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Felix Day

Publications and source records attributed to Felix Day.

3 recordsLinked to original sources

Genomic analyses for age at menarche identify 389 independent signals and indicate BMI-independent effects of puberty timing on cancer susceptibility

The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Here, we analyse 1000-Genome reference panel imputed genotype data on up to ~370,000 women and identify 389 independent signals (all P<5x10-8) for age at menarche, a notable milestone in female pubertal development. In Icelandic data from deCODE, these signals explain ~7.4% of the population variance in age at menarche, corresponding to one quarter of the estimated heritability. We implicate over 250 genes via coding variation or associated gene expression, and demonstrate enrichment across genes active in neural tissues. We identify multiple rare variants near the imprinted genes MKRN3 and DLK1 that exhibit large effects on menarche only when paternally inherited. Disproportionate effects of variants on early or late puberty timing are observed: single variant and heritability estimates are larger for early than late puberty timing in females. The opposite pattern is seen in males, with larger estimates for late than early puberty timing. Mendelian randomization analyses indicate causal inverse associations, independent of BMI, between puberty timing and risks for breast and endometrial cancers in women, and prostate cancer in men. In aggregate, our findings reveal new complexity in the genetic regulation of puberty timing and support new causal links with adult cancer risks.

Genomics

A robust example of collider bias in a genetic association study

A recent paper by Aschard et al described the potential for \"collider bias\" when adjusting for heritable covariates in genetic association studies1. However, in their examples the authors acknowledged that they could not exclude the possibility of a true biological explanation for the genetic association seen only in the adjusted model. Furthermore, the extent to which this bias could create a completely spurious genetic association, rather than just modify the magnitude of the effect,2 remains unclear.\n\nCollider bias describes the artificial association created between two uncorrelated exposures (A and B) when a shared outcome (X) is included in the model as a covariate (Figure 1). We sought to definitively illustrate collider bias by deliberately inducing it to generate a biologically implausible SNP-phenotype association. Both sex (A) and autosomal genetic determinants ...

Genomics

Partitioning heritability by functional category using GWAS summary statistics

Recent work has demonstrated that some functional categories of the genome contribute disproportionately to the heritability of complex diseases. Here, we analyze a broad set of functional elements, including cell-type-specific elements, to estimate their polygenic contributions to heritability in genome-wide association studies (GWAS) of 17 complex diseases and traits spanning a total of 1.3 million phenotype measurements. To enable this analysis, we introduce a new method for partitioning heritability from GWAS summary statistics while controlling for linked markers. This new method is computationally tractable at very large sample sizes, and leverages genome-wide information. Our results include a large enrichment of heritability in conserved regions across many traits; a very large immunological disease-specific enrichment of heritability in FANTOM5 enhancers; and many cell-type-specific enrichments including significant enrichment of central nervous system cell types in body mass index, age at menarche, educational attainment, and smoking behavior. These results demonstrate that GWAS can aid in understanding the biological basis of disease and provide direction for functional follow-up.

Genetics