Evidence map›Paper›PMID 39230791›Full record

ArticleMolecular genetics and genomics : MGG2024

Uncovering novel regulatory variants in carbohydrate metabolism: a comprehensive multi-omics study of glycemic traits in the Indian population.

Janaki M Nair, Khushdeep Bandesh, Anil K Giri, Gauri Prasad, Donaka Rajashekhar, Punam Jha, Analabha Basu, Nikhil Tandon, Dwaipayan Bharadwaj

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Article in Molecular genetics and genomics : MGG, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

1 citing paper in PubMed.

  1. 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

9 authors.

Janaki M NairSystems Genomics Laboratory, School of Biotechnology, Jawaharlal Nehru University, New Delhi, 110067, India.
Khushdeep BandeshCSIR-Institute of Genomics and Integrative Biology, New Delhi, 110025, India. khushdeepbandesh@gmail.com.
Anil K GiriCSIR-Institute of Genomics and Integrative Biology, New Delhi, 110025, India.
Gauri PrasadCSIR-Institute of Genomics and Integrative Biology, New Delhi, 110025, India.
Donaka RajashekharCSIR-Institute of Genomics and Integrative Biology, New Delhi, 110025, India.
Punam JhaCSIR-Institute of Genomics and Integrative Biology, New Delhi, 110025, India.
Analabha BasuNational Institute of Biomedical Genomics, Kalyani, West Bengal, 741251, India.
Nikhil TandonDepartment of Endocrinology and Metabolism, All India Institute of Medical Sciences, New Delhi, 110029, India.
Dwaipayan BharadwajSystems Genomics Laboratory, School of Biotechnology, Jawaharlal Nehru University, New Delhi, 110067, India. db@jnu.ac.in.ORCID http://orcid.org/0000-0001-5268-8482

Funding

CSIR BSC0122DST DST/SR/PURSE Phase II/11
6 · The paper itself

Abstract

Clinical biomarkers such as fasting glucose, HbA1c, and fasting insulin, which gauge glycemic status in the body, are highly influenced by diet. Indians are genetically predisposed to type 2 diabetes and their carbohydrate-centric diet further elevates the disease risk. Despite the combined influence of genetic and environmental risk factors, Indians have been inadequately explored in the studies of glycemic traits. Addressing this gap, we investigate the genetic architecture of glycemic traits at genome-wide level in 4927 Indians (without diabetes). Our analysis revealed numerous variants of sub-genome-wide significance, and their credibility was thoroughly assessed by integrating data from various levels. This identified key effector genes, ZNF470, DPP6, GXYLT2, PITPNM3, BEND7, and LORICRIN-PGLYRP3. While these genes were weakly linked with carbohydrate intake or glycemia earlier in other populations, our findings demonstrated a much stronger association in the Indian population. Associated genetic variants within these genes served as expression quantitative trait loci (eQTLs) in various gut tissues essential for digestion. Additionally, majority of these gut eQTLs functioned as methylation quantitative trait loci (meth-QTLs) observed in peripheral blood samples from 223 Indians, elucidating the underlying mechanism of their regulation of target gene expression. Specific co-localized eQTLs-meth-QTLs altered the binding affinity of transcription factors targeting crucial genes involved in glucose metabolism. Our study identifies previously unreported genetic variants that strongly influence the diet-glycemia relationship. These findings set the stage for future research into personalized lifestyle interventions integrating genetic insights with tailored dietary strategies to mitigate disease risk based on individual genetic profiles.

Indexed as

Blood GlucoseCarbohydrate MetabolismGenome-Wide Association StudyPolymorphism, Single NucleotideQuantitative Trait LociAdultDiabetes Mellitus, Type 2DNA MethylationFemaleGenetic Predisposition to DiseaseHumansIndiaMaleMiddle AgedMultiomicsBlood GlucoseAssociation testingCarbohydrate metabolismGenetic variantsGlycemic traitsGWASMethylation

Identifiers

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Registered trials

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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 Socratic graph.