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A group of 54 exceptional responders (ERs) to cancer treatment across a variety of cancers and treatments were compared to typical cancer patients using previously defined polygenic risk scores (PRS) for multiple autoimmune-related diseases including type 1 diabetes (T1D), hypothyroidism, psoriasis, rheumatoid arthritis, multiple sclerosis, and inflammatory bowel (IBD) disease. Most of the ERs were not treated with checkpoint inhibitors and included a broad array of tumor types. Significantly elevated PRSs were found between ERs relative to typical cancer patients in T1D, hypothyroidism, and psoriasis. IBD PRS scores were significantly decreased in the ERs.

Concerns about the ethical and social implications of genetics persist as more applications of genetic and genomic technology have become available. Pediatric testing for genetic influences on response to opioids like codeine is one area of application. We interviewed parents of children enrolled in a mixed-methods study following the communication of actual or hypothetical results for CYP2D6, which impacts opioid response. Forty-one parents of children naive to opioids and 42 parents of children previously exposed to opioids participated in qualitative interviews. Findings did not differ by the child's opioid exposure or by actual versus hypothetical results. Parents' responses centered on the experience of the parent(s) and the potential impact of that information on the parent, rather than the result's impact on the child. Parents also emphasized that the results did not impact their perceptions of the child, reaffirming that the child was still "normal" regardless of test result. When asked about the impact of receiving secondary results, parents' responses emphasized how the results would impact their ability to advocate for the child or impact their state of mind. While the answers reflect parents' role as surrogate decision maker for their child, they also reinforced concerns that health care decisions might be influenced by secondary parental concerns as much as by the best interests of the child. Emphasis on the child's "normality" challenges concerns about the impact of genetic essentialism, but further research is required to see whether the type of testing done or the way results were communicated shaped this response.

Identification of obesity at well-child care (WCC) examinations is a step toward intervention. Studies have shown suboptimal documentation in primary care clinics that can improve with the use of electronic health records (EHRs). This study investigated the impact of a standardized EHR template on documentation of obesity at WCC visits and its impact on physician behavior. A cohort of 585 children with severe early onset obesity (body mass index >99th percentile, age

Genetic variation can affect drug response in multiple ways, although it remains unclear how rare genetic variants affect drug response. The electronic Medical Records and Genomics (eMERGE) Network, collaborating with the Pharmacogenomics Research Network, began eMERGE‐PGx, a targeted sequencing study to assess genetic variation in 82 pharmacogenes critical for implementation of “precision medicine.” The February 2015 eMERGE‐PGx data release includes sequence‐derived data from ∼5,000 clinical subjects. We present the variant frequency spectrum categorized by variant type, ancestry, and predicted function. We found 95.12% of genes have variants with a scaled Combined Annotation‐Dependent Depletion score above 20, and 96.19% of all samples had one or more Clinical Pharmacogenetics Implementation Consortium Level A actionable variants. These data highlight the distribution and scope of genetic variation in relevant pharmacogenes, identifying challenges associated with implementing clinical sequencing for drug treatment at a broader level, underscoring the importance for multifaceted research in the execution of precision medicine.

Aim: To determine parents’ use of their children's CYP2D6 research result. We hypothesized that perceived utility, likelihood of sharing and actual sharing of results would differ between parents with children previously exposed (cases) or unexposed (controls) to opioids. Methods: We returned results by phone (baseline). We surveyed parents about perceived utility and likelihood of sharing their child's research result at baseline, and actual sharing at 3 and 12 months. Results: Cases were more likely than controls to agree that they (p = 0.022) and the doctors (p = 0.041) could use the results to care for their child, to report higher likelihood of sharing (p = 0.042) and to actually share results with the child's doctor (p = 0.026). Conclusion: Prior opioid exposure influenced perceived clinical utility and sharing behaviors.

We describe here the design and initial implementation of the eMERGE-PGx project. eMERGE-PGx, a partnership of the Electronic Medical Records and Genomics Network and the Pharmacogenomics Research Network, has three objectives: (i) to deploy PGRNseq, a next-generation sequencing platform assessing sequence variation in 84 proposed pharmacogenes, in nearly 9,000 patients likely to be prescribed drugs of interest in a 1- to 3-year time frame across several clinical sites; (ii) to integrate well-established clinically validated pharmacogenetic genotypes into the electronic health record with associated clinical decision support and to assess process and clinical outcomes of implementation; and (iii) to develop a repository of pharmacogenetic variants of unknown significance linked to a repository of electronic health record-based clinical phenotype data for ongoing pharmacogenomics discovery. We describe site-specific project implementation and anticipated products, including genetic variant and phenotype data repositories, novel variant association studies, clinical decision support modules, clinical and process outcomes, approaches to managing incidental findings, and patient and clinician education methods.

Objective: We report the first pediatric specific Phenome-Wide Association Study (PheWAS) using electronic medical records (EMRs). Given the early success of PheWAS in adult populations, we investigated the feasibility of this approach in pediatric cohorts in which associations between a previously known genetic variant and a wide range of clinical or physiological traits were evaluated. Although computationally intensive, this approach has potential to reveal disease mechanistic relationships between a variant and a network of phenotypes. Method: Data on 5049 samples of European ancestry were obtained from the EMRs of two large academic centers in five different genotyped cohorts. Recently, these samples have undergone whole genome imputation. After standard quality controls, removing missing data and outliers based on principal components analyses (PCA), 4268 samples were used for the PheWAS study. We scanned for associations between 2476 single-nucleotide polymorphisms (SNP) with available genotyping data from previously published GWAS studies and 539 EMR-derived phenotypes. The false discovery rate was calculated and, for any new PheWAS findings, a permutation approach (with up to 1,000,000 trials) was implemented. Results: This PheWAS found a variety of common variants (MAF > 10%) with prior GWAS associations in our pediatric cohorts including Juvenile Rheumatoid Arthritis (JRA), Asthma, Autism and Pervasive Developmental Disorder (PDD) and Type 1 Diabetes with a false discovery rate < 0.05 and power of study above 80%. In addition, several new PheWAS findings were identified including a cluster of association near the NDFIP1 gene for mental retardation (best SNP rs10057309, p = 4.33 × 10−7, OR = 1.70, 95%CI = 1.38 − 2.09); association near PLCL1 gene for developmental delays and speech disorder [best SNP rs1595825, p = 1.13 × 10−8, OR = 0.65(0.57 − 0.76)]; a cluster of associations in the IL5-IL13 region with Eosinophilic Esophagitis (EoE) [best at rs12653750, p = 3.03 × 10−9, OR = 1.73 95%CI = (1.44 − 2.07)], previously implicated in asthma, allergy, and eosinophilia; and association of variants in GCKR and JAZF1 with allergic rhinitis in our pediatric cohorts [best SNP rs780093, p = 2.18 × 10−5, OR = 1.39, 95%CI = (1.19 − 1.61)], previously demonstrated in metabolic disease and diabetes in adults. Conclusion: The PheWAS approach with re-mapping ICD-9 structured codes for our European-origin pediatric cohorts, as with the previous adult studies, finds many previously reported associations as well as presents the discovery of associations with potentially important clinical implications.

ObjectiveCohort 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.MethodsWe 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.ResultsThe 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.ConclusionsIn 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.

Analyse du conflit qui opposa squatters et gouvernement a Cape Town (Afrique du Sud) en 1981 et de l'ideologie politique et raciale que defend ce dernier