qtl analysis / mutagenesis
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QTL analysis / Mutagenesis
candidate genes
Humanpopulations
functionalstudies
Genetic basis of atherosclerotic organ damage:
From animal genetics to human cohorts
functionalstudies
atherosclerosisrenal damage
HDL cholesterolPLTP activity
Definitions
A quantitative trait is one that has measurable phenotypic variation owing to genetic and/or environmental influences.
A QTL is a genetic locus, the alleles of which affect this variation.
QTL analysis is a statistical method to map these loci in the species under investigation
Members of the Complex Trait Consortium (2003) Nature Reviews Genetics 4:911-916
Principle of QTL analysis (1)
Principle of QTL analysis (2)
Principle of QTL analysis (3)
Advantages of QTL analysis
QTL analysis allows identification of novel genes involved in the phenotype.
QTL mapping is more likely to find mutations in rate limiting or regulatory genes, which will be very important therapeutic targets.
Comparison between species as a search strategy (1):Comparison between species as a search strategy (1):Concordance of Concordance of HDL QTLHDL QTL between human and mouse between human and mouse
atherogenic diet
Apoe or Ldlr KO
human concordance
rabbit concordance
110
220
330
440
550
660
770
880
Ath190
10100
11110
12120
1
p0
110
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330
440
550
660
770
880
990
10100
d114
2
p0
110
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550
660
770
880
990d95
3
p0
110
220
330
440 Ath8
50
660
Athsq170
880d84
4
p0
110
220
330
440
550
660
770
880
990d92
5
p0
110
220
330
440
550
Athsq260
770d75
6
p0
110
220
330
440
Ath350
660
770d74
7
Ath16
Ath9
Artles
p0
110
220
330
440
550
660
770
d80
11
p0Ath6
110
220
330
40
550
660
d66
12
p0
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440
550
660
770
d80
13
p0
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d69
14
Ath18
Ath13
Ath7
Ath19
p0
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660
770
880d82
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p0
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20
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440
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660
770
d79
9
p0
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660
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d77
10
Ath11
Ath17
Ath20
p0
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770
880d81
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p0
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770d72
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p0
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880d82
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p0
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d60
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p0
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d56
19
Comparison between species as a search strategy (2):Comparison between species as a search strategy (2):Concordance of Concordance of atherosclerosis QTLatherosclerosis QTL between human and mouse between human and mouse
Locating Ath8, a locus for murine atherosclerosis susceptibility and testing several of its candidate genes in mice and humans.
Korstanje R, Eriksson P, Samnegard A, Olsson, Forsman-Semb K, Sen S, Churchill G,Rollins J, Harris S, Hamsten A, Paigen B
Atherosclerosis, 2004, 177:443-450
1. QTL for atherosclerosis susceptibility was identified in mouse
2. Candidate genes were tested
3. Gene was identified with likely functional difference
4. Association was found between human homolog and cohort
X
SM/J NZB/B1NJ
F1
F2
258 females
Angptl3 polymorphisms between NZB and SM mice.
Effect on proteinEffect on protein
PositionPosition bpbpaa NZBNZB SMSM domaindomain AAAAbb NZBNZB SMSM
Exon 3Exon 3 736736 AA GG linkerlinker 233233 GluGlu GlyGly
740740 AA CC linkerlinker 234234 ThrThr ThrThr
Exon 4Exon 4 788788 AA TT FHDFHD 250250 TyrTyr PhePhe
abasepair numbering based on Genbank No. XM_131498.bamino acid numbering based upon the first ATG as +1.
Controls Patients P
ANGPTL3_1 AA 153 171A/G 183 143G/G 39 48 <0.05
ANGPTL3_2 G/G 152 170G/A 183 138A/A 39 59 <0.01
Age (years) 53.0±4.8 52.3±5.6 NSSex (men/women) 307/66 304/63 NSBMI (kg/m2) 26.5±11.9 27.4±4.0 NS Plasma triglycerides (mmol/L) 1.37±0.74 1.95±1.21 <0.0001LDL cholesterol (mmol/L) 3.50±0.88 3.23±0.99 <0.0001HDL cholesterol (mmol/L) 1.39±0.41 1.10±0.30 <0.0001Plasma insulin (pmol/L) 42.05±23.67 57.13±40.49 <0.0001Plasma proinsulin (pmol/L) 4.48±3.48 7.21±7.69 <0.0001
ANGPTL3 genotype distribution in patients and controls.
Numbers of genotypes are shown for the two polymorphisms. Continuous values are means±SD
ANGPTL3 genotypes and severity of angiographically determined coronary artery disease in postinfarction patients.
ANGPTL3ANGPTL3_1_1
A/AA/A A/GA/G G/GG/G pp
NN 105105 9292 2929
Plaque areaPlaque area 0.24±0.080.24±0.08 0.22±0.080.22±0.08 0.20±0.050.20±0.05 <0.05 <0.05<0.05 <0.05aa
Min. lumen diameter (mm)Min. lumen diameter (mm) 2.32±0.452.32±0.45 2.32±0.452.32±0.45 2.34±0.512.34±0.51 NSNS
Mean stenosis (%)Mean stenosis (%) 32.44±8.3332.44±8.33 31.63±10.2531.63±10.25 32.45±9.8932.45±9.89 NSNS
Mean segment diameter (mm)Mean segment diameter (mm) 3.02±0.473.02±0.47 3.02±0.433.02±0.43 3.02±0.583.02±0.58 NSNS
Values are shown as means±SD. awhen adjusted for plasma triglyceride concentration. BMI, body mass index; LDL, low density lipoprotein; HDL, high density lipoprotein, insulin, proinsulin and smoking.
Conclusions (part 1)Conclusions (part 1)
Animal models (rat and mouse in particular) can make identifying candidate genes easier because of less genetic complexity, better genetic tools, and a controlled environment
Concordance between mouse, rat, and human QTL allow the use of animal models for candidate gene selection.
HaplotypesHaplotypes
Yalcin, B. et al. (2004) Proc. Natl. Acad. Sci. USA 101, 9734-9739
Haplotype structure of 1,450 diallelic variants with SDP frequency >1% between eight inbred strains (A/J, AKR, BALB/c, C3H, C57BL/6, DBA/2, I, and RIII) across a 4.8-Mb region of mouse chromosome 1
In silicoIn silico mapping (1) mapping (1)
Pletcher et al: 48 inbred strains, 10.990 SNPs
Presence or absence of the retinal degeneration and albino phenotypes was given a numericalvalue of 1 or 0 for use in the mapping algorithm. The most significant P value was obtained for the region that contains the gene known to produce these phenotypes.
In silicoIn silico mapping (2) mapping (2)
Comparison of in silico QTL with experimentally derived QTL
In silicoIn silico mapping (3) mapping (3)
Analysis of Adcy7 haplotypes reveals amino acid associated with HDL phenotypes
Kidney disease QTL are concordant in rat, human, and mouse
Korstanje and DiPetrillo, AJP Renal, 287:F347-F352
Promising regions for renal damage Promising regions for renal damage are our current focusare our current focus
Korstanje and DiPetrillo, AJP Renal, 287:F347-F352
Analysis of QTL studies and haplotypesAnalysis of QTL studies and haplotypes
D9Rat29
D9Rat26
D9Mit3
D9Mco6
UAE16LOD 8.0SSxSHR16 wkmalesGarrett et al
UAE25LOD 3.5MWFxSHR14 wkmalesSchulz et al
SSxSHR8 wkmalesMehr et al
0
50
100
D9Rat64
D9Rat3
NO QTL
MWFxLew14 wkmales/femalesSchulz et al
Haplotype analysis narrows QTL intervalHaplotype analysis narrows QTL intervaland excludes many genes and excludes many genes
Test candidate genes for sequence Test candidate genes for sequence and expression differences between strains and expression differences between strains
Lewis MWF
SHR Dahl SS
Lewis
8 wks
Lewis
16 wks
SHR
8 wks
SHR
16 wks
Dahl SS
8 wks
Dahl SS
16 wks
MWF
16 wks
MWF
16 wks
Quantifying Complex Traits:Quantifying Complex Traits:
Epidemiology of Phenotype-Genoype InteractionsEpidemiology of Phenotype-Genoype Interactions
Mike W. ZuurmanMike W. Zuurman
P
PG
G G
EF
Environment
Individual
EF
Complex Traits Diagram
FP
EF
EF
1
1. env. response to phenotype (treatment), 2. env. influence on gene expression, 3. env. inducing internal phenotype, 4. env. influencing expression of unknown gene, 5. phenotypes combine to one detectable phenotype, 6. phenotype is only partly surfacing, 7. internal feedback mechanisms 8. unidentified gene influencing detectable phenotype, 9. un- visible/detectable/known phenotype 10. gene-phenotype-phenotype-gene interaction
2
3
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P FP P+ + = trait
5
6
7
P9
= intermediate phenotype
10
Complex Traits Example: Cholesterol Metabolism
Genetic Complex Traits End organ damage
Some end-points of interest in the clinic
-Hypertension-Ischemia-Infarction-Diminished/Elevated filtration-Albuminuria-Mortality-Immunological abnormalities-Metabolic Syndrome-Other lipid-related phenotypes-Etc.
Confounders
-associated with exposureassociated with exposure-related to the outcomerelated to the outcome-not part of the causal pathway-not part of the causal pathway
Mother highly educatedMother highly educated Child Down syndromeChild Down syndrome
Alcohol intakeAlcohol intake Lung cancer Lung cancer
Blood pressure Blood pressure UAE UAE
Age
Smoking
Gender
CETP Taq 1B single nucleotide polymorphism
B1/B1 B1/B2 B2/B2
GG AG AA
CETP Taq1B
1,30
1,35
1,40
HD
L (
AZ
G)
Means
B1B1 B1B2 B2B2
CETP Taq B1B2 (R) Coefficient p
CETP Taq1B B1B1 -0,07097 >0.00001
CETP Taq1B B2B2 0,063692 >0.00001
Age 0,000906 >0.00001
Sex 0,329274 >0.00001
BMI nc1 -0,02786 >0.00001
Linear regression (HDL)
PREVEND-data
HDL Levels Low
(criterium Metabolic
Syndrome))
pOdds ratio
CETP Taq B1B2 Reference Reference 11
CETP Taq1B B1B1 0,005 1,377
CETP Taq1B B2B2 0,017 0,669
Age 0,0001 1,019
Logistic regression
Clinical relevance
Metabolic Syndrome p Odds ratio
CETP Taq1B B1B1 0,39 0,86
CETP Taq1B B2B2 0,09 0,68
Age >0,00001 1,06
Sex >0,00001 2,73
Significant effect on clinical intermediate phenotype
Borderline effect on clinical phenotype
Mortality p Odds ratio
CETP Taq1B B1B1 0,15 0,80
CETP Taq1B B2B2 0,07 0,71
Age >0,00001 1,11
Sex >0,00001 0,55
Borderline effect on clinical end point
co
mp
lex
ity
Complex Traits : 2 or more genotypes confound phenotype
Conceptual thinking:
Given a parameter measured in a population one is able to detectdifferences in frequency of a combination of geno- or phenotypesalong the range of the parameter when compared to the prevalanceof that combination in the whole population.
Visualization of complexity
Complexity and novel tools
HD
L-c
0
Fre
qu
en
cy o
f co
mb
ina
tio
n 1
combinations
Fre
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en
cy o
f co
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ina
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en
cy o
f co
mb
ina
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ina
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n n
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combinations
y f1a f2aa f3a f4a
b
c
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g
f
h
e
f1b f2b f3b f4b
f1c f2c f3c f4c
f1d f2d f3d f4d
f1e f2e f3e f4e
f1f f2f f3f f4f
f1g f2g f3g f4g
f1h f2h f3h f4h
Visualization of complexity
0% 20% 40% 60% 80% 100%
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ge H
DL-
c _22
_20
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_00
_12
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_01
Example 1: Hypothesis driven visualization
Phenotype : HDL-cholesterolComplex Trait: CETP-Taq1B + CETP-I405V
B1B1II
B1B2VV
B1B2II
Chi-square Test
cc p
B1B1II 0.0008
B1B2VV 0.0073
B1B2II 0.0069
PREVEND-data
FGClustor 1.0, XeNTaX
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0
1
_1225
_1205
_1005
_1004
_1024
_1224
_1204
_0222
_0225
_1125
_0002
_0201
_0221
_0001
_1022
_0005
_1021
_0022
_1002
_1201
_1222
_0202
_0023
_0115
_0021
_1123
_0203
_1025
_0123
Phenotype : Metabolic syndromeComplex Trait: Gender + Quintile Age + CETP-Taq1B + CETP-I405V
B1B2IV B1B2II B1B1II females in the highest quintile of ageFGClustor 1.0, XeNTaX
PREVEND-data
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0
1
_0225
_0205
_0005
_0025
_0015
_0125
_0105
_1115
_0215
_1222
_0115
_0202
_0201
_0221
_1221
_1205
_1225
_1001
_1105
_1022
_1005
_1201
_0001
_1203
_1025
_1002
_0021
_0122
_1215
Phenotype : MortalityComplex Trait: Gender + Quintile Age + CETP-Taq1B + CETP-I405V
B1B2IV B1B2II B1B1II B1B1IV males in the highest quintile of age
FGClustor 1.0, XeNTaX
PREVEND-data
In the general population, the CETP B1 and I allele, known to lead to lower HDL levels and less CETP activity, are associated with metabolic syndrome and higher mortality in the elderly.
Standard statistics and novel visualization of complexitycombined to generate the following working theory:
0% 20% 40% 60% 80% 100%
85
96,5
108
119,5
131
142,5
154
165,5
177
188,5
SB
P r
ange
_12
_01
_02
_13
_14
_03
_04
_11
Example 2 – Strong confounders
Phenotype: Systolic blood pressureComplex Trait: Quartiles Cholesterol + Gender Chi-square Test
F2 F1
M1 M2
F3 F4
M3 M4
F2 0,000217
M1 0,000703
M2 0,000606
F3 0,019796
F4 0,001564
M3 0,000205
M4 0,000192
F1 6,67E-05
PREVEND-data
FGClustor 1.0, XeNTaX
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
30
42
54
66
Age
ran
ge
Example 3: Non-hypothesis driven“Phenotype” : Age
Complex Trait : 5 Renin-aldosteron-angiotensin System genotypes
Chi-square Test
No low p values
Increasingly complex system requires huge sample size besides solid hypothesis
PREVEND-data
P
PG
G G
EF
EF
FP
EF
EF
1
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P 9
10
Concluding remarks on the epidemiology of Breedtestrategie
-Powerful statistical methods help uncover “mild”complex genetical pathways leading to clinically relevant phenotypes.
-Yet, increasing complexity of the trait shows limitations of standard epidemiological statistics when applied on current population sizes;
-Development of novel tools help identify undocumented traits of greater complexity
-Interdisciplinary communication and exchange of expertise in dealing with complex traits will boost research
Complex Trait Centre Groningen (CTCG)
http://www.ctcg.org
•CTCG is an interdisciplinary community of researchers that CTCG is an interdisciplinary community of researchers that deal with genetic traits in the broad sense of the worddeal with genetic traits in the broad sense of the word
•CTCG will organize seminars by people in the field that will CTCG will organize seminars by people in the field that will educate researchers in their approach educate researchers in their approach
– – join the mailinglist to receive emails informing of join the mailinglist to receive emails informing of upcoming events!upcoming events!- propose speakers for seminars at info@ctcg.org!- propose speakers for seminars at info@ctcg.org!
•CTCG aims at communicating problem solving in the daily CTCG aims at communicating problem solving in the daily routine of complex trait researchroutine of complex trait research
•CTCG is cooperative and not restricted to set departmentsCTCG is cooperative and not restricted to set departments
•CTCG invites anyone that is interested in complex trait CTCG invites anyone that is interested in complex trait research to join the CTCG communityresearch to join the CTCG community
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