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Arathimos, R.

Publications and source records attributed to Arathimos, R..

6 recordsLinked to original sources

General dimensions of human brain morphometry inferred from genome-wide association data

BackgroundUnderstanding the neurodegenerative mechanisms underlying cognitive declines in the general population may facilitate early detection of adverse health outcomes in late life. This study investigates biological pathways shared between brain morphometry, ageing, and cognitive ability. MethodsWe develop Genomic Principal Components Analysis (genomic PCA) to model general dimensions of variance in brain morphometry within brain networks at the level of their underlying genetic architecture. With genomic PCA we extract genetic principal components (PCs) that index global dimensions of genetic variance across phenotypes (unlike ancestral PCs that index genetic similarity between participants). Genomic PCA is applied to genome-wide association data for 83 brain regions which we calculated in 36,778 participants of the UK Biobank cohort. Using linkage disequilibrium score regression, we estimate genetic overlap between brain networks and indices of cognitive ability and brain ageing. ResultsA genomic principal component (PC) representing brain-wide dimensions of shared genetic architecture accounted for 40% of the genetic variance across 83 individual brain regions. Genomic PCs corresponding to canonical brain networks accounted for 47-65% of the genetic variance in the corresponding brain regions. These genomic PCs were negatively associated with brain age (rg = -0.34). Loadings of individual brain regions on the whole-brain genomic PC corresponded to sensitivity of a corresponding region to age (r = - 0.27). We identified positive genetic associations between genomic PCs of brain morphometry and general cognitive ability (rg= 0.17-0.21). ConclusionThese results demonstrate substantial shared genetic etiology between connectome-wide dimensions of brain morphometry, ageing, and cognitive ability, which will help guide investigations into risk factors and potential interventions of ageing-related cognitive decline.

genetics↗

dmrff: identifying differentially methylated regions efficiently with power and control

A differentially methylated region (DMR) is a genomic region in which DNA methylation is consistently positively or negatively associated with a phenotype or exposure. We demonstrate that existing algorithms for identifying DMRs either fail to consistently control false positive rates (comb-p and DMRcate), suffer from low power (bumphunter) or lack modeling flexibility (seqlm). We introduce a new method, dmrff, that overcomes these shortcomings and can additionally be used to meta-analyze multiple datasets. When applied to investigate associations of age in multiple datasets, dmrff identifies novel DMRs near genes previously linked to age. An R implementation is available on Github (http://github.com/perishky/dmrff).

bioinformatics↗

DNA methylation mediates genetic liability to non-syndromic cleft lip/palate

BackgroundNon-syndromic cleft lip/palate (nsCL/P) is a complex trait with genetic and environmental risk factors. Around 40 distinct genetic risk loci have been identified for nsCL/P, but many reside in non-protein-coding regions with an unclear function. We hypothesised that one possibility is that the genetic risk variants influence susceptibility to nsCL/P through gene regulation pathways, such as those involving DNA methylation.\n\nMethodsUsing nsCL/P Genome-wide association study summary data and methylation data from four studies, we used Mendelian randomization and joint likelihood mapping to identify putative loci where genetic liability to nsCL/P may be mediated by variation in DNA methylation in blood.\n\nResultsThere was evidence at three independent loci, VAX1 (10q25.3), LOC146880 (17q23.3) and NTN1 (17p13.1), that liability to nsCL/P and variation in DNA methylation might be driven by the same genetic variant. Follow up analyses using DNA methylation data, derived from lip and palate tissue, and gene expression catalogues provided further insight into possible biological mechanisms.\n\nConclusionsGenetic variation may increase liability to nsCL/P by influencing DNA methylation and gene expression at VAX1, LOC146880 and NTN1.

genetics↗

Maternal alcohol consumption during pregnancy and offspring epigenome-wide DNA methylation: findings from six general population-based birth cohorts

Some evidence suggests that light-to-moderate alcohol consumption during pregnancy is associated with adverse outcomes in the offspring, but the precise biological mechanisms underlying such associations are currently unknown. Epigenetic modifications have been suggested as one potential explanation.\n\nWithin the Pregnancy and Childhood Epigenetics (PACE) consortium, we performed meta-analysis to combine information from six population-based birth cohort studies to investigate DNA methylation at over 450,000 sites in the cord blood of newborns differentially exposed to alcohol in utero. We were primarily interested in the effects of sustained consumption throughout pregnancy (data available for five cohorts, 3,075 mother-child pairs), which represents a prolonged prenatal exposure to alcohol, but we also explored binge-drinking and timing-specific exposures. In addition to looking for differential methylation at individual CpG sites, we also used two different methods, Comb-P and DMRcate, to identify differentially methylated regions (DMRs).\n\nWe found no strong evidence of association between any of our alcohol exposure measures and DNA methylation at any individual CpG site. Using Comb-P, we identified 19 DMRs in the offspring of mothers who drank throughout pregnancy compared to the offspring of mothers who gave up drinking at the start of pregnancy, but these were not validated using DMRcate.\n\nIn this multi-cohort study of the general population we found no evidence that maternal alcohol consumption during pregnancy is associated with offspring cord blood DNA methylation, which is in stark contrast to the multiple, strong associations that previous studies have found for maternal smoking. However, it is possible that a combination of a larger sample size, higher doses, different timings of exposure and a more global assessment of genomic DNA methylation might show evidence of association.

epidemiology↗

Associations Of Prenatal And Postnatal Growth With Insulin-Like Growth Factor-I Levels In Pre-Adolescence

BackgroundRapid pre - and postnatal growth have been associated with later life adverse health outcomes, which could implicate (as a mediator) circulating insulin-like-growth-factor I (IGF-I), an important regulator of growth. We investigated associations of prenatal (birth weight and length) and postnatal growth in infancy and childhood with circulating IGF-I measured at 11.5 years of age.\n\nMethodsWe analysed 11.5-year follow-up data from 17,046 Belarusian children who participated in the Promotion of Breastfeeding Intervention Trial (PROBIT) since birth.\n\nResultsComplete data were available for 5422 boys and 4743 girls (60%). We stratified the analyses by sex, as there was evidence of interaction between growth and sex in their associations with IGF-I. Weight and length/height velocity during childhood were positively associated with IGF-I at 11.5 years; associations increased with age at growth assessment and were stronger for length/height gain than for weight gain. The change in internal run-normalized IGF-I z-score at 11.5 years was 0.038 (95% CI -0.004,0.080) per standard deviation (SD) increase in length gain at 0-3 months amongst girls and 0.025 (95% CI - 0.011,0.060) amongst boys, increasing to 0.336 (95% CI 0.281,0.391;) and 0.211 (95% CI 0.165,0.256) for girls and boys, respectively, for growth during 6.5-11.5 years.\n\nConclusionPostnatal growth velocities in childhood are positively associated with levels of circulating IGF-I in pre-adolescents. Future studies should focus on assessing whether IGF-I is on the causal pathway between early growth and later health outcomes, such as cancer and diabetes.

epidemiology↗

Epigenome-Wide Association Study Of Asthma And Wheeze In Childhood And Adolescence

Asthma heritability has only been partially explained by genetic variants and is known to be sensitive to environmental factors, implicating epigenetic modifications such as DNA methylation in its pathogenesis.\n\nUsing data collected in the Avon Longitudinal Study of Parents and Children (ALSPAC), we assessed associations of asthma and wheeze with DNA methylation at 7.5 years and 16.5 years, at over 450,000 CpG sites in DNA from the peripheral blood of approx. 1000 participants. We used Mendelian randomization (MR), a method of causal inference that uses genetic variants as instrumental variables, to infer the direction of association between DNA methylation and asthma.\n\nWe identified 302 CpGs associated with current asthma status (FDR-adjusted P-value <0.05) and 445 with current wheeze status at 7.5 years, with substantial overlap between the two. Genes annotated to the 302 associated CpGs were enriched for pathways related to movement of cellular/subcellular components, locomotion, interleukin-4 production and eosinophil migration. All associations attenuated when adjusted for eosinophil and neutrophil cell count estimates. At 16.5 years, two sites were associated with current asthma after adjustment for cell counts. The CpGs mapped to the AP2A2 and IL5RA genes, with a -2.32 [95% CI -1.47,-3.18] and -2.49 [95% CI -1.56,-3.43] change in percentage methylation in asthma cases respectively. Two-sample bi-directional MR indicated a causal effect of asthma on DNA methylation at several CpG sites at 7.5 years. However, associations did not persist after adjustment for multiple testing. There was no evidence of a causal effect of asthma on DNA methylation at either of the two CpG sites at 16.5 years.\n\nThe majority of observed associations are driven by higher eosinophil cell counts in asthma cases, acting as an intermediate phenotype, with important implications for future studies of DNA methylation in atopic diseases.

epidemiology↗