Note : Les descriptions sont présentées dans la langue officielle dans laquelle elles ont été soumises.
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HUMAN DIABETES SUSCEPTIBILITY SEMA6D 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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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
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genetically determined abnormalities of insulin action. The metabolic
abnormalities
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/m') 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.
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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
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
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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
5 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
interest in order to adapt the lifestyle of people at risk and to prevent the
onset of the
disease.
SUMMARY OF THE INVENTION
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 SEMA6D gene locus in a biological sample of said subject.
Specifically the invention pertains to single nucleotide polymorphisms in the
SEMA6D
gene on chromosome 15 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 15q21.1-q21.2. The
curve
depict the linkage results for the GenomeHip procedure in the region. A total
of 7 Bac
clones on human chromosome 15 ranging from position cen-44 511 375 to 49 515
339-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 BACA23ZG08 (p-value
5.9E-09).
The whole linkage region encompasses a region from 45 554 908 base pairs to 46
656 140
base pairs on human chromosome 15. The p-value less to 2x10-5 corresponding to
the
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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 SEMA6D 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 GenomeHIP process. This
process led
to the identification of particular identical-by-descent (IBD) fragments in
said populations
that are altered in diabetic subjects with a BMI > 27 kg/m2 . By screening of
the IBD
fragments, the inventors identified the SEMA6D gene as a candidate for type 2
diabetes.
SNPs of the SEMA6D 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).
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Within the context of this invention, the SEMA6D gene locus designates all
SEMA6D
sequences or products in a cell or organism, including SEMA6D coding
sequences,
SEMA6D non-coding sequences (e.g., introns), SEMA6D regulatory sequences
controlling
transcription and/or translation (e.g., promoter, enhancer, terminator, etc.),
as well as all
corresponding expression products, such as SEMA6D RNAs (e.g., mRNAs) and
SEMA6D
polypeptides (e.g., a pre-protein and a mature protein). The SEMA6D gene locus
also
comprise surrounding sequences of the SEMA6D gene which include SNPs that are
in
linkage disequilibrium with SNPs located in the SEMA6D gene.
As used in the present application, the term "SEMA6D gene" designates
semaphorin 6D,
also known as FLJ11598, KIAA1479, AB040912, AF389430. It is located on
chromosome
15, at position 15q21.1 (nucleotides 45797978-45853711 on build 35; HOMIM:
609295;
UniGene: Hs.511265).
Semaphorins are a large family, including both secreted and membrane
associated proteins,
many of which have been implicated as inhibitors or chemorepellents in axon
pathfinding,
fasciculation and branching, and target selection. All semaphorins possess a
semaphorin
(Sema) domain and a PSI domain (found in plexins, semaphorins and integrins)
in the N-
terminal extracellular portion. Additional sequence motifs C-terminal to the
semaphorin
domain allow classification into distinct subfamilies. Results demonstrate
that
transmembrane semaphorins, like the secreted ones, can act as repulsive axon
guidance
cues. This gene encodes a class 6 vertebrate transmembrane semaphorin that
demonstrates
alternative splicing. Six transcript variants have been identified and
expression of the
distinct encoded isoforms is thought to be regulated in a tissue- and
development-
dependent manner.
- Semaphorin 6D isoform 1 precursor (mRNA: NM020858 or SEQ ID NO: 1, 5923 bp ;
Protein: NP065909 or SEQ ID NO:2, 1011 aa ) uses an alternative splice site on
one exon
and lacks two internal exons, compared to variant 4. The encoded isoform 1 is
missing an
internal region compared to isoform 4 and contains an internal segment unique
to this
isoform.
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- Semaphorin 6D isoform 2 precursor (mRNA: NM153616 or SEQ ID NO: 3, 5884 bp;
Protein: NP705869 or SEQ ID NO: 4, 998 aa) lacks two internal exons compared
to
variant 4. The encoded isoform (2) is missing an internal segment relative to
isoform 4.
- Semaphorin 6D isoform 3 precursor (mRNA: NM153617 or SEQ ID NO: 5, 5941 bp;
Protein: NP705870 or SEQ ID NO: 6, 1017 aa) lacks an internal exon, compared
to
variant 4. The encoded isoform (3) is missing an internal segment relative to
isoform 4.
- Semaphorin 6D isoform 4 precursor (mRNA: NM153618 or SEQ ID NO: 7, 6109 bp;
Protein: NP705871 or SEQ ID NO: 8, 1073 aa) is the longest transcript and
encodes the
longest isoform (4).
- Semaphorin 6D isoform 5 precursor (mRNA: NM153619 or SEQ ID NO: 9, 5019 bp;
Protein: NP705872 or SEQ ID NO: 10, 597 aa) lacks an internal exon and uses an
alternative splice site on another exon, compared to variant 4. The encoded
isoform (5) is
missing an internal segment and has a unique C-terminus relative to isoform 4.
- Semaphorin 6D isoform 6 precursor (mRNA: NM024966 or SEQ ID NO: 11, 2290 bp,
Protein: NP079242 or SEQ ID NO: 12, 476 aa) represents the shortest transcript
and
encodes the shortest isoform (6). Lacking a PSI domain and a predicted
transmembrane
domain, isoform 6 is considered a putative secreted protein.
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 SEMA6D 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 SEMA6D 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 SEMA6D 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 SEMA6D 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 SEMA6D polypeptide designates any protein or polypeptide encoded by a SEMA6D
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 SEMA6D polypeptide
comprises
all or part of SEQ ID NO: 2.
DIAGNOSIS
The invention now provides diagnosis methods based on a monitoring of the
SEMA6D
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 SEMA6D 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
SEMA6D gene locus in said sample. The presence of said alteration is
indicative of the
5 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 SEMA6D gene locus in said sample is detected through the
genotyping of
a sample.
10 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. In a preferred embodiment, said SNP is selected from
the group
consisting of SNP61, SNP63, SNP68, and SNP70.
Other SNP(s), as listed in Table 3B, may be informative too.
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12
Preferably the SNP is allele A of SNP63.
More preferably, said haplotype comprises or consists of several SNPs selected
from the
group consisting of SNP, SNP63, SNP67, SNP68, more particularly the following
haplotype:
2 - 1- 1(i.e. SNP63 is A, SNP67 is A and SNP68 is T).
The invention further provides a method for preventing throug prophylactic
treatment type
2 diabetes in a subject, more particularly a subject with obesity, comprising
detecting the
presence of an alteration in the SEMA6D 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 SEMA6D gDNA, RNA or
polypeptide.
Optionally, the detection is performed by sequencing all or part of the SEMA6D
gene or by
selective hybridisation or amplification of all or part of the SEMA6D gene.
More
preferably a SEMA6D gene specific amplification is carried out before the
alteration
identification step.
An alteration in the SEMA6D 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 SEMA6D gene locus alteration may result in the creation of stop
codons,
frameshift mutations, amino acid substitutions, particular RNA splicing or
processing,
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product instability, truncated polypeptide production, etc. The alteration may
result in the
production of a SEMA6D polypeptide with altered function, stability, targeting
or structure.
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 SEMA6D gene locus is selected from a point mutation, a deletion and an
insertion in
the SEMA6D 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
SEMA6D gene
and certain haplotypes comprising SNP in the SEMA6D 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
SEMA6D
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 SEMA6D 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 SEMA6D
polypeptide expression. Altered SEMA6D polypeptide expression includes the
presence of
an altered polypeptide sequence, the presence of an altered quantity of SEMA6D
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 SEMA6D gene or RNA expression or sequence, including sequencing,
hybridisation, amplification and/or binding to specific ligands (such as
antibodies). Other
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suitable methods include allele-specific oligonucleotide (ASO), allele-
specific
amplification, Southern blot (for DNAs), Northern blot (for RNAs), single-
stranded
conformation analysis (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 SEMA6D 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 SEMA6D 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 SEMA6D gene or,
more
preferably, on specific domains thereof, typically those known or suspected to
carry
deleterious mutations or other alterations.
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Amplification
Amplification is based on the formation of specific hybrids between
complementary
nucleic acid sequences that serve to initiate nucleic acid reproduction.
5
Amplification may be performed according to various techniques known in the
art, such as
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.
10 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 SEMA6D gene or
locus are
able to specifically hybridize with a portion of the SEMA6D gene locus that
flank a target
15 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 SEMA6D target region comprising SNPs as
identified
in Table 3A or Table 3B may be designed based on the sequence of Seq ID No 1
or on the
genomic sequence of SEMA6D. In a particular embodiment, primers may be
designed
based on the sequence of SEQ ID Nos 13-24.
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 SEMA6D 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.
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Selective hybridization
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 SEMA6D 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 SEMA6D 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 SEMA6D 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 SEMA6D 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)
SEMA6D gene or RNA, and which is suitable for detecting polynucleotide
polymorphisms
associated with SEMA6D alleles which predispose to or are associated with
obesity or an
associated disorder. Probes are preferably perfectly complementary to the
SEMA6D 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
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stranded nucleic acid molecule of between 8 to 500 nucleotides in length,
which can
specifically hybridise to a region of a SEMA6D gene or RNA that carries an
alteration.
A specific embodiment of this invention is a nucleic acid probe specific for
an altered (e.g.,
a mutated) SEMA6D gene or RNA, i.e., a nucleic acid probe that specifically
hybridises to
said altered SEMA6D gene or RNA and essentially does not hybridise to a SEMA6D
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 SEMA6D 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 13-24 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 SEMA6D
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.
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Specific Ligand Binding
As indicated above, alteration in the SEMA6D gene locus may also be detected
by
screening for alteration(s) in SEMA6D polypeptide sequence or expression
levels. In this
regard, a specific embodiment of this invention comprises contacting the
sample with a
ligand specific for a SEMA6D 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 SEMA6D
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 SEMA6D polypeptide designates an antibody that
selectively
binds a SEMA6D polypeptide, namely, an antibody raised against a SEMA6D
polypeptide
or an epitope-containing fragment thereof. Although non-specific binding
towards other
antigens may occur, binding to the target SEMA6D 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 SEMA6D
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 SEMA6D
polypeptide,
such as a wild type and various altered forms thereof.
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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.
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 SEMA6D gene or polypeptide, in the SEMA6D gene or
polypeptide
expression, and/or in SEMA6D 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
SEMA6D 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 SEMA6D 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
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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
5 complex to be formed between the reagent and the nucleic acids or
polypeptides of the
sample.
The finding of an altered SEMA6D polypeptide, RNA or DNA in the sample is
indicative
of the presence of an altered SEMA6D gene locus in the subject, which can be
correlated to
10 the presence, predisposition or stage of progression of type 2 diabetes.
For example, an
individual having a germ line SEMA6D mutation has an increased risk of
developing type
2 diabetes. The determination of the presence of an altered SEMA6D gene locus
in a
subject also allows the design of appropriate therapeutic intervention, which
is more
effective and customized.
Linka e_ Disequilibirum
Once a first SNP has been identified in a genomic region of interest, more
particularly in
SEMA6D gene locus, the practitioner of ordinary skill in the art can easily
identify
additional 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.
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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.
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 SEMA6D gene which are responsible for type 2 diabetes may be
identified by comparing the sequences of the SEMA6D gene from patients
presenting type
2 diabetes and control individuals. Based on the identified association of
SNPs of
SEMA6D 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 SEMA6D 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
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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 SEMA6D gene comprising a SNP or a group of
SNPs
associated with type 2 diabetes from DNA samples of the SEMA6D gene from
patients
presenting TYPE 2 DIABETES and control individuals; sequencing of the
amplified
region; comparison of DNA sequences of the SEMA6D 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 SEMA6D 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
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SNP13 corresponded to a 1-bp insertion predicted to truncate the NOD2/CARD15
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
(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
SEMA6D gene locus. The invention thus provides a novel target of therapeutic
intervention. Various approaches can be contemplated to restore or modulate
the SEMA6D
activity or function in a subject, particularly those carrying an altered
SEMA6D 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 SEMA6D polypeptide activity (e.g., agonists
as
identified in the above screening assays).
Other molecules with SEMA6D activity (e.g., peptides, drugs, SEMA6D agonists,
or
organic compounds) may also be used to restore functional SEMA6D activity in a
subject
or to suppress the deleterious phenotype in a cell.
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Restoration of functional SEMA6D 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.
EXAMPLES
1. GenomeHIP platform to identify the chromosome 15 susceptibility 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.
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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
5 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 1.1 Mega
bases
10 in the region on chromosome 15 were identified, that showed significant
evidence for
linkage to NIDDM (p=5.9E-09).
2. Identification of an TYPE 2 DIABETES susceptibility gene on chromosome 15
15 By screening the aforementioned 1.1 Megabases in the linked chromosomal
region, the
inventors identified the SEMA6D 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.
20 Table 4: Linkage results for chromosome 15 in the SEMA6D locus: Indicated
is the region
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).
Human Clone Start Stop % of IBD p-value
chrom. IG-Name informative sharing
(Origin name) pairs (%)
15 BACA2ZA02
(RP11-81G13) 44.511.375 44.668.306 99.0% 0.74 0.0011
15 BACA8ZG01
(RP11-552E10) 45.554.908 45.746.131 89.0% 0.82 7.7E-7
15 BACA23ZC04
(none) 46.363.021 46.503.672 97.0 % 0.80 2.4E-6
15 BACA23ZHO8
(none) 46.363.662 46.523.276 90.0 % 0.82 4.3E-7
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15 BACA23ZG08
(CTD-2013016) 46.400.462 46.492.459 89.0 % 0.85 5.9E-9
15 BACA7ZF12
(RP11-498N3) 46.559.645 46.656.140 85.0% 0.83 6.6E-7
15 BACA8ZA04
(RP11-305A12) 49.328.195 49.515.339 100.0% 0.67 0.043
Taken together, the linkage results provided in the present application,
identifying the
human SEMA6D gene in the critical interval of genetic alterations linked to
type 2 diabetes
on chromosome 15.
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 ) = inu + Lbeta,.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)
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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
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 freguencies statistics test:
a - 528 Diabetes versus 528 normo-glycemic Controls: sample I
SNP dbSNP Allele Cases Frequence Controls Frequence p-values
identity reference in Cases in Controls
63 rs869731 1 528 0.54 633 0.61
2 444 0.46 391 0.39 0.00122
b - 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
61 rs1347473 1 597 0.89 601 0.84
2 75 0.11 113 0.16 0.01094
63 rs869731 1 342 0.54 438 0.62
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2 290 0.46 272 0.38 0.004982
68 rs765 1 360 0.54 340 0.48
2 310 0.46 372 0.52 0.02626
c - 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
63 rs869731 1 231 0.56 236 0.48
2 185 0.44 252 0.52 0.03149
70 rs518412 1 265 0.63 275 0.56
2 155 0.37 213 0.44 0.03885
3.2 - Association with sin0e SNPs, 1!enotype 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)
63 rs869731 cases 161 206 119
controls 189 255 71 18.75 8.00*10'5
RECESSIVE Model for allele 2:
SNP dbSNP Sample Genotype Genotype Yates p-values
identity reference 1 1 1 2+ 2 2 Statistic
(df = 1)
63 rs869731 cases 367 119
controls 444 71 17.92 2.00*10"5
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)
61 rs1347473 cases 264 69 3
controls 253 95 9 6.73 0.03463
SNP dbSNP Sample Genotype Genotype Genotype Yates p-values
identity reference 1 1 1 2 2 2 Statistic
(df = 2)
63 rs869731 cases 104 134 78
controls 136 166 53 10.22 0.00604
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RECESSIVE Model for allele 1:
SNP dbSNP Sample Genotype Genotype Yates p-values
identity reference 1 1 1 2+ 2 2 Statistic
(df = 1)
61 rs1347473 cases 264 72
controls 253 104 5.02 0.02503
RECESSIVE Model for allele 2:
SNP dbSNP Sample Genotype Genotype Yates p-values
identity reference 1 1+1 2 22 Statistic
df=1
63 rs869731 cases 238 78
controls 302 53 9.51 0.00204
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
Sample I 63 - 67 2-1 0.17 0.11 0.0007102
Sample Il 63 - 67 2-1 0.17 0.11 0.000853
SampleIll 63-67 2-1 0.16 0.11 0.01732
Sample SNP used in Alleles Frequenc Frequency p-value
haplotype composing y of of
haplotype haplotype haplotype
in cases in controls
SampleI 63-68 2-1 0.14 0.08 1.95*10
Sample Il 63 - 68 2-1 0.14 0.07 4.94*10
SampleIll 63-68 2-1 0.13 0.07 0.003114
Sample SNP used in Alleles Frequenc Frequency p-value
haplotype composing y of of
haplotype haplotype haplotype
in cases in controls
Sample l 63 - 67 - 68 2- 1- 1 0.14 0.081 2.7*10
Sample Il 63 - 67 - 68 2- 1- 1 0.14 0.07 5.8*10
Sample Ill 63 - 67 - 68 2- 1- 1 0.13 0.07 0.003821
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REFERENCES
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