E-ISSN: 2814 – 1822; P-ISSN: 2616 – 0668
ORIGINAL RESEARCH ARTICLE
*1Bitet, D. E. , 2Kumurya, A.S. , 2Aliyu, A. I., 3Ega, B. and 4Ajagbe J.M.
*1Bitet Dogo Ezekiel, Rural Hospital Kwoi, Ministry of Health Kaduna state.
2 Departments of Medical Laboratory Science, Bayero University, Kano, Nigeria
2Department of Medical Laboratory Science, Bayero University, Kano, Nigeria
Department of Medical Microbiology Ahmadu Bello University Teaching Hospital Shika, Zaria, Nigeria
Department of Medical Laboratory Science, School of Health
Technology, Kankia, Katsina State,Nigeria
* Corresponding Author: E-mail: ezekieldogobetet@ymail.com
Background: The purpose of this study was to molecularly detect and evaluate the prevalence of Chlamydia trachomatis and Neisseria gonorrhoeae, infections among infertile men that attended some health facilities in some states of the Northwest, Nigeria using a multiplex molecular method and the possible impact of C. trachomatis and N. gonorrhoeae, infections on semen parameters was also noted in the present study. Methods: A total of 383 infertile male semen samples were collected for this study. C. trachomatis and N. gonorrhoeae infections were molecularly detected in the semen samples using the multiplex method. Semen parameters, risk factors, and age were analyzed and collated. Results: A total of 28 and 21 semen samples were found positive for C. trachomatis and N. gonorrheae, respectively, with a prevalence of C. trachomatis and N. gonorrhoeae relatively lower 7.3% and 5.5%, respectively. Those with primary infertility have the highest infections, with those with secondary infertility showing the least infection. Conclusions: Our study demonstrated a moderately medium prevalence of C. trachomatis and N. gonorrheae infection based on the multiplex PCR detection method. C. trachomatis and N. gonorrheae infection could possibly impair the male fertility factor through increased sperm DNA damage.
Keywords: Multiplex PCR, Chlamydia trachomatis, Neisseria gonorrhoeae, Infertile Male, Semen samples
Infertility is defined as the inability of couples to reproduce after a year of unprotected sexual intercourse (Albert et al., 2014; Hassan et al., 2019; WHO, 2023). Male infertility is a public world health problem affecting about 10–15% of couples, which accounts for half of the infertile cases (Albert et al., 2014, WHO, 2023). The cause of male infertility has been multifactorial in which the role of urinary tract infections has been identified to be associated in recent reproductive health services. Chlamydia trachomatis, Neisseria gonorrhoeae, mycoplasma species (Mycoplasma genitalium and Mycoplasma hominis), ureaplasma species (Ureaplasma urealyticum and Ureaplasma parvum) and Treponema pallidum are the major urinary tract infections.
Precise mechanisms of urinary pathogens inflicting male fertility capability remain complex and unknown. The process of triggered inflammation by urinary pathogens leading to the deterioration of spermatogenesis and obstruction of the seminal tract could be partly related to the cause of infertility. Also, the process of apoptosis is related to inflammatory conditions, which could cause the impairment of semen parameters, though no established literature backs the association between infections and semen parameters (Gimenes et al., 2014; Kim et al., 2017).
There are two types of infertility: Primary and secondary infertility. Primary infertility is defined as a couple’s inability to conceive after at least one year of sexual intercourse without the use of contraception. Couples who have conceived at least once but were unable to conceive again have secondary infertility (Abu Khanjar and AL-Azari, 2022). Some research work says that urinary tract infections implicated by some infectious pathogens include; bacteria, viruses, fungi, and protozoa, which are responsible for 15% of male infertility (Hassan et al., 2019; Abu Khanjar and AL-Azari, 2022). Microorganisms may influence the male reproductive system through motile sperm agglutination, decreasing acrosome reaction capacity, and changing cell morphology, or indirectly by releasing reactive oxygen species produced by infection-induced inflammation (Oghael et al., 2020; Vadim, 2024), which has been linked to sperm DNA fragmentation and male infertility (Oghbael et al., 2020). Any man can have asymptomatic urinary tract infections, such as chlamydia and Neisseria infections, which can be detected in urine and seminal fluid (Hassan et al., 2019). Infections of the urinary tract are a common cause of infertility in men, and several bacteria have been implicated in infertility in men in several ways. Infections cause serious havoc on reproduction in several ways. Retardation to the spermatogenesis process, sperm malfunction, and urinary tract obstruction are some of these processes. Chlamydia trachomatis and N. gonorrheae pathogens are the most common bacteria linked to male genital infections (Abu Khanjar and Al-Azawi, 2022). The World Health Organization reports about 370 million UTI infections per year. The pathogenic bacteria N. gonorrhea and C. trachomatis are responsible for 87 million of them. The illness is one of the world’s most deadly and rapidly spreading diseases. Moreover, the second most common sexually transmitted disease is gonorrhea and Chlamydia. Predisposing factors include younger age, a new sex partner, a sex partner with concurrent partners, many sex partners, a history of gonorrhea infection, and having other sexually transmitted illnesses are the most common risk factor.
The fundamental contemporary diagnostic method of urinary tract pathogens has been the bacterial cultural method, which is prone to so many errors (personnel, reagents, and equipment), time-consuming, and with less sensitivity. The molecular method of detecting these pathogens directly from the samples based on nucleic acid amplification has been widely used in many research-related works, has proven reliable, and has relatively high sensitivity and specificity (Cook et al., 2016).
A semen sample was used in the detection of C. trachomatis and N. gonorrhoeae (Mohammed and Mutalib, 2022). Multiplex PCR method was adopted for the amplification testing method based on isothermal amplification of pathogens RNA, which has provided an accurate and rapid detection of the urinary pathogens (Cook et al., 2016; Mohammed and Mutalib, 2022). To our knowledge, there is no data available published regarding the prevalence of C. trachomatis and N. gonorrhoeae, in infertile men using direct semen samples for the detection of pathogens. Thus, this study aimed to molecularly detect and observe the prevalence of C. trachomatis and N. gonorrhoeae,
The study covered selected states of the Northwest geopolitical region of Nigeria. The region consist of seven states in the Northwestern Nigeria; Kano, Jigawa, Kaduna, Katsina, Kebbi, Sokoto, and Zamfara. The weather is usually dry, and the temperature drops at night; the region is largely agricultural.
The Northwest region has a population of about 35,786,944 million and a total land mass of 216,029 km2 (Ado, 2016; Kehinde, 2019; NPC/FMH, 2020).
The region shares boundaries with Bauchi State in the North East from Kano State, in the North with Niger Republic with Jigawa State, and Niger State through Zamfara State from Sokoto; it also borders with Niger Republic in the Northern part of the State. From Kebbi State, the region borders with Niger and the Benin Republic; through Katsina, Kaduna, and Jigawa State, the region borders the Niger Republic in the north, FCT Abuja, Nasarawa, Plateau, Bauchi, and Yobe states respectively (Ado, 2016; NPC/FMH, 2020).
The region is multicultural and multi-ethnic but majorly dominated by Hausa Fulani and many other minority ethnic groups (Ado, 2016; Kehinde, 2019; NPC/FMH, 2020).
The study population consisted of suspected male infertile patients attending health facilities within the selected States in the Northwestern region of Nigeria, who consented and gave their semen samples for the research. The selected States and health facilities are Kano State: Aminu Kano Teaching Hospital (AKTH Kano) and Murtala Specialist Hospital Kano, Kaduna State: Barau Dikko Teaching Hospital Kaduna and Dr. Gwamna Awan General Hospital Kakuri, Kaduna and Jiigawa State: Federal Medical Center Dutse and Rasheed Shekoni Specialist Hospital(now Teaching Hospital).
Adult married male patients with a suspected case of either primary or secondary infertility who can produce semen and are attending any of the health facilities within the selected states.
Adolescents, singles, those who cannot produce sperms (oligospermia), and those who refuse to consent.
A total of three hundred and eighty (380) samples were used for the research. This was obtained using the standard formula provided by Riley et al. (2020). Using the prevalence rate of infertility of 40 -50 % in Nigeria (Udia and Enokpe, 2017; Westmann, 2018) and a precision of 5 % (with 15% confidence).
Formula: n = Z2 P (1- P)
d2
Where:
n = Sampling size
P = Prevalence rate
Z = Standard normal distribution of 95% confidence limit = 1.96
d = Absolute desired precision at 5% = 0.05
Hence; 1.962 x 0.45 (1- 0.45) = 380
0.052
(But 383 samples were collected for equality and precision). The samples were not equally distributed because of the variation in the number of clients attending these selected varies. Therefore, based on the variation in the inflow of clients in these facilities, the following sample allocations were obtained: AKTH Kano – 91, BDTH Kaduna – 67, Federal Medical Center Birnin Kudu – 67, Murtala Mohammed Specialist Hospital Kano – 67, Rasheed Shekoni Specialist Hospital Dutse, Jigawa State – 46 and Gwamna Awan General Hospital Kakuri Kaduna State – 46.
Ethical approvals were obtained from the ethical committees of the various health institutions as attached in appendices iii – x with the following reference numbers: MOH/Off/797/T.1/1331, MOH/ADM/1744/VOL.1/754, MOH/SEC.3/S/808/1, FMC/HREC/APP/CLN/001/1/184, AKTH/MAC/SUB/12A/P-3/VI/2763, BDTH/HREC/RF: 19 - 00015 and RSSH/GEN/226/V.1/11. Verbal and written consents were obtained from the volunteers using the consent form attached in Appendix i. All clients received an explanation (both in Hausa and English) of the study before obtaining informed consent. Well-structured questionnaires attached in appendix ii (explained in Hausa for those who could not understand, read, or write) were administered to all clients before samples were collected (appendix 8).
All samples were collected by masturbation into sterile graduated wide-mouth containers following 3 days of sexual abstinence; equally plain condoms were given to those who couldn’t restrain self-control during masturbation/unable to use masturbation in order not to compromise the semen volume. After liquidation, a conventional analysis was performed according to the World Health Organization guidelines (WHO, 2010).
The parameters measured are the volume of the ejaculate (ml), the sperm concentration (x106/ml), the motility (%), and the morphology (% of normal forms).
The semen samples were observed for liquefaction for 1 hour after ejaculation to prevent dehydration, which may affect the semen volume and quality. The viscosity of the sample was estimated by gently aspirating it into a wide-bore (1.5 mm diameter) plastic disposable pipette, allowing the semen to drop by gravity and observing the length of the thread. The color of semen was checked, normal liquefied semen sample incorporated a homogeneous, grey-opalescent look.
The samples were directly collected into a graduated glass or plastic container with a wide mouth, and the volumes were directly from the graduations (0.1 ml accuracy); pH was measured using a pH meter within 1 hour of the collection, the pH paper was dipped into the semen sample for 30 seconds. After 30 seconds, the color of the impregnated zone was compared with the pH standard calibration chart.
The sample was thoroughly mixed to obtain a heterogeneous liquefied sample before taking representative semen for analysis, sperm motility, vitality, concentration, and morphology. A standard volume (10 µl) of semen was placed onto a clean glass slide and then covered with a coverslip of 22 × 22 mm with a chamber depth of approximately 20 µm, taken care to avoid the formation of air bubbles, then allowed to stand for 5minutes for the sperm cells to settle and then was examined microscopically under light microscope, aside from spermatozoa, other cells were looked for as some of which may be clinically relevant, such as leukocytes and immature germ cells, the latter 2 together brought up as “round cells.”
Two hundred microliters (200μl) of semen sample was transferred to a microcentrifuge tube, and 200μl of biofluid and cell buffer (red) 20μl of proteinase K was added. The mixture was vortex for 10 – 15 seconds and then incubated at 550C for 10 minutes. One (1) volume of genomic binding buffer was added to the digested sample and was vortex for 10 -15 seconds (equal volume; 420μl Genomic binding buffer to the 420μl digested sample). The mixture was transferred to a Zymo-spinTM IIC-XLR Column in a collection tube and Centrifuged at ˃12000 xg for 1 minute. The collection tube was discarded with the flow through. Then 400μl DNA pre-wash buffer was added to the spin column in a new collection tube and was centrifuged at ˃ 12000xg for 1 minute, and the collection tube was emptied. Then 700μl g-DNA wash buffer was added to the spin column, Centrifuged at 12000xg for 1 minute, and the collection tube was emptied. Then 200μl g-DNA wash buffer was added to the spin column and was centrifuged at 12000xg for 1 minute, and the collection tubes with the flow through were discarded.
The spin column was transferred to a clean microcentrifuge tube, and 100μl DNA Elution buffer was added directly to the matrix and was incubated for 5 minutes at room temperature, then was centrifuged at maximum speed for 1 minute to elute the DNA. The eluted DNA was used partly immediately and stored at -200C.
The Chlamydia trachomatis gene was detected by PCR using a pair of primers targeting the conserved region of the C. trachomatis, as described in Table 3.1. Each tube was made to a final volume of 20μL comprising of 4μl of DNA template, 10μL of 2xEasyTaq® PCR Supermix (TransGen, Beijing, China), 4μL of molecular grade water, and 2μL of each of the forward and reverse primers of the omp1 (Table 3.1). The negative control tube comprised of the same constituents except for the DNA which was replaced with molecular-grade water.
The mixtures were loaded into the PTC100 Peltier thermocycler (MJ Research, USA), and the PCR condition was set as follows: pre-denaturation at 95oC for 5 minutes; 40 cycles of denaturation at 95oC for 30 seconds, annealing at 60oC for 30 seconds and extension at 72oC for 30 seconds; then a final extension at 72oC for 5 minutes. After the PCR, 5μL of the amplicons were separated and detected by gel electrophoresis containing 2μL of Ethidium bromide on 1% TBE buffer with 100V for 1 hour. The bands were visualized using a UV Tran illuminator, captured, and analyzed by the Image computerJ software (Schroeder et al., 2021).
The Neisseria gonorrhoeae gene was detected by PCR using a pair of primers targeting the conserved region of the C. trachomatis, as described in Table 3.1. Each tube was made to a final volume of 20μL comprising of 4μl of DNA template, 10μL of 2xEasyTaq® PCR Supermix (TransGen, Beijing, China), 4μL of molecular grade water, and 2μL of each of the forward and reverse primers of the N. gonorrhoeae (Table 3.1). The negative control tube comprised of the same constituents except for the DNA which was replaced with molecular-grade water.
The mixtures were loaded into the PTC100 Peltier thermocycler (MJ Research, USA), and the PCR condition was set as follows: pre-denaturation at 95oC for 5 minutes; 40 cycles of denaturation at 95oC for 30 seconds, annealing at 55oC for 30 seconds and extension at 72oC for 30 seconds; then a final extension at 72oC for 5 minutes. After the PCR, 5μL of the amplicons were separated and detected by gel electrophoresis containing 2μL of Ethidium bromide on 1% TBE buffer with 100V for 1 hour. The bands were visualized using a UV Tran illuminator, captured, and analyzed by the ImageJ computer software (Schroeder et al., 2021).
Table 3.1 Primers and probes for PCR
| Primer | Primer sequence (5′ - 3′) | Band size (bp) |
|---|---|---|
| C. trachomatis (ompA) | F: ATG AAA AAA CTC CTT GAA ATC G R: GAA CTA AGG ATG CCT CTA TTG |
800 |
| N. gonorrhoeae (ProA) | F: CCG GAA CTG GTT TCA TCT GAT T R: CAA GCC GAT AAA GGA TTC CCT |
295 |
(Simoni et al., 1999, Chen et al., 2022; Zhai et al., 2022)
Data analysis was performed using SPSS version 22.0 for Windows Software Package (SPSS Inc., Chicago, IL, USA). Data were expressed as percentages and mean ± SD. To identify the independent association between the various seminal parameters and selected variables, independent t test.
The distribution of sociodemographic factors among the study population indicated that those between the ages of 29 – 37 had the highest number of study subjects, 207(54.0%), while ages 58-68 had the least number of subjects, 3(0.8%). The tribe had the Hausa/Fulani with the highest population of subjects, 254(66.3%), and Igbos with the lowest number of subjects, 25(6.5%). The occupation had farmers with the highest number of 160(41.8%), while others had the lowest number of subjects, 34(8.9%). Type of marriage had monogamy with the highest number of subjects, 294(76.8%), while polygamy had the least number of subjects, 89(23.2%). Years in marriage had those who have spent more than six years into their marriages with the highest number of subjects, 116(30.3%), while those who are 1 year old into their marriage had the least of subjects, 18(4.7%) Table 1.
Table 1: Socio-demographic characteristics of the participants
| VARIABLES | FREQUENCY | PERCENTAGES (%) |
|---|---|---|
| AGE | ||
| 18 – 28 | 60 | 15.7 |
| 29 – 37 | 207 | 54.0 |
| 38 – 48 | 89 | 23.2 |
| 49 – 57 | 24 | 6.3 |
| 58 – 68 | 3 | 0.8 |
| TRIBE | ||
| Hausa/Fulani | 254 | 66.3 |
| Yoruba | 36 | 9.4 |
| Igbo | 25 | 6.5 |
| Others | 68 | 17.8 |
| OCCUPATION | ||
| Civil servants | 110 | 28.7 |
| Farmers | 160 | 41.8 |
| Artisans | 79 | 20.6 |
| Others | 34 | 8.9 |
| TYPE OF MARRIAGE | ||
| Monogamy | 294 | 76.8 |
| Polygamy | 89 | 23.2 |
| YEARS IN MARRIAGE | ||
| 1 | 18 | 4.7 |
| 2 | 38 | 9.9 |
| 3 | 54 | 14.1 |
| 4 | 68 | 17.8 |
| 5 | 89 | 23.2 |
| 6+ | 116 | 30.3 |
The relationship between risk factors and semen parameters, independent t-test, and one-way ANOVA were used to test for significance between the two groups. The mean SD was also determined as seen from the Table 2a below. There was no significant relationship recorded among those who smoke, consume alcohol, infection, and drug use (p > 0.05). However, a significant result was recorded between fertility, pH, and viscosity, as well as diagnosed infections, viscosity, and liquefaction respectively with mean SD of 1.14±0.35 and 1.25±0.43; P = 0.02 (P < 0.05).2.05±1.75 and 1.64±1.38; P= 0.03, 1.10±0.30 and 1.19±0.39; P= 0.06, 1.00±0.00, 1.25±0.53, 1.40±0.63, 1.00±0.00, 1.83±0.41, 1.50±0.71, 1.06±0,00, 1.00±0.00, 1.00±0.00; P=0.006, 1.25±0.50, 1.90±1.63, 1.85±1.65, 1.00±0.00, 4.67±1.20, 1.00±0.00, 1.29±0.49, 1.50±0.71and 3.50±2.89; P=0.004(p > 0.05) respectively.
Table 2a: Distribution of the risk factors in relation to semen parameters among the study population
| Risk Factor | n | Sperm Count | Volume | Motility | Morphology | pH | Liquefaction | Viscosity |
|---|---|---|---|---|---|---|---|---|
| Smoking | ||||||||
| Yes | 38 | 4.68 ± 2.26 | 2.66 ± 0.71 | 1.76 ± 0.94 | 1.24 ± 0.43 | 1.13 ± 0.34 | 1.39 ± 0.68 | 1.71 ± 1.45 |
| No | 345 | 4.23 ± 2.22 | 2.76 ± 0.59 | 1.76 ± 0.93 | 1.30 ± 0.46 | 1.18 ± 0.38 | 1.28 ± 0.53 | 1.96 ± 0.69 |
| P-value | 0.24 | 0.32 | 0.98 | 0.41 | 0.49 | 0.20 | 0.33 | |
| Alcohol Consumption | ||||||||
| Yes | 79 | 4.63 ± 2.09 | 2.81 ± 0.48 | 1.75 ± 0.94 | 1.27 ± 0.45 | 1.10 ± 0.30 | 1.30 ± 0.63 | 1.80 ± 1.48 |
| No | 304 | 4.19 ± 2.25 | 2.73 ± 0.62 | 1.76 ± 0.92 | 1.30 ± 0.46 | 1.19 ± 0.39 | 1.28 ± 0.53 | 1.97 ± 1.71 |
| P-value | 0.11 | 0.31 | 0.89 | 0.52 | 0.06 | 0.79 | 0.38 | |
| Drug Use | ||||||||
| Normal | 369 | 4.28 ± 2.24 | 2.75 ± 0.59 | 1.75 ± 0.92 | 1.30 ± 0.46 | 1.18 ± 0.38 | 1.28 ± 0.54 | 1.91 ± 1.64 |
| Hard | 12 | 4.08 ± 1.88 | 2.67 ± 0.78 | 1.83 ± 1.03 | 1.33 ± 0.49 | 1.08 ± 0.29 | 1.42 ± 0.67 | 2.25 ± 1.26 |
| Snuff | 2 | 5.50 ± 0.71 | 3.00 ± 0.00 | 3.00 ± 0.00 | 1.00 ± 0.00 | 1.00 ± 0.00 | 1.50 ± 0.71 | 3.50 ± 1.54 |
| P-value | 0.71 | 0.74 | 0.16 | 0.63 | 0.57 | 0.61 | 0.32 | |
| Fertility Type | ||||||||
| Primary | 276 | 4.28 ± 2.19 | 2.74 ± 0.60 | 1.74 ± 0.92 | 1.31 ± 0.46 | 1.14 ± 0.35 | 1.29 ± 0.55 | 2.05 ± 1.75 |
| Secondary | 107 | 4.28 ± 2.31 | 2.77 ± 0.58 | 1.82 ± 0.95 | 1.25 ± 0.44 | 1.24 ± 0.43 | 1.29 ± 0.55 | 1.64 ± 1.38 |
| P-value | 1.00 | 0.73 | 0.42 | 0.26 | 0.02 | 0.96 | 0.03 |
Table 2b: Distribution of the risk factors in relation to semen parameters among the study population
| Risk Factor | n | Sperm Count | Volume | Motility | Morphology | pH | Liquefaction | Viscosity |
|---|---|---|---|---|---|---|---|---|
| Past Infection | ||||||||
| Yes | 226 | 4.42 ± 2.17 | 2.75 ± 0.60 | 1.79 ± 0.93 | 1.30 ± 0.46 | 1.16 ± 0.37 | 1.31 ± 0.55 | 1.95 ± 1.60 |
| No | 157 | 4.07 ± 2.28 | 2.75 ± 0.59 | 1.71 ± 0.92 | 1.29 ± 0.46 | 1.19 ± 0.39 | 1.26 ± 0.55 | 1.91 ± 1.67 |
| P-value | 0.13 | 0.95 | 0.41 | 0.94 | 0.43 | 0.44 | 0.80 | |
| Diagnosis | ||||||||
| Yes | 4 | 4.00 ± 2.45 | 2.50 ± 0.58 | 1.75 ± 0.96 | 1.00 ± 0.00 | 1.00 ± 0.00 | 1.00 ± 0.00 | 1.25 ± 0.50 |
| No | 303 | 4.23 ± 2.23 | 2.75 ± 0.58 | 1.75 ± 0.92 | 1.28 ± 0.45 | 1.18 ± 0.38 | 1.25 ± 0.53 | 1.90 ± 1.60 |
| Staph. | 53 | 4.49 ± 2.16 | 2.72 ± 0.66 | 1.66 ± 0.94 | 1.42 ± 0.50 | 1.13 ± 0.34 | 1.40 ± 0.63 | 1.85 ± 1.62 |
| Stap./E. coli | 2 | 4.50 ± 3.54 | 3.00 ± 0.00 | 1.00 ± 0.00 | 1.50 ± 0.71 | 1.00 ± 0.00 | 1.00 ± 0.00 | 1.00 ± 0.00 |
| Chlamydia | 6 | 2.67 ± 2.25 | 2.33 ± 1.03 | 2.67 ± 0.82 | 1.33 ± 0.52 | 1.50 ± 0.55 | 1.83 ± 0.41 | 4.67 ± 1.20 |
| Gonorrhea | 2 | 6.00 ± 1.41 | 3.00 ± 0.00 | 2.00 ± 1.41 | 1.50 ± 0.71 | 1.50 ± 0.71 | 2.50 ± 0.70 | 1.00 ± 0.00 |
| Gono/Staph. | 7 | 5.29 ± 1.50 | 3.00 ± 0.00 | 2.00 ± 1.00 | 1.00 ± 0.00 | 1.14 ± 0.39 | 1.29 ± 0.49 | 1.57 ± 1.13 |
| Syph/Staph. | 2 | 7.00 ± 0.00 | 3.00 ± 0.00 | 1.50 ± 0.71 | 1.50 ± 0.71 | 1.00 ± 0.00 | 1.50 ± 0.71 | 1.50 ± 0.71 |
| Chla/Staph. | 4 | 3.75 ± 2.06 | 3.00 ± 0.00 | 2.50 ± 1.00 | 1.50 ± 0.58 | 1.00 ± 0.00 | 1.25 ± 0.50 | 3.50 ± 2.89 |
| P-value | 0.28 | 0.55 | 0.20 | 0.21 | 0.33 | 0.006 | 0.004 |
Twenty-eight (28) samples were found with Chlamydia trachomatis given a percentage of 7.3, while Twenty-one (21) samples were detected with Neisseria gonorrheae, with the least percentage of 5.5 Tables 3.
Table 3: Frequency of Chlamydia trachomatis and Neisseria gonorrhoeae among the study population
| Parameter | no | Frequency | Percentage (% ) |
|---|---|---|---|
| Chlamydia trachomatis | 383 | 28 | 7.3 |
| Neisseria gonorrhoeae | 383 | 21 | 5.5 |
Primary infertility has the highest number of both Chlamydia trachomatis 20 (71.4) and Neisseria gonorrheae 13 (61.9) compared with those with secondary infertility with 8(28.6) for C. trachomatis and 8(38.10 for N. gonorrheae.
Table 4: Frequency of Chlamydia trachomatis and Neisseria gonorrheae primary and secondary infertile population
| Infertility Status | No. Examined | Chlamydia trachomatisn (%) | Neisseria gonorrhoeaen (%) | χ² | df | p-value |
|---|---|---|---|---|---|---|
| Primary Fertility | 277 | 20 (71.4%) | 13 (61.9%) | 0.012 | 1 | 0.91 |
| Secondary Fertility | 106 | 8 (28.6%) | 8 (38.1%) | 1.205 | 1 | 0.27 |
p > 0.05 – not statistically significant
Plate 1: A representative of Agarose gel electrophoresis patterns showing PCR amplification products from Chlamydia trachomatis isolates. L: A molecular weight size marker (100bp+). Lane 1-3: positive for omp1 gene as indicated by 800 base pairs. NC: negative control
Plate 2: A representative of Agarose gel electrophoresis patterns showing PCR amplification products from Neisseria gonorrhoeae isolates. L: A molecular weight size marker (100bp+). PC: positive control. NC: negative control. Lane 1-4: positive for proA gene as indicated by 295 base pairs.
Infertility is a common reproductive public health problem in our country and the world at large. Therefore, the need to find out the male partner’s impact on the infertility challenge in our society cannot be over-emphasized. The clinical subjective semen analysis still plays a critical role in the diagnosis and management of male infertility. However, précised diagnosis of infertility rarely depends on semen analysis results. There is a significance interrelationship between the semen parameters of fertile and infertile men. Hence, there is a need to assess the sperm nuclear integrity in our society.
Male urinary tract infection (UTI) has caused a lot of discussion in relation to male infertility, and it is believed to contribute to approximately 15% of male infertility (Abursarah et al., 2013; Qing et al., 2017; Bitet et al., 2021, Ahmadi et al., 2023). Chlamydia trachomatis and Neisseria gonorrhoeae are the most prevalent and asymptomatic urinary tract bacterial pathogens globally studied in most literatures. The clinical asymptomatic nature of these pathogens makes identifying the infection easily and equally difficult, the chances of contamination with other organisms and culturing more complex (Qing et al., 2017; Duvuru et al., 2022; Mohammed et al., 2022).
Our study detected N. gonorrhoeae and C. trachomatis infections in 7.3% and 5.5%, respectively, out of the 383 infertile male subjects. This outcome is similar to the study outcome of 6.5% for N. gonorrhoeae and C. trachomatis varied between 0.4 -42.3% by Qing et al. and Abursarah et al. (Abursarah et al., 2013; Qing et al., 2017). Other findings within Nigeria reveal some variation in prevalence from place to place, such as N. gonorrhoeae 1.4% in Lagos, 1.3% in Ilorin, 5.2% in Calabar, 3.2% in Abuja, 5.0% in Port Harcourt and 16.3% in Kaduna, 2.0% in Oweri (Nsofor and Eletuoh, 2017, Mbah et al., 2022). In another study in 2014 by Nwankwo and Sadiq (2014), Lagos showed a high prevalence rate of 51% and 18.2% with a wide margin, Jos 51.6%, South Eastern Nigeria 40.7%, Zaria and Kano in Northwestern Nigeria 38.3% and 18.4% respectively. Furthermore, 44.4% was reported in Zaria, 80.0% in Ibadan, and 13.3% in Benin City (Nwankwo and Sadiq, 2014; Keshinro et al., 2016). Some African countries have a prevalence of 16.3% in Hawasa Ethiopia Majnooni et al., (2022), 2.7% in Tunisia by Hammami et al., (2014). Global prevalence is 2.2%, with the highest prevalence in Africa at 5.0% (Chemaitelly et al., 2021). Generally speaking, there is a variation in the spread of N. gonorrhoeae among infertile subjects.
On the other hand, C. trachomatis also has a variable prevalence of 9.6% in Kano, Nigeria (Nwankwo et al., 2014), Delta 46.5%, South East 51%, Jos 51.6%, South West 41%, Northern Nigeria 38.3% and Benin City 13.3% (Bamikole et al., 2020). Other part of the world, Africa inclusive, had 10.0% in Ethiopia (Ahmadi et al., 2023), 15.3% in Iran and in Babol, Iran, 11.6%, and Tunisia 43.3% (Qing et al., 2017, Bamikole et al., 2020), Brazil .12.3%, USA 5%, and Europe 1.7 17% (Bamikole et al., 2020). Variation in prevalence could result from sample size and detection methods (Mawak et al., 2011; Nwankwo and Sadiq, 2014).
The differences in prevalence reports may be due to differences in laboratory methods, geographical and cultural characteristics of the states and countries, and equally important is variation in sample size (Ahmadi et al., 2023). The implications of urinary tract infections on male infertility are still under study, including the effect on semen parameters fertility capacity in the area of aided reproduction. Several studies outcomes fail to address the possible correlation between N. gonorrhoeae and C. trachomatis infections and semen paraters (Sallami et al., 2014; Qing et al., 2017; Duvuru et al., 2022, Mohammed and Abdul Mutalab, 2022), including this present study. While many others reported a decrease in semen volume, sperm count, morphology, and motility with C. trachomatis and N. gonorrhoeae infections but semen quality deteriorations probably caused by C .trachomatis and N. gonorrhoeae were not fully cleared with some reported a detrimental effect of bacteriological pathogens on male fertility power as others reported changes in semen parameters (Qing et al., 2017, Duvuru et al., 2022). Hence, the difference in the criteria for male infertility diagnosis and bacterial pathogens detection techniques in different studies may contribute to the reports' wide variation.
Using PCR to detect C. trachomatis and N. gonorrhoeae provides a sensitive, faster and accurate technique to detect the presence or absence of these urinary tract and symptomless pathogens in the semen. The result of this current study reveals that C. trachomatic and N. gonorrhoeae infections probably spread in infertile males and could cause a decrease in sperm DNA integrity, motility, morphology and count.
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