Understanding the genetic and epigenetic basis of common variable immunodeficiency disorder through omics approaches.

BACKGROUND: Common variable immunodeficiency disorder (CVID) is the most frequently encountered symptomatic primary immunodeficiency, characterized by highly heterogeneous immunological features and clinical presentations. As better targeted therapies are importantly needed for CVID, improved understanding of the genetic and epigenetic basis for the development of CVID presents the most promising venue for improvement. SCOPE OF REVIEW: Several genomic and epigenomic studies of CVID have recently been carried out on cohorts of sporadic cases of CVID. Using high-throughput array and sequencing technologies, these studies identified several loci associated with the disease. Here, we review the omics approaches used in these studies and resulting discoveries. We also discuss how these findings lead to improved understanding of the molecular basis of CVID and possible future directions to pursue. MAJOR CONCLUSIONS: High-throughput omics approaches have been productive in genetic and epigenetic studies of CVID, leading to the identifications of several significantly associated loci of different variant types, as well as genes and pathways elucidating the shared genetic basis of CVID and autoimmunity. Complex polygenic model of inheritance together with interplay between genetic components and environmental factors may account for the etiology of CVID and various associated comorbidities. GENERAL SIGNIFICANCE: The genetic and epigenetic basis of CVID when further translated through functional studies will allow for improved understanding of the CVID etiology and will provide new insights into the development of potential new therapeutic approaches for this devastating condition. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang.

Systematic data-querying of large pediatric biorepository identifies novel Ehlers-Danlos Syndrome variant.

BACKGROUND: Ehlers Danlos Syndrome is a rare form of inherited connective tissue disorder, which primarily affects skin, joints, muscle, and blood cells. The current study aimed at finding the mutation that causing EDS type VII C also known as "Dermatosparaxis" in this family. METHODS: Through systematic data querying of the electronic medical records (EMRs) of over 80,000 individuals, we recently identified an EDS family that indicate an autosomal dominant inheritance. The family was consented for genomic analysis of their de-identified data. After a negative screen for known mutations, we performed whole genome sequencing on the male proband, his affected father, and unaffected mother. We filtered the list of non-synonymous variants that are common between the affected individuals. RESULTS: The analysis of non-synonymous variants lead to identifying a novel mutation in the ADAMTSL2 (p. Gly421Ser) gene in the affected individuals. Sanger sequencing confirmed the mutation. CONCLUSION: Our work is significant not only because it sheds new light on the pathophysiology of EDS for the affected family and the field at large, but also because it demonstrates the utility of unbiased large-scale clinical recruitment in deciphering the genetic etiology of rare mendelian diseases. With unbiased large-scale clinical recruitment we strive to sequence as many rare mendelian diseases as possible, and this work in EDS serves as a successful proof of concept to that effect.

CNV Association of Diverse Clinical Phenotypes from eMERGE reveals novel disease biology underlying cardiovascular disease.

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

Copy number variation meta-analysis reveals a novel duplication at 9p24 associated with multiple neurodevelopmental disorders.

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.