Hello. This is Barbara Jennings. Welcome to your genetic variation tutorial. By the end of the session you’ll be able to define Mendelian traits and common complex traits. You’ll be able to contrast rare variants and common genetic variants, and you’ll be able to identify the variants that are important for genetic disease and pharmacogenetics, using online databases. If genetic factors contribute to a particular clinical trait, we usually notice the clustering of that phenotype within families. So if the phenotype is more prevalent within particular families than it is in the overall population, that’s evidence of heritability.
Taking a family history, drawing up a family tree, or pedigree ,and describing the occurrence of traits within that family tree, or pedigree diagram are very familiar and important clinical skills. In the 20th century, the application of genetics in medicine tended to focus on rather rare single-gene disorders ,managed within specialist genetic departments. This century, the use of genetic medicine will be much more widely used for the management of many common diseases, from cancer to diabetes and dementia. Let’s begin by defining some terms. So Mendelian disorders are often referred to a single gene or monogenic disorders.
They arise when a mutation in one gene disrupts the function of the gene, and in general terms, this is the sole or main cause of the disease. Inheritance patterns within the families can be predicted by the laws proposed and presented by Gregor Mendel, but there are caveats. The products of modifier genes can affect the observed disease phenotype. And the penetrance of a particular mutation may be incomplete. So the term penetrance describes the proportion of individuals with the given mutation who go on to show the phenotype. Complex traits such as hypertension, type 2 diabetes, and adverse responses to medicines, often result from the cumulative effects of variations in many genes, combined with environmental interactions.
So whilst we see family clustering, the patterns of inheritance are not predictable in the way they are for monogenic disorders. For your background studies, I now want to introduce you to a curated and regularly updated database of all Mendelian disorders. Now, although the individual conditions are rare, we know that these lead to childhood or adult onset conditions in two or three percent of all births. And this database describes almost 4,000 individual diseases. Each entry will have its own specific number linked to the disease and the associated genes described, with specific and defining nomenclature. The research that led to the identification of key genetic variants, many of which will be kindred specific, or private mutations, is comprehensively described within this database.
Now, there are several types of variation in DNA sequence that have functional effects. What I mean by this is that the mutation will lead to an alteration in the quantity or quality of particular gene products - the transcripts and proteins. So there are these small insertions and deletions between individual genomes known as in-dell variants, and much larger regions of the genome are affected by copy number variants. But the most common type of variant that we see between our genomes and which explains most phenotypic variation, is due to the single nucleotide variants, or snips.
So a polymorphism remember, is classically defined as a variant that affects more than one percent of chromosomes in a given population, and most common variants are bi-allelic, so there are two alternate forms, and we refer to the major allele, which is the most prevalent version of the gene in the given population, and the minor allele, which is the rarer version. So, more recently, definitions have been sort of redefined a bit. So variants can be classified as common, if the frequency is greater than 5%, and rare if the frequency is less than not 0.5%, with those of intermediate frequency being described as low frequency variants. Another definition to be aware of, is for the term, ‘private mutation’.
So, this means that some variants are unique to a single family or kindred. The descriptions for a particular locus will always be population specific. So there interethnic differences in allele frequency but if we compare the average human genome with a reference genome sequence, we will find about ten or eleven thousand nonsynonymous sequence variants. So that means sequence variants that lead to differences in protein expression. However, only a few hundred will be variants that lead to loss of gene function.
So the effects of variants will range from the beneficial, to the highly deleterious, and if we compare these common and rare variants it’s interesting to note that, in each of our individual genomes, we have far more rare and low frequency variants than those that are classified as common variants. The search for the common genetic variants associated with an underlying complex traits has led to the rise of a particular study type - the genome-wide association study or GWAS. Now these rely on the collection of genetic data from large populations of research participants with a given disease, or a pharmacogenetic trait, in parallel with a control population. And there’s a really helpful curated catalogue of published GWAS studies.
And in November last year, it had included and described more than 2,000 studies presenting disease association data from more than 15,000 variants. So, in the diagram on the right, we can see the chromosomal location of individual variants found to be strongly associated with a range of disease markers, from hypertension to drug hypersensitivity. Up to several million genetic variants are simultaneously analysed on microarrays of single nucleotide variants. These are referred to as snip chips. And GWAS are either cohort studies or case control studies and the risk ratios identified are reported accordingly. Many compelling and reproducible associations between particular markers and disease phenotypes have been identified but there are some caveats.
Most of the predicted heritability for complex traits has not been explained by GWAS data so far. And secondly, individual effect sizes for particular markers are in general very, very small and so have not generated predictive biomarkers with clinical utility. The use of GWAS studies to identify the genetic variants that contribute to common complex disorders is based on the common disease, common variant hypothesis. This simply proposes that for these conditions, disease associated genetic variants are likely to be found commonly within populations. However, the fact that most of the predicted heritability for complex traits has not been explained by GWAS data so far, means that other theories are being explored.
So perhaps, rare variants not directly included in many GWAS studies underlie most genetic disease risk. So for these common complex traits, as well as for single gene disorders,. And it seems likely that this ,the solution, may depend on the trait actually being considered and it’s plausible that common disease and common variant hypothesis is a better fit for pharmacogenetics traits, relevant to modern medicine, compared to other disease traits, where there would presumably have been selection pressures within human populations to purge damaging - that would that would purge damaging disease phenotypes. And it’s important that our hypotheses can accommodate a range of underlying etiologies because of an observed range of different genetic effects.
So we can apply everything discussed so far now to pharmacogenetics. Idiosyncratic responses to medicine are sometimes caused by an underlying rare genetic variant but for most pharmacogenetics scenarios, we have to consider complex multifactorial traits. Phenotypically, we may categorize these traits as variations between people in the benefit they gain from their treatment, or variations in the side-effects and adverse events. In truth, these are often not discrete categories but linked phenomena. So the next thing to consider is the perturbed biochemistry and physiology that underlies these clinical phenotypes. The genetic variants that additively or specifically underlie these traits encode proteins that may be important for the metabolism of medicine, or comprise the tissue and cellular targets.
Severe idiosyncratic adverse reactions in susceptible individuals may be associated with a drug interaction, with an additional unintended target, such as an immunological variant. So these hypersensitivity reactions have no clear relation to any easily measurable pharmacokinetic or pharmacodynamic parameter. I want to finish the seminar with an example of genetic variants associated with each of these - pharmacokinetics ,pharmacodynamics and hypersensitivity. In each case, the variant has been considered to have clinical utility as a pharmacogenetics biomarker.
Now here I want to introduce you to another excellent online database. It’s called the pharmacogenomics knowledge base or pharmgkb for short. It’s a comprehensive resource and it curates knowledge about the impact of genetic variation on drug response, available to clinicians and researchers. One really useful category of information is the pharmacogenetics based drug dosing guidelines, from the clinical pharmacogenetics implementation consortium, which is open for you to join. For each of the variants described in the table here, there is specific published advice about using genotype data to plan dosing.
In the first example, the pharmacokinetics of codeine is governed by the activity of the liver enzyme cytochrome p450 2d6 and more than 100 common variants have been identified for this enzyme, some of which dramatically affect enzyme activity. The second example relates to warfarin dosing complications, from which are some of the most commonly reported adverse drug reactions. Warfarin inhibits an enzyme complex encoded by the VKORC1 gene. Common and rare variants in the gene are known to significantly affect warfarin sensitivity, or resistance. The final example relates to the use of genotyping to avoid the risk of rare but very severe hypersensitivity reactions in patients treated with carbamazepine.
The highly polymorphic hla-b gene encodes human leukocyte antigen B and for some individuals carrying one particular HLA B, it is strongly advisable to prescribe a different agent. In summary, human disease traits including pharmacogenetics traits responses to medicine, can be categorized as Mendelian, if they’re caused by a variant in a single gene with a major functional effect. Or they can be categorised as complex, if the phenotype is caused by the additive, perhaps synergistic effects of many gene variants and environmental factors. There are useful, curated databases that I’ve introduced you to today, including omim and the GWAS catalogue and pharmgkb, describing the significant research findings for human diseases with a genetic component.