complex disease and susceptibility gene environment disease a disease b disease c multifactorial...

Complex Disease and Susceptibility

Gene

Gene

Gene

Gene

Environment

Disease A Disease B Disease C

Multifactorial disorders


• Single gene disorders– Huntington’s– Fragile X– SCA1– DMD– Werner’s syndrome– Cystic fibrosis

• Multifactorial– Heart disease– Cancer– Stroke– Asthma– Diabetes– Alzheimer’s– Parkinson’s

Cancer Statistics

68% of new cases involve individuals 60 years and older

Why does cancer incidence increase with age?

Cancer is the natural endpoint of a multicellular animal

Balance between mutation rate and losing control

Genetic Mutations Leading to Cancer“6-hit model”

10-7 mutations per gene per cell generation 1013 cells in a human For one cell to collect 6 mutations:

10-42 x 1013 = 10-29

Thus, 1 in 1029 chance

Then why do we get cancer?

Genetic Mutations Leading to Cancer

Multistage evolution model

Successive mutations provide a growth advantage, expanding that population of mutants

Genomic instability occurs when DNA repair mechanisms are mutated

Genes altered in Cancer

Oncogenes

EGFRPDGFR

ABLSRCPI3KAktBcl2

-catenin

Genomic Stability

ATMBRCA1BRCA2BARDXPA

Tumor Suppressors

APCAxinp53

PTENRb

TSC1,2p16 INK4A

S

G1/S

G2

G2/M

M

G1

p53

Rb

Apoptosis

p53 – Guardian of the Genome

Genes altered in Cancer

Oncogenes

EGFRPDGFR

ABLSRCPI3KAktBcl2

-catenin

Genomic Stability

ATMBRCA1BRCA2BARDXPA

Tumor Suppressors

APCAxinp53

PTENRb

TSC1,2p16 INK4A

By Clark et al; Part B Cropped from original Fig 1 by SLE346_B3 [CC BY-SA 3.0 (http://creativecommons.org/licenses/by-sa/3.0)]

Ceshi Chen, Arun K. Seth and Andrew E. Aplin


• Single gene disorders– Huntington’s– Fragile X– SCA1– DMD– Werner’s syndrome– Cystic fibrosis

• Multifactorial– Heart disease– Cancer– Stroke– Asthma– Diabetes– Alzheimer’s– Parkinson’s

Genetic Component in Complex Disorders

• Relative risk

r= frequency in relative of affected person

Population frequency


• Family Studies

Class of relative Proportion of genes shared

Examples

First degree 50% Parent/child, siblings

Second degree 25% Grandparent/grand-child, aunt/niece

Third degree 12.5% Cousins


• Problem of environmental impact

Congenital Malformations

Cleft lip Pyloric stenosis

General population 0.001 0.001

First degree relatives X40 (0.04) X10 (0.01)

Second degree relatives X7 X5

Third degree relatives X3 X1.5


Disorder Monozygotic Dizygotic

Breast cancer 6.5 5.5

Type I diabetes 30 5

Type II diabetes 50 30

Multiple sclerosis 20 6

Peptic ulcer 64 44

Rheumatoid arthritis 50 8

Tuberculosis 51 22


Disorder Monozygotic Dizygotic

Alcoholism 40 20

Autism 60 7

Schizophrenia 44 16

Alzheimer’s 58 26

Dyslexia 64 40

• In polygenic diseases, risk (susceptibility) alleles increase the phenotypic value

• Traits may appear continuously variable

• Traits may appear discontinuous



• How to find susceptibility gene?– Four main approaches

1. Candidate gene

2. Parametric linkage analysis

3. Non-parametric linkage analysis

4. Population association studies

Candidate gene

• Before searching the whole genome, think about what genes may be involved– Eg., Type I diabetes – Some genes involved in cell-mediated

immunity are located on chromosome 6 (Human leukocyte antigen region)

– Linkage between Type I diabetes and HLA was closely examined

• After a small genomic region is isolated, determine best candidate gene

Parametric Linkage Analysis

• Standard LOD score analysis, as used for single-gene disorders


• Eg., breast cancer susceptibility genes• Collect family history of >1500 breast cancer

patients

– Some family histories showed multiple cases occurring at early ages – could be a Mendelian allele segregating

– Best model suggested a dominant single-gene allele with a population frequency of 0.0006 – this suggested about 5% of total breast cancers



patients

– Now, look for families with multiple breast cancer cases with early onset

– Genotype family members and look for linkage

– Linkage (significant LOD score) to breast cancer was found to a marker on 17q21



patients

– The gene involved was cloned, like other single-gene disorders

– Breast cancer (BRCA) 1 gene– tumor suppressor gene involved in genomic stability

– LOH leads to high penetrance of breast cancer, as well as ovarian cancer



patients

– However, examination of BRCA1 mutations outside of affected families suggests lower penetrance


• Other successes in finding Mendelian risk factors in polygenic diseases

– HNPCC – non-polyposis colon cancer• MSH1, MLH1, PMS1, PMS2

– FAP – familial polyposis colon cancer• APC

– Premature heart disease - hypercholesterolemia• Mutation of the LDL receptor


• Familial hypercholesterolemia– Autosomal dominant


• Familial hypercholesterolemia

• 200 mg/dl - 350 mg/dl - dietary, common

• 400 mg/dl - 600 mg/dl - heterozygous, uncommon

• >600 mg/dl - homozygous, rare


• Familial hypercholesterolemia

• Autosomal dominant; allele frequency about 1:150


• Spectacular misfires as well:– Bi-polar disease (manic depression)– Initial linkage to HRAS and INS on

chromosome 11– LOD scores of 4.08 and 2.63– Two individuals in extended family

misdiagnosed– Lowered LOD score to 1.03 and 1.75

Non-parametric Linkage Analysis

• Genomic regions surrounding risk alleles will be inherited from a common ancestor in affected individuals to a greater frequency than by chance – also called autozygosity mapping

• Search for commonly inherited regions by polymorphic microsatellites, SNP’s, etc.

• High throughput analysis critical


• Common to use Affected Sib-Pairs (ASP)

• Collect genotypic data for 100’s of ASP

• 300+ microsatellite markers genotyped for 10cM coverage

• Look for significant IBD (>chance occurrence)


• IBD: if parental alleles differ at locus, then sibs that have both alleles in common are identical by decent

• IBS: if parental alleles are not know, then we can only say sibs are identical by state

Population association studies

• Association studies are carried out on populations

• Look for alleles that segregate with the disease in a whole population– Direct causation– Natural selection– Linkage disequilibrium


• Linkage disequilibrium

• Combination of alleles at two closely linked loci occur more often than expected by chance from population frequencies

• Recombination reduces linkage disequilibrium


• Linkage disequilibrium vs. Linkage Mapping– Mapping is performed on families with few

informative meiosis; LD is determined on populations after many generations

– Mapping will show linkage over large distances; LD is visible only over short distances


• How to find susceptibility genes?– Four main approaches

1. Candidate gene

2. Parametric linkage analysis

3. Non-parametric linkage analysis

4. Population association studies

Alzheimer’s Disease (AD)

• North America – 0.1% at 60, 10% at 80, 30% at 90

• Early onset: <60

• Neurofibrillary tangles in the cerebral cortex and amyloid plaques in the brain

• Neuronal apoptosis occurs in the hippocampus and cerebral cortex – memory and learning


• Neurofibrillary tangles – polymerized tau protein

• Amyloid plaques – deposition of the -amyloid protein


• Apoptosis of neuronal cells– Sometimes called “Programmed cell death”– Energy-utilizing program of orderly self-

destruction– Organized dismantling of the cell to avoid

autoimmune reaction

Apoptosis

Apoptosis

• Activation of proteases (cysteine-aspartic acid specific; called Caspases)

• Cascade of “irreversable” proteolysis

• Activation of endonuclease – chops up the cells DNA – no going back now!

Apoptosis

• Apoptosis occurs:– During development– Removal of immunological cells– In cells with DNA damage– Defeated in cancer cells

• Neuronal cells maintain survival by exposure to “neurotrophins”

Search for Susceptibility Alleles for Alzheimer’s Disease

• Some clues as to causative agents of AD

– Down syndrome individuals develop clinical features of AD when they live >30 years

– Suggested that chromosome 21 may be involved in AD

– Parametric linkage analysis located a locus on chromosome 21q in early-onset familial AD

Causative genes in AD

• Amyloid precursor protein (APP) over-abundant in Alzheimer’s and Down syndrome individuals

• Amyloid precursor protein gene mapped to chromosome 21

• Trisomy 21 causes a over-expression of genes from chromsome 21, including APP


• APP – a causative agent of AD and involved in pathology of Downs syndrome

• Large transmembrane protein processed by , or -secretase

• -secretase generates A40 protein – non-toxic and the main protein in normal brain


• and-secretase generates A42 protein – toxic and insoluble – which forms plaques

• After APP was found by parametric linkage, mutations were found

• In familial AD, mutations in APP increased the amount of A42 cleavage


• More parametric linkage analysis within families of early-onset AD

– Presenilin I and II were discovered on chromosome 14 and 2

– Presenilin I is a -secretase – leading to increased A42 secretion


• 1% of AD is familial, and shows strong Mendelian inheritance of altered A42 generation

• What about risk alleles in sporadic AD? – 99% of cases


• Non-parametric linkage analysis was performed on Affected Pedigree Member (APM)

• 32 families in which 87 of 293 members showed AD

• Linkage with locus on chromosome 19

Causative genes in AD• In this region was the gene for Apolipoprotein E.

• ApoE was found in plaques and tangles– Good candidate

• A population association study was performed

• Three alleles of ApoE were identified:– ApoE2 (6%), ApoE3 (78%) and ApoE4 (16%)

• Strong LD was found for allele ApoE4 and several nearby SNP’s


• ApoE4 is a risk factor Alzheimer’s disease

ApoE4 dose

% affected Relative Risk

Age of onset

0 20 1 84.3

1 46.6 2.84 75.5

2 91.3 8.07 68.4

Summary

• Family, adoption and twin studies provide evidence of genetic component to complex disease

• Risk of disease is the combined effect of polygenes influenced by environment, thus termed multifactorial

• Combined affect of many common alleles each providing a small effect, or of a few uncommon alleles with large effect

• Candidate gene, parametric and non-parametric linkage analysis, and population association analysis are used to find risk factors for multifactorial disease

complex disease and susceptibility gene environment disease a disease b disease c multifactorial...

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