Olfactory genes affect major depression in highly educated, emotionally stable, lean women: a bridge between animal models and precision medicine.

Most current approaches to establish subgroups of depressed patients for precision medicine aim to rely on biomarkers that require highly specialized assessment. Our present aim was to stratify participants of the UK Biobank cohort based on three readily measurable common independent risk factors, and to investigate depression genomics in each group to discover common and separate biological etiology. Two-step cluster analysis was run separately in males (n = 149,879) and females (n = 174,572), with neuroticism (a tendency to experience negative emotions), body fat percentage, and years spent in education as input variables. Genome-wide association analyses were implemented within each of the resulting clusters, for the lifetime occurrence of either a depressive episode or recurrent depressive disorder as the outcome. Variant-based, gene-based, gene set-based, and tissue-specific gene expression test were applied. Phenotypically distinct clusters with high genetic intercorrelations in depression genomics were found. A two-cluster solution was the best model in each sex with some differences including the less important role of neuroticism in males. In females, in case of a protective pattern of low neuroticism, low body fat percentage, and high level of education, depression was associated with pathways related to olfactory function. While also in females but in a risk pattern of high neuroticism, high body fat percentage, and less years spent in education, depression showed association with complement system genes. Our results, on one hand, indicate that alteration of olfactory pathways, that can be paralleled to the well-known rodent depression models of olfactory bulbectomy, might be a novel target towards precision psychiatry in females with less other risk factors for depression. On the other hand, our results in multi-risk females may provide a special case of immunometabolic depression.

Genetic risk of depression is different in subgroups of dietary ratio of tryptophan to large neutral amino acids.

Manipulation of intake of serotonin precursor tryptophan has been exploited to rapidly induce and alleviate depression symptoms. While studies show that this latter effect is dependent on genetic vulnerability to depression, the effect of habitual tryptophan intake in the context of predisposing genetic factors has not been explored. Our aim was to investigate the effect of habitual tryptophan intake on mood symptoms and to determine the effect of risk variants on depression in those with high and low tryptophan intake in the whole genome and specifically in serotonin and kynurenine pathways. 63,277 individuals in the UK Biobank with data on depressive symptoms and tryptophan intake were included. We compared two subpopulations defined by their habitual diet of a low versus a high ratio of tryptophan to other large amino acids (TLR). A modest protective effect of high dietary TLR against depression was found. NPBWR1 among serotonin genes and POLI in kynurenine pathway genes were significantly associated with depression in the low but not in the high TLR group. Pathway-level analyses identified significant associations for both serotonin and kynurenine pathways only in the low TLR group. In addition, significant association was found in the low TLR group between depressive symptoms and biological process related to adult neurogenesis. Our findings demonstrate a markedly distinct genetic risk profile for depression in groups with low and high dietary TLR, with association with serotonin and kynurenine pathway variants only in case of habitual food intake leading to low TLR. Our results confirm the relevance of the serotonin hypothesis in understanding the neurobiological background of depression and highlight the importance of understanding its differential role in the context of environmental variables such as complexity of diet in influencing mental health, pointing towards emerging possibilities of personalised prevention and intervention in mood disorders in those who are genetically vulnerable.

A sound mind in a sound body: a novel concept unravelling heterogeneity of depression.

Depression is a highly prevalent and debilitating condition, yet we still lack both in-depth knowledge concerning its etiopathology and sufficiently efficacious treatment options. With approximately one third of patients resistant to currently available antidepressants there is a pressing need for a better understanding of depression, identifying subgroups within the highly heterogeneous illness category and to understand the divergent underlying biology of such subtypes, to help develop and personalise treatments. The TRAJECTOME project aims to address such challenges by (1) identifying depression-related multimorbidity subgroups and shared molecular pathways based on temporal disease profiles from healthcare systems and biobank data using machine learning approaches, and by (2) characterising these subgroups from multiple aspects including genetic variants, metabolic processes, lifestyle and environmental factors. Following the identification of multimorbidity trajectories, a disease burden score related to depression and adjusted for multimorbidity was established summarising the current state of the patient to weigh the molecular mechanisms associated with depression. In addition, the role of genetic and environmental factors, and also their interactions were identified for all subgroups. The project also attempted to identify potential metabolomic markers for the early diagnostics of these multimorbidity conditions. Finally, we prioritized molecular drug candidates matching the multimorbidity pathways indicated for the individual subgroups which would potentially offer personalised treatment simultaneously for the observable multimorbid conditions yet minimising polypharmacy and related side effects. The present paper overviews the TRAJECTOME project including its aims, tasks, procedures and accomplishments. (Neuropsychopharmacol Hung 2023; 25(4): 183-193)

Biology of Perseverative Negative Thinking: The Role of Timing and Folate Intake.

Past-oriented rumination and future-oriented worry are two aspects of perseverative negative thinking related to the neuroticism endophenotype and associated with depression and anxiety. Our present aim was to investigate the genomic background of these two aspects of perseverative negative thinking within separate groups of individuals with suboptimal versus optimal folate intake. We conducted a genome-wide association study in the UK Biobank database (n = 72,621) on the "rumination" and "worry" items of the Eysenck Personality Inventory Neuroticism scale in these separate groups. Optimal folate intake was related to lower worry, but unrelated to rumination. In contrast, genetic associations for worry did not implicate specific biological processes, while past-oriented rumination had a more specific genetic background, emphasizing its endophenotypic nature. Furthermore, biological pathways leading to rumination appeared to differ according to folate intake: purinergic signaling and circadian regulator gene ARNTL emerged in the whole sample, blastocyst development, DNA replication, and C-C chemokines in the suboptimal folate group, and prostaglandin response and K+ channel subunit gene KCNH3 in the optimal folate group. Our results point to possible benefits of folate in anxiety disorders, and to the importance of simultaneously taking into account genetic and environmental factors to determine personalized intervention in polygenic and multifactorial disorders.

A replication study separates polymorphisms behind migraine with and without depression.

The largest migraine genome-wide association study identified 38 candidate loci. In this study we assessed whether these results replicate on a gene level in our European cohort and whether effects are altered by lifetime depression. We tested SNPs of the loci and their vicinity with or without interaction with depression in regression models. Advanced analysis methods such as Bayesian relevance analysis and a neural network based classifier were used to confirm findings. Main effects were found for rs2455107 of PRDM16 (OR = 1.304, p = 0.007) and five intergenic polymorphisms in 1p31.1 region: two of them showed risk effect (OR = 1.277, p = 0.003 for both rs11209657 and rs6686879), while the other three variants were protective factors (OR = 0.4956, p = 0.006 for both rs12090642 and rs72948266; OR = 0.4756, p = 0.005 for rs77864828). Additionally, 26 polymorphisms within ADGRL2, 2 in REST, 1 in HPSE2 and 33 mostly intergenic SNPs from 1p31.1 showed interaction effects. Among clumped results representing these significant regions, only rs11163394 of ADGRL2 showed a protective effect (OR = 0.607, p = 0.002), all other variants were risk factors (rs1043215 of REST with the strongest effect: OR = 6.596, p = 0.003). Bayesian relevance analysis confirmed the relevance of intergenic rs6660757 and rs12128399 (p31.1), rs1043215 (REST), rs1889974 (HPSE2) and rs11163394 (ADGRL2) from depression interaction results, and the moderate relevance of rs77864828 and rs2455107 of PRDM16 from main effect analysis. Both main and interaction effect SNPs could enhance predictive power with the neural network based classifier. In summary, we replicated p31.1, PRDM16, REST, HPSE2 and ADGRL2 genes with classic genetic and advanced analysis methods. While the p31.1 region and PRDM16 are worthy of further investigations in migraine in general, REST, HPSE2 and ADGRL2 may be prime candidates behind migraine pathophysiology in patients with comorbid depression.

Spatiotemporal brain activation pattern following acute citalopram challenge is dose dependent and associated with neuroticism: A human phMRI study.

BACKGROUND: The initial effects of selective serotonin reuptake inhibitors (SSRIs) in the human living brain are poorly understood. We carried out a 3T resting state fMRI study with pharmacological challenge to determine the brain activation changes over time following different dosages of citalopram. METHODS: During the study, 7.5 mg i.v. citalopram was administered to 32 healthy subjects. In addition, 11.25 mg citalopram was administered to a subset of 9 subjects to investigate the dose-response. Associations with neuroticism (assessed by the NEO PI-R) of the emerging brain activation to citalopram was also investigated. RESULTS: Citalopram challenge evoked significant activation in brain regions that are part of the default mode network, the visual network and the sensorimotor network, extending to the thalamus, and midbrain. Most effects appeared to be dose-dependent and this was statistically significant in the middle cingulate gyrus. Individual citalopram-induced brain responses were positively correlated with neuroticism scores and its subscales in specific brain areas; anxiety subscale scores in thalamus and midbrain and self-consciousness scores in middle cingulate gyrus. There were no sex differences. LIMITATIONS: We investigated only healthy subjects and we used a relatively low sample size in the 11.25 mg citalopram analysis. DISCUSSION: Our results suggest that SSRIs acutely induce an increased arousal-like state of distributed cortical and subcortical systems that is mediated by enhanced serotonin neurotransmission according to levels of neuroticism and underpins trait sensitivity to environmental stimuli and stressors. Studies in depression are needed to determine how therapeutic effects eventually emerge. This article is part of the special issue entitled 'Serotonin Research: Crossing Scales and Boundaries'.

Increased activation of the pregenual anterior cingulate cortex to citalopram challenge in migraine: an fMRI study.

BACKGROUND: The anterior cingulate cortex (ACC) is a key structure of the pain processing network. Several structural and functional alterations of this brain area have been found in migraine. In addition, altered serotonergic neurotransmission has been repeatedly implicated in the pathophysiology of migraine, although the exact mechanism is not known. Thus, our aim was to investigate the relationship between acute increase of brain serotonin (5-HT) level and the activation changes of the ACC using pharmacological challenge MRI (phMRI) in migraine patients and healthy controls. METHODS: Twenty-seven pain-free healthy controls and six migraine without aura patients participated in the study. All participant attended to two phMRI sessions during which intravenous citalopram, a selective serotonin reuptake inhibitor (SSRI), or placebo (normal saline) was administered. We used region of interest analysis of ACC to compere the citalopram evoked activation changes of this area between patients and healthy participants. RESULTS: Significant difference in ACC activation was found between control and patient groups in the right pregenual ACC (pgACC) during and after citalopram infusion compared to placebo. The extracted time-series showed that pgACC activation increased in migraine patients compared to controls, especially in the first 8-10 min of citalopram infusion. CONCLUSIONS: Our results demonstrate that a small increase in 5-HT levels can lead to increased phMRI signal in the pregenual part of the ACC that is involved in processing emotional aspects of pain. This increased sensitivity of the pgACC to increased 5-HT in migraine may contribute to recurring headache attacks and increased stress-sensitivity in migraine.

The UKB envirome of depression: from interactions to synergistic effects.

Major depressive disorder is a result of the complex interplay between a large number of environmental and genetic factors but the comprehensive analysis of contributing environmental factors is still an open challenge. The primary aim of this work was to create a Bayesian dependency map of environmental factors of depression, including life stress, social and lifestyle factors, using the UK Biobank data to determine direct dependencies and to characterize mediating or interacting effects of other mental health, metabolic or pain conditions. As a complementary approach, we also investigated the non-linear, synergistic multi-factorial risk of the UKB envirome on depression using deep neural network architectures. Our results showed that a surprisingly small number of core factors mediate the effects of the envirome on lifetime depression: neuroticism, current depressive symptoms, parental depression, body fat, while life stress and household income have weak direct effects. Current depressive symptom showed strong or moderate direct relationships with life stress, pain conditions, falls, age, insomnia, weight change, satisfaction, confiding in someone, exercise, sports and Townsend index. In conclusion, the majority of envirome exerts their effects in a dynamic network via transitive, interactive and synergistic relationships explaining why environmental effects may be obscured in studies which consider them individually.

Significance of risk polymorphisms for depression depends on stress exposure.

Depression is a polygenic and multifactorial disorder where environmental effects exert a significant impact, yet most genetic studies do not consider the effect of stressors which may be one reason for the lack of replicable results in candidate gene studies, GWAS and between human studies and animal models. Relevance of functional polymorphisms in seven candidate genes previously implicated in animal and human studies on a depression-related phenotype given various recent stress exposure levels was assessed with Bayesian relevance analysis in 1682 subjects. This Bayesian analysis indicated a gene-environment interaction whose significance was also tested with a traditional multivariate analysis using general linear models. The investigated genetic factors were only relevant in the moderate and/or high stress exposure groups. Rank order of genes was GALR2 > BDNF > P2RX7 > HTR1A > SLC6A4 > CB1 > HTR2A, with strong relevance for the first four. Robust gene-gene-environment interaction was found between BDNF and HTR1A. Gene-environment interaction effect was confirmed, namely no main effect of genes, but a significant modulatory effect on environment-induced development of depression were found. Our data support the strong causative role of the environment modified by genetic factors, similar to animal models. Gene-environment interactions point to epigenetic factors associated with risk SNPs. Galanin-2 receptor, BDNF and X-type purin-7 receptor could be drug targets for new antidepressants.

A new stress sensor and risk factor for suicide: the T allele of the functional genetic variant in the GABRA6 gene.

Low GABA transmission has been reported in suicide, and GABRA6 rs3219151 T allele has been associated with greater physiological and endocrine stress response in previous studies. Although environmental stress also plays a role in suicide, the possible role of this allele has not been investigated in this respect. In our present study effect of rs3219151 of GABRA6 gene in interaction with recent negative life events on lifetime and current depression, current anxiety, as well as lifetime suicide were investigated using regression models in a white European general sample of 2283 subjects. Post hoc measures for phenotypes related to suicide risk were also tested for association with rs3219151 in interaction with environmental stress. No main effect of the GABRA6 rs3219151 was detected, but in those exposed to recent negative life events GABRA6 T allele increased current anxiety and depression as well as specific elements of suicide risk including suicidal and death-related thoughts, hopelessness, restlessness and agitation, insomnia and impulsiveness as measured by the STOP task. Our data indicate that stress-associated suicide risk is elevated in carriers of the GABRA6 rs3219151 T allele with several independent markers and predictors of suicidal behaviours converging to this increased risk.

Variability in the effect of 5-HTTLPR on depression in a large European population: the role of age, symptom profile, type and intensity of life stressors.

BACKGROUND: Although 5-HTTLPR has been shown to influence the risk of life stress-induced depression in the majority of studies, others have produced contradictory results, possibly due to weak effects and/or sample heterogeneity. METHODS: In the present study we investigated how age, type and intensity of life-stressors modulate the effect of 5-HTTLPR on depression and anxiety in a European population cohort of over 2300 subjects. Recent negative life events (RLE), childhood adversity (CHA), lifetime depression, Brief Symptoms Inventory (BSI) depression and anxiety scores were determined in each subject. Besides traditional statistical analysis we calculated Bayesian effect strength and relevance of 5-HTTLPR genotypes in specified models. RESULTS: The short (s) low expressing allele showed association with increased risk of depression related phenotypes, but all nominally significant effects would turn to non-significant after correction for multiple testing in the traditional analysis. Bayesian effect strength and relevance analysis, however, confirmed the role of 5-HTTLPR. Regarding current (BSI) and lifetime depression 5-HTTLPR-by-RLE interactions were confirmed. Main effect, with other words direct association, was supported with BSI anxiety. With more frequent RLE the prevalence or symptoms of depression increased in ss carriers. Although CHA failed to show an interaction with 5-HTTLPR, in young subjects CHA sensitized towards the depression promoting effect of even mild RLE. Furthermore, the direct association of anxiety with the s allele was driven by young (≤30) individuals. LIMITATIONS: Our study is cross-sectional and applies self-report questionnaires. CONCLUSIONS: Albeit 5-HTTLPR has only weak/moderate effects, the s allele is directly associated with anxiety and modulates development of depression in homogeneous subgroups.

Novel genes in Human Asthma Based on a Mouse Model of Allergic Airway Inflammation and Human Investigations.

PURPOSE: Based on a previous gene expression study in a mouse model of asthma, we selected 60 candidate genes and investigated their possible roles in human asthma. METHODS: In these candidate genes, 90 SNPs were genotyped using MassARRAY technology from 311 asthmatic children and 360 healthy controls of the Hungarian (Caucasian) population. Moreover, gene expression levels were measured by RT PCR in the induced sputum of 13 asthmatics and 10 control individuals. t-tests, chi-square tests, and logistic regression were carried out in order to assess associations of SNP frequency and expression level with asthma. Permutation tests were performed to account for multiple hypothesis testing. RESULTS: The frequency of 4 SNPs in 2 genes differed significantly between asthmatic and control subjects: SNPs rs2240572, rs2240571, rs3735222 in gene SCIN, and rs32588 in gene PPARGC1B. Carriers of the minor alleles had reduced risk of asthma with an odds ratio of 0.64 (0.51-0.80; P=7×10(-5)) in SCIN and 0.56 (0.42-0.76; P=1.2×10(-4)) in PPARGC1B. The expression levels of SCIN, PPARGC1B and ITLN1 genes were significantly lower in the sputum of asthmatics. CONCLUSIONS: Three potentially novel asthma-associated genes were identified based on mouse experiments and human studies.

Bayesian systems-based genetic association analysis with effect strength estimation and omic wide interpretation: a case study in rheumatoid arthritis.

Rich dependency structures are often formed in genetic association studies between the phenotypic, clinical, and environmental descriptors. These descriptors may not be standardized, and may encompass various disease definitions and clinical endpoints which are only weakly influenced by various (e.g., genetic) factors. Such loosely defined complex intermediate clinical phenotypes are typically used in follow-up candidate gene association studies, e.g., after genome-wide analysis, to deepen the understanding of the associations and to estimate effect strength. This chapter discusses a solid methodology, which is useful in such a scenario, by using probabilistic graphical models, namely, Bayesian networks in the Bayesian statistical framework. This method offers systematically scalable, comprehensive hierarchical hypotheses about multivariate relevance. We discuss its workflow: from data engineering to semantic publication of the results. We overview the construction, visualization, and interpretation of complex hypotheses related to the structural analysis of relevance. Furthermore, we illustrate the use of a dependency model-based relevance measure, which takes into account the structural properties of the model, for quantifying the effect strength. Finally, we discuss the "interpretational" or translational challenge of a genetic association study, with a focus on the fusion of heterogeneous omic knowledge to reintegrate the results into a genome-wide context.

Brain galanin system genes interact with life stresses in depression-related phenotypes.

Galanin is a stress-inducible neuropeptide and cotransmitter in serotonin and norepinephrine neurons with a possible role in stress-related disorders. Here we report that variants in genes for galanin (GAL) and its receptors (GALR1, GALR2, GALR3), despite their disparate genomic loci, conferred increased risk of depression and anxiety in people who experienced childhood adversity or recent negative life events in a European white population cohort totaling 2,361 from Manchester, United Kingdom and Budapest, Hungary. Bayesian multivariate analysis revealed a greater relevance of galanin system genes in highly stressed subjects compared with subjects with moderate or low life stress. Using the same method, the effect of the galanin system genes was stronger than the effect of the well-studied 5-HTTLPR polymorphism in the serotonin transporter gene (SLC6A4). Conventional multivariate analysis using general linear models demonstrated that interaction of galanin system genes with life stressors explained more variance (1.7%, P = 0.005) than the life stress-only model. This effect replicated in independent analysis of the Manchester and Budapest subpopulations, and in males and females. The results suggest that the galanin pathway plays an important role in the pathogenesis of depression in humans by increasing the vulnerability to early and recent psychosocial stress. Correcting abnormal galanin function in depression could prove to be a novel target for drug development. The findings further emphasize the importance of modeling environmental interaction in finding new genes for depression.

Complex analysis of multiple single nucleotide polymorphisms as putative risk factors of tooth agenesis in the Hungarian population.

OBJECTIVES: The role was studied of multiple single nucleotide polymorphisms in tooth agenesis in the Hungarian population using a complex approach. METHODS: Eight SNPs, PAX9 -912 C/T, PAX9 -1031 A/G, MSX1 3755 A/G, FGFR1 T/C rs881301, IRF6 T/C rs764093, AXIN2-8150 A/G, AXIN2-8434 A/G and AXIN2-30224 C/T, were studied in 192 hypodontia and 17 oligodontia cases and in 260 healthy volunteers. Case-control analysis was performed to test both allelic and genotypic associations as well as associations at the level of haplotypes. Multivariate exploratory Bayesian network-based multi-level analysis of relevance (BN-BMLA) as well as logistic regression analysis were performed. RESULTS: Conventional statistics showed that PAX9 SNP -912 C/T and the MSX1 SNP changed the incidence of hypodontia, although after Bonferroni correction for multiple hypothesis testing, the effects were only borderline tendencies. Using a statistical analysis better suited for handling multiple hypotheses, the BN-BMLA, PAX9 SNPs clearly showed a synergistic effect. This was confirmed by other multivariate analyses and it remained significant after corrections for multiple hypothesis testing (p < 0.0025). The PAX9-1031-A-PAX9-912-T haplotype was the most relevant combination causing hypodontia. Interaction was weaker between PAX9 and MSX1, while other SNPs had no joint effect on hypodontia. CONCLUSION: This complex analysis shows the important role of PAX9 and MSX1 SNPs and of their interactions in tooth agenesis, while IRF6, FGFR1 and AXIN2 SNPs had no detectable role in the Hungarian population. These results also reveal that risk factors in hypodontia need to be identified in various populations, since there is considerable variability among them.

Roles of genetic polymorphisms in the folate pathway in childhood acute lymphoblastic leukemia evaluated by Bayesian relevance and effect size analysis.

In this study we investigated whether polymorphisms in the folate pathway influenced the risk of childhood acute lymphoblastic leukemia (ALL) or the survival rate of the patients. For this we selected and genotyped 67 SNPs in 15 genes in the folate pathway in 543 children with ALL and 529 controls. The results were evaluated by gender adjusted logistic regression and by the Bayesian network based Bayesian multilevel analysis of relevance (BN-BMLA) methods. Bayesian structure based odds ratios for the relevant variables and interactions were also calculated. Altogether 9 SNPs in 8 genes were associated with altered susceptibility to ALL. After correction for multiple testing, two associations remained significant. The genotype distribution of the MTHFD1 rs1076991 differed significantly between the ALL and control population. Analyzing the subtypes of the disease the GG genotype increased only the risk of B-cell ALL (p = 3.52×10(-4); OR = 2.00). The GG genotype of the rs3776455 SNP in the MTRR gene was associated with a significantly reduced risk to ALL (p = 1.21×10(-3); OR = 0.55), which resulted mainly from the reduced risk to B-cell and hyperdiploid-ALL. The TC genotype of the rs9909104 SNP in the SHMT1 gene was associated with a lower survival rate comparing it to the TT genotype (80.2% vs. 88.8%; p = 0.01). The BN-BMLA confirmed the main findings of the frequentist-based analysis and showed structural interactional maps and the probabilities of the different structural association types of the relevant SNPs especially in the hyperdiploid-ALL, involving additional SNPs in genes like TYMS, DHFR and GGH. We also investigated the statistical interactions and redundancies using structural model properties. These results gave further evidence that polymorphisms in the folate pathway could influence the ALL risk and the effectiveness of the therapy. It was also shown that in gene association studies the BN-BMLA could be a useful supplementary to the traditional frequentist-based statistical method.

Beyond structural equation modeling: model properties and effect size from a Bayesian viewpoint. An example of complex phenotype-genotype associations in depression.

Despite the rapid evolution of measurement technologies in biomedicine and genetics, most of the recent studies aiming to explore the genetic background of multifactorial diseases were only moderately successful. One of the causes of this phenomenon is that the bottleneck of genetic research is no longer the measurement process related to various laboratory technologies, but rather the analysis and interpretation of results. The commonly applied univariate methods are inadequate for exploring complex dependency patterns of multifactorial diseases which includes nearly all common diseases, such as depression, hypertension, and asthma. A comprehensive investigation requires multivariate modeling methods that enable the analysis of interactions between factors, and allow a more detailed interpretation of studies measuring complex phenotype descriptors. In this paper we discuss various aspects of multivariate modeling through a case study analyzing the effect of the single nucleotide polymorphism rs6295 in the HTR1A gene on depression and impulsivity. We overview basic concepts related to multivariate modeling and compare the properties of two investigated modeling techniques: Structural Equation Modeling and Bayesian network based learning algorithms. The resulting models demonstrate the advantages of the Bayesian approach in terms of model properties and effect size as it allows coherent handling of the weakly significant effect of rs6295. Results also confirm the mediating role of impulsivity between the SNP rs6295 of HTR1A and depression.

Non-synonymous single nucleotide polymorphisms in genes for immunoregulatory galectins: association of galectin-8 (F19Y) occurrence with autoimmune diseases in a Caucasian population.

BACKGROUND: Galectins are potent immune regulators, with galectin-8 acting as a pro-apoptotic effector on synovial fluid cells and thymocytes and stimulator on T-cells. To set a proof-of-principle example for risk assessment in autoimmunity, and for a mutation affecting physiological galectin sensor functions, a polymorphism in the coding region of the galectin-8 gene (rs2737713; F19Y) was studied for its association with two autoimmune disorders, i.e. rheumatoid arthritis and myasthenia gravis. METHODS: A case-control analysis and a related quantitative trait-association study were performed to investigate the association of this polymorphism in patients (myasthenia gravis 149, rheumatoid arthritis 214 and 134 as primary and repetitive cohorts, respectively) and 365 ethnically matched (Caucasian) healthy controls. Distribution was also investigated in patients grouped according to their antibody status and age at disease onset. Comparative testing for lectin activity was carried out in ELISA/ELLA-based binding tests with both wild-type and F19Y mutant galectin-8 from peripheral blood mononuclear cell lysates of healthy individuals with different genotypes as well as with recombinant wild-type and F19Y mutant galectin-8 proteins. RESULTS: A strong association was found for rheumatoid arthritis, and a mild one with myasthenia gravis. Furthermore, the presence of the sequence deviation also correlated with age at disease onset in the case of rheumatoid arthritis. The F19Y substitution did not appear to affect carbohydrate binding in solid-phase assays markedly. GENERAL SIGNIFICANCE: This is the first report of an association between a galectin-based polymorphism leading to a mutant protein and autoimmune diseases, with evidence for antagonistic pleiotropy.

Evaluation of a partial genome screening of two asthma susceptibility regions using bayesian network based bayesian multilevel analysis of relevance.

Genetic studies indicate high number of potential factors related to asthma. Based on earlier linkage analyses we selected the 11q13 and 14q22 asthma susceptibility regions, for which we designed a partial genome screening study using 145 SNPs in 1201 individuals (436 asthmatic children and 765 controls). The results were evaluated with traditional frequentist methods and we applied a new statistical method, called bayesian network based bayesian multilevel analysis of relevance (BN-BMLA). This method uses bayesian network representation to provide detailed characterization of the relevance of factors, such as joint significance, the type of dependency, and multi-target aspects. We estimated posteriors for these relations within the bayesian statistical framework, in order to estimate the posteriors whether a variable is directly relevant or its association is only mediated.With frequentist methods one SNP (rs3751464 in the FRMD6 gene) provided evidence for an association with asthma (OR = 1.43(1.2-1.8); p = 3×10(-4)). The possible role of the FRMD6 gene in asthma was also confirmed in an animal model and human asthmatics.In the BN-BMLA analysis altogether 5 SNPs in 4 genes were found relevant in connection with asthma phenotype: PRPF19 on chromosome 11, and FRMD6, PTGER2 and PTGDR on chromosome 14. In a subsequent step a partial dataset containing rhinitis and further clinical parameters was used, which allowed the analysis of relevance of SNPs for asthma and multiple targets. These analyses suggested that SNPs in the AHNAK and MS4A2 genes were indirectly associated with asthma. This paper indicates that BN-BMLA explores the relevant factors more comprehensively than traditional statistical methods and extends the scope of strong relevance based methods to include partial relevance, global characterization of relevance and multi-target relevance.

Lack of evidence for association of two functional SNPs of CHI3L1 gene (HC-gp39) with rheumatoid arthritis.

CHI3L1 gene encodes for a glycoprotein (HC-gp39 or YKL40) secreted by synovial fibroblasts, macrophages, neutrophil granulocytes and chondrocytes. Its expression is under the control of NF-kB. It is regarded as an acute phase protein, and its levels are significantly elevated in rheumatic diseases. Furthermore, HC-gp39 has been shown to be recognized by autoreactive T cells in rheumatoid arthritis. In the present study, we have examined two functional variants of the promoter region of CHI3L1 gene (CHI3L1-1 (rs4950928) and CHI3L1-2 (rs10399931) that have been reported earlier to be associated with schizophrenia and sarcoidosis. We used TaqMan allelic discrimination assays to study the genotypes of Hungarian patients with rheumatoid arthritis (n = 182) and of healthy controls (n = 194). No significant association of the investigated SNPs with the disease was found. Here we report that CHI3L1 SNPs, shown to be involved in the predisposition of schizophrenia, are not associated with rheumatoid arthritis.