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Absher, Devin

https://orcid.org/0000-0003-4405-1646

Mayo Clinic

HudsonAlpha Institute for Biotechnology

Citations 3

Abstract 1319: Epigenome-wide association study reveals differential DNA methylation consistent with progression of multiple myeloma
Gragg, Stephen D., Absher, Devin , Pillion, Christina, Myers, R , Kumar, Shaji , Vachon, Celine M. , Brown, Elizabeth , Cui, Xiangqin , Costa, Luciano J. , Chiu, Brian C.‐H. , Vachon, Celine M.

Cancer Research | July 31, 2017 | Volume: 77 | Issue: 13_Supplement | Pages: 1319-1319

10.1158/1538-7445.am2017-1319 Get It

Abstract Purpose: Multiple myeloma (MM) is the second most common hematological malignancy in the US. It is characterized by a clonal expansion of plasma cells in the bone marrow and extramedullary sites and is preceded by two precursor conditions including monoclonal gammopathy of undetermined significance (MGUS) and smoldering myeloma (SMM). Strong evidence suggests a germline and environmental etiology. However, efforts to characterize heritable changes in gene activity, such as DNA methylation, have not been widely reported. Methods: We examined epigenome-wide DNA methylation as markers of MGUS, SMM and MM in peripheral blood obtained from treatment-naïve European American cases with heavy-chain IgG or IgA MGUS (n=60), SMM (n=31) and MM (n=54) and age- and sex-matched controls (n=79) included from the University of Alabama at Birmingham, University of Chicago and the Mayo Clinic, Rochester [54.5% males; mean age, 64 years (range, 36 to 86)]. We quantified DNA methylation of over 450,000 CpG and non-CpG loci using the Infinium HumanMethylation450 array (Illumina). Differentially methylated positions were calculated using a general linear model framework adjusted for confounders and cellular heterogeneity. Results: A total of 6 CpGs were differentially methylated in MM cases compared to controls at a level of genome-wide statistical significance. MM was associated with hypomethylation at differentially methylated positions inside SBNO2 (P=3.37x10-10), WIZ (P=1.12x10-8), CA6 (P=4.29x10-8) and ADORA1 (P=3.68x10-8) as well as intergenic positions proximal to TNFRSF8 (Chr 1p36.22; P=2.24x10-9) and ENDOV (Chr 17q25.3; P=2.74x10-8). Each of these loci, with the exception of CA6 and ADORA1, were hypomethylated in each of the 3 plasma cell dyscrasia phenotypes including MGUS and SMM and MM cases compared to controls (P<0.03), albeit not at a level of genome-wide statistical significance. Conclusions: These preliminary findings suggest that differences in DNA methylation may contribute to altered risk of MM, as well as its precursor conditions, and may play a role in plasma cell dyscrasia progression as a consequence of heritable changes in gene activity due to past exposures. Replication in a large yet similarly well-characterized population is warranted. Citation Format: Stephen D. Gragg, Devin Absher, Xiangqin Cui, Christina Pillion, Richard Myers, Shaji Kumar, Luciano Costa, Brian Chiu, Celine Vachon, Elizabeth Brown. Epigenome-wide association study reveals differential DNA methylation consistent with progression of multiple myeloma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1319. doi:10.1158/1538-7445.AM2017-1319
A Bivariate Genome-Wide Approach to Metabolic Syndrome
Kraja, Aldi T., Vaidya, Dhananjay , Pankow, James S. , Goodarzi, Mark O., Assimes, Themistocles L. , Sovio, Ulla , Mathias, Rasika A. , Sun, Yan V. , Franceschini, Nora , Absher, Devin , Zhang, Qunyuan, Feitosa, Mary F. , Glazer, Nicole L. , Hartikainen, Anna-Liisa, Knowles, Joshua W. , Iribarren, Carlos , Kral, Brian G. , Yanek, Lisa R. , O’Reilly, Paul F. , McCarthy, Mark I. , Jaquish, Cashell E. , Couper, David , Chakravarti, Aravinda , Becker, Lewis C. , Province, Michael A. , Boerwinkle, Eric , Quertermous, Thomas , Palotie, L, Järvelin, Marjo‐Riitta , Becker, Diane M. , Kardia, Sharon L. R., Rotter, Jerome I. , Chen, Yii-Der Ida , Borecki, Ingrid B. , Goodarzi, Mark O. , Kullo, Iftikhar J. , Guo, Li , Haritunians, Talin , Hartikainen, Anna‐Liisa, North, Kari E. , Psaty, Bruce M. , McCarthy, Mark I , Assimes, Themistocles L , Rotter, Jerome I , Mathias, Rasika A , Pankow, James S , Couper, David , Province, Mike

Diabetes | March 9, 2011 | Volume: 60 | Issue: 4 | Pages: 1329-1339

10.2337/db10-1011 Get It

OBJECTIVE The metabolic syndrome (MetS) is defined as concomitant disorders of lipid and glucose metabolism, central obesity, and high blood pressure, with an increased risk of type 2 diabetes and cardiovascular disease. This study tests whether common genetic variants with pleiotropic effects account for some of the correlated architecture among five metabolic phenotypes that define MetS. RESEARCH DESIGN AND METHODS Seven studies of the STAMPEED consortium, comprising 22,161 participants of European ancestry, underwent genome-wide association analyses of metabolic traits using a panel of ∼2.5 million imputed single nucleotide polymorphisms (SNPs). Phenotypes were defined by the National Cholesterol Education Program (NCEP) criteria for MetS in pairwise combinations. Individuals exceeding the NCEP thresholds for both traits of a pair were considered affected. RESULTS Twenty-nine common variants were associated with MetS or a pair of traits. Variants in the genes LPL, CETP, APOA5 (and its cluster), GCKR (and its cluster), LIPC, TRIB1, LOC100128354/MTNR1B, ABCB11, and LOC100129150 were further tested for their association with individual qualitative and quantitative traits. None of the 16 top SNPs (one per gene) associated simultaneously with more than two individual traits. Of them 11 variants showed nominal associations with MetS per se. The effects of 16 top SNPs on the quantitative traits were relatively small, together explaining from ∼9% of the variance in triglycerides, 5.8% of high-density lipoprotein cholesterol, 3.6% of fasting glucose, and 1.4% of systolic blood pressure. CONCLUSIONS Qualitative and quantitative pleiotropic tests on pairs of traits indicate that a small portion of the covariation in these traits can be explained by the reported common genetic variants.