Analysis of Genetic Variation in the GenomEUtwin Project

Silander, Kaisa; Axelsson, Tomas; Widén, Elisabeth; Dahlgren, Andreas; Palotie, Aarno; Syvänen, Ann‐Christine

doi:10.1375/136905203770326394

Cited by 12 publications

(8 citation statements)

References 25 publications

(8 reference statements)

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“…The disease status of each individual genotyped was unknown to the genotyping laboratory and samples from cases and sub-cohort individuals were distributed on the plates independently of the disease status. All genotypes were manually reviewed for various quality control aspects as previously described [36], [42], [45]. The genotyping success rate for each variant included in the analysis was >90%, with an average genotyping success of 95.3%.…”

Section: Methodsmentioning

confidence: 99%

Gender Differences in Genetic Risk Profiles for Cardiovascular Disease

et al. 2008

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BackgroundCardiovascular 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.Methodology/Principal FindingsWe studied in two Finnish population cohorts, using the case-cohort design the association between common variation in 46 candidate genes and CHD, ischemic stroke, CVD, and CVD-related quantitative risk factors. We analyzed men and women jointly and also conducted genotype-gender interaction analysis. Several allelic variants conferred disease risk for men and women jointly, including rs1801020 in coagulation factor XII (HR = 1.31 (1.08–1.60) for CVD, uncorrected p = 0.006 multiplicative model). Variant rs11673407 in the fucosyltransferase 3 gene was strongly associated with waist/hip ratio (uncorrected p = 0.00005) in joint analysis. In interaction analysis we found statistical evidence of variant-gender interaction conferring risk of CHD and CVD: rs3742264 in the carboxypeptidase B2 gene, p(interaction) = 0.009 for CHD, and rs2774279 in the upstream stimulatory factor 1 gene, p(interaction) = 0.007 for CHD and CVD, showed strong association in women but not in men, while rs2069840 in interleukin 6 gene, p(interaction) = 0.004 for CVD, showed strong association in men but not in women (uncorrected p-values). Also, two variants in the selenoprotein S gene conferred risk for ischemic stroke in women, p(interaction) = 0.003 and 0.007. Importantly, we identified a larger number of gender-specific effects for women than for men.Conclusions/SignificanceA false discovery rate analysis suggests that we may expect half of the reported findings for combined gender analysis to be true positives, while at least third of the reported genotype-gender interaction results are true positives. The asymmetry in positive findings between the genders could imply that genetic risk loci for CVD are more readily detectable in women, while for men they are more confounded by environmental/lifestyle risk factors. The possible differences in genetic risk profiles between the genders should be addressed in more detail in genetic studies of CVD, and more focus on female CVD risk is also warranted in genome-wide association studies.

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Section: Methodsmentioning

confidence: 99%

Gender Differences in Genetic Risk Profiles for Cardiovascular Disease

et al. 2008

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“…The SNP assay was designed using SpectroDESIGNER (Sequenom), and the PCR and extension reactions were done as specified by the manufacturer. Genotypes were automatically called with the SpectroCALLER software (Sequenom), and manually checked as described [43]. Part of the SNPs in stage I were genotyped in a multiplex using allele-specific primer extension on microarrays with a protocol developed in our laboratory and described by Pastinen and co-workers [44] with minor modifications.…”

Section: Methodsmentioning

confidence: 99%

PRKCA and Multiple Sclerosis: Association in Two Independent Populations

et al. 2006

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Multiple sclerosis (MS) is a chronic disease of the central nervous system responsible for a large portion of neurological disabilities in young adults. Similar to what occurs in numerous complex diseases, both unknown environmental factors and genetic predisposition are required to generate MS. We ascertained a set of 63 Finnish MS families, originating from a high-risk region of the country, to identify a susceptibility gene within the previously established 3.4-Mb region on 17q24. Initial single nucleotide polymorphism (SNP)-based association implicated PRKCA (protein kinase C alpha) gene, and this association was replicated in an independent set of 148 Finnish MS families (p = 0.0004; remaining significant after correction for multiple testing). Further, a dense set of 211 SNPs evenly covering the PRKCA gene and the flanking regions was selected from the dbSNP database and analyzed in two large, independent MS cohorts: in 211 Finnish and 554 Canadian MS families. A multipoint SNP analysis indicated linkage to PRKCA and its telomeric flanking region in both populations, and SNP haplotype and genotype combination analyses revealed an allelic variant of PRKCA, which covers the region between introns 3 and 8, to be over-represented in Finnish MS cases (odds ratio = 1.34, 95% confidence interval 1.07–1.68). A second allelic variant, covering the same region of the PRKCA gene, showed somewhat stronger evidence for association in the Canadian families (odds ratio = 1.64, 95% confidence interval 1.39–1.94). Initial functional relevance for disease predisposition was suggested by the expression analysis: The transcript levels of PRKCA showed correlation with the copy number of the Finnish and Canadian “risk” haplotypes in CD4-negative mononuclear cells of five Finnish multiplex families and in lymphoblast cell lines of 11 Centre d'Etude du Polymorphisme Humain (CEPH) individuals of European origin.

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“…1). These SNPs were genotyped using the MassARRAY ® system (Sequenom, San Diego, CA, USA) as recommended by the manufacturer with additional quality assessment steps described in more detail in Silander et al [26]. The genotyping was done in multiplexes of 1-5 SNPs using hME assays in 384-well plates.…”

Section: Methodsmentioning

confidence: 99%

Allelic variants of IL1R1gene associate with severe hand osteoarthritis

et al. 2010

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BackgroundIn search for genes predisposing to osteoarthritis (OA), several genome wide scans have provided evidence for linkage on 2q. In this study we targeted a 470 kb region on 2q11.2 presenting the locus with most evidence for linkage to severe OA of distal interphalangeal joints (DIP) in our genome wide scan families.MethodsWe genotyped 32 single nucleotide polymorphisms (SNPs) in this 470 kb region comprising six genes belonging to the interleukin 1 superfamily and monitored for association with individual SNPs and SNP haplotypes among severe familial hand OA cases (material extended from our previous linkage study; n = 134), unrelated end-stage bilateral primary knee OA cases (n = 113), and population based controls (n = 436).ResultsFour SNPs in the IL1R1 gene, mapping to a 125 kb LD block, provided evidence for association with hand OA in family-based and case-control analysis, the strongest association being with SNP rs2287047 (p-value = 0.0009).ConclusionsThis study demonstrates an association between severe hand OA and IL1R1 gene. This gene represents a highly relevant biological candidate since it encodes protein that is a known modulator of inflammatory processes associated with joint destruction and resides within a locus providing consistent evidence for linkage to hand OA. As the observed association did not fully explain the linkage obtained in the previous study, it is plausible that also other variants in this genome region predispose to hand OA.

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Analysis of Genetic Variation in the GenomEUtwin Project

Cited by 12 publications

References 25 publications

Gender Differences in Genetic Risk Profiles for Cardiovascular Disease

Gender Differences in Genetic Risk Profiles for Cardiovascular Disease

PRKCA and Multiple Sclerosis: Association in Two Independent Populations

Allelic variants of IL1R1gene associate with severe hand osteoarthritis

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