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.

Multi-omic factors associated with future wheezing in infants.

BACKGROUND: The pathophysiology of wheezing is multifactorial, impacted by medical, demographic, environmental, and immunologic factors. We hypothesized that multi-omic analyses of host and microbial factors in saliva would enhance the ability to identify infants at risk for wheezing. METHODS: This longitudinal cohort study included 161 term infants. Infants who developed wheezing (n = 27) within 24 months of delivery were identified using the International Study of Asthma and Allergies in Childhood Written Questionnaire and review of the medical record. Standardized surveys were used to assess infant traits and environmental exposures. Saliva was collected for multi-omic assessment of cytokines, microRNAs, mRNAs, and microbiome/virome RNAs. RESULTS: Two infant factors (daycare attendance, family history of asthma) and three salivary "omic" features (miR-26a-5p, Elusimicrobia, Streptococcus phage phiARI0131-1) differed between the two groups (adjusted p < 0.05). miR-26a-5p levels were correlated with Elusimicrobia (R = -0.87, p = 3.7 × 10-31). A model employing the three omic features plus daycare attendance and family asthma history yielded the highest predictive accuracy for future wheezing episodes (AUC = 0.74, 95% CI: 0.703-0.772, 77% sensitivity, 62% specificity). CONCLUSIONS: Host-microbiome interactions in saliva may yield pathophysiologic clues about the origins of wheezing and aid identification of infants at risk of future wheezing episodes. IMPACT: Wheezing is multi-factorial, but the relative contributions of infant traits, environment, and underlying biology are poorly understood. This multi-omic study identifies three molecular factors, including salivary microRNAs, microbes, and viral phages associated with increased risk of infant wheezing. Measurement of these molecular factors enhanced predictive accuracy for future wheezing when combined with family asthma history and daycare attendance. Validation of this approach could be used to identify infants at risk for wheezing and guide personalized medical management.

Infant Saliva Levels of microRNA miR-151a-3p Are Associated with Risk for Neurodevelopmental Delay.

Prompt recognition of neurodevelopmental delay is critical for optimizing developmental trajectories. Currently, this is achieved with caregiver questionnaires whose sensitivity and specificity can be limited by socioeconomic and cultural factors. This prospective study of 121 term infants tested the hypothesis that microRNA measurement could aid early recognition of infants at risk for neurodevelopmental delay. Levels of four salivary microRNAs implicated in childhood autism (miR-125a-5p, miR-148a-5p, miR-151a-3p, miR-28-3p) were measured at 6 months of age, and compared between infants who displayed risk for neurodevelopmental delay at 18 months (n = 20) and peers with typical development (n = 101), based on clinical evaluation aided by the Survey of Wellbeing in Young Children (SWYC). Accuracy of microRNAs for predicting neurodevelopmental concerns at 18 months was compared to the clinical standard (9-month SWYC). Infants with neurodevelopmental concerns at 18 months displayed higher levels of miR-125a-5p (d = 0.30, p = 0.018, adj p = 0.049), miR-151a-3p (d = 0.30, p = 0.017, adj p = 0.048), and miR-28-3p (d = 0.31, p = 0.014, adj p = 0.048). Levels of miR-151a-3p were associated with an 18-month SWYC score (R = -0.19, p = 0.021) and probability of neurodevelopmental delay at 18 months (OR = 1.91, 95% CI, 1.14-3.19). Salivary levels of miR-151a-3p enhanced predictive accuracy for future neurodevelopmental delay (p = 0.010, X2 = 6.71, AUC = 0.71) compared to the 9-month SWYC score alone (OR = 0.56, 95% CI, 0.20-1.58, AUC = 0.567). This pilot study provides evidence that miR-151a-3p may aid the identification of infants at risk for neurodevelopmental delay. External validation of these findings is necessary.

Multi-Omic Factors Associated with Frequency of Upper Respiratory Infections in Developing Infants.

Susceptibility to upper respiratory infections (URIs) may be influenced by host, microbial, and environmental factors. We hypothesized that multi-omic analyses of molecular factors in infant saliva would identify complex host-environment interactions associated with URI frequency. A cohort study involving 146 infants was used to assess URI frequency in the first year of life. Saliva was collected at 6 months for high-throughput multi-omic measurement of cytokines, microRNAs, transcripts, and microbial RNA. Regression analysis identified environmental (daycare attendance, atmospheric pollution, breastfeeding duration), microbial (Verrucomicrobia, Streptococcus phage), and host factors (miR-22-5p) associated with URI frequency (p < 0.05). These results provide pathophysiologic clues about molecular factors that influence URI susceptibility. Validation of these findings in a larger cohort could one day yield novel approaches to detecting and managing URI susceptibility in infants.

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.

Rolling Circle Amplification-Coupled Glass Nanopore Counting of Mild Traumatic Brain Injury-Related Salivary miRNAs.

Mild traumatic brain injury (mTBI) could be underdiagnosed and underreported due to the delayed onset of symptoms and the conventional subjective assessment. Recent studies have suggested that salivary microRNAs (miRNAs) could be reliable biomarkers for objective mTBI diagnosis. In this work, we demonstrated a rolling circle amplification (RCA)-coupled resistive pulse-counting platform for profiling mTBI-related miRNAs, using easy-to-fabricate large glass nanopores (200 nm diameter). The method relies on the linear and specific elongation of the miRNA to a much larger RCA product, which the large glass nanopore can digitally count with a high signal-to-noise ratio. We developed and validated the RCA assay against let-7a, miR-30e, and miR-21. We demonstrated the quantification capability of this large glass nanopore counting platform for purified miRNAs as well as miRNAs in salivary total RNA background. Finally, we quantitatively evaluated the performance of profiling each individual miRNAs in a mixed analyte. Our results showed that the RCA-coupled large glass nanopore counting provides a promising and accessible alternative toward the clinical diagnosis of mTBI using salivary miRNAs.

Understanding immunological origins of atopic dermatitis through multi-omic analysis.

BACKGROUND: The pathophysiology of atopic dermatitis (AD) is multifactorial, impacted by individual medical, demographic, environmental, and immunologic factors. This study used multi-omic analyses to assess how host and microbial factors could contribute to infant AD development. METHODS: This longitudinal cohort study included 129 term infants, identified as AD (n = 37) or non-AD (n = 92) using the Infant Feeding Practices-II survey and review of medical records. Standardized surveys were used to assess medical and demographic traits (gestational age, sex, race, maternal AD, and atopy family history), and environmental exposures (delivery method, maternal tobacco use, pets, breastfeeding duration, and timing of solid food introduction). Saliva was collected at 6 months for multi-omic assessment of cytokines, microRNAs, mRNAs, and the microbiome. The contribution of each factor to AD status was assessed with logistic regression. RESULTS: Medical, demographic, and environmental factors did not differ between AD and non-AD infants. Five "omic" factors (IL-8/IL-6, miR-375-3p, miR-21-5p, bacterial diversity, and Proteobacteria) differed between groups (p < .05). The severity of AD was positively associated with levels of miR-375-3p (R = .17, p = .049) and Proteobacteria (R = .22, p = .011), and negatively associated with levels of miR-21-5p (R = .20, p = .022). Multi-omic features accounted for 17% of variance between groups, significantly improving an AD risk model employing medical, demographic, and environmental factors (X2  = 32.47, p = .006). CONCLUSION: Interactions between the microbiome and host signaling may predispose certain infants to AD by promoting a pro-inflammatory environment.

Personality Traits and Social Supports in Adolescents With Persistent Postconcussion Symptoms.

OBJECTIVES: To determine whether adolescents with persistent postconcussion symptoms (PPCS) differ from healthy peers in their personality traits and social supports. SETTING: Specialty Concussion Clinic and Primary Care Clinic affiliated with an academic medical center. PARTICIPANTS: Ninety-seven adolescents (42 with PPCS, 55 healthy peers; age: 15 ± 2 years). DESIGN: Participants completed a web-based survey that included medical and demographic characteristics, mechanisms of concussion, 10-item Big Five Inventory, and Child and Adolescent Social Support Scale. A Student's 2-tailed t test with multiple testing corrections was used to compare the youths with PPCS to healthy peers. MAIN MEASURES: The primary outcome was PPCS, defined by the presence of 2 or more concussion-related symptoms on the Post-Concussion Symptom Scale (PCSS), lasting for more than 4 weeks after initial injury. The secondary outcome was perceived personality traits and social support, based on the 10-item Big Five Inventory and the Child and Adolescent Social Support Scale, respectively. RESULTS: The PPCS group had higher neuroticism scores on their Big Five Inventory than healthy peers. They also reported less social support from teachers and classmates than healthy peers. CONCLUSION: Youths with PPCS report specific personality and social support characteristics that differ from their peers. These findings suggest that individual personality and school-based social supports may influence concussion recovery.

Visual Sentiment Analysis from Disaster Images in Social Media.

The increasing popularity of social networks and users' tendency towards sharing their feelings, expressions, and opinions in text, visual, and audio content have opened new opportunities and challenges in sentiment analysis. While sentiment analysis of text streams has been widely explored in the literature, sentiment analysis from images and videos is relatively new. This article focuses on visual sentiment analysis in a societally important domain, namely disaster analysis in social media. To this aim, we propose a deep visual sentiment analyzer for disaster-related images, covering different aspects of visual sentiment analysis starting from data collection, annotation, model selection, implementation, and evaluations. For data annotation and analyzing people's sentiments towards natural disasters and associated images in social media, a crowd-sourcing study has been conducted with a large number of participants worldwide. The crowd-sourcing study resulted in a large-scale benchmark dataset with four different sets of annotations, each aiming at a separate task. The presented analysis and the associated dataset, which is made public, will provide a baseline/benchmark for future research in the domain. We believe the proposed system can contribute toward more livable communities by helping different stakeholders, such as news broadcasters, humanitarian organizations, as well as the general public.

Discrepancies in child and parent reporting of concussion symptoms.

Objective: To assess discrepancies between child and parent symptom reports following concussion.Methods: Prospective cohort study involving 61 patients, age 7-21 years, diagnosed with a concussion within the previous 14 days. Children/parents completed the Child SCAT-3 symptom inventory at enrollment and 4 weeks post-injury. A within-subjects t-test was used to compare differences in child/parent response for each of 20 individual symptoms, 4 symptom domains, and total symptom severity. Pearson correlations were used to measure agreement between child/parent responses. A repeated measures analysis of variance assessed the effect of time on child/parent symptom discrepancy.Results: At enrollment, children reported higher symptom severity for 'distracted easily' (adj. p = .015) and 'confused' (adj. p = .015). There was moderate-to-high (r > 0.3) agreement between children and parents for more individual symptoms at enrollment (18/20) than at 4 weeks post-injury (14/20). Age had no effect (p > .05) on the discrepancy between child/parent reports.Conclusions: Although there was moderate-to-strong agreement between child/parent reports of concussion symptoms, discrepancies in individual cognitive symptom reports exist, in both children and adolescents. Therefore, collection of parent scales may provide useful information when tracking cognitive symptoms in adolescent patients, who may under-report or under-recognize cognitive deficits.

Cytokine Panels and Pediatric Acute Respiratory Distress Syndrome: A Translational Investigation.

OBJECTIVES: To identify and compare serum and lower respiratory tract fluid biomarkers of lung injury using well-characterized mouse models of lung injury. To explore the relationship between these preclinical biomarkers and clinical outcomes in a discovery cohort of pediatric patients with acute respiratory failure from pneumonia. DESIGN: Prospective, observational cohort study. SETTING: A basic science laboratory and the PICU of a tertiary-care children's hospital. PATIENTS: PICU patients intubated for respiratory failure from a suspected respiratory infection. INTERVENTIONS: Prospective enrollment and collection of lower respiratory tract fluid samples. MEASUREMENTS AND MAIN RESULTS: C57BL6/J mice were intranasally inoculated with escalating doses of influenza A virus or toll-like receptor agonists to simulate varying degrees of lung injury. Serum and bronchoalveolar lavage fluid were measured for the presence of cytokines using commercially available multiplex cytokine assays. Elevated levels of C-C motif chemokine ligand 7 at the peak of inflammation in both bronchoalveolar lavage fluid and serum correlated with lethality, with the bronchoalveolar lavage fluid ratio of C-C motif chemokine ligand 7:C-C motif chemokine ligand 22 providing the best prediction in the mouse models. These preclinical biomarkers were examined in the plasma and lower respiratory tract fluid of a discovery cohort of pediatric patients with acute respiratory failure from pneumonia. The primary clinical outcome measure was ventilator-free days, with secondary outcomes of pediatric acute respiratory distress syndrome severity and mortality. Elevation in peak lower respiratory tract fluid C-C motif chemokine ligand 7:C-C motif chemokine ligand 22 ratios demonstrated a significant negative correlation with ventilator-free days (r = -0.805; p < 0.02). CONCLUSIONS: This study provides evidence that lung immune profiling via lower respiratory tract fluid cytokine analysis is feasible and may provide insight into clinical outcomes. Further validation of markers, including the C-C motif chemokine ligand 7:C-C motif chemokine ligand 22 ratio in this limited study, in a larger cohort of patients is necessary.

Saliva microRNA Biomarkers of Cumulative Concussion.

Recurrent concussions increase risk for persistent post-concussion symptoms, and may lead to chronic neurocognitive deficits. Little is known about the molecular pathways that contribute to persistent concussion symptoms. We hypothesized that salivary measurement of microribonucleic acids (miRNAs), a class of epitranscriptional molecules implicated in concussion pathophysiology, would provide insights about the molecular cascade resulting from recurrent concussions. This hypothesis was tested in a case-control study involving 13 former professional football athletes with a history of recurrent concussion, and 18 age/sex-matched peers. Molecules of interest were further validated in a cross-sectional study of 310 younger individuals with a history of no concussion (n = 230), a single concussion (n = 56), or recurrent concussions (n = 24). There was no difference in neurocognitive performance between the former professional athletes and their peers, or among younger individuals with varying concussion exposures. However, younger individuals without prior concussion outperformed peers with prior concussion on three balance assessments. Twenty salivary miRNAs differed (adj. p < 0.05) between former professional athletes and their peers. Two of these (miR-28-3p and miR-339-3p) demonstrated relationships (p < 0.05) with the number of prior concussions reported by younger individuals. miR-28-3p and miR-339-5p may play a role in the pathophysiologic mechanism involved in cumulative concussion effects.

Distance running alters peripheral microRNAs implicated in metabolism, fluid balance, and myosin regulation in a sex-specific manner.

Microribonucleic acids (miRNAs) mediate adaptive responses to exercise and may serve as biomarkers of exercise intensity/capacity. Expression of miRNAs is altered in skeletal muscle, plasma, and saliva following exertion. Women display unique physiologic responses to endurance exercise, and miRNAs respond to pathologic states in sex-specific patterns. However sex-specific miRNA responses to exercise remain unexplored. This study utilized high-throughput RNA sequencing to measure changes in salivary RNA expression among 25 collegiate runners following a single long-distance run. RNA concentrations in pre- and post-run saliva was assessed through alignment and quantification of 4,694 miRNAs and 27,687 mRNAs. Pair-wise Wilcoxon rank-sum test identified miRNAs with significant [false discovery rate (FDR) < 0.05] post-run changes. Associations between miRNA levels and predicted mRNA targets were explored with Pearson correlations. Differences in miRNA patterns between men ( n = 13) and women ( n = 12) were investigated with two-way analysis of variance. Results revealed 122 salivary miRNAs with post-run changes. The eight miRNAs with the largest changes were miR-3671, miR-5095 (downregulated); and miR-7154-3p, miR-200b-5p, miR-5582-3p, miR-6859-3p, miR-6751-5p, miR-4419a (upregulated). Predicted mRNA targets for these miRNAs represented 15 physiologic processes, including glycerophospholipid metabolism (FDR = 0.042), aldosterone-regulated sodium reabsorption (FDR = 0.049), and arrhythmogenic ventricular cardiomyopathy (FDR = 0.018). Twenty-six miRNA/mRNA pairs had associated changes in post-run levels. Three miRNAs (miR-4675, miR-6745, miR-6746-3p) demonstrated sex-specific responses to exercise. Numerous salivary miRNAs change in response to endurance running and target the expression of genes involved in metabolism, fluid balance, and musculoskeletal adaptations. A subset of miRNAs may differentiate the metabolic response to exercise in men and women.

Metabolism-related microRNAs in maternal breast milk are influenced by premature delivery.

BackgroundMaternal breast milk (MBM) is enriched in microRNAs, factors that regulate protein translation throughout the human body. MBM from mothers of term and preterm infants differs in nutrient, hormone, and bioactive-factor composition, but the microRNA differences between these groups have not been compared. We hypothesized that gestational age at delivery influences microRNA in MBM, particularly microRNAs involved in immunologic and metabolic regulation.MethodsMBM from mothers of premature infants (pMBM) obtained 3-4 weeks post delivery was compared with MBM from mothers of term infants obtained at birth (tColostrum) and 3-4 weeks post delivery (tMBM). The microRNA profile in lipid and skim fractions of each sample was evaluated with high-throughput sequencing.ResultsThe expression profiles of nine microRNAs in lipid and skim pMBM differed from those in tMBM. Gene targets of these microRNAs were functionally related to elemental metabolism and lipid biosynthesis. The microRNA profile of tColostrum was also distinct from that of pMBM, but it clustered closely with tMBM. Twenty-one microRNAs correlated with gestational age demonstrated limited relationships with method of delivery, but not other maternal-infant factors.ConclusionPremature delivery results in a unique MBM microRNA profile with metabolic targets. This suggests that preterm milk may have adaptive functions for growth in premature infants.

Salivary miRNA profiles identify children with autism spectrum disorder, correlate with adaptive behavior, and implicate ASD candidate genes involved in neurodevelopment.

BACKGROUND: Autism spectrum disorder (ASD) is a common neurodevelopmental disorder that lacks adequate screening tools, often delaying diagnosis and therapeutic interventions. Despite a substantial genetic component, no single gene variant accounts for >1 % of ASD incidence. Epigenetic mechanisms that include microRNAs (miRNAs) may contribute to the ASD phenotype by altering networks of neurodevelopmental genes. The extracellular availability of miRNAs allows for painless, noninvasive collection from biofluids. In this study, we investigated the potential for saliva-based miRNAs to serve as diagnostic screening tools and evaluated their potential functional importance. METHODS: Salivary miRNA was purified from 24 ASD subjects and 21 age- and gender-matched control subjects. The ASD group included individuals with mild ASD (DSM-5 criteria and Autism Diagnostic Observation Schedule) and no history of neurologic disorder, pre-term birth, or known chromosomal abnormality. All subjects completed a thorough neurodevelopmental assessment with the Vineland Adaptive Behavior Scales at the time of saliva collection. A total of 246 miRNAs were detected and quantified in at least half the samples by RNA-Seq and used to perform between-group comparisons with non-parametric testing, multivariate logistic regression and classification analyses, as well as Monte-Carlo Cross-Validation (MCCV). The top miRNAs were examined for correlations with measures of adaptive behavior. Functional enrichment analysis of the highest confidence mRNA targets of the top differentially expressed miRNAs was performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID), as well as the Simons Foundation Autism Database (AutDB) of ASD candidate genes. RESULTS: Fourteen miRNAs were differentially expressed in ASD subjects compared to controls (p <0.05; FDR <0.15) and showed more than 95 % accuracy at distinguishing subject groups in the best-fit logistic regression model. MCCV revealed an average ROC-AUC value of 0.92 across 100 simulations, further supporting the robustness of the findings. Most of the 14 miRNAs showed significant correlations with Vineland neurodevelopmental scores. Functional enrichment analysis detected significant over-representation of target gene clusters related to transcriptional activation, neuronal development, and AutDB genes. CONCLUSION: Measurement of salivary miRNA in this pilot study of subjects with mild ASD demonstrated differential expression of 14 miRNAs that are expressed in the developing brain, impact mRNAs related to brain development, and correlate with neurodevelopmental measures of adaptive behavior. These miRNAs have high specificity and cross-validated utility as a potential screening tool for ASD.

Alterations in serum microRNA in humans with alcohol use disorders impact cell proliferation and cell death pathways and predict structural and functional changes in brain.

BACKGROUND: There is currently a lack of reliable, minimally invasive biomarkers that could predict the extent of alcoholism-induced CNS damage. Developing such biomarkers may prove useful in reducing the prevalence of alcohol use disorders (AUDs). Extracellular microRNAs (miRNAs) can be informative molecular indicators of changes in neuronal gene expression. In this study, we performed a global analysis of extracellular miRNAs to identify robust biomarkers of early CNS damage in humans diagnosed with DSM-IV AUDs. We recruited a relatively young set of 20 AUD subjects and 10 age-matched controls. They were subjected to comprehensive medical, neuropsychological and neuroimaging tests, followed by comparison of miRNA levels found in peripheral blood serum. Employing a conservative strategy to identify candidate biomarkers, miRNAs were quantified using two independent high-throughput methods: microarray and next-generation RNA-sequencing. This improved our capacity to discover and validate relevant miRNAs. RESULTS: Our results identified several miRNAs with significant and reproducible expression changes in AUD subjects versus controls. Moreover, several significant associations between candidate miRNA biomarkers and various medical, neuropsychological and neuroimaging parameters were identified using Pearson correlation and unbiased hierarchical clustering analyses. Some of the top candidate biomarkers identified, such as mir-92b and mir-96 have established roles in neural development. Cross-species validation of miRNA expression was performed using two different in vivo rat drinking models and two different in vitro mouse neural stem cell exposure models. A systems level analysis revealed a remarkable degree of convergence in the top changes seen in all of these data sets, specifically identifying cell death, cell proliferation and cell cycle processes as most consistently affected. Though not necessarily the same molecules, the affected miRNAs within these pathways clearly influence common genes, such as p53 and TNF, which stand out as potential keystone molecules. Lastly, we also examined the potential tissue origins of these biomarkers by quantifying their levels in 15 different tissue types and show that several are highly-enriched in the brain. CONCLUSIONS: Collectively, our results suggest that serum miRNA expression changes can directly relate to alterations in CNS structure and function, and may do so through effects on highly specific cellular pathways.

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.

A dataset for predicting cloud cover over Europe.

Clouds are important factors when projecting future climate. Unfortunately, future cloud fractional cover (the portion of the sky covered by clouds) is associated with significant uncertainty, making climate projections difficult. In this paper, we present the European Cloud Cover dataset, which can be used to learn statistical relations between cloud cover and other environmental variables, to potentially improve future climate projections. The dataset was created using a novel technique called Area Weighting Regridding Scheme to map satellite observations to cloud fractional cover on the same grid as the other variables in the dataset. Baseline experiments using autoregressive models document that it is possible to use the dataset to predict cloud fractional cover.

A Pilot Study of Saliva MicroRNA Signatures in Children with Moderate-to-Severe Traumatic Brain Injury.

Background/Objectives: Traumatic brain injury (TBI) is a leading cause of death and disability in children. Currently, no biological test can predict outcomes in pediatric TBI, complicating medical management. This study sought to identify brain-related micro-ribosomal nucleic acids (miRNAs) in saliva associated with moderate-to-severe TBI in children, offering a potential non-invasive, prognostic tool. Methods: A case-control design was used, enrolling participants ≤ 18 years old from three pediatric trauma centers. Participants were divided into moderate-to-severe TBI and non-TBI trauma control groups. Saliva samples were collected within 24 h of injury, with additional samples at 24-48 h and >48 h post-injury from the TBI group. miRNA profiles were visualized with partial least squares discriminant analysis (PLSDA) and hierarchical clustering. Mann-Whitney testing was used to compare miRNAs between groups, and mixed models were used to assess longitudinal expression patterns. DIANA miRPath v3.0 was used to interrogate the physiological functions of miRNAs. Results: Twenty-three participants were enrolled (14 TBI, nine controls). TBI and control groups displayed complete separation of miRNA profiles on PLSDA. Three miRNAs were elevated (adj. p < 0.05) in TBI (miR-1255b-5p, miR-3142, and miR-4320), and two were lower (miR-326 and miR-4646-5p). Three miRNAs (miR-3907, miR-4254, and miR-1273g-5p) showed temporal changes post-injury. Brain-related targets of these miRNAs included the glutamatergic synapse and GRIN2B. Conclusions: This study shows that saliva miRNA profiles in children with moderate-to-severe TBI may differ from those with non-TBI trauma and exhibit temporal changes post-injury. These miRNAs could serve as non-invasive biomarkers for prognosticating pediatric TBI outcomes. Further studies are needed to confirm these findings.

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.