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Enhanced genetic analysis of type 1 diabetes by selecting variants on both effect size and significance, and by integration with autoimmune thyroid disease

View ORCID ProfileDaniel J. M. Crouch, View ORCID ProfileJamie R.J. Inshaw, View ORCID ProfileCatherine C. Robertson, Jia-Yuan Zhang, Wei-Min Chen, Suna Onengut-Gumuscu, Antony J. Cutler, Carlo Sidore, Francesco Cucca, Flemming Pociot, Patrick Concannon, Stephen S. Rich, John A. Todd
doi: https://doi.org/10.1101/2021.02.05.429962
Daniel J. M. Crouch
1JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, United Kingdom
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  • ORCID record for Daniel J. M. Crouch
Jamie R.J. Inshaw
1JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, United Kingdom
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Catherine C. Robertson
2Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
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  • ORCID record for Catherine C. Robertson
Jia-Yuan Zhang
1JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, United Kingdom
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Wei-Min Chen
2Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
3Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, USA
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Suna Onengut-Gumuscu
2Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
3Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, USA
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Antony J. Cutler
1JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, United Kingdom
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Carlo Sidore
4Institute for Research in Genetics and Biomedicine (IRGB), Sardinia, Italy
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Francesco Cucca
4Institute for Research in Genetics and Biomedicine (IRGB), Sardinia, Italy
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Flemming Pociot
5Department of Pediatrics, Herlev University Hospital, Copenhagen, Denmark
6Institute of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
7Type 1 Diabetes Biology, Department of Clinical Research, Steno Diabetes Center Copenhagen, Gentofte, Denmark
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Patrick Concannon
8Department of Pathology, Immunology, and Laboratory Medicine, University of Florida, Gainesville, Florida, USA
9Genetics Institute, University of Florida, Gainesville, Florida, USA
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Stephen S. Rich
2Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
3Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, USA
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John A. Todd
1JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, United Kingdom
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  • For correspondence: jatodd@well.ox.ac.uk
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Abstract

For polygenic traits, associations with genetic variants can be detected over many chromosome regions, owing to the availability of large sample sizes. The majority of variants, however, have small effects on disease risk and, therefore, unraveling the causal variants, target genes, and biology of these variants is challenging. Here, we define the Bigger or False Discovery Rate (BFDR) as the probability that either a variant is a false-positive or a randomly drawn, true-positive association exceeds it in effect size. Using the BFDR, we identify new variants with larger effect associations with type 1 diabetes and autoimmune thyroid disease.

Competing Interest Statement

The authors have declared no competing interest.

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  • Supplementary tables included

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Enhanced genetic analysis of type 1 diabetes by selecting variants on both effect size and significance, and by integration with autoimmune thyroid disease
Daniel J. M. Crouch, Jamie R.J. Inshaw, Catherine C. Robertson, Jia-Yuan Zhang, Wei-Min Chen, Suna Onengut-Gumuscu, Antony J. Cutler, Carlo Sidore, Francesco Cucca, Flemming Pociot, Patrick Concannon, Stephen S. Rich, John A. Todd
bioRxiv 2021.02.05.429962; doi: https://doi.org/10.1101/2021.02.05.429962
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Enhanced genetic analysis of type 1 diabetes by selecting variants on both effect size and significance, and by integration with autoimmune thyroid disease
Daniel J. M. Crouch, Jamie R.J. Inshaw, Catherine C. Robertson, Jia-Yuan Zhang, Wei-Min Chen, Suna Onengut-Gumuscu, Antony J. Cutler, Carlo Sidore, Francesco Cucca, Flemming Pociot, Patrick Concannon, Stephen S. Rich, John A. Todd
bioRxiv 2021.02.05.429962; doi: https://doi.org/10.1101/2021.02.05.429962

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