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APOE polymorphism in a rural older population-based sample in India
B K Thelma1, R C Juyal, H H Dodge
1Department of Genetics, University of Delhi South Campus, New Delhi, India.
This study reports apolipoprotein E (APOE) allele frequencies in a large, representative Indian population. The APOE*4 allele frequency was found to be exceptionally low, providing crucial genetic data.
Area of Science:
- Genetics
- Population Genetics
- Human Genetics
Background:
- Allele frequencies are typically reported from small, non-representative samples, limiting generalizability.
- Understanding genetic variations like apolipoprotein E (APOE) genotype is crucial for population health studies.
- There is a need for reliable genetic data from diverse populations, including India.
Purpose of the Study:
- To determine the distribution of apolipoprotein E (APOE) genotype and allele frequencies in a large, representative, rural, population-based sample in Haryana, India.
- To provide a demographic breakdown of APOE allele frequencies by age, sex, and religious/caste groups.
- To establish a normative genetic background for future gene-disease association studies in the Indian population.
Main Methods:
- Genotyping of the apolipoprotein E (APOE) polymorphism in a sample of 4450 individuals aged 55-95 years.
- Utilizing a well-defined, representative, rural, population-based cohort from Ballabgarh, Haryana, India.
- Analysis of allele frequencies (E*2, E*3, E*4) and their distribution across demographic subgroups.
Main Results:
- The overall allele frequencies for APOE E*2, E*3, and E*4 were 0.039, 0.887, and 0.073, respectively.
- The APOE*4 allele frequency (0.073) is among the lowest reported globally.
- APOE allele frequencies showed no significant variation by age or sex within this study population.
Conclusions:
- This study presents the largest Indian sample genotyped for APOE polymorphism to date.
- The findings provide a valuable, representative genetic dataset for the North Indian population.
- The low APOE*4 frequency has implications for understanding population-specific genetic risk factors and disease associations.
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