Lewin Eisele

Aging of blood can be tracked by DNA methylation changes at just three CpG sites

BackgroundHuman aging is associated with DNA methylation changes at specific sites in the genome. These epigenetic modifications may be used to track donor age for forensic analysis or to estimate biological age.ResultsWe perform a comprehensive analysis of methylation profiles to narrow down 102 age-related CpG sites in blood. We demonstrate that most of these age-associated methylation changes are reversed in induced pluripotent stem cells (iPSCs). Methylation levels at three age-related CpGs - located in the genes ITGA2B, ASPA and PDE4C - were subsequently analyzed by bisulfite pyrosequencing of 151 blood samples. This epigenetic aging signature facilitates age predictions with a mean absolute deviation from chronological age of less than 5 years. This precision is higher than age predictions based on telomere length. Variation of age predictions correlates moderately with clinical and lifestyle parameters supporting the notion that age-associated methylation changes are associated more with biological age than with chronological age. Furthermore, patients with acquired aplastic anemia or dyskeratosis congenita - two diseases associated with progressive bone marrow failure and severe telomere attrition - are predicted to be prematurely aged.ConclusionsOur epigenetic aging signature provides a simple biomarker to estimate the state of aging in blood. Age-associated DNA methylation changes are counteracted in iPSCs. On the other hand, over-estimation of chronological age in bone marrow failure syndromes is indicative for exhaustion of the hematopoietic cell pool. Thus, epigenetic changes upon aging seem to reflect biological aging of blood.

Chromosome 7p11.2 (EGFR) variation influences glioma risk

While gliomas are the most common primary brain tumors, their etiology is largely unknown. To identify novel risk loci for glioma, we conducted genome-wide association (GWA) analysis of two case-control series from France and Germany (2269 cases and 2500 controls). Pooling these data with previously reported UK and US GWA studies provided data on 4147 glioma cases and 7435 controls genotyped for 424 460 common tagging single-nucleotide polymorphisms. Using these data, we demonstrate two statistically independent associations between glioma and rs11979158 and rs2252586, at 7p11.2 which encompasses the EGFR gene (population-corrected statistics, P(c) = 7.72 × 10(-8) and 2.09 × 10(-8), respectively). Both associations were independent of tumor subtype, and were independent of EGFR amplification, p16INK4a deletion and IDH1 mutation status in tumors; compatible with driver effects of the variants on glioma development. These findings show that variation in 7p11.2 is a determinant of inherited glioma risk.

Common variation at 3q26.2, 6p21.33, 17p11.2 and 22q13.1 influences multiple myeloma risk

To identify variants for multiple myeloma risk, we conducted a genome-wide association study with validation in additional series totaling 4,692 individuals with multiple myeloma (cases) and 10,990 controls. We identified four risk loci at 3q26.2 (rs10936599, P = 8.70 × 10−14), 6p21.33 (rs2285803, PSORS1C2, P = 9.67 × 10−11), 17p11.2 (rs4273077, TNFRSF13B, P = 7.67 × 10−9) and 22q13.1 (rs877529, CBX7, P = 7.63 × 10−16). These data provide further evidence for genetic susceptibility to this B-cell hematological malignancy, as well as insight into the biological basis of predisposition.

The CCND1 c.870G>A polymorphism is a risk factor for t(11;14)(q13;q32) multiple myeloma

A number of specific chromosomal abnormalities define the subgroups of multiple myeloma. In a meta-analysis of two genome-wide association studies of multiple myeloma including a total of 1,661 affected individuals, we investigated risk for developing a specific tumor karyotype. The t(11;14)(q13;q32) translocation in which CCND1 is placed under the control of the immunoglobulin heavy chain enhancer was strongly associated with the CCND1 c.870G>A polymorphism (P = 7.96 × 10−11). These results provide a model in which a constitutive genetic factor is associated with risk of a specific chromosomal translocation.

Variation at 3p24.1 and 6q23.3 influences the risk of Hodgkin’s lymphoma

In addition to HLA, recent genome-wide association studies (GWASs) of Hodgkin’s Lymphoma (HL) have identified susceptibility loci for HL at 2p16.1, 8q24.21 and 10p14. In this study, we perform a GWAS meta-analysis with published GWAS (totaling 1,465 cases and 6,417 controls of European background), and follow up the most significant association signals in 2,024 cases and 1,853 controls. A combined analysis identifies new HL susceptibility loci mapping to 3p24.1 (rs3806624; P=1.14×10-12, odds ratio [OR]=1.26) and 6q23.3 (rs7745098; P=3.42×10-9, OR=1.21). rs3806624 localizes 5’ to the EOMES (eomesodermin) gene within a p53 response element affecting p53 binding. rs7745098 maps intergenic to HBS1L and MYB, a region previously associated with hematopoiesis. These findings provide further insight into the genetic and biological basis of inherited susceptibility to HL.

Aberrant hypomethylation of the cancer–testis antigen PRAME correlates with PRAME expression in acute myeloid leukemia

PRAME is a tumor-associated antigen, which belongs to the family of cancer–testis antigens (CTA). The expression of CTA is mainly restricted to the testis and various tumors. In contrast to other CTA, PRAME expression is also frequently detected in acute and chronic leukemias. Due to this expression pattern, PRAME has attracted great interest as a prognostic tumor marker that can be used for the detection of minimal residual disease and as a potential target for immunotherapy. In acute myeloid leukemia (AML), PRAME expression has been observed in 30–64% of cases. To evaluate whether epigenetic mechanisms contribute to PRAME activation in AML, we studied DNA methylation of 15 CpG dinucleotides within a CpG-rich region located in the intron 1 of the PRAME gene. DNA methylation was determined by sequence analysis of cloned PCR products generated from bisulfite-treated genomic DNA. Methylation patterns were correlated with PRAME mRNA levels as determined by microarray analysis and real-time PCR. We found almost complete methylation in mononuclear blood cells from two healthy donors and in bone marrow cells of four PRAME-negative AML patients. In contrast, the degree of PRAME methylation was clearly reduced in four PRAME-positive AML bone marrow samples. In particular, these samples were characterized by the presence of clones, which were completely devoid of methylation. The significant inverse correlation between the degree of methylation and PRAME expression suggests a causal role of DNA methylation in PRAME regulation. Such a role is further supported by the observation that treatment of PRAME-negative cell lines U-937 and THP-1 with the demethylating agent 5′-Aza-2′dC resulted in a dose-related upregulation of PRAME expression.

Long-term residential exposure to urban air pollution, and repeated measures of systemic blood markers of inflammation and coagulation

Background In several studies, exposure to fine particulate matter (PM) has been associated with inflammation, with inconsistent results. We used repeated measurements to examine the association of long-term fine and ultrafine particle exposure with several blood markers of inflammation and coagulation. Methods We used baseline (2000–2003) and follow-up (2006–2008) data from the Heinz Nixdorf Recall Study, a German population-based prospective cohort of 4814 participants. A chemistry transport model was applied to model daily surface concentrations of PM air pollutants (PM10, PM2.5) and particle number on a grid of 1 km2. Applying mixed regression models, we analysed associations of long-term (mean of 365 days prior to blood draw) particle exposure at each participants residence with the level of high-sensitivity C reactive protein (hs-CRP), fibrinogen, platelet and white cell count (WCC), adjusting for short-term PM exposure (moving averages of 1–7 days), personal characteristics, season, ambient temperature (1–5 days), ozone and time trend. Results We analysed 6488 observations: 3275 participants with baseline data and 3213 with follow-up data. An increase of 2.4 µg/m3 in long-term PM2.5 was associated with an adjusted increase of 5.4% (95% CI 0.6% to 10.5%) in hs-CRP and of 2.3% (95% CI 1.4% to 3.3%) in the platelet count. Fibrinogen and WCC were not associated with long-term particle exposure. Conclusions In this population-based cohort, we found associations of long-term exposure to PM with markers of inflammation (hs-CRP) and coagulation (platelets). This finding supports the hypothesis that inflammatory processes might contribute to chronic effects of air pollution on cardiovascular disease.

Low penetrance susceptibility to glioma is caused by the TP53 variant rs78378222

Background:Most of the heritable risk of glioma is presently unaccounted for by mutations in known genes. In addition to rare inactivating germline mutations in TP53 causing glioma in the context of the Li-Fraumeni syndrome, polymorphic variation in TP53 may also contribute to the risk of developing glioma.Methods:To comprehensively evaluate the impact of variation in TP53 on risk, we analysed 23 tagSNPs and imputed 2377 unobserved genotypes in four series totaling 4147 glioma cases and 7435 controls.Results:The strongest validated association signal was shown by the imputed single-nucleotide polymorphism (SNP) rs78378222 (P=6.86 × 10−24, minor allele frequency ∼0.013). Confirmatory genotyping confirmed the high quality of the imputation. The association between rs78378222 and risk was seen for both glioblastoma multiforme (GBM) and non-GBM tumours. We comprehensively examined the relationship between rs78378222 and overall survival in two of the case series totaling 1699 individuals. Despite employing statistical tests sensitive to the detection of differences in early survival, no association was shown.Conclusion:Our data provided strong validation of rs78378222 as a risk factor for glioma but do not support the tenet that the polymorphism being a clinically useful prognostic marker. Acquired TP53 inactivation is a common feature of glioma. As rs78378222 changes the polyadenylation signal of TP53 leading to impaired 3′-end processing of TP53 mRNA, the SNP has strong plausibility for being directly functional contributing to the aetiological basis of glioma.

Combined PER2 and CRY1 expression predicts outcome in chronic lymphocytic leukemia.

The objective of this study was to confirm previous results regarding the differential expression and prognostic significance of the circadian gene CRY1 in chronic lymphocytic leukemia (CLL) patients and its relationship with the expression of other circadian genes and well‐established prognostic markers. We also aimed to investigate whether the peripheral circadian machinery may be deregulated in CLL cells. The expression of CRY1, PER1, and PER2 was determined by real‐time reverse transcriptase polymerase chain reaction (RT‐PCR) in 116 CLL patients. The expression at sequential time points over a 24‐h period was measured in six CLL patients and six normal donors. We confirmed the differential expression of CRY1 in ZAP‐70+/CD38+ and ZAP‐70−/CD38− CLL samples. Subgroups formed according to CRY1 expression levels differed significantly in time to treatment. This difference was even more pronounced for subgroups stratified by a CRY1 : PER2 expression ratio and the ratio was an independent prognostic marker in a multivariate model. Furthermore, our data indicate disturbances in the periodic expression of circadian genes in CLL cells. Because of their role in the expression of cell cycle‐related and DNA‐damage response genes, we suggest that the deregulated expression of circadian genes may be linked to the molecular pathogenesis of CLL.

Common variation at 10p12.31 near MLLT10 influences meningioma risk

To identify susceptibility loci for meningioma, we conducted a genome-wide association study of 859 affected individuals (cases) and 704 controls with validation in two independent sample sets totaling 774 cases and 1,764 controls. We identified a new susceptibility locus for meningioma at 10p12.31 (MLLT10, rs11012732, odds ratio = 1.46, Pcombined = 1.88 × 10−14). This finding advances our understanding of the genetic basis of meningioma development.