732-P: Biomarkers of Inflammation and Long-Term Microvasculature Integrity in Weight Loss–Induced Prediabetes Remission
Bibliographic record
Abstract
The Diabetes Prevention Program Outcomes Study demonstrated that even temporary resolution of prediabetes (remission) to normal glucose regulation (NGR) prevents development of T2D and vascular complications. However, cellular mechanisms are unknown. We have previously shown in the Prediabetes Lifestyle Intervention Study, a German Center for Diabetes Research multicenter study (n = 1105), that lifestyle intervention (LI)-mediated weight loss-induced remission of prediabetes to NGR vs. non-remission is largely driven by improved insulin sensitivity. We hypothesized that these two groups differ by markers of chronic low-grade inflammation. Therefore, we analyzed 31 cytokines implicated in energy metabolism and T2D complications before and after LI in subjects losing ≥5% body weight (n = 113) to compare responders achieving NGR (R, n = 40) to non-responders not achieving NGR (NR, n = 73). Cytokines linked to insulin resistance and T2D such as TNF-α (p = 0.73), IFNγ (p = 0.45) and IL-6 (p = 0.34) did not differ between groups. However, responders showed a significantly stronger reduction of lymphotoxin α (LTα, -0.15 ± 0.29-fold in NR vs. -0.23 ± 0.32 in R, p = 0.02). VCAM (-0.04 ± 0.14 NR vs. -0.08 ±10.9 R, p = 0.02) and ICAM (-0.11 ±0.15 NR vs. -0.16 ± 0.14 R, p = 0.02), which are induced by LTα and have been implied in mediating cardiovascular complications, were also more strongly reduced in responders. To assess if this is linked with long-term microvasculature integrity, we applied optoacoustic mesoscopy up to 5 years after LI (n = 22). Total vessel and junction density and number of junction to endpoint branches (NJEB) were higher in responders at follow-up (NJEB: 154.9 ± 25.3 vs. 186.9 ± 16.1, p < 0.01). These data describe a distinct pattern of reduced low-grade inflammation characterizing remission of prediabetes to NGR. Although limited by low n, this pattern may help explain the positive effects of prediabetes remission on vascular complications. Disclosure A.Sandforth: None. J.Szendroedi: None. S.M.Meyhöfer: Speaker's Bureau; Novo Nordisk, AstraZeneca, Lilly, Amgen Inc., Boehringer-Ingelheim, Novartis. M.Roden: Advisory Panel; Eli Lilly and Company, Consultant; TARGET PharmaSolutions, Inc., Research Support; Boehringer-Ingelheim, Novo Nordisk, Novartis, Sanofi. L.Fritsche: None. N.Stefan: Advisory Panel; Pfizer Inc., Research Support; Sanofi, Speaker's Bureau; AstraZeneca, Boehringer Ingelheim (Canada) Ltd., Lilly Diabetes, Novo Nordisk, Sanofi-Aventis Deutschland GmbH. R.Wagner: Advisory Panel; Daiichi Sankyo, Speaker's Bureau; Novo Nordisk, Sanofi. A.Fritsche: Advisory Panel; Novo Nordisk, Lilly, Sanofi, Boehringer-Ingelheim, Speaker's Bureau; AstraZeneca, SYNLAB Holding Deutschland GmbH. R.Jumpertz von schwartzenberg: Other Relationship; Sanofi, Amgen Inc., Lilly, Novo Nordisk. A.L.Birkenfeld: None. S.Katzenstein: None. J.Seissler: None. S.R.Bornstein: None. N.Perakakis: Advisory Panel; Bayer Inc., Other Relationship; Novo Nordisk, Novo Nordisk. S.Kabisch: Other Relationship; Berlin-Chemie AG, Sanofi, Lilly, Boehringer Ingelheim Inc., JuZo Akademie, Research Support; J. Rettenmaier / Söhne, Wilhelm-Doerenkamp Foundation, German Center of Diabetes Research. A.F.Pfeiffer: Advisory Panel; Abbott Diabetes, Speaker's Bureau; Novo Nordisk, Sanofi-Aventis Deutschland GmbH. H.Häring: None. M.Blüher: Advisory Panel; Boehringer Ingelheim Inc., Lilly, Novo Nordisk, Consultant; Novo Nordisk Foundation, Speaker's Bureau; Amgen Inc., AstraZeneca, Bayer Inc., Daiichi Sankyo, Novartis, Sanofi-Aventis Deutschland GmbH.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".