Changes in individual and contextual socio-economic level influence on reproductive behavior in Spanish women in the MCC-Spain study

Background The association between socioeconomic level and reproductive factors has been widely studied. For example, it is well known that women with lower socioeconomic status (SES) tend to have more children, the age at first-born being earlier. However, less is known about to what extent the great socioeconomic changes occurred in a country (Spain) could modify women reproductive factors. The main purpose of this article is to analyze the influence of individual and contextual socioeconomic levels on reproductive factors in Spanish women, and to explore whether this influence has changed over the last decades. Methods We performed a cross-sectional design using data from 2038 women recruited as population-based controls in an MCC-Spain case-control study. Results Higher parent’s economic level, education level, occupational level and lower urban vulnerability were associated with higher age at first delivery and lower number of pregnancies. These associations were stronger for women born after 1950: women with unfinished primary education had their first delivery 6 years before women with high education if they were born after 1950 (23.4 vs. 29.8 years) but only 3 years before if they were born before 1950 (25.7 vs. 28.0 years). For women born after 1950, the number of pregnancies dropped from 2.1 (unfinished primary school) to 1.7 (high education), whereas it remained almost unchanged in women born before 1950. Conclusions Reproductive behavior was associated with both individual and area-level socio-economic indicators. Such association was stronger for women born after 1950 regarding age at first delivery and number of pregnancies and for women born before 1950 regarding consumption of hormonal contraceptives or postmenopausal therapy

Genetic contributions to circadian activity rhythm and sleep pattern phenotypes in pedigrees segregating for severe bipolar disorder

Abnormalities in sleep and circadian rhythms are central features of bipolar disorder (BP), often persisting between episodes. We report here, to our knowledge, the first systematic analysis of circadian rhythm activity in pedigrees segregating severe BP (BP-I). By analyzing actigraphy data obtained from members of 26 Costa Rican and Colombian pedigrees [136 euthymic (i.e., interepisode) BP-I individuals and 422 non-BP-I relatives], we delineated 73 phenotypes, of which 49 demonstrated significant heritability and 13 showed significant trait-like association with BP-I. All BP-I-associated traits related to activity level, with BP-I individuals consistently demonstrating lower activity levels than their non-BP-I relatives. We analyzed all 49 heritable phenotypes using genetic linkage analysis, with special emphasis on phenotypes judged to have the strongest impact on the biology underlying BP. We identified a locus for interdaily stability of activity, at a threshold exceeding genome-wide significance, on chromosome 12pter, a region that also showed pleiotropic linkage to two additional activity phenotypes.National Institute of Health/[R01MH075007]/NIH/Estados UnidosNational Institute of Health/[R01MH095454]/NIH/Estados UnidosNational Institute of Health/[P30NS062691]/NIH/Estados UnidosNational Institute of Health/[T32MH073526]/NIH/Estados UnidosNational Institute of Health/[K23MH074644-01]/NIH/Estados UnidosNational Institute of Health/[K08MH086786]/NIH/Estados UnidosUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigación en Biología Celular y Molecular (CIBCM

Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Peer reviewe