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Background The genetic architecture of JIA remains only partially comprehended. There is a clear imperative for continued endeavours to uncover insights into the underlying causes of JIA. Methods This study encompassed a comprehensive spectrum of endeavours, including conducting a JIA genome-wide association study (GWAS) meta-analysis that incorporated data from 4550 JIA cases and 18 446 controls. We employed in silico and genome-editing approaches to prioritizing target genes. To investigate pleiotropic effects, we conducted phenome-wide association studies. Cell-type enrichment analyses were performed by integrating bulk and single-cell sequencing data. Finally, we delved into potential druggable targets for JIA. Results Fourteen genome-wide significant non-HLA loci were identified, including four novel loci, each exhibiting pleiotropic associations with other autoimmune diseases or musculoskeletal traits. We uncovered strong genetic correlation between JIA and BMD traits at 52 genomic regions, including three GWAS loci for JIA. Candidate genes with immune functions were captured by in silico analyses at each novel locus, with additional findings identified through our experimental approach. Cell-type enrichment analysis revealed 21 specific immune cell types crucial for the affected organs in JIA, indicating their potential contribution to the disease. Finally, 24 known or candidate druggable target genes were prioritized. Conclusions Our identification of four novel JIA-associated genes, CD247 , RHOH , COLEC10 and IRF8 , broadens the novel potential drug repositioning opportunities. We established a new genetic link between COLEC10 , TNFRSF11B and JIA/BMD. Additionally, the identification of RHOH underscores its role in positive thymocyte selection, thereby illuminating a critical facet of JIA's underlying biological mechanisms. [ABSTRACT FROM AUTHOR]

Sickle cell disease (SCD) is an inherited blood disorder marked by homozygosity of hemoglobin S, which is a defective hemoglobin caused by a missense mutation in the β-globin gene. However, clinical phenotypes of SCD vary among patients. To investigate genetic variants associated with various clinical phenotypes of SCD, we genotyped DNA samples from 520 SCD subjects and used a genome-wide association study (GWAS) approach to identify genetic variants associated with phenotypic features of SCD. For HbF levels, the previously reported 2p16.1 locus (BCL11A) reached genome significance (rs1427407, P = 8.58 × 10–10) in our GWAS as expected. In addition, we found a new genome-wide significance locus at 15q14 (rs8182015, P = 2.07 × 10–8) near gene EMC7. GWAS of acute chest syndrome (ACS) detected a locus (rs79915189, P = 3.70 × 10–8) near gene IDH2 at 15q26.1. The SNP, rs79915189, is also an expression quantitative trait locus (eQTL) of IDH2 in multiple tissues. For vasoocclusive episode (VOE), GWAS detected multiple significant signals at 2p25.1 (rs62118798, P = 4.27 × 10–8), 15q26.1 (rs62020555, P = 2.04 × 10–9) and 15q26.3 (rs117797325, P = 4.63 × 10–8). Our findings provide novel insights into the genetic mechanisms of SCD suggesting that common genetic variants play an important role in the presentation of the clinical phenotypes of patients with SCD. [ABSTRACT FROM AUTHOR]

Circassians and Chechens in Jordan, both with Caucasian ancestry, are genetically isolated due to high rate of endogamous marriages. Recent interest in these populations has led to studies on their genetic similarities, differences, and epidemiological differences in various diseases. Research has explored their predisposition to conditions like diabetes, hypertension, and cancer. Moreover, pharmacogenetic (PGx) studies have also investigated medication response variations within these populations, and forensic studies have further contributed to understanding these populations. In this review article, we first discuss the background of these minority groups. We then show the results of a principle component analysis (PCA) to investigate the genetic relationships between Circassian and Chechen populations living in Jordan. We here present a summary of the findings from the 10 years of research conducted on them. The review article provides a comprehensive summary of research findings that are truly valuable for understanding the unique genetic characteristics, diseases' prevalence, and medication responses among Circassians and Chechens living in Jordan. We believe that gaining deeper comprehension of the root causes of various diseases and developing effective treatment methods that benefit the society as a whole are imperative to engaging a wide range of ethnic groups in genetic research. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Peripheral blood mononuclear cells (PBMCs) are widely used as a model in the study of different human diseases. There is often a time delay from blood collection to PBMC isolation during the sampling process, which can result in an experimental bias, particularly when performing single cell RNA-seq (scRNAseq) studies. Methods: This study examined the impact of different time periods from blood draw to PBMC isolation on the subsequent transcriptome profiling of different cell types in PBMCs by scRNAseq using the 10X Chromium Single Cell Gene Expression assay. Results: Examining the five major cell types constituting the PBMC cell population, i.e., CD4+ T cells, CD8+ T cells, NK cells, monocytes, and B cells, both common changes and cell-type-specific changes were observed in the single cell transcriptome profiling over time. In particular, the upregulation of genes regulated by NF-kB in response to TNF was observed in all five cell types. Significant changes in key genes involved in AP-1 signaling were also observed. RBC contamination was a major issue in stored blood, whereas RBC adherence had no direct impact on the cell transcriptome. Conclusions: Significant transcriptome changes were observed across different PBMC cell types as a factor of time from blood draw to PBMC isolation and as a consequence of blood storage. This should be kept in mind when interpreting experimental results. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 r2 > 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 r2 < 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. [ABSTRACT FROM AUTHOR]

Copy number variations (CNVs) are a major source of structural variation in mammalian genomes. Here, we characterized the genome-wide CNV in 2059 sheep from 67 populations all over the world using the Ovine Infinium HD (600K) SNP BeadChip. We tested their associations with distinct phenotypic traits by conducting multiple independent genome-wide tests. In total, we detected 7547 unique CNVs and 18,152 CNV events in 1217 non-redundant CNV regions (CNVRs), covering 245 Mb (∼10%) of the whole sheep genome. We identified seven CNVRs with frequencies correlating to geographical origins and 107 CNVRs overlapping 53 known quantitative trait loci (QTLs). Gene ontology and pathway enrichment analyses of CNV-overlapping genes revealed their common involvement in energy metabolism, endocrine regulation, nervous system development, cell proliferation, immune, and reproduction. For the phenotypic traits, we detected significantly associated (adjusted P < 0.05) CNVRs harboring functional candidate genes, such as SBNO2 for polycerate; PPP1R11 and GABBR1 for tail weight; AKT1 for supernumerary nipple; CSRP1 , WNT7B , HMX1 , and FGFR3 for ear size; and NOS3 and FILIP1 in Wadi sheep; SNRPD3 , KHDRBS2 , and SDCCAG3 in Hu sheep; NOS3 , BMP1 , and SLC19A1 in Icelandic; CDK2 in Finnsheep; MICA in Romanov; and REEP4 in Texel sheep for litter size. These CNVs and associated genes are important markers for molecular breeding of sheep and other livestock species. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. Associations of copy number variations (CNVs) with complex traits are challenging to study because of their low frequency. Here, the authors analyse SNP array and array comparative genomic hybridization data of 100,028 individuals and report their associations with immune-related, cardiometabolic and neuropsychiatric diseases as well as cancer. [ABSTRACT FROM AUTHOR]

Human brain size changes dynamically through early development, peaks in adolescence, and varies up to 2-fold among adults. However, the molecular genetic underpinnings of interindividual variation in brain size remain unknown. Here, we leveraged postmortem brain RNA sequencing and measurements of brain weight (BW) in 2,531 individuals across three independent datasets to identify 928 genome-wide significant associations with BW. Genes associated with higher or lower BW showed distinct neurodevelopmental trajectories and spatial patterns that mapped onto functional and cellular axes of brain organization. Expression of BW genes was predictive of interspecies differences in brain size, and bioinformatic annotation revealed enrichment for neurogenesis and cell-cell communication. Genome-wide, transcriptome-wide, and phenome-wide association analyses linked BW gene sets to neuroimaging measurements of brain size and brain-related clinical traits. Cumulatively, these results represent a major step toward delineating the molecular pathways underlying human brain size variation in health and disease. [Display omitted] • Transcriptomic analysis of human BW revealed 928 significant genes • BW genes align with predicted developmental and evolutionary changes in brain size • BW genes are cell-type specific and align with structural neuroimaging GWASs and TWASs • BW genes are differentially expressed in psychiatric and neurodegenerative disorders Seidlitz et al. identify genes differentially expressed in individuals with larger or smaller brains that are enriched in growth signaling pathways and are highly expressed in cell types critical for human development and primate evolution. Translational results in a "real world" clinical biobank demonstrate promise for more informed polygenic scoring. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Juvenile idiopathic arthritis (JIA) is the most common chronic rheumatic disease among children, the etiology of which involves a strong genetic component, but much of the underlying genetic determinants still remain unknown. Our aim was to identify novel genetic variants that predispose to JIA. Methods: We performed a genome-wide association study (GWAS) and replication in a total of 1166 JIA cases and 9500 unrelated controls of European ancestry. Correlation of SNP genotype and gene expression was investigated. Then we conducted targeted resequencing of a candidate locus, among a subset of 480 cases and 480 controls. SUM test was performed to evaluate the association of the identified rare functional variants. Results: The CXCR4 locus on 2q22.1 was found to be significantly associated with JIA, peaking at SNP rs953387. However, this result is subjected to subpopulation stratification within the subjects of European ancestry. After adjusting for principal components, nominal significant association remained (p < 10-4). Because of its interesting known function in immune regulation, we carried out further analyses to assess its relationship with JIA. Expression of CXCR4 was correlated with CXCR4 rs953387 genotypes in lymphoblastoid cell lines (p = 0.014) and T-cells (p = 0.0054). In addition, rare non-synonymous and stop-gain sequence variants in CXCR4, putatively damaging for CXCR4 function, were significantly enriched in JIA cases (p = 0.015). Conclusion: Our results suggest the association of CXCR4 variants with JIA, implicating that this gene may be involved in the pathogenesis of autoimmune disease. However, because this locus is subjected to population stratification within the subjects of European ancestry, additional replication is still necessary for this locus to be considered a true risk locus for JIA. This cell-surface chemokine receptor has already been targeted in other diseases and may serve as a tractable therapeutic target for a specific subset of pediatric arthritis patients with additional replication and functional validation of the locus. [ABSTRACT FROM AUTHOR]

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

Background Genetics clearly plays a major role in the etiology of autism spectrum disorders (ASDs), but studies to date are only beginning to characterize the causal genetic variants responsible. Until recently, studies using multiple extended multi-generation families to identify ASD risk genes had not been undertaken. Methods We identified haplotypes shared among individuals with ASDs in large multiplex families, followed by targeted DNA capture and sequencing to identify potential causal variants. We also assayed the prevalence of the identified variants in a large ASD case/control population. Results We identified 584 non-conservative missense, nonsense, frameshift and splice site variants that might predispose to autism in our high-risk families. Eleven of these variants were observed to have odds ratios greater than 1.5 in a set of 1,541 unrelated children with autism and 5,785 controls. Three variants, in the RAB11FIP5, ABP1, and JMJD7-PLA2G4B genes, each were observed in a single case and not in any controls. These variants also were not seen in public sequence databases, suggesting that they may be rare causal ASD variants. Twentyeight additional rare variants were observed only in high-risk ASD families. Collectively, these 39 variants identify 36 genes as ASD risk genes. Segregation of sequence variants and of copy number variants previously detected in these families reveals a complex pattern, with only a RAB11FIP5 variant segregating to all affected individuals in one two-generation pedigree. Some affected individuals were found to have multiple potential risk alleles, including sequence variants and copy number variants (CNVs), suggesting that the high incidence of autism in these families could be best explained by variants at multiple loci. Conclusions Our study is the first to use haplotype sharing to identify familial ASD risk loci. In total, we identified 39 variants in 36 genes that may confer a genetic risk of developing autism. The observation of 11 of these variants in unrelated ASD cases further supports their role as ASD risk variants. [ABSTRACT FROM AUTHOR]

Agenesis of the corpus callosum (ACC), cerebellar hypoplasia (CBLH), and polymicrogyria (PMG) are severe congenital brain malformations with largely undiscovered causes. We conducted a large-scale chromosomal copy number variation (CNV) discovery effort in 255 ACC, 220 CBLH, and 147 PMG patients, and 2,349 controls. Compared to controls, significantly more ACC, but unexpectedly not CBLH or PMG patients, had rare genic CNVs over one megabase (p = 1.48×10−3; odds ratio [OR] = 3.19; 95% confidence interval [CI] = 1.89–5.39). Rare genic CNVs were those that impacted at least one gene in less than 1% of the combined population of patients and controls. Compared to controls, significantly more ACC but not CBLH or PMG patients had rare CNVs impacting over 20 genes (p = 0.01; OR = 2.95; 95% CI = 1.69–5.18). Independent qPCR confirmation showed that 9.4% of ACC patients had de novo CNVs. These, in comparison to inherited CNVs, preferentially overlapped de novo CNVs previously observed in patients with autism spectrum disorders (p = 3.06×10−4; OR = 7.55; 95% CI = 2.40–23.72). Interestingly, numerous reports have shown a reduced corpus callosum area in autistic patients, and diminished social and executive function in many ACC patients. We also confirmed and refined previously known CNVs, including significantly narrowing the 8p23.1-p11.1 duplication present in 2% of our current ACC cohort. We found six novel CNVs, each in a single patient, that are likely deleterious: deletions of 1p31.3-p31.1, 1q31.2-q31.3, 5q23.1, and 15q11.2-q13.1; and duplications of 2q11.2-q13 and 11p14.3-p14.2. One ACC patient with microcephaly had a paternally inherited deletion of 16p13.11 that included NDE1. Exome sequencing identified a recessive maternally inherited nonsense mutation in the non-deleted allele of NDE1, revealing the complexity of ACC genetics. This is the first systematic study of CNVs in congenital brain malformations, and shows a much higher prevalence of large gene-rich CNVs in ACC than in CBLH and PMG. [ABSTRACT FROM AUTHOR]

Objective To identify plasma uric acid-related genes in extremely obese and normal weight individuals using genome-wide association studies (GWASs). Design and Methods Using genotypes from a GWAS focusing on obesity and thinness, quantitative trait association analyses (PLINK) for plasma uric acid levels in 1,060 extremely obese individuals (BMI > 35 kg/m2) and normal-weight controls (BMI < 25kg/m2) were performed. In 961 samples with uric acid data, 924 were females. Results Significant associations were found in SLC2A9 gene SNPs and plasma uric acid levels (rs6449213, P = 3.15 × 10-12). DIP2C gene SNP rs877282 also reached genome-wide significance ( P = 4.56 × 10-8). Weaker associations ( P < 1× 10-5) were found in F5, PXDNL, FRAS1, LCORL, and MICAL2 genes. Besides SLC2A9, three previously identified uric acid-related genes ABCG2 (rs2622605, P= 0.0026), SLC17A1 (rs3799344, P = 0.0017), and RREB1 (rs1615495, P = 0.00055) received marginal support in our study. Conclusions Two genes/chromosome regions reached genome-wide association significance ( P < 1 × 10-7, 550K SNPs) in our GWAS: SLC2A9, the chromosome 2 60.1 Mb region (rs6723995), and the DIP2C gene region. Five other genes ( F5, PXDNL, FRAS1, LCORL, and MICAL2) yielded P < 1 × 10-5. Four previous reported associations were replicated in our study, including SLC2A9, ABCG2, RREB, and SLC17A1. [ABSTRACT FROM AUTHOR]

ABSTRACT This report describes an algorithm developed to predict the pathogenicity of copy number variants (CNVs) in large sample cohorts. CNVs (genomic deletions and duplications) are found in healthy individuals and in individuals with genetic diagnoses, and differentiation of these two classes of CNVs can be challenging and usually requires extensive manual curation. We have developed PECONPI, an algorithm to assess the pathogenicity of CNVs based on gene content and CNV frequency. This software was applied to a large cohort of patients with genetically heterogeneous non-syndromic hearing loss to score and rank each CNV based on its relative pathogenicity. Of 636 individuals tested, we identified the likely underlying etiology of the hearing loss in 14 (2%) of the patients (1 with a homozygous deletion, 7 with a deletion of a known hearing loss gene and a point mutation on the trans allele and 6 with a deletion larger than 1 Mb). We also identified two probands with smaller deletions encompassing genes that may be functionally related to their hearing loss. The ability of PECONPI to determine the pathogenicity of CNVs was tested on a second genetically heterogenous cohort with congenital heart defects (CHDs). It successfully identified a likely etiology in 6 of 355 individuals (2%). We believe this tool is useful for researchers with large genetically heterogeneous cohorts to help identify known pathogenic causes and novel disease genes. © 2013 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Objective: Common variation at the loci harboring fat mass and obesity ( FTO), melanocortin receptor 4 ( MC4R), and transmembrane protein 18 ( TMEM18) is consistently reported as being statistically most strongly associated with obesity. Investigations if these loci also harbor rarer missense variants that confer substantially higher risk of common childhood obesity in African American (AA) children were conducted. Design and Methods: The exons of FTO, MC4R, and TMEM18 in an initial subset of our cohort were sequenced, that is, 200 obese (BMI≥95th percentile) and 200 lean AA children (BMI≤5th percentile). Any missense exonic variants that were uncovered went on to be further genotyped in a further 768 obese and 768 lean (BMI≤50th percentile) children of the same ethnicity. Results: A number of exonic variants were observed from our sequencing effort: seven in FTO, of which four were non-synonymous (A163T, G182A, M400V, and A405V), thirteen in MC4R, of which six were non-synonymous (V103I, N123S, S136A, F202L, N240S, and I251L), and four in TMEM18, of which two were non-synonymous (P2S and V113L). Follow-up genotyping of these missense variants revealed only one significant difference in allele frequency between cases and controls, namely with N240S in MC4R (Fisher's exact P = 0.0001). Conclusion: In summary, moderately rare missense variants within the FTO, MC4R, and TMEM18 genes observed in our study did not confer risk of common childhood obesity in African Americans except for a degree of evidence for one known loss-of-function variant in MC4R. [ABSTRACT FROM AUTHOR]

Longevity has a strong genetic component evidenced by family-based studies. Lipoprotein metabolism, FOXO proteins, and insulin/IGF-1 signaling pathways in model systems have shown polygenic variations predisposing to shorter lifespan. To test the hypothesis that rare variants could influence lifespan, we compared the rates of CNVs in healthy children (0-18 years of age) with individuals 67 years or older. CNVs at a significantly higher frequency in the pediatric cohort were considered risk variants impacting lifespan, while those enriched in the geriatric cohort were considered longevity protective variants. We performed a whole-genome CNV analysis on 7,313 children and 2,701 adults of European ancestry genotyped with 302,108 SNP probes. Positive findings were evaluated in an independent cohort of 2,079 pediatric and 4,692 geriatric subjects. We detected 8 deletions and 10 duplications that were enriched in the pediatric group (P = 3.33x10-8-1.6x10-2 unadjusted), while only one duplication was enriched in the geriatric cohort (P = 6.3x10-4). Population stratification correction resulted in 5 deletions and 3 duplications remaining significant (P = 5.16x10-5-4.26x10-2) in the replication cohort. Three deletions and four duplications were significant combined (combined P = 3.7x10-4-3.9x10-2). All associated loci were experimentally validated using qPCR. Evaluation of these genes for pathway enrichment demonstrated ~50% are involved in alternative splicing (P = 0.0077 Benjamini and Hochberg corrected). We conclude that genetic variations disrupting RNA splicing could have long-term biological effects impacting lifespan. [ABSTRACT FROM AUTHOR]

Attention deficit hyperactivity disorder (ADHD) is a common, heritable neuropsychiatric disorder of unknown etiology. We performed a whole-genome copy number variation (CNV) study on 1,013 cases with ADHD and 4,105 healthy children of European ancestry using 550,000 SNPs. We evaluated statistically significant findings in multiple independent cohorts, with a total of 2,493 cases with ADHD and 9,222 controls of European ancestry, using matched platforms. CNVs affecting metabotropic glutamate receptor genes were enriched across all cohorts (P = 2.1 × 10?9). We saw GRM5 (encoding glutamate receptor, metabotropic 5) deletions in ten cases and one control (P = 1.36 × 10?6). We saw GRM7 deletions in six cases, and we saw GRM8 deletions in eight cases and no controls. GRM1 was duplicated in eight cases. We experimentally validated the observed variants using quantitative RT-PCR. A gene network analysis showed that genes interacting with the genes in the GRM family are enriched for CNVs in ?10% of the cases (P = 4.38 × 10?10) after correction for occurrence in the controls. We identified rare recurrent CNVs affecting glutamatergic neurotransmission genes that were overrepresented in multiple ADHD cohorts. [ABSTRACT FROM AUTHOR]

Obesity is a serious health concern for children and adolescents, particularly in Western societies, where its incidence is now considered to have reached epidemic proportions. A number of genetic determinants of adult BMI have already been established through genome wide association studies (GWAS), most recently from the GIANT meta-analysis of such datasets combined. In this current study of European Americans, we examined the 32 loci detected in that GIANT study in the context of common childhood obesity within a cohort of 1,097 cases (defined as BMI ≥95th percentile), together with 2,760 lean controls (defined as BMI <50th percentile), aged between 2 and 18 years old. Nine of these single-nucleotide polymorphims (SNPs) yielded at least nominal evidence for association with common childhood obesity, namely at the FTO, TMEM18, NRXN3, MC4R, SEC16B, GNPDA2, TNNI3K, QPCTL, and BDNF loci. However, overall 28 of the 32 loci showed directionally consistent effects to that of the adult BMI meta-analysis. We conclude that among the 32 loci that have been reported to associate with adult BMI in the largest meta-analysis of BMI to date, at least nine also contribute to the determination of common obesity in childhood in European Americans, as demonstrated by their associations in our pediatric cohort. [ABSTRACT FROM AUTHOR]

Diabetes impacts approximately 200 million people worldwide, of whom approximately 10% are affected by type 1 diabetes (T1D). The application of genome-wide association studies (GWAS) has robustly revealed dozens of genetic contributors to the pathogenesis of T1D, with the most recent meta-analysis identifying in excess of 40 loci. To identify additional genetic loci for T1D susceptibility, we examined associations in the largest meta-analysis to date between the disease and ,2.54 million SNPs in a combined cohort of 9,934 cases and 16,956 controls. Targeted follow-up of 53 SNPs in 1,120 affected trios uncovered three new loci associated with T1D that reached genome-wide significance. The most significantly associated SNP (rs539514, P = 5.66x10-11) resides in an intronic region of the LMO7 (LIM domain only 7) gene on 13q22. The second most significantly associated SNP (rs478222, P = 3.50x10-9) resides in an intronic region of the EFR3B (protein EFR3 homolog B) gene on 2p23; however, the region of linkage disequilibrium is approximately 800 kb and harbors additional multiple genes, including NCOA1, C2orf79, CENPO, ADCY3, DNAJC27, POMC, and DNMT3A. The third most significantly associated SNP (rs924043, P = 8.06x10-9) lies in an intergenic region on 6q27, where the region of association is approximately 900 kb and harbors multiple genes including WDR27, C6orf120, PHF10, TCTE3, C6orf208, LOC154449, DLL1, FAM120B, PSMB1, TBP, and PCD2. These latest associated regions add to the growing repertoire of gene networks predisposing to T1D. [ABSTRACT FROM AUTHOR]

Recent genome wide association studies (GWAS) have revealed a number of genetic variants robustly associated with bone mineral density (BMD) and/or osteoporosis. Evidence from epidemiological and clinical studies has shown an association between BMD and BMI, presumably as a consequence of bone loading. We investigated the 23 previously published BMD GWAS-derived loci in the context of childhood obesity by leveraging our existing genome-wide genotyped European American cohort of 1,106 obese children (BMI ≥95th percentile) and 5,997 controls (BMI <95th percentile). Evidence of association was only observed at one locus, namely Osterix (SP7), with the G allele of rs2016266 being significantly over-represented among childhood obesity cases (P = 2.85 × 10−3). When restricting these analyses to each gender, we observed strong association between rs2016266 and childhood obesity in females (477 cases and 2,867 controls; P = 3.56 × 10−4), which survived adjustment for all tests applied. However, no evidence of association was observed among males. Interestingly, Osterix is the only GWAS locus uncovered to date that has also been previously implicated in the determination of BMD in childhood. In conclusion, these findings indicate that a well established variant at the Osterix locus associated with increased BMD is also associated with childhood obesity primarily in females. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWAS) allow for a large number of samples to be assayed simultaneously, using a genome-wide tagging single nucleotide polymorphism (SNP) approach. The initial boon of success from disease studies such as macular degeneration and inflammatory bowel disease has been mitigated by lack of genome-wide significance for psychiatric disorders and related traits, despite evaluations of large populations. In addition to SNP genotypes, which are common variants typically attributing small or modest relative risk, copy number variations can be detected based on the same data set. Several rare recurrent copy number variations have been associated with psychiatric diseases in genome-wide analyses. Proper and responsible study design, followed by rigorous data quality assessment of genomic matching of cases and controls, is most likely to uncover regions of significant association that replicate in independent cohorts, thereby maximizing the chance of significant and confident association. [ABSTRACT FROM PUBLISHER]

Large-scale genome-wide association studies (GWAS) have identified many loci associated with body mass index (BMI), but few studies focused on obesity as a binary trait. Here we report the results of a GWAS and candidate SNP genotyping study of obesity, including extremely obese cases and never overweight controls as well as families segregating extreme obesity and thinness. We first performed a GWAS on 520 cases (BMI<35 kg/m²) and 540 control subjects (BMI,25 kg/m2), on measures of obesity and obesity-related traits. We subsequently followed up obesity-associated signals by genotyping the top ∼500 SNPs from GWAS in the combined sample of cases, controls and family members totaling 2,256 individuals. For the binary trait of obesity, we found 16 genome-wide significant signals within the FTO gene (strongest signal at rs17817449, P = 2.5×10-12). We next examined obesity-related quantitative traits (such as total body weight, waist circumference and waist to hip ratio), and detected genome-wide significant signals between waist to hip ratio and NRXN3 (rs11624704, P = 2.67×10-9), previously associated with body weight and fat distribution. Our study demonstrated how a relatively small sample ascertained through extreme phenotypes can detect genuine associations in a GWAS. [ABSTRACT FROM AUTHOR]

Major depressive disorder (MDD) is a common psychiatric and behavioral disorder. To discover novel variants conferring risk to MDD, we conducted a whole-genome scan of copy number variation (CNV), including 1,693 MDD cases and 4,506 controls genotyped on the Perlegen 600K platform. The most significant locus was observed on 5q35.1, harboring the SLIT3 gene (P = 2x10-3). Extending the controls with 30,000 subjects typed on the Illumina 550 k array, we found the CNV to remain exclusive to MDD cases (P = 3.2x10-9). Duplication was observed in 5 unrelated MDD cases encompassing 646 kb with highly similar breakpoints. SLIT3 is integral to repulsive axon guidance based on binding to Roundabout receptors. Duplication of 5q35.1 is a highly penetrant variation accounting for 0.7% of the subset of 647 cases harboring large CNVs, using a threshold of a minimum of 10 SNPs and 100 kb. This study leverages a large dataset of MDD cases and controls for the analysis of CNVs with matched platform and ethnicity. SLIT3 duplication is a novel association which explains a definitive proportion of the largely unknown etiology of MDD. [ABSTRACT FROM AUTHOR]

Objective: Recent genome-wide analysis identified a genetic variant on 5p14.1 (rs4307059), which is associated with risk for autism spectrum disorder. This study investigated whether rs4307059 also operates as a quantitative trait locus underlying a broader autism phenotype in the general population, focusing specifically on the social communication aspect of the spectrum. Method: Study participants were 7,313 children from the Avon Longitudinal Study of Parents and Children. Single-trait and joint-trait genotype associations were investigated for 29 measures related to language and communication, verbal intelligence, social interaction, and behavioral adjustment, assessed between ages 3 and 12 years. Analyses were performed in one-sided or directed mode and adjusted for multiple testing, trait interrelatedness, and random genotype dropout. Results: Single phenotype analyses showed that an increased load of rs4307059 risk allele is associated with stereotyped conversation and lower pragmatic communication skills, as measured by the Children's Communication Checklist (at a mean age of 9.7 years). In addition a trend toward a higher frequency of identification of special educational needs (at a mean age of 11.8 years) was observed. Variation at rs4307059 was also associated with the phenotypic profile of studied traits. This joint signal was fully explained neither by single-trait associations nor by overall behavioral adjustment problems but suggested a combined effect, which manifested through multiple subthreshold social, communicative, and cognitive impairments. Conclusions: Our results suggest that common variation at 5p14.1 is associated with social communication spectrum phenotypes in the general population and support the role of rs4307059 as a quantitative trait locus for autism spectrum disorder. [ABSTRACT FROM AUTHOR]

OBJECTIVE--Obesity is an increasingly common disorder that predisposes to several medical conditions, including type 2 diabetes. We investigated whether large and rare copy-number variations (CNVs) differentiate moderate to extreme obesity from never-overweight control subjects. RESEARCH DESIGN AND METHODS--Using single nucleotide polymorphism (SNP) arrays, we performed a genome-wide CNV survey on 430 obese case subjects (BMI >35 kg/m2) and 379 never-overweight control subjects (BMI <25 kg/m2). All subjects were of European ancestry and were genotyped on the Illumina HumanHap550 arrays with ~550,000 SNP markers. The CNV calls were generated by PennCNV software. RESULTS--CNVs >1 Mb were found to be overrepresented in case versus control subjects (odds ratio [OR] = 1.5 [95% CI 0.5-5]), and CNVs >2 Mb were present in 1.3% of the case subjects but were absent in control subjects (OR = infinity [95% CI 1.2-infinity]). When focusing on rare deletions that disrupt genes, even more pronounced effect sizes are observed (OR = 2.7 [95% CI 0.5-27.1] for CNVs >1 Mb). Interestingly, obese case subjects who carry these large CNVs have moderately high BMI and do not appear to be extreme cases. Several CNVs disrupt known candidate genes for obesity, such as a 3.3-Mb deletion disrupting NAPIL5 and a 2.1-Mb deletion disrupting UCP1 and IL15. CONCLUSIONS--Our results suggest that large CNVs, especially rare deletions, confer risk of obesity in patients with moderate obesity and that genes impacted by large CNVs represent intriguing candidates for obesity that warrant further study. Diabetes 59:2690-2694, 2010 [ABSTRACT FROM AUTHOR]

Schizophrenia is a psychiatric disorder with onset in late adolescence and unclear etiology characterized by both positive and negative symptoms, as well as cognitive deficits. To identify copy number variations (CNVs) that increase the risk of schizophrenia, we performed a whole-genome CNV analysis on a cohort of 977 schizophrenia cases and 2,000 healthy adults of European ancestry who were genotyped with 1.7 million probes. Positive findings were evaluated in an independent cohort of 758 schizophrenia cases and 1,485 controls. The Gene Ontology synaptic transmission family of genes was notably enriched for CNVs in the cases (P= 1.5 x 10-7). Among these, CACNA1B and DOC2A, both calcium-signaling genes responsible for neuronal excitation, were deleted in 16 cases and duplicated in 10 cases, respectively. In addition, RET and RIT2, both ras-related genes important for neural crest development, were significantly affected by CNVs. RET deletion was exclusive to seven cases, and RIT2 deletions were overrepresented common variant CNVs in the schizophrenia cases. Our results suggest that novel variations involving the processes of synaptic transmission contribute to the genetic susceptibility of schizophrenia. [ABSTRACT FROM AUTHOR]

Congenital heart disease (CHD) is the most common birth abnormality and the etiology is unknown in the overwhelming majority of cases. ISLET1 (ISL1) is a transcription factor that marks cardiac progenitor cells and generates diverse multipotent cardiovascular cell lineages. The fundamental role of ISL1 in cardiac morphogenesis makes this an exceptional candidate gene to consider as a cause of complex congenital heart disease. We evaluated whether genetic variation in ISL1 fits the common variant-common disease hypothesis. A 2-stage case-control study examined 27 polymorphisms mapping to the ISL1 locus in 300 patients with complex congenital heart disease and 2,201 healthy pediatric controls. Eight genic and flanking ISL1 SNPs were significantly associated with complex congenital heart disease. A replication study analyzed these candidate SNPs in 1,044 new cases and 3,934 independent controls and confirmed that genetic variation in ISL1 is associated with risk of non-syndromic congenital heart disease. Our results demonstrate that two different ISL1 haplotypes contribute to risk of CHD in white and black/African American populations. [ABSTRACT FROM AUTHOR]

OBJECTIVE--A number of studies have found that BMI in early life influences the risk of developing type 2 diabetes later in life. Our goal was to investigate if any type 2 diabetes variants uncovered through genome-wide association studies (GWAS) impact BMI in childhood. RESEARCH DESIGN AND METHODS--Using data from an ongoing GWAS of pediatric BMI in our cohort, we investigated the association of pediatric BMI with 20 single nucleotide polymorphisms at 18 type 2 diabetes loci uncovered through GWAS, consisting of ADAMTS9, CDC123-CAMKID, CDKAL1, CDKN2A/B, EXT2, FTO, HHEX-IDE, IGF2BP2, the intragenic region on 11p12, JAZF1, KCNQ1, LOC387761, MTNR1B, NOTCH2, SLC3OA8, TCF7L2, THADA, and TSPAN8-LGR5. We randomly partitioned our cohort exactly in half in order to have a discovery cohort (n = 3,592) and a replication cohort (n = 3,592). RESULTS--Our data show that the major type 2 diabetes risk-conferring G allele of rs7923837 at the HHEX-IDE locus was associated with higher pediatric BMI in both the discovery (P = 0.0013 and survived correction for 20 tests) and replication (P = 0.023) sets (combined P = 1.01 x 10[sup -4]). Association was not detected with any other known type 2 diabetes loci uncovered to date through GWAS except for the well-established FTO. CONCLUSIONS--Our data show that the same genetic HHEX-IDE variant, which is associated with type 2 diabetes from previous studies, also influences pediatric BMI. Diabetes 59: 751-755, 2010 [ABSTRACT FROM AUTHOR]

Background: Human height is considered highly heritable and correlated with certain disorders, such as type 2 diabetes and cancer. Despite environmental influences, genetic factors are known to play an important role in stature determination. A number of genetic determinants of adult height have already been established through genome wide association studies. Methods: To examine 51 single nucleotide polymorphisms (SNPs) corresponding to the 46 previously reported genomic loci for height in 8,184 European American children with height measurements. We leveraged genotyping data from our ongoing GWA study of height variation in children in order to query the 51 SNPs in this pediatric cohort. Results: Sixteen of these SNPs yielded at least nominally significant association to height, representing fifteen different loci including EFEMP1-PNPT1, GPR126, C6orf173, SPAG17, Histone class 1, HLA class III and GDF5-UQCC. Other loci revealed no evidence for association, including HMGA1 and HMGA2. For the 16 associated variants, the genotype score explained 1.64% of the total variation for height z-score. Conclusion: Among 46 loci that have been reported to associate with adult height to date, at least 15 also contribute to the determination of height in childhood. [ABSTRACT FROM AUTHOR]

The prevalence of obesity in children and adults in the United States has increased dramatically over the past decade. Besides environmental factors, genetic factors are known to play an important role in the pathogenesis of obesity. A number of genetic determinants of adult BMI have already been established through genome-wide association (GWA) studies. In this study, we examined 25 single-nucleotide polymorphisms (SNPs) corresponding to 13 previously reported genomic loci in 6,078 children with measures of BMI. Fifteen of these SNPs yielded at least nominally significant association to BMI, representing nine different loci including INSIG2, FTO, MC4R, TMEM18, GNPDA2, NEGR1, BDNF, KCTD15, and 1q25. Other loci revealed no evidence for association, namely at MTCH2, SH2B1, 12q13, and 3q27. For the 15 associated variants, the genotype score explained 1.12% of the total variation for BMI z-score. We conclude that among 13 loci that have been reported to associate with adult BMI, at least nine also contribute to the determination of BMI in childhood as demonstrated by their associations in our pediatric cohort. [ABSTRACT FROM AUTHOR]

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

OBJECTIVE--A number of studies have found that reduced birth weight is associated with type 2 diabetes later in life; however, the underlying mechanism for this correlation remains unresolved. Recently, association has been demonstrated between low birth weight and single nucleotide polymorphisms (SNPs) at the CDKAL1 and HHEX-IDE loci, regions that were previously implicated in the pathogenesis of type 2 diabetes. In order to investigate whether type 2 diabetes risk-conferring alleles associate with low birth weight in our Caucasian childhood cohort, we examined the effects of 20 such loci on this trait. RESEARCH DESIGN AND METHODS--Using data from an ongoing genome-wide association study in our cohort of 5,465 Caucasian children with recorded birth weights, we investigated the association of the previously reported type 2 diabetes-associated variation at 20 loci including TCFTL2, HHEX-IDE, PPARG, KCNJ11, SLC3OA8, IGF2BP2, CDKAL1, CDKN2A/2B, and JAZF1 with birth weight. RESULTS--Our data show that the minor allele of rs7756992 (P = 8 x 10-5) at the CDKAL1 locus is strongly associated with lower birth weight, whereas a perfect surrogate for variation previously implicated for the trait at the same locus only yielded nominally significant association (P = 0.01; re rs7756992 = 0.677). However, association was not detected with any of the other type 2 diabetes loci studied. CONCLUSIONS--We observe association between lower birth weight and type 2 diabetes risk-conferring alleles at the CDKAL1 locus. Our data show that the same genetic locus that has been identified as a marker for type 2 diabetes in previous studies also influences birth weight. Diabetes 58:2414-2418, 2009 [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWAS) have been fruitful in identifying disease susceptibility loci for common and complex diseases. A remaining question is whether we can quantify individual disease risk based on genotype data, in order to facilitate personalized prevention and treatment for complex diseases. Previous studies have typically failed to achieve satisfactory performance, primarily due to the use of only a limited number of confirmed susceptibility loci. Here we propose that sophisticated machine-learning approaches with a large ensemble of markers may improve the performance of disease risk assessment. We applied a Support Vector Machine (SVM) algorithm on a GWAS dataset generated on the Affymetrix genotyping platform for type 1 diabetes (T1D) and optimized a risk assessment model with hundreds of markers. We subsequently tested this model on an independent Illumina-genotyped dataset with imputed genotypes (1,008 cases and 1,000 controls), as well as a separate Affymetrix-genotyped dataset (1,529 cases and 1,458 controls), resulting in area under ROC curve (AUC) of ∼0.84 in both datasets. In contrast, poor performance was achieved when limited to dozens of known susceptibility loci in the SVM model or logistic regression model. Our study suggests that improved disease risk assessment can be achieved by using algorithms that take into account interactions between a large ensemble of markers. We are optimistic that genotype-based disease risk assessment may be feasible for diseases where a notable proportion of the risk has already been captured by SNP arrays. [ABSTRACT FROM AUTHOR]

Recently a modest, but consistently, replicated association was demonstrated between obesity and the single-nucleotide polymorphism (SNP), rs17782313, 3′ of the MC4R locus as a consequence of a meta-analysis of genome-wide association (GWA) studies of the disease in white populations. We investigated the association in the context of the childhood form of the disease utilizing data from our ongoing GWA study in a cohort of 728 European-American (EA) obese children (BMI ≥95th percentile) and 3,960 EA controls (BMI <95th percentile), as well as 1,008 African-American (AA) obese children and 2,715 AA controls. rs571312, rs10871777, and rs476828 (perfect surrogates for rs17782313) yielded odds ratios in the EA cohort of 1.142 (P = 0.045), 1.137 (P = 0.054), and 1.145 (P = 0.042); however, there was no significant association with these SNPs in the AA cohort. When investigating all 30 SNPs present on the Illumina BeadChip at this locus, again there was no evidence for association in AA cases when correcting for the number of tests employed. As such, variants 3′ to the MC4R locus present on the genotyping platform utilized confer a similar magnitude of risk of obesity in white children as to their adult white counterparts but this observation did not extend to AAs.Obesity (2009) 17 7, 1461–1465. doi:10.1038/oby.2009.53 [ABSTRACT FROM AUTHOR]