| 1. |
- Ahsan, Muhammad, et al.
(författare)
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The relative contribution of DNA methylation and genetic variants on protein biomarkers for human diseases.
- 2017
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Ingår i: PLOS Genetics. - : Public Library of Science (PLoS). - 1553-7390 .- 1553-7404. ; 13:9
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Tidskriftsartikel (refereegranskat)abstract
- Associations between epigenetic alterations and disease status have been identified for many diseases. However, there is no strong evidence that epigenetic alterations are directly causal for disease pathogenesis. In this study, we combined SNP and DNA methylation data with measurements of protein biomarkers for cancer, inflammation or cardiovascular disease, to investigate the relative contribution of genetic and epigenetic variation on biomarker levels. A total of 121 protein biomarkers were measured and analyzed in relation to DNA methylation at 470,000 genomic positions and to over 10 million SNPs. We performed epigenome-wide association study (EWAS) and genome-wide association study (GWAS) analyses, and integrated biomarker, DNA methylation and SNP data using between 698 and 1033 samples depending on data availability for the different analyses. We identified 124 and 45 loci (Bonferroni adjusted P < 0.05) with effect sizes up to 0.22 standard units' change per 1% change in DNA methylation levels and up to four standard units' change per copy of the effective allele in the EWAS and GWAS respectively. Most GWAS loci were cis-regulatory whereas most EWAS loci were located in trans. Eleven EWAS loci were associated with multiple biomarkers, including one in NLRC5 associated with CXCL11, CXCL9, IL-12, and IL-18 levels. All EWAS signals that overlapped with a GWAS locus were driven by underlying genetic variants and three EWAS signals were confounded by smoking. While some cis-regulatory SNPs for biomarkers appeared to have an effect also on DNA methylation levels, cis-regulatory SNPs for DNA methylation were not observed to affect biomarker levels. We present associations between protein biomarker and DNA methylation levels at numerous loci in the genome. The associations are likely to reflect the underlying pattern of genetic variants, specific environmental exposures, or represent secondary effects to the pathogenesis of disease.
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| 2. |
- Ek, Weronica E, et al.
(författare)
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Genetic variants influencing phenotypic variance heterogeneity
- 2018
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Ingår i: Human Molecular Genetics. - : OXFORD UNIV PRESS. - 0964-6906 .- 1460-2083. ; 27:5, s. 799-810
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Tidskriftsartikel (refereegranskat)abstract
- Most genetic studies identify genetic variants associated with disease risk or with the mean value of a quantitative trait. More rarely, genetic variants associated with variance heterogeneity are considered. In this study, we have identified such variance single-nucleotide polymorphisms (vSNPs) and examined if these represent biological gene x gene or gene x environment interactions or statistical artifacts caused by multiple linked genetic variants influencing the same phenotype. We have performed a genome-wide study, to identify vSNPs associated with variance heterogeneity in DNA methylation levels. Genotype data from over 10 million single-nucleotide polymorphisms (SNPs), and DNA methylation levels at over 430 000 CpG sites, were analyzed in 729 individuals. We identified vSNPs for 7195 CpG sites (P < 9.4 x 10(-11)). This is a relatively low number compared to 52 335 CpG sites for which SNPs were associated with mean DNA methylation levels. We further showed that variance heterogeneity between genotypes mainly represents additional, often rare, SNPs in linkage disequilibrium (LD) with the respective vSNP and for some vSNPs, multiple low frequency variants co-segregating with one of the vSNP alleles. Therefore, our results suggest that variance heterogeneity of DNA methylation mainly represents phenotypic effects by multiple SNPs, rather than biological interactions. Such effects may also be important for interpreting variance heterogeneity of more complex clinical phenotypes.
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| 3. |
- Höglund, Julia, et al.
(författare)
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Improved power and precision with whole genome sequencing data in genome-wide association studies of inflammatory biomarkers
- 2019
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9
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Tidskriftsartikel (refereegranskat)abstract
- Genome-wide association studies (GWAS) have identified associations between thousands of common genetic variants and human traits. However, common variants usually explain a limited fraction of the heritability of a trait. A powerful resource for identifying trait-associated variants is whole genome sequencing (WGS) data in cohorts comprised of families or individuals from a limited geographical area. To evaluate the power of WGS compared to imputations, we performed GWAS on WGS data for 72 inflammatory biomarkers, in a kinship-structured cohort. When using WGS data, we identified 18 novel associations that were not detected when analyzing the same biomarkers with genotyped or imputed SNPs. Five of the novel top variants were low frequency variants with a minor allele frequency (MAF) of <5%. Our results suggest that, even when applying a GWAS approach, we gain power and precision using WGS data, presumably due to more accurate determination of genotypes. The lack of a comparable dataset for replication of our results is a limitation in our study. However, this further highlights that there is a need for more genetic epidemiological studies based on WGS data.
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| 4. |
- Rask-Andersen, Mathias, 1979-, et al.
(författare)
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Epigenome-wide association study reveals differential DNA methylation in individuals with a history of myocardial infarction
- 2016
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Ingår i: Human Molecular Genetics. - : Oxford University Press (OUP). - 0964-6906 .- 1460-2083. ; 25:21, s. 4739-4748
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Tidskriftsartikel (refereegranskat)abstract
- Cardiovascular diseases (CVDs) are the leading causes of death worldwide and represent a substantial economic burden on public health care systems. Epigenetic markers have potential as diagnostic markers before clinical symptoms have emerged, and as prognostic markers to inform the choice of clinical intervention. In this study, we performed an epigenome-wide association study (EWAS) for CVDs, to identify disease-specific alterations in DNA methylation. CpG methylation in blood samples from the northern Sweden population health study (NSPHS) (n = 729) was assayed on the Illumina Infinium HumanMethylation450 BeadChip. Individuals with a history of a CVD were identified in the cohort. It included individuals with hypertension (N = 147), myocardial infarction (MI) (N = 48), stroke (N = 27), thrombosis (N = 22) and cardiac arrhythmia (N = 5). Differential DNA methylation was observed at 211 CpG-sites in individuals with a history of MI (q <0.05). These sites represent 196 genes, of which 42 have been described in the scientific literature to be related to cardiac function, cardiovascular disease, cardiogenesis and recovery after ischemic injury. We have shown that individuals with a history of MI have a deviating pattern of DNA methylation at many genomic loci of which a large fraction has previously been linked to CVD. Our results highlight genes that might be important in the pathogenesis of MI or in recovery. In addition, the sites pointed out in this study can serve as candidates for further evaluation as potential biomarkers for MI.
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