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Lu G, Liu H, Wang H, Tang X, Luo S, Du M, Christiani DC, Wei Q. Potentially functional variants of INPP5D and EXOSC3 in immunity B cell-related genes are associated with non-small cell lung cancer survival. Front Immunol 2024; 15:1440454. [PMID: 39176091 PMCID: PMC11338758 DOI: 10.3389/fimmu.2024.1440454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2024] [Accepted: 07/22/2024] [Indexed: 08/24/2024] Open
Abstract
B cells are adaptive immune cells in the tumor microenvironment and play an important role in tumor development and metastasis. However, the roles of genetic variants of the immunity B cell-related genes in the survival of patients with non-small cell lung cancer (NSCLC) remain unknown. In the present study, we first evaluated associations between 10,776 single nucleotide polymorphisms (SNPs) in 220 immunity B cell-related genes and survival of NSCLC in a discovery dataset of 1,185 patients from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. We found that 369 SNPs were significantly associated with overall survival (OS) of NSCLC in multivariable Cox proportional hazards regression analysis (P ≤ 0.05, Bayesian false discovery probability ≤ 0.80), of which 18 SNPs were validated in another independent genotyping dataset of 984 patients from the Harvard Lung Cancer Susceptibility (HLCS) Study. We then performed linkage disequilibrium (LD) analysis, followed by stepwise analysis with a multivariable Cox regression model. Finally, two independent SNPs, inositol polyphosphate-5-phosphatase D (INPP5D) rs13385922 C>T and exosome component 3 (EXOSC3) rs3208406 A>G, remained significantly associated withNSCLC OS with a combined hazards ratio (HR) of 1.14 (95% confidence interval = 1.06-1.23, P = 2.41×10-4) and 1.20 (95% confidence interval = 1.14-1.28, P = 3.41×10-9), respectively. Furthermore, NSCLC patients with the combination of unfavorable genotypes for these two SNPs were associated with a poor OS (P trend = 0.0002) and disease-specific survival (DSS, P trend < 0.0001) in the PLCO dataset. Expression quantitative trait loci (eQTL) analysis suggested that the INPP5D rs6782875 T allele was significantly correlated with elevated INPP5D mRNA expression levels in normal lung tissues and whole blood samples, while the EXOSC3 rs3208406 G allele was significantly correlated with increased EXOSC3 mRNA expression levels in normal lung tissues. Our data indicated that genetic variants in these immunity B cell-related genes may predict NSCLC survival possibly by influencing the gene expression.
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Affiliation(s)
- Guojun Lu
- Department of Respiratory Medicine, Nanjing Chest Hospital, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
- Duke Cancer Institute, Duke University Medical Center, Durham, NC, United States
- Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, United States
| | - Hongliang Liu
- Duke Cancer Institute, Duke University Medical Center, Durham, NC, United States
- Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, United States
| | - Huilin Wang
- Duke Cancer Institute, Duke University Medical Center, Durham, NC, United States
- Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, United States
- Department of Respiratory Oncology, Guangxi Cancer Hospital, Guangxi Medical University Cancer Hospital, Nanning, China
| | - Xiaozhun Tang
- Duke Cancer Institute, Duke University Medical Center, Durham, NC, United States
- Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, United States
- Department of Head and Neck Surgery, Guangxi Cancer Hospital, Guangxi Medical University Cancer Hospital, Nanning, China
| | - Sheng Luo
- Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, United States
| | - Mulong Du
- Departments of Environmental Health and Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, United States
| | - David C. Christiani
- Departments of Environmental Health and Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, United States
- Department of Medicine, Massachusetts General Hospital, Boston, MA, United States
| | - Qingyi Wei
- Duke Cancer Institute, Duke University Medical Center, Durham, NC, United States
- Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, United States
- Department of Medicine, Duke University Medical Center, Durham, NC, United States
- Duke Global Health Institute, Duke University Medical Center, Durham, NC, United States
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2
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Kelson VC, Kiser JN, Davenport KM, Suarez EM, Murdoch BM, Neibergs HL. Identifying Regions of the Genome Associated with Conception Rate to the First Service in Holstein Heifers Bred by Artificial Insemination and as Embryo Transfer Recipients. Genes (Basel) 2024; 15:765. [PMID: 38927701 PMCID: PMC11202900 DOI: 10.3390/genes15060765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2024] [Revised: 06/05/2024] [Accepted: 06/08/2024] [Indexed: 06/28/2024] Open
Abstract
Heifer conception rate to the first service (HCR1) is defined as the number of heifers that become pregnant to the first breeding service compared to the heifers bred. This study aimed to identify loci associated and gene sets enriched for HCR1 for heifers that were bred by artificial insemination (AI, n = 2829) or were embryo transfer (ET, n = 2086) recipients, by completing a genome-wide association analysis and gene set enrichment analysis using SNP data (GSEA-SNP). Three unique loci, containing four positional candidate genes, were associated (p < 1 × 10-5) with HCR1 for ET recipients, while the GSEA-SNP identified four gene sets (NES ≥ 3) and sixty-two leading edge genes (LEGs) enriched for HCR1. While no loci were associated with HCR1 bred by AI, one gene set and twelve LEGs were enriched (NES ≥ 3) for HCR1 with the GSEA-SNP. This included one gene (PKD2) shared between HCR1 AI and ET services. Identifying loci associated or enriched for HCR1 provides an opportunity to use them as genomic selection tools to facilitate the selection of cattle with higher reproductive efficiency, and to better understand embryonic loss.
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Affiliation(s)
- Victoria C. Kelson
- Department of Animal Sciences, Washington State University, Pullman, WA 99163, USA; (V.C.K.); (K.M.D.); (E.M.S.)
| | - Jennifer N. Kiser
- Washington Animal Disease Diagnostics Laboratory, Pullman, WA 99164, USA;
| | - Kimberly M. Davenport
- Department of Animal Sciences, Washington State University, Pullman, WA 99163, USA; (V.C.K.); (K.M.D.); (E.M.S.)
| | - Emaly M. Suarez
- Department of Animal Sciences, Washington State University, Pullman, WA 99163, USA; (V.C.K.); (K.M.D.); (E.M.S.)
| | - Brenda M. Murdoch
- Department of Animal, Veterinary and Food Sciences, University of Idaho, Moscow, ID 83844, USA;
| | - Holly L. Neibergs
- Department of Animal Sciences, Washington State University, Pullman, WA 99163, USA; (V.C.K.); (K.M.D.); (E.M.S.)
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3
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Gurung RL, Burdon KP, McComish BJ. A Guide to Genome-Wide Association Study Design for Diabetic Retinopathy. Methods Mol Biol 2023; 2678:49-89. [PMID: 37326705 DOI: 10.1007/978-1-0716-3255-0_5] [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] [Indexed: 06/17/2023]
Abstract
Diabetic retinopathy (DR) is the most common microvascular complication related to diabetes. There is evidence that genetics play an important role in DR pathogenesis, but the complexity of the disease makes genetic studies a challenge. This chapter is a practical overview of the basic steps for genome-wide association studies with respect to DR and its associated traits. Also described are approaches that can be adopted in future DR studies. This is intended to serve as a guide for beginners and to provide a framework for further in-depth analysis.
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Affiliation(s)
- Rajya L Gurung
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia.
| | - Kathryn P Burdon
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia.
| | - Bennet J McComish
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia
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4
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Gao G, Chen P, Zhou C, Zhao X, Zhang K, Wu R, Zhang C, Wang Y, Xie Y, Wang Q. Genome-wide association study for reproduction-related traits in Chinese domestic goose. Br Poult Sci 2022; 63:754-760. [PMID: 35775663 DOI: 10.1080/00071668.2022.2096402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
1. This study measured six reproduction traits in a Sichuan white goose population (209 individuals), including fertility, qualified egg rate, plasma concentrations of progesterone (P), follicle-stimulating hormone (FSH), prolactin (PRL) and oestrogen (E2).2. Whole-genome resequencing data from the same goose population (209 individuals) were used in a genome-wide association study (GWAS) utilising a mixed linear model to investigate the genes and genetic markers associated with reproduction traits. The frequency of the selected SNPs and haplotypes were determined using the Matrix-Assisted Laser Desorption Ionisation Time-Of-Flight Mass Spectrometry (MALDI-TOF MS) method.3. In total, 42 SNPs significantly associated with these traits were identified. A haplotype block was constructed based on five SNPs that were significantly associated with qualified egg rate, with individuals having the haplotype CCTTAAGGAA having the lowest qualified egg rate.4. In conclusion, these results provided potential markers for marker-assisted selection to improve goose reproductive performance and a basis for elucidating the genetics of goose reproduction.
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Affiliation(s)
- G Gao
- Department of Poultry Science, Chongqing Academy of Animal Science, Chongqing, P. R. China.,Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan, P. R. China.,Chongqing Engineering Research Center of Goose Genetic Improvement, Chongqing, P. R. China
| | - P Chen
- Animal Husbandry and Veterinary Station, Sucheng District Suqian, Jiangsu, P. R. China
| | - C Zhou
- Department of Poultry Science, Chongqing Academy of Animal Science, Chongqing, P. R. China.,Chongqing Engineering Research Center of Goose Genetic Improvement, Chongqing, P. R. China
| | - X Zhao
- Department of Poultry Science, Chongqing Academy of Animal Science, Chongqing, P. R. China.,Chongqing Engineering Research Center of Goose Genetic Improvement, Chongqing, P. R. China
| | - K Zhang
- Department of Poultry Science, Chongqing Academy of Animal Science, Chongqing, P. R. China.,Chongqing Engineering Research Center of Goose Genetic Improvement, Chongqing, P. R. China
| | - R Wu
- Department of Poultry Science, Chongqing Academy of Animal Science, Chongqing, P. R. China.,Chongqing Engineering Research Center of Goose Genetic Improvement, Chongqing, P. R. China
| | - C Zhang
- Department of Poultry Science, Chongqing Academy of Animal Science, Chongqing, P. R. China.,Chongqing Engineering Research Center of Goose Genetic Improvement, Chongqing, P. R. China
| | - Y Wang
- Department of Poultry Science, Chongqing Academy of Animal Science, Chongqing, P. R. China.,Chongqing Engineering Research Center of Goose Genetic Improvement, Chongqing, P. R. China
| | - Y Xie
- Department of Poultry Science, Chongqing Academy of Animal Science, Chongqing, P. R. China.,Chongqing Engineering Research Center of Goose Genetic Improvement, Chongqing, P. R. China
| | - Q Wang
- Department of Poultry Science, Chongqing Academy of Animal Science, Chongqing, P. R. China.,Chongqing Engineering Research Center of Goose Genetic Improvement, Chongqing, P. R. China
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5
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The APOE locus is linked to decline in general cognitive function: 20-years follow-up in the Doetinchem Cohort Study. Transl Psychiatry 2022; 12:496. [PMID: 36446774 PMCID: PMC9708640 DOI: 10.1038/s41398-022-02258-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Revised: 11/08/2022] [Accepted: 11/14/2022] [Indexed: 11/30/2022] Open
Abstract
Cognitive decline is part of the normal aging process. However, some people experience a more rapid decline than others due to environmental and genetic factors. Numerous single nucleotide polymorphisms (SNPs) have been linked to cognitive function, but only a few to cognitive decline. To understand whether cognitive function and cognitive decline are driven by the same mechanisms, we investigated whether 433 SNPs previously linked to cognitive function and 2 SNPs previously linked to cognitive decline are associated with both general cognitive functioning at baseline and general cognitive decline up to 20-years follow-up in the Doetinchem Cohort Study (DCS). The DCS is a longitudinal population-based study that enrolled men and women aged 20-59 years between 1987-1991, with follow-up examinations every 5 years. We used data of rounds 2-6 (1993-2017, n = 2559). General cognitive function was assessed using four cognition tests measuring memory, speed, fluency and flexibility. With these test scores, standardized residuals (adjusted for sex, age and examination round) were calculated for each cognition test at each round and subsequently combined into one general cognitive function measure using principal component analyses. None of the 435 previously identified variants were associated with baseline general cognitive function in the DCS. But rs429358-C, a coding apolipoprotein E (APOE) SNP and one of the variants previously associated with cognitive decline, was associated with general cognitive decline in our study as well (p-value = 1 × 10-5, Beta = -0.013). These findings suggest that decline of general cognitive function is influenced by other mechanisms than those that are involved in the regulation of general cognitive function.
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Rudman N, Kifer D, Kaur S, Simunović V, Cvetko A, Pociot F, Morahan G, Gornik O. Children at onset of type 1 diabetes show altered N-glycosylation of plasma proteins and IgG. Diabetologia 2022; 65:1315-1327. [PMID: 35622127 PMCID: PMC9283363 DOI: 10.1007/s00125-022-05703-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2021] [Accepted: 02/09/2022] [Indexed: 11/29/2022]
Abstract
AIMS/HYPOTHESIS Individual variation in plasma N-glycosylation has mainly been studied in the context of diabetes complications, and its role in type 1 diabetes onset is largely unknown. Our aims were to undertake a detailed characterisation of the plasma and IgG N-glycomes in patients with recent onset type 1 diabetes, and to evaluate their discriminative potential in risk assessment. METHODS In the first part of the study, plasma and IgG N-glycans were chromatographically analysed in a study population from the DanDiabKids registry, comprising 1917 children and adolescents (0.6-19.1 years) who were newly diagnosed with type 1 diabetes. A follow-up study compared the results for 188 of these participants with those for their 244 unaffected siblings. Correlation of N-glycan abundance with the levels and number of various autoantibodies (against IA-2, GAD, ZnT8R, ZnT8W), as well as with sex and age at diagnosis, were estimated by using general linear modelling. A disease predictive model was built using logistic mixed-model elastic net regression, and evaluated using a 10-fold cross-validation. RESULTS Our study showed that onset of type 1 diabetes was associated with an increase in the proportion of plasma and IgG high-mannose and bisecting GlcNAc structures, a decrease in monogalactosylation, and an increase in IgG disialylation. ZnT8R autoantibody levels were associated with higher IgG digalactosylated glycan with bisecting GlcNAc. Finally, an increase in the number of autoantibodies (which is a better predictor of progression to overt diabetes than the level of any individual antibody) was accompanied by a decrease in the proportions of some of the highly branched plasma N-glycans. Models including age, sex and N-glycans yielded notable discriminative power between children with type 1 diabetes and their healthy siblings, with AUCs of 0.915 and 0.869 for addition of plasma and IgG N-glycans, respectively. CONCLUSIONS/INTERPRETATION We defined N-glycan changes accompanying onset of type 1 diabetes, and developed a predictive model based on N-glycan profiles that could have valuable potential in risk assessment. Increasing the power of tests to identify individuals at risk of disease development would be a considerable asset for type 1 diabetes prevention trials.
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Affiliation(s)
- Najda Rudman
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
| | - Domagoj Kifer
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
| | | | - Vesna Simunović
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
| | - Ana Cvetko
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
| | - Flemming Pociot
- Steno Diabetes Center Copenhagen, Herlev, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Copenhagen Diabetes Research Center (CPH-DIRECT), Department of Pediatrics E, Herlev Hospital, Herlev, Denmark
| | - Grant Morahan
- Centre for Diabetes Research, The Harry Perkins Institute for Medical Research, Perth, WA, Australia.
- University of Melbourne, Parkville, VIC, Australia.
| | - Olga Gornik
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia.
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7
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Landini A, Trbojević-Akmačić I, Navarro P, Tsepilov YA, Sharapov SZ, Vučković F, Polašek O, Hayward C, Petrović T, Vilaj M, Aulchenko YS, Lauc G, Wilson JF, Klarić L. Genetic regulation of post-translational modification of two distinct proteins. Nat Commun 2022; 13:1586. [PMID: 35332118 PMCID: PMC8948205 DOI: 10.1038/s41467-022-29189-5] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Accepted: 03/02/2022] [Indexed: 11/13/2022] Open
Abstract
Post-translational modifications diversify protein functions and dynamically coordinate their signalling networks, influencing most aspects of cell physiology. Nevertheless, their genetic regulation or influence on complex traits is not fully understood. Here, we compare the genetic regulation of the same PTM of two proteins - glycosylation of transferrin and immunoglobulin G (IgG). By performing genome-wide association analysis of transferrin glycosylation, we identify 10 significantly associated loci, 9 of which were not reported previously. Comparing these with IgG glycosylation-associated genes, we note protein-specific associations with genes encoding glycosylation enzymes (transferrin - MGAT5, ST3GAL4, B3GAT1; IgG - MGAT3, ST6GAL1), as well as shared associations (FUT6, FUT8). Colocalisation analyses of the latter suggest that different causal variants in the FUT genes regulate fucosylation of the two proteins. Glycosylation of these proteins is thus genetically regulated by both shared and protein-specific mechanisms.
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Affiliation(s)
- Arianna Landini
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, United Kingdom
| | | | - Pau Navarro
- MRC Human Genetics Unit, Institute for Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Yakov A Tsepilov
- Laboratory of Glycogenomics, Institute of Cytology and Genetics, Novosibirsk, Russia.,Laboratory of Theoretical and Applied Functional Genomics, Novosibirsk State University, Novosibirsk, Russia
| | - Sodbo Z Sharapov
- Laboratory of Glycogenomics, Institute of Cytology and Genetics, Novosibirsk, Russia
| | | | - Ozren Polašek
- Department of Public Health, School of Medicine, University of Split, Split, Croatia.,Algebra University College, Zagreb, Croatia
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute for Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Tea Petrović
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
| | - Marija Vilaj
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
| | - Yurii S Aulchenko
- Laboratory of Glycogenomics, Institute of Cytology and Genetics, Novosibirsk, Russia
| | - Gordan Lauc
- Genos Glycoscience Research Laboratory, Zagreb, Croatia.,Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
| | - James F Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, United Kingdom. .,MRC Human Genetics Unit, Institute for Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom.
| | - Lucija Klarić
- MRC Human Genetics Unit, Institute for Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom.
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8
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Linking genetic, morphological, and behavioural divergence between inland island and mainland deer mice. Heredity (Edinb) 2022; 128:97-106. [PMID: 34952930 PMCID: PMC8814197 DOI: 10.1038/s41437-021-00492-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2021] [Revised: 12/09/2021] [Accepted: 12/10/2021] [Indexed: 02/03/2023] Open
Abstract
The island syndrome hypothesis (ISH) stipulates that, as a result of local selection pressures and restricted gene flow, individuals from island populations should differ from individuals within mainland populations. Specifically, island populations are predicted to contain individuals that are larger, less aggressive, more sociable, and that invest more in their offspring. To date, tests of the ISH have mainly compared oceanic islands to continental sites, and rarely smaller spatial scales such as inland watersheds. Here, using a novel set of genome-wide SNP markers in wild deer mice (Peromyscus maniculatus) we conducted a genomic assessment of predictions underlying the ISH in an inland riverine island system: analysing island-mainland population structure, and quantifying heritability of phenotypes thought to underlie the ISH. We found clear genomic differentiation between the island and mainland populations and moderate to high marker-based heritability estimates for overall variation in traits previously found to differ in line with the ISH between mainland and island locations. FST outlier analyses highlighted 12 loci associated with differentiation between mainland and island populations. Together these results suggest that the island populations examined are on independent evolutionary trajectories, the traits considered have a genetic basis (rather than phenotypic variation being solely due to phenotypic plasticity). Coupled with the previous results showing significant phenotypic differentiation between the island and mainland groups in this system, this study suggests that the ISH can hold even on a small spatial scale.
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9
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A multi-omics study of circulating phospholipid markers of blood pressure. Sci Rep 2022; 12:574. [PMID: 35022422 PMCID: PMC8755711 DOI: 10.1038/s41598-021-04446-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 12/13/2021] [Indexed: 01/02/2023] Open
Abstract
High-throughput techniques allow us to measure a wide-range of phospholipids which can provide insight into the mechanisms of hypertension. We aimed to conduct an in-depth multi-omics study of various phospholipids with systolic blood pressure (SBP) and diastolic blood pressure (DBP). The associations of blood pressure and 151 plasma phospholipids measured by electrospray ionization tandem mass spectrometry were performed by linear regression in five European cohorts (n = 2786 in discovery and n = 1185 in replication). We further explored the blood pressure-related phospholipids in Erasmus Rucphen Family (ERF) study by associating them with multiple cardiometabolic traits (linear regression) and predicting incident hypertension (Cox regression). Mendelian Randomization (MR) and phenome-wide association study (Phewas) were also explored to further investigate these association results. We identified six phosphatidylethanolamines (PE 38:3, PE 38:4, PE 38:6, PE 40:4, PE 40:5 and PE 40:6) and two phosphatidylcholines (PC 32:1 and PC 40:5) which together predicted incident hypertension with an area under the ROC curve (AUC) of 0.61. The identified eight phospholipids are strongly associated with triglycerides, obesity related traits (e.g. waist, waist-hip ratio, total fat percentage, body mass index, lipid-lowering medication, and leptin), diabetes related traits (e.g. glucose, insulin resistance and insulin) and prevalent type 2 diabetes. The genetic determinants of these phospholipids also associated with many lipoproteins, heart rate, pulse rate and blood cell counts. No significant association was identified by bi-directional MR approach. We identified eight blood pressure-related circulating phospholipids that have a predictive value for incident hypertension. Our cross-omics analyses show that phospholipid metabolites in the circulation may yield insight into blood pressure regulation and raise a number of testable hypothesis for future research.
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10
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Foo H, Thalamuthu A, Jiang J, Koch F, Mather KA, Wen W, Sachdev PS. Age- and Sex-Related Topological Organization of Human Brain Functional Networks and Their Relationship to Cognition. Front Aging Neurosci 2022; 13:758817. [PMID: 34975453 PMCID: PMC8718995 DOI: 10.3389/fnagi.2021.758817] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Accepted: 11/25/2021] [Indexed: 11/23/2022] Open
Abstract
Age and sex associated with changes in the functional brain network topology and cognition in large population of older adults have been poorly understood. We explored this question further by examining differences in 11 resting-state graph theory measures with respect to age, sex, and their relationships with cognitive performance in 17,127 United Kingdom Biobank participants (mean = 62.83 ± 7.41 years). Age was associated with an overall decrease in the effectiveness of network communication (i.e., integration) and loss of functional specialization (i.e., segregation) of specific brain regions. Sex differences were also observed, with women showing more efficient networks, which were less segregated than in men (FDR adjusted p < 0.05). The age-related changes were also more apparent in men than in women, which suggests that men may be more vulnerable to cognitive decline with age. Interestingly, while network segregation and strength of limbic network were only nominally associated with cognitive performance, the network measures collectively were significantly associated with cognition (FDR adjusted p ≤ 0.002). This may imply that individual measures may be inadequate to capture much of the variance in the neural activity or its output and need further refinement. The complexity of the organization of the functional brain may be shaped by the age and sex of an individual, which ultimately may influence the cognitive performance of older adults. Age and sex stratification may be used to inform clinical neuroscience research to identify older adults at risk of cognitive dysfunction.
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Affiliation(s)
- Heidi Foo
- Centre for Healthy Brain Aging, CHeBA, School of Psychiatry, University of New South Wales Medicine, Kensington, NSW, Australia
| | - Anbupalam Thalamuthu
- Centre for Healthy Brain Aging, CHeBA, School of Psychiatry, University of New South Wales Medicine, Kensington, NSW, Australia
| | - Jiyang Jiang
- Centre for Healthy Brain Aging, CHeBA, School of Psychiatry, University of New South Wales Medicine, Kensington, NSW, Australia
| | - Forrest Koch
- Centre for Healthy Brain Aging, CHeBA, School of Psychiatry, University of New South Wales Medicine, Kensington, NSW, Australia
| | - Karen A Mather
- Centre for Healthy Brain Aging, CHeBA, School of Psychiatry, University of New South Wales Medicine, Kensington, NSW, Australia.,Neuroscience Research Australia, Randwick, NSW, Australia
| | - Wei Wen
- Centre for Healthy Brain Aging, CHeBA, School of Psychiatry, University of New South Wales Medicine, Kensington, NSW, Australia
| | - Perminder S Sachdev
- Centre for Healthy Brain Aging, CHeBA, School of Psychiatry, University of New South Wales Medicine, Kensington, NSW, Australia.,Neuropsychiatric Institute, Euroa Centre, Prince of Wales Hospital, Randwick, NSW, Australia
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11
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Novel genetic variants associated with brain functional networks in 18,445 adults from the UK Biobank. Sci Rep 2021; 11:14633. [PMID: 34272439 PMCID: PMC8285376 DOI: 10.1038/s41598-021-94182-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 07/07/2021] [Indexed: 12/22/2022] Open
Abstract
Here, we investigated the genetics of weighted functional brain network graph theory measures from 18,445 participants of the UK Biobank (44–80 years). The eighteen measures studied showed low heritability (mean h2SNP = 0.12) and were highly genetically correlated. One genome-wide significant locus was associated with strength of somatomotor and limbic networks. These intergenic variants were located near the PAX8 gene on chromosome 2. Gene-based analyses identified five significantly associated genes for five of the network measures, which have been implicated in sleep duration, neuronal differentiation/development, cancer, and susceptibility to neurodegenerative diseases. Further analysis found that somatomotor network strength was phenotypically associated with sleep duration and insomnia. Single nucleotide polymorphism (SNP) and gene level associations with functional network measures were identified, which may help uncover novel biological pathways relevant to human brain functional network integrity and related disorders that affect it.
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12
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Mijakovac A, Jurić J, Kohrt WM, Krištić J, Kifer D, Gavin KM, Miškec K, Frkatović A, Vučković F, Pezer M, Vojta A, Nigrović PA, Zoldoš V, Lauc G. Effects of Estradiol on Immunoglobulin G Glycosylation: Mapping of the Downstream Signaling Mechanism. Front Immunol 2021; 12:680227. [PMID: 34113353 PMCID: PMC8186398 DOI: 10.3389/fimmu.2021.680227] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Accepted: 05/06/2021] [Indexed: 12/31/2022] Open
Abstract
Glycans attached to immunoglobulin G (IgG) directly affect this antibody effector functions and regulate inflammation at several levels. The composition of IgG glycome changes significantly with age. In women, the most notable change coincides with the perimenopausal period. Aiming to investigate the effect of estrogen on IgG glycosylation, we analysed IgG and total serum glycomes in 36 healthy premenopausal women enrolled in a randomized controlled trial of the gonadotropin-releasing hormone analogue (GnRHAG) leuprolide acetate to lower gonadal steroids to postmenopausal levels and then randomized to transdermal placebo or estradiol (E2) patch. The suppression of gonadal hormones induced significant changes in the IgG glycome, while E2 supplementation was sufficient to prevent changes. The observed glycan changes suggest that depletion of E2 primarily affects B cell glycosylation, while liver glycosylation stays mostly unchanged. To determine whether previously identified IgG GWAS hits RUNX1, RUNX3, SPINK4, and ELL2 are involved in downstream signaling mechanisms, linking E2 with IgG glycosylation, we used the FreeStyle 293-F transient system expressing IgG antibodies with stably integrated CRISPR/dCas9 expression cassettes for gene up- and downregulation. RUNX3 and SPINK4 upregulation using dCas9-VPR resulted in a decreased IgG galactosylation and, in the case of RUNX3, a concomitant increase in IgG agalactosylation.
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Affiliation(s)
- Anika Mijakovac
- Department of Molecular Biology, University of Zagreb Faculty of Science, Zagreb, Croatia
| | - Julija Jurić
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
| | - Wendy M. Kohrt
- Division of Geriatric Medicine, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
- Eastern Colorado VA Geriatric Research, Education and Clinical Center, Aurora, CO, United States
| | | | - Domagoj Kifer
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
| | - Kathleen M. Gavin
- Division of Geriatric Medicine, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
- Eastern Colorado VA Geriatric Research, Education and Clinical Center, Aurora, CO, United States
| | - Karlo Miškec
- Department of Molecular Biology, University of Zagreb Faculty of Science, Zagreb, Croatia
| | | | | | - Marija Pezer
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
| | - Aleksandar Vojta
- Department of Molecular Biology, University of Zagreb Faculty of Science, Zagreb, Croatia
| | - Peter A. Nigrović
- Division of Rheumatology, Immunology and Allergy, Brigham and Women´s Hospital, Boston, MA, United States
- Division of Immunology, Boston Children´s Hospital, Boston, MA, United States
| | - Vlatka Zoldoš
- Department of Molecular Biology, University of Zagreb Faculty of Science, Zagreb, Croatia
| | - Gordan Lauc
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
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13
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Gao G, Gao D, Zhao X, Xu S, Zhang K, Wu R, Yin C, Li J, Xie Y, Hu S, Wang Q. Genome-Wide Association Study-Based Identification of SNPs and Haplotypes Associated With Goose Reproductive Performance and Egg Quality. Front Genet 2021; 12:602583. [PMID: 33777090 PMCID: PMC7994508 DOI: 10.3389/fgene.2021.602583] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Accepted: 02/24/2021] [Indexed: 01/10/2023] Open
Abstract
Geese are one of the most economically important waterfowl. However, the low reproductive performance and egg quality of geese hinder the development of the goose industry. The identification and application of genetic markers may improve the accuracy of beneficial trait selection. To identify the genetic markers associated with goose reproductive performance and egg quality traits, we performed a genome-wide association study (GWAS) for body weight at birth (BBW), the number of eggs at 48 weeks of age (EN48), the number of eggs at 60 weeks of age (EN60) and egg yolk color (EYC). The GWAS acquired 2.896 Tb of raw sequencing data with an average depth of 12.44× and identified 9,279,339 SNPs. The results of GWAS showed that 26 SNPs were significantly associated with BBW, EN48, EN60, and EYC. Moreover, five of these SNPs significantly associated with EN48 and EN60 were in a haplotype block on chromosome 35 from 4,512,855 to 4,541,709 bp, oriented to TMEM161A and another five SNPs significantly correlated to EYC were constructed in haplotype block on chromosome 5 from 21,069,009 to 21,363,580, which annotated by TMEM161A, CALCR, TFPI2, and GLP1R. Those genes were enriched in epidermal growth factor-activated receptor activity, regulation of epidermal growth factor receptor signaling pathway. The SNPs, haplotype markers, and candidate genes identified in this study can be used to improve the accuracy of marker-assisted selection for the reproductive performance and egg quality traits of geese. In addition, the candidate genes significantly associated with these traits may provide a foundation for better understanding the mechanisms underlying reproduction and egg quality in geese.
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Affiliation(s)
- Guangliang Gao
- Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing, China
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
- Chongqing Engineering Research Center of Goose Genetic Improvement, Chongqing, China
| | - Dengfeng Gao
- State Key Laboratory of Agrobiotechnology, China Agricultural University, Beijing, China
| | - Xianzhi Zhao
- Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing, China
- Chongqing Engineering Research Center of Goose Genetic Improvement, Chongqing, China
| | | | - Keshan Zhang
- Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing, China
- Chongqing Engineering Research Center of Goose Genetic Improvement, Chongqing, China
| | - Rui Wu
- Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing, China
- Chongqing Engineering Research Center of Goose Genetic Improvement, Chongqing, China
| | - Chunhui Yin
- Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing, China
- Chongqing Engineering Research Center of Goose Genetic Improvement, Chongqing, China
| | - Jing Li
- Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing, China
- Chongqing Engineering Research Center of Goose Genetic Improvement, Chongqing, China
| | - Youhui Xie
- Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing, China
- Chongqing Engineering Research Center of Goose Genetic Improvement, Chongqing, China
| | - Silu Hu
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - Qigui Wang
- Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing, China
- Chongqing Engineering Research Center of Goose Genetic Improvement, Chongqing, China
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14
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Ceballos FC, Hazelhurst S, Clark DW, Agongo G, Asiki G, Boua PR, Xavier Gómez-Olivé F, Mashinya F, Norris S, Wilson JF, Ramsay M. Autozygosity influences cardiometabolic disease-associated traits in the AWI-Gen sub-Saharan African study. Nat Commun 2020; 11:5754. [PMID: 33188201 PMCID: PMC7666169 DOI: 10.1038/s41467-020-19595-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Accepted: 10/12/2020] [Indexed: 11/10/2022] Open
Abstract
The analysis of the effects of autozygosity, measured as the change of the mean value of a trait among offspring of genetic relatives, reveals the existence of directional dominance or overdominance. In this study we detect evidence of the effect of autozygosity in 4 out of 13 cardiometabolic disease-associated traits using data from more than 10,000 sub-Saharan African individuals recruited from Ghana, Burkina Faso, Kenya and South Africa. The effect of autozygosity on these phenotypes is found to be sex-related, with inbreeding having a significant decreasing effect in men but a significant increasing effect in women for several traits (body mass index, subcutaneous adipose tissue, low-density lipoproteins and total cholesterol levels). Overall, the effect of inbreeding depression is more intense in men. Differential effects of inbreeding depression are also observed between study sites with different night-light intensity used as proxy for urban development. These results suggest a directional dominant genetic component mediated by environmental interactions and sex-specific differences in genetic architecture for these traits in the Africa Wits-INDEPTH partnership for Genomic Studies (AWI-Gen) cohort.
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Affiliation(s)
- Francisco C Ceballos
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Scott Hazelhurst
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- School of Electrical & Information Engineering, University of the Witwatersrand, Johannesburg, South Africa
| | - David W Clark
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, UK
| | - Godfred Agongo
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Navrongo Health Research Centre, Navrongo, Ghana
| | - Gershim Asiki
- African Population and Health Research Center, Nairobi, Kenya
| | - Palwende R Boua
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Faculty of Health Sciences University of the Witwatersrand, Division of Human Genetics, National Health Laboratory Service and School of Pathology, Johannesburg, South Africa
- Clinical Research Unit of Nanoro, Institut de Recherche en Sciences de la Santé, Nanoro, Burkina Faso
| | - F Xavier Gómez-Olivé
- MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Felistas Mashinya
- Department of Pathology and Medical Science, School of Health Care Sciences, Faculty of Health Sciences, University of Limpopo, Polokwane, South Africa
| | - Shane Norris
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Faculty of Health Sciences University of the Witwatersrand, Division of Human Genetics, National Health Laboratory Service and School of Pathology, Johannesburg, South Africa
| | - James F Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, UK
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU, UK
| | - Michèle Ramsay
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
- Faculty of Health Sciences University of the Witwatersrand, Division of Human Genetics, National Health Laboratory Service and School of Pathology, Johannesburg, South Africa.
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15
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Hughes DA, Bacigalupe R, Wang J, Rühlemann MC, Tito RY, Falony G, Joossens M, Vieira-Silva S, Henckaerts L, Rymenans L, Verspecht C, Ring S, Franke A, Wade KH, Timpson NJ, Raes J. Genome-wide associations of human gut microbiome variation and implications for causal inference analyses. Nat Microbiol 2020; 5:1079-1087. [PMID: 32572223 PMCID: PMC7610462 DOI: 10.1038/s41564-020-0743-8] [Citation(s) in RCA: 127] [Impact Index Per Article: 25.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Accepted: 05/18/2020] [Indexed: 12/15/2022]
Abstract
Recent population-based1-4 and clinical studies5 have identified a range of factors associated with human gut microbiome variation. Murine quantitative trait loci6, human twin studies7 and microbiome genome-wide association studies1,3,8-12 have provided evidence for genetic contributions to microbiome composition. Despite this, there is still poor overlap in genetic association across human studies. Using appropriate taxon-specific models, along with support from independent cohorts, we show an association between human host genotype and gut microbiome variation. We also suggest that interpretation of applied analyses using genetic associations is complicated by the probable overlap between genetic contributions and heritable components of host environment. Using faecal 16S ribosomal RNA gene sequences and host genotype data from the Flemish Gut Flora Project (n = 2,223) and two German cohorts (FoCus, n = 950; PopGen, n = 717), we identify genetic associations involving multiple microbial traits. Two of these associations achieved a study-level threshold of P = 1.57 × 10-10; an association between Ruminococcus and rs150018970 near RAPGEF1 on chromosome 9, and between Coprococcus and rs561177583 within LINC01787 on chromosome 1. Exploratory analyses were undertaken using 11 other genome-wide associations with strong evidence for association (P < 2.5 × 10-8) and a previously reported signal of association between rs4988235 (MCM6/LCT) and Bifidobacterium. Across these 14 single-nucleotide polymorphisms there was evidence of signal overlap with other genome-wide association studies, including those for age at menarche and cardiometabolic traits. Mendelian randomization analysis was able to estimate associations between microbial traits and disease (including Bifidobacterium and body composition); however, in the absence of clear microbiome-driven effects, caution is needed in interpretation. Overall, this work marks a growing catalogue of genetic associations that will provide insight into the contribution of host genotype to gut microbiome. Despite this, the uncertain origin of association signals will likely complicate future work looking to dissect function or use associations for causal inference analysis.
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Affiliation(s)
- David A Hughes
- MRC Integrative Epidemiology Unit at University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Rodrigo Bacigalupe
- Department of Microbiology and Immunology, Rega Instituut, KU Leuven-University of Leuven, Leuven, Belgium
- Center for Microbiology, VIB, Leuven, Belgium
| | - Jun Wang
- Department of Microbiology and Immunology, Rega Instituut, KU Leuven-University of Leuven, Leuven, Belgium
- Center for Microbiology, VIB, Leuven, Belgium
- Institute of Microbiology, Chinese Academy of Sciences, Chaoyang District, Beijing, China
| | - Malte C Rühlemann
- Institute of Clinical Molecular Biology, Christian Albrechts University of Kiel, Kiel, Germany
| | - Raul Y Tito
- Department of Microbiology and Immunology, Rega Instituut, KU Leuven-University of Leuven, Leuven, Belgium
- Center for Microbiology, VIB, Leuven, Belgium
| | - Gwen Falony
- Department of Microbiology and Immunology, Rega Instituut, KU Leuven-University of Leuven, Leuven, Belgium
- Center for Microbiology, VIB, Leuven, Belgium
| | - Marie Joossens
- Department of Microbiology and Immunology, Rega Instituut, KU Leuven-University of Leuven, Leuven, Belgium
- Center for Microbiology, VIB, Leuven, Belgium
| | - Sara Vieira-Silva
- Department of Microbiology and Immunology, Rega Instituut, KU Leuven-University of Leuven, Leuven, Belgium
- Center for Microbiology, VIB, Leuven, Belgium
| | - Liesbet Henckaerts
- Department of Microbiology, Immunology and Transplantation, KU Leuven-University of Leuven, Leuven, Belgium
- Department of General Internal Medicine, KU Leuven-University Hospitals Leuven, Leuven, Belgium
| | - Leen Rymenans
- Department of Microbiology and Immunology, Rega Instituut, KU Leuven-University of Leuven, Leuven, Belgium
- Center for Microbiology, VIB, Leuven, Belgium
| | - Chloë Verspecht
- Department of Microbiology and Immunology, Rega Instituut, KU Leuven-University of Leuven, Leuven, Belgium
- Center for Microbiology, VIB, Leuven, Belgium
| | - Susan Ring
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Bristol Bioresource Laboratories, University of Bristol, Bristol, UK
| | - Andre Franke
- Institute of Clinical Molecular Biology, Christian Albrechts University of Kiel, Kiel, Germany
| | - Kaitlin H Wade
- MRC Integrative Epidemiology Unit at University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit at University of Bristol, Bristol, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
| | - Jeroen Raes
- Department of Microbiology and Immunology, Rega Instituut, KU Leuven-University of Leuven, Leuven, Belgium.
- Center for Microbiology, VIB, Leuven, Belgium.
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16
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Mezzavilla M, Cocca M, Guidolin F, Gasparini P. A population-based approach for gene prioritization in understanding complex traits. Hum Genet 2020; 139:647-655. [DOI: 10.1007/s00439-020-02152-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Accepted: 03/18/2020] [Indexed: 02/06/2023]
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17
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Martin TC, Ilieva KM, Visconti A, Beaumont M, Kiddle SJ, Dobson RJB, Mangino M, Lim EM, Pezer M, Steves CJ, Bell JT, Wilson SG, Lauc G, Roederer M, Walsh JP, Spector TD, Karagiannis SN. Dysregulated Antibody, Natural Killer Cell and Immune Mediator Profiles in Autoimmune Thyroid Diseases. Cells 2020; 9:E665. [PMID: 32182948 PMCID: PMC7140647 DOI: 10.3390/cells9030665] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Revised: 03/04/2020] [Accepted: 03/05/2020] [Indexed: 12/12/2022] Open
Abstract
The pathogenesis of autoimmune thyroid diseases (AITD) is poorly understood and the association between different immune features and the germline variants involved in AITD are yet unclear. We previously observed systemic depletion of IgG core fucosylation and antennary α1,2 fucosylation in peripheral blood mononuclear cells in AITD, correlated with anti-thyroid peroxidase antibody (TPOAb) levels. Fucose depletion is known to potentiate strong antibody-mediated NK cell activation and enhanced target antigen-expressing cell killing. In autoimmunity, this may translate to autoantibody-mediated immune cell recruitment and attack of self-antigen expressing normal tissues. Hence, we investigated the crosstalk between immune cell traits, secreted proteins, genetic variants and the glycosylation patterns of serum IgG, in a multi-omic and cross-sectional study of 622 individuals from the TwinsUK cohort, 172 of whom were diagnosed with AITD. We observed associations between two genetic variants (rs505922 and rs687621), AITD status, the secretion of Desmoglein-2 protein, and the profile of two IgG N-glycan traits in AITD, but further studies need to be performed to better understand their crosstalk in AITD. On the other side, enhanced afucosylated IgG was positively associated with activatory CD335- CD314+ CD158b+ NK cell subsets. Increased levels of the apoptosis and inflammation markers Caspase-2 and Interleukin-1α positively associated with AITD. Two genetic variants associated with AITD, rs1521 and rs3094228, were also associated with altered expression of the thyrocyte-expressed ligands known to recognize the NK cell immunoreceptors CD314 and CD158b. Our analyses reveal a combination of heightened Fc-active IgG antibodies, effector cells, cytokines and apoptotic signals in AITD, and AITD genetic variants associated with altered expression of thyrocyte-expressed ligands to NK cell immunoreceptors. Together, TPOAb responses, dysregulated immune features, germline variants associated with immunoactivity profiles, are consistent with a positive autoreactive antibody-dependent NK cell-mediated immune response likely drawn to the thyroid gland in AITD.
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Affiliation(s)
- Tiphaine C. Martin
- Department of Twin Research and Genetic Epidemiology, King’s College, London SE1 7EH, UK; (A.V.); (M.B.); (M.M.); (C.J.S.); (J.T.B.); (S.G.W.); (T.D.S.)
- School of Biomedical Sciences, University of Western Australia, Crawley, WA 6009, Australia
- Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Kristina M. Ilieva
- St John’s Institute of Dermatology, School of Basic & Medical Biosciences, King’s College London, Guy’s Hospital, London SE1 9RT, UK; (K.M.I.); (S.N.K.)
- Breast Cancer Now Research Unit, School of Cancer & Pharmaceutical Sciences, King’s College London, Guy’s Cancer Centre, London SE1 9RT, UK
| | - Alessia Visconti
- Department of Twin Research and Genetic Epidemiology, King’s College, London SE1 7EH, UK; (A.V.); (M.B.); (M.M.); (C.J.S.); (J.T.B.); (S.G.W.); (T.D.S.)
| | - Michelle Beaumont
- Department of Twin Research and Genetic Epidemiology, King’s College, London SE1 7EH, UK; (A.V.); (M.B.); (M.M.); (C.J.S.); (J.T.B.); (S.G.W.); (T.D.S.)
| | - Steven J. Kiddle
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King’s College, London SE5 8AF, UK; (S.J.K.); (R.J.B.D.)
- MRC Biostatistics Unit, University of Cambridge, Cambridge CB2 0SR, UK
| | - Richard J. B. Dobson
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King’s College, London SE5 8AF, UK; (S.J.K.); (R.J.B.D.)
- Health Data Research UK (HDR UK), London Institute of Health Informatics, University College London, London NW1 2DA, UK
| | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, King’s College, London SE1 7EH, UK; (A.V.); (M.B.); (M.M.); (C.J.S.); (J.T.B.); (S.G.W.); (T.D.S.)
- NIHR Biomedical Research Centre at Guy’s and St. Thomas’s NHS Foundation Trust, London SE1 9RT, UK
| | - Ee Mun Lim
- Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA 6009, Australia; (E.M.L.); (J.P.W.)
- Medical School, The University of Western Australia, Crawley, WA 6009, Australia
- PathWest Laboratory Medicine, QEII Medical Centre, Nedlands, WA 6009, Australia
| | - Marija Pezer
- Genos, Glycoscience Research Laboratory, 10000 Zagreb, Croatia; (M.P.); (G.L.)
| | - Claire J. Steves
- Department of Twin Research and Genetic Epidemiology, King’s College, London SE1 7EH, UK; (A.V.); (M.B.); (M.M.); (C.J.S.); (J.T.B.); (S.G.W.); (T.D.S.)
| | - Jordana T. Bell
- Department of Twin Research and Genetic Epidemiology, King’s College, London SE1 7EH, UK; (A.V.); (M.B.); (M.M.); (C.J.S.); (J.T.B.); (S.G.W.); (T.D.S.)
| | - Scott G. Wilson
- Department of Twin Research and Genetic Epidemiology, King’s College, London SE1 7EH, UK; (A.V.); (M.B.); (M.M.); (C.J.S.); (J.T.B.); (S.G.W.); (T.D.S.)
- School of Biomedical Sciences, University of Western Australia, Crawley, WA 6009, Australia
- Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA 6009, Australia; (E.M.L.); (J.P.W.)
| | - Gordan Lauc
- Genos, Glycoscience Research Laboratory, 10000 Zagreb, Croatia; (M.P.); (G.L.)
- Faculty of Pharmacy and Biochemistry, University of Zagreb, 10000 Zagreb, Croatia
| | - Mario Roederer
- ImmunoTechnology Section, Vaccine Research Center, NIAID, NIH, Bethesda, MD 20892, USA;
| | - John P. Walsh
- Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA 6009, Australia; (E.M.L.); (J.P.W.)
- Medical School, The University of Western Australia, Crawley, WA 6009, Australia
| | - Tim D. Spector
- Department of Twin Research and Genetic Epidemiology, King’s College, London SE1 7EH, UK; (A.V.); (M.B.); (M.M.); (C.J.S.); (J.T.B.); (S.G.W.); (T.D.S.)
| | - Sophia N. Karagiannis
- St John’s Institute of Dermatology, School of Basic & Medical Biosciences, King’s College London, Guy’s Hospital, London SE1 9RT, UK; (K.M.I.); (S.N.K.)
- Breast Cancer Now Research Unit, School of Cancer & Pharmaceutical Sciences, King’s College London, Guy’s Cancer Centre, London SE1 9RT, UK
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18
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Weich K, Affolter V, York D, Rebhun R, Grahn R, Kallenberg A, Bannasch D. Pigment Intensity in Dogs is Associated with a Copy Number Variant Upstream of KITLG. Genes (Basel) 2020; 11:genes11010075. [PMID: 31936656 PMCID: PMC7017362 DOI: 10.3390/genes11010075] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Revised: 01/06/2020] [Accepted: 01/08/2020] [Indexed: 01/14/2023] Open
Abstract
Dogs exhibit a wide variety of coat color types, and many genes have been identified that control pigment production, appearance, and distribution. Some breeds, such as the Nova Scotia Duck Tolling Retriever (NSDTR), exhibit variation in pheomelanin pigment intensity that is not explained by known genetic variants. A genome-wide association study comparing light red to dark red in the NSDTR identified a significantly associated region on canine chromosome 15 (CFA 15:23 Mb–38 Mb). Coverage analysis of whole genome sequence data from eight dogs identified a 6 kb copy number variant (CNV) 152 kb upstream of KITLG. Genotyping with digital droplet PCR (ddPCR) confirmed a significant association between an increased copy number with the dark-red coat color in NSDTR (p = 6.1 × 10−7). The copy number of the CNV was also significantly associated with coat color variation in both eumelanin and pheomelanin-based Poodles (p = 1.5 × 10−8, 4.0 × 10−9) and across other breeds. Moreover, the copy number correlated with pigment intensity along the hair shaft in both pheomelanin and eumelanin coats. KITLG plays an important role in melanogenesis, and variants upstream of KITLG have been associated with coat color variation in mice as well as hair color in humans consistent with its role in the domestic dog.
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Affiliation(s)
- Kalie Weich
- Department of Population Health and Reproduction, University of California-Davis, Davis, CA 95616, USA;
| | - Verena Affolter
- Department of Pathology, Microbiology, and Immunology, University of California-Davis, Davis, CA 95616, USA;
| | - Daniel York
- Department of Surgical and Radiological Sciences, University of California-Davis, Davis, CA 95616, USA; (D.Y.); (R.R.)
| | - Robert Rebhun
- Department of Surgical and Radiological Sciences, University of California-Davis, Davis, CA 95616, USA; (D.Y.); (R.R.)
| | - Robert Grahn
- Veterinary Genetics Laboratory, University of California-Davis, Davis, CA 95616, USA; (R.G.); (A.K.)
| | - Angelica Kallenberg
- Veterinary Genetics Laboratory, University of California-Davis, Davis, CA 95616, USA; (R.G.); (A.K.)
| | - Danika Bannasch
- Department of Population Health and Reproduction, University of California-Davis, Davis, CA 95616, USA;
- Correspondence: ; Tel.: +1-530-754-8728
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19
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Sim Z, Coltman DW. Heritability of Horn Size in Thinhorn Sheep. Front Genet 2019; 10:959. [PMID: 31681413 PMCID: PMC6797622 DOI: 10.3389/fgene.2019.00959] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Accepted: 09/09/2019] [Indexed: 12/31/2022] Open
Abstract
Understanding the genetic basis of fitness-related trait variation has long been of great interest to evolutionary biologists. Secondary sexual characteristics, such as horns in bovids, are particularly intriguing since they can be potentially affected by both natural and sexual selection. Until recently, however, the study of fitness-related quantitative trait variation in wild species has been hampered by a lack of genomic resources, pedigree, and/or phenotype data. Recent innovations in genomic technologies have enabled wildlife researchers to perform marker-based relatedness estimation and acquire adequate loci density, enabling both the “top-down” approach of quantitative genetics and the “bottom-up” approach of association studies to describe the genetic basis of fitness-related traits. Here we combine a cross species application of the OvineHD BeadChip and horn measurements (horn length, base circumference, and volume) from harvested thinhorn sheep to examine the heritability and to perform a genome-wide single-nucleotide polymorphism association study of horn size in the species. Thinhorn sheep are mountain ungulates that reside in the mountainous regions of northwestern North America. Thinhorn sheep males grow massive horns that determine the social rank and mating success. We found horn length, base circumference, and volume to be moderately heritable and two loci to be suggestively associated with horn length.
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Affiliation(s)
- Zijian Sim
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada.,Fish and Wildlife Forensic Unit, Alberta Fish and Wildlife Enforcement Branch, Government of Alberta, Edmonton, AB, Canada
| | - David W Coltman
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada
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20
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François L, Hoskens H, Velie BD, Stinckens A, Tinel S, Lamberigts C, Peeters L, Savelkoul HFJ, Tijhaar E, Lindgren G, Janssens S, Ducro BJ, Buys N, Schurink AA. Genomic Regions Associated with IgE Levels against Culicoides spp. Antigens in Three Horse Breeds. Genes (Basel) 2019; 10:genes10080597. [PMID: 31398914 PMCID: PMC6723964 DOI: 10.3390/genes10080597] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Revised: 07/25/2019] [Accepted: 08/06/2019] [Indexed: 11/16/2022] Open
Abstract
Insect bite hypersensitivity (IBH), which is a cutaneous allergic reaction to antigens from Culicoides spp., is the most prevalent skin disorder in horses. Misdiagnosis is possible, as IBH is usually diagnosed based on clinical signs. Our study is the first to employ IgE levels against several recombinant Culicoides spp. allergens as an objective, independent, and quantitative phenotype to improve the power to detect genetic variants that underlie IBH. Genotypes of 200 Shetland ponies, 127 Icelandic horses, and 223 Belgian Warmblood horses were analyzed while using a mixed model approach. No single-nucleotide polymorphism (SNP) passed the Bonferroni corrected significance threshold, but several regions were identified within and across breeds, which confirmed previously identified regions of interest and, in addition, identifying new regions of interest. Allergen-specific IgE levels are a continuous and objective phenotype that allow for more powerful analyses when compared to a case-control set-up, as more significant associations were obtained. However, the use of a higher density array seems necessary to fully employ the use of IgE levels as a phenotype. While these results still require validation in a large independent dataset, the use of allergen-specific IgE levels showed value as an objective and continuous phenotype that can deepen our understanding of the biology underlying IBH.
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Affiliation(s)
- Liesbeth François
- Livestock Genetics, Department of Biosystems, KU Leuven, B-3001 Leuven, Belgium
| | - Hanne Hoskens
- Department of Human Genetics, KU Leuven, B-3000 Leuven, Belgium
| | - Brandon D Velie
- School of Life & Environmental Sciences, B19-603 University of Sydney, Sydney, NSW 2006,Australia
| | - Anneleen Stinckens
- Livestock Genetics, Department of Biosystems, KU Leuven, B-3001 Leuven, Belgium
| | - Susanne Tinel
- Livestock Genetics, Department of Biosystems, KU Leuven, B-3001 Leuven, Belgium
| | - Chris Lamberigts
- Research Group Livestock Physiology, Department of Biosystems, KU Leuven, Leuven, B-3001 Leuven, Belgium
| | - Liesbet Peeters
- Biomedical Research Institute, Hasselt University, B-3590 Diepenbeek, Belgium
| | - Huub F J Savelkoul
- Cell Biology and Immunology Group, Wageningen University & Research, 6700 AH Wageningen, The Netherlands
| | - Edwin Tijhaar
- Cell Biology and Immunology Group, Wageningen University & Research, 6700 AH Wageningen, The Netherlands
| | - Gabriella Lindgren
- Livestock Genetics, Department of Biosystems, KU Leuven, B-3001 Leuven, Belgium
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, 75007 Uppsala, Sweden
| | - Steven Janssens
- Livestock Genetics, Department of Biosystems, KU Leuven, B-3001 Leuven, Belgium
| | - Bart J Ducro
- Animal Breeding and Genomics, Wageningen University & Research, 6700 AH Wageningen, The Netherlands
| | - Nadine Buys
- Livestock Genetics, Department of Biosystems, KU Leuven, B-3001 Leuven, Belgium
| | - And Anouk Schurink
- Animal Breeding and Genomics, Wageningen University & Research, 6700 AH Wageningen, The Netherlands.
- Centre for Genetic Resources, The Netherlands (CGN), Wageningen University & Research, 6700 AH Wageningen, The Netherlands.
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21
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Sharapov SZ, Tsepilov YA, Klaric L, Mangino M, Thareja G, Shadrina AS, Simurina M, Dagostino C, Dmitrieva J, Vilaj M, Vuckovic F, Pavic T, Stambuk J, Trbojevic-Akmacic I, Kristic J, Simunovic J, Momcilovic A, Campbell H, Doherty M, Dunlop MG, Farrington SM, Pucic-Bakovic M, Gieger C, Allegri M, Louis E, Georges M, Suhre K, Spector T, Williams FMK, Lauc G, Aulchenko YS. Defining the genetic control of human blood plasma N-glycome using genome-wide association study. Hum Mol Genet 2019; 28:2062-2077. [PMID: 31163085 PMCID: PMC6664388 DOI: 10.1093/hmg/ddz054] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2018] [Revised: 03/01/2019] [Accepted: 03/06/2019] [Indexed: 01/10/2023] Open
Abstract
Glycosylation is a common post-translational modification of proteins. Glycosylation is associated with a number of human diseases. Defining genetic factors altering glycosylation may provide a basis for novel approaches to diagnostic and pharmaceutical applications. Here we report a genome-wide association study of the human blood plasma N-glycome composition in up to 3811 people measured by Ultra Performance Liquid Chromatography (UPLC) technology. Starting with the 36 original traits measured by UPLC, we computed an additional 77 derived traits leading to a total of 113 glycan traits. We studied associations between these traits and genetic polymorphisms located on human autosomes. We discovered and replicated 12 loci. This allowed us to demonstrate an overlap in genetic control between total plasma protein and IgG glycosylation. The majority of revealed loci contained genes that encode enzymes directly involved in glycosylation (FUT3/FUT6, FUT8, B3GAT1, ST6GAL1, B4GALT1, ST3GAL4, MGAT3 and MGAT5) and a known regulator of plasma protein fucosylation (HNF1A). However, we also found loci that could possibly reflect other more complex aspects of glycosylation process. Functional genomic annotation suggested the role of several genes including DERL3, CHCHD10, TMEM121, IGH and IKZF1. The hypotheses we generated may serve as a starting point for further functional studies in this research area.
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Affiliation(s)
- Sodbo Zh Sharapov
- Institute of Cytology and Genetics SB RAS, Prospekt Lavrentyeva 10, Novosibirsk, Russia
- Novosibirsk State University, 1, Pirogova str., Novosibirsk, Russia
| | - Yakov A Tsepilov
- Institute of Cytology and Genetics SB RAS, Prospekt Lavrentyeva 10, Novosibirsk, Russia
- Novosibirsk State University, 1, Pirogova str., Novosibirsk, Russia
| | - Lucija Klaric
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road South, Edinburgh, UK
- Genos Glycoscience Research Laboratory, Borongajska cesta 83h, Zagreb, Croatia
| | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King’s College London, St Thomas’ Campus, London, UK
- NIHR Biomedical Research Centre at Guy’s and St Thomas’ Foundation Trust, London, UK
| | - Gaurav Thareja
- Department of Physiology and Biophysics, Weill Cornell Medicine-Qatar, Education City, Doha, Qatar
| | | | - Mirna Simurina
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Ante Kovacica 1, Zagreb, Croatia
| | - Concetta Dagostino
- Department of Medicine and Surgery, University of Parma, Via Gramsci 14, Parma, Italy
| | - Julia Dmitrieva
- Unit of Animal Genomics, WELBIO, GIGA-R and Faculty of Veterinary Medicine, University of Liège, Liège, Belgium
| | - Marija Vilaj
- Genos Glycoscience Research Laboratory, Borongajska cesta 83h, Zagreb, Croatia
| | - Frano Vuckovic
- Genos Glycoscience Research Laboratory, Borongajska cesta 83h, Zagreb, Croatia
| | - Tamara Pavic
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Ante Kovacica 1, Zagreb, Croatia
| | - Jerko Stambuk
- Genos Glycoscience Research Laboratory, Borongajska cesta 83h, Zagreb, Croatia
| | | | - Jasminka Kristic
- Genos Glycoscience Research Laboratory, Borongajska cesta 83h, Zagreb, Croatia
| | - Jelena Simunovic
- Genos Glycoscience Research Laboratory, Borongajska cesta 83h, Zagreb, Croatia
| | - Ana Momcilovic
- Genos Glycoscience Research Laboratory, Borongajska cesta 83h, Zagreb, Croatia
| | - Harry Campbell
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, UK
- Colon Cancer Genetics Group, MRC Human Genetics Unit, MRC Institute of Genetics & Molecular Medicine, Western General Hospital, The University of Edinburgh, Edinburgh, UK
| | - Margaret Doherty
- Institute of Technology Sligo, Department of Life Sciences, Sligo, Ireland
- National Institute for Bioprocessing Research & Training, Dublin, Ireland
| | - Malcolm G Dunlop
- Colon Cancer Genetics Group, MRC Human Genetics Unit, MRC Institute of Genetics & Molecular Medicine, Western General Hospital, The University of Edinburgh, Edinburgh, UK
| | - Susan M Farrington
- Colon Cancer Genetics Group, MRC Human Genetics Unit, MRC Institute of Genetics & Molecular Medicine, Western General Hospital, The University of Edinburgh, Edinburgh, UK
| | - Maja Pucic-Bakovic
- Genos Glycoscience Research Laboratory, Borongajska cesta 83h, Zagreb, Croatia
| | - Christian Gieger
- Institute of Epidemiology II, Research Unit of Molecular Epidemiology, Helmholtz Centre Munich, German Research Center for Environmental Health, Ingolstädter Landstr. 1, Neuherberg, Germany
| | - Massimo Allegri
- Pain Therapy Department, Policlinico Monza Hospital, Monza, Italy
| | - Edouard Louis
- CHU-Liège and Unit of Gastroenterology, GIGA-R and Faculty of Medicine, University of Liège, 1 Avenue de l’Hôpital, Liège, Belgium
| | - Michel Georges
- Unit of Animal Genomics, WELBIO, GIGA-R and Faculty of Veterinary Medicine, University of Liège, Liège, Belgium
| | - Karsten Suhre
- Department of Physiology and Biophysics, Weill Cornell Medicine-Qatar, Education City, Doha, Qatar
| | - Tim Spector
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King’s College London, St Thomas’ Campus, London, UK
| | - Frances M K Williams
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King’s College London, St Thomas’ Campus, London, UK
| | - Gordan Lauc
- Genos Glycoscience Research Laboratory, Borongajska cesta 83h, Zagreb, Croatia
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Ante Kovacica 1, Zagreb, Croatia
| | - Yurii S Aulchenko
- Institute of Cytology and Genetics SB RAS, Prospekt Lavrentyeva 10, Novosibirsk, Russia
- Novosibirsk State University, 1, Pirogova str., Novosibirsk, Russia
- PolyOmica, Het Vlaggeschip 61, PA 's-Hertogenbosch, The Netherlands
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22
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Agler CS, Shungin D, Ferreira Zandoná AG, Schmadeke P, Basta PV, Luo J, Cantrell J, Pahel TD, Meyer BD, Shaffer JR, Schaefer AS, North KE, Divaris K. Protocols, Methods, and Tools for Genome-Wide Association Studies (GWAS) of Dental Traits. Methods Mol Biol 2019; 1922:493-509. [PMID: 30838596 PMCID: PMC6613560 DOI: 10.1007/978-1-4939-9012-2_38] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Oral health and disease are known to be influenced by complex interactions between environmental (e.g., social and behavioral) factors and innate susceptibility. Although the exact contribution of genomics and other layers of "omics" to oral health is an area of active research, it is well established that the susceptibility to dental caries, periodontal disease, and other oral and craniofacial traits is substantially influenced by the human genome. A comprehensive understanding of these genomic factors is necessary for the realization of precision medicine in the oral health domain. To aid in this direction, the advent and increasing affordability of high-throughput genotyping has enabled the simultaneous interrogation of millions of genetic polymorphisms for association with oral and craniofacial traits. Specifically, genome-wide association studies (GWAS) of dental caries and periodontal disease have provided initial insights into novel loci and biological processes plausibly implicated in these two common, complex, biofilm-mediated diseases. This paper presents a summary of protocols, methods, tools, and pipelines for the conduct of GWAS of dental caries, periodontal disease, and related traits. The protocol begins with the consideration of different traits for both diseases and outlines procedures for genotyping, quality control, adjustment for population stratification, heritability and association analyses, annotation, reporting, and interpretation. Methods and tools available for GWAS are being constantly updated and improved; with this in mind, the presented approaches have been successfully applied in numerous GWAS and meta-analyses among tens of thousands of individuals, including dental traits such as dental caries and periodontal disease. As such, they can serve as a guide or template for future genomic investigations of these and other traits.
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Affiliation(s)
- Cary S Agler
- Oral and Craniofacial Health Sciences, UNC School of Dentistry, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
| | - Dmitry Shungin
- Department of Odontology, Umeå University, Umeå, Sweden
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
| | - Andrea G Ferreira Zandoná
- Department of Comprehensive Dentistry, Tufts University School of Dental Medicine, Tufts University, Boston, MA, USA
| | - Paige Schmadeke
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
- Biospecimen Core Processing Facility, Gillings School of Global Public Health, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
| | - Patricia V Basta
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
- Biospecimen Core Processing Facility, Gillings School of Global Public Health, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
| | - Jason Luo
- Lineberger Comprehensive Cancer Center, School of Medicine, University of North Carolina, Chapel Hill, NC, USA
- Mammalian Genotyping Core, University of North Carolina, Chapel Hill, NC, USA
| | - John Cantrell
- Oral and Craniofacial Health Sciences, UNC School of Dentistry, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
| | - Thomas D Pahel
- Oral and Craniofacial Health Sciences, UNC School of Dentistry, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
| | - Beau D Meyer
- Department of Pediatric Dentistry, UNC School of Dentistry, CB#7450, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
| | - John R Shaffer
- Center for Craniofacial and Dental Genetics, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Oral Biology, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Arne S Schaefer
- Department of Periodontology, Institute of Dental, Oral and Maxillary Medicine, Charité-University Medicine Berlin, Berlin, Germany
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
- Carolina Center for Genome Sciences, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
| | - Kimon Divaris
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA.
- Department of Pediatric Dentistry, UNC School of Dentistry, CB#7450, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA.
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23
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Herrera S, de Vega WC, Ashbrook D, Vernon SD, McGowan PO. Genome-epigenome interactions associated with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome. Epigenetics 2018; 13:1174-1190. [PMID: 30516085 DOI: 10.1080/15592294.2018.1549769] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a complex disease of unknown etiology. Multiple studies point to disruptions in immune functioning in ME/CFS patients as well as specific genetic polymorphisms and alterations of the DNA methylome in lymphocytes. However, potential interactions between DNA methylation and genetic background in relation to ME/CFS have not been examined. In this study we explored this association by characterizing the epigenetic (~480 thousand CpG loci) and genetic (~4.3 million SNPs) variation between cohorts of ME/CFS patients and healthy controls. We found significant associations of DNA methylation states in T-lymphocytes at several CpG loci and regions with ME/CFS phenotype. These methylation anomalies are in close proximity to genes involved with immune function and cellular metabolism. Finally, we found significant correlations of genotypes with methylation modifications associated with ME/CFS. The findings from this study highlight the role of epigenetic and genetic interactions in complex diseases, and suggest several genetic and epigenetic elements potentially involved in the mechanisms of disease in ME/CFS.
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Affiliation(s)
- Santiago Herrera
- a Centre for Environmental Epigenetics and Development , University of Toronto , Scarborough , Canada.,b Department of Biological Sciences , University of Toronto , Scarborough , Canada
| | - Wilfred C de Vega
- a Centre for Environmental Epigenetics and Development , University of Toronto , Scarborough , Canada.,b Department of Biological Sciences , University of Toronto , Scarborough , Canada.,c Department of Cell and Systems Biology , University of Toronto , Toronto , Canada
| | - David Ashbrook
- a Centre for Environmental Epigenetics and Development , University of Toronto , Scarborough , Canada.,b Department of Biological Sciences , University of Toronto , Scarborough , Canada
| | | | - Patrick O McGowan
- a Centre for Environmental Epigenetics and Development , University of Toronto , Scarborough , Canada.,b Department of Biological Sciences , University of Toronto , Scarborough , Canada.,c Department of Cell and Systems Biology , University of Toronto , Toronto , Canada.,e Department of Psychology , University of Toronto , Toronto , Canada.,f Department of Physiology, Faculty of Medicine , University of Toronto , Toronto , Canada
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24
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Ostrom QT, Kinnersley B, Armstrong G, Rice T, Chen Y, Wiencke JK, McCoy LS, Hansen HM, Amos CI, Bernstein JL, Claus EB, Eckel-Passow JE, Il'yasova D, Johansen C, Lachance DH, Lai RK, Merrell RT, Olson SH, Sadetzki S, Schildkraut JM, Shete S, Rubin JB, Andersson U, Rajaraman P, Chanock SJ, Linet MS, Wang Z, Yeager M, Houlston RS, Jenkins RB, Wrensch MR, Melin B, Bondy ML, Barnholtz-Sloan JS. Age-specific genome-wide association study in glioblastoma identifies increased proportion of 'lower grade glioma'-like features associated with younger age. Int J Cancer 2018; 143:2359-2366. [PMID: 30152087 PMCID: PMC6205887 DOI: 10.1002/ijc.31759] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2018] [Revised: 03/05/2018] [Accepted: 03/16/2018] [Indexed: 01/07/2023]
Abstract
Glioblastoma (GBM) is the most common malignant brain tumor in the United States. Incidence of GBM increases with age, and younger age-at-diagnosis is significantly associated with improved prognosis. While the relationship between candidate GBM risk SNPs and age-at-diagnosis has been explored, genome-wide association studies (GWAS) have not previously been stratified by age. Potential age-specific genetic effects were assessed in autosomal SNPs for GBM patients using data from four previous GWAS. Using age distribution tertiles (18-53, 54-64, 65+) datasets were analyzed using age-stratified logistic regression to generate p values, odds ratios (OR), and 95% confidence intervals (95%CI), and then combined using meta-analysis. There were 4,512 total GBM cases, and 10,582 controls used for analysis. Significant associations were detected at two previously identified SNPs in 7p11.2 (rs723527 [p54-63 = 1.50x10-9 , OR54-63 = 1.28, 95%CI54-63 = 1.18-1.39; p64+ = 2.14x10-11 , OR64+ = 1.32, 95%CI64+ = 1.21-1.43] and rs11979158 [p54-63 = 6.13x10-8 , OR54-63 = 1.35, 95%CI54-63 = 1.21-1.50; p64+ = 2.18x10-10 , OR64+ = 1.42, 95%CI64+ = 1.27-1.58]) but only in persons >54. There was also a significant association at the previously identified lower grade glioma (LGG) risk locus at 8q24.21 (rs55705857) in persons ages 18-53 (p18-53 = 9.30 × 10-11 , OR18-53 = 1.76, 95%CI18-53 = 1.49-2.10). Within The Cancer Genome Atlas (TCGA) there was higher prevalence of 'LGG'-like tumor characteristics in GBM samples in those 18-53, with IDH1/2 mutation frequency of 15%, as compared to 2.1% [54-63] and 0.8% [64+] (p = 0.0005). Age-specific differences in cancer susceptibility can provide important clues to etiology. The association of a SNP known to confer risk for IDH1/2 mutant glioma and higher prevalence of IDH1/2 mutation within younger individuals 18-53 suggests that more younger individuals may present initially with 'secondary glioblastoma.'
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Affiliation(s)
- Quinn T Ostrom
- Department of Medicine, Section of Epidemiology and Population Sciences, Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas
- Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, Ohio
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio
| | - Ben Kinnersley
- Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, Surrey, United Kingdom
| | - Georgina Armstrong
- Department of Medicine, Section of Epidemiology and Population Sciences, Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas
| | - Terri Rice
- Department of Neurological Surgery and Institute of Human Genetics, School of Medicine, University of California, San Francisco, San Francisco, California
| | - Yanwen Chen
- Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, Ohio
| | - John K Wiencke
- Department of Neurological Surgery and Institute of Human Genetics, School of Medicine, University of California, San Francisco, San Francisco, California
| | - Lucie S McCoy
- Department of Neurological Surgery and Institute of Human Genetics, School of Medicine, University of California, San Francisco, San Francisco, California
| | - Helen M Hansen
- Department of Neurological Surgery and Institute of Human Genetics, School of Medicine, University of California, San Francisco, San Francisco, California
| | - Christopher I Amos
- Baylor College of Medicine, Institute for Clinical and Translational Research, Houston, Texas
| | - Jonine L Bernstein
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Elizabeth B Claus
- School of Public Health, Yale University, New Haven, Connecticut
- Department of Neurosurgery, Brigham and Women's Hospital, Boston, Massachusetts
| | - Jeanette E Eckel-Passow
- Division of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Dora Il'yasova
- Department of Epidemiology and Biostatistics, School of Public Health, Georgia State University, Atlanta, Georgia
- Cancer Control and Prevention Program, Department of Community and Family Medicine, Duke University Medical Center, Durham, North Carolina
- Duke Cancer Institute, Duke University Medical Center, Durham, North Carolina
| | - Christoffer Johansen
- Oncology clinic, Finsen Center, Rigshospitalet and Survivorship Research Unit, The Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Daniel H Lachance
- Department of Neurology, Mayo Clinic Comprehensive Cancer Center, Mayo Clinic, Rochester, Minnesota
| | - Rose K Lai
- Departments of Neurology and Preventive Medicine, Keck School of Medicine, University of Southern California, California, Los Angeles
| | - Ryan T Merrell
- Department of Neurology, NorthShore University HealthSystem, Evanston, Illinois
| | - Sara H Olson
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Siegal Sadetzki
- Cancer and Radiation Epidemiology Unit, Gertner Institute, Chaim Sheba Medical Center, Tel Hashomer, Israel
- Department of Epidemiology and Preventive Medicine, School of Public Health, Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel
| | - Joellen M Schildkraut
- Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, Virginia
| | - Sanjay Shete
- Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Joshua B Rubin
- Departments of Pediatrics and Neuroscience, Washington University School of Medicine, St. Louis, Missouri
| | - Ulrika Andersson
- Department of Radiation Sciences, Faculty of Medicine, Umeå University, Umeå, Sweden
| | - Preetha Rajaraman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland
| | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland
- Core Genotyping Facility, National Cancer Institute, SAIC-Frederick, Inc, Gaithersburg, Maryland
| | - Martha S Linet
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland
| | - Zhaoming Wang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland
- Core Genotyping Facility, National Cancer Institute, SAIC-Frederick, Inc, Gaithersburg, Maryland
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Meredith Yeager
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland
- Core Genotyping Facility, National Cancer Institute, SAIC-Frederick, Inc, Gaithersburg, Maryland
| | - Richard S Houlston
- Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, Surrey, United Kingdom
| | - Robert B Jenkins
- Department of Laboratory Medicine and Pathology, Mayo Clinic Comprehensive Cancer Center, Mayo Clinic, Rochester, Minnesota
| | - Margaret R Wrensch
- Department of Neurological Surgery and Institute of Human Genetics, School of Medicine, University of California, San Francisco, San Francisco, California
| | - Beatrice Melin
- Department of Radiation Sciences, Faculty of Medicine, Umeå University, Umeå, Sweden
| | - Melissa L Bondy
- Department of Medicine, Section of Epidemiology and Population Sciences, Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas
| | - Jill S Barnholtz-Sloan
- Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, Ohio
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25
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Zimmerman KL, Panciera DL, Hoeschele I, Monroe WE, Todd SM, Werre SR, LeRoith T, Fecteau K, Lake BB. Adrenocortical Challenge Response and Genomic Analyses in Scottish Terriers With Increased Alkaline Phosphate Activity. Front Vet Sci 2018; 5:231. [PMID: 30356827 PMCID: PMC6189480 DOI: 10.3389/fvets.2018.00231] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2018] [Accepted: 09/06/2018] [Indexed: 11/13/2022] Open
Abstract
Scottish terriers (ST) frequently have increased serum alkaline phosphatase (ALP) of the steroid isoform. Many of these also have high serum concentrations of adrenal sex steroids. The study's objective was to determine the cause of increased sex steroids in ST with increased ALP. Adrenal gland suppression and stimulation were compared by low dose dexamethasone (LDDS), human chorionic gonadotropin (HCG) and adrenocorticotropic hormone (ACTH) response tests. Resting plasma pituitary hormones were measured. Steroidogenesis-related mRNA expression was evaluated in six ST with increased ALP, eight dogs of other breeds with pituitary-dependent hyperadrenocorticism (HAC), and seven normal dogs. The genome-wide association of single nucleotide polymorphisms (SNP) with ALP activity was evaluated in 168 ST. ALP (reference interval 8–70 U/L) was high in all ST (1,054 U/L) and HAC (985 U/L) dogs. All HAC dogs and 2/8 ST had increased cortisol post-ACTH administration. All ST and 2/7 Normal dogs had increased sex steroids post-ACTH. ST and Normal dogs had similar post-challenge adrenal steroid profiles following LDDS and HCG. Surprisingly, mRNA of hydroxysteroid 17-beta dehydrogenase 2 (HSD17B2) was lower in ST and Normal dogs than HAC. HSD17B2 facilities metabolism of sex steroids. A SNP region was identified on chromosome 5 in proximity to HSD17B2 that correlated with increased serum ALP. ST in this study with increased ALP had a normal pituitary-adrenal axis in relationship to glucocorticoids and luteinizing hormone. We speculate the identified SNP and HSD17B2 gene may have a role in the pathogenesis of elevated sex steroids and ALP in ST.
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Affiliation(s)
- Kurt L Zimmerman
- Department of Biomedical Sciences and Pathobiology, Virginia Maryland College of Veterinary Medicine, Virginia Tech, Blacksburg, VA, United States
| | - David L Panciera
- Department of Small Animal Clinical Sciences, Virginia Maryland College of Veterinary Medicine, Virginia Tech, Blacksburg, VA, United States
| | - Ina Hoeschele
- Department of Statistics, College of Science, and Biocomplexity Institute, Virginia Tech, Blacksburg, VA, United States
| | - W Edward Monroe
- Department of Small Animal Clinical Sciences, Virginia Maryland College of Veterinary Medicine, Virginia Tech, Blacksburg, VA, United States
| | - Stephanie Michelle Todd
- Veterinary Medicine Experiment Station, Virginia Maryland College of Veterinary Medicine, Virginia Tech, Blacksburg, VA, United States
| | - Stephen R Werre
- Study Design and Statistical Analysis Laboratory, Virginia Maryland College of Veterinary Medicine, Virginia Tech, Blacksburg, VA, United States
| | - Tanya LeRoith
- Department of Biomedical Sciences and Pathobiology, Virginia Maryland College of Veterinary Medicine, Virginia Tech, Blacksburg, VA, United States
| | - Kellie Fecteau
- Department of Biomedical and Diagnostic Sciences, College of Veterinary Medicine, University of Tennessee, Knoxville, TN, United States
| | - Bathilda B Lake
- Department of Biomedical Sciences and Pathobiology, Virginia Maryland College of Veterinary Medicine, Virginia Tech, Blacksburg, VA, United States
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Gao S, Casey AE, Sargeant TJ, Mäkinen VP. Genetic variation within endolysosomal system is associated with late-onset Alzheimer’s disease. Brain 2018; 141:2711-2720. [DOI: 10.1093/brain/awy197] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2018] [Accepted: 06/19/2018] [Indexed: 12/20/2022] Open
Abstract
AbstractLate-onset Alzheimer’s disease is the most common dementia type, yet no treatment exists to stop the neurodegeneration. Evidence from monogenic lysosomal diseases, neuronal pathology and experimental models suggest that autophagic and endolysosomal dysfunction may contribute to neurodegeneration by disrupting the degradation of potentially neurotoxic molecules such as amyloid-β and tau. However, it is uncertain how well the evidence from rare disorders and experimental models capture causal processes in common forms of dementia, including late-onset Alzheimer’s disease. For this reason, we set out to investigate if autophagic and endolysosomal genes were enriched for genetic variants that convey increased risk of Alzheimer’s disease; such a finding would provide population-based support for the endolysosomal hypothesis of neurodegeneration. We quantified the collective genetic associations between the endolysosomal system and Alzheimer’s disease in three genome-wide associations studies (combined n = 62 415). We used the Mergeomics pathway enrichment algorithm that incorporates permutations of the full hierarchical cascade of SNP-gene-pathway to estimate enrichment. We used a previously published collection of 891 autophagic and endolysosomal genes (denoted as AphagEndoLyso, and derived from the Lysoplex sequencing platform) as a proxy for cellular processes related to autophagy, endocytosis and lysosomal function. We also investigated a subset of 142 genes of the 891 that have been implicated in Mendelian diseases (MenDisLyso). We found that both gene sets were enriched for genetic Alzheimer’s associations: an enrichment score 3.67 standard deviations from the null model (P = 0.00012) was detected for AphagEndoLyso, and a score 3.36 standard deviations from the null model (P = 0.00039) was detected for MenDisLyso. The high enrichment score was specific to the AphagEndoLyso gene set (stronger than 99.7% of other tested pathways) and to Alzheimer’s disease (stronger than all other tested diseases). The APOE locus explained most of the MenDisLyso signal (1.16 standard deviations after APOE removal, P = 0.12), but the AphagEndoLyso signal was less affected (3.35 standard deviations after APOE removal, P = 0.00040). Additional sensitivity analyses further indicated that the AphagEndoLyso Gene Set contained an aggregate genetic association that comprised a combination of subtle genetic signals in multiple genes. We also observed an enrichment of Parkinson’s disease signals for MenDisLyso (3.25 standard deviations) and for AphagEndoLyso (3.95 standard deviations from the null model), and a brain-specific pattern of gene expression for AphagEndoLyso in the Gene Tissue Expression Project dataset. These results provide evidence that a diffuse aggregation of genetic perturbations to the autophagy and endolysosomal system may mediate late-onset Alzheimer’s risk in human populations.
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Affiliation(s)
- Song Gao
- Heart Health Theme, South Australian Health and Medical Research Institute, Adelaide, South Australia
- School of Biological Sciences, University of Adelaide, Adelaide, South Australia
| | - Aaron E Casey
- Heart Health Theme, South Australian Health and Medical Research Institute, Adelaide, South Australia
- School of Biological Sciences, University of Adelaide, Adelaide, South Australia
| | - Tim J Sargeant
- Hopwood Centre for Neurobiology, Nutrition and Metabolism Theme, South Australian Health and Medical Research Institute, Adelaide, South Australia
| | - Ville-Petteri Mäkinen
- Heart Health Theme, South Australian Health and Medical Research Institute, Adelaide, South Australia
- School of Biological Sciences, University of Adelaide, Adelaide, South Australia
- Computational Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland
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Ostrom QT, Kinnersley B, Wrensch MR, Eckel-Passow JE, Armstrong G, Rice T, Chen Y, Wiencke JK, McCoy LS, Hansen HM, Amos CI, Bernstein JL, Claus EB, Il'yasova D, Johansen C, Lachance DH, Lai RK, Merrell RT, Olson SH, Sadetzki S, Schildkraut JM, Shete S, Rubin JB, Lathia JD, Berens ME, Andersson U, Rajaraman P, Chanock SJ, Linet MS, Wang Z, Yeager M, Houlston RS, Jenkins RB, Melin B, Bondy ML, Barnholtz-Sloan JS. Sex-specific glioma genome-wide association study identifies new risk locus at 3p21.31 in females, and finds sex-differences in risk at 8q24.21. Sci Rep 2018; 8:7352. [PMID: 29743610 PMCID: PMC5943590 DOI: 10.1038/s41598-018-24580-z] [Citation(s) in RCA: 51] [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: 01/02/2018] [Accepted: 04/06/2018] [Indexed: 01/07/2023] Open
Abstract
Incidence of glioma is approximately 50% higher in males. Previous analyses have examined exposures related to sex hormones in women as potential protective factors for these tumors, with inconsistent results. Previous glioma genome-wide association studies (GWAS) have not stratified by sex. Potential sex-specific genetic effects were assessed in autosomal SNPs and sex chromosome variants for all glioma, GBM and non-GBM patients using data from four previous glioma GWAS. Datasets were analyzed using sex-stratified logistic regression models and combined using meta-analysis. There were 4,831 male cases, 5,216 male controls, 3,206 female cases and 5,470 female controls. A significant association was detected at rs11979158 (7p11.2) in males only. Association at rs55705857 (8q24.21) was stronger in females than in males. A large region on 3p21.31 was identified with significant association in females only. The identified differences in effect of risk variants do not fully explain the observed incidence difference in glioma by sex.
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Affiliation(s)
- Quinn T Ostrom
- Department of Medicine, Section of Epidemiology and Population Sciences, Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas, United States of America
- Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, Ohio, United States of America
- Department of Population and Quantitative Heath Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio, United States of America
| | - Ben Kinnersley
- Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, Surrey, United Kingdom
| | - Margaret R Wrensch
- Department of Neurological Surgery and Institute of Human Genetics, School of Medicine, University of California, San Francisco, San Francisco, California, United States of America
| | - Jeanette E Eckel-Passow
- Division of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine, Rochester, Minnesota, United States of America
| | - Georgina Armstrong
- Department of Medicine, Section of Epidemiology and Population Sciences, Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas, United States of America
| | - Terri Rice
- Department of Neurological Surgery and Institute of Human Genetics, School of Medicine, University of California, San Francisco, San Francisco, California, United States of America
| | - Yanwen Chen
- Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, Ohio, United States of America
| | - John K Wiencke
- Department of Neurological Surgery and Institute of Human Genetics, School of Medicine, University of California, San Francisco, San Francisco, California, United States of America
| | - Lucie S McCoy
- Department of Neurological Surgery and Institute of Human Genetics, School of Medicine, University of California, San Francisco, San Francisco, California, United States of America
| | - Helen M Hansen
- Department of Neurological Surgery and Institute of Human Genetics, School of Medicine, University of California, San Francisco, San Francisco, California, United States of America
| | - Christopher I Amos
- Institute for Clinical and Translational Research, Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas, United States of America
| | - Jonine L Bernstein
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America
| | - Elizabeth B Claus
- School of Public Health, Yale University, New Haven, Connecticut, United States of America
- Department of Neurosurgery, Brigham and Women's Hospital, Boston, Massachusetts, United States of America
| | - Dora Il'yasova
- Department of Epidemiology and Biostatistics, School of Public Health, Georgia State University, Atlanta, Georgia, United States of America
- Cancer Control and Prevention Program, Department of Community and Family Medicine, Duke University Medical Center, Durham, North Carolina, United States of America
- Duke Cancer Institute, Duke University Medical Center, Durham, North Carolina, United States of America
| | - Christoffer Johansen
- Oncology clinic, Finsen Center, Rigshospitalet, Copenhagen, Denmark
- Survivorship Research Unit, The Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Daniel H Lachance
- Department of Neurology, Mayo Clinic Comprehensive Cancer Center, Mayo Clinic, Rochester, Minnesota, United States of America
| | - Rose K Lai
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - Ryan T Merrell
- Department of Neurology, NorthShore University HealthSystem, Evanston, Illinois, United States of America
| | - Sara H Olson
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America
| | - Siegal Sadetzki
- Cancer and Radiation Epidemiology Unit, Gertner Institute, Chaim Sheba Medical Center, Tel Hashomer, Israel
- Department of Epidemiology and Preventive Medicine, School of Public Health, Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel
| | - Joellen M Schildkraut
- Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America
| | - Sanjay Shete
- Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America
| | - Joshua B Rubin
- Department of Pediatrics, Washington University School of Medicine, St. Louis, Missouri, United States of America
- Department of Neuroscience, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Justin D Lathia
- Department of Stem Cell Biology and Regenerative Medicine, Cleveland Clinic Foundation, Cleveland, Ohio, United States of America
| | - Michael E Berens
- Cancer and Cell Biology Division, The Translational Genomics Research Institute, Phoenix, Arizona, United States of America
| | - Ulrika Andersson
- Department of Radiation Sciences, Faculty of Medicine, Umeå University, Umeå, Sweden
| | - Preetha Rajaraman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, United States of America
| | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, United States of America
- Core Genotyping Facility, National Cancer Institute, SAIC-Frederick, Inc, Gaithersburg, Maryland, United States of America
| | - Martha S Linet
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, United States of America
| | - Zhaoming Wang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, United States of America
- Core Genotyping Facility, National Cancer Institute, SAIC-Frederick, Inc, Gaithersburg, Maryland, United States of America
| | - Meredith Yeager
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, United States of America
- Core Genotyping Facility, National Cancer Institute, SAIC-Frederick, Inc, Gaithersburg, Maryland, United States of America
| | - Richard S Houlston
- Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, Surrey, United Kingdom
| | - Robert B Jenkins
- Department of Laboratory Medicine and Pathology, Mayo Clinic Comprehensive Cancer Center, Mayo Clinic, Rochester, Minnesota, United States of America
| | - Beatrice Melin
- Department of Radiation Sciences, Faculty of Medicine, Umeå University, Umeå, Sweden
| | - Melissa L Bondy
- Department of Medicine, Section of Epidemiology and Population Sciences, Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas, United States of America
| | - Jill S Barnholtz-Sloan
- Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, Ohio, United States of America.
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Martínez-Montes ÁM, Fernández A, Muñoz M, Noguera JL, Folch JM, Fernández AI. Using genome wide association studies to identify common QTL regions in three different genetic backgrounds based on Iberian pig breed. PLoS One 2018. [PMID: 29522525 PMCID: PMC5844516 DOI: 10.1371/journal.pone.0190184] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
One of the major limitation for the application of QTL results in pig breeding and QTN identification has been the limited number of QTL effects validated in different animal material. The aim of the current work was to validate QTL regions through joint and specific genome wide association and haplotype analyses for growth, fatness and premier cut weights in three different genetic backgrounds, backcrosses based on Iberian pigs, which has a major role in the analysis due to its high productive relevance. The results revealed nine common QTL regions, three segregating in all three backcrosses on SSC1, 0–3 Mb, for body weight, on SSC2, 3–9 Mb, for loin bone-in weight, and on SSC7, 3 Mb, for shoulder weight, and six segregating in two of the three backcrosses, on SSC2, SSC4, SSC6 and SSC10 for backfat thickness, shoulder and ham weights. Besides, 18 QTL regions were specifically identified in one of the three backcrosses, five identified only in BC_LD, seven in BC_DU and six in BC_PI. Beyond identifying and validating QTL, candidate genes and gene variants within the most interesting regions have been explored using functional annotation, gene expression data and SNP identification from RNA-Seq data. The results allowed us to propose a promising list of candidate mutations, those identified in PDE10A, DHCR7, MFN2 and CCNY genes located within the common QTL regions and those identified near ssc-mir-103-1 considered PANK3 regulators to be further analysed.
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Affiliation(s)
- Ángel M. Martínez-Montes
- Departamento de Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Madrid, Spain
| | - Almudena Fernández
- Departamento de Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Madrid, Spain
| | - María Muñoz
- Departamento de Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Madrid, Spain
- Centro de I+D en Cerdo Ibérico, Zafra, Badajoz, Spain
| | - Jose Luis Noguera
- Departament de Genètica i Millora Animal, Institut de Recerca i Tecnologia Agroalimentàries (IRTA), Lleida, Spain
| | - Josep M. Folch
- Departament de Ciència Animal i dels Aliments, Facultat de Veterinària, Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain
- Plant and Animal Genomics, Centre de Recerca en Agrigenòmica (CRAG), Consorci CSIC-IRTA-UAB-UB, Campus UAB, Bellaterra, Spain
| | - Ana I. Fernández
- Departamento de Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Madrid, Spain
- * E-mail:
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29
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Miller JM, Festa-Bianchet M, Coltman DW. Genomic analysis of morphometric traits in bighorn sheep using the Ovine Infinium ® HD SNP BeadChip. PeerJ 2018; 6:e4364. [PMID: 29473002 PMCID: PMC5817937 DOI: 10.7717/peerj.4364] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2017] [Accepted: 01/23/2018] [Indexed: 11/20/2022] Open
Abstract
Elucidating the genetic basis of fitness-related traits is a major goal of molecular ecology. Traits subject to sexual selection are particularly interesting, as non-random mate choice should deplete genetic variation and thereby their evolutionary benefits. We examined the genetic basis of three sexually selected morphometric traits in bighorn sheep (Ovis canadensis): horn length, horn base circumference, and body mass. These traits are of specific concern in bighorn sheep as artificial selection through trophy hunting opposes sexual selection. Specifically, horn size determines trophy status and, in most North American jurisdictions, if an individual can be legally harvested. Using between 7,994–9,552 phenotypic measures from the long-term individual-based study at Ram Mountain (Alberta, Canada), we first showed that all three traits are heritable (h2 = 0.15–0.23). We then conducted a genome-wide association study (GWAS) utilizing a set of 3,777 SNPs typed in 76 individuals using the Ovine Infinium® HD SNP BeadChip. We found suggestive association for body mass at a single locus (OAR9_91647990). The absence of strong associations with SNPs suggests that the traits are likely polygenic. These results represent a step forward for characterizing the genetic architecture of fitness related traits in sexually dimorphic ungulates.
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Affiliation(s)
- Joshua M Miller
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.,Current affiliation: Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA
| | | | - David W Coltman
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada
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30
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Shen X, Klarić L, Sharapov S, Mangino M, Ning Z, Wu D, Trbojević-Akmačić I, Pučić-Baković M, Rudan I, Polašek O, Hayward C, Spector TD, Wilson JF, Lauc G, Aulchenko YS. Multivariate discovery and replication of five novel loci associated with Immunoglobulin G N-glycosylation. Nat Commun 2017; 8:447. [PMID: 28878392 PMCID: PMC5587582 DOI: 10.1038/s41467-017-00453-3] [Citation(s) in RCA: 60] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2016] [Accepted: 06/29/2017] [Indexed: 01/20/2023] Open
Abstract
Joint modeling of a number of phenotypes using multivariate methods has often been neglected in genome-wide association studies and if used, replication has not been sought. Modern omics technologies allow characterization of functional phenomena using a large number of related phenotype measures, which can benefit from such joint analysis. Here, we report a multivariate genome-wide association studies of 23 immunoglobulin G (IgG) N-glycosylation phenotypes. In the discovery cohort, our multi-phenotype method uncovers ten genome-wide significant loci, of which five are novel (IGH, ELL2, HLA-B-C, AZI1, FUT6-FUT3). We convincingly replicate all novel loci via multivariate tests. We show that IgG N-glycosylation loci are strongly enriched for genes expressed in the immune system, in particular antibody-producing cells and B lymphocytes. We empirically demonstrate the efficacy of multivariate methods to discover novel, reproducible pleiotropic effects.Multivariate analysis methods can uncover the relationship between phenotypic measures characterised by modern omic techniques. Here the authors conduct a multivariate GWAS on IgG N-glycosylation phenotypes and identify 5 novel loci enriched in immune system genes.
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Affiliation(s)
- Xia Shen
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland, UK.
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12 A, SE-17 177, Stockholm, Sweden.
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crew Road, Edinburgh, EH4 2XU, Scotland, UK.
| | - Lucija Klarić
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland, UK
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crew Road, Edinburgh, EH4 2XU, Scotland, UK
- Genos Glycoscience Research Laboratory, Hondlova 2/11, Zagreb, 10000, Croatia
| | - Sodbo Sharapov
- Novosibirsk State University, Pirogova 2, Novosibirsk, 630090, Russia
- Institute of Cytology and Genetics SB RAS, Lavrentyeva ave. 10, Novosibirsk, 630090, Russia
| | - Massimo Mangino
- Department for Twin Research, King's College London, London, WC2R 2LS, England, UK
- National Institute for Health Research (NIHR) Biomedical Research Centre at Guy's and St. Thomas' Foundation Trust, London, SE1 9RT, England, UK
| | - Zheng Ning
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12 A, SE-17 177, Stockholm, Sweden
| | - Di Wu
- Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Tomtebodavägen 23B, Stockholm, SE-171 65, Sweden
| | | | - Maja Pučić-Baković
- Genos Glycoscience Research Laboratory, Hondlova 2/11, Zagreb, 10000, Croatia
| | - Igor Rudan
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland, UK
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crew Road, Edinburgh, EH4 2XU, Scotland, UK
| | - Ozren Polašek
- Faculty of Medicine, University of Split, Šoltanska ul. 2, Split, 21000, Croatia
| | - Caroline Hayward
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crew Road, Edinburgh, EH4 2XU, Scotland, UK
| | - Timothy D Spector
- Department for Twin Research, King's College London, London, WC2R 2LS, England, UK
| | - James F Wilson
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland, UK
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crew Road, Edinburgh, EH4 2XU, Scotland, UK
| | - Gordan Lauc
- Genos Glycoscience Research Laboratory, Hondlova 2/11, Zagreb, 10000, Croatia
- Faculty of Pharmacy and Biochemistry, University of Zagreb, A. Kovacica 1, Zagreb, 10000, Croatia
| | - Yurii S Aulchenko
- Novosibirsk State University, Pirogova 2, Novosibirsk, 630090, Russia.
- Institute of Cytology and Genetics SB RAS, Lavrentyeva ave. 10, Novosibirsk, 630090, Russia.
- PolyOmica, Het Vlaggeschip 61, 's-Hertogenbosch, 5237PA, The Netherlands.
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31
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Scannell Bryan M, Argos M, Andrulis IL, Hopper JL, Chang-Claude J, Malone K, John EM, Gammon MD, Daly M, Terry MB, Buys SS, Huo D, Olopade O, Genkinger JM, Jasmine F, Kibriya MG, Chen L, Ahsan H. Limited influence of germline genetic variation on all-cause mortality in women with early onset breast cancer: evidence from gene-based tests, single-marker regression, and whole-genome prediction. Breast Cancer Res Treat 2017; 164:707-717. [PMID: 28503721 PMCID: PMC5510603 DOI: 10.1007/s10549-017-4287-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2017] [Accepted: 05/08/2017] [Indexed: 11/30/2022]
Abstract
PURPOSE Women diagnosed with breast cancer have heterogeneous survival outcomes that cannot be fully explained by known prognostic factors, and germline variation is a plausible but unconfirmed risk factor. METHODS We used three approaches to test the hypothesis that germline variation drives some differences in survival: mortality loci identification, tumor aggressiveness loci identification, and whole-genome prediction. The 2954 study participants were women diagnosed with breast cancer before age 50, with a median follow-up of 15 years who were genotyped on an exome array. We first searched for loci in gene regions that were associated with all-cause mortality. We next searched for loci in gene regions associated with five histopathological characteristics related to tumor aggressiveness. Last, we also predicted 10-year all-cause mortality on a subset of 1903 participants (3,245,343 variants after imputation) using whole-genome prediction methods. RESULTS No risk loci for mortality or tumor aggressiveness were identified. This null result persisted when restricting to women with estrogen receptor-positive tumors, when examining suggestive loci in an independent study, and when restricting to previously published risk loci. Additionally, the whole-genome prediction model also found no evidence to support an association. CONCLUSION Despite multiple complementary approaches, our study found no evidence that mortality in women with early onset breast cancer is influenced by germline variation.
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Affiliation(s)
- Molly Scannell Bryan
- University of Chicago, Chicago, IL, USA.
- University of Illinois at Chicago, Chicago, IL, 60608-1264, USA.
| | - Maria Argos
- University of Illinois at Chicago, Chicago, IL, 60608-1264, USA
| | - Irene L Andrulis
- Lunefeld-Tanenbaum Research Institute, Sinai Health System and Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | | | - Jenny Chang-Claude
- Deutsches Krebsforschungszentrum in der Helmholtz-Gemeinshaft, Hamburg, Germany
- University Cancer Center Hamburg (UCCH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | | | - Esther M John
- Cancer Prevention Institute of California, Fremont, CA, USA
- Stanford University School of Medicine, Stanford, CA, USA
| | - Marilie D Gammon
- University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Mary Daly
- Fox Chase Cancer Center, Philadelphia, PA, USA
| | | | | | | | | | | | | | | | - Lin Chen
- University of Chicago, Chicago, IL, USA
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Johari M, Arumilli M, Palmio J, Savarese M, Tasca G, Mirabella M, Sandholm N, Lohi H, Hackman P, Udd B. Association study reveals novel risk loci for sporadic inclusion body myositis. Eur J Neurol 2017; 24:572-577. [PMID: 28233382 DOI: 10.1111/ene.13244] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2016] [Accepted: 01/04/2017] [Indexed: 11/28/2022]
Abstract
BACKGROUND AND PURPOSE The aim was to identify potential genetic risk factors associated with sporadic inclusion body myositis (sIBM). METHODS An association based case-control approach was utilized on whole exome sequencing data of 30 Finnish sIBM patients and a control cohort (n = 193). A separate Italian cohort of sIBM patients (n = 12) was used for evaluation of the results. RESULTS Seven single nucleotide polymorphisms were identified in five genes that have a considerably higher observed frequency in Finnish sIBM patients compared to the control population, and the previous association of the genetic human leukocyte antigen region was confirmed. CONCLUSIONS All seven identified variants could individually or in combination increase the susceptibility for sIBM.
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Affiliation(s)
- M Johari
- Folkhälsan Institute of Genetics, Medicum, University of Helsinki, Helsinki, Finland
| | - M Arumilli
- Folkhälsan Institute of Genetics, Medicum, University of Helsinki, Helsinki, Finland.,Research Programs Unit, Molecular Neurology, University of Helsinki, Helsinki, Finland.,Department of Veterinary Biosciences, University of Helsinki, Helsinki, Finland
| | - J Palmio
- Neuromuscular Research Center, Tampere University and University Hospital, Tampere, Finland
| | - M Savarese
- Folkhälsan Institute of Genetics, Medicum, University of Helsinki, Helsinki, Finland
| | - G Tasca
- Institute of Neurology, Policlinico 'A. Gemelli' Foundation University Hospital, Rome, Italy
| | - M Mirabella
- Institute of Neurology, Catholic University School of Medicine, Rome, Italy
| | - N Sandholm
- Folkhälsan Institute of Genetics, Medicum, University of Helsinki, Helsinki, Finland.,Abdominal Center Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.,Research Program Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland
| | - H Lohi
- Folkhälsan Institute of Genetics, Medicum, University of Helsinki, Helsinki, Finland.,Research Programs Unit, Molecular Neurology, University of Helsinki, Helsinki, Finland.,Department of Veterinary Biosciences, University of Helsinki, Helsinki, Finland
| | - P Hackman
- Folkhälsan Institute of Genetics, Medicum, University of Helsinki, Helsinki, Finland
| | - B Udd
- Folkhälsan Institute of Genetics, Medicum, University of Helsinki, Helsinki, Finland.,Neuromuscular Research Center, Tampere University and University Hospital, Tampere, Finland.,Department of Neurology, Vaasa Central Hospital, Vaasa, Finland
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Abstract
Gametic phase disequilibrium is the nonrandom association of alleles within gametes. Linkage disequilibrium (LD) describes the special case of deviation from independence between alleles at two linked genetic loci. Estimation of allelic LD requires knowledge of haplotypes. Genotype-based LD measures dispense with the haplotype estimation step and avoid bias in LD estimation. In this chapter, the most important measures for allelic and genotypic LD are introduced. The use of software packages for LD estimation is illustrated.
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Affiliation(s)
- Maren Vens
- Institut für Medizinische Biometrie und Epidemiologie, Universitätsklinikum Hamburg-Eppendorf, Martinistraße 52, Hamburg, 20246, Germany.
| | - Andreas Ziegler
- Institut für Medizinische Biometrie und Statistik & Zentrum für klinische Studien, Universität zu Lübeck, Universitätsklinikum Schleswig-Holstein, Campus Lübeck, Ratzeburger Allee 160, Lübeck, 23562, Germany
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Martínez-Montes AM, Muiños-Bühl A, Fernández A, Folch JM, Ibáñez-Escriche N, Fernández AI. Deciphering the regulation of porcine genes influencing growth, fatness and yield-related traits through genetical genomics. Mamm Genome 2016; 28:130-142. [PMID: 27942838 DOI: 10.1007/s00335-016-9674-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2016] [Accepted: 11/25/2016] [Indexed: 10/20/2022]
Abstract
Genetical genomics approaches aim at identifying quantitative trait loci for molecular traits, also known as intermediate phenotypes, such as gene expression, that could link variation in genetic information to physiological traits. In the current study, an expression GWAS has been carried out on an experimental Iberian × Landrace backcross in order to identify the genomic regions regulating the gene expression of those genes whose expression is correlated with growth, fat deposition, and premium cut yield measures in pig. The analyses were conducted exploiting Porcine 60K SNP BeadChip genotypes and Porcine Expression Microarray data hybridized on mRNA from Longissimus dorsi muscle. In order to focus the analysis on productive traits and reduce the number of analyses, only those probesets whose expression showed significant correlation with at least one of the seven phenotypes of interest were selected for the eGWAS. A total of 63 eQTL regions were identified with effects on 36 different transcripts. Those eQTLs overlapping with phenotypic QTLs on SSC4, SSC9, SSC13, and SSC17 chromosomes previously detected in the same animal material were further analyzed. Moreover, candidate genes and SNPs were analyzed. Among the most promising results, a long non-coding RNA, ALDBSSCG0000001928, was identified, whose expression is correlated with premium cut yield. Association analysis and in silico sequence domain annotation support TXNRD3 polymorphisms as candidate to regulate ALDBSSCG0000001928 expression, which can be involved in the transcriptional regulation of surrounding genes, affecting productive and meat quality traits.
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Affiliation(s)
- Angel M Martínez-Montes
- Departamento de Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), 28040, Madrid, Spain.
| | - Anixa Muiños-Bühl
- Departamento de Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), 28040, Madrid, Spain
| | - Almudena Fernández
- Departamento de Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), 28040, Madrid, Spain
| | - Josep M Folch
- Departament de Ciència Animal i dels Aliments, Facultat de Veterinària, Universitat Autònoma de Barcelona (UAB), 08193, Bellaterra, Spain.,Plant and Animal Genomics, Centre de Recerca en Agrigenòmica (CRAG), Consorci CSIC-IRTA-UAB-UB, Campus UAB, 08193, Bellaterra, Spain
| | - Noelia Ibáñez-Escriche
- Departament de Genètica i Millora Animal, Institut de Recerca i Tecnologia Agroalimentàries (IRTA), 25198, Lleida, Spain
| | - Ana I Fernández
- Departamento de Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), 28040, Madrid, Spain
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35
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Non-additive genome-wide association scan reveals a new gene associated with habitual coffee consumption. Sci Rep 2016; 6:31590. [PMID: 27561104 PMCID: PMC4997959 DOI: 10.1038/srep31590] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2016] [Accepted: 07/19/2016] [Indexed: 12/27/2022] Open
Abstract
Coffee is one of the most consumed beverages world-wide and one of the primary sources of caffeine intake. Given its important health and economic impact, the underlying genetics of its consumption has been widely studied. Despite these efforts, much has still to be uncovered. In particular, the use of non-additive genetic models may uncover new information about the genetic variants driving coffee consumption. We have conducted a genome-wide association study in two Italian populations using additive, recessive and dominant models for analysis. This has uncovered a significant association in the PDSS2 gene under the recessive model that has been replicated in an independent cohort from the Netherlands (ERF). The identified gene has been shown to negatively regulate the expression of the caffeine metabolism genes and can thus be linked to coffee consumption. Further bioinformatics analysis of eQTL and histone marks from Roadmap data has evidenced a possible role of the identified SNPs in regulating PDSS2 gene expression through enhancers present in its intron. Our results highlight a novel gene which regulates coffee consumption by regulating the expression of the genes linked to caffeine metabolism. Further studies will be needed to clarify the biological mechanism which links PDSS2 and coffee consumption.
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Abstract
Development of free/libre open source software is usually done by a community of people with an interest in the tool. For scientific software, however, this is less often the case. Most scientific software is written by only a few authors, often a student working on a thesis. Once the paper describing the tool has been published, the tool is no longer developed further and is left to its own device. Here we describe the broad, multidisciplinary community we formed around a set of tools for statistical genomics. The GenABEL project for statistical omics actively promotes open interdisciplinary development of statistical methodology and its implementation in efficient and user-friendly software under an open source licence. The software tools developed withing the project collectively make up the GenABEL suite, which currently consists of eleven tools. The open framework of the project actively encourages involvement of the community in all stages, from formulation of methodological ideas to application of software to specific data sets. A web forum is used to channel user questions and discussions, further promoting the use of the GenABEL suite. Developer discussions take place on a dedicated mailing list, and development is further supported by robust development practices including use of public version control, code review and continuous integration. Use of this open science model attracts contributions from users and developers outside the “core team”, facilitating agile statistical omics methodology development and fast dissemination.
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Affiliation(s)
- Lennart C Karssen
- PolyOmica, Groningen, 9722 HC, Netherlands; Department of Epidemiology, Erasmus Medical Center, Rotterdam, 3000 CA, Netherlands
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, 3000 CA, Netherlands
| | - Yurii S Aulchenko
- PolyOmica, Groningen, 9722 HC, Netherlands; Institute of Cytology and Genetics, Siberian Division of the Russian Academy of Sciences, Novosibirsk, 630090, Russian Federation; Novosibirsk State University, Novosibirsk, 630090, Russian Federation; Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, UK
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