Custom scoring based on ecological topology of gut microbiota associated with cancer immunotherapy outcome.

The gut microbiota influences the clinical responses of cancer patients to immunecheckpoint inhibitors (ICIs). However, there is no consensus definition of detrimental dysbiosis. Based on metagenomics (MG) sequencing of 245 non-small cell lung cancer (NSCLC) patient feces, we constructed species-level co-abundance networks that were clustered into species-interacting groups (SIGs) correlating with overall survival. Thirty-seven and forty-five MG species (MGSs) were associated with resistance (SIG1) and response (SIG2) to ICIs, respectively. When combined with the quantification of Akkermansia species, this procedure allowed a person-based calculation of a topological score (TOPOSCORE) that was validated in an additional 254 NSCLC patients and in 216 genitourinary cancer patients. Finally, this TOPOSCORE was translated into a 21-bacterial probe set-based qPCR scoring that was validated in a prospective cohort of NSCLC patients as well as in colorectal and melanoma patients. This approach could represent a dynamic diagnosis tool for intestinal dysbiosis to guide personalized microbiota-centered interventions.

Pharmacodynamic biomarkers of long-term interferon beta-1a therapy in REFLEX and REFLEXION.

This post-hoc analysis evaluated candidate biomarkers of long-term efficacy of subcutaneous interferon beta-1a (sc IFN ß-1a) in REFLEX/REFLEXION studies of clinically isolated syndrome. Samples from 507 REFLEX and 287 REFLEXION study participants were analyzed. All investigated biomarkers were significantly upregulated 1.5-4-fold in response to sc IFN ß-1a treatment versus baseline (p ≤ 0.008). The validity of MX1, 2'5'OAS, and IL-1RA as biomarkers of response to sc IFN ß-1a was confirmed in this large patient cohort, with biomarkers consistently upregulated in a dose-dependent manner. Neopterin, TRAIL, and IP-10 were confirmed as biomarkers associated with long-term sc IFN ß-1a treatment efficacy over 5 years.

Protective effects of rimeporide on left ventricular function in golden retriever muscular dystrophy dogs.

BACKGROUND: Alterations in intracellular Na+ and Ca2+ have been observed in patients with Duchenne muscular dystrophy (DMD) and in animal models of DMD, and inhibition of Na+-H+ exchanger 1 (NHE1) by rimeporide has previously demonstrated cardioprotective effects in animal models of myocardial ischemia and heart failure. Since heart failure is becoming a predominant cause of death in DMD patients, this study aimed to demonstrate a cardioprotective effect of chronic administration of rimeporide in a canine model of DMD. METHODS: Golden retriever muscular dystrophy (GRMD) dogs were randomized to orally receive rimeporide (10 mg/kg, twice a day) or placebo from 2 months to 1 year of age. Left ventricular (LV) function was assessed by conventional and advanced echocardiography. RESULTS: Compared with placebo-treated GRMD, LV function deterioration with age was limited in rimeporide-treated GRMD dogs as indicated by the preservation of LV ejection fraction as well as overall cardiac parameters different from placebo-treated dogs, as revealed by composite cardiac scores and principal component analysis. In addition, principal component analysis clustered rimeporide-treated GRMD dogs close to healthy control dogs. CONCLUSIONS: Chronic administration of the NHE1 inhibitor rimeporide exerted a protective effect against LV function decline in GRMD dogs. This study provides proof of concept to explore the cardiac effects of rimeporide in DMD patients.

Proteomes of Paired Human Cerebrospinal Fluid and Plasma: Relation to Blood-Brain Barrier Permeability in Older Adults.

The systems-level relationship between the proteomes of cerebrospinal fluid (CSF) and plasma has not been comprehensively described so far. Recently developed shotgun proteomic workflows allow for deeper characterization of the proteomes from body fluids in much larger sample size. We deployed state-of-the-art mass spectrometry-based proteomics in paired CSF and plasma samples volunteered by 120 elders with and without cognitive impairment to comprehensively characterize and examine compartmental proteome differences and relationships between both body fluids. We further assessed the influence of blood-brain barrier (BBB) integrity and tested the hypothesis that BBB breakdown can be identified from CSF and plasma proteome alterations in nondemented elders. We quantified 790 proteins in CSF and 422 proteins in plasma, and 255 of the proteins were identified in both compartments. Pearson's statistics determined 28 proteins with associated levels between CSF and plasma. BBB integrity as defined with the CSF/serum albumin index influenced 76 CSF/plasma protein ratios. In least absolute shrinkage and selection operator models, CSF and plasma proteins improved identification of BBB impairment. In conclusion, we provide here a first comprehensive draft map of interacting human CSF and plasma proteomes, in view of their complex and dynamic compositions, and influence of the BBB.

Blood-brain barrier breakdown, neuroinflammation, and cognitive decline in older adults.

INTRODUCTION: Blood-brain barrier (BBB) breakdown is observed in older versus younger adults and in late-onset Alzheimer's disease versus age-matched controls, but its causes and consequences in aging are unclear. We tested the hypothesis that BBB breakdown is associated with cognitive decline and inflammation in nondemented elders. METHODS: Cerebrospinal fluid and serum inflammatory markers were measured using sandwich immunoassays in 120 subjects. Least Absolute Shrinkage and Selection Operator-logistic regression selected cerebrospinal fluid and serum signatures that best classified BBB impairment defined by the cerebrospinal fluid albumin index ≥9. Linear regression examined changes in Clinical Dementia Rating sum of boxes as a function of BBB integrity at baseline. RESULTS: Mean age was 70 years, mean Mini­Mental State Examination was 27, and BBB impairment was recorded in 13.5%. BBB breakdown was associated with cognitive decline (P = .015). Cerebrospinal fluid intercellular adhesion molecule-1, vascular endothelial growth factor, interleukin-8, serum amyloid A, macrophage derived chemokine, and gender generated an area under the curve of 0.95 for BBB impairment, and serum IL-16, VEGF-D, IL-15, and other variables generated an AUC of 0.92 for BBB impairment. DISCUSSION: BBB breakdown is associated with more rapid cognitive decline. Inflammatory mechanisms, including cell adhesion, neutrophil migration, lipid metabolism, and angiogenesis may be implicated.

Alzheimer disease pathology and the cerebrospinal fluid proteome.

BACKGROUND: Altered proteome profiles have been reported in both postmortem brain tissues and body fluids of subjects with Alzheimer disease (AD), but their broad relationships with AD pathology, amyloid pathology, and tau-related neurodegeneration have not yet been fully explored. Using a robust automated MS-based proteomic biomarker discovery workflow, we measured cerebrospinal fluid (CSF) proteomes to explore their association with well-established markers of core AD pathology. METHODS: Cross-sectional analysis was performed on CSF collected from 120 older community-dwelling adults with normal (n = 48) or impaired cognition (n = 72). LC-MS quantified hundreds of proteins in the CSF. CSF concentrations of ß-amyloid 1-42 (Aß1-42), tau, and tau phosphorylated at threonine 181 (P-tau181) were determined with immunoassays. First, we explored proteins relevant to biomarker-defined AD. Then, correlation analysis of CSF proteins with CSF markers of amyloid pathology, neuronal injury, and tau hyperphosphorylation (i.e., Aß1-42, tau, P-tau181) was performed using Pearson's correlation coefficient and Bonferroni correction for multiple comparisons. RESULTS: We quantified 790 proteins in CSF samples with MS. Four CSF proteins showed an association with CSF Aß1-42 levels (p value ≤ 0.05 with correlation coefficient (R) ≥ 0.38). We identified 50 additional CSF proteins associated with CSF tau and 46 proteins associated with CSF P-tau181 (p value ≤ 0.05 with R ≥ 0.37). The majority of those proteins that showed such associations were brain-enriched proteins. Gene Ontology annotation revealed an enrichment for synaptic proteins and proteins originating from reelin-producing cells and the myelin sheath. CONCLUSIONS: We used an MS-based proteomic workflow to profile the CSF proteome in relation to cerebral AD pathology. We report strong evidence of previously reported CSF proteins and several novel CSF proteins specifically associated with amyloid pathology or neuronal injury and tau hyperphosphorylation.

Plasma Proteomic Profiles of Cerebrospinal Fluid-Defined Alzheimer's Disease Pathology in Older Adults.

BACKGROUND: Cerebrospinal fluid (CSF) biomarkers of the beta-amyloid and microtubule associated protein tau metabolism have proven the capacity to improve classification of subjects developing Alzheimer's disease (AD). The blood plasma proteome was characterized to further elaborate upon the mechanisms involved and identify proteins that may improve classification of older adults developing an AD dementia. OBJECTIVE: Identify and describe plasma protein expressions that best classify subjects with CSF-defined presence of AD pathology and cerebral amyloidosis. METHODS: We performed a cross-sectional analysis of samples collected from community-dwelling elderly with (n = 72) or without (n = 48) cognitive impairment. CSF Aß1-42, tau, and phosphorylated tau (P-tau181) were measured using ELISA, and mass spectrometry quantified the plasma proteomes. Presence of AD pathology was defined as CSF P-tau181/Aß1-42 > 0.0779, and presence of amyloidosis was defined as CSF Aß1-42 < 724 pg/mL. RESULTS: Two hundred and forty-eight plasma proteins were quantified. Plasma proteins did not improve classification of the AD CSF biomarker profile in the whole sample. When the analysis was separately performed in the cognitively impaired individuals, the diagnosis accuracy of AD CSF profile was 88.9% with 19 plasma proteins included. Within the full cohort, there were 16 plasma proteins that improved diagnostic accuracy of cerebral amyloidosis to 92.4%. CONCLUSION: Plasma proteins improved classification accuracy of AD pathology in cognitively-impaired older adults and appeared representative of amyloid pathology. If confirmed, those candidates could serve as valuable blood biomarkers of the preclinical stages of AD or risk of developing AD.

One-carbon metabolism, cognitive impairment and CSF measures of Alzheimer pathology: homocysteine and beyond.

BACKGROUND: Hyperhomocysteinemia is a risk factor for cognitive decline and dementia, including Alzheimer disease (AD). Homocysteine (Hcy) is a sulfur-containing amino acid and metabolite of the methionine pathway. The interrelated methionine, purine, and thymidylate cycles constitute the one-carbon metabolism that plays a critical role in the synthesis of DNA, neurotransmitters, phospholipids, and myelin. In this study, we tested the hypothesis that one-carbon metabolites beyond Hcy are relevant to cognitive function and cerebrospinal fluid (CSF) measures of AD pathology in older adults. METHODS: Cross-sectional analysis was performed on matched CSF and plasma collected from 120 older community-dwelling adults with (n = 72) or without (n = 48) cognitive impairment. Liquid chromatography-mass spectrometry was performed to quantify one-carbon metabolites and their cofactors. Least absolute shrinkage and selection operator (LASSO) regression was initially applied to clinical and biomarker measures that generate the highest diagnostic accuracy of a priori-defined cognitive impairment (Clinical Dementia Rating-based) and AD pathology (i.e., CSF tau phosphorylated at threonine 181 [p-tau181]/ß-Amyloid 1-42 peptide chain [Aß1-42] >0.0779) to establish a reference benchmark. Two other LASSO-determined models were generated that included the one-carbon metabolites in CSF and then plasma. Correlations of CSF and plasma one-carbon metabolites with CSF amyloid and tau were explored. LASSO-determined models were stratified by apolipoprotein E (APOE) ε4 carrier status. RESULTS: The diagnostic accuracy of cognitive impairment for the reference model was 80.8% and included age, years of education, Aß1-42, tau, and p-tau181. A model including CSF cystathionine, methionine, S-adenosyl-L-homocysteine (SAH), S-adenosylmethionine (SAM), serine, cysteine, and 5-methyltetrahydrofolate (5-MTHF) improved the diagnostic accuracy to 87.4%. A second model derived from plasma included cystathionine, glycine, methionine, SAH, SAM, serine, cysteine, and Hcy and reached a diagnostic accuracy of 87.5%. CSF SAH and 5-MTHF were associated with CSF tau and p-tau181. Plasma one-carbon metabolites were able to diagnose subjects with a positive CSF profile of AD pathology in APOE ε4 carriers. CONCLUSIONS: We observed significant improvements in the prediction of cognitive impairment by adding one-carbon metabolites. This is partially explained by associations with CSF tau and p-tau181, suggesting a role for one-carbon metabolism in the aggregation of tau and neuronal injury. These metabolites may be particularly critical in APOE ε4 carriers.

Markers of neuroinflammation associated with Alzheimer's disease pathology in older adults.

BACKGROUND: In vitro and animal studies have linked neuroinflammation to Alzheimer's disease (AD) pathology. Studies on markers of inflammation in subjects with mild cognitive impairment or AD dementia provided inconsistent results. We hypothesized that distinct blood and cerebrospinal fluid (CSF) inflammatory markers are associated with biomarkers of amyloid and tau pathology in older adults without cognitive impairment or with beginning cognitive decline. OBJECTIVE: To identify blood-based and CSF neuroinflammation marker signatures associated with AD pathology (i.e. an AD CSF biomarker profile) and to investigate associations of inflammation markers with CSF biomarkers of amyloid, tau pathology, and neuronal injury. DESIGN/METHODS: Cross-sectional analysis was performed on data from 120 older community-dwelling adults with normal cognition (n=48) or with cognitive impairment (n=72). CSF Aß1-42, tau and p-tau181, and a panel of 37 neuroinflammatory markers in both CSF and serum were quantified. Least absolute shrinkage and selection operator (LASSO) regression was applied to determine a reference model that best predicts an AD CSF biomarker profile defined a priori as p-tau181/Aß1-42 ratio >0.0779. It was then compared to a second model that included the inflammatory markers from either serum or CSF. In addition, the correlations between inflammatory markers and CSF Aß1-42, tau and p-tau181 levels were assessed. RESULTS: Forty-two subjects met criteria for having an AD CSF biomarker profile. The best predictive models included 8 serum or 3 CSF neuroinflammatory markers related to cytokine mediated inflammation, vascular injury, and angiogenesis. Both models improved the accuracy to predict an AD biomarker profile when compared to the reference model. In analyses separately performed in the subgroup of participants with cognitive impairment, adding the serum or the CSF neuroinflammation markers also improved the accuracy of the diagnosis of AD pathology. None of the inflammatory markers correlated with the CSF Aß1-42 levels. Six CSF markers (IL-15, MCP-1, VEGFR-1, sICAM1, sVCAM-1, and VEGF-D) correlated with the CSF tau and p-tau181 levels, and these associations remained significant after controlling for age, sex, cognitive impairment, and APOEε4 status. CONCLUSIONS: The identified serum and CSF neuroinflammation biomarker signatures improve the accuracy of classification for AD pathology in older adults. Our results suggest that inflammation, vascular injury, and angiogenesis as reflected by CSF markers are closely related to cerebral tau pathology.

Validating genetic markers of response to recombinant human growth hormone in children with growth hormone deficiency and Turner syndrome: the PREDICT validation study.

OBJECTIVE: Single-nucleotide polymorphisms (SNPs) associated with the response to recombinant human growth hormone (r-hGH) have previously been identified in growth hormone deficiency (GHD) and Turner syndrome (TS) children in the PREDICT long-term follow-up (LTFU) study (Nbib699855). Here, we describe the PREDICT validation (VAL) study (Nbib1419249), which aimed to confirm these genetic associations. DESIGN AND METHODS: Children with GHD (n = 293) or TS (n = 132) were recruited retrospectively from 29 sites in nine countries. All children had completed 1 year of r-hGH therapy. 48 SNPs previously identified as associated with first year growth response to r-hGH were genotyped. Regression analysis was used to assess the association between genotype and growth response using clinical/auxological variables as covariates. Further analysis was undertaken using random forest classification. RESULTS: The children were younger, and the growth response was higher in VAL study. Direct genotype analysis did not replicate what was found in the LTFU study. However, using exploratory regression models with covariates, a consistent relationship with growth response in both VAL and LTFU was shown for four genes - SOS1 and INPPL1 in GHD and ESR1 and PTPN1 in TS. The random forest analysis demonstrated that only clinical covariates were important in the prediction of growth response in mild GHD (>4 to <10 µg/L on GH stimulation test), however, in severe GHD (≤4 µg/L) several SNPs contributed (in IGF2, GRB10, FOS, IGFBP3 and GHRHR). CONCLUSIONS: The PREDICT validation study supports, in an independent cohort, the association of four of 48 genetic markers with growth response to r-hGH treatment in both pre-pubertal GHD and TS children after controlling for clinical/auxological covariates. However, the contribution of these SNPs in a prediction model of first-year response is not sufficient for routine clinical use.

Single Nucleotide Polymorphism Clustering in Systemic Autoimmune Diseases.

Systemic Autoimmune Diseases, a group of chronic inflammatory conditions, have variable symptoms and difficult diagnosis. In order to reclassify them based on genetic markers rather than clinical criteria, we performed clustering of Single Nucleotide Polymorphisms. However naive approaches tend to group patients primarily by their geographic origin. To reduce this "ancestry signal", we developed SNPClust, a method to select large sources of ancestry-independent genetic variations from all variations detected by Principal Component Analysis. Applied to a Systemic Lupus Erythematosus case control dataset, SNPClust successfully reduced the ancestry signal. Results were compared with association studies between the cases and controls without or with reference population stratification correction methods. SNPClust amplified the disease discriminating signal and the ratio of significant associations outside the HLA locus was greater compared to population stratification correction methods. SNPClust will enable the use of ancestry-independent genetic information in the reclassification of Systemic Autoimmune Diseases. SNPClust is available as an R package and demonstrated on the public Human Genome Diversity Project dataset at https://github.com/ThomasChln/snpclust.

GH deficiency status combined with GH receptor polymorphism affects response to GH in children.

Meta-analysis has shown a modest improvement in first-year growth response to recombinant human GH (r-hGH) for carriers of the exon 3-deleted GH receptor (GHRd3) polymorphism but with significant interstudy variability. The associations between GHRd3 and growth response to r-hGH over 3 years in relation to severity of GH deficiency (GHD) were investigated in patients from 14 countries. Treatment-naïve pre-pubertal children with GHD were enrolled from the PREDICT studies (NCT00256126 and NCT00699855), categorized by peak GH level (peak GH) during provocation test: ≤4 µg/l (severe GHD; n=45) and >4 to <10 µg/l mild GHD; n=49) and genotyped for the GHRd3 polymorphism (full length (fl/fl, fl/d3, d3/d3). Gene expression (GE) profiles were characterized at baseline. Changes in growth (height (cm) and SDS) over 3 years were measured. There was a dichotomous influence of GHRd3 polymorphism on response to r-hGH, dependent on peak GH level. GH peak level (higher vs lower) and GHRd3 (fl/fl vs d3 carriers) combined status was associated with height change over 3 years (P<0.05). GHRd3 carriers with lower peak GH had lower growth than subjects with fl/fl (median difference after 3 years -3.3 cm; -0.3 SDS). Conversely, GHRd3 carriers with higher peak GH had better growth (+2.7 cm; +0.2 SDS). Similar patterns were observed for GH-dependent biomarkers. GE profiles were significantly different between the groups, indicating that the interaction between GH status and GHRd3 carriage can be identified at a transcriptomic level. This study demonstrates that responses to r-hGH depend on the interaction between GHD severity and GHRd3 carriage.

A genome-wide association study in progressive multiple sclerosis.

BACKGROUND: The role played by genetic factors in influencing the clinical course of multiple sclerosis (MS) is not yet well established. OBJECTIVE: We aimed to identify genetic variants associated with progressive MS (PrMS). METHODS: We conducted a genome-wide association study (GWAS) in 197 patients with PrMS and 234 controls of Italian origin. We tested the top 20 single nucleotide polymorphisms (SNPs) with suggestive evidence of association (p-value<10(-4)) in two independent sets of primary progressive MS cases and controls. RESULTS: We identified a risk-associated SNP in the HLA region in linkage disequilibrium (LD) with DRB1*1501 and DQB*0602 loci, with genome-wide significance (rs3129934(T), p (combined)=6.7×10(-16), OR=2.34, 95% CI=1.90-2.87), and a novel locus on chromosome 7q35 with suggestive evidence of association (rs996343(G), p (combined)=2.4×10(-5), OR=0.70, 95% CI=0.59-0.83) which maps within a human endogenous retroviral (HERV) element. The new locus did not have a 'cis' effect on RNA expression in lymphoblastic cell lines, but pathway analyses of 'trans' effects point to an expression regulation of genes involved in neurodegeneration, including glutamate metabolism (p<0.01) and axonal guidance signalling (p<0.02). CONCLUSIONS: We have confirmed the established association with the HLA region and, despite the low statistical power of the study, we found suggestive evidence for association with a novel locus on chromosome 7, with a putative regulatory role.

Genetic and physical interaction of the B-cell systemic lupus erythematosus-associated genes BANK1 and BLK.

OBJECTIVES: Altered signalling in B cells is a predominant feature of systemic lupus erythematosus (SLE). The genes BANK1 and BLK were recently described as associated with SLE. BANK1 codes for a B-cell-specific cytoplasmic protein involved in B-cell receptor signalling and BLK codes for an Src tyrosine kinase with important roles in B-cell development. To characterise the role of BANK1 and BLK in SLE, a genetic interaction analysis was performed hypothesising that genetic interactions could reveal functional pathways relevant to disease pathogenesis. METHODS: The GPAT16 method was used to analyse the gene-gene interactions of BANK1 and BLK. Confocal microscopy was used to investigate co-localisation, and immunoprecipitation was used to verify the physical interaction of BANK1 and BLK. RESULTS: Epistatic interactions between BANK1 and BLK polymorphisms associated with SLE were observed in a discovery set of 279 patients and 515 controls from northern Europe. A meta-analysis with 4399 European individuals confirmed the genetic interactions between BANK1 and BLK. As BANK1 was identified as a binding partner of the Src tyrosine kinase LYN, the possibility that BANK1 and BLK could also show a protein-protein interaction was tested. The co-immunoprecipitation and co-localisation of BLK and BANK1 were demonstrated. In a Daudi cell line and primary naive B cells endogenous binding was enhanced upon B-cell receptor stimulation using anti-IgM antibodies. CONCLUSION: This study shows a genetic interaction between BANK1 and BLK, and demonstrates that these molecules interact physically. The results have important consequences for the understanding of SLE and other autoimmune diseases and identify a potential new signalling pathway.

Detecting epistasis with restricted response patterns in pairs of biallelic loci.

Well-established examples of genetic epistasis between a pair of loci typically show characteristic patterns of phenotypic distributions in joint genotype tables. However, inferring epistasis given such data is difficult due to the lack of power in commonly used approaches, which decompose the epistatic patterns into main plus interaction effects followed by testing the interaction term. Testing additive-only or all terms may have more power, but they are sensitive to nonepistatic patterns. Alternatively, the epistatic patterns of interest can be enumerated and the best matching one is found by searching through the possibilities. Although this approach requires multiple testing correction over possible patterns, each pattern can be fitted with a regression model with just one degree of freedom and thus the overall power can still be high, if the number of possible patterns is limited. Here we compare the power of the linear decomposition and pattern search methods, by applying them to simulated data generated under several patterns of joint genotype effects with simple biological interpretations. Interaction-only tests are the least powerful; while pattern search approach is the most powerful if the range of possibilities is restricted, but still includes the true pattern.

MGAT5 and disease severity in progressive multiple sclerosis.

MGAT5 was demonstrated to be associated to multiple sclerosis (MS) severity. We evaluated its role in progressive MS. We studied 11 SNPs mapping to MGAT5 in an Italian cohort of primary progressive or progressive-relapsing patients. The rs1257169(G) allele is associated with lower disease severity (p-value = 0.02). Adding the age of onset as covariate, another SNP, rs539588, is nominally significant. None of the SNPs survived after multiple testing correction. These results, even if suggestive of MGAT5 involvement also in progressive MS severity, require a bigger sample size to confirm and better explore the role of this locus in this rare disease course.

Gene-based bin analysis of genome-wide association studies.

BACKGROUND: With the improvement of genotyping technologies and the exponentially growing number of available markers, case-control genome-wide association studies promise to be a key tool for investigation of complex diseases. However new analytical methods have to be developed to face the problems induced by this data scale-up, such as statistical multiple testing, data quality control and computational tractability. RESULTS: We present a novel method to analyze genome-wide association studies results. The algorithm is based on a Bayesian model that integrates genotyping errors and genomic structure dependencies. p-values are assigned to genomic regions termed bins, which are defined from a gene-biased partitioning of the genome, and the false-discovery rate is estimated. We have applied this algorithm to data coming from three genome-wide association studies of Multiple Sclerosis. CONCLUSION: The method practically overcomes the scale-up problems and permits to identify new putative regions statistically associated with the disease.

ExactFDR: exact computation of false discovery rate estimate in case-control association studies.

Genome-wide association studies require accurate and fast statistical methods to identify relevant signals from the background noise generated by a huge number of simultaneously tested hypotheses. It is now commonly accepted that exact computations of association probability value (P-value) are preferred to chi(2) and permutation-based approximations. Following the same principle, the ExactFDR software package improves speed and accuracy of the permutation-based false discovery rate (FDR) estimation method by replacing the permutation-based estimation of the null distribution by the generalization of the algorithm used for computing individual exact P-values. It provides a quick and accurate non-conservative estimator of the proportion of false positives in a given selection of markers, and is therefore an efficient and pragmatic tool for the analysis of genome-wide association studies.

Functional variants in the B-cell gene BANK1 are associated with systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is a prototypical autoimmune disease characterized by production of autoantibodies and complex genetic inheritance. In a genome-wide scan using 85,042 SNPs, we identified an association between SLE and a nonsynonymous substitution (rs10516487, R61H) in the B-cell scaffold protein with ankyrin repeats gene, BANK1. We replicated the association in four independent case-control sets (combined P = 3.7 x 10(-10); OR = 1.38). We analyzed BANK1 cDNA and found two isoforms, one full-length and the other alternatively spliced and lacking exon 2 (Delta2), encoding a protein without a putative IP3R-binding domain. The transcripts were differentially expressed depending on a branch point-site SNP, rs17266594, in strong linkage disequilibrium (LD) with rs10516487. A third associated variant was found in the ankyrin domain (rs3733197, A383T). Our findings implicate BANK1 as a susceptibility gene for SLE, with variants affecting regulatory sites and key functional domains. The disease-associated variants could contribute to sustained B cell-receptor signaling and B-cell hyperactivity characteristic of this disease.