Evidence map›Paper›PMID 40470351›Full record

ArticleFrontiers in physiology2025

In silico dietary interventions using whole-body metabolic models reveal sex-specific and differential dietary risk profiles for metabolic syndrome.

Drew S Alessi, Chloe V McCreery, Ali R Zomorrodi

Abstract read
In one paragraph

Article in Frontiers in physiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Drew S AlessiGraduate Medical Sciences, Boston University, Boston, MA, United States.
Chloe V McCreeryHarvard Medical School, Boston, MA, United States.
Ali R ZomorrodiDepartment of Pediatrics, Mucosal Immunology and Biology Research Center, Massachusetts General Hospital, Boston, MA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metabolic Syndrome (MetS) is a cluster of metabolic disorders that substantially increases the risk of chronic metabolic diseases. Diet plays a crucial role in MetS progression, yet a mechanistic understanding of its impact on MetS risk remains elusive. To address this gap, we conducted a rigorous in silico diet intervention study by leveraging organ-resolved sex-specific whole-body models of metabolism. These models were utilized to computationally evaluate the effect of 12 diverse dietary regimens on key MetS biomarkers-glucose, triacylglycerol, LDL-C, HDL-C-and fatty acid beta-oxidation in representative male and female subjects. Our analyses elucidated molecular mechanisms underlying the link between conventionally unhealthy diets and elevated MetS risk. Specifically, a typical Unhealthy diet indicated elevated triacylglycerol storage in the adipocytes and increased LDL-C to HDL-C ratios across both genders. Conversely, healthier dietary patterns like the Mediterranean, Balanced, and plant-based diets promoted favorable profiles for these biomarkers. Beyond substantiating these known dietary impacts, our analysis also revealed non-intuitive responses to diet. Notably, Vegan and Vegetarian diets induced elevated fatty acid oxidation compared to high-fat regimens like the Ketogenic diet, suggesting their potential in mitigating MetS risk. In addition to these overall trends, pronounced gender differences in metabolic responses to diets were observed, highlighting the need for gender-tailored dietary recommendations. Organ-specific dietary responses and their contributions to MetS biomarkers were also delineated, pinpointing the liver and lungs as major regulators of blood glucose homeostasis. This study contributes to a deeper understanding of the intricate interactions between diet and MetS risk.

Indexed as

computational modelingdietmetabolic syndromemetabolismwhole-body models

Identifiers

PMID40470351
PMCPMC12133891

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.