Dynamic Brain Lipid Profiles Modulate Microglial Lipid Droplet Accumulation and Inflammation Under Ischemic Conditions in Mice.

Microglia are critically involved in post-stroke inflammation affecting neurological outcomes. Lipid droplet (LD) accumulation in microglia results in a dysfunctional and pro-inflammatory state in the aged brain and worsens the outcome of neuroinflammatory and neurodegenerative diseases. However, the role of LD-rich microglia (LDRM) under stroke conditions is unknown. Using in vitro and in vivo stroke models, herein accumulation patterns of microglial LD and their corresponding microglial inflammatory signaling cascades are studied. Interactions between temporal and spatial dynamics of lipid profiles and microglial phenotypes in different post-stroke brain regions are found. Hence, microglia display enhanced levels of LD accumulation and elevated perilipin 2 (PLIN2) expression patterns when exposed to hypoxia or stroke. Such LDRM exhibit high levels of TNF-α, IL-6, and IL-1ß as well as a pro-inflammatory phenotype and differentially expressed lipid metabolism-related genes. These post-ischemic alterations result in distinct lipid profiles with spatial and temporal dynamics, especially with regard to cholesteryl ester and triacylglycerol levels, further exacerbating post-ischemic inflammation. The present study sheds new light on the dynamic changes of brain lipid profiles and aggregation patterns of LD in microglia exposed to ischemia, demonstrating a mutual mechanism between microglial phenotype and function, which contributes to progression of brain injury.

Polygenic scores for complex traits are associated with changes in concentration of circulating lipid species.

Understanding perturbations in circulating lipid levels that often occur years or decades before clinical symptoms may enhance our understanding of disease mechanisms and provide novel intervention opportunities. Here, we assessed if polygenic scores (PGSs) for complex traits could detect lipid dysfunctions related to the traits and provide new biological insights. We constructed genome-wide PGSs (approximately 1 million genetic variants) for 50 complex traits in 7,169 Finnish individuals with routine clinical lipid profiles and lipidomics measurements (179 lipid species). We identified 678 associations (P < 9.0 × 10-5) involving 26 traits and 142 lipids. Most of these associations were also validated with the actual phenotype measurements where available (89.5% of 181 associations where the trait was available), suggesting that these associations represent early signs of physiological changes of the traits. We detected many known relationships (e.g., PGS for body mass index (BMI) and lysophospholipids, PGS for type 2 diabetes and triacyglycerols) and those that suggested potential target for prevention strategies (e.g., PGS for venous thromboembolism and arachidonic acid). We also found association of PGS for favorable adiposity with increased sphingomyelins levels, suggesting a probable role of sphingomyelins in increased risk for certain disease, e.g., venous thromboembolism as reported previously, in favorable adiposity despite its favorable metabolic effect. Altogether, our study provides a comprehensive characterization of lipidomic alterations in genetic predisposition for a wide range of complex traits. The study also demonstrates potential of PGSs for complex traits to capture early, presymptomatic lipid alterations, highlighting its utility in understanding disease mechanisms and early disease detection.

Investigating mechanical deformation's role in cochlear implant durability.

Platinum and platinum-based alloys are used as the electrode material in cochlear implants because of the biocompatibility and the favorable electrochemical properties. Still, these implants can fail over time. The present study was conducted to shed light on the effects of microstructure on the electrochemical degradation of platinum. After three days of stimulation with a square wave signal, corrosive attack appeared on the platinum surface. The influence of mechanical deformation, in particular rolling, on the corrosion resistance of platinum was also prominent. The cyclic voltammetry showed a clear dependence on the electrolyte used, which was interpreted as an influence of the buffer in the artificial perilymph used. In addition, the polarization curves showed a shift with grain size that was not expected. This could be attributed to the defects present on the surface. These findings are crucial for the manufacture of cochlear implants to ensure their long-term functionality.

Imputation of missing values in lipidomic datasets.

Lipidomic data often exhibit missing data points, which can be categorized as missing completely at random (MCAR), missing at random, or missing not at random (MNAR). In order to utilize statistical methods that require complete datasets or to improve the identification of potential effects in statistical comparisons, imputation techniques can be employed. In this study, we investigate commonly used methods such as zero, half-minimum, mean, and median imputation, as well as more advanced techniques such as k-nearest neighbor and random forest imputation. We employ a combination of simulation-based approaches and application to real datasets to assess the performance and effectiveness of these methods. Shotgun lipidomics datasets exhibit high correlations and missing values, often due to low analyte abundance, characterized as MNAR. In this context, k-nearest neighbor approaches based on correlation and truncated normal distributions demonstrate best performance. Importantly, both methods can effectively impute missing values independent of the type of missingness, the determination of which is nearly impossible in practice. The imputation methods still control the type I error rate.

Multi-omics subgroups associated with glycaemic deterioration in type 2 diabetes: an IMI-RHAPSODY Study.

Introduction: Type 2 diabetes (T2D) onset, progression and outcomes differ substantially between individuals. Multi-omics analyses may allow a deeper understanding of these differences and ultimately facilitate personalised treatments. Here, in an unsupervised "bottom-up" approach, we attempt to group T2D patients based solely on -omics data generated from plasma. Methods: Circulating plasma lipidomic and proteomic data from two independent clinical cohorts, Hoorn Diabetes Care System (DCS) and Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS), were analysed using Similarity Network Fusion. The resulting patient network was analysed with Logistic and Cox regression modelling to explore relationships between plasma -omic profiles and clinical characteristics. Results: From a total of 1,134 subjects in the two cohorts, levels of 180 circulating plasma lipids and 1195 proteins were used to separate patients into two subgroups. These differed in terms of glycaemic deterioration (Hazard Ratio=0.56;0.73), insulin sensitivity and secretion (C-peptide, p=3.7e-11;2.5e-06, DCS and GoDARTS, respectively; Homeostatic model assessment 2 (HOMA2)-B; -IR; -S, p=0.0008;4.2e-11;1.1e-09, only in DCS). The main molecular signatures separating the two groups included triacylglycerols, sphingomyelin, testican-1 and interleukin 18 receptor. Conclusions: Using an unsupervised network-based fusion method on plasma lipidomics and proteomics data from two independent cohorts, we were able to identify two subgroups of T2D patients differing in terms of disease severity. The molecular signatures identified within these subgroups provide insights into disease mechanisms and possibly new prognostic markers for T2D.

Plasma Lipidomic Profiling Using Mass Spectrometry for Multiple Sclerosis Diagnosis and Disease Activity Stratification (LipidMS).

This investigation explores the potential of plasma lipidomic signatures for aiding in the diagnosis of Multiple Sclerosis (MS) and evaluating the clinical course and disease activity of diseased patients. Plasma samples from 60 patients with MS (PwMS) were clinically stratified to either a relapsing-remitting (RRMS) or a chronic progressive MS course and 60 age-matched controls were analyzed using state-of-the-art direct infusion quantitative shotgun lipidomics. To account for potential confounders, data were filtered for age and BMI correlations. The statistical analysis employed supervised and unsupervised multivariate data analysis techniques, including a principal component analysis (PCA), a partial least squares discriminant analysis (oPLS-DA) and a random forest (RF). To determine whether the significant absolute differences in the lipid subspecies have a relevant effect on the overall composition of the respective lipid classes, we introduce a class composition visualization (CCV). We identified 670 lipids across 16 classes. PwMS showed a significant increase in diacylglycerols (DAG), with DAG 16:0;0_18:1;0 being proven to be the lipid with the highest predictive ability for MS as determined by RF. The alterations in the phosphatidylethanolamines (PE) were mainly linked to RRMS while the alterations in the ether-bound PEs (PE O-) were found in chronic progressive MS. The amount of CE species was reduced in the CPMS cohort whereas TAG species were reduced in the RRMS patients, both lipid classes being relevant in lipid storage. Combining the above mentioned data analyses, distinct lipidomic signatures were isolated and shown to be correlated with clinical phenotypes. Our study suggests that specific plasma lipid profiles are not merely associated with the diagnosis of MS but instead point toward distinct clinical features in the individual patient paving the way for personalized therapy and an enhanced understanding of MS pathology.

MemPrep, a new technology for isolating organellar membranes provides fingerprints of lipid bilayer stress.

Biological membranes have a stunning ability to adapt their composition in response to physiological stress and metabolic challenges. Little is known how such perturbations affect individual organelles in eukaryotic cells. Pioneering work has provided insights into the subcellular distribution of lipids in the yeast Saccharomyces cerevisiae, but the composition of the endoplasmic reticulum (ER) membrane, which also crucially regulates lipid metabolism and the unfolded protein response, remains insufficiently characterized. Here, we describe a method for purifying organelle membranes from yeast, MemPrep. We demonstrate the purity of our ER membrane preparations by proteomics, and document the general utility of MemPrep by isolating vacuolar membranes. Quantitative lipidomics establishes the lipid composition of the ER and the vacuolar membrane. Our findings provide a baseline for studying membrane protein biogenesis and have important implications for understanding the role of lipids in regulating the unfolded protein response (UPR). The combined preparative and analytical MemPrep approach uncovers dynamic remodeling of ER membranes in stressed cells and establishes distinct molecular fingerprints of lipid bilayer stress.

An altered plasma lipidome-phenome network characterizes heart failure with preserved ejection fraction.

AIMS: Heart failure with preserved ejection fraction (HFpEF) is a multifactorial, multisystemic syndrome that involves alterations in lipid metabolism. This study aimed to test whether distinct plasma lipid profiles or lipid entities or both are associated with clinical and functional echocardiographic parameters in HFpEF. METHODS AND RESULTS: We examined the human plasma lipidome in HFpEF patients (n = 18) with left ventricular ejection fraction ≥50% and N-terminal pro-brain natriuretic peptide (NT-proBNP) >125 pg/mL and control subjects (n = 12) using mass spectrometry-based shotgun lipidomics. The cohort included 8 women and 22 men with average age of 67.8 ± 8.6 SD. The control and disease groups were not significantly different with respect to age, body mass index, systolic and diastolic blood pressure, and waist-to-hip ratio. The disease group experienced more fatigue (P < 0.001), had more often coronary artery disease (P = 0.04), and received more medications (beta-blockers, P < 0.001). The disease group had significantly different levels of HFpEF-relevant parameters, including NT-proBNP (P < 0.001), left ventricular mass index (P = 0.005), left atrial volume index (P = 0.001), and left ventricular filling index (P < 0.001), and lower left ventricular end-diastolic diameter (P = 0.014), with no difference in left ventricular ejection fraction. Significant differences in lipid profiles between HFpEF patients and controls could not be detected, including no significant differences in abundance of circulating lipids binned by carbon chain length or by double bonds, nor at the level of individual lipid species. However, there was a striking correlation between selected lipids with smoking status that was independent of disease status, as well as between specific lipids and hyperlipidaemia [with corresponding significance of either false discovery rate (FDR) <0.1 or FDR < 0.01]. In an exploratory network analysis of correlations, we observed significantly stronger correlations within the HFpEF group between individual lipids from the cholesterol ester and phosphatidylcholine (PC) classes and clinical/echocardiographic parameters such as left atrial volume index, left ventricular end-diastolic diameters, and heart rate (FDR < 0.1). In contrast, the control group showed significantly stronger negative correlations (FDR < 0.1) between individual species from the PC and sphingomyelin classes and left ventricular mass index or systolic blood pressure. CONCLUSIONS: We did not find significant direct associations between plasma lipidomic parameters and HFpEF and therefore could not conclude that any specific lipids are biomarkers of HFpEF. The validation in larger cohort is needed to confidently conclude the absence of first-order associations.

Genome-wide association analysis of plasma lipidome identifies 495 genetic associations.

The human plasma lipidome captures risk for cardiometabolic diseases. To discover new lipid-associated variants and understand the link between lipid species and cardiometabolic disorders, we perform univariate and multivariate genome-wide analyses of 179 lipid species in 7174 Finnish individuals. We fine-map the associated loci, prioritize genes, and examine their disease links in 377,277 FinnGen participants. We identify 495 genome-trait associations in 56 genetic loci including 8 novel loci, with a considerable boost provided by the multivariate analysis. For 26 loci, fine-mapping identifies variants with a high causal probability, including 14 coding variants indicating likely causal genes. A phenome-wide analysis across 953 disease endpoints reveals disease associations for 40 lipid loci. For 11 coronary artery disease risk variants, we detect strong associations with lipid species. Our study demonstrates the power of multivariate genetic analysis in correlated lipidomics data and reveals genetic links between diseases and lipid species beyond the standard lipids.

Cholesteryl hemiazelate identified in CVD patients causes in vitro and in vivo inflammation.

Oxidation of PUFAs in LDLs trapped in the arterial intima plays a critical role in atherosclerosis. Though there have been many studies on the atherogenicity of oxidized derivatives of PUFA-esters of cholesterol, the effects of cholesteryl hemiesters (ChEs), the oxidation end products of these esters, have not been studied. Through lipidomics analyses, we identified and quantified two ChE types in the plasma of CVD patients and identified four ChE types in human endarterectomy specimens. Cholesteryl hemiazelate (ChA), the ChE of azelaic acid (n-nonane-1,9-dioic acid), was the most prevalent ChE identified in both cases. Importantly, human monocytes, monocyte-derived macrophages, and neutrophils exhibit inflammatory features when exposed to subtoxic concentrations of ChA in vitro. ChA increases the secretion of proinflammatory cytokines such as interleukin-1ß and interleukin-6 and modulates the surface-marker profile of monocytes and monocyte-derived macrophage. In vivo, when zebrafish larvae were fed with a ChA-enriched diet, they exhibited neutrophil and macrophage accumulation in the vasculature in a caspase 1- and cathepsin B-dependent manner. ChA also triggered lipid accumulation at the bifurcation sites of the vasculature of the zebrafish larvae and negatively impacted their life expectancy. We conclude that ChA behaves as an endogenous damage-associated molecular pattern with inflammatory and proatherogenic properties.

Identification of biomarkers for glycaemic deterioration in type 2 diabetes.

We identify biomarkers for disease progression in three type 2 diabetes cohorts encompassing 2,973 individuals across three molecular classes, metabolites, lipids and proteins. Homocitrulline, isoleucine and 2-aminoadipic acid, eight triacylglycerol species, and lowered sphingomyelin 42:2;2 levels are predictive of faster progression towards insulin requirement. Of ~1,300 proteins examined in two cohorts, levels of GDF15/MIC-1, IL-18Ra, CRELD1, NogoR, FAS, and ENPP7 are associated with faster progression, whilst SMAC/DIABLO, SPOCK1 and HEMK2 predict lower progression rates. In an external replication, proteins and lipids are associated with diabetes incidence and prevalence. NogoR/RTN4R injection improved glucose tolerance in high fat-fed male mice but impaired it in male db/db mice. High NogoR levels led to islet cell apoptosis, and IL-18R antagonised inflammatory IL-18 signalling towards nuclear factor kappa-B in vitro. This comprehensive, multi-disciplinary approach thus identifies biomarkers with potential prognostic utility, provides evidence for possible disease mechanisms, and identifies potential therapeutic avenues to slow diabetes progression.

Evaluation of a Novel Skin Emollient Cream on Skin Lipidome and Lipid Organization.

INTRODUCTION: The stratum corneum (SC) matrix is composed of free fatty acids, cholesterol, and ceramides (CERs), which play a key role in the skin barrier function. Changes in the composition and content of skin lipids will affect the function of the skin barrier. The effect of a glycerol/petrolatum-based emollient (G/P-emollient) cream on the lipid profiles of isolated ex vivo human SC and the SC of a reconstructed human epidermis (RHE) model was measured. METHODS: The spatial organization of the cream and the isolated SC intercellular matrix were studied using X-ray diffraction. The inter-bilayer distances in the multi-lamellar lipid structures and lattice type were analyzed using small-angle X-ray scattering and wide-angle X-ray scattering (WAXS), respectively. Lipidomic analysis using shotgun lipidomics was performed on RHE models to quantify CER classes and chain lengths. This technology enables the analysis of thousands of lipids in a single biological sample. RESULTS: The crystallized components of the cream are lipids, which were mainly packed in orthorhombic lattices, as well as hexagonal lattices and were similar to the SC structure. The cream penetrated the SC but did not alter the WAXS profile. It increased the amount of higher carbon number CERs (>42 carbons) and decreased lower carbon number CERs (<42 carbons). All chain length of CERs and acyl-CER classes (CER EOS, EOH, EOP, EOdS) were increased as the total CER classes. A decrease of the CER C34 for hydroxylated and non-hydroxylated CERs was also observed. The cream altered the S and P CER forms (increased the NP/NS and AP/AS ratios), indicating it could reduce the relative feedback mechanism observed in inflammatory pathologies, for example, atopic dermatitis. The cream increased CER NP, which is decreased in dry skin. CONCLUSION: G/P-emollient cream may be beneficial for skin pathologies by modifying SC lipids, balancing CER levels and ratios, and improving the barrier function. Importantly, the cream structure mimics that of the SC and penetrated the lower SC layers without compromising its lamellar structure.

Remodeling of yeast vacuole membrane lipidomes from the log (one phase) to stationary stage (two phases).

Upon nutrient limitation, budding yeast of Saccharomyces cerevisiae shift from fast growth (the log stage) to quiescence (the stationary stage). This shift is accompanied by liquid-liquid phase separation in the membrane of the vacuole, an endosomal organelle. Recent work indicates that the resulting micrometer-scale domains in vacuole membranes enable yeast to survive periods of stress. An outstanding question is which molecular changes might cause this membrane phase separation. Here, we conduct lipidomics of vacuole membranes in both the log and stationary stages. Isolation of pure vacuole membranes is challenging in the stationary stage, when lipid droplets are in close contact with vacuoles. Immuno-isolation has previously been shown to successfully purify log-stage vacuole membranes with high organelle specificity, but it was not previously possible to immuno-isolate stationary-stage vacuole membranes. Here, we develop Mam3 as a bait protein for vacuole immuno-isolation, and demonstrate low contamination by non-vacuolar membranes. We find that stationary-stage vacuole membranes contain surprisingly high fractions of phosphatidylcholine lipids (∼40%), roughly twice as much as log-stage membranes. Moreover, in the stationary stage, these lipids have higher melting temperatures, due to longer and more saturated acyl chains. Another surprise is that no significant change in sterol content is observed. These lipidomic changes, which are largely reflected on the whole-cell level, fit within the predominant view that phase separation in membranes requires at least three types of molecules to be present: lipids with high melting temperatures, lipids with low melting temperatures, and sterols.

In vivo investigation of open-pored magnesium scaffolds LAE442 with different coatings in an open wedge defect.

The magnesium alloy LAE442 showed promising results as a bone substitute in numerous studies in non-weight bearing bone defects. This study aimed to investigate the in vivo behavior of wedge-shaped open-pored LAE442 scaffolds modified with two different coatings (magnesium fluoride (MgF2, group 1)) or magnesium fluoride/calcium phosphate (MgF2/CaP, group 2)) in a partial weight-bearing rabbit tibia defect model. The implantation of the scaffolds was performed as an open wedge corrective osteotomy in the tibia of 40 rabbits and followed for observation periods of 6, 12, 24, and 36 weeks. Radiological and microcomputed tomographic examinations were performed in vivo. X-ray microscopic, histological, histomorphometric, and SEM/EDS analyses were performed at the end of each time period. µCT measurements and X-ray microscopy showed a slight decrease in volume and density of the scaffolds of both coatings. Histologically, endosteal and periosteal callus formation with good bridging and stabilization of the osteotomy gap and ingrowth of bone into the scaffold was seen. The MgF2 coating favored better bridging of the osteotomy gap and more bone-scaffold contacts, especially at later examination time points. Overall, the scaffolds of both coatings met the requirement to withstand the loads after an open wedge corrective osteotomy of the proximal rabbit tibia. However, in addition to the inhomogeneous degradation behavior of individual scaffolds, an accumulation of gas appeared, so the scaffold material should be revised again regarding size dimension and composition.

Deficiency of the frontotemporal dementia gene GRN results in gangliosidosis.

Haploinsufficiency of GRN causes frontotemporal dementia (FTD). The GRN locus produces progranulin (PGRN), which is cleaved to lysosomal granulin polypeptides. The function of lysosomal granulins and why their absence causes neurodegeneration are unclear. Here we discover that PGRN-deficient human cells and murine brains, as well as human frontal lobes from GRN-mutation FTD patients have increased levels of gangliosides, glycosphingolipids that contain sialic acid. In these cells and tissues, levels of lysosomal enzymes that catabolize gangliosides were normal, but levels of bis(monoacylglycero)phosphates (BMP), lipids required for ganglioside catabolism, were reduced with PGRN deficiency. Our findings indicate that granulins are required to maintain BMP levels to support ganglioside catabolism, and that PGRN deficiency in lysosomes leads to gangliosidosis. Lysosomal ganglioside accumulation may contribute to neuroinflammation and neurodegeneration susceptibility observed in FTD due to PGRN deficiency and other neurodegenerative diseases.

Lipidome- and Genome-Wide Study to Understand Sex Differences in Circulatory Lipids.

Background Despite well-recognized differences in the atherosclerotic cardiovascular disease risk between men and women, sex differences in risk factors and sex-specific mechanisms in the pathophysiology of atherosclerotic cardiovascular disease remain poorly understood. Lipid metabolism plays a central role in the development of atherosclerotic cardiovascular disease. Understanding sex differences in lipids and their genetic determinants could provide mechanistic insights into sex differences in atherosclerotic cardiovascular disease and aid in precise risk assessment. Herein, we examined sex differences in plasma lipidome and heterogeneity in genetic influences on lipidome in men and women through sex-stratified genome-wide association analyses. Methods and Results We used data consisting of 179 lipid species measured by shotgun lipidomics in 7266 individuals from the Finnish GeneRISK cohort and sought for replication using independent data from 2045 participants. Significant sex differences in the levels of 141 lipid species were observed (P<7.0×10-4). Interestingly, 121 lipid species showed significant age-sex interactions, with opposite age-related changes in 39 lipid species. In general, most of the cholesteryl esters, ceramides, lysophospholipids, and glycerides were higher in 45- to 50-year-old men compared with women of same age, but the sex differences narrowed down or reversed with age. We did not observe any major differences in genetic effect in the sex-stratified genome-wide association analyses, which suggests that common genetic variants do not have a major role in sex differences in lipidome. Conclusions Our study provides a comprehensive view of sex differences in circulatory lipids pointing to potential sex differences in lipid metabolism and highlights the need for sex- and age-specific prevention strategies.

Ganglioside lipidomics of CNS myelination using direct infusion shotgun mass spectrometry.

Gangliosides are present and concentrated in axons and implicated in axon-myelin interactions, but how ganglioside composition changes during myelin formation is not known. Here, we present a direct infusion (shotgun) lipidomics method to analyze gangliosides in small amounts of tissue reproducibly and with high sensitivity. We resolve the mouse ganglioside lipidome during development and adulthood and determine the ganglioside content of mice lacking the St3gal5 and B4galnt1 genes that synthesize most ganglioside species. Our results reveal substantial changes in the ganglioside lipidome during the formation of myelinated nerve fibers. In sum, we provide insights into the CNS ganglioside lipidome with a quantitative and sensitive mass spectrometry method. Since this method is compatible with global lipidomic profiling, it will provide insights into ganglioside function in physiology and pathology.

A set of gene knockouts as a resource for global lipidomic changes.

Enzyme specificity in lipid metabolic pathways often remains unresolved at the lipid species level, which is needed to link lipidomic molecular phenotypes with their protein counterparts to construct functional pathway maps. We created lipidomic profiles of 23 gene knockouts in a proof-of-concept study based on a CRISPR/Cas9 knockout screen in mammalian cells. This results in a lipidomic resource across 24 lipid classes. We highlight lipid species phenotypes of multiple knockout cell lines compared to a control, created by targeting the human safe-harbor locus AAVS1 using up to 1228 lipid species and subspecies, charting lipid metabolism at the molecular level. Lipid species changes are found in all knockout cell lines, however, some are most apparent on the lipid class level (e.g., SGMS1 and CEPT1), while others are most apparent on the fatty acid level (e.g., DECR2 and ACOT7). We find lipidomic phenotypes to be reproducible across different clones of the same knockout and we observed similar phenotypes when two enzymes that catalyze subsequent steps of the long-chain fatty acid elongation cycle were targeted.

Lipidomic risk scores are independent of polygenic risk scores and can predict incidence of diabetes and cardiovascular disease in a large population cohort.

Type 2 diabetes (T2D) and cardiovascular disease (CVD) represent significant disease burdens for most societies and susceptibility to these diseases is strongly influenced by diet and lifestyle. Physiological changes associated with T2D or CVD, such has high blood pressure and cholesterol and glucose levels in the blood, are often apparent prior to disease incidence. Here we integrated genetics, lipidomics, and standard clinical diagnostics to assess future T2D and CVD risk for 4,067 participants from a large prospective population-based cohort, the Malmö Diet and Cancer-Cardiovascular Cohort. By training Ridge regression-based machine learning models on the measurements obtained at baseline when the individuals were healthy, we computed several risk scores for T2D and CVD incidence during up to 23 years of follow-up. We used these scores to stratify the participants into risk groups and found that a lipidomics risk score based on the quantification of 184 plasma lipid concentrations resulted in a 168% and 84% increase of the incidence rate in the highest risk group and a 77% and 53% decrease of the incidence rate in lowest risk group for T2D and CVD, respectively, compared to the average case rates of 13.8% and 22.0%. Notably, lipidomic risk correlated only marginally with polygenic risk, indicating that the lipidome and genetic variants may constitute largely independent risk factors for T2D and CVD. Risk stratification was further improved by adding standard clinical variables to the model, resulting in a case rate of 51.0% and 53.3% in the highest risk group for T2D and CVD, respectively. The participants in the highest risk group showed significantly altered lipidome compositions affecting 167 and 157 lipid species for T2D and CVD, respectively. Our results demonstrated that a subset of individuals at high risk for developing T2D or CVD can be identified years before disease incidence. The lipidomic risk, which is derived from only one single mass spectrometric measurement that is cheap and fast, is informative and could extend traditional risk assessment based on clinical assays.