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Michael E March,1 Patrick MA Sleiman,1 Hakon Hakonarson1,2 1Center for Applied Genomics, Abramson Research Center of the Joseph Stokes Jr Research Institute, The Children's Hospital of Philadelphia, 2Department of Pediatrics, University of Pennsylvania School of Medicine, Philadelphia, USA Abstract: As complex common diseases, asthma and allergic diseases are caused by the interaction of multiple genetic variants with a variety of environmental factors. Candidate-gene studies have examined the involvement of a very large list of genes in asthma and allergy, demonstrating a role for more than 100 loci. These studies have elucidated several themes in the biology and pathogenesis of these diseases. A small number of genes have been associated with asthma or allergy through traditional linkage analyses. The publication of the first asthma-focused genome-wide association (GWA) study in 2007 has been followed by nearly 30 reports of GWA studies targeting asthma, allergy, or associated phenotypes and quantitative traits. GWA studies have confirmed several candidate genes and have identified new, unsuspected, and occasionally uncharacterized genes as asthma susceptibility loci. Issues of results replication persist, complicating interpretation and making conclusions difficult to draw, and much of the heritability of these diseases remains undiscovered. In the coming years studies of complex diseases like asthma and allergy will probably involve the use of high-throughput next-generation sequencing, which will bring a tremendous influx of new information as well as new problems in dealing with vast datasets. Keywords: genome-wide association study, high-throughput next-generation sequencing, allergy, environmental irritant, allergen

Study Objectives: To identify genetic susceptibility variants in pediatric obstructive sleep apnea in European American and African American children., Methods: A phenotyping algorithm using electronic medical records was developed to recruit cases with OSA and control subjects from the Center for Applied Genomics at Children's Hospital of Philadelphia (CHOP). Genome-wide association studies (GWAS) were performed in pediatric OSA cases and control subjects with European American (EA) and African American (AA) ancestry followed by meta-analysis and sex stratification., Results: The algorithm accrued 1486 subjects (46.3% European American, 53.7% African American). We identified genomic loci at 1p36.22 and 15q26.1 that associated with OSA risk in EA and AA, respectively. We also revealed a shared risk locus at 18p11.32 (rs114124196, p = 1.72 × 10-8) across EA and AA populations. Additionally, association at 1q43 (rs12754698) and 2p25.1 (rs72775219) was identified in the male-only analysis of EA children with OSA, while association at 8q21.11 (rs6472959), 11q24.3 (rs4370952) and 15q21.1 (rs149936782) was detected in the female-only analysis of EA children and association at 18p11.23 (rs9964029) was identified in the female-only analysis of African-American children. Moreover, the 18p11.32 locus was replicated in an EA cohort (rs114124196, p = 8.8 × 10-3)., Conclusions: We report the first GWAS for pediatric OSA in European Americans and African Americans. Our results provide novel insights to the genetic underpins of pediatric OSA., (© The Author(s) 2022. Published by Oxford University Press on behalf of Sleep Research Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background & Aims: Biliary atresia (BA) is poorly understood and leads to liver transplantation (LT), with the requirement for and associated risks of lifelong immunosuppression, in most children. We performed a genome-wide association study (GWAS) to determine the genetic basis of BA., Methods: We performed a GWAS in 811 European BA cases treated with LT in US, Canadian and UK centers, and 4,654 genetically matched controls. Whole-genome sequencing of 100 cases evaluated synthetic association with rare variants. Functional studies included whole liver transcriptome analysis of 64 BA cases and perturbations in experimental models., Results: A GWAS of common single nucleotide polymorphisms (SNPs), i.e. allele frequencies >1%, identified intronic SNPs rs6446628 in AFAP1 with genome-wide significance (p = 3.93E-8) and rs34599046 in TUSC3 at sub-threshold genome-wide significance (p = 1.34E-7), both supported by credible peaks of neighboring SNPs. Like other previously reported BA-associated genes, AFAP1 and TUSC3 are ciliogenesis and planar polarity effectors (CPLANE). In gene-set-based GWAS, BA was associated with 6,005 SNPs in 102 CPLANE genes (p = 5.84E-15). Compared with non-CPLANE genes, more CPLANE genes harbored rare variants (allele frequency <1%) that were assigned Human Phenotype Ontology terms related to hepatobiliary anomalies by predictive algorithms, 87% vs. 40%, p <0.0001. Rare variants were present in multiple genes distinct from those with BA-associated common variants in most BA cases. AFAP1 and TUSC3 knockdown blocked ciliogenesis in mouse tracheal cells. Inhibition of ciliogenesis caused biliary dysgenesis in zebrafish. AFAP1 and TUSC3 were expressed in fetal liver organoids, as well as fetal and BA livers, but not in normal or disease-control livers. Integrative analysis of BA-associated variants and liver transcripts revealed abnormal vasculogenesis and epithelial tube formation, explaining portal vein anomalies that co-exist with BA., Conclusions: BA is associated with polygenic susceptibility in CPLANE genes. Rare variants contribute to polygenic risk in vulnerable pathways via unique genes., Impact and Implications: Liver transplantation is needed to cure most children born with biliary atresia, a poorly understood rare disease. Transplant immunosuppression increases the likelihood of life-threatening infections and cancers. To improve care by preventing this disease and its progression to transplantation, we examined its genetic basis. We find that this disease is associated with both common and rare mutations in highly specialized genes which maintain normal communication and movement of cells, and their organization into bile ducts and blood vessels during early development of the human embryo. Because defects in these genes also cause other birth defects, our findings could lead to preventive strategies to lower the incidence of biliary atresia and potentially other birth defects., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Neurodevelopmental disorders (NDDs), such as attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD), are examples of complex and partially overlapping phenotypes that often lack definitive corroborating genetic information. ADHD and ASD have complex genetic associations implicated by rare recurrent copy number variations (CNVs). Both of these NDDs have been shown to share similar biological etiologies as well as genetic pleiotropy., Methods: Platforms aimed at investigating genetic-based associations, such as high-density microarray technologies, have been groundbreaking techniques in the field of complex diseases, aimed at elucidating the underlying disease biology. Previous studies have uncovered CNVs associated with genes within shared candidate genomic networks, including glutamate receptor genes, across multiple different NDDs. To examine shared biological pathways across two of the most common NDDs, we investigated CNVs across 15,689 individuals with ADHD (n = 7920), ASD (n = 4318), or both (n = 3,416), as well as 19,993 controls. Cases and controls were matched by genotype array (i.e., Illumina array versions). Three case-control association studies each calculated and compared the observed vs. expected frequency of CNVs across individual genes, loci, pathways, and gene networks. Quality control measures of confidence in CNV-calling, prior to association analyses, included visual inspection of genotype and hybridization intensity., Results: Here, we report results from CNV analysis in search for individual genes, loci, pathways, and gene networks. To extend our previous observations implicating a key role of the metabotropic glutamate receptor (mGluR) network in both ADHD and autism, we exhaustively queried patients with ASD and/or ADHD for CNVs associated with the 273 genomic regions of interest within the mGluR gene network (genes with one or two degrees protein-protein interaction with mGluR 1-8 genes). Among CNVs in mGluR network genes, we uncovered CNTN4 deletions enriched in NDD cases (P = 3.22E - 26, OR = 2.49). Additionally, we uncovered PRLHR deletions in 40 ADHD cases and 12 controls (P = 5.26E - 13, OR = 8.45) as well as clinically diagnostic relevant 22q11.2 duplications and 16p11.2 duplications in 23 ADHD + ASD cases and 9 controls (P = 4.08E - 13, OR = 15.05) and 22q11.2 duplications in 34 ADHD + ASD cases and 51 controls (P = 9.21E - 9, OR = 3.93); those control samples were not with previous 22qDS diagnosis in their EHR records., Conclusion: Together, these results suggest that disruption in neuronal cell-adhesion pathways confers significant risk to NDDs and showcase that rare recurrent CNVs in CNTN4, 22q11.2, and 16p11.2 are overrepresented in NDDs that constitute patients predominantly suffering from ADHD and ASD., Trial Registration: ClinicalTrials.gov Identifier: NCT02286817 First Posted: 10 November 14, ClinicalTrials.gov Identifier: NCT02777931 first posted: 19 May 2016, ClinicalTrials.gov Identifier: NCT03006367 first posted: 30 December 2016, ClinicalTrials.gov Identifier: NCT02895906 first posted: 12 September 2016., (© 2023. The Author(s).)

Leveraging linkage disequilibrium (LD) patterns as representative of population substructure enables the discovery of additive association signals in genome-wide association studies (GWASs). Standard GWASs are well-powered to interrogate additive models; however, new approaches are required for invesigating other modes of inheritance such as dominance and epistasis. Epistasis, or non-additive interaction between genes, exists across the genome but often goes undetected because of a lack of statistical power. Furthermore, the adoption of LD pruning as customary in standard GWASs excludes detection of sites that are in LD but might underlie the genetic architecture of complex traits. We hypothesize that uncovering long-range interactions between loci with strong LD due to epistatic selection can elucidate genetic mechanisms underlying common diseases. To investigate this hypothesis, we tested for associations between 23 common diseases and 5,625,845 epistatic SNP-SNP pairs (determined by Ohta's D statistics) in long-range LD (>0.25 cM). Across five disease phenotypes, we identified one significant and four near-significant associations that replicated in two large genotype-phenotype datasets (UK Biobank and eMERGE). The genes that were most likely involved in the replicated associations were (1) members of highly conserved gene families with complex roles in multiple pathways, (2) essential genes, and/or (3) genes that were associated in the literature with complex traits that display variable expressivity. These results support the highly pleiotropic and conserved nature of variants in long-range LD under epistatic selection. Our work supports the hypothesis that epistatic interactions regulate diverse clinical mechanisms and might especially be driving factors in conditions with a wide range of phenotypic outcomes., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2023 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Improved copy number variation (CNV) detection remains an area of heavy emphasis for algorithm development; however, both CNV curation and disease association approaches remain in its infancy. The current practice of focusing on candidate CNVs, where researchers study specific CNVs they believe to be pathological while discarding others, refrains from considering the full spectrum of CNVs in a hypothesis-free GWAS. To address this, we present a next-generation approach to CNV association by natively supporting the popular VCF specification for sequencing-derived variants as well as SNP array calls using a PennCNV format. The code is fast and efficient, allowing for the analysis of large (>100,000 sample) cohorts without dividing up the data on a compute cluster. The scripts are condensed into a single tool to promote simplicity and best practices. CNV curation pre and post-association is rigorously supported and emphasized to yield reliable results of highest quality. We benchmarked two large datasets, including the UK Biobank (n > 450,000) and CAG Biobank (n > 350,000) both of which are genotyped at >0.5 M probes, for our input files. ParseCNV has been actively supported and developed since 2008. ParseCNV2 presents a critical addition to formalizing CNV association for inclusion with SNP associations in GWAS Catalog. Clinical CNV prioritization, interactive quality control (QC), and adjustment for covariates are revolutionary new features of ParseCNV2 vs. ParseCNV. The software is freely available at: https://github.com/CAG-CNV/ParseCNV2 ., (© 2022. The Author(s), under exclusive licence to European Society of Human Genetics.)

LIGHT (homologous to lymphotoxins, exhibits inducible expression, and competes with HSV glycoprotein D for herpes virus entry mediator, a receptor expressed by T lymphocytes), encoded by the TNFSF14 gene, is a cytokine belonging to the TNF superfamily. On binding to its receptors, herpes virus entry mediator and lymphotoxin β receptor, it activates inflammatory responses. We conducted this study to determine whether plasma LIGHT levels are elevated in Crohn's disease (CD) in a pediatric population with the aim of nominating this cytokine as a therapeutic target. We used a single-molecule immunoassay to determine the circulating levels of free LIGHT in plasma from pediatric patients with CD in our biobank (n = 183), a panel of healthy pediatric (n = 9) or adult (n = 22) reference samples, and pediatric biobank controls (n = 19). We performed correlational analyses between LIGHT levels and the clinical characteristics of the CD cohort, including age, Montreal classification, family history, medical/surgical therapy, and routine blood test parameters. LIGHT levels were greatly elevated in CD, with an average of 305 versus 32.4 pg/ml for controls from the biobank (p < 0.0001). The outside reference samples showed levels of 57 pg/ml in pediatric controls and 55 pg/ml in adults (p < 0.0001). We found a statistically significant correlation between white blood cell count and free LIGHT (p < 0.046). We conclude that free, soluble LIGHT is increased 5- to 10-fold in pediatric CD across an array of disease subtypes and characteristics., (Copyright © 2023 by The American Association of Immunologists, Inc.)

Mental disorders present a global health concern and have limited treatment options. In today's medical practice, medications such as antidepressants are prescribed not only for depression but also for conditions such as anxiety and attention deficit hyperactivity disorder (ADHD). Therefore, identifying gene targets for specific disorders is important and offers improved precision. In this study, we performed a genetic analysis of six common mental disorders-ADHD, anxiety, depression, delays in mental development, intellectual disabilities (IDs) and speech/language disorder-in the ethnic minority of African Americans (AAs) using whole genome sequencing (WGS). WGS data were generated from blood-derived DNA from 4178 AA individuals, including 1384 patients with the diagnosis of at least one mental disorder. Mutation burden analysis was applied based on rare and deleterious mutations in the AA population between cases and controls, and further analyzed in the context of patients with single mental disorder diagnosis. Certain genes uncovered demonstrated significant P-values in mutation burden analysis. In addition, exclusive recurrences in specific type of disorder were scanned through gene-drug interaction databases to assess for availability of potential medications. We uncovered 15 genes harboring deleterious mutations, including 3-Hydroxy-3-Methylglutaryl-CoA Reductase (HMGCR) and Uronyl 2-Sulfotransferase (UST) for ADHD; Farnesyltransferase, CAAX Box, Beta (FNTB) for anxiety; Xin Actin Binding Repeat Containing 2 (XIRP2), Natriuretic Peptide C (NPPC), Serine/Threonine Kinase 33 (STK33), Pannexin 1 (PANX1) and Neurotensin (NTS) for depression; RUNX Family Transcription Factor 3 (RUNX3), Tachykinin Receptor 1 (TACR1) and NADH:Ubiquinone Oxidoreductase Core Subunit S7 (NDUFS7) for delays in mental development; Hepsin (HPN) for ID and Collagen Type VI Alpha 3 Chain (COL6A3), Damage Specific DNA Binding Protein 1 (DDB1) and NADH:Ubiquinone Oxidoreductase Subunit A11 (NDUFA11) for speech/language disorder. Taken together, we have established critical insights into the development of new precision medicine approaches for mental disorders in AAs., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

The uptick in SARS-CoV-2 infection has resulted in a worldwide COVID-19 pandemic, which has created troublesome health and economic problems. We performed case-control meta-analyses in both African and European ethnicity COVID-19 disease cases based on laboratory test and phenotypic criteria. The cases had laboratory-confirmed SARS-CoV-2 infection. We uniquely investigated COVID infection genetics in a pediatric population. Our cohort has a large African ancestry component, also unique to our study. We tested for genetic variant association in 498 cases vs. 1,533 controls of African ancestry and 271 cases vs. 855 controls of European ancestry. We acknowledge that the sample size is relatively small, owing to the low prevalence of COVID infection among pediatric individuals. COVID-19 cases averaged 13 years of age. Pediatric genetic studies enhance the ability to detect genetic associations with a limited possible environment impact. Our findings support the notion that some genetic variants, most notably at the SEMA6D, FMN1, ACTN1, PDS5B, NFIA, ADGRL3, MMP27, TENM3, SPRY4, MNS1, and RSU1 loci, play a role in COVID-19 infection susceptibility. The pediatric cohort also shows nominal replication of previously reported adult study results: CCR9, CXCR6, FYCO1, LZTFL1, TDGF1, CCR1, CCR2, CCR3, CCR5, MAPT-AS1, and IFNAR2 gene variants. Reviewing the biological roles of genes implicated here, NFIA looks to be the most interesting as it binds to a palindromic sequence observed in both viral and cellular promoters and in the adenovirus type 2 origin of replication., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Glessner, Chang, Mentch, Qu, Abrams, Thomas, Sleiman and Hakonarson.)

Objective: Juvenile idiopathic arthritis (JIA) is the most common chronic immune-mediated joint disease among children and encompasses a heterogeneous group of immune-mediated joint disorders classified into 7 subtypes according to clinical presentation. However, phenotype overlap and biologic evidence suggest a shared mechanistic basis between subtypes. This study was undertaken to systematically investigate shared genetic underpinnings of JIA subtypes., Methods: We performed a heterogeneity-sensitive genome-wide association study encompassing a total of 1,245 JIA cases (classified into 7 subtypes) and 9,250 controls, followed by fine-mapping of candidate causal variants at each genome-wide significant locus, functional annotation, and pathway and network analysis. We further identified candidate drug targets and drug repurposing opportunities by in silico analyses., Results: In addition to the major histocompatibility complex locus, we identified 15 genome-wide significant loci shared between at least 2 JIA subtypes, including 10 novel loci. Functional annotation indicated that candidate genes at these loci were expressed in diverse immune cell types., Conclusion: This study identified novel genetic loci shared by JIA subtypes. Our findings identified candidate mechanisms underlying JIA subtypes and candidate targets with drug repurposing opportunities for JIA treatment., (© 2022 The Authors. Arthritis & Rheumatology published by Wiley Periodicals LLC on behalf of American College of Rheumatology.)

Background: In over half of pediatric cases, ADHD presents with comorbidities, and often, it is unclear whether the symptoms causing impairment are due to the comorbidity or the underlying ADHD. Comorbid conditions increase the likelihood for a more severe and persistent course and complicate treatment decisions. Therefore, it is highly important to establish an algorithm that identifies ADHD and comorbidities in order to improve research on ADHD using biorepository and other electronic record data., Methods: It is feasible to accurately distinguish between ADHD in isolation from ADHD with comorbidities using an electronic algorithm designed to include other psychiatric disorders. We sought to develop an EHR phenotype algorithm to discriminate cases with ADHD in isolation from cases with ADHD with comorbidities more effectively for efficient future searches in large biorepositories. We developed a multi-source algorithm allowing for a more complete view of the patient's EHR, leveraging the biobank of the Center for Applied Genomics (CAG) at Children's Hospital of Philadelphia (CHOP). We mined EHRs from 2009 to 2016 using International Statistical Classification of Diseases and Related Health Problems (ICD) codes, medication history and keywords specific to ADHD, and comorbid psychiatric disorders to facilitate genotype-phenotype correlation efforts. Chart abstractions and behavioral surveys added evidence in support of the psychiatric diagnoses. Most notably, the algorithm did not exclude other psychiatric disorders, as is the case in many previous algorithms. Controls lacked psychiatric and other neurological disorders. Participants enrolled in various CAG studies at CHOP and completed a broad informed consent, including consent for prospective analyses of EHRs. We created and validated an EHR-based algorithm to classify ADHD and comorbid psychiatric status in a pediatric healthcare network to be used in future genetic analyses and discovery-based studies., Results: In this retrospective case-control study that included data from 51,293 subjects, 5840 ADHD cases were discovered of which 46.1% had ADHD alone and 53.9% had ADHD with psychiatric comorbidities. Our primary study outcome was to examine whether the algorithm could identify and distinguish ADHD exclusive cases from ADHD comorbid cases. The results indicate ICD codes coupled with medication searches revealed the most cases. We discovered ADHD-related keywords did not increase yield. However, we found including ADHD-specific medications increased our number of cases by 21%. Positive predictive values (PPVs) were 95% for ADHD cases and 93% for controls., Conclusion: We established a new algorithm and demonstrated the feasibility of the electronic algorithm approach to accurately diagnose ADHD and comorbid conditions, verifying the efficiency of our large biorepository for further genetic discovery-based analyses., Trial Registration: ClinicalTrials.gov, NCT02286817 . First posted on 10 November 2014., Clinicaltrials: gov, NCT02777931 . First posted on 19 May 2016., Clinicaltrials: gov, NCT03006367 . First posted on 30 December 2016., Clinicaltrials: gov, NCT02895906 . First posted on 12 September 2016., (© 2022. The Author(s).)

Background: The vast majority of chronic myeloid leukemia (CML) patients have a single translocation t(9;22)(q34;q11), BCR/ABL1 fusion genes, which is regarded as the hallmark of CML. However, around 5 to 10% of CML patients exhibit the involvement of a third chromosome. In some very rare cases a fourth or even fifth chromosome can be involved with the t(9;22)., Methods: This case report is based on a 40-year-old Saudi Arabian male patient, diagnosed with CML in lymphoid blast crisis, and observed to have a four-way 46 XY, t(9;22;5;2)(q34;q11.2;p13;q44) translocation. The BCR/ABL1 fusion was identified by fluorescent in situ hybridization (FISH). Additionally, the BCR/ABL1 p210 mRNA fusion transcripts were identified by a molecular test., Results: The clinical and prognostic impact of additional partner chromosomes to t(9;22) remains unknown. The CML patient with this novel four-way translocation t(9;22;5;2) progressed to blast crisis and was resistant to Tyrosine Kinase Inhibitor (TKI) therapy. Therefore, this case is more in alignment with the negative impact of additional partner chromosomes to the translocation at t(9;22)., Conclusion: Here we report for the first time a novel four-way translocation at t(9;22;5;2)(q34;q11.2;p13;q44)., (© 2022 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals LLC.)

Importance: Knowledge about the spectrum of diseases associated with hereditary cancer syndromes may improve disease diagnosis and management for patients and help to identify high-risk individuals., Objective: To identify phenotypes associated with hereditary cancer genes through a phenome-wide association study., Design, Setting, and Participants: This phenome-wide association study used health data from participants in 3 cohorts. The Electronic Medical Records and Genomics Sequencing (eMERGEseq) data set recruited predominantly healthy individuals from 10 US medical centers from July 16, 2016, through February 18, 2018, with a mean follow-up through electronic health records (EHRs) of 12.7 (7.4) years. The UK Biobank (UKB) cohort recruited participants from March 15, 2006, through August 1, 2010, with a mean (SD) follow-up of 12.4 (1.0) years. The Hereditary Cancer Registry (HCR) recruited patients undergoing clinical genetic testing at Vanderbilt University Medical Center from May 1, 2012, through December 31, 2019, with a mean (SD) follow-up through EHRs of 8.8 (6.5) years., Exposures: Germline variants in 23 hereditary cancer genes. Pathogenic and likely pathogenic variants for each gene were aggregated for association analyses., Main Outcomes and Measures: Phenotypes in the eMERGEseq and HCR cohorts were derived from the linked EHRs. Phenotypes in UKB were from multiple sources of health-related data., Results: A total of 214 020 participants were identified, including 23 544 in eMERGEseq cohort (mean [SD] age, 47.8 [23.7] years; 12 611 women [53.6%]), 187 234 in the UKB cohort (mean [SD] age, 56.7 [8.1] years; 104 055 [55.6%] women), and 3242 in the HCR cohort (mean [SD] age, 52.5 [15.5] years; 2851 [87.9%] women). All 38 established gene-cancer associations were replicated, and 19 new associations were identified. These included the following 7 associations with neoplasms: CHEK2 with leukemia (odds ratio [OR], 3.81 [95% CI, 2.64-5.48]) and plasma cell neoplasms (OR, 3.12 [95% CI, 1.84-5.28]), ATM with gastric cancer (OR, 4.27 [95% CI, 2.35-7.44]) and pancreatic cancer (OR, 4.44 [95% CI, 2.66-7.40]), MUTYH (biallelic) with kidney cancer (OR, 32.28 [95% CI, 6.40-162.73]), MSH6 with bladder cancer (OR, 5.63 [95% CI, 2.75-11.49]), and APC with benign liver/intrahepatic bile duct tumors (OR, 52.01 [95% CI, 14.29-189.29]). The remaining 12 associations with nonneoplastic diseases included BRCA1/2 with ovarian cysts (OR, 3.15 [95% CI, 2.22-4.46] and 3.12 [95% CI, 2.36-4.12], respectively), MEN1 with acute pancreatitis (OR, 33.45 [95% CI, 9.25-121.02]), APC with gastritis and duodenitis (OR, 4.66 [95% CI, 2.61-8.33]), and PTEN with chronic gastritis (OR, 15.68 [95% CI, 6.01-40.92])., Conclusions and Relevance: The findings of this genetic association study analyzing the EHRs of 3 large cohorts suggest that these new phenotypes associated with hereditary cancer genes may facilitate early detection and better management of cancers. This study highlights the potential benefits of using EHR data in genomic medicine.

Background: Asthma is a complex condition largely attributed to the interactions among genes and environments as a heterogeneous phenotype. Obesity is significantly associated with asthma development, and genetic studies on obese vs. non-obese asthma are warranted., Methods: To investigate asthma in the minority African American (AA) population with or without obesity, we performed a whole genome sequencing (WGS) study on blood-derived DNA of 4289 AA individuals, included 2226 asthma patients (1364 with obesity and 862 without obesity) and 2006 controls without asthma. The burden analysis of functional rare coding variants was performed by comparing asthma vs. controls and by stratified analysis of obese vs. non-obese asthma, respectively., Results: Among the top 66 genes with P < 0.01 in the asthma vs. control analysis, stratified analysis by obesity showed inverse correlation of natural logarithm (LN) of P value between obese and non-obese asthma (r = - 0.757, P = 1.90E-13). Five genes previously reported in a genome-wide association study (GWAS) on asthma, including TSLP, SLC9A4, PSMB8, IGSF5, and IKZF4 were demonstrated association in the asthma vs. control analysis. The associations of IKZF4 and IGSF5 are only associated with obese asthma; and the association of SLC9A4 is only observed in non-obese asthma. In addition, the association of RSPH3 (the gene is related to primary ciliary dyskinesia) is observed in non-obese asthma., Conclusions: These findings highlight genetic heterogeneity between obese and non-obese asthma in patients of AA ancestry., (© 2022. The Author(s).)

Mental disorders present a global health concern, while the diagnosis of mental disorders can be challenging. The diagnosis is even harder for patients who have more than one type of mental disorder, especially for young toddlers who are not able to complete questionnaires or standardized rating scales for diagnosis. In the past decade, multiple genomic association signals have been reported for mental disorders, some of which present attractive drug targets. Concurrently, machine learning algorithms, especially deep learning algorithms, have been successful in the diagnosis and/or labeling of complex diseases, such as attention deficit hyperactivity disorder (ADHD) or cancer. In this study, we focused on eight common mental disorders, including ADHD, depression, anxiety, autism, intellectual disabilities, speech/language disorder, delays in developments, and oppositional defiant disorder in the ethnic minority of African Americans. Blood-derived whole genome sequencing data from 4179 individuals were generated, including 1384 patients with the diagnosis of at least one mental disorder. The burden of genomic variants in coding/non-coding regions was applied as feature vectors in the deep learning algorithm. Our model showed ~65% accuracy in differentiating patients from controls. Ability to label patients with multiple disorders was similarly successful, with a hamming loss score less than 0.3, while exact diagnostic matches are around 10%. Genes in genomic regions with the highest weights showed enrichment of biological pathways involved in immune responses, antigen/nucleic acid binding, chemokine signaling pathway, and G-protein receptor activities. A noticeable fact is that variants in non-coding regions (e.g., ncRNA, intronic, and intergenic) performed equally well as variants in coding regions; however, unlike coding region variants, variants in non-coding regions do not express genomic hotspots whereas they carry much more narrow standard deviations, indicating they probably serve as alternative markers., (© 2021. The Author(s).)

Previous genome-wide association studies revealed multiple common variants involved in eczema but the role of rare variants remains to be elucidated. Here, we investigate the role of rare variants in eczema susceptibility. We meta-analyze 21 study populations including 20,016 eczema cases and 380,433 controls. Rare variants are imputed with high accuracy using large population-based reference panels. We identify rare exonic variants in DUSP1, NOTCH4, and SLC9A4 to be associated with eczema. In DUSP1 and NOTCH4 missense variants are predicted to impact conserved functional domains. In addition, five novel common variants at SATB1-AS1/KCNH8, TRIB1/LINC00861, ZBTB1, TBX21/OSBPL7, and CSF2RB are discovered. While genes prioritized based on rare variants are significantly up-regulated in the skin, common variants point to immune cell function. Over 20% of the single nucleotide variant-based heritability is attributable to rare and low-frequency variants. The identified rare/low-frequency variants located in functional protein domains point to promising targets for novel therapeutic approaches to eczema., (© 2021. The Author(s).)

Despite experimental data linking HIF-1α dysfunction to inflammatory airway conditions, the effect of single nucleotide polymorphisms within the HIF1A gene on these conditions remains poorly understood. In the current study, we complete a phenotype wide association study to assess the link between SNPs with known disease associations and respiratory phenotypes. We report two SNPs of the HIF1A gene, the intronic rs79865957 and the missense rs41508050. In these positions the A and the T allele are significantly associated with allergic rhinitis and acute bronchitis and bronchiolitis, respectively. These findings further support the role of HIF-1α in inflammatory pulmonary conditions and may serve as a basis to refine our understanding of other HIF-1α associated phenotypes., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Kelchtermans, Chang, March, Mentch, Sleiman and Hakonarson.)

Copy number variations (CNVs) are an important class of variations contributing to the pathogenesis of many disease phenotypes. Detecting CNVs from genomic data remains difficult, and the most currently applied methods suffer from an unacceptably high false positive rate. A common practice is to have human experts manually review original CNV calls for filtering false positives before further downstream analysis or experimental validation. Here, we propose DeepCNV, a deep learning-based tool, intended to replace human experts when validating CNV calls, focusing on the calls made by one of the most accurate CNV callers, PennCNV. The sophistication of the deep neural network algorithm is enriched with over 10 000 expert-scored samples that are split into training and testing sets. Variant confidence, especially for CNVs, is a main roadblock impeding the progress of linking CNVs with the disease. We show that DeepCNV adds to the confidence of the CNV calls with an optimal area under the receiver operating characteristic curve of 0.909, exceeding other machine learning methods. The superiority of DeepCNV was also benchmarked and confirmed using an experimental wet-lab validation dataset. We conclude that the improvement obtained by DeepCNV results in significantly fewer false positive results and failures to replicate the CNV association results., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

With polygenic risk score (PRS) for autoimmune type 1 diabetes (T1D), this study identified T1D cases with low T1D PRS and searched for susceptibility loci in these cases. Our hypothesis is that genetic effects (likely mediated by relatively rare genetic variants) of non-mainstream (or non-autoimmune) T1D might have been diluted in the previous studies on T1D cases in general. Two cohorts for the PRS modeling and testing respectively were included. The first cohort consisted of 3302 T1D cases and 6181 controls, and the independent second cohort consisted of 3297 T1D cases and 6169 controls. Cases with low T1D PRS were identified using PRSice-2 and compared to controls with low T1D PRS by genome-wide association (GWA) test. Thirteen novel genetic loci with high imputation quality (Quality Score r 2  > 0.91) were identified of SNPs/SNVs associated with low PRS T1D at genome-wide significance (P ≤ 5.0 × E-08), in addition to 4 established T1D loci, 3 reported loci by our previous study, as well as 9 potential novel loci represented by rare SNVs, but with relatively low imputation quality (Quality Score r 2  < 0.90). For the 13 novel loci, 9 regions have been reported of association with obesity related traits by previous GWA studies. Three loci encoding long intergenic non-protein coding RNAs (lncRNA), and 2 loci involved in N-linked glycosylation are also highlighted in this study., (© 2021. The Author(s).)

Objective: Juvenile idiopathic arthritis (JIA) is the most common type of arthritis among children, but a few studies have investigated the contribution of rare variants to JIA. In this study, we aimed to identify rare coding variants associated with JIA for the genome-wide landscape., Methods: We established a rare variant calling and filtering pipeline and performed rare coding variant and gene-based association analyses on three RNA-seq datasets composed of 228 JIA patients in the Gene Expression Omnibus against different sets of controls, and further conducted replication in our whole-exome sequencing (WES) data of 56 JIA patients. Then we conducted differential gene expression analysis and assessed the impact of recurrent functional coding variants on gene expression and signalling pathway., Results: By the RNA-seq data, we identified variants in two genes reported in literature as JIA causal variants, as well as additional 63 recurrent rare coding variants seen only in JIA patients. Among the 44 recurrent rare variants found in polyarticular patients, 10 were replicated by our WES of patients with the same JIA subtype. Several genes with recurrent functional rare coding variants have also common variants associated with autoimmune diseases. We observed immune pathways enriched for the genes with rare coding variants and differentially expressed genes., Conclusion: This study elucidated a novel landscape of recurrent rare coding variants in JIA patients and uncovered significant associations with JIA at the gene pathway level. The convergence of common variants and rare variants for autoimmune diseases is also highlighted in this study., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. No commercial re-use. See rights and permissions. Published by BMJ.)

RNA-seq has been a powerful method to detect the differentially expressed genes/long non-coding RNAs (lncRNAs) in schizophrenia (SCZ) patients; however, due to overfitting problems differentially expressed targets (DETs) cannot be used properly as biomarkers. This study used machine learning to reduce gene/non-coding RNA features. Dorsolateral prefrontal cortex (dlpfc) RNA-seq data from 254 individuals was obtained from the CommonMind consortium. The average predictive accuracy for SCZ patients was 67% based on coding genes, and 96% based on long non-coding RNAs (lncRNAs). Machine learning is a powerful algorithm to reduce functional biomarkers in SCZ patients. The lncRNAs capture the characteristics of SCZ tissue more accurately than mRNA as the former regulate every level of gene expression, not limited to mRNA levels.

Hereditary cystatin C amyloid angiopathy is a dominantly inherited disease caused by a leucine to glutamine variant of human cystatin C (hCC). L68Q-hCC forms amyloid deposits in brain arteries associated with micro-infarcts, leading ultimately to paralysis, dementia and death in young adults. To evaluate the ability of molecules to interfere with aggregation of hCC while informing about cellular toxicity, we generated cells that produce and secrete WT and L68Q-hCC and have detected high-molecular weight complexes formed from the mutant protein. Incubations of either lysate or supernatant containing L68Q-hCC with reducing agents glutathione or N-acetyl-cysteine (NAC) breaks oligomers into monomers. Six L68Q-hCC carriers taking NAC had skin biopsies obtained to determine if hCC deposits were reduced following NAC treatment. Remarkably, ~50-90% reduction of L68Q-hCC staining was observed in five of the treated carriers suggesting that L68Q-hCC is a clinical target for reducing agents.

Background: Not all cells in a given individual are identical in their genomic makeup. Mosaicism describes such a phenomenon where a mixture of genotypic states in certain genomic segments exists within the same individual. Mosaicism is a prevalent and impactful class of non-integer state copy number variation (CNV). Mosaicism implies that certain cell types or subset of cells contain a CNV in a segment of the genome while other cells in the same individual do not. Several studies have investigated the impact of mosaicism in single patients or small cohorts but no comprehensive scan of mosaic CNVs has been undertaken to accurately detect such variants and interpret their impact on human health and disease., Results: We developed a tool called Montage to improve the accuracy of detection of mosaic copy number variants in a high throughput fashion. Montage directly interfaces with ParseCNV2 algorithm to establish disease phenotype genome-wide association and determine which genomic ranges had more or less than expected frequency of mosaic events. We screened for mosaic events in over 350,000 samples using 1% allele frequency as the detection limit. Additionally, we uncovered disease associations of multiple phenotypes with mosaic CNVs at several genomic loci. We additionally investigated the allele imbalance observations genome-wide to define non-diploid and non-integer copy number states., Conclusions: Our novel algorithm presents an efficient tool with fast computational runtime and high levels of accuracy of mosaic CNV detection. A curated mosaic CNV callset of 3716 events in 2269 samples is presented with comparability to previous reports and disease phenotype associations. The new algorithm can be freely accessed via: https://github.com/CAG-CNV/MONTAGE .

Background: Neuroblastoma is a childhood malignancy that arises from the developing sympathetic nervous system. Although mitochondrial dysfunctions have been implicated in the pathophysiology of neuroblastoma, the role of mitochondrial DNA (mtDNA) has not been extensively investigated., Methods: A total of 2404 Caucasian children diagnosed with neuroblastoma and 9310 ancestry-matched controls were recruited at the Children's Hospital of Philadelphia. The mtDNA haplogroups were identified from SNP array data of two independent cohorts. We conducted a case-control study to explore potential associations of mtDNA haplogroups with the susceptibility of neuroblastoma. The genetic effect of neuroblastoma was measured by odds ratios (ORs) of mitochondrial haplogroups. All tests were two-sided., Results: Haplogroup K was statistically significantly associated with reduced risk of neuroblastoma in the discovery cohort consisting of 1474 cases and 5699 controls (OR = 0.72, 95% confidence interval [CI] = 0.57 to 0.90; P = 4.8 × 10-3). The association was replicated in an independent cohort (OR = 0.69, 95% CI = 0.53 to 0.92; P = .01) of 930 cases and 3611 controls. Pooled analysis was performed by combining the two data sets. The association remained highly statistically significant after correction for multiple testing (OR = 0.71, 95% CI = 0.59 to 0.84, P = 1.96 × 10-4, Pcorrected = .002). Further analysis focusing on neuroblastoma subtypes indicated haplogroup K was more associated with high-risk neuroblastoma (OR = 0.57, 95% CI = 0.43 to 0.76; P = 1.46 × 10-4) than low-risk and intermediate-risk neuroblastoma., Conclusions: Haplogroup K is an independent genetic factor associated with reduced risk of developing neuroblastoma in European descents. These findings provide new insights into the genetic basis of neuroblastoma, implicating mitochondrial DNA encoded proteins in the etiology of neuroblastoma., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Although mitochondrial dysfunction has been implicated in the pathophysiology of attention deficit and hyperactivity disorder ADHD, the role of mitochondrial DNA (mtDNA) has not been extensively investigated. To determine whether mtDNA haplogroups influence risk of ADHD, we performed a case-control study comprising 2076 ADHD cases and 5078 healthy controls, all of whom were European decedents recruited from The Children's Hospital of Philadelphia (CHOP). Associations between eight major European mtDNA Haplogroups and ADHD risk were assessed in three independent European cohorts. Meta-analysis of the three studies indicated that mtDNA haplogroups K (odds ratio = 0.69, P = 2.24 × 10 -4 , P corrected  = 1.79 × 10 -3 ) and U (odds ratio = 0.77, P = 8.88 × 10 -4 , P corrected  = 7.11 × 10 -3 ) were significantly associated with reduced risk of ADHD. In contrast, haplogroup HHV* (odds ratio = 1.18, P = 2.32 × 10 -3 , P corrected  = 0.019) was significantly associated with increased risk of ADHD. Our results provide novel insight into the genetic basis of ADHD, implicating mitochondrial mechanisms in the pathophysiology of this relatively common psychiatric disorder.

Previous studies of attention-deficit hyperactivity disorder (ADHD) have suggested that structural variants (SVs) play an important role but these were mainly studied in subjects of European ancestry and focused on coding regions. In this study, we sought to address the role of SVs in non-European populations and outside of coding regions. To that end, we generated whole genome sequence (WGS) data on 875 individuals, including 205 ADHD cases and 670 non-ADHD controls. The ADHD cases included 116 African Americans (AA) and 89 of European Ancestry (EA) with SVs in comparison with 408 AA and 262 controls, respectively. Multiple SVs and target genes that associated with ADHD from previous studies were identified or replicated, and novel recurrent ADHD-associated SV loci were discovered. We identified clustering of non-coding SVs around neuroactive ligand-receptor interaction pathways, which are involved in neuronal brain function, and highly relevant to ADHD pathogenesis and regulation of gene expression related to specific ADHD phenotypes. There was little overlap (around 6%) in the genes impacted by SVs between AA and EA. These results suggest that SVs within non-coding regions may play an important role in ADHD development and that WGS could be a powerful discovery tool for studying the molecular mechanisms of ADHD.

Copy number variants (CNVs) are suggested to have a widespread impact on the human genome and phenotypes. To understand the role of CNVs across human diseases, we examine the CNV genomic landscape of 100,028 unrelated individuals of European ancestry, using SNP and CGH array datasets. We observe an average CNV burden of ~650 kb, identifying a total of 11,314 deletion, 5625 duplication, and 2746 homozygous deletion CNV regions (CNVRs). In all, 13.7% are unreported, 58.6% overlap with at least one gene, and 32.8% interrupt coding exons. These CNVRs are significantly more likely to overlap OMIM genes (2.94-fold), GWAS loci (1.52-fold), and non-coding RNAs (1.44-fold), compared with random distribution (P < 1 × 10 -3 ). We uncover CNV associations with four major disease categories, including autoimmune, cardio-metabolic, oncologic, and neurological/psychiatric diseases, and identify several drug-repurposing opportunities. Our results demonstrate robust frequency definition for large-scale rare variant association studies, identify CNVs associated with major disease categories, and illustrate the pleiotropic impact of CNVs in human disease.

Background: Cardiovascular disease is the leading cause of death in the United States. Consequently, individuals who are genetically predisposed for high risk of cardiovascular disease would benefit most from prevention and early intervention approaches. Among common health risk factors affecting adult populations, we evaluated 23 cardiovascular disease-related traits, including BMI, glucose levels and lipid profiling to determine their associations with low-frequency recurrent copy number variations (CNV) (population frequency < 5%)., Results: We examined 10,619 unrelated subjects of European ancestry from the Electronic Medical Records and Genomics (eMERGE) Network who were genotyped with 657,366 markers genome-wide on the Illumina Infinium Quad 660 array. We performed CNV calling based on array marker intensity and evaluated data quality, ancestry stratification, and relatedness to ensure unbiased association discovery. Using a segment-based scoring approach, we assessed the association of all CNVs with each trait. In this large genome-wide analysis of low-frequency CNVs, we observed 11 novel genome-wide significant associations of low-frequency CNVs with major cardiovascular disease traits., Conclusion: In one of the largest genome-wide studies for low-frequency recurrent CNVs, we identified 11 loci associated with cardiovascular disease and related traits at the genome-wide significance level that may serve as biomarkers for prevention and early intervention studies in subjects who are at elevated risk. Our study further supports the role of low-frequency recurrent CNVs in the pathogenesis of common complex disease traits., (Copyright © 2019. Published by Elsevier B.V.)

Congenital heart defects (CHDs) are a common birth defect, affecting approximately 1% of newborn children in the United States. As previously reported, a significant number of CHDs are potentially attributed to altered copy number variants (CNVs). However, as many genomic variants are rare, a large-scale CNV triad study is necessary to characterize the genetic architecture of CHD. We used whole-exome sequencing (WES) data generated by the Pediatric Cardiac Genomics Consortium (PCGC), including a discovery dataset of 2,103 individuals from 760 nuclear family trios and an independent replication set of 4,808 individuals from 1,712 trios. The candidate targets uncovered were further validated through different platforms, including the Omni single-nucleotide polymorphism (SNP) array chip in 1,860 individuals and the whole-genome sequencing (WGS) data in 33 trios. The genes harboring CNVs of interest were then investigated for expression alternations based on cardiac tissue RNA-Seq data. We identified multiple CNVs in the WES data that associated with specific sub-phenotypes of CHD in approximately 2,400 families, including 98 de novo CNV regions. We identified five CNV loci harboring LIMS1 , GCC2 , RANBP2 , TTC3 , and MAP3K7CL , respectively, where those genes are highly expressed in human heart and/or mouse embryo heart at 15 days. Five novel CNV loci were uncovered, demonstrating altered expression of the respective candidate genes involved. To our knowledge, this is the largest trio-based WES study of CHD and, in addition to uncovering novel CHD targets, presents an extensive resource with the potential to provide important insights to the architecture and impact of CNVs in CHD.

Autism spectrum disorder (ASD) is a complex neuropsychiatric disorder. A number of genetic risk loci have been identified for ASD from genome-wide association studies (GWAS); however, their target genes in relevant tissues and cell types remain to be investigated. The frontal cortex is a key region in the human brain for communication and cognitive function. To identify risk genes contributing to potential dysfunction in the frontal cortex of ASD patients, we took an in silico approach integrating multi-omics data. We first found genes with expression in frontal cortex tissue that correlates with ASD risk loci by leveraging expression quantitative trait loci (eQTLs) information. Among these genes, we then identified 76 genes showing significant differential expression in the frontal cortex between ASD cases and controls in microarray datasets and further replicated four genes with RNA-seq data. Among the ASD GWAS single nucleotide polymorphisms (SNPs) correlating with the 76 genes, 20 overlap with histone marks and 40 are associated with gene methylation level. Thus, through multi-omics data analyses, we identified genes that may work as target genes of ASD risk loci in the brain frontal cortex.

The treatment of lymphatic anomaly, a rare devastating disease spectrum of mostly unknown etiologies, depends on the patient manifestations 1 . Identifying the causal genes will allow for developing affordable therapies in keeping with precision medicine implementation 2 . Here we identified a recurrent gain-of-function ARAF mutation (c.640T>C:p.S214P) in a 12-year-old boy with advanced anomalous lymphatic disease unresponsive to conventional sirolimus therapy and in another, unrelated, adult patient. The mutation led to loss of a conserved phosphorylation site. Cells transduced with ARAF-S214P showed elevated ERK1/2 activity, enhanced lymphangiogenic capacity, and disassembly of actin skeleton and VE-cadherin junctions, which were rescued using the MEK inhibitor trametinib. The functional relevance of the mutation was also validated by recreating a lymphatic phenotype in a zebrafish model, with rescue of the anomalous phenotype using a MEK inhibitor. Subsequent therapy of the lead proband with a MEK inhibitor led to dramatic clinical improvement, with remodeling of the patient's lymphatic system with resolution of the lymphatic edema, marked improvement in his pulmonary function tests, cessation of supplemental oxygen requirements and near normalization of daily activities. Our results provide a representative demonstration of how knowledge of genetic classification and mechanistic understanding guides biologically based medical treatments, which in our instance was life-saving.

Background: Genome-wide association studies (GWASs) have identified multiple susceptibility loci for migraine in European adults. However, no large-scale genetic studies have been performed in children or African Americans with migraine., Methods: We conducted a GWAS of 380 African-American children and 2129 ancestry-matched controls to identify variants associated with migraine. We then attempted to replicate our primary analysis in an independent cohort of 233 African-American patients and 4038 non-migraine control subjects., Results: The results of this study indicate that common variants at 5q33.1 associated with migraine risk in African-American children (rs72793414, p=1.94×10 -9 ). The association was validated in an independent study (p=3.87×10 -3 ) for an overall meta-analysis p value of 3.81×10 -10 . eQTL (Expression quantitative trait loci) analysis of the Genotype-Tissue Expression data also shows the genotypes of rs72793414 were strongly correlated with the mRNA expression levels of NMUR2 at 5q33.1. NMUR2 encodes a G protein-coupled receptor of neuromedin-U (NMU). NMU, a highly conserved neuropeptide, participates in diverse physiological processes of the central nervous system., Conclusions: This study provides new insights into the genetic basis of childhood migraine and allow for precision therapeutic development strategies targeting migraine patients of African-American ancestry., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2018. No commercial re-use. See rights and permissions. Published by BMJ.)

Asthma is the leading chronic disease in children. Several studies have identified genetic biomarkers associated with susceptibility and severity in both adult and pediatric cases. In this study, we evaluated outcomes in 400 African American and European American pediatric cases all of whom were regular users of inhaled corticosteroids. Patients were stratified by genotype using two single nucleotide polymorphisms in the β-2-adrenergic receptor (ADRB2) gene - rs1042713 and rs1042714, previously associated with asthma outcome. These correspond to nonsynonymous single nucleotide polymorphisms at positions 16 [arginine to glycine (Arg16Gly); rs1042713] and 27 [glutamic acid to glutamine (Glu27Gln); rs1042714], which are relatively common (minor allele frequencies ∼40-50%), and have been well characterized in asthma pharmacogenetics. We controlled for adherence to the National Heart, Lung and Blood Institute guidelines using deep mining of electronic health record data to determine treatment course. We found no significant effect for rs1042713 (Arg16Gly) but did identify an effect for rs1042714, where participants homozygous for Gln27 had increased exacerbations while taking inhaled corticosteroids in comparison with those who were either heterozygous or homozygous for Glu27. This is consistent with previous studies and demonstrates for the first time that the Glu27 variant in the ADRB2 gene is associated with increased frequencies of asthma exacerbations. Moreover, this study also lends an important proof-of-principle on how electronic health records linked to genotype can be efficiently and systematically mined to delineate health outcomes.

Phenome-wide association studies (PheWAS) have been proposed as a possible aid in drug development through elucidating mechanisms of action, identifying alternative indications, or predicting adverse drug events (ADEs). Here, we select 25 single nucleotide polymorphisms (SNPs) linked through genome-wide association studies (GWAS) to 19 candidate drug targets for common disease indications. We interrogate these SNPs by PheWAS in four large cohorts with extensive health information (23andMe, UK Biobank, FINRISK, CHOP) for association with 1683 binary endpoints in up to 697,815 individuals and conduct meta-analyses for 145 mapped disease endpoints. Our analyses replicate 75% of known GWAS associations (P < 0.05) and identify nine study-wide significant novel associations (of 71 with FDR < 0.1). We describe associations that may predict ADEs, e.g., acne, high cholesterol, gout, and gallstones with rs738409 (p.I148M) in PNPLA3 and asthma with rs1990760 (p.T946A) in IFIH1. Our results demonstrate PheWAS as a powerful addition to the toolkit for drug discovery.

Individuals with psychiatric disorders have elevated rates of autoimmune comorbidity and altered immune signaling. It is unclear whether these altered immunological states have a shared genetic basis with those psychiatric disorders. The present study sought to use existing summary-level data from previous genome-wide association studies to determine if commonly varying single nucleotide polymorphisms are shared between psychiatric and immune-related phenotypes. We estimated heritability and examined pair-wise genetic correlations using the linkage disequilibrium score regression (LDSC) and heritability estimation from summary statistics methods. Using LDSC, we observed significant genetic correlations between immune-related disorders and several psychiatric disorders, including anorexia nervosa, attention deficit-hyperactivity disorder, bipolar disorder, major depression, obsessive compulsive disorder, schizophrenia, smoking behavior, and Tourette syndrome. Loci significantly mediating genetic correlations were identified for schizophrenia when analytically paired with Crohn's disease, primary biliary cirrhosis, systemic lupus erythematosus, and ulcerative colitis. We report significantly correlated loci and highlight those containing genome-wide associations and candidate genes for respective disorders. We also used the LDSC method to characterize genetic correlations among the immune-related phenotypes. We discuss our findings in the context of relevant genetic and epidemiological literature, as well as the limitations and caveats of the study., (© 2018 Wiley Periodicals, Inc.)

Hundreds of genomic loci have been identified with the recent advances of schizophrenia in genome-wide association studies (GWAS) and sequencing studies. However, the functional interactions among those genes remain largely unknown. We developed a network-based approach to integrate multiple genetic risk factors, which lead to the discovery of new susceptibility genes and causal sub-networks, or pathways in schizophrenia. We identified significantly and consistently over-represented pathways in the largest schizophrenia GWA studies, which are highly relevant to synaptic plasticity, neural development and signaling transduction, such as long-term potentiation, neurotrophin signaling pathway, and the ERBB signaling pathway. We also demonstrated that genes targeted by common SNPs are more likely to interact with genes harboring de novo mutations (DNMs) in the protein-protein interaction (PPI) network, suggesting a mutual interplay of both common and rare variants in schizophrenia. We further developed an edge-based search algorithm to identify the top-ranked gene modules associated with schizophrenia risk. Our results suggest that the N-methyl-D-aspartate receptor (NMDAR) interactome may play a leading role in the pathology of schizophrenia, as it is highly targeted by multiple types of genetic risk factors.

To date, most transcriptome studies of schizophrenia focus on the analysis of protein-coding genes. Long noncoding RNAs (lncRNAs) are emerging as key tissue-specific regulators of cellular and disease processes. The amygdala brain region has been implicated in the pathophysiology of schizophrenia. We performed unbiased whole transcriptome profiling of amygdala tissues from 22 schizophrenia patients and 24 non-psychiatric controls using RNA-seq. We reconstructed amygdala transcriptome and employed systems biology approaches to annotating the functional roles of lncRNAs. As a result, we identified 839 novel lncRNAs in amygdala. We found in amygdala lncRNAs are more subtype-specific than protein-coding genes. We identified functional modules associated with "synaptic transmission", "ribosome", and "immune responses" which were related to schizophrenia pathophysiology that involved lncRNAs. Integrative functional analyses associating individual lncRNAs with specific pathways and functions further show that amygdala lncRNAs are connected with all of these pathways. Our study presents the first systematic landscape of lncRNAs in amygdala tissue from schizophrenia cases., (Copyright © 2018. Published by Elsevier B.V.)

Background: Neurodevelopmental and neuropsychiatric disorders represent a wide spectrum of heterogeneous yet inter-related disease conditions. The overlapping clinical presentations of these diseases suggest a shared genetic etiology. We aim to identify shared structural variants spanning the spectrum of five neuropsychiatric disorders., Methods: We investigated copy number variations (CNVs) in five cohorts, including schizophrenia (SCZ), bipolar disease (BD), autism spectrum disorders (ASD), attention deficit hyperactivity disorder (ADHD), and depression, from 7849 cases and 10,799 controls. CNVs were called based on intensity data from genome-wide SNP arrays and CNV frequency was compared between cases and controls in each disease cohort separately. Meta-analysis was performed via a gene-based approach. Quantitative PCR (qPCR) was employed to validate novel significant loci., Results: In our meta-analysis, two genes containing CNVs with exonic overlap reached genome-wide significance threshold of meta P value < 9.4 × 10 -6 for deletions and 7.5 × 10 -6 for duplications. We observed significant overlap between risk CNV loci across cohorts. In addition, we identified novel significant associations of DOCK8/KANK1 duplications (meta P value = 7.5 × 10 -7 ) across all cohorts, and further validated the CNV region with qPCR., Conclusions: In the first large scale meta-analysis of CNVs across multiple neurodevelopmental/psychiatric diseases, we uncovered novel significant associations of structural variants in the locus of DOCK8/KANK1 shared by five diseases, suggesting common etiology of these clinically distinct neurodevelopmental conditions.