Genetic disorders

Session 5-2

BSMS205 Korea University

Asst/prof. Joon An (website)

Overview today

• Approaches to study genetic disorders
• Experimental methods to study genetic disorders.
• Comparison of Mendelian and common disorders.

Approaches to study genetic disorders

Indirect method to infer genetic cause in disorders

• 1909, Archibald Garrod: Inborn errors of metabolism.�
• 1910-1930s, Ronald Fisher: Pedigree information was introduced to consider genetic relatedness.
• How much you share your genetic background with your family members.
• How much sharing -> likelihood of having the trait.�
• 1940s, JBS Haldane & Julia Bell, Oligogenic model: variable penetrance and expressivity among affected individuals in a pedigree might be modified by other genetic factors.�
• 1990s, heritability measure phenotypic variance by familial relationship and sibling recurrence.

Genotyping technologies offer a direct method to find a genetic cause in disorders

1. Microarray (or SNP chip) finds common SNPs or chromosomal abnormality including copy-number variations.�
2. Whole exome sequencing (WES or exome sequencing) finds mutations in protein-coding regions.�
3. Whole genome sequencing (WGS) finds mutation in any region of the genome.

Different experimental design by genotyping technologies

• Microarray (or SNP chip) finds common SNPs or chromosomal abnormality including copy-number variations.
1. Genome-wide association study for common SNPs.
2. Study of genetic syndromes by CNVs.
• Whole exome sequencing (WES or exome sequencing) finds mutations in protein-coding regions.
• Gene burden test for candidate genes.
• Whole genome sequencing (WGS) finds mutation in any region of the genome.
• Genome wide association study for common and rare SNPs.
• Study of genetic syndromes by CNVs.
• Gene burden test for candidate genes.
• WGS can do everything but inefficient choice as to cost.

Experimental methods to study genetic disorders

Three experimental methods for genetic disorders

1. Linkage analysis
2. Association analysis
3. Direct genome sequencing.

Experimental methods for genetic disorders: Linkage analysis

• Family-based.
• Linkage analysis takes advantage of family pedigrees to follow the inheritance of a disease among family members and to test for consistent, repeated coinheritance of the disease with a particular genomic region or even with a specific variant or variants , whenever the disease is passed on in a family.

• The LOD score (logarithm (base 10) of odds), developed by Newton Morton, is a statistical test often used for linkage analysis in human, animal, and plant populations.
• The LOD score compares the likelihood of obtaining the test data if the two loci are linked, to the likelihood of observing the same data purely by chance. Positive LOD scores favour the presence of linkage, whereas negative LOD scores indicate that linkage is less likely.
• Computerised LOD score analysis is a simple way to analyse complex family pedigrees in order to determine the linkage between Mendelian traits (or between a trait and a marker, or two markers).

Genetics in Medicine Thompson & Thompson 8th edition

Experimental methods for genetic disorders: Association analysis

• Population-based.
• Large size samples and unbiased collection.
• Fragile to population structure.
• Look for increased or decreased frequency of a particular allele or set of alleles in a sample of affected individuals taken from the population, compared with a control set of unaffected people from that same population.
• Particularly useful for complex diseases that do not show a mendelian inheritance pattern - additive!
• There are two commonly used study designs for association studies:
• Case-control studies: Individuals with the disease are selected in a population, a matching group of controls without disease are then selected, and the genotypes of individuals in the two groups are determined and used to populate a two-by-two table.
• Cross-sectional or cohort studies: A random sample of the entire population is chosen and then analyzed for whether they have (cross-sectional) or, after being followed over time, develop (cohort) a particular disease; the genotypes of everyone in the study population are determined. The numbers of individuals with and without disease and with and without an allele (or genotype or haplotype) of interest are used to fill out the cells of a two-by-two table.

Genetics in Medicine Thompson & Thompson 8th edition

Odds Ratios and Relative Risks

• The two different types of association studies report the strength of the association, using either the odds ratio or relative risk.�
• In a case-control study , the frequency of a particular allele or haplotype (e.g., for a human leukocyte antigen [HLA] haplotype or a particular SNP allele or SNP haplotype) is compared between the selected affected and unaffected individuals, and an association between disease and genotype is then calculated by an odds ratio (OR) .

Genetics in Medicine Thompson & Thompson 8th edition

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Odds Ratios and Relative Risks

• Alternatively, if the association study was designed as a cross-sectional or cohort study , the strength of an association can be measured by the relative risk (RR).
• The RR is the ratio of the proportion of those with the disease who carry a particular allele ([a/(a + b)]) to the proportion of those without the disease who carry that allele ([c/(c + d)]).

Genetics in Medicine Thompson & Thompson 8th edition

​

Odds Ratios and Relative Risks

• The information obtained in an association study comes in two parts.
1. The magnitude of the association: the further the RR or OR diverges from 1, the greater is the effect of the genetic variant on the association.
2. A test of statistical significance. �
• The significance of any association can be assessed by simply asking with a chi-square test.�
• A common way of expressing whether there is statistical significance to an estimate of OR or RR is to provide a 95% (or 99%) confidence interval . The confidence interval is the range within which one would expect the OR or RR to fall 95% (or 99%) of the time by chance alone in a sample taken from the population.

Experimental methods for genetic disorders: Genome sequencing

• Direct genome sequencing of affected individuals and their parents and/or other individuals in the family or population. �
• Particularly useful for rare mendelian disorders in which linkage analysis is not possible because there are simply not enough such families to do linkage analysis or because the disorder is a genetic lethal that always results from new mutations and is never inherited. �
• In these situations, “sequencing the genome” or “just the coding exons of every gene, the exome” of an affected individual and sifting through the resulting billions (or in the case of the exome, tens of millions) of bases of DNA has been successfully used to find the gene responsible for the disorder.

Filtering WGS or WES data to find potential causal variants

• Assumption: “Risk mutations” should be rare enough or recurrent across patients.�
• Filtering rare variants from WES dataset
1. Location with respect to protein-coding genes.
2. Population frequency.
3. Deleterious nature of the mutation.
4. Consistency with likely inheritance pattern.

Mendelian vs. Common disorders

Mendelian vs. Common disorder

1. (Rare) Mendelian disorders.
1. Mendelian inheritance of rare variants.
2. Mendelian conditions are individually rare, but collectively contribute to disease in ~0.4% of children and young adults, and 8% of live births if all congenital anomalies are considered (Baird et al. 1988).
3. Often rarely observed in a population (low prevalence).
4. Genetic syndrome: known single or few genes or loci related to conditions.
1. Chromosomal aberrations (Down syndrome -> trisomy 21 chromosome).
2. Known genes (fragile X syndrome -> FMR1 gene).
2. Common disorders.
• Commonly occurred in a population.
• Determined by prevalence of disorders.
• Many genes involved in disease.

However, such classification is not fixed and can be updated with new findings.

NIH Centers for Mendelian Genomics

The CMGs have reported a total of ~3,600 disease gene–phenotype pairs, categorized as novel, phenotypic expansion (phenotypic features extending beyond those previously reported for a Mendelian condition) or known (Posey et al. 2019).

Online Mendelian Inheritance in Man (OMIM) database

• Expert review and curation of phenotypes and genes (Amberger 2015).
• If an expert meets patients, find a gene and report the phenotype with the matching gene.
• Who is an expert?
• ~5000 disorders affected by 3000 genes.

Victor A. McKusick

https://www.omim.org/

Critics from Chakravarti 2011

• “Mendelian inheritance of rare traits and diseases has defined patterns of segregation with well-defined quantitative risks of recurrence; but the vast majority of McKusick's entries are based on astute clinical observations of a handful of patients, not extensive quantitative analysis. In other words, in McKusick's catalog, the many rare disorders and syndromes are good hypotheses, not proven examples.”�
• “Exome or genome sequencing will reveal not only single-gene mutations, but also numerous cases of digenic, trigenic, and more complex inheritance.”

Critics: likely underestimate the true burden of Mendelian disorders (Posey 2019)

• Discovery of loci underlying Mendelian conditions relied heavily on traditional linkage mapping and positional cloning approaches (in 1990 to 2000).
• Little power to detect disorders characterized by de novo variation, incomplete penetrance, and locus heterogeneity.�
• Lack of genome-wide methodologies to find candidate genes or loci.
• Test one hypothesis due to the technical limitation.�
• Locus heterogeneity: indistinguishable between rare and common variants.�
• Gene-first approaches, in which a cohort of individuals with rare variation at a particular locus undergo careful phenotyping, can elucidate the full phenotypic spectrum associated with an allelic series at a disease gene locus.

Common disorders

• Common disorders are “common”: cause morbidity and premature mortality in nearly two of every three individuals during their lifetimes.
• Often called “multifactorial in origin” or “complex”. Now we know it’s polygenic and different genetic architecture by disorder.
• Not caused by one gene - additive.

Genetics in Medicine Thompson & Thompson 8th edition

Summary

• Recent advances in genomic technologies enables direct examination of genetic cause in human disorders
• There is a range of experimental design by different genetic technologies
• Mendelian and common disorders are different genetic architecture, though the complete architecture still remains unknown.