Nutrition xxx (2016) 1–6
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Nutrition
journal homepage: www.nutritionjrnl.com
Applied nutritional investigation
Ratio of dietary n-3 and n-6 fatty acidsdindependent
determinants of muscle massdin hemodialysis patients with
diabetes
Te-Chih Wong M.S. a, Yu-Tong Chen M.S. a, Pei-Yu Wu M.S. a, Tzen-Wen Chen Ph.D. b,
Hsi-Hsien Chen Ph.D. b, Tso-Hsiao Chen Ph.D. c, Yung-Ho Hsu M.S. d,
Shwu-Huey Yang Ph.D. a, e, *
a
School of Nutrition and Health Sciences, Taipei Medical University, Taipei, Taiwan, Republic of China
Division of Nephrology, Department of Internal Medicine, Taipei Medical University Hospital, Taipei, Taiwan, Republic of China
c
Division of Nephrology, Department of Internal Medicine, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan, Republic of China
d
Division of Nephrology, Department of Internal Medicine, Shuang Ho Hospital, Taipei Medical University, Taipei, Taiwan, Republic of China
e
Nutrition Research Center, Taipei Medical University Hospital, Taipei, Taiwan, Republic of China
b
a r t i c l e i n f o
a b s t r a c t
Article history:
Received 27 October 2015
Accepted 18 February 2016
Objective: n-3 and n-6 polyunsaturated fatty acids (PUFAs) are essential nutrients in the human
diet and possibly affect muscle mass. We evaluated the association between the dietary ratios of n3 and n-6 PUFAs and muscle mass, indicated as skeletal muscle mass (SMM) and appendicular
skeletal muscle mass (ASM), in patients with diabetes undergoing hemodialysis (HD).
Methods: In this cross-sectional study, data on 69 patients with diabetes who underwent standard
HD therapy were analyzed. For estimating muscle mass, anthropometric and bioelectrical
impedance analyses were conducted following dialysis. In addition, routine laboratory and 3-d
dietary data were obtained. The adequate intake (AI) cut-off for n-3 PUFAs was 1.6 g/d and
1.1 g/d for male and female patients, respectively.
Results: The average age of the participants was 63.0 10.4 y. The mean ratios of n-3/n-6 PUFA
intake, n-6/n-3 PUFA intake, SMM, and ASM of the patients were 0.13 0.07, 9.4 6.4,
24.6 5.4 kg, and 18.3 4.6 kg, respectively. Patients who had AI of n-3 PUFAs had significantly
higher SMM and ASM than did their counterparts. Linear and stepwise multivariable adjustment
analyses revealed that insulin resistance and the n-6/n-3 PUFA ratio were the independent deleterious determinants of ASM normalized to height in HD patients.
Conclusions: Patients with AI of n-3 PUFAs had total-body SMM and ASM that were more appropriate. A higher dietary ratio of n-6/n-3 PUFAs was associated with reduced muscle mass in HD
patients.
Ó 2016 Elsevier Inc. All rights reserved.
Keywords:
Polyunsaturated fatty acids
Skeletal muscle mass
Appendicular skeletal muscle mass
Hemodialysis
Diabetes
Introduction
The authors acknowledge the study participants and staff at the HD Centers of
Taipei Medical University Hospital, Wan Fang Hospital, and Shuang Ho Hospital
for their contribution. Moreover, the authors acknowledge the Ministry of Science and Technology (Taiwan) for funding this research (Grant Number:
NSC-102-2320-B-038-026).
* Corresponding author. Tel.: þ886 2 2736 1661 ext. 6568; fax: þ886 2
2739 7137.
E-mail address: [email protected] (S.-H. Yang).
Diabetes mellitus (DM), the most common cause of end-stage
renal disease (ESRD), has been a major risk factor for body protein loss and muscle wasting, which are associated with
increased morbidity and mortality in patients undergoing hemodialysis (HD) [1,2]. In 1970 [3], Thage reported that patients
with diabetes undergoing dialysis have a higher prevalence and
forms of uremic-induced skeletal myopathy that are more severe. Pupim et al. demonstrated that patients with diabetic ESRD
exhibited higher loss of lean body mass than did their age-, sex-,
http://dx.doi.org/10.1016/j.nut.2016.02.015
0899-9007/Ó 2016 Elsevier Inc. All rights reserved.
Please cite this article in press as: Wong T-C, et al., Ratio of dietary n-3 and n-6 fatty acidsdindependent determinants of muscle
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2
T.-C. Wong et al. / Nutrition xxx (2016) 1–6
and race-matched counterparts without diabetes [4]. Identifying
an approachable treatment for maintaining muscle mass or
mitigate the consequences associated with muscle wasting in HD
patients is expected to improve patient function, because the
coexistence of DM and potential stressful conditions result in
protein-energy wasting, which may synergistically increase the
death risk in patients undergoing HD [5].
A large body of evidence now shows that unbalanced ratio of
n-3 and n-6 polyunsaturated fatty acids (PUFAs), as is found in
today’s Western diets, leads to the pathogenesis of many diseases [6–9], including vascular disease, cancer, osteoporosis,
autoimmune diseases, cognitive decline, and incidence of dementia; however, studies investigated the ratio between these
two PUFAs in muscle science is less well known. Both n-3 and n-6
PUFAs are essential fatty acids for human body. These two PUFAs
not only play critical roles in cell membrane integrity, but
potentially contribute to muscle hypertrophy and atrophy; they
also have catabolic and anabolic effects on muscle cells [10].
Helge et al. demonstrated that participants with improved leg
muscle functioning had significantly lower n-6/n-3 ratio of
muscle phospholipid fatty acid composition [11]. In a
population-based study on older Italians [12], a higher plasma
n-6/n-3 ratio was associated with age-related decline in physical
performance. If the ratios between n-3 and n-6 PUFAs were
associated with indices of muscle mass, the effective nutrition
therapy strategies for patients with diabetes undergoing dialysis
are warranted.
Because of the health benefits of n-3 PUFAs in the general
population, the American Heart Association recommends the
consumption of fish at least twice a week [13]. Sakuma and
Yamaguchi (2012) affirmed that adequate intake (AI) of n-3
PUFAs is 1.6 g/d for men and 1.1 g/d for women [14]. Nevertheless, no specific recommendations currently exist regarding the
dietary intake of n-3 PUFAs for patients with ESRD. Friedman
et al. found that 67% of HD patients who did not follow the
American Heart Association fish-consumption guidelines had
low plasma n-3 PUFA concentrations [15]; therefore, they
considered patients undergoing HD to be ideal for exemplifying
the effects of n-3 PUFAs [16].
According to our review of relevant literature, few studies
have investigated how muscle mass is affected by dietary n-3
and n-6 PUFAs, particularly in HD patients. We hypothesized
that patients with diabetic ESRD having a higher dietary ratio
of n-3/n-6 PUFAs have a lower risk of muscle mass decline. The
broad aims of this study were 1) to investigate the relationship
between dietary PUFAs and muscle mass; and 2) to evaluate
the possible univariate significant and nonsignificant relevant
predictors of muscle mass in patients with diabetes undergoing HD.
Materials and methods
Study subjects
This study used cross-sectional data in a completed study design for investigating the association between improved nutritional care and the prognosis of
cardiovascular disease (CVD) in HD populations. In brief, participants ages 20 and
older undergoing HD for at least 3 mo were recruited from three hospital-based
HD centers of Taipei Medical University (TMU) during September 2013 to January
2015. Dialysis patients regularly underwent a thrice weekly HD regimen, for
achieving an equilibrated Kt/V (eKt/V) of 1.2 in the initial 3 mo. Patients with
severe edema, amputation, hyper- and hypothyroidism, <500 kcal/d or
>3500 kcal/d of reported energy intake, known malignancies, infection, hospitalization 1 mo before the study, or missing data in their assessments were
excluded. The study was conducted in accordance with the Declaration of Helsinki, and written informed consent was obtained from each participant. The
Research Ethics Committee of TMU approved the study protocol (201302024).
Fig. 1. Flow chart indicating patient enrolment and the study procedure.
We investigated all consecutive patients with type 2 diabetes undergoing HD by
reviewing their medical charts. Among the 163 HD participants, 69 patients with
diabetes were identified (Fig. 1).
Demographic characteristics and anthropometric measurements
Well-trained staff censored the medical records of the participants according
to standardized methods and procedures. Demographic data comprising age, sex,
dialysis vintage and dose, history of diabetes, hypertension, and CVD were
retrieved. In addition, anthropometric information, comprising height, dry
weight, and interdialytic weight gain, was retrieved through chart review. Body
mass index (BMI) was calculated as dry weight (in kg) divided by the square of
the height (in m). Skeletal muscle mass (SMM) and appendicular skeletal muscle
mass (ASM) were measured using InBody S10 Biospace (a multifrequency
bioelectrical impedance analyzer [BIA], InBody, Seoul, Korea), according to
manufacturer guidelines. The eight surface electrodes of the BIA were placed on
the thumbs, middle fingers, and either side of the ankles of the patients, who
rested in a sitting position after the HD session. In total, 30 impedance measurements were obtained at six frequencies (1 kHz, 5 kHz, 50 kHz, 250 kHz,
500 kHz, and 1000 kHz). SMM and ASM were estimated as the sum of the total
body and four-limb muscle mass, respectively, and normalized to the square of
the height (in m), thus yielding the body composition-defining SMM and ASM
indices.
Biochemical assays
Standard laboratory tests were performed during monthly routine examinations at the clinical laboratories of each hospital through automated and
standardized methods. The predialysis albumin (bromocresol green), creatinine,
Please cite this article in press as: Wong T-C, et al., Ratio of dietary n-3 and n-6 fatty acidsdindependent determinants of muscle
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T.-C. Wong et al. / Nutrition xxx (2016) 1–6
random blood glucose, total cholesterol, triacylglycerols, and intact parathyroid
hormone were retrieved and presented as mean values for the preceding 3 mo
period. High-sensitivity C-reactive protein (hs CRP) and insulin levels were
measured at the clinical laboratory of TMU Hospital. The homeostasis model
assessment–estimated insulin resistance (HOMA-IR) was used as an index of IR
as follows: (glucose) (insulin)/405 (glucose in mg/dL) [17]. In addition, the
geriatric nutritional risk index (GNRI), a simplified nutritional screening index,
was calculated from the serum albumin, body weight, and height of the patients
[18]. Regardless of sex and age, the cut-off values for hypoalbuminemia, lowgrade inflammation, and nutritional risk were albumin <3.5 g/dL, hs CRP
>0.5 mg/dL [19], and GNRI <91.2 [18], respectively.
Dietary intake
Procedures for collecting dietary data have been detailed previously [20,21].
In brief, the participants had to record daily food intake for 3 d (a dialysis day, a
non-dialysis day, and a weekend). A licensed dietitian conducted face-to-face or
telephone interviews with the participants during which dietary data were obtained, and used a 24 h recall with common household measuring utensils as the
measure to confirm the data. Three-day averages of total calories and proteins,
saturated fatty acids, monounsaturated fatty acids, and PUFAs, as well as the sum
of n-3 and n-6 PUFA intake, were analyzed using nutrient analysis software
(Nutritionist Edition, Enhancement Plus 3, Version 2009) containing a Taiwanese
food composition table as the nutrient database (Taichung, Taiwan). Moreover,
dietary energy and protein intake were normalized to body weight. Protein
intake was also estimated by calculating the normalized protein nitrogen
appearance (nPNA) as recommended by the guidelines of the National Kidney
Foundation [22]. n-3 PUFA intake of 1.6 g/d and 1.1 g/d for men and women,
respectively, were considered AI in this study, as recommended by Sakuma and
Yamaguchi (2012) [14]. In addition, ratios of n-3/n-6 PUFAs and n-6/n-3 PUFAs
were calculated.
Physical activity
Data on the habitual physical activity of the subjects were collected during
the interviews by using a self-description questionnaire designed by Liou et al.
[23]. A metabolic equivalent value was assigned according to the levels of
physical activity (light, moderate, intense, and very intense, and sleep) was reported in kcal/d.
Statistics
Statistical analyses were performed using SAS software Version 9.3. (SAS
Institute, Cary, NC, USA) The Shapiro–Wilk test was used to assess normality
before testing the hypothesis. Data in the text were presented as the
mean standard deviation, percentage, correlation coefficients (r), regression
coefficient (b) with 95% confidence intervals or standard error, as appropriate.
The Student t test, Wilcoxon rank sum test, or chi-square test was used to
determine the initial group differences for verifying whether the AI of n-3
PUFAs was achieved. Pearson or Spearman correlation coefficients were used
to determine the degree of association between variables, as appropriate. A P
value < 0.05 was considered significant. Simple linear regression was used for
identifying SMM and ASM predictors. For the multivariable analyses, stepwise
variable selection was used to obtain the candidate final regression model. All
univariate significant and nonsignificant relevant covariates (demographic
profiles, comorbidities, HOMA-IR, and hs CRP) and their interaction terms
were selected, and the significance levels for entry and stay were set at 0.12.
Variables such as sex, age, total energy, and fat intake were included in the
model. To assure the quality of the regression model, we assessed multicollinearity by examining the variance inflation factor of each variable estimate for values >10.
Results
Patient characteristics
Baseline characteristics of the studied participants are shown
in Table 1. In total, 69 subjects with ESRD diabetes (41 men and
28 women) were identified. The mean age and dialysis vintage of
the patients were 63.0 10.4 y (range: 27–86 y) and 3.8 2.7 y
(range: 3.6 mo–12 y), respectively. An adequate dialysis dose
according to the eKt/V was administered to the patients.
Regarding complications, 37.7% and 58.7% of the patients with
diabetes undergoing HD had hypertension and a history of CVD,
respectively. The serum albumin and GNRI score, indicators of
3
Table 1
Main demographic, anthropometric, laboratory, and dietary characteristics of
patients with diabetes on hemodialysis with and without adequate intake (AI) of
total omega-3 polyunsaturated fatty acid (n-3 PUFA)*,y
Total n-3 PUFA intakex
All
n
69
Demographic characteristics
Male/female
41/28
Age, y
63.0 Dialysis vintage, y
3.8 Hypertension, n (%)
26 (37.7)
History of CVD, n (%)
40 (58.7)
Interdialytic weight
4.1 gain, %
Anthropometry
Height, cm
163 Body weight, kg
65.5 2
BMI, kg/m
24.6 SMM, kg
24.6 SMM index, kg/m2
9.2 ASM, kg
18.3 ASM index, kg/m2
6.8 Laboratory
Alb, g/dL
4.0 Creatinine, mg/dL
10.6 Random blood glucose,
148 mg/dL
Insulin, mU/mL
17.8 TC, mg/dL
171 TG, mg/dL
184 hs CRP, mg/dL
0.7 Intact parathyroid
307.0 hormone, pg/L
Dietary intake
Energy, kcal/d
1706.0 Energy, kcal/d/kg
26.7 Protein, g/d
62.0 Protein, g/d/kg
0.8 Total fat, g/d
69.4 Total SFA, g/d
15.7 Total MUFA, g/d
20.8 Total PUFA, g/d
17.8 Total n-3 PUFA, g/d
2.0 Total n-6 PUFA, g/d
15.8 Ratio of n-3/n-6
0.13 PUFA
Ratio of n-6/n-3
9.4 PUFA
Others
HOMA-IR
7.1 GNRI
101.0 eKt/V
1.5 MET, kcal/d
603.0 nPNA, g/d
1.3 10.4
2.7
1.1
AI
<AI
44
25
27/17
61.8 9.1
3.8 2.7
14 (31.8)
28 (63.6)
4.0 1.1
14/11
65.0 12.4
3.9 2.8
12 (48.0)
12 (48.0)
4.1 1.1
8.8
11.8
3.8
5.4
1.3
4.6
1.2
164.4
67.6
25.0
25.6
9.4
19.2
7.0
0.3
2.0
56.5
4.0 0.3
10.9 1.9
149.5 56.1
14.4
38.1
114
1.4
308.0
17.7
169.0
192.0
0.8
286.5
8.9
12.6
4.1
5.8
1.4
4.8
1.2
16.1
39.6
123.6
1.7
289.7
160.9
61.8
23.8
22.9
8.8
16.8
6.4
8.3
9.4z
3.1
4.2z
1.1
3.8z
1.0z
4.0 0.2
10.0 2.0
146.5 58.4
18.1
174.3
169.2
0.5
344.3
11.2
36.1
95.7
0.5
341.9
515.0 1765.5 494.8 1600.6 542.2
9.0
26.6 8.0
26.7 10.7
26.6
64.3 22.4
57.8 32.9
0.4
0.9 0.3
0.7 0.4
31.8
73.0 31.4
63.1 32.0z
9.1
18.0 8.4
11.6 9.0z
12.5
24.1 12.8
14.9 9.7z
11.6
22.7 11.4
9.3 5.6z
1.5
2.8 1.3
0.8 0.5z
10.4
19.9 10.3
8.6 5.3z
0.07
0.15 0.10
0.10 0.06z
6.4
8.0
4.5
0.3
264.0
0.3
7.5 1.8
7.2
101.1
1.5
637.1
1.3
9.3
4.7
0.3
256.5
0.3
12.7 9.7z
6.9
100.5
1.5
542.6
1.4
5.1
4.2
0.2
271.1
0.3
AI, adequate intake; Alb, albumin; ASM, appendicular skeletal muscle mass; BMI,
body mass index; CVD, cardiovascular disease; eKt/V, equilibrated Kt/V; GNRI,
geriatric nutritional risk index; HOMA-IR, homoeostasis model assessmentestimated insulin resistance; hs CRP, high sensitivity C-reactive protein; MET,
metabolic equivalent; PUFA, polyunsaturated fatty acid; MUFA, monounsaturated fatty acid; nPNA, normalized protein nitrogen appearance; SFA,
saturated fatty acid; SMM, skeletal muscle mass; TC, total cholesterol; TG, triacylglycerol
x
The cut-off value for the AI of n-3 PUFA was 1.6 g/d and 1.1 g/d for men and
women, respectively, as described by Sakuma et al. (2012).
* Values are shown as the mean standard deviation or percentage, as
appropriate.
y
Statistical analyses were conducted using Student t test, Wilcoxon rank sum
test, or Chi-square test.
z
Significantly different (P < 0.05).
the nutritional status, were 4.0 0.3 mg/dL and 101.0 4.5,
respectively. According to the dietary data, the intake of energy,
fat, PUFA, n-3 PUFAs, n-6 PUFAs, the ratio of n-3/n-6 PUFAs, and
Please cite this article in press as: Wong T-C, et al., Ratio of dietary n-3 and n-6 fatty acidsdindependent determinants of muscle
mass&mda..., Nutrition (2016), http://dx.doi.org/10.1016/j.nut.2016.02.015
4
T.-C. Wong et al. / Nutrition xxx (2016) 1–6
Table 2
Simple linear regression for predicting muscle mass in 69 patients with diabetes undergoing hemodialysis*
SMM
Ratio of n-3/n-6 PUFA
Ratio of n-6/n-3 PUFA
SMM index
ASM
ASM index
b
95% CI (min–max)
b
95% CI (min–max)
b
95% CI (min–max)
b
95% CI (min–max)
14.94
L0.28
2.86 to 32.73
0.48 to 0.08
2.04
L0.06
2.42 to 6.50
0.11 to 0.01
15.89
L0.27
0.86 to 30.91
0.43 to 0.10
3.33
L0.07
0.48 to 7.14
0.11 to 0.03
ASM, appendicular skeletal muscle mass; PUFA, polyunsaturated fatty acid; SMM, skeletal muscle mass
* Values are shown as regression coefficients (b) with 95% confidence intervals (minimum–maximum). Values in boldfaced text correspond to a statistical significance
of P < 0.05 indicated as determinants of muscle mass. b refers to the regression coefficient that the change in muscle mass per kg change in the exposure variable.
the ratio of n-6/n-3 PUFAs were 1706.0 515.0 kcal/d,
69.4 31.8 g/d, 17.8 11.6 g/d, 2.0 1.5 g/d, 15.8 10.4 g/d,
0.13 0.07, and 9.4 6.4, respectively.
Comparison of patients with and without AI of n-3 PUFAs
As shown in Table 1, patients with AI of n-3 PUFAs had
significantly higher weight and muscle mass indicated as SMM,
ASM, and ASM indices; however, few substantive differences in
demographic, laboratory, and clinical variables were observed
between these groups (P > 0.05). Moreover, a distinct trend of
higher dietary fat and n-3/n-6 PUFA intake ratios was observed
in patients with diabetes undergoing HD with AI of n-3 PUFAs.
It is worth noting that dietary n-3 PUFAs were positively
correlated with total energy intake (r ¼ 0.25, P ¼ 0.044), total fat
intake (r ¼ 0.31, P ¼ 0.012), body weight (r ¼ 0.27, P ¼ 0.026),
SMM (r ¼ 0.26, P ¼ 0.037), ASM (r ¼ 0.35, P ¼ 0.005), and ASM
indices (r ¼ 0.26, P ¼ 0.035) after adjusting for sex and age.
Consistently, ratios of n-6/n-3 PUFA were negatively correlated
with ASM (r ¼ 0.28, P ¼ 0.025), ASM indices (r ¼ 0.30,
P ¼ 0.016) and creatinine (r ¼ 0.31, P ¼ 0.012). We also found
HOMA-IR was significantly correlated with body weight
(r ¼ 0.32, P ¼ 0.009), BMI (r ¼ 0.36, P ¼ 0.004), random blood
glucose (r ¼ 0.57, P < 0.0001), insulin (r ¼ 0.92, P < 0.0001), and
triacylglycerols (r ¼ 0.48, P < 0.0001).
Identified confounders associated with muscle mass
Univariate analysis was used to determine the factors associated with muscle mass in patients with diabetes undergoing
HD (Table 2). The ratio of n-3/n-6 PUFAs was positively associated with muscle mass, which was particularly significant in
ASM. The ratio of n-6/n-3 PUFAs inversely and significantly
associated with muscle mass indicated as SMM, the SMM index,
ASM, and the ASM index. Other general factors, including sex,
age, BMI, total energy, protein intake, creatinine, and presence of
diabetes, were significant predictors of muscle mass.
After linear and stepwise multivariable adjustment (Table 3),
BMI, creatinine, and eKt/V were the independent determinants
of muscle mass regardless of total body SMM or ASM. Moreover,
the ratio of n-6/n-3 PUFAs and HOMA-IR were the independent
risk determinants of the ASM index in patients with diabetes
undergoing HD (adjusted R2 ¼ 0.72). In addition, multicollinearity did not affect the result because no variables with
variance inflation factor exceeded 10.
Discussion
Our study indicated that dietary PUFAs, a higher ratio of n-6/
n-3 PUFAs was independently associated with muscle mass
decline in patients with diabetes undergoing HD. It has long been
speculated that unbalanced ratio of n-3 and n-6 PUFAs, as is
found in today’s Western diets, associated with many chronic
diseases [6–9], but the effects on muscle mass are less well
known. The rate of muscle protein synthesis is associated with
increased n-3 PUFAs in human [24–26] and animal [27,28]
studies. In this study, patients with diabetes undergoing HD
showed that dietary n-3 PUFAs were positively correlated with
muscle indices. Increasing higher quantities of n-3 PUFAs related
to a lower ratio of n-6/n-3 PUFAs. Other studies showed that
participants with improved muscle function had significantly
lower n-6/n-3 ratios of muscle membrane [11]. These data suggest that unbalanced dietary PUFAs may constitute a regulator
associated with catabolism/anabolism in the muscle mass.
Biologically maintaining a relatively balanced n-6/n-3 PUFA
ratio in the human body is crucial. Noori et al. correlated a higher
n-6/n-3 ratio in ingested food with worsening inflammation over
time and reported a trend toward an increased mortality risk in
patients undergoing HD [29]. Shoji et al. revealed that a
decreased ratio of n-3/n-6 PUFAs independently predicts CVD
events in patients undergoing HD [30]. In this study, muscle mass
was not only significantly higher in patients with AI of n-3 PUFAs
but also negatively and independently associated with the ratio
of n-6/n-3 PUFAs. The exact mechanisms responsible for the
protective effects of n-3 PUFAs on muscle mass are unknown but
likely involve in antiinflammatory properties of n-3 PUFAs [31]. A
high ratio of n-6/n-3 PUFAs in the diet triggers inflammatory
Table 3
Multivariable stepwise conditional regression for predicting muscle mass in 69
patients with diabetes undergoing hemodialysis*
SMM
BMI
Creatinine
eKt/V
SMM index
BMI
eKt/V
ASM
Ratio of n-3/n-6 PUFA
BMI
Creatinine
eKt/V
ASM index
Ratio of n-6/n-3 PUFA
BMI
HOMA-IR
eKt/V
b
SE
0.32
0.57
3.86
0.12
0.24
1.84
0.18
0.83
0.03
0.45
12.57
0.25
0.41
3.05
6.98
0.10
0.21
1.58
0.03
0.15
0.02
0.71
0.01
0.02
0.01
0.37
Adjusted R2
0.66
0.67
0.67
0.72
ASM, appendicular skeletal muscle mass; BMI, body mass index; eKt/V, equilibrated Kt/V; HOMA-IR, homeostatic model assessment-insulin resistance; PUFA,
polyunsaturated fatty acid; SMM, skeletal muscle mass
* Values are shown as regression coefficients (b) with standard error (SE) and
adjusted r square (R2), as appropriate. The significance levels of any potential
factor or interaction for entry (SLE) and for stay (SLS) in the stepwise variable
selection were set at 0.12. Variables, such as sex, age, total energy, and fat intake,
were always included in the model. Variables retained in the model are presented in the table. b refers to the regression coefficient that the change in
muscle mass per kg change in the exposure variable.
Please cite this article in press as: Wong T-C, et al., Ratio of dietary n-3 and n-6 fatty acidsdindependent determinants of muscle
mass&mda..., Nutrition (2016), http://dx.doi.org/10.1016/j.nut.2016.02.015
T.-C. Wong et al. / Nutrition xxx (2016) 1–6
responses [32], which may either interrupt the synthesis of
muscle mass [33] or accelerate muscle proteolysis [34]. Moreover, n-3 PUFAs may affect the mitochondrial function and the
lipid content of muscle membrane, which are important determinants of muscle function [35–37]. Additional interventional
and experimental trials are warranted to verify the importance of
dietary PUFAs in preventing and treating muscle wasting.
The present study investigated whether a higher HOMA-IR
was independently associated with reduced muscle mass indicated as the ASM index in patients with diabetes undergoing HD.
The present findings are consistent with those of previous
research. Thage (1970) proposed that patients with diabetes on
dialysis have a higher prevalence of severe uremic myopathy [3].
Pupim et al. reported that patients with diabetes undergoing HD
had an 83% increased rate of muscle protein loss compared with
their counterparts without diabetes [4]. Moreover, they subsequently determined that the presence of DM was the most
prominent predictor of lean body mass loss, independent of
other clinical-identified confounders such as age, sex, and status
of inflammation [5]. The possible mechanisms linking IR to
muscle degradation were identified. Muscle tissue is considered
the primary site for IR [38]. IR decreases the activity of the Class I
phosphatidylinositol 3-kinase (PI3K)/Akt pathway, leading to the
enhanced activation of the proteasome-ubiquitin pathway [39];
furthermore, it activates the apoptosis regulator Bax resulting in
stimulating the caspase-3 activity [40]. Overall, these explanations suggest that the resistance of metabolic effects of insulin
exacerbates muscle wasting.
HOMA-IR did not differ significantly between subjects with
and without AI of PUFAs. Rivellese et al. observed that long-term
(6 mo) supplementation with n-3 PUFAs did not improve insulin
sensitivity in patients with type 2 diabetes and hypertriacylglycerolemia [41]. Griffin et al. discovered that decreasing
the ratio of n-6/n-3 PUFAs through dietary intervention did not
influence insulin sensitivity in older subjects [42]. By contrast,
Huang et al. observed that an increased plasma ratio of n-3/n-6
PUFAs was related to decreased HOMA-IR in Chinese patients
with diabetes [43]. Storlien et al. revealed that a high ratio of n-6/
n-3 PUFAs in the muscle membrane was associated with negative insulin sensitivity [44]. These apparent inconsistencies may
be because of the differences in the research models and populations, the lack of adjustment for other residual and/or unmeasured confounders (such as a relatively small sample size),
and genetic polymorphisms involved in the insulin signal
pathway [45] and FA metabolism [46].
In the present study, Kt/V was an independent risk determinant of muscle mass in HD patients. Morishita et al. associated
higher Kt/V with reduced muscle mass in 34 Japanese HD patients [47]. These results imply that patients with low muscle
mass may require a higher clearance for dialysis. Moreover,
muscle mass should be considered when evaluating the
adequateness of a HD dose.
Several limitations exist in our analysis. First, the subjects
included in this study had a more appropriate nutritional status
compared with the general HD population; only 4.3% (n ¼ 3) and
8.7% (n ¼ 4) of the patients had <3.5 g/dL of albumin and <91.2
of GNRI, respectively. Future investigations must account for the
various characteristics of patients undergoing HD, such as
ethnicity, degrees of nutrition wasting, and uremia. Second, we
did not directly use plasma or erythrocyte fatty acid patterns as
biomarkers to demonstrate the association between dietary
PUFA intake and muscle mass. Svensson et al. observed the
clinically meaningful relationship between self-reported fish
intake and levels of n-3 PUFAs measured in serum phospholipids
5
in 152 HD patients [48]. Moreover, in our previous study, we
found that the results of plasma fatty acid composition of 16
patients with diabetes corresponded to their habitual fish consumption [49]. Future studies elucidating the possible relationship between dietary PUFA intake and lipid profiles in plasma,
erythrocytes, and muscle mass are warranted. Third, we assessed
body composition using a BIA, an inexpensive and easy-to-use
alternative to dual-energy X-ray absorptiometry, computed tomography, and magnetic resonance imaging. Kaysen et al.
investigated the estimation of total-body and limb muscle mass
by using a BIA correlated with that obtained through magnetic
resonance imaging [50]. Further research determining the
muscle mass cut-off point and the muscle loss rate in HD patients
are warranted. Finally, this cross-sectional study design provides
associative but not causal evidence between muscle mass and
dietary PUFA intake; therefore, the results of this study must be
cautiously interpreted.
Conclusion
Given the high prevalence of protein-energy wasting in ESRD,
we found that the ratios of dietary n-3 and n-6 PUFAs are
modifiable contributors toward muscle wasting in patients with
diabetes undergoing HD; a high n-6/n-3 ratio may be independently associated with a reduced muscle mass. In addition, IR,
indicated as HOMA-IR, was observed to be an independent risk
determinant of reduced muscle mass. Therefore, increasing n-3
PUFA dietary quantities is an approach to normalizing a high
ratio of n-6/n-3 PUFAs. We thus recommend that prospective
studies confirm our findings and investigate the potential
changes in additional outcomes, such as physical performance
and function over time, which are expected to favorably
influence the clinical prognosis in patients with diabetes
undergoing HD.
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