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Brain age is a widely used index for quantifying individuals’ brain health as deviation from a normative brain aging trajectory. Higher-than-expected brain age is thought partially to reflect above-average rate of brain aging. Here, we explicitly tested this assumption in two independent large test datasets (UK Biobank [main] and Lifebrain [replication]; longitudinal observations ≈ 2750 and 4200) by assessing the relationship between cross-sectional and longitudinal estimates of brain age. Brain age models were estimated in two different training datasets (n ≈ 38,000 [main] and 1800 individuals [replication]) based on brain structural features. The results showed no association between cross-sectional brain age and the rate of brain change measured longitudinally. Rather, brain age in adulthood was associated with the congenital factors of birth weight and polygenic scores of brain age, assumed to reflect a constant, lifelong influence on brain structure from early life. The results call for nuanced interpretations of cross-sectional indices of the aging brain and question their validity as markers of ongoing within-person changes of the aging brain. Longitudinal imaging data should be preferred whenever the goal is to understand individual change trajectories of brain and cognition in aging. Scientists who study the brain and aging are keen to find an effective way to measure brain health, which could help identify people at risk for dementia or memory problems. One popular marker is ‘brain age’. This measurement uses a brain scan to estimate a person’s chronological age, then compares the estimated brain age to the person’s actual age to determine whether their brain is aging faster or slower than expected for their age. However, since brain age relies on one brain scan taken at one point in time, it is not clear whether it really measures brain aging or if it might capture brain differences that have been present throughout the individual’s life. Studies comparing individual brain scans over several years would be necessary to know for sure. Now, Vidal-Piñeiro et al. show that the brain-age measurement does not reflect faster brain aging. In the experiments, the researchers compared repeated brain scans of thousands of individuals over 40 years of age. The experiments showed that deviations from normative brain age detected in a single scan reflected early life differences more than changes in the brain over time. For example, people with older-looking brains were more likely to have had a low birth weight or to have a combination of genes associated with having an older looking brain. Vidal-Piñeiro et al. show that brain age mostly reflects a pre-existing brain condition rather than brain aging. The experiments also suggest that genetics and early brain development likely have a strong impact on brain health throughout life. Future studies trying to test or develop brain-aging measurements should use serial measurements to track brain changes over time.

We aimed to characterize the cognitive profile of post-acute COVID-19 syndrome (PACS) patients with cognitive complaints, exploring the influence of biological and psychological factors. Participants with confirmed SARS-CoV-2 infection and cognitive complaints ≥ 8 weeks post-acute phase were included. A comprehensive neuropsychological battery (NPS) and health questionnaires were administered at inclusion and at 1, 3 and 6 months. Blood samples were collected at each visit, MRI scan at baseline and at 6 months, and, optionally, cerebrospinal fluid. Cognitive features were analyzed in relation to clinical, neuroimaging, and biochemical markers at inclusion and follow-up. Forty-nine participants, with a mean time from symptom onset of 10.4 months, showed attention-executive function (69%) and verbal memory (39%) impairment. Apathy (64%), moderate-severe anxiety (57%), and severe fatigue (35%) were prevalent. Visual memory (8%) correlated with total gray matter (GM) and subcortical GM volume. Neuronal damage and inflammation markers were within normal limits. Over time, cognitive test scores, depression, apathy, anxiety scores, MRI indexes, and fluid biomarkers remained stable, although fewer participants (50% vs. 75.5%; p = 0.012) exhibited abnormal cognitive evaluations at follow-up. Altered attention/executive and verbal memory, common in PACS, persisted in most subjects without association with structural abnormalities, elevated cytokines, or neuronal damage markers.

Patients with post-coronavirus disease 2019 (COVID-19) conditions typically experience cognitive problems. Some studies have linked COVID-19 severity with long-term cognitive damage, while others did not observe such associations. This discrepancy can be attributed to methodological and sample variations. We aimed to clarify the relationship between COVID-19 severity and long-term cognitive outcomes and determine whether the initial symptomatology can predict long-term cognitive problems. Cognitive evaluations were performed on 109 healthy controls and 319 post-COVID individuals categorized into three groups according to the WHO clinical progression scale: severe-critical ( n  = 77), moderate-hospitalized ( n  = 73), and outpatients ( n  = 169). Principal component analysis was used to identify factors associated with symptoms in the acute-phase and cognitive domains. Analyses of variance and regression linear models were used to study intergroup differences and the relationship between initial symptomatology and long-term cognitive problems. The severe-critical group performed significantly worse than the control group in general cognition (Montreal Cognitive Assessment), executive function (Digit symbol, Trail Making Test B, phonetic fluency), and social cognition (Reading the Mind in the Eyes test). Five components of symptoms emerged from the principal component analysis: the “Neurologic/Pain/Dermatologic” “Digestive/Headache”, “Respiratory/Fever/Fatigue/Psychiatric” and “Smell/ Taste” components were predictors of Montreal Cognitive Assessment scores; the “Neurologic/Pain/Dermatologic” component predicted attention and working memory; the “Neurologic/Pain/Dermatologic” and “Respiratory/Fever/Fatigue/Psychiatric” components predicted verbal memory, and the “Respiratory/Fever/Fatigue/Psychiatric,” “Neurologic/Pain/Dermatologic,” and “Digestive/Headache” components predicted executive function. Patients with severe COVID-19 exhibited persistent deficits in executive function. Several initial symptoms were predictors of long-term sequelae, indicating the role of systemic inflammation and neuroinflammation in the acute-phase symptoms of COVID-19.” Study Registration : www.ClinicalTrials.gov , identifier NCT05307549 and NCT05307575.

Recent studies associated rapid eye movement sleep behavior disorder (RBD) in Parkinson’s disease (PD) with severe cognitive impairment and brain atrophy. However, whole-brain functional connectivity has never been explored in this group of PD patients. In this study, whole-brain network-based statistics and graph-theoretical approaches were used to characterize resting-state interregional functional connectivity in PD with probable RBD (PD-pRBD) and its relationship with cognition. Our sample consisted of 30 healthy controls, 32 PD without probable RBD (PD-non pRBD), and 27 PD-pRBD. The PD-pRBD group showed reduced functional connectivity compared with controls mainly involving cingulate areas with temporal, frontal, insular, and thalamic regions ( p  < 0.001). Also, the PD-pRBD group showed reduced functional connectivity between right ventral posterior cingulate and left medial precuneus compared with PD-non pRBD ( p  < 0.05). We found increased normalized characteristic path length in PD-pRBD compared with PD-non pRBD. In the PD-pRBD group, mean connectivity strength from reduced connections correlated with visuoperceptual task and normalized characteristic path length correlated with processing speed and verbal memory tasks. This work demonstrates the existence of disrupted functional connectivity in PD-pRBD, together with abnormal network integrity, that supports its consideration as a severe PD subtype.

Background and objective: Brain atrophy and cognitive impairment in neurodegenerative diseases are influenced by sex. We aimed to investigate sex differences in brain atrophy and cognition in de novo Parkinson’s disease (PD) patients. Methods: Clinical, neuropsychological and T1-weighted MRI data from 205 PD patients (127 males:78 females) and 69 healthy controls (40 males:29 females) were obtained from the PPMI dataset. Results: PD males had a greater motor and rapid eye movement sleep behavior disorder symptomatology than PD females. They also showed cortical thinning in postcentral and precentral regions, greater global cortical and subcortical atrophy and smaller volumes in thalamus, caudate, putamen, pallidum, hippocampus, and brainstem, compared with PD females. Healthy controls only showed reduced hippocampal volume in males compared to females. PD males performed worse than PD females in global cognition, immediate verbal recall, and mental processing speed. In both groups males performed worse than females in semantic verbal fluency and delayed verbal recall; as well as females performed worse than males in visuospatial function. Conclusions: Sex effect in brain and cognition is already evident in de novo PD not explained by age per se, being a relevant factor to consider in clinical and translational research in PD.

Impulsivity is a complex behaviour composed of different domains encompassing behavioural dis-inhibition, risky decision-making and delay discounting abnormalities. To investigate regional brain correlates between levels of individual impulsivity and grey matter volume, we performed voxel-based morphometric correlation analysis in 34 young, healthy subjects using impulsivity scores measured with Barratt Impulsivity Scale-11 and computerized Kirby’s delay discounting task. The VBM analysis showed that impulsivity appears to be reliant on a network of cortical (medial prefrontal cortex and dorsolateral prefrontal cortex) and subcortical (ventral striatum) structures emphasizing the importance of brain networks associated with reward related decision-making in daily life as morphological biomarkers for impulsivity in a normal healthy population. While our results in healthy volunteers may not directly extend to pathological conditions, they provide an insight into the mechanisms of impulsive behaviour in patients with abnormalities in prefrontal/frontal-striatal connections, such as in drug abuse, pathological gambling, ADHD and Parkinson’s disease.

Postoperative acute kidney injury contributes to longer hospital stays and increased costs related to cardiac surgery in the elderly. We analyse the influence of the patient's age on risk factors for acute kidney injury after cardiac valve surgery. We evaluated the prevalence and risk factors for acute kidney injury in 939 consecutive patients undergoing valve surgery, between 2013 and 2018. The prevalence of acute kidney injury was 19.5%. Hypertension (P=0.017); RR (95% CI): 1.74 (1.10-3.48), age ≥70 years (P=0.006); RR (95% CI): 1.79 (1.17-2.72), preoperative haematocrit <33% (P=0.009); RR (95% CI): 2.04 (1.19-3.48), glomerular filtration rate <60 ml/min/1.73 m (P<0.0001); RR (95%) CI: 2.36 (1.54-3.62) and cardiac catheterization <8 days before surgery (P=0.021); RR (95% CI): 2.15 (1.12-4.11) were identified as independent risk factors. In patients older than 70 years, with no kidney disease diagnosed preoperatively, glomerular filtration rate <70 ml/min/1.73 m , male gender, cardiopulmonary bypass time, preoperative haematocrit <36% and preoperative therapy with angiotensin-converting enzyme inhibitors were risk factors for acute kidney injury after valve surgery. In elderly patients, postoperative acute kidney injury develops with higher values of preoperative glomerular filtration rate than those observed in a younger population. Preoperative correction of anaemia, discontinuation of angiotensin-converting enzyme inhibitors and surgical techniques reducing cardiopulmonary bypass time would be considered to reduce the prevalence of renal failure.

Objective This research aims to study structural brain changes in patients with persistent olfactory dysfunctions after coronavirus disease 2019 (COVID‐19). Methods COVID‐19 patients were evaluated using T1‐weighted and diffusion tensor imaging (DTI) on a 3T MRI scanner, 9.94 ± 3.83 months after COVID‐19 diagnosis. Gray matter (GM) voxel‐based morphometry was performed using FSL‐VBM. Voxelwise statistical analysis of the fractional anisotropy, mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity was carried out with the tract‐based spatial statistics in the olfactory system. The smell identification test (UPSIT) was used to classify patients as normal olfaction or olfactory dysfunction groups. Intergroup comparisons between GM and DTI measures were computed, as well as correlations with the UPSIT scores. Results Forty‐eight COVID‐19 patients were included in the study. Twenty‐three were classified as olfactory dysfunction, and 25 as normal olfaction. The olfactory dysfunction group had lower GM volume in a cluster involving the left amygdala, insular cortex, parahippocampal gyrus, frontal superior and inferior orbital gyri, gyrus rectus, olfactory cortex, caudate, and putamen. This group also showed higher MD values in the genu of the corpus callosum, the orbitofrontal area, the anterior thalamic radiation, and the forceps minor; and higher RD values in the anterior corona radiata, the genu of the corpus callosum, and uncinate fasciculus compared with the normal olfaction group. The UPSIT scores for the whole sample were negatively associated with both MD and RD values (p‐value ≤0.05 FWE‐corrected). Interpretation There is decreased GM volume and increased MD in olfactory‐related regions explaining prolonged olfactory deficits in post‐acute COVID‐19 patients.

High-oligomeric and low-total-α-synuclein cerebrospinal fluid (CSF) levels have been found in Parkinson’s disease (PD), but with inconsistent or limited data, particularly on their clinical and structural correlates in earliest (premotor) or latest (dementia) PD stages. We determined CSF oligomeric- and total-α-synuclein in 77 subjects: 23 with idiopathic REM-sleep behaviour disorder (iRBD, a condition likely to include a remarkable proportion of subjects in the premotor stage of PD) and 41 with PD [21 non-demented (PDND) + 20 demented (PDD)], intended to reflect the premotor–motor–dementia PD continuum, along with 13 healthy controls. The study protocol also included the Unified PD Rating Scale motor-section (UPDRS-III), mini mental state examination (MMSE), neuropsychological cognitive testing, 3T brain MRI for cortical-thickness analyses, CSF τ and CSF Aβ. CSF oligomeric-α-synuclein was higher in PDND than iRBD and in PDD than iRBD and controls, and correlated with UPDRS-III, MMSE, semantic fluency and visuo-perceptive scores across the proposed premotor–motor–dementia PD continuum (iRBD + PDND + PDD). CSF total-α-synuclein positively correlated with age, CSF Aβ, and, particularly, CSF τ , tending towards lower levels in PD (but not iRBD) vs. controls only when controlling for CSF τ . Low CSF total-α-synuclein was associated with dysfunction in phonetic-fluency (a frontal-lobe function) in PD and with frontal cortical thinning in iRBD and PDND independently of CSF τ . Conversely, the associations of high (instead of low) CSF total-α-synuclein with posterior-cortical neuropsychological deficits in PD and with posterior cortical thinning in PDD were driven by high CSF τ . These findings suggest that CSF oligomeric- and total-α-synuclein have different clinical, neuropsychological and MRI correlates across the proposed premotor–motor–dementia PD continuum. CSF total-α-synuclein correlations with CSF τ and Aβ support the hypothesis of an interaction among these proteins in PD, with CSF τ probably influencing the presence of high (instead of low) CSF total-α-synuclein and its correlates mostly in the setting of PD-related dementia.

After COVID-19 infection, some patients develop a post-COVID condition (PCC) that is popularly referred to as long COVID. Among its symptoms is persistent cognitive dysfunction that is potentially linked to altered brain functional connectivity (FC). While research has explored functional reorganization in patients with PCC, the intra- and inter- network connectivity and its relationship with cognitive status and clinical outcomes remain unclear. In this study, we recruited 121 individuals with PCC (67 with, and 54 without, cognitive impairment), 20 months after infection, along with 37 non-infected healthy controls from the NAUTILUS Project (ClinicalTrials.gov IDs: NCT05307549 and NCT05307575). Participants underwent resting-state functional magnetic resonance imaging and comprehensive neuropsychological assessment. Resting-state networks were characterized using independent component analyses, dual regression and network modelling for individual FC characterization. Group differences in intra- and inter-network FC, and their associations with clinical and neuropsychological data, were studied. Significance was set at a corrected p-value of < 0.05. Patients with PCC showed increased intra-network FC in 10 cognitively relevant networks, including the default mode, salience, executive control, auditory and basal ganglia networks, correlating positively with general cognition (Montreal Cognitive Assessment scores), time since infection, fatigue and subjective memory failures. Increased inter-network FC between default mode and sensorimotor networks was also observed. Increases in FC may reflect an inefficient compensatory mechanism in patients with PCC, associated with fatigue, subjective memory complaints and persistence of PCC.