ArticleThe Indian journal of medical research2017
Tumour protein 53 is linked with type 2 diabetes mellitus.
Article in The Indian journal of medical research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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.
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.
Who cites it
19 citing papers in PubMed, 31 citations in OpenAlex.
- Systems Biology and Atomistic Simulations Reveal Multi-Target Modulation of Alzheimer's Disease and Type 2 Diabetes byInternational journal of molecular sciences · 2026Article
- Rescuing TP53 from nonsense: novel triazoles for translational readthrough via optimized drug design.Scientific reports · 2026Article
- The interplay of tumor suppressor p53 and oxidative stress in pancreatic β-cell apoptosis and insulin resistance in newly diagnosed type 2 diabetes mellitus.Diabetology & metabolic syndrome · 2025Article
- Mechanistic insights into modified Danggui Buxue Decoction for diabetic retinopathy via integrative analysis.Frontiers in endocrinology · 2025Article
- Innovative Dual Therapy: Magnesium Oxide Nanoparticles and Royal Jelly for Parotid Gland Protection in Diabetic Male Rats.International journal of nanomedicine · 2025Article
- Exploration of Pharmacological Mechanisms of Dapagliflozin against Type 2 Diabetes Mellitus through PI3K-Akt Signaling Pathway based on Network Pharmacology Analysis and Deep Learning Technology.Current computer-aided drug design · 2025Article
- Mechanism of Jianpixiaoke Recipe in Treating Type 2 Diabetes Based on Network Pharmacology and Molecular Docking.International journal of endocrinology · 2025Article
- Article
- Multi-Omics Analysis Revealed the rSNPs Potentially Involved in T2DM Pathogenic Mechanism and Metformin Response.International journal of molecular sciences · 2024Article
- Mechanisms of Action ofDrug design, development and therapy · 2024Article
- Updates on Triple-Negative Breast Cancer in Type 2 Diabetes Mellitus Patients: From Risk Factors to Diagnosis, Biomarkers and Therapy.Diagnostics (Basel, Switzerland) · 2023Review
- Article
- Identification of core genes associated with type 2 diabetes mellitus and gastric cancer by bioinformatics analysis.Annals of translational medicine · 2022Article
- Investigating the Mechanism of Rhizoma Coptidis-Eupatorium fortunei Medicine in the Treatment of Type 2 Diabetes Based on Network Pharmacology and Molecular Docking.BioMed research international · 2022Article
- TP53 codon 72 polymorphism and type 2 diabetes: a case-control study in South Indian population.Molecular biology reports · 2021Article
- Network Pharmacology and Molecular Docking Study on the Potential Mechanism of Yi-Qi-Huo-Xue-Tong-Luo Formula in Treating Diabetic Peripheral Neuropathy.Journal of diabetes research · 2021Article
- Different Roles ofInternational journal of general medicine · 2021Article
- Bioinformatic Reconstruction and Analysis of Gene Networks Related to Glucose Variability in Diabetes and Its Complications.International journal of molecular sciences · 2020Article
- Integrated Analysis of the Mechanisms of Da-Chai-Hu Decoction in Type 2 Diabetes Mellitus by a Network Pharmacology Approach.Evidence-based complementary and alternative medicine : eCAM · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND &
objectivesTumour protein p53 (TP53) is a stress sensitive transcription factor responsible for the control of cell survival and death to prevent from tumour formation. In vitro and animal studies have indicated that TP53 also responds to metabolic changes and influences metabolic pathways. This study was undertaken to determine the serum level of TP53 and its correlations with clinical and biochemical parameters in type 2 diabetes mellitus (T2DM) patients in comparison to non-diabetic control individuals.
methodsAn observational study was conducted between December 2009 and November 2013 to evaluate TP53 serum level using ELISA. Cases (n=225) were defined as patients who were diagnosed with T2DM. Non-diabetic controls (n=255) were matched by age and sex. Multivariable modelling using logistic regression examined associations between clinical characteristics and TP53 level or T2DM predication was performed.
resultsSerum TP53 level was significantly higher in T2DM patients as compared to non-diabetic healthy controls (1.69 vs 2.07 ng/ml, P<0.001). In T2DM patients, the level of TP53 increased with the age, duration of diabetes and waist-to-hip ratio (WHR) value. A logistic regression analysis revealed that increased serum TP53 level was significantly associated with family history of diabetes, age and WHR. Moreover, TP53, triglyceride and body mass index could be used to predict T2DM. INTERPRETATION &
conclusionsOur results suggest that TP53 may be linked with T2DM. The fluctuations of serum TP53 level may reflect metabolic and oxidative stress associated with chronic hyperglycaemia. Further studies need to be done to confirm these findings.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.