. Therefore, we hypothesized that genetic variation in the IL-1 gene family is associated with measures of glucose homeostasis and diabetes.

Design And Outcome Measures: Fifteen haplotype-tagging single-nucleotide polymorphisms in the IL-1alpha, IL-1beta, and IL-1 receptor antagonist genes were determined in a Finnish population survey (n = 6771).

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Background: Interleukin-18 is a pro-inflammatory cytokine suspected to be associated with atherosclerosis and its complications. We had previously shown that one single nucleotide polymorphism (SNP) of the IL18 gene was associated with cardiovascular disease (CVD) through an interaction with smoking. As a further step for elucidating the contribution of the IL-18 pathway to the etiology of CVD, we here investigated the association between the genetic variability of two IL-18 receptor genes, IL18R1 and IL18RAP, with the risk of developing CVD.

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Background: Cardiovascular disease (CVD) incidence, complications and burden differ markedly between women and men. Although there is variation in the distribution of lifestyle factors between the genders, they do not fully explain the differences in CVD incidence and suggest the existence of gender-specific genetic risk factors. We aimed to estimate whether the genetic risk profiles of coronary heart disease (CHD), ischemic stroke and the composite end-point of CVD differ between the genders.

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Interleukin-18 (IL-18) is a key inflammatory molecule suspected of being involved in the etiology of cardiovascular diseases (CVD). Five single nucleotide polymorphisms (SNPs) capturing the common genetic variation of the IL-18 gene (tag SNPs) were genotyped in five European prospective CVD cohorts including 1933 cases and 1938 non-cases as part of the MORGAM Project. Not a single SNP was found associated with CVD.

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The genetic background of complex diseases is proposed to consist of several low-penetrance risk loci. Addressing this complexity likely requires both large sample size and simultaneous analysis of different predisposing variants. We investigated the role of four thrombosis genes: coagulation factor V (F5), intercellular adhesion molecule 1 (ICAM1), protein C (PROC), and thrombomodulin (THBD) in cardiovascular diseases.

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Selenoprotein S (SEPS1) is a novel candidate gene involved in the regulation of inflammatory response and protection from oxidative damage. This study explored the genetic variation in the SEPS1 locus for an association with CVD as well as with quantitative phenotypes related to obesity and inflammation. We used the case-cohort design and time-to-event analysis in two separate prospectively followed population-based cohorts FINRISK 92 and 97 (n = 999 and 1,223 individuals, respectively) to study the associations of five single nucleotide polymorphisms with the risk for coronary heart disease (CHD) and ischemic stroke events.

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Upstream transcription factor 1 (USF1) is a ubiquitously expressed transcription factor controlling several critical genes in lipid and glucose metabolism. Of some 40 genes regulated by USF1, several are involved in the molecular pathogenesis of cardiovascular disease (CVD). Although the USF1 gene has been shown to have a critical role in the etiology of familial combined hyperlipidemia, which predisposes to early CVD, the gene's potential role as a risk factor for CVD events at the population level has not been established.

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The amount of available DNA is often a limiting factor in pursuing genetic analyses of large-scale population cohorts. An association between higher DNA yield from blood and several phenotypes associated with inflammatory states has recently been demonstrated, suggesting that exclusion of samples with very low DNA yield may lead to biased results in statistical analyses. Whole genome amplification (WGA) could present a solution to the DNA concentration-dependent sample selection.

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