Dataset Information

Adjusting antimullerian hormone levels for age and body mass index improves detection of polycystic ovary syndrome.

ABSTRACT:

Objective

To examine whether accounting for a woman's age and body mass index (BMI) would improve the ability of antimüllerian hormone (AMH) to distinguish between women with (cases) and without (controls) polycystic ovarian syndrome (PCOS).

Design

An opportunistic case-control dataset of reproductive age women having evaluations for PCOS as defined by National Institutes of Health criteria.

Setting

Two medical centers in the United States enrolled women. Serum samples were analyzed for relevant analytes.

Patients

Women were between 18 and 39 years of age when samples and clinical information were collected. Residual samples had been stored for 2-17 years. AMH was measured via immunoassay.

Interventions

None; this was an observational study.

Main outcome measures

Detection and false-positive rates for PCOS were computed for AMH results expressed as multiples of the median (MoM) both before and after adjustment for the woman's age and BMI.

Results

Using unadjusted AMH MoM results, 168 cases (78%) cases were at or beyond the 90^th centile of controls (2.47 MoM). After accounting for each woman's age and BMI, 188 (87%) of those women were beyond the 90^th centile of controls (2.20 MoM), a significant increase (P = .015). The adjusted AMH MoM levels fitted logarithmic normal distributions well (mean, standard deviation for controls and cases of 0.0000, 0.2765 and 0.6884, 0.2874, respectively) and this allowed for computation of patient-specific PCOS risks.

Conclusions

Accounting for the woman's age and BMI resulted in significantly higher AMH-based detection rates for PCOS at a 10% false-positive rate, and patient-specific PCOS risks could be computed.

SUBMITTER: Palomaki GE

PROVIDER: S-EPMC7583345 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Study questionWhat are the causal relationships between polycystic ovary syndrome (PCOS) and body mass index (BMI)?Summary answerBidirectional Mendelian randomization analyses suggest that increased BMI is causal for PCOS while the reverse is not the case.What is known alreadyThe contribution of obesity to the pathogenesis of PCOS is controversial. To date, published genetic studies addressing this question have generated conflicting results and have not utilized the full extent of known single nucleotide polymorphisms associated with body mass index (BMI).Study design, size, durationThis cross-sectional Mendelian randomization (MR) and genetic association study was conducted in 750 individuals of European origin and with PCOS and 1567 BMI-matched controls.Participants/materials, setting, methodsCases and controls were matched for BMI as well as for distribution of weight categories (normal weight, overweight, obese). Two-sample MR using inverse variance weighting (IVW) was conducted using a 92-SNP instrument variable for BMI with PCOS as the outcome, followed by two-sample MR with a 16-SNP instrument variable for PCOS with BMI as the outcome. Sensitivity analyses included MR-Egger and maximum likelihood methods. Secondary analyses assessed associations of genetic risk scores and individual SNPs with PCOS, BMI and quantitative androgen-related and glucose homeostasis-related traits.Main results and the role of chanceEach standard deviation genetically higher BMI was associated with a 4.89 (95% CI 1.46-16.32) higher odds of PCOS. Conversely, genetic risk of PCOS did not influence BMI. Sensitivity analyses yielded directionally consistent results. The genetic risk score of 92 BMI SNPs was associated with the diagnosis of PCOS (OR 1.043, 95% CI 1.009-1.078, P = 0.012). Of the 92 BMI risk variants evaluated, none were associated individually with PCOS after considering multiple testing. The association of FTO SNP rs1421085 with BMI was stronger in women with PCOS (β = 0.071, P = 0.0006) than in controls (β = 0.046, P = 0.065).Limitations, reasons for cautionThe current sample size, while providing good power for MR and genetic risk score analyses, had limited power to demonstrate association of individual SNPs with PCOS. Cases and controls were not matched for age; however, this was mitigated by adjusting analyses for age. Dietary and lifestyle data, which could have been used to explore the greater association of the FTO SNP with BMI in women with PCOS, was not available.Wider implications of the findingsIncreasing BMI appears to be causal for PCOS but having PCOS does not appear to affect BMI. This study used the most comprehensive set of SNPs for BMI currently available. Prior studies using fewer SNPs had yielded conflicting results and may have been confounded because cases and controls were not matched for weight categories. The current results highlight the potential utility of weight management in the prevention and treatment of PCOS.Study funding/competing interest(s)National Institutes of Health Grants R01-HD29364 and K24-HD01346 (to R.A.), Grant R01-DK79888 (to M.O.G.), Grant U54-HD034449 (to R.S.L.), Grant U19-HL069757 (to R.M.K.). The funders had no influence on the data collection, analyses or conclusions of the study. No conflict of interests to declare.Trial registration numberN/A.