Multiomic profiling of iron-deficient infant monkeys reveals alterations in neurologically important biochemicals in serum and cerebrospinal fluid before the onset of anemia

Phototherapy Alters the Plasma Metabolite Profile in Infants Born Preterm with Hyperbilirubinemia

OBJECTIVE

To investigate the effects of gestational age (GA) and phototherapy on the plasma metabolite profile of preterm infants with neonatal hyperbilirubinemia (NHB).

STUDY DESIGN

From a cohort of prospectively enrolled infants born preterm (n = 92), plasma samples of very preterm (VPT; GA, 28 + 0 to 31 + 6 weeks, n = 27) and moderate/late preterm (M/LPT; GA, 32 + 0 to 35 + 6 weeks, n = 33) infants requiring phototherapy for NHB were collected prior to the initiation of phototherapy and 24 hours after starting phototherapy. An additional sample was collected 48 hours after starting phototherapy in a randomly selected subset (n = 30; VPT n = 15; M/LPT n = 15). Metabolite profiles were determined using ultraperformance liquid chromatography tandem mass spectroscopy. Two-way ANCOVA was used to identify metabolites that differed between GA groups and timepoints after adjusting for total serum bilirubin levels (false discovery rate q-value < 0.05). Top impacted pathways were identified using pathway over-representation analysis.

RESULTS

Phototherapy was initiated at lower total serum bilirubin (mean ± SD mg/dL) levels in VPT compared with M/LPT infants (7.3 ± 1.4 vs 9.9 ± 1.9, P < .01). We identified 664 metabolites that were significant for a phototherapy effect, 191 metabolites significant for GA, and 46 metabolites significant for GA × phototherapy interaction (false discovery rate q-value < 0.05). Longer duration phototherapy had a larger mean effect size (24 hours postphototherapy: d = 0.36; 48 hours postphototherapy: d = 0.43). Top pathways affected by phototherapy included membrane lipid metabolism, one-carbon metabolism, creatine biosynthesis, and oligodendrocyte differentiation.

CONCLUSION

Phototherapy alters the plasma metabolite profile more than GA in preterm infants with NHB, affecting pathways related to lipid and one-carbon metabolism, energy biosynthesis, and oligodendrocyte differentiation.

Biomarkers of Brain Dysfunction in Perinatal Iron Deficiency

Iron deficiency in the fetal and neonatal period (perinatal iron deficiency) bodes poorly for neurodevelopment. Given its common occurrence and the negative impact on brain development, a screening and treatment strategy that is focused on optimizing brain development in perinatal iron deficiency is necessary. Pediatric societies currently recommend a universal iron supplementation strategy for full-term and preterm infants that does not consider individual variation in body iron status and thus could lead to undertreatment or overtreatment. Moreover, the focus is on hematological normalcy and not optimal brain development. Several serum iron indices and hematological parameters in the perinatal period are associated with a risk of abnormal neurodevelopment, suggesting their potential use as biomarkers for screening and monitoring treatment in infants at risk for perinatal iron deficiency. A biomarker-based screening and treatment strategy that is focused on optimizing brain development will likely improve outcomes in perinatal iron deficiency.

Prognostic Performance of Hematological and Serum Iron and Metabolite Indices for Detection of Early Iron Deficiency Induced Metabolic Brain Dysfunction in Infant Rhesus Monkeys

BACKGROUND

The current pediatric practice of monitoring for infantile iron deficiency (ID) via hemoglobin (Hgb) screening at one y of age does not identify preanemic ID nor protect against later neurocognitive deficits.

OBJECTIVES

To identify biomarkers of iron-related metabolic alterations in the serum and brain and determine the sensitivity of conventional iron and heme indices for predicting risk of brain metabolic dysfunction using a nonhuman primate model of infantile ID.

METHODS

Simultaneous serum iron and RBC indices, and serum and cerebrospinal fluid (CSF) metabolomic profiles were determined in 20 rhesus infants, comparing iron sufficient (IS; N = 10) and ID (N = 10) infants at 2 and 4 mo of age.

RESULTS

Reticulocyte hemoglobin (RET-He) was lower at 2 wk in the ID group. Significant IS compared with ID differences in serum iron indices were present at 2 mo, but Hgb and RBC indices differed only at 4 mo (P < 0.05). Serum and CSF metabolomic profiles of the ID and IS groups differed at 2 and 4 mo (P < 0.05). Key metabolites, including homostachydrine and stachydrine (4-5-fold lower at 4 mo in ID group, P < 0.05), were altered in both serum and CSF. Iron indices and RET-He at 2 mo, but not Hgb or other RBC indices, were correlated with altered CSF metabolic profile at 4 mo and had comparable predictive accuracy (area under the receiver operating characteristic curve scores, 0.75-0.80).

CONCLUSIONS

Preanemic ID at 2 mo was associated with metabolic alterations in serum and CSF in infant monkeys. Among the RBC indices, only RET-He predicted the future risk of abnormal CSF metabolic profile with a predictive accuracy comparable to serum iron indices. The concordance of homostachydrine and stachydrine changes in serum and CSF indicates their potential use as early biomarkers of brain metabolic dysfunction in infantile ID.

Anemia, Iron Supplementation, and the Brain

The developing brain is particularly vulnerable to extrinsic environmental events such as anemia and iron deficiency during periods of rapid development. Studies of infants with postnatal iron deficiency and iron deficiency anemia clearly demonstrated negative effects on short-term and long-term brain development and function. Randomized interventional trials studied erythropoiesis-stimulating agents and hemoglobin-based red blood cell transfusion thresholds to determine how they affect preterm infant neurodevelopment. Studies of red blood cell transfusion components are limited in preterm neonates. A biomarker strategy measuring brain iron status and health in the preanemic period is desirable to evaluate treatment options and brain response.

Bayesian predictive modeling of multi-source multi-way data

A Bayesian approach to predict a continuous or binary outcome from data that are collected from multiple sources with a multi-way (i.e., multidimensional tensor) structure is described. As a motivating example, molecular data from multiple 'omics sources, each measured over multiple developmental time points, as predictors of early-life iron deficiency (ID) in a rhesus monkey model are considered. The method uses a linear model with a low-rank structure on the coefficients to capture multi-way dependence and model the variance of the coefficients separately across each source to infer their relative contributions. Conjugate priors facilitate an efficient Gibbs sampling algorithm for posterior inference, assuming a continuous outcome with normal errors or a binary outcome with a probit link. Simulations demonstrate that the model performs as expected in terms of misclassification rates and correlation of estimated coefficients with true coefficients, with large gains in performance by incorporating multi-way structure and modest gains when accounting for differing signal sizes across the different sources. Moreover, it provides robust classification of ID monkeys for the motivating application.

Intranasal insulin treatment partially corrects the altered gene expression profile in the hippocampus of developing rats with perinatal iron deficiency

Perinatal iron deficiency (FeD) targets the hippocampus and leads to long-term cognitive deficits. Intranasal insulin administration improves cognitive deficits in adult humans with Alzheimer's disease and type 2 diabetes and could provide benefits in FeD-induced hippocampal dysfunction. To objective was to assess the effects of intranasal insulin administration intranasal insulin administration on the hippocampal transcriptome in a developing rat model of perinatal FeD. Perinatal FeD was induced using low-iron diet from gestational day 3 until postnatal day (P) 7, followed by an iron sufficient (FeS) diet through P21. Intranasal insulin was administered at a dose of 0.3 IU twice daily from P8 to P21. Hippocampi were removed on P21 from FeS control, FeD control, FeS insulin, and FeD insulin groups. Total RNA was isolated and profiled using next-generation sequencing. Gene expression profiles were characterized using custom workflows and expression patterns examined using ingenuity pathways analysis (n = 7-9 per group). Select RNAseq results were confirmed via qPCR. Transcriptomic profiling revealed that mitochondrial biogenesis and flux, oxidative phosphorylation, quantity of neurons, CREB signaling in neurons, and RICTOR-based mTOR signaling were disrupted with FeD and positively affected by intranasal insulin treatment with the most benefit observed in the FeD insulin group. Both perinatal FeD and intranasal insulin administration altered gene expression profile in the developing hippocampus. Intranasal insulin treatment reversed the adverse effects of FeD on many molecular pathways and could be explored as an adjunct therapy in perinatal FeD.

Antibiotics augment the impact of iron deficiency on metabolism in a piglet model

Infancy and childhood represent a high-risk period for developing iron deficiency (ID) and is a period of increased susceptibility to infectious disease. Antibiotic use is high in children from low-, middle-, and high-income countries, and thus we sought to determine the impact of antibiotics in the context of ID. In this study, a piglet model was used to assess the impact of ID and antibiotics on systemic metabolism. ID was induced by withholding a ferrous sulfate injection after birth to piglets in the ID group and providing an iron deficient diet upon weaning on postnatal day (PD) 25. Antibiotics (gentamicin and spectinomycin) were administered on PD34-36 to a set of control (Con*+Abx) and ID piglets (ID+Abx) after weaning. Blood was analyzed on PD30 (before antibiotic administration) and PD43 (7 days after antibiotic administration). All ID piglets exhibited growth faltering and had lower hemoglobin and hematocrit compared to control (Con) and Con*+Abx throughout. The metabolome of ID piglets at weaning and sacrifice exhibited elevated markers of oxidative stress, ketosis, and ureagenesis compared to Con. The impact of antibiotics on Con*+Abx piglets did not result in significant changes to the serum metabolome 7-days after treatment; however, the impact of antibiotics on ID+Abx piglets resulted in the same metabolic changes observed in ID piglets, but with a greater magnitude when compared to Con. These results suggest that antibiotic administration in the context of ID exacerbates the negative metabolic impacts of ID and may have long lasting impacts on development.

Prediction of Proteins in Cerebrospinal Fluid and Application to Glioma Biomarker Identification

Cerebrospinal fluid (CSF) proteins are very important because they can serve as biomarkers for central nervous system diseases. Although many CSF proteins have been identified with wet experiments, the identification of CSF proteins is still a challenge. In this paper, we propose a novel method to predict proteins in CSF based on protein features. A two-stage feature-selection method is employed to remove irrelevant features and redundant features. The deep neural network and bagging method are used to construct the model for the prediction of CSF proteins. The experiment results on the independent testing dataset demonstrate that our method performs better than other methods in the prediction of CSF proteins. Furthermore, our method is also applied to the identification of glioma biomarkers. A differentially expressed gene analysis is performed on the glioma data. After combining the analysis results with the prediction results of our model, the biomarkers of glioma are identified successfully.

Reticulocyte Hemoglobin Equivalent has Comparable Predictive Accuracy as Conventional Serum Iron Indices for Predicting Iron Deficiency and Anemia in a Nonhuman Primate model of Infantile Iron Deficiency

BACKGROUND

Infantile iron deficiency (ID) causes anemia and compromises neurodevelopment. Current screening relies on hemoglobin (Hgb) determination at 1 year of age, which lacks sensitivity and specificity for timely detection of infantile ID. Low reticulocyte Hgb equivalent (RET-He) indicates ID, but its predictive accuracy relative to conventional serum iron indices is unknown.

OBJECTIVES

The objective was to compare diagnostic accuracies of iron indices, red blood cell (RBC) indices, and RET-He for predicting the risk of ID and IDA in a nonhuman primate model of infantile ID.

METHODS

Serum iron, total iron binding capacity, unsaturated iron binding capacity, transferrin saturation (TSAT), Hgb, RET-He, and other RBC indices were determined at 2 wk and 2, 4, and 6 mo in breastfed male and female rhesus infants (N = 54). The diagnostic accuracies of RET-He, iron, and RBC indices for predicting the development of ID (TSAT < 20%) and IDA (Hgb < 10 g/dL + TSAT < 20%) were determined using t tests, area under the receiver operating characteristic curve (AUC) analysis, and multiple regression models.

RESULTS

Twenty-three (42.6%) infants developed ID and 16 (29.6%) progressed to IDA. All 4 iron indices and RET-He, but not Hgb or RBC indices, predicted future risk of ID and IDA (P < 0.001). The predictive accuracy of RET-He (AUC = 0.78, SE = 0.07; P = 0.003) for IDA was comparable to that of the iron indices (AUC = 0.77-0.83, SE = 0.07; P ≤ 0.002). A RET-He threshold of 25.5 pg strongly correlated with TSAT < 20% and correctly predicted IDA in 10 of 16 infants (sensitivity: 62.5%) and falsely predicted possibility of IDA in only 4 of 38 unaffected infants (specificity: 89.5%).

CONCLUSIONS

RET-He is a biomarker of impending ID/IDA in rhesus infants and can be used as a hematological parameter to screen for infantile ID.

Modifiable contributing factors to COVID-19: A comprehensive review

The devastating complications of coronavirus disease 2019 (COVID-19) result from an individual's dysfunctional immune response following the initial severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Multiple toxic stressors and behaviors contribute to underlying immune system dysfunction. SARS-CoV-2 exploits the dysfunctional immune system to trigger a chain of events ultimately leading to COVID-19. The current study identifies eighty immune system dysfunction-enabling toxic stressors and behaviors (hereafter called modifiable contributing factors (CFs)) that also link directly to COVID-19. Each CF is assigned to one of the five categories in the CF taxonomy shown in Section 3.3.: Lifestyle (e.g., diet, substance abuse); Iatrogenic (e.g., drugs, surgery); Biotoxins (e.g., micro-organisms, mycotoxins); Occupational/Environmental (e.g., heavy metals, pesticides); Psychosocial/Socioeconomic (e.g., chronic stress, lower education). The current study shows how each modifiable factor contributes to decreased immune system capability, increased inflammation and coagulation, and increased neural damage and neurodegeneration. It is unclear how real progress can be made in combatting COVID-19 and other similar diseases caused by viral variants without addressing and eliminating these modifiable CFs.

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

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).

Early life nutrition and brain development: breakthroughs, challenges and new horizons

The role of early life nutrition's impact on relevant health outcomes across the lifespan laid the foundation for the field titled the developmental origins of health and disease. Studies in this area initially concentrated on nutrition and the risk of adverse cardio-metabolic and cancer outcomes. More recently the role of nutrition in early brain development and the subsequent influence of later mental health has become more evident. Scientific breakthroughs have elucidated two mechanisms behind long-term nutrient effects on the brain, including the existence of critical periods for certain nutrients during brain development and nutrient-driven epigenetic modifications of chromatin. While multiple nutrients and nutritional conditions have the potential to modify brain development, iron can serve as a paradigm to understand both mechanisms. New horizons in nutritional medicine include leveraging the mechanistic knowledge of nutrient-brain interactions to propose novel nutritional approaches that protect the developing brain through better timing of nutrient delivery and potential reversal of negative epigenetic marks. The main challenge in the field is detecting whether a change in nutritional status truly affects the brain's development and performance in human subjects. To that end, a strong case can be made to develop and utilise bioindicators of a nutrient's effect on the developing brain instead of relying exclusively on biomarkers of the nutrient's status.