Association of genetic variants of the α‑kinase 1 gene with type 2 diabetes mellitus in a longitudinal population‑based genetic epidemiological study

  • Authors:
    • Yoshiji Yamada
    • Kota Matsui
    • Ichiro Takeuchi
    • Mitsutoshi Oguri
    • Tetsuo Fujimaki
  • View Affiliations

  • Published online on: March 2, 2015     https://doi.org/10.3892/br.2015.439
  • Pages: 347-354
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Abstract

Previously, our studies identified nine genes and the chromosomal region 3q28 as susceptibility loci for myocardial infarction, ischemic stroke or chronic kidney disease in individuals by genome‑wide or candidate gene association studies. The present study examined the possible association of 13 polymorphisms at these 10 loci with the prevalence of type 2 diabetes mellitus (DM) in community‑dwelling individuals. Study subjects comprised 6,027 individuals (797 subjects with type 2 DM and 5,230 controls) who were recruited to the Inabe Health and Longevity Study, a longitudinal genetic epidemiological study of atherosclerotic, cardiovascular and metabolic diseases. The subjects were recruited from individuals who visited for an annual health checkup and they were followed up each year (mean follow‑up, 5 years). Longitudinal analysis with a generalized estimating equation and with adjustment for age, gender and body mass index (BMI) revealed that rs2116519 (C→T) of FAM78B (P=0.0188), as well as rs2074379 (G→A, P=0.0121) and rs2074388 (A→G, P=0.0053) of ALPK1 were significantly (P<0.05) associated with the prevalence of type 2 DM. Longitudinal analysis with a generalized linear mixed‑effect model and with adjustment for age, gender and BMI among all the individuals revealed that rs2116519, rs2074379 and rs2074388 were significantly associated with fasting plasma glucose level (P=0.0352, 0.0017 and 0.0010, respectively) and to blood glycosylated hemoglobin (hemoglobin A1c) content (P=0.0065, 0.0090 and 0.0079, respectively). Similar analysis among individuals not taking antidiabetic medication revealed that rs2074379 and rs2074388 were associated with the fasting plasma glucose level (P=0.0073 and 0.0042, respectively) and blood hemoglobin A1c content (P=0.0142 and 0.0126, respectively), whereas rs2116519 was associated with blood hemoglobin A1c content only (P=0.0470). ALPK1 may thus be a susceptibility gene for type 2 DM.

Introduction

The prevalence of type 2 diabetes mellitus (DM) is increasing rapidly worldwide, with >170 million individuals currently affected (1,2) and 439 million adults (7.7% of all adults) predicted to be affected by 2030 (2). The major site of this emerging epidemic is expected to be Asia, mainly as a result of changes in nutrition and other lifestyle factors (3). Given that type 2 DM increases the risk for cardiovascular disease and long-term mortality, the health care burden imposed by this condition is a matter of urgent concern (4,5). Aggressive strategies for disease prevention and early detection will be key to tackling this global issue. Approximately 95% of patients with DM have type 2 DM, with characteristics that range from insulin resistance with relatively minor insulin deficiency to insulin deficiency with relatively minor insulin resistance (6). The several mechanisms that have been suggested for the pathogenesis of type 2 DM include an increase in the production of nonesterified fatty acids, inflammatory cytokines or adipokines, and dysfunction of mitochondria for insulin resistance and glucotoxicity, lipotoxicity and amyloid formation for β-cell dysfunction (1). Although a sedentary lifestyle and overeating appear to be triggering factors, genetic factors are also indicated in the pathogenesis of type 2 DM, as a positive family history is associated with a 2.4-fold increase in the risk (1,7).

Previous genome-wide association studies (GWASs) have indicated numerous loci and genes in the predisposition to type 2 DM in various ethnic groups (817). Although KCNQ1 (13,14) and UBE2E2 (15) were identified as susceptibility genes for type 2 DM in Japanese individuals, the genes that contribute to genetic susceptibility to this condition remain to be identified.

Our previous studies identified nine genes and chromosomal region 3q28 as susceptibility loci for myocardial infarction, ischemic stroke or chronic kidney disease in Japanese individuals by genome-wide (1820) or candidate gene (2123) association studies. As type 2 DM is an important risk factor for these diseases (2426), we hypothesized that certain single-nucleotide polymorphisms (SNPs) at these 10 loci may contribute to the genetic susceptibility by affecting the susceptibility to type 2 DM. The present study examined the possible association of 13 SNPs at the 10 loci with the prevalence of type 2 DM in community-dwelling Japanese individuals.

Materials and methods

Study population

Study subjects comprised 6,027 community-dwelling individuals (797 subjects with type 2 DM and 5,230 controls) who were recruited to a population-based cohort study (Inabe Health and Longevity Study) in Inabe (Mie, Japan). The Inabe Health and Longevity Study is a longitudinal genetic epidemiological study of atherosclerotic, cardiovascular and metabolic diseases (2733). Detailed methods for recruitment of study subjects and collection of medical examination data were described previously (27).

Individuals with DM were defined as those with a fasting plasma glucose concentration of ≥126 mg/dl (6.93 mmol/l), with a blood glycosylated hemoglobin (hemoglobin A1c) content of ≥6.5%, or who were taking antidiabetic medication. Type 2 DM was defined according to the criteria accepted by the World Health Organization and described previously (6,34). Individuals with type 1 DM, maturity-onset diabetes of the young, DM associated with mitochondrial diseases or single-gene disorders, pancreatic diseases, including severe pancreatitis and pancreatic tumors, or other metabolic or endocrinological diseases were excluded from the study. Individuals taking drugs that cause secondary DM were also excluded. Control individuals had a fasting plasma glucose level of <110 mg/dl (6.05 mmol/l), a blood hemoglobin A1c content of <6.2% and no history of DM or of taking antidiabetic medication.

The study protocol complied with the Declaration of Helsinki and was approved by the Committees on the Ethics of Human Research of Mie University Graduate School of Medicine and Inabe General Hospital (Mie, Japan). Written informed consent was obtained from all the subjects.

Selection and genotyping of polymorphisms

The 13 SNPs examined in the present study were selected from our previous genome-wide (1820) or candidate gene (2123) association studies and were described previously (27). Wild-type (ancestral) and variant alleles of the SNPs were determined from the SNP database (dbSNP, National Center for Biotechnology Information, Bethesda, MD, USA; http://www.ncbi.nlm.nih.gov/SNP).

Venous blood (5 ml) was collected into tubes containing 50 mmol/l ethylenediaminetetraacetic acid (disodium salt), peripheral blood leukocytes were isolated and genomic DNA was extracted from these cells with a DNA extraction kit (SMITEST EX-R&D; Medical and Biological Laboratories, Co., Ltd., Nagoya, Japan). Genotypes of the 13 SNPs were determined at G&G Science Co., Ltd., (Fukushima, Japan) by a method that combines the polymerase chain reaction and sequence-specific oligonucleotide probes with suspension array technology (Luminex Corp., Austin, TX, USA). Primers, probes and other conditions for genotyping of SNPs examined in the present study were described previously (27), as was the detailed genotyping methodology (35).

Statistical analysis

Quantitative data were compared between subjects with type 2 DM and controls using the unpaired Student's t-test. Categorical data were compared with the χ2 test. The associations of 13 SNPs to the prevalence of type 2 DM, to fasting plasma glucose level or blood hemoglobin A1c content were examined in a 5-year longitudinal cohort study. Longitudinal changes in the prevalence of type 2 DM were compared between the two groups (dominant or recessive genetic model) by a generalized estimating equation (36) and with adjustment for age, gender and body mass index (BMI). Longitudinal changes in fasting plasma glucose level or blood hemoglobin A1c content in all the individuals or in individuals not taking antidiabetic medication were compared between the two groups (dominant or recessive model) in a generalized linear mixed-effect model (37) with adjustment for age, gender and BMI. Age-related changes in the prevalence of type 2 DM or in fasting plasma glucose level or blood hemoglobin A1c content were estimated with quadratic curves controlling for the observation year. P<0.05 was considered to indicate a statistically significant difference. Statistical analysis was performed with R software version 3-0-2 (The R Project for Statistical Computing) and JMP Genomics version 6.0 (SAS Institute, Inc., Cary, NC, USA).

Results

Subject characteristics

Characteristics of subjects with type 2 DM and controls in the cross-sectional analysis in March 2014 are shown in Table I. Age, the frequency of males and BMI were significantly greater in subjects with type 2 DM compared to the controls.

Table I.

Characteristics of the subjects with type 2 diabetes mellitus and controls: Cross-sectional analysis in March 2014.

Table I.

Characteristics of the subjects with type 2 diabetes mellitus and controls: Cross-sectional analysis in March 2014.

ParameterDiabetes mellitus (n)Controls (n)P-value
No. of subjects7975230
Age, years61.9±10.5 (797)53.0±12.9 (5230)<0.0001
Gender, % (male/female)70.5/29.5 (797)53.3/46.7 (5230)<0.0001
Height, cm162.6±9.7 (760)162.5±9.1 (5194)0.7605
Weight, kg64.6±13.5 (758)60.4±11.8 (5194)<0.0001
Body mass index, kg/m224.3±3.9 (758)22.8±3.3 (5194)<0.0001
Waist circumference, cm84.9±9.9 (683)79.8±9.0 (4922)<0.0001
Alcohol drinking, %50.2 (797)48.0 (5230)0.2437
Current or former smoking, %55.5 (797)44.2 (5230)<0.0001
Systolic blood pressure, mmHg127±18 (753)120±16 (5192)<0.0001
Diastolic blood pressure, mmHg77±12 (753)74±12 (5192)<0.0001
Mean blood pressure, mmHg94±13 (753)89±12 (5192)<0.0001
Ocular tension, right, mmHg14.1±3.2 (246)13.4±2.9 (1815)0.0005
Functional vital capacity, l3.14±0.78 (255)3.32±0.81 (1988)0.0009
FEV1%80.4±6.3 (255)81.4±6.6 (1988)0.0287
Serum albumin, g/l44.1±3.6 (613)44.7±2.5 (3599)<0.0001
Serum total cholesterol, mmol/l5.10±1.00 (784)5.23±0.87 (5166)0.0001
Serum triglycerides, mmol/l1.49±1.06 (772)1.23±0.82 (5164)<0.0001
Serum HDL-cholesterol, mmol/l1.51±0.42 (771)1.68±0.45 (5163)<0.0001
Serum LDL-cholesterol, mmol/l3.13±0.87 (770)3.18±0.79 (5162)0.1294
Fasting plasma glucose, mg/dl132.4±40.3 (789)95.8±8.6 (5167)<0.0001
Blood hemoglobin A1c, %6.65±1.27 (621)5.54±0.33 (3842)<0.0001
Blood urea nitrogen, mmol/l6.27±3.48 (612)5.03±1.54 (3489)<0.0001
Serum creatinine, µmol/l109.5±182.9 (767)68.3±45.3 (4809)<0.0001
eGFR, ml min−1 1.73 m−271.2±23.6 (767)77.5±15.2 (4809)<0.0001
Serum uric acid, µmol/l340±84 (759)324±86 (4772)<0.0001
Serum C-reactive protein, µg/l2515±14479 (295)981±3758 (1818)0.0001
White blood cells, 103/µl5.90±2.19 (554)5.31±1.57 (4053)<0.0001
Red blood cells, 104/µl438±50 (556)437±44 (4067)0.4542
Hemoglobin, g/l139±18 (556)138±15 (4067)0.0549
Hematocrit, %40.6±4.8 (555)40.2±4.2 (4063)0.0656
Platelets, 104/µl21.0±5.9 (551)22.5±5.3 (4017)<0.0001

[i] Quantitative data are mean ± standard deviation. FEV1, forced expiratory volume in 1 sec; HDL, high-density lipoprotein; LDL, low-density lipoprotein; eGFR, estimated glomerular filtration rate (ml min−1 1.73 m−2) = 194 × [age (years)]−0.287 × [serum creatinine (mg/dl)]−1.094 × [0.739 if female].

Associations with type 2 DM

The associations of the 13 SNPs to the prevalence of type 2 DM were analyzed with a generalized estimating equation and with adjustment for age, gender and BMI (Table II). The rs2116519 (C→T) SNP of the FAM78B gene (recessive model), as well as rs2074379 (G→A, dominant model) and rs2074388 (A→G, dominant model) of ALPK1 were significantly (P<0.05) associated with the prevalence of type 2 DM.

Table II.

Associations of polymorphisms with type 2 diabetes mellitus analyzed for 5-year longitudinal data with a generalized estimating equation.

Table II.

Associations of polymorphisms with type 2 diabetes mellitus analyzed for 5-year longitudinal data with a generalized estimating equation.

Gene or locusSNPGenotypeDiabetes mellitus, n (%)Control, n (%)P-value (dominant)aP-value (recessive)b
FAM78Brs2116519 (C→T)TT553 (29.0)5783 (31.0)0.06480.0188c
TC950 (49.8)9438 (50.5)
CC403 (21.1)3459 (18.5)
3q28rs9846911 (A→G)AA1642 (86.1)16272 (87.1)0.79240.9172
AG251 (13.2)2304 (12.3)
GG13 (0.7)104 (0.6)
ALPK1rs2074379 (G→A)AA807 (42.3)8680 (46.5)0.0121c0.2027
AG901 (47.3)8180 (43.8)
GG198 (10.4)1820 (9.7)
ALPK1rs2074380 (G→A)GG1613 (84.6)15797 (84.6)0.65790.3014
GA287 (15.1)2736 (14.6)
AA6 (0.3)147 (0.8)
ALPK1rs2074381 (A→G)AA1646 (86.4)15937 (85.3)0.45580.1330
AG258 (13.5)2622 (14.0)
GG2 (0.1)121 (0.6)
ALPK1rs2074388 (A→G)AA799 (41.9)8687 (46.5)0.0053c0.1492
AG906 (47.5)8169 (43.7)
GG201 (10.5)1824 (9.8)
BTN2A1rs6929846 (T→C)CC1507 (79.1)14566 (78.0)0.63220.9904
CT373 (19.6)3850 (20.6)
TT26 (1.4)264 (1.4)
THBS2rs8089 (T→G)TT1559 (81.8)15393 (82.4)0.77680.4105
TG329 (17.3)3120 (16.7)
GG18 (0.9)167 (0.9)
PDX1rs146021107 (G→-)GG540 (28.3)5303 (28.4)0.93810.6936
G924 (48.5)9284 (49.7)
−−442 (23.2)4093 (21.9)
F7rs6046 (G→A)GG1665 (87.4)16285 (87.2)0.60750.1153
GA234 (12.3)2313 (12.4)
AA7 (0.4)82 (0.4)
LLGL2rs1671021 (G→A)AA1393 (73.1)13813 (73.9)0.70720.5812
AG487 (25.6)4490 (24.0)
GG26 (1.4)377 (2.0)
ILF3rs2569512 (G→A)GG834 (43.8)8200 (43.9)0.84000.4642
GA878 (46.1)8442 (45.2)
AA194 (10.2)2038 (10.9)
CELSR1rs6007897 (C→T)TT1838 (96.4)18151 (97.2)0.1157ND
TC68 (3.6)529 (2.8)
CC0 (0)0 (0)

a Dominant, AA vs. AB + BB (A, major allele; B, minor allele).

b Recessive, AA + AB vs. BB.

c P<0.05. Prevalence of type 2 diabetes mellitus was compared between two groups (dominant or recessive model) for each polymorphism with adjustment for age, gender and body mass index. SNP, single-nucleotide polymorphism; ND, not determined.

The associations between the prevalence of type 2 DM and age analyzed longitudinally with a generalized estimating equation according to SNP genotype are shown in Fig. 1. The prevalence of type 2 DM was greater in subjects with the CC genotype of rs2116519 of FAM78B compared to the combined group of subjects with the TT or TC genotypes from 40 to 90 years of age (Fig. 1A), in the combined group of subjects with the AG or GG genotypes of rs2074379 of ALPK1 compared to those with the AA genotype (Fig. 1B) and in the combined group of subjects with the AG or GG genotypes of rs2074388 of ALPK1 compared to those with the AA genotype (Fig. 1C).

As three SNPs were significantly associated with type 2 DM, the associations of these SNPs to fasting plasma glucose level or blood hemoglobin A1c content in all the individuals or individuals not taking antidiabetic medication were analyzed with a generalized linear mixed-effect model and with adjustment for age, gender and BMI (Table III). The rs2116519 SNP of FAM78B, as well as rs2074379 and rs2074388 of ALPK1 were significantly (P<0.05) associated with fasting plasma glucose level and blood hemoglobin A1c content in a dominant model among all the individuals. Among individuals not taking antidiabetic medication, rs2116519 of FAM78B was significantly associated with blood hemoglobin A1c content in a dominant model, whereas rs2074379 and rs2074388 of ALPK1 were significantly associated with fasting plasma glucose level and blood hemoglobin A1c content in a dominant model.

Table III.

Associations of polymorphisms to fasting plasma glucose level or blood hemoglobin A1c content in all individuals or individuals not taking antidiabetic medication, analyzed for 5-year longitudinal data with a generalized linear mixed-effect model.

Table III.

Associations of polymorphisms to fasting plasma glucose level or blood hemoglobin A1c content in all individuals or individuals not taking antidiabetic medication, analyzed for 5-year longitudinal data with a generalized linear mixed-effect model.

Gene (SNP)Dominant modelaP-valueRecessive modelaP-value
All individuals
  FAM78B (rs2116519, C→T)TT (6336)TC + CC (14250) TT + TC (16724)CC (3862)
    Fasting plasma glucose, mg/dl99.9±16.4100.5±18.30.0352b100.3±17.5100.5±19.00.2251
    Blood hemoglobin A1c, %5.69±0.595.71±0.650.0065b5.70±0.635.70±0.660.4079
  ALPK1 (rs2074379, G→A)AA (9484)AG + GG (11099) AA + AG (18568)GG (2018)
    Fasting plasma glucose, mg/dl99.8±15.7100.8±19.40.0017b100.3±17.6101.0±19.00.5509
    Blood hemoglobin A1c, %5.68±0.575.72±0.690.0090b5.70±0.625.74±0.730.0502
  ALPK1 (rs2074388, A→G)AA (9486)AG + GG (11100) AA + AG (18561)GG (2025)
    Fasting plasma glucose, mg/dl99.8±15.6100.8±19.40.0010b100.3±17.6101.2±19.10.4149
    Blood hemoglobin A1c, %5.68±0.575.72±0.690.0079b5.70±0.625.74±0.730.0417
Individuals without antidiabetic medication
  FAM78B, (rs2116519, C→T)TT (6260)TC + CC (14045) TT + TC (16495)CC (3810)
    Fasting plasma glucose, mg/dl99.6±15.8100.0±17.20.108799.8±16.699.9±17.60.2482
    Blood hemoglobin A1c, %5.68±0.575.69±0.610.0470b5.68±0.605.68±0.620.3992
  ALPK1, (rs2074379, G→A)AA (9370)AG + GG (10935) AA + AG (18318)GG (1987)
    Fasting plasma glucose, mg/dl99.4±15.0100.2±18.10.0073b99.8±16.6100.5±18.30.5845
    Blood hemoglobin A1c, %5.66±0.545.70±0.650.0142b5.68±0.595.72±0.710.1134
  ALPK1, (rs2074388, A→G)AA (9369)AG + GG (10936) AA + AG (18311)GG (1994)
    Fasting plasma glucose, mg/dl99.4±15.0100.3±18.20.0042b99.8±16.6100.6±18.30.4372
    Blood hemoglobin A1c, %5.66±0.545.70±0.650.0126b5.68±0.595.72±0.710.0947

a Values in parentheses are numbers of measurements.

b P<0.05. Data for fasting plasma glucose level and blood hemoglobin A1c content are means ± standard deviation. Fasting plasma glucose level and blood hemoglobin A1c content were compared between two groups (dominant or recessive model) for each polymorphism with adjustment for age, gender and body mass index. SNP, single-nucleotide polymorphism.

The associations between fasting plasma glucose level and age analyzed longitudinally according to genotype in all the individuals with a generalized linear mixed-effect model are shown in Fig. 2. Fasting plasma glucose level was greater in the combined group of individuals with the TC or CC genotypes of rs2116519 of FAM78B compared to those with the TT genotype from 40 to 90 years of age (Fig. 2A), in the combined group of individuals with the AG or GG genotypes of rs2074379 of ALPK1 compared to those with the AA genotype (Fig. 2B) and in the combined group of individuals with the AG or GG genotypes of rs2074388 of ALPK1 compared to those with the AA genotype (Fig. 2C).

The associations between blood hemoglobin A1c content and age analyzed longitudinally according to genotype in all the individuals with a generalized linear mixed-effect model are shown in Fig. 3. Blood hemoglobin A1c was greater in the combined group of individuals with the TC or CC genotypes of rs2116519 of FAM78B compared to those with the TT genotype from 40 to 90 years of age (Fig. 3A), in the combined group of individuals with the AG or GG genotypes of rs2074379 of ALPK1 compared to those with the AA genotype (Fig. 3B) and in the combined group of individuals with the AG or GG genotypes of rs2074388 of ALPK1 compared to those with the AA genotype (Fig. 3C).

Discussion

As genetic factors and interactions between multiple genes and environmental factors are important in the development of type 2 DM (1,7), prediction of the risk for type 2 DM on the basis of genetic variants would be beneficial for personalized prevention of this condition. In the present study, rs2074379 and rs2074388 of ALPK1 were significantly associated with the prevalence of type 2 DM in a longitudinal genetic epidemiological study, with the minor G allele of each SNP representing a risk factor for this condition. Our previous study showed that ALPK1 is a susceptibility locus for chronic kidney disease in individuals with DM by a GWAS (20). We also observed that genetic variants of ALPK1 were associated with type 2 DM in a previous cross-sectional analysis of the Inabe Health and Longevity Study (28). The present results in the longitudinal population-based study are consistent with the previous observations in the cross-sectional study (28) and they validate the association of genetic variants of ALPK1 with type 2 DM.

ALPK1 functions in apical transport by phosphorylating myosin 1a in epithelial cells and is indicated in the regulation of intracellular trafficking processes by phosphorylation (38). ALPK1 may act synergistically with monosodium urate monohydrate crystals to promote the production of proinflammatory cytokines through the activation of nuclear factor-κB and mitogen-activated protein kinase (extracellular signal-regulated kinase 1/2 and p38) signaling in cultured HEK293 cells, suggesting that ALPK1 may contribute to the inflammatory process associated with the development of gout (39).

Impaired insulin secretion and increased insulin resistance are key components of type 2 DM (40). Although the contributions of these factors to the onset and progression of type 2 DM may differ between Caucasian and Asian populations, the two factors are significant for diagnostic and therapeutic strategies targeted to this disease (41). Previous studies have shown that proinflammatory cytokines (interleukin-1β and tumor necrosis factor) detrimentally affect insulin secretion and resistance (42,43). Additionally, signaling pathways activated by proinflammatory cytokines, including those mediated by nuclear factor-κB, have been identified to impair insulin secretion or to promote insulin resistance (44). As chronic inflammation may play an important role in the development of type 2 DM, the effects of rs2074379 and rs2074388 of ALPK1 on the inflammatory process may account for the association of this gene with type 2 DM.

rs2116519 of FAM78B was also associated with the prevalence of type 2 DM, as well as to fasting plasma glucose level and blood hemoglobin A1c content among all the individuals or to blood hemoglobin A1c content among the individuals not taking antidiabetic medication. FAM78B is located at chromosome 1q24.1, a region previously suggested to harbor a susceptibility locus for type 2 DM (45), although the function of this gene remains unclear.

There are certain limitations to the present study: i) As the results were not replicated, validation of these findings requires their replication with other independent subject panels or ethnic groups; ii) rs2074379 or rs2074388 are possibly in linkage disequilibrium with other polymorphisms in the same gene or in other nearby genes that are responsible for the development of type 2 DM; and iii) the functional relevance of rs2074379 or rs2074388 of ALPK1 to the pathogenesis of type 2 DM has not been determined.

In conclusion, the present results suggest that ALPK1 is a susceptibility gene for type 2 DM in community-dwelling Japanese individuals. Determination of genotypes for the polymorphisms of ALPK1 may prove informative for assessment of the genetic risk for type 2 DM in the Japanese population.

Acknowledgements

The present study was supported by Core Research for Evolutional Science and Technology of the Japan Science and Technology Agency (Y.Y. and I.T.) and by a Grant-in-Aid for Scientific Research from the Ministry of Education, Culture, Sports, Science and Technology of Japan (grant no. 24590746 to Y.Y.).

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May-2015
Volume 3 Issue 3

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Spandidos Publications style
Yamada Y, Matsui K, Takeuchi I, Oguri M and Fujimaki T: Association of genetic variants of the α‑kinase 1 gene with type 2 diabetes mellitus in a longitudinal population‑based genetic epidemiological study. Biomed Rep 3: 347-354, 2015
APA
Yamada, Y., Matsui, K., Takeuchi, I., Oguri, M., & Fujimaki, T. (2015). Association of genetic variants of the α‑kinase 1 gene with type 2 diabetes mellitus in a longitudinal population‑based genetic epidemiological study. Biomedical Reports, 3, 347-354. https://doi.org/10.3892/br.2015.439
MLA
Yamada, Y., Matsui, K., Takeuchi, I., Oguri, M., Fujimaki, T."Association of genetic variants of the α‑kinase 1 gene with type 2 diabetes mellitus in a longitudinal population‑based genetic epidemiological study". Biomedical Reports 3.3 (2015): 347-354.
Chicago
Yamada, Y., Matsui, K., Takeuchi, I., Oguri, M., Fujimaki, T."Association of genetic variants of the α‑kinase 1 gene with type 2 diabetes mellitus in a longitudinal population‑based genetic epidemiological study". Biomedical Reports 3, no. 3 (2015): 347-354. https://doi.org/10.3892/br.2015.439