Scoring personalized molecular portraits identify Systemic Lupus Erythematosus subtypes and predict individualized drug responses, symptomatology and disease progression
© The Author(s) 2022. Published by Oxford University Press..
OBJECTIVES: Systemic Lupus Erythematosus is a complex autoimmune disease that leads to significant worsening of quality of life and mortality. Flares appear unpredictably during the disease course and therapies used are often only partially effective. These challenges are mainly due to the molecular heterogeneity of the disease, and in this context, personalized medicine-based approaches offer major promise. With this work we intended to advance in that direction by developing MyPROSLE, an omic-based analytical workflow for measuring the molecular portrait of individual patients to support clinicians in their therapeutic decisions.
METHODS: Immunological gene-modules were used to represent the transcriptome of the patients. A dysregulation score for each gene-module was calculated at the patient level based on averaged z-scores. Almost 6100 Lupus and 750 healthy samples were used to analyze the association among dysregulation scores, clinical manifestations, prognosis, flare and remission events and response to Tabalumab. Machine learning-based classification models were built to predict around 100 different clinical parameters based on personalized dysregulation scores.
RESULTS: MyPROSLE allows to molecularly summarize patients in 206 gene-modules, clustered into nine main lupus signatures. The combination of these modules revealed highly differentiated pathological mechanisms. We found that the dysregulation of certain gene-modules is strongly associated with specific clinical manifestations, the occurrence of relapses or the presence of long-term remission and drug response. Therefore, MyPROSLE may be used to accurately predict these clinical outcomes.
CONCLUSIONS: MyPROSLE (https://myprosle.genyo.es) allows molecular characterization of individual Lupus patients and it extracts key molecular information to support more precise therapeutic decisions.
| Errataetall: |
CommentIn: Brief Bioinform. 2023 Sep 20;24(5):. - PMID 37670507 |
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| Medienart: |
E-Artikel |
| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:23 |
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| Enthalten in: |
Briefings in bioinformatics - 23(2022), 5 vom: 20. Sept. |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Toro-Domínguez, Daniel [VerfasserIn] |
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| Links: |
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| Themen: |
Autoimmune diseases |
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| Anmerkungen: |
Date Completed 26.09.2022 Date Revised 25.09.2023 published: Print ClinicalTrials.gov: NCT01205438, NCT01196091 CommentIn: Brief Bioinform. 2023 Sep 20;24(5):. - PMID 37670507 Citation Status MEDLINE |
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| doi: |
10.1093/bib/bbac332 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 100 | 1 | |a Toro-Domínguez, Daniel |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Scoring personalized molecular portraits identify Systemic Lupus Erythematosus subtypes and predict individualized drug responses, symptomatology and disease progression |
| 264 | 1 | |c 2022 | |
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| 500 | |a ClinicalTrials.gov: NCT01205438, NCT01196091 | ||
| 500 | |a CommentIn: Brief Bioinform. 2023 Sep 20;24(5):. - PMID 37670507 | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © The Author(s) 2022. Published by Oxford University Press. | ||
| 520 | |a OBJECTIVES: Systemic Lupus Erythematosus is a complex autoimmune disease that leads to significant worsening of quality of life and mortality. Flares appear unpredictably during the disease course and therapies used are often only partially effective. These challenges are mainly due to the molecular heterogeneity of the disease, and in this context, personalized medicine-based approaches offer major promise. With this work we intended to advance in that direction by developing MyPROSLE, an omic-based analytical workflow for measuring the molecular portrait of individual patients to support clinicians in their therapeutic decisions | ||
| 520 | |a METHODS: Immunological gene-modules were used to represent the transcriptome of the patients. A dysregulation score for each gene-module was calculated at the patient level based on averaged z-scores. Almost 6100 Lupus and 750 healthy samples were used to analyze the association among dysregulation scores, clinical manifestations, prognosis, flare and remission events and response to Tabalumab. Machine learning-based classification models were built to predict around 100 different clinical parameters based on personalized dysregulation scores | ||
| 520 | |a RESULTS: MyPROSLE allows to molecularly summarize patients in 206 gene-modules, clustered into nine main lupus signatures. The combination of these modules revealed highly differentiated pathological mechanisms. We found that the dysregulation of certain gene-modules is strongly associated with specific clinical manifestations, the occurrence of relapses or the presence of long-term remission and drug response. Therefore, MyPROSLE may be used to accurately predict these clinical outcomes | ||
| 520 | |a CONCLUSIONS: MyPROSLE (https://myprosle.genyo.es) allows molecular characterization of individual Lupus patients and it extracts key molecular information to support more precise therapeutic decisions | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a Systemic Lupus Erythematosus | |
| 650 | 4 | |a autoimmune diseases | |
| 650 | 4 | |a computational models | |
| 650 | 4 | |a molecular profiling | |
| 650 | 4 | |a personalized medicine | |
| 700 | 1 | |a Martorell-Marugán, Jordi |e verfasserin |4 aut | |
| 700 | 1 | |a Martinez-Bueno, Manuel |e verfasserin |4 aut | |
| 700 | 1 | |a López-Domínguez, Raúl |e verfasserin |4 aut | |
| 700 | 1 | |a Carnero-Montoro, Elena |e verfasserin |4 aut | |
| 700 | 1 | |a Barturen, Guillermo |e verfasserin |4 aut | |
| 700 | 1 | |a Goldman, Daniel |e verfasserin |4 aut | |
| 700 | 1 | |a Petri, Michelle |e verfasserin |4 aut | |
| 700 | 1 | |a Carmona-Sáez, Pedro |e verfasserin |4 aut | |
| 700 | 1 | |a Alarcón-Riquelme, Marta E |e verfasserin |4 aut | |
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