The Role of Clinical Proteomics, Lipidomics, and Genomics in the Diagnosis of Alzheimer's Disease

Alzheimer's Disease in Diabetic Patients: A Lipidomic Prospect

Diabetes Mellitus (DM) and Alzheimer's disease (AD) have been two of the most common chronic diseases affecting people worldwide. Type 2 DM (T2DM) is a metabolic disease depicted by insulin resistance, dyslipidemia, and chronic hyperglycemia while AD is a neurodegenerative disease marked by Amyloid β (Aβ) accumulation, neurofibrillary tangles aggregation, and tau phosphorylation. Various clinical, epidemiological, and lipidomics studies have linked those diseases claiming shared pathological pathways raising the assumption that diabetic patients are at an increased risk of developing AD later in their lives. Insulin resistance is the tipping point beyond where advanced glycation end (AGE) products and free radicals are produced leading to oxidative stress and lipid peroxidation. Additionally, different types of lipids are playing a crucial role in the development and the relationship between those diseases. Lipidomics, an analysis of lipid structure, formation, and interactions, evidently exhibits these lipid changes and their direct and indirect effect on Aβ synthesis, insulin resistance, oxidative stress, and neuroinflammation. In this review, we have discussed the pathophysiology of T2DM and AD, the interconnecting pathological pathways they share, and the lipidomics where different lipids such as cholesterol, phospholipids, sphingolipids, and sulfolipids contribute to the underlying features of both diseases. Understanding their role can be beneficial for diagnostic purposes or introducing new drugs to counter AD.

A Potential Link Between Visceral Obesity and Risk of Alzheimer's Disease

Alzheimer's disease (AD) is the most common type of dementia characterized by the deposition of amyloid beta (Aβ) plaques and tau-neurofibrillary tangles in the brain. Visceral obesity (VO) is usually associated with low-grade inflammation due to higher expression of pro-inflammatory cytokines by adipose tissue. The objective of the present review was to evaluate the potential link between VO and the development of AD. Tissue hypoxia in obesity promotes tissue injury, production of adipocytokines, and release of pro-inflammatory cytokines leading to an oxidative-inflammatory loop with induction of insulin resistance. Importantly, brain insulin signaling is involved in the pathogenesis of AD and lower cognitive function. Obesity and enlargement of visceral adipose tissue are associated with the deposition of Aβ. All of this is consonant with VO increasing the risk of AD through the dysregulation of adipocytokines which affect the development of AD. The activated nuclear factor kappa B (NF-κB) pathway in VO might be a potential link in the development of AD. Likewise, the higher concentration of advanced glycation end-products in VO could be implicated in the pathogenesis of AD. Taken together, different inflammatory signaling pathways are activated in VO that all have a negative impact on the cognitive function and progression of AD except hypoxia-inducible factor 1 which has beneficial and neuroprotective effects in mitigating the progression of AD. In addition, VO-mediated hypoadiponectinemia and leptin resistance may promote the progression of Aβ formation and tau phosphorylation with the development of AD. In conclusion, VO-induced AD is mainly mediated through the induction of oxidative stress, inflammatory changes, leptin resistance, and hypoadiponectinemia that collectively trigger Aβ formation and neuroinflammation. Thus, early recognition of VO by visceral adiposity index with appropriate management could be a preventive measure against the development of AD in patients with VO.

Lipidomics and proteomics: An integrative approach for early diagnosis of dementia and Alzheimer's disease

Alzheimer's disease (AD) is the most common neurodegenerative disorder and considered to be responsible for majority of worldwide prevalent dementia cases. The number of patients suffering from dementia are estimated to increase up to 115.4 million cases worldwide in 2050. Hence, AD is contemplated to be one of the major healthcare challenge in current era. This disorder is characterized by impairment in various signaling molecules at cellular and nuclear level including aggregation of Aβ protein, tau hyper phosphorylation altered lipid metabolism, metabolites dysregulation, protein intensity alteration etc. Being heterogeneous and multifactorial in nature, the disease do not has any cure or any confirmed diagnosis before the onset of clinical manifestations. Hence, there is a requisite for early diagnosis of AD in order to downturn the progression/risk of the disorder and utilization of newer technologies developed in this field are aimed to provide an extraordinary assistance towards the same. The lipidomics and proteomics constitute large scale study of cellular lipids and proteomes in biological matrices at normal stage or any stage of a disease. The study involves high throughput quantification and detection techniques such as mass spectrometry, liquid chromatography, nuclear mass resonance spectroscopy, fluorescence spectroscopy etc. The early detection of altered levels of lipids and proteins in blood or any other biological matrices could aid in preventing the progression of AD and dementia. Therefore, the present review is designed to focus on the recent techniques and early diagnostic criteria for AD, revealing the role of lipids and proteins in this disease and their assessment through different techniques.

Precision medicine journey through omics approach

It has been well established that understanding the underlying heterogeneity of numerous complex disease process needs new strategies that present in precision medicine for prediction, prevention and personalized treatment strategies. This approach must be tailored for each individual's unique omics that lead to personalized management of disease. The correlation between different omics data should be considered in precision medicine approach. The interaction provides a hypothesis which is called domino effect in the present minireview. Here we review the various potentials of omics data including genomics, transcriptomics, proteomics, metabolomics, pharmacogenomics. We comprehensively summarize the impact of omics data and its major role in precision medicine and provide a description about the domino effect on the pathophysiology of diseases. Each constituent of the omics data typically provides different information in associated with disease. Current research, although inadequate, clearly indicate that the information of omics data can be applicable in the concept of precision medicine. Integration of different omics data type in domino effect hypothesis can explain the causative changes of disease as it is discussed in the system biology too. While most existing studies investigate the omics data separately, data integration is needed on the horizon of precision medicine by using machine learning.

HSPA12A targets the cytoplasmic domain and affects the trafficking of the Amyloid Precursor Protein receptor SorLA

SorLA and Sortilin are multifunctional receptors involved in endocytosis and intracellular sorting of different and unrelated ligands. SorLA has recently attracted much attention as a novel strong risk gene for Alzheimer’s disease, and much effort is currently being put into understanding the underlying molecular mechanism. Trafficking of SorLA and Sortilin are mediated by interacting with AP-1, AP-2, GGA 1-3 and the retromer complex. Although these cytosolic adaptor proteins all bind to both SorLA and Sortilin, a large fraction of intracellular Sortilin and SorLA are located in different subcellular vesicles. This indicates that unknown specialised adaptor proteins targeting SorLA for trafficking are yet to be discovered. We have identified HSPA12A as a new adaptor protein that, among Vps10p-D receptors, selectively binds to SorLA in an ADP/ATP dependent manner. This is the first described substrate of HSPA12A, and we demonstrate that the binding, which affects both endocytic speed and subcellular localisation of SorLA, is mediated by specific acidic residues in the cytosolic domain of SorLA. The identification of the relatively unknown HSPA12A as a SorLA specific interaction partner could lead to novel insight into the molecular mechanism of SorLA, and re-emphasises the role of heat shock proteins in neurodegenerative diseases.

Imaging and Molecular Mechanisms of Alzheimer's Disease: A Review

Alzheimer's disease is the most common form of dementia and is a significant burden for affected patients, carers, and health systems. Great advances have been made in understanding its pathophysiology, to a point that we are moving from a purely clinical diagnosis to a biological one based on the use of biomarkers. Among those, imaging biomarkers are invaluable in Alzheimer's, as they provide an in vivo window to the pathological processes occurring in Alzheimer's brain. While some imaging techniques are still under evaluation in the research setting, some have reached widespread clinical use. In this review, we provide an overview of the most commonly used imaging biomarkers in Alzheimer's disease, from molecular PET imaging to structural MRI, emphasising the concept that multimodal imaging would likely prove to be the optimal tool in the future of Alzheimer's research and clinical practice.

Integrated Proteomics and Lipidomics Investigation of the Mechanism Underlying the Neuroprotective Effect of N-benzylhexadecanamide

Macamides are very important secondary metabolites produced by Lepidium meyenii Walp, which possess multiple bioactivities, especially in the neuronal system. In a previous study, we observed that macamides exhibited excellent effects in the recovery of injured nerves after 1-methyl-4-phenylpyridinium (MPP⁺)-induced dopaminergic neuronal damage in zebrafish. However, the mechanism underlying this effect remains unclear. In the present study, we observed that N-benzylhexadecanamide (XA), which is a typical constituent of macamides, improved the survival rate of neurons in vitro. We determined the concentration of neurotransmitters in MN9D cells and used it in conjunction with an integrated proteomics and lipidomics approach to investigate the mechanism underlying the neuroprotective effects of XA in an MPP⁺-induced neurodegeneration cell model using QqQ MS, Q-TOF MS, and Orbitrap MS. The statistical analysis of the results led to the identification of differentially-expressed biomarkers, including 11 proteins and 22 lipids, which may be responsible for the neuron-related activities of XA. All these potential biomarkers were closely related to the pathogenesis of neurodegenerative diseases, and their levels approached those in the normal group after treatment with XA. Furthermore, seven lipids, including five phosphatidylcholines, one lysophosphatidylcholine, and one phosphatidylethanolamine, were verified by a relative quantitative approach. Moreover, four proteins (Scarb2, Csnk2a2, Vti1b, and Bnip2) were validated by ELISA. The neurotransmitters taurine and norepinephrine, and the cholinergic constituents, correlated closely with the neuroprotective effects of XA. Finally, the protein–lipid interaction network was analyzed. Based on our results, the regulation of sphingolipid metabolism and mitochondrial function were determined to be the main mechanisms underlying the neuroprotective effect of XA. The present study should help us to better understand the multiple effects of macamides and their use in neurodegenerative diseases.

Mass-spectrometry-based lipidomics

Lipids, which have a core function in energy storage, signalling and biofilm structures, play important roles in a variety of cellular processes because of the great diversity of their structural and physiochemical properties. Lipidomics is the large-scale profiling and quantification of biogenic lipid molecules, the comprehensive study of their pathways and the interpretation of their physiological significance based on analytical chemistry and statistical analysis. Lipidomics will not only provide insight into the physiological functions of lipid molecules but will also provide an approach to discovering important biomarkers for diagnosis or treatment of human diseases. Mass-spectrometry-based analytical techniques are currently the most widely used and most effective tools for lipid profiling and quantification. In this review, the field of mass-spectrometry-based lipidomics was discussed. Recent progress in all essential steps in lipidomics was carefully discussed in this review, including lipid extraction strategies, separation techniques and mass-spectrometry-based analytical and quantitative methods in lipidomics. We also focused on novel resolution strategies for difficult problems in determining C=C bond positions in lipidomics. Finally, new technologies that were developed in recent years including single-cell lipidomics, flux-based lipidomics and multiomics technologies were also reviewed.

Clinical Proteomics: From Biological Sample to Clinical Exploitation

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