Kjærgaard J et al., Cell - This episode reviews a study that links in vivo insulin sensitivity phenotyping with proteome and signaling-pathway mapping to define molecular-phenotype associations across heterogeneous populations. The paper emphasizes population heterogeneity and maps proteomic signatures to functional signaling pathways associated with insulin sensitivity. Key terms: population heterogeneity, insulin sensitivity, proteome mapping, signaling pathways, molecular-phenotype association.
Study Highlights:
The study performs in vivo insulin sensitivity phenotyping alongside proteome mapping and signaling pathway mapping to characterize molecular-phenotype associations. It highlights population heterogeneity as a central feature influencing phenotype–molecular links. The authors present maps connecting proteomic signatures and signaling pathways to variation in insulin sensitivity across cohorts.
Conclusion:
Proteome and signaling-pathway mapping integrated with in vivo insulin sensitivity phenotyping reveals molecular-phenotype associations and underscores population heterogeneity.
Music:
Enjoy the music based on this article at the end of the episode.
Article title:
Personalized molecular signatures of insulin resistance and type 2 diabetes
First author:
Kjærgaard J
Journal:
Cell
DOI:
10.1016/j.cell.2025.05.005
Reference:
Kjærgaard J., Stocks B., Henderson J., Freemantle J.B., Rizo-Roca D., Puglia M., et al.. Personalized molecular signatures of insulin resistance and type 2 diabetes. Cell, 188, 4106-4122.e16. (2025). https://doi.org/10.1016/j.cell.2025.05.005
License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/
Support:
Base by Base – Stripe donations: https://donate.stripe.com/7sY4gz71B2sN3RWac5gEg00
Official website https://basebybase.com
On PaperCast Base by Base you'll discover the latest in genomics, functional genomics, structural genomics, and proteomics.
Episode link: https://basebybase.com/episodes/population-heterogeneity-insulin-proteome-signaling-mapping
QC:
This episode was checked against the original article PDF and publication metadata for the episode release published on 2025-06-11.
QC Scope:
- article metadata and core scientific claims from the narration
- excludes analogies, intro/outro, and music
- transcript coverage: Substantive audit of the transcript's core scientific narrative: insulin resistance in skeletal muscle, clamp methodology, proteomics/phosphoproteomics mapping, continuous molecular signatures vs binary labels, baseline proteome predictive power, LDHA/LDHB dynamics, S65 AMPK gamma3 phosphorylation, JNK-P38 stress signa
- transcript topics: Skeletal muscle insulin resistance paradox and continuous phenotype spectrum; Hyperinsulinemic-euglycemic clamp methodology and M value; DIA-based proteomics and phosphorylation mapping (proteome >3000 proteins; ~29000 phosphosites); Baseline (fasting) proteome as predictor of insulin sensitivity; LDHA/LDHB glycolytic vs oxidative enzyme balance; S65 phosphorylation on AMPK gamma 3 as a predictor and human-specific site; pig mutation context
QC Summary:
- factual score: 10/10
- metadata score: 10/10
- supported core claims: 6
- claims flagged for review: 0
- metadata checks passed: 4
- metadata issues found: 0
Metadata Audited:
- article_doi
- article_title
- article_journal
- license
Factual Items Audited:
- Discovery and validation cohorts: 77 and 46 participants respectively
- Hyperinsulinemic-euglycemic clamp used to measure insulin resistance; M value derived
- Continuous molecular spectrum that correlates with M value, not binary diabetic vs. healthy labels
- Baseline fasting muscle proteome predicts whole-body insulin sensitivity, outperforming HbA1c
- >3,000 distinct muscle proteins mapped; ~29,000 phosphorylation sites quantified
- LDHA/LDHB protein ratio correlates with insulin resistance (glycolytic vs oxidative bias)
QC result: Pass.
Fler avsnitt av Base by Base
Visa alla avsnitt av Base by BaseBase by Base med Gustavo Barra finns tillgänglig på flera plattformar. Informationen på denna sida kommer från offentliga podd-flöden.
