A cross-disorder dosage sensitivity map of the human genome.

Rare copy-number variants (rCNVs) include deletions and duplications that occur infrequently in the global human population and can confer substantial risk for disease. In this study, we aimed to quantify the properties of haploinsufficiency (i.e., deletion intolerance) and triplosensitivity (i.e., duplication intolerance) throughout the human genome. We harmonized and meta-analyzed rCNVs from nearly one million individuals to construct a genome-wide catalog of dosage sensitivity across 54 disorders, which defined 163 dosage sensitive segments associated with at least one disorder. These segments were typically gene dense and often harbored dominant dosage sensitive driver genes, which we were able to prioritize using statistical fine-mapping. Finally, we designed an ensemble machine-learning model to predict probabilities of dosage sensitivity (pHaplo & pTriplo) for all autosomal genes, which identified 2,987 haploinsufficient and 1,559 triplosensitive genes, including 648 that were uniquely triplosensitive. This dosage sensitivity resource will provide broad utility for human disease research and clinical genetics.

Target genes regulated by CLEC16A intronic region associated with common variable immunodeficiency.

BACKGROUND: CLEC16A intron 19 has been identified as a candidate locus for common variable immunodeficiency (CVID). OBJECTIVES: This study sought to elucidate the molecular mechanism by which variants at the CLEC16A intronic locus may contribute to the pathogenesis of CVID. METHODS: The investigators performed fine-mapping of the CLEC16A locus in a CVID cohort, then deleted the candidate functional SNP in T-cell lines by the CRISPR-Cas9 technique and conducted RNA-sequencing to identify target gene(s). The interactions between the CLEC16A locus and its target genes were identified using circular chromosome conformation capture. The transcription factor complexes mediating the chromatin interactions were determined by proteomic approach. The molecular pathways regulated by the CLEC16A locus were examined by RNA-sequencing and reverse phase protein array. RESULTS: This study showed that the CLEC16A locus is an enhancer regulating expression of multiple target genes including a distant gene ATF7IP2 through chromatin interactions. Distinct transcription factor complexes mediate the chromatin interactions in an allele-specific manner. Disruption of the CLEC16A locus affects the AKT signaling pathway, as well as the molecular response of CD4+ T cells to immune stimulation. CONCLUSIONS: Through multiomics and targeted experimental approaches, this study elucidated the underlying target genes and signaling pathways involved in the genetic association of CLEC16A with CVID, and highlighted plausible molecular targets for developing novel therapeutics.

Revealing novel genomic insights and therapeutic targets for juvenile idiopathic arthritis through omics.

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.

Shared molecular mechanisms and transdiagnostic potential of neurodevelopmental disorders and immune disorders.

The co-occurrence and familial clustering of neurodevelopmental disorders and immune disorders suggest shared genetic risk factors. Based on genome-wide association summary statistics from five neurodevelopmental disorders and four immune disorders, we conducted genome-wide, local genetic correlation and polygenic overlap analysis. We further performed a cross-trait GWAS meta-analysis. Pleotropic loci shared between the two categories of diseases were mapped to candidate genes using multiple algorithms and approaches. Significant genetic correlations were observed between neurodevelopmental disorders and immune disorders, including both positive and negative correlations. Neurodevelopmental disorders exhibited higher polygenicity compared to immune disorders. Around 50%-90% of genetic variants of the immune disorders were shared with neurodevelopmental disorders. The cross-trait meta-analysis revealed 154 genome-wide significant loci, including 8 novel pleiotropic loci. Significant associations were observed for 30 loci with both types of diseases. Pathway analysis on the candidate genes at these loci revealed common pathways shared by the two types of diseases, including neural signaling, inflammatory response, and PI3K-Akt signaling pathway. In addition, 26 of the 30 lead SNPs were associated with blood cell traits. Neurodevelopmental disorders exhibit complex polygenic architecture, with a subset of individuals being at a heightened genetic risk for both neurodevelopmental and immune disorders. The identification of pleiotropic loci has important implications for exploring opportunities for drug repurposing, enabling more accurate patient stratification, and advancing genomics-informed precision in the medical field of neurodevelopmental disorders.

Genomic Disorders in CKD across the Lifespan.

SIGNIFICANCE STATEMENT: Pathogenic structural genetic variants, also known as genomic disorders, have been associated with pediatric CKD. This study extends those results across the lifespan, with genomic disorders enriched in both pediatric and adult patients compared with controls. In the Chronic Renal Insufficiency Cohort study, genomic disorders were also associated with lower serum Mg, lower educational performance, and a higher risk of death. A phenome-wide association study confirmed the link between kidney disease and genomic disorders in an unbiased way. Systematic detection of genomic disorders can provide a molecular diagnosis and refine prediction of risk and prognosis. BACKGROUND: Genomic disorders (GDs) are associated with many comorbid outcomes, including CKD. Identification of GDs has diagnostic utility. METHODS: We examined the prevalence of GDs among participants in the Chronic Kidney Disease in Children (CKiD) cohort II ( n =248), Chronic Renal Insufficiency Cohort (CRIC) study ( n =3375), Columbia University CKD Biobank (CU-CKD; n =1986), and the Family Investigation of Nephropathy and Diabetes (FIND; n =1318) compared with 30,746 controls. We also performed a phenome-wide association analysis (PheWAS) of GDs in the electronic MEdical Records and GEnomics (eMERGE; n =11,146) cohort. RESULTS: We found nine out of 248 (3.6%) CKiD II participants carried a GD, replicating prior findings in pediatric CKD. We also identified GDs in 72 out of 6679 (1.1%) adult patients with CKD in the CRIC, CU-CKD, and FIND cohorts, compared with 199 out of 30,746 (0.65%) GDs in controls (OR, 1.7; 95% CI, 1.3 to 2.2). Among adults with CKD, we found recurrent GDs at the 1q21.1, 16p11.2, 17q12, and 22q11.2 loci. The 17q12 GD (diagnostic of renal cyst and diabetes syndrome) was most frequent, present in 1:252 patients with CKD and diabetes. In the PheWAS, dialysis and neuropsychiatric phenotypes were the top associations with GDs. In CRIC participants, GDs were associated with lower serum magnesium, lower educational achievement, and higher mortality risk. CONCLUSION: Undiagnosed GDs are detected both in children and adults with CKD. Identification of GDs in these patients can enable a precise genetic diagnosis, inform prognosis, and help stratify risk in clinical studies. GDs could also provide a molecular explanation for nephropathy and comorbidities, such as poorer neurocognition for a subset of patients.

Biliary atresia is associated with polygenic susceptibility in ciliogenesis and planar polarity effector genes.

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.

DeepCNV: a deep learning approach for authenticating copy number variations.

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.

Trans-ethnic genomic informed risk assessment for Alzheimer's disease: An International Hundred K+ Cohorts Consortium study.

BACKGROUND: As a collaboration model between the International HundredK+ Cohorts Consortium (IHCC) and the Davos Alzheimer's Collaborative (DAC), our aim was to develop a trans-ethnic genomic informed risk assessment (GIRA) algorithm for Alzheimer's disease (AD). METHODS: The GIRA model was created to include polygenic risk score calculated from the AD genome-wide association study loci, the apolipoprotein E haplotypes, and non-genetic covariates including age, sex, and the first three principal components of population substructure. RESULTS: We validated the performance of the GIRA model in different populations. The proteomic study in the participant sites identified proteins related to female infertility and autoimmune thyroiditis and associated with the risk scores of AD. CONCLUSIONS: As the initial effort by the IHCC to leverage existing large-scale datasets in a collaborative setting with DAC, we developed a trans-ethnic GIRA for AD with the potential of identifying individuals at high risk of developing AD for future clinical applications.

MONTAGE: a new tool for high-throughput detection of mosaic copy number variation.

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 .

Association of novel rare coding variants with juvenile idiopathic arthritis.

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.

Genome-wide association study of maternal and inherited effects on left-sided cardiac malformations.

Congenital left-sided lesions (LSLs) are serious, heritable malformations of the heart. However, little is known about the genetic causes of LSLs. This study was undertaken to identify common variants acting through the genotype of the affected individual (i.e. case) or the mother (e.g. via an in utero effect) that influence the risk of LSLs. A genome-wide association study (GWAS) was performed using data from 377 LSL case-parent triads, with follow-up studies in an independent sample of 224 triads and analysis of the combined data. Associations with both the case and maternal genotypes were assessed using log-linear analyses under an additive model. An association between LSLs and the case genotype for one intergenic SNP on chromosome 16 achieved genome-wide significance in the combined data (rs8061121, combined P = 4.0 × 10(-9); relative risk to heterozygote: 2.6, 95% CI: 1.9-3.7). In the combined data, there was also suggestive evidence of association between LSLs and the case genotype for a variant in the synaptoporin gene (rs1975649, combined P = 3.4 × 10(-7); relative risk to heterozygote: 1.6, 95% CI: 1.4-2.0) and between LSLs and the maternal genotype for an intergenic SNP on chromosome 10 (rs11008222, combined P = 6.3 × 10(-7); relative risk to heterozygote: 1.6, 95% CI: 1.4-2.0). This is the first GWAS of LSLs to evaluate associations with both the case and maternal genotypes. The results of this study identify three candidate LSL susceptibility loci, including one that appears to be associated with the risk of LSLs via the maternal genotype.

Copy Number Variations in CTNNA3 and RBFOX1 Associate with Pediatric Food Allergy.

Food allergy is a significant public health concern, especially among children. Previous candidate gene studies suggested a few susceptibility loci for food allergy, but no study investigated the contribution of copy number variations (CNVs) to food allergy on a genome-wide scale. To investigate the genetics of food allergy, we performed CNV assessment using high-resolution genome-wide single nucleotide polymorphism arrays. CNV calls from a total of 357 cases with confirmed food allergy and 3980 controls were analyzed within a discovery cohort, followed by a replication analysis composed of 167 cases and 1573 controls. We identified that CNVs in CTNNA3 were significantly associated with food allergy in both the discovery cohort and the replication cohort. Of particular interest, CTNNA3 CNVs hit exons or intron regions rich in histone marker H3K4Me1. CNVs in a second gene (RBFOX1) showed a significant association (p = 7.35 × 10(-5)) with food allergy at the genome-wide level in our meta-analysis of the European ancestry cohorts. The presence of these CNVs was confirmed by quantitative PCR. Furthermore, knockdown of CTNNA3 resulted in upregulation of CD63 and CD203c in mononuclear cells upon PMA stimulation, suggesting a role in sensitization to allergen. We uncovered at least two plausible genes harboring CNV loci that are enriched in pediatric patients with food allergies. The novel gene candidates discovered in this study by genome-wide CNV analysis are compelling drug and diagnostic targets for food allergy.

Variants in CXCR4 associate with juvenile idiopathic arthritis susceptibility.

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.

Increased frequency of de novo copy number variants in congenital heart disease by integrative analysis of single nucleotide polymorphism array and exome sequence data.

RATIONALE: Congenital heart disease (CHD) is among the most common birth defects. Most cases are of unknown pathogenesis. OBJECTIVE: To determine the contribution of de novo copy number variants (CNVs) in the pathogenesis of sporadic CHD. METHODS AND RESULTS: We studied 538 CHD trios using genome-wide dense single nucleotide polymorphism arrays and whole exome sequencing. Results were experimentally validated using digital droplet polymerase chain reaction. We compared validated CNVs in CHD cases with CNVs in 1301 healthy control trios. The 2 complementary high-resolution technologies identified 63 validated de novo CNVs in 51 CHD cases. A significant increase in CNV burden was observed when comparing CHD trios with healthy trios, using either single nucleotide polymorphism array (P=7×10(-5); odds ratio, 4.6) or whole exome sequencing data (P=6×10(-4); odds ratio, 3.5) and remained after removing 16% of de novo CNV loci previously reported as pathogenic (P=0.02; odds ratio, 2.7). We observed recurrent de novo CNVs on 15q11.2 encompassing CYFIP1, NIPA1, and NIPA2 and single de novo CNVs encompassing DUSP1, JUN, JUP, MED15, MED9, PTPRE SREBF1, TOP2A, and ZEB2, genes that interact with established CHD proteins NKX2-5 and GATA4. Integrating de novo variants in whole exome sequencing and CNV data suggests that ETS1 is the pathogenic gene altered by 11q24.2-q25 deletions in Jacobsen syndrome and that CTBP2 is the pathogenic gene in 10q subtelomeric deletions. CONCLUSIONS: We demonstrate a significantly increased frequency of rare de novo CNVs in CHD patients compared with healthy controls and suggest several novel genetic loci for CHD.

Functional impact of global rare copy number variation in autism spectrum disorders.

The autism spectrum disorders (ASDs) are a group of conditions characterized by impairments in reciprocal social interaction and communication, and the presence of restricted and repetitive behaviours. Individuals with an ASD vary greatly in cognitive development, which can range from above average to intellectual disability. Although ASDs are known to be highly heritable ( approximately 90%), the underlying genetic determinants are still largely unknown. Here we analysed the genome-wide characteristics of rare (<1% frequency) copy number variation in ASD using dense genotyping arrays. When comparing 996 ASD individuals of European ancestry to 1,287 matched controls, cases were found to carry a higher global burden of rare, genic copy number variants (CNVs) (1.19 fold, P = 0.012), especially so for loci previously implicated in either ASD and/or intellectual disability (1.69 fold, P = 3.4 x 10(-4)). Among the CNVs there were numerous de novo and inherited events, sometimes in combination in a given family, implicating many novel ASD genes such as SHANK2, SYNGAP1, DLGAP2 and the X-linked DDX53-PTCHD1 locus. We also discovered an enrichment of CNVs disrupting functional gene sets involved in cellular proliferation, projection and motility, and GTPase/Ras signalling. Our results reveal many new genetic and functional targets in ASD that may lead to final connected pathways.

Both rare and de novo copy number variants are prevalent in agenesis of the corpus callosum but not in cerebellar hypoplasia or polymicrogyria.

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.

Rare variants at 16p11.2 are associated with common variable immunodeficiency.

BACKGROUND: Common variable immunodeficiency (CVID) is characterized clinically by inadequate quantity and quality of serum immunoglobulins with increased susceptibility to infections, resulting in significant morbidity and mortality. Only a few genes have been uncovered, and the genetic background of CVID remains elusive to date for the majority of patients. OBJECTIVE: We sought to seek novel associations of genes and genetic variants with CVID. METHODS: We performed association analyses in a discovery cohort of 164 patients with CVID and 19,542 healthy control subjects genotyped on the Immuno BeadChip from Illumina platform; replication of findings was examined in an independent cohort of 135 patients with CVID and 2,066 healthy control subjects, followed by meta-analysis. RESULTS: We identified 11 single nucleotide polymorphisms (SNPs) at the 16p11.2 locus associated with CVID at a genome-wide significant level in the discovery cohort. The most significant SNP, rs929867 (P = 6.21 × 10(-9)), is in the gene fused-in-sarcoma (FUS), with 4 other SNPs mapping to integrin CD11b (ITGAM). Results were confirmed in our replication cohort. Conditional association analysis suggests a single association signal at the 16p11.2 locus. A strong trend of association was also seen for 38 SNPs (P < 5 × 10(-5)) in the MHC region, supporting that this is a genuine CVID locus. Interestingly, we found that 80% of patients with the rare ITGAM variants have reduced switched memory B-cell counts. CONCLUSION: We report a novel association of CVID with rare variants at the FUS/ITGAM (CD11b) locus on 16p11.2. The association signal is enriched for promoter/enhancer markers in the ITGAM gene. ITGAM encodes the integrin CD11b, a part of complement receptor 3, a novel candidate gene implicated here for the first time in the pathogenesis of CVID.

GWAS of blood cell traits identifies novel associated loci and epistatic interactions in Caucasian and African-American children.

Hematological traits are important clinical indicators, the genetic determinants of which have not been fully investigated. Common measures of hematological traits include red blood cell (RBC) count, hemoglobin concentration (HGB), hematocrit (HCT), mean corpuscular hemoglobin (MCH), MCH concentration (MCHC), mean corpuscular volume (MCV), platelet count (PLT) and white blood cell (WBC) count. We carried out a genome-wide association study of the eight common hematological traits among 7943 African-American children and 6234 Caucasian children. In African Americans, we report five novel associations of HBE1 variants with HCT and MCHC, the alpha-globin gene cluster variants with RBC and MCHC, and a variant at the ARHGEF3 locus with PLT, as well as replication of four previously reported loci at genome-wide significance. In Caucasians, we report a novel association of variants at the COPZ1 locus with PLT as well as replication of four previously reported loci at genome-wide significance. Extended analysis of an association observed between MCH and the alpha-globin gene cluster variants demonstrated independent effects and epistatic interaction at the locus, impacting the risk of iron deficiency anemia in African Americans with specific genotype states. In summary, we extend the understanding of genetic variants underlying hematological traits based on analyses in African-American children.

Large-scale gene-centric meta-analysis across 39 studies identifies type 2 diabetes loci.

To identify genetic factors contributing to type 2 diabetes (T2D), we performed large-scale meta-analyses by using a custom ∼50,000 SNP genotyping array (the ITMAT-Broad-CARe array) with ∼2000 candidate genes in 39 multiethnic population-based studies, case-control studies, and clinical trials totaling 17,418 cases and 70,298 controls. First, meta-analysis of 25 studies comprising 14,073 cases and 57,489 controls of European descent confirmed eight established T2D loci at genome-wide significance. In silico follow-up analysis of putative association signals found in independent genome-wide association studies (including 8,130 cases and 38,987 controls) performed by the DIAGRAM consortium identified a T2D locus at genome-wide significance (GATAD2A/CILP2/PBX4; p = 5.7 × 10(-9)) and two loci exceeding study-wide significance (SREBF1, and TH/INS; p < 2.4 × 10(-6)). Second, meta-analyses of 1,986 cases and 7,695 controls from eight African-American studies identified study-wide-significant (p = 2.4 × 10(-7)) variants in HMGA2 and replicated variants in TCF7L2 (p = 5.1 × 10(-15)). Third, conditional analysis revealed multiple known and novel independent signals within five T2D-associated genes in samples of European ancestry and within HMGA2 in African-American samples. Fourth, a multiethnic meta-analysis of all 39 studies identified T2D-associated variants in BCL2 (p = 2.1 × 10(-8)). Finally, a composite genetic score of SNPs from new and established T2D signals was significantly associated with increased risk of diabetes in African-American, Hispanic, and Asian populations. In summary, large-scale meta-analysis involving a dense gene-centric approach has uncovered additional loci and variants that contribute to T2D risk and suggests substantial overlap of T2D association signals across multiple ethnic groups.

Copy number variation at 1q21.1 associated with neuroblastoma.

Common copy number variations (CNVs) represent a significant source of genetic diversity, yet their influence on phenotypic variability, including disease susceptibility, remains poorly understood. To address this problem in human cancer, we performed a genome-wide association study of CNVs in the childhood cancer neuroblastoma, a disease in which single nucleotide polymorphism variations are known to influence susceptibility. We first genotyped 846 Caucasian neuroblastoma patients and 803 healthy Caucasian controls at approximately 550,000 single nucleotide polymorphisms, and performed a CNV-based test for association. We then replicated significant observations in two independent sample sets comprised of a total of 595 cases and 3,357 controls. Here we describe the identification of a common CNV at chromosome 1q21.1 associated with neuroblastoma in the discovery set, which was confirmed in both replication sets. This CNV was validated by quantitative polymerase chain reaction, fluorescent in situ hybridization and analysis of matched tumour specimens, and was shown to be heritable in an independent set of 713 cancer-free parent-offspring trios. We identified a previously unknown transcript within the CNV that showed high sequence similarity to several neuroblastoma breakpoint family (NBPF) genes and represents a new member of this gene family (NBPF23). This transcript was preferentially expressed in fetal brain and fetal sympathetic nervous tissues, and the expression level was strictly correlated with CNV state in neuroblastoma cells. These data demonstrate that inherited copy number variation at 1q21.1 is associated with neuroblastoma and implicate a previously unknown neuroblastoma breakpoint family gene in early tumorigenesis of this childhood cancer.