Towards a deeper understanding of protein sequence evolution

Most bioinformatic analyses start by building sequence alignments by means of scoring matrices. An implicit approximation on which many scoring matrices are built is that protein sequence evolution is considered a sequence of Point Accepted Mutations (PAM) (Dayhoff et al., 1978), in which each substitution happens independently of the history of the sequence, namely with a probability that depends only on the initial and final amino acids. But different protein sites evolve at a different rate (Echave et al., 2016) and this feature, though included in many phylogenetic reconstruction algorithms, is generally neglected when building or using substitution matrices. Moreover, substitutions at different protein sites are known to be entangled by coevolution (de Juan et al., 2013). This thesis is devoted to the analysis of the consequences of neglecting these effects and to the development of models of protein sequence evolution capable of incorporating them. We introduce a simple procedure that allows including the among-site rate variability in PAM-like scoring matrices through a mean-field-like framework, and we show that rate variability leads to non trivial evolutions when considering whole protein sequences. We also propose a procedure for deriving a substitution rate matrix from Single Nucleotide Polymorphisms (SNPs): we first test the statistical compatibility of frequent genetic variants within a species and substitutions accumulated between species; moreover we show that the matrix built from SNPs faithfully describes substitution rates for short evolutionary times, if rate variability is taken into account. Finally, we present a simple model, inspired by coevolution, capable of predicting at the same time the along-chain correlation of substitutions and the time variability of substitution rates. This model is based on the idea that a mutation at a site enhances the probability of fixing mutations in the other protein sites in its spatial proximity, but only for a certain amount of time

Dynamic properties of coarse-grained models of linear and circular DNA in nanochannels

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Non-Markovian effects on protein sequence evolution due to site dependent substitution rates

Many models of protein sequence evolution, in particular those based on Point Accepted Mutation (PAM) matrices, assume that its dynamics is Markovian. Nevertheless, it has been observed that evolution seems to proceed differently at different time scales, questioning this assumption. In 2011 Kosiol and Goldman proved that, if evolution is Markovian at the codon level, it can not be Markovian at the amino acid level. However, it remains unclear up to which point the Markov assumption is verified at the codon level

SLC22A3 polymorphisms do not modify pancreatic cancer risk, but may influence overall patient survival

Expression of the solute carrier (SLC) transporter SLC22A3 gene is associated with overall survival of pancreatic cancer patients. This study tested whether genetic variability in SLC22A3 associates with pancreatic cancer risk and prognosis. Twenty four single nucleotide polymorphisms (SNPs) tagging the SLC22A3 gene sequence and regulatory elements were selected for analysis. Of these, 22 were successfully evaluated in the discovery phase while six significant or suggestive variants entered the validation phase, comprising a total study number of 1,518 cases and 3,908 controls. In the discovery phase, rs2504938, rs9364554, and rs2457571 SNPs were significantly associated with pancreatic cancer risk. Moreover, rs7758229 associated with the presence of distant metastases, while rs512077 and rs2504956 correlated with overall survival of patients. Although replicated, the association for rs9364554 did not pass multiple testing corrections in the validation phase. Contrary to the discovery stage, rs2504938 associated with survival in the validation cohort, which was more pronounced in stage IV patients. In conclusion, common variation in the SLC22A3 gene is unlikely to significantly contribute to pancreatic cancer risk. The rs2504938 SNP in SLC22A3 significantly associates with an unfavorable prognosis of pancreatic cancer patients. Further investigation of this SNP effect on the molecular and clinical phenotype is warranted

Molecular profile and its clinical impact of IDH1 mutated versus IDH1 wild type intrahepatic cholangiocarcinoma

IDH1-mutated cholangiocarcinomas (CCAs) are an interesting group of neoplasia with particular behavior and therapeutic implications. The aim of the present work is to highlight the differences characterizing IDH1m and IDH1wt CCAs in terms of genomic landscape. 284 patients with iCCA treated for resectable, locally advanced or metastatic disease were selected and studied with the FOUNDATION Cdx technology. A comparative genomic analysis and survival analyses for the most relevant altered genes were performed between IDH1m and IDH1wt patients. Overall, 125 patients were IDH1m and 122 IDH1wt. IDH1m patients showed higher mutation rates compared to IDH1wt in CDKN2B and lower mutation rates in several genes including TP53, FGFR2, BRCA2, ATM, MAP3K1, NOTCH2, ZNF703, CCND1, NBN, NF1, MAP3KI3, and RAD21. At the survival analysis, IDH1m and IDH1wt patients showed no statistically differences in terms of survival outcomes, but a trend in favor of IDH1wt patients was observed. Differences in prognostic values of the most common altered genes were reported. In surgical setting, in IDH1m group the presence of CDKN2A and CDKN2B mutations negatively impact DFS, whereas the presence of CDKN2A, CDKN2B, and PBRM1 mutations negatively impact OS. In advanced setting, in the IDH1m group, the presence of KRAS/NRAS and TP53 mutations negatively impact PFS, whereas the presence of TP53 and PIK3CA mutations negatively impact OS; in the IDH1wt group, only the presence of MTAP mutation negatively impact PFS, whereas the presence of TP53 mutation negatively impact OS. We highlighted several molecular differences with distinct prognostic implications between IDH1m and IDH1wt patients

Common germline variants within the CDKN2A/2B region affect risk of pancreatic neuroendocrine tumors

Pancreatic neuroendocrine tumors (PNETs) are heterogeneous neoplasms which represent only 2% of all pancreatic neoplasms by incidence, but 10% by prevalence. Genetic risk factors could have an important role in the disease aetiology, however only a small number of case control studies have been performed yet. To further our knowledge, we genotyped 13 SNPs belonging to the pleiotropic CDKN2A/B gene region in 320 PNET cases and 4436 controls, the largest study on the disease so far. We observed a statistically significant association between the homozygotes for the minor allele of the rs2518719 SNP and an increased risk of developing PNET (ORhom = 2.08, 95% CI 1.05-4.11, p = 0.035). This SNP is in linkage disequilibrium with another polymorphic variant associated with increased risk of several cancer types. In silico analysis suggested that the SNP could alter the sequence recognized by the Neuron-Restrictive Silencer Factor (NRSF), whose deregulation has been associated with the development of several tumors. The mechanistic link between the allele and the disease has not been completely clarified yet but the epidemiologic evidences that link the DNA region to increased cancer risk are convincing. In conclusion, our results suggest rs2518719 as a pleiotropic CDKN2A variant associated with the risk of developing PNETs

A Hydrogenated amorphous silicon detector for Space Weather Applications

The characteristics of a hydrogenated amorphous silicon (a-Si:H) detector are presented here for monitoring in space solar flares and the evolution of large energetic proton events up to hundreds of MeV. The a-Si:H presents an excellent radiation hardness and finds application in harsh radiation environments for medical purposes, for particle beam characterization and in space weather science and applications. The critical flux detection threshold for solar X rays, soft gamma rays, electrons and protons is discussed in detail.Comment: 32 pages, 13 figures, submitted to Experimental Astronom

Acute Delta Hepatitis in Italy spanning three decades (1991–2019): Evidence for the effectiveness of the hepatitis B vaccination campaign

Updated incidence data of acute Delta virus hepatitis (HDV) are lacking worldwide. Our aim was to evaluate incidence of and risk factors for acute HDV in Italy after the introduction of the compulsory vaccination against hepatitis B virus (HBV) in 1991. Data were obtained from the National Surveillance System of acute viral hepatitis (SEIEVA). Independent predictors of HDV were assessed by logistic-regression analysis. The incidence of acute HDV per 1-million population declined from 3.2 cases in 1987 to 0.04 in 2019, parallel to that of acute HBV per 100,000 from 10.0 to 0.39 cases during the same period. The median age of cases increased from 27 years in the decade 1991-1999 to 44 years in the decade 2010-2019 (p < .001). Over the same period, the male/female ratio decreased from 3.8 to 2.1, the proportion of coinfections increased from 55% to 75% (p = .003) and that of HBsAg positive acute hepatitis tested for by IgM anti-HDV linearly decreased from 50.1% to 34.1% (p < .001). People born abroad accounted for 24.6% of cases in 2004-2010 and 32.1% in 2011-2019. In the period 2010-2019, risky sexual behaviour (O.R. 4.2; 95%CI: 1.4-12.8) was the sole independent predictor of acute HDV; conversely intravenous drug use was no longer associated (O.R. 1.25; 95%CI: 0.15-10.22) with this. In conclusion, HBV vaccination was an effective measure to control acute HDV. Intravenous drug use is no longer an efficient mode of HDV spread. Testing for IgM-anti HDV is a grey area requiring alert. Acute HDV in foreigners should be monitored in the years to come

DMTs and Covid-19 severity in MS: a pooled analysis from Italy and France

We evaluated the effect of DMTs on Covid-19 severity in patients with MS, with a pooled-analysis of two large cohorts from Italy and France. The association of baseline characteristics and DMTs with Covid-19 severity was assessed by multivariate ordinal-logistic models and pooled by a fixed-effect meta-analysis. 1066 patients with MS from Italy and 721 from France were included. In the multivariate model, anti-CD20 therapies were significantly associated (OR = 2.05, 95%CI = 1.39–3.02, p < 0.001) with Covid-19 severity, whereas interferon indicated a decreased risk (OR = 0.42, 95%CI = 0.18–0.99, p = 0.047). This pooled-analysis confirms an increased risk of severe Covid-19 in patients on anti-CD20 therapies and supports the protective role of interferon

Polygenic and multifactorial scores for pancreatic ductal adenocarcinoma risk prediction

Most cases of pancreatic ductal adenocarcinoma (PDAC) are asymptomatic in early stages, and the disease is typically diagnosed in advanced phases, resulting in very high mortality. Tools to identify individuals at high risk of developing PDAC would be useful to improve chances of early detection