Associations of genetically determined iron status across the phenome: A mendelian randomization study
Iron is integral to many physiological processes, and variations in its levels, even within the normal range, can have implications for health. The objective of this study was to explore the broad clinical effects of varying iron status. Genome-wide association study (GWAS) summary data obtained fro...
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| Published in | PLoS medicine Vol. 16; no. 6; p. e1002833 |
|---|---|
| Main Authors | , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Public Library of Science
20.06.2019
Public Library of Science (PLoS) |
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| Online Access | Get full text |
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| Abstract | Iron is integral to many physiological processes, and variations in its levels, even within the normal range, can have implications for health. The objective of this study was to explore the broad clinical effects of varying iron status.
Genome-wide association study (GWAS) summary data obtained from 48,972 European individuals (55% female) across 19 cohorts in the Genetics of Iron Status Consortium were used to identify 3 genetic variants (rs1800562 and rs1799945 in the hemochromatosis gene [HFE] and rs855791 in the transmembrane protease serine 6 gene [TMPRSS6]) that associate with increased serum iron, ferritin, and transferrin saturation and decreased transferrin levels, thus serving as instruments for systemic iron status. Phenome-wide association study (PheWAS) of these instruments was performed on 424,439 European individuals (54% female) in the UK Biobank who were aged 40-69 years when recruited from 2006 to 2010, with their genetic data linked to Hospital Episode Statistics (HES) from April, 1995 to March, 2016. Two-sample summary data mendelian randomization (MR) analysis was performed to investigate the effect of varying iron status on outcomes across the human phenome. MR-PheWAS analysis for the 3 iron status genetic instruments was performed separately and then pooled by meta-analysis. Correction was made for testing of multiple correlated phenotypes using a 5% false discovery rate (FDR) threshold. Heterogeneity between MR estimates for different instruments was used to indicate possible bias due to effects of the genetic variants through pathways unrelated to iron status. There were 904 distinct phenotypes included in the MR-PheWAS analyses. After correcting for multiple testing, the 3 genetic instruments for systemic iron status demonstrated consistent evidence of a causal effect of higher iron status on decreasing risk of traits related to anemia (iron deficiency anemia: odds ratio [OR] scaled to a standard deviation [SD] increase in genetically determined serum iron levels 0.72, 95% confidence interval [CI] 0.64-0.81, P = 4 × 10-8) and hypercholesterolemia (hypercholesterolemia: OR 0.88, 95% CI 0.83-0.93, P = 2 × 10-5) and increasing risk of traits related to infection of the skin and related structures (cellulitis and abscess of the leg: OR 1.25, 95% CI 1.10-1.42, P = 6 × 10-4). The main limitations of this study relate to possible bias from pleiotropic effects of the considered genetic variants and misclassification of diagnoses in the HES data. Furthermore, this work only investigated participants with European ancestry, and the findings may not be applicable to other ethnic groups.
Our findings offer novel, to our knowledge, insight into previously unreported effects of iron status, highlighting a potential protective effect of higher iron status on hypercholesterolemia and a detrimental role on risk of skin and skin structure infections. Given the modifiable and variable nature of iron status, these findings warrant further investigation. |
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| AbstractList | Using Mendelian randomization, Dipender Gill and colleagues investigate the clinical implications of iron levels. Background Iron is integral to many physiological processes, and variations in its levels, even within the normal range, can have implications for health. The objective of this study was to explore the broad clinical effects of varying iron status. Methods and findings Genome-wide association study (GWAS) summary data obtained from 48,972 European individuals (55% female) across 19 cohorts in the Genetics of Iron Status Consortium were used to identify 3 genetic variants (rs1800562 and rs1799945 in the hemochromatosis gene [HFE] and rs855791 in the transmembrane protease serine 6 gene [TMPRSS6]) that associate with increased serum iron, ferritin, and transferrin saturation and decreased transferrin levels, thus serving as instruments for systemic iron status. Phenome-wide association study (PheWAS) of these instruments was performed on 424,439 European individuals (54% female) in the UK Biobank who were aged 40–69 years when recruited from 2006 to 2010, with their genetic data linked to Hospital Episode Statistics (HES) from April, 1995 to March, 2016. Two-sample summary data mendelian randomization (MR) analysis was performed to investigate the effect of varying iron status on outcomes across the human phenome. MR–PheWAS analysis for the 3 iron status genetic instruments was performed separately and then pooled by meta-analysis. Correction was made for testing of multiple correlated phenotypes using a 5% false discovery rate (FDR) threshold. Heterogeneity between MR estimates for different instruments was used to indicate possible bias due to effects of the genetic variants through pathways unrelated to iron status. There were 904 distinct phenotypes included in the MR–PheWAS analyses. After correcting for multiple testing, the 3 genetic instruments for systemic iron status demonstrated consistent evidence of a causal effect of higher iron status on decreasing risk of traits related to anemia (iron deficiency anemia: odds ratio [OR] scaled to a standard deviation [SD] increase in genetically determined serum iron levels 0.72, 95% confidence interval [CI] 0.64–0.81, P = 4 × 10−8) and hypercholesterolemia (hypercholesterolemia: OR 0.88, 95% CI 0.83–0.93, P = 2 × 10−5) and increasing risk of traits related to infection of the skin and related structures (cellulitis and abscess of the leg: OR 1.25, 95% CI 1.10–1.42, P = 6 × 10−4). The main limitations of this study relate to possible bias from pleiotropic effects of the considered genetic variants and misclassification of diagnoses in the HES data. Furthermore, this work only investigated participants with European ancestry, and the findings may not be applicable to other ethnic groups. Conclusions Our findings offer novel, to our knowledge, insight into previously unreported effects of iron status, highlighting a potential protective effect of higher iron status on hypercholesterolemia and a detrimental role on risk of skin and skin structure infections. Given the modifiable and variable nature of iron status, these findings warrant further investigation. Iron is integral to many physiological processes, and variations in its levels, even within the normal range, can have implications for health. The objective of this study was to explore the broad clinical effects of varying iron status. Genome-wide association study (GWAS) summary data obtained from 48,972 European individuals (55% female) across 19 cohorts in the Genetics of Iron Status Consortium were used to identify 3 genetic variants (rs1800562 and rs1799945 in the hemochromatosis gene [HFE] and rs855791 in the transmembrane protease serine 6 gene [TMPRSS6]) that associate with increased serum iron, ferritin, and transferrin saturation and decreased transferrin levels, thus serving as instruments for systemic iron status. Phenome-wide association study (PheWAS) of these instruments was performed on 424,439 European individuals (54% female) in the UK Biobank who were aged 40-69 years when recruited from 2006 to 2010, with their genetic data linked to Hospital Episode Statistics (HES) from April, 1995 to March, 2016. Two-sample summary data mendelian randomization (MR) analysis was performed to investigate the effect of varying iron status on outcomes across the human phenome. MR-PheWAS analysis for the 3 iron status genetic instruments was performed separately and then pooled by meta-analysis. Correction was made for testing of multiple correlated phenotypes using a 5% false discovery rate (FDR) threshold. Heterogeneity between MR estimates for different instruments was used to indicate possible bias due to effects of the genetic variants through pathways unrelated to iron status. There were 904 distinct phenotypes included in the MR-PheWAS analyses. After correcting for multiple testing, the 3 genetic instruments for systemic iron status demonstrated consistent evidence of a causal effect of higher iron status on decreasing risk of traits related to anemia (iron deficiency anemia: odds ratio [OR] scaled to a standard deviation [SD] increase in genetically determined serum iron levels 0.72, 95% confidence interval [CI] 0.64-0.81, P = 4 × 10-8) and hypercholesterolemia (hypercholesterolemia: OR 0.88, 95% CI 0.83-0.93, P = 2 × 10-5) and increasing risk of traits related to infection of the skin and related structures (cellulitis and abscess of the leg: OR 1.25, 95% CI 1.10-1.42, P = 6 × 10-4). The main limitations of this study relate to possible bias from pleiotropic effects of the considered genetic variants and misclassification of diagnoses in the HES data. Furthermore, this work only investigated participants with European ancestry, and the findings may not be applicable to other ethnic groups. Our findings offer novel, to our knowledge, insight into previously unreported effects of iron status, highlighting a potential protective effect of higher iron status on hypercholesterolemia and a detrimental role on risk of skin and skin structure infections. Given the modifiable and variable nature of iron status, these findings warrant further investigation. Iron is integral to many physiological processes, and variations in its levels, even within the normal range, can have implications for health. The objective of this study was to explore the broad clinical effects of varying iron status. Genome-wide association study (GWAS) summary data obtained from 48,972 European individuals (55% female) across 19 cohorts in the Genetics of Iron Status Consortium were used to identify 3 genetic variants (rs1800562 and rs1799945 in the hemochromatosis gene [HFE] and rs855791 in the transmembrane protease serine 6 gene [TMPRSS6]) that associate with increased serum iron, ferritin, and transferrin saturation and decreased transferrin levels, thus serving as instruments for systemic iron status. Phenome-wide association study (PheWAS) of these instruments was performed on 424,439 European individuals (54% female) in the UK Biobank who were aged 40-69 years when recruited from 2006 to 2010, with their genetic data linked to Hospital Episode Statistics (HES) from April, 1995 to March, 2016. Two-sample summary data mendelian randomization (MR) analysis was performed to investigate the effect of varying iron status on outcomes across the human phenome. MR-PheWAS analysis for the 3 iron status genetic instruments was performed separately and then pooled by meta-analysis. Correction was made for testing of multiple correlated phenotypes using a 5% false discovery rate (FDR) threshold. Heterogeneity between MR estimates for different instruments was used to indicate possible bias due to effects of the genetic variants through pathways unrelated to iron status. There were 904 distinct phenotypes included in the MR-PheWAS analyses. After correcting for multiple testing, the 3 genetic instruments for systemic iron status demonstrated consistent evidence of a causal effect of higher iron status on decreasing risk of traits related to anemia (iron deficiency anemia: odds ratio [OR] scaled to a standard deviation [SD] increase in genetically determined serum iron levels 0.72, 95% confidence interval [CI] 0.64-0.81, P = 4 x 10.sup.-8) and hypercholesterolemia (hypercholesterolemia: OR 0.88, 95% CI 0.83-0.93, P = 2 x 10.sup.-5) and increasing risk of traits related to infection of the skin and related structures (cellulitis and abscess of the leg: OR 1.25, 95% CI 1.10-1.42, P = 6 x 10.sup.-4). The main limitations of this study relate to possible bias from pleiotropic effects of the considered genetic variants and misclassification of diagnoses in the HES data. Furthermore, this work only investigated participants with European ancestry, and the findings may not be applicable to other ethnic groups. Our findings offer novel, to our knowledge, insight into previously unreported effects of iron status, highlighting a potential protective effect of higher iron status on hypercholesterolemia and a detrimental role on risk of skin and skin structure infections. Given the modifiable and variable nature of iron status, these findings warrant further investigation. BackgroundIron is integral to many physiological processes, and variations in its levels, even within the normal range, can have implications for health. The objective of this study was to explore the broad clinical effects of varying iron status.Methods and findingsGenome-wide association study (GWAS) summary data obtained from 48,972 European individuals (55% female) across 19 cohorts in the Genetics of Iron Status Consortium were used to identify 3 genetic variants (rs1800562 and rs1799945 in the hemochromatosis gene [HFE] and rs855791 in the transmembrane protease serine 6 gene [TMPRSS6]) that associate with increased serum iron, ferritin, and transferrin saturation and decreased transferrin levels, thus serving as instruments for systemic iron status. Phenome-wide association study (PheWAS) of these instruments was performed on 424,439 European individuals (54% female) in the UK Biobank who were aged 40-69 years when recruited from 2006 to 2010, with their genetic data linked to Hospital Episode Statistics (HES) from April, 1995 to March, 2016. Two-sample summary data mendelian randomization (MR) analysis was performed to investigate the effect of varying iron status on outcomes across the human phenome. MR-PheWAS analysis for the 3 iron status genetic instruments was performed separately and then pooled by meta-analysis. Correction was made for testing of multiple correlated phenotypes using a 5% false discovery rate (FDR) threshold. Heterogeneity between MR estimates for different instruments was used to indicate possible bias due to effects of the genetic variants through pathways unrelated to iron status. There were 904 distinct phenotypes included in the MR-PheWAS analyses. After correcting for multiple testing, the 3 genetic instruments for systemic iron status demonstrated consistent evidence of a causal effect of higher iron status on decreasing risk of traits related to anemia (iron deficiency anemia: odds ratio [OR] scaled to a standard deviation [SD] increase in genetically determined serum iron levels 0.72, 95% confidence interval [CI] 0.64-0.81, P = 4 × 10-8) and hypercholesterolemia (hypercholesterolemia: OR 0.88, 95% CI 0.83-0.93, P = 2 × 10-5) and increasing risk of traits related to infection of the skin and related structures (cellulitis and abscess of the leg: OR 1.25, 95% CI 1.10-1.42, P = 6 × 10-4). The main limitations of this study relate to possible bias from pleiotropic effects of the considered genetic variants and misclassification of diagnoses in the HES data. Furthermore, this work only investigated participants with European ancestry, and the findings may not be applicable to other ethnic groups.ConclusionsOur findings offer novel, to our knowledge, insight into previously unreported effects of iron status, highlighting a potential protective effect of higher iron status on hypercholesterolemia and a detrimental role on risk of skin and skin structure infections. Given the modifiable and variable nature of iron status, these findings warrant further investigation. Background Iron is integral to many physiological processes, and variations in its levels, even within the normal range, can have implications for health. The objective of this study was to explore the broad clinical effects of varying iron status. Methods and findings Genome-wide association study (GWAS) summary data obtained from 48,972 European individuals (55% female) across 19 cohorts in the Genetics of Iron Status Consortium were used to identify 3 genetic variants (rs1800562 and rs1799945 in the hemochromatosis gene [HFE] and rs855791 in the transmembrane protease serine 6 gene [TMPRSS6]) that associate with increased serum iron, ferritin, and transferrin saturation and decreased transferrin levels, thus serving as instruments for systemic iron status. Phenome-wide association study (PheWAS) of these instruments was performed on 424,439 European individuals (54% female) in the UK Biobank who were aged 40-69 years when recruited from 2006 to 2010, with their genetic data linked to Hospital Episode Statistics (HES) from April, 1995 to March, 2016. Two-sample summary data mendelian randomization (MR) analysis was performed to investigate the effect of varying iron status on outcomes across the human phenome. MR-PheWAS analysis for the 3 iron status genetic instruments was performed separately and then pooled by meta-analysis. Correction was made for testing of multiple correlated phenotypes using a 5% false discovery rate (FDR) threshold. Heterogeneity between MR estimates for different instruments was used to indicate possible bias due to effects of the genetic variants through pathways unrelated to iron status. There were 904 distinct phenotypes included in the MR-PheWAS analyses. After correcting for multiple testing, the 3 genetic instruments for systemic iron status demonstrated consistent evidence of a causal effect of higher iron status on decreasing risk of traits related to anemia (iron deficiency anemia: odds ratio [OR] scaled to a standard deviation [SD] increase in genetically determined serum iron levels 0.72, 95% confidence interval [CI] 0.64-0.81, P = 4 x 10.sup.-8) and hypercholesterolemia (hypercholesterolemia: OR 0.88, 95% CI 0.83-0.93, P = 2 x 10.sup.-5) and increasing risk of traits related to infection of the skin and related structures (cellulitis and abscess of the leg: OR 1.25, 95% CI 1.10-1.42, P = 6 x 10.sup.-4). The main limitations of this study relate to possible bias from pleiotropic effects of the considered genetic variants and misclassification of diagnoses in the HES data. Furthermore, this work only investigated participants with European ancestry, and the findings may not be applicable to other ethnic groups. Conclusions Our findings offer novel, to our knowledge, insight into previously unreported effects of iron status, highlighting a potential protective effect of higher iron status on hypercholesterolemia and a detrimental role on risk of skin and skin structure infections. Given the modifiable and variable nature of iron status, these findings warrant further investigation. Background Iron is integral to many physiological processes, and variations in its levels, even within the normal range, can have implications for health. The objective of this study was to explore the broad clinical effects of varying iron status. Methods and findings Genome-wide association study (GWAS) summary data obtained from 48,972 European individuals (55% female) across 19 cohorts in the Genetics of Iron Status Consortium were used to identify 3 genetic variants (rs1800562 and rs1799945 in the hemochromatosis gene [HFE] and rs855791 in the transmembrane protease serine 6 gene [TMPRSS6]) that associate with increased serum iron, ferritin, and transferrin saturation and decreased transferrin levels, thus serving as instruments for systemic iron status. Phenome-wide association study (PheWAS) of these instruments was performed on 424,439 European individuals (54% female) in the UK Biobank who were aged 40–69 years when recruited from 2006 to 2010, with their genetic data linked to Hospital Episode Statistics (HES) from April, 1995 to March, 2016. Two-sample summary data mendelian randomization (MR) analysis was performed to investigate the effect of varying iron status on outcomes across the human phenome. MR–PheWAS analysis for the 3 iron status genetic instruments was performed separately and then pooled by meta-analysis. Correction was made for testing of multiple correlated phenotypes using a 5% false discovery rate (FDR) threshold. Heterogeneity between MR estimates for different instruments was used to indicate possible bias due to effects of the genetic variants through pathways unrelated to iron status. There were 904 distinct phenotypes included in the MR–PheWAS analyses. After correcting for multiple testing, the 3 genetic instruments for systemic iron status demonstrated consistent evidence of a causal effect of higher iron status on decreasing risk of traits related to anemia (iron deficiency anemia: odds ratio [OR] scaled to a standard deviation [SD] increase in genetically determined serum iron levels 0.72, 95% confidence interval [CI] 0.64–0.81, P = 4 × 10−8) and hypercholesterolemia (hypercholesterolemia: OR 0.88, 95% CI 0.83–0.93, P = 2 × 10−5) and increasing risk of traits related to infection of the skin and related structures (cellulitis and abscess of the leg: OR 1.25, 95% CI 1.10–1.42, P = 6 × 10−4). The main limitations of this study relate to possible bias from pleiotropic effects of the considered genetic variants and misclassification of diagnoses in the HES data. Furthermore, this work only investigated participants with European ancestry, and the findings may not be applicable to other ethnic groups. Conclusions Our findings offer novel, to our knowledge, insight into previously unreported effects of iron status, highlighting a potential protective effect of higher iron status on hypercholesterolemia and a detrimental role on risk of skin and skin structure infections. Given the modifiable and variable nature of iron status, these findings warrant further investigation. |
| Audience | Academic |
| Author | Benyamin, Beben Laffan, Mike Elliott, Paul Monori, Grace Gill, Dipender Zhou, Ang Koskeridis, Fotios Evangelou, Evangelos Dehghan, Abbas Tzoulaki, Ioanna Walker, Ann P Tsilidis, Konstantinos K Hyppönen, Elina Moore, Luke S P |
| AuthorAffiliation | 11 Medical Research Council-Public Health England Centre for Environment, School of Public Health, Imperial College London, London, United Kingdom 13 Health Data Research UK-London, London, United Kingdom 6 Chelsea & Westminster NHS Foundation Trust, London, United Kingdom 12 UK Dementia Research Institute, Imperial College London, London, United Kingdom 8 Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece 14 Population, Policy and Practice, Great Ormond Street Institute of Child Health, University College London, London, United Kingdom University of Oxford, UNITED KINGDOM 1 Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom 9 Centre for Haematology, Imperial College London, United Kingdom 5 National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, United Kingdom 7 Imperial Biomedic |
| AuthorAffiliation_xml | – name: 13 Health Data Research UK-London, London, United Kingdom – name: 6 Chelsea & Westminster NHS Foundation Trust, London, United Kingdom – name: 2 Australian Centre for Precision Health, University of South Australia, Adelaide, Australia – name: 7 Imperial Biomedical Research Centre, Imperial College London and Imperial College NHS Healthcare Trust, London, United Kingdom – name: 3 Institute for Molecular Bioscience, University of Queensland, Brisbane, Australia – name: 9 Centre for Haematology, Imperial College London, United Kingdom – name: 4 South Australian Health and Medical Research Institute, Adelaide, Australia – name: 5 National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, United Kingdom – name: 12 UK Dementia Research Institute, Imperial College London, London, United Kingdom – name: University of Oxford, UNITED KINGDOM – name: 11 Medical Research Council-Public Health England Centre for Environment, School of Public Health, Imperial College London, London, United Kingdom – name: 8 Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece – name: 10 Population Science & Experimental Medicine, Institute of Cardiovascular Science, University College London, London, United Kingdom – name: 1 Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom – name: 14 Population, Policy and Practice, Great Ormond Street Institute of Child Health, University College London, London, United Kingdom |
| Author_xml | – sequence: 1 givenname: Dipender orcidid: 0000-0001-7312-7078 surname: Gill fullname: Gill, Dipender organization: Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom – sequence: 2 givenname: Beben orcidid: 0000-0001-5608-2293 surname: Benyamin fullname: Benyamin, Beben organization: South Australian Health and Medical Research Institute, Adelaide, Australia – sequence: 3 givenname: Luke S P orcidid: 0000-0001-7095-7922 surname: Moore fullname: Moore, Luke S P organization: Imperial Biomedical Research Centre, Imperial College London and Imperial College NHS Healthcare Trust, London, United Kingdom – sequence: 4 givenname: Grace surname: Monori fullname: Monori, Grace organization: Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom – sequence: 5 givenname: Ang surname: Zhou fullname: Zhou, Ang organization: Australian Centre for Precision Health, University of South Australia, Adelaide, Australia – sequence: 6 givenname: Fotios surname: Koskeridis fullname: Koskeridis, Fotios organization: Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece – sequence: 7 givenname: Evangelos orcidid: 0000-0002-5488-2999 surname: Evangelou fullname: Evangelou, Evangelos organization: Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece – sequence: 8 givenname: Mike surname: Laffan fullname: Laffan, Mike organization: Centre for Haematology, Imperial College London, United Kingdom – sequence: 9 givenname: Ann P surname: Walker fullname: Walker, Ann P organization: Population Science & Experimental Medicine, Institute of Cardiovascular Science, University College London, London, United Kingdom – sequence: 10 givenname: Konstantinos K orcidid: 0000-0002-8452-8472 surname: Tsilidis fullname: Tsilidis, Konstantinos K organization: Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece – sequence: 11 givenname: Abbas orcidid: 0000-0001-6403-016X surname: Dehghan fullname: Dehghan, Abbas organization: UK Dementia Research Institute, Imperial College London, London, United Kingdom – sequence: 12 givenname: Paul surname: Elliott fullname: Elliott, Paul organization: Health Data Research UK-London, London, United Kingdom – sequence: 13 givenname: Elina orcidid: 0000-0003-3670-9399 surname: Hyppönen fullname: Hyppönen, Elina organization: Population, Policy and Practice, Great Ormond Street Institute of Child Health, University College London, London, United Kingdom – sequence: 14 givenname: Ioanna orcidid: 0000-0002-4275-9328 surname: Tzoulaki fullname: Tzoulaki, Ioanna organization: Medical Research Council-Public Health England Centre for Environment, School of Public Health, Imperial College London, London, United Kingdom |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/31220083$$D View this record in MEDLINE/PubMed |
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| ContentType | Journal Article |
| Copyright | COPYRIGHT 2019 Public Library of Science 2019 Gill et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2019 Gill et al 2019 Gill et al |
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| DocumentTitleAlternate | Phenome-wide associations of iron status: Mendelian randomization study |
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| Notes | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Undefined-1 ObjectType-Feature-3 content type line 23 These authors contributed equally and are joint first authors. I have read the journal's policy and the authors of this manuscript have the following competing interests: LSPM has consulted for bioMerieux (2014), DNAelectronics (2015-2018), Dairy Crest (2017-2018), and Pfizer (2018) and has received research grants from Leo Pharma (2016) and educational support from Eumedica (2016-2017). All other authors have no competing interest to declare. |
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| References | FPN Arcanjo (ref49) 2018 WQ Wei (ref20) 2017; 12 M F Del Greco (ref27) 2015; 34 LM De-Regil (ref48) 2017; 11 FA Khan (ref34) 2007; 11 (ref36) 2018; 392 JR Thompson (ref25) 2016; 12 D Gill (ref8) 2017; 37 E Poggiali (ref51) 2012; 10 JH Cross (ref35) 2015; 5 GI Stangl (ref40) 1998; 33 I Pichler (ref9) 2013; 10 G Hemani (ref30) 2018; 7 LC Pilling (ref42) 2019; 364 AE Taylor (ref13) 2014; 13 JB Wish (ref15) 2006; 1 K Jimenez (ref46) 2015; 11 J Ma (ref55) 2012 CS Bates (ref32) 2003; 71 J Bowden (ref29) 2016; 40 JC Denny (ref12) 2013; 31 MJ Cancelo-Hidalgo (ref47) 2013; 29 (ref3) 2016; 388 S Burgess (ref28) 2017; 28 LAC Millard (ref11) 2015; 5 A. Koga (ref38) 1985; 66 MS Low (ref52) 2016; 4 MJ Brion (ref23) 2013; 42 NM Davies (ref7) 2018; 362 U Ahmed (ref41) 2012; 18 TB Assi (ref50) 2014; 12 N Abbaspour (ref1) 2014; 19 J Bowden (ref43) 2018; 187 B Benyamin (ref2) 2014; 5 NL Parrow (ref33) 2013; 81 DI Swerdlow (ref16) 2016; 45 JP Pena-Rosas (ref53) 2015 S Puig (ref14) 2005; 120 X Li (ref21) 2018; 77 A Neuberger (ref56) 2016; 2 SE Dale (ref31) 2004; 72 LM Trotti (ref57) 2012 TM Palmer (ref18) 2012; 21 MJ Machiela (ref17) 2015; 31 G Sebastiani (ref5) 2011; 3 D Gill (ref10) 2018; 49 A Verma (ref22) 2018; 19 TG DeLoughery (ref4) 2017; 101 S Padmanabhan (ref44) 2019; 34 TM Teslovich (ref39) 2010; 466 S Padhi (ref54) 2015; 350 C Sudlow (ref19) 2015; 12 Y Benjamini (ref26) 1995; 57 YC Wu (ref45) 2014; 113 S Burgess (ref24) 2013; 37 G Davey Smith (ref6) 2005; 330 C Mercado (ref37) 2015; 64 |
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| Snippet | Iron is integral to many physiological processes, and variations in its levels, even within the normal range, can have implications for health. The objective... Background Iron is integral to many physiological processes, and variations in its levels, even within the normal range, can have implications for health. The... BACKGROUNDIron is integral to many physiological processes, and variations in its levels, even within the normal range, can have implications for health. The... Using Mendelian randomization, Dipender Gill and colleagues investigate the clinical implications of iron levels. BackgroundIron is integral to many physiological processes, and variations in its levels, even within the normal range, can have implications for health. The... Background Iron is integral to many physiological processes, and variations in its levels, even within the normal range, can have implications for health. The... |
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| SubjectTerms | Adult Aged Anemia Bias Biology and Life Sciences Biomarkers - blood Biomedical research Cardiovascular disease Cellulitis Cohort Studies Councils Dementia Demographic aspects Epidemiology Female Ferritin Genes Genetic aspects Genetic diversity Genetic research Genetic variance Genetics Genome-wide association studies Genome-Wide Association Study - methods Genomes Health Health aspects Health risks Hemochromatosis Heterogeneity Humans Hygiene Hypercholesterolemia Infections Instruments (Equipment) Iron Iron (Nutrient) Iron - blood Iron deficiency Iron deficiency anemia Lipids Male Medical research Medical schools Medicine and Health Sciences Mendelian Randomization Analysis - methods Metabolism Middle Aged Minority & ethnic groups Novels Nutrient deficiency Occupational health Phenotype Phenotypes Physiological aspects Population Prospective Studies Proteases Public health Randomization Research centers Restless legs syndrome Risk factors Serine Skin Statistical analysis Transferrin Transferrins University colleges Women |
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| Title | Associations of genetically determined iron status across the phenome: A mendelian randomization study |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/31220083 https://www.proquest.com/docview/2258795998/abstract/ https://search.proquest.com/docview/2245652476 https://pubmed.ncbi.nlm.nih.gov/PMC6586257 https://doaj.org/article/0adb5bfbe3e645978d2d8bd7fe045644 http://dx.doi.org/10.1371/journal.pmed.1002833 |
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