PMCC PMCC

Search tips
Search criteria

Advanced
Results 1-25 (53)
 

Clipboard (0)
None

Select a Filter Below

Year of Publication
1.  Metabolic profiling of pregnancy: cross-sectional and longitudinal evidence 
BMC Medicine  2016;14:205.
Background
Pregnancy triggers well-known alterations in maternal glucose and lipid balance but its overall effects on systemic metabolism remain incompletely understood.
Methods
Detailed molecular profiles (87 metabolic measures and 37 cytokines) were measured for up to 4260 women (24–49 years, 322 pregnant) from three population-based cohorts in Finland. Circulating molecular concentrations in pregnant women were compared to those in non-pregnant women. Metabolic profiles were also reassessed for 583 women 6 years later to uncover the longitudinal metabolic changes in response to change in the pregnancy status.
Results
Compared to non-pregnant women, all lipoprotein subclasses and lipids were markedly increased in pregnant women. The most pronounced differences were observed for the intermediate-density, low-density and high-density lipoprotein triglyceride concentrations. Large differences were also seen for many fatty acids and amino acids. Pregnant women also had higher concentrations of low-grade inflammatory marker glycoprotein acetyls, higher concentrations of interleukin-18 and lower concentrations of interleukin-12p70. The changes in metabolic concentrations for women who were not pregnant at baseline but pregnant 6 years later (or vice versa) matched (or were mirror-images of) the cross-sectional association pattern. Cross-sectional results were consistent across the three cohorts and similar longitudinal changes were seen for 653 women in 4-year and 497 women in 10-year follow-up. For multiple metabolic measures, the changes increased in magnitude across the three trimesters.
Conclusions
Pregnancy initiates substantial metabolic and inflammatory changes in the mothers. Comprehensive characterisation of normal pregnancy is important for gaining understanding of the key nutrients for fetal growth and development. These findings also provide a valuable molecular reference in relation to studies of adverse pregnancy outcomes.
Electronic supplementary material
The online version of this article (doi:10.1186/s12916-016-0733-0) contains supplementary material, which is available to authorized users.
doi:10.1186/s12916-016-0733-0
PMCID: PMC5153817  PMID: 27955712
Pregnancy; Trimesters; Postpartum; Metabolomics; Cytokines; Lipoprotein lipids; Fatty acids; Amino acids; Hormones; Inflammation; Metabolic networks
2.  Metabolic signatures of birthweight in 18 288 adolescents and adults 
Background: Lower birthweight is associated with increased susceptibility to cardiometabolic diseases in adulthood, but the underlying molecular pathways are incompletely understood. We examined associations of birthweight with a comprehensive metabolic profile measured in adolescents and adults.
Methods: High-throughput nuclear magnetic resonance metabolomics and biochemical assays were used to quantify 87 circulating metabolic measures in seven cohorts from Finland and the UK, comprising altogether 18 288 individuals (mean age 26 years, range 15–75). Metabolic associations with birthweight were assessed by linear regression models adjusted for sex, gestational age and age at blood sampling. The metabolic associations with birthweight were compared with the corresponding associations with adult body mass index (BMI).
Results: Lower birthweight adjusted for gestational age was adversely associated with cardiometabolic biomarkers, including lipoprotein subclasses, fatty acids, amino acids and markers of inflammation and impaired liver function (P < 0.0015 for 46 measures). Associations were consistent across cohorts with different ages at metabolic profiling, but the magnitudes were weak. The pattern of metabolic deviations associated with lower birthweight resembled the metabolic signature of higher adult BMI (R2 = 0.77) assessed at the same time as the metabolic profiling. The resemblance indicated that 1 kg lower birthweight is associated with similar metabolic aberrations as caused by 0.92 units higher BMI in adulthood.
Conclusions: Lower birthweight adjusted for gestational age is associated with adverse biomarker aberrations across multiple metabolic pathways. Coherent metabolic signatures between lower birthweight and higher adult adiposity suggest that shared molecular pathways may potentially underpin the metabolic deviations. However, the magnitudes of metabolic associations with birthweight are modest in comparison to the effects of adiposity, implying that birthweight is only a weak indicator of the metabolic risk profile in adulthood.
doi:10.1093/ije/dyw255
PMCID: PMC5100627  PMID: 27892411
Fetal programming; metabolic signatures; metabolomics; adiposity; fatty acids; amino acids
4.  Characterization of the metabolic profile associated with serum 25-hydroxyvitamin D: a cross-sectional analysis in population-based data 
Background: Numerous observational studies have observed associations between vitamin D deficiency and cardiometabolic diseases, but these findings might be confounded by obesity. A characterization of the metabolic profile associated with serum 25-hydroxyvitamin D [25(OH)D] levels, in general and stratified by abdominal obesity, may help to untangle the relationship between vitamin D, obesity and cardiometabolic health.
Methods: Serum metabolomics measurements were obtained from a nuclear magnetic resonance spectroscopy (NMR)- and a mass spectrometry (MS)-based platform. The discovery was conducted in 1726 participants of the population-based KORA-F4 study, in which the associations of the concentrations of 415 metabolites with 25(OH)D levels were assessed in linear models. The results were replicated in 6759 participants (NMR) and 609 (MS) participants, respectively, of the population-based FINRISK 1997 study.
Results: Mean [standard deviation (SD)] 25(OH)D levels were 15.2 (7.5) ng/ml in KORA F4 and 13.8 (5.9) ng/ml in FINRISK 1997; 37 metabolites were associated with 25(OH)D in KORA F4 at P < 0.05/415. Of these, 30 associations were replicated in FINRISK 1997 at P < 0.05/37. Among these were constituents of (very) large very-low-density lipoprotein and small low-density lipoprotein subclasses and related measures like serum triglycerides as well as fatty acids and measures reflecting the degree of fatty acid saturation. The observed associations were independent of waist circumference and generally similar in abdominally obese and non-obese participants.
Conclusions: Independently of abdominal obesity, higher 25(OH)D levels were associated with a metabolite profile characterized by lower concentrations of atherogenic lipids and a higher degree of fatty acid polyunsaturation. These results indicate that the relationship between vitamin D deficiency and cardiometabolic diseases is unlikely to merely reflect obesity-related pathomechanisms.
doi:10.1093/ije/dyw222
PMCID: PMC5100623  PMID: 27605587
25(OH)D; vitamin D; metabolomics; obesity; molecular epidemiology
5.  Variant rs10911021 that associates with coronary heart disease in type 2 diabetes, is associated with lower concentrations of circulating HDL cholesterol and large HDL particles but not with amino acids 
Cardiovascular Diabetology  2016;15(1):115.
Aims
An intergenic locus on chromosome 1 (lead SNP rs10911021) was previously associated with coronary heart disease (CHD) in type 2 diabetes (T2D). Using data from the UCLEB consortium we investigated the relationship between rs10911021 and CHD in T2D, whether rs10911021 was associated with levels of amino acids involved in the γ-glutamyl cycle or any conventional risk factors (CRFs) for CHD in the T2D participants.
Methods
Four UCLEB studies (n = 6531) had rs10911021 imputation, CHD in T2D, CRF and metabolomics data determined using a nuclear magnetic resonance based platform.
Results
The expected direction of effect between rs10911021 and CHD in T2D was observed (1377 no CHD/160 CHD; minor allele OR 0.80, 95 % CI 0.60–1.06) although this was not statistically significant (p = 0.13). No association between rs10911021 and CHD was seen in non-T2D participants (11218 no CHD/1274 CHD; minor allele OR 1.00 95 % CIs 0.92–1.10). In T2D participants, while no associations were observed between rs10911021 and the nine amino acids measured, rs10911021 was associated with HDL-cholesterol (p = 0.0005) but the minor “protective” allele was associated with lower levels (−0.034 mmol/l per allele). Focusing more closely on the HDL-cholesterol subclasses measured, we observed that rs10911021 was associated with six large HDL particle measures in T2D (all p < 0.001). No significant associations were seen in non-T2D subjects.
Conclusions
Our findings are consistent with a true association between rs10911021 and CHD in T2D. The protective minor allele was associated with lower HDL-cholesterol and reductions in HDL particle traits. Our results indicate a complex relationship between rs10911021 and CHD in T2D.
Electronic supplementary material
The online version of this article (doi:10.1186/s12933-016-0435-0) contains supplementary material, which is available to authorized users.
doi:10.1186/s12933-016-0435-0
PMCID: PMC4994200  PMID: 27549350
Coronary heart disease; Metabolomics; HDL-cholesterol; Genetic risk
6.  Effects of hormonal contraception on systemic metabolism: cross-sectional and longitudinal evidence 
Background: Hormonal contraception is commonly used worldwide, but its systemic effects across lipoprotein subclasses, fatty acids, circulating metabolites and cytokines remain poorly understood.
Methods: A comprehensive molecular profile (75 metabolic measures and 37 cytokines) was measured for up to 5841 women (age range 24–49 years) from three population-based cohorts. Women using combined oral contraceptive pills (COCPs) or progestin-only contraceptives (POCs) were compared with those who did not use hormonal contraception. Metabolomics profiles were reassessed for 869 women after 6 years to uncover the metabolic effects of starting, stopping and persistently using hormonal contraception.
Results: The comprehensive molecular profiling allowed multiple new findings on the metabolic associations with the use of COCPs. They were positively associated with lipoprotein subclasses, including all high-density lipoprotein (HDL) subclasses. The associations with fatty acids and amino acids were strong and variable in direction. COCP use was negatively associated with albumin and positively associated with creatinine and inflammatory markers, including glycoprotein acetyls and several growth factors and interleukins. Our findings also confirmed previous results e.g. for increased circulating triglycerides and HDL cholesterol. Starting COCPs caused similar metabolic changes to those observed cross-sectionally: the changes were maintained in consistent users and normalized in those who stopped using. In contrast, POCs were only weakly associated with metabolic and inflammatory markers. Results were consistent across all cohorts and for different COCP preparations and different types of POC delivery.
Conclusions: Use of COCPs causes widespread metabolic and inflammatory effects. However, persistent use does not appear to accumulate the effects over time and the metabolic perturbations are reversed upon discontinuation. POCs have little effect on systemic metabolism and inflammation.
doi:10.1093/ije/dyw147
PMCID: PMC5100613  PMID: 27538888
hormonal contraception; combined oral contraceptive pills; progestin-only contraceptives; metabolomics; cytokines; inflammation; amino acids; fatty acids; lipoproteins; hormones; risk factors
7.  Metabolic profiling of alcohol consumption in 9778 young adults 
Background: High alcohol consumption is a major cause of morbidity, yet alcohol is associated with both favourable and adverse effects on cardiometabolic risk markers. We aimed to characterize the associations of usual alcohol consumption with a comprehensive systemic metabolite profile in young adults.
Methods: Cross-sectional associations of alcohol intake with 86 metabolic measures were assessed for 9778 individuals from three population-based cohorts from Finland (age 24–45 years, 52% women). Metabolic changes associated with change in alcohol intake during 6-year follow-up were further examined for 1466 individuals. Alcohol intake was assessed by questionnaires. Circulating lipids, fatty acids and metabolites were quantified by high-throughput nuclear magnetic resonance metabolomics and biochemical assays.
Results: Increased alcohol intake was associated with cardiometabolic risk markers across multiple metabolic pathways, including higher lipid concentrations in HDL subclasses and smaller LDL particle size, increased proportions of monounsaturated fatty acids and decreased proportion of omega-6 fatty acids, lower concentrations of glutamine and citrate (P < 0.001 for 56 metabolic measures). Many metabolic biomarkers displayed U-shaped associations with alcohol consumption. Results were coherent for men and women, consistent across the three cohorts and similar if adjusting for body mass index, smoking and physical activity. The metabolic changes accompanying change in alcohol intake during follow-up resembled the cross-sectional association pattern (R2 = 0.83, slope = 0.72 ± 0.04).
Conclusions: Alcohol consumption is associated with a complex metabolic signature, including aberrations in multiple biomarkers for elevated cardiometabolic risk. The metabolic signature tracks with long-term changes in alcohol consumption. These results elucidate the double-edged effects of alcohol on cardiovascular risk.
doi:10.1093/ije/dyw175
PMCID: PMC5100616  PMID: 27494945
Alcohol; risk factors; metabolomics; fatty acids; metabolic profiling
8.  Metabolic Characterization of a Rare Genetic Variation Within APOC3 and Its Lipoprotein Lipase–Independent Effects 
Supplemental Digital Content is available in the text.
Background—
Plasma triglyceride levels have been implicated in atherosclerosis and coronary heart disease. Apolipoprotein C-III (APOC3) plays a key role in the hydrolysis of triglyceride-rich lipoproteins to remnant particles by lipoprotein lipase (LPL) and their uptake by the liver. A rare variant in APOC3(rs138326449) has been associated with triglyceride, very low–density lipoprotein, and high-density lipoprotein levels, as well as risk of coronary heart disease. We aimed to characterize the impact of this locus across a broad set of mainly lipids-focused metabolic measures.
Methods and Results—
A high-throughput serum nuclear magnetic resonance metabolomics platform was used to quantify 225 metabolic measures in 13 285 participants from 2 European population cohorts. We analyzed the effect of the APOC3 variant on the metabolic measures and used the common LPL(rs12678919) polymorphism to test for LPL-independent effects. Eighty-one metabolic measures showed evidence of association with APOC3(rs138326449). In addition to previously reported triglyceride and high-density lipoprotein associations, the variant was also associated with very low–density lipoprotein and high-density lipoprotein composition measures, other cholesterol measures, and fatty acids. Comparison of the APOC3 and LPL associations revealed that APOC3 association results for medium and very large very low–density lipoprotein composition are unlikely to be solely predictable by the action of APOC3 through LPL.
Conclusions—
We characterized the effects of the rare APOC3(rs138326449) loss of function mutation in lipoprotein metabolism, as well as the effects of LPL(rs12678919). Our results improve our understanding of the role of APOC3 in triglyceride metabolism, its LPL independent action, and the complex and correlated nature of human metabolites.
doi:10.1161/CIRCGENETICS.115.001302
PMCID: PMC4920206  PMID: 27114411
association studies; genetics; lipids; LPL; metabolism; triglycerides; VLDL
9.  Prolonged sleep restriction induces changes in pathways involved in cholesterol metabolism and inflammatory responses 
Scientific Reports  2016;6:24828.
Sleep loss and insufficient sleep are risk factors for cardiometabolic diseases, but data on how insufficient sleep contributes to these diseases are scarce. These questions were addressed using two approaches: an experimental, partial sleep restriction study (14 cases and 7 control subjects) with objective verification of sleep amount, and two independent epidemiological cohorts (altogether 2739 individuals) with questions of sleep insufficiency. In both approaches, blood transcriptome and serum metabolome were analysed. Sleep loss decreased the expression of genes encoding cholesterol transporters and increased expression in pathways involved in inflammatory responses in both paradigms. Metabolomic analyses revealed lower circulating large HDL in the population cohorts among subjects reporting insufficient sleep, while circulating LDL decreased in the experimental sleep restriction study. These findings suggest that prolonged sleep deprivation modifies inflammatory and cholesterol pathways at the level of gene expression and serum lipoproteins, inducing changes toward potentially higher risk for cardiometabolic diseases.
doi:10.1038/srep24828
PMCID: PMC4840329  PMID: 27102866
10.  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 analyzed 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.
doi:10.1002/ajhb.22381
PMCID: PMC4834886  PMID: 23649903
11.  Association between serum fatty acids and lipoprotein subclass profile in healthy young adults: Exploring common genetic and environmental factors 
Atherosclerosis  2014;233(2):394-402.
Objective
Little is known about the associations of serum fatty acids with lipoprotein profile and the underlying genetic and environmental etiology of these relationships. We aimed to analyze the phenotypic association of serum n-6 and n-3 polyunsaturated (PUFAs), monounsaturated (MUFAs) and saturated (SFAs) fatty acids (relative proportion to total fatty acids) with lipids and lipoproteins, and to quantify common genetic and environmental factors determining their covariation.
Methods
Two cohorts of healthy Finnish twins were assessed in young adulthood. Data were available for 1269 individual twins including 561 complete pairs. Serum metabolites were measured by nuclear magnetic resonance spectroscopy. Bivariate quantitative genetic models were used to decompose the phenotypic covariance between the pairs of traits into genetic and environmental components.
Results
Among the strongest correlations observed, serum total n-6 PUFAs and linoleic acid were inversely (max. r = −0.65) and MUFAs positively (max. r = 0.63) correlated with triglycerides and very low-density lipoprotein (VLDL) particle concentration, particularly with large VLDL (for n-6 PUFAs) and medium VLDL (for MUFAs). Genetic factors significantly contributed to their covariance with bivariate heritability estimates ranging from 44% to 56% for n-6 PUFAs and 58% to 66% for MUFAs. Genetic correlations with lipid traits were moderate to high (max. rA = −0.59 and 0.70 for n-6 PUFAs and MUFAs, respectively). Statistically significant, but substantially weaker phenotypic correlations of total n-3 PUFAs, docosahexaenoic acid (DHA) and SFAs with lipoprotein profile were not decomposed into their genetic and environmental components.
Conclusion
Shared genetic factors are important in explaining why higher concentrations of serum n-6 PUFAs and lower concentrations of serum MUFAs strongly associate with lower triglyceride and VLDL particle concentrations.
doi:10.1016/j.atherosclerosis.2013.12.053
PMCID: PMC4826157  PMID: 24530769
Serum fatty acids; Lipoprotein profile; Twins; Genetic pleiotropy; Environmental factors
12.  Genome-wide study for circulating metabolites identifies 62 loci and reveals novel systemic effects of LPA 
Nature Communications  2016;7:11122.
Genome-wide association studies have identified numerous loci linked with complex diseases, for which the molecular mechanisms remain largely unclear. Comprehensive molecular profiling of circulating metabolites captures highly heritable traits, which can help to uncover metabolic pathophysiology underlying established disease variants. We conduct an extended genome-wide association study of genetic influences on 123 circulating metabolic traits quantified by nuclear magnetic resonance metabolomics from up to 24,925 individuals and identify eight novel loci for amino acids, pyruvate and fatty acids. The LPA locus link with cardiovascular risk exemplifies how detailed metabolic profiling may inform underlying aetiology via extensive associations with very-low-density lipoprotein and triglyceride metabolism. Genetic fine mapping and Mendelian randomization uncover wide-spread causal effects of lipoprotein(a) on overall lipoprotein metabolism and we assess potential pleiotropic consequences of genetically elevated lipoprotein(a) on diverse morbidities via electronic health-care records. Our findings strengthen the argument for safe LPA-targeted intervention to reduce cardiovascular risk.
Circulating metabolites reflect human health and disease. Here, Kettunen et al. perform a genome-wide association study on 123 circulating metabolic traits and identify novel genetic loci influencing systemic metabolism. They also link new molecular pathways with a known cardiovascular risk factor Lp(a).
doi:10.1038/ncomms11122
PMCID: PMC4814583  PMID: 27005778
13.  Metabolomic Profiling of Statin Use and Genetic Inhibition of HMG-CoA Reductase 
Background
Statins are first-line therapy for cardiovascular disease prevention, but their systemic effects across lipoprotein subclasses, fatty acids, and circulating metabolites remain incompletely characterized.
Objectives
This study sought to determine the molecular effects of statin therapy on multiple metabolic pathways.
Methods
Metabolic profiles based on serum nuclear magnetic resonance metabolomics were quantified at 2 time points in 4 population-based cohorts from the United Kingdom and Finland (N = 5,590; 2.5 to 23.0 years of follow-up). Concentration changes in 80 lipid and metabolite measures during follow-up were compared between 716 individuals who started statin therapy and 4,874 persistent nonusers. To further understand the pharmacological effects of statins, we used Mendelian randomization to assess associations of a genetic variant known to mimic inhibition of HMG-CoA reductase (the intended drug target) with the same lipids and metabolites for 27,914 individuals from 8 population-based cohorts.
Results
Starting statin therapy was associated with numerous lipoprotein and fatty acid changes, including substantial lowering of remnant cholesterol (80% relative to low-density lipoprotein cholesterol [LDL-C]), but only modest lowering of triglycerides (25% relative to LDL-C). Among fatty acids, omega-6 levels decreased the most (68% relative to LDL-C); other fatty acids were only modestly affected. No robust changes were observed for circulating amino acids, ketones, or glycolysis-related metabolites. The intricate metabolic changes associated with statin use closely matched the association pattern with rs12916 in the HMGCR gene (R2 = 0.94, slope 1.00 ± 0.03).
Conclusions
Statin use leads to extensive lipid changes beyond LDL-C and appears efficacious for lowering remnant cholesterol. Metabolomic profiling, however, suggested minimal effects on amino acids. The results exemplify how detailed metabolic characterization of genetic proxies for drug targets can inform indications, pleiotropic effects, and pharmacological mechanisms.
doi:10.1016/j.jacc.2015.12.060
PMCID: PMC4783625  PMID: 26965542
cholesterol lowering; drug development; lipoproteins; Mendelian randomization; metabolomics; CVD, cardiovascular disease; HDL, high-density lipoprotein; HMGCR, HMG-CoA reductase; IDL, intermediate-density lipoprotein; LDL-C, low-density lipoprotein cholesterol; NMR, nuclear magnetic resonance; VLDL, very-low-density lipoprotein
14.  Metabolite Profiling and Cardiovascular Event Risk: A Prospective Study of Three Population-Based Cohorts 
Circulation  2015;131(9):774-785.
Background
High-throughput profiling of circulating metabolites may improve cardiovascular risk prediction over established risk factors.
Methods and Results
We applied quantitative NMR metabolomics to identify biomarkers for incident cardiovascular disease during long-term follow-up. Biomarker discovery was conducted in the FINRISK study (n=7256; 800 events). Replication and incremental risk prediction was assessed in the SABRE study (n=2622; 573 events) and British Women’s Health and Heart Study (n=3563; 368 events). In targeted analyses of 68 lipids and metabolites, 33 measures were associated with incident cardiovascular events at P<0.0007 after adjusting for age, sex, blood pressure, smoking, diabetes and medication. When further adjusting for routine lipids, four metabolites were associated with future cardiovascular events in meta-analyses: higher serum phenylalanine (hazard ratio per standard deviation: 1.18 [95%CI 1.12–1.24]; P=4×10−10) and monounsaturated fatty acid levels (1.17 [1.11–1.24]; P=1×10−8) were associated with increased cardiovascular risk, while higher omega-6 fatty acids (0.89 [0.84–0.94]; P=6×10−5) and docosahexaenoic acid levels (0.90 [0.86–0.95]; P=5×10−5) were associated with lower risk. A risk score incorporating these four biomarkers was derived in FINRISK. Risk prediction estimates were more accurate in the two validation cohorts (relative integrated discrimination improvement 8.8% and 4.3%), albeit discrimination was not enhanced. Risk classification was particularly improved for persons in the 5–10% risk range (net reclassification 27.1% and 15.5%). Biomarker associations were further corroborated with mass spectrometry in FINRISK (n=671) and the Framingham Offspring Study (n=2289).
Conclusions
Metabolite profiling in large prospective cohorts identified phenylalanine, monounsaturated and polyunsaturated fatty acids as biomarkers for cardiovascular risk. This study substantiates the value of high-throughput metabolomics for biomarker discovery and improved risk assessment.
doi:10.1161/CIRCULATIONAHA.114.013116
PMCID: PMC4351161  PMID: 25573147
biomarkers; metabolomics; risk prediction; amino acids; fatty acids
15.  metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis 
Bioinformatics  2016;32(13):1981-1989.
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.
Availability and implementation: Code is available at https://github.com/aalto-ics-kepaco
Contacts: anna.cichonska@helsinki.fi or matti.pirinen@helsinki.fi
Supplementary information: Supplementary data are available at Bioinformatics online.
doi:10.1093/bioinformatics/btw052
PMCID: PMC4920109  PMID: 27153689
16.  Epigenome-wide association of DNA methylation markers in peripheral blood from Indian Asians and Europeans with incident type 2 diabetes: a nested case-control study 
Summary
Background
Indian Asians, who make up a quarter of the world’s population, are at high risk of developing type 2 diabetes. We investigated whether DNA methylation is associated with future type 2 diabetes incidence in Indian Asians and whether differences in methylation patterns between Indian Asians and Europeans are associated with, and could be used to predict, differences in the magnitude of risk of developing type 2 diabetes.
Methods
We did a nested case-control study of DNA methylation in Indian Asians and Europeans with incident type 2 diabetes who were identified from the 8-year follow-up of 25 372 participants in the London Life Sciences Prospective Population (LOLIPOP) study. Patients were recruited between May 1, 2002, and Sept 12, 2008. We did epigenome-wide association analysis using samples from Indian Asians with incident type 2 diabetes and age-matched and sex-matched Indian Asian controls, followed by replication testing of top-ranking signals in Europeans. For both discovery and replication, DNA methylation was measured in the baseline blood sample, which was collected before the onset of type 2 diabetes. Epigenome-wide significance was set at p<1 × 10−7. We compared methylation levels between Indian Asian and European controls without type 2 diabetes at baseline to estimate the potential contribution of DNA methylation to increased risk of future type 2 diabetes incidence among Indian Asians.
Findings
1608 (11·9%) of 13 535 Indian Asians and 306 (4·3%) of 7066 Europeans developed type 2 diabetes over a mean of 8·5 years (SD 1·8) of follow-up. The age-adjusted and sex-adjusted incidence of type 2 diabetes was 3·1 times (95% CI 2·8–3·6; p<0·0001) higher among Indian Asians than among Europeans, and remained 2·5 times (2·1–2·9; p<0·0001) higher after adjustment for adiposity, physical activity, family history of type 2 diabetes, and baseline glycaemic measures. The mean absolute difference in methylation level between type 2 diabetes cases and controls ranged from 0·5% (SD 0·1) to 1·1% (0·2). Methylation markers at five loci were associated with future type 2 diabetes incidence; the relative risk per 1% increase in methylation was 1·09 (95% CI 1·07–1·11; p=1·3 × 10−17) for ABCG1, 0·94 (0·92–0·95; p=4·2 × 10−11) for PHOSPHO1, 0·94 (0·92–0·96; p=1·4 × 10−9) for SOCS3, 1·07 (1·04–1·09; p=2·1 × 10−10) for SREBF1, and 0·92 (0·90–0·94; p=1·2 × 10−17) for TXNIP. A methylation score combining results for the five loci was associated with future type 2 diabetes incidence (relative risk quartile 4 vs quartile 1 3·51, 95% CI 2·79–4·42; p=1·3 × 10−26), and was independent of established risk factors. Methylation score was higher among Indian Asians than Europeans (p=1 × 10−34).
Interpretation
DNA methylation might provide new insights into the pathways underlying type 2 diabetes and offer new opportunities for risk stratification and prevention of type 2 diabetes among Indian Asians.
Funding
The European Union, the UK National Institute for Health Research, the Wellcome Trust, the UK Medical Research Council, Action on Hearing Loss, the UK Biotechnology and Biological Sciences Research Council, the Oak Foundation, the Economic and Social Research Council, Helmholtz Zentrum Munchen, the German Research Center for Environmental Health, the German Federal Ministry of Education and Research, the German Center for Diabetes Research, the Munich Center for Health Sciences, the Ministry of Science and Research of the State of North Rhine-Westphalia, and the German Federal Ministry of Health.
doi:10.1016/S2213-8587(15)00127-8
PMCID: PMC4724884  PMID: 26095709
17.  Multi-omic signature of body weight change: results from a population-based cohort study 
BMC Medicine  2015;13:48.
Background
Excess body weight is a major risk factor for cardiometabolic diseases. The complex molecular mechanisms of body weight change-induced metabolic perturbations are not fully understood. Specifically, in-depth molecular characterization of long-term body weight change in the general population is lacking. Here, we pursued a multi-omic approach to comprehensively study metabolic consequences of body weight change during a seven-year follow-up in a large prospective study.
Methods
We used data from the population-based Cooperative Health Research in the Region of Augsburg (KORA) S4/F4 cohort. At follow-up (F4), two-platform serum metabolomics and whole blood gene expression measurements were obtained for 1,631 and 689 participants, respectively. Using weighted correlation network analysis, omics data were clustered into modules of closely connected molecules, followed by the formation of a partial correlation network from the modules. Association of the omics modules with previous annual percentage weight change was then determined using linear models. In addition, we performed pathway enrichment analyses, stability analyses, and assessed the relation of the omics modules with clinical traits.
Results
Four metabolite and two gene expression modules were significantly and stably associated with body weight change (P-values ranging from 1.9 × 10−4 to 1.2 × 10−24). The four metabolite modules covered major branches of metabolism, with VLDL, LDL and large HDL subclasses, triglycerides, branched-chain amino acids and markers of energy metabolism among the main representative molecules. One gene expression module suggests a role of weight change in red blood cell development. The other gene expression module largely overlaps with the lipid-leukocyte (LL) module previously reported to interact with serum metabolites, for which we identify additional co-expressed genes. The omics modules were interrelated and showed cross-sectional associations with clinical traits. Moreover, weight gain and weight loss showed largely opposing associations with the omics modules.
Conclusions
Long-term weight change in the general population globally associates with serum metabolite concentrations. An integrated metabolomics and transcriptomics approach improved the understanding of molecular mechanisms underlying the association of weight gain with changes in lipid and amino acid metabolism, insulin sensitivity, mitochondrial function as well as blood cell development and function.
Electronic supplementary material
The online version of this article (doi:10.1186/s12916-015-0282-y) contains supplementary material, which is available to authorized users.
doi:10.1186/s12916-015-0282-y
PMCID: PMC4367822  PMID: 25857605
Metabolomics; Transcriptomics; Weight change; Obesity; Molecular epidemiology; Bioinformatics
18.  Diabetes risk and amino acid profiles: cross-sectional and prospective analyses of ethnicity, amino acids and diabetes in a South Asian and European cohort from the SABRE (Southall And Brent REvisited) Study 
Diabetologia  2015;58(5):968-979.
Aims/hypothesis
South Asian individuals have an increased risk of diabetes compared with Europeans that is unexplained by obesity and traditional or established metabolic measures. Circulating amino acids (AAs) may provide additional explanatory insights. In a unique cohort of European and South Asian men, we compared cross-sectional associations between AAs, metabolic and obesity traits, and longitudinal associations with incident diabetes.
Methods
Nuclear magnetic spectroscopy was used to measure the baseline (1988–1991) levels of nine AAs in serum samples from a British population-based cohort of 1,279 European and 1,007 South Asian non-diabetic men aged 40–69 years. Follow-up was complete for 19 years in 801 European and 643 South Asian participants.
Results
The serum concentrations of isoleucine, phenylalanine, tyrosine and alanine were significantly higher in South Asian men, while cross-sectional correlations of AAs with glycaemia and insulin resistance were similar in the two ethnic groups. However, most AAs were less strongly correlated with measures of obesity in the South Asian participants. Diabetes developed in 227 (35%) South Asian and 113 (14%) European men. Stronger adverse associations were observed between branched chain and aromatic AAs and incident diabetes in South Asian men. Tyrosine was a particularly strong predictor of incident diabetes in South Asian individuals, even after adjustment for metabolic risk factors, including obesity and insulin resistance (adjusted OR for a 1 SD increment, 1.47, 95% CI 1.17,1.85, p = 0.001) compared with Europeans (OR 1.10, 0.87, 1.39, p = 0.4; p = 0.045 for ethnicity × tyrosine interaction).
Conclusions/interpretation
Branched chain and aromatic AAs, particularly tyrosine, may be a focus for identifying novel aetiological mechanisms and potential treatment targets for diabetes in South Asian populations and may contribute to their excess risk of diabetes.
Electronic supplementary material
The online version of this article (doi:10.1007/s00125-015-3517-8) contains peer-reviewed but unedited supplementary material, which is available to authorised users.
doi:10.1007/s00125-015-3517-8
PMCID: PMC4392114  PMID: 25693751
Amino acids; Cohort; Diabetes; Ethnicity; European; South Asian
19.  Metabolic Signatures of Adiposity in Young Adults: Mendelian Randomization Analysis and Effects of Weight Change 
PLoS Medicine  2014;11(12):e1001765.
In this study, Wurtz and colleagues investigated to what extent elevated body mass index (BMI) within the normal weight range has causal influences on the detailed systemic metabolite profile in early adulthood using Mendelian randomization analysis.
Please see later in the article for the Editors' Summary
Background
Increased adiposity is linked with higher risk for cardiometabolic diseases. We aimed to determine to what extent elevated body mass index (BMI) within the normal weight range has causal effects on the detailed systemic metabolite profile in early adulthood.
Methods and Findings
We used Mendelian randomization to estimate causal effects of BMI on 82 metabolic measures in 12,664 adolescents and young adults from four population-based cohorts in Finland (mean age 26 y, range 16–39 y; 51% women; mean ± standard deviation BMI 24±4 kg/m2). Circulating metabolites were quantified by high-throughput nuclear magnetic resonance metabolomics and biochemical assays. In cross-sectional analyses, elevated BMI was adversely associated with cardiometabolic risk markers throughout the systemic metabolite profile, including lipoprotein subclasses, fatty acid composition, amino acids, inflammatory markers, and various hormones (p<0.0005 for 68 measures). Metabolite associations with BMI were generally stronger for men than for women (median 136%, interquartile range 125%–183%). A gene score for predisposition to elevated BMI, composed of 32 established genetic correlates, was used as the instrument to assess causality. Causal effects of elevated BMI closely matched observational estimates (correspondence 87%±3%; R2 = 0.89), suggesting causative influences of adiposity on the levels of numerous metabolites (p<0.0005 for 24 measures), including lipoprotein lipid subclasses and particle size, branched-chain and aromatic amino acids, and inflammation-related glycoprotein acetyls. Causal analyses of certain metabolites and potential sex differences warrant stronger statistical power. Metabolite changes associated with change in BMI during 6 y of follow-up were examined for 1,488 individuals. Change in BMI was accompanied by widespread metabolite changes, which had an association pattern similar to that of the cross-sectional observations, yet with greater metabolic effects (correspondence 160%±2%; R2 = 0.92).
Conclusions
Mendelian randomization indicates causal adverse effects of increased adiposity with multiple cardiometabolic risk markers across the metabolite profile in adolescents and young adults within the non-obese weight range. Consistent with the causal influences of adiposity, weight changes were paralleled by extensive metabolic changes, suggesting a broadly modifiable systemic metabolite profile in early adulthood.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Adiposity—having excessive body fat—is a growing global threat to public health. Body mass index (BMI, calculated by dividing a person's weight in kilograms by their height in meters squared) is a coarse indicator of excess body weight, but the measure is useful in large population studies. Compared to people with a lean body weight (a BMI of 18.5–24.9 kg/m2), individuals with higher BMI have an elevated risk of developing life-shortening cardiometabolic diseases—cardiovascular diseases that affect the heart and/or the blood vessels (for example, heart failure and stroke) and metabolic diseases that affect the cellular chemical reactions that sustain life (for example, diabetes). People become unhealthily fat by consuming food and drink that contains more energy (calories) than they need for their daily activities. So adiposity can be prevented and reversed by eating less and exercising more.
Why Was This Study Done?
Epidemiological studies, which record the patterns of risk factors and disease in populations, suggest that the illness and death associated with excess body weight is partly attributable to abnormalities in how individuals with high adiposity metabolize carbohydrates and fats, leading to higher blood sugar and cholesterol levels. Further, adiposity is also associated with many other deviations in the metabolic profile than these commonly measured risk factors. However, epidemiological studies cannot prove that adiposity causes specific changes in a person's systemic (overall) metabolic profile because individuals with high BMI may share other characteristics (confounding factors) that are the actual causes of both adiposity and metabolic abnormalities. Moreover, having a change in some aspect of metabolism could also lead to adiposity, rather than vice versa (reverse causation). Importantly, if there is a causal effect of adiposity on cardiometabolic risk factor levels, it might be possible to prevent the progression towards cardiometabolic diseases by weight loss. Here, the researchers use “Mendelian randomization” to examine whether increased BMI within the normal and overweight range is causally influencing the metabolic risk factors from many biological pathways during early adulthood. Because gene variants are inherited randomly, they are not prone to confounding and are free from reverse causation. Several gene variants are known to lead to modestly increased BMI. Thus, an investigation of the associations between these gene variants and risk factors across the systemic metabolite profile in a population of healthy individuals can indicate whether higher BMI is causally related to known and novel metabolic risk factors and higher cardiometabolic disease risk.
What Did the Researchers Do and Find?
The researchers measured the BMI of 12,664 adolescents and young adults (average BMI 24.7 kg/m2) living in Finland and the blood levels of 82 metabolites in these young individuals at a single time point. Statistical analysis of these data indicated that elevated BMI was adversely associated with numerous cardiometabolic risk factors. For example, elevated BMI was associated with raised levels of low-density lipoprotein, “bad” cholesterol that increases cardiovascular disease risk. Next, the researchers used a gene score for predisposition to increased BMI, composed of 32 gene variants correlated with increased BMI, as an “instrumental variable” to assess whether adiposity causes metabolite abnormalities. The effects on the systemic metabolite profile of a 1-kg/m2 increment in BMI due to genetic predisposition closely matched the effects of an observed 1-kg/m2 increment in adulthood BMI on the metabolic profile. That is, higher levels of adiposity had causal effects on the levels of numerous blood-based metabolic risk factors, including higher levels of low-density lipoprotein cholesterol and triglyceride-carrying lipoproteins, protein markers of chronic inflammation and adverse liver function, impaired insulin sensitivity, and elevated concentrations of several amino acids that have recently been linked with the risk for developing diabetes. Elevated BMI also causally led to lower levels of certain high-density lipoprotein lipids in the blood, a marker for the risk of future cardiovascular disease. Finally, an examination of the metabolic changes associated with changes in BMI in 1,488 young adults after a period of six years showed that those metabolic measures that were most strongly associated with BMI at a single time point likewise displayed the highest responsiveness to weight change over time.
What Do These Findings Mean?
These findings suggest that increased adiposity has causal adverse effects on multiple cardiometabolic risk markers in non-obese young adults beyond the effects on cholesterol and blood sugar. Like all Mendelian randomization studies, the reliability of the causal association reported here depends on several assumptions made by the researchers. Nevertheless, these findings suggest that increased adiposity has causal adverse effects on multiple cardiometabolic risk markers in non-obese young adults. Importantly, the results of both the causal effect analyses and the longitudinal study suggest that there is no threshold below which a BMI increase does not adversely affect the metabolic profile, and that a systemic metabolic profile linked with high cardiometabolic disease risk that becomes established during early adulthood can be reversed. Overall, these findings therefore highlight the importance of weight reduction as a key target for metabolic risk factor control among young adults.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001765.
The Computational Medicine Research Team of the University of Oulu has a webpage that provides further information on metabolite profiling by high-throughput NMR metabolomics
The World Health Organization provides information on obesity (in several languages)
The Global Burden of Disease Study website provides the latest details about global obesity trends
The UK National Health Service Choices website provides information about obesity, cardiovascular disease, and type 2 diabetes (including some personal stories)
The American Heart Association provides information on all aspects of cardiovascular disease and diabetes and on keeping healthy; its website includes personal stories about heart attacks, stroke, and diabetes
The US Centers for Disease Control and Prevention has information on all aspects of overweight and obesity and information about heart disease, stroke, and diabetes
MedlinePlus provides links to other sources of information on heart disease, vascular disease, and obesity (in English and Spanish)
Wikipedia has a page on Mendelian randomization (note: Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
doi:10.1371/journal.pmed.1001765
PMCID: PMC4260795  PMID: 25490400
20.  Glycerol and Fatty Acids in Serum Predict the Development of Hyperglycemia and Type 2 Diabetes in Finnish Men 
Diabetes Care  2013;36(11):3732-3738.
OBJECTIVE
We investigated the association of fasting serum glycerol and fatty acids (FAs) as predictors for worsening of hyperglycemia and incident type 2 diabetes.
RESEARCH DESIGN AND METHODS
Cross-sectional and longitudinal analyses of the population-based METabolic Syndrome in Men (METSIM) Study included 9,398 Finnish men (mean age 57 ± 7 years). At baseline, levels of serum glycerol, free FAs (FFAs), and serum FA profile, relative to total FAs, were measured with proton nuclear magnetic resonance spectroscopy.
RESULTS
At baseline, levels of glycerol, FFAs, monounsaturated FAs, saturated FAs, and monounsaturated n-7 and -9 FAs, relative to total FAs, were increased in categories of fasting and 2-h hyperglycemia, whereas the levels of n-3 and n-6 FAs, relative to total FAs, decreased (N = 9,398). Among 4,335 men with 4.5-year follow-up data available, 276 developed type 2 diabetes. Elevated levels of glycerol, FFAs, monounsaturated FAs, and saturated and monounsaturated n-7 and -9 FAs, relative to total FAs, predicted worsening of hyperglycemia and development of incident type 2 diabetes after adjustment for confounding factors. n-6 FAs, mainly linoleic acid (LA), relative to total FAs, were associated with reduced risk for the worsening of hyperglycemia and conversion to type 2 diabetes.
CONCLUSIONS
Our large population-based study shows that fasting serum levels of glycerol, FFAs, monounsaturated FAs, saturated FAs, and n-7 and -9 FAs are biomarkers for an increased risk of development of hyperglycemia and type 2 diabetes, whereas high levels of serum n-6 FAs, reflecting dietary intake of LA, were associated with reduced risk for hyperglycemia and type 2 diabetes.
doi:10.2337/dc13-0800
PMCID: PMC3816902  PMID: 24026559
21.  Association of Ketone Body Levels With Hyperglycemia and Type 2 Diabetes in 9,398 Finnish Men 
Diabetes  2013;62(10):3618-3626.
We investigated the association of the levels of ketone bodies (KBs) with hyperglycemia and with 62 genetic risk variants regulating glucose levels or type 2 diabetes in the population-based Metabolic Syndrome in Men (METSIM) study, including 9,398 Finnish men without diabetes or newly diagnosed type 2 diabetes. Increasing fasting and 2-h plasma glucose levels were associated with elevated levels of acetoacetate (AcAc) and β-hydroxybutyrate (BHB). AcAc and BHB predicted an increase in the glucose area under the curve in an oral glucose tolerance test, and AcAc predicted the conversion to type 2 diabetes in a 5-year follow-up of the METSIM cohort. Impaired insulin secretion, but not insulin resistance, explained these findings. Of the 62 single nucleotide polymorphisms associated with the risk of type 2 diabetes or hyperglycemia, the glucose-increasing C allele of GCKR significantly associated with elevated levels of fasting BHB levels. Adipose tissue mRNA expression levels of genes involved in ketolysis were significantly associated with insulin sensitivity (Matsuda index). In conclusion, high levels of KBs predicted subsequent worsening of hyperglycemia, and a common variant of GCKR was significantly associated with BHB levels.
doi:10.2337/db12-1363
PMCID: PMC3781437  PMID: 23557707
22.  Patients with type 1 diabetes show signs of vascular dysfunction in response to multiple high-fat meals 
Background
A high-fat diet promotes postprandial systemic inflammation and metabolic endotoxemia. We investigated the effects of three consecutive high-fat meals on endotoxemia, inflammation, vascular function, and postprandial lipid metabolism in patients with type 1 diabetes.
Methods
Non-diabetic controls (n = 34) and patients with type 1 diabetes (n = 37) were given three high-caloric, fat-containing meals during one day. Blood samples were drawn at fasting (8:00) and every two hours thereafter until 18:00. Applanation tonometry was used to assess changes in the augmentation index during the investigation day.
Results
Three consecutive high-fat meals had only a modest effect on serum LPS-activity levels and inflammatory markers throughout the day in both groups. Of note, patients with type 1 diabetes were unable to decrease the augmentation index in response to the high-fat meals. The most profound effects of the consecutive fat loads were seen in chylomicron and HDL-metabolism. The triglyceride-rich lipoprotein remnant marker, apoB-48, was elevated in patients compared to controls both at fasting (p = 0.014) and postprandially (p = 0.035). The activities of the HDL-associated enzymes PLTP (p < 0.001), and CETP (p = 0.007) were higher and paraoxonase (PON-1) activity, an anti-oxidative enzyme bound to HDL, decreased in patients with type 1 diabetes (p = 0.027).
Conclusions
In response to high-fat meals, early signs of vascular dysfunction alongside accumulation of chylomicron remnants, higher augmentation index, and decreased PON-1 activity were observed in patients with type 1 diabetes. The high-fat meals had no significant impact on postprandial LPS-activity in non-diabetic subjects or patients with type 1 diabetes suggesting that metabolic endotoxemia may be more central in patients with chronic metabolic disturbances such as obesity, type 2 diabetes, or diabetic kidney disease.
doi:10.1186/1743-7075-11-28
PMCID: PMC4067102  PMID: 24959195
High-fat diet; Vascular dysfunction; Type 1 diabetes
23.  Genome metabolome integrated network analysis to uncover connections between genetic variants and complex traits: an application to obesity 
Current studies of phenotype diversity by genome-wide association studies (GWAS) are mainly focused on identifying genetic variants that influence level changes of individual traits without considering additional alterations at the system-level. However, in addition to level alterations of single phenotypes, differences in association between phenotype levels are observed across different physiological states. Such differences in molecular correlations between states can potentially reveal information about the system state beyond that reported by changes in mean levels alone. In this study, we describe a novel methodological approach, which we refer to as genome metabolome integrated network analysis (GEMINi) consisting of a combination of correlation network analysis and genome-wide correlation study. The proposed methodology exploits differences in molecular associations to uncover genetic variants involved in phenotype variation. We test the performance of the GEMINi approach in a simulation study and illustrate its use in the context of obesity and detailed quantitative metabolomics data on systemic metabolism. Application of GEMINi revealed a set of metabolic associations which differ between normal and obese individuals. While no significant associations were found between genetic variants and body mass index using a standard GWAS approach, further investigation of the identified differences in metabolic association revealed a number of loci, several of which have been previously implicated with obesity-related processes. This study highlights the advantage of using molecular associations as an alternative phenotype when studying the genetic basis of complex traits and diseases.
doi:10.1098/rsif.2013.0908
PMCID: PMC3973353  PMID: 24573330
correlation analysis; differential networks; genome-wide association analysis; metabolomics; GEMINi
24.  Upstream Transcription Factor 1 (USF1) allelic variants regulate lipoprotein metabolism in women and USF1 expression in atherosclerotic plaque 
Scientific Reports  2014;4:4650.
Upstream transcription factor 1 (USF1) allelic variants significantly influence future risk of cardiovascular disease and overall mortality in females. We investigated sex-specific effects of USF1 gene allelic variants on serum indices of lipoprotein metabolism, early markers of asymptomatic atherosclerosis and their changes during six years of follow-up. In addition, we investigated the cis-regulatory role of these USF1 variants in artery wall tissues in Caucasians. In the Cardiovascular Risk in Young Finns Study, 1,608 participants (56% women, aged 31.9 ± 4.9) with lipids and cIMT data were included. For functional study, whole genome mRNA expression profiling was performed in 91 histologically classified atherosclerotic samples. In females, serum total, LDL cholesterol and apoB levels increased gradually according to USF1 rs2516839 genotypes TT < CT < CC and rs1556259 AA < AG < GG as well as according to USF1 H3 (GCCCGG) copy number 0 < 1 < 2. Furthermore, the carriers of minor alleles of rs2516839 (C) and rs1556259 (G) of USF1 gene had decreased USF1 expression in atherosclerotic plaques (P = 0.028 and 0.08, respectively) as compared to non-carriers. The genetic variation in USF1 influence USF1 transcript expression in advanced atherosclerosis and regulates levels and metabolism of circulating apoB and apoB-containing lipoprotein particles in sex-dependent manner, but is not a major determinant of early markers of atherosclerosis.
doi:10.1038/srep04650
PMCID: PMC3983598  PMID: 24722012
25.  Assessing multivariate gene-metabolome associations with rare variants using Bayesian reduced rank regression 
Bioinformatics  2014;30(14):2026-2034.
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: samuli.ripatti@helsinki.fi; samuel.kaski@aalto.fi
Supplementary information: Supplementary data are available at Bioinformatics online.
doi:10.1093/bioinformatics/btu140
PMCID: PMC4080737  PMID: 24665129

Results 1-25 (53)