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Birdshot chorioretinopathy (BSCR) is a rare form of autoimmune uveitis that can lead to severe visual impairment. Intriguingly, >95% of cases carry the HLA-A29 allele, which defines the strongest documented HLA association for a human disease. We have conducted a genome-wide association study in 96 Dutch and 27 Spanish cases, and 398 unrelated Dutch and 380 Spanish controls. Fine-mapping the primary MHC association through high-resolution imputation at classical HLA loci, identified HLA-A*29:02 as the principal MHC association (odds ratio (OR) = 157.5, 95% CI 91.6-272.6, P = 6.6 × 10(-74)). We also identified two novel susceptibility loci at 5q15 near ERAP2 (rs7705093; OR = 2.3, 95% CI 1.7-3.1, for the T allele, P = 8.6 × 10(-8)) and at 14q32.31 in the TECPR2 gene (rs150571175; OR = 6.1, 95% CI 3.2-11.7, for the A allele, P = 3.2 × 10(-8)). The association near ERAP2 was confirmed in an independent British case-control samples (combined meta-analysis P = 1.7 × 10(-9)). Functional analyses revealed that the risk allele of the polymorphism near ERAP2 is strongly associated with high mRNA and protein expression of ERAP2 in B cells. This study further defined an extremely strong MHC risk component in BSCR, and detected evidence for a novel disease mechanism that affects peptide processing in the endoplasmic reticulum.

Seasonal patterns in behavior and biological parameters are widespread. Here, we examined seasonal changes in whole blood gene expression profiles of 233 healthy subjects. Using weighted gene co-expression network analysis, we identified three co-expression modules showing circannual patterns. Enrichment analysis suggested that this signal stems primarily from red blood cells and blood platelets. Indeed, a large clinical database with 51 142 observations of blood cell counts over 3 years confirmed a corresponding seasonal pattern of counts of red blood cells, reticulocytes and platelets. We found no direct evidence that these changes are linked to genes known to be key players in regulating immune function or circadian rhythm. It is likely, however, that these seasonal changes in cell counts and gene expression profiles in whole blood represent biological and clinical relevant phenomena. Moreover, our findings highlight possible confounding factors relevant to the study of gene expression profiles in subjects collected at geographical locations with disparaging seasonality patterns.

BackgroundAnimal studies have revealed seasonal patterns in cerebrospinal fluid (CSF) monoamine (MA) turnover. In humans, no study had systematically assessed seasonal patterns in CSF MA turnover in a large set of healthy adults.Methodology/principal findingsStandardized amounts of CSF were prospectively collected from 223 healthy individuals undergoing spinal anesthesia for minor surgical procedures. The metabolites of serotonin (5-hydroxyindoleacetic acid, 5-HIAA), dopamine (homovanillic acid, HVA) and norepinephrine (3-methoxy-4-hydroxyphenylglycol, MPHG) were measured using high performance liquid chromatography (HPLC). Concentration measurements by sampling and birth dates were modeled using a non-linear quantile cosine function and locally weighted scatterplot smoothing (LOESS, span = 0.75). The cosine model showed a unimodal season of sampling 5-HIAA zenith in April and a nadir in October (p-value of the amplitude of the cosine = 0.00050), with predicted maximum (PC(max)) and minimum (PC(min)) concentrations of 173 and 108 nmol/L, respectively, implying a 60% increase from trough to peak. Season of birth showed a unimodal 5-HIAA zenith in May and a nadir in November (p = 0.00339; PC(max) = 172 and PC(min) = 126). The non-parametric LOESS showed a similar pattern to the cosine in both season of sampling and season of birth models, validating the cosine model. A final model including both sampling and birth months demonstrated that both sampling and birth seasons were independent predictors of 5-HIAA concentrations.ConclusionIn subjects without mental illness, 5-HT turnover shows circannual variation by season of sampling as well as season of birth, with peaks in spring and troughs in fall.

Background: A minority of patients with attention-deficit hyperactivity disorder (ADHD) do not respond favorably to methylphenidate. This has been partially associated with homozygosity for the Dopamine transporter (DAT1) 10-repeat allele and the presence of one or two Dopamine D4 receptor (DRD4) 7-repeat alleles. This study examined the sibling correlation of methylphenidate response rate and the possible association between response rate and these risk alleles. Methods: A sample of 82 Dutch children with ADHD, from 54 families, (including 30 singletons and 28 sib pairs), who used methylphenidate, was phenotyped according to DSM-IV criteria. Patients were members of affected sib pairs and were genotyped for DAT1 and DRD4. The sibling Intraclass Correlation Coefficient for methylphenidate response rate was calculated. The association between individual response rates and the risk alleles was examined using linear regression techniques. Results: The Intraclass Correlation Coefficient was significant (r = 0.563, p = 0.001). No evidence was found establishing an association between methylphenidate response and DAT1-homozygosity. There was a positive trend towards association with the presence of one or two DRD4-7R alleles. Conclusions: The sibling correlation may indicate a familial clustering of methylphenidate response. This response is possibly associated with the presence of one or two alleles at the DRD4-7R locus, but not with DAT1-10R homozygosity in the Dutch population.

A large association study by O'Donovan et al recently suggested that genetic variation in fibroblast growth factor receptor (FGFR) 2 increases the risk for developing schizophrenia. Fibroblast growth factors (FGFs) are part of the family of glial growth factors; they control the growth and patterning of specific brain structures and regulate the maintenance and repair of neuronal tissues. In addition, a direct interaction was recently found between FGFRs and adenosine A(2A) receptors, leading to corticostriatal plasticity and antagonizing the signaling pathway of dopamine D(2) receptors. These findings make FGFs plausible candidate genes for schizophrenia. Here, we review the role of FGFs in schizophrenia and combine evidence from studies on variations in FGF genes, RNA expression, protein levels, and FGF administration, as well as the effects of medication and environmental risk factors for schizophrenia. These data suggest that changes in the FGF system contribute to schizophrenia and possibly to a wider range of psychiatric disorders. The role of FGFs in schizophrenia and related disorders needs to be studied in more detail.

Genetic association studies have yielded extensive but frequently inconclusive data about genetic risk factors for schizophrenia. Clinical and genetic heterogeneity are possible factors explaining the inconsistent findings. The objective of this study was to test the association of commonly incriminated candidate genes with two clinically divergent subgroups, non-deficit (SZ-ND) and deficit-schizophrenia (SZ-D), and symptom severity, in order to test for replication of previously reported results. A homogeneous sample of 280 schizophrenia patients and 230 healthy controls of Hungarian, Caucasian descent were genotyped for polymorphisms in schizophrenia candidate genes NRG1, DTNBP1, RGS4, G72/G30, and PIP5K2A. Patients were divided into the diagnostic subgroups of SZ-ND and SZ-D using the Schedule for Deficit Syndrome (SDS), and assessed clinically by the Positive and Negative Symptom Scale (PANSS). SNP8NRG241930 in NRG1 and rs1011313 in DTNBP1 were associated with SZ-ND (P = 0.04 and 0.03, respectively). Polymorphisms in RGS4, G72/G30, and PIP5K2A were neither associated with SZ-ND nor with SZ-D. SNP8NRG241930 showed association with the PANSS cognitive and hostility/excitability factors, rs1011313 with the negative factor and SDS total score, and rs10917670 in RGS4 was associated with the depression factor. Although these results replicate earlier findings about the genetic background of SZ-ND and SZ-D only partially, our data seem to confirm previously reported association of NRG1 with schizophrenia without prominent negative symptoms. It was possible to detect associations of small-to-medium effect size between the investigated candidate genes and symptom severity. Such studies have the potential to unravel the possible connection between genetic and clinical heterogeneity in schizophrenia.

Schizophrenia is a complex genetic disorder which is caused by multiple heritable and environmental factors. Large-scale screening of the entire DNA has recently resulted in the identification of several DNA variants associated with schizophrenia. The variants identified are single nucleotide polymorphisms (SNPs) with a high frequency in the population and a small effect, and rare copy number variants (CNVs) with larger effects. Variants are not unique to patients, and appear to be involved in multiple psychiatric disorders. The underlying biological mechanisms are not evident. Together, the identified variants only explain a fraction of all cases of the disease. Genetic testing of family members of patients may become feasible in the near future. For other clinical applications additional variants need to be identified first.