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Population Genetics & Epidemiology Flashcards

6 cards from real CGC practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.

Read the first 6 Population Genetics & Epidemiology flashcards as text
  1. Which of the following describes 'pleiotropy'?

    Answer: A single gene that influences multiple phenotypic traits or organ systems

    Pleiotropy refers to one gene having effects on multiple, seemingly unrelated phenotypic traits or organ systems.

  2. In a multifactorial condition like type 2 diabetes, heritability estimates describe:

    Answer: The proportion of phenotypic variance in a population attributable to genetic factors

    Heritability (h²) is a population statistic representing the fraction of phenotypic variance due to genetic variance, not an individual's risk.

  3. The recurrence risk for a multifactorial condition in a sibling of an affected individual is BEST approximated by:

    Answer: The square root of the population prevalence

    For multifactorial conditions, the empiric recurrence risk in first-degree relatives is approximately the square root of the population prevalence.

  4. Genomic imprinting results in conditions where disease expression depends on:

    Answer: Whether the pathogenic variant was inherited from the mother or father

    Genomic imprinting silences one parental allele depending on its parental origin, so the phenotype depends on whether the variant came from the mother or father.

  5. A population-based carrier screening program aims to identify which individuals?

    Answer: Unaffected individuals who carry one pathogenic variant for a recessive condition and are at reproductive risk

    Carrier screening identifies unaffected heterozygous individuals who are at risk of having affected children when partnered with another carrier.

  6. Genetic counselors use Bayesian analysis in clinical genetics primarily to:

    Answer: Combine prior probability with conditional information to derive a revised posterior probability of a genotype or diagnosis

    Bayesian analysis updates prior probability estimates using additional conditional information (e.g., normal test results, clinical features) to compute a posterior probability.

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