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Archie Campbell

Publications and source records attributed to Archie Campbell.

5 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

Shared genetics and couple-associated environment are major contributors to the risk of both clinical and self-declared depression

BackgroundBoth genetic and environmental contributions to risk of depression have been identified, but estimates of their effects are limited. Commonalities between major depressive disorder (MDD) and self-declared depression (SDD) are also unclear. Dissecting the genetic and environmental contributions to these traits and their correlation would inform the design and interpretation of genetic studies.\n\nMethodsUsing data from a large Scottish family-based cohort (GS:SFHS, N=21,387), we estimated the genetic and environmental contributions to MDD and SDD. Genetic effects associated with common genome-wide genetic variants (SNP heritability) and additional pedigree-associated genetic variation and Non-genetic effects associated with common environments were estimated using linear mixed modeling (LMM).\n\nFindingsBoth MDD and SDD had significant contributions from effects of common genetic variants, the additional genetic effect of the pedigree and the common environmental effect shared by couples. The correlation between SDD and MDD was high (r=1*00, se=0*21) for common-variant-associated genetic effects and moderate for both the additional genetic effect of the pedigree (r=0*58, se=0*08) and the couple-shared environmental effect (r=0*53, se=0*22).\n\nInterpretationBoth genetics and couple-shared environmental effects were the major factors influencing liability to depression. SDD may provide a scalable alternative to MDD in studies seeking to identify common risk variants. Rarer variants and environmental effects may however differ substantially according to different definitions of depression.\n\nFundingStudy supported by Wellcome Trust Strategic Award 104036/Z/14/Z. GS:SFHS funded by the Scottish Government Health Department, Chief Scientist Office, number CZD/16/6.

Genetics

Quantifying the extent to which index event biases influence large genetic association studies

As genetic association studies increase in size to 100,000s of individuals, subtle biases may influence conclusions. One possible bias is \"index event bias\" (IEB), also called \"collider bias\", caused by the stratification by, or enrichment for, disease status when testing associations between gene variants and a disease-associated trait. We first provided a statistical framework for quantifying IEB then identified real examples of IEB in a range of study and analytical designs. We observed evidence of biased associations for some disease alleles and genetic risk scores, even in population-based studies. For example, a genetic risk score consisting of type 2 diabetes variants was associated with lower BMI in 113,203 type 2 diabetes controls from the population based UK Biobank study (-0.010 SDs BMI per allele, P=5E-4), entirely driven by IEB. Three of 11 individual type 2 diabetes risk alleles, and 10 of 25 hypertension alleles were associated with lower BMI at p<0.05 in UK Biobank when analyzing disease free individuals only, of which six hypertension alleles remained associated at p<0.05 after correction for IEB. Our analysis suggested that the associations between CCND2 and TCF7L2 diabetes risk alleles and BMI could (at least partially) be explained by IEB. Variants remaining associated after correction may be pleiotropic and include those in CYP17A1 (allele associated with hypertension risk and lower BMI). In conclusion, IEB may result in false positive or negative associations in very large studies stratified or strongly enriched for/against disease cases.

Genetics

The genetic structure of the world’s first farmers

We report genome-wide ancient DNA from 44 ancient Near Easterners ranging in time between ~12,000-1,400 BCE, from Natufian hunter-gatherers to Bronze Age farmers. We show that the earliest populations of the Near East derived around half their ancestry from a Basal Eurasian lineage that had little if any Neanderthal admixture and that separated from other non-African lineages prior to their separation from each other. The first farmers of the southern Levant (Israel and Jordan) and Zagros Mountains (Iran) were strongly genetically differentiated, and each descended from local hunter-gatherers. By the time of the Bronze Age, these two populations and Anatolian-related farmers had mixed with each other and with the hunter-gatherers of Europe to drastically reduce genetic differentiation. The impact of the Near Eastern farmers extended beyond the Near East: farmers related to those of Anatolia spread westward into Europe; farmers related to those of the Levant spread southward into East Africa; farmers related to those from Iran spread northward into the Eurasian steppe; and people related to both the early farmers of Iran and to the pastoralists of the Eurasian steppe spread eastward into South Asia.

Genetics

Dissection of Major Depressive Disorder using polygenic risk scores for Schizophrenia in two independent cohort.

Major depressive disorder (MDD) is known for its substantial clinical and suspected causal heterogeneity. It is characterised by low mood, psychomotor slowing, and increased levels of the personality trait neuroticism; factors which are also associated with schizophrenia (SCZ). It is possible that some cases of MDD may have a substantial genetic loading for SCZ. A sign of the presence of SCZ-like MDD sub-groups would be indicated by an interaction between MDD status and polygenic risk of SCZ on cognitive, personality and mood measures. In the current study, we hypothesised that higher SCZ-polygenic risk would define larger MDD case-control differences in cognitive ability, and smaller differences in distress and neuroticism. Polygenic risk scores (PGRS) for SCZ and their association with cognitive variables, neuroticism, mood, and psychological distress were estimated in a large population-based cohort (Generation Scotland: Scottish Family Health Study, GS:SFHS). Individuals were divided into those with, and without, depression (n=2587 & n=16,764 respectively) to test whether there was an interaction between MDD status and schizophrenia risk. Replication was sought in UK Biobank (n=33,525). In both GS:SFHS and UK Biobank we found significant interactions between SCZ-PGRS and MDD status for measures of psychological distress and neuroticism. In both cohorts there was a reduction of case-control differences on a background of higher genetic risk of SCZ. These findings suggest that depression on a background of high genetic risk for SCZ may show attenuated associations with distress and neuroticism. This may represent a causally distinct form of MDD more closely related to SCZ.

Neuroscience