Lisa Ruvuna
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Lisa Ruvuna has a total of 9 co-authors. Here are the top co-authors by number of shared publications:
Aabida Saferali
Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA
1 shared publication- Craig P. Hersh
Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA.
1 shared publication - Enrico Schiavi
Department of Public Health and Infectious Diseases, Sapienza University of Rome, AOU Policlinico Umberto I, 00185 Rome, Italy
1 shared publication - Jeffrey L. Curtis
University of Michigan
1 shared publication - Jeong Hyun Yun
Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, USA
1 shared publication Kaman So
Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA
1 shared publication
Latest Publications
- Open Access
- 18 March 2026
- Published by Springer Nature in Respiratory Research
- Vol. 27 (1)
Blood cell ratio biomarkers of systemic inflammation in chronic obstructive pulmonary disease
Background: Blood eosinophil count is an accepted biomarker for type 2 inflammation in COPD. However, the majority of COPD patients are characterized by non-type 2 inflammation. We aimed to test readily obtainable immune cell ratios as biomarkers for clinical phenotypes in the broad COPD population and to determine pathways represented by these ratios using multi-omics data. Methods: Using complete blood counts with differential collected at the Phase 2 (5-year) visit in the COPDGene Study, we calculated three immune cell ratios previously described in COPD and other diseases: the neutrophil–lymphocyte ratio (NLR), the platelet-lymphocyte ratio (PLR), and the Systemic Immune-Inflammation Index (SII = NLR*platelets). We tested for associations with COPD outcomes, including lung function, chest CT scan phenotypes, and exacerbations. Blood RNA-sequencing and proteomics data were used to identify genes, proteins and pathways associated with the ratios. Results: In univariate analyses, the three biomarkers were associated with COPD severity measures. In zero inflated Poisson regression models, all three were associated with increased odds of having an exacerbation but were not associated with exacerbation counts. Conversely, the three biomarkers were generally associated with prospective exacerbation counts, but not the zero-inflation term. In logistic regression models, the three biomarkers were significantly associated with having two or more exacerbations in the prior year; however, receiver operating characteristic analyses did not lead to clear cutoff values. Complement and PI3K signaling pathways were enriched across more than one ratio in both the RNA-sequencing and proteomics results. Other inflammatory pathways relevant in COPD appeared in different enrichment sets in either omics data type. Conclusions: Higher levels of three easily obtained blood cell ratios were associated with COPD severity and exacerbations outcomes; however, there are not clear thresholds which would be required for clinical application. Blood RNA-sequencing and proteomics identified inflammatory pathways associated with the three biomarkers, including targets for COPD therapies currently in human trials.
- 18 March 2026
- Published by Springer Nature in Respiratory Research
- Vol. 27 (1)
Open AccessBlood cell ratio biomarkers of systemic inflammation in chronic obstructive pulmonary disease
Background: Blood eosinophil count is an accepted biomarker for type 2 inflammation in COPD. However, the majority of COPD patients are characterized by non-type 2 inflammation. We aimed to test readily obtainable immune cell ratios as biomarkers for clinical phenotypes in the broad COPD population and to determine pathways represented by these ratios using multi-omics data. Methods: Using complete blood counts with differential collected at the Phase 2 (5-year) visit in the COPDGene Study, we calculated three immune cell ratios previously described in COPD and other diseases: the neutrophil–lymphocyte ratio (NLR), the platelet-lymphocyte ratio (PLR), and the Systemic Immune-Inflammation Index (SII = NLR*platelets). We tested for associations with COPD outcomes, including lung function, chest CT scan phenotypes, and exacerbations. Blood RNA-sequencing and proteomics data were used to identify genes, proteins and pathways associated with the ratios. Results: In univariate analyses, the three biomarkers were associated with COPD severity measures. In zero inflated Poisson regression models, all three were associated with increased odds of having an exacerbation but were not associated with exacerbation counts. Conversely, the three biomarkers were generally associated with prospective exacerbation counts, but not the zero-inflation term. In logistic regression models, the three biomarkers were significantly associated with having two or more exacerbations in the prior year; however, receiver operating characteristic analyses did not lead to clear cutoff values. Complement and PI3K signaling pathways were enriched across more than one ratio in both the RNA-sequencing and proteomics results. Other inflammatory pathways relevant in COPD appeared in different enrichment sets in either omics data type. Conclusions: Higher levels of three easily obtained blood cell ratios were associated with COPD severity and exacerbations outcomes; however, there are not clear thresholds which would be required for clinical application. Blood RNA-sequencing and proteomics identified inflammatory pathways associated with the three biomarkers, including targets for COPD therapies currently in human trials.