Pathological Biomarkers Research Articles

Proteomic analysis of APOEε4 carriers implicates lipid metabolism, complement and lymphocyte signaling in cognitive resilience

BackgroundApolipoprotein E (APOE) ε4 allele is the strongest genetic risk factor for late onset Alzheimer’s disease (AD). This case-cohort study used targeted plasma biomarkers and large-scale proteomics to examine the biological mechanisms that allow some APOEε4 carriers to maintain normal cognitive functioning in older adulthood.MethodsAPOEε4 carriers and APOEε3 homozygotes enrolled in the Women’s Health Initiative Memory Study (WHIMS) from 1996 to 1999 were classified as resilient if they remained cognitively unimpaired beyond age 80, and as non-resilient if they developed cognitive impairment before or at age 80. AD pathology (Aß42/40) and neurodegeneration (NfL, tau) biomarkers, as well as 1007 proteins (Olink) were quantified in blood collected at study enrollment (on average 14 years prior) when participants were cognitively normal. We identified plasma proteins that distinguished between resilient and non-resilient APOEε4 carriers, examined whether these associations generalized to APOEε3 homozygotes, and replicated these findings in the UK Biobank.ResultsA total of 1610 participants were included (baseline age: 71.3 [3.8 SD] years; all White; 42% APOEε4 carriers). Compared to resilient APOEε4 carriers, non-resilient APOEε4 carriers had lower Aß42/40/tau ratio and greater NfL at baseline. Proteomic analyses identified four proteins differentially expressed between resilient and non-resilient APOEε4 carriers at an FDR-corrected P < 0.05. While one of the candidate proteins, a marker of neuronal injury (NfL), also distinguished resilient from non-resilient APOEε3 homozygotes, the other three proteins, known to be involved in lipid metabolism (ANGPTL4) and immune signaling (PTX3, NCR1), only predicted resilient vs. non-resilient status among APOEε4 carriers (protein*genotype interaction-P < 0.05). Three of these four proteins also predicted 14-year dementia risk among APOEε4 carriers in the UK Biobank validation sample (N = 9420). While the candidate proteins showed little to no association with targeted biomarkers of AD pathology, protein network and enrichment analyses suggested that natural killer (NK) cell and T lymphocyte signaling (via PKC-θ) distinguished resilient from non-resilient APOEε4 carriers.ConclusionsWe identified and replicated a plasma proteomic signature associated with cognitive resilience among APOEε4 carriers. These proteins implicate specific immune processes in the preservation of cognitive status despite elevated genetic risk for AD. Future studies in diverse cohorts will be needed to assess the generalizability of these results.

Acceleration of Brain Atrophy and Progression From Normal Cognition to Mild Cognitive Impairment

It remains unclear which risk factors accelerate brain atrophy along with a progression from normal cognition to mild cognitive impairment (MCI). To examine risk factors associated with the acceleration of brain atrophy and progression from normal cognition to MCI based on long-term longitudinal data for middle-aged and older adults. Data for this cohort study were extracted from the Biomarkers for Older Controls at Risk for Dementia (BIOCARD) cohort, initiated at the National Institutes of Health from January 1, 1995, to December 31, 2005, and continued at Johns Hopkins University from January 1, 2015, to October 31, 2023. All participants were cognitively normal at baseline. The participants whose structural magnetic brain imaging (MRI) of the brain and cerebrospinal fluid (CSF) measures were available for over 10 years were included. Longitudinal structural MRI of the brain and measurement of CSF biomarkers for Alzheimer disease pathology (ratio of amyloid β peptide 42 [Aβ42] to Aβ40, tau phosphorylated at threonine 181, and total tau). Annual change rates of segmental brain volumes, Kaplan-Meier survival curves plotting time to event for progression to MCI symptom onset, and hazard ratios (HRs) determined by Cox proportional hazards regression models. A total of 185 participants (mean [SD] age, 55.4 [8.4] years; 116 women [63%]) were included and followed up for a maximum of 27 years (median, 20 [IQR, 18-22] years). The groups with high levels of atrophy in the white matter and enlargement in the ventricles had an earlier progression from normal cognition to MCI symptom onset (HR for white matter, 1.86 [95% CI, 1.24-2.49]; P = .001; HR for ventricles, 1.71 [95% CI, 1.19-2.24]; P = .009). Diabetes was associated with progression to MCI (HR, 1.41 [95% CI, 1.06-1.76]; P = .04), as was a low CSF Aβ42:Aβ40 ratio (HR, 1.48 [95% CI, 1.09-1.88]; P = .04), and their combination had a higher HR of 1.55 (95% CI, 1.13-1.98]; P = .03), indicating a synergic association of diabetes and amyloid pathology with MCI progression. In this cohort study of middle-aged and older adults, higher rates of volume change in the white matter and ventricles, along with the presence of diabetes and a low CSF Aβ42:Aβ40 ratio, were identified as important risk factors for the progression to MCI. These results support the importance of identifying individuals who have accelerated brain atrophy to optimize preventive strategies for progression to MCI.

Associations of Microbleeds and Their Topography With Imaging and CSF Biomarkers of Alzheimer Pathology in Individuals With Down Syndrome.

Associations of Microbleeds and Their Topography With Imaging and CSF Biomarkers of Alzheimer Pathology in Individuals With Down Syndrome.

Associations between accelerated forgetting, amyloid deposition and brain atrophy in older adults.

Accelerated long-term forgetting (ALF) is the phenomenon whereby material is retained normally over short intervals (e.g. minutes) but forgotten abnormally rapidly over longer periods (days or weeks). ALF may be an early marker of cognitive decline, but little is known about its relationships with preclinical Alzheimer's disease pathology, and how memory selectivity may influence which material is forgotten. We assessed ALF in 'Insight 46', a sub-study of the MRC National Survey of Health and Development (a population-based cohort born during one week in 1946) (n=429; 47% female; assessed aged ∼73 years). ALF assessment comprised visual and verbal memory tests: Complex Figure Drawing and the Face-Name Associative Memory Exam (FNAME). ALF scores were calculated as the percentage of material retained after 7 days, relative to 30 minutes. In 306 cognitively-normal participants, we investigated effects on ALF of β-amyloid pathology (quantified using 18F-Florbetapir-PET, classified as positive/negative) and whole-brain and hippocampal atrophy rate (quantified from serial T1-MRI over ∼2.4 years preceding the ALF assessment), as well as interactions between these pathologies. We categorized Complex Figure Drawing items as 'outline' or 'detail', to test our hypothesis that forgetting the outline of the structure would be more sensitive to the effect of brain pathologies. We also investigated associations between ALF and Subjective Cognitive Decline, measured with the MyCog questionnaire. Complex Figure 'outline' items were better retained than 'detail' items (mean retention over 7 days = 94% vs 72%). Amyloid-positive participants showed greater forgetting of the Complex Figure outline, compared to amyloid-negatives (90% vs 95%; P<0.01). There were interactions between amyloid pathology and cerebral atrophy, such that whole-brain and hippocampal atrophy predicted greater ALF on Complex Figure Drawing among amyloid-positives only (e.g. 1.9 percentage-points lower retention per ml/year of whole-brain atrophy [95% confidence intervals 0.5, 3.7]; P<0.05). Greater ALF on FNAME was associated with increased rate of hippocampal atrophy. ALF on Complex Figure Drawing also correlated with subjective cognitive decline (-0.45 percentage-points per MyCog point [-0.85, -0.05], P<0.05). These results provide evidence of associations between some measures of ALF and biomarkers of brain pathologies and subjective cognitive decline in cognitively-normal older adults. On Complex Figure Drawing, 'outline' items were better remembered than 'detail' items - illustrating the strategic role of memory selectivity - but 'outline' items were also relatively more vulnerable to ALF in individuals with amyloid pathology. Overall, our findings suggest that ALF may be a sensitive marker of cognitive changes in preclinical Alzheimer's disease.

Elucidating the neuropathological and molecular heterogeneity of amyloid-beta and tau in Alzheimer's disease through machine learning and transcriptomic integration.

Discerning functional brain network variations related to neuropathological aggregates in Alzheimer's disease (AD), including amyloid-beta (Abeta) and phosphorylated tau (p-tau), is crucial for understanding their link to cognitive decline and underlying molecular mechanisms. However, these variations are often confounded by normal aging-related changes, complicating interpretation. To address this challenge, we first defined Alzheimer's continuum cases (Abeta positive (A+), n = 129) and normal elderly (Abeta negative (A-), n = 160) using cerebral spinal fluid amyloid levels, and then applied a novel deep learning approach to resting-state connectivity using functional magnetic resonance imaging (fMRI) of the 289 subjects to disentangle A+-specific dimensions in brain network alterations from those shared with A- individuals. The identified A+-specific dimensions were further refined to predict individual Abeta and p-tau levels separately. We observed that resulting brain signatures, defined from A+-specific dimensions for predicting these two CSF biomarkers, were both attributed to the right superior temporal and anterior cingulate cortices and associated with attention and memory domains. When linking the brain signatures to gene expression data from a public transcriptomic atlas, we found that the brain signatures were associated with molecular pathways involving synaptic dysfunction and disruptions in pathways containing activity of excitatory neurons, astrocytes, and microglia. For A--shared dimensions, the Aβ-linked brain signature involved the left fusiform and right middle cingulate cortices, correlating with the language cognitive measurement and language-related molecular pathways. The p-tau-linked signature predominantly involved the right insula and inferior temporal cortices, correlating with the aging-related molecular pathways. Collectively, our findings provided new insights in understanding of Alzheimer's continuum pathological biomarkers.

Clarifying the association of CSF Aβ, tau, BACE1, and neurogranin with AT(N) stages in Alzheimer disease.

Current AT(N) stratification for Alzheimer's disease (AD) accounts for complex combinations of amyloid (A), tau proteinopathy (T) and neurodegeneration (N) signatures. Understanding the transition between these different stages is a major challenge, especially in view of the recent development of disease modifying therapy. This is an observational study, CSF levels of Tau, pTau181, pTau217, Aβ38/40/42, sAPPα/β, BACE1 and neurogranin were measured in the BALTAZAR cohort of cognitively impaired patients and in the Alzheimer's Disease Neuroimaging Initiative (ADNI). Biomarkers levels were related to the AT(N) framework. (A) and (T) were defined in BALTAZAR with CSF Aβ42/40 ratio and pTau217 respectively, and in ADNI with amyloid and tau PET. (N) was defined using total CSF tau in both cohorts. As expected, CSF Aβ42 decreased progressively with the AD continuum going from the A-T-N- to the A + T + N + profile. On the other hand, Tau and pTau181 increased progressively with the disease. The final transition from A + T + N- to A + T + N + led to a sharp increase in Aβ38, Aβ42 and sAPP levels. Synaptic CSF biomarkers BACE1 and neurogranin, were lowest in the initial A + T-N- stage and increased with T + and N + . CSF pTau181 and total tau were closely related in both cohorts. The early transition to an A + phenotype (A + T-N-) primarily impacts synaptic function. The appearance of T + and then N + is associated with a significant and progressive increase in pathological Alzheimer's disease biomarkers. Our main finding is that CSF pTau181 is an indicator of N + rather than T + , and that N + is associated with elevated levels of BACE1 protein and beta-amyloid peptides. This increase may potentially fuel the amyloid cascade in a positive feedback loop. Overall, our data provide further insights into understanding the interconnected pathological processes of amyloid, tau, and neurodegeneration underlying Alzheimer's disease.

Neurology of Aging : adapting neurology provision for an aging population.

Background Over the past few decades, advances in neurology of aging have been considerable and have led to a better understanding of the science of age-related neurological disorders. Likewise, it changed the perception of classical neurology practice, research and the way of looking at age-related conditions. Neurological disorders are the most frequent cause of major disability in the elderly and account for almost half of the incapacitation occurring beyond age 65 and more than 90% of serious dependency. However, a number of neurological changes occur also in the absence of a specific disease, making the assessment and management of neurological complaints and findings a specific expertise. Summary Maximizing success in clinical care of the elderly requires expertise in geriatric neurology, which includes an understanding of current research regarding aging and age-related neurological dysfunctions, and the ability to work with other geriatric health care providers. Although current therapies for neurodegenerative diseases mainly offer symptomatic relief without slowing progression, the landscape is evolving. Biomarkers of pathology and neuroimaging have continued to develop, with a significant impact on diagnosis and treatment. These advances have helped to improve our knowledge of disease pathophysiology but also disease stages, guiding symptomatic monitoring, and possible therapeutic options at a pre-symptomatic stage. Key Messages Neurological disorders are a leading cause of major disability and dependency in the elderly, underscoring the need for expertise in geriatric neurology for effective clinical care of this population. Although current therapies for neurodegenerative diseases primarily provide symptomatic relief without slowing disease progression, advancements in biomarkers and neuroimaging are significantly evolving. These advancements enhance our understanding of disease pathophysiology and stages, guiding symptomatic monitoring and potential therapeutic options at a pre-symptomatic stage. As knowledge about age-associated conditions is steadily rising and geriatric medicine gains further recognition, this article argues for a new focus on the role of neurologists in geriatric medicine, emphasizing the importance of integrating current research and collaborative care approaches in the management of elderly patients.

APOE4 and Infectious Diseases Jointly Contribute to Brain Glucose Hypometabolism, a Biomarker of Alzheimer's Pathology: New Findings from the ADNI.

Impaired brain glucose metabolism is a preclinical feature of neurodegenerative diseases such as Alzheimer's disease (AD). Infections may promote AD-related pathology. Therefore, we investigated the interplay between infections and APOE4, a strong genetic risk factor for AD. We analyzed data on 1,509 participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) database using multivariate linear regression models. The outcomes were rank-normalized hypometabolic convergence index (HCI), statistical regions of interest (SROI) for AD, and mild cognitive impairment (MCI). Marginal mean estimates for infections, stratified by APOE4 carrier status, were then computed. Prior infections were associated with greater HCI [β=0.15, 95% CI: 0.03, 0.27, p=0.01]. The combined effects of infections and APOE4 carriers on HCI levels were significantly greater than either variable alone. Among APOE4 carriers, the estimated marginal mean was 0.62, rising to 0.77, with infections (p<0.001), indicating an interaction effect. Carriers with multiple infections showed greater hypometabolism (higher HCI), with an estimate of 0.44 (p=0.01) compared to 0.11 (p=0.08) for those with a single infection, revealing a dose-response relationship. The estimates for the association of infections with SROI AD and SROI MCI were β=-0.01 (p=0.02) and β=-0.01 (p=0.04), respectively. Our findings suggest that infections and APOE4 jointly contribute to brain glucose hypometabolism and AD pathology, supporting a "multi-hit" mechanism in AD development.

Artificial Intelligence Applications in Oral Cancer and Oral Dysplasia.

Oral squamous cell carcinoma (OSCC) is a highly unpredictable disease with devastating mortality rates that have not changed over the past decades, in the face of advancements in treatments and biomarkers, which have improved survival for other cancers. Delays in diagnosis are frequent, leading to more disfiguring treatments and poor outcomes for patients. The clinical challenge lies in identifying those patients at the highest risk of developing OSCC. Oral epithelial dysplasia (OED) is a precursor of OSCC with highly variable behavior across patients. There is no reliable clinical, pathological, histological, or molecular biomarker to determine individual risk in OED patients. Similarly, there are no robust biomarkers to predict treatment outcomes or mortality in OSCC patients. This review aims to highlight advancements in artificial intelligence (AI)-based methods to develop predictive biomarkers of OED transformation to OSCC or predictive biomarkers of OSCC mortality and treatment response. Biomarkers such as S100A7 demonstrate promising appraisal for the risk of malignant transformation of OED. Machine learning-enhanced multiplex immunohistochemistry workflows examine immune cell patterns and organization within the tumor immune microenvironment to generate outcome predictions in immunotherapy. Deep learning (DL) is an AI-based method using an extended neural network or related architecture with multiple "hidden" layers of simulated neurons to combine simple visual features into complex patterns. DL-based digital pathology is currently being developed to assess OED and OSCC outcomes. The integration of machine learning in epigenomics aims to examine the epigenetic modification of diseases and improve our ability to detect, classify, and predict outcomes associated with epigenetic marks. Collectively, these tools showcase promising advancements in discovery and technology, which may provide a potential solution to addressing the current limitations in predicting OED transformation and OSCC behavior, both of which are clinical challenges that must be addressed in order to improve OSCC survival.

Midlife dynamics of white matter architecture in lexical production

We aimed to examine the white matter changes associated with lexical production difficulties, beginning in midlife with increased naming latencies. To delay lexical production decline, middle-aged adults may rely on domain-general and language-specific compensatory mechanisms proposed by the LARA model (Lexical Access and Retrieval in Aging). However, the white matter changes supporting these mechanisms remains largely unknown. Using data from the CAMCAN cohort, we employed an unsupervised and data-driven methodology to examine the relationships between diffusion-weighted imaging and lexical production. Our findings indicate that midlife is marked by alterations in brain structure within distributed dorsal, ventral, and anterior cortico-subcortical networks, marking the onset of lexical production decline around ages 53–54. Middle-aged adults may initially adopt a “semantic strategy” to compensate for lexical production challenges, but this strategy seems compromised later (ages 55–60) as semantic control declines. These insights underscore the interplay between domain-general and language-specific processes in the trajectory of lexical production performance in healthy aging and hint at potential biomarkers for language-related neurodegenerative pathologies.

Clinical value of plasma pTau181 to predict Alzheimer's disease pathology in a large real-world cohort of a memory clinic

BackgroundThe identification of patients with an elevated risk of developing Alzheimer’s disease (AD) dementia and eligible for the disease modifying treatments (DMTs) in the earliest stages is one of the greatest challenges in the clinical practice. Plasma biomarkers has the potential to predict these issues, but further research is still needed to translate them to clinical practice. Here we evaluated the clinical applicability of plasma pTau181 as a predictive marker of AD pathology in a large real-world cohort of a memory clinic. MethodsThree independent cohorts (modelling [n=991, 59.7% female], testing [n=642, 56.2% female] and validation [n=441, 55.1% female]) of real-world patients with subjective cognitive decline (SCD), mild cognitive impairment (MCI), AD dementia, and other dementias were included. Paired cerebrospinal fluid (CSF) and plasma samples were used to measure AT(N) CSF biomarkers and plasma pTau181. FindingsCSF and plasma pTau181 showed correlation in all phenotypes except in SCD and other dementias. Age significantly influenced the biomarker’s performance. The general Aβ(+) vs Aβ(-) ROC curve showed an AUC = 0.77 [0.74 to 0.80], whereas the specific ROC curve of MCI due to AD vs non-AD MCI showed an AUC = 0.89 [0.85 to 0.93]. A cut-off value of 1.30 pg/ml of plasma pTau181 exhibited a sensitivity of 93.57% [88.72 to 96.52], specificity of 72.38 % [62.51 to 79.01], VPP of 77.85% [70.61 to 83.54], and 8.30% false negatives in the subjects with MCI of the testing cohort.The HR of cox regression showed that patients with MCI up to this cut-off value exhibited a HR = 1.84 [1.05 to 3.22] higher risk to convert to AD dementia than patients with MCI below the cut-off value. InterpretationPlasma pTau181 has the potential to be used in the memory clinics as a screening biomarker of AD pathology in subjects with MCI, presenting a valuable prognostic utility in predicting the MCI conversion to AD dementia. In the context of a real-world population, a confirmatory test employing gold-standard procedures is still advisable.Funding: this study has been mainly funded by Ace Alzheimer Center Barcelona, Instituto de Salud Carlos III (ISCIII), Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Spanish Ministry of Science and Innovation, Fundación ADEY, Fundación Echevarne and Grífols S.A.

Medial temporal lobe atrophy patterns in early-versus late-onset amnestic Alzheimer’s disease

BackgroundThe medial temporal lobe (MTL) is hypothesized to be relatively spared in early-onset Alzheimer’s disease (EOAD). Yet, detailed examination of MTL subfields and drivers of atrophy in amnestic EOAD is lacking.MethodsBioFINDER-2 participants with memory impairment, abnormal amyloid-β and tau-PET were included. Forty-one amnestic EOAD individuals ≤65 years and, as comparison, late-onset AD (aLOAD, ≥70 years, n = 154) and amyloid-β-negative cognitively unimpaired controls were included. MTL subregions and biomarkers of (co-)pathologies were measured.ResultsAD groups showed smaller MTL subregions compared to controls. Atrophy patterns were similar across AD groups: aLOAD showed thinner entorhinal cortices than aEOAD; aEOAD showed thinner parietal regions than aLOAD. aEOAD showed lower white matter hyperintensities than aLOAD. No differences in MTL tau-PET or transactive response DNA binding protein 43-proxy positivity were found.ConclusionsWe found evidence for MTL atrophy in amnestic EOAD and overall similar levels to aLOAD of MTL tau pathology and co-pathologies.

The Association of Cerebrospinal Fluid Biomarkers of Alzheimer’s Disease with Cognitive Intra-Individual Variability

Abstract Objective Cognitive intra-individual variability (IIV) is a sensitive predictor of cognitive decline and disease severity in Alzheimer’s disease (AD). Despite its sensitivity, whether IIV is merely a psychometric artifact or disease pathology biomarker remains unknown. The present study evaluated the association between IIV and cerebrospinal fluid (CSF) biomarkers of AD. Method Participants included 422 individuals from the National Alzheimer’s Coordinating Center Unified Dataset 3.0 who completed baseline neuropsychological assessment and had CSF data. All participants were adult monolingual English speakers. Participants with vision or hearing impairments were excluded. Cases were stratified into cognitively normal (n = 267) and AD groups (n = 155; mild cognitive impairment = 50, dementia = 105). Cross-sectional IIV was calculated by obtaining the individual standard deviation (iSD) of ten cognitive tests. Finally, the coefficient of variation (CoV) was computed by dividing iSD by the participant’s overall test battery mean. Non-parametric Spearman-rank correlations were used to assess the relation between CoV and CSF biomarkers, including beta-amyloid 1–42, total tau (t-tau), and phosphorylated tau (p-tau181). Results In the AD group, CoV was positively correlated with p-tau181 (r = 0.285, p = 0.003) and t-tau (r = 0.241, p = 0.009), and negatively correlated with beta-amyloid 1–42 (r = −0.314, p &amp;lt; 0.001). Correlations between CoV and CSF biomarkers were not significant in the cognitively normal group for beta-amyloid 1–42 (r = 0.076, p = 0.215), p-tau181 (r = −0.014, p = 0.840), and t-tau (r = −0.046, p = 0.485). Conclusions In people with mild cognitive impairment and dementia of presumed AD etiology, cognitive IIV is associated with CSF biomarkers. These findings provide preliminary evidence that IIV is not merely a statistical artifact, but is associated with AD neuropathology.

Gut Microbiome Compositional and Functional Features Associate with Alzheimer's Disease Pathology.

The gut microbiome is a potentially modifiable factor in Alzheimer's disease (AD); however, understanding of its composition and function regarding AD pathology is limited. Shallow-shotgun metagenomic data was used to analyze fecal microbiome from participants enrolled in the Wisconsin Microbiome in Alzheimer's Risk Study, leveraging clinical data and cerebrospinal fluid (CSF) biomarkers. Differential abundance and ordinary least squares regression analyses were performed to find differentially abundant gut microbiome features and their associations with CSF biomarkers of AD and related pathologies. Gut microbiome composition and function differed between people with AD and cognitively unimpaired individuals. The compositional difference was replicated in an independent cohort. Differentially abundant gut microbiome features were associated with CSF biomarkers of AD and related pathologies. These findings enhance our understanding of alterations in gut microbial composition and function in AD, and suggest that gut microbes and their pathways are linked to AD pathology.

Metastasis of World Health Organization Grade II and Grade III Meningiomas: Long-Term Survival and Associated Factor Analysis

ObjectiveMetastasis of WHO grade II or grade II meningiomas are rare. The aim of this study was to investigate their incidence, associated risk factors and treatment course. MethodsPatients with surgically resected WHO grade II or grade III meningiomas were reviewed based on histopathology with the 2016 WHO criteria. Metastasis was diagnosed through whole body image scan followed by surgical resection or biopsy. Clinical factors were analyzed for their association with metastasis. ResultsAmong the 131 enrolled patients, metastasis was diagnosed after tumor relapse in 7 (incidence rate 3.6%) at a mean 30.9 months after the initial surgery. The metastasis after tumor relapse group had the worst overall survival, followed by tumor relapse without metastasis and non-relapse groups (p<0.001). The independent factors associated with metastasis were major vessel compromise by primary tumors (hazard ratio [HR]=9.9, p=0.035), tumor relapse time less than 24 months (HR=7.0, p=0.036), and subtotal resection without adjuvant radiotherapy to the primary tumor (HR=3.5, p=0.047). Neither grading nor histochemical staining was significantly associated with metastasis, whereas higher vascularity seemed to be more common in metastatic lesions than primary tumors. ConclusionsThe presence of metastasis contributed to poor outcomes and was related to earlier tumor relapse and major vessel compromise. Subtotal resection should be followed by adjuvant radiotherapy to reduce the risk of metastasis. Further research is warranted to identify circulating or pathologic biomarkers for the early detection of metastasis.

A novel pipeline employing deep multi-attention channels network for the autonomous detection of metastasizing cells through fluorescence microscopy

Metastasis driven by cancer cell migration is the leading cause of cancer-related deaths. It involves significant changes in the organization of the cytoskeleton, which includes the actin microfilaments and the vimentin intermediate filaments. Understanding how these filament change cells from normal to invasive offers insights that can be used to improve cancer diagnosis and therapy. We have developed a computational, transparent, large-scale and imaging-based pipeline, that can distinguish between normal human cells and their isogenically matched, oncogenically transformed, invasive and metastasizing counterparts, based on the spatial organization of actin and vimentin filaments in the cell cytoplasm. Due to the intricacy of these subcellular structures, manual annotation is not trivial to automate. We used established deep learning methods and our new multi-attention channel architecture. To ensure a high level of interpretability of the network, which is crucial for the application area, we developed an interpretable global explainable approach correlating the weighted geometric mean of the total cell images and their local GradCam scores. The methods offer detailed, objective and measurable understanding of how different components of the cytoskeleton contribute to metastasis, insights that can be used for future development of novel diagnostic tools, such as a nanometer level, vimentin filament-based biomarker for digital pathology, and for new treatments that significantly can increase patient survival.

Amyloid-Negative, Neurodegeneration-Negative Amnestic Mild Cognitive Impairment.

The concept of amnestic mild cognitive impairment (aMCI) was developed to identify patients at an initial stage of Alzheimer's disease (AD). However, some patients with aMCI do not present biomarkers of amyloid pathology or neuronal injury. To know the natural history of amyloid-negative and neurodegeneration-negative patients with aMCI, namely to ascertain: 1) whether these patients remain cognitively stable or they present a slow decline in neuropsychological tests; 2) whether the memory complaints subside with the apparently benign clinical course of the disorder or if they persist along the time. Patients who fulfilled criteria for aMCI with no biomarkers of amyloid pathology or neuronal injury were selected from a large cohort of non-demented patients with cognitive complaints, and were followed with clinical and neuropsychological assessments. Twenty-one amyloid-negative and neurodegeneration-negative aMCI patients were followed for 7.1±3.7 years. At the baseline they had more pronounced deficits in verbal learning (California Verbal Learning Test) and were also impaired in Word Recall and Logical Memory. However, they did not decline in any cognitive test during follow-up. The patients maintained a high level of subjective memory complaints from baseline (9.7±4.1) to the follow-up visit (9.2±4.1, a non-significant difference), in spite of a statistically significant decrease in the depressive symptoms, with Geriatric Depression Scale (15 items) score 4.9±2.8 at baseline and 3.2±1.8 at the follow-up visit. Amyloid-negative, neurodegeneration-negative aMCI is a chronic clinical condition characterized by the long-term persistence of cognitive deficits and distressing memory complaints. Adequate strategies to treat this condition are needed.

Associations of Microbleeds and Their Topography With Imaging and CSF Biomarkers of Alzheimer Pathology in Individuals With Down Syndrome.

Cerebral hemorrhages are an exclusion criterion and potential adverse effect of antiamyloid agents. It is, therefore, critical to characterize the natural history of cerebral microbleeds in populations genetically predisposed to Alzheimer disease (AD), such as Down syndrome (DS). We aimed to assess microbleed emergence in adults with DS across the AD spectrum, defining their topography and associations with clinical variables, cognitive outcomes, and fluid and neuroimaging biomarkers. This cross-sectional study included participants aged 18 years or older from the Down-Alzheimer Barcelona Neuroimaging Initiative and Sant Pau Initiative on Neurodegeneration with T1-weighted and susceptibility-weighted images. Participants underwent comprehensive assessments, including apolipoprotein E (APOE) genotyping; fluid and plasma determinations of beta-amyloid, tau, and neurofilament light; cognitive outcomes (Cambridge Cognitive Examination and modified Cued Recall Test); and vascular risk factors (hypertension, diabetes mellitus, and dyslipidemia). We manually segmented microbleeds and characterized their topography. Associations between microbleed severity and AD biomarkers were explored using between-group comparisons (none vs 1 vs 2+) and multivariate linear models. We included 276 individuals with DS and 158 healthy euploid controls (mean age = 47.8 years, 50.92% female). Individuals with DS were more likely to have microbleeds than controls (20% vs 8.9%, p < 0.001), with more severe presentation (12% with 2+ vs 1.9%). Microbleeds increased with age (12% 20-30 years vs 60% > 60 years) and AD clinical stage (12.42% asymptomatic, 27.9% prodromal, 35.09% dementia) were more common in APOEε4 carriers (26% vs 18.3% noncarriers, p = 0.008), but not associated with vascular risk factors (p > 0.05). Microbleeds were predominantly posterior (cerebellum 33.66%; occipital 14.85%; temporal 21.29%) in participants with DS. Associations with microbleed severity were found for neuroimaging and fluid AD biomarkers, but only hippocampal volumes (standardized β = -0.18 [-0.31, -0.06], p < 0.005) and CSF p-tau-181 concentrations (β = 0.26 [0.12, 0.41], p < 0.005) survived regression controlling for age and disease stage, respectively. Microbleeds had limited effect on cognitive outcomes. In participants with DS, microbleeds present with a posterior, lobar predominance, are associated with disease severity, but do not affect cognitive performance. These results suggest an interplay between AD pathology and vascular lesions, implicating microbleeds as a risk factor limiting the use of antiamyloid agents in this population.

MAPLES-DR: MESSIDOR Anatomical and Pathological Labels for Explainable Screening of Diabetic Retinopathy

Reliable automatic diagnosis of Diabetic Retinopathy (DR) and Macular Edema (ME) is an invaluable asset in improving the rate of monitored patients among at-risk populations and in enabling earlier treatments before the pathology progresses and threatens vision. However, the explainability of screening models is still an open question, and specifically designed datasets are required to support the research. We present MAPLES-DR (MESSIDOR Anatomical and Pathological Labels for Explainable Screening of Diabetic Retinopathy), which contains, for 198 images of the MESSIDOR public fundus dataset, new diagnoses for DR and ME as well as new pixel-wise segmentation maps for 10 anatomical and pathological biomarkers related to DR. This paper documents the design choices and the annotation procedure that produced MAPLES-DR, discusses the interobserver variability and the overall quality of the annotations, and provides guidelines on using the dataset in a machine learning context.

Prognostic Impact and Clinical Features of Spread through Air Spaces in Operated Lung Cancer: Real-World Analysis.

Background and Objectives: Lung cancer is the leading cause of cancer-related deaths. Spread through air spaces (STAS) is an adverse prognostic factor that has become increasingly known in recent years. This study aims to investigate the impact of STAS presence on overall survival (OS) and disease-free survival (DFS) in patients with surgically resected stage IA-IIIA lung cancer and to identify clinicopathological features associated with STAS. Materials and Methods: This research involved 311 lung cancer surgery patients. The relationship between the presence of STAS in the patients' surgical pathology and OS and DFS values was examined. Clinicopathological features associated with the presence of STAS were determined. Results: There were 103 (33%) STAS-positive patients. Adenocarcinoma histological subtype, perineural invasion (PNI), and lymphovascular invasion (LVI) were significantly correlated with being STAS positive. STAS significantly predicted DFS and OS. One-year and five-year DFS rates were significantly lower in the STAS-positive group compared to the STAS-negative group (65% vs. 88%, 29% vs. 62%, respectively, p ≤ 0.001). Similarly, one-year and five-year OS rates were significantly lower in the STAS-positive group compared to the STAS-negative group (92% vs. 94%, 54% vs. 88%, respectively, p ≤ 0.001). In multivariate analysis, STAS was found to be an independent prognostic factor for both DFS and OS (HR: 3.2 (95%CI: 2.1-4.8) and 3.1 (95%CI: 1.7-5.5), p < 0.001 and <0.001, respectively). Conclusions: In our study, STAS was found to be an independent prognostic biomarker in operated stage IA-IIIA lung cancer patients. It may be a beneficial pathological biomarker in predicting the survival of patients and managing their treatments.