Integrative phenotyping of glycemic responders upon clinical weight loss using multi-omics
Abstract Weight loss aims to improve glycemic control in obese but strong variability is observed. Using a multi-omics approach, we investigated differences between 174 responders and 201 non-responders, that had lost >8% body weight following a low-caloric diet (LCD, 800 kcal/d for 8 weeks). The...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2020-06-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-020-65936-8 |
| _version_ | 1818735969887584256 |
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| author | Armand Valsesia Anirikh Chakrabarti Jörg Hager Dominique Langin Wim H. M. Saris Arne Astrup Ellen E. Blaak Nathalie Viguerie Mojgan Masoodi |
| author_facet | Armand Valsesia Anirikh Chakrabarti Jörg Hager Dominique Langin Wim H. M. Saris Arne Astrup Ellen E. Blaak Nathalie Viguerie Mojgan Masoodi |
| author_sort | Armand Valsesia |
| collection | DOAJ |
| description | Abstract Weight loss aims to improve glycemic control in obese but strong variability is observed. Using a multi-omics approach, we investigated differences between 174 responders and 201 non-responders, that had lost >8% body weight following a low-caloric diet (LCD, 800 kcal/d for 8 weeks). The two groups were comparable at baseline for body composition, glycemic control, adipose tissue transcriptomics and plasma ketone bodies. But they differed significantly in their response to LCD, including improvements in visceral fat, overall insulin resistance (IR) and tissue-specific IR. Transcriptomics analyses found down-regulation in key lipogenic genes (e.g. SCD, ELOVL5) in responders relative to non-responders; metabolomics showed increase in ketone bodies; while proteomics revealed differences in lipoproteins. Findings were consistent between genders; with women displaying smaller improvements owing to a better baseline metabolic condition. Integrative analyses identified a plasma omics model that was able to predict non-responders with strong performance (on a testing dataset, the Receiving Operating Curve Area Under the Curve (ROC AUC) was 75% with 95% Confidence Intervals (CI) [67%, 83%]). This model was based on baseline parameters without the need for intrusive measurements and outperformed clinical models (p = 0.00075, with a +14% difference on the ROC AUCs). Our approach document differences between responders and non-responders, with strong contributions from liver and adipose tissues. Differences may be due to de novo lipogenesis, keto-metabolism and lipoprotein metabolism. These findings are useful for clinical practice to better characterize non-responders both prior and during weight loss. |
| first_indexed | 2024-12-18T00:29:42Z |
| format | Article |
| id | doaj.art-b17731f6b55c46028452475f12f8184d |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-12-18T00:29:42Z |
| publishDate | 2020-06-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-b17731f6b55c46028452475f12f8184d2022-12-21T21:27:10ZengNature PortfolioScientific Reports2045-23222020-06-0110111410.1038/s41598-020-65936-8Integrative phenotyping of glycemic responders upon clinical weight loss using multi-omicsArmand Valsesia0Anirikh Chakrabarti1Jörg Hager2Dominique Langin3Wim H. M. Saris4Arne Astrup5Ellen E. Blaak6Nathalie Viguerie7Mojgan Masoodi8Nestlé Institute of Health SciencesNestlé Institute of Health SciencesNestlé Institute of Health SciencesINSERM, UMR 1048, Institute of Metabolic and Cardiovascular DiseasesDepartment of Human Biology, NUTRIM, School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre+(MUMC+)University of Copenhagen, Department of Nutrition, Exercise and Sports, Faculty of ScienceDepartment of Human Biology, NUTRIM, School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre+(MUMC+)INSERM, UMR 1048, Institute of Metabolic and Cardiovascular DiseasesNestlé Institute of Health SciencesAbstract Weight loss aims to improve glycemic control in obese but strong variability is observed. Using a multi-omics approach, we investigated differences between 174 responders and 201 non-responders, that had lost >8% body weight following a low-caloric diet (LCD, 800 kcal/d for 8 weeks). The two groups were comparable at baseline for body composition, glycemic control, adipose tissue transcriptomics and plasma ketone bodies. But they differed significantly in their response to LCD, including improvements in visceral fat, overall insulin resistance (IR) and tissue-specific IR. Transcriptomics analyses found down-regulation in key lipogenic genes (e.g. SCD, ELOVL5) in responders relative to non-responders; metabolomics showed increase in ketone bodies; while proteomics revealed differences in lipoproteins. Findings were consistent between genders; with women displaying smaller improvements owing to a better baseline metabolic condition. Integrative analyses identified a plasma omics model that was able to predict non-responders with strong performance (on a testing dataset, the Receiving Operating Curve Area Under the Curve (ROC AUC) was 75% with 95% Confidence Intervals (CI) [67%, 83%]). This model was based on baseline parameters without the need for intrusive measurements and outperformed clinical models (p = 0.00075, with a +14% difference on the ROC AUCs). Our approach document differences between responders and non-responders, with strong contributions from liver and adipose tissues. Differences may be due to de novo lipogenesis, keto-metabolism and lipoprotein metabolism. These findings are useful for clinical practice to better characterize non-responders both prior and during weight loss.https://doi.org/10.1038/s41598-020-65936-8 |
| spellingShingle | Armand Valsesia Anirikh Chakrabarti Jörg Hager Dominique Langin Wim H. M. Saris Arne Astrup Ellen E. Blaak Nathalie Viguerie Mojgan Masoodi Integrative phenotyping of glycemic responders upon clinical weight loss using multi-omics Scientific Reports |
| title | Integrative phenotyping of glycemic responders upon clinical weight loss using multi-omics |
| title_full | Integrative phenotyping of glycemic responders upon clinical weight loss using multi-omics |
| title_fullStr | Integrative phenotyping of glycemic responders upon clinical weight loss using multi-omics |
| title_full_unstemmed | Integrative phenotyping of glycemic responders upon clinical weight loss using multi-omics |
| title_short | Integrative phenotyping of glycemic responders upon clinical weight loss using multi-omics |
| title_sort | integrative phenotyping of glycemic responders upon clinical weight loss using multi omics |
| url | https://doi.org/10.1038/s41598-020-65936-8 |
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