Biology subjects

Kumari, M.

Publications and source records attributed to Kumari, M..

5 recordsLinked to original sources

bioRxiv2018

Properties of the epigenetic clock and age acceleration

BackgroundThe methylation status of numerous CpG sites in the human genome varies with age. The Horvath epigenetic clock used a wide variety of published DNA methylation data to produce an age prediction that has been widely used to, predict age in unknown samples, and draw conclusions about speed of ageing in various tissues, environments, and diseases. Despite its utility, there are a number of assumptions in the model that require examination. We explore the characteristics of the model in whole blood and multiple brain regions from older people, who are not well represented in the original training data, and in blood from a cross-sectional population study.\n\nResultsWe find that the model systematically underestimates age in tissues from older people. A decrease in slope of the predicted ages were observed at approximately 60 years, indicating that some loci in the model may change differently with age, and that age acceleration measures will themselves be age-dependent. This is seen most strongly in the cerebellum but is also present in other examined tissues, and is consistently observed in multiple datasets. An apparent association of Alzheimers disease with age acceleration disappears when age is used as a covariate. Association tests in the literature use a variety of methods for calculating age acceleration and often do not use age as a covariate. This is a potential cause of misleading findings.\n\nConclusionsAssociations of phenotypes with age acceleration should be evaluated cautiously, and chronological age should be included as a covariate in all analyses.

genomics↗

bioRxiv2018

Genetic studies of accelerometer-based sleep measures in 85,670 individuals yield new insights into human sleep behaviour

Sleep is an essential human function but its regulation is poorly understood. Identifying genetic variants associated with quality, quantity and timing of sleep will provide biological insights into the regulation of sleep and potential links with disease. Using accelerometer data from 85,670 individuals in the UK Biobank, we performed a genome-wide association study of 8 accelerometer-derived sleep traits, 5 of which are not accessible through self-report alone. We identified 47 genetic associations across the sleep traits (P<5x10-8) and replicated our findings in 5,819 individuals from 3 independent studies. These included 26 novel associations for sleep quality and 10 for nocturnal sleep duration. The majority of newly identified variants were associated with a single sleep trait, except for variants previously associated with restless legs syndrome that were associated with multiple sleep traits. Of the new associated and replicated sleep duration loci, we were able to fine-map a missense variant (p.Tyr727Cys) in PDE11A, a dual-specificity 3,5-cyclic nucleotide phosphodiesterase expressed in the hippocampus, as the likely causal variant. As a group, sleep quality loci were enriched for serotonin processing genes and all sleep traits were enriched for cerebellar-expressed genes. These findings provide new biological insights into sleep characteristics.

genetics↗

bioRxiv2018

Leveraging DNA methylation quantitative trait loci to characterize the relationship between methylomic variation, gene expression and complex traits.

Characterizing the complex relationship between genetic, epigenetic and transcriptomic variation has the potential to increase understanding about the mechanisms underpinning health and disease phenotypes. In this study, we describe the most comprehensive analysis of common genetic variation on DNA methylation (DNAm) to date, using the Illumina EPIC array to profile samples from the UK Household Longitudinal study. We identified 12,689,548 significant DNA methylation quantitative trait loci (mQTL) associations (P < 6.52x10-14) occurring between 2,907,234 genetic variants and 93,268 DNAm sites, including a large number not identified using previous DNAm-profiling methods. We demonstrate the utility of these data for interpreting the functional consequences of common genetic variation associated with > 60 human traits, using Summary data-based Mendelian Randomization (SMR) to identify 1,662 pleiotropic associations between 36 complex traits and 1,246 DNAm sites. We also use SMR to characterize the relationship between DNAm and gene expression, identifying 6,798 pleiotropic associations between 5,420 DNAm sites and the transcription of 1,702 genes. Our mQTL database and SMR results are available via a searchable online database (http://www.epigenomicslab.com/online-data-resources/) as a resource to the research community.

genetics↗

bioRxiv2017

Metabolic profiling of adiponectin levels in adults: Mendelian randomization analysis

BackgroundAdiponectin, a circulating adipocyte-derived protein has insulin-sensitizing, anti-inflammatory, anti-atherogenic, and cardiomyocyte-protective properties in animal models. However, the systemic effects of adiponectin in humans are unknown.\n\nObjectivesOur aims were to define the metabolic profile associated with higher blood adiponectin concentration and investigate whether variation in adiponectin concentration affects the systemic metabolic profile.\n\nMethodsWe applied multivariable regression in up to 5,906 adults and Mendelian randomization (using cis-acting genetic variants in the vicinity of the adiponectin gene as instrumental variables) for analysing the causal effect of adiponectin in the metabolic profile of up to 38,058 adults. Participants were largely European from six longitudinal studies and one genome-wide association consortium.\n\nResultsIn the multivariable regression analyses, higher circulating adiponectin was associated with higher HDL lipids and lower VLDL lipids, glucose levels, branched-chain amino acids, and inflammatory markers. However, these findings were not supported by Mendelian randomization analyses for most metabolites. Findings were consistent between sexes and after excluding high risk groups (defined by age and occurrence of previous cardiovascular event) and one study with admixed population.\n\nConclusionOur findings indicate that blood adiponectin concentration is more likely to be an epiphenomenon in the context of metabolic disease than a key determinant.

epidemiology↗

bioRxiv2017

Multivariate Genome-Wide and Integrated Transcriptome and Epigenome-Wide Analyses of the Well-being Spectrum.

Phenotypes related to well-being (life satisfaction, positive affect, neuroticism, and depressive symptoms), are genetically highly correlated (| rg | > .75). Multivariate genome-wide analyses (Nobs = 958,149) of these traits, collectively referred to as the well-being spectrum, reveals 63 significant independent signals, of which 29 were not previously identified. Transcriptome and epigenome analyses implicate variation in gene expression at 8 additional loci and CpG methylation at 6 additional loci in the etiology of well-being. We leverage an anatomically comprehensive survey of gene expression in the brain to annotate our findings, showing that SNPs within genes excessively expressed in the cortex and part of the hippocampal formation are enriched in their effect on well-being.

genetics↗