Breakpoint characterization of large deletions in EXT1 or EXT2 in 10 Multiple Osteochondromas families

<p>Abstract</p> <p>Background</p> <p>Osteochondromas (cartilage-capped bone tumors) are by far the most commonly treated of all primary benign bone tumors (50%). In 15% of cases, these tumors occur in the context of a hereditary syndrome called multiple osteochondromas (MO), an autosomal dominant skeletal disorder characterized by the formation of multiple cartilage-capped bone tumors at children's metaphyses. MO is caused by various mutations in <it>EXT1 </it>or <it>EXT2</it>, whereby large genomic deletions (single-or multi-exonic) are responsible for up to 8% of MO-cases.</p> <p>Methods</p> <p>Here we report on the first molecular characterization of ten large <it>EXT1</it>- and <it>EXT2</it>-deletions in MO-patients. Deletions were initially indentified using MLPA or FISH analysis and were subsequently characterized using an MO-specific tiling path array, allele-specific PCR-amplification and sequencing analysis.</p> <p>Results</p> <p>Within the set of ten large deletions, the deleted regions ranged from 2.7 to 260 kb. One <it>EXT2 </it>exon 8 deletion was found to be recurrent. All breakpoints were located outside the coding exons of <it>EXT1 </it>and <it>EXT2</it>. Non-allelic homologous recombination (NAHR) mediated by <it>Alu</it>-sequences, microhomology mediated replication dependent recombination (MMRDR) and non-homologous end-joining (NHEJ) were hypothesized as the causal mechanisms in different deletions.</p> <p>Conclusions</p> <p>Molecular characterization of <it>EXT1</it>- and <it>EXT2</it>-deletion breakpoints in MO-patients indicates that NAHR between <it>Alu-</it>sequences as well as NHEJ are causal and that the majority of these deletions are nonrecurring. These observations emphasize once more the huge genetic variability which is characteristic for MO. To our knowledge, this is the first study characterizing large genomic deletions in <it>EXT1 </it>and <it>EXT2</it>.</p

A many-analysts approach to the relation between religiosity and well-being

The relation between religiosity and well-being is one of the most researched topics in the psychology of religion, yet the directionality and robustness of the effect remains debated. Here, we adopted a many-analysts approach to assess the robustness of this relation based on a new cross-cultural dataset (N=10,535 participants from 24 countries). We recruited 120 analysis teams to investigate (1) whether religious people self-report higher well-being, and (2) whether the relation between religiosity and self-reported well-being depends on perceived cultural norms of religion (i.e., whether it is considered normal and desirable to be religious in a given country). In a two-stage procedure, the teams first created an analysis plan and then executed their planned analysis on the data. For the first research question, all but 3 teams reported positive effect sizes with credible/confidence intervals excluding zero (median reported β=0.120). For the second research question, this was the case for 65% of the teams (median reported β=0.039). While most teams applied (multilevel) linear regression models, there was considerable variability in the choice of items used to construct the independent variables, the dependent variable, and the included covariates

A many-analysts approach to the relation between religiosity and well-being

The relation between religiosity and well-being is one of the most researched topics in the psychology of religion, yet the directionality and robustness of the effect remains debated. Here, we adopted a many-analysts approach to assess the robustness of this relation based on a new cross-cultural dataset (N=10,535 participants from 24 countries). We recruited 120 analysis teams to investigate (1) whether religious people self-report higher well-being, and (2) whether the relation between religiosity and self-reported well-being depends on perceived cultural norms of religion (i.e., whether it is considered normal and desirable to be religious in a given country). In a two-stage procedure, the teams first created an analysis plan and then executed their planned analysis on the data. For the first research question, all but 3 teams reported positive effect sizes with credible/confidence intervals excluding zero (median reported ?=0.120). For the second research question, this was the case for 65% of the teams (median reported ?=0.039). While most teams applied (multilevel) linear regression models, there was considerable variability in the choice of items used to construct the independent variables, the dependent variable, and the included covariates