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Identifying modifiable comorbidities of schizophrenia by integrating electronic health records and polygenic risk
Patients with schizophrenia have substantial comorbidity contributing to reduced life expectancy of 10–20 years. Identifying which comorbidities might be modifiable could improve rates of premature mortality in this population. We hypothesize that conditions that frequently co-occur but lack shared...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Cold Spring Harbor Laboratory
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10274978/ https://www.ncbi.nlm.nih.gov/pubmed/37333378 http://dx.doi.org/10.1101/2023.06.01.23290057 |
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author | Vessels, Tess Strayer, Nicholas Choi, Karmel W. Lee, Hyunjoon Zhang, Siwei Han, Lide Morley, Theodore J. Smoller, Jordan W. Xu, Yaomin Ruderfer, Douglas M. |
author_facet | Vessels, Tess Strayer, Nicholas Choi, Karmel W. Lee, Hyunjoon Zhang, Siwei Han, Lide Morley, Theodore J. Smoller, Jordan W. Xu, Yaomin Ruderfer, Douglas M. |
author_sort | Vessels, Tess |
collection | PubMed |
description | Patients with schizophrenia have substantial comorbidity contributing to reduced life expectancy of 10–20 years. Identifying which comorbidities might be modifiable could improve rates of premature mortality in this population. We hypothesize that conditions that frequently co-occur but lack shared genetic risk with schizophrenia are more likely to be products of treatment, behavior, or environmental factors and therefore potentially modifiable. To test this hypothesis, we calculated phenome-wide comorbidity from electronic health records (EHR) in 250,000 patients in each of two independent health care institutions (Vanderbilt University Medical Center and Mass General Brigham) and association with schizophrenia polygenic risk scores (PRS) across the same phenotypes (phecodes) in linked biobanks. Comorbidity with schizophrenia was significantly correlated across institutions (r = 0.85) and consistent with prior literature. After multiple test correction, there were 77 significant phecodes comorbid with schizophrenia. Overall, comorbidity and PRS association were highly correlated (r = 0.55, p = 1.29×10(−118)), however, 36 of the EHR identified comorbidities had significantly equivalent schizophrenia PRS distributions between cases and controls. Fifteen of these lacked any PRS association and were enriched for phenotypes known to be side effects of antipsychotic medications (e.g., “movement disorders”, “convulsions”, “tachycardia”) or other schizophrenia related factors such as from smoking (“bronchitis”) or reduced hygiene (e.g., “diseases of the nail”) highlighting the validity of this approach. Other phenotypes implicated by this approach where the contribution from shared common genetic risk with schizophrenia was minimal included tobacco use disorder, diabetes, and dementia. This work demonstrates the consistency and robustness of EHR-based schizophrenia comorbidities across independent institutions and with the existing literature. It identifies comorbidities with an absence of shared genetic risk indicating other causes that might be more modifiable and where further study of causal pathways could improve outcomes for patients. |
format | Online Article Text |
id | pubmed-10274978 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-102749782023-06-17 Identifying modifiable comorbidities of schizophrenia by integrating electronic health records and polygenic risk Vessels, Tess Strayer, Nicholas Choi, Karmel W. Lee, Hyunjoon Zhang, Siwei Han, Lide Morley, Theodore J. Smoller, Jordan W. Xu, Yaomin Ruderfer, Douglas M. medRxiv Article Patients with schizophrenia have substantial comorbidity contributing to reduced life expectancy of 10–20 years. Identifying which comorbidities might be modifiable could improve rates of premature mortality in this population. We hypothesize that conditions that frequently co-occur but lack shared genetic risk with schizophrenia are more likely to be products of treatment, behavior, or environmental factors and therefore potentially modifiable. To test this hypothesis, we calculated phenome-wide comorbidity from electronic health records (EHR) in 250,000 patients in each of two independent health care institutions (Vanderbilt University Medical Center and Mass General Brigham) and association with schizophrenia polygenic risk scores (PRS) across the same phenotypes (phecodes) in linked biobanks. Comorbidity with schizophrenia was significantly correlated across institutions (r = 0.85) and consistent with prior literature. After multiple test correction, there were 77 significant phecodes comorbid with schizophrenia. Overall, comorbidity and PRS association were highly correlated (r = 0.55, p = 1.29×10(−118)), however, 36 of the EHR identified comorbidities had significantly equivalent schizophrenia PRS distributions between cases and controls. Fifteen of these lacked any PRS association and were enriched for phenotypes known to be side effects of antipsychotic medications (e.g., “movement disorders”, “convulsions”, “tachycardia”) or other schizophrenia related factors such as from smoking (“bronchitis”) or reduced hygiene (e.g., “diseases of the nail”) highlighting the validity of this approach. Other phenotypes implicated by this approach where the contribution from shared common genetic risk with schizophrenia was minimal included tobacco use disorder, diabetes, and dementia. This work demonstrates the consistency and robustness of EHR-based schizophrenia comorbidities across independent institutions and with the existing literature. It identifies comorbidities with an absence of shared genetic risk indicating other causes that might be more modifiable and where further study of causal pathways could improve outcomes for patients. Cold Spring Harbor Laboratory 2023-06-05 /pmc/articles/PMC10274978/ /pubmed/37333378 http://dx.doi.org/10.1101/2023.06.01.23290057 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 Vessels, Tess Strayer, Nicholas Choi, Karmel W. Lee, Hyunjoon Zhang, Siwei Han, Lide Morley, Theodore J. Smoller, Jordan W. Xu, Yaomin Ruderfer, Douglas M. Identifying modifiable comorbidities of schizophrenia by integrating electronic health records and polygenic risk |
title | Identifying modifiable comorbidities of schizophrenia by integrating electronic health records and polygenic risk |
title_full | Identifying modifiable comorbidities of schizophrenia by integrating electronic health records and polygenic risk |
title_fullStr | Identifying modifiable comorbidities of schizophrenia by integrating electronic health records and polygenic risk |
title_full_unstemmed | Identifying modifiable comorbidities of schizophrenia by integrating electronic health records and polygenic risk |
title_short | Identifying modifiable comorbidities of schizophrenia by integrating electronic health records and polygenic risk |
title_sort | identifying modifiable comorbidities of schizophrenia by integrating electronic health records and polygenic risk |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10274978/ https://www.ncbi.nlm.nih.gov/pubmed/37333378 http://dx.doi.org/10.1101/2023.06.01.23290057 |
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