Biology subjects

Jacobsson, B.

Publications and source records attributed to Jacobsson, B..

7 recordsLinked to original sources

bioRxiv2020

Haplotype-based heritability estimations reveal gestational duration as a maternal trait and fetal size measurements at birth as fetal traits in human pregnancy

AbstractGenotype-based approaches for the estimation of SNP-based narrow-sense heritability [Formula] have limited utility in pregnancy-related outcomes due to confounding by the shared alleles between mother and child. Here, we propose a haplotype-based approach to estimate the genetic variance attributable to three haplotypes - maternal transmitted [Formula], maternal non-transmitted [Formula] and paternal transmitted [Formula] in mother-child pairs. We show through extensive simulations that our haplotype-based approach outperforms the conventional and contemporary approaches for resolving the contribution of maternal and fetal effects, particularly when m1 and p1 have different effects in the offspring. We apply this approach to estimate the explicit and relative maternal-fetal genetic contribution to the phenotypic variance of gestational duration and gestational duration adjusted fetal size measurements at birth in 10,375 mother-child pairs. The results reveal that variance of gestational duration is mainly attributable to m1 and m2 ([Formula]= 17.3%, S. E. = 5.2%; [Formula] = 12.2%, S. E. = 5.2%; [Formula] = 0.0%, S. E. = 5.0%). In contrast, variance of fetal size measurements at birth are mainly attributable to m1 and p1 ([Formula] = 18.6 - 36.4%, [Formula] = 0.0 - 5.2% and [Formula] = 4.4 - 13.6%). Our results suggest that gestational duration and fetal size measurements are primarily genetically determined by the maternal and fetal genomes, respectively. In addition, a greater contribution of m1 as compared to m2 and p1 [Formula] to birth length and head circumference suggests a substantial influence of correlated maternal-fetal genetic effects on these traits. Our newly developed approach provides a direct and robust alternative for resolving explicit maternal and fetal genetic contributions to the phenotypic variance of pregnancy-related outcomes.

genetics↗

bioRxiv2020

Transcriptome and regulatory maps of decidua-derived stromal cells inform gene discovery in preterm birth

While a genetic component of preterm birth (PTB) has long been recognized and recently mapped by genome-wide association studies (GWAS), the molecular determinants underlying PTB remain elusive. This stems in part from an incomplete availability of comprehensive functional genomic annotations in human cell types relevant to pregnancy and PTB. Here, we generated extensive transcriptional and chromatin annotations of cultured primary decidua-derived mesenchymal stromal/stem cells (MSCs) and in vitro differentiated decidual stromal cells (DSCs) and developed a computational framework to integrate these functional annotations with results from a GWAS of gestational duration in 56,384 women. This resulted in a significant enrichment of heritability estimates in functional noncoding regions in stromal cells, as well as in the discovery of additional loci associated with gestational duration and target genes of associated loci. Our strategy illustrates how systematic functional annotations in pregnancy-relevant cell types aid in the experimental follow-up of GWAS for PTB and, likely, other pregnancy-related conditions.

genomics↗

bioRxiv2020

Wavelet Screening: a novel approach to analysing GWAS data

We present here an alternative method for genome-wide association study (GWAS) that is more powerful than traditional GWAS methods for locus detection. Single-variant GWAS methods incur a substantial multiple-testing burden because of the vast number of single nucleotide polymorphisms (SNPs) being tested simultaneously. Furthermore, these methods do not consider the functional genetic effect on the outcome because they ignore more complex joint effects of nearby SNPs within a region. By contrast, our method reduces the number of tests to be performed by screening the entire genome for associations using a sliding-window approach based on wavelets. In this context, a sequence of SNPs represents a genetic signal, and for each screened region, we transform the genetic signal into the wavelet space. The null and alternative hypotheses are modelled using the posterior distribution of the wavelet coefficients. We enhance our decision procedure by using additional information from the regression coefficients and by taking advantage of the pyramidal structure of wavelets. When faced with more complex signals than single-SNP associations, we show through simulations that Wavelet Screening provides a substantial gain in power compared to both the traditional GWAS modelling as well as another popular regional-based association test called SNP-set (Sequence) Kernel Association Test (SKAT). To demonstrate feasibility, we re-analysed data from the large Norwegian HARVEST cohort.

bioinformatics↗

bioRxiv2019

Palmitate induces apoptotic cell death and inflammasome activation in human placental macrophages

IntroductionThere is an increasing prevalence of non-communicable diseases worldwide. Metabolic diseases such as obesity and gestational diabetes mellitus (GDM) increasingly affect women during pregnancy, which can harm pregnancy outcomes and the long-term health and wellbeing of exposed offspring. Both obesity and GDM have been associated with proinflammatory effects within the placenta, the critical organ governing fetal development.\n\nMethodsThe purpose of these studies was to model, in vitro, the effects of metabolic stress (high levels of glucose, insulin and saturated lipids) on placental macrophage biology, since these cells are the primary innate immune phagocyte within the placenta with roles in governing maternofetal immune tolerance and antimicrobial host defense. Macrophages were isolated from the villous core of term, human placentae delivered through nonlaboring, elective Cesarean sections and exposed to combinations of elevated glucose (30 mM), insulin (10 nM) and the saturated lipid palmitic acid (palmitate, 0.4 mM).\n\nResultsWe found that palmitate alone induced the activation of the nucleotide-binding oligomerization domain-like receptor (NLR) Family Pyrin Domain Containing 3 (NLRP3) inflammasome in placental macrophages, which was associated with increased interleukin 1 beta release and an increase in apoptotic cell death. Glucose and insulin neither provoked these effects nor augmented the impact of palmitate itself.\n\nDiscussionOur findings confirm an impact of saturated fat on placental macrophage immune activation and could be relevant to the impact of metabolic stress in vivo.

immunology↗

bioRxiv2019

Haplotype genetic score analysis in 10,734 mother/infant pairs reveals complex maternal and fetal genetic effects underlying the associations between maternal phenotypes, birth outcomes and adult phenotypes

Many maternal traits are associated with a neonates gestational duration, birth weight and birth length. These birth outcomes are subsequently associated with late onset health conditions. Based on 10,734 mother/infant duos of European ancestry, we constructed haplotype genetic scores to dissect the maternal and fetal genetic effects underlying these observed associations. We showed that maternal height and fetal growth jointly affect the duration of gestation - maternal height positively influences the gestational duration, while faster fetal growth reduces gestational duration. Fetal growth is influenced by both maternal and fetal effects and can reciprocally influence maternal phenotypes: tall maternal stature and higher blood glucose causally increase birth size; in the fetus, the height and metabolic risk increasing alleles can lead to increased and decreased birth size respectively; birth weight-raising alleles in fetus may reduce gestational duration and increase maternal blood pressure. These maternal and fetal genetic effects can largely explain the observed associations between the studied maternal phenotypes and birth outcomes as well as the life-course associations between these birth outcomes and adult phenotypes.

genetics↗

bioRxiv2019

The genetic architecture of sporadic and recurrent miscarriage

Miscarriage is a common complex trait that affects 10-25% of clinically confirmed pregnancies1,2. Here we present the first large-scale genetic association analyses with 69,118 cases from five different ancestries for sporadic miscarriage and 750 cases of European ancestry for recurrent miscarriage, and up to 359,469 female controls. We identify one genome-wide significant association on chromosome 13 (rs146350366, minor allele frequency (MAF) 1.2%, Pmeta=3.2x -8 (CI) 1.2-1.6) for sporadic miscarriage in our European ancestry meta-analysis (50,060 cases and 174,109 controls), located near FGF9 involved in pregnancy maintenance3 and progesterone production4. Additionally, we identified three genome-wide significant associations for recurrent miscarriage, including a signal on chromosome 9 (rs7859844, MAF=6.4%, Pmeta=1.3x -8 in controlling extravillous trophoblast motility5. We further investigate the genetic architecture of miscarriage with biobank-scale Mendelian randomization, heritability and, genetic correlation analyses. Our results implicate that miscarriage etiopathogenesis is partly driven by genetic variation related to gonadotropin regulation, placental biology and progesterone production.

genetics↗

bioRxiv2018

Genome-wide association study reveals a dynamic role of common genetic variation in infant and early childhood growth

Infant and childhood growth are dynamic processes characterized by drastic changes in fat mass and body mass index (BMI) at distinct developmental stages. To elucidate how genetic variation influences these processes, we performed the first genome-wide association study (GWAS) of BMI measurements at 12 time points from birth to eight years of age (9,286 children, 74,105 measurements) in the Norwegian Mother and Child Cohort Study (MoBa) with replication in 5,235 children (41,502 measurements). We identified five loci associated with BMI at distinct developmental stages with different patterns of association. Notably, we identified a novel transient effect in the leptin receptor (LEPR) locus, with no effect at birth, increasing effect on BMI in infancy, peaking at 6-12 months (rs2767486, P6m = 2.0 x 10-21, {beta}6m = 0.16) and little effect after age five. A similar transient effect was found near the leptin gene (LEP), peaking at 1.5 years of age (rs10487505, P1.5y = 1.3 x 10-8, {beta}1.5y = 0.079). Both signals are protein quantitative trait loci (pQTLs) for soluble LEPR and LEP in plasma in adults and independent from signals associated with other adult traits mapped to the respective genes, suggesting novel key roles of common variation in the leptin signaling pathway for healthy infant growth. Hence, our longitudinal analysis uncovers a complex and dynamic influence of common variation on BMI during infant and early childhood growth, dominated by the LEP-LEPR axis in infancy.

genetics↗