PHARMACOGENETICS IN DIABETES - EWAN R. PEARSON, MBBCHIR, PHD
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Pharmacogenetics in Diabetes
Ewan R. Pearson, MBBChir, PhD
Corresponding author The response to a drug is determined by the con-
Ewan R. Pearson, MBBChir, PhD centration of active drug available at its site(s) of action
Biomedical Research Institute, Ninewells Hospital and Medical (pharmacokinetics) and the ability of the drug to elicit an
School, Ninewells Avenue, Dundee, DD1 9SY, United Kingdom.
E-mail: e.pearson@chs.dundee.ac.uk
effect at its site of action (pharmacodynamics). In phar-
macokinetics, drugs can be actively transported across
Current Diabetes Reports 2009, 9:172–181
Current Medicine Group LLC ISSN 1534-4827 the gut epithelium, into the target tissue, or into the
Copyright © 2009 by Current Medicine Group LLC renal tubules. In addition, drugs are often metabolized
to an active form, or are metabolized to an inactive form
before excretion from the body. Historically, pharmaco-
Genetic variation can impact on efficacy and risk genetics has focused on the study of variation in the drug
of adverse events to commonly used oral agents in metabolizing enzymes, in particular the cytochrome P450
diabetes. Metformin is not metabolized and its mech- enzymes. However, recent developments have occurred in
anism of action remains debated; however, several the understanding of drug transport with some exciting
cation transporters have been identified. Variation in new data on how variation in genes encoding transporters
these pharmacokinetic genes might influence metfor- might impact on drug response.
min response. Conversely, although the cytochrome The pharmacodynamics of a drug can be broadly
P450 system has been implicated in sulfonylurea divided into direct and indirect factors. The direct drug
response in some small studies, to date variants affect- effects will be influenced by its ability to bind to a receptor,
ing pharmacodynamics, including those in ABCC8 the function of that receptor, and the function of the down-
(SUR1) and TCF7L2, are the most promising. For stream pathways. The indirect factors are those that are
thiazolidinedione response, variants in PPARG or distinct from the effector pathway (eg, response to a drug
ADIPOQ (adiponectin) have been variably associ- that increases insulin secretion may well be more effective
ated with response. With increasing well-phenotyped in a patient who is more insulin sensitive, although the
cohorts and new methods, including genome-wide drug effect has no effect on insulin action). For a disease
association studies, the next few years offer great hope such as type 2 diabetes (which is highly heterogeneous,
to use pharmacogenetics to unravel drug and disease and in which the drugs used target the disease-causing
mechanisms, as well as the possibility to individualize defects), direct and indirect pharmacodynamics of a drug
therapy by genotype. will be influenced by disease etiology (ie, an individual
may respond well to sulfonylureas because their diabetes
is etiologically distinct from an individual who responds
Introduction poorly). Therefore, it may be possible to use drug response
Pharmacogenetics is the study of how genetic variation rather than the traditional case/control study, as a tool to
affects drug response—either drug efficacy or adverse out- investigate diabetes etiology.
come. Although in the treatment of diabetes, hypertension
and hyperlipidemia are also targeted, this article focuses on
the pharmacogenetics of oral antihyperglycemic medica- Pharmacokinetic Pharmacogenetics
tion in type 2 diabetes and monogenic diabetes and will not Sulfonylureas
address insulin treatment or type 1 diabetes. Compared with In 1979, a ninefold variation in the rate of tolbutamide
anticancer therapy, the field of pharmacogenetics of diabetes disappearance from plasma was described with a trimodal
is in its infancy. However, genetics has impacted on diabetes distribution suggestive of monogenic inheritance [1]. This
treatment in some clear areas. With the exponential growth variation in hydroxylation of tolbutamide was subsequently
of large-scale genotyping methods, including genome-wide shown to be due to variation in CYP2C9 [2]. CYP2C9
association (GWA) study, we may be able to identify further has also been shown to be a rate-limiting enzyme in the
variants that impact on response or side effects. In addition, metabolism of other sulfonylureas, including glibenclamide
as will be discussed, drug response potentially can be used [3], gliclazide [4], glipizide [5], and glimepiride [6]. Two
to investigate drug mechanisms and disease etiology. variants in CYP2C9 affect the catalytic function of thePharmacogenetics in Diabetes
I Pearson
I 173
enzyme: Arg144Cys (2C9*2; allele frequency 11%) and Ile- required to determine the clinical impact of variation in
359Leu (2C9*3; allele frequency 7%). For glibenclamide, this drug transporter in the diabetic population.
the clearance for the *2/*2 individuals was reduced by
25%, and for the *3/*3 individuals by 57% compared Thiazolidinediones
with wild-type [3]. Similar figures for tolbutamide are Thiazolidinediones are extensively metabolized in the
25% and 84% [7]. liver, predominantly by CYP2C8, with CYP2C9 (pio-
Despite the clear data showing dramatic differences in glitazone and rosiglitazone) and CYP3A4 (pioglitazone)
sulfonylurea metabolism for carriers of different CYP2C9 playing a minor role. The data on the role of CYP2C8
variants, minimal study has been done on the effect of on thiazolidinedione response are inconclusive. The in
these variants on response (Table 1). One recent study sug- vitro work suggests that the 2C8*3 variant should impair
gests, for the first time, that CYP2C9 variants may impact metabolism, yet in response to rosiglitazone, carriers of
on sulfonylurea prescribing. In a retrospective observa- the 2C8*3 polymorphism (Arg139Lys and Lys399Arg
tional study of 296 patients prescribed tolbutamide, those substitutions) had lower elimination half-lives than wild-
carrying the *3 allele of CYP2C9 did not have their tolbu- type but showed no difference in glucose lowering [16].
tamide dose increased when compared with the wild-type For pioglitazone, 2C9*3 polymorphisms reduced the area
(*1/*1) group [8]. This effect was not seen in a smaller under the plasma concentration time curve [17]; however,
number of patients treated with glibenclamide (n = 76) no studies have looked at the effect of this genotype on
and glimepiride (n = 76). This could reflect lack of power. pharmacodynamic response.
However, it may be important to look at other cytochrome
P450 genes because a study in a Chinese population recently
showed that gliclazide modified release is predominantly Pharmacodynamic Pharmacogenetics
metabolized by CYP2C19 rather than 2C9 [9]. Sulfonylureas
Sulfonylureas bind to the SUR1 moiety of the pancreatic
Metformin β-cell K ATP channel causing the channel to close and trig-
Metformin is not metabolized and is primarily excreted ger insulin secretion. The fact that genetic variation in this
unchanged in the urine. Recent studies have implicated pathway can alter sulfonylurea response is best highlighted
the role of organic cation transporters in metformin by the 1% to 2% of diabetes caused by Mendelian muta-
disposition: PMAT (plasma membrane monoamine trans- tions in TCF1 (encoding hepatocyte nuclear factor-1 α
porter) (SLC29A4) is involved in gut absorption [10], [HNF-1α]) causing maturity-onset diabetes of the young.
OCT1 (SLC22A1) primarily in hepatic uptake, and OCT2 In a randomized trial of sulfonylureas and metformin in
(SLC22A2) in tubular secretion [11,12]. patients with diabetes due to TCF1 mutations and type
In a transgenic mouse model, knockout of liver 2 diabetes, the fall in fasting plasma glucose (FPG) into
Slc22a1 virtually abolished hepatic lactate production gliclazide was 3.9-fold greater in patients with TCF1
supporting a key role of Oct1 in transporting metfor- mutations than their response to metformin (P = 0.002);
min into the hepatocytes [13]. An elegant study by Shu as expected, no difference in response to gliclazide or met-
et al. [14••] took this concept further and showed that formin was apparent in those with type 2 diabetes [18].
OCT1 plays an important role in determining metfor- The mechanism probably results from the fact that the
min response in humans. They showed that deletion major β-cell defects due to reduced HNF-1α function are
of Slc22a1 in mouse liver reduced metformin effects on in glucose metabolism, and are therefore bypassed by sul-
5′ adenosine monophosphate-activated protein kinase fonylureas that act on the K ATP channel to stimulate insulin
(AMPK) phosphorylation and gluconeogenesis; as a con- release [18]. This study highlighted, for the fi rst time, the
sequence, the glucose-lowering effect of metformin was importance of genetic etiology in determining response
abolished. In addition, they described four loss-of-func- to treatment in diabetes and has led to change in clinical
tion polymorphisms in SLC22A1 that in a study of 20 management of patients with TCF1 mutations. Sulfonyl-
normal glucose-tolerant individuals reduced the effect of ureas are now recommended as the fi rst-line antidiabetic
metformin on response to oral glucose [14••]. In a subse- therapy for these patients. It is exciting that patients who
quent paper, they demonstrated higher serum metformin have been assumed to have type 1 diabetes and are treated
concentrations in those carrying the reduced function with insulin, who are subsequently found to have a TCF1
OCT1 polymorphisms, suggesting that this is due to mutation, have been able to transfer off insulin onto sulfo-
reduced hepatic uptake of the drug [15]. In contrast to the nylurea therapy [19].
fi ndings by Shu et al. [14••], a study of 24 responders and A further example of how identifying monogenic dia-
nine non-responders to metformin showed no difference betes can impact dramatically on diabetes treatment can be
in the prevalence of OCT1 or OCT2 variants between seen in the recent discoveries in neonatal diabetes. In 2004,
these two groups. A large study of SLC22A1 variation a third of cases of diabetes diagnosed before 6 months of
on glycemic response and side effects to metformin is age were found to be due to activating mutations in the174
Table 1. Pharmacogenetic studies on sulfonylurea outcome assessed by clinical response with more than 1 month of oral treatment
I
Study Study population Intervention and outcome Gene polymorphisms Outcome
Pharmacokinetic
Genetics
Holstein et al. [55] Any sulfonylurea, 20 patients with Admissions to emergency department CYP2C9 *2 and *3 2 of the hypoglycemic group (10%)
severe hypoglycemia vs 337 without with hypoglycemia were *2/*3 or *3/*3 compared with 7
(2.1%) of the controls
Becker et al. [8] Observational study, 248 patients Change in daily prescribed dose CYP2C9 *2 and *3 Glibenclamide NS, tolbutamide *1/*3
treated with sulfonylurea for at least and *2/*3 12-mg dose increment
10 prescriptions (172 tolbutamide, compared with 279-mg dose incre-
42 glimepiride, 34 glibenclamide) ment for wild-type (*1/*1) (P = 0.009);
glimepiride NS
Pharmacodynamics
Gloyn et al. [29] Randomized prospective study Reduction in fasting glucose at 1 y, KCNJ11 E23K and L270V No significant genotypic effect
(UKPDS), 363 patients treated with or sooner if failed on sulfonylurea
chlopropamide, glibenclamide, treatment before 1 y
or glipizide
Sesti et al. [28] Prospective study, 525 patients treated Binary outcome–sulfonylurea failure KCNJ11 E23K Carriers of K allele (RR for treatment
with glibenclamide until failure when are those requiring insulin after failure, 1.45; P = 0.04) compared
metformin was added failure of combined sulfonylurea and with wild-type
metformin treatment
Sesti et al. [56] As above As above Gly972Arg IRS-1 Carriers of Arg972 IRS-1 variant
associated with treatment failure (RR,
2.7 [1.02–7.28]; P = 0.045) compared
with wild-type
Feng et al. [26••] Prospective study, gliclazide for 8 wk; FPG reduction at 6 wk; HbA1c reduction Ser1369Ala of ABCC8 In the combined group, subjects with
initial round (n = 661), replication Ala/Ala had a 7.7% greater FPG
(n = 607) reduction (P < 0.001), an 11.9% greater
decrease in 2-hour plasma glucose
(P = 0.003) compared with Ser/Ser. No
difference in HbA1c reduction
FPG—fasting plasma glucose; HbA1c—hemoglobin A1c; NS—not significant; RR—relative risk; UKPDS—United Kingdom Prospective Diabetes Study.Pharmacogenetics in Diabetes
I Pearson
I 175
KCNJ11 gene encoding the Kir6.2 subunit of the β-cell as failure of combination sulfonylurea and metformin
K ATP channel [20]. Subsequently, in 2006, mutations in therapy rather than sulfonylurea alone. In this study,
the ABCC8 gene encoding the other subunit of the K ATP carriers of the K allele had a relative risk for failure of
channel, SUR1, were also found to cause neonatal diabetes, this combination of 1.45 (95% CI, 1.01–2.09; P = 0.04).
although less commonly [21,22]. With these mutations, However, it is unclear whether this reflects sulfonylurea
the pancreatic K ATP channel is insensitive to the increase in failure, metformin failure, or simple differential rates in
intracellular adenosine triphosphate/adenosine diphosphate diabetes progression by genotype.
that results from glucose metabolism. Thus, the pancreatic In 2006, the DECODE group published an associa-
β cell does not secrete insulin in response to hyperglycemia. tion between TCF7L2 variants and type 2 diabetes risk,
Sulfonylureas bind to the K ATP channel, and intravenous such that the 10% of the population homozygous for
tolbutamide was able to stimulate insulin secretion in the risk variant were twice as likely to develop diabetes
patients with KCNJ11 mutations [20]. This work led to the as the wild-type population [30•]. This has been widely
successful transfer of patients with neonatal diabetes who replicated and remains the strongest genetic association
had lifelong insulin treatment to oral sulfonylurea therapy for type 2 diabetes described to date. The mechanism for
with near normalization of blood glucose [23,24]. how TCF7L2 variants cause diabetes remains unclear,
Can this monogenic paradigm be applied to common although several studies point to this being due to
type 2 diabetes? Do polymorphisms in glucose metabolism decreased β-cell function [31–33], possibly mediated by
enzymes, the K ATP channel, or downstream pathways influ- an impaired incretin response [32]. Given the potential
ence sulfonylurea response? Recently, several established role of TCF7L2 in insulin secretion, and its large effect
variants have been identified as associated with type 2 dia- (by type 2 diabetes standards), it is a good candidate
betes risk that impact primarily on β-cell insulin secretion; gene for assessing impact on sulfonylurea response. In
these include variants in TCF7L2, KCNJ11, CDKAL1, a large study from Tayside, Scotland, of 901 incident
CDKN2A-2B, WFS1, HHEX-IDE, and SLC30A8 [25]. To users of sulfonylureas, patients with type 2 diabetes who
date, the only etiologic candidate genes published investigat- were homozygous for the diabetes risk allele (G) at SNP
ing association with sulfonylurea response are in KCNJ11, rs12255372 were twice as likely not to be treated to below
ABCC8, and TCF7L2. Once again, the field is relatively a target HbA1c of 7% in the fi rst 3 to 12 months of treat-
small and the results are conflicting (Table 1). However, ment compared with patients homozygous for the T allele
a few reasonable sized studies of interest exist. In what is (OR, 1.95; P = 0.005) [34•]. Importantly, no effect was
probably the largest and cleanest diabetes pharmacogenetics observed of this variant on metformin response (n = 945)
study to date, 25 single nucleotide polymorphisms (SNPs) in [34•], showing that the association is with sulfonylurea
11 candidate genes were examined in a prospective trial of response rather than diabetes severity or progression.
1268 patients treated with gliclazide. After an initial round
(n = 661), the Ser1369Ala of the ABCC8 gene and rs5210 Metformin
of the KCNJ11 gene were significantly associated with As detailed above, the main success in metformin phar-
decreases in FPG (P = 0.002). This finding for Ser1369Ala macogenetics has been the elucidation of different drug
was replicated in a separate cohort (n = 607). In the com- transporters. The picture is not as clear for pharmacody-
bined groups, compared with subjects with the Ser/Ser namic pharmacogenetics as, in contrast to sulfonylureas,
genotype, subjects with the Ala/Ala genotype had a 7.7% the exact mechanistic pathway for metformin remains
greater decrease in FPG (P < 0.001), and an 11.9% greater unclear. At a physiologic level, metformin’s primary effect
decrease in 2-hour plasma glucose (P = 0.003), although no is probably to reduce hepatic glucose output by increasing
difference in hemoglobin A1c (HbA1c) was seen [26••]. insulin suppression of gluconeogenesis [35•]. However,
KCNJ11 (encoding the Kir6.2 subunit of the K ATP debate exists over its role in augmenting insulin-mediated
channel) is adjacent to ABCC8 on chromosome 11, and glucose disposal into muscle, and an often overlooked
ABCC8 Ser1369Ala and KCNJ11 rs5210 and E23K are in mechanism of metformin is a reduction in noninsulin-
strong linkage disequilibrium (ie, highly correlated). The mediated glucose clearance [35•], which explains as much
E23K variant of KCNJ11 was robustly associated with of the effect of metformin on glucose lowering as its role
type 2 diabetes in a large meta-analysis [27]. In a study on hepatic glucose production, and a reduction in glucose
of human donor islets, glibenclamide-induced insulin absorption from the gut.
secretion was impaired in the KK islets [28]. The associa- At a molecular level, metformin’s effects are mediated
tion of response to sulfonylureas and the E23K variant via AMPK, an effect that requires phosphorylation of
were studied in the UKPDS cohort, where in a study of AMPK by LKB1, but metformin does not directly activate
360 type 2 diabetic patients, no effect of the genotype AMPK or LKB1, and the mechanism by which metfor-
occurred on the change in FPG in the fi rst year of treat- min activates AMPK remains to be determined. This
ment [29]. In a subsequent study of 525 patients with type physiologic and molecular uncertainty makes it difficult
2 diabetes, sulfonylurea failure was confusingly defi ned to hypothesize good candidate genes. However, obvious176
Table 2. Pharmacogenetic studies on thiazolidinedione outcome assessed by clinical response with more than 1 month of oral treatment
I
Study Study population and intervention Outcome Gene polymorphisms Outcome
Pharmacokinetic
Genetics
None
Pharmacodynamic PPARG
Bluher et al. [43] Prospective study of 131 patients Reduction in HbA1c or FPG at 12 PPARG Pro12Ala No significant genotypic effect
with type 2 diabetes treated with and 26 wk
pioglitazone, 45 mg, for > 26 wk
Snitker et al. [44] 93 women with previous gestational Change in insulin sensitivity at PPARG Pro12Ala No significant genotypic effect
diabetes treated with troglitazone, 12 wk determined by IVGTT.
400 mg, daily for 12 wk Nonresponders (lower tertile)
compared with responders
(upper 2 tertiles)
Wolford et al. [45] As above As above PPARG sequenced, identifying 61 8 SNPs associated with response
SNPs (MAF > 5%). Single SNP (none significant after adjusting
and haplotype analysis for multiple testing); 3 of these
SNPs (rs4135263, rs10510419,
rs1152003) were marginally asso-
ciated with changes in insulin
sensitivity (as quantitative trait);
3 haplotypes were marginally
associated with response
Kang et al. [47] Prospective study, 198 patients FPG and HbA1c reduction at 3 mo PPARG Pro12Ala; NB Ala Decrease in FPG (3.20 mmol/L vs
treated with rosiglitazone, 4 mg, frequency very low in this 1.35; P = 0.003) and decrease in
for 3 mo Korean population (MAF 3%) so HbA1c (1.66 vs 0.48; P = 0.012)
only 11 Pro/Ala and no Ala/Ala greater in Ala carriers compared
individuals with wild-type
Florez et al. [46] Prospective study, 340 nondiabetic Change in insulin sensitivity PPARG Pro12Ala, and 5 No significant genotypic effect on
subjects with IGT or IFG index derived from OGTT SNPs from Wolford et al. FPG or HbA1c reduction
[45] (rs880663, rs4135263
rs1152003, rs6806708, and
rs13065455)
Pharmacodynamic other
Kang et al. [48] Prospective study, rosiglitazone, FPG and HbA1c reduction at 6 wk ADIPOQ (adiponectin) SNP Patients G/G at +45 or +276 had
4 mg, every day for 3 mo +45T/G and SNP +276G/T smaller FPG (P = 0.032 and
P = 0.001) and HbA1c (P = 0.028
and P = 0.006) reduction
with rosiglitazone
FPG—fasting plasma glucose; HbA1c—hemoglobin A1c; IFG—impaired fasting glucose; IGT—impaired glucose tolerance; IVGTT—intravenous glucose tolerance test; MAF—minor allele
frequency; OGTT—oral glucose tolerance test; SNP—single nucleotide polymorphism.Table 2. Pharmacogenetic studies on thiazolidinedione outcome assessed by clinical response with more than 1 month of oral treatment (Continued)
Study Study population and intervention Outcome Gene polymorphisms Outcome
Sun et al. [49] 42 patients treated with 4 mg of FPG reduction ADIPOQ; -11377 C/G, +45 T/G No significant genotypic effect of
rosiglitazone daily for 12 wk +45T/G. Lower FPG reduction
in carriers of G allele at -11377
(although baseline significantly
lower in this group)
Kang et al. [57] Rosiglitazone, 4 mg, daily for 3 mo FPG and HbA1c reduction Perilipin; 6209 G/A, 11482 G/A, No significant genotypic effect on
13041 A/G, 14995 A/T FPG or HbA1c reduction
Wang et al. [58] 113 patients treated with > 10% reduction in FPG or Lipoprotein lipase; S447X S/S genotype associated with
pioglitazone, 30 mg, for 10 wk absolute reduction in HbA1c >1% increased response
Wang et al. [51] 93 patients treated with 4 or 8 mg > 15% FPG reduction or absolute ABCA1; R219K, M883I, For R219K, KK had more treatment
of rosiglitazone for 48 wk reduction in HbA1c > 0.5% and R1587K failures than relative risk (per allele
OR, 2.14; P < 0.05; not adjusted
for multiple comparisons). No
significant genotypic effect of
M883I or R1587K
FPG—fasting plasma glucose; HbA1c—hemoglobin A1c; IFG—impaired fasting glucose; IGT—impaired glucose tolerance; IVGTT—intravenous glucose tolerance test; MAF—minor allele
frequency; OGTT—oral glucose tolerance test; SNP—single nucleotide polymorphism.
Pharmacogenetics in Diabetes
I
Pearson
I
177178
I Genetics
candidates are the genes encoding the AMPK subunits. A patients had no beneficial effect of troglitazone on insulin
Japanese study of 192 cases and 272 controls identified sensitivity. An initial analysis showed no effect of the Pro-
a haplotype across PRKAA2 (encoding the AMPK-α2 12Ala polymorphism on this response [44]; however, in a
subunit) that was associated with type 2 diabetes, was subsequent detailed haplotype analysis across the PPARG
replicated in two independent cohorts, and was associ- gene, a weak association with response was found with
ated with insulin resistance assessed by homeostasis certain haplotypes, although the small numbers here
model assessment [36]. However, a haplotype analysis make this haplotype analysis underpowered [45]. Florez
in 4206 Scandinavian and Canadian individuals showed et al. [46] also studied the influence of PPARG variants
no association between PRKAB1 (encoding the AMPK- on the effect of troglitazone on insulin sensitivity index
β1 subunit) and PRKAB2 (encoding AMPK-β2 subunit) in the Diabetes Prevention Program but showed no
and type 2 diabetes risk or insulin sensitivity [37]. Fur- association with response. The only result suggesting an
thermore, a study of 1787 unrelated Japanese subjects association with response was in a Korean population of
found no association between PRKAA2, STK11 (LKB1), 198 patients treated with rosiglitazone, 4 mg, daily. They
and CRTC2 (TORC2) variants and type 2 diabetes that reported that those carrying the Ala allele had a greater
withstood correction for multiple testing [38]. Thus, no response to rosiglitazone than the Pro/Pro homozygotes;
convincing evidence exists for an association between the however, the allele frequency in the Ala group was very
pathways of metformin action and diabetes risk. However, low (3%), and this result is only based on 11 Pro/Ala and
just because variants in this pathway do not explain dia- no Ala/Ala individuals [47].
betes risk does not preclude them from having an effect on Genes other than PPARG have been studied for asso-
metformin response, and the haplotypes identified would ciation with thiazolidinedione response (Table 2). A couple
be good candidates to assess metformin response. Inter- of groups looked at the adiponectin gene ADOPOQ,
estingly, in a small study in which metformin was used but again with no consistent replicated results [48,49].
to induce ovulation in patients with polycystic ovarian An interesting alternative candidate came from a mouse
syndrome, variation in rs8111699 of STK11 (LKB1) was model lacking the high-density lipoprotein synthesis gene
significantly associated with ovulation induction success: Abca1. Mice lacking Abca1 exhibited lipid accumulation
48% (10/21) of C/C women, 67% (32/48) of C/G women, and β-cell toxicity [50]. Rosiglitazone activates Abca1 and
and 79% (15/19) of G/G women ovulated [39]. Although therefore could protect against this β-cell lipotoxicity. In
the study numbers were very small, it would be interesting just one study, one SNP was identified in ABCA1 that was
to look at this variant with respect to glycemia or insulin nominally associated with response to rosiglitazone [51].
sensitivity outcomes. Thiazolidinediones are associated with increased risk of
heart failure and fluid retention. This has been attributed to
Thiazolidinediones PPAR-γ regulation of a renal-collecting duct sodium trans-
Thiazolidinediones promote the binding of the transcrip- porter (ENAC), and polymorphisms in the gene encoding
tion factor peroxisome proliferator-activated receptor-γ the ENAC β subunit have been associated significantly
(PPAR-γ) to its DNA response element. Among several with edema in a study of 207 patients receiving farglitazar
effects, the thiazolidinediones promote adipocyte dif- in phase 3 clinical trials [52]. In a study of another glitazar
ferentiation. Physiologically, thiazolidinediones increase (dual-acting PPAR-γ/-α agonists), ragaglitazar, edema was
insulin-stimulated glucose uptake into muscle, insulin less in those carrying the protective Ala allele at Pro12Ala
suppression of hepatic glucose output, and insulin-stimu- PPAR-γ than the wild-type patients, and was not influenced
lated lipolysis [40]. by the Leu162Val SNP in PPAR-α [53].
Variation at PPARG (encoding PPAR-γ) was one of
the fi rst loci to be robustly associated with type 2 dia-
betes, with the fi nding that carriers of the Ala variant at Future Directions for Diabetes Pharmacogenetics
codon 12 were protected against diabetes with a per-allele The arrival of the GWA study has had a dramatic impact
RR of 1.25 compared with the Pro/Pro individuals [41]. on gene discovery for disease traits, including type 2 dia-
Because the Pro12Ala variant influences transcriptional betes. The great advantage of these studies is they make
activity of PPARG and is located in the ligand-binding no prior assumption about mechanism and, as such, their
domain, this variant is a good candidate to affect thiazoli- primary role in diabetes gene discovery has been to reveal
dinedione response [42]. Several groups have studied this novel pathways not previously thought to be associated
and found variable results, probably reflecting the small with diabetes. Therefore, if drug response (efficacy or
sample sizes in each group (Table 2). Bluher et al. [43] adverse outcome) is used as the outcome of interest, a GWA
found no association with Pro12Ala and HbA1c reduction study could reveal new insights into drug mechanism. For
with pioglitazone, 45 mg, in 131 patients. In an analysis example, this might help unravel the mechanism of action
of the TRIPOD study, which treated women with pre- of metformin, or the mechanism of gastrointestinal intol-
vious gestation diabetes with troglitazone, one third of erance in up to 25% of individuals who are treated withPharmacogenetics in Diabetes
I Pearson
I 179
metformin. In addition, because disease etiology is an Clinical Trial Acronyms
important determinant of drug response, a GWA on drug DECODE—Diabetes Epidemiology: Collaborative analysis
response could reveal new etiologic variants. However, of Diagnostic criteria in Europe; TRIPOD—Troglitazone
a drawback for this approach is that large sample sizes in Prevention of Diabetes; UKPDS—United Kingdom Pro-
and independent replication cohorts are required. At the spective Diabetes Study.
present time, pharmacogenetic studies are too small and
rarely replicated, so efforts must be made to collect better
cohorts and form collaborations to increase sample sizes. Acknowledgments
Another limitation of the GWA approach is that it is only Ewan R. Pearson holds a clinician scientist fellowship (CSO/
able to detect common variation. It is likely that genetic NHS Scotland), and his work is supported by Diabetes UK
effects that will impact enough on drug response to affect (grant 07/0003525).
clinical prescribing will be rare, and therefore missed by
a GWA study. However, a recent study on myopathy in
statin users provided great support for using the GWA Disclosure
approach in pharmacogenetics. In this study, the genetic No potential confl ict of interest relevant to this article
effect size was so large that it was possible to perform a was reported.
genome-wide scan on just 85 patients with severe myopa-
thy and 90 controls on high-dose statins [54••]. This
contrasts with the sample sizes of greater than 30,000 References and Recommended Reading
that are now being studied in meta-analyses of multiple Papers of particular interest, published recently,
GWA studies to fi nd disease association with a relative have been highlighted as:
risk of 1.1. A “hit” achieving genome-wide significance at • Of importance
rs4149056 in SLCO1B1 (encoding OATP1B, an organic •• Of major importance
anion transporter involved in statin transport into the
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4. Elliot DJ, Suharjono, Lewis BC, et al.: Identification of
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