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

Glessner, Joseph; Li, Jin; Desai, Akshatha; Palmer, Melody R.; Kim, Dokyoon; Lucas, Anastasia; Chang, Xiao; Connolly, John J.; Almoguera, Berta; Harley, John B.; Jarvik, Gail P.; Ritchie, Marylyn D.; Sleiman, Patrick; Roden, Dan M.; Crosslin, David R.; Hákonarson, Hákon

doi:10.1016/j.ijcard.2019.07.058

Cited by 8 publications

(10 citation statements)

References 47 publications

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“…Our results demonstrate increased burden of rare CNVs in NDD disease biology, both novel and known in keeping with previous reports [ 6 , 7 , 17 , 20 ]. The robustness of using large cohorts of pediatric patients diagnosed with ADHD and/or ASD ( N = 15,654 cases N = 19,993 controls) improves our ability and confidence of accurately capturing rare recurrent statistical events, such as the CNVs reported herein.…”

Section: Discussionsupporting

confidence: 92%

Rare recurrent copy number variations in metabotropic glutamate receptor interacting genes in children with neurodevelopmental disorders

Glessner

Khan

Chang

et al. 2023

J Neurodevelop Disord

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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.

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Section: Discussionsupporting

confidence: 92%

Rare recurrent copy number variations in metabotropic glutamate receptor interacting genes in children with neurodevelopmental disorders

Glessner

Khan

Chang

et al. 2023

J Neurodevelop Disord

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“…45 We performed CNV analysis on 11,146 eMERGE I participants genotyped on Illumina 660W arrays, for whom both high-quality microarray intensity level data and International Classification of Diseases (ICD) 9 and 10 codes records were available. 46,47 These eMERGE I participants were not selected on the basis of a CKD phenotype, but comprised a wide range of phenotypes, including CKD.…”

Section: Methodsmentioning

confidence: 99%

Genomic Disorders in CKD across the Lifespan

Verbitsky

Krishnamurthy

Krithivasan

et al. 2022

JASN

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Background:Genomic Disorders (GDs) are associated with many comorbid outcomes, including chronic kidney disease (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 study (CRIC, N = 3,375), Columbia University CKD Biobank (CU-CKD, N=1,146), and the Family Investigation of Nephropathy and Diabetes (FIND, N=1,318) compared to 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 9/248 (3.6%) CKiD II participants carried a GD, replicating prior findings in pediatric CKD. We also identified GDs in 72/6,679 (1.1%) adult CKD patients in the CRIC, CU-CKD, and FIND cohorts, compared to 199/30,746 (0.65%) GDs in controls (OR=1.7, 95% CI 1.3-2.2). 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 CKD cases with 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.

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“…For African American, genes for top 10 important SNPs are COL24A1, INSL6, MTTP, ATF7IP, CUBN, SLC39A12, ZNF208, LPIN3, UTRN; COL24A1, INSL6, MTTP, ATF7IP, CUBN, SLC39A12, and ZNF208 and are showed to have close relationship to cardiac functions [21][22][23][24][25][26]. For Caucasian cohort, genes for top 10 important SNPs are DNHD1, ASPM, TTC21B, GMPS-KCNAB1, HEATR1, OR10J1, and LGALS8; except for DNHD1, all other genes are related to cardiovascular function [27][28][29][30][31].…”

Section: Discussionmentioning

confidence: 99%

Genetic-Based Hypertension Subtype Identification Using Informative SNPs

Jiang

Shah

et al. 2020

Genes

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In this work, we proposed a process to select informative genetic variants for identifying clinically meaningful subtypes of hypertensive patients. We studied 575 African American (AA) and 612 Caucasian hypertensive participants enrolled in the Hypertension Genetic Epidemiology Network (HyperGEN) study and analyzed each race-based group separately. All study participants underwent GWAS (Genome-Wide Association Studies) and echocardiography. We applied a variety of statistical methods and filtering criteria, including generalized linear models, F statistics, burden tests, deleterious variant filtering, and others to select the most informative hypertension-related genetic variants. We performed an unsupervised learning algorithm non-negative matrix factorization (NMF) to identify hypertension subtypes with similar genetic characteristics. Kruskal–Wallis tests were used to demonstrate the clinical meaningfulness of genetic-based hypertension subtypes. Two subgroups were identified for both African American and Caucasian HyperGEN participants. In both AAs and Caucasians, indices of cardiac mechanics differed significantly by hypertension subtypes. African Americans tend to have more genetic variants compared to Caucasians; therefore, using genetic information to distinguish the disease subtypes for this group of people is relatively challenging, but we were able to identify two subtypes whose cardiac mechanics have statistically different distributions using the proposed process. The research gives a promising direction in using statistical methods to select genetic information and identify subgroups of diseases, which may inform the development and trial of novel targeted therapies.

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

Cited by 8 publications

References 47 publications

Rare recurrent copy number variations in metabotropic glutamate receptor interacting genes in children with neurodevelopmental disorders

Rare recurrent copy number variations in metabotropic glutamate receptor interacting genes in children with neurodevelopmental disorders

Genomic Disorders in CKD across the Lifespan

Genetic-Based Hypertension Subtype Identification Using Informative SNPs

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