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Yaghootkar, H.

Publications and source records attributed to Yaghootkar, H..

6 recordsLinked to original sources

Unraveling the polygenic architecture of complex traits using blood eQTL meta-analysis

SummaryWhile many disease-associated variants have been identified through genome-wide association studies, their downstream molecular consequences remain unclear.\n\nTo identify these effects, we performed cis- and trans-expression quantitative trait locus (eQTL) analysis in blood from 31,684 individuals through the eQTLGen Consortium.\n\nWe observed that cis-eQTLs can be detected for 88% of the studied genes, but that they have a different genetic architecture compared to disease-associated variants, limiting our ability to use cis-eQTLs to pinpoint causal genes within susceptibility loci.\n\nIn contrast, trans-eQTLs (detected for 37% of 10,317 studied trait-associated variants) were more informative. Multiple unlinked variants, associated to the same complex trait, often converged on trans-genes that are known to play central roles in disease etiology.\n\nWe observed the same when ascertaining the effect of polygenic scores calculated for 1,263 genome-wide association study (GWAS) traits. Expression levels of 13% of the studied genes correlated with polygenic scores, and many resulting genes are known to drive these traits.

genomics

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

Meta-analysis of genome-wide association studies for body fat distribution in 694,649 individuals of European ancestry

One in four adults worldwide are either overweight or obese. Epidemiological studies indicate that the location and distribution of excess fat, rather than general adiposity, is most informative for predicting risk of obesity sequellae, including cardiometabolic disease and cancer. We performed a genome-wide association study meta-analysis of body fat distribution, measured by waist-to-hip ratio adjusted for BMI (WHRadjBMI), and identified 463 signals in 346 loci. Heritability and variant effects were generally stronger in women than men, and we found approximately one-third of all signals to be sexually dimorphic. The 5% of individuals carrying the most WHRadjBMI-increasing alleles were 1.62 times more likely than the bottom 5% to have a WHR above the thresholds used for metabolic syndrome. These data, made publicly available, will inform the biology of body fat distribution and its relationship with disease.

genetics

A common allele in FGF21 associated with preference for sugar consumption lowers body fat in the lower body and increases blood pressure

Fibroblast Growth Factor 21 (FGF21) is a hormone that induces weight loss in model organisms. These findings have led to trials in humans of FGF21 analogues with some showing weight loss and lipid lowering effects. Recent genetic studies have shown that a common allele in the FGF21 gene alters the balance of macronutrients consumed but there was little evidence of an effect on metabolic traits. We studied a common FGF21 allele (A:rs838133) in 451,099 people from the UK Biobank study. We replicated the association between the A allele and higher percentage carbohydrate intake. We then showed that this allele is more strongly associated with body fat distribution, with less fat in the lower body, and higher blood pressure, than it is with BMI, where there is only nominal evidence of an effect. These human phenotypes of naturally occurring variation in the FGF21 gene will inform decisions about FGF21s therapeutic potential.

genetics

Phenotypes associated with female X chromosome aneuploidy in UK Biobank: an unselected, adult, population-based cohort

Women with X chromosome aneuploidy such as 45,X (Turner syndrome) or 47,XXX (Triple X syndrome) present with characteristics including differences in stature, increased cardiovascular disease risk and primary ovarian insufficiency. Many women with X chromosome aneuploidy undergo lifetime clinical monitoring for possible complications. However, ascertainment of cases in the clinic may mean that the phenotypic penetrance is overestimated. Studies of prenatally ascertained X chromosome aneuploidy cases have limited follow-up data and so the long-term consequences into adulthood are often not reported. We aimed to characterise the prevalence and phenotypic consequences of X chromosome aneuploidy in a large population of women over 40 years of age. We detected 30 women with 45,X, 186 with mosaic 45,X/46,XX and 110 with 47,XXX among 244,848 UK Biobank women, using SNP array data. The prevalence of non-mosaic 45,X (1/8,162) and 47,XXX (1/2,226) was lower than expected, but was higher for mosaic 45,X/46,XX (1/1,316). The characteristics of women with 45,X were consistent with the characteristics of a clinically recognised Turner syndrome phenotype, including a 17.2cm shorter stature (SD = 5.72cm; P = 1.5 x 10-53) and 16/30 did not report an age at menarche. The phenotype of women with 47,XXX included taller stature (5.3cm; SD = 5.52cm; P = 5.8 x 10-20), earlier menopause age (5.12 years; SD = 5.1 years; P = 1.2 x 10-14) and a lower fluid intelligence score (24%; SD = 29.7%; P = 3.7 x 10-8). In contrast, the characteristics of women with mosaic 45,X/46,XX were much less pronounced than expected. Women with mosaic 45,X/46,XX were less short, had a normal reproductive lifespan and birth rate, and no reported cardiovascular complications. In conclusion, the availability of data from 244,848 women allowed us to assess the phenotypic penetrance of traits associated with X chromosome aneuploidy in an adult population setting. Our results suggest that the clinical management of women with 45,X/46,XX mosaicism should be minimal, particularly those identified incidentally.\n\nFundingNone

genetics

Red Blood Cell Distribution Width: genetic evidence for aging pathways in 116,666 volunteers

Variability in red blood cell volumes (distribution width, RDW) increases with age and is strongly predictive of mortality, incident coronary heart disease and cancer. We investigated inherited genetic variation associated with RDW in 166,666 UK Biobank human volunteers.\n\nA large proportion RDW is explained by genetic variants (29%), especially in the older group (60+ year olds, 33.8%, <50 year olds, 28.4%). RDW was associated with 194 independent genetic signals; 71 are known for conditions including autoimmune disease, certain cancers, BMI, Alzheimers disease, longevity, age at menopause, bone density, myositis, Parkinsons disease, and age-related macular degeneration. Pathways analysis showed enrichment for telomere maintenance, ribosomal RNA and apoptosis.\n\nAlthough increased RDW is predictive of cardiovascular outcomes, this was not explained by known CVD or related lipid genetic risks. The predictive value of RDW for a range of negative health outcomes may in part be due to variants influencing fundamental pathways of aging.

genomics