Biology subjects

Montgomery, G.

Publications and source records attributed to Montgomery, G..

4 recordsLinked to original sources

bioRxiv2018

Genome Scale Epigenetic Profiling Reveals Five Distinct Subtypes of Colorectal Cancer

BACKGROUNDColorectal cancer is an epigenetically heterogeneous disease, however the extent and spectrum of the CpG Island Methylator Phenotype (CIMP) is not clear.\n\nRESULTSAn unselected cohort of 216 colorectal cancers clustered into five clinically and molecularly distinct subgroups using Illumina 450K DNA methylation arrays. CIMP-High cancers were most frequent in the proximal colons of female patients. These dichotomised into CIMP-Hl and CIMP-H2 based on methylation profile which was supported by over representation of BRAF (74%, P<0.0001) or KRAS (55%, P<0.0001) mutation, respectively. Congruent with increasing methylation, there was a stepwise increase in patient age from 62 years in the CI MP-Negative subgroup to 75 years in the CIMP-Hl subgroup (P<0.0001). There was a striking association between PRC2-marked loci and those subjected to significant gene body methylation in CIMP-type cancers (P<1.6xl078). We identified oncogenes susceptible to gene body methylation and Wnt pathway antagonists resistant to gene body methylation. CIMP cluster specific mutations were observed for genes involved in chromatin remodelling, such as in the SWI/SNF and NuRD complexes, suggesting synthetic lethality.\n\nCONCLUSIONThere are five clinically and molecularly distinct subgroups of colorectal cancer based on genome wide epigenetic profiling. These analyses highlighted an unidentified role for gene body methylation in progression of serrated neoplasia. Subgroup-specific mutation of distinct epigenetic regulator genes revealed potentially druggable vulnerabilities for these cancers, which may provide novel precision medicine approaches.

genomics↗

bioRxiv2018

Improved prediction of chronological age from DNA methylation limits it as a biomarker of ageing

DNA methylation is associated with age. The deviation of age predicted from DNA methylation from actual age has been proposed as a biomarker for ageing. However, a better prediction of chronological age implies less opportunity for biological age. Here we used 13,661 samples (from blood and saliva) in the age range of 2 to 104 years from 14 cohorts measured on Illumina HumanMethylation450/EPIC arrays to perform prediction analyses. We show that increasing the sample size achieves a smaller prediction error and higher correlations in test datasets. We demonstrate that smaller prediction errors provide a limit to how much variation in biological ageing can be captured by methylation and provide evidence that age predictors from small samples are prone to confounding by cell composition. Our predictor shows a similar or better performance in non-blood tissues including saliva, endometrium, breast, liver, adipose and muscle, compared with Horvaths across-tissue age predictor.

bioinformatics↗

bioRxiv2017

The Anorexia Nervosa Genetics Initiative: Overview and Methods

BackgroundGenetic factors contribute to anorexia nervosa (AN); and the first genome-wide significant locus has been identified. We describe methods and procedures for the Anorexia Nervosa Genetics Initiative (ANGI), an international collaboration designed to rapidly recruit 13000 individuals with AN as well as ancestrally matched controls. We present sample characteristics and the utility of an online eating disorder diagnostic questionnaire suitable for large-scale genetic and population research.\n\nMethodsANGI recruited from the United States (US), Australia/New Zealand (ANZ), Sweden (SE), and Denmark (DK). Recruitment was via national registers (SE, DK); treatment centers (US, ANZ, SE, DK); and social and traditional media (US, ANZ, SE). All cases had a lifetime AN diagnosis based on DSM-IV or ICD-10 criteria (excluding amenorrhea). Recruited controls had no lifetime history of disordered eating behaviors. To assess the positive and negative predictive validity of the online eating disorder questionnaire (ED100K-v1), 109 women also completed the Structured Clinical Interview for DSM-IV (SCID), Module H.\n\nResultsBlood samples and clinical information were collected from 13,364 individuals with lifetime AN and from controls. Online diagnostic phenotyping was effective and efficient; the validity of the questionnaire was acceptable.\n\nConclusionsOur multipronged recruitment approach was highly effective for rapid recruitment and can be used as a model for efforts by other groups. High online presence of individuals with AN rendered the Internet/social media a remarkably effective recruitment tool in some countries. ANGI has substantially augmented Psychiatric Genomics Consortium AN sample collection. ANGI is a registered clinical trial: clinicaltrials.gov NCT01916538; https://clinicaltrials.gov/ct2/show/NCT01916538?cond=Anorexia+Nervosa&draw=1&rank=3.

genetics↗

bioRxiv2017

Widespread signatures of negative selection in the genetic architecture of human complex traits

Estimation of the joint distribution of effect size and minor allele frequency (MAF) for genetic variants is important for understanding the genetic basis of complex trait variation and can be used to detect signature of natural selection. We develop a Bayesian mixed linear model that simultaneously estimates SNP-based heritability, polygenicity (i.e. the proportion of SNPs with nonzero effects) and the relationship between effect size and MAF for complex traits in conventionally unrelated individuals using genome-wide SNP data. We apply the method to 28 complex traits in the UK Biobank data (N = 126,752), and show that on average across 28 traits, 6% of SNPs have nonzero effects, which in total explain 22% of phenotypic variance. We detect significant (p < 0.05/28 =1.8x10-3) signatures of natural selection for 23 out of 28 traits including reproductive, cardiovascular, and anthropometric traits, as well as educational attainment. We further apply the method to 27,869 gene expression traits (N = 1,748), and identify 30 genes that show significant (p < 2.3x10-6) evidence of natural selection. All the significant estimates of the relationship between effect size and MAF in either complex traits or gene expression traits are consistent with a model of negative selection, as confirmed by forward simulation. We conclude that natural selection acts pervasively on human complex traits shaping genetic variation in the form of negative selection.

genetics↗