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Genetic Epidemiological StrategiesGenetic Epidemiological Strategiesto the Search for Osteoporosis Genesto the Search for Osteoporosis Genes
Dr. Tuan V. NguyenBone and Mineral Research ProgramGarvan Institute of Medical Research
Sydney, Australia
• Epidemiologic results
• Clinical features of osteoporosis
• Determinants of fracture risk
• Genetics of bone mineral density
• The search for osteoporosis genes
Contents of PresentationContents of Presentation
Osteoporosis is a metabolic bone disease, which is characterised by low bone mass, microarchitectural deterioration of bone tissue leading to enhanced bone fragility and a consequent increase in fracture risk
(Consensus Development Conference, 1991)
DefinitionDefinition
Magnitude of the ProblemMagnitude of the Problem
0
10
20
30
40
50
60
70
80
60-64 65-69 70-74 75-79 80+
0
2000
4000
6000
8000
10000
12000
60-64 65-69 70-74 75-79 80+
Males
Females
Incidence of all FracturesIncidence of all FracturesPrevalence of OsteoporosisPrevalence of Osteoporosis
% Per 100,000
Incidence of Hip Fx WorldwideIncidence of Hip Fx Worldwide
Type of FracturesType of Fractures
Types of FracturesTypes of Fractures
Fracture
Bone strength
Trauma
Bone density
Bone quality
Fall
Force impact
A Model of FractureA Model of Fracture
Females Unit Relative Risk
Femoral neck BMD 0.12 g/cm2 2.1 (1.6 - 2.6)
Falls Each fall 2.4 (1.5 - 3.8)
Postural sway 2000 mm2 1.3 (1.1 - 1.5)
Males
Femoral neck BMD 0.12 g/cm2 2.4 (1.6 - 3.7)
Falls Each fall 3.9 (1.7 - 9.3)
Age 5 years 1.7 (1.2 - 2.3)
Risks Factors for Hip FracturesRisks Factors for Hip Fractures
Relationship between Fracture and Bone Mineral Density
Relationship between Fracture and Bone Mineral Density
Change in BMC and BMD with AgeChange in BMC and BMD with Age
Baseline age
Perc
ent p
er y
ear
-10
0
10
20
30
40
50
5 10 15 20 25
Baseline age
Perc
ent p
er y
ear
-10
0
10
20
30
40
50
5 10 15 20 25
Hip BMC
Spine BMC
Baseline age
Perc
ent p
er y
ear
-2
2
6
10
14
4 8 12 16 20 24 28
Baseline age
Perc
ent p
er y
ear
-2
2
6
10
14
5 10 15 20 25
Hip BMD
Spine BMD
Determinants of Peak Bone MassDeterminants of Peak Bone Mass
Peak Bone Mass
16-25 yr of age
Genetic factors
Exercise and
environmental factors
Hormonal factorsNutritional factors
Risk Factors for OsteoporosisRisk Factors for Osteoporosis
GeneticsGenetics Race, Sex, Familial prevalence
HormonesHormones Menopause, Oophorectomy, Body composition
NutritionNutrition Low calcium intake, High caffeine intake, High sodium intake, High animal protein intake
LifestylesLifestyles Cigarette use, High alcoholic intake, Low level of physical activity
DrugDrug Heparin, Anticonculsants, Immunosuppressants Chemotherapy, Corticosteroids, Thyroid hormone
-8 -6 -4 -2 0 2 4 6 8
Percent change in BMD
SmokerAge (per 5 years)Maternal history of fxSteroid use
Caffeine intakeActivity score
Age at menopause
Milk intakeEver pregnant
Surgical menopauseWaist/hip ratio
Weight
Grip strengthHeight
Thiazide use
Oestrogen use
Risk factors for Low Bone DensityRisk factors for Low Bone Density
Genetics of Bone Mineral Density
Clues to Genetics and EnvironmentClues to Genetics and EnvironmentClues to Genetics and EnvironmentClues to Genetics and Environment
Epidemiol characteristics Genetics EnvironmentGeographic variation + +Ethnic variation + +Temporal variation - +Epidemics +/- +Social class variation - +Gender variation + +Age +/- +Family variables
History of disease + +Birth order +/- +Birth interval - +Co-habitation - +
Methods of InvestigationMethods of InvestigationMethods of InvestigationMethods of Investigation
• Family studies. Examine phenotypes (diseases) in the relatives of affected subjects (probands).
• Twin studies. Examine the intraclass correlation between MZ (who share 100% genotypes) and DZ twins (who share 50% genotypes).
• Adoption studies. Seek to distinguish genetic from environmental effects by comparing phenotypes in children more closely resemble their biological than adoptive parents.
• Offspring of discordant MZ twins. Control for environmental effect; test for large genetic contribution to etiology.
Basic Genetic ModelBasic Genetic ModelBasic Genetic ModelBasic Genetic Model
Phenotype (P) = Genetics + Environment
Genetics = Additive (A) + Dominant (D)
Environment = Common (C) + Specific (E)
=> P = A + D + C + E
Statistical Genetic ModelStatistical Genetic ModelStatistical Genetic ModelStatistical Genetic Model
Cov(Yi,Yj) = 2ij2(a) + ij2(d) + ij2(c) + ij2(e)
ij : kinship coefficient
ij : Jacquard’s coefficient of identical-by-descent
ij : Probability of sharing environmental factors
ij : Residual coefficient
VP = VA + VD + VC + VE
V = variance; P = Phenotype; A, D, C, E = as defined
Expected Kinship CoefficientsExpected Kinship CoefficientsExpected Kinship CoefficientsExpected Kinship Coefficients
Expected coefficient forRelative 2(a) 2(d) 2(c)Spouse-spouse 0 0 1Parent-offspring 1/2 0 1Full sibs 1/2 1/4 1Half-sibs 1/4 0 1Aunt-niece 1/4 0 1First cousins 1/8 0 0Dizygotic twins 1/2 1/4 1Monozygotic twins 1 1 1
Twin 1 Twin 2
E1 C1 D1 A1 A2 D2 C2 E2
A Genetic Model for Twins StudyA Genetic Model for Twins StudyA Genetic Model for Twins StudyA Genetic Model for Twins Study
r = 1
r = .5 / .25
r = 1 / .5
a c d e a d c e
A=additive; D=dominant; C=common environment; E=specific environment
0.5
0.6
0.7
0.8
0.9
1
1.1
1.2
1.3
1.4
0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4
Twin 1
Tw
in 2
0.5
0.6
0.7
0.8
0.9
1
1.1
1.2
1.3
1.4
0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4
Twin 1
Tw
in 2
Intraclass Correlation: Femoral Neck BMDIntraclass Correlation: Femoral Neck BMDIntraclass Correlation: Femoral Neck BMDIntraclass Correlation: Femoral Neck BMD
MZ DZ
rMZ = 0.73 rMZ = 0.47
rMZ rDZ H2 (%)
Lumar spine BMD 0.74 (0.06) 0.48 (0.10) 77.8
Femoral neck BMD 0.73 (0.06) 0.47 (0.11) 76.4
Total body BMD 0.80 (0.05) 0.48 (0.10) 78.6
Lean mass 0.72 (0.06) 0.32 (0.12) 83.5
Fat mass 0.62 (0.08) 0.30 (0.12) 64.8
Genetic Determination of Lean, Fat and Bone MassGenetic Determination of Lean, Fat and Bone MassGenetic Determination of Lean, Fat and Bone MassGenetic Determination of Lean, Fat and Bone Mass
rMZ and rDZ are shown in coefficient of correlation and standard error in brackets;H2, Heritability index: proportion of variance of a traited attributed to genetic factors
Multivariate Analysis: Multivariate Analysis: The Cholesky Decomposition ModelThe Cholesky Decomposition Model
Multivariate Analysis: Multivariate Analysis: The Cholesky Decomposition ModelThe Cholesky Decomposition Model
Leanmass
Fatmass
LSBMD
FNBMD
TBBMD
E1 E2 E3 E4 E5
G1 G2 G3 G4 G5
LS=lumbar spine, FN=femoral neck, TB=total body, BMD = bone mineral density
LM FM LS FN TB
Lean mass (LM) 0.52 0.39 0.23 0.51
Ft mass (FM) 0.16 0.41 0.36 0.70
Lumbar spine BMD (LS) 0.08 0.02 0.57 0.70
Femoral neck BMD (FN) 0.16 0.05 0.64 0.61
Total body BMD (TB) 0.09 0.31 0.75 0.58
Genetic and Environmental Correlation between Genetic and Environmental Correlation between Lean, Fat and Bone MassLean, Fat and Bone Mass
Genetic and Environmental Correlation between Genetic and Environmental Correlation between Lean, Fat and Bone MassLean, Fat and Bone Mass
Upper diagonal: genetic correlation; lower diagonal: environmental correlationLS=lumbar spine, FN=femoral neck, TB=total body, BMD = bone mineral density
Strategies for Finding GenesStrategies for Finding GenesStrategies for Finding GenesStrategies for Finding Genes
How many genes ?How many genes ?How many genes ?How many genes ?
• Initial estimate: 120,000.
• DNA sequence: 60,000 - 70,000.
• Estimates from the Human Genome Project: 32,000 - 39,000 (including non-functional genes = inactive genes).
• Osteporosis genes = 50 - 70 (?)
Effect size
Num
ber of genes
Major genes
Polygenes
Oligogenes
Distribution of the number of genesDistribution of the number of genes
Finding genes: a challengeFinding genes: a challenge
One of the most difficult challenges ahead is to find genes involved in diseases that have a complex pattern of inheritance, such as those that contribute to osteoporosis, diabetes, asthma, cancer and mental illness.
Why search for genes?Why search for genes?
• Scientific value • Study genes’ actions at the molecular level
• Therapeutic value• Gene product and development of new drugs;
• Gene therapy
• Public health value• Identification of “high-risk” individuals
• Interaction between genes and environment
Genomewise screening vs Genomewise screening vs Candidate geneCandidate gene
• Genome-wide screening approach• No physiological assumption
• Systematic screening for chromosomal regions of interest in the entire genome
• Candidate gene approach• Proven or hypothetical physiological mechanism
• Direct test for individual genes
Linkage vs AssociationLinkage vs Association
• Linkage– traces cosegregation and recombination phenomena between
observed markers and unobserved putative trait. Significance is shown by a LOD (log-odds) score.
• Association – compares the frequencies of alleles between unrelated cases
(diseased) and controls.
• Transmission disequilibrium test (TDT)– examines the transmission of alleles from heterozygous parents to
those children exhibiting the phenotype of interest.
Two-point linkage analysis: an exampleTwo-point linkage analysis: an exampleTwo-point linkage analysis: an exampleTwo-point linkage analysis: an example
??138 /142
134 /142 146 / 154
142 /146 142 /154 134 / 146 142 / 154 134 / 146 134 / 154 134 / 146 134 / 154
Non Rec Non Non Non Non Rec Non
D142
D142
d134
Non = non-recombination; Rec = recombination
134
142
D d
1/4 1/4
1/41/4
134
142
D d
0 1/2
01/2
134
142
D d
(1-)/2
/2(1-)/2
No linkage Complete linkage
Incomplete linkage
8
26
10
41
221
log
θθ
LOD
Recombination fraction
LODscore
Estimated value of 0 0.1 0.2 0.3 0.4 0.5
Estimation of the recombination fraction Estimation of the recombination fraction
-6
-4
-2
0
+2
+4
+6Max LOD score
A model for sibpair linkage analysisA model for sibpair linkage analysisA model for sibpair linkage analysisA model for sibpair linkage analysis
Xi1 = value of sib 1; Xi2 = value of sib 2 i = abs(Xi1 - Xi2)2
i = probability of genes shared identical-by-descentE(i | i) = + i
If = 0 => 2(g) = 0; = 0.5, i.e. No linkageIf < 0 => 2(g) > 0; ne 0.5, i.e. Linkage
Behav Genet 1972; 2:3-19
Identical-by-Descent (IBD)Identical-by-Descent (IBD)Identical-by-Descent (IBD)Identical-by-Descent (IBD)
126 / 130 134 / 138
126 / 134 126 / 138 130 / 134 130 / 138 126 / 138 A B C D E
• A and D share no alleles• A, B and E share 1 allele (126) ibd; C vs D; A vs C; B, D and E• B and E share 2 (126 and 138) alleles ibd
Alleles ibd if they are identical and descended from the same ancestral allele
oooooooo
o
ooooooooo
ooooooooo
Squareddifference in BMDamong siblings
Number of alleles shared IBD
0 1 2
Sibpair linkage analysis: an exampleSibpair linkage analysis: an exampleSibpair linkage analysis: an exampleSibpair linkage analysis: an example
0
5
10
15
20
25
0 1 2
Alleles shared IBD
Intr
apai
r d
iffe
ren
ce i
n B
MD
(%
)
Nature 1994; 367:284-287
Association analysis: an exampleAssociation analysis: an exampleAssociation analysis: an exampleAssociation analysis: an example
0.8
0.9
1
1.1
BB Bb bb
VDR genotype
g/cm
2
Association between vitamin D receptor gene and bone mineral density
Location Name Symbol1q25 Osteocalcin BGLAP2q13 IL-1 Receptor Antagonist CASR3q21-24 Calcium Sensing Receptor CASR 3q27 2HS Glycoprotein AHSG4q11-13 Vitamin D binding protein DBP/GCv4q21 Osteopontin SPP15q31 Osteonectin SPOCK6q25.1 Estrogen receptor ESR
7p21 Interleukin-6 IL-67q21.3 Calcitonin receptor CALCR7q22 Collagen type I2 COLIA211p15 Parathyroid hormone PTH12q13 Vitamin D receptor VDR17q22 Collagen Type I1 COLIA119q13 Transforming growth factor 1 TGF-119q13 Apolipoprotein E ApoE
Candidate BMD genes : association analysisCandidate BMD genes : association analysisCandidate BMD genes : association analysisCandidate BMD genes : association analysis
Localization of BMD genes in humansLocalization of BMD genes in humansLocalization of BMD genes in humansLocalization of BMD genes in humans
Some notable genesSome notable genesSome notable genesSome notable genes
• Vitamin D receptor (VDR)
• Collagen I alpha 1 (COLIA1)
• Estrogen receptor (ER)
• Interleukin-6 (IL6)
• Transforming growth factor (TGF)
Problems Problems Problems Problems
• None of the candidate genes have clinically meaningful effect on BMD.
• Inconsistent (even conflicting) results.
• Past studies have suffered serious problems in experimental design and methodology.– Association– Inadequate sample size– Univariate analysis– Sibpair analysis
New paradigmsNew paradigmsNew paradigmsNew paradigms
• Sampling design– large multi-generational families
• Phenotypes– consideration of multitraits rather than a single
trait.
• Analysis– Combine linkage and association analyses
• Animal model– Mouse genome and transgenic model
SummarySummarySummarySummary
• Fracture is an ultimate and clinically relevant outcome of osteoporosis.
• BMD is a primary predictor of fracture.
• Variation in BMD is largely determined by genetic factors.
• The search for specific genes that are linked to BMD has not been successful nor productive.
PerspectivePerspective
• Can genes be found? – Definitely.
• The Human Genome Project role? – Very helpful.
• Influences of biotechnology? – Great realization.
• Gene therapy? – Quite possible.
• Lôøi queâ (genes) chaép nhaët doâng daøi
• Mua vui cuõng ñöôïc moät vaøi troáng canh (phuùt giaây)
• Nguyeãn Du