Discussion
Our results indicate that in this high-risk group of women, a type 2 diabetes PRS modifies the association between an HLS and glycemic abnormalities still 5 years after delivery. After adjusting for age, HLS was associated with reduced risk of glycemic abnormalities only among women at highest genetic risk of type 2 diabetes. This is well in line with our previous findings from pregnancy and the first postpartum year.19 In the total study sample, however, the HLS associated with health benefits such as a lower BMI and body fat percentage, highlighting the importance of supporting healthy lifestyle among all postpartum women.
The PRS for type 2 diabetes was associated with HOMA-beta in our study. Although there also was a higher occurrence of IFG and other glycemic abnormalities among the women at the highest genetic risk, these associations did not reach statistical significance. Women who develop postpartum diabetes have shown lower HOMA-beta cell indexes.26–28 It reflects the insulin secretion capacity of beta-cells and may act as an important sign of future diabetes risk.
Contrary to our results, many studies,29–32 including our own during pregnancy and first postpartum year,19 have shown an association between a type 2 diabetes PRS and glycemic outcomes. Similar to our study, many studies have also addressed women with a history of GDM.30–32 In a recent population-based study, women with prior GDM who developed type 2 diabetes in 10 years of follow-up had a higher diabetes PRS compared with those remaining normoglycemic. Also, women with GDM but no later diagnosis of type 2 diabetes had a higher PRS than age-matched and BMI-matched women without GDM indicating that a higher PRS increases the risk of both GDM and later progression to type 2 diabetes.31 Reasons for the undetectable associations in this study could be due to our smaller study population. Differences in the PRSs and selected SNPs could also influence the results.
In our total study population, the HLS showed no significant association with glycemic abnormalities. In many previous studies, on the other hand, HLS has been linked to glycemic abnormalities both during pregnancy and in general population.33–35 Among pregnant women, adhering to each additional lifestyle factor (diet, PA, stress level, and smoking) lowered the risk of GDM by 23%.33 Moreover, a large study in the general population (500 000 participants) demonstrated that an HLS consisting of BMI, alcohol consumption, PA, diet, and smoking status was associated with a lower risk of diabetes, regardless of genetic background.34
There have been, however, only a limited number of studies assessing the association between an HLS and glycemic abnormalities among postpartum women. Importantly, in our study the HLS showed a significant association with both BMI and body fat percentage which possibly indicates a positive influence on the overall metabolic health. Body fat percentage and BMI both significantly associate with CVD risk highlighting the importance of healthy lifestyle in all postpartum women.36
Lifestyle may have individual effects on people.15 16 20 In a large cohort study, all participants benefitted from achieving lifestyle goals, for example, by improving glycemic health, but the participants at higher genetic risk benefitted the most.37 Also, in a gene-lifestyle interaction study, the individuals at higher genetic risk of diabetes were more likely to have a successful lifestyle modification.38 Our current results are well in line with these studies demonstrating a statistically significant interaction between HLS and type 2 diabetes PRS on glycemic abnormalities,15 16 showing a greater benefit among the participants at highest genetic risk. Also, during pregnancy and first year postpartum, the exact same PRS for type 2 diabetes modified the response to lifestyle intervention, lending credence to this current finding.19
Overall, there has not been many studies focusing on gene-environment interactions in women with prior GDM, and none of them has used a PRS for assessing genetic risk. In one randomized study, women with prior GDM and a CDKAL1 risk variant received more benefit from the lifestyle intervention.17 Also MC4R has shown an interaction with lifestyle intervention on changes in fasting insulin and HOMA-IR 1–3 years postpartum: again, individuals with the risk allele responded to a lifestyle intervention with improvements in insulin resistance.39 In the RADIEL study, 5 years postpartum lifestyle was associated with better glycemic health only among women with prepregnancy obesity.20 In this current study, however, there were no differences in clinical characteristics, for example, BMI, between genetic risk groups suggesting that this gene-lifestyle interaction might not explain our prior findings.
One of the strengths in our study comes down to the well-characterized cohort, consisting of an early pregnancy randomized lifestyle intervention with a follow-up continuing up to 5 years postpartum. Our strength also lies in the methods of measuring lifestyle: objective measurement of PA with Armband and the standardized recording of diet with FFQ. Calculating the HFII gave us a comprehensive understanding of an individual’s diet as an entity. Another notable strength is the use of a PRS for assessing the genetic risk, offering a more comprehensive estimate of the genetic risk than just individual SNPs.
There are, however, some limitations in our study; one is genotyping only preselected SNPs. A genome-wide genotyping would have given a larger view of the genetic risk, but on the other hand, 50 SNPs could be more affordable for future clinical use. Another limitation is relying solely on calculated indices of insulin secretion and resistance. This may cause varying results due to a partial alteration of hepatic insulin extraction caused by obesity. Unfortunately, we also lack reliable data on pregnancies following the study period which limits the possibilities for assessing the influence of parity. Although the participation rate in the follow-up study was surprisingly good, the number of women is still limited. This might have an influence on the effect of healthy lifestyle in the lowest and middle tertiles where the occurrence of glycemic abnormalities is lower. There was also some missing data on the lifestyle variables included in the HLS which required multiple imputation. The results were, however, well in line when using either the original HLS or the imputed HLS, confirming the reliability of our results.
Women with prior GDM are at markedly increased risk for type 2 diabetes postpartum and therefore form an important group for preventive interventions. As our study demonstrates, clinical characteristics are not enough for identifying those at the highest risk of type 2 diabetes and benefitting the most from lifestyle interventions. From this perspective, all women with GDM history, independent of their BMI, deserve a postpartum follow-up program. Assessing the genetic background could offer one means for selecting candidates for individualized and more intensive preventive interventions. We still need longer and larger follow-up studies focusing on women with GDM history to assess whether this interaction is still evident 10–20 years postpartum. By time, age increases the risk of diabetes even further and gradually rising BMI by age and the menopausal transition compromise metabolic health even further. After delivery, we should not only focus on the child, but also remember the long-term health of the mothers.