Epigenetic changes in myelofibrosis:Distinct methylation changes in the myeloid compartments and in cases with <i>ASXL1</i> mutations

Abstract This is the first study to compare genome-wide DNA methylation profiles of sorted blood cells from myelofibrosis (MF) patients and healthy controls. We found that differentially methylated CpG sites located to genes involved in ‘cancer’ and ‘embryonic development’ in MF CD34+ cells, in ‘inflammatory disease’ in MF mononuclear cells, and in ‘immunological diseases’ in MF granulocytes. Only few differentially methylated CpG sites were common among the three cell populations. Mutations in the epigenetic regulators ASXL1 (47%) and TET2 (20%) were not associated with a specific DNA methylation pattern using an unsupervised approach. However, in a supervised analysis of ASXL1 mutated versus wild-type cases, differentially methylated CpG sites were enriched in regions marked by histone H3K4me1, histone H3K27me3, and the bivalent histone mark H3K27me3 + H3K4me3 in human CD34+ cells. Hypermethylation of selected CpG sites was confirmed in a separate validation cohort of 30 MF patients by pyrosequencing. Altogether, we show that individual MF cell populations have distinct differentially methylated genes relative to their normal counterparts, which likely contribute to the phenotypic characteristics of MF. Furthermore, differentially methylated CpG sites in ASXL1 mutated MF cases are found in regulatory regions that could be associated with aberrant gene expression of ASXL1 target genes

A Highly Sensitive Quantitative Real-Time PCR Assay for Determination of Mutant JAK2 Exon 12 Allele Burden

Mutations in the Janus kinase 2 (JAK2) gene have become an important identifier for the Philadelphia-chromosome negative chronic myeloproliferative neoplasms. In contrast to the JAK2V617F mutation, the large number of JAK2 exon 12 mutations has challenged the development of quantitative assays. We present a highly sensitive real-time quantitative PCR assay for determination of the mutant allele burden of JAK2 exon 12 mutations. In combination with high resolution melting analysis and sequencing the assay identified six patients carrying previously described JAK2 exon 12 mutations and one novel mutation. Two patients were homozygous with a high mutant allele burden, whereas one of the heterozygous patients had a very low mutant allele burden. The allele burden in the peripheral blood resembled that of the bone marrow, except for the patient with low allele burden. Myeloid and lymphoid cell populations were isolated by cell sorting and quantitative PCR revealed similar mutant allele burdens in CD16+ granulocytes and peripheral blood. The mutations were also detected in B-lymphocytes in half of the patients at a low allele burden. In conclusion, our highly sensitive assay provides an important tool for quantitative monitoring of the mutant allele burden and accordingly also for determining the impact of treatment with interferon-α-2, shown to induce molecular remission in JAK2V617F-positive patients, which may be a future treatment option for JAK2 exon 12-positive patients as well

Exploration of Shared Genetic Architecture Between Subcortical Brain Volumes and Anorexia Nervosa

In MRI scans of patients with anorexia nervosa (AN), reductions in brain volume are often apparent. However, it is unknown whether such brain abnormalities are influenced by genetic determinants that partially overlap with those underlying AN. Here, we used a battery of methods (LD score regression, genetic risk scores, sign test, SNP effect concordance analysis, and Mendelian randomization) to investigate the genetic covariation between subcortical brain volumes and risk for AN based on summary measures retrieved from genome-wide association studies of regional brain volumes (ENIGMA consortium, n = 13,170) and genetic risk for AN (PGC-ED consortium, n = 14,477). Genetic correlations ranged from − 0.10 to 0.23 (all p > 0.05). There were some signs of an inverse concordance between greater thalamus volume and risk for AN (permuted p = 0.009, 95% CI: [0.005, 0.017]). A genetic variant in the vicinity of ZW10, a gene involved in cell division, and neurotransmitter and immune system relevant genes, in particular DRD2, was significantly associated with AN only after conditioning on its association with caudate volume (pFDR = 0.025). Another genetic variant linked to LRRC4C, important in axonal and synaptic development, reached significance after conditioning on hippocampal volume (pFDR = 0.021). In this comprehensive set of analyses and based on the largest available sample sizes to date, there was weak evidence for associations between risk for AN and risk for abnormal subcortical brain volumes at a global level (that is, common variant genetic architecture), but suggestive evidence for effects of single genetic markers. Highly powered multimodal brain- and disorder-related genome-wide studies are needed to further dissect the shared genetic influences on brain structure and risk for AN

Amplification plots of dilution series and standard curve of qPCR assay.

<p>A: Representative amplification plots of plasmid containing <i>JAK2</i> exon 12 mutation diluted into wildtype genomic DNA detected by the mutation specific assay. The ten fold dilution series starting at 15,000 copies is continued as two-fold dilutions after 15 copies down to 1.9 copies as indicated. B: Representative standard curve for the mutation and wildtype assays producing correlation coefficients >0.990. The average slope of the standard curves was −3.4.</p

Reproducibility of mutant allele burden determination by the qPCR assays.

<p>Histogram plots showing reproducibility of percentage mutant allele burden in six separate qPCR runs. The mutant allele burden was determined for 11 different DNA samples from four different patients as indicated. The <i>JAK2</i> exon 12 mutations include K539L (PV6), V536-I546dup11 (PV4), and N542-E543del (PV1 and PV2) in high, intermediate and low levels of mutant allele burden. The data is presented as percentage mean values ± standard deviation (SD).</p

Primer and probe sequences for <i>JAK2</i> exon 12.

<p>Primers used for qPCR screening and quantitative determination consisting of a common forward primer and probe in addition to a mutation specific reverse primer. The primers listed for quantitative determination were only used exclusively for determination of mutant allele burden. Lowercase letters in sequences indicate intended mismatches.</p

Identification of <i>JAK2</i> exon 12 mutations.

<p>A: Sequence of F537-I540delinsLV mutation of PV4 revealing a 10 base-pair deletion and a four base-pair insertion. B: Difference plot of high resolution melting (HRM) analysis detecting N542-E543del, F537-I540delinsLV and K539L <i>JAK2</i> exon 12 mutations in PV1, PV3, PV4, PV5 and PV6. C: Phase-contrast microphotograph showing Epo-independent growth of endogenous erythroid colonies (EEC) at day 14 of culture. Scalebar: 200 µm. HRM, high resolution melting.</p

Mutant <i>JAK2</i> exon 12 allele burden in bone marrow and peripheral blood cell lineages.

<p>Histogram plot displaying the <i>JAK2</i> exon 12 mutation burden in bone marrow, peripheral blood, CD16⁺ granulocytes, CD14⁺ monocytes, CD3⁺ T-lymphocytes, and CD19⁺ B-lymphocytes in patients PV1-PV6. PV2 had very low level of <i>JAK2</i> exon 12 mutant allele burden except for the bone marrow sample. PV1-PV3 and PV5 appeared to be heterozygous, whereas PV4 and PV6 were homozygous. Note that DNA from bone marrow samples could not be obtained from patients PV5 and PV6. BM, bone marrow and PB, peripheral blood.</p