Original Article |
Corresponding author: Muhammad Raza Sarfraz ( mrazasarfraz@outlook.com ) © 2024 Huma Salahuddin, Rehana Rehman, Sadia Rehman, Muhammad Raza Sarfraz, Raheela Rafiq, Fatima Rehman.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Salahuddin H, Rehman R, Rehman S, Sarfraz MR, Rafiq R, Rehman F (2024) Does insulin-like growth factor-I level associate with pregnancy outcomes in primary and secondary infertile women undergoing in vitro fertilization? A prospective cohort study. Folia Medica 66(4): 481-490. https://doi.org/10.3897/folmed.66.e125587
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Background: Infertility, which affects 8%–12% of couples worldwide and 21.9% of couples in Pakistan in particular, is a major reproductive health issue. In vitro fertilization (IVF) has emerged as a prevalent therapeutic intervention. Recent studies have identified insulin-like growth factor-I (IGF-I) as a promising biomarker for assessing embryo viability and predicting implantation outcomes in IVF procedures.
Objective: To evaluate the relationship between IGF-I levels and IVF outcomes in women with primary and secondary infertility.
Materials and methods: This prospective cohort study included 133 infertile women (99 with primary infertility and 34 with secondary infertility) aged 20-45 years. IGF-I levels were measured using an ELISA kit. Participants were grouped based on infertility type and cause of infertility. Statistical analyses included the Mann-Whitney U test, Pearson chi-square test, Kruskal-Wallis test, and Pearson correlation coefficient.
Results: Women with secondary infertility had significantly higher IGF-I levels compared to those with primary infertility (279.40±85.89 ng/ml vs. 239.11±74.55 ng/ml, p=0.02). Male factors were the predominant cause of infertility in both groups. Patients with male-factor infertility had the highest IGF-I levels (267.1±77.6 ng/ml). Significant positive correlations were found between IGF-I levels and the number of oocytes fertilized (r=0.398, p<0.01), oocytes retrieved (r=0.326, p<0.01), oocytes at metaphase II (r=0.386, p<0.01), and cleaved embryos (r=0.369, p<0.01).
Conclusion: This study demonstrates a positive correlation between IGF-I levels and various IVF outcomes. Higher IGF-I levels were associated with improved oocyte retrieval, fertilization, and embryo development.
embryo development, infertility, insulin-like growth factor-I, in vitro fertilization, oocyte quality
According to the World Health Organization (WHO), the clinical debility of a couple to achieve pregnancy within or after 12 months of regular sexual intercourse without using any contraceptive method is termed infertility.[
Globally, people use assisted reproductive technologies (ART) like in vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI) to treat infertility. Numerous factors affect the likelihood of clinical pregnancy outcomes in ART. Securing a suitable embryo for implantation depends on various internal and external factors, with the female hormonal environment playing a crucial role.[
This study aims to evaluate the outcomes and cost-effectiveness of IVF by assessing IGF-I levels in women with primary and secondary infertility. It seeks to understand IGF-I’s role in predicting successful pregnancy outcomes, including the number of eggs retrieved and the quality of embryos. The findings have the potential to inform and influence IVF treatment decisions, thereby reducing costs and minimizing the risks associated with redundant interventions.
This was a prospective cohort study that was conducted in collaboration with the Basic Medical Sciences Institute and Jinnah Postgraduate Medical Centre at the Australian Concept Infertility Clinic in Karachi for a period of 12 months. The Open Epi calculator was used to determine the sample size. Based on an expected sensitivity and specificity of 80%, a 5% margin of error, and a 95% confidence level, the required sample size was calculated to be 133.
During data collection, samples were chosen using a convenient sampling technique. After securing consent, study subjects were categorized into two groups depending on the causes and manifestations of infertility. One hundred thirty-three infertile females of the age group 20–45 who had been infertile for more than two years and had a regular ovulation cycle (duration: 25–35 days) with no abnormalities in the morphology of either of the two ovaries were included in the study. Women under 20 and over 45 years of age who previously failed IVF/ICSI and had ovarian pathologies or endometriosis were excluded from the study.
We performed a full family history check and general medical examination on both partners to rule out likely causes of infertility. For the study, we used an IGF-I ELISA kit to measure IGF-I levels in lab samples. This kit uses a sandwich ELISA method. The kit’s product number was SEA050Hu, and it could detect IGF-I levels between 0.19 and 12 ng/ml.
We divided the participants into two groups, group A1 and group A2, based on their type of infertility according to the WHO definition of infertility. Group A1 included women with primary infertility. Group A2 consisted of women with secondary infertility. Fig.
The study procedure followed the ethical guidelines of the institutional and national research committees, as well as the Helsinki Declaration. JPMC’s institutional review committee granted ethical authorization, and all subjects provided informed consent. The information gathered throughout the research was kept entirely confidential.
The data were analyzed using IBM SPSS 23.0. Mean and standard deviation were presented for quantitative data, while percentages and counts were reported for qualitative variables. The Mann-Whitney U test was used to compare age, BMI, duration of infertility, and IGF-I levels between primary and secondary infertility. The Pearson chi-square test assessed the association between the type and causes of infertility. The Kruskal-Wallis test was used to compare age, BMI, and IGF-I levels across different causes of infertility, with post hoc analysis using Tukey’s HSD test for BMI and IGF-I levels. The Pearson coefficient of correlation was used to measure the strength of the relationship between IGF-I, the number of oocytes fertilized, the number of oocytes retrieved, the number of oocytes in metaphase II, and the number of cleaved embryos. P-values ≤0.05 were considered statistically significant. Scatter plots were used to depict the correlations between IGF-I levels and other variables.
Among the 133 samples, 99 females had primary infertility (A1), while 34 had secondary infertility (A2). The mean age, BMI, and duration of infertility among group A1 and A2 are shown in Table
Fig.
Table
Table
Linear regression analysis shows a positive relationship between IGF-I levels and various reproductive outcomes, such as the number of oocytes retrieved, fertilized, at metaphase II, and embryos cleaved (Fig.
Comparison of quantitative characteristics between the types of infertility
Characteristics | A1 (n=99) | A2 (n=34) | p-value | ||
Mean | SD | Mean | SD | ||
Age | 31.51 | 4.45 | 32.59 | 4.41 | 0.37 |
BMI (kg/m2) | 25.88 | 2.72 | 25.35 | 3.14 | 0.57 |
Duration of infertility (years) | 5.21 | 3.92 | 6.76 | 5.03 | 0.12 |
IGF-I (ng/ml) | 239.11 | 74.55 | 279.40 | 85.89 | 0.02* |
Parameters | Cause of infertility | p-value | |||||
Male factors (n=87) | Female factors (n=28) | Unexplained (n=18) | |||||
Mean | SD | Mean | SD | Mean | SD | ||
Age | 31.59 | 4.00 | 32.11 | 6.15 | 32.22 | 3.52 | 0.38 |
BMI | 26.08 | 2.99 | 24.50 | 1.90 | 26.06 | 2.84 | <0.01* |
IGF-I | 267.1 | 77.6 | 232.6 | 46.5 | 190.0 | 95.2 | <0.01* |
Multiple comparisons of significant characteristics across causes of infertility
Parameters | Comparison | Mean difference | p-value |
BMI | Male factors vs. Female factors | 1.58 | 0.02* |
Male factors vs. Unexplained | 0.02 | 0.99 | |
Female factors vs. Unexplained | −1.56 | 0.15 | |
IGF-I | Male factors vs. Female factors | 34.44 | 0.09 |
Male factors vs. Unexplained | 77.04 | <0.01* | |
Female factors vs. Unexplained | 42.60 | 0.15 |
Correlation analysis of IGF-I and various reproductive parameters using Pearson correlation
Parameters | IGF-I | No of oocytes fertilized | No of oocytes retrieved / patient | No of oocytes metaphase II | |
IGF-I | r | 1 | |||
p | |||||
Number of oocytes fertilized | r | 0.398 | 1 | ||
p | <0.01* | ||||
Number of oocytes retrieved / patient | r | 0.326 | 0.933 | 1 | |
p | <0.01* | <0.01* | |||
Number of oocytes metaphase II | r | 0.386 | 0.989 | 0.953 | 1 |
p | <0.01* | <0.01* | <0.01* | ||
Number of cleaved embryos | r | 0.369 | 0.99 | 0.932 | 0.984 |
p | <0.01* | <0.01* | <0.01* | <0.01* |
Correlation of IGF-I with various reproductive parameters. A) Correlation between IGF-I levels and the number of oocytes retrieved; B) Correlation between IGF-I levels and the number of oocytes fertilized; C) Correlation between IGF-I levels and number of oocytes in metaphase II; D) Correlation between IGF-I levels and number of embryos cleaved.
Infertility is emotionally and mentally challenging. WHO ranks it as the fifth most serious disability worldwide. While infertility has many causes, advancements in ART methods, particularly IVF and ICSI, have increased hope for couples seeking help.[
Most participants in our study had primary infertility. We found no significant differences in age, BMI, or infertility duration between primary (A1) and secondary (A2) infertility groups. However, IGF-I levels were significantly higher in group A2. Male factors were the main cause of infertility in both groups. We found no significant association between infertility type and cause. Patients with male factor infertility had higher IGF-I levels compared to those with female factor or unexplained infertility. We observed an inverse relationship between BMI and IGF-I levels, with lower BMI subjects showing higher IGF-I concentrations. Statistical analysis revealed a significant difference in BMI between male factor and female factor infertility groups (p=0.02). The results of our study show that the IGF-I levels positively correlated with the number of oocytes fertilized, retrieved, at metaphase II, and cleaved embryos. Linear regression analysis showed positive relationships between IGF-I levels and these reproductive outcomes. These findings highlight IGF-I’s potential role in reproductive outcomes, particularly in male factor infertility, and suggest that higher IGF-I levels may benefit certain reproductive parameters.
Our findings align with those of Afradiasbagharani et al., who suggest a positive role for IGF-I in ovulation and folliculogenesis regulation.[
However, Imterat et al. reported no association between IGF-I levels and pregnancy rate.[
This study demonstrates a significant positive correlation between IGF-I levels and various IVF outcomes, including oocyte retrieval, fertilization, and embryo development. Women with secondary infertility showed higher IGF-I levels than those with primary infertility, and patients with male factor infertility had the highest levels. These findings support the potential use of IGF-I as a biomarker for predicting IVF success, which could lead to more personalized and cost-effective treatments. However, the relatively low R² values indicate that IGF-I levels alone cannot fully predict outcomes, highlighting the complexity of fertility. Future research should focus on standardizing protocols, establishing definitive IGF-I thresholds, and exploring its use in combination with other biomarkers. These results contribute to our understanding of IGF-I’s role in reproductive biology and represent a step towards more personalized fertility treatments, potentially improving IVF success rates and offering new hope to those struggling with infertility.
The use of a convenient sampling technique and conducting the study at a single center may limit the generalizability of the findings. The lack of long-term follow-up precludes assessment of the sustained impact of IGF-I levels on pregnancy outcomes. Potential confounding factors, such as lifestyle and genetic predispositions, were not fully accounted for, which could influence the results. The study’s focus on only IGF-I, along with the relatively low R² values, shows that a multifactor approach is needed to better predict IVF outcomes. Financial constraints prevented the inclusion of other biomarkers, which could have provided a more comprehensive analysis. Future research should include multi-center studies, longitudinal follow-up, and combined biomarker analysis to enhance predictive accuracy and applicability.
The authors express their gratitude to the patients who generously gave their time and participated in this study.
The authors declare no conflicts of interest.
This paper has been derived from Dr. Huma Salahuddin M. Phil. thesis.
None.
Conceptualization: Huma Salahuddin, Rehana Rehman, Sadia Rehman, and Muhammad Raza Sarfraz; writing of initial drafts: Huma Salahuddin, Sadia Rehman, and Muhammad Raza Sarfraz; review and editing: Raheela Rafiq, Fatima Rehman, and Muhammad Raza Sarfraz; project supervision: Rehana Rehman, Huma Salahuddin, and Sadia Rehman; data curation: Raheela Rafiq and Fatima Rehman; software: Muhammad Raza Sarfraz; data analysis: Huma Salahuddin, Sadia Rehman, and Muhammad Raza Sarfraz; resources: Huma Salahuddin, Sadia Rehman, and Muhammad Raza Sarfraz. All authors approved the final manuscript before submission to the journal.