Dataset Information

Premature menopause and autoimmune primary ovarian insufficiency in two international multi-center cohorts.

ABSTRACT:

Objective

To investigate markers of premature menopause (<40 years) and specifically the prevalence of autoimmune primary ovarian insufficiency (POI) in European women.

Design

Postmenopausal women were categorized according to age at menopause and self-reported reason for menopause in a cross-sectional analysis of 6870 women.

Methods

Variables associated with the timing of menopause and hormone measurements of 17β-estradiol and follicle-stimulating hormone were explored using multivariable logistic regression analysis. Specific immunoprecipitating assays of steroidogenic autoantibodies against 21-hydroxylase (21-OH), side-chain cleavage enzyme (anti-SCC) and 17alpha-hydroxylase (17 OH), as well as NACHT leucine-rich-repeat protein 5 were used to identify women with likely autoimmune POI.

Results

Premature menopause was identified in 2.8% of women, and these women had higher frequencies of nulliparity (37.4% vs 19.7%), obesity (28.7% vs 21.4%), osteoporosis (17.1% vs 11.6%), hormone replacement therapy (59.1% vs 36.9%) and never smokers (60.1% vs 50.9%) (P < 0.05), compared to women with menopause ≥40 years. Iatrogenic causes were found in 91 (47%) and non-ovarian causes in 27 (14%) women, while 77 (39%) women were classified as POI of unknown cause, resulting in a 1.1% prevalence of idiopathic POI. After adjustments nulliparity was the only variable significantly associated with POI (odds ratio 2.46; 95% CI 1.63-3.42). Based on the presence of autoantibodies against 21 OH and SCC, 4.5% of POI cases were of likely autoimmune origin.

Conclusion

Idiopathic POI affects 1.1% of all women and almost half of the women with premature menopause. Autoimmunity explains 4.5% of these cases judged by positive steroidogenic autoantibodies.

SUBMITTER: Vogt EC

PROVIDER: S-EPMC9175594 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Premature menopause and autoimmune primary ovarian insufficiency in two international multi-center cohorts.

Vogt Elinor Chelsom EC Real Francisco Gómez FG Husebye Eystein Sverre ES Björnsdottir Sigridur S Benediktsdottir Bryndis B Bertelsen Randi Jacobsen RJ Demoly Pascal P Franklin Karl Anders KA de Aja Gallastegui Leire Sainz LS González Francisco Javier Callejas FJC Heinrich Joachim J Holm Mathias M Jogi Nils Oscar NO Leynaert Benedicte B Lindberg Eva E Malinovschi Andrei A Martínez-Moratalla Jesús J Mayoral Raúl Godoy RG Oudin Anna A Pereira-Vega Antonio A Semjen Chantal Raherison CR Schlünssen Vivi V Triebner Kai K Øksnes Marianne M

Endocrine connections 20220525 5

<h4>Objective</h4>To investigate markers of premature menopause (<40 years) and specifically the prevalence of autoimmune primary ovarian insufficiency (POI) in European women.<h4>Design</h4>Postmenopausal women were categorized according to age at menopause and self-reported reason for menopause in a cross-sectional analysis of 6870 women.<h4>Methods</h4>Variables associated with the timing of menopause and hormone measurements of 17β-estradiol and follicle-stimulating hormone were explored usi ...[more]

PMID: 35521804

Similar Datasets

Project description:BackgroundPremature ovarian insufficiency (POI) patients are predisposed to metabolic disturbances, including in lipid metabolism and glucose metabolism, and metabolic disorders appear to be a prerequisite of the typical long-term complications of POI, such as cardiovascular diseases or osteoporosis. However, the metabolic changes underlying the development of POI and its subsequent complications are incompletely understood, and there are few studies characterizing the disturbed metabolome in POI patients. The aim of this study was to characterize the plasma metabolome in POI by using ultrahigh-performance liquid chromatography-mass spectrometry (UHPLC-MS/MS) metabolomics and to evaluate whether these disturbances identified in the plasma metabolome relate to ovarian reserve and have diagnostic value in POI.MethodsThis observational study recruited 30 POI patients and 30 age- and body mass index (BMI)-matched controls in the Center for Reproductive Medicine, Department of Gynecology and Obstetrics, Nanfang Hospital, Southern Medical University, from January 2018 to October 2020. Fasting venous blood was collected at 9:00 am on days 2-4 of the menstrual cycle and centrifuged for analysis. An untargeted quantitative metabolomic analysis was performed using UHPLC-MS/MS.ResultsOur study identified 48 upregulated and 21 downregulated positive metabolites, and 13 upregulated and 48 downregulated negative metabolites in the plasma of POI patients. The differentially regulated metabolites were involved in pathways such as caffeine metabolism and ubiquinone and other terpenoid-quinone biosynthesis. Six metabolites with an AUC value > 0.8, including arachidonoyl amide, 3-hydroxy-3-methylbutanoic acid, dihexyl nonanedioate, 18-HETE, cystine, and PG (16:0/18:1), were correlated with ovarian reserve and thus have the potential to be diagnostic biomarkers of POI.ConclusionThis UHPLC-MS/MS untargeted metabolomics study revealed differentially expressed metabolites in the plasma of patients with POI. The differential metabolites may not only be involved in the aetiology of POI but also contribute to its major complications. These findings offer a panoramic view of the plasma metabolite changes caused by POI, which may provide useful diagnostic and therapeutic clues for POI disease.

Project description:Premature ovarian insufficiency (POI) is defined as a primary ovarian defect characterized by absent menarche (primary amenorrhea) or premature depletion of ovarian follicles before the age of 40 (secondary amenorrhea) with hypergonadotropism and hypoestrogenism. Premature ovarian insufficiency has few known genetic causes but in familial cases a genetic link is often suspected. A large consanguineous family with three female affected with POI was investigated. All samples including 3 affected and 5 unaffecd underwent whole genome SNP genotyping using Affymetric Axiom_GW_Hu_SNP array. Linkage analysis was carried out using HomozygosityMapper and Allegro softwares.Linkage analysis mapped the disease phenotype to long arm of chromosome 20. Sequence data analysis of potential candidate genes failed to detect any pathogenic variant. Affymetrix SNP arrays were performed according to the manufacturer's directions on DNA extracted from peripheral blood samples. DNA of eight individuals including three affected subjects was used for homozygosity mapping. Genotyping was performed using the Affymetrix Axiom_GW_Hu_SNP array. Briefly, 250 ng genomic DNA was digested with Digestion Master Mix containing 2 µl NE buffer 2 (10X), 0.5 µl BSA (100X; 10 mg/ml) and 1 µl Nsp1. Digested DNA sample was ligated to Nsp1 adaptor using T4 DNA ligase and amplified by 2 µl of TITANIUM Taq DNA polymerase (50X) and 100 µM PCR primer. PCR products were purified on a Clean-Up plate (Clontech Lab, Madison, USA) and eluted by RB buffer. Purified PCR products were fragmented using Fragmentation Reagent (0.05U/µl DNase 1) for 35 minutes at 37°C followed by labeling of fragmented samples with Labeling Master Mix (30 mM GeneChip DNA Labeling Reagent, 30 U/µl Terminal Deoxynucleotidyl Transferase) for 4 hours at 37°C. Labeled samples were hybridized to Axiom_GW_Hu_SNP array by mixing the sample with Hybridization Master Mix, denatured on thermoblock and loaded on to Array. Array was then placed in a hybridization oven (GeneChip Hybridization Oven 640, USA) for 16-18 hours. After hybridization, array was washed and stained on an automated Fluidic Station 450 followed by scanning on GeneChip Scanner 3000 7G using GeneChip Operating Software (GCOS).

Dataset Information

Premature menopause and autoimmune primary ovarian insufficiency in two international multi-center cohorts.

Objective

Design

Methods

Results

Conclusion

Publications

Premature menopause and autoimmune primary ovarian insufficiency in two international multi-center cohorts.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets