Justiina Ronkainen

Gestational diabetes mellitus (GDM) affects ~14% of pregnancies and increases maternal type 2 diabetes mellitus (T2DM) risk. The GenDiP Consortium presents trans-generational, multi-ancestry genome-wide association study meta-analyses of GDM and pregnancy glycemic traits in up to 38,305 GDM cases and 776,145 controls. We identify 37 GDM-associated loci (7 novel) and five novel loci for pregnancy glycemic traits, all operating through the maternal genome. We classify 12 GDM variants with stronger effects in GDM than T2DM into five biologically informed categories, revealing pleiotropy patterns, pregnancy-dependent effect modification, and diagnostic heterogeneity. While all these loci overlap with T2DM and/or non-pregnant glycaemic traits, four (G6PC2, CAST-PCSK1, HKDC1, FOXA2) lack genome-wide-significant T2DM associations; GCK shows distinct causal variants for GDM, and MTNR1B exhibits pregnancy-amplified effects. Our findings provide new genetic insights into GDM and highlight the need for larger, ancestrally diverse studies of GDM and glycaemic traits during pregnancy to understand potential pregnancy-specific effects.

Preterm birth and very low birth weight (VLBW; p < 0.05) between VLBW and siblings. Top sites were annotated to genes related to lipid metabolism (cg00264176 (FADS2), 0.077 (0.007), FDR p = 3.24 × 10^-14) and neural development (cg08277679 (KIF26A), 0.053 (0.005), FDR p = 8.22 × 10^-12). IPA identified enrichment for 81 pathways (FDR p < 0.05). Our results suggest tissue-specific DNAm differences in VLBW adults compared to their siblings. The changes cluster in pathways related to lipid metabolism, neurodevelopment, and cardiometabolic regulation, suggesting lasting tissue-specific epigenetic modifications in VLBW adults.

Aim: Gestational diabetes (GDM) has important environmental and genetic components. Genetic variants associated with GDM (n=14 SNPs) were recently classified into 2 groups: those with stronger effects on type 2 diabetes than GDM (Class-T, 3 SNPs) and those with stronger effects on GDM than on type 2 diabetes (Class-G, 8 SNPs), leaving 3 SNPs unclassified. It was suggested that the Class-G variants contribute to hyperglycaemia predominantly during gestation, but it is not known whether the effects of the two variant classes on maternal glucose levels vary with pregnancy status. We aimed to compare the effects of GDM-associated variants on glucose levels (fasting glucose and 2-hour post-OGTT) measured during vs. after pregnancy in longitudinal cohorts. Methods: We calculated genetic scores (GS) by class (T_GS and G_GS) and overall (All_GS) in 10,225 pregnant women and 4,763 women post-pregnancy (mean 10.5 years post pregnancy) from 8 datasets representing 4 ancestrally-diverse cohorts: EFSOCH, Gen3G, HAPO and FinnGeDi. We used linear regression models adjusted for ancestry principal components to investigate associations between standardised GS and glucose levels during or after pregnancy. Analyses were performed separately in each dataset and then combined using inverse-variance weighted random-effects meta-analyses. Results: In the meta-analysis, All_GS was associated with fasting glucose both during and after pregnancy (β[95%CI], in mmol/L per 1SD higher GS = 0.06 [0.04;0.08] during vs. 0.06 [0.04;0.07] post-pregnancy). All_GS was also associated with 2-hour post-OGTT glucose levels during pregnancy but not after (0.10 [0.04; 0.15] during vs. 0.01 [-0.04; 0.07] post-pregnancy). Both G_GS and T_GS showed consistent associations with fasting glucose during and post pregnancy (0.06 [0.04; 0.08] during and 0.05 [0.03; 0.07] post pregnancy for G_GS; 0.02 [0.01; 0.02] during and 0.02 [-0.001; 0.05] post pregnancy for T_GS). G_GS showed weak evidence of association with 2-hour glucose levels during pregnancy (0.06 [-0.002; 0.11]) and no association with 2-hour glucose levels post pregnancy (-0.03 [-0.08; 0.03]). However, T_GS was associated with 2-hour glucose during pregnancy and post pregnancy (0.10 [0.04; 0.16] and 0.06 [0.01; 0.12]). Conclusion: Genetic scores for GDM have consistent associations with fasting glucose levels during and after pregnancy. This finding suggests that biological pathways underlying GDM genetic susceptibility to fasting hyperglycaemia are not pregnancy specific. However, the results for All_GS and 2-hour glucose provide evidence that some genetic associations with postprandial glucose may be stronger in pregnancy and should be followed up in larger samples.

Background/Objectives: Children’s biological age does not always correspond to their chronological age. In the case of BMI trajectories, this can appear as phase variation, which can be seen as shift, stretch, or shrinking between trajectories. With maturation thought of as a process moving towards the final state - adult BMI, we assessed whether children can be divided into latent groups reflecting similar maturational age of BMI. The groups were characterised by early factors and time-related features of the trajectories. Subjects/Methods: We used data from two general population birth cohort studies, Northern Finland Birth Cohorts 1966 and 1986 (NFBC1966 and NFBC1986). Height (n = 6329) and weight (n = 6568) measurements were interpolated in 34 shared time points using B-splines, and BMI values were calculated between 3 months to 16 years. Pairwise phase distances of 2999 females and 3163 males were used as a similarity measure in k-medoids clustering. Results: We identified three clusters of trajectories in females and males (Type 1: females, n = 1566, males, n = 1669; Type 2: females, n = 1028, males, n = 973; Type 3: females, n = 405, males, n = 521). Similar distinct timing patterns were identified in males and females. The clusters did not differ by sex, or early growth determinants studied. Conclusions: Trajectory cluster Type 1 reflected to the shape of what is typically illustrated as the childhood BMI trajectory in literature. However, the other two have not been identified previously. Type 2 pattern was more common in the NFBC1966 suggesting a generational shift in BMI maturational patterns.

Higher birth order is associated with altered risk of many disease states. Changes in placentation and exposures to in utero growth factors with successive pregnancies may impact later life disease risk via persistent DNA methylation alterations. We investigated birth order with Illumina DNA methylation array data in each of 16 birth cohorts (8164 newborns) with European, African, and Latino ancestries from the Pregnancy and Childhood Epigenetics Consortium. Meta-analyzed data demonstrated systematic DNA methylation variation in 341 CpGs (FDR adjusted P < 0.05) and 1107 regions. Forty CpGs were located within known quantitative trait loci for gene expression traits in blood, and trait enrichment analysis suggested a strong association with immune-related, transcriptional control, and blood pressure regulation phenotypes. Decreasing fertility rates worldwide with the concomitant increased proportion of first-born children highlights a potential reflection of birth order-related epigenomic states on changing disease incidence trends.

A well-functioning placenta is essential for fetal and maternal health throughout pregnancy. Using placental weight as a proxy for placental growth, we report genome-wide association analyses in the fetal (n = 65,405), maternal (n = 61,228) and paternal (n = 52,392) genomes, yielding 40 independent association signals. Twenty-six signals are classified as fetal, four maternal and three fetal and maternal. A maternal parent-of-origin effect is seen near KCNQ1. Genetic correlation and colocalization analyses reveal overlap with birth weight genetics, but 12 loci are classified as predominantly or only affecting placental weight, with connections to placental development and morphology, and transport of antibodies and amino acids. Mendelian randomization analyses indicate that fetal genetically mediated higher placental weight is causally associated with preeclampsia risk and shorter gestational duration. Moreover, these analyses support the role of fetal insulin in regulating placental weight, providing a key link between fetal and placental growth.

Background: Preterm birth is the leading cause of perinatal morbidity and mortality and is associated with adverse developmental and long-term health outcomes, including several cardiometabolic risk factors and outcomes. However, evidence about the association of preterm birth with later body size derives mainly from studies using birth weight as a proxy of prematurity rather than an actual length of gestation. We investigated the association of gestational age (GA) at birth with body size from infancy through adolescence. Methods and findings: We conducted a two-stage individual participant data (IPD) meta-analysis using data from 253,810 mother–child dyads from 16 general population-based cohort studies in Europe (Denmark, Finland, France, Italy, Norway, Portugal, Spain, the Netherlands, United Kingdom), North America (Canada), and Australasia (Australia) to estimate the association of GA with body mass index (BMI) and overweight (including obesity) adjusted for the following maternal characteristics as potential confounders: education, height, prepregnancy BMI, ethnic background, parity, smoking during pregnancy, age at child’s birth, gestational diabetes and hypertension, and preeclampsia. Pregnancy and birth cohort studies from the LifeCycle and the EUCAN-Connect projects were invited and were eligible for inclusion if they had information on GA and minimum one measurement of BMI between infancy and adolescence. Using a federated analytical tool (DataSHIELD), we fitted linear and logistic regression models in each cohort separately with a complete-case approach and combined the regression estimates and standard errors through random-effects study-level meta-analysis providing an overall effect estimate at early infancy (>0.0 to 0.5 years), late infancy (>0.5 to 2.0 years), early childhood (>2.0 to 5.0 years), mid-childhood (>5.0 to 9.0 years), late childhood (>9.0 to 14.0 years), and adolescence (>14.0 to 19.0 years). GA was positively associated with BMI in the first decade of life, with the greatest increase in mean BMI z-score during early infancy (0.02, 95% confidence interval (CI): 0.00; 0.05, p < 0.05) per week of increase in GA, while in adolescence, preterm individuals reached similar levels of BMI (0.00, 95% CI: −0.01; 0.01, p 0.9) as term counterparts. The association between GA and overweight revealed a similar pattern of association with an increase in odds ratio (OR) of overweight from late infancy through mid-childhood (OR 1.01 to 1.02) per week increase in GA. By adolescence, however, GA was slightly negatively associated with the risk of overweight (OR 0.98 [95% CI: 0.97; 1.00], p 0.1) per week of increase in GA. Although based on only four cohorts (n = 32,089) that reached the age of adolescence, data suggest that individuals born very preterm may be at increased odds of overweight (OR 1.46 [95% CI: 1.03; 2.08], p < 0.05) compared with term counterparts. Findings were consistent across cohorts and sensitivity analyses despite considerable heterogeneity in cohort characteristics. However, residual confounding may be a limitation in this study, while findings may be less generalisable to settings in low- and middle-income countries. Conclusions: This study based on data from infancy through adolescence from 16 cohort studies found that GA may be important for body size in infancy, but the strength of association attenuates consistently with age. By adolescence, preterm individuals have on average a similar mean BMI to peers born at term.

Background: Smoking is the biggest preventable factor causing mortality and morbidity and the health benefits of smoking cessation are commonly known. Smoking cessation-related weight gain is well documented. We evaluated the association between smoking cessation and the incidence of obesity-related morbidities such as hypertension, diabetes and metabolic syndrome as well as mortality. We also evaluated telomere length related to smoking cessation. Material and methods: This study was part of the OPERA (Oulu Project Elucidating Risk of Atherosclerosis) study. The mean follow up time among the 600 study subjects was 20 years. We divided the study subjects into four groups by smoking status (“never”, “current”, “ex-smokers” and “quit”) and analyzed their health status. “Ex-smokers” had quit smoking before baseline and “quit” quit during the follow-up time. Information about total mortality between the years 2013–2020 was also utilized. Results: During the follow-up time systolic blood pressure decreased the most in the “current” and in the “ex-smoker” groups. Office SBP decreased the least in the “quit” group (p = 0.001). BMI increased the most in the “quit” and the least in the “ex-smokers” group (p = 0.001). No significant increases were seen in the incidence of obesity-related-diseases, such as metabolic syndrome, hypertension and diabetes was seen. There was no significant difference in the shortening of telomeres. Odds of short-term mortality was increased in the “current” group (2.43 (CI 95% 1.10; 5.39)), but not in the “quit” (1.43 (CI 95% 0.73–2.80)) or “ex-smoker” (1.02 (CI 95% 0.56–1.86)) groups when compared to “never” group. Conclusions: Even though, the blood pressure levels were unfavorable in the “quit” group, there was no significant increase in the incidence of obesity-related-diseases, and a noticeable benefit in short-term mortality was seen during the 6-year follow-up. The benefits of smoking cessation outweigh the disadvantages in the long-term.

Background: Preterm birth is the leading cause of perinatal morbidity and mortality, and is associated with adverse developmental and long-term health outcomes, including several cardio-metabolic risk factors. However, evidence about the association of preterm birth with later body size derives mainly from studies using birth weight as proxy of prematurity rather than actual length of gestation. We investigated the association of gestational age at birth (GA) with body size from infancy through adolescence. Methods and Findings: We conducted a two-stage Individual Participant Data (IPD) meta-analysis using data from 253,810 mother-children dyads from 16 general population-based cohort studies in Europe, North America and Australasia to estimate the association of GA with standardized Body Mass Index (BMI) and overweight (including obesity) adjusted for confounders. Using a federated analytical tool (DataSHIELD), we fitted linear and logistic regression models in each cohort separately, and combined the regression estimates and standard errors through random-effects study-level meta-analysis providing an overall effect estimate at early infancy (>0.0-0.5 years), late infancy (>0.5-2.0 years), early childhood (>2.0-5.0 years), mid-childhood (>5.0-9.0 years), late childhood (>9.0-14.0 years) and adolescence (>14.0-19.0 years). GA was positively associated with BMI in the first decade of life with mean differences in BMI z-score (0.01-0.02) per week of increase in GA, however preterm infants reached similar levels of BMI as term infants by adolescence. The association of GA with risk of overweight revealed a similar pattern of results from late infancy through mid-childhood with an increased odds of overweight (OR 1.01-1.02) per week increase in GA. By adolescence, however, GA was slightly negatively associated with risk of overweight (OR 0.98 [95% CI: 0.97:1.00]) per week of increase in GA, and children born very preterm had increased odds of overweight (OR 1.46 [95% CI: 1.03; 2.08]) compared with term. The findings were consistent across cohorts and sensitivity analyses, despite considerable heterogeneity in cohort characteristics. Conclusion: Higher GA is potentially clinically important for higher BMI in infancy, while the association attenuates consistently with age. By adolescence, preterm children have on average a similar mean BMI to those born term.