Differential Network Analysis Reveals Molecular Determinants Associated with Blood Pressure and Heart Rate in Healthy Subjects

Vignoli, Alessia; Tenori, Leonardo; Luchinat, Claudio; Saccenti, Edoardo

doi:10.1021/acs.jproteome.0c00882

Cited by 2 publications

(2 citation statements)

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“…Random Forest ( 42 ) classification models were built using the R package “randomForest” ( 43 ) as described before ( 44 ). Six different models were built to discriminate between the different mother-child allergy groups, covering all pairwise comparisons of allergic/non-allergic mothers with allergic/non-allergic children.…”

Section: Methodsmentioning

confidence: 99%

The human milk proteome and allergy of mother and child: Exploring associations with protein abundances and protein network connectivity

Dekker

Azad²,

Boeren³

et al. 2022

Front. Immunol.

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BackgroundThe human milk proteome comprises a vast number of proteins with immunomodulatory functions, but it is not clear how this relates to allergy of the mother or allergy development in the breastfed infant. This study aimed to explore the relation between the human milk proteome and allergy of both mother and child.MethodsProteins were analyzed in milk samples from a subset of 300 mother-child dyads from the Canadian CHILD Cohort Study, selected based on maternal and child allergy phenotypes. For this selection, the definition of “allergy” included food allergy, eczema, allergic rhinitis, and asthma. Proteins were analyzed with non-targeted shotgun proteomics using filter-aided sample preparation (FASP) and nanoLC-Orbitrap-MS/MS. Protein abundances, based on label-free quantification, were compared using multiple statistical approaches, including univariate, multivariate, and network analyses.ResultsUsing univariate analysis, we observed a trend that milk for infants who develop an allergy by 3 years of age contains higher abundances of immunoglobulin chains, irrespective of the allergy status of the mother. This observation suggests a difference in the milk’s immunological potential, which might be related to the development of the infant’s immune system. Furthermore, network analysis showed overall increased connectivity of proteins in the milk of allergic mothers and milk for infants who ultimately develop an allergy. This difference in connectivity was especially noted for proteins involved in the protein translation machinery and may be due to the physiological status of the mother, which is reflected in the interconnectedness of proteins in her milk. In addition, it was shown that network analysis complements the other methods for data analysis by revealing complex associations between the milk proteome and mother-child allergy status.ConclusionTogether, these findings give new insights into how the human milk proteome, through differences in the abundance of individual proteins and protein-protein associations, relates to the allergy status of mother and child. In addition, these results inspire new research directions into the complex interplay of the mother-milk-infant triad and allergy.

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Section: Methodsmentioning

confidence: 99%

The human milk proteome and allergy of mother and child: Exploring associations with protein abundances and protein network connectivity

Dekker

Azad²,

Boeren³

et al. 2022

Front. Immunol.

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“…To expand the vision from the particular to the general, it is necessary to perform a further step considering the shape of the metabolite-metabolite association networks [ 16 ]. Changes in metabolite association patterns are associated with changes in the pathophysiological conditions, and the resulting networks can be compared across conditions under the postulate that the differences and commonalities observed in the reconstructed networks faithfully mirror the reshape of the underlying biological networks [ 17 , 18 , 19 , 20 ].…”

Section: Introductionmentioning

confidence: 99%

Exploration of Blood Metabolite Signatures of Colorectal Cancer and Polyposis through Integrated Statistical and Network Analysis

et al. 2023

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Colorectal cancer (CRC), one of the most prevalent and deadly cancers worldwide, generally evolves from adenomatous polyps. The understanding of the molecular mechanisms underlying this pathological evolution is crucial for diagnostic and prognostic purposes. Integrative systems biology approaches offer an optimal point of view to analyze CRC and patients with polyposis. The present study analyzed the association networks constructed from a publicly available array of 113 serum metabolites measured on a cohort of 234 subjects from three groups (66 CRC patients, 76 patients with polyposis, and 92 healthy controls), which concentrations were obtained via targeted liquid chromatography-tandem mass spectrometry. In terms of architecture, topology, and connectivity, the metabolite-metabolite association network of CRC patients appears to be completely different with respect to patients with polyposis and healthy controls. The most relevant nodes in the CRC network are those related to energy metabolism. Interestingly, phenylalanine, tyrosine, and tryptophan metabolism are found to be involved in both CRC and polyposis. Our results demonstrate that the characterization of metabolite–metabolite association networks is a promising and powerful tool to investigate molecular aspects of CRC.

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Differential Network Analysis Reveals Molecular Determinants Associated with Blood Pressure and Heart Rate in Healthy Subjects

Cited by 2 publications

References 80 publications

The human milk proteome and allergy of mother and child: Exploring associations with protein abundances and protein network connectivity

The human milk proteome and allergy of mother and child: Exploring associations with protein abundances and protein network connectivity

Exploration of Blood Metabolite Signatures of Colorectal Cancer and Polyposis through Integrated Statistical and Network Analysis

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