Etiology analysis for term newborns with severe hyperbilirubinemia in eastern Guangdong of China

BACKGROUND Neonatal hyperbilirubinemia is one of the common diseases of newborns that typically presents with yellow staining of skin,resulting in sequelaes such as hearing loss,motor and intellectual development disorders,and even death.The pathogenic factors of neonatal hyperbilirubinemia are complex.Different cases of hyperbilirubinemia may have a single or mixed etiology.AIM To explore the etiological characteristics of severe hyperbilirubinemia in term newborns of eastern Guangdong of China.METHODS Term newborns with severe hyperbilirubinemia in one hospital from January 2012 to December 2021 were retrospectively analyzed.The etiology was determined according to the laboratory results and clinical manifestations.RESULTS Among 1602 term newborns with hyperbilirubinemia in eastern Guangdong of China,32.20%(580/1602)was severe hyperbilirubinemia.Among the causes of severe hyperbilirubinemia,neonatal hemolysis accounted for 15.17%,breast milk jaundice accounted for 12.09%,infection accounted for 10.17%,glucose-6-phosphate dehydrogenase(G6PD)deficiency accounted for 9.14%,and the coexistence of multiple etiologies accounted for 6.55%,unknown etiology accounted for 41.72%.ABO hemolysis and G6PD deficiency were the most common causes in the 20 cases with bilirubin encephalopathy.94 severe hyperbilirubinemia newborns were tested for uridine diphosphate glucuronosyl transferase 1A1(UGT1A1)*6 variant(rs4148323,c.211G>A,p.Arg71Gly),9 cases were 211 G to A homozygous variant,37 cases were 211 G to A heterozygous variant,and 48 cases were wild genotypes.CONCLUSION The main cause for severe hyperbilirubinemia and bilirubin encephalopathy in eastern Guangdong of China were the hemolytic disease of the newborns,G6PD deficiency and infection.UGT1A1 gene variant was also a high-risk factor for neonatal hyperbilirubinemia.Targeted prevention and treatment according to the etiology may reduce the occurrence of bilirubin encephalopathy and kernicterus.

Clinical features and genetic variations of severe neonatal hyperbilirubinemia:Five case reports

BACKGROUND Neonatal hyperbilirubinemia is a common problem faced by pediatricians.The role of genetic factors in neonatal jaundice has been gradually recognized.This study aims to identify genetic variants that influence the bilirubin level in five patients using next-generation sequencing(NGS).CASE SUMMARY Five neonates with severe hyperbilirubinemia were retrospectively studied.They exhibited bilirubin encephalopathy,hypothyroidism,ABO blood type incompatibility hemolysis,glucose-6-phosphate dehydrogenase(G6PD)deficiency and premature birth,respectively.A customized 22-gene panel was designed,and NGS was carried out for these neonates.Eight variations(G6PD c.G1388A,HBA2 c.C369G,ABCC2 c.C3825G,UGT1A1 c.G211A,SPTB c.A1729G,EPB41 c.G520A,c.1213-4T>G and c.A1474G)were identified in these five neonates.Genetic mutations of these genes are associated with G6PD deficiency,thalassemia,Dubin-Johnson syndrome,Gilbert syndrome,hereditary spherocytosis,and hereditary elliptocytosis.One of the neonates was found to have compound variants of the EPB41 splice site c.1213-4T>G and c.G520A(p.E174K),but no elliptocyte was seen on his blood smear of 4 years old.CONCLUSION Pathological factors of severe neonatal hyperbilirubinemia are complicated.Genetic variants may play an important role in an increased risk of neonatal hyperbilirubinemia,and severe jaundice in neonates may be related to a cumulative effect of genetic variants.

FATOC:Bug Isolation Based Multi-Fault Localization by Using OPTICS Clustering

Bug isolation is a popular approach for multi-fault localization(MFL),where all failed test cases are clustered into several groups,and then the failed test cases in each group combined with all passed test cases are used to localize only a single fault.However,existing clustering algorithms cannot always obtain completely correct clustering results,which is a potential threat for bug isolation based MFL approaches.To address this issue,we first analyze the influence of the accuracy of the clustering on the performance of MFL,and the results of a controlled study indicate that using the clustering algorithm with the highest accuracy can achieve the best performance of MFL.Moreover,previous studies on clustering algorithms also show that the elements in a higher density cluster have a higher similarity.Based on the above motivation,we propose a novel approach FATOC(One-Fault-at-a-Time via OPTICS Clustering).In particular,FATOC first leverages the OPTICS(Ordering Points to Identify the Clustering Structure)clustering algorithm to group failed test cases,and then identifies a cluster with the highest density.OPTICS clustering is a density-based clustering algorithm,which can reduce the misgrouping and calculate a density value for each cluster.Such a density value of each cluster is helpful for finding a cluster with the highest clustering effectiveness.FATOC then combines the failed test cases in this cluster with all passed test cases to localize a single-fault through the traditional spectrum-based fault localization(SBFL)formula.After this fault is localized and fixed,FATOC will use the same method to localize the next single-fault,until all the test cases are passed.Our evaluation results show that FATOC can significantly outperform the traditional SBFL technique and a state-of-the-art MFL approach MSeer on 804 multi-faulty versions from nine real-world programs.Specifically,FATOC’s performance is 10.32%higher than that of traditional SBFL when using Ochiai formula in terms of metric A-EXAM.Besides,the results also indicate that,when checking 1%,3%and 5%statements of all subject programs,FATOC can locate 36.91%,48.50%and 66.93%of all faults respectively,which is also better than the traditional SBFL and the MFL approach MSeer.