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Biology subjects

Sarah Medland

Publications and source records attributed to Sarah Medland.

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

Maternal genome-wide association study identifies a fasting glucose variant associated with offspring birth weight

Genome-wide association studies (GWAS) of birth weight have focused on fetal genetics, while relatively little is known about how maternal genetic variation influences fetal growth. We aimed to identify maternal genetic variants associated with birth weight that could highlight potentially relevant maternal determinants of fetal growth.\n\nWe meta-analysed GWAS data on up to 8.7 million SNPs in up to 86,577 women of European descent from the Early Growth Genetics (EGG) Consortium and the UK Biobank. We used structural equation modelling (SEM) and analyses of mother-child pairs to quantify the separate maternal and fetal genetic effects.\n\nMaternal SNPs at 10 loci (MTNR1B, HMGA2, SH2B3, KCNAB1, L3MBTL3, GCK, EBF1, TCF7L2, ACTL9 and CYP3A7) showed evidence of association with offspring birth weight at P<5x10-8. The SEM analyses showed at least 7 of the 10 associations were consistent with effects of the maternal genotype acting via the intrauterine environment, rather than via effects of shared alleles with the fetus. Variants, or correlated proxies, at many of the loci had been previously associated with adult traits, including fasting glucose (MTNR1B, GCK and TCF7L2) and sex hormone levels (CYP3A7), and one (EBF1) with gestational duration.\n\nThe identified associations indicate effects of maternal glucose, cytochrome P450 activity and gestational duration, and potential effects of maternal blood pressure and immune function on fetal growth. Further characterization of these associations, for example in mechanistic and causal analyses, will enhance understanding of the potentially modifiable maternal determinants of fetal growth, with the goal of reducing the morbidity and mortality associated with low and high birth weights.

Genetics

Genome-wide analysis of over 106,000 individuals identifies 9 neuroticism-associated loci

Neuroticism is a personality trait of fundamental importance for psychological wellbeing and public health. It is strongly associated with major depressive disorder (MDD) and several other psychiatric conditions. Although neuroticism is heritable, attempts to identify the alleles involved in previous studies have been limited by relatively small sample sizes and heterogeneity in the measurement of neuroticism. Here we report a genome-wide association study of neuroticism in 91,370 participants of the UK Biobank cohort and a combined meta-analysis which includes a further 7,197 participants from the Generation Scotland Scottish Family Health Study (GS:SFHS) and 8,687 participants from a Queensland Institute of Medical Research (QIMR) cohort. All participants were assessed using the same neuroticism instrument, the Eysenck Personality Questionnaire-Revised (EPQ-R-S) Short Forms Neuroticism scale. We found a SNP-based heritability estimate for neuroticism of approximately 15% (SE = 0.7%). Meta-analysis identified 9 novel loci associated with neuroticism. The strongest evidence for association was at a locus on chromosome 8 (p = 1.28x10-15) spanning 4 Mb and containing at least 36 genes. Other associated loci included genes of interest on chromosome 1 (GRIK3, glutamate receptor ionotropic kainate 3), chromosome 4 (KLHL2, Kelch-like protein 2), chromosome 17 (CRHR1, corticotropin-releasing hormone receptor 1 and MAPT, microtubule-associated protein Tau), and on chromosome 18 (CELF4, CUGBP elav-like family member 4). We found no evidence for genetic differences in the common allelic architecture of neuroticism by sex. By comparing our findings with those of the Psychiatric Genetics Consortia, we identified a large genetic correlation between neuroticism and MDD (0.64) and a smaller genetic correlation with schizophrenia (0.22) but not with bipolar disorder. Polygenic scores derived from the primary UK Biobank sample captured about 1% of the variance in trait liability to neuroticism. Overall, our findings confirm a polygenic basis for neuroticism and substantial shared genetic architecture between neuroticism and MDD. The identification of 9 new neuroticism-associated loci will drive forward future work on the neurobiology of neuroticism and related phenotypes.

Genetics