Xianlin Han

The apolipoprotein E ( APOE ) gene is the strongest genetic risk factor for Alzheimer’s disease (AD), influencing amyloid-β (Aβ) aggregation, clearance, and glial function. While APOE4 promotes Aβ pathology and APOE2 is protective, how these opposing alleles interact in the heterozygous APOE2/4 state remains unknown. Here, using littermate-controlled heterozygous APOE mice ( APOE2/3 , APOE3/4 , and APOE2/4 ) alongside APOE3/3 controls crossed with 5xFAD mice, we show that APOE3/4 mice exhibit increased Aβ deposition, maladaptive microglial activation, and reduced microglial interactions with plaques. These changes were attenuated in APOE2/4 mice, accompanied by a brain proteomic profile more similar to those of APOE3/3 and APOE2/3 mice. Increased myelin basic protein (MBP) abundance was observed in APOE2/3 but not APOE2/4 mice. Plasma lipidomics revealed shared alterations in APOE3/4 and APOE2/4 mice, with distinct signatures in APOE2/3 mice. These findings define allele interaction-dependent effects of APOE on brain and systemic phenotypes and provide a framework for understanding the biological consequences of the APOE2/4 genotype.

An LC/MS-based deep multi-omics platform for integrated molecular characterization from a single sample.

Investigating the relationship of circulating lipidome profiles with cross-sectional and longitudinal changes of central Alzheimer's disease (AD) biomarkers, including amyloid/tau/neurodegeneration (A/T/N), can provide a holistic view between the lipidome and AD pathophysiology. In this study, we quantified a total of 749 plasma lipid species at baseline using liquid chromatography-mass spectrometry and performed cross-sectional and longitudinal association analysis of plasma lipidome profiles with longitudinal A/T/N biomarkers for AD in the Alzheimer's Disease Neuroimaging Initiative cohort (N = 1395). We identified several lipid species, classes, and network modules of correlated lipids that were significantly associated with cross-sectional and longitudinal changes of A/T/N biomarkers. Notably, we identified lysoalkylphosphatidylcholine (LPC(O)) as associated with cross-sectional "A/N" biomarkers at the lipid species, class, and module levels. Also, Phosphatidylethanolamine (PE) ethers were associated with A/T/N biomarkers in the species level and with "N" biomarkers in the class and module levels. G_M3 ganglioside showed association with cross-sectional and longitudinal changes of "N" biomarkers at the species and class levels. Furthermore, 20 lipid species, out of all 57 species identified as associated with "less severe" AD biomarkers, contained docosahexaenoic acid (DHA), indicating that the previously reported beneficial effects of DHA on AD were significant at the central biomarker level. In conclusion, our approach linking peripheral metabolic changes with brain metabolic, structural, and functional states strengthens evidence from previous studies that were performed using only clinical AD diagnosis. Importantly, our study also enabled identification of novel lipids that play potential roles in progression of AD pathophysiology, suggesting dysregulation of lipid metabolic pathways as precursors to AD development and progression.

Biological age scores capture ageing heterogeneity beyond chronological age but are often dominated by lifestyle and environmental exposures, limiting clinical interpretability. We developed an environmentally adjusted metabolic age score (EAmAge) to isolate intrinsic ageing biology relevant to neurodegeneration and chronic disease. Major environmental influences were statistically removed from plasma lipidomic profiles before constructing an age-prediction model using ridge regression. EAmAge was derived in the AusDiab cohort (n = 10,339) and validated across three independent cohorts (BHS, ADNI and ASPREE; total n = 9,835). Compared with an unadjusted lipidomic age model (mAge_orig), EAmAge showed stronger and more consistent associations with incident Alzheimer’s disease-related dementia, cardiovascular events and all-cause mortality. EAmAge was also associated with Alzheimer’s disease-related biomarkers, including amyloid burden, reduced glucose metabolism and hippocampal atrophy. These findings establish EAmAge as a robust and partially modifiable biomarker that improves risk stratification by disentangling intrinsic metabolic ageing from environmental confounding.

Lipidomics, a rapidly evolving discipline at the interface of biology and analytical chemistry, seeks to comprehensively characterize the lipid composition of biological systems. Driven by advances in mass spectrometry, chromatography and computational analysis, lipidomics has enabled the high-resolution mapping of lipid networks and their functional dynamics across molecular, cellular and organismal scales. In biomedical research, lipidomics is emerging as a powerful platform for biomarker discovery, enabling early diagnosis, prognosis, and therapeutic monitoring of cancer, metabolic, and neurodegenerative diseases. The field is also reshaping drug discovery by uncovering lipid-mediated pathways, identifying novel therapeutic targets, and refining assessments of drug efficacy and safety. Beyond medicine, lipidomic analyses are redefining food and nutrition science by elucidating how dietary lipids influence metabolic health and disease risk. In parallel, environmental and ecological lipidomics are emerging as powerful frameworks for assessing ecosystem health, tracking the impact of pollutants and exploring the biological consequences of climate change. Such approaches are also informing the discovery of sustainable lipid resources and the development of novel biotechnological and agricultural innovations. With its rapidly expanding analytical repertoire and cross-disciplinary relevance, lipidomics is poised to make substantial contributions to both fundamental biology and applied science. This Perspective aims to synthesise the current state of the field, delineate major analytical and conceptual challenges, and outline future directions for translating lipidomic knowledge into tangible societal and environmental benefits.

Glucosylceramide synthase (GCS) catalyzes ceramide glycosylation in response to cell stress that produces glucosylceramide and other glycosphingolipids. GCS overexpression is a cause of drug resistance and enriches cancer stem cells (CSCs) during cancer chemotherapy. Previous studies showed that GCS modulates the expression of p53 mutants and oncogenic gain-of-function (GOF) in heterozygous knock-in cell models (TP53 R273H^−/+). However, it is unclear whether GCS can modulate the effects of homozygous p53 mutations, which are common in many cancer cases. We report herewith that inhibition of GCS, via UGCG knockout and using an inhibitor (Genz-161), effectively re-sensitizes drug resistance and diminishes CSCs in colon cancer cells carrying the homozygous p53 R273H mutation. In aggressive WiDr cells carrying TP53 R273H mutation, knockout of UGCG gene using CRISPR/Cas9 editing or inhibition of GCS with Genz-161 sensitized cancer cells to oxaliplatin, irinotecan and paclitaxel. With decreased ceramide glycosylation in lipidomic profiling, both UGCG knockout and Genz-161 treatments substantially decreased wound healing, and diminished CSCs and tumor growth under chemotherapy. Interestingly, inhibition of RNA m⁶A methylation by neplanocin A markedly increased p53 function and reversed drug resistance. Mechanistic investigation revealed that GCS inhibition downregulated methyltransferase-like 3 (METTL3) expression and decreased RNA-m⁶A modification on mutant p53 R273H effects. Altogether, our findings demonstrate that ceramide glycosylation promotes METTL3 expression and RNA m⁶A methylation in response to drug-induced stress, thereby promoting mutant p53 expression and associated GOF. Conversely, inhibition of GCS can diminish CSCs and drug resistance via reduction in m⁶A modification and advance of p53-assocaited tumor suppressive function. GCS inhibition is an achievable approach for mutant cancer treatment.

Lysosomes are critical for maintaining cellular homeostasis and nutrient availability, yet how tumor cells survive under lysosomal inhibition remains unclear. Here, we revealed that inhibiting lysosome function with chloroquine unexpectedly stimulated glucose uptake across various cancer cells. This effect was driven by sterol regulatory element–binding protein 1 (SREBP-1), a key lipogenic transcription factor, which specifically increased the expression of glucose transporters GLUT3 and GLUT6, enhancing glucose uptake and macromolecule synthesis. Elevated glucose, induced by chloroquine, stabilized SREBP cleavage-activating protein (SCAP), the activator of SREBP-1, further amplifying its activity and contributing to tumor resistance to lysosome inhibition. Disrupting this SREBP-1–glucose uptake feedforward loop by combining chloroquine with inhibitors of glucose transporters, SREBP-1, or lipogenic enzymes induced a synergistic antitumor effect in squamous cell and adenocarcinoma lung cancer patient-derived organoids and xenografts. This combination impaired mitochondrial structure and function, inducing apoptotic tumor cell death. Our study uncovers a role for SREBP-1 in regulating glucose metabolism and provides a promising therapeutic strategy that combines lysosome inhibition with glucose transporter or lipogenic enzyme inhibition for effective cancer treatment.