TY - JOUR
T1 - The proteomic fingerprint in infants with single ventricle heart disease in the interstage period
T2 - evidence of chronic inflammation and widespread activation of biological networks
AU - Thomson, Lindsay M.
AU - Mancuso, Christopher A.
AU - Wolfe, Kelly R.
AU - Khailova, Ludmila
AU - Niemiec, Sierra
AU - Ali, Eiman
AU - DiMaria, Michael
AU - Mitchell, Max
AU - Twite, Mark
AU - Morgan, Gareth
AU - Frank, Benjamin S.
AU - Davidson, Jesse A.
N1 - Publisher Copyright:
2023 Thomson, Mancuso, Wolfe, Khailova, Niemiec, Ali, DiMaria, Mitchell, Twite, Morgan, Frank and Davidson.
PY - 2023/2/8
Y1 - 2023/2/8
N2 - Introduction: Children with single ventricle heart disease (SVHD) experience significant morbidity across systems and time, with 70% of patients experiencing acute kidney injury, 33% neurodevelopmental impairment, 14% growth failure, and 5.5% of patients suffering necrotizing enterocolitis. Proteomics is a method to identify new biomarkers and mechanisms of injury in complex physiologic states. Methods: Infants with SVHD in the interstage period were compared to similar-age healthy controls. Serum samples were collected, stored at −80°C, and run on a panel of 1,500 proteins in single batch analysis (Somalogic Inc., CO). Partial Least Squares-Discriminant Analysis (PLS-DA) was used to compare the proteomic profile of cases and controls and t-tests to detect differences in individual proteins (FDR <0.05). Protein network analysis with functional enrichment was performed in STRING and Cytoscape. Results: PLS-DA readily discriminated between SVHD cases (n = 33) and controls (n = 24) based on their proteomic pattern alone (Accuracy = 0.96, R2= 0.97, Q2= 0.80). 568 proteins differed between groups (FDR <0.05). We identified 25 up-regulated functional clusters and 13 down-regulated. Active biological systems fell into six key groups: angiogenesis and cell proliferation/turnover, immune system activation and inflammation, altered metabolism, neural development, gastrointestinal system, and cardiac physiology and development. Conclusions: We report a clear differentiation in the circulating proteome of patients with SVHD and healthy controls with >500 circulating proteins distinguishing the groups. These proteomic data identify widespread protein dysregulation across multiple biologic systems with promising biological plausibility as drivers of SVHD morbidity.
AB - Introduction: Children with single ventricle heart disease (SVHD) experience significant morbidity across systems and time, with 70% of patients experiencing acute kidney injury, 33% neurodevelopmental impairment, 14% growth failure, and 5.5% of patients suffering necrotizing enterocolitis. Proteomics is a method to identify new biomarkers and mechanisms of injury in complex physiologic states. Methods: Infants with SVHD in the interstage period were compared to similar-age healthy controls. Serum samples were collected, stored at −80°C, and run on a panel of 1,500 proteins in single batch analysis (Somalogic Inc., CO). Partial Least Squares-Discriminant Analysis (PLS-DA) was used to compare the proteomic profile of cases and controls and t-tests to detect differences in individual proteins (FDR <0.05). Protein network analysis with functional enrichment was performed in STRING and Cytoscape. Results: PLS-DA readily discriminated between SVHD cases (n = 33) and controls (n = 24) based on their proteomic pattern alone (Accuracy = 0.96, R2= 0.97, Q2= 0.80). 568 proteins differed between groups (FDR <0.05). We identified 25 up-regulated functional clusters and 13 down-regulated. Active biological systems fell into six key groups: angiogenesis and cell proliferation/turnover, immune system activation and inflammation, altered metabolism, neural development, gastrointestinal system, and cardiac physiology and development. Conclusions: We report a clear differentiation in the circulating proteome of patients with SVHD and healthy controls with >500 circulating proteins distinguishing the groups. These proteomic data identify widespread protein dysregulation across multiple biologic systems with promising biological plausibility as drivers of SVHD morbidity.
KW - biomarkers
KW - congenital heart defect
KW - congenital heart disease
KW - Glenn
KW - hypoplastic left heart syndrome
KW - inflammation
KW - protein dysregulation
KW - single ventricle palliation
UR - https://www.scopus.com/pages/publications/85180658572
U2 - 10.3389/fped.2023.1308700
DO - 10.3389/fped.2023.1308700
M3 - Article
AN - SCOPUS:85180658572
SN - 2296-2360
VL - 11
JO - Frontiers in Pediatrics
JF - Frontiers in Pediatrics
M1 - 1308700
ER -