Biological constraints on GWAS SNPs at suggestive significance thresholds reveal additional BMI loci
- Children's Hospital of Philadelphia, United States
- Columbia University Vagelos College of Physicians and Surgeons, United States
- University of Michigan Medical School, United States
Abstract
To uncover novel significant association signals (P<5x10-8), GWAS requires increasingly larger sample sizes to overcome statistical correction for multiple testing. As an alternative, we aimed to identify associations among suggestive signals (5x10-8 ≤ P < 5x10-4) 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 ESC-derived hypothalamic-like neurons. This approach, with its extremely low false positive rate, identified 15 loci at P<5x10-5 in the 2010 GWAS, 13 of which achieved genome-wide significance by 2018, including at NAV1, MTIF3 and ADCY3. 80% 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 datasets without increasing sample size.
Data availability
Adipose ATAC-seq and promoter-focused capture C data is available in GEO under accession number GSE164912Hypothalamic Neuron ATAC-eq and promoter-focused capture C data is the subject of another atlas-based manuscript currently under peer review and through that process that dataset will be made available once the paper is published- the corresponding hypothalamus preprint can be found at: https://www.biorxiv.org/content/10.1101/2020.07.06.146951v1.full
-
Biological constraints on GWAS SNPs at suggestive significance thresholds reveal true BMI lociNCBI Gene Expression Omnibus, GSE164912.
Article and author information
Author details
Funding
Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01-HD056465)
- Struan FA Grant
National Human Genome Research Institute (R01-HG010067)
- Struan FA Grant
Children's Hospital of Philadelphia (Daniel B. Burke Endowed Chair for Diabetes Research)
- Struan FA Grant
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2021, Hammond et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 2,825
- views
-
- 217
- downloads
-
- 43
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Biological constraints on GWAS SNPs at suggestive significance thresholds reveal additional BMI loci
eLife 10:e62206.
https://doi.org/10.7554/eLife.62206
Further reading
-
- Computational and Systems Biology
- Neuroscience
Audiovisual information reaches the brain via both sustained and transient input channels, representing signals’ intensity over time or changes thereof, respectively. To date, it is unclear to what extent transient and sustained input channels contribute to the combined percept obtained through multisensory integration. Based on the results of two novel psychophysical experiments, here we demonstrate the importance of the transient (instead of the sustained) channel for the integration of audiovisual signals. To account for the present results, we developed a biologically inspired, general-purpose model for multisensory integration, the multisensory correlation detectors, which combines correlated input from unimodal transient channels. Besides accounting for the results of our psychophysical experiments, this model could quantitatively replicate several recent findings in multisensory research, as tested against a large collection of published datasets. In particular, the model could simultaneously account for the perceived timing of audiovisual events, multisensory facilitation in detection tasks, causality judgments, and optimal integration. This study demonstrates that several phenomena in multisensory research that were previously considered unrelated, all stem from the integration of correlated input from unimodal transient channels.
-
- Computational and Systems Biology
Live-cell microscopy routinely provides massive amounts of time-lapse images of complex cellular systems under various physiological or therapeutic conditions. However, this wealth of data remains difficult to interpret in terms of causal effects. Here, we describe CausalXtract, a flexible computational pipeline that discovers causal and possibly time-lagged effects from morphodynamic features and cell–cell interactions in live-cell imaging data. CausalXtract methodology combines network-based and information-based frameworks, which is shown to discover causal effects overlooked by classical Granger and Schreiber causality approaches. We showcase the use of CausalXtract to uncover novel causal effects in a tumor-on-chip cellular ecosystem under therapeutically relevant conditions. In particular, we find that cancer-associated fibroblasts directly inhibit cancer cell apoptosis, independently from anticancer treatment. CausalXtract uncovers also multiple antagonistic effects at different time delays. Hence, CausalXtract provides a unique computational tool to interpret live-cell imaging data for a range of fundamental and translational research applications.
