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An association test of the spatial distribution of rare missense variants within protein structures identifies Alzheimer's disease–related patterns

More than 90% of genetic variants are rare in most modern sequencing studies, such as the Alzheimer's Disease Sequencing Project (ADSP) whole-exome sequencing (WES) data. Furthermore, 54% of the rare variants in ADSP WES are singletons. However, both single variant and unit-based tests are limi...

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Autores principales: Jin, Bowen, Capra, John A., Benchek, Penelope, Wheeler, Nicholas, Naj, Adam C., Hamilton-Nelson, Kara L., Farrell, John J., Leung, Yuk Yee, Kunkle, Brian, Vadarajan, Badri, Schellenberg, Gerard D., Mayeux, Richard, Wang, Li-San, Farrer, Lindsay A., Pericak-Vance, Margaret A., Martin, Eden R., Haines, Jonathan L., Crawford, Dana C., Bush, William S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8997344/
https://www.ncbi.nlm.nih.gov/pubmed/35210353
http://dx.doi.org/10.1101/gr.276069.121
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author Jin, Bowen
Capra, John A.
Benchek, Penelope
Wheeler, Nicholas
Naj, Adam C.
Hamilton-Nelson, Kara L.
Farrell, John J.
Leung, Yuk Yee
Kunkle, Brian
Vadarajan, Badri
Schellenberg, Gerard D.
Mayeux, Richard
Wang, Li-San
Farrer, Lindsay A.
Pericak-Vance, Margaret A.
Martin, Eden R.
Haines, Jonathan L.
Crawford, Dana C.
Bush, William S.
author_facet Jin, Bowen
Capra, John A.
Benchek, Penelope
Wheeler, Nicholas
Naj, Adam C.
Hamilton-Nelson, Kara L.
Farrell, John J.
Leung, Yuk Yee
Kunkle, Brian
Vadarajan, Badri
Schellenberg, Gerard D.
Mayeux, Richard
Wang, Li-San
Farrer, Lindsay A.
Pericak-Vance, Margaret A.
Martin, Eden R.
Haines, Jonathan L.
Crawford, Dana C.
Bush, William S.
author_sort Jin, Bowen
collection PubMed
description More than 90% of genetic variants are rare in most modern sequencing studies, such as the Alzheimer's Disease Sequencing Project (ADSP) whole-exome sequencing (WES) data. Furthermore, 54% of the rare variants in ADSP WES are singletons. However, both single variant and unit-based tests are limited in their statistical power to detect an association between rare variants and phenotypes. To best use missense rare variants and investigate their biological effect, we examine their association with phenotypes in the context of protein structures. We developed a protein structure–based approach, protein optimized kernel evaluation of missense nucleotides (POKEMON), which evaluates rare missense variants based on their spatial distribution within a protein rather than their allele frequency. The hypothesis behind this test is that the three-dimensional spatial distribution of variants within a protein structure provides functional context to power an association test. POKEMON identified three candidate genes (TREM2, SORL1, and EXOC3L4) and another suggestive gene from the ADSP WES data. For TREM2 and SORL1, two known Alzheimer's disease (AD) genes, the signal from the spatial cluster is stable even if we exclude known AD risk variants, indicating the presence of additional low-frequency risk variants within these genes. EXOC3L4 is a novel AD risk gene that has a cluster of variants primarily shared by case subjects around the Sec6 domain. This cluster is also validated in an independent replication data set and a validation data set with a larger sample size.
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spelling pubmed-89973442022-04-22 An association test of the spatial distribution of rare missense variants within protein structures identifies Alzheimer's disease–related patterns Jin, Bowen Capra, John A. Benchek, Penelope Wheeler, Nicholas Naj, Adam C. Hamilton-Nelson, Kara L. Farrell, John J. Leung, Yuk Yee Kunkle, Brian Vadarajan, Badri Schellenberg, Gerard D. Mayeux, Richard Wang, Li-San Farrer, Lindsay A. Pericak-Vance, Margaret A. Martin, Eden R. Haines, Jonathan L. Crawford, Dana C. Bush, William S. Genome Res Method More than 90% of genetic variants are rare in most modern sequencing studies, such as the Alzheimer's Disease Sequencing Project (ADSP) whole-exome sequencing (WES) data. Furthermore, 54% of the rare variants in ADSP WES are singletons. However, both single variant and unit-based tests are limited in their statistical power to detect an association between rare variants and phenotypes. To best use missense rare variants and investigate their biological effect, we examine their association with phenotypes in the context of protein structures. We developed a protein structure–based approach, protein optimized kernel evaluation of missense nucleotides (POKEMON), which evaluates rare missense variants based on their spatial distribution within a protein rather than their allele frequency. The hypothesis behind this test is that the three-dimensional spatial distribution of variants within a protein structure provides functional context to power an association test. POKEMON identified three candidate genes (TREM2, SORL1, and EXOC3L4) and another suggestive gene from the ADSP WES data. For TREM2 and SORL1, two known Alzheimer's disease (AD) genes, the signal from the spatial cluster is stable even if we exclude known AD risk variants, indicating the presence of additional low-frequency risk variants within these genes. EXOC3L4 is a novel AD risk gene that has a cluster of variants primarily shared by case subjects around the Sec6 domain. This cluster is also validated in an independent replication data set and a validation data set with a larger sample size. Cold Spring Harbor Laboratory Press 2022-04 /pmc/articles/PMC8997344/ /pubmed/35210353 http://dx.doi.org/10.1101/gr.276069.121 Text en © 2022 Jin et al.; Published by Cold Spring Harbor Laboratory Press https://creativecommons.org/licenses/by-nc/4.0/This article, published in Genome Research, is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Method
Jin, Bowen
Capra, John A.
Benchek, Penelope
Wheeler, Nicholas
Naj, Adam C.
Hamilton-Nelson, Kara L.
Farrell, John J.
Leung, Yuk Yee
Kunkle, Brian
Vadarajan, Badri
Schellenberg, Gerard D.
Mayeux, Richard
Wang, Li-San
Farrer, Lindsay A.
Pericak-Vance, Margaret A.
Martin, Eden R.
Haines, Jonathan L.
Crawford, Dana C.
Bush, William S.
An association test of the spatial distribution of rare missense variants within protein structures identifies Alzheimer's disease–related patterns
title An association test of the spatial distribution of rare missense variants within protein structures identifies Alzheimer's disease–related patterns
title_full An association test of the spatial distribution of rare missense variants within protein structures identifies Alzheimer's disease–related patterns
title_fullStr An association test of the spatial distribution of rare missense variants within protein structures identifies Alzheimer's disease–related patterns
title_full_unstemmed An association test of the spatial distribution of rare missense variants within protein structures identifies Alzheimer's disease–related patterns
title_short An association test of the spatial distribution of rare missense variants within protein structures identifies Alzheimer's disease–related patterns
title_sort association test of the spatial distribution of rare missense variants within protein structures identifies alzheimer's disease–related patterns
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8997344/
https://www.ncbi.nlm.nih.gov/pubmed/35210353
http://dx.doi.org/10.1101/gr.276069.121
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