Understanding the genetic basis of disease is important, not only, for understanding the molecular mechanisms driving a particular disease phenotype, but also for providing informative prognostic, and diagnostic markers, as well as allowing for the design of personalized therapeutic intervention. Identifying these causative genetic variants is a complex problem because of the relatively small level of risk some variants may contribute, the interplay of variants which may be neutral in isolation, population stratification in purely statistical identification of risk variants, and the overwhelming number of neutral variants present in any individuals genome or tumor genome. A number of computational methods for prioritization of risk factors have been developed, each with a large weakness due to efforts to form generalized predictions. In this dissertation, I describe a specialized prediction method, tailored towards identification of causative polymorphisms in the protein kinase gene family, and demonstrate its applicability to identification of polymorphisms involved in inherited disease as well as cancer. Chapter 1 describes the method itself, Chapter 2 describes its applicability to cancer, and Chapters 3 and 4 delve into further details of the contributions of some of the predictive attributes

Among numerous damage identification techniques, those which are used for online data-driven damage identification have received considerable attention recently. One of the most widely-used vibration-based time-domain techniques for nonlinear system identification is the extended Kalman filter, which exhibits a good performance when the parameter to be identified is a constant parameter. However, it is not as successful in identification of changes in time-varying system parameters, which is essential for real-time identification. Alternatively, the extended Kalman-Bucy filter has been recently proposed due to its enhanced capabilities in parameter estimation compared with extended Kalman filter. On the other hand, when applied as the excitation in some attractor-based damage identification techniques, chaotic and hyperchaotic dynamics produce better outcomes than does common stochastic white noise. The current study combines hyperchaotic excitations and the enhanced capabilities of extended Kalman-Bucy filter to propose a real-time approach for identification of damage in nonlinear structures. Simulation results show that the proposed approach is capable of online identification and assessment of damage in nonlinear elastic and hysteretic structures with single or multiple degrees-of-freedom using noise-corrupted measured acceleration response. © The Society for Experimental Mechanics 2014.

© 2015 Springer Science+Business Media Dordrecht A real-time damage identification approach using an extended Kalman–Bucy filter is proposed for identification and real-time monitoring of damage-induced changes which is applicable both as a vibration-based technique and as a guided-wave technique for structural health monitoring. The proposed approach makes use of the intrinsic hypersensitivity of hyperchaotic systems to subtle changes in system parameters by applying the augmented state method along with an optimal filtering problem to provide simultaneous estimation of the states and parameters of a (possibly) nonlinear structural system driven by a tuned hyperchaotic excitation in order to monitor damage-induced changes. The proposed approach can also be employed for guided-wave structural health monitoring by discretizing the governing partial differential equation to obtain a process model in the context of optimal filtering problem, and thus to estimate the transmitted hyperchaotic wave and model parameters. Numerical simulation shows that the proposed approach is capable of real-time identification of reduction in elastic modulus of an isotropic beam.

Mitochondrial diseases are rare, often go undiagnosed and can lead to devastating cascades of multisystem organ dysfunction. This report of a young woman with hearing loss and gestational diabetes illustrates a novel presentation of a cardiomyopathy caused by a previously described mutation in a mitochondrial gene, MT-TL1. She initially had biventricular heart dysfunction and ventricular arrhythmia that ultimately recovered with beta blockade and time. She continues to participate in sport without decline. It is important to keep mitochondrial diseases in the differential diagnosis and understand the testing and management strategies in order to provide the best patient care.

Background and objectives

The availability of whole genome sequencing (WGS) is increasing in clinical care, and WGS is a promising tool in diagnostic odyssey cases. Physicians' ability to effectively communicate genomic information with patients, however, is unclear. In this multiperspective study, we assessed physicians' communication of patient genome sequencing information in a diagnostic odyssey case series.

Methods

We evaluated physician communication of genome sequencing results in the context of an ongoing study of the utility of WGS for the diagnosis of rare and idiopathic diseases. A modified version of the Medical Communication Competence Scale was used to compare patients' ratings of their physicians' communication of general medical information to communication of genome sequencing information. Physician self-ratings were also compared with patient ratings.

Results

A total of 47 patients, parents, and physicians across 11 diagnostic odyssey cases participated. In 6 of 11 cases (54%), the patient respondent rated the physician's communication of genome sequencing information as worse than that of general medical information. In 9 of 11 cases (82%), physician self-ratings of communication of genome sequencing information were worse than the patient respondent's rating. Identification of a diagnosis via WGS was positively associated with physician self-ratings (P = .021) but was not associated with patient respondent ratings (P = .959).

Conclusions

These findings reveal that even in diagnostic odyssey cases, in which genome sequencing may be clinically beneficial, physicians may not be well-equipped to communicate genomic information to patients. Future studies may benefit from multiperspective approaches to assessing and understanding physician-patient communication of genome-sequencing information.

Introduction

Advances in health technology such as genome sequencing and wearable sensors now allow for the collection of highly granular personal health data from individuals. It is unclear how people think about privacy in the context of these emerging health technologies. An open question is whether early adopters of these advances conceptualize privacy in different ways than non-early adopters.

Purpose

This study sought to understand privacy attitudes of early adopters of emerging health technologies.

Methods

Transcripts from in-depth, semi-structured interviews with early adopters of genome sequencing and health devices and apps were analyzed with a focus on participant attitudes and perceptions of privacy. Themes were extracted using inductive content analysis.

Results

Although interviewees were willing to share personal data to support scientific advancements, they still expressed concerns, as well as uncertainty about who has access to their data, and for what purpose. In short, they were not dismissive of privacy risks. Key privacy-related findings are organized into four themes as follows: first, personal data privacy; second, control over personal information; third, concerns about discrimination; and fourth, contributing personal data to science.

Conclusion

Early adopters of emerging health technologies appear to have more complex and nuanced conceptions of privacy than might be expected based on their adoption of personal health technologies and participation in open science. Early adopters also voiced uncertainty about the privacy implications of their decisions to use new technologies and share their data for research. Though not representative of the general public, studies of early adopters can provide important insights into evolving attitudes toward privacy in the context of emerging health technologies and personal health data research.

Purpose

Nail-Patella syndrome is a dominantly inherited genetic disorder characterized by abnormalities of the nails, knees, elbows, and pelvis. Nail abnormalities are the most constant feature of Nail-Patella syndrome. Pathogenic mutations in a single gene, LMX1B, a mesenchymal determinant of dorsal-ventral patterning, explain approximately 95% of Nail-Patella syndrome cases. However, 5% of cases remain unexplained.

Methods

Here, we present exome sequencing and analysis of four generations of a family with a dominantly inherited Nail-Patella-like disorder (nail dysplasia with some features of Nail-Patella syndrome) who tested negative for LMX1B mutation.

Results

We identify a loss-of-function mutation in WIF1 (NM_007191 p.W15*), which is involved in mesoderm segmentation, as the suspected cause of the Nail-Patella-like disorder observed in this family.

Conclusions

Mutation of WIF1 is a potential novel cause of a Nail-Patella-like disorder. Testing of additional patients negative for LMX1B mutation is needed to confirm this finding and further clarify the phenotype.Genet Med advance online publication 06 April 2017.

Background

Community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA) is a significant bacterial pathogen that poses considerable clinical and public health challenges. The majority of the CA-MRSA disease burden consists of skin and soft tissue infections (SSTI) not associated with significant morbidity; however, CA-MRSA also causes severe, invasive infections resulting in significant morbidity and mortality. The broad range of disease severity may be influenced by bacterial genetic variation.

Results

We sequenced the complete genomes of 36 CA-MRSA clinical isolates from the predominant North American community acquired clonal type USA300 (18 SSTI and 18 severe infection-associated isolates). While all 36 isolates shared remarkable genetic similarity, we found greater overall time-dependent sequence diversity among SSTI isolates. In addition, pathway analysis of non-synonymous variations revealed increased sequence diversity in the putative virulence genes of SSTI isolates.

Conclusions

Here we report the first whole genome survey of diverse clinical isolates of the USA300 lineage and describe the evolution of the pathogen over time within a defined geographic area. The results demonstrate the close relatedness of clinically independent CA-MRSA isolates, which carry implications for understanding CA-MRSA epidemiology and combating its spread.

How common polymorphisms in noncoding genome regions can regulate cellular function remains largely unknown. Here we show that cardiac fibrosis, mimicked using a hydrogel with controllable stiffness, affects the regulation of the phenotypes of human cardiomyocytes by a portion of the long noncoding RNA ANRIL, the gene of which is located in the disease-associated 9p21 locus. In a physiological environment, cultured cardiomyocytes derived from induced pluripotent stem cells obtained from patients who are homozygous for cardiovascular-risk alleles (R/R cardiomyocytes) or from healthy individuals who are homozygous for nonrisk alleles contracted synchronously, independently of genotype. After hydrogel stiffening to mimic fibrosis, only the R/R cardiomyocytes exhibited asynchronous contractions. These effects were associated with increased expression of the short ANRIL isoform in R/R cardiomyocytes, which induced a c-Jun N-terminal kinase (JNK) phosphorylation-based mechanism that impaired gap junctions (particularly, loss of connexin-43 expression) following stiffening. Deletion of the risk locus or treatment with a JNK antagonist was sufficient to maintain gap junctions and prevent asynchronous contraction of cardiomyocytes. Our findings suggest that mechanical changes in the microenvironment of cardiomyocytes can activate the regulation of their function by noncoding loci.

Efficient tools for data management and integration are essential for many aspects of high-throughput biology. In particular, annotations of genes and human genetic variants are commonly used but highly fragmented across many resources. Here, we describe MyGene.info and MyVariant.info, high-performance web services for querying gene and variant annotation information. These web services are currently accessed more than three million times permonth. They also demonstrate a generalizable cloud-based model for organizing and querying biological annotation information. MyGene.info and MyVariant.info are provided as high-performance web services, accessible at http://mygene.info and http://myvariant.info . Both are offered free of charge to the research community.