To the Editor
Bariatric surgery induces long-term, sustainable weight loss and improves type 2 diabetes and hypertension, thereby contributing to lower mortality1–3. The resulting weight loss also improves glomerular hyperfiltration and albuminuria4,5. However, the conclusion that bariatric surgery improves kidney function have been based on using only estimated GFR or 24-hour creatinine clearance in those with CKD6,7. In this prospective cohort study, we directly measured kidney function (via measured GFR) in obese individuals with reduced GFR following bariatric surgery and investigated metabolic mechanisms that might account for the effects of weight loss on changes in kidney function.
Fifteen patients undergoing bariatric surgery who had serum creatinine >1.3 mg/dl were included; 13 completed the last follow-up. Patients came to the Clinical Research Unit before and 3, 6, and 12 months after surgery to assess body composition, lipid, metabolic (oral glucose tolerance, adipokines, inflammatory markers), kidney function, and QoL parameters (Table 1; detailed methods in Item S1). Changes from baseline to 12 months postsurgery were evaluated using the Wilcoxon signed rank test. Spearman correlations were used to determine associations between the change in mGFR, other kidney function markers, and the changes in metabolic markers.
Table 1.
Changes in obesity, lipid, metabolic, kidney function, and QoL parameters before and 12 months after bariatric surgery
| Variable | Baseline | 12 months | Change | p |
|---|---|---|---|---|
| Obesity measures* | ||||
| Weight (kg) | 160.3 [123.5, 172.0] | 109.0 [96.1, 125.3] | −30.7 [−38.9, −24.0] | <0.001 |
| Height (cm) | 176.5 [172.0, 181.9] | -- | -- | |
| BMI (kg/m2) | 51.0 [36.8, 57.8] | 34.4 [30.8, 46.7] | −9.3 [−14.0, −8.1] | <0.001 |
| Waist circumference (cm) | 138.5 [122.0, 157.5] | 118.5 [106.0, 130.0] | −21.8 [−25.3, −15.0] | <0.001 |
| Fat% | 47.2 [40.1, 53.2] | 34.2 [30.2, 44.6] | −10.2 [−15.7, −5.3] | <0.001 |
| Fat mass (kg) | 68.3 [46.0, 89.2] | 37.4 [28.6, 59.8] | −24.8 [−31.5, −20.4] | <0.001 |
| Fat-free mass (kg) | 72.1 [68.5, 87.7] | 68.4 [64.1, 77.6] | −7.6 [−10.1, −3.2] | 0.002 |
| Lipid parameters | ||||
| Total cholesterol (mg/dl) | 134.0 [122.0, 146.0] | 133.0 [107.0, 138.0] | −13.0 [−26.0, 15.0] | 0.3 |
| HDL cholesterol (mg/dl) | 34.0 [31.0, 38.0] | 44.0 [38.0, 61.0] | +11.0 [8.0, 14.0] | 0.001 |
| Serum triglycerides (mg/dl) | 156.0 [106.0, 183.0] | 99.0 [75.0, 119.0] | −54.0 [−90.0, 2.0] | 0.05 |
| LDL Cholesterol (mg/dl) | 60.2 [47.6, 71.8] | 57.4 [46.8, 69.2] | −0.80 [−23.0, 6.6] | 0.5 |
| Metabolic Parameters | ||||
| Log(hs-CRP) | 0.98 [0.90, 1.00] | 0.30 [−0.18, 0.76] | −0.56 [−1.1, −0.24] | <0.001 |
| HOMA-IR | 18.6 [5.2, 34.1] | 4.8 [3.0, 6.0] | −13.8 [−29.2, −1.5] | 0.008 |
| Matsuda index | 0.91 [0.42, 1.9] | 2.4 [1.9, 2.7] | 1.5 [0.51, 2.2] | 0.04 |
| HMW Adiponectin | 2244 [1654, 3438] | 6617 [2696, 7771] | 1939 [869, 5559] | <0.001 |
| Total Adiponectin | 4815 [4339, 7858] | 14491 [5837, 17756] | 8329 [1021, 12180] | <0.001 |
| Leptin | 37.8 [22.8, 60.8] | 10.6 [6.0, 16.1] | −15.7 [−26.2, −7.2] | 0.001 |
| Kidney function* | ||||
| Serum creatinine (mg/dl) | 1.6 [1.5, 1.8] | 1.4 [1.2, 1.6] | −0.27 [−0.34, −0.08] | 0.006 |
| Cystatin C (mg/dl) | 1.8 [1.7, 1.9] | 1.6 [1.5, 2.0] | 0.02 [−0.17, 0.10] | 0.5 |
| B2M (mg/dl) | 3.5 [3.3, 3.8] | 3.5 [2.9, 3.8] | 0.00 [−0.40, 0.40] | 0.9 |
| eGFRcr (ml/min) | 47.7 [37.4, 52.4] | 52.3 [45.1, 63.8] | 7.9 [0.77, 16.2] | 0.01 |
| eGFRcr (ml/min/1.73 m2) | 30.5 [26.8, 34.5] | 36.5 [35.9, 44.8] | 11.0 [3.9, 14.3] | <0.001 |
| eGFRcys (ml/min) | 34.6 [33.4, 37.7] | 41.7 [31.0, 46.2] | −0.73 [−2.5, 10.9] | 0.3 |
| eGFRcys (ml/min/1.73 m2) | 23.7 [22.4, 29.0] | 28.9 [24.6, 34.9] | 2.2 [0.57, 10.7] | 0.003 |
| eGFRcr-cys (ml/min) | 41.6 [32.3, 47.2] | 45.8 [34.6, 56.3] | 4.8 [0.82, 9.2] | 0.02 |
| eGFRcr-cys (ml/min/1.73 m2) | 26.0 [25.2, 31.5] | 34.3 [26.8, 41.9] | 6.3 [3.4, 10.4] | <0.001 |
| mGFR (ml/min) | 82.0 [60.9, 89.7] | 80.5 [63.0, 111.5] | 1.2 [−1.6, 10.9] | 0.3 |
| mGFR (ml/min/1.73 m2) | 50.0 [44.0, 58.0] | 64.0 [48.0, 87.0] | 8.0 [5.0, 12.0] | 0.02 |
| 24-h Proteinuria (g) | 0.60 [0.16, 1.60] | 0.43 [0.16, 0.85] | −0.02 [−0.28, 0.28] | 0.8 |
| QoL composite score | ||||
| SF-12 Physical Health | 39.8[25.3,47.8] | 49.1[42.1,51.6] | 4.9[0.77,19.3] | 0.007 |
| SF-12 Mental Health | 49.9[40.1,57.8] | 56.4[48.9,58.2] | 2.8[−1.6,11.6] | 0.2 |
N = 13. Values are given as median [interquartile range].
Wilcoxon signed rank test
Abbreviations: B2M, β2-microglobulin; BMI, body mass index; cr, creatinine; cys, cystatin C; m/eGFR: measured/estimated glomerular filtration rate; HOMA-IR: homeostatic model assessment of insulin resistance; hs-CRP, high-sensitivity C-Reactive Protein; HMW, high-molecular-weight; SF-12, 12-Item Short Form Health Survey; HDL, high-density lipoprotein; LDL, low-density lipoprotein
Patients underwent Roux-en-Y gastric bypass (n = 7), laparoscopic adjustable gastric banding (n = 3), or laparoscopic sleeve gastrectomy (n = 3). Median age was 56 (IQR, 49–63) years, with 92% males and 77% Caucasian. All included patients had hypertension and hyperlipidemia and most had type 2 diabetes. At baseline, median unadjusted and BSA-adjusted mGFR were 82 (IQR, 60.9–89.7) ml/min and 50 (IQR, 44.0–58.0) ml/min/1.73 m2, respectively.
Twelve months after surgery, BMI, waist circumference, fat mass, and fat-free mass decreased significantly, along with some improvement in lipid profile and SF-12 physical composite scores. Matsuda Index and total/HMW adiponectin also increased, while HOMA-IR, plasma leptin, and hs-CRP levels decreased (Table 1). These anthropometric and metabolic changes corresponded with improvements in most kidney disease measures. Although unadjusted mGFR did not change significantly, there was a significant improvement in BSA-adjusted mGFRs at 3-, 6- and 12-months’ follow-up (Item S1). Serum cystatin C and B2M levels did not change at 12 last follow-up (Table 1). Item S1 reports a sensitivity analysis focusing on the Roux-en-Y gastric bypass patients. Change in kidney function (both adjusted and unadjusted mGFR) correlated with leptin and B2M level changes (Table 2), while change in BMI and fat mass did not correlate with kidney function and metabolic parameters.
Table 2.
Spearman correlations between changes in kidney function parameters, obesity measures, adipokines, and insulin resistance
| Variable | Correlation with change in | Rho (95% CI) | p |
|---|---|---|---|
| Change in mGFR (ml/min) | Matsuda index | 0.33 (−0.30, 0.96) | 0.3 |
| Leptin | −0.60 (−1.00, −0.07) | 0.03 | |
| Total adiponectin | 0.08 (−0.58, 0.74) | 0.8 | |
| B2M | −0.65 (−1.00, −0.14) | 0.02 | |
| Cystatin C | −0.26 (−0.90, 0.38) | 0.4 | |
| Log(hs-CRP) | −0.50 (−1.00, 0.07) | 0.08 | |
| Change in mGFR (ml/min/1.73 m2) | Matsuda index | 0.54 (−0.02, 1.00) | 0.06 |
| Leptin | −0.74 (−1.00, −0.29) | 0.004 | |
| Total adiponectin | 0.21 (−0.44, 0.86) | 0.5 | |
| B2M | −0.76 (−1.00, −0.33) | 0.003 | |
| Cystatin C | −0.36 (−0.98, 0.26) | 0.2 | |
| Log(hs-CRP) | −0.61 (−1.00, −0.09) | 0.03 | |
| Change in Matsuda index | Leptin | −0.73 (−1.00, −0.28) | 0.005 |
| Total adiponectin | 0.24 (−0.41, 0.88) | 0.4 | |
| B2M | −0.47 (−1.00, 0.11) | 0.1 | |
| Cystatin C | −0.23 (−0.88, 0.41) | 0.5 | |
| Log(hs-CRP) | −0.35 (−0.97, 0.28) | 0.3 | |
| Change in HOMA-IR | Leptin | 0.63 (0.11, 1.00) | 0.02 |
| Total adiponectin | −0.02 (−0.68, 0.65) | 0.9 | |
| B2M | 0.76 (0.33, 1.00) | 0.002 | |
| Cystatin C | 0.64 (0.13, 1.00) | 0.02 | |
| Log(hs-CRP) | 0.12 (−0.54, 0.78) | 0.7 |
Our results suggest potential benefits of bariatric surgery and the variations among the different measures of kidney function in those with reduced GFR. The metabolic effects of gastric bypass are well known; as expected, we noted improvements in metabolic parameters with bariatric surgery. We speculate that the absence of decline in kidney function over the course of our study may be a potential benefit in those with reduced GFR, but the lack of control group precludes definitive conclusions8. With rapid weight loss during the first few months after surgery, associated hemodynamic changes could lead to an acute drop in GFR9. Our data suggest that the mGFR did not change at 3 or 6 months postsurgery, suggesting an attenuation of the expected acute deterioration in kidney function (Table S1). Also, the observed correlations between leptin and mGFR suggest that leptin might act renoprotectively following surgery; further studies to understand this relationship and examine other potential mechanistic pathways are warranted.
Because measuring GFR is expensive and time-consuming, it is of interest whether novel filtration biomarkers can predict changes in mGFR in this setting. Given the loss of fat-free mass, serum creatinine and eGFR were expected to improve and did not correlate with mGFR. B2M is freely filtered, metabolized in the renal tubule, and reported to correlate with mGFR in other populations. Our results suggest its potential utility in bariatric surgery patients but its role as a biomarker of change in kidney function should be studied in other cohorts. In a recent study with mean mGFR 117±40 ml/min, cystatin C was associated with mGFR in those undergoing bariatric surgery10. However, we did not observe any changes in cystatin C and such correlation. This may be attributed to the differences in baseline kidney function or to our study’s small sample size.
In summary, bariatric surgery is associated with an improvement in insulin resistance, adipokines, and QoL, with no changes in kidney function at 12 months’ follow-up. B2M correlates with mGFR in this setting. Cumulatively, this hypothesis-generating study argues for larger long-term studies in this area.
Supplementary Material
Acknowledgments
We thank the research volunteers for their outstanding dedication and effort, and the nursing staff and technicians of the CCF Clinical Research Unit who helped with the implementation of the study and data collection.
Support: SDN was supported by a career development award from the National Center for Research Resources (NCRR) and the National Center for Advancing Translational Sciences (grant TR000440). SKM was supported by National Institutes of Health (NIH) grant T32 DK007319. This work was supported in part by the NCRR Clinical and Translational Science Award 1UL1RR024989.
Footnotes
The results of this study were presented as an abstract at the American Society of Nephrology meeting held November 9 2013 in Atlanta, GA.
The article’s content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH, which did not have any role in study design; collection, analysis, and interpretation of data; writing the report; and the decision to submit the report for publication.
Author contributions: Research area and study design: SDN, JPK, PRS; data acquisition: SDN, SKM, JPK, PRS; data analysis and interpretation: SDN, SKM, SA, SRK, JPK, PRS. Each author contributed important intellectual content during manuscript drafting or revision and accepts accountability for the overall work by ensuring that questions pertaining to the accuracy or integrity of any portion of the work are appropriately investigated and resolved. SDN takes responsibility that this study has been reported honestly, accurately, and transparently; that no important aspects of the study have been omitted, and that any discrepancies from the study as planned have been explained.
Item S1: Detailed methods and supplementary results.
Note: The supplementary material accompanying this article (doi:_______) is available at www.ajkd.org
Financial Disclosure: PRS is principal investigator of the STAMPEDE trial, funded by Ethicon, and consults for Ethicon. The remaining authors declare that they have no other relevant financial interests.
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
References
- 1.Kashyap SR, Bhatt DL, Wolski K, et al. Metabolic effects of bariatric surgery in patients with moderate obesity and type 2 diabetes: Analysis of a randomized control trial comparing surgery with intensive medical treatment. Diabetes Care. 2013;36(8):2175–2182. doi: 10.2337/dc12-1596. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Schauer PR, Bhatt DL, Kirwan JP, et al. Bariatric surgery versus intensive medical therapy for diabetes - 3-year outcomes. N Engl J Med. 2014 doi: 10.1056/NEJMoa1401329. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Sjostrom L, Narbro K, Sjostrom CD, et al. Effects of bariatric surgery on mortality in swedish obese subjects. N Engl J Med. 2007;357(8):741–752. doi: 10.1056/NEJMoa066254. [DOI] [PubMed] [Google Scholar]
- 4.Navaneethan SD, Yehnert H, Moustarah F, Schreiber MJ, Schauer PR, Beddhu S. Weight loss interventions in chronic kidney disease: A systematic review and meta-analysis. Clin J Am Soc Nephrol. 2009;4(10):1565–1574. doi: 10.2215/CJN.02250409. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Afshinnia F, Wilt TJ, Duval S, Esmaeili A, Ibrahim HN. Weight loss and proteinuria: Systematic review of clinical trials and comparative cohorts. Nephrol Dial Transplant. 2010;25(4):1173–1183. doi: 10.1093/ndt/gfp640. [DOI] [PubMed] [Google Scholar]
- 6.Navaneethan SD, Yehnert H. Bariatric surgery and progression of chronic kidney disease. Surg Obes Relat Dis. 2009;5(6):662–665. doi: 10.1016/j.soard.2009.01.006. [DOI] [PubMed] [Google Scholar]
- 7.Getty JL, Hamdallah IN, Shamseddeen HN, et al. Changes in renal function following roux-en-Y gastric bypass: A prospective study. Obes Surg. 2012;22(7):1055–1059. doi: 10.1007/s11695-012-0617-0. [DOI] [PubMed] [Google Scholar]
- 8.Haynes R, Staplin N, Emberson J, et al. Evaluating the contribution of the cause of kidney disease to prognosis in CKD: Results from the study of heart and renal protection (SHARP) Am J Kidney Dis. 2014 doi: 10.1053/j.ajkd.2013.12.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Weingarten TN, Gurrieri C, McCaffrey JM, et al. Acute kidney injury following bariatric surgery. Obes Surg. 2013;23(1):64–70. doi: 10.1007/s11695-012-0766-1. [DOI] [PubMed] [Google Scholar]
- 10.Friedman AN, Moe S, Fadel WF, et al. Predicting the glomerular filtration rate in bariatric surgery patients. Am J Nephrol. 2014;39(1):8–15. doi: 10.1159/000357231. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.