Evidence mapPaperPMID 37192883Full record

ReviewThe Egyptian journal of medical human genetics2022

Genetics of type 2 diabetes mellitus in Indian and Global Population: A Review.

Anjaly Joseph, Maradana Thirupathamma, Elezebeth Mathews, Manickavelu Alagu

Open access · diamondAbstract readReview
In one paragraph

Review in The Egyptian journal of medical human genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
4.1field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

9 citing papers in PubMed, 26 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Review
  6. Integrating Polygenic Risk Scores (PRS) for Personalized Diabetes Care: Advancing Clinical Practice with Tailored Pharmacological Approaches.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2025
    Review
  7. Article
  8. Review
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Anjaly JosephDepartment of Public Health and Community Medicine, Central University of Kerala, Kasaragod, Kerala 671320 India.
Maradana ThirupathammaDepartment of Genomic Science, Central University of Kerala, Kasaragod, Kerala 671320 India.
Elezebeth MathewsDepartment of Public Health and Community Medicine, Central University of Kerala, Kasaragod, Kerala 671320 India.
Manickavelu AlaguDepartment of Genomic Science, Central University of Kerala, Kasaragod, Kerala 671320 India.ORCID 0000-0003-2875-2290
Central University of Kerala · IN

Funding

DBT-Wellcome Trust India Alliance IA/CPHE/17/1/503345Wellcome Trust
6 · The paper itself

Abstract

Background: Non-communicable diseases such as cardiovascular diseases, respiratory diseases and diabetes contribute to the majority of deaths in India. Public health programmes on non-communicable diseases (NCD) prevention primarily target the behavioural risk factors of the population. Hereditary is known as a risk factor for most NCDs, specifically, type 2 diabetes mellitus (T2DM), and hence, understanding of the genetic markers of T2DM may facilitate prevention, early case detection and management. Main body: We reviewed the studies that explored marker-trait association with type 2 diabetes mellitus globally, with emphasis on India. Globally, single nucleotide polymorphisms (SNPs) rs7903146 of Transcription Factor 7-like 2 (TCF7L2) gene was common, though there were alleles that were unique to specific populations. Within India, the state-wise data were also taken to foresee the distribution of risk/susceptible alleles. The findings from India showcased the common and unique alleles for each region. Conclusion: Exploring the known and unknown genetic determinants might assist in risk prediction before the onset of behavioural risk factors and deploy prevention measures. Most studies were conducted in non-representative groups with inherent limitations such as smaller sample size or looking into only specific marker-trait associations. Genome-wide association studies using data from extensive prospective studies are required in highly prevalent regions worldwide. Further research is required to understand the singular effect and the interaction of genes in predicting diabetes mellitus and other comorbidities.

Indexed as

GeneticsMarker–trait associationRisk allelesSNPType 2 diabetes

Identifiers

PMID37192883
PMCPMC9438889
OpenAlexW4294276852

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.