Genetics%20of%20Osteoporosis

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Genetics of Osteoporosis
Dr. Tuan V. NguyenAssociate Professor, Senior
FellowBone and Mineral Research ProgramGarvan
Institute of Medical ResearchSydney, Australia
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Overview

• Osteoporosis definition and consequences
• Risk factors of fracture
• Genetics of bone mineral density
• Gene hunting
• Candidate genes
• Future ?

3
Increase in life expectancy
WHO. Human Population Fundamentals of Growth
World Health, 2000.
4
The ageing of population
Percent of population aged 65
ABS and US Bureau of Census, 1996.
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Osteoporosis definitions
compromised bone strength predisposing a
person to an increased risk of fracture. Bone
strength primarily reflects the integration of
bone density and bone quality (NIH Consensus
Development Panel on Osteoporosis JAMA
285785-95 2001)
Osteoporosis ? Risk factor Fracture ? Outcome
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Incidence of all-limb fractures
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Annual fracture incidence in Australia 1996-2051
Projected annual number of all-limb fractures in
Australia aged 35 (Sanders et al, MJA 1999)
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Hip, vertebrae, and Colles fractures
Fracture 2006 2051
Hip 20,700 60,000
Vertebrae 14,500 31,700
Colles 11,900 23,000
Humerus 7,500 16,300
Pelvis 4,100 9,800
Projected annual number of all-limb fractures in
Australia aged 35(Sanders et al, MJA 1999)
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Lifetime risk of some diseases - women
Any osteoporotic fracture Hip fracture Clinical
vertebral fracture Cancer (any site) Breast
cancer Lung/bronchus Coronary heart
diseases Diabetes Mellitus
, from birth
(from the age of 50)
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Lifetime risk of some diseases - men
Any osteoporotic fracture Hip fracture Clinical
vertebral fracture Cancer (any site) Prostate
cancer Lung/bronchus Coronary heart
diseases Diabetes Mellitus
, from birth
(from the age of 50)
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Survival probability in thosewith and without
fracture
Nguyen et al, 2005
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Risk factors of fracture
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A model for predicting fracture
Bone mineral Density (BMD)
Bone strength
Bone quality (ultrasound ?)
Fracture
Fall
Trauma / mechanical
Force of impact
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Risk factors for low bone mass
Smoker
Age (per 5 years)
Maternal history of fx
Steroid use
Caffeine intake
Activity score
Age at menopause
Milk intake
Ever pregnant
Surgical menopause
Waist/hip ratio
Weight
Grip strength
Height
Thiazide use
Oestrogen use
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Risk factors for low BMD
Genetics Race, Sex, Familial prevalence Hormones
Menopause, Oophorectomy, Body
composition Nutrition Low calcium intake, High
caffeine intake, High sodium intake, High
animal protein intake Lifestyles Cigarette use,
High alcoholic intake, Low level of physical
activity Drug Heparin, Anticonculsants,
Immunosuppressants Chemotherapy,
Corticosteroids, Thyroid hormone
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Change in BMD with Age
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Bone mineral density and fracture
T lt 2.5 osteoporosis
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Low BMD and fracture - women
1287women
Osteoporosis 345 (27)
Non-osteop. 942 (73)
Fx 137 (40)
No Fx 208 (60)
No Fx 751 (80)
Fx 191 (20)
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Interaction between BMD and falls
Nguyen et al, JBMR 2005
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Genetics of Osteoporosis
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Heritability of femoral neck BMD
DZ
MZ
r 0.75
r 0.45
Nguyen et al, Am J Epidemiol 1998
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Genetics of fracture risk

• MZ twins have higher concordance in fracture rate
  than DZ twins (Kannus, BMJ 1999)
• Around 1/3 variance of fracture risk is due to
  genetic factors (Deng et al, JBMR 2000)

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Gene search

• Genotype

Phenotype
Mathematical function
Fracture Bone mineral density Quantitative
ultrasound
Polymorphisms Genetic markers SNPs
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Strategies for gene search

• Linkage analysis
• Association analysis

• Genome-wide screen
• Candidate gene

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Linkage analysis identical by descent (ibd)
AB
AC
AB
CD
AB
CD
AB
AC
AC
AD
BC
BC
IBD 0
IBD 1
IBD 2
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Linkage analysis basic model
Squared difference in BMD among siblings
o
o
o
o
Regression line
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
0 1 2
Number of alleles shared IBD
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Population-based association analysis
Fracture
AB
AC
BC
AA
AB
BB
AA
AC
AB
AC
No fracture
BB
BC
BC
CC
AB
BB
CC
BC
BB
AC
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Family-based association analysis
AB
AA
AB
AC
BC
AA
AB
BC
AB
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Genome-wide vs candidate gene approach

• Genome-wide screen

Candidate gene analysis
Complex No prior knowledge of mechanism Expensive
No specific genes
Simple Prior knowledge of mechanism Inexpensive Sp
ecific genes
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Linkage vs association phenomena
Linkage Association
Magnitude of effect No Yes
Transmission Yes No/Yes
Study design complexity Complex Simple
Power Low High
False ve High High
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Some recent osteoporosis genes

• Vitamin D receptor gene (Morrison et al, Nature
  1994)
• Collagen I alpha 1 gene COLIA1 (Grant et al,
  Nat Genet, 1996).
• LRP5 gene (Am J Hum Genet, 1998)

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Candidate genes of osteoporosis
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Localization of genes for BMD
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VDR, COLIA1 and fracture
Risk Genotype Prevalence () Relative Risk1 Attributable Risk Fraction ()
Taq-1 tt 15.4 2.6 19.8
Sp-1 ss 5.0 3.8 12.3
tt AND ss 1.0 3.0 2.0
tt OR ss 19.8 3.5 32.1
Nguyen et al, JCEM 2005
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Poor replication of genetic associations

• 600 positive associations between common gene
  variants and disease reported 1986-2000
• 166 were studied 3 times
• 6 have been consistently replicated

J N Hirschhorn et al. Genetics in Medicine 2002
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Evolution of the strength of an association as
more information is accumulated Ioannidis et
al, Nat Genet 2001
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Problems of gene search p-value

• Traditional model of inference
• Hypothesis H
• Collecting data D
• Computing p-value Pr(D H)
• If p-value lt 0.05 ? reject H
• If p-value gt 0.05 ? accept H

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The logic of P-value

• If Tuan has hypertension, he is unlikely to have
  red hair
• Tuan has red hair
• Tuan is unlikley to have hypertension

• If there was truly no association, then the
  observation is unlikely
• The observation occurred
• The no-association hypothesis is unlikely

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Diagnostic analogy
Has cancer test ve OK
Has cancer test ve ! (false -ve)
No cancer test ve ! (false ve)
No cancer test ve OK
Diagnosis
Genetic research
Association Significant Power
Association NS
No assoc. Significant P-value
No assoc. NS
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What do we want to know?

• Clinical
• P(ve cancer), or
• P(cancer ve) ?
• Research
• P(Significant test Association), or
• P(Association Significant test) ?

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Breast cancer screening
Prevalence 1 Sensitivity 90 Specificity
91
Population
Cancer (n10)
No Cancer (n990)
ve N9
-ve N900
-ve N1
ve N90
P(Cancer ve result) 9/(990) 9
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Probability of a true association
Prior prob. association 0.05 Power 90
P-value 5
1000 SNPs
True (n50)
False (n950)
ve N45
-ve N902
-ve N5
ve N48
P(True association ve result) 45/(4548) 48
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Risk factors for fracture

• Blonde hair
• Being tall
• Wear trouser (women)
• High heel (women)

• Drinking coffee
• Drinking tea
• Coca cola
• High protein intake

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• Half of what doctors know is wrong.
  Unfortunately we dont know which half.
• Quoted from the Dean of Yale Medical School, in
  Medicine and Its Myths, New York Times
  Magazine, 16/3/2003

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Can genes be used to predict fracture?
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Genetics in medicine hope

• within the next decade genetic testing will be
  used widely for predictive testing in healthy
  people and for diagnosis and management of
  patients. . . . The excitement in the field has
  shifted to the elucidation of the genetic basis
  of the common diseases. (J Bell, BMJ 1998)
• new understanding of genetic contributions to
  human disease and the development of rational
  strategies for minimizing or preventing disease
  phenotypes altogether. (F. S Collins NEJM 1999)

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Positive predictive value as a function of gene
frequency and relative risk
What is the probability that I will sustain a
fracture if I have high risk genotype?
Susceptibility genotype frequency Relative Risk 1.5 Relative Risk 2.0 Relative Risk 5.0 Relative Risk 10
0.1 15.0 20.0 49.8 99.1
0.5 15.0 19.9 49.0 95.7
1 14.9 19.8 48.1 91.7
10 14.3 18.2 35.7 52.6
20 13.6 16.7 27.8 35.7
PPV () of susceptibility genotype for a disease
with lifetime risk of 10
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Positive predictive value as a function of gene
frequency and relative risk and co-factor
Frequency of co-factor Frequency of genotype RR associated with co-factor 2.0 RR associated with co-factor 5
Disregard co-factor 19.8 19.8
1 1 39.2 95.2
1 10 33.0 55.0
5 1 38.7 91.6
5 10 34.6 68.0
10 1 52.9 87.4
10 10 36.0 64.9
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How many fractures are due to genes?
Population attributable risk fraction as a
function of gene frequency and relative risk
Susceptibility genotype frequency RR1.5 RR2.0 RR5.0 RR10
0.1 0.05 0.1 0.4 0.9
0.5 0.25 0.5 2.0 4.3
1 0.5 1.0 3.9 8.3
10 4.8 9.1 28.6 47.4
20 9.1 16.7 44.4 64.3
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Summary

• Osteoporosis and fracture serious public health
  problem
• Bone mineral density primary predictor of
  fracture risk
• BMD is largely regulated by genetic factors

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Summary

• BMD is largely regulated by genetic factors
• Finding genes for fracture challenge
• Genetics, clinical medicine, statistics,
  bioinformatics
• Predictive value of genes in fracture prediction
  consider environmental risk factors