👤 Mattia Falcone

Evidence linking modifiable risk factors to age-related brain diseases, such as dementia, stroke, and depression (DSD), is robust, yet limited regarding long-term change in modifiable risk factors in association with these conditions, particularly in real-world settings. This study aimed to assess whether longitudinal changes in modifiable brain health risk factors were associated with reduced risk of DSD. We analyzed UK Biobank data (2006-2019) from 155,469 participants with general practitioner-linked data. The Brain Care Score (BCS) assesses 12 modifiable risk factors across lifestyle, physical, and social-emotional domains. Longitudinal BCS measurements were derived from repeated general practitioner (GP)-recorded measurements. Changes in the BCS were modeled using linear mixed-effects models, and associations with DSD were evaluated using multivariable Cox models, adjusting for baseline BCS and genetic risk (polygenic risk scores for stroke and depression, and APOE genotype for dementia). Among 155,469 participants (median age = 51 years, 54.3% women), the median annual BCS change was 0.14 (Q1-Q3 = 0.008-0.30) points over a median follow-up of 12.3 years (Q1-Q3 = 11.5-13.1 years). Over time, 82.1% improved their BCS, 12.9% remained stable, and 5.0% worsened over time. Each 1-point annual increase in the BCS was associated with 4% lower risk of incident age-related brain diseases (hazard ratio [HR] = 0.96, 95% confidence interval [CI] = 0.95-0.97). In this large real-world cohort, improvements in modifiable risk factor profiles were associated with lower incidence of DSD, regardless of genetic risk or baseline BCS. Our results provide important information for communicating with patients about the brain health benefits of improving risk factor profiles. ANN NEUROL 2026;99:1113-1123. Show less

Circulating tumor cells (CTCs) drive metastasis, the leading cause of death in individuals with breast cancer. Due to their low abundance in the circulation, robust CTC expansion protocols are urgently needed to effectively study disease progression and therapy responses. Here we present the establishment of long-term CTC-derived organoids from female individuals with metastatic breast cancer. Multiomics analysis of CTC-derived organoids along with preclinical modeling with xenografts identified neuregulin 1 (NRG1)-ERBB2 receptor tyrosine kinase 3 (ERBB3/HER3) signaling as a key pathway required for CTC survival, growth and dissemination. Genome-wide CRISPR activation screens revealed that fibroblast growth factor receptor 1 (FGFR1) signaling serves a compensatory function to the NRG1-HER3 axis and rescues NRG1 deficiency in CTCs. Conversely, NRG1-HER3 activation induced resistance to FGFR1 inhibition, whereas combinatorial blockade impaired CTC growth. The dynamic interplay between NRG1-HER3 and FGFR1 signaling reveals the molecular basis of cancer cell plasticity and clinically relevant strategies to target it. Our CTC organoid platform enables the identification and validation of patient-specific vulnerabilities and represents an innovative tool for precision medicine. Show less

Multiple osteochondromas (MO), also known as hereditary multiple exostoses (HME), is one of the most common hereditary musculoskeletal diseases in Caucasians (1/50,000) with wide clinical variability and genetic heterogeneity. Two genes have thus far been identified as causing the disease, namely EXT1 and EXT2. Various methods to detect mutations in the EXT genes have been used. Here a cohort of 100 MO patients belonging to unrelated Italian families have been analyzed by single-strand conformation polymorphism (SSCP) analysis or by denaturing high performance liquid chromatography (DHPLC). However, neither of these techniques can detect deletions or duplications of entire exons. Families that were negative at SSCP/DHPLC analysis underwent two-color multiple ligation-dependent probe amplification (MLPA) analysis. By these complementary techniques mutation detection was significantly improved and 26 novel mutations have been revealed as well as 18 previously described mutations to give a total of 44 different mutations. Thus we can conclude that combining MLPA with DHPLC in point-mutations negative MO families, the detection of mutations in EXT genes can significantly improve the identification of both point-mutations and mid-size rearrangements. More important, we were able to characterize all those patients who were negative at the first PCR-based method screening. Show less