Semantic integration of clinical laboratory tests from electronic health records for deep phenotyping and biomarker discovery.

Electronic Health Record (EHR) systems typically define laboratory test results using the Laboratory Observation Identifier Names and Codes (LOINC) and can transmit them using Fast Healthcare Interoperability Resource (FHIR) standards. LOINC has not yet been semantically integrated with computational resources for phenotype analysis. Here, we provide a method for mapping LOINC-encoded laboratory test results transmitted in FHIR standards to Human Phenotype Ontology (HPO) terms. We annotated the medical implications of 2923 commonly used laboratory tests with HPO terms. Using these annotations, our software assesses laboratory test results and converts each result into an HPO term. We validated our approach with EHR data from 15,681 patients with respiratory complaints and identified known biomarkers for asthma. Finally, we provide a freely available SMART on FHIR application that can be used within EHR systems. Our approach allows readily available laboratory tests in EHR to be reused for deep phenotyping and exploits the hierarchical structure of HPO to integrate distinct tests that have comparable medical interpretations for association studies

Test-retest variability of high resolution positron emission tomography (PET) imaging of cortical serotonin (5HT2A) receptors in older, healthy adults

<p>Abstract</p> <p>Background</p> <p>Position emission tomography (PET) imaging using [¹⁸F]-setoperone to quantify cortical 5-HT_2Areceptors has the potential to inform pharmacological treatments for geriatric depression and dementia. Prior reports indicate a significant normal aging effect on serotonin 5HT_2Areceptor (5HT_2AR) binding potential. The purpose of this study was to assess the test-retest variability of [¹⁸F]-setoperone PET with a high resolution scanner (HRRT) for measuring 5HT_2AR availability in subjects greater than 60 years old. Methods: Six healthy subjects (age range = 65–78 years) completed two [¹⁸F]-setoperone PET scans on two separate occasions 5–16 weeks apart.</p> <p>Results</p> <p>The average difference in the binding potential (BP_ND) as measured on the two occasions in the frontal and temporal cortical regions ranged between 2 and 12%, with the lowest intraclass correlation coefficient in anterior cingulate regions.</p> <p>Conclusion</p> <p>We conclude that the test-retest variability of [¹⁸F]-setoperone PET in elderly subjects is comparable to that of [¹⁸F]-setoperone and other 5HT_2AR radiotracers in younger subject samples.</p

GA4GH: International policies and standards for data sharing across genomic research and healthcare.

The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits