Tandem mass tag proteomic and untargeted metabolomic profiling reveals altered serum and CSF biochemical datasets in iron deficient monkeys

Abstract

The effects of early-life iron deficiency anemia (IDA) extend past the blood and include both short- and long-term adverse effects on many tissues including the brain. Prior to IDA, iron deficiency (ID) can cause similar tissue effects, but a sensitive biomarker of iron-dependent brain health is lacking. To determine serum and CSF biomarkers of ID-induced metabolic dysfunction we performed proteomic and metabolomic analysis of serum and CSF at 4- and 6- months from a nonhuman primate model of infantile IDA. LC/MS/MS analyses identified a total of 227 metabolites and 205 proteins in serum. In CSF, we measured 210 metabolites and 1,560 proteins. Data were either processed from a Q-Exactive (Thermo Scientific, Waltham, MA) through Progenesis QI with accurate mass and retention time comparisons to a proprietary small molecule database and Metlin or with raw files imported directly from a Fusion Orbitrap (Thermo Scientific, Waltham, MA) through Sequest in Proteome Discoverer 2.4.0.305 (Thermo Scientific, Waltham, MA) with peptide matches through the latest Rhesus Macaque HMDB database. Metabolite and protein identifiers, p-values, and q-values were utilized for molecular pathway analysis with Ingenuity Pathways Analysis (IPA). We applied multiway distance weighted discrimination (DWD) to identify a weighted sum of the features (proteins or metabolites) that distinguish ID from IS at 4-months (pre-anemic period) and 6-months of age (anemic).

Keywords

• Rhesus Macaque
• Multiomics
• Synaptogenesis