Dataset Information

Extracellular Glutathione Peroxidase 3 GPx3 Levels are Markedly Reduced in Children Affected with Konzo an Irreversible Spastic Paralysis Associated with Food Poisoning

ABSTRACT: Konzo, a neglected paralytic neurological disease associated with food (cassava) poisoning, affects the world poorest children and women of childbearing ages across regions of sub Saharan Africa, with the Democratic Republic of the Congo having the largest case burden. The primary risk factors for development include a dietary reliance on cyanogenic rich cassava and malnutrition, factors which are exacerbated by environmental stressors such as drought and famine. Despite understanding the dietary risks that lead to konzo, the molecular markers and mechanisms that trigger this disease remain unknown. Plasma, collected from two large independent cohorts 10 years apart, were subjected to multiple high throughput mass spectrometry in search of disease biomarkers and proteins that were differentially expressed in children affected with konzo relative to those unaffected, including their siblings. DDA experiment was performed on the first cohort with a validation by SRM analysis. For the second cohort, DIA experiment was performed with a validation by PRM.

INSTRUMENT(S): TSQ Altis, Orbitrap Fusion, Orbitrap Exploris 480

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Arnaud Droit

PROVIDER: MSV000094134 | MassIVE | Tue Feb 20 12:11:00 GMT 2024

SECONDARY ACCESSION(S): PXD049973

REPOSITORIES: MassIVE

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Background: Septic shock heterogeneity has important implications for the conduct of clinical trials and individual patient management. We previously addressed this heterogeneity by indentifying 3 putative subclasses of children with septic shock based on a 100-gene expression signature corresponding to adaptive immunity and glucocorticoid receptor signaling. Herein we attempted to prospectively validate the existence of these gene expression-based subclasses in a validation cohort. Methods: Gene expression mosaics were generated from the 100 class-defining genes for 82 individual patients in the validation cohort. Patients were classified into 1 of 3 subclasses (“A”, “B”, or “C”) based on color and pattern similarity relative to reference mosaics generated from the original derivation cohort. Separate classifications were conducted by 21 individual clinicians and a computer-based algorithm. After subclassification the clinical database was mined for clinical phenotyping. Results: In the final consensus subclassification generated by clinicians, subclass A patients had a higher illness severity, as measured by illness severity scores and maximal organ failure, relative to subclasses B and C. The k coefficient across all possible inter-evaluator comparisons was 0.633. Similar observations were made based on the computer-generated subclassification. Patients in subclass A were also characterized by repression of a large number of genes having functional annotations related to zinc biology. Conclusions: We have validated the existence of subclasses of children with septic shock based on a biologically relevant, 100-gene expression signature. The subclasses can be indentified by clinicians without formal bioinformatics training, at a clinically relevant time point, and have clinically relevant phenotypic differences. Expression data from 82 children with septic shock and 21 normal controls were generated using whole blood-derived RNA samples representing the first 24 hours of admission to the pediatric intensive care unit. The controls were used for normalization. Subsequently, we used the expression data from 100 class defining genes to validate the existence of pediatric septic shock subclasses having phenotypic differences.

Dataset Information

Extracellular Glutathione Peroxidase 3 GPx3 Levels are Markedly Reduced in Children Affected with Konzo an Irreversible Spastic Paralysis Associated with Food Poisoning

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets