Evidence mapPaperPMID 39688777Full record

ReviewDiabetes therapy : research, treatment and education of diabetes and related disorders2025

Integrating Polygenic Risk Scores (PRS) for Personalized Diabetes Care: Advancing Clinical Practice with Tailored Pharmacological Approaches.

Omna Singh, Madhur Verma, Nikita Dahiya, Sabyasachi Senapati, Rakesh Kakkar, Sanjay Kalra

Abstract readReview
In one paragraph

Review in Diabetes therapy : research, treatment and education of diabetes and related disorders, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

6 authors.

Omna SinghDepartment of Community and Family Medicine, All India Institute of Medical Sciences-Bathinda, Bathinda, 151001, Punjab, India. singhomna2000@gmail.com.
Madhur VermaDepartment of Community and Family Medicine, All India Institute of Medical Sciences-Bathinda, Bathinda, 151001, Punjab, India.
Nikita DahiyaDepartment of Human Genetics and Molecular Medicine, Central University of Punjab, Bathinda, Punjab, India.
Sabyasachi SenapatiDepartment of Human Genetics and Molecular Medicine, Central University of Punjab, Bathinda, Punjab, India.
Rakesh KakkarDepartment of Community and Family Medicine, All India Institute of Medical Sciences-Bathinda, Bathinda, 151001, Punjab, India.
Sanjay KalraDepartment of Endocrinology, Bharti Hospital, Karnal, India. brideknl@gmail.com.ORCID http://orcid.org/0000-0003-1308-121X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rising global prevalence of diabetes poses a serious threat to public health, national economies, and the healthcare system. Despite a high degree of disease heterogeneity and advancing techniques, there is still an unclear diagnosis of patients with diabetes compounded by the array of long-term microvascular and macrovascular complications associated with the disease. In addition to environmental variables, diabetes susceptibility is significantly influenced by genetic components. The risk stratification of genetically predisposed individuals may play an important role in disease diagnosis and management. Precision medicine methods are crucial to reducing this global burden by delivering a more personalised and patient-centric approach. Compared to the European population, genetic susceptibility variants of type 2 diabetes mellitus (T2DM) are still not fully understood in other major populations, including South Asians, Latinos, and people of African descent. Polygenic risk scores (PRS) can be used to identify individuals who are more susceptible to complex diseases such as diabetes. PRS is selective and effective in developing novel diagnostic interventions. This comprehensive predictive approach facilitates the understanding of distinct response profiles, resulting in the development of more effective management strategies. The targeted implementation of PRS is especially advantageous for people who fall into a higher-risk category for diabetes. Through early risk assessment and the creation of individualised diabetes treatment plans, the integration of PRS in clinical practice shows potential for reducing the prevalence of diabetes and its complications. Diabetes self-management depends significantly on patient empowerment, with behavioural monitoring emerging as a vital facilitator. The main aim of this review article is to formulate a more structured intervention strategy by advocating for increased awareness of the clinical utility of PRS and counseling among healthcare practitioners, patients, and individuals at risk of diabetes.

Indexed as

Association studiesClinical utilityDiabetes mellitusGenetic risk scoreGenome-wideHealth risk assessmentsPersonalised medicinePharmacological approaches

Identifiers

PMID39688777
PMCPMC11794728

What Socratic holds

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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.