Application of Full-Spectrum Rapid Clinical Genome Sequencing Improves Diagnostic Rate and Clinical Outcomes in Critically Ill Infants in the China Neonatal Genomes Project.

OBJECTIVES: To determine the diagnostic and clinical utility of trio-rapid genome sequencing in critically ill infants. DESIGN: In this prospective study, samples from critically ill infants were analyzed using both proband-only clinical exome sequencing and trio-rapid genome sequencing (proband and biological parents). The study occurred between April 2019 and December 2019. SETTING: Thirteen member hospitals of the China Neonatal Genomes Project spanning 10 provinces were involved. PARTICIPANTS: Critically ill infants (n = 202), from birth up until 13 months of life were enrolled based on eligibility criteria (e.g., CNS anomaly, complex congenital heart disease, evidence of metabolic disease, recurrent severe infection, suspected immune deficiency, and multiple malformations). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of the 202 participants, neuromuscular (45%), respiratory (22%), and immunologic/infectious (18%) were the most commonly observed phenotypes. The diagnostic yield of trio-rapid genome sequencing was higher than that of proband-only clinical exome sequencing (36.6% [95% CI, 30.1-43.7%] vs 20.3% [95% CI, 15.1-26.6%], respectively; p = 0.0004), and the average turnaround time for trio-rapid genome sequencing (median: 7 d) was faster than that of proband-only clinical exome sequencing (median: 20 d) (p < 2.2 × 10-16). The metagenomic analysis identified pathogenic or likely pathogenic microbes in six infants with symptoms of sepsis, and these results guided the antibiotic treatment strategy. Sixteen infants (21.6%) experienced a change in clinical management following trio-rapid genome sequencing diagnosis, and 24 infants (32.4%) were referred to a new subspecialist. CONCLUSIONS: Trio-rapid genome sequencing provided higher diagnostic yield in a shorter period of time in this cohort of critically ill infants compared with proband-only clinical exome sequencing. Precise and fast molecular diagnosis can alter medical management and positively impact patient outcomes.

[Relationship between serum erythropoietin levels and brain injury in preterm infants].

OBJECTIVE: To study the relationship between the levels of erythropoietin (EPO) in serum and brain injury in preterm infants. METHODS: Three hundred and four preterm infants (gestational age: 28-34 weeks) born between October 2014 and September 2015 were enrolled in this study. Brain injury was diagnosed using cerebral ultrasound and MRI. The levels of EPO, S100 protein, neuron-specific enolase (NSE) and myelin basic protein (MBP) in serum were detected using ELISA. To compare the incidence of brain injury in different serum EPO levels in preterm infants, and the relationship between brain injury and serum EPO levels was analyzed. RESULTS: The incidence rate of brain injury in preterm infants was 41.1% (125/304). The incidence rate of brain injury in the low EPO level group was significantly higher than that in the middle-high EPO level groups (P<0.01). The serum levels of S100 protein, NSE, and MBP in the brain injury groups were significantly higher than in the control group (P<0.01). The serum EPO levels were negatively correlated with serum S100 protein concentration and NSE levels (P<0.05). According to the multiple logistic regression analysis, low gestational age, low birth weight, asphyxia, prolonged mechanical ventilation, anemia and low serum EPO levels were the risk factor for brain injury in preterm infants. CONCLUSIONS: There is a higher incidence rate of brain injury in preterm infants with lower serum EPO levels. The serum EPO levels may be correlated with brain injury in preterm infants.

The Association of Neonatal Gut Microbiota Community State Types with Birth Weight.

BACKGROUND: while most gut microbiota research has focused on term infants, the health outcomes of preterm infants are equally important. Very-low-birth-weight (VLBW) or extremely-low-birth-weight (ELBW) preterm infants have a unique gut microbiota structure, and probiotics have been reported to somewhat accelerate the maturation of the gut microbiota and reduce intestinal inflammation in very-low preterm infants, thereby improving their long-term outcomes. The aim of this study was to investigate the structure of gut microbiota in ELBW neonates to facilitate the early identification of different types of low-birth-weight (LBW) preterm infants. METHODS: a total of 98 fecal samples from 39 low-birth-weight preterm infants were included in this study. Three groups were categorized according to different birth weights: ELBW (n = 39), VLBW (n = 39), and LBW (n = 20). The gut microbiota structure of neonates was obtained by 16S rRNA gene sequencing, and microbiome analysis was conducted. The community state type (CST) of the microbiota was predicted, and correlation analysis was conducted with clinical indicators. Differences in the gut microbiota composition among ELBW, VLBW, and LBW were compared. The value of gut microbiota composition in the diagnosis of extremely low birth weight was assessed via a random forest-machine learning approach. RESULTS: we briefly analyzed the structure of the gut microbiota of preterm infants with low birth weight and found that the ELBW, VLBW, and LBW groups exhibited gut microbiota with heterogeneous compositions. Low-birth-weight preterm infants showed five CSTs dominated by Enterococcus, Staphylococcus, Klebsiella, Streptococcus, Pseudescherichia, and Acinetobacter. The birth weight and clinical indicators related to prematurity were associated with the CST. We found the composition of the gut microbiota was specific to the different types of low-birth-weight premature infants, namely, ELBW, VLBW, and LBW. The ELBW group exhibited significantly more of the potentially harmful intestinal bacteria Acinetobacter relative to the VLBW and LBW groups, as well as a significantly lower abundance of the intestinal probiotic Bifidobacterium. Based on the gut microbiota's composition and its correlation with low weight, we constructed random forest model classifiers to distinguish ELBW and VLBW/LBW infants. The area under the curve of the classifiers constructed with Enterococcus, Klebsiella, and Acinetobacter was found to reach 0.836 by machine learning evaluation, suggesting that gut microbiota composition may be a potential biomarker for ELBW preterm infants. CONCLUSIONS: the gut bacteria of preterm infants showed a CST with Enterococcus, Klebsiella, and Acinetobacter as the dominant genera. ELBW preterm infants exhibit an increase in the abundance of potentially harmful bacteria in the gut and a decrease in beneficial bacteria. These potentially harmful bacteria may be potential biomarkers for ELBW preterm infants.

Machine learning-causal inference based on multi-omics data reveals the association of altered gut bacteria and bile acid metabolism with neonatal jaundice.

Early identification of neonatal jaundice (NJ) appears to be essential to avoid bilirubin encephalopathy and neurological sequelae. The interaction between gut microbiota and metabolites plays an important role in early life. It is unclear whether the composition of the gut microbiota and metabolites can be used as an early indicator of NJ or to aid clinical decision-making. This study involved a total of 196 neonates and conducted two rounds of "discovery-validation" research on the gut microbiome-metabolome. It utilized methods of machine learning, causal inference, and clinical prediction model evaluation to assess the significance of gut microbiota and metabolites in classifying neonatal jaundice (NJ), as well as the potential causal relationships between corresponding clinical variables and NJ. In the discovery stage, NJ-associated gut microbiota, network modules, and metabolite composition were identified by gut microbiome-metabolome association analysis. The NJ-associated gut microbiota was closely related to bile acid metabolites. By Lasso machine learning assessment, we found that the gut bacteria were associated with abnormal bile acid metabolism. The machine learning-causal inference approach revealed that gut bacteria affected serum total bilirubin and NJ by influencing bile acid metabolism. NJ-associated gut bile acids are potential biomarkers of NJ, and clinical prediction models constructed based on these biomarkers have some clinical effects and the model may be used for disease risk prediction. In the validation stage, it was found that intestinal metabolites can predict NJ, and the machine learning-causal inference approach revealed that bile acid metabolites affected NJ itself by affecting the total bilirubin content. Intestinal bile acid metabolites are potential biomarkers of NJ. By applying machine learning-causal inference methods to gut microbiome-metabolome association studies, we found NJ-associated intestinal bacteria and their network modules and bile acid metabolite composition. The important role of intestinal bacteria and bile acid metabolites in NJ was determined, which can predict the risk of NJ.

Association analysis of the intestinal microbiome-metabolome found that neonatal jaundice (NJ)-related intestinal microbiota, network modules and metabolite composition, and the intestinal microbiota are closely related to bile acid metabolites.Gut bacteria were found to affect serum total bilirubin (TBIL) and NJ by influencing bile acid metabolism through a machine learning-causal inference approach, and bile acid metabolites affected NJ itself by affecting the TBIL content.NJ-associated gut bacteria and bile acids are potential biomarkers of NJ, and clinical decision-making models based on these biomarkers have some clinical effects for disease risk prediction.

A frameshift mutation of TMPRSS3 in a Chinese family with non-syndromic hearing loss.

Background: Deafness is the most common sensory defect in humans worldwide. Approximately 50% of cases are attributed to genetic factors, and about 70% are non-syndromic hearing loss (NSHL). Objectives: To identify clinically relevant gene variants associated with NSHL in a Chinese family using trio-based whole-exome sequencing (WES). Materials and methods: WES was performed on the 18-month-old female proband, and her parents. Gene variants specific to the family were identified by bioinformatics analysis and evaluated for their relevance to NSHL. We verified the novel variant in this family by the next-generation sequencing.In order to elucidate the frameshift mutation of TMPRSS3 in a Chinese family, we used the Mass spectrometry to detect the gene from 1,010 healthy subjects. Results: We identified a novel homozygous deletion (c.51delA) in exon 2 of the type II transmembrane serine protease 3 gene TMPRSS3, which resulted in a frameshift mutation just before the protein transmembrane domain (p.Q17fs). The deletion was present in the proband and her father, but not in her mother and the healthy controls. We also found mutations with potential relevance to hearing loss in DCAF17, which encodes a protein of unknown function (c. T555A: p.H185Q), and ZNF276, which encodes zinc finger protein 276 (c.1350-2A > G). Conclusions and significance: We shown a novel frameshift mutation in TMPRSS3 associated with autosomal recessive NSHL in a Han Chinese family.

miR-214-3p Deficiency Enhances Caspase-1-Dependent Pyroptosis of Microglia in White Matter Injury.

White matter injury (WMI) is the most frequent impairment of neurodevelopment in preterm infants. Here, we report that the caspase-1 inflammasome is abundantly activated in the microglia of WMI mice and results in increased pyroptosis of microglia. Pharmacology inhibition of caspase-1 cleavage alleviated the pathogenesis of WMI mice. The expression of microRNA miR-214-3p was largely reduced in the microglia of WMI mice compared to controls. Compromised expression of miR-214-3p on microglia gives rise to the inflammasome activation and microglial pyroptosis. Treatment with miR-214-3p agomir is sufficient to relieve the white matter lesion and demyelination in WMI mice. miR-214-3p is able to bind to the 3' region of the NLRP-3 inflammasome compartment NEK7, preventing the transcription of NEK7 mRNA. As a result, in WMI mice, the lack of miR-214-3p leads to the accumulation of NEK7 which supports NLRP 3 inflammasome activation, microglial pyroptosis, and white matter pathogenesis.

Dendritic Spine in Autism Genetics: Whole-Exome Sequencing Identifying De Novo Variant of CTTNBP2 in a Quad Family Affected by Autism Spectrum Disorder.

Autism spectrum disorder (ASD) affects around 1% of children with no effective blood test or cure. Recent studies have suggested that these are neurological disorders with a strong genetic basis and that they are associated with the abnormal formation of dendritic spines. Chromosome microarray (CMA) together with high-throughput sequencing technology has been used as a powerful tool to identify new candidate genes for ASD. In the present study, CMA was first used to scan for genome-wide copy number variants in a proband, and no clinically significant copy number variants were found. Whole-exome sequencing (WES) was used further for genetic testing of the whole quad family affected by ASD, including the proband, his non-autistic sister, and his parents. Sanger sequencing and MassARRAY-based validation were used to identify and confirm variants associated with ASD. WES yielded a 151-fold coverage depth for each sample. A total of 98.65% of the targeted whole-exome region was covered at >20-fold depth. A de novo variant in CTTNBP2, p.M115T, was identified. The CTTNBP2 gene belongs to a family of ankyrin repeat domain-containing proteins associated with dendritic spine formation. Although CTTNBP2 has been associated with ASD, limited studies have been developed to identify clinically relevant de novo mutations of CTTNBP2 in children with ASD; family-based WES successfully identified a clinically relevant mutation in the CTTNBP2 gene in a quad family affected by ASD. Considering the neuron-specific expression of CTTNBP2 and its role in dendritic spine formation, our results suggest a correlation between the CTTNBP2 mutation and ASD, providing genetic evidence for ASD spine pathology. Although the present study is currently insufficient to support the assertion that the de novo mutation M115T in CTTNBP2 directly causes the autism phenotype, our study provides support for the assertion that this mutation is a candidate clinically relevant variant in autism.

Inductively coupled plasma mass spectrometry based urine metallome to construct clinical decision models for autism spectrum disorder.

BACKGROUND: The global prevalence of autism spectrum disorder (ASD) is on the rise, and high levels of exposure to toxic heavy metals may be associated with this increase. Urine analysis is a noninvasive method for investigating the accumulation and excretion of heavy metals. The aim of this study was to identify ASD-associated urinary metal markers. METHODS: Overall, 70 children with ASD and 71 children with typical development (TD) were enrolled in this retrospective case-control study. In this metallomics investigation, inductively coupled plasma mass spectrometry was performed to obtain the urine profile of 27 metals. RESULTS: Children with ASD could be distinguished from children with TD based on the urine metal profile, with ASD children showing an increased urine metal Shannon diversity. A metallome-wide association analysis was used to identify seven ASD-related metals in urine, with cobalt, aluminum, selenium, and lithium significantly higher, and manganese, mercury, and titanium significantly lower in the urine of children with ASD than in children with TD. The least absolute shrinkage and selection operator (LASSO) machine learning method was used to rank the seven urine metals in terms of their effect on ASD. On the basis of these seven urine metals, we constructed a LASSO regression model for ASD classification and found an area under the receiver operating characteristic curve of 0.913. We also constructed a clinical prediction model for ASD based on the seven metals that were different in the urine of children with ASD and found that the model would be useful for the clinical prediction of ASD risk. CONCLUSIONS: The study findings suggest that altered urine metal concentrations may be an important risk factor for ASD, and we recommend further exploration of the mechanisms and clinical treatment measures for such alterations.

Identifying Rare Genetic Variants of Immune Mediators as Risk Factors for Autism Spectrum Disorder.

Autism spectrum disorder (ASD) affects more than 1% of children, and there is no viable pharmacotherapeutic agent to treat the core symptoms of ASD. Studies have shown that children with ASD show changes in their levels of immune response molecules. Our previous studies have shown that ASD is more common in children with folate receptor autoantibodies. We also found that children with ASD have abnormal gut immune function, which was characterized by a significant increase in the content of immunoglobulin A and an increase in gut-microbiota-associated epitope diversity. These studies suggest that the immune mechanism plays an important role in the occurrence of ASD. The present study aims to systematically assess gene mutations in immune mediators in patients with ASD. We collected genetic samples from 72 children with ASD (2−12 years old) and 107 healthy controls without ASD (20−78 years old). We used our previously-designed immune gene panel, which can capture cytokine and receptor genes, the coding regions of MHC genes, and genes of innate immunity. Target region sequencing (500×) and bioinformatics analytical methods were used to identify variants in immune response genes associated with patients with ASD. A total of 4 rare variants were found to be associated with ASD, including HLA-B: p.A93G, HLA-DQB1: p.S229N, LILRB2: p.R322H, and LILRB2: c.956-4C>T. These variants were present in 44.44% (32/72) of the ASD patients and were detected in 3.74% (4/107) of the healthy controls. We expect these genetic variants will serve as new targets for the clinical genetic assessment of ASD, and our findings suggest that immune abnormalities in children with ASD may have a genetic basis.

Clinical Manifestations of Neonatal Hyperbilirubinemia Are Related to Alterations in the Gut Microbiota.

BACKGROUND AND PURPOSE: Neonatal hyperbilirubinemia, also known as neonatal jaundice, is a common and frequent clinical condition with a complex etiology that can lead to brain damage in severe cases. Early recognition of hyperbilirubinemia and timely intervention and treatment can help reduce the occurrence of sequelae. This study was conducted to identify whether the gut microbiota composition can distinguish neonates with hyperbilirubinemia. METHODS: Meconium samples were collected from 69 neonates with neonatal jaundice (NJ) and 69 age- and sex-matched neonates without clinically significant jaundice (healthy controls; HCs) for 16S rRNA gene sequencing and microbiome analysis. RESULTS: Compared with HCs, the Chao 1 richness index of the gut microbiota was significantly decreased in the NJ group. The relative abundance of the probiotic gut bacterium, Lactobacillus, was significantly lower in the NJ group than in the HC group, whereas the abundances of potentially harmful gut bacteria, such as Escherichia coli and Staphylococcus, were significantly higher in the NJ group than in HCs. Correlation of the gut microbiota and clinical indicators revealed a positive correlation between Escherichia coli/Staphylococcus and serum total bilirubin levels. Finally, the results of a random forest machine-learning method to evaluate the possibility of using NJ-associated gut microbiota compositions as potential NJ biomarkers revealed an area under the curve of 96.88%. CONCLUSIONS: The abundances of Escherichia coli and Staphylococcus were positively correlated with serum total bilirubin levels. Hence, the gut microbiota composition is a potential biomarker of NJ.

Machine learning approach identifies meconium metabolites as potential biomarkers of neonatal hyperbilirubinemia.

Background: The gut microbiota plays an important role in the early stages of human life. Our previous study showed that the abundance of intestinal flora involved in galactose metabolism was altered and correlated with increased serum bilirubin levels in children with jaundice. We conducted the present study to systematically evaluate alterations in the meconium metabolome of neonates with jaundice and search for metabolic markers associated with neonatal jaundice. Methods: We included 68 neonates with neonatal hyperbilirubinemia, also known as neonatal jaundice (NJ) and 68 matched healthy controls (HC), collected meconium samples from them at birth, and performed metabolomic analysis via liquid chromatography-mass spectrometry. Results: Gut metabolites enabled clearly distinguishing the neonatal jaundice (NJ) and healthy control (HC) groups. We also identified the compositions of the gut metabolites that differed significantly between the NJ and HC groups; these differentially significant metabolites were enriched in aminyl tRNA biosynthesis; pantothenic acid and coenzyme biosynthesis; and the valine, leucine and isoleucine biosynthesis pathways. Gut branched-chain amino acid (BCAA) levels were positively correlated with serum bilirubin levels, and the area under the receiver operating characteristic curve of the random forest classifier model based on BCAAs, proline, methionine, phenylalanine and total bilirubin reached 96.9%, showing good potential for diagnostic applications. Machine learning-based causal inference analysis revealed the causal effect of BCAAs on serum total bilirubin and NJ. Conclusions: Altered gut metabolites in neonates with jaundice showed that increased BCAAs and total serum bilirubin were positively correlated. BCAAs proline, methionine, phenylalanine are potential biomarkers of NJ.

Efficacy of human immunoglobulin injection and effects on serum inflammatory cytokines in neonates with acute lung injury.

The present study aimed to explore the efficacy of intravenous immunoglobulin (IVIG) injection in neonates with acute lung injury (ALI) and assess its effects on serum inflammatory cytokine levels. The research subjects were 140 neonates with ALI who were evenly distributed into a control group (COG) and a study group (STG). The COG patients were treated routinely, whereas patients in the STG were administered IVIG in addition to the standard treatment received by the COG. The arterial partial pressure of oxygen (PaO2), PaO2/fraction of inspired oxygen (FIO2), mechanical ventilation time and hospitalization time were compared between the two groups. ELISA was used to determine the levels of interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) in the patients before treatment and at 12, 24 and 36 h after treatment. The Kaplan-Meier method was used to analyze the survival of the patients, including their survival for 30 days after treatment. The patients were divided into high and low cytokine expression groups based on their mean expression levels of serum IL-6 and TNF-α before treatment. After treatment, PaO2 and PaO2/FiO2 were significantly higher and mechanical ventilation and hospitalization time were reduced in the STG in comparison with the COG (all P<0.001). At 12, 24 and 36 h after treatment, serum IL-6 and TNF-α levels in the STG were lower than those in the COG (both P<0.05). The 30-day survival rate after treatment was not significantly different between the two groups (P>0.05). The 30-day survival rate in the high IL-6 and high TNF-α expression COG was lower than that in the low IL-6 and low TNF-α expression COG (both P<0.05). The results of the present study indicate that IVIG may improve pulmonary gas exchange, shorten the course of disease and reduce the inflammatory response in neonates with ALI.

Machine learning applied to serum and cerebrospinal fluid metabolomes revealed altered arginine metabolism in neonatal sepsis with meningoencephalitis.

BACKGROUND: Neonatal sepsis with meningoencephalitis is a common complication of sepsis, which is a leading cause of neonatal death and neurological dysfunction. Early identification of neonatal sepsis with meningoencephalitis is particularly important for reducing brain damage. We recruited 70 patients with neonatal sepsis, 42 of which were diagnosed as meningoencephalitis, and collected cerebrospinal fluid (CSF) and serum samples. The purpose of this study was to find neonatal sepsis with meningoencephalitis-related markers using unbiased metabolomics technology and artificial intelligence analysis based on machine learning methods. RESULTS: We found that the characteristics of neonatal sepsis with meningoencephalitis were manifested mainly as significant decreases in the concentrations of homo-l-arginine, creatinine, and other arginine metabolites in serum and CSF, suggesting possible changes in nitric oxide synthesis. The antioxidants taurine and proline in the serum of the neonatal sepsis with meningoencephalitis increased significantly, suggesting abnormal oxidative stress. Potentially harmful bile salts and aromatic compounds were significantly increased in the serum of the group with meningoencephalitis. We compared different machine learning methods and found that the lasso algorithm performed best. Combining the lasso and XGBoost algorithms was successful in predicting the concentration of homo-l-arginine in CSF per the concentrations of metabolite markers in the serum. CONCLUSIONS: On the basis of machine learning combined with analysis of the serum and CSF metabolomes, we found metabolite markers related to neonatal sepsis with meningoencephalitis. The characteristics of neonatal sepsis with meningoencephalitis were manifested mainly by changes in arginine metabolism and related changes in creatinine metabolism.

Knockdown of G protein-coupled receptor-17 (GPR17) facilitates the regeneration and repair of myelin sheath post-periventricular leukomalacia (PVL).

The G protein-coupled receptor-17 (GPR17) plays an important role in regulating the differentiation of oligodendrocytes and remyelination, which is a key negative regulator of oligodendrocyte differentiation. The present study aimed to investigate the function of GPR17 in the white matter of periventricular leukomalacia (PVL) neonatal rats. The PVL model was established in 2-day old neonatal rats by intracerebral injection of LPS (1 mg/kg). Compared to sham, GPR17 was significantly upregulated, while Olig1 was significantly downregulated in the PVL group at 1 d, 3 days, and 7 days post-modeling. Compared to the negative control (NC) group, the expression of GPR17 was suppressed, while that of Olig1 was elevated in the siRNA-GPR17 group as time progressed; the opposite results were observed in the GPR17-overexpressed group. Decreased formation of myelin sheaths as well as poor structure and loose arrangement were observed in the PVL group. Similar observations were found in the PVL + siRNA-GPR17 group at 1 d and 3 days post-modeling. However, on day 7 post-modeling, a dramatic increase in the formation of myelin sheath as well as thicker myelin sheaths were observed in the PVL + siRNA-GPR17 group. The migration ability of oligodendrocyte progenitor cells (OPCs) isolated from animals was found to be significantly suppressed in the GPR17-overexpressed group, accompanied by the downregulation of Olig1. Taken together, the regeneration and repair of myelin sheaths post-PVL white matter injury were induced by downregulating the GPR17 gene, which elevated the expression of Olig1.

Association of serum bilirubin in newborns affected by jaundice with gut microbiota dysbiosis.

BACKGROUND AND AIMS: Breast milk jaundice (BMJ) is common and benign, but neonatal cholestasis (NC) is rare and not benign, so early differentiation between NC and non-NC jaundice is important and may facilitate diagnosis and treatment. Gut microbiota plays an important role in enterohepatic circulation, which in turn plays an important role in the secretion of bilirubin. We aimed to determine the composition of gut microbiota in patients with NC and BMJ, and to identify the gut microbiota composition associated with NC and BMJ. METHODS: Data on age, gender, delivery, feeding mode, serum total bilirubin, direct bilirubin, and liver function were collected for NC patients, BMJ patients and healthy controls, respectively. Shotgun metagenomic sequencing and metagenome-wide association were performed. RESULTS: Forty NC patients, 16 patients affected by BMJ, and 14 healthy controls (CON) without jaundice were enrolled. A significant increase in species richness, especially Bacteroides, was found in NC patients. The abundances of potentially pathogenic species and KEGG orthologies (KOs) of virulence factor genes were positively correlated with serum bilirubin level. The abundances of nine species of Bifidobacterium and three KOs of galactose metabolism were significantly decreased in the jaundice group (NC and BMJ) and were negatively correlated with serum bilirubin level. CONCLUSIONS: The gut microbiota in NC patients is characterized by a significant increase in species richness, possibly due to the proliferation of potentially pathogenic species. Additionally, the gut microbiota in jaundice patients is characterized by a decreased abundance of Bifidobacterium. Decreased Bifidobacterium has been associated with elevated bilirubin and abnormal gut microbiota galactose metabolic pathway. Further, ten bacteria species were identified as potential biomarker of jaundice. KEY POINTS: Question Is there any alteration of gut microbiotain neonatal cholestasis patients? Does gut microbiota have any involvement in the occurrence of neonatal cholestasis or breast milk jaundice? Findings The alteration of gut microbiota in neonatal cholestasis patients mainly manifested as a significant increase in species richness and an increased abundance of potentially pathogenic species, while the main manifestation in jaundice patients was a significant decrease in Bifidobacterium which may be involved in the metabolism of bilirubin through the galactose metabolic pathway. Meaning The results suggest that an imbalance of gut microbiota exist in neonatal cholestasis and breast milk jaundice patients, primarily in the form of a substantial reduction in the abundance of Bifidobacterium, suggesting the possibility of intervention treatment for neonatal cholestasis and breast milk jaundice by supplementing probiotics.

Erythropoietin Gene Polymorphism rs551238 is Associated with a Reduced Susceptibility to Brain Injury in Preterm Infants.

BACKGROUND: Single Nucleotide Polymorphisms (SNPs) in the Erythropoietin (EPO) promoter region have been shown to influence EPO protein expression, and high blood levels of EPO are associated with an increased risk of brain injury in very preterm infants. Here, we investigated the genotype distributions and association of three EPO gene polymorphisms (rs1617640, rs551238, and rs507392) with the risk of brain injury in preterm infants. METHODS: 304 preterm infants with a gestational age of 28 to 34 weeks were enrolled in this study. Brain injury was evaluated by brain ultrasound and MRI examination. EPO gene Single- Nucleotide Polymorphisms (SNPs) were genotyped by the Agena MassARRAY system, and their association with brain injury susceptibility in preterm infants was analyzed. RESULTS: EPO polymorphism rs551238 showed a significant difference in the genotypic distributions between the brain injury group and the control group, and was significantly correlated with reduced susceptibility to brain injury in preterm infants according to the results obtained from both the additive model (OR = 0.520, 95% CI: 0.339-0.799, P = 0.003) and the dominant model (OR = 0.523, 95% CI: 0.332-0.853, P = 0.009). EPO polymorphisms rs1617640 and rs507392 did not meet the Hardy-Weinberg equilibrium in the study population (P < 0.05) and were, thus, not subjected to further analysis for their impacts on brain injuries. CONCLUSION: The "C" allele of rs551238 was correlated with a reduced risk of brain injury in preterm infants which may serve as a potential marker for brain injury prediction in preterm infants.