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The alpha1/beta2/gamma2-containing heteropentamer is the most abundant gamma-amino-n-butyric acid type A receptor subtype in mammalian brains and the corresponding genes, the GABRA1, GABRB2, and GABRG2 genes, are located in chromosomal region 5q34 that several genome wide scans have implicated as a susceptibility region for schizophrenia. Given this positional and functional evidence, Lo et al. (Mol Psychiatry 2004; 9: 603-608) performed systematic linkage disequilibrium mapping of the GABAAR gene cluster on 5q34 in 130 schizophrenic patients and 170 controls, all of Chinese Han origin. In the single locus and haplotype analyses, single nucleotide polymorphisms in the GABRB2 gene showed highly significant association. The estimated effect caused by GABRB2 varied between odds ratios of 2.27 and 5.12. In order to re-examine their findings, we analyzed the most significantly associated single nucleotide polymorphism in the GABRB2 gene in a sample of 367 patients with schizophrenia and 360 controls, all of German descent. Our sample had a sufficient power to detect the effects described. Neither single marker nor haplotype analysis revealed a significant association with the disease status. Thus, our results do not support the hypothesis that genetic variation at the GABRB2 locus plays a major role in schizophrenic patients of European descent and that such variation would explain the previously observed linkage findings at this chromosomal region.

Chemokines and their receptors are involved in many aspects of immunity. Chemokine CX3CL1, acting via its receptor CX3CR1, regulates monocyte migration and macrophage differentiation as well as T cell-dependent inflammation. Two common, nonsynonymous polymorphisms in CX3CR1 have previously been shown to alter the function of the CX3CL1/CX3CR1 pathway and were suggested to modify the risk for asthma. Using matrix-assisted laser desorption/ionization time-of-flight technology, we genotyped polymorphisms Val249Ile and Thr280Met in a cross-sectional population of German children from Munich (n = 1,159) and Dresden (n = 1,940). For 249Ile an odds ratio of 0.77 (95% confidence interval 0.63-0.96; p = 0.017) and for 280Met an odds ratio of 0.71 (95% confidence interval 0.56-0.89; p = 0.004) were found with atopy in Dresden but not in Munich. Neither polymorphism was associated with asthma. Thus, amino acid changes in CX3CR1 may influence the development of atopy but not asthma in German children. Potentially, other factors such as environmental effects may modify the role of CX3CR1 polymorphisms.

Disturbed glutamatergic neurotransmission has been implicated in the pathogenesis of schizophrenia and bipolar disorder, with the N-methy-D-aspartate receptors being in the focus of research. The NR1 subunit, which is encoded by the gene GRIN1, plays a key role in the functionality of N-methy-D-aspartate receptors. We tested the association between GRIN1 and bipolar disorder in a sample of German descent, consisting of 306 bipolar disorder patients and 319 population-based controls. No significant association was found. In accordance with our recent findings, we hypothesized that restricting case definition to individuals with a history of persecutory delusions might clarify the relationship between bipolar disorder and GRIN1. This stratified analysis did not yield any significant association either. Our results do not support an association of the GRIN1 gene with bipolar disorder in the German population.

A number of susceptibility loci for Alzheimer's disease (AD) have been identified including a region on Chromosome 10q21-q22. Within this region the plasminogen activator urokinase gene (PLAU) was considered as a reasonable candidate from its functional implication in plasmin generation, a serine protease capable of degrading beta-Amyloid (Abeta) protein. We screened 56 single nucleotide polymorphisms (SNPs) around PLAU using 1751 individuals from four independent case-control samples (Munich, N=679; Bonn N=282; Brescia (Italy) N=219; Perth (Australia) N=557 and one discordant sib-pair sample (Munich N=622). In brain tissue samples of neuropathologically confirmed cases with AD (N=33) we analyzed plaque counts according to the risk allele. We identified that one functional exonic SNP (rs2227564) is associated with development of AD using the four independent case-control samples (Munich, P=0.02; Bonn, P=0.005; Brescia (Italy), P=0.001; Perth (Australia), P=0.03) and the discordant sib-pair sample (P=0.001). In brain tissue, from neuropathologically confirmed cases with AD, we identified significantly higher plaque counts in carriers of the risk allele (N=6; 60.3+/-16.9) compared with non-carriers (N=9; 26.3+/-8.8; P=0.007). This study provides compelling evidence of a genetic and functional involvement of a common PLAU variant into the pathogenesis of AD. Further functional investigations are warranted to elucidate the specific role of PLAU, respectively, PLAU variants in the metabolism of Abeta proteins.

Background ADAM33, the first asthma candidate gene identified by positional cloning, may be associated with childhood asthma, lung function decline and bronchial hyperresponsiveness. However, replication results have been inconclusive in smaller previous study populations probably due to inconsistencies in asthma phenotypes or yet unknown environmental influences. Thus, we tried to further elucidate the role of ADAM33 polymorphisms (SNPs) in a genetic analysis of German case control and longitudinal populations. Methods Using MALDI-TOF, ten ADAM33 SNPs were genotyped in 1,872 children from the International Study of Asthma and Allergy in Childhood (ISAAC II) in a case control setting and further 824 children from the longitudinal cohort Multicentre Study of Allergy (MAS). In both populations the effects of single SNPs and haplotypes were studied and a gene environment analysis with passive smoke exposure was performed using SAS/Genetics. Results No single SNP showed a significant association with doctor's diagnosis of asthma. A trend for somewhat more profound effects of ADAM33 SNPs was observed in individuals with asthma and BHR. Haplotype analyses suggested a minor effect of the ADAM33 haplotype H4 on asthma (p = 0.033) but not on BHR. Associations with non atopic asthma and baseline lung function were identified but no interaction with passive smoke exposure could be detected. Conclusion The originally reported association between ADAM33 polymorphisms and asthma and BHR could not be confirmed. However, our data may suggest a complex role of ADAM33 polymorphisms in asthma ethiology, especially in non atopic asthma.

Objective: To evaluate the relevance and necessity to account for the effects of population substructure on association studies under a case-control design in central Europe, we analysed three samples drawn from different geographic areas of Germany. Two of the three samples, POPGEN (n = 720) and SHIP (n = 709), are from north and north-east Germany, respectively, and one sample, KORA (n = 730), is from southern Germany. Methods: Population genetic differentiation was measured by classical F-statistics for different marker sets, either consisting of genome-wide selected coding SNPs located in functional genes, or consisting of selectively neutral SNPs from ‘genomic deserts’. Quantitative estimates of the degree of stratification were performed comparing the genomic control approach [Devlin B, Roeder K: Biometrics 1999;55:997–1004], structured association [Pritchard JK, Stephens M, Donnelly P: Genetics 2000;155:945–959] and sophisticated methods like random forests [Breiman L: Machine Learning 2001;45:5–32]. Results: F-statistics showed that there exists a low genetic differentiation between the samples along a north-south gradient within Germany (FST(KORA/POPGEN): 1.7 · 10–4; FST(KORA/SHIP): 5.4 · 10–4; FST(POPGEN/SHIP): –1.3 · 10–5). Conclusion: Although the FST -values are very small, indicating a minor degree of population structure, and are too low to be detectable from methods without using prior information of subpopulation membership, such as STRUCTURE [Pritchard JK, Stephens M, Donnelly P: Genetics 2000;155:945–959], they may be a possible source for confounding due to population stratification.

Altered glutamatergic neurotransmission is considered a potential etiological factor of schizophrenia (SCZ) and affective disorders. The gene ASCT1 (SLC1A4) coding for a Na+-dependent neutral aminoacid transporter is a member of the glutamate transporter superfamily and is located on 2p13-14, a region showing linkage to both SCZ and bipolar disorder (BD). ASCT1 can thus be considered a candidate gene for both disorders. In a German sample, we tested for association between ASCT1 and both SCZ and BD. Allele and haplotype frequencies, however, did not differ between cases and controls. Recent findings on the associations between brainderived neurotrophic factor (BDNF) and SCZ and between G72/G30 and BD suggest that SCZ patients with a history of major depressive episodes (MDE) outside psychotic episodes and BD cases with a history of persecutory delusions constitute genetically distinct subgroups of these disorders. Thus, we hypothesized that restricting case definition to those 95 SCZ individuals with MDE and to those 107 BD patients with a history of persecutory delusions might clarify the relationship between BD, SCZ and ASCT1. However, these stratification approaches did not yield any significant association either. Allele and haplotype frequencies did not differ between cases and controls. Our results do not support an association of the ASCT1 gene with BD or SCZ in the German population.

BACKGROUND: An isolated form of congenital cataract associated with macular hypoplasia and a generally hypopigmented fundus in infancy was observed in a German family. To test the hypothesis that a de-novo mutation had occurred in one of the parental germ lines, a functional candidate gene approach was applied. METHODS: The family was carefully examined by a senior paediatric ophthalmologist according to routine procedures (slit lamp, funduscopy, ERG). Blood was taken from the proband and his parents, genomic DNA was isolated and some candidate genes for cataract (CRYAA, CRYBB2, GJA8) or macular hypoplasia (OA1, P) or both (PAX6) were analyzed. RESULTS: The proband showed bilateral cataracts at the age of 4 months; the fundus appeared pale, the optic disc grayish, and macular reflexes were absent. After cataract surgery, the nystagmus persisted, and a control ERG at age 9 years showed essentially normal scotopic and photopic wave forms. An infectious aetiology as well as galactosemia were excluded. However, a heterozygous mutation was found in the proband in exon 1 of CRYAA (62 C-->T), which leads to an exchange from Arg to Leu at amino acid position 21 (R21L). This sequence alteration was not found in the parents and in 96 randomly selected DNA samples from ophthalmologically normal individuals of the KORA S4 study population. In addition, two heterozygous mutations in P were identified (R419Q and A481T); one of both was present in each of the unaffected parents. CONCLUSION: Based upon the unique finding of the mutation and the expression of CRYAA in the lens, this R21L mutation in the CRYAA is considered to be causative for the dominant cataract phenotype. Moreover, the macular hypoplasia has to be considered a concerted interaction with compound heterozygous mutations in the P gene manifesting a mild form of oculocutaneous albinism. Nevertheless, this combination is rare and future studies will focus on identifying similar phenotypes.

Background Interactions with microbial pathogens are crucial for the maturation of the immune system. The nucleotide-binding oligomerization domain protein 1 (NOD1) is a cytosolic receptor sensing a muropeptide found mostly in gram-negative bacterial peptidoglycans. NOD1 is located on chromosome 7p14-p15, a region that has been linked with atopy. Recently, polymorphisms of the closely related NOD2 have been associated with atopy-related traits. Objectives Within a large population-based cohort of German adults (n=1417), a case-control population for atopic eczema (n=454), and a large cohort of parent-offspring trios for atopic eczema (189 trios), we evaluated 11 NOD1 polymorphisms for associations with atopic phenotypes. Methods Subjects were phenotyped by standardized questionnaires and interviews, skin examination, and serum IgE measurements. Genotyping was performed by using matrix-assisted laser desorption ionization–time of flight mass spectrometry. Results Analyses revealed significant association of one NOD1 haplotype with atopic eczema in the population-based cohort ( P =.004) and the case-control population ( P =.003). Another NOD1 haplotype was associated with decreased total IgE ( P =.008). In addition, significant associations with total serum IgE levels were observed for polymorphisms rs2907748 ( P =.006), rs2907749 ( P =.012), and rs2075822 ( P =.018). These polymorphisms were significantly associated with atopic eczema and asthma in the family-based association analyses ( P =.001-.043). Seven polymorphisms showed significant transmission distortion for total IgE levels ( P values Conclusion These data indicate that genetic variants within NOD1 are important determinants of atopy susceptibility.

OBJECTIVE: The authors previously reported an association between the D-amino acid oxidase activator (DAOA)/G30 locus and both schizophrenia and bipolar affective disorder. Given the presumed role of DAOA/G30 in the neurochemistry of psychosis and its localization in a schizophrenia and bipolar affective disorder linkage region (13q34), it was hypothesized that the bipolar affective disorder finding would be mainly due to an association with psychotic features. METHOD: The marker/haplotype associations obtained in a subset of 173 bipolar affective disorder patients with psychotic features were similar to those in the overall patient group, suggesting that stratification on the basis of psychotic features in general might be too crude a procedure. The authors therefore tested whether confining caseness to specific psychotic features would improve detection of genotype-phenotype correlations. RESULTS: In a logistic regression, "persecutory delusions" were found to be the only significant explanatory variable for the DAOA/G30 risk genotype among 21 OPCRIT symptoms of psychosis. The authors therefore tested for association between DAOA/G30 and bipolar affective disorder in the 90 cases with a history of persecutory delusions. Whereas this subset showed strong association (odds ratio=1.83 for the best marker), the remaining larger sample of 165 patients with no such history did not differ from comparison subjects, suggesting that the association between DAOA/G30 and bipolar affective disorder is due to persecutory delusions. This was confirmed in an independent study of 294 bipolar affective disorder patients and 311 comparison subjects from Poland, in which an association between bipolar affective disorder and DAOA/G30 was only seen when case definition was restricted to cases with persecutory delusions. CONCLUSIONS: These data suggest that bipolar affective disorder with persecutory delusions constitutes a distinct subgroup of bipolar affective disorder that overlaps with schizophrenia.

Background Because of its central role in the IL-4/IL-13 pathway, the intracellular signaling molecule signal transducer and activator of transcription 6 (STAT6) may be crucial for IgE production in asthma and allergy. Objective We analyzed the association between polymorphisms in the STAT6 gene and the regulation of serum IgE levels. Methods In a population of 1120 German schoolchildren (age 9-11 years), we genotyped 6 previously identified polymorphisms spanning the STAT6 gene by using the matrix-assisted laser desorption ionization–time of flight mass spectrometry method. Haplotypes were estimated and population-derived IgE percentiles (50% IgE > 60 IU/mL, 66% IgE > 115 IU/mL, and 90% IgE > 457 IU/mL) were modeled as outcome variables in haplotype-trend regression analysis. Results Polymorphisms located in intron 2 (C2892T) and the 3′ untranslated region (T12888C) significantly and consistently contributed to elevated total serum IgE levels. One STAT6 haplotype showed increased odds ratios of 1.58 (95% CI, 1.08-2.32; P = .020), 1.82 (95% CI, 1.19-2.77; P = .006), and 3.92 (95% CI, 1.93-7.96; P = .0002) for elevated IgE levels at percentiles 50%, 66%, and 90%, respectively. Because C2892T is located within a nuclear factor κB transcription factor binding site, a functional role of this polymorphism is very likely. Conclusion The data indicate that within the IL-4/IL-13 pathway, genetic variants in the STAT6 gene significantly contribute to the regulation of serum IgE levels.

PURPOSE. The purpose of this study was the characterization of eight new dominant cataract mutations. METHODS. Lenses of mutant mice were described morphologically and histologically. Each mutation was mapped by linkage studies. The candidate genes (the Cryg gene cluster and the closely linked Cryba2 gene) were sequenced. RESULTS. Molecular analysis confirmed all mutations in Cryg genes. Five mutations lead to amino acid exchanges, two are due to premature stop codons, and one is a 10-bp deletion in the Cryge gene. Morphologically, mutant carriers expressed nonsyndromic cataracts, ranging from diffuse lenticular opacities (Crygd ENU910 and Cryge ENU449 ), to dense nuclear and subcortical opacity (Crygd K10 , Crygc MNU8 , Cryge Z2 , Crygd ENU4011 , and Cryge ADD15306 ), to dense nuclear opacity and ruptured lenses (Cryga ENU469 ). Results of histologic analyses correlate well with the severity of lens opacity, ranging from alterations in the process of secondary fiber nucleus degradation to lens vacuoles, fiber degeneration, and disruption of the lens capsule. CONCLUSIONS. In total, 20 mutations have been described that affect the Cryg gene cluster: Nine mutations affect the Cryge gene, but only one affects the Crygb or Crygf genes. No mutation was observed in the closely linked Cryba2. Two mutations occur at the same site in the Crygd and Cryge genes (Leu45→Pro). The unequal distribution of mutations suggests hot spots in the Cryg genes. The overall high number of mutations in these genes demonstrates their central role in the maintenance of lens transparency.

Lack of support for a genetic association of the XBP1 promoter polymorphism with bipolar disorder in probands of European origin

The Rop (radial opacity) mutation, which was recovered in a mutagenicity screen after paternal treatment with procarbazine, was analyzed to determine phenotype, chromosomal localization, candidate genes, and molecular lesion.Native lenses were photographed under a dissecting microscope. Histologic sections of the eye were made according to standard procedures. Fine mapping of the mutation in relation to microsatellite markers for mouse chromosome 1 was performed. Candidate genes were amplified by PCR from cDNA or genomic DNA and sequenced.The nuclear opacity of the heterozygous mutants showed radial structures, whereas the opacity of the homozygotes was homogenous. The histologic analysis revealed changes in the lens nucleus, which corresponds to the pronounced opacification in lenses of homozygous mutants. The allelism of Rop to the Cat2 group of dominant cataracts on mouse chromosome 1 was confirmed by linkage to microsatellite markers D1Mit156 and D1Mit181. The cluster of the Cryg genes and the closely linked Cryba2 gene were tested as candidates. A T--A exchange in exon 2 of the Crygf gene leads to a Val--Glu exchange in codon 38 and was considered to be causative for the cataract phenotype; therefore, Crygf(Rop) has been suggested as the designation for the mutation.Crygf(Rop) is the first mutation affecting the Crygf gene. Dominant cataract mutations for all six Cryg genes on mouse chromosome 1 have now been characterized, demonstrating the importance of this gene cluster in lens transparency.

A unique sutural cataract was observed in a 4-generation German family to be transmitted as an isolated autosomal, dominant trait. Since mutations in the γ-crystallin encoding CRYG genes have previously been demonstrated to be the most frequent reason for isolated congenital cataracts, all 4 active CRYG genes have been sequenced. A single base-pair change in the CRYGA gene has been shown, leading to a premature stop codon. This was not observed in 170 control individuals. However, it did not segregate with the disease phenotype. This is the first truncating mutation in an active CRYG gene without a dominant phenotype. As the CRYGA mutation did not explain the cataract, several other candidate loci (CCV, GJA8, CRYBB2, BFSP2, MIP, GJA8, central pouch-like, CRYBA1) were investigated by microsatellite markers and linkage analysis, but they were excluded based on the combination of haplotype analysis and two-point linkage analysis. The phenotype in this family is due to a mutation in another sutural cataract gene yet to be identified.

The human signal transducer and activator of transcription 6 (STAT6) gene represents one of the most promising candidate genes for asthma and other inflammatory diseases on the chromosomal region 12q13-q24. Therefore we screened all 23 exons, including parts of the neighbouring introns, as well as the promoter region for common polymorphisms and tested them for linkage/association with asthma and related traits (total serum IgE level, eosinophil cell count and SLOPE of the dose-response curve after bronchial challenge) in a Caucasian sib-pair study (108 families with at least two affected children). We could identify 13 single nucleotide polymorphisms (SNPs), which are all non-coding. A recently described dinucleotide (GT) repeat in exon 1 was also examined. Besides the confirmation of the four alleles described elsewhere we could identify a new one, named allele A5. Neither the SNPs nor the GT repeat showed linkage/association to asthma. Two intronic SNPs and one SNP in the 3'untranslated region of the gene showed weak association to total IgE levels (P = 0.0200, 0.0260 and 0.0280, respectively), whereas a significant association was found between a SNP in intron 18 and an increase in total IgE levels (P = 0.0070). However, the most promising effect was seen between allele A4 of the GT repeat polymorphism and an increase in eosinophil cell count (P = 0.0010). From these findings we conclude that the human STAT6 gene is rather involved in the development of eosinophilia and changes in total IgE levels than contributing to the pathogenesis of asthma.

To trace cell lineages and the origin and fate of cells in transplantation and embryo chimeras, a DNA/DNA in situ hybridization cell labelling system was developed, based on a 50-copy murine c-myc transgene on mouse chromosome 8. Elevated levels of cMyc mRNA were found in Myc*tg50 (Myc(tg50)/0 and Myc(tg50)/Myc(tg50)) transgenic tissues, but adult transgenic NMRI mice were anatomically and histologically indistinguishable from control NMRI mice and did not develop tumours on a wild-type or nude (nu/nu) background. The hybridization label detected transgenic nuclei with an efficiency of similar to 80%. In muscle grafts, this transgene label was successfully applied to trace donor cells in a labelled host and to study the invasion of a graft by host cells. When the cMyc hybridization was used in allophenic mice of the control NMRI-Myc(tg50)/? (nu/+ or +/+) type, an up to a three-fold excess of MYC*tg50 positive over control nuclei was found in all organs examined (ventricle, skeletal muscle, liver, small intestine). This overgrowth of MYC*tg50 cells is probably due to transgene expression. Four out of seven (C57BL/6 x BALB/c) or (C57BL/6 x NMRI) MYC*tg50 allophenic mice displayed anatomical abnormalities, e.g. an enlarged thymus and a tumour in the groin region. As these abnormalities were only observed in allophenic mice, they might be due to the imbalance of growth potential between MYC*tg50 transgenic and normal cells in the same individual. (C) 1998 Academic Press.

Environmental factors such as tobacco smoking may have long-lasting effects on DNA methylation patterns, which might lead to changes in gene expression and in a broader context to the development or progression of various diseases. We conducted an epigenome-wide association study (EWAs) comparing current, former and never smokers from 1793 participants of the population-based KORA F4 panel, with replication in 479 participants from the KORA F3 panel, carried out by the 450K BeadChip with genomic DNA obtained from whole blood. We observed wide-spread differences in the degree of site-specific methylation (with p-values ranging from 9.31E-08 to 2.54E-182) as a function of tobacco smoking in each of the 22 autosomes, with the percent of variance explained by smoking ranging from 1.31 to 41.02. Depending on cessation time and pack-years, methylation levels in former smokers were found to be close to the ones seen in never smokers. In addition, methylation-specific protein binding patterns were observed for cg05575921 within AHRR, which had the highest level of detectable changes in DNA methylation associated with tobacco smoking (-24.40% methylation; p = 2.54E-182), suggesting a regulatory role for gene expression. The results of our study confirm the broad effect of tobacco smoking on the human organism, but also show that quitting tobacco smoking presumably allows regaining the DNA methylation state of never smokers.

Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10−8–1.2×10−43). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p, Author Summary Serum adiponectin levels are highly heritable and are inversely correlated with the risk of type 2 diabetes (T2D), coronary artery disease, stroke, and several metabolic traits. To identify common genetic variants associated with adiponectin levels and risk of T2D and metabolic traits, we conducted a meta-analysis of genome-wide association studies of 45,891 multi-ethnic individuals. In addition to confirming that variants at the ADIPOQ and CDH13 loci influence adiponectin levels, our analyses revealed that 10 new loci also affecting circulating adiponectin levels. We demonstrated that expression levels of several genes in these candidate regions are associated with serum adiponectin levels. Using a powerful novel method to assess the contribution of the identified variants with other traits using summary-level results from large-scale GWAS consortia, we provide evidence that the risk alleles for adiponectin are associated with deleterious changes in T2D risk and metabolic syndrome traits (triglycerides, HDL, post-prandial glucose, insulin, and waist-to-hip ratio), demonstrating that the identified loci, taken together, impact upon metabolic disease.

Abstract 2518 Introduction: Mutations in IDH1 and IHD2 at arginines 132 and 140 or 172, respectively, have recently been shown to play an important role in AML. Also the IDH1105GGT minor allele of the IDH1G105 (SNPrs11554137) polymorphism that is localized in the same exon as the IDH1R132 mutation has recently been reported to be an adverse prognostic factor in AML (JCO: 14, 2356–2364, 2010). Aim: We aimed at further delineating the frequency and impact of the IDH1105GGT minor allele in AML and also analyzed a healthy control cohort. Methods:IDH1G105 (SNPrs11554137) was analyzed in 961 AML patients by a LightCycler-based melting curve assay. Female/male ratio was 433/528 and age ranged from 13.1–100.4 years (median, 66.7 years). The results were compared to a healthy control cohort from the KORA (Cooperative Health Research in the Region of Augsburg) survey S4, which consists of 475 cases who where matched to the leukemia samples with respect to sex (193f/282m) and age (median: 67, range 32–81 years). Informed consent for participation in anonymized genetic studies was obtained from all individuals. IDH1G105 in the healthy cohort was analyzed by Sanger sequencing. Further mutation analyses were available in subsets of the AML patients, respectively, as follows: (IDH1R132 n=625, IDH2R140 n=587, IDH2R172 n=590, FLT3-ITD n=629, FLT3-TKD n=503, NPM1 n=628, CEBPA n=587, RUNX1 n=231, MLL-PTD n=629, NRAS n=273, KRAS n=133, ASXL1 n=470) and were analyzed as described previously. A subcohort of 634 AML with intermediate risk karyotype was analyzed for survival. Female/male ratio of this subcohort was 280/354 and age ranged from 15.7–86.6 years (median, 66.9 years). The adverse impact of IDH1R132, IDH2R140 and IDH2R172 on the NPM1+/FLT3-ITD- group has been shown previously for this group (Blood 2010 116: Abstract 102). Results: The IDH1105GGT minor allele was detected in 11.2% (108/961) in AML and in 8.8% (42/475) of the KORA control. This slight difference does not reach statistical significance (p=0.17) and thus there is no indication that this variance is a predisposing factor for leukemia. Also the frequency of a homozygous IDH1105GGT minor allele was not different between the AML cohort (3/108, 2.8%) and the KORA cohort (2/42, 4.8%, n.s.). In the AML cohort there was no association of the IDH1105GGT minor allele with age, WBC, platelet count or any of the above mentioned molecular mutations. In contrast, some differences in survival were observed: patients with the IDH1105GGT minor allele had a longer event free survival (EFS) than those with the IDH1105GGC major allele (median: 30.1 vs. 21.6 months, p=0.052) in the intermediate risk cohort. This prognostically favourable effect of the IDH1105GGT minor allele was most prominent in the NPM1+/FLT3- group with a median EFS of 45.1 vs 23.5 months as compared to those with the IDH1105GGC major allele (p=0.015). Conclusions: 1) The polymorphic IDH1105GGT minor allele was not found to be a marker predisposing for AML. 2) No association of the IDH1105GGT minor allele to any mutation or other biological parameters was detected. 3) We were not able to reproduce the previously published adverse impact of the IDH1105GGT minor allele on survival in AML. In contrast, in our cohort of 475 patients with intermediate risk AML the EFS was even better in patients carrying the IDH1105GGT minor allele, especially in the subcohort with NPM1+/FLT3−ITD−. Thus, we would suppose that the IDH1105GGT minor allele is a favorable molecular marker in intermediate risk AML. However, as these findings are in contrast to previously published data, further confirmation in additional studies is necessary to draw firm conclusions on the utility of the IDH1105 polymorphism as a marker for diagnostics and prognosis in AML. Disclosures: Schnittger: MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Eder:MLL Munich Leukemia Laboratory: Employment. Alpermann:MLL Munich Leukemia Laboratory: Employment. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.

Purpose The population-based KORA (Cooperative Health Research in the Region of Augsburg [Germany]) study was used to evaluate the prevalence of eye diseases and potential interactions with general health status, laboratory data, medication, and genetic background. Methods In all, 2593 probands, ranging in age from 32 to 71 years (mean: 52 years), were asked in a standardized interview for the presence of cataracts, glaucoma, and corneal or retinal disorders; positive answers were validated and specified by treating ophthalmologists. Additional data came from a questionnaire or from laboratory data. Results We validated 10 probands with corneal diseases (validation rate: 32%), 26 with retinal diseases (validation rate: 60%), 40 with glaucoma (validation rate: 75%), and 100 participants with cataracts (validation rate: 88%). Glaucoma was significantly associated with increasing age, diabetes and its treatment, and the use of drugs in airway diseases. Cataracts were significantly associated with increasing age, female sex, hypertension, and diabetes. In females, cataracts were particularly associated with the use of ophthalmological corticosteroids, some antihypertensives, and antidiabetics. In contrast, cataracts in males were associated only with the use of angiotensin-converting enzyme inhibitors. We also tested some polymorphic markers; two (GJA8, CRYBB3) were significantly associated with cataracts. Conclusions Self-reported ocular diagnoses by questionnaire showed varying degrees of accuracy; this method of data collection is valid, providing confirmation is obtained from treating ophthalmologists. It revealed a similar profile of major risk factors for cataracts (age, female sex, and diabetes) in Germany like that of other international studies. The reported associations between medical treatment and genetic polymorphisms in early-onset cataract merit further functional study.

The first genome wide association study (GWAS) for childhood asthma identified a novel major susceptibility locus on chromosome 17q21 harboring the ORMDL3 gene, but the role of previous asthma candidate genes was not specifically analyzed in this GWAS. We systematically identified 89 SNPs in 14 candidate genes previously associated with asthma in >3 independent study populations. We re-genotyped 39 SNPs in these genes not covered by GWAS performed in 703 asthmatics and 658 reference children. Genotyping data were compared to imputation data derived from Illumina HumanHap300 chip genotyping. Results were combined to analyze 566 SNPs covering all 14 candidate gene loci. Genotyped polymorphisms in ADAM33, GSTP1 and VDR showed effects with p-values

Summary Objective: The metabolic syndrome, a major cluster of risk factors for cardiovascular diseases, shows increasing prevalence worldwide. Several studies have established associations of both apolipoprotein A5 (APOA5) gene variants and upstream stimulatory factor 1 (USF1) gene variants with blood lipid levels and metabolic syndrome. USF1 is a transcription factor for APOA5. Methods: We investigated a possible interaction between these two genes on the risk for the metabolic syndrome, using data from the German population-based KORA survey 4 (1,622 men and women aged 55–74 years). Seven APOA5 single nucleotide polymorphisms (SNPs) were analyzed in combination with six USF1 SNPs, applying logistic regression in an additive model adjusting for age and sex and the definition for metabolic syndrome from the National Cholesterol Education Program’s Adult Treatment Panel III (NCEP (AIII)) including medication. Results: The overall prevalence for metabolic syndrome was 41%. Two SNP combinations showed a nominal gene-gene interaction (p values 0.024 and 0.047). The effect of one SNP was modified by the other SNP, with a lower risk for the metabolic syndrome with odds ratios (ORs) between 0.33 (95% CI = 0.13–0.83) and 0.40 (95% CI = 0.15–1.12) when the other SNP was homozygous for the minor allele. Nevertheless, none of the associations remained significant after correction for multiple testing. Conclusion: Thus, there is an indication of an interaction between APOA5 and USF1 on the risk for metabolic syndrome.

Background Early exposure to microbes reduces the risk for asthma. Toll-like receptors (TLRs) represent a major group of receptors for the specific recognition of pathogen-associated molecular patterns of microbes capable of activating innate and adaptive immunity. Objective Because TLRs can influence key events in the induction and perpetuation of asthma and atopy, we sought to determine whether genetic alterations in TLR genes affect asthma risk. Methods We systematically evaluated putatively functional genetic variants in all 10 human TLR genes for their association with different asthma phenotypes in a case-control study (n = 1872) by using matrix-assisted laser desorption/ionization time-of-flight genotyping. For polymorphisms showing association with atopic asthma, effects on gene and protein expression were studied by means of RT-PCR and flow cytometry ex vivo . T-cell cytokine production was evaluated by means of ELISA after stimulation of the respective TLRs with specific ligands. Results Protective effects on atopic asthma were identified for single nucleotide polymorphisms in TLR1 (odds ratio [OR], 0.54; 95% CI, 0.37-0.81; P = .002), TLR6 (OR, 0.54; 95% CI, 0.37-0.79; P = .003), and TLR10 (OR, 0.58; 95% CI, 0.39-0.86; P = .006), all capable of forming heterodimers with TLR2 . Effects remained significant after correction for multiple comparisons. PBMCs of minor allele carriers showed increased levels of the respective TLR mRNA and proteins, augmented inflammatory responses, increased T H 1 cytokine expression, and reduced T H 2-associated IL-4 production after specific stimulation. Conclusion These results suggest that functional relevant TLR1 and TLR6 variants are directly involved in asthma development.

Background Toll-like receptor 4 (TLR4), the signaling receptor for lipopolysaccharides, is an important member of the innate immunity system. Since several studies have suggested that type 2 diabetes might be associated with changes in the innate immune response, we sought to investigate the association between genetic variants in the TLR4 gene and incident type 2 diabetes. Methods A case-cohort study was conducted in initially healthy, middle-aged subjects from the MONICA/KORA Augsburg studies including 498 individuals with incident type 2 diabetes and 1,569 non-cases. Seven SNPs were systematically selected in the TLR4 gene and haplotypes were reconstructed. Results The effect of TLR4 SNPs on incident type 2 diabetes was modified by the ratio of total cholesterol to high-density lipoprotein cholesterol (TC/HDL-C). In men, four out of seven TLR4 variants showed significant interaction with TC/HDL-C after correction for multiple testing (p < 0.01). The influence of the minor alleles of those variants on the incidence of type 2 diabetes was observed particularly for male patients with high values of TC/HDL-C. Consistent with these findings, haplotype-based analyses also revealed that the effect of two haplotypes on incident type 2 diabetes was modified by TC/HDL-C in men (p < 10-3). However, none of the investigated variants or haplotypes was associated with type 2 diabetes in main effect models without assessment of effect modifications. Conclusion We conclude that minor alleles of several TLR4 variants, although not directly associated with type 2 diabetes might increase the risk for type 2 diabetes in subjects with high TC/HDL-C. Additionally, our results confirm previous studies reporting sex-related dissimilarities in the development of type 2 diabetes.

Interindividual variation in mean leukocyte telomere length (LTL) is associated with cancer and several age-associated diseases. We report here a genome-wide meta-analysis of 37,684 individuals with replication of selected variants in an additional 10,739 individuals. We identified seven loci, including five new loci, associated with mean LTL (P

article i nfo Objective: The interplay of genetic and nutritional regulation of the insulin-like growth factor-I axis in children is unclear. Therefore, potential gene-nutrient effects on serum levels of the IGF-I axis in a formula feeding trial were studied. Design: European multicenter randomized clinical trial of 1090 term, formula-fed infants assigned to receive cow's milk-based infant and follow-on formulae with lower (LP: 1.25 and 1.6 g/100 mL) or higher (HP: 2.05 and 3.2 g/100 mL) protein contents for the first 12 months of life; a comparison group of 588 breastfed infants (BF) was included. Eight single nucleotide polymorphisms (SNPs) of the IGF-1-(rs6214, rs1520220, rs978458, rs7136446, rs10735380, rs2195239, rs35767, and rs35766) and two of the IGFBP-3-(rs1496495, rs6670) gene were analyzed. Serum levels of total and free IGF-I, IGFBP-3 and the molar ratio IGF-1/IGFBP-3 at age 6 months were regressed on determined SNPs and feeding groups in 501 infants. Results: IGF-1-SNPs rs1520220, rs978458, and rs2195239 significantly increased total-IGF-I and molar-ratio IGF-I/IGFBP-3 by ~1.3 ng/mL and ~1.3 per allele, respectively; compared to LP infants concentration and molar-ratio were increased in HP by ~1.3 ng/mL and ~1.3 and decreased in BF infants by ~0.6 ng/mL and ~0.6, respectively. IGFBP-3 was only affected by the BF group with ~450 ng/mL lower levels than the LP group. No gene-feeding-group interaction was detected for any SNP, even without correction for multiple testing. Conclusions: Variants of the IGF-1-gene play an important role in regulating serum levels of the IGF-I axis but there is no gene-protein-interaction. The predominant nutritional regulation of IGF-I and IGFBP-3 gives further evidence that higher protein intake contributes to metabolic programming of growth.

Contains fulltext : 88201.pdf (Publisher’s version ) (Closed access) Atopic dermatitis (AD) and psoriasis are common skin diseases characterized by cutaneous inflammation and disturbed epidermal differentiation. Genome-wide analyses have shown overlapping susceptibility loci, such as the epidermal differentiation complex on chromosome 1q21. Recently, a deletion on 1q21 (LCE3C_LCE3B-del), comprising LCE3B and LCE3C, two members of the late cornified envelope (LCE) gene cluster, was found to be associated with psoriasis. Although the mechanistic role of LCE proteins in psoriasis has not been identified, these proteins are putatively involved in skin barrier formation and repair. Considering the potential genetic overlap between the two diseases and the recent finding that mutations in the skin barrier protein filaggrin are associated with AD, we investigated a possible association between LCE3C_LCE3B-del and AD. Evaluation of four different cohorts of European ancestry, containing a total of 1075 AD patients and 1658 controls, did not provide evidence for such an association. Subgroup analysis did not reveal an association with concomitant asthma. Our data suggest that the potential roles of skin barrier defects in the pathogenesis of AD and psoriasis are based on distinct genetic causes. 01 augustus 2010

The polymorphism SNP309 (rs2279744) in the promoter region of the MDM2 gene has been shown to alter protein expression and may play a role in the susceptibility to lung cancer. The MDM2 protein is a key inhibitor of p53 and several mechanisms of MDM2/p53 interactions are presently known: modulating DNA-repair, cell-cycle control, cell growth and apoptosis. We used 635 Caucasian patients diagnosed with lung cancer before 51 years of age and 1300 healthy gender and age frequency matched population Caucasian controls to investigate the association between the MDM2 SNP309 and the risk of developing early onset lung cancer. Conditional logistic models were applied to assess the genotype-phenotype association, adjusted for smoking. Compared to the GG genotype, the adjusted ORs for the TG and TT genotype were 0.9 (95% CI: 0.7–1.5) and 1.0 (95% CI: 0.7–1.5), respectively. Also no association was found for histological subtypes of lung cancer. The strength of this study is that within young cases the genetic component to develop lung cancer may be greater. Our results indicate that the MDM2 SNP309 is not significantly associated with lung carcinogenesis but point towards gender-specific differences.

Abstract 1394 Introduction: ASXL1 encodes a chromatin-binding protein that is member of the Polycomb group of proteins. Mutations in Exon 12 of ASXL1 have recently been described in a number of different myeloid malignancies. Reported frequencies in the respective entities are highly variable and may rely on in part on the difficulty to differentiate between somatic mutations and inborn polymorphisms. Especially the frequent variant G646WfsX12 of ASXL1 has been described to be most likely a polymorphism or even a technical artefact. Aim: The aim of this study was to evaluate frequencies of ASXL1 mutations in different myeloid entities, compare the mutation types and exclude polymorphisms. Methods: Exon 12 of ASXL1 was analyzed by direct Sanger sequencing. In total 1,053 patients with myeloid malignancies were analyzed. In detail, the cohort consisted of 657 patients (pts) with acute myeloid leukemia (AML), 76 pts with myelodysplastic syndrome (MDS), 21 pts with myeloproliferative neoplasias (MPN) not further classified, 14 pts with MDS/MPN overlaps, 229 pts with chronic myelomonocytic leukemia (CMML), 40 pts with chronic myeloid leukemia in blast crisis (CML-BC), and 16 pts with primary myelofibrosis (PMF). Female/male ratio was 440/613 and age ranged from 13.3–100.4 years (median, 68.0 years). In addition, we analyzed a healthy control cohort from the KORA (Cooperative Health Research in the Region of Augsburg) survey S4, which consists of 491 cases which were matched to the leukemia samples with respect to sex and age. Results: In total 273 ASXL1 variants were detected. All variants were detected with a mutation/wildtype load of 40–50%. 23 of these have been described to be rare polymorphisms (G652S: n=1, L815P: n=2, N986S: n=2, E1102D: n=15, A1312V: n=1, M1249V: n=1, S1253S: n=1) and were excluded from further calculations. Of the remaining 250 variants most were frameshifts (n=187, 74.8%) and stop mutations (n=46, 18.4%). Thus, 93.2% had disruptive character. Only 17 (6.8%) were missense mutations. The most frequent mutation was G646WfsX12 detected in 106 cases (42.4%). This variant was detected with similar frequency in all entities (AML: 49/657, 7.5%; MDS: 9/76, 11.8%; MPN: 2/21, 9.5%; MDS/MPN: 3/14, 23.4%; CMML: 37/229, 16.2%, CML-BC: 4/40, 10%, PMF: 2/16, 12.5%). G646WfsX12 has repeatedly been discussed not to be a somatic mutation but more likely a polymorphism or even a sequencing artefact due to an 8 base-pair guanine homopolymere at that site. Unfortunately, in none of these cases a healthy control tissue or a complete remission sample was available. However, we excluded a polymorphic character of G646WfsX12 in three ways: 1) a technical problem was excluded as all G646WfsX12 cases remained positive and all G646wt samples remained negative upon repeated testing. 2) In the KORA cohort of 491 samples one (0.2%) G646WfsX12 positive sample with mutation load of only 10% was identified. This incidence is significantly below that observed in myeloid malignancies and because of the low mutation load this case was interpreted as having a small premalignant clone or an early yet undetected clonal disease. 3) G646WfsX12 occurs due to three different mechanisms at the nucleic acid level: c.1934dupG (n=101), c.1927_1928insA (n=2), or c.1935dupT (n=3). Thus, we strongly believe that G646WfsX12 has to be regarded as a somatic mutation. In contrast, the so far undescribed G652S, T688M, and P722R variants were detected with a 50% load in 2, 1, and 1 KORA samples, respectively, and may be addressed as new rare germline variants. Other missense mutations observed in the patient cohort were not detected in the control cohort and were regarded as somatic mutations. Consequently, the total frequency of ASXL1 mutations in the different entities was determined as follows: AML: 100/657, 15.2%; MDS: 24/76, 31.6%; MPN: 7/21, 33.3%; MDS/MPN: 6/14, 46.8%; CMML: 94/229, 41.0%, CML-BC: 13/40, 32.5%, PMF: 6/16, 37.5%). Summary:ASXL1 mutations are frequent in all myeloid malignancies with the highest incidences in CMML, MDS/MPN overlap and CML-BC. There are no disease specific ASXL1 mutation patterns. Disrupting mutations (frameshift and nonsense) are the most common mutation types (93.2%). G646WfsX12 is the most frequent alteration and was verified here as a true somatic mutation. Missense mutations are rare and should be regarded carefully as possibly innocent bystanders or very rare polymorphisms. Disclosures: Schnittger: MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Eder:MLL Munich Leukemia Laboratory: Employment. Fasan:MLL Munich Leukemia Laboratory: Employment. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.

Serum urate, the final breakdown product of purine metabolism, is causally involved in the pathogenesis of gout, and implicated in cardiovascular disease and type 2 diabetes. Serum urate levels highly differ between men and women; however the underlying biological processes in its regulation are still not completely understood and are assumed to result from a complex interplay between genetic, environmental and lifestyle factors. In order to describe the metabolic vicinity of serum urate, we analyzed 355 metabolites in 1,764 individuals of the population-based KORA F4 study and constructed a metabolite network around serum urate using Gaussian Graphical Modeling in a hypothesis-free approach. We subsequently investigated the effect of sex and urate lowering medication on all 38 metabolites assigned to the network. Within the resulting network three main clusters could be detected around urate, including the well-known pathway of purine metabolism, as well as several dipeptides, a group of essential amino acids, and a group of steroids. Of the 38 assigned metabolites, 25 showed strong differences between sexes. Association with uricostatic medication intake was not only confined to purine metabolism but seen for seven metabolites within the network. Our findings highlight pathways that are important in the regulation of serum urate and suggest that dipeptides, amino acids, and steroid hormones are playing a role in its regulation. The findings might have an impact on the development of specific targets in the treatment and prevention of hyperuricemia. Electronic supplementary material The online version of this article (doi:10.1007/s11306-013-0565-2) contains supplementary material, which is available to authorized users.

Background— High-density lipoprotein cholesterol (HDLC) is a strong risk factor for atherosclerosis and is assumed to be under considerable genetic control. We aimed to identify gene regions that influence HDLC levels by a genome-wide association analysis in the population-based KORA (Cooperative Health Research in the Region of Augsburg) study. Methods and Results— In KORA S3/F3 (n=1643), we analyzed 377 865 quality-checked single-nucleotide polymorphisms (SNPs; 500K, Affymetrix, Santa Clara, Calif), complemented by the publicly available genome-wide association results from the Diabetes Genetics Initiative (n=2631) and by replication data from KORA S4 (n=4037) and the Copenhagen City Heart Study (n=9205). Among the 13 SNPs selected from the KORA S3/F3 500K probability value list, 3 showed consistent associations in subsequent replications: 1 SNP 10 kb upstream of CETP (pooled probability value=8.5�10 −27 ), 1 SNP approximately 40 kb downstream of LIPG (probability value=4.67�10 −10 ), both independent of previously reported SNPs, and 1 from an already reported region of LPL (probability value=2.82�10 −11 ). Bioinformatical analyses indicate a potential functional relevance of the respective SNPs. Conclusions— The present genome-wide association study identified 2 interesting HDLC-relevant regions upstream of CETP and downstream of LIPG . This draws attention to the importance of long-range effects of intergenic regions, which have been underestimated so far, and may impact future candidate-gene–association studies toward extending the region analyzed. Furthermore, the present study reinforced CETP and LPL as HDLC genes and thereby underscores the power of this type of genome-wide association approach to pinpoint associations of common polymorphisms with effects explaining as little as 0.5% of the HDLC variance in the general population.

The interleukin-1 cluster on human chromosome 2q12-2q14 harbors various promising candidate genes for asthma and other inflammatory diseases. We conducted a systematic association study with single-nucleotide polymorphisms (SNPs) located in candidate genes situated in this cluster. Single-marker, two-locus and three-locus haplotype analysis of SNPs yielded several significant results (p < 0.05-0.0021) for the human IL1RN gene encoding the IL-1 receptor antagonist protein, an antiinflammatory cytokine that plays an important role in maintaining the balance between inflammatory and antiinflammatory cytokines. These findings were replicated and confirmed in an independent Italian family sample in which significant, although weaker, association with asthma was detected. A sequencing approach to the coding region of the human IL1RN gene revealed additional DNA variants, from which a selection was also associated with the disease in German and Italian samples. Calculation of the linkage disequilibrium for the human IL1RN gene showed strong linkage disequilibrium for nearly all analyzed SNPs. Further haplotype analysis indicated that six SNPs are sufficient for tagging all haplotypes with a prevalence of more than 1%. The most frequent haplotype constructed from these SNPs was 1.4-fold overtransmitted in the German family sample.

Recent increases in SARS-CoV-2 infections have led to questions about duration and quality of vaccine-induced immune protection. While numerous studies have been published on immune responses triggered by vaccination, these often focus on studying the impact of one or two immunisation schemes within subpopulations such as immunocompromised individuals or healthcare workers. To provide information on the duration and quality of vaccine-induced immune responses against SARS-CoV-2, we analyzed antibody titres against various SARS-CoV-2 antigens and ACE2 binding inhibition against SARS-CoV-2 wild-type and variants of concern in samples from a large German population-based seroprevalence study (MuSPAD) who had received all currently available immunisation schemes. We found that homologous mRNA-based or heterologous prime-boost vaccination produced significantly higher antibody responses than vector-based homologous vaccination. Ad26.CoV2S.2 performance was particularly concerning with reduced titres and 91.7% of samples classified as non-responsive for ACE2 binding inhibition, suggesting that recipients require a booster mRNA vaccination. While mRNA vaccination induced a higher ratio of RBD- and S1-targeting antibodies, vector-based vaccines resulted in an increased proportion of S2-targeting antibodies. Given the role of RBD- and S1-specific antibodies in neutralizing SARS-CoV-2, their relative over-representation after mRNA vaccination may explain why these vaccines have increased efficacy compared to vector-based formulations. Previously infected individuals had a robust immune response once vaccinated, regardless of which vaccine they received, which could aid future dose allocation should shortages arise for certain manufacturers. Overall, both titres and ACE2 binding inhibition peaked approximately 28 days post-second vaccination and then decreased.

Publisher's version (útgefin grein), Objective: To explore genetic and lifestyle risk factors of MRI-defined brain infarcts (BI) in large population-based cohorts. Methods We performed meta-analyses of genome-wide association studies (GWAS) and examined associations of vascular risk factors and their genetic risk scores (GRS) with MRI-defined BI and a subset of BI, namely, small subcortical BI (SSBI), in 18 population-based cohorts (n=20,949) from 5 ethnicities (3,726 with BI, 2,021 with SSBI). Top loci were followed up in 7 population-based cohorts (n = 6,862; 1,483 with BI, 630 with SBBI), and we tested associations with related phenotypes including ischemic stroke and pathologically defined BI. Results: The mean prevalence was 17.7% for BI and 10.5% for SSBI, steeply rising after age 65. Two loci showed genome-wide significant association with BI: FBN2, p = 1.77 × 10-8; and LINC00539/ZDHHC20, p = 5.82 × 10-9. Both have been associated with blood pressure (BP)-related phenotypes, but did not replicate in the smaller follow-up sample or show associations with related phenotypes. Age- and sex-adjusted associations with BI and SSBI were observed for BP traits (p value for BI, p[BI] = 9.38 × 10-25; p [SSBI] = 5.23 × 10-14 for hypertension), smoking (p[BI]= 4.4 × 10-10; p [SSBI] = 1.2 × 10 -4), diabetes (p[BI] = 1.7 × 10 -8; p [SSBI] = 2.8 × 10 -3), previous cardiovascular disease (p [BI] = 1.0 × 10-18; p [SSBI] = 2.3 × 10-7), stroke (p [BI] = 3.9 × 10-69; p [SSBI] = 3.2 × 10 -24), and MRI-defined white matter hyperintensity burden (p [BI]=1.43 × 10-157; p [SSBI] = 3.16 × 10-106), but not with body mass index or cholesterol. GRS of BP traits were associated with BI and SSBI (p ≤ 0.0022), without indication of directional pleiotropy. Conclusion: In this multiethnic GWAS meta-analysis, including over 20,000 population-based participants, we identified genetic risk loci for BI requiring validation once additional large datasets become available. High BP, including genetically determined, was the most significant modifiable, causal risk factor for BI., CHAP: R01-AG-11101, R01-AG-030146, NIRP-14-302587. SMART: This study was supported by a grant from the Netherlands Organization for Scientific Research–Medical Sciences (project no. 904-65–095). LBC: The authors thank the LBC1936 participants and the members of the LBC1936 research team who collected and collated the phenotypic and genotypic data. The LBC1936 is supported by Age UK (Disconnected Mind Programme grant). The work was undertaken by The University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology, part of the cross-council Lifelong Health and Wellbeing Initiative (MR/K026992/1). The brain imaging was performed in the Brain Research Imaging Centre (https://www.ed.ac.uk/clinical-sciences/edinburgh-imaging), a center in the SINAPSE Collaboration (sinapse.ac.uk) supported by the Scottish Funding Council and Chief Scientist Office. Funding from the UK Biotechnology and Biological Sciences Research Council (BBSRC) and the UK Medical Research Council is acknowledged. Genotyping was supported by a grant from the BBSRC (ref. BB/F019394/1). PROSPER: The PROSPER study was supported by an investigator-initiated grant obtained from Bristol-Myers Squibb. Prof. Dr. J.W. Jukema is an Established Clinical Investigator of the Netherlands Heart Foundation (grant 2001 D 032). Support for genotyping was provided by the seventh framework program of the European commission (grant 223004) and by the Netherlands Genomics Initiative (Netherlands Consortium for Healthy Aging grant 050-060-810). SCES and SiMES: National Medical Research Council Singapore Centre Grant NMRC/CG/013/2013. C.-Y.C. is supported by the National Medical Research Council, Singapore (CSA/033/2012), Singapore Translational Research Award (STaR) 2013. Dr. Kamran Ikram received additional funding from the Singapore Ministry of Health's National Medical Research Council (NMRC/CSA/038/2013). SHIP: SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grants no. 01ZZ9603, 01ZZ0103, and 01ZZ0403), the Ministry of Cultural Affairs, as well as the Social Ministry of the Federal State of Mecklenburg–West Pomerania, and the network “Greifswald Approach to Individualized Medicine (GANI_MED)” funded by the Federal Ministry of Education and Research (grant 03IS2061A). Genome-wide data have been supported by the Federal Ministry of Education and Research (grant no. 03ZIK012) and a joint grant from Siemens Healthineers, Erlangen, Germany, and the Federal State of Mecklenburg–West Pomerania. Whole-body MRI was supported by a joint grant from Siemens Healthineers, Erlangen, Germany, and the Federal State of Mecklenburg–West Pomerania. The University of Greifswald is a member of the Caché Campus program of the InterSystems GmbH. OATS (Older Australian Twins Study): OATS was supported by an Australian National Health and Medical Research Council (NHRMC)/Australian Research Council (ARC) Strategic Award (ID401162) and by a NHMRC grant (ID1045325). OATS was facilitated via access to the Australian Twin Registry, which is supported by the NHMRC Enabling Grant 310667. The OATS genotyping was partly supported by a Commonwealth Scientific and Industrial Research Organisation Flagship Collaboration Fund Grant. NOMAS: The Northern Manhattan Study is funded by the NIH grant “Stroke Incidence and Risk Factors in a Tri-Ethnic Region” (NINDS R01NS 29993). TASCOG: NHMRC and Heart Foundation. AGES: The study was funded by the National Institute on Aging (NIA) (N01-AG-12100), Hjartavernd (the Icelandic Heart Association), and the Althingi (the Icelandic Parliament), with contributions from the Intramural Research Programs at the NIA, the National Heart, Lung, and Blood Institute (NHLBI), and the National Institute of Neurological Disorders and Stroke (NINDS) (Z01 HL004607-08 CE). ERF: The ERF study as a part of European Special Populations Research Network (EUROSPAN) was supported by European Commission FP6 STRP grant no. 018947 (LSHG-CT-2006-01947) and also received funding from the European Community's Seventh Framework Programme (FP7/2007–2013)/grant agreement HEALTH-F4-2007-201413 by the European Commission under the programme “Quality of Life and Management of the Living Resources” of 5th Framework Programme (no. QLG2-CT-2002-01254). High-throughput analysis of the ERF data was supported by a joint grant from Netherlands Organization for Scientific Research and the Russian Foundation for Basic Research (NWO-RFBR 047.017.043). Exome sequencing analysis in ERF was supported by the ZonMw grant (project 91111025). Najaf Amin is supported by the Netherlands Brain Foundation (project no. F2013[1]-28). ARIC: The Atherosclerosis Risk in Communities study was performed as a collaborative study supported by NHLBI contracts (HHSN268201100005C, HSN268201100006C, HSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, and HHSN268201100012C), R01HL70825, R01HL087641, R01HL59367, and R01HL086694; National Human Genome Research Institute contract U01HG004402; and NIH contract HHSN268200625226C. Infrastructure was partly supported by grant no. UL1RR025005, a component of the NIH and NIH Roadmap for Medical Research. This project was also supported by NIH R01 grant NS087541 to M.F. FHS: This work was supported by the National Heart, Lung and Blood Institute's Framingham Heart Study (contracts no. N01-HC-25195 and no. HHSN268201500001I), and its contract with Affymetrix, Inc. for genotyping services (contract no. N02-HL-6-4278). A portion of this research utilized the Linux Cluster for Genetic Analysis (LinGA-II) funded by the Robert Dawson Evans Endowment of the Department of Medicine at Boston University School of Medicine and Boston Medical Center. This study was also supported by grants from the NIA (R01s AG033040, AG033193, AG054076, AG049607, AG008122, and U01-AG049505) and the NINDS (R01-NS017950, UH2 NS100605). Dr. DeCarli is supported by the Alzheimer's Disease Center (P30 AG 010129). ASPS: The research reported in this article was funded by the Austrian Science Fund (FWF) grant nos. P20545-P05, P13180, and P20545-B05, by the Austrian National Bank Anniversary Fund, P15435, and the Austrian Ministry of Science under the aegis of the EU Joint Programme–Neurodegenerative Disease Research (JPND) (jpnd.eu). LLS: The Leiden Longevity Study has received funding from the European Union's Seventh Framework Programme (FP7/2007–2011) under grant agreement no. 259679. This study was supported by a grant from the Innovation-Oriented Research Program on Genomics (SenterNovem IGE05007), the Centre for Medical Systems Biology, and the Netherlands Consortium for Healthy Ageing (grant 050-060-810), all in the framework of the Netherlands Genomics Initiative, Netherlands Organization for Scientific Research (NWO), UnileverColworth, and by BBMRI-NL, a Research Infrastructure financed by the Dutch government (NWO 184.021.007). CHS: This CHS research was supported by contracts HHSN268201200036C, HHSN268200800007C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086, N01HC15103, and HHSN268200960009C and grants U01HL080295, R01HL087652, R01HL105756, R01HL103612, R01HL120393, R01HL085251, and R01HL130114 from the NHLBI with additional contribution from NINDS. Additional support was provided through R01AG023629 from the NIA. A full list of principal CHS investigators and institutions can be found at CHS-NHLBI.org. The provision of genotyping data was supported in part by the National Center for Advancing Translational Sciences, CTSI grant UL1TR001881, and the National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center grant DK063491 to the Southern California Diabetes Endocrinology Research Center. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. Rotterdam Study: The generation and management of GWAS genotype data for the Rotterdam Study is supported by the Netherlands Organisation of Scientific Research (NWO) Investments (no. 175.010.2005.011, 911-03-012). This study is funded by the Research Institute for Diseases in the Elderly (014-93-015; RIDE2), the Netherlands Genomics Initiative (NGI)/NWO project no. 050-060-810. The Rotterdam Study is funded by Erasmus MC Medical Center and Erasmus MC University, Rotterdam, Netherlands Organization for Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam. M.A.I. is supported by an NWO Veni grant (916.13.054). The 3-City Study: The 3-City Study is conducted under a partnership agreement among the Institut National de la Santé et de la Recherche Médicale (INSERM), the University of Bordeaux, and Sanofi-Aventis. The Fondation pour la Recherche Médicale funded the preparation and initiation of the study. The 3C Study is also supported by the Caisse Nationale Maladie des Travailleurs Salariés, Direction Générale de la Santé, Mutuelle Générale de l’Education Nationale (MGEN), Institut de la Longévité, Conseils Régionaux of Aquitaine and Bourgogne, Fondation de France, and Ministry of Research–INSERM Programme “Cohortes et collections de données biologiques.” C.T. and S.D. have received investigator-initiated research funding from the French National Research Agency (ANR) and from the Fondation Leducq. S.D. is supported by a starting grant from the European Research Council (SEGWAY), a grant from the Joint Programme of Neurodegenerative Disease research (BRIDGET), from the European Union's Horizon 2020 research and innovation programme under grant agreements No 643417 & No 640643, and by the Initiative of Excellence of Bordeaux University. Part of the computations were performed at the Bordeaux Bioinformatics Center (CBiB), University of Bordeaux. This work was supported by the National Foundation for Alzheimer's Disease and Related Disorders, the Institut Pasteur de Lille, the Labex DISTALZ, and the Centre National de Génotypage. ADGC: The Alzheimer Disease Genetics Consortium is supported by NIH. NIH-NIA supported this work through the following grants: ADGC, U01 AG032984, RC2 AG036528; NACC, U01 AG016976; NCRAD, U24 AG021886; NIA LOAD, U24 AG026395, U24 AG026390; Banner Sun Health Research Institute, P30 AG019610; Boston University, P30 AG013846, U01 AG10483, R01 CA129769, R01 MH080295, R01 AG017173, R01 AG025259, R01AG33193; Columbia University, P50 AG008702, R37 AG015473; Duke University, P30 AG028377, AG05128; Emory University, AG025688; Group Health Research Institute, UO1 AG06781, UO1 HG004610; Indiana University, P30 AG10133; Johns Hopkins University, P50 AG005146, R01 AG020688; Massachusetts General Hospital, P50 AG005134; Mayo Clinic, P50 AG016574; Mount Sinai School of Medicine, P50 AG005138, P01 AG002219; New York University, P30 AG08051, MO1RR00096, UL1 RR029893, 5R01AG012101, 5R01AG022374, 5R01AG013616, 1RC2AG036502, 1R01AG035137; Northwestern University, P30 AG013854; Oregon Health & Science University, P30 AG008017, R01 AG026916; Rush University, P30 AG010161, R01 AG019085, R01 AG15819, R01 AG17917, R01 AG30146; TGen, R01 NS059873; University of Alabama at Birmingham, P50 AG016582, UL1RR02777; University of Arizona, R01 AG031581; University of California, Davis, P30 AG010129; University of California, Irvine, P50 AG016573, P50, P50 AG016575, P50 AG016576, P50 AG016577; University of California, Los Angeles, P50 AG016570; University of California, San Diego, P50 AG005131; University of California, San Francisco, P50 AG023501, P01 AG019724; University of Kentucky, P30 AG028383, AG05144; University of Michigan, P50 AG008671; University of Pennsylvania, P30 AG010124; University of Pittsburgh, P50 AG005133, AG030653; University of Southern California, P50 AG005142; University of Texas Southwestern, P30 AG012300; University of Miami, R01 AG027944, AG010491, AG027944, AG021547, AG019757; University of Washington, P50 AG005136; Vanderbilt University, R01 AG019085; and Washington University, P50 AG005681, P01 AG03991. The Kathleen Price Bryan Brain Bank at Duke University Medical Center is funded by NINDS grant NS39764, NIMH MH60451, and by GlaxoSmithKline. Genotyping of the TGEN2 cohort was supported by Kronos Science. The TGen series was also funded by NIA grant AG041232, the Banner Alzheimer's Foundation, The Johnnie B. Byrd Sr. Alzheimer's Institute, the Medical Research Council, and the state of Arizona and also includes samples from the following sites: Newcastle Brain Tissue Resource (funding via the Medical Research Council [MRC], local NHS trusts, and Newcastle University), MRC London Brain Bank for Neurodegenerative Diseases (funding via the Medical Research Council), South West Dementia Brain Bank (funding via numerous sources including the Higher Education Funding Council for England [HEFCE], Alzheimer's Research Trust [ART], BRACE, as well as North Bristol NHS Trust Research and Innovation Department and DeNDRoN), The Netherlands Brain Bank (funding via numerous sources including Stichting MS Research, Brain Net Europe, Hersenstichting Nederland Breinbrekend Werk, International Parkinson Fonds, Internationale Stiching Alzheimer Onderzoek), Institut de Neuropatologia, Servei Anatomia Patologica, and Universitat de Barcelona). ADNI: Funding for ADNI is through the Northern California Institute for Research and Education by grants from Abbott, AstraZeneca AB, Bayer Schering Pharma AG, Bristol-Myers Squibb, Eisai Global Clinical Development, Elan Corporation, Genentech, GE Healthcare, GlaxoSmithKline, Innogenetics, Johnson & Johnson, Eli Lilly and Co., Medpace, Inc., Merck and Co., Inc., Novartis AG, Pfizer Inc, F. Hoffman-La Roche, Schering-Plough, Synarc, Inc., Alzheimer's Association, Alzheimer's Drug Discovery Foundation, the Dana Foundation, and the National Institute of Biomedical Imaging and Bioengineering and NIA grants U01 AG024904, RC2 AG036535, and K01 AG030514. Support was also provided by the Alzheimer's Association (LAF, IIRG-08-89720; MAP-V, IIRG-05-14147) and the US Department of Veterans Affairs Administration, Office of Research and Development, Biomedical Laboratory Research Program. SiGN: Stroke Genetic Network (SiGN) was supported in part by award nos. U01NS069208 and R01NS100178 from NINDS. Genetics of Early-Onset Stroke (GEOS) Study was supported by the NIH Genes, Environment and Health Initiative (GEI) grant U01 HG004436, as part of the GENEVA consortium under GEI, with additional support provided by the Mid-Atlantic Nutrition and Obesity Research Center (P30 DK072488); and the Office of Research and Development, Medical Research Service, and the Baltimore Geriatrics Research, Education, and Clinical Center of the Department of Veterans Affairs. Genotyping services were provided by the Johns Hopkins University Center for Inherited Disease Research (CIDR), which is fully funded through a federal contract from the NIH to Johns Hopkins University (contract no. HHSN268200782096C). Assistance with data cleaning was provided by the GENEVA Coordinating Center (U01 HG 004446; PI Bruce S. Weir). Study recruitment and assembly of datasets were supported by a Cooperative Agreement with the Division of Adult and Community Health, Centers for Disease Control and Prevention, and by grants from NINDS and the NIH Office of Research on Women's Health (R01 NS45012, U01 NS069208-01). METASTROKE: ASGC: Australian population control data were derived from the Hunter Community Study. This research was funded by grants from the Australian National and Medical Health Research Council (NHMRC Project Grant ID: 569257), the Australian National Heart Foundation (NHF Project Grant ID: G 04S 1623), the University of Newcastle, the Gladys M Brawn Fellowship scheme, and the Vincent Fairfax Family Foundation in Australia. E.G.H. was supported by a Fellowship from the NHF and National Stroke Foundation of Australia (ID: 100071). J.M. was supported by an Australian Postgraduate Award. BRAINS: Bio-Repository of DNA in Stroke (BRAINS) is partly funded by a Senior Fellowship from the Department of Health (UK) to P.S., the Henry Smith Charity, and the UK-India Education Research Institutive (UKIERI) from the British Council. GEOS: Genetics of Early Onset Stroke (GEOS) Study, Baltimore, was supported by GEI Grant U01 HG004436, as part of the GENEVA consortium under GEI, with additional support provided by the Mid-Atlantic Nutrition and Obesity Research Center (P30 DK072488), and the Office of Research and Development, Medical Research Service, and the Baltimore Geriatrics Research, Education, and Clinical Center of the Department of Veterans Affairs. Genotyping services were provided by the Johns Hopkins University Center for Inherited Disease Research (CIDR), which is fully funded through a federal contract from the NIH to the Johns Hopkins University (contract no. HHSN268200782096C). Assistance with data cleaning was provided by the GENEVA Coordinating Center (U01 HG 004446; PI Bruce S. Weir). Study recruitment and assembly of datasets were supported by a Cooperative Agreement with the Division of Adult and Community Health, Centers for Disease Control and Prevention, and by grants from NINDS and the NIH Office of Research on Women's Health (R01 NS45012, U01 NS069208-01). HPS: Heart Protection Study (HPS) (ISRCTN48489393) was supported by the UK MRC, British Heart Foundation, Merck and Co. (manufacturers of simvastatin), and Roche Vitamins Ltd. (manufacturers of vitamins). Genotyping was supported by a grant to Oxford University and CNG from Merck and Co. J.C.H. acknowledges support from the British Heart Foundation (FS/14/55/30806). ISGS: Ischemic Stroke Genetics Study (ISGS)/Siblings With Ischemic Stroke Study (SWISS) was supported in part by the Intramural Research Program of the NIA, NIH project Z01 AG-000954-06. ISGS/SWISS used samples and clinical data from the NIH-NINDS Human Genetics Resource Center DNA and Cell Line Repository (ccr.coriell.org/ninds), human subjects protocol nos. 2003-081 and 2004-147. ISGS/SWISS used stroke-free participants from the Baltimore Longitudinal Study of Aging (BLSA) as controls. The inclusion of BLSA samples was supported in part by the Intramural Research Program of the NIA, NIH project Z01 AG-000015-50, human subjects protocol no. 2003-078. The ISGS study was funded by NIH-NINDS Grant R01 NS-42733 (J.F.M.). The SWISS study was funded by NIH-NINDS Grant R01 NS-39987 (J.F.M.). This study used the high-performance computational capabilities of the Biowulf Linux cluster at the NIH (biowulf.nih.gov). MGH-GASROS: MGH Genes Affecting Stroke Risk and Outcome Study (MGH-GASROS) was supported by NINDS (U01 NS069208), the American Heart Association/Bugher Foundation Centers for Stroke Prevention Research 0775010N, the NIH and NHLBI's STAMPEED genomics research program (R01 HL087676), and a grant from the National Center for Research Resources. The Broad Institute Center for Genotyping and Analysis is supported by grant U54 RR020278 from the National Center for Research resources. Milan: Milano–Besta Stroke Register Collection and genotyping of the Milan cases within CEDIR were supported by the Italian Ministry of Health (grant nos.: RC 2007/LR6, RC 2008/LR6; RC 2009/LR8; RC 2010/LR8; GR-2011-02347041), FP6 LSHM-CT-2007-037273 for the PROCARDIS control samples. WTCCC2: Wellcome Trust Case-Control Consortium 2 (WTCCC2) was principally funded by the Wellcome Trust, as part of the Wellcome Trust Case Control Consortium 2 project (085475/B/08/Z and 085475/Z/08/Z and WT084724MA). The Stroke Association provided additional support for collection of some of the St George's, London cases. The Oxford cases were collected as part of the Oxford Vascular Study, which is funded by the MRC, Stroke Association, Dunhill Medical Trust, National Institute of Health Research (NIHR), and the NIHR Biomedical Research Centre, Oxford. The Edinburgh Stroke Study was supported by the Wellcome Trust (clinician scientist award to C.L.M.S.) and the Binks Trust. Sample processing occurred in the Genetics Core Laboratory of the Wellcome Trust Clinical Research Facility, Western General Hospital, Edinburgh. Much of the neuroimaging occurred in the Scottish Funding Council Brain Imaging Research Centre (https://www.ed.ac.uk/clinical-sciences/edinburgh-imaging), Division of Clinical Neurosciences, University of Edinburgh, a core area of the Wellcome Trust Clinical Research Facility, and part of the SINAPSE (Scottish Imaging Network: A Platform for Scientific Excellence) collaboration (sinapse.ac.uk), funded by the Scottish Funding Council and the Chief Scientist Office. Collection of the Munich cases and data analysis was supported by the Vascular Dementia Research Foundation. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreements no. 666881, SVDs@target (to M.D.) and no. 667375, CoSTREAM (to M.D.); the DFG as part of the Munich Cluster for Systems Neurology (EXC 1010 SyNergy) and the CRC 1123 (B3) (to M.D.); the Corona Foundation (to M.D.); the Fondation Leducq (Transatlantic Network of Excellence on the Pathogenesis of Small Vessel Disease of the Brain) (to M.D.); the e:Med program (e:AtheroSysMed) (to M.D.) and the FP7/2007-2103 European Union project CVgenes@target (grant agreement no. Health-F2-2013-601456) (to M.D.). M.F. and A.H. acknowledge support from the BHF Centre of Research Excellence in Oxford and the Wellcome Trust core award (090532/Z/09/Z). VISP: The GWAS component of the Vitamin Intervention for Stroke Prevention (VISP) study was supported by the US National Human Genome Research Institute (NHGRI), grant U01 HG005160 (PI Michèle Sale and Bradford Worrall), as part of the Genomics and Randomized Trials Network (GARNET). Genotyping services were provided by the Johns Hopkins University Center for Inherited Disease Research (CIDR), which is fully funded through a federal contract from the NIH to Johns Hopkins University. Assistance with data cleaning was provided by the GARNET Coordinating Center (U01 HG005157; PI Bruce S. Weir). Study recruitment and collection of datasets for the VISP clinical trial were supported by an investigator-initiated research grant (R01 NS34447; PI James Toole) from the US Public Health Service, NINDS, Bethesda, MD. Control data obtained through the database of genotypes and phenotypes (dbGAP) maintained and supported by the United States National Center for Biotechnology Information, US National Library of Medicine. WHI: Funding support for WHI-GARNET was provided through the NHGRI GARNET (grant no. U01 HG005152). Assistance with phenotype harmonization and genotype cleaning, as well as with general study coordination, was provided by the GARNET Coordinating Center (U01 HG005157). Funding support for genotyping, which was performed at the Broad Institute of MIT and Harvard, was provided by the GEI (U01 HG004424). R.L. is a senior clinical investigator of FWO Flanders. F.W.A. is supported by a Dekker scholarship-Junior Staff Member 2014T001–Netherlands Heart Foundation and UCL Hospitals NIHR Biomedical Research Centre.