The age-specific microbiome of children with milk, egg, and peanut allergy.

BACKGROUND: Immune regulation by gut microbiota is affected by dysbiosis and may precede food allergy onset. Prior studies lacked comparisons stratified by age and clinical phenotype. OBJECTIVE: To assess the microbiome of children with food allergy (<3 years, 3-18 years) compared with similar aged children without food allergy. METHODS: A real-world prospective cross-sectional study performed from 2014 to 2019 recruited children highly likely to have milk, egg, or peanut allergy defined by history and serum IgE or confirmed by food challenge. 16S ribosomal RNA sequencing identified stool microbial DNA. Alpha and beta diversity was compared between groups with food allergy and healthy controls stratified by age. Differential abundance for non a priori taxa was accepted at absolute fold-change greater than 2 and q value less than 0.05. RESULTS: A total of 70 patients were included (56 with food allergy and 14 healthy controls). Groups were not significantly different in age, gender at birth, race, mode of delivery, breastfeeding duration, or antibiotic exposure. Younger children with food allergy had similar alpha diversity compared with controls. Beta diversity was significantly different by age (P = .001). There was differential abundance of several a priori (P < .05) taxa (including Clostridia) only in younger children. Both a priori (including Coprococcus and Clostridia) and non a priori (q < 0.05) Acidobacteria_Gp15, Aestuariispira, Tindallia, and Desulfitispora were significant in older children with food allergy, especially with peanut allergy. CONCLUSION: Dysbiosis associates with food allergy, most prominent in older children with peanut allergy. Younger children with and without food allergy have fewer differences in gut microbiota. This correlates with clinical observations of persistence of peanut allergy and improved efficacy and safety of oral immunotherapy in younger children. Age younger than 3 years should be considered when initiating therapeutic interventions.

Predictive molecular biomarkers for determining neoadjuvant chemosensitivity in muscle invasive bladder cancer.

INTRODUCTION: Identifying neoadjuvant chemotherapy (NAC) response in patients with muscle invasive bladder cancer (MIBC) has had limited success based on clinicopathological features and molecular subtyping. Identification of chemotherapy responsive cohorts would facilitate delivery to those most likely to benefit. OBJECTIVE: Develop a molecular signature that can identify MIBC NAC responders (R) and non-responders (NR) using a cohort of known NAC response phenotypes, and better understand differences in molecular pathways and subtype classifications between NAC R and NR. MATERIALS AND METHODS: Presented are the messenger RNA (mRNA) and microRNA (miRNA) differential expression profiles from initial transurethral resection of bladder tumor (TURBT) specimens of a discovery cohort of MIBC patients consisting of 7 known NAC R and 11 NR, and a validation cohort consisting of 3 R and 5 NR. Pathological response at time of cystectomy after NAC was used to classify initial TURBT specimens as R (pT0) versus NR (≥pT2). RNA and miRNA from FFPE blocks were sequenced using RNAseq and qPCR, respectively. RESULTS: The discovery cohort had 2309 genes, while the validation cohort had 602 genes and 13 miRNA differentially expressed between R and NR. Gene set enrichment analysis identified mitochondrial gene expression, DNA replication initiation, DNA unwinding in the R discovery cohort and positive regulation of vascular associated smooth muscle cell proliferation in the NR discovery cohort. Canonical correlation (CC) analysis was applied to differentiate R versus NR. 3 CCs (CC13, CC16, and CC17) had an AUC >0.65 in the discovery and validation dataset. Gene ontology enrichment showed CC13 as nucleoside triphosphate metabolic process, CC16 as cell cycle and cellular response to DNA damage, CC17 as DNA packaging complex. All patients were classified using established molecular subtypes: Baylor, UNC, CIT, Lund, MD Anderson, TCGA, and Consensus Class. The MD Anderson p53-like subtype, CIT MC4 subtype and Consensus Class stroma rich subtype had the strongest correlation with a NR phenotype, while no subtype had a strong correlation with the R phenotype. CONCLUSIONS: Our results identify molecular signatures that can be used to differentiate MIBC NAC R versus NR, salient molecular pathway differences, and highlight the utility of molecular subtyping in relation to NAC response.

Single-cell analysis of menstrual endometrial tissues defines phenotypes associated with endometriosis.

BACKGROUND: Endometriosis is a common, complex disorder which is underrecognized and subject to prolonged delays in diagnosis. It is accompanied by significant changes in the eutopic endometrial lining. METHODS: We have undertaken the first single-cell RNA-sequencing (scRNA-Seq) comparison of endometrial tissues in freshly collected menstrual effluent (ME) from 33 subjects, including confirmed endometriosis patients (cases) and controls as well as symptomatic subjects (who have chronic symptoms suggestive of endometriosis but have not been diagnosed). RESULTS: We identify a unique subcluster of proliferating uterine natural killer (uNK) cells in ME-tissues from controls that is almost absent from endometriosis cases, along with a striking reduction of total uNK cells in the ME of cases (p < 10-16). In addition, an IGFBP1+ decidualized subset of endometrial stromal cells are abundant in the shed endometrium of controls when compared to cases (p < 10-16) confirming findings of compromised decidualization of cultured stromal cells from cases. By contrast, endometrial stromal cells from cases are enriched in cells expressing pro-inflammatory and senescent phenotypes. An enrichment of B cells in the cases (p = 5.8 × 10-6) raises the possibility that some may have chronic endometritis, a disorder which predisposes to endometriosis. CONCLUSIONS: We propose that characterization of endometrial tissues in ME will provide an effective screening tool for identifying endometriosis in patients with chronic symptoms suggestive of this disorder. This constitutes a major advance, since delayed diagnosis for many years is a major clinical problem in the evaluation of these patients. Comprehensive analysis of ME is expected to lead to new diagnostic and therapeutic approaches to endometriosis and other associated reproductive disorders such as female infertility.

Prognostic Molecular Signatures for Metastatic Potential in Clinically Low-Risk Stage I and II Clear Cell Renal Cell Carcinomas.

Introduction: For patients with localized node-negative (Stage I and II) clear cell renal cell carcinomas (ccRCC), current clinicopathological staging has limited predictive capability because of their low risk. Analyzing molecular signatures at the time of nephrectomy can aid in understanding future metastatic potential. Objective: Develop a molecular signature that can stratify patients who have clinically low risk ccRCC, but have high risk genetic changes driving an aggressive metastatic phenotype. Patients, Materials, and Methods: Presented is the differential expression of mRNA and miRNA in 44 Stage I and Stage II patients, 21 who developed metastasis within 5 years of nephrectomy, compared to 23 patients who remained disease free for more than 5 years. Extracted RNA from nephrectomy specimens preserved in FFPE blocks was sequenced using RNAseq. MiRNA expression was performed using the TaqMan OpenArray qPCR protocol. Results: One hundred thirty one genes and 2 miRNA were differentially expressed between the two groups. Canonical correlation (CC) analysis was applied and four CCs (CC32, CC20, CC9, and CC7) have an AUC > 0.65 in our dataset with similar predictive power in the TCGA-KIRC dataset. Gene set enrichment showed CC9 as kidney development/adhesion, CC20 as oxidative phosphorylation pathway, CC32 as RNA binding/spindle and CC7 as immune response. In a multivariate Cox model, the four CCs were able to identify high/low risk groups for metastases in the TCGA-KIRC (p < 0.05) with odds ratios of CC32 = 5.7, CC20 = 4.4, CC9 = 3.6, and CC7 = 2.7. Conclusion: These results identify molecular signatures for more aggressive tumors in clinically low risk ccRCC patients who have a higher potential of metastasis than would be expected.

Focused HLA analysis in Caucasians with myositis identifies significant associations with autoantibody subgroups.

OBJECTIVES: Idiopathic inflammatory myopathies (IIM) are a spectrum of rare autoimmune diseases characterised clinically by muscle weakness and heterogeneous systemic organ involvement. The strongest genetic risk is within the major histocompatibility complex (MHC). Since autoantibody presence defines specific clinical subgroups of IIM, we aimed to correlate serotype and genotype, to identify novel risk variants in the MHC region that co-occur with IIM autoantibodies. METHODS: We collected available autoantibody data in our cohort of 2582 Caucasian patients with IIM. High resolution human leucocyte antigen (HLA) alleles and corresponding amino acid sequences were imputed using SNP2HLA from existing genotyping data and tested for association with 12 autoantibody subgroups. RESULTS: We report associations with eight autoantibodies reaching our study-wide significance level of p<2.9×10-5. Associations with the 8.1 ancestral haplotype were found with anti-Jo-1 (HLA-B*08:01, p=2.28×10-53 and HLA-DRB1*03:01, p=3.25×10-9), anti-PM/Scl (HLA-DQB1*02:01, p=1.47×10-26) and anti-cN1A autoantibodies (HLA-DRB1*03:01, p=1.40×10-11). Associations independent of this haplotype were found with anti-Mi-2 (HLA-DRB1*07:01, p=4.92×10-13) and anti-HMGCR autoantibodies (HLA-DRB1*11, p=5.09×10-6). Amino acid positions may be more strongly associated than classical HLA associations; for example with anti-Jo-1 autoantibodies and position 74 of HLA-DRB1 (p=3.47×10-64) and position 9 of HLA-B (p=7.03×10-11). We report novel genetic associations with HLA-DQB1 anti-TIF1 autoantibodies and identify haplotypes that may differ between adult-onset and juvenile-onset patients with these autoantibodies. CONCLUSIONS: These findings provide new insights regarding the functional consequences of genetic polymorphisms within the MHC. As autoantibodies in IIM correlate with specific clinical features of disease, understanding genetic risk underlying development of autoantibody profiles has implications for future research.

Challenges and Inconsistencies in Using Lysophosphatidic Acid as a Biomarker for Ovarian Cancer.

Increased detection of plasma lysophosphatidic acid (LPA) has been proposed as a potential diagnostic biomarker in ovarian cancer, but inconsistency exists in these reports. It has been shown that LPA can undergo an artificial increase during sample processing and analysis, which has not been accounted for in ovarian cancer research. The aim of this study is to provide a potential explanation about how the artificial increase in LPA may have interfered with previous LPA analysis in ovarian cancer research. Using an established LC-MS method, we measured LPA and other lysophospholipid levels in plasma obtained from three cohorts of patients: non-cancer controls, patients with benign ovarian tumors, and those with ovarian cancer. We did not find the LPA level to be higher in cancer samples. To understand this inconsistency, we observed that LPA content changed more significantly than other lysophospholipids as a function of plasma storage time while frozen. Additionally, only LPA was found to be adversely impacted by incubation time depending on the Ethylenediaminetetraacetic acid (EDTA) concentration used during blood drawing. We also show that the inhibition of autotaxin effectively prevented artificial LPA generation during incubation at room temperature. Our data suggests that the artificial changes in LPA content may contribute to the discrepancies reported in literature. Any future studies planning to measure plasma LPA should carefully design the study protocol to consider these confounding factors.

Relative Ratios Enhance the Diagnostic Power of Phospholipids in Distinguishing Benign and Cancerous Ovarian Masses.

Ovarian cancer remains a highly lethal disease due to its late clinical presentation and lack of reliable early biomarkers. Protein-based diagnostic markers have presented limitations in identifying ovarian cancer. We tested the potential of phospholipids as markers of ovarian cancer by utilizing inter-related regulation of phospholipids, a unique property that allows the use of ratios between phospholipid species for quantitation. High-performance liquid chromatography mass spectrometry was used to measure phospholipid, lysophospholipid, and sphingophospholipid content in plasma from patients with benign ovarian masses, patients with ovarian cancer, and controls. We applied both absolute and relative phospholipid ratios for quantitation. Receiver operating characteristic analysis was performed to test the sensitivity and specificity. We found that utilization of ratios between phospholipid species greatly outperformed absolute quantitation in the identification of ovarian cancer. Of the phospholipids analyzed, species in phosphatidylcholine (PC), lysophosphatidylcholine (LPC), and sphingomyelin (SM) were found to have great biomarker potential. LPC(20:4)/LPC(18:0) carried the greatest capacity to differentiate cancer from control, SM(d18:1/24:1)/SM(d18:1/22:0) to differentiate benign from cancer, and PC(18:0/20:4)/PC(18:0/18:1) to differentiate benign from control. These results demonstrate the potential of plasma phospholipids as a novel marker of ovarian cancer by utilizing the unique characteristics of phospholipids to further enhance the diagnostic power.

Correction: Identification of grade and origin specific cell populations in serous epithelial ovarian cancer by single cell RNA-seq.

[This corrects the article DOI: 10.1371/journal.pone.0206785.].

Identification of grade and origin specific cell populations in serous epithelial ovarian cancer by single cell RNA-seq.

Here we investigated different cell populations within ovarian cancer using single-cell RNA seq: fourteen samples from nine patients with differing grades (high grade, low grade and benign) as well as different origin sites (primary and metastatic tumor site, ovarian in origin and fallopian in origin). We were able to identify sixteen distinct cell populations with specific cells correlated to high grade tumors, low grade tumors, benign and one population unique to a patient with a breast cancer relapse. Furthermore the proportion of these populations changes from primary to metastatic in a shift from mainly epithelial cells to leukocytes with few cancer epithelial cells in the metastases. Differential gene expression shows myeloid lineage cells are the primary cell group expressing soluble factors in primary samples while fibroblasts do so in metastatic samples. The leukocytes that were captured did not seem to be suppressed through known pro-tumor cytokines from any of the cell populations. Single cell RNA-seq is necessary to de-tangle cellular heterogeneity for better understanding of ovarian cancer progression.

Gene-level association analysis of systemic sclerosis: A comparison of African-Americans and White populations.

Gene-level analysis of ImmunoChip or genome-wide association studies (GWAS) data has not been previously reported for systemic sclerosis (SSc, scleroderma). The objective of this study was to analyze genetic susceptibility loci in SSc at the gene level and to determine if the detected associations were shared in African-American and White populations, using data from ImmunoChip and GWAS genotyping studies. The White sample included 1833 cases and 3466 controls (956 cases and 2741 controls from the US and 877 cases and 725 controls from Spain) and the African American sample, 291 cases and 260 controls. In both Whites and African Americans, we performed a gene-level analysis that integrates association statistics in a gene possibly harboring multiple SNPs with weak effect on disease risk, using Versatile Gene-based Association Study (VEGAS) software. The SNP-level analysis was performed using PLINK v.1.07. We identified 4 novel candidate genes (STAT1, FCGR2C, NIPSNAP3B, and SCT) significantly associated and 4 genes (SERBP1, PINX1, TMEM175 and EXOC2) suggestively associated with SSc in the gene level analysis in White patients. As an exploratory analysis we compared the results on Whites with those from African Americans. Of previously established susceptibility genes identified in Whites, only TNFAIP3 was significant at the nominal level (p = 6.13x10-3) in African Americans in the gene-level analysis of the ImmunoChip data. Among the top suggestive novel genes identified in Whites based on the ImmunoChip data, FCGR2C and PINX1 were only nominally significant in African Americans (p = 0.016 and p = 0.028, respectively), while among the top novel genes identified in the gene-level analysis in African Americans, UNC5C (p = 5.57x10-4) and CLEC16A (p = 0.0463) were also nominally significant in Whites. We also present the gene-level analysis of SSc clinical and autoantibody phenotypes among Whites. Our findings need to be validated by independent studies, particularly due to the limited sample size of African Americans.

Two microRNA signatures for malignancy and immune infiltration predict overall survival in advanced epithelial ovarian cancer.

MicroRNAs have been established as key regulators of tumor gene expression and as prime biomarker candidates for clinical phenotypes in epithelial ovarian cancer (EOC). We analyzed the coexpression and regulatory structure of microRNAs and their co-localized gene targets in primary tumor tissue of 20 patients with advanced EOC in order to construct a regulatory signature for clinical prognosis. We performed an integrative analysis to identify two prognostic microRNA/mRNA coexpression modules, each enriched for consistent biological functions. One module, enriched for malignancy-related functions, was found to be upregulated in malignant versus benign samples. The second module, enriched for immune-related functions, was strongly correlated with imputed intratumoral immune infiltrates of T cells, natural killer cells, cytotoxic lymphocytes, and macrophages. We validated the prognostic relevance of the immunological module microRNAs in the publicly available The Cancer Genome Atlas data set. These findings provide novel functional roles for microRNAs in the progression of advanced EOC and possible prognostic signatures for survival.

Immune-Array Analysis in Sporadic Inclusion Body Myositis Reveals HLA-DRB1 Amino Acid Heterogeneity Across the Myositis Spectrum.

OBJECTIVE: Inclusion body myositis (IBM) is characterized by a combination of inflammatory and degenerative changes affecting muscle. While the primary cause of IBM is unknown, genetic factors may influence disease susceptibility. To determine genetic factors contributing to the etiology of IBM, we conducted the largest genetic association study of the disease to date, investigating immune-related genes using the Immunochip. METHODS: A total of 252 Caucasian patients with IBM were recruited from 11 countries through the Myositis Genetics Consortium and compared with 1,008 ethnically matched controls. Classic HLA alleles and amino acids were imputed using SNP2HLA. RESULTS: The HLA region was confirmed as the most strongly associated region in IBM (P = 3.58 × 10-33 ). HLA imputation identified 3 independent associations (with HLA-DRB1*03:01, DRB1*01:01, and DRB1*13:01), although the strongest association was with amino acid positions 26 and 11 of the HLA-DRB1 molecule. No association with anti-cytosolic 5'-nucleotidase 1A-positive status was found independent of HLA-DRB1*03:01. There was no association of HLA genotypes with age at onset of IBM. Three non-HLA regions reached suggestive significance, including the chromosome 3 p21.31 region, an established risk locus for autoimmune disease, where a frameshift mutation in CCR5 is thought to be the causal variant. CONCLUSION: This is the largest, most comprehensive genetic association study to date in IBM. The data confirm that HLA is the most strongly associated region and identifies novel amino acid associations that may explain the risk in this locus. These amino acid associations differentiate IBM from polymyositis and dermatomyositis and may determine properties of the peptide-binding groove, allowing it to preferentially bind autoantigenic peptides. A novel suggestive association within the chromosome 3 p21.31 region suggests a role for CCR5.

Genome-Wide Association Study of Late-Onset Myasthenia Gravis: Confirmation of TNFRSF11A and Identification of ZBTB10 and Three Distinct HLA Associations.

To investigate the genetics of late-onset myasthenia gravis (LOMG), we conducted a genome-wide association study imputation of>6 million single nucleotide polymorphisms (SNPs) in 532 LOMG cases (anti-acetylcholine receptor [AChR] antibody positive; onset age≥50 years) and 2,128 controls matched for sex and population substructure. The data confirm reported TNFRSF11A associations (rs4574025, P = 3.9 × 10-7, odds ratio [OR] 1.42) and identify a novel candidate gene, ZBTB10, achieving genome-wide significance (rs6998967, P = 8.9 × 10-10, OR 0.53). Several other SNPs showed suggestive significance including rs2476601 (P = 6.5 × 10-6, OR 1.62) encoding the PTPN22 R620W variant noted in early-onset myasthenia gravis (EOMG) and other autoimmune diseases. In contrast, EOMG-associated SNPs in TNIP1 showed no association in LOMG, nor did other loci suggested for EOMG. Many SNPs within the major histocompatibility complex (MHC) region showed strong associations in LOMG, but with smaller effect sizes than in EOMG (highest OR ~2 versus ~6 in EOMG). Moreover, the strongest associations were in opposite directions from EOMG, including an OR of 0.54 for DQA1*05:01 in LOMG (P = 5.9 × 10-12) versus 2.82 in EOMG (P = 3.86 × 10-45). Association and conditioning studies for the MHC region showed three distinct and largely independent association peaks for LOMG corresponding to (a) MHC class II (highest attenuation when conditioning on DQA1), (b) HLA-A and (c) MHC class III SNPs. Conditioning studies of human leukocyte antigen (HLA) amino acid residues also suggest potential functional correlates. Together, these findings emphasize the value of subgrouping myasthenia gravis patients for clinical and basic investigations and imply distinct predisposing mechanisms in LOMG.

Autoimmune disease-associated haplotypes of BLK exhibit lowered thresholds for B cell activation and expansion of Ig class-switched B cells.

OBJECTIVE: B lymphoid kinase (BLK) is associated with rheumatoid arthritis (RA) and several other B cell-associated autoimmune disorders. BLK risk variants are consistently associated with reduced BLK expression, but the mechanisms by which reduced expression alters human B cell function to confer autoimmune disease susceptibility are unknown. This study was undertaken to characterize the BLK risk haplotype and to determine associated B cell functional phenotypes involved in autoimmunity. METHODS: The BLK risk haplotype association with RA (determined using whole-genome sequencing data) was confirmed in 2,526 RA cases and 2,134 controls. Peripheral blood mononuclear cells (PBMCs) from RA patients, healthy adults, and umbilical cord blood were used to study B cell functional phenotypes associated with the BLK risk genotype. Association of the BLK haplotype with B cell phenotypes was analyzed using cell culture and flow cytometry. RESULTS: Two insertion/deletions were found on the RA risk haplotype in BLK, and the reduction in BLK expression associated with the risk haplotype was confirmed in primary B lymphocytes. Carriers of the RA-associated haplotype had evidence of lower basal B cell receptor (BCR) signaling activity, yet their B cells were hyperactivatable, with enhanced up-regulation of CD86 after BCR crosslinking and greater T cell stimulatory capacity. The number of isotype-switched memory B cells was also significantly increased in subjects carrying the risk haplotype. CONCLUSION: A major mechanism underlying the BLK association with autoimmune disease involves lowered thresholds for BCR signaling, enhanced B cell-T cell interactions, and altered patterns of isotype switching.

Bone morphogenetic protein-focused strategies to induce cytotoxicity in lung cancer cells.

BACKGROUND: High bone morphogenetic protein (BMP)-2 expression in lung carcinoma correlates with poor patient prognosis. The present study explored strategies to repress BMP signaling. MATERIALS AND METHODS: The cytotoxicity of BMP2-knockdown, dorsomorphin derivatives, and microRNAs was tested in transformed and non-transformed lung cells. Microarray analyses of 1,145 microRNAs in A549 lung adenocarcinoma cells and two other transformed lung cell types relative to BEAS-2B bronchial epithelial cells were performed. RESULTS: Reduced BMP2 synthesis inhibited A549 cell growth. The dorsomorphin derivative LDN-193189, but not DMH1 or DMH4, was strongly cytotoxic towards A549 cells, but not towards BEAS-2B cells. Microarray analysis revealed that 106 miRNAs were down-regulated and 69 miRNAs were up-regulated in the three transformed lines. Three down-regulated miRNAs, hsa-mir-34b, hsa-mir-34c-3p, and hsa-miR-486-3p, repressed a BMP2 reporter gene and were cytotoxic in A549 cells, but not towards BEAS-2B cells. CONCLUSION: The observed cytotoxicity suggests that reducing BMP signaling is a useful line of attack for therapy of lung cancer.

Immunochip analysis identifies multiple susceptibility loci for systemic sclerosis.

In this study, 1,833 systemic sclerosis (SSc) cases and 3,466 controls were genotyped with the Immunochip array. Classical alleles, amino acid residues, and SNPs across the human leukocyte antigen (HLA) region were imputed and tested. These analyses resulted in a model composed of six polymorphic amino acid positions and seven SNPs that explained the observed significant associations in the region. In addition, a replication step comprising 4,017 SSc cases and 5,935 controls was carried out for several selected non-HLA variants, reaching a total of 5,850 cases and 9,401 controls of European ancestry. Following this strategy, we identified and validated three SSc risk loci, including DNASE1L3 at 3p14, the SCHIP1-IL12A locus at 3q25, and ATG5 at 6q21, as well as a suggested association of the TREH-DDX6 locus at 11q23. The associations of several previously reported SSc risk loci were validated and further refined, and the observed peak of association in PXK was related to DNASE1L3. Our study has increased the number of known genetic associations with SSc, provided further insight into the pleiotropic effects of shared autoimmune risk factors, and highlighted the power of dense mapping for detecting previously overlooked susceptibility loci.

Genome-wide association study implicates NDST3 in schizophrenia and bipolar disorder.

Schizophrenia and bipolar disorder are major psychiatric disorders with high heritability and overlapping genetic variance. Here we perform a genome-wide association study in an ethnically homogeneous cohort of 904 schizophrenia cases and 1,640 controls drawn from the Ashkenazi Jewish population. We identify a novel genome-wide significant risk locus at chromosome 4q26, demonstrating the potential advantages of this founder population for gene discovery. The top single-nucleotide polymorphism (SNP; rs11098403) demonstrates consistent effects across 11 replication and extension cohorts, totalling 23, 191 samples across multiple ethnicities, regardless of diagnosis (schizophrenia or bipolar disorder), resulting in Pmeta=9.49 × 10(-12) (odds ratio (OR)=1.13, 95% confidence interval (CI): 1.08-1.17) across both disorders and Pmeta=2.67 × 10(-8) (OR=1.15, 95% CI: 1.08-1.21) for schizophrenia alone. In addition, this intergenic SNP significantly predicts postmortem cerebellar gene expression of NDST3, which encodes an enzyme critical to heparan sulphate metabolism. Heparan sulphate binding is critical to neurite outgrowth, axon formation and synaptic processes thought to be aberrant in these disorders.

Do biologic markers predict cardiovascular end points in diabetic end-stage renal disease? A prospective longitudinal study.

BACKGROUND: Diabetic patients on hemodialysis are at high risk of death from cardiovascular disease, and research has suggested that various biologic markers of inflammation, oxidative stress and hemostasis may give added value to clinical information for predicting cardiovascular event (CVE)-free survival. This information could be particularly important in evaluating this population for renal transplant, given the scarcity of organs. We hypothesized that in diabetic patients undergoing renal replacement therapy (RRT) these biologic markers would prove useful in predicting event-free follow-up in a prospective study. METHODS: One hundred and fifty diabetic (76 type 1, 74 type 2) and 27 non-diabetic stable RRT patients were followed for 0.04-13.69 years for CVE (myocardial infarction, coronary arterial intervention, peripheral arterial bypass or amputation, cerebrovascular accident or carotid artery intervention), cardiac and all-cause mortality. Measured biologic markers of inflammation included the following: Il-6, C reactive protein, fibrinogen; of hemostasis: fibrinogen, plasminogen activator inhibitor (PAI), fibrinolytic activity, von Willebrand factor VII (vWF), platelet-selectin, viscosity and of oxidative stress: advanced glycated end products and antibody to oxidized low-density lipoprotein. For each, upper versus lower tertiles were compared for duration of event-free follow-up. RESULTS: Cardiovascular events prior to study entry occurred in 51.3% of DM1, 54.0% of DM2 and 25.9% of DM0 patients. Subsequent cardiovascular events were noted in 31.6% of DM1, 45.9% of DM2 and 11.1% of DM0 patients. All mean levels of biologic markers at baseline were abnormal (P < 0.05). CONCLUSIONS: In this RRT population, all biologic marker levels except PAI did not improve clinical prediction of events.

Genome-wide association study reveals novel genetic determinants of DNA repair capacity in lung cancer.

Suboptimal cellular DNA repair capacity (DRC) has been shown to be associated with enhanced cancer risk, but genetic variants affecting the DRC phenotype have not been comprehensively investigated. In this study, with the available DRC phenotype data, we analyzed correlations between the DRC phenotype and genotypes detected by the Illumina 317K platform in 1,774 individuals of European ancestry from a Texas lung cancer genome-wide association study. The discovery phase was followed by a replication in an independent set of 1,374 cases and controls of European ancestry. We applied a generalized linear model with single nucleotide polymorphisms as predictors and DRC (a continuous variable) as the outcome. Covariates of age, sex, pack-years of smoking, DRC assay-related variables, and case-control status of the study participants were adjusted in the model. We validated that reduced DRC was associated with an increased risk of lung cancer in both independent datasets. Several suggestive loci that contributed to the DRC phenotype were defined in ERCC2/XPD, PHACTR2, and DUSP1. In summary, we determined that DRC is an independent risk factor for lung cancer, and we defined several genetic loci contributing to DRC phenotype.

Genome-wide association analysis of anti-TNF drug response in patients with rheumatoid arthritis.

BACKGROUND: Treatment strategies blocking tumour necrosis factor (anti-TNF) have proven very successful in patients with rheumatoid arthritis (RA). However, a significant subset of patients does not respond for unknown reasons. Currently, there are no means of identifying these patients before treatment. This study was aimed at identifying genetic factors predicting anti-TNF treatment outcome in patients with RA using a genome-wide association approach. METHODS: We conducted a multistage, genome-wide association study with a primary analysis of 2 557 253 single-nucleotide polymorphisms (SNPs) in 882 patients with RA receiving anti-TNF therapy included through the Dutch Rheumatoid Arthritis Monitoring (DREAM) registry and the database of Apotheekzorg. Linear regression analysis of changes in the Disease Activity Score in 28 joints after 14 weeks of treatment was performed using an additive model. Markers with p<10(-3) were selected for replication in 1821 patients from three independent cohorts. Pathway analysis including all SNPs with p<10(-3) was performed using Ingenuity. RESULTS: 772 markers showed evidence of association with treatment outcome in the initial stage. Eight genetic loci showed improved p value in the overall meta-analysis compared with the first stage, three of which (rs1568885, rs1813443 and rs4411591) showed directional consistency over all four cohorts studied. We were unable to replicate markers previously reported to be associated with anti-TNF outcome. Network analysis indicated strong involvement of biological processes underlying inflammatory response and cell morphology. CONCLUSIONS: Using a multistage strategy, we have identified eight genetic loci associated with response to anti-TNF treatment. Further studies are required to validate these findings in additional patient collections.