The

spectrum

of

ATM

missense

variants

and

their

contribution

to

contralateral

breast

cancer

Heterozygous

carriers

of

ATM

mutations

are

at

increased

risk

of

breast

cancer

In

this

case-control

study

we

evaluated

the

significance

of

germline

ATM

missense

variants

to

the

risk

of

contralateral

breast

cancer

-LRB-

CBC

-RRB-

We

have

determined

the

spectrum

and

frequency

of

ATM

missense

variants

in

breast

cancer

patients

diagnosed

before

age

including

patients

who

subsequently

developed

CBC

Twenty-one

per

cent

of

the

women

with

unilateral

breast

cancer

and

of

the

women

with

CBC

had

at

least

one

ATM

germline

missense

variant

indicating

no

significant

difference

in

variant

frequency

between

these

two

groups

We

have

found

that

carriers

of

an

ATM

missense

mutation

who

were

treated

with

radiotherapy

for

the

first

breast

tumour

developed

their

second

tumour

on

average

in

a

interval

compared

to

a

mean

interval

for

those

CBC

patients

who

neither

received

RT

nor

carried

a

germline

variant

-LRB-

p

-RRB-

Our

results

indicate

that

the

presence

of

ATM

variants

does

not

have

a

major

impact

on

the

overall

risk

of

CBC

However

the

combination

of

RT

and

-LRB-

certain

-RRB-

ATM

missense

variants

seems

to

accelerate

tumour

development

Introduction

Homozygous

or

compound

heterozygous

germline

mutations

in

the

ATM

gene

cause

the

autosomal

recessive

disorder

ataxia-telangiectasia

-LRB-

A-T

-RRB-

This

progressive

neurological

childhood

disease

is

characterized

by

cerebellar

degeneration

immunological

defects

extreme

sensitivity

for

ionising

radiation

and

increased

risk

for

cancers

particularly

lymphomas

-LSB-

-RSB-

ATM

mutations

identified

in

A-T

families

can

be

classified

in

three

categories

truncating

mutations

mutations

that

lead

to

some

expression

of

mutant

protein

that

lacks

kinase

activity

and

missense

mutations

with

reduced

kinase

activity

-LRB-

-RRB-

Heterozygous

pathogenic

ATM

mutation

carriers

of

the

general

population

do

not

display

the

symptoms

observed

in

A-T

patients

Several

epidemiological

studies

have

consistently

shown

elevated

rates

of

breast

cancer

among

female

blood

relatives

of

patients

with

A-T

-LSB-

-RSB-

Thompson

et

al.

have

shown

that

the

overall

relative

risk

in

carriers

was

-LSB-

confidence

interval

-LRB-

CI

-RRB-

-RSB-

compared

to

the

general

population

and

-LRB-

CI

-RRB-

in

those

younger

that

age

A

large

review

showed

that

ATM

mutations

are

more

frequent

in

breast

cancer

patients

selected

on

the

basis

of

a

family

history

of

breast

cancer

than

in

unselected

patients

-LSB-

-RSB-

Besides

pathogenic

ATM

mutations

a

large

number

of

ATM

variants

-LRB-

common

polymorphisms

and

unclassified

variants

-RRB-

have

been

described

which

were

found

in

cancer

patients

as

well

as

in

the

general

population

It

has

been

hypothesized

that

the

cancer

risk

among

ATM

heterozygotes

might

be

related

to

mutation

type

suggesting

that

particularly

missense

mutations

are

associated

with

an

increased

risk

-LSB-

-RSB-

However

two

recent

studies

by

Thompson

et

al.

and

Renwick

et

al.

showed

that

pathogenic

ATM

mutations

that

cause

A-T

are

breast

cancer

susceptibility

alleles

-LSB-

-RSB-

This

argues

against

the

hypothesis

that

missense

rather

that

truncating

are

associated

with

breast

cancer

Women

with

breast

cancer

have

in

general

a

three

to

fourfold

increased

risk

of

developing

a

new

primary

cancer

in

the

opposite

breast

-LSB-

-RSB-

The

contralateral

breast

cancer

-LRB-

CBC

-RRB-

risk

might

be

explained

by

the

same

genetic

and

hormonal

factors

that

caused

the

first

breast

cancer

Treatment

related

factors

e.g.

radiotherapy

for

primary

breast

cancer

may

also

contribute

to

the

development

of

cancer

in

the

contralateral

breast

-LSB-

-RSB-

-LRB-

our

own

data

manuscript

under

review

-RRB-

To

evaluate

whether

germline

ATM

missense

variants

are

significantly

associated

with

CBC

risk

-LRB-

results

regarding

ATM

truncating

mutations

are

reported

elsewhere

-RRB-

and

whether

treatment

modifies

this

risk

we

conducted

a

case-control

study

in

which

we

assessed

the

ATM

missense

mutation

spectrum

and

frequency

in

women

who

developed

their

first

breast

cancer

before

age

with

and

without

a

second

primary

breast

cancer

Methods

Patients

The

consecutive

breast

cancer

patients

included

in

this

study

were

all

selected

from

the

hospital

tumour

registries

of

The

Netherlands

Cancer

Institute

Amsterdam

-LRB-

NKI-AVL

-RRB-

or

The

Dr.

Daniel

den

Hoed

Cancer

Center/Erasmus

Medical

Center

Rotterdam

-LRB-

DDHK

-RRB-

Of

all

patients

that

were

invited

to

participate

we

achieved

an

response

rate

The

breast

cancer

patients

were

included

if

their

-LRB-

first

-RRB-

breast

cancer

was

diagnosed

before

age

-LRB-

n

-RRB-

For

CBC

we

required

an

interval

of

at

least

year

-LRB-

n

-RRB-

The

unilateral

breast

cancer

patients

-LRB-

UBC

-RRB-

patients

all

had

to

be

disease-free

-LRB-

of

a

second

breast

cancer

-RRB-

for

at

least

years

The

first

CBC

patients

were

individually

age-matched

-LRB-

-RRB-

to

UBC

controls

All

patients

had

invasive

breast

carcinoma

and

were

treated

with

surgery

Of

the

CBC

patients

did

and

did

not

receive

radiotherapy

treatment

for

their

primary

breast

tumour

Average

age

at

diagnosis

for

the

first

breast

cancer

in

the

RT

group

was

years

-LRB-

mean/median

-RRB-

and

the

non-exposed

group

years

-LRB-

mean/median

-RRB-

Detailed

treatment

data

disease

and

patient

characteristics

were

obtained

from

medical

records

and

risk

factor

questionnaires

-LRB-

data

not

shown

-RRB-

-LSB-

-RSB-

Patients

were

asked

to

donate

a

ml

blood

sample

or

permission

for

use

of

paraffin-embedded

tissue

blocks

and

patients

gave

their

written

informed

consent

for

mutation

analysis

This

study

received

approval

of

the

Medical

Ethical

Committees

of

NKI-AVL

and

DDHK

Genomic

DNA

isolation

Genomic

DNA

was

either

isolated

from

peripheral

blood

lymphocytes

with

DNAzol

-LRB-

Invitrogen

Breda

The

Netherlands

-RRB-

methods

according

to

the

manufacturer

's

instructions

or

from

three

paraffin

embedded

normal

tissue

slides

according

to

standard

protocols

-LSB-

-RSB-

For

histopathological

examination

we

used

a

hematoxylin-eosin

stained

slide

Mutation

analysis

The

complete

ATM

Open

Reading

Frame

-LRB-

ORF

-RRB-

was

analysed

each

exon

-LRB-

exon

-RRB-

and

all

intron-exon

boundaries

were

screened

for

germline

mutations

using

Denaturing

Gradient

Gel

Electrophoresis

-LRB-

DGGE

-RRB-

identifying

of

all

ATM

mutations

and

polymorphisms

-LRB-

details

from

the

author

upon

request

-RRB-

All

aberrations

were

confirmed

with

genomic

sequence

analysis

performed

using

the

ABI

PRISM

BigDyeTerminator

Cycle

Sequencing

Ready

Reaction

Kit

Version

-LRB-

Applied

Biosystems

Nieuwerkerk

a/d

yssel

The

Netherlands

-RRB-

Sequencing

products

were

analysed

with

the

ABI

PRISM

DNA

Analyzer

and

corresponding

software

Statistical

analysis

Statistical

analyses

were

performed

using

standard

methods

for

analysis

of

case-control

studies

-LSB-

-RSB-

We

compared

the

mutation

frequency

between

UBC

and

CBC

and

between

CBC

cases

previously

treated

with

RT

and

cases

not-treated

with

RT.

Odds

ratios

-LRB-

ORs

-RRB-

and

CI

were

calculated

to

evaluate

the

association

between

mutation

carriers

status

and

breast

cancer

risk

We

have

used

the

Mann

Whitney

test

to

determine

whether

the

difference

between

the

intervals

between

the

two

breast

cancers

of

the

CBC

patients

was

significant

All

analyses

were

performed

using

SPSS

-LRB-

SPSS

Inc.

Chicago

IL

USA

-RRB-

Results

and

discussion

ATM

germline

mutations

In

the

present

study

we

have

used

the

DGGE

method

to

screen

the

complete

ATM

ORF

to

obtain

insight

in

the

ATM

missense

mutation

spectrum

in

-LRB-

contralateral

-RRB-

breast

cancer

patients

With

DGGE

we

were

able

to

confirm

all

the

previously

identified

truncating

mutations

A

subset

of

the

CBC

patients

described

in

this

study

had

been

screened

in

the

past

for

ATM

truncating

mutations

with

the

Protein

Truncating

Test

revealing

seven

ATM

truncating

mutations

-LRB-

including

a

non-sense

mutation

and

small

insertions

and

deletions

generating

stop

codons

within

a

previously

functional

protein

coding

sequence

causing

premature

termination

of

translation

of

the

protein

-RRB-

-LSB-

-RSB-

Among

all

cancer

patients

that

were

tested

in

this

study

with

DGGE

we

detected

a

large

number

of

ATM

silent

mutations

-LRB-

presumed

neutral

polymorphisms

data

not

shown

and

excluded

from

all

analyses

-RRB-

and

missense

mutations

-LRB-

causing

an

amino

acid

substitution

in

the

coded

protein

most

common

ones

i.e.

not

included

in

further

analysis

-RRB-

ATM

missense

mutation

spectrum

In

our

study

cohort

we

have

detected

distinct

ATM

missense

variants

and

distinct

truncating

mutations

Several

of

the

detected

missense

variants

have

been

reported

in

the

ATM

database

as

being

detected

in

A-T

patients/or

as

polymorphisms

-LRB-

Table

-RRB-

of

the

missense

variants

identified

in

this

study

are

known

as

pathogenic

A-T

causing

missense

mutations

Seventeen

of

the

missense

variants

have

not

been

reported

previously

Eleven

missense

variants

were

exclusively

found

in

the

CBC

group

and

exclusively

in

the

UBC

group

Whether

this

distinction

in

the

spectrum

indicates

an

association

between

particular

variants

and

bilateral

breast

cancer

risk

can

not

be

concluded

from

the

small

numbers

obtained

in

this

study

population

The

ATM

protein

has

several

functional

domains

and

the

identified

missense

variants

are

located

throughout

the

ORF

Potential

functional

implications

of

the

newly

identified

unclassified

variants

remain

to

be

established

Table

missense

variant

and

truncating

mutation

spectrum

in

contralateral

and

unilateral

breast

cancer

patientsMissense

variantsAmino

acid

changeCBC

n

n

or

-LSB-

-RSB-

-LSB-

-RSB-

-LSB-

-RSB-

-LSB-

-RSB-

A

-LSB-

-RSB-

-LSB-

-RSB-

-LSB-

-RSB-

-LSB-

-RSB-

-LSB-

-RSB-

Gdel

http://chromium.liacs.nk/lovd/b Not

included

in

frequency

analysis

Despite

the

fact

that

ATM

plays

a

role

in

breast

cancer

risk

the

role

of

most

distinct

ATM

missense

variants

remains

unclear

Some

studies

tried

to

predict

the

relevance

of

each

particular

mutation

on

basis

of

co-segregation

with

breast

cancer

in

families

the

location

in

a

functional

domain

or

interference

with

the

splicing

machinery

Only

a

few

studies

present

functional

analysis

that

are

necessary

to

assess

the

biological

impact

of

unidentified

variants

found

frequently

in

ATM

-LSB-

-RSB-

ATM

missense

mutations

and

contralateral

breast

cancer

Twenty-one

per

cent

of

the

patients

carried

at

least

one

ATM

germline

variant

-LRB-

missense

and

truncating

Table

-RRB-

Among

the

patients

with

CBC

-LRB-

n

-RRB-

we

identified

in

total

ATM

variants

in

individuals

-LRB-

-RRB-

missense

variants

and

truncating

mutations

-LRB-

Table

-RRB-

Eight

CBC

patients

had

multiple

ATM

missense

variants

and

patients

carried

both

a

missense

and

a

truncating

ATM

mutation

In

the

women

with

UBC

-LRB-

n

-RRB-

we

identified

ATM

variants

in

individuals

-LRB-

-RRB-

missense

and

truncating

mutations

Three

UBC

patients

carried

double

missense

and

patients

both

a

truncating

and

a

missense

variant

Although

it

is

known

from

the

literature

that

ATM

missense

variants

might

be

involved

in

breast

cancer

pathogenesis

the

identified

missense

variant

carriers

among

the

CBC

patients

compared

to

the

missense

variants

among

the

UBC

patients

indicate

that

there

is

not

a

significantly

increased

risk

for

bilateral

breast

cancer

among

ATM

missense

variant

carriers

OR

-LRB-

CI

-RRB-

Table

variant

frequencies

in

all

breast

cancer

patients

diagnosed

under

age

and

according

to

uni

or

contralateral

breast

cancerBreast

cancer

patients

withAll

patients

n

n

n

ATM

missense

and

missense

and

truncatingAt

least

one

ATM

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

At

least

one

ATM

missense

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

Only

one

ATM

truncating

truncating

and

one

missense

missense

Not

included

are

the

most

common

and

silent

variants

Association

with

radiation

treatment

Women

at

high

risk

for

developing

breast

cancer

may

respond

differently

to

radiation

exposures

associated

with

screening

and

treatment

than

the

general

population

Candidate-genes

like

ATM

are

implicated

in

maintenance

of

genome

integrity

Their

involvements

in

breast

cancer

susceptibility

as

well

as

their

role

in

DNA-damage

repair

signalling

make

them

excellent

candidates

for

a

role

in

radiation-induced

breast

cancer

-LSB-

-RSB-

Recently

we

showed

that

women

with

a

pathogenic

germline

mutation

in

a

DNA

repair

pathway

gene

-LRB-

e.g.

and

ATM

-RRB-

have

an

over

increased

risk

of

developing

radiation-associated

breast

cancer

-LRB-

manuscript

under

review

-RRB-

Therefore

we

now

investigated

whether

exposure

to

ionising

radiation

had

a

greater

biological

impact

on

certain

ATM

genotypes

than

on

others

We

did

not

detect

a

significantly

increased

risk

of

developing

radiation-associated

CBC

among

missense

mutation

carriers

Among

those

CBC

patients

who

had

developed

a

second

primary

breast

tumour

following

radiotherapy

for

their

first

breast

tumour

we

identified

ATM

missense

variants

carriers

compared

to

among

those

CBC

patients

who

did

not

receive

RT

the

OR

from

this

case-only

analysis

is

-LSB-

CI

-LRB-

-RRB-

p

-RSB-

Furthermore

we

have

observed

that

of

the

UBC

patients

who

received

RT

but

did

not

develop

a

CBC

carried

an

ATM

missense

variant

compared

to

of

the

CBC

patients

that

received

RT

for

their

first

tumour

-LSB-

OR

-LRB-

CI

-RRB-

-RSB-

These

results

suggest

that

RT

is

not

a

strong

risk

factor

for

the

development

of

CBC

among

carriers

of

those

ATM

missense

variants

It

has

however

been

shown

that

particular

alterations

in

the

ATM

gene

are

associated

with

increased

radiation

sensitivity

-LSB-

-RSB-

Gutierrez-Enriquez

et

al.

showed

that

lymfoblastoid

cell

lines

carrying

the

ATM

variant

-LRB-

linked

to

-RRB-

was

associated

with

increased

in

vitro

chromosomal

radio-sensitivity

perhaps

by

interfering

with

ATM

function

in

a

dominant-negative

manner

-LSB-

-RSB-

We

found

this

particular

variant

allele

-LRB-

-RRB-

exclusively

in

our

CBC

group

exposed

to

radiotherapy

-LRB-

four

times

-RRB-

and

not

in

the

non-RT-exposed

CBC

group

This

finding

supports

the

hypothesis

that

particular

ATM

variants

might

play

a

differential

role

in

radiation

response

Although

a

subset

of

the

missense

variants

was

only

detected

in

the

RT

exposed

subpopulation

individual

numbers

were

probably

too

small

to

detect

a

significant

effect

of

particular

mutations

associated

with

treatment

We

observed

that

CBC

patients

with

an

ATM

missense

variant

had

an

mean

interval

between

the

first

and

second

breast

tumour

of

months

compared

to

months

for

non-carriers

CBC

patients

-LRB-

p

-RRB-

Interestingly

the

combination

of

radiation

treatment

and

a

missense

variant

resulted

in

an

even

shorter

mean

interval

of

a

months

in

the

CBC

patients

compared

to

a

interval

for

CBC

patients

who

neither

received

RT

nor

carried

a

germline

variant

-LRB-

p

-RRB-

These

data

suggest

that

carrier-ship

of

an

ATM

missense

variant

may

accelerate

the

development

of

a

second

tumour

and

decreases

the

age

at

onset

of

the

second

breast

tumour

especially

in

case

of

exposure

to

RT.

The

suggestion

of

a

shorter

induction

period

of

RT-associated

breast

cancer

in

patients

who

carry

an

ATM

missense

mutation

while

the

proportion

of

patients

with

missense

variants

was

similar

in

CBC

and

UBC

cases

might

be

attributable

to

a

different

spectrum

of

mutations

in

those

patients

who

developed

CBC

A

big

challenge

in

such

a

study

remains

to

assess

which

particular

missense

mutations

have

an

impact

on

ATM

function

Large

association

studies

as

performed

by

the

Breast

Cancer

Association

Consortium

-LRB-

coordinated

by

Doug

Easton

and

Paul

Pharoah

Cambridge

-RRB-

and

functional

studies

are

clearly

necessary

to

determine

the

importance

of

particular

variants

and

their

contribution

to

the

breast

cancer

risk

O O O B B I O O O O O B I O O O B O O O O O O B I O O O O O O O O O O O O B B I O O O O O B I O O O O O O O O O O O O B B I O O B I O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O B B I O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O B I O O O O O O O O O O B I O O O O O O O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O B I O O O O O O O O O O O O O O O O O O O O O B I O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O B I O O O O O O B O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B I O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B I O O O O O O O O O O B I O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O B O O O O O O B O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O B B I O O O O O O O O O O B I O O O O O B O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O B I O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O B O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O B I O O O O O O O B B I O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O B O O O O B I O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O B I O O O O O O O O O O O O O O B B I O O O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B I O O O O B I O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O B I O B O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O B B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B I O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O B O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O

breast cancer
atm
missense variants
radiotherapy


Impact of the population at risk of diabetes on projections of diabetes burden in the United States : an epidemic on the way Aims/hypothesis The aim of this study was to make projections of the future diabetes burden for the adult US population based in part on the prevalence of individuals at high risk of developing diabetes . Introduction Considerable evidence has been presented on the rise in diabetes prevalence in the United States and the United Kingdom -LSB- 1 , 2 -RSB- . The prevalence of diabetes has become so large that it has been termed an epidemic -LSB- 1 , 3 -RSB- . This rise is particularly important for healthcare needs in the US because almost 30 % of individuals with diabetes are currently undiagnosed and diabetes is disproportionately represented in minority populations -LSB- 4 -RSB- . Projection of future disease prevalence helps to plan for healthcare needs . An understanding of the population at risk of developing the disease is critical when projecting future disease burden . Several studies have projected future diagnosed diabetes prevalence for the US and other countries -LSB- 2 , 5 -- 9 -RSB- . These studies , however , did not consider that not all individuals are equally at risk of developing diabetes , thereby possibly distorting estimates of downstream prevalence . For example , some risk factors for diabetes , e.g. obesity , have increased substantially in the population -LSB- 10 -- 12 -RSB- . Moreover , many of these projections are based on estimates of diagnosed diabetes and exclude estimates of total diabetes -LRB- diagnosed and undiagnosed -RRB- , which may lead to serious underestimation of the diabetes burden in the population . Major risk factors for diabetes have been identified and are currently used by the American Diabetes Association to guide screening strategies . Although there are various measures for assessing the risk of having undiagnosed diabetes -LSB- 13 -- 17 -RSB- , few measures are available for assessing the risk of developing diabetes -LSB- 18 , 19 -RSB- . Moreover , accounting for changes in the proportion of high-risk individuals , particularly as assessed through clinical indicators , has not been incorporated into previous projections of future diabetes burden . The purpose of this study was to project the prevalence of diabetes for the adult US population up to 2031 , using models based on data contained in the nationally representative National Health and Nutrition Examination Survey -LRB- NHANES -RRB- II mortality survey -LRB- 1976 -- 1992 -RRB- , NHANES III -LRB- 1988 -- 1994 -RRB- and NHANES 1999 -- 2002 . Materials and methods Diabetes prevalence model The model for diabetes prevalence used in this study was created using data from the NHANES III -LRB- 1988 -- 1994 -RRB- , and then fitted to data from the NHANES 1999 -- 2002 as a validity check of the accuracy of the model 's projections . The resulting model was then used to project the number of individuals with diabetes in the US in 10-year increments into the future . We evaluated 10-year age classes at each 10-year interval . Our model has the following components : Number of individuals with diabetesTime 2 = ∑ -LRB- number of individuals with diabetesTime 1i + incident casesi − mortalityi -RRB- , where i equals each 10-year age group , and incident cases consist of : -LRB- 1 -RRB- persons converting from a disease-free state to having diabetes ; -LRB- 2 -RRB- diabetic patients immigrating to the United States ; and -LRB- 3 -RRB- persons with diabetes moving into the 20 to 29-year-old age class.The percentage of persons with diabetes , which is calculated thus : percentage diabetesTime 2 = -LRB- number of individuals with diabetesTime 2 / total populationTime 2 -RRB- × 100 . The estimate of future diabetes is therefore based on this equation , including the number of individuals with diabetes in the previous time period , conversion to diabetes , migration , and mortality , rather than being a linear extrapolation of the change in diabetes prevalence from the known values of 1991 and 2001 . Data sets The NHANES is a programme of surveys conducted by the National Center for Health Statistics and designed to assess the health and nutritional status of adults and children in the United States . The survey is unique on a national level in that it combines interviews and physical examinations . The NHANES uses a complex multistage sampling design , making it representative of the non-institutionalised US population and allowing weighted estimates to be computed . For this study we used several of the NHANES data sets . Specifically , we used the NHANES III -LRB- 1988 -- 1994 -RRB- -LRB- unweighted n = 4,950 -RRB- and the NHANES 1999 -- 2002 -LRB- unweighted n = 3,804 -RRB- to estimate among individuals of 20 years of age and older the prevalence of diagnosed diabetes , the total diabetes burden -LRB- diagnosed and undiagnosed diabetes -RRB- , and the proportion of the population at risk of developing diabetes . Since mortality within the population affects future prevalence -LSB- 20 -RSB- , we also used the cohort from the NHANES II mortality survey -LRB- 1976 -- 1992 -RRB- -LRB- unweighted n = 3,916 -RRB- to provide estimates of diabetes mortality . Computation of all analyses using the NHANES data sets to provide nationally representative estimates for the models was designed to account for the complex survey design and the appropriate sample weights . All analyses were conducted using SUDAAN software -LRB- Research Triangle Institute , Research Triangle Park , NC , USA -RRB- . Variables used in models Prevalence of diabetes Diabetes burden was assessed as diagnosed diabetes plus undiagnosed diabetes . Because of the substantial proportion of people with undetected diabetes , we focused on this formula for total diabetes , rather than using diagnosed diabetes to indicate diabetes burden in the population . Moreover , by focusing on diabetes as diagnosed and undiagnosed disease , we minimised the possible impact on future diabetes prevalence of changes in screening practices for diagnosing diabetes during an ensuing time period . Diagnosed diabetes was assessed as individuals who answered yes to a question of whether a doctor had told them they had diabetes . Undiagnosed diabetes was estimated on the basis of individuals who said they had not had a previous diagnosis of diabetes , but who had fasting plasma glucose -LRB- FPG -RRB- > 7.0 mmol/l . Although , the diagnostic criteria for diabetes during the time between the NHANES II and the NHANES III changed from FPG > 7.8 mmol/l to FPG > 7.0 mmol/l , we used the newer criteria to gain an awareness of the total diabetes burden at each point in time using the same criteria -LSB- 21 -RSB- . Persons converting from a disease-free state to having diabetes Although a variety of diabetes risk scores exist , most have been created from cross-sectional studies and have as their aim the identification of individuals with undiagnosed diabetes . Their ability , therefore , to make predictions on development of diabetes is unknown -LSB- 13 , 14 , 16 -RSB- . The risk score used in this study is based on one developed for the Atherosclerosis Risk in Communities -LRB- ARIC -RRB- cohort study -LSB- 18 -RSB- . Among individuals without diagnosed diabetes or FPG > 7.0 mmol/l , we used a scoring strategy which includes : high waist circumference -LRB- > 102 cm in men , > 88 cm for women -RRB- , raised blood pressure -LRB- > 130/85 mmHg or antihypertensive medications -RRB- , low HDL-cholesterol -LRB- < 1.03 mmol/l for men , < 1.29 mmol/l for women -RRB- , high triacylglycerol -LRB- > 1.7 mmol/l -RRB- , BMI > 30 kg/m2 , and hyperglycaemia . Each of the characteristics is worth 1 point except for hyperglycaemia , which can be worth 2 points if FPG is > 5.6 mmol/l or 5 points when FPG is > 6.1 mmol/l . A score of > 4 puts an individual at high risk of developing diabetes , whether diagnosed or undiagnosed . A score of < 4 indicates that a person has a low risk of developing diabetes . This particular risk score was chosen for several reasons . First , it has moderate sensitivity -LRB- 68 % -RRB- and specificity -LRB- 75 % -RRB- . Second , it is computed in a reasonably straightforward manner without having to use coefficients from the ARIC cohort that may be specific to that cohort . Third , data and results provided in the study by Schmidt et al. -LSB- 18 -RSB- allowed for computation of the rate of development of diabetes in both the high-risk group and the low-risk group . The ratio of development of diabetes in the high-risk group versus the low-risk group was 4.5:1 . Variables needed to compute this diabetes risk score are available only in the NHANES III and the NHANES 1999 -- 2002 . Although the ARIC diabetes risk score did not specifically consider race or age in the computation -LSB- 18 -RSB- , we computed conversion rates for 10-year age classes for three race/ethnic groups -LRB- non-Hispanic Whites , non-Hispanic Blacks and Hispanic individuals -RRB- by fitting age categories for the data from 1991 to 2001 and then fitting race/ethnicity on to the same time change . We did not compute specific sex-specific conversion rates because sex was already differentiated in several of the variables in the ARIC diabetes risk score -LSB- 18 -RSB- . Migration of persons with diabetes Migration of individuals with or without diabetes into the population can also affect future diabetes prevalence . Recent projections have included migration within their models -LSB- 5 -RSB- . Because we are looking at changes in diabetes prevalence among adults , migration of adults , particularly from ethnic minorities , could substantially affect the 10-year projections . We used data from the NHANES III to estimate migration of persons with diabetes in the 20 years and older age groups . The NHANES III measured how many years foreign-born immigrants had been in the US . Thus , we estimated the number of foreign-born individuals who had been in the country for 9 years or less for the total population as well as for different racial/ethnic groups . The NHANES III data allowed us to make estimates for non-Hispanic Whites , non-Hispanic Blacks and Hispanic individuals . Persons with diabetes moving into the 20 to 29-year-old age class For 2011 , 2021 and 2031 the total number of persons with diabetes in the 20 to 29-year-old age class was estimated using a linear projection of the NHANES III and NHANES 1999 -- 2002 data . The proportion of 20 to 29-year-olds with diabetes in each race/ethnic group was held constant at the proportions found in the NHANES 1999 -- 2002 data at the later time intervals . Mortality among individuals with diabetes Diabetes mortality for the total population was based on data from the NHANES II mortality survey -LRB- 1976 -- 1992 -RRB- . This population-based cohort study was used to provide estimates of diabetes mortality , since mortality within the population affects future prevalence -LSB- 20 -RSB- . Diabetes mortality was estimated as all-cause mortality among individuals with diabetes -LRB- either diagnosed or undiagnosed -RRB- at baseline , rather than as mortality with diabetes listed as the cause of death . This definition is more consistent with the potential impact of diabetes on future prevalence . Mortality estimates were computed separately for the total population by age classes . The NHANES II mortality cohort is based on a sample of individuals aged 30 to 75 , whereas we made diabetes estimates on individuals aged 20 years and older . Consequently , we assumed no deaths due to diabetes in the 20 to 29-year-old age group over the 10-year period . Population estimates Total population of 10-year age classes was estimated using data from NHANES III for 1991 , NHANES 1999 -- 2002 for 2001 , and US Census Bureau , Middle Series projections for 2011 , 2021 and 2031 -LSB- 22 -RSB- . Total population of race/ethnic groups was also determined by 10-year age classes using the same sources of information . Analysis In an effort to provide an estimate of future trends in diabetes and the population at high risk of developing diabetes , we employed the following procedure . We used the NHANES III data to fit a model to predict total diabetes in the NHANES 1999 -- 2002 . We used this strategy prior to making future projections , because it allowed us to develop and fit the model to an existing national estimate of diabetes prevalence . Because both the NHANES III and the NHANES 1999 -- 2002 are based on multi-year data collection , we estimated a mid-point of 1991 and 2001 for the two surveys . The number of persons with diabetes 10 years post-baseline was calculated for 10-year age classes by first adding baseline prevalence and incidence -LRB- the number of low-risk and number of high-risk persons who developed diabetes over the 10-year interval -RRB- , then adding persons with diabetes who immigrated to the United States , and persons with diabetes who moved into the 20 to 29-year-old age class , and finally subtracting the number of diabetic subjects who died . Percentage of persons with diabetes was estimated for each time period by taking the total number of persons with diabetes and dividing by the expected total population , then multiplying by 100 . Varying model assumptions Our initial predictions of future diabetes burden were based on the assumption of a constant proportion of individuals at high risk of diabetes at the levels present in the NHANES 1999 -- 2002 . To account for potential changes in the proportion of persons at high risk of diabetes , we also evaluated increases in the proportion of persons at high risk by 10 , 20 and 30 % , as well as estimates based on decreases in the proportion of persons at high risk by 10 , 20 and 30 % . Theoretically , it is unlikely that the proportion of persons at high risk will remain stable , because from NHANES III to NHANES 1999 -- 2002 the proportion at high risk was seen to increase . Also , a major risk factor for diabetes , obesity , has increased substantially over a 40-year time period -LSB- 10 , 12 -RSB- . We evaluated the effect of decreasing proportions at high risk , to account for the possibility that interventions to improve lifestyle of adults in the US may be effective . In addition , to address the potential impact on mortality of healthcare interventions in management of diabetes , we examined potential reductions of 10 , 20 and 30 % in mortality among individuals with diabetes . Finally , we computed a model examining a combination of effects , assuming that lifestyle interventions would yield a 10 % decrease of persons at high risk and healthcare interventions would yield a 10 % decrease in mortality of persons with diabetes . Results Table 1 shows estimates of the total diabetes burden from the NHANES III and the NHANES 1999 -- 2002 and the future 10-year projections for 2011 through to 2031 . The number of individuals at high risk of diabetes based on the multivariable diabetes risk score was 38.4 million in 1991 and 49.9 million in 2001 . Using our model to predict the known diabetes prevalence in 2001 from the 1991 data , results were satisfactory and within 0.2 % of the actual population prevalence of total diabetes . If the proportion of individuals at high risk within the adult population remains stable at 2001 levels , we could expect 55.8 million in 2011 , 60.9 million in 2021 , and 66.1 million in 2031 . As can be seen , the prevalence of diabetes is projected to increase . The diabetes prevalence of 6.3 % in 1991 and 8.8 % in 2001 is projected to increase to 14.5 % in 2031 with 37.7 million adults having diagnosed or undiagnosed diabetes . Assuming stability in the population proportion of individuals at high risk of developing diabetes , the rate of increase in the number of individuals with diabetes and the proportion with diabetes tends to slow over time . Among individuals aged 30 to 39 years who are not currently targeted for screening according to age , the prevalence of diabetes is expected to rise from 3.7 % in 2001 to 5.2 % in 2031 . Table 1Number of people -LRB- in millions of persons -RRB- with and prevalence of diabetes by year and age categoryAge -LRB- in years -RRB- NHANES IIINHANES 1999 -- 200220112021203120 -- 29Number0 .20.40.50.70.9 Percentage0 .51.01.31.72.030 -- 39Number0 .61.61.82.12.3 Percentage1 .43.74.75.05.240 -- 49Number1 .53.54.34.34.9 Percentage4 .58.110.311.111.250 -- 59Number2 .53.96.67.26.9 Percentage11 .412.215.617.718.260 -- 69Number3 .14.16.59.810.2 Percentage15 .319.822.025.126.6 > 70Number3 .24.15.78.412.4 Percentage16 .217.420.522.623.9 TotalNumber11 .117.525.432.637.7 Percentage6 .38.811.513.514.5 NHANES National Health and Nutrition Examination Survey The results shown in Electronic supplementary material -LRB- ESM -RRB- Table 1 show the projected prevalence of diabetes according to different racial/ethnic groups . Non-Hispanic White adults are projected to continue to have a lower prevalence of diabetes than both non-Hispanic Black and Hispanic individuals . By 2031 , the Hispanic community will have an overwhelming diabetes burden , with more than 20 percent of the adult population having diabetes . The projections in ESM Table 2 are based on different assumptions regarding changes in the number of individuals who are at high risk of developing diabetes and changes in mortality among individuals with diabetes . As might be expected , as mortality decreases the prevalence of diabetes increases in the subsequent 10 years . The estimate for 2031 indicates that potential decreases in mortality and a potential decrease in individuals at high risk of developing diabetes yields a prevalence similar to that achieved if the proportion at high risk is kept stable from 2001 . All of these estimates indicate a larger diabetes burden among Hispanics . Discussion This national projection of diabetes prevalence for the US is the first to model the projection on the number of individuals at high risk of developing diabetes using a multivariable risk assessment . Projections suggest a rising and substantial diabetes burden for the population . Hispanic adults will be most affected , with estimates suggesting that by 2031 more than 20 % of the adult Hispanic community will have diabetes . These results are particularly worrisome for this community in light of recent evidence that the gap in healthcare quality between Hispanic and non-Hispanic White individuals has continued to widen -LSB- 23 -RSB- . Many previous diabetes projections have been limited to estimates of diagnosed diabetes and thus have lower estimates of projected diabetes burden , and have not incorporated an evaluation of the population at high risk of diabetes , with clinical indicators , into their models -LSB- 5 , 9 -RSB- . Our estimates will be less likely to be affected by changes in screening strategies . Additionally , they incorporate potential changes in the level of risk for diabetes in the US population , a change which is likely given national trends in obesity -LSB- 3 -RSB- . Moreover , recent data have suggested that individuals with undiagnosed diabetes are similar to those with diagnosed diabetes with regard to the development of complications ; thus our estimates are more robust in describing the burden of disease in the population -LSB- 24 -RSB- . Comparing our projections with those from other studies , we note that an estimate , published in 2006 , for diagnosed diabetes in the US among individuals aged 20 to 64 years in 2030 is 16.8 million -LSB- 25 -RSB- . Our estimates are based both on diagnosed and undiagnosed diabetes , and our projection of total diabetes among that age group for 2031 is higher , namely 19 million . It is possible that estimates based solely on diagnosed diabetes could become more consistent with our estimates , if greater vigilance were shown for screening for undiagnosed diabetes . However , not accounting for the at-risk population in the estimates is likely to lead to inaccurate estimates . A comparison of our estimates of total diabetes with those of another study -LSB- 7 -RSB- , which projected total diabetes but did not account for the population at high risk of developing diabetes , reveals that the latter 's projections are most probably underestimates . Using data from 1993 , the investigators projected a population prevalence estimate of total diabetes in the US among individuals aged 20 years and older for the year 2000 to be 7.6 % , while the NHANES 1999 -- 2002 yielded a prevalence of 8.8 % . For 2025 the same team -LSB- 7 -RSB- projected a prevalence of 8.9 % versus 13.5 % for 2021 in our study . The results have several implications for the delivery of healthcare and healthcare financing . First , we estimated our models under several assumptions for the number of individuals at high risk of diabetes in the population . Regardless of these assumptions , the US will have a substantial number of individuals at high risk of diabetes in 2011 , 2021 and 2031 . Interventions to modify lifestyle are critical to decrease the number of individuals at high risk , and consequently to lower the expected increase in diabetes in the future . Although some of the diabetes estimates suggest seemingly small decreases in future prevalence , based on decreases in the population at risk , the actual numbers are substantial . For example , a one-percentage point drop in the US population estimate of diabetes among individuals aged 20 and older in 2031 is quite substantial and would account for a decrease in prevalence of diabetes equivalent to 2,600,000 people . Second , the projection that a substantial proportion of the population will have diabetes indicates greater spending will be necessary to manage the disease . This will include spending on drugs , ongoing monitoring , and treating of complications including nephropathy , retinopathy , and cardiovascular disease . Third , the disproportionate impact of diabetes on minorities , particularly Hispanics , demands new intervention strategies to decrease the number of individuals at high risk and to deliver care to individuals who have historically had poor access to care . Additionally , with the projected increase in diabetes prevalence among 30 to 39-year-olds , a population not currently targeted for screening , a re-examination of current public health policy and screening strategies may be warranted -LSB- 26 -RSB- . There are several strengths to the design of this study . One is that the study utilised multiple NHANES data sets , which have the advantage of allowing for nationally representative population estimates . Thus , the initial data used to fit the model as well as to make mortality estimates of diabetes , both diagnosed and undiagnosed , are nationally representative . Another strength is that this study is the first to make a nationally representative assessment of the at-risk population for development of diabetes and then use that assessment to model the future prevalence of diabetes . The assessment of risk used , moreover , is based on the ARIC diabetes risk score -LSB- 18 -RSB- , a multivariable risk score that used clinical indicators . When interpreting our results , however , several limitations need to be considered . Thus , although this is the first study to use a validated diabetes risk score to assess the high-risk population for the development of diabetes for the entire US population , potential limitations exist with regard to the diabetes risk score . The ARIC diabetes risk score -LSB- 18 -RSB- was based on a cohort of individuals aged 45 to 64 years at baseline and may therefore be limited when estimating diabetes development among individuals aged 20 years and older . However , we estimated diabetes prevalence in 10-year age increments . Moreover , the risk score 's moderate sensitivity and specificity may cause the model to under - or potentially overestimate future prevalence projections . Another possible limitation is that estimates of future disease burden are based on assumptions about the number at risk of disease and about mortality within the population . We have attempted to address this limitation by presenting the results of a sensitivity analysis , which includes variations in the proportion of the population at risk and in mortality . The third limitation is the diagnosis of diabetes in the NHANES data on the basis of a single FPG value . This strategy , although common in epidemiological studies , could potentially underestimate the prevalence of diabetes associated with isolated post-challenge hyperglycaemia , which occurs more commonly in women , the elderly , and in lean populations . It could also overestimate diabetes prevalence , because a clinical diagnosis of diabetes in asymptomatic patients requires two abnormal fasting glucose levels . In summary , a continued focus on effective interventions for lifestyle modifications to decrease diabetes risk , as well as vigilant ascertainment of diabetes , appears crucial if the future prevalence and burden of diabetes in the US population are to be adequately addressed . This is especially important for minority populations , particularly the Hispanic community , which is projected to have an overwhelming future diabetes burden . Considering that minorities have historically had limited access to healthcare , these findings emphasise the importance of interventions targeting these populations . Electronic supplementary material Below is the link to the electronic supplementary material . Table 1 Projections of non-Hispanic White , non-Hispanic Black and Hispanic persons with diabetesa and prevalence in 2011 , 2021 , and 2031 -LRB- 43 kb -RRB- Table 2 Projections , using different assumptions , of diabetes prevalence among individuals aged > 20 years in 2031 -LRB- 32 kb -RRB-

O O O O O O O B O O O B O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O B O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O B O O O O O O O O O O B O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O O O B O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O B O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O 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The -1997 G/T and Sp1 Polymorphisms in the Collagen Type I alpha1 -LRB- COLIA1 -RRB- Gene in Relation to Changes in Femoral Neck Bone Mineral Density and the Risk of Fracture in the Elderly : The Rotterdam Study The COLIA1 Sp1 polymorphism has been associated with bone mineral density -LRB- BMD -RRB- and fracture . A promoter polymorphism , -1997 G/T , also has been associated with BMD . In this study , we examined whether these polymorphisms alone and in the form of haplotypes influence bone parameters and fracture risk in a large population-based cohort of elderly Caucasians . We determined the COLIA1 -1997 G/T -LRB- promoter -RRB- and Sp1 G/T -LRB- intron -RRB- polymorphisms in 6,280 individuals and inferred haplotypes . Femoral neck BMD and BMD change were compared across COLIA1 genotypes at baseline and follow-up -LRB- mean 6.5 years -RRB- . We also investigated the relationship between the COLIA1 polymorphisms and incident nonvertebral fractures , which were recorded during a mean follow-up period of 7.4 years . Vertebral fractures were assessed by radiographs on 3,456 genotyped individuals . Femoral neck BMD measured at baseline was 3.8 % lower in women carrying two copies of the T-Sp1 allele -LRB- P for trend = 0.03 -RRB- . No genotype dependent differences in BMD loss were observed . In women homozygous for the T allele of the Sp1 polymorphism , the risk of fragility fracture increased 2.3 times -LRB- 95 % confidence interval 1.4 -- 3.9 , P = 0.001 -RRB- . No such association was observed with the promoter polymorphism . In men , no association with either the Sp1 or the -1997 G/T promoter polymorphism was seen with BMD or fracture . High linkage disequilibrium -LRB- LD ; D ′ = 0.99 , r2 = 0.03 -RRB- exists between the two studied polymorphisms . We observed three haplotypes in our population : haplotype 1 -LRB- Gpromoter -- Gintron -RRB- frequency -LRB- f -RRB- = 69 % , haplotype 2 -LRB- Gpromoter -- Tintron -RRB- f = 17.6 % , and haplotype 3 -LRB- Tpromoter -- Gintron -RRB- f = 13.4 % . Haplotype 2 was associated with a 2.1-fold increased risk of fragility fracture in women -LRB- 95 % confidence interval 1.2 -- 3.7 , P = 0.001 -RRB- . We confirm that the COLIA1 Sp1 polymorphism influences BMD and the risk of fracture in postmenopausal Caucasian women . In contrast , we found no independent effect of the -1997 G/T promoter polymorphism on BMD or fracture . Introduction Osteoporosis is a multifactorial disease with both genetic and environmental determinants . It is characterized by a reduction in bone mineral density -LRB- BMD -RRB- and microarchitectural deterioration of bone tissue , which leads to an increased risk of fracture in later life -LSB- 1 , 2 -RSB- . Being a predictor of bone fragility and susceptibility to fracture , BMD is used for the diagnosis of osteoporosis -LSB- 3 , 4 -RSB- . The risk of fracture is dependent not only on BMD but also on geometry , architecture , material properties , and mass distribution -LSB- 5 -RSB- . The skeletal determinants of osteoporotic fracture risk such as BMD , bone loss , and bone geometry are all subject to strong genetic influences -LSB- 2 , 6 , 7 -RSB- . It has been estimated from twin studies that 60-80 % of the variance in BMD is attributable to genetic factors -LSB- 8 , 9 -RSB- . Several genes are thought to be involved in the pathogenesis of osteoporosis . Collagen type I alpha 1 -LRB- COLIA1 -RRB- is one of the most prominent candidate genes , which has been consistently associated with osteoporosis in different populations -LSB- 10 -- 12 -RSB- . COLIA1 encodes the alpha 1 chain of collagen type I , which is the most abundant structural protein in the bone matrix ; rare mutations in this gene cause osteogenesis imperfecta , a mendelian disorder presenting with moderate to severe bone fragility -LSB- 13 , 14 -RSB- . Previously , Grant et al. -LSB- 15 -RSB- identified a relatively common guanine to thymidine -LRB- G → T -RRB- polymorphism in the first intron of COLIA1 . This polymorphism affects one of the binding sites of the transcription factor Sp1 and results in increased expression of collagen type I alpha 1 in bone matrix in T carriers -LSB- 11 -RSB- . We and others have shown that the T allele is associated with osteoporosis , lower BMD -LSB- 10 , 15 -RSB- , and increased fracture risk -LSB- 10 , 12 , 16 , 17 -RSB- . Moreover , in a very large prospective meta-analysis of individual data , we observed that the Sp1 polymorphism in the COLIA1 gene is associated with reduced BMD and incident vertebral fractures independent of BMD -LSB- 18 -RSB- . In addition to the Sp1 polymorphism , Garcia-Giralt et al. -LSB- 19 -RSB- described two polymorphisms within the COLIA1 promoter region : -1997 G/T and -1663 indelT . The study showed in a small cohort of postmenopausal Spanish women that the T allele of the -1997 G/T polymorphism was significantly associated with a 7.5 % decreased lumbar spine BMD and a 12 % decreased femoral neck BMD . Furthermore , they analyzed compound genotypes including three polymorphic sites . However , this small study of the promoter polymorphisms in women investigated the relation in form of compound genotypes , was not extended to haplotypes of promoter and Sp1 polymorphisms , and most importantly , did not analyze fractures , the clinically most relevant end point of osteoporosis . Therefore , we investigated the influence of both COLIA1 polymorphisms independently and in the form of haplotypes in relation to baseline femoral neck BMD , change in BMD with follow-up , and risk of vertebral and nonvertebral fractures in a large population-based cohort of elderly Caucasian men and women . Materials and Methods Study Population This study was embedded in the Rotterdam Study , a population -- based cohort study in which all residents of the Rotterdam suburb Ommoord aged 55 years and older were invited to take part . The design of the study has been described elsewhere -LSB- 20 -RSB- . Written informed consent was obtained from all participants , and the Medical Ethics Committee of the Erasmus Medical Center approved the study . Baseline data collection was conducted in January 1990 and June 1993 , while two follow-up assessments were performed between July 1993 and January 1996 and from July 1996 until December 1999 . A total of 7,983 subjects participated in the study -LRB- response rate 78 % -RRB- , and for the present study , we examined 6,280 individuals who were genotyped . Study Design This study was performed in three steps . In the first step , we performed a cross-sectional analysis where we examined the relation between the genotype and baseline BMD -LRB- n = 5,737 -RRB- . In the second step , we performed a longitudinal analysis to study change in BMD between baseline and the second follow-up -LRB- mean 6.5 ± standard deviation -LSB- SD -RSB- 0.6 years , n = 2,670 -RRB- . In the third step , we looked at the relation between COLIA1 polymorphisms and the risk of incident fracture . We studied incidence of nonvertebral fracture -LRB- mean follow-up 7.4 ± 3.3 years , n = 6,280 -RRB- and vertebral fractures assessed by radiographs both at baseline -LRB- 1990 -- 1993 -RRB- and at follow-up visit ' between 1997 and 1999 , thoracolumbar radiographs of the spine were available for 3,469 individuals in a mean follow-up of 6.4 years . Measurements BMD -LRB- g/cm2 -RRB- of the hip and L2-L4 of the lumbar spine were measured by dual-energy X-ray absorptiometry -LRB- DXA -RRB- using a Lunar DPX densitometry -LRB- DPX-L -RRB- -LRB- Lunar Radiation , Madison , WI -RRB- and reanalyzed with DPX-IQ software , under standard protocols . Methods , quality assurance , accuracy , and precision issues of the DXA measurements have been described previously -LSB- 21 -RSB- . The relative change of BMD from baseline was estimated as the difference in BMD between assessment periods divided by the BMD at baseline . Height -LRB- cm -RRB- and weight -LRB- kg -RRB- were measured with a stadiometer at the initial examination , in standing position wearing indoor clothes without shoes . Body mass index -LRB- BMI -RRB- was computed as weight divided by height -LRB- kg/cm2 -RRB- . Fracture Follow-up Information on incident nonvertebral fractures was collected from baseline -LRB- 1990 -- 1993 -RRB- until January 1 , 2002 -LRB- mean follow-up ± SD 7.4 ± 3.3 years , n = 6,280 -RRB- . Nonvertebral fracture events were retrieved from computerized records of the general practitioners -LRB- GPs -RRB- in the research area . Research physicians regularly followed participant information in GP records outside the research area and made an independent review , encoding all reported events . Subsequently , a medical expert in the field reviewed all coded events for final classification . We excluded fractures that were considered nonosteoporotic , i.e. , caused by cancer and high trauma , including fractures of the hand , foot , skull , and face . Subsequently , we analyzed separately `` fragility '' fractures , which were defined as any fracture of the hip , pelvis , or proximal humerus that had occurred with minimal trauma at older age -LRB- mean > 75 years -RRB- . Vertebral Fracture Assessment Both at baseline and at first follow-up , between 1997 and 1999 , thoracolumbar radiographs of the spine were obtained . The follow-up radiographs were available for 3,456 individuals , who survived an average of 6.4 -LRB- SD = 0.4 -RRB- years after the baseline visit and who were still able to come to our research center . All follow-up radiographs were scored for the presence of vertebral fracture by the McCloskey/Kanis method , as described previously -LSB- 22 -RSB- . Genotyping Genomic DNA was extracted from samples of peripheral venous blood according to standard procedures . Genomic DNA -LRB- 1 -- 2 ng -RRB- was dispensed into 384-well plates using a Sciclone ALH3000 pipetting robot -LRB- Caliper , Mountain View , CA -RRB- . Genotypes were determined using the Taqman allelic discrimination assay . The Assay-by-Design service -LRB- http://www.appliedbio-systems.com -RRB- was used to set up a Taqman allelic discrimination assay for the COL1PR-1997 polymorphism -LRB- primers : Fw , GCCTCCGGAGGGTGTCA , Rv , AAGGAGAGCAATTCTTACAGGTGTCT ; probes : FAM-CCTGAGGGATGGAA-MGB , VIC-CCTGAAGGATGGAAG-MGB . The polymerase chain reaction -LRB- PCR -RRB- mixture included 1 -- 2 ng of genomic DNA in a 2 μL volume and the following reagents : FAM and VIC probes -LRB- 200 nM -RRB- , primers -LRB- 0.9 μM -RRB- , and 2 × Taqman PCR master mix -LRB- ABgene , Epsom , UK -RRB- . Reagents were dispensed in a 384-well plate using the Deerac Equator NS808 -LRB- Deerac Fluidics , Dublin , Ireland -RRB- . PCR cycling was performed in 384-well PCR plates in an ABI 9700 system -LRB- Applied Biosystems , Foster City , CA -RRB- and consisted of initial denaturation for 15 minutes at 95 °C , 40 cycles with denaturation of 15 seconds at 95 °C , and annealing and extension for 60 seconds at 60 °C . Results were analyzed by the ABI Taqman 7900HT using the sequence detection system 2.22 software -LRB- Applied Biosystems -RRB- . To confirm the accuracy of genotyping results , 332 -LRB- 5 % -RRB- randomly selected samples were regenotyped with the same method . No inconsistencies were observed . For Sp1 -LRB- intron1 -RRB- an assay was set up using Primer Express Software version 2.0 -LRB- Applied Biosystems , Foster city , CA -RRB- . Forward and reverse primer sequences were 5 ′ - GTTGTCTAGGTGCTGGAGGTT-3 ′ and 5 ′ - GGCGAGGGAGGAGAGAAGG-3 ′ . The PCR mixture included 5 ng of genomic DNA in a 4 μL volume and the following reagents : FAM-CCCGCCCACATTCCCTGG-MGB probes -LRB- 250 nM -RRB- , TET-CCCGCCCCCATTCCCTGG-MGB probe -LRB- 500 nM -RRB- , primers -LRB- 300 nM -RRB- , 2 × Taqman PCR master mix -LRB- Applied Biosystems -RRB- . PCR cycling was performed in 384-well PCR plates in the ABI 9700 PCR system and consisted of initial denaturation for 15 minutes at 95 °C , 40 cycles with denaturation of 15 seconds at 95 °C , and annealing and extension for 60 seconds at 60 °C . Results were analyzed by the ABI Taqman 7900HT using the sequence detection system 2.1 software -LRB- Applied Biosystems -RRB- . To confirm the accuracy of the genotyping results , 332 randomly selected samples were genotyped for a second time with the same method . All polymorphisms had an error rate lower than 1 % . Statistical Analysis Hardy-Weinberg equilibrium of the COLIA1 polymorphism genotypes was tested using the GENEPOP package -LSB- 23 -RSB- . Linkage disequilibrium -LRB- LD -RRB- between each pair of alleles at both polymorphic loci was calculated as D ′ and r2 -LSB- 24 -RSB- . We stratified all analyses by gender , considering peak bone mass , changes in BMD , and fractures , following age - and sex-specific patterns . Baseline BMD and BMD rate of change were compared across COLIA1 polymorphisms using univariate analysis of variance -LRB- ANOVA -RRB- . Corrections were made for age and BMI . Trend analysis assuming an underlying additive genetic model was done for the presence of zero , one , or two copies of the associated allele , incorporating the genotype variable as a continuous term in a general linear regression model . For the analysis of nonvertebral fracture follow-up data , we computed the incidence rates of fracture among genotypes and used Cox 's proportional hazards model , adjusting for age and BMI to estimate risk of fracture . For vertebral fractures , odd ratios with 95 % confidence intervals -LRB- 95 % CIs -RRB- were calculated using logistic regression models since no data on the exact time of occurrence could be determined . We used HaploStats -LRB- available at http://www.cran.r-project.org/ -RRB- to estimate the frequency of inferred haplotypes and investigate the association of haplotypes with BMD and the risk of fractures . We restricted the analysis to haplotypes with an inferred frequency of more than 0.02 . The first haplotype , which was most frequent , was used as reference . Significant P values were 0.05 or lower . Finally , model assumptions were verified and model residuals checked for goodness-of-fit . SPSS 11.0 -LRB- SPSS , Chicago , IL -RRB- was used for the analyses . Results Allele and genotype frequencies of the -1997 G/T and Sp1 polymorphisms were in Hardy-Weinberg equilibrium -LRB- P = 0.61 and P = 0.10 , respectively -RRB- . General characteristics of the study population at baseline and follow-up are shown in Table 1 . Table 1General characteristics of the study population at baseline and second follow-upWomenMenBaselineSecond follow-upBaselineSecond follow-upNumbern = 3,374 n = 1,724 n = 2,452 n = 1,287 Age -LRB- years -RRB- 68.3 ± 8.272.7 ± 6.867.6 ± 7.772.2 ± 6.5 Height -LRB- cm -RRB- 161.1 ± 6.8160.6 ± 6.4174.6 ± 6.8174.0 ± 6.7 Weight -LRB- kg -RRB- 69.3 ± 11.470.3 ± 12.278.2 ± 10.879.5 ± 11.3 BMI -LRB- kg/m2 -RRB- 26.7 ± 4.127.2 ± 4.425.6 ± 3.026.3 ± 3.2FN-BMD -LRB- g/cm2 -RRB- a0 .83 ± 0.140.80 ± 0.130.92 ± 0.140.90 ± 0.14 Lumbar spine BMD -LRB- g/cm2 -RRB- 1.03 ± 0.18-1.16 ± 0.20-FN-BMD changen = 1,527 n = 1,143FN-BMD change -LRB- relative % of baseline year -RRB- b − 0.84 ± 1.09-Values are means ± SD . Anthropometric measurement based on 5,826 individuals at baseline and 3,011 individuals at follow-upaBMD measurements based on 5,737 individual at baseline and 2,670 individual at second follow-upbFemoral neck -LRB- FN -RRB- BMD change was measured between second follow-up and baseline . Second follow-up measurements were performed on average 6.5 -LRB- SD = 0.6 -RRB- years after baseline Baseline BMD by COLIA1 Genotypes In both genders , age , height , weight , and BMI did not differ significantly between genotypes for the -1997 G/T and Sp1 polymorphisms -LRB- data not shown -RRB- . Table 2 shows the BMD values according to COLIA1 genotypes in men and women . Femoral neck BMD was 3.8 % lower -LRB- mean difference = 0.03 g/cm2 , P = 0.09 -RRB- in women who were homozygous carriers of the Sp1 T allele compared to noncarriers , with evidence for an allele dose effect -LRB- P for trend = 0.03 -RRB- -LRB- Table 2 -RRB- . No association was found between the -1997 promoter polymorphism and lumbar spine BMD or femoral neck BMD in men or women -LRB- Table 2 -RRB- . We did not observe any significant association between the Sp1 and -1997 promoter polymorphisms with changes in BMD during follow-up in men or women -LRB- Table 2 -RRB- . Table 2BMD measurements by COLIA1 genotypes at baseline and follow-upPromoter -1997 G/TIntron 1 Sp1 G/TGGGTTTP * GGGTTTP * Menn = 1,663 n = 494n = 37n = 1,484 n = 655n = 55Femoral neck -LRB- g/cm2 -RRB- 0.92 ± 0.130.92 ± 0.140.90 ± 0.141.000.92 ± 0.140.92 ± 0.140.90 ± 0.120.45 Lumbar spine -LRB- g/cm2 -RRB- 1.16 ± 0.191.17 ± 0.201.15 ± 0.220.961.17 ± 0.191.16 ± 0.201.16 ± 0.200.91 Numbern = 668n = 233n = 16n = 606n = 293n = 18FN-BMD change -LRB- relative % of baseline year -RRB- − 0.46 ± 0.91 − 0.36 ± 0.93 − 0.38 ± 0.600.62 − 0.39 ± 0.93 − 0.56 ± 0.87 − 0.30 ± 0.820.01 Womenn = 2,157 n = 710n = 53n = 1,971 n = 858n = 91Femoral neck -LRB- g/cm2 -RRB- 0.83 ± 0.140.84 ± 0.130.85 ± 0.130 . 220.83 ± 0.130.82 ± 0.140.80 ± 0.140.09 ** Lumbar spine -LRB- g/cm2 -RRB- 1.03 ± 0.181.04 ± 0.181.01 ± 0.180.691.04 ± 0.181.04 ± 0.191.01 ± 0.200.52 Numbern = 820n = 298n = 24n = 773n = 340n = 29FN-BMD change -LRB- relative % of baseline year -RRB- − 0.84 ± 1.11 − 0.83 ± 1.01 − 0.78 ± 1.030.85 − 0.85 ± 1.08 − 0.80 ± 1.04 − 0.74 ± 1.490.55 Values are expressed as mean ± SD . Adjustments for age and BMI . Femoral neck -LRB- FN -RRB- BMD change was measured between second follow-up and baseline * P for ANOVA . ** For trend linear regression : P = 0.03 Risk of Fracture by COLIA1 Genotypes The relation between risk of fracture and COLIA1 Sp1 polymorphism is shown in Table 3 . Women with two copies of the T allele of the Sp1 polymorphism had a 2.3 times higher risk of fragility fracture -LRB- 95 % CI 1.4-3.9 , P = 0.001 -RRB- . Adjustment for femoral neck BMD did not essentially modify the association . A similar association was observed in men who were homozygous carriers of the Sp1 T allele , which was borderline significant -LRB- risk ratio = 2.3 , 95 % CI 0.9 -- 5.8 , P = 0.07 -RRB- . For the -1997 promoter polymorphism no association was found with any type of fracture in either men or women -LRB- Table 3 -RRB- . Table 3Risk of fractures by COLIA1 genotypesCOLIA1 genotypesTypes of fractureEvent -LRB- % -RRB- Risk ratio -LRB- 95 % CI -RRB- GGGTTTGG -LRB- reference -RRB- GT vs. referenceTT vs. referenceMenPromoter -1997 G/TNonvertebral147/1952 -LRB- 7.5 -RRB- 49/592 -LRB- 8.3 -RRB- 1/46 -LRB- 2.2 -RRB- 1.0 -LRB- reference -RRB- 3.18 -LRB- 0.45 -- 22.74 -RRB- 3.44 -LRB- 0.47 -- 29.94 -RRB- Fragility72/1952 -LRB- 3.7 -RRB- 14/592 -LRB- 2.4 -RRB- 1/46 -LRB- 1.8 -RRB- 1.0 -LRB- reference -RRB- 1.46 -LRB- 0.20 -- 10.55 -RRB- 0.94 -LRB- 0.12.7.14 -RRB- Vertebral100/1056 -LRB- 9.5 -RRB- 35/340 -LRB- 10.3 -RRB- 3/28 -LRB- 10.7 -RRB- 1.0 -LRB- reference -RRB- 1.07 -LRB- 0.71 -- 1.61 -RRB- 1.23 -LRB- 0.36 -- 4.18 -RRB- Intron 1 Sp1 G/TNonvertebral91/1254 -LRB- 7.3 -RRB- 39/574 -LRB- 6.8 -RRB- 4/44 -LRB- 9.1 -RRB- 1.0 -LRB- reference -RRB- 0.97 -LRB- 0.71 -- 1.33 -RRB- 1.40 -LRB- 0.65 -- 3.00 -RRB- Fragility36/1254 -LRB- 2.9 -RRB- 14/574 -LRB- 2.4 -RRB- 2/44 -LRB- 4.5 -RRB- 1.0 -LRB- reference -RRB- 0.94 -LRB- 0.58 -- 1.51 -RRB- 2.34 -LRB- 0.94 -- 5.85 -RRB- Vertebral68/719 -LRB- 9.5 -RRB- 31/350 -LRB- 8.9 -RRB- 2/22 -LRB- 9.1 -RRB- 1.0 -LRB- reference -RRB- 0.83 -LRB- 0.55 -- 1.24 -RRB- 1.59 -LRB- 0.60 -- 4.22 -RRB- WomenPromoter -1997 G/TNonvertebral528/2721 -LRB- 19.4 -RRB- 182/879 -LRB- 20.7 -RRB- 8/63 -LRB- 12.7 -RRB- 1.0 -LRB- reference -RRB- 1.53 -LRB- 0.76 -- 3.09 -RRB- 1.66 -LRB- 0.82 -- 3.36 -RRB- Fragility216/2721 -LRB- 7.9 -RRB- 73/879 -LRB- 8.3 -RRB- 4/63 -LRB- 6.3 -RRB- 1.0 -LRB- reference -RRB- 1.13 -LRB- 0.42 -- 3.05 -RRB- 1.19 -LRB- 0.44 -- 3.26 -RRB- Vertebral159/1320 -LRB- 12.0 -RRB- 52/445 -LRB- 11.7 -RRB- 5/35 -LRB- 14.3 -RRB- 1.0 -LRB- reference -RRB- 0.98 -LRB- 0.70 -- 1.37 -RRB- 1.31 -LRB- 0.49 -- 3.45 -RRB- Intron 1 Sp1 G/TNonvertebral279/1626 -LRB- 17.2 -RRB- 121/710 -LRB- 17.0 -RRB- 17/76 -LRB- 22.4 -RRB- 1.0 -LRB- reference -RRB- 1.05 -LRB- 0.90 -- 1.23 -RRB- 1.34 -LRB- 0.92 -- 1.23 -RRB- Fragility98/1626 -LRB- 6.0 -RRB- 42/710 -LRB- 5.9 -RRB- 10/76 -LRB- 13.2 -RRB- 1.0 -LRB- reference -RRB- 1.01 -LRB- 0.78 -- 1.31 -RRB- 2.33 -LRB- 1.39 -- 3.87 -RRB- Vertebral98/891 -LRB- 11.0 -RRB- 51/401 -LRB- 12.7 -RRB- 3/34 -LRB- 8.8 -RRB- 1.0 -LRB- reference -RRB- 1.21 -LRB- 0.88 -- 1.65 -RRB- 1.37 -LRB- 0.56 -- 3.35 -RRB- Adjustments for age and BMI Haplotype Analysis High LD exists between the -1997 G/T and Sp1 polymorphisms , as assessed by D ′ measure -LRB- D ′ = 0.99 , r2 = 0.03 -RRB- . We observed in our population three -1997 G/T , Sp1 G/T haplotype alleles -LRB- Fig. 1 -RRB- : haplotype 1 -LRB- Gpromoter -- GIntron -RRB- , 69.0 % ; haplotype 2 -LRB- Gpromoter -- TIntron -RRB- , 17.6 % ; and haplotype 3 -LRB- Tpromoter -- GIntron -RRB- , 13.4 % . Haplotype 4 -LRB- Tpromoter -- TIntron -RRB- was not present -LRB- Fig. 1 -RRB- . The strong LD between the -1997 G/T and Sp1 G/T polymorphism and the virtual nonexistence of haplotype 4 suggests there is absence of ancestral recombination in the region . We observed a borderline significant association -LRB- P = 0.06 -RRB- between haplotype 2 -LRB- Gpromoter -- TIntron -RRB- and femoral neck BMD in women . Women who carried haplotype 2 -LRB- Gpromoter -- TIntron -RRB- had lower -LRB- − 0.01 mg/cm2 -RRB- femoral neck BMD compared with those who carried haplotype 1 -LRB- Gpromoter -- GIntron -RRB- . Fig. 1Schematic representation of the COLIA1 gene with the structural-1997 G/T polymorphism in the promoter region and G/T Sp1 polymorphism at binding site , with observed haplotype frequencies in the Rotterdam Study The relation between risk of fracture and COLIA1 haplotypes is shown in Table 4 . Women with haplotype 2 -LRB- Gpromoter -- TIntron -RRB- had a 2.1 times higher relative risk of fragility fracture -LRB- P = 0.03 -RRB- ; in men the increase in risk was 2.0 -LRB- P = 0.31 -RRB- . These results were essentially unchanged after adjustment for femoral neck BMD . For haplotype 3 -LRB- Tpromoter -- GIntron -RRB- we found no association with any type of fracture in either men or women . Table 4Risk of fracture by COLIA1 haplotypesTypes of fractureMen , OR -LRB- 95 % CI -RRB- Women , OR -LRB- 95 % CI -RRB- Haplotype 1Haplotype 2Haplotype 3Haplotype 1Haplotype 2Haplotype 3Nonvertebral1 -LRB- reference -RRB- 1.29 -LRB- 0.55 -- 3.02 -RRB- 0.00 -LRB- 0.00 - ∞ -RRB- 1 -LRB- reference -RRB- 1.31 -LRB- 0.83 -- 2.07 -RRB- 0.61 -LRB- 0.29 -- 1.29 -RRB- Fragility1 -LRB- reference -RRB- 2.01 -LRB- 0.71 -- 5.67 -RRB- 0.00 -LRB- 0.00 - ∞ -RRB- 1 -LRB- reference -RRB- 2.12 -LRB- 1.23 -- 3.66 -RRB- 0.80 -LRB- 0.29 -- 2.23 -RRB- Vertebral1 -LRB- reference -RRB- 1.64 -LRB- 0.62 -- 4.31 -RRB- 1.19 -LRB- 0.35 -- 4.00 -RRB- 1 -LRB- reference -RRB- 1.23 -LRB- 0.51 -- 2.95 -RRB- 1.31 -LRB- 0.50 -- 3.42 -RRB- Adjustments for age and BMI . Haplotype 1 , -LRB- Gpromoter -- GIntron -RRB- ; haplotype 2 , -LRB- Gpromoter -- TIntron -RRB- ; haplotype 3 , -LRB- Tpromoter -- GIntron -RRB- Discussion In this large population-based study , we found that the Sp1 polymorphism influences the risk of fragility fracture in elderly women , with a similar yet not significant effect in men . Similarly , women homozygous for the T allele had 3.8 % lower BMD at baseline . The -1997 G/T polymorphism showed no independent effect on fracture risk or BMD levels in both genders . The haplotype analysis showed an association with BMD and fracture in women , which appeared to be driven by the effect of the Sp1 polymorphism . A study in Spain -LSB- 19 -RSB- showed that the -1997 G/T polymorphism located in the promoter region of the COLIA1 gene was associated with BMD in postmenopausal women of Spanish origin . In addition , analysis of compound genotypes of the three studied polymorphisms -LRB- -1997 G/T , Sp1 , and -1663 indelT -RRB- suggested that the lowest value for BMD corresponded to GG homozygous at -1997 and heterozygous at the other two loci . Furthermore , in another report , the same group observed a possible functional mechanism for the -1997 G/T polymorphism -LSB- 25 -RSB- . Our population-based study suggests there is no independent effect of the -1997 polymorphism on BMD and the risk of fractures . Recently , Stewart et al. -LSB- 26 -RSB- examined the three polymorphisms of the COLIA1 gene in forms of haplotypes in postmenopausal women . In contrast with our study , they observed an association between reduced BMD values and the promoter -- 1997G/T polymorphism . Since the promoter -1997 G/T polymorphism is in strong LD with the Sp1 polymorphism , the observed association of haplotype 2 is driven by the SP1 polymorphism . We showed that the association between fragility fractures and Sp1 polymorphism is significant only in women . We also found that the association between fragility fracture and the Sp1 polymorphism was independent of femoral neck BMD . A possible explanation for an increased risk of fracture is the different number of fractures between men and women . There are a higher number of fractures in women compared to men -LRB- 13.2 % in women and 4.5 % in men -RRB- . This suggests that other underlying biological mechanisms beyond BMD levels , such as the role of microarchitecture and composition of mineral crystals in bone tissue , might explain the increased fracture risk -LSB- 11 , 27 , 28 -RSB- . Biomechanical testing of bone samples from heterozygous individuals with the GT genotype showed reduced bone strength compared to the homozygous GG genotype and a slight reduction in mineralization of bone -LSB- 11 -RSB- . Presence of the T allele in the COLIA1 Sp1 binding site leads to an abnormal relative level of COLIA1/COLIA2 , which may reduce bone quality and quantity -LSB- 11 -RSB- . Accordingly , we assume that a weaker network of abnormal collagen cross-linking may generate a three-dimensional unstable condition that may be responsible for its relatively greater risk of fragility fracture in elderly women homozygous for the Sp1 T allele . Similarly , it is likely that the Sp1 polymorphism drives these associations since evidence of functionality of this polymorphism has been reported previously . In the Genetic Markers for Osteoporosis -LRB- GENOMOS -RRB- Study , which is the largest study examining the Sp1 polymorphism -LRB- n = 20,786 -RRB- in relation to osteoporosis , an association between the Sp1 polymorphism and a 1.3 times incident risk of vertebral fractures was also observed . An effect of the -1997 promoter polymorphism due to power limitations can not be fully excluded and should be subject to study in a larger population like that of GENOMOS . Our present study has some limitations . Survival bias may play a role if individuals who were lost to follow-up were associated to genotype . Considering this selection bias , a possible relationship of the COLIA1 polymorphisms with changes in BMD can not be fully excluded . In conclusion , we observed an increased risk of fragility fractures in women carriers of the COLIA1 Sp1 T allele . In contrast , the -1997 G/T polymorphism by itself appears to have no influence on fracture or BMD in postmenopausal women , though the role of power limitations can not be excluded .

O O O O O O O O O O O O O B O O O O O O O O O B O O O O O O B O O O O O O O O B O O O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B O O B O O O O O O O O O O O O O O O O O O B O O O O O O O O O B O O O O O O O O O B O O O O O O O O O O O O O B O O O O B O O O O O O O O B O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O B O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O B O O O O O O O O O O O O O O O O B O O O O O O O O O B O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O B O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O B O O O O O O B O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O B O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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