Chi-yuan Hsu, MD, MSc UCSF, Carlos Iribarren, MD, MPH, PhD and Alan S Go, MD
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Re: In Response
hsuchi{at}medicine.ucsf.edu Chi-yuan Hsu, et al.
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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/min/1.73m2 or dipstick proteinuria or hematuria). In the overall cohort, as expected, those with higher BMI had a higher risk of death from any cause (Table).
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
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Obesity related nephropathy and TGF-beta |
1 February 2006 |
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Yujiro Kida, MD, PhD Tsurumi University, School of Dental Medicine, Tetsuji Sato, DMD, PhD
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Re: Obesity related nephropathy and TGF-beta
kida-yujiro{at}tsurumi-u.ac.jp Yujiro Kida, et al.
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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 |
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Estimation of the Glomerular Filtration Rate could be Easier with the Inclusion of Pulse.Mass Index |
17 January 2006 |
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Prof. Enrique J. Sánchez-Delgado, MD, Director for Medical Education. Internist and Clinical Pharmacologist Hospital Metropolitano Vivian Pellas, Managua, Nicaragua
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Re: Estimation of the Glomerular Filtration Rate could be Easier with the Inclusion of Pulse.Mass Index
esanchez{at}metropolitano.com.ni Prof. Enrique J. Sánchez-Delgado, MD
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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 |
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Body Mass Index, End Stage Renal Disease and "Reverse Epidemiology" |
17 January 2006 |
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Micah L Thorp, DO, MPH Kaiser Permanente Northwest
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Re: Body Mass Index, End Stage Renal Disease and "Reverse Epidemiology"
Micahthorp{at}comcast.net Micah L Thorp
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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 |
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Body Mass Index and Competing Risks of Death and End-Stage Renal Disease |
12 January 2006 |
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Kamyar Kalantar-Zadeh, MD PhD MPH Harbor-UCLA, Joel D Kopple
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Re: Body Mass Index and Competing Risks of Death and End-Stage Renal Disease
kamkal{at}ucla.edu Kamyar Kalantar-Zadeh, et al.
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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 |
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Elevated circulating TGF beta-1 and progression to ESRD |
10 January 2006 |
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Michael C. Peterson, MD Division of General Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT
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Re: Elevated circulating TGF beta-1 and progression to ESRD
mike.peterson{at}utahtelehealth.net Michael C. Peterson
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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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