The association of high-sensitivity c-reactive protein and other biomarkers with cardiovascular disease in patients treated for HIV: a nested case–control study

Background: Elevated high-sensitivity C-reactive protein (hsCRP) increases the risk of cardiovascular disease (CVD) in the general population, but its role as a predictive marker in HIV-positive patients remains unclear. Aim of the study was to evaluate whether hsCRP or other biomarkers are independent predictors of CVD risk in HIV-infected patients.Methods: Retrospective, nested case-control study. HIV-positive men and women (35-69 years of age) receiving combination antiretroviral therapy (cART) were included. Cases (n = 35) had a major CVD event. Controls (n = 74) free from CVD events for at least 5 years from starting ART were matched on diabetes and smoking. HsCRP, D-dimer, P-selectin, interleukin-6 (IL-6), tissue plasminogen activator, plasminogen activator inhibitor-1 levels were measured.Results: High hsCRP was associated with CVD risk, independently of traditional cardiovascular risk factors, HIV replication and the type of ART received at the time of sampling (adjusted odds ratio 8.00 [1.23-51.94] comparing >3.3 mg/L with <0.9 mg/L; P = 0.03). Higher IL-6 and P-selectin levels were also independently associated with increased CVD risk, although the association was weaker than for hsCRP. Higher total cholesterol and lower HDL cholesterol increased CVD risk, independent of hsCRP.Conclusion: hsCRP may be a useful additional biomarker to predict CVD risk in HIV-infected patients receiving cART

Clinical Network for Big Data and Personalized Health: Study Protocol and Preliminary Results

The use of secondary hospital-based clinical data and electronical health records (EHR) represent a cost-efficient alternative to investigate chronic conditions. We present the Clinical Network Big Data and Personalised Health project, which collects EHRs for patients accessing hospitals in Central-Southern Italy, through an integrated digital platform to create a digital hub for the collection, management and analysis of personal, clinical and environmental information for patients, associated with a biobank to perform multi-omic analyses. A total of 12,864 participants (61.7% women, mean age 52.6 ± 17.6 years) signed a written informed consent to allow access to their EHRs. The majority of hospital access was in obstetrics and gynaecology (36.3%), while the main reason for hospitalization was represented by diseases of the circulatory system (21.2%). Participants had a secondary education (63.5%), were mostly retired (25.45%), reported low levels of physical activity (59.6%), had low adherence to the Mediterranean diet and were smokers (30.2%). A large percentage (35.8%) were overweight and the prevalence of hypertension, diabetes and hyperlipidemia was 36.4%, 11.1% and 19.6%, respectively. Blood samples were retrieved for 8686 patients (67.5%). This project is aimed at creating a digital hub for the collection, management and analysis of personal, clinical, diagnostic and environmental information for patients, and is associated with a biobank to perform multi-omic analyses

Prevalence and cardiovascular risk profile of chronic kidney disease in Italy: Results of the 2008-12 National Health Examination Survey

Background National surveys in countries outside Europe have reported a high prevalence (11-13%) of chronic kidney disease (CKD). Studies in Europe have provided a variable prevalence likely due to differences in study design, including age and extent of geographic areas, equation used to evaluate estimated glomerular filtration rate (eGFR) and CKD stages examined. Methods The 2008-12 National Health Examination Survey in Italy randomly extracted samples from the general population aged 35-79 years, stratified by age and gender, from the resident list of each Italian region (440 persons/1.5 million of residents). We estimated the prevalence of CKD by means of urinary albumin: creatinine ratio and eGFR (CKD-EPI equation-enzymatic assay of serum creatinine). Cardiovascular (CV) risk profile was also evaluated. Results Three thousand eight hundred and forty-eight men and 3704 women were examined. In the whole population, mean age was 57 ± 12 and 56 ± 12 years in men and women, respectively; hypertension was prevalent in men and women, respectively (56 and 43%) and the same held true for overweight (48 and 33%), obesity (26 and 27%), diabetes (14 and 9%) and smoking (21 and 18%), whereas CV disease was less frequent (9 and 6%). Overall, the prevalence of CKD (95% confidence interval) was 7.05% (6.48-7.65). Early stages constituted 59% of the CKD population [Stage G1-2 A2-3: 4.16% (3.71-4.61) and Stage G3-5: 2.89% (2.51-3.26)]. At multivariate regression analysis, age, obesity, hypertension, diabetes, CV disease and smoking were all independent correlates of CKD. Conclusions CKD has a relatively lower prevalence in Italy, in particular for advanced stages, when compared with similar national surveys outside Europe. This occurs despite older age and unfavourable CV risk profile of the whole population

Blood-based biological ageing and red cell distribution width are associated with prevalent Parkinson’s disease: findings from a large Italian population cohort

Background Aging clocks tag the actual underlying age of an organism and its discrepancy with chronological age and have been reported to predict incident disease risk in the general population. However, the relationship with neurodegenerative risk and in particular with Parkinson's Disease (PD) remains unclear, with few discordant findings reporting associations with both incident and prevalent PD risk.Objective To clarify this relationship, we computed a common aging clock based on blood markers and tested the resulting discrepancy with chronological age (Delta PhenoAge) for association with both incident and prevalent PD risk.Methods In a large Italian population cohort - the Moli-sani study (N=23,437; age &gt;= 35 years; 52% women) - we carried out both Cox Proportional Hazards regressions modelling Delta PhenoAge as exposure and incident PD as outcome, and linear models testing prevalent PD as exposure and Delta PhenoAge as outcome. All models were incrementally adjusted for age, sex, education level completed and other risk/protective factors previously associated with PD risk in the same cohort (prevalent dysthyroidism, hypertension, diabetes, use of oral contraceptives, exposure to paints, daily coffee intake and cigarette smoking).Results No significant association between incident PD risk (209 cases, median (IQR) follow-up time 11.19 (2.03) years) and PhenoAging was observed (Hazard Ratio [95% Confidence Interval] = 0.98 [0.71; 1.37]). However, a small but significant increase of Delta PhenoAge was observed in prevalent PD cases vs healthy subjects (beta (Standard Error) = 1.39 (0.70)). An analysis of each component biomarker of PhenoAge revealed a significant positive association of prevalent PD status with red cell distribution width (RDW; beta (SE) = 0.46 (0.18)). All the remaining markers did not show any significant evidence of association.Conclusion The reported evidence highlights systemic effects of prevalent PD status on biological aging and red cell distribution width. Further cohort and functional studies may help shedding a light on the related pathways altered at the organism level in prevalent PD, like red cells variability, inflammatory and oxidative stress mechanisms

Association of nutritional glycaemic indices with global DNA methylation patterns: results from the Moli-sani cohort

Background: High dietary glycaemic index (GI) and load (GL) have been associated with increased risk of various cardiometabolic conditions. Among the molecular potential mechanisms underlying this relationship, DNA methylation has been studied, but a direct link between high GI and/or GL of diet and global DNA methylation levels has not been proved yet. We analyzed the associations between GI and GL and global DNA methylation patterns within an Italian population. Results: Genomic DNA methylation (5mC) and hydroxymethylation (5hmC) levels were measured in 1080 buffy coat samples from participants of the Moli-sani study (mean(SD) = 54.9(11.5) years; 52% women) via ELISA. A 188-item Food Frequency Questionnaire was used to assess food intake and dietary GI and GL for each participant were calculated. Multiple linear regressions were used to investigate the associations between dietary GI and GL and global 5mC and 5hmC levels, as well as the proportion of effect explained by metabolic and inflammatory markers. We found negative associations of GI with both 5mC (β (SE) = - 0.073 (0.027), p = 0.007) and 5hmC (- 0.084 (0.030), p = 0.006), and of GL with 5mC (- 0.14 (0.060), p = 0.014). Circulating biomarkers did not explain the above-mentioned associations. Gender interaction analyses revealed a significant association of the gender-x-GL interaction with 5mC levels, with men showing an inverse association three times as negative as in women (interaction β (SE) = - 0.16 (0.06), p = 0.005). Conclusions: Our findings suggest that global DNA methylation and hydroxymethylation patterns represent a biomarker of carbohydrate intake. Based on the differential association of GL with 5mC between men and women, further gender-based separate approaches are warranted

Nut consumption is inversely associated with both cancer and total mortality in a Mediterranean population: prospective results from the Moli-sani study

AbstractNut intake has been associated with reduced inflammatory status and lower risk of CVD and mortality. The aim of this study was to examine the relationship between nut consumption and mortality and the role of inflammation. We conducted a population-based prospective investigation on 19 386 subjects enrolled in the Moli-sani study. Food intake was recorded by the Italian version of the European Project Investigation into Cancer and Nutrition FFQ. C-reactive protein, leucocyte and platelet counts and the neutrophil:lymphocyte ratio were used as biomarkers of low-grade inflammation. Hazard ratios (HR) were calculated using multivariable Cox proportional hazard models. During a median follow-up of 4·3 years, 334 all-cause deaths occurred. As compared with subjects who never ate nuts, rare intake (≤2 times/month) was inversely associated with mortality (multivariable HR=0·68; 95 % CI 0·54, 0·87). At intake ≥8 times/month, a greater protection was observed (HR=0·53; 0·32, 0·90). Nut intake (v. no intake) conveyed a higher protection to individuals poorly adhering to the Mediterranean diet (MD). A significant reduction in cancer deaths (HR=0·64; 95 % CI 0·44, 0·94) was also observed, whereas the impact on CVD deaths was limited to an inverse, but not significant, trend. Biomarkers of low-grade inflammation were reduced in nut consumers but did not account for the association with mortality. In conclusion, nut intake was associated with reduced cancer and total mortality. The protection was stronger in individuals with lower adherence to MD, whereas it was similar in high-risk groups (diabetics, obese, smokers or those with the metabolic syndrome), as compared with low-risk subjects. Inflammation did not explain the observed relationship.</jats:p

Machine-learning prediction model for acute skin toxicity after breast radiation therapy using spectrophotometry

PurposeRadiation-induced skin toxicity is a common and distressing side effect of breast radiation therapy (RT). We investigated the use of quantitative spectrophotometric markers as input parameters in supervised machine learning models to develop a predictive model for acute radiation toxicity. Methods and materialsOne hundred twenty-nine patients treated for adjuvant whole-breast radiotherapy were evaluated. Two spectrophotometer variables, i.e. the melanin (I-M) and erythema (I-E) indices, were used to quantitatively assess the skin physical changes. Measurements were performed at 4-time intervals: before RT, at the end of RT and 1 and 6 months after the end of RT. Together with clinical covariates, melanin and erythema indices were correlated with skin toxicity, evaluated using the Radiation Therapy Oncology Group (RTOG) guidelines. Binary group classes were labeled according to a RTOG cut-off score of &gt;= 2. The patient's dataset was randomly split into a training and testing set used for model development/validation and testing (75%/25% split). A 5-times repeated holdout cross-validation was performed. Three supervised machine learning models, including support vector machine (SVM), classification and regression tree analysis (CART) and logistic regression (LR), were employed for modeling and skin toxicity prediction purposes. ResultsThirty-four (26.4%) patients presented with adverse skin effects (RTOG &gt;= 2) at the end of treatment. The two spectrophotometric variables at the beginning of RT (I-M,I-T0 and I-E,I-T0), together with the volumes of breast (PTV2) and boost surgical cavity (PTV1), the body mass index (BMI) and the dose fractionation scheme (FRAC) were found significantly associated with the RTOG score groups (p&lt;0.05) in univariate analysis. The diagnostic performances measured by the area-under-curve (AUC) were 0.816, 0.734, 0.714, 0.691 and 0.664 for IM, IE, PTV2, PTV1 and BMI, respectively. Classification performances reported precision, recall and F1-values greater than 0.8 for all models. The SVM classifier using the RBF kernel had the best performance, with accuracy, precision, recall and F-score equal to 89.8%, 88.7%, 98.6% and 93.3%, respectively. CART analysis classified patients with I-M,I-T0 &gt;= 99 to be associated with RTOG &gt;= 2 toxicity; subsequently, PTV1 and PTV2 played a significant role in increasing the classification rate. The CART model provided a very high diagnostic performance of AUC=0.959. ConclusionsSpectrophotometry is an objective and reliable tool able to assess radiation induced skin tissue injury. Using a machine learning approach, we were able to predict grade RTOG &gt;= 2 skin toxicity in patients undergoing breast RT. This approach may prove useful for treatment management aiming to improve patient quality of life

Dietary Macronutrient Composition and Risk of Radiation-Induced Acute Skin Toxicity in Women with Breast Cancer: Results from the ATHENA Project

Background: The impact of the dietary macronutrient composition and its subcomponents (saccharides, fatty acids, and protein sources) on radiation-induced acute skin toxicity (AST) in breast cancer (BC) patients is unknown. Hence, we examined the association between dietary macronutrients and their subcomponents and the risk of ≥grade 2 (G2) AST post-radiotherapy among women with BC. Methods: An observational study was conducted among 161 BC patients treated with radiotherapy and enrolled in the ATHENA project in Italy. Habitual dietary intake was assessed at study entry (T0) using a 188-item food frequency questionnaire (FFQ). AST was measured at T1 (after 3 or 5 weeks of radiotherapy) and defined according to the Radiation Therapy Oncology Group criteria. A prospective analysis used multivariable-adjusted logistic regression models to examine the association between the dietary macronutrient composition and its subcomponents at T0 and the odds of ≥G2 AST post-radiotherapy. Results: ≥G2 AST post-radiotherapy was observed in 43 (27%) patients. Among dietary macronutrient models, a higher intake of dietary carbohydrates was positively associated with a 30% higher odds of ≥G2 AST post-radiotherapy (OR = 1.30; 95% CI 1.01 to 1.67; for 30 g/d). Conversely, a higher dietary protein intake was inversely associated with a 76% lower odds of ≥G2 AST post-radiotherapy (OR = 0.24; 95% CI 0.06 to 0.91; for 30 g/d). There was no association with dietary fat. In macronutrient subcomponent models, only animal protein was inversely associated with a 51% lower odds of ≥G2 AST post-radiotherapy (0.49; 95% CI 0.25 to 0.95; for 15 g/d). Conclusions: Dietary carbohydrates were associated with a higher risk of radiation-induced AST among women with BC, whereas dietary protein, especially animal protein, was associated with a lower risk. Cautiously balancing carbohydrate and protein intakes could be a part of the clinical management strategy for ≥G2 AST reduction post-radiotherapy among BC women

The association between hypoalbuminemia and risk of death due to cancer and vascular disease in individuals aged 65 years and older: findings from the prospective Moli-sani cohort study

Background Serum albumin is inversely associated with overall mortality, but its association with specific causes of death remains uncertain. This study aims to investigate whether hypoalbuminemia, defined as serum albumin levels &lt;= 35 g/L, is associated with mortality specifically attributed to cancer and/or vascular diseases. Methods Serum albumin levels were measured in the population-based, prospective cohort of the Moli-sani study, established between 2005 and 2010. Hypoalbuminemia was defined as serum albumin levels &lt;= 35 g/L. Cause-specific mortality was assessed using the validated Italian mortality registry and coded according to the International Classification of Diseases, Revision 9. Over a median follow-up period of 13.1 years, the relationship between serum albumin and mortality, adjusted for covariates, was investigated using competing-risk survival analysis. Findings The analysed cohort comprised 17,930 individuals aged &gt;= 35 years, of whom 8445 were men (47.1%). The mean age was 54 years (standard deviation (SD) = 11 years), with 3299 individuals (18.4%) aged older than 65 years. All participants had C-reactive protein levels &lt;10 mg/L and no history of liver, renal, cardiovascular, or cancer disease. Hypoalbuminemia was found in 406 individuals (2.3%). The study documented a total of 1428 deaths, with 574 attributed to cancer and 464 to vascular causes. Hypoalbuminemia was independently associated with mortality when compared to serum albumin &gt;40 g/L (Hazard Ratio (HR) = 1.61, 95% Confidence Interval: 1.21-2.13). A decrease of 1-SD in serum albumin levels corresponded to HR of 1.16 (1.09-1.22), 1.16 (1.05-1.28), and 1.13 (1.03-1.23) for total, vascular and cancer mortality, respectively. Upon stratifying by age, hypoalbuminemia was associated with total mortality solely in those aged &gt;= 65 years (HR = 1.83; 1.33-2.50) but not in the &lt;65 years group (HR = 1.03; 0.53-2.00; P &lt; 0.0001 for difference). Similar age-related patterns emerged for vascular death (per 1-SD decrease HR = 1.19; 1.07-1.33 in individuals &gt;= 65 years and HR = 1.05; 0.86-1.29 in individuals &lt;65 years) and cancer mortality (HR = 1.15; 1.02-1.30; &gt;= 65 years and HR = 1.08; 0.96-1.23; &lt;65 years). Interpretation Individuals &gt;= 65 years old with serum albumin levels &lt;= 35 g/L are at higher risk of total, cancer, and vascular mortality. Copyright (c) 2024 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)

Normal hearing function genetics: have you heard all about it? An integrated approach of genome-wide association studies and transcriptome-wide association studies in three Italian cohorts

Introduction: Deepening the genetic mechanisms underlying Normal Hearing Function (NHF) has proven challenging, despite extensive efforts through Genome-Wide Association Studies (GWAS). Methods: NHF was described as a set of nine quantitative traits (i.e., hearing thresholds at 0.25, 0.5, 1, 2, 4, and 8 kHz, and three pure-tone averages of thresholds at low, medium, and high frequencies). For each trait, GWAS analyses were performed on the Moli-sani cohort (n = 1,209); then, replication analyses were conducted on Carlantino (CAR, n = 261) and Val Borbera (VBI, n = 425) cohorts. Expression levels of the most significantly associated genes were assessed employing single-nucleus RNA sequencing data (snRNA-seq) on human fetal and adult inner ear tissues. Finally, for all nine NHF traits, Transcriptome-Wide Association Studies (TWAS) were performed, combining GWAS summary statistics and pre-computed gene expression weights in 12 brain tissues. Results: GWAS on the Discovery cohort allowed the detection of 667 SNPs spanning 327 protein coding genes at a p < 10−5, across the nine NHF traits. Two loci with a p < 5 × 10−8 were replicated: 1. rs112501869 within SLC1A6 gene, encoding a brain high-affinity glutamate transporter, reached p = 6.21 × 10−9 in the 0.25 kHz trait. 2. rs73519456 within ASTN2 gene, encoding the Astrotactin protein 2, reached genome-wide significance in three NHF traits: 0.5 kHz (p = 1.86 × 10−8), PTAL (p = 9.40 × 10−9), and PTAM (p = 3.64 × 10−8). SnRNA-seq data analyses revealed a peculiar expression of the ASTN2 gene in the neuronal and dark cells populations, while for SLC1A6 no significant expression was detected. TWAS analyses detected that the ARF4-AS1 gene (eQTL: rs1584327) was statistically significant (p = 4.49 × 10−6) in the hippocampal tissue for the 0.25 kHz trait. Conclusion: This study took advantage of three Italian cohorts, deeply characterized from a genetic and audiological point of view. Bioinformatics and biostatistics analyses allowed the identification of three novel candidate genes, namely, SLC1A6, ASTN2, and ARF4-AS1. Functional studies and replication in larger and independent cohorts will be essential to confirm the biological role of these genes in regulating hearing function; however, these results confirm GWAS and TWAS as powerful methods for novel gene discovery, thus paving the way for a deeper understanding of the entangled genetic landscape underlying the auditory system