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Related Concept Videos

Pharmacogenomics: Identification of New Drug Targets01:29

Pharmacogenomics: Identification of New Drug Targets

Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

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.
GWAS does not require the identification of the target gene involved in...
Human Genetics01:28

Human Genetics

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.
The complex relationship between genetics and psychology is observable through common biological components such...
Polygenic Traits01:18

Polygenic Traits

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...
Incomplete Dominance01:43

Incomplete Dominance

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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Related Experiment Videos

Genetic Correlation and Causal Inference Between Female Fat Distribution and Preeclampsia: An Integrative Genomic

Man Wang1, Li Huang2, Danfeng Zhang3

  • 1Department of Outpatient, Hubei Provincial Clinical Research Center for Umbilical Cord Blood Hematopoietic Stem Cells, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei, China.

FASEB Journal : Official Publication of the Federation of American Societies for Experimental Biology
|June 23, 2026
PubMed
Summary
This summary is machine-generated.

Genetic factors linking body fat distribution, specifically waist-hip ratio adjusted for BMI (WHRadjBMI), are associated with preeclampsia (PE). This study reveals shared genetic pathways, particularly involving vascular and immune processes, contributing to PE risk.

Keywords:
Mendelian randomizationfat distributiongenetic correlationpreeclampsiawaist‐hip ratio

Related Experiment Videos

Area of Science:

  • Genetics
  • Obstetrics
  • Metabolic Disorders

Background:

  • Preeclampsia (PE) is a significant cause of maternal and perinatal complications.
  • Abnormal body fat distribution is linked to metabolic dysfunction, vascular injury, and hypertension during pregnancy.

Purpose of the Study:

  • To investigate the shared genetic architecture between preeclampsia and waist-hip ratio adjusted for body mass index (WHRadjBMI).
  • To identify genetic factors and biological pathways that may link WHRadjBMI to PE susceptibility.

Main Methods:

  • Integrated large-scale genome-wide association study (GWAS) summary statistics for WHRadjBMI and PE.
  • Employed methods including genetic correlation (LDSC, MiXeR), cross-trait GWAS meta-analysis, and Mendelian randomization.
  • Performed tissue/cell type enrichment and functional annotation analyses.

Main Results:

  • Identified approximately 0.5k shared causal variants and a modest but significant polygenic overlap between WHRadjBMI and PE (rg=0.08, p=0.006).
  • Detected a shared genetic locus near MTHFR-CLCN6.
  • Enrichment analyses implicated VEGFA-driven vascular and immune processes, with uterine pericytes showing the strongest shared cell-type enrichment.
  • Mendelian randomization supported a causal effect of WHRadjBMI on PE (p=2.7×10⁻⁴).

Conclusions:

  • Genetically predicted fat distribution, as measured by WHRadjBMI, may contribute to preeclampsia susceptibility.
  • Shared vascular-immune pathways are highlighted as potential links between WHR-related genetic risk and pregnancy complications.