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Biological constraints on GWAS SNPs at suggestive significance thresholds reveal additional BMI loci

To uncover novel significant association signals (p<5×10(−8)), genome-wide association studies (GWAS) requires increasingly larger sample sizes to overcome statistical correction for multiple testing. As an alternative, we aimed to identify associations among suggestive signals (5 × 10(−8)≤p<5...

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Autores principales: Hammond, Reza K, Pahl, Matthew C, Su, Chun, Cousminer, Diana L, Leonard, Michelle E, Lu, Sumei, Doege, Claudia A, Wagley, Yadav, Hodge, Kenyaita M, Lasconi, Chiara, Johnson, Matthew E, Pippin, James A, Hankenson, Kurt D, Leibel, Rudolph L, Chesi, Alessandra, Wells, Andrew D, Grant, Struan FA
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7815306/
https://www.ncbi.nlm.nih.gov/pubmed/33459256
http://dx.doi.org/10.7554/eLife.62206
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author Hammond, Reza K
Pahl, Matthew C
Su, Chun
Cousminer, Diana L
Leonard, Michelle E
Lu, Sumei
Doege, Claudia A
Wagley, Yadav
Hodge, Kenyaita M
Lasconi, Chiara
Johnson, Matthew E
Pippin, James A
Hankenson, Kurt D
Leibel, Rudolph L
Chesi, Alessandra
Wells, Andrew D
Grant, Struan FA
author_facet Hammond, Reza K
Pahl, Matthew C
Su, Chun
Cousminer, Diana L
Leonard, Michelle E
Lu, Sumei
Doege, Claudia A
Wagley, Yadav
Hodge, Kenyaita M
Lasconi, Chiara
Johnson, Matthew E
Pippin, James A
Hankenson, Kurt D
Leibel, Rudolph L
Chesi, Alessandra
Wells, Andrew D
Grant, Struan FA
author_sort Hammond, Reza K
collection PubMed
description To uncover novel significant association signals (p<5×10(−8)), genome-wide association studies (GWAS) requires increasingly larger sample sizes to overcome statistical correction for multiple testing. As an alternative, we aimed to identify associations among suggestive signals (5 × 10(−8)≤p<5×10(−4)) in increasingly powered GWAS efforts using chromatin accessibility and direct contact with gene promoters as biological constraints. We conducted retrospective analyses of three GIANT BMI GWAS efforts using ATAC-seq and promoter-focused Capture C data from human adipocytes and embryonic stem cell (ESC)-derived hypothalamic-like neurons. This approach, with its extremely low false-positive rate, identified 15 loci at p<5×10(−5) in the 2010 GWAS, of which 13 achieved genome-wide significance by 2018, including at NAV1, MTIF3, and ADCY3. Eighty percent of constrained 2015 loci achieved genome-wide significance in 2018. We observed similar results in waist-to-hip ratio analyses. In conclusion, biological constraints on sub-significant GWAS signals can reveal potentially true-positive loci for further investigation in existing data sets without increasing sample size.
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spelling pubmed-78153062021-01-21 Biological constraints on GWAS SNPs at suggestive significance thresholds reveal additional BMI loci Hammond, Reza K Pahl, Matthew C Su, Chun Cousminer, Diana L Leonard, Michelle E Lu, Sumei Doege, Claudia A Wagley, Yadav Hodge, Kenyaita M Lasconi, Chiara Johnson, Matthew E Pippin, James A Hankenson, Kurt D Leibel, Rudolph L Chesi, Alessandra Wells, Andrew D Grant, Struan FA eLife Computational and Systems Biology To uncover novel significant association signals (p<5×10(−8)), genome-wide association studies (GWAS) requires increasingly larger sample sizes to overcome statistical correction for multiple testing. As an alternative, we aimed to identify associations among suggestive signals (5 × 10(−8)≤p<5×10(−4)) in increasingly powered GWAS efforts using chromatin accessibility and direct contact with gene promoters as biological constraints. We conducted retrospective analyses of three GIANT BMI GWAS efforts using ATAC-seq and promoter-focused Capture C data from human adipocytes and embryonic stem cell (ESC)-derived hypothalamic-like neurons. This approach, with its extremely low false-positive rate, identified 15 loci at p<5×10(−5) in the 2010 GWAS, of which 13 achieved genome-wide significance by 2018, including at NAV1, MTIF3, and ADCY3. Eighty percent of constrained 2015 loci achieved genome-wide significance in 2018. We observed similar results in waist-to-hip ratio analyses. In conclusion, biological constraints on sub-significant GWAS signals can reveal potentially true-positive loci for further investigation in existing data sets without increasing sample size. eLife Sciences Publications, Ltd 2021-01-18 /pmc/articles/PMC7815306/ /pubmed/33459256 http://dx.doi.org/10.7554/eLife.62206 Text en © 2021, Hammond et al http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Computational and Systems Biology
Hammond, Reza K
Pahl, Matthew C
Su, Chun
Cousminer, Diana L
Leonard, Michelle E
Lu, Sumei
Doege, Claudia A
Wagley, Yadav
Hodge, Kenyaita M
Lasconi, Chiara
Johnson, Matthew E
Pippin, James A
Hankenson, Kurt D
Leibel, Rudolph L
Chesi, Alessandra
Wells, Andrew D
Grant, Struan FA
Biological constraints on GWAS SNPs at suggestive significance thresholds reveal additional BMI loci
title Biological constraints on GWAS SNPs at suggestive significance thresholds reveal additional BMI loci
title_full Biological constraints on GWAS SNPs at suggestive significance thresholds reveal additional BMI loci
title_fullStr Biological constraints on GWAS SNPs at suggestive significance thresholds reveal additional BMI loci
title_full_unstemmed Biological constraints on GWAS SNPs at suggestive significance thresholds reveal additional BMI loci
title_short Biological constraints on GWAS SNPs at suggestive significance thresholds reveal additional BMI loci
title_sort biological constraints on gwas snps at suggestive significance thresholds reveal additional bmi loci
topic Computational and Systems Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7815306/
https://www.ncbi.nlm.nih.gov/pubmed/33459256
http://dx.doi.org/10.7554/eLife.62206
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