Neurofilament light chain (NFL) is a structural axonal protein released into extracellular fluids following neuroaxonal injury. Blood-based NfL measurement has emerged as a marker of neurodegeneration, but its relevance in geriatric psychiatry remains insufficiently defined. We conducted a narrative review of peer-reviewed studies reporting serum or plasma NfL concentrations in older adults with neurodegenerative diseases or major psychiatric disorders. In MEDLINE/PubMed, were searched up to 31 October 2025. We synthesised data on normative values and biological determinants, compared NfL levels across diagnostic categories, examined evidence from mild behavioral impairment and late-onset psychiatric presentations, and developed a clinically oriented interpretative framework. Across studies, blood NfL concentrations increased with age and were influenced by medical comorbidities, particularly renal function. Neurodegenerative disorders were associated with higher NfL levels than primary psychiatric disorders, whereas most psychiatric conditions overlapped with age-adjusted normative ranges. Meta-analytic evidence showed no significant elevation in major depressive disorder and modest, heterogeneous increases in bipolar disorder, while schizophrenia spectrum disorders largely overlapped with physiological ageing. In transdiagnostic contexts, including mild behavioral impairment and late-onset psychiatric syndromes, higher baseline NfL levels and steeper longitudinal increases were associated with greater risk of underlying neurodegeneration. These findings support a stepwise interpretation strategy integrating age, comorbidities, clinical context and longitudinal trajectories. Age- and comorbidity-adjusted interpretation of blood NfL can support risk stratification in geriatric psychiatry. Used as an adjunctive biomarker, NfL may help identify patients requiring monitoring or additional neurological assessment.

Conventional psychiatric diagnoses often fail to reflect the underlying neurobiological and behavioral complexity of mental health conditions. Here, we propose a transdiagnostic, data-driven framework for stratifying youth based on large-scale multisite electroencephalography (EEG) data from 1,707 individuals aged 5–18 years, including healthy controls and individuals diagnosed with attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), anxiety disorders (ANX), and learning disabilities (LD), along with their common comorbidities. By applying normative modeling to quantify individual deviations from typical brain functional maturation, and integrating multidimensional EEG features across spectral, temporal, complexity, and dynamical domains via similarity network fusion clustering, we identified three robust neurophysiological biotypes. These biotypes showed distinct electrophysiological and behavioral profiles, and captured meaningful brain-behavior relationships. Our findings suggest that biologically informed subtypes capture meaningful neuropsychiatric heterogeneity in youth, challenging conventional diagnostic boundaries in psychiatric nosology. ### Competing Interest Statement The authors have declared no competing interest.

INTRODUCTION:Negative symptoms, such as apathy and diminished motivation, are critical for prognosis and treatment outcomes in neurological and psychiatric disorders. However, constructs and assessment scales differ significantly across neuropsychiatric disorders. This study examines the psychometric properties of two scales used to assess apathy - the apathy-motivation index (AMI) and the diagnostic criteria for apathy (DCA) - compared to schizophrenia-specific tools, namely the brief negative symptoms scale (BNSS) and the positive and negative syndrome scale (PANSS). METHODS:We conducted a cross-sectional, multicenter study with 151 individuals with schizophrenia across six European sites. Participants were assessed using the AMI, DCA, BNSS, PANSS, and other clinical and functional scales. BNSS motivation and pleasure factor (BNSS_MAP) assessed motivation, and personal and social performance (PSP) assessed functioning. Convergent validity across these tools was examined through bivariate correlations (Pearson r) and exploratory factor analysis for the AMI. Cut-off points for apathy used receiver operating characteristic (ROC) analysis, with DCA as the reference. RESULTS:We found low convergence between BNSS_MAP and AMI (r=.31, p<.001) and moderate convergence between BNSS_MAP and DCA (r=.48, p<.001). PSP correlated with BNSS_MAP, PANSS_negative and DCA (r=-.615, r=-.446 and r=-.430, respectively, all p<0.001), but not with AMI (r=-.108; p=.218). ROC analysis yielded cut-off points of 28.5 (BNSS total), 16.5 (BNSS_MAP), 14.5 (PANSS_negative), and 33.5 (AMI total) for detecting clinical apathy. CONCLUSION:Current apathy and motivation scales show limited overlap, reflecting the complexity of measuring transdiagnostic constructs. Combining clinician- and patient-rated measures may provide a more comprehensive understanding of apathy in schizophrenia and other neuropsychiatric conditions.

Electroencephalography (EEG) has been thoroughly studied for decades in neurodevelopmental and psychiatric research. Yet its integration into clinical practice as a diagnostic/prognostic tool remains unachieved. We hypothesize that a key reason is the underlying patient's heterogeneity, overlooked in EEG research relying on a case-control approach. We combine high-density EEG with normative modeling to quantify this heterogeneity using two well-established and extensively investigated EEG characteristics -spectral power and functional connectivity- across a cohort of 1674 patients with attention-deficit/hyperactivity disorder, autism spectrum disorder, learning disorder, or anxiety, and 560 matched controls. Normative models showed that deviations from population norms among patients were highly heterogeneous and frequency-dependent. Deviation spatial overlap across patients did not exceed 40% and 24% for spectral and connectivity, respectively. Considering individual deviations in patients has significantly enhanced comparative analysis, and the identification of patient-specific markers has demonstrated a correlation with clinical assessments, representing a crucial step towards attaining precision psychiatry through EEG.

OBJECTIVES:The ASAP study investigated whether amyloid load in the brain would be associated with poor antidepressant response in the short term (8 weeks) and worse clinical outcomes (remission status) in the long term (2 years). METHODS:Nondemented older adults with non-treatment-resistant depression were enrolled in an 8-week observational study to assess the relationship between amyloid load and antidepressant response and subsequently followed for 2 years. Amyloid load was measured using 18F-Florbetapir Positron Emission Tomography scans, and treatment response was evaluated using the Montgomery-Åsberg Depression Rating Scale. The primary analysis compared amyloid load in responders versus nonresponders at week 8 and in remitters versus non-remitters at year 1 and year 2, employing logistic regressions controlled for potential confounders. RESULTS:A total of 73 (among which 56% were responders and 30% were remitters), 63 (48% remitters) and 56 (54% remitters) participants were included in the analysis at week 8, year 1 and year 2, respectively. We found no significant association between amyloid load and treatment response at week 8. However, remission status at year 2 was positively associated with higher total amyloid load at baseline, independent of confounders (OR = 1.28, 95% CI [1.02-1.60]). CONCLUSIONS:In this observational cohort of nondemented depressed older adults, amyloid load does not appear to modify response status in the short term. Conversely, greater amyloid load was associated with better clinical outcomes in the long term. Amyloid may influence the long-term course of depressive symptoms by altering the serotoninergic system and/or modifying the clinical presentation of depression.

Introduction Les troubles psychiatriques sont des pathologies chroniques à risque de décompensation, donc d’hospitalisations. La réadmission précoce se caractérise par une hospitalisation dans les trois mois suivant la sortie. Les facteurs de risque dans la littérature sont les antécédents d’hospitalisation, âge jeune, sexe, diagnostic, durée de séjour allongée et comorbidité addictive. Le recours à la chambre de soins intensifs (CSI) est un témoin objectivable d’instabilité psychomotrice. Cliniquement, les patients admis en CSI semblent plus susceptibles d’être réhospitalisés. Cette étude a pour objectif d’analyser si le recours à la CSI est un facteur de risque pronostique de réadmission précoce. Matériel et méthodes Il s’agit d’une étude observationnelle rétrospective monocentrique de 712 patients ayant eu une sortie définitive d’une unité de psychiatre adulte du centre hospitalier Guillaume Régnier sur l’année 2019. Les données cliniques, paracliniques, administratives et sociodémographiques ont été recueillies. Deux types d’analyses a posteriori ont été réalisés : analyses de sensibilité avec retrait de variables et en sous-population. Résultats Les patients étaient répartis en deux groupes, selon le recours à la CSI (groupe CSI+ ; n=108) ou non (groupe CSI– ; n=604). Le taux de réadmission précoce était de 25,9 % pour le groupe CSI+ contre 23,7 % pour le groupe CSI–. Les analyses univariées et multivariées n’ont pas permis de mettre en évidence d’association significative entre le recours à la CSI et la réadmission précoce (p=0,62, OR=1,13 [0,67–1,89]). L’hospitalisation antérieure était significativement associée à la réadmission précoce (p=2,4.10–8, OR=3,99 [2,49–6,63]). Sur un an de suivi, 36,4 % des patients étaient réadmis, dont deux tiers durant le premier trimestre, avec une sur-représentativité du groupe CSI+. Les résultats des analysesa posteriorin’ont pas modifié le résultat initial. Conclusion Le recours à la CSI, témoin d’une instabilité psychomotrice, n’est pas significativement associé avec la réadmission précoce.

Systemic inflammation has been linked with major depressive episode (MDE) severity and treatment-resistant depression (TRD), but not for all patients. Brain mechanisms underlying these processes are still under investigation. Objectives: based on an integrative approach, we aimed at identifying clinical, inflammatory and perfusion markers predictive of depression outcome at 6 months. We conducted a longitudinal study including 60 patients diagnosed with MDE, focusing on anxiety and anhedonia as main clinical candidates, inflammation (C-Reactive Protein - CRP) and cerebral blood flow (CBF) using pseudo-continuous arterial spin labeling (pcASL) MRI. A bootstrapped elastic net regression analysis was conducted including clinical, CBF and inflammation as predictors with depressive severity at 6 months as the dependent variable. Our findings exhibited positive association of depression outcome with baseline depression intensity, duration of current episode, CRP, right accumbens, as well as left and right orbito-frontal CBF. Negative predictors were age, disease duration, right and left caudate nuclei, left amygdala, left mid frontal gyrus, and right ventromedial prefrontal cortex CBF. Neither anxiety nor anhedonia were significant predictors. Combining clinical, inflammation and brain imaging outperformed other models in diagnosing depression severity change over time, highlighting the interest of integrative approaches. These results suggested that systemic inflammation and cerebral perfusion abnormalities in key regions involved in emotion, reward processing and decision making, may serve as biomarkers for identifying patients at risk for persistence of depression.

Diabetic retinopathy (DR) is a leading cause of vision loss in patients with diabetes. While medical treatments like retinal laser photocoagulation, anti-VEGF therapy, and vitrectomy are primary, complementary therapies are gaining increasing attention. Based on the existing literature, a healthy lifestyle, including a balanced diet, stress management techniques, and regular physical activity targeting DR, can help regulate blood sugar levels and improve overall physical and mental health to reduce complications. This article explores physical activities and visual training methods related to DR, emphasizing complementary therapies, even though some of these practices are currently not fully integrated into evidence-based ophthalmology. Low vision exercises and aids help patients make the most of their remaining vision, improving their ability to perform everyday tasks, reducing the impact of vision loss, and promoting independence. There is some evidence that eye-related physiotherapy can improve the quality of life for patients with DR, although selection bias cannot be excluded in the presented studies. Consistent physical activity promotes holistic health, and therapies should be regularly monitored by ophthalmologists. This review further helps integrative healthcare professionals in offering appropriate therapies for rehabilitation purposes in the treatment of ophthalmic diseases, particularly DR.

Late-life depression (LLD) is both common and disabling and doubles the risk of dementia onset. Apathy might constitute an additional risk of cognitive decline but clear understanding of its pathophysiology is lacking. While white matter (WM) alterations have been assessed using diffusion tensor imaging (DTI), this model cannot accurately represent WM microstructure. We hypothesized that a more complex multi-compartment model would provide new biomarkers of LLD and apathy. Fifty-six individuals (LLD n = 35, 26 females, 75.2 ± 6.4 years, apathy evaluation scale scores (41.8 ± 8.7) and Healthy controls, n = 21, 16 females, 74.7 ± 5.2 years) were included. In this article, a tract-based approach was conducted to investigate novel diffusion model biomarkers of LLD and apathy by interpolating microstructural metrics directly along the fiber bundle. We performed multivariate statistical analysis, combined with principal component analysis for dimensional data reduction. We then tested the utility of our framework by demonstrating classically reported from the literature modifications in LDD while reporting new results of biological-basis of apathy in LLD. Finally, we aimed to investigate the relationship between apathy and microstructure in different fiber bundles. Our study suggests that new fiber bundles, such as the striato-premotor tracts, may be involved in LLD and apathy, which bring new light of apathy mechanisms in major depression. We also identified statistical changes in diffusion MRI metrics in 5 different tracts, previously reported in major cognitive disorders dementia, suggesting that these alterations among these tracts are both involved in motivation and cognition and might explain how apathy is a prodromal phase of degenerative disorders.

Owing to its promiscuous roles, poly (ADP-ribose) polymerase-1 (PARP-1) is involved in various neurological disorders including several retinal pathologies. Diabetic retinopathy (DR) is the most common microvascular complication of diabetes mellitus affecting the retina. In the present review, we highlight the importance of PARP-1 participation in pathophysiology of DR and discuss promising potential inhibitors for treatment. A high glucose level enhances PARP-1 expression; PARP inhibitors have gained attention due to their potential therapeutic effects in DR. They target different checkpoints (blocking nuclear transcription factor (NF-κB) activation; oxidative stress protection, influence on vascular endothelial growth factor (VEGF) expression, impacting neovascularization). Nowadays, there are several improved clinical PARP-1 inhibitors with different allosteric effects. Combining PARP-1 inhibitors with other compounds is another promising option in DR treatments. Besides pharmacological inhibition, genetic disruption of the PARP-1 gene is another approach in PARP-1-initiated therapies. In terms of future treatments, the limitations of single-target approaches shift the focus onto combined therapies. We emphasize the importance of multi-targeted therapies, which could be effective not only in DR, but also in other ischemic conditions.

In middle-aged or elderly patients with treatment-resistant depression (TRD), gray matter (GM) volume changes have been reported in amygdala and related limbic regions. Here, we investigate GM and white matter (WM) volumes in young adult patients with resistant or remitted depression using voxel-based morphometry, an established research method.

The negative symptoms of schizophrenia can determine its functional outcome. Despite this clinical significance, no treatment exists to date; numerous pharmacological and non-pharmacological clinical trials have failed to demonstrate efficacy. Many of these trials have evaluated negative symptoms as a single clinical construct despite emerging evidence that negative symptoms constitute at least two independent clinical dimensions: deficits in motivation and pleasure (MAP) and in emotional expression (EXP). These two dimensions are best evaluated using new assessment tools, such as the Brief Negative Symptom Scale (BNSS). However, older assessment tools, and particularly the Positive and Negative Syndrome Scale (PANSS) remain widely used in past and current research. Here, we sought to predict BNSS MAP and EXP dimensions from the PANSS. Using complementary modelling approaches across three heterogeneous, multi-centre, multi-culture patient samples (n=1241 patients, 1846 observations), we show that EXP can be estimated predominantly using two PANSS items N1 and N6 (55%-81% variance explained across models and samples), MAP can be estimated (43%-60% variance explained) predominantly using N2 and N4. Additionally, PANSS-estimated MAP shows similar associations with functioning to that measured on BNSS MAP dimension. Together, our results suggest that while EXP can be reliably estimated from PANSS, MAP cannot be consistently estimated from PANSS across samples and cultures. This warrants caution when using the PANSS to estimate MAP and emphasises the need for using the newer assessment tools for negative symptoms. Funding: The data for the Italian sample were collected as part of a national multicenter project promoted by the Italian Network for Research on Psychoses. For the baseline data, the study was funded by the PRIN 2014 project from the Italian Ministry of Education, University and Research "Factors Influencing Social Functioning of People With Schizophrenia" (Grant Number: 2010XP2XR4), the Italian Society of Psychopathology (SOPSI), the Italian Society of Biological Psychiatry (SIPB), Roche, Lilly, AstraZeneca, Lundbeck and Bristol-Myers Squibb. For the follow-up data, the study was funded by the PRIN 2017 project from the Italian Ministry of Education, University and Research "Factors influencing real-life functioning of people with a diagnosis of schizophrenia: a four-year follow-up multicenter study" (Grant Number: 2017M7SZM8). Declaration of Interest: Corresponding authors AM received advisory board or consultant fees from the following drug companies: Gedeon Richter Bulgaria, Janssen Pharmaceuticals, Lundbeck, Otsuka Pharmaceutical, Pfizer, Pierre Fabre and Rovi Pharma outside the submitted work. JL has received honoraria from Sumitomo Pharmaceuticals, Lundbeck Singapore, Otsuka Pharmaceutical and Janssen Pharmaceutical. EFE has received consultancy honoraria from Boehringer-Ingelheim (2022), Atheneum (2022) and Rovi (2022-24), speaker fees by Adamed (2022-24), Otsuka (2023) and Viatris (2024) and training and research material from Merz (2020) and editorial honoraria from Elsevier. All other authors, included first author, has no conflict of interest to disclose in this project. Ethical Approval: Ethical approval was obtained by each participating centre for each of the three samples.

Background: The treatment of depressive episodes is well established, with clearly demonstrated effectiveness of antidepressants and psychotherapies. However, more than one-third of depressed patients do not respond to treatment. Identifying the brain structural basis of treatment-resistant depression could prevent useless pharmacological prescriptions,adverse events, and lost therapeutic opportunities.Methods: Using diffusion magnetic resonance imaging, we performed structural connectivity analyses on a cohort of 154 patients with mood disorder (MD) – and 77 sex- and age-matched healthy control (HC) participants. To assess illness improvement, the MD patients went through two clinical interviews at baseline and at 6-month follow-up and were classified based on the Clinical Global Impression-Improvement score into improved or not-improved. First, the threshold-free network-based statistics was conducted to measure the differences in regional network architecture. Second, nonparametric permutations tests were performed on topological metrics based on graph theory to examine differences in connectome organization. Results: The threshold-free network-based statistics revealed impaired connections involvingregions of the basal ganglia in MD patients compared to HC. Significant increase of local efficiency and clustering coefficient was found in the lingual gyrus, insula and amygdala in the MD group. Compared with the not-improved, the improved displayed significantly reduced network integration and segregation, predominately in the default-mode regions, including the precuneus, middle temporal lobe and rostral anterior cingulate.Conclusions: This study highlights the involvement of regions belonging to the basal ganglia, the fronto-limbic network and the default mode network, leading to a better understanding of MD disease and its unfavorable outcome.

Electroencephalography (EEG) has been thoroughly studied for decades in psychiatry research. Yet its integration into clinical practice as a diagnostic/prognostic tool remains unachieved. We hypothesize that a key reason is the underlying patient’s heterogeneity, overlooked in psychiatric EEG research relying on a case-control approach. We combine HD-EEG with normative modeling to quantify this heterogeneity using two well-established and extensively investigated EEG characteristics -spectral power and functional connectivity-across a cohort of 1674 patients with attention-deficit/hyperactivity disorder, autism spectrum disorder, learning disorder, or anxiety, and 560 matched controls. Normative models showed that deviations from population norms among patients were highly heterogeneous and frequency-dependent. Deviation spatial overlap across patients did not exceed 40% and 24% for spectral and connectivity, respectively. Considering individual deviations in patients has significantly enhanced comparative analysis, and the identification of patient-specific markers has demonstrated a correlation with clinical assessments, representing a crucial step towards attaining precision psychiatry through EEG.### Competing Interest StatementThe authors have declared no competing interest.

BACKGROUND:Better understanding apathy in late-life depression would help improve prediction of poor prognosis of diseases such as dementia. Actimetry provides an objective and ecological measure of apathy from patients' daily motor activity. We aimed to determine whether patterns of motor activity were associated with apathy and brain connectivity in networks that underlie goal-directed behaviors. METHODS:Resting-state functional magnetic resonance imaging and diffusion magnetic resonance imaging were collected from 38 nondemented participants with late-life depression. Apathy was evaluated using the diagnostic criteria for apathy, Apathy Evaluation Scale, and Apathy Motivation Index. Functional principal components (fPCs) of motor activity were derived from actimetry recordings taken for 72 hours. Associations between fPCs and apathy were estimated by linear regression. Subnetworks whose connectivity was significantly associated with fPCs were identified via threshold-free network-based statistics. The relationship between apathy and microstructure metrics was estimated along fibers by diffusion tensor imaging and a multicompartment model called neurite orientation dispersion and density imaging via tractometry. RESULTS:We found 2 fPCs associated with apathy: mean diurnal activity, negatively associated with Apathy Evaluation Scale scores, and an early chronotype, negatively associated with Apathy Motivation Index scores. Mean diurnal activity was associated with increased connectivity in the default mode, cingulo-opercular, and frontoparietal networks, while chronotype was associated with a more heterogeneous connectivity pattern in the same networks. We did not find significant associations between microstructural metrics and fPCs. CONCLUSIONS:Our findings suggest that mean diurnal activity and chronotype could provide indirect ambulatory measures of apathy in late-life depression, associated with modified functional connectivity of brain networks that underlie goal-directed behaviors.

Late-life depression is a common disorder in the elderly, difficult to treat, where apathy contributes to a poor prognosis. Despite its severity and frequency, the pathophysiology of LLD remains complex and its exploration challenging. While white matter (WM) damages have been assessed using diffusion tensor imaging, this model cannot correctly represent the WM microstructure. We hypothesized that using a more complex multi-compartment model, never used on LLD, would better describe the WM microstructure. In this article, we performed a tract-based approach to investigate novel diffusion-model biomarkers of LLD and apathy, by interpolating the microstructural metrics directly along the fibers. We performed a multivariate statistical analysis along the fiber, combined with a principal component analysis for dimensional data reduction. Then, we tested the utility of our framework by showing classical modifications in LDD. Finally, we aimed to investigate the relationship between apathy and microstructure in different fibers. Our study suggests that new tracts, such as striato-premotor, may be involved in LLD and apathy, which has not been observed in previous studies. We also identified modifications of inflammation metrics in 5 different tracts, already reported in dementia, which may contribute to the cognitive decline observed with apathy.