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1. In Response

   • Chi-yuan Hsu, MD, MSc
   • Carlos Iribarren, MD, MPH, PhD and Alan S Go, MD

   UCSF

   To the Editor

   We thank Drs. Thorp, Kalantar-Zadeh and Kopple for their interest in our study which showed that higher baseline body mass index (BMI) is a strong risk factor for end-stage renal disease (ESRD). They raised the question whether or not persons with chronic kidney disease who are obese have paradoxically better survival than those who are not obese and whether what has been called “reverse epidemiology” could explain our findings.

   We would like to emphasize that our study was not limited only to those persons with baseline chronic kidney disease. Overall, 1036 out of 1471 cases of ESRD developed among individuals who did not have baseline chronic kidney disease (defined as an estimated glomerular filtration rate <_60 ml="ml" min="min" _1.73m2="_1.73m2" or="or" dipstick="dipstick" proteinuria="proteinuria" hematuria.="hematuria." in="in" the="the" overall="overall" cohort="cohort" as="as" expected="expected" those="those" with="with" higher="higher" bmi="bmi" had="had" a="a" risk="risk" of="of" death="death" from="from" any="any" cause="cause" table.="table." _="_" p="p">

   To address the concern directly, we note that in the subgroup of persons who had baseline chronic kidney disease, increased BMI remained a risk factor for mortality (Table).

   BMI category	Multivariable RR (95% CI) for Death*
   	Entire cohort (N = 320,252)	Persons with baseline chronic kidney disease† (N = 44,583)
   	(55,425 deaths before onset of ESRD)	(11,768 deaths before onset of ESRD)
   Normal weight (18.5-24.9 kg/m2)	1.00	1.00
   Overweight (25.0-29.9 kg/m2)	1.04 (1.02 – 1.06)	1.03 (0.99 - 1.07)
   Obesity Class I (30.0-34.9 kg/m2)	1.20(1.17 – 1.24)	1.19 (1.12 - 1.27)
   Obesity Class II (35.0-39.9 kg/m2)	1.42 (1.35 – 1.50)	1.32 (1.19 - 1.47)
   Obesity Class III (>40.0 kg/m2)

   Conflict of Interest:

   None declared

   Submit response
   Published March 27, 2006
2. Obesity related nephropathy and TGF-beta

   • Yujiro Kida, MD, PhD
   • Tetsuji Sato, DMD, PhD

   Tsurumi University, School of Dental Medicine

   Hsu CY et al. reported obesity is an independent risk factor for the development of end-stage renal disease (ESRD) (1). The authors described that leptin may directly lead to renal fibrosis in their discussion section (1). However, the authors did not refer to the important factor related to the progressive renal disease in the obese state. Henegar JR et al. showed that transforming growth factor- beta1 (TGF-bata1) was strongly expressed both in the glomeruli and the interstitinum of obese dogs compared with in those of lean dogs (2). The roles of TGF-beta1 in renal fibrosis are widely accepted. TGF-beta1-induced apoptosis is likely to play a pathologic role in podocyte depletion and glomerulosclerosis, tubular degeneration, and loss of glomerular and peritubular capillaries (3). Recently, epithelial-mesenchymal transition (EMT) of tubular epithelia induced by TGF-beta1, was shown to promote the generation of interstitital myofibroblasts, leading to tubulointerstitial fibrosis (4).

   References:

   (1) Hsu CY, et al. Body mass index and risk for end-stage renal disease. Ann Intern Med 2006; 144: 21-8.

   (2) Henegar JR, et al. Functional and structural changes in the kidney in the early stages of obesity. J Am Soc Nephrol 2001; 12: 1211-7.

   (3) Bottinger E, et al. TGF-beta signaling in renal disease. J Am Soc Nephrol 2002; 13: 2600-10.

   (4) Liu Y. Epithelial to mesenchymal transition in renal fibrogenesis. J Am Soc Nephro 2004; 15: 1-12.

   Conflict of Interest:

   None declared

   Submit response
   Published February 1, 2006
3. Estimation of the Glomerular Filtration Rate could be Easier with the Inclusion of Pulse.Mass Index

   • Prof. Enrique J. Sánchez-Delgado, MD, Director for Medical Education. Internist and Clinical Pharmacologist

   Hospital Metropolitano Vivian Pellas, Managua, Nicaragua

   The reciprocal of serum creatinine (1/SCr) is frequently used as a simple but inaccurate estimated glomerular filtration rate (eGFR.

   I proposed one year ago to investigate the possible usefulness and accuracy of 1/SCr divided by the PULSE by MASS INDEX or PMI (1)(see my response to Rule et. al., Annal, Dec.21, 2004).

   For example, for a normal SCr of 1.1 mg/dl and a normal PMI of 1.0, the eGFR would be 0.9 or 90% of normal. For a SCr of 1.5, it would be 0.66. If the PMI was 1.3, which is common in patients with a high global cardiovascular risk according to the Framingham Risk Equation, the eGFR would be 0.7 (70 % of normal) in the case of 1.1 mg SCr or 0.51 (less than 60 % of normal) for a SCr of 1.5 mg. The higher the PMI, the lower the expected eGFR for a given value of SCr.

   Using one of the original examples from Rule, if a 50-year-old woman presented to donate a kidney and had a Mayo Clinic serum creatinine of 1.1 mg/dL , she would have an eGFR of 90 mL/min per 1.73 m2 (equation 3). If this woman had a BMI of 27 (69 kg, 1.6m), and a RHR of 80, her PMI would be 1.25 and her eGFR 0.73 (73% of normal). This eGFR is normal, but less than ideal, reflecting her higher cardiovascular risk.

   The PULSExMASS INDEX (PMI) is calculated as follows: Body Mass Index (BMI) multiplied by Resting Heart Rate (RHR) and divided by 1730 (24x72). The PMI considers the weigh in kilograms, the high in meters (BMI =Kg/m2) and the RHR. The normal values of BMI (average 24) are similar in males and females. The RHR (average 72) reflects the basal metabolic rate and related factors, both in healthy, fit, potential donors, and in sick people. The PMI reflects all these elements and correlates highly both with the body surface area, and the global cardiovascular risk (known to be elevated in renal patients), being much easier to calculate.

   If 1/SCr/PMI resulted acceptably accurate to estimate the GFR, it would facilitate the daily work with renal patients, until we know more from cystatin C. This report by Hsu et. al. appears to reinforce this concept.

   References 1.Gilbert Ross, Jeff Stier, Donald M Lloyd-Jones, Daniel Levy, Enrique Sánchez-Delgado, et al. Lifetime risk of developing coronary heart disease. Lancet 1999 (13 March); 353:924-925 Conflict of Interest: None declared

   Conflict of Interest:

   None declared

   Submit response
   Published January 17, 2006
4. Body Mass Index, End Stage Renal Disease and "Reverse Epidemiology"

   • Micah L Thorp, DO, MPH

   Kaiser Permanente Northwest

   To the Editor,

   In their excellent paper Hsu et. al. (1) found a significant correlation between body mass index (BMI) and subsequent renal replacement therapy. Perhaps due to the generous sample size, lengthy follow up or survival bias, the relationship was more substantial than previously reported. This finding provides an important insight in determining the significance of BMI in the development of renal disease, a relationship that is both complex and not yet fully understood.

   While elevated BMI may be associated with the development of renal disease (and subsequent renal replacement therapy), it is an association that may change throughout disease progression. Studies examining risk factors for progression of renal disease and mortality among patients with established chronic kidney disease have found modest or no correlations between either outcome and BMI.(2,3) Once patients require renal replacement therapy, increased BMI is associated with increased survival.(4) This phenomenon has been referred to as “reverse epidemiology” or the “dialysis-risk-paradox”.(5)

   Potential explanations for these seemingly contradictory results include both physiological and methodological reasons. Co-occurrence of diabetes and hypertension seems likely to have an effect on the development of kidney disease in obese individuals. In addition, it has been established that increased BMI leads to glomerular hyperfiltration, which may independently lead to renal disease.(6) Once renal disease has been established, the impact of BMI may be obscured by other pathological processes, including malnutrition, inflammation and changes in vitamin D metabolism. Finally, the role of survival bias, reverse causation and timing of competing risk factors need to be considered when exploring etiologies for “reverse epidemiology”. The outcomes reported by Hsu and other investigators provide insight into this complex relationship and are likely to play an important role in determining how clinicians manage patients with renal disease.

   (1) Hsu CY, McCulloch CE, Iribarren C, Darbinian J, Go AS. Body mass index and risk for end-stage renal disease. Ann Intern Med. 2006;144(1):21 -8.

   (2) Bonnet F, Deprele C, Sassolas A, Moulin P, Alamartine E, Berthezene F, Berthoux F. Excessive body weight as a new independent risk factor for clinical and pathological progression in primary IgA nephritis. Am J Kidney Dis. 2001;37(4):720-7.

   (3) Evans M, Fryzek JP, Elinder CG, Cohen SS, McLaughlin JK, Nyren O, Fored CM. The natural history of chronic renal failure: results from an unselected, population-based, inception cohort in Sweden. Am J Kidney Dis. 2005;46(5):863-70.

   (4) Kalantar-Zadeh K, Kopple JD, Kilpatrick RD, McAllister CJ, Shinaberger CS, Gjertson DW, Greenland S. Association of morbid obesity and weight change over time with cardiovascular survival in hemodialysis population. Am J Kidney Dis. 2005;46(3):489-500.

   (5) Kalantar-Zadeh K, Abbott KC, Salahudeen AK, Kilpatrick RD, Horwich TB. Survival advantages of obesity in dialysis patients. Am J Clin Nutr. 2005;81(3):543-54

   (6) Chagnac A, Weinstein T, Korzets A, Ramadan E, Hirsch J, Gafter U. Glomerular hemodynamics in severe obesity. Am J Physiol Renal Physiol. 2000;278:F817-22

   Conflict of Interest:

   None declared

   Submit response
   Published January 17, 2006
5. Body Mass Index and Competing Risks of Death and End-Stage Renal Disease

   • Kamyar Kalantar-Zadeh, MD PhD MPH
   • Joel D Kopple

   Harbor-UCLA

   We found the strong associations between obesity and the risk of end- stage renal disease (ESRD) reported in the study by Hsu et al [1] extremely interesting and a valuable addition to the list of risk factors for ESRD. It seems possible, however, that these findings are influenced by survival bias [2], especially if obese individuals with chronic kidney disease (CKD) have a paradoxically better survival chance than non-obese ones. An inverse association between obesity including morbid obesity and survival has been frequently shown among advanced CKD patients who undergo maintenance hemodialysis [3]. Hence, it is possible, although not yet shown, that even obese patients with earlier CKD stages, i.e., those who have not yet required maintenance dialysis treatment, have a significantly higher likelihood of surviving and reaching ESRD, when compared to non- obese CKD patients, many of whom may die before progressing to more advanced stages of CKD. Indeed, Keith et al [4] showed that the risk of death among patients with earlier stages of CKD is as much as 10 to 20 times higher than the risk of progression towards ESRD. Because far more CKD patients die than ever reach ESRD and because obesity might confer survival advantages in CKD, it would seem important to reevaluate these data considering possible survival biases for obesity.

   Reference:

   1. Hsu C-y, McCulloch CE, Iribarren C, Darbinian J, Go AS: Body Mass Index and Risk for End-Stage Renal Disease. Ann Intern Med 144:21-28, 2006

   2. Rothman K, Greenland S: Sources of bias, in Modern Epidemiology, edited by Rothman K, Greenland S, Philadelphia, Lipincott-Raven, 1998

   3. Kalantar-Zadeh K, Kopple JD, Kilpatrick RD, McAllister CJ, Shinaberger CS, Gjertson DW, Greenland S: Association of morbid obesity and weight change over time with cardiovascular survival in hemodialysis population. Am J Kidney Dis 46:489-500, 2005

   4. Keith DS, Nichols GA, Gullion CM, Brown JB, Smith DH: Longitudinal follow-up and outcomes among a population with chronic kidney disease in a large managed care organization. Arch Intern Med 164:659-663, 2004

   Conflict of Interest:

   None declared

   Submit response
   Published January 12, 2006
6. Elevated circulating TGF beta-1 and progression to ESRD

   • Michael C. Peterson, MD

   Division of General Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT

   To the Editor:

   I would like to suggest a potential explanation(1) (or partial explanation) for the finding of Hsu et al that obesity is associated with progression toward end stage renal disease after controlling for both diabetes and hypertension.

   In very brief terms, transforming growth factor beta-1 (TGF beta-1) is known to signal for fibrosis and matrix deposition in the development of many varieties of renal disease. Several risk factors for progression of renal disease have associated elevations in circulating levels of TGF beta-1, these include diabetes,(2) hypertension,(3) African American race,(4) smoking(5) and obesity.(6)

   Short-term administration of recombinant TGF beta-1 to small animals results in renal injury(7) and similar injury occurs in several transgenic TGF beta-1 over-expression models in animals. In humans, circulating TGF beta-1 levels correlate with treatment efficacy in diabetic nephropathy patients treated with captopril.(8) Interestingly, weight loss in hypertensive patients results in lower circulating levels of TGF beta- 1.(9)

   This model allows for contributions from several known risks for progression of renal disease, and suggests that the risk for progression of renal disease related to obesity is likely modifiable. The model might also influence the choice of an antihypertensive drug in obese patients with hypertension toward an ACE inhibitor or an angiotensin II receptor antagonist both of which block signaling of TGF beta-1 upstream – though this deserves further scrutiny.

   References:

   1. Peterson MC. Circulating transforming growth factor beta-1: a partial molecular explanation for associations between hypertension, diabetes, obesity, smoking and human diseases involving fibrosis. Med Sci Monit 2005:11:RA229-232.

   2. Pfeiffer A, Drewes C, Middelberg-Bisping K, Schatz H. Elevated plasma levels of transforming growth factor-beta 1 in NIDDM. Diabet Care. 1996;19:1113-1117.

   3. Derhashnig U, Shehata M, Herkner H, Bur A, Woisetschlager C, Laggner AN, Hirschl MM. Increased levels of transforming growth factor- beta 1 in essential hypertension. AJH. 2002;15:207-211.

   4. August P, Suthanthirian M. Transforming growth factor beta and progression of renal disease. Kidney Int 2003;64(suppl 87):S99-104.

   5. Esmatjes E, Flores L, Lavio S, Claria J, Cases A, Inigo P, Campistol JM. Smoking increases serum levels of transforming growth factor -beta in diabetic patients. Diabet Care. 1999;22:1915-1916.

   6. Romano M, Guagnano MT, Pacini G, Vigneri S, Falco A, Marinopiccoli M, et al. Association of inflammation markers with impaired insulin sensitivity and coagulative activation in obese healthy women. J Clin Endocrinol Metab. 2003;88:5321-5326.

   7. Terrell TG, Working PK, Chow CP, Green JD. Pathology of recombinant human transforming growth factor-beta-1 in rats and rabbits. Int Rev Exp Pathol 1993;34:43-67.

   8. Sharma K, Eltayeb BO, McGowan TA, Dunn SR, Alzahabi B, Rohde R, Ziyadeh FN, Lewis EJ. Captopril-induced reduction of serum levels of transforming growth factor-beta 1 correlates with long-term renoprotection in insulin-dependent diabetic patients. Am J Kid Dis. 1999;34:818-823.

   9. Porreca E, Di Febbo C, Vitacollona E, Baccante G, Di Catastelnuevo A, Angelini A, et al. Transforming growth factor-beta 1 levels in hypertensive patients: association with body mass index and leptin. AJH. 2002;15:759-765.

   Conflict of Interest:

   None declared

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   Published January 10, 2006