The inflammatory bowel diseases (IBD) Crohn’s disease and ulcerative colitis are common causes of morbidity in children and young adults in the western world. Here we report the results of a genome-wide association study in early-onset IBD involving 3,426 affected individuals and 11,963 genetically matched controls recruited through international collaborations in Europe and North America, thereby extending the results from a previous study of 1,011 individuals with early-onset IBD1. We have identified five new regions associated with early-onset IBD susceptibility, including 16p11 near the cytokine gene IL27 (rs8049439, P = 2.41 × 10−9), 22q12 (rs2412973, P = 1.55 × 10−9), 10q22 (rs1250550, P = 5.63 × 10−9), 2q37 (rs4676410, P = 3.64 × 10−8) and 19q13.11 (rs10500264, P = 4.26 × 10−10). Our scan also detected associations at 23 of 32 loci previously implicated in adult-onset Crohn’s disease and at 8 of 17 loci implicated in adult-onset ulcerative colitis, highlighting the close pathogenetic relationship between early- and adult-onset IBD.

Inflammatory bowel disease (IBD) is a common inflammatory disorder with complex etiology that involves both genetic and environmental triggers, including but not limited to defects in bacterial clearance, defective mucosal barrier and persistent dysregulation of the immune response to commensal intestinal bacteria. IBD is characterized by two distinct phenotypes: Crohn’s disease (CD) and ulcerative colitis (UC). Previously reported GWA studies have identified genetic variation accounting for a small portion of the overall genetic susceptibility to CD and an even smaller contribution to UC pathogenesis. We hypothesized that stratification of IBD by age of onset might identify additional genes associated with IBD. To that end, we carried out a GWA analysis in a cohort of 1,011 individuals with pediatric-onset IBD and 4,250 matched controls. We identified and replicated significantly associated, previously unreported loci on chromosomes 20q13 (rs2315008[T] and rs4809330[A]; P = 6.30 × 10−8 and 6.95 × 10−8, respectively; odds ratio (OR) = 0.74 for both) and 21q22 (rs2836878[A]; P = 6.01 × 10−8; OR = 0.73), located close to the TNFRSF6B and PSMG1 genes, respectively.

Genome-wide association studies (GWASs) have identified hundreds of susceptibility genes, including shared associations across clinically distinct autoimmune diseases. We performed an inverse χ2 meta-analysis across ten pediatric-age-of-onset autoimmune diseases (pAIDs) in a case-control study including more than 6,035 cases and 10,718 shared population-based controls. We identified 27 genome-wide significant loci associated with one or more pAIDs, mapping to in silico–replicated autoimmune-associated genes (including IL2RA) and new candidate loci with established immunoregulatory functions such as ADGRL2, TENM3, ANKRD30A, ADCY7 and CD40LG. The pAID-associated single-nucleotide polymorphisms (SNPs) were functionally enriched for deoxyribonuclease (DNase)-hypersensitivity sites, expression quantitative trait loci (eQTLs), microRNA (miRNA)-binding sites and coding variants. We also identified biologically correlated, pAID-associated candidate gene sets on the basis of immune cell expression profiling and found evidence of genetic sharing. Network and protein-interaction analyses demonstrated converging roles for the signaling pathways of type 1, 2 and 17 helper T cells (TH1, TH2 and TH17), JAK-STAT, interferon and interleukin in multiple autoimmune diseases.

Many different fields of medicine are now utilizing video conferencing as a means to offer consultations to individuals in rural communities. However, there is a lack of published literature regarding the use of telehealth in clinical genetics and, specifically, in genetic counseling. Those experiences that have been reported mostly centered on cancer genetic counseling, sickle cell anemia consultation and care, or pediatric/adult genetic assessment. In these studies, the patients reported an overall satisfaction with telehealth, signifying that this type of communication may play an important role in the future of medicine. This pilot study compared patient satisfaction with prenatal genetic counseling performed via video conferencing versus that performed on-site. The results show that there was a high level of patient satisfaction when video conferencing was used to conduct prenatal genetic counseling consultations, suggesting that telehealth can be utilized as a means to offer this service to underserved populations.

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.