Investigating mortality trends in Italy during the COVID-19 pandemic: life expectancy changes within provinces and vaccination campaign impact up to December 2022.

OBJECTIVES: We used publicly available population data from 1 January 2019 up to 31 December 2022, to investigate mortality trends in Italy during the COVID-19 pandemic, evaluating changes in life expectancy (LE) at birth within provinces and the impact of COVID-19 vaccinations. STUDY DESIGN: Aggregate data analysis. METHODS: Annual period life tables were used to estimate sex-specific LEs within provinces from 2019 to 2022. We used Arriaga decomposition to analyze the contribution of age groups (<60 years and ≥60 years) to annual LE changes. We implemented a Quasi-Poisson regression model to estimate the number of averted deaths by the achieved COVID-19 vaccination rates from January 2021 up to December 2022, simulating a counterfactual scenario where vaccine doses were not administered. RESULTS: The results revealed geographical heterogeneity in annual LE changes across Italian provinces during the pandemic. By the end of 2022, LE was below the prepandemic levels in 88% of provinces for females and in 76% for males. In addition, we estimated that the achieved vaccination rates averted 460,831 deaths (95% confidence interval: 250,976-707,920), corresponding to a 25% reduction in expected all-cause mortality. CONCLUSIONS: Overall, the study highlighted the significant role of COVID-19 vaccinations in averting a considerable number of deaths and improving LE. However, by the end of 2022, LE had not fully recovered to prepandemic levels in many provinces. This could be attributed to concurrent factors, including enduring COVID-19 pandemic effects, intense summer heat waves and early onset of seasonal flu. Further research and continuous monitoring are essential to fully comprehend long-term mortality trends and optimize public health strategies.

Enrichment for Northern European-derived multiple sclerosis risk alleles in Sardinia.

BACKGROUND: The list of genomic loci associated with multiple sclerosis (MS) susceptibility outside the major histocompatibility complex (MHC) in patients of Northern European (NE) ancestry has increased to 103. Despite the extraordinarily high MS prevalence in the isolated Sardinian population, the contribution of genetic risk factors to MS in Sardinia is largely not understood. OBJECTIVE: The objective of this paper is to examine the relevance of non-MHC MS susceptibility variants in Sardinia. METHODS: We examined a log-additive MS-specific genetic burden score (MSGB) using 110 NE-derived risk alleles in a dataset of 75 Sardinian cases, 346 Sardinian controls and 177 cases and 1967 controls from the United States (US). RESULTS: Sardinian cases demonstrate a heavier non-MHC MSGB load than Sardinian controls and US cases (p = 2E-06, p = 1E-06, respectively). Furthermore, Sardinian controls carry a heavier burden than US controls (p = 2E-14). Our results confirm the limited ability of the 110-SNP MSGB to predict disease status in Sardinia (AUROC = 0.629). CONCLUSIONS: Risk alleles discovered in samples of NE ancestry are relevant to MS in Sardinia. Our results suggest a general enrichment of MS susceptibility alleles in Sardinians, encouraging the pursuit of further studies of MS in this population.

Berberine phospholipid exerts a positive effect on the glycemic profile of overweight subjects with impaired fasting blood glucose (IFG): a randomized double-blind placebo-controlled clinical trial.

OBJECTIVE: Berberine is a plant alkaloid known to exert positive metabolic effects. Human studies have confirmed its ability to improve the lipid and glycemic profile. This study aimed to evaluate the potential benefit of oral supplementation of Berberine PhytosomeTM (2 tablets/day, 550 mg/tablet) on the metabolic profile of subjects with impaired fasting blood glucose (IFG). PATIENTS AND METHODS: A total of 49 overweight subjects, 28 females and 21 males, were randomly assigned to either the supplemented group (n=24) or placebo (n=25). We considered glycemia as the primary endpoint and total cholesterol, high-density lipoprotein (HDL), total cholesterol/HLD, low-density lipoprotein (LDL), LDL/HDL, triglycerides, insulin, glycated hemoglobin, Homeostasis Model Assessment (HOMA), ApoA, ApoB, ApoB/ApoA, androgen suppression treatment (AST), alternative lengthening of telomeres (ALT), gamma-glutamyl transferase (GGT), creatinine, and body composition by dual-energy X-ray absorptiometry (DXA) as secondary endpoints. These parameters have been assessed at baseline, after 30 days, and after 60 days. RESULTS: After two months of treatment, through the use of linear mixed effect models, a statistically significant difference between supplemented and placebo groups was observed for glycemia [ß=-0.2495% C.I. (-0.47; -0.06), p=0.004], total cholesterol [ß=-0.25, 95% C.I. (-0.45; -0.04), p=0.05], total cholesterol/HDL [ß=-0.25, 95% C.I. (-0.43; -0.06), p=0.04], triglycerides [ß=-0.14, 95% C.I. (-0.25; -0.02), p=0.05], insulin [ß=-1.78, 95% C.I. (-2.87; -0.66), p=0.009], ApoB/ApoA [ß=-0.08, 95% C.I. (-0.13; -03), p=0.004], Visceral adipose tissue (VAT) [ß=-91.50, 95% C.I. (-132.60; -48.19), p<0.0001] and fat mass [ß=-945.56, 95% C.I. (-1,424.42; -441.57), p=0.004]. CONCLUSIONS: The use of berberine had no adverse events, supporting its use as a natural alternative to pharmacological therapies in the case of IFG.

Natural Killer Response and Lipo-Metabolic Profile in Adults with Low HDL-Cholesterol and Mild Hypercholesterolemia: Beneficial Effects of Artichoke Leaf Extract Supplementation.

The aim of the present study is to evaluate the effects of 60-day artichoke leaf extract (ALE) supplementation (250mg, twice daily) on cytokines levels, natural killer cell (NK) response, and lipo-metabolic profile (HDL, LDL, and total-cholesterol, triglycerides (TG), ApoB, ApoA, lipid accumulation product (LAP), glucose, insulin, and homeostasis model assessment of insulin resistance (HOMA-IR)) in twenty adults (9/11 males/females, age=49.10 ± 13.74 years, and BMI=33.12 ± 5.14 kg/m2) with low HDL-C and mild hypercholesterolemia. Hierarchical generalized linear model, adjusted for sex, BMI, and age, has been used to evaluate pre-post treatment changes. A significant increase for HDL-C (ß=0.14, p=0.0008) and MCP-1 (ß=144.77, p=0.004) and a significant decrease for ApoB/ApoA (ß=-0.07, p=0.03), total-C/HDL-C ratio (ß=-0.58, p<0.001), and NK response at stimulus low (ß=0.43, p=0.04), medium (ß=0.40, p<0.001), and high (ß=0.42, p=0.001) have been found. These results support the benefits of ALE supplementation on metabolic profile.

Multifactorial analysis of the stochastic epigenetic variability in cord blood confirmed an impact of common behavioral and environmental factors but not of in vitro conception.

Background: An increased incidence of imprint-associated disorders has been reported in babies born from assisted reproductive technology (ART). However, previous studies supporting an association between ART and an altered DNA methylation status of the conceived babies have been often conducted on a limited number of methylation sites and without correction for critical potential confounders. Moreover, all the previous studies focused on the identification of methylation changes shared among subjects while an evaluation of stochastic differences has never been conducted. This study aims to evaluate the effect of ART and other common behavioral or environmental factors associated with pregnancy on stochastic epigenetic variability using a multivariate approach. Results: DNA methylation levels of cord blood from 23 in vitro and 41 naturally conceived children were analyzed using the Infinium HumanMethylation450 BeadChips. After multiple testing correction, no statistically significant difference emerged in the number of cord blood stochastic epigenetic variations or in the methylation levels between in vitro- and in vivo-conceived babies. Conversely, four multiple factor analysis dimensions summarizing common phenotypic, behavioral, or environmental factors (cord blood cell composition, pre or post conception supplementation of folates, birth percentiles, gestational age, cesarean section, pre-gestational mother's weight, parents' BMI and obesity status, presence of adverse pregnancy outcomes, mother's smoking status, and season of birth) were significantly associated with stochastic epigenetic variability. The stochastic epigenetic variation analysis allowed the identification of a rare imprinting defect in the locus GNAS in one of the babies belonging to the control population, which would not have emerged using a classical case-control association analysis. Conclusions: We confirmed the effect of several common behavioral or environmental factors on the epigenome of newborns and described for the first time an epigenetic effect related to season of birth. Children born after ART did not appear to have an increased risk of genome-wide changes in DNA methylation either at specific loci or randomly scattered throughout the genome. The inability to identify differences between cases and controls suggests that the number of stochastic epigenetic variations potentially induced by ART was not greater than that naturally produced in response to maternal behavior or other common environmental factors.

Anti-beta 2 glycoprotein I antibodies and the risk of myocardial infarction in young premenopausal women.

BACKGROUND: Contrasting data have been reported on the association between the presence of anti-phospholipid antibodies (aPL) and arterial thrombotic events, particularly those in coronary arteries. This discrepancy is perhaps related to the confounding effect of traditional risk factors. Among them, coronary atherosclerosis appears to be the most important in studies conducted in middle-aged and elderly patients. OBJECTIVE: To minimize such confounding effects, a multicenter case-control study on the association between aPL and myocardial infarction (MI) was carried out in a rare cohort of young premenopausal women. METHODS: We evaluated 172 cases hospitalized for a first MI before the age of 45 years and 172 controls individually matched with cases for age, sex and geographical origin. Clinical and laboratory data were collected and levels of anti-cardiolipin (aCL), anti-beta2 glycoprotein I (anti-beta2GPI) and anti-nuclear antibodies (ANA) were measured. RESULTS: A significant association between MI and IgG/IgM anti-beta2GPI antibodies was observed; the results were confirmed after adjusting for smoking and hypertension (anti-beta2GPI IgG OR = 2.47, 95% CI 1.81-3.38; anti-beta2GPI IgM 4th quartile OR 3.68, 95% CI 1.69-8.02). The association between anti-beta2GPI antibodies and MI was detected in both subgroups with and without coronary artery stenosis. Whereas the association of aCL IgG with MI was modest, ANA showed no significant association with MI. No aPL were found in unselected patients (mainly males) who recently developed acute MI. CONCLUSIONS: Anti-beta2GPI antibodies are a significant risk factor for MI in young premenopausal women independently of other risk factors, including the degree of coronary artery stenosis.

Bayesian mapping of multiple sclerosis prevalence in the province of Pavia, northern Italy.

The geographical analysis of a disease risk is particularly difficult when the disease is non-frequent and the area units are small. The practical use of the Bayesian modelling, instead of the classical frequentist one, is applied to study the geographical variation of multiple sclerosis (MS) across the province of Pavia, Northern Italy. 464 MS-affected individuals resident in the province of Pavia were identified on December 31st 2000. The overall prevalence was 94 per 100,000 inhabitants. This estimate indicates an increasing MS prevalence in the province, in accordance with the vast majority of the Italian areas where prevalence studies have been repeated. We mapped the geographical variation of MS prevalence across the 190 communes of the province both with a classical approach and a Bayesian approach. The frequentist approach produced an extremely dishomogeneous map, while the Bayesian map was much smoother and more interpretable. Our study underlines the usefulness of Bayesian methods to obtain reliable maps of disease prevalence and to identify possible clusters of disease where to carry out further epidemiological investigations.

Tissue plasminogen activator antigen is strongly associated with myocardial infarction in young women.

Women who develop acute myocardial infarction (AMI) at a young age have fewer classical risk factors and less coronary stenosis than older women. In this rare population, it is plausible that a heightened hemostatic system may play an important mechanistic role in thrombus formation and in the development of AMI. We chose to investigate whether or not there is an association between premature AMI and the plasma concentrations of five hemostatic measurements that had been previously established as risk factors for AMI, and of the inflammation marker C-reactive protein (CRP). Women who had survived AMI at the age of 45 years or less (n = 141) were drawn from those admitted to 125 Italian coronary care units over a 3-year period. In them, and in an equal number of controls, plasma levels of immunoreactive tissue plasminogen activator (tPA), plasminogen activation inhibitor 1 (PAI-1), von Willebrand factor (VWF), fibrinogen, D-dimer and CRP were measured. Higher levels of VWF, fibrinogen, CRP and tPA were associated with AMI. After adjustment for both classical and hemostatic risk factors, only tPA maintained an independent association with AMI: the odds ratios (taken as an index of relative risk) for tPA values in the middle and higher tertiles were 2.86 (CI 1.63-5.02) and 8.18 (CI 2.66-25.20), respectively. In conclusion, there is a strong association between non-fatal AMI and increased plasma levels of tPA antigen. This finding is thought to be the expression of a reduced rather than enhanced fibrinolytic activity.

Spatial correlation in ecological analysis.

This paper presents a statistical approach, originally developed for mapping disease risk, to ecological regression analysis in the presence of spatial autocorrelated extra-Poisson variation. An insight into the effect of allowing for spatial autocorrelation on the relationship between disease rates and explanatory variables is given. Examples based on cancer frequency in Scotland and Sardinia are used to illustrate the interpretation of regression coefficient and further methodological issues.

Childhood leukemia in south-west Sardinia (Italy).

AIM AND BACKGROUND: Public concern on an increased incidence of childhood leukemia in SW Sardinia prompted the authors to an epidemiological investigation. METHODS: Incident childhood neoplasms observed in the Cagliari province (Sardinia--Italy) in 1974-1989 were registered. Expected cases of the most frequent childhood cancers were calculated for each town, based on the sex-and age-specific incidence rates in the province. RESULTS: An excess risk of childhood acute lymphoblastic leukemia (ALL) was observed in Carbonia, a town located in the SW part of the province. The risk was highest in 1983-85, when 7 cases occurred versus 0.8 expected (RR = 8.7; 95% C.I. = 4.6, 16.3). No spatial clustering of ALL cases was observed within the town. CONCLUSIONS: A significantly higher than expected incidence of childhood ALL was observed in the town of Carbonia in 1983-85. In alternative to chance, possible exposure to environmental pollutants from a near industrial settlement is discussed as the cause of the observed excess, but it is far to be proven. Other hypotheses, including a viral infection in a population with increased susceptibility, as suggested for new urban settlements, cannot be discarded.

[Bayesian analysis of ecological studies]. / Analisi bayesiana di studi ecologici.

Studying the space-time variation of risk for a given disease may give etiological clues and suggestions for planning further studies to investigate the underlying causes. When the observed events are rare, approaches based on maximum likelihood may lead to unstable and largely uninformative estimates of risk and of its time trend due to Poisson sampling variation. In this paper we propose a general Bayesian model for analyzing the variation of risk in space and time. We applied the Bayesian model to the analysis of the geographical variation of breast cancer mortality, to an ecological study on the correlation between lung cancer mortality and degree of urbanization and industrialization and to the analysis of the space-time variation of cumulative prevalence of Insulin Dependent Diabetes Mellitus (IDDM) as observed in military examinations between 1954 and 1989.

[The use of a multistage model in the analysis of the occupational risks in those exposed to hexavalent chromium]. / Utilizzo del modello multistage nell'analisi dei rischi professionali in esposti a cromo esavalente.

A brief presentation is made of the theory underlying the multistage model of Armitage and Doll and its implications in assessing the effect of exposure to a carcinogen. The theory foresees different relationships between cancer risk and the dependent time variables (time from beginning of exposure, age at start of employment, duration of exposure and time since end of exposure) according to whether the carcinogen acts in the early or late stages of the process of cell transformation leading to tumour formation. The trend in risk of death from lung cancer was studied in a cohort of workers exposed to hexavalent chromium followed up between 1948 and 1985. The results, referred to the multistage model, indicate that hexavalent chromium probably acts in the later stages of the cell transformation process; the implications of this hypothesis for prevention and/or occupational safety strategies are discussed.

Localization and behaviors in null mice suggest that ASIC1 and ASIC2 modulate responses to aversive stimuli.

Acid-sensing ion channels (ASICs) generate H(+) -gated Na(+) currents that contribute to neuronal function and animal behavior. Like ASIC1, ASIC2 subunits are expressed in the brain and multimerize with ASIC1 to influence acid-evoked currents and facilitate ASIC1 localization to dendritic spines. To better understand how ASIC2 contributes to brain function, we localized the protein and tested the behavioral consequences of ASIC2 gene disruption. For comparison, we also localized ASIC1 and studied ASIC1(-/-) mice. ASIC2 was prominently expressed in areas of high synaptic density, and with a few exceptions, ASIC1 and ASIC2 localization exhibited substantial overlap. Loss of ASIC1 or ASIC2 decreased freezing behavior in contextual and auditory cue fear conditioning assays, in response to predator odor and in response to CO2 inhalation. In addition, loss of ASIC1 or ASIC2 increased activity in a forced swim assay. These data suggest that ASIC2, like ASIC1, plays a key role in determining the defensive response to aversive stimuli. They also raise the question of whether gene variations in both ASIC1 and ASIC2 might affect fear and panic in humans.

Empirical Bayes versus fully Bayesian analysis of geographical variation in disease risk.

This paper reviews methods for mapping geographical variation in disease incidence and mortality. Recent results in Bayesian hierarchical modelling of relative risk are discussed. Two approaches to relative risk estimation, along with the related computational procedures, are described and compared. The first is an empirical Bayes approach that uses a technique of penalized log-likelihood maximization; the second approach is fully Bayesian, and uses an innovative stochastic simulation technique called the Gibbs sampler. We chose to map geographical variation in breast cancer and Hodgkin's disease mortality as observed in all the health care districts of Sardinia, to illustrate relevant problems, methods and techniques.

Bayesian estimates of disease maps: how important are priors?

In the fully Bayesian (FB) approach to disease mapping the choice of the hyperprior distribution of the dispersion parameter is a key issue. In this context we investigated the sensitivity of the rate ratio estimates to the choice of the hyperprior via a simulation study. We also compared the performance of the FB approach to mapping disease risk to the conventional approach of mapping maximum likelihood (ML) estimates and p-values. The study was modelled on the incidence data of insulin dependent diabetes mellitus (IDDM) as observed in the communes of Sardinia.

Bayesian trio models for association in the presence of genotyping errors.

Errors in genotyping can greatly affect family-based association studies. If a mendelian inconsistency is detected, the family is usually removed from the analysis. This reduces power, and may introduce bias. In addition, a large proportion of genotyping errors remain undetected, and these also reduce power. We present a Bayesian framework for performing association studies with SNP data on samples of trios consisting of parents with an affected offspring, while allowing for the presence of both detectable and undetectable genotyping errors. This framework also allows for the inclusion of missing genotypes. Associations between the SNP and disease were modelled in terms of the genotypic relative risks. The performances of the analysis methods were investigated under a variety of models for disease association and genotype error, looking at both power to detect association and precision of genotypic relative risk estimates. As expected, power to detect association decreased as genotyping error probability increased. Importantly, however, analyses allowing for genotyping error had similar power to standard analyses when applied to data without genotyping error. Furthermore, allowing for genotyping error yielded relative risk estimates that were approximately unbiased, together with 95% credible intervals giving approximately correct coverage. The methods were also applied to a real dataset: a sample of schizophrenia cases and their parents genotyped at SNPs in the dysbindin gene. The analysis methods presented here require no prior information on the genotyping error probabilities, and may be fitted in WinBUGS.