Economic hardship resulting from the late 2000s Great Recession and long-term changes in mental health: a prospective analysis from the Moli-sani study.

PURPOSE: Economic downturns may have detrimental effects on mental health. We investigated the association of economic hardship resulting from the late 2000s Great Recession with long-term changes in mental health. METHODS: We analysed data from 1,647 participants to the larger Moli-sani cohort (2005-2010, Italy), who were re-examined between 2017 and 2020. To evaluate economic hardship, we performed a Latent Class Analysis on nine items linked to change in employment status and financial hardship. Depression symptoms were measured by the Patients' Health Questionnaire (PHQ-2; higher values indicate more depressive symptoms; data available in N = 941 individuals) and health perception as assessed by the 36-Item Short Form Health Survey (decreased values indicate worsening of health perception). RESULTS: Economic hardship was categorized into three classes: "None", "Average" and "High", the latter reflecting increasing economic hardship. Mean (standard deviation) changes in PHQ-2, SF-36 mental and physical after 12.8 years (median) were - 0.1 (1.3), 0.5 (9.9) and - 2.2 (6.2) units, respectively. Changes in SF-36 mental score decreased by 1.0 unit (0.3) monotonically across "none" to "average" to "high" category in a multivariable-adjusted model analysis; the SF-36 physical score decreased by 0.4 (0.2) unit and PHQ-2 increased by 0.1 (0.1). In comparison with participants in the "none", those in the "high" class had 84% (95%CI: 26%-170%) higher odds to report an increment in PHQ-2 values from baseline to re-examination. CONCLUSIONS: Economic hardship resulting from the Great Recession in late 2000s was associated with deterioration of mental health, as reflected by increased depression symptoms and reduced perceived mental health.

Life-Course Socioeconomic Trajectories and Biological Aging: The Importance of Lifestyles and Physical Wellbeing.

BACKGROUND/OBJECTIVES: Studies investigating the associations between life-course socioeconomic status (SES) and biological aging (the difference between biological and chronological age, Δage) have mostly been focused on epigenetic clocks and on a limited number of mediators. The aim of this study was to investigate this relationship using a blood-based aging clock, as well as the potential mediation of different factors including lifestyles or their proxies and physical and mental wellbeing. METHODS: A deep-learning aging clock based on 36 blood markers was deployed, in a large Italian population cohort: the Moli-sani study (N = 4772; ≥35 years; 48% men). SES was defined as an eight-level trajectory over the life course, which was tested with Δage in linear models incrementally adjusted for age, sex, and prevalent health conditions. Moreover, the proportion of associations explained by diverse potential mediators, including diet, smoking, physical activity, alcohol, body mass index (BMI), and physical and mental quality of life (QoL) was estimated. RESULTS: Compared to participants with a stably high SES, those showing an educational and financial downward trajectory were older than their CA (ß (95%CI) = 1.28 (0.73-1.83) years), as were those with a stably low SES (0.75 (0.25-01.25) years). These associations were largely explained by the tested mediators (overall proportion: 36.2% and 66.3%, respectively), prominently by physical QoL (20.7% and 41.0%), BMI (16.8% and 34.3%), lifestyle (10.6% and 24.6%), and dietary inflammatory score (5.3% and 9.2%). CONCLUSIONS: These findings indicate that life-course socioeconomic inequalities are associated with accelerated biological aging, suggesting physical wellbeing and pro-inflammatory lifestyles as potential public health targets to slow down this process in susceptible socioeconomic strata of the population.

Are Methylation Patterns in the KALRN Gene Associated with Cognitive and Depressive Symptoms? Findings from the Moli-sani Cohort.

The KALRN gene (encoding kalirin) has been implicated in several neuropsychiatric and neurodegenerative disorders. However, genetic evidence supporting this implication is limited and targeted epigenetic analyses are lacking. Here, we tested associations between epigenetic variation in KALRN and interindividual variation in depressive symptoms (PHQ9) and cognitive (MoCA) performance, in an Italian population cohort (N = 2409; mean (SD) age: 67 (9) years; 55% women). First, we analyzed the candidate region chr3:124584826-124584886 (hg38), within the KALRN promoter, through pyrosequencing of 1385 samples. Then, we widened the investigated region by analyzing 137 CpGs annotated to the whole gene, rescued from epigenome-wide (Illumina EPIC) data from 1024 independent samples from the same cohort. These were tested through stepwise regression models adjusted for age, sex, circulating leukocytes fractions, education, prevalent health conditions and lifestyles. We observed no statistically significant associations with methylation levels in the three CpGs tested through pyrosequencing, or in the gene-wide association analysis with MoCA score. However, we observed a statistically significant association between PHQ9 and cg13549966 (chr3:124106738; ß (Standard Error) = 0.28 (0.08), Bonferroni-corrected p = 0.025), located close to the transcription start site of the gene. This association was driven by a polychoric factor tagging somatic depressive symptoms (ß (SE) = 0.127 (0.064), p = 0.048). This evidence underscores the importance of studying epigenetic variation within the KALRN gene and the role that it may play in brain diseases, particularly in atypical depression, which is often characterized by somatic symptoms.

Association of perceived mental health with mortality, and analysis of potential pathways in Italian men and women: Prospective results from the Moli-sani Study cohort.

BACKGROUND: Perceived mental health (PMH) was reportedly associated with mortality in general populations worldwide. However, little is known about sex differences and pathways potentially linking PMH to mortality. We explored the relationship between PMH and mortality in Italian men and women, and analysed potential explanatory factors. METHODS: We performed longitudinal analyses on 9045 men and 9467 women (population mean age 53.8 ± 11.2 years) from the Moli-sani Study. Baseline PMH was assessed through a self-administered Short Form 36-item questionnaire. Cox proportional hazard regression was used to estimate hazard ratios (HRs) and 95 % confidence intervals (95%CI) of death across sex-specific quartiles of PMH, controlling for age, chronic health conditions, and perceived physical health. Socioeconomic, behavioural, and physiological factors were examined as potential explanatory factors of the association between PMH and mortality. RESULTS: In women, HRs for the highest (Q4) vs. bottom quartile (Q1) of PMH were 0.75 (95%CI 0.60-0.96) for all-cause mortality and 0.59 (0.40-0.88) for cardiovascular mortality. Part of these associations (25.8 % and 15.7 %, for all-cause and cardiovascular mortality, respectively) was explained by physiological factors. In men, higher PMH was associated with higher survival (HR = 0.82; 0.69-0.98, for Q4 vs. Q1) and reduced hazard of other cause mortality (HR = 0.67; 0.48-0.95). More than half of the association with all-cause mortality was explained by physiological factors. LIMITATIONS: PMH was measured at baseline only. CONCLUSIONS: PMH was independently associated with mortality in men and women. Public health policies aimed at reducing the burden of chronic diseases should prioritize perceived mental health assessment along with other interventions.

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 (ΔPhenoAge) for association with both incident and prevalent PD risk. Methods: In a large Italian population cohort - the Moli-sani study (N=23,437; age ≥ 35 years; 52% women) - we carried out both Cox Proportional Hazards regressions modelling ΔPhenoAge as exposure and incident PD as outcome, and linear models testing prevalent PD as exposure and ΔPhenoAge 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 ΔPhenoAge was observed in prevalent PD cases vs healthy subjects (ß (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; ß (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.

Identifying brain tumor patients' subtypes based on pre-diagnostic history and clinical characteristics: a pilot hierarchical clustering and association analysis.

Introduction: Central nervous system (CNS) tumors are severe health conditions with increasing incidence in the last years. Different biological, environmental and clinical factors are thought to have an important role in their epidemiology, which however remains unclear. Objective: The aim of this pilot study was to identify CNS tumor patients' subtypes based on this information and to test associations with tumor malignancy. Methods: 90 patients with suspected diagnosis of CNS tumor were recruited by the Neurosurgery Unit of IRCCS Neuromed. Patients underwent anamnestic and clinical assessment, to ascertain known or suspected risk factors including lifestyle, socioeconomic, clinical and psychometric characteristics. We applied a hierarchical clustering analysis to these exposures to identify potential groups of patients with a similar risk pattern and tested whether these clusters associated with brain tumor malignancy. Results: Out of 67 patients with a confirmed CNS tumor diagnosis, we identified 28 non-malignant and 39 malignant tumor cases. These subtypes showed significant differences in terms of gender (with men more frequently presenting a diagnosis of cancer; p = 6.0 ×10-3) and yearly household income (with non-malignant tumor patients more frequently earning ≥25k Euros/year; p = 3.4×10-3). Cluster analysis revealed the presence of two clusters of patients: one (N=41) with more professionally active, educated, wealthier and healthier patients, and the other one with mostly retired and less healthy men, with a higher frequency of smokers, personal history of cardiovascular disease and cancer familiarity, a mostly sedentary lifestyle and generally lower income, education and cognitive performance. The former cluster showed a protective association with the malignancy of the disease, with a 74 (14-93) % reduction in the prevalent risk of CNS malignant tumors, compared to the other cluster (p=0.026). Discussion: These preliminary data suggest that patients' profiling through unsupervised machine learning approaches may somehow help predicting the risk of being affected by a malignant form. If confirmed by further analyses in larger independent cohorts, these findings may be useful to create potential intelligent ranking systems for treatment priority, overcoming the lack of histopathological information and molecular diagnosis of the tumor, which are typically not available until the time of surgery.

Biomarkers of aging in frailty and age-associated disorders: State of the art and future perspective.

According to the Geroscience concept that organismal aging and age-associated diseases share the same basic molecular mechanisms, the identification of biomarkers of age that can efficiently classify people as biologically older (or younger) than their chronological (i.e. calendar) age is becoming of paramount importance. These people will be in fact at higher (or lower) risk for many different age-associated diseases, including cardiovascular diseases, neurodegeneration, cancer, etc. In turn, patients suffering from these diseases are biologically older than healthy age-matched individuals. Many biomarkers that correlate with age have been described so far. The aim of the present review is to discuss the usefulness of some of these biomarkers (especially soluble, circulating ones) in order to identify frail patients, possibly before the appearance of clinical symptoms, as well as patients at risk for age-associated diseases. An overview of selected biomarkers will be discussed in this regard, in particular we will focus on biomarkers related to metabolic stress response, inflammation, and cell death (in particular in neurodegeneration), all phenomena connected to inflammaging (chronic, low-grade, age-associated inflammation). In the second part of the review, next-generation markers such as extracellular vesicles and their cargos, epigenetic markers and gut microbiota composition, will be discussed. Since recent progresses in omics techniques have allowed an exponential increase in the production of laboratory data also in the field of biomarkers of age, making it difficult to extract biological meaning from the huge mass of available data, Artificial Intelligence (AI) approaches will be discussed as an increasingly important strategy for extracting knowledge from raw data and providing practitioners with actionable information to treat patients.

Rationale and design of the CV-PREVITAL study: an Italian multiple cohort randomised controlled trial investigating innovative digital strategies in primary cardiovascular prevention.

INTRODUCTION: Prevention of cardiovascular disease (CVD) is of key importance in reducing morbidity, disability and mortality worldwide. Observational studies suggest that digital health interventions can be an effective strategy to reduce cardiovascular (CV) risk. However, evidence from large randomised clinical trials is lacking. METHODS AND ANALYSIS: The CV-PREVITAL study is a multicentre, prospective, randomised, controlled, open-label interventional trial designed to compare the effectiveness of an educational and motivational mobile health (mHealth) intervention versus usual care in reducing CV risk. The intervention aims at improving diet, physical activity, sleep quality, psycho-behavioural aspects, as well as promoting smoking cessation and adherence to pharmacological treatment for CV risk factors. The trial aims to enrol approximately 80 000 subjects without overt CVDs referring to general practitioners' offices, community pharmacies or clinics of Scientific Institute for Research, Hospitalization and Health Care (Italian acronym IRCCS) affiliated with the Italian Cardiology Network. All participants are evaluated at baseline and after 12 months to assess the effectiveness of the intervention on short-term endpoints, namely improvement in CV risk score and reduction of major CV risk factors. Beyond the funded life of the study, a long-term (7 years) follow-up is also planned to assess the effectiveness of the intervention on the incidence of major adverse CV events. A series of ancillary studies designed to evaluate the effect of the mHealth intervention on additional risk biomarkers are also performed. ETHICS AND DISSEMINATION: This study received ethics approval from the ethics committee of the coordinating centre (Monzino Cardiology Center; R1256/20-CCM 1319) and from all other relevant IRBs and ethics committees. Findings are disseminated through scientific meetings and peer-reviewed journals and via social media. Partners are informed about the study's course and findings through regular meetings. TRIAL REGISTRATION NUMBER: NCT05339841.

Risk and protective factors in Parkinson's disease: a simultaneous and prospective study with classical statistical and novel machine learning models.

BACKGROUND: Several environmental/lifestyle factors have been individually investigated in previous Parkinson's disease (PD) studies with controversial results. No study has prospectively and simultaneously investigated potential risk/protective factors of PD using both classical statistical and novel machine learning analyses. The latter may reveal more complex associations and new factors that are undetected by merely linear models. To fill this gap, we simultaneously investigated potential risk/protective factors involved in PD in a large prospective population study using both approaches. METHODS: Participants in the Moli-sani study were enrolled between 2005 and 2010 and followed up until December 2018. Incident PD cases were identified by individual-level record linkage to regional hospital discharge forms, the Italian death registry, and the regional prescription register. Exposure to potential risk/protective factors was assessed at baseline. Multivariable Cox Proportional Hazards (PH) regression models and survival random forests (SRF) were built to identify the most influential factors. RESULTS: We identified 213 incident PD cases out of 23,901 subjects. Cox PH models revealed that age, sex, dysthyroidism and diabetes were associated with an increased risk of PD. Both hyper and hypothyroidism were independently associated with PD risk. SRF showed that age was the most influential factor in PD risk, followed by coffee intake, daily physical activity, and hypertension. CONCLUSION: This study sheds light on the role of dysthyroidism, diabetes and hypertension in PD onset, characterized to date by an uncertain relationship with PD, and also confirms the relevance of most factors (age, sex, coffee intake, daily physical activity) reportedly shown be associated with PD. Further methodological developments in SRF models will allow to untangle the nature of the potential non-linear relationships identified.

Association between BMI, RFM and mortality and potential mediators: Prospective findings from the Moli-sani study.

BACKGROUND: Body mass index (BMI) is the most frequently used adiposity measure, yet it is unable to differentiate fat mass from lean mass. Relative fat mass (RFM) has been proposed as an alternative. This paper aims to study RFM and BMI association with mortality in a general Italian population and potential mediators of such association. METHODS: 20,587 individuals from the Moli-sani cohort were analysed (mean age = 54 ± 11, women = 52%, median follow up = 11.2 years, interquartile range = 1.96 years). Cox regressions were used to assess BMI, RFM, and their interactive association with mortality. Dose-response relationships were computed with spline regression, mediation analysis was performed. All analyses were separated for men and women. RESULTS: Men and women with BMI > 35 kg/m2 and men in the 4th quartile of RFM showed an independent association with mortality (HR = 1.71, 95% CI = 1.30-2.26 BMI in men, HR = 1.37, 95%CI = 1.01-1.85 BMI in women, HR = 1.37 CI 95% = 1.11-1.68 RFM in men), that was lost once adjusted for potential mediators. Cubic splines showed a U-shaped association for BMI in men and women, and for RFM in men. Mediation analysis showed that 46.5% of the association of BMI with mortality in men was mediated by glucose, C reactive protein, forced expiratory volume in 1 s (FEV1), and cystatin C; 82.9% of the association of BMI in women was mediated by HOMA index, cystatin C and FEV1; lastly, 55% of RFM association with mortality was mediated by glucose, FEV1 and cystatin C. Regression models including BMI and RFM showed that RFM drives most of the risk in men, but is not predictive in women. CONCLUSIONS: The association between anthropometric measures and mortality was U shaped and it was largely dependent on sex. Associations were mediated by glucose metabolism, renal and lung function. Public health interventions should mainly focus on people with severe obesity or impaired metabolic, renal, or respiratory function.

Association between the Inflammatory Potential of the Diet and Biological Aging: A Cross-Sectional Analysis of 4510 Adults from the Moli-Sani Study Cohort.

Chronological age (CA) may not accurately reflect the health status of an individual. Rather, biological age (BA) or hypothetical underlying "functional" age has been proposed as a relevant indicator of healthy aging. Observational studies have found that decelerated biological aging or Δage (BA-CA) is associated with a lower risk of disease and mortality. In general, CA is associated with low-grade inflammation, a condition linked to the risk of the incidence of disease and overall cause-specific mortality, and is modulated by diet. To address the hypothesis that diet-related inflammation is associated with Δage, a cross-sectional analysis of data from a sub-cohort from the Moli-sani Study (2005-2010, Italy) was performed. The inflammatory potential of the diet was measured using the Energy-adjusted Dietary Inflammatory Index (E-DIITM) and a novel literature-based dietary inflammation score (DIS). A deep neural network approach based on circulating biomarkers was used to compute BA, and the resulting Δage was fit as the dependent variable. In 4510 participants (men 52.0%), the mean of CA (SD) was 55.6 y (±11.6), BA 54.8 y (±8.6), and Δage -0.77 (±7.7). In a multivariable-adjusted analysis, an increase in E-DIITM and DIS scores led to an increase in Δage (ß = 0.22; 95%CI 0.05, 0.38; ß = 0.27; 95%CI 0.10, 0.44, respectively). We found interaction for DIS by sex and for E-DIITM by BMI. In conclusion, a pro-inflammatory diet is associated with accelerated biological aging, which likely leads to an increased long-term risk of inflammation-related diseases and mortality.

A Multi-Trait Association Analysis of Brain Disorders and Platelet Traits Identifies Novel Susceptibility Loci for Major Depression, Alzheimer's and Parkinson's Disease.

Among candidate neurodegenerative/neuropsychiatric risk-predictive biomarkers, platelet count, mean platelet volume and platelet distribution width have been associated with the risk of major depressive disorder (MDD), Alzheimer's disease (AD) and Parkinson's disease (PD) through epidemiological and genomic studies, suggesting partial co-heritability. We exploited these relationships for a multi-trait association analysis, using publicly available summary statistics of genome-wide association studies (GWASs) of all traits reported above. Gene-based enrichment tests were carried out, as well as a network analysis of significantly enriched genes. We analyzed 4,540,326 single nucleotide polymorphisms shared among the analyzed GWASs, observing 149 genome-wide significant multi-trait LD-independent associations (p < 5 × 10-8) for AD, 70 for PD and 139 for MDD. Among these, 27 novel associations were detected for AD, 34 for PD and 40 for MDD. Out of 18,781 genes with annotated variants within ±10 kb, 62 genes were enriched for associations with AD, 70 with PD and 125 with MDD (p < 2.7 × 10-6). Of these, seven genes were novel susceptibility loci for AD (EPPK1, TTLL1, PACSIN2, TPM4, PIF1, ZNF689, AZGP1P1), two for PD (SLC26A1, EFNA3) and two for MDD (HSPH1, TRMT61A). The resulting network showed a significant excess of interactions (enrichment p = 1.0 × 10-16). The novel genes that were identified are involved in the organization of cytoskeletal architecture (EPPK1, TTLL1, PACSIN2, TPM4), telomere shortening (PIF1), the regulation of cellular aging (ZNF689, AZGP1P1) and neurodevelopment (EFNA3), thus, providing novel insights into the shared underlying biology of brain disorders and platelet parameters.

Increased Adherence to a Mediterranean Diet Is Associated With Reduced Low-Grade Inflammation after a 12.7-Year Period: Results From the Moli-sani Study.

BACKGROUND: There is little knowledge on the association of changes over time in adherence to a Mediterranean diet (MD) with changes in modifiable cardiovascular disease (CVD) risk factors and of markers of low-grade inflammation. OBJECTIVE: To evaluate the association between long-term changes in MD adherence and concurrent changes in established CVD risk factors and in markers of low-grade inflammation among adult Italians. DESIGN: A prospective cohort study was conducted. Dietary and health data were obtained both at baseline (2005-2010) and at follow-up (2017-2020). Adherence to the MD was estimated by a Mediterranean Diet Score ranging from zero to nine points, and the exposure was change in this score measured after a median 12.7-year period. PARTICIPANTS/SETTING: This study included a subgroup of 897 men and 1,126 women aged ≥35 years at enrolment in the Moli-sani Study (n = 24,325). MAIN OUTCOME MEASURES: Changes in two composite z scores, including nine established CVD risk factors (eg, serum lipid levels and blood pressure) and four inflammatory markers (including C-reactive protein), respectively, were measured both at enrolment and after the same 12.7-year period. STATISTICAL ANALYSES PERFORMED: Multivariable-adjusted linear regression models were used. RESULTS: In a multivariable-adjusted analysis, an increased Mediterranean Diet Score over time was associated with decreased levels in the Inflammatory score (ß = -0.372, 95% CI -0.720 to -0.025), but had little or no influence on the CVD risk score (ß = -0.200, 95% CI -0.752 to 0.351), compared with individuals who had decreased their MD adherence. Among individual food groups/nutrients included in the Mediterranean Diet Score, an increased intake of monounsaturated over saturated fats over time was associated with lower CVD Risk Score, whereas increased consumption of cereals was inversely linked to the Inflammatory Score, compared with the reduced consumption group. CONCLUSIONS: An increased adherence to a traditional MD over time was associated with reduced low-grade inflammation. These findings suggest the potential of a traditional Mediterranean eating pattern to help reduce the long-term risk of inflammation-related chronic diseases in an ageing population.

Food processing and risk of central nervous system tumours: A preliminary case-control analysis from the MEditerranean DIet in relation to CancEr of brAin (MEDICEA) study.

BACKGROUND: The relationship between diet and central nervous system (CNS) tumours was almost exclusively focused on food composition. We evaluated the relationship of different degrees of food processing with risk of CNS tumours. METHODS: The study sample included 44 CNS tumours cases (20 non-malignant and 24 malignant) recruited from the Neurosurgery Department at the IRCCS Neuromed (Italy), and 88 controls matched 1:2 for sex and age± 10 years, identified from the Moli-sani Study. Dietary intake was assessed using a 188-item FFQ. Food items were grouped according to the NOVA classification on the basis of processing as: (1) unprocessed/minimally processed foods; (2) processed culinary ingredients; (3) processed foods; and (4) ultra-processed food (UPF). Conditional logistic regression models were used to estimate odds ratio (OR) and 95% confidence intervals (95%CI) of dietary contributions from each NOVA group (as weight ratio on the total food eaten) and adjusting for potential confounders. RESULTS: In a multivariable conditional to match logistic regression analysis also controlled for overall diet quality, 1% increment in UPF intake was associated with higher odds of all CNS tumours (OR = 1.06; 1.01-1.13), particularly of malignant CNS tumours (OR = 1.11; 1.02-1.22), while no association with non-malignant CNS tumours was found (OR = 1.06; 0.99-1.15). In contrast, only processed food was inversely associated with risk of both CNS tumours overall (OR = 0.94; 0.90-0.98) and of malignant CNS tumours (OR = 0.90; 0.83-0.96). CONCLUSION: Increasing UPF intake was associated with higher risk of CNS tumours, especially malignant ones, independently of the overall diet quality, while only processed food (but not UPF) was inversely related to the risk of this disease.

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 (ß (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 ß (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.

Role of leukocytes, gender, and symptom domains in the influence of depression on hospitalization and mortality risk: Findings from the Moli-sani study.

Background: Major depressive disorder is a mental illness associated with chronic conditions like cardiovascular disease (CVD). Circulating inflammation has been proposed as a potential mechanism underlying this link, although the role of specific biomarkers, gender, and symptom domains is not well elucidated. Methods: We performed multivariable Cox regressions of first hospitalization/all-cause mortality and CVD, ischemic heart (IHD), and cerebrovascular disease (CeVD) causes vs. depression severity in an Italian population cohort (N = 13,191; age ≥ 35 years; 49.3% men; 4,856 hospitalizations and 471 deaths, median follow-up 7.28 and 8.24 years, respectively). In models adjusted for age, sex, and socioeconomic status, we estimated the proportion of association explained by C-reactive protein (CRP), platelet count, granulocyte-to-lymphocyte ratio (GLR), and white blood cell count (WBC). Gender-by-depression interaction and gender-stratified analyses were performed. Associations of polychoric factors tagging somatic and cognitive symptoms with incident clinical risks were also tested, as well as the proportion explained by a composite index of circulating inflammation (INFLA score). Results: Significant proportions of the influence of depression on clinical risks were explained by CRP (4.8% on IHD hospitalizations), GLR (11% on all-cause mortality), and WBC (24% on IHD/CeVD hospitalizations). Gender-by-depression interaction was significantly associated only with all-cause mortality (p = 0.03), with moderate depression showing a + 60% increased risk in women, but not in men. Stable associations of somatic, but not of cognitive, symptoms with increased hospitalization risk were observed (+ 16% for all causes, + 14% for CVD causes), with INFLA score explaining small but significant proportions of these associations (2.5% for all causes, 8.6% for IHD causes). Conclusions: These findings highlight the importance of cellular components of inflammation, gender, and somatic depressive symptoms in the link between depression and clinical (especially CVD) risks, pointing to the existence of additional pathways through which depression may play a detrimental effect on the cardiovascular system.

Genome-wide analyses of individual differences in quantitatively assessed reading- and language-related skills in up to 34,000 people.

The use of spoken and written language is a fundamental human capacity. Individual differences in reading- and language-related skills are influenced by genetic variation, with twin-based heritability estimates of 30 to 80% depending on the trait. The genetic architecture is complex, heterogeneous, and multifactorial, but investigations of contributions of single-nucleotide polymorphisms (SNPs) were thus far underpowered. We present a multicohort genome-wide association study (GWAS) of five traits assessed individually using psychometric measures (word reading, nonword reading, spelling, phoneme awareness, and nonword repetition) in samples of 13,633 to 33,959 participants aged 5 to 26 y. We identified genome-wide significant association with word reading (rs11208009, P = 1.098 × 10-8) at a locus that has not been associated with intelligence or educational attainment. All five reading-/language-related traits showed robust SNP heritability, accounting for 13 to 26% of trait variability. Genomic structural equation modeling revealed a shared genetic factor explaining most of the variation in word/nonword reading, spelling, and phoneme awareness, which only partially overlapped with genetic variation contributing to nonword repetition, intelligence, and educational attainment. A multivariate GWAS of word/nonword reading, spelling, and phoneme awareness maximized power for follow-up investigation. Genetic correlation analysis with neuroimaging traits identified an association with the surface area of the banks of the left superior temporal sulcus, a brain region linked to the processing of spoken and written language. Heritability was enriched for genomic elements regulating gene expression in the fetal brain and in chromosomal regions that are depleted of Neanderthal variants. Together, these results provide avenues for deciphering the biological underpinnings of uniquely human traits.

Increased BMI and Blood Lipids Are Associated With a Hypercoagulable State in the Moli-sani Cohort.

The coagulation system can be assessed by the thrombin generation (TG) assay, and increased TG peak height, endogenous thrombin potential (ETP), and velocity index are associated with an increased risk of thrombosis. Obesity had been reported to increase TG and is associated with dyslipidemia, which also predisposes to atherosclerotic cardiovascular disease (CVD). However, the effect of the blood lipid profile on TG has not been studied extensively. To gain more insight into the associations of TG, body mass index (BMI) and lipid profile, we studied TG in relation to these parameters in a large Italian population cohort, the Moli-sani study (N = 22,546; age ≥ 35 years; 48% men). TG was measured in plasma samples collected at the enrollment of subjects in the Moli-sani study. TG was triggered with 1 or 5 pM tissue factor, and TG parameters lag time, peak, ETP, time-to-peak (TTP) and velocity index (VI). Additionally, thrombomodulin was added to assess the function of the activated protein C system during TG. In both women and men, overweight (BMI 25-30 kg/m2) and obesity (BMI > 30 kg/m2) were significantly associated with higher ETP, peak and VI (all p < 0.001). High total cholesterol, triglycerides and LDL-cholesterol levels were significantly associated with increased ETP and peak (all p < 0.001). Linear regression analysis revealed that the ETP is positively associated with both plasma LDL and HDL cholesterol levels, whereas the velocity index is positively associated with HDL cholesterol. Additionally, ETP, peak and VI were significantly associated with the plasma triglycerides content. In conclusion, our study shows significant associations of high BMI and blood lipid levels with increased TG parameters, and this hypercoagulability may partly explain the increased risk of CVD in individuals with obesity and/or dyslipidemia.

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.

Does COVID-19 increase the risk of neuropsychiatric sequelae? Evidence from a mendelian randomization approach.

Observational studies based on electronic health records (EHR) report an increased risk of neurological/neuropsychiatric sequelae for patients who have had coronavirus disease 2019 (COVID-19). However, these studies may suffer from biases such as unmeasured confounding, residual reverse causality, or lack of precision in EHR-based diagnoses. To rule out these biases, we tested causal links between COVID-19 and different potential neurological/neuropsychiatric sequelae through a two-sample Mendelian randomization analysis of summary statistics from large Genome-Wide Association Scans of susceptibility to COVID-19 and different neurological and neuropsychiatric disorders, including major depression, anxiety, schizophrenia, stroke, Parkinson's and Alzheimer's diseases. We found robust evidence suggesting that COVID-19 - notably the hospitalized and most severe forms - carries an increased risk of neuropsychiatric sequelae, particularly Alzheimer's disease, and to a lesser extent anxiety disorder. In line with a large longitudinal EHR-based study, this evidence was stronger for more severe COVID-19 forms. These results call for a targeted screening strategy to tackle the post-COVID neuropsychiatric pandemic.