Cardiometabolic health in offspring of women with PCOS compared to healthy controls: a systematic review and individual participant data meta-analysis

Abstract

Background: Women diagnosed with polycystic ovary syndrome (PCOS) suffer from an unfavorable cardiometabolic risk profile, which is already established by child-bearing age.

Objective and rationale: The aim of this systematic review along with an individual participant data meta-analysis is to evaluate whether cardiometabolic features in the offspring (females and males aged 1-18 years) of women with PCOS (OPCOS) are less favorable compared to the offspring of healthy controls.

Search methods: PubMed, Embase and gray literature databases were searched by three authors independently (M.N.G., M.A.W and J.C.) (last updated on 1 February 2018). Relevant key terms such as 'offspring' and 'PCOS' were combined. Outcomes were age-specific standardized scores of various cardiometabolic parameters: BMI, blood pressure, glucose, insulin, lipid profile and the sum scores of various cardiometabolic features (metabolic sum score). Linear mixed models were used for analyses with standardized beta (β) as outcome.

Outcomes: Nine relevant observational studies could be identified, which jointly included 1367 children: OPCOS and controls, originating from the Netherlands, Chile and the USA. After excluding neonates, duplicate records and follow-up screenings, a total of 885 subjects remained. In adjusted analyses, we observed that OPCOS (n = 298) exhibited increased plasma levels of fasting insulin (β = 0.21(95%CI: 0.01-0.41), P = 0.05), insulin-resistance (β = 0.21(95%CI: 0.01-0.42), P = 0.04), triglycerides (β = 0.19(95%CI: 0.02-0.36), P = 0.03) and high-density lipoprotein (HDL)-cholesterol concentrations (β = 0.31(95%CI: 0.08-0.54), P < 0.01), but a reduced birthweight (β = -116(95%CI: -195 to 38), P < 0.01) compared to controls (n = 587). After correction for multiple testing, however, differences in insulin and triglycerides lost their statistical significance. Interaction tests for sex revealed differences between males and females when comparing OPCOS versus controls. A higher 2-hour fasting insulin was observed among female OPCOS versus female controls (estimated difference for females (βf) = 0.45(95%CI: 0.07 to 0.83)) compared to the estimated difference between males ((βm) = -0.20(95%CI: -0.58 to 0.19)), with interaction-test: P = 0.03. Low-density lipoprotein-cholesterol differences in OPCOS versus controls were lower among females (βf = -0.39(95%CI: -0.62 to 0.16)), but comparable between male OPCOS and male controls (βm = 0.27(95%CI: -0.03 to 0.57)), with interaction-test: P < 0.01. Total cholesterol differences in OPCOS versus controls were also lower in females compared to the difference in male OPCOS and male controls (βf = -0.31(95%CI: -0.57 to 0.06), βm = 0.28(95%CI: -0.01 to 0.56), interaction-test: P = 0.01). The difference in HDL-cholesterol among female OPCOS versus controls (βf = 0.53(95%CI: 0.18-0.88)) was larger compared to the estimated mean difference among OPCOS males and the male controls (βm = 0.13(95%CI: -0.05-0.31), interaction-test: P < 0.01). Interaction test in metabolic sum score revealed a significant difference between females (OPCOS versus controls) and males (OPCOS versus controls); however, sub analyses performed in both sexes separately did not reveal a difference among females (OPCOS versus controls: βf = -0.14(95%CI: -1.05 to 0.77)) or males (OPCOS versus controls: βm = 0.85(95%CI: -0.10 to 1.79)), with P-value < 0.01.

Wider implications: We observed subtle signs of altered cardiometabolic health in OPCOS. Therefore, the unfavorable cardiovascular profile of women with PCOS at childbearing age may-next to a genetic predisposition-influence the health of their offspring. Sensitivity analyses revealed that these differences were predominantly observed among female offspring aged between 1 and 18 years. Moreover, studies with minimal risk of bias should elucidate the influence of a PCOS diagnosis in mothers on both sexes during fetal development and subsequently during childhood.

Keywords: PCOS; cardiometabolic health; cardiovascular health; children; metabolic health; offspring; periconception; preconception; sex differences.

Figure 1

Flowchart of the search, according to PRISMA guidelines. ^* = all data in this step were available obtained and analyzed, n = number. All numbers (n) mentioned in the exclusion criteria were extracted in the ‘screening on full-text’ step (Figure adjusted from the PRISMA group (Moher 2009).

Figure 2. Flowchart of the study: from systematic search results to IPD dataset. This flowchart represents the four steps (four columns’ from left to right), which were undertaken to collect our final data for the IPD meta-analysis. Column (1) Participants (n) per study. Our screening resulted in nine publications from three research groups with (n) participants per article (cases and controls together). Column (2) Received data. Each research group shared one file with all offspring of women with PCOS (OPCOS) and all healthy controls (n), which showed that some subjects participated in more than one publication. Column (3) Extraction <1 yr (year) and duplicates. In the third step, we excluded all children below 1 year old and all duplicate children (children who were screened multiple times). Column (4) IPD analysis n = 885. In the fourth step, a dataset remained with 885 unique children aged 1–18 years (OPCOS and controls), on which we conducted our IPD meta-analyses.

Figure 3. Parameters measured per age category in all included centers. Total number of included children on their first visit is 885: for two children their age and sex is missing. (n) = number of children in which the parameter is available.