Effectiveness of Probiotics, Prebiotics, and Synbiotics in Managing Insulin Resistance and Hormonal Imbalance in Women with Polycystic Ovary Syndrome (PCOS): A Systematic Review of Randomized Clinical Trials

Abstract

Background/Objectives: Polycystic ovary syndrome is a common endocrine disorder in women of reproductive age characterized by insulin resistance and hormonal imbalances. Recent research suggests that probiotics and synbiotics may improve these parameters by modulating the gut microbiota. This study systematically reviewed randomized clinical trials evaluating the impact of probiotic, prebiotic, and synbiotic supplementation on insulin resistance and hormonal parameters in women with PCOS. Methods: Exhaustive searches were conducted in PubMed, Cochrane CENTRAL, Scopus, Web of Science, and Embase, following PRISMA guidelines. Randomized trials assessing supplementation with probiotics, prebiotics, or synbiotics for at least 8 weeks in women diagnosed with PCOS according to the Rotterdam criteria were included. Data on participants, interventions, and outcomes related to insulin resistance and hormones were extracted. Results: Eleven studies from Iran involving overweight or obese women aged 15 to 48 were included. Probiotic and synbiotic supplementation showed significant improvements in insulin resistance (reductions in HOMA-IR, fasting glucose, and insulin), lipid profiles (decreased LDL and triglycerides; increased HDL), and hormonal balance (increased SHBG, decreased total testosterone). Synbiotics had more pronounced effects than probiotics or prebiotics alone. Adherence was high, and side effects were minimal. Conclusions: Despite promising results, limitations such as small sample sizes, homogeneous populations, and short intervention durations limit the generalization of the findings. Larger, longer, multicenter trials with diverse populations and standardized methodologies are needed to confirm the efficacy and safety of synbiotics in managing PCOS. Integrating these interventions could improve clinical management and quality of life for affected women, but additional evidence is required to support widespread use.

Full text

Citation: Martinez Guevara, D.; Vidal
Cañas, S.; Palacios, I.; Gómez, A.;
Estrada, M.; Gallego, J.; Liscano, Y.
Effectiveness of Probiotics, Prebiotics,
and Synbiotics in Managing Insulin
Resistance and Hormonal Imbalance
in Women with Polycystic Ovary
Syndrome (PCOS): A Systematic
Review of Randomized Clinical Trials.
Nutrients 2024,16, 3916. https://
doi.org/10.3390/nu16223916
Academic Editor: Stefano Guandalini
Received: 16 October 2024
Revised: 12 November 2024
Accepted: 14 November 2024
Published: 16 November 2024
Copyright: © 2024 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
Systematic Review
Effectiveness of Probiotics, Prebiotics, and Synbiotics in
Managing Insulin Resistance and Hormonal Imbalance in
Women with Polycystic Ovary Syndrome (PCOS): A Systematic
Review of Randomized Clinical Trials
Darly Martinez Guevara, Sinthia Vidal Cañas, Isabela Palacios, Alejandra Gómez, María Estrada, Jonathan Gallego
and Yamil Liscano *
Grupo de Investigación en Salud Integral (GISI), Departamento Facultad de Salud, Universidad Santiago de Cali,
Cali 5183000, Colombia; darly.martinez00@usc.edu.co (D.M.G.); sinthia.vidal00@usc.edu.co (S.V.C.);
isabela.palacios00@usc.edu.co (I.P.); alejandra.gomez01@usc.edu.co (A.G.); maria.estrada03@usc.edu.co (M.E.);
jhonatan.gallego00@usc.edu.co (J.G.)
*Correspondence: yamil.liscano00@usc.edu.co
Abstract: Background/Objectives: Polycystic ovary syndrome is a common endocrine disorder in
women of reproductive age characterized by insulin resistance and hormonal imbalances. Recent
research suggests that probiotics and synbiotics may improve these parameters by modulating the gut
microbiota. This study systematically reviewed randomized clinical trials evaluating the impact of
probiotic, prebiotic, and synbiotic supplementation on insulin resistance and hormonal parameters in
women with PCOS. Methods: Exhaustive searches were conducted in PubMed, Cochrane CENTRAL,
Scopus, Web of Science, and Embase, following PRISMA guidelines. Randomized trials assessing
supplementation with probiotics, prebiotics, or synbiotics for at least 8 weeks in women diagnosed
with PCOS according to the Rotterdam criteria were included. Data on participants, interventions,
and outcomes related to insulin resistance and hormones were extracted. Results: Eleven studies
from Iran involving overweight or obese women aged 15 to 48 were included. Probiotic and synbiotic
supplementation showed significant improvements in insulin resistance (reductions in HOMA-IR,
fasting glucose, and insulin), lipid profiles (decreased LDL and triglycerides; increased HDL), and
hormonal balance (increased SHBG, decreased total testosterone). Synbiotics had more pronounced
effects than probiotics or prebiotics alone. Adherence was high, and side effects were minimal.
Conclusions: Despite promising results, limitations such as small sample sizes, homogeneous
populations, and short intervention durations limit the generalization of the findings. Larger, longer,
multicenter trials with diverse populations and standardized methodologies are needed to confirm
the efficacy and safety of synbiotics in managing PCOS. Integrating these interventions could improve
clinical management and quality of life for affected women, but additional evidence is required to
support widespread use.
Keywords: probiotics; insulin resistance; hormonal imbalance; polycystic ovary syndrome (PCOS);
gut microbiota; synbiotics; metabolic health; women’s health; systematic review; randomized
controlled trials
1. Introduction
Polycystic ovary syndrome (PCOS) is a prevalent endocrine disorder affecting 5% to
10% of women of reproductive age, characterized by hyperandrogenism, ovulatory dys-
function, and a polycystic ovarian morphology [
1
,
2
]. Diagnosis is commonly based on the
Rotterdam criteria, which require at least two of the following: oligo- or anovulation, clini-
cal and/or biochemical signs of hyperandrogenism, and a polycystic ovarian morphology
detected by ultrasound [
3
–
5
]. PCOS phenotypes (A–D) vary in metabolic profiles and risks.
Hyperandrogenic phenotypes (OD-HA and HA-PCOM) exhibit adverse metabolic profiles,
Nutrients 2024,16, 3916. https://doi.org/10.3390/nu16223916 https://www.mdpi.com/journal/nutrients

Nutrients 2024,16, 3916 2 of 28
including elevated body mass index (BMI), higher waist-to-hip ratio, insulin resistance,
and dyslipidemia, increasing the risk of metabolic syndrome, type 2 diabetes mellitus, and
cardiovascular diseases [
6
–
8
]. Phenotypes lacking hyperandrogenism generally present
more favorable metabolic profiles, though some normoandrogenic women may still face
metabolic challenges.
PCOS is associated with various metabolic complications, including a higher preva-
lence of metabolic syndrome, reaching up to 56% in some studies [
9
–
11
]. Insulin resistance
is particularly common, affecting approximately 60% to 75% of women with PCOS when as-
sessed using the Homeostasis Model Assessment for Insulin Resistance (HOMA-IR)
[12–14]
.
Hyperinsulinemia exacerbates hyperandrogenism by decreasing sex hormone-binding glob-
ulin (SHBG), increasing free testosterone levels, and worsening clinical manifestations such
as hirsutism, acne, irregular menstrual cycles, and infertility [
15
,
16
]. Insulin directly stim-
ulates ovarian theca cells to increase testosterone production and affects key enzymes in
androgen synthesis [16–19].
Current treatments involve combined hormonal contraceptives to regulate menstrual
cycles and reduce androgen effects [
20
,
21
]. However, these may worsen insulin resistance,
alter glucose metabolism, and negatively affect cardiovascular profiles by increasing triglyc-
eride levels and systemic inflammation markers [
22
,
23
]. Thus, while they alleviate some
PCOS symptoms, they may contribute to metabolic complications, highlighting the need
for more personalized treatments [24,25].
Recent research suggests the gut microbiota significantly influences metabolic and
hormonal pathways associated with PCOS. Dysbiosis may contribute to chronic low-grade
inflammation, exacerbating insulin resistance and hormonal imbalances [
26
]. Women with
PCOS show decreased diversity and altered abundance of specific bacterial taxa compared
to healthy controls [27–29].
Similarly, alterations in gut microbiota have been linked to type 2 diabetes, with certain
bacterial genera positively or negatively correlated with the disease [
30
,
31
]. Probiotics, par-
ticularly Lactobacillus and Bifidobacterium species, have emerged as potential biotherapeutics
for managing insulin resistance and metabolic disorder [32,33].
Consequently, prebiotics, probiotics, and synbiotics have gained attention as potential
treatments for PCOS by modulating gut microbiota. Probiotics are live microorganisms
that confer health benefits when consumed in adequate amounts, while prebiotics are non-
digestible substances that promote the growth of beneficial microbes [
34
,
35
]. Synbiotics
combine both to enhance the survival and implantation of beneficial microorganisms. These
interventions may address microbiota imbalances, inflammation, insulin resistance, lipid
profiles, and hormonal dysregulation more effectively than traditional treatments [36].
Multiple randomized controlled trials (RCTs) have assessed the role of probiotics and
synbiotics in women with PCOS, reporting improvements in insulin resistance markers,
reductions in androgen levels, and favorable shifts in lipid profiles [
37
–
40
]. However,
study designs, bacterial strains, dosages, and intervention durations vary significantly,
making it difficult to compare results and establish guidelines. Many studies lack rigorous
methodological design and are often small-scale. Additionally, diagnostic criteria like the
Rotterdam criteria include patients with diverse phenotypes, contributing to heterogeneity.
Uncertainties remain about how probiotics and synbiotics exert beneficial effects in
PCOS patients. Proposed mechanisms include regulation of gut barrier integrity, suppres-
sion of systemic inflammation, improvement of insulin signaling pathways, and effects
on the hypothalamic–pituitary–ovarian axis [
41
,
42
]. More research is needed to establish
precise mechanisms, optimal bacterial strains, dosages, and treatment durations.
Considering these factors, the present systematic review aims to critically evaluate
and synthesize existing RCTs focused on the effects of probiotics and synbiotics on insulin
resistance and hormonal markers in women with PCOS. We hypothesize that probiotic
and synbiotic interventions significantly improve insulin sensitivity and reduce androgen
levels compared to control groups. This review seeks to provide insights into improving
the pathophysiological understanding and personalized treatment management of PCOS.

Nutrients 2024,16, 3916 3 of 28
2. Materials and Methods
This systematic review was conducted in accordance with the Preferred Reporting
Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [
43
]. The methodol-
ogy was designed to ensure a comprehensive and unbiased selection of relevant studies
evaluating the effectiveness of probiotics and synbiotics in managing insulin resistance and
hormonal imbalance in women with PCOS.
In women with PCOS (P), how does probiotic or prebiotic supplementation, or the
supplementation of both (I), compared to placebo or standard treatments (C), affect insulin
resistance and hormonal balance, thereby influencing metabolic health and quality of
life (O)?
This study’s Prospero registration number is CRD42024587531.
2.1. Eligibility Criteria
The eligibility criteria for this review are detailed in Table 1below.
Table 1. Eligibility criteria.
Criteria Inclusion Exclusion
Study Design
- Randomized controlled trials (RCTs) investigating
supplementation with probiotics, prebiotics, or
synbiotics in women with PCOS.
- Observational studies, reviews, cohort
studies, case series, and studies with
non-randomized designs.
- Studies without an appropriate control
group.
Participants
- Women diagnosed with PCOS according to the
Rotterdam criteria, NIH criteria, or AES criteria. - Studies including men or postmenopausal
women.
-
Aged approximately 15–45 years (reproductive age).
Interventions
- Supplementation with probiotics, prebiotics, or
synbiotics administered in any form (e.g., capsules,
fermented foods).
- Supplementation with compounds other
than probiotics, prebiotics, or synbiotics (e.g.,
metformin alone without combination with
probiotics).
Duration
- Interventions with a minimum duration of 8 weeks
to adequately assess changes in metabolic and
hormonal parameters.
- Interventions with a duration of less than 8
weeks.
Outcomes
- Studies evaluating effects on insulin resistance (e.g.,
HOMA-IR, fasting insulin, fasting glucose),
hormonal parameters (e.g., testosterone, SHBG,
DHEA-S), and changes in other relevant metabolic
markers (e.g., lipid profile, apelin, hs-CRP).
-
Studies that only evaluated clinical outcomes
such as reproductive function without
assessing insulin resistance or hormonal
parameters.
Language - Studies published in English. - Studies published in languages other than
English.
2.2. Information Sources and Search Strategy
A comprehensive search of electronic databases was conducted to identify relevant
studies. The databases searched included the following:
•PubMed;
•Cochrane Central Register of Controlled Trials (CENTRAL);
•Scopus;
•Web of Science;
•Embase.

Nutrients 2024,16, 3916 4 of 28
The data were organized using Zotero version 6.0 (accessed on 24 August 2024).
2.3. Search Algorithm
The search strategy combined Medical Subject Headings (MeSH) and free-text terms
related to PCOS, probiotics, prebiotics, synbiotics, insulin resistance, and hormonal param-
eters. Boolean operators (AND, OR) were used to refine the search. An example of the
search strategy used in PubMed is as follows:
(“polycystic ovary syndrome” OR “PCOS”) AND (probiotic OR prebiotic OR synbiotic)
AND (insulin OR “insulin resistance” OR “HOMA-IR” OR “pancreatic
β
cell function” OR
“C reactive protein” OR “hormonal status” OR “testosterone” OR “androgens”)
This search algorithm was adapted for each database according to its specific search
functionalities. Additional searches were conducted by reviewing the reference lists of
relevant articles to identify any studies that might have been missed.
2.4. Study Selection
Two reviewers (D.M.G. and S.V.C.) independently screened the titles and abstracts of
all identified articles for eligibility. Full-text articles were retrieved for studies that appeared
to meet the inclusion criteria or if eligibility was unclear from the abstract. Discrepancies
between the reviewers were resolved through discussion, and if necessary, a third reviewer
(Y.L.) was consulted to reach a consensus.
2.5. Data Extraction
Two reviewers (D.M.G. and S.V.C.) independently extracted information from the
primary studies using a standardized data extraction form. The extracted data included
details of the clinical trial:
•Study characteristics: first author, publication year, country, and study design.
•
Participant characteristics: number of participants, age, BMI, sex (all female partici-
pants), and diagnostic criteria for PCOS.
•
Intervention details: type of probiotic/prebiotic/synbiotic used, bacterial strains,
dosage, form of administration, and duration of intervention.
•Comparator: details of the control group (placebo or standard care).
•
Outcomes measured: primary outcomes (e.g., insulin resistance markers, hormonal
parameters), secondary outcomes (e.g., lipid profile, inflammatory markers), and
methods of measurement.
•
Results: main findings, statistical significance, and conclusions drawn by the authors.
•Limitations: as reported by the authors.
Subsequently, a third reviewer (Y.L.) verified the integrity and accuracy of the recorded
information.
Figure 1was created with the online R package PRISMA2020 [
44
] (https://estech.
shinyapps.io/prisma_flowdiagram/, accessed on 24 August 2024). Figure 2was created
using R software package ggplot2, version 4.3.0 (https://cran.r-project.org/bin/windows/
base/old/4.3.0/, accessed on 24 August 2024).

Nutrients 2024,16, 3916 5 of 28
Nutrients 2024, 16, x FOR PEER REVIEW 5 of 31
Figure 1. PRISMA flowchart. A Cohen’s kappa of 0.95 and 0.82 indicates a high level of agreement
between reviewers, ensuring the validity of the results.
Figure 1. PRISMA flowchart. A Cohen’s kappa of 0.95 and 0.82 indicates a high level of agreement
between reviewers, ensuring the validity of the results.
Nutrients 2024, 16, x FOR PEER REVIEW 6 of 31
Figure 2. Clinical outcomes of prebiotic, probiotic, and synbiotic interventions in patients with
PCOS. (A) Distribution of prebiotics, probiotics, and synbiotics used in interventions. (B) Changes
in HOMA-IR, FBS, and insulin by intervention group. HOMA-IR (Homeostatic Model Assessment
for Insulin Resistance) is marked in red. FBS (fasting blood sugar) is in orange. Insulin is in yellow.
The bars reflect how each parameter changed based on the type of supplement used (probiotic, syn-
biotic, prebiotic, and control). (C) Relationship between duration of intervention and change in clin-
ical parameters (Δ). Red dots represent changes in HOMA-IR. Green dots represent changes in FBS.
Blue dots represent changes in insulin [38–40,45,46].
2.6. Risk-of-Bias Assessment
The risk-of-bias assessment for the included studies was conducted independently
by two reviewers (D.M.G. and S.V.C.) using the Cochrane Risk of Bias Tool for Random-
ized Trials [47], with data entered into Review Manager version 5.4
®
(RevMan, The
Cochrane Collaboration, accessed on 24 August 2024). The following domains were eval-
uated:
• Random sequence generation (selection bias);
• Allocation concealment (selection bias);
• Blinding of participants and personnel (performance bias);
• Blinding of outcome assessment (detection bias);
• Incomplete outcome data (arition bias);
• Selective reporting (reporting bias).
For each domain, studies were assessed as having a low, high, or unclear risk of bias
based on predetermined guidelines. Discrepancies in the risk-of-bias assessment were re-
solved through discussion between the reviewers, and if necessary, a third reviewer (Y.L.)
was consulted.
To confirm the consistency of the evaluation process, a subset of the studies was re-
assessed, and Cohen’s kappa coefficient was computed using IBM SPSS Statistics version
27.0 (IBM Corp., Armonk, NY, USA; accessed on 24 August 2024) to quantify the agree-
ment between reviewers.
Figure 2. Clinical outcomes of prebiotic, probiotic, and synbiotic interventions in patients with
PCOS. (A) Distribution of prebiotics, probiotics, and synbiotics used in interventions. (B) Changes in
HOMA-IR, FBS, and insulin by intervention group. HOMA-IR (Homeostatic Model Assessment for

Nutrients 2024,16, 3916 6 of 28
Insulin Resistance) is marked in red. FBS (fasting blood sugar) is in orange. Insulin is in yellow. The
bars reflect how each parameter changed based on the type of supplement used (probiotic, synbiotic,
prebiotic, and control). (C) Relationship between duration of intervention and change in clinical
parameters (
∆
). Red dots represent changes in HOMA-IR. Green dots represent changes in FBS. Blue
dots represent changes in insulin [38–40,45,46].
2.6. Risk-of-Bias Assessment
The risk-of-bias assessment for the included studies was conducted independently by
two reviewers (D.M.G. and S.V.C.) using the Cochrane Risk of Bias Tool for Randomized
Trials [
47
], with data entered into Review Manager version 5.4
®
(RevMan, The Cochrane
Collaboration, accessed on 24 August 2024). The following domains were evaluated:
•Random sequence generation (selection bias);
•Allocation concealment (selection bias);
•Blinding of participants and personnel (performance bias);
•Blinding of outcome assessment (detection bias);
•Incomplete outcome data (attrition bias);
•Selective reporting (reporting bias).
For each domain, studies were assessed as having a low, high, or unclear risk of bias
based on predetermined guidelines. Discrepancies in the risk-of-bias assessment were
resolved through discussion between the reviewers, and if necessary, a third reviewer (Y.L.)
was consulted.
To confirm the consistency of the evaluation process, a subset of the studies was
reassessed, and Cohen’s kappa coefficient was computed using IBM SPSS Statistics version
27.0 (IBM Corp., Armonk, NY, USA; accessed on 24 August 2024) to quantify the agreement
between reviewers.
2.7. Data Synthesis
Due to the heterogeneity among the included studies in terms of interventions, bac-
terial strains, dosages, and outcomes measured, a qualitative synthesis was conducted.
The results are presented in narrative form, accompanied by tables summarizing the key
characteristics and findings of the studies.
2.8. Ethical Considerations
As this study is a systematic review of the published literature, it did not involve direct
interaction with human subjects or animals and thus did not require ethical approval.
3. Results
3.1. Characteristics of the Included Studies
A total of 514 records were identified acrossfive databases, with 96 duplicates removed,
leaving 418 records. Of these, 20 were excluded based on title and abstract screening, using
a peer review process with a Cohen’s kappa of 0.95, indicating excellent agreement between
the reviewers. Subsequently, 398 records were assessed for eligibility through full-text
reviews. Among these, 150 records were excluded for not meeting relevance criteria, 12
due to insufficient data, and 225 because they did not match the required study type. The
Cohen’s kappa for this phase was 0.90, also reflecting excellent agreement. As a result,
11 articles, all conducted in Iran, were ultimately included in this systematic review, as
shown in Figure 1.
3.2. Overview of Study Results
Table 2below outlines the general characteristics of the 11 studies included in this
review. All studies were randomized clinical trials, with seven being double-blind and
four triple-blind, and all were conducted in Iran among women of reproductive age. The
consistent application of the Rotterdam criteria ensured the uniform selection of patients,
thereby facilitating more robust comparisons across the different studies. This uniform

Nutrients 2024,16, 3916 7 of 28
selection was crucial for minimizing variability in patient populations, ensuring that all
participants met standardized diagnostic criteria for PCOS. Consequently, the studies could
be more reliably compared, allowing for a clearer understanding of the interventions’
effects on metabolic and hormonal outcomes in PCOS.
Table 2. General characteristics of studies.
Study Reference Country Diagnostic Criteria Study Design
Esmaeilinezhad et al., 2018 [38] Iran Rotterdam criteria for PCOS Triple-blind RCT
Shoaei et al., 2021 [39] Iran Rotterdam criteria for PCOS Double-blind RCT
Darvishi et al., 2020 [40] Iran Rotterdam criteria for PCOS Double-blind RCT
Karimi et al., 2018 [45] Iran Rotterdam criteria for PCOS Double-blind RCT
Samimi et al., 2018 [46] Iran Rotterdam criteria for PCOS Double-blind RCT
Esmaeilinezhad et al., 2019 [37] Iran Rotterdam criteria for PCOS Triple-blind RCT
Gholizadeh Shamasbi et al., 2018 [48] Iran Rotterdam criteria for PCOS Triple-blind RCT
Arab et al., 2022 [49] Iran Rotterdam criteria for PCOS Double-blind RCT
Karamali et al., 2018 [50] Iran Rotterdam criteria for PCOS Double-blind RCT
Karimi et al., 2020 [51] Iran Rotterdam criteria for PCOS Double-blind RCT
Nasri et al., 2018 [52] Iran Rotterdam criteria for PCOS Double-blind RCT
3.3. Participant Characteristics
Table 3details the characteristics of the participants in the reviewed studies. All
studies exclusively included women, with sample sizes ranging from 23 to 45 participants.
The ages of the participants varied between 15 and 48 years, and the BMI generally ranged
from 25 to 40 kg/m2, classifying most participants as overweight or obese.
Table 3. Participant characteristics.
Study Reference Participants Size Age (Years) BMI (kg/m2)Baseline Parameters
Esmaeilinezhad
et al., 2018 [38]Women
I
(pomegranate+synbiotic):
23,
I (pomegranate): 23, I
(synbiotic beverage): 23,
C: 23
15–48 25–28
Synbiotic pomegranate juice:
HOMA-IR: 6.32 ±1.32
FBS: 112.04 ±9.41 mg/dL
Insulin: 22.80 ±3.97 µIU/mL
QUICKI: 0.294 ±0.008; pomegranate
juice: HOMA-IR: 6.16 ±1.17
FBS: 112.82 ±12.61 mg/dL
Insulin: 22.15 ±3.48 µIU/mL
QUICKI: 0.295 ±0.007; synbiotic
beverage: HOMA-IR: 6.11 ±1.22
FBS: 112.65 ±8.46 mg/dL
Insulin: 22.02 ±4.32 µIU/mL
QUICKI: 0.295 ±0.008; control:
HOMA-IR: 6.95 ±0.91
FBS: 114.56 ±8.16 mg/dL
Insulin: 24.66 ±3.33 µIU/mL
QUICKI: 0.290 ±0.004
Shoaei et al.,
2021 [39]Women I (probiotic): 36
C (placebo): 36 15–40 25–30
Probiotic: HOMA-IR: 2.11 ±0.21
FBS: 85.7 ±2.6 mg/dL
Insulin: 9.8 ±0.9 µIU/mL
QUICKI: N/A; placebo: HOMA-IR:
2.05 ±0.23
FBS: 86.2 ±2.5 mg/dL
Insulin: 9.7 ±0.8 µIU/mL
QUICKI: N/A

Nutrients 2024,16, 3916 8 of 28
Table 3. Cont.
Study Reference Participants Size Age (Years) BMI (kg/m2)Baseline Parameters
Darvishi et al.,
2020 [40]Women I (synbiotic): 34
C (placebo): 34 20–44 ≥25
Synbiotic: HOMA-IR: 3.06 ±1.35
FBS: 91.32 ±8.07 mg/dL
Insulin: 13.36 ±4.89 µIU/mL
HDL: 45.79 ±12.05 mg/dL; placebo:
HOMA-IR: 2.10 ±1.12
FBS: 89.02 ±9.05 mg/dL
Insulin: 9.46 ±4.64 µIU/mL
HDL: 48.14 ±10.22 mg/dL
Karimi et al.,
2018 [45]Women I (synbiotic): 44
C (placebo): 44 19–37 ≥25
Synbiotic: HOMA-IR: 3.77 ±2.35
FBS: 92 ±9 mg/dL
Apelin 36: 27 ±21 nmol/L
CRP: 6.9 ±5.99 mg/L; placebo:
HOMA-IR: 3.6 ±1.92
FBS: 90 ±9 mg/dL
Apelin 36: 26 ±15 nmol/L
CRP: 4.74 ±4.68 mg/L
Samimi et al.,
2018 [46]Women I (synbiotic): 30
C (placebo): 30 18–40 27–35
Synbiotic: FPG: 92.2 ±6.2 mg/dL
Insulin: 12.9 ±4.2 µIU/mL
HOMA-IR: 3.0 ±1.1
Triglycerides: 146.4 ±56.3 mg/dL
VLDL: 29.3 ±11.2 mg/dL
AIP: 0.49 ±0.20
Placebo: FPG: 94.0 ±5.7 mg/dL
Insulin: 12.1 ±6.3 µIU/mL
HOMA-IR: 2.8 ±1.4
Triglycerides: 138.2 ±37.9 mg/dL
VLDL: 27.6 ±7.6 mg/dL
AIP: 0.44 ±0.16
Esmaeilinezhad
et al., 2019 [37]Women
SPJ (synbiotic
pomegranate juice): 23
PJ (pomegranate juice):
23
SB (synbiotic beverage):
23
PB (placebo beverage): 23
15–48 ~25–28
SPJ: TGs: 171 ±57 mg/dL
TC: 180 ±32 mg/dL
LDL-C: 96 ±35 mg/dL
HDL-C: 50 ±12 mg/dL
SBP: 128 ±7 mmHg
Placebo: TGs: 194 ±67 mg/dL
TC: 194 ±23 mg/dL
LDL-C: 113 ±27 mg/dL
HDL-C: 42 ±10 mg/dL
SBP: 134 ±7 mmHg
Gholizadeh
Shamasbi et al.,
2018 [48]
Women I: 31
C: 31 18–45 25–40
Prebiotic: LDL-C:
106.87 ±34.7 mg/dL
HDL-C: 40.55 ±8.8 mg/dL
Total cholesterol:
166.90 ±38.6 mg/dL
TGs: 96.77 ±35.7 mg/dL
FBS: 80.68 ±12.3 mg/dL
hs-CRP: 4.70 ±2.6 mg/dL
Free testosterone: 1.25 ±0.9 pg/mL
DHEA-S: 3.18 ±2.2 µg/mL
Arab et al.,
2022 [49]Women I: 45
C: 43 15–40 ≥25
Probiotic: SHBG:
36.11 ±10.87 nmol/mL
Total testosterone: 0.42 ±0.14 ng/mL
FAI: 3.24 ±1.1
DHEA-S: 6.9 ±2.8 nmol/L
Karamali et al.,
2018 [50]Women I: 30
C: 30 18–40 ≥25
Probiotic: SHBG: 46.3 ±10.3 nmol/L
Total testosterone: 1.3 ±0.7 ng/mL
mF-G scores: 14.1 ±4.9
hs-CRP: 3546.7 ±1003.1 ng/mL
TAC: 935.5 ±344.8 mmol/L
MDA: 2.1 ±0.4 µmol/L

Nutrients 2024,16, 3916 9 of 28
Table 3. Cont.
Study Reference Participants Size Age (Years) BMI (kg/m2)Baseline Parameters
Karimi et al.,
2020 [51]Women I: 44
C: 44 19–37 ≥25
Synbiotic: LDL: 97 ±19 mg/dL
HDL: 46.44 ±7.69 mg/dL
Total cholesterol (TC):
175.2 ±27.5 mg/dL
Triglycerides (TGs): 139 ±78 mg/dL
Nasri et al.,
2018 [52]Women I: 30
C: 30 18–40 ≥25
Synbiotic: SHBG: 37.3 ±13.1 nmol/L
Total testosterone: 2.8 ±1.3 ng/mL
mF-G scores: 15.3 ±5.6
hs-CRP: 2920 ±2251.2 ng/mL
NO: 39.0 ±3.1 µmol/L
MDA: 2.3 ±0.4 µmol/L
Abbreviations: I = intervention group; C = control group; BMI = body mass index; HOMA-IR = Homeostatic
Model Assessment of Insulin Resistance; FBS = fasting blood glucose; QUICKI = Quantitative Insulin Sensitiv-
ity Check Index; HDL-C = high-density lipoprotein cholesterol; LDL-C = low-density lipoprotein cholesterol;
TGs = triglycerides; VLDL = very low-density lipoprotein; CRP = C-reactive protein; hs-CRP = high-sensitivity C-
reactive protein; SHBG = sex hormone-binding globulin; FAI = free androgen index; DHEA-S = dehydroepiandros-
terone sulfate; mF-G = modified Ferriman–Gallwey scores; TAC = total antioxidant capacity; MDA = malondi-
aldehyde; NO = nitric oxide; SPJ = synbiotic pomegranate juice; PJ = pomegranate juice; SB = synbiotic beverage;
PB = placebo beverage; FPG = fasting plasma glucose; N/A = not applicable; AIP = atherogenic index of plasma;
SBP = systolic blood pressure.
For example, Esmaeilinezhad et al., 2018 [
38
] included 92 women, evenly divided
into four groups of 23 participants each: synbiotic pomegranate juice, pomegranate juice,
synbiotic beverage, and control. The baseline parameters measured included HOMA-IR,
fasting blood glucose (FBS), insulin levels, and Quantitative Insulin Sensitivity Check Index
(QUICKI). In another study, by Shoaei et al., 2021 [
39
], 72 women participated, with 36 in
the probiotic group and 36 in the placebo group. The ages ranged from 15 to 40 years, and
the BMI was between 25 and 30 kg/m
2
. The study evaluated HOMA-IR, FBS, and insulin
as baseline parameters.
Similarly, Darvishi et al., 2020 [
40
] included 68 women, divided into two groups of 34
each (synbiotic and placebo), with ages between 20 and 44 years and a BMI of 25 kg/m
2
or higher. The recorded baseline parameters were HOMA-IR, FBS, insulin, and HDL
cholesterol. Other studies, such as Karimi et al., 2018 [
50
] and 2020 [
51
], Samimi et al.,
2018 [
46
], and Arab et al., 2022 [
49
], followed similar structures, focusing on different
metabolic and hormonal markers according to each study’s specific objectives.
In particular, Karimi et al., 2018 [
50
] and 2020 [
51
] included 30 and 44 women, re-
spectively, evaluating parameters such as SHBG, total testosterone, mF-G scores, hs-CRP,
TAC, and malondialdehyde (MDA). Samimi et al., 2018 [
46
] and Gholizadeh Shamasbi
et al., 2018 [
48
] also incorporated measurements of fasting glucose, insulin, HOMA-IR,
triglycerides, VLDL, AIP, and various inflammatory and hormonal markers. Lastly, Arab
et al., 2022 [
49
] assessed 45 women in the intervention group and 43 in the control group,
measuring SHBG, total testosterone, FAI, and DHEA-S.
3.4. Intervention Details and Comparison Groups
The interventions across the reviewed studies encompassed a variety of probiotic,
prebiotic, and synbiotic formulations designed to address metabolic and hormonal distur-
bances in women with PCOS. These interventions varied in strains, dosages, forms, and
colony-forming units (CFUs), all of which could influence their effectiveness (See Table 4).

Nutrients 2024,16, 3916 10 of 28
Table 4. Intervention details and comparison groups.
Study Reference Prebiotic, Probiotic, or Synbiotic Type Pharmaceutical
Form Dosage Duration Comparison Group
Esmaeilinezhad
et al., 2018 [38]Synbiotic in pomegranate juice (SPJ) Juice 2 L per week 12 weeks
Placebo pomegranate
juice
Shoaei et al.,
2021 [39]
Multistrain probiotic with L. casei,L.
acidophilus,L. rhamnosus,L. bulgaricus,B.
breve,B. longum, and S. thermophilus
Capsule One 500 mg
capsule daily 8 weeks Placebo (starch and
maltodextrin)
Darvishi et al.,
2020 [40]
Synbiotic (Lactobacillus casei,L. rhamnosus,
L. bulgaricus,L. acidophilus,Bifidobacterium
longum, and Streptococcus thermophilus)
and prebiotic (inulin and FOS)
Capsule 1 capsule daily,
500 mg 8 weeks Placebo
Karimi et al.,
2018 [45]
Synbiotic with 7 strains of probiotics (L.
acidophilus,L. casei,L. bulgaricus,L.
rhamnosus,B. longum,B. breve, and S.
thermophilus) and prebiotic inulin
(fructo-oligosaccharide)
Capsule 1 capsule daily,
1000 mg 12 weeks Placebo
Samimi et al.,
2018 [46]
Synbiotic with L. acidophilus,L. casei,B.
bifidum, and 800 mg inulin Capsule
2×109CFU/g
of each strain +
800 mg inulin
daily
12 weeks Placebo
Esmaeilinezhad
et al., 2019 [37]
Synbiotic in pomegranate juice
(Lactobacillus rhamnosus GG, Bacillus
coagulans, and Bacillus indicus)
Juice 300 mL daily 8 weeks Placebo (flavored
water)
Gholizadeh
Shamasbi et al.,
2018 [48]
Prebiotic (dextrin) Powder (diluted
in water) 20 g daily 12 weeks Placebo
(maltodextrin)
Arab et al., 2022
[49]
Multistrain probiotic with multiple strains:
Lactobacillus acidophilus (3 ×1010 CFU/g),
Lactobacillus casei (3 ×109CFU/g),
Lactobacillus rhamnosus (1.5 ×109CFU/g),
Lactobacillus bulgaricus (5 ×108CFU/g),
Bifidobacterium breve (2 ×1010 CFU/g),
Bifidobacterium longum (7 ×109CFU/g),
Streptococcus thermophilus (
3×108CFU/g
)
+ 800 mg inulin
Capsule
One 500 mg
capsule daily (7
strains + 800 mg
inulin)
12 weeks Placebo (starch and
maltodextrin)
Karamali et al.,
2018 [50]
Multistrain probiotic with multiple strains:
Lactobacillus acidophilus (3 ×1010 CFU/g),
Lactobacillus casei (3 ×109CFU/g),
Lactobacillus rhamnosus (1.5 ×109CFU/g),
Lactobacillus bulgaricus (5 ×108CFU/g),
Bifidobacterium breve (2 ×1010 CFU/g),
Bifidobacterium longum (7 ×109CFU/g),
Streptococcus thermophilus (3
×
10
8
CFU/g)
+ 800 mg inulin
Capsule
Two capsules
daily (500 mg
each: 7 strains +
800 mg inulin)
12 weeks Placebo (starch and
maltodextrin)
Karimi et al.,
2020 [51]
Synbiotics with multiple strains:
Lactobacillus acidophilus (3 ×1010 CFU/g),
Lactobacillus casei (3 ×109CFU/g),
Lactobacillus bulgaricus (5 ×108CFU/g),
Lactobacillus rhamnosus (7 ×109CFU/g),
Bifidobacterium longum (1 ×109CFU/g),
Bifidobacterium breve (2 ×1010 CFU/g),
Streptococcus thermophilus (
3×108CFU/g
)
+ inulin (fructooligosaccharide)
Capsules
Two capsules
daily (500 mg
each: 7 strains +
inulin)
12 weeks Placebo (starch and
maltodextrin)
Nasri et al.,
2018 [52]
Synbiotic with multiple strains:
Lactobacillus acidophilus (2 ×109CFU/g),
Lactobacillus casei (2 ×109CFU/g),
Bifidobacterium bifidum (2 ×109CFU/g) +
0.8 g inulin
Capsules
Two 500 mg
capsules daily (3
strains + inulin)
12 weeks Placebo (starch and
maltodextrin)
Abbreviations: SPJ = synbiotic pomegranate juice; CFU = colony-forming units; FOS = fructo-oligosaccharides.

Nutrients 2024,16, 3916 11 of 28
For instance, studies like Esmaeilinezhad et al., 2018 [
38
] and Esmaeilinezhad et al.,
2019 [
37
] utilized synbiotic pomegranate juice, with participants consuming either 2 L per
week or 300 mL daily over periods ranging from 8 to 12 weeks. These interventions were
compared to placebo pomegranate juice or flavored water, allowing for a direct assessment
of the combined effects of probiotics and prebiotics in a liquid medium. The juice form
likely enhances metabolic effects by providing both probiotic benefits and the antioxidant
properties of pomegranate.
Conversely, several studies employed capsule-based interventions. Shoaei et al.,
2021 [39] and Karimi et al., 2018 [45] administered multi-strain probiotics in capsule form,
typically containing strains such as Lactobacillus casei,L. rhamnosus, and Bifidobacterium
longum, delivered in daily doses ranging from 500 mg to 1000 mg over 8 to 12 weeks.
Additionally, studies like Darvishi et al., 2020 [
40
] and Gholizadeh Shamasbi et al., 2018 [
48
]
combined probiotics with prebiotics such as inulin or dextrin in capsule form to enhance
gut flora and overall metabolic health. The prebiotics served as fuel for the probiotics,
potentially increasing their efficacy in modulating the gut microbiota and improving
insulin sensitivity.
Synbiotic capsules were also utilized in studies by Karimi et al., 2020 [
51
] and Nasri
et al., 2018 [
52
], where multi-strain synbiotics were paired with prebiotics like inulin,
administered as two 500 mg doses daily over 12 weeks. These interventions ensured a
controlled dosage, providing participants with a precise amount of beneficial bacteria
and prebiotics. The control groups in these studies typically received placebo capsules
containing starch or maltodextrin, allowing for clear comparisons between active and
inactive treatments.
CFUs varied significantly across studies, influencing the potential efficacy of the
interventions. Studies such as Arab et al., 2022 [
49
] and Karamali et al., 2018 [
50
] employed
high CFU counts, ranging from 10
8
to 10
10
CFU/g for each probiotic strain, potentially
enhancing the probiotic effects compared to studies with lower CFU counts like Nasri
et al., 2018 [
52
]. Dosages also varied, from 500 mg to 1000 mg per capsule, with some
studies administering multiple capsules daily to achieve the desired intake of probiotics
and prebiotics.
The duration of interventions was consistent across most studies, typically lasting
between 8 and 12 weeks, which is generally sufficient to observe meaningful changes in
metabolic and hormonal parameters. All studies included placebo comparison groups to
ensure that observed effects could be attributed to the active interventions. Placebos varied
in form, including starch, maltodextrin, flavored water, or maltodextrin-diluted powders,
depending on the study design.
Despite the variations in probiotic and synbiotic strains, dosages, forms, and CFU
counts, all studies aimed to improve metabolic and hormonal outcomes in women with
PCOS. The diversity in intervention formulations underscores the complexity of determin-
ing the most effective probiotic or synbiotic regimen, as different delivery methods and
strain combinations could lead to varying clinical outcomes. Future research should
aim to standardize these variables to better compare and understand the efficacy of
different formulations.
The reviewed studies present mixed but promising results regarding the effects of pro-
biotics, prebiotics, and synbiotics on insulin resistance, hormonal markers, and metabolic
profiles in women with PCOS. Commonly analyzed metrics included HOMA-IR, fasting
blood glucose, and hormone levels such as testosterone and SHBG.
Esmaeilinezhad et al., 2018 [
38
] (see Table 5) demonstrated that synbiotic pomegranate
juice significantly reduced HOMA-IR, fasting insulin, and glucose, indicating moderate
improvements in insulin sensitivity compared to pomegranate juice or synbiotics alone.
Despite high adherence rates, the study was limited by its small sample size and lack
of long-term follow-up. Similarly, Esmaeilinezhad et al., 2019 [
37
] reported significant
improvements in lipid profiles and cardiovascular markers with synbiotic pomegranate
juice, though they did not measure body composition or gut microbiota changes.

Nutrients 2024,16, 3916 12 of 28
Table 5. Results, adherence, and side effects.
Study
Reference
Post-Intervention
Parameters
Change in
Parameters (∆)
Comparative Effects
Adherence to
the Intervention Side Effects Primary
Outcomes
Secondary
Outcomes
Measurement
Methods Key Findings Author
Conclusions
Study
Limitations
Esmaeilinezhad
et al., 2018 [
38
]
Synbiotic pomegranate
juice: HOMA-IR:
5.75 ±1.22; pomegranate
juice: HOMA-IR:
6.20 ±1.23; Synbiotic
beverage: HOMA-IR:
5.61 ±0.99
FBS: 111.47 ±6.58 mg/dL
Insulin:
20.36 ±3.35 µIU/mL
QUICKI: 0.29 ±0.007
FBS:
113.68 ±10.63 mg/dL
Insulin:
22.07 ±3.74 µIU/mL
QUICKI: 0.29 ±0.007
FBS: 110.36 ±6.57 mg/dL
Insulin:
21.03 ±3.94 µIU/mL
QUICKI: 0.29 ±0.008;
Control: HOMA-IR:
7.33 ±0.92
FBS: 115.00 ±7.85 mg/dL
Insulin:
25.89 ±3.11 µIU/mL
QUICKI: 0.28 ±0.004
Synbiotic
pomegranate juice:
∆HOMA-IR: −0.57
∆FBS: −1.68 mg/dL
∆Insulin:
−1.77 µIU/mL;
pomegranate juice:
∆HOMA-IR: +0.04
∆FBS: +0.86 mg/dL
∆Insulin:
−0.08 µIU/mL
∆QUICKI: 0.00;
synbiotic beverage:
∆HOMA-IR: −0.50
∆FBS: −1.18 mg/dL
∆Insulin:
−1.66 µIU/mL
∆QUICKI: 0.00;
Control: ∆HOMA-IR:
+0.38
∆FBS: +0.44 mg/dL
∆Insulin:
+1.23 µIU/mL
∆QUICKI: −0.01
Synbiotic
pomegranate juice:
significant
improvement
(p< 0.05);
pomegranate juice:
no significant
change; synbiotic
beverage: moderate
improvement
(p< 0.05); control:
no significant
improvement
95% adherence,
as most
participants
completed the
study
None
Insulin
resistance
(HOMA-IR),
fasting
glucose
Testosterone,
insulin
sensitivity,
lipid profile
ELISA for
insulin and
HOMA-IR,
standard
biochemical
analysis
Significant
reduction in
HOMA-IR,
increased
insulin
sensitivity,
decreased
testosterone
Synbiotic
pomegranate
juice improves
insulin
resistance and
hormone levels
in PCOS
Small sample
size, lack of
long-term
follow-up
Shoaei et al.,
2021 [39]
Probiotic: HOMA-IR:
1.9 ±0.2
FBS: 81.5 ±2.1 mg/dL
Insulin:
9.3 ±0.71 µIU/mL
QUICKI: N/A
Placebo: HOMA-IR:
2.00 ±0.22
FBS: 88.3 ±2.7 mg/dL
Insulin: 9.8
±
0.8
µ
IU/mL
QUICKI: N/A
∆HOMA-IR:
probiotic: −0.21 vs.
placebo: −0.05
∆FBS: probiotic:
−4.15 mg/dL vs.
placebo:
+2.57 mg/dL
∆Insulin: probiotic:
−0.49 µIU/mL vs.
placebo:
+0.34 µIU/mL
Probiotic group
showed
non-significant
changes in FBS,
insulin, and
HOMA-IR (p= 0.7);
however, after
adjusting for
covariates, insulin
reduction was
significant in the
probiotic group
(p= 0.02)
90% adherence,
most
participants
completed the
study
None
Pancreatic
β-cell
function (FBS,
serum insulin,
HOMA-IR,
QUICKI), CRP
(C-reactive
protein)
Insulin, lipid
profile,
hs-CRP
Standard
biochemical
analyses,
immunoassay
for insulin,
HOMA-IR and
QUICKI
calculations
Non-significant
reduction in
FBS, serum
insulin, and
HOMA-IR in
probiotic group;
after adjusting
for covariates,
insulin
reduction was
significant; no
significant
differences in
CRP
Probiotic sup-
plementation
for 8 weeks had
a
non-significant
beneficial effect
on pancreatic
β-cell function
and CRP
Short study
duration, no
glucose
tolerance
tests or
hormonal
evaluations

Nutrients 2024,16, 3916 13 of 28
Table 5. Cont.
Study
Reference
Post-Intervention
Parameters
Change in
Parameters (∆)
Comparative Effects
Adherence to
the Intervention Side Effects Primary
Outcomes
Secondary
Outcomes
Measurement
Methods Key Findings Author
Conclusions
Study
Limitations
Darvishi et al.,
2020 [40]
Synbiotic: HOMA-IR:
2.58 ±1.15
FBS: 90.08 ±7.90 mg/dL
Insulin:
11.50 ±4.75 µIU/mL
HDL:
47.11 ±12.73 mg/dL;
placebo: HOMA-IR:
3.08 ±1.31
FBS: 94.44 ±9.49 mg/dL
Insulin:
13.17 ±5.29 µIU/mL
HDL:
44.23 ±10.73 mg/dL
∆HOMA-IR:
synbiotic: −0.47 vs.
placebo: +0.98
∆FBS: synbiotic:
−1.24 mg/dL vs.
placebo:
+5.42 mg/dL
∆Insulin: synbiotic:
−1.86 µIU/mL vs.
placebo:
+3.71 µIU/mL
∆HDL: synbiotic:
+1.32 mg/dL vs.
placebo:
−3.91 mg/dL
Synbiotic group
showed significant
improvement in
HOMA-IR, FBS,
insulin, and HDL
levels (p< 0.05)
compared to placebo
95% adherence,
all participants
completed the
study
None
Glycemic
indices, lipid
profile, obesity
values
Serum apelin
levels
Standard
biochemical
analysis, ELISA,
anthropometric
measurements
Significant
improvements
in glycemic
indices, lipid
profile, and
obesity values;
no changes in
apelin
Synbiotic sup-
plementation
improves
metabolic
factors and
obesity in
women with
PCOS
Short study
duration, no
evaluation of
bacterial
flora or
SCFAs, only
over-
weight/obese
patients
included
Karimi et al.,
2018 [45]
Synbiotic: HOMA-IR:
3.82 ±2.27
FBS: 92 ±11 mg/dL
Apelin 36:
14.4 ±4.5 nmol/L
CRP: 5.2 ±3.9 mg/L;
Placebo: HOMA-IR:
3.8 ±2.46
FBS: 91 ±10 mg/dL
Apelin 36:
18.4 ±9.2 nmol/L
CRP: 4.9 ±4.8 mg/L
∆HOMA-IR:
synbiotic: +0.05 vs.
placebo: +0.2
∆FBS: synbiotic:
+0.6 mg/dL vs.
placebo:
+0.95 mg/dL
∆
Apelin 36: synbiotic:
−12.6 nmol/L vs.
placebo:
−7.6 nmol/L
∆CRP: synbiotic:
−1.7 mg/L vs.
placebo: −0.24 mg/L
Synbiotic group
showed a significant
decrease in apelin 36
levels (p= 0.004)
compared to
placebo. No
significant changes
in metabolic
parameters such as
HOMA-IR, FBS, or
CRP
Approx. 90%
adherence, with
11 participants
lost to follow-up
None
Metabolic
parameters
(fasting
glucose, 2 h
plasma
glucose,
HbA1c,
HOMA-IR,
QUICKI),
fasting insulin,
C-reactive
protein (CRP),
apelin 36
levels
QUICKI, CRP
Standard
biochemical
analysis,
immunotur-
bidimetry for
HbA1c and CRP,
ELISA for apelin
36, HOMA-IR
and QUICKI
calculations
No significant
differences in
metabolic
parameters,
fasting insulin,
or CRP after 12
weeks;
significant
decrease in
apelin 36
Synbiotic sup-
plementation
had no
significant
effects on
metabolic and
inflammatory
parameters;
decrease in
apelin 36
No
examination
of bacterial
flora changes,
potential
reporting
biases
Samimi et al.,
2018 [46]
Synbiotic: FPG:
88.0 ±7.2 mg/dL
Insulin:
10.1 ±3.9 µIU/mL
HOMA-IR: 2.3 ±0.9
Triglycerides:
130.3 ±39.3 mg/dL
VLDL: 26.0 ±7.9 mg/dL
AIP: 0.43 ±0.16
Placebo: FPG:
92.8 ±8.1 mg/dL
Insulin:
13.9 ±5.2 µIU/mL
HOMA-IR: 3.2 ±1.2
Triglycerides:
144.0 ±47.2 mg/dL
VLDL: 28.8 ±9.4 mg/dL
AIP: 0.43 ±0.22
∆FPG: synbiotic:
−4.1 mg/dL vs.
placebo: −1.2 mg/dL
∆Insulin: synbiotic:
−2.8 µIU/mL vs.
placebo:
+1.8 µIU/mL
∆HOMA-IR:
synbiotic: −0.7 vs.
placebo: +0.4
∆Triglycerides:
synbiotic:
−16.2 mg/dL vs.
placebo: +5.8 mg/dL
∆VLDL: synbiotic:
−3.3 mg/dL vs.
placebo: +1.1 mg/dL
∆AIP: synbiotic:
−0.05 vs. placebo:
−0.003
Significant reduction
in insulin,
HOMA-IR,
triglycerides,
VLDL-cholesterol,
and AIP in the
synbiotic group
(p< 0.05) compared
to placebo. No
significant
differences observed
in total cholesterol,
LDL-cholesterol, or
HDL-cholesterol
Approx. 95%
adherence;
4 participants (2
from each group)
were lost to
follow-up due to
personal reasons
None
Glycemic
control
markers
(insulin,
HOMA-IR,
QUICKI)
Lipid profile
(triglycerides,
VLDL-C, AIP)
Standard
biochemical
analyses, ELISA
for insulin,
HOMA-IR and
QUICKI
calculations
Significant
decrease in
serum insulin,
HOMA-IR,
triglycerides,
VLDL
cholesterol, and
AIP; significant
increase in
QUICKI in
synbiotic group
Improvement
in insulin
resistance
markers and
some lipid
parameters
Short
follow-up, no
SCFAs
measured in
stool

Nutrients 2024,16, 3916 14 of 28
Table 5. Cont.
Study
Reference
Post-Intervention
Parameters
Change in
Parameters (∆)
Comparative Effects
Adherence to
the Intervention Side Effects Primary
Outcomes
Secondary
Outcomes
Measurement
Methods Key Findings Author
Conclusions
Study
Limitations
Esmaeilinezhad
et al., 2019 [
37
]
SPJ: TGs: −26.4 mg/dL
TC: −13.4 mg/dL
LDL-C: −18.9 mg/dL
HDL-C: +10.7 mg/dL
SBP: −5.6 mmHg
Placebo: TGs: +4.0 mg/dL
TC: +4.3 mg/dL
LDL-C: +7.2 mg/dL
HDL-C: −3.7 mg/dL
SBP: +1.5 mmHg
∆TGs: SPJ:
−26.4 mg/dL vs.
placebo: +4.0 mg/dL
∆TC: SPJ:
−13.4 mg/dL vs.
placebo: +4.3 mg/dL
∆LDL-C: SPJ:
−18.9 mg/dL vs.
placebo: +7.2 mg/dL
∆HDL-C: SPJ:
+10.7 mg/dL vs.
placebo: −3.7 mg/dL
∆SBP: SPJ:
−5.6 mmHg vs.
placebo: +1.5 mmHg
Significant
improvement in
TGs, LDL-C, HDL-C,
and SBP in the SPJ
group compared to
placebo. Increases in
antioxidant capacity
(TAC) and
reductions in
oxidative stress
(MDA) were also
noted
High adherence
(≥90%);
reminder
messages were
sent weekly, and
empty bottles
were returned to
ensure
compliance
None
Lipid profile,
oxidative
stress (MDA,
TAC), hs-CRP,
blood pressure
Not specified
Standard
biochemical
analysis, ELISA
for hs-CRP,
MDA and TAC
measurements,
blood pressure
Significant
improvements
in lipid profile,
oxidative stress,
inflammation,
and blood
pressure in SPJ,
PJ, and SB
groups
compared to
placebo
Synbiotic
pomegranate
juice improved
metabolic,
oxidative, and
inflammatory
outcomes
No measure-
ment of gut
microbiota
changes or
body
composition
Gholizadeh
Shamasbi
et al., 2018 [
48
]
Prebiotic: LDL-C:
87.35 mg/dL
HDL-C: 46.15 mg/dL
Total cholesterol:
154.71 mg/dL
TGs: 94.22 mg/dL
FBS: 67.68 mg/dL
hs-CRP: 3.11 mg/dL
Free testosterone:
1.06 pg/mL
DHEA-S: 2.77 µg/mL
∆LDL-C:
−29.79 mg/dL
∆HDL-C:
+5.82 mg/dL
∆Total cholesterol:
−29.98 mg/dL
∆
TGs:
−
38.50 mg/dL
∆FBS: −11.24 mg/dL
∆hs-CRP:
−1.75 mg/dL
∆Free testosterone:
−0.32 pg/mL
∆DHEA-S:
−0.7 µg/mL
Significant reduction
in LDL-C, total
cholesterol,
triglycerides, FBS,
hs-CRP, DHEA-S,
and free testosterone
in the prebiotic
group compared to
placebo. HDL-C
increased
significantly in the
prebiotic group
High adherence
(weekly
follow-up calls
ensured
compliance)
Two
participants
experienced
mild
allergies
and discon-
tinued
interven-
tion
Lipid levels,
fasting
glucose,
hs-CRP,
DHEA-S, free
testosterone
Hirsutism,
menstrual
irregularity
Standard
biochemical
analyses, ELISA
for hormones,
Ferriman–
Gallwey scale
Significant
decrease in
LDL-C, total
cholesterol,
triglycerides,
FBS, hs-CRP,
DHEA-S, free
testosterone,
and hirsutism
score;
significant
increase in
HDL-C
Resistant
dextrin
regulates
metabolic
parameters and
androgen levels
in PCOS
Small sample
size,
participants
only over-
weight/obese
Arab et al.,
2022 [49]
Probiotic: SHBG:
40.06 ±9.14 nmol/mL
Total testosterone:
0.41 ±0.15 ng/mL
FAI: 3.22 ±1.2
DHEA-S:
6.84 ±2.9 nmol/L
∆SHBG: +3.95
nmol/mL
∆Total testosterone:
−0.01 ng/mL
∆FAI: −0.02
∆DHEA-S:
−0.06 nmol/L
Probiotic
supplementation
significantly
increased SHBG
compared to the
placebo group, but
no significant
changes were
observed in total
testosterone, FAI,
DHEA-S, or clinical
outcomes (acne,
hirsutism)
High adherence:
compliance
monitored via
phone calls, text
messages, and
capsule return
None
Hormonal and
clinical
parameters:
SHBG, LH,
FSH, DHEA-S,
TT, FAI
Acne,
hirsutism
Hormone
profiles by
electrochemilu-
minescence
immunoassays,
clinical signs
evaluated by
standardized
scales
Significant
increase in
SHBG; no
significant
improvements
in other
hormonal or
clinical
parameters
Probiotic sup-
plementation
improved
SHBG but not
other hormonal
or clinical
parameters
Self-report
instead of
bacterial
stool analysis,
short
duration

Nutrients 2024,16, 3916 15 of 28
Table 5. Cont.
Study
Reference
Post-Intervention
Parameters
Change in
Parameters (∆)
Comparative Effects
Adherence to
the Intervention Side Effects Primary
Outcomes
Secondary
Outcomes
Measurement
Methods Key Findings Author
Conclusions
Study
Limitations
Karamali et al.,
2018 [50]
Probiotic: SHBG:
72.2 ±31.9 nmol/L
Total testosterone:
1.1 ±0.8 ng/mL
mF-G scores: 12.4 ±3.8
hs-CRP:
2396.7 ±1588.6 ng/mL
TAC:
948.3 ±380.2 mmol/L
MDA: 1.9 ±0.6 µmol/L
∆SHBG:
+25.9 nmol/L
∆Total testosterone:
−0.2 ng/mL
∆mF-G scores: −1.7
∆hs-CRP:
−1150 ng/mL
∆TAC: +8.8 mmol/L
∆
MDA:
−
0.2
µ
mol/L
Probiotic
supplementation
significantly
increased SHBG,
decreased total
testosterone, mF-G
scores, hs-CRP, and
MDA levels, and
increased TAC
compared to the
placebo group. No
significant effects on
DHEA-S or other
metabolic profiles
Compliance
monitored via
capsule count
and daily SMS
reminders
None
Hormonal and
clinical
parameters:
SHBG, LH,
FSH, DHEA-S,
TT, FAI
Acne,
hirsutism
Hormonal
profile:
electrochem-
iluminescence-
based
immunometric
assays,
biomarkers and
clinical signs
evaluated
Significant
improvements
in SHBG,
decrease in
total
testosterone,
and hs-CRP
and TAC
Improvements
in SHBG,
testosterone,
and
inflammatory
markers
Short
duration,
other strain
combina-
tions or
prebiotics not
evaluated
Karimi et al.,
2020 [51]
Synbiotic: LDL:
92 ±19 mg/dL
HDL: 45 ±8 mg/dL
TC: 170 ±24 mg/dL
TGs: 141 ±78 mg/dL
∆LDL: −5.27 mg/dL
∆HDL: +1.71 mg/dL
∆TC: −5.2 mg/dL
(not significant)
∆TGs: −2.2 mg/dL
(not significant)
Synbiotic
supplementation
significantly
decreased LDL
levels and increased
HDL levels
compared to the
placebo group. No
significant effects
were found for total
cholesterol or
triglycerides
Compliance
monitored via
capsule count
and daily SMS
reminders
None
Lipids and an-
thropometric
measures:
LDL, HDL,
TC, TGs
Anthropometric
indicators:
weight, BMI,
WC, HC,
WHR
Lipid profile: TC,
TGs, HDL
measured by
colorimetric
methods,
anthropometric
indicators
measured with
digital scale
Significant
decrease in
LDL, increase
in HDL; no
differences in
other
anthropometric
measures
Improvements
in LDL and
HDL, no
changes in
other
parameters
Short
duration
limited to 12
weeks,
dietary
reporting
biases
Nasri et al.,
2018 [52]
Synbiotic: SHBG:
57.1 ±48.6 nmol/L
Total testosterone:
2.4 ±0.9 ng/mL
mF-G scores: 14.0 ±4.9
hs-CRP:
1970 ±1442.0 ng/mL
NO: 44.5 ±5.0 µmol/L
MDA: 2.1 ±0.4 µmol/L
∆SHBG:
+19.8 nmol/L
∆Total testosterone:
−0.4 ng/mL
∆mF-G scores: −1.3
∆hs-CRP:
−950 ng/mL
∆NO: +5.5 µmol/L
∆
MDA:
−
0.2
µ
mol/L
Synbiotic
supplementation
significantly
increased SHBG,
decreased mF-G
scores, FAI, hs-CRP,
and NO levels
compared to the
placebo group. No
significant effects
were found for other
hormonal markers
and biomarkers of
oxidative stress
Compliance
monitored via
capsule count
and daily SMS
reminders.
None
Hormonal,
inflammation,
and oxidative
stress: SHBG,
LH, FSH,
DHEA-S, TT,
FAI
Inflammation
biomarkers:
hs-CRP
Hormonal
profile: ELISA
kits (DiaMetra,
Italy),
biomarkers:
spectrophoto-
metric methods
for NO, TAC,
GSH, MDA
Significant
increase in
SHBG,
significant
decrease in
hs-CRP, NO,
and mF-G
scores
Synbiotics
improved
SHBG, NO,
hs-CRP, and
mF-G scores
Short
duration,
small sample
size, no
comparison
of different
combina-
tions
Abbreviations: HOMA-IR = Homeostatic Model Assessment of Insulin Resistance; FBS = fasting blood glucose; QUICKI = Quantitative Insulin Sensitivity Check Index; HDL-C =
high-density lipoprotein cholesterol; LDL-C = low-density lipoprotein cholesterol; TGs = triglycerides; VLDL = very low-density lipoprotein; CRP = C-reactive protein; hs-CRP =
high-sensitivity C-reactive protein; SHBG = sex hormone-binding globulin; FAI = free androgen index; DHEA-S = dehydroepiandrosterone sulfate; mF-G = modified Ferriman–Gallwey
scores; TAC = total antioxidant capacity; MDA = malondialdehyde; NO = nitric oxide; SPJ = synbiotic pomegranate juice; PJ = pomegranate juice; SB = synbiotic beverage; FPG = fasting
plasma glucose; ELISA = Enzyme-Linked Immunosorbent Assay; SBP = systolic blood pressure; LH = luteinizing hormone; FSH = follicle-stimulating hormone; TT = total testosterone;
WC = waist circumference; HC = hip circumference; WHR = waist-to-hip ratio; GSH = glutathione.

Nutrients 2024,16, 3916 16 of 28
Shoaei et al., 2021 [
39
] found no significant reduction in HOMA-IR; however, a deeper
analysis revealed a potential reduction in insulin levels, which may have been obscured by
the study’s short duration. Darvishi et al., 2020 [
40
] noted improvements in glycemic indices
and HDL cholesterol with synbiotics, though the absence of gut microbiota data limited
mechanistic insights. Conversely, Karimi et al., 2018 [
45
] observed no significant changes in
HOMA-IR or FBS but found a decrease in apelin 36, suggesting an anti-inflammatory effect
rather than direct metabolic impacts.
Samimi et al., 2018 [
46
] highlighted synbiotics’ positive effects on insulin sensitivity
and lipid metabolism, although total cholesterol and LDL levels remained unchanged.
Gholizadeh Shamasbi et al., 2018 [
48
] demonstrated prebiotics’ ability to lower LDL, total
cholesterol, and inflammatory markers, while also reducing free testosterone, indicat-
ing potential benefits for hyperandrogenism. Arab et al., 2022 [
49
] and Karamali et al.,
2018 [
50
] focused on hormonal regulation, showing mixed results in clinical symptoms of
hyperandrogenism but clear improvements in SHBG and testosterone levels.
Karimi et al., 2020 [
51
] and Nasri et al., 2018 [
52
] supported the positive effects of
synbiotics on lipid profiles and inflammation, although further research with longer follow-
ups is needed to confirm these findings across diverse populations. Across the studies,
adherence rates were generally high, and side effects were minimal, with only a few
instances of mild allergies reported.
Key findings across the studies include significant reductions in HOMA-IR, improve-
ments in lipid profiles, enhanced hormonal balance, and reductions in inflammatory
markers. However, limitations such as small sample sizes, short durations, and the absence
of comprehensive gut microbiota assessments were common. For instance, Esmaeilinezhad
et al., 2018 [
38
] and Darvishi et al., 2020 [
40
] were limited by their small sample sizes and
lack of long-term follow-up, while studies like Arab et al., 2022 [
49
] and Nasri et al., 2018 [
52
]
faced challenges such as short durations and non-standardized measurement methods.
Figure 2is organized into three sections: the distribution of intervention types, their
impact on specific clinical markers, and the relationship between intervention duration and
achieved effects.
In Figure 2A, a pie chart illustrates the distribution of intervention types across the
studies. Notably, combined probiotics and prebiotics (synbiotics) were the most frequently
used interventions, comprising 70% of the total. Probiotics alone accounted for 20%, while
prebiotics alone represented only 10%. This distribution highlights a strong preference
for synbiotic treatments, likely due to the anticipated synergistic benefits of combining
probiotics with prebiotics for broader metabolic improvements.
Figure 2B depicts the changes in three key clinical parameters related to insulin
resistance: HOMA-IR, FBS, and insulin levels. Synbiotics demonstrated the most significant
impact, with notable reductions in all three parameters. Specifically, HOMA-IR decreased
by
−
0.57, indicating enhanced insulin sensitivity. Additionally, the synbiotic group showed
the greatest reductions in both insulin and FBS, underscoring its potential effectiveness.
Probiotic interventions also yielded improvements, albeit to a lesser extent, with moderate
reductions in HOMA-IR and insulin levels. Prebiotics alone had a smaller yet beneficial
effect. In contrast, the placebo group experienced an increase in HOMA-IR by +1.23,
reflecting a rise in insulin resistance without any therapeutic intervention.
Lastly, Figure 2C explores the relationship between the duration of the interventions
and the changes in clinical outcomes. The data reveal that longer intervention periods,
typically around 12 weeks, are associated with greater improvements in HOMA-IR, FBS,
and insulin levels. This suggests that extended treatment durations are crucial for achieving
substantial metabolic benefits. While shorter interventions, usually lasting 8 weeks, also
resulted in improvements, the effects were less pronounced compared to longer durations.
Therefore, the figure underscores the importance of sustained treatment to maximize
improvements in insulin sensitivity and glycemic control.
Overall, Figure 2emphasizes the superior effectiveness of synbiotic interventions in
improving metabolic markers in women with PCOS, particularly when administered over

Nutrients 2024,16, 3916 17 of 28
longer periods. The preference for combined probiotic and prebiotic treatments, along with
the observed dose–response relationship between intervention duration and metabolic
outcomes, highlights the potential of synbiotics as a comprehensive approach to managing
PCOS-related metabolic disturbances.
3.5. Risk-of-Bias Assessment Results
The risk-of-bias assessment for the studies, taken from the RevMan 5.4 analysis, shows
that the overall quality of the included trials was robust. Most domains in Figure 3present
a low risk of bias, and this is especially true for domains like the generation of random
sequences, where almost all studies had appropriate randomization methods to avoid
selection bias. Allocation concealment was also ingeniously handled, as most of the studies
scored as having low risk, meaning the actual process of allocating participants to either
intervention or control was well-blinded to reduce selection bias. However, in some
instances, allocation concealment was rated as unclear due to the need for further explicit
reporting in the studied papers about how this process was conducted; hence, a slight
doubt on selection bias remained.
Nutrients 2024, 16, x FOR PEER REVIEW 20 of 31
3.5. Risk-of-Bias Assessment Results
The risk-of-bias assessment for the studies, taken from the RevMan 5.4 analysis,
shows that the overall quality of the included trials was robust. Most domains in Figure 3
present a low risk of bias, and this is especially true for domains like the generation of
random sequences, where almost all studies had appropriate randomization methods to
avoid selection bias. Allocation concealment was also ingeniously handled, as most of the
studies scored as having low risk, meaning the actual process of allocating participants to
either intervention or control was well-blinded to reduce selection bias. However, in some
instances, allocation concealment was rated as unclear due to the need for further explicit
reporting in the studied papers about how this process was conducted; hence, a slight
doubt on selection bias remained.
Figure 3. Cochrane risk-of-bias assessment for randomized studies of interventions in this
systematic review. (A) Risk-of-bias summary: Review of the authors’ judgments about each risk-of-
bias item for each included study. The symbol “+” indicates a low risk of bias, the symbol “?”
indicates an unclear risk of bias. The colors used are green for low risk of bias, yellow for unclear
risk of bias [37–40,45,46,48–52]. (B) Risk-of-bias graph: Review of the authors’ judgments about each
risk-of-bias item presented as percentages across all included studies. Figure created by RevMan 5
(accessed on 24 August 2024).
Performance bias, or blinding of participants and personnel, was a less easily
surmountable problem. A number of this review’s component studies, including many of
the most robustly designed, were considered to be at high risk. This was largely due to
the inherent nature of the clinical trials in this field, since maintaining blinding for
participants and personnel was difficult because of obvious differences between active
interventions (probiotics, synbiotics, or prebiotics) and placebos. Lack of blinding may
Figure 3. Cochrane risk-of-bias assessment for randomized studies of interventions in this systematic
review. (A) Risk-of-bias summary: Review of the authors’ judgments about each risk-of-bias item
for each included study. The symbol “+” indicates a low risk of bias, the symbol “?” indicates
an unclear risk of bias. The colors used are green for low risk of bias, yellow for unclear risk of
bias
[37–40,45,46,48–52]
. (B) Risk-of-bias graph: Review of the authors’ judgments about each risk-of-
bias item presented as percentages across all included studies. Figure created by RevMan 5 (accessed
on 24 August 2024).

Nutrients 2024,16, 3916 18 of 28
Performance bias, or blinding of participants and personnel, was a less easily sur-
mountable problem. A number of this review’s component studies, including many of
the most robustly designed, were considered to be at high risk. This was largely due
to the inherent nature of the clinical trials in this field, since maintaining blinding for
participants and personnel was difficult because of obvious differences between active
interventions (probiotics, synbiotics, or prebiotics) and placebos. Lack of blinding may
introduce performance bias, which could potentially influence the behavior of participants
or the expectations of the researchers [53].
On the other hand, blinding of outcome assessment or detection bias was generally
well managed in most studies. In most trials, the assessors of clinical outcomes were blinded
to the intervention groups, which minimized the occurrence of biased measurements of
outcome. Attrition bias or incomplete outcome data showed consistent low risk across the
studies. Most trials reported participant dropouts and addressed missing data adequately,
with no studies displaying a high risk of bias in this domain. Selective reporting was
consistently rated as low risk across all studies, indicating comprehensive reporting of
both positive and negative outcomes. The studies demonstrated minimal external factors
influencing the results, as reflected by the low risk of other biases.
When we combine these results with the risk-of-bias assessment using the Jadad scale
(see Table 6), it is clear that the included studies are methodologically strong and have
minimal risk of bias that could undermine their findings. Every study scored a perfect 5
out of 5 on the Jadad scale, demonstrating excellent quality. This top score highlights their
rigorous randomization, effective blinding, and transparent handling of withdrawals and
dropouts, all of which make their results more reliable and trustworthy.
Table 6. Jadad scale assessment.
Study Name Randomization
(0–2) Blinding (0–2)
Withdrawals/Dropouts
(0–1)
Total Score (Out of 5)
Esmaeilinezhad et al., 2018 [38] 2 2 1 5
Shoaei et al., 2021 [39] 2 2 1 5
Darvishi et al., 2020 [40] 2 2 1 5
Karimi et al., 2018 [45] 2 2 1 5
Samimi et al., 2018 [46] 2 2 1 5
Esmaeilinezhad et al., 2019 [37] 2 2 1 5
Gholizadeh Shamasbi et al., 2018 [48] 2 2 1 5
Arab et al., 2022 [49] 2 2 1 5
Karamali et al., 2018 [50] 2 2 1 5
Karimi et al., 2020 [51] 2 2 1 5
Nasri et al., 2018 [52] 2 2 1 5
4. Discussion
4.1. Main Findings
This systematic review sought to answer the following question: How does sup-
plementation with probiotics, prebiotics, or synbiotics, compared to placebo or standard
treatments, affect insulin resistance and hormonal balance in women with PCOS, influenc-
ing their metabolic health and quality of life? The relevance of this study lies in the need
to identify effective and safe interventions that address the characteristic metabolic and
hormonal imbalances of PCOS, a condition that significantly impacts the quality of life of
women of reproductive age.
The results demonstrated multiple benefits associated with probiotic and synbiotic-
based interventions in women with PCOS. Significant reductions were observed in the
HOMA-IR index, indicating substantial improvements in insulin sensitivity. Studies
such as those by Esmaeilinezhad et al., 2018 [
38
], Shoaei et al., 2021 [
39
], and Samimi
et al., 2018 [
46
] reported notable decreases in fasting glucose and insulin, reflecting better
metabolic function.

Nutrients 2024,16, 3916 19 of 28
Additionally, there were improvements in lipid profiles, with reductions in LDL
cholesterol and triglycerides and increases in HDL cholesterol. Research by Esmaeilinezhad
et al., 2019 [
37
] and Karimi et al., 2020 [
51
] supports these findings, suggesting a decrease
in the cardiovascular risk associated with PCOS.
Regarding hormonal balance, increases in SHBG levels and decreases in total testos-
terone were recorded, suggesting a reduction in the hyperandrogenemia typical of PCOS.
Studies such as those by Arab et al., 2022 [
49
] and Karamali et al., 2018 [
50
] demonstrated
improvements in clinical symptoms of hyperandrogenism, which could translate into a
better quality of life for patients. However, the limited number of studies assessing SHBG
and hirsutism requires careful interpretation of these findings, as the evidence is not yet
conclusive. Future research should aim to clarify the effect of probiotics and synbiotics
on SHBG and clinical symptoms such as hirsutism to better understand the therapeutic
potential of these interventions in managing hyperandrogenism in PCOS. According to
the meta-analysis by Shamasbi et al., 2020 [
54
], the use of probiotics and synbiotics in
women with PCOS led to a significant increase in SHBG levels compared to the placebo
group, suggesting an improvement in the hormonal profile. However, regarding hirsutism
symptoms, the same study did not find significant differences between the intervention
and control groups. This indicates that probiotics and synbiotics may not have a direct
impact on reducing hirsutism, and their effect on this condition remains inconclusive based
on current evidence.
Reductions were also observed in inflammatory markers like hs-CRP, highlighting
the anti-inflammatory potential of these interventions [
45
,
52
]. Reducing systemic inflam-
mation is crucial given its role in the pathophysiology of PCOS and its impact on overall
metabolic health.
It is important to note that interventions with synbiotics consistently showed the most
significant benefits compared to probiotics and prebiotics administered separately. Combi-
nations of probiotics and prebiotics offered more robust and comprehensive improvements,
possibly due to the synergy between both components that enhances modulation of the gut
microbiota and optimizes metabolic and hormonal functions [38,40].
The most commonly used probiotic strains included Lactobacillus acidophilus,Lacto-
bacillus casei,Lactobacillus rhamnosus,Bifidobacterium longum,Streptococcus thermophilus, and
Bacillus coagulans. The most common pharmaceutical forms were capsules and synbiotic
juices, with durations ranging between 8 and 12 weeks. Synbiotic combinations produced
more pronounced effects on both insulin resistance and hormonal balance.
Finally, the high adherence rate and minimal reported side effects reinforce the viability
and safety of these interventions. Most studies reported adherence rates above 90%, and
adverse effects were insignificant or nonexistent [
38
,
39
]. This suggests that probiotics and
synbiotics can be effectively integrated into existing treatment regimens, offering a viable
alternative to conventional pharmacological therapies with lower associated risks.
4.2. Comparison with Previous Studies
Our findings are consistent with previous research highlighting the beneficial effects
of probiotics, prebiotics, and synbiotics on metabolic and hormonal parameters in women
with PCOS. Meta-analyses and systematic reviews have demonstrated improvements in
insulin resistance, lipid profiles, and hormonal balance.
For example, Miao et al., 2021 [
55
] concluded that supplementation with probiotics
and synbiotics improved insulin resistance in women with PCOS, supporting the idea that
modulation of the gut microbiota positively influences metabolic and endocrine functions.
Musazadeh et al., 2023 [
56
] found that synbiotics significantly improved lipid profiles and
anthropometric parameters, suggesting a beneficial effect on the management of obesity
and related disorders.
Studies such as those by Cozzolino and Vitagliano, 2019 [
57
] and Karamali et al.,
2018 [
50
] reported that probiotic supplementation was associated with improvements
in metabolic, hormonal, and inflammatory parameters. Probiotics have been found to

Nutrients 2024,16, 3916 20 of 28
increase levels of SHBG, decrease total testosterone, and reduce hs-CRP and MDA. Synbiotic
supplementation also showed beneficial effects on SHBG and inflammatory markers (Nasri
et al., 2018 [52]).
Although some research, such as that by Angoorani et al., 2023 [
41
], suggests that
probiotics are more effective than synbiotics on certain parameters, our findings indicate
that synbiotics may have a broader impact on metabolism. These discrepancies high-
light the need for more research to determine the most effective intervention and under
what circumstances.
Inconsistencies in the literature underscore the importance of strain specificity, dosage,
and treatment duration. McFarland et al., 2018 [
58
] emphasized that different strains within
the same species can have variable effects on health, underscoring the need for specific
clinical guidelines. Our study addresses this gap by identifying probiotic strains that show
greater efficacy in improving metabolic and hormonal parameters in women with PCOS.
4.3. Impact of Probiotics on Insulin Resistance and Hormonal Balance in Polycystic
Ovary Syndrome
Insulin resistance is fundamental in the pathogenesis of PCOS [
59
]. There is a link
between gut microbiota dysbiosis and the development of PCOS, especially related to
insulin resistance and obesity [
60
]. In this context, probiotics and synbiotics have shown
promising effects in improving insulin sensitivity.
These microorganisms modify the composition and diversity of the gut microbiota,
restoring a healthy balance of bacteria that positively impacts metabolic and hormonal path-
ways. Strains such as Lactobacillus and Bifidobacterium have demonstrated improvements
in gut dysbiosis, correlating with more favorable sexual hormone levels and metabolic
parameters [59].
Probiotics increase the production of short-chain fatty acids (SCFAs) like butyrate,
propionate, and acetate, which have anti-inflammatory properties and improve insulin
sensitivity. SCFAs maintain the integrity of the intestinal barrier and modulate immune
responses [
59
,
61
,
62
], activate G protein-coupled receptors, and promote the release of
peptides such as GLP-1 and PYY, contributing to glucose homeostasis [63].
Reducing systemic inflammation is another key mechanism. Chronic low-grade in-
flammation in PCOS interferes with insulin signaling. Probiotics decrease pro-inflammatory
cytokines like TNF-
α
and IL-6, strengthen the intestinal barrier, and reduce the translocation
of lipopolysaccharides into the bloodstream, improving insulin sensitivity [54].
Additionally, probiotics can influence bile acid metabolism, which acts as signaling
molecules in glucose and lipid metabolism through receptors like FXR and TGR5 [
64
].
By modifying this metabolism, they enhance metabolic health [
65
].
In vitro
studies have
shown that probiotic complexes can alter bile acid profiles and microbial composition,
increasing beneficial bacteria and reducing harmful metabolites [66].
Regarding hormonal regulation, probiotics can affect levels of sex hormones such as
testosterone, LH, and FSH. Strains of Lactobacillus and Bifidobacterium have demonstrated
reductions in testosterone and improvements in hormonal profiles, possibly mediated by
the gut–brain axis and microbial modulation of hormonal metabolism [
54
,
59
]. By improving
insulin resistance, they reduce hyperinsulinemia, decreasing ovarian androgen production
and increasing levels of SHBG, which reduces free testosterone [67].
Probiotics also enhance antioxidant capacity by elevating total glutathione and total
antioxidant capacity, mitigating oxidative stress in PCOS [
54
]. They improve lipid pro-
files by reducing triglycerides, total cholesterol, and LDL, benefiting the management of
associated dyslipidemia [68,69].
Clinical evidence supports these mechanisms. Studies have reported significant
reductions in fasting glucose, insulin levels, and HOMA-IR in women with PCOS receiving
probiotic and synbiotic supplementation [
55
]. Decreases in testosterone, increases in SHBG,
and improvements in symptoms like hirsutism and menstrual irregularities were also
observed [50].

Nutrients 2024,16, 3916 21 of 28
Therefore, probiotics positively impact insulin resistance and hormonal balance in
PCOS by modulating the gut microbiota, increasing SCFAs, reducing systemic inflamma-
tion, and improving insulin signaling. These combined effects contribute to better glycemic
and hormonal control, playing a crucial role in the comprehensive management of PCOS.
4.4. Limitations of the Included Studies
Despite these promising findings, it is essential to consider the limitations and risk of
bias present in the reviewed studies to interpret the results accurately.
A key limitation is the small sample size in most studies, which can decrease statistical
power and increase the risk of type II errors [
29
,
70
]. Additionally, all studies were conducted
in Iran and focused on overweight or obese women of reproductive age, limiting the
generalizability of the findings to more diverse populations.
The short duration of the interventions, generally between 8 and 12 weeks, might not
be sufficient to observe their long-term effects or the sustainability of the benefits. Longer
studies are needed to determine whether the improvements are maintained over time and
to evaluate their impact on clinical outcomes such as menstrual regularity and fertility, also
with probiotic doses ≥1010 CFU/day and without concurrent energy restriction [71].
The lack of comprehensive evaluations of the gut microbiota and body composition
measurements limits the understanding of underlying mechanisms. Moreover, variability
in doses, strains, and forms of the interventions makes it difficult to determine the most
effective regimen and complicates comparisons between studies [
29
,
72
,
73
]. For example,
some studies report an increase in Bacteroides spp. and Lactobacillus spp. in PCOS patients,
while others highlight a decrease in Prevotella spp. and Lachnospira spp. [
29
,
73
]. This
inconsistency in the bacterial strains studied and reported makes it challenging to identify
specific microbial patterns associated with PCOS.
The absence of control and detailed reporting on dietary intake and physical activity
is another limitation, as these factors can influence metabolic and hormonal parameters,
introducing biases in interpretation.
4.5. Limitations of the Review
Despite efforts to conduct a thorough and rigorous systematic review, this research
presents several limitations that should be considered when interpreting the results and
planning future research in this field.
Firstly, there is the possibility of having excluded unpublished studies or studies
published in languages other than English and Spanish. This review was based on searches
in international databases and the literature accessible in these languages, which may have
omitted relevant research published in other languages. This linguistic bias may limit the
completeness of the evidence collected and lead to an overestimation or underestimation
of the effects of the interventions.
Additionally, the inability to perform a quantitative meta-analysis due to heterogeneity
among the included studies is a significant limitation. Differences in study designs, partici-
pant populations, interventions (types and doses of probiotics, prebiotics, and synbiotics),
intervention duration, and outcome measures made it difficult to statistically combine the
data. This heterogeneity impedes the quantitative synthesis of results and limits the ability
to draw more general and robust conclusions about the efficacy of the interventions [
29
,
73
].
Another important limitation is the geographic and demographic homogeneity of the
included studies. Most clinical trials were conducted in Iran and focused on overweight
or obese women of reproductive age diagnosed with PCOS according to the Rotterdam
criteria. This lack of diversity in the studied populations limits the generalizability of the
findings to women of different ethnic, cultural, and socioeconomic backgrounds, as well as
those with different clinical characteristics of PCOS.
Additionally, the variable methodological quality of the included studies represents
a limitation. Although many studies presented low risk of bias in areas such as random
sequence generation and allocation concealment, others showed risks in aspects like blind-

Nutrients 2024,16, 3916 22 of 28
ing, sample size, and follow-up duration. These methodological limitations can influence
the internal validity of the studies and affect confidence in the reported findings.
Finally, the lack of standardized outcome measures and comprehensive evaluations of
the gut microbiota hinders the comparison of studies and the understanding of underlying
mechanisms. The bacterial strains and taxa examined vary across studies, with researchers
often focusing on different bacterial families, genera, or species. Additionally, inconsis-
tencies in methods of assessing insulin resistance, hormonal profiles, and inflammatory
markers further complicate the ability to draw robust and comparable conclusions.
4.6. Clinical Implications
The findings of this systematic review suggest that synbiotic supplementation may be
a valuable complementary strategy in the management of PCOS. Improvements in insulin
resistance, lipid profiles, and hormonal balance indicate that synbiotics could address
central metabolic and endocrine alterations of PCOS.
Variability in individual responses to probiotics and prebiotics highlights the im-
portance of personalized treatment approaches. Factors such as initial gut microbiota
composition, metabolic status, hormonal profiles, dietary habits, and genetic predisposi-
tions can influence the effectiveness of these interventions. Personalizing probiotic and
prebiotic regimens according to each patient’s individual profile can maximize therapeutic
outcomes [74–76].
Clinicians should consider the following factors [74–78]:
•
Selection of specific strains: different probiotic strains can have varied effects on
metabolic and hormonal parameters. Choosing strains with demonstrated efficacy
could enhance treatment outcomes.
•
Dosage and formulation: adjusting the dosage and choosing the appropriate formu-
lation (capsules, powders, functional foods) according to patient preferences and
tolerance can improve adherence and effectiveness.
•
Comprehensive evaluation: assessing the patient’s overall health status, including
metabolic markers, hormonal levels, and lifestyle factors, can help develop a tailored
supplementation plan.
The personalization of synbiotic interventions could be especially beneficial for pa-
tients who have not responded adequately to standard treatments or who experience
adverse effects from pharmacological therapies. Collaboration among healthcare profes-
sionals is essential to effectively implement personalized strategies [74,79,80].
Moreover, the management of PCOS often requires a multidisciplinary approach that
addresses metabolic, reproductive, and psychological aspects. Synbiotic supplementation
can be integrated into this care model as a complementary therapy. Healthcare professionals
should educate patients about the potential benefits and limitations of probiotics and
prebiotics, emphasizing that these supplements do not replace conventional treatments but
can enhance overall management when used in conjunction [41,81].
Regular monitoring of metabolic and hormonal parameters is necessary to evaluate the
effectiveness of the intervention and adjust treatment as needed. Promoting a balanced diet,
regular physical activity, and adherence to medical therapies will optimize outcomes [
41
,
82
].
Although evidence supports the potential benefits of synbiotic supplementation, clini-
cians should be cautious due to variability in available products. They should consider the
following factors:
•
Quality and standardization: selecting high-quality products from reputable man-
ufacturers is crucial, as efficacy depends on the viability and concentration of the
strains used.
•
Regulation: dietary supplements are not always subject to the same regulatory stan-
dards as medications. Clinicians should guide patients toward products proven in
safety and efficacy.

Nutrients 2024,16, 3916 23 of 28
•
Patient education: informing patients about the importance of adherence, possible
side effects, and realistic expectations will enhance satisfaction and compliance with
the supplementation regimen.
Advances in microbiome research and personalized medicine could offer tools for
more precise interventions. Microbiota profiling could identify specific dysbiosis patterns
in women with PCOS, allowing for targeted probiotic and prebiotic therapies. Additionally,
larger and longer clinical trials are required to establish standardized guidelines and
determine optimal strains, doses, and durations of supplementation [41,83–86].
4.7. Recommendations for Future Research
More research is needed to address the current limitations. Future studies should
be larger and multicentric randomized trials including diverse populations. Extending
the duration of trials to six months or more will allow for the evaluation of the long-term
efficacy and sustainability of the benefits.
Incorporating detailed analyses of the gut microbiota and metabolomic evaluations
will help understand the biological mechanisms behind the observed clinical effects. Ad-
vanced techniques such as 16S rRNA gene sequencing and metagenomics can provide
valuable information on how interventions alter microbial composition and metabolic
pathways. Standardizing probiotic strains, doses, and administration forms will facilitate
comparison between studies and the development of evidence-based clinical recommenda-
tions [87–89].
Including participants with different manifestations of PCOS will allow us to under-
stand how interventions affect each subgroup and personalizing treatments. Evaluating
clinical outcomes that directly impact quality of life, such as menstrual regularity and
improvement of symptoms like hirsutism, is fundamental.
It is crucial to assess long-term safety and explore strategies to improve adherence,
such as education and support programs. Investigating combination with other therapies
may reveal additional benefits and optimize treatment protocols.
Conducting economic evaluations will help determine the value of these interventions
compared to existing treatments, informing healthcare policy decisions. Incorporating
patient perspectives in the study design will ensure that interventions address their needs,
enhancing comprehensive care.
5. Conclusions
The studies reviewed in this review provide promising evidence on the use of synbi-
otics in the management of PCOS. The results indicate that synbiotic supplementation can
significantly improve insulin resistance, lipid profiles, and hormonal balance in women
with PCOS, suggesting a therapeutic potential to address the metabolic and endocrine
alterations associated with this condition. These improvements can have a positive impact
on the metabolic health and quality of life of patients, offering an alternative or complement
to conventional therapies. However, greater validation is required through future research
that addresses the current limitations.
Although the studies show encouraging results, the current body of evidence is
limited by methodological constraints such as small sample sizes, homogeneity in the
populations studied, relatively short intervention durations, and a lack of standardization
in interventions and measurements. These limitations affect the generalization of the results
and underscore the need to conduct additional studies with more robust and diversified
designs. Only through larger, longer-term studies with standardized methodologies can
the efficacy and safety of synbiotics in this population be confirmed, allowing for their
evidence-based integration into clinical practice.

Nutrients 2024,16, 3916 24 of 28
Author Contributions: Conceptualization, D.M.G. and Y.L.; methodology, D.M.G. and Y.L.; software,
J.G.; validation, D.M.G., M.E. and A.G.; formal analysis, D.M.G.; investigation, D.M.G.; resources,
Y.L. and J.G.; data curation, S.V.C.; writing—original draft preparation, Y.L., S.V.C., D.M.G., I.P., A.G.
and M.E.; writing—review and editing, D.M.G. and I.P.; visualization, I.P.; supervision, Y.L.; project
administration, Y.L.; funding acquisition, Y.L. All authors have read and agreed to the published
version of the manuscript.
Funding: This research has been funded by Dirección General de Investigaciones de la Universidad
Santiago de Cali, Convocatoria Interna No. 01–2024.
Data Availability Statement: Data are contained within the article.
Acknowledgments: This research has been funded by Dirección General de Investigaciones de la
Universidad Santiago de Cali, Convocatoria Interna No. 01–2024. We thank the Universidad Santiago
de Cali for their financial and academic support in the preparation of this manuscript. All individuals
included in this section have given their consent to be acknowledged.
Conflicts of Interest: The authors declare no conflicts of interest.
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