Biology subjects

Giles, G. G.

Publications and source records attributed to Giles, G. G..

8 recordsLinked to original sources

bioRxiv2020

A combined proteomics and Mendelian randomization approach to investigate the effects of aspirin-targeted proteins on colorectal cancer

BackgroundEvidence for aspirins chemopreventative properties on colorectal cancer (CRC) is substantial, but its mechanism of action is not well-understood. We combined a proteomic approach with Mendelian randomization (MR) to identify possible new aspirin targets that decrease CRC risk. MethodsHuman colorectal adenoma cells (RG/C2) were treated with aspirin (24 hours) and a stable isotope labelling with amino acids in cell culture (SILAC) based proteomics approach identified altered protein expression. Protein quantitative trait loci (pQTLs) from INTERVAL (N=3,301) and expression QTLs (eQTLs) from the eQTLGen Consortium (N=31,684) were used as genetic proxies for protein and mRNA expression levels. Two-sample MR of mRNA/protein expression on CRC risk was performed using eQTL/pQTL data combined with CRC genetic summary data from the Colon Cancer Family Registry (CCFR), Colorectal Transdisciplinary (CORECT), Genetics and Epidemiology of Colorectal Cancer (GECCO) consortia and UK Biobank (55,168 cases and 65,160 controls). ResultsAltered expression was detected for 125/5886 proteins. Of these, aspirin decreased MCM6, RRM2 and ARFIP2 expression and MR analysis showed that a standard deviation increase in mRNA/protein expression was associated with increased CRC risk (OR:1.08, 95% CI:1.03-1.13, OR:3.33, 95% CI:2.46-4.50 and OR:1.15, 95% CI:1.02-1.29, respectively). ConclusionMCM6 and RRM2 are involved in DNA repair whereby reduced expression may lead to increased DNA aberrations and ultimately cancer cell death, whereas ARFIP2 is involved in actin cytoskeletal regulation indicating a possible role in aspirins reduction of metastasis. ImpactOur approach has shown how laboratory experiments and population-based approaches can combine to identify aspirin-targeted proteins possibly affecting CRC risk.

cancer biology↗

bioRxiv2019

Physical activity and risks of breast and colorectal cancer: A Mendelian randomization analysis

Physical activity has been associated with lower risks of breast and colorectal cancer in epidemiological studies; however, it is unknown if these associations are causal or confounded. In two-sample Mendelian randomization analyses, using summary genetic data from the UK Biobank and GWA consortia, we found that a one standard deviation increment in average acceleration was associated with lower risks of breast cancer (odds ratio [OR]: 0.59, 95% confidence interval [CI]: 0.42 to 0.84, P-value=0.003) and colorectal cancer (OR: 0.66, 95% CI: 0.53 to 0.82, P-value=2*E-4). We found similar magnitude inverse associations by breast cancer subtype and by colorectal cancer anatomical site. Our results support a potentially causal relationship between higher physical activity levels and lower risks of breast cancer and colorectal cancer. Based on these data, the promotion of physical activity is probably an effective strategy in the primary prevention of these commonly diagnosed cancers.\n\nDisclaimerWhere authors are identified as personnel of the International Agency for Research on Cancer / World Health Organization, the authors alone are responsible for the views expressed in this article and they do not necessarily represent the decisions, policy or views of the International Agency for Research on Cancer / World Health Organization.

genetics↗

bioRxiv2019

Smoking and blood DNA methylation: novel associations, replication of previous findings and assessment of reversibility

We conducted a genome-wide association study of blood DNA methylation and smoking, attempted replication of previously discovered associations, and assessed the reversibility of smoking-associated methylation changes. DNA methylation was measured in baseline peripheral blood samples for 5,044 participants in the Melbourne Collaborative Cohort Study. For 1,032 participants, these measures were repeated using blood samples collected at follow-up, a median of 11 years later. A cross-sectional analysis of the association between smoking and DNA methylation and a longitudinal analysis of changes in smoking status and changes in DNA methylation were conducted. We used our cross-sectional analysis to replicate previously reported associations for current (N=3,327) and former (N=172) smoking. A comprehensive smoking index accounting for the bioactivity of smoking and several aspects of smoking history was constructed to assess the reversibility of smoking-induced methylation changes. We identified 4,496 cross-sectional associations at P<10-7, including 3,296 that were novel. We replicated the majority (90%) of previously reported associations for current and former smokers. In our data, we observed for former smokers a substantial degree of return to the methylation levels of never smokers, compared with current smokers (median: 74%, IQR=63-86%). Consistent with this, we found wide-ranging estimates for the half-life parameter of the comprehensive smoking index. Longitudinal analyses identified 368 sites at which methylation changed upon smoking cessation. Our study provides evidence of many novel associations between smoking and DNA methylation at CpGs across the genome, replicates the vast majority of previously reported associations, and indicates wide-ranging reversibility rates for smoking-induced methylation changes.

genomics↗

bioRxiv2018

The association between weight at birth and breast cancer risk revisited using Mendelian randomisation

Observational studies suggest that higher birth weight (BW) is associated with increased risk of breast cancer in adult life. We conducted a two-sample Mendelian randomisation (MR) study to assess whether this association is causal. Sixty independent single nucleotide polymorphisms (SNPs) known to be associated at P < 5 x 10-8 with BW were used to construct (1) a 41-SNP instrumental variable (IV) for univariable MR after removing SNPs with pleiotropic associations with other breast cancer risk factors and (2) a 49-SNP IV for multivariable MR after filtering SNPs for data availability. BW predicted by the 41-SNP IV was not associated with overall breast cancer risk in inverse-variance weighted (IVW) univariable MR analysis of genetic association data from 122,977 breast cancer cases and 105,974 controls (odds ratio = 0.86 per 500 g higher BW; 95% confidence interval: 0.73--1.01). Sensitivity analyses using four alternative methods and three alternative IVs, including an IV with 59 of the 60 BW-associated SNPs, yielded similar results. Multivariable MR adjusting for the effects of the 49-SNP IV on birth length, adult height, adult body mass index, age at menarche, and age at menopause using IVW and MR-Egger methods provided estimates consistent with univariable analyses. Results were also similar when all analyses were repeated after restricting to estrogen receptor-positive or -negative breast cancer cases. Point estimates of the odds ratios from most analyses performed indicated an inverse relationship between genetically-predicted BW and breast cancer. Thus, there is little evidence from MR to suggest that the previously observed association between higher BW and increased risk of breast cancer in adult life is causal.

epidemiology↗

bioRxiv2018

The association between low-density lipoprotein cholesterol predicted by HMGCR genetic variants and breast cancer risk may be mediated by body mass index

Orho-Melander et al. recently reported that lower low-density lipoprotein cholesterol (LDLC) as predicted by the T-allele of the variant rs12916 in HMGCR is associated with a decreased risk of developing breast cancer [odds ratio (OR) = 0.89; 95% confidence interval (CI): 0.82-0.96].1 This analysis was embedded in a wider Mendelian randomization (MR) study performed using genotype data from a prospective cohort of 26,589 individuals that included 16,022 women and 1176 incident breast cancer cases. HMGCR encodes 3-hydroxy-3-methylglutaryl-coenzyme A reductase, the enzyme inhibited by statins. The T-allele of rs12916 is associated with reduced HMGCR expression and therefore, in principle, its effects should be analogous to the effects of lifelong statin administration starting at birth.2 The MR study of Orho-Melander et al. also found that a genome-wide LDLC score based on 32 independent LDLC-associated single nucleotide polymorphisms (SNPs) was not associated with breast cancer. In light of this finding, they suggest that the protective effect of the rs12916 T-allele on breast cancer may either be specific to LDLC lowering via genetic inhibition of HMGCR or be the result of a distinct mechanism that is regulated by rs12916 and HMGCR.

epidemiology↗

bioRxiv2018

Genome-wide association study of peripheral blood DNA methylation and conventional mammographic density measures

Age- and body mass index (BMI)-adjusted mammographie density is one the strongest breast cancer risk factors. DNA methylation is a molecular mechanism that could underlie interindividual variation in mammographic density. We aimed to investigate the association between breast cancer risk-predicting mammographic density measures and blood DNA methylation. For 436 women from the Australian Mammographic Density Twins and Sisters Study and 591 women from the Melbourne Collaborative Cohort Study, mammographic density (dense area, non-dense area and percentage dense area) defined by the conventional brightness threshold was measured using the CUMULUS software, and peripheral blood DNA methylation was measured using the HumanMethylation450 (HM450) BeadChip assay. Associations between DNA methylation at >400,000 sites and mammographic density measures adjusted for age and BMI were assessed within each cohort and pooled using fixed-effect meta-analysis. Associations with methylation at genetic loci known to be associated with mammographic density were also examined. We found no genome-wide significant(P<10-7)association for any mammographic density measure from the meta-analysis, or from the cohort-specific analyses. None of the 299 methylation sites located at genetic loci associated with mammographic density was associated with any mammographic density measure after adjusting for multiple testing (all P>0.05/299 = 1.7 x 10-4). In summary, our study did not detect associations between blood DNA methylation, as measured by the HM450 assay, and conventional mammographic density measures that predict breast cancer risk.

epidemiology↗

bioRxiv2018

Associations between environmental breast cancer risk factors and DNA methylation-based risk-predicting measures

BackgroundGenome-wide average DNA methylation (GWAM) and epigenetic age acceleration have been suggested to predict breast cancer risk. We aimed to investigate the relationships between these putative risk-predicting measures and environmental breast cancer risk factors.\n\nMethodsUsing the Illumina HumanMethylation450K assay methylation data, we calculated GWAM and epigenetic age acceleration for 132 female twin pairs and their 215 sisters. Linear regression was used to estimate associations between these risk-predicting measures and multiple breast cancer risk factors. Within-pair analysis was performed for the 132 twin pairs.\n\nResultsGWAM was negatively associated with number of live births, and positively with age at first live birth (both P<0.05). Epigenetic age acceleration was positively associated with body mass index (BMI), smoking, alcohol drinking and age at menarche, and negatively with age at first live birth (all P<0.05), and the associations with BMI, alcohol drinking and age at first live birth remained in the within-pair analysis.\n\nConclusionsThis exploratory study shows that lifestyle and hormone-related breast cancer risk factors are associated with DNA methylation-based measures that could predict breast cancer risk. The associations of epigenetic age acceleration with BMI, alcohol drinking and age at first live birth are unlikely to be due to familial confounding.

epidemiology↗

bioRxiv2017

Inference about causation between body mass index and DNA methylation in blood from a twin family study

BackgroundSeveral studies have reported DNA methylation in blood to be associated with body mass index (BMI), but only a few have investigated causal aspects of the association. We used a twin family design to assess this association at two life points and applied a novel analytical approach to investigate the evidence for causality.\n\nMethodsThe methylation profile of DNA from peripheral blood was measured for 479 Australian women (mean age 56 years) from 130 twin families. Linear regression was used to estimate the associations of methylation at ~410 000 cytosine-guanine dinucleotides (CpG), and of the average methylation at ~20 000 genes, with current BMI, BMI at age 18-21 years, and the change between the two (BMI change). A novel regression-based methodology for twins, Inference about Causation through Examination of Familial Confounding (ICE FALCON), was used to assess causation.\n\nResultsAt 5% false discovery rate, nine, six and 12 CpGs at 24 loci were associated with current BMI, BMI at age 18-21 years and BMI change, respectively. The average methylation of BHLHE40 and SOCS3 loci was associated with current BMI, and of PHGDH locus was associated with BMI change. From the ICE FALCON analyses with BMI as the predictor and methylation as the outcome, a womans methylation level was associated with her co-twins BMI, and the association disappeared conditioning on her own BMI, consistent with BMI causing methylation. To the contrary, using methylation as the predictor and BMI as the outcome, a womans BMI was not associated with her co-twins methylation level, consistent with methylation not causing BMI.\n\nConclusionFor middle-aged women, peripheral blood DNA methylation at several genomic locations is associated with current BMI, BMI at age 18-21 years and BMI change. Our study suggests that BMI has a causal effect on peripheral blood DNA methylation.

epidemiology↗