Association of height and pubertal timing with lipoprotein subclass profile: exploring the role of genetic and environmental effects

Objectives: Little is known about the relationship between growth and lipoprotein profile. We aimed to analyze common genetic and environmental factors in the association of height from late childhood to adulthood and pubertal timing with serum lipid and lipoprotein subclass profile. Methods: A longitudinal cohort of Finnish twin pairs (FinnTwin12) was analysed using self-reported height at 11-12, 14, 17 years and measured stature at adult age (21-24 years). Data were available for 719 individual twins including 298 complete pairs. Serum lipids and lipoprotein subclasses were measured by proton nuclear magnetic resonance spectroscopy. Multivariate variance component models for twin data were fitted. Cholesky decomposition was used to partition the phenotypic covariation among traits into additive genetic and unique environmental correlations. Results: In men, the strongest associations for both adult height and puberty were observed with total cholesterol, low-density lipoprotein cholesterol, intermediate-density lipoprotein cholesterol and low-density lipoprotein particle subclasses (max. r = -0.19). In women, the magnitude of the correlations was weaker (max. r = -0.13). Few associations were detected between height during adolescence and adult lipid profile. Early onset of puberty was related to an adverse lipid profile, but delayed pubertal development in girls was associated with an unfavorable profile, as well. All associations were mediated mainly by additive genetic factors, but unique environmental effects cannot be disregarded. Conclusions: Early puberty and shorter adult height relate to higher concentrations of atherogenic lipids and lipoprotein particles in early adulthood. Common genetic effects behind these phenotypes substantially contribute to the observed associations

Abdominal obesity and circulating metabolites : A twin study approach

Objective. To investigate how obesity, insulin resistance and low-grade inflammation link to circulating metabolites, and whether the connections are due to genetic or environmental factors. Subjects and methods. Circulating serum metabolites were determined by proton NMR spectroscopy. Data from 1368 (531 monozygotic (MZ) and 837 dizygotic (DZ)) twins were used for bivariate twin modeling to derive the genetic (r(g)) and environmental (re) correlations between waist circumference (WC) and serum metabolites. Detailed examination of the associations between fat distribution (DEXA) and metabolic health (HOMA-IR, CRP) was performed among 286 twins including 33 BMI-discordant MZ pairs (intrapair BMI difference >= 3 kg/m(2)). Results. Fat, especially in the abdominal area (i.e. WC, android fat % and android to gynoid fat ratio), together with HOMA-IR and CRP correlated significantly with an atherogenic lipoprotein profile, higher levels of branched-chain (BCAA) and aromatic amino acids, higher levels of glycoprotein, and a more saturated fatty acid profile. In contrast, a higher proportion of gynoid to total fat associated with a favorable metabolite profile. There was a significant genetic overlap between WC and several metabolites, most strongly with phenylalanine (r(g) = 0.40), glycoprotein (r(g) = 0.37), serum triglycerides (r(g) = 0.36), BCAAs (r(g) = 0.30-0.40), HDL particle diameter (r(g) = -0.33) and HDL cholesterol (r(g) = -0.30). The effect of acquired obesity within the discordant MZ pairs was particularly strong for atherogenic lipoproteins. Conclusions. A wide range of unfavorable alterations in the serum metabolome was associated with abdominal obesity, insulin resistance and low-grade inflammation. Twin modeling and obesity-discordant twin analysis suggest that these associations are partly explained by shared genes but also reflect mechanisms independent of genetic liability. (C) 2015 Elsevier Inc. All rights reserved.Peer reviewe

Metabolic profiling of fatty liver in young and middle-aged adults : Cross-sectional and prospective analyses of the Young Finns Study

Nonalcoholic fatty liver is associated with obesity-related metabolic disturbances, but little is known about the metabolic perturbations preceding fatty liver disease. We performed comprehensive metabolic profiling to assess how circulating metabolites, such as lipoprotein lipids, fatty acids, amino acids, and glycolysis-related metabolites, reflect the presence of and future risk for fatty liver in young adults. Sixty-eight lipids and metabolites were quantified by nuclear magnetic resonance metabolomics in the population-based Young Finns Study from serum collected in 2001 (n = 1,575), 2007 (n = 1,509), and 2011 (n = 2,002). Fatty liver was diagnosed by ultrasound in 2011 when participants were aged 34-49 years (19% prevalence). Cross-sectional associations as well as 4-year and 10-year risks for fatty liver were assessed by logistic regression. Metabolites across multiple pathways were strongly associated with the presence of fatty liver (P <0.0007 for 60 measures in age-adjusted and sex-adjusted cross-sectional analyses). The strongest direct associations were observed for extremely large very-low-density lipoprotein triglycerides (odds ratio [OR] = 4.86 per 1 standard deviation, 95% confidence interval 3.48-6.78), other very-low-density lipoprotein measures, and branched-chain amino acids (e.g., leucine OR = 2.94, 2.51-3.44). Strong inverse associations were observed for high-density lipoprotein measures, e.g., high-density lipoprotein size (OR = 0.36, 0.30-0.42) and several fatty acids including omega-6 (OR = 0.37, 0.32-0.42). The metabolic associations were attenuated but remained significant after adjusting for waist, physical activity, alcohol consumption, and smoking (P <0.0007). Similar aberrations in the metabolic profile were observed already 10 years before fatty liver diagnosis. Conclusion: Circulating lipids, fatty acids, and amino acids reflect fatty liver independently of routine metabolic risk factors; these metabolic aberrations appear to precede the development of fatty liver in young adults. (Hepatology 2017;65:491-500).Peer reviewe

metaCCA : summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis

Motivation: A dominant approach to genetic association studies is to perform univariate tests between genotype-phenotype pairs. However, analyzing related traits together increases statistical power, and certain complex associations become detectable only when several variants are tested jointly. Currently, modest sample sizes of individual cohorts, and restricted availability of individual-level genotype-phenotype data across the cohorts limit conducting multivariate tests. Results: We introduce metaCCA, a computational framework for summary statistics-based analysis of a single or multiple studies that allows multivariate representation of both genotype and phenotype. It extends the statistical technique of canonical correlation analysis to the setting where original individual-level records are not available, and employs a covariance shrinkage algorithm to achieve robustness. Multivariate meta-analysis of two Finnish studies of nuclear magnetic resonance metabolomics by metaCCA, using standard univariate output from the program SNPTEST, shows an excellent agreement with the pooled individual-level analysis of original data. Motivated by strong multivariate signals in the lipid genes tested, we envision that multivariate association testing using metaCCA has a great potential to provide novel insights from already published summary statistics from high-throughput phenotyping technologies.Peer reviewe

Assessing multivariate gene-metabolome associations with rare variants using Bayesian reduced rank regression

Motivation: A typical genome-wide association study searches for associations between single nucleotide polymorphisms (SNPs) and a univariate phenotype. However, there is a growing interest to investigate associations between genomics data and multivariate phenotypes, for example, in gene expression or metabolomics studies. A common approach is to perform a univariate test between each genotype–phenotype pair, and then to apply a stringent significance cutoff to account for the large number of tests performed. However, this approach has limited ability to uncover dependencies involving multiple variables. Another trend in the current genetics is the investigation of the impact of rare variants on the phenotype, where the standard methods often fail owing to lack of power when the minor allele is present in only a limited number of individuals. Results: We propose a new statistical approach based on Bayesian reduced rank regression to assess the impact of multiple SNPs on a high-dimensional phenotype. Because of the method’s ability to combine information over multiple SNPs and phenotypes, it is particularly suitable for detecting associations involving rare variants. We demonstrate the potential of our method and compare it with alternatives using the Northern Finland Birth Cohort with 4702 individuals, for whom genome-wide SNP data along with lipoprotein profiles comprising 74 traits are available. We discovered two genes (XRCC4 and MTHFD2L) without previously reported associations, which replicated in a combined analysis of two additional cohorts: 2390 individuals from the Cardiovascular Risk in Young Finns study and 3659 individuals from the FINRISK study. Availability and implementation: R-code freely available for download at http://users.ics.aalto.fi/pemartti/gene_metabolome/. Contact: [email protected]; [email protected] Supplementary information: Supplementary data are available at Bioinformatics online

Metabonomic, transcriptomic, and genomic variation of a population cohort

Peer reviewe

The biomarker and causal roles of homoarginine in the development of cardiometabolic diseases: an observational and Mendelian randomization analysis

High L-homoarginine (hArg) levels are directly associated with several risk factors for cardiometabolic diseases whereas low levels predict increased mortality in prospective studies. The biomarker role of hArg in young adults remains unknown. To study the predictive value of hArg in the development of cardiometabolic risk factors and diseases, we utilized data on high-pressure liquid chromatography-measured hArg, cardiovascular risk factors, ultrasound markers of preclinical atherosclerosis and type 2 diabetes from the population-based Young Finns Study involving 2,106 young adults (54.6% females, aged 24-39). We used a Mendelian randomization approach involving tens to hundreds of thousands of individuals to test causal associations. In our 10-year follow-up analysis, hArg served as an independent predictor for future hyperglycaemia (OR 1.31, 95% CI 1.06-1.63) and abdominal obesity (OR 1.60, 95% 1.14-2.30) in men and type 2 diabetes in women (OR 1.55, 95% CI 1.02-2.41). The MR analysis revealed no evidence of causal associations between serum hArg and any of the studied cardiometabolic outcomes. In conclusion, lifetime exposure to higher levels of circulating hArg does not seem to alter cardiometabolic disease risk. Whether hArg could be used as a biomarker for identification of individuals at risk developing cardiometabolic abnormalities merits further investigation

A comparison of anthropometric, metabolic, and reproductive characteristics of young adult women from opposite-sex and same-sex twin pairs

Background: Prenatal exposure to androgens has been linked to masculinization of several traits. We aimed to determine whether putative female intra-uterine exposure to androgens influences anthropometric, metabolic, and reproductive parameters using a twin design. Methods: Two cohorts of Finnish twins born in 1975-1979 and 1983-1987 formed the basis for the longitudinal FinnTwin16 (FT16) and FinnTwin12 (FT12) studies. Self-reported anthropometric characteristics, disease status, and reproductive history were compared between 679 same-sex (SS) and 789 opposite-sex (OS) female twins (mean age ± SD: 34 ± 1.1) from the wave 5 of data collection in FT16. Serum lipid and lipoprotein subclass concentrations measured by nuclear magnetic resonance spectroscopy were compared in 226 SS and 169 OS female twins (mean age ± SD: 24 ± 2.1) from the wave 4 of data collection in FT12 and FT16. Results: Anthropometric measures, the prevalence of hypertension and diabetes mellitus type 2 did not differ significantly between females from SS and OS twin pairs at age 34. Similarly, the prevalence of infertility, age at first pregnancy and number of induced and spontaneous abortions did not differ significantly between these two groups of women. The serum lipid and lipoprotein profile did not differ between females from SS and OS twins at age 24. Conclusion: We found no evidence that androgen overexposure of the female fetus affects obesity, metabolic profile, or reproductive health in young adult females. However, these results do not exclude the possibility that prenatal androgen exposure in females could be adversely associated with these phenotypes later in life.Peer reviewe

EpiMetal:an open-source graphical web browser tool for easy statistical analyses in epidemiology and metabolomics

MOTIVATION: An intuitive graphical interface that allows statistical analyses and visualizations of extensive data without any knowledge of dedicated statistical software or programming. IMPLEMENTATION: EpiMetal is a single-page web application written in JavaScript, to be used via a modern desktop web browser. GENERAL FEATURES: Standard epidemiological analyses and self-organizing maps for data-driven metabolic profiling are included. Multiple extensive datasets with an arbitrary number of continuous and category variables can be integrated with the software. Any snapshot of the analyses can be saved and shared with others via a www-link. We demonstrate the usage of EpiMetal using pilot data with over 500 quantitative molecular measures for each sample as well as in two large-scale epidemiological cohorts (N >10 000). AVAILABILITY: The software usage exemplar and the pilot data are open access online at [http://EpiMetal.computationalmedicine.fi]. MIT licensed source code is available at the Github repository at [https://github.com/amergin/epimetal]

A comparison of anthropometric, metabolic, and reproductive characteristics of young adult women from opposite-sex and same-sex twin pairs

Background: Prenatal exposure to androgens has been linked to masculinization of several traits. We aimed to determine whether putative female intra-uterine exposure to androgens influences anthropometric, metabolic, and reproductive parameters using a twin design. Methods: Two cohorts of Finnish twins born in 1975&ndash;1979 and 1983&ndash;1987 formed the basis for the longitudinal FinnTwin16 (FT16) and FinnTwin12 (FT12) studies. Self-reported anthropometric characteristics, disease status, and reproductive history were compared between 679 same-sex (SS) and 789 opposite-sex (OS) female twins (mean age &plusmn; SD: 34 &plusmn; 1.1) from the wave 5 of data collection in FT16. Serum lipid and lipoprotein subclass concentrations measured by nuclear magnetic resonance spectroscopy were compared in 226 SS and 169 OS female twins (mean age &plusmn; SD: 24 &plusmn; 2.1) from the wave 4 of data collection in FT12 and FT16. Results: Anthropometric measures, the prevalence of hypertension and diabetes mellitus type 2 did not differ significantly between females from SS and OS twin pairs at age 34. Similarly, the prevalence of infertility, age at first pregnancy and number of induced and spontaneous abortions did not differ significantly between these two groups of women. The serum lipid and lipoprotein profile did not differ between females from SS and OS twins at age 24. Conclusion: We found no evidence that androgen overexposure of the female fetus affects obesity, metabolic profile, or reproductive health in young adult females. However, these results do not exclude the possibility that prenatal androgen exposure in females could be adversely associated with these phenotypes later in life.</p