An artificial neural network approach integrating plasma proteomics and genetic data identifies PLXNA4 as a new susceptibility locus for pulmonary embolism
Abstract Venous thromboembolism is the third common cardiovascular disease and is composed of two entities, deep vein thrombosis (DVT) and its potential fatal form, pulmonary embolism (PE). While PE is observed in ~ 40% of patients with documented DVT, there is limited biomarkers that can help ident...
Guardado en:
| Autores principales: | , , , , , , , , , , , , , , , , , |
|---|---|
| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2021
|
| Materias: | |
| Acceso en línea: | https://doaj.org/article/74d0ce5beba343ef8ad57e5adf7555bd |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| id |
oai:doaj.org-article:74d0ce5beba343ef8ad57e5adf7555bd |
|---|---|
| record_format |
dspace |
| spelling |
oai:doaj.org-article:74d0ce5beba343ef8ad57e5adf7555bd2021-12-02T15:22:56ZAn artificial neural network approach integrating plasma proteomics and genetic data identifies PLXNA4 as a new susceptibility locus for pulmonary embolism10.1038/s41598-021-93390-72045-2322https://doaj.org/article/74d0ce5beba343ef8ad57e5adf7555bd2021-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-93390-7https://doaj.org/toc/2045-2322Abstract Venous thromboembolism is the third common cardiovascular disease and is composed of two entities, deep vein thrombosis (DVT) and its potential fatal form, pulmonary embolism (PE). While PE is observed in ~ 40% of patients with documented DVT, there is limited biomarkers that can help identifying patients at high PE risk. To fill this need, we implemented a two hidden-layers artificial neural networks (ANN) on 376 antibodies and 19 biological traits measured in the plasma of 1388 DVT patients, with or without PE, of the MARTHA study. We used the LIME algorithm to obtain a linear approximate of the resulting ANN prediction model. As MARTHA patients were typed for genotyping DNA arrays, a genome wide association study (GWAS) was conducted on the LIME estimate. Detected single nucleotide polymorphisms (SNPs) were tested for association with PE risk in MARTHA. Main findings were replicated in the EOVT study composed of 143 PE patients and 196 DVT only patients. The derived ANN model for PE achieved an accuracy of 0.89 and 0.79 in our training and testing sets, respectively. A GWAS on the LIME approximate identified a strong statistical association peak (rs1424597: p = 5.3 × 10–7) at the PLXNA4 locus. Homozygote carriers for the rs1424597-A allele were then more frequently observed in PE than in DVT patients from the MARTHA (2% vs. 0.4%, p = 0.005) and the EOVT (3% vs. 0%, p = 0.013) studies. In a sample of 112 COVID-19 patients known to have endotheliopathy leading to acute lung injury and an increased risk of PE, decreased PLXNA4 levels were associated (p = 0.025) with worsened respiratory function. Using an original integrated proteomics and genetics strategy, we identified PLXNA4 as a new susceptibility gene for PE whose exact role now needs to be further elucidated.Misbah RazzaqMaria Jesus IglesiasManal Ibrahim-KostaLouisa GoumidiOmar SoukariehCarole ProustMaguelonne RouxPierre SuchonAnne BolandDelphine DaiainRobert OlasoSebastian HavervallCharlotte ThalinLynn ButlerJean-François DeleuzeJacob OdebergPierre-Emmanuel MorangeDavid-Alexandre TrégouëtNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-13 (2021) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
Medicine R Science Q |
| spellingShingle |
Medicine R Science Q Misbah Razzaq Maria Jesus Iglesias Manal Ibrahim-Kosta Louisa Goumidi Omar Soukarieh Carole Proust Maguelonne Roux Pierre Suchon Anne Boland Delphine Daiain Robert Olaso Sebastian Havervall Charlotte Thalin Lynn Butler Jean-François Deleuze Jacob Odeberg Pierre-Emmanuel Morange David-Alexandre Trégouët An artificial neural network approach integrating plasma proteomics and genetic data identifies PLXNA4 as a new susceptibility locus for pulmonary embolism |
| description |
Abstract Venous thromboembolism is the third common cardiovascular disease and is composed of two entities, deep vein thrombosis (DVT) and its potential fatal form, pulmonary embolism (PE). While PE is observed in ~ 40% of patients with documented DVT, there is limited biomarkers that can help identifying patients at high PE risk. To fill this need, we implemented a two hidden-layers artificial neural networks (ANN) on 376 antibodies and 19 biological traits measured in the plasma of 1388 DVT patients, with or without PE, of the MARTHA study. We used the LIME algorithm to obtain a linear approximate of the resulting ANN prediction model. As MARTHA patients were typed for genotyping DNA arrays, a genome wide association study (GWAS) was conducted on the LIME estimate. Detected single nucleotide polymorphisms (SNPs) were tested for association with PE risk in MARTHA. Main findings were replicated in the EOVT study composed of 143 PE patients and 196 DVT only patients. The derived ANN model for PE achieved an accuracy of 0.89 and 0.79 in our training and testing sets, respectively. A GWAS on the LIME approximate identified a strong statistical association peak (rs1424597: p = 5.3 × 10–7) at the PLXNA4 locus. Homozygote carriers for the rs1424597-A allele were then more frequently observed in PE than in DVT patients from the MARTHA (2% vs. 0.4%, p = 0.005) and the EOVT (3% vs. 0%, p = 0.013) studies. In a sample of 112 COVID-19 patients known to have endotheliopathy leading to acute lung injury and an increased risk of PE, decreased PLXNA4 levels were associated (p = 0.025) with worsened respiratory function. Using an original integrated proteomics and genetics strategy, we identified PLXNA4 as a new susceptibility gene for PE whose exact role now needs to be further elucidated. |
| format |
article |
| author |
Misbah Razzaq Maria Jesus Iglesias Manal Ibrahim-Kosta Louisa Goumidi Omar Soukarieh Carole Proust Maguelonne Roux Pierre Suchon Anne Boland Delphine Daiain Robert Olaso Sebastian Havervall Charlotte Thalin Lynn Butler Jean-François Deleuze Jacob Odeberg Pierre-Emmanuel Morange David-Alexandre Trégouët |
| author_facet |
Misbah Razzaq Maria Jesus Iglesias Manal Ibrahim-Kosta Louisa Goumidi Omar Soukarieh Carole Proust Maguelonne Roux Pierre Suchon Anne Boland Delphine Daiain Robert Olaso Sebastian Havervall Charlotte Thalin Lynn Butler Jean-François Deleuze Jacob Odeberg Pierre-Emmanuel Morange David-Alexandre Trégouët |
| author_sort |
Misbah Razzaq |
| title |
An artificial neural network approach integrating plasma proteomics and genetic data identifies PLXNA4 as a new susceptibility locus for pulmonary embolism |
| title_short |
An artificial neural network approach integrating plasma proteomics and genetic data identifies PLXNA4 as a new susceptibility locus for pulmonary embolism |
| title_full |
An artificial neural network approach integrating plasma proteomics and genetic data identifies PLXNA4 as a new susceptibility locus for pulmonary embolism |
| title_fullStr |
An artificial neural network approach integrating plasma proteomics and genetic data identifies PLXNA4 as a new susceptibility locus for pulmonary embolism |
| title_full_unstemmed |
An artificial neural network approach integrating plasma proteomics and genetic data identifies PLXNA4 as a new susceptibility locus for pulmonary embolism |
| title_sort |
artificial neural network approach integrating plasma proteomics and genetic data identifies plxna4 as a new susceptibility locus for pulmonary embolism |
| publisher |
Nature Portfolio |
| publishDate |
2021 |
| url |
https://doaj.org/article/74d0ce5beba343ef8ad57e5adf7555bd |
| work_keys_str_mv |
AT misbahrazzaq anartificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT mariajesusiglesias anartificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT manalibrahimkosta anartificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT louisagoumidi anartificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT omarsoukarieh anartificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT caroleproust anartificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT maguelonneroux anartificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT pierresuchon anartificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT anneboland anartificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT delphinedaiain anartificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT robertolaso anartificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT sebastianhavervall anartificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT charlottethalin anartificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT lynnbutler anartificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT jeanfrancoisdeleuze anartificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT jacobodeberg anartificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT pierreemmanuelmorange anartificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT davidalexandretregouet anartificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT misbahrazzaq artificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT mariajesusiglesias artificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT manalibrahimkosta artificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT louisagoumidi artificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT omarsoukarieh artificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT caroleproust artificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT maguelonneroux artificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT pierresuchon artificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT anneboland artificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT delphinedaiain artificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT robertolaso artificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT sebastianhavervall artificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT charlottethalin artificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT lynnbutler artificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT jeanfrancoisdeleuze artificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT jacobodeberg artificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT pierreemmanuelmorange artificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism AT davidalexandretregouet artificialneuralnetworkapproachintegratingplasmaproteomicsandgeneticdataidentifiesplxna4asanewsusceptibilitylocusforpulmonaryembolism |
| _version_ |
1718387387202011136 |