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A Genome-wide Association Analysis in Four Populations Reveals Strong Genetic Heterogeneity For Birth Weight.

ABSTRACT: Low or high birth weight is one of the main causes for neonatal morbidity and mortality. They are also associated with adulthood chronic illness. Birth weight is a complex trait which is affected by baby's genes, maternal environments as well as the complex interactions between them. To understand the genetic basis of birth weight, we reanalyzed a genome-wide association study data set which consists of four populations, namely Thai, Afro-Caribbean, European, and Hispanic population with regular linear models. In addition to fit the data with parametric linear models, we fitted the data with a nonparametric varying-coefficient model to identify variants that are nonlinearly modulated by mother's condition to affect birth weight. For this purpose, we used baby's cord glucose level as the mother's environmental variable. At the 10-5 genome-wide threshold, we identified 33 SNP variants in the Thai population, 26 SNPs in the Afro-Caribbean population, 18 SNPs in the European population, and 7 SNPs in the Hispanic population. Some of the variants are significantly modulated by baby's cord glucose level either linearly or nonlinearly, implying potential interactions between baby's gene and mother's glucose level to affect baby's birth weight. There is no overlap between variants identified in the four populations, indicating strong genetic heterogeneity of birth weight between the four ethnic groups. The findings of this study provide insights into the genetic basis of birth weight and reveal its genetic heterogeneity.

SUBMITTER: Luo T

PROVIDER: S-EPMC5320544 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

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A Genome-wide Association Analysis in Four Populations Reveals Strong Genetic Heterogeneity For Birth Weight.

Luo Tiane T Liu Xu X Cui Yuehua Y

Current genomics 20161001 5

Low or high birth weight is one of the main causes for neonatal morbidity and mortality. They are also associated with adulthood chronic illness. Birth weight is a complex trait which is affected by baby's genes, maternal environments as well as the complex interactions between them. To understand the genetic basis of birth weight, we reanalyzed a genome-wide association study data set which consists of four populations, namely Thai, Afro-Caribbean, European, and Hispanic population with regular ...[more]

PMID: 28479870

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Project description:ObjectiveThe Sjögren's International Collaborative Clinical Alliance (SICCA) is an international data registry and biorepository derived from a multisite observational study of participants in whom genotyping was performed on the Omni2.5M platform and who had undergone deep phenotyping using common protocol-directed methods. The aim of this study was to examine the genetic etiology of Sjögren's syndrome (SS) across ancestry and disease subsets.MethodsWe performed genome-wide association study analyses using SICCA subjects and external controls obtained from dbGaP data sets, one using all participants (1,405 cases, 1,622 SICCA controls, and 3,125 external controls), one using European participants (585, 966, and 580, respectively), and one using Asian participants (460, 224, and 901, respectively) with ancestry adjustments via principal components analyses. We also investigated whether subphenotype distributions differ by ethnicity, and whether this contributes to the heterogeneity of genetic associations.ResultsWe observed significant associations in established regions of the major histocompatibility complex (MHC), IRF5, and STAT4 (P = 3 × 10-42 , P = 3 × 10-14 , and P = 9 × 10-10 , respectively), and several novel suggestive regions (those with 2 or more associations at P < 1 × 10-5 ). Two regions have been previously implicated in autoimmune disease: KLRG1 (P = 6 × 10-7 [Asian cluster]) and SH2D2A (P = 2 × 10-6 [all participants]). We observed striking differences between the associations in Europeans and Asians, with high heterogeneity especially in the MHC; representative single-nucleotide polymorphisms from established and suggestive regions had highly significant differences in the allele frequencies in the study populations. We showed that SSA/SSB autoantibody production and the labial salivary gland focus score criteria were associated with the first worldwide principal component, indicative of higher non-European ancestry (P = 4 × 10-15 and P = 4 × 10-5 , respectively), but that subphenotype differences did not explain most of the ancestry differences in genetic associations.ConclusionGenetic associations with SS differ markedly according to ancestry; however, this is not explained by differences in subphenotypes.

Project description:ObjectivePrior studies have shown that there is an inverse association between birth weight and stroke in adulthood; however, whether such association is causal remains yet known and those studies cannot distinguish between the direct fetal effect and the indirect maternal effect. The aim of the study is to untangle such relationship using novel statistical genetic approaches.MethodsWe first utilized linkage disequilibrium score regression (LDSC) and Genetic analysis incorporating Pleiotropy and Annotation (GPA) to estimate the overall genetic correlation between birth weight and stroke. Then, with a set of valid birth-weight instruments which had adjusted fetal and maternal effects, we performed a two-sample Mendelian randomization (MR) to evaluate its causal effect on stroke based summary statistics from large scale genome-wide association study (GWAS) (n = 264,498 for birth weight and 446,696 for stroke). We further validated the MR results with extensive sensitivity analyses.ResultsBoth LDSC and GPA demonstrated significant evidence of shared maternal genetic foundation between birth weight and stroke, with the genetic correlation estimated to -0.176. However, no fetal genetic correlation between birth weight and stroke was detected. Furthermore, the inverse variance weighted MR demonstrated the maternally causal effect of birth weight on stroke was 1.12 (95% confidence interval [CI] 1.00-1.27). The maternal ORs of birth weight on three subtypes of stroke including cardioembolic stroke (CES), large artery stroke (LAS) and small vessel stroke (SVS) were 1.16 (95% CI 0.93-1.43), 1.50 (95% CI 1.14-1.96) and 1.47 (95% CI 1.15-1.87), respectively. In contrast, no fetal causal associations were found between birth weight and stroke or the subtypes. Those results were robust against extensive sensitivity analyses, with Egger regression ruling out the possibility of pleiotropy and multivariable MR excluding the likelihood of confounding or mediation effects of other risk factors of stroke.ConclusionThis study provides empirically supportive evidence on the fetal developmental origins of stroke and its subtypes. However, further investigation is warranted to understand the pathophysiological role of low birth weight in developing stroke.

Project description:BackgroundMarine fish populations are often characterized by high levels of gene flow and correspondingly low genetic divergence. This presents a challenge to define management units. Goldsinny wrasse (Ctenolabrus rupestris) is a heavily exploited species due to its importance as a cleaner-fish in commercial salmonid aquaculture. However, at the present, the population genetic structure of this species is still largely unresolved. Here, full-genome sequencing was used to produce the first genomic reference for this species, to study population-genomic divergence among four geographically distinct populations, and, to identify informative SNP markers for future studies.ResultsAfter construction of a de novo assembly, the genome was estimated to be highly polymorphic and of ~600Mbp in size. 33,235 SNPs were thereafter selected to assess genomic diversity and differentiation among four populations collected from Scandinavia, Scotland, and Spain. Global FST among these populations was 0.015-0.092. Approximately 4% of the investigated loci were identified as putative global outliers, and ~ 1% within Scandinavia. SNPs showing large divergence (FST > 0.15) were picked as candidate diagnostic markers for population assignment. One hundred seventy-three of the most diagnostic SNPs between the two Scandinavian populations were validated by genotyping 47 individuals from each end of the species' Scandinavian distribution range. Sixty-nine of these SNPs were significantly (p < 0.05) differentiated (mean FST_173_loci = 0.065, FST_69_loci = 0.140). Using these validated SNPs, individuals were assigned with high probability (≥ 94%) to their populations of origin.ConclusionsGoldsinny wrasse displays a highly polymorphic genome, and substantial population genomic structure. Diversifying selection likely affects population structuring globally and within Scandinavia. The diagnostic loci identified now provide a promising and cost-efficient tool to investigate goldsinny wrasse populations further.

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A Genome-wide Association Analysis in Four Populations Reveals Strong Genetic Heterogeneity For Birth Weight.

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A Genome-wide Association Analysis in Four Populations Reveals Strong Genetic Heterogeneity For Birth Weight.

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