Resolution of Disease Phenotypes Resulting from Multilocus Genomic Variation.

BACKGROUND: Whole-exome sequencing can provide insight into the relationship between observed clinical phenotypes and underlying genotypes. METHODS: We conducted a retrospective analysis of data from a series of 7374 consecutive unrelated patients who had been referred to a clinical diagnostic laboratory for whole-exome sequencing; our goal was to determine the frequency and clinical characteristics of patients for whom more than one molecular diagnosis was reported. The phenotypic similarity between molecularly diagnosed pairs of diseases was calculated with the use of terms from the Human Phenotype Ontology. RESULTS: A molecular diagnosis was rendered for 2076 of 7374 patients (28.2%); among these patients, 101 (4.9%) had diagnoses that involved two or more disease loci. We also analyzed parental samples, when available, and found that de novo variants accounted for 67.8% (61 of 90) of pathogenic variants in autosomal dominant disease genes and 51.7% (15 of 29) of pathogenic variants in X-linked disease genes; both variants were de novo in 44.7% (17 of 38) of patients with two monoallelic variants. Causal copy-number variants were found in 12 patients (11.9%) with multiple diagnoses. Phenotypic similarity scores were significantly lower among patients in whom the phenotype resulted from two distinct mendelian disorders that affected different organ systems (50 patients) than among patients with disorders that had overlapping phenotypic features (30 patients) (median score, 0.21 vs. 0.36; P=1.77×10-7). CONCLUSIONS: In our study, we found multiple molecular diagnoses in 4.9% of cases in which whole-exome sequencing was informative. Our results show that structured clinical ontologies can be used to determine the degree of overlap between two mendelian diseases in the same patient; the diseases can be distinct or overlapping. Distinct disease phenotypes affect different organ systems, whereas overlapping disease phenotypes are more likely to be caused by two genes encoding proteins that interact within the same pathway. (Funded by the National Institutes of Health and the Ting Tsung and Wei Fong Chao Foundation.).

Parent of origin, mosaicism, and recurrence risk: probabilistic modeling explains the broken symmetry of transmission genetics.

Most new mutations are observed to arise in fathers, and increasing paternal age positively correlates with the risk of new variants. Interestingly, new mutations in X-linked recessive disease show elevated familial recurrence rates. In male offspring, these mutations must be inherited from mothers. We previously developed a simulation model to consider parental mosaicism as a source of transmitted mutations. In this paper, we extend and formalize the model to provide analytical results and flexible formulas. The results implicate parent of origin and parental mosaicism as central variables in recurrence risk. Consistent with empirical data, our model predicts that more transmitted mutations arise in fathers and that this tendency increases as fathers age. Notably, the lack of expansion later in the male germline determines relatively lower variance in the proportion of mutants, which decreases with paternal age. Subsequently, observation of a transmitted mutation has less impact on the expected risk for future offspring. Conversely, for the female germline, which arrests after clonal expansion in early development, variance in the mutant proportion is higher, and observation of a transmitted mutation dramatically increases the expected risk of recurrence in another pregnancy. Parental somatic mosaicism considerably elevates risk for both parents. These findings have important implications for genetic counseling and for understanding patterns of recurrence in transmission genetics. We provide a convenient online tool and source code implementing our analytical results. These tools permit varying the underlying parameters that influence recurrence risk and could be useful for analyzing risk in diverse family structures.

Molecular diagnostic experience of whole-exome sequencing in adult patients.

PURPOSE: Whole-exome sequencing (WES) is increasingly used as a diagnostic tool in medicine, but prior reports focus on predominantly pediatric cohorts with neurologic or developmental disorders. We describe the diagnostic yield and characteristics of WES in adults. METHODS: We performed a retrospective analysis of consecutive WES reports for adults from a diagnostic laboratory. Phenotype composition was determined using Human Phenotype Ontology terms. RESULTS: Molecular diagnoses were reported for 17.5% (85/486) of adults, which is lower than that for a primarily pediatric population (25.2%; P = 0.0003); the diagnostic rate was higher (23.9%) for those 18-30 years of age compared to patients older than 30 years (10.4%; P = 0.0001). Dual Mendelian diagnoses contributed to 7% of diagnoses, revealing blended phenotypes. Diagnoses were more frequent among individuals with abnormalities of the nervous system, skeletal system, head/neck, and growth. Diagnostic rate was independent of family history information, and de novo mutations contributed to 61.4% of autosomal dominant diagnoses. CONCLUSION: Early WES experience in adults demonstrates molecular diagnoses in a substantial proportion of patients, informing clinical management, recurrence risk, and recommendations for relatives. A positive family history was not predictive, consistent with molecular diagnoses often revealed by de novo events, informing the Mendelian basis of genetic disease in adults.Genet Med 18 7, 678-685.

NetComm: a network analysis tool based on communicability.

MOTIVATION: Set-based network similarity metrics are increasingly used to productively analyze genome-wide data. Conventional approaches, such as mean shortest path and clique-based metrics, have been useful but are not well suited to all applications. Computational scientists in other disciplines have developed communicability as a complementary metric. Network communicability considers all paths of all lengths between two network members. Given the success of previous network analyses of protein-protein interactions, we applied the concepts of network communicability to this problem. Here we show that our communicability implementation has advantages over traditional approaches. Overall, analyses suggest network communicability has considerable utility in analysis of large-scale biological networks. AVAILABILITY AND IMPLEMENTATION: We provide our method as an R package for use in both human protein-protein interaction network analyses and analyses of arbitrary networks along with a tutorial at http://www.shawlab.org/NetComm/.

The Hematopoietic Expression Viewer: expanding mobile apps as a scientific tool.

UNLABELLED: Many important data in current biological science comprise hundreds, thousands or more individual results. These massive data require computational tools to navigate results and effectively interact with the content. Mobile device apps are an increasingly important tool in the everyday lives of scientists and non-scientists alike. These software present individuals with compact and efficient tools to interact with complex data at meetings or other locations remote from their main computing environment. We believe that apps will be important tools for biologists, geneticists and physicians to review content while participating in biomedical research or practicing medicine. We have developed a prototype app for displaying gene expression data using the iOS platform. To present the software engineering requirements, we review the model-view-controller schema for Apple's iOS. We apply this schema to a simple app for querying locally developed microarray gene expression data. The challenge of this application is to balance between storing content locally within the app versus obtaining it dynamically via a network connection. AVAILABILITY: The Hematopoietic Expression Viewer is available at http://www.shawlab.org/he_viewer. The source code for this project and any future information on how to obtain the app can be accessed at http://www.shawlab.org/he_viewer.

Self-assembly of fibrochondrocytes and chondrocytes for tissue engineering of the knee meniscus.

Chondrocyte self-assembly in high-density scaffoldless culture has shown success in producing articular cartilage constructs, and a similar process could be applied to fibrocartilage tissue engineering. Three cell combinations were compared in self-assembly culture-100% chondrocytes, 100% meniscal fibrochondrocytes, and 50:50 co-cultures of fibrochondrocytes and chondrocytes with the goal of creating a proteoglycan, collagen I, and collagen II matrix similar to native meniscus. Two culture surfaces were also compared for self-assembly: agarose-coated wells and tissue culture plastic. After 4 weeks, the resulting self-assembled chondrocyte constructs were 10.24+/-0.63 mm in diameter and 0.96+/-0.14 mm thick, weighing 84.5+/-7.2 mg. Co-culture constructs were smaller and weighed 22.5+/-1.0 mg. In contrast, the fibrochondrocyte constructs contracted into spheres weighing 1.3+/-0.3 mg. Immunostaining showed collagen II in the chondrocyte constructs, both collagen I and collagen II in the co-cultures, and only collagen I in the fibrochondrocyte constructs. Collagen densities for chondrocyte, co-culture, and fibrochondrocyte constructs were 41+/-3, 38+/-3, and 20+/-2 microg/mg dry weight, and glycosaminoglycan densities were 230+/-2, 80+/-6, and 10+/-1 microg/mg dry weight, respectively. Self-assembled co-cultures, with their mixed collagen I and II matrix and robust gross characteristics, appear promising for tissue engineering of the knee meniscus.

A visual and curatorial approach to clinical variant prioritization and disease gene discovery in genome-wide diagnostics.

BACKGROUND: Genome-wide data are increasingly important in the clinical evaluation of human disease. However, the large number of variants observed in individual patients challenges the efficiency and accuracy of diagnostic review. Recent work has shown that systematic integration of clinical phenotype data with genotype information can improve diagnostic workflows and prioritization of filtered rare variants. We have developed visually interactive, analytically transparent analysis software that leverages existing disease catalogs, such as the Online Mendelian Inheritance in Man database (OMIM) and the Human Phenotype Ontology (HPO), to integrate patient phenotype and variant data into ranked diagnostic alternatives. METHODS: Our tool, "OMIM Explorer" ( http://www.omimexplorer.com ), extends the biomedical application of semantic similarity methods beyond those reported in previous studies. The tool also provides a simple interface for translating free-text clinical notes into HPO terms, enabling clinical providers and geneticists to contribute phenotypes to the diagnostic process. The visual approach uses semantic similarity with multidimensional scaling to collapse high-dimensional phenotype and genotype data from an individual into a graphical format that contextualizes the patient within a low-dimensional disease map. The map proposes a differential diagnosis and algorithmically suggests potential alternatives for phenotype queries--in essence, generating a computationally assisted differential diagnosis informed by the individual's personal genome. Visual interactivity allows the user to filter and update variant rankings by interacting with intermediate results. The tool also implements an adaptive approach for disease gene discovery based on patient phenotypes. RESULTS: We retrospectively analyzed pilot cohort data from the Baylor Miraca Genetics Laboratory, demonstrating performance of the tool and workflow in the re-analysis of clinical exomes. Our tool assigned to clinically reported variants a median rank of 2, placing causal variants in the top 1 % of filtered candidates across the 47 cohort cases with reported molecular diagnoses of exome variants in OMIM Morbidmap genes. Our tool outperformed Phen-Gen, eXtasy, PhenIX, PHIVE, and hiPHIVE in the prioritization of these clinically reported variants. CONCLUSIONS: Our integrative paradigm can improve efficiency and, potentially, the quality of genomic medicine by more effectively utilizing available phenotype information, catalog data, and genomic knowledge.

Effects of agarose mould compliance and surface roughness on self-assembled meniscus-shaped constructs.

The meniscus is a fibrocartilaginous tissue that is critically important to the loading patterns within the knee joint. If the meniscus structure is compromised, there is little chance of healing, due to limited vascularity in the inner portions of the tissue. Several tissue-engineering techniques to mimic the complex geometry of the meniscus have been employed. Of these, a self-assembly, scaffoldless approach employing agarose moulds avoids drawbacks associated with scaffold use, while still allowing the formation of robust tissue. In this experiment two factors were examined, agarose percentage and mould surface roughness, in an effort to consistently obtain constructs with adequate geometric properties. Co-cultures of ACs and MCs (50:50 ratio) were cultured in smooth or rough moulds composed of 1% or 2% agarose for 4 weeks. Morphological results showed that constructs formed in 1% agarose moulds, particularly smooth moulds, were able to maintain their shape over the 4 week culture period. Significant increases were observed for the collagen II:collagen I ratio, total collagen, GAG and tensile and compressive properties in smooth wells. Cell number per construct was higher in the rough wells. Overall, it was observed that the topology of an agarose surface may be able to affect the phenotypic properties of cells that are on that surface, with smooth surfaces supporting a more chondrocytic phenotype. In addition, wells made from 1% agarose were able to prevent construct buckling potentially, due to their higher compliance.