Associations of Maternal Breastmilk microRNAs and Infant Obesity Status at 1 Year.

Infant consumption of human milk (HM) is associated with a reduced risk of overweight and obesity, but the reasons for this relationship are not completely understood. There is emerging evidence that micro RNAs (miRNAs) regulate infant development and metabolism, but the associations between HM miRNAs and infant growth remain poorly understood. We examined the relationship between HM miRNA consumption and infant obesity in 163 mother-infant dyads to determine (1) if miRNA profiles differentiate infants with obesity, and (2) if individual miRNAs accurately predicted infant obesity status at one year of age. Infant obesity was categorized as weight-for-length (WFL) Z scores or conditional weight gain (CWG) in the 95th percentile. HM miRNA profile was associated with infant age (r2 = 6.4%, p = 0.001), but not maternal obesity status (r2 = 1.5%, p = 0.87) or infant weight status (WFL Z-score) at birth (r2 = 0.6%, p = 0.4), 1 month (r2 = 0.5%, p = 0.6), or 4 months (r2 = 0.8%, p = 0.2). Nine HM miRNAs were associated with either 12-month CWG or 12-month WFL Z scores. Among these 9 miRNAs, miR-224-5p remained significant in a logistic regression model that accounted for additional demographic factors (estimate = -27.57, p = 0.004). These findings suggest involvement of HM miRNAs and particularly miR-224-5p in infant growth, warranting further investigation. To our knowledge, this is the largest study of HM miRNAs and early-life obesity and contributes to the understanding of the relationship between HM miRNAs and infant growth.

Milk levels of transforming growth factor beta 1 identify mothers with low milk supply.

Human milk is optimal for infant nutrition. However, many mothers cease breastfeeding because of low milk supply (LMS). It is difficult to identify mothers at risk for LMS because its biologic underpinnings are not fully understood. Previously, we demonstrated that milk micro-ribonucleic acids (miRNAs) may be related to LMS. Transforming growth factor beta (TGFß) also plays an important role in mammary involution and may contribute to LMS. We performed a longitudinal cohort study of 139 breastfeeding mothers to test the hypothesis that milk levels of TGFß would identify mothers with LMS. We explored whether TGFß impacts the expression of LMS-related miRNAs in cultured human mammary epithelial cells (HMECs). LMS was defined by maternal report of inadequate milk production, and confirmed by age of formula introduction and infant weight trajectory. Levels of TGF-ß1 and TGF-ß2 were measured one month after delivery. There was a significant relationship between levels of TGF-ß1 and LMS (X2 = 8.92, p = 0.003) on logistic regression analysis, while controlling for lactation stage (X2 = 1.28, p = 0.25), maternal pre-pregnancy body mass index (X2 = 0.038, p = 0.84), and previous breastfeeding experience (X2 = 7.43, p = 0.006). The model accounted for 16.8% of variance in the data (p = 0.005) and correctly predicted LMS for 84.6% of mothers (22/26; AUC = 0.72). Interactions between TGF-ß1 and miR-22-3p displayed significant effect on LMS status (Z = 2.67, p = 0.008). Further, incubation of HMECs with TGF-ß1 significantly reduced mammary cell number (t = -4.23, p = 0.003) and increased levels of miR-22-3p (t = 3.861, p = 0.008). Interactions between TGF-ß1 and miR-22-3p may impact mammary function and milk levels of TGF-ß1 could have clinical utility for identifying mothers with LMS. Such information could be used to provide early, targeted lactation support.

Evaluating the Effect of Maternal Opioid Maintenance Dose on the NOWS-COS Outcome Criteria: A Pilot Study.

This retrospective cohort study included 77 mother-infant dyads that delivered term pregnancies at a single tertiary care institution. The primary objective was to investigate whether maternal dose of opioid maintenance therapy during pregnancy affects infant outcomes. All infants had prenatal exposure to opioid maintenance therapies. Maternal dose was converted into morphine milligram equivalents (MMEs) and stratified into high- (MME >1000 mg) and low-dose groups (MME ≤1000 mg). Associations between infant outcomes and MME dosage were examined using Wilcoxon rank-sum and Fisher's Exact tests. Days to symptom control were significantly higher in the high MME group (5 days vs 2.8 days, P = .016). Rates of developmental delay at 24 months were higher in the high MME group (21.2% vs 4.5%, P = .0335). Maternal MME did not predict need for NOWS treatment. Higher MME-exposed infants should have optimized nonpharmacologic interventions for consolation and be increasingly observed for signs of developmental delay.

Saliva microRNA Profile in Children with and without Severe SARS-CoV-2 Infection.

Severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) may impair immune modulating host microRNAs, causing severe disease. Our objectives were to determine the salivary miRNA profile in children with SARS-CoV-2 infection at presentation and compare the expression in those with and without severe outcomes. Children <18 years with SARS-CoV-2 infection evaluated at two hospitals between March 2021 and February 2022 were prospectively enrolled. Severe outcomes included respiratory failure, shock or death. Saliva microRNAs were quantified with RNA sequencing. Data on 197 infected children (severe = 45) were analyzed. Of the known human miRNAs, 1606 (60%) were measured and compared across saliva samples. There were 43 miRNAs with ≥2-fold difference between severe and non-severe cases (adjusted p-value < 0.05). The majority (31/43) were downregulated in severe cases. The largest between-group differences involved miR-4495, miR-296-5p, miR-548ao-3p and miR-1273c. These microRNAs displayed enrichment for 32 gene ontology pathways including viral processing and transforming growth factor beta and Fc-gamma receptor signaling. In conclusion, salivary miRNA levels are perturbed in children with severe COVID-19, with the majority of miRNAs being down regulated. Further studies are required to validate and determine the utility of salivary miRNAs as biomarkers of severe COVID-19.

Putting the "mi" in omics: discovering miRNA biomarkers for pediatric precision care.

In the past decade, growing interest in micro-ribonucleic acids (miRNAs) has catapulted these small, non-coding nucleic acids to the forefront of biomarker research. Advances in scientific knowledge have made it clear that miRNAs play a vital role in regulating cellular physiology throughout the human body. Perturbations in miRNA signaling have also been described in a variety of pediatric conditions-from cancer, to renal failure, to traumatic brain injury. Likewise, the number of studies across pediatric disciplines that pair patient miRNA-omics with longitudinal clinical data are growing. Analyses of these voluminous, multivariate data sets require understanding of pediatric phenotypic data, data science, and genomics. Use of machine learning techniques to aid in biomarker detection have helped decipher background noise from biologically meaningful changes in the data. Further, emerging research suggests that miRNAs may have potential as therapeutic targets for pediatric precision care. Here, we review current miRNA biomarkers of pediatric diseases and studies that have combined machine learning techniques, miRNA-omics, and patient health data to identify novel biomarkers and potential therapeutics for pediatric diseases. IMPACT: In the following review article, we summarized how recent developments in microRNA research may be coupled with machine learning techniques to advance pediatric precision care.

Confounding Factors Impacting microRNA Expression in Human Saliva: Methodological and Biological Considerations.

There is growing interest in saliva microRNAs (miRNAs) as non-invasive biomarkers for human disease. Such an approach requires understanding how differences in experimental design affect miRNA expression. Variations in technical methodologies, coupled with inter-individual variability may reduce study reproducibility and generalizability. Another barrier facing salivary miRNA biomarker research is a lack of recognized "control miRNAs". In one of the largest studies of human salivary miRNA to date (922 healthy individuals), we utilized 1225 saliva samples to quantify variability in miRNA expression resulting from aligner selection (Bowtie1 vs. Bowtie2), saliva collection method (expectorated vs. swabbed), RNA stabilizer (presence vs. absence), and individual biological factors (sex, age, body mass index, exercise, caloric intake). Differential expression analyses revealed that absence of RNA stabilizer introduced the greatest variability, followed by differences in methods of collection and aligner. Biological factors generally affected a smaller number of miRNAs. We also reported coefficients of variations for 643 miRNAs consistently present in saliva, highlighting several salivary miRNAs to serve as reference genes. Thus, the results of this analysis can be used by researchers to optimize parameters of salivary miRNA measurement, exclude miRNAs confounded by numerous biologic factors, and identify appropriate miRNA controls.