Literature DB >> 28357066

Association of two synonymous splicing-associated CpG single nucleotide polymorphisms in calpain 10 and solute carrier family 2 member 2 with type 2 diabetes.

Maria Karambataki1, Andigoni Malousi2, Georgios Tzimagiorgis2, Constantinos Haitoglou2, Aikaterini Fragou2, Elisavet Georgiou2, Foteini Papadopoulou3, Gerasimos E Krassas3, Sofia Kouidou2.   

Abstract

Coding synonymous single nucleotide polymorphisms (SNPs) have attracted little attention until recently. However, such SNPs located in epigenetic, CpG sites modifying exonic splicing enhancers (ESEs) can be informative with regards to the recently verified association of intragenic methylation and splicing. The present study describes the association of type 2 diabetes (T2D) with the exonic, synonymous, epigenetic SNPs, rs3749166 in calpain 10 (CAPN10) glucose transporter (GLUT4) translocator and rs5404 in solute carrier family 2, member 2 (SLC2A2), also termed GLUT2, which, according to prior bioinformatic analysis, strongly modify the splicing potential of glucose transport-associated genes. Previous association studies reveal that only rs5404 exhibits a strong negative T2D association, while data on the CAPN10 polymorphism are contradictory. In the present study DNA from blood samples of 99 Greek non-diabetic control subjects and 71 T2D patients was analyzed. In addition, relevant publicly available cases (40) resulting from examination of 110 Personal Genome Project data files were analyzed. The frequency of the rs3749166 A allele, was similar in the patients and non-diabetic control subjects. However, AG heterozygotes were more frequent among patients (73.24% for Greek patients and 54.55% for corresponding non-diabetic control subjects; P=0.0262; total cases, 52.99 and 75.00%, respectively; P=0.0039). The rs5404 T allele was only observed in CT heterozygotes (Greek non-diabetic control subjects, 39.39% and Greek patients, 22.54%; P=0.0205; total cases, 34.69 and 21.28%, respectively; P=0.0258). Notably, only one genotype, heterozygous AG/CC, was T2D-associated (Greek non-diabetic control subjects, 29.29% and Greek patients, 56.33%; P=0.004; total cases, 32.84 and 56.58%, respectively; P=0.0008). Furthermore, AG/CC was strongly associated with very high (≥8.5%) glycosylated plasma hemoglobin levels among patients (P=0.0002 for all cases). These results reveal the complex heterozygotic SNP association with T2D, and indicate possible synergies of these epigenetic, splicing-regulatory, synonymous SNPs, which modify the splicing potential of two alternative glucose transport-associated genes.

Entities:  

Keywords:  CAPN10; HbA1c; SLC2A2; bioinformatics analysis; family history; heterozygosity; synonymous CpG polymorphisms

Year:  2016        PMID: 28357066      PMCID: PMC5351308          DOI: 10.3892/br.2016.833

Source DB:  PubMed          Journal:  Biomed Rep        ISSN: 2049-9434


Introduction

RNA splicing is a fundamental process, which contributes to the structural and functional complexity of proteins and influences their regulatory role and tissue specificity (1,2). Splicing enhancers in exons are considered to be responsible for the inclusion of exonic sequences in the gene transcript. There is growing evidence that polymorphisms in high impact exonic splicing enhancers (ESEs) strongly influence the activity of disease-associated genes and modify their association with different pathological conditions (3). Bioinformatic resources are available for evaluating the efficiency of ESEs (4). It has been previously demonstrated that a major role of intragenic DNA methylation is associated with the regulation of alternative splicing (5,6). It should therefore be expected that polymorphisms, which modify a G or a C in a CpG dinucleotide, affect the epigenetic profile in exonic sequences that are most frequently found to be methylated (7). In sites of tentative DNA methylation, particularly when located in ESEs, this would lead to allele-specific methylation differences (8). In view of the recently demonstrated impact of DNA methylation on the splicing process (6), it is also expected that exonic CpG polymorphisms may further affect splicing. The presence of ESEs and their relative potential are predictable by bioinformatic analysis. Recent experimental evidence verified the consistency of the computational results with experimentally observed exon inclusion using a minigene (9). It is also evident that CpG-single nucleotide polymorphisms (SNPs) in prominent ESEs of disease-associated genes are of particular importance (10,11). Based on this evidence, various studies have focused on genetic variations (SNPs) at CpGs, which may be responsible for predisposition to various pathological conditions, including type 2 diabetes (T2D) (11,12). T2D is a metabolic disorder characterized by high glucose blood levels associated with insulin resistance and relatively low levels of insulin. Together with obesity, blood hypertension and hyperlipidemia, T2D is one of the most frequent conditions associated with metabolic syndrome, which is currently considered a major cause for cardiovascular disease. Genetic association studies for the identification of SNPs associated with these diseases are performed by genome-wide association study (13). However, the distinct epigenetic/splicing-associated role of these SNPs has not, to the best of our knowledge, been addressed, despite previous evidence that the expression of different splicing isoforms is a major factor for disease association even in the heterozygous state (14,15). In view of the above, a bioinformatic analysis of synonymous SNPs in all T2D-associated genes (11) was performed in the present study to identify prominent CpG-SNPs, which introduce major modifications in the splicing potential of exonic sequences, which may be responsible for T2D. This analysis identified two principle CpG-SNPs, rs5404 in solute carrier family 2, member 2 (SLC2A2), and rs3749166 in calpain (CAPN10), a membrane protease, which is involved in glucose transporter (GLUT)4 translocation (16). rs3749166 (A>G) is located in exon 11 of the CAPN10 gene and rs5404 (C>T) in exon 5 of the SLC2A2 gene. The two CpG-SNPs introduce pronounced changes in the ESE score (splicing potential) of the corresponding exonic sequences in these genes. The association of CAPN10 SNP with T2D in particular, has been addressed in previous studies (17–22). In the present study, the association of these two epigenetic CpG-SNPs were analyzed, which introduced the greatest changes of the splicing potential in the corresponding genes, with T2D and other metabolic syndrome-associated pathological conditions (arterial hypertension and obesity). In addition, the possibility that this association might be observed only in the heterozygotic state of these SNPs was investigated.

Materials and methods

Study population

The investigated population included 99 non-diabetic control participants (Table IA) and 71 T2D patients (Table IB). Participants were classified as having T2D based on the American Diabetic Association criteria (23) as follows: i) ≥126 mg/dl fasting plasma glucose concentration; ii) glycosylated plasma hemoglobin (HbA1c) ≥6.5%; iii) insulin use; iv) use of other diabetes medication. All participants provided their medical family history, smoking habits and dietary information, followed by written informed consent. Their names were anonymized prior to study completion. The methods followed in the present study were performed according to the Declaration of Helsinki.
Table I.

Genotypes and epidemiological parameters (age, gender, BMI, metabolic, family history, smoking status, dietary conditions and accompanying diseases) of non-diabetic control subjects (Table A) and T2D patients (Table B).

A, Non-diabetic control subjects

S/No.nAge (years)GenderBMIrs3749166rs5404FG (mg/dl)HbA1c (%)Chol (mg/dl)LDL (mg/dl)HDL (mg/dl)TGL (mg/dl)FHSmoking statusNo dietDiseases
1    1  65M  23G/GC/C1105.9106  80  36  95++
2    3  47F  25A/AC/C  855.3178139  46150+HL
3    4  58F  21A/GC/C  845.4223182  59146
4    6  71F  22A/GC/T1106.4220182  63131HL
5    7  80F  28A/AC/C1066.0163141  42  69HT
6    9  77F  26A/AC/C  965.6353305  51190HL
7  10  60F  29A/GC/T1186.2153111  40174+HT/HL
8  12  58M  34A/GC/C  945.6177143  33139+HT
9  13  54M  25A/GC/T1045.7267219  67177
10  14  50F  35A/AC/C  985.6298256  53160HL
11  16  66F  24G/GC/C1105.9185153  60104HT/HL
12  19  50F  35G/GC/T  825.6225194  31126++
13  20  68F  32A/GC/C  885.5215184  53103HT
14  21  75M  28A/AC/C  875.6112  92  28  76+HT
15  23  50M  22A/GC/T  875.2239206  61106+
16  25  76F  29A/GC/T  985.6236186  49204HT/HL
17  26  65F  26A/GC/T1075.8187152  57118+HT/HL
18  27  54F  29G/GC/C1075.9250218  56106+HL
19  28  57F  46A/GC/T1156.0239200  51143+HT/HL
20  29  80F  24A/GC/C  835.3188161  63  73HT/HL
21  30  80F  27A/AC/C  855.4212180  58100HT/HL
22  31  77M  31A/GC/C  895.6178154  38  82HT
23  32  66M  26A/GC/T  925.6229188  50159
24  37  54F  28A/AC/C1105.8230198  40124+HT/HL
25  38  69M  29A/AC/T1015.9202153  40209+HT/HL
26  39  52F  35A/AC/T  955.6171119  40220HL
27  40  74F  23G/GC/C1005.7172143  69  79HT/HL
28  43  45F  38A/GC/T1005.7216190  38  96
29  44  56M  38A/AC/C  785.6179144  50128
30  48  71F  27A/GC/T1015.8171122  33215HT/HL
31  50  79M  23A/GC/C  915.6167134  46123HT/HL
32  51  45F  34A/GC/T  885.6242199  49167+HL
33  52  52F  31A/AC/C  945.6211162  41208HL
34  54  58M  36A/GC/T1115.8154113  40167HT
35  56  61F  31A/GC/C1016.2257216  52155
36  58  76F  28A/GC/C1075.8259228  73  83HT
37  59  69F31.5A/GC/C1035.7202172  48103HT
38  60  73F  25A/GC/C  905.4222190  53109HT
39  61  45F  34G/GC/C  895.2173144  51  97
40  63  66M  30A/AC/T1176.4170138  41121+HT/HL
41  64  60F  30A/GC/C  935.6170131  40155HT/HL
42  66  65F  28A/GC/C  985.6193150  41171
43  67  45F  17G/GC/T  985.0176147  53  93
44  68  63F  28A/GC/C  905.1214185  57  92HL
45  70  50F  33A/GC/T1056.4217180  48137+HL
46  71  62F  28A/GC/C1096.0263220  62152HL
47  75  60F  29G/GC/C  885.6225192  48114HT
48  76  52M  25G/GC/C  915.5197160  54134
49  77  50F  25A/AC/T  995.6210168  42168HL
50  78  58F  25A/GC/C  885.3249214  81  93HL
51  81  70F  29G/GC/C1175.8212172  49150+HL
52  84  55F  32G/GC/C  955.4218187  49103HT/HL
53  85  53F  25A/AC/C  915.5223183  67132HT
54  87  65F  34G/GC/C1065.8240202  51139HT/HL
55  88  49F  33A/GC/T  985.6213170  33185++HT/HL
56  89  73F  28A/AC/C1086.3216188  52  89
57  90  57M  32A/AC/C  915.5205157  30208+HT/HL
58  92  73F  21A/GC/T1095.9261215  55175HT/HL
59  94  66F  30A/GC/C1156.3163132  52105HT/HL
60  99  68M  30A/AC/C  855.5213163  45202HL
61100  58F  30A/AC/C  955.6232203  44100
62101  53F  27A/GC/T1065.7218177  64140
63102  59F  23A/GC/C  955.3169142  45  89HT
64104  78M  24A/AC/C1005.7211186  55  70HT
65106  64F  33A/GC/T1086.4208164  43177HT
66107  47F  27A/AC/T1055.7239196  57155HL
67108  43F  28A/AC/T  895.4159130  44103+
68109  71M  27A/GC/C1015.7171122  33215HT
69110  57F  32A/GC/T1045.8220155  40286HL
70111  60F  26G/GC/C  995.3167144  49  65
71112  65F  26A/GC/C  935.4201165  76104HT/HL
72113  47F  29G/GC/C1025.7216180  61122
73114  73F  24A/GC/C1206.2216188  52  89
74118  46F  29A/AC/T  885.5148  88  30267HT/HL
75120  58F  26A/GC/C1045.7263138  61  61HL
76121  56F  32G/GC/C  875.6187149  70120
77153  60F  33G/GC/C  875.3235200  64112++HT/HL
78155  66M  26A/GC/C1245.7256200  45232++HT/HL
79156  50F  26A/GC/C  935.2256176  60337+HL
80158  54F  24A/AC/T1045.7257218  62131HT
81159  63F  25A/AC/C1155.8181148  64  99HL
82161  49F  22A/GC/T  935.3213178100  75++
83165  50F  29A/GC/T  855.1158  84  31339HL
84166  50M  29A/GC/T1075.7258215  32174+HL
85171  52M  28A/AC/T1015.7213175  36151+
86173  51M  32A/GC/T  785.3191153  38151++
87174  50M  28A/AC/T  965.0171139  38120
88176  80F  32A/GC/C1215.9158112  43183HT/HL
89177  71M  28A/GC/C1055.8220175  77144HT/HL
90178  56F  30A/GC/T1085.8182152  53  93HT
91179  67M  29A/GC/C1055.7179149  34112
92180  65F  26A/GC/C  915.7198168  73  73HT/HL
93189  50F  31A/GC/T  825.2197168  58  87+
94190  50M  31A/AC/T  955.4286228  51187HL
95192  58F  58A/AC/T  935.6244210  68100+HT/HL
96194  52F  25A/GC/T  855.2219194  44  81+HL
97195  61F  27A/GC/C  825.6242202  69  93HT/HL
98196  77F  39A/AC/C1086.2218185  71  90+HT/HL
99197  61F  35A/GC/C  945.6182  49145122+HT/HL

B, T2D patients

S/No.nAge (years)GenderBMIAge of diagnosisrs3749166rs5404FG (mg/dl)HbA1cChol (mg/dl)LDL (mg/dl)HDL (mg/dl)TGL (mg/dl)FHSmoking statusMedicationNo dietDCDiseases

1    2  62M  30  50A/GC/C1289.4154125  39109DNAHT/HL
2    5  60F  41  35A/GC/C1838.9156128  39102+DNAHT/HL
3    8  80F  32  80A/GC/C143  11177143  39134T+HT/HL
4  11  54F  27  40A/GC/C1429.5190159  55104T/IN
5  15  80F  23  75A/AC/C1289.8135108  40  98+INDNAHT
6  17  71F  44A/AC/C1447.4150117  37129++DNAHT/HL
7  18  65F  24A/GC/C2069.0204168  47136THL
8  22  60M  28A/GC/C  936.1281188  39429THL
9  24  66F  30A/GC/T1107.1191164  50  86TDNAHT
10  33  57F  24A/AC/C1777.8219189  55  97T/INHT/HL
11  34  78F  41  65G/GC/T1557.5157124  40126++THT
12  35  63M  36  50A/AC/C2549.9252198  321077+T+HT/HL
13  36  71F  33  54A/GC/C1397.8216175  54153T/IN+DNAHL
14  41  64M  30  50A/GC/T2868.8219173  31202+T/IN+DNAHT/HL
15  42  80M  18  60A/GC/T34610.5192162  51100+TDNA
16  45  72F  30  65A/GC/C  836.4126  98  29115T
17  46  62F  31  62A/AC/C1687.4223184  52148+DietHT/HL
18  47  73F  33  60A/AC/T1858.0189156  48117TDNAHT
19  49  71M  28  65A/AC/C1117.6219180  45153THT/HL
20  53  58F  30  57A/GC/C2958.7201154  43195DietHL
21  55  67M  25  55A/AC/C29510.6205162  36182+DNAHT/HL
22  57  66F  29A/GC/C1097.4200153  36200THL
23  62  79F  30A/GC/T1517.8169141  45  99T/INDNA
24  65  59M  36A/AC/C1306.8125  84  29178T
25  69  63F  29  40A/GC/C  897.2178133  37190T
26  72  62F  26A/GC/C2288.6178133  50175INHL
27  73  69  30A/AC/C1717.5166132  57114THT/HL
28  74  54F  24A/GC/C2108.6290216  32339+T
29  79  51M  28A/GC/C1277.6181127  26246T/INHT/HL
30  80  70M  39A/AC/T1347.7152106  33200IN+DNAHT/HL
31  82  68F  34  40A/GC/T1558.2243186  61224INHL
32  83  45F  60  45A/GC/C1117.8240180  27275Diet+HL
33  86  81F  28  68A/GC/C1327.4171132  41156INDNAHT
34  91  62F  34  62A/GC/T  987.2312241  41313+Diet+HT
35  93  59F  36  58A/GC/C  917.2193153  40161+DietHT
36  95  52F  40  50A/GC/T1197.0212172  53148THT
37  96  79F  30  60G/GC/C1457.6169141  49  94+THT
38  97  45F  30  37A/GC/C1497.2144102  28182++THT
39  98  45F  22  37A/GC/C2698.8188162  60  73++IN+
40103  62F  38  52A/GC/T1527.8145  80  45284T+DNAHT
41105  67M  32  57A/GC/C2338.8235182  37232+T/IN
42115  65M  19A/GC/C4228.9182149  41125+TDNA
43116  79F  32  75A/GC/T1517.8151120  36124TDNAHT
44117  74F  38  67A/AC/T1647.8130  93  35152T/INHT/HL
45119  45F  56A/GC/C1677.6191134  36250++DietHL
46151  74F  31A/GC/C1027.2239206  62106+Diet+HT/HL
47152  66F  30  62A/GC/C1266.8152120  34127++T+HT
48154  78M  32  58A/GC/C1799.1123  80  33183+T/IN+DNAHT/HL
49157  73M  33  58A/GC/C1387.7108  85  38  77T+DNAHT
50160  59F  48  59A/GC/C1487.5190156  43130+T+HT/HL
51162  68F  33  45A/GC/C1658.7168122  37197+INDNAHT
52163  63M  28  58A/GC/C25710.3164130  38134TDNAHT/HL
53164  74F  30  64G/GC/C1245.8181130  62  93DietHT/HL
54167  72F  26  46A/GC/C1347.0162137  49  77THT/HL
55169  67F  28  49A/GC/C1257.4167130  47141TDNAHT/HL
56170  73F  34  48G/GC/C23510.1177134  31187T/INDNA
57172  73F  35  60A/GC/C19212.5153  98  28248+T/IN+DNAHT/HL
58175  79F  33  69A/GC/C2178.8179  95  30391T+HT/HL
59181  78F  33  62A/GC/C3418.5212160  55207IN
60182  80M  29  60A/GC/T1308.5171126  37192T/INDNAHT/HL
61183  80F  29  75A/GC/C1717.5152117  35143TDNAHT/HL
62184  66F  62  51A/GC/T  687.8190160  47107INHL
63185  72M  47  55A/GC/C2698.8243150  37429T/INDNAHT/HL
64186  78M  30  75A/AC/C1277.4170145  43  82THT
65187  57F  26  53A/GC/C2409.5256196  33271++T+HL
66188  77M  30  60A/AC/C1548.3229193  40141+TDNAHT
67191  53F  32  51A/GC/C1146.9216191  54  74+THT
68193  67M  26A/AC/C1557.2211181  58  95++HT/HL
69198  67F  30  32A/GC/T1676.8228193  57122+T+DNAHT/HL
70199  64F  31  55A/GC/C1748.2219180  47148+INDNAHL
71200  80M  29  68A/GC/C1637.5155125  41113TDNAHT

The + symbol refers to smokers, individuals with a positive family history and those individuals not following a specific diet in the smoking status, FH and no diet columns, respectively. S/No., serial number; n, sample number; BMI, body mass index; F, female; M, male, FG, fasting glucose; HbA1c, glycosylated plasma hemoglobin; Chol, total cholesterol; LDL, low-density lipoprotein cholesterol; HDL, high-density lipoprotein cholesterol; TGL, triglycerides; FH, family history; T, tables; IN, insulin; T/IN, tables and insulin; No diet, no dietary compliance; DC, diabetic complications; DNA, diabetic neuropathy and angiopathy; HT, arterial hypertension; HL, hyperlipidemia; HT/HL, arterial hypertension and hyperlipidemia.

The present study was approved by the Bioethics Committee of Aristotle University Medical School (Thessaloniki, Greece; protocol no. 2629; 19 April 2011), the Scientific Council of Thessaloniki Panagia General Hospital (Thessaloniki, Greece; protocol no. A9825; 9 June 2011) and the Research Committee of Aristotle University, Operational Program ‘Education and Lifelong Learning’ of the National Strategic Reference Framework (NSRF) - Research Funding Program: Heracleitus II (project no. 87113).

Anthropometric and biochemical analysis

Anthropometric measurements, including weight and height were obtained according to standardized protocols. The epidemiological profile consisted of age, gender, metabolic family history, smoking status, dietary conditions, and accompanying diseases (arterial hypertension and hyperlipidemia). Participants were classified as having an accompanying disease (arterial hypertension and hyperlipidemia) when the use of antihypertensive or antihyperlipidemic medication was reported respectively, independently of their biochemical lipid profile determination. Information regarding the type of medication (tablets and insulin) and potential diabetic complications were recorded for the diabetic patients. The biochemical analysis included determination of fasting plasma glucose, HbA1c, total serum cholesterol, low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol and serum triglycerides. Peripheral blood samples (2 ml) from all 170 participants for molecular genetic analysis were collected in tubes containing EDTA and centrifuged at 4,500 × g for 20 min at room temperature. Buffy coat leukocytes were then isolated and stored at −20°C.

DNA extraction and genotype analysis

Genomic DNA was extracted from the buffy coat fraction prepared as described above using PureLink Genomic DNA kit (Invitrogen; Thermo Fisher Scientific, Inc., Waltham, MA, USA), according to the manufacturer's instructions. DNA integrity was verified by gel electrophoresis (70 V/cm for 20 min) using 0.8% agarose gel and ethidium bromide staining. DNA purity was determined by the optical density (OD)260/OD280 nm absorption ratio using an Eppendorf Biophotometer. Genomic sequences containing SNPs (rs3749166 and rs5404) were amplified by DNA polymerase chain reaction (PCR) using Platinum Taq DNA polymerase (Invitrogen; Thermo Fisher Scientific, Inc.). The PCR conditions for rs3749166 amplification were as follows: 94°C for 2 min, 35 cycles of 94°C for 45 sec, 60°C for 45 sec and 72°C for 1.5 min followed by 72°C for 10 min. A forward primer (5′-CAGGTCCCAGAGGGTGGAA-3′) and a reverse primer (5′-CAGGTAGGTGGAGGGCACAA-3′) were used for amplifying a 153-bp fragment containing SNP rs3749166. A 344-bp fragment containing SNP rs5404, was amplified by PCR using a forward primer (5′-TCAGGGAGGGGCTTTCATTC-3′) and a reverse primer (5′-CAGTCAGGGAGGGACGAGA-3′) under the following conditions: 94°C for 2 min, 35 cycles of 94°C for 45 sec, 58°C for 45 sec and 72°C for 1.5 min followed by 72°C for 10 min. Primer design was facilitated by Primer-BLAST (https://www.ncbi.nlm.nih.gov/tools/primer-blast/), an online primer designing tool (24). Twelve microliters of each PCR product were separated (70 V/cm for 20 min) on a 2% agarose gel and visualized using ethidium bromide staining. In addition, the PCR products were purified using a PureLink PCR Purification kit (Invitrogen; Thermo Fisher Scientific, Inc.), according to the manufacturer's instructions. The sequence of the purified PCR products was verified by commercial sequence analysis (VBC-Biotech Service GmbH, Vienna, Austria) using the forward primer for rs3749166 and the reverse primer for rs5404). Nucleotide sequence analysis was performed using the Chromas software (version 2.6.2).

Personal Genome Project (PGP) data

To validate the results of the analysis, the allele frequencies of the rs5404 and rs3749166 polymorphisms were evaluated using public genome and exome data, available through the PGP repository (25). Cases matching the patient and non-diabetic control profiles of the present study were selected and 40 additional cases (35 non-diabetic controls and 5 T2D patients) were included, containing allele information of the rs3749166 polymorphism. In addition, 71 cases (48 non-diabetic controls and 23 T2D patients) with allele information of the rs5404 polymorphism were evaluated. Among these, 35 non-diabetic controls and 5 T2D patients contained genetic data for the two polymorphisms. Of the 71 PGP individuals, 32.4% were female and the mean age was 58 years (standard deviation, 10.85).

Statistical analysis

Graphpad online tool (https://www.graphpad.com) was used to perform statistical analyses. Student's t-test was used to compare groups of continuous variables, and the χ2 and Fisher's test were used to compare the proportions of genotypes or alleles. A two-tailed P<0.05 was considered to indicate a statistically significant difference. The difference of the ESE scores between the major SA and minor Sa alleles was calculated as the ΔScore = |SA-Sa|.

Results

Clinical data and statistical analysis of epidemiological parameters

Statistical analysis of the data from T2D patients and non-diabetic control subjects (Table II) demonstrated that among the T2D patients, fasting glucose levels and ΗbΑ1c were significantly higher (P<0.0001); however, there was no correlation with accompanying diseases, such as arterial hypertension or hyperlipidemia. By contrast, LDL and triglyceride levels were significantly higher among T2D patients (P<0.0001; P=0.0052) and HDL levels were significantly lower (P<0.0001). The observed age difference among T2D patients and non-diabetic control subjects was significant (P<0.0001), potentially because the majority of individuals with T2D are diagnosed at an older age (data not shown). All other parameters, such as smoking status, did not differ among T2D patients and non-diabetic control subjects in the present study.
Table II.

Statistical analysis of epidemiological parameters of individuals included in Table I.

ParameterNon-diabetic controls[a] (n=99)T2D patients[b] (n=71)χ2P-value
Male  24  210.6050.4368
Female  75  50
Age (years)60.62±10.1166.94±9.65<0.0001
Body mass index (kg/m2)28.96±5.3432.30±7.980.0013
Age of T2D diagnosis56.37±10.95
T2D duration (years)11.65±8.33
Fasting glucose (mg/dl)98.31±10.45170.32±6.63<0.0001
Glycosylated hemoglobin (%)5.65±0.318.13±1.21<0.0001
Total cholesterol (mg/dl)208.57±38.52188.96±40.460.0016
Low-density lipoprotein cholesterol (mg/dl)147.14±35.00169.78±36.81<0.0001
High-density lipoprotein cholesterol (mg/dl)50.93±13.0642.14±9.46<0.0001
Trigycerides (mg/dl)137.18±54.49179.45±134.090.0052
Family history (positive)    6  2523.565<0.0001
Smoking status  20  101.0650.3021
Not following dietary instructions  13  205.9770.0014
Diet    8
Medication (tablets)  35
Medication (insulin)  10
Medication (tablets and insulin)  13
No medication or dietary intervention    5
Diabetic complications (neuropathy, angiopathy)  30
Diabetic complications and disease duration (>4 years)  240.0014
Diabetic complications and disease duration (≤4 years)    1
Accompanying diseases  72  592.5160.1127
Accompanying diseases (arterial hypertension)  17  192.2780.1313
Accompanying diseases (hyperlipidemia)  24  121.3350.2479
Accompanying diseases (arterial hypertension and hyperlipidemia)  31  281.2040.2725

Of the 48 PGP non-diabetic controls, 27 are male and 21 are female. The mean age of the 48 PGP non-diabetic controls with one or the two polymorphisms is 59.4 years (SD=10.5).

Of the 23 PGP T2D patients, 21 are male and 2 are female. The mean age of the 23 patients with one or the two polymorphisms is 56.7 years (SD=11.2). T2D, type 2 diabetes; PGP, Personal Genome Project; SD, standard deviation.

Genotype frequencies for rs3749166 and rs5404 SNPs in T2D patients and non-diabetic control subjects

The rs3749166 polymorphism was detected by PCR amplification (data not shown) and sequencing of a 153-bp PCR fragment, which included the SNP (Fig. 1A). Similarly, a 344-bp fragment, including the rs5404 SNP was amplified by PCR (data not shown) and analyzed by sequencing (Fig. 1B).
Figure 1.

(A) Nucleotide sequence of the amplified fragments containing the rs3749166 (A>G) calpain 10 polymorphism for samples 34, 40, 187, 200, 46 and 117 (rows 1–6, respectively). (B) Nucleotide sequences of the amplified fragments of rs5404 (C>T) solute carrier family 2 member 2 for the samples 3, 68, 74, 19, 47 and 77 (rows 1–6, respectively). rs3749166 and rs5404 polymorphic sites are indicated using arrows.

The rs3749166 and rs5404 frequencies for the Greek T2D patients and non-diabetic controls are summarized in Table III. Statistical analysis of these data revealed that only the heterozygous rs3749166 genotype (AG, partially epigenetic) was associated with T2D, while the epigenetic genotype (GG) appeared to be protective for the disease (P=0.0262; Table IIIA). A more significant positive correlation was obtained when the PGP data were incorporated into the study (P=0.0039; Table IIIA).
Table III.

Statistical evaluation of (A) rs3749166 and (B) rs5404 SNP frequencies and genotypes among total and Greek T2D patients and non-diabetic controls. (C) Association of observed rs3749166 and rs5404 genotype combinations with disease among total, and Greek T2D patients and non-diabetic control subjects.

A, rs3749166 genotypes

SubjectAA, n (%)AG, n (%)GG, n (%)χ2P-value
Non-diabetic control (total)40 (29.85)71 (52.99)23 (17.16)11.090.0039
T2D patients (total)15 (19.74)57 (75.00)4 (5.26)
Non-diabetic control (Greek)29 (29.29)54 (54.55)16 (16.16)7.280.0262
T2D patients (Greek)15 (21.13)52 (73.24)4 (5.63)

B, rs5404 genotypes

SubjectTT, n (%)CT, n (%)CC, n (%)χ2P-value

Non-diabetic control (total)0 (0)51 (34.69)96 (65.31)4.9670.0258
T2D patients (total)0 (0)20 (21.28)74 (78.72)
Non-diabetic control (Greek)0 (0)39 (39.39)60 (60.61)5.3690.0205
T2D patients (Greek)0 (0)16 (22.54)55 (77.46)

C, rs3749166 and rs5404 combined genotypes

SubjectGG/CC, n (%)GG/CT, n (%)AG/CC, n (%)AG/CT, n (%)AA/CC, n (%)AA/CT, n (%)

Non-diabetic control (total)18 (13.43)5 (3.73)44 (32.84)27 (20.15)23 (17.16)17 (12.69)
T2D patients (total)3 (3.95)1 (1.32)43 (56.58)14 (18.42)12 (15.79)3 (3.95)
P-value0.0310.42110.0008[a]0.76140.79730.0491
Non-diabetic control (Greek)14 (14.14)2 (2.02)29 (29.29)25 (25.25)17 (17.17)12 (12.12)
T2D patients (Greek)3 (4.22)1 (1.40)40 (56.33)12 (16.90)12 (16.90)3 (4.22)
P-value0.0391.0000.004[b]0.1690.9630.100

P-values were evaluated with respect to the disease association of each genotype combination relative to the remaining genotype combinations.

OR=2.67

OR=3.11. T2D, type 2 diabetes; OR, odds ratio.

Analysis of the rs5404 polymorphism from the two sets of data revealed that the homozygous TT genotype was not observed, although the CT frequency was significant (21.28% in T2D patients and 34.69% in non-diabetic control subjects) and that the T genotype may be protective for the disease (Table IIIB; P=0.0205 and P=0.0258). Finally, the association of these splicing-affecting genotype combinations with TD2 was analyzed. The results are presented in Table IIIC and reveal that only the AG/CC genotype is strongly associated with T2D in all cases examined [Greek: P=0.004 and odds ratio (OR), 3.11; PGP: P=0.0008 and OR, 2.67]. Furthermore, the GG/CC and AG/CT genotypes may be protective for the disease. In addition, the T allele was infrequent among individuals who were homozygous for rs3749166 (GG/CT epigenetic genotype).

Association of the rs3749166/rs5404 genotype combinations with glucose metabolism

Another common characteristic among carriers of the AG/CC genotype (disease-associated) is the presence of high HbA1c levels (≥8.5%) (Table IV; P=0.0002, OR, 5.10) although neither of the polymorphisms was found to be independently associated with the T2D criteria (elevated fasting glucose levels and HbA1c).
Table IV.

AG/CC genotype combination among all individuals and T2D patients, relative to the HbA1c levels (≥8.5%). T2D patients are shown in parenthesis.

AG/CCAA/CCGG/CCAG/CTAA/CTGG/CT
HbA1c ≥8.5%19 (19)3 (3)1 (1)3 (3)    0    0
HbA1c <8.5%50 (21)26 (9)16 (2)34 (9)15 (3)3 (1)
Total69 (40)[a]29 (12)17 (3)37 (12)15 (3)3 (1)

P=0.0002, OR=5.10 (P=0.0306, OR=1.30). T2D, type 2 diabetes; HbA1c, glycosylated plasma hemoglobin; OR, odds ratio.

Discussion

Elucidating the impact of epigenetic synonymous SNPs, particularly those involved in the regulation of alternatively spliced exons, is critical for understanding the pathogenesis of complex diseases. The polymorphisms included in the present study were selected on the basis of their epigenetic character and because they are the only synonymous SNPs strongly modifying the splicing-associated exonic enhancers associated with glucose transport (11). CAPN10 and GLUT2 participate in complementary transporter systems, which might be expected to act in a concerted manner. CAPN10 is a T2D-associated protease, which facilitates insulin-stimulated GLUT4 translocation via its activity on the distal secretory pathway (16). Although the association of rs3749166 with T2D has been the subject of various reviews and meta-analytic studies, it is still questioned if it may influence the development of T2D independently or in combination with other CAPN10 gene polymorphisms (17,18). Furthermore, the second SNP investigated in the present study, rs5404 in SLC2A2, has been evaluated in association with T2D (19–22); however, the obtained results were contradictory. In certain studies (20,21) a significant risk was observed among homozygotes, which was similar to the present results, while in another study (19) the minor allele was found to be associated with increased disease risk and with reduced postprandial glucose levels. To the best of our knowledge, the present study is the first to provide a comprehensive concurrent analysis of two SNPs (rs3749166 and rs5404) under investigation, which appear to be critical for the splicing of genes involved in complementary glucose transport systems. Computational analysis has shown that the two polymorphisms interfere with splicing regulation (11). However, according to the data reported by Karambataki et al (11) and summarized in Table V (4), these SNPs modify the binding potential of splicing factors in different ways. rs3749166 (A allele) in CAPN10 strongly modifies the binding site of 3SS_U2 splicing enhancer of alternatively expressed exon 11 and, thus, may lead to the production of more than one splicing product in AG heterozygotes. By contrast, in its heterozygotic state, rs5404 (T allele) in SLC2A2 modifies the response of the ESE elements in this sequence to serine/arginine-rich (SR) proteins, particularly SRp40 and SF2/ASF (IgM-BRCA1) (26). As the two SNPs modify CpG sequences, they also perturb epigenetic regulation for the homozygotic genotypes AA and TT (but not GG and CC, or AG and CT genotypes); however, they do not introduce functionally significant single amino acid modifications (coding synonymous).
Table V.

Evaluation of the ESE modifications introduced by the rs3749166 (A>G) and rs5404 (C>T) SNPs using ESE finder [Cartegni et al (4)].

GeneSNPExon typeSplice site/SR protein bindingMajor allele ESE finder scoreMinor allele ESE finder scoreΔScore[a]
CAPN10rs3749166AlternativeExon 11 splice site (3SS_U2_human)10.350−3.22013.570
SLC2A2rs5404ConstitutiveSRp403.7936.3242.531
SF2/ASF (IgM-BRCA1)2.3373.7691.402
SF2/ASF3.1623.7780.616

ΔScore: Difference of the ESE scores between the major and minor allele. Lower splicing score limit according to ESE finder: 3SS_U2_human=6.632; SRp40=2.670; SF2/ASF(IgM-BRCA1)=1.867; SF2/ASF=1.956. ESE, exonic splicing enhancers; SNP, single nucleotide polymorphism; CAPN10, calpain 10; SLC2A2, solute carrier family 2, member 2.

The present results, summarized in Fig. 2, indicate that the most protective genotype for T2D is the fully epigenetic genotype. In accordance with the above-mentioned analysis, the heterozygous rs3749166 and rs5404 genotypes are also differently associated with T2D. Carriers of the AG/CC genotype (heterozygous for rs3749166) are significantly more frequent among the T2D patients and exhibit particularly high levels of HbA1c, probably indicating resistance to pharmaceutical intervention for T2D. Similar findings regarding the negative effect associated with the synthesis of two different isoforms have been recently reported in association with heterozygous SNPs causing alternative splicing. For example, Tian et al (27) reported a number of disorders associated with alternative exon expression and splicing. In addition, Kurzawski et al (14) reported on the effect of epigenetic SNP rs5030952 in CAPN10, which exhibits a heterozygotic association with post-transplant diabetes mellitus.
Figure 2.

Frequencies of combined observed and expected genotypes resulting from rs3749166 and rs5404 single nucleotide polymorphism in all analyzed cases. The T2D patient frequencies are presented in parenthesis. The genotypes are presented in order of decreasing epigenetic character. Missing combined genotypes are also included. T2D, type 2 diabetes.

By contrast, the presence of the apparently protective rs5404 SNP (CT genotype in SLC2A2) is potentially associated with the modified response of CT heterozygotes to different stimuli (based on the data from ESE score analysis at least one novel ESE is formed, which significantly responds to SRp40 proteins). This appears to be particularly significant for carriers of the rs3749166 CAPN10 AG genotype (the combined AG/CT genotype is not T2D-associated, and its carriers do not exhibit particularly high levels of HbA1c. The advantage of epigenetic regulation provided by the C allele and, thus, the ESE response may be lost among TT homozygotes. This could be a possible explanation for the absence of TT homozygotes regardless of the relatively high total frequency of the T allele (21.28%, non-Mendelian genetics). These findings provide the hypothesis that mutations modifying the response to splicing regulatory mechanisms (epigenetic and ESE) may be associated with strong negative functional changes, and exhibit complex, nonlinear disease associations (28). Provided that functionally significant epigenetic SNPs are frequent (11), this type of genetic variation is expected to have a strong impact on disease and evolution. A major obstacle in investigating complex pathological conditions, such as metabolic syndrome, is the limited understanding of the regulatory factors involved in the expression of interacting components. Recent evidence indicates the key role of alternative RNA expression in developmental changes (29), and the production of coding and non-coding RNA sequences. Another factor is the complex epigenetic modifications, which may also lead to the expression of different RNA isoforms. The current results indicate likely synergies between synonymous splicing-regulatory epigenetic SNPs, which modify the splicing potential of two different glucose transport-associated genes, and reveal that bioinformatic analysis and careful investigation of the SNPs under investigation may become a powerful tool for identifying potentially significant genetic modifications with respect to splicing. In conclusion, the results presented above indicate for the first time, to the best of our knowledge, the correlation and disease association of two synonymous epigenetic SNPs, which participate in the regulation of the glucose transport system and introduce exclusively splicing-associated modifications. Taken together, these results reveal that T2D is subject to deregulation by complex splicing mechanisms, which may exhibit heterozygous disease association or protection, depending on the splicing-affecting genetic variation. A detailed bioinformatic analysis of the changes introduced by SNPs would facilitate the understanding of the impact of functional changes introduced by genetic variation.
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Journal:  Biochim Biophys Acta Mol Basis Dis       Date:  2016-09-14       Impact factor: 5.187

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Journal:  Diabetes       Date:  2007-01       Impact factor: 9.461

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Authors:  Pedro R Romero; Saima Zaidi; Ya Yin Fang; Vladimir N Uversky; Predrag Radivojac; Christopher J Oldfield; Marc S Cortese; Megan Sickmeier; Tanguy LeGall; Zoran Obradovic; A Keith Dunker
Journal:  Proc Natl Acad Sci U S A       Date:  2006-05-22       Impact factor: 11.205

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Authors:  Yiqing Song; Nai-chieh You; Yi-Hsiang Hsu; James Sul; Lin Wang; Lesley Tinker; Charles B Eaton; Simin Liu
Journal:  Hum Mol Genet       Date:  2007-09-12       Impact factor: 6.150

7.  Association of calpain-10 gene polymorphism and posttransplant diabetes mellitus in kidney transplant patients medicated with tacrolimus.

Authors:  Mateusz Kurzawski; Krzysztof Dziewanowski; Karolina Kedzierska; Wanda Gornik; Anna Banas; Marek Drozdzik
Journal:  Pharmacogenomics J       Date:  2009-09-15       Impact factor: 3.550

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Authors:  Andigoni Malousi; Sofia Kouidou
Journal:  Mol Genet Genomics       Date:  2012-06-28       Impact factor: 3.291

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Authors:  Jian Ye; George Coulouris; Irena Zaretskaya; Ioana Cutcutache; Steve Rozen; Thomas L Madden
Journal:  BMC Bioinformatics       Date:  2012-06-18       Impact factor: 3.169

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Authors:  Inês Barroso; Jian'an Luan; Rita P S Middelberg; Anne-Helen Harding; Paul W Franks; Rupert W Jakes; D Clayton; Alan J Schafer; Stephen O'Rahilly; Nicholas J Wareham
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