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Metformin modifies plasma microbial-derived extracellular vesicles in polycystic ovary syndrome with insulin resistance Original paper

Researched by:

  • Dr. Umar ID
    Dr. Umar

    User avatarClinical Pharmacist and Clinical Pharmacy Master’s candidate focused on antibiotic stewardship, AI-driven pharmacy practice, and research that strengthens safe and effective medication use. Experience spans digital health research with Bloomsbury Health (London), pharmacovigilance in patient support programs, and behavioral approaches to mental health care. Published work includes studies on antibiotic use and awareness, AI applications in medicine, postpartum depression management, and patient safety reporting. Developer of an AI-based clinical decision support system designed to enhance antimicrobial stewardship and optimize therapeutic outcomes.

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November 22, 2025

Researched by:

  • Dr. Umar ID
    Dr. Umar

    User avatarClinical Pharmacist and Clinical Pharmacy Master’s candidate focused on antibiotic stewardship, AI-driven pharmacy practice, and research that strengthens safe and effective medication use. Experience spans digital health research with Bloomsbury Health (London), pharmacovigilance in patient support programs, and behavioral approaches to mental health care. Published work includes studies on antibiotic use and awareness, AI applications in medicine, postpartum depression management, and patient safety reporting. Developer of an AI-based clinical decision support system designed to enhance antimicrobial stewardship and optimize therapeutic outcomes.

    Read More

Last Updated: 2024-01-01

Microbiome Signatures identifies and validates condition-specific microbiome shifts and interventions to accelerate clinical translation. Our multidisciplinary team supports clinicians, researchers, and innovators in turning microbiome science into actionable medicine.

Karen Pendergrass

Karen Pendergrass is a microbiome researcher specializing in microbiome-targeted interventions (MBTIs). She systematically analyzes scientific literature to identify microbial patterns, develop hypotheses, and validate interventions. As the founder of the Microbiome Signatures Database, she bridges microbiome research with clinical practice. In 2012, based on her own investigative research, she became the first documented case of FMT for Celiac Disease—four years before the first published case study.

Location
China
Sample Site
Blood plasma
Species
Homo sapiens

What was studied?

This study investigated metformin plasma microbial EVs by analyzing how metformin treatment alters plasma microbial-derived extracellular vesicles (EVs) in women with polycystic ovary syndrome and insulin resistance (PCOS-IR). Using full-length 16S rRNA sequencing, the researchers characterized microbial composition, diversity, and taxonomic shifts in circulating EVs before and after three months of metformin therapy. The goal was to determine whether specific microbial taxa within plasma EVs could serve as biomarkers of treatment response or illuminate mechanistic connections between microbiota-derived signaling and PCOS-related metabolic dysfunction. By focusing on EV-associated DNA rather than whole-microbiome samples, the authors attempted to capture biologically active microbial signals capable of translocating systemically and influencing host physiology.

Who was studied?

Five women of childbearing age diagnosed with PCOS-IR according to Chinese national guidelines were recruited. All participants exhibited hyperglycemia and insulin resistance (HOMA-IR ≥2.7) and had not used metformin, antibiotics, probiotics, antihistamines, or steroids in the six months prior to enrollment. Plasma samples were collected before treatment and again following three months of metformin therapy (500 mg/day in divided doses). Although the final sample size was small due to dropouts and sequencing failures, paired before-and-after analyses allowed direct comparison of individual microbial EV signatures across treatment.

Most important findings

Metformin significantly improved fasting plasma glucose and insulin resistance, while EV-associated microbial diversity increased after treatment. Alpha diversity (Simpson, Berger-Parker, Shannoneven, Simpsoneven) and beta-diversity analyses showed clear separation between pre- and post-treatment EV communities.

At multiple taxonomic levels, key microbial shifts emerged:

LevelIncreased Before TreatmentIncreased After Treatment
PhylumBacteroidota, CyanobacteriaProteobacteria
OrderPseudomonadales, XanthomonadalesRhizobiales, Burkholderiales, Lactobacillales
GenusAcinetobacter, FlavobacteriumMethylobacterium, Sphingomonas, Streptococcus
SpeciesAcinetobacter nosocomialis, Eubacterium rectaleRalstonia mannitoligenes, Methylobacterium organophilum, Streptococcus salivarius

The most clinically relevant microbial change was the dramatic increase in Streptococcus salivarius–derived EVs, rising from 0.03% to 4.33% after metformin treatment. Known for beneficial metabolic effects in prior probiotic trials, S. salivarius may represent a microbiome-linked mechanism through which metformin improves metabolic parameters. Environmental microbial EVs (e.g., Sphingobacterium hotanense, Bradyrhizobium) also shifted, though their biological relevance remains uncertain due to low abundance.

Key implications

These results suggest that metformin’s metabolic benefits in PCOS-IR may be partly mediated through alterations in systemic microbial EV signaling, particularly through increases in potentially probiotic taxa such as Streptococcus salivarius. Plasma EV profiling may provide a sensitive, functionally relevant snapshot of host-microbiome interactions and could serve as a biomarker platform for PCOS-IR treatment monitoring. Larger studies are needed, but the findings support the concept that circulating microbial EVs participate in endocrine-metabolic regulation and may reveal therapeutic targets or diagnostic signatures for metabolic dysfunction in PCOS.

Citation

Hu L, Hong G, Li J, et al. Metformin modifies plasma microbial-derived extracellular vesicles in polycystic ovary syndrome with insulin resistance.Journal of Ovarian Research. 2024;17:136. doi:10.1186/s13048-024-01444-x

Polycystic ovary syndrome (PCOS)

Polycystic ovary syndrome (PCOS) is a common endocrine disorder that affects women of reproductive age, characterized by irregular menstrual cycles, hyperandrogenism, and insulin resistance. It is often associated with metabolic dysfunctions and inflammation, leading to fertility issues and increased risk of type 2 diabetes and cardiovascular disease.

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