Untitled Quiz

A trait controlled by a single gene, often following Mendelian inheritance patterns.

A trait influenced by multiple genes with additive effects. Often involves environmental factors.

A model where nearly all genes in a genome can influence a trait indirectly through core genes in relevant pathways.

A model that suggests disease risk is a quantitative trait, where exceeding a certain threshold leads to disease.

A measurable quantitative phenotype that contributes to the genetic architecture of a complex trait.

The proportion of variance in a quantitative trait attributable to genetic variation within a population.

Variation in a trait due to the additive effects of alleles.

Variation in a trait attributable to environmental factors.

This scenario is challenging for genetic association studies as it requires large sample sizes to detect small effects.

Genetic association studies are easier in this case, as strong effects are easier to identify in smaller samples.

This scenario is where association studies are most commonly employed. They require large samples due to the widespread variability present.

This involves assigning a numerical score to each variant based on the number of copies of the coded allele an individual carries: 0, 1, or 2.

These studies specifically target genes believed to be relevant to a trait, testing for associations with disease.

GWAS assess millions of genetic variants across the entire genome for their association with specific traits.

Instead of using Bonferroni correction, GWAS uses a more lenient threshold of < 5 x 10 ^ -8, correcting for 1 million independent tests.

Repeating the study in an independent sample helps to validate findings and minimize false positives.

Larger sample sizes are crucial for GWAS power, making the number of cases more important than the number of controls.

Measures how much the results from GWAS are inflated due to factors like population structure. A value close to 1 suggests a lack of true associations.

An inflation rate greater than 1.1%. This rate is considered too high and can negatively impact the economy.

The ability of a study to detect a statistically significant difference or association. In genetic studies, it's influenced by effect size, allele frequency, and sample size.

A method to adjust the significance level (alpha) for multiple hypothesis testing. It reduces the chance of false positives by dividing the original alpha by the number of tests.

A confounding factor in genetic studies where a population is divided into subpopulations with different disease prevalences and allele frequencies.

Non-random association of alleles at two loci. Alleles are found together more often than expected by chance.

A combination of alleles at closely linked loci on a chromosome. It's inherited as a unit.

A single nucleotide polymorphism (SNP) that is in strong linkage disequilibrium with other SNPs in a region. It can be used to represent a group of SNPs.

A genetic variant that directly influences a trait or disease.

Predicting missing or unmeasured genotype values based on known linkage disequilibrium patterns.

A database of whole genome sequences used to inform imputation. Provides information on haplotype frequencies.

How a drug affects the body. Focuses on the drug's interactions with biological targets like enzymes, receptors, ion channels, and transporters.

What the body does to a drug. Involves how the drug is absorbed, distributed, metabolized, and eliminated.

The study of how genetic variations influence drug response. Aims to personalize drug prescriptions based on individual genetic profiles.

Warfarin is a blood thinner that can be affected by genetic variation in the VKORC1 gene, impacting how the body metabolizes the drug.

Genome-wide association studies (GWAS) can be used to identify genetic variants associated with drug efficacy, toxicity, and drug metabolism.

Genome-wide interaction study (GWIS) investigates how genetic variants interact with medications to influence drug efficacy.

Describes how genetic variants affect gene activity. Loss-of-function reduces gene function, while gain-of-function increases function.

When a gene affects multiple traits in the body.

A measure of an individual's overall genetic risk for a disease, taking into account multiple genetic variants.

Replacing faulty genes with functional copies to treat inherited diseases.

A gene editing technology used to precisely target and correct genetic mutations, mainly for Mendelian disorders.

Cancer isn't a single disease, but a group of conditions caused by abnormal cell growth. This growth is often uncontrolled, leading to the formation of tumors.

Cancer arises from mutations in genes that control cell growth and division. These can be oncogenes, which promote growth, or tumor suppressor genes, which prevent uncontrolled growth.

Proto-oncogenes are normal genes that promote cell growth. Mutations in these genes can create oncogenes that trigger uncontrolled cell growth, like a broken throttle in a car.

Tumor suppressor genes act like brakes, controlling cell growth and stopping it from becoming uncontrolled. Mutations in these genes lead to uncontrolled cell division.

DNA repair genes act like repairmen, fixing DNA damage to prevent errors from accumulating. A loss of function in these genes increases the risk of cancer.

This theory proposes that cancer doesn't arise from a single mutation, but from a series of accumulated mutations in key genes. It's like a domino effect leading to cancer.

A germline mutation occurs in a sperm or egg cell, meaning that it can be inherited by offspring. These mutations are rare but can have significant impact on cancer risk.

Mutations can lead to cancer through several ways: over-expression of a normal protein, creation of an abnormal protein, or changes in how a gene is regulated. These disruptions disrupt the delicate balance of cell growth.