169J Contemp Med Sci | Vol. 8, No. 3, May-June 2022: 169–175 Original Roles of C-Peptide and Triglyceride as Effective Indices for Insulin Resistance Investigations in Iraqi Women with Polycystic Ovarian Syndrome Hadbaa H. Al-Murshedi1,*, Fadhil J. Al-Tu’ma1, Eman A. Hadi2, Borhan Mustafa Mohammed3, Tarik Al-Kayat4 1Department of Chemistry and Biochemistry, College of Medicine, University of Kerbala, Kerbala, Iraq. 2Department of Chemistry, College of Science, University of Mosul, Mosul, Iraq. 3Department of Pharmacy, Mazaya University College, Thi-Qar, Iraq. 4Medical Technical College, Al-Farahidi University, Baghdad, Iraq. *Correspondence to: Hadbaa Helwas Al-Murshedi. (Email: hdbaa88@gmail.com) (Submitted: 08 June 2022 – Revised version received: 14 June 2022 – Accepted: 15 June 2022 – Published online: 26 June 2022) ISSN 2413-0516 Introduction Polycystic ovarian syndrome (PCOS) is a common endocrine disorder with an impact on hormonal and metabolic regula- tion. Women with PCOS are at increased risk of anovulation and infertility.1 The clinical presentation is extremely variable but generally includes clinical and/or biochemical hyper- androgenism, menstrual dysfunction (oligo-amenorrhea) and polycystic ovaries on ultrasound.2 Diagnostic criteria for PCOS mostly use the revised Rotterdam 2003 criteria.3 Insulin resistance (IR) is a very common finding in sub- jects with PCOS which not included among the diagnostic features.4 IR is usually defined as a pathological condition characterized by a decreased responsiveness or sensitivity to the metabolic actions of insulin. In women with PCOS, IR plays an important role in the development and persistence of this disorder.5 IR stimulates ovarian theca cells to secrete androgens and increasing luteinizing hormone (LH) effect on ovarian androgen production. Insulin inhibits sex hormone binding globulin (SHBG) secretion, increasing free and bioactive androgen levels and worsen hyperandrogenism status.6 Moreover, IR is critically involved in the development of met- abolic syndrome and cardiovascular disease in PCOS women.7 The need for accurate screening of IR in women with PCOS is obvious. Thus, early recognition and management would offer important preventive measures.8 Several methods have been developed to quantify this metabolic phenomenon. The hyperinsulinemic euglycemic clamp technique (HIEG) is generally accepted as the best available direct method to assess insulin sensitivity.9 However, this technique is very complex and not appropriate in clinical practice. As an alternative strategy, practical surrogate markers have been proposed to measure IR; considering the concept that patients who have insulin resistance will have more insulin hormone in blood than those who does not. Homeo- stasis model assessment-insulin resistance index (HOMA-IR) and the quantitative insulin sensitivity check index (QUICKI) are the most widely used surrogate indices of IR, which reflect the feedback between fasting serum insulin and glucose.10,11 Excess adiposity and dyslipidemia may influence insulin sensitivity. Based on these factors, different indices have been developed to measure IR, which better reflect lipid pro- files such as triglyceride (TG) (McAuley index).12 The Abstract Objectives: To assess the insulin resistance by determination of C-peptide and triglyceride levels in women with polycystic ovarian syndrome (PCOS) and then investigation of insulin resistance by various methods and comparing them with the homeostatic model assessment method used. Methods: A study included 120 participants (68 women have PCOS subdivide according to their BMI to 45 obese (BMI>=30) and 23 non-obese (BMI<30). The remaining 52 participants represent as apparently control group with normal weight and normal menstrual cycle. Patients with PCOS were selected from the Infertility Department, Gynecology and Obstetrics Teaching Hospital,Kerbala province, Iraq. Diagnosis of PCOS is based on 2 of 3 findings: oligo/anovulation, hyperandrogenism, polycystic ovaries in ultrasound (Rotterdam criteria). The patients were interviewed and examined for weight, height, waist circumference, and hip circumference. Venous blood samples were collected at 9 AM after an overnight fast. Measurement of serum insulin, glucose, triglyceride and C-peptide were performed using Cobas instrument and by ELISA technique. Results: Based on HOMA-IR, the prevalence of insulin resistance in obese PCOS women was 77% while in non-obese PCOS women was 70%. HOMA-IR, QUICKI, McAuley and CPI showed significant difference between obese PCOS (4.39 ± 1.83), (0.309 ± 0.024), (3.85 ± 0.91) and (4.39 ± 1.63) respectively; and control group (2.68 ± 0.61), (0.331 ± 0.011), (4.53 ± 0.57) and (8.72 ± 1.33) respectively. CPI also showed significant difference between obese PCOS (4.39 ± 1.63) and non-obese PCOS (6.85 ± 1.74). In obese PCOS women, both QUICKI (r = –1.00, P < 0.001) and McAuley (r = –0.81, P < 0.001) were strongly correlated with HOMA-IR, whereas CPI was not. For non-obese PCOS, there was a strong correlation for both QUICKI (r = –0.97, P < 0.001), (r = –0.62, P < 0.05) and HOMA-IR, CPI was also strongly correlated with HOMA-IR (r = –0.78, P < 0.001). Conclusion: Significant number of women with PCOS can be classified as being either insulin sensitive or insulin resistant (IR) depending on the method applied, as correlation between various IR indices is highly variable. Clinical application of surrogate indices for assessment of IR in PCOS must be therefore viewed with an extreme caution. Keywords: C-Peptide, polycystic ovary syndrome, insulin resistance 170 J Contemp Med Sci | Vol. 8, No. 3, May-June 2022: 169–175 Roles of C-Peptide and Triglyceride as Effective Indices for Insulin Resistance Investigations in Iraqi Women Original H.H. Al-Murshedi et al. triglyceride-glucose index is the logarithmized product of fasting triglycerides and fasting glucose and has been pro- posed as the alternative indicator of IR due to its relevance to dyslipidemia.13 The glucose insulin ratio (G/I) has also been employed as an index of IR. It has been described, as a useful measure of insulin sensitivity in obese PCOS women and has both high sensitivity and specificity for detecting IR in women.14 In addition, previous studies suggested that measuring C-peptide can help to determine how much of insulin a person is producing as C-peptide is secreted in equimolar amounts to insulin.15,16 C-peptide does not undergo hepatic first-pass metabolism and has a longer half-life than insulin which affords a more stable test window of fluctuating beta cell response. Therefore, it has been suggested that peripheral C-peptide levels more precisely reflect β-cell secretory activity than peripheral insulin.17 An increase in its levels suggests a high level of endogenous insulin which indicates worsened insulin resistant state. The aim of the study was to assess how much IR is in both obese and non-obese PCOS women using most commonly used index of IR (HOMA-IR) and find out a correlation between HOMA-IR and the other surrogate indices: G/I, QUICKI, McAuley, triglyceride-glucose index (TyG) and C-peptide index (CPI). Materials and Methods A case-control study included 120 participants of which 68 women have PCOS subdivide according to their BMI to 45 obese (BMI >= 30) and 23 non-obese (BMI < 30). The remaining 52 represent the control group who were apparently healthy women with normal weight and normal menstrual cycle. Patients with PCOS were selected from the Infertility Department, Gynecology and Obstetrics Teaching Hospital, Kerbala Health Directorate/Kerbala – Iraq. Institutional ethics committee approval was sought before starting the study. Oral informed consent was obtained from subjects. PCOS was diagnosed in presence of at least two out of the three diag- nostic criteria established by the revised 2003 Rotterdam European Society for Human Reproduction/American Society of Reproductive Medicine PCOS Consensus Workshop Group: i) oligo- and/or anovulation, ii) clinical and/or bio- chemical signs of hyperandrogenism, and iii) polycystic ova- ries in ultrasound.18 All women underwent anthropometric assessment like measurement of weight, height, waist circumference (WC), hip circumference, waist-hip circumference ratio (WHR) and body mass index (BMI). Transvaginal ultrasound was used to identify polycystic ovaries. Five milliliters (5 ml) of venous blood samples were col- lected at 9 AM after an overnight fast on the second or third day of the menstrual cycle, centrifuged and frozen immedi- ately at –20ºC. The levels of glucose, triglycerides, cholesterol and High-Density Lipoprotein (HDL) were measured using chemistry analyzer (AU480, Beckman Coulter, USA). Serum luteinizing hormone (LH) and follicle-stimulating hormone (FSH) were carried out with automated immuno- assay system based on the enzyme linked fluorescent assay principles (ELFA) (bioMérieux, France). Free testosterone was measured by enzyme-linked immunosorbent assay (ELISA) technique. Insulin Resistant Assessment Fasting insulin was measured using ELISA technique. Fasting C-peptide was determined using cobas C 111 analyzer. IR was estimated as: 1. HOMA-IR = (I × G)/405 2. Fasting glucose to insulin ratio = G/I 3. QUICKI = 1/(log(I) + log(G)) 4. McA = exp (2.63–0.28 × ln(I) – 0.31 × ln (TG/18) 5. TyG = ln [TG × G/2] 6. CPI = 20/(CP × G/18) Fasting insulin (I) in (µIU/ml), fasting glucose (G) in (mg/dl), triglycerides (TG) in (mg/dl) and fasting C-peptide (CP) in (nmol/l). The data were analyzed using the Statistical Package for Social Sciences (SPSS version 22.0). Continuous variables were expressed as means ± standard deviation (SD). Mean comparisons were made using one-way analysis of variance (ANOVA) followed by Tukey’s post hoc test. Pearson correla- tion analysis was used to assess the association of various IR indices with HOMA-IR. Receiver operator characteristic curves (ROC) were drawn to compare different insulin resist- ance/sensitivity indices. Insulin-based HOMA-IR was consid- ered as a gold standard to define insulin resistance. HOMA-IR values less than 2.7 were considered insulin sensitive (IS) and more than that were considered as IR. Results The demographic and clinical features of the total study population, as well as baseline values of the various indices of insulin resistance are presented in Table 1. The non- obese PCOS patients were less in age than obese. The parameters like WC and BMI, were found to be signifi- cantly increased in obese PCOS women than other groups while WHR was increased in obese PCOS than control group. WHR was not varied between obese and non-obese PCOS women. Both obese and non-obese PCOS had increased levels of insulin, glucose, cholesterol, triglyceride and LDL compared to the controls. Whereas HDL levels had not reached statistical significance (P > 0.05) among three groups. Neither analysis of obese and non-obese PCOS women, nor controls and non-obese PCOS had significant difference regarding C-peptide values. While C-peptide was higher in obese PCOS. Compared with controls, PCOS women had ele- vated levels of LH, FSH, LH/FSH ratio and free testosterone. For non-obese PCOS group, there was significant difference in term of LH and free testosterone compared with controls while FSH and LH/FSH ratio were not. The assessment of IR revealed that HOMA-IR, QUICKI, McAuley, TyG and CPI had significant difference in both PCOS groups compared with controls. G/I ratio was signifi- cantly higher in the controls than obese PCOS women. The prevalence of IR based on HOMA-IR was 80% in obese PCOS and 48% in non-obese PCOS women as shown in Figure 1. Pearson correlation coefficient was performed to show the correlation of the different parameters. For both obese and non-obese PCOS patients, the results revealed a positive cor- relation of the BMI with insulin, C-peptide, HOMA-IR and 171J Contemp Med Sci | Vol. 8, No. 3, May-June 2022: 169–175 H.H. Al-Murshedi et al. Original Roles of C-Peptide and Triglyceride as Effective Indices for Insulin Resistance Investigations in Iraqi Women Table 1. Difference in demographic, metabolic, hormonal features and IR status among obese PCOS, non-obese PCOS and control women Obese PCOS (N = 45) Non obese PCOS (N = 23) Control (N = 52) P-value Demographic characteristics Age (years) 29 ± 6.06 25 ± 4.99 27 ± 5.71 Waist circumference (cm) 108 ± 12.82 84 ± 10.06 80 ± 10.94 <0.001 WHR 0.92 ± 0.10 0.87 ± 0.10 0.82 ± 0.08 <0.001 Body mass index (kg/m2) 35.83 ± 4.64 24.24 ± 2.56 24.09 ± 3.56 <0.001 Clinical characteristics Cholesterol (mg/dl) 163 ± 26.80 144 ± 35.25 117 ± 20.97 <0.001 Triglyceride (mg/dl) 103 ± 1.50 82 ± 1.57 70 ± 1.55 <0.001 HDL (mg/dl) 40 ± 6.76 39 ± 5.17 43 ± 8.95 NS LDL (mg/dl) 97.43 ± 1.30 83 ± 1.33 56 ± 1.39 <0.001 Fasting glucose (mg/dl) 92 ± 8.25 92 ± 8.88 84 ± 5.12 <0.001 Fasting insulin (μU/ml) 18.15 ± 1.76 15.32 ± 1.70 10.74 ± 1.56 <0.001 Fasting C-peptide (nmol/l) 0.55 ± 0.38 0.50 ± 0.26 0.37 ± 0.18 <0.05 LH (IU/l) 10.23 ± 1.68 10.05 ± 1.48 6.67 ± 1.44 <0.001 FSH (IU/l) 6.55 ± 1.38 6.45 ± 1.25 5.56 ± 1.32 <0.05 LH/FSH ratio 1.70 ± 0.76 1.73 ± 0.92 1.30 ± 0.60 <0.05 Free testosterone (pg/ml) 17.57 ± 2.31 14.97 ± 2.19 4.21 ± 2.50 <0.001 Insulin resistance indices HOMA-IR 4.10 ± 1.78 3.47 ± 1.69 2.22 ± 1.58 <0.001 G/I 5.79 ± 2.90 6.81 ± 3.20 8.49 ± 3.31 <0.001 QUICKI 0.312 ± 0.02 0.319 ± 0.02 0.340 ± 0.022 <0.001 McAuley 3.69 ± 0.85 4.16 ± 1.00 4.76 ± 0.94 <0.001 TyG 4.58 ± 0.20 4.46 ± 0.21 4.34 ± 0.22 <0.001 CPI 8.53 ± 1.79 9.19 ± 1.90 13.01 ± 1.64 <0.05 Data was expressed as Mean ± SD. P < 0.05 is considered significant. Fig. 1 The prevalence of insulin resistance (IR)/sensitivity (IS) based on HOMA-IR in both obese and non-obese PCOS women. TyG index and negative correlation with G/I, QUICKI, McAuley and CPI. HOMA-IR showed significant positive cor- relation with insulin, C-peptide and TyG. While it shows sig- nificant negative correlation with G/I, QUICKI, McAuley and CPI. More details were demonstrated in Tables 2 and 3. McNemar test was performed on both obese/non-obese PCOS women to check the concordance/discordance between insulin resistance indices and HOMA-IR, as shown in Tables 4 and 5. Figure 2 shows the ROC curve for G/I ratio, QUICKI, McAuley, TyG and CPI indices as predictors for HOMA-IR. G/I ratio, QUICKI and McAuley strongly predicted HOMA-IR in both PCOS groups. TyG can be Predicted HOMA-IR in obese PCOS with AUC value of 0.79 (P < 0.05). CPI failed to predict HOMA-IR in both obese/non-obese PCOS, as shown in Table 6. Discussion The issue of IR in PCOS, though seemingly obvious, is indeed highly problematic, when supposed to be transformed from a theoretical concept into a clinical application. Some studied suggested that IR was apparent not in terms of exceeding a predefined cut-off point, but as lack in insulin sensitivity in comparison to BMI-matched non-PCOS.19 It must be noted that there is no universal agreement as to the best cut-off point for various insulin-resistance indices. Thus, any cut-off points should be related to particular studied population, as signifi- cant ethnic differences have been reported (Wijeyaratne et al., 2002).20 172 J Contemp Med Sci | Vol. 8, No. 3, May-June 2022: 169–175 Roles of C-Peptide and Triglyceride as Effective Indices for Insulin Resistance Investigations in Iraqi Women Original H.H. Al-Murshedi et al. Table 2. Pearson correlation analysis (obese PCOS) WC WHR BMI Insulin TG G/I ratio HOMA-IR QUICKI McAuley TyG C-peptide CPI WC r 1 0.78 0.68 0.32 .266 0.51 0.32 0.48 0.50 0.35 .128 –.234 P .000 .000 .022 .057 .000 .023 .000 .000 .012 .366 .095 WHR r 1 0.39 0.33 .164 0.46 0.32 0.41 0.41 .214 .058 –.075 P .004 .016 .245 .001 .023 .003 .002 .127 .683 .595 BMI r 1 0.56 0.44 0.55 0.57 0.60 0.61 0.48 0.41 0.4 P .000 .001 .000 .000 .000 .000 .000 .002 .004 Insulin r 1 0.48 0.83 0.99 0.88 0.79 0.49 0.7 0.54 P .000 .000 .000 .000 .000 .000 .000 .000 TG r 1 0.49 0.48 0.50 0.82 0.96 0.35 0.33 P .000 .000 .000 .000 .000 .010 .018 G/I ratio r 1 0.81 0.94 0.86 0.49 0.48 0.49 P .000 .000 .000 .000 .000 .000 HOMA-IR r 1 0.89 0.79 0.51 0.71 0.56 P .000 .000 .000 .000 .000 QUICKI r 1 0.87 0.57 0.56 0.61 P .000 .000 .000 .000 McAuley r 1 0.86 0.52 0.55 P .000 .000 .000 TyG r 1 0.38 0.43 P .006 .002 C-peptide r 1 0.72 P .000 CPI r 1 P Yellow color refers to positive correlation, blue color refers to negative correlation. Table 3. Pearson correlation analysis (non-obese PCOS) WC WHR BMI Insulin TG G/I ratio HOMA-IR QUICKI McAuley TyG C-peptide CPI WC r 1 0.57 0.27 –0.07 0.08 –0.04 –0.10 0.08 –0.05 0.06 –0.08 0.07 P .004 .211 .768 .712 .863 .661 .705 .828 .796 .721 .743 WHR r 1 –0.09 –0.15 -.021 –0.12 –0.17 0.007 –0.08 .028 .114 –.088 P .686 .504 .924 .571 .451 .973 .709 .900 .605 .690 BMI r 1 0.69 0.70 0.70 0.66 0.62 0.78 0.63 0.43 –0.21 P .000 .000 .000 .001 .002 .000 .001 .042 .328 Insulin r 1 0.52 0.81 0.99 0.90 0.78 0.49 0.45 –0.37 P .011 .000 .000 .000 .000 .017 .033 .084 TG r 1 0.53 0.49 0.47 0.86 0.96 0.266 –0.2 P .009 .016 .022 .000 .000 .220 .349 G/I ratio r 1 0.79 0.90 0.85 0.48 0.44 0.41 P .000 .000 .000 .020 .037 .050 HOMA-IR r 1 0.93 0.77 0.49 0.47 0.41 P .000 .000 .017 .024 .055 QUICKI r 1 0.81 0.49 0.52 0.53 P .000 .018 .011 .009 (Continued) 173J Contemp Med Sci | Vol. 8, No. 3, May-June 2022: 169–175 H.H. Al-Murshedi et al. Original Roles of C-Peptide and Triglyceride as Effective Indices for Insulin Resistance Investigations in Iraqi Women Table 4. Comparison of insulin resistance indices and HOMA-IR for assessment of IR in obese women with PCOS (cut-off for HOMA-IR > 2.7) IR indices HOMA-IR Total Yes N (%) No N (%) G/I ratio Yes 33 (100%)a 0 (0%)c 33 (73%) No 3 (25%)b 9 (75%)d 12 (27%) QUICKI Yes 36 (100%)a 0 (0%)a 36 (80%) No 0 (0%)b 9 (100%)d 9 (20%) McAuley Yes 35 (97%)a 1 (3%)c 36 (80%) No 1 (11%)b 8 (89%)d 9 (20%) TyG Yes 27 (93%)a 2 (7%)c 29 (64%) No 9 (56%)b 7 (44%)d 16 (36%) CPI Yes 18 (86%)a 3 (14%)c 21 (47%) No 18 (75%)b 6 (25%)d 24 (53%) aTrue positive, bFalse negative, cFalse positive, dTrue negative. Table 3. Pearson correlation analysis (non-obese PCOS)—Continued WC WHR BMI Insulin TG G/I ratio HOMA-IR QUICKI McAuley TyG C-peptide CPI McAuley r 1 0.86 0.42 0.347 P .000 .044 .105 TyG r 1 0.285 –0.23 P .188 .300 C-peptide r 1 0.79 P .000 CPI r 1 P Yellow refers to positive correlation, blue color refers to negative correlation. Table 5. Comparison of insulin resistance indices and HOMA-IR for assessment of IR in non-obese women with PCOS (cut-off for HOMA-IR > 2.7) IR indices HOMA-IR Total Yes n (%) No n (%) G/I ratio Yes 11 (79%)a 3 (21%)c 14 (61%) No 0 (0%)b 9 (100%)d 9 (39%) QUICKI Yes 11 (92%)a 1 (8%)c 12 (52%) No 0 (0%)b 11 (100%)d 11 (48%) McAuley Yes 10 (71%)a 4 (29%)c 14 (61%) No 1 (11%)b 8 (89%)d 9 (39%) TyG Yes 7 (70%)a 3 (30%)c 10 (44%) No 4 (31%)b 9 (69%)d 13 (56%) CPI Yes 8 (62%)a 5 (38%)c 13 (56%) No 3 (30%)b 7 (70%)d 10 (44%) aTrue positive, bFalse negative, cFalse positive, dTrue negative. In current study IR reported to be more prevalent in obese PCOS group than non-obese PCOS, the same finding was recorded previously, who reported that IR in PCOS had linked to obesity.21 Although non-obese women exhibit lower IR is still a common finding in this population. Indeed, several studies have suggested IR as a pathophysiological component independent of weight.22 Obese PCOS have a high probability of IR.23 It was also observed a significant, but relatively weak correlation between all analyzed IR indices and adiposity indices: WC, WHR and BMI in obese PCOS group. Recent studies reported that WHR was positively correlated with the HOMA-IR.24 A study of Šumarac-Dumanović et al., confirmed that PCOS women are more susceptible to increasing WHR regarding the development of insulin resistance.25 In the current study, women with PCOS had higher fasting insulin levels than controls. Similar results were found by another investigators.26 It is also indicated that C-peptide was higher only in obese PCOS. Another study reported that C-peptide concentrations were not reached statistically signif- icant among PCOS overweight group, PCOS obese group and healthy women. Also, it did not correlate significantly with FSH and LH serum levels within studied groups.27 Conversely, another investigators suggested that C-peptide can be used as a surrogate marker of IR in PCOS.28 A study by Banu et al. also indicated that assessment of C-peptide levels, along with HDL-C levels, in patients can be used to monitor IR.29 There is a very good correlation between indices of IR based on fasting glucose and insulin HOMA with G/I and QUICKI, also HOMA has a good correlation with McAuley that utilizes fasting triglyceride concentrations and insulin. Hence, there is an implication that fasting triglyceride concen- trations can be safely used to assess IR, instead of fasting glu- cose. In a previous study by Lewandowski et al., McAuley 174 J Contemp Med Sci | Vol. 8, No. 3, May-June 2022: 169–175 Roles of C-Peptide and Triglyceride as Effective Indices for Insulin Resistance Investigations in Iraqi Women Original H.H. Al-Murshedi et al. Fig. 2 The results of ROC curve analysis regarding the predictability of G/I ratio, QUICKI, McAuley, TyG and CPI indices in classifying the IR considering HOMA-IR in (a) non-obese PCOS and (b) obese PCOS. Table 6. The areas under ROC curve (AUC), sensitivity, specificity by the optimized cut-off points for IR indices in predicting the HOMA-IR Predictors AUC (95% CI) P-value Cut-off value Sensitivity Specificity Obese PCOS G/I ratio 0.04 (0.00–0.09) 0.000 7.37 92% 100% QUICKI 0.00 (0.00–0.00) 0.000 0.33 100% 100% McAuley 0.06 (0.00–0.14) 0.000 4.3 97% 89% TyG 0.79 (0.64–0.94) 0.008 4.51 75% 78% CPI 0.36 (0.14–0.57) 0.182 8.52 50% 66% Non-obese PCOS G/I ratio 0.05 (0.00–0.12) 0.000 7.37 100% 75% QUICKI 0.00 (0.00–0.00) 0.000 0.33 100% 100% McAuley 0.11 (0.00–0.23) 0.001 4.3 91% 66% TyG 0.72 (0.51–0.93) 0.074 4.51 64% 75% CPI 0.34 (0.11–0.57) 0.196 8.52 73% 58% index was found to have a good correlation with HOMA-IR (r = −0.849) in large (n = 478) group of women with PCOS aged 25 ± 8.05, BMI 27.27 ± 7.18 kg/m2 (Lewandowski et al., 2018).30 Kheirollahi et al. suggested that TyG index strongly correlated with IR as estimated by HOMA-IR, among Iranian women diagnosed with PCOS.31 Also, a recent study included 11,378 adults proposed TyG index as a useful surrogate measure of IR (AUC was 0.723) as reported previously.32 C-peptide is accepted as a better descriptor of pancreatic activity than peripheral insulin itself. In the current study, a weak correlation was found between HOMA-IR and C-peptide. Previously, Tura et al. found that an index based on insulin and glucose (IGI) strongly correlated with corre- sponding index for C-peptide, indicating that hepatic insulin extraction is not a confounding factor in the relationship between insulin and C-peptide-based indices.33 Additionally, MJ found that values of fasting glucose, insulin, C-peptide and the HOMA index significantly increased with age and pubertal stage, while the QUICKI index decreased.34 A study by Ohkura et al. revealed that the index CPI was more strongly correlated with glucose infusion rate (GIR) derived from the glucose clamp technique, than were HOMA-IR and QUICKI, as CPI requires a single blood sample and plasma C-peptide levels better reflect insulin bioactivity in skeletal muscle, it was recommend for screening of IR.35 Conclusion It can be concluded that TyG is a valuable indicator to predict IR in obese women with PCOS, partly due to its analytical and financial ease-of-access in all clinical laboratories. The use of TyG index is recommended in the assessment of IR risk among Iraqi women with PCOS. Further epidemiological research is advised. Conflicts of Interest None.  175J Contemp Med Sci | Vol. 8, No. 3, May-June 2022: 169–175 H.H. Al-Murshedi et al. Original Roles of C-Peptide and Triglyceride as Effective Indices for Insulin Resistance Investigations in Iraqi Women References 1. Legro, R. S., Arslanian, S. A., Ehrmann, D. A., Hoeger, K. M., Murad, M. H., Pasquali, R. & Welt, C. K. 2013. Diagnosis and Treatment of Polycystic Ovary Syndrome: An Endocrine Society Clinical Practice Guideline. The Journal of Clinical Endocrinology & Metabolism, 98, 4565–4592. 2. Azziz, R., Woods, K. S., Reyna, R., Key, T. J., Knochenhauer, E. S. & Yildiz, B. O. 2004. The prevalence and features of the polycystic ovary syndrome in an unselected population. The Journal of Clinical Endocrinology & Metabolism, 89, 2745–2749. 3. Fauser, B. C., Tarlatzis, B. C., Rebar, R. W., Legro, R. S., Balen, A. 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