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Evaluating brain structure traits as endophenotypes using polygenicity and discoverability
Human brain structure traits have been hypothesized to be broad endophenotypes for neuropsychiatric disorders, implying that brain structure traits are comparatively “closer to the underlying biology.” Genome‐wide association studies from large sample sizes allow for the comparison of common variant...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8675430/ https://www.ncbi.nlm.nih.gov/pubmed/33098356 http://dx.doi.org/10.1002/hbm.25257 |
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author | Matoba, Nana Love, Michael I. Stein, Jason L. |
author_facet | Matoba, Nana Love, Michael I. Stein, Jason L. |
author_sort | Matoba, Nana |
collection | PubMed |
description | Human brain structure traits have been hypothesized to be broad endophenotypes for neuropsychiatric disorders, implying that brain structure traits are comparatively “closer to the underlying biology.” Genome‐wide association studies from large sample sizes allow for the comparison of common variant genetic architectures between traits to test the evidence supporting this claim. Endophenotypes, compared to neuropsychiatric disorders, are hypothesized to have less polygenicity, with greater effect size of each susceptible SNP, requiring smaller sample sizes to discover them. Here, we compare polygenicity and discoverability of brain structure traits, neuropsychiatric disorders, and other traits (91 in total) to directly test this hypothesis. We found reduced polygenicity (FDR = 0.01) and increased discoverability (FDR = 3.68 × 10(−9)) of cortical brain structure traits, as compared to aggregated estimates of multiple neuropsychiatric disorders. We predict that ~8 M individuals will be required to explain the full heritability of cortical surface area by genome‐wide significant SNPs, whereas sample sizes over 20 M will be required to explain the full heritability of depression. In conclusion, our findings are consistent with brain structure satisfying the higher power criterion of endophenotypes. |
format | Online Article Text |
id | pubmed-8675430 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley & Sons, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-86754302021-12-27 Evaluating brain structure traits as endophenotypes using polygenicity and discoverability Matoba, Nana Love, Michael I. Stein, Jason L. Hum Brain Mapp Research Articles Human brain structure traits have been hypothesized to be broad endophenotypes for neuropsychiatric disorders, implying that brain structure traits are comparatively “closer to the underlying biology.” Genome‐wide association studies from large sample sizes allow for the comparison of common variant genetic architectures between traits to test the evidence supporting this claim. Endophenotypes, compared to neuropsychiatric disorders, are hypothesized to have less polygenicity, with greater effect size of each susceptible SNP, requiring smaller sample sizes to discover them. Here, we compare polygenicity and discoverability of brain structure traits, neuropsychiatric disorders, and other traits (91 in total) to directly test this hypothesis. We found reduced polygenicity (FDR = 0.01) and increased discoverability (FDR = 3.68 × 10(−9)) of cortical brain structure traits, as compared to aggregated estimates of multiple neuropsychiatric disorders. We predict that ~8 M individuals will be required to explain the full heritability of cortical surface area by genome‐wide significant SNPs, whereas sample sizes over 20 M will be required to explain the full heritability of depression. In conclusion, our findings are consistent with brain structure satisfying the higher power criterion of endophenotypes. John Wiley & Sons, Inc. 2020-10-24 /pmc/articles/PMC8675430/ /pubmed/33098356 http://dx.doi.org/10.1002/hbm.25257 Text en © 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Articles Matoba, Nana Love, Michael I. Stein, Jason L. Evaluating brain structure traits as endophenotypes using polygenicity and discoverability |
title | Evaluating brain structure traits as endophenotypes using polygenicity and discoverability |
title_full | Evaluating brain structure traits as endophenotypes using polygenicity and discoverability |
title_fullStr | Evaluating brain structure traits as endophenotypes using polygenicity and discoverability |
title_full_unstemmed | Evaluating brain structure traits as endophenotypes using polygenicity and discoverability |
title_short | Evaluating brain structure traits as endophenotypes using polygenicity and discoverability |
title_sort | evaluating brain structure traits as endophenotypes using polygenicity and discoverability |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8675430/ https://www.ncbi.nlm.nih.gov/pubmed/33098356 http://dx.doi.org/10.1002/hbm.25257 |
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