Evidence map›Paper›PMID 29704148›Full record

ArticleClinical and translational medicine2018

Clinical lipidomics: a new way to diagnose human diseases.

Jiapei Lv, Linlin Zhang, Furong Yan, Xiangdong Wang

Open access · goldAbstract read
In one paragraph

Article in Clinical and translational medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed
2.4field-weighted citation impact, top 10% 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

39 citing papers in PubMed, 88 citations in OpenAlex.

  1. Trial
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  6. Lipidomics, Microbiota, and IntestinalInternational journal of molecular sciences · 2025
    Review
  7. Article
  8. Lipidomic insights on abdominal aortic aneurysm and peripheral arterial disease.Journal of molecular medicine (Berlin, Germany) · 2025
    Review
  9. Article
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  14. Article
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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 2 institutions in 1 country.

Jiapei LvZhongshan Hospital Institute of Clinical Science, Fudan University Shanghai Medical School, Shanghai Institute of Clinical Bioinformatics, Shanghai, China.
Linlin ZhangZhongshan Hospital Institute of Clinical Science, Fudan University Shanghai Medical School, Shanghai Institute of Clinical Bioinformatics, Shanghai, China.
Furong YanZhongshan Hospital Institute of Clinical Science, Fudan University Shanghai Medical School, Shanghai Institute of Clinical Bioinformatics, Shanghai, China.
Xiangdong WangZhongshan Hospital Institute of Clinical Science, Fudan University Shanghai Medical School, Shanghai Institute of Clinical Bioinformatics, Shanghai, China. xiangdong.wang@clintransmed.org.
Zhongshan Hospital · CNShanghai Medical College of Fudan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lipidomics is a measurement of a large scale of lipid species to understand roles of their carbon atoms, dual bonds, or isomerism in the lipid molecule. Clinical lipidomics was recently defined "as a new integrative biomedicine to discover the correlation and regulation between a large scale of lipid elements measured and analyzed in liquid biopsies from patients with those patient phenomes and clinical phenotypes". The first step to translate lipidomics into clinical lipidomics is to settle a number of standard operation procedures and protocols of lipidomics performance and measurement. Clinical lipidomics is the part of clinical trans-omics which was coined as a new emerging scientific discipline where clinical phenomes are integrated with molecular multiomics. We believe it is the time to translate lipid science and lipidomics into clinical application and to understand the importance of clinical lipidomics as one of the most helpful approaches during the design and decision-making of therapeutic strategies for individuals. We emphasize here that clinical lipidomics should be merged with clinical phenomes, e.g. patient signs and symptoms, biomedical analyses, pathology, images, and responses to therapies, although it is difficult to integrate and fuse the information of clinical lipidomics with clinical phenomes. It will be a great achievement if we can draw the networks of lipidomic species fused with networks of genes and proteins to describe the molecular mechanisms of the disease in multi-dimensions.

Indexed as

BiomarkersClinical lipidomicsDiseaseLipidsPhenomes

Identifiers

PMID29704148
PMCPMC5923182
OpenAlexW2804498896

What OpenQuestion 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 OpenQuestion graph.