renal and systemic effects of calorie restriction in type ... · abdominal obesity defined as waist...

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RENAL AND SYSTEMIC EFFECTS OF CALORIE RESTRICTION IN TYPE-2 DIABETES PATIENTS

WITH ABDOMINAL OBESITY: A RANDOMIZED CONTROLLED TRIAL

Piero Ruggenenti MD1,2*

, Manuela Abbate1*

MSc, Barbara Ruggiero MD1,

Stefano Rota, MD2, Matias Trillini MD

1, Carolina Aparicio MD

1, Aneliya Parvanova MD

1,

Ilian Petrov Iliev MD1, Giovanna Pisanu MD

1, Annalisa Perna MSc

1,

Angela Russo StatSciD1, Olimpia Diadei, ChemD

1,

Davide Martinetti EngD1, Antonio Cannata Chemist

1, Fabiola Carrara Chemist

1,

Silvia Ferrari Chemist1, Nadia Stucchi Chemist

1,

Giuseppe Remuzzi MD, FRCP1,2,3

, Luigi Fontana MD, PhD4,5,6

on behalf of the CRESO Study Group*

1IRCCS – Istituto di Ricerche Farmacologiche Mario Negri, Centro di Ricerche Cliniche per

le Malattie Rare “Aldo e Cele Daccò”, Bergamo, Italy; 2Unit of Nephrology, Azienda Socio

Sanitaria Territoriale (ASST) Ospedale Papa Giovanni XXIII, Bergamo, Italy; 3Department

of Biomedical and Clinical Sciences, University of Milan, Milan, Italy; 4Department of

Clinical and Experimental Sciences, Brescia University Medical School, Brescia, Italy; 5Department of Medicine, Washington University in St. Louis, MO, USA;

6CEINGE

Biotecnologie Avanzate, Napoli, Italy

* These authors contributed equally to this research

Running Title: Renal effects of calorie restriction

World count: Abstract n=199, Text: n=4898

Corresponding author:

Giuseppe Remuzzi, MD, FRCP

IRCCS - Istituto di Ricerche Farmacologiche Mario Negri

Centro Anna Maria Astori, Science and Technology Park Kilometro Rosso

Via Stezzano 87, 24126 Bergamo, Italy

Tel: +39.03542131; Fax: +39.035319888

e-mail: [email protected]

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Diabetes Publish Ahead of Print, published online September 15, 2016

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ABSTRACT

In type-2 diabetics with abdominal obesity, hyperfiltration is a risk factor for accelerated

GFR decline and nephropathy. In this academic, single-center, parallel-group, Prospective,

Randomized, Open-label, Blinded Endpoint (PROBE) trial (ClinicalTRials.gov number:

NCT01213212), consenting >18-year-old, type-2 diabetics with waist circumference >94

(males) or >80 (females) cm, serum creatinine <1.2 mg/dl, and normoalbuminuria were

randomized (1:1) with permuted blocks to 6-month 25% CR or standard diet (SD). Primary

outcome was measured GFR (iohexol plasma clearance). Analyses were by modified

intention-to-treat. At 6 months GFR significantly decreased in 34 patients on CR and did not

change appreciably in 36 on SD. Changes were significantly different between groups. GFR

and body weight reduction were correlated. GFR reduction was larger in hyperfiltering (GFR

>120 ml/min) than non-hyperfiltering patients, and associated with body mass index, waist

circumference, blood pressure, heart rate, HbA1C, blood glucose, LDL/HDL cholesterol

ratio, C-reactive protein, Angiotensin-II, and albuminuria reduction and with increased

glucose disposal rate (measured by hyperinsulinemic euglycemic clamps). Protein and

sodium intake and concomitant treatments were similar between groups. CR was tolerated

well. In Type-2 diabetics with abdominal obesity, CR ameliorates glomerular hyperfiltration,

insulin sensitivity and other cardiovascular risk factors, effects that might translate into long-

term nephro- and cardio-protection.

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Obesity, especially if centrally located (1), and diabetes (2) are both associated with renal

dysfunction sustained by glomerular hyperfiltration (3,4), a risk factor for accelerated renal

function loss and onset and progression of nephropathy (5). Thus, glomerular hyperfiltration

might be one of the possible pathogenic links between obesity and chronic kidney disease

(CKD) (6,7). Finding that bariatric surgery ameliorates glomerular hyperfiltration associated

with severe obesity (8), suggests that weight loss, in addition to ameliorating a series of

cardiovascular risk factors, might also affect the onset and progression of CKD (5,8). This

invasive procedure is, however, necessarily restricted to a selected population at very high

risk of obesity-related complications. Thus, calorie restriction (CR) remains the principal

method for inducing weight loss (9). However, no trial so far has formally tested the role of

CR and weight loss on glomerular filtration, in particular by directly measuring the GFR in

subjects with glomerular hyperfiltration and abdominal obesity (10).

Thus, we evaluated whether and to what extent measured GFR (11) could be affected by CR

in the context of a controlled, randomized clinical trial (ClinicalTrials.gov number:

NCT01213212) of “Caloric REstriction in Subjects with abdominal Obesity and Type-2

diabetes at increased risk (C.RE.S.O)”.

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RESEARCH DESIGN AND METHODS

This academic, single-center, parallel-group, Prospective, Randomized, Open-label, Blinded

Endpoint (PROBE) trial was conducted at the Clinical Research Center (CRC) for Rare

Diseases of the IRCCS - Istituto di Ricerche Farmacologiche Mario Negri. Participants were

identified among patients referred to the Outpatient Clinics of the CRC and of the

Diabetology Units of Bergamo, Treviglio-Caravaggio, Romano di Lombardia and Seriate

Hospitals, all in Italy. Participants were >18-year-old Type-2 diabetics (ADA Criteria) with

abdominal obesity defined as waist circumference of >94 cm in males and >80 cm in females

(12), serum creatinine <1.2 mg/dL and urinary albumin excretion (UAE) <20 µg/min in

overnight urine collections. They had a stable body weight and calorie intake, and a stable

diet with a standardized content in micro- and macro-nutrients and salt, according to

guidelines (13) and no systematic changes in blood pressure (BP), glucose and lipid-lowering

medications over the last six months. We excluded patients with primary, immune-mediated

or ischemic kidney disease, urinary tract obstruction or infection, concomitant therapy with

renin-angiotensin-system (RAS) inhibitors, steroids or non-steroid anti-inflammatory agents,

heart failure, uncontrolled diabetes, hypo- or hypernatremia from any cause, previous

bariatric surgery, depression or alcohol and drug abuse, pregnancy, ineffective contraception

or of peri-menopausal age, who had cancer or chronic disease that might jeopardize study

completion, primary endocrinological diseases, poor compliance or were unable to provide

informed consent. The study conformed to the principles of the EU Clinical Trials Directive

(2001/20/EC), Good Clinical Practice and the Declaration of Helsinki. It was approved by the

ethics committee of the local health agency in Bergamo, Italy. All patients provided written

informed consent. Data were recorded in dedicated case record forms and then entered into

the database at the CRC. The study was reported according to CONSORT guidelines.

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Baseline evaluations

Abdominal circumference was measured at the end of a normal expiration at the level of the

iliac crest. Body weight was measured in duplicate in the morning following a 12-h fast with

the subject wearing a hospital gown and no shoes. The body mass index (BMI) was calculated

using standard formula. Office BP was measured with an oscillometric device (Omron HEM-

705CP, Tokyo, Japan) with the patient in the sitting position after 15 min of rest. The average

of three measurements two minutes apart was recorded. Blood was sampled the morning after

overnight fasting for laboratory assessments. UAE was measured in three consecutive

overnight urine collections and the median was recorded.

Then, GFR was measured by the plasma clearance of unlabeled iohexol (11) after a single,

intravenous injection of 5 ml iohexol solution (647 mg/ml Omnipaque 300; Nycomed

Amersham Sorin, Milano, Italy). Participants with GFR >120 ml/min (that is with a GFR

exceeding the upper limit of normal range for measured GFR) were defined as hyperfiltering,

and those with GFR ≤120 ml/min as non-hyperfiltering (5,14). The GFR was not normalized

for the body surface area (BSA) in order to avoid the confounding effect of changes in BSA

associated with diet induced changes in body weight (15,16) and absolute GFR values were

considered for the analyses. On the following day, total-body glucose disposal rate (GDR) was

assessed with hyperinsulinemic-euglycemic clamp (17).

Randomization and masking

Participants were randomly assigned (1:1) to 25% CR or to continue on their already

prescribed SD by a computer-generated list of random permuted blocks prepared by a

statistician (Giovanni Antonio Giuliano) of the CRC who was not involved in the analyses.

All data assessors were masked to treatment allocation.

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Intervention and Follow-up

Intervention in the SD aimed to reinforce compliance with the recommended diet. Patients in

the CR arm were provided with personalized dietary guidelines to decrease their daily calorie

intake by 25%. The nutrient composition recommended with both CR and SD interventions

was flexible to accommodate individual preferences, but was designed to provide 45 to 50%

of energy from carbohydrates, 30 to 35% from fat and 15 to 20% from proteins and to supply

100% of the daily recommended micronutrient intake, >20 g/day of fiber, and <300 mg/day of

cholesterol. Patients were encouraged to consume moderate and low glycaemic index and

nutrient-dense foods (18). No particular life-style modification was introduced. Dietary

prescriptions were based on energy intake at baseline, estimated by the subjects’ Resting

Metabolic Rate (RMR) using the Mifflin predictive equation (19), and results from the

Physical Activity Recall (PAR) and Total Daily Energy Expenditure (TDEE) questionnaire

(20). CR corresponded to a 25% calorie decrease from estimated total daily energy intake.

Patients allocated to the CR intervention were given a prescription of total calories to consume

daily and dietary plans based on exchange systems, which deliver a fixed amount of calories

per food portion. Weight loss goals were set together with the patients and in order to facilitate

adherence, patient-dietitian contact (in person, by telephone, or e-mail) was provided

throughout the study period once a week during the fist three months and once every two-

three weeks during the remaining three months. In case patient-dietitian contact did not prove

enough for maintaining dietary compliance, behavioral intervention strategies such as stimulus

control (avoiding triggers that prompt eating), social support (assistance from family members

and friends in modifying lifestyle behaviors), cognitive restructuring (thinking in a positive

manner), problem solving skills (systematic method of analyzing problems and identifying

possible solutions) and relapse prevention (methods to help recovery from episodes of

overeating or weight regain) were provided. Patients were instructed to keep daily records of

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their weight and weekly fasting glucose measurements. One week prior to each tri-monthly

follow-up visit, participants completed a 7-day food diary using household measures. Diaries

were analyzed by means of the dietary analysis software package MètaDieta, Version 1.0.2,

2009 (Me.Te.Da. S.r.l., San Benedetto del Tronto, AP, Italy) and used to assess compliance in

the allocated study group. The dietary software uses official national food composition

databases such as the INRAN's (Istituto Nazionale di Ricerca per gli Alimenti) and the IEO's

(Istituto Europeo di Oncologia).

Clinical and laboratory parameters, including serum urea levels taken as an indirect marker of

dietary protein intake, evaluated at baseline were re-evaluated at three and six months after

randomization, with the exception of GFR and GDR, which were re-evaluated at six months

only (final visit). At each visit, adverse events were recorded and physical and laboratory

parameters were assessed for safety.

Measurements

Blood and urine samples were collected after subjects had fasted overnight, and were

centrally analyzed at the CRC for Rare Diseases. Routine laboratory parameters were

measured by spectrophotometry (UniCel Synchron Clinical System DXC800, Beckman

Coulter, Inc., U.S.A.). Glycated hemoglobin values were expressed by using mmol/mol units

according to the International Federation of Clinical Chemistry (IFCC) and were then

converted in percent values according to the National Glycohemoglobin Standardization

Program (NGSP) by using the online HbA1c converter at http://www.ngsp.org/convert1.asp.

Serum insulin and angiotensin II concentrations by chemifluorescence (Access 2, Beckman

Coulter, Inc., U.S.A.) and the enzyme immunoassay kit (Angiotensin II SPIE-IA, Bertin

Pharma, Montigny le Bretonneux, France), respectively, and high sensitive C-reactive protein,

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apolipoprotein A, apolipoprotein B and urinary albumin by rate nephelometry (Immage,

Beckman Coulter, Inc., U.S.A.).

Statistical analyses

The primary endpoint was change in GFR at six-month follow-up vs baseline. Other

outcomes included changes in GDR (co-primary outcome), BP, heart rate (HR), blood

glucose, HbA1C, serum lipid, plasma renin activity, C Reactive Protein and safety variables

including vital signs, clinical laboratory tests and adverse events.

Sample size was estimated for the main pre-specified outcome variable assuming a two-group

t test (two-sided) of the difference between CR and SD. On the basis of GFR data available at

the database of the CRC at the time of study planning, we assumed a baseline mean (± SD)

GFR of 111±19.0 ml/min. We predicted a 15% GFR reduction from 111 to 94.35 ml/min

with CR and no change with SD. On the basis of these assumptions, a sample size of 29

evaluable participants per group would give the trial 90% power to detect as statistically

significant (α=0.05), two tailed test) the expected difference in GFR change between the two

treatment groups. To account for a 20% dropout rate, we planned to include 36 participants

per group.

All statistical analyses were conducted by modified intention-to-treat, using SAS (version

9.1) and STATA (version 12). Changes in GFR and all other between-group effects were

assessed by ANCOVA, adjusted for baseline measures. Within-group comparisons were

assessed by paired t tests, repeated-measures ANOVA, or McNemar test. Correlations were

tested with Pearson’s r correlation coefficient. Multiple regression models were used to

investigate the association between baseline independent covariates and GFR changes. We

considered age, sex and those baseline covariates that, in simple regression models, were

associated with GFR change at alpha=0.10 level of significance (two-tailed). In the case of

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correlated covariates, variable selection was guided by clinical criteria. To test the

relationships between changes in different considered parameters and concomitant 6-month

changes in GFR, we first identified which one among considered anthropometric, clinical and

metabolic variables and serum lipids had a strongest correlation with the outcome. Then, we

entered changes in these variables along with changes in mean BP (taken as a surrogate of

both systolic and diastolic BP) into a multivariable model considering GFR changes at 6

months as the outcome variable. Data were expressed as mean (SD), median (IQR), or

number (%) unless otherwise specified. All p values were two-sided.

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RESULTS

Of the 149 screened patients, 75 did not fulfil the selection criteria or declined to participate.

From September 2009 to May 2012, 36 of the 74 included patients were randomized to CR

and 38 to SD. Two participants withdrew from the CR arm at treatment months 1 and 5,

because of non-compliance. One participant on SD was excluded at month 3 due to a protocol

violation (initiation of RAS inhibition therapy during hospitalization because of atrial

fibrillation) and another one withdrew consent at month 3 for personal reasons. Thus, 34

participants on CR and 36 on SD completed the study and were available for final analyses

(Figure 1).

Patient characteristics

All 74 included patients were Caucasian: 56 (75.7%) were male and 11 (14.9%) were current

smokers. Age averaged 59.8±7.1 years. At baseline 34 participants (45.9%) were overweight

(BMI 25 to 29.9 Kg/m2) and 33 (44.6%) were obese (BMI >30 Kg/m

2), with a mean BMI of

29.8±3.8 kg/m2, and a waist circumference of 103.1±10.3 cm. The GFR averaged 107.9±20.0

ml/min and 20 (27.0%) patients were hyperfiltering. Blood pressure, blood glucose and

serum lipids were relatively well controlled. Other laboratory parameters were unremarkable.

Socio-demographic (Supplemental Table 1) and anthropometric, clinical and laboratory

parameters (Table 1), calorie intake, energy consumption and diet composition (Table 2), and

distribution of concomitant medications (Table 3) at inclusion were similar between groups,

with the exception of some excess of patients on statins in the standard diet group. Ten

patients per group were hyperfiltering (Table 1). Independently of treatment allocation, at

baseline the GFR correlated with body weight, BMI, serum angiotensin II levels, LDL/HDL

ratio and UAE (Supplemental Table 2).

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Treatment effect on kidney function

The GFR significantly decreased by 7.6±11.7% (p=0.0006) with CR, whereas the 2.7±11.1%

reduction observed with SD was not significant (p=0.172). GFR changes versus baseline

were significantly different between groups (p=0.0472) (Table 1 and Figure 2, Top Panel).

Within the hyperfiltering group, the GFR significantly decreased by 11.7±9.9% (p=0.005)

with CR, whereas the 5.3±9.0% reduction observed with SD failed to achieve statistical

significance (p=0.095). In the non-hyperfiltering group, the GFR decreased by 3.8±8.1%

(p=0.032) with CR and did not change appreciably with SD (Table 1, Figure 2, Middle and

Bottom Panel). GFR reduction tended to be larger in patients with BMI >30 kg/m2 than in

those with smaller BMI. No significant change was observed with SD in both BMI groups

(Table 1).

UAE decreased significantly from 5.1±2.7 to 4.4±2.4 µg/min (p=0.0248) in the CR group but

did not change appreciably in the SD group (Table 1, Supplemental Figure 1, Bottom panel).

Treatment effect on other considered parameters

ANTHROPOMETRIC PARAMETERS –Body weight decreased by 4.7±5.5 kg (5.2±5.8%) in the CR

group (p<0.0001) and by only 0.6 ±1.6 kg (0.7±1.9%, p=0.031) in the SD group (Table 1,

Supplemental Figure 2, Top Panel). These changes were significantly different between

groups (p=0.0001). BMI consistently decreased by 1.6+1.9 kg/m2 (5.2+5.8%, p<0.0001), and

waist circumference by 5.9+4.7 cm (5.8+4.5%, p<0.0001) with CR, and by only 0.2+0.6

kg/m2 (0.7+1.9%, p=0.034) and 1.6+3.5 cm (1.5+3.4%, p=0.009), respectively, with SD.

Changes were significantly different between groups (p<0001 for both parameters, Table 1,

Supplemental Figure 2 Middle and Bottom Panel).

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CLINICAL AND LABORATORY PARAMETERS – Systolic (p=0.0003), diastolic (p<0.0001) and mean

(p<0.0001) BP consistently decreased with CR, and only marginally decreased with SD.

Interestingly, HR also decreased significantly with CR (p=0.0003), but did not change

appreciably with SD. Changes between groups were significantly (p<0.05) different for all

considered parameters (Table 1, Supplemental Figure 3).

Both serum glucose (p=0.0001) and HbA1C (p=0.0001) levels significantly decreased with

CR, and on SD the opposite trend was observed, which was significant for HbA1C

(p=0.039). Changes in both parameters were significantly different (p=0.0004 and p<0.0001

respectively) between groups (Table 1, Figure 3, Top and Middle Panel). These changes were

associated with a significant increase in GDR with CR (p=0007). GDR was stable with SD

and GDR changes were significantly different between the two treatment groups (p=0.0075,

Table 1, Figure 3, Bottom Panel). In patients without long-acting insulin therapy, insulin

levels were similar between treatment groups and did not change appreciably during the

observation period.

Serum HDL levels increased (p=0.043) and LDL levels decreased (p= 0.027) with CR. The

opposite was observed in SD. Thus the LDL/HDL ratio significantly decreased with CR

(p<0.01) and tended to increase in SD. Changes in this parameter were significantly different

between groups (p=0.023, Table 1). Other considered parameters did not change appreciably

within and between groups (Table 1)

Changes in BP, metabolic control and serum lipids were not explained by changes in

concomitant treatment since the distribution of different BP and lipid lowering medications in

the two groups did not change appreciably during the study, and the proportion of patients on

oral hypoglycemic agents similarly increased in both groups (Table 3).

OTHER LABORATORY PARAMETERS – Aspartate transaminase (p=0.0001) and alanine

aminotransferase (p=0.0001) levels both decreased with CR and tended to increase with SD.

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Changes between groups were significantly different (p=0.0067 and p= 0.0089, respectively,

Table 1). Creatinphosphokynase did not change appreciably within and between groups. Hs-

CRP levels significantly decreased (p=0.0075) on CR and did not change appreciably with

SD, whereas serum angiotensin II levels tended to decrease with CR and to increase with SD.

Changes in both variables were significantly different between groups (p=0.0164 and

p=0.0421, respectively, Table 1, Supplemental Figure 1, Top and Middle panel).

Calorie intake, energy consumption and diet composition

According to seven-day food diaries, mean energy intake decreased by 14.95±17.8%

(p<0.0001) with CR and 5.35±15.7% (p=0.049) with SD. These changes were significantly

different between groups (p=0.0061), whereas RMR, MET and TDEE did not change

appreciably within and between groups (Table 2). Calorie intake reduction achieved in the

CR, compared to the SD group, was largely explained by a reduced intake of carbohydrates

and alcohol, whereas the total intake of proteins was similar between groups as documented

by data obtained by dietary diaries evaluation, including data on phosphate intake (Table 2),

and by serum urea values that were very similar between treatment groups and did not change

appreciably throughout the whole study period (Table 1). The dietary intake of

monounsaturated fatty acids, saturated fats, animal proteins and fat decreased, whereas the

intake of total fiber, polyunsaturated fatty acids and vegetable fat increased with CR

compared to SD (Table 2). Subjects in the CR group introduced significantly more iron,

magnesium, phosphorus, potassium, vitamin C, riboflavin, folate and beta-carotene than

those in the SD group, whereas the intake of other dietary micronutrients was similar between

groups. In particular, sodium intake was very much the same at inclusion and decreased

similarly in the two groups during the study (Table 2).

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Correlation analyses and predictors of GFR reduction

GFR reduction significantly correlated with body weight (p=0.048), BMI (p=0.017) and GFR

(p=0.008) at inclusion. At multiple regression analyses, considering the variables listed in

Table 1, which at simple regression analyses were associated with the outcome at a

significance level of p<0.10, GFR reduction was predicted by CR (p=0.045) and baseline

GFR (p=0.004).

GFR reduction significantly correlated also with reduction in daily calorie intake, body

weight, BMI, waist circumference, systolic, diastolic and mean BP, blood glucose, serum

triglyceride levels and an increase in GDR (Table 4). The correlation between changes in

GFR and body weight was significant in the study group as a whole (r=0.409, p=0.0007) and

in patients with CR (r=438, p=0.0095) considered separately, but not in those with SD.

(r=0.271, p=0.133). At multivariable regression analyses, the reduction in mean BP was the

strongest predictor of GFR reduction. The association of weight reduction with GFR

reduction was borderline significant, whereas changes in blood glucose and serum

triglycerides had no predictive value (similar findings were observed when diastolic BP was

entered into the model instead of mean BP) (Table 4). Independently of treatment allocation,

1 mmHg of mean BP reduction and 1 kg of weight loss were associated with a mean GFR

reduction of 0.45 and 0.60 ml/min, respectively.

Safety

There were only two serious adverse events, both in the SD group. Overall, non-serious

adverse events were generally mild and transient in nature and were similarly distributed

between groups. Viral and respiratory tract infections were slightly more frequently reported

in the SD group, whereas muskuloscheletal events tended to be more frequent with CR

(Table 5). No event, however, was considered to be treatment-related by the investigators.

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DISCUSSION

In this PROBE clinical trial in Type-2 diabetes patients with abdominal obesity, six-month

CR significantly decreased GFR compared to SD, an effect that was largely driven by GFR

reduction in patients with higher GFR to start with, and which was associated with a

reduction in waist circumference, body weight, BMI, systolic and diastolic BP, blood

glucose, serum LDL/HDL cholesterol levels, and amelioration of insulin sensitivity, as

assessed by euglycemic hyperinsulinemic clamps in all patients. Of interest, every one-Kg of

weight loss was associated with approximately one ml/min GFR reduction. Both CR and SD

were tolerated well and no side effects possibly related to inadequate or unbalanced nutrient

supply were observed throughout the study. Treatment effect was unlikely explained by

changes in factors independent of CR that can affect glomerular hemodynamics, such as

protein and sodium intake, which was very much the same between treatment groups, or

phosphorus intake, which in fact happened to be slightly higher with SD than with CR.

Moreover, baseline patient characteristics and distribution of concomitant medications at

inclusion and during the study were also similar between groups. Thus, study results appear

to reflect a genuine effect of CR on glomerular filtration.

These findings could have clinical implications, since persistent hyperfiltration predicts a

faster GFR decline and an excess risk of progression to micro- or macroalbuminuria in

patients with Type-1 (2) or Type-2 diabetes (5,21), whereas amelioration of hyperfiltration is

associated with a slower GFR decline in the long-term, and nephroprotection (5). We

previously found that in a large cohort of patients quite similar to the CRESO cohort, a larger

GFR reduction at six months strongly and independently predicted a slower GFR decline in

the long term (5). In particular, a 7.6% short-term GFR reduction similar to that achieved by

CR predicted a mean (SEM) long-term GFR decline of 0.08 (013) ml/min/1.73m2 per month,

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whereas a 2.7% reduction similar to that observed in patients on SD predicted a long-term

decline of 0.36 (0.07) ml/min/1.73m2 per month. If the above findings are generalized to our

CRESO cohort, we can speculate that CR might reduce the rate of long term GFR decline by

approximately four to five folds as compared to SD. This renoprotective effect might

translate into a rate of renal function loss similar to that observed in healthy adults with aging

(22). Interestingly, the benefit of CR on glomerular dysfunction was more consistent and

clinically relevant in those patients with the highest GFR at baseline. Thus, the renoprotective

effect of CR is expected to be larger right in those patients who, because of hyperfiltration,

are at increased risk of accelerated renal function loss (5).

Finding that large part of the effect of CR on kidney function appeared to be explained by the

reduction in blood pressure and, to a lower extent, by weight reduction is consistent with the

hypothesis that early rise in GFR in obesity is largely mediated by sodium retention (23).

Increased renal sodium reabsorption, which appears to be mediated by activation of the

RAAS and sympathetic system and altered intrarenal physical forces, may eventually result

in volume expansion and increased blood pressure (24). Moreover, increased proximal

tubular reabsorption may reduce sodium chloride delivery to the macula densa and cause via

deactivation of tubuloglomerular feedback, reductions in afferent arteriolar resistance and

increases in glomerular perfusion and filtration (8,23,25). Thus, we speculate that CR might

reduce the GFR by reducing the sodium pool and therefore reducing blood pressure and

kidney perfusion. This effect could be mediated by decreased RAAS and sympathetic

activity, as suggested by the reduction in angiotensin II levels and heart rate we observed

with CR as compared to SD. Enhanced responsiveness to natriuretic peptides, that may even

precede CR-induced weight loss, might also play a role (26). Moreover, by reducing tubular

sodium reabsorption, CR might enhance sodium chloride delivery to the macula densa,

restore pre-glomerular resistances and therefore limit glomerular hyperperfusion and

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consequent hyperfiltration. Aforementioned findings, however, must be interpreted with

caution due to the post hoc and observational nature of the analyses and mechanisms

mediating the effects of CR on kidney function should be investigated in prospective

pathophysiology studies.

CR was associated also with other clinically relevant functional and metabolic effects:

i. AMELIORATION OF METABOLIC, BLOOD PRESSURE AND LIPID CONTROL – These changes were

associated with a significant increase in GDR with CR compared to SD, an effect that

indicated amelioration of insulin sensitivity. This functional effect most likely explained

blood glucose and HbA1C reduction in the active treatment arm and probably could have

contributed, at least in part, to BP reduction and amelioration of dyslipidemia in this

subgroup. However, this effect could not be explained by changes in energy consumption

and concomitant medications which were similar between groups. Independent of

involved mechanisms, amelioration of the above functional and metabolic parameters can

be seen in the context of an overall amelioration of metabolic syndrome, and are expected

to translate into a clinically relevant reduction in long-term cardiovascular risk.

Interestingly, the increase in GDR was also independently associated with GFR reduction,

a finding that is consistent with the hypothesis that insulin resistance may also have a role

in the pathogenesis of glomerular hyperfiltration (27).

ii. REDUCTION IN SYMPATHETIC TONE AND RENIN-ANGIOTENSIN-SYSTEM ACTIVITY - The significant

decrease in HR and serum angiotensin II levels observed with CR compared with SD

might have clinical relevance. Indeed, a high resting HR has long been independently

associated with an increased risk of all-cause mortality and cardiovascular complications

in Type-2 diabetes (28) - as well as in the general population (29) - and, more recently,

with new onset and worsening of retinopathy and nephropathy (30): findings that are most

likely explained by the increase in BP and sympathetic activity associated with overweight

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and obesity (31). Consistently, long-term CR reduced HR and improved its variability in

overweight but otherwise healthy adults, an effect associated with reduced sympathetic

activity and concomitant increase in parasympathetic nervous system tone (32). RAS

activation is another cardiovascular risk factor which has also been involved in the

pathogenesis of glomerular hyperfiltration and progression of renal disease in

experimental and human diabetes (33,34). Actually, the initial state of hyperfiltration

associated with excessive adiposity, especially if centrally located, is largely sustained by

raised systemic and renal production of angiotensin II, (35) which may promote systemic

and local chronic inflammation, reactive oxygen species formation, lipogenesis and

hypertension (35,36), with progressive renal dysfunction and structural damage (37). We

consistently found that six months of CR significantly reduced C-reactive protein, a

systemic marker of inflammation and an independent cardiovascular risk factor (38). The

small reduction in albuminuria we observed with CR might also have clinical relevance

since albuminuria has been identified as an independent and continuous risk factor for

renal and cardiovascular disease, even in the normoalbuminuric range (39).

iii. DECREASE IN LIVER AMINOTRANSFERASE LEVELS - This effect was most likely explained by

reduced alcohol intake, but also by weight loss and improved insulin resistance achieved

by CR. Elevated liver enzymes are a risk of progressive non-virus related non-alcoholic

fatty liver disease in Type-2 diabetes, and they associate strongly with increased

glycosylated hemoglobin, insulin resistance and obesity. Reduced liver aminotransferase

levels through CR could preserve liver function and reduce steatohepatitis, as primary

prevention requires weight loss, improved glucose control, and metabolic syndrome

amelioration (40).

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19

Strengths and limitations

The number of participants was estimated a priori on the basis of the expected treatment

effect, which made it possible to adequately power analyses despite the relatively small

sample size. Moreover this was a pilot, exploratory and technically challenging study, and

renal function, insulin sensitivity and albuminuria were measured by gold standard

techniques, which, by reducing the risk of random data fluctuations, increased the statistical

power of study analyses. Protein intake was not monitored by measuring urinary urea

excretion since 24-hour urine collections were not available. However, finding that serum

urea levels were stable over time and comparable between treatment groups at all visits,

along with data from dietary diaries evaluation, confirmed that protein intake was comparable

between groups and stable over time, and reasonably, could not explain the GFR changes

observed with calorie restriction. This conclusion is corroborated by finding that at least 50 to

60 percent reduction in dietary proteins is needed to obtain an appreciable change in GFR,

and that protein intake in both CRESO group was more than double than that reported in the

low protein diet groups of previous studies in patients with diabetes (41,42).

Despite the highly labor-intensive design, the study had a high retention rate of enrolled

participants and good adherence to the study interventions, as shown by the successful weight

and waist circumference reduction achieved by CR. These findings confirm that compliance

to dietary recommendations is an achievable goal provided that dieticians and doctors are

strongly motivated and are devoted enough to transmit their motivations also to more

disinclined patients. A “trial effect” most likely explained why during the treatment period

some weight loss was observed in controls on the SD too, an effect that most likely

diminished between-group differences in at least some of the considered outcome variables.

Finding that the treatment effect was captured despite this limiting factor provided additional

evidence of the robustness of the results. However, whether these results can also be

of 43 Diabetes

20

generalized to obese patients without diabetes must be investigated. One major strength was

the PROBE design, which allowed blinded analyses of outcome variables despite the open

design, and at the same time minimized costs and closely reflected standard clinical practice,

which should make the results more easily applicable in routine medical care (43). Changes

in considered variables over the follow-up period were consistent and uniformly confirmed

the potential beneficial effect of CR on a series of renal and cardiovascular risk factors.

However, whether this short-term effect will/can translate into long-term nephro and

cardioprotection in this clinical context needs to be addressed in longer and appropriately

powered trials.

Conclusions

CR-induced negative energy balance results in substantial improvements of several major

risk factors for the initiation and progression of CKD in diabetic patients with abdominal

obesity and no evidence of renal involvement. In particular, CR and weight loss, along with

amelioration of insulin resistance and other functional and metabolic abnormalities, achieved

a significant short-term reduction in the GFR that conceivably reflected amelioration of

glomerular hyperfiltration and that resembled the reduction observed following an invasive

procedure such as bariatric surgery (8). Long-term randomized clinical trials are needed to

assess whether calorie restriction may achieve clinically relevant protection against

progressive renal function loss and development of nephropathy in the long-term, as well as

reduce overall patient cardiovascular risk.

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21

ACKNOWLEDGEMENTS

AUTHOR CONTRIBUTIONS - Luigi Fontana, Giuseppe Remuzzi and Piero Ruggenenti had the

original idea; Giuseppe Remuzzi, Stefano Rota, Manuela Abbate, Piero Ruggenenti and Luigi

Fontana wrote the study protocol; Manuela Abbate, Barbara Ruggiero, Stefano Rota, Matias

Trillini, Carolina Aparicio, Aneliya Parvanova and Ilian Petrov Iliev identified, treated and

monitored study participants and contributed to data recording; Manuela Abbate and

Giovanna Pisanu prescribed CR or SD and monitored compliance to the recommended diets;

Annalisa Perna and Angela Russo performed the statistical analyses, Olimpia Diadei

monitored the study, Davide Martinetti prepared the data base and helped in data handling;

Antonio Cannata, Fabiola Carrara, Silvia Ferrari, and Nadia Stucchi performed all the GFR

measurements and laboratory tests; Manuela Abbate, Luigi Fontana, Giuseppe Remuzzi and

Piero Ruggenenti contributed to data analyses and interpretation; Luigi Fontana and Manuela

Abbate wrote the first draft and Piero Ruggenenti the final version of the manuscript. All the

Authors had direct access to original data, critically revised the draft and approved the final

manuscript. Giuseppe Remuzzi is the guarantor and takes final responsibility for the contents

of the manuscript. No medical writer was involved.

The Authors are indebted to Flavio Gaspari who supervised all the laboratory analyses; Jorge Arturo

Reyes Loaeza, Claudia Patricia Ferrer Siles, Karen Courville, Patricia Espindola, Silvia Prandini,

Veruscka Lecchi and Svitlana Yakymchuk who took care of the study participants, Giovanni Antonio

Giuliano who generated the list of random permuted blocks, Nadia Rubis and Giulia Gherardi who

respectively supervised the monitoring of the study and the activities of the day hospital of the CRC;

Paola Boccardo who took care of the ethical and regulatory aspects of the trial; Norberto Perico and

the staff of the CRC who contributed to the conduction of the study (all from IRCCS – Istituto di

Ricerche Farmacologiche Mario Negri, Centro di Ricerche Cliniche per le Malattie Rare “Aldo e Cele

Daccò”, Bergamo, Italy); Antonio Bossi (ASST Ospedali di Treviglio-Caravaggio and Romano di

of 43 Diabetes

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Lombardia), Ruggero Mangili (ASST Ospedale Bolognini di Seriate), Roberto Trevisan (ASST

Ospedale Papa Giovanni XXIII of Bergamo, and the staff of their Outpatient Clinics for the major

contribution to patient screening and selection.

FUNDING - This research was supported by grants from the ISS/NIH Collaborative Projects of the

Italian Ministry of Health, the Bakewell Foundation, the Longer Life Foundation (an

RGA/Washington University Partnership). The sponsors had no role in study conduction and

reporting.

CONFLICTS OF INTEREST

All the Authors declare they have no conflicts of interest.

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LEGENDS TO THE FIGURES

Figure 1

Study flow-chart

Figure 2

GFR at baseline and at six-month follow-up according to randomization to CR or SD in the

whole study group (Top panel) and in the two subgroups with (Middle panel) or without

(Bottom panel) hyperfiltration at inclusion.

Figure 3

GDR (Top panel) and HbA1C (Middle panel) and Blood Glucose (Bottom panel)

concentrations at baseline and at six-month follow-up according to randomization to CR or

SD.

of 43 Diabetes

Table 1. Baseline and six-month primary and secondary outcome measures in the two study groups.

Calorie Restriction Standard Diet

Baseline Six months Baseline Six months p-value†

Anthropometric variables

Waist circumference (cm) 104·1 (9·4) 98·2 (10·7)** 102·3 (10·2) 100·7 (9·9)* <0·0001

Weight (Kg) 87·2 (13·7) 82·5 (13·2)** 83·4 (15·0) 82·8 (14·7)° 0·0001

BMI (Kg/m-2)

- BMI <30 Kg/m-2

- BMI >30 Kg/m-2

30·0 (3·9)

27.1 (1.7)

33.7 (2.4)

28·4 (3·8)**

25.9 (1.9)°°

31.6 (3.0)*

29·6 (3·8)

27.0 (2.0)

32.7 (2.9)

29·3 (3·7)°

26.8 (2.0)

32.5 (2.7)

<0·0001

0.0065

0.0064

Clinical parameters

SBP (mmHg) 127·8 (9·7) 121·1 (9·9)°° 129·3 (9·1) 126·1 (8·6)° 0·0322

DBP (mmHg) 80·5 (7·1) 75·3 (7·1)** 79·6 (7·3) 77·6 (7·3) 0·0349

MAP (mmHg) 96·3 (6·9) 90·6 (7·5)** 96·2 (7·3) 93·8 (7·1)° 0·0222

HR (beats/min) 68·2 (8·8) 63·7 (8·6)°° 67·0 (8·7) 66·7 (7·8) 0·0094

Metabolic variables

GDR (mg/kg/min) 6·1 (2·3) 7·9 (3·1)°° 6·4 (2·0) 6·6 (2·2) 0·0075

Serum glucose (mg/dL) 138·9 (26·0) 120·8 (26·9)** 141·6 (25·6) 148·6 (41·5) 0·0004

HbA1c (mmol/mol, IFCC) 50·7 (11·1) 44·9 (7·6)** 48·4 (8·1) 51·3 (10·9)° <0·0001

HbA1c (%, NGSP) 6·8 (1·0) 6·3 (0·7)** 6·6 (0·7) 6·8 (1·0)° <0·0001

Fasting Insulin (µIU/L)^ 7·3 (3·4) 6·5 (5·4) 7·8 (4.6) 8.7 (4·6) 0·3738

Lipids

Total cholesterol (mg/dL) 171·2 (27·1) 167·3 (27·3) 171·4 (29·4) 172·8 (35·1) 0·3384

HDL-cholesterol (mg/dL) 41·0 (11·3) 43·4 (10·8)° 41·8 (11·2) 41·0 (10·9) 0·0501

LDL-cholesterol (mg/dL) 106·9 (26·1) 103·4 (27·8)° 105·8 (30·5) 106·8 (32·0) 0·3718

LDL/HDL 2·8 (0·97) 2·5 (0·91)* 2·6 (0·83) 2·7 (0·96) 0·0234

Triglycerides (mg/dL) 99·0 (35·7) 85·4 (34·3)° 117·8 (70·0) 132·1 (126·3) 0·1182

Apolipoprotein A (mg/dL) 136·2 (19·6) 135·0 (15·9) 136·9 (16·8) 132·2 (21·8) 0·2030

Apolipoprotein B (mg/dL) 84·3 (17·6) 79·9 (18·6) 86·4 (19·2) 86·4 (20·9) 0·1278

Other markers

Hs-CRP (mg/dL) 0·32 (0·28) 0·20 (0·20)* 0·25 (0·33) 0·27 (0·34) 0·0164

AST (IU/L) 22·6 (4·1) 20·2 (3·5)** 22·7 (5·4) 25·7 (17·7) 0·0067

ALT (IU/L) 26·0 (7·8) 21·9 (6·4)** 26·2 (10·3) 34·2 (47·2) 0·0089

CPK (IU/L) 149·0 (141·4) 123·0 (67·9) 132·1 (89·5) 113·5 (73·2)° 0·798

Angiotensin II (pg/ml) 4·6 (3·5) 3·5 (2·9) 4·0 (2·7) 5·0 (4·2) 0·0421

Urea (mg/dl) 37·6 (8·3) 39·5 (8·7) 38·8 (9·4) 39·0 (7·7) 0·3930

Kidney function

GFR (ml/min)

- Overall 107·8 (21) 100·2 (16·5)°° 109·2 (19) 106·5 (20·2) 0·0472

- Hyperfiltering 134.4 (8.7) 118.1 (8.5)* 130.9 (8.8) 123.8 (13.2) 0.245

- Non-hyperfiltering 96.7 (12.9) 92.7 (12.9)° 99.4 (13.2) 98.6 (17.9) 0.237

- BMI <30 Kg/m-2 99.5 (18.6) 95.2 (15.7)° 104.1 (17.3) 104.4 (18.4) 0.079

- BMI >30 Kg/m-2 118.2 (19.6) 106.4 (15.8)* 115.1 (19.7) 108.9 (22.6) 0.279

UAE (mg/min)# 5·1 (2·7) 4·4 (2·4)° 4·5 (2·7) 4·3 (2·3) 0·268

of 43Diabetes

Data are mean (SD). BMI = body mass index; GDR = glucose disposal rate; HbA1C = Glycated Hemoglobin (normal

range: 25.0 to 28.9 mmol/mol or 4.4 to 5.7%); SBP = systolic blood pressure; DBP = diastolic blood pressure; MAP =

mean arterial pressure; HR = heart rate; LDL = low density lipoprotein; HDL = high density lipoprotein; Hs-CRP= High

sensitivity C reactive protein; AST = aspartate transaminase; ALT = alanine aminotransferase; CPK = Creatin

phosphokynase; GFR = glomerular filtration rate; UAE = Urinary Albumin Excretion. †Comparisons of changes in the

Calorie Restriction as compared to the Standard Diet group at six months after adjustment for baseline values by

analysis of covariance (ANCOVA). ^analysis carried out excluding patients receiving long-acting insulin therapy.

°p<0.05, *p≤0.01, °°p≤0.001, **p≤0.0001 vs baseline within the same treatment group.#logtransformed

of 43 Diabetes

Table 2

Baseline and six-month metabolic parameters and daily diet macro- and micro-nutrients in the two

study groups

Calorie restriction Standard Diet

Baseline Six months Baseline Six months †p-value

Metabolic parameters

RMR (Kcal) 1614.3 (236.8) 1558·7 (233·6)** 1544.0 (255.7) 1536·1 (250·7)° 0·0001

MET (hors/day) 34.5 (3.7) 34·8 (4·2) 34.6 (3.1) 35·0 (4·9) 0·9293

TDEE (Kcal) 2327.4 (459.2) 2254·3 (405·9)° 2230.8 (430.0) 2245·0 (523·1) 0·1630

Calorie Intake (Kcal) 1899.5 (496.5) 1570·9 (384·6)** 1896.5(524.1) 1760·5 (423·8)° 0·0061

Macronutrients

Protein (%) 17.7 (2.2) 20·1 (2·6)°° 18.5 (2.5) 18·3 (2·6) 0·0006

Total lipid (%) 34·5 (5·7) 35·7 (4·8) 34·4 (5·1) 34·4 (6·0) 0·2719

Carbohydrate (%) 48·0 (6·9) 44·4 (5·3)* 47·2 (6·4) 47·5 (7·8) 0·0132

Protein (g) 81·0 (19·6) 74·6 (18·3)° 82·4 (20·6) 75·8 (20·0)* 0·9686

Total lipid (g) 70·9 (22·3) 59·8 (12·1)°° 68·9 (21·2) 63·2 (16·1)° 0·1134

Carbohydrate (g) 234·4 (69·1) 183·9 (61·2)** 230·2 (76·5) 211·8 (60·3)° 0·0074

Total dietary fiber (g) 23·6 (8·7) 23·9 (6·5) 20·1 (6·9) 18·7 (6·0) 0·0053

Alcohol (g) 8·3 (10·9) 5·9 (7·4) 12·2 (13·4) 13·8 (13·0) 0·0047

MUFA (g) 30·5 (9·7) 24·8 (5·2)** 28·8 (9·4) 26·9 (8·2) 0·0488

PUFA (g) 9·3 (3·8) 9·7 (3·1) 8·6 (3·8) 8·2 (2·8) 0·0534

Satured fats (g) 22·8 (7·9) 16·4 (4·4)** 23·0 (7·4) 20·7 (6·3)° 0·0001

Animal protein (g) 52·5 (15·1) 46·7 (11·1)° 56·1 (15·0) 50·4 (15·0)* 0·0337

Vegetable protein (g) 27·3 (10·5) 27·9 (10·5) 25·1 (8·9) 24·3 (8·8) 0·2098

Micronutrients

Calcium (mg) 857·7 (341·8) 849·4 (250·1) 824·8 (226·6) 775·8 (347·0) 0·3771

Iron (mg) 12·6 (4·3) 14·2 (4·5)° 11·7 (4·0) 11·3 (3·6) 0·0042

Magnesium (mg) 225·75 (89·9) 230·25 (63·8) 252·5 (68·1) 232·7 (68·1) 0·0335

Phosphorus (mg) 1287·9 (387·7) 1280·55 (280·1) 1251·0 (331·0) 1174·2 (359·4) 0·0099

of 43Diabetes

Potassium (mg) 3111·3 (912·4) 3241·0 (610·35) 2911·4 (728·9) 2815·1 (689·5) 0·0109

Sodium (mg) 2024·1 (874·3) 1821·1 (854·3) 2026·8 (699·2) 1906·7 (800·9) 0·6323

Zinc (mg) 11·5 (3·3) 11·25 (2·5) 11·1 (2·8) 10·4 (3·0)° 0·2234

Copper (mg) 1·0 (0·47) 0·94 (0·29) 0·95 (0·37) 0·94 (0·32) 0·8506

Selenium (µg) 36·9 (14·1) 38·2 (15·6) 38·8 (15·4) 38·0 (16·5) 0·7106

Vitamin A(µg) 1137·4 (648·3) 1311·1 (823·9) 1208·7 (643·0) 1245·8 (677·1) 0·5430

Vitamin D (µg) 3·0 (2·4) 3·0 (1·9) 2·5 (1·5) 2·5 (1·7) 0·3194

Vitamin E (mg) 10·0 (3·4) 10·7 (2·4) 8·7 (2·7) 9·2 (3·2) 0·1025

Vitamin C (mg) 137·0 (70·4) 170·8 (77·5) 106·8 (49·3) 101·5 (48·7) 0·0002

Thiamin (mg) 1·2 (0·34) 1·1 (0·33) 1·1 (0·34) 1·0 (0·29) 0·1313

Riboflavin (mg) 1·6 (0·52) 1·7 (0·41) 1·6 (0·45) 1·5 (0·44) 0·0232

Niacin (mg) 20·4 (6·9) 19·8 (5·8) 21·3 (6·4) 18·8 (4·5)* 0·1798

Pantothenic acid (mg) 2·1 (0·79) 2·3 (0·66) 2·4 (0·71) 2·3 (0·79) 0·3889

Vitamin B-6 (mg) 1·8 (0·47) 1·9 (0·44) 1·7 (0·43) 1·6 (0·40) 0·0587

Folate (µg) 295·7 (112·5) 337·6 (106·3) 261·1 (105·6) 265·4 (89·5) 0·0066

Beta-carotene (mg) 3754·9 (3187·05) 4545·2 (2018·3) 3320·9 (2279·7) 3572·6 (2150·1) 0·0332

Data are mean (SD). Abbreviations:RMR = resting metabolic rate; MET = metabolic equivalent for task;

TDEE: Total daily energy expenditure, MUFA = mono unsaturated fattu acid; PUFA = poly unsaturaded fatty

acids. †Comparisons of changes in the Calorie Restriction as compared to the Standard Diet group at six months

after adjustment for baseline values by analysis of covariance (ANCOVA). °p<0.05, *p≤0.01, °°p≤0.001,

**p≤0.0001 vs baseline within the same treatment group.

of 43 Diabetes

Table 3

Patients with concomitant medications at baseline and at six-month follow-up in the two treatment

groups

Data are absolute number (%). No significant difference was observed between the two groups at

baseline and at six months, as well as between changes at six month vs baseline in the two groups.

Calorie restriction

(n=34) Stanndard Diet

(n=36)

Concomitant medications Baseline Six months Baseline Six months

Hypoglycaemic agents

Any 19 29 18 29

Oral Hypoglycemic agents alone 17 26 15 26

Insulin and oral hypoglycemic agents 2 3 3 3

Antihypertensive agents

Any 12 12 11 13

Diuretic 5 7 0 3

Beta-blocker 2 3 6 6

Calcium-channel blockers 4 6 3 3

Sympatholytic agents 1 1 0 1

ACE inhibitors, Angiotensin

Blockers 0 0 0 2

Lipid-lowering agents

Any 10 10 21 19

Statin alone 9 9 21 18

Fibrate alone 1 1 0 o

Statin and fibrate 0 0 0 1

Antiplatelet agent 2 2 8 7

of 43Diabetes

Table 4

Correlation and multivariable analyses of the relationships between GFR changes (ml/min) at six months

compared to baseline and concomitant changes in other considered covariates

Correlation analyses Multivariable analyses

r p-value SββββC p-value

Anthropometric parameters

Weight (kg) 0·41 0·0007 0.2379 0.0613

BMI 0.39 0.011

Waist circumference (cm) 0·32 0·0095

Clinical parameters

SBP (mmHg) 0·27 0·030

DBP (mmHg) 0·41 0·0006

MAP 0.39 0.0012 0.2484 0.0384

HR 0.041 0.746

Metabolic parameters

GDR (mg/kg/min) -0·25 0·048

Blood glucose (mg/dL) 0·30 0·016 0.0764 0.5511

Hba1c -0.02 0.87

Fasting Insulin 0.23 0.068

Serum lipids

Total cholesterol 0.14 0.270

HDL -0.01 0.935

LDL 0.02 0.815

LDL/HDL 0.07 0.604

Triglycerides 0.35 0.0043 0.2031 0.1022

Apolipoprotein A 0.10 0.429

Apolipoprotein B 0.10 0.436

Other markers

Hs-CRP 0.01 0.968

AST -0.13 0.284

ALT -0.11 0.363

CPK -0.05 0.688

Angiotensin II 0.20 0.108

UAE 0.21 0.97

r = Pearson correlation coefficient; SΒC = Standardized Beta Coefficient BMI = body mass index; GDR =

glucose disposal rate; HbA1C = Glycated Hemoglobin; SBP = systolic blood pressure; DBP = diastolic

blood pressure; MAP = mean arterial pressure; HR = heart rate; LDL = low density lipoprotein; HDL =

high density lipoprotein; Hs-CRP= High sensitivity C reactive protein; AST = aspartate transaminase; ALT

= alanine aminotransferase; CPK = Creatin phosphokynase; UAE = Urinary Albumin Excretion

of 43 Diabetes

Table 5. Serious and non-serious adverse in the two treatment groups

Calorie

Restriction

Standard

Diet

Serious Adverse Events

Atrial fibrillation 0 1

Prostatic intraepithelial neoplasia 0 1

Total 0 2

Non Serious Adverse Events

Flu-like symptoms, cough, bronchitis, synusitis 2 9

Stranguria, cystitis 4 2

Cervical, shoulder, knee pain 4 1

Muscolar strain/pain 4 1

Tooth extraction/ache, gengivitis 3 3

Traumatic back, ankle, wrist pain 3 1

Headache/migraine 0 2

Transient lymphocytopenia/eosinophilia 2 0

Basal cell carcinoma right zygomus 0 1

Prostatic hypertrophy 1 0

Nephrolythiasis 0 1

Right finger Dupuytren’s fibromatosis 0 1

Vagal reaction 1 0

Epigastralgia 0 1

Cervical ernia 0 1

Labyrinthitis 1 0

Transient liver transaminases increase 0 1

Transient C Reactive protein increase 0 1

Total 25 26

of 43Diabetes

75 excluded:

- 24 did not meet inclusion criteria

- 42 declined participation

- 9 for other reasons

74 randomized

36 allocated to Calorie Restriction

34 completed all visits

2 excluded because

of non-compliance

34 included in intention-to-treat

analysis

149 screened patients

38 allocated to Standard Diet

36 completed all visits

2 excluded:

1 unrelated SAE

1non-compliance

36 included in intention-to-treat

analysis

Figure 1

of 43 Diabetes

GF

R

(ml/m

in)

80

100

130

90

110

120

p = 0.0472

p = 0.0006

Ba

se

lin

e

6 m

on

ths

Ba

se

lin

e

6 m

on

ths

80

100

130

p = 0.0064

90

110

120

80

100

P = 0.025

90

110

140

Figure 2

GF

R

(ml/m

in)

GF

R

(ml/m

in)

CR SD

of 43Diabetes

CR SD

Blo

od

glu

co

se

(m

g/d

L)

170

90

110

130

150

p = 0∙0004

p < 0∙0001

Figure 3

GD

R

(mg

/kg

/min

)

12

0

2

4

6

8

10

p = 0∙0075

p = 0∙0007

Bas

eli

ne

6 m

on

ths

Bas

eli

ne

6 m

on

ths

Hb

A1

c

(mm

ol/m

ol)

55

40

45

50

p < 0∙0001

p < 0∙0001 p = 0∙039

of 43 Diabetes

Supplemental Table 1

Baseline socio-demographic characteristics of patients in the two treatment

groups

Calorie Restriction Standard Diet

Age (years) 60.2 (7·2) 59·5 (7·1)

Male gender 29 (80·6%) 27 (71·1%)

Smoking Habits

Non-smoker 17 (47·2%) 16 (42·1%)

Current smoker 6 (16·7%) 5 (13·2%)

Ex-smoker, >1y 13 (36·1%) 17 (44·7%)

Marital Status

Single 4 (11·1%) 1 (2·6%)

Married 29 (80·6%) 33 (86·8%)

Divorced 3 (8·3%) 2 (5·3%)

Marriage-like arrangement 0 (-) 1 (2·6%)

Widowed 0 (-) 1 (2·6%)

Education level

Basic 8 (22·2%) 6 (15·8%)

Primary 9 (25.0%) 15 (39·5%)

Secondary 16 (44·4%) 14 (36·8%)

Higher 3 (8·3%) 3 (7·9%)

Working Status

Full-time Employment 14 (38·9%) 14 (36·8%)

Part-time Employment 0 (-) 2 (5·3%)

Houseworking 3 (8·3%) 4 (10·5%)

Retired 19 (52·8%) 18 (47·4%)

Data are means (SD) or numbers (%).

of 43Diabetes

Supplemental Table 2

Correlations between GFR and other covariates at inclusion

r p-value

Weight (kg) 0·67 <0·0001

BMI (kg/m2) 0·49 <0·0001

Serum Angiotensin II (pg/mL) 0·32 0·0070

LDL/HDL -0·29 0·0117

UAE (µg/min) 0·26 0·0276

r : Pearson correlation coefficients

BMI = Body Mass Index, LDL = Low Density Lipoprotein, HDL =

High Density Lipoprotein, UAE = Urinary Albumin Excretion

of 43 Diabetes

1

RENAL AND SYSTEMIC EFFECTS OF CALORIE RESTRICTION IN TYPE-2 DIABETES PATIENTS

WITH ABDOMINAL OBESITY: A RANDOMIZED CONTROLLED TRIAL

LEGENDS TO SUPPLEMENTAL FIGURES

Supplemental Figure 1

Hs-CRP (Top panel) and Angiotensin II (Middle panel) serum levels and UAE (Bottom

panel) at baseline and at six-month follow-up according to randomization to CR or SD.


Body weight (Top panel), BMI (Middle panel) and Waist Circumference (Bottom panel) at

baseline and at six-month follow-up according to randomization to CR or SD.


Systolic BP (Top panel), Diastolic BP (Middle panel) and HR (Bottom panel) at baseline and

at six-month follow-up according to randomization to CR or SD.

of 43Diabetes

Hs

-CR

P

(mg

/dL

)

0.6

0

0.1

0.3 A

ng

iote

ns

in I

I (p

g/m

L)

8

0

2

4

0.5

0.4

0.2

6

p = 0∙0164

p = 0∙0075

Bas

elin

e

6 m

on

ths

Bas

elin

e

6 m

on

ths

p = 0∙0421

UA

E

(pg

/mL

)

8

0 CR

2

4

SD

6

p = 0∙0248


of 43 Diabetes


Weig

ht

(Kg

)

BM

I (K

g/m

2)

Wais

t cir

cu

mfe

ren

ce

(cm

)

100

75

80

85

90

95 p = <0.0001

Bas

elin

e

6 m

on

ths

Bas

elin

e

6 m

on

ths

p = 0.0001

p = 0∙031

32

26

28

30

27

29

31

p = <0.0001

p < 0.0001

p = 0∙039

110

95 CR

100

105

SD

p = <0.0001

p < 0.0001

p = 0∙009

of 43Diabetes

Systo

lic B

P

(mm

Hg

)

140

110

115

125

Dia

sto

lic B

P

(mm

Hg

)

85

70

75

80

Heart

rate

(b

pm

)

80

45

50

70

135

130

120

55

60

65

75

CR SD

p = 0∙0322

p = 0∙0003

Bas

elin

e

6 m

on

ths

Bas

elin

e

6 m

on

ths

p = 0∙0349

p < 0∙0001

p = 0∙0094

p = 0∙0003


p = 0∙012

of 43 Diabetes

renal and systemic effects of calorie restriction in type ... · abdominal obesity defined as waist...

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