RNA Editing Genes Associated with Extreme Old Age in Humans and with Lifespan in C. elegans

Background

The strong familiality of living to extreme ages suggests that human longevity is genetically regulated. The majority of genes found thus far to be associated with longevity primarily function in lipoprotein metabolism and insulin/IGF-1 signaling. There are likely many more genetic modifiers of human longevity that remain to be discovered.

Methodology/Principal Findings

Here, we first show that 18 single nucleotide polymorphisms (SNPs) in the RNA editing genes ADARB1 and ADARB2 are associated with extreme old age in a U.S. based study of centenarians, the New England Centenarian Study. We describe replications of these findings in three independently conducted centenarian studies with different genetic backgrounds (Italian, Ashkenazi Jewish and Japanese) that collectively support an association of ADARB1 and ADARB2 with longevity. Some SNPs in ADARB2 replicate consistently in the four populations and suggest a strong effect that is independent of the different genetic backgrounds and environments. To evaluate the functional association of these genes with lifespan, we demonstrate that inactivation of their orthologues adr-1 and adr-2 in C. elegans reduces median survival by 50%. We further demonstrate that inactivation of the argonaute gene, rde-1, a critical regulator of RNA interference, completely restores lifespan to normal levels in the context of adr-1 and adr-2 loss of function.

Conclusions/Significance

Our results suggest that RNA editors may be an important regulator of aging in humans and that, when evaluated in C. elegans, this pathway may interact with the RNA interference machinery to regulate lifespan.     

Cost‐effectiveness of Endoscopic Surveillance for Gastric Intestinal Metaplasia

Background: Patients with intestinal metaplasia (IM) are at increased risk for gastric cancer. Endoscopic surveillance has been shown to anticipate cancer diagnosis in an earlier stage. Cost‐effectiveness of endoscopic surveillance in IM patients is unknown. To assess the efficacy and cost‐effectiveness of an yearly endoscopic surveillance in patients with IM. Methods: A decision analysis model was constructed in order to compare a strategy of performing an EGD every year for a 10‐year period (surveillance strategy) following a new diagnosis of IM to a policy of nonsurveillance in a simulated cohort of 10,000 American patients. A 1.8% 10‐year cumulative incidence of gastric cancer in IM patients was estimated from the literature. Endoscopic surveillance was simulated to downstage the detected cancers by 58–84%. Costs of EGD and cancer care were estimated from Medicare reimbursement data. The main outcome measurement was the incremental cost‐effectiveness ratio. Results: The number of EGDs required to detect one cancer and to prevent one gastric cancer‐related death in the surveillance arm were 556 and 3738, respectively. The incremental cost‐effectiveness ratio of endoscopic surveillance as compared to a nonsurveillance policy was $72,519 per life‐year gained (5–95% percentiles Monte Carlo analysis: $54,843–$98,853). At sensitivity analysis, cancer incidence and the rate of downstaging were the most important variables. Conclusions: According to our simulation, the relatively high risk of cancer in patients with IM and the substantial efficacy of endoscopic surveillance in reducing cancer‐related mortality would support the cost‐effectiveness of an endoscopic surveillance program in patients with IM. Further research is needed before implementing it in the clinical practice.     

Protein Networks Reveal Detection Bias and Species Consistency When Analysed by Information-Theoretic Methods

We apply our recently developed information-theoretic measures for the characterisation and comparison of protein–protein interaction networks. These measures are used to quantify topological network features via macroscopic statistical properties. Network differences are assessed based on these macroscopic properties as opposed to microscopic overlap, homology information or motif occurrences. We present the results of a large–scale analysis of protein–protein interaction networks. Precise null models are used in our analyses, allowing for reliable interpretation of the results. By quantifying the methodological biases of the experimental data, we can define an information threshold above which networks may be deemed to comprise consistent macroscopic topological properties, despite their small microscopic overlaps. Based on this rationale, data from yeast–two–hybrid methods are sufficiently consistent to allow for intra–species comparisons (between different experiments) and inter–species comparisons, while data from affinity–purification mass–spectrometry methods show large differences even within intra–species comparisons.     

Incorporating Gravity Model Principles into Disease Mapping

The space‐time variation of disease risk, considering the closeness and availability of care units, is studied by a hierarchical Bayesian model in a gravitational formulation. The pattern of mortality for Hodgkin's lymphoma over the last twenty‐five years in the Tuscany region and the evaluation of the consequences of distance from the nearest radiation‐therapy center are described. Results show a decrease in mortality for Hodgkin's lymphoma and the attraction exercised by each care units.     

Statistical modelling of the spatial distribution of prevalence of Calicophoron daubneyi infection in sheep from central Italy

Statistical modelling for Disease Mapping and Ecological Analysis is of particular importance in veterinary parasitology because environmental characteristics can affect parasite distribution. However, the main difficulties relate to the concentration of animal populations within farms, which contrasts to the study of wild animal populations. In the present paper we report the results of a cross-sectional coprological survey designed to study the presence and distribution of the rumen fluke Calicophoron daubneyi--which causes paramphistomosis, a snail borne disease--in pastured sheep living in the Latina province of central Italy. We show how techniques derived from human epidemiology can be used to study the spatial distribution of parasite infection in animals. We proposed a hierarchical Bayesian model with random terms for unstructured variability (heterogeneity) to account for local farm characteristics and spatially structure terms (clustering) to cope with medium-large scale environmental characteristics.     

Copper depletion increases the mitochondrial-associated SOD1 in neuronal cells

The role of copper in the toxicity of mutant copper-dependent enzyme superoxide dismutase (SOD1) found in patients affected with the familial form of amyotrophic lateral sclerosis (fALS) is widely debated. Here we report that treatment of human neuroblastoma cells SH-SY5Y with a specific copper chelator, triethylene tetramine (Trien) induces the decrease of intracellular copper level, paralleled by decreased activity of SOD1. A comparable effect is observed in mouse NSC-34-derived cells, a motoneuronal model, transfected for the inducible expression of either wild-type or G93A mutant human SOD1, one of the mutations associated with fALS. In both cell types, the drop of SOD1 activity is not paralleled by the same extent of decrease in SOD1 protein content. This discrepancy can be explained by the occurrence of a fraction of copper-free SOD1 upon copper depletion, which is demonstrated by the partial recovery of the enzyme activity after the addition of copper sulphate to homogenates of SH-SY5Y cells. Furthermore, copper depletion produces the enrichment of the physiological mitochondrial fraction of SOD1 protein, in both cells models. However, increasing the fraction of mitochondrial, possibly copper-free, mutant human SOD1 does not further alter mitochondrial morphology in NSC-34-derived cells. Thus, copper deficiency is not a factor which may worsen mitochondrial damage, which is one of the earliest events in fALS associated with mutant SOD1.     

Progress in quantitative single-molecule localization microscopy

With the advent of single-molecule localization microscopy (SMLM) techniques, intracellular proteins can be imaged at unprecedented resolution with high specificity and contrast. These techniques can lead to a better understanding of cell functioning, as they allow, among other applications, counting the number of molecules of a protein specie in a single cell, studying the heterogeneity in protein spatial organization, and probing the spatial interactions between different protein species. However, the use of these techniques for accurate quantitative measurements requires corrections for multiple inherent sources of error, including: overcounting due to multiple localizations of a single fluorophore (i.e., photoblinking), undercounting caused by incomplete photoconversion, uncertainty in the localization of single molecules, sample drift during the long imaging time, and inaccurate image registration in the case of dual-color imaging. In this paper, we review recent efforts that address some of these sources of error in quantitative SMLM and give examples in the context of photoactivated localization microscopy (PALM).