The analysis of the microbial structure based on linear discriminant analysis (A) and Random Forest (B), abundance analysis using EdgeR (C) according to the type of inflammatory disease and body weight in METAINFLAMMATION cohort.
<p>The most differentially abundant taxa between patients with low-grade MI and SLE according to BMI are represented in a bar graph LDA score, an estimation of the effect size. Only taxa meeting a <i>P</i> < 0.05 and LDA score significant threshold | > 2| are shown. Red, bact...
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2025
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| _version_ | 1849927628542181376 |
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| author | Lourdes Chero-Sandoval (22683418) |
| author2 | Andrea Higuera-Gómez (22683421) Begoña de Cuevillas (22683424) Raquel Castejón (13980860) María Martínez-Urbistondo (22683427) Susana Mellor-Pita (22683430) Víctor Moreno-Torres (9634628) Daniel de Luis (22683433) Amanda Cuevas-Sierra (9278315) J. Alfredo Martínez (6989336) |
| author2_role | author author author author author author author author author |
| author_facet | Lourdes Chero-Sandoval (22683418) Andrea Higuera-Gómez (22683421) Begoña de Cuevillas (22683424) Raquel Castejón (13980860) María Martínez-Urbistondo (22683427) Susana Mellor-Pita (22683430) Víctor Moreno-Torres (9634628) Daniel de Luis (22683433) Amanda Cuevas-Sierra (9278315) J. Alfredo Martínez (6989336) |
| author_role | author |
| dc.creator.none.fl_str_mv | Lourdes Chero-Sandoval (22683418) Andrea Higuera-Gómez (22683421) Begoña de Cuevillas (22683424) Raquel Castejón (13980860) María Martínez-Urbistondo (22683427) Susana Mellor-Pita (22683430) Víctor Moreno-Torres (9634628) Daniel de Luis (22683433) Amanda Cuevas-Sierra (9278315) J. Alfredo Martínez (6989336) |
| dc.date.none.fl_str_mv | 2025-11-25T18:28:53Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0335452.g002 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/The_analysis_of_the_microbial_structure_based_on_linear_discriminant_analysis_A_and_Random_Forest_B_abundance_analysis_using_EdgeR_C_according_to_the_type_of_inflammatory_disease_and_body_weight_in_METAINFLAMMATION_cohort_/30713830 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Biochemistry Ecology Sociology Immunology Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified improving clinical management div >< p alongside significant changes 127 adults diagnosed personalized approaches based body mass index systemic lupus erythematosus inflammatory markers within higher anthropometric values lupus inflammatory features gut microbiota composition alistipes shahii </ elevated crp levels grade metabolic inflammation inflammatory markers gut microbiota body composition personalized interventions inflammatory variables grade mi analyze anthropometric alistipes </ higher crp triglyceride levels lupus individuals fibrinogen levels crp levels study aimed still unclear several investigations results showed precise interaction phenotypically analyzed mi ), metainflamation cohort glycosylated hemoglobin findings showed fecal samples elevated il documented relationships categorized according 16s sequencing |
| dc.title.none.fl_str_mv | The analysis of the microbial structure based on linear discriminant analysis (A) and Random Forest (B), abundance analysis using EdgeR (C) according to the type of inflammatory disease and body weight in METAINFLAMMATION cohort. |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <p>The most differentially abundant taxa between patients with low-grade MI and SLE according to BMI are represented in a bar graph LDA score, an estimation of the effect size. Only taxa meeting a <i>P</i> < 0.05 and LDA score significant threshold | > 2| are shown. Red, bacterial taxa statistically overrepresented in low-grade MI participants and high BMI; blue, bacterial taxa overrepresented in participants with low-grade MI and low BMI; green, bacterial taxa overrepresented in participants with SLE and high BMI and purple bacterial taxa overrepresented in participants with SLE and low BMI (A).The Random Forest analysis was performed with the importance plot showing the importance of each variable in the prediction of the model, where the first variable is the most important when discerning between a low and a high BMI (B). The differential abundance analysis performed using EdgeR between patients with low-grade MI and SLE are represented with a bar plot (<i>P</i> value corrected by FDR). Red boxes represent patients with SLE and low BMI; green boxes represent patients with SLE and high BMI; light blue boxes represent patients with low-grade MI and low BMI and purple boxes represent patients with low-grade MI and high BMI (C).</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_7a2927af982fd59923817458d8bc60e6 |
| identifier_str_mv | 10.1371/journal.pone.0335452.g002 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/30713830 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | The analysis of the microbial structure based on linear discriminant analysis (A) and Random Forest (B), abundance analysis using EdgeR (C) according to the type of inflammatory disease and body weight in METAINFLAMMATION cohort.Lourdes Chero-Sandoval (22683418)Andrea Higuera-Gómez (22683421)Begoña de Cuevillas (22683424)Raquel Castejón (13980860)María Martínez-Urbistondo (22683427)Susana Mellor-Pita (22683430)Víctor Moreno-Torres (9634628)Daniel de Luis (22683433)Amanda Cuevas-Sierra (9278315)J. Alfredo Martínez (6989336)BiochemistryEcologySociologyImmunologyBiological Sciences not elsewhere classifiedChemical Sciences not elsewhere classifiedimproving clinical managementdiv >< palongside significant changes127 adults diagnosedpersonalized approaches basedbody mass indexsystemic lupus erythematosusinflammatory markers withinhigher anthropometric valueslupus inflammatory featuresgut microbiota compositionalistipes shahii </elevated crp levelsgrade metabolic inflammationinflammatory markersgut microbiotabody compositionpersonalized interventionsinflammatory variablesgrade mianalyze anthropometricalistipes </higher crptriglyceride levelslupus individualsfibrinogen levelscrp levelsstudy aimedstill unclearseveral investigationsresults showedprecise interactionphenotypically analyzedmi ),metainflamation cohortglycosylated hemoglobinfindings showedfecal sampleselevated ildocumented relationshipscategorized according16s sequencing<p>The most differentially abundant taxa between patients with low-grade MI and SLE according to BMI are represented in a bar graph LDA score, an estimation of the effect size. Only taxa meeting a <i>P</i> < 0.05 and LDA score significant threshold | > 2| are shown. Red, bacterial taxa statistically overrepresented in low-grade MI participants and high BMI; blue, bacterial taxa overrepresented in participants with low-grade MI and low BMI; green, bacterial taxa overrepresented in participants with SLE and high BMI and purple bacterial taxa overrepresented in participants with SLE and low BMI (A).The Random Forest analysis was performed with the importance plot showing the importance of each variable in the prediction of the model, where the first variable is the most important when discerning between a low and a high BMI (B). The differential abundance analysis performed using EdgeR between patients with low-grade MI and SLE are represented with a bar plot (<i>P</i> value corrected by FDR). Red boxes represent patients with SLE and low BMI; green boxes represent patients with SLE and high BMI; light blue boxes represent patients with low-grade MI and low BMI and purple boxes represent patients with low-grade MI and high BMI (C).</p>2025-11-25T18:28:53ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pone.0335452.g002https://figshare.com/articles/figure/The_analysis_of_the_microbial_structure_based_on_linear_discriminant_analysis_A_and_Random_Forest_B_abundance_analysis_using_EdgeR_C_according_to_the_type_of_inflammatory_disease_and_body_weight_in_METAINFLAMMATION_cohort_/30713830CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/307138302025-11-25T18:28:53Z |
| spellingShingle | The analysis of the microbial structure based on linear discriminant analysis (A) and Random Forest (B), abundance analysis using EdgeR (C) according to the type of inflammatory disease and body weight in METAINFLAMMATION cohort. Lourdes Chero-Sandoval (22683418) Biochemistry Ecology Sociology Immunology Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified improving clinical management div >< p alongside significant changes 127 adults diagnosed personalized approaches based body mass index systemic lupus erythematosus inflammatory markers within higher anthropometric values lupus inflammatory features gut microbiota composition alistipes shahii </ elevated crp levels grade metabolic inflammation inflammatory markers gut microbiota body composition personalized interventions inflammatory variables grade mi analyze anthropometric alistipes </ higher crp triglyceride levels lupus individuals fibrinogen levels crp levels study aimed still unclear several investigations results showed precise interaction phenotypically analyzed mi ), metainflamation cohort glycosylated hemoglobin findings showed fecal samples elevated il documented relationships categorized according 16s sequencing |
| status_str | publishedVersion |
| title | The analysis of the microbial structure based on linear discriminant analysis (A) and Random Forest (B), abundance analysis using EdgeR (C) according to the type of inflammatory disease and body weight in METAINFLAMMATION cohort. |
| title_full | The analysis of the microbial structure based on linear discriminant analysis (A) and Random Forest (B), abundance analysis using EdgeR (C) according to the type of inflammatory disease and body weight in METAINFLAMMATION cohort. |
| title_fullStr | The analysis of the microbial structure based on linear discriminant analysis (A) and Random Forest (B), abundance analysis using EdgeR (C) according to the type of inflammatory disease and body weight in METAINFLAMMATION cohort. |
| title_full_unstemmed | The analysis of the microbial structure based on linear discriminant analysis (A) and Random Forest (B), abundance analysis using EdgeR (C) according to the type of inflammatory disease and body weight in METAINFLAMMATION cohort. |
| title_short | The analysis of the microbial structure based on linear discriminant analysis (A) and Random Forest (B), abundance analysis using EdgeR (C) according to the type of inflammatory disease and body weight in METAINFLAMMATION cohort. |
| title_sort | The analysis of the microbial structure based on linear discriminant analysis (A) and Random Forest (B), abundance analysis using EdgeR (C) according to the type of inflammatory disease and body weight in METAINFLAMMATION cohort. |
| topic | Biochemistry Ecology Sociology Immunology Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified improving clinical management div >< p alongside significant changes 127 adults diagnosed personalized approaches based body mass index systemic lupus erythematosus inflammatory markers within higher anthropometric values lupus inflammatory features gut microbiota composition alistipes shahii </ elevated crp levels grade metabolic inflammation inflammatory markers gut microbiota body composition personalized interventions inflammatory variables grade mi analyze anthropometric alistipes </ higher crp triglyceride levels lupus individuals fibrinogen levels crp levels study aimed still unclear several investigations results showed precise interaction phenotypically analyzed mi ), metainflamation cohort glycosylated hemoglobin findings showed fecal samples elevated il documented relationships categorized according 16s sequencing |