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Related Concept Videos

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
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Heritability01:06

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Heritability is a statistical concept that measures the degree to which genetic differences among individuals contribute to trait variations within a population. It is a fundamental idea in genetics, often prone to misinterpretation. Heritability is expressed as a percentage, reflecting the proportion of variation in a specific trait across a population that can be linked to genetic differences. However, it's important to understand that heritability does not determine how "genetic"...
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When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...
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Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
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Refining multivariate disease phenotypes for high chip heritability.

Jiangwen Sun, Henry R Kranzler, Jinbo Bi

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    Summary
    This summary is machine-generated.

    This study introduces a new statistical method to find disease subtypes with high heritability using genetic data from unrelated individuals. The approach successfully identified a cocaine dependence subtype with significant chip heritability.

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    Area of Science:

    • Statistical genetics
    • Complex disease genetics

    Background:

    • Heritability is crucial for genetic studies of complex diseases.
    • Existing methods require related individuals; novel approaches for unrelated individuals are needed.
    • Chip heritability estimation from genome-wide markers in unrelated individuals offers new opportunities.

    Purpose of the Study:

    • To develop a statistical model for identifying highly heritable disease components (subtypes) using genome-wide data from unrelated individuals.
    • To enhance genetic studies by focusing on disease subtypes with high chip heritability.
    • To account for fixed effects of covariates like age and race.

    Main Methods:

    • An optimization approach was developed to identify disease components based on multiple clinical variables.
    • Heritability was estimated directly from genome-wide single nucleotide polymorphisms in unrelated individuals.
    • A sequential quadratic programming algorithm was implemented for efficient computation.

    Main Results:

    • The method successfully identified hypothesized components in simulations.
    • A cocaine dependence subtype was identified with a chip heritability of 0.86.
    • This subtype characterized individuals with heavy cocaine use and minimal withdrawal symptoms.

    Conclusions:

    • The proposed approach effectively identifies meaningful disease components with high chip heritability.
    • Validation through simulations and real-world data confirms the method's utility.
    • This facilitates more powerful genetic analyses of complex diseases.