Genes,Genetics,and Environment in Type 2 Diabetes: Implication in Personalized Medicine

Abstract

Type 2 diabetes (T2D) is a multifactorial anomaly involving 57 genes located on 16 different chromosomes and 136 single nucleotide polymorphisms (SNPs). Ten genes are located on chromosome 1, followed by seven genes on chromosome 11 and six genes on chromosomes 3. Remaining chromosomes harbor two to five genes. Significantly, chromosomes 13, 14, 16, 18, 21, 22, X, and Y do not have any associated diabetogenic gene. Genetic components have their own pathways encompassing insulin secretion, resistance, signaling, and β-cell dysfunction. Environmental factors include epigenetic changes, nutrition, intrauterine surroundings, and obesity. In addition, ethnicity plays a role in conferring susceptibility to T2D. This scenario poses a challenge toward the development of biomarker for quick disease diagnosis or for generating a consensus to delineate different categories of T2D patients. We believe, before prescribing a generic drug, detailed genotypic information with the background of ethnicity and environmental factors may be taken into consideration. This nonconventional approach is envisaged to be more robust in the context of personalized medicine and perhaps would cause lot less burden on the patient ensuring better management of T2D.

Introduction

Type 2 diabetes (T2D) is a complex multifactorial disorder involving genetics and environmental factors (American Diabetes Association, 2011). T2D include genes from various pathways such as insulin secretion, its resistance, signaling, and pancreatic β-cell (PBC) dysfunction. Environmental factors include epigenetic changes, adverse nutrition, intrauterine environment, and obesity. In addition, ethnicity also has a role in conferring susceptibility to T2D. Earlier studies have genotyped the common variants associated with T2D in different populations of the world. However, the efforts to understand the underlying pathways have remained limited. In this study, we have listed the candidate genes involved in the main pathways and have discussed their involvement in the light of environmental factors having implication in personalized medicine. Literature on T2D showed involvement of about 57 genes located on 16 different chromosomes having 136 single nucleotide polymorphisms (SNPs). This includes 63 SNPs from 18 genes related to insulin secretion pathway, 37 SNPs from 21 genes related to insulin signaling and PBC dysfunction pathway, and finally 36 SNPs from 18 genes related to insulin resistance (IR) pathway.

Insulin Secretory Pathway

Glucose-stimulated insulin secretion (GSIS) starts as glucose molecules enter into PBC by GLUT2. Glucose gets phosphorylated by glucokinase (GCK) enzyme leading to ATP generation through glycolysis pathway. This step is termed as the rate-limiting step of GSIS. For complete oxidation of glucose, pyruvate undergoes oxidative phosphorylation through electron transport chain (ETC) in mitochondria. It begins as electrons within the carbon bonds are transferred to dinucleotide electron carriers, NADH, and FADH₂. They donate electrons to ETC, a multiprotein unit grouped into four complexes (I–IV). Complexes I, III, and IV are reduction and oxidation-driven proton pumps. Ultimately, electrons cause reduction of oxygen to water. ETC utilizes electrons to obtrude the protons out of the matrix. This creates an electrochemical potential gradient across the mitochondrial inner membrane. Energy stored in this gradient is utilized by ATP synthase to generate ATP from ADP (Lowell and Shulman, 2005) causing an increase in ATP/ADP ratio and thus closure of ATP-sensitive potassium (K⁺) channel. This closure depolarizes the PBC membrane, which opens the voltage-dependent Ca⁺⁺ channel. Opening of calcium (Ca) channel initiates incoming of Ca ions and stimulates secretion of stored insulin granules from PBCs through exocytosis (Guyton and Hall, 2010). The detailed pathway is shown as a diagrammatic illustration highlighting the potent candidate genes involved in insulin secretion (Fig. 1).

FIG. 1.

Diagrammatic illustration highlighting insulin secretion pathways encompassing some potent genes and their involvement in type 2 diabetes (T2D) pathophysiology. Glucose molecules enter pancreatic β-cell (PBC) by GLUT2 and undergo glycolysis. Pyruvate (substrate of glycolysis) enters electron transport chain (ETC) in mitochondria for complete oxidation. This leads to increase in the ATP/ADP ratio, which is sensed by K_(ATP) channel, and leads to membrane depolarization causing Ca channel to open. Influx of Ca ions initiates secretion of insulin from PBC through exocytosis. In addition to this, the name of the genes, which are involved at various steps in the pathways, have also been mentioned along side. Ca, calcium. Color images available online at www.liebertpub.com/dna

Candidate Genes and Variants Associated with Insulin Secretion and T2D

Insulin secretion is an important pathway in pathogenesis of T2D. Literature showed 63 SNPs in 18 genes from this pathway in T2D (Table 1).

Table 1.

List of Candidate Genes and Variants Associated with Insulin Secretion and Type 2 Diabetes

Gene name	Full gene name	Chromosome number	SNP common name	db SNP	Position	References
SLC2A2	Solute carrier family 2 (facilitated glucose transporter), member 2	3		rs5406	Intron	Kilpelainen et al. (2007)
				rs5404	Synonymous	Kilpelainen et al. (2007)
				rs5400	Missense	Kilpelainen et al. (2007)
				rs5398	Synonymous	Kilpelainen et al. (2007)
GCK	Glucokinase	7		rs1799884		Wang et al. (2013)
				rs3757840		Weedon et al. (2006)
GCKR	Glucokinase regulator	2		rs780094	Intron	Wang et al. (2013)
SUR1	ATP-binding cassette, sub-family C (CFTR/MRP), member 8	11	IV38 + 54	rs4148646	Intron	Haghverdizadeh et al. (2014)
			IV18-36	rs4148628	Intron	Haghverdizadeh et al. (2014)
			IVS11-74	rs2074308	Intron	Haghverdizadeh et al. (2014)
			K649	rs1799858	Exon	Haghverdizadeh et al. (2014)
				rs2237984	Intron	Haghverdizadeh et al. (2014)
				rs2188966	Intron	Haghverdizadeh et al. (2014)
				rs59852838	Exon	Haghverdizadeh et al. (2014)
				rs358953	5′UTR	Haghverdizadeh et al. (2014)
				rs3758947	Intron	Haghverdizadeh et al. (2014)
				rs1799859	Exon	Haghverdizadeh et al. (2014)
			S1369A	rs757110	Exon	Haghverdizadeh et al. (2014)
			IVS19 + 123	rs8192692	Intron	Haghverdizadeh et al. (2014)
			IMS-JST032704	rs2283257	Intron	Haghverdizadeh et al. (2014)
			Syn T759T	rs1801261	Exon	Haghverdizadeh et al. (2014)
			Intron 24 T/C	rs1799854	Intron	Haghverdizadeh et al. (2014)
			Syn R1273R	rs4148643	Intron	Haghverdizadeh et al. (2014)
Kir6.2	Potassium inwardly rectifying channel, subfamily J, member 11	11	E23K	rs5219	Intron	Qin et al. (2013)
			A190	rs5218	Synonymous codon	Qin et al. (2013)
			3p+215	rs5210	3′UTR	Qin et al. (2013)
				rs5215	Missense	Qin et al. (2013)
CACNA1E	Calcium channel, voltage dependent, R type, alpha 1E subunit	1	−1039G/T	rs10797728	Intron	Trombetta et al. (2012)
			+8130G/A	rs3753737	Intron	Trombetta et al. (2012)
				rs175338	Intron	Trombetta et al. (2012)
				rs2184945	Intron	Trombetta et al. (2012)
				rs3905011	Intron	Trombetta et al. (2012)
				rs4652679	Intron	Trombetta et al. (2012)
CAPN10	Calpain 10	2	SNP 19	rs3842570	Intron	Sharma et al. (2013)
			SNP 43 Intron 3	rs3792267	Intron	Sharma et al. (2013)
			SNP 63	rs5030952		Sharma et al. (2013)
			SNP 44 C/T or T504A	rs2975760	Intron	Sharma et al. (2013)
HHEX	Hematopoietically expressed homeobox	10		rs7923837		Cai et al. (2011)
				rs1111875		Cai et al. (2011)
				rs5015480		Klimentidis et al. (2014)
IDE	Insulin-degrading enzyme	19		rs2209772		Zee et al. (2008)
				rs1887922	Intron	Karamohamed et al. (2003)
				rs2149632	Intron	Rudovich et al. (2009)
PPARGC1A	Peroxisome proliferative activated receptor, gamma, coactivator 1	4	G482S	rs8192678	Exon	Franks et al. (2014)
			T528T	rs3755863	Exon	Franks et al. (2014)
SLC30A8	Solute carrier family 30, class A, member 2	8	T325A	rs13266634	Missense	Rutter and Chimienti (2014)
			R325W	rs7480010	Intron	Kifagi et al. (2011)
WFS1	Wolfram syndrome 1	4		rs6446482	Intron	Mita et al. (2008)
				rs1251142	Intron	Mita et al. (2008)
			R456H	rs1801208	Missense	Mita et al. (2008)
			H611R	rs734312	Missense	Mita et al. (2008)
UCP2	Uncoupling protein 2	11	Ala55Val	rs660339	Exon	Crispim et al. (2010)
				rs659366	Promoter	Crispim et al. (2010)
PTGS2	Prostaglandin-synthase 2	1		rs2066826	Intron	Konheim and Wolford (2003)
				rs20417	Promoter	Konheim and Wolford (2003)
			Arg298His	rs13283456	Promoter	Nitz et al. (2007)
CDKN2A/B	Cyclin-dependent kinase inhibitor-2A/B	9		rs10811661		Peng et al. (2013)
				rs564398	Intron	Peng et al. (2013)
CDKAL1	Cyclin-dependent kinase-5 regulatory subunit-associated protein-like-1	6		rs7754840	Intron	Peng et al. (2013)
				rs7756992	Intron	Peng et al. (2013)
				rs10946398	Intron	Peng et al. (2013)
SLC2A1	Solute carrier family 2 (facilitated glucose transporter, member 1)	1		rs841853	Intron	Du et al. (2013)
MTNR1B	Melatonin receptor 1B	11		rs10830963	Intron	Ren et al. (2014)

SNP, single nucleotide polymorphism.

Sixteen SNPs are associated with SUR1 and four with Kir6.2. The ATP-sensitive potassium channel is the key component of GSIS. K_(ATP) channels are the heterooctameric complexes consisting of pore and ATP-sensitive regulatory subunit. Pore is formed by Kir6.1/Kir6.2 genes and regulatory subunit is formed by SUR1/SUR2A/SUR2B genes. K_(ATP) channel couples metabolic changes to membrane electric signals leading to GSIS. Given the vital role of K_(ATP) channel in GSIS, polymorphisms in these genes are found associated with causation of T2D (Qin et al., 2013; Haghverdizadeh et al., 2014). However, mitochondrial inner membrane anion carrier protein acts as uncoupling proteins (UCP), which regulate ATP production by oxidative phosphorylation. UCP2 mediates proton leak across mitochondrial membrane and hence decreased insulin secretion. −866 G>A polymorphism of UCP2 is the most extensively studied variant of this gene. Positive association of this gene has been reported in Bavarians, Austro-Germans, Caucasians, Japanese, Hispanics, Africans, and Asian Americans. Besides, another variant Ala55Val of UCP2 is also associated with T2D as a haplotype (Crispim et al., 2010).

Another set of genes significantly associated with T2D were the pancreatic membrane transporters (SLC2A2-rs5406, rs5404, rs5400, rs5398, SLC2A1-rs841853, and SLC30A8-rs13266634). SLC2A2 encodes GLUT2 and SLC2A1 encodes GLUT1, which are the facilitative glucose transporters of PBC. Polymorphisms in SLC2A2 play a role in the conversion of impaired glucose intolerance (IGT) into T2D in Finnish, Japanese, and Caucasian populations (Kilpelainen et al., 2007). However, SLC2A1 polymorphism rs841853 has been found to be associated only in Asians (Du et al., 2013). SLC30A8 encodes pancreas-restricted zinc transporter ZnT8. Zinc is required for insulin biosynthesis and maturation of insulin secretory granules (Wijesekara et al., 2009). SLC30A8-rs13266634 is a nonsynonymous variant encoding tryptophan to arginine change at position 325 of the carboxyl terminal domain. This SNP associates reduced zinc transport activity, reduced zinc levels in β-cells, and diminished insulin secretion (Rutter and Chimienti, 2014). Another variant of this gene rs7480010 was also associated with T2D in Tunisians comprising 734 subjects (Kifagi et al., 2011).

Glucose metabolism starts with glycolysis involving GCK enzyme. The activity of GCK is inhibited by GCKR. GCK is selectively expressed in liver and PBC. Given its function in glycolysis, the variants in these two genes (GCK-rs199884 and GCKR-rs3757840) are associated with fasting plasma glucose (FPG) and hence T2D in Caucasians, Whites, Chinese, and South Asians (Wang et al., 2013). Another variant of GCK-rs3757840 is also associated with FPG and birth weight (Weedon et al., 2006).

Similarly, CDK2A/B and CDKAL1 are shown to have regulatory effects on glucose metabolism and insulin secretion. Two variants in CDK2A/B gene rs10811661 and rs564398 and three variants in CDKAL1 gene—rs7754840, rs7756992, and rs10946398 are widely associated with T2D in different populations. Recent meta-analysis across populations confirmed the associations of rs10811661, rs7756992, and rs10946398 variants with T2D (Peng et al., 2013).

For secretion of insulin from PBCs, calcium influx is critical. CACNA1E is member of voltage-gated Ca²⁺ channel family. It mediates entry of Ca²⁺ ions into the cells upon membrane depolarization initiating insulin release. The variants in this gene have been associated with insulin secretion and sensitivity in Pima Indians and Swedish population. Revalidation in Italians confirmed that CACNA1E tag SNPs (rs10797728, rs3753737, rs175338, rs2184945, rs3905011, and rs4652679) were associated with different aspects of PBC functions leading to T2D (Trombetta et al., 2012).

CACNA1E gene is located on chromosome 1 similar to PTGS2. PTGS2 generates prostaglandins, which is a negative regulator of GSIS and also causes insulin insensitivity. It lies in the region (1q25.2) closely associated with early onset of T2D. Similarly, PTGS2 (rs20417 and rs2066826) polymorphisms were found to be associated with T2D in Pima Indians comprising 1000 subjects. SNP rs20417 was found to decrease the activity of promoter emphasizing its functional relevance (Konheim and Wolford, 2003). Variant rs13283456 has a protective role against T2D in two German cohorts with odds ratio of 0.63 and p-value 0.04 (Nitz et al., 2007).

CAPN10 gene on chromosome 2 encodes Calpain 10 enzyme, which is a cysteine protease. SNPs-43 (rs3792267), 63 (rs5030952), and 19 (rs3842570) are individually as well as in combination with haplotype are associated with different phenotypes of T2D. This includes insulin secretion, IR, and IGT. Association of these SNP has been replicated in several populations belonging to different ethnicities (Sharma et al., 2013).

PGC-1α and WFS1 are the two genes present on chromosome 4. PGC-1α integrates with metabolic pathways, which include increased hepatic gluconeogenesis and β-oxidation and mitochondrial biogenesis. Further, insulin-independent uptake of glucose and metabolism, reduced insulin secretion providing more glucose for brain and kidney during starvation has been well documented. Positive association of Gly482Ser has been documented in Danish and Slovene Caucasians. Positive association of both Thr394Thr and Gly482Ser variants has been seen in Japanese population. Recently Gly482Ser has been reported to be associated with accumulation of subcutaneous adiposity and Thr394Thr is reportedly associated with modified effects of metformin on triacylglycerol level in diabetic patients (Franks et al., 2014).

Wolfram syndrome is caused by mutations in WFS1 gene. It is a rare autosomal recessive disorder characterized by juvenile diabetes mellitus and diabetes insipidus. WFS1 encodes for a gene product, which is involved in β-cell loss, increased apoptosis and diminished insulin secretion. The variants (WFS1-rs6446482, rs12511742, rs1801208, and rs734312) were found to be associated with T2D through genome-wide association studies (GWAS) carried out on 9533 cases and 11,389 controls. Same variants were found to be associated in the Japanese population as well (Mita et al., 2008).

HHEX gene located on chromosome 10 encodes for a transcription factor involved in WNT signaling pathway. It is expressed during early stages and required for the development of ventral pancreas and liver. SNPs rs7923837 and rs1111875 are associated with impaired insulin secretion and T2D in several populations. However, a large meta-analysis of 88,495 samples showed significant association with odds ratio of 1.19 and 1.23, respectively, in Caucasians and Asians only (Cai et al., 2011). Another variant in HHEX gene, rs5015480 showed association with lower prevalence of T2D in native population of Alaska (n = 1144) with p-value of 0.00046 (Klimentidis et al., 2014).

IDE located on chromosome 11 can degrade the number of peptides, including insulin-like growth factor (IGF)-I, IGF-II, transforming growth factor, and proteins damaged oxidatively. IDE is implicated with fasting glucose plasma (FGP) levels and glycated hemoglobin A1c (HBA1C). Positive association of these IDE (rs2209772 and rs1887922) variants in men has been reported in Framingham Heart study (Karamohamed et al., 2003). Another variant, rs2149632, was also associated with decreased insulin secretion in German cohort comprising 3049 subjects (Rudovich et al., 2009).

Another gene present on chromosome 11 is MTNR1B, which encodes for 7-transmembrane melatonin receptor secreted by pineal gland. MTNR1B (rs10830963) variant was found to be associated with FGP, T2D, and insulin secretion uncovered by recent GWAS in Mexican Americans (Ren et al., 2014). This variant was also found to be associated with South Indians (Mohammed et al., 2015), Caucasians, and Hispanics (Zheng et al., 2015).

Insulin Signaling Pathway, Candidate Genes, and Polymorphisms Implicated with T2D

Insulin signaling involves major pathways in T2D pathophysiology and its signaling and resistance goes hand in hand to cause overt T2D. Insulin signaling cascade begins with IRS1/PI3K/AKT genes. Glucose uptake activates IRS-2/PI3K complex, which targets Akt and protein kinase C zeta to begin downstream signaling (Rudovich et al., 2009). Mutations and polymorphisms involved with insulin signaling include 21 genes and 37 SNPs (Table 2). Few genes may not be playing a direct role in insulin signaling, instead participating indirectly. However, such details are not available.

Table 2.

List of Genes and Their Variants Associated with Insulin Signaling and Miscellaneous Pathways

Gene name	Full gene name	Chromosome number	SNP common name	db SNP	Position	References
STK11	Serine/threonine kinase 11	19		rs741765	Intron	Keshavarz et al. (2008)
CRTC2	CREB-regulated transcription factor coactivator 2	3	6909 C>T			Keshavarz et al. (2008)
AMPK	Protein kinase AMP-activated, alpha catalytic subunit	5		rs1418442	Intron	Keshavarz et al. (2008)
WNTB5	Wolfram syndrome 5	4	IVS3C>G	rs2270031	Intron	Salpea et al. (2009)
PRKCZ	Protein kinase C, zeta	1		rs436045	Intron	Li et al. (2003)
RPTP,S	Receptor protein tyrosine phosphatase sigma	19		rs1978237	Intron	Langberg et al. (2007)
				rs1143699	Exon	Langberg et al. (2007)
				rs4807015	Intron	Langberg et al. (2007)
GNB3	G protein beta3 subunit	12	C825T	rs5443	Exon	Daimon et al. (2008)
				rs5446	3′UTR	Daimon et al. (2008)
				rs2301339	Intron	Daimon et al. (2008)
SREBF1	Sterol regulatory element binding transcription factor 1			rs11868035	Exon	Liu et al. (2012)
				rs2297508	Exon	Liu et al. (2012)
		17		rs1889018	5′UTR	Grarup et al. (2008)
				rs6502618	5′UTR	Grarup et al. (2008)
				rs2236513	5′UTR	Harding et al. (2006)
IL6	Interlukin 6	7	−174G>C	rs1800797	Promoter	Saxena et al. (2014)
				rs1800795	Promoter	Saxena et al. (2014)
BCAT1	Branched-chain amino acid transaminase-1, cytosolic	12		rs2242400	Intron	Rampersaud et al. (2007)
ENDOGL1	Endonuclease G-like 1 gene	3	A375G	rs2051211	Intron	Moritani et al. (2007)
EXT2	Exostosin glycosyltransferase 2			rs1113132	Intron	Liu et al. (2013)
		11		rs3740878	Intron	Liu et al. (2013)
				rs11037909	Intron	Liu et al. (2013)
GRB10	Growth factor receptor-bound protein 10	11		rs2237457	Intron	Rampersaud et al. (2007)
PCK1	Phosphoenolpyruvate carboxykinase, 1	2	−232C>G	rs2071023	Promoter	Rees et al. (2009)
FXN	Friedreich's ataxia	9		rs2498429		Holmkvist et al. (2005)
IL6R	Interlukin 6 receptor	1	Asp358Ala	rs8192284	Exon	Qi et al. (2007)
CRP	C-reactive protein gene	1		rs3093059	Promoter	Zee et al. (2008)
				rs2794521	Promoter	Zee et al. (2008)
CASQ1	Calsequestrin-1	1		rs2275703	Intron	Fu et al. (2004)
				rs617698	Intron	Fu et al. (2004)
ATF6	Activating transcription factor 6		M67V	rs1058405	Exon	Chu et al. (2007)
		1		rs11579627	3′UTR	Chu et al. (2007)
IGF2BP2	Insulin-like growth factor 2 m-RNA-binding protein 2			rs4402960	Intron	Omori et al. (2008)
		3		rs1470579	Intron	Omori et al. (2008)
IRS1	Insulin receptor substrate 1			rs1801278	Missense	Alharbi et al. (2014)
		2		rs2943641		Sun et al. (2014)
TCF7L2	Transcription factor 7-like 2	10		rs7903146	Intron	Pradas-Juni et al. (2014)
ENPP1	Ectonucleotide pyrophosphatase 1	6		rs1044498		de Lorenzo et al. (2013)

The STK11-AMPK-CRTC2 complex forms a signaling pathway which controls glucose homeostasis in the liver. This complex is a target for antidiabetes drugs. SNPs in these genes (STK11-rs741765, AMPK-rs1418442, and CRTC2-6909C>T) were found to be associated with moderate risk of developing T2D in the Japanese population comprising 1787 subjects. AMPK (rs1418442) is also associated with serum cholesterol levels in Caucasian females (Keshavarz et al., 2008).

Maximum number of candidate genes associated with insulin signaling is present on chromosome 1, which includes PRKCZ, IL6, CRP, CASQ1, and ATF6. PRKCZ is a member of PKC serine/threonine kinase family and plays a role in cell differentiation, proliferation, and secretion. This gene mapped to 1p36.33-1p36.23 region of chromosome 1 and is reported to be associated with T2D in Han Chinese showing association with rs436045 variant (Li et al., 2003). Another gene present on chromosome 1 is CASQ1 that codes for Calsequestrin protein. It is involved in intracellular storage and release of calcium. Two polymorphisms (rs2275703 and rs617698) of this gene were significantly associated with T2D in Amish population comprising 651 subjects (Fu et al., 2004). In addition, ATF6 is also located in the same region associated with T2D. ATF6 gene plays a role in endoplasmic reticulum stress response. Two variants of this gene have been shown to be associated with T2D in Utah Caucasians comprising 544 subjects (Chu et al., 2007). IL6R, which is the receptor for IL6 gene, is also located on chromosome 1. A polymorphism (IL6R-rs8192284) was associated with T2D in women from United States in a study comprising of 1730 subjects (Qi et al., 2007). CRP gene present on chromosome 1, encodes for a protein that belongs to pentaxim family and has a major role in host defense mechanisms. The level of protein increases in response to injury, infection, or inflammation. Two variants (rs3093059 and rs2794521) of this gene have been originally associated with T2D in European populations (Carlson et al., 2005). However, only rs3093059 (p = 0.03, OR: 7.01) could be well replicated in different populations, including Caucasians (Zee et al., 2008).

Two genes PCK1 and IRS1 present on chromosome 2 have been implicated with insulin signaling. PCK1 encodes for cytosolic, phosphoenolpyruvate carboxykinase, which is a known candidate gene for T2D. Variant rs2071023 was found to be associated (OR: 1.21, p = 0.019) with T2D in a South Asian population residing in United Kingdom. The study consisted on 1374 subjects from Mirpur, Pakistan (Rees et al., 2009). However, IRS1 plays a crucial role in insulin signaling pathway. The protein encoded by IRS1 is phosphorylated by insulin receptor tyrosine kinase leading to downstream signaling. Glysine972Arginine (rs18011278) is associated (p = 0.04, OR: 1.7) with T2D in populations worldwide (Alharbi et al., 2014). Another variant of this gene, rs2943641 was found implicated with IR, hyperinsulinemia, and reduced basal IRS-1 protein level in Europeans (Sun et al., 2014).

Two genes present on chromosome 3 are ENDOGL1 and IGF2BP2. ENDOGL1 encodes for 5′-3′ endonuclease enzyme. This gene plays a role in apoptosis. However, the role in T2D is unclear. A polymorphism of this gene rs2051211 was found to be significantly associated (p = 0.000046, OR: 1.33) with T2D in Japanese population (Moritani et al., 2007). While, IGF2BP2 is an mRNA-binding protein, which regulates IGF2 by binding to its 5′UTR. It also plays a role in growth and insulin signaling pathways influencing insulin secretion. Two variants (rs4402960 and rs1470579) in IGF2BP2 gene have been associated with T2D in different populations of the world, including Asian and Caucasian. Carriers of these variants were found to have decreased first phase of insulin secretion. Recently these variants were also associated (OR: 1.87 and OR: 2) with Pioglitazone drug response in T2D patients acting as a potential biomarker (Omori et al., 2008).

The only gene present on chromosome 4 is WNTB5. It belongs to the Wnt signaling pathway and regulates adiposeness and insulin secretion. WNTB5 gene variant IVS3C>G was found to provide risk of T2D in absence of obesity in Japanese and Caucasian populations (Salpea et al., 2009).

Chromosome 6 harbors ENPP1 gene, which is a transmembrane glycoprotein. It interacts with insulin receptor inhibiting downstream signaling. rs1044498 is a gain of function mutation, which causes inhibited autophosphorylation of insulin receptor and hence decreased tissue-specific insulin action affecting glucose uptake and glycogen synthesis (de Lorenzo et al., 2013).

Chromosome 7 harbors IL6 gene, which encodes for a proinflammatory hormone. As insulin has an anti-inflammatory role, it is believed that IL6 interferes with insulin and hinders the downstream signaling leading to T2D. Two IL6 polymorphisms rs1800797 and rs1800795 were associated with T2D in populations from Boston, American, and Spanish Caucasians. However, in North Indian population only rs1800795 showed association with T2D (Saxena et al., 2014).

A gene FXN present on chromosome 9 causes Friedreich's ataxia (FRDA), which is a neurodegenerative disease involving GAA repeat. More than 20% of the patients develop T2D in their later parts of life. A SNP in X25 gene (rs2498429) was found to be associated with causation of T2D in FRDA patients (220 trios) with p-value of 0.02. However, the exact pathway leading to T2D in the context of this gene is unknown (Holmkvist et al., 2005).

TCF7L2 gene is present on chromosome 10. TCF7L2 harbors the most replicated and implicated genetic variant (rs7903146) associated with T2D till date. Studies carried out on mice models and cell lines have suggested that TC7L2 mRNA levels are upregulated and protein levels are downregulated in PBC. For this, splice variants are mainly responsible for its regulation. However, the exact pathway is still unknown (Pradas-Juni et al., 2014).

Chromosome 11 harbors two important insulin-signaling genes, EXT2 and GRB10. EXT2 encodes exostocin 2, which is required during early pancreatic development and insulin synthesis. Three variants (rs3740878: OR: 1.07, p = 0.038; rs11037909: OR: 1.05, p = 0.008; rs1113132: OR: 1.04, p = 0.005) of this gene showed marginal association with Han Chinese population consisting of 2533 cases and 2643 controls (Liu et al., 2013). GRB10 encodes for growth factor protein 10, which binds to activated insulin receptor and hence negatively regulate insulin signaling and glucose uptake. Highly significant association (p = 1.07 × 10⁻⁵) of rs2237457 has been reported with T2D (Rampersaud et al., 2007).

Chromosome 12 has GNB3 and BCAT1 genes implicated in insulin signaling. G proteins relay information from one cell to another through G protein–coupled receptors. GNB3 gene encodes for G protein β3 subunit. Given its pivotal role in ion channels and signaling, the polymorphisms in this gene were analyzed in Japanese population comprising 2956 subjects. rs5443 was associated with T2D along with flanking SNPs rs5446 and rs2301339. BCAT1 encodes for cytosolic branched chain amino acid transaminase, which is essential for cell growth. BCAT1 variant rs2242400 was associated with decreased risk of T2D in Amish (OR: 0.71, p = 0.004), Pima Indians (OR: 0.66, p = 0.019), and Mexican Americans (OR: 0.78, p = 0.034) (Daimon et al., 2008).

SREBF1 gene present on chromosome 17 is a transcription factor regulating lipid and glucose metabolism by downregulating genes like PGC-1α. Based on three different studies, five variants of this gene have been reported to be associated with T2D (Harding et al., 2006; Grarup et al., 2008; Liu et al., 2012). rs2297508 and rs11868035 are associated in Han and Dongxiang populations, whereas rs1889018 is associated with Danish Caucasians. Variants rs2236513 and rs6502618 are associated with population from United Kingdom.

RPTP,S gene present on chromosome 19 encodes for a phosphatase enzyme associated with the maintenance of glucose homeostasis and insulin signaling. Polymorphisms (rs1143699, rs4807015, and rs1978237) of this gene were also found to be associated with T2D in Swedish Caucasian population in a study conducted on 497 participants (Langberg et al., 2007).

Genes Involved in IR Pathway

IR marks the beginning of pathophysiology of T2D. At the molecular level, IR correlates with impaired insulin signaling. Due to the progressive demand of insulin, PBC are stressed to secrete more insulin to compensate for the IR. This phenomenon is known as compensatory mechanism. This leads to a condition called as hyperinsulinemia. Burden on PBC initiates insulin secretory defects and pancreas are no longer able to compensate for the IR. Extensive stress, calcium influx, and effects of cytokines graduate the process of PBC apoptosis leading to overt T2D form of prediabetes. Genes like PPAR-γ play a crucial role in IR by its effects on adiponectin, obesity, and free fatty acids (Porter and Barrett, 2005). Along with PPAR-γ, defects in insulin receptor also lead to IR. Genes implicated in IR and T2D are given in the Table 3.

Table 3.

List of the Candidate Genes and Their Variants Associated with Insulin Resistance Causing Type 2 Diabetes

Gene symbol	Full name of the genes	Chromosomal location	SNP common name	db SNP	Position	References
LPIN2	Lipin 2	17		rs3745012	3′UTR	Aulchenko et al. (2007)
PPARG	Peroxisome proliferator-activated receptor gamma	3	Pro12Ala	rs1801282	Intron	Li et al. (2014)
HNF4A	Hepatocyte nuclear factor 4, alpha			rs4810424	Promoter	Saif-Ali et al. (2011)
		20		rs1884613	Promoter	Saif-Ali et al. (2011)
				rs1884614	Promoter	Saif-Ali et al. (2011)
PTPN1	Protein tyrosine phosphatase, nonreceptor type 1			rs941798	5′UTR	Cheyssac et al. (2006)
		20		rs2426159	Intron	Cheyssac et al. (2006)
				rs914458	Intron	Cheyssac et al. (2006)
PRKAA2	Protein kinase, AMP-activated, alpha 2, catalytic subunit	1		rs2051040	Intron	Horikoshi et al. (2006)
UCP3	Uncoupling protein 3			rs1800849	5′UTR	Salopuro et al. (2009)
		11		rs3781907	5′UTR	Salopuro et al. (2009)
SOCS3	Suppressor of cytokine signaling 3			rs12953258	5′UTR	Meng et al. (2014)
		17		rs4969168	3′UTR	Meng et al. (2014)
				rs9914220	Intron	Meng et al. (2014)
CAV2	Calveolin 2	7		rs2270188	Intron	Fisher et al. (2011)
UCP1	Uncoupling protein 1	8	−112A>C	rs10011540	Promoter	Salopuro et al. (2009)
ADRB2	Adrenoceptor beta 2, surface			rs1042711	5′UTR	Tellechea et al. (2013)
				rs1801704	5′UTR	Tellechea et al. (2013)
		5		rs1042713	5′UTR	Tellechea et al. (2013)
				rs1042714	5′UTR	Tellechea et al. (2013)
HSD11B1	Hydroxysteroid (11-beta) dehydrogenase 1	1		rs846910	Intron	Gandhi et al. (2013)
				rs12086634	Intron	Gandhi et al. (2013)
ADIPOQ	Adiponectin	3	−11391G/A	rs17300539	Promoter	Foucan et al. (2014)
			45T>G	rs2241766	Exon	Foucan et al. (2014)
			276G>T	rs1501299	Intron	Foucan et al. (2014)
			G(−10069)A	rs182052	Intron	Foucan et al. (2014)
ESR1	Estrogen recceptor-alpha gene	6		rs2431260	Intron	Gallagher et al. (2007)
				rs1709183	Intron	Gallagher et al. (2007)
NRF1	Nuclear respiratory factor 1		−24833A>G	rs6969098	Intron	Liu et al. (2008)
		7	G141T	rs1882094	5′UTR	Liu et al. (2008)
NOS3	Nitric oxide synthase	7	G894T	rs1799983	Missense	Jia et al. (2013)
LTA	Lymphotoxin-alpha	6		rs2229094	Missense	Mahajan et al. (2010)
RACE	Receptor for advanced glycation end product	5		rs3134945	Intron	Gaens et al. (2008)
TNF	Tumor necrosis factor		−857C>T	rs1799724	Promoter	Xu et al. (2013)
		6	−803 A>C	rs1800630	Promoter	Xu et al. (2013)
			−1031T>C	rs1799964	Promoter	Xu et al. (2013)

The candidate genes associated with IR and T2D are spread all across the genome. Two genes present on chromosome 1 are PRKAA2 and HSD11B1. PRKAA2 gene encodes alpha 2 isoform of catalytic subunit of AMPK, which is involved in glucose and lipid metabolism, IR and T2D. Moreover, PRKAA2 is located at the highly susceptible loci on chromosome 1 (1p36-32), which is associated with T2D in populations worldwide. SNP rs2051040 is independently and as a haplotype have been associated with IR in Japanese population (p = 0.009) in a sample set of 1205 cases and 824 controls (Horikoshi et al., 2006). HSD11B1 is an enzyme, which converts cortisol to cortisone. Changes in enzymatic action have been associated with metabolic syndrome, IR, and T2D. Two variants of this gene (rs846910, p = 0.03 and rs12086634, p = 0.03) have been reported in the context of IR, dyslipidemia, and T2D (Gandhi et al., 2013).

Two genes PPARG and ADIPOQ present on chromosome 3 are implicated with IR. LPN2 encodes for protein Lipin required for normal adipose tissue differentiation and triglyceride (TG) metabolism. Lipin2 binds upstream to PPARG to carry out this process. Owing to its role, the SNP in its 3′UTR was associated (p = 0.03, OR: 1.96) with IR in the Dutch population comprising 3506 subjects (Aulchenko et al., 2007). Pro12Ala variant of PPARG, which has been found associated with IR and obesity leading to T2D in various populations of the world, including Caucasians, Americans, and Japanese (Li et al., 2014). ADIPOQ (Adiponectin) is a protein peptide secreted by adipose cells, which has anti-inflammatory effects. Decreased concentration of adiponectin in plasma is associated with T2D, IR, and obesity. Four major SNPs (rs17300539, rs2241766, rs1501299, and 182052) related to this gene are implicated with T2D in Han Chinese, Japanese, Caucasian, and Asian populations (Foucan et al., 2014).

Chromosome 5 also harbors two genes ADRB2 and RACE. ADRB2 is a beta adrenergic G protein coupled receptor, which is directly associated with the calcium channel for fast transport. Haplotype analysis of 5′UTR SNPs (rs1042711, rs1801704, rs1042713, rs1042714) of this gene revealed its protective role (p = 0.018) against IR (Tellechea et al., 2013). RAGE is a cell surface receptor implicated in the development of T2D. One variant (rs3134945) has been associated (p < 0.05) with IR in T2D patients from the Netherlands (Gaens et al., 2008).

ESR1, LTA, and TNF-α are the three genes present on chromosome 6. ESR1 encodes for sex steroids. Treatments with sex steroids are known to cause IR. Two SNPs (rs2431260 and rs1709183) in these genes are found to cause IR in European American cohort with 300 cases and 310 controls with p-value of p = 0.015 and p = 0.019, respectively (Gallagher et al., 2007). TNF-α encodes for a proinflammatory cytokine, secreted by macrophages. TNFα plays a role in the regulation of cell proliferation, apoptosis, lipid metabolism, and cancer. Being part of lipid metabolism regulation, it has been associated with IR. Haplotype analysis of three SNPs (rs179964, rs1800630, rs1799724) in this gene revealed significant association (OR: 2.7 and p < 0.05) in T2D patients on insulin therapy (Xu et al., 2013). LTA encodes for lymphotoxin alpha protein. A study conducted on North Indians comprising of 1073 cases and 1042 controls showed significant association (OR: 0.86, p = 0.02) of this gene with decreased body mass index (BMI) and waist circumference (WC) in diabetic subjects (Mahajan et al., 2010).

Chromosome 7 harbors three genes CAV2, NRF1, and NOS3. CAV is a protein present on the inner surface of plasma membrane involved in lipid metabolism and cancer. SNP in this gene (rs2270188) is reported to be associated with dietary fat intake (p = 0.004) in a European population (Fisher et al., 2011). NRF1, a nuclear respiratory factor-1 gene, downregulates mitochondrial respiratory genes during oxidative phosphorylation. Two SNPs (rs1882094 and rs6969098) of this gene were found to be associated with T2D in Han Chinese population comprising 1027 subjects. GG carriers of rs1882094 were found to have low plasma glucose levels (p = 0.0002) and rs6969098 was associated with this polymorphism as a risk-conferring haplotype. These SNPs were also associated in Korean population (Liu et al., 2008). NO is encoded by nitric oxide synthase (NOS) isoenzyme gene and is known to cause IR and glucose intolerance especially in Asian populations. Based on meta analysis, rs1799983 correlated with the risk of T2D in Chinese diabetic subjects (n = 8600, OR: 1.14) (Jia et al., 2013).

UCP1 present on chromosome 8 and UCP3 on chromosome 11 are the metabolite transporters belonging to the subfamily of the mitochondrial anion carrier. UCP1 is involved in adaptive thermogenesis and decrease in reactive oxygen species (ROS) production, whereas UCP3 is believed to be involved in free fatty acids (FFA) metabolism and transport (Lim et al., 2012). A promoter polymorphism (rs10011540) in UCP1 gene has been associated (p = 0.0089) with IR and accumulation of hepatic lipid in the Japanese population. Two variants (rs1800849 and 3781907) in UCP3 gene have been found to be associated with high lipid levels and waist hip ratio (WHR) reported from Finnish population. These SNPs have also been well associated with T2D, obesity indices, and cholesterol levels in Caucasians, Japanese, South Indians and Asian populations (Salopuro et al., 2009).

SOCS3 gene is present on chromosome 17. SOCS3 expression is induced by IL6. Haplotype of three SNPS (rs12953258, rs4969168, and rs9914220) was found to be associated with IR (p = 0.023) in Uygur males and rs12953258 with IR in Uygur females (Meng et al., 2014).

Chromosome 20 harbors two genes. HNF4A gene encodes for a nuclear transcription factor involved in the development of kidneys, liver, and intestine. Mutations in this gene have been associated with monogenic form of diabetes called MODY. Three promoter variants (rs4810424, p = 0.017; rs1884613, p = 0.037; rs1884616, p = 0.024) in this gene have been associated with IR in Malaysian population (Saif-Ali et al., 2011). PTPN1 is a negative regulator of insulin and leptin signaling, which modulates glucose homeostasis and IR. In a French cohort comprising 2264 subjects, three variants (rs914458, p = 0.02; rs941798, p = 0.04; rs2426159, p = 0.02) of this gene were reportedly associated with IR (Cheyssac et al., 2006).

Epigenetics in T2D

Epigenetics is implicated in control of gene expression and epigenetic changes can be endogenously programmed or may occur in response to exogenous factors. Endogenous factors comprise changes during early developmental stages, diverse cell lineage, stem cell variation, and age-related modifications. Exogenous factors are of two types, which include physical and chemical ones. Physical factors include exposure to radiations, hypoxia, calorie restriction, and excessive cold and heat. Bisphenol-A, herbicides, emulsifiers, surfactants, and arsenic are some of the chemicals leading to epigenetic changes.

DNA methylation of the CpG sites in promoters of the candidate genes was noticed in T2D. About 70% of the SNPs in the promoter region are associated with T2D through DNA methylation. Most of the genes, such as IL6, IL6R, and TNF, were proinflammatory (Wren and Garner, 2005). Ageing apparently could cause errors in methylation. It leads to production of short-chain fatty acids accompanied by hypomethylation resulting in dysregulation of the proinflammatory cytokines. Patients with T2D reported with enhanced methylation display aging, hyperglycemia, and obesity (Gilbert and Liu, 2012).

The number of mi-RNA is altered in various tissues in T2D. Hyperglycemia and lipotoxicity are the key modulators of mi-RNA expression in response to environmental damage. mi-RNA plays a role in PBC development, maturity, and function. Increase in mi-RNA expression leads to altered fat metabolism, chronic hyperglycemia, increase in proinflammatory cytokine signaling, and finally β-cell apoptosis.

PGC-1α, GCK, PDX-1, PPAR-γ, GLUT-4, TCF7L2 genes have shown altered expression in response to DNA methylation. Increased methylation of insulin gene promoter causes decreased PGC-1α expression leading to decreased insulin secretion. Hypermethylation of DNA causes decreased expression of GCK. Increased methylation leads to decreased expression of PDX1 in β-cells and histone modifications impairing β-cell development and function (Yang et al., 2012). TCF7L2 promoter was found 50% more methylated in patients with T2D without medication (Canivell et al., 2014).

Intrauterine environment also initiates epigenetic changes such as PPAR-γ coactivator gene promoter hyperacetylation observed in the liver of intrauterine growth restriction rat models (IUGR). Similarly, in skeletal muscle of female IUGR, GLUT-4 genes were found to be regulated by methylation and deacetylation (Fu et al., 2004). Human studies were carried out using blood, where CpG hypomethylation of IGF-II gene in response to periconceptional famine was reported (Heijmans et al., 2008). Similarly, nonCpG hypermethylation of PPAR-γ coactivator was observed when incubated with TNF-α, free fatty acids, insulin, and glucose (Barres et al., 2009). In skeletal muscle, the PPAR-γ coactivator gene CpGs was hypermethylated in response to a high-fat diet (Brons et al., 2010).

Obesity in T2D

The changing environmental and economic growth owing to green and white revolutions leads to improved socioeconomic status contributing to obesity and diabetes (Sharma et al., 2013). Studies for Asian Indian populations have also indicated that central obesity poses a greater risk than general obesity toward T2D and associated complications. WC and WHR are the commonly used parameter to assess central obesity and may act as a risk factor for T2D. Central obesity reflects enhanced abdominal fat, visceral adipose tissue, and hepatic fat cells contributing to increased values of WC and WHR (Lear et al., 2002). However, in western countries, BMI is more associated with T2D.

The biological reason is that the central fat deposits have direct access to liver through portal vain circulation. When more energy is required, central fat deposits mobilize first as compared to other subcutaneous and gluteofemoral fat. Central obesity results in the overload of abdominal adipocytes with TG, reducing the capacity of fat depots to utilize dietary fat. Central adipocytes have high basal lipolysis and are very sensitive to fat mobilizing hormones like catecholamines (Arner, 1997), but they respond poorly to insulin. The enlarged central adipocytes flood the portal circulation with FFA exposing nonadipose tissue to excess of fat. This leads to accumulation of TG in muscles, liver, and PBCs, resulting in IR and β-cell dysfunction. Therefore, to reduce the ectopic fat deposition in insulin-sensitive tissues and to reduce excessive outflow of fat, it is recommended to decrease central fat reserves (Raz et al., 2005). Thus, obesity is the reason behind the epidemic rise of T2D, either measured by WC or by BMI. Obesity disrupts many pathways interlinked with T2D such as IR, and increased FFA circulation, which makes it even more dangerous as a risk factor for T2D.

Gene Environment Interactions

Interactions between genes and environmental factors contribute toward causation of T2D. The detrimental effects of genetic factors are elevated in the presence of environmental triggers. During the last few years, several studies have documented gene environment interaction showing associations with SNP markers. Diet and excessive intake of calories have been identified as the major force escalating the prevalence of T2D in the populations worldwide (Qi et al., 2008).

Most of the genetic variants associated with T2D in Caucasian population have been successfully replicated in Asians. Regardless of the heterogeneity, the number of risk variants seems to be similar across populations. Each variant increases the risk of developing T2D by 10–20%. However, increased T2D susceptibility can be better investigated in presence of the environmental factors (Murcray et al., 2008). In Caucasians, inflammatory genes were found to aggrandize the risk in the presence of western diet, which included sugar-sweetened beverages, refined/white grains, red/processed meat. Along with diet, other anthropometric measures like BMI were also found to aggravate the risk of T2D in Caucasian populations (Hu, 2011). On the other hand, in Asian populations the presence of thrifty genes is believed to play an important role in T2D. Due to the exposure of Asian populations to feast and famine cycle, they are believed to have inherited thrifty genes which are supposed to release more energy even with small amount of food intake (Neel, 1962). However, now with industrial and green revolutions, accompanied with sedentary lifestyles, have led to an increased prevalence of T2D in these populations. Besides thrifty genes, low birth weight and intrauterine nutrition are also the important factors deciding the risk for T2D in Asians populations. Asians are also found to have greater risk of obesity and T2D even at lower BMI values. WC and WHR are some of the important parameters implicated with T2D in Asians (Lear et al., 2007).

Thus, for the management of T2D, the genetic factors, environmental factors, ethnic differences, and dietary intake should be taken into consideration before attempting to develop a possible biomarker.

Ethnicity, T2D, and Prospect of Personalized Medicine

Ethnicity is an inevitable factor contributing toward T2D (Kaul et al., 2015). Different populations are susceptible toward T2D due to different environmental conditions, which modulate genetic backgrounds. The climatic conditions and dietary pattern in Western and European countries are entirely different from Asian countries. Moreover, the level of physical activity is more in Western and European countries than East Asian countries. In addition, the level of physical activity is highly reduced in South Asian countries because of cheap labor options, lack of awareness, and hectic job timing schedules. The thrifty genes are adapted to produce more energy even with less amount of food intake in cases of T2D. These environmental factors, climatic conditions, dietary pattern, and physical activity affect different populations in a different manner giving rise to varying genotype.

There are about 47 genetic loci responsible for T2D in the European population. However, genetic loci in East Asians included few loci common from European and some new loci like KCNQ1 (rs2237892), ZFAND3 (rs659470794), and MAEA (rs6815464) etc. Most of the GWAS were carried out on Europeans. After 2008, GWAS were also carried out in other populations like East Asians, South Asians, Mexican Americans, and African Americans. The differential association of variants was noticed in different populations, which included some variants that were common in all the populations (PPAR-γ, KCNJ11, TCF7L2 etc) to some variants that were specific to one population, such as MEAE and ZFAND3 in East Asians, and TMEM163 and MAP3K1 in Indians (Tabassum et al., 2013).

These reports suggest that in case of T2D, there are several genes having their own variants correlated with a given ethnic group. Thus, the only consensus in the present scenario is that there is no consensus whatsoever nor would there be any in the future. What all has gone wrong in a T2D patient in one population compared to those in another T2D patient of another population would always be different. Therefore, genotypically, each patient from a population is expected to be unique and thus, the response of the medicament given to such a patient would also be different. With respect to personalized medicine, all these factors qualify to be taken seriously. One possibility is that the T2D patients from across the world may be systematically classified based on their lifestyle and food intake coupled with ancestral history. This would provide some semblance on the category-wise genotypic variation across the population. The information on the intake of food habit would help in developing more efficient personalized medicine in tune with recognized genotype encompassing all the chromosomes and SNPs implicated with T2D.

Conclusion

T2D has become a threat to mankind globally. Unfortunately, there seem to be no respite from this or similar such burdens. Thus, before prescribing a generic drug, the complete knowledge of a person's genetic makeup, ethnicity, and the environmental factors that he has been exposed to should be considered. Till now, the drugs and medication provided to a diabetic person is more or less similar, irrespective of the abovementioned factors. This means that a personalized drug for T2D patient is nowhere in sight. This surely requires concerted efforts on the part of researchers, scientists, and clinicians and able all drug discoverers to join hands and move forward to meet the challenge.

Footnotes

Acknowledgments

S.A. acknowledges the core support from the Department of Biotechnology (DBT), New Delhi to the National Institute of Immunology and award of J.C. Bose National fellowship, Department of Science and Technology (DST), New Delhi.

Disclosure Statement

Both authors have read and approved the article. The authors declare that they have no competing interests.

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