Alzheimer’s disease (AD) is the most common neurodegenerative disorder and a leading cause of dementia. One major challenge for clinicians is accurately assessing the rate of disease progression (RoP) early in the diagnostic process, which is crucial for patient management and clinical trial stratification. This study evaluated the role of cerebrospinal fluid biomarkers—Aβ42, t-Tau, pTau, Neurogranin (Ng), and Neurofilament light-chain (NF-L)—in predicting RoP at the time of AD diagnosis. We included 56 AD patients and monitored cognitive impairment using MMSE scores at diagnosis and during six-month follow-up visits. RoP scores were calculated based on these assessments. Our correlation analyses revealed significant associations between RoP and pTau, Aβ42/Ng ratio, and NF-L levels. When patients were stratified by median RoP values into low-to-moderate (L-M: 2) groups, those in the U-M group had notably higher CSF NF-L levels compared to the L-M group. Logistic regression analysis further demonstrated that elevated CSF NF-L levels were predictive of a faster RoP. These findings highlight the potential of CSF NF-L as a prognostic biomarker for rapid disease progression in AD. By identifying patients at risk for accelerated cognitive decline, CSF NF-L could significantly enhance early intervention strategies and improve patient management in clinical settings.

Background/Objectives: Dementia is a major public health challenge, with age as its primary non-modifiable risk factor. Several modifiable conditions, such as hypertension, diabetes, and depression, have been identified as potential targets for prevention. The aim is to describe the methodology and preliminary results of a study that will be conducted within the Italian National Health Service (INHS), designed to assess the impact of hypertension, diabetes, depression, and their interactions on the onset of dementia. Methods: This population-based cohort study, part of the PREV-ITA-DEM project, was conducted using a Common Data Model (CDM) approach across five Italian regions and cities participating in the NeuroEpiNet network. Individuals aged ≥ 50 years without prior diagnoses of dementia, depression, diabetes, or hypertension were followed from cohort entry (2011–2013) until dementia diagnosis, death, emigration, or study end (2019–2022). Exposures were time-dependent and defined using validated algorithms applied to Healthcare Utilization Databases (HUDs). Associations between chronic conditions and dementia risk will be estimated using competing risks regression models adjusted for confounders. Results: The final cohort comprised more than 3 million individuals, with a mean baseline age of 63–65 years and a female proportion of 52–55%. On 1 January 2011, the prevalence of individuals aged ≥ 50 years with dementia ranged from 8.7 to 14.7 per 1000 population. A harmonized methodological framework based on a CDM was developed and implemented across all sites, incorporating a shared protocol, standardized local databases, and uniform analytic scripts, and the results will be pooled using meta-analytic techniques. Conclusions: Preliminary findings confirm the feasibility of a standardized, multi-regional CDM approach and the potential for HUDs to support large-scale dementia prevention studies in real-world settings.

Background/Objectives: At the international level, harmonized networks of dementia clinical studies are available, but Italian participation remains limited. This systematic review aims to define harmonization rules to facilitate the inclusion of Italian clinical studies in existing networks and to propose standardized data collection methods to enable comparison of the study results. Methods: A systematic review was conducted (January 2019–December 2024) to identify Italian clinical studies evaluating Alzheimer’s disease and other dementias as outcomes. Eight modifiable risk factors were extracted: BMI, arterial hypertension, diabetes, dietary patterns, alcohol consumption, smoking habits, depressive symptomatology, and physical activity. WHO definitions and internationally accepted criteria were used as reference standards. Variable harmonization potential was assessed using the DataSHaPER methodology and classified as complete, partial, or impossible, considering information loss across studies. Results: Of 365 records identified, 18 studies met the inclusion criteria. Obesity assessed via BMI showed the highest harmonization potential (44% complete, 33% partial), along with dietary habits measured by food frequency questionnaires (44% complete). Diabetes and physical inactivity followed (33% complete), assessed through fasting glucose or pharmacological treatment and the IPAQ, respectively. Smoking habits classified as current, former, or never smokers were reported in 28% of studies. Depression (assessed by GDS or CES-D) and hypertension (blood pressure measurement or antihypertensive treatment) showed complete harmonization in only 22% of studies. Conclusions: Italian studies show substantial limitations in the harmonization of modifiable risk factor data for Alzheimer’s disease, mainly due to heterogeneous and non-standardized data collection methods, highlighting the need for uniform research protocols.

Background/Objectives: Alzheimer’s disease (AD) is the most common cause of dementia. Among the various factors associated with the risk of AD, growing attention in recent years has focused on environmental influences, particularly air pollution. The association between air pollutants and AD remains inconclusive due to heterogeneity in available studies. Given these gaps, we performed a systematic review on the topic. Methods: We systematically searched Pubmed, Embase and Scopus. Retrieved records underwent screening by title and abstract and then in full text. We included studies quantitatively exploring the association between exposure to air pollutants and risk of AD. We performed a meta-analysis to identify a pooled estimate of the impact of each pollutant on the probability of developing AD. Results: We retrieved 1081 records and included 27 studies. We found a significant association between PM_2.5 levels and AD risk (HR 1.74, 95%CI 1.36–2.23). Our data did not support a relevant role for the other pollutants we analyzed (for PM₁₀ HR = 1.35, 95%CI: 0.86–2.11; for NO₂ HR = 1.34, 95%CI 0.96–1.86; and for O₃ HR = 1.03, 95%CI 0.68–1.57). Conclusions: PM_2.5 emerged as the pollutant most strongly and consistently associated with an increased risk of AD. This robust and statistically significant association underscores the potential neurotoxic effects of fine particulate matter. For other pollutants, a clear role was not found. These results should be interpreted with caution, due to high heterogeneity in the definition of AD in the included studies (in most cases, a clinical definition was used). More research will be needed in the future.

Introduction: The significant impact of attention deficit/hyperactivity disorder (ADHD) on health in adult life has been widely recognized. Among the comorbidities of this disorder in later life, dementia is one of the most relevant ones. We performed a systematic review and meta-analysis to explore the impact of previous ADHD diagnosis on dementia risk. Materials and methods: We systematically searched Pubmed, Embase and Scopus for the relevant literature. Cohort and case–control studies were included in our review. Retrieved records were selected by title and abstract and then by full text reading. For quality appraisal, the Newcastle–Ottawa scale was used. A meta-analysis of hazard ratios (HRs) was performed for each type of dementia. Results: Four cohort studies and one case–control study were included, for a total of 3,703,877 and 400 participants, respectively. For all-cause dementia, the pooled HR was 2.52 (95%CI 1.51–4.22, p < 0.001), pointing out a significantly higher hazard in subjects with ADHD. For Alzheimer’s disease, vascular dementia and Lewy body dementia, no meta-analysis was performed due to the low number of available studies. Discussion and conclusions: Our results support a significant association between ADHD and risk of dementia. The results regarding specific types of dementia are more challenging to interpret and could have been influenced by sample size issues. These findings show that ADHD deserves attention in future research on cognitive disorders of the elderly; in particular, more studies are needed to reveal if a true causal relationship links ADHD and dementia.