Evidence map›Paper›PMID 28271161›Full record

ArticleMolecular genetics and genomics : MGG2017

DNA methylation profiling reveals the presence of population-specific signatures correlating with phenotypic characteristics.

Anil K Giri, Soham Bharadwaj, Priyanka Banerjee, Shraddha Chakraborty, Vaisak Parekatt, Donaka Rajashekar, Abhishek Tomar, Aarthi Ravindran, Analabha Basu, Nikhil Tandon and 1 more

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Article in Molecular genetics and genomics : MGG, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

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0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Methylation profiles at birth linked to early childhood obesity.Journal of developmental origins of health and disease · 2024
    Article
  6. Methylation profiles at birth linked to early childhood obesity.medRxiv : the preprint server for health sciences · 2024
    Article
  7. Article
  8. A biosocial return to race? A cautionary view for the postgenomic era.American journal of human biology : the official journal of the Human Biology Council · 2022
    Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Culture as an ingredient of personalized medicine.Journal of psychiatry & neuroscience : JPN · 2018
    Article
4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Anil K GiriGenomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, 110020, India.
Soham BharadwajUniversity School of Biotechnology, Guru Gobind Singh Indraprastha University (GGSIPU), Dwarka, New Delhi, 110078, India.
Priyanka BanerjeeGenomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, 110020, India.
Shraddha ChakrabortyGenomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, 110020, India.
Vaisak ParekattGenomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, 110020, India.
Donaka RajashekarGenomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, 110020, India.
Abhishek TomarSystems Genomics Laboratory, School of Biotechnology, Jawaharlal Nehru University, New Delhi, 110067, India.
Aarthi RavindranGenomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, 110020, India.
Analabha BasuNational Institute of Biomedical Genomics, Netaji Subhas Sanatorium (Tuberculosis Hospital), Kalyani, West Bengal, 741251, India.
Nikhil TandonDepartment of Endocrinology and Metabolism, All India Institute of Medical Sciences, New Delhi, 110029, India. nikhil_tandon@hotmail.com.
Dwaipayan BharadwajAcademy of Scientific and Innovative Research, CSIR-Institute of Genomics and Integrative Biology, New Delhi, 110020, India. db@jnu.ac.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Phenotypic characteristics are known to vary substantially among different ethnicities around the globe. These variations are mediated by number of stochastic events and cannot be attributed to genetic architecture alone. DNA methylation is a well-established mechanism that sculpts our epigenome influencing phenotypic variation including disease manifestation. Since DNA methylation is an important determinant for health issues of a population, it demands a thorough investigation of the natural differences in genome wide DNA methylation patterns across different ethnic groups. This study is based on comparative analyses of methylome from five different ethnicities with major focus on Indian subjects. The current study uses hierarchical clustering approaches, principal component analysis and locus specific differential methylation analysis on Illumina 450K methylation data to compare methylome of different ethnic subjects. Our data indicates that the variations in DNA methylation patterns of Indians are less among themselves compared to other global population. It empirically correlated with dietary, cultural and demographical divergences across different ethnic groups. Our work further suggests that Indians included in this study, despite their genetic similarity with the Caucasian population, are in close proximity with Japanese in terms of their methylation signatures.

Indexed as

Chromosome MappingAdultCluster AnalysisCpG IslandsDNADNA MethylationEpigenesis, GeneticEthnicityFemaleHumansIndiaMaleMiddle AgedPhenotypeDNADNA methylationEpigenomePhenotypic plasticityPopulation signature

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.