Alzheimer's Disease Biomarkers Research Articles

Longitudinal Monitoring of Glutathione Stability in Different Microenvironments.

Glutathione (GSH) is a master antioxidant which primarily protects cells from oxidative stress. Clinical studies have found significant depletion of GSH from the hippocampus in patients with mild cognitive impairment (MCI), a transitional stage before conversion to Alzheimer's disease (AD). Significant depletion of GSH is considered an early diagnostic biomarker of AD. Postmortem studies have confirmed significant GSH depletion in hippocampal tissue in MCI patients. The stability of GSH in different microenvironments is essential to validate GSH as a reliable biomarker for AD. Accordingly, we have conducted longitudinal monitoring of GSH from various brain regions (frontal cortex (FC), parietal cortex (PC), occipital cortex (OC), and cerebellum (CER)) from healthy subjects using MEshcher-GArwood Point RESolved Spectroscopy (MEGA-PRESS) pulse sequence on a 3T scanner. Additionally, in vitro magnetic resonance spectroscopy (MRS) assessments were conducted longitudinally using the same study protocol involving GSH supplement in a physiologically relevant phosphate buffer solution (PBS). We report that GSH within the brain microenvironment of a healthy person remains stable over time. GSH, however, is susceptible to oxidation over time in a phosphate buffer environment. The stability of GSH in a longitudinal study in the brains of healthy individuals supports the consideration of GSH as a candidate for stable biomarker for AD.

Integration of Single-Cell and Spatial Transcriptomic Data Reveals Spatial Architecture and Potential Biomarkers in Alzheimer's Disease.

Alzheimer's disease (AD) is a complex neurodegenerative disorder characterized by the gradual loss of neurons and the accumulation of amyloid plaques and neurofibrillary tangles. Despite advancements in the understanding of AD's pathophysiology, the cellular organization and interactions in the prefrontal cortex (PFC) remain elusive. Eight single-cell RNA sequencing (scRNA-seq) datasets from both normal controls and individuals with AD were harmonized. Stringent preprocessing protocols were implemented to uphold dataset integrity. Unsupervised clustering and annotation revealed 22 distinct cell clusters corresponding to 19 unique cell types. The spatial architecture of the PFC region was constructed using the CARD tool. Further analyses encompassed trajectory examination of Oligodendrocyte subtypes, evaluation of regulon activity scores, and spot clustering within white matter regions (WM). Differential expression analysis and functional enrichment assays unveiled molecular signatures linked to AD progression and were validated using microarray data sourced from neurodegenerative disorder patients. Our investigation employs scRNA-seq and spatial transcriptomics to uncover the cellular atlas and spatial architecture of the human PFC in AD. Moreover, our results indicate that Oligodendrocytes are more prevalent in AD patients, showcasing diverse subtypes and spatial organization within WM regions. Each subtype appears to be associated with distinct biological processes and transcriptional regulators, shedding light on their involvement in AD pathology. Notably, the Oligodendrocyte_C6 subtype is linked to neurological damage in AD patients, characterized by heightened expression of genes involved in cell-cell connections, cell membrane stability, and myelination. Additionally, 12 target genes regulated by NFIA were identified, which are upregulated in AD patients and associated with disease progression. Elevated PLXDC2 expression in peripheral blood was also identified, suggesting its potential as a non-invasive biomarker for early AD detection. Our study provides novel insights into the role of Oligodendrocytes in AD and highlights the potential of PLXDC2 as a blood biomarker for non-invasive diagnosis and monitoring of AD patients.

WMH Contributions to Cognitive Impairment: Rationale and Design of the Diverse VCID Study.

As awareness of dementia increases, more individuals with minor cognitive complaints are requesting clinical assessment. Neuroimaging studies frequently identify incidental white matter hyperintensities, raising patient concerns about their brain health and future risk for dementia. Moreover, current US demographics indicate that ≈50% of these individuals will be from diverse backgrounds by 2060. Racial and ethnic minority populations bear a disproportionate burden of vascular risk factors magnifying dementia risk. Despite established associations between white matter hyperintensities and cognitive impairment, including dementia, no study has comprehensively and prospectively examined the impact of individual and combined magnetic resonance imaging measures of white matter injury, their risk factors, and comorbidities on cognitive performance among a diverse, nondemented, stroke-free population with cognitive complaints over an extended period of observation. The Diverse VCID (Diverse Vascular Cognitive Impairment and Dementia) study is designed to fill this knowledge gap through 3 assessments of clinical, behavioral, and risk factors; neurocognitive and magnetic resonance imaging measures; fluid biomarkers of Alzheimer disease, vascular inflammation, angiogenesis, and endothelial dysfunction; and measures of genetic risk collected prospectively over a minimum of 3 years in a cohort of 2250 individuals evenly distributed among Americans of Black/African, Latino/Hispanic, and non-Hispanic White backgrounds. The goal of this study is to investigate the basic mechanisms of small vessel cerebrovascular injury, emphasizing clinically relevant assessment tools and developing a risk score that will accurately identify at-risk individuals for possible treatment or clinical therapeutic trials, particularly individuals of diverse backgrounds where vascular risk factors and disease are more prevalent.

Alzheimer's disease-Biomarkers, clinical evaluation or both?

Alzheimer's disease-Biomarkers, clinical evaluation or both?

Considering Biomarkers of Neurodegeneration in Alzheimer’s Disease: The Potential of Circulating Cell-Free DNA in Precision Neurology

Neurodegenerative diseases, such as Alzheimer’s disease (AD), are a growing public health crisis, exacerbated by an aging global population and the lack of effective early disease-modifying therapies. Early detection of neurodegenerative disorders is critical to delaying symptom onset and mitigating disease progression, but current diagnostic tools often rely on detecting pathology once clinical symptoms have emerged and significant neuronal damage has already occurred. While disease-specific biomarkers, such as amyloid-beta and tau in AD, offer precise insights, they are too limited in scope for broader neurodegeneration screening for these conditions. Conversely, general biomarkers like neurofilament light chain (NfL) provide valuable staging information but lack targeted insights. Circulating cell-free DNA (cfDNA), released during cell death, is emerging as a promising biomarker for early detection. Derived from dying cells, cfDNA can capture both general neurodegenerative signals and disease-specific insights, offering multi-layered genomic and epigenomic information. Though its clinical potential remains under investigation, advances in cfDNA detection sensitivity, standardized protocols, and reference ranges could establish cfDNA as a valuable tool for early screening. cfDNA methylation signatures, in particular, show great promise for identifying tissue-of-origin and disease-specific changes, offering a minimally invasive biomarker that could transform precision neurology. However, further research is required to address technological challenges and validate cfDNA’s utility in clinical settings. Here, we review recent work assessing cfDNA as a potential early biomarker in AD. With continued advances, cfDNA could play a pivotal role in shifting care from reactive to proactive, improving diagnostic timelines and patient outcomes.

Single step capture and assessment of multiple plasma extracellular vesicle biomarkers in Alzheimer's disease detection.

Blood tests for Alzheimer's disease (AD) that measure biomarkers related to neuropathology have demonstrated to be useful, minimally-invasive ways to identify patients for screening into clinical trials. While some AD biomarkers can be detected in plasma, greater sensitivity is needed to make plasma AD tests more effective. Extracellular vesicles (EVs) in plasma carry AD-related biomarkers from the brain and could offer a concentrated source of brain-related biomarkers, though the methodological complexities involved in isolating plasma EVs have hampered its validation for clinical use. To explore the feasibility and effectiveness of developing blood tests for AD utilizing extracellular vesicle-bound protein biomarkers. We developed a simplified method for isolating EVs directly from plasma using an alternating current electrokinetic (ACE) microchip. No sample pretreatment steps were needed. Protein biomarkers on the EVs were detected by adding fluorescent antibodies to the plasma samples before capture by the chip. This allowed measurement of EV biomarker levels directly on the chip. AD or non-AD control plasma was measured for ten different AD-related biomarkers. EV-associated NCAM1, pTau231, α-synuclein, and TDP-43 levels were able to distinguish a group of 10 AD, 10 mild cognitive impairment (MCI), and 10 non-AD subjects. pTau231 was different between AD and non-AD (p = 0.0300) and α-synuclein differentiated AD from MCI (p = 0.0148). This study shows how ACE microfluidic chip technology can help differentiate AD and MCI patients from non-AD controls with clinical relevance. This work also highlights the important diagnostic role of plasma EV biomarkers in neurodegenerative disease.

Plasma Alzheimer's disease biomarker variability: Amyloid-independent and amyloid-dependent factors.

We aimed to investigate which factors affect plasma biomarker levels via amyloid beta (Aβ)-independent or Aβ-dependent effects and improve the predictive performance of these biomarkers for Aβ positivity on positron emission tomography (PET). A total of 2935 participants underwent blood sampling for measurements of plasma Aβ42/40 ratio, phosphorylated tau 217 (p-tau217; ALZpath), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) levels usingsingle-molecule array and Aβ PET. Laboratory findings were collected using a routine blood test battery. Aβ-independent factors included hemoglobin and estimated glomerular filtration rate (eGFR) for p-tau217 and hemoglobin, eGFR, and triiodothyronine (T3) for GFAP and NfL. Aβ-dependent factors included apolipoprotein E genotypes, body mass index status for Aβ42/40, p-tau217, GFAP, and NfL. However, these factors exhibited negligible or modest effects on Aβ positivity on PET. Our findings highlight the importance of accurately interpreting plasma biomarkers for predicting Aβ uptake in real-world settings. We investigated factor-Alzheimer's disease plasma biomarker associations in a large Korean cohort. Hemoglobin and estimated glomerular filtration rate affect the biomarkers independently of brain amyloid beta (Aβ). Apolipoprotein E genotypes and body mass index status affect the biomarkers dependent on brain Aβ. Addition of Aβ-independent factors shows negligible effect in predicting Aβ positivity. Adjusting for Aβ-dependent factors shows amodest effect in predicting Aβ positivity.

Ultrasensitive Detection of Blood-Based Alzheimer's Disease Biomarkers: A Comprehensive SERS-Immunoassay Platform Enhanced by Machine Learning.

Accurate and early disease detection is crucial for improving patient care, but traditional diagnostic methods often fail to identify diseases in their early stages, leading to delayed treatment outcomes. Early diagnosis using blood derivatives as a source for biomarkers is particularly important for managing Alzheimer's disease (AD). This study introduces a novel approach for the precise and ultrasensitive detection of multiple core AD biomarkers (Aβ40, Aβ42, p-tau, and t-tau) using surface-enhanced Raman spectroscopy (SERS) combined with machine-learning algorithms. Our method employs an antibody-immobilized aluminum SERS substrate, which offers high precision, sensitivity, and accuracy. The platform achieves an impressive detection limit in the attomolar (aM) range and spans a wide dynamic range from aM to micromolar (μM) concentrations. This ultrasensitive and specific SERS immunoassay platform shows promise for identifying mild cognitive impairment (MCI), a potential precursor to AD, from blood plasma. Machine-learning algorithms applied to the spectral data enhance the differentiation of MCI from AD and healthy controls, yielding excellent sensitivity and specificity. Our integrated SERS-machine-learning approach, with its interpretability, advances AD research and underscores the effectiveness of a cost-efficient, easy-to-prepare Al-SERS substrate for clinical AD detection.

Blood biomarkers in Down syndrome: Facilitating Alzheimer's disease detection and monitoring.

Blood-based biomarkers continue to be explored for disease detection, monitoring of progression, and therapeutic outcomes as the diagnostic determination of Alzheimer's Disease in Down Syndrome (DS-AD) remains challenging in clinical settings. This perspective highlights the current status of this effort. Overall, amyloid (A), tau (T), and neurodegeneration (AT[N]) blood-based biomarkers have been shown to increase with disease pathology for individuals with DS. Phosphorylated tau biomarkers (p-tau217, p-tau181) have been consistently shown to track disease progression for DS-AD and are likely good candidates for use in clinical settings. Biomarkers of inflammation (glial fibrillary acidic protein) also show promise; however, additional work is needed. Findings from stability work of blood-based biomarkers conducted among non-DS also supportthe potential longitudinal utility of biomarkers such as neurofilament light chain and p-tau181 in DS. Gaps in our knowledge are highlighted, and a potential role for sex differences in biomarker outcomes is noted, along with recommendations for determining the appropriate context of use when translating biomarkers into clinical applications. HIGHLIGHTS: An overview of blood-based biomarkers for Alzheimer's disease (AD) was provided for consideration of their utility among individuals with Down syndrome when looking toward potential clinical applications. Longitudinal stability of many blood biomarkers and improvement in detection sensitivity make blood such as plasma a viable source for exploring AD pathology. Variability in reviewed findings regarding the application of blood biomarkers highlights the importance of understanding and defining the appropriate context of use, particularly when translating them into clinical practice.

Markers of amyloid-β deposition and burden of enlarged perivascular spaces in patients with cognitive impairment and small vessel disease.

MRI-visible enlarged perivascular spaces (EPVS) are common in patients with cognitive impairment and possibly linked to Alzheimer's disease (AD) and cerebral amyloid angiopathy (CAA). In a study of memory clinic patients (n = 450; mean age 66.5 ± 7.45, 45.8% female), we investigated CSF amyloid-β (Aβ)1-42 (AD biomarker) and strictly lobar microbleeds (CAA marker) in relation to centrum semiovale EPVS (CSO-EPVS). Age-controlled analyses showed that severe CSO-EPVS associated with Aβ status (odds ratio [OR] = 1.51, 95%CI = 1.02-2.24), but not strictly lobar microbleeds (OR = 1.39, 95%CI = 0.92-2.11), with no significant Aβ status and microbleeds interaction. This implies that in this setting, severe CSO-EPVS is not a specific indicator of CAA.

Sex differences in the association between repetitive negative thinking and neurofilament light.

Emerging evidence suggests that repetitive negative thinking (RNT; i.e., worry and ruminative brooding) is associated with biomarkers of Alzheimer's disease. Given that women have a greater risk of many neurodegenerative diseases, this study investigated whether worry and brooding are associated with general neurodegeneration and whether associations differ by sex. Exploratory analyses examined whether allostatic load, a marker of chronic stress, mediates any observed relationships. Baseline data from 134 cognitively healthy older adults in the Age-Well clinical trial were utilised. Worry and brooding were assessed using questionnaires. Plasma neurofilament light chain (NfL), a biomarker of neurodegeneration, was quantified using a Meso Scale Discovery assay. We found a positive interaction between brooding and sex on NfL, with higher brooding associated with greater NfL levels in women. No associations were observed between worry/ruminative brooding and allostatic load. These results offer preliminary support that RNT is associated with worse brain health, specifically in women.

Neuropathological Heterogeneity of Dementia Due to Combined Pathology in Aged Patients: Clinicopathological Findings in the Vallecas Alzheimer’s Reina Sofía Cohort

Background/Objectives: Clinicopathological research in late-life dementia has focused recently on combined neurodegenerative and vascular conditions underlying the high phenotypic heterogeneity of patients. The Vallecas Alzheimer’s Reina Sofía (VARS) cohort (n > 550), and particularly the series of associated brain donations (VARSpath cohort) are presented here. The aim of this study is to contribute to research in dementia with a well-characterized cohort from a single center. Methods: A total of 167 patients with complete neuropathological work-ups were analyzed here. The cohort is characterized by a high female predominance (79%), advanced age at death (88 yrs.), and a high frequency of ApoE-e4 haplotype (43%). Results: The main neuropathological diagnosis was Alzheimer’s disease (79.6%), followed by vascular dementia (10.2%) and Lewy body dementia (6%). Overall, intermediate-to-high cerebrovascular disease was observed in 38.9%, Lewy body pathology in 57.5%, LATE (TDP-43 pathology) in 70.7%, ARTAG in 53%, and argyrophilic grain disease in 12% of the patients. More than one pathology with a clinically relevant burden of disease was present in 71.1% of the brains, and a selection of premortem neuropsychological and functional scores showed significant correlation with the number of co-pathologies identified in postmortem brains. Conclusions: The VARS cohort, with thorough clinical follow-up, regular blood sampling, 3-Tesla MR, and a high rate of postmortem brain donation, can provide essential multidisciplinary data in the rising age of modifying therapies and biomarkers for Alzheimer’s disease and related dementias.

Discovery of Urinary Biomarker: Urine Amyloid Beta as a Non-Invasive Biomarker for Early Alzheimer’s Disease and Cognitive Impairment - A Study of 24 Patients with Cognitive Decline

Discovery of Urinary Biomarker: Urine Amyloid Beta as a Non-Invasive Biomarker for Early Alzheimer’s Disease and Cognitive Impairment - A Study of 24 Patients with Cognitive Decline

Pharmacodynamic effects of semorinemab on plasma and CSF biomarkers of Alzheimer's disease pathophysiology.

Semorinemab, an anti-tau monoclonal antibody, was assessed in two Phase II trials for Alzheimer's disease (AD). Plasma and cerebrospinal fluid (CSF) biomarkers provided insights into the drug's potential mechanism of action. Qualified assays were used to measure biomarkers of tau, amyloidosis, glial activity, neuroinflammation, synaptic function, and neurodegeneration from participant samples in Tauriel (NCT03289143) and Lauriet (NCT03828747) Phase II trials. Plasma phosphorylated Tau 181 (pTau181) and CSF chitinase-3-like protein 1 (YKL-40) increased following semorinemab treatment in both studies. In Lauriet, increasing plasma glial fibrillary protein (GFAP) concentrations stabilized with semorinemab, while this was not observed in Tauriel. Other AD pathophysiology biomarkers showed no consistent response to semorinemab. Increases in CSF YKL-40 suggest that semorinemab may stimulate microglia activation in the presence of AD-associated Tau pathology, but not in healthy controls. Stabilization of plasma GFAP in Lauriet indicates a possible impact on reactive gliosis in mild-to-moderate AD. Tauriel ClinicalTrials.gov Identifier: NCT03289143. Lauriet ClinicalTrials.gov Identifier: NCT03828747. Phase 1 ClinicalTrials.gov Identifier: NCT02820896. AD pathophysiology biomarkers were measured to assess the mechanism of action. Semorinemab increased CSF YKL-40 in participants with AD but not in healthy controls. Semorinemab possibly stabilized plasma GFAP in the Lauriet trial. Semorinemab treatment may activate microglia and moderate reactive gliosis.

Glial fibrillary acidic protein in Alzheimer’s disease: a narrative review

Abstract Astrocytes are fundamental in neural functioning and homeostasis in the Central Nervous System. These cells respond to injuries and pathological conditions through astrogliosis, a reactive process associated with neurodegenerative diseases such as Alzheimer’s disease. This process is thought to begin in the early stages of these conditions. Glial Fibrillary Acidic Protein (GFAP), a type III intermediate filament protein predominantly expressed in astrocytes, has emerged as a key biomarker for monitoring this response. During astrogliosis, GFAP is released into biofluids, making it a candidate for non-invasive diagnosis and tracking of neurodegenerative diseases. Growing evidence positions GFAP as a biomarker for Alzheimer’s disease with specificity and disease-correlation characteristics comparable to established clinical markers, such as Aβ peptides and phosphorylated tau protein. To improve diagnostic accuracy, particularly in the presence of confounders and comorbidities, incorporating a panel of biomarkers may be advantageous. This review will explore the potential of GFAP within such a panel, examining its role in early diagnosis, disease progression monitoring, and its integration into clinical practice for Alzheimer’s disease management.

Elevated serum sodium is linked to increased amyloid-dependent tau pathology, neurodegeneration, and cognitive impairment in Alzheimer's disease.

Vascular dysfunction is implicated in the pathophysiology of Alzheimer's disease (AD). While sodium is essential for maintaining vascular function, its role in AD pathology remains unclear. We included 353 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI), assessing serum sodium levels, cerebrospinal fluid (CSF) and positron emission tomography (PET) biomarkers, magnetic resonance imaging (MRI), and cognitive function. An independent sample (N = 471) with available CSF sodium-related proteins and AD biomarkers was also included. Associations between serum sodium levels and AD pathology, neurodegeneration, and cognition were evaluated using linear regression models. Spearman's correlation analyses assessed the relationships between CSF sodium-related proteins and AD biomarkers. Higher serum sodium levels were associated with increased AD pathology, reduced hippocampal volume, and greater cognitive decline (all p < 0.05). The relationship between serum sodium and amyloid PET was evident in several AD-susceptible brain regions, including the neocortex and limbic system. Individuals with high serum sodium exhibited higher tau pathology, lower hippocampal volume, and more severe cognitive decline per unit increase in amyloid PET compared to those with low serum sodium (all p < 0.05). Among the 14 CSF sodium-related proteins, which were inter-correlated, six were significantly correlated with CSF AD pathology and amyloid PET, while two were correlated with hippocampal volume and cognitive function, with sodium channel subunit beta-2 (SCN2B) and sodium channel subunit beta-3 (SCN3B) showing the strongest correlations. These findings underscore the crucial role of serum sodium in AD progression, highlighting a potential network of sodium dysregulation involved in AD pathology. Targeting sodium may offer a novel therapeutic approach to slowing AD progression, particularly by impeding the progression of amyloid-related downstream events.

Identifying the Role of Oligodendrocyte Genes in the Diagnosis of Alzheimer's Disease through Machine Learning and Bioinformatics Analysis.

Due to the heterogeneity of Alzheimer's disease (AD), the underlying pathogenic mechanisms have not been fully elucidated. Oligodendrocyte (OL) damage and myelin degeneration are prevalent features of AD pathology. When oligodendrocytes are subjected to amyloid-beta (Aβ) toxicity, this damage compromises the structural integrity of myelin and results in a reduction of myelin-associated proteins. Consequently, the impairment of myelin integrity leads to a slowdown or cessation of nerve signal transmission, ultimately contributing to cognitive dysfunction and the progression of AD. Consequently, elucidating the relationship between oligodendrocytes and AD from the perspective of oligodendrocytes is instrumental in advancing our understanding of the pathogenesis of AD. Here, an attempt is made in this study to identify oligodendrocyte-related biomarkers of AD. AD datasets were obtained from the Gene Expression Omnibus database and used for consensus clustering to identify subclasses. Hub genes were identified through differentially expressed genes (DEGs) analysis and oligodendrocyte gene set enrichment. Immune infiltration analysis was conducted using the CIBERSORT method. Signature genes were identified using machine learning algorithms and logistic regression. A diagnostic nomogram for predicting AD was developed and validated using external datasets and an AD model. A small molecular compound was identified using the eXtreme Sum algorithm. 46 genes were found to be significantly correlated with AD progression by examining the overlap between DEGs and oligodendrocyte genes. Two subclasses of AD, Cluster A, and Cluster B, were identified, and 9 signature genes were identified using a machine learning algorithm to construct a nomogram. Enrichment analysis showed that 9 genes are involved in apoptosis and neuronal development. Immune infiltration analysis found differences in immune cell presence between AD patients and controls. External datasets and RT-qPCR verification showed variation in signature genes between AD patients and controls. Five small molecular compounds were predicted. It was found that 9 oligodendrocyte genes can be used to create a diagnostic tool for AD, which could help in developing new treatments.

Altered immune response is associated with sex difference in vulnerability to Alzheimer's disease in human prefrontal cortex.

Alzheimer's disease (AD) is a neurodegenerative disorder with a higher risk incidence in females than in males, and there are also differences in AD pathophysiology between sexes. The role of sex in the pathogenesis of AD may be crucial, yet the cellular and molecular basis remains unclear. Here, we performed a comprehensive analysis using four public transcriptome datasets of AD patients and age-matched control individuals in prefrontal cortex, including bulk transcriptome (295 females and 402 males) and single-nucleus RNA sequencing (snRNA-seq) data (224 females and 219 males). We found that the transcriptomic profile in female control was similar to those in AD. To characterize the key features associated with both the pathogenesis of AD and sex difference, we identified a co-expressed gene module that positively correlated with AD, sex, and aging, and was also enriched with immune-associated pathways. Using snRNA-seq datasets, we found that microglia (MG), a resident immune cell in the brain, demonstrated substantial differences in several aspects between sexes, such as an elevated proportion of activated MG, altered transcriptomic profile and cell-cell interaction between MG and other brain cell types in female control. Additionally, genes upregulated in female MG, such as TLR2, MERTK, SPP1, SLA, ACSL1, and FKBP5, had high confidence to be identified as biomarkers to distinguish AD status, and these genes also interacted with some approved drugs for treatment of AD. These findings underscore the altered immune response in female is associated with sex difference in susceptibility to AD, and the necessity of considering sex factors when developing AD biomarkers and therapeutic strategies, providing a scientific basis for further in-depth studies on sex differences in AD.

The association of the triglyceride-glucose index with Alzheimer's disease and its potential mechanisms.

The correlation between Alzheimer's disease (AD) and the glucose-triglyceride (TyG) index remains undetermined. This study aimed to investigate the relationship between the TyG index and AD, as well as the relationship between the TyG index and cerebrospinal fluid (CSF) AD biomarkers and cognition. Six hundred twenty-eight non-dementia participants were included. The TyG index, pathological markers, and cognitive measures were studied using multiple linear regression. Also calculated using a multivariate Cox regression model were the hazard ratio (HR) and its 95% confidence interval (CI). Ten thousand bootstrap iterative causal mediation analyses were performed to investigate the potential mediating effect of AD pathology on cognition. The TyG index was linked to CSF AD biomarkers (βAβ42 = 0.880; βTau = -0.674; βpTau = -0.884; βAβ42/pTau = 1.764; βAβ42/Tau = 1.554; βpTau/Tau = -0.210) and cognitive measurements (βMEM = 0.570; βEF = 0.535; βADAS11 = -0.789). Mediation analysis revealed that the TyG index may influence cognition via CSF AD biomarkers, including Aβ42, tau, and pTau. Furthermore, each 1-unit increase in TyG index was associated with a 29.5% reduction in the risk of incident AD. A delayed rate of cognitive decline and a reduced risk of AD were found to be correlated with higher levels of the TyG index, but this does not mean increasing TyG index levels is beneficial for health. Through AD pathology, the TyG index may influence AD and cognitive changes.

Relationship between MRI brain-age heterogeneity, cognition, genetics and Alzheimer’s disease neuropathology

Brain ageing is highly heterogeneous, as it is driven by a variety of normal and neuropathological processes. These processes may differentially affect structural and functional brain ageing across individuals, with more pronounced ageing (older brain age) during midlife being indicative of later development of dementia. Here, we examined whether brain-ageing heterogeneity in unimpaired older adults related to neurodegeneration, different cognitive trajectories, genetic and amyloid-beta (Aβ) profiles, and to predicted progression to Alzheimer's disease (AD). Functional and structural brain age measures were obtained for resting-state functional MRI and structural MRI, respectively, in 3460 cognitively normal individuals across an age range spanning 42-85 years. Participants were categorised into four groups based on the difference between their chronological and predicted age in each modality: advanced age in both (n=291), resilient in both (n=260) or advanced in one/resilient in the other (n=163/153). With the resilient group as the reference, brain-age groups were compared across neuroimaging features of neuropathology (white matter hyperintensity volume, neuronal loss measured with Neurite Orientation Dispersion and Density Imaging, AD-specific atrophy patterns measured with the Spatial Patterns of Abnormality for Recognition of Early Alzheimer's Disease index, amyloid burden using amyloid positron emission tomography (PET), progression to mild cognitive impairment and baseline and longitudinal cognitive measures (trail making task, mini mental state examination, digit symbol substitution task). Individuals with advanced structural and functional brain-ages had more features indicative of neurodegeneration and they had poor cognition. Individuals with a resilient brain-age in both modalities had a genetic variant that has been shown to be associated with age of onset of AD. Mixed brain-age was associated with selective cognitive deficits. The advanced group displayed evidence of increased atrophy across all neuroimaging features that was not found in either of the mixed groups. This is in line with biomarkers of preclinical AD and cerebrovascular disease. These findings suggest that the variation in structural and functional brain ageing across individuals reflects the degree of underlying neuropathological processes and may indicate the propensity to develop dementia in later life. The National Institute on Aging, the National Institutes of Health, the Swiss National Science Foundation, the Kaiser Foundation Research Institute and the National Heart, Lung, and Blood Institute.