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Summary The next-generation sequencing brought opportunities for the diagnosis of genetic disorders due to its high-throughput capabilities. However, the majority of existing methods were limited to only sequencing candidate variants, and the process of linking these variants to a diagnosis of genetic disorders still required medical professionals to consult databases. Therefore, we introduce diseaseGPS, an integrated platform for the diagnosis of genetic disorders that combines both phenotype and genotype data for analysis. It offers not only a user-friendly GUI web application for those without a programming background but also scripts that can be executed in batch mode for bioinformatics professionals. The genetic and phenotypic data are integrated using the ACMG-Bayes method and a novel phenotypic similarity method, to prioritize the results of genetic disorders. diseaseGPS was evaluated on 6085 cases from Deciphering Developmental Disorders project and 187 cases from Shanghai Children's hospital. The results demonstrated that diseaseGPS performed better than other commonly used methods. Availability and implementation diseaseGPS is available to freely accessed at https://diseasegps.sjtu.edu.cn with source code at https://github.com/BioHuangDY/diseaseGPS. [ABSTRACT FROM AUTHOR]

Background: Abnormal androgen receptor (AR) genes can cause androgen insensitivity syndrome (AIS), and AIS can be classified into complete androgen insensitivity syndrome (CAIS), partial androgen insensitivity syndrome (PAIS) and mild AIS. We investigated the characteristics of clinical manifestations, serum sex hormone levels and AR gene mutations of 39 AIS patients, which provided deeper insight into this disease. Methods: We prospectively evaluated 39 patients with 46, XY disorders of sex development (46, XY DSD) who were diagnosed with AIS at the Department of Endocrinology of Shanghai Children's Hospital from 2014 to 2019. We analysed clinical data from the patients including hormone levels and AR gene sequences. Furthermore, we screened the AR gene sequences of the 39 AIS patients to identify probable mutations. Results: The 39 AIS patients came from 37 different families; 19 of the patients presented CAIS, and 20 of them presented PAIS. The CAIS patients exhibited a higher cryptorchidism rate than the PAIS (100 and 55%, P = 0.001). There were no significant difference between the CAIS and PAIS groups regarding the levels of inhibin B (INHB), sex hormone-binding globulin (SHBG), basal luteinizing hormone (LH), testosterone (T), or basal dihydrotestosterone (DHT), the T:DHT ratio, DHT levels after human chorionic gonadotropin (HCG) stimulation or T levels after HCG stimulation. However, the hormone levels of AMH (P = 0.010), peak LH (P = 0.033), basal FSH (P = 0.009) and peak FSH (P = 0.033) showed significant differences between the CAIS group and the PAIS group. Twenty-one reported pathogenic and 9 novel AR mutations were identified. Spontaneous AR mutations were found in 5 AIS patients, and 21 patients inherited mutations from their mothers, who carried heterozygous mutations. Conclusions: Forty-six XY DSD patients with cryptorchidism and female phenotypes were highly suspected of having AIS. We demonstrated that CAIS patients could not be distinguished by their hormone levels alone. Compared with PAIS patients, CAIS patients exhibited higher basal FSH, peak FSH, and peak LH hormone levels but lower AMH expression. We identified 21 reported pathogenic AR mutations and 9 novel AR mutations that led to different types of AIS. Missense mutations were the major cause of AIS and mostly occurred in exon 7 of the AR gene. These findings provided deeper insight into the diagnosis and classification of AIS and will even contributed to its clinical assessment. [ABSTRACT FROM AUTHOR]

The aim of this study was to investigate incidence trend of childhood type 1 diabetes in Shanghai, a megalopolis in east China. We established a population-based retrospective registry for the disease in the city's registered population during 1997-2011 and collected 622 incident type 1 diabetes in children aged 0-14 years. Standardized incidence rates and 95 % CI were estimated by applying the capture-recapture method and assuming Poisson distribution. Incidence trend was analyzed using the Poisson regression model. The mean annual incidence of childhood type 1 diabetes was 3.1 per 100,000 person-years. We did not observe significant difference in incidence between boys and girls. The incidence is unstable and had a mean annual increase 14.2 % per year during the studied period. A faster annual increase was observed in boys, warmer seasons, and in the outer regions of the city. If present trends continue, the number of new type 1 diabetes cases will double from 2016 to 2020, and prevalent cases will sextuple by 2025. Our results showed the incidence of childhood type 1 diabetes was rising rapidly in Shanghai. More studies are needed to analyze incidence changes in other regions of China for appropriate allocation of healthcare resources. [ABSTRACT FROM AUTHOR]