Polygenic risk has an impact on the structural plasticity of hippocampal subfields during aerobic exercise combined with cognitive remediation in multi-episode schizophrenia.

Preliminary studies suggest that, besides improving cognition, aerobic exercise might increase hippocampal volume in schizophrenia patients; however, results are not consistent. Individual mechanisms of volume changes are unknown but might be connected to the load of risk genes. Genome-wide association studies have uncovered the polygenic architecture of schizophrenia. The secondary analysis presented here aimed to determine the modulatory role of schizophrenia polygenic risk scores (PRSs) on volume changes in the total hippocampus and cornu ammonis (CA) 1, CA2/3, CA4/dentate gyrus (DG) and subiculum over time. We studied 20 multi-episode schizophrenia patients and 23 healthy controls who performed aerobic exercise (endurance training) combined with cognitive remediation for 3 months and 21 multi-episode schizophrenia patients allocated to a control intervention (table soccer) combined with cognitive remediation. Magnetic resonance imaging-based assessments were performed at baseline and after 3 months with FreeSurfer. No effects of PRSs were found on total hippocampal volume change. Subfield analyses showed that the volume changes between baseline and 3 months in the left CA4/DG were significantly influenced by PRSs in schizophrenia patients performing aerobic exercise. A larger genetic risk burden was associated with a less pronounced volume increase or a decrease in volume over the course of the exercise intervention. Results of exploratory enrichment analyses reinforced the notion of genetic risk factors modulating biological processes tightly related to synaptic ion channel activity, calcium signaling, glutamate signaling and regulation of cell morphogenesis. We hypothesize that a high polygenic risk may negatively influence neuroplasticity in CA4/DG during aerobic exercise in schizophrenia.

Impact of genomic risk factors on survival after haematopoietic stem cell transplantation for patients with acute leukaemia.

The EBMT risk score is an established tool successfully used in the prognosis of survival post-HSCT and is applicable for a range of haematological disorders. One of its main advantages is that score generation involves summation of clinical parameters that are available pretransplant. However, the EBMT risk score is recognized as not being optimal. Previous analyses, involving patients with various diagnoses, have shown that non-HLA gene polymorphisms influence outcome after allogeneic HSCT. This study is novel as it focuses only on patients having acute leukaemia (N = 458) and attempts to demonstrate how non-HLA gene polymorphisms can be added to the EBMT risk score in a Cox regression model to improve prognostic ability for overall survival. The results of the study found that three genetic factors improved EBMT risk score. The presence of MAL (rs8177374) allele T in the patient, absence of glucocorticoid receptor haplotype (consisting of rs6198, rs33389 and rs33388) ACT in the patient and absence of heat-shock protein 70-hom (+2437) (rs2227956) allele C in the patient were associated with decreased survival time. When compared to the EBMT risk score, the scores combining EBMT risk score with the genetic factors had an improved correlation with clinical outcome and better separation of risk groups. A bootstrapping technique, involving repeated testing of a model using multiple validation sets, also revealed that the newly proposed model had improved predictive value when compared to the EBMT risk score alone. Results support the view that non-HLA polymorphisms could be useful for pretransplant clinical assessment and provide evidence that polymorphisms in the recipient genotype may influence incoming donor cells, suppressing the initiation of the graft versus leukaemia effect and reducing survival.

Genome-wide meta-analysis reveals common splice site acceptor variant in CHRNA4 associated with nicotine dependence.

We conducted a 1000 Genomes-imputed genome-wide association study (GWAS) meta-analysis for nicotine dependence, defined by the Fagerström Test for Nicotine Dependence in 17 074 ever smokers from five European-ancestry samples. We followed up novel variants in 7469 ever smokers from five independent European-ancestry samples. We identified genome-wide significant association in the alpha-4 nicotinic receptor subunit (CHRNA4) gene on chromosome 20q13: lowest P=8.0 × 10(-9) across all the samples for rs2273500-C (frequency=0.15; odds ratio=1.12 and 95% confidence interval=1.08-1.17 for severe vs mild dependence). rs2273500-C, a splice site acceptor variant resulting in an alternate CHRNA4 transcript predicted to be targeted for nonsense-mediated decay, was associated with decreased CHRNA4 expression in physiologically normal human brains (lowest P=7.3 × 10(-4)). Importantly, rs2273500-C was associated with increased lung cancer risk (N=28 998, odds ratio=1.06 and 95% confidence interval=1.00-1.12), likely through its effect on smoking, as rs2273500-C was no longer associated with lung cancer after adjustment for smoking. Using criteria for smoking behavior that encompass more than the single 'cigarettes per day' item, we identified a common CHRNA4 variant with important regulatory properties that contributes to nicotine dependence and smoking-related consequences.

Predicting survival using clinical risk scores and non-HLA immunogenetics.

Previous studies of non-histocompatibility leukocyte antigen (HLA) gene single-nucleotide polymorphisms (SNPs) on subgroups of patients undergoing allogeneic haematopoietic stem cell transplantation (HSCT) revealed an association with transplant outcome. This study further evaluated the association of non-HLA polymorphisms with overall survival in a cohort of 762 HSCT patients using data on 26 polymorphisms in 16 non-HLA genes. When viewed in addition to an already established clinical risk score (EBMT-score), three polymorphisms: rs8177374 in the gene for MyD88-adapter-like (MAL; P=0.026), rs9340799 in the oestrogen receptor gene (ESR; P=0.003) and rs1800795 in interleukin-6 (IL-6; P=0.007) were found to be associated with reduced overall survival, whereas the haplo-genotype (ACC/ACC) in IL-10 was protective (P=0.02). The addition of these non-HLA polymorphisms in a Cox regression model alongside the EBMT-score improved discrimination between risk groups and increased the level of prediction compared with the EBMT-score alone (gain in prediction capability for EBMT-genetic-score 10.8%). Results also demonstrated how changes in clinical practice through time have altered the effects of non-HLA analysis. The study illustrates the significance of non-HLA genotyping prior to HSCT and the importance of further investigation into non-HLA gene polymorphisms in risk prediction.

Dissociation of accumulated genetic risk and disease severity in patients with schizophrenia.

Genotype-phenotype correlations of common monogenic diseases revealed that the degree of deviation of mutant genes from wild-type structure and function often predicts disease onset and severity. In complex disorders such as schizophrenia, the overall genetic risk is still often >50% but genotype-phenotype relationships are unclear. Recent genome-wide association studies (GWAS) replicated a risk for several single-nucleotide polymorphisms (SNPs) regarding the endpoint diagnosis of schizophrenia. The biological relevance of these SNPs, however, for phenotypes or severity of schizophrenia has remained obscure. We hypothesized that the GWAS 'top-10' should as single markers, but even more so upon their accumulation, display associations with lead features of schizophrenia, namely positive and negative symptoms, cognitive deficits and neurological signs (including catatonia), and/or with age of onset of the disease prodrome as developmental readout and predictor of disease severity. For testing this hypothesis, we took an approach complementary to GWAS, and performed a phenotype-based genetic association study (PGAS). We utilized the to our knowledge worldwide largest phenotypical database of schizophrenic patients (n>1000), the GRAS (Göttingen Research Association for Schizophrenia) Data Collection. We found that the 'top-10' GWAS-identified risk SNPs neither as single markers nor when explored in the sense of a cumulative genetic risk, have any predictive value for disease onset or severity in the schizophrenic patients, as demonstrated across all core symptoms. We conclude that GWAS does not extract disease genes of general significance in schizophrenia, but may yield, on a hypothesis-free basis, candidate genes relevant for defining disease subgroups.

The longitudinal nonparametric test as a new tool to explore gene-gene and gene-time effects in cohorts.

Current approaches for analysis of longitudinal genetic epidemiological data of quantitative traits are typically restricted to normality assumptions of the trait. We introduce the longitudinal nonparametric test (LNPT) for cohorts with quantitative follow-up data to test for overall main effects of genes and for gene-gene and gene-time interactions. The LNPT is a rank procedure and does not depend on normality assumptions of the trait. We demonstrate by simulations that the LNPT is powerful, keeps the type-1 error level, and has very good small sample size behavior. For phenotypes with normal residuals, loss of power compared to parametric approaches (linear mixed models) was small for the quite general scenarios, which we simulated. For phenotypes with non-normal residuals, gain in power by the LNPT can be substantial. In contrast to parametric approaches, the LNPT is invariant with respect to monotone transformations of the trait. It is mathematically valid for arbitrary trait distribution.

Complexin2 null mutation requires a 'second hit' for induction of phenotypic changes relevant to schizophrenia.

Schizophrenia is a devastating disease that affects approximately 1% of the population across cultures. Its neurobiological underpinnings are still unknown. Accordingly, animal models of schizophrenia often lack construct validity. As concordance rate in monozygotic twins amounts to only 50%, environmental risk factors (e.g. neurotrauma, drug abuse, psychotrauma) likely act as necessary 'second hit' to trigger/drive the disease process in a genetically predisposed individual. Valid animal models would have to consider this genetic-environmental interaction. Based on this concept, we designed an experimental approach for modeling a schizophrenia-like phenotype in mice. As dysfunction in synaptic transmission plays a key role in schizophrenia, and complexin2 (CPLX2) gene expression is reduced in hippocampus of schizophrenic patients, we developed a mouse model with Cplx2 null mutation as genetic risk factor and a mild parietal neurotrauma, applied during puberty, as environmental 'second hit'. Several months after lesion, Cplx2 null mutants showed reduced pre-pulse inhibition, deficit of spatial learning and loss of inhibition after MK-801 challenge. These abnormalities were largely absent in lesioned wild-type mice and non-lesioned Cplx2 null mutants. Forced alternation in T-maze, object recognition, social interaction and elevated plus maze tests were unaltered in all groups. The previously reported mild motor phenotype of Cplx2 null mutants was accentuated upon lesion. MRI volumetrical analysis showed a decrease of hippocampal volume exclusively in lesioned Cplx2 null mutants. These findings provide suggestive evidence for the 'second hit' hypothesis of schizophrenia and may offer new tools for the development of advanced treatment strategies.

KIR genes and KIR ligands affect occurrence of acute GVHD after unrelated, 12/12 HLA matched, hematopoietic stem cell transplantation.

Interactions of polymorphic killer Ig-like receptor (KIR) receptors with KIR ligands have been shown to modify the outcome of hematopoietic SCT (HSCT). The association of these genetic factors with different transplantation endpoints, however, varies substantially, depending on clinical and study setup variables. We aimed to assess whether KIR ligands, KIR genes and KIR haplotypes are associated with HSCT outcome of 124 patients with various hematological malignancies, transplanted with 12/12 HLA matched grafts from unrelated donors. For this purpose, patient and donor KIR gene and KIR ligand polymorphisms were determined and correlated with clinical data in simple and multiple models. We found that a missing HLA-C2 ligand for donor inhibitory KIR2DL1 was significantly associated with an increased risk of acute GVHD (aGVHD) (II-IV) (hazard ratio (HR)=2.23, 95% confidence interval (95% CI): 1.21-4.10, P=0.010), as were the AA KIR haplotypes in patients and donors in HLA-C1CX (HR=2.37, 95% CI: 1.16-4.84, P=0.018) and in HLA-Bw4(-) (HR=3.20, 95% CI: 1.35-7.60, P=0.008) patients. On the contrary, transplantation of HLA-C1C2 patients with KIR2DS2 positive grafts were associated with a decreased risk of aGVHD (II-IV) (HR=0.24, 95% CI: 0.07-0.85, P=0.027). Thus, our single center study provides evidence for the modification of aGVHD risk by KIRs and their ligands.

Strategy for detecting susceptibility genes with weak or no marginal effect.

Most human diseases result from complex interactions among multiple genes that yield weak or modest effects. Despite the growing awareness of the importance of gene-gene interactions, the paradigm of detectable effects of individual variants remains the cornerstone of genome association studies with tagSNPs. The interactive effect of two variants is only tested once the individual effect of one variant is detected. Both genes, however, may have at the same time a weak (or even no) marginal effect but an important effect through their interaction. In such a situation, current approaches may fail to detect variants having a crucial role in the causal chain. Here, we propose a new strategy: the 2-locus TDT. It allows the detection of the involvement of two genes without individual effect. Our strategy simultaneously uses information on biallelic candidate polymorphisms in two genes M and N. We first estimate the relative marginal penetrances of the genotype at each locus and of the joint (two-locus) genotype and then we test for the interactive effect of the two genes using a likelihood ratio test. We show that our approach has good power to detect the effect of two genes in situations for which a locus-by-locus strategy would have been unsuccessful. At a time where genome-wide association studies are fashionable, we think it is important to consider the strategy of studying good candidate pathways with our approach.

Significant association of a M129V independent polymorphism in the 5' UTR of the PRNP gene with sporadic Creutzfeldt-Jakob disease in a large German case-control study.

BACKGROUND: A single nucleotide polymorphism (SNP) in the coding region of the prion protein gene (PRNP) at codon 129 has been repeatedly shown to be an associated factor to sporadic Creutzfeldt-Jakob disease (sCJD), but additional major predisposing DNA variants for sCJD are still unknown. Several previous studies focused on the characterisation of polymorphisms in PRNP and the prion-like doppel gene (PRND), generating contradictory results on relatively small sample sets. Thus, extensive studies are required for validation of the polymorphisms in PRNP and PRND. METHODS: We evaluated a set of nine SNPs of PRNP and one SNP of PRND in 593 German sCJD patients and 748 German healthy controls. Genotyping was performed using MALDI-TOF mass spectrometry. RESULTS: In addition to PRNP 129, we detected a significant association between sCJD and allele frequencies of six further PRNP SNPs. No significant association of PRND T174M with sCJD was shown. We observed strong linkage disequilibrium within eight adjacent PRNP SNPs, including PRNP 129. However, the association of sCJD with PRNP 1368 and PRNP 34296 appeared to be independent on the genotype of PRNP 129. We additionally identified the most common haplotypes of PRNP to be over-represented or under-represented in our cohort of patients with sCJD. CONCLUSION: Our study evaluated previous findings of the association of SNPs in the PRNP and PRND genes in the largest cohorts for association study in sCJD to date, and extends previous findings by defining for the first time the haplotypes associated with sCJD in a large population of the German CJD surveillance study.

Case-control association tests correcting for population stratification.

In case-control association studies unobserved population stratification may act as a confounder, leading to an increased number of false positive results. Methods accounting for population structure by using additional genetic markers broadly follow one of two concepts: Genomic Control (GC) and Structured Association (SA). While extending existing methods of Structured Association we show that it is necessary to incorporate phenotypic information when inferring population structure, otherwise a systematic bias is introduced. Moreover, for moderate population stratification a Wald test statistic should be preferred as a Structured Association test statistic in comparison to a likelihood ratio test. The introduced extensions are compared to existing methods of Structured Association, as well as to Genomic Control, in a simulation study which is based on realistic situations of large case-control studies with moderate population stratification. A disadvantage of Genomic Control turns out to be the large variation in estimating the variance inflation factor, as well as the power loss if population structure increases. We come to the overall conclusion that Structured Association, if applied correctly, is superior to Genomic Control, at least in the case of simple population structure as simulated here.

Modeling and dissection of longitudinal blood pressure and hypertension phenotypes in genetic epidemiological studies.

We discuss analyses of the Genetic Analysis Workshop 13 data from the Framingham Heart Study and simulations based on this study. We summarize analyses that investigated measures of systolic blood pressure or hypertension as the main phenotype, with the main focus being the modeling of this complex longitudinal phenotype. The approaches include familial aggregation methods and one-stage and two-stage linkage methods. For one-stage linkage methods, phenotype modeling is carried out jointly with the linkage analysis or incorporated in the analysis design. For two-stage linkage methods, phenotypes are first modeled in order to develop summary measures that are then analyzed in a subsequent linkage analysis. Results depend on phenotype selection and on how analyses account for longitudinality, treatment effects, and heterodasticity.

Fine mapping and single nucleotide polymorphism association results of candidate genes for asthma and related phenotypes.

Several genome-wide screens for asthma and related phenotypes have been published to date but data on fine-mapping are scarce. For higher resolution we performed a fine-mapping study with 2 cM average spacing in often discussed asthma candidate regions (2p, 5q, 6p, 7p, 9q, 11p, and 12q) to narrow down the regions of interest. All participants of a Caucasian family study (97 families with at least two affected sib pairs) were genotyped for 49 supplementary polymorphic dinucleotide markers. Our results indicate increased evidence for linkage on chromosome 6p, 9q, and 12q. These candidate regions were further analyzed with SNP polymorphisms in the endothelin 1 (EDN1), lymphotoxin alpha (LTA), and neuronal nitric oxide synthase (NOS1) genes. In addition, IL4 -590C>T and IL10 -592C>A, localized on chromosomes 5q and 1q, respectively, have been analyzed for SNP association. Of the six SNPs tested, four revealed weak association with the examined phenotypes. These are the IL10 -592C>A SNP in the interleukin 10 gene (p=0.036 for eosinophil cell counts), the 4124T>C SNP in EDN1 (p=0.044 for asthma), the 3391C>T SNP in NOS1 with eosinophil cell counts (p=0.0086), and the 5266C>T polymorphism, also in the NOS1 gene, for high IgE levels (p=0.022). In summary, fine mapping data enable us to confine asthma candidate regions, while variants of EDN1 and NOS1, or nearby genes, may play an important role in this context.

Weighting schemes in pooled linkage analysis.

To identify susceptibility gene regions for complex diseases a combined linkage analysis of several genome scans might give additional insights to individual studies. In this article we consider different weighting schemes to combine the score statistics of individual studies to an overall statistic within multipoint nonparametric linkage analysis by GENEHUNTER/ALLEGRO. With the Genetic Analysis Workshop (GAW) 12 asthma data sets the weights are dominated by the large differences in the relevant sample sizes.

Association of beta(2)-adrenoreceptor variants with bronchial hyperresponsiveness.

Because of its involvement in the regulation of airway tone, the beta(2)-adrenoreceptor is considered a candidate for bronchial hyperresponsiveness (BHR) associated with asthma. This notion is supported by several reports that have implicated the chromosomal region 5q31-q33 harboring the gene for the beta(2)-adrenoreceptor in the genetics of asthma and related phenotypes. We performed a population-based association study focusing on BHR as a qualitative trait and omitting other asthma-related phenotypes. From a German population sample of 1,150 individuals we extracted all 152 bronchohyperreactive probands, who were compared with 295 bronchonormoreactive control subjects. All individuals were genotyped for three single nucleotide polymorphisms of the beta(2)-adrenoreceptor gene resulting in variants at the amino acid positions 16, 27, and 164. The genotyping protocol used allowed the determination of haplotypes of these polymorphisms. Whereas no individual polymorphism was associated with BHR, the Gly16/Gln27/Th164 haplotype was significantly underrepresented in the case group indicating a protective effect of this haplotype with regard to BHR. Upon reanalysis by sex a significant association persisted only for female probands.

Incorporating larger families in identity-by-descent based linkage analysis.

Genome scans for alcoholism susceptibility genes were carried out using identity-by-descent-based statistics for qualitative traits. We compared the results when 1) multipoint information was used for all families, where some had to be truncated, 2) multipoint information was used only for small families while large (untruncated) pedigrees were analyzed with a single-point approach, and 3) single-point analysis was used for all pedigrees. Differences between the methods were observed, but neither method could identify regions related to the susceptibility for alcoholism.