OBJECTIVE—The purpose of this article was to compare the effects of cod protein to those of other animal proteins on insulin sensitivity in insulin-resistant human subjects.

RESEARCH DESIGN AND METHODS—Insulin sensitivity (M/I) was assessed using a hyperinsulinemic-euglycemic clamp in 19 insulin-resistant subjects fed a cod protein diet and a similar diet containing lean beef, pork, veal, eggs, milk, and milk products (BPVEM) for 4 weeks in a crossover design study. Both diets were formulated to differ only in protein source, thus providing equivalent amounts of dietary fibers and monounsaturated, polyunsaturated (including n-3), and saturated fatty acids (1.1:1.8:1.0). β-Cell function, estimated by oral glucose tolerance test–derived parameters, was also assessed.

RESULTS—There was a significant improvement in insulin sensitivity (P = 0.027) and a strong tendency for a better disposition index (β-cell function × M/I) (P = 0.055) in subjects consuming the cod protein diet compared with those consuming the BPVEM diet. When median baseline M/I (4.8 × 10−3 mg · kg−1 · min−1 · pmol−1) was taken into account, an interaction on the 30-min C-peptide–to–30-min glucose ratio, used as an index of β-cell function, was observed between diet and M/I status (P = 0.022). Indeed, this ratio strongly tended to increase in subjects with low M/I consuming the cod protein diet compared with those consuming the BPVEM diet (P = 0.065).

CONCLUSIONS—Dietary cod protein improves insulin sensitivity in insulin-resistant individuals and thus could contribute to prevention of type 2 diabetes by reducing the metabolic complications related to insulin resistance.

Insulin resistance contributes to the pathophysiology of type 2 diabetes (1). Studies to reduce insulin resistance using insulin-sensitizing agents, such as thiazolidinediones, suggest that such therapies may delay or prevent progression from insulin resistance to type 2 diabetes (2,3) and preserve β-cell function (4). Among other therapeutic approaches, dietary interventions are also being studied.

An increasing number of studies have been performed to investigate the metabolic effects of dietary proteins on insulin and glucose homeostasis. According to von Post-Skagegard et al. (5), a cod protein meal, compared with a milk protein meal, lowered insulin levels and reduced insulin–to–C-peptide and insulin-to-glucose ratios in healthy women. In a previous study, both cod and soy proteins reduced fasting and postprandial glucose and insulin responses and increased peripheral insulin sensitivity compared with casein in rats fed a high-sucrose diet (6). Furthermore, dietary cod protein, compared with soy protein and casein, prevented the development of skeletal muscle insulin resistance (7) by normalizing insulin activation of the phosphatidylinositol 3-kinase/Akt-protein kinase B pathway and by improving GLUT4 translocation in skeletal muscle of high-fat–fed obese rats (8). Studies in humans also showed that including lean fish, whose major component is fish protein, as opposed to other animal proteins, in a prudent-type hypolipidemic diet increased sex hormone–binding globulin (9) and HDL2 cholesterol concentrations (9,10), well-recognized parameters associated with insulin sensitivity (11).

Thus, the objective of this study was to compare the effects of dietary cod protein with those of other animal proteins (beef, pork, veal, and milk) on insulin sensitivity in insulin-resistant men and women. Based on previous studies in animals (7,8) and humans (9,10), we hypothesized that cod protein would improve insulin sensitivity in insulin-resistant subjects, compared with other animal proteins. Insulin secretion was also explored because both insulin sensitivity and secretion interact in determining diabetes risk (1).

After a medical examination and evaluation, including routine laboratory testing and a 75-g oral glucose tolerance test (OGTT), 10 men and 9 women, recruited through media advertising in the Quebec City metropolitan area, aged 40–65 years, who were overweight or obese (BMI >25 kg/m2) were selected. Exclusion criteria included smoking; chronic, metabolic, or acute disease; use of medication known to affect lipid or glucose metabolism; major surgery in the 3 months before onset of the study; significant weight change (±10%) within the 6 months that preceded the study; and incompatibility with fish consumption (allergy, intolerance, or dislike) and/or calcium supplementation. Inclusion criteria were fasting plasma insulin >90 pmol/l (12), which is >75th percentile for fasting insulin levels in a sample from the adult Quebec population (13), with fasting plasma glucose (FPG) <7.0 mmol/l and 2-h plasma glucose <11.1 mmol/l. Because insulin sensitivity reductions in the luteal phase have been reported (14), the effect of menstrual phase was controlled by performing all tests during the follicular phase (days 4–11 of the menstrual cycle) for the two premenopausal women. Participants provided written informed consent after the experimental protocol was carefully explained. This study was approved by the Clinical Research Ethical Committee of Laval University Hospital Center.

The study included two experimental periods in a crossover design. After a first 2-week run-in period, subjects were randomly assigned to either a cod protein diet or a diet containing lean beef, pork, veal, eggs, milk, and milk products (BPVEM) for 4 weeks. At the end of the first experimental period, participants returned to their usual diet for a washout period of 4 weeks including a second 2-week run-in period. They were subsequently assigned to the other experimental diet for an additional 4 weeks. Subjects were asked to maintain their physical activity level and to refrain from alcohol consumption for the entire study period.

Diets

Experimental diets, given as 7-day rotating menus, were formulated to meet the National Cholesterol Education Program Adult Treatment Panel III (15), American Diabetes Association (16), and Dietary Reference Intakes (17) recommendations, thus providing 51–52% of total energy as carbohydrate, 18–19% as protein, 32% as fat (with <10% as saturated fat), 225 mg cholesterol/day, and 30 g dietary fibers/day. Nutritional composition of the experimental diets was calculated using a computer-assisted analysis of the Canadian Nutrient File database (18).

The nutrient composition of the formulated experimental diets is presented in Table 1. The cod protein diet consisted of cod fillets and the BPVEM diet consisted of lean beef, pork, and veal, eggs and egg substitutes, and skimmed milk and milk products as the main protein sources. A proportion of 58–68% of daily dietary proteins came from cod or BPVEM proteins, whereas the remaining proteins were of vegetable origin. The cod protein diet provided more alanine, arginine, aspartic acid, glycine, methionine, and lysine and less cysteine, glutamic acid, histidine, isoleucine, leucine, phenylalanine, proline, serine, threonine, tryptophan, tyrosine, valine, and branched-chain amino acids (isoleucine, leucine, and valine) than the BPVEM diet. Both experimental diets were adjusted to provide equivalent amounts of monounsaturated, polyunsaturated (polyunsaturated fatty acids [PUFAs]), and saturated fats (1.1:1.8:1.0), as well as dietary fibers. Cod liver oil was added to the BPVEM diet to provide amounts of n-3 PUFAs similar to those in the cod protein diet. α-Tocopherol (5 mg/g eicosapentaenoic acid + docosahexaenoic acid) was added to the cod liver oil to protect the PUFAs against oxidation. The cod liver oil was divided into aliquots, carefully put under a nitrogen atmosphere, and frozen immediately. Each aliquot was thawed just before being added to the meal and served to the participants. Subjects were asked to take daily calcium (600 mg) and vitamin D (125 IU) supplements during the cod protein diet because no milk or milk products were included. They received one or two tablets to reach adequate intakes (19) for both nutrients.

Subjects were asked to complete a 5-day food diary (4 weekdays and 1 weekend day) before the onset of the study to determine their usual energy intake. Participants were provided with kitchen scales and asked to weigh or measure with household measurement tools (e.g., cups and tablespoons) all foods and beverages consumed. Eight different energy levels were established for each diet (from 7,500 to 16,500 kJ). Subjects began the study at the energy level nearest to their usual intake. Subjects were weighed every day before lunch and were moved from one level to another when their body weight fluctuated. A maximum body weight variation of 2 kg was allowed within each experimental period. Waist circumference was also determined before and after each diet, as described previously (20).

On weekdays, lunches and dinners were prepared and eaten at the metabolic kitchen of the Institute of Nutraceuticals and Functional Foods of Laval University. All food was precisely weighed (to the nearest 0.1 g). Weekend lunches and dinners were distributed on Friday. Breakfast and snacks were purchased and prepared by the participants from a list of foods indicating the type and quantity of food to be consumed. Participants were provided with kitchen scales to weigh food. Subjects’ compliance was assessed by an oral questionnaire every day, and any deviation from the diets was noted.

OGTT

A 75-g OGTT was conducted before and after each experimental period after a 12-h overnight fast as described previously (20). Blood samples were drawn at −15, 0, 15, 30, 60, and 120 min for the determination of plasma glucose, insulin, and C-peptide concentrations. The total glucose, insulin, and C-peptide incremental areas under the curve (IAUCs) during the OGTT were determined with the trapezoid method. The 30-min C-peptide–to–30-min glucose ratio was calculated as an index of β-cell function (21). OGTTs were performed at the Diabetes Research Unit of Laval University Hospital Center.

Hyperinsulinemic-euglycemic clamp

A 120-min hyperinsulinemic-euglycemic clamp was performed to determine insulin sensitivity before and after each experimental diet as described previously (20). The insulin-stimulated glucose disposal rate (M) was calculated from the glucose infusion rate during the last 30 min of the clamp divided by body weight (kilograms). Insulin sensitivity (M/I) was then determined as the M value divided by the mean insulin concentration during the last 30 min of the clamp (I). The disposition index, which is a measure of the ability of β-cells to compensate for insulin resistance (22), was calculated as follows: β-cell function (30-min C-peptide–to–30-min glucose ratio) × insulin sensitivity (M/I). The clamps were performed at the Diabetes Research Unit of Laval University Hospital Center.

Statistical analyses

Based on previous published data (7,9), a minimum of 16 subjects were needed to provide 90% power to detect a treatment difference of 30% in insulin sensitivity at P < 0.05. Statistical analyses were performed using the Statistical Analysis System (version 9.0; SAS Institute, Cary, NC). The PROC MIXED procedure for an ANOVA for crossover design with two periods as described by Hills and Armitage (23) was used to compare the effects of the two dietary treatments. As no effect of experimental period or diet sequence and no residual effect of the first experimental period over the second period were observed for any measured variables, the data for experimental period, diet sequence, and dietary treatment were pooled. The potential interactions of the diets with sex, body weight change, and baseline insulin sensitivity status on the measured variables were tested by individual entry of terms and interaction terms into the ANOVA model. When an interaction was significant, the least significant difference test was then used for multiple comparisons. Baseline insulin sensitivity status was stratified according to the baseline median value (4.8 × 10−3 mg · kg−1 · min−1 · pmol−1). Data from two subjects for the hyperinsulinemic-euglycemic clamp variables were excluded because of technical problems during one of their clamps. Data for glucose, insulin, and C-peptide from one subject were missing, so she was excluded from all analysis needing these data (IAUC, β-cell function, and disposition index). The significance level was set to P < 0.05. Results are expressed as means ± SEM.

Subject baseline characteristics

All subjects completed the study. Subjects’ physical and clinical characteristics at baseline are presented in Table 2. All of our subjects were overweight or obese (BMI 27–41 kg/m2) (15) with increased abdominal adiposity (waist circumferences >100 cm for men and >96 cm for women) (15) and hyperinsulinemia (13). According to the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus (24), 21% of the subjects could be classified as having normal glucose tolerance (NGT), 11% as having isolated impaired fasting glucose (FPG between 6.1 and 6.9 mmol/l and 2-h plasma glucose <7.8 mmol/l), and 32% as having isolated impaired glucose tolerance (IGT) (FPG <6.1 mmol/l and 2-h plasma glucose between 7.8 and 11.0 mmol/l), whereas 37% had both impaired fasting glucose and IGT (FPG between 6.1 and 6.9 mmol/l and 2-h plasma glucose between 7.8 and 11.0 mmol/l).

Anthropometric measures

Before the 4-week intervention, there were no significant differences in mean initial body weight and waist circumference between the BPVEM (91.0 ± 3.3 kg and 106.6 ± 2.5 cm, respectively) and the cod protein (90.7 ± 3.2 kg and 106.4 ± 2.5 cm, respectively) diet groups. After the 4-week intervention, no significant differences in body weight and waist circumference were observed between the BPVEM (90.0 ± 3.2 kg and 106.4 ± 2.6 cm, respectively) and the cod protein (89.7 ± 3.2 kg and 106.3 ± 2.6 cm, respectively) diet groups.

Glucose-insulin homeostasis

From the OGTT, no significant differences were observed between the effects of the experimental diets on FPG and glucose IAUC, indicating that glucose tolerance was not modified, and on fasting plasma insulin, insulin IAUC, C-peptide, and C-peptide IAUC (Table 1 of the online appendix [available at http://dx.doi.org/10.2337/dc07-0273]). As shown in Fig. 1A, dietary cod protein increased M/I by 29% (from 5.6 ± 0.6 to 7.2 ± 0.8 × 10−3 mg · kg−1 · min−1 · pmol−1), whereas dietary BPVEM decreased it by 3% (from 6.4 ± 0.8 to 6.2 ± 0.7 ×10−3 mg · kg−1 · min−1 · pmol−1), showing a significant improvement in insulin sensitivity in subjects consuming the cod protein diet compared with those consuming the BPVEM diet (P = 0.027). No correlation between weight change and changes in insulin sensitivity (n = 34; r = 0.002, P = 0.990) was observed. Also of interest, there was a strong tendency for a better disposition index after the cod protein diet compared with the BPVEM diet (P = 0.055), suggesting improved overall glucose homeostasis.

To determine the effects of both diets on insulin secretion in relation to insulin resistance status, subjects were divided into two subgroups, the low insulin-sensitivity subjects and the moderately low insulin-sensitivity subjects, according to their baseline M/I (median 4.8 × 10−3 mg · kg−1 · min−1 · pmol−1). Interestingly, a significant interaction on the 30-min C-peptide–to–30-min glucose ratio (P = 0.022), used as an index of β-cell function, was observed between the subgroups in their response to the cod protein and BPVEM diets (Fig. 1B). Although there was no difference between the cod protein and BPVEM diets (P = 0.113) in the moderately low insulin-sensitivity subjects, we observed a 25% increase in the 30-min C-peptide–to–30-min glucose ratio with the cod protein diet (from 668 ± 97 to 836 ± 86) and a slight 4% decrease (from 632 ± 73 to 605 ± 104) with the BPVEM diet (P = 0.065) in the low insulin-sensitivity subjects, suggesting a strong tendency for improved insulin secretion with cod protein in these subjects.

The present results provide the first evidence that cod protein improves insulin sensitivity compared with other animal proteins in insulin-resistant men and women. In our study, the consumption of both controlled-feeding diets resulted in an average weight loss of 1 kg (1%). A 5–10% body weight loss (25), particularly from visceral adipose tissue (26), has been reported to improve insulin sensitivity in overweight subjects with insulin resistance. In this study, waist circumference, which is a good marker for visceral fat (27), remained unchanged during both diets. Moreover, no significant interactions of diet by weight change were seen for any of the measured variables. Therefore, the observed changes in M/I and β-cell function are unlikely to be due to this slight body weight loss.

The 29% increase in M/I obtained with the consumption of cod protein is in good agreement with the beneficial effects of cod protein already observed in animal studies. Indeed, Lavigne et al. (6,7) reported a better insulin sensitivity in cod protein–fed rats compared with rats fed casein. The mechanism underlying the beneficial effect of cod protein on insulin sensitivity could be attributed to its specific amino acid composition. A previous cell culture study in our laboratory (7) indeed showed that L6 myocytes incubated in an amino acid mixture corresponding to the concentrations of plasma amino acids in rats fed cod protein were more insulin sensitive than those incubated in amino acid mixtures representing plasma amino acids of rats fed casein or soy protein. Interestingly, these effects were observed in the total absence of n-3 PUFAs and therefore support the concept that the protein in fish per se can influence insulin sensitivity. Specific amino acids or mixtures of amino acids have been suggested to be responsible for the observed effects on insulin action. Lower branched-chain amino acids (valine, leucine, and isoleucine) and the higher arginine content of the cod protein diet compared with the BPVEM diet are of particular interest. Infusion of branched-chain amino acids was shown to inhibit insulin-stimulated glucose uptake in the forearm muscle (28). This inhibition is probably linked to activation of the mammalian target of the rapamycin/S6K1 pathway, which has recently been found to be responsible for nutrient-induced insulin resistance in humans (29). As for arginine, a study in patients with type 2 diabetes reported that the administration of l-arginine for 1 month significantly increased peripheral insulin sensitivity (30). Arginine is a substrate for nitric oxide production, which induces vasodilatation and thus contributes to better glucose disposal by increasing muscle perfusion and providing adequate insulin and glucose supply. Furthermore, it has been shown that taurine, whose content is about three to four times greater in white fish than in beef and pork (31), may improve insulin sensitivity in animal models of insulin resistance (32) and type 2 diabetes (33) through lowered protein tyrosine phosphatase and increased protein tyrosine kinase (32). Therefore, our data suggest that cod protein improves insulin sensitivity possibly through its amino acid composition acting on the insulin signaling pathway.

We added cod liver oil to the BPVEM diet to provide equivalent amounts of n-3 PUFAs in both diets. However, when we measured the n-3 PUFA content in plasma phospholipids, we observed a greater increase after consumption of the cod protein diet (from 5.74 ± 0.29 to 8.62 ± 0.21% of total fatty acids) than after consumption of the BPVEM diet (from 5.73 ± 0.26 to 7.20 ± 0.21% of total fatty acids) (P < 0.001), suggesting, as did Visioli et al. (34), that n-3 PUFAs consumed in the form of fish could be more available than those consumed in the form of added fish oil. Most intervention studies in diabetic humans have reported no change in insulin sensitivity after n-3 PUFA supplementation of 2 weeks to 6 months (35,36). However, some beneficial effects of n-3 PUFAs on insulin sensitivity have been observed in animal models (35) and on some parameters related to insulin sensitivity (e.g., triglycerides, hypertension, and inflammation) in human studies (36,37). Therefore, we cannot completely rule out a contribution of n-3 PUFAs to the improvement in insulin sensitivity after consumption of the cod protein diet, suggesting that cod protein could interact with n-3 PUFAs in improving insulin sensitivity, but further studies are needed to address this point.

It is well recognized that in insulin-resistant subjects, NGT is maintained by a compensatory increase in insulin secretion. However, insulin secretion progressively fails to adequately increase when moving from NGT to IGT to type 2 diabetes (1). In the present study, we observed a strong tendency (P = 0.055) for a greater increase in the disposition index with the cod protein diet, suggesting a better capacity of β-cells to adequately compensate for insulin resistance and, therefore, a potential to decrease the risk of progression from NGT/IGT to type 2 diabetes when a cod protein diet is consumed compared with a BPVEM diet. Because overall β-cell function was not different between the diets, the improvement in insulin sensitivity after consumption of the cod protein diet seems to account for the improvement in the disposition index. However, β-cell function strongly tended to increase in the subgroup of subjects with low insulin sensitivity after consumption of the cod protein diet compared with the BPVEM diet (P = 0.065), suggesting that subjects with the potentially greatest risk of progressing to type 2 diabetes benefit more from consuming cod protein. These results were observed in a small number of subjects and thus need to be further explored in a larger cohort.

In conclusion, the data from this study indicate that in the short-term, consumption of cod protein is effective as a dietary insulin sensitizer and, thus, could contribute to reducing the metabolic complications related to insulin resistance, which may prevent type 2 diabetes. In order to support dietary recommendations, further studies are required to determine the optimal number of servings of fish needed to obtain these health benefits. Additional studies will also be required to clarify the potential effects on insulin secretion and to elucidate the cellular mechanisms underlying the beneficial effects observed with cod protein.

Figure 1—

Effects of cod protein (CP) compared with other animal proteins (BPVEM) on insulin sensitivity (top), β-cell function (middle), and disposition index (bottom) before (□) and after (▪) 4 weeks of feeding of insulin-resistant subjects (A) and the interaction between diet and baseline insulin sensitivity (median 4.8 × 10−3 mg · kg−1 · min−1 · pmol−1) (B). Values are means ± SEM. *P = 0.027, †P = 0.055, and ‡P = 0.065 (ANOVA for crossover design). Insulin sensitivity and β-cell function data were available for 17 subjects. Disposition index data were available for 15 subjects. Data were available for 9 subjects in the low insulin-sensitivity subgroup and for 8 subjects in the moderately low insulin-sensitivity subgroup for insulin sensitivity and β-cell function. Data were available for 8 subjects in the low insulin-sensitivity subgroup and for 7 subjects in the moderately low insulin-sensitivity subgroup for the disposition index.

Figure 1—

Effects of cod protein (CP) compared with other animal proteins (BPVEM) on insulin sensitivity (top), β-cell function (middle), and disposition index (bottom) before (□) and after (▪) 4 weeks of feeding of insulin-resistant subjects (A) and the interaction between diet and baseline insulin sensitivity (median 4.8 × 10−3 mg · kg−1 · min−1 · pmol−1) (B). Values are means ± SEM. *P = 0.027, †P = 0.055, and ‡P = 0.065 (ANOVA for crossover design). Insulin sensitivity and β-cell function data were available for 17 subjects. Disposition index data were available for 15 subjects. Data were available for 9 subjects in the low insulin-sensitivity subgroup and for 8 subjects in the moderately low insulin-sensitivity subgroup for insulin sensitivity and β-cell function. Data were available for 8 subjects in the low insulin-sensitivity subgroup and for 7 subjects in the moderately low insulin-sensitivity subgroup for the disposition index.

Close modal
Table 1—

Nutrient composition of the experimental diets*

Diet
BPVEMCod protein
Energy (kJ) 10,984 10,920 
Carbohydrates (% of energy) 51 52 
Lipids (% of energy) 32 32 
Protein (% of energy) 19 18 
    Alanine (g) 5.53 6.02 
    Arginine (g) 6.26 7.04 
    Aspartic acid (g) 10.05 11.59 
    Cysteine (g) 1.56 1.45 
    Glutamic acid (g) 23.35 21.11 
    Glycine (g) 4.99 5.15 
    Histidine (g) 3.38 3.05 
    Isoleucine (g) 5.38 4.96 
    Leucine (g) 9.28 8.64 
    Methionine (g) 2.52 2.73 
    Lysine (g) 7.83 8.21 
    Phenylalanine (g) 5.09 4.79 
    Proline (g) 7.91 5.55 
    Serine (g) 5.33 4.96 
    Threonine (g) 4.60 4.53 
    Tryptophan (g) 1.44 1.30 
    Tyrosine (g) 4.18 3.71 
    Valine (g) 6.21 5.68 
    BCAA (g) 20.87 19.28 
    EAA (g) 45.73 43.89 
PUFA (g) 25 26 
MUFA (g) 39 39 
SFA (g) 22 23 
PUFA-to-MUFA-to-SFA ratio 1.1:1.8:1.0 1.1:1.7:1.0 
ω-3 (g) 3.5 3.3 
ω-6 (g) 20.9 21.6 
Cholesterol (mg) 228 220 
Total fiber (g) 28.0 29.7 
Calcium (mg) 1595 1487 
Vitamin D (μg) 15.3 12.8 
Diet
BPVEMCod protein
Energy (kJ) 10,984 10,920 
Carbohydrates (% of energy) 51 52 
Lipids (% of energy) 32 32 
Protein (% of energy) 19 18 
    Alanine (g) 5.53 6.02 
    Arginine (g) 6.26 7.04 
    Aspartic acid (g) 10.05 11.59 
    Cysteine (g) 1.56 1.45 
    Glutamic acid (g) 23.35 21.11 
    Glycine (g) 4.99 5.15 
    Histidine (g) 3.38 3.05 
    Isoleucine (g) 5.38 4.96 
    Leucine (g) 9.28 8.64 
    Methionine (g) 2.52 2.73 
    Lysine (g) 7.83 8.21 
    Phenylalanine (g) 5.09 4.79 
    Proline (g) 7.91 5.55 
    Serine (g) 5.33 4.96 
    Threonine (g) 4.60 4.53 
    Tryptophan (g) 1.44 1.30 
    Tyrosine (g) 4.18 3.71 
    Valine (g) 6.21 5.68 
    BCAA (g) 20.87 19.28 
    EAA (g) 45.73 43.89 
PUFA (g) 25 26 
MUFA (g) 39 39 
SFA (g) 22 23 
PUFA-to-MUFA-to-SFA ratio 1.1:1.8:1.0 1.1:1.7:1.0 
ω-3 (g) 3.5 3.3 
ω-6 (g) 20.9 21.6 
Cholesterol (mg) 228 220 
Total fiber (g) 28.0 29.7 
Calcium (mg) 1595 1487 
Vitamin D (μg) 15.3 12.8 
*

Average of the 7-day menu cycle for the 11,000-kJ diets, as determined by using the Canadian Nutrient File database (18).

Values include the vitamin D provided by cod liver oil in the BPVEM diet and by calcium and vitamin D supplements in the cod protein diet. BCAA, sum of branched-chain amino acids (isoleucine, leucine, and valine); EAA, sum of essential amino acids (histidine, isoleucine, leucine, methionine, lysine, phenylalanine, threonine, tryptophan, and valine); MUFA, monounsaturated fatty acid; SFA, saturated fatty acid.

Table 2—

Physical and clinical characteristics of the subjects at baseline

MenWomen
n 10 
Age (years) 53.8 ± 2.6 55.4 ± 2.9 
Body weight (kg) 92.7 ± 4.9 89.4 ± 4.4 
BMI (kg/m230.9 ± 1.3 33.8 ± 1.6 
Waist circumference (cm) 107.2 ± 4.0 107.0 ± 2.9 
Hip circumference (cm) 110.1 ± 2.8 121.4 ± 3.4 
Cholesterol (mmol/l)   
    Total 5.64 ± 0.39 5.27 ± 0.29 
    LDL 3.85 ± 0.32 3.22 ± 0.34 
    HDL 1.05 ± 0.05 1.45 ± 0.13 
    Total–to–HDL cholesterol ratio 5.41 ± 0.41 3.89 ± 0.42 
Total triacylglycerols (mmol/l) 1.87 ± 0.20 1.69 ± 0.23 
Fasting plasma glucose (mmol/l) 6.0 ± 0.1 6.1 ± 0.2 
2-h plasma glucose (mmol/l) 8.0 ± 0.6 8.2 ± 0.7 
Fasting insulin (pmol/l) 130 ± 22 146 ± 30 
MenWomen
n 10 
Age (years) 53.8 ± 2.6 55.4 ± 2.9 
Body weight (kg) 92.7 ± 4.9 89.4 ± 4.4 
BMI (kg/m230.9 ± 1.3 33.8 ± 1.6 
Waist circumference (cm) 107.2 ± 4.0 107.0 ± 2.9 
Hip circumference (cm) 110.1 ± 2.8 121.4 ± 3.4 
Cholesterol (mmol/l)   
    Total 5.64 ± 0.39 5.27 ± 0.29 
    LDL 3.85 ± 0.32 3.22 ± 0.34 
    HDL 1.05 ± 0.05 1.45 ± 0.13 
    Total–to–HDL cholesterol ratio 5.41 ± 0.41 3.89 ± 0.42 
Total triacylglycerols (mmol/l) 1.87 ± 0.20 1.69 ± 0.23 
Fasting plasma glucose (mmol/l) 6.0 ± 0.1 6.1 ± 0.2 
2-h plasma glucose (mmol/l) 8.0 ± 0.6 8.2 ± 0.7 
Fasting insulin (pmol/l) 130 ± 22 146 ± 30 

Data are means ± SEM.

This study was supported by the Canadian Institutes of Health Research (CIHR).

Data from this study were presented in an oral abstract session at the 10th Annual Meeting of the Canadian Diabetes Association, Toronto, Ontario, Canada, 18–21 October 2006.

1.
DeFronzo RA: Pathogenesis of type 2 diabetes mellitus.
Med Clin North Am
88
:
787
–835,
2004
2.
Nolan JJ, Ludvik B, Beerdsen P, Joyce M, Olefsky J: Improvement in glucose tolerance and insulin resistance in obese subjects treated with troglitazone.
N Engl J Med
331
:
1188
–1193,
1994
3.
Gerstein HC, Yusuf S, Bosch J, Pogue J, Sheridan P, Dinccag N, Hanefeld M, Hoogwerf B, Laakso M, Mohan V, Shaw J, Zinman B, Holman RR: Effect of rosiglitazone on the frequency of diabetes in patients with impaired glucose tolerance or impaired fasting glucose: a randomized controlled trial.
Lancet
368
:
1096
–1105,
2006
4.
Cavaghan MK, Ehrmann DA, Byrne MM, Polonsky KS: Treatment with oral antidiabetic agent troglitazone improves β cell responses to glucose in subjects with impaired glucose tolerance.
J Clin Invest
100
:
530
–537,
1997
5.
von Post-Skagegard M, Vessby B, Karlstrom B: Glucose and insulin responses in healthy women after intake of composite meals containing cod-, milk- and soy protein.
Eur J Clin Nutr
60
:
949
–954,
2006
6.
Lavigne C, Marette A, Jacques H: Cod and soy proteins compared with casein improve glucose tolerance and insulin sensitivity in rats.
Am J Physiol Endocrinol Metab
278
:
E491
–E500,
2000
7.
Lavigne C, Tremblay F, Asselin G, Jacques H, Marette A: Prevention of skeletal muscle insulin resistance by dietary cod protein in high fat-fed rats.
Am J Physiol
281
:
E62
–E71,
2001
8.
Tremblay F, Lavigne C, Jacques H, Marette A: Dietary cod protein restores insulin-induced activation of phosphatidylinositol 3-kinase/Akt and GLUT4 translocation to the T-tubules in skeletal muscle of high-fat-fed obese rats.
Diabetes
52
:
29
–37,
2003
9.
Lacaille B, Julien P, Deshaies Y, Lavigne C, Brun LD, Jacques H: Responses of plasma lipoproteins and sex hormones to the consumption of lean fish incorporated in a prudent-type diet in normolipidemic men.
J Am Coll Nutr
19
:
745
–753,
2000
10.
Beauchesne-Rondeau E, Gascon A, Bergeron J, Jacques H: Plasma lipids and lipoproteins in hypercholesterolemic men fed a lipid-lowering diet containing lean beef, lean fish, or poultry.
Am J Clin Nutr
77
:
587
–593,
2003
11.
Despres JP, Marette A: Relation of components of insulin resistance syndrome to coronary disease risk.
Curr Opin Lipidol
5
:
274
–289,
1994
12.
Kahn S, McCulloch D, Porte D: Insulin secretion in the normal and diabetic human. In
International Textbook of Diabetes Mellitus
, 2nd ed. Alberti KGMM, Zimmet P, DeFronzo RA, Keen H, Eds. New York, John Wiley and Sons,
1997
, p.
337
–354
13.
Scarsella C, Alméras N, Mauriège P, Blanchet C, Dewailly E, Després JP, Bergeron J: Determination of reference values for fasting insulin levels in a representative sample of the adult Quebec population.
Atherosclerosis
151
:
101
,
2000
14.
Escalante Pulido JM, Alpizar Salazar M: Changes in insulin sensitivity, secretion and glucose effectiveness during menstrual cycle.
Arch Med Res
30
:
19
–22,
1999
15.
Third report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report.
Circulation
106
:
3143
–3421,
2002
16.
American Diabetes Association: Evidence-based nutrition principles and recommendations for the treatment and prevention of diabetes and related complications (Position Statement).
Diabetes Care
25
:
S50
–S60,
2002
17.
Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein and Amino Acids.
Washington, DC, National Academy Press,
2002
18.
Bureau of Nutritional Sciences Food Directorate, Health Protection Branch:
The Canadian Nutrient File.
Ottawa, ON, Canada, Department of National Health and Welfare,
1997
19.
Standing Committee on the Scientific Evaluation of Dietary Reference Intakes, Food and Nutrition Board, and Institute of Medicine:
Dietary Reference Intakes for Calcium, Phosphorus, Magnesium, Vitamin D, and Fluoride.
Washington, DC, National Academy Press,
1997
20.
Piche ME, Weisnagel SJ, Corneau L, Nadeau A, Bergeron J, Lemieux S: Contribution of abdominal visceral obesity and insulin resistance to the cardiovascular risk profile of postmenopausal women.
Diabetes
54
:
770
–777,
2005
21.
Bergstrom RW, Wahl PW, Leonetti DL, Fujimoto WY: Association of fasting glucose levels with a delayed secretion of insulin after oral glucose in subjects with glucose intolerance.
J Clin Endocrinol Metab
71
:
1447
–1453,
1990
22.
Buchanan TA, Xiang AH, Peters RK, Kjos SL, Berkowitz K, Marroquin A, Goico J, Ochoa C, Azen SP: Response of pancreatic β-cells to improved insulin sensitivity in women at high risk for type 2 diabetes.
Diabetes
49
:
782
–788,
2000
23.
Hills M, Armitage P: The two-period cross-over clinical trial.
Br J Clin Pharmacol
8
:
7
–20,
1979
24.
Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus.
Diabetes Care
26(Suppl. 1)
:
S5
–S20,
2003
25.
McLaughlin T, Abbasi F, Kim HS, Lamendola C, Schaaf P, Reaven G: Relationship between insulin resistance, weight loss, and coronary heart disease risk in healthy, obese women.
Metabolism
50
:
795
–800,
2001
26.
Goodpaster BH, Kelley DE, Wing RR, Meier A, Thaete FL: Effects of weight loss on regional fat distribution and insulin sensitivity in obesity.
Diabetes
48
:
839
–847,
1999
27.
Pouliot MC, Despres JP, Lemieux S, Moorjani S, Bouchard C, Tremblay A, Nadeau A, Lupien PJ: Waist circumference and abdominal sagittal diameter: best simple anthropometric indexes of abdominal visceral adipose tissue accumulation and related cardiovascular risk in men and women.
Am J Cardiol
73
:
460
–468,
1994
28.
Schwenk WF, Haymond MW: Decreased uptake of glucose by human forearm during infusion of leucine, isoleucine, or threonine.
Diabetes
36
:
199
–204,
1987
29.
Tremblay F, Krebs M, Dombrowski L, Brehm A, Bernroider E, Roth E, Nowotny P, Waldhausl W, Marette A, Roden M: Overactivation of S6 kinase 1 as a cause of human insulin resistance during increased amino acid availability.
Diabetes
54
:
2674
–2684,
2005
30.
Piatti PM, Monti LD, Valsecchi G, Magni F, Setola E, Marchesi F, Galli-Kienle M, Pozza G, Alberti KG: Long-term oral l-arginine administration improves peripheral and hepatic insulin sensitivity in type 2 diabetic patients.
Diabetes Care
24
:
875
–880,
2001
31.
Laidlaw SA, Grosvenor M, Kopple JD: The taurine content of common foodstuffs.
JPEN J Parenter Enteral Nutr
14
:
183
–188,
1990
32.
Nandhini AT, Thirunavukkarasu V, Anuradha CV: Taurine modifies insulin signaling enzymes in the fructose-fed insulin resistant rats.
Diabetes Metab
31
:
337
–344,
2005
33.
Nakaya Y, Minami A, Harada N, Sakamoto S, Niwa Y, Ohnaka M: Taurine improves insulin sensitivity in the Otsuka Long-Evans Tokushima fatty rat, a model of spontaneous type 2 diabetes.
Am J Clin Nutr
71
:
54
–58,
2000
34.
Visioli F, Rise P, Barassi MC, Marangoni F, Galli C: Dietary intake of fish vs. formulations leads to higher plasma concentrations of n-3 fatty acids.
Lipids
38
:
415
–418,
2003
35.
Storlien LH, Baur LA, Kriketos AD, Pan DA, Cooney GJ, Jenkins AB, Calvert GD, Campbell LV: Dietary fats and insulin action.
Diabetologia
39
:
621
–631,
1996
36.
Riccardi G, Giacco R, Rivellese A: Dietary fat, insulin sensitivity and the metabolic syndrome.
Clin Nutr
23
:
447
–456,
2004
37.
Nettleton JA, Katz R: N-3 long-chain polyunsaturated fatty acids in type 2 diabetes: a review.
J Am Diet Assoc
105
:
428
–440,
2005

Published ahead of print at http://care.diabetesjournals.org on 6 August 2007. DOI: 10.2337/dc07-0273. Clinical trial reg. no. NCT00400036, clinicaltrials.gov.

Additional information for this article can be found in an online appendix at http://dx.doi.org/10.2337/dc07-0273.

A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C Section 1734 solely to indicate this fact.