Biology subjects

Ulfarsson, M. O.

Publications and source records attributed to Ulfarsson, M. O..

3 recordsLinked to original sources

bioRxiv2021

The sequences of 150,119 genomes in the UK biobank

We describe the analysis of whole genome sequences (WGS) of 150,119 individuals from the UK biobank (UKB). This constitutes a set of high quality variants, including 585,040,410 SNPs, representing 7.0% of all possible human SNPs, and 58,707,036 indels. The large set of variants allows us to characterize selection based on sequence variation within a population through a Depletion Rank (DR) score for windows along the genome. DR analysis shows that coding exons represent a small fraction of regions in the genome subject to strong sequence conservation. We define three cohorts within the UKB, a large British Irish cohort (XBI) and smaller African (XAF) and South Asian (XSA) cohorts. A haplotype reference panel is provided that allows reliable imputation of most variants carried by three or more sequenced individuals. We identified 895,055 structural variants and 2,536,688 microsatellites, groups of variants typically excluded from large scale WGS studies. Using this formidable new resource, we provide several examples of trait associations for rare variants with large effects not found previously through studies based on exome sequencing and/or imputation.

genetics↗

bioRxiv2020

Analysis of diffusion tensor imaging data from UK Biobank confirms dosage effect of 15q11.2 copy-number variation on white matter and shows association with cognition

BackgroundCopy-number variations at the 15q11.2 BP1-BP2 locus are present in 0.5 to 1.0% of the population, and the deletion is associated with a range of neurodevelopmental disorders. Previously, we showed a reciprocal effect of 15q11.2 copy-number variation on fractional anisotropy, with widespread increases in deletion carriers. We aim to replicate and expand these findings, using a larger sample of participants (n=30,930), higher resolution imaging, and examining the implications for cognitive performance. MethodsDiffusion tensor imaging measures from participants with no neurological/psychiatric diagnoses were obtained from the UK Biobank database. We compared 15q11.2 BP1-BP2 deletion (n=103) and duplication (n=119) carriers to a large cohort of control individuals with no neuropsychiatric copy-number variants (n=29,870). Additionally, we assessed how changes in white matter mediated the association between carrier status and cognitive performance. ResultsDeletion carriers showed increases in fractional anisotropy in the internal capsule and cingulum, and decreases in the posterior thalamic radiation, compared to both duplication carriers and controls (who had intermediate values). Deletion carriers had lower scores across cognitive tasks compared to controls, which were mildly influenced by white matter alterations. Reduced fractional anisotropy in the posterior thalamic radiation partially contributed to worse cognitive performance in deletion carriers. ConclusionsThis study, together with our previous findings, provides convergent evidence for a dosage-dependent effect of 15q11.2 BP1-BP2 on white matter microstructure. Additionally, changes in white matter were found to partially mediate cognitive ability in deletion carriers, providing a link between white matter changes in 15q11.2 BP1-BP2 carriers and cognitive function.

neuroscience↗

bioRxiv2019

Deep learning based brain age prediction uncovers associated sequence variants

Machine learning algorithms trained to recognize age-related structural changes in magnetic resonance images (MRIs) of healthy individuals can be used to predict biological brain age in independent samples. The difference between predicted and chronological age, predicted age difference (PAD), is a phenotype holding promise for the study of normal brain ageing and brain diseases, and genetic discovery via genome-wide association studies (GWASs). Here, we present a new deep learning approach to predict brain age from a T1-weighted MRI. The method was trained on a dataset of healthy Icelanders (N = 1264) and tested on two datasets, the IXI (N = 544) and UK Biobank (N = 12395) datasets, utilizing transfer learning to improve accuracy on new sites. A GWAS of PAD in the UK Biobank data (discovery set: N=12395, replication set: N=4453) yielded two sequence variants, rs1452628-T ({beta}=-0.08, P = 1.15 {middle dot} 10-9) and rs2435204-G ({beta}=0.102, P = 9.73 {middle dot} 10-12). The former is near KCNK2 and correlates with reduced sulcal width, whereas the latter correlates with reduced white matter surface area and tags a well-known inversion at 17q21.31 (H2). The genetic association analysis was also confined to variants known to associate with brain structure, yielding three additional sequence variants associating with PAD.

neuroscience↗