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Migration and DNA methylation: a comparison of methylation patterns in type 2 diabetes susceptibility genes between indians and europeans.

Elliott HR, Walia GK, Duggirala A, Groom A, Reddy SU, Chandak GR, Gupta V, Laakso M, Dekker JM - J Diabetes Res Clin Metab (2013)

Bottom Line: However, these observations were not linked to local variation in DNA methylation levels.No differences in methylation patterns were observed in urban-dwelling migrants compared to their non-migrant rural-dwelling siblings in India.These differences may be attributed to genetic and/or region-specific environmental factors.

View Article: PubMed Central - PubMed

Affiliation: Institute of Genetic Medicine, Newcastle University, Newcastle-upon-Tyne, UK.

ABSTRACT

Background: Type 2 diabetes is a global problem that is increasingly prevalent in low and middle income countries including India, and is partly attributed to increased urbanisation. Genotype clearly plays a role in type 2 diabetes susceptibility. However, the role of DNA methylation and its interaction with genotype and metabolic measures is poorly understood. This study aimed to establish whether methylation patterns of type 2 diabetes genes differ between distinct Indian and European populations and/or change following rural to urban migration in India.

Methods: Quantitative DNA methylation analysis in Indians and Europeans using Sequenom(®) EpiTYPER(®) technology was undertaken in three genes: ADCY5, FTO and KCNJ11. Metabolic measures and genotype data were also analysed.

Results: Consistent differences in DNA methylation patterns were observed between Indian and European populations in ADCY5, FTO and KCNJ11. Associations were demonstrated between FTO rs9939609 and BMI and between ADCY5rs17295401 and HDL levels in Europeans. However, these observations were not linked to local variation in DNA methylation levels. No differences in methylation patterns were observed in urban-dwelling migrants compared to their non-migrant rural-dwelling siblings in India.

Conclusions: Analysis of DNA methylation at three type 2 diabetes susceptibility loci highlighted geographical and ethnic differences in methylation patterns. These differences may be attributed to genetic and/or region-specific environmental factors.

No MeSH data available.


Related in: MedlinePlus

Figures show the region of the chromosome that methylation was measured in and location of SNPs analysed. Upper images show the amplicons across which methylation was measured. Each circle represents a CpG site in the amplicon analysed. Dark filled circles represent CpG sites from which the average methylation value for the amplicon was generated. Lower images show linkage disequilibrium between SNPs. Values in diamonds are r2 values. Diamond colours represent LOD and D’ (white: D’<1, LOD <2; dark grey: D’= 1, LOD≥ 2; shades of grey:D’<1, LOD≥ 2).
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Figure 1: Figures show the region of the chromosome that methylation was measured in and location of SNPs analysed. Upper images show the amplicons across which methylation was measured. Each circle represents a CpG site in the amplicon analysed. Dark filled circles represent CpG sites from which the average methylation value for the amplicon was generated. Lower images show linkage disequilibrium between SNPs. Values in diamonds are r2 values. Diamond colours represent LOD and D’ (white: D’<1, LOD <2; dark grey: D’= 1, LOD≥ 2; shades of grey:D’<1, LOD≥ 2).

Mentions: Assays were designed using EpiDesigner software (Sequenom®) and methylation analysis was conducted using the Sequenom® EpiTYPER® according to the Sequenom® protocol. Amplicons were designed to capture the largest number of CpG sites possible within or close to CpG islands at each of the three loci investigated. Assays for ADCY5 and FTO loci were located within CpG islands while the amplicon designed for KCNJ11 was 221 base pairs upstream of the nearest CpG island. Further details regarding the CpG sites measured are shown in Figures 1A-C. Oligonucleotide sequences are available from the authors on request. Methylation data were generated as β values between 0 and 1, indicating percentage methylation of the original template.


Migration and DNA methylation: a comparison of methylation patterns in type 2 diabetes susceptibility genes between indians and europeans.

Elliott HR, Walia GK, Duggirala A, Groom A, Reddy SU, Chandak GR, Gupta V, Laakso M, Dekker JM - J Diabetes Res Clin Metab (2013)

Figures show the region of the chromosome that methylation was measured in and location of SNPs analysed. Upper images show the amplicons across which methylation was measured. Each circle represents a CpG site in the amplicon analysed. Dark filled circles represent CpG sites from which the average methylation value for the amplicon was generated. Lower images show linkage disequilibrium between SNPs. Values in diamonds are r2 values. Diamond colours represent LOD and D’ (white: D’<1, LOD <2; dark grey: D’= 1, LOD≥ 2; shades of grey:D’<1, LOD≥ 2).
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4835020&req=5

Figure 1: Figures show the region of the chromosome that methylation was measured in and location of SNPs analysed. Upper images show the amplicons across which methylation was measured. Each circle represents a CpG site in the amplicon analysed. Dark filled circles represent CpG sites from which the average methylation value for the amplicon was generated. Lower images show linkage disequilibrium between SNPs. Values in diamonds are r2 values. Diamond colours represent LOD and D’ (white: D’<1, LOD <2; dark grey: D’= 1, LOD≥ 2; shades of grey:D’<1, LOD≥ 2).
Mentions: Assays were designed using EpiDesigner software (Sequenom®) and methylation analysis was conducted using the Sequenom® EpiTYPER® according to the Sequenom® protocol. Amplicons were designed to capture the largest number of CpG sites possible within or close to CpG islands at each of the three loci investigated. Assays for ADCY5 and FTO loci were located within CpG islands while the amplicon designed for KCNJ11 was 221 base pairs upstream of the nearest CpG island. Further details regarding the CpG sites measured are shown in Figures 1A-C. Oligonucleotide sequences are available from the authors on request. Methylation data were generated as β values between 0 and 1, indicating percentage methylation of the original template.

Bottom Line: However, these observations were not linked to local variation in DNA methylation levels.No differences in methylation patterns were observed in urban-dwelling migrants compared to their non-migrant rural-dwelling siblings in India.These differences may be attributed to genetic and/or region-specific environmental factors.

View Article: PubMed Central - PubMed

Affiliation: Institute of Genetic Medicine, Newcastle University, Newcastle-upon-Tyne, UK.

ABSTRACT

Background: Type 2 diabetes is a global problem that is increasingly prevalent in low and middle income countries including India, and is partly attributed to increased urbanisation. Genotype clearly plays a role in type 2 diabetes susceptibility. However, the role of DNA methylation and its interaction with genotype and metabolic measures is poorly understood. This study aimed to establish whether methylation patterns of type 2 diabetes genes differ between distinct Indian and European populations and/or change following rural to urban migration in India.

Methods: Quantitative DNA methylation analysis in Indians and Europeans using Sequenom(®) EpiTYPER(®) technology was undertaken in three genes: ADCY5, FTO and KCNJ11. Metabolic measures and genotype data were also analysed.

Results: Consistent differences in DNA methylation patterns were observed between Indian and European populations in ADCY5, FTO and KCNJ11. Associations were demonstrated between FTO rs9939609 and BMI and between ADCY5rs17295401 and HDL levels in Europeans. However, these observations were not linked to local variation in DNA methylation levels. No differences in methylation patterns were observed in urban-dwelling migrants compared to their non-migrant rural-dwelling siblings in India.

Conclusions: Analysis of DNA methylation at three type 2 diabetes susceptibility loci highlighted geographical and ethnic differences in methylation patterns. These differences may be attributed to genetic and/or region-specific environmental factors.

No MeSH data available.


Related in: MedlinePlus