Stesura Seveso


455Archivio Italiano di Urologia e Andrologia 2022; 94, 4

ORIGINAL PAPER

No conflict of interest declared.

these commensal, symbiotic or pathogenic microorganisms
is called human microbiota. The human microbiota is
mainly located at four anatomical regions: Skin, genitouri-
nary system, respiratory system, and gastrointestinal sys-
tem (3). The full array of these microorganisms that live on
and in humans and, more specifically, the collection of
microbial genomes that contribute to the genetic portrait is
called the human microbiome. The specific changes in the
microbiome are named dysbiosis (3). The gut microbiome
plays a major role in the regulation, maturation, and func-
tion of the host immune system from the birth. The
immune system has co-evolved a mutualistic relationship
with the gut microbiome residing our bodies while mount-
ing efficient responses to fight invading pathogens.
Distortion of the balance between the useful and harmful
intestinal microorganisms in favor of the harmful ones was
associated with acute or chronic disease processes such as
irritable bowel syndrome, inflammatory bowel disease,
allergic diseases, obesity, depression, atherosclerosis, and
colon cancer (4).
It was reported that urinary dysbiosis was associated with
lower urinary tract symptoms (5). However, while the
relevant studies were conducted with adult patients, none
included the pediatric population. Therefore, we investi-
gated the differences between children with and without
VD regarding intestinal (fecal) microbiota.

MATERIALS AND METHODS
This study was approved by the Ethical Review Committee of
the Sitki Kocman University (180172). Informed consent was
obtained by parents or caregivers of all participants who
signed the relevant forms before assignment to the study.
The subjects were selected among children aged between 5
and 16 who presented to the pediatric urology and nephrol-
ogy outpatient clinics. Patients with congenital genitourinary
(GU) or gastrointestinal (GI) anomalies, GI diseases, acute
infections, neurological anomalies, and chronic constipa-
tion were excluded. Also, patients with a history of GU sur-
gery, GI surgery, or monosymptomatic enuresis, those
treated for VD or given antibiotics, antiviral or antifungal
medications during the last six months were omitted. 
Any functional disturbance in voiding after the completion
of toilet training was defined as VD. This occurs due to over
activity or inadequate relaxation of the pelvic floor muscles,
which are striated muscles under voluntary control. The

Objective: Voiding dysfunction (VD), which
encompasses many urinary symptoms that

are not caused by neurological or anatomical anomalies, is a
frequently encountered functional urinary bladder disorder in
children. It was reported that there was an association between
lower urinary tract symptoms and fecal microbiota in adult
patients. Therefore, we aimed to investigate the differences in
fecal microbiota between children with or without VD. 
Methods: Two patient groups, including 30 patients, were com-
pared. Group 1 included patients with VD, while Group 2 con-
sisted of healthy children. All study participants were asked to
fill lower urinary tract and voiding dysfunction symptom score
forms with the assistance of their parents. Subsequently,
uroflowmetry tests and postvoiding residual urine measurements
were performed. Fresh stool samples were collected from all
children and analyzed by polymerase chain reaction. General
bacterial load and presence of Roseburia intestinalis,
Clostridium difficile, Fusobacterium nucleatum, and Bacteroides
clarus were tested.
Results: The two groups were significantly different regarding
general bacterial load; the presence of Fusobacterium nuclea-
tum. Clostridium difficile and Bacteroides clarus was not detect-
ed in the fresh stool samples of the patients in Group 2; the
counts of Roseburia intestinalis were less in Group 1 than in
Group 2, although there was no statistically significant differ-
ence. There was a negative correlation between symptom scores,
general bacterial load, and the presence of Fusobacterium
nucleatum. However, there was no correlation between the pres-
ence of Roseburia intestinalis and symptom scores.
Conclusions: There is a potential relationship between VD and a
deviation in the fecal microbiota in the pediatric population.

KEY WORDS: Voiding dysfunction; Fecal microbiota; Fecal
 microbiota change.

Submitted 28 October 2022; Accepted 6 November 2022 

INTRODUCTION
Voiding dysfunction (VD) is also named bladder dysfunction
in children. It is a general term encompassing both voiding
and storage dysfunctions. It is a functional bladder anom-
aly encountered in children who do not have any neuro-
logical and anatomical abnormalities. It is not rare in chil-
dren; approximately 40% of children presenting to pedi-
atric urology clinics are affected by VD (1, 2). The human
body is a complex system hosting various microorganisms,
including bacteria, fungi, and parasites. The assemblage of

Is there a difference in fecal microbiota of children 
with and without voiding dysfunction? 

Ilker Akarken 1, Hüseyin Tarhan 1, Gamze Şener 2, Hasan Deliktas 1, Nurcan Cengiz 3, Hayrettin Şahin 1

1 Mugla Sıtkı Kocman University, School of Medicine, Department of Urology, Turkey;
2 Izmir Katip Celebi University, School of Medicine, Department of Microbiology, Turkey;
3 Mugla Sıtkı Kocman University, School of Medicine, Department of Pediatric Nephrology, Turkey.

DOI: 10.4081/aiua.2022.4.455

Summary



Archivio Italiano di Urologia e Andrologia 2022; 94, 4

I. Akarken, H. Tarhan, G. Şener, H. Deliktas, N. Cengiz, H. Şahin

456

patients presented to outpatient clinics with lower urinary
tract symptoms (LUTS) and diagnosed with VD were
included in Group 1. Group 2 consisted of healthy pedi-
atric patients who presented to the same outpatient clin-
ic for check-up purposes.
All study participants were evaluated regarding LUTS with
the assistance of their caregivers. First, voiding dysfunction
symptom score (VDSS) forms were filled for each subject
(6). Subsequently, a uroflowmetry test was performed.
Next, the voiding patterns (i.e., normal, parabolic, tower,
plateau, staccato, interrupted) and voided volumes were
recorded for each patient. Following this, post-voiding
residual urine volumes were measured and recorded.
A 3-gram fresh stool sample was collected from all
patients, and the samples were stored at -80°C. 

Analysis of the stool samples

DNA isolation
Roche Magna Pure Compact robotic DNA isolation sys-
tem (Roche, Germany) protocol was used to isolate DNA
at room temperature.

DNA quantification
The DNA was quantified using a Nanodrop 2000 (Thermo
Scientific, USA). The absorbance ratios 260/280 and
260/230 were used to assess the purity of DNA. 

Real-time PCR (qPCR)
Fusobacterium nucleatum (FusN), Clostridium difficile
(CloD), Bacteroides clarus (BacC), Roseburia intestinalis
(RosIn) and general intestinal bacteria (16SInt) were
detected in the samples. 
Primers and the Taqman probe (Hydrolysis probe) were
designed for five targets (Figure 1). 
The ready-to-use lyophilized primers (5 nmol) and probes
(3 nmol) were wettened on synthesis paper (TIB Molbiol,
Germany) and diluted to 10 pmol/ul stocks. 

LightCycler480 Probes Master (Roche Diagnostics, Germany)
served as Enzyme&master mix. The processes were imple-
mented in LightCycler480 II (Roche Diagnostics, Germany).
The results were analyzed in the Abs Quant/2nd derivative
analysis module. Samples creating sigmoidal curves were
considered positive, while others were considered negative. 
General bacterial load was measured, and the presence of
Roseburia intestinalis, Clostridium difficile, Fusobacterium
nucleatum, and Bacteroides clarus was assessed.

Statistical analysis
The Kolmogorov-Smirnov test was used for assessing the
distribution of data. Student’s t-test was used to compare
the groups regarding continuous variables and the chi-
square test was used to compare categorical variables.
The Pearson correlation coefficients (r) were used for cor-
relation analysis. The data were displayed as means, stan-
dard deviations (SD), and ranges (minimum-maximum).
The p value was considered statistically significant when
it was less than 0,05. All statistical analyses were per-
formed using the Statistical Package for Social Sciences
software (SPSS v24, IBM Corporation, New York, US).

Table 1. 
Demographic and clinical data and results 
of the comparative analysis.

Groups Group 1 Group 2 p value
Age- year 8.26 ± 1.9 8.00 ± 1.6 0.574
Gender 0.902
Female n (%) 15 (60.0) 14 (58.3)
Male n (%) 10 (40.0) 10 (41.7)
Frequency (8 >) 0.001
Present n (%) 21 (84.0) 4 (16.7)
Absent n (%) 4 (16.0) 20 (83.3)
Urgency 0.001
Present n (%) 19 (76.0) 6 (25.0)
Absent n (%) 6 (24.0) 18 (75.0)
Hesitancy 0.015
Present n (%) 11 (44.0) 3 (12.5)
Absent n (%) 14 (56.0) 21 (87.5)
Terminal dribbling 0.001
Present n (%) 18 (72.0) 4 (16.7)
Absent n (%) 7 (28.0) 20 (83.3)
Low urine flow rate 0.001
Present n (%) 13 (52.0) 1 (4.2)
Absent n (%) 12 (48.0) 23 (95.8)
Maneuvers to hold urine 0.001
Present n (%) 19 (76.0) 2 (8.3)
Absent n (%) 6 (24.0) 22 (91.7)
Interrupted voiding 0.001
Var n (%) 16 (64.0) 4 (16.7)
Yok n (%) 9 (36.0) 20 (83.3)
Straining to void 0.001
Present n (%) 15 (60.0) 0 (0.0)
Absent n (%) 10 (40.0) 24 (100)
Voiding pattern 0.001
Normal n (%) 8 (32.0) 21 (87.5)
Staccato n (%) 6 (24.0) 0 (0)
Tower n (%) 11 (44.0) 3 (12.5)
Plateau n (%) 0 (0) 0 (0)
Interrupted n (%) 0 (0) 0 (0)
Voided volume 0.001
Lower than expected bladder capacity (%) 17 (68.0) 1 (4.2)
Consistent with the expected bladder capacity (%) 8 (32.0) 23 (95.8)
Post-voiding residual urine volume (ml) 44.4 ± 21.6 19.4 ± 6.4 0.574
Voiding dysfunction symptom scores 21.9 ±  6.9 6.3 ± 1.3 0.001

Figure 1. 
Primer sequences.

Gene Sequencee

FusN-F TTCAATAAAAgTggCAggTCAAg

FusN-R TAACAACACATgCAggTCAATgg

FusN-Pr 6FAM-ACTCgAACCCCCAACCCTCggTTT--TMR

CloD-F gCAAgTTgAgCgATTTACTTCggT

CloD-R gTACTggCTCACCTTTgATATTYAAgAg

CloD-Pr 6FAM-TgCCTCTCAAATATATTATCCCgTATTAg--TMR

BacC-F TCCATCCgCAAgCCTTTACT

BacC-R gCTTCCggTgCCATTgACTA

BacC-Pr 6FAM-TTCATCATCACAgCCgACAACgCA--TMR

RosIn-F CggATTTgCAgTggCAAgTT

RosIn-R TgATTgCAgACgCCAATgTC

RosIn-Pr 6FAM-CgTgAAAAATCCgCgCATCTggC--TMR

16S-IntC-F CgTCAgCTCgTgYCgTgAg

16S-IntC-R CgTCRTCCCCRCCTTCC

16S-IntC-Pr HEX-TTAAgTCCCRYAACgAgCgCAACCC--BBQ



457Archivio Italiano di Urologia e Andrologia 2022; 94, 4

Microbiota of children with urinary dysfunction

RESULTS
The mean patient age was 8.1 ± 0.25 (6-13). Although we
planned to include 30 patients in each group, 5 patients
were excluded from Group 1, and 6 patients were excluded
from Group 2 due to the failure in the DNA isolation
process. Thus, there were 25 patients in Group 1 and 24
patients in Group 2. Demographic data and clinical features
of the study patients, including lower urinary tract symp-
toms, uroflowmetry, PVR measurement results, and voiding
dysfunction symptom scores, are displayed in Table 1. The
comparative analysis revealed that general bacterial load
and the rate of Fusobacterium nucleatum presence were sig-
nificantly lower in patients with VD than in healthy patients
(p = 0.043 and p = 0.009, respectively).  Although Roseburia
intestinalis was present in fresh stool samples of both patient
groups, its rate was relatively lower in the patient group
with VD. Clostridium difficile and Bacteroides clarus were not
detected in the fresh stool samples of the healthy patient
group (Table 2). In fresh stool samples, the correlation
between voiding dysfunction symptom score (VDSS) and gen-
eral bacterial load, Roseburia intestinalis, Clostridium difficile,
Fusobacterium nucleatum, and Bacteroides clarus counts were
analyzed. There was a negative correlation between VDSS
and general bacterial load and Fusobacterium nucleatum
counts (p = 0.033 and p = 0.004, respectively). Although
there was also a negative correlation with Roseburia intesti-
nalis, it was statistically insignificant (p = 0.25) (Table 3).
Since Clostridium difficile was not detected in the fresh stool
samples of the patients in Group 2, a correlation analysis
could not be performed. 

DISCUSSION
Since bowels have a 250 m2 absorptive surface area and a
nutrient-rich content, they have the most extensive flora
bearing various microorganisms. Therefore, it is difficult
to determine all types of bacteria and their counts includ-
ed in the intestinal flora. However, investigations utilizing

current methods elucidated more than 100 trillion bacte-
ria and more than 1000 bacteria types in the bowel (7). 

The microbiota, which includes various and many
microorganisms, starts to develop after birth. Its initial
content depends on genetic and geographical factors,
route of labor, age at labor, and diet (8). continues to
develop and modulate in species abundance for about 3
years, until the microbiota becomes adult-like.
Until age 1, bowel microbiota shows significantly less vari-
ation than microbiota in toddlers, adolescents, or adults.
Remarkable changes occur in the content of intestinal
microbiota until age 3. The primary microbiota evolves to
adult microbiota after age 3 regarding the variability of
 bacteria types (9, 10). Anaerobic, facultative anaerobic, and
aerobic bacteria are present in the gastrointestinal micro-
biota. Approximately 90% of this flora consists of
Bacteroides and Firmicutes species. Other microbial phyla
are Actinobacteria, Proteobacteria, Verrucomicrobia, and
Fusobacteria. The bacteria investigated in our study were
selected as per the variability in microbiota. 
The association between LUTS and urinary microbiome
was previously reported using 16S rRNA gene sequence
(5). However, only a few studies investigated the associa-
tion between intestinal microbiota and LUTS. Holland et al.
studied 30 male patients with LUTS and suggested a sig-
nificant relationship between the symptom scores and the
presence of specific bacteria types in the intestinal micro-
biota. Of note, this study did not include a comparative
analysis between patients with and without LUTS (11).
Braundmeier-Fleming et al. compared the stool samples of
the patients who had interstitial cystitis with those of
healthy subjects (12). In line with our study, these
researchers performed polymerase chain reaction (PCR) on
stool samples. They reported that the counts of E. sinensis,
C. aerofecaciens, F. prausnitzii, and O. splanchnicus were sig-
nificantly lower in the fecal microbiota of the patients with
interstitial cystitis than in healthy subjects. In a fecal micro-
biota study including patients with chronic prostatitis/
chronic pelvic pain syndrome (another functional lower
urinary tract disorder such as interstitial cystitis) the alpha
diversity analysis revealed that the diversity of fecal micro-
biota was significantly lower in the patient group than in
healthy subjects (13). Okamoto et al. studied 1113 patients
comparing patients with high overactive bladder symptom
scores and urgency with those who had low symptom
scores without urgency. They found that the former group
had a significantly lower bacterial load in the fecal micro-
biota (14). They suggested that the natural bacterial load
reduction might be correlated with the disease process.
Our study determined a significant difference between
patients with normal and abnormal voiding dysfunction
symptom scores concerning general bacterial load and a
negative correlation between VDSS and the general bacter-
ial load. Of note, reduction in the bacterial load infers
reduction of the microorganisms beneficial for health. 
Some bacteria such as Bifidobacterium species in microbiota
have beneficial critical roles, and they can be used as
 probiotics. These bacteria were low in patients with overac-
tive bladder (14). On the other hand, the counts of
Faecalibacterium species were higher in patients with over-
active bladder than in the control group patients (14).
Detection of high numbers of these bacteria in overactive

Table 2. 
The comparison of the groups regarding bacteria 
in the fresh stool samples.

Groups Group 1 Group 2 p value
General bacterial load 16.5 ± 3.2 18.3 ± 2.9 0.043
Fusobacterium nucleatum 34.8 ± 2.6 37.2 ± 2.9 0.009
Clostridium difficile 33.8 ± 0 - -
Bacteroides clarus 27.3 ± 4.4 - -
Roseburia intestinalis 27.3 ± 4.9 28.4 ± 2.5 0.486

Table 3. 
Results of the correlation analysis between voiding 
dysfunction symptom scores, general bacterial load and 
counts of specific bacteria.

Correlation coefficient p value
General bacterial load    -0.305 0.033
Fusobacterium nucleatum -0.435 0.004
Roseburia intestinalis -0.225 0.250
Bacteroides clarus 0.919 0.258
Clostridium difficile - * - *

* Since Clostridium Difficile was not detected in the fresh stool samples of the patients in Group 2, 
a correlation analysis could not be performed.



Archivio Italiano di Urologia e Andrologia 2022; 94, 4

I. Akarken, H. Tarhan, G. Şener, H. Deliktas, N. Cengiz, H. Şahin

458

bladder patients is an unfavorable sign indicating the devi-
ation in the intestinal microbiota. 
In our study, Fusobacterium nucleatum counts were signifi-
cantly lower in patients with VD than in controls (p =
0.009). The counts of Roseburia intestinalis were relatively
lower in the former group than in the latter although the
difference was not statistically significant (p = 0.486). 
Clostridium difficile and Bacteroides clarus were not detected
in the healthy patient group. Detection of these bacteria in
the patient group with VD can be considered an indicator
of dysbiosis. It is widely accepted that deviations in the
intestinal microbiota led to an increase in the levels of toxic
metabolites and a reduction in the number of useful
metabolites, thus contributing to disease processes (15).
The intestine-brain axis is a two-way communication net-
work. This network consists of the central nervous system
(CNS), which includes the brain and the spinal cord, auto-
nomic nervous system, enteric nervous system, and the
hypothalamic-pituitary-adrenal axis (16). Thus, the intes-
tinal microbiota can affect the enteric neurons and the
CNS via metabolites secretion. A potential dysfunction
affects both sides since this is a two-way interaction (17).
The effects of the intestinal microbiota on brain develop-
ment and the emergence of neurodegenerative diseases
were also reported (18). Also, it was noted that there was
a relationship between the reduction of intestinal micro-
bial diversity and cognitive dysfunction. In addition, it
was suggested that a healthy microbiota was associated
with learning skills and memory development (19). Our
study showed a significant reduction in the general bacte-
rial load in the patient group with VD. Therefore, we sug-
gest that dysbiosis could negatively affect autonomic nerv-
ous system maturation or the coordination between the
CNS and the lower urinary tract. 
Our study has some limitations. First, it was conducted
with a limited number of patients because of Coronavirus
disease-2019 (COVID-19) pandemic during the study
period. Second, the total bacterial diversity could not be
analyzed since DNA sequence sampling could not be per-
formed in fresh stool samples due to financial reasons.

CONCLUSIONS
We conclude that there is a potential relationship between
VD and a deviation of the fecal microbiota. However, we
further studies, including more extensive patient series, are
needed in to confirm this finding.

ACKNOWLEDGEMENTS
The authors would like to thank “Mugla Sitki Kocman
University Scientific Research Project Department” for their
support.

REFERENCES
1. Farhat W, Bägli Dj, Capolicchio G, et al. The dysfunctional void-
ing scoring system: quantitative standardization of dysfunctional
voiding symptoms in children. J Urol 2000; 164:1011-5.

2. Austin PF, Bauer SB, Bower W, et al. The standardization of termi-
nology of lower urinary tract function in children and adolescents:
Update report from the standardization committee of the International
Children's Continence Society. Neurourol Urodyn 2016; 35:471-81.

3. Gill SR, Pop M, DeBoy RT, et al. Metagenomic analysis of the
human distal gut microbiome. Science 2006; 312:1355-9.

4. Duvallet C, Gibbons SM, Gurry T, et al. Meta-analysis of gut
microbiome studies identifies disease-specific and shared responses.
Nat Commun 2017; 8:1-10.

5. Antunes-Lopes T, Vale L, Coelho AM, et al. The role of urinary
microbiota in lower urinary tract dysfunction: a systematic review.
Eur Urol Focus 2020; 6:361-9.

6. Akbal C, Genc Y, Burgu B, et al. Dysfunctional voiding and incon-
tinence scoring system: quantitative evaluation of incontinence symp-
toms in pediatric population. J Urol 2005; 173:969-73.

7. Qin J, Li R, Raes J, Arumugam M, et al. A human gut microbial
gene catalogue established by metagenomic sequencing. Nature
2010; 464:59-65.

8. Pelzer E, Gomez-Arango LF, Barrett HL, Nitert MD. Maternal
health and the placental microbiome. Placenta 2017; 54:30-7.

9. Arrieta M-C, Stiemsma LT, Amenyogbe N, et al. The intestinal
microbiome in early life: health and disease. Front Immunol 2014;
5:427.

10. Yatsunenko T, Rey FE, Manary MJ, et al. Human gut microbio-
me viewed across age and geography. Nature 2012; 486:222-7.

11. Holland B, Karr M, Delfino K, et al. The effect of the urinary and
faecal microbiota on lower urinary tract symptoms measured by the
International Prostate Symptom Score: analysis utilising next-gener-
ation sequencing. BJU Int 2020; 125:905-10.

12. Braundmeier-Fleming A, Russell NT, Yang W, et al. Stool-based
biomarkers of interstitial cystitis/bladder pain syndrome. Sci Rep
2016; 6:1-10.

13. Shoskes DA, Wang H, Polackwich AS, et al. Analysis of gut
microbiome reveals significant differences between men with chronic
prostatitis/chronic pelvic pain syndrome and controls. J Urol 2016;
196:435-41.

14. Okamoto T, Hatakeyama S, Imai A, et al. Altered gut microbio-
me associated with overactive bladder and daily urinary urgency.
World J Urol 2021; 39:847-53.

15. Yin J, Liao SX, He Y, et al. Dysbiosis of gut microbiota with
reduced trimethylamine-N-oxide level in patients with large-artery
atherosclerotic stroke or transient ischemic attack. J Am Heart
Assoc2015; 4:e002699.

16. Carabotti M, Scirocco A, Maselli MA, Severi C. Erratum: The
gut-brain axis: interactions between enteric microbiota, central and
enteric nervous systems. Ann Gastroenterol. 2015; 28:203-209.

17. Yang NJ, Chiu IM. Bacterial signaling to the nervous system
through toxins and metabolites. J Mol Biol 2017; 429:587-605.

18. Martin CR, Osadchiy V, Kalani A, Mayer EA. The brain-gut-
microbiome axis. Cell Mol Gastroenterol Hepatol. 2018; 6:133-48.

19. Davidson GL, Cooke AC, Johnson CN, Quinn JL. The gut micro-
biome as a driver of individual variation in cognition and functional
behaviour. Philos Trans R Soc Lond B Biol Sci. 2018; 373:20170286.

Correspondence
Ilker Akarken, MD - ilkerakarken@gmail.com
Hüseyin Tarhan, MD (Corresponding Author)
drhuseyintarhan@gmail.com
Hasan Deliktas, MD - drhasand@gmail.com
Hayrettin Şahin, MD - hsahin63@gmail.com
Mugla Sıtkı Kocman University, School of Medicine, 
Department of Urology, Turkey

Gamze Şener, MD - asligamze.seher@saglik.gov.tr
Izmir Katip Celebi University, School of Medicine, 
Department of Microbiology, Turkey

Nurcan Cengiz, MD - nurcandinler@mu.edu.tr
Mugla Sıtkı Kocman University, School of Medicine, 
Department of Pediatric Nephrology, Turkey