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. 2021 Jun 3;107(4):877–886. doi: 10.3324/haematol.2021.278477

Figure 1.

Figure 1.

Identification of methylation changes that independently predict short time to treatment. (A) Test of the association between the methylation level (as bvalue) with the IGHV mutation load (as percentage identity to germline sequence) using a linear regression model for 114 patients and 671 684 CpG sites. Two scatterplots display a non-significant association for cg17698174 (left) and a significant association for cg08090385 (right) between the b-values on the y-axis and IGHV mutation load on the x-axis. A total of 4 518 CpG showed significant association between b-values and IGHV mutation load using a significance threshold of P<10-8. (B) Selection of CpG with qualitative methylation changes. The boxplots display the distribution of methylation at cg08090385 (left) and cg00029031 (right), where each black dot represents a patient (n=114) with the b-value for the specific CpG indicated on the y-axis. The box displays the 25-, 50- and 75-percentiles. An interquartile range (IQR) >0.80 was defined as a qualitative methylation change (Online Supplementary Methods, Section 1), and CpG with an IQR >0.80 were selected for further analyses (n=147). (C) Univariate Cox regression analysis of the association between methylation level (as a continuous b-value) and time to treatment (TTT) in 114 patients for 147 CpG. The Manhattan plot displays the significance to predict TTT for each of the 147 CpG (dots), with the -log10(P value) from Cox regression analysis on the y-axis against the chromosomal location of the CpG on the x-axis. A total of 44 CpG (red dots) showed a significance level below the threshold of P<10-7. (D) Results from the multivariable Cox regression of 44 CpG to identify CpG sites that independently predict TTT performed using backward elimination. A final set of nine CpG sites was identified with a statistical significance of P<0.05.