- Email: [email protected]
Relationships between plasma lactate, plasma alanine, genetic variations in lactate transporters and type 2 diabetes in the Japanese population
Drug Metabolism and Pharmacokinetics xxx (xxxx) xxx
Contents lists available at ScienceDirect
Drug Metabolism and Pharmacokinetics journal homepage: http://www.journals.elsevier.com/drug-metabolism-andpharmacokinetics
Regular Article
Relationships between plasma lactate, plasma alanine, genetic variations in lactate transporters and type 2 diabetes in the Japanese population Issei Higuchi a, Yuki Kimura b, Masaki Kobayashi b, **, Katsuya Narumi b, Ayako Furugen b, Hideaki Miyoshi c, Akinobu Nakamura c, Takehiro Yamada a, Tatsuya Atsumi c, Ken Iseki b, * a
Department of Pharmacy, Hokkaido University Hospital, Kita-14-jo, Nishi-5-chome, Kita-ku, Sapporo, 060-8648, Japan Laboratory of Clinical Pharmaceutics & Therapeutics, Division of Pharmasciences, Faculty of Pharmaceutical Sciences, Hokkaido University, Kita-12-jo, Nishi-6-chome, Kita-ku, Sapporo, 060-0812, Japan c Department of Rheumatology, Endocrinology and Nephrology, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Kita-15-jo, Nishi-7-chome, Kita-ku, Sapporo, 060-8638, Japan b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 7 May 2019 Received in revised form 28 August 2019 Accepted 3 October 2019 Available online xxx
The present study aimed to characterize the relationships between plasma lactate, plasma alanine, monocarboxylate transporter (MCT) polymorphisms, and indices of diabetes in patients with type 2 diabetes (T2D) in Japan. Eighty-three patients with T2D were prospectively enrolled. The gluconeogenesis and glycogenolysis are enhanced and uptake of glucose is decreased in the T2D liver. Since the liver plays an important role in maintaining glucose metabolism, we examined the relationships between liver enzymes and indices of diabetes. Some studies have reported that MCT1 (SLC16A1) polymorphism causes metabolic diseases. In addition, a high frequency of MCT1 polymorphism was reported in a healthy Japanese population. However, little is known about the relationships between T2D and MCT polymorphisms. Plasma L-lactate concentration positively correlated with indices of diabetes (fasting plasma glucose [FPG] and hemoglobin A1c [HbA1c]) and with the liver enzymes alanine aminotransferase (ALT) and gamma-glutamyl transpeptidase (g-GTP). MCT1 polymorphisms were associated with all of these markers. We identified no significant correlations between D-lactate or alanine concentrations and any of these markers, but a significant association was observed between L-lactate, a marker of oxidative capacity, and indices of diabetes. We conclude that plasma L-lactate concentration may represent a predictor of the progression or severity of T2D.
Keywords: L-lactate Diabetes Monocarboxylate transporter Single nucleotide polymorphism Liver enzymes
© 2019 Published by Elsevier Ltd on behalf of The Japanese Society for the Study of Xenobiotics.
1. Introduction Lactate exists as two stereoisomers (L-lactate and D-lactate) in the human body. L-lactate is the major physiologic stereoisomer and is produced by the glycolytic pathway. Plasma lactate concentration correlates with the rate of glycolysis and is thought to reflect mitochondrial oxidative capacity [1], and lower oxidative capacity is strongly associated with type 2 diabetes mellitus (T2D) [2]. Several studies have reported an association between high
* Corresponding author. ** Corresponding author. E-mail addresses: [email protected] (M. Kobayashi), ken-i@pharm. hokudai.ac.jp (K. Iseki).
plasma lactate concentration and insulin resistance [3,4], as well as T2D [5]. D-lactate is only present at approximately 1e5% of the Llactate concentration [6] and mainly originates from two sources in humans: the methylglyoxal pathway and intestinal bacteria. Previous studies have demonstrated higher D-lactate concentrations in patients with diabetes, infection, or ulcerative colitis, and following bowel surgery, and the use of D-lactate as a biomarker has therefore been explored [7e9]. In addition, the plasma concentration of the glucogenic amino acid, alanine, has also been reported to be altered in T2D [10,11]. However, the time points at which plasma L-lactate, D-lactate, and alanine were measured in these previous studies are unclear, and the relationships between these concentrations and T2D remain to be elucidated.
https://doi.org/10.1016/j.dmpk.2019.10.001 1347-4367/© 2019 Published by Elsevier Ltd on behalf of The Japanese Society for the Study of Xenobiotics.
Please cite this article as: Higuchi I et al., Relationships between plasma lactate, plasma alanine, genetic variations in lactate transporters and type 2 diabetes in the Japanese population, Drug Metabolism and Pharmacokinetics, https://doi.org/10.1016/j.dmpk.2019.10.001
2
I. Higuchi et al. / Drug Metabolism and Pharmacokinetics xxx (xxxx) xxx
Skeletal muscle plays an important role in lactate metabolism in the human body, because it not only produces and releases lactate, but can also use it [12]. Lactate passes through the sarcolemma by simple diffusion, but to a greater extent via the monocarboxylate transporter (MCT) proteins MCT1 (SLC16A1) and MCT4 (SLC16A3), both of which co-transport lactate and Hþ into or out of the cell, and which are expressed in skeletal muscle and liver. Consistent with this, our previous studies have shown that the uptake of monocarboxylates such as 5-oxoproline and L-lactate by MCT1 and MCT4-expressing oocytes show pH-dependency [13,14]. Juel et al. have reported that membrane MCT1 protein content is much lower in the skeletal muscle of men with T2D than in healthy individuals, whereas there is no difference in skeletal muscle MCT4 content [15]. Therefore, it seems that patients with T2D have a diminished lactate transport capacity for lactate exchange between skeletal muscle and the circulatory system. Although we have previously reported genetic variations in SLC16A1 and SLC16A3 in healthy Japanese subjects [16], little has known about these polymorphisms in T2D. Therefore, to elucidate the relationships between plasma lactate or alanine concentration and clinical diabetes, we measured the concentrations of each metabolite and measured the frequency of MCT polymorphisms in Japanese patients with T2D. 2. Materials and methods 2.1. Patients In this prospective observational study, 83 patients with T2D who were hospitalized at the Hokkaido University Hospital Internal Medicine II ward (Hokkaido, Japan) during the period April 2014eMarch 2017 were enrolled. This study was approved by the ethics committee of Hokkaido University Hospital (clinical research number 013e0196) and complied with the Helsinki Declaration and ethical guidelines on clinical research. We selected participants according to the following criteria: (1) age 20 years at the time of the provision of written informed consent for study participation, and (2) a diagnosis of diabetes, according to the Japan Diabetes Society Committee report on the classification and diagnostic criteria for diabetes mellitus [17]. The following exclusion criteria were applied: (1) a diagnosis of type 1 diabetes or the presence of pancreas-associated autoantibodies, such as glutamic acid decarboxylase; (2) a diagnosis of respiratory failure or serious liver failure; and (3) patients who were judged inappropriate as subjects by the research director. We evaluated the relationships between plasma L-lactate, Dlactate, or alanine, and known indices of diabetes (fasting plasma glucose [FPG] and hemoglobin A1c [HbA1c]) or plasma liver enzyme activities. 2.2. Blood samples Blood was drawn in the early morning after >10 h of fasting. Samples for plasma lactate assay and DNA sequencing were collected in 3-mL potassium-EDTA tubes (Becton, Dickinson and Company [BD], Franklin Lakes, NJ, USA). Samples for plasma alanine determination were collected in 3-mL lithium-heparin tubes (BD). The plasma used for lactate measurement was obtained by centrifugation at 2000g at 4 C for 10 min, and that for alanine measurement was obtained by centrifugation at 500g at 4 C for 8 min. Plasma was isolated 30e60 min after blood collection and stored at 80 C in micro-centrifuge tubes with screw caps. Clinical information (Table 1), including laboratory data collected at the time of admission, and details of complications and medication, was obtained from the patients’ medical
records. Laboratory data were recorded when blood samples for lactate and alanine assay, and DNA sequencing, were collected on admission. 2.3. Plasma L- and D-lactate concentrations Plasma L- and D-lactate concentrations were measured by highperformance liquid chromatography (HPLC) using an L-7110 pump and an L-7485 detector (Hitachi, Tokyo, Japan). Fluorescence was detected at 491 nm, with excitation at 547 nm. L- and D-lactate were separated at 35 C on a Chiralpak® AD-RH column (4.6 mm 150 mm, internal diameter 5 mm; Daicel, Osaka, Japan). Mobile phase A comprised methanol and formic acid (pH 2.0) (3:7, v/v), and mobile phase B was 100% methanol. The flow rate was 1.0 mL/min (mobile phase A:mobile phase B ¼ 1:9) and the total run time was 40 min. Fluorescent derivatization of L- and D-lactate in plasma was performed according to a previously described method, with slight modifications [8]. Briefly, 80 mL plasma and 50 mL H2O were placed into a 1.5-mL tube and 280 mL methanol/ acetonitrile (1:1) was added for deproteinization. The mixture was vortexed for 1 min and centrifuged for 5 min at 800g. The supernatant (40 mL) was then filtered through a 0.45-mm membrane filter and the sample was transferred to a 1.5-mL polypropylene brown tube, before adding 30 mL 200 mM triphenylphosphine, 30 mL 200 mM 2, 20 -dipyridyl disulfide, and 100 mL 2 mM 4-nitro-7piperazino-2,1,3-benzoxadiazole dissolved in CH3CN. The mixture was then vortexed for a few seconds and reacted for 2 h at room temperature. Next, 200 mL 5% formic acid in H2O was added and the mixture vortexed for a few seconds to stop the reaction. The sample (300 mL) was transferred to a 1.5-mL tube and dried, and the residue was reconstituted in 120 mL mobile phase. The product (70 mL) was then injected into the HPLC system. 2.4. Plasma alanine concentration Plasma alanine concentration was measured by HPLC using an L-7110 pump and an L-7485 detector (Hitachi). Fluorescence was detected at 340 nm, with excitation at 450 nm. Alanine was separated at 40 C on an Inertsil® ODS-3 column (4.6 mm 100 mm, internal diameter 3 mm; GL Sciences, Tokyo, Japan). Mobile phase A comprised methanol, 50 mM Na2HPO4, 50 mM NaH2PO4, and tetrahydrofuran (10:45:45:1, v/v/v/v), and mobile phase B comprised methanol, 50 mM Na2HPO4, and 50 mM NaH2PO4 (3:1:1, v/v/v). A binary mobile phase system was used at a flow rate of 1.2 mL/min, with a total run time of 30 min. The initial mobile phase composition was 100% mobile phase A and mobile phase B was increased from 0% to 35% along a linear gradient for the first 15 min. From 15 to 30 min, mobile phase B was increased from 35% to 100% along a linear gradient and then maintained at 100%. Plasma (70 mL) was placed in a 1.5-mL tube with 30 mL 3 mM L-norleucine (internal standard [IS]), and the mixture (10 mL) was added to 70 mL AccQ Fluor Borate Buffer (Waters, Milford, MA, USA), before 20 mL AccQ Fluor Reagent (Waters) was added, and the mixture was immediately vortexed for 10 s. The sample was then allowed to stand for 1 min at room temperature and heated at 55 C for 10 min, before amino acid derivatization. After derivatization, 100 mL methanol was added for deproteinization, and the mixture was centrifuged for 5 min at 15,000g. Ten microliters of the product were then injected into the HPLC system. 2.5. Human genomic DNA samples DNA was extracted from whole blood using the ReliaPrep™ Blood gDNA Miniprep System (Promega, Madison, WI, USA).
Please cite this article as: Higuchi I et al., Relationships between plasma lactate, plasma alanine, genetic variations in lactate transporters and type 2 diabetes in the Japanese population, Drug Metabolism and Pharmacokinetics, https://doi.org/10.1016/j.dmpk.2019.10.001
I. Higuchi et al. / Drug Metabolism and Pharmacokinetics xxx (xxxx) xxx
3
Table 1 Patient characteristics.
Indices of diabetes
Basic information
Insulin secretion
Insulin resistance Kidney function test
Liver enzyme activity
Blood lipid concentration
Medication use
Parameters
Measured value range
Reference range
L-lactate
(mM) D-lactate (mM) Alanine (mM) HbA1c (%) FPG (mg/dL) GA (%) Age (years) Duration of diabetes (years) Gender (Male %) Smoking status never (%) former (%) current (%) Alcohol intake never (%) current (%) Family history (%) Height (cm) Body weight (kg) BMI (kg/m2) Waist (cm) Visceral fat (cm2) SBP (mmHg) DBP (mmHg) DCPR (ng/mL) S-CPR (ng/mL) U-CPR/day (mg/day) HOMA-b (%) HOMA-R UACR (mg/g$Cr) eGFR (mL/min/1.73m2) S-Cr (mg/dL)
1.4 (1.2e1.6) 198.5 (134.9e377.4) 291.9 (254.7e373.9) 8.2 (7.6e9.7) 141.0 (119e178) 20.1 (16.1e24.2) 60 (48e67) 11.5 (5e18) 56.6
0.44e1.5 13.0e48.0 180e560 4.9e6.0 73e109 12.3e16.5
BUN (mg/dL) CCr (mL/min/1.73m2) AST (U/L) ALT (U/L)
14 (12e17) 106.9 (80.8e129.9) 22 (17e32) 22 (16e41)
LDH (U/L)
g-GTP (U/L)
167 (145e203) 26 (17e46)
T-CHO (mg/dL) LDL-C (mg/dL) HDL-C (mg/dL)
166 (147e186) 100 (80e124) 45 (37e53)
TG (mg/dL)
112 (86e159)
LDL-C/HDL-C TG/HDL-C CK (U/L)
2.13 (1.71e2.94) 2.40 (1.79e4.09) 88 (57e110)
SU (%) Glinide (%) BG (%) TZD (%) DPP4i (%) GLP-1 (%) aGI (%) SGLT2i (%) Insulin (%) HMG-CoA (%) Antihypertensive drug (%)
28.9 3.6 63.9 8.4 49.4 16.9 15.7 6.0 41.0 51.8 53.0
33 37 30 53 47 63.3 163.8 (157.4e171.1) 72.2 (61.3e87.6) 26.8 (23.2e31.7) 94.0 (85.5e104.0) 98.0 (63.0e131.0) 130 (117e148) 74 (67e84) 1.48 (0.8e2.6) 2.14 (1.00e2.90) 50.8 (36.1e82.6) 44.1 (21.5e71.1) 3.0 (1.8e5.2) 12.3 (5.9e59.2) 74.5 (58.8e88.0) 0.7 (0.6e0.9)
<25 <100 <140 <90 2.0e 0.69e2.45 53.6e130.8 40.0e100 1.6
M 0.65e1.07 F 0.46e0.79 8e20 108.6e191.2 13e30 M 10e42 F 7e23 124e222 M 13e64 F 9e32 142e248 65e163 (139) M 38 (40)e90 F 48 (40)e103 M 40e234 (149) F 30e117 (149) 0.00e1.50 M 59e248 F 41e153
GA, glycoalbumin; HOMA-b, homeostasis model assessment-beta function; LDH, lactate dehydrogenase; T-CHO, total cholesterol; CK, creatine kinase; SU, sulfonylurea; BG, biguanide; TZD, thiazolidinediones; DPP4i, dipeptidyl peptidase-4 inhibitor; GLP-1, glucagon-like peptide-1; aGI, alpha-glucosidase inhibitor; SGLT2i, sodium-dependent glucose transporter 2 inhibitor; HMG-CoA, 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase inhibitor; Data are medians (interquartile range) or %.
2.6. PCR analysis Primers were designed to amplify the coding regions of SLC16A1 (NM_003051.3) and SLC16A3 (NM_001206950.1) using Primer3Plus (http://www.bioinformatics.nl/cgi-bin/primer3plus/ primer3plus.cgi). Amplification was performed using a PfuUltra™ High-Fidelity DNA Polymerase Kit (Agilent, Santa Clara, CA,
USA) in a total volume of 10 mL, containing 0.4 mM each primer (Eurofins Genomics, Tokyo, Japan) and 15 ng DNA. The PCR conditions were as follows: initial denaturation at 95 C for 2 min, followed by 30 cycles of denaturation at 95 C for 30 s, annealing at 55e60 C for 30 s, and extension at 72 C for 2e5 min, followed by a final extension at 72 C for 10 min. The annealing temperatures and extension times for the primers and
Please cite this article as: Higuchi I et al., Relationships between plasma lactate, plasma alanine, genetic variations in lactate transporters and type 2 diabetes in the Japanese population, Drug Metabolism and Pharmacokinetics, https://doi.org/10.1016/j.dmpk.2019.10.001
4
I. Higuchi et al. / Drug Metabolism and Pharmacokinetics xxx (xxxx) xxx
amplicons of SLC16A1 and SLC16A3 were as previously reported [16]. 2.7. Mutation analysis Sequence analysis of the candidate genes was performed using a BigDye™ Terminator v3.1 Cycle Sequencing Kit (Thermo Fisher Scientific, Waltham, MA, USA) and an automated ABI Prism 3100 Genetic Analyzer (Thermo Fisher Scientific). The primer sequences used were as previously reported [16]. The sequences were analyzed using Sequence Scanner Software v.2 (Thermo Fisher Scientific), and PolyPhen (http://genetics.bwh.harvard.edu/pph/) and SIFT (http://sift.jcvi.org/) were used to predict the possible impacts of amino acid substitution on the structure and function of the human proteins. 2.8. Statistical analysis The present study was a prospective cross-sectional study. The primary endpoints were correlations between plasma L-lactate, Dlactate, or alanine concentration and well-characterized indices of diabetes (FPG and HbA1c). The secondary endpoints were (1) correlations between plasma L-lactate, D-lactate, or alanine concentration and other clinical parameters (plasma liver enzyme activities, blood lipid concentrations, and the incidence of diabetic complications), and (2) the relationships between the frequency of the MCT1 T1470A polymorphism and indices of diabetes, or liver enzyme activities. Data are presented as median (interquartile range) or percentage, and were analyzed using SPSS version 23 (IBM, Armonk, NY, USA). Plasma L-lactate, D-lactate, and alanine concentrations and laboratory data were analyzed using Spearman's rank correlation analysis. Correlation coefficients are shown as r. The associations between L-lactate quartiles and laboratory data were analyzed using the Kruskal-Wallis test and the Steel-Dwass test. Comparisons of laboratory data according to MCT1 T1470A frequency were analyzed using the Mann-Whitney U test or the chi-square test. p < 0.05 was considered to represent statistical significance. 3. Results 3.1. Correlations between plasma L-lactate, D-lactate, or alanine concentration and indices of diabetes The clinical data for the 83 patients with T2D enrolled in the present study are listed in Table 1. The median plasma L-lactate and alanine concentrations were within their reference ranges (1.4 mM, and 291.9 mM, respectively), but the median plasma D-lactate concentration was high (198.5 mM). As shown in Fig. 1A, L-lactate was positively correlated with FPG (r ¼ 0.388, p ¼ 0.0003) and HbA1c (r ¼ 0.294, p ¼ 0.007). Moreover, FPG was associated with the 1st Llactate quartile (Q1) versus the 3rd L-lactate quartile (Q3), and Q1 with Q4 (p < 0.005 and p < 0.007, respectively). Furthermore, HbA1c was associated with Q1 versus Q4 (p < 0.034, Fig. S1). However, we observed no significant correlations between Dlactate or alanine and either of these parameters (Fig. 1B, C). 3.2. Correlations between plasma L-lactate, D-lactate, or alanine concentrations and liver enzyme activities Next, we determined the relationships between plasma Llactate, D-lactate, or alanine concentrations and other parameters. As shown in Fig. 2, L-lactate positively correlated with some liver enzyme activities, (alanine aminotransferase [ALT]; r ¼ 0.253, p ¼ 0.021) and (gamma-glutamyl transpeptidase [g-GTP];
r ¼ 0.304, p ¼ 0.005). However, no significant correlations were identified between L-lactate and aspartate aminotransferase (AST) activity. We hypothesize that unlike ALT and g-GTP, AST may not be specifically distributed in the liver. In addition, no significant correlations were identified between D-lactate or alanine concentrations and liver enzyme activities (Fig. 2B, C). 3.3. Influence of SLC16A1 polymorphisms on indices of diabetes and liver enzyme activities We have previously reported the prevalence of the SLC16A1 polymorphism rs1049434 in the healthy Japanese population, in which the allele frequency was 0.701 [16]. In contrast, the MCT1 T1470A polymorphism was present with an allele frequency of 0.590 in the diabetic participants of the present study. The allele frequency of the MCT1 T1470A polymorphism was higher in the healthy Japanese population than in the diabetic participants. The wild type (wt)/mutated type (mt) and mt/mt genotypes of the MCT1 T1470A polymorphism were associated with lower FPG values than the wt/wt genotype (138.0 mg/dL (117.0e168.0 mg/dL) versus 161.5 mg/dL (120.3e199.0 mg/dL), p ¼ 0.040). However, HbA1c was slightly lower in individuals with wt/mt and mt/mt genotypes than in those with the wt/wt genotype, although this difference was not significant (8.1% (7.6e9.6%) versus 9.0% (8.0e10.6%), p ¼ 0.075, Fig. 3A). The wt/mt and mt/mt genotypes of the MCT1 T1470A polymorphism were associated with significantly lower liver enzyme activities (AST 20.0 U/L [17.0e27.0 U/L] versus 28.5 U/L [22.8e51.8 U/L], p ¼ 0.005; ALT 19.0 U/L [15.5e36.5 U/L] versus 36.5 U/L [19.0e54.3 U/L], p ¼ 0.003; and g-GTP 25.0 U/L [17.0e38.0 U/L] versus 39.5 U/L [21.8e73.0 U/L], p ¼ 0.024) than the wt/wt genotype (Fig. 3B). 4. Discussion In the present study, as shown in Table 1, the FPG and HbA1c values were high. The indices of insulin secretion values (delta Cpeptide immunoreactivity [DCPR], serum C-peptide immunoreactivity [S-CPR], 24-h urinary excretion rate of C-peptide immunoreactivity [U-CPR/day]) and liver enzyme activities were close to their reference ranges. The indices of diabetes nephropathy values (Urine albumin-to-creatinine ratio [UACR], estimated glomerular filtration rate [eGFR], serum creatinine [S-Cr], blood urea nitrogen [BUN], creatinine clearance [CCr]) were also close to their reference. The age, duration of diabetes, smoking status, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), low-density lipoprotein-cholesterol (LDL-C), and high-density lipoprotein-cholesterol (HDL-C) in our patients were similar to the values obtained in other Japanese patients with T2D [18]. Sixty-four percent of the participants were using metformin, a risk factor for hyperlactacidemia, but the median plasma L-lactate values were similar (metformin use group 1.3 mM [1.1e1.5 mM] versus nonmetformin use group 1.5 mM [1.3e1.7 mM]) (data not shown). Llactate was positively correlated with plasma triglyceride (TG) concentration (r ¼ 0.301, p ¼ 0.006) and the TG:HDL-C ratio ([TG/ HDL-C]; r ¼ 0.259, p ¼ 0.018; Table S1) as well as FPG (r ¼ 0.388, p ¼ 0.0003) and HbA1c (r ¼ 0.294, p ¼ 0.007) (Fig. 1A). Several previous studies have described TG concentration and TG/HDL-C as surrogate markers of insulin resistance [19e21]. Homeostasis model assessment - insulin resistance (HOMA-R) is calculated using FPG and the fasting plasma immunoreactive insulin concentration, but this cannot be measured in patients using exogenous insulin. In the present study, 41% of the participants were using insulin; therefore, HOMA-R was calculated for a limited number of the participants. Therefore, it was perhaps not surprising that we observed no significant correlation between plasma L-lactate and
Please cite this article as: Higuchi I et al., Relationships between plasma lactate, plasma alanine, genetic variations in lactate transporters and type 2 diabetes in the Japanese population, Drug Metabolism and Pharmacokinetics, https://doi.org/10.1016/j.dmpk.2019.10.001
I. Higuchi et al. / Drug Metabolism and Pharmacokinetics xxx (xxxx) xxx
5
Fig. 1. Correlations between plasma L-lactate, D-lactate, or alanine concentrations and indices of diabetes in Japanese patients with type 2 diabetes (T2D). Correlations between plasma L-lactate (A), D-lactate (B), and alanine (C) concentrations and indices of diabetes (fasting plasma glucose [FPG] and hemoglobin A1c [HbA1c]) in Japanese patients with T2D.
HOMA-R (r ¼ 0.173, p ¼ 0.224; Table S1). Accordingly, L-lactate may be used in combination with surrogate markers of insulin resistance. Using multiple logistic regression analysis, we evaluated whether plasma L-lactate concentration is independently associated with indices of diabetes. The results of multivariate analysis revealed that FPG (126 mg/dL) is an independent risk factor for hyperlactacidemia (L-lactate). In addition, only plasma L-lactate concentration was correlated with indices of diabetes (data not shown). Scheijen et al. reported significantly higher plasma Llactate concentrations in patients with T2D than in non-diabetic controls [9], and Juraschek et al. reported that high plasma lactate, a marker of oxidative capacity, was significantly associated with diabetes risk, and suggested that low oxidative capacity may precede the development of diabetes [22]. Lactate is also a marker of impaired oxidative respiration [23], associated with mitochondrial dysfunction [1], and loss of mitochondrial function has been implicated in a variety of human diseases, including diabetes [24]. Taken together, these findings suggest that plasma L-lactate concentration is higher in T2D.
Next, in the present study, we found that L-lactate positively correlated with some liver enzyme activities, ALT and g-GTP (Fig. 2A). Moreover, in the L-lactate quartile analysis, ALT was associated with Q1 versus Q4 (p < 0.045) and g-GTP was associated with Q1 versus Q3, and Q1 versus Q4 (p < 0.016 and p < 0.027, respectively, Fig. S2). Wang et al. has shown that high ALT and gGTP are significantly associated with a risk of T2D [25] and a Korean study revealed positive associations between g-GTP or ALT and T2D risk among patients without fatty liver disease [26], implying that fatty liver does not explain this association. In addition, high ALT was found to be associated with lower hepatic insulin sensitivity and predict the development of T2D [27], and high g-GTP was found to be mediated through oxidative stress [28] and inflammation [29], which were important pathways for the development of T2D. However, associations between ALT or g-GTP and T2D have been shown to be independent of other important pathologic features of T2D, such as whole-body insulin resistance [27,30] and blood lipid concentrations [30e33]. Nevertheless, the use of ALT and g-GTP concentrations has been shown to improve T2D risk
Please cite this article as: Higuchi I et al., Relationships between plasma lactate, plasma alanine, genetic variations in lactate transporters and type 2 diabetes in the Japanese population, Drug Metabolism and Pharmacokinetics, https://doi.org/10.1016/j.dmpk.2019.10.001
6
I. Higuchi et al. / Drug Metabolism and Pharmacokinetics xxx (xxxx) xxx
Fig. 2. Correlations between plasma L-lactate, D-lactate, or alanine concentrations and liver enzyme activities in Japanese patients with T2D. Correlations between plasma Llactate (A), D-lactate (B), or alanine (C) and liver enzyme activities (aspartate aminotransferase [AST], alanine aminotransferase [ALT], and gamma-glutamyl transpeptidase [g-GTP]) in Japanese patients with T2D.
prediction in several previous studies [31,34e37]. Thus, because plasma L-lactate concentration was associated with ALT and g-GTP activities in this study, it may represent a useful predictor of T2D. Finally, we examined the influence of SLC16A1 polymorphisms on indices of diabetes and liver enzyme activities. The SLC16A1 polymorphism rs1049434; T1470A, D490E is quite common and is significantly associated with exercise [38,39], while another SLC16A1 polymorphism, rs606231302; G938A, L313Q, is reported to be associated with the severity of ketoacidosis [40]. As shown in Fig. 3A, the wild type (wt)/mutated type (mt) and mt/mt genotypes of the MCT1 T1470A polymorphism were associated with lower FPG values than the wt/wt genotype. And the allele frequency of the MCT1 T1470A polymorphism was higher in the healthy Japanese population than in the diabetic participants. The wt/mt and mt/mt genotypes of the MCT1 T1470A polymorphism were associated with significantly lower liver enzyme activities than the wt/wt genotype (Fig. 3B). We have previously reported an association between high MCT1-mediated transport and this polymorphism (c.T1470A, p.D490E) [13]. We speculate that Asp-490 residue may be important for interacting with His residue, which is involved in MCT1 transport activity. Furthermore, Glu substitution affects the
conformational changes of MCT1 and activation of the transporter. On the other hand, Juel et al. have reported that MCT1 expression is much lower in insulin-resistant skeletal muscle in T2D [15]. In this study the wt/mt and mt/mt genotypes of the MCT1 T1470A polymorphism were associated with significantly more advantageous FPG and liver enzyme values, suggesting that MCT1 activity is associated with oxidative capacity. This may be because the wt/mt and mt/mt genotypes of the MCT1 T1470A polymorphism confer greater oxidative capacity than the wt/wt genotype. Conversely, although the SLC16A3 polymorphism rs368788465; C641T, S214F was found in patients with T2D in the present study, as well as in the healthy Japanese population, as previously reported [16], its frequency was low (Supplemental Table 2). Lactate transporters export lactate from muscle or liver to other tissues [41]. Because it is a precursor for gluconeogenesis, the presence of lactate in high concentrations may contribute to greater hepatic glucose production. Hence, this compensatory mechanism may contribute, in combination with lipid-induced hepatic insulin resistance, to the development of hyperglycemia and T2D. However, further investigation is required to clarify and explain the association between lactate concentrations and T2D. Our study demonstrated that
Please cite this article as: Higuchi I et al., Relationships between plasma lactate, plasma alanine, genetic variations in lactate transporters and type 2 diabetes in the Japanese population, Drug Metabolism and Pharmacokinetics, https://doi.org/10.1016/j.dmpk.2019.10.001
I. Higuchi et al. / Drug Metabolism and Pharmacokinetics xxx (xxxx) xxx
7
Fig. 3. Influence of an SLC16A1 polymorphism on indices of diabetes and liver enzyme activities in Japanese patients with T2D. Influence of an SLC16A1 polymorphism on indices of diabetes (FPG and HbA1c) (A) and liver enzyme activities (AST, ALT, and g-GTP) (B) in Japanese patients with T2D. “WW” on the horizontal axis label represents the wild type (wt)/wt genotype of the MCT1 T1470A polymorphism and “WM-MM” represents the wt/mutated type (mt) and mt/mt genotypes of the same polymorphism. L-lactate was positively associated with FPG and HbA1c, although their correlation coefficients might be low. However, we consider Llactate as a potential biomarker of T2D progression or severity in clinical practice, for the reasons given hereafter. In diabetic patients with renal failure, anemia and reduced hemoglobin levels can influence HbA1c level. L-lactate can be considered a useful biomarker in combination with the known indices of diabetes (FPG and HbA1c) in diabetic patients. In addition, a longitudinal study over a follow-up period of 12 years reported that high plasma lactate concentration is associated with the risk of incident diabetes [22]. Our study demonstrates that lactate has potential significance in predicting the onset of diabetes. This study had a few limitations. Firstly, the sample size was adequate for primary endpoint determination, such as the correlations between L-lactate, D-lactate, or alanine concentrations and indices of diabetes or liver enzyme activities. However, to clarify the relationships between plasma lactate or alanine concentrations and diabetic complications or SLC16A1 polymorphisms as a secondary endpoint, a larger sample is required. Secondly, in this study, only patients with T2D were included, so no comparisons could be drawn with healthy individuals. In the future, these limitations should be obviated in further studies.
Furthermore, we have shown associations between L-lactate and ALT or g-GTP, which have been previously reported to be predictors of T2D risk. Our results are consistent with the hypothesis that L-lactate may represent an important potential biomarker of T2D progression or pathology.
5. Conclusion
This study was supported by a grant-in-aid for scientific research (the Japan Society for the Promotion of Science (JSPS) KAKENHI grant Number JP25928022). We thank Mark Cleasby, PhD, from Edanz Group (www.edanzediting.com/ac) for editing a draft of this manuscript.
We have shown a statistically significant association between Llactate, a marker of oxidative capacity, and indices of diabetes, including FPG and HbA1c, in Japanese people with diabetes.
Authorship contributions Participated in research design: Issei Higuchi, Yuki Kimura, Masaki Kobayashi. Performed the experiments: Issei Higuchi, Yuki Kimura. Analyzed the data: Issei Higuchi, Yuki Kimura, Masaki Kobayashi. Contributed to the writing of the manuscript: Issei Higuchi, Yuki Kimura, Masaki Kobayashi, Katsuya Narumi, Ayako Furugen, Hideaki Miyoshi, Akinobu Nakamura, Takehiro Yamada, Tatsuya Atsumi, Ken Iseki. Declaration of Competing Interest The authors declare that they have no conflict of interest. Acknowledgements
Please cite this article as: Higuchi I et al., Relationships between plasma lactate, plasma alanine, genetic variations in lactate transporters and type 2 diabetes in the Japanese population, Drug Metabolism and Pharmacokinetics, https://doi.org/10.1016/j.dmpk.2019.10.001
8
I. Higuchi et al. / Drug Metabolism and Pharmacokinetics xxx (xxxx) xxx
Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.dmpk.2019.10.001. References [1] Avogaro A, Toffolo G, Miola M, Valerio A, Tiengo A, Cobelli C, et al. Intracellular lactate- and pyruvate-interconversion rates are increased in muscle tissue of non-insulin-dependent diabetic individuals. J Clin Investig 1996;98(1): 108e15. [2] Pagel-Langenickel I, Bao J, Pang L, Sack MN. The role of mitochondria in the pathophysiology of skeletal muscle insulin resistance. Endocr Rev 2010;31(1): 25e51. [3] Lovejoy J, Newby FD, Gebhart SS, DiGirolamo M. Insulin resistance in obesity is associated with elevated basal lactate levels and diminished lactate appearance following intravenous glucose and insulin. Metabolism 1992;41(1): 22e7. [4] Reaven GM, Hollenbeck C, Jeng CY, Wu MS, Chen YD. Measurement of plasma glucose, free fatty acid, lactate, and insulin for 24 h in patients with NIDDM. Diabetes 1988;37(8):1020e4. [5] Chen YD, Varasteh BB, Reaven GM. Plasma lactate concentration in obesity and type 2 diabetes. Diabetes Metab 1993;19(4):348e54. [6] McLellan AC, Phillips SA, Thornalley PJ. Fluorimetric assay of D-lactate. Anal Biochem 1992;206(1):12e6. [7] Talasniemi JP, Pennanen S, Savolainen H, Niskanen L, Liesivuori J. Analytical investigation: assay of D-lactate in diabetic plasma and urine. Clin Biochem 2008;41(13):1099e103. [8] Hasegawa H, Fukushima T, Lee JA, Tsukamoto K, Moriya K, Ono Y, et al. Determination of serum D-lactic and L-lactic acids in normal subjects and diabetic patients by column-switching HPLC with pre-column fluorescence derivatization. Anal Bioanal Chem 2003;377:886e91. [9] Scheijen JL, Hanssen NM, van de Waarenburg MP, Jonkers DM, Stehouwer CD, Schalkwijk CG, et al. L(þ) and D(-) lactate are increased in plasma and urine samples of type 2 diabetes as measured by a simultaneous quantification of L(þ) and D(-) lactate by reversed-phase liquid chromatography tandem mass spectrometry. Exp Diabetes Res 2012;2012:234812. [10] Würtz P, Tiainen M, M€ akinen VP, Kangas AJ, Soininen P, Saltevo J, et al. Circulating metabolite predictors of glycemia in middle-aged men and women. Diabetes Care 2012;35(8):1749e56. [11] Robert JJ, Beaufrere B, Koziet J, Desjeux JF, Bier DM, Young VR, et al. Whole body de novo amino acid synthesis in type I (insulin-dependent) diabetes studied with stable isotope-labeled leucine, alanine, and glycine. Diabetes 1985;34(1):67e73. [12] Bonen A. The expression of lactate transporters (MCT1 and MCT4) in heart and muscle. Eur J Appl Physiol 2001;86:6e11. [13] Sasaki S, Futagi Y, Kobayashi M, Ogura J, Iseki K. Functional characterization of 5- oxoproline transport via SLC16A1/MCT1. J Biol Chem 2015;290(4): 2303e11. [14] Sasaki S, Kobayashi M, Futagi Y, Ogura J, Yamaguchi H, Takahashi N, et al. Crucial residue involved in L-lactate recognition by human monocarboxylate transporter 4 (hMCT4). PLoS One 2013;8:e67690. [15] Juel C, Holten MK, Dela F. Effects of strength training on muscle lactate release and MCT1 and MCT4 content in healthy and type 2 diabetic humans. J Physiol (London) 2004;556:297e304. [16] Kimura Y, Kobayashi M, Asari M, Higuchi I, Narumi K, Furugen A, et al. Genetic variations in the monocarboxylate transporter genes (SLC16A1, SLC16A3, and SLC16A11) in the Japanese population. Drug Metab Pharmacokinet 2018;33(5):215e8. [17] Committee of the Japan Diabetes Society on the Diagnostic Criteria of Diabetes Mellitus, Seino Y, Nanjo K, Tajima N, Kadowaki T, Kashiwagi A, et al. Report of the committee on the classification and diagnostic criteria of diabetes mellitus. J Diabetes Investig 2010;1(5):212e28. [18] Yokoyama H, Araki SI, Kawai K, Yamazaki K, Tomonaga O, Shirabe SI, et al. Declining trends of diabetic nephropathy, retinopathy and neuropathy with improving diabetes care indicators in Japanese patients with type 2 and type 1 diabetes (JDDM 46). BMJ Open Diabetes Res Care 2018;6(1):e000521. [19] Crawford SO, Hoogeveen RC, Brancati FL, Astor BC, Ballantyne CM, Schmidt MI, et al. Association of blood lactate with type 2 diabetes: the atherosclerosis risk in communities carotid MRI study. Int J Epidemiol 2010;39(6):1647e55.
nez-Flores JR, Sigrist-Flores SC, Espinoza[20] Murguía-Romero M, Jime nez-Morales M, Pin ~ a E, et al. Plasma triglyceride/HDLCamacho MA, Jime cholesterol ratio, insulin resistance, and cardiometabolic risk in young adults. J Lipid Res 2013;54(10):2795e9. [21] Miksztowicz V, Schreier L, McCoy M, Lucero D, Fassio E, Billheimer J, et al. Role of SN1 lipases on plasma lipids in metabolic syndrome and obesity. Arterioscler Thromb Vasc Biol 2014;34(3):669e75. [22] Juraschek SP, Selvin E, Miller ER, Brancati FL, Young JH. Plasma lactate and diabetes risk in 8045 participants of the atherosclerosis risk in communities study. Ann Epidemiol 2013;23(12):791e6. faut C, Mercier J. Impaired [23] Py G, Lambert K, Perez-Martin A, Raynaud E, Pre sarcolemmal vesicle lactate uptake and skeletal muscle MCT1 and MCT4 expression in obese Zucker rats. Am J Physiol Endocrinol Metab 2001;281(6): E1308e15. [24] Jeong EM, Chung J, Liu H, Go Y, Gladstein S, Farzaneh-Far A, et al. Role of mitochondrial oxidative stress in glucose tolerance, insulin resistance, and cardiac diastolic dysfunction. J Am Heart Assoc 2016;5:e003046. [25] Wang YL, Koh WP, Yuan JM, Pan A. Association between liver enzymes and incident type 2 diabetes in Singapore Chinese men and women. BMJ Open Diabetes Res Care 2016;4(1):e000296. [26] Kim CH, Park JY, Lee KU, Kim JH, Kim HK. Association of serum gammaglutamyltransferase and alanine aminotransferase activities with risk of type 2 diabetes mellitus independent of fatty liver. Diabetes Metab Res Rev 2009;25:64e9. [27] Vozarova B, Stefan N, Lindsay RS, Saremi A, Pratley RE, Bogardus C, et al. High alanine aminotransferase is associated with decreased hepatic insulin sensitivity and predicts the development of type 2 diabetes. Diabetes 2002;51: 1889e95. [28] Turgut O, Tandogan I. Gamma-glutamyltransferase to determine cardiovascular risk: shifting the paradigm forward. J Atheroscler Thromb 2011;18: 177e81. [29] Lee DH, Jacobs Jr DR. Association between serum gamma-glutamyltransferase and C-reactive protein. Atherosclerosis 2005;178:327e30. [30] Hanley AJ, Williams K, Festa A, Wagenknecht LE, D'Agostino Jr RB, Kempf J, et al. Elevations in markers of liver injury and risk of type 2 diabetes: the insulin resistance atherosclerosis study. Diabetes 2004;53:2623e32. [31] Sattar N, Scherbakova O, Ford I, O'Reilly DS, Stanley A, Forrest E, et al. Elevated alanine aminotransferase predicts new-onset type 2 diabetes independently of classical risk factors, metabolic syndrome, and C-reactive protein in the west of Scotland coronary prevention study. Diabetes 2004;53:2855e60. [32] Doi Y, Kubo M, Yonemoto K, Ninomiya T, Iwase M, Tanizaki Y, et al. Liver enzymes as a predictor for incident diabetes in a Japanese population: the Hisayama study. Obesity (Silver Spring) 2007;15:1841e50. [33] Cho NH, Jang HC, Choi SH, Kim HR, Lee HK, Chan JC, et al. Abnormal liver function test predicts type 2 diabetes: a community-based prospective study. Diabetes Care 2007;30:2566e8. [34] Schulze MB, Weikert C, Pischon T, Bergmann MM, Al-Hasani H, Schleicher E, et al. Use of multiple metabolic and genetic markers to improve the prediction of type 2 diabetes: the EPIC-Potsdam Study. Diabetes Care 2009;32: 2116e9. [35] Balkau B, Lange C, Vol S, Fumeron F, Bonnet F. Nine-year incident diabetes is predicted by fatty liver indices: the French D.E.S.I.R. study. BMC Gastroenterol 2010;10:56. [36] Wannamethee SG, Papacosta O, Whincup PH, Thomas MC, Carson C, Lawlor DA, et al. The potential for a two-stage diabetes risk algorithm combining non-laboratory-based scores with subsequent routine non-fasting blood tests: results from prospective studies in older men and women. Diabet Med 2011;28:23e30. [37] Lorenzo C, Hanley AJ, Rewers MJ, Haffner SM. Discriminatory value of alanine aminotransferase for diabetes prediction: the Insulin Resistance Atherosclerosis Study. Diabet Med 2016;33:348e55. [38] Fedotovskaya ON, Mustafina LJ, Popov DV, Vinogradova OL, Ahmetov II. A common polymorphism of the MCT1 gene and athletic performance. Int J Sports Physiol Perform 2014;9(1):173e80. [39] Massidda M, Eynon N, Bachis V, Corrias L, Culigioni C, Piras F, et al. Influence of the MCT1 rs1049434 on indirect muscle disorders/injuries in elite football players. Sport Med Open 2015;1(1):33. [40] van Hasselt PM, Ferdinandusse S, Monroe GR, Ruiter JP, Turkenburg M, Geerlings MJ, et al. Monocarboxylate transporter 1 deficiency and ketone utilization. N Engl J Med 2014;371(20):1900e7. [41] Brooks GA. Lactate shuttles in nature. Biochem Soc Trans 2002;30(2):258e64.
Please cite this article as: Higuchi I et al., Relationships between plasma lactate, plasma alanine, genetic variations in lactate transporters and type 2 diabetes in the Japanese population, Drug Metabolism and Pharmacokinetics, https://doi.org/10.1016/j.dmpk.2019.10.001
Contents lists available at ScienceDirect
Drug Metabolism and Pharmacokinetics journal homepage: http://www.journals.elsevier.com/drug-metabolism-andpharmacokinetics
Regular Article
Relationships between plasma lactate, plasma alanine, genetic variations in lactate transporters and type 2 diabetes in the Japanese population Issei Higuchi a, Yuki Kimura b, Masaki Kobayashi b, **, Katsuya Narumi b, Ayako Furugen b, Hideaki Miyoshi c, Akinobu Nakamura c, Takehiro Yamada a, Tatsuya Atsumi c, Ken Iseki b, * a
Department of Pharmacy, Hokkaido University Hospital, Kita-14-jo, Nishi-5-chome, Kita-ku, Sapporo, 060-8648, Japan Laboratory of Clinical Pharmaceutics & Therapeutics, Division of Pharmasciences, Faculty of Pharmaceutical Sciences, Hokkaido University, Kita-12-jo, Nishi-6-chome, Kita-ku, Sapporo, 060-0812, Japan c Department of Rheumatology, Endocrinology and Nephrology, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Kita-15-jo, Nishi-7-chome, Kita-ku, Sapporo, 060-8638, Japan b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 7 May 2019 Received in revised form 28 August 2019 Accepted 3 October 2019 Available online xxx
The present study aimed to characterize the relationships between plasma lactate, plasma alanine, monocarboxylate transporter (MCT) polymorphisms, and indices of diabetes in patients with type 2 diabetes (T2D) in Japan. Eighty-three patients with T2D were prospectively enrolled. The gluconeogenesis and glycogenolysis are enhanced and uptake of glucose is decreased in the T2D liver. Since the liver plays an important role in maintaining glucose metabolism, we examined the relationships between liver enzymes and indices of diabetes. Some studies have reported that MCT1 (SLC16A1) polymorphism causes metabolic diseases. In addition, a high frequency of MCT1 polymorphism was reported in a healthy Japanese population. However, little is known about the relationships between T2D and MCT polymorphisms. Plasma L-lactate concentration positively correlated with indices of diabetes (fasting plasma glucose [FPG] and hemoglobin A1c [HbA1c]) and with the liver enzymes alanine aminotransferase (ALT) and gamma-glutamyl transpeptidase (g-GTP). MCT1 polymorphisms were associated with all of these markers. We identified no significant correlations between D-lactate or alanine concentrations and any of these markers, but a significant association was observed between L-lactate, a marker of oxidative capacity, and indices of diabetes. We conclude that plasma L-lactate concentration may represent a predictor of the progression or severity of T2D.
Keywords: L-lactate Diabetes Monocarboxylate transporter Single nucleotide polymorphism Liver enzymes
© 2019 Published by Elsevier Ltd on behalf of The Japanese Society for the Study of Xenobiotics.
1. Introduction Lactate exists as two stereoisomers (L-lactate and D-lactate) in the human body. L-lactate is the major physiologic stereoisomer and is produced by the glycolytic pathway. Plasma lactate concentration correlates with the rate of glycolysis and is thought to reflect mitochondrial oxidative capacity [1], and lower oxidative capacity is strongly associated with type 2 diabetes mellitus (T2D) [2]. Several studies have reported an association between high
* Corresponding author. ** Corresponding author. E-mail addresses: [email protected] (M. Kobayashi), ken-i@pharm. hokudai.ac.jp (K. Iseki).
plasma lactate concentration and insulin resistance [3,4], as well as T2D [5]. D-lactate is only present at approximately 1e5% of the Llactate concentration [6] and mainly originates from two sources in humans: the methylglyoxal pathway and intestinal bacteria. Previous studies have demonstrated higher D-lactate concentrations in patients with diabetes, infection, or ulcerative colitis, and following bowel surgery, and the use of D-lactate as a biomarker has therefore been explored [7e9]. In addition, the plasma concentration of the glucogenic amino acid, alanine, has also been reported to be altered in T2D [10,11]. However, the time points at which plasma L-lactate, D-lactate, and alanine were measured in these previous studies are unclear, and the relationships between these concentrations and T2D remain to be elucidated.
https://doi.org/10.1016/j.dmpk.2019.10.001 1347-4367/© 2019 Published by Elsevier Ltd on behalf of The Japanese Society for the Study of Xenobiotics.
Please cite this article as: Higuchi I et al., Relationships between plasma lactate, plasma alanine, genetic variations in lactate transporters and type 2 diabetes in the Japanese population, Drug Metabolism and Pharmacokinetics, https://doi.org/10.1016/j.dmpk.2019.10.001
2
I. Higuchi et al. / Drug Metabolism and Pharmacokinetics xxx (xxxx) xxx
Skeletal muscle plays an important role in lactate metabolism in the human body, because it not only produces and releases lactate, but can also use it [12]. Lactate passes through the sarcolemma by simple diffusion, but to a greater extent via the monocarboxylate transporter (MCT) proteins MCT1 (SLC16A1) and MCT4 (SLC16A3), both of which co-transport lactate and Hþ into or out of the cell, and which are expressed in skeletal muscle and liver. Consistent with this, our previous studies have shown that the uptake of monocarboxylates such as 5-oxoproline and L-lactate by MCT1 and MCT4-expressing oocytes show pH-dependency [13,14]. Juel et al. have reported that membrane MCT1 protein content is much lower in the skeletal muscle of men with T2D than in healthy individuals, whereas there is no difference in skeletal muscle MCT4 content [15]. Therefore, it seems that patients with T2D have a diminished lactate transport capacity for lactate exchange between skeletal muscle and the circulatory system. Although we have previously reported genetic variations in SLC16A1 and SLC16A3 in healthy Japanese subjects [16], little has known about these polymorphisms in T2D. Therefore, to elucidate the relationships between plasma lactate or alanine concentration and clinical diabetes, we measured the concentrations of each metabolite and measured the frequency of MCT polymorphisms in Japanese patients with T2D. 2. Materials and methods 2.1. Patients In this prospective observational study, 83 patients with T2D who were hospitalized at the Hokkaido University Hospital Internal Medicine II ward (Hokkaido, Japan) during the period April 2014eMarch 2017 were enrolled. This study was approved by the ethics committee of Hokkaido University Hospital (clinical research number 013e0196) and complied with the Helsinki Declaration and ethical guidelines on clinical research. We selected participants according to the following criteria: (1) age 20 years at the time of the provision of written informed consent for study participation, and (2) a diagnosis of diabetes, according to the Japan Diabetes Society Committee report on the classification and diagnostic criteria for diabetes mellitus [17]. The following exclusion criteria were applied: (1) a diagnosis of type 1 diabetes or the presence of pancreas-associated autoantibodies, such as glutamic acid decarboxylase; (2) a diagnosis of respiratory failure or serious liver failure; and (3) patients who were judged inappropriate as subjects by the research director. We evaluated the relationships between plasma L-lactate, Dlactate, or alanine, and known indices of diabetes (fasting plasma glucose [FPG] and hemoglobin A1c [HbA1c]) or plasma liver enzyme activities. 2.2. Blood samples Blood was drawn in the early morning after >10 h of fasting. Samples for plasma lactate assay and DNA sequencing were collected in 3-mL potassium-EDTA tubes (Becton, Dickinson and Company [BD], Franklin Lakes, NJ, USA). Samples for plasma alanine determination were collected in 3-mL lithium-heparin tubes (BD). The plasma used for lactate measurement was obtained by centrifugation at 2000g at 4 C for 10 min, and that for alanine measurement was obtained by centrifugation at 500g at 4 C for 8 min. Plasma was isolated 30e60 min after blood collection and stored at 80 C in micro-centrifuge tubes with screw caps. Clinical information (Table 1), including laboratory data collected at the time of admission, and details of complications and medication, was obtained from the patients’ medical
records. Laboratory data were recorded when blood samples for lactate and alanine assay, and DNA sequencing, were collected on admission. 2.3. Plasma L- and D-lactate concentrations Plasma L- and D-lactate concentrations were measured by highperformance liquid chromatography (HPLC) using an L-7110 pump and an L-7485 detector (Hitachi, Tokyo, Japan). Fluorescence was detected at 491 nm, with excitation at 547 nm. L- and D-lactate were separated at 35 C on a Chiralpak® AD-RH column (4.6 mm 150 mm, internal diameter 5 mm; Daicel, Osaka, Japan). Mobile phase A comprised methanol and formic acid (pH 2.0) (3:7, v/v), and mobile phase B was 100% methanol. The flow rate was 1.0 mL/min (mobile phase A:mobile phase B ¼ 1:9) and the total run time was 40 min. Fluorescent derivatization of L- and D-lactate in plasma was performed according to a previously described method, with slight modifications [8]. Briefly, 80 mL plasma and 50 mL H2O were placed into a 1.5-mL tube and 280 mL methanol/ acetonitrile (1:1) was added for deproteinization. The mixture was vortexed for 1 min and centrifuged for 5 min at 800g. The supernatant (40 mL) was then filtered through a 0.45-mm membrane filter and the sample was transferred to a 1.5-mL polypropylene brown tube, before adding 30 mL 200 mM triphenylphosphine, 30 mL 200 mM 2, 20 -dipyridyl disulfide, and 100 mL 2 mM 4-nitro-7piperazino-2,1,3-benzoxadiazole dissolved in CH3CN. The mixture was then vortexed for a few seconds and reacted for 2 h at room temperature. Next, 200 mL 5% formic acid in H2O was added and the mixture vortexed for a few seconds to stop the reaction. The sample (300 mL) was transferred to a 1.5-mL tube and dried, and the residue was reconstituted in 120 mL mobile phase. The product (70 mL) was then injected into the HPLC system. 2.4. Plasma alanine concentration Plasma alanine concentration was measured by HPLC using an L-7110 pump and an L-7485 detector (Hitachi). Fluorescence was detected at 340 nm, with excitation at 450 nm. Alanine was separated at 40 C on an Inertsil® ODS-3 column (4.6 mm 100 mm, internal diameter 3 mm; GL Sciences, Tokyo, Japan). Mobile phase A comprised methanol, 50 mM Na2HPO4, 50 mM NaH2PO4, and tetrahydrofuran (10:45:45:1, v/v/v/v), and mobile phase B comprised methanol, 50 mM Na2HPO4, and 50 mM NaH2PO4 (3:1:1, v/v/v). A binary mobile phase system was used at a flow rate of 1.2 mL/min, with a total run time of 30 min. The initial mobile phase composition was 100% mobile phase A and mobile phase B was increased from 0% to 35% along a linear gradient for the first 15 min. From 15 to 30 min, mobile phase B was increased from 35% to 100% along a linear gradient and then maintained at 100%. Plasma (70 mL) was placed in a 1.5-mL tube with 30 mL 3 mM L-norleucine (internal standard [IS]), and the mixture (10 mL) was added to 70 mL AccQ Fluor Borate Buffer (Waters, Milford, MA, USA), before 20 mL AccQ Fluor Reagent (Waters) was added, and the mixture was immediately vortexed for 10 s. The sample was then allowed to stand for 1 min at room temperature and heated at 55 C for 10 min, before amino acid derivatization. After derivatization, 100 mL methanol was added for deproteinization, and the mixture was centrifuged for 5 min at 15,000g. Ten microliters of the product were then injected into the HPLC system. 2.5. Human genomic DNA samples DNA was extracted from whole blood using the ReliaPrep™ Blood gDNA Miniprep System (Promega, Madison, WI, USA).
Please cite this article as: Higuchi I et al., Relationships between plasma lactate, plasma alanine, genetic variations in lactate transporters and type 2 diabetes in the Japanese population, Drug Metabolism and Pharmacokinetics, https://doi.org/10.1016/j.dmpk.2019.10.001
I. Higuchi et al. / Drug Metabolism and Pharmacokinetics xxx (xxxx) xxx
3
Table 1 Patient characteristics.
Indices of diabetes
Basic information
Insulin secretion
Insulin resistance Kidney function test
Liver enzyme activity
Blood lipid concentration
Medication use
Parameters
Measured value range
Reference range
L-lactate
(mM) D-lactate (mM) Alanine (mM) HbA1c (%) FPG (mg/dL) GA (%) Age (years) Duration of diabetes (years) Gender (Male %) Smoking status never (%) former (%) current (%) Alcohol intake never (%) current (%) Family history (%) Height (cm) Body weight (kg) BMI (kg/m2) Waist (cm) Visceral fat (cm2) SBP (mmHg) DBP (mmHg) DCPR (ng/mL) S-CPR (ng/mL) U-CPR/day (mg/day) HOMA-b (%) HOMA-R UACR (mg/g$Cr) eGFR (mL/min/1.73m2) S-Cr (mg/dL)
1.4 (1.2e1.6) 198.5 (134.9e377.4) 291.9 (254.7e373.9) 8.2 (7.6e9.7) 141.0 (119e178) 20.1 (16.1e24.2) 60 (48e67) 11.5 (5e18) 56.6
0.44e1.5 13.0e48.0 180e560 4.9e6.0 73e109 12.3e16.5
BUN (mg/dL) CCr (mL/min/1.73m2) AST (U/L) ALT (U/L)
14 (12e17) 106.9 (80.8e129.9) 22 (17e32) 22 (16e41)
LDH (U/L)
g-GTP (U/L)
167 (145e203) 26 (17e46)
T-CHO (mg/dL) LDL-C (mg/dL) HDL-C (mg/dL)
166 (147e186) 100 (80e124) 45 (37e53)
TG (mg/dL)
112 (86e159)
LDL-C/HDL-C TG/HDL-C CK (U/L)
2.13 (1.71e2.94) 2.40 (1.79e4.09) 88 (57e110)
SU (%) Glinide (%) BG (%) TZD (%) DPP4i (%) GLP-1 (%) aGI (%) SGLT2i (%) Insulin (%) HMG-CoA (%) Antihypertensive drug (%)
28.9 3.6 63.9 8.4 49.4 16.9 15.7 6.0 41.0 51.8 53.0
33 37 30 53 47 63.3 163.8 (157.4e171.1) 72.2 (61.3e87.6) 26.8 (23.2e31.7) 94.0 (85.5e104.0) 98.0 (63.0e131.0) 130 (117e148) 74 (67e84) 1.48 (0.8e2.6) 2.14 (1.00e2.90) 50.8 (36.1e82.6) 44.1 (21.5e71.1) 3.0 (1.8e5.2) 12.3 (5.9e59.2) 74.5 (58.8e88.0) 0.7 (0.6e0.9)
<25 <100 <140 <90 2.0e 0.69e2.45 53.6e130.8 40.0e100 1.6
M 0.65e1.07 F 0.46e0.79 8e20 108.6e191.2 13e30 M 10e42 F 7e23 124e222 M 13e64 F 9e32 142e248 65e163 (139) M 38 (40)e90 F 48 (40)e103 M 40e234 (149) F 30e117 (149) 0.00e1.50 M 59e248 F 41e153
GA, glycoalbumin; HOMA-b, homeostasis model assessment-beta function; LDH, lactate dehydrogenase; T-CHO, total cholesterol; CK, creatine kinase; SU, sulfonylurea; BG, biguanide; TZD, thiazolidinediones; DPP4i, dipeptidyl peptidase-4 inhibitor; GLP-1, glucagon-like peptide-1; aGI, alpha-glucosidase inhibitor; SGLT2i, sodium-dependent glucose transporter 2 inhibitor; HMG-CoA, 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase inhibitor; Data are medians (interquartile range) or %.
2.6. PCR analysis Primers were designed to amplify the coding regions of SLC16A1 (NM_003051.3) and SLC16A3 (NM_001206950.1) using Primer3Plus (http://www.bioinformatics.nl/cgi-bin/primer3plus/ primer3plus.cgi). Amplification was performed using a PfuUltra™ High-Fidelity DNA Polymerase Kit (Agilent, Santa Clara, CA,
USA) in a total volume of 10 mL, containing 0.4 mM each primer (Eurofins Genomics, Tokyo, Japan) and 15 ng DNA. The PCR conditions were as follows: initial denaturation at 95 C for 2 min, followed by 30 cycles of denaturation at 95 C for 30 s, annealing at 55e60 C for 30 s, and extension at 72 C for 2e5 min, followed by a final extension at 72 C for 10 min. The annealing temperatures and extension times for the primers and
Please cite this article as: Higuchi I et al., Relationships between plasma lactate, plasma alanine, genetic variations in lactate transporters and type 2 diabetes in the Japanese population, Drug Metabolism and Pharmacokinetics, https://doi.org/10.1016/j.dmpk.2019.10.001
4
I. Higuchi et al. / Drug Metabolism and Pharmacokinetics xxx (xxxx) xxx
amplicons of SLC16A1 and SLC16A3 were as previously reported [16]. 2.7. Mutation analysis Sequence analysis of the candidate genes was performed using a BigDye™ Terminator v3.1 Cycle Sequencing Kit (Thermo Fisher Scientific, Waltham, MA, USA) and an automated ABI Prism 3100 Genetic Analyzer (Thermo Fisher Scientific). The primer sequences used were as previously reported [16]. The sequences were analyzed using Sequence Scanner Software v.2 (Thermo Fisher Scientific), and PolyPhen (http://genetics.bwh.harvard.edu/pph/) and SIFT (http://sift.jcvi.org/) were used to predict the possible impacts of amino acid substitution on the structure and function of the human proteins. 2.8. Statistical analysis The present study was a prospective cross-sectional study. The primary endpoints were correlations between plasma L-lactate, Dlactate, or alanine concentration and well-characterized indices of diabetes (FPG and HbA1c). The secondary endpoints were (1) correlations between plasma L-lactate, D-lactate, or alanine concentration and other clinical parameters (plasma liver enzyme activities, blood lipid concentrations, and the incidence of diabetic complications), and (2) the relationships between the frequency of the MCT1 T1470A polymorphism and indices of diabetes, or liver enzyme activities. Data are presented as median (interquartile range) or percentage, and were analyzed using SPSS version 23 (IBM, Armonk, NY, USA). Plasma L-lactate, D-lactate, and alanine concentrations and laboratory data were analyzed using Spearman's rank correlation analysis. Correlation coefficients are shown as r. The associations between L-lactate quartiles and laboratory data were analyzed using the Kruskal-Wallis test and the Steel-Dwass test. Comparisons of laboratory data according to MCT1 T1470A frequency were analyzed using the Mann-Whitney U test or the chi-square test. p < 0.05 was considered to represent statistical significance. 3. Results 3.1. Correlations between plasma L-lactate, D-lactate, or alanine concentration and indices of diabetes The clinical data for the 83 patients with T2D enrolled in the present study are listed in Table 1. The median plasma L-lactate and alanine concentrations were within their reference ranges (1.4 mM, and 291.9 mM, respectively), but the median plasma D-lactate concentration was high (198.5 mM). As shown in Fig. 1A, L-lactate was positively correlated with FPG (r ¼ 0.388, p ¼ 0.0003) and HbA1c (r ¼ 0.294, p ¼ 0.007). Moreover, FPG was associated with the 1st Llactate quartile (Q1) versus the 3rd L-lactate quartile (Q3), and Q1 with Q4 (p < 0.005 and p < 0.007, respectively). Furthermore, HbA1c was associated with Q1 versus Q4 (p < 0.034, Fig. S1). However, we observed no significant correlations between Dlactate or alanine and either of these parameters (Fig. 1B, C). 3.2. Correlations between plasma L-lactate, D-lactate, or alanine concentrations and liver enzyme activities Next, we determined the relationships between plasma Llactate, D-lactate, or alanine concentrations and other parameters. As shown in Fig. 2, L-lactate positively correlated with some liver enzyme activities, (alanine aminotransferase [ALT]; r ¼ 0.253, p ¼ 0.021) and (gamma-glutamyl transpeptidase [g-GTP];
r ¼ 0.304, p ¼ 0.005). However, no significant correlations were identified between L-lactate and aspartate aminotransferase (AST) activity. We hypothesize that unlike ALT and g-GTP, AST may not be specifically distributed in the liver. In addition, no significant correlations were identified between D-lactate or alanine concentrations and liver enzyme activities (Fig. 2B, C). 3.3. Influence of SLC16A1 polymorphisms on indices of diabetes and liver enzyme activities We have previously reported the prevalence of the SLC16A1 polymorphism rs1049434 in the healthy Japanese population, in which the allele frequency was 0.701 [16]. In contrast, the MCT1 T1470A polymorphism was present with an allele frequency of 0.590 in the diabetic participants of the present study. The allele frequency of the MCT1 T1470A polymorphism was higher in the healthy Japanese population than in the diabetic participants. The wild type (wt)/mutated type (mt) and mt/mt genotypes of the MCT1 T1470A polymorphism were associated with lower FPG values than the wt/wt genotype (138.0 mg/dL (117.0e168.0 mg/dL) versus 161.5 mg/dL (120.3e199.0 mg/dL), p ¼ 0.040). However, HbA1c was slightly lower in individuals with wt/mt and mt/mt genotypes than in those with the wt/wt genotype, although this difference was not significant (8.1% (7.6e9.6%) versus 9.0% (8.0e10.6%), p ¼ 0.075, Fig. 3A). The wt/mt and mt/mt genotypes of the MCT1 T1470A polymorphism were associated with significantly lower liver enzyme activities (AST 20.0 U/L [17.0e27.0 U/L] versus 28.5 U/L [22.8e51.8 U/L], p ¼ 0.005; ALT 19.0 U/L [15.5e36.5 U/L] versus 36.5 U/L [19.0e54.3 U/L], p ¼ 0.003; and g-GTP 25.0 U/L [17.0e38.0 U/L] versus 39.5 U/L [21.8e73.0 U/L], p ¼ 0.024) than the wt/wt genotype (Fig. 3B). 4. Discussion In the present study, as shown in Table 1, the FPG and HbA1c values were high. The indices of insulin secretion values (delta Cpeptide immunoreactivity [DCPR], serum C-peptide immunoreactivity [S-CPR], 24-h urinary excretion rate of C-peptide immunoreactivity [U-CPR/day]) and liver enzyme activities were close to their reference ranges. The indices of diabetes nephropathy values (Urine albumin-to-creatinine ratio [UACR], estimated glomerular filtration rate [eGFR], serum creatinine [S-Cr], blood urea nitrogen [BUN], creatinine clearance [CCr]) were also close to their reference. The age, duration of diabetes, smoking status, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), low-density lipoprotein-cholesterol (LDL-C), and high-density lipoprotein-cholesterol (HDL-C) in our patients were similar to the values obtained in other Japanese patients with T2D [18]. Sixty-four percent of the participants were using metformin, a risk factor for hyperlactacidemia, but the median plasma L-lactate values were similar (metformin use group 1.3 mM [1.1e1.5 mM] versus nonmetformin use group 1.5 mM [1.3e1.7 mM]) (data not shown). Llactate was positively correlated with plasma triglyceride (TG) concentration (r ¼ 0.301, p ¼ 0.006) and the TG:HDL-C ratio ([TG/ HDL-C]; r ¼ 0.259, p ¼ 0.018; Table S1) as well as FPG (r ¼ 0.388, p ¼ 0.0003) and HbA1c (r ¼ 0.294, p ¼ 0.007) (Fig. 1A). Several previous studies have described TG concentration and TG/HDL-C as surrogate markers of insulin resistance [19e21]. Homeostasis model assessment - insulin resistance (HOMA-R) is calculated using FPG and the fasting plasma immunoreactive insulin concentration, but this cannot be measured in patients using exogenous insulin. In the present study, 41% of the participants were using insulin; therefore, HOMA-R was calculated for a limited number of the participants. Therefore, it was perhaps not surprising that we observed no significant correlation between plasma L-lactate and
Please cite this article as: Higuchi I et al., Relationships between plasma lactate, plasma alanine, genetic variations in lactate transporters and type 2 diabetes in the Japanese population, Drug Metabolism and Pharmacokinetics, https://doi.org/10.1016/j.dmpk.2019.10.001
I. Higuchi et al. / Drug Metabolism and Pharmacokinetics xxx (xxxx) xxx
5
Fig. 1. Correlations between plasma L-lactate, D-lactate, or alanine concentrations and indices of diabetes in Japanese patients with type 2 diabetes (T2D). Correlations between plasma L-lactate (A), D-lactate (B), and alanine (C) concentrations and indices of diabetes (fasting plasma glucose [FPG] and hemoglobin A1c [HbA1c]) in Japanese patients with T2D.
HOMA-R (r ¼ 0.173, p ¼ 0.224; Table S1). Accordingly, L-lactate may be used in combination with surrogate markers of insulin resistance. Using multiple logistic regression analysis, we evaluated whether plasma L-lactate concentration is independently associated with indices of diabetes. The results of multivariate analysis revealed that FPG (126 mg/dL) is an independent risk factor for hyperlactacidemia (L-lactate). In addition, only plasma L-lactate concentration was correlated with indices of diabetes (data not shown). Scheijen et al. reported significantly higher plasma Llactate concentrations in patients with T2D than in non-diabetic controls [9], and Juraschek et al. reported that high plasma lactate, a marker of oxidative capacity, was significantly associated with diabetes risk, and suggested that low oxidative capacity may precede the development of diabetes [22]. Lactate is also a marker of impaired oxidative respiration [23], associated with mitochondrial dysfunction [1], and loss of mitochondrial function has been implicated in a variety of human diseases, including diabetes [24]. Taken together, these findings suggest that plasma L-lactate concentration is higher in T2D.
Next, in the present study, we found that L-lactate positively correlated with some liver enzyme activities, ALT and g-GTP (Fig. 2A). Moreover, in the L-lactate quartile analysis, ALT was associated with Q1 versus Q4 (p < 0.045) and g-GTP was associated with Q1 versus Q3, and Q1 versus Q4 (p < 0.016 and p < 0.027, respectively, Fig. S2). Wang et al. has shown that high ALT and gGTP are significantly associated with a risk of T2D [25] and a Korean study revealed positive associations between g-GTP or ALT and T2D risk among patients without fatty liver disease [26], implying that fatty liver does not explain this association. In addition, high ALT was found to be associated with lower hepatic insulin sensitivity and predict the development of T2D [27], and high g-GTP was found to be mediated through oxidative stress [28] and inflammation [29], which were important pathways for the development of T2D. However, associations between ALT or g-GTP and T2D have been shown to be independent of other important pathologic features of T2D, such as whole-body insulin resistance [27,30] and blood lipid concentrations [30e33]. Nevertheless, the use of ALT and g-GTP concentrations has been shown to improve T2D risk
Please cite this article as: Higuchi I et al., Relationships between plasma lactate, plasma alanine, genetic variations in lactate transporters and type 2 diabetes in the Japanese population, Drug Metabolism and Pharmacokinetics, https://doi.org/10.1016/j.dmpk.2019.10.001
6
I. Higuchi et al. / Drug Metabolism and Pharmacokinetics xxx (xxxx) xxx
Fig. 2. Correlations between plasma L-lactate, D-lactate, or alanine concentrations and liver enzyme activities in Japanese patients with T2D. Correlations between plasma Llactate (A), D-lactate (B), or alanine (C) and liver enzyme activities (aspartate aminotransferase [AST], alanine aminotransferase [ALT], and gamma-glutamyl transpeptidase [g-GTP]) in Japanese patients with T2D.
prediction in several previous studies [31,34e37]. Thus, because plasma L-lactate concentration was associated with ALT and g-GTP activities in this study, it may represent a useful predictor of T2D. Finally, we examined the influence of SLC16A1 polymorphisms on indices of diabetes and liver enzyme activities. The SLC16A1 polymorphism rs1049434; T1470A, D490E is quite common and is significantly associated with exercise [38,39], while another SLC16A1 polymorphism, rs606231302; G938A, L313Q, is reported to be associated with the severity of ketoacidosis [40]. As shown in Fig. 3A, the wild type (wt)/mutated type (mt) and mt/mt genotypes of the MCT1 T1470A polymorphism were associated with lower FPG values than the wt/wt genotype. And the allele frequency of the MCT1 T1470A polymorphism was higher in the healthy Japanese population than in the diabetic participants. The wt/mt and mt/mt genotypes of the MCT1 T1470A polymorphism were associated with significantly lower liver enzyme activities than the wt/wt genotype (Fig. 3B). We have previously reported an association between high MCT1-mediated transport and this polymorphism (c.T1470A, p.D490E) [13]. We speculate that Asp-490 residue may be important for interacting with His residue, which is involved in MCT1 transport activity. Furthermore, Glu substitution affects the
conformational changes of MCT1 and activation of the transporter. On the other hand, Juel et al. have reported that MCT1 expression is much lower in insulin-resistant skeletal muscle in T2D [15]. In this study the wt/mt and mt/mt genotypes of the MCT1 T1470A polymorphism were associated with significantly more advantageous FPG and liver enzyme values, suggesting that MCT1 activity is associated with oxidative capacity. This may be because the wt/mt and mt/mt genotypes of the MCT1 T1470A polymorphism confer greater oxidative capacity than the wt/wt genotype. Conversely, although the SLC16A3 polymorphism rs368788465; C641T, S214F was found in patients with T2D in the present study, as well as in the healthy Japanese population, as previously reported [16], its frequency was low (Supplemental Table 2). Lactate transporters export lactate from muscle or liver to other tissues [41]. Because it is a precursor for gluconeogenesis, the presence of lactate in high concentrations may contribute to greater hepatic glucose production. Hence, this compensatory mechanism may contribute, in combination with lipid-induced hepatic insulin resistance, to the development of hyperglycemia and T2D. However, further investigation is required to clarify and explain the association between lactate concentrations and T2D. Our study demonstrated that
Please cite this article as: Higuchi I et al., Relationships between plasma lactate, plasma alanine, genetic variations in lactate transporters and type 2 diabetes in the Japanese population, Drug Metabolism and Pharmacokinetics, https://doi.org/10.1016/j.dmpk.2019.10.001
I. Higuchi et al. / Drug Metabolism and Pharmacokinetics xxx (xxxx) xxx
7
Fig. 3. Influence of an SLC16A1 polymorphism on indices of diabetes and liver enzyme activities in Japanese patients with T2D. Influence of an SLC16A1 polymorphism on indices of diabetes (FPG and HbA1c) (A) and liver enzyme activities (AST, ALT, and g-GTP) (B) in Japanese patients with T2D. “WW” on the horizontal axis label represents the wild type (wt)/wt genotype of the MCT1 T1470A polymorphism and “WM-MM” represents the wt/mutated type (mt) and mt/mt genotypes of the same polymorphism. L-lactate was positively associated with FPG and HbA1c, although their correlation coefficients might be low. However, we consider Llactate as a potential biomarker of T2D progression or severity in clinical practice, for the reasons given hereafter. In diabetic patients with renal failure, anemia and reduced hemoglobin levels can influence HbA1c level. L-lactate can be considered a useful biomarker in combination with the known indices of diabetes (FPG and HbA1c) in diabetic patients. In addition, a longitudinal study over a follow-up period of 12 years reported that high plasma lactate concentration is associated with the risk of incident diabetes [22]. Our study demonstrates that lactate has potential significance in predicting the onset of diabetes. This study had a few limitations. Firstly, the sample size was adequate for primary endpoint determination, such as the correlations between L-lactate, D-lactate, or alanine concentrations and indices of diabetes or liver enzyme activities. However, to clarify the relationships between plasma lactate or alanine concentrations and diabetic complications or SLC16A1 polymorphisms as a secondary endpoint, a larger sample is required. Secondly, in this study, only patients with T2D were included, so no comparisons could be drawn with healthy individuals. In the future, these limitations should be obviated in further studies.
Furthermore, we have shown associations between L-lactate and ALT or g-GTP, which have been previously reported to be predictors of T2D risk. Our results are consistent with the hypothesis that L-lactate may represent an important potential biomarker of T2D progression or pathology.
5. Conclusion
This study was supported by a grant-in-aid for scientific research (the Japan Society for the Promotion of Science (JSPS) KAKENHI grant Number JP25928022). We thank Mark Cleasby, PhD, from Edanz Group (www.edanzediting.com/ac) for editing a draft of this manuscript.
We have shown a statistically significant association between Llactate, a marker of oxidative capacity, and indices of diabetes, including FPG and HbA1c, in Japanese people with diabetes.
Authorship contributions Participated in research design: Issei Higuchi, Yuki Kimura, Masaki Kobayashi. Performed the experiments: Issei Higuchi, Yuki Kimura. Analyzed the data: Issei Higuchi, Yuki Kimura, Masaki Kobayashi. Contributed to the writing of the manuscript: Issei Higuchi, Yuki Kimura, Masaki Kobayashi, Katsuya Narumi, Ayako Furugen, Hideaki Miyoshi, Akinobu Nakamura, Takehiro Yamada, Tatsuya Atsumi, Ken Iseki. Declaration of Competing Interest The authors declare that they have no conflict of interest. Acknowledgements
Please cite this article as: Higuchi I et al., Relationships between plasma lactate, plasma alanine, genetic variations in lactate transporters and type 2 diabetes in the Japanese population, Drug Metabolism and Pharmacokinetics, https://doi.org/10.1016/j.dmpk.2019.10.001
8
I. Higuchi et al. / Drug Metabolism and Pharmacokinetics xxx (xxxx) xxx
Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.dmpk.2019.10.001. References [1] Avogaro A, Toffolo G, Miola M, Valerio A, Tiengo A, Cobelli C, et al. Intracellular lactate- and pyruvate-interconversion rates are increased in muscle tissue of non-insulin-dependent diabetic individuals. J Clin Investig 1996;98(1): 108e15. [2] Pagel-Langenickel I, Bao J, Pang L, Sack MN. The role of mitochondria in the pathophysiology of skeletal muscle insulin resistance. Endocr Rev 2010;31(1): 25e51. [3] Lovejoy J, Newby FD, Gebhart SS, DiGirolamo M. Insulin resistance in obesity is associated with elevated basal lactate levels and diminished lactate appearance following intravenous glucose and insulin. Metabolism 1992;41(1): 22e7. [4] Reaven GM, Hollenbeck C, Jeng CY, Wu MS, Chen YD. Measurement of plasma glucose, free fatty acid, lactate, and insulin for 24 h in patients with NIDDM. Diabetes 1988;37(8):1020e4. [5] Chen YD, Varasteh BB, Reaven GM. Plasma lactate concentration in obesity and type 2 diabetes. Diabetes Metab 1993;19(4):348e54. [6] McLellan AC, Phillips SA, Thornalley PJ. Fluorimetric assay of D-lactate. Anal Biochem 1992;206(1):12e6. [7] Talasniemi JP, Pennanen S, Savolainen H, Niskanen L, Liesivuori J. Analytical investigation: assay of D-lactate in diabetic plasma and urine. Clin Biochem 2008;41(13):1099e103. [8] Hasegawa H, Fukushima T, Lee JA, Tsukamoto K, Moriya K, Ono Y, et al. Determination of serum D-lactic and L-lactic acids in normal subjects and diabetic patients by column-switching HPLC with pre-column fluorescence derivatization. Anal Bioanal Chem 2003;377:886e91. [9] Scheijen JL, Hanssen NM, van de Waarenburg MP, Jonkers DM, Stehouwer CD, Schalkwijk CG, et al. L(þ) and D(-) lactate are increased in plasma and urine samples of type 2 diabetes as measured by a simultaneous quantification of L(þ) and D(-) lactate by reversed-phase liquid chromatography tandem mass spectrometry. Exp Diabetes Res 2012;2012:234812. [10] Würtz P, Tiainen M, M€ akinen VP, Kangas AJ, Soininen P, Saltevo J, et al. Circulating metabolite predictors of glycemia in middle-aged men and women. Diabetes Care 2012;35(8):1749e56. [11] Robert JJ, Beaufrere B, Koziet J, Desjeux JF, Bier DM, Young VR, et al. Whole body de novo amino acid synthesis in type I (insulin-dependent) diabetes studied with stable isotope-labeled leucine, alanine, and glycine. Diabetes 1985;34(1):67e73. [12] Bonen A. The expression of lactate transporters (MCT1 and MCT4) in heart and muscle. Eur J Appl Physiol 2001;86:6e11. [13] Sasaki S, Futagi Y, Kobayashi M, Ogura J, Iseki K. Functional characterization of 5- oxoproline transport via SLC16A1/MCT1. J Biol Chem 2015;290(4): 2303e11. [14] Sasaki S, Kobayashi M, Futagi Y, Ogura J, Yamaguchi H, Takahashi N, et al. Crucial residue involved in L-lactate recognition by human monocarboxylate transporter 4 (hMCT4). PLoS One 2013;8:e67690. [15] Juel C, Holten MK, Dela F. Effects of strength training on muscle lactate release and MCT1 and MCT4 content in healthy and type 2 diabetic humans. J Physiol (London) 2004;556:297e304. [16] Kimura Y, Kobayashi M, Asari M, Higuchi I, Narumi K, Furugen A, et al. Genetic variations in the monocarboxylate transporter genes (SLC16A1, SLC16A3, and SLC16A11) in the Japanese population. Drug Metab Pharmacokinet 2018;33(5):215e8. [17] Committee of the Japan Diabetes Society on the Diagnostic Criteria of Diabetes Mellitus, Seino Y, Nanjo K, Tajima N, Kadowaki T, Kashiwagi A, et al. Report of the committee on the classification and diagnostic criteria of diabetes mellitus. J Diabetes Investig 2010;1(5):212e28. [18] Yokoyama H, Araki SI, Kawai K, Yamazaki K, Tomonaga O, Shirabe SI, et al. Declining trends of diabetic nephropathy, retinopathy and neuropathy with improving diabetes care indicators in Japanese patients with type 2 and type 1 diabetes (JDDM 46). BMJ Open Diabetes Res Care 2018;6(1):e000521. [19] Crawford SO, Hoogeveen RC, Brancati FL, Astor BC, Ballantyne CM, Schmidt MI, et al. Association of blood lactate with type 2 diabetes: the atherosclerosis risk in communities carotid MRI study. Int J Epidemiol 2010;39(6):1647e55.
nez-Flores JR, Sigrist-Flores SC, Espinoza[20] Murguía-Romero M, Jime nez-Morales M, Pin ~ a E, et al. Plasma triglyceride/HDLCamacho MA, Jime cholesterol ratio, insulin resistance, and cardiometabolic risk in young adults. J Lipid Res 2013;54(10):2795e9. [21] Miksztowicz V, Schreier L, McCoy M, Lucero D, Fassio E, Billheimer J, et al. Role of SN1 lipases on plasma lipids in metabolic syndrome and obesity. Arterioscler Thromb Vasc Biol 2014;34(3):669e75. [22] Juraschek SP, Selvin E, Miller ER, Brancati FL, Young JH. Plasma lactate and diabetes risk in 8045 participants of the atherosclerosis risk in communities study. Ann Epidemiol 2013;23(12):791e6. faut C, Mercier J. Impaired [23] Py G, Lambert K, Perez-Martin A, Raynaud E, Pre sarcolemmal vesicle lactate uptake and skeletal muscle MCT1 and MCT4 expression in obese Zucker rats. Am J Physiol Endocrinol Metab 2001;281(6): E1308e15. [24] Jeong EM, Chung J, Liu H, Go Y, Gladstein S, Farzaneh-Far A, et al. Role of mitochondrial oxidative stress in glucose tolerance, insulin resistance, and cardiac diastolic dysfunction. J Am Heart Assoc 2016;5:e003046. [25] Wang YL, Koh WP, Yuan JM, Pan A. Association between liver enzymes and incident type 2 diabetes in Singapore Chinese men and women. BMJ Open Diabetes Res Care 2016;4(1):e000296. [26] Kim CH, Park JY, Lee KU, Kim JH, Kim HK. Association of serum gammaglutamyltransferase and alanine aminotransferase activities with risk of type 2 diabetes mellitus independent of fatty liver. Diabetes Metab Res Rev 2009;25:64e9. [27] Vozarova B, Stefan N, Lindsay RS, Saremi A, Pratley RE, Bogardus C, et al. High alanine aminotransferase is associated with decreased hepatic insulin sensitivity and predicts the development of type 2 diabetes. Diabetes 2002;51: 1889e95. [28] Turgut O, Tandogan I. Gamma-glutamyltransferase to determine cardiovascular risk: shifting the paradigm forward. J Atheroscler Thromb 2011;18: 177e81. [29] Lee DH, Jacobs Jr DR. Association between serum gamma-glutamyltransferase and C-reactive protein. Atherosclerosis 2005;178:327e30. [30] Hanley AJ, Williams K, Festa A, Wagenknecht LE, D'Agostino Jr RB, Kempf J, et al. Elevations in markers of liver injury and risk of type 2 diabetes: the insulin resistance atherosclerosis study. Diabetes 2004;53:2623e32. [31] Sattar N, Scherbakova O, Ford I, O'Reilly DS, Stanley A, Forrest E, et al. Elevated alanine aminotransferase predicts new-onset type 2 diabetes independently of classical risk factors, metabolic syndrome, and C-reactive protein in the west of Scotland coronary prevention study. Diabetes 2004;53:2855e60. [32] Doi Y, Kubo M, Yonemoto K, Ninomiya T, Iwase M, Tanizaki Y, et al. Liver enzymes as a predictor for incident diabetes in a Japanese population: the Hisayama study. Obesity (Silver Spring) 2007;15:1841e50. [33] Cho NH, Jang HC, Choi SH, Kim HR, Lee HK, Chan JC, et al. Abnormal liver function test predicts type 2 diabetes: a community-based prospective study. Diabetes Care 2007;30:2566e8. [34] Schulze MB, Weikert C, Pischon T, Bergmann MM, Al-Hasani H, Schleicher E, et al. Use of multiple metabolic and genetic markers to improve the prediction of type 2 diabetes: the EPIC-Potsdam Study. Diabetes Care 2009;32: 2116e9. [35] Balkau B, Lange C, Vol S, Fumeron F, Bonnet F. Nine-year incident diabetes is predicted by fatty liver indices: the French D.E.S.I.R. study. BMC Gastroenterol 2010;10:56. [36] Wannamethee SG, Papacosta O, Whincup PH, Thomas MC, Carson C, Lawlor DA, et al. The potential for a two-stage diabetes risk algorithm combining non-laboratory-based scores with subsequent routine non-fasting blood tests: results from prospective studies in older men and women. Diabet Med 2011;28:23e30. [37] Lorenzo C, Hanley AJ, Rewers MJ, Haffner SM. Discriminatory value of alanine aminotransferase for diabetes prediction: the Insulin Resistance Atherosclerosis Study. Diabet Med 2016;33:348e55. [38] Fedotovskaya ON, Mustafina LJ, Popov DV, Vinogradova OL, Ahmetov II. A common polymorphism of the MCT1 gene and athletic performance. Int J Sports Physiol Perform 2014;9(1):173e80. [39] Massidda M, Eynon N, Bachis V, Corrias L, Culigioni C, Piras F, et al. Influence of the MCT1 rs1049434 on indirect muscle disorders/injuries in elite football players. Sport Med Open 2015;1(1):33. [40] van Hasselt PM, Ferdinandusse S, Monroe GR, Ruiter JP, Turkenburg M, Geerlings MJ, et al. Monocarboxylate transporter 1 deficiency and ketone utilization. N Engl J Med 2014;371(20):1900e7. [41] Brooks GA. Lactate shuttles in nature. Biochem Soc Trans 2002;30(2):258e64.
Please cite this article as: Higuchi I et al., Relationships between plasma lactate, plasma alanine, genetic variations in lactate transporters and type 2 diabetes in the Japanese population, Drug Metabolism and Pharmacokinetics, https://doi.org/10.1016/j.dmpk.2019.10.001