The Journal of Clinical Medicine (ISSN 2995-6315) The Impact of Antibiotic Use on Puberty. Dr.Leyla Kara, MD Corresponding author Dr.Leyla Kara, MD, Kayseri City Training and Research Hospital, Pediatric Endocrinology Kayseri , Turkey. Telephone: +90 533 624 22 70, Email : leyladumann@gmail.com orchid ID : 0000-0002-5261-9222 Received Date : October 02, 2024 Accepted Date : October 03, 2024 Published Date : November 02, 2024 ABSTRACT Introduction: Antibiotic exposures in early life may affect weight by altering the gut microbiota, potentially increasing the likelihood of early pubertal maturation. Objective: To examine whether repeated antibiotic exposure by age eight is associated with early pubertal maturation. Design, Setting, and Participants: This research is a retrospective study involving 122 children. There were sixty-nine cases with early pubertal development (pubertal group), in which fourteen cases (20%) were started with leuprolide acetate. There were fifty-three cases without pubertal development (control group). The antibiotics prescriptions were evaluated retrospectively in both groups using electronic health records. The first age antibiotic prescription, the type of antibiotics, and the total number of antibiotic prescriptions were recorded. Results: There were no significant differences between the groups regarding the first-age antibiotic prescription, the type of antibiotics, and the total number of antibiotic prescriptions. There was no correlation between the number of antibiotics prescriptions, the first-age antibiotic prescription, and levels of LH, FSH, E2, and the difference between bone age and chronological age. Conclusion: Although environmental antibiotic exposure may trigger precocious. puberty, the use of antibiotics prescribed for treatment may not affect precocious puberty. Keywords: Antibiotics, Early Puberty, Bone Age, Bone Age- Chronological Age Difference (ΔKY-TY). INTRODUCTION Antibiotics are the most commonly prescribed drugs in the pediatric age group, reducing morbidity and mortality associated with bacterial infections. Antibiotic use has increased, and bacterial resistance and microbiota dysbiosis have become substantial concerns [1]. Precocious puberty in girls is characterized by breast development and pubic hair growth before the age of eight, with idiopathic central precocious puberty being the most common type. In these cases, the hypothalamic-pituitary- gonadal (HPG) axis has activated prematurely [2]. Although the exact reason for the early activation of the HPG axis is not clearly understood, a complex interaction of metabolic, nutritional, and hormonal factors resulted [3]. The human microbiota is impressed by diet and antibiotics. The metabolites of gut microbiota can impact the secretion of sex hormones through pathways involving the immune system, chronic inflammation, and the gut-brain axis, which are some neuroendocrine axis [4]. The girls with precocious puberty have an overproduction of bacterial species in their gut microbiota that produce metabolites capable of activating the HPG axis [5]. Antibiotic therapy reduces the diversity of gut microbiota species, leading to a condition known as dysbiosis, which causes antibiotic resistance and diarrhoea in the short term and obesity, asthma, and inflammatory bowel disease in the long term. However, there were no studies suggesting that antibiotic use triggers precocious puberty. In our country, the use of antibiotics and antibiotic prescriptions is frequent. The incidence of precocious puberty is also increasing [6]. While the role of genetic and environmental factors is partially known, the impact of antibiotics used for treatment purposes is not clear in pubertal maturation. This study aimed to evaluate the contribution of antibiotic use to the development of early pubertal symptoms. Additionally, we sought to answer a common question asked by parents in pediatric endocrinology practice: Is there a relationship between the early onset of pubertal symptoms and the use of multiple antibiotics at an early age? METHODS A total of 122 girls aged 6 to 8 years attended the Pediatric Endocrinology Clinic at Kayseri City Hospital. These girls underwent an examination by a pediatric endocrinologist. Among them, 69 girls exhibited Tanner stage ≥ 2 breast Research Article 1www.directivepublications.org

The Journal of Clinical Medicine (ISSN 2995-6315) development (the pubertal group), while 53 girls had no breast development (the control group). Medical records were retrospectively reviewed. The study protocol was approved by the Kayseri City Hospital Clinical Research Ethics Committee under reference number 949 and conducted by the Helsinki Declaration. Exclusion criteria encompassed malnutrition (defined as a body mass index below -2 SD), chronic illnesses necessitating regular medication, organic etiologies of precocious puberty, and male gender. Exclusion criteria encompassed malnutrition (defined as a body mass index below -2 SD), chronic illnesses necessitating regular medication, organic etiologies of precocious puberty, and male gender.” Anthropometric measurements (weight, height, body mass index, and standard deviation scores [SD]) and pubertal stages were analyzed using medical records [7]. Additionally, factors such as birth weight, gestational age, duration of breastfeeding, maternal height, paternal height, age at first maternal menarche, and maternal BMI were evaluated. In patients with breast development, bone age, the difference between bone age and chronological age, pelvic ultrasound findings, and levels of luteinizing hormone (LH), follicle- stimulating hormone (FSH), and estradiol (E2) were recorded. For both groups, the age at first antibiotic prescription, the number and types of antibiotics prescribed, and confirmation of their use were also recorded. Anthropometric measurements were conducted in the morning under fasting conditions, with the child barefoot and without outer garments. Stature was assessed using a Harpenden stadiometer (Holstein Limited, Crymych, Dyfed, U.K.), which offers a precision of 0.1 cm. Concurrently, body mass was determined using a SECA scale (GmbH & Co. KG, Hamburg, Germany) with an accuracy of 0.1 kg.” The pubertal staging was meticulously conducted by the pediatric endocrinologist employing the Marshall and Tanner method [8]. Bone age was determined through left wrist radiography by the Greulich and Pyle atlas [9]. In patients presenting with breast development, those exhibiting an estradiol level exceeding 9 pg/ml, bone age surpassing chronological age, and a GnRH stimulation response (1h LH ICMA ≥ 5 mIU/ml) were diagnosed with central precocious puberty. Gonadotropin-releasing hormone therapy was initiated if pelvic ultrasonography revealed a uterine height exceeding 35 mm and an ovarian long diameter greater than 20 mm [10] [11]. Statistical Analysis Data were analyzed utilizing IBM SPSS Statistics version 24.0. Descriptive statistics encompass mean values, standard deviations, frequencies, and percentages. Parametric data comparisons between groups were performed using Student’s t-test. Non-parametric data were analyzed using the Mann- Whitney U test. The Pearson Chi-Square test was employed for the assessment of categorical variables. Relationships between variables were examined through Pearson or Spearman correlation analyses. Statistical significance was set at a p-value of <0.05. A power analysis conducted with G*Power software established that, with a confidence level of 95% (1-α), a test power of 81% (1-β), and an effect size of 0.50 (medium effect size according to Cohen’s criteria), a sample size of 52 per group was required for independent sample t-tests.” RESULTS The clinical, laboratory and radiological characteristics of the cases are delineated in Table 1. Amoxicillin-clavulanic acid emerged as the most frequently prescribed antibiotic. Antibiotics were administered to all cases, with a mean prescription rate of 20.4 ± 12.9 per case. The pubertal group exhibited significantly higher values in terms of weight, weight standard deviation (SD), body mass index (BMI), BMI SD, the difference between bone age and chronological age (ΔKY-TY), and luteinizing hormone (LH) levels (p < 0.05). There were no discernible differences between the groups concerning the age at first antibiotic prescription, the total number of antibiotics prescribed, or the number of cases receiving antibiotics within the first six months, first year, or two years of life. Furthermore, the types and quantities of antibiotics prescribed were no significant differences between the groups (Table 2). Adjustments for age at first antibiotic prescription, the number of antibiotics prescribed, and BMI revealed no statistically significant correlations (Table 3). Fourteen cases (11%) were diagnosed with idiopathic central precocious puberty and were initiated on leuprolide acetate treatment. No significant differences in antibiotic prescription data were observed between those who received leuprolide acetate and those who did not (Table 4). Research Article 2www.directivepublications.org

The Journal of Clinical Medicine (ISSN 2995-6315) Table 1. Clinical Laboratory and Radiological Data of Subjects. Pubertal (n=69) Control (n=53) p Age, Years * 7.44 (6-7.99) 7.39 (6-7.99) 0.395 Duration of Breastfeeding, Months * 18 (0-36) 12.5 (0-30) 0.718 Age at Mother’s First Menstruation, Years *13 (10-140) 12 (9-16) 0.167 Maternal BMI, kg/m² 27.8 ±5.5 29.2 ±5.94 0.358 Target Height, cm 160.3 ±5.52 161.2 ±5.43 0.549 Target Height, SD -0.46 ±0.94 -0.30 ±0.91 0.562 Weight, kg * 30 (15.4-44.8) 25 (15.1-51.15) 0.015 Weight, SD * 1.40 (-2.15-3.79) 0.44 (-2.54-4.90) 0.032 Height, cm 126.1 ±6.9 124.2±7.9 0.162 Height, SD 0.59 ±1.12 0.34 ±1.28 0.250 BMI, kg/m² * 18.56 (13.2-26.3) 16 (13.17-30.27) 0.030 BMI, SD 0.9 ±1.27 0.41 ±1.31 0.039 Basal FSH, mIU/L * 1.53 (0.33-6.57) 1.22 (0.1-4.38) 0.158 Basal LH, mIU/L 0.3 (0.1-3.4) 0.3 (0-0.5) 0.031 Bazal E2, pg/ml* 5 (5-42) 5 (0-26.3) 0.911 Bone Age, years* 8 (5.8-11) 7.8 (4-8.8) 0.053 ΔBA-CA, years* 0.61 (-1.55-3.07) 0.4 (-2.62-1.27) 0.021 * Non-parametric Test Abbreviations:BMI: Body Mass Index; SD: Standard Deviation; FSH: Follicle Stimulating Hormone; LH: Luteinizing Hormone; E2: Estradiol; BA: Bone Age; CA: Calendar Age Table 2. Antibiotic Usage Data of Groups.

Pubertal (n=69)Kontrol (n=53) p Timing of Exposure to Any Antibiotics Age at Start of Antibiotic Use, Years * 0.73 (0.08-5.64)0.72 (0.2-6.15)0.943 Number of Antibiotic Courses per Case * 17 (2-53) 17 (3-78) 0.896 % Starting Antibiotics Before 6 Months ** 21 (30) 13 (24) 0.471 % Starting Antibiotics Before 1 Year ** 29 (42) 23 (43) 0.880 % Starting Antibiotics Before 2 Years ** 59 (85) 45 (84) 0.926 Type of Antibiotics Penicillins (%)** None - - 0,740 1-3 7 (10.3) 7 (13) 4-6 12 (17.3) 11 (20.7) >6 50 (72.4) 35 (66) Macrolides(%)** None 10 (14.4) 10 (18.9) 0.876 1-3 37 (53.6) 25 (47.1) 4-6 13 (18.8) 10 (18.9) Research Article 3www.directivepublications.org

The Journal of Clinical Medicine (ISSN 2995-6315) >6 9 (13.2) 8 (15.1) Cephalosporins (%)** None 11 (16) 6 (11.3) 0.162 1-3 27 (39) 21(39.7) 4-6 14 (20.4) 19 (35.8) >6 17 (24.6) 7 (13.2) Metronidazole (%)** None 32 (46.3) 29 (54.7) 0.580 1-3 31(44.9) 19 (35.9) 4-6 5 (7.3) 5 (9.4) >6 1 (1.5) - Trimethoprim sulfometakszaol (%)** None 54 (78.3) 46 (86.8) 0.304 1-3 13 (18.8) 7 (13.2 4-6 2 (2.9) - >6 - - *Non-parametric test ** Chi-square test Tablo 3. Correlation between the age at first antibiotic prescription and the number of antibiotics prescribed

Age at first antibiotic prescription, years Number of antibiotics prescribed, n LH, mIU /L r=0.013 p=0.946 r=-0,177 p=0.544 FSH, mIU /L r=0.146 p=0.451 r=-0.138 p=0.475 E2, pg/ml r=0.08 p=0.968 r=0.040 p=0.835 ΔBA-CA, years* r=0.137 p=0.479 r=-0.307 p=0.105 Number of antibiotics prescribed, nr=-0.170 p=0.378 - * Adjusted for BMI and age Research Article 4www.directivepublications.org

The Journal of Clinical Medicine (ISSN 2995-6315) Table 4. Antibiotic data of patients started on leuprolide acetate

Leuprolide acetate initiated (n=14) Leuprolide acetate not initiated (n=55) p Number of antibiotic prescriptions, n 16.5 (5-53) 18 (2-50) 0.858 Age at first antibiotic prescription, years0.79 (0.12-3.97) 0.72 (0.08-5.64) 0.654 Percentage of cases prescribed antibiotics before the age of one, % 9 (64) 31 (56) 0.592 Percentage of cases prescribed antibiotics before the age of two, % 12 (85) 47 (85) 0.980 Research Article 5www.directivepublications.org DISCUSSION This study evaluates the impact of antibiotic use for treating upper respiratory infections, urinary tract infections, and similar conditions on the early development of pubertal signs. We assessed the age of the first antibiotic prescription, the total number of antibiotics prescribed, and the types of antibiotics used in girls with and without breast development before the age of eight. No statistically significant differences were found between these two groups. The prevalence of early puberty in children is showing a marked and rapid increase [12]. Genetic factors, rising obesity rates, and endocrine disruptors are contributing to the early onset of pubertal signs. The effects of antibiotics on early pubertal development remain contentious [13] [14] [15] [16]. Between 2014 and 2017, a program was implemented in Turkey that banned over-the-counter antibiotic use in 2015 and initiated public awareness campaigns to reduce outpatient antibiotic use. Consequently, daily antibiotic usage decreased from 42.2 daily doses per 1,000 patients in 2011, to 40.4 daily doses per 1,000 patients in 2014, and further to 35.25 daily doses per 1,000 patients in 2017 [17]. In our study, an average of 2.8 antibiotic prescriptions per patient per year was recorded (2.7 prescriptions/year for the pubertal group and 2.9 prescriptions/year for the non- pubertal group). Early puberty is a complex process influenced by obesity and endocrine disruptors. Antibiotic use before the age of four and during pregnancy has been reported to increase the risk of obesity[18]. Li et al.’s study did not associate antibiotic use with obesity but argued that infections during infancy contribute to increased obesity risk [19]. Despite the pubertal group being more obese, no differences in antibiotic use or types of antibiotics were found compared to the non-pubertal group. The microbiota-gut-brain axis regulates intestinal neuronal, endocrine, and immunological pathways, affecting the central nervous system. Huang et al. demonstrated higher levels of Bifidobacterium, Balutia, and Streptococcus species, as well as tetracycline biosynthesis pathway activation, in girls with precocious puberty, suggesting that antibiotic exposure could be a factor [14]. Recent studies have shown that gut microbiota influences sex hormones and affects the initiation of the HPG axis. In rat models of obesity-related early puberty, decreased production of short-chain fatty acids in the gut microbiota was observed, which could be mitigated by supplementing with short-chain fatty acids, thus delaying the development of the HPG axis [20]. Antibiotics are widely used in medical treatment as well as in agriculture [21]. Residual antibiotics are commonly found in environmental and animal-derived foods, accumulating in humans through the food chain. Elevated levels of fluoroquinolones and tetracyclines have been detected in the urine of children with precocious puberty, indicating exposure through water and food. However, no patients in our study were found to use tetracyclines or fluoroquinolones [13]. In our study, after adjusting for age and BMI data, no statistically significant correlations were found between the number of antibiotics prescribed, the age at first antibiotic prescription, and the onset age of pubertal signs. For true precocious puberty cases, treatment with gonadotropin agonists is administered. In our patient cohort, the rate of initiating treatment at the first examination was 25%, which is consistent with similar studies. Pubertal disorders are assessed within a spectrum, categorized as true precocious puberty or telarche variants. Telarche variants are characterized by ΔKY-TY of less than one year, with no Tanner stage progression within six months [22]. In our cohort, no treatment was administered to this group at the time of presentation. Follow-up is ongoing, and prospective evaluation could be the subject of future research. No significant differences in the number of antibiotic prescriptions, age at first antibiotic prescription, or the number of cases receiving antibiotics before one year or two years of age were found between the leuprolide acetate- treated group and those who did not receive this treatment. The most significant confounding factor in this study is

The Journal of Clinical Medicine (ISSN 2995-6315) infections, which are known to impair the immune system and contribute to conditions such as asthma, type 1 diabetes mellitus, and obesity [23]. The impact of infections on the early onset of pubertal signs was not detected in this study. Limitations of the study include its retrospective and cross- sectional nature, which precludes knowledge of the duration of antibiotic use. While cohort studies on antibiotic exposure and obesity are being conducted, similar studies for puberty are challenging. The limited number of cases is due to the need for concurrent antibiotic use information and pubertal examination. Although it was considered to analyze antibiotic levels in urine samples, budget constraints prevented this. Another limitation is that only cases from the Pediatric Endocrinology Clinic were assessed. The control group may also experience the onset of pubertal signs during follow-up. This study is cross-sectional. CONCLUSION Various genetic and environmental factors influence the onset of pubertal signs. Given its association with hormone secretion and obesity, gut microbiota could trigger precocious puberty. Although larger-scale studies have noted antibiotic exposure in cases of precocious puberty, the role of antibiotics prescribed for treatment purposes in triggering pubertal signs remains unclear. Our study found no effect of treatment- related antibiotic use on the early onset of pubertal signs. REFERENCES 1. Karakan T, Ozkul C, Küpeli Akkol E, Bilici S, Sobarzo- Sánchez E, Capasso R. Gut-Brain-Microbiota Axis: Antibiotics and Functional Gastrointestinal Disorders. Nutrients. 2021 Jan 27;13(2):389.

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