Hostname: page-component-78c5997874-8bhkd Total loading time: 0 Render date: 2024-11-15T11:19:53.479Z Has data issue: false hasContentIssue false

Genetic and Environmental Correlation Analysis of Serum Creatinine Levels in Chinese Twins

Published online by Cambridge University Press:  12 May 2023

Anni Wang
Affiliation:
Department of Epidemiology and Health Statistics, The School of Public Health of Qingdao University, Qingdao, Shandong Province, China
Tianhao Zhang
Affiliation:
Department of Epidemiology and Health Statistics, The School of Public Health of Qingdao University, Qingdao, Shandong Province, China
Jingxian Li
Affiliation:
Department of Epidemiology and Health Statistics, The School of Public Health of Qingdao University, Qingdao, Shandong Province, China
Weijing Wang
Affiliation:
Department of Epidemiology and Health Statistics, The School of Public Health of Qingdao University, Qingdao, Shandong Province, China
Chunsheng Xu
Affiliation:
Qingdao Municipal Centre for Disease Control and Prevention, Qingdao, Shandong Province, China
Haiping Duan
Affiliation:
Qingdao Municipal Centre for Disease Control and Prevention, Qingdao, Shandong Province, China
Xiaocao Tian
Affiliation:
Qingdao Municipal Centre for Disease Control and Prevention, Qingdao, Shandong Province, China
Dongfeng Zhang*
Affiliation:
Department of Epidemiology and Health Statistics, The School of Public Health of Qingdao University, Qingdao, Shandong Province, China
*
Corresponding author: Prof. Dongfeng Zhang; E-mail: zhangdf1961@126.com

Abstract

Almost all creatinine is excreted by the kidney in individuals. Serum creatinine concentration, a widely used renal function index in clinical practice, can be affected by both genetic and environmental factors, as evidenced by current research exploring the relationship between these factors and kidney function. However, few studies have explored the heritability of serum creatinine in Asian populations. Therefore, we explored the genetic and environmental factors that affect the serum creatinine level in Asian populations. Participants in this study came from the Qingdao Twin Registry in China, and 374 pairs of twins were included, of which 139 pairs were dizygotic twins, whose ages ranged from 40 to 80 years old, and the serum creatinine level ranged from 10 to 126 μmol/L. Structural equation models were constructed using Mx software to calculate heritability, with adjusted covariates being age, sex, and body mass index. The results of heritability analysis showed that ACE was the best fit model. Serum creatinine level is influenced by genetic and environmental factors. The result of heritability was 35.44%, and the influence of shared environmental factors accounted for 52.13%. This study provided the relevant basis for future research on genetic and environmental factors affecting serum creatinine levels in Asian populations.

Type
Article
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of International Society for Twin Studies

Creatinine is the result of nonenzymatic dehydration of muscle creatine (Borsook & Dubnoff, Reference Borsook and Dubnoff1947). Some studies have found that serum creatinine concentration is related to cardiovascular disease (Fried et al., Reference Fried, Shlipak, Crump, Bleyer, Gottdiener, Kronmal, Kuller and Newman2003), metabolic syndrome (J. Wang et al., Reference Wang, Li, Han, Yang, Liu, Li, Peipei, Xuezhen, Kuai, Xiayun, Yuan, Yao, Zhang, Huan, Youjie, Weihong, Sheng, Miao and Xinwen2015) and type 2 diabetes (Culleton et al., Reference Culleton, Larson, Evans, Wilson, Barrett, Parfrey and Levy1999). Almost all creatinine is excreted by the kidneys in individuals, and in today’s clinical practice, the serum creatinine concentration is a widely used index of kidney function (Levey et al., Reference Levey, Perrone and Madias1988; Vidal-Petiot & Flamant, Reference Vidal-Petiot and Flamant2017). The impact of decreased renal function extends to nearly all bodily systems, and early identification and intervention in its decrease are very important to slow disease progress, maintain quality of life and improve prognosis (Snively & Gutierrez, Reference Snively and Gutierrez2004). Complex conditions, such as decreased renal function, are usually caused by a combination of environmental and genetic risk factors (Kluwe & Hook, Reference Kluwe and Hook1980). By studying the factors that cause the changes in serum creatinine levels, we can suggest which ones lead to the decline in renal function (Rakesh Kumar et al., Reference Rakesh Kumar, Shaikh and Chuang2021).

The heritability of serum creatinine levels has been explored in several studies, with results ranging from .19 to .59. For a Mexican American study, the inheritance of serum creatinine was only .19 (Arar et al., Reference Arar, Voruganti, Nath, Thameem, Bauer, Cole, Blangero, MacCluer, Comuzzie and Abboud2008). In a study from an American population, the heritability estimate was .29 (Fox et al., Reference Fox, Yang, Cupples, Guo, Larson, Leip, Wilson and Levy2004). In a study of Dutch participants, the estimated heritability was 37% (Zhang et al., Reference Zhang, Thio, Gansevoort and Snieder2021). In another European study, the heritability was .44 (Pattaro et al., Reference Pattaro, Aulchenko, Isaacs, Vitart, Hayward, Franklin, Polasek, Kolcic, Biloglav, Campbell, Hastie, Lauc, Meitinger, Oostra, Gyllensten, Wilson, Pichler, Hicks and Campbell2009). In the Australian population, the result was .47 (Whitfield & Martin, Reference Whitfield and Martin1984). In a study in Sweden, the inheritance of serum creatinine levels was .59 (Arpegård et al., Reference Arpegård, Viktorin, Chang, de Faire, Magnusson and Svensson2015). Currently, there is a lack of exploratory research on the heritability of serum creatinine levels in the Chinese population. Therefore, in this study, 382 pairs of adult twins from Qingdao were selected as research subjects to explore the effects of genetic and environmental factors on serum creatinine level.

Materials and Methods

Research Population

Our study participants came from the Qingdao twin registration system (Xu, Zhang, Tian, Wu et al., Reference Xu, Zhang, Tian, Wu, Pang, Li and Tan2017), and included 382 pairs of twins from Qingdao city in Shandong province, China. Inclusion criteria for the twin pairs were as follows: age 40 years or above, completed data from all investigations, and signed informed consent form (W. Wang et al., Reference Wang, Zhang, Xu, Wu, Duan, Li and Tan2018). All subjects used the same questionnaire. The twins completed their physical examination, blood test and questionnaire on the same day. Before researchers investigate the subjects, they must be trained correctly (Xu, Zhang, Tian, Duan et al., Reference Xu, Zhang, Tian, Duan, Wu, Pang, Li and Tan2017). Finally, 374 pairs of twins were used for genetic analysis.

Investigation of Research Content

The demographic characteristics, such as age and sex of the subjects, were obtained from the questionnaire. Information such as height and weight of subjects were obtained through physical examination. The serum creatinine level of the subjects was detected by laboratory examination. The subjects were asked to take a sitting position and 10 mL of venous blood was collected. Serum creatinine levels were measured using an automated biochemical analyzer (Liu et al., Reference Liu, Wang, Zhang, Xu, Duan, Tian and Zhang2018).

Zygosity Identification

Zygosity identification was by sex, ABO blood group and microsatellite DNA gene scan and genotyping (W. Wang et al., Reference Wang, Zhang, Liu, Xu, Duan, Tian and Zhang2020). Twins of different sex are dizygotic and those of the same sex but with different blood types are also dizygotic. If both sex and blood type were the same, the zygosity was further identified using microsatellite DNA gene scanning and genotyping technology (He et al., Reference He, Zhu, Han, Liu, Wang, Chu, Zhang, Zhou, Mao, Zhuang, Zhao and Huang2001).

Statistical Analysis

Data entry using EpiData 3.0 software was carried out by two operators at the same time. SPSS 22.0 software was used to calculate the intraclass correlation coefficient (ICC) of serum creatinine levels of the participants. Using Mx software package to build a structural equation model, phenotypic variation can be divided into dominant genetic effect (D), additive genetic effect (A), common or shared environmental effect (C), and unique/nonshared environmental effect (E). If the ICC in the monozygotic twin group was greater than 2 times the ICC in the dizygotic twin group, the ADE model was selected, and if not, the ACE model was selected (Chen et al., Reference Chen, Wang, Li, Xu, Tian and Zhang2021).

In the optimal model, heritability (h2) was considered as the contribution of additive genetic effects to the total phenotypic variation. The best-fit model was determined by a chi-square test of likelihood ratio to compare whether the difference between the full model (ADE or ACE) and its nested models (CE, AE, or DE) was significant. When p > .05, it showed that there is no difference between the full model and its nested model, and the parsimonious principle and Akaike’s information criterion (AIC) were used for determining the best model. When p > .05, we chose the full model. The covariates adjusted in the model were body mass index (BMI; Kashani et al., Reference Kashani, Rosner and Ostermann2020), age (Karam & Tuazon, Reference Karam and Tuazon2013), and sex (Sabolić et al., Reference Sabolić, Asif, Budach, Wanke, Bahn and Burckhardt2007).

Results

Basic Characteristics of Twins

A total of 374 pairs of twins, 359 males and 389 females, aged from 40 to 80, were enrolled in the study. The proportion of female participants was 52%. The median age was 50 years old, and the interquartile range was 11 years old. Serum creatinine levels were between 10 and 126 μmol/L, with a median of 71 μmol/L and interquartile range of 25 μmol/L. Basic characteristics of the twins enrolled in the study are presented in Table 1.

Table 1. Basic characteristics of twins included in the study

Note: MZ, monozygotic; DZ, dizygotic; M (Q), median (interquartile); BMI, body mass index; Scr, Serum creatinine level.

Heritability

As shown in Table 2, the ICC of monozygotic twins (rMZ) was .87 (95% CI [.82, .90]), and that of dizygotic twins (rDZ) was .68 (95% CI [.58, .75]). Since 2*rDZ>rMZ, finally the ACE model was fitted.

Table 2. Interclass correlation coefficient of serum creatinine levels in monozygotic and dizygotic twins

Note: Corr., interclass correlation coefficient; CI, confidence interval.

As shown in Table 3, there were differences between the ACE model and the nested AE model (p < .05), thus the ACE model was still selected. Additive genetic effect (A) (i.e., the heritability of serum creatinine levels) accounted for 35.44% (95% CI [21.48, 53.78]), common or shared environmental effect (C) for 52.13% (95% CI [33.72, 65.90]), and unique/nonshared environmental effect (E) for 12.43% (95% CI [9.99, 15.50]).

Table 3. Model fitting results of the respective proportions of environmental and genetic effects

Note: *Best fit model; A, additive genetic effect; C, common or shared environmental effect; E, unique/nonshared environmental effect; -2LL, 2 times the negative log-likelihood function value; df, degree of freedom; AIC, Akaike’s information criterion; χ2, chi-square value.

Discussion

The results of the heritability analysis showed that the ACE model was the best fit model. The heritability result of serum creatinine level was 35.44%, the shared environmental impact accounted for 52.13%, and the nonshared environmental effect accounted for 12.43%.

The heritability of serum creatinine level has been widely studied. A study in Sweden recruited 5635 subjects with an average age of 64.9 years, 55% of whom were women, and the average creatinine level was 77.5μmol/L. The fitting model was the ADE model, and the heredity result of serum creatinine level was 59% (Arpegård et al., Reference Arpegård, Viktorin, Chang, de Faire, Magnusson and Svensson2015). An Australian study of 206 pairs of twins found that the inheritance of serum creatinine was .47 (Whitfield & Martin, Reference Whitfield and Martin1984). A Danish twin study, fitting the DE model, found heritability in women only, at 44% (Bathum et al., Reference Bathum, Fagnani, Christiansen and Christensen2004). In a study of British female twins, the participants ranged in age from 18 to 72 years. The heritability result was 37% and the ACE model was fitted; shared environmental factors (C) accounted for 26%, and specific environmental influence accounted for 37% (Hunter et al., Reference Hunter, Lange, Snieder, MacGregor, Swaminathan, Thakker and Spector2002). Our research also found the influence of shared environmental factors, but the proportion was higher, and the influence of nonshared environment was lower, which might be due to the influence of different races. In our study, the potential source of shared environmental effects may derive from differences in meat intake or muscle mass. Although our participants came from the same city, differences in economic level and living habits (such as labor intensity) among different families might lead to differences in meat intake or muscle mass.

Some studies have explored the heritability of serum creatinine levels in nontwin populations. A study of 2859 European subjects, including Italian, Dutch and Croatian participants, showed a heritability of .44 for serum creatinine levels (Pattaro et al., Reference Pattaro, Aulchenko, Isaacs, Vitart, Hayward, Franklin, Polasek, Kolcic, Biloglav, Campbell, Hastie, Lauc, Meitinger, Oostra, Gyllensten, Wilson, Pichler, Hicks and Campbell2009). The average age of 1224 participants in the Framingham Heart Study in the United States was 59 years old, and 52% of them were women. The average serum creatinine level was 0.87 mg/dl. The heritability estimate for serum creatinine was .29 (Fox et al., Reference Fox, Yang, Cupples, Guo, Larson, Leip, Wilson and Levy2004). In a study of 155,911 Dutch participants, of whom 58.1% were women with an average age of 43.1 ± 14.7 years, for serum creatinine, the heritability estimates were 37% (Zhang et al., Reference Zhang, Thio, Gansevoort and Snieder2021). The heritability results were different among different studies.

Compared with most other studies on the heritability of serum creatinine, our heritability results were lower. This might be due to the differences among different ethnic groups. In the previous twin studies, most of the people were from Europe and America, while our study focused on the Han ethnic group in northern China. In addition, it might also be related to the age of the research object, the difference of sample size and other factors.

Our research has some shortcomings. Our sample size is small compared to other studies, which is a major limitation, but our study is the first to look at the inheritance of serum creatinine levels in a twin population in China. Twin samples improve study efficiency in studies of complex traits or complex diseases. Second, there are many indicators besides the serum creatinine level that can be used to reflect renal function. At present, each indicator has its own limitations (Filler et al., Reference Filler, Yasin and Medeiros2014; Weingart & Wirnsberger, Reference Weingart and Wirnsberger2021). Many studies use the serum creatinine level to reflect renal function, but some studies also use cystatin C and blood urea nitrogen. Therefore, our conclusion needs further exploration in the future, such as exploring multiple indicators that reflect renal function.

In summary, the results of our study of 373 pairs of adult twins in China showed that the heritability of serum creatinine level was 35%. The influence of shared environmental factors on serum creatinine level accounted for 52%. The serum creatinine level is influenced by genetic and environmental factors. Serum creatinine level tests are widely used in the screening for renal function, and an understanding of the genetic mechanisms underlying these tests may be of value in their interpretation.

Data availability statement

The raw/processed data required to reproduce these findings cannot be shared at this time as the data also forms part of an ongoing study.

Acknowledgments

This study utilized data from the Qingdao Twin Registry (QTR). We would like to thank the twins who participated in this study. And we acknowledge the staff at the Qingdao Center for Disease Control and Prevention (Qingdao CDC).

Funding

None.

Ethical statement

The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008.

References

Arar, N. H., Voruganti, V. S., Nath, S. D., Thameem, F., Bauer, R., Cole, S. A., Blangero, J., MacCluer, J. W., Comuzzie, A. G., & Abboud, H. E. (2008). A genome-wide search for linkage to chronic kidney disease in a community-based sample: The SAFHS. Nephrology Dialysis Transplantation, 23, 31843191. https://doi.org/10.1093/ndt/gfn215 CrossRefGoogle Scholar
Arpegård, J., Viktorin, A., Chang, Z., de Faire, U., Magnusson, P. K., & Svensson, P. (2015). Comparison of heritability of Cystatin C- and creatinine-based estimates of kidney function and their relation to heritability of cardiovascular disease. Journal of the American Heart Association, 4, e001467. https://doi.org/10.1161/jaha.114.001467 CrossRefGoogle ScholarPubMed
Bathum, L., Fagnani, C., Christiansen, L., & Christensen, K. (2004). Heritability of biochemical kidney markers and relation to survival in the elderly ¾ Results from a Danish population-based twin study. Clinica Chimica Acta, 349, 143150. https://doi.org/10.1016/j.cccn.2004.06.017 CrossRefGoogle ScholarPubMed
Borsook, H., & Dubnoff, J. W. (1947). The hydrolysis of phosphocreatine and the origin of urinary creatinine. Journal of Biological Chemistry, 168, 493510.CrossRefGoogle ScholarPubMed
Chen, J., Wang, W., Li, Z., Xu, C., Tian, X., & Zhang, D. (2021). Heritability and genome-wide association study of blood pressure in Chinese adult twins. Molecular Genetics & Genomic Medicine, 9, e1828. https://doi.org/10.1002/mgg3.1828 CrossRefGoogle ScholarPubMed
Culleton, B. F., Larson, M. G., Evans, J. C., Wilson, P. W., Barrett, B. J., Parfrey, P. S., & Levy, D. (1999). Prevalence and correlates of elevated serum creatinine levels: The Framingham Heart Study. Archives of Internal Medicine, 159, 17851790. https://doi.org/10.1001/archinte.159.15.1785 CrossRefGoogle ScholarPubMed
Filler, G., Yasin, A., & Medeiros, M. (2014). Methods of assessing renal function. Pediatric Nephrology, 29, 183192. https://doi.org/10.1007/s00467-013-2426-7 CrossRefGoogle ScholarPubMed
Fox, C. S., Yang, Q., Cupples, L. A., Guo, C. Y., Larson, M. G., Leip, E. P., Wilson, P. W., & Levy, D. (2004). Genomewide linkage analysis to serum creatinine, GFR, and creatinine clearance in a community-based population: The Framingham Heart Study. Journal of the American Society of Nephrology, 15, 24572461. https://doi.org/10.1097/01.Asn.0000135972.13396.6f CrossRefGoogle Scholar
Fried, L. F., Shlipak, M. G., Crump, C., Bleyer, A. J., Gottdiener, J. S., Kronmal, R. A., Kuller, L. H., & Newman, A. B. (2003). Renal insufficiency as a predictor of cardiovascular outcomes and mortality in elderly individuals. Journal of the American College of Cardiolog, 41, 13641372. https://doi.org/10.1016/s0735-1097(03)00163-3 CrossRefGoogle ScholarPubMed
He, X., Zhu, D., Han, Z., Liu, X., Wang, G., Chu, S., Zhang, W., Zhou, H., Mao, S., Zhuang, Q., Zhao, Y., & Huang, W. (2001). [Use of microsatellites in zygosity diagnosis of twins]. Zhonghua Yi Xue Yi Chuan Xue Za Zhi, 18, 421425.Google ScholarPubMed
Hunter, D. J., Lange, M., Snieder, H., MacGregor, A. J., Swaminathan, R., Thakker, R. V., & Spector, T. D. (2002). Genetic contribution to renal function and electrolyte balance: a twin study. Clinical Science, 103, 259265. https://doi.org/10.1042/cs1030259 CrossRefGoogle ScholarPubMed
Karam, Z., & Tuazon, J. (2013). Anatomic and physiologic changes of the aging kidney. Clinics in Geriatric Medicine, 29, 555564. https://doi.org/10.1016/j.cger.2013.05.006 CrossRefGoogle ScholarPubMed
Kashani, K., Rosner, M. H., & Ostermann, M. (2020). Creatinine: From physiology to clinical application. European Journal of Internal Medicine, 72, 914. https://doi.org/10.1016/j.ejim.2019.10.025 CrossRefGoogle ScholarPubMed
Kluwe, W. M., & Hook, J. B. (1980). Effects of environmental chemicals on kidney metabolism and function. Kidney International, 18, 648655. https://doi.org/10.1038/ki.1980.182 CrossRefGoogle ScholarPubMed
Levey, A. S., Perrone, R. D., & Madias, N. E. (1988). Serum creatinine and renal function. Annual Review of Medicine, 39, 465490. https://doi.org/10.1146/annurev.me.39.020188.002341 CrossRefGoogle ScholarPubMed
Liu, H., Wang, W., Zhang, C., Xu, C., Duan, H., Tian, X., & Zhang, D. (2018). Heritability and genome-wide association study of plasma cholesterol in Chinese adult twins. Frontiers in Endocrinology, 9, 677. https://doi.org/10.3389/fendo.2018.00677 CrossRefGoogle ScholarPubMed
Pattaro, C., Aulchenko, Y. S., Isaacs, A., Vitart, V., Hayward, C., Franklin, C. S., Polasek, O., Kolcic, I., Biloglav, Z., Campbell, S., Hastie, N., Lauc, G., Meitinger, T., Oostra, B. A., Gyllensten, U., Wilson, J. F., Pichler, I., Hicks, A. A., Campbell, H., ¼ Pramstaller, P. P.; EUROSPAN Consortium. (2009). Genome-wide linkage analysis of serum creatinine in three isolated European populations. Kidney International, 76, 297306. https://doi.org/10.1038/ki.2009.135 CrossRefGoogle ScholarPubMed
Rakesh Kumar, R. K., Shaikh, M. O., & Chuang, C. H. (2021). A review of recent advances in non-enzymatic electrochemical creatinine biosensing. Analytica Chimica Acta, 1183, 338748. https://doi.org/10.1016/j.aca.2021.338748 CrossRefGoogle ScholarPubMed
Sabolić, I., Asif, A. R., Budach, W. E., Wanke, C., Bahn, A., & Burckhardt, G. (2007). Gender differences in kidney function. Pflügers Archiv European Journal of Physiology, 455, 397429. https://doi.org/10.1007/s00424-007-0308-1 CrossRefGoogle ScholarPubMed
Snively, C. S., & Gutierrez, C. (2004). Chronic kidney disease: Prevention and treatment of common complications. American Family Physician, 70, 19211928.Google ScholarPubMed
Vidal-Petiot, E., & Flamant, M. (2017). [Measurement and estimation of glomerular filtration rate]. Journal of Clinical Nephrology and Therapeutics, 13, 560568. https://doi.org/10.1016/j.nephro.2017.10.001 (Mesure et estimation du débit de filtration glomérulaire.)Google ScholarPubMed
Wang, J., Li, X., Han, X., Yang, K., Liu, B., Li, Y., Peipei, W., Xuezhen, L., Kuai, Y., Xiayun, D., Yuan, J., Yao, P., Zhang, X., Huan, G., Youjie, W., Weihong, C., Sheng, W., Miao, X., Xinwen, M., ¼ He, M. (2015). Serum creatinine levels and risk of metabolic syndrome in a middle-aged and older Chinese population. Clinica Chimica Acta, 440, 177182. https://doi.org/10.1016/j.cca.2014.11.025 CrossRefGoogle Scholar
Wang, W., Zhang, C., Liu, H., Xu, C., Duan, H., Tian, X., & Zhang, D. (2020). Heritability and genome-wide association analyses of fasting plasma glucose in Chinese adult twins. BMC Genomics, 21, 491. https://doi.org/10.1186/s12864-020-06898-z CrossRefGoogle ScholarPubMed
Wang, W., Zhang, D., Xu, C., Wu, Y., Duan, H., Li, S., & Tan, Q. (2018). Heritability and genome-wide association analyses of serum uric acid in middle and old-aged Chinese twins. Frontiers in Endocrinology, 9, 75. https://doi.org/10.3389/fendo.2018.00075 CrossRefGoogle ScholarPubMed
Weingart, C., & Wirnsberger, G. H. (2021). [Clinical implications of the estimated glomerular filtration rate]. Zeitschrift für Gerontologie und Geriatrie, 54, 205210. https://doi.org/10.1007/s00391-021-01839-1 (Klinische Implikationen der geschätzten glomerulären Filtrationsrate.)CrossRefGoogle ScholarPubMed
Whitfield, J. B., & Martin, N. G. (1984). The effects of inheritance on constituents of plasma: A twin study on some biochemical variables. Annals of Clinical Biochemistry, 21, 176183. https://doi.org/10.1177/000456328402100303 CrossRefGoogle ScholarPubMed
Xu, C., Zhang, D., Tian, X., Duan, H., Wu, Y., Pang, Z., Li, S., & Tan, Q. (2017). Genetic and environmental influences on correlations between hearing and cognitive functions in middle and older Chinese twins. Twin Research and Human Genetics, 20, 374379. https://doi.org/10.1017/thg.2017.42 CrossRefGoogle ScholarPubMed
Xu, C., Zhang, D., Tian, X., Wu, Y., Pang, Z., Li, S., & Tan, Q. (2017). Genetic and environmental basis in phenotype correlation between physical function and cognition in aging Chinese twins. Twin Research and Human Genetics, 20, 6065. https://doi.org/10.1017/thg.2016.98 CrossRefGoogle ScholarPubMed
Zhang, J., Thio, C. H. L., Gansevoort, R. T., & Snieder, H. (2021). Familial aggregation of CKD and heritability of kidney biomarkers in the general population: The Lifelines Cohort Study. American Journal of Kidney Diseases, 77, 869878. https://doi.org/10.1053/j.ajkd.2020.11.012 CrossRefGoogle ScholarPubMed
Figure 0

Table 1. Basic characteristics of twins included in the study

Figure 1

Table 2. Interclass correlation coefficient of serum creatinine levels in monozygotic and dizygotic twins

Figure 2

Table 3. Model fitting results of the respective proportions of environmental and genetic effects