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Shore CJ, Villicaña S, El-Sayed Moustafa JS, Roberts AL, Gunn DA, Bataille V, Deloukas P, Spector TD, Small KS, Bell JT. Genetic effects on the skin methylome in healthy older twins. Am J Hum Genet 2024; 111:1932-1952. [PMID: 39137780 PMCID: PMC11393713 DOI: 10.1016/j.ajhg.2024.07.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 05/22/2024] [Accepted: 07/15/2024] [Indexed: 08/15/2024] Open
Abstract
Whole-skin DNA methylation variation has been implicated in several diseases, including melanoma, but its genetic basis has not yet been fully characterized. Using bulk skin tissue samples from 414 healthy female UK twins, we performed twin-based heritability and methylation quantitative trait loci (meQTL) analyses for >400,000 DNA methylation sites. We find that the human skin DNA methylome is on average less heritable than previously estimated in blood and other tissues (mean heritability: 10.02%). meQTL analysis identified local genetic effects influencing DNA methylation at 18.8% (76,442) of tested CpG sites, as well as 1,775 CpG sites associated with at least one distal genetic variant. As a functional follow-up, we performed skin expression QTL (eQTL) analyses in a partially overlapping sample of 604 female twins. Colocalization analysis identified over 3,500 shared genetic effects affecting thousands of CpG sites (10,067) and genes (4,475). Mediation analysis of putative colocalized gene-CpG pairs identified 114 genes with evidence for eQTL effects being mediated by DNA methylation in skin, including in genes implicating skin disease such as ALOX12 and CSPG4. We further explored the relevance of skin meQTLs to skin disease and found that skin meQTLs and CpGs under genetic influence were enriched for multiple skin-related genome-wide and epigenome-wide association signals, including for melanoma and psoriasis. Our findings give insights into the regulatory landscape of epigenomic variation in skin.
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Affiliation(s)
- Christopher J Shore
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
| | - Sergio Villicaña
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | | | - Amy L Roberts
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | | | - Veronique Bataille
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Panos Deloukas
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Kerrin S Small
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
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Roche J, Besson M, Allal F, Haffray P, Patrice P, Vandeputte M, Phocas F. GenoTriplo: A SNP genotype calling method for triploids. PLoS Comput Biol 2024; 20:e1012483. [PMID: 39316624 PMCID: PMC11452025 DOI: 10.1371/journal.pcbi.1012483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2024] [Revised: 10/04/2024] [Accepted: 09/12/2024] [Indexed: 09/26/2024] Open
Abstract
Triploidy is very useful in both aquaculture and some cultivated plants as the induced sterility helps to enhance growth and product quality, as well as acting as a barrier against the contamination of wild populations by escapees. To use genetic information from triploids for academic or breeding purposes, an efficient and robust method to genotype triploids is needed. We developed such a method for genotype calling from SNP arrays, and we implemented it in the R package named GenoTriplo. Our method requires no prior information on cluster positions and remains unaffected by shifted luminescence signals. The method relies on starting the clustering algorithm with an initial higher number of groups than expected from the ploidy level of the samples, followed by merging groups that are too close to each other to be considered as distinct genotypes. Accurate classification of SNPs is achieved through multiple thresholds of quality controls. We compared the performance of GenoTriplo with that of fitPoly, the only published method for triploid SNP genotyping with a free software access. This was assessed by comparing the genotypes generated by both methods for a dataset of 1232 triploid rainbow trout genotyped for 38,033 SNPs. The two methods were consistent for 89% of the genotypes, but for 26% of the SNPs, they exhibited a discrepancy in the number of different genotypes identified. For these SNPs, GenoTriplo had >95% concordance with fitPoly when fitPoly genotyped better. On the contrary, when GenoTriplo genotyped better, fitPoly had less than 50% concordance with GenoTriplo. GenoTriplo was more robust with less genotyping errors. It is also efficient at identifying low-frequency genotypes in the sample set. Finally, we assessed parentage assignment based on GenoTriplo genotyping and observed significant differences in mismatch rates between the best and second-best couples, indicating high confidence in the results. GenoTriplo could also be used to genotype diploids as well as individuals with higher ploidy level by adjusting a few input parameters.
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Affiliation(s)
- Julien Roche
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, Jouy-en-Josas, France
- SYSAAF (French Poultry and Aquaculture Breeders Technical Centre), Rennes, France
| | - Mathieu Besson
- SYSAAF (French Poultry and Aquaculture Breeders Technical Centre), Rennes, France
| | - François Allal
- MARBEC, University of Montpellier, CNRS, Ifremer, IRD, INRAE, Palavas-les-Flots, France
| | - Pierrick Haffray
- SYSAAF (French Poultry and Aquaculture Breeders Technical Centre), Rennes, France
| | - Pierre Patrice
- SYSAAF (French Poultry and Aquaculture Breeders Technical Centre), Rennes, France
| | - Marc Vandeputte
- MARBEC, University of Montpellier, CNRS, Ifremer, IRD, INRAE, Palavas-les-Flots, France
| | - Florence Phocas
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, Jouy-en-Josas, France
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3
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Saarinen A, Keltikangas-Järvinen L, Dobewall H, Cloninger CR, Ahola-Olli A, Lehtimäki T, Hutri-Kähönen N, Raitakari O, Rovio S, Ravaja N. Does social intolerance vary according to cognitive styles, genetic cognitive capacity, or education? Brain Behav 2022; 12:e2704. [PMID: 36047482 PMCID: PMC9480910 DOI: 10.1002/brb3.2704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 06/22/2022] [Accepted: 06/25/2022] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND Low education, low cognitive abilities, and certain cognitive styles are suggested to predispose to social intolerance and prejudices. Evidence is, however, restricted by comparatively small samples, neglect of confounding variables and genetic factors, and a narrow focus on a single sort of prejudice. We investigated the relationships of education, polygenic cognitive potential, cognitive performance, and cognitive styles with social intolerance in adulthood over a 15-year follow-up. METHODS We used data from the prospective population-based Young Finns Study (n = 960-1679). Social intolerance was evaluated with the Social Intolerance Scale in 1997, 2001, and 2011; cognitive performance with the Cambridge Neuropsychological Test Automated Battery in 2011; cognitive styles in 1997; and socioeconomic factors in 1980 (childhood) and 2011 (adulthood); and polygenic cognitive potential was calculated based on genome-wide association studies. RESULTS We found that nonrational thinking, polygenic cognitive potential, cognitive performance, or socioeconomic factors were not related to social intolerance. Regarding cognitive styles, low flexibility (B = -0.759, p < .001), high perseverance (B = 1.245, p < .001), and low persistence (B = -0.329, p < .001) predicted higher social intolerance consistently in the analyses. DISCUSSION When developing prejudice-reduction interventions, it should be considered that educational level or cognitive performance may not be crucial for development of social intolerance. Adopting certain cognitive styles may play more important roles in development of social intolerance.
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Affiliation(s)
- Aino Saarinen
- Faculty of Medicine, Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | | | - Henrik Dobewall
- Faculty of Medicine, Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland.,Research Unit of Psychology, University of Oulu, Oulu, Finland.,Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center, Tampere, Finland
| | | | - Ari Ahola-Olli
- Department of Internal Medicine, Satasairaala Central Hospital, Pori, Finland.,Psychiatric and Neurodevelopmental Genetics Unit, Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts.,Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center, Tampere, Finland.,Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Nina Hutri-Kähönen
- Tampere Centre for Skills Training and Simulation, Tampere University, Tampere, Finland
| | - Olli Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland.,Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland.,Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Suvi Rovio
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland.,Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Niklas Ravaja
- Faculty of Medicine, Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
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Life-Course Associations between Blood Pressure-Related Polygenic Risk Scores and Hypertension in the Bogalusa Heart Study. Genes (Basel) 2022; 13:genes13081473. [PMID: 36011384 PMCID: PMC9408577 DOI: 10.3390/genes13081473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Revised: 07/30/2022] [Accepted: 08/15/2022] [Indexed: 11/16/2022] Open
Abstract
Genetic information may help to identify individuals at increased risk for hypertension in early life, prior to the manifestation of elevated blood pressure (BP) values. We examined 369 Black and 832 White Bogalusa Heart Study (BHS) participants recruited in childhood and followed for approximately 37 years. The multi-ancestry genome-wide polygenic risk scores (PRSs) for systolic BP (SBP), diastolic BP (DBP), and hypertension were tested for an association with incident hypertension and stage 2 hypertension using Cox proportional hazards models. Race-stratified analyses were adjusted for baseline age, age2, sex, body mass index, genetic principal components, and BP. In Black participants, each standard deviation increase in SBP and DBP PRS conferred a 38% (p = 0.009) and 22% (p = 0.02) increased risk of hypertension and a 74% (p < 0.001) and 50% (p < 0.001) increased risk of stage 2 hypertension, respectively, while no association was observed with the hypertension PRSs. In Whites, each standard deviation increase in SBP, DBP, and hypertension PRS conferred a 24% (p < 0.05), 29% (p = 0.01), and 25% (p < 0.001) increased risk of hypertension, and a 27% (p = 0.08), 29% (0.01), and 42% (p < 0.001) increased risk of stage 2 hypertension, respectively. The addition of BP PRSs to the covariable-only models generally improved the C-statistics (p < 0.05). Multi-ancestry BP PRSs demonstrate the utility of genomic information in the early life prediction of hypertension.
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Viinikainen J, Bryson A, Böckerman P, Kari JT, Lehtimäki T, Raitakari O, Viikari J, Pehkonen J. Does better education mitigate risky health behavior? A mendelian randomization study. ECONOMICS AND HUMAN BIOLOGY 2022; 46:101134. [PMID: 35354116 DOI: 10.1016/j.ehb.2022.101134] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Revised: 03/14/2022] [Accepted: 03/15/2022] [Indexed: 06/14/2023]
Abstract
Education and risky health behaviors are strongly negatively correlated. Education may affect health behaviors by enabling healthier choices through higher disposable income, increasing information about the harmful effects of risky health behaviors, or altering time preferences. Alternatively, the observed negative correlation may stem from reverse causality or unobserved confounders. Based on the data from the Cardiovascular Risk in Young Finns Study linked to register-based information on educational attainment and family background, this paper identifies the causal effect of education on risky health behaviors. To examine causal effects, we used a genetic score as an instrument for years of education. We found that individuals with higher education allocated more attention to healthy habits. In terms of health behaviors, highly educated people were less likely to smoke. Some model specifications also indicated that the highly educated consumed more fruit and vegetables, but the results were imprecise in this regard. No causal effect was found between education and abusive drinking. In brief, inference based on genetic instruments showed that higher education leads to better choices in some but not all dimensions of health behaviors.
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Affiliation(s)
- Jutta Viinikainen
- University of Jyväskylä, Jyväskylä University School of Business and Economics, Jyväskylä, Finland.
| | - Alex Bryson
- University College London, Social Research Institute, London, United Kingdom; National Institute of Economic and Social Research, London, United Kingdom; IZA Institute of Labor Economics, Bonn, Germany
| | - Petri Böckerman
- University of Jyväskylä, Jyväskylä University School of Business and Economics, Jyväskylä, Finland; IZA Institute of Labor Economics, Bonn, Germany; Labour Institute for Economic Research LABORE, Helsinki, Finland
| | - Jaana T Kari
- University of Jyväskylä, Jyväskylä University School of Business and Economics, Jyväskylä, Finland
| | - Terho Lehtimäki
- Tampere University, Department of Clinical Chemistry, Tampere, Finland; Fimlab Laboratories, Tampere, Finland; Tampere University, Faculty of Medicine and Health Technology, Tampere, Finland; Tampere University, Finnish Cardiovascular Research Center, Tampere, Finland
| | - Olli Raitakari
- University of Turku and Turku University Hospital, Centre for Population Health Research, Turku, Finland; University of Turku, Research Centre of Applied and Preventive Cardiovascular Medicine, Turku, Finland; Turku University Hospital, Department of Clinical Physiology and Nuclear Medicine, Turku, Finland
| | - Jorma Viikari
- University of Turku, Department of Medicine, Turku, Finland; Turku University Hospital, Division of Medicine, Turku, Finland
| | - Jaakko Pehkonen
- University of Jyväskylä, Jyväskylä University School of Business and Economics, Jyväskylä, Finland
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Tölli P, Keltikangas‐Järvinen L, Lehtimäki T, Ravaja N, Hintsanen M, Ahola‐Olli A, Pahkala K, Kähönen M, Hutri‐Kähönen N, Laitinen TT, Tossavainen P, Taittonen L, Dobewall H, Jokinen E, Raitakari O, Cloninger CR, Rovio S, Saarinen A. The relationship between temperament, polygenic score for intelligence and cognition: A population-based study of middle-aged adults. GENES, BRAIN, AND BEHAVIOR 2022; 21:e12798. [PMID: 35170850 PMCID: PMC9744494 DOI: 10.1111/gbb.12798] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 01/12/2022] [Accepted: 01/15/2022] [Indexed: 11/30/2022]
Abstract
We investigated whether temperament modifies an association between polygenic intelligence potential and cognitive test performance in midlife. The participants (n = 1647, born between 1962 and 1977) were derived from the Young Finns Study. Temperament was assessed with Temperament and Character Inventory over a 15-year follow-up (1997, 2001, 2007, 2012). Polygenic intelligence potential was assessed with a polygenic score for intelligence. Cognitive performance (visual memory, reaction time, sustained attention, spatial working memory) was assessed with CANTAB in midlife. The PGSI was significantly associated with the overall cognitive performance and performance in visual memory, sustained attention and working memory tests but not reaction time test. Temperament did not correlate with polygenic score for intelligence and did not modify an association between the polygenic score and cognitive performance, either. High persistence was associated with higher visual memory (B = 0.092; FDR-adj. p = 0.007) and low harm avoidance with higher overall cognitive performance, specifically better reaction time (B = -0.102; FDR-adj; p = 0.007). The subscales of harm avoidance had different associations with cognitive performance: higher "anticipatory worry," higher "fatigability," and lower "shyness with strangers" were associated with lower cognitive performance, while the role of "fear of uncertainty" was subtest-related. In conclusion, temperament does not help or hinder one from realizing their genetic potential for intelligence. The overall modest relationships between temperament and cognitive performance advise caution if utilizing temperament-related information e.g. in working-life recruitments. Cognitive abilities may be influenced by temperament variables, such as the drive for achievement and anxiety about test performance, but they involve distinct systems of learning and memory.
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Affiliation(s)
- Pekka Tölli
- Department of Psychology and Logopedics, Faculty of MedicineUniversity of HelsinkiHelsinkiFinland
| | | | - Terho Lehtimäki
- Department of Clinical ChemistryFimlab Laboratories, and Finnish Cardiovascular Research CenterTampereFinland
- Faculty of Medicine and Health TechnologyTampere UniversityTampereFinland
| | - Niklas Ravaja
- Department of Psychology and Logopedics, Faculty of MedicineUniversity of HelsinkiHelsinkiFinland
| | - Mirka Hintsanen
- Research Unit of Psychology, Faculty of EducationUniversity of OuluOuluFinland
| | - Ari Ahola‐Olli
- Department of Internal MedicineSatasairaala Central HospitalPoriFinland
- Psychiatric and Neurodevelopmental Genetics UnitDepartment of Psychiatry, Massachusetts General HospitalBostonMassachusettsUSA
- Institute for Molecular Medicine Finland (FIMM)University of HelsinkiHelsinkiFinland
| | - Katja Pahkala
- Research Centre for Applied and Preventive Cardiovascular MedicineUniversity of TurkuTurkuFinland
- Sports Exercise Medicine Unit, Department of Physical Activity and HealthPaavo Nurmi CentreTurkuFinland
| | - Mika Kähönen
- Faculty of Medicine and Health TechnologyTampere UniversityTampereFinland
- Department of Clinical PhysiologyTampere University HospitalTampereFinland
| | - Nina Hutri‐Kähönen
- Tampere Centre for Skills Training and SimulationTampere UniversityTampereFinland
| | - Tomi T. Laitinen
- Research Centre for Applied and Preventive Cardiovascular MedicineUniversity of TurkuTurkuFinland
- Sports Exercise Medicine Unit, Department of Physical Activity and HealthPaavo Nurmi CentreTurkuFinland
| | - Päivi Tossavainen
- Department of Pediatrics and AdolescentsOulu University HospitalOuluFinland
- PEDEGO Research Unit and Medical Research Center OuluUniversity of OuluOuluFinland
| | - Leena Taittonen
- Vaasa Central HospitalVaasaFinland
- Department of PediatricsUniversity of OuluOuluFinland
| | - Henrik Dobewall
- Research Unit of Psychology, Faculty of EducationUniversity of OuluOuluFinland
| | - Eero Jokinen
- Department of PediatricsUniversity of HelsinkiHelsinkiFinland
- Hospital for Children and AdolescentsHelsinki University HospitalHelsinkiFinland
| | - Olli Raitakari
- Department of Internal MedicineSatasairaala Central HospitalPoriFinland
- Centre for Population Health ResearchUniversity of Turku and Turku University HospitalTurkuFinland
- Department of Clinical Physiology and Nuclear MedicineTurku University HospitalTurkuFinland
| | | | - Suvi Rovio
- Research Centre for Applied and Preventive Cardiovascular MedicineUniversity of TurkuTurkuFinland
| | - Aino Saarinen
- Department of Psychology and Logopedics, Faculty of MedicineUniversity of HelsinkiHelsinkiFinland
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7
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Pehkonen J, Viinikainen J, Kari JT, Böckerman P, Lehtimäki T, Viikari J, Raitakari O. Birth weight, adult weight, and cardiovascular biomarkers: Evidence from the Cardiovascular Young Finns Study. Prev Med 2022; 154:106894. [PMID: 34801564 DOI: 10.1016/j.ypmed.2021.106894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 10/12/2021] [Accepted: 11/14/2021] [Indexed: 10/19/2022]
Abstract
This study quantifies the causal effect of birth weight on cardiovascular biomarkers in adulthood using the Cardiovascular Risk in Young Finns Study (YFS). We apply a multivariable Mendelian randomization (MVMR) method that provides a novel approach to improve inference in causal analysis based on a mediation framework. The results show that birth weight is linked to triglyceride levels (β = -0.294; 95% CI [-0.591, 0.003]) but not to low-density lipoprotein (LDL) cholesterol levels (β = 0.007; 95% CI [-0.168, 0.183]). The total effect of birth weight on triglyceride levels is partly offset by a mediation pathway linking birth weight to adult BMI (β = 0.111; 95% CI [-0.013, 0.234]). The negative total effect is consistent with the fetal programming hypothesis. The positive indirect effect via adult BMI highlights the persistence of body weight throughout a person's life and the adverse effects of high BMI on health. The results are consistent with previous findings that both low birth weight and weight gain increase health risks in adulthood.
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Affiliation(s)
- Jaakko Pehkonen
- School of Business and Economics, University of Jyväskylä, Jyväskylä, Finland.
| | - Jutta Viinikainen
- School of Business and Economics, University of Jyväskylä, Jyväskylä, Finland
| | - Jaana T Kari
- School of Business and Economics, University of Jyväskylä, Jyväskylä, Finland
| | - Petri Böckerman
- School of Business and Economics, University of Jyväskylä, Jyväskylä, Finland; Labour Institute for Economic Research, Helsinki, Finland; IZA, Bonn, Germany
| | - Terho Lehtimäki
- Department of Clinincal Chemistry, Tampere University, Finland; Fimlab Laboratoriot Oy Ltd, Tampere, Finland; Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland; Finnish Cardiovascular Research Center Tampere, Tampere University, Tampere, Finland
| | - Jorma Viikari
- Department of Medicine, University of Turku, Turku, Finland, Division of Medicine, Turku University Hospital, Turku, Finland
| | - Olli Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland; Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland; Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
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8
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Bourgeois S, Carr DF, Musumba CO, Penrose A, Esume C, Morris AP, Jorgensen AL, Zhang JE, Pritchard DM, Deloukas P, Pirmohamed M. Genome-Wide association between EYA1 and Aspirin-induced peptic ulceration. EBioMedicine 2021; 74:103728. [PMID: 34864618 PMCID: PMC8646165 DOI: 10.1016/j.ebiom.2021.103728] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 11/13/2021] [Accepted: 11/17/2021] [Indexed: 11/29/2022] Open
Abstract
Background Low-dose aspirin can cause gastric and duodenal ulceration, hereafter called peptic ulcer disease (PUD). Predisposition is thought to be related to clinical and genetic factors; our aim was to identify genetic risk factors associated with aspirin-induced PUD. Methods Patients (n=1478) were recruited from 15 UK hospitals. Cases (n=505) were defined as patients with endoscopically confirmed PUD within 2 weeks of using aspirin and non-aspirin Non-Steroidal Anti-Inflammatory Drugs (NSAIDs). They were compared to two control groups: patients with endoscopically confirmed PUD without any history of NSAID use within 3 months of diagnosis (n=495), and patients with no PUD on endoscopy (n=478). A genome-wide association study (GWAS) of aspirin-induced cases (n=247) was compared to 476 controls. The results were validated by replication in another 84 cases and 162 controls. Findings The GWAS identified one variant, rs12678747 (p=1·65×10−7) located in the last intron of EYA1 on chromosome 8. The association was replicated in another sample of 84 PUD patients receiving aspirin (p=0·002). Meta-analysis of discovery and replication cohort data for rs12678747, yielded a genome-wide significant association (p=3·12×10−11; OR=2·03; 95% CI 1·65-2·50). Expression of EYA1 was lower at the gastric ulcer edge when compared with the antrum. Interpretation Genetic variation in an intron of the EYA1 gene increases the risk of endoscopically confirmed aspirin-induced PUD. Reduced EYA1 expression in the upper gastrointestinal epithelium may modulate risk, but the functional basis of this association will need mechanistic evaluation. Funding Department of Health Chair in Pharmacogenetics, MRC Centre for Drug Safety Science and the Barts Cardiovascular NIHR Biomedical Research Centre, British Heart Foundation (BHF)
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Affiliation(s)
- Stephane Bourgeois
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London UK
| | - Daniel F Carr
- Department of Pharmacology and Therapeutics, University of Liverpool, UK
| | - Crispin O Musumba
- Department of Pharmacology and Therapeutics, University of Liverpool, UK
| | - Alexander Penrose
- Department of Pharmacology and Therapeutics, University of Liverpool, UK
| | - Celestine Esume
- Department of Pharmacology and Therapeutics, University of Liverpool, UK
| | - Andrew P Morris
- Department of Pharmacology and Therapeutics, University of Liverpool, UK; Department of Health Data Science, University of Liverpool, UK; Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, University of Manchester, Manchester, UK
| | | | - J Eunice Zhang
- Department of Pharmacology and Therapeutics, University of Liverpool, UK
| | - D Mark Pritchard
- Department of Cellular and Molecular Physiology, University of Liverpool, Liverpool, UK
| | - Panos Deloukas
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London UK.
| | - Munir Pirmohamed
- Department of Pharmacology and Therapeutics, University of Liverpool, UK.
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9
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Pehkonen J, Viinikainen J, Kari JT, Böckerman P, Lehtimäki T, Raitakari O. Birth weight and adult income: An examination of mediation through adult height and body mass. HEALTH ECONOMICS 2021; 30:2383-2398. [PMID: 34250692 DOI: 10.1002/hec.4387] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Revised: 06/09/2021] [Accepted: 06/21/2021] [Indexed: 06/13/2023]
Abstract
This paper examines the causal links between early human endowments and socioeconomic outcomes in adulthood. We use a genotyped longitudinal survey (Cardiovascular Risk in Young Finns Study) that is linked to the administrative registers of Statistics Finland. We focus on the effect of birth weight on income via two anthropometric mediators: body mass index (BMI) and height in adulthood. We find that (i) the genetic instruments for birth weight, adult height, and adult BMI are statistically powerful; (ii) there is a robust total effect of birth weight on income for men but not for women; (iii) the total effect of birth weight on income for men is partly mediated via height but not via BMI; and (iv) the share of the total effect mediated via height is substantial, of approximately 56%.
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Affiliation(s)
- Jaakko Pehkonen
- Jyväskylä University School of Business and Economics, University of Jyväskylä, Jyväskylä, Finland
| | - Jutta Viinikainen
- Jyväskylä University School of Business and Economics, University of Jyväskylä, Jyväskylä, Finland
| | - Jaana T Kari
- Jyväskylä University School of Business and Economics, University of Jyväskylä, Jyväskylä, Finland
| | - Petri Böckerman
- Jyväskylä University School of Business and Economics, University of Jyväskylä, Jyväskylä, Finland
- Labour Institute for Economic Research, Helsinki, Finland and IZA, Bonn, Germany
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center, Tampere, Finland
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Olli Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
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10
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Donor genetic variants in interleukin-6 and interleukin-6 receptor associate with biopsy-proven rejection following kidney transplantation. Sci Rep 2021; 11:16483. [PMID: 34389747 PMCID: PMC8363661 DOI: 10.1038/s41598-021-95714-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2021] [Accepted: 07/29/2021] [Indexed: 02/07/2023] Open
Abstract
Rejection after kidney transplantation remains an important cause of allograft failure that markedly impacts morbidity. Cytokines are a major player in rejection, and we, therefore, explored the impact of interleukin-6 (IL6) and IL-6 receptor (IL6R) gene polymorphisms on the occurrence of rejection after renal transplantation. We performed an observational cohort study analyzing both donor and recipient DNA in 1271 renal transplant‐pairs from the University Medical Center Groningen in The Netherlands and associated single nucleotide polymorphisms (SNPs) with biopsy-proven rejection after kidney transplantation. The C-allele of the IL6R SNP (Asp358Ala; rs2228145 A > C, formerly rs8192284) in donor kidneys conferred a reduced risk of rejection following renal transplantation (HR 0.78 per C-allele; 95%-CI 0.67–0.90; P = 0.001). On the other hand, the C-allele of the IL6 SNP (at position-174 in the promoter; rs1800795 G > C) in donor kidneys was associated with an increased risk of rejection for male organ donors (HR per C-allele 1.31; 95%-CI 1.08–1.58; P = 0.0006), but not female organ donors (P = 0.33). In contrast, neither the IL6 nor IL6R SNP in the recipient showed an association with renal transplant rejection. In conclusion, donor IL6 and IL6R genotypes but not recipient genotypes represent an independent prognostic marker for biopsy-proven renal allograft rejection.
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11
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Hakala JO, Pahkala K, Juonala M, Salo P, Kähönen M, Hutri-Kähönen N, Lehtimäki T, Laitinen TP, Jokinen E, Taittonen L, Tossavainen P, Viikari JSA, Raitakari OT, Rovio SP. Cardiovascular Risk Factor Trajectories Since Childhood and Cognitive Performance in Midlife: The Cardiovascular Risk in Young Finns Study. Circulation 2021; 143:1949-1961. [PMID: 33966448 DOI: 10.1161/circulationaha.120.052358] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Cardiovascular risk factors, such as high blood pressure, adverse serum lipids, and elevated body mass index in midlife, may harm cognitive performance. It is important to note that longitudinal accumulation of cardiovascular risk factors since childhood may be associated with cognitive performance already since childhood, but the previous evidence is scarce. We studied the associations of cardiovascular risk factors from childhood to midlife, their accumulation, and midlife cognitive performance. METHODS From 1980, a population-based cohort of 3596 children (3-18 years of age) have been repeatedly followed up for 31 years. Blood pressure, serum lipids, and body mass index were assessed in all follow-ups. Cardiovascular risk factor trajectories from childhood to midlife were identified using latent class growth mixture modeling. Cognitive testing was performed in 2026 participants 34 to 49 years of age using a computerized test. The associations of the cardiovascular risk factor trajectories and cognitive performance were studied for individual cardiovascular risk factors and cardiovascular risk factor accumulation. RESULTS Consistently high systolic blood pressure (β=-0.262 SD [95% CI, -0.520 to -0.005]) and serum total cholesterol (β=-0.214 SD [95% CI, -0.365 to -0.064]) were associated with worse midlife episodic memory and associative learning compared with consistently low values. Obesity since childhood was associated with worse visual processing and sustained attention (β=-0.407 SD [95% CI, -0.708 to -0.105]) compared with normal weight. An inverse association was observed for the cardiovascular risk factor accumulation with episodic memory and associative learning (P for trend=0.008; 3 cardiovascular risk factors: β=-0.390 SD [95% CI, -0.691 to -0.088]), with visual processing and sustained attention (P for trend<0.0001; 3 cardiovascular risk factors: β=-0.443 SD [95% CI, -0.730 to -0.157]), and with reaction and movement time (P for trend=0.048; 2 cardiovascular risk factors: β=-0.164 SD [95% CI, -0.318 to -0.010]). CONCLUSIONS Longitudinal elevated systolic blood pressure, high serum total cholesterol, and obesity from childhood to midlife were inversely associated with midlife cognitive performance. It is important to note that the higher the number of cardiovascular risk factors, the worse was the observed cognitive performance. Therefore, launching preventive strategies against cardiovascular risk factors beginning from childhood might benefit primordial promotion of cognitive health in adulthood.
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Affiliation(s)
- Juuso O Hakala
- Research Centre of Applied and Preventive Cardiovascular Medicine (J.O.H., K.P., P.S., O.T.R., S.P.R.), University of Turku, Finland.,Paavo Nurmi Centre, Sports and Exercise Medicine Unit, Department of Physical Activity and Health (J.O.H., K.P.), University of Turku, Finland.,Centre for Population Health Research (J.O.H., K.P., P.S., O.T.R., S.P.R.), University of Turku and Turku University Hospital, Turku, Finland
| | - Katja Pahkala
- Research Centre of Applied and Preventive Cardiovascular Medicine (J.O.H., K.P., P.S., O.T.R., S.P.R.), University of Turku, Finland.,Paavo Nurmi Centre, Sports and Exercise Medicine Unit, Department of Physical Activity and Health (J.O.H., K.P.), University of Turku, Finland.,Centre for Population Health Research (J.O.H., K.P., P.S., O.T.R., S.P.R.), University of Turku and Turku University Hospital, Turku, Finland
| | - Markus Juonala
- Department of Medicine (M.J., J.S.A.V.), University of Turku, Finland.,Division of Medicine (M.J., J.S.A.V.), Turku University Hospital, Finland
| | - Pia Salo
- Research Centre of Applied and Preventive Cardiovascular Medicine (J.O.H., K.P., P.S., O.T.R., S.P.R.), University of Turku, Finland.,Centre for Population Health Research (J.O.H., K.P., P.S., O.T.R., S.P.R.), University of Turku and Turku University Hospital, Turku, Finland
| | - Mika Kähönen
- Department of Clinical Physiology (M.K.), Tampere University Hospital, Finland.,DFaculty of Medicine and Health Technology (M.K., N.H.-K., T.L.), Tampere University, Finland
| | - Nina Hutri-Kähönen
- Department of Pediatrics (N.H.-K.), Tampere University Hospital, Finland.,DFaculty of Medicine and Health Technology (M.K., N.H.-K., T.L.), Tampere University, Finland
| | - Terho Lehtimäki
- DFaculty of Medicine and Health Technology (M.K., N.H.-K., T.L.), Tampere University, Finland.,Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center, Tampere (T.L.)
| | - Tomi P Laitinen
- Department of Clinical Physiology, University of Eastern Finland and Kuopio University Hospital, Finland (T.P.L.)
| | - Eero Jokinen
- Department of Paediatric Cardiology, Hospital for Children and Adolescents, University of Helsinki, Finland (E.J.)
| | - Leena Taittonen
- Vaasa Central Hospital, Finland (L.T.).,Department of Pediatrics, University of Oulu, Finland (L.T., P.T.)
| | | | - Jorma S A Viikari
- Department of Medicine (M.J., J.S.A.V.), University of Turku, Finland.,Division of Medicine (M.J., J.S.A.V.), Turku University Hospital, Finland
| | - Olli T Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine (J.O.H., K.P., P.S., O.T.R., S.P.R.), University of Turku, Finland.,Centre for Population Health Research (J.O.H., K.P., P.S., O.T.R., S.P.R.), University of Turku and Turku University Hospital, Turku, Finland.,Department of Clinical Physiology and Nuclear Medicine (O.T.R.), Turku University Hospital, Finland
| | - Suvi P Rovio
- Research Centre of Applied and Preventive Cardiovascular Medicine (J.O.H., K.P., P.S., O.T.R., S.P.R.), University of Turku, Finland.,Centre for Population Health Research (J.O.H., K.P., P.S., O.T.R., S.P.R.), University of Turku and Turku University Hospital, Turku, Finland
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12
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Gebreyesus G, Aagaard Poulsen N, Krogh Larsen M, Bach Larsen L, Skipper Sørensen E, Würtz Heegaard C, Buitenhuis B. Vitamin B 12 and transcobalamin in bovine milk: Genetic variation and genome-wide association with loci along the genome. JDS COMMUNICATIONS 2021; 2:127-131. [PMID: 36339496 PMCID: PMC9623645 DOI: 10.3168/jdsc.2020-0048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Accepted: 01/19/2021] [Indexed: 06/16/2023]
Abstract
In human nutrition, bovine milk is an essential source of bioavailable vitamin B12 and B12-binding proteins, including transcobalamin. In this study, we estimated genetic parameters for milk content of vitamin B12 and transcobalamin using milk samples from 341 and 663 Danish Holstein cows, respectively. Additionally, we conducted whole-genome association analysis to identify SNP and genes associated with vitamin B12 and transcobalamin. Our results indicated moderate to high heritability for vitamin B12 (0.37 ± 0.18) and transcobalamin (0.61 ± 0.13) content in the Danish Holstein. With a significance threshold of -log10 P-value > 5.87, significant associations were detected between SNP in Bos taurus autosome (BTA)17 and the log-transformed transcobalamin content of milk; no significant association was detected for vitamin B12. The significant region in BTA17 was imputed to full sequence for further fine mapping, and the SNP with the most significant associations to transcobalamin were assigned to the transcobalamin 2 (TCN2) gene.
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Affiliation(s)
- Grum Gebreyesus
- Center for Quantitative Genetics and Genomics, Aarhus University, Blichers Allé 20, PO Box 50, DK-8830 Tjele, Denmark
| | - Nina Aagaard Poulsen
- Department of Food Science, Aarhus University, Agro Food Park 48, DK-8200 Aarhus N, Denmark
| | - Mette Krogh Larsen
- Department of Food Science, Aarhus University, Agro Food Park 48, DK-8200 Aarhus N, Denmark
- Arla Foods Amba, Mæalkevejen 4, DK-6920 Videbæk, Denmark
| | - Lotte Bach Larsen
- Department of Food Science, Aarhus University, Agro Food Park 48, DK-8200 Aarhus N, Denmark
| | - Esben Skipper Sørensen
- Molecular Nutrition, Department of Molecular Biology and Genetics, Aarhus University, Gustav Wieds Vej 10, DK-8000 Aarhus C, Denmark
| | - Christian Würtz Heegaard
- Molecular Nutrition, Department of Molecular Biology and Genetics, Aarhus University, Gustav Wieds Vej 10, DK-8000 Aarhus C, Denmark
| | - Bart Buitenhuis
- Center for Quantitative Genetics and Genomics, Aarhus University, Blichers Allé 20, PO Box 50, DK-8830 Tjele, Denmark
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13
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Cole BS, Gudiseva HV, Pistilli M, Salowe R, McHugh CP, Zody MC, Chavali VRM, Ying GS, Moore JH, O'Brien JM. The Role of Genetic Ancestry as a Risk Factor for Primary Open-angle Glaucoma in African Americans. Invest Ophthalmol Vis Sci 2021; 62:28. [PMID: 33605984 PMCID: PMC7900887 DOI: 10.1167/iovs.62.2.28] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Accepted: 01/27/2021] [Indexed: 01/01/2023] Open
Abstract
Purpose POAG is the leading cause of irreversible blindness in African Americans. In this study, we quantitatively assess the association of autosomal ancestry with POAG risk in a large cohort of self-identified African Americans. Methods Subjects recruited to the Primary Open-Angle African American Glaucoma Genetics (POAAGG) study were classified as glaucoma cases or controls by fellowship-trained glaucoma specialists. POAAGG subjects were genotyped using the MEGA Ex array (discovery cohort, n = 3830; replication cohort, n = 2135). Population structure was interrogated using principal component analysis in the context of the 1000 Genomes Project superpopulations. Results The majority of POAAGG samples lie on an axis between African and European superpopulations, with great variation in admixture. Cases had a significantly lower mean value of the ancestral component q0 than controls for both cohorts (P = 6.14-4; P = 3-6), consistent with higher degree of African ancestry. Among POAG cases, higher African ancestry was also associated with thinner central corneal thickness (P = 2-4). Admixture mapping showed that local genetic ancestry was not a significant risk factor for POAG. A polygenic risk score, comprised of 23 glaucoma-associated single nucleotide polymorphisms from the NHGRI-EBI genome-wide association study catalog, was significant in both cohorts (P < 0.001), suggesting that both known POAG single nucleotide polymorphisms and an omnigenic ancestry effect influence POAG risk. Conclusions In sum, the POAAGG study population is very admixed, with a higher degree of African ancestry associated with an increased POAG risk. Further analyses should consider social and environmental factors as possible confounding factors for disease predisposition.
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Affiliation(s)
- Brian S. Cole
- Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, Pennsylvania, United States
| | - Harini V. Gudiseva
- Scheie Eye Institute, University of Pennsylvania, Philadelphia, Pennsylvania, United States
| | - Maxwell Pistilli
- Scheie Eye Institute, University of Pennsylvania, Philadelphia, Pennsylvania, United States
| | - Rebecca Salowe
- Scheie Eye Institute, University of Pennsylvania, Philadelphia, Pennsylvania, United States
| | | | - Michael C. Zody
- New York Genome Center, New York City, New York, United States
| | - Venkata R. M. Chavali
- Scheie Eye Institute, University of Pennsylvania, Philadelphia, Pennsylvania, United States
| | - Gui Shuang Ying
- Scheie Eye Institute, University of Pennsylvania, Philadelphia, Pennsylvania, United States
| | - Jason H. Moore
- Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, Pennsylvania, United States
| | - Joan M. O'Brien
- Scheie Eye Institute, University of Pennsylvania, Philadelphia, Pennsylvania, United States
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14
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Sayed S, Nabi AHMN. Diabetes and Genetics: A Relationship Between Genetic Risk Alleles, Clinical Phenotypes and Therapeutic Approaches. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1307:457-498. [PMID: 32314317 DOI: 10.1007/5584_2020_518] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Unveiling human genome through successful completion of Human Genome Project and International HapMap Projects with the advent of state of art technologies has shed light on diseases associated genetic determinants. Identification of mutational landscapes such as copy number variation, single nucleotide polymorphisms or variants in different genes and loci have revealed not only genetic risk factors responsible for diseases but also region(s) playing protective roles. Diabetes is a global health concern with two major types - type 1 diabetes (T1D) and type 2 diabetes (T2D). Great progress in understanding the underlying genetic predisposition to T1D and T2D have been made by candidate gene studies, genetic linkage studies, genome wide association studies with substantial number of samples. Genetic information has importance in predicting clinical outcomes. In this review, we focus on recent advancement regarding candidate gene(s) associated with these two traits along with their clinical parameters as well as therapeutic approaches perceived. Understanding genetic architecture of these disease traits relating clinical phenotypes would certainly facilitate population stratification in diagnosing and treating T1D/T2D considering the doses and toxicity of specific drugs.
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Affiliation(s)
- Shomoita Sayed
- Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, Bangladesh
| | - A H M Nurun Nabi
- Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, Bangladesh.
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15
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Rovio SP, Pihlman J, Pahkala K, Juonala M, Magnussen CG, Pitkänen N, Ahola-Olli A, Salo P, Kähönen M, Hutri-Kähönen N, Lehtimäki T, Jokinen E, Laitinen T, Taittonen L, Tossavainen P, Viikari JSA, Raitakari OT. Childhood Exposure to Parental Smoking and Midlife Cognitive Function. Am J Epidemiol 2020; 189:1280-1291. [PMID: 32242223 DOI: 10.1093/aje/kwaa052] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2019] [Accepted: 03/23/2020] [Indexed: 11/14/2022] Open
Abstract
We studied whether exposure to parental smoking in childhood/adolescence is associated with midlife cognitive function, leveraging data from the Cardiovascular Risk in Young Finns Study. A population-based cohort of 3,596 children/adolescents aged 3-18 years was followed between 1980 and 2011. In 2011, cognitive testing was performed on 2,026 participants aged 34-49 years using computerized testing. Measures of secondhand smoke exposure in childhood/adolescence consisted of parental self-reports of smoking and participants' serum cotinine levels. Participants were classified into 3 exposure groups: 1) no exposure (nonsmoking parents, cotinine <1.0 ng/mL); 2) hygienic parental smoking (1-2 smoking parents, cotinine <1.0 ng/mL); and 3) nonhygienic parental smoking (1-2 smoking parents, cotinine ≥1.0 ng/mL). Analyses adjusted for sex, age, family socioeconomic status, polygenic risk score for cognitive function, adolescent/adult smoking, blood pressure, and serum total cholesterol level. Compared with the nonexposed, participants exposed to nonhygienic parental smoking were at higher risk of poor (lowest quartile) midlife episodic memory and associative learning (relative risk (RR) = 1.38, 95% confidence interval (CI): 1.08, 1.75), and a weak association was found for short-term and spatial working memory (RR = 1.25, 95% CI: 0.98, 1.58). Associations for those exposed to hygienic parental smoking were nonsignificant (episodic memory and associative learning: RR = 1.19, 95% CI: 0.92, 1.54; short-term and spatial working memory: RR = 1.10, 95% CI: 0.85, 1.34). We conclude that avoiding childhood/adolescence secondhand smoke exposure promotes adulthood cognitive function.
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16
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Shah R, Keeble-Gagnère G, Whan A. Accurate calling of homeoallelic genotypes of iSelect markers using inbred structured populations. Bioinformatics 2020; 36:4240-4247. [PMID: 32374818 DOI: 10.1093/bioinformatics/btaa295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2019] [Revised: 02/26/2020] [Accepted: 04/28/2020] [Indexed: 11/14/2022] Open
Abstract
MOTIVATION Genetic map construction is a foundational step in the analysis of structured experimental populations. For markers that hybridize to several genetically similar locations, or where several alleles are present (such as in multiparental populations), current methods often discard the marker or incorrectly call the genotypes. These errors result in information loss, or incorrect genotypes that can corrupt map construction. RESULTS We present a new approach for simultaneously performing genetic map construction and marker calling. Our new approach allows the calling of a larger number of markers, a larger number of unique alleles per marker and the correct use of markers which hybridize to multiple genetically similar locations. We demonstrate our new approach using simulations, a biparental wheat population and an eight-parent population of spring bread wheat. Applying our method to the eight-parent population increased the number of mapped markers by 71%. We show that the new genetic map allows the investigation of synteny in ways that were not previously possible in that dataset. AVAILABILITY AND IMPLEMENTATION The method described in this article has been incorporated into R package mpMap2. It is available from CRAN and also from https://github.com/rohan-shah/mpMap2. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Rohan Shah
- CSIRO Agriculture and Food, Canberra, ACT 2601, Australia.,ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Gabriel Keeble-Gagnère
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, Victoria 3083, Australia
| | - Alex Whan
- CSIRO Agriculture and Food, Canberra, ACT 2601, Australia
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17
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Gasperi C, Andlauer TFM, Keating A, Knier B, Klein A, Pernpeintner V, Lichtner P, Gold R, Zipp F, Then Bergh F, Stangel M, Tumani H, Wildemann B, Wiendl H, Bayas A, Kümpfel T, Zettl UK, Linker RA, Ziemann U, Knop M, Warnke C, Friese MA, Paul F, Tackenberg B, Berthele A, Hemmer B. Genetic determinants of the humoral immune response in MS. NEUROLOGY-NEUROIMMUNOLOGY & NEUROINFLAMMATION 2020; 7:7/5/e827. [PMID: 32675288 PMCID: PMC7371373 DOI: 10.1212/nxi.0000000000000827] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Accepted: 05/26/2020] [Indexed: 01/09/2023]
Abstract
OBJECTIVE In this observational study, we investigated the impact of genetic factors at the immunoglobulin heavy chain constant locus on chromosome 14 and the major histocompatibility complex region on intrathecal immunoglobulin G, A, and M levels as well as on B cells and plasmablasts in the CSF and blood of patients with multiple sclerosis (MS). METHODS Using regression analyses, we tested genetic variants on chromosome 14 and imputed human leukocyte antigen (HLA) alleles for associations with intrathecal immunoglobulins in 1,279 patients with MS or clinically isolated syndrome and with blood and CSF B cells and plasmablasts in 301 and 348 patients, respectively. RESULTS The minor alleles of variants on chromosome 14 were associated with higher intrathecal immunoglobulin G levels (β = 0.58 [0.47 to 0.68], lowest adjusted p = 2.32 × 10-23), and lower intrathecal immunoglobulin M (β = -0.56 [-0.67 to -0.46], p = 2.06 × 10-24) and A (β = -0.42 [-0.54 to -0.31], p = 7.48 × 10-11) levels. Alleles from the HLA-B*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02 haplotype were associated with higher (lowest p = 2.14 × 10-7) and HLA-B*44:02 with lower (β = -0.35 [-0.54 to -0.17], p = 1.38 × 10-2) immunoglobulin G levels. Of interest, different HLA alleles were associated with lower intrathecal immunoglobulin M (HLA-C*02:02, β = -0.45 [-0.61 to -0.28], p = 1.01 × 10-5) and higher immunoglobulin A levels (HLA-DQA1*01:03-DQB1*06:03-DRB1*13:01 haplotype, β = 0.40 [0.21 to 0.60], p = 4.46 × 10-3). The impact of HLA alleles on intrathecal immunoglobulin G and M levels could mostly be explained by associations with CSF B cells and plasmablasts. CONCLUSION Although some HLA alleles seem to primarily drive the extent of humoral immune responses in the CNS by increasing CSF B cells and plasmablasts, genetic variants at the immunoglobulin heavy chain constant locus might regulate intrathecal immunoglobulins levels via different mechanisms.
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Affiliation(s)
- Christiane Gasperi
- From the Department of Neurology (C.G., T.F.M.A., A. Keating, B.K., A. Klein, V.P., A. Berthele, B.H.), Klinikum rechts der Isar, School of Medicine, Technical University of Munich; Institute of Human Genetics (P.L.), Helmholtz Zentrum München, Neuherberg; Department of Neurology (R.G.), St. Josef Hospital, Ruhr-University Bochum; Department of Neurology, Focus Program Translational Neurosciences (FTN) and Research Center for Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn2) (F.Z.), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology and Translational Center for Regenerative Medicine (F.T.B.), University of Leipzig; Clinical Neuroimmunology and Neurochemistry (M.S.), Department of Neurology, Hannover Medical School, Hannover; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Department of Neurology (B.W.), University Hospital Heidelberg; Department of Neurology (H.W.), University of Münster; Department of Neurology (A. Bayas), University Hospital Augsburg; Institute of Clinical Neuroimmunology (T.K.), University Hospital and Biomedical Center, Ludwig-Maximilians University Munich; Department of Neurology (U.K.Z.), Neuroimmunological Section, University of Rostock; Department of Neurology (R.A.L.), University Hospital Erlangen; Department of Neurology (R.A.L.), University of Regensburg; Department of Neurology & Stroke and Hertie-Institute for Clinical Brain Research (U.Z.), Eberhard-Karls-Universität Tübingen; Max Planck Institute of Psychiatry (M.K.), Munich; Department of Neurology (C.W.), Medical Faculty, Heinrich Heine University, Düsseldorf; Department of Neurology (C.W.), University Hospital Cologne; Institute of Neuroimmunology and Multiple Sclerosis (M.A.F), University Medical Centre Hamburg-Eppendorf, Hamburg; NeuroCure Clinical Research Center (F.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin; Berlin Institute of Health and Experimental and Clinical Research Center (F.P.), Max Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin; and Center of Neuroimmunology (B.T.), Philipps-University Marburg; and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Germany
| | - Till F M Andlauer
- From the Department of Neurology (C.G., T.F.M.A., A. Keating, B.K., A. Klein, V.P., A. Berthele, B.H.), Klinikum rechts der Isar, School of Medicine, Technical University of Munich; Institute of Human Genetics (P.L.), Helmholtz Zentrum München, Neuherberg; Department of Neurology (R.G.), St. Josef Hospital, Ruhr-University Bochum; Department of Neurology, Focus Program Translational Neurosciences (FTN) and Research Center for Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn2) (F.Z.), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology and Translational Center for Regenerative Medicine (F.T.B.), University of Leipzig; Clinical Neuroimmunology and Neurochemistry (M.S.), Department of Neurology, Hannover Medical School, Hannover; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Department of Neurology (B.W.), University Hospital Heidelberg; Department of Neurology (H.W.), University of Münster; Department of Neurology (A. Bayas), University Hospital Augsburg; Institute of Clinical Neuroimmunology (T.K.), University Hospital and Biomedical Center, Ludwig-Maximilians University Munich; Department of Neurology (U.K.Z.), Neuroimmunological Section, University of Rostock; Department of Neurology (R.A.L.), University Hospital Erlangen; Department of Neurology (R.A.L.), University of Regensburg; Department of Neurology & Stroke and Hertie-Institute for Clinical Brain Research (U.Z.), Eberhard-Karls-Universität Tübingen; Max Planck Institute of Psychiatry (M.K.), Munich; Department of Neurology (C.W.), Medical Faculty, Heinrich Heine University, Düsseldorf; Department of Neurology (C.W.), University Hospital Cologne; Institute of Neuroimmunology and Multiple Sclerosis (M.A.F), University Medical Centre Hamburg-Eppendorf, Hamburg; NeuroCure Clinical Research Center (F.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin; Berlin Institute of Health and Experimental and Clinical Research Center (F.P.), Max Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin; and Center of Neuroimmunology (B.T.), Philipps-University Marburg; and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Germany
| | - Ana Keating
- From the Department of Neurology (C.G., T.F.M.A., A. Keating, B.K., A. Klein, V.P., A. Berthele, B.H.), Klinikum rechts der Isar, School of Medicine, Technical University of Munich; Institute of Human Genetics (P.L.), Helmholtz Zentrum München, Neuherberg; Department of Neurology (R.G.), St. Josef Hospital, Ruhr-University Bochum; Department of Neurology, Focus Program Translational Neurosciences (FTN) and Research Center for Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn2) (F.Z.), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology and Translational Center for Regenerative Medicine (F.T.B.), University of Leipzig; Clinical Neuroimmunology and Neurochemistry (M.S.), Department of Neurology, Hannover Medical School, Hannover; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Department of Neurology (B.W.), University Hospital Heidelberg; Department of Neurology (H.W.), University of Münster; Department of Neurology (A. Bayas), University Hospital Augsburg; Institute of Clinical Neuroimmunology (T.K.), University Hospital and Biomedical Center, Ludwig-Maximilians University Munich; Department of Neurology (U.K.Z.), Neuroimmunological Section, University of Rostock; Department of Neurology (R.A.L.), University Hospital Erlangen; Department of Neurology (R.A.L.), University of Regensburg; Department of Neurology & Stroke and Hertie-Institute for Clinical Brain Research (U.Z.), Eberhard-Karls-Universität Tübingen; Max Planck Institute of Psychiatry (M.K.), Munich; Department of Neurology (C.W.), Medical Faculty, Heinrich Heine University, Düsseldorf; Department of Neurology (C.W.), University Hospital Cologne; Institute of Neuroimmunology and Multiple Sclerosis (M.A.F), University Medical Centre Hamburg-Eppendorf, Hamburg; NeuroCure Clinical Research Center (F.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin; Berlin Institute of Health and Experimental and Clinical Research Center (F.P.), Max Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin; and Center of Neuroimmunology (B.T.), Philipps-University Marburg; and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Germany
| | - Benjamin Knier
- From the Department of Neurology (C.G., T.F.M.A., A. Keating, B.K., A. Klein, V.P., A. Berthele, B.H.), Klinikum rechts der Isar, School of Medicine, Technical University of Munich; Institute of Human Genetics (P.L.), Helmholtz Zentrum München, Neuherberg; Department of Neurology (R.G.), St. Josef Hospital, Ruhr-University Bochum; Department of Neurology, Focus Program Translational Neurosciences (FTN) and Research Center for Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn2) (F.Z.), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology and Translational Center for Regenerative Medicine (F.T.B.), University of Leipzig; Clinical Neuroimmunology and Neurochemistry (M.S.), Department of Neurology, Hannover Medical School, Hannover; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Department of Neurology (B.W.), University Hospital Heidelberg; Department of Neurology (H.W.), University of Münster; Department of Neurology (A. Bayas), University Hospital Augsburg; Institute of Clinical Neuroimmunology (T.K.), University Hospital and Biomedical Center, Ludwig-Maximilians University Munich; Department of Neurology (U.K.Z.), Neuroimmunological Section, University of Rostock; Department of Neurology (R.A.L.), University Hospital Erlangen; Department of Neurology (R.A.L.), University of Regensburg; Department of Neurology & Stroke and Hertie-Institute for Clinical Brain Research (U.Z.), Eberhard-Karls-Universität Tübingen; Max Planck Institute of Psychiatry (M.K.), Munich; Department of Neurology (C.W.), Medical Faculty, Heinrich Heine University, Düsseldorf; Department of Neurology (C.W.), University Hospital Cologne; Institute of Neuroimmunology and Multiple Sclerosis (M.A.F), University Medical Centre Hamburg-Eppendorf, Hamburg; NeuroCure Clinical Research Center (F.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin; Berlin Institute of Health and Experimental and Clinical Research Center (F.P.), Max Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin; and Center of Neuroimmunology (B.T.), Philipps-University Marburg; and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Germany
| | - Ana Klein
- From the Department of Neurology (C.G., T.F.M.A., A. Keating, B.K., A. Klein, V.P., A. Berthele, B.H.), Klinikum rechts der Isar, School of Medicine, Technical University of Munich; Institute of Human Genetics (P.L.), Helmholtz Zentrum München, Neuherberg; Department of Neurology (R.G.), St. Josef Hospital, Ruhr-University Bochum; Department of Neurology, Focus Program Translational Neurosciences (FTN) and Research Center for Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn2) (F.Z.), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology and Translational Center for Regenerative Medicine (F.T.B.), University of Leipzig; Clinical Neuroimmunology and Neurochemistry (M.S.), Department of Neurology, Hannover Medical School, Hannover; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Department of Neurology (B.W.), University Hospital Heidelberg; Department of Neurology (H.W.), University of Münster; Department of Neurology (A. Bayas), University Hospital Augsburg; Institute of Clinical Neuroimmunology (T.K.), University Hospital and Biomedical Center, Ludwig-Maximilians University Munich; Department of Neurology (U.K.Z.), Neuroimmunological Section, University of Rostock; Department of Neurology (R.A.L.), University Hospital Erlangen; Department of Neurology (R.A.L.), University of Regensburg; Department of Neurology & Stroke and Hertie-Institute for Clinical Brain Research (U.Z.), Eberhard-Karls-Universität Tübingen; Max Planck Institute of Psychiatry (M.K.), Munich; Department of Neurology (C.W.), Medical Faculty, Heinrich Heine University, Düsseldorf; Department of Neurology (C.W.), University Hospital Cologne; Institute of Neuroimmunology and Multiple Sclerosis (M.A.F), University Medical Centre Hamburg-Eppendorf, Hamburg; NeuroCure Clinical Research Center (F.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin; Berlin Institute of Health and Experimental and Clinical Research Center (F.P.), Max Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin; and Center of Neuroimmunology (B.T.), Philipps-University Marburg; and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Germany
| | - Verena Pernpeintner
- From the Department of Neurology (C.G., T.F.M.A., A. Keating, B.K., A. Klein, V.P., A. Berthele, B.H.), Klinikum rechts der Isar, School of Medicine, Technical University of Munich; Institute of Human Genetics (P.L.), Helmholtz Zentrum München, Neuherberg; Department of Neurology (R.G.), St. Josef Hospital, Ruhr-University Bochum; Department of Neurology, Focus Program Translational Neurosciences (FTN) and Research Center for Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn2) (F.Z.), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology and Translational Center for Regenerative Medicine (F.T.B.), University of Leipzig; Clinical Neuroimmunology and Neurochemistry (M.S.), Department of Neurology, Hannover Medical School, Hannover; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Department of Neurology (B.W.), University Hospital Heidelberg; Department of Neurology (H.W.), University of Münster; Department of Neurology (A. Bayas), University Hospital Augsburg; Institute of Clinical Neuroimmunology (T.K.), University Hospital and Biomedical Center, Ludwig-Maximilians University Munich; Department of Neurology (U.K.Z.), Neuroimmunological Section, University of Rostock; Department of Neurology (R.A.L.), University Hospital Erlangen; Department of Neurology (R.A.L.), University of Regensburg; Department of Neurology & Stroke and Hertie-Institute for Clinical Brain Research (U.Z.), Eberhard-Karls-Universität Tübingen; Max Planck Institute of Psychiatry (M.K.), Munich; Department of Neurology (C.W.), Medical Faculty, Heinrich Heine University, Düsseldorf; Department of Neurology (C.W.), University Hospital Cologne; Institute of Neuroimmunology and Multiple Sclerosis (M.A.F), University Medical Centre Hamburg-Eppendorf, Hamburg; NeuroCure Clinical Research Center (F.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin; Berlin Institute of Health and Experimental and Clinical Research Center (F.P.), Max Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin; and Center of Neuroimmunology (B.T.), Philipps-University Marburg; and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Germany
| | - Peter Lichtner
- From the Department of Neurology (C.G., T.F.M.A., A. Keating, B.K., A. Klein, V.P., A. Berthele, B.H.), Klinikum rechts der Isar, School of Medicine, Technical University of Munich; Institute of Human Genetics (P.L.), Helmholtz Zentrum München, Neuherberg; Department of Neurology (R.G.), St. Josef Hospital, Ruhr-University Bochum; Department of Neurology, Focus Program Translational Neurosciences (FTN) and Research Center for Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn2) (F.Z.), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology and Translational Center for Regenerative Medicine (F.T.B.), University of Leipzig; Clinical Neuroimmunology and Neurochemistry (M.S.), Department of Neurology, Hannover Medical School, Hannover; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Department of Neurology (B.W.), University Hospital Heidelberg; Department of Neurology (H.W.), University of Münster; Department of Neurology (A. Bayas), University Hospital Augsburg; Institute of Clinical Neuroimmunology (T.K.), University Hospital and Biomedical Center, Ludwig-Maximilians University Munich; Department of Neurology (U.K.Z.), Neuroimmunological Section, University of Rostock; Department of Neurology (R.A.L.), University Hospital Erlangen; Department of Neurology (R.A.L.), University of Regensburg; Department of Neurology & Stroke and Hertie-Institute for Clinical Brain Research (U.Z.), Eberhard-Karls-Universität Tübingen; Max Planck Institute of Psychiatry (M.K.), Munich; Department of Neurology (C.W.), Medical Faculty, Heinrich Heine University, Düsseldorf; Department of Neurology (C.W.), University Hospital Cologne; Institute of Neuroimmunology and Multiple Sclerosis (M.A.F), University Medical Centre Hamburg-Eppendorf, Hamburg; NeuroCure Clinical Research Center (F.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin; Berlin Institute of Health and Experimental and Clinical Research Center (F.P.), Max Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin; and Center of Neuroimmunology (B.T.), Philipps-University Marburg; and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Germany
| | - Ralf Gold
- From the Department of Neurology (C.G., T.F.M.A., A. Keating, B.K., A. Klein, V.P., A. Berthele, B.H.), Klinikum rechts der Isar, School of Medicine, Technical University of Munich; Institute of Human Genetics (P.L.), Helmholtz Zentrum München, Neuherberg; Department of Neurology (R.G.), St. Josef Hospital, Ruhr-University Bochum; Department of Neurology, Focus Program Translational Neurosciences (FTN) and Research Center for Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn2) (F.Z.), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology and Translational Center for Regenerative Medicine (F.T.B.), University of Leipzig; Clinical Neuroimmunology and Neurochemistry (M.S.), Department of Neurology, Hannover Medical School, Hannover; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Department of Neurology (B.W.), University Hospital Heidelberg; Department of Neurology (H.W.), University of Münster; Department of Neurology (A. Bayas), University Hospital Augsburg; Institute of Clinical Neuroimmunology (T.K.), University Hospital and Biomedical Center, Ludwig-Maximilians University Munich; Department of Neurology (U.K.Z.), Neuroimmunological Section, University of Rostock; Department of Neurology (R.A.L.), University Hospital Erlangen; Department of Neurology (R.A.L.), University of Regensburg; Department of Neurology & Stroke and Hertie-Institute for Clinical Brain Research (U.Z.), Eberhard-Karls-Universität Tübingen; Max Planck Institute of Psychiatry (M.K.), Munich; Department of Neurology (C.W.), Medical Faculty, Heinrich Heine University, Düsseldorf; Department of Neurology (C.W.), University Hospital Cologne; Institute of Neuroimmunology and Multiple Sclerosis (M.A.F), University Medical Centre Hamburg-Eppendorf, Hamburg; NeuroCure Clinical Research Center (F.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin; Berlin Institute of Health and Experimental and Clinical Research Center (F.P.), Max Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin; and Center of Neuroimmunology (B.T.), Philipps-University Marburg; and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Germany
| | - Frauke Zipp
- From the Department of Neurology (C.G., T.F.M.A., A. Keating, B.K., A. Klein, V.P., A. Berthele, B.H.), Klinikum rechts der Isar, School of Medicine, Technical University of Munich; Institute of Human Genetics (P.L.), Helmholtz Zentrum München, Neuherberg; Department of Neurology (R.G.), St. Josef Hospital, Ruhr-University Bochum; Department of Neurology, Focus Program Translational Neurosciences (FTN) and Research Center for Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn2) (F.Z.), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology and Translational Center for Regenerative Medicine (F.T.B.), University of Leipzig; Clinical Neuroimmunology and Neurochemistry (M.S.), Department of Neurology, Hannover Medical School, Hannover; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Department of Neurology (B.W.), University Hospital Heidelberg; Department of Neurology (H.W.), University of Münster; Department of Neurology (A. Bayas), University Hospital Augsburg; Institute of Clinical Neuroimmunology (T.K.), University Hospital and Biomedical Center, Ludwig-Maximilians University Munich; Department of Neurology (U.K.Z.), Neuroimmunological Section, University of Rostock; Department of Neurology (R.A.L.), University Hospital Erlangen; Department of Neurology (R.A.L.), University of Regensburg; Department of Neurology & Stroke and Hertie-Institute for Clinical Brain Research (U.Z.), Eberhard-Karls-Universität Tübingen; Max Planck Institute of Psychiatry (M.K.), Munich; Department of Neurology (C.W.), Medical Faculty, Heinrich Heine University, Düsseldorf; Department of Neurology (C.W.), University Hospital Cologne; Institute of Neuroimmunology and Multiple Sclerosis (M.A.F), University Medical Centre Hamburg-Eppendorf, Hamburg; NeuroCure Clinical Research Center (F.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin; Berlin Institute of Health and Experimental and Clinical Research Center (F.P.), Max Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin; and Center of Neuroimmunology (B.T.), Philipps-University Marburg; and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Germany
| | - Florian Then Bergh
- From the Department of Neurology (C.G., T.F.M.A., A. Keating, B.K., A. Klein, V.P., A. Berthele, B.H.), Klinikum rechts der Isar, School of Medicine, Technical University of Munich; Institute of Human Genetics (P.L.), Helmholtz Zentrum München, Neuherberg; Department of Neurology (R.G.), St. Josef Hospital, Ruhr-University Bochum; Department of Neurology, Focus Program Translational Neurosciences (FTN) and Research Center for Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn2) (F.Z.), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology and Translational Center for Regenerative Medicine (F.T.B.), University of Leipzig; Clinical Neuroimmunology and Neurochemistry (M.S.), Department of Neurology, Hannover Medical School, Hannover; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Department of Neurology (B.W.), University Hospital Heidelberg; Department of Neurology (H.W.), University of Münster; Department of Neurology (A. Bayas), University Hospital Augsburg; Institute of Clinical Neuroimmunology (T.K.), University Hospital and Biomedical Center, Ludwig-Maximilians University Munich; Department of Neurology (U.K.Z.), Neuroimmunological Section, University of Rostock; Department of Neurology (R.A.L.), University Hospital Erlangen; Department of Neurology (R.A.L.), University of Regensburg; Department of Neurology & Stroke and Hertie-Institute for Clinical Brain Research (U.Z.), Eberhard-Karls-Universität Tübingen; Max Planck Institute of Psychiatry (M.K.), Munich; Department of Neurology (C.W.), Medical Faculty, Heinrich Heine University, Düsseldorf; Department of Neurology (C.W.), University Hospital Cologne; Institute of Neuroimmunology and Multiple Sclerosis (M.A.F), University Medical Centre Hamburg-Eppendorf, Hamburg; NeuroCure Clinical Research Center (F.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin; Berlin Institute of Health and Experimental and Clinical Research Center (F.P.), Max Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin; and Center of Neuroimmunology (B.T.), Philipps-University Marburg; and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Germany
| | - Martin Stangel
- From the Department of Neurology (C.G., T.F.M.A., A. Keating, B.K., A. Klein, V.P., A. Berthele, B.H.), Klinikum rechts der Isar, School of Medicine, Technical University of Munich; Institute of Human Genetics (P.L.), Helmholtz Zentrum München, Neuherberg; Department of Neurology (R.G.), St. Josef Hospital, Ruhr-University Bochum; Department of Neurology, Focus Program Translational Neurosciences (FTN) and Research Center for Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn2) (F.Z.), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology and Translational Center for Regenerative Medicine (F.T.B.), University of Leipzig; Clinical Neuroimmunology and Neurochemistry (M.S.), Department of Neurology, Hannover Medical School, Hannover; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Department of Neurology (B.W.), University Hospital Heidelberg; Department of Neurology (H.W.), University of Münster; Department of Neurology (A. Bayas), University Hospital Augsburg; Institute of Clinical Neuroimmunology (T.K.), University Hospital and Biomedical Center, Ludwig-Maximilians University Munich; Department of Neurology (U.K.Z.), Neuroimmunological Section, University of Rostock; Department of Neurology (R.A.L.), University Hospital Erlangen; Department of Neurology (R.A.L.), University of Regensburg; Department of Neurology & Stroke and Hertie-Institute for Clinical Brain Research (U.Z.), Eberhard-Karls-Universität Tübingen; Max Planck Institute of Psychiatry (M.K.), Munich; Department of Neurology (C.W.), Medical Faculty, Heinrich Heine University, Düsseldorf; Department of Neurology (C.W.), University Hospital Cologne; Institute of Neuroimmunology and Multiple Sclerosis (M.A.F), University Medical Centre Hamburg-Eppendorf, Hamburg; NeuroCure Clinical Research Center (F.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin; Berlin Institute of Health and Experimental and Clinical Research Center (F.P.), Max Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin; and Center of Neuroimmunology (B.T.), Philipps-University Marburg; and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Germany
| | - Hayrettin Tumani
- From the Department of Neurology (C.G., T.F.M.A., A. Keating, B.K., A. Klein, V.P., A. Berthele, B.H.), Klinikum rechts der Isar, School of Medicine, Technical University of Munich; Institute of Human Genetics (P.L.), Helmholtz Zentrum München, Neuherberg; Department of Neurology (R.G.), St. Josef Hospital, Ruhr-University Bochum; Department of Neurology, Focus Program Translational Neurosciences (FTN) and Research Center for Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn2) (F.Z.), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology and Translational Center for Regenerative Medicine (F.T.B.), University of Leipzig; Clinical Neuroimmunology and Neurochemistry (M.S.), Department of Neurology, Hannover Medical School, Hannover; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Department of Neurology (B.W.), University Hospital Heidelberg; Department of Neurology (H.W.), University of Münster; Department of Neurology (A. Bayas), University Hospital Augsburg; Institute of Clinical Neuroimmunology (T.K.), University Hospital and Biomedical Center, Ludwig-Maximilians University Munich; Department of Neurology (U.K.Z.), Neuroimmunological Section, University of Rostock; Department of Neurology (R.A.L.), University Hospital Erlangen; Department of Neurology (R.A.L.), University of Regensburg; Department of Neurology & Stroke and Hertie-Institute for Clinical Brain Research (U.Z.), Eberhard-Karls-Universität Tübingen; Max Planck Institute of Psychiatry (M.K.), Munich; Department of Neurology (C.W.), Medical Faculty, Heinrich Heine University, Düsseldorf; Department of Neurology (C.W.), University Hospital Cologne; Institute of Neuroimmunology and Multiple Sclerosis (M.A.F), University Medical Centre Hamburg-Eppendorf, Hamburg; NeuroCure Clinical Research Center (F.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin; Berlin Institute of Health and Experimental and Clinical Research Center (F.P.), Max Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin; and Center of Neuroimmunology (B.T.), Philipps-University Marburg; and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Germany
| | - Brigitte Wildemann
- From the Department of Neurology (C.G., T.F.M.A., A. Keating, B.K., A. Klein, V.P., A. Berthele, B.H.), Klinikum rechts der Isar, School of Medicine, Technical University of Munich; Institute of Human Genetics (P.L.), Helmholtz Zentrum München, Neuherberg; Department of Neurology (R.G.), St. Josef Hospital, Ruhr-University Bochum; Department of Neurology, Focus Program Translational Neurosciences (FTN) and Research Center for Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn2) (F.Z.), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology and Translational Center for Regenerative Medicine (F.T.B.), University of Leipzig; Clinical Neuroimmunology and Neurochemistry (M.S.), Department of Neurology, Hannover Medical School, Hannover; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Department of Neurology (B.W.), University Hospital Heidelberg; Department of Neurology (H.W.), University of Münster; Department of Neurology (A. Bayas), University Hospital Augsburg; Institute of Clinical Neuroimmunology (T.K.), University Hospital and Biomedical Center, Ludwig-Maximilians University Munich; Department of Neurology (U.K.Z.), Neuroimmunological Section, University of Rostock; Department of Neurology (R.A.L.), University Hospital Erlangen; Department of Neurology (R.A.L.), University of Regensburg; Department of Neurology & Stroke and Hertie-Institute for Clinical Brain Research (U.Z.), Eberhard-Karls-Universität Tübingen; Max Planck Institute of Psychiatry (M.K.), Munich; Department of Neurology (C.W.), Medical Faculty, Heinrich Heine University, Düsseldorf; Department of Neurology (C.W.), University Hospital Cologne; Institute of Neuroimmunology and Multiple Sclerosis (M.A.F), University Medical Centre Hamburg-Eppendorf, Hamburg; NeuroCure Clinical Research Center (F.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin; Berlin Institute of Health and Experimental and Clinical Research Center (F.P.), Max Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin; and Center of Neuroimmunology (B.T.), Philipps-University Marburg; and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Germany
| | - Heinz Wiendl
- From the Department of Neurology (C.G., T.F.M.A., A. Keating, B.K., A. Klein, V.P., A. Berthele, B.H.), Klinikum rechts der Isar, School of Medicine, Technical University of Munich; Institute of Human Genetics (P.L.), Helmholtz Zentrum München, Neuherberg; Department of Neurology (R.G.), St. Josef Hospital, Ruhr-University Bochum; Department of Neurology, Focus Program Translational Neurosciences (FTN) and Research Center for Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn2) (F.Z.), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology and Translational Center for Regenerative Medicine (F.T.B.), University of Leipzig; Clinical Neuroimmunology and Neurochemistry (M.S.), Department of Neurology, Hannover Medical School, Hannover; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Department of Neurology (B.W.), University Hospital Heidelberg; Department of Neurology (H.W.), University of Münster; Department of Neurology (A. Bayas), University Hospital Augsburg; Institute of Clinical Neuroimmunology (T.K.), University Hospital and Biomedical Center, Ludwig-Maximilians University Munich; Department of Neurology (U.K.Z.), Neuroimmunological Section, University of Rostock; Department of Neurology (R.A.L.), University Hospital Erlangen; Department of Neurology (R.A.L.), University of Regensburg; Department of Neurology & Stroke and Hertie-Institute for Clinical Brain Research (U.Z.), Eberhard-Karls-Universität Tübingen; Max Planck Institute of Psychiatry (M.K.), Munich; Department of Neurology (C.W.), Medical Faculty, Heinrich Heine University, Düsseldorf; Department of Neurology (C.W.), University Hospital Cologne; Institute of Neuroimmunology and Multiple Sclerosis (M.A.F), University Medical Centre Hamburg-Eppendorf, Hamburg; NeuroCure Clinical Research Center (F.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin; Berlin Institute of Health and Experimental and Clinical Research Center (F.P.), Max Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin; and Center of Neuroimmunology (B.T.), Philipps-University Marburg; and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Germany
| | - Antonios Bayas
- From the Department of Neurology (C.G., T.F.M.A., A. Keating, B.K., A. Klein, V.P., A. Berthele, B.H.), Klinikum rechts der Isar, School of Medicine, Technical University of Munich; Institute of Human Genetics (P.L.), Helmholtz Zentrum München, Neuherberg; Department of Neurology (R.G.), St. Josef Hospital, Ruhr-University Bochum; Department of Neurology, Focus Program Translational Neurosciences (FTN) and Research Center for Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn2) (F.Z.), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology and Translational Center for Regenerative Medicine (F.T.B.), University of Leipzig; Clinical Neuroimmunology and Neurochemistry (M.S.), Department of Neurology, Hannover Medical School, Hannover; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Department of Neurology (B.W.), University Hospital Heidelberg; Department of Neurology (H.W.), University of Münster; Department of Neurology (A. Bayas), University Hospital Augsburg; Institute of Clinical Neuroimmunology (T.K.), University Hospital and Biomedical Center, Ludwig-Maximilians University Munich; Department of Neurology (U.K.Z.), Neuroimmunological Section, University of Rostock; Department of Neurology (R.A.L.), University Hospital Erlangen; Department of Neurology (R.A.L.), University of Regensburg; Department of Neurology & Stroke and Hertie-Institute for Clinical Brain Research (U.Z.), Eberhard-Karls-Universität Tübingen; Max Planck Institute of Psychiatry (M.K.), Munich; Department of Neurology (C.W.), Medical Faculty, Heinrich Heine University, Düsseldorf; Department of Neurology (C.W.), University Hospital Cologne; Institute of Neuroimmunology and Multiple Sclerosis (M.A.F), University Medical Centre Hamburg-Eppendorf, Hamburg; NeuroCure Clinical Research Center (F.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin; Berlin Institute of Health and Experimental and Clinical Research Center (F.P.), Max Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin; and Center of Neuroimmunology (B.T.), Philipps-University Marburg; and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Germany
| | - Tania Kümpfel
- From the Department of Neurology (C.G., T.F.M.A., A. Keating, B.K., A. Klein, V.P., A. Berthele, B.H.), Klinikum rechts der Isar, School of Medicine, Technical University of Munich; Institute of Human Genetics (P.L.), Helmholtz Zentrum München, Neuherberg; Department of Neurology (R.G.), St. Josef Hospital, Ruhr-University Bochum; Department of Neurology, Focus Program Translational Neurosciences (FTN) and Research Center for Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn2) (F.Z.), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology and Translational Center for Regenerative Medicine (F.T.B.), University of Leipzig; Clinical Neuroimmunology and Neurochemistry (M.S.), Department of Neurology, Hannover Medical School, Hannover; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Department of Neurology (B.W.), University Hospital Heidelberg; Department of Neurology (H.W.), University of Münster; Department of Neurology (A. Bayas), University Hospital Augsburg; Institute of Clinical Neuroimmunology (T.K.), University Hospital and Biomedical Center, Ludwig-Maximilians University Munich; Department of Neurology (U.K.Z.), Neuroimmunological Section, University of Rostock; Department of Neurology (R.A.L.), University Hospital Erlangen; Department of Neurology (R.A.L.), University of Regensburg; Department of Neurology & Stroke and Hertie-Institute for Clinical Brain Research (U.Z.), Eberhard-Karls-Universität Tübingen; Max Planck Institute of Psychiatry (M.K.), Munich; Department of Neurology (C.W.), Medical Faculty, Heinrich Heine University, Düsseldorf; Department of Neurology (C.W.), University Hospital Cologne; Institute of Neuroimmunology and Multiple Sclerosis (M.A.F), University Medical Centre Hamburg-Eppendorf, Hamburg; NeuroCure Clinical Research Center (F.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin; Berlin Institute of Health and Experimental and Clinical Research Center (F.P.), Max Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin; and Center of Neuroimmunology (B.T.), Philipps-University Marburg; and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Germany
| | - Uwe K Zettl
- From the Department of Neurology (C.G., T.F.M.A., A. Keating, B.K., A. Klein, V.P., A. Berthele, B.H.), Klinikum rechts der Isar, School of Medicine, Technical University of Munich; Institute of Human Genetics (P.L.), Helmholtz Zentrum München, Neuherberg; Department of Neurology (R.G.), St. Josef Hospital, Ruhr-University Bochum; Department of Neurology, Focus Program Translational Neurosciences (FTN) and Research Center for Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn2) (F.Z.), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology and Translational Center for Regenerative Medicine (F.T.B.), University of Leipzig; Clinical Neuroimmunology and Neurochemistry (M.S.), Department of Neurology, Hannover Medical School, Hannover; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Department of Neurology (B.W.), University Hospital Heidelberg; Department of Neurology (H.W.), University of Münster; Department of Neurology (A. Bayas), University Hospital Augsburg; Institute of Clinical Neuroimmunology (T.K.), University Hospital and Biomedical Center, Ludwig-Maximilians University Munich; Department of Neurology (U.K.Z.), Neuroimmunological Section, University of Rostock; Department of Neurology (R.A.L.), University Hospital Erlangen; Department of Neurology (R.A.L.), University of Regensburg; Department of Neurology & Stroke and Hertie-Institute for Clinical Brain Research (U.Z.), Eberhard-Karls-Universität Tübingen; Max Planck Institute of Psychiatry (M.K.), Munich; Department of Neurology (C.W.), Medical Faculty, Heinrich Heine University, Düsseldorf; Department of Neurology (C.W.), University Hospital Cologne; Institute of Neuroimmunology and Multiple Sclerosis (M.A.F), University Medical Centre Hamburg-Eppendorf, Hamburg; NeuroCure Clinical Research Center (F.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin; Berlin Institute of Health and Experimental and Clinical Research Center (F.P.), Max Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin; and Center of Neuroimmunology (B.T.), Philipps-University Marburg; and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Germany
| | - Ralf A Linker
- From the Department of Neurology (C.G., T.F.M.A., A. Keating, B.K., A. Klein, V.P., A. Berthele, B.H.), Klinikum rechts der Isar, School of Medicine, Technical University of Munich; Institute of Human Genetics (P.L.), Helmholtz Zentrum München, Neuherberg; Department of Neurology (R.G.), St. Josef Hospital, Ruhr-University Bochum; Department of Neurology, Focus Program Translational Neurosciences (FTN) and Research Center for Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn2) (F.Z.), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology and Translational Center for Regenerative Medicine (F.T.B.), University of Leipzig; Clinical Neuroimmunology and Neurochemistry (M.S.), Department of Neurology, Hannover Medical School, Hannover; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Department of Neurology (B.W.), University Hospital Heidelberg; Department of Neurology (H.W.), University of Münster; Department of Neurology (A. Bayas), University Hospital Augsburg; Institute of Clinical Neuroimmunology (T.K.), University Hospital and Biomedical Center, Ludwig-Maximilians University Munich; Department of Neurology (U.K.Z.), Neuroimmunological Section, University of Rostock; Department of Neurology (R.A.L.), University Hospital Erlangen; Department of Neurology (R.A.L.), University of Regensburg; Department of Neurology & Stroke and Hertie-Institute for Clinical Brain Research (U.Z.), Eberhard-Karls-Universität Tübingen; Max Planck Institute of Psychiatry (M.K.), Munich; Department of Neurology (C.W.), Medical Faculty, Heinrich Heine University, Düsseldorf; Department of Neurology (C.W.), University Hospital Cologne; Institute of Neuroimmunology and Multiple Sclerosis (M.A.F), University Medical Centre Hamburg-Eppendorf, Hamburg; NeuroCure Clinical Research Center (F.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin; Berlin Institute of Health and Experimental and Clinical Research Center (F.P.), Max Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin; and Center of Neuroimmunology (B.T.), Philipps-University Marburg; and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Germany
| | - Ulf Ziemann
- From the Department of Neurology (C.G., T.F.M.A., A. Keating, B.K., A. Klein, V.P., A. Berthele, B.H.), Klinikum rechts der Isar, School of Medicine, Technical University of Munich; Institute of Human Genetics (P.L.), Helmholtz Zentrum München, Neuherberg; Department of Neurology (R.G.), St. Josef Hospital, Ruhr-University Bochum; Department of Neurology, Focus Program Translational Neurosciences (FTN) and Research Center for Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn2) (F.Z.), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology and Translational Center for Regenerative Medicine (F.T.B.), University of Leipzig; Clinical Neuroimmunology and Neurochemistry (M.S.), Department of Neurology, Hannover Medical School, Hannover; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Department of Neurology (B.W.), University Hospital Heidelberg; Department of Neurology (H.W.), University of Münster; Department of Neurology (A. Bayas), University Hospital Augsburg; Institute of Clinical Neuroimmunology (T.K.), University Hospital and Biomedical Center, Ludwig-Maximilians University Munich; Department of Neurology (U.K.Z.), Neuroimmunological Section, University of Rostock; Department of Neurology (R.A.L.), University Hospital Erlangen; Department of Neurology (R.A.L.), University of Regensburg; Department of Neurology & Stroke and Hertie-Institute for Clinical Brain Research (U.Z.), Eberhard-Karls-Universität Tübingen; Max Planck Institute of Psychiatry (M.K.), Munich; Department of Neurology (C.W.), Medical Faculty, Heinrich Heine University, Düsseldorf; Department of Neurology (C.W.), University Hospital Cologne; Institute of Neuroimmunology and Multiple Sclerosis (M.A.F), University Medical Centre Hamburg-Eppendorf, Hamburg; NeuroCure Clinical Research Center (F.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin; Berlin Institute of Health and Experimental and Clinical Research Center (F.P.), Max Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin; and Center of Neuroimmunology (B.T.), Philipps-University Marburg; and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Germany
| | - Matthias Knop
- From the Department of Neurology (C.G., T.F.M.A., A. Keating, B.K., A. Klein, V.P., A. Berthele, B.H.), Klinikum rechts der Isar, School of Medicine, Technical University of Munich; Institute of Human Genetics (P.L.), Helmholtz Zentrum München, Neuherberg; Department of Neurology (R.G.), St. Josef Hospital, Ruhr-University Bochum; Department of Neurology, Focus Program Translational Neurosciences (FTN) and Research Center for Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn2) (F.Z.), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology and Translational Center for Regenerative Medicine (F.T.B.), University of Leipzig; Clinical Neuroimmunology and Neurochemistry (M.S.), Department of Neurology, Hannover Medical School, Hannover; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Department of Neurology (B.W.), University Hospital Heidelberg; Department of Neurology (H.W.), University of Münster; Department of Neurology (A. Bayas), University Hospital Augsburg; Institute of Clinical Neuroimmunology (T.K.), University Hospital and Biomedical Center, Ludwig-Maximilians University Munich; Department of Neurology (U.K.Z.), Neuroimmunological Section, University of Rostock; Department of Neurology (R.A.L.), University Hospital Erlangen; Department of Neurology (R.A.L.), University of Regensburg; Department of Neurology & Stroke and Hertie-Institute for Clinical Brain Research (U.Z.), Eberhard-Karls-Universität Tübingen; Max Planck Institute of Psychiatry (M.K.), Munich; Department of Neurology (C.W.), Medical Faculty, Heinrich Heine University, Düsseldorf; Department of Neurology (C.W.), University Hospital Cologne; Institute of Neuroimmunology and Multiple Sclerosis (M.A.F), University Medical Centre Hamburg-Eppendorf, Hamburg; NeuroCure Clinical Research Center (F.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin; Berlin Institute of Health and Experimental and Clinical Research Center (F.P.), Max Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin; and Center of Neuroimmunology (B.T.), Philipps-University Marburg; and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Germany
| | - Clemens Warnke
- From the Department of Neurology (C.G., T.F.M.A., A. Keating, B.K., A. Klein, V.P., A. Berthele, B.H.), Klinikum rechts der Isar, School of Medicine, Technical University of Munich; Institute of Human Genetics (P.L.), Helmholtz Zentrum München, Neuherberg; Department of Neurology (R.G.), St. Josef Hospital, Ruhr-University Bochum; Department of Neurology, Focus Program Translational Neurosciences (FTN) and Research Center for Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn2) (F.Z.), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology and Translational Center for Regenerative Medicine (F.T.B.), University of Leipzig; Clinical Neuroimmunology and Neurochemistry (M.S.), Department of Neurology, Hannover Medical School, Hannover; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Department of Neurology (B.W.), University Hospital Heidelberg; Department of Neurology (H.W.), University of Münster; Department of Neurology (A. Bayas), University Hospital Augsburg; Institute of Clinical Neuroimmunology (T.K.), University Hospital and Biomedical Center, Ludwig-Maximilians University Munich; Department of Neurology (U.K.Z.), Neuroimmunological Section, University of Rostock; Department of Neurology (R.A.L.), University Hospital Erlangen; Department of Neurology (R.A.L.), University of Regensburg; Department of Neurology & Stroke and Hertie-Institute for Clinical Brain Research (U.Z.), Eberhard-Karls-Universität Tübingen; Max Planck Institute of Psychiatry (M.K.), Munich; Department of Neurology (C.W.), Medical Faculty, Heinrich Heine University, Düsseldorf; Department of Neurology (C.W.), University Hospital Cologne; Institute of Neuroimmunology and Multiple Sclerosis (M.A.F), University Medical Centre Hamburg-Eppendorf, Hamburg; NeuroCure Clinical Research Center (F.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin; Berlin Institute of Health and Experimental and Clinical Research Center (F.P.), Max Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin; and Center of Neuroimmunology (B.T.), Philipps-University Marburg; and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Germany
| | - Manuel A Friese
- From the Department of Neurology (C.G., T.F.M.A., A. Keating, B.K., A. Klein, V.P., A. Berthele, B.H.), Klinikum rechts der Isar, School of Medicine, Technical University of Munich; Institute of Human Genetics (P.L.), Helmholtz Zentrum München, Neuherberg; Department of Neurology (R.G.), St. Josef Hospital, Ruhr-University Bochum; Department of Neurology, Focus Program Translational Neurosciences (FTN) and Research Center for Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn2) (F.Z.), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology and Translational Center for Regenerative Medicine (F.T.B.), University of Leipzig; Clinical Neuroimmunology and Neurochemistry (M.S.), Department of Neurology, Hannover Medical School, Hannover; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Department of Neurology (B.W.), University Hospital Heidelberg; Department of Neurology (H.W.), University of Münster; Department of Neurology (A. Bayas), University Hospital Augsburg; Institute of Clinical Neuroimmunology (T.K.), University Hospital and Biomedical Center, Ludwig-Maximilians University Munich; Department of Neurology (U.K.Z.), Neuroimmunological Section, University of Rostock; Department of Neurology (R.A.L.), University Hospital Erlangen; Department of Neurology (R.A.L.), University of Regensburg; Department of Neurology & Stroke and Hertie-Institute for Clinical Brain Research (U.Z.), Eberhard-Karls-Universität Tübingen; Max Planck Institute of Psychiatry (M.K.), Munich; Department of Neurology (C.W.), Medical Faculty, Heinrich Heine University, Düsseldorf; Department of Neurology (C.W.), University Hospital Cologne; Institute of Neuroimmunology and Multiple Sclerosis (M.A.F), University Medical Centre Hamburg-Eppendorf, Hamburg; NeuroCure Clinical Research Center (F.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin; Berlin Institute of Health and Experimental and Clinical Research Center (F.P.), Max Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin; and Center of Neuroimmunology (B.T.), Philipps-University Marburg; and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Germany
| | - Friedemann Paul
- From the Department of Neurology (C.G., T.F.M.A., A. Keating, B.K., A. Klein, V.P., A. Berthele, B.H.), Klinikum rechts der Isar, School of Medicine, Technical University of Munich; Institute of Human Genetics (P.L.), Helmholtz Zentrum München, Neuherberg; Department of Neurology (R.G.), St. Josef Hospital, Ruhr-University Bochum; Department of Neurology, Focus Program Translational Neurosciences (FTN) and Research Center for Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn2) (F.Z.), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology and Translational Center for Regenerative Medicine (F.T.B.), University of Leipzig; Clinical Neuroimmunology and Neurochemistry (M.S.), Department of Neurology, Hannover Medical School, Hannover; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Department of Neurology (B.W.), University Hospital Heidelberg; Department of Neurology (H.W.), University of Münster; Department of Neurology (A. Bayas), University Hospital Augsburg; Institute of Clinical Neuroimmunology (T.K.), University Hospital and Biomedical Center, Ludwig-Maximilians University Munich; Department of Neurology (U.K.Z.), Neuroimmunological Section, University of Rostock; Department of Neurology (R.A.L.), University Hospital Erlangen; Department of Neurology (R.A.L.), University of Regensburg; Department of Neurology & Stroke and Hertie-Institute for Clinical Brain Research (U.Z.), Eberhard-Karls-Universität Tübingen; Max Planck Institute of Psychiatry (M.K.), Munich; Department of Neurology (C.W.), Medical Faculty, Heinrich Heine University, Düsseldorf; Department of Neurology (C.W.), University Hospital Cologne; Institute of Neuroimmunology and Multiple Sclerosis (M.A.F), University Medical Centre Hamburg-Eppendorf, Hamburg; NeuroCure Clinical Research Center (F.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin; Berlin Institute of Health and Experimental and Clinical Research Center (F.P.), Max Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin; and Center of Neuroimmunology (B.T.), Philipps-University Marburg; and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Germany
| | - Björn Tackenberg
- From the Department of Neurology (C.G., T.F.M.A., A. Keating, B.K., A. Klein, V.P., A. Berthele, B.H.), Klinikum rechts der Isar, School of Medicine, Technical University of Munich; Institute of Human Genetics (P.L.), Helmholtz Zentrum München, Neuherberg; Department of Neurology (R.G.), St. Josef Hospital, Ruhr-University Bochum; Department of Neurology, Focus Program Translational Neurosciences (FTN) and Research Center for Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn2) (F.Z.), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology and Translational Center for Regenerative Medicine (F.T.B.), University of Leipzig; Clinical Neuroimmunology and Neurochemistry (M.S.), Department of Neurology, Hannover Medical School, Hannover; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Department of Neurology (B.W.), University Hospital Heidelberg; Department of Neurology (H.W.), University of Münster; Department of Neurology (A. Bayas), University Hospital Augsburg; Institute of Clinical Neuroimmunology (T.K.), University Hospital and Biomedical Center, Ludwig-Maximilians University Munich; Department of Neurology (U.K.Z.), Neuroimmunological Section, University of Rostock; Department of Neurology (R.A.L.), University Hospital Erlangen; Department of Neurology (R.A.L.), University of Regensburg; Department of Neurology & Stroke and Hertie-Institute for Clinical Brain Research (U.Z.), Eberhard-Karls-Universität Tübingen; Max Planck Institute of Psychiatry (M.K.), Munich; Department of Neurology (C.W.), Medical Faculty, Heinrich Heine University, Düsseldorf; Department of Neurology (C.W.), University Hospital Cologne; Institute of Neuroimmunology and Multiple Sclerosis (M.A.F), University Medical Centre Hamburg-Eppendorf, Hamburg; NeuroCure Clinical Research Center (F.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin; Berlin Institute of Health and Experimental and Clinical Research Center (F.P.), Max Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin; and Center of Neuroimmunology (B.T.), Philipps-University Marburg; and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Germany
| | - Achim Berthele
- From the Department of Neurology (C.G., T.F.M.A., A. Keating, B.K., A. Klein, V.P., A. Berthele, B.H.), Klinikum rechts der Isar, School of Medicine, Technical University of Munich; Institute of Human Genetics (P.L.), Helmholtz Zentrum München, Neuherberg; Department of Neurology (R.G.), St. Josef Hospital, Ruhr-University Bochum; Department of Neurology, Focus Program Translational Neurosciences (FTN) and Research Center for Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn2) (F.Z.), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology and Translational Center for Regenerative Medicine (F.T.B.), University of Leipzig; Clinical Neuroimmunology and Neurochemistry (M.S.), Department of Neurology, Hannover Medical School, Hannover; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Department of Neurology (B.W.), University Hospital Heidelberg; Department of Neurology (H.W.), University of Münster; Department of Neurology (A. Bayas), University Hospital Augsburg; Institute of Clinical Neuroimmunology (T.K.), University Hospital and Biomedical Center, Ludwig-Maximilians University Munich; Department of Neurology (U.K.Z.), Neuroimmunological Section, University of Rostock; Department of Neurology (R.A.L.), University Hospital Erlangen; Department of Neurology (R.A.L.), University of Regensburg; Department of Neurology & Stroke and Hertie-Institute for Clinical Brain Research (U.Z.), Eberhard-Karls-Universität Tübingen; Max Planck Institute of Psychiatry (M.K.), Munich; Department of Neurology (C.W.), Medical Faculty, Heinrich Heine University, Düsseldorf; Department of Neurology (C.W.), University Hospital Cologne; Institute of Neuroimmunology and Multiple Sclerosis (M.A.F), University Medical Centre Hamburg-Eppendorf, Hamburg; NeuroCure Clinical Research Center (F.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin; Berlin Institute of Health and Experimental and Clinical Research Center (F.P.), Max Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin; and Center of Neuroimmunology (B.T.), Philipps-University Marburg; and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Germany
| | - Bernhard Hemmer
- From the Department of Neurology (C.G., T.F.M.A., A. Keating, B.K., A. Klein, V.P., A. Berthele, B.H.), Klinikum rechts der Isar, School of Medicine, Technical University of Munich; Institute of Human Genetics (P.L.), Helmholtz Zentrum München, Neuherberg; Department of Neurology (R.G.), St. Josef Hospital, Ruhr-University Bochum; Department of Neurology, Focus Program Translational Neurosciences (FTN) and Research Center for Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn2) (F.Z.), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology and Translational Center for Regenerative Medicine (F.T.B.), University of Leipzig; Clinical Neuroimmunology and Neurochemistry (M.S.), Department of Neurology, Hannover Medical School, Hannover; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Department of Neurology (B.W.), University Hospital Heidelberg; Department of Neurology (H.W.), University of Münster; Department of Neurology (A. Bayas), University Hospital Augsburg; Institute of Clinical Neuroimmunology (T.K.), University Hospital and Biomedical Center, Ludwig-Maximilians University Munich; Department of Neurology (U.K.Z.), Neuroimmunological Section, University of Rostock; Department of Neurology (R.A.L.), University Hospital Erlangen; Department of Neurology (R.A.L.), University of Regensburg; Department of Neurology & Stroke and Hertie-Institute for Clinical Brain Research (U.Z.), Eberhard-Karls-Universität Tübingen; Max Planck Institute of Psychiatry (M.K.), Munich; Department of Neurology (C.W.), Medical Faculty, Heinrich Heine University, Düsseldorf; Department of Neurology (C.W.), University Hospital Cologne; Institute of Neuroimmunology and Multiple Sclerosis (M.A.F), University Medical Centre Hamburg-Eppendorf, Hamburg; NeuroCure Clinical Research Center (F.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin; Berlin Institute of Health and Experimental and Clinical Research Center (F.P.), Max Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin; and Center of Neuroimmunology (B.T.), Philipps-University Marburg; and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Germany.
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Vogel I, Blanshard RC, Hoffmann ER. SureTypeSC-a Random Forest and Gaussian mixture predictor of high confidence genotypes in single-cell data. Bioinformatics 2020; 35:5055-5062. [PMID: 31116387 DOI: 10.1093/bioinformatics/btz412] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2018] [Revised: 04/08/2019] [Accepted: 05/21/2019] [Indexed: 11/12/2022] Open
Abstract
MOTIVATION Accurate genotyping of DNA from a single cell is required for applications such as de novo mutation detection, linkage analysis and lineage tracing. However, achieving high precision genotyping in the single-cell environment is challenging due to the errors caused by whole-genome amplification. Two factors make genotyping from single cells using single nucleotide polymorphism (SNP) arrays challenging. The lack of a comprehensive single-cell dataset with a reference genotype and the absence of genotyping tools specifically designed to detect noise from the whole-genome amplification step. Algorithms designed for bulk DNA genotyping cause significant data loss when used for single-cell applications. RESULTS In this study, we have created a resource of 28.7 million SNPs, typed at high confidence from whole-genome amplified DNA from single cells using the Illumina SNP bead array technology. The resource is generated from 104 single cells from two cell lines that are available from the Coriell repository. We used mother-father-proband (trio) information from multiple technical replicates of bulk DNA to establish a high quality reference genotype for the two cell lines on the SNP array. This enabled us to develop SureTypeSC-a two-stage machine learning algorithm that filters a substantial part of the noise, thereby retaining the majority of the high quality SNPs. SureTypeSC also provides a simple statistical output to show the confidence of a particular single-cell genotype using Bayesian statistics. AVAILABILITY AND IMPLEMENTATION The implementation of SureTypeSC in Python and sample data are available in the GitHub repository: https://github.com/puko818/SureTypeSC. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Ivan Vogel
- DNRF Center for Chromosome Stability, Department of Cellular and Molecular Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen N, Denmark.,Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic
| | - Robert C Blanshard
- Illumina Cambridge Ltd., Fulbourn, UK.,Genome Damage and Stability Centre, School of Life Sciences, University of Sussex, Brighton, UK
| | - Eva R Hoffmann
- DNRF Center for Chromosome Stability, Department of Cellular and Molecular Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen N, Denmark.,Genome Damage and Stability Centre, School of Life Sciences, University of Sussex, Brighton, UK
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19
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Longitudinal association of a body mass index (BMI) genetic risk score with growth and BMI changes across the life course: The Cardiovascular Risk in Young Finns Study. Int J Obes (Lond) 2020; 44:1733-1742. [PMID: 32494039 DOI: 10.1038/s41366-020-0611-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Revised: 03/27/2020] [Accepted: 05/20/2020] [Indexed: 01/06/2023]
Abstract
BACKGROUND The role of genetic risk scores associated with adult body mass index (BMI) on BMI levels across the life course is unclear. We examined if a 97 single nucleotide polymorphism weighted genetic risk score (wGRS97) associated with age-related progression in BMI at different life stages and distinct developmental trajectories of BMI across the early life course. METHODS 2188 Cardiovascular Risk in Young Finns Study participants born pre-1980 who had genotype data and objective measurements of height and weight collected up to 8 times from age 6 to 49 years. Associations were examined using Individual Growth Curve analysis, Latent Class Growth Mixture Modelling, and Poisson modified regression. RESULTS The wGRS97 associated with BMI from age 6 years with peak effect sizes observed at age 30 years (females: 1.14 kg/m2; males: 1.09 kg/m2 higher BMI per standard deviation increase in wGRS97). The association between wGRS97 and BMI became stronger with age in childhood but slowed in adolescence, especially in females, and weakened at age 35-40 years. A higher wGRS97 associated with an increased BMI velocity in childhood and adulthood, but not with BMI change in adulthood. Compared with belonging to a 'normal stable' life-course trajectory group (normal BMI from childhood to adulthood), a one standard deviation higher wGRS97 associated with a 13-127% increased risk of belonging to a less favourable life-course BMI trajectory group. CONCLUSIONS Individuals with genetic susceptibility to higher adult BMI have higher levels and accelerated rates of increase in BMI in childhood/adolescence, and are at increased risk of having a less favourable life-course BMI trajectory.
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20
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Gzara C, Dallmann-Sauer M, Orlova M, Van Thuc N, Thai VH, Fava VM, Bihoreau MT, Boland A, Abel L, Alcaïs A, Schurr E, Cobat A. Family-based genome-wide association study of leprosy in Vietnam. PLoS Pathog 2020; 16:e1008565. [PMID: 32421744 PMCID: PMC7259797 DOI: 10.1371/journal.ppat.1008565] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2020] [Revised: 05/29/2020] [Accepted: 04/20/2020] [Indexed: 12/14/2022] Open
Abstract
Leprosy is a chronic infectious disease of the skin and peripheral nerves with a strong genetic predisposition. Recent genome-wide approaches have identified numerous common variants associated with leprosy, almost all in the Chinese population. We conducted the first family-based genome-wide association study of leprosy in 622 affected offspring from Vietnam, followed by replication in an independent sample of 1181 leprosy cases and 668 controls of the same ethnic origin. The most significant results were observed within the HLA region, in which six SNPs displayed genome-wide significant associations, all of which were replicated in the independent case/control sample. We investigated the signal in the HLA region in more detail, by conducting a multivariate analysis on the case/control sample of 319 GWAS-suggestive HLA hits for which evidence for replication was obtained. We identified three independently associated SNPs, two located in the HLA class I region (rs1265048: OR = 0.69 [0.58-0.80], combined p-value = 5.53x10-11; and rs114598080: OR = 1.47 [1.46-1.48], combined p-value = 8.77x10-13), and one located in the HLA class II region (rs3187964 (OR = 1.67 [1.55-1.80], combined p-value = 8.35x10-16). We also validated two previously identified risk factors for leprosy: the missense variant rs3764147 in the LACC1 gene (OR = 1.52 [1.41-1.63], combined p-value = 5.06x10-14), and the intergenic variant rs6871626 located close to the IL12B gene (OR = 0.73 [0.61-0.84], combined p-value = 6.44x10-8). These results shed new light on the genetic control of leprosy, by dissecting the influence of HLA SNPs, and validating the independent role of two additional variants in a large Vietnamese sample.
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Affiliation(s)
- Chaima Gzara
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM UMR1163, Paris, France
- Université de Paris, Imagine Institute, Paris, France
| | - Monica Dallmann-Sauer
- McGill International TB Centre, Montreal, QC, Canada
- Program in Infectious Diseases and Immunity in Global Health, The Research Institute of the McGill University Health Centre, Montreal, QC, Canada
- Department of Medicine and Human Genetics, Faculty of Medicine, McGill University, Montreal, QC, Canada
| | - Marianna Orlova
- McGill International TB Centre, Montreal, QC, Canada
- Program in Infectious Diseases and Immunity in Global Health, The Research Institute of the McGill University Health Centre, Montreal, QC, Canada
- Department of Medicine and Human Genetics, Faculty of Medicine, McGill University, Montreal, QC, Canada
| | - Nguyen Van Thuc
- Hospital for Dermato-Venereology, District, Ho Chi Minh City, Vietnam
| | - Vu Hong Thai
- Hospital for Dermato-Venereology, District, Ho Chi Minh City, Vietnam
| | - Vinicius M. Fava
- McGill International TB Centre, Montreal, QC, Canada
- Program in Infectious Diseases and Immunity in Global Health, The Research Institute of the McGill University Health Centre, Montreal, QC, Canada
| | - Marie-Thérèse Bihoreau
- Université Paris-Saclay, CEA, Centre National de Recherche en Génomique Humaine, Evry, France
| | - Anne Boland
- Université Paris-Saclay, CEA, Centre National de Recherche en Génomique Humaine, Evry, France
| | - Laurent Abel
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM UMR1163, Paris, France
- Université de Paris, Imagine Institute, Paris, France
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, United States of America
| | - Alexandre Alcaïs
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM UMR1163, Paris, France
- Université de Paris, Imagine Institute, Paris, France
| | - Erwin Schurr
- McGill International TB Centre, Montreal, QC, Canada
- Program in Infectious Diseases and Immunity in Global Health, The Research Institute of the McGill University Health Centre, Montreal, QC, Canada
- Department of Medicine and Human Genetics, Faculty of Medicine, McGill University, Montreal, QC, Canada
| | - Aurélie Cobat
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM UMR1163, Paris, France
- Université de Paris, Imagine Institute, Paris, France
- * E-mail:
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21
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Kari JT, Viinikainen J, Böckerman P, Tammelin TH, Pitkänen N, Lehtimäki T, Pahkala K, Hirvensalo M, Raitakari OT, Pehkonen J. Education leads to a more physically active lifestyle: Evidence based on Mendelian randomization. Scand J Med Sci Sports 2020; 30:1194-1204. [PMID: 32176397 DOI: 10.1111/sms.13653] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Revised: 02/14/2020] [Accepted: 03/05/2020] [Indexed: 12/14/2022]
Abstract
Physical inactivity is a major health risk worldwide. Observational studies suggest that higher education is positively related to physical activity, but it is not clear whether this relationship constitutes a causal effect. Using participants (N = 1651) drawn from the Cardiovascular Risk in Young Finns Study linked to nationwide administrative data from Statistics Finland, this study examined whether educational attainment, measured by years of education, is related to adulthood physical activity in terms of overall physical activity, weekly hours of intensive activity, total steps per day, and aerobic steps per day. We employed ordinary least squares (OLS) models and extended the analysis using an instrumental variables approach (Mendelian randomization, MR) with a genetic risk score as an instrument for years of education. Based on the MR results, it was found that years of education is positively related to physical activity. On average, one additional year of education leads to a 0.62-unit higher overall physical activity (P < .01), 0.26 more hours of weekly intensive activity (P < .05), 560 more steps per day (P < .10), and 390 more aerobic steps per day (P < .09). The findings indicate that education may be a factor leading to higher leisure-time physical activity and thus promoting global health.
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Affiliation(s)
- Jaana T Kari
- Jyväskylä University School of Business and Economics, University of Jyväskylä, Jyväskylä, Finland
| | - Jutta Viinikainen
- Jyväskylä University School of Business and Economics, University of Jyväskylä, Jyväskylä, Finland
| | - Petri Böckerman
- Jyväskylä University School of Business and Economics, University of Jyväskylä, Jyväskylä, Finland.,Labour Institute for Economic Research, Helsinki, Finland.,IZA Institute of Labor Economics, Bonn, Germany
| | - Tuija H Tammelin
- LIKES Research Centre for Physical Activity and Health, Jyväskylä, Finland
| | - Niina Pitkänen
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland.,Centre for Population Health Research, Turku University Hospital, University of Turku, Turku, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and Faculty of Medicine and Health Technology, Finnish Cardiovascular Research Center - Tampere, Tampere University, Tampere, Finland
| | - Katja Pahkala
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland.,Centre for Population Health Research, Turku University Hospital, University of Turku, Turku, Finland.,Paavo Nurmi Centre, Sports & Exercise Medicine Unit, Department of Physical Activity and Health, Turku, Finland
| | - Mirja Hirvensalo
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Olli T Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland.,Centre for Population Health Research, Turku University Hospital, University of Turku, Turku, Finland.,Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Jaakko Pehkonen
- Jyväskylä University School of Business and Economics, University of Jyväskylä, Jyväskylä, Finland
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22
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Insights into malaria susceptibility using genome-wide data on 17,000 individuals from Africa, Asia and Oceania. Nat Commun 2019; 10:5732. [PMID: 31844061 PMCID: PMC6914791 DOI: 10.1038/s41467-019-13480-z] [Citation(s) in RCA: 92] [Impact Index Per Article: 18.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Accepted: 11/11/2019] [Indexed: 12/31/2022] Open
Abstract
The human genetic factors that affect resistance to infectious disease are poorly understood. Here we report a genome-wide association study in 17,000 severe malaria cases and population controls from 11 countries, informed by sequencing of family trios and by direct typing of candidate loci in an additional 15,000 samples. We identify five replicable associations with genome-wide levels of evidence including a newly implicated variant on chromosome 6. Jointly, these variants account for around one-tenth of the heritability of severe malaria, which we estimate as ~23% using genome-wide genotypes. We interrogate available functional data and discover an erythroid-specific transcription start site underlying the known association in ATP2B4, but are unable to identify a likely causal mechanism at the chromosome 6 locus. Previously reported HLA associations do not replicate in these samples. This large dataset will provide a foundation for further research on the genetic determinants of malaria resistance in diverse populations. Four genome-wide associated loci are currently known for malaria susceptibility. Here, the authors expand on earlier work by combining data from 11 malaria-endemic countries and additional population sequencing informing an African-enriched imputation reference panel, with findings including a previously unreported association on chromosome 6.
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23
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Nath AP, Ritchie SC, Grinberg NF, Tang HHF, Huang QQ, Teo SM, Ahola-Olli AV, Würtz P, Havulinna AS, Santalahti K, Pitkänen N, Lehtimäki T, Kähönen M, Lyytikäinen LP, Raitoharju E, Seppälä I, Sarin AP, Ripatti S, Palotie A, Perola M, Viikari JS, Jalkanen S, Maksimow M, Salmi M, Wallace C, Raitakari OT, Salomaa V, Abraham G, Kettunen J, Inouye M. Multivariate Genome-wide Association Analysis of a Cytokine Network Reveals Variants with Widespread Immune, Haematological, and Cardiometabolic Pleiotropy. Am J Hum Genet 2019; 105:1076-1090. [PMID: 31679650 DOI: 10.1016/j.ajhg.2019.10.001] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2019] [Accepted: 09/30/2019] [Indexed: 01/18/2023] Open
Abstract
Cytokines are essential regulatory components of the immune system, and their aberrant levels have been linked to many disease states. Despite increasing evidence that cytokines operate in concert, many of the physiological interactions between cytokines, and the shared genetic architecture that underlies them, remain unknown. Here, we aimed to identify and characterize genetic variants with pleiotropic effects on cytokines. Using three population-based cohorts (n = 9,263), we performed multivariate genome-wide association studies (GWAS) for a correlation network of 11 circulating cytokines, then combined our results in meta-analysis. We identified a total of eight loci significantly associated with the cytokine network, of which two (PDGFRB and ABO) had not been detected previously. In addition, conditional analyses revealed a further four secondary signals at three known cytokine loci. Integration, through the use of Bayesian colocalization analysis, of publicly available GWAS summary statistics with the cytokine network associations revealed shared causal variants between the eight cytokine loci and other traits; in particular, cytokine network variants at the ABO, SERPINE2, and ZFPM2 loci showed pleiotropic effects on the production of immune-related proteins, on metabolic traits such as lipoprotein and lipid levels, on blood-cell-related traits such as platelet count, and on disease traits such as coronary artery disease and type 2 diabetes.
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Affiliation(s)
- Artika P Nath
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria 3004, Australia; Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, United Kingdom; Department of Microbiology and Immunology, University of Melbourne, Parkville, Victoria 3010, Australia.
| | - Scott C Ritchie
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria 3004, Australia; Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, United Kingdom
| | - Nastasiya F Grinberg
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, Department of Medicine, University of Cambridge, Cambridge CB2 0AW, United Kingdom
| | - Howard Ho-Fung Tang
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria 3004, Australia
| | - Qin Qin Huang
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria 3004, Australia; Department of Clinical Pathology, University of Melbourne, Parkville, Victoria 3010, Australia
| | - Shu Mei Teo
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria 3004, Australia; Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, United Kingdom
| | - Ari V Ahola-Olli
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA; Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland
| | - Peter Würtz
- Research Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki 00014, Finland; Nightingale Health Ltd., Helsinki 00300, Finland
| | - Aki S Havulinna
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland; National Institute of Health and Welfare, Helsinki 00271, Finland
| | - Kristiina Santalahti
- Medicity Research Laboratory, Department of Medical Microbiology and Immunology, University of Turku, Turku 20520, Finland
| | - Niina Pitkänen
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku 20520, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere 33520, Finland; Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland
| | - Mika Kähönen
- Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland; Department of Clinical Physiology, Tampere University Hospital, Tampere 33521, Finland
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere 33520, Finland; Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland
| | - Emma Raitoharju
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere 33520, Finland; Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland
| | - Ilkka Seppälä
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere 33520, Finland; Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland
| | - Antti-Pekka Sarin
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland; National Institute of Health and Welfare, Helsinki 00271, Finland
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland; Department of Public Health, University of Helsinki, Helsinki 00014, Finland; Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
| | - Aarno Palotie
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland; Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114, USA; Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts 02114, USA; Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
| | - Markus Perola
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland; National Institute of Health and Welfare, Helsinki 00271, Finland
| | - Jorma S Viikari
- Department of Medicine, University of Turku, Turku 20520, Finland; Division of Medicine, Turku University Hospital, Turku 20520, Finland
| | - Sirpa Jalkanen
- Medicity Research Laboratory, Department of Medical Microbiology and Immunology, University of Turku, Turku 20520, Finland
| | - Mikael Maksimow
- Medicity Research Laboratory, Department of Medical Microbiology and Immunology, University of Turku, Turku 20520, Finland
| | - Marko Salmi
- Medicity Research Laboratory and Institute of Biomedicine, University of Turku, Turku 20520, Finland
| | - Chris Wallace
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, Department of Medicine, University of Cambridge, Cambridge CB2 0AW, United Kingdom; MRC Biostatistics Unit, Institute of Public Health, Cambridge CB2 0SR, United Kingdom
| | - Olli T Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku 20520, Finland; The Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku 20520, Finland
| | - Veikko Salomaa
- Medicity Research Laboratory, Department of Medical Microbiology and Immunology, University of Turku, Turku 20520, Finland
| | - Gad Abraham
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria 3004, Australia; Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, United Kingdom; Department of Clinical Pathology, University of Melbourne, Parkville, Victoria 3010, Australia
| | - Johannes Kettunen
- Medicity Research Laboratory, Department of Medical Microbiology and Immunology, University of Turku, Turku 20520, Finland; Computational Medicine, Centre for Life Course Health Research, University of Oulu, Oulu 90014, Finland; NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio 70211, Finland; Biocenter Oulu, University of Oulu, Oulu 90014, Finland
| | - Michael Inouye
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria 3004, Australia; Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, United Kingdom; Department of Clinical Pathology, University of Melbourne, Parkville, Victoria 3010, Australia; The Alan Turing Institute, London, United Kingdom.
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24
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Viitasalo A, Schnurr TM, Pitkänen N, Hollensted M, Nielsen TRH, Pahkala K, Atalay M, Lind MV, Heikkinen S, Frithioff-Bøjsøe C, Fonvig CE, Grarup N, Kähönen M, Carrasquilla GD, Larnkjaer A, Pedersen O, Michaelsen KF, Lakka TA, Holm JC, Lehtimäki T, Raitakari O, Hansen T, Kilpeläinen TO. Abdominal adiposity and cardiometabolic risk factors in children and adolescents: a Mendelian randomization analysis. Am J Clin Nutr 2019; 110:1079-1087. [PMID: 31504107 PMCID: PMC6904295 DOI: 10.1093/ajcn/nqz187] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2018] [Accepted: 07/18/2019] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND Mendelian randomization studies in adults suggest that abdominal adiposity is causally associated with increased risk of type 2 diabetes and coronary artery disease in adults, but its causal effect on cardiometabolic risk in children remains unclear. OBJECTIVE We aimed to study the causal relation of abdominal adiposity with cardiometabolic risk factors in children by applying Mendelian randomization. METHODS We constructed a genetic risk score (GRS) using variants previously associated with waist-to-hip ratio adjusted for BMI (WHRadjBMI) and examined its associations with cardiometabolic factors by linear regression and Mendelian randomization in a meta-analysis of 6 cohorts, including 9895 European children and adolescents aged 3-17 y. RESULTS WHRadjBMI GRS was associated with higher WHRadjBMI (β = 0.021 SD/allele; 95% CI: 0.016, 0.026 SD/allele; P = 3 × 10-15) and with unfavorable concentrations of blood lipids (higher LDL cholesterol: β = 0.006 SD/allele; 95% CI: 0.001, 0.011 SD/allele; P = 0.025; lower HDL cholesterol: β = -0.007 SD/allele; 95% CI: -0.012, -0.002 SD/allele; P = 0.009; higher triglycerides: β = 0.007 SD/allele; 95% CI: 0.002, 0.012 SD/allele; P = 0.006). No differences were detected between prepubertal and pubertal/postpubertal children. The WHRadjBMI GRS had a stronger association with fasting insulin in children and adolescents with overweight/obesity (β = 0.016 SD/allele; 95% CI: 0.001, 0.032 SD/allele; P = 0.037) than in those with normal weight (β = -0.002 SD/allele; 95% CI: -0.010, 0.006 SD/allele; P = 0.605) (P for difference = 0.034). In a 2-stage least-squares regression analysis, each genetically instrumented 1-SD increase in WHRadjBMI increased circulating triglycerides by 0.17 mmol/L (0.35 SD, P = 0.040), suggesting that the relation between abdominal adiposity and circulating triglycerides may be causal. CONCLUSIONS Abdominal adiposity may have a causal, unfavorable effect on plasma triglycerides and potentially other cardiometabolic risk factors starting in childhood. The results highlight the importance of early weight management through healthy dietary habits and physically active lifestyle among children with a tendency for abdominal adiposity.
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Affiliation(s)
- Anna Viitasalo
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark,Address correspondence to AV (e-mail: )
| | - Theresia M Schnurr
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Niina Pitkänen
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Mette Hollensted
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Tenna R H Nielsen
- The Children's Obesity Clinic, Department of Pediatrics, Copenhagen University Hospital Holbæk, Holbæk, Denmark,Department of Pediatrics, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
| | - Katja Pahkala
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland,Paavo Nurmi Centre, Sports and Exercise Medicine Unit, Department of Physical Activity and Health, University of Turku, Turku, Finland
| | - Mustafa Atalay
- Institute of Biomedicine, University of Eastern Finland, Kuopio, Finland
| | - Mads V Lind
- Department of Nutrition, Exercise, and Sports, Faculty of Science, University of Copenhagen, Copenhagen, Denmark
| | - Sami Heikkinen
- Institute of Biomedicine, University of Eastern Finland, Kuopio, Finland,Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Christine Frithioff-Bøjsøe
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark,The Children's Obesity Clinic, Department of Pediatrics, Copenhagen University Hospital Holbæk, Holbæk, Denmark
| | - Cilius E Fonvig
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark,The Children's Obesity Clinic, Department of Pediatrics, Copenhagen University Hospital Holbæk, Holbæk, Denmark,The Hans Christian Andersen Children's Hospital, Odense University Hospital, Odense, Denmark
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland,Faculty of Medicine and Health Technology, Finnish Cardiovascular Research Center, Tampere University, Tampere, Finland
| | - Germán D Carrasquilla
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Anni Larnkjaer
- Department of Nutrition, Exercise, and Sports, Faculty of Science, University of Copenhagen, Copenhagen, Denmark
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Kim F Michaelsen
- Department of Nutrition, Exercise, and Sports, Faculty of Science, University of Copenhagen, Copenhagen, Denmark
| | - Timo A Lakka
- Institute of Biomedicine, University of Eastern Finland, Kuopio, Finland,Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland,Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Jens-Christian Holm
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark,The Children's Obesity Clinic, Department of Pediatrics, Copenhagen University Hospital Holbæk, Holbæk, Denmark,Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Terho Lehtimäki
- Faculty of Medicine and Health Technology, Finnish Cardiovascular Research Center, Tampere University, Tampere, Finland,Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
| | - Olli Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland,Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Tuomas O Kilpeläinen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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Impact of the rumen microbiome on milk fatty acid composition of Holstein cattle. Genet Sel Evol 2019; 51:23. [PMID: 31142263 PMCID: PMC6542034 DOI: 10.1186/s12711-019-0464-8] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Accepted: 05/14/2019] [Indexed: 12/15/2022] Open
Abstract
Background Fatty acids (FA) in bovine milk derive through body mobilization, de novo synthesis or from the feed via the blood stream. To be able to digest feedstuff, the cow depends on its rumen microbiome. The relative abundance of the microbes has been shown to differ between cows. To date, there is little information on the impact of the microbiome on the formation of specific milk FA. Therefore, in this study, our aim was to investigate the impact of the rumen bacterial microbiome on milk FA composition. Furthermore, we evaluated the predictive value of the rumen microbiome and the host genetics on the composition of individual FA in milk. Results Our results show that the proportion of variance explained by the rumen bacteria composition (termed microbiability or \documentclass[12pt]{minimal}
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\begin{document}$$h_{B}^{2}$$\end{document}hB2) was generally smaller than that of the genetic component (heritability), and that rumen bacteria influenced most C15:0, C17:0, C18:2 n-6, C18:3 n-3 and CLA cis-9, trans-11 with estimated \documentclass[12pt]{minimal}
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\begin{document}$$h_{B}^{2}$$\end{document}hB2 ranging from 0.26 to 0.42. For C6:0, C8:0, C10:0, C12:0, C16:0, C16:1 cis-9 and C18:1 cis-9, the variance explained by the rumen bacteria component was close to 0. In general, both the rumen microbiome and the host genetics had little value for predicting FA phenotype. Compared to genetic information only, adding rumen bacteria information resulted in a significant improvement of the predictive value for C15:0 from 0.22 to 0.38 (P = 9.50e−07) and C18:3 n-3 from 0 to 0.29 (P = 8.81e−18). Conclusions The rumen microbiome has a pronounced influence on the content of odd chain FA and polyunsaturated C18 FA, and to a lesser extent, on the content of the short- and medium-chain FA in the milk of Holstein cattle. The accuracy of prediction of FA phenotypes in milk based on information from either the animal’s genotypes or rumen bacteria composition was very low. Electronic supplementary material The online version of this article (10.1186/s12711-019-0464-8) contains supplementary material, which is available to authorized users.
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Poulsen NA, Robinson RC, Barile D, Larsen LB, Buitenhuis B. A genome-wide association study reveals specific transferases as candidate loci for bovine milk oligosaccharides synthesis. BMC Genomics 2019; 20:404. [PMID: 31117955 PMCID: PMC6532250 DOI: 10.1186/s12864-019-5786-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2018] [Accepted: 05/08/2019] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Human milk oligosaccharides (OS) play a key role in brain and gut microbiota development of the neonate, but the underlying biosynthetic steps of OS in the mammary gland are still largely unknown. As bovine milk contains OS with somewhat similar structures and functionalities there is increased interest in further understanding the genetic basis underlying the OS content of milk for eventual extraction and generation of value-added ingredients for infant formulas and nutraceuticals. The present study is the first to report on genetic parameter estimation as well as on a genome wide association study (GWAS) from the largest bovine milk OS dataset analyzed to date. RESULTS In total 15 different bovine milk OS were monitored. Heritabilities ranged from 0 to 0.68 in Danish Holstein and from 0 to 0.92 in Danish Jersey. The GWAS identified in total 1770 SNPs (FDR < 0.10) for five different OS in Danish Holstein and 6913 SNPs (FDR < 0.10) for 11 OS in Danish Jersey. In Danish Holstein, a major overlapping QTL was identified on BTA1 for LNH and LNT explaining 24% of the variation in these OS. The most significant SNPs were associated with B3GNT5, a gene encoding a glycosyltransferase involved in glycan synthesis. In Danish Jersey, a very strong QTL was detected for the OS with composition 2 Hex 1 HexNAc (isomer 1) on BTA11. The most significant SNP had -log10(P-value) of 52.88 (BOVINEHD1100030300) and was assigned to ABO, a gene encoding ABO blood group glycosyltransferases. This SNP has been reported to be a missense mutation and explains 56% of the OS variation. Other candidate genes of interest identified for milk OS were ALG3, B3GALNT2, LOC520336, PIGV, MAN1C1, ST6GALNAC6, GLT6D1, GALNT14, GALNT17, COLGALT2, LFNG and SIGLEC. CONCLUSION To our knowledge, this is the first study documenting a solid breeding potential for bovine milk OS and a strong indication of specific candidate genes related to OS synthesis underlying this genetic influence. This new information has the potential to guide breeding strategies to achieve production of milk with higher diversity and concentration of OS and ultimately facilitate large-scale extraction of bovine milk OS.
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Affiliation(s)
- Nina A. Poulsen
- Department of Food Science, Aarhus University, Blichers Allé 20, P. O. Box 50, DK-8830 Tjele, Denmark
| | - Randall C. Robinson
- Department of Food Science and Technology, University of California, Davis, One Shields Ave., Davis, CA 95616 USA
| | - Daniela Barile
- Department of Food Science and Technology, University of California, Davis, One Shields Ave., Davis, CA 95616 USA
- Foods for Health Institute, University of California, Davis, One Shields Ave., Davis, CA 95616 USA
| | - Lotte B. Larsen
- Department of Food Science, Aarhus University, Blichers Allé 20, P. O. Box 50, DK-8830 Tjele, Denmark
| | - Bart Buitenhuis
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Blichers Allé 20, P. O. Box 50, DK-8830 Tjele, Denmark
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Pehkonen J, Viinikainen J, Böckerman P, Pitkänen N, Lehtimäki T, Raitakari O. Health endowment and later-life outcomes in the labour market: Evidence using genetic risk scores and reduced-form models. SSM Popul Health 2019; 7:100379. [PMID: 30906844 PMCID: PMC6411586 DOI: 10.1016/j.ssmph.2019.100379] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2018] [Revised: 02/14/2019] [Accepted: 02/17/2019] [Indexed: 10/28/2022] Open
Abstract
This paper examines the relationship between health endowment and later-life outcomes in the labour market. The analysis is based on reduced-form models in which labour market outcomes are regressed on genetic variants related to the increased risk of cardiovascular diseases. We use linked Finnish data that have many strengths. Genetic risk scores constitute exogenous measures for health endowment, and accurate administrative tax records on earnings, employment and social income transfers provide a comprehensive account of an individual's long-term performance in the labour market. The results show that although the direction of an effect is generally consistent with theoretical reasoning, the effects of health endowment on outcomes are statistically weak, and the hypothesis of no effect can be rejected only in one case: genetic endowment related to obesity influences male earnings and employment in prime age. Due to the sample size (N = 1651), the results should be interpreted with caution and should be confirmed in larger samples and in other institutional settings.
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Affiliation(s)
- Jaakko Pehkonen
- University of Jyväskylä, School of Business and Economics, Jyväskylä, Finland
| | - Jutta Viinikainen
- University of Jyväskylä, School of Business and Economics, Jyväskylä, Finland
| | - Petri Böckerman
- University of Jyväskylä, School of Business and Economics, Jyväskylä, Finland
- Labour Institute for Economic Research, Helsinki, Finland
- IZA, Bonn, Germany
| | - Niina Pitkänen
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
| | - Olli Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
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Guyatt AL, Brennan RR, Burrows K, Guthrie PAI, Ascione R, Ring SM, Gaunt TR, Pyle A, Cordell HJ, Lawlor DA, Chinnery PF, Hudson G, Rodriguez S. A genome-wide association study of mitochondrial DNA copy number in two population-based cohorts. Hum Genomics 2019; 13:6. [PMID: 30704525 PMCID: PMC6357493 DOI: 10.1186/s40246-018-0190-2] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2018] [Accepted: 12/27/2018] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND Mitochondrial DNA copy number (mtDNA CN) exhibits interindividual and intercellular variation, but few genome-wide association studies (GWAS) of directly assayed mtDNA CN exist. We undertook a GWAS of qPCR-assayed mtDNA CN in the Avon Longitudinal Study of Parents and Children (ALSPAC) and the UK Blood Service (UKBS) cohort. After validating and harmonising data, 5461 ALSPAC mothers (16-43 years at mtDNA CN assay) and 1338 UKBS females (17-69 years) were included in a meta-analysis. Sensitivity analyses restricted to females with white cell-extracted DNA and adjusted for estimated or assayed cell proportions. Associations were also explored in ALSPAC children and UKBS males. RESULTS A neutrophil-associated locus approached genome-wide significance (rs709591 [MED24], β (change in SD units of mtDNA CN per allele) [SE] - 0.084 [0.016], p = 1.54e-07) in the main meta-analysis of adult females. This association was concordant in magnitude and direction in UKBS males and ALSPAC neonates. SNPs in and around ABHD8 were associated with mtDNA CN in ALSPAC neonates (rs10424198, β [SE] 0.262 [0.034], p = 1.40e-14), but not other study groups. In a meta-analysis of unrelated individuals (N = 11,253), we replicated a published association in TFAM (β [SE] 0.046 [0.017], p = 0.006), with an effect size much smaller than that observed in the replication analysis of a previous in silico GWAS. CONCLUSIONS In a hypothesis-generating GWAS, we confirm an association between TFAM and mtDNA CN and present putative loci requiring replication in much larger samples. We discuss the limitations of our work, in terms of measurement error and cellular heterogeneity, and highlight the need for larger studies to better understand nuclear genomic control of mtDNA copy number.
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Affiliation(s)
- Anna L. Guyatt
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Rebecca R. Brennan
- Wellcome Centre for Mitochondrial Research, Newcastle University, Newcastle, UK
- Institute of Genetic Medicine, Newcastle University, Newcastle, UK
| | - Kimberley Burrows
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Philip A. I. Guthrie
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Raimondo Ascione
- Bristol Heart Institute, Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Susan M. Ring
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Tom R. Gaunt
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Angela Pyle
- Wellcome Centre for Mitochondrial Research, Newcastle University, Newcastle, UK
| | | | - Debbie A. Lawlor
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Patrick F. Chinnery
- Department of Clinical Neurosciences and MRC Mitochondrial Biology Unit, University of Cambridge, Cambridge, UK
| | - Gavin Hudson
- Wellcome Centre for Mitochondrial Research, Newcastle University, Newcastle, UK
- Institute of Genetic Medicine, Newcastle University, Newcastle, UK
| | - Santiago Rodriguez
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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Viinikainen J, Bryson A, Böckerman P, Elovainio M, Pitkänen N, Pulkki-Råback L, Lehtimäki T, Raitakari O, Pehkonen J. Does education protect against depression? Evidence from the Young Finns Study using Mendelian randomization. Prev Med 2018; 115:134-139. [PMID: 30145350 DOI: 10.1016/j.ypmed.2018.08.026] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/12/2018] [Revised: 08/09/2018] [Accepted: 08/21/2018] [Indexed: 02/07/2023]
Abstract
Using participants (N = 1733) drawn from the nationally representative longitudinal Young Finns Study (YFS) we estimate the effect of education on depressive symptoms. In 2007, when the participants were between 30 and 45 years old, they reported their depressive symptoms using a revised version of Beck's Depression Inventory. Education was measured using register information on the highest completed level of education in 2007, which was converted to years of education. To identify a causal relationship between education and depressive symptoms we use an instrumental variables approach (Mendelian randomization, MR) with a genetic risk score as an instrument for years of education. The genetic risk score was based on 74 genetic variants, which were associated with years of education in a genome-wide association study (GWAS). Because the genetic variants are randomly assigned at conception, they induce exogenous variation in years of education and thus identify a causal effect if the assumptions of the MR approach are met. In Ordinary Least Squares (OLS) estimation years of education in 2007 were negatively associated with depressive symptoms in 2007 (b = -0.027, 95% Confidence Interval (CI) = -0.040, -0.015). However, the results based on Mendelian randomization suggested that the effect is not causal (b = 0.017; 95% CI = -0.144, 0.178). This indicates that omitted variables correlated with education and depression may bias the linear regression coefficients and exogenous variation in education caused by differences in genetic make-up does not seem to protect against depressive symptoms.
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Affiliation(s)
- Jutta Viinikainen
- University of Jyväskylä, Jyväskylä University School of Business and Economics, Jyväskylä, Finland.
| | - Alex Bryson
- University College London, London, United Kingdom; IZA, Bonn, Germany
| | - Petri Böckerman
- University of Jyväskylä, Jyväskylä University School of Business and Economics, Jyväskylä, Finland; IZA, Bonn, Germany; Labour Institute for Economic Research, Helsinki, Finland
| | - Marko Elovainio
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland and National Institute for Health and Welfare, Helsinki, Finland
| | - Niina Pitkänen
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Laura Pulkki-Råback
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland and National Institute for Health and Welfare, Helsinki, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
| | - Olli Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku and Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Jaakko Pehkonen
- University of Jyväskylä, Jyväskylä University School of Business and Economics, Jyväskylä, Finland
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Genetic polymorphism of sterol transporters in children with future gallstones. Dig Liver Dis 2018; 50:954-960. [PMID: 29764733 DOI: 10.1016/j.dld.2018.04.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2017] [Revised: 04/09/2018] [Accepted: 04/11/2018] [Indexed: 12/11/2022]
Abstract
BACKGROUND & AIMS Gallstone disease is related to hypersecretion of cholesterol in bile, and low serum phytosterol levels. We examined how genetic polymorphisms of sterol transporters affect childhood cholesterol metabolism trait predicting adult gallstone disease. PATIENTS AND METHODS In retrospective controlled study, we determined D19H polymorphism of ABCG8 gene, genetic variation at Niemann-Pick C1-like 1 (NPC1L1) gene locus (rs41279633, rs17655652, rs2072183, rs217434 and rs2073548), and serum cholesterol, noncholesterol sterols and lipids in children affected by gallstones decades later (n = 66) and controls (n = 126). RESULTS In childhood, phytosterols were lower (9.7%-23.4%) in carriers of risk allele 19H compared to 19D homozygotes. Lowest campesterol/cholesterol tertile consisted of 1.9-times more future gallstone subjects, and 3.7-times more 19H carriers than highest one. Campesterol/cholesterol-ratio was highest in 19D homozygote controls, but ∼11% lower in gallstone 19D homozygotes and ∼25% lower among gallstone and control carriers of 19H. Gallstone subjects with alleles CC of rs41279633 and TT of rs217434 of NPC1L1 had ∼18% lower campesterol/cholesterol-ratio compared to mutation carriers. CONCLUSIONS Risk trait of cholesterol metabolism (low phytosterols) in childhood favouring cholesterol gallstone disease later in adulthood is influenced by risk variant 19H of ABCG8 and obviously also other factors. NPC1L1 variants have minor influence on noncholesterol sterols.
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Pathway-Wide Genetic Risks in Chlamydial Infections Overlap between Tissue Tropisms: A Genome-Wide Association Scan. Mediators Inflamm 2018; 2018:3434101. [PMID: 29967566 PMCID: PMC6008910 DOI: 10.1155/2018/3434101] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Revised: 01/11/2018] [Accepted: 02/08/2018] [Indexed: 01/22/2023] Open
Abstract
Chlamydia trachomatis is the most commonly diagnosed bacterial sexually transmitted infection and can lead to tubal factor infertility, a disease characterised by fibrosis of the fallopian tubes. Genetic polymorphisms in molecular pathways involving G protein-coupled receptor signalling, the Akt/PI3K cascade, the mitotic cell cycle, and immune response have been identified in association with the development of trachomatous scarring, an ocular form of chlamydia-related fibrotic pathology. In this case-control study, we performed genome-wide association and pathways-based analysis in a sample of 71 Dutch women who attended an STI clinic who were seropositive for Chlamydia trachomatis antibodies and 169 high-risk Dutch women who sought similar health services but who were seronegative. We identified two regions of within-gene SNP association with Chlamydia trachomatis serological response and found that GPCR signalling and cell cycle pathways were also associated with the trait. These pathway-level associations appear to be common to immunological sequelae of chlamydial infections in both ocular and urogenital tropisms. These pathways may be central mediators of human refractoriness to chlamydial diseases.
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Seyednasrollah F, Mäkelä J, Pitkänen N, Juonala M, Hutri-Kähönen N, Lehtimäki T, Viikari J, Kelly T, Li C, Bazzano L, Elo LL, Raitakari OT. Prediction of Adulthood Obesity Using Genetic and Childhood Clinical Risk Factors in the Cardiovascular Risk in Young Finns Study. ACTA ACUST UNITED AC 2018; 10:CIRCGENETICS.116.001554. [PMID: 28620069 DOI: 10.1161/circgenetics.116.001554] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2016] [Accepted: 12/06/2016] [Indexed: 12/21/2022]
Abstract
BACKGROUND Obesity is a known risk factor for cardiovascular disease. Early prediction of obesity is essential for prevention. The aim of this study is to assess the use of childhood clinical factors and the genetic risk factors in predicting adulthood obesity using machine learning methods. METHODS AND RESULTS A total of 2262 participants from the Cardiovascular Risk in YFS (Young Finns Study) were followed up from childhood (age 3-18 years) to adulthood for 31 years. The data were divided into training (n=1625) and validation (n=637) set. The effect of known genetic risk factors (97 single-nucleotide polymorphisms) was investigated as a weighted genetic risk score of all 97 single-nucleotide polymorphisms (WGRS97) or a subset of 19 most significant single-nucleotide polymorphisms (WGRS19) using boosting machine learning technique. WGRS97 and WGRS19 were validated using external data (n=369) from BHS (Bogalusa Heart Study). WGRS19 improved the accuracy of predicting adulthood obesity in training (area under the curve [AUC=0.787 versus AUC=0.744, P<0.0001) and validation data (AUC=0.769 versus AUC=0.747, P=0.026). WGRS97 improved the accuracy in training (AUC=0.782 versus AUC=0.744, P<0.0001) but not in validation data (AUC=0.749 versus AUC=0.747, P=0.785). Higher WGRS19 associated with higher body mass index at 9 years and WGRS97 at 6 years. Replication in BHS confirmed our findings that WGRS19 and WGRS97 are associated with body mass index. CONCLUSIONS WGRS19 improves prediction of adulthood obesity. Predictive accuracy is highest among young children (3-6 years), whereas among older children (9-18 years) the risk can be identified using childhood clinical factors. The model is helpful in screening children with high risk of developing obesity.
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Affiliation(s)
- Fatemeh Seyednasrollah
- From the Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Finland (F.S., J.M., L.L.E.); Department of Mathematics and Statistics (F.S.), Research Centre of Applied and Preventive Cardiovascular Medicine (N.P., O.T.R.), and Department of Medicine (M.J., J.V.), University of Turku, Finland; Division of Medicine (M.J., J.V.) and Clinical Physiology and Nuclear Medicine (O.T.R.), Turku University Hospital, Finland; Department of Pediatrics (N.H.-K.) and School of Medicine (T.L.), University of Tampere, Finland; Tampere University Hospital, Finland (N.H.-K.); Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland (T.L.); Tulane University Health Sciences Center, New Orleans, LA (T.K., L.B.); and Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens (C.L.)
| | - Johanna Mäkelä
- From the Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Finland (F.S., J.M., L.L.E.); Department of Mathematics and Statistics (F.S.), Research Centre of Applied and Preventive Cardiovascular Medicine (N.P., O.T.R.), and Department of Medicine (M.J., J.V.), University of Turku, Finland; Division of Medicine (M.J., J.V.) and Clinical Physiology and Nuclear Medicine (O.T.R.), Turku University Hospital, Finland; Department of Pediatrics (N.H.-K.) and School of Medicine (T.L.), University of Tampere, Finland; Tampere University Hospital, Finland (N.H.-K.); Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland (T.L.); Tulane University Health Sciences Center, New Orleans, LA (T.K., L.B.); and Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens (C.L.).
| | - Niina Pitkänen
- From the Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Finland (F.S., J.M., L.L.E.); Department of Mathematics and Statistics (F.S.), Research Centre of Applied and Preventive Cardiovascular Medicine (N.P., O.T.R.), and Department of Medicine (M.J., J.V.), University of Turku, Finland; Division of Medicine (M.J., J.V.) and Clinical Physiology and Nuclear Medicine (O.T.R.), Turku University Hospital, Finland; Department of Pediatrics (N.H.-K.) and School of Medicine (T.L.), University of Tampere, Finland; Tampere University Hospital, Finland (N.H.-K.); Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland (T.L.); Tulane University Health Sciences Center, New Orleans, LA (T.K., L.B.); and Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens (C.L.)
| | - Markus Juonala
- From the Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Finland (F.S., J.M., L.L.E.); Department of Mathematics and Statistics (F.S.), Research Centre of Applied and Preventive Cardiovascular Medicine (N.P., O.T.R.), and Department of Medicine (M.J., J.V.), University of Turku, Finland; Division of Medicine (M.J., J.V.) and Clinical Physiology and Nuclear Medicine (O.T.R.), Turku University Hospital, Finland; Department of Pediatrics (N.H.-K.) and School of Medicine (T.L.), University of Tampere, Finland; Tampere University Hospital, Finland (N.H.-K.); Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland (T.L.); Tulane University Health Sciences Center, New Orleans, LA (T.K., L.B.); and Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens (C.L.)
| | - Nina Hutri-Kähönen
- From the Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Finland (F.S., J.M., L.L.E.); Department of Mathematics and Statistics (F.S.), Research Centre of Applied and Preventive Cardiovascular Medicine (N.P., O.T.R.), and Department of Medicine (M.J., J.V.), University of Turku, Finland; Division of Medicine (M.J., J.V.) and Clinical Physiology and Nuclear Medicine (O.T.R.), Turku University Hospital, Finland; Department of Pediatrics (N.H.-K.) and School of Medicine (T.L.), University of Tampere, Finland; Tampere University Hospital, Finland (N.H.-K.); Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland (T.L.); Tulane University Health Sciences Center, New Orleans, LA (T.K., L.B.); and Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens (C.L.)
| | - Terho Lehtimäki
- From the Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Finland (F.S., J.M., L.L.E.); Department of Mathematics and Statistics (F.S.), Research Centre of Applied and Preventive Cardiovascular Medicine (N.P., O.T.R.), and Department of Medicine (M.J., J.V.), University of Turku, Finland; Division of Medicine (M.J., J.V.) and Clinical Physiology and Nuclear Medicine (O.T.R.), Turku University Hospital, Finland; Department of Pediatrics (N.H.-K.) and School of Medicine (T.L.), University of Tampere, Finland; Tampere University Hospital, Finland (N.H.-K.); Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland (T.L.); Tulane University Health Sciences Center, New Orleans, LA (T.K., L.B.); and Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens (C.L.)
| | - Jorma Viikari
- From the Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Finland (F.S., J.M., L.L.E.); Department of Mathematics and Statistics (F.S.), Research Centre of Applied and Preventive Cardiovascular Medicine (N.P., O.T.R.), and Department of Medicine (M.J., J.V.), University of Turku, Finland; Division of Medicine (M.J., J.V.) and Clinical Physiology and Nuclear Medicine (O.T.R.), Turku University Hospital, Finland; Department of Pediatrics (N.H.-K.) and School of Medicine (T.L.), University of Tampere, Finland; Tampere University Hospital, Finland (N.H.-K.); Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland (T.L.); Tulane University Health Sciences Center, New Orleans, LA (T.K., L.B.); and Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens (C.L.)
| | - Tanika Kelly
- From the Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Finland (F.S., J.M., L.L.E.); Department of Mathematics and Statistics (F.S.), Research Centre of Applied and Preventive Cardiovascular Medicine (N.P., O.T.R.), and Department of Medicine (M.J., J.V.), University of Turku, Finland; Division of Medicine (M.J., J.V.) and Clinical Physiology and Nuclear Medicine (O.T.R.), Turku University Hospital, Finland; Department of Pediatrics (N.H.-K.) and School of Medicine (T.L.), University of Tampere, Finland; Tampere University Hospital, Finland (N.H.-K.); Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland (T.L.); Tulane University Health Sciences Center, New Orleans, LA (T.K., L.B.); and Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens (C.L.)
| | - Changwei Li
- From the Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Finland (F.S., J.M., L.L.E.); Department of Mathematics and Statistics (F.S.), Research Centre of Applied and Preventive Cardiovascular Medicine (N.P., O.T.R.), and Department of Medicine (M.J., J.V.), University of Turku, Finland; Division of Medicine (M.J., J.V.) and Clinical Physiology and Nuclear Medicine (O.T.R.), Turku University Hospital, Finland; Department of Pediatrics (N.H.-K.) and School of Medicine (T.L.), University of Tampere, Finland; Tampere University Hospital, Finland (N.H.-K.); Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland (T.L.); Tulane University Health Sciences Center, New Orleans, LA (T.K., L.B.); and Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens (C.L.)
| | - Lydia Bazzano
- From the Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Finland (F.S., J.M., L.L.E.); Department of Mathematics and Statistics (F.S.), Research Centre of Applied and Preventive Cardiovascular Medicine (N.P., O.T.R.), and Department of Medicine (M.J., J.V.), University of Turku, Finland; Division of Medicine (M.J., J.V.) and Clinical Physiology and Nuclear Medicine (O.T.R.), Turku University Hospital, Finland; Department of Pediatrics (N.H.-K.) and School of Medicine (T.L.), University of Tampere, Finland; Tampere University Hospital, Finland (N.H.-K.); Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland (T.L.); Tulane University Health Sciences Center, New Orleans, LA (T.K., L.B.); and Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens (C.L.)
| | - Laura L Elo
- From the Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Finland (F.S., J.M., L.L.E.); Department of Mathematics and Statistics (F.S.), Research Centre of Applied and Preventive Cardiovascular Medicine (N.P., O.T.R.), and Department of Medicine (M.J., J.V.), University of Turku, Finland; Division of Medicine (M.J., J.V.) and Clinical Physiology and Nuclear Medicine (O.T.R.), Turku University Hospital, Finland; Department of Pediatrics (N.H.-K.) and School of Medicine (T.L.), University of Tampere, Finland; Tampere University Hospital, Finland (N.H.-K.); Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland (T.L.); Tulane University Health Sciences Center, New Orleans, LA (T.K., L.B.); and Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens (C.L.)
| | - Olli T Raitakari
- From the Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Finland (F.S., J.M., L.L.E.); Department of Mathematics and Statistics (F.S.), Research Centre of Applied and Preventive Cardiovascular Medicine (N.P., O.T.R.), and Department of Medicine (M.J., J.V.), University of Turku, Finland; Division of Medicine (M.J., J.V.) and Clinical Physiology and Nuclear Medicine (O.T.R.), Turku University Hospital, Finland; Department of Pediatrics (N.H.-K.) and School of Medicine (T.L.), University of Tampere, Finland; Tampere University Hospital, Finland (N.H.-K.); Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland (T.L.); Tulane University Health Sciences Center, New Orleans, LA (T.K., L.B.); and Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens (C.L.)
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33
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Lin BD, Carnero Montoro E, Bell JT, Boomsma DI, de Geus EJ, Jansen R, Kluft C, Mangino M, Penninx B, Spector TD, Willemsen G, Hottenga JJ. 2SNP heritability and effects of genetic variants for neutrophil-to-lymphocyte and platelet-to-lymphocyte ratio. J Hum Genet 2017; 62:979-988. [PMID: 29066854 PMCID: PMC5669488 DOI: 10.1038/jhg.2017.76] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2017] [Revised: 05/24/2017] [Accepted: 06/13/2017] [Indexed: 01/13/2023]
Abstract
Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) are important biomarkers for disease development and progression. To gain insight into the genetic causes of variance in NLR and PLR in the general population, we conducted genome-wide association (GWA) analyses and estimated SNP heritability in a sample of 5901 related healthy Dutch individuals. GWA analyses identified a new genome-wide significant locus on the HBS1L-MYB intergenic region for PLR, which replicated in a sample of 2538 British twins. For platelet count, we replicated three known genome-wide significant loci in our cohort (at CCDC71L-PIK3CG, BAK1 and ARHGEF3). For neutrophil count, we replicated the PSMD3 locus. For the identified top SNPs, we found significant cis and trans expression quantitative trait loci effects for several loci involved in hematological and immunological pathways. Linkage Disequilibrium score (LD) regression analyses for PLR and NLR confirmed that both traits are heritable, with a polygenetic SNP heritability for PLR of 14.1%, and for NLR of 2.4%. Genetic correlations were present between ratios and the constituent counts, with the genetic correlation (r=0.45) of PLR with platelet count reaching statistical significance. In conclusion, we established that two important biomarkers have a significant heritable SNP component, and identified the first genome-wide locus for PLR.
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Affiliation(s)
- Bochao Danae Lin
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Elena Carnero Montoro
- Department of Twin Research and Genetic Epidemiology, Kings College London, London SE1 7EH, UK
| | - Jordana T. Bell
- Department of Twin Research and Genetic Epidemiology, Kings College London, London SE1 7EH, UK
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Eco J. de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- EMGO+ Institute for Health & Care Research, VU Medical Center, Amsterdam, The Netherlands
| | - Rick Jansen
- Department of Psychiatry, VU Medical Center, Amsterdam, The Netherlands
| | | | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, Kings College London, London SE1 7EH, UK
- NIHR Biomedical Research Centre at Guy’s and St Thomas’ Foundation Trust, London SE1 9RT, UK
| | - Brenda Penninx
- Department of Psychiatry, VU Medical Center, Amsterdam, The Netherlands
| | - Tim D. Spector
- Department of Twin Research and Genetic Epidemiology, Kings College London, London SE1 7EH, UK
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- EMGO+ Institute for Health & Care Research, VU Medical Center, Amsterdam, The Netherlands
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34
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Nath AP, Ritchie SC, Byars SG, Fearnley LG, Havulinna AS, Joensuu A, Kangas AJ, Soininen P, Wennerström A, Milani L, Metspalu A, Männistö S, Würtz P, Kettunen J, Raitoharju E, Kähönen M, Juonala M, Palotie A, Ala-Korpela M, Ripatti S, Lehtimäki T, Abraham G, Raitakari O, Salomaa V, Perola M, Inouye M. An interaction map of circulating metabolites, immune gene networks, and their genetic regulation. Genome Biol 2017; 18:146. [PMID: 28764798 PMCID: PMC5540552 DOI: 10.1186/s13059-017-1279-y] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2017] [Accepted: 07/14/2017] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Immunometabolism plays a central role in many cardiometabolic diseases. However, a robust map of immune-related gene networks in circulating human cells, their interactions with metabolites, and their genetic control is still lacking. Here, we integrate blood transcriptomic, metabolomic, and genomic profiles from two population-based cohorts (total N = 2168), including a subset of individuals with matched multi-omic data at 7-year follow-up. RESULTS We identify topologically replicable gene networks enriched for diverse immune functions including cytotoxicity, viral response, B cell, platelet, neutrophil, and mast cell/basophil activity. These immune gene modules show complex patterns of association with 158 circulating metabolites, including lipoprotein subclasses, lipids, fatty acids, amino acids, small molecules, and CRP. Genome-wide scans for module expression quantitative trait loci (mQTLs) reveal five modules with mQTLs that have both cis and trans effects. The strongest mQTL is in ARHGEF3 (rs1354034) and affects a module enriched for platelet function, independent of platelet counts. Modules of mast cell/basophil and neutrophil function show temporally stable metabolite associations over 7-year follow-up, providing evidence that these modules and their constituent gene products may play central roles in metabolic inflammation. Furthermore, the strongest mQTL in ARHGEF3 also displays clear temporal stability, supporting widespread trans effects at this locus. CONCLUSIONS This study provides a detailed map of natural variation at the blood immunometabolic interface and its genetic basis, and may facilitate subsequent studies to explain inter-individual variation in cardiometabolic disease.
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Affiliation(s)
- Artika P Nath
- Department of Microbiology and Immunology, The University of Melbourne, Parkville, 3010, Victoria, Australia.,Systems Genomics Lab, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Scott C Ritchie
- Systems Genomics Lab, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.,Department of Pathology, The University of Melbourne, Parkville, 3010, Victoria, Australia
| | - Sean G Byars
- Department of Pathology, The University of Melbourne, Parkville, 3010, Victoria, Australia.,School of BioSciences, The University of Melbourne, Parkville, 3010, Victoria, Australia
| | - Liam G Fearnley
- Department of Pathology, The University of Melbourne, Parkville, 3010, Victoria, Australia.,School of BioSciences, The University of Melbourne, Parkville, 3010, Victoria, Australia
| | - Aki S Havulinna
- National Institute for Health and Welfare, Helsinki, 00271, Finland.,Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, 00014, Finland
| | - Anni Joensuu
- National Institute for Health and Welfare, Helsinki, 00271, Finland
| | - Antti J Kangas
- Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, 90014, Finland
| | - Pasi Soininen
- Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, 90014, Finland.,NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, 70211, Finland
| | | | - Lili Milani
- University of Tartu, Estonian Genome Center, Tartu, 51010, Estonia
| | - Andres Metspalu
- University of Tartu, Estonian Genome Center, Tartu, 51010, Estonia
| | - Satu Männistö
- National Institute for Health and Welfare, Helsinki, 00271, Finland
| | - Peter Würtz
- Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, 90014, Finland.,Diabetes and Obesity Research Program, University of Helsinki, Helsinki, Finland
| | - Johannes Kettunen
- National Institute for Health and Welfare, Helsinki, 00271, Finland.,Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, 90014, Finland.,NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, 70211, Finland.,Biocenter Oulu, University of Oulu, Oulu, 90014, Finland
| | - Emma Raitoharju
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Life Sciences, University of Tampere, 33014, Tampere, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, University of Tampere and Tampere University Hospital, FI-33521, Tampere, Finland
| | - Markus Juonala
- Department of Medicine, University of Turku and Division of Medicine, Turku University Hospital, FI-20520, Turku, Finland.,Murdoch Childrens Research Institute, Parkville, 3052, Victoria, Australia
| | - Aarno Palotie
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, 00014, Finland.,Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.,Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA.,Psychiatric & Neurodevelopmental Genetics Unit, Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Mika Ala-Korpela
- Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, 90014, Finland.,NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, 70211, Finland.,Biocenter Oulu, University of Oulu, Oulu, 90014, Finland.,Computational Medicine, School of Social and Community Medicine, University of Bristol, Bristol, BS8 1TH, UK.,Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, UK
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, 00014, Finland.,Department of Public Health, University of Helsinki, Helsinki, 00014, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Life Sciences, University of Tampere, 33014, Tampere, Finland
| | - Gad Abraham
- Systems Genomics Lab, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.,Department of Pathology, The University of Melbourne, Parkville, 3010, Victoria, Australia.,School of BioSciences, The University of Melbourne, Parkville, 3010, Victoria, Australia
| | - Olli Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, 20520, Finland.,Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, 20520, Finland
| | - Veikko Salomaa
- National Institute for Health and Welfare, Helsinki, 00271, Finland
| | - Markus Perola
- National Institute for Health and Welfare, Helsinki, 00271, Finland.,Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, 00014, Finland.,University of Tartu, Estonian Genome Center, Tartu, 51010, Estonia
| | - Michael Inouye
- Department of Microbiology and Immunology, The University of Melbourne, Parkville, 3010, Victoria, Australia. .,Systems Genomics Lab, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia. .,Department of Pathology, The University of Melbourne, Parkville, 3010, Victoria, Australia. .,School of BioSciences, The University of Melbourne, Parkville, 3010, Victoria, Australia.
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Abstract
OBJECTIVES The aim of this explorative study was to examine the effect of education on obesity using Mendelian randomization. METHODS Participants (N=2011) were from the on-going nationally representative Young Finns Study (YFS) that began in 1980 when six cohorts (aged 30, 33, 36, 39, 42 and 45 in 2007) were recruited. The average value of BMI (kg/m2) measurements in 2007 and 2011 and genetic information were linked to comprehensive register-based information on the years of education in 2007. We first used a linear regression (Ordinary Least Squares, OLS) to estimate the relationship between education and BMI. To identify a causal relationship, we exploited Mendelian randomization and used a genetic score as an instrument for education. The genetic score was based on 74 genetic variants that genome-wide association studies (GWASs) have found to be associated with the years of education. Because the genotypes are randomly assigned at conception, the instrument causes exogenous variation in the years of education and thus enables identification of causal effects. RESULTS The years of education in 2007 were associated with lower BMI in 2007/2011 (regression coefficient (b)=-0.22; 95% Confidence Intervals [CI]=-0.29, -0.14) according to the linear regression results. The results based on Mendelian randomization suggests that there may be a negative causal effect of education on BMI (b=-0.84; 95% CI=-1.77, 0.09). CONCLUSION The findings indicate that education could be a protective factor against obesity in advanced countries.
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36
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Bjelland DW, Lingala U, Patel PS, Jones M, Keller MC. A fast and accurate method for detection of IBD shared haplotypes in genome-wide SNP data. Eur J Hum Genet 2017; 25:617-624. [PMID: 28176766 PMCID: PMC5437913 DOI: 10.1038/ejhg.2017.6] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2016] [Revised: 11/22/2016] [Accepted: 12/24/2016] [Indexed: 11/08/2022] Open
Abstract
Identical by descent (IBD) segments are used to understand a number of fundamental issues in genetics. IBD segments are typically detected using long stretches of identical alleles between haplotypes in phased, whole-genome SNP data. Phase or SNP call errors in genomic data can degrade accuracy of IBD detection and lead to false-positive/negative calls and to under/overextension of true IBD segments. Furthermore, the number of comparisons increases quadratically with sample size, requiring high computational efficiency. We developed a new IBD segment detection program, FISHR (Find IBD Shared Haplotypes Rapidly), in an attempt to accurately detect IBD segments and to better estimate their endpoints using an algorithm that is fast enough to be deployed on very large whole-genome SNP data sets. We compared the performance of FISHR to three leading IBD segment detection programs: GERMLINE, refined IBD, and HaploScore. Using simulated and real genomic sequence data, we show that FISHR is slightly more accurate than all programs at detecting long (>3 cm) IBD segments but slightly less accurate than refined IBD at detecting short (~1 cm) IBD segments. More centrally, FISHR outperforms all programs in determining the true endpoints of IBD segments, which is crucial for several applications of IBD information. FISHR takes two to three times longer than GERMLINE to run, whereas both GERMLINE and FISHR were orders of magnitude faster than refined IBD and HaploScore. Overall, FISHR provides accurate IBD detection in unrelated individuals and is computationally efficient enough to be utilized on large SNP data sets >60 000 individuals.
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Affiliation(s)
- Douglas W Bjelland
- Institute for Behavioral Genetics, University of Colorado at Boulder, Boulder, CO, USA
| | - Uday Lingala
- Institute for Behavioral Genetics, University of Colorado at Boulder, Boulder, CO, USA
| | - Piyush S Patel
- Institute for Behavioral Genetics, University of Colorado at Boulder, Boulder, CO, USA
| | - Matt Jones
- Department of Psychology & Neuroscience, University of Colorado at Boulder, Boulder, CO, USA
| | - Matthew C Keller
- Institute for Behavioral Genetics, University of Colorado at Boulder, Boulder, CO, USA
- Department of Psychology & Neuroscience, University of Colorado at Boulder, Boulder, CO, USA
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37
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Estimates of linkage disequilibrium and effective population sizes in Chinese Merino (Xinjiang type) sheep by genome-wide SNPs. Genes Genomics 2017; 39:733-745. [PMID: 28706593 PMCID: PMC5486679 DOI: 10.1007/s13258-017-0539-2] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2016] [Accepted: 03/19/2017] [Indexed: 12/14/2022]
Abstract
Knowledge of linkage disequilibrium (LD) is important for effective genome-wide association studies and accurate genomic prediction. Chinese Merino (Xinjiang type) is well-known fine wool sheep breed. However, the extent of LD across the genome remains unexplored. In this study, we calculated autosomal LD based on genome-wide SNPs of 635 Chinese Merino (Xinjiang type) sheep by Illumina Ovine SNP50 BeadChip. A moderate level of LD (r2 ≥ 0.25) across the whole genome was observed at short distances of 0–10 kb. Further, the ancestral effective population size (Ne) was analyzed by extent of LD and found that Ne increased with the increase of generations and declined rapidly within the most recent 50 generations, which is consistent with the history of Chinese Merino sheep breeding, initiated in 1971. We also noted that even when the effective population size was estimated across different single chromosomes, Ne only ranged from 140.36 to 183.33 at five generations in the past, exhibiting a rapid decrease compared with that at ten generations in the past. These results indicated that the genetic diversity in Chinese Merino sheep recently decreased and proper protective measures should be taken to maintain the diversity. Our datasets provided essential genetic information to track molecular variations which potentially contribute to phenotypic variation in Chinese Merino sheep.
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38
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Böckerman P, Viinikainen J, Vainiomäki J, Hintsanen M, Pitkänen N, Lehtimäki T, Pehkonen J, Rovio S, Raitakari O. Stature and long-term labor market outcomes: Evidence using Mendelian randomization. ECONOMICS AND HUMAN BIOLOGY 2017; 24:18-29. [PMID: 27846416 DOI: 10.1016/j.ehb.2016.10.009] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2016] [Revised: 10/21/2016] [Accepted: 10/27/2016] [Indexed: 06/06/2023]
Abstract
We use the Young Finns Study (N=∼2000) on the measured height linked to register-based long-term labor market outcomes. The data contain six age cohorts (ages 3, 6, 9, 12, 15 and 18, in 1980) with the average age of 31.7, in 2001, and with the female share of 54.7. We find that taller people earn higher earnings according to the ordinary least squares (OLS) estimation. The OLS models show that 10cm of extra height is associated with 13% higher earnings. We use Mendelian randomization, with the genetic score as an instrumental variable (IV) for height to account for potential confounders that are related to socioeconomic background, early life conditions and parental investments, which are otherwise very difficult to fully account for when using covariates in observational studies. The IV point estimate is much lower and not statistically significant, suggesting that the OLS estimation provides an upward biased estimate for the height premium. Our results show the potential value of using genetic information to gain new insights into the determinants of long-term labor market success.
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Affiliation(s)
- Petri Böckerman
- Turku School of Economics, Labour Institute for Economic Research, Helsinki, Finland.
| | - Jutta Viinikainen
- Jyväskylä University School of Business and Economics, Jyväskylä, Finland
| | | | | | - Niina Pitkänen
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and School of Medicine, University of Tampere, Finland
| | - Jaakko Pehkonen
- Jyväskylä University School of Business and Economics, Jyväskylä, Finland
| | - Suvi Rovio
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Olli Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku and Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
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39
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Soderquest K, Hertweck A, Giambartolomei C, Henderson S, Mohamed R, Goldberg R, Perucha E, Franke L, Herrero J, Plagnol V, Jenner RG, Lord GM. Genetic variants alter T-bet binding and gene expression in mucosal inflammatory disease. PLoS Genet 2017; 13:e1006587. [PMID: 28187197 PMCID: PMC5328407 DOI: 10.1371/journal.pgen.1006587] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2016] [Revised: 02/27/2017] [Accepted: 01/17/2017] [Indexed: 01/21/2023] Open
Abstract
The polarization of CD4+ T cells into distinct T helper cell lineages is essential for protective immunity against infection, but aberrant T cell polarization can cause autoimmunity. The transcription factor T-bet (TBX21) specifies the Th1 lineage and represses alternative T cell fates. Genome-wide association studies have identified single nucleotide polymorphisms (SNPs) that may be causative for autoimmune diseases. The majority of these polymorphisms are located within non-coding distal regulatory elements. It is considered that these genetic variants contribute to disease by altering the binding of regulatory proteins and thus gene expression, but whether these variants alter the binding of lineage-specifying transcription factors has not been determined. Here, we show that SNPs associated with the mucosal inflammatory diseases Crohn's disease, ulcerative colitis (UC) and celiac disease, but not rheumatoid arthritis or psoriasis, are enriched at T-bet binding sites. Furthermore, we identify disease-associated variants that alter T-bet binding in vitro and in vivo. ChIP-seq for T-bet in individuals heterozygous for the celiac disease-associated SNPs rs1465321 and rs2058622 and the IBD-associated SNPs rs1551398 and rs1551399, reveals decreased binding to the minor disease-associated alleles. Furthermore, we show that rs1465321 is an expression quantitative trait locus (eQTL) for the neighboring gene IL18RAP, with decreased T-bet binding associated with decreased expression of this gene. These results suggest that genetic polymorphisms may predispose individuals to mucosal autoimmune disease through alterations in T-bet binding. Other disease-associated variants may similarly act by modulating the binding of lineage-specifying transcription factors in a tissue-selective and disease-specific manner.
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Affiliation(s)
- Katrina Soderquest
- Department of Experimental Immunobiology, King’s College London, London, United Kingdom
- NIHR Biomedical Research Centre at Guy’s and St Thomas’ Hospital and King’s College London, London, United Kingdom
| | - Arnulf Hertweck
- UCL Cancer Institute, University College London, London, United Kingdom
| | | | - Stephen Henderson
- UCL Cancer Institute, University College London, London, United Kingdom
| | - Rami Mohamed
- Department of Experimental Immunobiology, King’s College London, London, United Kingdom
- NIHR Biomedical Research Centre at Guy’s and St Thomas’ Hospital and King’s College London, London, United Kingdom
- The Francis Crick Institute, London, United Kingdom
| | - Rimma Goldberg
- Department of Experimental Immunobiology, King’s College London, London, United Kingdom
- NIHR Biomedical Research Centre at Guy’s and St Thomas’ Hospital and King’s College London, London, United Kingdom
| | - Esperanza Perucha
- Department of Experimental Immunobiology, King’s College London, London, United Kingdom
| | - Lude Franke
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Javier Herrero
- UCL Cancer Institute, University College London, London, United Kingdom
| | - Vincent Plagnol
- UCL Genetics Institute, University College London, London, United Kingdom
| | - Richard G. Jenner
- UCL Cancer Institute, University College London, London, United Kingdom
| | - Graham M. Lord
- Department of Experimental Immunobiology, King’s College London, London, United Kingdom
- NIHR Biomedical Research Centre at Guy’s and St Thomas’ Hospital and King’s College London, London, United Kingdom
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40
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Neville MJ, Lee W, Humburg P, Wong D, Barnardo M, Karpe F, Knight JC. High resolution HLA haplotyping by imputation for a British population bioresource. Hum Immunol 2017; 78:242-251. [PMID: 28111166 PMCID: PMC5367449 DOI: 10.1016/j.humimm.2017.01.006] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2016] [Revised: 12/03/2016] [Accepted: 01/17/2017] [Indexed: 12/02/2022]
Abstract
This study aimed to establish the occurrence and frequency of HLA alleles and haplotypes for a healthy British Caucasian population bioresource from Oxfordshire. We present the results of imputation from HLA SNP genotyping data using SNP2HLA for 5553 individuals from Oxford Biobank, defining one- and two-field alleles together with amino acid polymorphisms. We show that this achieves a high level of accuracy with validation using sequence-specific primer amplification PCR. We define six- and eight-locus HLA haplotypes for this population by Bayesian methods implemented using PHASE. We determine patterns of linkage disequilibrium and recombination for these individuals involving classical HLA loci and show how analysis within a haplotype block structure may be more tractable for imputed data. Our findings contribute to knowledge of HLA diversity in healthy populations and further validate future large-scale use of HLA imputation as an informative approach in population bioresources.
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Affiliation(s)
- Matt J Neville
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Old Road, Oxford OX3 7LJ, UK; Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford, UK
| | - Wanseon Lee
- Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK
| | - Peter Humburg
- Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK
| | - Daniel Wong
- Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK
| | - Martin Barnardo
- Transplant Immunology and Immunogenetics Laboratory, Oxford Transplant Centre, Churchill Hospital, Oxford OX3 7LJ, UK
| | - Fredrik Karpe
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Old Road, Oxford OX3 7LJ, UK; Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford, UK
| | - Julian C Knight
- Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK.
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Abstract
The last decade has seen substantial advances in the understanding of the genetics of complex traits and disease. This has been largely driven by genome-wide association studies (GWAS), which have identified thousands of genetic loci associated with these traits and disease. This chapter provides a guide on how to perform GWAS on both binary (case-control) and quantitative traits. As poor data quality, through both genotyping failures and unobserved population structure, is a major cause of false-positive genetic associations, there is a particular focus on the crucial steps required to prepare the SNP data prior to analysis. This is followed by the methods used to perform the actual GWAS and visualization of the results.
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Affiliation(s)
- Allan F McRae
- Centre for Neurogenetics and Statistical Genomics, Queensland Brain Institute, The University of Queensland, St Lucia, QLD, 4072, Australia.
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Buitenhuis B, Poulsen NA, Gebreyesus G, Larsen LB. Estimation of genetic parameters and detection of chromosomal regions affecting the major milk proteins and their post translational modifications in Danish Holstein and Danish Jersey cattle. BMC Genet 2016; 17:114. [PMID: 27485317 PMCID: PMC4969662 DOI: 10.1186/s12863-016-0421-2] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2016] [Accepted: 07/27/2016] [Indexed: 01/08/2023] Open
Abstract
Background In the Western world bovine milk products are an important protein source in human diet. The major proteins in bovine milk are the four caseins (CN), αS1-, αS2-, β-, and k-CN and the two whey proteins, β-LG and α-LA. It has been shown that both the amount of specific CN and their isoforms including post-translational modifications (PTM) influence technological properties of milk. Therefore, the aim of this study was to 1) estimate genetic parameters for individual proteins in Danish Holstein (DH) (n = 371) and Danish Jersey (DJ) (n = 321) milk, and 2) detect genomic regions associated with specific milk protein and their different PTM forms using a genome-wide association study (GWAS) approach. Results For DH, high heritability estimates were found for protein percentage (0.47), casein percentage (0.43), k-CN (0.77), β-LG (0.58), and α-LA (0.40). For DJ, high heritability estimates were found for protein percentage (0.70), casein percentage (0.52), and α-LA (0.44). The heritability for G-k-CN, U-k-CN and GD was higher in the DH compared to the DJ, whereas the heritability for the PD of αS1-CN was lower in DH compared to DJ, whereas the PD for αS2-CN was higher in DH compared to DJ. The GWAS results for the main milk proteins were in line what has been earlier published. However, we showed that there were SNPs specifically regulating G-k-CN in DH. Some of these SNPs were assigned to casein protein kinase genes (CSNK1G3, PRKCQ). Conclusion The genetic analysis of the major milk proteins and their PTM forms revealed that these were heritable in both DH and DJ. In DH, genomic regions specific for glycosylation of k-CN were detected. Furthermore, genomic regions for the major milk proteins confirmed the regions on BTA6 (casein cluster), BTA11 (PEAP), and BTA14 (DGAT1) as important regions influencing protein composition in milk. The results from this study provide confidence that it is possible to breed for specific milk protein including the different PTM forms. Electronic supplementary material The online version of this article (doi:10.1186/s12863-016-0421-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Bart Buitenhuis
- Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, Blichers Allé 20, P.O. Box 50, Tjele, DK-8830, Denmark.
| | - Nina A Poulsen
- Department of Food Science, Aarhus University, Blichers Allé 20, P.O. Box 50, Tjele, DK-8830, Denmark
| | - Grum Gebreyesus
- Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, Blichers Allé 20, P.O. Box 50, Tjele, DK-8830, Denmark
| | - Lotte B Larsen
- Department of Food Science, Aarhus University, Blichers Allé 20, P.O. Box 50, Tjele, DK-8830, Denmark
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Pitkänen N, Juonala M, Rönnemaa T, Sabin MA, Hutri-Kähönen N, Kähönen M, Lehtimäki T, Viikari JSA, Raitakari OT. Role of Conventional Childhood Risk Factors Versus Genetic Risk in the Development of Type 2 Diabetes and Impaired Fasting Glucose in Adulthood: The Cardiovascular Risk in Young Finns Study. Diabetes Care 2016; 39:1393-9. [PMID: 27298332 DOI: 10.2337/dc16-0167] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2016] [Accepted: 05/06/2016] [Indexed: 02/03/2023]
Abstract
OBJECTIVE We examined whether the addition of novel genetic risk variant data to conventional childhood risk factors improves risk assessment of impaired fasting glucose (IFG) and type 2 diabetes in adulthood. RESEARCH DESIGN AND METHODS An association of a weighted genetic risk score (wGRS) based on 73 risk variants with IFG and type 2 diabetes was analyzed in 2,298 participants of the Cardiovascular Risk in Young Finns Study who were followed for 24-31 years from childhood to adulthood. In addition, the value of the wGRS in pediatric prediction of type 2 diabetes was examined. RESULTS Of the 2,298 participants, 484 (21.8%) and 79 (3.4%) had IFG or type 2 diabetes in adulthood, respectively. Adjusting for age, sex, baseline BMI, parental diabetes, mother's BMI, fasting insulin concentration, systolic blood pressure, and smoking status, wGRS was associated with an increased risk of IFG (odds ratio 1.64 [95% CI 1.33-2.01] per unit increase in the wGRS) and type 2 diabetes (2.22 [1.43-3.44]). Incorporating wGRS into pediatric risk models improved model discrimination and reclassification properties. Area under the receiver operating curve improved for IFG (from 0.678 to 0.691, P = 0.015), combined IFG and type 2 diabetes outcome (from 0.678 to 0.692, P = 0.007), and type 2 diabetes (from 0.728 to 0.749, P = 0.158). The net reclassification improvement and integrated discrimination improvement were significant for all outcomes. CONCLUSIONS A multifactorial approach combining genetic and clinical risk factors may be useful in identifying children at high risk for adult IFG and type 2 diabetes.
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Affiliation(s)
- Niina Pitkänen
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Markus Juonala
- Division of Medicine, Turku University Hospital, Turku, Finland Department of Medicine, University of Turku, Turku, Finland
| | - Tapani Rönnemaa
- Division of Medicine, Turku University Hospital, Turku, Finland Department of Medicine, University of Turku, Turku, Finland
| | - Matthew A Sabin
- Murdoch Childrens Research Institute, Royal Children's Hospital, Australia, and Department of Paediatrics, University of Melbourne, Melbourne, VIC, Australia
| | - Nina Hutri-Kähönen
- Department of Pediatrics, University of Tampere, and Tampere University Hospital, Tampere, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, University of Tampere, and Tampere University Hospital, Tampere, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, and School of Medicine, University of Tampere, Tampere, Finland
| | - Jorma S A Viikari
- Division of Medicine, Turku University Hospital, Turku, Finland Department of Medicine, University of Turku, Turku, Finland
| | - Olli T Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
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Li G. A new model calling procedure for Illumina BeadArray data. BMC Genet 2016; 17:90. [PMID: 27343118 PMCID: PMC4921002 DOI: 10.1186/s12863-016-0398-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2016] [Accepted: 06/16/2016] [Indexed: 11/10/2022] Open
Abstract
Background Accurate genotype calling for high throughput Illumina data is an important step to extract more genetic information for a large scale genome wide association studies. Many popular calling algorithms use mixture models to infer genotypes of a large number of single nucleotide polymorphisms in a fast and efficient way. In practice, mixture models are mostly restricted to infer genotypes for common SNPs where their minor allele frequencies are quite large. However, it is still challenging to accurately genotype rare variants, especially for some rare variants where the boundaries of their genotypes are not clearly defined. Results To further improve the call accuracy and the quality of genotypes on rare variants, a new model calling procedure, named M-D, is proposed to infer genotypes for the Illumina BeadArray data. In this calling procedure, a Gaussian Mixture Model and a Dirichlet Process Gaussian Mixture Model are integrated to infer genotypes. Conclusions Applications to Illumina data illustrate that this new approach can improve calling performance compared to other popular genotyping algorithms.
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Affiliation(s)
- Gengxin Li
- Department of Mathematics and Statistics, Wright State University, 3640 Colonel Glenn Hwy, Dayton, 45435, USA.
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Cheng TH, Thompson DJ, O'Mara TA, Painter JN, Glubb DM, Flach S, Lewis A, French JD, Freeman-Mills L, Church D, Gorman M, Martin L, Hodgson S, Webb PM, Attia J, Holliday EG, McEvoy M, Scott RJ, Henders AK, Martin NG, Montgomery GW, Nyholt DR, Ahmed S, Healey CS, Shah M, Dennis J, Fasching PA, Beckmann MW, Hein A, Ekici AB, Hall P, Czene K, Darabi H, Li J, Dörk T, Dürst M, Hillemanns P, Runnebaum I, Amant F, Schrauwen S, Zhao H, Lambrechts D, Depreeuw J, Dowdy SC, Goode EL, Fridley BL, Winham SJ, Njølstad TS, Salvesen HB, Trovik J, Werner HM, Ashton K, Otton G, Proietto T, Liu T, Mints M, Tham E, Consortium C, Jun Li M, Yip SH, Wang J, Bolla MK, Michailidou K, Wang Q, Tyrer JP, Dunlop M, Houlston R, Palles C, Hopper JL, Peto J, Swerdlow AJ, Burwinkel B, Brenner H, Meindl A, Brauch H, Lindblom A, Chang-Claude J, Couch FJ, Giles GG, Kristensen VN, Cox A, Cunningham JM, Pharoah PDP, Dunning AM, Edwards SL, Easton DF, Tomlinson I, Spurdle AB. Five endometrial cancer risk loci identified through genome-wide association analysis. Nat Genet 2016; 48:667-674. [PMID: 27135401 PMCID: PMC4907351 DOI: 10.1038/ng.3562] [Citation(s) in RCA: 58] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2015] [Accepted: 04/08/2016] [Indexed: 12/18/2022]
Abstract
We conducted a meta-analysis of three endometrial cancer genome-wide association studies (GWAS) and two follow-up phases totaling 7,737 endometrial cancer cases and 37,144 controls of European ancestry. Genome-wide imputation and meta-analysis identified five new risk loci of genome-wide significance at likely regulatory regions on chromosomes 13q22.1 (rs11841589, near KLF5), 6q22.31 (rs13328298, in LOC643623 and near HEY2 and NCOA7), 8q24.21 (rs4733613, telomeric to MYC), 15q15.1 (rs937213, in EIF2AK4, near BMF) and 14q32.33 (rs2498796, in AKT1, near SIVA1). We also found a second independent 8q24.21 signal (rs17232730). Functional studies of the 13q22.1 locus showed that rs9600103 (pairwise r(2) = 0.98 with rs11841589) is located in a region of active chromatin that interacts with the KLF5 promoter region. The rs9600103[T] allele that is protective in endometrial cancer suppressed gene expression in vitro, suggesting that regulation of the expression of KLF5, a gene linked to uterine development, is implicated in tumorigenesis. These findings provide enhanced insight into the genetic and biological basis of endometrial cancer.
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Affiliation(s)
- Timothy Ht Cheng
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Deborah J Thompson
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Tracy A O'Mara
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Jodie N Painter
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Dylan M Glubb
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Susanne Flach
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Annabelle Lewis
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Juliet D French
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Luke Freeman-Mills
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - David Church
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Maggie Gorman
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Lynn Martin
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Shirley Hodgson
- Department of Clinical Genetics, St George's, University of London, London, UK
| | - Penelope M Webb
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - John Attia
- Hunter Medical Research Institute, John Hunter Hospital, Newcastle, NSW, Australia
- Centre for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, University of Newcastle, NSW, Australia
| | - Elizabeth G Holliday
- Hunter Medical Research Institute, John Hunter Hospital, Newcastle, NSW, Australia
- Centre for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, University of Newcastle, NSW, Australia
| | - Mark McEvoy
- Centre for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, University of Newcastle, NSW, Australia
| | - Rodney J Scott
- Hunter Medical Research Institute, John Hunter Hospital, Newcastle, NSW, Australia
- Hunter Area Pathology Service, John Hunter Hospital, Newcastle, NSW, Australia
- Centre for Information Based Medicine, University of Newcastle, NSW, Australia
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, NSW, Australia
| | - Anjali K Henders
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Nicholas G Martin
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Grant W Montgomery
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Dale R Nyholt
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia
| | - Shahana Ahmed
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Catherine S Healey
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Mitul Shah
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Peter A Fasching
- University of California at Los Angeles, Department of Medicine, Division of Hematology/Oncology, David Geffen School of Medicine, Los Angeles, CA, USA
- Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Matthias W Beckmann
- Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Alexander Hein
- Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Arif B Ekici
- Institute of Human Genetics, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Hatef Darabi
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Jingmei Li
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Thilo Dörk
- Hannover Medical School, Gynaecology Research Unit, Hannover, Germany
| | - Matthias Dürst
- Department of Gynaecology, Jena University Hospital - Friedrich Schiller University, Jena, Germany
| | - Peter Hillemanns
- Hannover Medical School, Clinics of Gynaecology and Obstetrics, Hannover, Germany
| | - Ingo Runnebaum
- Department of Gynaecology, Jena University Hospital - Friedrich Schiller University, Jena, Germany
| | - Frederic Amant
- Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, University Hospitals, KU Leuven - University of Leuven, Belgium
| | - Stefanie Schrauwen
- Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, University Hospitals, KU Leuven - University of Leuven, Belgium
| | - Hui Zhao
- Vesalius Research Center, VIB, Leuven, Belgium
- Laboratory for Translational Genetics, Department of Oncology, University Hospitals Leuven, Leuven, Belgium
| | - Diether Lambrechts
- Vesalius Research Center, VIB, Leuven, Belgium
- Laboratory for Translational Genetics, Department of Oncology, University Hospitals Leuven, Leuven, Belgium
| | - Jeroen Depreeuw
- Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, University Hospitals, KU Leuven - University of Leuven, Belgium
- Vesalius Research Center, VIB, Leuven, Belgium
- Laboratory for Translational Genetics, Department of Oncology, University Hospitals Leuven, Leuven, Belgium
| | - Sean C Dowdy
- Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Mayo Clinic, Rochester, MN, USA
| | - Ellen L Goode
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Brooke L Fridley
- Department of Biostatistics, University of Kansas Medical Center, Kansas City, KS, USA
| | - Stacey J Winham
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Tormund S Njølstad
- Centre for Cancerbiomarkers, Department of Clinical Science, The University of Bergen, Norway
- Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway
| | - Helga B Salvesen
- Centre for Cancerbiomarkers, Department of Clinical Science, The University of Bergen, Norway
- Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway
| | - Jone Trovik
- Centre for Cancerbiomarkers, Department of Clinical Science, The University of Bergen, Norway
- Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway
| | - Henrica Mj Werner
- Centre for Cancerbiomarkers, Department of Clinical Science, The University of Bergen, Norway
- Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway
| | - Katie Ashton
- Hunter Medical Research Institute, John Hunter Hospital, Newcastle, NSW, Australia
- Centre for Information Based Medicine, University of Newcastle, NSW, Australia
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, NSW, Australia
| | - Geoffrey Otton
- School of Medicine and Public Health, University of Newcastle, Newcastle, NSW, Australia
| | - Tony Proietto
- School of Medicine and Public Health, University of Newcastle, Newcastle, NSW, Australia
| | - Tao Liu
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Miriam Mints
- Department of Women's and Children's Health, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
| | - Emma Tham
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Clinical Genetics, Karolinska University Hospital Solna, Stockholm, Sweden
| | - Chibcha Consortium
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- A list of members and affiliations appears in the Supplementary Note
| | - Mulin Jun Li
- Centre for Genomic Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Shun H Yip
- Centre for Genomic Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Junwen Wang
- Centre for Genomic Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Manjeet K Bolla
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Kyriaki Michailidou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Qin Wang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Jonathan P Tyrer
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Malcolm Dunlop
- Colon Cancer Genetics Group, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, Western General Hospital Edinburgh, Edinburgh, UK
| | - Richard Houlston
- Division of Genetics and Epidemiology, Institute of Cancer Research, London, UK
| | - Claire Palles
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Vic, Australia
| | - Julian Peto
- London School of Hygiene and Tropical Medicine, London, UK
| | - Anthony J Swerdlow
- Division of Genetics and Epidemiology, Institute of Cancer Research, London, UK
- Division of Breast Cancer Research, Institute of Cancer Research, London, UK
| | - Barbara Burwinkel
- Molecular Biology of Breast Cancer, Department of Gynecology and Obstetrics, University of Heidelberg, Heidelberg, Germany
- Molecular Epidemiology Group, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Alfons Meindl
- Department of Obstetrics and Gynecology, Division of Tumor Genetics, Technical University of Munich, Munich, Germany
| | - Hiltrud Brauch
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
- Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany
- University of Tübingen, Tübingen, Germany
| | - Annika Lindblom
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- University Cancer Center Hamburg (UCCH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Fergus J Couch
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Graham G Giles
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Vic, Australia
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Vic, Australia
- Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Vic, Australia
| | - Vessela N Kristensen
- Department of Genetics, Institute for Cancer Research, The Norwegian Radium Hospital, Oslo, Norway
- Department of Clinical Molecular Oncology, Division of Medicine, Akershus University Hospital, Lørenskog, Norway
| | - Angela Cox
- Sheffield Cancer Research, Department of Oncology, University of Sheffield, Sheffield, UK
| | - Julie M Cunningham
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Paul D P Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Alison M Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Stacey L Edwards
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Ian Tomlinson
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Amanda B Spurdle
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
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Campoy JA, Lerigoleur-Balsemin E, Christmann H, Beauvieux R, Girollet N, Quero-García J, Dirlewanger E, Barreneche T. Genetic diversity, linkage disequilibrium, population structure and construction of a core collection of Prunus avium L. landraces and bred cultivars. BMC PLANT BIOLOGY 2016; 16:49. [PMID: 26912051 PMCID: PMC4765145 DOI: 10.1186/s12870-016-0712-9] [Citation(s) in RCA: 50] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2015] [Accepted: 01/11/2016] [Indexed: 05/18/2023]
Abstract
BACKGROUND Depiction of the genetic diversity, linkage disequilibrium (LD) and population structure is essential for the efficient organization and exploitation of genetic resources. The objectives of this study were to (i) to evaluate the genetic diversity and to detect the patterns of LD, (ii) to estimate the levels of population structure and (iii) to identify a 'core collection' suitable for association genetic studies in sweet cherry. RESULTS A total of 210 genotypes including modern cultivars and landraces from 16 countries were genotyped using the RosBREED cherry 6 K SNP array v1. Two groups, mainly bred cultivars and landraces, respectively, were first detected using STRUCTURE software and confirmed by Principal Coordinate Analysis (PCoA). Further analyses identified nine subgroups using STRUCTURE and Discriminant Analysis of Principal Components (DAPC). Several sub-groups correspond to different eco-geographic regions of landraces distribution. Linkage disequilibrium was evaluated showing lower values than in peach, the reference Prunus species. A 'core collection' containing 156 accessions was selected using the maximum length sub tree method. CONCLUSION The present study constitutes the first population genetics analysis in cultivated sweet cherry using a medium-density SNP (single nucleotide polymorphism) marker array. We provided estimations of linkage disequilibrium, genetic structure and the definition of a first INRA's Sweet Cherry core collection useful for breeding programs, germplasm management and association genetics studies.
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Affiliation(s)
- José Antonio Campoy
- INRA, UMR 1332 de Biologie du Fruit et Pathologie, F-33140, Villenave d'Ornon, France.
- University Bordeaux, UMR 1332 de Biologie du Fruit et Pathologie, F-33140, Villenave d'Ornon, France.
| | - Emilie Lerigoleur-Balsemin
- INRA, UMR 1332 de Biologie du Fruit et Pathologie, F-33140, Villenave d'Ornon, France.
- University Bordeaux, UMR 1332 de Biologie du Fruit et Pathologie, F-33140, Villenave d'Ornon, France.
- Current address: CNRS, UMR 5602 GEODE, Géographie de l'environnement, F-31058, Toulouse, France.
| | - Hélène Christmann
- INRA, UMR 1332 de Biologie du Fruit et Pathologie, F-33140, Villenave d'Ornon, France.
- University Bordeaux, UMR 1332 de Biologie du Fruit et Pathologie, F-33140, Villenave d'Ornon, France.
| | - Rémi Beauvieux
- INRA, UMR 1332 de Biologie du Fruit et Pathologie, F-33140, Villenave d'Ornon, France.
- University Bordeaux, UMR 1332 de Biologie du Fruit et Pathologie, F-33140, Villenave d'Ornon, France.
| | - Nabil Girollet
- INRA, UAR 0415 SDAR, Services Déconcentrés d'Appui à la Recherche, F 33140, Villenave d'Ornon, France.
- Current address: INRA, ISVV, UMR Ecophysiologie et Génomique Fonctionnelle de la Vigne, F 33140, Villenave d'Ornon, France.
| | - José Quero-García
- INRA, UMR 1332 de Biologie du Fruit et Pathologie, F-33140, Villenave d'Ornon, France.
- University Bordeaux, UMR 1332 de Biologie du Fruit et Pathologie, F-33140, Villenave d'Ornon, France.
| | - Elisabeth Dirlewanger
- INRA, UMR 1332 de Biologie du Fruit et Pathologie, F-33140, Villenave d'Ornon, France.
- University Bordeaux, UMR 1332 de Biologie du Fruit et Pathologie, F-33140, Villenave d'Ornon, France.
| | - Teresa Barreneche
- INRA, UMR 1332 de Biologie du Fruit et Pathologie, F-33140, Villenave d'Ornon, France.
- University Bordeaux, UMR 1332 de Biologie du Fruit et Pathologie, F-33140, Villenave d'Ornon, France.
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Fukushima A, Paul T, Shingaki R, Koiso T, Umeno S, Ueno K. A proposal for improvement of genotyping performance for ethnically homogeneous population using DNA microarray. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2016; 2015:6816-9. [PMID: 26737859 DOI: 10.1109/embc.2015.7319959] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
DNA microarray is used to determine the genotypes of several hundred thousand to several million SNPs (Single Nucleotide Polymorphisms) on multiple samples at a time. In the conventional method of genotyping using DNA microarray, it is assumed that each SNP has three types of genotypes: two homozygous and one heterozygous genotypes. However, in an ethnically homogeneous population, there are cases when all the samples of a SNP belong to one homozygous genotype, and there are some other cases, especially in the SNPs of low MAFs (Minor Allele Frequencies), each sample belongs to either of the two genotypes: one homozygous and one heterozygous genotypes. In those cases, the conventional method of genotyping may fail to properly determine the genotypes of the samples. In this paper, we propose a new genotyping method, which can be used as a post-processing technique of the conventional genotyping method, for re-judgment of the SNPs having one or two types of genotypes. The proposed method takes fluctuations of the fluorescence intensities of the signals of DNA microarray into account, assigns genotypes to samples from those genotype patterns that may occur under natural mating conditions and applies different genotype judgment methods depending on the number of genotype clusters of a SNP. We evaluate our proposed method using the data of 1000 Genome Project and have found that our proposed method is able to improve the genotyping performance of the conventional method.
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Bourgeois S, Jorgensen A, Zhang EJ, Hanson A, Gillman MS, Bumpstead S, Toh CH, Williamson P, Daly AK, Kamali F, Deloukas P, Pirmohamed M. A multi-factorial analysis of response to warfarin in a UK prospective cohort. Genome Med 2016; 8:2. [PMID: 26739746 PMCID: PMC4702374 DOI: 10.1186/s13073-015-0255-y] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2015] [Accepted: 12/10/2015] [Indexed: 01/13/2023] Open
Abstract
Background Warfarin is the most widely used oral anticoagulant worldwide, but it has a narrow therapeutic index which necessitates constant monitoring of anticoagulation response. Previous genome-wide studies have focused on identifying factors explaining variance in stable dose, but have not explored the initial patient response to warfarin, and a wider range of clinical and biochemical factors affecting both initial and stable dosing with warfarin. Methods A prospective cohort of 711 patients starting warfarin was followed up for 6 months with analyses focusing on both non-genetic and genetic factors. The outcome measures used were mean weekly warfarin dose (MWD), stable mean weekly dose (SMWD) and international normalised ratio (INR) > 4 during the first week. Samples were genotyped on the Illumina Human610-Quad chip. Statistical analyses were performed using Plink and R. Results VKORC1 and CYP2C9 were the major genetic determinants of warfarin MWD and SMWD, with CYP4F2 having a smaller effect. Age, height, weight, cigarette smoking and interacting medications accounted for less than 20 % of the variance. Our multifactorial analysis explained 57.89 % and 56.97 % of the variation for MWD and SMWD, respectively. Genotypes for VKORC1 and CYP2C9*3, age, height and weight, as well as other clinical factors such as alcohol consumption, loading dose and concomitant drugs were important for the initial INR response to warfarin. In a small subset of patients for whom data were available, levels of the coagulation factors VII and IX (highly correlated) also played a role. Conclusion Our multifactorial analysis in a prospectively recruited cohort has shown that multiple factors, genetic and clinical, are important in determining the response to warfarin. VKORC1 and CYP2C9 genetic polymorphisms are the most important determinants of warfarin dosing, and it is highly unlikely that other common variants of clinical importance influencing warfarin dosage will be found. Both VKORC1 and CYP2C9*3 are important determinants of the initial INR response to warfarin. Other novel variants, which did not reach genome-wide significance, were identified for the different outcome measures, but need replication. Electronic supplementary material The online version of this article (doi:10.1186/s13073-015-0255-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Stephane Bourgeois
- Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridgeshire, CB10 1SA, UK.
| | | | - Eunice J Zhang
- University of Liverpool, Liverpool, Merseyside, L69 3GE, UK.
| | - Anita Hanson
- University of Liverpool, Liverpool, Merseyside, L69 3GE, UK.
| | - Matthew S Gillman
- Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridgeshire, CB10 1SA, UK.
| | - Suzannah Bumpstead
- Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridgeshire, CB10 1SA, UK.
| | - Cheng Hock Toh
- University of Liverpool, Liverpool, Merseyside, L69 3GE, UK.
| | | | - Ann K Daly
- Newcastle University, Newcastle upon Tyne, UK.
| | | | - Panos Deloukas
- Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridgeshire, CB10 1SA, UK. .,William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK.
| | - Munir Pirmohamed
- University of Liverpool, Liverpool, Merseyside, L69 3GE, UK. .,Royal Liverpool and Broadgreen University Hospital NHS Trust, Liverpool, L7 8XP, UK. .,The Wolfson Centre for Personalised Medicine, Institute of Translational Medicine, University of Liverpool, Block A: Waterhouse Building, 1-5 Brownlow Street, Liverpool, L69 3GL, UK.
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Lassen J, Poulsen NA, Larsen MK, Buitenhuis AJ. Genetic and genomic relationship between methane production measured in breath and fatty acid content in milk samples from Danish Holsteins. ANIMAL PRODUCTION SCIENCE 2016. [DOI: 10.1071/an15489] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
In this study the objective was to estimate the genetic and genomic relationship between methane-related traits and milk fatty acid profiles. This was done using two different estimation procedures: a single nucleotide polymorphism-based genomic relationship matrix and a classical pedigree-based relationship matrix. Data was generated on three Danish Holstein herds and a total of 339 cows were available for the study. Methane phenotypes were generated in milking robots during milking over a weekly period and the milk phenotypes were quantified from milk from one milking. Genetic and genomic parameters were estimated using a mixed linear model. Results showed that heritability estimates were comparable between models, but the standard error was lower for genomic heritabilities compared with genetic heritabilities. Genetic as well as genomic correlations were highly variable and had high standard errors, reflecting a similar pattern as for the heritability estimates with lower standard errors for the genomic correlations compared with the pedigree-based genetic correlations. Many of the correlations though had a magnitude that makes further studies on larger datasets worthwhile. The results indicate that genotypes are highly valuable in studies where limited number of phenotypes can be recorded. Also it shows that there is some significant genetic association between methane in the breath of the cow and milk fatty acids profiles.
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Sinisalo J, Vlachopoulou E, Marchesani M, Nokelainen J, Mäyränpää MI, Lappalainen J, Paakkanen R, Wennerström A, Salli K, Niemi HJ, Männistö S, Salo P, Junttila J, Eskola M, Nikus K, Arstila TP, Perola M, Huikuri H, Karhunen PJ, Kovanen PT, Palotie A, Havulinna AS, Lluis-Ganella C, Marrugat J, Elosua R, Salomaa V, Nieminen MS, Lokki ML. Novel 6p21.3 Risk Haplotype Predisposes to Acute Coronary Syndrome. ACTA ACUST UNITED AC 2015; 9:55-63. [PMID: 26679868 DOI: 10.1161/circgenetics.115.001226] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2015] [Accepted: 12/16/2015] [Indexed: 12/19/2022]
Abstract
BACKGROUND The HLA-DRB1*01 allele of the human leukocyte antigen has been associated with acute coronary syndrome. Genome-wide association studies have revealed associations with human leukocyte antigen and non-human leukocyte antigen genes of 3 major histocompatibility complex gene classes but not at allelic level. METHODS AND RESULTS We conducted a large-scale genetic analysis on a case-control cohort comprising 5376 acute coronary syndrome cases and 4852 unrelated controls from 4 populations of 2 European countries. We analyzed the risk candidate allele of HLA-DRB1*01 by genomic real-time polymerase chain reaction together with high-density single nucleotide polymorphisms of the major histocompatibility complex to precisely identify risk loci for acute coronary syndrome with effective clinical implications. We found a risk haplotype for the disease containing single nucleotide polymorphisms from BTNL2 and HLA-DRA genes and the HLA-DRB1*01 allele. The association of the haplotype appeared in 3 of the 4 populations, and the direction of the effect was consistent in the fourth. Coronary samples from subjects homozygous for the disease-associated haplotype showed higher BTNL2 mRNA levels (r=0.760; P<0.00001).We localized, with immunofluorescence staining, BTNL2 in CD68-positive macrophages of the coronary artery plaques. In homozygous cases, BTNL2 blocking, in T-cell stimulation assays, enhanced CD4(+)FOXP3(+) regulatory T cell proliferation significantly (blocking versus nonblocking; P<0.05). CONCLUSIONS In cases with the risk haplotype for acute coronary syndrome, these results suggest involvement of enhanced immune reactions. BTNL2 may have an inhibitory effect on FOXP3(+) T cell proliferation, especially in patients homozygous for the risk alleles. CLINICAL TRIAL REGISTRATION https://www.clinicaltrials.gov; Unique Identifier: NCT00417534.
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