Relationships between frontal metabolites and Alzheimer's disease biomarkers in cognitively normal older adults

Feasibility of Using Magnetic Resonance Spectroscopy Test Biomarkers to Diagnose Alzheimer's Disease: Systematic Evaluation and Meta-Analysis

BACKGROUND

Alzheimer's disease (AD) is the leading cause of dementia, resulting in impairments in memory, cognition, decision-making, and social skills. Thus, accurate preclinical diagnosis of Alzheimer's disease is paramount. The identification of biomarkers for Alzheimer's disease through magnetic resonance spectroscopy (MRS) represents a novel adjunctive diagnostic approach.

OBJECTIVE

This study conducted a meta-analysis of the diagnostic results of this technology to explore its feasibility and accuracy.

METHODS

PubMed, Cochrane Library, EMBASE, and Web of Science databases were searched without restrictions, with the search period extending up to July 31, 2022. The search strategy employed a combination of subject headings and keywords. All retrieved documents underwent screening by two researchers, who selected them for meta-analysis. The included literature was analyzed using Review Manager 5.4 software, with corresponding bias maps, forest plots, and summary receiver operating characteristic (SROC) curves generated and analyzed.

RESULTS

A total of 344 articles were retrieved initially, with 11 articles meeting the criteria for inclusion in the analysis. The analysis encompassed data from approximately 1766 patients. In the forest plot, both sensitivity (95% CI) and specificity (95% CI) approached 1. Examining the true positive rate, false positive rate, true negative rate, and false negative rate, all studies on the summary receiver operating characteristic (SROC) curve clustered in the upper left quadrant, suggesting a very high accuracy of biomarkers detected by MRS for diagnosing Alzheimer's disease.

CONCLUSION

The detection of biomarkers by MRS demonstrates feasibility and high accuracy in diagnosing AD. This technology holds promise for widespread adoption in the clinical diagnosis of AD in the future.

Insulin-stimulated brain glucose uptake correlates with brain metabolites in severe obesity: A combined neuroimaging study

The human brain undergoes metabolic adaptations in obesity, but the underlying mechanisms have remained largely unknown. We compared concentrations of often reported brain metabolites measured with magnetic resonance spectroscopy (1H-MRS, 3 T MRI) in the occipital lobe in subjects with obesity and lean controls under different metabolic conditions (fasting, insulin clamp, following weight loss). Brain glucose uptake (BGU) quantified with 18F-fluorodeoxyglucose positron emission tomography (18F-FDG-PET)) was also performed in a subset of subjects during clamp. In dataset A, 48 participants were studied during fasting with brain 1H-MRS, while in dataset B 21 participants underwent paired brain 1H-MRS acquisitions under fasting and clamp conditions. In dataset C 16 subjects underwent brain 18F-FDG-PET and 1H-MRS during clamp. In the fasting state, total N-acetylaspartate was lower in subjects with obesity, while brain myo-inositol increased in response to hyperinsulinemia similarly in both lean participants and subjects with obesity. During clamp, BGU correlated positively with brain glutamine/glutamate, total choline, and total creatine levels. Following weight loss, brain creatine levels were increased, whereas increases in other metabolites remained not significant. To conclude, insulin signaling and glucose metabolism are significantly coupled with several of the changes in brain metabolites that occur in obesity.

Circular-SWAT for deep learning based diagnostic classification of Alzheimer's disease: application to metabolome data

BACKGROUND

Deep learning has shown potential in various scientific domains but faces challenges when applied to complex, high-dimensional multi-omics data. Alzheimer's Disease (AD) is a neurodegenerative disorder that lacks targeted therapeutic options. This study introduces the Circular-Sliding Window Association Test (c-SWAT) to improve the classification accuracy in predicting AD using serum-based metabolomics data, specifically lipidomics.

METHODS

The c-SWAT methodology builds upon the existing Sliding Window Association Test (SWAT) and utilizes a three-step approach: feature correlation analysis, feature selection, and classification. Data from 997 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) served as the basis for model training and validation. Feature correlations were analyzed using Weighted Gene Co-expression Network Analysis (WGCNA), and Convolutional Neural Networks (CNN) were employed for feature selection. Random Forest was used for the final classification.

FINDINGS

The application of c-SWAT resulted in a classification accuracy of up to 80.8% and an AUC of 0.808 for distinguishing AD from cognitively normal older adults. This marks a 9.4% improvement in accuracy and a 0.169 increase in AUC compared to methods without c-SWAT. These results were statistically significant, with a p-value of 1.04 × 10ˆ-4. The approach also identified key lipids associated with AD, such as Cer(d16:1/22:0) and PI(37:6).

INTERPRETATION

Our results indicate that c-SWAT is effective in improving classification accuracy and in identifying potential lipid biomarkers for AD. These identified lipids offer new avenues for understanding AD and warrant further investigation.

FUNDING

The specific funding of this article is provided in the acknowledgements section.

MRS in neurodegenerative dementias, prodromal syndromes and at-risk states: A systematic review of the literature

BACKGROUND

In recent years, MRS has benefited from increased MRI field strengths, new acquisition protocols and new processing techniques. This review aims to determine how this has altered our understanding of MRS neurometabolic markers in neurodegenerative dementias.

METHODS

Our systematic review of human in vivo MRS literature since 2002 pertains to Alzheimer's disease (AD), dementia with Lewy bodies (DLB), Parkinson's disease dementia, frontotemporal dementia (FTD), prodromal and 'at-risk' states. Studies using field strengths of 3 T or more were included.

RESULTS

Of 85 studies, AD and/or mild cognitive impairment (MCI) were the most common conditions of interest (58 papers, 68%). Only 14 (16%) studies included other dementia syndromes and 13 (15%) investigated 'at-risk' cohorts. Earlier findings of lower N-acetylaspartate and higher myo-inositol were confirmed. Additionally, lower choline and creatine in AD and MCI were reported, though inconsistently. Previously challenging-to-measure metabolites (glutathione, glutamate and gamma-aminobutyric acid) were reportedly lower in AD, FTD and DLB compared with controls.

DISCUSSION

Increasing field strength alongside targeted acquisition protocols has revealed additional metabolite changes. Most studies were small and regional metabolite differences between dementia types may not have been captured due to the predominant placement of voxels in the posterior cingulate cortex. The standard of data collection, quality control and analysis is improving due to greater consensus regarding acquisition and processing techniques. Ongoing harmonization of techniques, creation of larger and longitudinal cohorts, and placement of MRS voxels in more diverse regions will strengthen future research.

APOE Peripheral and Brain Impact: APOE4 Carriers Accelerate Their Alzheimer Continuum and Have a High Risk of Suicide in PM2.5 Polluted Cities

This Review emphasizes the impact of APOE4-the most significant genetic risk factor for Alzheimer's disease (AD)-on peripheral and neural effects starting in childhood. We discuss major mechanistic players associated with the APOE alleles' effects in humans to understand their impact from conception through all life stages and the importance of detrimental, synergistic environmental exposures. APOE4 influences AD pathogenesis, and exposure to fine particulate matter (PM_2.5), manufactured nanoparticles (NPs), and ultrafine particles (UFPs) associated with combustion and friction processes appear to be major contributors to cerebrovascular dysfunction, neuroinflammation, and oxidative stress. In the context of outdoor and indoor PM pollution burden-as well as Fe, Ti, and Al alloys; Hg, Cu, Ca, Sn, and Si UFPs/NPs-in placenta and fetal brain tissues, urban APOE3 and APOE4 carriers are developing AD biological disease hallmarks (hyperphosphorylated-tau (P-tau) and amyloid beta 42 plaques (Aβ₄₂)). Strikingly, for Metropolitan Mexico City (MMC) young residents ≤ 40 y, APOE4 carriers have 4.92 times higher suicide odds and 23.6 times higher odds of reaching Braak NFT V stage versus APOE4 non-carriers. The National Institute on Aging and Alzheimer's Association (NIA-AA) framework could serve to test the hypothesis that UFPs and NPs are key players for oxidative stress, neuroinflammation, protein aggregation and misfolding, faulty complex protein quality control, and early damage to cell membranes and organelles of neural and vascular cells. Noninvasive biomarkers indicative of the P-tau and Aβ₄₂ abnormal protein deposits are needed across the disease continuum starting in childhood. Among the 21.8 million MMC residents, we have potentially 4 million APOE4 carriers at accelerated AD progression. These APOE4 individuals are prime candidates for early neuroprotective interventional trials. APOE4 is key in the development of AD evolving from childhood in highly polluted urban centers dominated by anthropogenic and industrial sources of pollution. APOE4 subjects are at higher early risk of AD development, and neuroprotection ought to be implemented. Effective reductions of PM_2.5, UFP, and NP emissions from all sources are urgently needed. Alzheimer's Disease prevention ought to be at the core of the public health response and physicians-scientist minority research be supported.

Acute administration of ketone beta-hydroxybutyrate downregulates 7T proton magnetic resonance spectroscopy-derived levels of anterior and posterior cingulate GABA and glutamate in healthy adults

Glucose metabolism is impaired in brain aging and several neurological conditions. Beneficial effects of ketones have been reported in the context of protecting the aging brain, however, their neurophysiological effect is still largely uncharacterized, hurdling their development as a valid therapeutic option. In this report, we investigate the neurochemical effect of the acute administration of a ketone d-beta-hydroxybutyrate (D-βHB) monoester in fasting healthy participants with ultrahigh-field proton magnetic resonance spectroscopy (MRS). In two within-subject metabolic intervention experiments, 7 T MRS data were obtained in fasting healthy participants (1) in the anterior cingulate cortex pre- and post-administration of D-βHB (N = 16), and (2) in the posterior cingulate cortex pre- and post-administration of D-βHB compared to active control glucose (N = 26). Effect of age and blood levels of D-βHB and glucose were used to further explore the effect of D-βHB and glucose on MRS metabolites. Results show that levels of GABA and Glu were significantly reduced in the anterior and posterior cortices after administration of D-βHB. Importantly, the effect was specific to D-βHB and not observed after administration of glucose. The magnitude of the effect on GABA and Glu was significantly predicted by older age and by elevation of blood levels of D-βHB. Together, our results show that administration of ketones acutely impacts main inhibitory and excitatory transmitters in the whole fasting cortex, compared to normal energy substrate glucose. Critically, such effects have an increased magnitude in older age, suggesting an increased sensitivity to ketones with brain aging.

Frontal Metabolites and Alzheimer's Disease Biomarkers in Healthy Older Women and Women Diagnosed with Mild Cognitive Impairment

BACKGROUND

Women account for two thirds of the prevalence and incidence of Alzheimer's disease (AD) and mild cognitive impairment (MCI). Evidence suggest that sex may differently influence the expression of proteins amyloid-beta (Aβ1-42) and tau, for which early detection is crucial in prevention of the disease.

OBJECTIVE

We investigated the effect of aging and cerebrospinal fluid (CSF) levels of Aβ1-42 and tau on frontal metabolites measured with proton magnetic resonance spectroscopy (MRS) in a cohort of cognitively normal older women and women with MCI.

METHODS

3T single-voxel MRS was performed on the medial frontal cortex, using Point Resolved Spectroscopy (PRESS) and Mescher-Garwood Point Resolved Spectroscopy (MEGA-PRESS) in 120 women (age range 50-85). CSF samples of Aβ1-42 and tau and scores of general cognition were also obtained.

RESULTS

Levels of frontal gamma aminobutyric acid (GABA+) were predicted by age, independently of disease and CSF biomarkers. Importantly, levels of GABA+ were reduced in MCI patients. Additionally, we found that levels of N-acetylaspartate relative to myo-inositol (tNAA/mI) predicted cognition in MCI patients only and were not related to CSF biomarkers.

CONCLUSION

This study is the first to demonstrate a strong association between frontal GABA+ levels and neurological aging in a sample consisting exclusively of healthy older women with various levels of CSF tau and Aβ1-42 and women with MCI. Importantly, our results show no correlation between CSF biomarkers and MRS metabolites in this sample.