. 2023 Oct 6;17(1):92.

doi: 10.1186/s40246-023-00540-1.

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

Julia S Mouat^{1

2

3

4}, Shaobo Li⁵, Swe Swe Myint⁵, Benjamin I Laufer^{1

2

3

4}, Philip J Lupo⁶, Jeremy M Schraw⁶, John P Woodhouse⁶, Adam J de Smith^#⁵, Janine M LaSalle^#^{7

8

9

10}

Affiliations

¹ Department of Medical Microbiology and Immunology, School of Medicine, University of California, Davis, CA, USA.
² Perinatal Origins of Disparities Center, University of California, Davis, CA, USA.
³ Genome Center, University of California, Davis, CA, USA.
⁴ MIND Institute, University of California, Davis, CA, USA.
⁵ Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
⁶ Division of Hematology-Oncology, Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA.
⁷ Department of Medical Microbiology and Immunology, School of Medicine, University of California, Davis, CA, USA. jmlasalle@ucdavis.edu.
⁸ Perinatal Origins of Disparities Center, University of California, Davis, CA, USA. jmlasalle@ucdavis.edu.
⁹ Genome Center, University of California, Davis, CA, USA. jmlasalle@ucdavis.edu.
¹⁰ MIND Institute, University of California, Davis, CA, USA. jmlasalle@ucdavis.edu.

^# Contributed equally.

PMID: 37803336
PMCID: PMC10559462
DOI: 10.1186/s40246-023-00540-1

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

Julia S Mouat et al. Hum Genomics. 2023.

. 2023 Oct 6;17(1):92.

doi: 10.1186/s40246-023-00540-1.

Authors

Affiliations

¹ Department of Medical Microbiology and Immunology, School of Medicine, University of California, Davis, CA, USA.
² Perinatal Origins of Disparities Center, University of California, Davis, CA, USA.
³ Genome Center, University of California, Davis, CA, USA.
⁴ MIND Institute, University of California, Davis, CA, USA.
⁵ Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
⁶ Division of Hematology-Oncology, Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA.
⁷ Department of Medical Microbiology and Immunology, School of Medicine, University of California, Davis, CA, USA. jmlasalle@ucdavis.edu.
⁸ Perinatal Origins of Disparities Center, University of California, Davis, CA, USA. jmlasalle@ucdavis.edu.
⁹ Genome Center, University of California, Davis, CA, USA. jmlasalle@ucdavis.edu.
¹⁰ MIND Institute, University of California, Davis, CA, USA. jmlasalle@ucdavis.edu.

^# Contributed equally.

PMID: 37803336
PMCID: PMC10559462
DOI: 10.1186/s40246-023-00540-1

Abstract

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.

Keywords: Congenital heart defect; DNA methylation; Differentially methylated regions; Down syndrome; Epigenetics; Epigenome-wide association study; Hypomethylation; Newborn dried blood spot; Whole-genome bisulfite sequencing; nRBC.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

**Fig. 1**
Global hypomethylation in DS-CHD males versus DS non-CHD males is driven by samples with high nRBC proportions. Density plot of average percent smoothed methylation in DS-CHD (Yes: blue) and DS non-CHD (No: red) in A females (note that red and blue lines are overlapping) and B males. Percent global methylation correlated with nRBC proportion in C females (Pearson’s r = − 0.93, p = 2.16E−24) and D males (Pearson’s r = − 0.84, p = 2.13E−9)

**Fig. 2**
DMR profiles of CHD versus non-CHD in Sex Combined, Females Only, and Males Only comparisons within DS. A Heatmaps of nominally significant (p < 0.05) DMRs from DS-CHD versus DS non-CHD samples in Sex Combined, Females Only, and Males Only comparisons. All heatmaps show hierarchical clustering of Z-scores, which are the number of standard deviations from the mean of non-adjusted percent smoothed individual methylation values for each DMR. B PCA analysis using the smoothed methylation values of all DMRs from the Sex Combined and Females Only comparisons and the 1000 most significant DMRs in the Males Only comparison. C Hierarchical clustering heatmap of the machine learning feature selection analysis of the consensus DMRs from the Males Only comparison

**Fig. 3**
Overlapping CHD DMRs across Sex Combined, Female Only, and Male Only comparisons within DS. A The percent of DMRs which were hypermethylated versus hypomethylated in each of the three comparisons. B Venn diagram reflecting the numbers of unique and overlapping DMR genomic coordinates across the three comparisons. C DS-CHD DMRs which overlap in two or more comparisons mapped to genes. Red indicates hypermethylation in CHD compared to non-CHD, while blue represents hypomethylation, with stronger shades representing a greater percent methylation difference. Gray is used when a DMR was not called for that comparison. Black dots indicate methylation in the same direction in the discovery and replication datasets [10 non-CHD (2 female, 8 male) and 11 CHD (6 female, 5 male)], while white dots indicate methylation in the opposite direction in the two datasets. No dot means that the DMR genomic coordinates were not covered in the replication dataset

**Fig. 4**
Annotation enrichments of CHD DMRs. A Genic and B CpG enrichments of all significant (p < 0.05) DMRs from Sex Combined, Females Only, and Males Only comparisons. DMRs were compared to background regions for each comparison, and significance was determined by the Fisher’s test and FDR correction. * = q < 0.05

**Fig. 5**
Gene ontology enrichments. Bar plot of the fifteen most significant GO enrichments for biological processes in DS-CHD versus DS non-CHD DMRs from the Sex Combined comparison

**Fig. 6**
Comparison of DS-CHD DMRs with DS versus TD samples. A Percent of DS-CHD DMRs and background regions that were significantly differentially methylated in DS versus TD samples. Z test for two population proportions, Sex Combined (z = 1.7343, two-tailed p = 0.08364), Females Only (z = 1.93, two-tailed p = 0.0536), Males Only (z = 1.8808, two-tailed p = 0.0601). + = p < 0.1. B Percent of DS-CHD DMRs that were methylated in same direction in DS versus TD as in DS-CHD versus DS non-CHD. Z test for two populations proportions, Sex Combined (z = − 0.4274, two-tailed p = 0.6672), Females Only (z = − 0.8936, two-tailed p = 0.37346), Males Only (z = 6.5357, two-tailed p < 0.00001). **** = p < 0.00001. C Heatmap showing DS-CHD DMRs that were significant (q < 0.05) in DS versus TD samples mapped to genes. Red indicates hypermethylation in CHD compared to non-CHD, while blue represents hypomethylation, with stronger shades representing a greater percent methylation difference and gray meaning that that DMR was not significant for that comparison. Black dots indicate that methylation is in the same direction for DS versus TD as DS-CHD versus DS non-CHD, while white dots indicate methylation is in the opposite direction

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Update of

Epigenomic signature of major congenital heart defects in newborns with Down syndrome.
Mouat JS, Li S, Myint SS, Laufer BI, Lupo PJ, Schraw JM, Woodhouse JP, de Smith AJ, LaSalle JM. Mouat JS, et al. medRxiv [Preprint]. 2023 May 5:2023.05.02.23289417. doi: 10.1101/2023.05.02.23289417. medRxiv. 2023. Update in: Hum Genomics. 2023 Oct 6;17(1):92. doi: 10.1186/s40246-023-00540-1. PMID: 37205408 Free PMC article. Updated. Preprint.

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

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

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