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. 2019 Sep 11;14(9):e0222239.
doi: 10.1371/journal.pone.0222239. eCollection 2019.

Hormonal, metabolic and inflammatory circulating biomarker profiles in obese and non-obese Brazilian middle-aged women

Leonardo Victor Galvão-Moreira  1 , Anna Cyntia Brandão Nascimento  2 , Izabella Mikaella Souza Campos D'Albuquerque  1 , Marcus Antonio Silva Sousa  1 , Haissa Oliveira Brito  2 , Maria do Desterro Soares Brandão Nascimento  2 , Maria Bethânia da Costa Chein  2 , Luciane Maria Oliveira Brito  2
Affiliations

Hormonal, metabolic and inflammatory circulating biomarker profiles in obese and non-obese Brazilian middle-aged women

Leonardo Victor Galvão-Moreira et al. PLoS One. .

Abstract

Aim: To investigate circulating hormonal, metabolic and inflammatory biomarker profiles in obese and non-obese middle-aged women.

Methods: A total of 110 women, aged 40-60 years, were included in this cross-sectional study. Patients were allocated, according to the occurrence of menopause and body mass index (BMI), into four groups: PM0 (premenopausal non-obese), PM1 (premenopausal obese), M0 (postmenopausal non-obese), and M1 (postmenopausal obese). Serum levels of gonadotropins, sex hormones, lipid markers, leptin, hs-CRP and interleukin-6 were obtained using either colorimetric or immunoenzymatic assays. Univariate and correlation analyses were performed among all clinical and laboratorial parameters. Principal component analysis was used to characterize subsets of biomarkers, which had their discriminatory capacity tested using discriminant function analysis.

Results: Levels of gonadotropins and female sex hormones were similar between PM0 and PM1 and between M0 and M1 (p > 0.05), all of them varied between PM0 and M0 (p < 0.05), but only estradiol was significantly altered in the comparison between PM1 and M1 (p = 0.027). Regarding metabolic markers, leptin was lower in PM0 than in M0 (p = 0.010) and higher in M1 than in M0 (p = 0.046). In premenopausal women, BMI correlated only to leptin, while it correlated to several other markers in postmenopausal women. A combination of FSH and leptin serum levels significantly discriminated the four groups (Wilks's lambda < 0.001, in canonical functions 1 and 2).

Conclusion: A combined analysis of hormonal biomarkers may potentially distinguish obese from non-obese women with distinct menopause status. Further research is thus required to clarify the clinical significance of such findings.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Comparison of medians of plasma leptin levels (ng/mL) between non-obese and obese women with different menopausal status.
PM0: premenopausal non-obese; PMI: premenopausal obese; M0: postmenopausal non-obese; M1: postmenopausal obese.
Fig 2
Fig 2. Comparison of medians of plasma IL-6 levels (ng/mL) between non-obese and obese women with different menopausal status.
PM0: premenopausal non-obese; PMI: premenopausal obese; M0: postmenopausal non-obese; M1: postmenopausal obese.
Fig 3
Fig 3. Discriminatory potential of serum biomarkers between the subgroups PM0, PM1, M0 and M1.
The panel plot displays a significant separation in discriminant function analysis according to a combination of biomarkers from PC1-4 that were pooled for this analysis: Note a separation among all groups, particularly PM0 from the other three groups (PM1, M0 and M1) by a biomarker combination of FSH and leptin (Wilks’s lambda <0.001, in canonical functions 1 and 2). PC: principal component; PM0: premenopausal non-obese; PMI: premenopausal obese; M0: postmenopausal non-obese; M1: postmenopausal obese.
See this image and copyright information in PMC

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References

    1. Davis SR, Lambrinoudaki I, Lumsden M, Mishra GD, Pal L, Rees M et al. Menopause. Nat Rev Dis Primers. 2015;1:15004 10.1038/nrdp.2015.4 - DOI - PubMed
    1. Levine ME, Lu AT, Chen BH, Hernandez DG, Singleton AB, Ferrucci L et al. Menopause accelerates biological aging. Proc Natl Acad Sci USA. 2016;113(33):9327–9332. 10.1073/pnas.1604558113 - DOI - PMC - PubMed
    1. Ossewaarde ME, Bots ML, Verbeek AL, Peeters PH, van der Graaf Y, Grobbee DE et al. Age at menopause, cause-specific mortality and total life expectancy. Epidemiology. 2005;16(4):556–562. - PubMed
    1. Picon-Ruiz M, Morata-Tarifa C, Valle-Goffin JJ, Friedman ER, Slingerland JM. Obesity and adverse breast cancer risk and outcome: Mechanistic insights and strategies for intervention. CA Cancer J Clin. 2017;67(5):378–397. 10.3322/caac.21405 - DOI - PMC - PubMed
    1. Kabat GC, Kim MY, Lee JS, Ho GY, Going SB, Beebe-Dimmer J et al. Metabolic obesity phenotypes and risk of breast cancer in postmenopausal women. Cancer Epidemiol Biomarkers Prev. 2017;26(12):1730–1735. 10.1158/1055-9965.EPI-17-0495 - DOI - PMC - PubMed

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