A Simplified Screening Model to Predict the Risk of Gestational Diabetes Mellitus in Caucasian and Latin American Pregnant Women

Round 1

Reviewer 1 Report

Main Question Addressed by the Research:

The main question is how to develop an accurate prediction model for GDM in Caucasian and Latin American pregnant women that takes into account both clinical and genetic risk variables, to see if adding genetic variants to known clinical risk variables (age, BMI before pregnancy) improves GDM prediction accuracy.

Originality and Relevance:

 As to originality and scientific sanity – I think this is acceptable. The topic is extremely relevant and novel in the fields of obstetrics and endocrinology, filling a huge gap in prenatal treatment.

Methodological Improvements:

The study could benefit from more specific information about eating habits and physical activity, both of which can increase GDM risk.
It would be beneficial to investigate the interaction of genetic and environmental factors in greater depth to understand how they can increase or reduce GDM risk.
The Materials and Methods section must appear before the Results section.

Consistency of Conclusions:

The conclusions section appears to be well-written but not exciting. Conclude the article with suggestions for future research in this area.

Minor editing of the English language is required.

Author Response

Main Question Addressed by the Research: The main question is how to develop an accurate prediction model for GDM in Caucasian and Latin American pregnant women that takes into account both clinical and genetic risk variables, to see if adding genetic variants to known clinical risk variables (age, BMI before pregnancy) improves GDM prediction accuracy.

Originality and Relevance: As to originality and scientific sanity – I think this is acceptable. The topic is extremely relevant and novel in the fields of obstetrics and endocrinology, filling a huge gap in prenatal treatment.

We thank the reviewer for the positive view of our manuscript. A detailed point-by-point response to the comments is included below.

Methodological Improvements:

The study could benefit from more specific information about eating habits and physical activity, both of which can increase GDM risk.

We thank the reviewer for this comment, as it will contribute to improve the manuscript. The study design included the evaluation of eating habits using a validated questionnaire based on adherence to Mediterranean Diet (MEDAS)¹. However, we did not find significant differences between groups regarding this feature, so we did not include it in the final statistical models. Unfortunately, we did not have more information regarding diet or physical activity. We will bear in mind this observation for future studies and we have added it as a limitation. Please see lines 353-354: “… Particularly, the effects of the diet and physical activity should be further considered.”

¹Schröder H, Fitó M, Estruch R, Martínez-González MA, Corella D, Salas-Salvadó J, et al. A short screener is valid for assessing Mediterranean diet adherence among older Spanish men and women. J Nutr. 2011;141(6):1140-5. doi: 10.3945/jn.110.135566.

It would be beneficial to investigate the interaction of genetic and environmental factors in greater depth to understand how they can increase or reduce GDM risk.

We agree with the reviewer’s comment. The results from the present study represent a starting point for further investigation. In fact, we are starting a randomized controlled trial to evaluate more precisely the GDM risk according to the interaction between genetic and environmental factors.

The Materials and Methods section must appear before the Results section.

We thank the reviewer for this comment. We have changed the order. Please see the revised version of the manuscript.

Consistency of Conclusions: The conclusions section appears to be well-written but not exciting. Conclude the article with suggestions for future research in this area.

Following the reviewer’s suggestion, we have modified the conclusions. Please see lines 358-362: “In conclusion, adding genetic variants enhanced the prediction model of GDM risk in CAU and LAT pregnant women, facilitating a prompt identification and management of GDM. The present findings could entail modifications in our routine clinical practice. Further studies with larger sample sizes and longer follow-up deem relevant to further confirm our results.”

Comments on the Quality of English Language: Minor editing of the English language is required.

We appreciate the reviewer’s comment. A native English speaker has revised the full manuscript and pertinent changes have been made where appropriate to improve the final version.

Reviewer 2 Report

Dear authors,

Specific Comments:

·       Authors have used FPG at some places in the test, whereas FBG at some. Use common abbreviations.

·       In the abstract, it has been mentioned that “An RCT is underway to demonstrate its usefulness” which is an irrelevant sentence to the current study.

·       In the introduction section, none of the single-nucleotide polymorphism (SNP) related to GDM has been mentioned. Incorporate some literature that exhibits an association between SNPs and GDM, if available.

·       In the methods section, the Exclusion criteria did not reveal the smoking and drinking habits of women, whether they had or not. As these habits are also associated with the risk of GDM. Also, what was the level of insulin in all enrolled women?

·       In the methods section, it has been mentioned that “Genotyping samples were obtained from 1711 (79.4%) women, of which 1645 (96%) were valid. In 1588 (93%), 1069 CAU and 519 LAT, the samples were sufficient to determine > 95 SNPs to be assessed in this study”. Which criteria were used for the validation of 1645 samples? How were 1588 samples selected? Mention properly.

·       In lifestyle evaluation, it has been mentioned that “This questionnaire considers 14 items and evaluates adherence to Mediterranean Diet”. Include the questionnaire in the supplementary documents.

In Genotype analysis, it has been mentioned that “Genomic DNA was extracted from EDTA-stabilized blood samples”. Which method was used for genomic DNA extraction either manual or kit?

Minor editing is required.

Author Response

We appreciate the reviewer’s effort to revise our manuscript and all his/her suggestions and coments.

Specific Comments:

Authors have used FPG at some places in the test, whereas FBG at some. Use common abbreviations.

We thank the reviewer for this comment. We have unified the term throughout the manuscript, leaving it as “fasting plasma glucose” (FPG).

In the abstract, it has been mentioned that “An RCT is underway to demonstrate its usefulness” which is an irrelevant sentence to the current study.

We appreciate this observation. We have deleted this sentence, please see line 42.  

In the introduction section, none of the single-nucleotide polymorphism (SNP) related to GDM has been mentioned. Incorporate some literature that exhibits an association between SNPs and GDM, if available.

We agree with the reviewer’s comment. Accordingly, we have modified the manuscript. Please see lines 64-68: “… Genome-wide association studies (GWAS) have identified single-nucleotide polymorphisms (SNPs) associated with GDM^1,2. SPNs from different genes such as the TCF7L2, GCK, KCNJ11, IGF2BP2, IRS1³, MTNR1B, CDKAL1^2,3 have been linked to higher GDM risk. In addition, some studies evaluated genetic data through genetic risk score (GRS)⁴.”

¹Hayes MG, Urbanek M, Hivert MF, Armstrong LL, Morrison J, Guo C, et al. Identification of HKDC1 and BACE2 as genes influencing glycemic traits during pregnancy through genome-wide association studies. Diabetes. 2013;62(9):3282-91. doi: 10.2337/db12-1692. Erratum in: Diabetes. 2013;62(10):3641.

²Kwak SH, Kim SH, Cho YM, Go MJ, Cho YS, Choi SH, et al. A genome-wide association study of gestational diabetes mellitus in Korean women. Diabetes. 2012;61(2):531-41. doi: 10.2337/db11-1034.

³Zhang C, Bao W, Rong Y, Yang H, Bowers K, Yeung E, et al. Genetic variants and the risk of gestational diabetes mellitus: a systematic review. Hum Reprod Update. 2013;19(4):376-90. doi: 10.1093/humupd/dmt013.

⁴Tian Y, Li P. Genetic risk score to improve prediction and treatment in gestational diabetes mellitus. Front Endocrinol (Lausanne). 2022;13:955821. doi: 10.3389/fendo.2022.955821.

In the methods section, the Exclusion criteria did not reveal the smoking and drinking habits of women, whether they had or not. As these habits are also associated with the risk of GDM. Also, what was the level of insulin in all enrolled women?

We appreciate the reviewer’s comment, since smoking, drinking habits and insulin levels could influence GDM risk. In our sample, the rate of current smokers and pregestational drinkers (between 7-28 g/day) was so low and were not associated with the occurrence of GDM, that it did not allow us to include it in our analysis. Please see the table below for specific details on this issue.

In the methods section, it has been mentioned that “Genotyping samples were obtained from 1711 (79.4%) women, of which 1645 (96%) were valid. In 1588 (93%), 1069 CAU and 519 LAT, the samples were sufficient to determine > 95 SNPs to be assessed in this study”. Which criteria were used for the validation of 1645 samples? How were 1588 samples selected? Mention properly.

Again, we appreciate this comment. We have clarified this sentence in our manuscript. Please see lines 100-104: “Genotyping samples were obtained from 1711 (79.4%) women, of which 1645 (96%) samples were sufficient to determine > 95 SNPs. A total of 1588 (93%) women, 1069 CAU and 519 LAT, were assessed in this study. Fifty-seven women from other minorities (China, Philippines, India, North African, Sub-Saharan Africa) were excluded in this study because of their minimal representation.”

In lifestyle evaluation, it has been mentioned that “This questionnaire considers 14 items and evaluates adherence to Mediterranean Diet”. Include the questionnaire in the supplementary documents.

We appreciate this suggestion. The questionnaire has been previously validated and published¹. We believe in the convenience of citing this article for future details, but if the whole questionnaire were to be fully included in detail, we should request permission to the authors and the editorial. Please see lines 114-115: “The dietary intake and physical activity were evaluated using the 14-point Mediterranean Diet Adherence Screener (MEDAS)¹.”

¹Schröder H, Fitó M, Estruch R, Martínez-González MA, Corella D, Salas-Salvadó J, et al. A short screener is valid for assessing Mediterranean diet adherence among older Spanish men and women. J Nutr. 2011;141(6):1140-5. doi: 10.3945/jn.110.135566.

In Genotype analysis, it has been mentioned that “Genomic DNA was extracted from EDTA-stabilized blood samples”. Which method was used for genomic DNA extraction either manual or kit?

A 16 Maxwell automated DNA extractor (Promega, Switzerland) with its associated Maxwell® 16 Blood DNA Purification Kits was used to extract genomic DNA.

Comments on the Quality of English Language: Minor editing is required.

We appreciate the reviewer’s comment. A native English speaker has revised the full manuscript and pertinent changes have been made where appropriate, to improve the final version.

Reviewer 3 Report

Strengths of the Study: Cohort Diversity: The study included a racially diverse group of white, African American, and Latin American women, therefore ensuring further generalizability of the findings among the different ethnicities. Genetic and Clinical Integration: The attempt to integrate both clinical risk factors and genetic markers into the prediction model for GDM is quite commendable. It falls into the precision medicine approach, whereby medical treatment is offered based on the individual characteristic of a given patient. Solid Methodology: The article gives solid details in the methodology; from the inclusion criteria to the methods used for genotyping. Comprehensive Data Analysis: The other strategy very robust in the process of narrowing down the predictors of GDM employs the use of different forms of logistic regression models to establish the best predictive model both in terms of backward and forward stepwise methods. Areas for Improvement and Consideration: Specificity of the Genetic Variants: Though well analyzed, further elaboration as to why some SNPs were selected and the pathophysiological relevance of these to GDM may strengthen the findings. Whether these are the active pathways in glucose metabolism for these SNPs or related pathways? Clinical Relevance: Translating such statistical significance into clinical relevance would be, for example, how would the presence of these SNPs modify practice. Would it change the timing or nature of screening for GDM or of interventions for prevention or reduction of its complications? Interventional Strategies: While the study suggests early detection and management of GDM, it never tends to make a clear point on the kind of intervention that would be helpful. What would be some preventive measures you would advise that at-risk genetic predisposition for those women? Replication and Validation: The predictions or models developed on this cohort shall be replicated in independent cohorts to validate the prediction prior to deployment of these models in clinical practice. Cost

It would, therefore, be of interest to discuss the costing of genotyping this SNP within the general pregnant population, as it will have implications for setting healthcare policy and resource allocation. Potential Limitations: Generalizability: The fact that the study has been done in a certain geographical area (Madrid) and on two ethnic groups may limit its generalization to other regions and ethnicities. Sample size: although the sample size is large, the article does mention this as one of the limitations and calls for further, larger studies to validate these findings. Larger multi-center studies may provide more conclusive evidence. Environmental Factors: Some detail is likely to be offered by the study into the environmental factors accessed. Many lifestyle-based factors have been found to have an influence on GDM; their interaction with genetics would provide a far more complete assessment of risk. Suggestions for Future Research: Longitudinal Follow-Up: Offspring from mothers with GDM should be followed up longitudinally for long-term outcomes in relation to glucose metabolism. Functional Studies: Thus, functional genomic studies for more insight into how these SNPs actually influence gene expression either independently or together with environmental factors in GDM pathophysiology. Interim trials: The ongoing trial will be of uttermost importance in that it is a randomized controlled trial (RCT) that will show how the use of the genetic risk score applies in actual clinical practice. Results from this should be integrated into guidelines and recommendations. The research thus represents a definable movement toward the knowledge of genetic factors in GDM and offers a predictive model that has promise, which, through further validation, could be used to improve GDM early detection and management.

Author Response

Comments and Suggestions for Authors

Strengths of the Study: Cohort Diversity: The study included a racially diverse group of white, African American, and Latin American women, therefore ensuring further generalizability of the findings among the different ethnicities. Genetic and Clinical Integration: The attempt to integrate both clinical risk factors and genetic markers into the prediction model for GDM is quite commendable. It falls into the precision medicine approach; whereby medical treatment is offered based on the individual characteristic of a given patient. Solid Methodology: The article gives solid details in the methodology; from the inclusion criteria to the methods used for genotyping. Comprehensive Data Analysis: The other strategy very robust in the process of narrowing down the predictors of GDM employs the use of different forms of logistic regression models to establish the best predictive model both in terms of backward and forward stepwise methods.

We thank the reviewer for raising all these interesting points.

Areas for Improvement and Consideration:

Specificity of the Genetic Variants: Though well analysed, further elaboration as to why some SNPs were selected and the pathophysiological relevance of these to GDM may strengthen the findings. Whether these are the active pathways in glucose metabolism for these SNPs or related pathways?

We appreciate this comment and we have modified the manuscript accordingly. We have added a little description of some of the loci with known associations with glycemic traits and gestational diabetes mellitus. We believe  that an extensive description of all the SNPs and pathways involved is beyond the scope of our study, so we have referenced the pertinent previously published literature accordingly. . Please see lines 148-153: “A set of 110 SNPs with known associations with glycemic metabolism and GDM^1-7 were analyzed. Specifically, we selected SNPs from GCKR, TCF7L2, PPARG and IGF-1 genes related to fasting insulin levels and SNPs from PROX1, GCKR, G6PC2, ADCY5, SLC2A2, IGF2BP2, DGKB, GCK, SLC30A8, GLIS3, CDKN2B, ADRA2A, TCF7L2, CRY2, MADD, FADS1, MTNR1B genes linked to fasting glucose levels.¹ A detailed description of the SNPs studied has been previously published⁸.”

¹Manning AK, Hivert MF, Scott RA, Grimsby JL, Bouatia-Naji N, Chen H, et al. A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance. Nat Genet. 2012;44(6):659-69. doi: 10.1038/ng.2274.

²Zhang C, Bao W, Rong Y, Yang H, Bowers K, Yeung E, et al. Genetic variants and the risk of gestational diabetes mellitus: a systematic review. Hum Reprod Update. 2013;19(4):376-90. doi: 10.1093/humupd/dmt013.

³Hayes MG, Urbanek M, Hivert MF, Armstrong LL, Morrison J, Guo C, et al. Identification of HKDC1 and BACE2 as genes influencing glycemic traits during pregnancy through genome-wide association studies. Diabetes. 2013;62(9):3282-91. doi: 10.2337/db12-1692. Erratum in: Diabetes. 2013;62(10):3641.

⁴Huerta-Chagoya A, Vázquez-Cárdenas P, Moreno-Macías H, Tapia-Maruri L, Rodríguez-Guillén R, López-Vite E, et al. Genetic determinants for gestational diabetes mellitus and related metabolic traits in Mexican women. PLoS One. 2015;10(5):e0126408. doi: 10.1371/journal.pone.0126408.

⁵Lowe WL Jr, Scholtens DM, Sandler V, Hayes MG. Genetics of Gestational Diabetes Mellitus and Maternal Metabolism. Curr Diab Rep. 2016;16(2):15. doi: 10.1007/s11892-015-0709-z.

⁶Wu L, Cui L, Tam WH, Ma RC, Wang CC. Genetic variants associated with gestational diabetes mellitus: a meta-analysis and subgroup analysis. Sci Rep. 2016;6:30539. doi: 10.1038/srep30539.

⁷Ding M, Chavarro J, Olsen S, Lin Y, Ley SH, Bao W, et al. Genetic variants of gestational diabetes mellitus: a study of 112 SNPs among 8722 women in two independent populations. Diabetologia. 2018;61(8):1758-1768. doi: 10.1007/s00125-018-4637-8.

⁸Ramos-Levi A, Barabash A, Valerio J, García de la Torre N, Mendizabal L, Zulueta M, et al. Genetic variants for prediction of gestational diabetes mellitus and modulation of susceptibility by a nutritional intervention based on a Mediterranean diet. Front Endocrinol (Lausanne). 2022;13:1036088. doi: 10.3389/fendo.2022.1036088.

Clinical Relevance: Translating such statistical significance into clinical relevance would be, for example, how would the presence of these SNPs modify practice. Would it change the timing or nature of screening for GDM or of interventions for prevention or reduction of its complications?

This is a very interesting point. Based on the reviewer’s suggestion, we have calculated the number of women that might be identified, considering  the addition of genetics to traditional risk factors. . Please see the table below. However, these results are preliminary data and thus, a randomized controlled trail is carrying on in an attempt to translate the present findings into clinical practice.

Number of identified women combining environmental and genetic factors.

BMI; body mass index; FPG, fasting plasma glucose.

*FPG > 82.5 mg/dL in Latin American women.

In addition, a randomized controlled trail is ongoing in an attempt to extrapolate  the present findings to clinical practice. All pregnant women are screened at the beginning of pregnancy using this simplified risk model. The main objective is to identify patients with high risk of developing gestational diabetes mellitus , in order to promptly monitor and establish adequate management. 

Interventional Strategies: While the study suggests early detection and management of GDM, it never tends to make a clear point on the kind of intervention that would be helpful. What would be some preventive measures you would advise that at-risk genetic predisposition for those women?

We appreciate this comment. Our Hospital has well-established gestational diabetes mellitus inpatient unit that provides rapid and close care for women with this condition. Intervention is based on a Mediterranean diet,  including specific eating and physical activity habits. This strategy has proved beneficial effects in this population, as it has been previously published.^1,2 Thus, we hypothesized that an early detection of high-risk women (before 12 gestational weeks) and adherence to Mediterranean lifestyle could lead to a decreased rate of gestational diabetes mellitus and complications. We expect further finsings with the ongoing randomized controlled trial.

¹Assaf-Balut C, García de la Torre N, Durán A, Fuentes M, Bordiú E, Del Valle L, et al. A Mediterranean diet with additional extra virgin olive oil and pistachios reduces the incidence of gestational diabetes mellitus (GDM): A randomized controlled trial: The St. Carlos GDM prevention study. PLoS One. 2017;12(10):e0185873. doi: 10.1371/journal.pone.0185873.

²de la Torre NG, Assaf-Balut C, Jiménez Varas I, Del Valle L, Durán A, Fuentes M, et al. Effectiveness of Following Mediterranean Diet Recommendations in the Real World in the Incidence of Gestational Diabetes Mellitus (GDM) and Adverse Maternal-Foetal Outcomes: A Prospective, Universal, Interventional Study with a Single Group. The St Carlos Study. Nutrients. 2019;11(6):1210. doi: 10.3390/nu11061210.

Replication and Validation: The predictions or models developed on this cohort shall be replicated in independent cohorts to validate the prediction prior to deployment of these models in clinical practice.

We agree with the reviewer’s observation, and we have included it as a limitation of the study. Please see lines 348-350: “Despite the important sample size of our study (1588 pregnant women), studies with larger sample sizes in different cohorts would be needed to validate this GRS model.”

fore, be of interest to discuss the costing of genotyping this SNP within the general pregnant population, as it will have implications for setting healthcare policy and resource allocation.

We truly agree with the reviewer’s comment. We appreciate this suggestion for future studies. We have added it as a limitation. Please see lines 350-351: “Furthermore, a cost-effectiveness analysis might be crucial to implement it on clinical routine practice.”

Potential Limitations:

Generalizability: The fact that the study has been done in a certain geographical area (Madrid) and on two ethnic groups may limit its generalization to other regions and ethnicities.

Thank you for the comment. We have included it as another limitation. Please see lines 354-356: “Finally, our study included only CAU and LAT women. Whether our findings can be generalized and replicated to other ethnic groups deserves further investigation.”

Sample size: although the sample size is large, the article does mention this as one of the limitations and calls for further, larger studies to validate these findings. Larger multi-center studies may provide more conclusive evidence.

We truly agree with his issue, so it was additionaly  noted as a limitation. Please see lines 348-350: “Despite the important sample size of our study (1588 pregnant women), studies with larger samples sizes in different cohorts would be needed to validate this GRS model.”

Environmental Factors: Some detail is likely to be offered by the study into the environmental factors accessed. Many lifestyle-based factors have been found to have an influence on GDM; their interaction with genetics would provide a far more complete assessment of risk.

We appreciate this suggestion. Unfortunately, in the present study, we analysed all the available environmental factors. However,  we are now collecting more parameters, particularly related to diet and physical activity. We have also included it as a limitation. Please see lines 351-354: “In addition, this is an observational study and we adjusted for multiple confounders; however, further underlying confounding factors might still be missed, for instance, regarding the effects of diet and physical activity, which  should be further considered.”

Suggestions for Future Research: Longitudinal Follow-Up: Offspring from mothers with GDM should be followed up longitudinally for long-term outcomes in relation to glucose metabolism. Functional Studies: Thus, functional genomic studies for more insight into how these SNPs actually influence gene expression either independently or together with environmental factors in GDM pathophysiology. Interim trials: The ongoing trial will be of uttermost importance in that it is a randomized controlled trial (RCT) that will show how the use of the genetic risk score applies in actual clinical practice. Results from this should be integrated into guidelines and recommendations. The research thus represents a definable movement toward the knowledge of genetic factors in GDM and offers a predictive model that has promise, which, through further validation, could be used to improve GDM early detection and management.

We want to thank the reviewer for the helpful and encouraging comments and insights, which will derive in a substantial improvement of future studies. We greatly appreciate their expertise and stimulating ideas.

Round 2

Reviewer 1 Report

Accept in present form.

Reviewer 3 Report

I am satisfied by the authors revisions. I recommend the work for publication.