Effects of two common polymorphisms in the 3' untranslated regions of estrogen receptor β on mRNA stability and translatability

Estrogen signaling is mediated by estrogen receptors (ERs), ERα and ERβ. Aberrant estrogen signaling is involved in breast cancer development. ERα is one of the key biomarkers for diagnosis and treatment of breast cancer. Unlike ERα, ERβ is still not introduced as a marker for diagnosis and established as a target of therapy. Numerous studies suggest antiproliferative effects of ERβ, however its role remains to be fully explored. Albeit important, ERα is not a perfect marker, and some aspects of ERα function are still unclear. This thesis aims to characterize distinct molecular facets of ER action relevant for breast cancer and provide valuable information for ER-based diagnosis and treatment design. In PAPER I, we analyzed the functionality of two common single nucleotide polymorphisms in the 3’ untranslated regions of ERβ, rs4986938 and rs928554, which have been extensively investigated for association with various diseases. A significant difference in allelic expression was observed for rs4986938 in breast tumor samples from heterozygous individuals. However, no difference in mRNA stability or translatability between the alleles was observed. In PAPER II, we provided a more comprehensive understanding of ERβ function independent of ERα. A global gene expression analysis in a HEK293/ERβ cell model identified a set of ERβ-regulated genes. Gene Ontology (GO) analysis showed that they are involved in cell-cell signaling, morphogenesis and cell proliferation. Moreover, ERβ expression resulted in a significant decrease in cell proliferation. In PAPER III, using the human breast cancer MCF-7/ERβ cell model, we demonstrated, for the first time, the binding of ERα/β heterodimers to various DNA-binding regions in intact chromatin. In PAPER IV, we investigated a potential cross-talk between estrogen signaling and DNA methylation by identifying their common target genes in MCF-7 cells. Gene expression profiling identified around 150 genes regulated by both 17β- estradiol (E2) and a hypomethylating agent 5-aza-2’-deoxycytidine. Based on GO analysis, CpG island prediction analysis and previously reported ER binding regions, we selected six genes for further analysis. We identified BTG3 and FHL2 as direct target genes of both pathways. However, our data did not support a direct molecular interplay of mediators of estrogen and epigenetic signaling at promoters of regulated genes. In PAPER V, we further explored the interactions between estrogen signaling and DNA methylation, with focus on DNA methyltransferases (DNMT1, DNMT3a and DNMT3b). E2, via ERα, up-regulated DNMT1 and down-regulated DNMT3a and DNMT3b mRNA expression. Furthermore, DNMT3b interacted with ERα. siRNA-mediated DNMT3b depletion increased the expression of two genes, CDKN1A and FHL2. We proposed that the molecular mechanism underlying regulation of FHL2 and CDKN1A gene expression involves interplay of DNMT3b and ERα. In conclusion, the studies presented in this thesis contribute to the knowledge of ERβ function, and give additional insight into the cross-talk mechanisms underlying ERα signaling with ERβ and with DNA methylation pathways

Healthcare fragmentation, multimorbidity, potentially inappropriate medication, and mortality: a Danish nationwide cohort study

Abstract Background Patients with multimorbidity are frequent users of healthcare, but fragmented care may lead to suboptimal treatment. Yet, this has never been examined across healthcare sectors on a national scale. We aimed to quantify care fragmentation using various measures and to analyze the associations with patient outcomes. Methods We conducted a register-based nationwide cohort study with 4.7 million Danish adult citizens. All healthcare contacts to primary care and hospitals during 2018 were recorded. Clinical fragmentation indicators included number of healthcare contacts, involved providers, provider transitions, and hospital trajectories. Formal fragmentation indices assessed care concentration, dispersion, and contact sequence. The patient outcomes were potentially inappropriate medication and all-cause mortality adjusted for demographics, socioeconomic factors, and morbidity level. Results The number of involved healthcare providers, provider transitions, and hospital trajectories rose with increasing morbidity levels. Patients with 3 versus 6 conditions had a mean of 4.0 versus 6.9 involved providers and 6.6 versus 13.7 provider transitions. The proportion of contacts to the patient’s own general practice remained stable across morbidity levels. High levels of care fragmentation were associated with higher rates of potentially inappropriate medication and increased mortality on all fragmentation measures after adjusting for demographic characteristics, socioeconomic factors, and morbidity. The strongest associations with potentially inappropriate medication and mortality were found for ≥ 20 contacts versus none (incidence rate ratio 2.83, 95% CI 2.77–2.90) and ≥ 20 hospital trajectories versus none (hazard ratio 10.8, 95% CI 9.48–12.4), respectively. Having less than 25% of contacts with your usual provider was associated with an incidence rate ratio of potentially inappropriate medication of 1.49 (95% CI 1.40–1.58) and a mortality hazard ratio of 2.59 (95% CI 2.36–2.84) compared with full continuity. For the associations between fragmentation measures and patient outcomes, there were no clear interactions with number of conditions. Conclusions Several clinical indicators of care fragmentation were associated with morbidity level. Care fragmentation was associated with higher rates of potentially inappropriate medication and increased mortality even when adjusting for the most important confounders. Frequent contact to the usual provider, fewer transitions, and better coordination were associated with better patient outcomes regardless of morbidity level