Neurodevelopmental delay accompanied unexplained dyspnea is a highly lethal disease in clinic. This study is to investigate the performance characteristics of trio whole exome sequencing (Trio-WES) in a pediatric setting by presenting our patient cohort and displaying the diagnostic yield. A total of 31 pediatric patients showing neurodevelopmental delay accompanied unexplained dyspnea were admitted to our hospital and referred for molecular genetic testing using Trio-WES. Eight genes namely MMACHC, G6PC, G6PT, ETFDH, OTC, NDUFAF5, SLC22A5, and MAGEL2 were suspected to be responsible for the onset of the clinical symptoms and 6 variants were novel. Standard interpretation according to ACMG guideline showed that the variants were pathogenic. Finally, diagnosis of methylmalonic aciduria and homocystinuria, glycogen storage disease, ornithine transcarbamylase deficiency, glutaric acidemia II, mitochondrial complex 1 deficiency, carnitine deficiency, and Schaaf-Yang syndrome was made in 12 out of the 31 patients. Trio-WES is an effective means for molecular diagnosis of infantile neurodevelopmental delay accompanied unexplained dyspnea. As for molecular etiology identification, when routine potential monogenetic inheritance patterns including de novo, autosomal recessive, autosomal dominant, and X-linked recessive inheritance analysis is negative, physicians should take into account imprinted genes.

Silver–Russell syndrome (SRS) is a rare, but well-recognized disease characterized by growth disorder. To date, there are two reports arguing IGF2 mutation for the onset of SRS. Herein, we present another sporadic case harboring IGF2 mutation. The male proband was the first and only child of a non-consanguineous Chinese couple. He was small for gestational age, with relative macrocephaly at birth. Severe feeding difficulties, low feeding, and growth retardation were revealed during neonatal period. At 4.5 years old, obvious body asymmetry was noted. Whole exome sequencing identified a novel de novo c.101G > A (p.Gly34Asp, NM_000612) variant in IGF2 and Sanger sequencing validated the variant. Amplification refractory mutation system polymerase chain reaction demonstrated that the IGF2 variant was on the paternal allele. Alignment shows the variant is evolutionarily conserved. Structural modeling argues that the variant site might be important for the binding of IGF2 to its receptor. Our study provides further evidence that IGF2 mutation may be another mechanism of SRS, and we consider that IGF2 should be included in a disease specific gene panel in case it is designed for SRS routine diagnostics.

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Multiple mitochondrial dysfunctions syndrome (MMDS) is an autosomal recessive disorder of systemic energy metabolism. This study is to present the diagnosis of two MMDS Chinese sufferers. Physical and auxiliary examination was performed. Next generation sequencing (NGS) was conducted to identify candidate causal genes and Sanger sequencing was adopted to validate the variants detected. Fluorescence quantitative polymerase chain reaction (FQ-PCR) amplification was carried out to testify allelic loss existence. Structural investigation was performed to study the possibility of the candidate variants for disease onset. Physical examination showed that the children were with neurological impairment. Auxiliary examination demonstrated energy metabolism disturbance and abnormal brain signals. NGS found that the probands had homozygous mutation of c.545 + 5G > A and compound heterozygous variants of exon 4 deletion and c.721G > T in NFU1, respectively. NFU1 was considered as candidate molecular etiology and indicating that the kids were with MMDS. Sanger sequencing confirmed the variants. FQ-PCR amplification characterized that patient 1 had a de novo allele mutation while patient 2 inherited from his parents. Structural investigation demonstrated that the variants were possible for MMDS occurrence. This is the first report of patients diagnosed as MMDS with novel mutation types from the Asia-Pacific region.

Next-generation sequencing (NGS) has become a promising approach for tumor somatic mutation detection. However, stringent validation is required for its application on clinical specimens, especially for low-quality formalin-fixed paraffin-embedded (FFPE) tissues. Here, we validated the performance of an amplicon-based targeted NGS assay, OncoAim™ DNA panel, on both commercial reference FFPE samples and clinical FFPE samples of Chinese colorectal cancer (CRC) patients. Then we profiled the mutation spectrum of 648 Chinese CRC patients in a multicenter study to explore its clinical utility. This NGS assay achieved 100% test specificity and 95-100% test sensitivity for variants with mutant allele frequency (MAF) ≥ 5% when median read depth ≥ 500×. The orthogonal methods including amplification refractory mutation system (ARMS)-PCR and Sanger sequencing validated that NGS generated three false negatives (FNs) but no false positives (FPs) among 516 clinical samples for KRAS aberration detection. Genomic profiling of Chinese CRC patients with this assay revealed that 63.3% of the tumors harbored clinically actionable alterations. Besides the commonly mutated genes including TP53 (52.82%), KRAS (46.68%), APC (24.09%), PIK3CA (18.94%), SMAD4 (9.47%), BRAF (6.15%), FBXW7 (5.32%), and NRAS (4.15%), other less frequently mutated genes were also identified. Statistically significant association of specific mutated genes with certain clinicopathological features was detected, e.g., both BRAF and PIK3CA were more prevalent in right-side CRC (p < 0.001 and p = 0.002, respectively). We concluded this targeted NGS assay is qualified for clinical practice, and our findings could help the diagnosis and prognosis of Chinese CRC patients.

BackgroundSitosterolemia (STSL), also known as phytosterolemia, is a rare autosomal recessive hereditary disease caused by mutations in the ABCG5 or ABCG8 genes. The disease is a result of disorders in lipoprotein metabolism, and is characterized by tendinous and tuberous xanthomas, elevated plasma cholesterol and phytosterol levels, and thrombocytopenia and hemolytic anemia in several patients. The manifestations of STSL are diverse and can easily be misdiagnosed. In recent years, cases of this disease in children have been reported in succession. There is therefore a need for clinicians to improve identification of STSL and perform early intervention.MethodsWe evaluated four children with STSL caused by genetic mutations in ABCG5 or ABCG8, as well as their family members, by analyzing their clinical characteristics and performing Trio‐whole exome sequencing. The biological consequences of the mutations were analyzed using various bioinformatics software. We also analyzed the consequences of a mutation commonly observed in STSL patients on the structure of the protein involved.ResultsWe identified five previously unreported pathogenic mutations of different phenotypes of STSL: ABCG5 NM_022436:c.1337G>A; ABCG8 NM_022437:c.965‐1G>A, c.323‐1G>C, c.1418C>G and c.1534G>A. We also report the structural changes brought about by a mutation common in STSL patients, as well as the possible consequences of these changes.ConclusionsOur findings further broaden the genotypic and phenotypic profiles of the onset of STSL in the pediatric population and provide information for the diagnosis and treatment of this disease.

To improve device robustness, a highly desirable key feature of a competitive data-driven acoustic scene classification (ASC) system, a novel two-stage system based on fully convolutional neural networks (CNNs) is proposed. Our two-stage system leverages on an ad-hoc score combination based on two CNN classifiers: (i) the first CNN classifies acoustic inputs into one of three broad classes, and (ii) the second CNN classifies the same inputs into one of ten finergrained classes. Three different CNN architectures are explored to implement the two-stage classifiers, and a frequency sub-sampling scheme is investigated. Moreover, novel data augmentation schemes for ASC are also investigated. Evaluated on DCASE 2020 Task 1a, our results show that the proposed ASC system attains a state-of-theart accuracy on the development set, where our best system, a twostage fusion of CNN ensembles, delivers a 81.9% average accuracy among multi-device test data, and it obtains a significant improvement on unseen devices. Finally, neural saliency analysis with class activation mapping (CAM) gives new insights on the patterns learnt by our models.