Blood-Based Biomarkers for Predictive Diagnosis of Cognitive Impairment in a Pakistani Population

Altering plasma lipids and liver enzyme activities via hippocampal injections of hen Lysozyme amyloid aggregates in an Alzheimer's disease mouse model: Insights into the therapeutic role of Bis (Indolyl) phenylmethane

Alzheimer's disease (AD) is a prevalent form of dementia in the elderly. There is currently no effective treatment available for this disease. Diagnosis of AD typically relies on clinical manifestations and specific biomarkers. The present study investigated the impact of inducing Alzheimer's disease (AD) in mice through the injection of lysozyme amyloids formed in the presence or absence of Bis (Indolyl) phenylmethane (BIPM) on alterations in plasma lipid profiles and liver enzyme activities. 24 adult Wistar rats were divided into control, Scopolamine, Lysozyme, BIPM groups and the blood samples were obtained from the groups for biochemical analysis. The findings of the study revealed significant changes in the plasma lipid profiles and liver enzyme markers of the Lysozyme group compared to the control group. The Lysozyme group exhibited elevated triglycerides (n = 6, P < 0.02) and LDL levels (n = 6, P < 0.02), reduced HDL (n = 6, P < 0.05) and cholesterol levels (n = 6, P < 0.02), and altered serum glutamic oxaloacetic transaminase (SGOT) level (n = 6, P < 0.05) compared to controls. While the level of serum glutamic pyruvic transaminase (SGPT) did not change significantly compared to the control. BIPM groups showed no significant changes in lipid or enzyme levels compared to controls. Overall, our research has shown that BIPM has the ability to modify the structure of HEWL aggregates, thereby improving the detrimental effects associated with AD caused by these aggregates. Analyzing lipid profiles and liver enzyme markers presents a promising avenue for targeted therapeutic approaches. These alterations observed in the plasma may potentially serve as candidate biomarkers for diagnosing this disease.

Clinical advances in analytical profiling of signature lipids: implications for severe non-communicable and neurodegenerative diseases

BACKGROUND

Lipids play key roles in numerous biological processes, including energy storage, cell membrane structure, signaling, immune responses, and homeostasis, making lipidomics a vital branch of metabolomics that analyzes and characterizes a wide range of lipid classes. Addressing the complex etiology, age-related risk, progression, inflammation, and research overlap in conditions like Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and Cancer poses significant challenges in the quest for effective therapeutic targets, improved diagnostic markers, and advanced treatments. Mass spectrometry is an indispensable tool in clinical lipidomics, delivering quantitative and structural lipid data, and its integration with technologies like Liquid Chromatography (LC), Magnetic Resonance Imaging (MRI), and few emerging Matrix-Assisted Laser Desorption Ionization- Imaging Mass Spectrometry (MALDI-IMS) along with its incorporation into Tissue Microarray (TMA) represents current advances. These innovations enhance lipidomics assessment, bolster accuracy, and offer insights into lipid subcellular localization, dynamics, and functional roles in disease contexts.

AIM OF THE REVIEW

The review article summarizes recent advancements in lipidomic methodologies from 2019 to 2023 for diagnosing major neurodegenerative diseases, Alzheimer's and Parkinson's, serious non-communicable cardiovascular diseases and cancer, emphasizing the role of lipid level variations, and highlighting the potential of lipidomics data integration with genomics and proteomics to improve disease understanding and innovative prognostic, diagnostic and therapeutic strategies.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Clinical lipidomic studies are a promising approach to track and analyze lipid profiles, revealing their crucial roles in various diseases. This lipid-focused research provides insights into disease mechanisms, biomarker identification, and potential therapeutic targets, advancing our understanding and management of conditions such as Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and specific cancers.

Large-scale functional network connectivity mediates the associations between lipids metabolism and cognition in type 2 diabetes

Type 2 diabetes (T2D) is associated with dyslipidemia and mild cognitive impairment. This study investigated the relationships between serum lipids metabolism, cognition, and functional connectivity (FC) within and between brain networks in T2D patients. The study included 102 T2D patients and 45 healthy controls who underwent functional magnetic resonance imaging, lipid profile tests, and cognitive assessments. Thirteen functional networks were identified using independent component analysis. The statistical analyses included multivariate analysis of covariance, partial correlation, canonical correlation, and mediation analyses. We found widely reduced between-network FCs in T2D, especially between the ventral sensorimotor network (SMN) and dorsal attention network (DAN) (p = 0.001) and between the ventral SMN and lateral visual network (VN) (p < 0.001). Moreover, lower between-network FCs were correlated with worse serum lipids metabolism and poorer cognitive performance (all p < 0.05). Importantly, between-network FCs mediated the relationship between lipid metabolism and cognition (β = -0.3136, 95% CI: -0.7660, -0.0186). Within-network analyses revealed altered FCs within the anterior default mode network, DAN, and lateral VN, each positively correlated with global cognition (all p < 0.01). Our results suggest the potential of improving cognitive function by regulating serum lipids in individuals with T2D.

Association between Serum GDF-15 and Cognitive Dysfunction in Hemodialysis Patients

Cognitive dysfunction is more frequent in end-stage renal disease (ESRD) patients undergoing hemodialysis compared with the healthy population, emphasizing the need for early detection. Interest in serum markers that reflect cognitive function has recently increased. Elevated serum growth differentiation factor 15 (GDF-15) levels are known to be associated with an increased risk of decreased renal function and cognitive dysfunction. This study investigated the relationship between GDF-15 and cognitive dysfunction in hemodialysis patients using a retrospective analysis of 92 individuals aged ≥ 18 years. Cognitive function was assessed using the Korean version of the Mini-Mental Status Examination (K-MMSE), categorizing patients into normal (≥24 points) and cognitive dysfunction (<24 points). As a result, serum GDF-15 concentrations were at significantly higher levels in the cognitive dysfunction group (7500.42 pg/mL, p = 0.001). Logistic regression indicated an increased risk of K-MMSE scores < 24 points when serum GDF-15 exceeded 5408.33 pg/mL. After indoxyl sulfate exposure in HT22 cells, HT22 cells survival was decreased and GDF-15 expression in HT22 cells was increased. Similarly, exposure to indoxyl sulfate in mouse brain tissue resulted in an increased expression of GDF-15. This study highlights the potential of serum GDF-15 as a marker for cognitive dysfunction in hemodialysis patients, offering a valuable screening tool. Serum GDF-15 is related to cognitive dysfunction in hemodialysis patients and may be helpful in screening for cognitive dysfunction in hemodialysis patients.

Lipid metabolism and oxidative stress in patients with Alzheimer's disease and amnestic mild cognitive impairment

Lipid metabolism and oxidative stress are key mechanisms in Alzheimer's disease (AD). The link between plasma lipid metabolites and oxidative stress in AD patients is poorly understood. This study was to identify markers that distinguish AD and amnestic mild cognitive impairment (aMCI) from NC, and to reveal potential links between lipid metabolites and oxidative stress. We performed non-targeted lipid metabolism analysis of plasma from patients with AD, aMCI, and NC using LC-MS/MS. The plasma malondialdehyde (MDA), glutathione peroxidase (GSH-Px), and superoxide dismutase (SOD) levels were assessed. We found significant differences in lipid metabolism between patients with AD and aMCI compared to those in NC. AD severity is associated with lipid metabolites, especially TG (18:0_16:0_18:0) + NH4, TG (18:0_16:0_16:0) + NH4, LPC(16:1e)-CH3, and PE (20:0_20:4)-H. SPH (d16:0) + H, SPH (d18:1) + H, and SPH (d18:0) + H were high-performance markers to distinguish AD and aMCI from NC. The AUC of three SPHs combined to predict AD was 0.990, with specificity and sensitivity as 0.949 and 1, respectively; the AUC of three SPHs combined to predict aMCI was 0.934, with specificity and sensitivity as 0.900, 0.981, respectively. Plasma MDA concentrations were higher in the AD group than in the NC group (p = 0.003), whereas plasma SOD levels were lower in the AD (p < 0.001) and aMCI (p = 0.045) groups than in NC, and GSH-Px activity were higher in the AD group than in the aMCI group (p = 0.007). In addition, lipid metabolites and oxidative stress are widely associated. In conclusion, this study distinguished serum lipid metabolism in AD, aMCI, and NC subjects, highlighting that the three SPHs can distinguish AD and aMCI from NC. Additionally, AD patients showed elevated oxidative stress, and there are complex interactions between lipid metabolites and oxidative stress.

The QPLEX™ Plus Assay Kit for the Early Clinical Diagnosis of Alzheimer's Disease

We recently developed a multiplex diagnostic kit, QPLEX™ Alz plus assay kit, which captures amyloid-β1-40, galectin-3 binding protein, angiotensin-converting enzyme, and periostin simultaneously using microliters of peripheral blood and utilizes an optimized algorithm for screening Alzheimer's disease (AD) by correlating with cerebral amyloid deposition. Owing to the demand for early AD detection, we investigate the potential of our kit for the early clinical diagnosis of AD. A total of 1395 participants were recruited, and their blood samples were analyzed with the QPLEX™ kit. The average of QPLEX™ algorithm values in each group increased gradually in the order of the clinical progression continuum of AD: cognitively normal (0.382 ± 0.150), subjective cognitive decline (0.452 ± 0.130), mild cognitive impairment (0.484 ± 0.129), and AD (0.513 ± 0.136). The algorithm values between each group showed statistically significant differences among groups divided by Mini-Mental State Examination and Clinical Dementia Rating. The QPLEX™ algorithm values could be used to distinguish the clinical continuum of AD or cognitive function. Because blood-based diagnosis is more accessible, convenient, and cost- and time-effective than cerebral spinal fluid or positron emission tomography imaging-based diagnosis, the QPLEX™ kit can potentially be used for health checkups and the early clinical diagnosis of AD.

A Comprehensive Investigation of the Potential Role of Lipoproteins and Metabolite Profile as Biomarkers of Alzheimer's Disease Compared to the Known CSF Biomarkers

Introduction

While cerebrospinal fluid (CSF) core biomarkers have been considered diagnostic biomarkers for a long time, special attention has been recently dedicated to lipoproteins and metabolites that could be potentially associated with Alzheimer's disease (AD) neurodegeneration. Herein, we aimed to investigate the relationship between the levels of CSF core biomarkers including Aβ-42, TAU, and P-TAU and plasma lipoproteins and metabolites of patients with AD from the baseline cohort of the Alzheimer's Disease Neuroimaging Initiative (ADNI) database.

Method

Using the ADNI database, fourteen subclasses of lipoproteins as well as a number of lipids and fatty acids and low-molecular metabolites including amino acids, ketone bodies, and glycolysis-related metabolites in blood samples were measured as potential noninvasive markers, and their association with the CSF core biomarkers was statistically investigated controlling for age and gender.

Results

A total number of 251 AD subjects were included, among whom 71 subjects were negative for the Apo-E ε4 allele and 150 were positive. There was no significant difference between the two groups regarding cognitive assessments, CSF core biomarkers, and lipoproteins and metabolites except the level of Aβ-42 (p < 0.001) and phenylalanine (p = 0.049), which were higher in the negative group. CSF TAU and P-TAU were significantly correlated with medium and small HDL in the negative group, and with extremely large VLDL in the positive group. Our results also indicated significant correlations of metabolites including unsaturated fatty acids, glycerol, and leucine with CSF core biomarkers.

Conclusion

Based on our findings, a number of lipoproteins and metabolites were associated with CSF core biomarkers of AD. These correlations showed some differences in Apo-E ε4 positive and negative groups, which reminds the role of Apo-E gene status in the pathophysiology of AD development. However, further research is warranted to explore the exact association of lipoproteins and other metabolites with AD core biomarkers and pathology.

Nutrients and amyloid β status in the brain: A narrative review

Amyloid beta (Aβ) is a peptide and a hallmark of Alzheimer's disease (AD). Emerging evidence suggests that Aβ levels could be influenced by diet. However, the evidence is sparse and for some nutrients, controversial. The aim of this narrative review is to gather the findings of observational and clinical trials involving human participants on the relationships between nutrients and brain Aβ status. Some dietary patterns are associated to reduced levels of Aβ in the brain, such as the Mediterranean diet, ketogenic diet as well as low intake of saturated fat, high-glycemic-index food, sodium, and junk/fast food. Low Aβ status in the brain was also associated with higher density lipoproteins (HDL) cholesterol and polyunsaturated fatty acids consumption. Data on alcohol intake is not conclusive. On the contrary, high Aβ levels in the brain were related to a higher intake of total cholesterol, triglycerides, low-density lipoproteins (LDL) cholesterol, saturated fat, sucrose, and fructose. Folic acid, cobalamin, vitamin E, and vitamin D were not associated to Aβ status, while high blood concentrations of Calcium, Aluminum, Zinc, Copper, and Manganese were associated with decreased Aβ blood levels but were not associated with Aβ cerebral spinal fluid (CSF) concentrations. In conclusion, certain dietary patterns and nutrients are associated to brain Aβ status. Further research on the association between nutrients and brain Aβ status is needed in order to pave the way to use nutritional interventions as efficacious strategies to prevent Aβ disturbance and potentially AD.

Emerging role of HDL in brain cholesterol metabolism and neurodegenerative disorders

High-density lipoproteins (HDLs play a key role in cholesterol homeostasis maintenance in the central nervous system (CNS), by carrying newly synthesized cholesterol from astrocytes to neurons, to support their lipid-related physiological functions. As occurs for plasma HDLs, brain lipoproteins are assembled through the activity of membrane cholesterol transporters, undergo remodeling mediated by specific enzymes and transport proteins, and finally deliver cholesterol to neurons by a receptor-mediated internalization process. A growing number of evidences indicates a strong association between alterations of CNS cholesterol homeostasis and neurodegenerative disorders, in particular Alzheimer's disease (AD), and a possible role in this relationship may be played by defects in brain HDL metabolism. In the present review, we summarize and critically examine the current state of knowledge on major modifications of HDL and HDL-mediated brain cholesterol transport in AD, by taking into consideration the individual steps of this process. We also describe potential and encouraging HDL-based therapies that could represent new therapeutic strategies for AD treatment. Finally, we revise the main plasma and brain HDL modifications in other neurodegenerative disorders including Parkinson's disease (PD), Huntington's disease (HD), and frontotemporal dementia (FTD).

Plasma neurofilament light chain is associated with cognitive decline in non-dementia older adults

Neurofilament light chain (NfL) has been associated with cognitive status in multiple neurodegenerative conditions. Studies about plasma NfL and cognitive decline in older adults are still limited. 504 older adults (median age 75 years) who expressed memory complaints were selected from the Multidomain Alzheimer's Preventive Trial (MAPT) and were classified as normal cognition (NC) or mild cognitive impairment (MCI). Cognitive functions were measured as mini mental state examination (MMSE) and composite cognitive score (CCS) over a 4-year period. Plasma NfL was measured at the first or the second year of the MAPT. Mixed-effects linear models were performed to evaluate cross-sectional and longitudinal associations. In the whole population, higher plasma NfL was cross-sectionally associated with lower cognitive functions (MMSE: β =  - 0.007, 95% CI [- 0.013, - 0.001]; CCS: β =  - 0.003, 95% CI [- 0.006, - 0.001]). In adults with MCI, but not NC, higher plasma NfL was associated with lower CCS at the cross-sectional level (β =  - 0.003, 95% CI [- 0.005, - 0.0002]). The upper quartile NfL group further demonstrated more over time decline in CCS (β =  - 0.07, 95% CI [- 0.12, - 0.01]) under the MCI status. Plasma NfL can be a promising biomarker of progressive cognition decline in older adults with MCI.

Plasma Lipids as Biomarkers for Alzheimer's Disease: A Systematic Review

Alzheimer's disease (AD) is caused by several risk factors leading to dementia. It's diagnosis usually depends on clinical presentation and certain biomarkers in the cerebrospinal fluid (CSF). The brain has a high content of cholesterol and the metabolism of cholesterol in the brain can be associated with beta-amyloid plaques formation, which is seen in Alzheimer's disease. Given these implications, we studied if plasma lipid levels can vary in Alzheimer's disease and if these can be used as biomarkers to diagnose and predict the progression of Alzheimer's disease. Certain mutations in the brain cholesterol transport receptors and proteins and their association with Alzheimer's were also studied. This systematic review abides by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We searched multiple databases, such as Pubmed, Google Scholar, Pubmed central, ScienceDirect, Web of Science, and Medline with the help of keywords like Alzheimer's disease, cognitive impairment, plasma lipid biomarkers, cholesterol, brain cholesterol metabolism separately and in combination with each other. We collected 49 quality appraised articles on the association between plasma lipids and Alzheimer's disease and the genetic mutations in alleles related to cholesterol metabolism and Alzheimer's disease by applying the inclusion and exclusion criteria. Based on the finding of the studies reviewed, we found an association between plasma lipids, polymorphisms in genes associated with cholesterol transport, and Alzheimer's disease. Increased serum low-density lipoprotein (LDL-C), triglycerides (TG), total cholesterol (TC), sphingolipids, 24S hydroxycholesterol (24S-HC), 27O hydroxycholesterol (27O-HC) was associated with Alzheimer's. Decreased high-density lipoprotein (HDL-C) and phospholipids were noticed. Genetic mutations in apolipoprotein E (ApoE), apolipoprotein B (ApoB), apolipoprotein A (ApoA), ATP binding cassette transporter 1 (ABCA1), ATP binding cassette transporter 7 (ABCA7), amyloid precursor protein (APP), cytochrome P450 family 46 subfamilies A member 1 (CYP46A1), presenilin 1 (PSEN1), presenilin 2 (PSEN2) are also associated with increased risk of Alzheimer's disease. This study found an association between plasma lipids and Alzheimer's, proving that plasma lipids can be used as biomarkers for early diagnosis of Alzheimer's disease. It may also help predict the prognosis and stage the disease severity. Further studies are needed to find out the exact mechanism behind these changes.