Increased Lactate Release per Fat Cell in Normoglycemic First-Degree Relatives of Individuals With Type 2 Diabetes

Seven healthy subjects with at least two first-degree relatives with type 2 diabetes and seven control subjects without any known heredity for type 2 diabetes were recruited through an advertisement in a local newspaper. Diabetic relatives and control subjects were pairwise matched with respect to sex, age, and BMI. Anthropometric variables and biochemical characteristics of the subjects are shown in Table 1. The subjects gave their informed consent, and the study was approved by the Ethical Committee of Göteborg University.

On the days of investigation, all subjects arrived at 7:30 a.m. after an overnight fast. The participants were asked to maintain their regular diet and to avoid extreme physical activity on the days before the study. On the first visit, the subjects underwent an oral glucose tolerance test (75 g) and bioimpedance (BIA-103; RJL Systems, Detroit, MI) (25), and an abdominal subcutaneous needle biopsy was performed to determine fat cell size (26). Within a month after the first visit, the subjects returned for a euglycemic-hyperinsulinemic clamp, and we concomitantly performed abdominal subcutaneous microdialysis and ¹³³Xe clearance. All subjects were examined in the supine position, and the temperature in the laboratory was kept at ∼27°C.

The microdialysis technique was used as previously described (27). Briefly, two microdialysis catheters (Cuprophane, cutoff 3000 D, 0.25 × 30 mm; Gambro AB, Lund, Sweden) were placed in the periumbilical subcutaneous tissue by an ordinary cannula. No local anesthetics were used. The nylon tubings of the microdialysis catheters were connected to a microinjection pump (CMA/100 Microinjection Pump; CMA Microdialysis AB, Stockholm), and the catheters were perfused with saline containing 250 μmol/l lactate and 2.5 mmol/l glucose to prevent drainage of substances from the interstitial tissue (17). The perfusion rate was 3.0 μl/min. To obtain the interstitial concentration of lactate, each catheter was calibrated in situ according to the no net flux method (27). After the calibration procedure, samples were collected every 15 min. Steady-state sampling was performed during the last 30 min of the clamp.

Adipose tissue blood flow (ATBF) was measured with the ¹³³Xe clearance method (28) both before and during the insulin clamp. This method has a coefficient of variation for experimental inaccuracy of ∼15% in adipose tissue (29). Then, 3 to 6 MBq of ¹³³Xe (Mallinckrodt, Petten, the Netherlands) was dissolved in 0.1 ml of sterile saline and injected in the subcutaneous adipose tissue on both sides of the umbilicus at a depth of ∼5 mm. After 60 min of equilibration, clearance of ¹³³Xe was registered in 30-min intervals with NaI (TI) detectors (Canberra Industries, Meriden, CT) placed 30–50 cm above the ¹³³Xe depots and coupled to a multichannel analyzer (ND 62; Nuclear Data Instrumentation, Schaumburg, IL). Subcutaneous ATBF (ml · 100 g^–1 · min^–1) was then calculated according to the formula: ATBF = k × λ × 100, where λ is the tissue to blood partition coefficient for ¹³³Xe at equilibrium (approximated to 10 ml/g in both groups), and k is the rate constant for the washout curve.

Briefly, two polyethylene catheters (Venflon; Viggo, Helsingborg, Sweden) were positioned intravenously; for blood sampling, one was placed in the right dorsal hand vein with the forearm covered with heating pads to allow sampling of arterialized venous blood, and a second was placed in an antecubital vein of the contralateral arm for insulin and glucose infusion. The clamp started with a priming dose of regular human insulin (Actrapid; Novo Nordisk, Bagsvaerd, Denmark) for 10 min, followed by a continuous infusion at 60 mU · m² body surface · min^–1, and then, for 110 min. Albumin (Immuno, Vienna) was added to the isotonic saline to prevent adhesion to the plastic. Simultaneously, a 200-mg/ml glucose infusion (Kabi Pharmacia, Uppsala, Sweden) was started, and the infusion rate was adjusted to maintain a steady-state blood glucose level at 5.0 mmol/l and was assessed at 5-min intervals with a glucose analyzer (Yellow Springs Instrument, Yellow Springs, OH). Potassium chloride (Kabi Pharmacia) was infused at a rate of 5.0 mmol/h to prevent hypokalemia. Steady-state blood glucose was 5.1 ± 0.1 mmol/l (coefficient of variation 5.9%) and 5.1 ± 0.1 (5.5%) in relatives and control subjects, respectively. The degree of insulin sensitivity was expressed as the glucose infusion rate at steady state divided by lean body mass (LBM) (mg · kg LBM⁻¹ · min⁻¹) (M), and the glucose utilization was obtained from the average of the measurements of the final 40 min of the clamp. The insulin sensitivity index (ISI) is an adjustment for the prevailing insulin level and is calculated by dividing M by the insulin concentration during the same period of the clamp ([100 × mg × l]/kg LBM/min/pmol).

Lactate release was estimated according to Fick’s principle. Lactate release (μmol · 100 g^–1 · min^–1) = (V − A) × Q, where V is the venous plasma concentration of lactate, A is the arterialized venous plasma concentration, and Q is the plasma flow. Q = ATBF × (1 − Hct × 0.01), where Hct is hematocrit in percent. The calculation of interstitial (I) to venous plasma concentration was performed by the formula: V = (I − A) × (1 − e^−PS/Q) + A, where PS is the permeability surface product area (adopted as ∼5 ml · 100 g^–1 · min^–1 for lactate).

We determined fat cell size for each subject (26), and the volume of a fat cell was calculated as 4/3 × π × r³, where r is the radius of a fat cell. Assuming that 100 g subcutaneous adipose tissue equals ∼80 cm³ fat cells (∼20% extracellular volume) (30) and that fat cells are essentially spherical, it should be possible to estimate the number of fat cells in 100 g subcutaneous tissue by the formula 80 cm³ subcutaneous adipose tissue/fat cell volume. To estimate net lactate release per fat cell, lactate release per 100 g subcutaneous adipose tissue was divided by the assessed fat cell number of that amount of tissue.

All blood samples were kept on ice until centrifuged and stored at −20°C. Lactate and glucose concentrations in plasma and dialysates were analyzed enzymatically with a YSI 2,300 (YSI, Yellow Springs, OH). Insulin was analyzed with a radioimmunoassay technique (Pharmacia Insulin RIA 100; Pharmacia), and the concentration of nonesterified fatty acid (NEFA) was analyzed with an enzymatic colorimetric method (Wako Chemicals, Neuss, Germany).

Data are presented as means ± SE and represent observations on seven type 2 diabetic relatives and seven control subjects, respectively. Wilcoxon’s signed-rank test was applied for paired comparisons between and within the two groups. Simple linear regression was adopted for the no net flux method, and Spearman’s rank test was used for the correlation analysis. A two-tailed P ≤ 0.05 was considered as significant. StatView (Abacus Concepts, Berkeley, CA) was used for all statistical calculations.

Relatives of type 2 diabetic patients were individually matched for age, sex, and BMI but differed in waist-to-hip ratio (WHR) (P = 0.043) and subcutaneous fat cell size (P = 0.018) when compared with control subjects. In addition, the relatives had normal glucose tolerance (Table 1). Metabolic data achieved from postabsorptive and euglycemic-hyperinsulinemic clamp conditions are shown in Table 2.

The abdominal interstitial lactate concentration was 40% higher in relatives than in control subjects (P = 0.043). This difference vanished when calculating the interstitial-arterial lactate difference (IA-lactate) concentration over the abdominal site, although the IA-lactate was increased by 50% in relatives. On the contrary, subcutaneous adipose ATBF was slightly but not significantly lower in relatives (P = 0.128). Hence, estimated net lactate release per 100 g subcutaneous tissue was similar among the study groups. In addition, assessment of fat cell number per 100 g tissue demonstrated a twofold higher net lactate release per fat cell in relatives, but, due to great variation in results, this difference did not reach statistical significance.

There was a correlation between fat cell size and interstitial lactate concentration (r_s = 0.64, P = 0.020) (Fig. 1A). This association was of borderline significance when one extreme data point was omitted (r_s = 0.56, P = 0.055). However, no correlation was found between ATBF and interstitial lactate (r_s = −0.34, P = 0.222) (Fig. 1B).

Insulin infusion increased serum insulin similarly in both groups, ∼4.5-fold, but the insulin level was higher in relatives (P = 0.042). Plasma lactate was similar, whereas subcutaneous glucose conversion to lactate was clearly more pronounced in relatives, as indicated by a twofold augmentation of the IA-lactate when compared with that in the control subjects (P = 0.028). Moreover, net lactate release per fat cell was enhanced approximately fourfold in the relatives compared with the control subjects (P = 0.018). Again, the relatives showed an impaired antilipolytic effect of insulin, as indicated by an approximately threefold higher NEFA concentration compared with control subjects that was not, however, statistically significant (P = 0.063). The M value did not differ between relatives and control subjects (P = 0.612), but ISI per LBM indicated a tendency toward insulin resistance in the relatives (P = 0.063).

No relationship was found between either the IA-lactate and the M value or the IA-lactate and the ISI (data not shown).

The main finding of this study was that normoglycemic relatives of type 2 diabetic patients show an enhanced net lactate production per fat cell in subcutaneous adipose tissue. This was found, although we tried to pairwise match subjects for degree of obesity. Notwithstanding these measures, relatives proved to have a higher WHR, which another study also recently demonstrated in this group (31). Furthermore, we showed that subcutaneous fat cells were larger in relatives (32), which is a critical observation regarding the increased lactate production noticed in this and previous works (16,33).

How important is subcutaneous lactate production for whole-body lactate turnover in type 2 diabetic relatives? That question remains to be answered because we did not include any isotope dilution techniques to our protocol (such techniques have been criticized) (34). Nevertheless, net lactate production per 100 g subcutaneous tissue was similar among the groups and in agreement with previous findings in subcutaneous adipose tissue in 50-year-old obese type 2 diabetic patients and matched control subjects (35). Unlike the type 2 diabetic patients and the control group who were matched for WHR (35), the relatives of type 2 diabetic patients in our study exhibited central obesity. Unfortunately, it is not feasible to use the microdialysis technique and ¹³³Xe clearance for measurements of lactate production in visceral fat, but previous studies have shown that fat cells from the intra-abdominal fat depot are more metabolically active than subcutaneous fat cells (33). Thus, in postabsorptive type 2 diabetic relatives, total body fat and, probably more importantly, the proportion of visceral fat may significantly contribute to lactate turnover.

An obvious question is whether enlargement of fat cells in type 2 diabetic relatives is the primary defect; if it is, interstitial lactate (33) and subcutaneous blood flow (36) may be secondary phenomena to fat cell size. In this study, we were able to demonstrate a correlation between fat cell size and interstitial lactate, but this does not prove any causality between the two variables. Interestingly, in vitro studies by DiGirolamo et al. (33) and a subcutaneous microdialysis study (16) have reported the same results. The mechanism(s) leading to larger fat cells is unknown, but hormonal (37,38,39) and dietary factors (40) that were not controlled for in this study might be of importance. Furthermore, an impaired ability to differentiate new fat cells, which may lead to an enlargement of existing ones, might have a causal role (41). Peroxisome proliferator–activated receptor-γ agonists, which stimulate differentiation of preadipocytes, were shown to improve insulin sensitivity and reduce subcutaneous fat cell size in rodents (42). Thus, adipose tissue seems to play a critical role in lipid storage (43,44) and therefore decreases the abnormal partitioning of lipids in different organs (i.e., decreases the likelihood of lipotoxicity) (45).

Recently, it was reported that lactate produced in situ may enhance blood flow in skeletal muscle (46), however, this was not shown to be true in adipose tissue in this (Fig. 1B) or previous studies (16,33). Instead, one study (36) suggested that blood flow per fat cell is constant in adipose tissue. In light of the various fates of lactate in the tissues (47), the data on blood flow and lactate in muscle and adipose tissue may correlate.

Why do larger fat cells in type 2 diabetic relatives produce more lactate? In a previous study (9), we demonstrated an impaired antilipolytic effect of insulin in subcutaneous tissue in type 2 diabetic relatives. Similar results were also reported in other studies (4,48) of individuals early on in the course of diabetes. However, no difference in fasting NEFA concentration was shown in our groups, leaving a putative role for intracellular NEFA metabolism to stimulate glucose formation to lactate in enlarged fat cells (49,50). Furthermore, other factors expressed and probably secreted from enlarged fat cells, such as leptin and cytokines, may also be of importance (51,52,53). Tumor necrosis factor-α and/or interleukin-6 might impair insulin signaling in skeletal muscle (53,54,55), and, hypothetically, glucose may therefore be shunted to other tissues, such as the adipose organ.

Insulin infusion led to almost superimposable data on plasma lactate and ATBF in the groups. It has been shown that glucose entering fat cells is mainly converted to lactate and α-glycerol-phosphate, whereas only a few percent of glucose is oxidized (20,21). In type 2 diabetic relatives, the IA-lactate concentration and lactate production per fat cell were increased. Therefore, it could be argued that higher insulin levels in type 2 diabetic relatives might be responsible for the increase in lactate release. We find this less probable because the insulin doses needed to acutely cause a change in lactate production were considerably higher in a previous study (47). Interestingly, a marked increase in glucose flux to the adipose tissue was observed under euglycemic-hyperinsulinemic conditions in the MIRKO mouse, which has a knockout of the insulin receptor gene in skeletal muscle (56). In the present study, however, insulin-mediated glucose uptake under a euglycemic clamp was similar in type 2 diabetic relatives and control subjects, with borderline significance for ISI. This makes the shunting of glucose from muscle to adipose tissue a less likely explanation for the increased lactate production per fat cell in type 2 diabetic relatives. Instead, it is more likely that insulin resistance at the level of pyruvate dehydrogenase (49) and/or, theoretically, NEFAs according to the glucose fatty acid cycle (57) led to a facilitated nonoxidative glucose metabolism in adipose tissue. If the increased lactate production per fat cell under hyperinsulinemic conditions, as demonstrated in this study, has any relation to the increased risk of type 2 diabetes in individuals with enlarged subcutaneous abdominal fat cell size (58), then it needs to be evaluated in future studies. However, lactate elevation could possibly be a forerunner of or causative factor in (22,23,24) the development of carbohydrate intolerance and type 2 diabetes (12,13,14).

In conclusion, our data indicate that first-degree relatives of type 2 diabetic patients have enlarged abdominal subcutaneous fat cells and increased net lactate release per fat cell during controlled hyperinsulinemia. This could suggest a pathological regulation in adipose tissue that is of importance for the known metabolic defects in the relatives of type 2 diabetic patients.

This study was supported by the Swedish Diabetes Association, the Regional Health Care Authority of West Sweden, and the Inga-Britt and Arne Lundberg Foundation.

The authors gratefully acknowledge Margareta Landén and Lena Strindberg for their skillful technical assistance.