Metabolome-wide association study on ABCA7 indicates a role of ceramide metabolism in Alzheimer's disease

Harnessing Artificial Intelligence in Multimodal Omics Data Integration: Paving the Path for the Next Frontier in Precision Medicine

The integration of multiomics data with detailed phenotypic insights from electronic health records marks a paradigm shift in biomedical research, offering unparalleled holistic views into health and disease pathways. This review delineates the current landscape of multimodal omics data integration, emphasizing its transformative potential in generating a comprehensive understanding of complex biological systems. We explore robust methodologies for data integration, ranging from concatenation-based to transformation-based and network-based strategies, designed to harness the intricate nuances of diverse data types. Our discussion extends from incorporating large-scale population biobanks to dissecting high-dimensional omics layers at the single-cell level. The review underscores the emerging role of large language models in artificial intelligence, anticipating their influence as a near-future pivot in data integration approaches. Highlighting both achievements and hurdles, we advocate for a concerted effort toward sophisticated integration models, fortifying the foundation for groundbreaking discoveries in precision medicine.

Multiple Roles of Apolipoprotein E4 in Oxidative Lipid Metabolism and Ferroptosis During the Pathogenesis of Alzheimer's Disease

Alzheimer's disease (AD) is the most prevalent neurodegenerative disease worldwide and has a great socio-economic impact. Modified oxidative lipid metabolism and dysregulated iron homeostasis have been implicated in the pathogenesis of this disorder, but the detailed pathophysiological mechanisms still remain unclear. Apolipoprotein E (APOE) is a lipid-binding protein that occurs in large quantities in human blood plasma, and a polymorphism of the APOE gene locus has been identified as risk factors for AD. The human genome involves three major APOE alleles (APOE2, APOE3, APOE4), which encode for three subtly distinct apolipoprotein E isoforms (APOE2, APOE3, APOE4). The canonic function of these apolipoproteins is lipid transport in blood and brain, but APOE4 allele carriers have a much higher risk for AD. In fact, about 60% of clinically diagnosed AD patients carry at least one APOE4 allele in their genomes. Although the APOE4 protein has been implicated in pathophysiological key processes of AD, such as extracellular beta-amyloid (Aβ) aggregation, mitochondrial dysfunction, neuroinflammation, formation of neurofibrillary tangles, modified oxidative lipid metabolism, and ferroptotic cell death, the underlying molecular mechanisms are still not well understood. As for all mammalian cells, iron plays a crucial role in neuronal functions and dysregulation of iron homeostasis has also been implicated in the pathogenesis of AD. Imbalances in iron homeostasis and impairment of the hydroperoxy lipid-reducing capacity induce cellular dysfunction leading to neuronal ferroptosis. In this review, we summarize the current knowledge on APOE4-related oxidative lipid metabolism and the potential role of ferroptosis in the pathogenesis of AD. Pharmacological interference with these processes might offer innovative strategies for therapeutic interventions.

Mass spectrometry imaging highlights dynamic patterns of lipid co-expression with Aβ plaques in mouse and human brains

Lipids play crucial roles in the susceptibility and brain cellular responses to Alzheimer's disease (AD) and are increasingly considered potential soluble biomarkers in cerebrospinal fluid (CSF) and plasma. To delineate the pathological correlations of distinct lipid species, we conducted a comprehensive characterization of both spatially localized and global differences in brain lipid composition in AppNL-G-F mice with spatial and bulk mass spectrometry lipidomic profiling, using human amyloid-expressing (h-Aβ) and WT mouse brains controls. We observed age-dependent increases in lysophospholipids, bis(monoacylglycerol) phosphates, and phosphatidylglycerols around Aβ plaques in AppNL-G-F mice. Immunohistology-based co-localization identified associations between focal pro-inflammatory lipids, glial activation, and autophagic flux disruption. Likewise, in human donors with varying Braak stages, similar studies of cortical sections revealed co-expression of lysophospholipids and ceramides around Aβ plaques in AD (Braak stage V/VI) but not in earlier Braak stage controls. Our findings in mice provide evidence of temporally and spatially heterogeneous differences in lipid composition as local and global Aβ-related pathologies evolve. Observing similar lipidomic changes associated with pathological Aβ plaques in human AD tissue provides a foundation for understanding differences in CSF lipids with reported clinical stage or disease severity.

Circulating sphingolipids in relation to cognitive decline and incident dementia: The Cardiovascular Health Study

INTRODUCTION

Whether circulating levels of sphingolipids are prospectively associated with cognitive decline and dementia risk is uncertain.

METHODS

We measured 14 sphingolipid species in plasma samples from 4488 participants (mean age 76.2 years; 40% male; and 25% apolipoprotein E (APOE) ε4 allele carriers). Cognitive decline was assessed annually across 6 years using modified Mini-Mental State Examination (3MSE) and Digital Symbol Substitution Test (DSST). Additionally, a subset of 3050 participants were followed for clinically adjudicated dementia.

RESULTS

Higher plasma levels of sphingomyelin-d18:1/16:0 (SM-16) were associated with a faster cognitive decline measured with 3MSE, in contrast, higher levels of sphingomyelin-d18:1/22:0 (SM-22) were associated with slower decline in cognition measured with DSST. In Cox regression, higher levels of SM-16 (hazard ration [HR] = 1.24 [95% confidence interval [CI]: 1.08-1.44]) and ceramide-d18:1/16:0 (Cer-16) (HR = 1.26 [95% CI: 1.10-1.45]) were associated with higher risk of incident dementia.

DISCUSSION

Several sphingolipid species appear to be involved in cognitive decline and dementia risk.

Highlights

Plasma levels of sphingolipids were associated with cognitive decline and dementia risk.Ceramides and sphingomyelins with palmitic acid were associated with faster annual cognitive decline and increased risk of dementia.The direction of association depended on the covalently bound saturated fatty acid chain length in analysis of cognitive decline.

Microglial response to aging and neuroinflammation in the development of neurodegenerative diseases

ABSTRACT

Cellular senescence and chronic inflammation in response to aging are considered to be indicators of brain aging; they have a great impact on the aging process and are the main risk factors for neurodegeneration. Reviewing the microglial response to aging and neuroinflammation in neurodegenerative diseases will help understand the importance of microglia in neurodegenerative diseases. This review describes the origin and function of microglia and focuses on the role of different states of the microglial response to aging and chronic inflammation on the occurrence and development of neurodegenerative diseases, including Alzheimer's disease, Huntington's chorea, and Parkinson's disease. This review also describes the potential benefits of treating neurodegenerative diseases by modulating changes in microglial states. Therefore, inducing a shift from the neurotoxic to neuroprotective microglial state in neurodegenerative diseases induced by aging and chronic inflammation holds promise for the treatment of neurodegenerative diseases in the future.

Relationship Between Sphingomyelin and Risk of Alzheimer's Disease: A Bidirectional Mendelian Randomization Study

Background

Alzheimer's disease (AD) is a complex neurodegenerative disorder whose etiology involves multiple genetic and environmental factors. Sphingomyelin (SM) is a type of sphingolipid found in cell membranes, and recent evidence suggests a potential link between SM and AD. However, the nature of this relationship remains unclear.

Objective

To elucidate the potential causal relationship between SM levels and the risk of developing AD using a two-sample Mendelian randomization approach.

Methods

The study utilized data extracted from the genome wide association study database. The primary analysis method was the inverse variance weighted (IVW) method, which was supplemented by weighted median, weighted mode, and MR Egger methods. The study specifically investigated the bidirectional causal relationship between SM and AD, evaluating odds ratios (OR) with a 95% confidence interval (95% CI).

Results

Elevated levels of SM were found to be a risk factor for AD, as shown by IVW(MRE) [OR: 1.001, 95% CI: 1.000 to 1.002; p = 0.020 < 0.05], IVW(FE) [OR: 1.001, 95% CI: 1.001 to 1.002; p = 3.36e-07 < 0.05], and MR Egger. Conversely, AD was demonstrated to lead to an increase in SM levels [IVW(MRE): OR: 5.64e+08, 95% CI: 1.69e+05 to 1.89e+12; p = 1.14e-06 < 0.05], with consistent findings across the IVW(FE), MR Egger, weighted median, and weighted mode methods.

Conclusions

The study establishes a bidirectional positive correlation between SM and AD. Increased SM levels are associated with a higher risk of developing AD, and the presence of AD can further elevate SM levels, potentially exacerbating the disease's progression.

Alzheimer's genes in microglia: a risk worth investigating

Despite expressing many key risk genes, the role of microglia in late-onset Alzheimer's disease pathophysiology is somewhat ambiguous, with various phenotypes reported to be either harmful or protective. Herein, we review some key findings from clinical and animal model investigations, discussing the role of microglial genetics in mediating perturbations from homeostasis. We note that impairment to protective phenotypes may include prolonged or insufficient microglial activation, resulting in dysregulated metabolomic (notably lipid-related) processes, compounded by age-related inflexibility in dynamic responses. Insufficiencies of mouse genetics and aggressive transgenic modelling imply severe limitations in applying current methodologies for aetiological investigations. Despite the shortcomings, widely used amyloidosis and tauopathy models of the disease have proven invaluable in dissecting microglial functional responses to AD pathophysiology. Some recent advances have brought modelling tools closer to human genetics, increasing the validity of both aetiological and translational endeavours.

A Multiplexed Urinary Biomarker Panel Has Potential for Alzheimer's Disease Diagnosis Using Targeted Proteomics and Machine Learning

As disease-modifying therapies are now available for Alzheimer's disease (AD), accessible, accurate and affordable biomarkers to support diagnosis are urgently needed. We sought to develop a mass spectrometry-based urine test as a high-throughput screening tool for diagnosing AD. We collected urine from a discovery cohort (n = 11) of well-characterised individuals with AD (n = 6) and their asymptomatic, CSF biomarker-negative study partners (n = 5) and used untargeted proteomics for biomarker discovery. Protein biomarkers identified were taken forward to develop a high-throughput, multiplexed and targeted proteomic assay which was tested on an independent cohort (n = 21). The panel of proteins identified are known to be involved in AD pathogenesis. In comparing AD and controls, a panel of proteins including MIEN1, TNFB, VCAM1, REG1B and ABCA7 had a classification accuracy of 86%. These proteins have been previously implicated in AD pathogenesis. This suggests that urine-targeted mass spectrometry has potential utility as a diagnostic screening tool in AD.

Integrative metabolomics science in Alzheimer's disease: Relevance and future perspectives

Alzheimer's disease (AD) is determined by various pathophysiological mechanisms starting 10-25 years before the onset of clinical symptoms. As multiple functionally interconnected molecular/cellular pathways appear disrupted in AD, the exploitation of high-throughput unbiased omics sciences is critical to elucidating the precise pathogenesis of AD. Among different omics, metabolomics is a fast-growing discipline allowing for the simultaneous detection and quantification of hundreds/thousands of perturbed metabolites in tissues or biofluids, reproducing the fluctuations of multiple networks affected by a disease. Here, we seek to critically depict the main metabolomics methodologies with the aim of identifying new potential AD biomarkers and further elucidating AD pathophysiological mechanisms. From a systems biology perspective, as metabolic alterations can occur before the development of clinical signs, metabolomics - coupled with existing accessible biomarkers used for AD screening and diagnosis - can support early disease diagnosis and help develop individualized treatment plans. Presently, the majority of metabolomic analyses emphasized that lipid metabolism is the most consistently altered pathway in AD pathogenesis. The possibility that metabolomics may reveal crucial steps in AD pathogenesis is undermined by the difficulty in discriminating between the causal or epiphenomenal or compensatory nature of metabolic findings.

Moving beyond amyloid and tau to capture the biological heterogeneity of Alzheimer's disease

Alzheimer's disease (AD) manifests along a spectrum of cognitive deficits and levels of neuropathology. Genetic studies support a heterogeneous disease mechanism, with around 70 associated loci to date, implicating several biological processes that mediate risk for AD. Despite this heterogeneity, most experimental systems for testing new therapeutics are not designed to capture the genetically complex drivers of AD risk. In this review, we first provide an overview of those aspects of AD that are largely stereotyped and those that are heterogeneous, and we review the evidence supporting the concept that different subtypes of AD are important to consider in the design of agents for the prevention and treatment of the disease. We then dive into the multifaceted biological domains implicated to date in AD risk, highlighting studies of the diverse genetic drivers of disease. Finally, we explore recent efforts to identify biological subtypes of AD, with an emphasis on the experimental systems and data sets available to support progress in this area.

Status of Metabolomic Measurement for Insights in Alzheimer's Disease Progression-What Is Missing?

Alzheimer's disease (AD) is an aging-related neurodegenerative disease, leading to the progressive loss of memory and other cognitive functions. As there is still no cure for AD, the growth in the number of susceptible individuals represents a major emerging threat to public health. Currently, the pathogenesis and etiology of AD remain poorly understood, while no efficient treatments are available to slow down the degenerative effects of AD. Metabolomics allows the study of biochemical alterations in pathological processes which may be involved in AD progression and to discover new therapeutic targets. In this review, we summarized and analyzed the results from studies on metabolomics analysis performed in biological samples of AD subjects and AD animal models. Then this information was analyzed by using MetaboAnalyst to find the disturbed pathways among different sample types in human and animal models at different disease stages. We discuss the underlying biochemical mechanisms involved, and the extent to which they could impact the specific hallmarks of AD. Then we identify gaps and challenges and provide recommendations for future metabolomics approaches to better understand AD pathogenesis.

Cerebral Gray and White Matter Monogalactosyl Diglyceride Levels Rise with the Progression of Alzheimer's Disease

BACKGROUND

Multiple studies have reported brain lipidomic abnormalities in Alzheimer's disease (AD) that affect glycerophospholipids, sphingolipids, and fatty acids. However, there is no consensus regarding the nature of these abnormalities, and it is unclear if they relate to disease progression.

OBJECTIVE

Monogalactosyl diglycerides (MGDGs) are a class of lipids which have been recently detected in the human brain. We sought to measure their levels in postmortem human brain and determine if these levels correlate with the progression of the AD-related traits.

METHODS

We measured MGDGs by ultrahigh performance liquid chromatography tandem mass spectrometry in postmortem dorsolateral prefrontal cortex gray matter and subcortical corona radiata white matter samples derived from three cohorts of participants: the Framingham Heart Study, the Boston University Alzheimer's Disease Research Center, and the Arizona Study of Aging and Neurodegenerative Disorders/Brain and Body Donation Program (total n = 288).

RESULTS

We detected 40 molecular species of MGDGs (including diacyl and alkyl/acyl compounds) and found that the levels of 29 of them, as well as total MGDG levels, are positively associated with AD-related traits including pathologically confirmed AD diagnosis, clinical dementia rating, Braak and Braak stage, neuritic plaque score, phospho-Tau AT8 immunostaining density, levels of phospho-Tau396 and levels of Aβ40. Increased MGDG levels were present in both gray and white matter, indicating that they are widespread and likely associated with myelin-producing oligodendrocytes-the principal cell type of white matter.

CONCLUSIONS

Our data implicate the MGDG metabolic defect as a central correlate of clinical and pathological progression in AD.