Independent Set Of Patients Research Articles

Lipidomics Reveals Cerebrospinal-Fluid Signatures of ALS

Amyotrophic lateral sclerosis (ALS), the commonest adult-onset motor neuron disorder, is characterized by a survival span of only 2–5 years after onset. Relevant biomarkers or specific metabolic signatures would provide powerful tools for the management of ALS. The main objective of this study was to investigate the cerebrospinal fluid (CSF) lipidomic signature of ALS patients by mass spectrometry to evaluate the diagnostic and predictive values of the profile. We showed that ALS patients (n = 40) displayed a highly significant specific CSF lipidomic signature compared to controls (n = 45). Phosphatidylcholine PC(36:4), higher in ALS patients (p = 0.0003) was the most discriminant molecule, and ceramides and glucosylceramides were also highly relevant. Analysis of targeted lipids in the brain cortex of ALS model mice confirmed the role of some discriminant lipids such as PC. We also obtained good models for predicting the variation of the ALSFRS-r score from the lipidome baseline, with an accuracy of 71% in an independent set of patients. Significant predictions of clinical evolution were found to be correlated to sphingomyelins and triglycerides with long-chain fatty acids. Our study, which shows extensive lipid remodelling in the CSF of ALS patients, provides a new metabolic signature of the disease and its evolution with good predictive performance.

Prediction of recurrence in early stage non-small cell lung cancer using computer extracted nuclear features from digital H&E images

Identification of patients with early stage non-small cell lung cancer (NSCLC) with high risk of recurrence could help identify patients who would receive additional benefit from adjuvant therapy. In this work, we present a computational histomorphometric image classifier using nuclear orientation, texture, shape, and tumor architecture to predict disease recurrence in early stage NSCLC from digitized H&E tissue microarray (TMA) slides. Using a retrospective cohort of early stage NSCLC patients (Cohort #1, n = 70), we constructed a supervised classification model involving the most predictive features associated with disease recurrence. This model was then validated on two independent sets of early stage NSCLC patients, Cohort #2 (n = 119) and Cohort #3 (n = 116). The model yielded an accuracy of 81% for prediction of recurrence in the training Cohort #1, 82% and 75% in the validation Cohorts #2 and #3 respectively. A multivariable Cox proportional hazard model of Cohort #2, incorporating gender and traditional prognostic variables such as nodal status and stage indicated that the computer extracted histomorphometric score was an independent prognostic factor (hazard ratio = 20.81, 95% CI: 6.42–67.52, P < 0.001).

Plasma Nervonic Acid Is a Potential Biomarker for Major Depressive Disorder: A Pilot Study.

BackgroundDiagnostic biomarkers of major depressive disorder, bipolar disorder, and schizophrenia are urgently needed, because none are currently available.MethodsWe performed a comprehensive metabolome analysis of plasma samples from drug-free patients with major depressive disorder (n=9), bipolar disorder (n=6), schizophrenia (n=17), and matched healthy controls (n=19) (cohort 1) using liquid chromatography time-of-flight mass spectrometry. A significant effect of diagnosis was found for 2 metabolites: nervonic acid and cortisone, with nervonic acid being the most significantly altered. The reproducibility of the results and effects of psychotropic medication on nervonic acid were verified in cohort 2, an independent sample set of medicated patients [major depressive disorder (n=45), bipolar disorder (n=71), schizophrenia (n=115)], and controls (n=90) using gas chromatography time-of-flight mass spectrometry.ResultsThe increased levels of nervonic acid in patients with major depressive disorder compared with controls and patients with bipolar disorder in cohort 1 were replicated in the independent sample set (cohort 2). In cohort 2, plasma nervonic acid levels were also increased in the patients with major depressive disorder compared with the patients with schizophrenia. In cohort 2, nervonic acid levels were increased in the depressive state in patients with major depressive disorder compared with the levels in the remission state in patients with major depressive disorder and the depressive state in patients with bipolar disorder.ConclusionThese results suggested that plasma nervonic acid is a good candidate biomarker for the depressive state of major depressive disorder.

Exome array analysis identifies ETFB as a novel susceptibility gene for anthracycline-induced cardiotoxicity in cancer patients.

Anthracyclines are widely used chemotherapeutic drugs that can cause progressive and irreversible cardiac damage and fatal heart failure. Several genetic variants associated with anthracycline-induced cardiotoxicity (AIC) have been identified, but they explain only a small proportion of the interindividual differences in AIC susceptibility. In this study, we evaluated the association of low-frequency variants with risk of chronic AIC using the Illumina HumanExome BeadChip array in a discovery cohort of 61 anthracycline-treated breast cancer patients with replication in a second independent cohort of 83 anthracycline-treated pediatric cancer patients, using gene-based tests (SKAT-O). The most significant associated gene in the discovery cohort was ETFB (electron transfer flavoprotein beta subunit) involved in mitochondrial β-oxidation and ATP production (P=4.16×10-4) and this association was replicated in an independent set of anthracycline-treated cancer patients (P=2.81×10-3). Within ETFB, we found that the missense variant rs79338777 (p.Pro52Leu; c.155C>T) made the greatest contribution to the observed gene association and it was associated with increased risk of chronic AIC in the two cohorts separately and when combined (OR 9.00, P=1.95×10-4, 95% CI 2.83-28.6). We identified and replicated a novel gene, ETFB, strongly associated with chronic AIC independently of age at tumor onset and related to anthracycline-mediated mitochondrial dysfunction. Although experimental verification and further studies in larger patient cohorts are required to confirm our finding, we demonstrated that exome array data analysis represents a valuable strategy to identify novel genes contributing to the susceptibility to chronic AIC.

A classifier integrating plasma biomarkers and radiological characteristics for distinguishing malignant from benign pulmonary nodules.

Lung cancer is primarily caused by cigarette smoking and the leading cancer killer in the USA and across the world. Early detection of lung cancer by low-dose CT (LDCT) can reduce the mortality. However, LDCT dramatically increases the number of indeterminate pulmonary nodules (PNs), leading to overdiagnosis. Having a definitive preoperative diagnosis of malignant PNs is clinically important. Using microarray and droplet digital PCR to directly profile plasma miRNA expressions of 135 patients with PNs, we identified 11 plasma miRNAs that displayed a significant difference between patients with malignant versus benign PNs. Using multivariate logistic regression analysis of the molecular results and clinical/radiological characteristics, we developed an integrated classifier comprising two miRNA biomarkers and one radiological characteristic for distinguishing malignant from benign PNs. The classifier had 89.9% sensitivity and 90.9% specificity, being significantly higher compared with the biomarkers or clinical/radiological characteristics alone (all p < 0.05). The classifier was validated in two independent sets of patients. We have for the first time shown that the integration of plasma biomarkers and radiological characteristics could more accurately identify lung cancer among indeterminate PNs. Future use of the classifier could spare individuals with benign growths from the harmful diagnostic procedures, while allowing effective treatments to be immediately initiated for lung cancer, thereby reduces the mortality and cost. Nevertheless, further prospective validation of this classifier is warranted.

C-terminal fragments of the amyloid precursor protein in cerebrospinal fluid as potential biomarkers for Alzheimer disease

This study assesses whether C-terminal fragments (CTF) of the amyloid precursor protein (APP) are present in cerebrospinal fluid (CSF) and their potential as biomarkers for Alzheimer’s disease (AD). Immunoprecipitation and simultaneous assay by Western blotting using multiplex fluorescence imaging with specific antibodies against particular domains served to characterize CTFs of APP in human CSF. We demonstrate that APP-CTFs are detectable in human CSF, being the most abundant a 25-kDa fragment, probably resulting from proteolytic processing by η-secretase. The level of the 25-kDa APP-CTF was evaluated in three independent CSF sample sets of patients and controls. The CSF level of this 25-kDa CTF is higher in subjects with autosomal dominant AD linked to PSEN1 mutations, in demented Down syndrome individuals and in sporadic AD subjects compared to age-matched controls. Our data suggest that APP-CTF could be a potential diagnostic biomarker for AD.

Candidate susceptibility variants for esophageal squamous cell carcinoma.

Esophageal cancer is common worldwide, and often fatal. The major histological subtype is esophageal squamous cell carcinoma (ESCC). ESCC shows familial aggregation and high heritability. Mutations in RHBDF2 cause tylosis, a very rare disorder characterized by high life-time risk of ESCC, but no other well-established predisposition genes have been identified. To identify candidate susceptibility variants for ESCC we utilized the Population Information System and the Finnish cancer registry to find study materials by clustering ESCC patients by family name at birth and municipality at birth. We collected archival tissue material and exome sequenced a total of 30 ESCC cases. We prioritized shared, deleterious and rare variants that were significantly enriched in our sample set compared to Finnish and population subset specific controls. Six variants passed filtering, the most frequent being a nonsense mutation in DNAH9 (p.Tyr1573Ter) found in four unrelated patients. DNAH9 has been reported to be frequently lost in ESCC tumors. In this study, one patient's tumor showed loss of the wild type allele of DNAH9 suggesting a tumor suppressive function. A missense variant in GKAP1 was shared by three patients, and missense variants in BAG1, NFX1, FUK, and DDOST by two each. EP300 which has previously been implicated in the genesis of ESCC had a missense variant segregating in three affected individuals in a single family. If validated in independent patient sets, these variants could serve as a tool towards prevention and early diagnosis of ESCC.

C-reactive protein and N-terminal prohormone brain natriuretic peptide as biomarkers in acute exacerbations of COPD leading to hospitalizations.

There are currently no accepted and validated blood tests available for diagnosing acute exacerbations of chronic obstructive pulmonary disease (AECOPD). In this study, we sought to determine the discriminatory power of blood C-reactive protein (CRP) and N-terminal prohormone brain natriuretic peptide (NT-proBNP) in the diagnosis of AECOPD requiring hospitalizations. The study cohort consisted of 468 patients recruited in the COPD Rapid Transition Program who were hospitalized with a primary diagnosis of AECOPD, and 110 stable COPD patients who served as controls. Logistic regression was used to build a classification model to separate AECOPD from convalescent or stable COPD patients. Performance was assessed using an independent validation set of patients who were not included in the discovery set. Serum CRP and whole blood NT-proBNP concentrations were highest at the time of hospitalization and progressively decreased over time. Of the 3 classification models, the one with both CRP and NT-proBNP had the highest AUC in discriminating AECOPD (cross-validated AUC of 0.80). These data were replicated in a validation cohort with an AUC of 0.88. A combination of CRP and NT-proBNP can reasonably discriminate AECOPD requiring hospitalization versus clinical stability and can be used to rapidly diagnose patients requiring hospitalization for AECOPD.

DNA methylation at modifier genes of lung disease severity is altered in cystic fibrosis

BackgroundLung disease progression is variable among cystic fibrosis (CF) patients and depends on DNA mutations in the CFTR gene, polymorphic variations in disease modifier genes, and environmental exposure. The contribution of genetic factors has been extensively investigated, whereas the mechanism whereby environmental factors modulate the lung disease is unknown. In this project, we hypothesized that (i) reiterative stress alters the epigenome in CF-affected tissues and (ii) DNA methylation variations at disease modifier genes modulate the lung function in CF patients.ResultsWe profiled DNA methylation at CFTR, the disease-causing gene, and at 13 lung modifier genes in nasal epithelial cells and whole blood samples from 48 CF patients and 24 healthy controls. CF patients homozygous for the p.Phe508del mutation and ≥18-year-old were stratified according to the lung disease severity. DNA methylation was measured by bisulfite and next-generation sequencing. The DNA methylation profile allowed us to correctly classify 75% of the subjects, thus providing a CF-specific molecular signature. Moreover, in CF patients, DNA methylation at specific genes was highly correlated in the same tissue sample. We suggest that gene methylation in CF cells may be co-regulated by disease-specific trans-factors. Three genes were differentially methylated in CF patients compared with controls and/or in groups of pulmonary severity: HMOX1 and GSTM3 in nasal epithelial samples; HMOX1 and EDNRA in blood samples. The association between pulmonary severity and DNA methylation at EDNRA was confirmed in blood samples from an independent set of CF patients. Also, lower DNA methylation levels at GSTM3 were associated with the GSTM3*B allele, a polymorphic 3-bp deletion that has a protective effect in cystic fibrosis.ConclusionsDNA methylation levels are altered in nasal epithelial and blood cell samples from CF patients. Analysis of CFTR and 13 lung disease modifier genes shows DNA methylation changes of small magnitude: some of them are a consequence of the disease; other changes may result in small expression variations that collectively modulate the lung disease severity.

Improving medication safety: Development and impact of a multivariate model-based strategy to target high-risk patients.

BackgroundPreventive strategies to reduce clinically significant medication errors (MEs), such as medication review, are often limited by human resources. Identifying high-risk patients to allow for appropriate resource allocation is of the utmost importance. To this end, we developed a predictive model to identify high-risk patients and assessed its impact on clinical decision-making.MethodsFrom March 1st to April 31st 2014, we conducted a prospective cohort study on adult inpatients of a 1,644-bed University Hospital Centre. After a clinical evaluation of identified MEs, we fitted and internally validated a multivariate logistic model predicting their occurrence. Through 5,000 simulated randomized controlled trials, we compared two clinical decision pathways for intervention: one supported by our model and one based on the criterion of age.ResultsAmong 1,408 patients, 365 (25.9%) experienced at least one clinically significant ME. Eleven variables were identified using multivariable logistic regression and used to build a predictive model which demonstrated fair performance (c-statistic: 0.72). Major predictors were age and number of prescribed drugs. When compared with a decision to treat based on the criterion of age, our model enhanced the interception of potential adverse drug events by 17.5%, with a number needed to treat of 6 patients.ConclusionWe developed and tested a model predicting the occurrence of clinically significant MEs. Preliminary results suggest that its implementation into clinical practice could be used to focus interventions on high-risk patients. This must be confirmed on an independent set of patients and evaluated through a real clinical impact study.

Heterogeneous patterns of DNA methylation-based field effects in histologically normal prostate tissue from cancer patients

Prostate cancer (PC) diagnosis is based on histological evaluation of prostate needle biopsies, which have high false negative rates. Here, we investigated if cancer-associated epigenetic field effects in histologically normal prostate tissue may be used to increase sensitivity for PC. We focused on nine genes (AOX1, CCDC181 (C1orf114), GABRE, GAS6, HAPLN3, KLF8, MOB3B, SLC18A2, and GSTP1) known to be hypermethylated in PC. Using quantitative methylation-specific PCR, we analysed 66 malignant and 134 non-malignant tissue samples from 107 patients, who underwent ultrasound-guided prostate biopsy (67 patients had at least one cancer-positive biopsy, 40 had exclusively cancer-negative biopsies). Hypermethylation was detectable for all genes in malignant needle biopsy samples (AUC: 0.80 to 0.98), confirming previous findings in prostatectomy specimens. Furthermore, we identified a four-gene methylation signature (AOX1xGSTP1xHAPLN3xSLC18A2) that distinguished histologically non-malignant biopsies from patients with vs. without PC in other biopsies (AUC = 0.65; sensitivity = 30.8%; specificity = 100%). This signature was validated in an independent patient set (59 PC, 36 adjacent non-malignant, and 9 normal prostate tissue samples) analysed on Illumina 450 K methylation arrays (AUC = 0.70; sensitivity = 40.6%; specificity = 100%). Our results suggest that a novel four-gene signature may be used to increase sensitivity for PC diagnosis through detection of epigenetic field effects in histologically non-malignant prostate tissue samples.

Gene Expression Profiling Reveals Novel Candidate Markers of Ovarian Carcinoma Intraperitoneal Metastasis.

Epithelial ovarian cancer (EOC) has the highest mortality among gynecological carcinomas. The lack of specific markers for prognostic determination of EOC progression hinders the search for novel effective therapies.The aim of the present study was (i) to explore differences in expressions of ATP-binding cassette (ABC) and solute carrier (SLC) transporter genes, genes associated with drug metabolism and cell cycle regulation between control ovarian tissues (n = 14), primary EOCs (n = 44) and intraperitoneal metastases (n = 29); (ii) to investigate associations of gene expression levels with prognosis of patients with intraperitoneal metastases.In all tissue samples, transcript levels of the above target genes were assessed using quantitative real-time PCR. Gene expression levels were compared between particular tissue types and evaluated with regard to progression-free survival (PFS) and drug-resistance status of patients with metastases.Gene expression of ABCA7 significantly increased and that of ESR2 decreased in the order control ovarian tissues - primary EOCs - metastases. High expressions of ABCA2/8/9/10, ABCB1, ABCC9, ABCG2, ATP7A, SLC16A14, and SOD3 genes were significantly associated with longer progression-free survival of patients. In intraperitoneal metastases, expression of all of these genes highly correlated and indicated prognostic profile. Transporters from the ABCA family, ABCG2, and ESR2 are involved mainly in lipid metabolism, membrane transport, and cell proliferation. These processes are thus probably the most important for EOC progression.Based on these results, we have proposed novel markers of ovarian carcinoma progression and metastatic spread which might be potentially useful as therapeutic targets. Their significance should be further explored on a larger independent set of patients.

Replication of New Genomic Classification System in Acute Myeloid Leukemia with Normal Karyotype

IntroductionAcute myeloid leukemia (AML) is a genetically heterogeneous disease. A recent study (NEJM, 2016) classified 1540 patients into 14 subgroups using mutation information from targeted next generation sequencing data as well as cytogenetic information [1]. The classification criteria of 7 of these subgroups rely solely on mutation information. NK-AML is characterized by its lack of cytogenetic abnormalities. In this study, we attempted to replicate the prognostic stratification in an independent set of NK-AML patients using the NEJM study's genomic classification criteria.Patients and MethodsThis study included a total of 393 patients who met the following eligibility criteria: 1) age ≥ 15 years; 2) a diagnosis of NK-AML confirmed by conventional cytogenetic analysis; 3) treatment with induction chemotherapy using a standard protocol (a 3-day course of anthracycline with a 7-day course of cytosine arabinoside). The median follow-up duration was 55.1 months (range, 0.7-182.9). Analysis of genetic mutations were performed using targeted sequencing by Illumina Hiseq 2000 (Agilent custom probe set targeting entire exon regions of a myeloid panel consisting of 94 genes).ResultsWe identified driver mutations across 28 genes or genomic regions, with 2 or more driver mutations identified in 15/393 patients (3.8%). Based on the genomic classification criteria, the patients were classified as follows: 136 patients (34.6%) with NPM1 mutations, 42 patients (10.7%) with mutated chromatin modifiers and/or RNA-splicing genes, 6 patients (1.5%) with TP53 mutations, 40 patients (10.2%) with biallelic CEBPA mutations, 8 patients (2.0%) with IDH2-R172 mutations and no other class-defining lesions, 108 patients (27.5%) with driver mutations but no detected class-defining lesions, 38 patients (9.7%) with no detected driver mutations, and 15 patients (3.8%) who met the criteria of more than one genomic subgroup.Of the 393 patients, 325 patients (82.7%) achieved complete remission (CR). CR rates vary depending on the genomic subgroup (75.9%-97.4%). The CR rate for each subgroup was as follows: •86.8% (118/136) of patients with NPM1 mutations•61.9% (26/42) of patients with mutated chromatin and/or RNA-splicing genes•83.3% (5/6) of patients with TP53 mutations•97.5% (38/40) of patients with biallelic CEBPA mutations•87.5% (7/8) of patients with IDH2-R172 mutations and no other class-defining lesions•75.9% (82/108) of patients with driver mutations but no detected class-defining lesions•97.3% (37/38) of patients with no detected driver mutations•80.0% (12/15) of patients meeting criteria of more than one subgroup5-year OS and 5-year relapse incidence (RI) for each subgroup was as follows: •49.3% (95% CI, 40.1-58.5) and 39.8% (95% CI, 30.1-49.2) of patients with NPM1 mutations•11.6% (95% CI, 1.4-21.8) and 71.4% (95% CI, 45.7-86.5) of patients with mutated chromatin and/or RNA-splicing genes•50.0% (95% CI, 10.0-90.0) and 20.0% (95% CI, 0.4-61.2) of patients with TP53 mutations•68.3% (95% CI, 53.4-83.2) and 19.7% (95% CI, 8.5-34.4) of patients with biallelic CEBPA mutations•56.3% (95% CI, 17.3-95.3) and 21.4% (95% CI, 0.3-67.3) of patients with IDH2-R172 mutations and no other class-defining lesions•26.6% (95% CI, 17.4-35.8) and 53.2% (95% CI, 40.7-64.3) of patients with driver mutations but no detected class-defining lesions•29.1% (95% CI, 14.2-44.0) and 43.8% (95% CI, 27.1-59.3) of patients with no detected driver mutations•40.0% (95% CI, 15.3-64.7) and 33.3% (95% CI, 9.2-60.3) of patients that meet the criteria of more than one subgroup.The CR rates of the subgroup with mutated chromatin and/or RNA-splicing genes was significantly lower than the rest of the cohort (61.9% vs. 85.2%, p=0.00016). The 5-year OS and 5-year RI of the subgroup were also poorer than the others [61.9% vs. 85.2% in OS (p=0.00016), 71.4% vs. 40.1% in RI (p < 0.0001)].ConclusionOur NK-AML cohort showed similar survival patterns to the cohort in Papaemmanuil et al (NEJM 2016). The subgroup in AML with mutated chromatin and/or RNA-Splicing genes had the poorest prognosis with respect to CR rate and overall survival. This analysis replicates the result of recently published genomic classification and supports its use for categorizing NK-AML patients.Reference[1] Genomic Classification and Prognosis in Acute Myeloid Leukemia. Papaemmanuil E et al. N Engl J Med, 2016 vol. 374 (23) pp. 2209-2221. [Display omitted] DisclosuresJang:Kyowa Hakko Kirin Co., Ltd.: Research Funding.

Genome-wide profiling identifies associations between lupus nephritis and differential methylation of genes regulating tissue hypoxia and type 1 interferon responses

ObjectivePrevious studies have shown that differential DNA methylation is associated with SLE susceptibility. How DNA methylation affects the clinical heterogeneity of SLE has not been fully defined. We conducted this...

Search for plasma biomarkers in drug-free patients with bipolar disorder and schizophrenia using metabolome analysis.

There is an urgent need for diagnostic biomarkers of bipolar disorder (BD) and schizophrenia (SZ); however, confounding effects of medication hamper biomarker discovery. In this study, we conducted metabolome analyses to identify novel plasma biomarkers in drug-free patients with BD and SZ. We comprehensively analyzed plasma metabolites using capillary electrophoresis time-of-flight mass spectrometry in patients with SZ (n = 17), BD (n = 6), and major depressive disorder (n = 9) who had not received psychotropics for at least 2 weeks, and in matched healthy controls (n = 19). The results were compared with previous reports, or verified in an independent sample set using an alternative analytical approach. Lower creatine level and higher 2-hydroxybutyric acid level were observed in SZ than in controls (uncorrected P = 0.016 and 0.043, respectively), whereas they were unaltered in a previously reported dataset. Citrulline was nominally significantly decreased in BD compared to controls (uncorrected P = 0.043); however, this finding was not replicated in an independent sample set of medicated patients with BD. N-methyl-norsalsolinol, a metabolite of dopamine, was suggested as a candidate biomarker of BD; however, it was not detected by the other analytical method. Levels of betaine, a previously reported candidate biomarker of schizophrenia, were unchanged in the current dataset. Our preliminary findings suggest that the effect of confounding factors, such as duration of illness and medication, should be carefully controlled when searching for plasma biomarkers. Further studies are required to establish robust biomarkers for these disorders.

Coexistence of obesity and asthma determines a distinct respiratory metabolic phenotype

Epidemiologic and clinical evidence supports the existence of an obesity-related asthma phenotype. No distinct pathophysiologic elements or specific biomarkers have been identified thus far, but increased oxidative stress has been reported. We aimed at verifying whether metabolomics of exhaled breath condensate from obese asthmatic (OA) patients, lean asthmatic (LA) patients, and obese nonasthmatic (ONA) subjects could recognize specific and statistically validated biomarkers for a separate "asthma-obesity" respiratory metabolic phenotype, here defined as "metabotype." Twenty-five OA patients, 30 ONA subjects, and 30 mild-to-moderate LA age-matched patients participated in a cross-sectional study. Nuclear magnetic resonance (NMR) profiles were analyzed by using partial least-squares discriminant analysis, and the results were validated with an independent patient set. From NMR profiles, we obtained strong regression models that distinguished OA patients from ONA subjects (quality parameters: goodness-of-fit parameter [R2]=0.81 and goodness-of-prediction parameter [Q2]=0.79), as well as OA patients from LA patients (R2=0.91 and Q2=0.89). The all-classes comparison (R2=0.86 and Q2=0.83) indicated that OA patients possess a respiratory metabolic profile fully divergent from those obtained in the other patient groups. We also identified specific biomarkers for between-class separation, which are independent from clinical bias. They are involved in the methane, pyruvate, and glyoxylate and dicarboxylate metabolic pathways. NMR-based metabolomics indicates that OA patients are characterized by a respiratory metabolic fingerprint fully different from that of patients independently affected by asthma or obesity. Such a phenotypic difference strongly suggests unique pathophysiologic pathways involved in the pathogenesis of asthma in adult obese subjects. Furthermore, the OA metabotype could define a strategy for patient stratification based on unbiased biomarkers, with important diagnostic and therapeutic implications.

The pre-synaptic vesicle protein synaptotagmin is a novel biomarker for Alzheimer's disease.

BackgroundSynaptic degeneration is a central pathogenic event in Alzheimer’s disease that occurs early during the course of disease and correlates with cognitive symptoms. The pre-synaptic vesicle protein synaptotagmin-1 appears to be essential for the maintenance of an intact synaptic transmission and cognitive function. Synaptotagmin-1 in cerebrospinal fluid is a candidate Alzheimer biomarker for synaptic dysfunction that also may correlate with cognitive decline.MethodsIn this study, a novel mass spectrometry-based assay for measurement of cerebrospinal fluid synaptotagmin-1 was developed, and was evaluated in two independent sample sets of patients and controls. Sample set I included cerebrospinal fluid samples from patients with dementia due to Alzheimer’s disease (N = 17, age 52–86 years), patients with mild cognitive impairment due to Alzheimer’s disease (N = 5, age 62–88 years), and controls (N = 17, age 41–82 years). Sample set II included cerebrospinal fluid samples from patients with dementia due to Alzheimer’s disease (N = 24, age 52–84 years), patients with mild cognitive impairment due to Alzheimer’s disease (N = 18, age 58–83 years), and controls (N = 36, age 43–80 years).ResultsThe reproducibility of the novel method showed coefficients of variation of the measured synaptotagmin-1 peptide 215–223 (VPYSELGGK) and peptide 238–245 (HDIIGEFK) of 14 % or below. In both investigated sample sets, the CSF levels of synaptotagmin-1 were significantly increased in patients with dementia due to Alzheimer’s disease (P ≤ 0.0001) and in patients with mild cognitive impairment due to Alzheimer’s disease (P < 0.001). In addition, in sample set I the synaptotagmin-1 level was significantly higher in patients with mild cognitive impairment due to Alzheimer’s disease compared with patients with dementia due to Alzheimer’s disease (P ≤ 0.05).ConclusionsCerebrospinal fluid synaptotagmin-1 is a promising biomarker to monitor synaptic dysfunction and degeneration in Alzheimer’s disease that may be useful for clinical diagnosis, to monitor effect on synaptic integrity by novel drug candidates, and to explore pathophysiology directly in patients with Alzheimer’s disease.Electronic supplementary materialThe online version of this article (doi:10.1186/s13195-016-0208-8) contains supplementary material, which is available to authorized users.

Proteomics-based identification and validation of novel plasma biomarkers phospholipid transfer protein and mannan-binding lectin serine protease-1 in age-related macular degeneration.

Age-related macular degeneration (AMD) is a major cause of severe, progressive visual loss among the elderly. There are currently no established serological markers for the diagnosis of AMD. In this study, we carried out a large-scale quantitative proteomics analysis to identify plasma proteins that could serve as potential AMD biomarkers. We found that the plasma levels of phospholipid transfer protein (PLTP) and mannan-binding lectin serine protease (MASP)-1 were increased in AMD patients relative to controls. The receiver operating characteristic curve based on data from an independent set of AMD patients and healthy controls had an area under the curve of 0.936 for PLTP and 0.716 for MASP-1, revealing excellent discrimination between the two groups. A proteogenomic combination model that incorporated PLTP and MASP-1 along with two known risk genotypes of age-related maculopathy susceptibility 2 and complement factor H genes further enhanced discriminatory power. Additionally, PLTP and MASP-1 mRNA and protein expression levels were upregulated in retinal pigment epithelial cells upon exposure to oxidative stress in vitro. These results indicate that PLTP and MASP-1 can serve as plasma biomarkers for the early diagnosis and treatment of AMD, which is critical for preventing AMD-related blindness.

Gene Signature of High White Blood Cell Count in B-Precursor Acute Lymphoblastic Leukemia.

In this study we sought to identify genetic factors associated with the presenting white blood cell (WBC) count in B-precursor acute lymphoblastic leukemia (BP-ALL). Using ETV6-RUNX1-positive BP-ALL patient samples, a homogeneous subtype, we identified 16 differentially expressed genes based on the presenting WBC count (< 50,000/cumm vs > 50,000). We further confirmed that IL1R1, BCAR3, KCNH2, PIR, and ZDHHC23 were differentially expressed in a larger cohort of ETV6-RUNX1-negative BP-ALL patient samples. Statistical analysis demonstrated that expression levels of these genes could accurately categorize high and low WBC count subjects using two independent patient sets, representing positive and negative ETV6-RUNX1 cases. Further studies in leukemia cell line models will better delineate the role of these genes in regulating the white blood cell count and potentially identify new therapeutic targets.

Abstract 2570: Identification of genetic polymorphisms associated with myelodysplastic syndromes by genome-wide association study

Abstract Background: The myelodysplastic syndromes (MDS) are senescence-dependent stem cell malignancies. Although germ line mutations in RUNX1, CEBPA, ETV6, or GATA2 may underlie familial cases, inherited genetic polymorphisms influencing MDS susceptibility has not been evaluated. We performed the first genome-wide association study (GWAS) to identify single nucleotide polymorphisms (SNPs) linked to MDS predisposition. Methods: DNA from 1361 MDS patients from 9 international centers was genotyped on the Affymetrix Genome-Wide Human SNP Array 6.0; all patients signed informed consent. Data on 4597 healthy controls genotyped on the same platform were obtained from the Database of Genotypes and Phenotypes (dbGaP). Applying standard quality control metrics and limiting to individuals of European ancestry, we analysed 999 MDS patients and 4,309 controls at 545,924 markers. We used logistic regression to determine associations with MDS after appropriate adjustment assuming an additive genetic model. Results: We identified 15 SNPs at 9 loci associated with MDS, including rs6780298 (3q13; p = 5.0×10-6) and rs1206819 (20q13; p = 1.54×10-6) that mapped to the intragenic regions of MORC1 and EYA2, respectively; and rs2473784 (1p31; p = 3.32×10-7) that mapped downstream of DEPDC1. Other hits (p≤5×10-6) at 4q28, 5p14, 9p22, 6p22, 10q21 are in or near SLC7A11, GUSBP1, SH3GL2, MOG and TRIM27, respectively. Using publicly available gene expression profiling data, we confirmed all of these genes are expressed in the hematopoietic compartment and MORC1, EYA2, DEPDC1, and SH3GL2 are increased in leukemic samples suggesting that variation in these genes may be functionally relevant in myeloid malignancies. Notably, EYA2 (20q13) flanks the commonly deleted region in del(20q) MDS and has oncogenic properties in solid tumors. SH3GL2 is very highly upregulated in leukemic samples and interacts with Dynamin-1, a GTP-binding protein involved in cellular trafficking and is similarly associated with solid tumorigenesis. To validate our observed associations, we analysed the 15 SNP markers in an independent set of 12,385 individuals of whom 117 developed hematologic malignancy (including MDS) during follow up. The markers at 1p31 including rs2473784 and 4 others in strong linkage disequilibrium were associated with individuals who developed hematologic malignancy (p&amp;lt;0.05). One other SNP (rs404660) showing an association in both the MDS GWAS analysis and the hematologic malignancy dataset is also currently under further investigation. Conclusions: These data provide the first genome-wide identification of germline variants associated with MDS. Current work is underway to replicate these findings in an independent sample set of MDS patients and healthy controls. If confirmed, these SNPs may serve as biomarkers to identify individuals at risk for MDS and potentially support new prevention strategies. Citation Format: Kathy McGraw, Chia-Ho Cheng, Ann Chen, Giulio Genovese, Thomas Cluzeau, Hui-Yi Lin, Bartlomiej Przychodzen, Mar Mallo, Leonor Arenillas, Azim Mohamedali, Lionel Ades, Ashley Basiorka, Brittany Irvine, David Sallman, Eric Padron, Lubomir Sokol, Andrea Pellagatti, Chimene Brest, Sophie Raynaud, Bjorn Nilsson, Jacqueline Boultwood, Benjamin Ebert, Francesc Sole, Pierre Fenaux, Ghulam Mufti, Jaroslaw Maciejewski, Peter Kanetsky, Alan List. Identification of genetic polymorphisms associated with myelodysplastic syndromes by genome-wide association study. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2570.