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Usefulness of metabolic score for insulin resistance index in estimating the risk of mildly reduced estimate glomerular filtration rate: a cross-sectional study of rural population in China

Objectives This study aimed to reveal the association between metabolic score for insulin resistance (MetS-IR) and the risk of mildly decreased estimated glomerular filtration rate (eGFR), and explore the evaluation effect of MetS-IR on the progress of eGFR decline. Study design A cross-sectional study. Setting and participants A total of 11 956 rural participants (aged ≥35 years) from northeastern China were enrolled in the study. After excluding the subjects whose data were not integrated or who met the exclusion criteria, we finally obtained 11 042 participants in the present study. Main outcome measures Mildly decreased eGFR was defined as 60–90 mL/min/1.73 m2. Results The prevalence of mildly decreased eGFR in the general population was 36.9%. After adjustment of covariates, each SD increment of MetS-IR could bring 26.3% additional risk of mildly decreased eGFR (OR: 1.263, 95% CI: 1.066 to 1.497, p=0.007). When MetS-IR was classified into four levels by quartile, we observed participants in the top level had 3.032-fold risk of mildly decreased eGFR (OR: 3.032, 95% CI: 1.841 to 4.991, p<0.001) compared with those from the bottom level. Further, we found the participants with higher MetS-IR score were more likely to aggravate into a worse renal state which presented as higher risk of accelerated decline of eGFR, by additional 28.3% risk in whole participants (OR: 1.283, 95% CI: 1.150 to 1.430, p<0.001) and 41.9% in men (OR: 1.419, 95% CI: 1.183 to 1.701, p<0.001). Conclusion High MetS-IR was associated with high risk of mildly reduced eGFR and often accompanied by a high risk of accelerated decline in eGFR. Hence, we believed MetS-IR was a suitable indicator to evaluate the risk of early-stage renal dysfunction.

. If a reader watches table 1, it is unclear to what "mildly reduced" is referred. Please, describe better the information on the table in the title and in the legend. Discussion. The Authors discussed the "U-shaped" risk curve relative to eGFR and Mets-IR with a survivor bias. However, other papers published in two pediatric cohorts (doi.org/10.1371/journal.pone.0193755; doi.org/10.1002/oby.20497) observed the same effect and in this case, a survivor bias is not consistent. Please, discuss more this point in light of the results of these papers.

REVIEWER
Flores-Guerrero, Jose L. University of Groningen, Internal Medicine Introduction 3. A brief description of previous studies analyzing proxys of insulin resistance (with out actually measuring insulin) is needed, particularly in the same population. Methods 4. Please change the term "multivariate" for multivariable as it seems to be the case. 5. Please notice that categorizing the independent variable Mets-ir (creating cuartiles) introduces a big risk of bias to your study, please avoid it. 6. It is of major importance to compare the performance of this metric Mets-ir to already existing metrics, for instance, and at least triglyceride-glucose index. Please provide a ROC curve analysis to show the performance of the 2 metrics, using both metrics as continuous variables (please do not dichotomize it or create cuartiles, given the fact that you lose information, introduce bias, and reduces the chance to extrapolate information), in the same analysis evaluate your outcome (egfr) as a continuous variable. 7. Provide information about the missing data; how much data was missing? How it was treated? Do all the 11 042 subjects have full data available? Results 8. Table 3 shows that this metric "MetS-IR" actually have a poor performance, with a very close to 1 lower CI boundary. The metric is not even associated in the males group. This, considering the relatively big sample of the study suggest that this metric may not be adequate for this population. I encourage the author to rigorously explore the usefulness of the metric within their population, please notice that for the critical study of all the new proposed metrics, negative results have the same value as positive results; do not feel the pressure to report a positive association (for example categorizing the variable and dividing the dataset in subgroups to find a positive association). 9. Page 11 reads "Meanwhile the objects with reduced eGFR were lacked of physical activities and they had a larger WC and greater degree of IR manifested as a higher MetS-IR." Please notice that people are not objects! Please correct it. 10. In figure 1 reads: "we finally got a study population with 11042 objects." Please notice that people are not objects! Please correct it.
Discussion 11. Table one shows that this metric "MetS-IR" has a small difference among the 2 groups 36.46±7.72 vs 37.59±7. 33 with standard errors that clearly cross each other groups. The goal of this study would be to evaluate whether this metric could actually reflect a clinical difference. Please discuss it. 12. The paragraph about TNF-alfa and SIPR-alpha (page 18) seems a little bit out of context, and it seems more like a harking, please consider avoiding it. 13. Page 17 reads: "Our results indicated that people with higher MetS-IR tended to show a higher risk of mildly reduced eGFR, and the progression of eGFR deterioration was more rapid." This seems to be an overstatement. Please notice that this study does not provide any foundation to evaluate "progression of eGFR deterioration", since it includes only 1 timepoint date (as the authors have properly acknowledged) there is no basis to judge the progression of eGFR. Please adapt it.

Reviewer1:
First of all, we'd like to express our heartfelt thanks to you for your guidance and we totally agree with your suggestion. With your guidance, we revised the relevant issues in the manuscript, which greatly improved the quality of the article. Once again, we thank you for giving us such meticulous help in this article.
Abstract: Please, insert the CI95% of the OR.
Reply: Thank you for your helpful advice and I'm sorry for our negligence. Accordingly, we have supplemented and improved the complete information of the relevant data in the Abstract Section as following:  21 . Therefore, we believed it wa<="" span="" style="font-family: "Times New Roman"; color: rgb(255, 0, 0);">unvalidated cut-off value to divide participants into different IR subgroups in our study. Meanwhile, we also couldn't sufficiently compare and improve our findings with other related studies which focused on MetS-IR. We still need large-scale, less bias, high-level evidence-based studies to confirm the relationship between MetS-IR and mildly reduced eGFR." Thank you again for your useful help; we hope that our corrections will meet with your satisfaction and approval.
Some typos are presents. Please, substitute "objects" with "subjects". Line 352 crosssectional (instead of cross-sectionalal) and other. Please, check all the manuscript.
Reply: Thank you for your comment and I'm really sorry for our negligence. We carefully checked our manuscript and corrected the typos. Once again, we apologized for our negligence and thank you for giving us such meticulous help in this article.
Please, specify what is BUN for non-expert on the topic.
Reply: Thank you for this useful comment and your advice led us to realize some necessary improvements to our manuscript. We completely agree with your valuable suggestions, so we thus added this important point in the first paragraph of Introduction Section as following.
"BUN(blood urea nitrogen), Scr(serum creatinine) and eGFR are usually used to evaluate renal function. BUN is the decomposition product of protein in the human body. Normally, it can be filtered out of the body through the kidney and maintained in a stable range, but the CKD patients usually present an elevated BUN levels due to deficiency renal functional. Meanwhile, the BUN levels can be greatly affected by various factors such as the consumption of hormone drugs, heart failure and obesity. Creatinine is the product of muscle metabolism in the human body which is mainly excreted through kidney as well. Under renal dysfunction conditions, creatinine can't be discharged through glomerular filtration, leading to the level of creatinine in blood will increase in serum.
However, Scr levels are also affected by age, race, gender and BMI. Considering that  Reply: First, we would like to express our heartfelt thanks to you for your guidance and we completely agree with your suggestion. We improved the subgroup name from "mildly reduced" to "mildly reduced eGFR" and also added the definition of normal group and mildly reduced eGFR in the legend of Table 1. Reply: We appreciate the valuable advice that you provided which led us to realize some necessary improvements to our manuscript. We fully studied and compared the above two studies mentioned, combined with our research, we further analyzed the similarities and differences in detail in the Discussion Section which as following:

Discussion. The Authors discussed the "U-shaped" risk curve relative to eGFR and Mets
"Additional, we unexpectedly found that the relationship between increased MetS-IR and the risk of mild eGFR reduction in male participants was "inverted U-shaped". This phenomenon seems to be inconsistent with some previous results 19 20 . These two studies also observed the relationship between IR and eGFR, but the risk curves were presented as "U-shape" which was different with ours. We analyzed the differences might be brought by our research objectives. To evaluate the state of pre-renal failure state, we set the event as a slightly decreased eGFR, leading to our study didn't contain low eGFR population. Secondly, we had different category methods which we simply grouped according to the quartile, while the above research divided the population according to the percentage. These two classification methods have their own advantages and suitable population, which made our results were different in the description of population characteristics. Finally, we further compared and found that we have different research population. We obtained the conclusion from the male adult population, and the above two studies were carried out in the adolescent population (age< 18years). It was generally believed that the adolescent population have better compensatory function. Except for the too high or too low level of IR or eGFR, the disease risk of the rest population was low and stable, Therefore, it presented a "U-shaped" disease risk curve, while the adult population gradually showed an irreversible process with the development of the disease.
Therefore, the high-risk population or boundary population were easier to further develop and deterirate into renal failure state, resulting in our results presented survivor bias and thus we got an "inverted U-shaped" risk curve. To confirm our speculation, so we further divided the slightly decreased eGFR level into three states of gradual aggravation, and evaluated the ability of MetS-IR to describe the progress of eGFR by multivariate ordinal regression. The results showed that high level of MetS-IR was significantly associated with deterioration of eGFR, and the highest risk was 3.146 times. Some studies also found IR level could affect eGFR declined progress, the renal dysfunction patients with lower HOMA-IR had slower development of CKD 22 23 . Therefore, we believed that the higher the MetS-IR in men, the greater the decline of eGFR and the higher the risk of further deterioration of kidney disease. In this study, the renal function of male population with high MetS-IR could rapidly develop into renal failure or even death, which reduced the number of people with nildly decreased eGFR, resulting in survivor bias, and eventually led to an "inverted U-shaped" risk curve."

Reviewer2:
Too many thanks for your guidance and we totally agree with your suggestion. Your advices have led us to realize what remains to improve on our study. We reflect on and discuss your questions. Under your guidance, we have revised as following: Abstract.

Please rephrase the concept of eGFR decline, given the fact that this study only provides 1time measurements.
Reply: Too many thanks for your guidance which led us to realize what remains to improve on our manuscript. Our study only enrolled 1-time renal function measurement, so we rephrase the participants whose eGFR ranged from 60-90 ml/min/1.73m 2 as random mildly reduced eGFR, and corrected related content in the manuscript.
On the other hand, we supplemented the related contents in the Limitations Section as following: "Our study also had some limitations. First, this study was a cross-sectional study, which determined that our results had a weak evidence-based efficacy and therefore we couldn't draw a clear causal association between MetS-IR and mildly reduced eGFR. Moreover, our study defined random mildly Reply: Thank you for your attention to this issue and too many thanks for this comment. I'm very sorry that we didn't explain it in detail which made you confused, and we explained the reasons and modified the related contents in Abstract Section as following: In the male participants, we found that the risk of mildly reduce eGFR presented an "inverted U- And we modified the related content in "Abstract Section" as following: "Further, we found the participants with higher MetS-IR score were more likely to aggravate into a worse renal states which presented as higher risk of accelerated decline of eGFR, by  Reply: Thank you for your valuable comment which led us to realize some necessary improvements to our manuscript, and we modified the introduction and supplemented related content in the Introduction Section as following: "Among the variable methods to assess IR, the gold standard method is hyperinsulinemic / euglycemic clamp (HEC) 24  with traditional insulin indexes. Some studies indicated TyG could predict coronary artery calcification progression and coronary atherosclerosis better than HOMA-IR 27 28 , and even had better evaluation effect than HEC method in males 29 . And some research also believed MetS-IR could effectively identify the early hypertensive population 5 , especially for patients with dyslipidemia 30 . And compared with HEC method, MetS-IR was more effective in predicting the risk of type 2 diabetes 10 and ischemic heart disease 31 . Taken together, increasing evidences suggested that it was suitable for these novel indicators to replace the traditional insulin indexes to evaluate the IR level. Among the above three indicators, MetS-IR involved more lipid types and evaluated metabolic status more comprehensive which made it could represent metabolic status and IR status respectively, leading to MetS-IR was recognized as a validated index for the estimation of IR in a Chinese population [5][6][7][8][9] and able to evaluate IR states more stable and accurate than the others which also confirmed by some chronic disease studies [10][11][12] . Hence, we speculated that MetS-IR might be an independent risk factor for mildly reduced eGFR. In this study we tried to use MetS-IR to evaluate the risk of mildly reduced eGFR and describe the trend of eGFR change, so that we could achieve the early detecton of people with mild eGFR reduction and delay the transition progress of them into CDK CKD." Thank you again for your advice, we hope our improvement could meet your satisfaction and approval.

Please change the term "multivariate" for multivariable as it seems to be the case.
Reply: First, we would like to express our heartfelt thanks to you for your guidance and completely agree with your suggestion. Accordingly, we corrected the related typos in the manuscript.

Please notice that categorizing the independent variable Mets-ir (creating quartiles)
introduces a big risk of bias to your study, please avoid it.
Reply: Thank you for your careful and responsible review. I'm very sorry that we didn't explain it in detail which made you confused, and we explained the reasons in following: Under the guidance of previous studies, the present study conducted analyzed the impact of MetS-IR under continuous variable condition and category variable condition, which inevitably brought some bias. However, we have further analyzed the bias and tried to reveal the internal mechanism which presented some strengths and limitations of this study compared with previous.
Lastly, we would like to express our heartfelt thanks to you for your guidance and valuable advice, we really hope our explanation could meet your satisfaction and approval.

It is of major importance to compare the performance of this metric Mets-ir to already existing metrics, for instance, and at least triglyceride-glucose index. Please provide a ROC curve analysis to show the performance of the 2 metrics, using both metrics as continuous variables (please do not dichotomize it or create cuartiles, given the fact that you lose information, introduce bias, and reduces the chance to extrapolate information), in the same analysis evaluate your outcome (egfr) as a continuous variable.
Reply: We appreciate the valuable advice that you provided. Accordingly, we enrolled 3 traditional non-insulin indicators, TyG, TG/HDL-C and MetS-IR, further conducted AUC analysis to describe performance of these non-insulin indicators and compare with each other. The results were summarized in Figure S1 and Table S1 as following. We found TyG had the best performance for   Finally, we're grateful to your concern about this issue and for your careful review, we hope our explanation could meet your satisfaction and approval.

Provide information about the missing data; how much data was missing? How it was treated? Do all the 11 042 subjects have full data available?
Reply: Thank you very much for your attention to the issue of missing data, and I'm very sorry that we didn't explain it clearly in the "Study population Section" which made you confused.
In summary, we had totally 14016 original individuals, we excluded all the 2503 participants who had missing data from our present study by two steps, and finally we further excluded 472 renal failure patients. Hence, we had 11042 study population in the present research who all had full data available.
And in detail, our study totally enrolled 14016 individuals in northeast of China rural regions.
Secondly, we found there were 2060 participants whose data was incomplete or met our exclusion criteria, we thus excluded these part participants apart from our research. Further, we screened the related variables that involved into our present study, and we found 442 subjects had missing values, so we excluded these part participants. And based on this study population, we also excluded 472 patients whose eGFR below 60 ml/min/1.73m 2 . Finally, we obtained 11042 subjects with full available data in the present study. Table 3  Reply: Thank you for your attention to this issue. I'm sorry we didn't elaborate it clearly which made you confused. And we now discuss this topic in detail as following:

8.
In summary, the results of Table2 depicted the relationship between MetS-IR and mildly reduced eGFR, and the results of Table3 were just used to explain the "inverted U-shaped" risk curve presented in Table2, not to reveal the correlation between insulin resistance and eGFR.
Firstly, we conducted logistic regression analysis to reveal the potential association between MetS-IR and early stage renal dysfunction which presented as mildly reduced eGFR in the whole population and gender subgroups (Table2). And we found there was no association only in the male participants, which made the lower limit of 95% CI was close to 1.0 in the whole population.
Meanwhile, we found the risk curve in males was also different from the whole participants or females, which presented "inverted U-shape". To find out the potential mechanism of decreased risk in the highest MetS-IR quartile, we performed the ordinal regression analysis to reveal whether the participants with high MetS-IR score would have a higher risk of deteriorating into renal failure which was characteristic as accelerated decline of eGFR. The results in Table3 were consistent with our conjecture that the participants with high MetS-IR score do indeed have a faster deterioration rate and a higher risk of aggravating renal injury, which the eGFR level was more likely to develop into a worse renal function state from a mildly state especially in the males (OR: 1.419, 95%CI: 1.183-1.701).
Moreover, we also observed the males in 4 th quartile had highest risk of aggravating, leading to these participants were more likely to become renal failure (eGFR< 60 ml/min/1.73m 2 ) and eventually we observed the risk of mildly reduced eGFR was decreased in this quartile. The results of Table3 were the explanation of the potential mechanism of the "inverted U-shap" risk curve in Table2.
Lastly, we completely agree with reviewer that the negative results had the same value as the positive results, and we performed subgroup analysis of the population not to pursue positive results, but to explore the potential causes of abnormalities. And once again, we're grateful to your concern about this issue and for your careful review, we hope our explanation could uncover your confusion. Reply: We would like to express our heartfelt thanks to you for your comment which we completely agree and I'm really sorry for our negligence. We checked our manuscript and corrected the mistakes.
10. In figure 1 reads: "we finally got a study population with 11042 objects." Please notice that people are not objects! Please correct it.
Reply: Once again, we thank you for your suggestions and apologize for our carelessness and mistakes. We carefully proofread our manuscript and corrected the corresponding problems. Finally, we apologize for our mistakes and sincerely thank you for your suggestions

Please discuss it.
Reply: Thank you for your attention to this issue and too many thanks for this comment. I'm very sorry that we didn't explain it in detail which made you confused, and we explained the reasons and supplemented the related content before the Strengths and Limitations Paragraph in the Discussion Section as following: "Besides, we noticed the standard errors of MetS-IR were crossed between two subgroups in males and we believed that these were caused by characteristic of the subgroups. In the subsequent analysis, we found that the male subjects with higher MetS-IR score usually had a higher risk and deterioration rate of declining eGFR, which were more likely to develop into renal dysfunction from early renal failure. Therefore, there would cause survivor bias in the subgroup of male population with high MetS-IR, leading to the standard errors of MetS-IR in this subgroup were lower than others and eventually even presented an "inverted U-shaped" risk curve. higher MetS-IR score may have a higher risk of having early-stage renal dysfunction and accelerated trend of eGFR decline than the patients with lower MetS-IR score, and we didn't try to use this index to directly evaluate the level of renal function to instead of eGFR. Therefore, we suggested to pay more attention to the renal function of patients with high MetS-IR score, to detect the patients in early stage of CKD in time which presented by random mildly reduced eGFR." Thank you again for your review and valuable comment, we hope that our explanation and improvement will eliminate your confusion and meet your approval.

The paragraph about TNF-alfa and SIPR-alpha (page 18) seems a little bit out of context,
and it seems more like a harking, please consider avoiding it.
Reply: Thank you for your valuable advice which led us to realize some necessary improvements to our manuscript, and we completely agree with your comment. We modified the related content and made them more suitable and logical in the Discussion Section and as following: "Some epidemiology studies have found that IR and hyperinsulinemia were involved in the development of chronic renal dysfunction and ESRD 33 34 , even in the early-stage of CKD population which presented mildly reduced GFR 35 . And IR states could effectively evaluate eGFR levels and predict the risk of complications in renal failure patients 36 37 . Meanwhile, some studies revealed various potential mechanism between the IR and development of CKD. They believed IR or hyperinsulinemia could change the structurand function of vascular, such as endothelial injury and increased vascular permeability, resulting in glomerular ultrafiltration and excessive mesangial proliferation which eventually led to the decrease of eGFR 38-40 . On the other side, some studies also observed increased IR states could be regulated via over-activated inflammatory response in the CKD Reply: Thank you for your valuable advice which we completely agree. We re-wrote the conclusion in the first paragraph of Discussion Section as following: "This study revealed for the first time the relationship between IR and eGFR in rural population of northeast China. Our results indicated that people with higher MetS-IR tended to show a higher risk of early-stage renal dysfunction. Moreover, we also observed that high MetS-IR score was usually accompany with a higher risk of accelerating decline of eGFR, especially in male population. These results suggested that we should pay more attention to the renal function of patients with high MetS-IR. Furthermore, the patients with high MetS-IR scores and already accompanied by random mildly reduced eGFR should be intervened as soon as possible tavoid the eventual development of renal failure." We thank you for the meticulous review and we hope that our corrections will meet with your approval.

GENERAL COMMENTS
The Authors answered all criticisms and the paper was improved.
Limitations are clearly described.

REVIEWER
Flores-Guerrero, Jose L. University of Groningen, Internal Medicine REVIEW RETURNED 20-Nov-2021

GENERAL COMMENTS
Thanks to the authors for doing an extensive and well-conducted revision of the manuscript. I have no further comments.