Clinical Correlates of Autosomal Chromosomal Abnormalities in an Electronic Medical Record-Linked Genome-Wide Association Study: A Case Series

Duplication of 19p13.3 in 11-Year-Old Male Patient with Dysmorphic Features and Intellectual Disability: A Review

We present a clinical report of an 11-year-old male patient with an interstitial duplication of 19p13.3 (829 kb in size) at genomic coordinates 3,804,495-4,033,722 bp (hg19) identified by chromosomal microarray analysis and review the literature from nine published reports adding knowledge regarding this chromosomal anomaly and clinical outcomes. The size of the duplication ranged from 0.83 to 8.9 Mb in the nine individuals. The young boy in our report was dysmorphic with microcephaly, abnormal craniofacial features, intellectual disability, aggression, and a heart murmur. All patients were found to have a psychomotor developmental delay and/or intellectual disability with the majority having microcephaly, intrauterine growth retardation, and hypotonia. Common craniofacial findings included a tall, prominent forehead, an elongated face, epicanthal folds, hypertelorism, prominent low-set ears, philtrum anomaly, and a small mouth. Other less common features included abnormal digits, sparse hair, and cardiac defects. Clinical features, chromosome duplication sizes, locations, and the number of genes will be summarized in a tabular form.

Translational bioinformatics in the era of real-time biomedical, health care and wellness data streams

Monitoring and modeling biomedical, health care and wellness data from individuals and converging data on a population scale have tremendous potential to improve understanding of the transition to the healthy state of human physiology to disease setting. Wellness monitoring devices and companion software applications capable of generating alerts and sharing data with health care providers or social networks are now available. The accessibility and clinical utility of such data for disease or wellness research are currently limited. Designing methods for streaming data capture, real-time data aggregation, machine learning, predictive analytics and visualization solutions to integrate wellness or health monitoring data elements with the electronic medical records (EMRs) maintained by health care providers permits better utilization. Integration of population-scale biomedical, health care and wellness data would help to stratify patients for active health management and to understand clinically asymptomatic patients and underlying illness trajectories. In this article, we discuss various health-monitoring devices, their ability to capture the unique state of health represented in a patient and their application in individualized diagnostics, prognosis, clinical or wellness intervention. We also discuss examples of translational bioinformatics approaches to integrating patient-generated data with existing EMRs, personal health records, patient portals and clinical data repositories. Briefly, translational bioinformatics methods, tools and resources are at the center of these advances in implementing real-time biomedical and health care analytics in the clinical setting. Furthermore, these advances are poised to play a significant role in clinical decision-making and implementation of data-driven medicine and wellness care.