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Related Concept Videos

Human Genetics01:28

Human Genetics

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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.
The complex relationship between genetics and psychology is observable through common biological components such...
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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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Protein Networks02:26

Protein Networks

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An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
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Notch Signaling Pathway03:14

Notch Signaling Pathway

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The Notch signaling pathway is a major intracellular signaling pathway that is highly conserved over a broad spectrum of metazoan species. It stands unique from other intracellular signaling mechanisms in animals because notch protein itself acts as the receptor as well as the primary signaling molecule.
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Interactions Between Signaling Pathways01:19

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Signaling cascades usually lack linearity. Multiple pathways interact and regulate one another, allowing cells to integrate and respond to diverse environmental stimuli.
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Related Experiment Video

Updated: Dec 7, 2025

A Phenotyping Regimen for Genetically Modified Mice Used to Study Genes Implicated in Human Diseases of Aging
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Gene networks determine predisposition to AMD.

Kaushal Sharma1, Neel Kamal Sharma2, Ramandeep Singh3

  • 1Neuroscience Research Lab, Department of Neurology, Post Graduate Institute of Medical Education and Research, Chandigarh, India; Centre for Systems Biology and Bioinformatics, Panjab University, Chandigarh, India.

Genomics
|September 26, 2020
PubMed
Summary

Genetic factors and environmental influences interact to impact Indian Age-related Macular Degeneration (AMD) pathology. Understanding these interactions can improve AMD diagnosis and treatment strategies.

Keywords:
Age related macular degenerationGenotype interactionHTRA1LIPCLogistic regressionPersonalized medicineTIMP-3

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Area of Science:

  • Genetics
  • Ophthalmology
  • Biochemistry

Background:

  • Age-related Macular Degeneration (AMD) is a complex disease with known genetic components.
  • Understanding the interplay of genetic predisposition and environmental factors is crucial for managing AMD, particularly in diverse populations like India.

Purpose of the Study:

  • To investigate the genetic complexity of Indian AMD by analyzing genotype-environment interactions and their effect on protein expression.
  • To identify specific genetic variants and protein alterations associated with AMD in the Indian population.

Main Methods:

  • Studied 464 participants (277 AMD, 187 controls) for eight genetic variants and corresponding protein expression.
  • Utilized SNP analysis, protein expression analysis, and longitudinal assessment.
  • Employed ANCOVA, contrast analysis, Logistic Regression (LR) modeling, and Area Under the Receiver Operating Characteristic curve (AUROC) for analysis.

Main Results:

  • Identified significant associations between AMD and genetic variants rs5749482 (TIMP-3), rs11200638 (HTRA1), rs769449 (APOE), and rs6795735 (ADAMTS9).
  • Observed significant alterations in protein levels correlated with these genetic variants.
  • Found that the interaction between APOE-HTRA1 genotypes and LIPC levels plays a critical role in AMD pathogenesis.
  • Developed an LR model predicting AMD with 88% efficacy and 95.6% AUROC using seven factors.

Conclusions:

  • Diagnostic and therapeutic strategies for Indian AMD should incorporate the estimation of genetic interactions.
  • Concomitant changes in protein expression levels, influenced by environmental factors, are vital considerations for AMD management.