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Non-additive effects of schizophrenia risk genes reflect convergent downstream function

Genetic studies of schizophrenia (SCZ) reveal a complex polygenic risk architecture comprised of hundreds of risk variants, the majority of which are common in the population at-large and confer only modest increases in disorder risk. Precisely how genetic variants with individually small predicted...

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Autores principales: Deans, PJ Michael, Seah, Carina, Johnson, Jessica, Gonzalez, Judit Garcia, Townsley, Kayla, Cao, Evan, Schrode, Nadine, Stahl, Eli, O’Reilly, Paul, Huckins, Laura M., Brennand, Kristen J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10055596/
https://www.ncbi.nlm.nih.gov/pubmed/36993466
http://dx.doi.org/10.1101/2023.03.20.23287497
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author Deans, PJ Michael
Seah, Carina
Johnson, Jessica
Gonzalez, Judit Garcia
Townsley, Kayla
Cao, Evan
Schrode, Nadine
Stahl, Eli
O’Reilly, Paul
Huckins, Laura M.
Brennand, Kristen J.
author_facet Deans, PJ Michael
Seah, Carina
Johnson, Jessica
Gonzalez, Judit Garcia
Townsley, Kayla
Cao, Evan
Schrode, Nadine
Stahl, Eli
O’Reilly, Paul
Huckins, Laura M.
Brennand, Kristen J.
author_sort Deans, PJ Michael
collection PubMed
description Genetic studies of schizophrenia (SCZ) reveal a complex polygenic risk architecture comprised of hundreds of risk variants, the majority of which are common in the population at-large and confer only modest increases in disorder risk. Precisely how genetic variants with individually small predicted effects on gene expression combine to yield substantial clinical impacts in aggregate is unclear. Towards this, we previously reported that the combinatorial perturbation of four SCZ risk genes (“eGenes”, whose expression is regulated by common variants) resulted in gene expression changes that were not predicted by individual perturbations, being most non-additive among genes associated with synaptic function and SCZ risk. Now, across fifteen SCZ eGenes, we demonstrate that non-additive effects are greatest within groups of functionally similar eGenes. Individual eGene perturbations reveal common downstream transcriptomic effects (“convergence”), while combinatorial eGene perturbations result in changes that are smaller than predicted by summing individual eGene effects (“sub-additive effects”). Unexpectedly, these convergent and sub-additive downstream transcriptomic effects overlap and constitute a large proportion of the genome-wide polygenic risk score, suggesting that functional redundancy of eGenes may be a major mechanism underlying non-additivity. Single eGene perturbations likewise fail to predict the magnitude or directionality of cellular phenotypes resulting from combinatorial perturbations. Overall, our results indicate that polygenic risk cannot be extrapolated from experiments testing one risk gene at a time and must instead be empirically measured. By unravelling the interactions between complex risk variants, it may be possible to improve the clinical utility of polygenic risk scores through more powerful prediction of symptom onset, clinical trajectory, and treatment response, or to identify novel targets for therapeutic intervention.
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spelling pubmed-100555962023-03-30 Non-additive effects of schizophrenia risk genes reflect convergent downstream function Deans, PJ Michael Seah, Carina Johnson, Jessica Gonzalez, Judit Garcia Townsley, Kayla Cao, Evan Schrode, Nadine Stahl, Eli O’Reilly, Paul Huckins, Laura M. Brennand, Kristen J. medRxiv Article Genetic studies of schizophrenia (SCZ) reveal a complex polygenic risk architecture comprised of hundreds of risk variants, the majority of which are common in the population at-large and confer only modest increases in disorder risk. Precisely how genetic variants with individually small predicted effects on gene expression combine to yield substantial clinical impacts in aggregate is unclear. Towards this, we previously reported that the combinatorial perturbation of four SCZ risk genes (“eGenes”, whose expression is regulated by common variants) resulted in gene expression changes that were not predicted by individual perturbations, being most non-additive among genes associated with synaptic function and SCZ risk. Now, across fifteen SCZ eGenes, we demonstrate that non-additive effects are greatest within groups of functionally similar eGenes. Individual eGene perturbations reveal common downstream transcriptomic effects (“convergence”), while combinatorial eGene perturbations result in changes that are smaller than predicted by summing individual eGene effects (“sub-additive effects”). Unexpectedly, these convergent and sub-additive downstream transcriptomic effects overlap and constitute a large proportion of the genome-wide polygenic risk score, suggesting that functional redundancy of eGenes may be a major mechanism underlying non-additivity. Single eGene perturbations likewise fail to predict the magnitude or directionality of cellular phenotypes resulting from combinatorial perturbations. Overall, our results indicate that polygenic risk cannot be extrapolated from experiments testing one risk gene at a time and must instead be empirically measured. By unravelling the interactions between complex risk variants, it may be possible to improve the clinical utility of polygenic risk scores through more powerful prediction of symptom onset, clinical trajectory, and treatment response, or to identify novel targets for therapeutic intervention. Cold Spring Harbor Laboratory 2023-03-21 /pmc/articles/PMC10055596/ /pubmed/36993466 http://dx.doi.org/10.1101/2023.03.20.23287497 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.
spellingShingle Article
Deans, PJ Michael
Seah, Carina
Johnson, Jessica
Gonzalez, Judit Garcia
Townsley, Kayla
Cao, Evan
Schrode, Nadine
Stahl, Eli
O’Reilly, Paul
Huckins, Laura M.
Brennand, Kristen J.
Non-additive effects of schizophrenia risk genes reflect convergent downstream function
title Non-additive effects of schizophrenia risk genes reflect convergent downstream function
title_full Non-additive effects of schizophrenia risk genes reflect convergent downstream function
title_fullStr Non-additive effects of schizophrenia risk genes reflect convergent downstream function
title_full_unstemmed Non-additive effects of schizophrenia risk genes reflect convergent downstream function
title_short Non-additive effects of schizophrenia risk genes reflect convergent downstream function
title_sort non-additive effects of schizophrenia risk genes reflect convergent downstream function
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10055596/
https://www.ncbi.nlm.nih.gov/pubmed/36993466
http://dx.doi.org/10.1101/2023.03.20.23287497
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