Analysis of Copy Number Variants on Chromosome 21 in Down Syndrome-Associated Congenital Heart Defects

Genome-Wide Association Studies of Down Syndrome Associated Congenital Heart Defects Suggests a Genetically Heterogeneous Risk for CHD in DS

Congenital heart defects (CHDs) are the most common structural birth defect and are present in 40%-50% of children born with Down syndrome (DS). To characterize the genetic architecture of DS-associated CHD, we sequenced genomes of a multiethnic group of children with DS and a CHD (n = 886: atrioventricular septal defects (AVSD), n = 438; atrial septal defects (ASD), n = 122; ventricular septal defects (VSD), n = 170; other types of CHD, n = 156) and DS with a structurally normal heart (DS + NH, n = 572). We performed four genome-wide association study (GWAS) for common variants (MAF > 0.05) comparing DS with CHD, stratified by CHD-subtype, to DS + NH controls. Although no SNP achieved genome-wide significance, multiple loci in each analysis achieved suggestive significance (p < 2 × 10-6). Of these, the 1p35.1 locus (near RBBP4) was specifically associated with ASD risk, and the 5q35.2 locus (near MSX2) was associated with any type of CHD. Each of the suggestive loci contained one or more plausible candidate genes expressed in the developing heart. While no SNP replicated (p < 2 × 10-6) in an independent cohort of DS + CHD (DS + CHD: n = 229; DS + NH: n = 197), most SNPs that were suggestive in our GWASs remained suggestive when meta-analyzed with the GWASs from the replication cohort. These results build on previous work to identify genetic modifiers of DS-associated CHD.

Genome-wide association studies of Down syndrome associated congenital heart defects

Congenital heart defects (CHDs) are the most common structural birth defect and are present in 40-50% of children born with Down syndrome (DS). To characterize the genetic architecture of DS-associated CHD, we sequenced genomes of a multiethnic group of children with DS and a CHD (n=886: atrioventricular septal defects (AVSD), n=438; atrial septal defects (ASD), n=122; ventricular septal defects (VSD), n=170; other types of CHD, n=156) and DS with a structurally normal heart (DS+NH, n=572). We performed four GWAS for common variants (MAF>0.05) comparing DS with CHD, stratified by CHD-subtype, to DS+NH controls. Although no SNP achieved genome-wide significance, multiple loci in each analysis achieved suggestive significance (p<2×10-6). Of these, the 1p35.1 locus (near RBBP4) was specifically associated with ASD risk and the 5q35.2 locus (near MSX2) was associated with any type of CHD. Each of the suggestive loci contained one or more plausible candidate genes expressed in the developing heart. While no SNP replicated (p<2×10-6) in an independent cohort of DS+CHD (DS+CHD: n=229; DS+NH: n=197), most SNPs that were suggestive in our GWASs remained suggestive when meta-analyzed with the GWASs from the replication cohort. These results build on previous work to identify genetic modifiers of DS-associated CHD.

Human Genetics of Atrioventricular Septal Defect

Atrioventricular septal defects (AVSD), also known as a common atrioventricular canal (CAVC), are clinically severe heart malformations that affect about 1 out of every 2100 live births. AVSD makes up about 5% of all congenital heart defects. AVSD is associated with cytogenetic disorders such as Down syndrome and numerous other rare genetic syndromes, but also occurs as a simplex trait. Studies in mouse models have identified over 100 genetic mutations that have the potential to cause an AVSD. However, studies in humans indicate that AVSD is genetically heterogeneous, and that the cause in humans is very rarely a single-gene defect. Familial cases do occur albeit rarely, usually with autosomal dominant inheritance and variable expression. In addition, the frequent occurrence of AVSD in some syndromes with known genetic causes such as heterotaxy syndrome points to additional genes/pathways that increase AVSD risk. Accordingly, while the genetic underpinnings for most AVSD remain unknown, there have been advances in identifying genetic risk factors for AVSD in both syndromic and nonsyndromic cases. This chapter summarizes the current knowledge of the genetic basis for AVSD.

Epigenomic signature of major congenital heart defects in newborns with Down syndrome

BACKGROUND

Congenital heart defects (CHDs) affect approximately half of individuals with Down syndrome (DS), but the molecular reasons for incomplete penetrance are unknown. Previous studies have largely focused on identifying genetic risk factors associated with CHDs in individuals with DS, but comprehensive studies of the contribution of epigenetic marks are lacking. We aimed to identify and characterize DNA methylation differences from newborn dried blood spots (NDBS) of DS individuals with major CHDs compared to DS individuals without CHDs.

METHODS

We used the Illumina EPIC array and whole-genome bisulfite sequencing (WGBS) to quantitate DNA methylation for 86 NDBS samples from the California Biobank Program: (1) 45 DS-CHD (27 female, 18 male) and (2) 41 DS non-CHD (27 female, 14 male). We analyzed global CpG methylation and identified differentially methylated regions (DMRs) in DS-CHD versus DS non-CHD comparisons (both sex-combined and sex-stratified) corrected for sex, age of blood collection, and cell-type proportions. CHD DMRs were analyzed for enrichment in CpG and genic contexts, chromatin states, and histone modifications by genomic coordinates and for gene ontology enrichment by gene mapping. DMRs were also tested in a replication dataset and compared to methylation levels in DS versus typical development (TD) WGBS NDBS samples.

RESULTS

We found global CpG hypomethylation in DS-CHD males compared to DS non-CHD males, which was attributable to elevated levels of nucleated red blood cells and not seen in females. At a regional level, we identified 58, 341, and 3938 CHD-associated DMRs in the Sex Combined, Females Only, and Males Only groups, respectively, and used machine learning algorithms to select 19 Males Only loci that could distinguish CHD from non-CHD. DMRs in all comparisons were enriched for gene exons, CpG islands, and bivalent chromatin and mapped to genes enriched for terms related to cardiac and immune functions. Lastly, a greater percentage of CHD-associated DMRs than background regions were differentially methylated in DS versus TD samples.

CONCLUSIONS

A sex-specific signature of DNA methylation was detected in NDBS of DS-CHD compared to DS non-CHD individuals. This supports the hypothesis that epigenetics can reflect the variability of phenotypes in DS, particularly CHDs.

New Molecular and Organelle Alterations Linked to Down Syndrome Heart Disease

Down syndrome (DS) is a genetic disorder caused by a trisomy of the human chromosome 21 (Hsa21). Overexpression of Hsa21 genes that encode proteins and non-coding RNAs (ncRNAs) can disrupt several cellular functions and biological processes, especially in the heart. Congenital heart defects (CHDs) are present in 45–50% of individuals with DS. Here, we describe the genetic background of this condition (Hsa21 and non-Hsa21 genes), including the role of ncRNAs, and the relevance of these new players in the study of the pathophysiology of DS heart diseases. Additionally, we discuss several distinct pathways in cardiomyocytes which help maintain a functional heart, but that might trigger hypertrophy and oxidative stress when altered. Moreover, we highlight the importance of investigating how mitochondrial and lysosomal dysfunction could eventually contribute to understanding impaired heart function and development in subjects with the Hsa21 trisomy. Altogether, this review focuses on the newest insights about the gene expression, molecular pathways, and organelle alterations involved in the cardiac phenotype of DS.

Cardiac Defects and Genetic Syndromes: Old Uncertainties and New Insights

Recent advances in understanding the genetic causes and anatomic subtypes of cardiac defects have revealed new links between genetic etiology, pathogenetic mechanisms and cardiac phenotypes. Although the same genetic background can result in different cardiac phenotypes, and similar phenotypes can be caused by different genetic causes, researchers’ effort to identify specific genotype–phenotype correlations remains crucial. In this review, we report on recent advances in the cardiac pathogenesis of three genetic diseases: Down syndrome, del22q11.2 deletion syndrome and Ellis–Van Creveld syndrome. In these conditions, the frequent and specific association with congenital heart defects and the recent characterization of the underlying molecular events contributing to pathogenesis provide significant examples of genotype–phenotype correlations. Defining these correlations is expected to improve diagnosis and patient stratification, and it has relevant implications for patient management and potential therapeutic options.

Importance of determining variations in the number of copies in newborns with autosomal aneuploidies

Introducción.

Las aneuploidías son trastornos genéticos frecuentes en la práctica clínica; sin embargo, se conoce poco sobre las otras variantes genéticas que modifican el fenotipo final.

Objetivo.

Determinar las variantes en el número de copias y las regiones con pérdida de heterocigosidad autosómica mayor de 0,5 % o de regiones mayores de 10 Mb en neonatos con aneuploidías autosómicas.

Materiales y métodos.

Se hizo el análisis cromosómico por micromatrices a los neonatos con aneuploidías autosómicas (n=7), trisomía 21 (n=5) y trisomía 18 (n=2) evaluados en los hospitales Antonio Lorena y Regional de Cusco, Perú, en el 2018.

Resultados.

En dos neonatos se encontraron variantes en el número de copias, patogénicas o probablemente patogénicas, en regiones diferentes al cromosoma 21 o al 18. Además, se observaron dos variantes del número de copias con más de 500 kpb de patogenia desconocida.

Conclusiones.

Si bien el número de pacientes era muy reducido, es importante resaltar que se encontraron otras variantes en el número de copias que se han descrito asociadas con trastornos del neurodesarrollo, varias anomalías congénitas, hipoacusia y talla baja o alta, entre otras, lo que probablemente influye negativamente en el fenotipo de este grupo de pacientes.

Opportunities, barriers, and recommendations in down syndrome research

BACKGROUND

Recent advances in medical care have increased life expectancy and improved the quality of life for people with Down syndrome (DS). These advances are the result of both pre-clinical and clinical research but much about DS is still poorly understood. In 2020, the NIH announced their plan to update their DS research plan and requested input from the scientific and advocacy community.

OBJECTIVE

The National Down Syndrome Society (NDSS) and the LuMind IDSC Foundation worked together with scientific and medical experts to develop recommendations for the NIH research plan.

METHODS

NDSS and LuMind IDSC assembled over 50 experts across multiple disciplines and organized them in eleven working groups focused on specific issues for people with DS.

RESULTS

This review article summarizes the research gaps and recommendations that have the potential to improve the health and quality of life for people with DS within the next decade.

CONCLUSIONS

This review highlights many of the scientific gaps that exist in DS research. Based on these gaps, a multidisciplinary group of DS experts has made recommendations to advance DS research. This paper may also aid policymakers and the DS community to build a comprehensive national DS research strategy.

Identifying genetic factors that contribute to the increased risk of congenital heart defects in infants with Down syndrome

Atrioventricular septal defects (AVSD) are a severe congenital heart defect present in individuals with Down syndrome (DS) at a > 2000-fold increased prevalence compared to the general population. This study aimed to identify risk-associated genes and pathways and to examine a potential polygenic contribution to AVSD in DS. We analyzed a total cohort of 702 individuals with DS with or without AVSD, with genomic data from whole exome sequencing, whole genome sequencing, and/or array-based imputation. We utilized sequence kernel association testing and polygenic risk score (PRS) methods to examine rare and common variants. Our findings suggest that the Notch pathway, particularly NOTCH4, as well as genes involved in the ciliome including CEP290 may play a role in AVSD in DS. These pathways have also been implicated in DS-associated AVSD in prior studies. A polygenic component for AVSD in DS has not been examined previously. Using weights based on the largest genome-wide association study of congenital heart defects available (2594 cases and 5159 controls; all general population samples), we found PRS to be associated with AVSD with odds ratios ranging from 1.2 to 1.3 per standard deviation increase in PRS and corresponding liability r2 values of approximately 1%, suggesting at least a small polygenic contribution to DS-associated AVSD. Future studies with larger sample sizes will improve identification and quantification of genetic contributions to AVSD in DS.

Influence of allelic differences in Down syndrome

Both trisomic and non-trisomic genes may affect the incidence and severity of phenotypes associated with Down syndrome (DS). The importance of extra (trisomic) genetic material is emphasized in DS, with less emphasis to the allelic composition of candidate trisomic genes in defining the trisomic gene-phenotype relationship in DS. Allelic differences in non-trisomic genes have been shown to be important moderators of cardiac, leukemia, and developmental phenotypes associated with DS. Trisomic mouse models provide an in vivo genetic platform for examining the gene-phenotype relationship, including the influence of allelic variants, on DS-like phenotypes. DS mouse models have differing trisomic genetic makeup, and optimal development, viability and translational value of these mouse models may require a non-inbred genetic background with heterogeneity at many loci. Additionally, understanding the contribution of specific genes or regions to DS phenotypes often requires the utilization of genetically manipulated mice that may be established on a different inbred background than the trisomic mice. The impact of allelic differences of trisomic and background genes in human and model systems may offer insight into the variability in occurrence and severity of trisomic phenotypes.

Molecular mechanisms of congenital heart disease in down syndrome

Down syndrome (DS), as a typical genomic aneuploidy, is a common cause of various birth defects, among which is congenital heart disease (CHD). 40-60% neonates with DS have some kinds of CHD. However, the molecular pathogenic mechanisms of DS associated CHD are still not fully understood. This review summarizes available studies on DS associated CHD from seven aspects so as to provide a crucial and updated overview of what we known so far in this domain.

Next-generation sequencing identified genetic variations in families with fetal non-syndromic atrioventricular septal defects

Atrioventricular septal defects (AVSDs) account for approximately 5% of all congenital heart disease (CHD). About half of AVSDs are diagnosed in cases with trisomy 21 (Down's syndrome, DS). However, many AVSDs occur sporadically and manifest as non-syndromic. The pathogenesis is complex and has not yet been fully elucidated. In the present study, we applied two advanced applications of next-generation sequencing (NGS) to explore the genetic variations in families with fetal non-syndromic AVSDs. Our study was mainly divided into two steps: (1) low-pass whole-genome sequencing (WGS) was used to detect the genome-wide copy number variations (CNVs) for included subjects; (2) whole-exome sequencing (WES) was used to detect the gene mutations for the subjects without AVSD-associated CNVs. A total of 17 heterozygous de novo CNVs and 19 heterozygous de novo gene mutations were selected, and 15 candidate genes were involved in these variations. Among these heterozygous de novo variations, most have potential pathogenicity for AVSDs, but the others require further investigation to confirm their pathogenicity. Our study not only shows the genetic diversity and the etiological complexity of AVSDs but also shows the rationality and practicability of this sequential genetic detection and analysis strategy.

Identifying Patients with Atrioventricular Septal Defect in Down Syndrome Populations by Using Self-Normalizing Neural Networks and Feature Selection

Atrioventricular septal defect (AVSD) is a clinically significant subtype of congenital heart disease (CHD) that severely influences the health of babies during birth and is associated with Down syndrome (DS). Thus, exploring the differences in functional genes in DS samples with and without AVSD is a critical way to investigate the complex association between AVSD and DS. In this study, we present a computational method to distinguish DS patients with AVSD from those without AVSD using the newly proposed self-normalizing neural network (SNN). First, each patient was encoded by using the copy number of probes on chromosome 21. The encoded features were ranked by the reliable Monte Carlo feature selection (MCFS) method to obtain a ranked feature list. Based on this feature list, we used a two-stage incremental feature selection to construct two series of feature subsets and applied SNNs to build classifiers to identify optimal features. Results show that 2737 optimal features were obtained, and the corresponding optimal SNN classifier constructed on optimal features yielded a Matthew’s correlation coefficient (MCC) value of 0.748. For comparison, random forest was also used to build classifiers and uncover optimal features. This method received an optimal MCC value of 0.582 when top 132 features were utilized. Finally, we analyzed some key features derived from the optimal features in SNNs found in literature support to further reveal their essential roles.