Electronic Health Record Based Algorithm to Identify Patients with Autism Spectrum Disorder

Objective: Cohort selection is challenging for large-scale electronic health record (EHR) analyses, as International Classification of Diseases 9th edition (ICD-9) diagnostic codes are notoriously unreliable disease predictors. Our objective was to develop, evaluate, and validate an automated algorithm for determining an Autism Spectrum Disorder (ASD) patient cohort from EHR. We demonstrate its utility via the largest investigation to date of the co-occurrence patterns of medical comorbidities in ASD. Methods: We extracted ICD-9 codes and concepts derived from the clinical notes. A gold standard patient set was labeled by clinicians at Boston Children’s Hospital (BCH) (N = 150) and Cincinnati Children’s Hospital and Medical Center (CCHMC) (N = 152). Two algorithms were created: (1) rule-based implementing the ASD criteria from Diagnostic and Statistical Manual of Mental Diseases 4th edition, (2) predictive classifier. The positive predictive values (PPV) achieved by these algorithms were compared to an ICD-9 code baseline. We clustered the patients based on grouped ICD-9 codes and evaluated subgroups. Results: The rule-based algorithm produced the best PPV: (a) BCH: 0.885 vs. 0.273 (baseline); (b) CCHMC: 0.840 vs. 0.645 (baseline); (c) combined: 0.864 vs. 0.460 (baseline). A validation at Children’s Hospital of Philadelphia yielded 0.848 (PPV). Clustering analyses of comorbidities on the three-site large cohort (N = 20,658 ASD patients) identified psychiatric, developmental, and seizure disorder clusters. Conclusions: In a large cross-institutional cohort, co-occurrence patterns of comorbidities in ASDs provide further hypothetical evidence for distinct courses in ASD. The proposed automated algorithms for cohort selection open avenues for other large-scale EHR studies and individualized treatment of ASD

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Targeting the MEK1 Cascade in Lung Epithelium Inhibits Proliferation and Fibrogenesis by Asbestos

The extracellular signal–regulated kinases 1 and 2 (ERK1/2) are phosphorylated after inhalation of asbestos. The effect of blocking this signaling pathway in lung epithelium is unclear. Asbestos-exposed transgenic mice expressing a dominant-negative mitogen-activated protein kinase kinase-1 (dnMEK1) (i.e., the upstream kinase necessary for phosphorylation of ERK1/2) targeted to lung epithelium exhibited morphologic and molecular changes in lung. Transgene-positive (Tg+) (i.e., dnMEK1) and transgene-negative (Tg−) littermates were exposed to crocidolite asbestos for 2, 4, 9, and 32 days or maintained in clean air (sham controls). Distal bronchiolar epithelium was isolated using laser capture microdissection and mRNA analyzed for molecular markers of proliferation and Clara cell secretory protein (CCSP). Lungs and bronchoalveolar lavage fluids were analyzed for inflammatory and proliferative changes and molecular markers of fibrogenesis. Distal bronchiolar epithelium of asbestos-exposed wild-type mice showed increased expression of c-fos at 2 days. Elevated mRNA levels of histone H3 and numbers of Ki-67–labeled proliferating bronchiolar epithelial cells were decreased at 4 days in asbestos-exposed Tg+ mice. At 32 days, distal bronchioles normally composed of Clara cells in asbestos-exposed Tg+ mouse lungs exhibited nonreplicating ciliated and mucin-secreting cells as well as decreased mRNA levels of CCSP. Gene expression (procollagen 3-a-1, procollagen 1-a-1, and IL-6) linked to fibrogenesis was also increased in lung homogenates of asbestos-exposed Tg− mice, but reduced in asbestos-exposed Tg+ mice. These results suggest a critical role of MEK1 signaling in epithelial cell proliferation and lung remodeling after toxic injury