Dairy Milk Casein and Whey Proteins Differentially Alter the Postprandial Lipidome in Persons with Prediabetes: A Comparative Lipidomics Study

Hypercholesterolemia drives microglial dysfunction and weakens response to amyloid plaques

Hypercholesterolemia is a recognized comorbidity of Alzheimer's disease (AD), yet its mechanistic connection to AD pathology, particularly its impact on microglial function and amyloid-beta (Aβ) dynamics remains unclear. To investigate this, we utilized the APPNL-G-F (AK) mouse model, which develops robust Aβ pathology, and the APPNL-G-F;LDLR-/- (ALKO) model, which combines Aβ pathology with LDL receptor deficiency to induce hypercholesterolemia under a Western diet (WD). These models were designed to study the combined effects of genetic predisposition and dietary factors on AD progression. At six months of age, mice were maintained on a control diet or switched to a WD for two months to induce hypercholesterolemia. Our findings demonstrate that hypercholesterolemia suppresses microglial responses to Aβ plaques, evidenced by reduced clustering and activation of microglia around plaques. The combination of WD and LDLR deficiency synergistically diminished the expression of disease-associated microglia markers, resulting in reduced Aβ plaque compactness. Mechanistically, RNA sequencing revealed hypercholesterolemia impaired microglial mitochondrial function, reduced protein synthesis, and heightened neuroinflammation. Lipidomic profiling revealed significant changes in the microglial lipidome, including elevated ceramides, hexosylceramides, and lysophosphatidylcholine, along with reduced N-acylethanolamines, reflecting a pro-inflammatory and metabolically stressed microglial state. Behavioral analyses further revealed that both WD and LDLR deficiency independently and synergistically impaired cognitive performance and increased anxiety-like behaviors in AD mice. Together, this study highlights the role of hypercholesterolemia in exacerbating AD pathology by disrupting microglial function, altering lipid metabolism, and impairing cognitive function, and suggests that pharmacological management of hypercholesterolemia could slow AD progression.

Mapping pesticide-induced metabolic alterations in human gut bacteria

Pesticides can modulate gut microbiota composition, but their specific effects on it remain largely elusive. In our study, we show that pesticides inhibit or promote the growth of various gut microbial species and can be accumulated to prolong their presence in the host. Pesticide exposure also induces significant alterations in gut bacterial metabolism, as reflected by changes in hundreds of metabolites. We generate a pesticide-gut microbiota-metabolite network that not only reveals pesticide-sensitive gut bacteria species but also reports specific metabolic changes in 306 pesticide-gut microbiota pairs. Using an in vivo mouse model, we further demonstrate the interactions of a representative pesticide-gut microbiota pair and verify the inflammation-inducing effects of pesticide exposure on the host, mediated by microbially dysregulated lipid metabolism. Taken together, our findings generate a comprehensive atlas of pesticide-gut microbiota-metabolite interactions atlas and shed light on the molecular mechanisms by which pesticides affect host health via gut microbiota-modulated metabolism.

Mapping Pesticide-Induced Metabolic Alterations in Human Gut Bacteria

Pesticides can modulate gut microbiota (GM) composition, but their specific effects on GM remain largely elusive. Our study demonstrated that pesticides inhibit or promote growth in various GM species, even at low concentrations, and can accumulate in GM to prolong their presence in the host. Meanwhile, the pesticide induced changes in GM composition are associated with significant alterations in gut bacterial metabolism that reflected by the changes of hundreds of metabolites. We generated a pesticide-GM-metabolites (PMM) network that not only reveals pesticide-sensitive gut bacteria species but also report specific metabolic changes in 306 pesticide-GM pairs (PGPs). Using an in vivo mice model, we further demonstrated a PGP's interactions and verified the inflammation-inducing effects of pesticides on the host through dysregulated lipid metabolism of microbes. Taken together, our findings generate a PMM interactions atlas, and shed light on the molecular level of how pesticides impact host health by modulating GM metabolism.

Arachidonic Acid Mobilization and Peroxidation Promote Microglial Dysfunction in Aβ Pathology

Aberrant increase of arachidonic acid (ARA) has long been implicated in the pathology of Alzheimer's disease (AD), while the underlying causal mechanism remains unclear. In this study, we revealed a link between ARA mobilization and microglial dysfunction in Aβ pathology. Lipidomic analysis of primary microglia from AppNL-GF mice showed a marked increase in free ARA and lysophospholipids (LPLs) along with a decrease in ARA-containing phospholipids, suggesting increased ARA release from phospholipids (PLs). To manipulate ARA-containing PLs in microglia, we genetically deleted lysophosphatidylcholine acyltransferase 3 (Lpcat3), the main enzyme catalyzing the incorporation of ARA into PLs. Loss of microglial Lpcat3 reduced the levels of ARA-containing PLs, free ARA and LPLs, leading to a compensatory increase in monounsaturated fatty acid (MUFA)-containing PLs in both male and female App NL-GF mice. Notably, the reduction of ARA in microglia significantly ameliorated oxidative stress and inflammatory responses while enhancing the phagocytosis of Aβ plaques and promoting the compaction of Aβ deposits. Mechanistically, scRNA seq suggested that LPCAT3 deficiency facilitates phagocytosis by facilitating de novo lipid synthesis while protecting microglia from oxidative damage. Collectively, our study reveals a novel mechanistic link between ARA mobilization and microglial dysfunction in AD. Lowering brain ARA levels through pharmacological or dietary interventions may be a potential therapeutic strategy to slow down AD progression.

Lipidome isotope labelling of gut microbes (LILGM): A method of discovering endogenous microbial lipids

Lipidomics analysis of gut microbiome has become critical in recent surge of extensive human disease studies that investigate microbiome contributions. However, challenges remain in comprehending the origins of thousands of lipid species produced by the diverse microbes. Here, we proposed the development and utilization of a liquid chromatography-mass spectrometry-based approach, named lipidome isotope labelling of gut microbes (LILGM), which enables confident detection and identification of endogenous gut microbial lipidome via 13C/15N labeling strategy and high-resolution mass spectrometry. Our method leveraged in vitro microbial cultures and stable isotope-labeled 13C and 15N, allowing a reasonable degree of isotope incorporation into microbial lipids over short-term of inoculation. We then systematically detected the mass spectral patterns of 182 labeled lipid species by our in-house data analysis pipeline. Further bioinformatics analyses confidently identified biologically relevant microbial lipids from lipid classes such as diacylglycerols (DGs), fatty acids (FAs), phosphatidylglycerols (PGs), and phosphatidylethanolamines (PEs) that may have profound impacts to human physiology. Our study also demonstrated the application of LILGM by showcasing the confident detection of dysregulated microbial lipids post antibiotic perturbation. The debiased sparse partial correlation analysis provides insights into lipid metabolism intricacies. Overall, our method can provide unambiguous analyses to the endogenous microbial lipids in given biological context, and can also instantly reflect the lipidomic changes of gut microbes in response to environmental factors. We believe our LILGM approach has the potential to provide new body of knowledge by combining promising analytical approaches for sensitive and specific lipid detection to support functional microbiome studies.

Chewing the fat: How lipidomics is changing our understanding of human health and disease in 2022

Lipids are biological molecules that play vital roles in all living organisms. They perform many cellular functions, such as 1) forming cellular and subcellular membranes, 2) storing and using energy, and 3) serving as chemical messengers during intra- and inter-cellular signal transduction. The large-scale study of the pathways and networks of cellular lipids in biological systems is called "lipidomics" and is one of the fastest-growing omics technologies of the last two decades. With state-of-the-art mass spectrometry instrumentation and sophisticated data handling, clinical studies show how human lipid composition changes in health and disease, thereby making it a valuable medium to collect for clinical applications, such as disease diagnostics, therapeutic decision-making, and drug development. This review gives a comprehensive overview of current workflows used in clinical research, from sample collection and preparation to data and clinical interpretations. This is followed by an appraisal of applications in 2022 and a perspective on the exciting future of clinical lipidomics.

Dairy product consumption and incident prediabetes in the Australian Diabetes, Obesity and Lifestyle Study with 12 years follow up

BACKGROUND

Investigating modifiable risk factors of early stages of the development of type 2 diabetes is essential for effective prevention. Some studies show protective associations between dairy and prediabetes, yet associations are heterogenous by type and fat content of dairy foods.

OBJECTIVE

To examine the relationship between the consumption of dairy, including different types of dairy products and the risk of prediabetes.

METHODS

The study included 4,891 participants with normal glucose tolerance (aged 49.0±12.3 years, 57% female) of the Australian Diabetes, Obesity and Lifestyle (AusDiab) study, a longitudinal population-based study. Dairy intake was measured at baseline using a food frequency questionnaire. Prediabetes at 5-year and 12-year follow-up was defined according to WHO criteria as fasting plasma glucose levels of 110-125 mg/dl or 2-hour plasma glucose levels of 140-199 mg/dl. Associations were analyzed using Poisson regression, adjusted for social demographics, lifestyle behaviors, family history of diabetes, and food group intake.

RESULTS

765 (15.6%) incident cases of prediabetes were observed. The mean intake of dairy foods was 2.4±1.2 servings/day, mostly consisting of low-fat milk (0.70±0.78) and high-fat milk (0.47±0.72). A higher intake of high-fat dairy (RR_servings/day, 0.92, 95%CI 0.85-1.00), high-fat milk (0.89, 0.80-0.99), and total cheese (0.74, 0.56-0.96)was associated with lower prediabetes risk. Low-fat milk intake was associated non-linearly with prediabetes risk. Low-fat dairy foods, total milk, yogurt, low-fat cheese, and ice cream were not associated with prediabetes risk.

CONCLUSION

In this large Australian cohort, protective associations were found for high-fat dairy types, while neutral associations were seen for low-fat dairy. Studies with more detail on sugar content of types of dairy foods and products eaten with dairy foods (e.g., cereals or jam), as well as studies into potential causal mechanisms of the health effects of dairy intake are required.