Tatiana I. Axenovich

Genetic determinants of circulating sphingolipid concentrations in European populations

Sphingolipids have essential roles as structural components of cell membranes and in cell signalling, and disruption of their metabolism causes several diseases, with diverse neurological, psychiatric, and metabolic consequences. Increasingly, variants within a few of the genes that encode enzymes involved in sphingolipid metabolism are being associated with complex disease phenotypes. Direct experimental evidence supports a role of specific sphingolipid species in several common complex chronic disease processes including atherosclerotic plaque formation, myocardial infarction (MI), cardiomyopathy, pancreatic β-cell failure, insulin resistance, and type 2 diabetes mellitus. Therefore, sphingolipids represent novel and important intermediate phenotypes for genetic analysis, yet little is known about the major genetic variants that influence their circulating levels in the general population. We performed a genome-wide association study (GWAS) between 318,237 single-nucleotide polymorphisms (SNPs) and levels of circulating sphingomyelin (SM), dihydrosphingomyelin (Dih-SM), ceramide (Cer), and glucosylceramide (GluCer) single lipid species (33 traits); and 43 matched metabolite ratios measured in 4,400 subjects from five diverse European populations. Associated variants (32) in five genomic regions were identified with genome-wide significant corrected p-values ranging down to 9.08×10−66. The strongest associations were observed in or near 7 genes functionally involved in ceramide biosynthesis and trafficking: SPTLC3, LASS4, SGPP1, ATP10D, and FADS1–3. Variants in 3 loci (ATP10D, FADS3, and SPTLC3) associate with MI in a series of three German MI studies. An additional 70 variants across 23 candidate genes involved in sphingolipid-metabolizing pathways also demonstrate association (p = 10−4 or less). Circulating concentrations of several key components in sphingolipid metabolism are thus under strong genetic control, and variants in these loci can be tested for a role in the development of common cardiovascular, metabolic, neurological, and psychiatric diseases.

Genome-Wide Association Study Identifies Novel Loci Associated with Circulating Phospho- and Sphingolipid Concentrations

Phospho- and sphingolipids are crucial cellular and intracellular compounds. These lipids are required for active transport, a number of enzymatic processes, membrane formation, and cell signalling. Disruption of their metabolism leads to several diseases, with diverse neurological, psychiatric, and metabolic consequences. A large number of phospholipid and sphingolipid species can be detected and measured in human plasma. We conducted a meta-analysis of five European family-based genome-wide association studies (N = 4034) on plasma levels of 24 sphingomyelins (SPM), 9 ceramides (CER), 57 phosphatidylcholines (PC), 20 lysophosphatidylcholines (LPC), 27 phosphatidylethanolamines (PE), and 16 PE-based plasmalogens (PLPE), as well as their proportions in each major class. This effort yielded 25 genome-wide significant loci for phospholipids (smallest P-value = 9.88×10−204) and 10 loci for sphingolipids (smallest P-value = 3.10×10−57). After a correction for multiple comparisons (P-value<2.2×10−9), we observed four novel loci significantly associated with phospholipids (PAQR9, AGPAT1, PKD2L1, PDXDC1) and two with sphingolipids (PLD2 and APOE) explaining up to 3.1% of the variance. Further analysis of the top findings with respect to within class molar proportions uncovered three additional loci for phospholipids (PNLIPRP2, PCDH20, and ABDH3) suggesting their involvement in either fatty acid elongation/saturation processes or fatty acid specific turnover mechanisms. Among those, 14 loci (KCNH7, AGPAT1, PNLIPRP2, SYT9, FADS1-2-3, DLG2, APOA1, ELOVL2, CDK17, LIPC, PDXDC1, PLD2, LASS4, and APOE) mapped into the glycerophospholipid and 12 loci (ILKAP, ITGA9, AGPAT1, FADS1-2-3, APOA1, PCDH20, LIPC, PDXDC1, SGPP1, APOE, LASS4, and PLD2) to the sphingolipid pathways. In large meta-analyses, associations between FADS1-2-3 and carotid intima media thickness, AGPAT1 and type 2 diabetes, and APOA1 and coronary artery disease were observed. In conclusion, our study identified nine novel phospho- and sphingolipid loci, substantially increasing our knowledge of the genetic basis for these traits.

A Genomewide Screen for Late-Onset Alzheimer Disease in a Genetically Isolated Dutch Population

Alzheimer disease (AD) is the most common cause of dementia. We conducted a genome screen of 103 patients with late-onset AD who were ascertained as part of the Genetic Research in Isolated Populations (GRIP) program that is conducted in a recently isolated population from the southwestern area of The Netherlands. All patients and their 170 closely related relatives were genotyped using 402 microsatellite markers. Extensive genealogy information was collected, which resulted in an extremely large and complex pedigree of 4,645 members. The pedigree was split into 35 subpedigrees, to reduce the computational burden of linkage analysis. Simulations aiming to evaluate the effect of pedigree splitting on false-positive probabilities showed that a LOD score of 3.64 corresponds to 5% genomewide type I error. Multipoint analysis revealed four significant and one suggestive linkage peaks. The strongest evidence of linkage was found for chromosome 1q21 (heterogeneity LOD [HLOD]=5.20 at marker D1S498). Approximately 30 cM upstream of this locus, we found another peak at 1q25 (HLOD=4.0 at marker D1S218). These two loci are in a previously established linkage region. We also confirmed the AD locus at 10q22-24 (HLOD=4.15 at marker D10S185). There was significant evidence of linkage of AD to chromosome 3q22-24 (HLOD=4.44 at marker D3S1569). For chromosome 11q24-25, there was suggestive evidence of linkage (HLOD=3.29 at marker D11S1320). We next tested for association between cognitive function and 4,173 single-nucleotide polymorphisms in the linked regions in an independent sample consisting of 197 individuals from the GRIP region. After adjusting for multiple testing, we were able to detect significant associations for cognitive function in four of five AD-linked regions, including the new region on chromosome 3q22-24 and regions 1q25, 10q22-24, and 11q25. With use of cognitive function as an endophenotype of AD, our study indicates the that the RGSL2, RALGPS2, and C1orf49 genes are the potential disease-causing genes at 1q25. Our analysis of chromosome 10q22-24 points to the HTR7, MPHOSPH1, and CYP2C cluster. This is the first genomewide screen that showed significant linkage to chromosome 3q23 markers. For this region, our analysis identified the NMNAT3 and CLSTN2 genes. Our findings confirm linkage to chromosome 11q25. We were unable to confirm SORL1; instead, our analysis points to the OPCML and HNT genes.

Predicting human height by Victorian and genomic methods

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 Galtons 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 Galtons 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 traits variation can be identified.

Rapid variance components-based method for whole-genome association analysis.

The variance component tests used in genome-wide association studies (GWAS) including large sample sizes become computationally exhaustive when the number of genetic markers is over a few hundred thousand. We present an extremely fast variance components–based two-step method, GRAMMAR-Gamma, developed as an analytical approximation within a framework of the score test approach. Using simulated and real human GWAS data sets, we show that this method provides unbiased estimates of the SNP effect and has a power close to that of the likelihood ratio test–based method. The computational complexity of our method is close to its theoretical minimum, that is, to the complexity of the analysis that ignores genetic structure. The running time of our method linearly depends on sample size, whereas this dependency is quadratic for other existing methods. Simulations suggest that GRAMMAR-Gamma may be used for association testing in whole-genome resequencing studies of large human cohorts.

Common variants in the JAZF1 gene associated with height identified by linkage and genome-wide association analysis

Genes for height have gained interest for decades, but only recently have candidate genes started to be identified. We have performed linkage analysis and genome-wide association for height in approximately 4000 individuals from five European populations. A total of five chromosomal regions showed suggestive linkage and in one of these regions, two SNPs (rs849140 and rs1635852) were associated with height (nominal P = 7.0 x 10(-8) and P = 9.6 x 10(-7), respectively). In total, five SNPs across the genome showed an association with height that reached the threshold of genome-wide significance (nominal P < 1.6 x 10(-7)). The association with height was replicated for two SNPs (rs1635852 and rs849140) using three independent studies (n = 31 077, n=1268 and n = 5746) with overall meta P-values of 9.4 x 10(-10) and 5.3 x 10(-8). These SNPs are located in the JAZF1 gene, which has recently been associated with type II diabetes, prostate and endometrial cancer. JAZF1 is a transcriptional repressor of NR2C2, which results in low IGF1 serum concentrations, perinatal and early postnatal hypoglycemia and growth retardation when knocked out in mice. Both the linkage and association analyses independently identified the JAZF1 region affecting human height. We have demonstrated, through replication in additional independent populations, the consistency of the effect of the JAZF1 SNPs on height. Since this gene also has a key function in the metabolism of growth, JAZF1 represents one of the strongest candidates influencing human height identified so far.

Segregation analysis of idiopathic scoliosis: demonstration of a major gene effect.

Segregation analysis using a model with age and gender effects was applied to 101 pedigrees ascertained through a proband with idiopathic scoliosis. The transmission probability model was used to detect major gene effect. When we analyzed the pedigrees where affected status was assigned to persons with a Cobbs angle of more than 5 degrees we did not detect a significant major gene effect. However, when the affected status was assigned to persons with pronounced forms of disease only (a curve of at least 11 degrees) a significant contribution of a major causal gene could be established and inheritance could be described according to a dominant major gene diallele model, assuming incomplete sex and age dependent penetrance of genotypes. According to this model, the pronounced forms of idiopathic scoliosis should never occur in the absence of the mutant allele. This indicates that only the carriers of the mutant allele develop pronounced forms of the disease. At the same time, only a fraction of the carriers of the mutant gene should manifest the disease (30% of males and 50% of females).

Heritability of blood pressure traits and the genetic contribution to blood pressure variance explained by four blood-pressure-related genes.

Objective To study the heritability of four blood pressure traits and the proportion of variance explained by four blood-pressure-related genes. Methods All participants are members of an extended pedigree from a Dutch genetically isolated population. Heritability and genetic correlations of systolic blood pressure, diastolic blood pressure, mean arterial pressure and pulse pressure were assessed using a variance components approach (SOLAR). Polymorphisms of the α-adducin (ADD1), angiotensinogen (AGT), angiotensin II type 1 receptor (AT1R) and G protein β3 (GNB3) genes were typed. Results Heritability estimates were significant for all four blood pressure traits, ranging between 0.24 and 0.37. Genetic correlations between systolic blood pressure, diastolic blood pressure and mean arterial pressure were high (0.93–0.98), and those between pulse pressure and diastolic blood pressure were low (0.05). The ADD1 polymorphism explained 0.3% of the variance of pulse pressure (P = 0.07), and the polymorphism of GNB3 explained 0.4% of the variance of systolic blood pressure (P = 0.02), 0.2% of mean arterial pressure (P = 0.05) and 0.3% of pulse pressure (P = 0.06). Conclusion Genetic factors contribute to a substantial proportion of blood pressure variance. In this study, the effect of polymorphisms of ADD1, AGT, AT1R and GNB3 explained a very small proportion of the heritability of blood pressure traits. As new genes associated with blood pressure are localized in the future, their effect on blood pressure variance should be calculated.

The apolipoprotein E gene and its age-specific effects on cognitive function

The E4 allele of the apolipoprotein E gene (APOE) is a well-established determinant of Alzheimers disease but its relation to cognitive function is much less understood. We studied the age-specific effects of the APOE*E4 allele on cognitive function and cardiovascular risk factors in 2208 related individuals. APOE*E4 allele was significantly associated with reduced test scores for Adult Verbal Learning Test, particularly on the memory and learning sub domains, in persons older than 50 years of age. The effect of APOE*E4 was independent of the effect of APOE*E4 on vascular risk factors and most pronounced on learning ability. Our findings suggest that APOE*E4 has an effect on cognitive function predominantly in the elderly, independent of vascular risk factors.

An approach for cutting large and complex pedigrees for linkage analysis

Utilizing large pedigrees in linkage analysis is a computationally challenging task. The pedigree size limits applicability of the Lander–Green–Kruglyak algorithm for linkage analysis. A common solution is to split large pedigrees into smaller computable subunits. We present a pedigree-splitting method that, within a user supplied bit-size limit, identifies subpedigrees having the maximal number of subjects of interest (eg patients) who share a common ancestor. We compare our method with the maximum clique partitioning method using a large and complex human pedigree consisting of 50 patients with Alzheimers disease ascertained from genetically isolated Dutch population. We show that under a bit-size limit our method can assign more patients to subpedigrees than the clique partitioning method, particularly when splitting deep pedigrees where the subjects of interest are scattered in recent generations and are relatively distantly related via multiple genealogic connections. Our pedigree-splitting algorithm and associated software can facilitate genome-wide linkage scans searching for rare mutations in large pedigrees coming from genetically isolated populations. The software package PedCut implementing our approach is available at http://mga.bionet.nsc.ru/soft/index.html.