bims-obesme 2026-08-23 papers

Issue of 2026–08–23
six papers selected by
Xiong Weng, University of Edinburgh

Sci Adv. 2026 Aug 21. 12(34): eaec7066

Sphingosine kinase 2 regulates adipocyte browning and whole-body metabolism.

Ryan D R Brown, Cynthia Weigel, Yadu Vijayan, Katarzyna M Tyc, Christiane Carter, Christopher D Green, Sarah Spiegel.

Obesity increases circulating levels of the bioactive sphingolipid metabolite sphingosine-1-phosphate (S1P). Here, we identify adipocyte-expressed sphingosine kinase 2 (SPHK2), an enzyme that produces S1P, as a regulator of adipose tissue browning. Mice with adipocyte-specific deletion of Sphk2 were protected from Western diet-induced obesity concomitantly with elevated energy expenditure and browning of subcutaneous fat. Sphk2 deletion also enhanced expression of Ucp1 and key thermogenic genes, resulting in reduced adiposity and hepatic steatosis, improved glucose tolerance, and insulin sensitivity. Mechanistically, obesogenic diet promoted nuclear localization of SPHK2 in adipocytes, where it cooperated with transcription factors to suppress the thermogenic transcriptome. Adipocyte SPHK2 contributes to homeostatic circulating S1P levels and drive the pathogenic rise of S1P in response to obesogenic diet. Our findings reveal a distinct role of adipocyte SPHK2 in regulation of the thermogenic program important for whole-body metabolic homeostasis and energy expenditure, highlighting SPHK2 as a potential therapeutic target for treatment of metabolic disorders.

DOI: https://doi.org/10.1126/sciadv.aec7066

Nat Metab. 2026 Aug 21.

Multi-organ proteomic atlas of obesity regression in male mice.

Felix Boel, Ellen Gammelmark Klinggaard, Vyacheslav Akimov, Daniel Hansen, M L Uthpala, Babukrishna Maniyadath, Flora Reincke Fuglsang, Marc Pielies Avellí, Simon Rasmussen, Kim Ravnskjær, Susanne Mandrup, Blagoy Blagoev.

Obesity drives systemic metabolic dysfunction, yet how the body adapts and recovers at a system-wide level remains unclear. Here we generate a multi-organ proteomic atlas of diet-induced obesity and its regression in male mice. Using a standardized, semi-automated sample preparation workflow, we quantify 12,936 unique proteins across 15 organs and four timepoints. We find proteomic changes to be highly tissue-dependent, with a small number of proteins displaying shared changes across multiple tissues. While proteomes of most tissues revert to lean levels after weight loss, white adipose tissue retains strong phagocytic and inflammatory responses, and the brain, kidney, bone, thymus and spleen display delayed obesity-induced alterations. We map the adipose tissue-specific immune regulators using ligand-target inference and show reduced expression of proteasomal subunits in brown adipose tissue, resulting in stalled ubiquitin turnover. Finally, we make all datasets open access and create an interactive webtool to facilitate further community-driven discovery.

DOI: https://doi.org/10.1038/s42255-026-01599-5

Nat Med. 2026 Aug 21.

Responsiveness of epigenetic aging biomarkers to longevity interventions in humans.

Raghav Sehgal, Daniel Borrus, Jenel F Armstrong, John Gonzalez, Jessica Kasamoto, Yaroslav Markov, Ahana Priyanka, Ryan Smith, Natàlia Carreras-Gallo, Jessica Lasky-Su, Varun B Dwaraka, Michael J Corley, Albert Higgins-Chen.

Aging biomarkers can potentially allow researchers to rapidly monitor the impact of an aging intervention without the need for decade-spanning trials. However, before the use of aging biomarkers, such as epigenetic clocks, as surrogate endpoints, their responsiveness to interventions that target aging must be tested. Here we curate TranslAGE, a harmonized database of 51 public and private longitudinal interventional studies, and calculate a consistent set of 16 prominent epigenetic clocks for each study, along with 94 other DNA methylation (DNAm) biomarkers that can help explain the changes observed for each clock. Using this database, we discover patterns of responsiveness across a variety of interventions and DNAm biomarkers. For example, clocks trained to predict mortality or pace of aging show the strongest responses across all interventions and show consistent results with one another; pharmacological and lifestyle interventions drive the strongest responses from DNAm biomarkers; and the characteristics of the study population and study duration are key factors in determining the responsiveness of DNAm biomarkers to an intervention. Moreover, clocks with multiple subscores (that is 'explainable clocks') provide specificity and greater mechanistic insight into the responsiveness of interventions than single-score clocks. These findings can help to design future clinical trials by guiding the choice of interventions and of specific subsets of DNAm biomarkers to minimize multiple testing, study duration, study population and sample size, with the eventual aim of uncovering DNAm biomarkers that can be used as surrogate aging endpoints.

DOI: https://doi.org/10.1038/s41591-026-04562-9

Cell Metab. 2026 Aug 17. pii: S1550-4131(26)00330-X. [Epub ahead of print]

Protein restriction and the hallmarks of aging: A coordinated physiological adaptive response?

Sora Q Kim, Sangho Yu, Christopher D Morrison.

Protein restriction extends lifespan across species and engages many hallmarks of aging. We propose that these diverse responses can be understood as components of a single coordinated physiological state. This response involves both cellular nutrient sensing and endocrine and neural coordination, with enhanced longevity emerging from this adaptive response.

DOI: https://doi.org/10.1016/j.cmet.2026.08.005

Nat Genet. 2026 Aug 17.

Rare variant effect estimation and polygenic risk prediction.

Kisung Nam, Minjung Kho, Wei Zhou, Bhramar Mukherjee, Seunggeun Lee.

Due to their low frequency, estimating the effects of rare variants is challenging. Here we propose RareEffect, a method that first estimates gene-based or region-based heritability and then each variant effect size using an empirical Bayes approach. Our method uses a variance component model, which is popular in rare variant tests, and is designed to provide two levels of effect sizes-gene/region level and variant level-that can provide better interpretation. To adjust for the case-control imbalance in phenotypes, our approach uses a fast implementation of the Firth bias correction. We demonstrate the accuracy and computational efficiency of our method through extensive simulations and analysis of UK Biobank whole-exome sequencing data for 100 traits. Additionally, we show that the effect sizes obtained from our model can be leveraged to improve polygenic score performance, thereby outperforming recently developed methods for rare variant polygenic scoring.

DOI: https://doi.org/10.1038/s41588-026-02705-9