Literature DB >> 26114957

Profound parental bias associated with chromosome 14 acquired uniparental disomy indicates targeting of an imprinted locus.

A Chase1,2, W Leung1,2, W Tapper2, A V Jones1,2, L Knoops3, C Rasi4, L A Forsberg4, P Guglielmelli5, K Zoi6, V Hall1,2, L Chiecchio1, L Eder-Azanza1, C Bryant1,2, L Lannfelt7, L Docherty1,2, H E White1,2, J Score1,2, D J G Mackay1,2, A M Vannucchi5, J P Dumanski4, N C P Cross1,2.   

Abstract

Acquired uniparental disomy (aUPD) is a common finding in myeloid malignancies and typically acts to convert a somatically acquired heterozygous mutation to homozygosity. We sought to identify the target of chromosome 14 aUPD (aUPD14), a recurrent abnormality in myeloid neoplasms and population cohorts of elderly individuals. We identified 29 cases with aUPD14q that defined a minimal affected region (MAR) of 11.2 Mb running from 14q32.12 to the telomere. Exome sequencing (n=7) did not identify recurrently mutated genes, but methylation-specific PCR at the imprinted MEG3-DLK1 locus located within the MAR demonstrated loss of maternal chromosome 14 and gain of paternal chromosome 14 (P<0.0001), with the degree of methylation imbalance correlating with the level of aUPD (r=0.76; P=0.0001). The absence of driver gene mutations in the exomes of three individuals with aUPD14q but no known haematological disorder suggests that aUPD14q may be sufficient to drive clonal haemopoiesis. Analysis of cases with both aUPD14q and JAK2 V617F (n=11) indicated that aUPD14q may be an early event in some cases but a late event in others. We conclude that aUPD14q is a recurrent abnormality that targets an imprinted locus and may promote clonal haemopoiesis either as an initiating event or as a secondary change.

Entities:  

Mesh:

Year:  2015        PMID: 26114957      PMCID: PMC4687469          DOI: 10.1038/leu.2015.130

Source DB:  PubMed          Journal:  Leukemia        ISSN: 0887-6924            Impact factor:   11.528


Introduction

Uniparental disomy (UPD) refers to the situation in which both copies of a chromosome pair or parts of chromosomes have originated from one parent. Constitutional UPD is associated with developmental disorders caused by the abnormal expression of imprinted genes, that is, genes that are differentially expressed depending on whether they have been maternally or paternally inherited. By contrast, somatically acquired UPD (aUPD) in cancer is a mechanism by which a pre-existing driver mutation (usually somatically acquired) is converted to homozygosity, thereby providing an additional clonal advantage. aUPD may involve whole chromosomes as a result of non-disjunction or, more commonly, whole chromosome arms or terminal segments as a consequence of mitotic recombination. aUPD cannot be detected by conventional cytogenetics but is readily apparent by the finding of somatically acquired long homozygous tracts without change in copy number by genome-wide single nucleotide polymorphism (SNP) analysis.[1] aUPD is prevalent in myeloid neoplasms: chromosomes 4q, 7q, 9p, 11q and 13q are commonly affected and target mutated TET2, EZH2, JAK2, CBL and FLT3, respectively.[1] Several other regions of recurrent aUPD have been identified for which the target is unknown, for example, chromosome 14q aUPD (aUPD14q) is seen in myeloid neoplasms[2] and is one of the most common abnormalities associated with clonal haemopoiesis in population cohorts of elderly individuals.[3, 4] Here we show an unexpected and highly significant parental bias associated with aUPD14q, implicating an imprinted locus at 14q32 as the primary target rather than a specific mutated gene.

Patients and methods

Study cohorts

Our study comprised two major groups of individuals: (i) patients diagnosed with a myeloproliferative neoplasm (MPN) or myelodysplastic (MDS)/MPN according to standard morphological, haematologic and laboratory criteria; (ii) population cohorts of elderly individuals from Sweden, specifically the Uppsala Longitudinal Study of Adult Men[5] and the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS).[6] The study was approved by the following ethics committees or review boards: the National Research Ethics Service (UK) Committee South West, the Uppsala Regional Ethical Review Board, the Ethics Committee of the Biomedical Research Foundation of the Academy of Athens, Comitato Etico, Azienda Ospedaliero-Universitaria Careggi, Firenze. Informed consent was obtained according to the Declaration of Helsinki.

Molecular analysis

Genome wide SNP profiles for MPN and MDS/MPN cases, most of which have been published previously,[2, 7] were obtained from peripheral blood or bone marrow leucocyte DNA using the Affymetrix SNP 6.0 (Affymetrix, Santa Clara, CA, USA) or Illumina Human OmniExpressExome v1.2 platforms (Illumina, San Diego, CA, USA). Peripheral blood leucocyte profiles for the Swedish population cohorts were obtained using Illumina 2.5M HumanOmni arrays (Illumina) have also been published.[8] Exome sequencing for MPN and MDS/MPN cases was performed using the Agilent SureSelect kit (Agilent Technologies, Palo Alto, CA, USA) (Human All Exon 50 Mb) and sequenced using an Illumina HiSeq 2000 (Illumina) at the Wellcome Trust Centre for Human Genetics at Oxford, UK. Exome sequencing for the Swedish cases was performed by SciLifeLab, Stockholm, Sweden. For methylation analysis, DNA was bisulphited (Zymo Research, Ervine, CA, USA) alongside four healthy controls, amplified using forward primers specific for methylated or unmethylated MEG3 or NHP2L1 with a common FAM labelled reverse primer and analysed with a 3130xl Genetic Analyser (Applied Biosystems, Foster City, CA, USA) as described.[9] Loss of heterozygosity analysis at 14q32 was performed using microsatellites D14S553, D14S267, D14S1006, D14S542, D14S292 and D14S1007, again using a 3130xl Genetic Analyser. All primer sequences are listed in Supplementary Table 1.

SNP array analysis

Array analysis was performed as described.[7, 10, 11] For each SNP the log R Ratio, a measure of normalised total signal intensity, and B Allele Frequency (BAF), a measure of normalised allelic intensity ratio, were determined using the BeadStudio (Illumina) and pennCNV[12] software for Illumina and Affymetrix arrays, respectively. Regions of aUPD were identified by BAF segmentation[10] which excluded non-informative SNPs (SNPs with BAF >0.9 or BAF <0.1 and SNPs where the absolute difference in BAF between preceding and succeeding SNPs is >0.6), mirrored BAF at 0.5 and used circular binary segmentation to identify regions with similar allelic proportions. For heterozygous SNPs, the BAF is the proportion of the total signal (A+B) accounted for by one allele (B). In a mixed population of cells, the segmented mirrored BAF value will be a combination of values of 1 and 0.5 for cells with and without aUPD, respectively. Regions of aUPD were therefore defined as a region of allelic imbalance (segmented mirrored BAF >0.56) with neutral copy number (log R ratio ~0) that extended to the telomere.[12] For samples with known JAK2 V617F levels, determined by pyrosequencing,[13] and BAF for both aUPD9p and aUPD14q aUPD, we were able to calculate both the proportion of cells with aUPD14 and the proportion of cells which were homozygous or heterozygous for JAK2 V617F. This allowed us to infer the likely order of acquisition of aUPD14 and JAK2 V617F (see Supplementary Table 2 for detailed calculations).

Sequence analysis

Analysis of exome sequencing data was as previously described.[14] On average, the targeted exome of chromosome 14 was sequenced to a depth of 179 ×, and 94.3% of the target bases were covered by at least 20 reads (Supplementary Table 3). For variants passing quality control (read depth ⩾4, alternate read depth ⩾2, phred scaled quality ⩾20, phred scaled base call accuracy ⩾10, strand bias P⩾0.0001, base quality bias P⩾1e-100, tail bias P⩾0.0001 and HWE P⩾0.0001), variant allele frequencies were used to approximate BAF and were analysed accordingly to confirm regions of aUPD. The minimally affected region identified in patient E5364 (chr14:94,245,652-qter) was interrogated in all aUPD14q exomes for rare variants that were either novel or had a minor allele frequency of ⩽1% in databases of common variation (1000 genomes, Complete Genomics, Exome Variant Server).

Results

Prevalence of aUPD14q

We analysed in house array data on cases with MPN or MDS/MPN and identified aUPD14q extending to the 14q telomere in 25 cases. Of the UK cases (n=21), 1/293 (0.3%) had MDS/MPN, 8/563 (1.6%) had JAK2 V617F negative MPN (7 CALR mutated; 1 MPL mutated) and 12/1054 (1.1%) had JAK2 V617F positive MPN, an overall prevalence similar to that identified in other studies of myeloid neoplasms (8/498; 1.6%).[2, 7, 15, 16, 17] Trisomy chromosome 14 (+14) was seen in 4/293 (1.4%) MDS/MPN cases.[2] Of the 1641 individuals ⩾70 years of age in the Swedish population-based cohorts, 4 (0.2%) had aUPD14,[8] similar to the frequency in elderly individuals reported by other larger studies of cases recruited for a variety of genome-wide association studies.[3, 4] Cases with aUPD14q or other chromosome 14 abnormalities in our study are summarised in Table 1.
Table 1

Summary of cases with chromosome 14 abnormalities

Patient identifieraUPD14q region or karyotype (hg19 co-ordinates)aUPD14q size (Mb)DisorderExomeDriver mutationsMean B-allele frequency of aUPD14q regionMethylation levela
E7173chr14: 70924501-10593040635.0ETYesSF3B1 K700E0.810.45
E5364chr14: 94245652-10541731311.2CMMLYesEZH2 exon9:c.729-2A>-0.910.49
E6459chr14: 33291583-10593040672.6PMFYesJAK2 V617F; TET2 D1242V0.730.52
PT03B08chr14:20211644-10728543787.1PMFCALR Type 20.820.28
CB44chr14:22053729-10728543785.2ETCALR Type 10.740.05
PT02B05chr14:73672831-10727405233.6ETMPL W515K0.80.25
PT02E11chr14:23582569-10722089883.6ETCALR Type 20.80.27
AN804chr14:21240673-10728543786.0PMFCALR Type 10.800.32
11_4629chr14:21209871-10728766386.1ETCALR Type 20.710.21
E6430chr14:23102969-10727405284.2ETCALR Type 10.640.12
E09853chr14:20213937-10727405287.1PVJAK2 V617F0.62−0.10
E09861chr14:20295510-10727405287.0PVJAK2 V617F0.770.19
E09895chr14:56103882-10728766351.1PVJAK2 V617F0.710.22
E09984chr14:50192257-10728766357.1ETJAK2 V617F0.790.31
H3589_11chr14:59183573-10728766348.1PVJAK2 V617F0.580.07
H10872_10chr14:24653187-10722249382.6PVJAK2 V617F0.580.12
W1212280chr14:24843620-10728766382.4PVJAK2 V617F0.570.07
H131_12chr14:92280675-10727405215.0PVJAK2 V617F0.630.07
PT1544chr14: 94238353- 10728766313.0ETCALR Type 20.69ND
PT1645chr14: 21070264- 10596510284.9ETJAK2 V617F0.89ND
PT1670chr14: 23248583- 10728766384.0ETJAK2 V617F0.79ND
PT1876chr14: 72220169- 10723196735.0ETJAK2 V617F0.89ND
G_735chr14:27349540-10734954080bPMFJAK2 V617FNA0.40
G_3358chr14:83349540-10734954024bPMFJAK2 V617FNA0.52
G_3499chr14:101250540-1073495406bPMFJAK2 V617FNA0.19
ULSAM 546chr14:24944467-10734954082.4PCYesNone detected0.690.07
ULSAM 831chr14:40334000-10734954067.0PCYesNone detected0.67ND
PIVUS 931chr14:94156220-10733119013.2PCYesJAK2 V617F; TP53 exon6:c.376-2 A>G0.77ND
PIVUS 892chr14:77435975-10734954029.9PCYesNone detected0.61ND
E4051+14aCMLYes  0.15
E6901+14CMML  −0.14
W81348346,XX,?dup(12)(p11p12),idic(14) (p11)/47,idem,+idic(14)AML  0.29
W130189147,XX,+14[20]MDS  0.12
W140710946,XX,del(5)(q13q33)[1]/58,sl,+1,+2,+del(5),+8,+9,+10,+11,+13,+14,+19,+21,+22[9]/60,sdl1,+6,add(6)(q1),+mar[2]MDS  0.11
W140948945,X,-Y[6]/46,idem,+14[8]/46,XY[6]MDS  −0.13
E7820aUPD14q by microsatellite analysisCMMLEZH2 C590F  

Abbreviations: aCML, atypical chronic myeloid leukemia; AML, acute myeloid leukemia; CMML, chronic myelomonocytic leukemia; ET, essential thrombocythemia; MDS, myelodysplastic syndrome; NA, not applicable; ND, not determined; PC, cases from Swedish elderly population-based cohorts with no haematological malignancy diagnosed at the time of sampling (PIVUS 931 was subsequently diagnosed with polycythemia vera); PMF, primary myelofibrosis; PV, polycythemia vera.

Paternal chromosome loss or gain is given by the methylated (paternal) peak height divided by the sum of methylated and unmethylated peaks, normalised to shift control values to zero. A positive value indicates methylation (paternal chromosome) gain compared with controls.

Regions of aUPD14q only defined to the nearest megabase, the minimally affected region of aUPD14q was therefore conservatively defined by case E5364 as 11.2 Mb, chr14: 94245652-qter.

Minimally affected region

The region affected by aUPD14q was variable between individuals and there was no difference between cases diagnosed with a haematological malignancy and those picked up in population-based screens (Figure 1). Since the boundary of our smallest region of aUPD14q, case G_3499, was only defined to the nearest megabase, our minimally affected region was conservatively defined by case E5364 as 11.2 Mb running from 14q32.12 to the telomere (chr14: 94,245,652-105,417,313). The minimal affected region (MAR) in previously published analyses of genome-wide association studies data was similar: 7.4 Mb (chr14: 98,962,371-qter)[4] and 6.9 Mb (chr14: 99,425,044-qter).[3] This region does not include FANCM, a variant of which was associated with aUPD14q in a single case.[18]
Figure 1

Extent of aUPD14q in the 29 cases, indicating the minimally affected region and location of DLK1-MEG3.

Exome sequencing

Initially, with the aim of identifying a recurrently mutated 14q gene, we sequenced the whole exomes of cases with aUPD14q (n=7) or +14 (n=1). We focused on the identification of novel variants in the minimal region of aUPD14q (chr14: 94,245,652-qter), thus capturing both constitutional and somatic mutations that might provide a selective advantage when reduced to homozygosity. No gene was identified with likely causative variants in more than one individual (Supplementary Table 3). In addition, no rare variants were identified in FANCM which falls outside our MAR. Although it is possible that a target gene might have been missed due to inadequate coverage or mutational complexity, we considered an alternative explanation.

Methylation bias associated with aUPD14q

Constitutional maternal UPD14q causes Temple syndrome, whereas paternal UPD14q causes Kagami–Ogata syndrome. Both are developmental conditions resulting from aberrant expression of genes in the imprinted DLK1-MEG3 domain at 14q32. DLK1-MEG3 is the only known imprinted locus on chromosome 14 and is retained in the aUPD14q MAR defined above. To test if DLK1-MEG3 might be targeted by chromosome 14 abnormalities, we determined the MEG3 methylation status of cases with aUPD14q (n=22) or +14 (n=6; Table 1). MEG3 is methylated on the paternally inherited chromosome 14 but is unmethylated when maternally inherited. An increase in methylation therefore indicates paternal aUPD14q, that is, gain of the region containing MEG3 from the paternal chromosome 14 and loss of the corresponding region from the maternal chromosome 14 (Figure 2). Samples from cases with aUPD14q showed a striking increase in methylation (mean methylation value 0.24, s.d. ±0.17) compared with healthy controls (n=24; mean methylated value 0.00, s.d. ±0.04) consistent with paternal aUPD (Figures 2a and b; Mann–Whitney U-test, P<0.0001). Methylation values and BAF in the region of aUPD14q were strongly correlated (Spearman's rank correlation, r=0.76, P=0.0001) (Figure 2), suggesting that the relatively low levels of methylation imbalance in some individuals was due to the presence of a small clone with aUPD14q. In contrast, methylation in the +14 cases showed no parental bias (mean methylation value 0.05, s.d. ±0.17; +14 cases versus controls, P=0.34, Mann–Whitney U-test). This is the first time to our knowledge that aUPD has been associated with a specific parent of origin effect, a finding that indicates that aUPD14q targets an imprinted locus.
Figure 2

MEG3 methylation analysis. (a) PCR of bisulphited DNA allowed differential amplification and relative quantification of the methylated (paternal) and unmethylated (maternal) alleles. Control samples show approximately equal paternal and maternal peak sizes, whereas samples with a high level of aUPD14 show complete loss of the maternal allele. Methylation values are calculated as the methylated paternal allele peak height divided by the sum of methylated and unmethylated peaks, with control values normalised to zero. Complete loss of the maternal allele and gain of the paternal allele in cases is seen in cases with aUPD14q in the great majority of cells and is indicated by a methylation value of 0.5. In many cases, aUPD14q is only seen in a proportion of cells, as indicated by the SNP array BAF in the affected region. Consequently, the methylation value ranges between 0 and 0.5 for paternal gain/maternal loss and between 0 and −0.5 for paternal loss/maternal gain. (b) Methylation values for healthy controls (n=24), cases with aUPD14q (n=22), trisomy 14 (n=6), randomly selected MDS/MPN cases without knowledge of their aUPD14q status (n=48) and MDS/MPN cases that were known to be negative for aUPD14q or other visible chromosome 14 abnormalities (n=48). The results show a highly significant skewing (P<0.0001 Mann–Whitney U-test) in the aUPD14q cases towards paternal aUPD. (c) Graph illustrating the strong correlation between the methylation value and mean aUPD BAF for each case.

Methylation bias is specific for aUPD14q

To determine if a parent of origin effect is seen in other regions of aUPD, we analysed MDS/MPN cases with aUPD22q (n=5), an abnormality that is also seen recurrently in myeloid malignancies and population cohorts of elderly individuals. Like aUPD14q, the target of aUPD22q has not been identified but there is a candidate imprinted locus (NHP2L1) within the affected region.[19] Methylation analysis indicated maternal aUPD22q in two cases and paternal aUPD22q in three cases (Supplementary Figure 1). Although the number of cases is small, the findings clearly indicate no parent of origin effect, supporting the notion that the imbalance observed for aUPD14q is likely to be pathogenetically relevant.

Methylation bias in cases without aUPD14q

To determine if 14q imprinting abnormalities are more widespread in myeloid neoplasia, MEG3 methylation status was examined in additional MDS/MPN cases (n=96) that had either been analysed by SNP arrays and were known to be negative for aUPD14q (n=48) or were randomly selected without knowledge of their aUPD14 status (n=48). Most cases had methylation levels that were indistinguishable from healthy controls, but three had a clear gain of methylation (Figure 2b). All three were of unknown aUPD14q status and so we tested six microsatellite loci at 14q32: only one case was homozygous at all six loci suggesting that gain of methylation in the remaining two cases had arisen by a mechanism other than aUPD14q (Supplementary Table 4).

EZH2 mutations in some cases with aUPD14q

MEG3 and other transcripts within the MEG3-DLK1 locus have been implicated in regulation of the polycomb repressive complex 2 (PRC2),[20] components of which are recurrently inactivated in myeloid neoplasia by mutation of EZH2, SUZ12 or EED.[2, 21] It is possible therefore that the consequence of aUPD14q might be functional inactivation of PRC2, in which case we would expect aUPD14q and PRC2 mutations to be mutually exclusive. Partial sequence analysis of EZH2 and SUZ12, the most commonly mutated components of PRC2, revealed causative EZH2 mutations in two out of eight aUPD14q cases (Supplementary Table 5), which suggests that functional inactivation of PRC2 is unlikely to be the primary consequence of aUPD14.

aUPD14q may be an early or late event

Inspection of the exome sequencing data for the aUPD14q cases (n=7) revealed no other obvious driver mutations in three out of four individuals from the population cohorts, suggesting that aUPD14q alone may be sufficient to promote clonal haemopoiesis. The fourth individual (PIVUS 931) was positive for JAK2 V617F as well as a TP53 mutation; he was subsequently diagnosed with polycythemia vera following recruitment into the PIVUS study. In contrast, all three cases with diagnosed myeloid malignancy that were exome sequenced had additional somatic driver mutations in SF3B1, EZH2, JAK2 or TET2 (Table 1). Of the aUPD14q cases that were positive for JAK2 V617F, information on the mutation level as well as the BAF for 9p and 14q aUPD was available for 11 individuals. For these, we were able to estimate both the proportion of cells with aUPD14q and the proportion of cells which were homozygous or heterozygous for JAK2 V617F (Figure 3). This in turn enabled us to infer whether aUPD14q or JAK2 V617F was likely to have arisen first. Assuming that JAK2 V617F and aUPD14q arose within the same clone, our findings suggest that aUPD14q arose before JAK2 V617F in cases E09853, PT1645, PT1670 and PT1876 since the proportion of cells positive for aUPD14q was twofold or higher than the proportion positive for the JAK2 mutation. In contrast, JAK2 V617F is likely to have arisen first in cases E09861, H3589_11, H10872_10, W1212280 H131_12 and E09984. The order is uncertain for case E09895. It is notable therefore that aUPD14q arose first in three out of four cases with essential thrombocythemia but in only one out of seven cases of polycythemia vera.
Figure 3

Proportions of cells positive for JAK2 V617F and aUPD14q in cases with both abnormalities. Black bars indicate cells positive for aUPD14q; grey bars indicate homozygous JAK2 V617F mutant cells and white bars indicate heterozygous JAK2 V617F mutant cells.

Discussion

Developmental abnormalities arising from constitutional UPD result from inappropriate expression of imprinted genes. Inherited maternal UPD14q is associated with Temple Syndrome, characterized by low birth weight, hypotonia, motor delay, early onset of puberty and short adult stature.[22] Inherited paternal UPD14q is associated with Kagami–Ogata syndrome, characterized by severe developmental delay, hepatoblastoma and characteristic dysmorphology.[23] Both abnormalities result from aberrant expression of the DLK1-MEG3 domain at 14q32, a large and complex imprinted cluster of genes and non-coding RNAs. The methylated paternally derived chromosome expresses the protein-coding genes DLK1, RTL1 and DIO3, while the non-methylated maternally derived chromosome expresses the non-coding genes MEG3, MEG8, asRTL1, multiple miRNAs and snoRNAs.[24] It is not known whether the observed clinical phenotypes are caused by aberrant expression of an individual gene, individual non-coding RNAs or a combination of factors. Our finding of a highly significant parent of origin effect associated with aUPD14q strongly implicates an imprinted locus as the primary target, and that paternal homozygosity for this target provides a growth advantage over cells that harbour both alleles. Del(20q), another somatic abnormality associated with myeloid neoplasms, has been shown to target an imprinted gene cluster[25] but this is the first time to our knowledge that aUPD has been associated with an imprinted target. Although we cannot exclude the possibility that aUPD14q might target another imprinted locus at 14q32, we believe it is highly likely that the true target is DLK1-MEG3 since (i) this cluster falls with the 11.2 Mb MAR, an interval that contains 121 known protein-coding genes plus the immunoglobulin region, and (ii) despite extensive searches there are no other confirmed imprinted loci within the MAR, or indeed elsewhere on chromosome 14. Furthermore, expression of DLK1-MEG3 has been reported to be deregulated in diverse neoplasms in the absence of chromosome 14 abnormalities, including acute promyelocytic leukaemia[26, 27] and myelofibrosis.[28, 29] In our study, we did not have suitably stored material for expression analysis of aUPD14q cases; however, expression analysis alone is unlikely to be informative since by definition aUPD would be expected to distort the normal expression of imprinted genes in the affected region whether they were of pathogenetic relevance or not. Of the 22 aUPD14q cases analysed for MEG3 methylation in our study, 21 had positive values indicative of paternal aUPD. One case had a negative methylation value. We do not have an explanation for this aberrant case, but potentially other mutations may have been present that promoted clonal expansion. We note that aUPD for other regions has not been associated with a specific mutational target in all cases, for example, we found that only 9 of 12 MDS/MPN cases with aUPD7q had EZH2 mutations, with the target of the remaining 3 cases remaining unclear.[2] Similar to other mutations associated with clonal haemopoiesis in population cohorts,[30, 31] aUPD14q is more prevalent in the elderly. Previous studies found aUPD14q in 21/50 222 (0.04%) individuals, rising to 14/15 101 (0.09%) in those >60 years of age,[3, 4] an increase that parallels the increase in myeloid neoplasia seen in the elderly. Analysis of longitudinal data estimated a 10-fold elevated risk of developing a haematological malignancy for individuals with any acquired chromosome anomaly,[4] and a similar risk was estimated for individuals with somatic mutations in genes known to be associated with myeloid malignancies.[30, 31] The most commonly mutated genes in population cohorts were DNMT3A, TET2 and ASXL1, and the finding that most individuals had only a single abnormality suggested that mutations in these genes are often initiating events for clonal haemopoiesis. Inspection of our exome sequencing data for the aUPD14q cases revealed no mutations in known driver genes in three out of four population cohort cases. By contrast, all three cases with diagnosed myeloid malignancy had additional somatic driver mutations. We suggest therefore that aUPD14q may also initiate clonal haemopoiesis and predispose to overt malignancy. However, when we examined cases that had both aUPD14q and JAK2 V617F, it was clear that aUPD14q may be an early event in some MPN cases but a late event in others. Furthermore, we found that aUPD14q tends to arise before JAK2 V617F in essential thrombocythaemia but after V617F in polycythemia vera. This is reminiscent of the finding that mutated TET2 may precede or follow the acquisition of JAK2 V617F in MPN, with the order of acquisition influencing clinical features and stem cell biology.[32]
  32 in total

1.  Rare germline variants in regions of loss of heterozygosity may influence clinical course of hematological malignancies.

Authors:  A Harutyunyan; B Gisslinger; T Klampfl; T Berg; K Bagienski; H Gisslinger; R Kralovics
Journal:  Leukemia       Date:  2011-06-17       Impact factor: 11.528

2.  Inactivation of polycomb repressive complex 2 components in myeloproliferative and myelodysplastic/myeloproliferative neoplasms.

Authors:  Joannah Score; Claire Hidalgo-Curtis; Amy V Jones; Nils Winkelmann; Alison Skinner; Daniel Ward; Katerina Zoi; Thomas Ernst; Frank Stegelmann; Konstanze Döhner; Andrew Chase; Nicholas C P Cross
Journal:  Blood       Date:  2011-11-03       Impact factor: 22.113

3.  Inactivating mutations of the histone methyltransferase gene EZH2 in myeloid disorders.

Authors:  Thomas Ernst; Andrew J Chase; Joannah Score; Claire E Hidalgo-Curtis; Catherine Bryant; Amy V Jones; Katherine Waghorn; Katerina Zoi; Fiona M Ross; Andreas Reiter; Andreas Hochhaus; Hans G Drexler; Andrew Duncombe; Francisco Cervantes; David Oscier; Jacqueline Boultwood; Francis H Grand; Nicholas C P Cross
Journal:  Nat Genet       Date:  2010-07-04       Impact factor: 38.330

4.  CpG methylation analysis of the MEG3 and SNRPN imprinted genes in acute myeloid leukemia and myelodysplastic syndromes.

Authors:  Leonidas Benetatos; Eleftheria Hatzimichael; Aggeliki Dasoula; George Dranitsaris; Stavroula Tsiara; Maria Syrrou; Ioannis Georgiou; Konstantinos L Bourantas
Journal:  Leuk Res       Date:  2010-02       Impact factor: 3.156

5.  Chromosomal lesions and uniparental disomy detected by SNP arrays in MDS, MDS/MPD, and MDS-derived AML.

Authors:  Lukasz P Gondek; Ramon Tiu; Christine L O'Keefe; Mikkael A Sekeres; Karl S Theil; Jaroslaw P Maciejewski
Journal:  Blood       Date:  2007-10-22       Impact factor: 22.113

6.  Gain-of-function of mutated C-CBL tumour suppressor in myeloid neoplasms.

Authors:  Masashi Sanada; Takahiro Suzuki; Lee-Yung Shih; Makoto Otsu; Motohiro Kato; Satoshi Yamazaki; Azusa Tamura; Hiroaki Honda; Mamiko Sakata-Yanagimoto; Keiki Kumano; Hideaki Oda; Tetsuya Yamagata; Junko Takita; Noriko Gotoh; Kumi Nakazaki; Norihiko Kawamata; Masafumi Onodera; Masaharu Nobuyoshi; Yasuhide Hayashi; Hiroshi Harada; Mineo Kurokawa; Shigeru Chiba; Hiraku Mori; Keiya Ozawa; Mitsuhiro Omine; Hisamaru Hirai; Hiromitsu Nakauchi; H Phillip Koeffler; Seishi Ogawa
Journal:  Nature       Date:  2009-07-20       Impact factor: 49.962

7.  Frequent CBL mutations associated with 11q acquired uniparental disomy in myeloproliferative neoplasms.

Authors:  Francis H Grand; Claire E Hidalgo-Curtis; Thomas Ernst; Katerina Zoi; Christine Zoi; Carolann McGuire; Sebastian Kreil; Amy Jones; Joannah Score; Georgia Metzgeroth; David Oscier; Andrew Hall; Christian Brandts; Hubert Serve; Andreas Reiter; Andrew J Chase; Nicholas C P Cross
Journal:  Blood       Date:  2009-04-22       Impact factor: 22.113

Review 8.  Genomic imprinting at the mammalian Dlk1-Dio3 domain.

Authors:  Simao Teixeira da Rocha; Carol A Edwards; Mitsuteru Ito; Tsutomu Ogata; Anne C Ferguson-Smith
Journal:  Trends Genet       Date:  2008-06       Impact factor: 11.639

9.  Acquired mutations in TET2 are common in myelodysplastic syndromes.

Authors:  Saskia M C Langemeijer; Roland P Kuiper; Marieke Berends; Ruth Knops; Mariam G Aslanyan; Marion Massop; Ellen Stevens-Linders; Patricia van Hoogen; Ad Geurts van Kessel; Reinier A P Raymakers; Eveline J Kamping; Gregor E Verhoef; Estelle Verburgh; Anne Hagemeijer; Peter Vandenberghe; Theo de Witte; Bert A van der Reijden; Joop H Jansen
Journal:  Nat Genet       Date:  2009-05-31       Impact factor: 38.330

10.  Segmentation-based detection of allelic imbalance and loss-of-heterozygosity in cancer cells using whole genome SNP arrays.

Authors:  Johan Staaf; David Lindgren; Johan Vallon-Christersson; Anders Isaksson; Hanna Göransson; Gunnar Juliusson; Richard Rosenquist; Mattias Höglund; Ake Borg; Markus Ringnér
Journal:  Genome Biol       Date:  2008-09-16       Impact factor: 13.583

View more
  5 in total

Review 1.  Mosaicism in health and disease - clones picking up speed.

Authors:  Lars A Forsberg; David Gisselsson; Jan P Dumanski
Journal:  Nat Rev Genet       Date:  2016-12-12       Impact factor: 53.242

Review 2.  Recent advances in the genomics and therapy of BCR/ABL1-positive and -negative chronic myeloproliferative neoplasms.

Authors:  Tariq I Mughal; Jason Gotlib; Ruben Mesa; Steffen Koschmieder; H Jean Khoury; Jorge E Cortes; Tiziano Barbui; Rüdiger Hehlmann; Michael Mauro; Susanne Saussele; Jerald P Radich; Richard A Van Etten; Giuseppe Saglio; Srdnan Verstovek; Robert Peter Gale; Omar Abdel-Wahab
Journal:  Leuk Res       Date:  2018-02-14       Impact factor: 3.156

Review 3.  Clonal hematopoiesis in acquired aplastic anemia.

Authors:  Seishi Ogawa
Journal:  Blood       Date:  2016-04-27       Impact factor: 22.113

4.  Monogenic and polygenic inheritance become instruments for clonal selection.

Authors:  Po-Ru Loh; Giulio Genovese; Steven A McCarroll
Journal:  Nature       Date:  2020-06-24       Impact factor: 49.962

5.  Insights into clonal haematopoiesis from 8,342 mosaic chromosomal alterations.

Authors:  Po-Ru Loh; Giulio Genovese; Robert E Handsaker; Hilary K Finucane; Yakir A Reshef; Pier Francesco Palamara; Brenda M Birmann; Michael E Talkowski; Samuel F Bakhoum; Steven A McCarroll; Alkes L Price
Journal:  Nature       Date:  2018-07-11       Impact factor: 49.962

  5 in total

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