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OTTO: a new strategy to extract mental disease-relevant combinations of GWAS hits from individuals

Despite high heritability of schizophrenia, genome-wide association studies (GWAS) have not yet revealed distinct combinations of single-nucleotide polymorphisms (SNPs), relevant for mental disease-related, quantifiable behavioral phenotypes. Here we propose an individual-based model to use genome-w...

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Autores principales: Ehrenreich, H, Mitjans, M, Van der Auwera, S, Centeno, T P, Begemann, M, Grabe, H J, Bonn, S, Nave, K-A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5794905/
https://www.ncbi.nlm.nih.gov/pubmed/27922606
http://dx.doi.org/10.1038/mp.2016.208
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author Ehrenreich, H
Mitjans, M
Van der Auwera, S
Centeno, T P
Begemann, M
Grabe, H J
Bonn, S
Nave, K-A
author_facet Ehrenreich, H
Mitjans, M
Van der Auwera, S
Centeno, T P
Begemann, M
Grabe, H J
Bonn, S
Nave, K-A
author_sort Ehrenreich, H
collection PubMed
description Despite high heritability of schizophrenia, genome-wide association studies (GWAS) have not yet revealed distinct combinations of single-nucleotide polymorphisms (SNPs), relevant for mental disease-related, quantifiable behavioral phenotypes. Here we propose an individual-based model to use genome-wide significant markers for extracting first genetic signatures of such behavioral continua. ‘OTTO’ (old Germanic=heritage) marks an individual characterized by a prominent phenotype and a particular load of phenotype-associated risk SNPs derived from GWAS that likely contributed to the development of his personal mental illness. This load of risk SNPs is shared by a small squad of ‘similars’ scattered under the genetically and phenotypically extremely heterogeneous umbrella of a schizophrenia end point diagnosis and to a variable degree also by healthy subjects. In a discovery sample of >1000 deeply phenotyped schizophrenia patients and several independent replication samples, including the general population, a gradual increase in the severity of ‘OTTO’s phenotype’ expression is observed with an increasing share of ‘OTTO’s risk SNPs’, as exemplified here by autistic and affective phenotypes. These data suggest a model in which the genetic contribution to dimensional behavioral traits can be extracted from combinations of GWAS SNPs derived from individuals with prominent phenotypes. Even though still in the ‘model phase’ owing to a world-wide lack of sufficiently powered, deeply phenotyped replication samples, the OTTO approach constitutes a conceptually novel strategy to delineate biological subcategories of mental diseases starting from GWAS findings and individual subjects.
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spelling pubmed-57949052018-02-05 OTTO: a new strategy to extract mental disease-relevant combinations of GWAS hits from individuals Ehrenreich, H Mitjans, M Van der Auwera, S Centeno, T P Begemann, M Grabe, H J Bonn, S Nave, K-A Mol Psychiatry Original Article Despite high heritability of schizophrenia, genome-wide association studies (GWAS) have not yet revealed distinct combinations of single-nucleotide polymorphisms (SNPs), relevant for mental disease-related, quantifiable behavioral phenotypes. Here we propose an individual-based model to use genome-wide significant markers for extracting first genetic signatures of such behavioral continua. ‘OTTO’ (old Germanic=heritage) marks an individual characterized by a prominent phenotype and a particular load of phenotype-associated risk SNPs derived from GWAS that likely contributed to the development of his personal mental illness. This load of risk SNPs is shared by a small squad of ‘similars’ scattered under the genetically and phenotypically extremely heterogeneous umbrella of a schizophrenia end point diagnosis and to a variable degree also by healthy subjects. In a discovery sample of >1000 deeply phenotyped schizophrenia patients and several independent replication samples, including the general population, a gradual increase in the severity of ‘OTTO’s phenotype’ expression is observed with an increasing share of ‘OTTO’s risk SNPs’, as exemplified here by autistic and affective phenotypes. These data suggest a model in which the genetic contribution to dimensional behavioral traits can be extracted from combinations of GWAS SNPs derived from individuals with prominent phenotypes. Even though still in the ‘model phase’ owing to a world-wide lack of sufficiently powered, deeply phenotyped replication samples, the OTTO approach constitutes a conceptually novel strategy to delineate biological subcategories of mental diseases starting from GWAS findings and individual subjects. Nature Publishing Group 2018-02 2016-12-06 /pmc/articles/PMC5794905/ /pubmed/27922606 http://dx.doi.org/10.1038/mp.2016.208 Text en Copyright © 2018 The Author(s) http://creativecommons.org/licenses/by-nc-nd/4.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/
spellingShingle Original Article
Ehrenreich, H
Mitjans, M
Van der Auwera, S
Centeno, T P
Begemann, M
Grabe, H J
Bonn, S
Nave, K-A
OTTO: a new strategy to extract mental disease-relevant combinations of GWAS hits from individuals
title OTTO: a new strategy to extract mental disease-relevant combinations of GWAS hits from individuals
title_full OTTO: a new strategy to extract mental disease-relevant combinations of GWAS hits from individuals
title_fullStr OTTO: a new strategy to extract mental disease-relevant combinations of GWAS hits from individuals
title_full_unstemmed OTTO: a new strategy to extract mental disease-relevant combinations of GWAS hits from individuals
title_short OTTO: a new strategy to extract mental disease-relevant combinations of GWAS hits from individuals
title_sort otto: a new strategy to extract mental disease-relevant combinations of gwas hits from individuals
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5794905/
https://www.ncbi.nlm.nih.gov/pubmed/27922606
http://dx.doi.org/10.1038/mp.2016.208
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