tetano
Editor, Senior Moderator
Mol Med
. 2026 May 27.
doi: 10.1186/s10020-026-01512-6. Online ahead of print.
Machine learning, whole genome sequencing, and Mendelian randomization support a role of CRP on COVID-19 severity
Francesca Lantieri[SUP] #[/SUP][SUP] 1 2 [/SUP], Stefania Croci[SUP] #[/SUP][SUP] 3 [/SUP], Sergio Decherchi[SUP] #[/SUP][SUP] 4 [/SUP], Marta Rusmini[SUP] 2 [/SUP], Giada Recchi[SUP] 5 [/SUP], Martina Bonacini[SUP] 3 [/SUP], Ilaria Ferrigno[SUP] 3 [/SUP], Alessandro Rossi[SUP] 3 [/SUP], Yeraldin Chiquinquira Castillo De Spelorzi[SUP] 6 [/SUP], Edoardo Henzen[SUP] 6 [/SUP], Francesca Rosamilia[SUP] 2 [/SUP], Davide Cangelosi[SUP] 2 [/SUP], Fabio Landuzzi[SUP] 7 [/SUP], Andrea Angius[SUP] 8 [/SUP], Vincenzo Rallo[SUP] 8 [/SUP], Pamela Mancuso[SUP] 9 [/SUP], Annamaria Pezzarossi[SUP] 9 [/SUP], Paolo Giorgi Rossi[SUP] 9 [/SUP], Mariagrazia Catanoso[SUP] 10 [/SUP], Marco Gattorno[SUP] 5 [/SUP], Andrea Cavalli[SUP] 11 12 [/SUP], Pier Luigi Meroni[SUP] 13 [/SUP], Diego Vozzi[SUP] 6 [/SUP], Paolo Uva[SUP] 2 [/SUP], Isabella Ceccherini[SUP] 14 [/SUP], Carlo Salvarani[SUP] 10 15 [/SUP]
Affiliations
Background: The coronavirus disease 2019 (COVID-19) ranges from asymptomatic to very severe infection and death, largely depending on host factors, including genetics. We have investigated clinical and genetic data from 200 COVID-19 patients to search for factors predisposing to increased disease severity.
Methods: Patients were divided into non-hospitalized mild/pauci-symptomatic and hospitalized severe. An interpretable Machine Learning approach was applied to blood biomarkers while genome-wide associations were performed for COVID-19 severity. Finally, a possible causal role of chronic low-grade inflammation on COVID-19 severity was searched by Mendelian Randomization.
Results: A high severity predictive role was observed in our sample by Machine Learning for the C-Reactive Protein measured in the course of SARS-CoV-2 infection (iCRP). This was also suggested by evidence of association with variants known to be involved in the CRP levels in the general population (pCRP). Finally, a possible causal role of chronic low-grade inflammation on COVID-19 severity could be shown by Mendelian Randomization using publicly available summary statistics of two COVID-19 Genome-Wide Association Studies.
Conclusions: Consistent with previous results, a predictive role of CRP levels on COVID-19 severity was detected in our sample. Furthermore, Mendelian Randomization supported a causal role of genetically predicted chronic CRP levels.
Keywords: C-Reactive Protein; COVID-19 severity prediction; CRP causal role; Interpretable Machine Learning; Mendelian Randomization; TFEB.
. 2026 May 27.
doi: 10.1186/s10020-026-01512-6. Online ahead of print.
Machine learning, whole genome sequencing, and Mendelian randomization support a role of CRP on COVID-19 severity
Francesca Lantieri[SUP] #[/SUP][SUP] 1 2 [/SUP], Stefania Croci[SUP] #[/SUP][SUP] 3 [/SUP], Sergio Decherchi[SUP] #[/SUP][SUP] 4 [/SUP], Marta Rusmini[SUP] 2 [/SUP], Giada Recchi[SUP] 5 [/SUP], Martina Bonacini[SUP] 3 [/SUP], Ilaria Ferrigno[SUP] 3 [/SUP], Alessandro Rossi[SUP] 3 [/SUP], Yeraldin Chiquinquira Castillo De Spelorzi[SUP] 6 [/SUP], Edoardo Henzen[SUP] 6 [/SUP], Francesca Rosamilia[SUP] 2 [/SUP], Davide Cangelosi[SUP] 2 [/SUP], Fabio Landuzzi[SUP] 7 [/SUP], Andrea Angius[SUP] 8 [/SUP], Vincenzo Rallo[SUP] 8 [/SUP], Pamela Mancuso[SUP] 9 [/SUP], Annamaria Pezzarossi[SUP] 9 [/SUP], Paolo Giorgi Rossi[SUP] 9 [/SUP], Mariagrazia Catanoso[SUP] 10 [/SUP], Marco Gattorno[SUP] 5 [/SUP], Andrea Cavalli[SUP] 11 12 [/SUP], Pier Luigi Meroni[SUP] 13 [/SUP], Diego Vozzi[SUP] 6 [/SUP], Paolo Uva[SUP] 2 [/SUP], Isabella Ceccherini[SUP] 14 [/SUP], Carlo Salvarani[SUP] 10 15 [/SUP]
Affiliations
- PMID: 42192286
- DOI: 10.1186/s10020-026-01512-6
Background: The coronavirus disease 2019 (COVID-19) ranges from asymptomatic to very severe infection and death, largely depending on host factors, including genetics. We have investigated clinical and genetic data from 200 COVID-19 patients to search for factors predisposing to increased disease severity.
Methods: Patients were divided into non-hospitalized mild/pauci-symptomatic and hospitalized severe. An interpretable Machine Learning approach was applied to blood biomarkers while genome-wide associations were performed for COVID-19 severity. Finally, a possible causal role of chronic low-grade inflammation on COVID-19 severity was searched by Mendelian Randomization.
Results: A high severity predictive role was observed in our sample by Machine Learning for the C-Reactive Protein measured in the course of SARS-CoV-2 infection (iCRP). This was also suggested by evidence of association with variants known to be involved in the CRP levels in the general population (pCRP). Finally, a possible causal role of chronic low-grade inflammation on COVID-19 severity could be shown by Mendelian Randomization using publicly available summary statistics of two COVID-19 Genome-Wide Association Studies.
Conclusions: Consistent with previous results, a predictive role of CRP levels on COVID-19 severity was detected in our sample. Furthermore, Mendelian Randomization supported a causal role of genetically predicted chronic CRP levels.
Keywords: C-Reactive Protein; COVID-19 severity prediction; CRP causal role; Interpretable Machine Learning; Mendelian Randomization; TFEB.