Association of maternal prenatal smoking GFI1-locus and cardio-metabolic phenotypes in 18,212 adults

© 2018 The Authors Background: DNA methylation at the GFI1-locus has been repeatedly associated with exposure to smoking from the foetal period onwards. We explored whether DNA methylation may be a mechanism that links exposure to maternal prenatal smoking with offspring's adult cardio-metabolic health. Methods: We meta-analysed the association between DNA methylation at GFI1-locus with maternal prenatal smoking, adult own smoking, and cardio-metabolic phenotypes in 22 population-based studies from Europe, Australia, and USA (n = 18,212). DNA methylation at the GFI1-locus was measured in whole-blood. Multivariable regression models were fitted to examine its association with exposure to prenatal and own adult smoking. DNA methylation levels were analysed in relation to body mass index (BMI), waist circumference (WC), fasting glucose (FG), high-density lipoprotein cholesterol (HDL—C), triglycerides (TG), diastolic, and systolic blood pressure (BP). Findings: Lower DNA methylation at three out of eight GFI1-CpGs was associated with exposure to maternal prenatal smoking, whereas, all eight CpGs were associated with adult own smoking. Lower DNA methylation at cg14179389, the strongest maternal prenatal smoking locus, was associated with increased WC and BP when adjusted for sex, age, and adult smoking with Bonferroni-corrected P < 0·012. In contrast, lower DNA methylation at cg09935388, the strongest adult own smoking locus, was associated with decreased BMI, WC, and BP (adjusted 1 × 10-7 < P < 0.01). Similarly, lower DNA methylation at cg12876356, cg18316974, cg09662411, and cg18146737 was associated with decreased BMI and WC (5 × 10-8 < P < 0.001). Lower DNA methylation at all the CpGs was consistently associated with higher TG levels. Interpretation: Epigenetic changes at the GFI1 were linked to smoking exposure in-utero/in-adulthood and robustly associated with cardio-metabolic risk factors. Fund: European Union's Horizon 2020 research and innovation programme under grant agreement no. 633595 DynaHEALTH

Constrained multivariate association with longitudinal phenotypes

The incorporation of longitudinal data into genetic epidemiological studies has the potential to provide valuable information regarding the effect of time on complex disease etiology. Yet, the majority of research focuses on variables collected from a single time point. This aim of this study was to test for main effects on a quantitative trait across time points using a constrained maximum-likelihood measured genotype approach. This method simultaneously accounts for all repeat measurements of a phenotype in families. We applied this method to systolic blood pressure (SBP) measurements from three time points using the Genetic Analysis Workshop 19 (GAW19) whole-genome sequence family simulated data set and 200 simulated replicates. Data consisted of 849 individuals from 20 extended Mexican American pedigrees. Comparisons were made among 3 statistical approaches: (a) constrained, where the effect of a variant or gene region on the mean trait value was constrained to be equal across all measurements; (b) unconstrained, where the variant or gene region effect was estimated separately for each time point; and (c) the average SBP measurement from three time points. These approaches were run for nine genetic variants with known effect sizes (\u3e0.001) for SBP variability and a known gene-centric kernel (MAP4)-based test under the GAW19 simulation model across 200 replicates

Patterns of DNA Methlyation across the Leptin Core Promoter in Four Diverse Asian and North American Populations

DNA methylation is the most widely studied of epigenetic mechanisms, with environmental effects recorded through patterned attachments of methyl groups along the DNA that are capable of modifying gene expression without altering the DNA sequencing. The degree to which these patterns of DNA methylation are heritable, the expected range of normality across populations, and the phenotypic relevance of pattern variation remain unclear. Genes regulating metabolic pathways appear to be vulnerable to ongoing nutritional programming over the life course, as dietary nutrients are significant environmental determinants of DNA methylation, supplying both the methyl groups and energy to generate the methylation process. Here we examine methylation patterns along a region of the metabolic gene leptin (LEP). LEP's putative functions include regulation of energy homeostasis, with its signals affecting energy intake and expenditure, adipogenesis and energy storage, lipid and glucose metabolism, bone metabolism, and reproductive endocrine function. A pattern of differential methylation across CpG sites of the LEP core promoter has been previously identified; however, any consistency of pattern or its phenotypic significance is not fully elucidated among populations. Using DNA extracted from unfractionated white blood cells of peripheral blood samples, our pilot study, divided into two parts, examined the significance of variation in DNA methylation patterns along the leptin core promoter in four populations (phase 1) and used biomarkers reflecting leptin's functional process in two of those populations, western Buryat of Siberia and the Mennonite of central Kansas, to investigate the relevance of the ethnic variation identified in the DNA methylation (phase 2). LEP's core promoter region contains both the binding site for C/EBPα (CCAAT/enhancer binding protein alpha), which tempers the final step in adipocyte maturity and capacity to synthesize leptin, and the TATA motif controlling leptin synthesis. Previous studies report that increased methylation in this region is correlated to decreased gene expression, suggesting tissue-specific methylation variation at this region (Melzner et al. 2002). We hypothesized that evidence of nutritional epigenetic programming would be identified through variation in patterns of DNA methylation and that functional relevance of that variation among populations would be identified through biomarkers that reflect leptin's metabolic signals: serum leptin levels, lipoproteins of the lipid transport system, and anthropometric measures. In phase 1, our combined analyses of 313 individuals documented a distinct and consistent overall pattern of differential DNA methylation across seven CpG sites of LEP core promoter in all ethnicities and both sexes. This pattern replicates those identified in previous studies, suggesting a conserved core promoter region across populations. Phase 2 analyses of two of the four populations (n = 239), correlating methylation at the C/EBPα transcription binding site (TBS) with metabolic and anthropometric biomarkers reflecting LEP roles, showed that stature, which reflects bone growth and remodeling, was significantly and inversely correlated with the percentage of DNA methylation at this site in both sexes. We suggest that variation in DNA methylation along the LEP core promoter plays a substantial role in energy signals affecting both adipogenesis and bone metabolism

Mitochondrial DNA Diversity in Mennonite Communities from the Midwestern United States

We examined mitochondrial DNA (mtDNA) variation in six Mennonite communities from Kansas (Goessel, Lone Tree, Garden View, Meridian, and Garden City) and Nebraska (Henderson) to determine their genetic structure and its relationship to population history. Mitochondrial DNA haplogroup and haplotype information were obtained from blood samples from 118 individuals. Molecular genetic variation was analyzed using diversity measures, neutrality test statistics, spatial analysis of molecular variance (SAMOVA), and multidimensional scaling plots. The Mennonite samples exhibited eight western European mtDNA haplogroups: H, HVO, I, J, K, T, U, and X. Comparable to other populations of European descent, haplogroup H was the most frequent in all six communities and ranged from 35% in Lone Tree to 75% in Old Order Mennonites from Garden City. Fifty-eight different mtDNA haplotypes were found in these groups with only one shared among all six populations. Haplotype diversities varied from 0.81 in Goessel to 0.96 in Henderson and Garden View. Multivariate statistical analysis of these populations indicates that these Anabaptist communities formed new congregations by fissioning along familial lines. Population subdivision of these communities into congregations supports previously documented patterns of fission-fusion. These haploid molecular data provide a more accurate reflection of biological relationships between midwestern Mennonite communities than evidence based on classical genetic markers

Large scale mitochondrial sequencing in Mexican Americans suggests a reappraisal of Native American origins

<p>Abstract</p> <p>Background</p> <p>The Asian origin of Native Americans is largely accepted. However uncertainties persist regarding the source population(s) within Asia, the divergence and arrival time(s) of the founder groups, the number of expansion events, and migration routes into the New World. mtDNA data, presented over the past two decades, have been used to suggest a single-migration model for which the Beringian land mass plays an important role.</p> <p>Results</p> <p>In our analysis of 568 mitochondrial genomes, the coalescent age estimates of shared roots between Native American and Siberian-Asian lineages, calculated using two different mutation rates, are A4 (27.5 ± 6.8 kya/22.7 ± 7.4 kya), C1 (21.4 ± 2.7 kya/16.4 ± 1.5 kya), C4 (21.0 ± 4.6 kya/20.0 ± 6.4 kya), and D4e1 (24.1 ± 9.0 kya/17.9 ± 10.0 kya). The coalescent age estimates of pan-American haplogroups calculated using the same two mutation rates (A2:19.5 ± 1.3 kya/16.1 ± 1.5 kya, B2:20.8 ± 2.0 kya/18.1 ± 2.4 kya, C1:21.4 ± 2.7 kya/16.4 ± 1.5 kya and D1:17.2 ± 2.0 kya/14.9 ± 2.2 kya) and estimates of population expansions within America (~21-16 kya), support the pre-Clovis occupation of the New World. The phylogeography of sublineages within American haplogroups A2, B2, D1 and the C1b, C1c andC1d subhaplogroups of C1 are complex and largely specific to geographical North, Central and South America. However some sub-branches (B2b, C1b, C1c, C1d and D1f) already existed in American founder haplogroups before expansion into the America.</p> <p>Conclusions</p> <p>Our results suggest that Native American founders diverged from their Siberian-Asian progenitors sometime during the last glacial maximum (LGM) and expanded into America soon after the LGM peak (~20-16 kya). The phylogeography of haplogroup C1 suggest that this American founder haplogroup differentiated in Siberia-Asia. The situation is less clear for haplogroup B2, however haplogroups A2 and D1 may have differentiated soon after the Native American founders divergence. A moderate population bottle neck in American founder populations just before the expansion most plausibly resulted in few founder types in America. The similar estimates of the diversity indices and Bayesian skyline analysis in North America, Central America and South America suggest almost simultaneous (~ 2.0 ky from South to North America) colonization of these geographical regions with rapid population expansion differentiating into more or less regional branches across the pan-American haplogroups.</p

The antihypertensive MTHFR gene polymorphism rs17367504-G is a possible novel protective locus for preeclampsia

Objective: Preeclampsia is a complex heterogeneous disease commonly defined by new-onset hypertension and proteinuria in pregnancy. Women experiencing preeclampsia have increased risk for cardiovascular diseases (CVD) later in life. Preeclampsia and CVD share risk factors and pathophysiologic mechanisms, including dysregulated inflammation and raised blood pressure. Despite commonalities, little is known about the contribution of shared genes (pleiotropy) to these diseases. This study aimed to investigate whether genetic risk factors for hypertension or inflammation are pleiotropic by also being associated with preeclampsia. Methods: We genotyped 122 single nucleotide polymorphisms (SNPs) in women with preeclampsia (n = 1006) and nonpreeclamptic controls (n = 816) from the Norwegian HUNT Study. SNPs were chosen on the basis of previously reported associations with either nongestational hypertension or inflammation in genome-wide association studies. The SNPs were tested for association with preeclampsia in a multiple logistic regression model. Results: The minor (G) allele of the intronic SNP rs17367504 in the gene methylenetetrahydrofolate reductase (MTHFR) was associated with a protective effect on preeclampsia (odds ratio 0.65, 95% confidence interval 0.53–0.80) in the Norwegian cohort. This association did not replicate in an Australian preeclampsia case–control cohort (P = 0.68, odds ratio 1.05, 95% confidence interval 0.83–1.32, minor allele frequency = 0.15). Conclusion: MTHFR is important for regulating transmethylation processes and is involved in regulation of folate metabolism. The G allele of rs17367504 has previously been shown to protect against nongestational hypertension. Our study suggests a novel association between this allele and reduced risk for preeclampsia. This is the first study associating the minor (G) allele of a SNP within the MTHFR gene with a protective effect on preeclampsia, and in doing so identifying a possible pleiotropic protective effect on preeclampsia and hypertension

Epigenetics, heritability and longitudinal analysis

Background Longitudinal data and repeated measurements in epigenome-wide association studies (EWAS) provide a rich resource for understanding epigenetics. We summarize 7 analytical approaches to the GAW20 data sets that addressed challenges and potential applications of phenotypic and epigenetic data. All contributions used the GAW20 real data set and employed either linear mixed effect (LME) models or marginal models through generalized estimating equations (GEE). These contributions were subdivided into 3 categories: (a) quality control (QC) methods for DNA methylation data; (b) heritability estimates pretreatment and posttreatment with fenofibrate; and (c) impact of drug response pretreatment and posttreatment with fenofibrate on DNA methylation and blood lipids. Results Two contributions addressed QC and identified large statistical differences with pretreatment and posttreatment DNA methylation, possibly a result of batch effects. Two contributions compared epigenome-wide heritability estimates pretreatment and posttreatment, with one employing a Bayesian LME and the other using a variance-component LME. Density curves comparing these studies indicated these heritability estimates were similar. Another contribution used a variance-component LME to depict the proportion of heritability resulting from a genetic and shared environment. By including environmental exposures as random effects, the authors found heritability estimates became more stable but not significantly different. Two contributions investigated treatment response. One estimated drug-associated methylation effects on triglyceride levels as the response, and identified 11 significant cytosine-phosphate-guanine (CpG) sites with or without adjusting for high-density lipoprotein. The second contribution performed weighted gene coexpression network analysis and identified 6 significant modules of at least 30 CpG sites, including 3 modules with topological differences pretreatment and posttreatment. Conclusions Four conclusions from this GAW20 working group are: (a) QC measures are an important consideration for EWAS studies that are investigating multiple time points or repeated measurements; (b) application of heritability estimates between time points for individual CpG sites is a useful QC measure for DNA methylation studies; (c) drug intervention demonstrated strong epigenome-wide DNA methylation patterns across the 2 time points; and (d) new statistical methods are required to account for the environmental contributions of DNA methylation across time. These contributions demonstrate numerous opportunities exist for the analysis of longitudinal data in future epigenetic studies

Whole genome sequencing of 91 multiplex schizophrenia families reveals increased burden of rare, exonic copy number variation in schizophrenia probands and genetic heterogeneity

The importance of genomic copy number variants (CNVs) has long been recognized in the etiology of neurodevelopmental diseases. We report here the results from the CNV analysis of whole-genome sequences from 91 multiplex schizophrenia families. Employing four algorithms (CNVnator, Cn.mops, DELLY and LUMPY) to identify CNVs, we find 1231 rare deletions and 287 rare duplications in 300 individuals (77 with schizophrenia (SZ), 32 with schizoaffective disorder (SAD), 82 with another neuropsychiatric diagnosis and 109 unaffected). The size of the CNVs ranges from a few hundred base-pairs to about 1.3Mb. The total burden of CNVs does not differ significantly between affected (SZ and SAD) and unaffected individuals. Parent-to-child transmission rate for rare CNVs affecting exonic regions is significantly higher for affected (SZ and SAD) probands as compared to their siblings, but rates for all CNVs is not. We observe heterogeneity between families in terms of genes involved in CNVs, and find several CNVs involving genes previously implicated in either schizophrenia or other neuropsychiatric disorders