323 research outputs found

    Iron and hepcidin as risk factors in atherosclerosis: what do the genes say?

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    BACKGROUND: Previous reports suggested a role for iron and hepcidin in atherosclerosis. Here, we evaluated the causality of these associations from a genetic perspective via (i) a Mendelian randomization (MR) approach, (ii) study of association of atherosclerosis-related single nucleotide polymorphisms (SNPs) with iron and hepcidin, and (iii) estimation of genomic correlations between hepcidin, iron and atherosclerosis. RESULTS: Analyses were performed in a general population sample. Iron parameters (serum iron, serum ferritin, total iron-binding capacity and transferrin saturation), serum hepcidin and genome-wide SNP data were available for N = 1,819; non-invasive measurements of atherosclerosis (NIMA), i.e., presence of plaque, intima media thickness and ankle-brachial index (ABI), for N = 549. For the MR, we used 12 iron-related SNPs that were previously identified in a genome-wide association meta-analysis on iron status, and assessed associations of individual SNPs and quartiles of a multi-SNP score with NIMA. Quartile 4 versus quartile 1 of the multi-SNP score showed directionally consistent associations with the hypothesized direction of effect for all NIMA in women, indicating that increased body iron status is a risk factor for atherosclerosis in women. We observed no single SNP associations that fit the hypothesized directions of effect between iron and NIMA, except for rs651007, associated with decreased ferritin concentration and decreased atherosclerosis risk. Two of six NIMA-related SNPs showed association with the ratio hepcidin/ferritin, suggesting that an increased hepcidin/ferritin ratio increases atherosclerosis risk. Genomic correlations were close to zero, except for hepcidin and ferritin with ABI at rest [-0.27 (SE 0.34) and -0.22 (SE 0.35), respectively] and ABI after exercise [-0.29 (SE 0.34) and -0.30 (0.35), respectively]. The negative sign indicates an increased atherosclerosis risk with increased hepcidin and ferritin concentrations. CONCLUSIONS: Our results suggest a potential causal role for hepcidin and ferritin in atherosclerosis, and may indicate that iron status is causally related to atherosclerosis in women

    Candidate Gene Sequencing of SLC11A2 and TMPRSS6 in a Family with Severe Anaemia: Common SNPs, Rare Haplotypes, No Causative Mutation

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    Contains fulltext : 110476.pdf (publisher's version ) (Open Access)BACKGROUND: Iron-refractory iron deficiency anaemia (IRIDA) is a rare disorder which was linked to mutations in two genes (SLC11A2 and TMPRSS6). Common polymorphisms within these genes were associated with serum iron levels. We identified a family of Serbian origin with asymptomatic non-consanguineous parents with three of four children presenting with IRIDA not responding to oral but to intravenous iron supplementation. After excluding all known causes responsible for iron deficiency anaemia we searched for mutations in SLC11A2 and TMPRSS6 that could explain the severe anaemia in these children. METHODOLOGY/RESULTS: We sequenced the exons and exon-intron boundaries of SLC11A2 and TMPRSS6 in all six family members. Thereby, we found seven known and fairly common SNPs, but no new mutation. We then genotyped these seven SNPs in the population-based SAPHIR study (n = 1,726) and performed genetic association analysis on iron and ferritin levels. Only two SNPs, which were top-hits from recent GWAS on iron and ferritin, exhibited an effect on iron and ferritin levels in SAPHIR. Six SAPHIR participants carrying the same TMPRSS6 genotypes and haplotype-pairs as one anaemic son showed lower ferritin and iron levels than the average. One individual exhibiting the joint SLC11A2/TMPRSS6 profile of the anaemic son had iron and ferritin levels lying below the 5(th) percentile of the population's iron and ferritin level distribution. We then checked the genotype constellations in the Nijmegen Biomedical Study (n = 1,832), but the profile of the anaemic son did not occur in this population. CONCLUSIONS: We cannot exclude a gene-gene interaction between SLC11A2 and TMPRSS6, but we can also not confirm it. As in this case candidate gene sequencing did not reveal causative rare mutations, the samples will be subjected to whole exome sequencing

    Genome-wide association study with 1000 genomes imputation identifies signals for nine sex hormone-related phenotypes.

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    Genetic factors contribute strongly to sex hormone levels, yet knowledge of the regulatory mechanisms remains incomplete. Genome-wide association studies (GWAS) have identified only a small number of loci associated with sex hormone levels, with several reproductive hormones yet to be assessed. The aim of the study was to identify novel genetic variants contributing to the regulation of sex hormones. We performed GWAS using genotypes imputed from the 1000 Genomes reference panel. The study used genotype and phenotype data from a UK twin register. We included 2913 individuals (up to 294 males) from the Twins UK study, excluding individuals receiving hormone treatment. Phenotypes were standardised for age, sex, BMI, stage of menstrual cycle and menopausal status. We tested 7,879,351 autosomal SNPs for association with levels of dehydroepiandrosterone sulphate (DHEAS), oestradiol, free androgen index (FAI), follicle-stimulating hormone (FSH), luteinizing hormone (LH), prolactin, progesterone, sex hormone-binding globulin and testosterone. Eight independent genetic variants reached genome-wide significance (P<5 × 10(-8)), with minor allele frequencies of 1.3-23.9%. Novel signals included variants for progesterone (P=7.68 × 10(-12)), oestradiol (P=1.63 × 10(-8)) and FAI (P=1.50 × 10(-8)). A genetic variant near the FSHB gene was identified which influenced both FSH (P=1.74 × 10(-8)) and LH (P=3.94 × 10(-9)) levels. A separate locus on chromosome 7 was associated with both DHEAS (P=1.82 × 10(-14)) and progesterone (P=6.09 × 10(-14)). This study highlights loci that are relevant to reproductive function and suggests overlap in the genetic basis of hormone regulation.We thank Roche Diagnostics Australia Pty Limited, Castle Hill, Australia, who provided support for the analysis of the hormones. We thank the volunteer twins for their participation in the study. Twins UK received funding support from NIHR Biomedical Research Centre (grant to Guys’ and St. Thomas’ Hospitals and King’s College London); the Chronic Disease Research Foundation; Canadian Institutes of Health Research, the Canadian Foundation for Innovation, the Fonds de la Recherche en Santé Québec, The Lady Davis Institute, the Jewish General Hospital and Ministère du Développement économique, de l'Innovation et de l'Exportation du Quebec. The Australian National Health and Medical Research Council (NHMRC project grants 1010494, 1048216), and Sir Charles Gairdner Hospital Research (grant PP2009/028). This work was supported by funding from the Wellcome Trust (092447/Z/10/Z) and Medical Research Council (MC_U106179472).This is the final version of the article. It first appeared from NPG via http://dx.doi.org/10.1038/ejhg.2015.10

    Exome chip analyses in adult attention deficit hyperactivity disorder

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    Attention-deficit/hyperactivity disorder (ADHD) is a highly heritable childhood-onset neuropsychiatric condition, often persisting into adulthood. The genetic architecture of ADHD, particularly in adults, is largely unknown. We performed an exome-wide scan of adult ADHD using the Illumina Human Exome Bead Chip, which interrogates over 250 000 common and rare variants. Participants were recruited by the International Multicenter persistent ADHD CollaboraTion (IMpACT). Statistical analyses were divided into 3 steps: (1) gene-level analysis of rare variants (minor allele frequency (MAF)<1%); (2) single marker association tests of common variants (MAFgreater than or equal to1%), with replication of the top signals; and (3) pathway analyses. In total, 9365 individuals (1846 cases and 7519 controls) were examined. Replication of the most associated common variants was attempted in 9847 individuals (2077 cases and 7770 controls) using fixed-effects inverse variance meta-analysis. With a Bonferroni-corrected significance level of 1.82E−06, our analyses of rare coding variants revealed four study-wide significant loci: 6q22.1 locus (P=4.46E−08), where NT5DC1 and COL10A1 reside; the SEC23IP locus (P=6.47E−07); the PSD locus (P=7.58E−08) and ZCCHC4 locus (P=1.79E−06). No genome-wide significant association was observed among the common variants. The strongest signal was noted at rs9325032 in PPP2R2B (odds ratio=0.81, P=1.61E−05). Taken together, our data add to the growing evidence of general signal transduction molecules (NT5DC1, PSD, SEC23IP and ZCCHC4) having an important role in the etiology of ADHD. Although the biological implications of these findings need to be further explored, they highlight the possible role of cellular communication as a potential core component in the development of both adult and childhood forms of ADHD

    Multi-trait analysis characterizes the genetics of thyroid function and identifies causal associations with clinical implications

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    To date only a fraction of the genetic footprint of thyroid function has been clarified. We report a genome-wide association study meta-analysis of thyroid function in up to 271,040 individuals of European ancestry, including reference range thyrotropin (TSH), free thyroxine (FT4), free and total triiodothyronine (T3), proxies for metabolism (T3/FT4 ratio) as well as dichotomized high and low TSH levels. We revealed 259 independent significant associations for TSH (61% novel), 85 for FT4 (67% novel), and 62 novel signals for the T3 related traits. The loci explained 14.1%, 6.0%, 9.5% and 1.1% of the total variation in TSH, FT4, total T3 and free T3 concentrations, respectively. Genetic correlations indicate that TSH associated loci reflect the thyroid function determined by free T3, whereas the FT4 associations represent the thyroid hormone metabolism. Polygenic risk score and Mendelian randomization analyses showed the effects of genetically determined variation in thyroid function on various clinical outcomes, including cardiovascular risk factors and diseases, autoimmune diseases, and cancer. In conclusion, our results improve the understanding of thyroid hormone physiology and highlight the pleiotropic effects of thyroid function on various diseases.</p

    Multi-trait analysis characterizes the genetics of thyroid function and identifies causal associations with clinical implications

    Get PDF
    To date only a fraction of the genetic footprint of thyroid function has been clarified. We report a genome-wide association study meta-analysis of thyroid function in up to 271,040 individuals of European ancestry, including reference range thyrotropin (TSH), free thyroxine (FT4), free and total triiodothyronine (T3), proxies for metabolism (T3/FT4 ratio) as well as dichotomized high and low TSH levels. We revealed 259 independent significant associations for TSH (61% novel), 85 for FT4 (67% novel), and 62 novel signals for the T3 related traits. The loci explained 14.1%, 6.0%, 9.5% and 1.1% of the total variation in TSH, FT4, total T3 and free T3 concentrations, respectively. Genetic correlations indicate that TSH associated loci reflect the thyroid function determined by free T3, whereas the FT4 associations represent the thyroid hormone metabolism. Polygenic risk score and Mendelian randomization analyses showed the effects of genetically determined variation in thyroid function on various clinical outcomes, including cardiovascular risk factors and diseases, autoimmune diseases, and cancer. In conclusion, our results improve the understanding of thyroid hormone physiology and highlight the pleiotropic effects of thyroid function on various diseases.</p
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