31 research outputs found
Evidence for regulatory diversity and auto-regulation at the TAC1 locus in sensory neurones
Peer reviewedPublisher PD
Attitudinal and Demographic Predictors of Measles-Mumps-Rubella Vaccine (MMR) Uptake during the UK Catch-Up Campaign 2008–09: Cross-Sectional Survey
Background and Objective Continued suboptimal measles-mumps-rubella (MMR) vaccine uptake has re-established measles epidemic risk, prompting a UK catch-up campaign in 2008–09 for children who missed MMR doses at scheduled age. Predictors of vaccine uptake during catch-ups are poorly understood, however evidence from routine schedule uptake suggests demographics and attitudes may be central. This work explored this hypothesis using a robust evidence-based measure. Design Cross-sectional self-administered questionnaire with objective behavioural outcome. Setting and Participants 365 UK parents, whose children were aged 5–18 years and had received <2 MMR doses before the 2008–09 UK catch-up started. Main Outcome Measures Parents' attitudes and demographics, parent-reported receipt of invitation to receive catch-up MMR dose(s), and catch-up MMR uptake according to child's medical record (receipt of MMR doses during year 1 of the catch-up). Results Perceived social desirability/benefit of MMR uptake (OR = 1.76, 95% CI = 1.09–2.87) and younger child age (OR = 0.78, 95% CI = 0.68–0.89) were the only independent predictors of catch-up MMR uptake in the sample overall. Uptake predictors differed by whether the child had received 0 MMR doses or 1 MMR dose before the catch-up. Receipt of catch-up invitation predicted uptake only in the 0 dose group (OR = 3.45, 95% CI = 1.18–10.05), whilst perceived social desirability/benefit of MMR uptake predicted uptake only in the 1 dose group (OR = 9.61, 95% CI = 2.57–35.97). Attitudes and demographics explained only 28% of MMR uptake in the 0 dose group compared with 61% in the 1 dose group. Conclusions Catch-up MMR invitations may effectively move children from 0 to 1 MMR doses (unimmunised to partially immunised), whilst attitudinal interventions highlighting social benefits of MMR may effectively move children from 1 to 2 MMR doses (partially to fully immunised). Older children may be best targeted through school-based programmes. A formal evaluation element should be incorporated into future catch-up campaigns to inform their continuing improvement
Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans
Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have
fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in
25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16
regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of
correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP,
while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in
Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium
(LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region.
Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant
enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the
refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa,
an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of
PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent
signals within the same regio
Allele-specific Differences in Activity of a Novel Cannabinoid Receptor 1 (CNR1) Gene Intronic Enhancer in Hypothalamus, Dorsal Root Ganglia, and Hippocampus*
Background: Intron 2 of CNR1 gene contains multiple disease-associated SNPs
Long-Range Regulatory Synergy Is Required to Allow Control of the TAC1 Locus by MEK/ERK Signalling in Sensory Neurones
Changes in the expression of the neuropeptide substance P (SP) in different populations of sensory neurones are associated with the progression of chronic inflammatory disease. Thus, understanding the genomic and cellular mechanisms driving the expression of the TAC1 gene, which encodes SP, in sensory neurones is essential to understanding its role in inflammatory disease. We used a novel combination of computational genomics, primary-cell culture and mouse transgenics to determine the genomic and cellular mechanisms that control the expression of TAC1 in sensory neurones. Intriguingly, we demonstrated that the promoter of the TAC1 gene must act in synergy with a remote enhancer, identified using comparative genomics, to respond to MAPK signalling that modulates the expression of TAC1 in sensory neurones. We also reveal that noxious stimulation of sensory neurones triggers this synergy in larger diameter sensory neurones – an expression of SP associated with hyperalgesia. This noxious stimulation of TAC1 enhancer-promotor synergy could be strongly blocked by antagonism of the MEK pathway. This study provides a unique insight into the role of long-range enhancer-promoter synergy and selectivity in the tissue-specific response of promoters to specific signal transduction pathways and suggests a possible new avenue for the development of novel anti-inflammatory therapies
Analysis code
This link is to a page providing access to code hosted on Zenodo. The Zenodo page also includes a link to analysis code hosted on GitHub
Data from: A dynamic framework for the study of optimal birth intervals reveals the importance of sibling competition and mortality risks
Human reproductive patterns have been well studied, but the mechanisms by which physiology, ecology and existing kin interact to affect the life history need quantification. Here, we create a model to investigate how age-specific interbirth intervals adapt to environmental and intrinsic mortality, and how birth patterns can be shaped by competition and help between siblings. The model provides a flexible framework for studying the processes underlying human reproductive scheduling. We developed a state-based optimality model to determine age-dependent and family-dependent sets of reproductive strategies, including the state of the mother and her offspring. We parameterized the model with realistic mortality curves derived from five human populations. Overall, optimal birth intervals increase until the age of 30 after which they remain relatively constant until the end of the reproductive lifespan. Offspring helping each other does not have much effect on birth intervals. Increasing infant and senescent mortality in different populations decreases interbirth intervals. We show that sibling competition and infant mortality interact to lengthen interbirth intervals. In lower-mortality populations, intense sibling competition pushes births further apart. Varying the adult risk of mortality alone has no effect on birth intervals between populations; competition between offspring drives the differences in birth intervals only when infant mortality is low. These results are relevant to understanding the demographic transition, because our model predicts that sibling competition becomes an important determinant of optimal interbirth intervals only when mortality is low, as in post-transition societies. We do not predict that these effects alone can select for menopause
Model data files
Data files from all experiments used to generate figures in the pape
Model source code
This link is to a page providing access to code hosted on Zenodo. The Zenodo page also includes a link to source code hosted on GitHub