THE ASSOCIATION BETWEEN MATERNAL ANTHROPOMETRY AND BLOOD PRESSURE IN PREGNANCY – RESULTS FROM THE CROATIAN ISLANDS’ BIRTH COHORT STUDY (CRIBS)

Elevated blood pressure (BP) in pregnancy, especially gestational hypertension and preeclampsia, can lead to serious pregnancy complications and adverse birth outcomes. A large body of literature already reported the effect of baseline body mass index (BMI) on changes in blood pressure during pregnancy. The aim of this study was therefore to define trajectory of systolic (SBP) and diastolic (DBP) blood pressure in 308 pregnant participants from the CRIBS study (146 from the mainland and 162 from the islands of Brač and Hvar) and to analyze the association of blood pressure with maternal BMI prior to pregnancy and maternal anthropometry during pregnancy. Pregnant women included in the CRIBS study had no history of chronic diseases. The BP of CRIBS participants was measured at least once in each trimester, and maternal pre-pregnancy weight was self-reported. All analyses were performed using SPSS 10.0. Results showed that pre-pregnancy BMI was the strongest predictor of pregnancy blood pressure. This association was evident for pre-pregnancy BMI independently (p<0.001), and it also persisted after adjusting for maternal age, education, income, parity, smoking and physical activity (p<0.05). The association between maternal anthropometry during pregnancy and blood pressure was not as strong and was therefore less informative. The study reinforces the role of BMI on SBP and DBP and highlights its importance during prenatal care monitoring. Significant association also emerged between blood pressure in pregnancy and place of residence (mainland vs. island). Women on Dalmatian islands have lower educational level, higher pre-pregnancy BMI and different levels of blood pressure than women from the mainland (namely, higher SBP and lower DBP). Such comparisons between mainland and island populations are valuable, because they can, in the long term, lead to better maternal health care on the islands

Extent of Height Variability Explained by Known Height-Associated Genetic Variants in an Isolated Population of the Adriatic Coast of Croatia

BACKGROUND: Human height is a classical example of a polygenic quantitative trait. Recent large-scale genome-wide association studies (GWAS) have identified more than 200 height-associated loci, though these variants explain only 2∼10% of overall variability of normal height. The objective of this study was to investigate the variance explained by these loci in a relatively isolated population of European descent with limited admixture and homogeneous genetic background from the Adriatic coast of Croatia. METHODOLOGY/PRINCIPAL FINDINGS: In a sample of 1304 individuals from the island population of Hvar, Croatia, we performed genome-wide SNP typing and assessed the variance explained by genetic scores constructed from different panels of height-associated SNPs extracted from five published studies. The combined information of the 180 SNPs reported by Lango Allen el al. explained 7.94% of phenotypic variation in our sample. Genetic scores based on 20~50 SNPs reported by the remaining individual GWA studies explained 3~5% of height variance. These percentages of variance explained were within ranges comparable to the original studies and heterogeneity tests did not detect significant differences in effect size estimates between our study and the original reports, if the estimates were obtained from populations of European descent. CONCLUSIONS/SIGNIFICANCE: We have evaluated the portability of height-associated loci and the overall fitting of estimated effect sizes reported in large cohorts to an isolated population. We found proportions of explained height variability were comparable to multiple reference GWAS in cohorts of European descent. These results indicate similar genetic architecture and comparable effect sizes of height loci among populations of European descent

Finding Missing Heritability in Less Significant Loci and Allelic Heterogeneity: Genetic Variation in Human Height

<div><p>Genome-wide association studies (GWAS) have identified many common variants associated with complex traits in human populations. Thus far, most reported variants have relatively small effects and explain only a small proportion of phenotypic variance, leading to the issues of ‘missing’ heritability and its explanation. Using height as an example, we examined two possible sources of missing heritability: first, variants with smaller effects whose associations with height failed to reach genome-wide significance and second, allelic heterogeneity due to the effects of multiple variants at a single locus. Using a novel analytical approach we examined allelic heterogeneity of height-associated loci selected from SNPs of different significance levels based on the summary data of the GIANT (stage 1) studies. In a sample of 1,304 individuals collected from an island population of the Adriatic coast of Croatia, we assessed the extent of height variance explained by incorporating the effects of less significant height loci and multiple effective SNPs at the same loci. Our results indicate that approximately half of the 118 loci that achieved stringent genome-wide significance (p-value<5×10⁻⁸) showed evidence of allelic heterogeneity. Additionally, including less significant loci (i.e., p-value<5×10⁻⁴) and accounting for effects of allelic heterogeneity substantially improved the variance explained in height.</p> </div

Two example loci with allelic heterogeneity.

<p>(A) The GHSR locus included a secondary signal (rs7652177) after accounting for the primary signal (rs572169). (B) The HMGA1 locus had a more complicated pattern of allelic heterogeneity; with significant secondary, tertiary and quaternary signals after multiple rounds of conditioning (only the first round of conditioning is shown). The secondary p-values (bottom plots) conditioning on the primary SNP were estimated from GIANT summary data using the analytical approach described in main text.</p

Numbers of significant loci and conditional signals.

&<p>Lowering the significance level substantially increased the number (or the density) of significant SNPs used in clustering height loci. Therefore, shorter context lengths were arbitrarily selected in defining “physical adjacency” when relaxed significance levels were used, which might artificially reduce the length of significant loci and hence the chance of allelic heterogeneity in these loci clustered at lower significance level.</p

Additional fraction of variance explained could be obtained by including less significant SNPs and secondary/tertiary SNPs.

<p>Additional fraction of variance explained could be obtained by including less significant SNPs and secondary/tertiary SNPs.</p

Testing the Institute of Medicine (IOM) recommendations on maternal reproductive health and associated neonatal characteristics in a transitional, Mediterranean population

Background:  High pre-pregnancy body mass index (BMI) and excessive gestational weight gain (GWG) are significant risk factors for maternal and neonatal health.  Aim:  To assess pre-pregnancy BMI and GWG during pregnancy and their association with different maternal and neonatal characteristics in the transitional Mediterranean population from the Eastern Adriatic islands.  Subjects and methods:  Two hundred and sixty-two mother–child dyads from the CRoatian Islands’ Birth Cohort Study (CRIBS) were included in the study. Chi-square test, ANOVA, and regression analysis were used to test the association between selected characteristics. Results: In total, 22% of women entered pregnancy as overweight/obese and 46.6% had excessive GWG. Pre-pregnancy overweight and obesity were significantly associated with elevated triglycerides uric acid levels, and decreased HDL cholesterol in pregnancy. Excessive GWG was associated with elevated fibrinogen and lipoprotein A levels. Women with high pre-pregnancy BMI and GWG values were more likely to give birth to babies that were large for gestational age (LGA), additionally confirmed in the multiple logistic regression model.  Conclusion:  High maternal pre-pregnancy BMI and excessive GWG were both significantly associated with deviated biochemical parameters and neonatal size. More careful monitoring of maternal nutritional status can lead to better pre- and perinatal maternal healthcare.</p

Replication of genetic variants from genome-wide association studies with metabolic traits in an island population of the Adriatic coast of Croatia

Twenty-two single-nucleotide polymorphisms (SNPs) in 10 gene regions previously identified in obesity and type 2 diabetes (T2D) genome-wide association studies (GWAS) were evaluated for association with metabolic traits in a sample from an island population of European descent. We performed a population-based study using 18 anthropometric and biochemical traits considered as continuous variables in a sample of 843 unrelated subjects (360 men and 483 women) aged 18–80 years old from the island of Hvar on the eastern Adriatic coast of Croatia. All eight GWAS SNPs in FTO were significantly associated with weight, body mass index, waist circumference and hip circumference; 20 of the 32 nominal P-values remained significant after permutation testing for multiple corrections. The strongest associations were found between the two TCF7L2 GWAS SNPs with fasting plasma glucose and HbA1c levels, all four P-values remained significant after permutation tests. Nominally significant associations were found between several SNPs and other metabolic traits; however, the significance did not hold after permutation tests. Although the sample size was modest, our study strongly replicated the association of FTO variants with obesity-related measures and TCF7L2 variants with T2D-related traits. The estimated effect sizes of these variants were larger or comparable to published studies. This is likely attributable to the homogenous genetic background of the relatively isolated study population