Shaunna L Clark1, Karolina A Aberg1, Srilaxmi Nerella1, Gaurav Kumar1, Joseph L McClay1, Wenan Chen2, Linying Y Xie1, Aki Harada1, Andrey A Shabalin1, Guimin Gao2, Sarah E Bergen3,4, Christina M Hultman5, Patrik K E Magnusson5, Patrick F Sullivan5,6, Edwin J C G van den Oord1. 1. Center for Biomarker Research and Precision Medicine, School of Pharmacy, Virginia Commonwealth University, Richmond, Virginia. 2. Department of Biostatistics, School of Medicine, Virginia Commonwealth University, Richmond, Virginia. 3. Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts. 4. Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts. 5. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. 6. Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.
Abstract
BACKGROUND: Methylome-wide association (MWAS) studies present a new way to advance the search for biological correlates for alcohol use. A challenge with methylation studies of alcohol involves the causal direction of significant methylation-alcohol associations. One way to address this issue is to combine MWAS data with genomewide association study (GWAS) data. METHODS: Here, we combined MWAS and GWAS results for alcohol use from 619 individuals. Our MWAS data were generated by next-generation sequencing of the methylated genomic DNA fraction, producing over 60 million reads per subject to interrogate methylation levels at ~27 million autosomal CpG sites in the human genome. Our GWAS included 5,571,786 single nucleotide polymorphisms (SNPs) imputed with 1000 Genomes. RESULTS: When combining the MWAS and GWAS data, our top finding was a region in an intron of CNTN4 (p = 2.55 × 10(-8) ), located between chr3: 2,555,403 and 2,555,524, encompassing SNPs rs1382874 and rs1382875. This finding was then replicated in an independent sample of 730 individuals. We used bisulfite pyrosequencing to measure methylation and found significant association with regular alcohol use in the same direction as the MWAS (p = 0.021). Rs1382874 and rs1382875 were genotyped and found to be associated in the same direction as the GWAS (p = 0.008 and p = 0.009). After integrating the MWAS and GWAS findings from the replication sample, we replicated our combined analysis finding (p = 0.0017) in CNTN4. CONCLUSIONS: Through combining methylation and SNP data, we have identified CNTN4 as a risk factor for regular alcohol use.
BACKGROUND: Methylome-wide association (MWAS) studies present a new way to advance the search for biological correlates for alcohol use. A challenge with methylation studies of alcohol involves the causal direction of significant methylation-alcohol associations. One way to address this issue is to combine MWAS data with genomewide association study (GWAS) data. METHODS: Here, we combined MWAS and GWAS results for alcohol use from 619 individuals. Our MWAS data were generated by next-generation sequencing of the methylated genomic DNA fraction, producing over 60 million reads per subject to interrogate methylation levels at ~27 million autosomal CpG sites in the human genome. Our GWAS included 5,571,786 single nucleotide polymorphisms (SNPs) imputed with 1000 Genomes. RESULTS: When combining the MWAS and GWAS data, our top finding was a region in an intron of CNTN4 (p = 2.55 × 10(-8) ), located between chr3: 2,555,403 and 2,555,524, encompassing SNPs rs1382874 and rs1382875. This finding was then replicated in an independent sample of 730 individuals. We used bisulfite pyrosequencing to measure methylation and found significant association with regular alcohol use in the same direction as the MWAS (p = 0.021). Rs1382874 and rs1382875 were genotyped and found to be associated in the same direction as the GWAS (p = 0.008 and p = 0.009). After integrating the MWAS and GWAS findings from the replication sample, we replicated our combined analysis finding (p = 0.0017) in CNTN4. CONCLUSIONS: Through combining methylation and SNP data, we have identified CNTN4 as a risk factor for regular alcohol use.
Authors: Karolina A Aberg; Joseph L McClay; Srilaxmi Nerella; Shaunna Clark; Gaurav Kumar; Wenan Chen; Amit N Khachane; Linying Xie; Alexandra Hudson; Guimin Gao; Aki Harada; Christina M Hultman; Patrick F Sullivan; Patrik K E Magnusson; Edwin J C G van den Oord Journal: JAMA Psychiatry Date: 2014-03 Impact factor: 21.596
Authors: Karolina A Aberg; Lin Y Xie; Joseph L McClay; Srilaxmi Nerella; Sarah Vunck; Sarah Snider; Patrick M Beardsley; Edwin J C G van den Oord Journal: Epigenomics Date: 2013-08 Impact factor: 4.778
Authors: Gaurav Kumar; Shaunna L Clark; Joseph L McClay; Andrey A Shabalin; Daniel E Adkins; Linying Xie; Robin Chan; Srilaxmi Nerella; Yunjung Kim; Patrick F Sullivan; Christina M Hultman; Patrik K E Magnusson; Karolina A Aberg; Edwin J C G van den Oord Journal: Hum Genet Date: 2014-10-07 Impact factor: 4.132
Authors: Ryan Lister; Eran A Mukamel; Joseph R Nery; Mark Urich; Clare A Puddifoot; Nicholas D Johnson; Jacinta Lucero; Yun Huang; Andrew J Dwork; Matthew D Schultz; Miao Yu; Julian Tonti-Filippini; Holger Heyn; Shijun Hu; Joseph C Wu; Anjana Rao; Manel Esteller; Chuan He; Fatemeh G Haghighi; Terrence J Sejnowski; M Margarita Behrens; Joseph R Ecker Journal: Science Date: 2013-07-04 Impact factor: 47.728
Authors: C Liu; R E Marioni; Å K Hedman; L Pfeiffer; P-C Tsai; L M Reynolds; A C Just; Q Duan; C G Boer; T Tanaka; C E Elks; S Aslibekyan; J A Brody; B Kühnel; C Herder; L M Almli; D Zhi; Y Wang; T Huan; C Yao; M M Mendelson; R Joehanes; L Liang; S-A Love; W Guan; S Shah; A F McRae; A Kretschmer; H Prokisch; K Strauch; A Peters; P M Visscher; N R Wray; X Guo; K L Wiggins; A K Smith; E B Binder; K J Ressler; M R Irvin; D M Absher; D Hernandez; L Ferrucci; S Bandinelli; K Lohman; J Ding; L Trevisi; S Gustafsson; J H Sandling; L Stolk; A G Uitterlinden; I Yet; J E Castillo-Fernandez; T D Spector; J D Schwartz; P Vokonas; L Lind; Y Li; M Fornage; D K Arnett; N J Wareham; N Sotoodehnia; K K Ong; J B J van Meurs; K N Conneely; A A Baccarelli; I J Deary; J T Bell; K E North; Y Liu; M Waldenberger; S J London; E Ingelsson; D Levy Journal: Mol Psychiatry Date: 2016-11-15 Impact factor: 15.992