Heuristic exploitation of genetic structure in marker-assisted gene pyramiding problems.

BACKGROUND: Over the last decade genetic marker-based plant breeding strategies have gained increasing attention because genotyping technologies are no longer limiting. Now the challenge is to optimally use genetic markers in practical breeding schemes. For simple traits such as some disease resistances it is possible to target a fixed multi-locus allele configuration at a small number of causal or linked loci. Efficiently obtaining this genetic ideotype from a given set of parental genotypes is known as the marker-assisted gene pyramiding problem. Previous methods either imposed strong restrictions or used black box integer programming solutions, while this paper explores the power of an explicit heuristic approach that exploits the underlying genetic structure to prune the search space. RESULTS: Gene Stacker is introduced as a novel approach to marker-assisted gene pyramiding, combining an explicit directed acyclic graph model with a pruned generation algorithm inspired by a simple exhaustive search. Both exact and heuristic pruning criteria are applied to reduce the number of generated schedules. It is shown that this approach can effectively be used to obtain good solutions for stacking problems of varying complexity. For more complex problems, the heuristics allow to obtain valuable approximations. For smaller problems, fewer heuristics can be applied, resulting in an interesting quality-runtime tradeoff. Gene Stacker is competitive with previous methods and often finds better and/or additional solutions within reasonable time, because of the powerful heuristics. CONCLUSIONS: The proposed approach was confirmed to be feasible in combination with heuristics to cope with realistic, complex stacking problems. The inherent flexibility of this approach allows to easily address important breeding constraints so that the obtained schedules can be widely used in practice without major modifications. In addition, the ideas applied for Gene Stacker can be incorporated in and extended for a plant breeding context that e.g. also addresses complex quantitative traits or conservation of genetic background. Gene Stacker is freely available as open source software at http://genestacker.ugent.be . The website also provides documentation and examples of how to use Gene Stacker.

Development and initial validation of a dog quality of life instrument.

The increasing attention for the dog-owner relationship combined with advances in nutrition and veterinary care have made wellbeing a focal point for dog owners, veterinarians, and dog product and service providers. While canine wellbeing can be quantified by survey-based quality of life instruments like those used in human healthcare, there are currently few instruments available that can do this reliably and at scale. Here we report the development and initial validation of a canine quality of life instrument specifically designed to quantify wellbeing in the general dog population. The instrument is based on a simple 32-question survey and includes 5 daytime domains (energetic, mobile, relaxed, happy, sociable) and 3 mealtime domains (relaxed, interested and satisfied). It captures specific health-related aspects as well as more general wellbeing aspects and, in an initial sample of 2813 dogs, already provides useful insights on canine wellbeing. We believe that data collection at scale with this instrument will help bring optimal wellbeing to the dogs we care for.

An early prediction model for canine chronic kidney disease based on routine clinical laboratory tests.

The aim of this study was to derive a model to predict the risk of dogs developing chronic kidney disease (CKD) using data from electronic health records (EHR) collected during routine veterinary practice. Data from 57,402 dogs were included in the study. Two thirds of the EHRs were used to build the model, which included feature selection and identification of the optimal neural network type and architecture. The remaining unseen EHRs were used to evaluate model performance. The final model was a recurrent neural network with 6 features (creatinine, blood urea nitrogen, urine specific gravity, urine protein, weight, age). Identifying CKD at the time of diagnosis, the model displayed a sensitivity of 91.4% and a specificity of 97.2%. When predicting future risk of CKD, model sensitivity was 68.8% at 1 year, and 44.8% 2 years before diagnosis. Positive predictive value (PPV) varied between 15 and 23% and was influenced by the age of the patient, while the negative predictive value remained above 99% under all tested conditions. While the modest PPV limits its use as a stand-alone diagnostic screening tool, high specificity and NPV make the model particularly effective at identifying patients that will not go on to develop CKD.

Predicting early risk of chronic kidney disease in cats using routine clinical laboratory tests and machine learning.

BACKGROUND: Advanced machine learning methods combined with large sets of health screening data provide opportunities for diagnostic value in human and veterinary medicine. HYPOTHESIS/OBJECTIVES: To derive a model to predict the risk of cats developing chronic kidney disease (CKD) using data from electronic health records (EHRs) collected during routine veterinary practice. ANIMALS: A total of 106 251 cats that attended Banfield Pet Hospitals between January 1, 1995, and December 31, 2017. METHODS: Longitudinal EHRs from Banfield Pet Hospitals were extracted and randomly split into 2 parts. The first 67% of the data were used to build a prediction model, which included feature selection and identification of the optimal neural network type and architecture. The remaining unseen EHRs were used to evaluate the model performance. RESULTS: The final model was a recurrent neural network (RNN) with 4 features (creatinine, blood urea nitrogen, urine specific gravity, and age). When predicting CKD near the point of diagnosis, the model displayed a sensitivity of 90.7% and a specificity of 98.9%. Model sensitivity decreased when predicting the risk of CKD with a longer horizon, having 63.0% sensitivity 1 year before diagnosis and 44.2% 2 years before diagnosis, but with specificity remaining around 99%. CONCLUSIONS AND CLINICAL IMPORTANCE: The use of models based on machine learning can support veterinary decision making by improving early identification of CKD.

Moving Beyond Managing Realized Genomic Relationship in Long-Term Genomic Selection.

Long-term genomic selection (GS) requires strategies that balance genetic gain with population diversity, to sustain progress for traits under selection, and to keep diversity for future breeding. In a simulation model for a recurrent selection scheme, we provide the first head-to-head comparison of two such existing strategies: genomic optimal contributions selection (GOCS), which limits realized genomic relationship among selection candidates, and weighted genomic selection (WGS), which upscales rare allele effects in GS. Compared to GS, both methods provide the same higher long-term genetic gain and a similar lower inbreeding rate, despite some inherent limitations. GOCS does not control the inbreeding rate component linked to trait selection, and, therefore, does not strike the optimal balance between genetic gain and inbreeding. This makes it less effective throughout the breeding scheme, and particularly so at the beginning, where genetic gain and diversity may not be competing. For WGS, truncation selection proved suboptimal to manage rare allele frequencies among the selection candidates. To overcome these limitations, we introduce two new set selection methods that maximize a weighted index balancing genetic gain with controlling expected heterozygosity (IND-HE) or maintaining rare alleles (IND-RA), and show that these outperform GOCS and WGS in a nearly identical way. While requiring further testing, we believe that the inherent benefits of the IND-HE and IND-RA methods will transfer from our simulation framework to many practical breeding settings, and are therefore a major step forward toward efficient long-term genomic selection.

Neurotoxicity marker profiles in the CSF are not age-dependent but show variation in children treated for acute lymphoblastic leukemia.

BACKGROUND: In children treated for hematological malignancies, a transient elevation of the neurodegenerative marker Tau was found in the cerebrospinal fluid (CSF). In the first part of this study, CSF-Tau, CSF-Phospho-Tau, and CSF-Neuromodulin (CSF-NM) were measured in a heterogeneous group of patients presenting in the pediatric oncology department. In the second part, the neurodegenerative markers were analyzed in a group of children with non-B-cell acute lymphoblastic leukemia (nB-ALL) treated according to EORTC protocols 58881 and 58951. PROCEDURE: CSF was collected from lumbar punctures at diagnosis only in the first group, and at diagnosis and during treatment in the second group. CSF-proteins were measured with ELISA. RESULTS: There was no age variation in any of the markers at diagnosis in the first group of children. After prephase induction therapy with one intrathecal (IT) injection of methotrexate (MTX) and 7 days systemic corticosteroids, an increase in CSF-Tau was observed, and accompanied with increase of both CSF-P-Tau and CSF-NM. While CSF-Tau remained high during induction treatment, CSF-P-Tau, and CSF-NM decreased. CONCLUSION: Neurodegenerative markers do not vary with age. The different protein profiles suggest that the neurotoxicity from the prephase, which results in an increase of CSF-Tau, CSF-P-Tau, and CSF-NM, may have a different mechanism to the neurotoxicity induced later during induction treatment, when only CSF-Tau remains high.

The effect of weight loss on lameness in obese dogs with osteoarthritis.

This paper describes the effect of weight loss on lameness in obese dogs with osteoarthritis (OA). Fourteen obese client-owned dogs with clinical and radiographic signs of OA participated in an open prospective clinical trial. After a screening visit and a visit for collection of baseline data, the dogs were fed a restricted-calorie diet over a study period of 16 weeks that incorporated six follow-up visits. At each visit, body weight and pelvic circumference were measured and severity of lameness was assessed using a numeric rating scale (NRS), a visual analogue scale (VAS) and kinetic gait analysis. This is the first study to assess both subjectively and objectively, the effect of weight loss alone on lameness in obese dogs with OA. The results indicate that body weight reduction causes a significant decrease in lameness from a weight loss of 6.10% onwards. Kinetic gait analysis supported the results from a body weight reduction of 8.85% onwards. These results confirm that weight loss should be presented as an important treatment modality to owners of obese dogs with OA and that noticeable improvement may be seen after modest weight loss in the region of 6.10 - 8.85% body weight.

Diagnosis-independent Alzheimer disease biomarker signature in cognitively normal elderly people.

OBJECTIVE: To identify biomarker patterns typical for Alzheimer disease (AD) in an independent, unsupervised way, without using information on the clinical diagnosis. DESIGN: Mixture modeling approach. SETTING: Alzheimer's Disease Neuroimaging Initiative database. PATIENTS OR OTHER PARTICIPANTS: Cognitively normal persons, patients with AD, and individuals with mild cognitive impairment. MAIN OUTCOME MEASURES: Cerebrospinal fluid-derived beta-amyloid protein 1-42, total tau protein, and phosphorylated tau(181P) protein concentrations were used as biomarkers on a clinically well-characterized data set. The outcome of the qualification analysis was validated on 2 additional data sets, 1 of which was autopsy confirmed. RESULTS: Using the US Alzheimer's Disease Neuroimaging Initiative data set, a cerebrospinal fluid beta-amyloid protein 1-42/phosphorylated tau(181P) biomarker mixture model identified 1 feature linked to AD, while the other matched the "healthy" status. The AD signature was found in 90%, 72%, and 36% of patients in the AD, mild cognitive impairment, and cognitively normal groups, respectively. The cognitively normal group with the AD signature was enriched in apolipoprotein E epsilon4 allele carriers. Results were validated on 2 other data sets. In 1 study consisting of 68 autopsy-confirmed AD cases, 64 of 68 patients (94% sensitivity) were correctly classified with the AD feature. In another data set with patients (n = 57) with mild cognitive impairment followed up for 5 years, the model showed a sensitivity of 100% in patients progressing to AD. CONCLUSIONS: The mixture modeling approach, totally independent of clinical AD diagnosis, correctly classified patients with AD. The unexpected presence of the AD signature in more than one-third of cognitively normal subjects suggests that AD pathology is active and detectable earlier than has heretofore been envisioned.

Attention and information processing in survivors of childhood acute lymphoblastic leukemia treated with chemotherapy only.

BACKGROUND: Omitting radiotherapy for central nervous system (CNS) prophylaxis has improved the overall quality of life for long-term survivors of childhood acute lymphoblastic leukemia (ALL). However, recent reports suggest minor cognitive impairment in survivors who received chemotherapy only. PROCEDURE: This study focused on attentional functioning and speed of information processing in 23 children previously treated for ALL according to EORTC 58881 and EORTC 58951 protocol. Patients received intrathecal methotrexate combined with high doses intravenous methotrexate as CNS prophylaxis. Cognitive functioning was assessed with the Amsterdam Neuropsychological Tasks, a computerized attention assessment program. Variables of both speed and accuracy of the patients were compared with those obtained from 23 age- and sex-matched control children. RESULTS: Patients were equal to control children concerning baseline speed, sustained attention, response inhibition, and response organization. However, they were significantly slower than controls in three tasks: encoding, memory search letters, and focused attention 4-letters. Interactions with the difficulty of the task were found. There were no differences in number or type of errors between groups on all tasks. CONCLUSIONS: ALL survivors treated with chemotherapy have specific information processing difficulties. They process information slower than control children, especially when more information has to be processed or when attention has to be focused precisely. In spite of being slower, patients are equally accurate compared to control children.

Amino-truncated beta-amyloid42 peptides in cerebrospinal fluid and prediction of progression of mild cognitive impairment.

BACKGROUND: Early identification of patients with mild cognitive impairment (MCI) progressing to Alzheimer disease (MCI-AD) by use of biomarkers in cerebrospinal fluid (CSF) is an essential step toward improving clinical diagnosis and drug development. We evaluated whether different beta-amyloid(42) (Abeta42) peptides can add further information to the combined use of tau and Abeta1-42 for predicting risk of progression of MCI to AD. METHODS: We used xMAP technology to simultaneously quantify different Abeta42 peptides modified at the amino terminus, tau, and phosphorylated tau (P-tau181P) in CSF. Abeta42 peptide concentrations were measured by use of immunoreactivity toward Abeta monoclonal antibodies [3D6 (Abeta42-3D6), WO2 (Abeta42-WO2), 6E10 (Abeta42-6E10), and 4G8 (Abeta42-4G8)]. The discriminant ability of the markers was evaluated by ROC curve analysis. RESULTS: The areas under the curves for the separation of MCI-AD from nonprogressing MCI (MCI-N) were significantly higher when we used Abeta42-3D6/Abeta42-WO2, Abeta42-3D6/Abeta42-6E10, or Abeta42-3D6/Abeta42-4G8 compared with Abeta42-3D6. In addition, differentiation of MCI-N from MCI-AD was improved by quantification of full-length Abeta1-42 (Abeta42-3D6) compared with Abeta42-WO2, Abeta42-6E10, or Abeta42-4G8. Several Abeta42 peptides truncated at the amino terminus (Abeta11-42 and Abeta8-42) were identified in CSF by surface-enhanced laser desorption/ionization time-of-flight technology. CONCLUSION: The CSF markers tau, Abeta42 forms, and P-tau181P, when used as adjuncts to clinical diagnosis, have the potential to help identify AD pathology and could be a valuable asset for early AD diagnosis.

Simultaneous measurement of beta-amyloid(1-42), total tau, and phosphorylated tau (Thr181) in cerebrospinal fluid by the xMAP technology.

BACKGROUND: To simultaneously study several biomarkers for Alzheimer disease (AD), we used the xMAP technology to develop and evaluate a multiparametric bead-based assay for quantification of beta-amyloid((1-42)) [Abeta((1-42))], total tau (T-TAU), and hyperphosphorylated tau [P-TAU((181P))] in cerebrospinal fluid (CSF). METHODS: We compared the new multianalyte assay format with established ELISA techniques for the same proteins. We then performed a clinical study using CSF samples from patients with AD or mild cognitive impairment with progression to AD, healthy controls, and patients with other neurologic disorders. RESULTS: The INNO-BIA AlzBio3 selectively and specifically measured Abeta((1-42)), T-TAU, and P-TAU((181P)) in the CSF. The new assay format had intra- and interassay CVs <10% for all analytes, even at low concentrations. The measurement range of the new assay was 3 to 4 logs compared with 1 to 2 logs for ELISAs. By plotting the mean of the values obtained in ELISA and the xMAP technology against the difference, we found that a correction factor could be used to convert xMAP results to ELISA values. The clinical study demonstrated that the new multiparametric assay could accurately distinguish patients with AD from patients with other neurologic disorders or control patients, with the diagnostic accuracy reaching recommended consensus criteria for specificity and sensitivity. CONCLUSION: The new multiparametric method may be able to replace the corresponding ELISA methods.

Abscisic acid determines basal susceptibility of tomato to Botrytis cinerea and suppresses salicylic acid-dependent signaling mechanisms.

Abscisic acid (ABA) is one of the plant hormones involved in the interaction between plants and pathogens. In this work, we show that tomato (Lycopersicon esculentum Mill. cv Moneymaker) mutants with reduced ABA levels (sitiens plants) are much more resistant to the necrotrophic fungus Botrytis cinerea than wild-type (WT) plants. Exogenous application of ABA restored susceptibility to B. cinerea in sitiens plants and increased susceptibility in WT plants. These results indicate that ABA plays a major role in the susceptibility of tomato to B. cinerea. ABA appeared to interact with a functional plant defense response against B. cinerea. Experiments with transgenic NahG tomato plants and benzo(1,2,3)thiadiazole-7-carbothioic acid demonstrated the importance of salicylic acid in the tomato-B. cinerea interaction. In addition, upon infection with B. cinerea, sitiens plants showed a clear increase in phenylalanine ammonia lyase activity, which was not observed in infected WT plants, indicating that the ABA levels in healthy WT tomato plants partly repress phenylalanine ammonia lyase activity. In addition, sitiens plants became more sensitive to benzo(1,2,3)thiadiazole-7-carbothioic acid root treatment. The threshold values for PR1a gene expression declined with a factor 10 to 100 in sitiens compared with WT plants. Thus, ABA appears to negatively modulate the salicylic acid-dependent defense pathway in tomato, which may be one of the mechanisms by which ABA levels determine susceptibility to B. cinerea.