Corrigendum: A copy number variation morbidity map of developmental delay

Comparative Proteomic Profiling and Biomarker Identification of Traditional Chinese Medicine-Based HIV/AIDS Syndromes

Given the challenges in exploring lifelong therapy with little side effect for human immunodeficiency virus infection and acquired immune deficiency syndrome (HIV/AIDS) cases, there is increasing interest in developing traditional Chinese medicine (TCM) treatments based on specific TCM syndrome. However, there are few objective and biological evidences for classification and diagnosis of HIV/AIDS TCM syndromes to date. In this study, iTRAQ-2DLC-MS/MS coupled with bioinformatics were firstly employed for comparative proteomic profiling of top popular TCM syndromes of HIV/AIDS: accumulation of heat-toxicity (AHT) and Yang deficiency of spleen and kidney (YDSK). It was found that for the two TCM syndromes, the identified differential expressed proteins (DEPs) as well as their biological function distributions and participation in signaling pathways were significantly different, providing biological evidence for the classification of HIV/AIDS TCM syndromes. Furthermore, the TCM syndrome-specific DEPs were confirmed as biomarkers based on western blot analyses, including FN1, GPX3, KRT10 for AHT and RBP4, ApoE, KNG1 for YDSK. These biomarkers also biologically linked with the specific TCM syndrome closely. Thus the clinical and biological basis for differentiation and diagnosis of HIV/AIDs TCM syndromes were provided for the first time, providing more opportunities for stable exertion and better application of TCM efficacy and superiority in HIV/AIDS treatment.

Copy Number Variants in Patients with Autism and Additional Clinical Features: Report of VIPR2 Duplication and a Novel Microduplication Syndrome

Autism is a common neurodevelopmental disorder estimated to affect 1 in 68 children. Many studies have shown the role of copy number variants (CNVs) as a major contributor in the etiology of autism with the overall detection rate of about 10-15 % and over 20 % when syndromic forms of autism exist. In this study, we used array CGH to identify CNVs in 15 Iranian patients with autism. To elevate our diagnostic yield, we selected the sporadic patients who had additional clinical features including intellectual disability (ID), craniofacial anomaly, and seizure. Six out of 15 patients showed clinically relevant CNVs including pathogenic and likely pathogenic copy number gains or losses. We report a novel gene duplication syndrome (10q21.2q21.3 microduplication) and present a new evidence for VIPR2 duplication, as a candidate gene for autism. Furthermore, we describe the first manifesting carrier female with deletion of SLC6A8 and BCAP31 genes on Xq28. Our findings suggest that there might be a higher prevalence of clinically significant CNVs in patients with autism and additional clinical manifestations. The CNV analysis in such patients could lead to the discovery of novel syndromes as well as unraveling the etiology of autism.

Systematic identification of phenotypically enriched loci using a patient network of genomic disorders

Background

Network medicine is a promising new discipline that combines systems biology approaches and network science to understand the complexity of pathological phenotypes. Given the growing availability of personalized genomic and phenotypic profiles, network models offer a robust integrative framework for the analysis of "omics" data, allowing the characterization of the molecular aetiology of pathological processes underpinning genetic diseases.

Methods

Here we make use of patient genomic data to exploit different network-based analyses to study genetic and phenotypic relationships between individuals. For this method, we analyzed a dataset of structural variants and phenotypes for 6,564 patients from the DECIPHER database, which encompasses one of the most comprehensive collections of pathogenic Copy Number Variations (CNVs) and their associated ontology-controlled phenotypes. We developed a computational strategy that identifies clusters of patients in a synthetic patient network according to their genetic overlap and phenotype enrichments.

Results

Many of these clusters of patients represent new genotype-phenotype associations, suggesting the identification of newly discovered phenotypically enriched loci (indicative of potential novel syndromes) that are currently absent from reference genomic disorder databases such as ClinVar, OMIM or DECIPHER itself.

Conclusions

We provide a high-resolution map of pathogenic phenotypes associated with their respective significant genomic regions and a new powerful tool for diagnosis of currently uncharacterized mutations leading to deleterious phenotypes and syndromes.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2569-6) contains supplementary material, which is available to authorized users.