Peripheral inflammatory and metabolic markers as potential biomarkers in treatment-resistant schizophrenia: Insights from a Qatari Cohort
<p dir="ltr">Schizophrenia presents significant diagnostic and treatment challenges, particularly in distinguishing between treatment-resistant (TRS) and non-treatment-resistant schizophrenia (NTRS). This cross-sectional study analyzed routine laboratory parameters as potential bioma...
محفوظ في:
| المؤلف الرئيسي: | |
|---|---|
| مؤلفون آخرون: | , , , , , , , , , , , |
| منشور في: |
2024
|
| الموضوعات: | |
| الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
| _version_ | 1864513539510632448 |
|---|---|
| author | Mohamed Adil Shah Khoodoruth (14589828) |
| author2 | Tarteel Hussain (21480143) Sami Ouanes (9617363) Nuzhah Widaad Chut-kai Khoodoruth (22282546) Adel Hmissi (22282549) Samuel L. Lachica (22282552) Mustafa Nissar Bankur (22282555) Abdul Waheed Khan (4835988) Mohamad Samir Makki (22282558) Yasser Saeed Khan (17191735) James Currie (16079431) Majid Alabdullah (17945051) Farhan Mohammad (256409) |
| author2_role | author author author author author author author author author author author author |
| author_facet | Mohamed Adil Shah Khoodoruth (14589828) Tarteel Hussain (21480143) Sami Ouanes (9617363) Nuzhah Widaad Chut-kai Khoodoruth (22282546) Adel Hmissi (22282549) Samuel L. Lachica (22282552) Mustafa Nissar Bankur (22282555) Abdul Waheed Khan (4835988) Mohamad Samir Makki (22282558) Yasser Saeed Khan (17191735) James Currie (16079431) Majid Alabdullah (17945051) Farhan Mohammad (256409) |
| author_role | author |
| dc.creator.none.fl_str_mv | Mohamed Adil Shah Khoodoruth (14589828) Tarteel Hussain (21480143) Sami Ouanes (9617363) Nuzhah Widaad Chut-kai Khoodoruth (22282546) Adel Hmissi (22282549) Samuel L. Lachica (22282552) Mustafa Nissar Bankur (22282555) Abdul Waheed Khan (4835988) Mohamad Samir Makki (22282558) Yasser Saeed Khan (17191735) James Currie (16079431) Majid Alabdullah (17945051) Farhan Mohammad (256409) |
| dc.date.none.fl_str_mv | 2024-12-06T12:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1016/j.psychres.2024.116307 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Peripheral_inflammatory_and_metabolic_markers_as_potential_biomarkers_in_treatment-resistant_schizophrenia_Insights_from_a_Qatari_Cohort/30173257 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Biological sciences Genetics Biomedical and clinical sciences Clinical sciences Neurosciences Health sciences Health services and systems Treatment resistant schizophrenia Schizophrenia Biomarkers Inflammation Clozapine Machine learning Qatar precision health institute-Qatar biobank |
| dc.title.none.fl_str_mv | Peripheral inflammatory and metabolic markers as potential biomarkers in treatment-resistant schizophrenia: Insights from a Qatari Cohort |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">Schizophrenia presents significant diagnostic and treatment challenges, particularly in distinguishing between treatment-resistant (TRS) and non-treatment-resistant schizophrenia (NTRS). This cross-sectional study analyzed routine laboratory parameters as potential biomarkers to differentiate TRS, NTRS, and healthy individuals within a Qatari cohort. The study included 31 TRS and 38 NTRS patients diagnosed with schizophrenia, alongside 30 control subjects from the Qatar Biobank. Key measurements included complete blood count, lipid panel, HbA1c, and ferritin levels. Our findings indicated elevated body mass index (BMI) and triglyceride (TG) levels in both patient groups compared to controls. The NTRS group also showed higher HbA1c levels. Variations in inflammatory markers were noted, with the NTRS group exhibiting a higher platelet/lymphocyte ratio (PLR). Multivariate analysis highlighted significant differences in platelet count, mean platelet volume (MPV), TG, HbA1c, BMI, neutrophil/lymphocyte ratio (NLR), monocyte/lymphocyte ratio (MLR), and ferritin among the groups. Linear regression analysis revealed that MLR and clozapine treatment were significantly correlated with the severity of schizophrenia symptoms. The Random Forest model, a supervised machine learning algorithm, efficiently differentiated between cases and controls and between TRS and NTRS, with accuracies of 86.87 % and 88.41 %, respectively. However, removing <u>PANSS</u> scores notably decreased the model's diagnostic effectiveness. These results suggest that accessible peripheral laboratory parameters can serve as useful biomarkers for schizophrenia, potentially aiding in the early identification of TRS, enhancing personalized treatment strategies, and contributing to precision psychiatry. Future longitudinal studies are necessary to confirm these findings and further explore the role of inflammation in schizophrenia pathophysiology and treatment response.</p><h2>Other Information</h2><p dir="ltr">Published in: Psychiatry Research<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.psychres.2024.116307" target="_blank">https://dx.doi.org/10.1016/j.psychres.2024.116307</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_d6be09f45f1a677d0bc899cf781cede0 |
| identifier_str_mv | 10.1016/j.psychres.2024.116307 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/30173257 |
| publishDate | 2024 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Peripheral inflammatory and metabolic markers as potential biomarkers in treatment-resistant schizophrenia: Insights from a Qatari CohortMohamed Adil Shah Khoodoruth (14589828)Tarteel Hussain (21480143)Sami Ouanes (9617363)Nuzhah Widaad Chut-kai Khoodoruth (22282546)Adel Hmissi (22282549)Samuel L. Lachica (22282552)Mustafa Nissar Bankur (22282555)Abdul Waheed Khan (4835988)Mohamad Samir Makki (22282558)Yasser Saeed Khan (17191735)James Currie (16079431)Majid Alabdullah (17945051)Farhan Mohammad (256409)Biological sciencesGeneticsBiomedical and clinical sciencesClinical sciencesNeurosciencesHealth sciencesHealth services and systemsTreatment resistant schizophreniaSchizophreniaBiomarkersInflammationClozapineMachine learningQatar precision health institute-Qatar biobank<p dir="ltr">Schizophrenia presents significant diagnostic and treatment challenges, particularly in distinguishing between treatment-resistant (TRS) and non-treatment-resistant schizophrenia (NTRS). This cross-sectional study analyzed routine laboratory parameters as potential biomarkers to differentiate TRS, NTRS, and healthy individuals within a Qatari cohort. The study included 31 TRS and 38 NTRS patients diagnosed with schizophrenia, alongside 30 control subjects from the Qatar Biobank. Key measurements included complete blood count, lipid panel, HbA1c, and ferritin levels. Our findings indicated elevated body mass index (BMI) and triglyceride (TG) levels in both patient groups compared to controls. The NTRS group also showed higher HbA1c levels. Variations in inflammatory markers were noted, with the NTRS group exhibiting a higher platelet/lymphocyte ratio (PLR). Multivariate analysis highlighted significant differences in platelet count, mean platelet volume (MPV), TG, HbA1c, BMI, neutrophil/lymphocyte ratio (NLR), monocyte/lymphocyte ratio (MLR), and ferritin among the groups. Linear regression analysis revealed that MLR and clozapine treatment were significantly correlated with the severity of schizophrenia symptoms. The Random Forest model, a supervised machine learning algorithm, efficiently differentiated between cases and controls and between TRS and NTRS, with accuracies of 86.87 % and 88.41 %, respectively. However, removing <u>PANSS</u> scores notably decreased the model's diagnostic effectiveness. These results suggest that accessible peripheral laboratory parameters can serve as useful biomarkers for schizophrenia, potentially aiding in the early identification of TRS, enhancing personalized treatment strategies, and contributing to precision psychiatry. Future longitudinal studies are necessary to confirm these findings and further explore the role of inflammation in schizophrenia pathophysiology and treatment response.</p><h2>Other Information</h2><p dir="ltr">Published in: Psychiatry Research<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.psychres.2024.116307" target="_blank">https://dx.doi.org/10.1016/j.psychres.2024.116307</a></p>2024-12-06T12:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1016/j.psychres.2024.116307https://figshare.com/articles/journal_contribution/Peripheral_inflammatory_and_metabolic_markers_as_potential_biomarkers_in_treatment-resistant_schizophrenia_Insights_from_a_Qatari_Cohort/30173257CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/301732572024-12-06T12:00:00Z |
| spellingShingle | Peripheral inflammatory and metabolic markers as potential biomarkers in treatment-resistant schizophrenia: Insights from a Qatari Cohort Mohamed Adil Shah Khoodoruth (14589828) Biological sciences Genetics Biomedical and clinical sciences Clinical sciences Neurosciences Health sciences Health services and systems Treatment resistant schizophrenia Schizophrenia Biomarkers Inflammation Clozapine Machine learning Qatar precision health institute-Qatar biobank |
| status_str | publishedVersion |
| title | Peripheral inflammatory and metabolic markers as potential biomarkers in treatment-resistant schizophrenia: Insights from a Qatari Cohort |
| title_full | Peripheral inflammatory and metabolic markers as potential biomarkers in treatment-resistant schizophrenia: Insights from a Qatari Cohort |
| title_fullStr | Peripheral inflammatory and metabolic markers as potential biomarkers in treatment-resistant schizophrenia: Insights from a Qatari Cohort |
| title_full_unstemmed | Peripheral inflammatory and metabolic markers as potential biomarkers in treatment-resistant schizophrenia: Insights from a Qatari Cohort |
| title_short | Peripheral inflammatory and metabolic markers as potential biomarkers in treatment-resistant schizophrenia: Insights from a Qatari Cohort |
| title_sort | Peripheral inflammatory and metabolic markers as potential biomarkers in treatment-resistant schizophrenia: Insights from a Qatari Cohort |
| topic | Biological sciences Genetics Biomedical and clinical sciences Clinical sciences Neurosciences Health sciences Health services and systems Treatment resistant schizophrenia Schizophrenia Biomarkers Inflammation Clozapine Machine learning Qatar precision health institute-Qatar biobank |