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Background Serological assays for SARS-CoV-2 are important tools for diagnosis in patients with negative RT-PCR testing, pediatric patients with multisystem inflammatory syndrome, and serosurveillance studies. However, lateral flow-based serological assays have previously demonstrated poor analytical and clinical performance, limiting their utility. Methods We assessed the ADEXUSDx COVID-19 lateral flow assay for agreement with diagnostic RT-PCR testing using 120 specimens from RT-PCR–positive patients, 77 specimens from symptomatic RT-PCR–negative patients, and 47 specimens obtained prepandemic. Specimens collected Results The ADEXUSDx COVID-19 Test yielded an overall positive percent agreement (PPA) of 92.5% (95%CI 85.8 to 96.3) and negative percent agreement of 99.2% (95% CI 94.9–100.0) relative to RT-PCR and in prepandemic specimens. Relative to days from symptom onset, the PPA after 13 days was 100% (95% CI 94.2–100); from 7 to 13 days, 89.7 (95% CI 71.5–97.2); and from 0 to 7 days, 53.8 (95% CI 26.1–79.6). The overall agreement between the Abbott and ADEXUSDx assays was 80.9%. Twenty-five specimens were positive by both assays, 9 specimens were negative by both assays, and 8 specimens were positive by only the ADEXUSDx assay. Conclusions We demonstrate high PPA and negative percent agreement of the ADEXUSDx COVID-19 assay and diagnostic testing by RT-PCR, with PPA approximately 90% by 7 days following symptom onset. The use of waived testing for antibodies to SARS-CoV-2 with high sensitivity and specificity provide a further tool for combatting the COVID-19 pandemic.

Genomic medicine holds great promise for improving health care, but integrating searchable and actionable genetic data into electronic health records (EHRs) remains a challenge. Here we describe Neptune, a system for managing the interaction between a clinical laboratory and an EHR system during the clinical reporting process. We developed Neptune and applied it to two clinical sequencing projects that required report customization, variant reanalysis, and EHR integration. Neptune has been applied for the generation and delivery of over 15,000 clinical genomic reports. This work spans two clinical tests based on targeted gene panels that contain 68 and 153 genes respectively. These projects demanded customizable clinical reports that contained a variety of genetic data types including single-nucleotide variants (SNVs), copy-number variants (CNVs), pharmacogenomics, and polygenic risk scores. Two variant reanalysis activities were also supported, highlighting this important workflow. Methods are needed for delivering structured genetic data to EHRs. This need extends beyond developing data formats to providing infrastructure that manages the reporting process itself. Neptune was successfully applied on two high-throughput clinical sequencing projects to build and deliver clinical reports to EHR systems. The software is open source and available at https://gitlab.com/bcm-hgsc/neptune .

The advancement of precision medicine requires new methods to coordinate and deliver genetic data from heterogeneous sources to physicians and patients. The eMERGE III Network enrolled >25,000 participants from biobank and prospective cohorts of predominantly healthy individuals for clinical genetic testing to determine clinically actionable findings. The network developed protocols linking together the 11 participant collection sites and 2 clinical genetic testing laboratories. DNA capture panels targeting 109 genes were used for testing of DNA and sample collection, data generation, interpretation, reporting, delivery, and storage were each harmonized. A compliant and secure network enabled ongoing review and reconciliation of clinical interpretations, while maintaining communication and data sharing between clinicians and investigators. A total of 202 individuals had positive diagnostic findings relevant to the indication for testing and 1,294 had additional/secondary findings of medical significance deemed to be returnable, establishing data return rates for other testing endeavors. This study accomplished integration of structured genomic results into multiple electronic health record (EHR) systems, setting the stage for clinical decision support to enable genomic medicine. Further, the established processes enable different sequencing sites to harmonize technical and interpretive aspects of sequencing tests, a critical achievement toward global standardization of genomic testing. The eMERGE protocols and tools are available for widespread dissemination.

Background Non-alcoholic fatty liver disease (NAFLD) is a common chronic liver illness with a genetically heterogeneous background that can be accompanied by considerable morbidity and attendant health care costs. The pathogenesis and progression of NAFLD is complex with many unanswered questions. We conducted genome-wide association studies (GWASs) using both adult and pediatric participants from the Electronic Medical Records and Genomics (eMERGE) Network to identify novel genetic contributors to this condition. Methods First, a natural language processing (NLP) algorithm was developed, tested, and deployed at each site to identify 1106 NAFLD cases and 8571 controls and histological data from liver tissue in 235 available participants. These include 1242 pediatric participants (396 cases, 846 controls). The algorithm included billing codes, text queries, laboratory values, and medication records. Next, GWASs were performed on NAFLD cases and controls and case-only analyses using histologic scores and liver function tests adjusting for age, sex, site, ancestry, PC, and body mass index (BMI). Results Consistent with previous results, a robust association was detected for the PNPLA3 gene cluster in participants with European ancestry. At the PNPLA3-SAMM50 region, three SNPs, rs738409, rs738408, and rs3747207, showed strongest association (best SNP rs738409 p = 1.70 × 10− 20). This effect was consistent in both pediatric (p = 9.92 × 10− 6) and adult (p = 9.73 × 10− 15) cohorts. Additionally, this variant was also associated with disease severity and NAFLD Activity Score (NAS) (p = 3.94 × 10− 8, beta = 0.85). PheWAS analysis link this locus to a spectrum of liver diseases beyond NAFLD with a novel negative correlation with gout (p = 1.09 × 10− 4). We also identified novel loci for NAFLD disease severity, including one novel locus for NAS score near IL17RA (rs5748926, p = 3.80 × 10− 8), and another near ZFP90-CDH1 for fibrosis (rs698718, p = 2.74 × 10− 11). Post-GWAS and gene-based analyses identified more than 300 genes that were used for functional and pathway enrichment analyses. Conclusions In summary, this study demonstrates clear confirmation of a previously described NAFLD risk locus and several novel associations. Further collaborative studies including an ethnically diverse population with well-characterized liver histologic features of NAFLD are needed to further validate the novel findings. Electronic supplementary material The online version of this article (10.1186/s12916-019-1364-z) contains supplementary material, which is available to authorized users.

Coronavirus Disease 2019 (COVID-19) emerged as a global pandemic resulting in significant mortality and morbidity. COVID-19 vaccines have been shown to be highly effective in preventing COVID-19 infections and significantly reducing disease severity and mortality. We report on a novel COVID-19 antibody test assay using a unique platform to rapidly detect SARS-CoV-2 antibodies with a drop of fingerstick blood in a subject following COVID-19 vaccination. We show early detection of SARS-CoV-2 antibodies post vaccination and persistence of detectable antibodies for at least 6 months. Rapid point of care COVID-19 antibody tests might have a role in assessing the appearance and durability of immune response following COVID-19 vaccination.

SummaryThe objective of this study is to develop an algorithm to accurately identify children with severe early onset childhood obesity (ages 1–5.99 years) using structured and unstructured data from the electronic health record (EHR).Childhood obesity increases risk factors for cardiovascular morbidity and vascular disease. Accurate definition of a high precision phenotype through a standardize tool is critical to the success of large-scale genomic studies and validating rare monogenic variants causing severe early onset obesity.Rule based and machine learning based algorithms were developed using structured and unstructured data from two EHR databases from Boston Children’s Hospital (BCH) and Cincinnati Children’s Hospital and Medical Center (CCHMC). Exclusion criteria including medications or comorbid diagnoses were defined. Machine learning algorithms were developed using cross-site training and testing in addition to experimenting with natural language processing features.Precision was emphasized for a high fidelity cohort. The rule-based algorithm performed the best overall, 0.895 (CCHMC) and 0.770 (BCH). The best feature set for machine learning employed Unified Medical Language System (UMLS) concept unique identifiers (CUIs), ICD-9 codes, and RxNorm codes.Detecting severe early childhood obesity is essential for the intervention potential in children at the highest long-term risk of developing comorbidities related to obesity and excluding patients with underlying pathological and non-syndromic causes of obesity assists in developing a high-precision cohort for genetic study. Further such phenotyping efforts inform future practical application in health care environments utilizing clinical decision support.Citation: Lingren T, Thaker V, Brady C, Namjou B, Kennebeck S, Bickel J, Patibandla N, Ni Y, Van Driest SL, Chen L, Roach A, Cobb B, Kirby J, Denny J, Bailey-Davis L, Williams MS, Marsolo K, Solti I, Holm IA, Harley J, Kohane IS, Savova G, Crimmins N. Developing an algorithm to detect early childhood obesity in two tertiary pediatric medical centers.

Biorepositories provide access to specimens for biomarker investigation of subjects with or without a given condition or clinical outcome. They must record collection, transport, processing, and storage information to ensure that specimens are fit-for-use once a particular analyte has been identified as a candidate biomarker. Ongoing (post-collection) clinical and outcome documentation provides more value to researchers than a static, clinical snapshot at the time of collection. Frequently, biorepository specimens are residua from those obtained for clinical management of a patient; whether routine clinical processing is acceptable, given the stability profile for a given analyte, will dictate whether non-standard processing will be required. Introducing nonstandard steps into clinical lab processing in order to preserve an analyte such as RNA or protein requires careful workflow planning. Accreditation for biorepositories is now available; standards have been developed to ensure that biorepository personnel, equipment, laboratory space, information systems, and policies/procedures, including those for quality management, meet the same high standards by which clinical laboratories are judged and accredited. An additional accreditation standard relates to the development of, and adherence to, policies surrounding informed consent. The current regulatory landscape for pediatric specimen research requires consideration of many issues around informed consent, assent, and reconsent at the age of majority for the collection and use of identifiable specimens for research. Consideration of these requirements based on the current (and evolving) regulatory landscape can be difficult, in light of pending legislative and regulatory changes. Issues surrounding return of incidental findings is another challenge for institutional review boards.

Introduction: Of the nearly 38 million people in the USA who receive statin therapy, 0.1-0.5% experience severe or life-threatening myopathic side effects. Methods: We performed a genome-wide association study (GWAS) in a group of patients with severe statin myopathy versus a statin-tolerant group to identify genetic susceptibility loci. Results: Replication studies in independent groups of severe statin myopathy (n = 190) and statin-tolerant controls (n = 130) resulted in the identification of three single-nucleotide polymorphisms (SNPs), rs9342288, rs1337512, and rs3857532, in the eyes shut homolog (EYS) on chromosome 6 suggestive of an association with risk for severe statin myopathy (P = 0.0003–0.0008). Analysis of EYS cDNA demonstrated that EYS gene products are complex and expressed with relative abundance in the spinal cord as well as in the retina. Conclusion: Structural similarities of these EYS gene products to members of the Notch signaling pathway and to agrin suggest a possible functional role in the maintenance and regeneration of the structural integrity of skeletal muscle. Muscle Nerve, 2011

Purpose Patients with systemic lupus erythematosus (SLE) frequently develop lupus nephritis (LN), a complication frequently leading to end stage kidney disease. Immune complex deposition in the glomerulus is central to the development of LN. Using a targeted proteomic approach, we tested the hypothesis that autoantibodies targeting glomerular antigens contribute to the development of LN. Experimental design Human podocyte and glomerular proteins were separated by SDS-PAGE and immunoblotted with sera from SLE patients with and without LN. The regions of those gels corresponding to reactive bands observed with sera from LN patients were analyzed using LC-MS/MS. Results LN reactive bands were seen at approximately 50 kDa in podocyte extracts and between 36 and 50 kDa in glomerular extracts. Those bands were analyzed by LC-MS/MS and 102 overlapping proteins were identified. Bioinformatic analysis determined that 36 of those proteins were membrane associated, including a protein previously suggested to contribute to glomerulonephritis and LN, annexin A2. By ELISA, patients with proliferative LN demonstrated significantly increased antibodies against annexin A2. Conclusion and clinical relevance Proteomic approaches identified multiple candidate antigens for autoantibodies in patients with LN. Serum antibodies against annexin A2 were significantly elevated in subjects with proliferative LN, validating those antibodies as potential biomarkers.

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.

Efforts to identify lupus-associated causal variants in the FAM167A/BLK locus on 8p21 are hampered by highly associated noncausal variants. In this report, we used a trans-population mapping and sequencing strategy to identify a common variant (rs922483) in the proximal BLK promoter and a tri-allelic variant (rs1382568) in the upstream alternative BLK promoter as putative causal variants for association with systemic lupus erythematosus. The risk allele (T) at rs922483 reduced proximal promoter activity and modulated alternative promoter usage. Allelic differences at rs1382568 resulted in altered promoter activity in B progenitor cell lines. Thus, our results demonstrated that both lupus-associated functional variants contribute to the autoimmune disease association by modulating transcription of BLK in B cells and thus potentially altering immune responses.

UNLABELLED:To explore the potential influence of the polymorphic 8p23.1 inversion on known autoimmune susceptibility risk at or near BLK locus, we validated a new bioinformatics method that utilizes SNP data to enable accurate, high-throughput genotyping of the 8p23.1 inversion in a Caucasian population. METHODS:Principal components analysis (PCA) was performed using markers inside the inversion territory followed by k-means cluster analyses on 7416 European derived and 267 HapMaP CEU and TSI samples. A logistic regression conditional analysis was performed. RESULTS:Three subgroups have been identified; inversion homozygous, heterozygous and non-inversion homozygous. The status of inversion was further validated using HapMap samples that had previously undergone Fluorescence in situ hybridization (FISH) assays with a concordance rate of above 98%. Conditional analyses based on the status of inversion were performed. We found that overall association signals in the BLK region remain significant after controlling for inversion status. The proportion of lupus cases and controls (cases/controls) in each subgroup was determined to be 0.97 for the inverted homozygous group (1067 cases and 1095 controls), 1.12 for the inverted heterozygous group (1935 cases 1717 controls) and 1.36 for non-inverted subgroups (924 cases and 678 controls). After calculating the linkage disequilibrium between inversion status and lupus risk haplotype we found that the lupus risk haplotype tends to reside on non-inversion background. As a result, a new association effect between non-inversion status and lupus phenotype has been identified ((p = 8.18×10(-7), OR = 1.18, 95%CI = 1.10-1.26). CONCLUSION:Our results demonstrate that both known lupus risk haplotype and inversion status act additively in the pathogenesis of lupus. Since inversion regulates expression of many genes in its territory, altered expression of other genes might also be involved in the development of lupus.

The nematode Caenorhabditis elegans is a powerful model system to study contemporary biological problems. This system would be even more useful if we had mutations in all the genes of this multicellular metazoan. The combined efforts of the C. elegans Deletion Mutant Consortium and individuals within the worm community are moving us ever closer to this goal. At present, of the 20,377 protein-coding genes in this organism, 6764 genes with associated molecular lesions are either deletions or null mutations (WormBase WS220). Our three laboratories have contributed the majority of mutated genes, 6841 mutations in 6013 genes. The principal method we used to detect deletion mutations in the nematode utilizes polymerase chain reaction (PCR). More recently, we have used array comparative genome hybridization (aCGH) to detect deletions across the entire coding part of the genome and massively parallel short-read sequencing to identify nonsense, splicing, and missense defects in open reading frames. As deletion strains can be frozen and then thawed when needed, these strains will be an enduring community resource. Our combined molecular screening strategies have improved the overall throughput of our gene-knockout facilities and have broadened the types of mutations that we and others can identify. These multiple strategies should enable us to eventually identify a mutation in every gene in this multicellular organism. This knowledge will usher in a new age of metazoan genetics in which the contribution to any biological process can be assessed for all genes.

Many autoimmune diseases (ADs) share similar underlying pathology and have a tendency to cluster within families, supporting the involvement of shared susceptibility genes. To date, most of the genetic variants associated with systemic lupus erythematosus (SLE) susceptibility also show association with others ADs. ITGAM and its associated 'predisposing' variant (rs1143679, Arg77His), predicted to alter the tertiary structures of the ligand-binding domain of ITGAM, may play a key role for SLE pathogenesis. The aim of this study is to examine whether the ITGAM variant is also associated with other ADs. We evaluated case-control association between rs1143679 and ADs (N=18,457) including primary Sjögren's syndrome, systemic sclerosis, multiple sclerosis, rheumatoid arthritis, juvenile idiopathic arthritis, celiac disease, and type-1 diabetes. We also performed meta-analyses using our data in addition to available published data. Although the risk allele 'A' is relatively more frequent among cases for each disease, it was not significantly associated with any other ADs tested in this study. However, the meta-analysis for systemic sclerosis was associated with rs1143679 (p meta=0.008). In summary, this study explored the role of ITGAM in general autoimmunity in seven non-lupus ADs, and only found association for systemic sclerosis when our results were combined with published results. Thus ITGAM may not be a general autoimmunity gene but this variant may be specifically associated with SLE and systemic sclerosis. © 2011 Elsevier B.V. Fil: Anaya, Juan Manuel. Universidad Colegio Mayor de Nuestra Señora del Rosario; Colombia Fil: Kim-Howard, Xana. Oklahoma Medical Research Foundation; Estados Unidos Fil: Prahalad, Sampath. Emory University School Of Medicine; Estados Unidos Fil: Cherñavsky, Alejandra Claudia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Medicina. Hospital de Clínicas General San Martín; Argentina Fil: Cañas, Carlos. Fundación Valle del Lili; Colombia Fil: Rojas Villarraga, Adriana. Universidad Colegio Mayor de Nuestra Señora del Rosario; Colombia Fil: Bohnsack, John. University of Utah; Estados Unidos Fil: Jonsson, Roland. University Of Bergen; Noruega Fil: Bolstad, Anne Isine. University Of Bergen; Noruega. Helse Bergen Haukeland University Hospital; Fil: Brun, Johan G.. University Of Bergen; Noruega. Haukeland University Hospital; Noruega Fil: Cobb, Beth. Oklahoma Medical Research Foundation; Estados Unidos Fil: Moser, Kathy L.. Oklahoma Medical Research Foundation; Estados Unidos Fil: James, Judith A.. University Of Oklahoma Health Sciences Center; Estados Unidos. Oklahoma Medical Research Foundation; Estados Unidos Fil: Harley, John B.. University Of Cincinnati College Of Medicine; Estados Unidos Fil: Nath, Swapan K.. Oklahoma Medical Research Foundation; Estados Unidos

Malignant hyperthermia (MH) is a pharmacogenetic, autosomal dominantly inherited disorder of skeletal muscle triggered by volatile anesthetics and infrequently by extreme exertion and heat exposure. MH has variable penetrance with an incidence ranging from 1 in 5,000 to 1 in 50,000–100,000 anesthesias. Mutations in the ryanodine receptor gene, RYR1, are found in 50–70% of cases. We hypothesized that a portion of patients with drug-induced muscle diseases, unrelated to anesthesia, such as severe statin myopathy, have underlying genetic liability that may include RYR1 gene mutations. DNA samples were collected from 885 patients in 4 groups: severe statin myopathy (n=197), mild statin myopathy (n=163), statin-tolerant controls (n=133), and non-drug-induced myopathies of unknown etiology characterized by exercise-induced muscle pain and weakness (n=392). Samples were screened for 105 mutations and variants in 26 genes associated with 7 categories of muscle disease including 34 mutations and variants in the RYR1 gene. Disease-causing mutations or variants in RYR1 were present in 3 severe statin myopathy cases, 1 mild statin myopathy case, 8 patients with non-drug-induced myopathy, and none in controls. These results suggest that disease-causing mutations and certain variants in the RYR1 gene may contribute to underlying genetic risk for non-anesthesia-induced myopathies and should be included in genetic susceptibility screening in patients with severe statin myopathy and in patients with non-statin-induced myopathies of unknown etiology.

Primary Sjogren's syndrome (pSS) is a complex autoimmune disease that is incompletely understood. The principal manifestations of pSS are dry eyes and dry mouth due to lymphocytic infiltration of the salivary and lacrimal glands. Like lupus, women are affected by pSS over nine times more than with men. The association of human leucocyte antigen loci with pSS and other autoimmune diseases is well documented.1,–,3 A genetic association of the methyl-CpG binding protein 2 ( MECP2 ) gene with lupus has been reported and confirmed in multiple independent cohorts.4 5 Herein, we examine the genetic association between MECP2 and pSS in a large cohort of pSS patients and healthy controls. We studied a cohort of 460 European-derived independent pSS patients (423 women and 37 men) and 1828 ethnically matched normal healthy controls (1279 women and 549 men). All patients fulfiled the American–European Consensus Group classification criteria for pSS.6 Our study protocols were …

Introduction Behcet's disease is a chronic systemic inflammatory disease that remains incompletely understood. Herein, we perform the first genome-wide association study in Behcet's disease. Methods Using DNA pooling technology and the Affymetrix 500K arrays, we identified possible candidate gene associations with Behcet's disease in a cohort of 152 Behcet's disease patients and 172 healthy ethnically matched controls. Genetic loci that were identified in the pooling study were genotyped in patients and controls using TaqMan genotyping technology. Results We identified genetic associations between Behcet's disease and single-nucleotide polymorphisms ( SNPs) in KIAA1529, CPVL, LOC100129342, UBASH3B, and UBAC2 ( odds ratio = 2.04, 2.26, 1.84, 1.71, and 1.61, respectively; P value = 4.2 x 10(-5), 1.0 x 10(-4), 3.0 x 10(-4), 1.5 x 10(-3), and 5.8 x 10(-3), respectively). Among the associated SNPs, the Behcet's disease-risk allele in rs2061634 leads to substitution of serine to cysteine at amino acid position 995 (S995C) in the KIAA1529 protein. Conclusions Using an unbiased whole-genome genetic association approach, we identified novel candidate genetic loci that are associated with increased susceptibility for Behcet's disease. These findings will help to better understand the pathogenesis of Behcet's disease and identify novel targets for therapeutic intervention.

The evidence for a strong genetic component conferring susceptibility to primary Sjogren's syndrome (SS) is mounting. Several associations with SS have been reported and provide evidence that the HLA region harbors important susceptibility loci and that multiple genes outside the HLA region play a role. Genetic discovery lags behind success observed in related autoimmune diseases. Identifying genetic factors that cause SS will allow more precise definition of pathogenic mechanisms leading to the overall SS phenotype and clinically heterogeneous subsets of patients. Critical opportunities are certain to follow for translation into improved diagnosis and therapies for SS and its spectrum diseases.

Systemic lupus erythematosus (SLE) is a common systemic autoimmune disease with complex etiology but strong clustering in families (lambda(S) = approximately 30). We performed a genome-wide association scan using 317,501 SNPs in 720 women of European ancestry with SLE and in 2,337 controls, and we genotyped consistently associated SNPs in two additional independent sample sets totaling 1,846 affected women and 1,825 controls. Aside from the expected strong association between SLE and the HLA region on chromosome 6p21 and the previously confirmed non-HLA locus IRF5 on chromosome 7q32, we found evidence of association with replication (1.1 x 10(-7)P(overall)1.6 x 10(-23); odds ratio = 0.82-1.62) in four regions: 16p11.2 (ITGAM), 11p15.5 (KIAA1542), 3p14.3 (PXK) and 1q25.1 (rs10798269). We also found evidence for association (P1 x 10(-5)) at FCGR2A, PTPN22 and STAT4, regions previously associated with SLE and other autoimmune diseases, as well as ator =9 other loci (P2 x 10(-7)). Our results show that numerous genes, some with known immune-related functions, predispose to SLE.

Sjögren's syndrome (SS) is a complex polygenic autoimmune disorder. A few major genetic effects have been identified. Historically, HLA and non-HLA genetic associations have been reported. Recently, the HLA region continued to reveal association findings. A new susceptibility region has been suggested by a study of a D6S349 microsatellite marker. Among non-HLA studies, recent association of immunoglobulin kappa chain allotype KM1 with anti-La autoantibodies in primary Sjögren's syndrome confirms findings in a study from two decades ago. Meanwhile, mouse models have been employed to study the genetic contribution to salivary lymphadenitis or dry eyes and mouth. Gene transfer exploration in mouse models shows promise. The authors review the HLA and non-HLA association studies and the mouse model work that has been reported. Newly developed genomic capacity will provide, in the future, a much closer approximation of the true picture of the genetic architecture of Sjögren's syndrome.

Background: Genomic medicine has the potential to improve care by tailoring treatments to the individual. There is consensus in the literature that pharmacogenomics (PGx) may be an ideal starting point for real-world implementation, due to the presence of well-characterized drug-gene interactions. Clinical Decision Support (CDS) is an ideal avenue by which to implement PGx at the bedside. Previous literature has established theoretical models for PGx CDS implementation and discussed a number of anticipated real-world challenges. However, work detailing actual PGx CDS implementation experiences has been limited. Anticipated challenges include data storage and management, system integration, physician acceptance, and more. Methods: In this study, we analyzed the experiences of ten members of the Electronic Medical Records and Genomics (eMERGE) Network, and one affiliate, in their attempts to implement PGx CDS. We examined the resulting PGx CDS system characteristics and conducted a survey to understand the unanticipated implementation challenges sites encountered. Results: Ten sites have successfully implemented at least one PGx CDS rule in the clinical setting. The majority of sites elected to create an Omic Ancillary System (OAS) to manage genetic and genomic data. All sites were able to adapt their existing CDS tools for PGx knowledge. The most common and impactful delays were not PGx-specific issues. Instead, they were general IT implementation problems, with top challenges including team coordination/communication and staffing. The challenges encountered caused a median total delay in system go-live of approximately two months. Conclusions: These results suggest that barriers to PGx CDS implementations are generally surmountable. Moreover, PGx CDS implementation may not be any more difficult than other healthcare IT projects of similar scope, as the most significant delays encountered were not unique to genomic medicine. These are encouraging results for any institution considering implementing a PGx CDS tool, and for the advancement of genomic medicine.