Developing symptom clusters: linking inflammatory biomarkers to depressive symptom profiles
Abstract Considering the burden of depression and the lack of efficacy of available treatments, there is a need for biomarkers to predict tailored or personalized treatments. However, identifying reliable biomarkers for depression has been challenging, likely owing to the vast symptom heterogeneity...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2022-03-01
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| Series: | Translational Psychiatry |
| Online Access: | https://doi.org/10.1038/s41398-022-01900-6 |
| _version_ | 1819025098630234112 |
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| author | Sabina I. Franklyn Jayme Stewart Cecile Beaurepaire Emily Thaw Robyn J. McQuaid |
| author_facet | Sabina I. Franklyn Jayme Stewart Cecile Beaurepaire Emily Thaw Robyn J. McQuaid |
| author_sort | Sabina I. Franklyn |
| collection | DOAJ |
| description | Abstract Considering the burden of depression and the lack of efficacy of available treatments, there is a need for biomarkers to predict tailored or personalized treatments. However, identifying reliable biomarkers for depression has been challenging, likely owing to the vast symptom heterogeneity and high rates of comorbidity that exists. Examining biomarkers that map onto dimensions of depression as well as shared symptoms/constructs that cut across disorders could be most effective for informing personalized treatment approaches. With a sample of 539 young adults, we conducted a principal component analysis (PCA) followed by hierarchical cluster analysis to develop transdiagnostic clusters of depression and anxiety symptoms. We collected blood to assess whether neuroendocrine (cortisol) and inflammatory profiles (C-reactive protein (CRP), Interleukin (IL)-6, and tumor necrosis factor (TNF) – α) could be used to differentiate symptom clusters. Six distinct clusters were identified that differed significantly on symptom dimensions including somatic anxiety, general anxiety, anhedonia, and neurovegetative depression. Moreover, the neurovegetative depression cluster displayed significantly elevated CRP levels compared to other clusters. In fact, inflammation was not strongly associated with overall depression scores or severity, but rather related to specific features of depression marked by eating, appetite, and tiredness. This study emphasizes the importance of characterizing the biological underpinnings of symptom dimensions and subtypes to better understand the etiology of complex mental health disorders such as depression. |
| first_indexed | 2024-12-21T05:05:17Z |
| format | Article |
| id | doaj.art-75adb2499cb045eeab73a4841da40a89 |
| institution | Directory Open Access Journal |
| issn | 2158-3188 |
| language | English |
| last_indexed | 2024-12-21T05:05:17Z |
| publishDate | 2022-03-01 |
| publisher | Nature Publishing Group |
| record_format | Article |
| series | Translational Psychiatry |
| spelling | doaj.art-75adb2499cb045eeab73a4841da40a892022-12-21T19:15:09ZengNature Publishing GroupTranslational Psychiatry2158-31882022-03-011211710.1038/s41398-022-01900-6Developing symptom clusters: linking inflammatory biomarkers to depressive symptom profilesSabina I. Franklyn0Jayme Stewart1Cecile Beaurepaire2Emily Thaw3Robyn J. McQuaid4Department of Psychology, Carleton UniversityDepartment of Psychology, Carleton UniversityUniversity of Ottawa Institute of Mental Health ResearchDepartment of Neuroscience, Carleton UniversityUniversity of Ottawa Institute of Mental Health ResearchAbstract Considering the burden of depression and the lack of efficacy of available treatments, there is a need for biomarkers to predict tailored or personalized treatments. However, identifying reliable biomarkers for depression has been challenging, likely owing to the vast symptom heterogeneity and high rates of comorbidity that exists. Examining biomarkers that map onto dimensions of depression as well as shared symptoms/constructs that cut across disorders could be most effective for informing personalized treatment approaches. With a sample of 539 young adults, we conducted a principal component analysis (PCA) followed by hierarchical cluster analysis to develop transdiagnostic clusters of depression and anxiety symptoms. We collected blood to assess whether neuroendocrine (cortisol) and inflammatory profiles (C-reactive protein (CRP), Interleukin (IL)-6, and tumor necrosis factor (TNF) – α) could be used to differentiate symptom clusters. Six distinct clusters were identified that differed significantly on symptom dimensions including somatic anxiety, general anxiety, anhedonia, and neurovegetative depression. Moreover, the neurovegetative depression cluster displayed significantly elevated CRP levels compared to other clusters. In fact, inflammation was not strongly associated with overall depression scores or severity, but rather related to specific features of depression marked by eating, appetite, and tiredness. This study emphasizes the importance of characterizing the biological underpinnings of symptom dimensions and subtypes to better understand the etiology of complex mental health disorders such as depression.https://doi.org/10.1038/s41398-022-01900-6 |
| spellingShingle | Sabina I. Franklyn Jayme Stewart Cecile Beaurepaire Emily Thaw Robyn J. McQuaid Developing symptom clusters: linking inflammatory biomarkers to depressive symptom profiles Translational Psychiatry |
| title | Developing symptom clusters: linking inflammatory biomarkers to depressive symptom profiles |
| title_full | Developing symptom clusters: linking inflammatory biomarkers to depressive symptom profiles |
| title_fullStr | Developing symptom clusters: linking inflammatory biomarkers to depressive symptom profiles |
| title_full_unstemmed | Developing symptom clusters: linking inflammatory biomarkers to depressive symptom profiles |
| title_short | Developing symptom clusters: linking inflammatory biomarkers to depressive symptom profiles |
| title_sort | developing symptom clusters linking inflammatory biomarkers to depressive symptom profiles |
| url | https://doi.org/10.1038/s41398-022-01900-6 |
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