Fig. 2: Heatmap and unsupervised hierarchical clustering of the top 2000 most variable CpGs genome-wide in Down syndrome (DS) and non-DS newborns, and by GATA1 mutation status.

These plots were generated using genome-wide DNA methylation data excluding chromosomes X, Y, and 21, and with β values converted to M values, using the “ComplexHeatmap” R package. Only the top 2000 CpGs with the greatest mean absolute deviation are displayed. a Hierarchical clustering and heatmap of 196 DS and 439 non-DS newborns, in relation to subject sex and deconvoluted blood cell proportions of B cells, CD4⁺ T cells, CD8⁺ T cells, granulocytes, monocytes, natural killer (NK) cells, and nucleated red blood cells (nRBCs). The first separation in hierarchical clustering represented DS (teal) versus non-DS (red) newborns. Two DS newborns clustered with the non-DS newborns, and were the same as those that clustered similarly in the t-SNE plot in Fig. 1. The DS newborns clustered into two main subgroups, those with high nRBC proportions and those with low nRBC proportions. b Hierarchical clustering and heatmap of 184 DS newborns, including 30 found to harbor somatic GATA1 mutations via targeted sequencing, and 154 found to be GATA1 mutation wildtype. DS newborns with GATA1 mutations are represented by black bars, and the variant allele frequency (VAF) range of mutations shown in the row below. The first split appeared to separate DS newborns with high nRBC proportions from those with low nRBC proportions, whereas the second split was largely driven by subjects with GATA1 mutations with high VAF. DS newborns with GATA1 mutations with high VAF clustered together and tended to have high nRBC proportions; however, a proportion of GATA1 wild-type newborns were also found to have high nRBC proportions, and these also clustered separately.