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Keywords:

  • chronic kidney disease;
  • dietary fat;
  • fatty acid composition;
  • insulin resistance;
  • metabolic syndrome

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Conflict of interest statement
  9. References
  10. Supporting Information

Objectives

The causes of the multiple metabolic disorders of individuals with chronic kidney disease (CKD) are not fully known. We investigated the relationships between dietary fat quality, the metabolic syndrome (MetS), insulin sensitivity and inflammation in individuals with CKD.

Subjects

Two population-based surveys were conducted in elderly Swedish individuals (aged 70 years) with serum cystatin C-estimated glomerular filtration rate <60 mL min−1/1.73 m2: the Uppsala Longitudinal Study of Adult Men (ULSAM) and the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) surveys. The present population comprised 274 men and 187 subjects (63% women) from the ULSAM and PIVUS cohorts, respectively.

Design

Factor analyses of serum fatty acids were used to evaluate dietary fat quality. Insulin sensitivity was measured by homeostasis model assessment of insulin resistance (IR) and, in ULSAM, also by euglycaemic clamp.

Results

Factor analyses generated two fatty acid patterns of (i) low linoleic acid (LA)/high saturated fatty acid (SFA) or (ii) high n-3 polyunsaturated fatty acid (n-3 PUFA) levels. In both surveys, the low LA/high SFA pattern increased the odds of having MetS [adjusted odds ratio 0.60 [95% confidence interval (CI) 0.44–0.81] and 0.45 (95% CI 0.30–0.67) per SD decrease in factor score in the ULSAM and PIVUS surveys, respectively] and was directly associated with both IR and C-reactive protein. The n-3 PUFA pattern was not consistently associated with these risk factors.

Conclusions

A serum fatty acid pattern reflecting low LA and high SFA was strongly associated with MetS, IR and inflammation in two independent surveys of elderly individuals with CKD. At present, there are no specific dietary guidelines for individuals with CKD; however, these findings indirectly support current recommendations to replace SFAs with PUFAs from vegetable oils.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Conflict of interest statement
  9. References
  10. Supporting Information

The prevalence of metabolic syndrome (MetS), which at present affects approximately 25% of the adult population, is likely to rise further given the current epidemic of obesity [1]. This in turn will lead to an increased incidence of type-2 diabetes mellitus (DM), cardiovascular disease (CVD) and premature death [1]. There is also evidence to suggest that MetS increases the risk of chronic kidney disease (CKD) [2-4] as well as mortality risk in patients with CKD [5]. Central obesity and insulin resistance (IR) are key features of MetS, in combination with other metabolic disorders such as dyslipidaemia and elevated blood pressure (BP) [1]. In addition, chronic low-grade inflammation is closely associated with both MetS and IR and has been suggested as an important causal factor for these glucometabolic disorders [6].

Studies in populations without CKD suggest that diet and lifestyle interventions are effective in preventing the development of MetS [7, 8]. Energy-dense, high-fat diets promote obesity, IR and MetS [9, 10]. However, dietary fat quality, rather than quantity, may be important in increasing these risks: whereas saturated fatty acid (SFA) intake seems to promote MetS and IR [11], dietary n-6 polyunsaturated fatty acids (PUFAs) from vegetable sources have been linked to improved insulin sensitivity and reduced risk of developing MetS and DM [12, 13]. Marine n-3 PUFAs [eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA)] have also been associated with favourable effects on MetS, such as lowering of triglyceride levels [14], whereas evidence for improvement in insulin sensitivity is weak [15]. In the context of CKD, to our knowledge, no studies have been conducted to investigate dietary fat quality. We recently reported that high n-6 PUFA or low SFA intake is associated with reduced chronic inflammation and improved survival in dialysis patients [16, 17]. Whether dietary fat patterns are associated with IR and MetS in patients with CKD is presently unclear, but represents an attractive possibility because of amenability to therapeutic intervention.

Fatty acid biomarkers in blood could represent accurate and convenient tools for estimating the long-term dietary fat intake of patients with CKD [18]. However, fatty acid composition in blood is expressed as a percentage of total fatty acids and is therefore a relative measure. As such, fatty acids are inter-related; a change in the proportion of one type of fatty acid will influence the proportions of others. In the field of nutritional epidemiology, the inter-relation between nutrients and food items is addressed by factor analysis, a statistical method of dimension reduction to study dietary patterns [19]. In the present study, we performed factor analyses to define serum fatty acid patterns as indicators of dietary fat quality. The aim of our study was to explore and validate associations between these fatty acid patterns and MetS, insulin sensitivity and systemic inflammation in two independent community-based samples of elderly individuals with CKD.

Materials and methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Conflict of interest statement
  9. References
  10. Supporting Information

Study population

We conducted a cross-sectional survey including individuals with CKD from two independent community-based cohorts: the Uppsala Longitudinal Study of Adult Men (ULSAM) and the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS). Detailed descriptions of these cohorts have been published previously [20, 21] and are available at http://www.pubcare.uu.se/ULSAM/ and http://www.medsci.uu.se/pivus/, respectively. All participants gave written informed consent, and the Ethics Committee of Uppsala University approved the study protocols.

The ULSAM study was initiated in 1970. All 50-year-old men living in Uppsala, Sweden, between 1970 and 1974 were invited to participate in a health survey for the ULSAM study. Participants returned for subsequent examinations at 60, 70, 77 and 82 years of age. The present study is based on the third examination cycle of the ULSAM survey, when participants were approximately 70 years of age (examinations performed during 1991 and 1995). A total of 543 individuals were identified as having CKD on the basis of a cystatin C-estimated glomerular filtration rate (eGFR) <60 mL min−1/1.73 m2 in accordance with the current Kidney Disease Outcomes Quality Initiative guidelines [22]. Fatty acid composition of serum cholesterol esters was available in 274 individuals who were included in the present analysis.

All 70-year-old individuals living in Uppsala, Sweden, between 2001 and 2004 were eligible for the PIVUS study. In total, 187 (63% women) participants of the PIVUS study, with a cystatin C-based eGFR <60 mL min−1/1.73 m2 and available data on fatty acid composition of serum cholesterol esters, were included in the present analysis.

The examinations in the ULSAM and PIVUS studies, including anthropometric measurements, BP monitoring, blood sampling and questionnaires regarding medical history, smoking habits, medication use and physical activity level, were performed under standardized conditions as described previously [20, 21]. Body mass index (BMI) was calculated as the ratio of the body weight (in kg) to the height (in m2). Waist circumference (WC) was measured midway between the lowest rib and the iliac crest. Smoking status was defined as current smoking or nonsmoking. Physical activity was defined as self-reported leisure-time exercise habits according to four categories (sedentary, mild, moderate and intense activity) [23]. Supine systolic and diastolic BPs were measured twice in the right arm after rest for 10 min, and the means were calculated.

Laboratory analyses

Venous blood samples were drawn after an overnight fast and stored at −70 °C until required for analyses. Assays were performed at the Department of Clinical Chemistry, University Hospital, Uppsala, which is accredited according to the Swedish Board for Accreditation and Conformity Assessment (Swedac) standard ISO/IEC 17025. Serum triglyceride and high-density lipoprotein (HDL) concentrations were determined using enzymatic techniques. Fasting blood glucose concentration was measured using an oxidase method and insulin using a radioimmunoassay. High-sensitivity C-reactive protein (CRP) was measured using latex-enhanced reagent (Dade Behring, Deerfield, IL, USA) and a Behring BN ProSpec analyser (Dade Behring). Serum cystatin C (ULSAM: N Latex Cystatin C, Dade Behring; PIVUS: Gentian, Moss, Norway) was used to estimate GFR [24, 25].

Fatty acid analysis

The fatty acid composition of serum cholesterol esters was analysed in a random sample of subjects with CKD (= 274 in the ULSAM cohort; = 187 in the PIVUS cohort). The analysis was performed using frozen samples stored at −70 °C for several weeks. As previously described [26], an extraction with chloroform was performed. The dry extracts were dissolved in a few drops of chloroform and were placed on thin liquid chromatography plates for separation of the lipids. The lipid esters were trans-methylated, and the methyl esters were extracted. The fatty acid methyl esters were dissolved in hexane and separated by gas–liquid chromatography (GLC). The Hewlett Packard (Palo Alto, CA, USA) GLC system used for the analyses consisted of a gas chromatograph (5890), an automatic sampler (7671A), an integrator (3392A) and a 25-m Quadrex (New Haven, CT, USA) fused silica capillary column (OV-351). The fatty acids were identified by comparison of the retention times of separation was controlled by Nu Chek Prep (Elysian, MN, USA) GLC reference standard GLC-68A. The coefficients of variation (CV) for all fatty acids were between 1% and 5.5% (except stearic acid which had a CV of 9.9%). Individual fatty acids are given as the relative percentage of the sum of the fatty acids analysed.

Metabolic syndrome and IR

We adopted the modified National Cholesterol Education Program Adult Treatment Panel III (NCEP: ATP III) criteria, with MetS defined as three or more of the following [1]: (i) abdominal obesity (WC >102 cm for men and >88 cm for women), (ii) hypertriglyceridaemia (serum triglyceride level ≥1.7 mmol L−1 or lipid-lowering drug treatment), (iii) low serum HDL cholesterol (<1.04 mmol L−1 for men and <1.3 mmol L−1 for women, or lipid-lowering drug treatment), (iv) hypertension (systolic BP ≥130 mmHg, diastolic BP ≥85 mmHg or antihypertensive drug treatment) and (v) hyperglycaemia (fasting plasma glucose concentration ≥5.6 mmol L−1, antiglycaemic medication or previous diagnosis of type 2 DM).

Both the euglycaemic hyperinsulinaemic clamp technique and homeostasis model assessment of insulin resistance (HOMA-IR) were used to evaluate IR in the ULSAM survey, whereas IR was solely assessed using the latter method in the PIVUS survey. Insulin sensitivity, assessed as the insulin-mediated glucose disposal (M), was estimated by the hyperinsulinaemic euglycaemic clamp method described by DeFronzo et al. [27], with slight modification that infusion of insulin (Actrapid Human; Novo, Copenhagen, Denmark) at a constant rate of 56 mU per body surface area per minutes over a period of 120 min (body surface area was measured in m2). It was estimated that this rate would suppress hepatic glucose output almost completely in all participants including those with type 2 DM. The target plasma glucose concentration was 5.1 mmol L−1. M was calculated as the amount of glucose per kg of body weight taken up during the last 60 min of the study and expressed as mg kg body weight−1 min−1. HOMA-IR was calculated using the formula: fasting plasma glucose (mmol L−1)*fasting serum insulin (mU L−1)/22.5 [28].

Statistical analyses

Values are expressed as mean ± SD, median (interquartile range) or percentage, as appropriate. Logarithmic transformation was applied for non-normally distributed continuous valuables. To determine how fatty acids in serum cholesterol esters are inter-related in the ULSAM and PIVUS surveys, we performed a factor analysis with a varimax rotation in each study to extract factors of biological significance, representing different patterns of dietary fatty acid intake [12]. All fatty acids were entered into the factor analyses. The most powerful factors (eigenvalues >2.0) were retained for further analyses. The resulting factor patterns were interpreted using factor loadings, eigenvalues and the percentages of total variance explained by the generated factors.

Spearman's univariate correlation coefficients (rho) were calculated to determine correlations between the factor scores and M, HOMA-IR and CRP. Factor scores of derived factors were plotted against the number of MetS components. Linear regression analyses were used to detect linear changes across ordinal groups with a different number of MetS components, and P values for trend were reported. Multiple regression models were fitted to assess the independent associations between the factor scores and the MetS components, IR indices and CRP, with adjustment for potential confounders such as smoking status, physical activity, eGFR and BMI. Sex was also included as a covariate in the PIVUS survey. Analyses related to IR were performed after exclusion of individuals on treatment for DM (oral medication or injections). Data are expressed as standardized regression coefficients (beta). Crude and multiple adjusted logistic models were fitted to predict the prevalence of MetS. The factor score, analysed as either a continuous variable or tertiles, was the independent variable in these models. Covariates included smoking status, physical activity and eGFR, as well as sex in the PIVUS survey. P values for trend were used to assess linear changes in relationships across the ordinal groups. Data are presented as odds ratio (OR) and 95% CI.

For sensitivity analyses, all associations were tested in individuals without DM for the two surveys and in women for PIVUS. Also, to test the robustness of our findings, analyses were repeated using single fatty acid proportions [i.e. the proportions of linoleic acid (LA), palmitic acid, EPA and DHA in serum cholesterol esters] as well as the ratio of LA to palmitic acid. All tests were two-tailed, and < 0.05 was considered significant. All statistical analyses were performed using statistical software stata, version 12 (Stata Corporation, College Station, TX, USA).

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Conflict of interest statement
  9. References
  10. Supporting Information

General and metabolic characteristics

A total of 68 (25%) and 61 (33%) individuals with CKD in the ULSAM and PIVUS studies, respectively, met at least three NCEP: ATP III criteria and were considered to have MetS. General and metabolic characteristics of patients in both surveys are summarized in Table 1.

Table 1. General and metabolic characteristics in elderly individuals (age 70 years) with chronic kidney disease in the Uppsala Longitudinal Study of Adult Men (ULSAM) and the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) surveys
ParameterULSAM (= 274)PIVUS (= 187)
  1. BMI, body mass index; BP, blood pressure; eGFR, estimated glomerular filtration rate; HDL, high-density lipoprotein; HOMA-IR, homeostasis model assessment of insulin resistance.

  2. a

    Data are expressed as mean ± standard deviation, median (interquartile range) or number (percentage), as appropriate.

  3. b

    Data available in 247 individuals in ULSAM and 187 individuals in PIVUS. bData available in 237 individuals in ULSAM and 179 individuals in PIVUS.

Men, n (%)274 (100)69 (37)
BMI, kg m−226.5 ± 3.428.0 ± 5.1
Smokers, n (%)a51 (21)88 (47)
Physical activity, n (%)b
Sedentary7 (3)23 (13)
Mild91 (38)108 (60)
Moderate132 (56)38 (21)
Intense7 (3)10 (6)
eGFR, mL min−1/1.73 m251.4 (45.7–56.0)55.1 (50.9–57.4)
Metabolic syndrome
Metabolic syndrome, n (%)68 (25)61 (33)
Waist circumference, cm96.1 ± 9.791.7 ± 13.0
Triglycerides, mmol L−11.3 (1.0–1.7)1.3 (0.9–1.6)
HDL, mmol L−11.3 ± 0.31.5 ± 0.4
Systolic BP, mmHg149 ± 19149 ± 23
Diastolic BP, mmHg86 ± 970 ± 10
Fasting glucose, mmol L−15.7 ± 1.25.5 ± 2.3
Insulin sensitivity
Glucose disposal, mg min−1 kg−14.9 (3.7–6.4) 
HOMA-IR1.4 (1.0–2.2)1.9 (1.3–3.0)
Inflammation
C-reactive protein, mg L−12.1 (1.2–5.3)2.3 (1.3–4.4)

Fatty acid composition and factor analyses

The fatty acid compositions of serum cholesterol esters in the participants in the two surveys are presented in Table 2. In both surveys, LA was the most abundant of all fatty acids. Palmitic acid and oleic acid were major fatty acids of the SFA and monounsaturated fatty acid (MUFA) subfamilies, respectively. Marine n-3 PUFAs accounted for 2.68 ± 0.97% of all fatty acids in the ULSAM and 3.12 ± 1.27% in the PIVUS cohorts. Two factors with biological importance were extracted by factor analysis in the ULSAM survey. The most powerful factor, termed ‘low LA/high SFA’, comprised a strong negative loading from the proportion of LA and inverse loadings from a major SFA (palmitic acid) as well as palmitoleic acid, MUFAs, γ-linolenic acid and dihomo-γ-linolenic acid, all of which are non-essential fatty acids and can be synthesized endogenously in response to a high SFA intake [18]. The second factor, termed ‘high n-3 PUFA’, largely comprised positive loadings from the proportions of EPA and DHA. The same factor analysis procedure extracted two factors in the PIVUS survey, the biological significance of which was very similar to that of their counterparts in the ULSAM cohort. The high n-3 PUFA factor in PIVUS also comprised a moderate positive loading from arachidonic acid (20 : 4 n-6), along with stronger loadings from EPA and DHA. These two factors/patterns were taken as reflections of dietary fat quality and together explained approximately 53% and 41% of total variance of the whole fatty acid profiles in the ULSAM and PIVUS populations, respectively.

Table 2. Fatty acid compositions of serum cholesterol esters and rotated factor loadings between individual fatty acids and factors derived from fatty acid compositions in individuals with chronic kidney disease in the two surveys
Fatty acidULSAMPIVUS
Percentage of total fatty acidsFactor 1 (low LA/high SFA)Factor 2 (high n-3 PUFA)Percentage of total fatty acidsFactor 1 (low LA/high SFA)Factor 2 (high n-3 PUFA)
  1. LA, linoleic acid; MUFA, monounsaturated fatty acid; PIVUS, Prospective Investigation of the Vasculature in Uppsala Seniors; PUFA, polyunsaturated fatty acid; SFA, saturated fatty acid; ULSAM, Uppsala Longitudinal Study of Adult Men.

  2. Data are expressed as mean ± standard deviation. A factor analysis with a varimax rotation was performed to extract factors with biological significance, representing different patterns of dietary fatty acid intake in the two surveys separately. Absolute values of factor loadings above 0.5 are given in bold.

SFA
Myristic acid   0.91 ± 0.21 0.51 −0.03
Pentadecanoic acid   0.25 ± 0.07−0.04−0.18
Palmitic acid11.77 ± 0.93 0.65 0.4311.69 ± 0.89 0.50 0.37
Stearic acid0.96 ± 0.190.140.120.78 ± 0.190.340.02
MUFA
Palmitoleic acid3.72 ± 1.30 0.81 0.013.56 ± 1.15 0.77 −0.06
Oleic acid20.58 ± 2.29 0.80 0.0822.70 ± 1.92 0.70 −0.15
PUFA
Linoleic acid52.36 ± 4.610.93−0.3247.99 ± 4.040.84−0.45
γ-Linolenic acid0.65 ± 0.26 0.73 −0.290.80 ± 0.31 0.67 0.02
Dihomo-γ-linolenic acid0.71 ± 0.15 0.62 −0.340.73 ± 0.170.480.09
Arachidonic acid5.83 ± 1.080.390.085.97 ± 1.370.25 0.57
α-Linolenic acid0.83 ± 0.210.120.031.01 ± 0.260.11−0.41
Eicosapentaenoic acid1.70 ± 0.770.11 0.88 2.25 ± 1.090.01 0.74
Docosahexaenoic acid0.95 ± 0.24−0.03 0.88 0.95 ± 0.25−0.17 0.81
Eigenvalue 3.702.07 3.192.11
Total variance, % 3419 2516

Associations between factor scores and MetS, IR and inflammation

In univariate correlation analyses (Fig. 1), scores of the low LA/high SFA factor were directly related to insulin-mediated M and CRP in the ULSAM survey. Scores of this factor also directly correlated with HOMA-IR and CRP in the PIVUS survey. Multivariable regression models demonstrated independent direct associations between the low LA/high SFA factor and individual MetS components (excluding BP), IR and CRP in both surveys (Table 3). The n-3 PUFA factor was not significantly associated with these parameters, with the exceptions of WC, triglycerides and HOMA-IR, in the PIVUS cohort.

Table 3. Multivariable regression model to predict metabolic risk factors in subjects with chronic kidney disease according to the generated serum fatty acid factors
Dependent variableULSAMPIVUS
Factor 1 (low LA/high SFA)Factor 2 (high n-3 PUFA)Factor 1 (low LA/high SFA)Factor 2 (high n-3 PUFA)
Std. betaP valueStd. betaP valueStd. betaP valueStd. betaP value
  1. BP, blood pressure; eGFR, estimated glomerular filtration rate; HDL, high-density lipoprotein; HOMA-IR, homeostasis model assessment of insulin resistance; LA, linoleic acid; PIVUS, Prospective Investigation of the Vasculature in Uppsala Seniors; PUFA, polyunsaturated fatty acid; SFA, saturated fatty acid; ULSAM, Uppsala Longitudinal Study of Adult Men.

  2. Data are presented as standardized regression coefficient (Std. beta) and P value. P values in bold are statistically significant.

  3. aAdjusted for smoking status, physical activity and eGFR (as well as sex in the PIVUS survey). bAdjusted for smoking status, physical activity and eGFR (as well as sex in the PIVUS survey); participants (= 12 in the ULSAM survey and = 16 in the PIVUS survey) on treatment for diabetes (oral medication or injections) were excluded. cAdjusted for smoking status, physical activity, eGFR and body mass index (as well as sex in the PIVUS survey). dLogarithmic transformation was performed to correct for skewness.

Metabolic syndrome componentsa
Waist circumference0.21 0.001 −0.010.90.25 0.001 0.22 0.002
Triglyceridesd0.32 <0.001 −0.110.080.37 <0.001 0.17 0.02
HDL−0.130.060.050.5−0.18 0.02 −0.080.3
Systolic BP0.100.1−0.050.50.070.40.040.6
Diastolic BP0.120.080.010.90.060.50.090.3
Fasting glucose0.17 0.008 −0.070.30.30 <0.001 0.020.8
Insulin sensitivityb
Glucose disposald−0.38 <0.001 0.120.08    
HOMA-IRd0.34 <0.001 −0.060.40.27 0.001 0.24 0.002
Inflammationc
C-reactive proteind0.17 0.01 0.050.40.20 0.008 0.030.7
image

Figure 1. Correlations between the low linoleic acid/high saturated fatty acid factor and glucose disposal in the Uppsala Longitudinal Study of Adult Men (ULSAM) survey, homeostasis model assessment of insulin resistance (HOMA-IR) in the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) survey and high-sensitivity C-reactive protein (CRP) in both surveys. Participants (n = 12 in ULSAM and n = 16 in PIVUS) on treatment for diabetes (oral medication or injections) were excluded from the analyses of glucose disposal and HOMA-IR.

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Figure 2 shows that increasing scores of the low LA/high SFA factors in both surveys were strongly and positively associated with the number of MetS components. A borderline increasing trend was revealed for the n-3 PUFA factor in the PIVUS cohort, but this could not be confirmed in the ULSAM survey. In multiple logistic regression models (Table 4), every SD decrease in the low LA/high SFA factor (i.e. denoting an increase in LA intake and a reduction in SFA intake) reduced the risk of MetS in the two studies. Likewise, across decreasing tertiles of the low LA/high SFA factor, the risk of MetS was increasingly reduced. No significant relationship with MetS was observed for scores of the n-3 PUFA factor in either survey.

Table 4. Logistic regression models to predict the prevalence of the metabolic syndrome in individuals with chronic kidney disease according to the generated serum fatty acid patterns
 ULSAMPIVUS
Crude modelAdjusted modelCrude modelAdjusted model
  1. LA, linoleic acid; PIVUS, Prospective Investigation of the Vasculature in Uppsala Seniors; PUFA, polyunsaturated fatty acid; Ref., reference; SD, standard deviation; SFA, saturated fatty acid; ULSAM, Uppsala Longitudinal Study of Adult Men.

  2. Data are presented as odds ratio (95% confidence interval). P values in bold are statistically significant. Models were adjusted for smoking status, physical activity and estimated glomerular filtration rate (as well as sex in the PIVUS survey).

Factor 1 (low LA/high SFA)
Continuous (per SD decrement)0.59 (0.45–0.79)0.60 (0.44–0.81)0.42 (0.29–0.61)0.45 (0.30–0.67)
Categorized as
Low LA (high factor scores)Ref.Ref.Ref.Ref.
Medium LA (medium factor scores)0.67 (0.36–1.25)0.52 (0.25–1.06)0.47 (0.23–0.97)0.52 (0.24–1.13)
High LA (low factor scores)0.19 (0.08–0.42)0.22 (0.09–0.51)0.14 (0.06–0.34)0.16 (0.06–0.43)
P for trend <0.001 0.002 <0.001 0.001
Factor 2 (high n-3 PUFA)
Continuous (per SD increment)0.97 (0.74–1.28)0.84 (0.61–1.15)1.18 (0.87–1.61)1.27 (0.91–1.76)
Categorized as
Low n-3 PUFA (low factor scores)Ref.Ref.Ref.Ref.
Medium n-3 PUFA (medium factor scores)1.84 (0.94–3.60)1.48 (0.72–3.05)0.67 (0.31–1.44)0.65 (0.29–1.47)
High n-3 PUFA (high factor scores)0.99 (0.48–2.02)0.65 (0.29–1.44)1.00 (0.48–2.09)1.06 (0.49–2.30)
P for trend0.10.10.50.5
image

Figure 2. Factor scores across increasing number of metabolic syndrome (MetS) components in the Uppsala Longitudinal Study of Adult Men (ULSAM) and the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) surveys. Data are presented as mean ± standard error. Standardized coefficients (beta) and P values for trend were derived from linear regression analyses. LA, linoleic acid; PUFA, polyunsaturated fatty acid; SFA, saturated fatty acid.

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Sensitivity and confirmatory analyses

In sensitivity analyses, after exclusion of individuals with diagnosed DM (43 and 23 in the ULSAM and PIVUS populations, respectively), multivariable regression and multiple logistic regression models yielded essentially the same results (data not shown). Similarly, results were confirmed in the subpopulation of women alone in the PIVUS study (= 118, data not shown). To test the robustness of these results and the representativeness of the generated factors, analyses were repeated using single fatty acid proportions (i.e. the proportions of LA, EPA and DHA in serum cholesterol esters). LA and the LA/palmitic acid ratio were negatively, whereas palmitic acid was positively, associated with most MetS components, IR and CRP (Table S1), as well as the prevalence of MetS (Table S2). Although the n-3 PUFA factor was positively associated with HOMA-IR in the PIVUS survey, neither EPA nor DHA individually confirmed this relationship (data not shown).

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Conflict of interest statement
  9. References
  10. Supporting Information

The presence of MetS strongly predicts total and cardiovascular mortality in the community [29] as well as in individuals with CKD [5]. MetS may also represent a risk factor for CKD [3-5], which has recently been incorporated into the evaluation of total CVD risk in the updated European Guidelines on CVD prevention [30]. The current results are of clinical interest as we were able to identify links between modifiable dietary fat patterns and MetS components as well as IR in high-risk individuals with impaired renal function from two surveys conducted in independent population-based cohorts. Of note, these relationships were similar in magnitude to those in individuals without CKD from the two surveys (data not shown), suggesting that they are unaffected by the presence of CKD.

Our main finding is the independent association between a serum fatty acid pattern of low LA/high SFA and individual MetS components in individuals with CKD. This finding, in two independent surveys, is consistent with previous observations in the community and in individuals with DM, CVD or MetS [12, 13]. It has also been proposed that a low LA and/or high SFA pattern may be associated with many metabolic abnormalities, such as abdominal fat accumulation [11], high triglyceride levels and ratio of serum total to HDL cholesterol [31] and high BP [32], in populations without CKD. Strengthening these observations, we also found strong associations between this dietary pattern, IR and inflammation, both key pathogenic links underlying the abnormalities clustering in MetS [1]. Previous studies in populations without CKD have indeed shown that individuals with a low proportion of serum LA have impaired fasting glycaemia [33] and increased risk of developing DM [34]. In addition, although the plasma level of LA was inversely correlated with pro-inflammatory biomarkers [35], SFAs have been shown repeatedly to be pro-inflammatory [36]. Such findings agree with and extend our previous results in dialysis patients showing a relation between both LA and SFA and systemic inflammation and increased risk of mortality [16, 17]. Altogether, these findings suggest a potential link between dietary fat quality and risk profile in individuals with CKD. Causality in this relationship cannot be inferred from the observational nature of our study design. Nonetheless, there is mounting evidence from both mechanistic and interventional studies to support the potential involvement of dietary fatty acids in the development (and prevention) of MetS, IR and inflammation [7-10, 12, 13, 37]. In particular, interventional studies have shown that whereas a diet enriched in LA improves insulin sensitivity, a diet high in SFA is likely to result in IR [11, 38]. It was recently demonstrated that a diet rich in PUFAs in insulin-resistant men acutely reduces triacylglycerol-derived skeletal muscle fatty acid uptake, accompanied by improved postprandial insulin sensitivity [39].

The dietary factor representing high n-3 PUFA intake was not consistently associated with MetS components, IR or inflammation, in line with previous studies [16, 21, 35, 40]. We did observe an independent negative association with triglyceride levels in both surveys, in agreement with the hypotriglyceridaemic effect attributed to marine fatty acids [14]. The associations and trends reported in the PIVUS survey may be attributed to the fact that there was also a moderate positive loading from arachidonic acid, which is usually from dietary animal sources [41]. Indeed, we did not observe such associations when EPA or DHA was evaluated individually. The present results, however, do not contradict the notion that EPA and DHA supplementation may have potential benefits on cardiovascular and metabolic disorders [42]. In the context of a Swedish diet, in which the intake of fish is relatively high compared with for instance that in an American diet, these links may be less evident [16]. Further studies in CKD populations with inadequate fish intake should confirm these relationships.

The benefits of dietary n-6 PUFAs in general and of LA in particular are becoming apparent, with current American Heart Association dietary guidelines for prevention of CVD in the community recommending an increase in both n-6 and n-3 PUFA consumption together with a reduction in SFAs [43]. Whereas interventional studies in CKD patients have exclusively focused on n-3 PUFA supplementation, the current results taken together suggest that research efforts should also target the purported benefits of n-6 PUFAs. This may be particularly interesting with regards to MetS and IR. In a longitudinal population-based cohort study from Finland, it was demonstrated that an increase in plasma n-6 PUFAs, but not n-3 PUFAs, was associated with a lower incidence of MetS during a 6.5-year period [44]. Furthermore, LA supplementation in individuals with type 2 DM was more effective in achieving blood glucose and insulin control than n-3 PUFAs [45], and in general, independent and inverse associations between serum LA and development of type 2 DM have been shown in prospective cohort studies [46]. The key to dietary benefits for glucose control may lie not only in supplementation of healthy fat, but in the improvement in fat quality overall. In this regard, it was recently shown in a randomized controlled clinical trial in abdominally obese individuals that dietary replacement of butter (SFA rich) by sunflower oil (LA rich) reduces liver fat and improves lipid profile, inflammatory status and insulin sensitivity in compliant individuals [37].

Several strengths and limitations should be considered in the interpretation of our data. First, the confirmation of our findings in an independent survey is strength. Secondly, the use of factor analysis of serum fatty acid composition is also an advantage, as it avoids the problems of under-/over-reporting of dietary recalls [47] and captures inner relationships between the spectrum of dietary fatty acids, both grasping the concept of dietary fat quality and facilitating the interpretation of findings. Thirdly, in the ULSAM survey, insulin sensitivity was determined using the gold standard technique [27], thus improving the validity of the data. However, a limitation of this study is the presence of unmeasured or unknown confounders, which we cannot take into account. Our results are cross-sectional, and although serum fatty acid patterns can be used as indicators of dietary fat quality, some fatty acids undergo endogenous conversion [48]; therefore, these patterns may to some extent also reflect altered metabolism. Nevertheless, given the limitation of dietary recall to accurately report nutrient intake, we consider the use of circulating fatty acids to be a strength of this study [18]. Because P values were not adjusted for multiple testing, they have to be considered as descriptive. Nonetheless, the replication of our findings in an independent survey would argue against type 1 error as an explanation of our findings. Finally, although the inclusion of individuals of similar age reduced important confounding, our results in elderly subjects with moderate CKD may not necessarily apply to other populations.

In conclusion, we have shown associations between a serum fatty acid pattern, representing low LA and high SFA intake, and MetS, IR and inflammation in two surveys from independent community-based cohorts of elderly individuals with CKD. Patients with CKD are prone to nutritional deficiencies and protein–energy wasting [49]. The results of this study are the first to suggest that current dietary recommendations for CVD prevention in the community to increase the intake of PUFAs from vegetable oils in place of SFAs [43] may also apply to populations with CKD. Interventional studies should address the hypothesis that improving dietary fat quality may ameliorate risk profile and possibly clinical outcomes in individuals with this condition.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Conflict of interest statement
  9. References
  10. Supporting Information

We thank of Siv Tengblad (Uppsala University, Sweden) for excellent technical assistance. This study was supported by grants from the Swedish Research Council, the Swedish Heart Lung Foundation, the Swedish Kidney Foundation, the Marianne and Marcus Wallenberg Foundation, the Osterman Foundation, the Westman Foundation, the Thuring Foundation and the Centre for Gender Medicine at Karolinska Insitutet as well as the Strategic Research Program in Diabetes at Karolinska Institutet. Xiaoyan Huang received a Ph.D. scholarship from the China Scholarship Council. Baxter Novum is a research centre at the Karolinska Institutet supported by an unrestricted grant from Baxter Healthcare Corporation.

Conflict of interest statement

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Conflict of interest statement
  9. References
  10. Supporting Information

Bengt Lindholm is employed by Baxter Healthcare Corporation. None of the other authors has any conflicts of interest to declare. The sponsors had no role in the design and conduct of the study.

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  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Conflict of interest statement
  9. References
  10. Supporting Information
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Supporting Information

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Conflict of interest statement
  9. References
  10. Supporting Information
FilenameFormatSizeDescription
joim12130-sup-0001-TableS1-S2.docWord document47K

Table S1. Standardized regression coefficients of multivariable regressions for metabolic risk factors according to linoleic acid, palmitic acid, and the ratio of linoleic acid to palmitic acid.

Table S2. Multivariable logistic regressions for the presence of the metabolic syndrome according to linoleic acid, palmitic acid, and the ratio of linoleic acid to palmitic acid.

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