INT J CURR SCI 2014, 12: E 110-127
REVIEW ARTICLE ISSN 2250-1770
Type 2 Diabetes Mellitus: Impact of genetics and environment
Md. Shamim Hossaina*, Md. Saidul Islama,b, Mst. Touhida khatuna and Md. Ashrafuzzaman Sapona
aDepartment of Biotechnology and Genetic Engineering, Faculty of Applied Science and Technology
Islamic University, Kushtia-7003, Bangladesh
bLaboratory of Microbiology and Genetics, Department of Biomedical Sciences, Medical School
Chonbuk National University, Jeonju, 561-712, Republic of Korea
*Corresponding author: [email protected]; Phone: +8801719409846
Abstract
Type 2 diabetes (T2D) develops while the body can still produce insulin, but not enough, or when the insulin produced
doesn’t work properly. It has become a health-care problem worldwide, with the raise in disease prevalence being all the
more worrying as it not only affects the developed world but also developing nations with fewer resources to cope with yet
another major disease burden. Furthermore, the problem is no longer restricted to the ageing population, such as young
adults and children are also being diagnosed with T2D. Genes play an important role in the development of diabetes
mellitus. Type 2 diabetes is a polygenic disorder with multiple genes located on different chromosomes contributing to its
susceptibility, including TCF7L2, KCNJ11, PPARG, ENPP1, Adiponectin, Calpain 10, PTPN1, CDKAL1, ABCC8, HNF4A,
SLC2A2, UCP2, INS, PIK3R1 and SOS1 gene. The environmental factor (arsenic, pesticides, selenium, bisphenol A,
phthalates and microorganism) also associated with Type 2 diabetes. Researchers found that taking proper exercise,
vaccination against causing enterovirous, regulation of taking diet and keep away from smoking are the best away prevent
from type 2 diabetes. This review aims to provide the link of causative factor to develop type 2 diabetes and search the
possible away of prevention against type 2 diabetes.
Keywords: Type 2 diabetes, insulin resistance, gene, environmental factor
Received: 04thMay; Revised: 18thJune; Accepted: 07thJuly © IJCS New Liberty Group 2014
Introduction
Diabetes mellitus type 2 also known as noninsulin-
dependent diabetes mellitus (NIDDM) or adult-onset
diabetes is a metabolic disorder that is characterized by
high blood glucose level in the context of insulin
resistance and relative insulin deficiency (Vinay et al.,
2005). Insulin resistance is a term that describes the
reduced ability for cells to store away blood sugar. In
essence, the hormone insulin, which activates the blood
sugar storage process, becomes increasingly ineffective.
Type 2 Diabetes has a complex pathogenesis that was
classically characterized by pancreatic β-cell dysfunction
followed by decrease of the beta cell mass, peripheral
insulin resistance and raised hepatic glucose production.
β-cell dysfunction is occurred initially by diminished
firstphase insulin response after glucose stimulation but
also following stimulation with nonglucose
secretagogues such as the incretin hormone glucagon-
like peptide-1 (GLP-1) ( Guja et al., 2012). This type of
diabetes is in contrast to diabetes mellitus type 1 where
causes an absolute insulin deficiency due to destruction
of islet cells in the pancreas. Type 2 diabetes makes up
about 90% of cases of diabetes with the other 10% due
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primarily to diabetes mellitus type 1 and gestational
diabetes. Obesity is thought to be the primary cause of
type 2 diabetes in people who are genetically predisposed
to the disease. Rates of type 2 diabetes have elevated
markedly over the last 50 years. As of 2010 there are
approximately 285 million people with the disease
compared to around 30 million in 1985 (Smyth and
Heron, 2006). Long-term complications from high blood
sugar can result in heart disease, strokes, diabetic
retinopathy where eyesight is affected, kidney failure
which may require dialysis, and poor circulation of limbs
leading to amputations. Diabetes mellitus affects people
of every age, race, and background, and is now a major
modern cause of premature death in many countries
around the world, with someone dying from Diabetes
Type 2 every 10 seconds worldwide (Gillespie, 2008).
Genetic factor
Type 2 diabetes is a polygenic disease that different
kinds of genes are involved to its expression. On the
basis of locus or combination of loci, it may be
dominant, recessive, or between of them. Though the
identifying of a complex disease is challenging but
different strategies have been used in efforts to identify
type 2 diabetes susceptibility genes.
TCF7L2 gene
In 2003, a modest peak of linkage was described
on chromosome 10 by researchers at deCODE genetics
consortium on Icelandic T2D families. The exploration
of this linkage signal led to the identification of a T2D
associated gene (Grant et al., 2006), namely the gene
encoding the Transcription Factor 7-Like 2 (TCF7L2)
located at 10q25.3. TCF7L2 (also known as TCF-4) is a
transcriptional factor involved in Wnt signaling, being
able to bind b-catenin. This pathway of signaling is
connected in embryogenesis, including adipocyte and
pancreatic tissue formation. A strong association
between type 2 diabetes and variation in the transcription
factor 7-like 2 (TCF7L2) gene found in Icelandic,
Danish, and American populations (Grant et al., 2006).
Some studies confirmed TCF7L2 as the locus that
confers the strongest responsible on T2D diabetes risk,
so that some authors even stated that this could be the
biggest story in diabetes genetics since the discovery of
HLA’s in T1D (Zeggini and McCarthy, 2007). The
physiological implication of this transcription factor is
responsible in glucose homeostasis. It has been suggested
that intestinal proglucagon gene expression may be
regulated by the Wnt/TCF7L2 pathway in
enteroendocrine cells (Yi et al., 2005). Thus, TCF7L2
variants may modify type 2 diabetes susceptibility
through modulation of glucagon-like peptide-1 (GLP-1)
secretion. As for the molecular mechanism of TCF7L2
involvement in T2D pathogenesis, where found that the
risk allele leads to impaired insulin secretion by altering
three different mechanisms: glucose-stimulated insulin
secretion, incretinstimulated insulin secretion and
proinsulin-toinsulin conversion (Schafer et al., 2011).
PPARG gene
PPARG gene on chromosome 3in locus 3p25 was
an attractive candidate gene because it encodes the
molecular target for thiazolidinediones. In 1997, Yen et
al. described an association between the proline-to-
alanine change at position 12 of PPARG (Pro12Ala or
rs1801282) in and the risk of T2D (Guja et al., 2012). A
common missense variant in the g2 isoform of
peroxisome proliferator–activated receptor gamma, a
protein of PPARG gene (PPAR g) [Pro12 to Ala12
(Pro12Ala)] has shown to association with diabetes in
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multiple studies, where a meta-analysis suggesting that
the common allele is associated with an increased
diabetes risk of 25% (Altshuler et al., 2000). A major
missense mutations in this gene result in severe,
dominantly inherited insulin resistance, diabetes mellitus,
and additional features such as partial lipodystrophy and
hypertension (Barroso et al., 1999).
KCNJ11 gene
The KCNJ11 gene, located on the short arm of
chromosome 11p15.1, encodes the pore-forming subunit
of the ATP-sensitive potassium channel Kir6.2 of the
pancreatic β-cells. The ATP-sensitive potassium channel
which plays a key role in regulating the release of
hormones, such as insulin and glucagon, in the beta cell.
Gain-of-function mutations of KCNJ11 open the
potassium channel and inhibit the depolarization of β-
cells, leading to a defect in insulin secretion (Gloyn
et al., 2004). Remarkably, this gene was reported to be
involved in the pathogenesis of neonatal diabetes. A
missense Glu23Lys mutation was described (E23K or
rs5210) in which Glutamate is changed into Lysine at
codon 23 of KCNJ11. Studies in various populations
have consistently reported that substitution of lysine for
glutamic acid at the 23rd amino acid (E23K) is
associated with an increased risk of T2DM (Florez et al.,
2004; Nielsenb et al., 2003). In recent reports of large-
scale association studies and meta-analyses, the E23K
variation was found to raise the risk of T2DM with an
OR of 1.15 (Florez et al., 2006).
ENPP1gene
The gene ectonucleotide pyrophosphatase
phosphodiesterase 1 (ENPP1), also known as plasma cell
glycoprotein 1, which recently found to be associated
with both childhood and adult obesity in a French
population. A moderate excess of the risk haplotype was
also observed in adults with T2DM compared with
controls (10.7% vs 7.1%, OR 1.44), and this association
was also replicated in an Austrian cohort with similar
frequencies. The study of Mantel-Haenszel of 2,569
European subjects supported the association, with OR
1.56 and p=0.00002 (Meyre et al., 2005). The
nonsynonymous variant lysine 212 to glutamine
(K121Q) has been best studied, and also shown to be
associated with obesity but not diabetes in Caucasian and
African American subjects ascertained from the New
York Cancer Project (Matsuoka et al., 2005). Other
researchers also found a connection of K121Q with
earlier T2DM onset and coronary disease among T2DM
patients (Bacci et al., 2005). The association of K121Q
with T2DM was replicated in three relatively small
populations among them two of South Asian ancestry
and one Caucasian (Abate et al., 2005). Although the
K121Q variant appears to associate with T2DM and
obesity, additional work is needed to determine the
magnitude of the risk. In 2001, Hegele et al. described a
K121Q SNP of ENPP1 gene that was strongly associated
with insulin resistant. Though different studies on this
gene reported a positive association with type 2 diabetes
but other well-powered studies failed to replicate this
association (Florez, 2008). However, a recent
metaanalysis of about 42,000 samples (McAteer et al.,
2008) confirmed the association of this ENPP1 gene
variant with T2D in European populations under a
recessive model (OR 1.38, p < 0.005).
Calpain 10 gene
The first common diabetes gene report of a positive
result emerging from GWL scanning in T2D families
was represented by CAPN-10 (region of chromosome 2),
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the gene encoding Calpain 10. CAPN10 encodes an
intracellular calcium-dependent cysteine protease that is
ubiquitously expressed in both adult and fetal tissues
(Cox et al., 2004). A haplotype that was initially linked
to T2D included an intronic A to G mutation at position
43, which shows to be involved in CAPN10 transcription.
In 2000, Horikawa et al. reported three single nucleotide
polymorphisms (SNPs) in the CAPN-10 gene associated
with T2D: SNP-43 (G/A) in intron 3, SNP -19 (3/2) in
intron 6 and SNP-63 (C/T) in intron 13 and described
several T2D associated haplotypes. Though the exact
mechanism of CAPN-10 gene involvement in T2D
pathogenesis remains unknown but functional evidence
accumulated in recent studies suggests a potential role in
both insulin resistance and insulin secretion (Turner
et al., 2005).
Adiponectin gene
In 2000, a GWL study on French families identified
a peak of linkage on chromosome 3q27-qter (Vionnet
et al., 2000) and it was shown to segregate with T2D and
MetS on chromosome 3q27 in both French and Japanese
populations. A strong linkage was found this gene in
Hispanic Americans by the Insulin Resistance and
Atherosclerosis Study Family Study (Guo et al., 2006)
but not reconfirmed in Pima Indians and African
Americans (Grigorescu et al., 2011). Adiponectin (ApN
or ADPN or ADIPOQ or APM1) is a 30 kDa protein
structurally similar to complement 1q, secreted by
adipocytes. ApN plays an important role in insulin
action, energy homeostasis, inflammation etc. ApN
levels are declined in insulin-resistant patients with
obesity, T2D or MetS and correlate well with insulin
sensitivity. Adiponectin levels correlate negatively with
glucose, insulin and triglyceride levels as well as the
body mass index (BMI), while there is a positive
correlation with high-density lipoproteins (HDL),
cholesterol level. SNPs of APM1, the gene encoding
adiponectin, were associated with the development of
hyperglycemia (Dedoussis et al., 2007). More than 10
SNPs were described in the ADIPOQ gene with possible
correlation to the plasma ApN levels, MetS and risk to
develop T2D, the best studied being SNP-45 in exon 2
and SNP 276 in intron 2. For SNP-45T/G, the G allele
would be pathogenic in most studies and associated to
high risk of T2D and reduced insulin sensitivity (Tso
et al., 2006). In the French population, two other SNPs
(C–11377G and G-11391A) from the promoter region
were reported to be associated with hypoadiponectemia
and T2D (Vasseur et al., 2002).
PTPN1 gene
The PTPN1 gene ubiquitously expressed protein
tyrosine phosphatase-1B (PTP1B), catalyzes the
dephosphorylation of tyrosine residues from the insulin
receptor kinase activation segment (Seely et al., 1996)
and IRS1 (Goldstein et al., 2000) resulting in the down-
regulation of insulin signaling. PTP1B also shows
negative control on leptin signaling through the
dephosphorylation of JAK2 and STAT3 (Cheng et al.,
2002). The disruption of the PTPN1 gene in mice results
in elevated insulin sensitivity and in resistance to diet-
induced obesity (Elchebly et al., 1999), as well as
enabling normalization of blood glucose levels. Several
studies have investigated the association of T2DM with
genetic variants of PTPN1. When analyzing the PTPN1
gene locus, Bento et al. (2004) discovered convincing
associations between multiple SNPs and T2DM in two
independent Caucasian American case-control samples.
Recently published data indicate that PTPN1 variants
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might modify the lipid profile, thereby influencing
susceptibility to the metabolic syndrome (Cheyssac et al.,
2006).
CDKAL1 gene
The results of the first T2D genome-wide
association studies (GWAS) were published in 2007 in
Nature, Nature Genetics and Science and reported
CDKAL1 gene associated with T2D. CDKAL1 encodes
CDK5 regulatory subunit-associated protein 1-like 1
(Steinthorsdottir et al., 2007), which is thought to inhibit
cyclin-dependent kinase 5 (CDK5) activity by binding to
the CDK5 activator p35. A genetic variation located in
6p22.3 of the CDKAL1 gene was discovered to be sig-
nificantly associated with T2DM through the deCODE
study (Steinthorsdottir et al., 2007). CDKAL1 gene also
encodes a 579-residue, 65-kD protein sharing
considerable amino acid homology with CDK5RAP1, an
inhibitor of CDK5 activation and is expressed in human
pancreatic islet and skeletal muscle. In a recent study,
revealed that disruption of CDKAL1 in mouse β-cells
resulted in impaired first-phase insulin secretion (Ohara-
Imaizumi et al., 2010). The people who had risk variants
of CDKAL1 had decreased insulin secretion capacity.
HNF4A (hepatocyte nuclear factor 4-α)
Mutations in promoter and coding regions of the
HNF4A gene cause MODY1. HNF4A encodes an orphan
hormone nuclear receptor that, together with TCF1
(LocusLink ID 6927), encoding HNF1α, TCF2
(LocusLink ID 6928), encoding HNF1β, and FOXA2
(LocusLink ID 3170), encoding HNF3β, constitutes part
of a network of transcription factors regulating gene
expression in pancreatic β-cells, liver, and other tissues.
These transcription factors control expression of the
insulin gene as well as genes encoding proteins
associated in glucose transport and metabolism and in
mitochondrial metabolism, all of which are linked to
insulin secretion in β-cells (Fajans et al., 2001). HNF4A
maps to Chromosome 20 (Argyrokastritis et al., 1997) in
a region that has been connected to Type 2 diabetes in
multiple studies (Klupa et al., 2000; Permutt et al., 2001).
This positional information, combined with the known
role of major mutations at this gene in the causation of
autosomal-dominant maturity-onset diabetes of the
young (MODY), has led to HNF4A being thought as a
strong candidate for involvement in causing Type 2
diabetes. The heterozygous nonsense and missense
mutations in HNF4α lead to an insulinopaenic form of
MODY strongly believes that β-cell dysfunction is
sensitive to the amount of HNF4α in the β-cell and that
haploinsufficiency is the likely mode of molecular
pathogenesis in that condition (Barroso et al., 2003).
ABCC8 (ATP binding cassette, subfamily C, member 8)
The ABCC8 gene is located on chromosome
11p15.1 and several gene variants of both genes have
been associated with disorders of insulin secretion and
T2DM (Dedoussis et al., 2007). ABCC8 encodes an
ATP-sensitive potassium channel, which plays a key role
in regulating the release of hormones, such as insulin and
glucagon, in the beta cell. Mutations in either gene can
affect the potassium 7 channel’s activity and insulin
secretion, ultimately leading to the development of T2D.
ABCC8 variants have been associated with Type 2
diabetes which is shown in multiple studies (Barroso
et al., 2003). ABCC8 (Ala) genes have been associated
with T2D, as well as other diabetes-related traits.
Because of the close proximity of these gene, current
studies are evaluating whether this gene work in concert
with each other, or rather have an independent effect on
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T2D susceptibility.More recently Florez and colleagues
(2004) investigated the ABCC8 gene and tested sufficient
variants to completely tag all variation in this region.
After that the E23K variant was associated with T2DM
in 3,413 subjects, and the association was confirmed in a
meta-analysis that contained over 5000 T2DM subjects
and 4747 controls (p<10-5, OR 1.15). The E23K variant
is in nearly complete linkage disequilibrium (completely
correlated) with a Serine to Alanine change at position
1369 in exon 33 of the sulfonylurea receptor, and thus
S1369A and E23K cannot be distinguished genetically
(Das and Elbein, 2006).
Jack Spratt gene (new diabetes Gene identified)
It has long been hypothesized that type 2 diabetes in
lean people is more genetically driven. A new study
found from a research team which was led by the
Peninsula College of Medicine and Dentistry (PCMD),
University of Exeter. This research institutions from
around the world, has for the first time proved that lean
type 2 diabetes patients have a larger genetic disposition
to the disease than their obese counterparts. Their study
has also identified a new genetic factor associated only
with lean diabetes sufferers. The study is published in
PLoS Genetics. Using genetic data from genome-wide
association studies, the research team tested genetic
markers across the genome in approximately 5,000 lean
patients with type 2 diabetes 13,000 obese patients with
the disease and 75,000 healthy controls. The team
revealed differences in genetic enrichment between lean
and obese cases which support the hypothesis that lean
diabetes sufferer have a greater genetic predisposition to
the disease. This is in contrast to obese patients with type
2 diabetes, where factors other than type 2 diabetes genes
are more likely to be responsible. In addition, genetic
variants near the gene, LAMA1 were linked to type 2
diabetes risk for the first time, with an effect that
appeared only in the lean patients (Perry et al., 2012).
SLC2A2 (encoding GLUT2)
SLC2A2 encodes the glucose transporter GLUT2, a
member of the facilitative glucose transporter family that
is highly expressed in pancreatic β-cells and liver. It is a
highly plausible candidate gene for Type 2 diabetes, as it
is a high Km transporter that regulates entry of glucose
into the pancreatic β-cell. This initiating the cascade of
events, leading to insulin secretion. GLUT2 is also
highly expressed in the liver, where it is associated in the
regulation of both glucose uptake and output. It is
notable that the alleles that associated with increased
diabetes risk were also all linked with lower fasting
insulin levels, suggesting that these may influence basal
insulin secretion. In 2003, Barroso et al. typed six SNPs
in SLC2A2, three of which SNP21, SNP23, and SNP24
and found significantly associated with diabetes status
with an OR of approximately 1.4-1.5. In the QT study,
all three disease-associated SNPs were also associated
with lower levels of fasting plasma insulin. Rather
surprisingly allele 2 (A) at T198, which was connected
with increased disease risk, was associated with lower 2-
h plasma glucose. No other significant associations with
intermediate phenotypes were found (Barroso et al.,
2003).
UCP2 gene
UCP2 gene located on chromosome 11q13 (SNP,
rs659366). It is responsible for impaired insulin secretion
hat has been shown to predominate over insulin
resistance in individuals with early onset T2D. The
UCP2 variant has a strong predictor of T2D with earlier
onset. The promoter variant in the UCP2 gene has been
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associated with increased expression of the gene in
adipose tissue. If this variant is associated with increased
UCP2 mRNA levels in human pancreatic β-cells (which
is not known), this could result in increased uncoupling
and, in turn, in decreased formation of ATP and impaired
insulin secretion. In 2005, Lyssenko et al. revealed that
fifty-eight (44.3%) of the converters were homozygous
for the risk genotype (GG) of the UCP2 −866G>A
variant and this GG genotype was associated with a
modestly increased risk of T2D (HR 1.4, p = 0.049).
Though this risk was not influenced by BMI and FPG at
baseline whereas the GG genotype was also associated
with increased risk of developing T2D in patients with
earlier onset of diabetes (HR 2.0, 95% CI 1.2–3.3, p =
0.0057).
INS (encoding insulin)
The INS (LocusLink ID 3630) gene encodes the
hormone preproinsulin, which upon proteolytic cleavage
creates mature insulin and C-peptide. Barroso et al.
(2003) tested a single SNP in the 3′-UTR (SNP72) of the
insulin gene (INS) with disease status and found this
SNP, significantly associated with increased Type 2
diabetes risk under a recessive model for the T allele (OR
2.02, p = 0.0258). The insulin gene variable number
tandem repeat (INS–VNTR) has been extensively studied
and is proposed to exert pleiotropic effects on birth
weight and diabetes susceptibility (Huxtable et al., 2000).
The data for the single SNP Barroso et al. (2003) tested
suggest that either the insulin gene or other loci in LD
may be involved in Type 2 diabetes risk.
PIK3R1 and SOS1 gene: The gene PIK3R1, encoding the
p85α regulatory subunit of the phosphatidylinositol 3-
kinase which is a logical candidate gene for involvement
in causing of Type 2 diabetes owing to its role in insulin
signal transduction. An intronic variant, SNP42, was
associated with increased disease risk under two genetic
models (OR 1.41, p = 0.0090 for the allele 2 dominant
and OR1.34, p = 0.0088 for the additive model (Barroso
et al., 2003). According to QT study, Barroso et al.
(2003) revealed that SNP42 was significantly associated
with increased BMI and showed a borderline
significance with increased fasting insulin (measure of
insulin resistance) under a dominant model for allele 2.
Obesity is a major risk factor for insulin resistance, and
the observed increase in BMI coupled with increased
insulin resistance in carriers of allele G at SNP42
suggests that variation at this gene may be increasing
Type 2 diabetes risk through impaired insulin action.
One study did describe an association with disease status
and with QTs underlying Type 2 diabetes (Baier et al.,
1998). Finally Barroso et al. (2003) suggested about their
research data that variation in this gene is a risk factor for
the development of Type 2 diabetes. The gene SOS1 (son
of sevenless homolog 1 in Drosophila) encodes a guanine
nucleotide exchange factor that performs in the
transduction of signals that control cell growth and
differentiation. Barroso et al. (2003) analysed two SNPs
for association with disease status, a nonsynonymous
SNP (N1011S) and an intronic variant (SNP8). While the
nonsynonymous S1011 variant, which was very rare
(minor allele, 0.003), did not associate with disease
status, the intronic SNP was highly significantly
associated with decreased disease risk (OR 0.58, p =
0.0032). After their study, Barroso et al. (2003) noted
that this was the first investigation into the role of SOS1
in Type 2 diabetes risk.
Environmental factor: Arsenic: Arsenic can be found
naturally in drinking water. Studies of people exposed to
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high levels of arsenic from Taiwan, Bangladesh,
Mexico, and Sweden have found that arsenic may
contribute to the development of diabetes (Coronado-
Gonzalez, 2007). Arsenic could influence type 1 diabetes
development by mechanisms involving oxidative stress,
inflammation, or programmed cell death (apoptosis)
(Navas-Acien et al., 2006). Rat pancreatic beta cells
treated with arsenic showed impaired insulin secretion
and function (Díaz-Villaseñor et al., 2006). A recent
study published in the Journal of the American Medical
Association (JAMA) revealed that even at lower levels,
arsenic exposure was associated with increased
prevalence of diabetes in U.S. adults (Navas-Acien et al.,
2008). A study from Korea did find an association
between arsenic exposure and diabetes in people exposed
to normal, background exposure levels of arsenic,
especially women (Kim and Lee, 2011). Another newer
study found that in people from rural communities in the
US with high rates of diabetes, arsenic was associated
with poorer diabetes control (a higher HbA1c) in people
with. A study from parts of Mexico with historically high
levels of arsenic exposure noticed that people who had
certain genes are more likely to develop diabetes when
exposed to arsenic (Drobna et al., 2012).
Pesticides
Pesticides include a number of substances,
including herbicides and insecticides. The women who
reported agricultural exposure during pregnancy, the risk
of diabetes was associated with the use of four herbicides
(2,4,5-T; 2,4,5-TP; atrazine; butylate) and three
insecticides (diazinon; phorate; carbofuran) (Saldana
et al., 2007). Some pesticides can interfere with beta cell
function in ways that may promote diabetes
development. For an example, atrazine was found to
induce obesity and insulin resistance in rats by impairing
the function of mitochondria (Lim et al., 2009).
Mitochondria dysfunction may be involved in the
development of both type 1 and type 2 diabetes
(Szabadkai and Duchen, 2009). A study of the staff of an
Australian insecticide application program found higher
mortality rates for diabetes (probably type 2), as
compared with the general Australian population (Beard
et al., 2003). The widely-used organophosphate
pesticides (including malathion, diazinon, parathion, and
chlorpyrifos) have been found to be toxic to the immune
system in animals and sometimes humans (Galloway and
Handy, 2003). Early life exposure to these pesticides also
causes metabolic dysfunction resembling pre-diabetes in
animals, especially when adults eat a high-fat diet
(Slotkin, 2011). If animals exposed to malathion develop
high blood sugar levels, and their carbohydrate
metabolism is affected in ways that could increase
insulin resistance (Rezg et al., 2010).
Selenium
Selenium is an essential trace element, but it can
also be toxic at high doses. Selenium has bioaccumulated
to four times the toxic level in the food chain, a level that
can cause harm in fish and birds. Groundwater wells are
also affected, and state advisories are in effect for
consumption of fish due to high selenium levels (Palmer
et al., 2010). Selenium has been found to associate with
type 2 diabetes in some studies of people in the U.S.
Laclaustra et al. (2009) revealed that in U.S. adults
exposed to background selenium levels, the prevalence
of diabetes raised with raising levels of selenium. Fasting
glucose levels and hemoglobin A1C
levels increased with increasing selenium levels as
well. Another study using the same dataset but from an
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earlier time period also found selenium levels to be
associated with diabetes (Bleys et al., 2007). The dataset
used in these studies does not differentiate between type
1 and type 2 diabetes, although most participants would
have had type 2.
Bisphenol A
It is found that plastic such as water bottles, metal
can linings, dental sealants, toys, and other products, and
can leach out of these products, especially when exposed
to heat or acidity (Welshons et al., 2006). Worldwide,
over 6 billion pounds of BPA are produced each year,
and over 100 tons are released into the air annually
(Vandenberg et al., 2009).A human study has found an
association between BPA exposure and increased insulin
resistance, general obesity, and abdominal obesity in
Chinese adults (Wang et al., 20112). Nadal et al. (2009)
expressed how BPA targets the insulin-producing beta
cells in the pancreas, and creates insulin resistance in
animals. By doing so, it may contribute to beta cell
exhaustion. More recent study revealed from the same
laboratory confirms these effects, in human beta cells as
well as mouse beta cells (Soriano et al., 2012). A further
study finds that BPA slows down whole-body
metabolism in mice and ingulences insulin resistance
throughout their bodies (Batista et al., 2012).
Phthalates
Phthalates are widely used chemicals that soften
PVC plastic, and are also used in cosmetics, perfumes,
and industrial paints and solvents. Phthalates activate
certain hormone receptors called PPARs. PPARs are
known to influence blood glucose levels, via insulin
resistance, insulin secretion, and fat formation. When
pregnant and lactating rats were given DEHP, their
offspring formed abnormal beta cells, and alternations of
the genes controlling beta cell function at the time of
weaning. These results propose that developmental
exposure to phthalates can lead to beta cell dysfunction
and glucose abnormalities, and is a potential risk factor
for diabetes development (Lin et al., 2011). In New York
City children, certain phthalate exposures measured at
age 6-8 were associated with a higher body mass index
and waist circumference one year later (Teitelbaum et al.,
2012). Another study on Swedish women, the phthalate
MiBP was related to increased abdominal body fat two
years later (Lind et al., 2012).
Gut microbiota
Gut microbiota may be involved in the development
of obesity and type 2 diabetes as well (Cani and
Delzenne, 2010). Animal studies find that gut microbiota
can affect the formation of obesity, insulin resistance,
and diabetes through a variety of mechanisms. A
Western diet can raise microbiota that promotes obesity,
as could overuse of antibiotics (Musso et al., 2010). In a
study of rats, the animals given probiotics had a lower
body weight and more diverse intestinal biota than the
controls and those who received E coli (a harmful
microorganism) (Karlsson et al., 2011). It is especially
curious that gastric bypass surgery often leads to
lessening of type 2 diabetes without causing any weight
loss (Pournaras et al., 2010).
Prevention from type 2 diabetes
Exercise
Exercise is very important in the control of type 2
diabetes. Obesity is associated with hepatic and
peripheral insulin resistance and may have a deleterious
influence on the regulation of glucose homeostasis
(Coker et al., 2009). Weight gain, especially with central
fat accumulation, as indicated by a high waist
Hossain et al., 2014
www.currentsciencejournal.info
circumference is associated with impaired glucose
tolerance (IGT) and type 2 diabetes. Obesity in persons
with diabetes is also associated with poorer control of
blood glucose levels, blood pressure and cholesterol
(Anderson et al., 2003). Increased physical activity and
improved diet can delay or even prevent the progression
of insulin insensitivity from IGT to overt type 2
diabetes. Insulin resistance is an important pre-cursor to
type 2 diabetes, and in its early stages is reversible by
weight loss and an increase in physical activity (Ross
et al., 2000). The metabolic abnormalities of established
type 2 diabetes, including hyperglycaemia,
hyperinsulinaema and dyslipidaemia can be improved by
an increase in physical activity. Regular taking of
exercise reduce the risk of obesity and thereby minimize
the incidence of causing of diabetes types diseases. By
losing of weight and increasing physical activity can
neutralize the powerful effect of insulin resistance on
progression to diabetes (Hossain and Khatun, 2013). A
person who takes regular physical exercise appears to:
firstly reduce the activity of the pancreatic β-cells and
makes cellular tissues more sensitive to insulin, secondly
increase the rate at which glucose is taken into the
muscles, independent of the activity of insulin and finally
improve cardiovascular health and aids weight
management (Goodyear and Kahn, 1998).
Keep way from smoking
Smoking has been shown to increase insulin
resistance and diminish insulin secretion, both of which
are connected with the onset type 1 diabetes. There is a
growing body of evidence to show that smoking is a risk
factor for Type 2 Diabetes (Yeh et al., 2010). Smoking
has been identified as a possible risk factor for insulin
resistance, a precursor for diabetes. Smoking has also
been shown to deteriorate glucose metabolism which
may lead to the onset of type 2 diabetes (Fagard and
Nilsson, 2009). In 2010, Yeh et al. conducted a
community-based study of 15 792 middle-aged adults, to
test the hypothesis that although smoking is an
independent predictor of incident type 2 diabetes,
smoking cessation increases diabetes risk in the short
term, possibly because of cessation-related weight gain.
There is also some evidence which suggests that smoking
increases diabetes risk through a body mass index
independent mechanism. Smoking has been connected
with a risk of chronic pancreatitis and pancreatic cancer,
suggesting that tobacco smoke may be toxic to the
pancreas. A systematic review of 25 studies found that
all but one revealed an association between active
smoking and an increased risk of diabetes (Willi et al.,
2007). On the basis of this review, it is estimated that
12% of all type 2 diabetes in the United States may be
attributable to smoking (Ding and Hu, 2007). If the same
proportion is applied to the UK, smoking may account
for as many as 360,000 cases of diabetes. So, keep way
from smoking, is the best away to prevent from type 2
diabetes.
Conclusion
Type 2 diabetes risk is mainly depending upon a
genetic susceptibility and environmental factor that make
the insulin resistance. Some researches have suggested
that taking proper physical exercise to reduce over body
weight and maintain proper nutritional diet may also
contribute to prevent diabetes. Though the genetic
therapy are not well established yet we hope, in the near
future scientist can know the roles of these causative
genes and their molecular pathways that are related to the
risk of T2D and may potentially lead to targeted therapies
Hossain et al., 2014
www.currentsciencejournal.info
for type 2 diabetes patient for treating or preventing
diabetes.
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