The total burden of rare,non-synonymous exome genetic variants is not associated with childhood or late-life cognitive ability

Human cognitive ability shows consistent, positive associations with fitness components across the life-course. Underlying genetic variation should therefore be depleted by selection, which is not observed. Genetic variation in general cognitive ability (intelligence) could be maintained by a mutation–selection balance, with rare variants contributing to its genetic architecture. This study examines the association between the total number of rare stop-gain/loss, splice and missense exonic variants and cognitive ability in childhood and old age in the same individuals. Exome array data were obtained in the Lothian Birth Cohorts of 1921 and 1936 (combined N = 1596). General cognitive ability was assessed at age 11 years and in late life (79 and 70 years, respectively) and was modelled against the total number of stop-gain/loss, splice, and missense exonic variants, with minor allele frequency less than or equal to 0.01, using linear regression adjusted for age and sex. In both cohorts and in both the childhood and late-life models, there were no significant associations between rare variant burden in the exome and cognitive ability that survived correction for multiple testing. Contrary to our a priori hypothesis, we observed no evidence for an association between the total number of rare exonic variants and either childhood cognitive ability or late-life cognitive ability.     

Evolutionary processes of melanomas from giant congenital melanocytic nevi

Melanoma can develop in a congenital melanocytic nevus (CMN). In fact, a large CMN is associated with a high risk of developing melanoma. Although melanomas arising from CMNs are thought to have a pathogenesis distinct from conventional melanomas, no studies have been conducted on the evolution or tumor heterogeneity of CMN melanomas. We applied multi‐region whole‐exome sequencing to investigate the clonal nature of driver events and evolutionary processes in CMNs and melanomas arising from CMNs. In two patients, we observed an independent subclonal evolution in cancerized fields of CMNs and chromosome 8q amplification in both melanomas arising from CMNs. The amplification of MYC, located in chromosome 8q, was correlated with the percentage of tumor cells expressing high levels of MYC protein detected in melanoma cells by immunohistochemistry. Our analysis suggests that each CMN cell may evolve sporadically and that amplification of MYC might be a key event for melanoma development in CMNs.     

A Bayes factor approach with informative prior for rare genetic variant analysis from next generation sequencing data

The discovery of rare genetic variants through next generation sequencing is a very challenging issue in the field of human genetics. We propose a novel region‐based statistical approach based on a Bayes Factor (BF) to assess evidence of association between a set of rare variants (RVs) located on the same genomic region and a disease outcome in the context of case‐control design. Marginal likelihoods are computed under the null and alternative hypotheses assuming a binomial distribution for the RV count in the region and a beta or mixture of Dirac and beta prior distribution for the probability of RV. We derive the theoretical null distribution of the BF under our prior setting and show that a Bayesian control of the false Discovery Rate can be obtained for genome‐wide inference. Informative priors are introduced using prior evidence of association from a Kolmogorov‐Smirnov test statistic. We use our simulation program, sim1000G, to generate RV data similar to the 1000 genomes sequencing project. Our simulation studies showed that the new BF statistic outperforms standard methods (SKAT, SKAT‐O, Burden test) in case‐control studies with moderate sample sizes and is equivalent to them under large sample size scenarios. Our real data application to a lung cancer case‐control study found enrichment for RVs in known and novel cancer genes. It also suggests that using the BF with informative prior improves the overall gene discovery compared to the BF with noninformative prior.