Myeloid Leukemia

Submicroscopic mutation profiling of 54 genes frequently mutated in myeloid leukemias was done by the Illuminas TruSight Myeloid Gene Panel and sequenced using the MiSeq system and reagent kit v3 (all from Illumina, San Diego, CA, USA) (Additional file 1: Table S4). Amplicon sequencing library was prepared from 50 ng DNA according to the manufacturer’s instructions with the exception of normalization being done manually. 8–16 samples were sequenced each time and the total DNA input on the flow cell was 15 picomolar. Secondary analysis was performed using MiSeqReporter version 2.4.60.8 (Illumina) mapping to the human genome reference hg19. Sequence alignment of selected variants was manually examined with the Integrative Genomics Viewer (IGV) [27 (link)]. Annotation was done by snpSIFT og snpEFF v 4.1. As no matching normal DNA was available variants with >1% minor allele frequency in the 1000 genomes data were presumed to be germline and removed from further interpretations. Synonymous substitutions, intronic variants not in the splice site and variant interpreted as benign or most likely benign are not included. The variant allele frequency (VAF) was calculated for each mutation as number of variant reads divided by total reads. Cut-off for reported variants for VAF was 8% and read depth 100. Only variants interpreted as pathogenic, probably pathogenic and variants of unknown significance are reported. The nomenclature is according to Human Genome Structural Variation consortium.
Fragment analysis of FLT3 exon 14–15 and NPM1 exon 12 were done as described in [28 (link)] and CEBPA mutation analysis as described previously [28 (link)].

Descriptive statistics are reported as count (percent) for categorical variables and as median (interquartile range [IQR]) for continuous variables. Demographics and baseline variables are also reported by IgG antibody status before/after receiving 3V dose.
To assess the association between each individual characteristics and seroconversion status, patients were placed into two groups based on IgG antibody status pre and post the 3V dose, (−/+) and (−/−). Categorical variables were compared using a Chi-squared test or a Fisher’s exact test, as appropriate, and continuous variables using a Mann–Whitney U-test. P-value less than 0.05 were used as an indicator of statistical significance. For categorical variables with more than two levels, P-values were calculated for both the global and the pairwise comparisons. Odds ratios (OR) are displayed as measures of association for all categorical variables. Logistic regressions were used to measure the association between HM condition and seroconversion. A multivariable logistic regression model was run to assess significant associations fitting seroconversion on cancer diagnosis adjusting for age, sex, and days between dose 2 and dose 3. Myeloid leukemia and Hodgkin lymphoma were eliminated from the model due to small cell size (Table 4). Achieving seroconversion (−/+) was used as the reference outcome. Male, White, non-Hispanic/Latino, receiving Pfizer-BioNTech as the 3V dose, having previous COVID-19 infection, and NHL were used as reference groups for the respective variables for the OR calculation [3 (link)]. NHL was chosen as the reference group because it is the most common condition in our dataset. Data management and analysis were performed by the study team using R 4.1.1 (R Core Team, 2021).