Evidence For Shared Genetic Basis Research Articles

Abstract 224: Evidence for a shared genetic basis between breast cancer and mammographic density phenotypes

Abstract Background: Radiologically dense area (DA) on a mammogram represents the stromal and epithelial tissue in the breast, while non-dense area (NDA) represents adipose tissue. Quantitative measurements of DA, NDA as well as the proportion of dense area in the breast (percent density, PD) adjusted for age and body mass index (BMI) have all been associated with breast cancer (BC) risk. Previous genome-wide association studies (GWAS) have identified genetic loci that show association with both mammographic density (MD) phenotypes and BC, but little is known about the genome-wide and local genetic correlation between MD phenotypes and BC. Methods: We estimated the genome-wide and local genetic correlation between MD phenotypes adjusted for age and BMI and BC, leveraging GWAS summary statistics for MD phenotypes based on 12,866 women (MODE consortium) and for BC based on 122,977 cases and 105,974 controls (BCAC consortium). We also conducted partitioned heritability analysis to identify specific functional annotations that contribute to MD heritability. Results: We observed a negative genetic correlation between DA and NDA (-0.62, p=0.002). Both DA and PD showed positive genetic correlations with overall BC (DA: rg=0.24, p=0.004; PD: rg=0.27, p=0.0001), estrogen receptor-positive (ER+) BC (DA: rg=0.23, p=0.005; PD: rg=0.23, p=0.001), and ER- BC (DA: rg=0.26, p=0.01; PD: rg=0.32, p=0.0006). In contrast, NDA showed a nonsignificant negative genetic correlation with BC (rg=-0.11, p=0.21). Local genetic correlation analyses between MD phenotypes and BC reflected known findings including positive correlation at 10q21 region between both PD and DA and BC (both p<5x10-7), negative correlation at 22q13.1 between DA and BC (p=4.6x10-6), and positive correlation at 8p11.23 between NDA and BC (p=2.8x10-6). Two known BC regions that have not previously been associated with MD showed suggestive genetic correlations between BC and DA: 1q21.2 (negative genetic correlation, p=1.3x10-4) and 12q21.31 (positive genetic correlation, p=6.7x10-4). In exploratory analyses estimating the genome-wide genetic correlation between MD and hormone-related phenotypes in UK Biobank (n=337,199), we observed nominally significant positive genetic correlations between PD and benign mammary dysplasia (rg=0.45, p=0.01), NDA and endometriosis (rg=0.45, p=0.02), and negative genetic correlation between NDA and menstrual cycle length (rg=-0.30, p=0.05). We identified multiple functional annotations that contribute to MD heritability including histone mark H3K27ac that marks active enhancers (~2,5-fold enrichment in heritability for both DA and NDA) and DNAsel Hypersensitive Sites (DHS, 9.1-fold enrichment in heritability for DA). Conclusion: Our results provide evidence of shared genetic basis between mammographic density and breast cancer. Citation Format: Hongjie Chen, Julie Douglas, William Gordon, Deborah Thompson, Fergus Couch, Peter Fasching, Per Hall, John Hopper, Gertraud Maskarenic, Marina Pollan, Jennifer Stone, Rulla Tamimi, Sara Lindstroem. Evidence for a shared genetic basis between breast cancer and mammographic density phenotypes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 224.

No evidence for shared genetic basis of common variants in multiple sclerosis and amyotrophic lateral sclerosis

Genome-wide association studies have been successful in identifying common variants that influence the susceptibility to complex diseases. From these studies, it has emerged that there is substantial overlap in susceptibility loci between diseases. In line with those findings, we hypothesized that shared genetic pathways may exist between multiple sclerosis (MS) and amyotrophic lateral sclerosis (ALS). While both diseases may have inflammatory and neurodegenerative features, epidemiological studies have indicated an increased co-occurrence within individuals and families. To this purpose, we combined genome-wide data from 4088 MS patients, 3762 ALS patients and 12 030 healthy control individuals in whom 5 440 446 single-nucleotide polymorphisms (SNPs) were successfully genotyped or imputed. We tested these SNPs for the excess association shared between MS and ALS and also explored whether polygenic models of SNPs below genome-wide significance could explain some of the observed trait variance between diseases. Genome-wide association meta-analysis of SNPs as well as polygenic analyses fails to provide evidence in favor of an overlap in genetic susceptibility between MS and ALS. Hence, our findings do not support a shared genetic background of common risk variants in MS and ALS.

Disruption of the aortic elastic lamina and medial calcification share genetic determinants in mice.

Disruption of the elastic lamina, as an early indicator of aneurysm formation, and vascular calcification frequently occur together in atherosclerotic lesions of humans. We now report evidence of shared genetic basis for disruption of the elastic lamina (medial disruption) and medial calcification in an F(2) mouse intercross between C57BL/6J and C3H/HeJ on a hyperlipidemic apolipoprotein E (ApoE(-/-)) null gene, known to mediate myocardial calcification. Using transgenic complementation, we show that Abcc6 also contributes to aortic medial calcification. Our data indicate that calcification, though possibly contributory, does not always lead to medial disruption and that in addition to aneurysm formation, medial disruption may be the precursor to calcification.

Identifying disease associations via genome-wide association studies

BackgroundGenome-wide association studies prove to be a powerful approach to identify the genetic basis of different human diseases. We studied the relationship between seven diseases characterized in a previous genome-wide association study by the Wellcome Trust Case Control Consortium. Instead of doing a horizontal association of SNPs to diseases, we did a vertical analysis of disease associations by comparing the genetic similarities of diseases. Our analysis was carried out at four levels – the nucleotide level (SNPs), the gene level, the protein level (through protein-protein interaction network), and the phenotype level.ResultsOur results show that Crohn's disease, rheumatoid arthritis, and type 1 diabetes share evidence of genetic associations at all levels of analysis, offering strong molecular support for the current grouping of the diseases. On the other hand, coronary artery disease, hypertension, and type 2 diabetes, despite being considered as a natural group with potential aetiological overlap, do not show any evidence of shared genetic basis at all levels.ConclusionOur study is a first attempt on mining of GWA data to examine genetic associations between different diseases. The positive result is apparently not a coincidence and hence demonstrates the promising use of our approach.