Pathological Biomarkers Research Articles

Cerebrovascular markers of WMH and infarcts in ADNI: A historical perspective and future directions.

White matter hyperintensities (WMH) and infarcts found on magnetic resonance imaging (MR infarcts) are common biomarkers of cerebrovascular disease. In this review, we summarize the methods, publications, and conclusions stemming from the Alzheimer's Disease Neuroimaging Initiative (ADNI) related to these measures. We combine analysis of WMH and MR infarct data from across the three main ADNI cohorts with a review of existing literature discussing new methodologies and scientific findings derived from these data. Although ADNI inclusion criteria were designed to minimize vascular risk factors and disease, data across all the ADNI cohorts found consistent trends of increasing WMH volumes associated with advancing age, female sex, and cognitive impairment. ADNI, initially proposed as a study to investigate biomarkers of AD pathology, has also helped elucidate the impact of asymptomatic cerebrovascular brain injury on cognition within a cohort relatively free of vascular disease. Future ADNI work will emphasize additional vascular biomarkers. HIGHLIGHTS: White matter hyperintensities (WMHs) are common to advancing age and likely reflect brain vascular injury among older individuals. WMH and to a lesser extent, magnetic resonance (MR) infarcts, affect risk for transition to cognitive impairment. WMHs and MR infarcts are present, even among Alzheimer's Disease Neuroimaging Initiative (ADNI) participants highly selected to have Alzheimer's disease (AD) as the primary pathology. WMH burden in ADNI is greater among individuals with cognitive impairment and has been associated with AD neurodegenerative markers and cerebral amyloidosis. The negative additive effects of cerebrovascular disease appear present, even in select populations, and future biomarker work needs to further explore this relationship.

MiR203a-3p as a potential biomarker for synovial pathology associated with osteoarthritis: a pilot study.

Osteoarthritis (OA) is a degenerative musculoskeletal disease that significantly impacts the quality of life. Currently, no validated biomarkers for early detection of OA are defined. The possibility of discovering OA biomarkers is the focus of this study. Human primary OA synovial cells (SVs), isolated from discarded joint tissue of patients with Kellgren & Lawrence score (KL) < 3, (mild/moderate) and KL ≥ 3 (severe), were characterized by FACS analysis. Through qRT-PCR and ELISA assays the inflammation, fibrosis status and the different miRNAs expression has been investigated. The role of miR-203a-3p and its precursors were evaluated through gain and loss of function study, IL-1β synoviocytes treatments and methylation analysis of miR203a promoter. The qRT-PCR analysis of miR203a-3p and pre-miR203a on plasma (isolated 24h before surgery, 3days and 1month after surgery) and synovial fluid (recovered during the surgery) were done to support our in vitro data. MiR203a-3p expression is inversely correlated with the aggressiveness of OA, modulating the expression of epithelial to mesenchymal transition (EMT) and pro-inflammatory factors, as well as regulating the expression of secreted protein acidic and rich in cysteine (SPARC) mRNA. Methylation analysis of the miR203a promoter and SVs IL-1β treatment's highlighted the impact of inflammation on miR203a-3p and pre-miR203a expression; as confirmed by both miRNAs detection in biological fluids derived from patients with severe OA. Our preliminary results suggest that miR-203a-3p might be a potential candidate for staging OA progression and a new protective/predictive biomarker for synovial OA degeneration. Further studies are needed to validate its potential impact on OA.

Diagnosis of Alzheimer's disease using plasma biomarkers adjusted to clinical probability.

Recently approved anti-amyloid immunotherapies for Alzheimer's disease (AD) require evidence of amyloid-β pathology from positron emission tomography (PET) or cerebrospinal fluid (CSF) before initiating treatment. Blood-based biomarkers promise to reduce the need for PET or CSF testing; however, their interpretation at the individual level and the circumstances requiring confirmatory testing are poorly understood. Individual-level interpretation of diagnostic test results requires knowledge of disease prevalence in relation to clinical presentation (clinical pretest probability). Here, in a study of 6,896 individuals evaluated from 11 cohort studies from six countries, we determined the positive and negative predictive value of five plasma biomarkers for amyloid-β pathology in cognitively impaired individuals in relation to clinical pretest probability. We observed that p-tau217 could rule in amyloid-β pathology in individuals with probable AD dementia (positive predictive value above 95%). In mild cognitive impairment, p-tau217 interpretation depended on patient age. Negative p-tau217 results could rule out amyloid-β pathology in individuals with non-AD dementia syndromes (negative predictive value between 90% and 99%). Our findings provide a framework for the individual-level interpretation of plasma biomarkers, suggesting that p-tau217 combined with clinical phenotyping can identify patients where amyloid-β pathology can be ruled in or out without the need for PET or CSF confirmatory testing.

Exploring subcortical pathology and processing speed in neuromyelitis optica spectrum disorder with myelin water imaging.

Neuromyelitis optica spectrum disorder (NMOSD) affects the optic nerves and spinal cord but can also cause focal brain inflammation. Subcortical pathology may contribute to the etiology of cognitive deficits in NMOSD. Using myelin water imaging, we investigated cerebral normal-appearing white matter (NAWM) and thalamic metrics and their association with cognition in NMOSD participants compared to healthy controls (HC). Seventeen NMOSD participants and 21 HC were scanned on a 3.0-Tesla MRI scanner using a multicomponent driven-equilibrium single-pulse observation of T1 and T2 protocol. Tissue compartment and thalamic volumes (normalized to intracranial volume), T1 relaxation time, and myelin water fraction (MWF) were reported. Eleven NMOSD participants underwent the Symbol Digit Modalities Test (SDMT) for cognitive evaluation. Group comparisons were performed using Student's t-test. The association between thalamic metrics and SDMT score was assessed using multiple regression analysis with age as a covariate. Compared to HC, NMOSD participants had reduced white matter volume (-14.2%, p<.0001), increased T1 relaxation time (+2.29%, p=.022), and lower MWF (-3.64%, p=.024) in NAWM. NMOSD group had a trend for smaller thalamic volumes than HC (-5.52%, p=.082) and no differences in thalamic MWF (p=.258) or T1 (p=.714). Thalamic T1 predicted SDMT score (adjusted R2=.51, p=.04) when controlling for age. NAWM in NMOSD demonstrates diffuse abnormalities with increased water content and demyelination, suggesting a diffuse disease process overlooked by focal inflammation measures. Increased water content, as a biomarker for diffuse thalamic pathology, may partially explain cognitive impairment in NMOSD.

Mild cognitive impairment and early Alzheimer's disease eligibility for disease modification therapies in a tertiary centre for cognitive disorders: A simultaneous real-word study on aducanumab and lecanemab.

The Food and Drug Administration approved two disease-modifying treatments (DMTs) for Alzheimer's disease (AD), aducanumab and lecanemab, with limited clinical impact but significant biomarker changes. Identifying suitable candidates for these DMTs outside randomized clinical trials (RCTs) remains uncertain. This cross-sectional study, conducted in an Italian tertiary centre for cognitive disorders, aimed to evaluate how the RCT eligibility criteria for DMT treatments applies to participants with early AD. The broader Cummings etal. (Journal of Prevention of Alzheimer's Disease, 2021, 2023) criteria and the clinical differences between DMT candidates were also assessed. The study involved 408 participants (mean age 71.1 ± 8.5 years, 48% male) with a clinical diagnosis of mild cognitive impairment (161/408, 39.5%) or mild dementia (247/408, 60.5%). Amongst them, 169 individuals (41%) showed positive AD pathology biomarkers. Eligibility RCT assessment revealed 14 patients eligible for aducanumab (3.43% of 408) and 28 for lecanemab (6.86% of 408). Following Cummings' real-world criteria, aducanumab eligibility increased to 9.56%, whereas lecanemab eligibility rose to 8.33%. Applying selection criteria to only the amyloid positive (169 out of 408), the selection for DMTs was 8.3% for aducanumab and 16.5% for lecanemab. Amongst subjects diagnosed with mild AD and mild cognitive impairment in a tertiary centre for cognitive disorders, only a small percentage of patients using RCT diagnostic criteria are eligible for DMT. The application of Cummings criteria strongly increased the DMT candidates. Nevertheless, the majority of patients with cognitive disorders have been excluded from DMTs approved so far.

Added value of inflammatory plasma biomarkers to pathologic biomarkers in predicting preclinical Alzheimer's disease.

Plasma biomarkers have recently emerged for the diagnosis, assessment, and disease monitoring of Alzheimer's disease (AD), but have yet to be fully validated in preclinical AD. In addition to AD pathologic plasma biomarkers (amyloid-β (Aβ) and phosphorylated tau (p-tau) species), a proteomic panel can discriminate between symptomatic AD and cognitively unimpaired older adults in a dementia clinic population. Examine the added value of a plasma proteomic panel, validated in symptomatic AD, over standard AD pathologic plasma biomarkers and demographic and genetic (apolipoprotein (APOE) ɛ4 status) risk factors in detecting preclinical AD. 125 cognitively unimpaired older adults (mean age = 66 years) who completed Aβ PET and plasma draw were analyzed using multiple regression with Aβ PET status (positive versus negative) as the outcome to determine the best fit for predicting preclinical AD. Model 1 included age, education, and gender. Model 2 and 3 added predictors APOE ɛ4 status (carrier versus non-carrier) and AD pathologic blood biomarkers (Aβ42/40 ratio, p-tau181), respectively. Random forest modeling established the 5 proteomic markers from the proteomic panel that best predicted Aβ PET status, and these markers were added in Model 4. The best model for predicting Aβ PET status included age, years of education, APOE ɛ4 status, Aβ42/40 ratio, and p-tau181. Adding the top 5 proteomic markers did not significantly improve the model. Proteomic markers in plasma did not add predictive value to standard AD pathologic plasma biomarkers in predicting preclinical AD in this sample.

Uncovering SPP1+ Macrophage, Neutrophils and Their Related Diagnostic Biomarkers in Intracranial Aneurysm and Subarachnoid Hemorrhage.

Intracranial aneurysms (IA) frequently cause subarachnoid hemorrhage (SAH) and have poor prognosis. However, the molecular mechanisms and diagnostic biomarkers associated with IA and ruptured IA (rIA) remain poorly understood. In this study, single-cell and transcriptome datasets were obtained from the GEO database. The cell populations were annotated to identify potential pathogenic subpopulations, followed by intercellular communication, pseudotime, and SCENIC analyses. Proteome-wide and transcriptome-wide Mendelian randomization (MR) analyses were conducted to identify risk factors for IA and SAH. The major pathological changes and diagnostic biomarkers of IA and SAH were identified based on the transcriptome datasets. A clinical cohort was established to identify the diagnostic biomarkers and validate the results. Macrophages and neutrophils were predominantly increased in IA and rIA tissues, and neutrophils were markedly upregulated in the blood of SAH patients. SPP1+ Macrophage was progressively elevated in aneurysms, promoting vascular smooth muscle cell (VSMC) phenotypic transformation and collagen matrix remodeling through the SPP1 and TGF-β pathways. Furthermore, HIF1α regulon was enriched in SPP1+ Macrophage, mediating inflammation and metabolic reprogramming, which contributed to IA progression. Integrated MR analysis identified CD36 as a risk factor for both IA and SAH, and it has been recognized as an effective blood biomarker for SAH. Neutrophils and their related indicators have emerged as excellent biomarkers of SAH in clinical cohorts. This study highlighted the detrimental role of SPP1+ Macrophage in IA and SAH using single-cell sequencing and MR analyses. CD36 was identified as a risk factor for IA and SAH and was also an efficient blood biomarker for SAH. In a clinical cohort, neutrophils and related indicators were valuable for the early diagnosis of SAH.

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.

Tandem mass tag-based proteomic analysis of granulosa and theca interna cells of the porcine ovarian follicle following in vitro treatment with vitamin D3 and insulin alone or in combination

This study was performed to investigate the proteomic basis underlying the interaction between vitamin D3 (VD) and insulin (I) within ovarian follicle using the pig as a model. Porcine antral follicles were incubated in vitro for 12 h with VD alone and I alone or in combination (VD + I) or with no treatment as the control (C). In total, 7690 and 7467 proteins were identified in the granulosa and theca interna compartments, respectively. Comparative proteomic analysis revealed 97 differentially abundant proteins (DAPs) within the granulosa layer and 11 DAPs within the theca interna layer. In the granulosa compartment, VD affected proteome leading to the promotion of cell proliferation, whereas I influenced mainly proteins related to cellular adhesion. The VD + I treatment induced granulosa cell proliferation probably via the DAPs involved in DNA synthesis and the cell cycle regulation. In the theca interna layer, VD alone or in co-treatment with I affected DAPs associated with cholesterol transport and lipid and steroid metabolic processes that was further confirmed by diminished lipid droplet accumulation. SignificanceThe application of quantitative proteomics demonstrated for the first time the complexity of VD and I interactions in porcine ovarian follicle, providing a framework for understanding the molecular mechanisms underlying their cross-talk. Although identified DAPs were related to crucial ovarian processes, including the granulosa cell proliferation and cholesterol transport in the theca interna layer, novel molecular pathways underlying these processes have been proposed. The identified unique proteins may serve as indicators of VD and I interactions in both follicle layers, and could be useful biomarkers of ovarian pathologies characterized by impaired VD and I levels, such as polycystic ovary syndrome.