Note: Descriptions are shown in the official language in which they were submitted.
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1
HUMAN DIABETES SUSCEPTIBILITY BTBD9 GENE
The present invention relates to a method for determining a predisposition to
diabetes in
patients, preferably in patients with obesity.
BACKGROUND OF THE INVENTION
According to the new etiologic classification of diabetes mellitus, four
categories are
differentiated: type 1 diabetes, type 2 diabetes, other specific types, and
gestational diabetes
mellitus (ADA, 2003). In the United States, Canada, and Europe, over 80% of
cases of
Diabetes are due to type 2 diabetes, 5 to 10 % to type 1 diabetes, and the
remainder to other
specific causes.
In Type 1 diabetes, formerly known as insulin-dependent, the pancreas fails to
produce the
insulin which is essential for survival. This form develops most frequently in
children and
adolescents, but is being increasingly diagnosed later in life. Type 2
diabetes mellitus,
formerly known as non-insulin dependent diabetes mellitus (NIDDM), or adult
onset
Diabetes, is the most common form of diabetes, accounting for approximately 90-
95% of
all diabetes cases. Type 2 diabetes is characterized by insulin resistance of
peripheral
tissues, especially muscle and liver, and primary or secondary insufficiency
of insulin
secretion from pancreatic beta-cells. Type 2 diabetes is defined by abnormally
increased
blood glucose levels and diagnosed if the fasting blood glucose level is
superior to 126
mg/dl (7.0 mmol/1) or blood glucose levels are superior to 200 mg/dl (11.0
mmol/1) 2 hours
after an oral glucose uptake of 75g (oral glucose tolerance test, OGTT). Pre-
diabetic states
with already abnormal glucose values are defined as fasting hyperglycemia (FH)
>6.1
mmol/1 and <7.0 mmol/1 or impaired glucose tolerance (IGT) >7.75 mmol/1 and
<11.0
mmol/l 2 hours after an OGTT.
Table 1: Classification of Type 2 diabetes (WHO, 2006)
Classification Fasting blood glucose 2 hours after an OGTT
level (mmol/l) (mmol/l)
Normo glycemia < 7.0 and < 11.0
FH only > 6.1 to < 7.0 and < 7.75
IGT only < 6.1 and >7.75 to <11.0
FH and IGT > 6.1 to < 7.0 and >7.75 to <11.0
Type 2 diabetes > 7.0 or > 11.0
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2
In 2000, there were approximately 171 million people, worldwide, with type 2
diabetes.
The number of people with type 2 diabetes will expectedly more than double
over the next
25 years, to reach a total of 366 million by 2030 (WHO/IDF, 2006). Most of
this increase
will occur as a result of a 150% rise in developing countries. In the US 7% of
the general
population are considered diabetic (over 15 million diabetics and an estimated
15 million
people with impaired glucose tolerance).
Twin and adoption studies, marked ethnic differences in the incidence and
prevalence of
type 2 diabetes and the increase in incidence of type 2 diabetes in families
suggest that
heritable risk factors play a major role in the development of the disease.
Known
monogenic forms of diabetes are classified in two categories: genetic defects
of the beta
cell and genetic defects in insulin action (ADA, 2003). The diabetes forms
associated with
monogenetic defects in beta cell function are frequently characterized by
onset of
hyperglycemia at an early age (generally before age 25 years). They are
referred to as
maturity-onset diabetes of the Young (MODY) and are characterized by impaired
insulin
secretion with minimal or no defects in insulin action (Herman WH et al, 1994;
Clement K
et all, 1996; Byrne MM et all, 1996). They are inherited in an autosomal
dominant pattern.
Abnormalities at three genetic loci on different chromosomes have been
identified to date.
The most common form is associated with mutation on chromosome 12q in the
locus of
hepatic transcription factor referred to as hepatocyte nuclear factor (HNF)-1
a(Vaxillaire M
et all, 1995; Yamagata et all, 1996). A second form is associated with
mutations in the
locus of the glucokinase gene on chromosome 7q and result in a defective
glucokinase
molecule (Froguel P et all, 1992; Vionnet N et all, 1992). Glucokinase
converts glucose to
glucose-6-phosphase, the metabolism of which, in turn, stimulates insulin
secretion by the
beta cell. Because of defects in the glucokinase gene, increased plasma levels
of glucose are
necessary to elicit normal levels of insulin secretion. A third form is
associated with a
mutation in the HnfMa gene on chromosome 20q (Bell GI et all, 1991; Yamagata K
et all,
1996). HNF-4a is a transcription factor involved in the regulation of the
expression of
HNF-4a. Point mutations in mitochondrial DNA can cause diabetes mellitus
primarily by
impairing pancreatic beta cell function (Reardon W et all, 1992; VanDen
Ouwenland JMW
et all, 1992; Kadowaki T et all, 1994). There are unusual causes of diabetes
that result from
genetically determined abnormalities of insulin action. The metabolic
abnormalities
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associated with mutation of the insulin receptor may range from
hyperinsulinemia and
modest hyperglycemia to severe diabetes (Kahn CR et all, 1976; Taylor
SI,1992).
Type 2 diabetes is a major risk factor for serious micro- and macro-vascular
complications.
The two major diabetic complications are cardiovascular disease, culminating
in
myocardial infarction. 50% of diabetics die of cardiovascular disease
(primarily heart
disease and stroke) and diabetic nephropathy. Diabetes is among the leading
causes of
kidney failure. 10-20% ofpeople with diabetes die of kidney failure. Diabetic
retinopathy is
an important cause of blindness, and occurs as a result of long-term
accumulated damage to
the small blood vessels in the retina. After 15 years of diabetes,
approximately 2% of
people become blind, and about 10% develop severe visual impairment. Diabetic
neuropathy is damage to the nerves as a result of diabetes, and affects up to
50% of all
diabetics. Although many different problems can occur as a result of diabetic
neuropathy,
common symptoms are tingling, pain, numbness, or weakness in the feet and
hands.
Combined with reduced blood flow, neuropathy in the feet increases the risk of
foot ulcers
and eventual limb amputation.
The two main contributors to the worldwide increase in prevalence of diabetes
are
population ageing and urbanization, especially in developing countries, with
the consequent
increase in the prevalence of obesity (WHO/IDF, 2006). Obesity is associated
with insulin
resistance and therefore a major risk factor for the development of type 2
diabetes. Obesity
is defined as a condition of abnormal or excessive accumulation of adipose
tissue, to the
extent that health may be impaired. The body mass index (BMI; kg/ml) provides
the most
useful, albeit crude, population-level measure of obesity. Obesity has also
been defined
using the WHO classification of the different weight classes for adults.
Table 2: Classification of overweight in adults according to BMI (WHO, 2006)
Classification BMI (kg/m~) Risk of co-morbidities
Underweight < 18.5 Low (but risks of other
clinical problems increased)
Normal range 18.5 - 24.9 Average
Overweight > 25
Pre-obese 25 - 29.9 Increased
Obese class I 30 - 34.9 Moderate
Obese class II 35 - 39.9 Severe
Obese class III > 40 Very severe
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More than 1 billion adults world-wide are considered overweight, with at least
300 million
of them being clinically obese. Current obesity levels range from below 5% in
China, Japan
and certain African nations, to over 75% in urban Samoa. The prevalence of
obesity is 10-
25% in Western Europe and 20-27% in the Americas (WHO, 2006).
The rigorous control of balanced blood glucose levels is the foremost goal of
all treatment
in type 2 diabetes be it preventative or acute. Clinical intervention studies
have shown that
early intervention to decrease both obesity and/or pre-diabetic glucose levels
through
medication or lifestyle intervention, can reduce the risk to develop overt
type 2 diabetes by
up to 50% (Knowler WC et al, 2002). However, only 30% of obese individuals
develop
type 2 diabetes and the incentive for radical lifestyle intervention is often
low as additional
risk factors are lacking. Also, the diagnosis of type 2 diabetes through
fasting blood glucose
is insufficient to identify all individuals at risk for type 2 diabetes.
A further obstacle to rapidly achieve a balanced glucose homeostasis in
diabetic patients is
the multitude of therapeutic molecules with a wide range of response rates in
the patients.
Type 2 diabetes is treated either by oral application of anti-glycemic
molecules or insulin
injection. The oral antidiabetics either increase insulin secretion from the
pancreatic beta-
cells or that reduce the effects of the peripheral insulin resistance.
Multiple rounds of
differing treatments before an efficient treatment is found significantly
decreases the
compliance rates in diabetic patients.
Molecular and especially genetic tests hold the potential of identifying at
risk individuals
early, before onset of clinical symptoms and thereby the possibility for early
intervention
and prevention of the disease. They may also be useful in guiding treatment
options thereby
short-circuiting the need for long phases of sub-optimal treatment. Proof-of-
principle has
been shown for the treatment of individuals with maturity-onset diabetes of
the young
(MODY). Following molecular diagnosis many individuals with MODY3 or MODY2 can
be put off insulin therapy and instead be treated with sulfonylureas (MODY 3)
or adapted
diet (MODY 2) respectively. Therefore, there is a need for a diagnostic test
capable of
evaluating the genetic risk factor associated with this disease. Such a test
would be of great
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interest in order to adapt the lifestyle of people at risk and to prevent the
onset of the
disease.
SUMMARY OF THE INVENTION
5 The present invention now discloses the identification of a diabetes
susceptibility gene.
The invention thus provides a diagnostic method of determining whether a
subject is at risk
of developing type 2 diabetes, which method comprises detecting the presence
of an
alteration in the BTBD9 gene locus in a biological sample of said subject.
Specifically the invention pertains to single nucleotide polymorphisms in the
BTBD9 gene
on chromosome 6 associated with type 2 diabetes and body weight.
In a particular embodiment, the subject to test is affected with obesity.
Preferably the
subject shows a body mass index (BMI; kg/m~) of at least 27, preferably of at
least 30.
LEGEND TO THE FIGURES
Figure 1: High density mapping using Genomic Hybrid Identity Profiling
(GenomeHIP).
Graphical presentation of the linkage peak on chromosome 6p2l.32-p2l.l. The
curve
depict the linkage results for the GenomeHip procedure in the region. A total
of 8 Bac
clones on human chromosome 6 ranging from position p-ter-33315824 to 43294973-
cen
were tested for linkage using GenomeHip. Each point on the x-axis corresponds
to a clone.
Significant evidence for linkage was calculated for clone BACA23ZF11 (p-value
2.8E-08).
The whole linkage region encompasses a region from 36 721 951 base pairs to
41255967
base pairs on human chromosome 6. The p-value less to 2x10-5 corresponding to
the
significance level for significant linkage was used as a significance level
for whole genome
screens as proposed by Lander and Kruglyak (1995).
DETAILED DESCRIPTION OF THE INVENTION
The present invention discloses the identification of BTBD9 as a diabetes
susceptibility
gene in individuals with type 2 diabetes. More specifically the invention
pertains to
individuals with both type 2 diabetes and a BMI > 27 kg/m2. Various nucleic
acid samples
from diabetes families were submitted to a particular GenomeHlP process. This
process led
to the identification of particular identical-by-descent (IBD) fragments in
said populations
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that are altered in diabetic subjects with a BMI > 27 kg/m2 . By screening of
the IBD
fragments, the inventors identified the BTBD9 gene as a candidate for type 2
diabetes.
SNPs of the BTBD9 gene were also identified, as being associated to type 2
diabetes, more
particularly in obese subjects.
DEFINITIONS
Type 2 diabetes is characterized by chronic hyperglycemia caused by pancreatic
insulin
secretion deficiency and/or insulin resistance of peripheral insulin sensitive
tissues (e.g.
muscle, liver). Long term hyperglycemia has been shown to lead to serious
damage to
various tissue including nerves tissue and blood vessels. Type 2 diabetes
accounts for 90 %
all diabetes mellitus cases around the world (10% being type 1 diabetes
characterized by
the auto-immune destruction of the insulin producing pancreatic beta-cells).
About 70-80%
of type 2 diabetics are considered overweight or obese and the excess in body
weight
significantly contributes to the peripheral insulin resistance and constitutes
a major
independent risk factor for the development of type 2 diabetes. Obesity is
generally
assessed by calculating the body mass index (BMI; kg/m'), as described above.
The
invention described here pertains to a genetic risk factor for individuals to
develop type 2
diabetes. Preferably the invention describes increased risk for overweight
individuals (BMI
> 27 kg/m2). More preferably the invention describes increased risk for
overweight
individuals (BMI > 30 kg/m2).
Within the context of this invention, the BTBD9 gene locus designates all
BTBD9
sequences or products in a cell or organism, including BTBD9 coding sequences,
BTBD9
non-coding sequences (e.g., introns), BTBD9 regulatory sequences controlling
transcription
and/or translation (e.g., promoter, enhancer, terminator, etc.), as well as
all corresponding
expression products, such as BTBD9 RNAs (e.g., mRNAs) and BTBD9 polypeptides
(e.g.,
a pre-protein and a mature protein). The BTBD9 gene locus also comprise
surrounding
sequences of the BTBD9 gene which include SNPs that are in linkage
disequilibrium with
SNPs located in the BTBD9 gene.
As used in the present application, the term "BTBD9 gene" designates the gene
BTB (POZ)
domain containing 9, as well as variants or fragments thereof, including
alleles thereof
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(e.g., germline mutations) which are related to susceptibility to TYPE 2
DIABETES. The
BTBD9 gene may also be referred to as RP3-322I12.1, FLJ32945, KIAA1880,
MGC120517, MGC120519, MGC120520, dJ322I12.1. It is located on chromosome 6 at
position 6p21.2.
The cDNA sequence is shown as SEQ ID NO:1, and the protein as SEQ ID NO:2
(GenBank Source: BC101356 - BC101354; Unigene: Hs.1 16233).
The BTB (for BR-C, ttk and bab) or POZ (for Pox virus and Zinc finger) domain
is present
near the N-terminus of a fraction of zinc finger (pfam00096) proteins and in
proteins that
contain the pfam01344 motif such as Kelch and a family of pox virus proteins.
The
BTB/POZ domain mediates homomeric dimerisation and in some instances
heteromeric
dimerisation. The structure of the dimerised PLZF BTB/POZ domain has been
solved and
consists of a tightly intertwined homodimer. The central scaffolding of the
protein is made
up of a cluster of alpha-helices flanked by short beta-sheets at both the top
and bottom of
the molecule. POZ domains from several zinc finger proteins have been shown to
mediate
transcriptional repression and to interact with components of histone
deacetylase co-
repressor complexes including N-CoR and SMRT. The POZ or BTB domain is also
known
as BR-C/Ttk or ZiN.
The term "gene" shall be construed to include any type of coding nucleic acid,
including
genomic DNA (gDNA), complementary DNA (cDNA), synthetic or semi-synthetic DNA,
as well as any form of corresponding RNA.
The BTBD9 variants include, for instance, naturally-occurring variants due to
allelic
variations between individuals (e.g., polymorphisms), mutated alleles related
to diabetes,
alternative splicing forms, etc. The term variant also includes BTBD9 gene
sequences from
other sources or organisms. Variants are preferably substantially homologous
to SEQ ID
No 1, i.e., exhibit a nucleotide sequence identity of at least about 65%,
typically at least
about 75%, preferably at least about 85%, more preferably at least about 95%
with SEQ ID
No 1. Variants of a BTBD9 gene also include nucleic acid sequences, which
hybridize to a
sequence as defined above (or a complementary strand thereof) under stringent
hybridization conditions. Typical stringent hybridisation conditions include
temperatures
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above 30 C, preferably above 35 C, more preferably in excess of 42 C, and/or
salinity of
less than about 500 mM, preferably less than 200 mM. Hybridization conditions
may be
adjusted by the skilled person by modifying the temperature, salinity and/or
the
concentration of other reagents such as SDS, SSC, etc.
A fragment of a BTBD9 gene designates any portion of at least about 8
consecutive
nucleotides of a sequence as disclosed above, preferably at least about 15,
more preferably
at least about 20 nucleotides, further preferably of at least 30 nucleotides.
Fragments
include all possible nucleotide lengths between 8 and 100 nucleotides,
preferably between
15 and 100, more preferably between 20 and 100.
A BTBD9 polypeptide designates any protein or polypeptide encoded by a BTBD9
gene as
disclosed above. The term "polypeptide" refers to any molecule comprising a
stretch of
amino acids. This term includes molecules of various lengths, such as peptides
and
proteins. The polypeptide may be modified, such as by glycosylations and/or
acetylations
and/or chemical reaction or coupling, and may contain one or several non-
natural or
synthetic amino acids. A specific example of a BTBD9 polypeptide comprises all
or part of
SEQ ID No: 2.
DIAGNOSIS
The invention now provides diagnosis methods based on a monitoring of the
BTBD9 gene
locus in a subject. Within the context of the present invention, the term
`diagnosis" includes
the detection, monitoring, dosing, comparison, etc., at various stages,
including early, pre-
symptomatic stages, and late stages, in adults or children. Diagnosis
typically includes the
prognosis, the assessment of a predisposition or risk of development, the
characterization of
a subject to define most appropriate treatment (pharmacogenetics), etc.
The present invention provides diagnostic methods to determine whether a
subject, more
particularly an obese subject, is at risk of developing type 2 diabetes
resulting from a
mutation or a polymorphism in the BTBD9 gene locus.
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It is therefore provided a method of detecting the presence of or
predisposition to type 2
diabetes in a subject, more particularly a subject with obesity, the method
comprising
detecting in a biological sample from the subject the presence of an
alteration in the
BTBD9 gene locus in said sample. The presence of said alteration is indicative
of the
presence or predisposition to type 2 diabetes. Optionally, said method
comprises a
preliminary step of providing a sample from a subject. Preferably, the
presence of an
alteration in the BTBD9 gene locus in said sample is detected through the
genotyping of a
sample.
In a preferred embodiment, said alteration is one or several SNP(s) or a
haplotype of SNPs
associated with type 2 diabetes. More preferably, said SNP associated with
type 2 diabetes
is as shown in Table 3A, i.e. said SNP is selected from the group consisting
of SNP87,
SNP88, SNP92, and SNP94.
Other SNP(s), as listed in Table 3B, may be informative too.
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12
Preferably the SNP is allele T of SNP87.
More preferably, said haplotype comprises or consists of several SNPs selected
from the
group consisting of SNP87, SNP88, SNP92, SNP94, more particularly the
following
haplotype:
2 - 1- 1- 1(i.e. SNP87 is T, SNP88 is T, SNP92 is C and SNP94 is G).
The invention further provides a method for preventing type 2 diabetes in a
subject, more
particularly a subject with obesity, comprising detecting the presence of an
alteration in the
BTBD9 gene locus in a sample from the subject, the presence of said alteration
being
indicative of the predisposition to type 2 diabetes, and administering a
prophylactic
treatment against type 2 diabetes.
The alteration may be determined at the level of the BTBD9 gDNA, RNA or
polypeptide.
Optionally, the detection is performed by sequencing all or part of the BTBD9
gene or by
selective hybridisation or amplification of all or part of the BTBD9 gene.
More preferably a
BTBD9 gene specific amplification is carried out before the alteration
identification step.
An alteration in the BTBD9 gene locus may be any form of mutation(s),
deletion(s),
rearrangement(s) and/or insertion(s) in the coding and/or non-coding region of
the locus,
alone or in various combination(s). Mutations more specifically include point
mutations.
Deletions may encompass any region of two or more residues in a coding or non-
coding
portion of the gene locus, such as from two residues up to the entire gene or
locus. Typical
deletions affect smaller regions, such as domains (introns) or repeated
sequences or
fragments of less than about 50 consecutive base pairs, although larger
deletions may occur
as well. Insertions may encompass the addition of one or several residues in a
coding or
non-coding portion of the gene locus. Insertions may typically comprise an
addition of
between 1 and 50 base pairs in the gene locus. Rearrangement includes
inversion of
sequences. The BTBD9 gene locus alteration may result in the creation of stop
codons,
frameshift mutations, amino acid substitutions, particular RNA splicing or
processing,
product instability, truncated polypeptide production, etc. The alteration may
result in the
production of a BTBD9 polypeptide with altered function, stability, targeting
or structure.
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The alteration may also cause a reduction in protein expression or,
alternatively, an increase
in said production.
In a particular embodiment of the method according to the present invention,
the alteration
in the BTBD9 gene locus is selected from a point mutation, a deletion and an
insertion in
the BTBD9 gene or corresponding expression product, more preferably a point
mutation
and a deletion.
In any method according to the present invention, one or several SNP in the
BTBD9 gene
and certain haplotypes comprising SNP in the BTBD9 gene can be used in
combination
with other SNP or haplotype associated with type 2 diabetes and located in
other gene(s).
In another variant, the method comprises detecting the presence of an altered
BTBD9 RNA
expression. Altered RNA expression includes the presence of an altered RNA
sequence, the
presence of an altered RNA splicing or processing, the presence of an altered
quantity of
RNA, etc. These may be detected by various techniques known in the art,
including by
sequencing all or part of the BTBD9 RNA or by selective hybridisation or
selective
amplification of all or part of said RNA, for instance.
In a further variant, the method comprises detecting the presence of an
altered BTBD9
polypeptide expression. Altered BTBD9 polypeptide expression includes the
presence of an
altered polypeptide sequence, the presence of an altered quantity of BTBD9
polypeptide,
the presence of an altered tissue distribution, etc. These may be detected by
various
techniques known in the art, including by sequencing and/or binding to
specific ligands
(such as antibodies), for instance.
As indicated above, various techniques known in the art may be used to detect
or quantify
altered BTBD9 gene or RNA expression or sequence, including sequencing,
hybridisation,
amplification and/or binding to specific ligands (such as antibodies). Other
suitable
methods include allele-specific oligonucleotide (ASO), allele-specific
amplification,
Southern blot (for DNAs), Northern blot (for RNAs), single-stranded
conformation analysis
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(SSCA), PFGE, fluorescent in situ hybridization (FISH), gel migration, clamped
denaturing
gel electrophoresis, heteroduplex analysis, RNase protection, chemical
mismatch cleavage,
ELISA, radio-immunoassays (RIA) and immuno-enzymatic assays (IEMA).
Some of these approaches (e.g., SSCA and CGGE) are based on a change in
electrophoretic
mobility of the nucleic acids, as a result of the presence of an altered
sequence. According
to these techniques, the altered sequence is visualized by a shift in mobility
on gels. The
fragments may then be sequenced to confirm the alteration.
Some others are based on specific hybridisation between nucleic acids from the
subject and
a probe specific for wild type or altered BTBD9 gene or RNA. The probe may be
in
suspension or immobilized on a substrate. The probe is typically labeled to
facilitate
detection of hybrids.
Some of these approaches are particularly suited for assessing a polypeptide
sequence or
expression level, such as Northern blot, ELISA and RIA. These latter require
the use of a
ligand specific for the polypeptide, more preferably of a specific antibody.
In a particular, preferred, embodiment, the method comprises detecting the
presence of an
altered BTBD9 gene expression profile in a sample from the subject. As
indicated above,
this can be accomplished more preferably by sequencing, selective
hybridisation and/or
selective amplification of nucleic acids present in said sample.
Sequencing
Sequencing can be carried out using techniques well known in the art, using
automatic
sequencers. The sequencing may be performed on the complete BTBD9 gene or,
more
preferably, on specific domains thereof, typically those known or suspected to
carry
deleterious mutations or other alterations.
Amplification
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Amplification is based on the formation of specific hybrids between
complementary
nucleic acid sequences that serve to initiate nucleic acid reproduction.
Amplification may be performed according to various techniques known in the
art, such as
5 by polymerase chain reaction (PCR), ligase chain reaction (LCR), strand
displacement
amplification (SDA) and nucleic acid sequence based amplification (NASBA).
These
techniques can be performed using commercially available reagents and
protocols.
Preferred techniques use allele-specific PCR or PCR-SSCP. Amplification
usually requires
the use of specific nucleic acid primers, to initiate the reaction.
Nucleic acid primers useful for amplifying sequences from the BTBD9 gene or
locus are
able to specifically hybridize with a portion of the BTBD9 gene locus that
flank a target
region of said locus, said target region being altered in certain subjects
having type 2
diabetes. Examples of such target regions are provided in Table 3A or Table
3B.
Primers that can be used to amplify BTBD9 target region comprising SNPs as
identified in
Tables 3A or 3B may be designed based on the sequence of SEQ ID No 1 or on the
genomic sequence of BTBD9. In a particular embodiment, primers may be designed
based
on the sequence of SEQ ID Nos 3-22.
Typical primers of this invention are single-stranded nucleic acid molecules
of about 5 to
60 nucleotides in length, more preferably of about 8 to about 25 nucleotides
in length. The
sequence can be derived directly from the sequence of the BTBD9 gene locus.
Perfect
complementarity is preferred, to ensure high specificity. However, certain
mismatch may
be tolerated.
The invention also concerns the use of a nucleic acid primer or a pair of
nucleic acid
primers as described above in a method of detecting the presence of or
predisposition to
type 2 diabetes in a subject, in particular in a subject with obesity.
Selective hybridization
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Hybridization detection methods are based on the formation of specific hybrids
between
complementary nucleic acid sequences that serve to detect nucleic acid
sequence
alteration(s).
A particular detection technique involves the use of a nucleic acid probe
specific for wild
type or altered BTBD9 gene or RNA, followed by the detection of the presence
of a hybrid.
The probe may be in suspension or immobilized on a substrate or support (as in
nucleic
acid array or chips technologies). The probe is typically labeled to
facilitate detection of
hybrids.
In this regard, a particular embodiment of this invention comprises contacting
the sample
from the subject with a nucleic acid probe specific for an altered BTBD9 gene
locus, and
assessing the formation of an hybrid. In a particular, preferred embodiment,
the method
comprises contacting simultaneously the sample with a set of probes that are
specific,
respectively, for wild type BTBD9 gene locus and for various altered forms
thereof. In this
embodiment, it is possible to detect directly the presence of various forms of
alterations in
the BTBD9 gene locus in the sample. Also, various samples from various
subjects may be
treated in parallel.
Within the context of this invention, a probe refers to a polynucleotide
sequence which is
complementary to and capable of specific hybridisation with a (target portion
of a) BTBD9
gene or RNA, and which is suitable for detecting polynucleotide polymorphisms
associated
with BTBD9 alleles which predispose to or are associated with obesity or an
associated
disorder. Probes are preferably perfectly complementary to the BTBD9 gene,
RNA, or
target portion thereof. Probes typically comprise single-stranded nucleic
acids of between 8
to 1000 nucleotides in length, for instance of between 10 and 800, more
preferably of
between 15 and 700, typically of between 20 and 500. It should be understood
that longer
probes may be used as well. A preferred probe of this invention is a single
stranded nucleic
acid molecule of between 8 to 500 nucleotides in length, which can
specifically hybridise to
a region of a BTBD9 gene or RNA that carries an alteration.
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A specific embodiment of this invention is a nucleic acid probe specific for
an altered (e.g.,
a mutated) BTBD9 gene or RNA, i.e., a nucleic acid probe that specifically
hybridises to
said altered BTBD9 gene or RNA and essentially does not hybridise to a BTBD9
gene or
RNA lacking said alteration. Specificity indicates that hybridisation to the
target sequence
generates a specific signal which can be distinguished from the signal
generated through
non-specific hybridisation. Perfectly complementary sequences are preferred to
design
probes according to this invention. It should be understood, however, that a
certain degree
of mismatch may be tolerated, as long as the specific signal may be
distinguished from
non-specific hybridisation.
Particular examples of such probes are nucleic acid sequences complementary to
a target
portion of the genomic region including the BTBD9 gene or RNA carrying a point
mutation as listed in Table 3A or Table 3B above. More particularly, the
probes can
comprise a sequence selected from the group consisting of SEQ ID Nos 3-22 or a
fragment
thereof comprising the SNP or a complementary sequence thereof
The sequence of the probes can be derived from the sequences of the BTBD9 gene
and
RNA as provided in the present application. Nucleotide substitutions may be
performed, as
well as chemical modifications of the probe. Such chemical modifications may
be
accomplished to increase the stability of hybrids (e.g., intercalating groups)
or to label the
probe. Typical examples of labels include, without limitation, radioactivity,
fluorescence,
luminescence, enzymatic labeling, etc.
The invention also concerns the use of a nucleic acid probe as described above
in a method
of detecting the presence of or predisposition to type 2 diabetes in a subject
or in a method
of assessing the response of a subject to a treatment of type 2 diabetes or an
associated
disorder.
Specific Ligand Binding
As indicated above, alteration in the BTBD9 gene locus may also be detected by
screening
for alteration(s) in BTBD9 polypeptide sequence or expression levels. In this
regard, a
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specific embodiment of this invention comprises contacting the sample with a
ligand
specific for a BTBD9 polypeptide and determining the formation of a complex.
Different types of ligands may be used, such as specific antibodies. In a
specific
embodiment, the sample is contacted with an antibody specific for a BTBD9
polypeptide
and the formation of an immune complex is determined. Various methods for
detecting an
immune complex can be used, such as ELISA, radioimmunoassays (RIA) and immuno-
enzymatic assays (IEMA).
Within the context of this invention, an antibody designates a polyclonal
antibody, a
monoclonal antibody, as well as fragments or derivatives thereof having
substantially the
same antigen specificity. Fragments include Fab, Fab'2, CDR regions, etc.
Derivatives
include single-chain antibodies, humanized antibodies, poly-functional
antibodies, etc.
An antibody specific for a BTBD9 polypeptide designates an antibody that
selectively
binds a BTBD9 polypeptide, namely, an antibody raised against a BTBD9
polypeptide or
an epitope-containing fragment thereof. Although non-specific binding towards
other
antigens may occur, binding to the target BTBD9 polypeptide occurs with a
higher affinity
and can be reliably discriminated from non-specific binding.
In a specific embodiment, the method comprises contacting a sample from the
subject with
(a support coated with) an antibody specific for an altered form of a BTBD9
polypeptide,
and determining the presence of an immune complex. In a particular embodiment,
the
sample may be contacted simultaneously, or in parallel, or sequentially, with
various
(supports coated with) antibodies specific for different forms of a BTBD9
polypeptide,
such as a wild type and various altered forms thereof.
The invention also concerns the use of a ligand, preferably an antibody, a
fragment or a
derivative thereof as described above, in a method of detecting the presence
of or
predisposition to type 2 diabetes in a subject, in particular in a subject
with obesity.
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In order to carry out the methods of the invention, one can employ diagnostic
kits
comprising products and reagents for detecting in a sample from a subject the
presence of
an alteration in the BTBD9 gene or polypeptide, in the BTBD9 gene or
polypeptide
expression, and/or in BTBD9 activity. Said diagnostic kit comprises any
primer, any pair of
primers, any nucleic acid probe and/or any ligand, preferably antibody,
described in the
present invention. Said diagnostic kit can further comprise reagents and/or
protocols for
performing a hybridization, amplification or antigen-antibody immune reaction.
The diagnosis methods can be performed in vitro, ex vivo or in vivo,
preferably in vitro or
ex vivo. They use a sample from the subject, to assess the status of the BTBD9
gene locus.
The sample may be any biological sample derived from a subject, which contains
nucleic
acids or polypeptides. Examples of such samples include fluids, tissues, cell
samples,
organs, biopsies, etc. Most preferred samples are blood, plasma, saliva,
urine, seminal fluid,
etc. The sample may be collected according to conventional techniques and used
directly
for diagnosis or stored. The sample may be treated prior to performing the
method, in order
to render or improve availability of nucleic acids or polypeptides for
testing. Treatments
include, for instant, lysis (e.g., mechanical, physical, chemical, etc.),
centrifugation, etc.
Also, the nucleic acids and/or polypeptides may be pre-purified or enriched by
conventional techniques, and/or reduced in complexity. Nucleic acids and
polypeptides
may also be treated with enzymes or other chemical or physical treatments to
produce
fragments thereof Considering the high sensitivity of the claimed methods,
very few
amounts of sample are sufficient to perform the assay.
As indicated, the sample is preferably contacted with reagents such as probes,
primers or
ligands in order to assess the presence of an altered BTBD9 gene locus.
Contacting may be
performed in any suitable device, such as a plate, tube, well, glass, etc. In
specific
embodiments, the contacting is performed on a substrate coated with the
reagent, such as a
nucleic acid array or a specific ligand array. The substrate may be a solid or
semi-solid
substrate such as any support comprising glass, plastic, nylon, paper, metal,
polymers and
the like. The substrate may be of various forms and sizes, such as a slide, a
membrane, a
bead, a column, a gel, etc. The contacting may be made under any condition
suitable for a
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complex to be formed between the reagent and the nucleic acids or polypeptides
of the
sample.
The finding of an altered BTBD9 polypeptide, RNA or DNA in the sample is
indicative of
5 the presence of an altered BTBD9 gene locus in the subject, which can be
correlated to the
presence, predisposition or stage of progression of type 2 diabetes. For
example, an
individual having a germ line BTBD9 mutation has an increased risk of
developing type 2
diabetes. The determination of the presence of an altered BTBD9 gene locus in
a subject
also allows the design of appropriate therapeutic intervention, which is more
effective and
10 customized.
Linka eg Disequilibirum
Once a first SNP has been identified in a genomic region of interest, more
particularly in
BTBD9 gene locus, the practitioner of ordinary skill in the art can easily
identify additional
15 SNPs in linkage disequilibrium with this first SNP. Indeed, any SNP in
linkage
disequilibrium with a first SNP associated with type 2 diabetes will be
associated with this
trait. Therefore, once the association has been demonstrated between a given
SNP and type
2 diabetes, the discovery of additional SNPs associated with this trait can be
of great
interest in order to increase the density of SNPs in this particular region.
Identification of additional SNPs in linkage disequilibrium with a given SNP
involves: (a)
amplifying a fragment from the genomic region comprising or surrounding a
first SNP
from a plurality of individuals; (b) identifying of second SNPs in the genomic
region
harboring or surrounding said first SNP; (c) conducting a linkage
disequilibrium analysis
between said first SNP and second SNPs; and (d) selecting said second SNPs as
being in
linkage disequilibrium with said first marker. Subcombinations comprising
steps (b) and (c)
are also contemplated.
Methods to identify SNPs and to conduct linkage disequilibrium analysis can be
carried out
by the skilled person without undue experimentation by using well-known
methods.
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These SNPs in linkage disequilibrium can also be used in the methods according
to the
present invention, and more particularly in the diagnosic methods according to
the present
invention.
For example, a linkage locus of Crohn's disease has been mapped to a large
region
spanning 18cM on chromosome 5q31 (Rioux et al., 2000 and 2001). Using dense
maps of
microsatellite markers and SNPs across the entire region, strong evidence of
linkage
disequilibrium (LD) was found. Having found evidence of LD, the authors
developed an
ultra-high-density SNP map and studied a denser collection of markers selected
from this
map. Multilocus analyses defined a single common risk haplotype characterised
by
multiple SNPs that were each independently associated using TDT. These SNPs
were
unique to the risk haplotype and essentially identical in their information
content by virtue
of being in nearly complete LD with one another. The equivalent properties of
these SNPs
make it impossible to identify the causal mutation within this region on the
basis of genetic
evidence alone.
Causal Mutation
Mutations in the BTBD9 gene which are responsible for type 2 diabetes may be
identified
by comparing the sequences of the BTBD9 gene from patients presenting type 2
diabetes
and control individuals. Based on the identified association of SNPs of BTBD9
and type 2
diabetes, the identified locus can be scanned for mutations. In a preferred
embodiment,
functional regions such as exons and splice sites, promoters and other
regulatory regions of
the BTBD9 gene are scanned for mutations. Preferably, patients presenting type
2 diabetes
carry the mutation shown to be associated with type 2 diabetes and controls
individuals do
not carry the mutation or allele associated with type 2 diabetes or an
associated disorder. It
might also be possible that patients presenting type 2 diabetes carry the
mutation shown to
be associated with type 2 diabetes with a higher frequency than controls
individuals.
The method used to detect such mutations generally comprises the following
steps:
amplification of a region of the BTBD9 gene comprising a SNP or a group of
SNPs
associated with type 2 diabetes from DNA samples of the BTBD9 gene from
patients
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presenting type 2 diabetes and control individuals; sequencing of the
amplified region;
comparison of DNA sequences of the BTBD9 gene from patients presenting type 2
diabetes
and control individuals; determination of mutations specific to patients
presenting type 2
diabetes.
Therefore, identification of a causal mutation in the BTBD9 gene can be
carried out by the
skilled person without undue experimentation by using well-known methods.
For example, the causal mutations have been identified in the following
examples by using
routine methods.
Hugot et al. (2001) applied a positional cloning strategy to identify gene
variants with
susceptibly to Crohn's disease in a region of chromosome 16 previously found
to be linked
to susceptibility to Crohn's disease. To refine the location of the potential
susceptibility
locus 26 microsatellite markers were genotyped and tested for association to
Crohn's
disease using the transmission disequilibrium test. A borderline significant
association was
found between one allele of the microsatellite marker D16S136. Eleven
additional SNPs
were selected from surrounding regions and several SNPs showed significant
association.
SNP5-8 from this region were found to be present in a single exon of the
NOD2/CARD 15
gene and shown to be non-synonymous variants. This prompted the authors to
sequence the
complete coding sequence of this gene in 50 CD patients. Two additional non-
synonymous
mutations (SNP12 and SNP13) were found. SNP13 was most significant associated
(p=6x10-6) using the pedigree transmission disequilibrium test. In another
independent
study, the same variant was found also by sequencing the coding region of this
gene from
12 affected individuals compared to 4 controls (Ogura et al., 2001). The rare
allele of
SNP 13 corresponded to a 1-bp insertion predicted to truncate the NOD2/CARD 15
protein.
This allele was also present in normal healthy individuals, albeit with
significantly lower
frequency as compared to the controls.
Similarly, Lesage et al. (2002) performed a mutational analyses of CARD15 in
453 patients
with CD, including 166 sporadic and 287 familial cases, 159 patients with
ulcerative colitis
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(UC), and 103 healthy control subjects by systematic sequencing of the coding
region. Of
67 sequence variations identified, 9 had an allele frequency >5% in patients
with CD. Six
of them were considered to be polymorphisms, and three (SNP12-R702W, SNP8-
G908R,
and SNP13-1007fs) were confirmed to be independently associated with
susceptibility to
CD. Also considered as potential disease-causing mutations (DCMs) were 27 rare
additional mutations. The three main variants (R702W, G908R, and 1007fs)
represented
32%, 18%, and 31%, respectively, of the total CD mutations, whereas the total
of the 27
rare mutations represented 19% of DCMs. Altogether, 93% of the mutations were
located
in the distal third of the gene. No mutations were found to be associated with
UC. In
contrast, 50% of patients with CD carried at least one DCM, including 17% who
had a
double mutation.
The present invention demonstrates the correlation between type 2 diabetes and
the BTBD9
gene locus. The invention thus provides a novel target of therapeutic
intervention. Various
approaches can be contemplated to restore or modulate the BTBD9 activity or
function in a
subject, particularly those carrying an altered BTBD9 gene locus. Supplying
wild-type
function to such subjects is expected to suppress phenotypic expression of
type 2 diabetes
in a pathological cell or organism. The supply of such function can be
accomplished
through gene or protein therapy, or by administering compounds that modulate
or mimic
BTBD9 polypeptide activity (e.g., agonists as identified in the above
screening assays).
Other molecules with BTBD9 activity (e.g., peptides, drugs, BTBD9 agonists, or
organic
compounds) may also be used to restore functional BTBD9 activity in a subject
or to
suppress the deleterious phenotype in a cell.
Restoration of functional BTBD9 gene function in a cell may be used to prevent
the
development of type 2 diabetes or to reduce progression of said diseases. Such
a treatment
may suppress the type 2 diabetes -associated phenotype of a cell, particularly
those cells
carrying a deleterious allele.
Further aspects and advantages of the present invention will be disclosed in
the following
experimental section, which should be regarded as illustrative and not
limiting the scope of
the present application.
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EXAMPLES
1. GenomeHIP platform to identify the chromosome 6 susceptibili gene
The GenomeHIP platform was applied to allow rapid identification of a TYPE 2
DIABETES susceptibility gene.
Briefly, the technology consists of forming pairs from the DNA of related
individuals. Each
DNA is marked with a specific label allowing its identification. Hybrids are
then formed
between the two DNAs. A particular process (W000/53802) is then applied that
selects all
fragments identical-by-descent (IBD) from the two DNAs in a multi step
procedure. The
remaining IBD enriched DNA is then scored against a BAC clone derived DNA
microarray
that allows the positioning of the IBD fraction on a chromosome.
The application of this process over many different families results in a
matrix of IBD
fractions for each pair from each family. Statistical analyses then calculate
the minimal IBD
regions that are shared between all families tested. Significant results (p-
values) are
evidence for linkage of the positive region with the trait of interest (here
TYPE 2
DIABETES). The linked interval can be delimited by the two most distant clones
showing
significant p-values.
In the present study, 88 diabetes (type 2 diabetes) relative pairs with a BMI
superior to 27,
were submitted to the GenomeHIP process. The resulting IBD enriched DNA
fractions
were then labelled with Cy5 fluorescent dyes and hybridised against a DNA
array
consisting of 2263 BAC clones covering the whole human genome with an average
spacing
of 1.2 Mega base pairs. Non-selected DNA labelled with Cy3 was used to
normalize the
signal values and compute ratios for each clone. Clustering of the ratio
results was then
performed to determine the IBD status for each clone and pair.
By applying this procedure, several BAC clones spanning approximately 4.5 Mega
bases
in the region on chromosome 6 were identified, that showed significant
evidence for
linkage to type 2 diabetes (p=2.80E-08).
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2. Identification of an TYPE 2 DIABETES susceptibility gene on chromosome 6
By screening the aforementioned 4.5 Megabases in the linked chromosomal
region, the
5 inventors identified the BTBD9 gene as a candidate for type 2 diabetes. This
gene is indeed
present in the critical interval, with evidence for linkage delimited by the
clones outlined
above.
Table 4: Linkage results for chromosome 6 in the BTBD9 locus: Indicated is the
region
10 correspondent to BAC clones with evidence for linkage. The start and stop
positions of the
clones correspond to their genomic location based on NCBI Build 36 sequence
respective
to the start of the chromosome (p-ter).
Clone Start Stop % of IBD p-value
IG-Name informative sharing
(Origin name) pairs (%)
BACA7ZA09
(RP 11- 0.62
497A24) 33 315 824 33 525 149 98 % 0.31
BACA23ZF08
(CTD- 0.77
2121012) 36 721 951 36 864 626 93 % 1.0 E-04
BACA23ZE08
(CTD2118F18) 36 921 630 36 921 737 94% 0.78 1.3 E-05
BACA23ZH11
(CTD- 0.82
2122A15) 37243418 37444519 75% 5.3E-06
BACA23ZF11
(CTD- 0.84
2048M16) 37 341 301 37 341 492 94% 2.8 E-08
BACA23ZG11
(CDT-2097F8) 37 355 913 37 356 015 86% 0.83 2.7 E-07
BACA7ZBO3
(RP11-426L3) 41 255 967 41 471 612 98 % 0.73 0.0013
BACA5ZH08
(RP11-328M4) 43 123 957 43 294 973 100% 0.69 0.013
Taken together, the linkage results provided in the present application,
identifying the
human BTBD9 gene in the critical interval of genetic alterations linked to
TYPE 2
DIABETES on chromosome 6.
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3. Association study
Single SNP and haplotype analysis :
Differences in allele distributions between cases and controls were screened
for all SNPs.
Three cases and controls sample have been used in the analysis:
- Sample I corresponding on 528 TYPE 2 DIABETES cases versus 528 normo-
glycemic controles;
- Sample II corresponding on 341 TYPE 2 DIABETES with BMI 27 versus 364
normo-glycemic Controls with BMI < 27;
- sample III corresponding on 211 TYPE 2 DIABETES with BMI 30 versus 251
normo-glycemic Controls with BMI < 25. Association analyses have been
conducted using COCAPHASE v2.404 software from the UNPHASED suite of
programs.
The method is based on likelihood ratio tests in a logistic model:
log( p ) = mu + y,`beta,.x,
1-p
where p is the probability of a chromosome being a "case" rather than a
"control", x; are
variables which represent the allele or haplotypes in some way depending upon
the
particular test, and mu and beta; are coefficients to be estimated. Reference
for this
application of log-linear models is Cordell & Clayton, AJHG (2002)
In cases of uncertain haplotype, the method for case-control sample is a
standard
unconditional logistic regression identical to the model-free method T5 of
EHPLUS (Zhao
et al Hum Hered (2000) and the log-linear modelling of Mander. The beta; are
log odds
ratios for the haplotypes. The EM algorithm is used to obtain maximum
likelihood
frequency estimates.
SNP Genotype analysis:
Differences in genotype distributions between cases and controls were screened
for all
SNPs. For each SNPs, three genotype is possible genotype A A, genotype A a and
genotype
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a a where a represented the associate allele of the SNP with TYPE 2 DIABETES.
Dominant transmission model for associated allele (a) were tested by counting
A a and a a
genotype together. The statistic test was carried out using the standard Chi-
square
independence test with 1 df (genotype distribution, 2x2 table). Recessive
transmission
model for associated allele (a) were tested by counting A A and A a genotype
together. The
statistic test was carried out using the standard Chi-square independence test
with 1 df
(genotype distribution, 2x2 table). Additive transmission model for associated
allele (a)
were tested using the standard Chi-square independence test with 2 df
(genotype
distribution, 2x3 table).
3.1 - Association with single SNPs, allele distribution statistics test:
a - Table 4:528 Diabetes versus 528 normo-glycemic Controls: sample I
SNP dbSNP Allele Cases Frequence Controls Frequence p-values
identity reference in Cases in Controls
87 rs12525647 1 857 0.82 912 0.88
2 187 0.18 126 0.12 0.000219
b - Table 5: 341 Diabetes with BMI - 27 vs. 364 normo-glycemic Controls with
BMI <
27: sample II
SNP dbSNP Allele Cases Frequence Controls Frequence p-values
identity reference in Cases in Controls
87 rs12525647 1 549 0.81 638 0.90
2 127 0.19 74 0.10 8.21*10'6
88 rs2814889 1 459 0.68 450 0.62
2 215 0.32 272 0.38 0.02358
92 rs1739629 1 466 0.69 452 0.63
2 206 0.31 266 0.37 0.01181
94 rs 1781738 1 475 0.71 461 0.64
2 193 0.29 255 0.36 0.007487
c - Table 6: 211 Diabetes with BMI 30 vs. 251 normo-glycemic Controls with BMI
<
25: sample III
SNP dbSNP Allele Cases Frequence Controls Frequence p-values
identity reference in Cases in Controls
87 rs12525647 1 342 0.81 445 0.90
2 78 0.19 51 0.10 0.000329
88 rs2814889 1 291 0.70 309 0.62
2 127 0.30 187 0.38 0.02001
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92 rs 1739629 1 291 0.70 311 0.63
2 127 0.30 183 0.37 0.03398
94 rs1781738 1 293 0.71 316 0.64
2 119 0.29 176 0.36 0.02744
3.2 - Association with single SNPs, genotype distributions statistics test:
a - 528 Diabetes versus 528 normo-glycemic Controls:
ADDITIVE Model:
SNP dbSNP Sample Genotype Genotype Genotype Yates p-values
identity reference 1 1 1 2 2 2 Statistic
(df = 2)
87 rs12525647 cases 350 157 15
controls 402 108 9 14.15 0.00085
DOMINANT Model:
SNP dbSNP Sample Genotype Genotype Yates p-values
identity reference 1 1 1 2+ 2 2 Statistic
(df = 1)
87 rs12525647 cases 350 172
controls 402 117 13.54 0.00023
b - 341 Diabetes with BMI _ 27 vs. 364 normo-glycemic Controls with BMI < 27:
ADDITIVE Model:
SNP dbSNP Sample Genotype Genotype Genotype Yates p-values
identity reference 1 1 1 2 2 2 Statistic
df=2
87 rs12525647 cases 221 107 10
controls 287 64 5 20.6 3.00*10'5
SNP dbSNP Sample Genotype Genotype Genotype Yates p-values
identity reference 1 1 1 2 2 2 Statistic
(df = 2)
92 rs1739629 cases 155 156 25
controls 140 172 47 7.51 0.02337
SNP dbSNP Sample Genotype Genotype Genotype Yates p-values
identity reference 1 1 1 2 2 2 Statistic
(df = 2)
94 rs1781738 cases 159 157 18
controls 146 169 43 10.42 0.00546
DOMINANT Model for allele 2:
SNP dbSNP Sample Genotype Genotype Yates p-values
identity reference 1 1 1 2+ 2 2 Statistic
(df = 1)
87 rs12525647 cases 221 117
controls 287 69 19.74 1.00*10.5
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DOMINANT Model for allele 1:
SNP dbSNP Sample Genotype Genotype Yates p-values
identity reference 1 1+1 2 22 Statistic
(df = 1)
92 rs1739629 cases 311 25
controls 312 47 5.38 0.02041
DOMINANT Model for allele 1:
SNP dbSNP Sample Genotype Genotype Yates p-values
identity reference 1 1+ 1 2 22 Statistic
(df = 1)
94 rs1781738 cases 316 18
controls 315 43 8.62 0.00332
c - 211 Diabetes with BMI _ 30 vs. 251 normo-glycemic Controls with BMI < 25:
ADDITIVE Model:
SNP dbSNP Sample Genotype Genotype Genotype Yates p-values
identity reference 1 1 1 2 2 2 Statistic
(df = 2)
87 rs12525647 cases 139 64 7
controls 200 45 3 12.82 0.00164
SNP dbSNP Sample Genotype Genotype Genotype Yates p-values
identity reference 1 1 1 2 2 2 Statistic
(df = 2)
88 rs2814889 cases 97 97 15
controls 94 121 33 6.16 0.04605
SNP dbSNP Sample Genotype Genotype Genotype Yates p-values
identity reference 1 1 1 2 2 2 Statistic
(df = 2)
94 rs1781738 cases 97 99 10
controls 98 120 28 7.06 0.0293
DOMINANT Model for allele 2:
SNP dbSNP Sample Genotype Genotype Yates p-values
identity reference 1 1 1 2+ 2 2 Statistic
(df = 1)
87 rs12525647 cases 139 71
controls 200 48 11.61 0.00065
DOMINANT Model for allele 1:
SNP dbSNP Sample Genotype Genotype Yates p-values
identity reference 1 1+1 2 22 Statistic
(df = 1)
88 rs2814889 cases 194 15
controls 215 33 3.9 0.04816
DOMINANT Model for allele 1:
SNP dbSNP Sample Genotype Genotype Yates p-values
identity reference 1 1+ 1 2 22 Statistic
df=1
94 rs1781738 cases 196 10
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I I controls 218 28 5.39 0.02031
3.3 - Association with haplotypes :
Sample SNP used in Alleles Frequenc Frequency p-value
haplotype composing y of of
haplotype haplotype haplotype
in cases in controls
SAMPLEI 87 - 88 - 92 - 94 2-1-1-1 0.1801 0.122 0.0002632
SAMPLEII 87 - 88 - 92 - 94 2-1-1-1 0.1884 0.102 5.893 * 10-
SAMPLE III 87 - 88 - 92 - 94 2-1-1-1 0.1822 0.1004 0.0005064
5
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31
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