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Lipidomic profiling of extracellular vesicles (EVs) from lean and obese individuals. (A) Unsupervised hierarchical clustering heatmap of lipidomic profiles from EVs isolated from lean and obese individuals. The analysis was performed using MetaboAnalyst 5.0 based on normalized lipid abundance values. Each column represents an individual sample (blue for lean, pink for obese), and each row corresponds to a lipid species. Color scale indicates Z‐score–normalized relative abundance, with blue representing lower levels and brown indicating higher levels. (B, C) Quantification of major lipid classes in EVs from lean and obese individuals. (B) Levels of specific lipid species—including triacylglycerol (TAG), free fatty acids <t>(FA),</t> <t>lysophosphatidylcholine</t> <t>(LPC),</t> lysophosphatidylethanolamine (LPE), phosphatidic acid (PA), phosphatidylcholine (PC), phosphatidylserine (PS), and sphingomyelin (SM)—were measured from EVs derived from pooled adipocyte isolates in each group (n = 5 per group). (C) Lipid class quantification in EVs from individual patients ( n = 4‐5 per group), showing interindividual variation. Data are normalized to total EV protein (p or n mol/mg protein). Data are presented as mean ± SEM; two‐tailed t‐test; *, increase; # , decrease; compared with the corresponding controls, * /# p < 0.05, and ** /## p < 0.01. (D,E) Simplified Manhattan plots of lipid class alterations between obese and lean EVs (including Lean 1). (D) Fold changes (log₁₀[Obese/Lean]) of individual lipid classes stratified by lipid species. Each dot represents a detected lipid species, color‐coded by class. (E) Statistical significance (−log₁₀ P value) of lipid class differences calculated based on unpaired two‐tailed t ‐tests using raw lipidomic concentrations from lean and obese individuals. Notable classes such as FAC, TAG, PC, LPC, and PA exhibit significant alterations in fold change and/or p ‐value distribution. (F) Lipid–lipid correlation heatmap of EV lipidomic profiles from lean and obese individuals. Pairwise correlations between lipid species were calculated using MetaboAnalyst 5.0 based on combined datasets from both groups. The color scale represents the Pearson correlation coefficient, ranging from –0.5 (purple, negative correlation) to 1.0 (yellow, strong positive correlation). Hierarchical clustering was applied to group lipid species with similar covariation patterns, revealing distinct lipid modules and potential coregulatory networks. Ten major lipid clusters (a–j) were identified, each outlined and annotated with representative lipid classes on the right. Key lipid species contributing to each cluster are summarized and compared between obese and lean groups in the accompanying Supporting Information Tables 4 and . Fold‐change (obese/lean) values for each lipid species are also shown as a grayscale bar (FC O/L) adjacent to the cluster annotation, highlighting cluster‐specific lipid alterations associated with obesity. (G) Partial least squares discriminant analysis (PLS‐DA) plots showing lipid class–specific separation between EVs from lean and obese individuals (including Lean 1). EV lipidomic data were analyzed with individual patient samples as input. Samples from lean and obese subjects are shown in blue and brown, respectively, with ellipses representing 95% confidence intervals. The percentage of explained variance for the first and second components (T score [1] and orthogonal T score [1]) is indicated in parentheses. (H) Volcano plot identifying differentially abundant lipid species between obese and lean EVs. Each dot represents a lipid species, plotted by log 2 (fold change Obese/Lean) on the x ‐axis and −log₁₀(P value) on the y ‐axis. Blue dots indicate significantly downregulated species in obesity ( p < 0.05 and FC < −1), red dots represent significantly upregulated species ( p < 0.05 and FC > 1), and grey dots are nonsignificant. Top 15 upregulated and 15 downregulated lipid species are annotated and listed by class and composition.
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Lipidomic profiling of extracellular vesicles (EVs) from lean and obese individuals. (A) Unsupervised hierarchical clustering heatmap of lipidomic profiles from EVs isolated from lean and obese individuals. The analysis was performed using MetaboAnalyst 5.0 based on normalized lipid abundance values. Each column represents an individual sample (blue for lean, pink for obese), and each row corresponds to a lipid species. Color scale indicates Z‐score–normalized relative abundance, with blue representing lower levels and brown indicating higher levels. (B, C) Quantification of major lipid classes in EVs from lean and obese individuals. (B) Levels of specific lipid species—including triacylglycerol (TAG), free fatty acids <t>(FA),</t> <t>lysophosphatidylcholine</t> <t>(LPC),</t> lysophosphatidylethanolamine (LPE), phosphatidic acid (PA), phosphatidylcholine (PC), phosphatidylserine (PS), and sphingomyelin (SM)—were measured from EVs derived from pooled adipocyte isolates in each group (n = 5 per group). (C) Lipid class quantification in EVs from individual patients ( n = 4‐5 per group), showing interindividual variation. Data are normalized to total EV protein (p or n mol/mg protein). Data are presented as mean ± SEM; two‐tailed t‐test; *, increase; # , decrease; compared with the corresponding controls, * /# p < 0.05, and ** /## p < 0.01. (D,E) Simplified Manhattan plots of lipid class alterations between obese and lean EVs (including Lean 1). (D) Fold changes (log₁₀[Obese/Lean]) of individual lipid classes stratified by lipid species. Each dot represents a detected lipid species, color‐coded by class. (E) Statistical significance (−log₁₀ P value) of lipid class differences calculated based on unpaired two‐tailed t ‐tests using raw lipidomic concentrations from lean and obese individuals. Notable classes such as FAC, TAG, PC, LPC, and PA exhibit significant alterations in fold change and/or p ‐value distribution. (F) Lipid–lipid correlation heatmap of EV lipidomic profiles from lean and obese individuals. Pairwise correlations between lipid species were calculated using MetaboAnalyst 5.0 based on combined datasets from both groups. The color scale represents the Pearson correlation coefficient, ranging from –0.5 (purple, negative correlation) to 1.0 (yellow, strong positive correlation). Hierarchical clustering was applied to group lipid species with similar covariation patterns, revealing distinct lipid modules and potential coregulatory networks. Ten major lipid clusters (a–j) were identified, each outlined and annotated with representative lipid classes on the right. Key lipid species contributing to each cluster are summarized and compared between obese and lean groups in the accompanying Supporting Information Tables 4 and . Fold‐change (obese/lean) values for each lipid species are also shown as a grayscale bar (FC O/L) adjacent to the cluster annotation, highlighting cluster‐specific lipid alterations associated with obesity. (G) Partial least squares discriminant analysis (PLS‐DA) plots showing lipid class–specific separation between EVs from lean and obese individuals (including Lean 1). EV lipidomic data were analyzed with individual patient samples as input. Samples from lean and obese subjects are shown in blue and brown, respectively, with ellipses representing 95% confidence intervals. The percentage of explained variance for the first and second components (T score [1] and orthogonal T score [1]) is indicated in parentheses. (H) Volcano plot identifying differentially abundant lipid species between obese and lean EVs. Each dot represents a lipid species, plotted by log 2 (fold change Obese/Lean) on the x ‐axis and −log₁₀(P value) on the y ‐axis. Blue dots indicate significantly downregulated species in obesity ( p < 0.05 and FC < −1), red dots represent significantly upregulated species ( p < 0.05 and FC > 1), and grey dots are nonsignificant. Top 15 upregulated and 15 downregulated lipid species are annotated and listed by class and composition.
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Lipidomic profiling of extracellular vesicles (EVs) from lean and obese individuals. (A) Unsupervised hierarchical clustering heatmap of lipidomic profiles from EVs isolated from lean and obese individuals. The analysis was performed using MetaboAnalyst 5.0 based on normalized lipid abundance values. Each column represents an individual sample (blue for lean, pink for obese), and each row corresponds to a lipid species. Color scale indicates Z‐score–normalized relative abundance, with blue representing lower levels and brown indicating higher levels. (B, C) Quantification of major lipid classes in EVs from lean and obese individuals. (B) Levels of specific lipid species—including triacylglycerol (TAG), free fatty acids <t>(FA),</t> <t>lysophosphatidylcholine</t> <t>(LPC),</t> lysophosphatidylethanolamine (LPE), phosphatidic acid (PA), phosphatidylcholine (PC), phosphatidylserine (PS), and sphingomyelin (SM)—were measured from EVs derived from pooled adipocyte isolates in each group (n = 5 per group). (C) Lipid class quantification in EVs from individual patients ( n = 4‐5 per group), showing interindividual variation. Data are normalized to total EV protein (p or n mol/mg protein). Data are presented as mean ± SEM; two‐tailed t‐test; *, increase; # , decrease; compared with the corresponding controls, * /# p < 0.05, and ** /## p < 0.01. (D,E) Simplified Manhattan plots of lipid class alterations between obese and lean EVs (including Lean 1). (D) Fold changes (log₁₀[Obese/Lean]) of individual lipid classes stratified by lipid species. Each dot represents a detected lipid species, color‐coded by class. (E) Statistical significance (−log₁₀ P value) of lipid class differences calculated based on unpaired two‐tailed t ‐tests using raw lipidomic concentrations from lean and obese individuals. Notable classes such as FAC, TAG, PC, LPC, and PA exhibit significant alterations in fold change and/or p ‐value distribution. (F) Lipid–lipid correlation heatmap of EV lipidomic profiles from lean and obese individuals. Pairwise correlations between lipid species were calculated using MetaboAnalyst 5.0 based on combined datasets from both groups. The color scale represents the Pearson correlation coefficient, ranging from –0.5 (purple, negative correlation) to 1.0 (yellow, strong positive correlation). Hierarchical clustering was applied to group lipid species with similar covariation patterns, revealing distinct lipid modules and potential coregulatory networks. Ten major lipid clusters (a–j) were identified, each outlined and annotated with representative lipid classes on the right. Key lipid species contributing to each cluster are summarized and compared between obese and lean groups in the accompanying Supporting Information Tables 4 and . Fold‐change (obese/lean) values for each lipid species are also shown as a grayscale bar (FC O/L) adjacent to the cluster annotation, highlighting cluster‐specific lipid alterations associated with obesity. (G) Partial least squares discriminant analysis (PLS‐DA) plots showing lipid class–specific separation between EVs from lean and obese individuals (including Lean 1). EV lipidomic data were analyzed with individual patient samples as input. Samples from lean and obese subjects are shown in blue and brown, respectively, with ellipses representing 95% confidence intervals. The percentage of explained variance for the first and second components (T score [1] and orthogonal T score [1]) is indicated in parentheses. (H) Volcano plot identifying differentially abundant lipid species between obese and lean EVs. Each dot represents a lipid species, plotted by log 2 (fold change Obese/Lean) on the x ‐axis and −log₁₀(P value) on the y ‐axis. Blue dots indicate significantly downregulated species in obesity ( p < 0.05 and FC < −1), red dots represent significantly upregulated species ( p < 0.05 and FC > 1), and grey dots are nonsignificant. Top 15 upregulated and 15 downregulated lipid species are annotated and listed by class and composition.
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Lipidomic profiling of extracellular vesicles (EVs) from lean and obese individuals. (A) Unsupervised hierarchical clustering heatmap of lipidomic profiles from EVs isolated from lean and obese individuals. The analysis was performed using MetaboAnalyst 5.0 based on normalized lipid abundance values. Each column represents an individual sample (blue for lean, pink for obese), and each row corresponds to a lipid species. Color scale indicates Z‐score–normalized relative abundance, with blue representing lower levels and brown indicating higher levels. (B, C) Quantification of major lipid classes in EVs from lean and obese individuals. (B) Levels of specific lipid species—including triacylglycerol (TAG), free fatty acids <t>(FA),</t> <t>lysophosphatidylcholine</t> <t>(LPC),</t> lysophosphatidylethanolamine (LPE), phosphatidic acid (PA), phosphatidylcholine (PC), phosphatidylserine (PS), and sphingomyelin (SM)—were measured from EVs derived from pooled adipocyte isolates in each group (n = 5 per group). (C) Lipid class quantification in EVs from individual patients ( n = 4‐5 per group), showing interindividual variation. Data are normalized to total EV protein (p or n mol/mg protein). Data are presented as mean ± SEM; two‐tailed t‐test; *, increase; # , decrease; compared with the corresponding controls, * /# p < 0.05, and ** /## p < 0.01. (D,E) Simplified Manhattan plots of lipid class alterations between obese and lean EVs (including Lean 1). (D) Fold changes (log₁₀[Obese/Lean]) of individual lipid classes stratified by lipid species. Each dot represents a detected lipid species, color‐coded by class. (E) Statistical significance (−log₁₀ P value) of lipid class differences calculated based on unpaired two‐tailed t ‐tests using raw lipidomic concentrations from lean and obese individuals. Notable classes such as FAC, TAG, PC, LPC, and PA exhibit significant alterations in fold change and/or p ‐value distribution. (F) Lipid–lipid correlation heatmap of EV lipidomic profiles from lean and obese individuals. Pairwise correlations between lipid species were calculated using MetaboAnalyst 5.0 based on combined datasets from both groups. The color scale represents the Pearson correlation coefficient, ranging from –0.5 (purple, negative correlation) to 1.0 (yellow, strong positive correlation). Hierarchical clustering was applied to group lipid species with similar covariation patterns, revealing distinct lipid modules and potential coregulatory networks. Ten major lipid clusters (a–j) were identified, each outlined and annotated with representative lipid classes on the right. Key lipid species contributing to each cluster are summarized and compared between obese and lean groups in the accompanying Supporting Information Tables 4 and . Fold‐change (obese/lean) values for each lipid species are also shown as a grayscale bar (FC O/L) adjacent to the cluster annotation, highlighting cluster‐specific lipid alterations associated with obesity. (G) Partial least squares discriminant analysis (PLS‐DA) plots showing lipid class–specific separation between EVs from lean and obese individuals (including Lean 1). EV lipidomic data were analyzed with individual patient samples as input. Samples from lean and obese subjects are shown in blue and brown, respectively, with ellipses representing 95% confidence intervals. The percentage of explained variance for the first and second components (T score [1] and orthogonal T score [1]) is indicated in parentheses. (H) Volcano plot identifying differentially abundant lipid species between obese and lean EVs. Each dot represents a lipid species, plotted by log 2 (fold change Obese/Lean) on the x ‐axis and −log₁₀(P value) on the y ‐axis. Blue dots indicate significantly downregulated species in obesity ( p < 0.05 and FC < −1), red dots represent significantly upregulated species ( p < 0.05 and FC > 1), and grey dots are nonsignificant. Top 15 upregulated and 15 downregulated lipid species are annotated and listed by class and composition.
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Lipidomic profiling of extracellular vesicles (EVs) from lean and obese individuals. (A) Unsupervised hierarchical clustering heatmap of lipidomic profiles from EVs isolated from lean and obese individuals. The analysis was performed using MetaboAnalyst 5.0 based on normalized lipid abundance values. Each column represents an individual sample (blue for lean, pink for obese), and each row corresponds to a lipid species. Color scale indicates Z‐score–normalized relative abundance, with blue representing lower levels and brown indicating higher levels. (B, C) Quantification of major lipid classes in EVs from lean and obese individuals. (B) Levels of specific lipid species—including triacylglycerol (TAG), free fatty acids <t>(FA),</t> <t>lysophosphatidylcholine</t> <t>(LPC),</t> lysophosphatidylethanolamine (LPE), phosphatidic acid (PA), phosphatidylcholine (PC), phosphatidylserine (PS), and sphingomyelin (SM)—were measured from EVs derived from pooled adipocyte isolates in each group (n = 5 per group). (C) Lipid class quantification in EVs from individual patients ( n = 4‐5 per group), showing interindividual variation. Data are normalized to total EV protein (p or n mol/mg protein). Data are presented as mean ± SEM; two‐tailed t‐test; *, increase; # , decrease; compared with the corresponding controls, * /# p < 0.05, and ** /## p < 0.01. (D,E) Simplified Manhattan plots of lipid class alterations between obese and lean EVs (including Lean 1). (D) Fold changes (log₁₀[Obese/Lean]) of individual lipid classes stratified by lipid species. Each dot represents a detected lipid species, color‐coded by class. (E) Statistical significance (−log₁₀ P value) of lipid class differences calculated based on unpaired two‐tailed t ‐tests using raw lipidomic concentrations from lean and obese individuals. Notable classes such as FAC, TAG, PC, LPC, and PA exhibit significant alterations in fold change and/or p ‐value distribution. (F) Lipid–lipid correlation heatmap of EV lipidomic profiles from lean and obese individuals. Pairwise correlations between lipid species were calculated using MetaboAnalyst 5.0 based on combined datasets from both groups. The color scale represents the Pearson correlation coefficient, ranging from –0.5 (purple, negative correlation) to 1.0 (yellow, strong positive correlation). Hierarchical clustering was applied to group lipid species with similar covariation patterns, revealing distinct lipid modules and potential coregulatory networks. Ten major lipid clusters (a–j) were identified, each outlined and annotated with representative lipid classes on the right. Key lipid species contributing to each cluster are summarized and compared between obese and lean groups in the accompanying Supporting Information Tables 4 and . Fold‐change (obese/lean) values for each lipid species are also shown as a grayscale bar (FC O/L) adjacent to the cluster annotation, highlighting cluster‐specific lipid alterations associated with obesity. (G) Partial least squares discriminant analysis (PLS‐DA) plots showing lipid class–specific separation between EVs from lean and obese individuals (including Lean 1). EV lipidomic data were analyzed with individual patient samples as input. Samples from lean and obese subjects are shown in blue and brown, respectively, with ellipses representing 95% confidence intervals. The percentage of explained variance for the first and second components (T score [1] and orthogonal T score [1]) is indicated in parentheses. (H) Volcano plot identifying differentially abundant lipid species between obese and lean EVs. Each dot represents a lipid species, plotted by log 2 (fold change Obese/Lean) on the x ‐axis and −log₁₀(P value) on the y ‐axis. Blue dots indicate significantly downregulated species in obesity ( p < 0.05 and FC < −1), red dots represent significantly upregulated species ( p < 0.05 and FC > 1), and grey dots are nonsignificant. Top 15 upregulated and 15 downregulated lipid species are annotated and listed by class and composition.
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Lipidomic profiling of extracellular vesicles (EVs) from lean and obese individuals. (A) Unsupervised hierarchical clustering heatmap of lipidomic profiles from EVs isolated from lean and obese individuals. The analysis was performed using MetaboAnalyst 5.0 based on normalized lipid abundance values. Each column represents an individual sample (blue for lean, pink for obese), and each row corresponds to a lipid species. Color scale indicates Z‐score–normalized relative abundance, with blue representing lower levels and brown indicating higher levels. (B, C) Quantification of major lipid classes in EVs from lean and obese individuals. (B) Levels of specific lipid species—including triacylglycerol (TAG), free fatty acids <t>(FA),</t> <t>lysophosphatidylcholine</t> <t>(LPC),</t> lysophosphatidylethanolamine (LPE), phosphatidic acid (PA), phosphatidylcholine (PC), phosphatidylserine (PS), and sphingomyelin (SM)—were measured from EVs derived from pooled adipocyte isolates in each group (n = 5 per group). (C) Lipid class quantification in EVs from individual patients ( n = 4‐5 per group), showing interindividual variation. Data are normalized to total EV protein (p or n mol/mg protein). Data are presented as mean ± SEM; two‐tailed t‐test; *, increase; # , decrease; compared with the corresponding controls, * /# p < 0.05, and ** /## p < 0.01. (D,E) Simplified Manhattan plots of lipid class alterations between obese and lean EVs (including Lean 1). (D) Fold changes (log₁₀[Obese/Lean]) of individual lipid classes stratified by lipid species. Each dot represents a detected lipid species, color‐coded by class. (E) Statistical significance (−log₁₀ P value) of lipid class differences calculated based on unpaired two‐tailed t ‐tests using raw lipidomic concentrations from lean and obese individuals. Notable classes such as FAC, TAG, PC, LPC, and PA exhibit significant alterations in fold change and/or p ‐value distribution. (F) Lipid–lipid correlation heatmap of EV lipidomic profiles from lean and obese individuals. Pairwise correlations between lipid species were calculated using MetaboAnalyst 5.0 based on combined datasets from both groups. The color scale represents the Pearson correlation coefficient, ranging from –0.5 (purple, negative correlation) to 1.0 (yellow, strong positive correlation). Hierarchical clustering was applied to group lipid species with similar covariation patterns, revealing distinct lipid modules and potential coregulatory networks. Ten major lipid clusters (a–j) were identified, each outlined and annotated with representative lipid classes on the right. Key lipid species contributing to each cluster are summarized and compared between obese and lean groups in the accompanying Supporting Information Tables 4 and . Fold‐change (obese/lean) values for each lipid species are also shown as a grayscale bar (FC O/L) adjacent to the cluster annotation, highlighting cluster‐specific lipid alterations associated with obesity. (G) Partial least squares discriminant analysis (PLS‐DA) plots showing lipid class–specific separation between EVs from lean and obese individuals (including Lean 1). EV lipidomic data were analyzed with individual patient samples as input. Samples from lean and obese subjects are shown in blue and brown, respectively, with ellipses representing 95% confidence intervals. The percentage of explained variance for the first and second components (T score [1] and orthogonal T score [1]) is indicated in parentheses. (H) Volcano plot identifying differentially abundant lipid species between obese and lean EVs. Each dot represents a lipid species, plotted by log 2 (fold change Obese/Lean) on the x ‐axis and −log₁₀(P value) on the y ‐axis. Blue dots indicate significantly downregulated species in obesity ( p < 0.05 and FC < −1), red dots represent significantly upregulated species ( p < 0.05 and FC > 1), and grey dots are nonsignificant. Top 15 upregulated and 15 downregulated lipid species are annotated and listed by class and composition.
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Lipidomic profiling of extracellular vesicles (EVs) from lean and obese individuals. (A) Unsupervised hierarchical clustering heatmap of lipidomic profiles from EVs isolated from lean and obese individuals. The analysis was performed using MetaboAnalyst 5.0 based on normalized lipid abundance values. Each column represents an individual sample (blue for lean, pink for obese), and each row corresponds to a lipid species. Color scale indicates Z‐score–normalized relative abundance, with blue representing lower levels and brown indicating higher levels. (B, C) Quantification of major lipid classes in EVs from lean and obese individuals. (B) Levels of specific lipid species—including triacylglycerol (TAG), free fatty acids (FA), lysophosphatidylcholine (LPC), lysophosphatidylethanolamine (LPE), phosphatidic acid (PA), phosphatidylcholine (PC), phosphatidylserine (PS), and sphingomyelin (SM)—were measured from EVs derived from pooled adipocyte isolates in each group (n = 5 per group). (C) Lipid class quantification in EVs from individual patients ( n = 4‐5 per group), showing interindividual variation. Data are normalized to total EV protein (p or n mol/mg protein). Data are presented as mean ± SEM; two‐tailed t‐test; *, increase; # , decrease; compared with the corresponding controls, * /# p < 0.05, and ** /## p < 0.01. (D,E) Simplified Manhattan plots of lipid class alterations between obese and lean EVs (including Lean 1). (D) Fold changes (log₁₀[Obese/Lean]) of individual lipid classes stratified by lipid species. Each dot represents a detected lipid species, color‐coded by class. (E) Statistical significance (−log₁₀ P value) of lipid class differences calculated based on unpaired two‐tailed t ‐tests using raw lipidomic concentrations from lean and obese individuals. Notable classes such as FAC, TAG, PC, LPC, and PA exhibit significant alterations in fold change and/or p ‐value distribution. (F) Lipid–lipid correlation heatmap of EV lipidomic profiles from lean and obese individuals. Pairwise correlations between lipid species were calculated using MetaboAnalyst 5.0 based on combined datasets from both groups. The color scale represents the Pearson correlation coefficient, ranging from –0.5 (purple, negative correlation) to 1.0 (yellow, strong positive correlation). Hierarchical clustering was applied to group lipid species with similar covariation patterns, revealing distinct lipid modules and potential coregulatory networks. Ten major lipid clusters (a–j) were identified, each outlined and annotated with representative lipid classes on the right. Key lipid species contributing to each cluster are summarized and compared between obese and lean groups in the accompanying Supporting Information Tables 4 and . Fold‐change (obese/lean) values for each lipid species are also shown as a grayscale bar (FC O/L) adjacent to the cluster annotation, highlighting cluster‐specific lipid alterations associated with obesity. (G) Partial least squares discriminant analysis (PLS‐DA) plots showing lipid class–specific separation between EVs from lean and obese individuals (including Lean 1). EV lipidomic data were analyzed with individual patient samples as input. Samples from lean and obese subjects are shown in blue and brown, respectively, with ellipses representing 95% confidence intervals. The percentage of explained variance for the first and second components (T score [1] and orthogonal T score [1]) is indicated in parentheses. (H) Volcano plot identifying differentially abundant lipid species between obese and lean EVs. Each dot represents a lipid species, plotted by log 2 (fold change Obese/Lean) on the x ‐axis and −log₁₀(P value) on the y ‐axis. Blue dots indicate significantly downregulated species in obesity ( p < 0.05 and FC < −1), red dots represent significantly upregulated species ( p < 0.05 and FC > 1), and grey dots are nonsignificant. Top 15 upregulated and 15 downregulated lipid species are annotated and listed by class and composition.

Journal: Alzheimer's & Dementia

Article Title: Decoding adipose–brain crosstalk: Distinct lipid cargo in human adipose‐derived extracellular vesicles modulates amyloid aggregation in Alzheimer's disease

doi: 10.1002/alz.70603

Figure Lengend Snippet: Lipidomic profiling of extracellular vesicles (EVs) from lean and obese individuals. (A) Unsupervised hierarchical clustering heatmap of lipidomic profiles from EVs isolated from lean and obese individuals. The analysis was performed using MetaboAnalyst 5.0 based on normalized lipid abundance values. Each column represents an individual sample (blue for lean, pink for obese), and each row corresponds to a lipid species. Color scale indicates Z‐score–normalized relative abundance, with blue representing lower levels and brown indicating higher levels. (B, C) Quantification of major lipid classes in EVs from lean and obese individuals. (B) Levels of specific lipid species—including triacylglycerol (TAG), free fatty acids (FA), lysophosphatidylcholine (LPC), lysophosphatidylethanolamine (LPE), phosphatidic acid (PA), phosphatidylcholine (PC), phosphatidylserine (PS), and sphingomyelin (SM)—were measured from EVs derived from pooled adipocyte isolates in each group (n = 5 per group). (C) Lipid class quantification in EVs from individual patients ( n = 4‐5 per group), showing interindividual variation. Data are normalized to total EV protein (p or n mol/mg protein). Data are presented as mean ± SEM; two‐tailed t‐test; *, increase; # , decrease; compared with the corresponding controls, * /# p < 0.05, and ** /## p < 0.01. (D,E) Simplified Manhattan plots of lipid class alterations between obese and lean EVs (including Lean 1). (D) Fold changes (log₁₀[Obese/Lean]) of individual lipid classes stratified by lipid species. Each dot represents a detected lipid species, color‐coded by class. (E) Statistical significance (−log₁₀ P value) of lipid class differences calculated based on unpaired two‐tailed t ‐tests using raw lipidomic concentrations from lean and obese individuals. Notable classes such as FAC, TAG, PC, LPC, and PA exhibit significant alterations in fold change and/or p ‐value distribution. (F) Lipid–lipid correlation heatmap of EV lipidomic profiles from lean and obese individuals. Pairwise correlations between lipid species were calculated using MetaboAnalyst 5.0 based on combined datasets from both groups. The color scale represents the Pearson correlation coefficient, ranging from –0.5 (purple, negative correlation) to 1.0 (yellow, strong positive correlation). Hierarchical clustering was applied to group lipid species with similar covariation patterns, revealing distinct lipid modules and potential coregulatory networks. Ten major lipid clusters (a–j) were identified, each outlined and annotated with representative lipid classes on the right. Key lipid species contributing to each cluster are summarized and compared between obese and lean groups in the accompanying Supporting Information Tables 4 and . Fold‐change (obese/lean) values for each lipid species are also shown as a grayscale bar (FC O/L) adjacent to the cluster annotation, highlighting cluster‐specific lipid alterations associated with obesity. (G) Partial least squares discriminant analysis (PLS‐DA) plots showing lipid class–specific separation between EVs from lean and obese individuals (including Lean 1). EV lipidomic data were analyzed with individual patient samples as input. Samples from lean and obese subjects are shown in blue and brown, respectively, with ellipses representing 95% confidence intervals. The percentage of explained variance for the first and second components (T score [1] and orthogonal T score [1]) is indicated in parentheses. (H) Volcano plot identifying differentially abundant lipid species between obese and lean EVs. Each dot represents a lipid species, plotted by log 2 (fold change Obese/Lean) on the x ‐axis and −log₁₀(P value) on the y ‐axis. Blue dots indicate significantly downregulated species in obesity ( p < 0.05 and FC < −1), red dots represent significantly upregulated species ( p < 0.05 and FC > 1), and grey dots are nonsignificant. Top 15 upregulated and 15 downregulated lipid species are annotated and listed by class and composition.

Article Snippet: For the lipid details, sodium oleate (Sigma, #07501), sodium palmitate (Sigma, #P9767), Brain SM (Avanti, #860062P), egg SM (Avanti, #860061P), milk SM (Avanti, #860063P), egg lysophosphatidylcholine (LPC) (Lyso PC; Avanti, #830071P), 18:0 LPC (Lyso PC; Avanti, #855775), 16:0‐20:4 phosphatidylethanolamine (PE) (Avanti, #850759C), 16:0‐18:1 PE (Avanti, #850757P), C18(Plasm)‐18:1 PE (Avanti, #852758P), and C18(Plasm)‐20:4 PE in ethanol (Cayman, #37137).

Techniques: Isolation, Derivative Assay, Two Tailed Test

Experimental kinetics of amyloid‐β (Aβ) aggregation in the presence of egg lysophosphatidylcholine (LPC; Lyso PC). (A) Molecular structure of lipids of egg Lyso PC and 18:0 Lyso PC. (B‐E) Experimental kinetics for Aβ40 and Aβ42 aggregation under varying concentrations of LPC (16:0). (B and D) Aggregation kinetics of Aβ40 and Aβ42 in the presence of serially diluted LPC (16:0) (0.1–100 mM), using the ThT fluorescence assay. Fluorescence intensity is shown as relative fluorescence units (RFU) at Ex/Em = 440/484 nm. Positive control: Aβ40 or Aβ42 + ThT; negative control: Aβ40 or Aβ42 + ThT + phenol red + morin. (C, E) Quantification of aggregation kinetics at varying concentrations. Each dot represents an individual fluorescence measurement (RFU) at a specific time point for the indicated lipid concentration. Bars indicate the mean ± SEM for each group. Asterisks (*) and hash symbols (#) indicate statistical significance compared to the Positive control group. Statistical approach consistent with Methods Section , with significance thresholds as follows: *, increase; # , decrease; p > 0.05 (ns), p < 0.05 (* /# ), p < 0.01 (** /## ), p < 0.001 (*** /### ), and p < 0.0001 (**** /#### ).

Journal: Alzheimer's & Dementia

Article Title: Decoding adipose–brain crosstalk: Distinct lipid cargo in human adipose‐derived extracellular vesicles modulates amyloid aggregation in Alzheimer's disease

doi: 10.1002/alz.70603

Figure Lengend Snippet: Experimental kinetics of amyloid‐β (Aβ) aggregation in the presence of egg lysophosphatidylcholine (LPC; Lyso PC). (A) Molecular structure of lipids of egg Lyso PC and 18:0 Lyso PC. (B‐E) Experimental kinetics for Aβ40 and Aβ42 aggregation under varying concentrations of LPC (16:0). (B and D) Aggregation kinetics of Aβ40 and Aβ42 in the presence of serially diluted LPC (16:0) (0.1–100 mM), using the ThT fluorescence assay. Fluorescence intensity is shown as relative fluorescence units (RFU) at Ex/Em = 440/484 nm. Positive control: Aβ40 or Aβ42 + ThT; negative control: Aβ40 or Aβ42 + ThT + phenol red + morin. (C, E) Quantification of aggregation kinetics at varying concentrations. Each dot represents an individual fluorescence measurement (RFU) at a specific time point for the indicated lipid concentration. Bars indicate the mean ± SEM for each group. Asterisks (*) and hash symbols (#) indicate statistical significance compared to the Positive control group. Statistical approach consistent with Methods Section , with significance thresholds as follows: *, increase; # , decrease; p > 0.05 (ns), p < 0.05 (* /# ), p < 0.01 (** /## ), p < 0.001 (*** /### ), and p < 0.0001 (**** /#### ).

Article Snippet: For the lipid details, sodium oleate (Sigma, #07501), sodium palmitate (Sigma, #P9767), Brain SM (Avanti, #860062P), egg SM (Avanti, #860061P), milk SM (Avanti, #860063P), egg lysophosphatidylcholine (LPC) (Lyso PC; Avanti, #830071P), 18:0 LPC (Lyso PC; Avanti, #855775), 16:0‐20:4 phosphatidylethanolamine (PE) (Avanti, #850759C), 16:0‐18:1 PE (Avanti, #850757P), C18(Plasm)‐18:1 PE (Avanti, #852758P), and C18(Plasm)‐20:4 PE in ethanol (Cayman, #37137).

Techniques: Fluorescence, Positive Control, Negative Control, Concentration Assay