4-H plant & seed identification & crop judging: leader guide

Revised July 1989. Reprinted July 1988. Facts and recommendations in this publication may no longer be valid. Please look for up-to-date information in the OSU Extension Catalog: http://extension.oregonstate.edu/catalo

Longitudinal Cytokine Profiling Identifies GRO-α and EGF as Potential Biomarkers of Disease Progression in Essential Thrombocythemia.

Myeloproliferative neoplasms (MPNs) are characterized by deregulation of mature blood cell production and increased risk of myelofibrosis (MF) and leukemic transformation. Numerous driver mutations have been identified but substantial disease heterogeneity remains unexplained, implying the involvement of additional as yet unidentified factors. The inflammatory microenvironment has recently attracted attention as a crucial factor in MPN biology, in particular whether inflammatory cytokines and chemokines contribute to disease establishment or progression. Here we present a large-scale study of serum cytokine profiles in more than 400 MPN patients and identify an essential thrombocythemia (ET)-specific inflammatory cytokine signature consisting of Eotaxin, GRO-α, and EGF. Levels of 2 of these markers (GRO-α and EGF) in ET patients were associated with disease transformation in initial sample collection (GRO-α) or longitudinal sampling (EGF). In ET patients with extensive genomic profiling data (n = 183) cytokine levels added significant prognostic value for predicting transformation from ET to MF. Furthermore, CD56+CD14+ pro-inflammatory monocytes were identified as a novel source of increased GRO-α levels. These data implicate the immune cell microenvironment as a significant player in ET disease evolution and illustrate the utility of cytokines as potential biomarkers for reaching beyond genomic classification for disease stratification and monitoring.The serum cytokine studies were supported by a research grant from the Rosetrees Trust. NFØ was supported by grants from the Danish Lundbeck Foundation and Danish Cancer Society, J.G. was supported by fellowships from Bloodwise and the Kay Kendall Leukaemia Fund; and M.S.S. is the recipient of a Biotechnology and Biological Sciences Research Council Industrial Collaborative Awards in Science and Engineering PhD Studentship. Work in the R.C.S. laboratory was supported by grants from the Stiftung Blutspendezentrum SRK beider Basel, the Swiss National Science Foundation (31003A-147016/1 and 31003A_166613), and the Swiss Cancer League (KLS-2950-02-2012 and KFS-3655-02-2015). A.K. was supported by the Else Kröner-Fresenius Foundation. Work in the A.R.G. laboratory is supported by the Wellcome Trust, Bloodwise, Cancer Research UK, the Kay Kendall Leukaemia Fund, and the Leukemia and Lymphoma Society of America. Work in the D.G.K. laboratory is supported by a Bloodwise Bennett Fellowship (15008), a European Hematology Association Non-Clinical Advanced Research Fellowship, and an ERC Starting Grant (ERC-2016-STG–715371). D.G.K. and A.R.G. are supported by a core support grant from the Wellcome Trust and Medical Research Council to the Wellcome MRC Cambridge Stem Cell Institute, the National Institute for Health Research Cambridge Biomedical Research Centre, and the CRUK Cambridge Cancer Centre

Genetic assessment of age-associated Alzheimer disease risk: Development and validation of a polygenic hazard score

Background Identifying individuals at risk for developing Alzheimer disease (AD) is of utmost importance. Although genetic studies have identified AD-associated SNPs in APOE and other genes, genetic information has not been integrated into an epidemiological framework for risk prediction. Methods and findings Using genotype data from 17,008 AD cases and 37,154 controls from the International Genomics of Alzheimer’s Project (IGAP Stage 1), we identified AD-associated SNPs (at p < 10−5 ). We then integrated these AD-associated SNPs into a Cox proportional hazard model using genotype data from a subset of 6,409 AD patients and 9,386 older controls from Phase 1 of the Alzheimer’s Disease Genetics Consortium (ADGC), providing a polygenic hazard score (PHS) for each participant. By combining population-based incidence rates and the genotype-derived PHS for each individual, we derived estimates of instantaneous risk for developing AD, based on genotype and age, and tested replication in multiple independent cohorts (ADGC Phase 2, National Institute on Aging Alzheimer’s Disease Center [NIA ADC], and Alzheimer’s Disease Neuroimaging Initiative [ADNI], total n = 20,680). Within the ADGC Phase 1 cohort, individuals in the highest PHS quartile developed AD at a considerably lower age and had the highest yearly AD incidence rate. Among APOE ε3/3 individuals, the PHS modified expected age of AD onset by more than 10 y between the lowest and highest deciles (hazard ratio 3.34, 95% CI 2.62–4.24, p = 1.0 × 10−22). In independent cohorts, the PHS strongly predicted empirical age of AD onset (ADGC Phase 2, r = 0.90, p = 1.1 × 10−26) and longitudinal progression from normal aging to AD (NIA ADC, Cochran–Armitage trend test, p = 1.5 × 10−10), and was associated with neuropathology (NIA ADC, Braak stage of neurofibrillary tangles, p = 3.9 × 10−6 , and Consortium to Establish a Registry for Alzheimer’s Disease score for neuritic plaques, p = 6.8 × 10−6 ) and in vivo markers of AD neurodegeneration (ADNI, volume loss within the entorhinal cortex, p = 6.3 × 10−6 , and hippocampus, p = 7.9 × 10−5 ). Additional prospective validation of these results in non-US, non-white, and prospective community-based cohorts is necessary before clinical use. Conclusions We have developed a PHS for quantifying individual differences in age-specific genetic risk for AD. Within the cohorts studied here, polygenic architecture plays an important role in modifying AD risk beyond APOE. With thorough validation, quantification of inherited genetic variation may prove useful for stratifying AD risk and as an enrichment strategy in therapeutic trials

A Distributed Chemosensory Circuit for Oxygen Preference in C. elegans

The nematode Caenorhabditis elegans has complex, naturally variable behavioral responses to environmental oxygen, food, and other animals. C. elegans detects oxygen through soluble guanylate cyclase homologs (sGCs) and responds to it differently depending on the activity of the neuropeptide receptor NPR-1: npr-1(lf) and naturally isolated npr-1(215F) animals avoid high oxygen and aggregate in the presence of food; npr-1(215V) animals do not. We show here that hyperoxia avoidance integrates food with npr-1 activity through neuromodulation of a distributed oxygen-sensing network. Hyperoxia avoidance is stimulated by sGC-expressing oxygen-sensing neurons, nociceptive neurons, and ADF sensory neurons. In npr-1(215V) animals, the switch from weak aerotaxis on food to strong aerotaxis in its absence requires close regulation of the neurotransmitter serotonin in the ADF neurons; high levels of ADF serotonin promote hyperoxia avoidance. In npr-1(lf) animals, food regulation is masked by increased activity of the oxygen-sensing neurons. Hyperoxia avoidance is also regulated by the neuronal TGF-β homolog DAF-7, a secreted mediator of crowding and stress responses. DAF-7 inhibits serotonin synthesis in ADF, suggesting that ADF serotonin is a convergence point for regulation of hyperoxia avoidance. Coalitions of neurons that promote and repress hyperoxia avoidance generate a subtle and flexible response to environmental oxygen

Polygenic hazard score to guide screening for aggressive prostate cancer: development and validation in large scale cohorts.

OBJECTIVES: To develop and validate a genetic tool to predict age of onset of aggressive prostate cancer (PCa) and to guide decisions of who to screen and at what age. DESIGN: Analysis of genotype, PCa status, and age to select single nucleotide polymorphisms (SNPs) associated with diagnosis. These polymorphisms were incorporated into a survival analysis to estimate their effects on age at diagnosis of aggressive PCa (that is, not eligible for surveillance according to National Comprehensive Cancer Network guidelines; any of Gleason score ≥7, stage T3-T4, PSA (prostate specific antigen) concentration ≥10 ng/L, nodal metastasis, distant metastasis). The resulting polygenic hazard score is an assessment of individual genetic risk. The final model was applied to an independent dataset containing genotype and PSA screening data. The hazard score was calculated for these men to test prediction of survival free from PCa. SETTING: Multiple institutions that were members of international PRACTICAL consortium. PARTICIPANTS: All consortium participants of European ancestry with known age, PCa status, and quality assured custom (iCOGS) array genotype data. The development dataset comprised 31 747 men; the validation dataset comprised 6411 men. MAIN OUTCOME MEASURES: Prediction with hazard score of age of onset of aggressive cancer in validation set. RESULTS: In the independent validation set, the hazard score calculated from 54 single nucleotide polymorphisms was a highly significant predictor of age at diagnosis of aggressive cancer (z=11.2, P98th centile) were compared with those with average scores (30th-70th centile), the hazard ratio for aggressive cancer was 2.9 (95% confidence interval 2.4 to 3.4). Inclusion of family history in a combined model did not improve prediction of onset of aggressive PCa (P=0.59), and polygenic hazard score performance remained high when family history was accounted for. Additionally, the positive predictive value of PSA screening for aggressive PCa was increased with increasing polygenic hazard score. CONCLUSIONS: Polygenic hazard scores can be used for personalised genetic risk estimates that can predict for age at onset of aggressive PCa

Polygenic overlap between C-reactive protein, plasma lipids, and Alzheimer disease

Background—Epidemiological findings suggest a relationship between Alzheimer disease (AD), inflammation, and dyslipidemia, although the nature of this relationship is not well understood. We investigated whether this phenotypic association arises from a shared genetic basis. Methods and Results—Using summary statistics (P values and odds ratios) from genome-wide association studies of >200 000 individuals, we investigated overlap in single-nucleotide polymorphisms associated with clinically diagnosed AD and C-reactive protein (CRP), triglycerides, and high- and low-density lipoprotein levels. We found up to 50-fold enrichment of AD single-nucleotide polymorphisms for different levels of association with C-reactive protein, low-density lipoprotein, high-density lipoprotein, and triglyceride single-nucleotide polymorphisms using a false discovery rate threshold <0.05. By conditioning on polymorphisms associated with the 4 phenotypes, we identified 55 loci associated with increased AD risk. We then conducted a meta-analysis of these 55 variants across 4 independent AD cohorts (total: n=29 054 AD cases and 114 824 healthy controls) and discovered 2 genome-wide significant variants on chromosome 4 (rs13113697; closest gene, HS3ST1; odds ratio=1.07; 95% confidence interval=1.05–1.11; P=2.86×10−8) and chromosome 10 (rs7920721; closest gene, ECHDC3; odds ratio=1.07; 95% confidence interval=1.04–1.11; P=3.38×10−8). We also found that gene expression of HS3ST1 and ECHDC3 was altered in AD brains compared with control brains. Conclusions—We demonstrate genetic overlap between AD, C-reactive protein, and plasma lipids. By conditioning on the genetic association with the cardiovascular phenotypes, we identify novel AD susceptibility loci, including 2 genome-wide significant variants conferring increased risk for AD.acceptedVersio

Polygenic hazard score to guide screening for aggressive - prostate cancer: development and validation in large scale - cohorts

OBJECTIVESTo develop and validate a genetic tool to predict age of onset of aggressive prostate cancer (PCa) and to guide decisions of who to screen and at what age.DESIGNAnalysis of genotype, PCa status, and age to select single nucleotide polymorphisms (SNPs) associated with diagnosis. These polymorphisms were incorporated into a survival analysis to estimate their effects on age at diagnosis of aggressive PCa (that is, not eligible for surveillance according to National Comprehensive Cancer Network guidelines; any of Gleason score >= 7, stage T3-T4, PSA (prostate specific antigen) concentration >= 10 ng/L, nodal metastasis, distant metastasis). The resulting polygenic hazard score is an assessment of individual genetic risk. The final model was applied to an independent dataset containing genotype and PSA screening data. The hazard score was calculated for these men to test prediction of survival free from PCa.SETTINGMultiple institutions that were members of international PRACTICAL consortium.PARTICIPANTSAll consortium participants of European ancestry with known age, PCa status, and quality assured custom (iCOGS) array genotype data. The development dataset comprised 31 747 men; the validation dataset comprised 6411 men.MAIN OUTCOME MEASURESPrediction with hazard score of age of onset of aggressive cancer in validation set.RESULTSIn the independent validation set, the hazard score calculated from 54 single nucleotide polymorphisms was a highly significant predictor of age at diagnosis of aggressive cancer (z= 11.2, P98th centile) were compared with those with average scores (30th-70th centile), the hazard ratio for aggressive cancer was 2.9 (95% confidence interval 2.4 to 3.4). Inclusion of family history in a combined model did not improve prediction of onset of aggressive PCa (P= 0.59), and polygenic hazard score performance remained high when family history was accounted for. Additionally, the positive predictive value of PSA screening for aggressive PCa was increased with increasing polygenic hazard score.CONCLUSIONSPolygenic hazard scores can be used for personalised genetic risk estimates that can predict for age at onset of aggressive PCa