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Attention Score in Context
| Title |
DNA methylation analysis of phenotype specific stratified Indian population
|
|---|---|
| Published in |
Journal of Translational Medicine, May 2015
|
| DOI | 10.1186/s12967-015-0506-0 |
| Pubmed ID | |
| Authors |
Harish Rotti, Sandeep Mallya, Shama Prasada Kabekkodu, Sanjiban Chakrabarty, Sameer Bhale, Ramachandra Bharadwaj, Balakrishna K Bhat, Amrish P Dedge, Vikram Ram Dhumal, GG Gangadharan, Puthiya M Gopinath, Periyasamy Govindaraj, Kalpana S Joshi, Paturu Kondaiah, Sreekumaran Nair, SN Venugopalan Nair, Jayakrishna Nayak, BV Prasanna, Pooja Shintre, Mayura Sule, Kumarasamy Thangaraj, Bhushan Patwardhan, Marthanda Varma Sankaran Valiathan, Kapaettu Satyamoorthy |
| Abstract |
DNA methylation and its perturbations are an established attribute to a wide spectrum of phenotypic variations and disease conditions. Indian traditional system practices personalized medicine through indigenous concept of distinctly descriptive physiological, psychological and anatomical features known as prakriti. Here we attempted to establish DNA methylation differences in these three prakriti phenotypes. Following structured and objective measurement of 3416 subjects, whole blood DNA of 147 healthy male individuals belonging to defined prakriti (Vata, Pitta and Kapha) between the age group of 20-30years were subjected to methylated DNA immunoprecipitation (MeDIP) and microarray analysis. After data analysis, prakriti specific signatures were validated through bisulfite DNA sequencing. Differentially methylated regions in CpG islands and shores were significantly enriched in promoters/UTRs and gene body regions. Phenotypes characterized by higher metabolism (Pitta prakriti) in individuals showed distinct promoter (34) and gene body methylation (204), followed by Vata prakriti which correlates to motion showed DNA methylation in 52 promoters and 139 CpG islands and finally individuals with structural attributes (Kapha prakriti) with 23 and 19 promoters and CpG islands respectively. Bisulfite DNA sequencing of prakriti specific multiple CpG sites in promoters and 5'-UTR such as; LHX1 (Vata prakriti), SOX11 (Pitta prakriti) and CDH22 (Kapha prakriti) were validated. Kapha prakriti specific CDH22 5'-UTR CpG methylation was also found to be associated with higher body mass index (BMI). Differential DNA methylation signatures in three distinct prakriti phenotypes demonstrate the epigenetic basis of Indian traditional human classification which may have relevance to personalized medicine. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 78 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 1 | 1% |
| Unknown | 77 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 20 | 26% |
| Researcher | 12 | 15% |
| Other | 8 | 10% |
| Student > Master | 5 | 6% |
| Student > Bachelor | 4 | 5% |
| Other | 12 | 15% |
| Unknown | 17 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 26 | 33% |
| Medicine and Dentistry | 16 | 21% |
| Agricultural and Biological Sciences | 4 | 5% |
| Nursing and Health Professions | 4 | 5% |
| Pharmacology, Toxicology and Pharmaceutical Science | 3 | 4% |
| Other | 5 | 6% |
| Unknown | 20 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 May 2015.
All research outputs
#18,409,030
of 22,803,211 outputs
Outputs from Journal of Translational Medicine
#2,945
of 3,991 outputs
Outputs of similar age
#192,465
of 264,548 outputs
Outputs of similar age from Journal of Translational Medicine
#80
of 91 outputs
Altmetric has tracked 22,803,211 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,991 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one is in the 17th percentile – i.e., 17% of its peers scored the same or lower than it.
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