One of the major causative genes involved in Frontotemporal dementia (FTD) is Granulin (GRN), encoding for Progranulin (PGRN). GRN mutation carriers show a substantial heterogeneity with high variability in age at onset and pathological presentation, even within the same family or identical mutations, suggesting the presence of additional genetic factors. Single nucleotide polymorphisms in the Transmembrane protein 106B (TMEM106B) locus were identified as a genetic risk-associated factor for FTD. The top variant identified was the non-coding rs1990622, with the major allele (T) associated with an increased risk to develop FTD, while subjects with the minor allele (C) were less likely to develop disease, suggesting a protective effect. In this study, we investigate in a large Italian cohort of GRN mutation carriers, how the coding variant TMEM106B-rs3173615, in linkage disequilibrium with rs1990622, modulates age at onset, survival, and PGRN levels, including, up to date, the highest sample size of homozygous protective allele carriers. Genetic screening for TMEM106B-rs3173615 was performed on a total of 187 GRN mutation carriers, comprising 131 FTD patients and 56 pre-symptomatic subjects. Individuals with the protective genotype (GG) had a risk of FTD onset reduced by 80%, with a median age at onset of 77 years compared to a median age at onset of 63 years for individuals without the protective genotype. TMEM106B-rs3173615 acts as a genetic modifier of age at onset in the presence of GRN mutations and could be considered in clinical practice to optimize risk stratification for FTD.

The integration of multi-omics data holds great promise for identifying robust and clinically relevant biomarkers, yet the increasing complexity of computational methods raises questions about their practical utility. In this study, we present a comprehensive benchmarking framework that evaluates 27 feature selection strategies and 11 predictive models across three real-world disease cohorts: Alzheimer's disease, progressive supranuclear palsy, and breast cancer. We compare traditional machine learning, ensemble-based methods, and state-of-the-art deep learning models in terms of predictive performance, stability, and biological interpretability. Our results reveal that ensemble feature selection consistently improves robustness and accuracy, particularly for compact biomarker panels. Surprisingly, deep learning models did not outperform simpler classifiers such as logistic regression (L.Regression), support vector machines, or multilayer perceptrons, which often achieved comparable or superior results with lower computational cost and greater interpretability. Triple-omics yielded the highest validation, followed by dual-omics and then single-omics (Triple > Dual > Single). Biological validation against five independent databases confirmed the clinical relevance of the identified biomarkers, including both well-established and novel candidates. To support reproducibility and community adoption, we provide a web-based tool for applying our benchmarking pipeline. Our findings advocate for a pragmatic approach to biomarker discovery-prioritizing methodological transparency, reproducibility, and biological insight over algorithmic complexity.

BACKGROUND:Individuals carrying Progranulin (GRN) mutations show asymmetrical grey matter atrophy, which could be used for early detection in the long asymptomatic phase. To capture these alterations, we employed both conventional Surface-Based Morphometry (SBM) and Mode-Based Morphometry (MBM). While the former provides high-resolution, location-specific estimates of cortical thickness (CT) differences, the latter has recently been introduced as a novel framework that decomposes CT maps into geometric eigenmodes, allowing a multiscale characterization of brain structural variability. Using both approaches enables the detection of complementary aspects of GRN-related neurodegeneration across spatial scales. METHODS:SBM and MBM were applied to CT maps to quantify structural alterations in individuals, 15 presymptomatic and 27 symptomatic, compared to 19 healthy controls (HC). SBM was used to assess vertex-wise CT differences, whereas MBM was used to decompose individual CT maps into geometric eigenmodes and quantify alterations across spatial scales. From both pipelines asymmetry indices (SBM-AI and MBM-AI) were computed. Associations between SBM/MBM-derived measures and domain-specific cognitive performance as well as global disease severity scores were then assessed. RESULTS:Compared with HC, symptomatic GRN showed significant alterations in seven eigenmodes in the left hemisphere, while only two modes contributed to CT differences in the right hemisphere. For MBM-AI and SBM-AI symptomatic GRN exhibited significantly different values compared to HC and presymptomatic GRN (p < 0.001). Although both asymmetry indices showed significant differences across disease stages (p = 1.3 × 10-5 SBM-AI; p = 3.5 × 10-5 MBM-AI), only the MBM-AI revealed a U-shaped trajectory across disease progression, characterized by an early increase in asymmetry followed by a partial re-symmetrisation in later stages. CONCLUSIONS:MBM revealed multiscale cortical alterations in symptomatic GRN mutation carriers, capturing both large-scale hemispheric differences and more localized regional variations in CT that are less apparent with conventional SBM. These findings indicate that GRN-related neurodegeneration involves complex spatial pattern across multiple anatomical scales. Brain asymmetry remains a core hallmark of GRN-related pathology, supporting the use of asymmetry indices (derived from both SBM and MBM) as potential markers of disease progression at the symptomatic stage.

Copy-number variants (CNVs) are major contributors to human disease. In Alzheimer disease (AD), APP duplications cause autosomal-dominant forms, but the role of CNVs in non-monogenic AD remains poorly characterized. We analyzed rare CNVs (frequency <1%) from 22,319 exomes (4,150 early-onset AD [EOAD, ≤65 years], 8,519 late-onset AD [LOAD], 9,650 unaffected control subjects) using harmonized calling and quality control. After identifying 17 individuals with a pathogenic CNV, we performed exome-wide and gene-set burden analyses. EOAD-affected individuals showed increased burdens of rare CNVs affecting coding genes, particularly deletions in AD-related genes. Integrated loss-of-function (LoF) analysis gathering short truncating variants with deletions showed that ABCA1 (odds ratio [OR] = 5.77 [95% confidence interval 2.25; 17.06], p = 0.0002) and ABCA7 deletions contribute to this deletion burden (OR = 2.29 [1.44; 3.65], p = 0.0006), while CTSB LoF alleles appear as candidates (OR = 5.03 [1.50; 20.71], p = 0.0089). We then performed exome-wide gene-level dosage analysis and highlighted 18 genes across five loci with a false discovery rate of <10%, including the 22q11.21 central region, where deletions were restricted to EOAD (including one de novo event) and duplications were enriched in control individuals, with intermediate frequencies in LOAD. We narrowed this locus to the SCARF2-KLHL22-MED15 region after integrating short truncating variants. Replication in 33,977 affected individuals and 362,322 control subjects confirmed association for 22q11.21 dosage with exome-wide significance (ORSCARF2 = 0.34 [0.21; 0.53]; mega-p value = 5.52 × 10-7). SCARF2 overexpression significantly increased amyloid-β uptake, congruent with duplication-associated decreased AD risk. We conclude that rare coding CNVs in a proportion of AD-associated genes and 22q11.21 deletions, including some found in DiGeorge syndrome, increase AD risk. Conversely, we identify 22q11.21 duplication as a strong AD-risk-decreasing factor.

Psychiatric disorders represent a leading cause of disability worldwide and are characterized by substantial biological and therapeutic heterogeneity. Despite significant research efforts, peripheral biomarkers capable of guiding diagnosis, patient stratification, and personalized treatment selection are still lacking. Circulating cell-free DNA (cfDNA) has recently emerged as a promising candidate biomarker, as it may integrate signals of cellular damage, apoptotic activity, and immune activation across multiple tissues. Beyond its role as a marker, cfDNA may also actively contribute to disease processes by functioning as a damage-associated molecular pattern (DAMP), thereby perpetuating inflammatory signaling. The mitochondrial component of cfDNA (cf-mtDNA), which also possesses strong immunostimulatory properties, represents a particularly sensitive indicator of mitochondrial vulnerability to stress. In this context, the present review aims to synthesize the most recent evidence on cfDNA and cf-mtDNA in major psychiatric disorders, including major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ). Specifically, we examine their association with psychological stress exposure and childhood trauma, as well as their involvement in inflammation-related pathophysiological mechanisms such as mitochondrial dysfunction, oxidative stress, and hypothalamic-pituitary-adrenal (HPA) axis dysregulation. Available evidence suggests that alterations in cfDNA may be present in subgroups of patients with MDD, BD, and SCZ. However, findings remain heterogeneous and sometimes contradictory, partly due to methodological limitations, including the lack of standardized analytical protocols and insufficient control for potential confounders. Nevertheless, cfDNA holds promise as a tool for inflammation-based patient stratification and for informing personalized therapeutic strategies. Future research directions include the integration of cfDNA within multi-omics frameworks, the analysis of cfDNA methylation profiles to infer tissue of origin, and the exploration of pharmacological strategies aimed at modulating cfDNA as a potential therapeutic target.

Psychiatric disorders, such as major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SZ), comprise a heterogenous group of severe mental illnesses (SMIs) characterized by disturbances in cognition, emotional regulation, or behavior. Cognitive impairment represents an accompanying feature of many SMIs, often interfering with or limiting essential daily life activities. SMIs arise from a complex interplay of genetic, epigenetic, developmental, and environmental factors that disrupt neural and cellular processes. SMIs often present with overlapping symptoms and sometimes co-occur, making misdiagnosis a common clinical challenge. To date, there is a lack of reliable and specific biological markers to aid in the differential diagnosis of cognitive impairment in SMIs and for distinguishing neurodegenerative dementias from SMIs with overlapping symptoms. In this context, blood-based biomarkers of the ATX(N) system associated with cognitive deficits in neurodegenerative diseases, such as neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), amyloid beta (Aβ), and tau proteins, may help to understand the biological basis of cognitive dysfunction in SMIs and support differential diagnosis. This narrative review summarizes the current evidence on the application of blood-based biomarkers of neurodegenerative dementias in SMIs and their association with the cognitive deficits observed in these conditions, as well as their relevance for differential diagnosis, disease monitoring, and the evaluation of treatment efficacy in psychiatric disorders.

BACKGROUND:What drives the heterogeneity of survival estimates in genetic frontotemporal dementia is unknown. We sought to understand the natural history and predictors of disease trajectory, which are crucial not only for effective care but also for the design of therapeutic clinical trials and efficacy evaluation. METHODS:In this international, cohort study, we used the Kaplan-Meier method to retrospectively assess survival estimates in patients enrolled in the GENFI cohort, which included 32 research sites located in Belgium, Canada, Finland, France, Germany, Italy, the Netherlands, Portugal, Spain, Sweden, and the UK, and comprised participants carrying a causal C9orf72 expansion or a causal mutation in GRN or MAPT genes. Survival was calculated as the time from symptom onset to time of death or censoring date; median survival estimate for all patients was the primary endpoint. Cox proportional hazards models were used to identify predictors of survival, which were subsequently externally validated in an independent cohort. We further designed a structural equation model to assess the relationships between predictors, applying a least absolute shrinkage and selection operator method. FINDINGS:Of 278 participants of the GENFI cohort included in this study, 160 (58%) were men and 118 (42%) were women. 162 died during follow-up (58%) and 116 were still alive (42%) on June 1, 2024, the chosen censoring date. 138 participants carried a C9orf72 expansion, 94 carried a GRN mutation, and 46 a MAPT mutation. 179 participants were diagnosed with behavioural variant frontotemporal dementia, 46 with primary progressive aphasia, and 31 with frontotemporal dementia-amyotrophic lateral sclerosis. 22 participants had other diagnoses. The median survival estimate for all patients with genetic frontotemporal dementia was 6·94 years (95% CI 6·59-7·80) from symptom onset. The median survival estimate for patients with GRN mutations was 6·63 years (6·08-7·98), for patients with a C9orf72 expansion was 7·04 years (6·45-8·77), and for patients with MAPT mutations was 8·56 years (7·06-13·50). Older age at onset, shorter disease duration from onset to enrolment in the GENFI study, clinical presentation (ie, frontotemporal dementia-amyotrophic lateral sclerosis), domain of first symptom (ie, motor or language onset), and geographical area of residency (ie, central and southern Europe) were associated with poorer prognosis. Genetic group did not directly affect survival estimates; rather its effect was mediated by age at onset and clinical phenotype. We computed a genetic frontotemporal dementia survival risk index, which can be used at an individual patient level. INTERPRETATION:Our results highlight that motor impairment in addition to cognitive and behavioural symptoms should be considered when estimating prognosis in genetic frontotemporal dementia. Individual risk scores might be of help for patient stratification in future therapeutic trials, although refinement and prospective validation are now needed. FUNDING:Italian Ministry of Health (Ricerca Corrente), Fondation Philippe Chatrier, and Fondation Vaincre Alzheimer.

BACKGROUND:Biomarkers reflecting the complex pathophysiology of genetic frontotemporal dementia (FTD) will be increasingly important with the advent of therapeutic trials aiming to slow or prevent the disease. In this study, we aimed to identify blood biomarker candidates using a multiplex panel of CNS-related proteins. METHODS:We cross-sectionally evaluated 67 carriers (21 presymptomatic and 46 symptomatic) of pathogenic FTD-causing mutations in the GRN (n = 30 symptomatic) and C9orf72 (n = 16 symptomatic) genes and 42 matched non-carriers. Clinical severity was estimated using the CDR Dementia Staging Instrument with National Alzheimer Coordinating Centre Frontotemporal Lobar Degeneration component (CDR plus NACC FTLD). A total of 124 CNS-related proteins were measured in plasma using the NUcleic acid Linked Immuno-Sandwich Assay (NULISA) CNS panel. Group-level changes were then investigated using linear and non-linear regression models. RESULTS:In GRN- and C9orf72-FTD, neurofilament light (NfL) was the most clearly altered protein compared with non-carriers (GRN: β [95% CI] = 4.0 standard deviations [3.6-4.4], C9orf72: β = 2.8 [2.2-3.4]), followed by neurofilament heavy (NfH; GRN: β = 0.83 [0.39-1.3], C9orf72: β = 1.4 [0.8-2.0]). Proteins exclusively altered in GRN-FTD included glial fibrillary acidic protein (GFAp; β = 0.50 [0.20-0.81]) and vascular cell adhesion protein 1 (VCAM1; Standardized β = -0.90 [-1.4 to -0.38]), changing with increasing disease severity. Neuronal pentraxin receptor (NPTXR; β = -0.94 [-1.5 to -0.4]) was selectively reduced in C9orf72-FTD. Nominally changed proteins in C9orf72-FTD included several inflammatory mediators. CONCLUSIONS:Using this multiplex panel, established markers recapitulated previously established trends, while less-studied biomarker candidates were also identified. If validated in independent cohorts, these candidates could broaden the repertoire of blood biomarkers reflecting genetic FTD pathophysiology.

Timely and accurate diagnosis of Alzheimer’s disease (AD) in clinical practice is a great challenge, especially during early disease stages with subtle or mild symptoms of cognitive decline. Moreover, robust and more accessible blood-based screening tests for early diagnosis are needed. In this study, we investigated the core AD blood biomarkers — amyloid beta 42 (Aβ42) and 40 (Aβ40) peptides, phosphorylated tau 181 (p-Tau181), neurofilament light chain (NfL), and total tau (t-Tau) — and extracellular vesicle (EVs) size and concentration in individuals characterized by different stages of cognitive decline to identify biochemical markers of dementia for early diagnosis. A total of n = 800 human plasma samples were analyzed. Plasma levels of NfL, t-Tau, p-Tau181, Aβ42, Aβ40 and plasma EVs were evaluated in n = 217 elderly healthy subjects (CTRL), in individuals with subjective cognitive complaints (SCC, n = 48), pre-mild cognitive impairment (pre-MCI, n = 58) and mild cognitive impairment (MCI, n = 426), and in n = 51 probable AD dementia patients (AD-dem), using ultrasensitive Single Molecule Array technology (Simoa®) and nanoparticle tracking analysis (NTA). Logistic regression and Receiver Operating Characteristic (ROC) analyses were employed. Plasma NfL displayed increased levels in AD-dem and MCI patients, while p-Tau181, Aβ42/Aβ40 ratio, Aβ42/p-Tau181 ratio, and EVs plasma levels were altered since the early stages of the pathology: in particular, p-Tau181 levels increased as cognitive symptoms worsened, already in the SCC and pre-MCI groups compared to CTRL, while the ratio of EVs concentration and size (EVs ratio) was decreased in all groups compared to CTRL. Plasma p-Tau181 best classified AD-dem patients from CTRL with an area under the curve (AUC) equal to 0.87, while EVs ratio best differentiated SCC from CTRL (AUC = 0.78). Combining p-Tau181 and EVs ratio with Aβ42/Aβ40 ratio and NfL, respectively, significantly improved the classification of pre-MCI and MCI from CTRL (AUCcomb = 0.79 and AUCcomb = 0.85). Combining biomarkers did not improve accuracy in discriminating MCI from SCC, pre-MCI and AD-dem. p-Tau181 and EVs ratio are promising biomarkers for the identification of individuals at risk of degenerative dementia. Combining the core AD plasma biomarkers with EVs ratio can aid in diagnosing the early stages of AD dementia.

Body mass index (BMI), type 2 diabetes (T2D) and associated cardiometabolic features modify Alzheimer's disease (AD) risk, yet shared mechanisms remain poorly understood. Using sex- and age-stratified genotyping data for BMI and T2D, we investigate how these traits converge on shared genetic pathways to AD risk. Employing multi-trait, machine learning and single-cell transcriptomics, we identify sex-specific cardiometabolic liability linked to higher BMI-associated risk in women and T2D-driven risk in men. Variant-level analyses reveal AD risk associates with genetically-driven hypotension and hypoglycaemia. We identify 35 putative effector genes in seven independent loci colocalizing between BMI/T2D and AD, mapping to peripheral immune and metabolic tissues and cell-types. Pathway enrichment identifies druggable targets in calcium and potassium channel signaling. Across 81 approved drugs modulating shared risk genes, levosimendan - a calcium sensitizer for heart failure - inhibits tau oligomerization and emerges as a repurposing candidate. These findings elucidate sex-specific cardiometabolic drivers of AD, identify actionable biological pathways, and reveal drug candidates for AD prevention and treatment.

BACKGROUND:The temporal sequence of clinical, imaging, and biological changes in sporadic frontotemporal lobar degeneration (FTLD)-associated syndromes remains poorly characterized, and a comprehensive biomarker cascade model is lacking. METHODS:We developed a data-driven biomarker cascade model in 489 patients across the FTLD spectrum (211 behaviorial variant frontotemporal dementia [bvFTD], 129 primary progressive aphasia [PPA], 71 corticobasal syndrome [CBS], 66 progressive supranuclear palsy [PSP], and 12 FTD associated with amyotrophic lateral sclerosis [FTD-ALS]; 1904 patient-visit observations). Plasma, magnetic resonance imaging (MRI), and clinical biomarkers were modeled using sigmoid trajectories fitted to covariate-adjusted longitudinal data. RESULTS:Plasma glial fibrillary acidic protein departed from normality earliest, followed by Trail Making Test Part B (TMT-B), white matter lesion volume, and neurofilament light chain. Insular atrophy showed the steepest transition among MRI measures; clinical dementia rating dementia staging instrument plus National Alzheimer's Coordinating Center behavior and language domains sum of boxes declined most steeply overall. TMT-B inflected earliest in bvFTD, whereas insula atrophy dominated in PPA. CONCLUSIONS:This first data-driven temporal cascade of multimodal biomarkers in sporadic FTLD-associated syndromes offers a framework for disease staging and stage-specific clinical trial design.

Individuals with autosomal dominant frontotemporal dementia (FTD) exhibit considerable variability in disease onset and progression. Both modifiable and non-modifiable factors-such as sex, educational attainment or geographic region of residence-may contribute to this heterogeneity, potentially through their influence on cognitive reserve. The aim of the present study was to investigate the role of cognitive reserve modulators within the Genetic Frontotemporal dementia Initiative (GENFI) cohort. To this end, we used functional MRI (i.e. spatial chronnectome measures) and neurodegenerative markers (i.e. plasma neurofilament light chains levels) to determine disease stage using a Discriminative Event-Based Model (DEBM). We then examined how potential modulators influence the relationship between disease stage and cognitive performance. We analysed a total of 711 participants, including 106 patients with genetic FTD, 325 presymptomatic mutation carriers and 280 non-carriers healthy controls. Female participants showed a weaker association between disease stage and cognitive performance compared to males (P < 0.001), with difference becoming progressively more pronounced across symptomatic stages. Educational attainment exhibited a similar effect: individuals with higher education demonstrated an attenuated association compared to those with secondary or primary schooling (P < 0.001), with differences already detectable at prodromal disease stages. The effect of geographical region of residence was associated with education levels, but appeared to have an indirect and less strong influence. In summary, sex and educational attainment significantly affect the development and maintenance of cognitive reserve in individuals with genetic FTD. These findings underscore the importance of identifying disease-modifying interventions since the presymptomatic stages of the disease.

Monogenic forms of Alzheimer's Disease (AD) and Frontotemporal Dementia (FTD) represent the two principal neurodegenerative disorders leading to early-onset dementia, primarily linked to mutations in key AD- and FTD-associated genes. The marked heterogeneity in age at onset and penetrance among carriers of pathogenic mutations suggests that monogenic variants act within a broader polygenic background. The combined impact of AD- and FTD-related genetic variation on disease incidence in monogenic forms remains largely unexplored. Herein, we investigate gene-gene interaction patterns in monogenic AD and FTD, with a focus on genetic variability in key AD (APP, PSEN1, PSEN2) and FTD (MAPT, GRN, C9orf72)-associated genes and their association with cumulative disease incidence. Within the GARDENIA Consortium, we studied 426 individuals from Italian pedigrees, including patients (n = 319) and presymptomatic (n = 107) carriers of causative variants in APP (n = 39), PSEN1 (n = 71), PSEN2 (n = 13), MAPT (n = 29), GRN (n = 188), and C9orf72 (n = 86). Age at symptoms onset, age at last follow-up and sex were recorded. Whole exome sequencing was performed, focusing on non-causative variants (n = 64) in the key AD (APP, PSEN1, PSEN2) and FTD genes (MAPT, GRN, C9orf72). Weighted genetic burden scores were derived using Fine-Gray competing risk models to estimate variant-specific effects on cumulative AD and FTD incidence, accounting for mutually exclusive outcomes and family clustering. Model fit was evaluated using Akaike Information Criterion. Higher AD-risk-weighted burden scores in AD-related genes were associated with a significantly increased cumulative incidence of AD, while higher FTD-risk-weighted scores in FTD-related genes showed a trend toward association with increased cumulative incidence of FTD. A significant interaction between burden scores was observed. AD and FTD burden scores showed a negative interaction for AD (~79% attenuation) but a modest synergistic effect for FTD (~6% increase). These findings could imply context-dependent pleiotropy rather than simple additive genetic effects. Our study suggests that even in carriers oh highly penetrant AD or FTD causative variants, genetic background could substantially modulate cumulative disease incidence. Integrating polygenic information with monogenic status may improve prognostic stratification and inform precision approaches in dementia research and clinical trials.

Dysregulation contributes to Alzheimer’s disease (AD) pathophysiology. Zinc therapy promotes enterocyte copper sequestration, potentially reducing systemic copper. Individual biological responses may vary. Methods: ZINCAiD was a 24-week, randomized, double-blind, placebo-controlled phase II trial assessing zinc therapy in individuals with mild cognitive impairment (MCI) due to AD (EudraCT No.: 2019-000604-15; registered on 26 March 2020). Participants were randomized 2:1 to receive elemental zinc (135 mg/day for 12 weeks, then 65 mg/day) or placebo. Ceruloplasmin was measured at predefined intervals for safety monitoring, blinded to the investigators. Post hoc, “Zinc Responders” were defined by ≥20% reduction in ceruloplasmin at week 12. The primary cognitive endpoint was the Cognitive Composite 2 scale (CC2); secondary endpoints included MMSE and CDR-Sob. Findings: Of the 48 participants randomized, 9 discontinued, primarily due to unrelated clinical deterioration; 39 had complete ceruloplasmin data. Two serious adverse events occurred in the Placebo group. Mild gastrointestinal symptoms occurred in eight participants, with only four leading to dropout. In the primary zinc vs. placebo analysis, no significant differences emerged in cognitive outcomes. A post hoc exploratory analysis stratified participants by pharmacodynamic response: 12 individuals with MCI due to AD (31%) met the criteria for “Zinc Responder,” defined by ≥20% reduction in serum ceruloplasmin at week 12. Only Zinc Responders maintained cognitive stability over 24 weeks, whereas the combined group of Zinc Non-Responders and placebo-treated participants showed a significant decline. For the composite cognitive score (CC2), the interaction between visit and response group was significant (p = 0.030), with deterioration observed only in the Non-Responder + Placebo group (Δ = –2.72, p < 0.0001 vs. –0.71, p = 0.35 in Responders). Similar patterns were observed for CDR-Sob (interaction p = 0.017) and MMSE (trend p = 0.09). Interpretation: Zinc therapy stabilized cognition in a pharmacodynamically defined MCI subgroup. These exploratory findings suggest serum ceruloplasmin as a feasible biomarker of target engagement. Larger trials are needed for confirmation.

Purpose. Treatments for mental disorders, such as pharmacotherapy and psychosocial interventions, do not always guarantee symptomatic remission. The effectiveness of Physical Activity (PA) in improving the psycho- physical health of individuals with various mental disorders is well-established; however, its effects on borderline personality disorder (BPD) have yet to be adequately studied. Currently, there are not approved pharmacological treatments for BPD, and access to effective psychotherapeutic interventions remains limited. This study aims to evaluate the efficacy of a PA programme as an adjunctive treatment for patients with BPD, in comparison with a control treatment. Objectives include reducing BPD symptoms and improving PA levels, as well as physical and psychological health. Methods. PABORD is a randomised controlled trial (RCT) targeting female outpatients aged 18-40 with a diagnosis of BPD. The intervention group (n=32) will participate in a structured 12-week PA programme, supervised by a sports physician and preceded by three psychoeducational sessions on healthy eating habits. The control group (n=32) will receive 8 parallel psychoeducational sessions focusing on PA, diet, and the risks associated with sedentary behaviour. Standardised assessments will be conducted at baseline, at the end of the intervention, and three months post-intervention. Results. Not yet available. Discussion and conclusions. The PA programme is expected to outperform the control treatment in terms of health status and PA levels at the end of the intervention. Repeated clinical assessments will aid in identifying psychosocial factors associated with the maintenance of PA. The study may provide valuable insights that could improve therapeutic options for patients with BPD.

Scopo. I trattamenti per i disturbi mentali, come la farmacoterapia e gli interventi psicosociali, non garantiscono sempre la remissione sintomatologica. L’efficacia dell’attività fisica (AF) nel miglioramento della salute psicofisica di individui affetti da vari disturbi mentali è ormai consolidata, ma i suoi effetti sul disturbo borderline di personalità (DBP) non sono stati ancora adeguatamente studiati. Attualmente, non esistono trattamenti farmacologici approvati per il DBP e l’accesso a interventi psicoterapeutici efficaci rimane limitato. Questo studio si propone di valutare l’efficacia di un programma di AF come trattamento aggiuntivo per pazienti con DBP, confrontandolo con un trattamento di controllo. Gli obiettivi includono la riduzione dei sintomi del DBP e il miglioramento dei livelli di AF, della salute fisica e psicologica. Metodi. PABORD è uno studio clinico randomizzato controllato (RCT) rivolto a pazienti ambulatoriali di sesso femminile (18-40 anni) con diagnosi di DBP. Il gruppo di intervento (n=32) parteciperà a un programma strutturato di AF della durata di 12 settimane, supervisionato da un medico dello sport e preceduto da tre sessioni di psicoeducazione sulle corrette abitudini alimentari. Il gruppo di controllo (n=32) seguirà in parallelo 8 sessioni di psicoeducazione focalizzate su AF, dieta e sui rischi della sedentarietà. Saranno condotte valutazioni standardizzate all’inizio, alla fine dell’intervento e a tre mesi dal termine dello stesso. Risultati. Non ancora disponibili. Discussione e Conclusioni. Si ipotizza che il programma di AF risulti superiore al trattamento di controllo in termini di stato di salute e di livelli di AF al termine dell’intervento. Valutazioni cliniche ripetute contribuiranno a identificare i fattori psicosociali associati al mantenimento dell’AF. Lo studio potrebbe fornire nuove informazioni utili a migliorare le opzioni terapeutiche per le pazienti affette da DBP.

Traditional statistical approaches have advanced our understanding of the genetics of complex diseases, yet are limited to linear additive models. Here we applied machine learning (ML) to genome-wide data from 41,686 individuals in the largest European consortium on Alzheimer's disease (AD) to investigate the effectiveness of various ML algorithms in replicating known findings, discovering novel loci, and predicting individuals at risk. We utilised Gradient Boosting Machines (GBMs), biological pathway-informed Neural Networks (NNs), and Model-based Multifactor Dimensionality Reduction (MB-MDR) models. ML approaches successfully captured all genome-wide significant genetic variants identified in the training set and 22% of associations from larger meta-analyses. They highlight 6 novel loci which replicate in an external dataset, including variants which map to ARHGAP25, LY6H, COG7, SOD1 and ZNF597. They further identify novel association in AP4E1, refining the genetic landscape of the known SPPL2A locus. Our results demonstrate that machine learning methods can achieve predictive performance comparable to classical approaches in genetic epidemiology and have the potential to uncover novel loci that remain undetected by traditional GWAS. These insights provide a complementary avenue for advancing the understanding of AD genetics.

The non-fluent/agrammatic variant of primary progressive aphasia is a neurodegenerative disorder characterized by effortful language production and impaired comprehension of grammatically complex sentences. Recently, interest in non-pharmacological interventions has increased, particularly regarding techniques that allow for non-invasive brain stimulation, such as transcranial direct current stimulation. The main purpose of this study was to investigate whether the use of anodal transcranial direct current stimulation applied to the dorsolateral prefrontal cortex during individualized language training for 25 min a day at 5 days a week for 2 weeks would lead to significant oral naming improvements in patients with agrammatic variant of primary progressive aphasia. Specifically, we hypothesized that anodal transcranial direct current stimulation plus individualized language training may improve the oral naming of treated and untreated objects compared with both placebo transcranial direct current stimulation plus individualized language therapy and anodal transcranial direct current stimulation combined with computerized cognitive training. Forty-seven agrammatic variant of primary progressive aphasia patients were consecutively enrolled and randomized into one of three groups that received the following treatments: (i) anodal transcranial direct current stimulation over the left dorsolateral prefrontal cortex during individualized language rehabilitation treatment; (ii) placebo transcranial direct current stimulation during individualized language rehabilitation treatment; or (iii) anodal transcranial direct current stimulation with computerized cognitive training. Clinical, neuropsychological and language assessments were recorded at baseline (T0), post-treatment (T1, 2 weeks) and at 12 weeks from T0 (T2). Magnetic resonance imaging data, functional magnetic resonance imaging data and blood samples were collected at T0 and T1. All of the groups demonstrated improvements in oral object naming at T1, with maintenance effects being observed at T2. At T1, the enhancement in the oral naming of treated and untreated objects was significantly greater in patients who underwent anodal transcranial direct current stimulation during individualized language rehabilitation treatment. There were no significant changes observed across the groups regarding the magnetic resonance imaging, functional magnetic resonance imaging or blood biochemical marker data. Our results support the beneficial effects of individualized language rehabilitation treatment in combination with anodal transcranial direct current stimulation in agrammatic variant of primary progressive aphasia patients.

Mental health disorders (MHD) are conditions marked by disturbances in thinking, mood, or behavior that can cause significant distress or impair daily functioning. Diagnosis remains challenging, particularly in precision medicine, due to the scarcity of reliable biomarkers as objective diagnostic tools and external validators. This study investigates essential trace metals, cofactors in vital enzymes, as potential biomarkers for MHD. A total of 168 patients with mood spectrum disorders (MSD), schizophrenia spectrum disorders (SSD), and personality disorders (PD) and 61 healthy controls (HC) were evaluated for serum levels of zinc (Zn), copper (Cu), iron (Fe), magnesium (Mg), as well as transferrin (TF), transferrin saturation (% TF-sat), ferritin (F), and Cu/Zn, Cu/Mg, Fe/Cu ratios. Principal Component Analysis (PCA) and regression models assessed the relationship between these biological variables and MHD. Zn levels were lower in patients, particularly in the PD group. Fe, TF, and % TF-sat were also lower in patients, with the SSD group showing the greatest decrease. Mg levels were similarly lower in patients than in controls. Zn, Fe, Fe/Cu, and TF showed protective effects against MHD, with odds ratios ranging from 0.22 to 0.50. The Cu/Zn ratio was higher in all patients' groups. The Cu component, including Cu, Cu/Zn, and Cu/Mg levels, was linked to an 84% increase in the odds of having an MHD. This study highlights the potential of trace metals as adjunctive biomarkers in psychiatry, supporting clinical diagnosis and offering new insights into psychiatric pathophysiology.