Categorii: Tot - study - genetics - disease - traits

realizată de Jacob Dooley 1 an în urmă

95

Genetics II: Molecular Basis for Genetic Diseases

Genetic diseases often have complex causes involving multiple genes and environmental factors. Understanding the molecular basis of these diseases involves studying the associations between genetic variations and disease occurrence.

Genetics II: Molecular Basis for Genetic Diseases

Genetics II: Molecular Basis for Genetic Diseases

Identifying genetic basis for complex disease

** P- value**
Bonferroni Threshold: 1.00x10^-6
Overview of association methods
Family Data methods
Displaying association results Manhattan plot Regional Association plot
Accounting for multiple comparisons (false discovery rate)
Regression methods Joint estimation of multiple variables Modeling outcome with SNP and covariates (e.g. age, sex, population structure)
Allelic Test of association Simple case-control study with no covariates or population structure
Linkage Disequilibrium
Alternatively, any detected degree of association (greater than chance) between the allele frequencies (of the SNPs) indicates linkage disequilibrium.

Refer to concept of previous lecture on population genetics and Hardy- Weinberg equilibrium. Assumes no evolution, and focus on random mating. Goes against idea of random assortment (principal of mendelian genetics)

If SNPs are completely independent from one another, they are considered to be in linkage equilibrium.
The non-random association of alleles at two or more loci.
GWAS
Refer to slide 21 for comparison of linkage analysis and association.

Mainly: Linakge = mendilion and Association=complex diseases

Associations studies

**there exist correlations between the marker you genotyped and the functional polymorphism (due to LD)**

Key concept: Exploring associations between the variations in a gene and a trait assumes:

Current high throughput genotyping allows us to inexpensively genotype large numbers* of genetic markers(or variants) across the genome

***Mapping the human genome and linkage disequilibrium motivated and enabled the GWAS paradigm.**
Agnostic (genome scan) approach

Dissimliar to candidate gene appraoach

across entire genome

Similar to linkage analysis

Designed to identify genetic associations with observable triats

Quantitative: BMI, Fasting glucose

Qualitative: Obesity, T2D, Asthma, CVD

Many SNPs
Examination of genetic variation across a given genome
Genetics to Phenotype
Genomic association studies

Dense genotyping

Large study pop (case/control unrelated)

Mendelian disorders

Good for high heritability

Complex traits: height, Type 2 diabetes mix of genetic and environment
Mendelian traits: Ex. Sickle cell Anemia and CF
Objectives:
Understand the fundamentals of study design for a genome-wide association study (GWAS). Become familiar with analytical approaches to extend the capabilities of GWAS, e.g. LD and imputation. Acknowledge the strengths and limitations of the GWAS approach

Multifactorial Disorders

Familial Aggregation and Correlation
Distinguish Genetic and environmental

Estimate Heritability of twins: H2= 2 x (rmz-rdz)

MZ/DZ graph

DNA finger printing

Use fam Studies: Use twin studies- MZ and DZ

Fam Ag: greater than expected number of affected relatives compared to that of the freq of general pop.

(higher heritability, greater contribution of genetic diff. 0= no genetic contrib 1=genotype is responsible (totally)

Quantitative: Correlation and Heritability

Coefficient of Correlation (r)

Larger rrr, greater fam ag (greater than 1)

Measures: RR and Fam hx case-control

More close the fam member, share more allele
Siblings share 50% of alleles
Qualitative and Quantitative traits
Qunatiative:Measurable physiological or biochem quantity that differs among diff indivs, usually follows normal dis.
Qualitative: trait that the person either does or does not have

Biochemical and genetic basis for disease

Disease based on Mutation in diff class of proteins
Structural Proteins

DMD

X linked rec, mutation rate 10^-4

Muscle weakness at 3-5 yoa, heart and resp are also affected

Duchenne Muscular Dystrophy

Transport defects

Cystic Fibrosis

CFTR only gene assoc with CF

Genocopy: Similar phenotypes show varying genotypes on different loci

Principal effects in lungs and exocrine pancreas increase in sweat sodium and Cl concentration

Defects in receptor proteins

Familial Hypercholesterolemia

Gene dosage: earlier manifestation and sev.

LDLR mutations are auto semidom trait Both homo and heterogeneity phenotypes

Group of metabolic disorders chracterized by elevated plasma lipids carried by apolipoprotein B

Enzymes

PKU and Tay-Sachs

Tay-Sachs: Lysosomal storage disease Pseudodeficiency Alleles: clinically benign allele that has a reduction in function activity detected by in vitro assays but has suffiecnt activity

Example of allelic Heterogeneity: Over 1557 mutations world wide found in patients with PKU Variant and non-variant PKU

PKU: mutation in PAH--> neg impact on degre of phenylalanine PAH expressed in liver, damage CNS First genetic defect to cause intellectual disability normal at birth, microcephaly, hyperactivity, seizures, and learning disability Phenyalaline--> Tyrosine, with help from BH4 (cofactor) and PAH

Protein Classes
Specialty Proteins
Housekeeping proteins

Genetic basis for mendelian disease

Phase concept
Specific alleles that a person has/ that are inherited
Problems:

Mendelian diseases are not really “simple” • Reduced penetrance • Heterogeneity (allelic, phenotypic) • Genotyping errors leads to spurious recombinants → loss of power • The multi-locus map helps to detect this error by checking for unusual double recombinants

Likelihood: probability of data given the prarmetiers

1-theta=Pr (no recom)

theta: Pr (recombination

LOD

Log Likelihood ratio

Z(theta) = log 10 (L(theta)/L(theta=0.5))

Two point linkage analysis

Test if a genetic marker & disease locus are linked • Genotypes at disease locus are unknown but phenotype (affection status) is known

Goal:

Goal: Identify a chromosomal region linked to a disease within families that exceeds the null expectation, which enable localization of disease gene in the genome

Characteristics for Mendelian Disease
Low frequency of variants and low risk disease prevalence
Risk variants have high disease penetrance with strong genetic defects
Allelic heterogeneity
single gene mutation
Recognizable pattern of inheritance
Steps for Disease Gene Identification
Genome wide association study (GWAS)
Candidate gene
Linkage analysis

Recombination happens in prophase

Why Linkage:

• In most cases little is known about the genomic location of genes contributing to disease • Thus, the study design usually consists of systematically surveying the entire genome • The extent of linkage is a function of the physical distance between the loci on the chromosome • Based on recombination between loci 10

use fam with disease, identify regions that co-seg with phenotype

Posostionlal cloning

Objectives
-Demonstrate genetic mapping by following the co- segregation of alleles within a family, i.e. linkage analysis - Quantify the extent to which a genetic marker and disease locus are linked, i.e. co-inherited - Review successful examples of disease loci identified through linkage analysis 3

Population Genetics

Sexual Selection vs Assortative Mating
Assorative mating: Increases homozygosity of variants, creates correlations across distant loci within complex traits creates confounding across traits overestimates heritability of traits
Sexual selection: increases trait frequency
Hardy-Weinberg Law
Assumes no evolution
1=p+q
p2 + 2pq + q2=1
Calculating allele frequency
Number of Indi x allele count
Forces of Evolution
NS

Mutations increase in freq if they increase in number of offspring

Gene Flow

Mutations spread by migration

Genetic Drift

Mutations may change in frequency by chance events

Random Mutation

New Traits arise via chance mutations in DNA

Mutation and Protein Function

Hemoglobin and Hemoglobinopathies
The Hemoglobins:

Practical:

The most common forms of α-Thalassemia are the result of gene deletions. Rationalize the high frequency of deletions in mutational carriers.

a- Thalassemia: -Two identical a-globin genes on each chromosome (16) Tandem homologous a-globin genes facilitates misalignment between domains

Hereditary persistence of fetal hemoglobin

A group of clinically benign conditions that impair perinatal switch: y-globin --> B-globin synthesis Ex: Hb F

Thalassemias

Diseases that result from decreased abundance of one or more of globin chains Ex: B-thalassemias

Structural variants

Alters AA sequence of globin PP--> alter properties of the protein Ex: Sickle Cell and Methemoglobin

Locus Control Region (LCR): req for expression of all genes in B-globin cluster areas of "open" DNA gives TF access to reg elements that mediate expression

Temporal switches of globin synthesis are accompanied by changes in the principal site of erythropoiesis

a, b, and y: Globin switching changes in expression of global molecules during development

Heterogeneity
Phenotypic Heterogeneity

Sickle cell disease and B-thalassemeia each result from distinct B-globin gene mutations.

Locus Heterogeneity

Ex: thalassemia. genes at diff loci (16 a-globin and 11 B-globin gene both causing thalassemia

Assosiation of more than one locus with clinical phenotype

Allelic Heterogeneity

B-Thalassemia: HBB: chromosome 11p15.4 over 200 disease causing mutations identified

The occurrence of more than one allele at a locus Diff mutation at same gene

Review of Terms
Genotype

Alleles present at that locus

Allele

One of several alternative forms of sequence at a locus 2 alleles per locus, one per chromosome

Marker

A measurable unit on a chromosome single nucleotide polymorphism (SNP)

Locus

Position on the chromosome: Disease Locus & Marker Locus

Mutations
Heterotropic or ectopic gene expression
Novel Property mutations

Sickle Cell Anemia: Hemoglobin chains aggregate. E6V (AA Sub)

Gain of Function

Enhance one or more of the functions of the protein Increase in amount of function or abundance of the protein

Loss of funtion

May alter coding, regulatory, or other regions Can have range of effects if residual function is maintained

Ultimate source of genetic variation