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The Predictivity Concept. Peter Propping Institute of Human Genetics University of Bonn, Germany. CDBI Seminar on predictivity, genetic tests and insurance Strasbourg, 3-4 December 2007. Heart disease. PKU. Schizophrenia. Motor vehicle accident. Cancer. Multiple sclerosis.

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the predictivity concept

The Predictivity Concept

Peter Propping

Institute of Human Genetics

University of Bonn, Germany

CDBI Seminar on predictivity, genetic tests and insurance

Strasbourg, 3-4 December 2007

slide2

Heart disease

PKU

Schizophrenia

Motor vehicle accident

Cancer

Multiple sclerosis

Cystic fibrosis

Alzheimer

Diabetes

Fragile X

TB

Asthma

Duchenne muscular dystrophy

Struck

by

lightning

Obesity

Rheumatoid arthritis

Meningococcus

Autism

‘Totally’ Genetic

‘Totally’

Environmental

Gene-environment Interaction:

Source: Dr. Ron Zimmern, Oxford

slide3

The Human Genome

3,2 x 109 nucleotide pairs

not a “unique” sequence,

but appreciable interindividual variation

any two genomes:

99,9% DNA sequence identity,

thus, 0.1 % sequence differences (3 mio).

Any individual (diploid, i. e. two genomes):

6 mio differences to the reference genome.

slide4

Autosomal dominant

Autosomal recessive

X-chromosomal

?

?

?

Modes of inheritance

slide5

Two major groups of genetic diseases

  • Monogenic (= Mendelian) disorders
  • - monocausal
  • clear relationship between genotype and phenotype
  • - about 2.000 disorders clarified
  • - most disorders are rare
  • - therapy mostly difficult
  • Genetically complex (multifactorial) disorders
  • - complicated genetic structure
  • - many of them common in the population
  • may be influenced by exogenous factors
  • therapy frequently possible
slide6

Conceptual distinction

- Prognosis: statement about the future course of a past

or currently existing disorder

- Prediction: probability of the onset of a disease

that has not yet occurred

slide7

Methods of prediction and prognosis in a proband

- medical history

- medical examinations

- family history

- predictive genetic diagnosis

- prediction based on lifestyle

slide8

Prediction on the basis of medical examinations

Imaging techniques (CT, MRT, Ultrasound)

- e.g. polycystic kidney disease

hereditary brain tumors, e.g. tuberous sclerosis

degenerative brain disorders

Electrocardiogram

- e.g. hereditary disturbance of conductivity (long QT-syndrome)

Blood biochemistry

- e.g. hypercholesterolemia

hyperlipidemia

slide9

60 y

58 y

I:1

I:2

36 y

34 y

34 y

21 y

II:1

II:2

II:3

II:4

10 y

8 y

5 y

III:1

III:2

III:3

Genetic diagnostics

in familial adenomatous polyposis (FAP)

slide10

60 y

58 y

I:1

I:2

36 y

34 y

34 y

21 y

II:1

II:2

II:3

II:4

10 y

8 y

5 y

III:1

III:2

III:3

Predictive diagnostics

in familial adenomatous polyposis (FAP)

slide11

?

?

CRC, 56y

CRC, 32y

30y

28y

HNPCC?

2y

Persons at risk for Lynch Syndrome

(Hereditary Nonpolyposis Colorectal Cancer, HNPCC)

cumulative risk in carriers of a mutation in the brca1 or brca2 gene

100

90

80

BRCA1 BrCa

70

BRCA2 BrCa

60

BRCA1 OvCa

50

BRCA2 OvCa

X

40

Gen.pop. BrCa

30

Gen.pop. OvCa

X

20

X

10

X

X

0

X

0

30

40

50

60

70

80

Cumulative risk in carriers of amutation in the BRCA1 or BRCA2 gene

Meta-analysis, King et al., Science 2003

slide13

Examples for Hereditary disorders with late onset for which predictive genetic diagnosis is possible (autosomal-dominant)

Treatable:

Hereditary tumor syndromes:

- breast/ovarian cancer

- colorectal cancer

- familial adenomatous polyposis

Polycystic kidney disease, type 1

Hereditary deafness, several late onset forms

Untreatable:

Huntington disease

Myotonic dystrophy

Alzheimer disease, autosomal-dominant forms

Spinocerebellar ataxia, several forms

Facio-scapulo-humeral muscular dystrophy

Retinitis pigmentosa, several late onset forms

slide14

Concordance rates in identical (monozygotic, MZ)

and fraternal (dizygotic, DZ) twins

%

MZ DZ

Coronary heart disease 46 12

Hyperthyroidism 47 7

Neurodermitis 83 28

Diabetes mellitus I 45 5

Diabetes mellitus II 95 10

Lepra 59 20

Epilepsy („idiopathic“) 86 4

Schizophrenia – narrow definition 26 4-10

– wide definition 41 10-20

slide15

Genetic model of a complex (multifactorial) disease:

Hypertension as an example

„super-normal“

slightly predisposed

slightly increased

definitely increased

severely ill

slide16

Relationship between genotype and phenotype in a complex disease

- Predictive value of a genotype

•Positive Predictive Value (PPV)

-Fraction of persons with a predisposing genotype who

will develop the disease

•Negative Predictive Value (NPV)

-Fraction of persons without the genotype who do not

have the disease

slide17

NOD2 Genotype Patients Controls

Wildtype / Wildtype 227 248

Wildtype / Ins 57 23

Ins / Ins 20 1

Positive Predictive Value (PPV):

Example: Crohn disease and association with NOD2 variant

Positive predictive value:

Homozygous 20 = 0,95

Heterozygous 57 = 0,71

20

21

57

80

slide18

Relationship between Genotype Frequency, Relative Risk and Positive Predictive Value

Disease Disease Genotype Genotype Relative Risk PPV

Frequency Frequency

COPD+ 0,05 Pi ZZ 0,0005 20,0 99,1%

Narcolepsy 0,0005 DQB1*0602 0,021 10,5 0,4%

homozygosity

+COPD = chronic obstructive pulmonary disease

slide19

Predictability of affection status in the carrier of a predisposing genotype

- monogenic diseases

•up to 100% depending on penetrance

- complex (multifactorial) diseases

•often low

•eventually higher after genotypic profiling

slide20

To what degree can multifactorial

disorders be predicted ?

Generally, the concordance rate of MZ twins is the upper limit of prediction;

but:

only cross-sectional information taken into account, no age correction possible;

global concordance rates give only average data, in fact part of the cases higher degrees of heritability may exist.

slide21

Screening approaches:

- Genetic population screening

•newborn screening for treatable diseases

•e. g. preconceptual thalassemia screening on Sardinia and

Cyprus

•preconceptual screening in certain ethnic groups, e. g. for

Tay-Sachs in Jews

•cascade screening, e. g. for hypercholesterolemia in the

Netherlands

slide22

Screening approaches:

- Ascertainment of persons at high risk through family history

• e. g. inherited breast/ovary cancer and Lynch syndrome

(HNPCC)

• population-based for preconceptual testing in recessive

diseases

slide23

The Future:

The “1000 Dollar Genome”

- nightmare of informed consent

- nightmare of interpretation