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.

Infant Saliva Microbiome Activity Modulates Nutritional Impacts on Neurodevelopment.

Neurodevelopment is influenced by complex interactions between environmental factors, including social determinants of health (SDOH), nutrition, and even the microbiome. This longitudinal cohort study of 142 infants tested the hypothesis that microbial activity modulates the effects of nutrition on neurodevelopment. Salivary microbiome activity was measured at 6 months using RNA sequencing. Infant nutrition was assessed longitudinally with the Infant Feeding Practices survey. The primary outcome was presence/absence of neurodevelopmental delay (NDD) at 18 months on the Survey of Wellbeing in Young Children. A logistic regression model employing two microbial factors, one nutritional factor, and two SDOH accounted for 33.3% of the variance between neurodevelopmental groups (p < 0.001, AIC = 77.7). NDD was associated with Hispanic ethnicity (OR 18.1, 2.36-139.3; p = 0.003), no fish consumption (OR 10.6, 2.0-54.1; p = 0.003), and increased Candidatus Gracilibacteria activity (OR 1.43, 1.00-2.07; p = 0.007). Home built after 1977 (OR 0.02, 0.001-0.53; p = 0.004) and Chlorobi activity (OR 0.76, 0.62-0.93, p = 0.001) were associated with reduced risk of NDD. Microbial alpha diversity modulated the effect of fish consumption on NDD (X2 = 5.7, p = 0.017). These data suggest the benefits of fish consumption for neurodevelopment may be mediated by microbial diversity. Confirmation in a larger, randomized trial is required.

Increased Sleep Latency and Decreased Sleep Duration are Associated With Elevated Risk of Bed Sharing Among Mother-Infant Dyads.

Bed sharing increases risk of sleep-related infant deaths. We hypothesized that infant sleep difficulties increase bed sharing, independent of social determinants of health (SDOH). In total, 191 mother-infant dyads in a prospective, longitudinal cohort study completed the Brief Infant Sleep Questionnaire at 1, 4, 6, and 12 months. Sleep characteristics at 1 month (latency, duration, night awakenings) were compared between dyads with/without bed sharing in the first 12 months. Infants who participated in bed sharing slept fewer hours at night (7.1 ± 1.7 hours vs 8.3 ± 1.5 hours, P = .001, d = -0.79), and took longer to fall asleep (0.7 ± 0.6 hours vs 0.5 ± 0.5 hours, P = .021, d = 0.43), even when controlling for SDOH variables that influence bed sharing. Maternal perception of sleep problems did not differ between groups (P = .12). Our findings suggest that infants with quantifiable sleep difficulties at 1 month are more likely to bed share.

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.

The Association between Infant Colic and the Multi-Omic Composition of Human Milk.

Infant colic is a common condition with unclear biologic underpinnings and limited treatment options. We hypothesized that complex molecular networks within human milk (i.e., microbes, micro-ribonucleic acids (miRNAs), cytokines) would contribute to colic risk, while controlling for medical, social, and nutritional variables. This hypothesis was tested in a cohort of 182 breastfed infants, assessed with a modified Infant Colic Scale at 1 month. RNA sequencing was used to interrogate microbial and miRNA features. Luminex assays were used to measure growth factors and cytokines. Milk from mothers of infants with colic (n = 28) displayed higher levels of Staphylococcus (adj. p = 0.038, d = 0.30), miR-224-3p (adj. p = 0.023, d = 0.33), miR-125b-5p (adj. p = 0.028, d = 0.29), let-7a-5p (adj. p = 0.028, d = 0.27), and miR-205-5p (adj. p = 0.029, d = 0.26) compared to milk from non-colic mother-infant dyads (n = 154). Colic symptom severity was directly associated with milk hepatocyte growth factor levels (R = 0.21, p = 0.025). A regression model involving let-7a-5p, miR-29a-3p, and Lactobacillus accurately modeled colic risk (X2 = 16.7, p = 0.001). Molecular factors within human milk may impact colic risk, and provide support for a dysbiotic/inflammatory model of colic pathophysiology.

Human Milk-Derived Levels of let-7g-5p May Serve as a Diagnostic and Prognostic Marker of Low Milk Supply in Breastfeeding Women.

Low milk supply (LMS) is associated with early breastfeeding cessation; however, the biological underpinnings in the mammary gland are not understood. MicroRNAs (miRNAs) are small non-coding RNAs that post-transcriptionally downregulate gene expression, and we hypothesized the profile of miRNAs secreted into milk reflects lactation performance. Longitudinal changes in milk miRNAs were measured using RNAseq in women with LMS (n = 47) and adequate milk supply (AMS; n = 123). Relationships between milk miRNAs, milk supply, breastfeeding outcomes, and infant weight gain were assessed, and interactions between milk miRNAs, maternal diet, smoking status, and BMI were determined. Women with LMS had lower milk volume (p = 0.003), were more likely to have ceased breast feeding by 24 wks (p = 0.0003) and had infants with a lower mean weight-for-length z-score (p = 0.013). Milk production was significantly associated with milk levels of miR-16-5p (R = -0.14, adj p = 0.044), miR-22-3p (R = 0.13, adj p = 0.044), and let-7g-5p (R = 0.12, adj p = 0.046). Early milk levels of let-7g-5p were significantly higher in mothers with LMS (adj p = 0.0025), displayed an interaction between lactation stage and milk supply (p < 0.001), and were negatively related to fruit intake (p = 0.015). Putative targets of let-7g-5p include genes important to hormone signaling, RNA regulation, ion transport, and the extracellular matrix, and down-regulation of two targets (PRLR and IGF2BP1/IMP1) was confirmed in mammary cells overexpressing let-7g-5p in vitro. Our data provide evidence that milk-derived miRNAs reflect lactation performance in women and warrant further investigation to assess their utility for predicting LMS risk and early breastfeeding cessation.

Comparison of Symptom Duration Between Children With SARS-CoV-2 and Peers With Other Viral Illnesses During the COVID-19 Pandemic.

Some children and young people (CYP) with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) experience persistent symptoms, commonly called "long COVID." It remains unclear whether symptoms of SARS-CoV-2 persist longer than those of other respiratory viruses, particularly in young children. This cross-sectional study involved 372 CYP (0-15 years) tested for SARS-CoV-2. Character and duration of symptoms (cough, runny nose, sore throat, rash, diarrhea, vomiting, sore muscles, fatigue, fever, loss of smell) were compared between CYP with a positive test (n = 100) and those with a negative test (n = 272), while controlling for medical/demographic covariates. The average duration of symptoms for CYP with a positive SARS-CoV-2 test (8.5 ± 10 days) did not differ from that of CYP with a negative test (7.2 ± 5 days, P = .71, d = 0.046). A positive SARS-CoV-2 test did not increase the risk (36/372, 10%) of symptoms persisting for ≥3 weeks (odds ratio = 0.96, 95% confidence interval = 0.45-2.0). These results suggest CYP with non-SARS-CoV-2 infections experience a similar duration of symptoms as peers with SARS-CoV-2 infection.

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.

Refinement of saliva microRNA biomarkers for sports-related concussion.

BACKGROUND: Recognizing sport-related concussion (SRC) is challenging and relies heavily on subjective symptom reports. An objective, biological marker could improve recognition and understanding of SRC. There is emerging evidence that salivary micro-ribonucleic acids (miRNAs) may serve as biomarkers of concussion; however, it remains unclear whether concussion-related miRNAs are impacted by exercise. We sought to determine whether 40 miRNAs previously implicated in concussion pathophysiology were affected by participation in a variety of contact and non-contact sports. Our goal was to refine a miRNA-based tool capable of identifying athletes with SRC without the confounding effects of exercise. METHODS: This case-control study harmonized data from concussed and non-concussed athletes recruited across 10 sites. Levels of salivary miRNAs within 455 samples from 314 individuals were measured with RNA sequencing. Within-subjects testing was used to identify and exclude miRNAs that changed with either (a) a single episode of exercise (166 samples from 83 individuals) or (b) season-long participation in contact sports (212 samples from 106 individuals). The miRNAs that were not impacted by exercise were interrogated for SRC diagnostic utility using logistic regression (172 samples from 75 concussed and 97 non-concussed individuals). RESULTS: Two miRNAs (miR-532-5p and miR-182-5p) decreased (adjusted p < 0.05) after a single episode of exercise, and 1 miRNA (miR-4510) increased only after contact sports participation. Twenty-three miRNAs changed at the end of a contact sports season. Two of these miRNAs (miR-26b-3p and miR-29c-3p) were associated (R > 0.50; adjusted p < 0.05) with the number of head impacts sustained in a single football practice. Among the 15 miRNAs not confounded by exercise or season-long contact sports participation, 11 demonstrated a significant difference (adjusted p < 0.05) between concussed and non-concussed participants, and 6 displayed moderate ability (area under curve > 0.70) to identify concussion. A single ratio (miR-27a-5p/miR-30a-3p) displayed the highest accuracy (AUC = 0.810, sensitivity = 82.4%, specificity = 73.3%) for differentiating concussed and non-concussed participants. Accuracy did not differ between participants with SRC and non-SRC (z = 0.5, p = 0.60). CONCLUSION: Salivary miRNA levels may accurately identify SRC when not confounded by exercise. Refinement of this approach in a large cohort of athletes could eventually lead to a non-invasive, sideline adjunct for SRC assessment.

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.

Multi-Omic Profiles in Infants at Risk for Food Reactions.

Food reactions (FR) are multifactorial and impacted by medical, demographic, environmental, and immunologic factors. We hypothesized that multi-omic analyses of host-microbial factors in saliva would enhance our understanding of FR development. This longitudinal cohort study included 164 infants followed from birth through two years. The infants were identified as FR (n = 34) or non-FR (n = 130) using the Infant Feeding Practice II survey and medical record confirmation. Saliva was collected at six months for the multi-omic assessment of cytokines, mRNAs, microRNAs, and the microbiome/virome. The levels of one miRNA (miR-203b-3p, adj. p = 0.043, V = 2913) and one viral phage (Proteus virus PM135, adj. p = 0.027, V = 2955) were lower among infants that developed FRs. The levels of one bacterial phylum (Cyanobacteria, adj. p = 0.048, V = 1515) were higher among infants that developed FR. Logistical regression models revealed that the addition of multi-omic features (miR-203b-3p, Cyanobacteria, and Proteus virus PM135) improved predictiveness for future FRs in infants (p = 0.005, X2 = 12.9), predicting FRs with 72% accuracy (AUC = 0.81, sensitivity = 72%, specificity = 72%). The multi-omic analysis of saliva may enhance the accurate identification of infants at risk of FRs and provide insights into the host/microbiome interactions that predispose certain infants to FRs.

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.

Infant consumption of microRNA miR-375 in human milk lipids is associated with protection from atopy.

BACKGROUND: Human milk is thought to reduce infant atopy risk. The biologic mechanism for this protective effect is not fully understood. OBJECTIVES: We tested the hypothesis that infant consumption of 4 microRNAs (miR-146b-5p, miR-148b-3p, miR-21-5p, and miR-375-3p) in human milk would be associated with reduced atopy risk. METHODS: The Breast Milk Influence of the Microtranscriptome Profile on Atopy in Children over Time (IMPACT) study involved a cohort of mother-infant dyads who planned to breastfeed beyond 4 mo. Infant consumption of the 4 human milk microRNAs (miRNAs) in the first 6 mo was calculated as the product of milk miRNA concentration and the number of human milk feeds, across 3 lactation stages: early milk (0-4 wk), transitional milk (4-16 wk), and mature milk (16-24 wk). The primary outcome was infant atopy in the first year, defined as atopic dermatitis (AD), food allergies, or wheezing. The final analysis included 432 human milk samples and 7824 wk of longitudinal health data from 163 dyads. RESULTS: Seventy-three infants developed atopy. Forty-one were diagnosed with AD (25%), 33 developed food allergy (20%), and 10 had wheezing (6%). Eleven developed >1 condition (7%). Infants who did not develop atopy consumed higher concentrations of miR-375-3p (d = 0.18, P = 0.022, adj P = 0.044) and miR-148b-3p (d = 0.23, P = 0.007, adj P = 0.028). The consumption of miR-375-3p (X2 = 5.7, P = 0.017, OR: 0.92, 95% CI: 0.86, 0.99) was associated with reduced atopy risk. Concentrations of miR-375-3p increased throughout lactation (r = 0.46, F = 132.3, P = 8.4 × 10-34) and were inversely associated with maternal body mass (r = -0.11, t = -2.1, P = 0.032). CONCLUSIONS: This study provides evidence that infant consumption of miR-375-3p may reduce atopy risk.

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.

Early Salivary miRNA Expression in Extreme Low Gestational Age Newborns.

Background: MicroRNAs (miRNA) are small non-coding RNAs that regulate gene expression playing a key role in organogenesis. MiRNAs are studied in tracheal aspirates (TA) of preterm infants. However; this is difficult to obtain in infants who are not intubated. This study examines early salivary miRNA expression as non-invasive early biomarkers in extremely low gestational age newborns (ELGANs). Methods: Saliva was collected using DNA-genotek swabs, miRNAs were analyzed using RNA seq and RT PCR arrays. Salivary miRNA expression was compared to TA using RNA seq at 3 days of age, and longitudinal changes at 28 days of age were analyzed using RT PCR arrays in ELGANs. Results: Approximately 822 ng of RNA was extracted from saliva of 7 ELGANs; Of the 757 miRNAs isolated, 161 miRNAs had significant correlation in saliva and TA at 3 days of age (r = 0.97). Longitudinal miRNA analysis showed 29 miRNAs downregulated and 394 miRNAs upregulated at 28 days compared to 3 days of age (adjusted p < 0.1). Bioinformatic analysis (Ingenuity Pathway Analysis) of differentially expressed miRNAs identified organismal injury and abnormalities and cellular development as the top physiological system development and cellular function. Conclusion: Salivary miRNA expression are source for early biomarkers of underlying pathophysiology in ELGANs.

Defining Biological Phenotypes of Mild Traumatic Brain Injury Using Saliva MicroRNA Profiles.

Concussion is a heterogeneous injury that relies predominantly on subjective symptom reports for patient assessment and treatment. Developing an objective, biological test could aid phenotypic categorization of concussion patients, leading to advances in personalized treatment. This prospective multi-center study employed saliva micro-ribonucleic acid (miRNA) levels to stratify 251 individuals with concussion into biological subgroups. Using miRNA biological clusters, our objective was to assess for differences in medical/demographic characteristics, symptoms, and functional measures of balance and cognition. The miRNAs that best defined each cluster were used to identify physiological pathways that characterized each cluster. The 251 participants (mean age: 18 ± 7 years; 57% male) were optimally grouped into 10 clusters based on 22 miRNA levels. The clusters differed in age (χ2 = 19.1, p = 0.024), days post-injury at the time of saliva collection (χ2 = 22.6; p = 0.007), and number of prior concussions (χ2 = 17.6, p = 0.040). The clusters also differed in symptom reports for fatigue (χ2 = 17.7; p = 0.039), confusion (χ2 = 22.3; p = 0.008), difficulty remembering (χ2 = 22.0; p = 0.009), and trouble falling asleep (χ2 = 17.2; p = 0.046), but not objective balance or cognitive performance (p > 0.05). The miRNAs that defined concussion clusters regulate 16 physiological pathways, including adrenergic signaling, estrogen signaling, fatty acid metabolism, GABAergic signaling, synaptic vesicle cycling, and transforming growth factor (TGF)-ß signaling. These results show that saliva miRNA levels may stratify individuals with concussion based on underlying biological perturbations that are relevant to both symptomology and pharmacological targets. If validated in a larger cohort, miRNA assessment could aid individualized, biology-driven concussion treatment.