Scoring personalized molecular portraits identify Systemic Lupus Erythematosus subtypes and predict individualized drug responses, symptomatology and disease progression
| Autor: | Daniel Toro-Domínguez, Jordi Martorell-Marugán, Manuel Martinez-Bueno, Raúl López-Domínguez, Elena Carnero-Montoro, Guillermo Barturen, Daniel Goldman, Michelle Petri, Pedro Carmona-Sáez, Marta E Alarcón-Riquelme |
|---|---|
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Briefings in Bioinformatics |
| ISSN: | 1477-4054 1467-5463 |
| DOI: | 10.1093/bib/bbac332 |
| Popis: | 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. PID2020-119032RB-I00 supported by MCIN/AEI/10.13039/501100011033 FEDER and the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement No 831434 (3TR) European Union’s Horizon 2020 EFPIA FEDER/Junta de Andalucía-Consejer’a de Transformación Económica, Industria, Conocimiento y Universidades (grants P20_00335 and B-CTS-40-UGR20) ‘Consejería de Transformación Económica, Industria, Conocimiento y Universidades’ (CTEICU) European Union through the European Social Fund (ESF) named ‘Andalucía se mueve con Europa” Andalusian ESF Operational Program 2014–2020 ISCIII CD18/00149 Ministerio de Universidades (Spain’s Government) and the European Union – NextGenerationEU |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|