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Pollard, M.

Publications and source records attributed to Pollard, M..

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Out with the old and in with the new: The role of intolerance of uncertainty in reversal of threat and safety

The ability to learn and reverse threat associations is crucial for survival. The extent to which old threat associations are inhibited and new threat associations are formed may depend on sensitivity to future threat uncertainty. To assess the extent to which Intolerance of Uncertainty (IU) predicts threat learning and reversal, we recorded expectancy ratings and skin conductance in 44 healthy participants during an associative learning paradigm, where threat and safety contingencies were reversed. During acquisition and reversal, we observed larger SCR magnitude and expectancy ratings for threat vs. safety cues. However, during reversal higher IU was associated with larger SCR magnitude to new threat vs. new safety cues, compared to lower IU. These results were specific to IU-related variance, over shared variance with trait anxiety (STAIX-2). Overall, these findings suggest that individuals high in IU are able to reverse threat and safety associations in the presence of direct threat. Such findings help us understand the recently revealed link between IU and threat extinction, where direct threat is absent. Moreover, these findings highlight the potential relevance of IU in clinical intervention and treatment for anxiety disorders.

neuroscience

Very low depth whole genome sequencing in complex trait association studies

MotivationVery low depth sequencing has been proposed as a cost-effective approach to capture low-frequency and rare variation in complex trait association studies. However, a full characterisation of the genotype quality and association power for very low depth sequencing designs is still lacking.\n\nResultsWe perform cohort-wide whole genome sequencing (WGS) at low depth in 1,239 individuals (990 at 1x depth and 249 at 4x depth) from an isolated population, and establish a robust pipeline for calling and imputing very low depth WGS genotypes from standard bioinformatics tools. Using genotyping chip, whole-exome sequencing (WES, 75x depth) and high-depth (22x) WGS data in the same samples, we examine in detail the sensitivity of this approach, and show that imputed 1x WGS recapitulates 95.2% of variants found by imputed GWAS with an average minor allele concordance of 97% for common and low-frequency variants. In our study, 1x further allowed the discovery of 140,844 true low-frequency variants with 73% genotype concordance when compared to high-depth WGS data. Finally, using association results for 57 quantitative traits, we show that very low depth WGS is an efficient alternative to imputed GWAS chip designs, allowing the discovery of up to twice as many true association signals than the classical imputed GWAS design.\n\nSupplementary DataSupplementary Data are appended to this manuscript.

genetics