The significant role of IL-15, IL-22, IL-37, and caspase 9 in polycystic ovary syndrome: A case-control study in a sample of Iraqi women.

Noor A. Mohammed: Writing – original draft, Methodology. Ghassan M. Sulaiman: Supervision, Project administration, Conceptualization. Hazima M. Alabassi: Writing – original draft, Supervision, Methodology. Khalil A.A. Khalil: Writing – review & editing, Conceptualization. Elsadig M. Ahmed: Writing – review & editing, Conceptualization.

The experimental animal protocol was approved by the University of Technology and Baghdad Health Directorate (Reference No. 360, Nov 31, 2022).

Not applicable.

This research received no specific grant from any funding agency in the public, commercial, or not‐for‐profit.

The sample size of PCOS patients ( n  = 90) and controls ( n  = 48) was tested using the G*power software. The power of the sample size was estimated under a 0.05 two-tailed alpha error probability and a 0.5 d effect size and was 0.95. The statistically acceptable power of the sample size is 0.80, and this may validate the current sample size of patients and controls. Results presented in Table 2 show that PCOS and control groups had mean ages of 28.8 ± 5.9 and 28.0 ± 5.6 years, ranging from 22 to 45 years. Age differences between study groups were insignificant (p = 0.064); mean BMI differences were highly statistically significant at p ≤ 0.001 between PCOS and control groups, respectively. The PCOS group had a greater mean waist circumference (p = 0.001) than the control group. Table 2 Characteristics at baseline in PCOS patients compared to controls. PCOS Controls P value No % No % Age (years) 35 years 21 23.3 8 16.0 Mean ± SD (Range) 28.8 ± 5.9 (18–39) 28.0 ± 5.6 (19–35) 0.064 BMI (Kg/m2) Underweight (30) 15 42.9 2 13.3 BMI: Mean ± SD (Range) 28.90 ± 5.50 (15.57–38.22) 23.26 ± 4.23 (17.80–30.33) 0.001 ** Weight (Kg) Mean ± SD (Range) 72.64 ± 14.05 (45–115) 60.54 ± 8.03 (45–76) 0.0001 *** Height (cm) Mean ± SD (Range) 1.59 ± 0.07 (1.50–1.73) 1.62 ± 0.05 (1.53–1.70) 0.152 Waist circumference (cm) Underweight 13 14.4 3 6.0 0.066 Normal (80–88) 27 30.0 24 48.0 Obese 50 55.6 23 26.0 Mean ± SD (Range) 95.45 ± 15.61 (60–124) 87.01 ± 8.88 (58.42–96.52) 0.001 ** Note: ** and *** were significant at P ≤ 0.01 and 0.0001, respectively. There is a statistically significant difference between the two independent means. Characteristics at baseline in PCOS patients compared to controls. Note: ** and *** were significant at P ≤ 0.01 and 0.0001, respectively. There is a statistically significant difference between the two independent means. As illustrated in Table 3 , the immunological parameters in PCOS patients and controls showed significant differences. IL-15 levels in PCOS patients were significantly higher (48.325 ± 16.586 pg/mL) compared to controls (34.373 ± 6.886 pg/mL) with a p-value of 0.0001. Similarly, IL-22 levels were notably elevated in PCOS patients (183.86 ± 51.384 pg/mL) compared to controls (77.912 ± 35.966 pg/mL), with a p-value of 0.0001. In contrast, IL-37 levels were significantly lower in PCOS patients (39.223 ± 13.051 pg/mL) compared to controls (89.301 ± 28.777 pg/mL), also with a P ≤ 0.0001. These results demonstrate statistically significant variations in immune parameters between the two groups. Table 3 The details of the results serum level of immunological parameters in PCOS and control. Immunological parameters PCOS Patients Controls IL-15 (pg/mL) 48.325 ± 16.586 # 34.373 ± 6.886 IL-22 (pg/mL) 183.86 ± 51.384 # 77.912 ± 35.966 IL-37 (pg/mL) 39.223 ± 13.051 # 89.301 ± 28.777 # : P value is significant at ≤0.0001 level. The details of the results serum level of immunological parameters in PCOS and control. # : P value is significant at ≤0.0001 level. Table 4 demonstrates the relationship between IL-15, IL-22, and IL-37 and the main features of PCOS patients and control groups, including age, BMI, and waist circumference. To reveal the statistically significant relationship between these parameters and the interleukins, further subdivisions were made as follows: Age was divided into five categories (<20, 20–24, 25–29, 30–34, and ≥35 years); body mass index (BMI) was divided into four categories (underweight, normal, overweight, and obese); and waist circumference was divided into three categories (underweight, normal, and obese). The results regarding the relationship between age, BMI, waist circumference, and IL-15 were as follows: Within the age range of 20–24 years, a highly statistically significant difference with a probability p of 0.0001 was observed in the mean IL-15, with a higher value in the PCOS group compared to the control group (47.29 ± 14.16 vs. 32.61 ± 5.53 pg/mL) for PCOS and control groups, respectively. Additionally, for the age group 25–29, a statistically significant difference was observed with a higher mean in PCOS compared to the control group (54.53 ± 22.32 vs. 33.08 ± 6.72 pg/mL) at p  ≤ 0.003. Similarly, for the age group 30–34, a statistically significant difference was observed with a higher mean in PCOS compared to the control group (48.12 ± 9.31 vs. 37.63 ± 7.44 pg/mL) at p  ≤ 0.009. Finally, there were no statistically significant differences observed in the age groups of <20 and ≥35 in the mean of IL-15 when comparing both PCOS and control groups. On the other hand, underweight individuals were the only subdivision of the BMI category that showed a statistically significant difference, with a lower IL-15 mean in the PCOS group compared to the control group (32.11 vs. 46.96 pg/mL) for control and PCOS, respectively, at p ≤ 0.015 . However, no statistically significant differences were observed in normal, overweight, and obese subdivisions when the PCOS group was compared to the control group. When considering waist circumference, statistically significant differences were observed in the underweight, normal, and obese categories, with a higher mean of IL-15 in the PCOS group compared to the control group. It was found that the underweight group had 53.39 ± 12.97 pg/mL compared to 35.29 ± 9.19 pg/mL for PCOS and control groups ( p  ≤ 0.047), the normal group had 53.07 ± 21.27 pg/mL compared to 33.55 ± 7.02 pg/mL for PCOS and control groups (p ≤ 0.0001), and the obese group had 44.45 ± 13.56 pg/mL compared to 35.04 ± 6.7 pg/mL compared to the control groups ( p  ≤ 0.002). The results of the relationship between age, BMI, waist circumference, and IL-22 were as follows: within the age range of 20–24 years, a highly statistically significant difference with a probability was observed in the mean IL-22, with a higher value in the PCOS group compared to the control group (183.81 ± 58.12 vs. 84.05 ± 43.46 pg/mL) for the PCOS and control groups at p  ≤ 0.0001. In addition, for the age 25–29 group, there was a highly statistically significant difference, with a higher mean in PCOS when compared to the control group (186.48 ± 56.04 vs. 86.92 ± 43.82 pg/mL) for PCOS and control groups at p  ≤ 0.0001. There was also a very important difference between the age groups of 30 and 34, with a higher mean level of IL-22 in the PCOS group compared to the control group (189.78 ± 51.41 vs. 65.73 ± 11.12 pg/mL, p ≤ 0.0001, respectively). A very big difference was seen in IL-22 levels between the PCOS group of patients and the control group at age 35, with a mean level that was 174.76 ± 40.17 pg/mL compared to 64.99 ± 8.7 pg/mL for the PCOS group and p ≤ 0.0001 for the control group. Also, there were no statistically significant differences observed ( p ≥  0.05) in the age of < 20 years and in the mean of IL-22 when both PCOS and control groups were compared to each other. Also, to see if there were any differences within the age groups, the data was put through more statistical analysis. However, there were no significant differences found between the age groups in the PCOS group or the control group ( p  ≥ 0.05). On the other hand, normal and overweight subgroups were the only subdivisions of the BMI that showed a statistically significant difference with a higher IL-22 mean in the PCOS group when compared to the control group of patients: the normal subgroup (152.08 ± 26.40 vs. 100.97 ± 33.76 pg/mL) for control and PCOS at p  ≤ 0.015, and the overweight subgroup (158.54 ± 32.43 vs. 110.56 ± 41.43 pg/mL) at p  ≤ 0.019; however, no statistically significant differences were observed in underweight or obese subdivisions when the PCOS group was compared to the control group. Waist circumference indicated a statistically significant differences in underweight, normal and obese with higher mean of IL-22 in PCOS when compared to control group for all the waist circumference subgroups: for the underweight (195.23 ± 50.58 vs. 67.18 ± 10.71 pg/mL for PCOS and control groups at p  ≤ 0.0001, for the normal (181.15 ± 51.63 vs. 74.22 ± 36.71 pg/mL) for PCOS and control groups at p  ≤ 0.0001 and finally for the obese (182.37 ± 52.10 vs . 83.16 ± 37.45 pg/mL) for PCOS and control groups at p  ≤ 0.0001. The results of the relationship between age, BMI, waist circumference, and IL-37 were as follows: within the age range of 20–24 years, a highly statistically significant difference with a probability of p ≤ 0.0001 was observed in the mean IL-37, with lower values in the PCOS group compared to the control group (39.03 ± 14.05 vs. 89.72 ± 25.92 pg/mL) for the PCOS and control groups, respectively. In addition, for the age 25–29 group, there was a highly statistically significant difference observed, with a lower mean of IL-37 in PCOS when compared to the control group (39.33 ± 12.40 vs. 89.21 ± 27.50 pg/mL) for PCOS and control groups at p  ≤ 0.0001. Also, in the 30–34 age group, there was a very important difference with a lower mean level of IL-37 in the PCOS group compared to the control group (42.82 ± 12.97 vs. 91.16 ± 36.99 pg/mL for PCOS and control groups at p  ≤ 0.0001). Similar results with a highly statistically significant difference at the age of ≥ 35 were observed in the IL-37 with a lower mean in the PCOS group of patients than the control group. 37.35 ± 13.44 vs. 83.15 ± 33.62 pg/mL for PCOS and control groups, at p  ≤ 0.0001.Also, there were no statistically significant differences observed in the age of < 20 years and in the mean of IL-37 when both PCOS and control groups were compared to each other. Furthermore, to reveal the internal subgroup differences in the age parameter, it was subjected to further statistical analysis; however, no significant differences were observed among the subgroups of age in the PCOS group, and no significant differences were observed among the subgroups of age in the control group. On the other hand, underweight, normal, overweight, and obese subgroups of the MBI show a statistically significant difference with a lower IL-37 mean in the PCOS group when compared to the control group of patients, as follows: for the underweight subgroup (28.9 ± 29.17 vs. 143.90 ± 6.14 pg/mL) for PCOS and control groups at p  ≤ 0.042, and for the normal subgroup (25.51 ± 10.92 vs. 105.54 ± 23.19 pg/mL) for PCOS and control groups at p  ≤ 0.0001, and for the overweight subgroup (41.95 ± 9.17 ± 33.76 vs. 116.25 ± 22.90 pg/mL) for PCOS and control groups at p  ≤ 0.0001. Obese subgroup (35.03 ± 15.50 vs. 117.74 ± 29.44 pg/mL) for PCOS and control groups at p  ≤ 0.0001. Waist circumference indicated statistically significant differences in underweight, normal, and obese with a lower mean IL-37 level in PCOS when compared to the control group for all the waist circumference subgroups: for the underweight (37.67 ± 8.92 vs. 88.78 ± 46.16 pg/mL) for PCOS and control groups at p  ≤ 0.001; for the normal subgroup (42.02 ± 13.18 vs. 89.80 ± 30.16 pg/mL) for PCOS and control groups at p  ≤ 0.0001; and finally for the obese subgroup (38.12 ± 13.84 vs. 88.84 ± 26.44 pg/mL) for PCOS and control groups at p  ≤ 0.0001. As shown in Table 4 , there is no significant difference in IL-37 concentration between the subgroups of PCOS patients according to age, BMI, and waist circumference ( P ≥ 0.722, 0.081, and 0.416, respectively). Moreover, the age, body mass index, and waist circumference of the controls did not significantly alter the IL-37 concentration (P ≥ 0.945, 0.287, and 0.993, respectively). Table 4 The relationship between IL-15, IL-22, IL-37 anthropometric features of PCOS patients and control groups. Mean ± SD Anthropometric features IL-15 IL-22 IL-37 PCOS Control P value PCOS Control P value PCOS Control P value Age (years) < 20 years 27.90 ± 11.81 ns 33.13 ± 5.17 0.624 196.29 ± 30.09 73.47 ± 49.21 0.095 32.41 ± 14.94 101.90 ± 27.24 0.087 20–24 47.29 ± 14.16* 32.61 ± 5.53 0.0001* 183.81 ± 58.12 * 84.05 ± 43.46 0.0001* 39.03 ± 14.05* 89.72 ± 25.92 0.0001* 25–29 54.53 ± 22.32* 33.08 ± 6.72 0.003* 186.48 ± 56.04 86.92 ± 43.82 0.0001* 39.33 ± 12.40* 89.21 ± 27.50 0.0001* 30–34 48.12 ± 9.31* 37.63 ± 7.44 0.009* 189.78 ± 51.41 65.73 ± 11.12 0.0001* 42.82 ± 12.97* 91.16 ± 36.99 0.0001* ≥ 35 years 42.63 ± 9.43 ^ 37.20 ± 9.09 0.173 174.76 ± 40.17 64.99 ± 8.70 0.0001* 37.35 ± 13.44* 83.15 ± 33.62 0.0001* P value 0.040* 0.280 0.906 0.513 0.722 0.945 BMI (Kg/m2) Underweight 32.11* 46.96 ± 0.28 0.015* 141.89 70.65 ± 19.98 0.211 28.92 ± 29.17 143.90 ± 6.14 0.042* Normal 33.86 ± 4.07 41.88 ± 8.11 0.056 152.08 ± 26.40 100.97 ± 33.76 0.015* 25.51 ± 10.92* 105.54 ± 23.19 0.0001* Overweight 39.57 ± 7.95 39.75 ± 7.42 0.966 158.54 ± 32.43* 110.56 ± 41.43 0.019* 41.95 ± 9.17* 116.25 ± 22.90 0.0001* Obese 38.04 ± 3.32 41.95 ± 14.04 0.301 160.03 ± 34.49 119.69 ± 57.18 0.162 35.03 ± 15.50* 117.74 ± 29.44 0.0001* P value 0.181 0.780 0.918 0.589 0.081 0.287 Waist circumference (cm) Underweight 53.39 ± 12.97* 35.92 ± 9.19 0.047* 195.23 ± 50.58* 67.18 ± 10.71 0.001* 37.67 ± 8.92* 88.78 ± 46.16 0.001* Normal 53.07 ± 21.27* 33.55 ± 7.02 0.0001* 181.15 ± 51.63* 74.22 ± 36.71 0.0001* 42.02 ± 13.18* 89.80 ± 30.16 0.0001* Obese 44.45 ± 13.56 *^ 35.04 ± 6.70 0.002* 182.37 ± 52.10* 83.16 ± 37.45 0.0001* 38.12 ± 13.84* 88.84 ± 26.44 0.0001* P value 0.044 ^ 0.710 0.691 0.613 0.416 0.993 *Significant difference between two independent means using Students- t -test at P  ≤ 0.05 level. ^ Significant difference among more than two independent means using ANOVA-test at 0.05 level; ns: non-significant variations. The relationship between IL-15, IL-22, IL-37 anthropometric features of PCOS patients and control groups. *Significant difference between two independent means using Students- t -test at P  ≤ 0.05 level. ^ Significant difference among more than two independent means using ANOVA-test at 0.05 level; ns: non-significant variations. The study examines the levels of IL-15, IL-22, and IL-37 in PCOS patients based on various factors as shown in Table 5 . For marital status, married women (n = 69) had significantly higher levels of IL-15 (51.64 ± 17.40 pg/mL) and IL-22 (193.02 ± 53.91 pg/mL) and similar IL-37 levels (39.03 ± 13.12 pg/mL) compared to unmarried women (n = 21) (IL-15: 37.43 ± 5.70, IL-22: 153.78 ± 25.11, IL-37: 39.87 ± 13.13), with significant differences in IL-15 ( p  ≤ 0.0001) and IL-22 ( p  ≤ 0.002), but no significant difference in IL-37 ( p  ≥ 0.05). Menstrual cycle regularity showed no significant differences in IL-15, IL-22, or IL-37 levels between regular and irregular cycles ( p  ≥ 0.05). Past medical history had no significant impact on IL levels, with IL-15, IL-22, and IL-37 values showing no substantial difference ( p  ≥ 0.05). Similarly, drug usage showed no significant differences in IL-15, IL-22, or IL-37 levels ( p  ≥ 0.05). Regarding family history, no significant differences were found in IL-15, IL-22, or IL-37 levels ( p  ≥ 0.05). For duration of PCOS, no significant variations were observed across the three groups ( p  ≥ 0.05). However, for history of abortion, a significant difference was found in IL-37 levels ( p  ≤ 0.036), with those having a history of abortion showing lower IL-37 levels (35.36 ± 12.80) compared to those without (41.35 ± 12.80). Other factors did not show significant effects, suggesting that marital status and history of abortion are the most influential factors on IL-15, IL-22, and IL-37 levels. Table 5 The relationship between IL-15, IL-22, IL-37 and main features of PCOS patients group, internal comparison. PCOS Patients IL-15 (pg/mL) IL-22 (pg/mL) IL-37 (pg/mL) No. Mean ± SD No. Mean ± SD No. Mean ± SD Married Yes 69 51.64 ± 17.40 69 193.02 ± 53.91 69 39.03 ± 13.12 No 21 37.43 ± 5.70 21 153.78 ± 25.11 21 39.87 ± 13.13 p value 0.0001 # 0.002 # 0.798 Menstrual cycle Irregular 87 48.30 ± 16.55 87 182.92 ± 51.08 87 39.18 ± 12.71 Regular 3 49.18 ± 21.42 3 211.25 ± 64.14 3 40.60 ± 25.18 P value 0.928 0.351 0.854 Past medical history Yes 6 40.34 ± 3.25 6 158.50 ± 24.51 6 41.89 ± 9.46 No 84 48.90 ± 17.01 84 185.67 ± 52.39 84 39.03 ± 13.29 p value 0.224 0.213 0.607 Drugs Yes 5 39.54 ± 3.65 5 155.54 ± 25.54 5 47.21 ± 3.82 No 85 48.84 ± 16.91 85 185.53 ± 52.11 85 38.75 ± 13.26 p value 0.225 0.206 0.160 Family history Yes 9 40.95 ± 5.59 9 154.23 ± 28.38 9 40.09 ± 15.57 No 81 49.14 ± 17.21 81 187.15 ± 52.41 81 39.13 ± 12.85 p value 0.161 0.068 0.835 Duration (years) <1year 35 46.01 ± 14.94 35 184.86 ± 56.12 35 38.82 ± 15.23 1–4 37 48.38 ± 19.32 37 176.52 ± 50.22 37 38.82 ± 12.25 5–9 years 18 52.71 ± 13.12 18 197.01 ± 43.36 18 40.83 ± 10.31 p value 0.384 0.382 0.845 History of abortion Yes 32 49.55 ± 19.90 32 185.97 ± 39.43 32 35.36 ± 12.80 No 58 47.65 ± 14.59 58 182.70 ± 57.21 58 41.35 ± 12.80 P value 0.606 0.775 0.036 # # Significant difference between two independent means using Students- t -test at 0.05 level. The relationship between IL-15, IL-22, IL-37 and main features of PCOS patients group, internal comparison. # Significant difference between two independent means using Students- t -test at 0.05 level. The objective is to assess the potential utility of interleukins as diagnostic or screening tools for PCOS, with a specific focus on establishing a “cut-off value” that maximizes sensitivity and specificity for accurate PCOS diagnosis. As shown in Fig. 1 and Table 6 , the results for IL-37, IL-15, and IL-22, along with their corresponding sensitivity and specificity values, highlight the recommended cut-off points for optimal performance. For IL-37, the cut-off value of 57.737 ng/mL provides the best balance, with a sensitivity of 90.0 % and specificity of 90.0 %. For IL-15, the value of 36.925 ng/mL offers the optimal threshold, showing a sensitivity of 80.0 % and specificity of 80.0 %. Lastly, for IL-22, the recommended cut-off value is 119.5465 ng/mL, which achieves a sensitivity of 93.3 % and specificity of 90.0 %. These blue-marked values represent the most effective thresholds for distinguishing between conditions with high sensitivity and specificity, making them the ideal reference points in clinical practice. Fig. 1 Graphical ROC analysis and AUC of IL-15, IL-22 and IL-37. Table 6 Receiver Operating Characteristic (ROC) analysis of IL- 15, IL-22, and IL-37. Test Result Variables Positive if Greater Than or Equal Sensitivity Specificity IL-37 (pg/mL) 23.35250 100 10.0 36.20950 100 40.0 39.34100 100 50.0 41.29600 100 55.6 43.51400 98.0 60.0 46.96200 94.0 70.0 49.44550 94.0 80.0 57.73700 90.0 90.0 70.86700 70.0 100 IL-15 (pg/mL) 28.09400 97.8 10.0 29.86050 96.7 30.0 31.15200 96.7 40.0 32.37500 93.3 50.0 33.44850 91.1 60.0 34.40100 87.8 64.0 36.92500 80.0 80.0 40.13450 70.0 84.0 42.12100 60.0 84.0 45.19150 50.0 84.0 IL-22 (pg/mL) 29.33000 100 10.0 72.32900 100 50.0 79.21000 100 60.0 91.71400 100 70.0 107.59850 100 80.0 109.38300 100 84.0 119.54650 93.3 90.0 134.61700 80.0 90.0 141.91600 70.0 90.0 161.24600 63.3 98.0 162.19450 62.2 100 Blue boxes represent the recommended cut-off value for optimal sensitivity and optimal specificity. Graphical ROC analysis and AUC of IL-15, IL-22 and IL-37. Receiver Operating Characteristic (ROC) analysis of IL- 15, IL-22, and IL-37. Blue boxes represent the recommended cut-off value for optimal sensitivity and optimal specificity. Results in Table 7 represent the difference in Caspase 9 gene expression in different fold graduations for both PCOS and control groups; no statistically significant difference in the mean was observed when these folds were compared to each other (27.02 ± 96.3 vs. 7.34 ± 21.50) at P ≥  0.05. Table 7 Comparison between PCOS and control groups folds for the Caspase 9 gene expression. ΔCT ΔΔCT Folding (2-ΔΔCt) Patients 8.69 ± 4.38 0.96 ± 4.38 27.02 ± 96.33 Control 7.73 ± 2.47 1.06 ± 2.47 7.34 ± 21.50 Range 1.34 – 10.36 0.44 – 2.63 0.16 – 84.08 p value 0.432 (ns) 0.432 (ns) 0.440 (ns) ns: Non-significant variations are denoted p  ≥ 0.05. Comparison between PCOS and control groups folds for the Caspase 9 gene expression. ns: Non-significant variations are denoted p  ≥ 0.05. Table 8 illustrates the correlation between the main features of PCOS patients and control groups, as well as the expression of the Caspase 9 gene in PCR folds. These parameters were age, BMI, and waist circumference. However, to uncover the precise statistical relationship between these parameters and the expression of the caspase 9 gene, we further subdivided the data as follows: age was subdivided into five categories: <20, 20–24, 25–29, 30–34, and ≥ 35; BMI was subdivided into four categories: underweight, normal, overweight, and obese; and waist circumference was subdivided into three categories: underweight, normal, and obese. Only the control group showed a significant difference in the mean waist index of the PCOS patients, with a p-value of less than 0.0001. Table 8 Relation between PCOS and control groups in age, BMI and waist circumference for the Caspase 9 gene expression represented as PCR folds. Parameters PCR (folds) PCOS Patients Controls No. Mean ± SD No. Mean ± SD Age (years) < 20 years 2 157.120 ± 222.13 ^ − − 20–24 11 7.522 ± 21.081 7 1.400 ± 1.931 25–29 11 3.995 ± 7.809 3 4.903 ± 7.103 30–34 3 163.040 ± 279.86 3 28.367 ± 48.25 ≥ 35 years 8 1.941 ± 2.857 2 0.245 ± 0.120 p value 0.014 ^ 0.324(ns) BMI (Kg/m2) Underweight 1 0.010 ns 2 3.210 ± 3.521 Normal 6 0.175 ± 0.318 6 0.650 ± 0.472 Overweight 13 9.118 ± 19.846 5 17.288 ± 37.34 Obese 15 55.065 ± 143.863 2 6.670 ± 9.065 p value 0.538(ns) 0.680(ns) Waist circumference (cm) Underweight 3 9.053 ± 14.950 # 1 84.080 Normal 5 14.944 ± 31.281 6 1.398 ± 2.141 Obese 27 31.248 ± 109.009 8 2.204 ± 4.414 p value 0.895(ns) 0.0001 ^ # Significant difference between two independent means using Students- t -test at 0.05 level. ^ Significant difference among more than two independent means using ANOVA-test at 0.05 levels. ns: Non-significant variations are denoted P ≥ 0.05. Relation between PCOS and control groups in age, BMI and waist circumference for the Caspase 9 gene expression represented as PCR folds. # Significant difference between two independent means using Students- t -test at 0.05 level. ^ Significant difference among more than two independent means using ANOVA-test at 0.05 levels. ns: Non-significant variations are denoted P ≥ 0.05. Table 9 presents the results of a statistical analysis that compares PCOS subgroups categorized by regular and irregular menstrual cycles with the regular control group. The table's results indicate that there are no statistically significant differences between Caspase-9 and factors such as maternal status, menstrual cycle, medical history, drugs taken, family history, and the history of abortion in PCOS. In the PCOS group of patients, the only one of these factors that showed a statistically significant difference was the history of abortion. The mean PCR folds of the PCOS patients with a history of abortion were higher than those without a history of abortion (82.163 ± 172.474 vs. 4.958 ± 14.712) at p  ≤ 0.030. Table 9 Relation between main features of PCOS and Caspase 9 gene expression represented as PCR folds. PCOS Patients PCR (folds) No Mean ± SD Married Yes 15 56.536 ± 143.423 No 20 4.877 ± 15.630 p value 0.118 (ns) Menstrual cycle Irregular 34 27.810 ± 97.662 Regular 1 0.030 ± 16.470 p value 0.781(ns) Past medical history Yes 6 2.575 ± 2.576 No 29 32.073 ± 105.414 p value 0.503(ns) Drugs Yes 5 2.146 ± 2.611 No 30 31.161 ± 103.701 p value 0.541(ns) Family history Yes 4 2.143 ± 1.991 No 31 30.226 ± 102.093 p value 0.591(ns) Duration (years) <1year 16 24.775 ± 79.145 1–4 18 29.048 ± 114.116 5–9 years 1 26.310 ± 112.600 p value 0.992 (ns) History of abortion Yes 10 82.163 ± 172.474 No 25 4.958 ± 14.712 p value 0.030 # # : P value is significant at the 0.05 level, ns: Non-significant variations are denoted P  ≥ 0.05. Relation between main features of PCOS and Caspase 9 gene expression represented as PCR folds. # : P value is significant at the 0.05 level, ns: Non-significant variations are denoted P  ≥ 0.05. The objective is to assess the potential utility of caspase 9 gene expression as diagnostic or screening tools for PCOS, with a specific focus on establishing a “cut-off value” that maximizes sensitivity and specificity for accurate PCOS diagnosis. However, a failure and significant point of area under the curve Table 10 and Fig. 2 , were observed for the PCR folds of the caspase 9 gene expression (AUC ± SE = 0.570 ± 0.081). Table 10 ROC analysis of the studied Caspase 9 gene expression. Test Result Variables Area Under the Curve (AUC) Std. Error 95 % Confidence Interval Lower Bound Upper Bound PCR (folds) 0.570  ns 0.081 0.412 0.729 ns: Non-significant variations are denoted P  ≥ 0.05. Fig. 2 Graphical ROC analysis of the studied Caspase 9 gene expression. ROC analysis of the studied Caspase 9 gene expression. ns: Non-significant variations are denoted P  ≥ 0.05. Graphical ROC analysis of the studied Caspase 9 gene expression. As shown in Table 11 , in the correlation analysis of immunological parameters in PCOS patients (n = 90), IL-37 showed no significant correlation with IL-15 (r = −0.066, p ≥  0.534), IL-22 (r = −0.072, p ≥ 0.502 ), or PCR (r = −0.209, p ≥  0.228). A highly significant positive correlation was observed between IL-15 and IL-22 (r = 0.606, p ≤  0.0001). However, IL-15 showed no significant correlation with PCR (r = −0.057, p ≥  0.745), and IL-22 also showed no significant correlation with PCR (r = 0.308, p ≥  0.071). Table 11 Correlation between IL-15, IL-22, and IL-37 in both PCOS and control groups. PCOS Patients (n = 90) IL-37 (pg/mL) IL-15 (pg/mL) IL-22 (pg/mL) PCR(folds) IL-37 (pg/mL) r − −0.066 −0.072 −0.209 P − 0.534 0.502 0.228 IL-15 (pg/mL) r −0.066 − 0.606 ** −0.057 P 0.534 − 0.0001 0.745 IL-22 (pg/mL) r −0.072 0.606 ** − 0.308 P 0.502 0.0001 − 0.071 PCR (folds) (n = 35) r −0.209 −0.057 0.308 − P 0.228 0.745 0.071 − Controls IL-37 (pg/mL) IL-15 (pg/mL) IL-22 (pg/mL) PCR(folds) IL-37 (pg/mL) r − 0.597 ** 0.264 0.364 P − 0.0001 0.064 0.182 IL-15 (pg/mL) r 0.597 ** − 0.072 0.220 P 0.0001 − 0.619 0.432 IL-22 (pg/mL) r 0.264 0.072 − −0.206 P 0.064 0.619 − 0.462 PCR (folds) (n = 15) r 0.364 0.220 −0.206 − P 0.182 0.432 0.462 − *Correlation is significant at the 0.05 level. ** Correlation is highly significant at the 0.01 level. Correlation between IL-15, IL-22, and IL-37 in both PCOS and control groups. *Correlation is significant at the 0.05 level. ** Correlation is highly significant at the 0.01 level. In the control group, IL-37 showed a significant positive correlation with IL-15 (r = 0.597, p  ≤ 0.0001), but no significant correlation with IL-22 (r = 0.264, p  ≥ 0.064) or PCR (r = 0.364, p  ≥ 0.182). IL-15 showed no significant correlation with IL-22 (r = 0.072, p  ≥ 0.619) and a weak, non-significant correlation with PCR (r = 0.220, p  ≥ 0.432). IL-22 had no significant correlation with PCR (r = −0.206, p  ≥ 0.462).

In a case-control study conducted from August 2022 to June 2023 involving a total of 138 subjects. Ethical approval was obtained from the University of Technology and Baghdad Health Directorate (Reference No. 360, Nov 31, 2022). Additional approvals were secured from the administration of Al-Kadhimiya Teaching Hospital, as well as private clinics and laboratories, with informed consent from each patient after explaining the study's purpose. Of these subjects, ninety females were diagnosed with PCOS, with ages ranging from 22 to 45 years, and 48 age-matched healthy women served as the control group. PCOS diagnosis followed the Rotterdam criteria-2003, requiring at least two of the following conditions: hyperandrogenemia, ovarian dysfunction, ovarian volume exceeding 10 mm on ultrasonography, and fewer than 12 follicles measuring 2 to 9 mm in diameter. Exclusions were made for women with certain medical conditions and those receiving specific medications. In the selected healthy control group, individuals without a PCOS diagnosis were characterized by the absence of menstrual irregularities, polycystic ovaries, and elevated androgen levels. They would also have normal hormonal profiles, excluding those with thyroid disorders, diabetes, or metabolic syndrome. Additionally, the controls were likely age- and BMI-matched with the PCOS patients to minimize confounding factors. Lastly, the controls would not be using medications that could influence hormone levels or immune function, ensuring their baseline measures reflected a healthy state. Waist circumference is a key indicator of obesity and related health risks. For women, a waist measurement over 35 in. (88 cm) and for men, over 40 in. (102 cm), suggests a higher risk of conditions like heart disease and type 2 diabetes. This measure reflects abdominal fat, which is more strongly linked to health risks than total body weight. Body Mass Index (BMI) is another tool used to assess weight relative to height. A BMI between 18.5 and 24.9 is considered normal; 25–29.9 is overweight and 30 or higher is obese. However, BMI doesn’t directly measure body fat and may not be accurate for those with high muscle mass or elderly individuals. 12 Peripheral blood samples were collected for ELISA and molecular studies. The serum was separated from a 4 ml blood sample in a gel tube, while 0.25 mL of blood was mixed with 0.5 mL of TRIzol Reagent for the molecular analysis. Both samples were appropriately stored for further analysis. In this assay, the “Double Antibody Sandwich” technique (ELISA Kits, Mybiosource, USA) is utilized. It involves quantifying the concentrations of human IL-15, human IL-22, and human IL-37 in the samples. This is achieved by comparing the optical density (O.D.) of the samples to a standard curve that has been calculated. To ensure accuracy and consistency, all standards, samples, and reagents were meticulously prepared in strict accordance with the test preparation guidelines provided in the kit leaflet. In the RNA purification process, blood samples were lysed by combining 0.25 mL of blood with 0.5 mL of TRIzol™ Reagent, followed by thorough homogenization through pipetting. Three-phase separations were then conducted by introducing 0.2 mL of chloroform into each tube, leading to the formation of distinct lower organic, interphase, and upper aqueous phases after centrifugation. The aqueous phase, containing the target RNA, was transferred to a new tube. Subsequently, RNA was precipitated by adding 0.5 mL of isopropanol, forming a white pellet upon centrifugation. After discarding the supernatant, RNA washing took place, involving the addition of 0.5 mL of 70 % ethanol, vortexing, and subsequent centrifugation. The ethanol was removed, and the RNA pellet air-dried. To achieve RNA solubility, the pellet was rehydrated in 100 μl of Nuclease-Free Water, followed by incubation in a water bath or heat block at 55–60 °C for 10–15 min. In the determination of RNA yield, the Quantus Fluorometer was utilized to gauge the concentration and quality of the extracted RNA. This method involved mixing 1 μl of RNA with 200 μl of diluted QuantiFluor Dye, followed by a 5-minute incubation in darkness at room temperature to assess RNA concentration values, thereby confirming its suitability for downstream applications. Additionally, primer preparation was carried out by reconstituting lyophilized primers from Macrogen Company in nuclease-free water, resulting in a stock solution with a final concentration of 100 pmol/μl. To facilitate practical use, a working primer solution at 10 pmol/μl was created by combining 10 μl of the stock solution, stored at −20 °C, with 90 μl of nuclease-free water. The reaction setup and thermal cycling protocol for the one-step RT-PCR process were designed; a total of 50 reactions were prepared, each with a volume of 10 μl, providing a 5 % safety margin for the experimental setup. The annealing temperature for the primers ranged from 60 to 65 °C, accommodating the diversity of primer sequences. The distinct primers in Table 1 were employed for the analysis. The PCR process entailed 40 cycles to ensure robust amplification and accurate results and to ensure precise and accurate execution of the RT-PCR analysis. Table 1 Primers used this study. Primer Name Sequence 5‘-3‘(b) Annealing Temp. (℃) Ref. Caspase-9-F ACAGGGTCTGCTCTTTCT 60 31 Caspase-9-R GCATTCATCTGTCCCTCTTC 60 β-Globin-F ACACAACTGTGTTCACTAGC 60 32 β-Globin-R CAACTTCATCCACGTTCACC 60 Primers used this study. The real-time PCR program involves various steps, including enzyme activation, denaturation, annealing, and extension, with specific temperature and time settings to achieve accurate gene expression analysis. Gene expression levels were determined using the Livak method. Folding = 2-ΔΔCT. ΔCT = CT gene − CT House Keeping gene. ΔΔCT = ΔCT Treated or Control − ΔCT Control. Data analysis was conducted using IBM SPSS-29. Frequency, percentage, mean, standard deviation, and range were used to describe the data. For quantitative data, Student's t -test or ANOVA tested differences among means, while Pearson Chi-square or Fisher Exact tests assessed differences among percentages. A significance level of 0.05 or less was considered statistically significant. Pearson correlation measured the associations between quantitative variables, with r values indicating strength (0.3–0.5 weak, 0.5–0.7 moderate, and > 0.7 strong). R-squared (r2) quantified the variation explained by one variable on another (e.g., r = 0.58, r2 = 0.34 means 34 % variation).Receiver Operating Characteristic (ROC) curves identified diagnostic tool potential. The Area Under the Curve (AUC) indicated test accuracy (0.9 “Perfect,” 0.8 “Good,” 0.7 “Fair,” 0.6 “Poor,” <0.6 “Failure”). We calculated sensitivity, specificity, false negatives, false positives, predictive values, and accuracy rates.

The present study's findings showed a significant increase in the serum levels of the inflammatory cytokines IL-15 and IL-22 in PCOS patients when compared to the control group. This suggests that these cytokines could serve as potential therapeutic targets and actively contribute to the pathogenicity of PCOS. On the other hand, the anti-inflammatory cytokine IL-37 indicated a significant decrease in PCOS patients compared to the control group. No significant differences were observed in the expression of the caspase9 gene between the PCOS and control groups. Significant differences in the correlations with clinical parameters are identified. IL-22 and IL-37 show promise as diagnostic markers, but Caspase9 gene expression lacks diagnostic utility. The study contributes valuable insights into the complex interplay of inflammatory cytokines and gene expression in PCOS among Iraqi women.

The mean age for both groups was nearly identical, which aligns with the concept of group matching. Along with increasing age, fertility declines, especially in women. 4 Age is an important parameter that affects fertility; however, the impact of age on PCOS has captivated the attention of many researchers and served as the initial driving force behind several investigations into PCOS worldwide. 8 It is important to mention that the postponement of childbearing poses a significant obstacle in the field of reproductive medicine due to the influential effect of advancing age on the likelihood of successful conception, whether through natural means or with the assistance of medical interventions. 5 Obesity is strongly linked to infertility in different ways, including at the molecular level. Females with obesity face more challenges when trying to get fertility treatments and have a successful pregnancy. 3 This can exacerbate their economic and social stresses. 6 Pregnancy risk is strongly linked to BMI, especially in PCOS patients. However, among women diagnosed with PCOS, a greater initial BMI was linked to a reduced chance of achieving pregnancy. However, reducing weight increased the likelihood of pregnancy compared to maintaining a steady weight or gaining weight. 15 The PCOS group had a greater mean waist circumference (p = 0.001). These results agreed with previous results. 3 , 6 This study revealed that PCOS patients had higher serum levels of IL-15 than the control group. PCOS patients consistently exhibit elevated levels of inflammatory markers, including interleukin-2 (IL-2), IL-6, IL-18, interferon-γ (IFN-γ), and tumor necrosis factor-α (TNF-α), both in their serum and ovaries when compared to normal controls. 9 , 10 , 21 This association between inflammatory cytokines and ovarian dysfunction implies that inflammation may be considered the most potent risk factor for PCOS. 28 Interleukin-15 (IL-15) is a protein encoded by the IL-15 gene in humans. Structurally, IL-15 is similar to interleukin-2 (IL-2) and binds to and signals through a complex composed of the IL-2/IL-15 receptor beta chain (CD122) and the common gamma chain (gamma-C, CD132). 12 Furthermore, serum IL-15 concentrations were found to be higher in overweight subjects, suggesting that adipose tissue depots might be a source of IL-15. 33 IL-15 has also been observed to be increased in follicular fluid (FF) from women with endometriosis, implying that IL-15 might impair oocyte quality, leading to lower fertilization rates. 34 The concentrations of IL-15 in follicular fluid from follicles with immature oocytes were significantly higher than those with mature oocytes. IL-15 plays a role in maintaining memory T cells and is implicated in NK cell development. It prevents apoptosis in rodent lymphocytes by inducing BCL2L1/BCL-x(L), an inhibitor of the apoptosis pathway. 20 On the other side, Abdullah and Alabassi found that serum Programming Cell Death-1 (PD-1) levels exhibited a significant increase in individuals with PCOS compared to the control group; not only that, but also the PD-1 gene expression levels (fold change) showed a notable increase in PCOS participants compared to the control group (unpublished data). These results suggest that IL-15 may be involved in the pathogenesis of PCOS, potentially by influencing survival and the inflammatory state. 14 Despite the favorable effects of IL-15, there are reports of IL-15′s involvement in chronic inflammation of adipose tissue, contributing to obesity-associated metabolic syndrome. Notably, the absence of IL-15 in knockout mice was found to prevent fat accumulation in white adipose tissue and encourage lipid utilization through adaptive thermogenesis. 35 Additionally, higher serum IL-15 concentrations were observed in overweight subjects, suggesting that IL-15 may originate from adipose tissue depots. 33 The presence of increased IL-15 in follicular fluid from women with endometriosis suggests a potential link to impaired oocyte quality, leading to lower fertilization rates. 34 Also, the study found the serum IL-22 was higher in PCOS compared to control. Conversely, another research study involving 23 PCOS patients and 23 healthy individuals with matched body mass indexes (BMIs) revealed that the levels of IL-22 in the blood of PCOS patients were significantly lower compared to the control group. 36 Interleukin-22 (IL-22), categorized within the IL-10 superfamily, plays a pivotal role in the inflammatory response. It originates from various cellular subsets, including TH17, Th22, natural killer cells, and innate lymphoid cells (ILC), and its expression and activities are subject to intricate modulation by an array of cytokines and transcription factors. IL-22 is instrumental in preserving the equilibrium of barrier functions in the presence of intestinal pathogens and commensal microorganisms. It can have protective and regenerative effects on epithelial tissues in various contexts, such as liver necrosis and inflammatory bowel disease. However, it can also incite a pro-inflammatory response under specific conditions, as seen in chronic phases of certain viral infections like HIV. Recent research has indicated a reduction in IL-22 concentrations within the serum and follicle fluid of PCOS patients. It was also observed that the introduction of IL-22 exhibited the potential to ameliorate instances of insulin resistance, ovarian dysfunction, and infertility, especially in murine models simulating PCOS-like conditions. The future potential of IL-22 as a treatment for PCOS patients is promising, but its dosage and administration must be carefully considered to avoid negative outcomes. Managing metabolic and inflammatory issues is crucial for women with PCOS. 37 Moreover, gut bacteria and gut fungi seem to influence IL-22 levels, contributing to the onset and progression of PCOS. Various medical institutions and clinical facilities rely on the Rotterdam criteria for the diagnostic assessment of PCOS. 38 A study by 36 suggests that bile acids play a pivotal role in modulating IL-22 production, thereby influencing ovarian function in PCOS. Their research demonstrated reductions in IL-22 messenger ribonucleic acid (mRNA) in mice transplanted from PCOS individuals, with corresponding declines in IL-22 levels in serum and PCOS-like mouse models. PCOS patients also exhibited significantly lower IL-22 levels in both serum and follicular fluid compared to controls. 39 This is significant because PCOS is known to promote inflammation. Hence, IL-37, as an inflammation inhibitor, holds promise as a potential treatment for PCOS. 40 Studies have consistently shown that IL-37 levels are significantly lower in PCOS patients compared to healthy controls. 41 Remarkably, the history of abortion has been linked to significant decreases in IL-37 levels in PCOS patients with a history of abortion compared to those without a history of abortion. In the context of PCOS, which is associated with hyperandrogenemia, obesity, insulin resistance, inflammation, and metabolic disorders, inflammation is considered a leading cause of adverse pregnancy outcomes, such as elevated abortion rates and pregnancy complications. 21 , 42 The study found that the serum level of IL-37 decreased in PCOS patients compared to the control group. IL-37′s anti-inflammatory role is crucial, and any deficiency in IL-37 can lead to increased inflammation, potentially contributing to abortion. Moreover, IL-37 has been positively correlated with body mass index (BMI). Furthermore, this research is the first to discover a significant positive correlation between IL-37 and IL-15 in healthy individuals. These findings suggest the important role of IL-37 in reducing inflammation and countering insulin resistance, particularly in the context of obesity, both in mice and humans. This highlights IL-37 as a potential therapeutic target for addressing insulin resistance and Type 2 diabetes mellitus (T2DM) resulting from obesity. 43 The analysis of caspase-9 gene expression revealed no significant differences between PCOS and control. The lack of significance in caspase 9 gene expression between PCOS patients and controls could be due to various factors, such as natural variability in gene expression, where caspase 9 activity may not be notably altered in PCOS. Additionally, factors like sample size, which may limit statistical power, could prevent the detection of subtle differences. Moreover, caspase 9 expression can be influenced by timing, hormonal fluctuations, or environmental factors, and its role in apoptosis may not be distinctly different between PCOS and control groups under the conditions studied. Caspase-9 is the most intensively studied initiator caspase and is a key player in the intrinsic or mitochondrial pathway, responding to various stimuli, such as chemotherapies, stress agents, and radiation. Its activation on the apoptosome complex is crucial for maintaining its catalytic status, often involving homodimerization of monomeric zymogens. Failing to activate caspase-9 can have profound physiological and pathophysiological consequences, leading to degenerative disorders, developmental disorders, and even cancer. The apoptotic commitment process is finely regulated by a multitude of proteins and small molecules. 44 Surprisingly, the results of caspase 9 gene expression in this study do not align with a study conducted by Hacer and others, where they found that women diagnosed with PCOS had elevated levels of total oxidant status and oxidative stress index (OSI) and reduced levels of caspase 9 compared to the control group. They suggested that women with PCOS experience increased oxidative stress and decreased caspase 9 activity, contributing to the pathophysiology of the disorder. 45 On a different note, a study investigated the effect of growth hormone therapy on oxidative stress (OS) and apoptosis through the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) signaling pathway in granulosa cells of PCOS patients. They found that caspase-9 mRNA expression and cleaved caspase-9 protein levels were significantly lower in the PCOS group undergoing growth hormone therapy compared to the PCOS group without therapy. However, the caspase-9 levels in the PCOS group were similar to those in the control group. This suggests that growth hormone therapy can modulate caspase-9 activity in granulosa cells. 46 Furthermore, some research has proposed a potential correlation between diminished serum concentrations of caspase 9 and the development of PCOS. 47 Moreover, a study found differences between women with regular ovulation and those with PCOS, indicating reduced levels of caspases 3, 8, and 9 expression alongside elevated expression of anti-apoptotic regulators Calf Intestinal Alkaline Phosphatase (cIAP-2) and heat shock protein 27 (Hsp27) within oocytes of the PCOS group. 48 , 49 A notable limitation of this study is the sample size of the PCOS group. While PCOS is a recognized condition, a larger patient cohort would strengthen the generalizability of the findings. Furthermore, the underlying causes and optimal treatment strategies for PCOS remain elusive. Future research with larger and more diverse patient populations is warranted to solidify the observed associations between IL-15, IL-22, IL37 and caspase-9 with PCOS and to explore their potential as therapeutic targets.

The complex interaction between genetic and environmental factors, metabolic alterations, and neuroendocrine and immune systems is thought to contribute to the pathogenesis of PCOS. 1 , 2 And due to its unclear etiology and the diverse range of clinical manifestations, the current therapeutic approaches for PCOS primarily focus on managing symptoms, as a definitive cure is still lacking. Moreover, PCOS is increasingly understood as a condition resulting from a mismatch between evolution and the modern environment. It presents with a variety of interconnected symptoms related to metabolism and hormones. 3 , 4 , 5 Additionally, it is important to note that the female reproductive tract experiences physiological inflammation during various processes, such as menstruation, ovulation, implantation, and labor at term. However, it has been suggested that the development of mild, persistent inflammation could potentially be involved in the etiology of PCOS. 6 , 7 The exact mechanism of inflammation in women with PCOS is not fully known yet; however, this inflammation, characterized by chronic low-grade inflammation, is important to address as it may contribute to current and future potential health problems when following a Mediterranean diet. 8 . Studies have revealed that individuals with PCOS exhibit consistently higher levels of inflammatory markers in both their serum and ovaries when compared to healthy individuals. 9 , 10 Recent studies also suggest that exercise can influence other inflammatory markers in women with PCOS and have a positive effect on reducing their CRP levels. 11 The link between inflammatory cytokines and ovarian dysfunction suggests that inflammation could be regarded as one of the most influential risk factors for PCOS. 12 In PCOS, visceral fat cells influence insulin and glucose processing, mimicking the effect of LH on theca cells, thereby increasing androgen levels. Adipose tissue's immune cells, notably macrophages, release inflammatory substances, intensifying inflammation. PCOS disrupts ovarian function, causing hormone imbalances, elevated androgens, and reduced egg quality. Immune cell imbalances and cytokine disruptions contribute to fertility challenges. 13 Conducting further research into the involvement of inflammatory mediators in the onset and progression of PCOS is crucial for obtaining a deeper understanding of the disease's pathophysiology and identifying potential therapeutic targets. 14 Recently, it has been emphasized how important immune therapeutic targets are in treating PCOS. One example is chemokines, which are molecules that play important roles in the development, promotion, and treatment of two reproductive health conditions: PCOS and endometriosis. Chemokine-based therapeutic strategies hold a lot of promise for the future in managing PCOS and endometriosis. 15 PCOS exhibits elevated IL-18, C3, and insulin levels, indicating inflammation independent of obesity or insulin resistance. 16 Physiological inflammation occurs in the female reproductive tract during various stages, such as ovulation, menstruation, implantation, and labor at term. This inflammation may also be linked to the development of Polycystic Ovary Syndrome (PCOS). 6 , 7 In this context, IL-15 is a noteworthy factor released by various cell types, including immune and non-immune cells like macrophages, T-lymphocytes, neutrophils, and skeletal muscle cells. 17 IL-15 has gained attention for its multiple advantages, which include suppressing inflammation in white adipose tissue, enhancing lipid and glucose metabolism, alleviating endoplasmic reticulum stress, and promoting mitochondrial function. 18 , 19 Interestingly, the amount of IL-15 in the follicular fluid of follicles with immature oocytes was much higher than that of follicles with mature oocytes. This suggests investigating IL-15 as a potential oocyte maturity indicator. 20 Due to the adverse correlation between follicular fluid IL-15 concentration and oocyte maturity, efforts have been made to explore the potential pathogenic role of IL-15 in women with PCOS. 21 The relationship between IL and 22 and PCOS has been subject to study, yielding varying results. While one study suggests that PCOS women's circulating IL-22 and IL-22 binding protein concentration is similar to that of healthy women, the ratio of IL-22/IL-22 binding protein significantly increases after three months of oral contraceptive therapy in PCOS women, implying a biological activity of IL-22. 22 Another player in this complex landscape is IL-37, a newly discovered member of the IL-1 family. IL-37 possesses a remarkable ability to inhibit inflammation and the immune response by suppressing the production of pro-inflammatory cytokines. It also alleviates inflammation-induced fatigue through metabolic reprogramming and by limiting the metabolic effects of inflammation. 23 IL-37 is constitutively expressed in various human tissues and cells, contributing to the maintenance of immune homeostasis. It's mainly expressed in immune cells, including circulating monocytes, tissue macrophages, dendritic cells (DCs), tonsil B cells, and plasma cells. 24 , 25 However, baseline levels of IL-37 transcripts in resting human blood monocytes and DCs are low due to the presence of an instability sequence in IL-37 mRNA and its short half-life. 26 Similarly, the constitutive expression of IL-37 is low or absent in IL-37 transgenic mice. 27 Nevertheless, IL-37 expression significantly increases in response to certain pro-inflammatory stimuli in tissue cells. 28 After stimulation, immune cells, including monocytes, DCs, and T cells, express IL-37, with the majority being monocytes. 25 In summary, although its expression is relatively low, the inducible expression of IL-37 can exert a powerful anti-inflammatory or immune regulatory role. In a recent report, it was found that in PCOS patients, the free androgen index and body mass index were negatively correlated with IL-37. 29 The cysteine-aspartic protease caspase-9 is known for its role in intrinsic apoptosis. On a different note, it controls both normal cell death and abnormal tissue degeneration in many ways. Beyond apoptosis, it participates in non-apoptotic functions, including the regulation of cellular differentiation, innate immunity, mitochondrial homeostasis, and autophagy. Recent research conducted by Avrutsky and Troy has unveiled that caspase-9 can induce neurovascular injury through non-apoptotic dysfunction within endothelial cells. 30 This array of molecules, including IL-15, IL-22, IL-37, and caspase-9, showcases the intricate interplay between inflammation and immune responses in the context of PCOS and various physiological and pathological conditions. The goal of this study was to look into the possible roles of the cytokines IL-15, IL-22, and IL-37, as well as the Caspase 9 gene, in polycystic ovary syndrome (PCOS) in a group of Iraqi women, giving us a first idea of how they might affect the condition's pathophysiology.

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.