We evaluate fine particulate matter
(PM2.5) exposure–response
models to propose a consistent set of global effect factors for product
and policy assessments across spatial scales and across urban and
rural environments. Relationships among exposure concentrations and
PM2.5-attributable health effects largely depend on location,
population density, and mortality rates. Existing effect factors build
mostly on an essentially linear exposure–response function
with coefficients from the American Cancer Society study. In contrast,
the Global Burden of Disease analysis offers a nonlinear integrated
exposure–response (IER) model with coefficients derived from
numerous epidemiological studies covering a wide range of exposure
concentrations. We explore the IER, additionally provide a simplified
regression as a function of PM2.5 level, mortality rates,
and severity, and compare results with effect factors derived from
the recently published global exposure mortality model (GEMM). Uncertainty
in effect factors is dominated by the exposure–response shape,
background mortality, and geographic variability. Our central IER-based
effect factor estimates for different regions do not differ substantially
from previous estimates. However, IER estimates exhibit significant
variability between locations as well as between urban and rural
environments, driven primarily by variability in PM2.5 concentrations
and mortality rates. Using the IER as the basis for effect factors
presents a consistent picture of global PM2.5-related effects
for use in product and policy assessment frameworks.
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Genome-wide association studies have identified more than 200 genetic variants to be associated with an increased risk of developing multiple sclerosis (MS). Still, little is known about the causal molecular mechanisms that underlie the genetic contribution to disease susceptibility. In this study, we investigated the role of the single-nucleotide polymorphism (SNP) rs1414273, which is located within the microRNA-548ac stem-loop sequence in the first intron of the CD58 gene. We conducted an expression quantitative trait locus (eQTL) analysis based on public RNA-sequencing and microarray data of blood-derived cells of more than 1000 subjects. Additionally, CD58 transcripts and mature hsa-miR-548ac molecules were measured using real-time PCR in peripheral blood samples of 32 MS patients. Cell culture experiments were performed to evaluate the efficiency of Drosha-mediated stem-loop processing dependent on genotype and to determine the target genes of this underexplored microRNA. Across different global populations and data sets, carriers of the MS risk allele showed reduced CD58 mRNA levels but increased hsa-miR-548ac levels. We provide evidence that the SNP rs1414273 might alter Drosha cleavage activity, thereby provoking partial uncoupling of CD58 gene expression and microRNA-548ac production from the shared primary transcript in immune cells. Moreover, the microRNA was found to regulate genes, which participate in inflammatory processes and in controlling the balance of protein folding and degradation. We thus uncovered new regulatory implications of the MS-associated haplotype of the CD58 gene locus, and we remind that paradoxical findings can be encountered in the analysis of eQTLs upon data aggregation. Our study illustrates that a better understanding of RNA processing events might help to establish the functional nature of genetic variants, which predispose to inflammatory and neurological diseases.
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