Struchalin, M.V.

Plasma phosphatidylcholine and sphingomyelin concentrations are associated with depression and anxiety symptoms in a Dutch family-based lipidomics study (Article)

2012-12-03T00:00:00Z

The central nervous system has the second highest concentration of lipids after adipose tissue. Alterations in neural membrane phospho- and sphingolipid composition can influence crucial intra- and intercellular signalling and alter the membrane's properties. Recently, the polyunsaturated fatty acids (PUFA) hypothesis for depression suggests that phospho- and sphingolipid metabolism includes potential pathways for the disease. In 742 people from a Dutch family-based study, we assessed the relationships between 148 different plasma phospho- and sphingolipid species and depression/anxiety symptoms as measured by the Hospital Anxiety and Depression Scales (HADS-A and HADS-D) and the Centre for Epidemiological Studies Depression Scale (CES-D). We observed significant differences in plasma sphingomyelins (SPM), particularly the SPM 23:1/SPM 16:0 ratio, which was inversely correlated with depressive symptom scores. We observed a similar trend for plasma phosphatidylcholines (PC), particularly the molar proportion of PC O 36:4 and its ratio to ceramide CER 20:0. Absolute levels of PC O 36:4 were also associated with depression symptoms in an independent replication. To our knowledge this is the first study on depressive symptoms that focuses on specific phospho- and sphingolipid molecules in plasma rather than total PUFA concentrations. The findings of this lipidomic study suggests that plasma sphingomyelins and ether phospholipids should be further studied for their potential as biomarkers and for a better understanding of the underlying mechanisms of this systemic disease.

Genome-wide association and functional follow-up reveals new loci for kidney function (Article)

2012-03-01T00:00:00Z

Chronic kidney disease (CKD) is an important public health problem with a genetic component. We performed genome-wide association studies in up to 130,600 European ancestry participants overall, and stratified for key CKD risk factors. We uncovered 6 new loci in association with estimated glomerular filtration rate (eGFR), the primary clinical measure of CKD, in or near MPPED2, DDX1, SLC47A1, CDK12, CASP9, and INO80. Morpholino knockdown of mpped2 and casp9 in zebrafish embryos revealed podocyte and tubular abnormalities with altered dextran clearance, suggesting a role for these genes in renal function. By providing new insights into genes that regulate renal function, these results could further our understanding of the pathogenesis of CKD.

An R package "VariABEL" for genome-wide searching of potentially interacting loci by testing genotypic variance heterogeneity (Article)

2012-01-24T00:00:00Z

Background: Hundreds of new loci have been discovered by genome-wide association studies of human traits. These studies mostly focused on associations between single locus and a trait. Interactions between genes and between genes and environmental factors are of interest as they can improve our understanding of the genetic background underlying complex traits. Genome-wide testing of complex genetic models is a computationally demanding task. Moreover, testing of such models leads to multiple comparison problems that reduce the probability of new findings. Assuming that the genetic model underlying a complex trait can include hundreds of genes and environmental factors, testing of these models in genome-wide association studies represent substantial difficulties.We and Pare with colleagues (2010) developed a method allowing to overcome such difficulties. The method is based on the fact that loci which are involved in interactions can show genotypic variance heterogeneity of a trait. Genome-wide testing of such heterogeneity can be a fast scanning approach which can point to the interacting genetic variants.Results: In this work we present a new method, SVLM, allowing for variance heterogeneity analysis of imputed genetic variation. Type I error and power of this test are investigated and contracted with these of the Levene's test. We also present an R package, VariABEL, implementing existing and newly developed tests.Conclusions: Variance heterogeneity analysis is a promising method for detection of potentially interacting loci. New method and software package developed in this work will facilitate such analysis in genome-wide context.

Detecting low frequent loss-of-function alleles in genome wide association studies with red hair color as example (Article)

2011-11-29T00:00:00Z

Multiple loss-of-function (LOF) alleles at the same gene may influence a phenotype not only in the homozygote state when alleles are considered individually, but also in the compound heterozygote (CH) state. Such LOF alleles typically have low frequencies and moderate to large effects. Detecting such variants is of interest to the genetics community, and relevant statistical methods for detecting and quantifying their effects are sorely needed. We present a collapsed double heterozygosity (CDH) test to detect the presence of multiple LOF alleles at a gene. When causal SNPs are available, which may be the case in next generation genome sequencing studies, this CDH test has overwhelmingly higher power than single SNP analysis. When causal SNPs are not directly available such as in current GWA settings, we show the CDH test has higher power than standard single SNP analysis if tagging SNPs are in linkage disequilibrium with the underlying causal SNPs to at least a moderate degree (r2>0.1). The test is implemented for genome-wide analysis in the publically available software package GenABEL which is based on a sliding window approach. We provide the proof of principle by conducting a genome-wide CDH analysis of red hair color, a trait known to be influenced by multiple loss-of-function alleles, in a total of 7,732 Dutch individuals with hair color ascertained. The association signals at the MC1R gene locus from CDH were uniformly more significant than traditional GWA analyses (the most significant P for CDH = 3.11×10-142vs. P for rs258322 = 1.33×10-66). The CDH test will contribute towards finding rare LOF variants in GWAS and sequencing studies.

A genome-wide screen for interactions reveals a new locus on 4p15 modifying the effect of waist-to-hip ratio on total cholesterol (Article)

2011-10-01T00:00:00Z

Recent genome-wide association (GWA) studies described 95 loci controlling serum lipid levels. These common variants explain ~25% of the heritability of the phenotypes. To date, no unbiased screen for gene-environment interactions for circulating lipids has been reported. We screened for variants that modify the relationship between known epidemiological risk factors and circulating lipid levels in a meta-analysis of genome-wide association (GWA) data from 18 population-based cohorts with European ancestry (maximum N = 32,225). We collected 8 further cohorts (N = 17,102) for replication, and rs6448771 on 4p15 demonstrated genome-wide significant interaction with waist-to-hip-ratio (WHR) on total cholesterol (TC) with a combined P-value of 4.79×10-9. There were two potential candidate genes in the region, PCDH7 and CCKAR, with differential expression levels for rs6448771 genotypes in adipose tissue. The effect of WHR on TC was strongest for individuals carrying two copies of G allele, for whom a one standard deviation (sd) difference in WHR corresponds to 0.19 sd difference in TC concentration, while for A allele homozygous the difference was 0.12 sd. Our findings may open up possibilities for targeted intervention strategies for people characterized by specific genomic profiles. However, more refined measures of both body-fat distribution and metabolic measures are needed to understand how their joint dynamics are modified by the newly found locus.

Genetic variants influencing circulating lipid levels and risk of coronary artery disease (Article)

2010-11-01T00:00:00Z

OBJECTIVE-: Genetic studies might provide new insights into the biological mechanisms underlying lipid metabolism and risk of CAD. We therefore conducted a genome-wide association study to identify novel genetic determinants of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides. METHODS AND RESULTS-: We combined genome-wide association data from 8 studies, comprising up to 17 723 participants with information on circulating lipid concentrations. We did independent replication studies in up to 37 774 participants from 8 populations and also in a population of Indian Asian descent. We also assessed the association between single-nucleotide polymorphisms (SNPs) at lipid loci and risk of CAD in up to 9 633 cases and 38 684 controls. We identified 4 novel genetic loci that showed reproducible associations with lipids (probability values, 1.6×10-8to 3.1×10-10). These include a potentially functional SNP in the SLC39A8 gene for HDL-C, an SNP near the MYLIP/GMPR and PPP1R3B genes for LDL-C, and at the AFF1 gene for triglycerides. SNPs showing strong statistical association with 1 or more lipid traits at the CELSR2, APOB, APOE-C1-C4-C2 cluster, LPL, ZNF259-APOA5-A4-C3-A1 cluster and TRIB1 loci were also associated with CAD risk (probability values, 1.1×10-3to 1.2×10-9). CONCLUSION-: We have identified 4 novel loci associated with circulating lipids. We also show that in addition to those that are largely associated with LDL-C, genetic loci mainly associated with circulating triglycerides and HDL-C are also associated with risk of CAD. These findings potentially provide new insights into the biological mechanisms underlying lipid metabolism and CAD risk.

Variance heterogeneity analysis for detection of potentially interacting genetic loci: Method and its limitations (Article)

2010-10-13T00:00:00Z

Background: Presence of interaction between a genotype and certain factor in determination of a trait's value, it is expected that the trait's variance is increased in the group of subjects having this genotype. Thus, test of heterogeneity of variances can be used as a test to screen for potentially interacting single-nucleotide polymorphisms (SNPs). In this work, we evaluated statistical properties of variance heterogeneity analysis in respect to the detection of potentially interacting SNPs in a case when an interaction variable is unknown.Results: Through simulations, we investigated type I error for Bartlett's test, Bartlett's test with prior rank transformation of a trait to normality, and Levene's test for different genetic models. Additionally, we derived an analytical expression for power estimation. We showed that Bartlett's test has acceptable type I error in the case of trait following a normal distribution, whereas Levene's test kept nominal Type I error under all scenarios investigated. For the power of variance homogeneity test, we showed (as opposed to the power of direct test which uses information about known interacting factor) that, given the same interaction effect, the power can vary widely depending on the non-estimable direct effect of the unobserved interacting variable. Thus, for a given interaction effect, only very wide limits of power of the variance homogeneity test can be estimated. Also we applied Levene's approach to test genome-wide homogeneity of variances of the C-reactive protein in the Rotterdam Study population (n = 5959). In this analysis, we replicate previous results of Pare and colleagues (2010) for the SNP rs12753193 (n = 21, 799).Conclusions: Screening for differences in variances among genotypes of a SNP is a promising approach as a number of biologically interesting models may lead to the heterogeneity of variances. However, it should be kept in mind that the absence of variance heterogeneity for a SNP can not be interpreted as the absence of involvement of the SNP in the interaction network.

A genome-wide association study identifies a susceptibility locus for refractive errors and myopia at 15q14 (Letter To Editor)

2010-09-01T00:00:00Z

Refractive errors are the most common ocular disorders worldwide and may lead to blindness. Although this trait is highly heritable, identification of susceptibility genes has been challenging. We conducted a genome-wide association study for refractive error in 5,328 individuals from a Dutch population-based study with replication in four independent cohorts (combined 10,280 individuals in the replication stage). We identified a significant association at chromosome 15q14 (rs634990, P = 2.21 × 10−14). The odds ratio of myopia compared to hyperopia for the minor allele (minor allele frequency = 0.47) was 1.41 (95% CI 1.16–1.70) for individuals heterozygous for the allele and 1.83 (95% CI 1.42–2.36) for individuals homozygous for the allele. The associated locus is near two genes that are expressed in the retina, GJD2 and ACTC1, and appears to harbor regulatory elements which may influence transcription of these genes. Our data suggest that common variants at 15q14 influence susceptibility for refractive errors in the general population.

A genome-wide association study identifies a susceptibility locus for refractive errors and myopia at 15q14 (Letter To Editor)

2010-09-01T00:00:00Z

ProbABEL package for genome-wide association analysis of imputed data (Article)

2010-03-16T00:00:00Z

Background: Over the last few years, genome-wide association (GWA) studies became a tool of choice for the identification of loci associated with complex traits. Currently, imputed single nucleotide polymorphisms (SNP) data are frequently used in GWA analyzes. Correct analysis of imputed data calls for the implementation of specific methods which take genotype imputation uncertainty into account.Results: We developed the ProbABEL software package for the analysis of genome-wide imputed SNP data and quantitative, binary, and time-till-event outcomes under linear, logistic, and Cox proportional hazards models, respectively. For quantitative traits, the package also implements a fast two-step mixed model-based score test for association in samples with differential relationships, facilitating analysis in family-based studies, studies performed in human genetically isolated populations and outbred animal populations.Conclusions: ProbABEL package provides fast efficient way to analyze imputed data in genome-wide context and will facilitate future identification of complex trait loci.

Genome-wide association studies of mri-defined brain infarcts: Meta-analysis from the charge consortium (Article)

2010-02-01T00:00:00Z

Background and Purpose-Previous studies examining genetic associations with MRI-defined brain infarct have yielded inconsistent findings. We investigated genetic variation underlying covert MRI infarct in persons without histories of transient ischemic attack or stroke. We performed meta-analysis of genome-wide association studies of white participants in 6 studies comprising the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium. Methods-Using 2.2 million genotyped and imputed single nucleotide polymorphisms, each study performed crosssectional genome-wide association analysis of MRI infarct using age- and sex-adjusted logistic regression models. Study-specific findings were combined in an inverse-variance-weighted meta-analysis, including 9401 participants with mean age 69.7 (19.4% of whom had 1 MRI infarct). Results-The most significant association was found with rs2208454 (minor allele frequency, 20%), located in intron 3 of MACRO domain containing 2 gene and in the downstream region of fibronectin leucine-rich transmembrane protein 3 gene. Each copy of the minor allele was associated with lower risk of MRI infarcts (odds ratio, 0.76; 95% confidence interval, 0.68-0.84; P4.64107). Highly suggestive associations (P1.0105) were also found for 22 other single nucleotide polymorphisms in linkage disequilibrium (r20.64) with rs2208454. The association with rs2208454 did not replicate in independent samples of 1822 white and 644 black participants, although 4 single nucleotide polymorphisms within 200 kb from rs2208454 were associated with MRI infarcts in the black population sample. Conclusions-This first community-based, genome-wide association study on covert MRI infarcts uncovered novel associations. Although replication of the association with top single nucleotide polymorphisms failed, possibly because of insufficient power, results in the black population sample are encouraging, and further efforts at replication are needed.

A study of the SORL1 Gene in Alzheimer's disease and cognitive function (Article)

2009-09-21T00:00:00Z

Several studies have investigated the role of the neuronal sortilin-related receptor (SORL1) gene in Alzheimer's disease (AD), but findings have been inconsistent. We conducted a study of 7 single nucleotide polymorphisms (SNPs), rs668387, rs689021, rs641120, rs1699102, rs3824968, rs2282649, and rs1010159, in the SORL1 gene that were associated to AD in previous studies. We tested for association with AD and cognitive function in 6741 participants of the Rotterdam Study and in 2883 individuals from the Erasmus Rucphen Family study. We performed meta-analyses on AD using our data together with those of previous studies published prior to September 2008 in Caucasians. Further, we studied up to 76 SNPs in a 400 kb region within and flanking the gene to evaluate the evidence that other genetic variants are associated with AD or cognitive function. There was no significant evidence for association between SORL1 SNPs and incident AD patients in the Rotterdam Study. In a meta-analysis of our data with those of others, six out of seven SNPs attained borderline significance. However, removal of the first study reporting association from the meta-analysis resulted in non-significant odds ratios for all SNPs. SNPs rs668387, rs689021, and rs641120 were associated with cognitive function in non-demented individuals at borderline statistical significance in two independent Dutch cohorts, but in the opposite direction. Testing for association using dense SNPs in the SORL1 gene did not reveal significant association with AD, or with cognitive function when adjusting for multiple testing. In conclusion, our data do not support the hypothesis that genetic variants in SORL1 are related to the risk of AD.

Genetic variants associated with cardiac structure and function: A meta-analysis and replication of genome-wide association data (Article)

2009-07-08T00:00:00Z

Context: Echocardiographic measures of left ventricular (LV) structure and function are heritable phenotypes of cardiovascular disease. Objective: To identify common genetic variants associated with cardiac structure and function by conducting a meta-analysis of genome-wide association data in 5 population-based cohort studies (stage 1) with replication (stage 2) in 2 other community-based samples. Design, Setting, and Participants: Within each of 5 community-based cohorts comprising the EchoGen consortium (stage 1; n=12 612 individuals of European ancestry; 55% women, aged 26-95 years; examinations between 1978-2008), we estimated the association between approximately 2.5 million single-nucleotide polymorphisms (SNPs; imputed to the HapMap CEU panel) and echocardiographic traits. In stage 2, SNPs significantly associated with traits in stage 1 were tested for association in 2 other cohorts (n=4094 people of European ancestry). Using a prespecified P value threshold of 5 x 10-7to indicate genome-wide significance, we performed an inverse variance-weighted fixed-effects meta-analysis of genome-wide association data from each cohort. Main Outcome Measures: Echocardiographic traits: LV mass, internal dimensions, wall thickness, systolic dysfunction, aortic root, and left atrial size. Results: In stage 1, 16 genetic loci were associated with 5 echocardiographic traits: 1 each with LV internal dimensions and systolic dysfunction, 3 each with LV mass and wall thickness, and 8 with aortic root size. In stage 2, 5 loci replicated (6q22 locus associated with LV diastolic dimensions, explaining <1%of trait variance; 5q23, 12p12, 12q14, and 17p13 associated with aortic root size, explaining 1%-3% of trait variance). Conclusions: We identified 5 genetic loci harboring common variants that were associated with variation in LV diastolic dimensions and aortic root size, but such findings explained a very small proportion of variance. Further studies are required to replicate these findings, identify the causal variants at or near these loci, characterize their functional significance, and determine whether they are related to overt cardiovascular disease.

NRXN3Is a novel locus for waist circumference: A genome-wide association study from the CHARGE consortium (Article)

2009-06-01T00:00:00Z

Central abdominal fat is a strong risk factor for diabetes and cardiovascular disease. To identify common variants influencing central abdominal fat, we conducted a two-stage genome-wide association analysis for waist circumference (WC). In total, three loci reached genome-wide significance. In stage 1, 31,373 individuals of Caucasian descent from eight cohort studies confirmed the role of FTO and MC4R and identified one novel locus associated with WC in the neurexin 3 gene [NRXN3 (rs10146997, p = 6.4×10 -7)]. The association with NRXN3 was confirmed in stage 2 by combining stage 1 results with those from 38,641 participants in the GIANT consortium (p = 0.009 in GIANT only, p = 5.3×10-8 for combined analysis, n = 70,014). Mean WC increase per copy of the G allele was 0.0498 z-score units (0.65 cm). This SNP was also associated with body mass index (BMI) [p = 7.4×10-6, 0.024 z-score units (0.10 kg/m2) per copy of the G allele] and the risk of obesity (odds ratio 1.13, 95% CI 1.07-1.19; p = 3.2×10-5 per copy of the G allele). The NRXN3 gene has been previously implicated in addiction and reward behavior, lending further evidence that common forms of obesity may be a central nervous system-mediated disorder. Our findings establish that common variants in NRXN3 are associated with WC, BMI, and obesity.

Linkage analysis of adult height in a large pedigree from a Dutch genetically isolated population (Article)

2009-05-25T00:00:00Z

Despite extensive research of genetic determinants of human adult height, the genes identified up until now allow to predict only a small proportion of the trait's variance. To identify new genes we analyzed 2,486 genotyped and phenotyped individuals in a large pedigree including 23,612 members in 18 generations. The pedigree was derived from a young genetically isolated Dutch population, where genetic heterogeneity is expected to be low and linkage disequilibrium has been shown to be increased. Complex segregation analysis confirmed high heritability of adult height, and suggested mixed model of height inheritance in this population. The estimates of the model parameters obtained from complex segregation analysis were used in parametric linkage analysis, which highlighted three genome-wide significant and additionally at least four suggestive loci involved in height. Significant peaks were located at the chromosomal regions 1p32 (LOD score = 3.35), 2p16 (LOD score = 3.29) and 16q24 (LOD score = 3.94). For the latter region, a strong association signal (FDR q < 0.05) was obtained for 19 SNPs, 17 of them were located in the CDH13 (cadherin 13) gene of which one (rs1035569) explained 1.5% of the total height variance.

Genomewide association studies of stroke (Article)

2009-04-23T00:00:00Z

BACKGROUND: The genes underlying the risk of stroke in the general population remain undetermined. METHODS: We carried out an analysis of genomewide association data generated from four large cohorts composing the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, including 19,602 white persons (mean [±SD] age, 63±8 years) in whom 1544 incident strokes (1164 ischemic strokes) developed over an average follow-up of 11 years. We tested the markers most strongly associated with stroke in a replication cohort of 2430 black persons with 215 incident strokes (191 ischemic strokes), another cohort of 574 black persons with 85 incident strokes (68 ischemic strokes), and 652 Dutch persons with ischemic stroke and 3613 unaffected persons. RESULTS: Two intergenic single-nucleotide polymorphisms on chromosome 12p13 and within 11 kb of the gene NINJ2 were associated with stroke (P<5×10-8). NINJ2 encodes an adhesion molecule expressed in glia and shows increased expression after nerve injury. Direct genotyping showed that rs12425791 was associated with an increased risk of total (i.e., all types) and ischemic stroke, with hazard ratios of 1.30 (95% confidence interval [CI], 1.19 to 1.42) and 1.33 (95% CI, 1.21 to 1.47), respectively, yielding population attributable risks of 11% and 12% in the discovery cohorts. Corresponding hazard ratios were 1.35 (95% CI, 1.01 to 1.79; P = 0.04) and 1.42 (95% CI, 1.06 to 1.91; P = 0.02) in the large cohort of black persons and 1.17 (95% CI, 1.01 to 1.37; P = 0.03) and 1.19 (95% CI, 1.01 to 1.41; P = 0.04) in the Dutch sample; the results of an underpowered analysis of the smaller black cohort were nonsignificant. CONCLUSIONS: A genetic locus on chromosome 12p13 is associated with an increased risk of stroke.

Predicting human height by Victorian and genomic methods (Article)

2009-02-24T00:00:00Z

In the Victorian era, Sir Francis Galton showed that 'when dealing with the transmission of stature from parents to children, the average height of the two parents, ... is all we need care to know about them' (1886). One hundred and twenty-two years after Galton's work was published, 54 loci showing strong statistical evidence for association to human height were described, providing us with potential genomic means of human height prediction. In a population-based study of 5748 people, we find that a 54-loci genomic profile explained 4-6% of the sex- and age-adjusted height variance, and had limited ability to discriminate tall/short people, as characterized by the area under the receiver-operating characteristic curve (AUC). In a family-based study of 550 people, with both parents having height measurements, we find that the Galtonian mid-parental prediction method explained 40% of the sex- and age-adjusted height variance, and showed high discriminative accuracy. We have also explored how much variance a genomic profile should explain to reach certain AUC values. For highly heritable traits such as height, we conclude that in applications in which parental phenotypic information is available (eg, medicine), the Victorian Galton's method will long stay unsurpassed, in terms of both discriminative accuracy and costs. For less heritable traits, and in situations in which parental information is not available (eg, forensics), genomic methods may provide an alternative, given that the variants determining an essential proportion of the trait's variation can be identified.