Evidence map›Paper›PMID 34301304›Full record

ArticleBreast cancer research : BCR2021

Biomarkers of mammographic density in premenopausal women.

Mathilde His, Martin Lajous, Liliana Gómez-Flores-Ramos, Adriana Monge, Laure Dossus, Vivian Viallon, Audrey Gicquiau, Carine Biessy, Marc J Gunter, Sabina Rinaldi

Abstract read
In one paragraph

Article in Breast cancer research : BCR, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

10 authors.

Mathilde HisInternational Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, CEDEX 08, 69372, Lyon, France.
Martin LajousCenter for Research on Population Health, National Institute of Public Health, 62100, Cuernavaca, México. mlajous@insp.mx.ORCID 0000-0002-8471-4128
Liliana Gómez-Flores-RamosCenter for Research on Population Health, National Institute of Public Health, 62100, Cuernavaca, México.
Adriana MongeCenter for Research on Population Health, National Institute of Public Health, 62100, Cuernavaca, México.
Laure DossusInternational Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, CEDEX 08, 69372, Lyon, France.
Vivian ViallonInternational Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, CEDEX 08, 69372, Lyon, France.
Audrey GicquiauInternational Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, CEDEX 08, 69372, Lyon, France.
Carine BiessyInternational Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, CEDEX 08, 69372, Lyon, France.
Marc J GunterInternational Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, CEDEX 08, 69372, Lyon, France.
Sabina RinaldiInternational Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, CEDEX 08, 69372, Lyon, France.

Funding

World Health Organization 001
6 · The paper itself

Abstract

backgroundWhile mammographic density is one of the strongest risk factors for breast cancer, little is known about its determinants, especially in young women. We applied targeted metabolomics to identify circulating metabolites specifically associated with mammographic density in premenopausal women. Then, we aimed to identify potential correlates of these biomarkers to guide future research on potential modifiable determinants of mammographic density.

methodsA total of 132 metabolites (acylcarnitines, amino acids, biogenic amines, glycerophospholipids, sphingolipids, hexose) were measured by tandem liquid chromatography/mass spectrometry in plasma samples from 573 premenopausal participants in the Mexican Teachers' Cohort. Associations between metabolites and percent mammographic density were assessed using linear regression models, adjusting for breast cancer risk factors and accounting for multiple tests. Mean concentrations of metabolites associated with percent mammographic density were estimated across levels of several lifestyle and metabolic factors.

resultsSphingomyelin (SM) C16:1 and phosphatidylcholine (PC) ae C30:2 were inversely associated with percent mammographic density after correction for multiple tests. Linear trends with percent mammographic density were observed for SM C16:1 only in women with body mass index (BMI) below the median (27.4) and for PC ae C30:2 in women with a BMI over the median. SM C16:1 and PC ae C30:2 concentrations were positively associated with cholesterol (total and HDL) and inversely associated with number of metabolic syndrome components.

conclusionsWe identified new biomarkers associated with mammographic density in young women. The association of these biomarkers with mammographic density and metabolic parameters may provide new perspectives to support future preventive actions for breast cancer.

Indexed as

PremenopauseAdultBiomarkersBody Mass IndexBreastBreast DensityBreast NeoplasmsCholesterolCross-Sectional StudiesFemaleHumansMammographyMetabolomicsMexicoMiddle AgedPhosphatidylcholinesBiomarkersCholesterolPhosphatidylcholinesSphingomyelinsMammographic densityMexican womenPremenopausalTargeted metabolomics

Identifiers

PMID34301304
PMCPMC8305592

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.