Genetic control of N-glycosylation of human blood plasma proteins.

Glycosylation is an important protein modification, which influences the physical and chemical properties as well as biological function of these proteins. Large-scale population studies have shown that the levels of various plasma protein N-glycans are associated with many multifactorial human diseases. Observed associations between protein glycosylation levels and human diseases have led to the conclusion that N-glycans can be considered a potential source of biomarkers and therapeutic targets. Although biochemical pathways of glycosylation are well studied, the understanding of the mechanisms underlying general and tissue-specific regulation of these biochemical reactions in vivo is limited. This complicates both the interpretation of the observed associations between protein glycosylation levels and human diseases, and the development of glycan-based biomarkers and therapeutics. By the beginning of the 2010s, high-throughput methods of N-glycome profiling had become available, allowing research into the genetic control of N-glycosylation using quantitative genetics methods, including genome-wide association studies (GWAS). Application of these methods has made it possible to find previously unknown regulators of N-glycosylation and expanded the understanding of the role of N-glycans in the control of multifactorial diseases and human complex traits. The present review considers the current knowledge of the genetic control of variability in the levels of N-glycosylation of plasma proteins in human populations. It briefly describes the most popular physical-chemical methods of N-glycome profiling and the databases that contain genes involved in the biosynthesis of N-glycans. It also reviews the results of studies of environmental and genetic factors contributing to the variability of N-glycans as well as the mapping results of the genomic loci of N-glycans by GWAS. The results of functional in vitro and in silico studies are described. The review summarizes the current progress in human glycogenomics and suggests possible directions for further research.

The GWAS-MAP|ovis platform for aggregation and analysis of genome-wide association study results in sheep.

In recent years, the number of genome-wide association studies (GWAS) carried out for various economically important animal traits has been increasing. GWAS discoveries provide summary statistics that can be used both for targeted marker-oriented selection and for studying the genetic control of economically important traits of farm animals. In contrast to research in human genetics, GWAS on farm animals often does not meet generally accepted standards (availability of information about effect and reference alleles, the size and direction of the effect, etc.). This greatly complicates the use of GWAS results for breeding needs. Within the framework of human genetics, there are several technological solutions for researching the harmonized results of GWAS, including one of the largest, the GWAS-MAP platform. For other types of living organisms, including economically important agricultural animals, there are no similar solutions. To our knowledge, no similar solution has been proposed to date for any of the species of economically important animals. As part of this work, we focused on creating a platform similar to GWAS-MAP for working with the results of GWAS of sheep, since sheep breeding is one of the most important branches of agriculture. By analogy with the GWAS-MAP platform for storing, unifying and analyzing human GWAS, we have created the GWAS-MAP|ovis platform. The platform currently contains information on more than 34 million associations between genomic sequence variants and traits of meat production in sheep. The platform can also be used to conduct colocalization analysis, a method that allows one to determine whether the association of a particular locus with two different traits is the result of pleiotropy or whether these traits are associated with different variants that are in linkage disequilibrium. This platform will be useful for breeders to select promising markers for breeding, as well as to obtain information for the introduction of genomic breeding and for scientists to replicate the results obtained.

The GWAS-MAP platform for aggregation of results of genome-wide association studies and the GWAS-MAP|homo database of 70 billion genetic associations of human traits.

Hundreds of genome-wide association studies (GWAS) of human traits are performed each year. The results of GWAS are often published in the form of summary statistics. Information from summary statistics can be used for multiple purposes - from fundamental research in biology and genetics to the search for potential biomarkers and therapeutic targets. While the amount of GWAS summary statistics collected by the scientific community is rapidly increasing, the use of this data is limited by the lack of generally accepted standards. In particular, the researchers who would like to use GWAS summary statistics in their studies have to become aware that the data are scattered across multiple websites, are presented in a variety of formats, and, often, were not quality controlled. Moreover, each available summary statistics analysis tools will ask for data to be presented in their own internal format. To address these issues, we developed GWAS-MAP, a high-throughput platform for aggregating, storing, analyzing, visualizing and providing access to a database of big data that result from region- and genome-wide association studies. The database currently contains information on more than 70 billion associations between genetic variants and human diseases, quantitative traits, and "omics" traits. The GWAS-MAP platform and database can be used for studying the etiology of human diseases, building predictive risk models and finding potential biomarkers and therapeutic interventions. In order to demonstrate a typical application of the platform as an approach for extracting new biological knowledge and establishing mechanistic hypotheses, we analyzed varicose veins, a disease affecting on average every third adult in Russia. The results of analysis confirmed known epidemiologic associations for this disease and led us to propose a hypothesis that increased levels of MICB and CD209 proteins in human plasma may increase susceptibility to varicose veins.

A network-based conditional genetic association analysis of the human metabolome.

Background: Genome-wide association studies have identified hundreds of loci that influence a wide variety of complex human traits; however, little is known regarding the biological mechanism of action of these loci. The recent accumulation of functional genomics ("omics"), including metabolomics data, has created new opportunities for studying the functional role of specific changes in the genome. Functional genomic data are characterized by their high dimensionality, the presence of (strong) statistical dependency between traits, and, potentially, complex genetic control. Therefore, the analysis of such data requires specific statistical genetics methods. Results: To facilitate our understanding of the genetic control of omics phenotypes, we propose a trait-centered, network-based conditional genetic association (cGAS) approach for identifying the direct effects of genetic variants on omics-based traits. For each trait of interest, we selected from a biological network a set of other traits to be used as covariates in the cGAS. The network can be reconstructed either from biological pathway databases (a mechanistic approach) or directly from the data, using a Gaussian graphical model applied to the metabolome (a data-driven approach). We derived mathematical expressions that allow comparison of the power of univariate analyses with conditional genetic association analyses. We then tested our approach using data from a population-based Cooperative Health Research in the region of Augsburg (KORA) study (n = 1,784 subjects, 1.7 million single-nucleotide polymorphisms) with measured data for 151 metabolites. Conclusions: We found that compared to single-trait analysis, performing a genetic association analysis that includes biologically relevant covariates can either gain or lose power, depending on specific pleiotropic scenarios, for which we provide empirical examples. In the context of analyzed metabolomics data, the mechanistic network approach had more power compared to the data-driven approach. Nevertheless, we believe that our analysis shows that neither a prior-knowledge-only approach nor a phenotypic-data-only approach is optimal, and we discuss possibilities for improvement.

Population specific analysis of Yakut exomes.

We studied the genetic diversity of the Yakut population using exome sequencing. We performed comparative analysis of the Yakut population and the populations that are included in the "1000 Genomes" project and we identified the alleles specific to the Yakut population. We showed, that the Yakuts population is a separate cluster between Europeans and East Asians.

Meta-analysis of genome-wide association studies for personality.

Personality can be thought of as a set of characteristics that influence people's thoughts, feelings and behavior across a variety of settings. Variation in personality is predictive of many outcomes in life, including mental health. Here we report on a meta-analysis of genome-wide association (GWA) data for personality in 10 discovery samples (17,375 adults) and five in silico replication samples (3294 adults). All participants were of European ancestry. Personality scores for Neuroticism, Extraversion, Openness to Experience, Agreeableness and Conscientiousness were based on the NEO Five-Factor Inventory. Genotype data of ≈ 2.4M single-nucleotide polymorphisms (SNPs; directly typed and imputed using HapMap data) were available. In the discovery samples, classical association analyses were performed under an additive model followed by meta-analysis using the weighted inverse variance method. Results showed genome-wide significance for Openness to Experience near the RASA1 gene on 5q14.3 (rs1477268 and rs2032794, P=2.8 × 10(-8) and 3.1 × 10(-8)) and for Conscientiousness in the brain-expressed KATNAL2 gene on 18q21.1 (rs2576037, P=4.9 × 10(-8)). We further conducted a gene-based test that confirmed the association of KATNAL2 to Conscientiousness. In silico replication did not, however, show significant associations of the top SNPs with Openness and Conscientiousness, although the direction of effect of the KATNAL2 SNP on Conscientiousness was consistent in all replication samples. Larger scale GWA studies and alternative approaches are required for confirmation of KATNAL2 as a novel gene affecting Conscientiousness.

A genome-wide linkage study of individuals with high scores on NEO personality traits.

The NEO-Five-Factor Inventory divides human personality traits into five dimensions: neuroticism, extraversion, openness, conscientiousness and agreeableness. In this study, we sought to identify regions harboring genes with large effects on the five NEO personality traits by performing genome-wide linkage analysis of individuals scoring in the extremes of these traits (>90th percentile). Affected-only linkage analysis was performed using an Illumina 6K linkage array in a family-based study, the Erasmus Rucphen Family study. We subsequently determined whether distinct, segregating haplotypes found with linkage analysis were associated with the trait of interest in the population. Finally, a dense single-nucleotide polymorphism genotyping array (Illumina 318K) was used to search for copy number variations (CNVs) in the associated regions. In the families with extreme phenotype scores, we found significant evidence of linkage for conscientiousness to 20p13 (rs1434789, log of odds (LOD)=5.86) and suggestive evidence of linkage (LOD >2.8) for neuroticism to 19q, 21q and 22q, extraversion to 1p, 1q, 9p and12q, openness to 12q and 19q, and agreeableness to 2p, 6q, 17q and 21q. Further analysis determined haplotypes in 21q22 for neuroticism (P-values = 0.009, 0.007), in 17q24 for agreeableness (marginal P-value = 0.018) and in 20p13 for conscientiousness (marginal P-values = 0.058, 0.038) segregating in families with large contributions to the LOD scores. No evidence for CNVs in any of the associated regions was found. Our findings imply that there may be genes with relatively large effects involved in personality traits, which may be identified with next-generation sequencing techniques.

Genome-wide association analysis of coffee drinking suggests association with CYP1A1/CYP1A2 and NRCAM.

Coffee consumption is a model for addictive behavior. We performed a meta-analysis of genome-wide association studies (GWASs) on coffee intake from 8 Caucasian cohorts (N=18 176) and sought replication of our top findings in a further 7929 individuals. We also performed a gene expression analysis treating different cell lines with caffeine. Genome-wide significant association was observed for two single-nucleotide polymorphisms (SNPs) in the 15q24 region. The two SNPs rs2470893 and rs2472297 (P-values=1.6 × 10(-11) and 2.7 × 10(-11)), which were also in strong linkage disequilibrium (r(2)=0.7) with each other, lie in the 23-kb long commonly shared 5' flanking region between CYP1A1 and CYP1A2 genes. CYP1A1 was found to be downregulated in lymphoblastoid cell lines treated with caffeine. CYP1A1 is known to metabolize polycyclic aromatic hydrocarbons, which are important constituents of coffee, whereas CYP1A2 is involved in the primary metabolism of caffeine. Significant evidence of association was also detected at rs382140 (P-value=3.9 × 10(-09)) near NRCAM-a gene implicated in vulnerability to addiction, and at another independent hit rs6495122 (P-value=7.1 × 10(-09))-an SNP associated with blood pressure-in the 15q24 region near the gene ULK3, in the meta-analysis of discovery and replication cohorts. Our results from GWASs and expression analysis also strongly implicate CAB39L in coffee drinking. Pathway analysis of differentially expressed genes revealed significantly enriched ubiquitin proteasome (P-value=2.2 × 10(-05)) and Parkinson's disease pathways (P-value=3.6 × 10(-05)).

Genetic risk profiles for depression and anxiety in adult and elderly cohorts.

The first generation of genome-wide association studies (GWA studies) for psychiatric disorders has led to new insights regarding the genetic architecture of these disorders. We now start to realize that a larger number of genes, each with a small contribution, are likely to explain the heritability of psychiatric diseases. The contribution of a large number of genes to complex traits can be analyzed with genome-wide profiling. In a discovery sample, a genetic risk profile for depression was defined based on a GWA study of 1738 adult cases and 1802 controls. The genetic risk scores were tested in two population-based samples of elderly participants. The genetic risk profiles were evaluated for depression and anxiety in the Rotterdam Study cohort and the Erasmus Rucphen Family (ERF) study. The genetic risk scores were significantly associated with different measures of depression and explained up to ∼0.7% of the variance in depression in Rotterdam Study and up to ∼1% in ERF study. The genetic score for depression was also significantly associated with anxiety explaining up to 2.1% in Rotterdam study. These findings suggest the presence of many genetic loci of small effect that influence both depression and anxiety. Remarkably, the predictive value of these profiles was as large in the sample of elderly participants as in the middle-aged samples.

The genetic association between personality and major depression or bipolar disorder. A polygenic score analysis using genome-wide association data.

The relationship between major depressive disorder (MDD) and bipolar disorder (BD) remains controversial. Previous research has reported differences and similarities in risk factors for MDD and BD, such as predisposing personality traits. For example, high neuroticism is related to both disorders, whereas openness to experience is specific for BD. This study examined the genetic association between personality and MDD and BD by applying polygenic scores for neuroticism, extraversion, openness to experience, agreeableness and conscientiousness to both disorders. Polygenic scores reflect the weighted sum of multiple single-nucleotide polymorphism alleles associated with the trait for an individual and were based on a meta-analysis of genome-wide association studies for personality traits including 13,835 subjects. Polygenic scores were tested for MDD in the combined Genetic Association Information Network (GAIN-MDD) and MDD2000+ samples (N=8921) and for BD in the combined Systematic Treatment Enhancement Program for Bipolar Disorder and Wellcome Trust Case-Control Consortium samples (N=6329) using logistic regression analyses. At the phenotypic level, personality dimensions were associated with MDD and BD. Polygenic neuroticism scores were significantly positively associated with MDD, whereas polygenic extraversion scores were significantly positively associated with BD. The explained variance of MDD and BD, ∼0.1%, was highly comparable to the variance explained by the polygenic personality scores in the corresponding personality traits themselves (between 0.1 and 0.4%). This indicates that the proportions of variance explained in mood disorders are at the upper limit of what could have been expected. This study suggests shared genetic risk factors for neuroticism and MDD on the one hand and for extraversion and BD on the other.

Insulin-resistance and metabolic syndrome are related to executive function in women in a large family-based study.

While type 2 diabetes is well-known to be associated with poorer cognitive performance, few studies have reported on the association of metabolic syndrome (MetS) and contributing factors, such as insulin-resistance (HOMA-IR), low adiponectin-, and high C-reactive protein (CRP)-levels. We studied whether these factors are related to cognitive function and which of the MetS components are independently associated. The study was embedded in an ongoing family-based cohort study in a Dutch population. All participants underwent physical examinations, biomedical measurements, and neuropsychological testing. Linear regression models were used to determine the association between MetS, HOMA-IR, adiponectin levels, CRP, and cognitive test scores. Cross-sectional analyses were performed in 1,898 subjects (mean age 48 years, 43% men). People with MetS had significantly higher HOMA-IR scores, lower adiponectin levels, and higher CRP levels. MetS and high HOMA-IR were associated with poorer executive function in women (P = 0.03 and P = 0.009). MetS and HOMA-IR are associated with poorer executive function in women.

Shared genetic factors in migraine and depression: evidence from a genetic isolate.

OBJECTIVE: To investigate the co-occurrence of migraine and depression and assess whether shared genetic factors may underlie both diseases. METHODS: Subjects were 2,652 participants of the Erasmus Rucphen Family genetic isolate study. Migraine was diagnosed using a validated 3-stage screening method that included a telephone interview. Symptoms of depression were assessed using the Center for Epidemiologic Studies Depression scale and the depression subscale of the Hospital Anxiety and Depression Scale (HADS-D). The contribution of shared genetic factors in migraine and depression was investigated by comparing heritability estimates for migraine with and without adjustment for symptoms of depression, and by comparing the heritability scores of depression between migraineurs and controls. RESULTS: We identified 360 migraine cases: 209 had migraine without aura (MO) and 151 had migraine with aura (MA). Odds ratios for depression in patients with migraine were 1.29 (95% confidence interval [CI] 0.98-1.70) for MO and 1.70 (95% CI 1.28-2.24) for MA. Heritability estimates were significant for all migraine (0.56), MO (0.77), and MA (0.96), and decreased after adjustment for symptoms of depression or use of antidepressant medication, in particular for MA. Comparison of the heritability scores for depression between patients with migraine and controls showed a genetic correlation between HADS-D score and MA. CONCLUSIONS: There is a bidirectional association between depression and migraine, in particular migraine with aura, which can be explained, at least partly, by shared genetic factors.

Novel strategy to identify genetic risk factors for COPD severity: a genetic isolate.

Studies using genetic isolates with limited genetic variation may be useful in chronic obstructive pulmonary disease (COPD) genetics, but are thus far lacking. The associations between single nucleotide polymorphisms (SNPs) in candidate genes and lung function in COPD were studied in a genetic isolate. In 91 subjects with Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage >or=1 COPD, who were members of an extended pedigree including 6,175 people from the Genetic Research in Isolated Populations study, 32 SNPs were analysed in 13 candidate genes: a disintegrin and metalloprotease domain 33 gene (ADAM33), transforming growth factor-beta1 gene ( TGFB1), matrix metalloprotease-1 gene (MMP1), MMP2, MMP9, MMP12, tissue inhibitor of metalloprotease-1 gene (TIMP1), surfactant protein A1 gene (SFTPA1 ), SFTPA2, SFTPB, SFTPD, glutathione S-transferase P1 gene (GSTP1), and haem oxygenase 1 gene ( HMOX1). Their relation to forced expiratory volume in 1 s (FEV( 1)), inspiratory vital capacity (IVC) and FEV(1)/IVC were studied using restricted maximum likelihood linear mixed modelling, accounting for pedigree structure. Significant associations were replicated in the general Vlagtwedde/Vlaardingen study. Six SNPs in TGFB1, SFTPA1, SFTPA2 and SFTPD were significantly associated with FEV(1)/IVC in subjects with GOLD stage >or=1 COPD. Two SNPs in TGFB1 (C to T substitution at nucleotide -509 and substitution of leucine 10 with proline (Leu10Pro)), Leu50Val in SFTPA1 and Ala160Thr in SFTPD showed evidence suggestive of association with FEV(1)/IVC in subjects with GOLD stage >or=2 COPD. The TGFB1 associations were replicated in GOLD stage >or=2 patients from the Vlagtwedde/Vlaardingen population, with similar effect sizes. It was shown that a genetic isolate can be used to determine the genetics of lung function, which can be replicated in COPD patients from an independent population.

Linkage analysis of adult height in a large pedigree from a Dutch genetically isolated population.

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.

Sex-specific genetic effects influence variation in body composition.

AIMS/HYPOTHESIS: Despite well-known sex differences in body composition it is not known whether sex-specific genetic or environmental effects contribute to these differences. METHODS: We assessed body composition in 2,506 individuals, from a young Dutch genetic isolate participating in the Erasmus Rucphen Family study, by dual-energy X-ray absorptiometry and anthropometry. We used variance decomposition procedures to partition variation of body composition into genetic and environmental components common to both sexes and to men and women separately and calculated the correlation between genetic components in men and women. RESULTS: After accounting for age, sex and inbreeding, heritability ranged from 0.39 for fat mass index to 0.84 for height. We found sex-specific genetic effects for fat percentage (fat%), lean mass, lean mass index (LMI) and fat distribution, but not for BMI and height. Genetic correlations between sexes were significantly different from 1 for fat%, lean mass, LMI, android fat, android:gynoid fat ratio and WHR, indicating that there are sex-specific genes contributing to variation of these traits. Genetic variance was significantly higher in women for the waist, hip and thigh circumference and WHR, implying that genes account for more variance of fat distribution in women than in men. Environmental variance was significantly higher in men for the android:gynoid fat ratio. CONCLUSIONS/INTERPRETATION: Sex-specific genetic effects underlie sexual dimorphism in several body composition traits. The findings are relevant for studies on the relationship of body composition with common diseases like cardiovascular disease and type 2 diabetes and for genetic association studies.

Familial aggregation of preeclampsia and intrauterine growth restriction in a genetically isolated population in The Netherlands.

Preeclampsia and intrauterine growth restriction are related, pregnancy-specific disorders with a substantial genetic influence, which may have a joint genetic aetiology. We investigated familial aggregation, consanguinity and parent-of-origin effects for preeclampsia and IUGR. Fifty women with previous preeclampsia and 56 with previous pregnancies complicated by intrauterine growth restriction were recruited from a recent genetically isolated population in the Netherlands. Their relationships were estimated by means of a large genealogy database that contains information on more than 110 000 individuals from the isolate over 23 generations. Relationships were quantified using kinship and inbreeding coefficients. Parent-of-origin effects were evaluated by comparing parental kinships. Eighty-six women (39 preeclampsia and 47 intrauterine growth restriction) could be linked to one common ancestor within 14 generations. The proportion of related women with previous preeclampsia (95.6%) or pregnancies complicated by intrauterine growth restriction (95.1%) was significantly greater than expected by chance (P<0.001). Combined analysis of both disorders did not change the magnitude of familial aggregation. The proportion of women born from consanguineous marriages was increased in women with previous preeclampsia (81.8%) and those with intrauterine growth restriction (78%) compared to a random sample (P<0.001). Maternal and paternal kinships were not significantly different in both disorders. We demonstrate cosegregation of preeclampsia and intrauterine growth restriction, supporting a common genetic aetiology. The high proportion of parental consanguineous marriages suggests the possibility of an underlying recessive mutation. No evidence was found for a parent-of-origin effect either in preeclampsia or in intrauterine growth restriction.

Prevalence and heritability of the metabolic syndrome and its individual components in a Dutch isolate: the Erasmus Rucphen Family study.

BACKGROUND: Metabolic syndrome (MetS) is defined by a combination of abnormalities that are all individual risk factors for the development of type 2 diabetes and/or cardiovascular disease. The aetiology of MetS includes both an environmental and genetic component. We studied the prevalence and heritability of MetS and its individual components Dutch genetic isolate. METHODS: The Erasmus Rucphen Family study (ERF) consists of some 3000 genealogically documented individuals from a Dutch genetic isolate. Data on waist circumference (WC), blood pressure (BP), high density lipoprotein cholesterol (HDL-C), triglycerides (TG) and fasting plasma glucose values (FPG) are available. MetS was defined according to the International Diabetes Federation (IDF) (2003) and National Cholesterol Education program Adult Panel III (NCEP ATPIII) criteria. Variance component analysis was applied to extended family data to test for evidence of heritability. RESULTS: The prevalence of MetS in the ERF cohort ranged from 23-37% depending on MetS definition and gender considered. Low HDL-C and high WC are the main contributors to MetS. The heritability of MetS corrected for sibship effect was 10.6% (p = 0.01) according to IDF and 13.2% (p = 0.07) according to NCEP ATPIII criteria. In addition, the heritability of individual components of MetS were analysed and found to range from 21.9-42.9%. The highest heritability was found for HDL-C (42.9%, p<0.0001) and WC (37.8%, p<0.0001). In addition, WC, systolic BP, HDL-C and TG showed low to moderate genetic correlation (RhoG) between genders, whereas FPG and diastolic BP showed absolute genetic correlation between genders. CONCLUSION: Although the prevalence of MetS was high, the heritability of MetS in the ERF population was found to be moderate. The high heritability of the individual components of MetS indicates that the genetic dissection of MetS should be approached from its individual components.

EVI5 is a risk gene for multiple sclerosis.

HLA-DRB1 is the major locus associated with risk for multiple sclerosis (MS). A recent genome-wide study showed three additional single-nucleotide polymorphisms (SNPs), within the IL2RA and IL7RA genes respectively, also to be associated with MS. Consistent association but lower significance was found for 13 other SNPs. In this study, we aimed to verify association of these SNPs with MS in 46 MS patients and 194 controls from a Dutch genetically isolated population. Apart from the human leukocyte antigen locus, the EVI5 gene on chromosome 1 was confirmed as a novel risk gene, with odds ratios (ORs) even higher than those from the MS Consortium (ORs 2.01 and 1.9; P=0.01). The risk effect of EVI5 was further validated for the general MS population in an independent set of 1318 MS patients from the Canadian Collaborative Project on the Genetic Susceptibility to MS. On the basis of the transmission disequilibrium testing, a weak but significant risk effect was observed (OR 1.15; P=0.03 and OR 1.15; P=0.04). This study confirms EVI5 as another risk locus for MS; however, much of the genetic basis of MS remains unidentified.

Familial clustering of multiple sclerosis in a Dutch genetic isolate.

Multiple sclerosis (MS) is a complex disease with a substantial, yet poorly identified, genetic influence. We estimated the pattern of familial aggregation of MS in a recent genetically isolated population in The Netherlands. Forty-eight MS patients were identified. Their relationship was evaluated by tracing extended pedigrees, making use of municipal and church records. Of the 48 MS patients, 24 could be linked to a common ancestor in 14 generations. However, multiple relationships exist between patients and, to take these into account, we calculated inbreeding and kinship coefficients. We found that MS patients from the isolate were significantly more often related to each other and significantly more often inbred than a non-MS control group, drawn from the same isolate. There was no clustering of Type 1 diabetes and autoimmune thyroid diseases in families of MS patients from this isolate. Finally, HLA typing was performed. Although there was a trend towards a higher prevalence of the HLA DRB1*15 allele in patients compared to controls, differences did not reach significance. This study suggests familial aggregation in the genetically isolated population. The high level of inbreeding makes this population valuable for finding novel genes involved in MS.