Gut dysbiosis is closely associated with obesity and related metabolic diseases including type 2 diabetes (T2D) and nonalcoholic fatty liver disease (NAFLD). The gut microbial features and biomarkers have been increasingly investigated in many studies, which require further validation due to the limited sample size and various confounding factors that may affect microbial compositions in a single study. So far, it lacks a comprehensive bioinformatics pipeline providing automated statistical analysis and integrating multiple independent studies for cross-validation simultaneously.
This study aimed to explore the relationship between the phenotype and genotype of congenital hypothyroidism (CH) caused by dual oxidase 2 (DUOX2) mutation in Chinese children, and to investigate the genetic causes of permanent and transient hypothyroidism through next-generation genetic testing technology and long-term clinical follow-up data.
Prader-Willi syndrome (PWS) is the first multi-systemic genetic disorder known to be caused by imprinting defect. The clinical manifestations of PWS vary with age. At the prenatal stage, decreased fetal movements are frequent. The major clinical manifestations during neonatal period include hypotonia, weak cry, poor suck and feeding difficulties. Growth retardation and delayed language and motor development are observed during infancy. Short stature, small hands and feet, cognitive deficiency are noticed in the childhood. At adolescence, prominent growth retardation, obesity, gonadal dysplasia, abnormal behavior and learning difficulties are the major issues. Morbid obesity caused by insatiable appetite is the major factor for prognosis. Early diagnosis and intervention play a significance role in improving the quality of life, preventing serious complications and prolonging survival. This guideline covers the clinical manifestations, developmental process, pathogenesis, molecular diagnosis and genetic counseling of PWS, with an aim to provide reference for clinicians for early identification, proper intervention and genetic counseling for this disease.
AimsWilliams-Beuren syndrome (WBS; OMIM no.194050) is a multisystemic neurodevelopmental disorder caused by a hemizygous deletion of 1.55Mb on chromosome 7q11.23spanning 28 genes.Here we report a patient showing mild WBS physical phenotype, who carries a longer 21Mb atypical deletion. MethodsGenomic DNA from the proband was extracted from peripheral blood leukocyte.Karyotype analysis was performed on metaphase cells.Array-based comparative genomic hybridization of DNA from the patient's peripheral blood lymphocytes was performed.
Mandibulofacial dysostosis with microcephaly (MFDM) is characteristic of multiple skeletal anomalies comprising craniofacial anomalies/dysplasia, microcephaly, dysplastic ears, choanal atresia, and short stature. Heterozygous loss of function variants of EFTUD2 was previously reported in MFDM; however, the mechanism underlying EFTUD2-associated skeletal dysplasia remains unclear.We identified a novel frameshift variant of EFTUD2 (c.1030_1031delTG, p.Trp344fs*2) in an MFDM Chinese patient with craniofacial dysmorphism including ear canal structures and microcephaly, mild intellectual disability, and developmental delay. We generated a zebrafish model of eftud2 deficiency, and a consistent phenotype consisting of mandibular bone dysplasia and otolith loss was observed. We also showed that EFTUD2 deficiency significantly inhibited proliferation, differentiation, and maturation in human calvarial osteoblast (HCO) and human articular chondrocyte (HC-a) cells. RNA-Seq analysis uncovered activated TP53 signaling with increased phosphorylation of the TP53 protein and upregulation of five TP53 downstream target genes (FAS, STEAP3, CASP3, P21, and SESN1) both in HCO and in eftud2-/- zebrafish. Additionally, inhibition of p53 by morpholino significantly reduced the mortality of eftud2-/- larvae.Our results confirm a novel de novo variant of the EFTUD2 gene and suggest that EFTUD2 may participate in the maturation and differentiation of osteoblasts and chondrocytes, possibly via activation of the TP53 signaling pathway. Thus, mutations in this gene may lead to skeletal anomalies in vertebrates.
Diabetes mellitus is now fast emerging as one of the biggest health catastrophes the world has ever witnessed. It has huge global and societal implications, particularly in developing countries such as China and India [1]. China is now bring with it potential massive increase in type 1 diabetes (2-5% per annum increases in incidence in the world's most populous countries) and childhood obesity (with its associated insulin resistance and type 2 diabetes)[2]. A nine-year prospective study on the incidence of childhood type 1 diabetes mellitus in China by the WHO DiaMond Project China Participating Center and Chinese Academy of Preventive Medicine (CAPM) showed that between 1988 and 1996, the overall incidence rate (IR) was 0.59 per 100,000 person-year. The IR was 0.52/100,000 (95% CI: 0.50-0.54) for males and 0.66/100,000 (95% CI: 0.64-0.68) for females[3]. We recently conducted a nationwide study to evaluate the state and the trend of diabetes based on hospital inpatient data from China’s 14 medical centers and pre-diabetes among obese children from October 1995 through September 2010. We found that in the past 15 years, the prevalence of Chinese childhood diabetes increased dramatically and the growth of T2DM has exceeded T1DM. T1DM has occurrence rate of 89.6% of all diabetes and is still the dominant form of diabetes in children. The prevalence of T1DM was relatively stable from the year of 1995 to 2005, but increased obviously in the recent 5 years according to the hospital records in China. The clear increasing trend from Southwest to East and North disclosed strong regional differences (T1DM from 59.76 to 80.02 and 120.45, T2DM from 2.52 to 3.77 and 15.64 (1/100,000) (p all < 0.0001). Well developed areas had a higher prevalence compared to less developed areas {T1DM: 151.51 vs. 32.2; T2DM: 15.16 vs. 1.64 and other types: 7.54 vs. 0.42 (1/100,000)}. An important finding in this study is that the prevalence of childhood T2DM in China doubled from 4.1/100,000 in the first 5 years to 10.0/100,000 in the recent 5 years, which was 7.44 % of total diabetics. Though the ratio is still lower than that of America (8%-46%)[4] , the trend is clear and the consequences are serious because China has the largest population in the world. Another important finding in this study showed obese children are potential pools of T2DM. Of the 3153 obese children, 18.24% had IFG alone, 5.99% had IGT, 4% had combined IFG and IGT.
Osteogenesis imperfecta (OI) is a genetic disease with an estimated prevalence of 1 in 13,500 and 1 in 9700. The classification into subtypes of OI is important for prognosis and management. In this study, we established a clinical severity prediction model depending on multiple features of variants in COL1A1/2 genes.Ninety percent of OI cases are caused by pathogenic variants in the COL1A1/COL1A2 gene. The Sillence classification describes four OI types with variable clinical features ranging from mild symptoms to lethal and progressively deforming symptoms.We established a prediction model of the clinical severity of OI based on the random forest model with a training set obtained from the Human Gene Mutation Database, including 790 records of the COL1A1/COL1A2 genes. The features used in the prediction model were respectively based on variant-type features only, and the optimized features.With the training set, the prediction results showed that the area under the receiver operating characteristic curve (AUC) for predicting lethal to severe OI or mild/moderate OI was 0.767 and 0.902, respectively, when using variant-type features only and optimized features for COL1A1 defects, 0.545 and 0.731, respectively, for COL1A2 defects. For the 17 patients from our hospital, prediction accuracy for the patient with the COL1A1 and COL1A2 defects was 76.5% (95% CI: 50.1-93.2%) and 88.2% (95% CI: 63.6-98.5%), respectively.We established an OI severity prediction model depending on multiple features of the specific variants in COL1A1/2 genes, with a prediction accuracy of 76-88%. This prediction algorithm is a promising alternative that could prove to be valuable in clinical practice.
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