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Genome-wide Association Studies-GWAS01:11

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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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Human genetics provides a profound framework for understanding the interplay between genetic predispositions and human psychology. At the heart of this discipline lies the study of how genes influence physical traits, behaviors, and susceptibility to diseases. Each person carries a unique genetic code that subtly or significantly shapes their psychological and behavioral landscape.
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A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
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Gregor Mendel's work (1822 - 1884) was primarily focused on pea plants. Through his initial experiments, he determined that every gene in a diploid cell has two variants called alleles inherited from each parent. He suggested that amongst these two alleles, one allele is dominant in character and the other recessive. The combination of alleles determines the phenotype of a gene in an organism.
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Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
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Related Experiment Video

Updated: Jul 17, 2025

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies
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WHOLE GENOME SEQUENCING ANALYSIS OF BODY MASS INDEX IDENTIFIES NOVEL AFRICAN ANCESTRY-SPECIFIC RISK ALLELE.

Xinruo Zhang1, Jennifer A Brody2, Mariaelisa Graff1

  • 1Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

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Summary

This study used whole-genome sequencing data from diverse populations to identify new genetic signals linked to body mass index (BMI). These findings advance our understanding of obesity genetics and personalized medicine approaches.

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Area of Science:

  • Genetics
  • Public Health
  • Genomics

Background:

  • Obesity is a significant global health issue with high mortality.
  • Previous genetic studies on body mass index (BMI) predominantly used European-ancestry data.
  • Limited diversity in genetic studies hinders comprehensive understanding of obesity risk factors.

Purpose of the Study:

  • To identify novel genetic variants associated with BMI using diverse whole-genome sequencing data.
  • To expand the catalog of genes contributing to obesity risk across different ancestries.
  • To advance the development of personalized medicine for obesity.

Main Methods:

  • Utilized whole-genome sequencing (WGS) data from 88,873 participants in the Trans-Omics for Precision Medicine (TOPMed) Program.
  • Included 51% of participants from non-European population groups to ensure diversity.
  • Performed genome-wide association analyses to identify BMI-associated signals.

Main Results:

  • Discovered 18 novel BMI-associated genetic signals (P < 5 × 10^-9).
  • Identified and replicated a novel low-frequency single nucleotide polymorphism (SNP) in MTMR3, prevalent in individuals of African descent.
  • Pinpointed likely causal variants in POC5 and DMD loci and identified two novel secondary signals in known BMI loci.

Conclusions:

  • Whole-genome sequencing in diverse cohorts is crucial for discovering obesity-associated genetic variants.
  • The findings expand the understanding of genetic contributions to obesity across populations.
  • This research moves closer to enabling personalized medicine strategies for obesity prevention and treatment.