Biology subjects

David Liewald

Publications and source records attributed to David Liewald.

3 recordsLinked to original sources

bioRxiv2016

Genetic Prediction of Male Pattern Baldness

Male pattern baldness can have substantial psychosocial effects, and it has been phenotypically linked to adverse health outcomes such as prostate cancer and cardiovascular disease. We explored the genetic architecture of the trait using data from over 52,000 male participants of UK Biobank, aged 40-69 years. We identified over 250 independent novel genetic loci associated with severe hair loss. By developing a prediction algorithm based entirely on common genetic variants, and applying it to an independent sample, we could discriminate accurately (AUC = 0.82) between those with no hair loss from those with severe hair loss. The results of this study might help identify those at the greatest risk of hair loss and also potential genetic targets for intervention.

Genetics↗

bioRxiv2016

Subcortical volume and white matter integrity abnormalities in major depressive disorder: findings from UK Biobank (N=4446)

BackgroundPrevious reports of altered grey and white matter structure in Major Depressive Disorder (MDD) have been inconsistent. Recent meta-analyses have, however, reported reduced hippocampal grey matter volume in MDD and reduced white matter integrity in several brain regions. The use of different diagnostic criteria, different scanners and imaging sequences may, however, obscure further anatomical differences.\n\nMethodsIn this study, we tested for differences in subcortical grey matter volume and white matter integrity between depressed individuals and controls in a large sample of subjects from the first data release of the UK Biobank imaging study of 4446 individuals, which used consistent diagnostic criteria at a single assessment centre, with a single MRI scanner and protocol.\n\nResultsWhilst we found no significant differences in subcortical volumes, we report significant reductions in depressed individuals versus controls in global white matter integrity, as measured by fractional anisotropy (FA) ({beta} = -0.187, p = 0.017). We also report reductions in FA in association/commissural fibres ({beta} = -0.184, p = 0.019) and thalamic radiations ({beta} = -0.175, p = 0.027). Examining tracts individually, we report tract-specific FA reductions in the left superior longitudinal fasciculus ({beta} = -0.218, pcorrected = 0.012) and superior thalamic radiation ({beta} = -0.258, pcorrected = 0.010) in subjects with depression.\n\nConclusionsOur findings highlight the need for further large adequately-powered studies of depression and provide further evidence for disrupted white matter integrity in the disorder. Future studies would focus on exploring the typical neuro-phenotype in homogenous subgroups of depression.

Neuroscience↗

bioRxiv2016

Molecular genetic aetiology of general cognitive function is enriched in evolutionarily conserved regions

Differences in general cognitive function have been shown to be partly heritable and to show genetic correlations with a several psychiatric and physical disease states. However, to date few single nucleotide polymorphisms (SNPs) have demonstrated genome-wide significance, hampering efforts aimed at determining which genetic variants are most important for cognitive function and which regions drive the genetic associations between cognitive function and disease states. Here, we combine multiple large genome-wide association study (GWAS) data sets, from the CHARGE cognitive consortium and UK Biobank, to partition the genome into 52 functional annotations and an additional 10 annotations describing tissue-specific histone marks. Using stratified linkage disequilibrium score regression we show that, in two measures of cognitive function, SNPs associated with cognitive function cluster in regions of the genome that are under evolutionary negative selective pressure. These conserved regions contained ~2.6% of the SNPs from each GWAS but accounted for ~40% of the SNP-based heritability. The results suggest that the search for causal variants associated with cognitive function, and those variants that exert a pleiotropic effect between cognitive function and health, will be facilitated by examining these enriched regions.

Genetics↗