Evidence map›Paper›PMID 35949812›Full record

ReviewWorld journal of clinical cases2022

Diabetes mellitus susceptibility with varied diseased phenotypes and its comparison with phenome interactome networks.

Madhusmita Rout, Bhumandeep Kour, Sugunakar Vuree, Sajitha S Lulu, Krishna Mohan Medicherla, Prashanth Suravajhala

Open access · diamondAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in World journal of clinical cases, 2022. 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
0.2field-weighted citation impact, top 53% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  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

6 authors at 2 institutions in 1 country.

Madhusmita RoutDepartment of Pediatrics, University of Oklahoma Health Sciences Centre, Oklahoma City, OK 73104, United States.
Bhumandeep KourDepartment of Biotechnology, Lovely Professional University, Phagwara 144001, Punjab, India.
Sugunakar VureeDepartment of Biotechnology, Lovely Professional University, Phagwara 144001, Punjab, India.
Sajitha S LuluDepartment of Biotechnology, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India.
Krishna Mohan MedicherlaDepartment of Biotechnology and Bioinformatics, Birla Institute of Scientific Research, Jaipur 302001, Rajasthan, India.
Prashanth SuravajhalaAmrita School of Biotechnology, Amrita Vishwa Vidyapeetham, Vallikavu PO, Amritapuri, Clappana, Kollam 690525, Kerala, India. prash@bioclues.org.
Birla Institute of Scientific Research · INVellore Institute of Technology University · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An emerging area of interest in understanding disease phenotypes is systems genomics. Complex diseases such as diabetes have played an important role towards understanding the susceptible genes and mutations. A wide number of methods have been employed and strategies such as polygenic risk score and allele frequencies have been useful, but understanding the candidate genes harboring those mutations is an unmet goal. In this perspective, using systems genomic approaches, we highlight the application of phenome-interactome networks in diabetes and provide deep insights. LINC01128, which we previously described as candidate for diabetes, is shown as an example to discuss the approach.

Indexed as

Gestational diabetes mellitusPhenomePleiotropyProstate cancerType 1 diabetesType 2 diabetes

Identifiers

PMID35949812
PMCPMC9254192
OpenAlexW4282960395

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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 OpenQuestion graph.