Abstract

   Modern treatment, a healthy diet, and physical activity routines lower
   the risk factors for metabolic syndrome; however, this condition is
   associated with all-cause and cardiovascular mortality worldwide. This
   investigation involved a randomized controlled trial, double-blind,
   parallel study. Fifty-eight participants with risk factors of metabolic
   syndrome according to the inclusion criteria were randomized into two
   groups and given probiotics (Lacticaseibacillus paracasei MSMC39-1 and
   Bifidobacterium animalis TA-1) (n = 31) or a placebo (n = 27). The
   participants had a mean age of 42.29 ± 7.39 and 43.89 ± 7.54 years in
   the probiotics and placebo groups, respectively. Stool samples,
   anthropometric data, and blood chemistries were taken at baseline and
   at 12 weeks. The primary outcome was achieved by the probiotics group
   as their low-density lipoprotein-cholesterol level dramatically lowered
   compared to the placebo group (the difference was 39.97 ± 26.83 mg/dl,
   p-value <0.001). Moreover, significant reductions in body weight, body
   mass index, waist circumference, systolic blood pressure, and total
   cholesterol were observed in the volunteers treated with probiotics
   compared to the placebo. In the gut microbiome analysis, the results
   showed statistically significant differences in the beta diversity in
   the post-intervention probiotics group. Blautia, Roseburia,
   Collinsella, and Ruminococcus were among the gut microbiomes that were
   more prevalent in the post-intervention probiotics group. In addition,
   this group exhibited increases in the predicted functional changes in
   ATP-binding cassette (ABC) transporters, as well as ribonucleic acid
   transport, the biosynthesis of unsaturated fatty acids,
   glycerophospholipid metabolism, and pyruvate metabolism. In conclusion,
   this research demonstrated that the probiotics L. paracasei MSMC39-1
   and B. animalis TA-1 have the efficacy to lower risk factors associated
   with metabolic syndrome.

Introduction

   Metabolic syndrome is characterized by a cluster of clinical features
   and metabolic abnormalities, including dyslipidemia, insulin
   resistance, hypertension, and abdominal obesity, which together
   increase the risk of developing cardiovascular disease and type 2
   diabetes mellitus [[40]1, [41]2]. It affects approximately 20% of the
   population, impacting millions of lives globally [[42]3]. Many
   countries encourage their citizens to modify their dietary habits and
   engage in regular exercise to prevent and reduce the risk factors
   associated with metabolic syndrome [[43]4]. Despite these efforts, the
   condition remains linked to increased all-cause and cardiovascular
   mortality [[44]5].

   The gastrointestinal tract is colonized by the intestinal microbiota, a
   key environmental factor that directly influences host health and
   contributes to the exacerbation of various diseases [[45]6–[46]9].
   Dysbiosis, an imbalance in the microbiota, reduces its diversity and
   function, leading to metabolic issues [[47]10]. A high-fat diet can
   worsen dysbiosis by increasing circulating lipopolysaccharide (LPS) and
   lipid levels, as well as compromising the intestinal barrier [[48]11].
   Additionally, dysbiosis may contribute to chronic inflammation and the
   development of obesity, diabetes mellitus, and metabolic syndrome
   through interactions between genetic and environmental factors [[49]12,
   [50]13]. Treatment for metabolic syndrome and obesity-related metabolic
   endotoxemia involves preventing microbial dysbiosis and maintaining
   intestinal barrier integrity [[51]14].

   According to Hill et al. [[52]15], the consensus statement that the
   International Scientific Association for Probiotics and Prebiotics
   (ISAPP) proposed for the proper usage of the term probiotic refers to
   live microorganisms that, when administered in adequate amounts, confer
   a health benefit on the host. Commercial strains are more likely to
   contain probiotics from the genera Lactobacillus and Bifidobacterium
   [[53]16]. The key health benefits of probiotics include immune
   modulation, enhanced mineral and vitamin absorption, constipation
   relief, microbiome regulation, post-antibiotic microbiome
   stabilization, increased gastrointestinal resistance to pathogens, and
   pathogen reduction through short-chain fatty acid (SCFA) production
   [[54]17–[55]19].

   Probiotics offer a potential strategy for managing body weight as well
   as metabolic syndrome by modulating the gut microbiome [[56]20,
   [57]21]. They help maintain microbial balance and may reduce the risk
   of metabolic syndrome by controlling inflammation. A meta-analysis
   showed that probiotics, compared to placebos, significantly reduce body
   weight, fat mass, and the body mass index (BMI), supporting their role
   in improving metabolic health [[58]22, [59]23]. Probiotic species like
   Bifidobacterium longum, Lactobacillus acidophilus, and Lactobacillus
   gasseri have demonstrated benefits by enhancing lipid metabolism,
   upregulating carbohydrate transport and metabolism genes, and improving
   digestion. They also modulate bile acid metabolism, reduce plasma
   glucose, cholesterol, and triglycerides, promote bile salt
   deconjugation, and aid in weight loss [[60]24]. A 12-week mice study
   confirmed that L. paracasei HII01, xylo-oligosaccharides (XOS), and
   synbiotics improved dyslipidemia and insulin sensitivity, enhancing
   metabolic functions [[61]25]. Similarly, a randomized
   placebo-controlled trial found L. plantarum PBS067, L. acidophilus
   PBS066, and L. reuteri PBS072, along with prebiotics significantly
   reduced glucose, lipids, and inflammatory mediators in metabolic
   syndrome patients [[62]26].

   Interestingly, few clinical studies demonstrate the effect of
   probiotics on metabolic syndrome. Therefore, a double-blinded,
   randomized controlled trial was conducted to evaluate the efficacy of
   probiotics L. paracasei MSMC39-1 and B. animalis TA-1 in modulating gut
   microbiota and reducing the risk factors of metabolic syndrome.

Materials and methods

Subject enrollment

   This study was a randomized, double-blind, controlled, parallel-design
   trial. The study population comprised 60 participants who met the
   inclusion criteria for metabolic syndrome risk factors and were
   recruited from the outpatient clinic at the Faculty of Medicine,
   Srinakharinwirot University, between September 29, 2022, and April 5,
   2023. Stratified permuted block randomization was utilized to assign
   the participants into two groups. Group 1 received probiotics,
   consisting of Lacticaseibacillus paracasei MSMC39-1 (formerly
   Lactobacillus paracasei) at a dose of 1.0 x 10^9 colony-forming units
   (CFU) and Bifidobacterium animalis TA-1 (1.0 x 10^9 CFU), along with a
   vegetable-based pellet. Group 2 received a placebo vegetable-based
   pellet. The participants in each group consumed five tablets (250
   milligrams [mg]) per tablet), totaling 1,250 mg daily, 60 minutes
   before breakfast, for 12 weeks. The tablets were manufactured at a good
   manufacturing practice (GMP) certified food production facility.
   Probiotics with a vegetable-based pellet and a placebo vegetable-based
   pellet were compressed into tablets using microcrystalline cellulose
   (MCC) as a binder to enhance cohesion. The tablets were coated with
   hydroxypropyl methylcellulose (HPMC) to protect against moisture.

   After being randomized into two groups, the participants’ history,
   physical examination, blood test, and fresh stool were recorded at
   baseline and 12 weeks after the intervention. In this double-blind
   study, the probiotic and placebo capsules were identical in terms of
   appearance and packaging, guaranteeing that neither the volunteers nor
   the researchers knew who was receiving which medication.

   During the study, the researcher called the participants to follow up
   each week for two weeks. Then, they followed up every two weeks until
   12 weeks to check that the participants were demonstrating good
   compliance in taking the probiotics or the placebo, as this must be at
   a level of 80% or more.

   The investigation was conducted following the Declaration of Helsinki
   and was approved by the ethics committee of Srinakharinwirot University
   (SWUEC/F-212/2565, September 29, 2022). The registration number for
   this study is TCTR20230505002. The probiotic strains used in this test
   can reduce sugar and lipid levels in both in vitro and in animal models
   [[63]27–[64]29]. The probiotic strains were approved for use as
   probiotic microorganisms in food by the Thai Food and Drug
   Administration (FDA), according to the Ministry of Public Health
   announcement. Written informed consent was obtained from all subjects
   involved in the research.

   To assess participants’ tolerance and satisfaction with the
   intervention, a quality-of-life questionnaire was administered at the
   final visit (12 weeks). The seven items included: (1) frequency of
   defecation (5 points for daily, down to 1 point for none); (2)
   difficulty in defecation (5 points for never, down to 1 for always);
   (3) stomach pain (5 points for never, down to 1 for always); (4)
   bloating (5 points for never, down to 1 for always); (5) use of
   laxatives (5 for never, down to 1 for always); (6) duration of
   defecation (5 points for <5 minutes, down to 1 for >30 minutes); (7)
   overall satisfaction (5 points for strongly agree, down to 1 for
   strongly disagree). This evaluation provided insights into
   participants’ gastrointestinal health and satisfaction with the
   intervention.

Inclusion criteria

   The inclusion criteria for the participants in this study required
   individuals to meet the following conditions: (1) be within an age
   range of 18 to 60 years, and (2) exhibit three or more of the following
   criteria: (a) an elevated waist circumference (≥102 cm in men and ≥88
   cm in women), (b) elevated blood pressure (≥130/85 mmHg), (c) reduced
   high-density lipoprotein cholesterol (HDL-C) levels (<40 mg/dL in men
   and <50 mg/dL in women), (d) elevated triglycerides (≥150 mg/dL), or
   (e) elevated fasting blood glucose (FBG) (100–125 mg/dL) [[65]1].

Exclusion criteria

   Participants who met the following criteria were excluded: (1) they had
   been diagnosed with the following underlying diseases: diabetes
   mellitus (hemoglobin A1c [HbA1c] ≥ 6.5 mg%) [[66]30], hypertension
   (systolic blood pressure [SBP] > 140 mmHg, diastolic blood pressure
   [DBP] > 90 mmHg) [[67]31], chronic kidney disease stage 3 and above or
   an estimated glomerular filtration rate (eGFR) value < 60 ml/min/1.73^2
   [[68]32], liver disease (aspartate transaminase [AST]/ alanine
   transaminase [ALT] > 5 times the normal value or jaundice), cancer,
   coronary artery disease (CAD), thyroid disease, immunodeficiency, or
   intestinal diseases such as inflammatory bowel disease, (2) they had
   used of antibiotics, immunosuppressants, probiotics supplements,
   synbiotics, herbal supplements, antacids or laxatives within 12 weeks
   before participating in the study, (3) smoked; (4) had alcoholism, (5)
   were pregnant or lactating, or (6) had acquired a Covid-19 infection
   within four weeks of the trial.

Withdrawal or termination criteria

   Participants were withdrawn from the investigation if they met any of
   the following criteria: (1) they received antibiotics, laxatives, or
   immunosuppressive drugs during the study period, (2) they experienced
   side effects from probiotics, including nausea, vomiting, diarrhea,
   facial swelling, or shortness of breath, as well as rashes or swollen
   lips, (3) were diagnosed with a non-communicable disease during the
   evaluation period, or (4) chose to withdraw.

Sample size calculation

   Low-density lipoprotein cholesterol (LDL-C) is considered a critical
   contributor to the development of cardiovascular disease [[69]33]. For
   the present study, the primary outcome, changes in LDL-C, was used to
   determine the sample size, informed by previous research comparing
   placebo and intervention groups [[70]34]. The placebo group exhibited a
   change of 0.17 ± 0.46 mmol/L, while the intervention group showed a
   difference of -0.40 ± 0.70 mmol/L. Using STATA software, the sample
   size was calculated with α = 0.05 and a power (1-β) = 0.90, resulting
   in 24 participants per group. To account for potential missing data
   (approximately 20%), the sample size was increased to approximately 28
   participants per group.

Sample collection and high-throughput sequencing

   Blood samples were taken from each participant to measure the following
   parameters: FBG, HbA1c, total cholesterol, triglyceride, LDL-C, HDL-C,
   creatinine, AST, and ALT at baseline and 12 weeks post-intervention in
   both groups. At baseline and 12 weeks following the intervention, fresh
   stool was collected in deoxyribonucleic acid (DNA)/ribonucleic acid
   (RNA) shield fecal collection tubes (Zymo Research, USA). It was then
   promptly frozen at -20°C for 48 hours before additional analysis. The
   QIAamp DNA Stool Mini Kit (Qiagen, USA) was used to extract DNA
   [[71]35]. The quantity and quality of the DNA were assessed using
   nanodrop and electrophoresis [[72]36]. By using 2X KAPA hot-start ready
   mix and 515 F and 806R primers, the V4 hypervariable region of the 16S
   rRNA gene was amplified by polymerase chain reaction (PCR) [[73]37].

   The initial denaturation at 94°C for three minutes was followed by 25
   cycles of 98°C for 20 seconds, 55°C for 30 seconds, 72°C for 30
   seconds, and a final extension step at 72°C for five minutes in the
   PCR. After eight cycles of the previously described PCR condition, the
   16S amplicons were purified using AMPure XP beads and indexed with a
   Nextera XT Index Kit [[74]38]. Ultimately, the PCR products underwent
   cleaning and pooling in preparation for the Illumina® MiSeq™250-base
   paired-end read sequencing and cluster formation [[75]39, [76]40].

Sequencing data analysis

   The microbiome bioinformatics was analyzed using QIIME 2 2019.10. The
   q2-demux plugin was utilized to demultiplex the raw sequence data, and
   DADA2 (via q2-dada2) was employed to exclude reads that had expected
   errors (maxEE) greater than 3.0. With the SEPP q2-plugin, a phylogeny
   was built by inserting brief sequences into the reference phylogenetic
   tree, sepp-refs-gg-13-8.qza. Following the rarefaction of samples to a
   minimum read, the alpha-diversity metric, beta-diversity meter, and
   principle coordinate analysis (PCoA) were computed with q2-diversity
   [[77]41]. The classify-sklearn naive Bayes taxonomy classifier was
   adopted to assign taxonomy to amplicon sequence variants (ASVs) based
   on comparison with the Greengenes 13_8 99% operational taxonomic units
   (OTUs) reference sequences [[78]42]. By applying the Kruskal-Wallis
   test and a permutational multivariate analysis of variance (PERMANOVA)
   with 999 permutations, respectively, statistical tests of the alpha and
   beta diversity were carried out [[79]43]. A heat tree analysis was
   generated for pairwise comparisons of the taxonomic differences between
   microbial communities with the MicrobiomeAnalyst web-based platform
   [[80]44].

Functional pathway enrichment analysis

   The metabolic functions and pathways of the gut microbiome in each
   group were predicted with the PICRUSt2 software to explore their role
   in the metabolism [[81]45]. Next, we utilized the STAMP software
   [[82]46] to detect the differences in the metabolic function abundance
   between the groups. This was completed using Welch’s t-test, a
   statistical method that compares the means of two groups to determine
   if there is a significant difference, with a confidence interval of
   0.95 and a significance threshold of a corrected p-value <0.05.

Statistical analysis and visualization

   Stata/SE 16.1 software (StataCorp LP, College Station, TX, USA) was
   employed to analyze the statistical data [[83]47]. Statistics were
   considered significant when the p-value < 0.05. All the study variables
   were subjected to descriptive statistics analysis, which was provided
   as the frequency (%) for categorical data and mean ± standard deviation
   (SD) or median for nonnormal quantitative data. The independent t-test
   with a p-value < 0.05 was utilized if the distribution of the
   quantitative data, such as age and laboratory results, was normal. The
   Mann-Whitney U test with a p-value <0.05 was applied if the data
   distribution was not normal. The Chi-square test or Fisher’s exact test
   was used to compare the two groups for categorical data. The
   Benjamini-Hochberg (FDR) correction was applied to p-values for
   multiple hypothesis testing [[84]48].

Results

   Sixty participants were randomized into either the probiotics
   (Lacticaseibacillus paracasei MSMC39-1 and Bifidobacterium animalis
   TA-1) or the placebo group. Notably, during the study, two participants
   from the placebo group were lost to follow-up, resulting in the
   analysis of 58 blood and gut microbiota samples. No participants
   experienced any adverse events ([85]Fig 1). Both groups consisted of
   approximately 70% female participants, with a mean age of 42.29 ± 7.39
   years in the probiotics group and 43.89 ± 7.54 years in the placebo
   group. There was no statistically significant difference in age or
   gender among the groups ([86]S1 Table).

Fig 1. The study flow diagram.

   [87]Fig 1
   [88]Open in a new tab

   Following the administration of the probiotic strains L. paracasei
   MSMC39-1 and B. animalis TA-1 over 12 weeks, a significant reduction
   was observed in the participants’ body weight, BMI, waist
   circumference, SBP, and DBP when compared to the placebo group at
   baseline and 12 weeks. Additionally, the total cholesterol,
   triglycerides, LDL-C, and HbA1c levels showed statistically significant
   decreases from the baseline in the probiotics group by the end of the
   12 weeks. However, no significant changes were observed in the placebo
   group ([89]Table 1).

Table 1. Clinical and laboratory characteristics of the probiotics and
placebo groups at baseline and week 12.

   Variables Placebo
   (n = 27) P-value Probiotics
   (n = 31) P-value
   Baseline Week 12 Baseline Week 12
   Weight (kg) 75.90 (63.5–79.1) 73.5 (61.3–79.2) 0.089[90]^2 76.47 ±
   21.72 72.38 ± 21.23 <0.001[91]^1
   BMI (kg/m ^2 ) 27.07 (24.06–30.60) 27.02 (24.39–30.18) 0.070[92]^2
   28.27 ± 6.65 26.74 ± 6.56 <0.001[93]^1
   Waist circumference (cm) 34.5 (32.5–38) 34 (32–37.5) 0.024[94]^2 34.5
   (30–39) 32 (28–36.5) <0.001[95]^1
   Hip circumference (cm) 40.5 (39.5–43.5) 40.5 (38.5–43.5) <0.001[96]^2
   41 (39–44) 39 (37–42) <0.001[97]^1
   SBP (mmHg) 120 (110–127) 119 (110–127) 0.826[98]^2 127 (115–137) 115
   (108–124) <0.001[99]^2
   DBP (mmHg) 80 (73–86) 74 (70–80) 0.002[100]^2 82 (72–87) 77 (69–82)
   0.007[101]^2
   Total cholesterol (mg/dl) 239.11 ± 29.85 235.11 ± 30.49 0.463[102]^1
   242 (218–262) 194 (186–219) <0.001[103]^2
   Triglyceride (mg/dl) 113 (84–168) 107 (80–161) 0.421[104]^2 127.84 ±
   55.57 109.32 ± 41.85 0.001[105]^1
   HDL-C (mg/dl) 54 (47–74) 55 (47–69) 0.791[106]^2 56.65 ± 14.37 61.19 ±
   16.05 0.001[107]^1
   LDL-C (mg/dl) 168.63 ± 29.68 163.67 ± 27.31 0.252[108]^1 171 (146–188)
   124 (118–134) <0.001[109]^2
   FBG (mg/dl) 92.67 ± 11.35 89.48 ± 9.20 0.111[110]^1 92 (87–99) 89
   (83–98) 0.543[111]^2
   HbA1c (mg%) 5.59 ± 0.39 5.54 ± 0.35 0.260[112]^1 5.63 ± 0.41 5.49 ±
   0.40 0.002[113]^1
   Creatinine (mg/dl) 0.71 (0.62–0.89) 0.79 (0.67–1.04) 0.008[114]^2 0.75
   ± 0.14 0.81 ± 0.14 0.001[115]^1
   eGRF (ml/min/1.73 ^2 ) 107.73 (89.53–111.57) 96.78 (79.05–105.53)
   0.009[116]^2 103.42 ±12.35 97.02 ± 14.23 0.004[117]^1
   AST (IU/L) 19 (16–22) 21 (17–24) 0.129[118]^2 19 (16–26) 18 (17–26)
   0.998[119]^2
   ALT (IU/L) 16 (12–24) 19 (11–28) 0.524[120]^2 18 (13–27) 16 (14–25)
   0.399[121]^2
   [122]Open in a new tab

   ^1 Paired t-test

   ^2 Wilcoxon signed rank test; ALT, alanine aminotransferase; AST,
   aspartate aminotransferase; BMI, body mass index; DBP, diastolic blood
   pressure; FBG, fasting blood glucose; HbA1c, hemoglobin A1c; HDL-C,
   high-density lipoprotein cholesterol; IU/L, international units per
   liter; kg, kilogram; LDL-C, low-density lipoprotein cholesterol; mmHg,
   millimeters of mercury; mg, milligrams; mg/dl, milligrams per
   deciliter; SBP, systolic blood pressure

   The differences between the pre-intervention and post-intervention
   results in the placebo and probiotics groups at 12 weeks are presented
   in [123]Table 2. Following the administration of both strains of
   probiotics, namely L. paracasei MSMC39-1 and B. animalis TA-1 at 12
   weeks, the difference in participants’ body weight, BMI, and waist
   circumference, all significantly decreased from the baseline (3.90 kg,
   1.36 kg/m^2, and 2.00 cm, p-value <0.001 for body weight, BMI, and
   waist circumference, respectively), and the variation differed
   significantly from the placebo group ([124]Table 2). Moreover,
   following probiotics administration, the participant’s SBP levels were
   significantly lower.

Table 2. The changes in 12 weeks of the intervention and control groups.

   Variables Placebo
   (n = 27) Probiotics
   (n = 31) P-value
   Weight (kg) -0.90 (-2.00, 1.10) -3.90 (-4.70, 3.00) <0.001[125]^2
   BMI (kg/m ^2 ) -0.37 (-0.65, 0.36) -1.36 (-1.75, 1.07) <0.001[126]^2
   Waist circumference (cm) -0.50 (-2.00, 0.00) -2.00 (-3.00, -2.00)
   <0.001[127]^2
   Hip circumference (cm) -0.60 ± 0.62 -2.21 ± 0.94 <0.001[128]^1
   SBP (mmHg) -1 (-8, 7) -10 (-24, -3) 0.003[129]^2
   DBP (mmHg) -5 (-9, 1) -5 (-13, 1) 0.913[130]^2
   Total cholesterol (mg/dl) -4.00 ± 27.87 -38.84 ± 27.47 <0.001[131]^1
   Triglyceride (mg/dl) 4 (-9, 33) -9 (-43, 0) 0.011[132]^2
   HDL-C (mg/dl) 0 (-5, 4) 4 (1, 7) 0.007[133]^2
   LDL-C (mg/dl) -4.96 ± 22.02 -39.97 ± 26.83 <0.001[134]^1
   FBG (mg/dl) -3.19 ± 10.03 -0.87 ± 12.43 0.443[135]^1
   HbA1c (mg%) 0.00 (0.20, 0.10) -0.10 (-0.20, 0.00) 0.086[136]^2
   Creatinine (mg/dl) 0.08 (-0.01, 0.11) 0.05 (0.00, 0.13) 0.981[137]^2
   eGRF (ml/min/1.73 ^2 ) -6.50 ± 12.65 -6.40 ± 11.25 0.975[138]^1
   AST (IU/L) 2 (-3, 5) 0 (-3, 3) 0.250[139]^2
   ALT (IU/L) 0 (-3, 6) 1 (-4, 5) 0.827[140]^2
   [141]Open in a new tab

   ^1 Independent t-test (mean ± SD)

   ^2 Mann-Whitney U test (median [interquartile range]); ALT, alanine
   aminotransferase; AST, aspartate aminotransferase; BMI, body mass
   index; DBP, diastolic blood pressure; FBG, fasting blood glucose;
   HbA1c, hemoglobin A1c; HDL-C, high-density lipoprotein cholesterol;
   IU/L, international units per liter; kg, kilogram; LDL-C, low-density
   lipoprotein cholesterol; mmHg, millimeters of mercury; mg, milligrams;
   mg/dl, milligrams per deciliter; SBP, systolic blood pressure

   The total cholesterol, triglycerides, and LDL-C levels, considerably
   decreased after taking probiotics compared to before with statistical
   significance (the differences were 38.84 ± 27.47 mg/dl, p-value <0.001;
   9 mg/dl, p-value 0.011; and 39.97 ± 26.83 mg/dl, p-value <0.001,
   respectively). Specifically, the primary outcome of this study, the
   LDL-C level, experienced a significantly high reduction in the
   probiotics group with statistical significance at 12 weeks ([142]Table
   2).

   The FBG level considerably dropped after taking probiotics compared to
   previously in the same group, but it did not change significantly from
   the placebo group. The majority of participants, however, had normal
   FBG and HbA1c before the experiment. As a result, there was no
   discernible difference between the probiotic-treated and control groups
   ([143]Table 2).

   Following the intervention in the probiotics group, reductions in both
   male and female participants were also observed in total cholesterol,
   triglycerides, LDL-C, and HbA1c levels, along with an increase in
   HDL-C, when compared to the placebo group ([144]S2 and [145]S3 Tables).

   Multivariate regression analysis revealed that the clinical and
   laboratory characteristics, as well as changes in variables between the
   probiotics and placebo groups, remained consistent. After 12 weeks of
   administration of the probiotic strains L. paracasei MSMC39-1 and B.
   animalis TA-1, a significant reduction in LDL-C after taking probiotics
   (39.97 ± 26.83 mg/dl) was achieved (p-value <0.001). Additionally,
   compared to the placebo group, participants in the probiotics group
   showed significant reductions at 12 weeks from baseline in body weight
   (4.09 ± 2.70 kg), BMI (1.52 ± 0.92 kg/m^2), waist circumference (2.12 ±
   2.03 cm), systolic blood pressure (11.65 ± 13.77 mmHg), and total
   cholesterol (38.84 ± 27.47 mg/dl) ([146]S4 Table).

   At the last visit, all participants, including those in the control and
   intervention groups, as well as those in the bloating, gas production,
   stomach pain, diarrhea, and constipation ones, were asked about their
   experiences. The results showed that there were no notable differences
   between the probiotics and placebo groups ([147]S5 Table).

The diversity of the gut microbiota

   The alpha diversity analysis was used to examine diversity in the two
   participant groups before and after intervention by measuring the
   Shannon diversity ([148]Fig 2A and 2B). In both the probiotics and
   placebo groups, the alpha diversity index showed higher diversity in
   the post-intervention with no statistical significance.

Fig 2. Alpha- and beta-diversity of microbial composition pre- and
post-intervention in both groups.

   [149]Fig 2
   [150]Open in a new tab

   The Shannon diversity index in placebo (A) and probiotics (B), and
   principal coordinate analysis (PCoA) of beta diversity based on
   weighted UniFrac distances in placebo (C) and probiotics (D).

   The beta diversity was used to determine the similarities and
   dissimilarities in the composition structure of the group of microbial
   communities with the weighted UniFrac distances. The principal
   coordinates analysis (PCoA) illustrated a statistically significant
   difference (PERMANOVA, p-value = 0.002, q-value = 0.01) in the
   clustering of fecal samples between the gut microbiomes in both groups
   pre- and post-intervention ([151]Fig 2C and 2D). The PCoA plots
   indicated that the probiotics group showed a higher dissimilarity
   between the pre-intervention and post-intervention results due to a
   more significant proportion of variation explained in the first and
   second axes.

Assessment of the bacterial taxonomic composition

   At the phylum level, among the two groups, the most common bacterial
   phyla were Firmicutes, Bacteroidetes, Actinobacteria, and
   Proteobacteria. The relative abundance of Proteobacteria decreased in
   the post-intervention probiotics group compared to the pre-intervention
   one, while in the placebo group, there was no difference (the
   proportion of Proteobacteria in the post-intervention probiotics group,
   the pre-intervention probiotics group, the post-intervention placebo
   group, and the pre-intervention placebo group: 2.10%, 3.02%, 3.53%, and
   3.77%, respectively) ([152]S1A and S1B Fig).

   At the family level, the Lachnospiraceae and Bacteroidaceae families
   were shown to be the two most common families. Compared to the
   pre-intervention probiotics group, the Prevotellaceae and
   Enterobacteriaceae families were less prevalent proportionately in the
   post-intervention probiotics group (the proportion of Prevotellaceae
   and Enterobacteriaceae families in the post-intervention probiotics
   group and the pre-intervention probiotics group: 10.19% vs. 13.43% and
   0.98% vs. 1.50%, respectively) ([153]S1C and S1D Fig).

   At the genus level, the highest abundance in each group belonged to the
   genus Bacteroides. In the post-intervention probiotics group, the
   Bacteroides, Prevotella, and Megamonas genera were less prevalent than
   in the pre-intervention probiotics group (the proportion of
   Bacteroides, Prevotella, and Megamonas genera in the post-intervention
   probiotics group and the pre-intervention probiotics group: 14.41% vs
   20.99%, 10.01% vs 13.07%, and 2.48% vs 3.63%, respectively). Moreover,
   the relative abundance of Blautia, Roseburia, and Ruminococcus genera
   was greater in the post-intervention probiotics group than in the other
   (the proportion of Blautia, Roseburia, and Ruminococcus genera in the
   post-intervention probiotics group and the pre-intervention probiotics
   group: 10.22% vs. 6.16%, 2.52% vs. 1.62%, and 0.89% vs. 0.85%,
   respectively) ([154]S1E and S1F Fig).

   According to the pairwise phylogenetic heat tree, the abundance of
   Blautia, Roseburia, Collinsella, and Ruminococcus was greater in the
   post-intervention probiotics group than in the other group, with
   statistical significance. Conversely, there was a significantly lower
   detection of Parabacteroides merdae and Alistipes obesi in this group.
   However, there was no change in the placebo one ([155]Fig 3A and 3B).

Fig 3. Heat tree analysis.

   [156]Fig 3
   [157]Open in a new tab

   Comparison of bacterial microbiota pre-intervention and
   post-intervention in placebo (A) and probiotics (B).

Assessment of the predicted function of the gut microbiome

   The predicted functional changes were based on the differential
   abundance pre- and post-intervention in the placebo and probiotics
   groups. Remarkably, during the 12 weeks, the post-intervention
   probiotics group showed significant pathway enrichment in ATP-binding
   cassette (ABC) transporters, in addition to ribonucleic acid (RNA)
   transport, the biosynthesis of unsaturated fatty acids,
   glycerophospholipid metabolism, and pyruvate metabolism ([158]Fig 4).

Fig 4. Functional characterization of different intervention groups based on
PICRUSt2 analysis.

   [159]Fig 4
   [160]Open in a new tab

   Bar chart showing the functional difference (corrected p-value < 0.05)
   between placebo pre-test and post-test (A), probiotic pre-test and
   post-test (B).

Discussion

   This double-blind, randomized controlled trial investigated the
   efficacy of Lacticaseibacillus paracasei MSMC39-1 and Bifidobacterium
   animalis TA-1 in reducing metabolic syndrome risk factors, particularly
   LDL-C levels, which are a key risk factor for coronary artery disease
   and other cardiovascular conditions [[161]33, [162]49, [163]50].
   Vegetable-based pellets were used as the placebo in both groups and had
   no effect on the study outcomes. The primary objective was to evaluate
   the effectiveness of the probiotics in reducing the risk of the
   characteristics of metabolic syndrome.

   The gut microbiota typically requires weeks to months to exhibit
   measurable changes in response to probiotics. While short-term effects
   (e.g., changes in metabolite levels) can occur sooner, 12 weeks allows
   sufficient time for sustained microbial colonization, shifts in
   microbial diversity, and host responses [[164]51, [165]52]. Many health
   benefits linked to probiotics, such as improved gastrointestinal
   function, immune response, or systemic inflammation, often manifest
   after 8–12 weeks [[166]53–[167]55]. Therefore, evaluating at 12 weeks
   ensures that intermediate and longer-term outcomes can be captured
   reliably. A systematic review and meta-analysis of randomized clinical
   trials concluded that probiotic supplementation significantly reduces
   total cholesterol and LDL-C levels, with a stronger effect on LDL-C
   observed in interventions lasting longer than six weeks [[168]56].
   Likewise, a randomized controlled study found that L. plantarum strains
   (CECT7527, CECT7528, and CECT7529) reduced LDL-C and total cholesterol
   after 12 weeks compared to placebo, with the LDL-C-lowering effect
   potentially influenced by individual gut microbiota differences
   [[169]57]. Similarly, this study conducted a 12-week follow-up to
   assess laboratory changes, aiming to validate and expand upon these
   findings. Furthermore, a 12-week intervention allows for observing
   effects while ensuring participant adherence. Longer durations may
   increase dropout rates, weakening the study. This timeframe helps
   reduce transient variations or short-term influences (e.g., dietary
   changes, seasonal effects) that could confound results.

   In this investigation, the LDL-C levels in the intervention group
   decreased significantly after receiving the probiotics compared to the
   placebo one. High levels of LDL-C are a risk factor for diabetes
   mellitus and cardiovascular disease [[170]49, [171]58–[172]60]. It has
   been reported that a 1% reduction in blood lipid levels is associated
   with a 2%–3% reduction in the risk of coronary artery disease
   [[173]61]. Previous works have reported that both strains of probiotics
   can reduce blood glucose and lipid levels in both in vitro and animal
   models. Moreover, L. paracasei MSMC39-1 can reduce inflammation, and B.
   animalis TA-1 can create bile salt hydrolase (BSH), which reduces
   cholesterol [[174]28, [175]62]. Studies have reported that several
   mechanisms in probiotics can reduce cholesterol levels. For example,
   probiotics can use cholesterol to form cell membranes, increasing their
   strength. This helps to reduce the amount of cholesterol in food
   passages [[176]63, [177]64]. Probiotics can also convert cholesterol to
   coprostanol in the intestines and excrete it directly in the feces.
   This reduces the amount of cholesterol that is absorbed in the
   intestines and results in a reduction of cholesterol accumulation in
   the body [[178]34]. The breakdown of bile salts in the digestive tract
   is attributed to BSH, which is another way in which probiotics can
   decrease cholesterol. It is then eliminated through the feces and is in
   an insoluble state. Consequently, the liver must extract more
   cholesterol to produce bile salts. This is an indirect method of
   decreasing cholesterol [[179]65, [180]66].

   In this research, the total cholesterol and triglyceride levels
   decreased significantly after the consumption of the probiotics for 12
   weeks. Compared with pre-intervention placebo values, total cholesterol
   declined by 16.05% in the probiotic group versus 1.67% in placebo,
   while triglycerides fell by 7.04% versus 3.54%, respectively. Although
   HDL-C decreased in the probiotic group, the change was not
   statistically significant. These results align with previous trials:
   one involving dyslipidemic patients showed a 13.6% reduction in total
   cholesterol in the L. plantarum group after 12 weeks [[181]67], and
   another by Keleszade et al. found that six weeks of L. plantarum ECGC
   13110402 use significantly lowered total cholesterol and LDL-C levels
   [[182]68]. Additionally, B. longum CCFM1077 reduced total cholesterol
   by 13.87% in hyperlipidemic patients, and synbiotic foods containing L.
   sporogenes and inulin improved triglycerides and HDL-C [[183]69].
   Overall, both fermented milk products and probiotics significantly
   reduced total cholesterol and LDL-C, with interventions exceeding four
   weeks proving more effective [[184]70].

   Probiotics could influence SBP through several mechanisms related to
   gut microbiome modulation [[185]71]. These outcomes are a result of the
   complex interactions that occur between the host’s physiological
   processes, their metabolic products, and the gut microbiome [[186]72].
   Certain probiotic strains can ferment and create peptides that mimic
   the effects of angiotensin-converting enzyme inhibitors, a type of
   medication used to treat hypertension [[187]73]. These peptides have
   the ability to block the angiotensin-converting enzyme, which lowers
   the amount of angiotensin II, a strong vasoconstrictor, produced
   [[188]73]. The body’s levels of pro- and anti-inflammatory cytokines
   may be affected by probiotics. Probiotics could improve endothelial
   function and reduce arterial stiffness, essential for maintaining
   normal blood pressure, by lowering inflammation, especially in the
   vascular system [[189]53]. The gut-brain axis, or biochemical
   communication between the central nervous system and the
   gastrointestinal tract, may also be affected by probiotics. In
   addition, blood pressure may be impacted by this interaction because
   the autonomic nervous system regulates blood vessel constriction and
   the heart rate [[190]74]. These clinical trials have investigated the
   impact of probiotics on blood pressure, with some reporting modest
   reductions in SBP reductions (reduced SBP by 3.05 mmHg and DBP by 1.51
   mmHg), which is consistent with our work (reduced SBP by 10 mmHg with
   statistical significance, DBP 5 mmHg with no statistical significance)
   [[191]75, [192]76]. The extent of blood pressure reduction often
   depends on the baseline levels, the strains of probiotics utilized, and
   the duration of the intervention.

   In this study, the LDL-C levels showed a marked decrease in the
   probiotic group compared to the placebo group, dropping by 23.37% and
   2.94%, respectively, following the intervention. These results are
   supported by a meta-analysis of randomized controlled trials, which
   reported that consuming probiotic Lactobacillus strains, particularly
   L. reuteri and L. plantarum, significantly reduced both total
   cholesterol and LDL-C levels [[193]69]. In a controlled, randomized,
   double-blind trial conducted among dyslipidemic patients,
   supplementation with a combination of three L. plantarum strains (CECT
   7527, CECT 7528, and CECT 7529) resulted in a 17.6% reduction in LDL-C
   levels after 12 weeks compared to the placebo group [[194]67]. In
   another randomized trial, the administration of Bifidobacterium longum
   CCFM1077 to hyperlipidemic patients reduced LDL-C levels by
   approximately 13.88%. This benefit may be attributed to the
   proliferation of anti-obesity-related bacterial genera and favorable
   shifts in fecal metabolite profiles [[195]77]. In this investigation,
   we demonstrated that the lipid profile, which includes total
   cholesterol, LDL-C, HDL-C, and triglycerides, improved following the
   use of probiotics compared to before. Furthermore, in comparison to the
   pre-intervention probiotics group, the post-intervention one
   demonstrated a substantial increase in the relative abundance of
   Blautia, Collinsella, Bifidobacterium, and Roseburia. These gut
   microorganisms are the short-chain fatty acids (SCFAs)-producing
   genera. Moreover, higher quantities of SCFAs can be produced more
   effectively by a more diversified gut microbiota [[196]78, [197]79].

   The fermentation of complex carbohydrates produces metabolites known as
   SCFAs [[198]80, [199]81]. Although butyrate can only be generated by
   members of the phylum Firmicutes, members of the Bacteroidetes phylum
   can also create acetate [[200]82, [201]83]. Eubacterium rectale and
   Roseburia show a positive connection with SCFAs [[202]84]. Colonocytes
   and liver gluconeogenesis depend on SCFAs as a primary source of
   energy. Furthermore, they provide health benefits by strengthening the
   host’s immune response, maintaining the integrity of the intestinal
   barrier by regulating the expression of tight junction proteins,
   lowering blood lipid levels by inhibiting the synthesis of cholesterol,
   and controlling insulin sensitivity [[203]85, [204]86]. Up to 10% of
   the host’s daily caloric needs may be met using SCFAs as an energy
   source. For the host to remain healthy and in good condition, these
   acids, primarily acetic, butyric, and propionic acids, must be present
   in sufficient amounts in the body [[205]87].

   SCFAs can be produced by lactic acid bacteria, such as those of the
   genera Lactobacillus and Bifidobacterium, even though these are not
   classified under the SCFAs category [[206]88]. However, due to the
   existence of some bacterial species, such as E. hallii, which may
   convert lactate into various SCFAs, it does not accumulate in the colon
   under normal conditions [[207]78]. It is hypothesized that SCFAs
   mediate the microbiota-gut-brain axis crosstalk [[208]89]. For
   instance, certain probiotics (such as B. longum SP 07/3 or B. bifidum
   MF 20/5) could produce acetic acid, propionic acid, and lactic acid
   [[209]87].

   At baseline, the gut microbiome profiles displayed low diversity,
   indicating characteristics of gut dysbiosis, which refers to an
   imbalance in the microbial community within the gut. This imbalance is
   caused by an overgrowth of opportunistic bacteria and can lead to
   various health issues, including inflammatory bowel disease (IBD)
   [[210]90], obesity [[211]91], and metabolic disorders [[212]92]. In the
   present study, we observed a significantly higher abundance of
   Phascolarctobacterium and Alistipes obesi prior to the intervention of
   both treatments. Alistipes obesi is often found in higher abundance in
   individuals with gut dysbiosis and its presence is associated with
   conditions like non-alcoholic steatohepatitis and liver fibrosis,
   indicating its role in gut health disturbances [[213]93]. Furthermore,
   Alistipes obesi has the ability to create metabolites that alter the
   immune response and may be involved in the chronic low-grade
   inflammation that can occur in metabolic syndrome [[214]94]. Shifts in
   the levels of Phascolarctobacterium have been connected to changes in
   immune responses. For example, in conditions like psoriasis, an
   increase in Phascolarctobacterium has been linked to abnormal immune
   activity [[215]95]. This indicates that Phascolarctobacterium may be
   have a role in regulating inflammation and immune responses in the gut.

   Patients with autoimmune disorders [[216]96], type 2 diabetes
   [[217]97], and atherosclerotic diseases [[218]98] frequently have
   abnormally low levels of SCFA-producing gut microbes [[219]99]. This
   disruption could result from a decrease in the number of gut microbes
   that cross-feed SCFA-producing bacteria or from an increase in the
   synthesis of harmful compounds by the host’s gastrointestinal tract or
   other coexisting microbes [[220]100]. For instance, the absence of
   butyrate-producing bacteria can disrupt the gut barrier, which in turn
   can facilitate the release of microbial toxins such as LPS that bind to
   toll-like receptors and cause inflammation. Higher levels of LPS
   production in the microbiome of CAD patients have been linked to
   insulin resistance and abdominal fat [[221]101]. The atherosclerotic
   process may be protected by SCFAs, whereas lipopolysaccharide (LPS)
   could trigger inflammation and accelerate the onset of atherosclerosis.
   The proportion of butyric acid-producing bacteria, such as
   Lachnospiraceae and Ruminococcaceae, declined as CAD progressed,
   according to research by Liu H. et al. [[222]102]. Therefore, creating
   and introducing bacterial occupants (or co-inhabitants) that have the
   ability to cross-feed and increase/reduce the number of SCFA-producing
   bacteria in the gut could be a viable probiotic strategy to aid in the
   treatment of several human illnesses [[223]78, [224]79].

   Patients with obesity typically have altered gut microbiota
   compositions, suggesting that the gut microbiome may be a contributing
   component to the development of obesity [[225]103, [226]104].
   Probiotics can be used to manipulate microbial populations in order to
   enhance the integrity of the intestinal barrier and increase the amount
   of beneficial bacteria, all of which contribute to weight loss.
   Moreover, the use of probiotics has been linked to improvements in
   intestinal dysbiosis and obesity in both humans and animals [[227]105,
   [228]106]. These data validate the current investigation, which showed
   that after receiving both probiotic strains for 12 weeks, volunteers’
   body weight (5.10%), BMI (4.81%), and waist circumference (5.80%) all
   significantly dropped from baseline and differed from the placebo
   group.

   Prevotella and Megamonas genera were less common than the other group
   in the post-intervention probiotics group. The study conducted by
   Lopez-Montoya et al. validated our findings, demonstrating a strong
   correlation between Megasphaera and Escherichia-Shigella and patients
   diagnosed with atherogenic dyslipidemia, which is characterized by
   hypertriglyceridemia and low HDL-C [[229]107]. Megasphaera dramatically
   increased in relative abundance and was linked with inadequate physical
   activity in individuals who were obese or overweight [[230]108].

   An increased risk of cardiovascular disease may be closely linked to
   diabetes mellitus [[231]109]. A changed gut microbiome can lead to
   oxidative stress-related diseases, as well as obesity, metabolic
   endotoxemia, B-cell dysfunction, and systemic inflammation [[232]110,
   [233]111]. Probiotic therapy may be useful in managing diabetes
   mellitus because intestinal bacteria produce more SCFAs. Other works
   demonstrate that probiotics (B. animalis subsp. lactis BB-12 and L.
   acidophilus La-5) improve glycemic control in patients with type 2
   diabetes mellitus, which can reduce FBG and hemoglobin A1c levels by
   6.59% and 11.04%, respectively, although these reductions were not
   statistically significant [[234]112]. In support of the current
   investigation, the FBG level decreased significantly following the use
   of probiotics compared to the baseline, resulting in reductions of FBG
   and hemoglobin A1c levels by 0.95% and 3.44%, respectively. Most
   participants had normal fasting glucose and cumulative hemoglobin A1c
   levels before the study. There was, therefore, no appreciable
   difference between the probiotic-treated and control groups.

   The microbial functional analysis revealed significant increases in
   ATP-binding cassette (ABC) transporters, as well as ribonucleic acid
   (RNA) transport, the biosynthesis of unsaturated fatty acids,
   glycerophospholipid metabolism, and pyruvate metabolism in the
   post-intervention probiotics group at 12 weeks. It is assumed that ABC
   transporter proteins facilitate the ATP-dependent translocation of
   lipids or lipid-related substances, including cholesterol, bile acids,
   phospholipids, and sphingolipids [[235]113]. A solute-binding
   protein-dependent ABC transporter mediates the gut’s response of B.
   longum subsp. longum 105-A to the lactulose intake. This reaction
   contributes to predicting the probiotic responder and non-responder
   status and offers insight into clinical interventions that evaluate the
   effectiveness of probiotics [[236]114].

   One of the key components of lipid metabolism is RNA transport. The
   tissue-specific targeting of RNA-based therapies is now possible,
   increasing the safety of this treatment [[237]115, [238]116].RNA-based
   therapies have the potential to dramatically improve outcomes for
   individuals who have or are at risk for atherosclerotic cardiovascular
   disease, and multiple putative target proteins have been identified
   [[239]117]. The biosynthesis of unsaturated fatty acids, which are
   considered healthy fats, can lower blood cholesterol levels and
   decrease the risks of cardiovascular diseases [[240]118, [241]119].
   They can be separated into two groups: monounsaturated fats and
   polyunsaturated fats. Certain unsaturated fatty acids and SCFAs protect
   against dysbiosis and barrier function impairment. By reducing
   inflammation brought on by dysbiosis and metabolic endotoxemia, these
   lipids may increase insulin sensitivity [[242]119]. In cells,
   glycerophospholipid metabolism plays a role in both metabolism and
   signaling; it either produces membrane-derived second messengers or is
   a precursor to them [[243]120]. By affecting colonic
   glycerophospholipid metabolism and fecal metabolites, the gut
   microbiota may play a role in the pathophysiology of depression
   [[244]121]. In addition, one of the key metabolic processes of SCFAs is
   pyruvate metabolism. Pyruvate, the last product of glycolysis, is
   crucial for cell metabolism [[245]81, [246]122].

   This study was subject to some limitations, one of which was its use of
   shotgun sequencing, which produced more information than 16S rRNA V4
   region sequencing because of its ability to characterize metabolic
   pathways and larger gene lists. In addition, potential confounders
   included baseline variability in diet, physical activity levels,
   genetic predispositions, and microbiome composition, which may have
   influenced individual responses to the probiotic intervention. To
   mitigate adherence-related issues, biweekly follow-ups were conducted
   during the 12-week intervention to ensure participants achieved at
   least 80% compliance with the probiotics or placebo regimen. Moreover,
   despite the lack of standardization in the quality-of-life
   questionnaire utilized in this trial, the results showed that the
   intervention was well tolerated and had no negative side effects.

Conclusion

   In summary, this study showed that Lacticaseibacillus paracasei
   MSMC39-1 and Bifidobacterium animalis TA-1 probiotics effectively
   reduced metabolic syndrome risk factors, including significant
   decreases in low-density lipoprotein cholesterol, triglycerides, and
   total cholesterol. Improvements in body weight, body mass index, and
   waist circumference were observed exclusively in the probiotics group.
   Gut microbiome analysis revealed enhanced beta-diversity and increased
   abundance of short-chain fatty acid-producing bacteria (Blautia,
   Roseburia, Collinsella, and Ruminococcus), along with predicted
   functional changes in ribonucleic acid transport, ATP-binding cassette
   transporters, and lipid metabolism pathways, supporting the probiotics’
   role in metabolic regulation.

Supporting information

   S1 Fig. Bacterial taxonomic profile.

   Relative abundance in the placebo and probiotics groups,
   pre-intervention and post-intervention, at the phylum (A and B), family
   (C and D), and genus (E and F) levels, respectively.

   (TIF)
   [247]pone.0317202.s001.tif^ (582.5KB, tif)
   S1 Table. Baseline characteristics of the intervention and control
   groups.

   (DOCX)
   [248]pone.0317202.s002.docx^ (23.8KB, docx)
   S2 Table. Clinical and laboratory characteristics of male participants.

   (DOCX)
   [249]pone.0317202.s003.docx^ (24.9KB, docx)
   S3 Table. Clinical and laboratory characteristics of female
   participants.

   (DOCX)
   [250]pone.0317202.s004.docx^ (24.9KB, docx)
   S4 Table. Multivariate regression analysis of clinical and laboratory
   changes.

   (DOCX)
   [251]pone.0317202.s005.docx^ (24.5KB, docx)
   S5 Table. Quality of life assessment results.

   (DOCX)
   [252]pone.0317202.s006.docx^ (24.5KB, docx)

Data Availability

   The raw sequence data are available under BioSample SAMN42867309 and
   BioProject PRJNA1141093.

Funding Statement

   the study was supported by the Chiangmai Bioveggie and National
   Innovation Agency (grant number PE0201-02-64-11-0252) and the Center of
   Excellence in Probiotics at Srinakharinwirot University (grant number
   324/2565). The funders had no role in study design, data collection and
   analysis, decision to publish, or preparation of the manuscript.

References