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Computable phenotype

Brooke N Wolford, Cristen J Willer, Ida Surakka
The combination of Electronic Health Records (EHRs) with genetic data has ushered in the next wave of complex disease genetics. Population-based biobanks and other large cohorts provide sufficient sample sizes to identify novel genetic associations across the hundreds to thousands of phenotypes gleaned from EHRs. In this review we summarize the current state of these EHR-linked biobanks, explore ongoing methods development in the field, and highlight recent discoveries of genetic associations. We enumerate the many existing biobanks with EHRs linked to genetic data, many of which are available to researchers via application and contain sample sizes > 50,000...
March 14, 2018: Human Molecular Genetics
Clément Niel, Christine Sinoquet, Christian Dina, Ghislain Rocheleau
Motivation: Large scale genome-wide association studies (GWAS) are tools of choice for discovering associations between genotypes and phenotypes. To date, many studies rely on univariate statistical tests for association between the phenotype and each assayed single nucleotide polymorphism (SNP). However, interaction between SNPs, namely epistasis, must be considered when tackling the complexity of underlying biological mechanisms. Epistasis analysis at large scale entails a prohibitive computational burden when addressing the detection of more than two interacting SNPs...
March 14, 2018: Bioinformatics
Melissa Tomkins, Adi Kliot, Athanasius Fm Marée, Saskia A Hogenhout
Members of the Candidatus genus Phytoplasma are small bacterial pathogens that hijack their plant hosts via the secretion of virulence proteins (effectors) leading to a fascinating array of plant phenotypes, such as witch's brooms (stem proliferations) and phyllody (retrograde development of flowers into vegetative tissues). Phytoplasma depend on insect vectors for transmission, and interestingly, these insect vectors were found to be (in)directly attracted to plants with these phenotypes. Therefore, phytoplasma effectors appear to reprogram plant development and defence to lure insect vectors, similarly to social engineering malware, which employs tricks to lure people to infected computers and webpages...
March 13, 2018: Current Opinion in Plant Biology
Raphaël Le Bouc, Mathias Pessiglione
Motivation can be defined as the function that orients and activates the behavior. Motivation deficits such as apathy are pervasive in both neurological and psychiatric diseases, and are currently assessed with clinical scales that do not give any mechanistic insight. Here, we present another approach that consists in phenotyping the behaviour of patients in motivation tests, using computational models. These formal models impose a precise and operational definition of motivation that is embedded in decision theory...
March 2018: Médecine Sciences: M/S
Florian Ferreri, Alexis Bourla, Stephane Mouchabac, Laurent Karila
Background: New technologies can profoundly change the way we understand psychiatric pathologies and addictive disorders. New concepts are emerging with the development of more accurate means of collecting live data, computerized questionnaires, and the use of passive data. Digital phenotyping , a paradigmatic example, refers to the use of computerized measurement tools to capture the characteristics of different psychiatric disorders. Similarly, machine learning-a form of artificial intelligence-can improve the classification of patients based on patterns that clinicians have not always considered in the past...
2018: Frontiers in Psychiatry
Charlotte Wang, Jung-Ying Tzeng, Pei-Zhen Wu, Martin Preisig, Chuhsing Kate Hsiao
A properly designed distance-based measure can capture informative genetic differences among individuals with different phenotypes and be used to detect variants responsible for the phenotypes. To detect associated variants, various tests have been designed to contrast genetic dis/similarity scores of certain subject groups in different ways, among which the most widely used strategy is to quantify the difference between the within-group genetic dis/similarities (i.e., case-case and control-control similarities) and the between-group dis/similarities (i...
March 15, 2018: Genetics
Núria Folguera-Blasco, Elisabet Cuyàs, Javier A Menéndez, Tomás Alarcón
Understanding the control of epigenetic regulation is key to explain and modify the aging process. Because histone-modifying enzymes are sensitive to shifts in availability of cofactors (e.g. metabolites), cellular epigenetic states may be tied to changing conditions associated with cofactor variability. The aim of this study is to analyse the relationships between cofactor fluctuations, epigenetic landscapes, and cell state transitions. Using Approximate Bayesian Computation, we generate an ensemble of epigenetic regulation (ER) systems whose heterogeneity reflects variability in cofactor pools used by histone modifiers...
March 15, 2018: PLoS Computational Biology
Juliana Brum Moraes, Michael Maes, Chutima Roomruangwong, Kamila Landucci Bonifacio, Decio Sabbatini Barbosa, Heber Odebrecht Vargas, George Anderson, Marta Kubera, Andre F Carvalho, Sandra Odebrecht Vargas Nunes
Early life trauma (ELT) may increase the risk towards bipolar disorder (BD) and major depression (MDD), disorders associated with activated neuro-oxidative and neuro-nitrosative stress (O&NS) pathways. It has remained elusive whether ELTs are associated with O&NS and which ELTs are associated with distinct affective disorder phenotypes. This case-control study examined patients with BD (n = 68) and MDD (n = 37) and healthy controls (n = 66). The Child Trauma Questionnaire (CTQ) was used to assess specific ELT...
March 14, 2018: Metabolic Brain Disease
Anna-Lena Heins, Dirk Weuster-Botz
Population heterogeneity is omnipresent in all bioprocesses even in homogenous environments. Its origin, however, is only so well understood that potential strategies like bet-hedging, noise in gene expression and division of labour that lead to population heterogeneity can be derived from experimental studies simulating the dynamics in industrial scale bioprocesses. This review aims at summarizing the current state of the different parts of single cell studies in bioprocesses. This includes setups to visualize different phenotypes of single cells, computational approaches connecting single cell physiology with environmental influence and special cultivation setups like scale-down reactors that have been proven to be useful to simulate large-scale conditions...
March 14, 2018: Bioprocess and Biosystems Engineering
Muhammad Ramzan Manwar Hussain, Zeeshan Iqbal, Wajahat M Qazi, Daniel C Hoessli
The structural and functional diversity of the human proteome is mediated by N - and O- linked glycosylations that define the individual properties of extracellular and membrane-associated proteins. In this study, we utilized different computational tools to perform in silico based genome-wide mapping of 1,117 human proteins and unravel the contribution of both penultimate and vicinal amino acids for the asparagine-based, site-specific N -glycosylation. Our results correlate the non-canonical involvement of charge and polarity environment of classified amino acids (designated as L, O, A, P, and N groups) in the N -glycosylation process, as validated by NetNGlyc predictions, and 130 literature-reported human proteins...
2018: Frontiers in Oncology
Clifford R Jack, Heather J Wiste, Christopher G Schwarz, Val J Lowe, Matthew L Senjem, Prashanthi Vemuri, Stephen D Weigand, Terry M Therneau, Dave S Knopman, Jeffrey L Gunter, David T Jones, Jonathan Graff-Radford, Kejal Kantarci, Rosebud O Roberts, Michelle M Mielke, Mary M Machulda, Ronald C Petersen
Our objective was to compare different whole-brain and region-specific measurements of within-person change on serial tau PET and evaluate its utility for clinical trials. We studied 126 individuals: 59 cognitively unimpaired with normal amyloid, 37 cognitively unimpaired with abnormal amyloid, and 30 cognitively impaired with an amnestic phenotype and abnormal amyloid. All had baseline amyloid PET and two tau PET, MRI, and clinical assessments. We compared the topography across all cortical regions of interest of tau PET accumulation rates and the rates of four different whole-brain or region-specific meta-regions of interest among the three clinical groups...
March 12, 2018: Brain: a Journal of Neurology
Ilia Korvigo, Andrey Afanasyev, Nikolay Romashchenko, Mikhail Skoblov
Many automatic classifiers were introduced to aid inference of phenotypical effects of uncategorised nsSNVs (nonsynonymous Single Nucleotide Variations) in theoretical and medical applications. Lately, several meta-estimators have been proposed that combine different predictors, such as PolyPhen and SIFT, to integrate more information in a single score. Although many advances have been made in feature design and machine learning algorithms used, the shortage of high-quality reference data along with the bias towards intensively studied in vitro models call for improved generalisation ability in order to further increase classification accuracy and handle records with insufficient data...
2018: PloS One
Wei Lan, Liyu Huang, Dehuan Lai, Qingfeng Chen
With the development and improvement of next-generation sequencing technology, a great number of noncoding RNAs have been discovered. Long noncoding RNAs (lncRNAs) are the biggest kind of noncoding RNAs with more than 200 nt nucleotides in length. There are increasing evidences showing that lncRNAs play key roles in many biological processes. Therefore, the mutation and dysregulation of lncRNAs have close association with a number of complex human diseases. Identifying the most likely interaction between lncRNAs and diseases becomes a fundamental challenge in human health...
2018: Methods in Molecular Biology
Olivier Delalande, Anne-Elisabeth Molza, Raphael Dos Santos-Morais, Angélique Chéron, Émeline Pollet, Céline Raguenes-Nicol, Christophe Tascon, Emmanuel Giudice, Marine Guilbaud, Aurélie Nicolas, Arnaud Bondon, France Leturcq, Nicolas Férey, Marc Baaden, Javier Perez, Pierre Roblin, France Piétri-Rouxel, Jean-François Hubert, Mirjam Czjzek, Elisabeth Le Rumeur
Dystrophin, encoded by the DMD gene, is critical for maintaining plasma membrane integrity during muscle contraction events. Mutations in the DMD gene disrupting the reading frame prevent dystrophin production and result in the high severe Duchenne muscular dystrophy (DMD); in-frame internal deletions allow production of partly functional internally deleted dystrophin and result in the less severe Becker muscular dystrophy (BMD). Many known BMD deletions occur in dystrophin's central domain, generally considered to be a monotonous rod-shaped domain based on the knowledge of spectrin-family proteins...
March 13, 2018: Journal of Biological Chemistry
Tomasz Dobrzycki, Monika Krecsmarik, Florian Bonkhofer, Roger Patient, Rui Monteiro
Advances in genome engineering have resulted in the generation of numerous zebrafish mutant lines. A commonly used method to assess gene expression in the mutants is in situ hybridization (ISH). Because the embryos can be distinguished by genotype after ISH, comparing gene expression between wild type and mutant siblings can be done blinded and in parallel. Such experimental design reduces the technical variation between samples and minimises the risk of bias. This approach, however, requires an efficient method of genomic DNA extraction from post-ISH fixed zebrafish samples to ascribe phenotype to genotype...
March 13, 2018: Biology Open
Pooya Mobadersany, Safoora Yousefi, Mohamed Amgad, David A Gutman, Jill S Barnholtz-Sloan, José E Velázquez Vega, Daniel J Brat, Lee A D Cooper
Cancer histology reflects underlying molecular processes and disease progression and contains rich phenotypic information that is predictive of patient outcomes. In this study, we show a computational approach for learning patient outcomes from digital pathology images using deep learning to combine the power of adaptive machine learning algorithms with traditional survival models. We illustrate how these survival convolutional neural networks (SCNNs) can integrate information from both histology images and genomic biomarkers into a single unified framework to predict time-to-event outcomes and show prediction accuracy that surpasses the current clinical paradigm for predicting the overall survival of patients diagnosed with glioma...
March 12, 2018: Proceedings of the National Academy of Sciences of the United States of America
Y Wang, X Mi, G J M Rosa, Z Chen, P Lin, S Wang, Z Bao
Neural networks (NN) have emerged as a new tool for genomic selection (GS) in animal breeding. However, the properties of NN used in GS for the prediction of phenotypical outcomes are not well characterized due to the problem of over-parameterization of NN and difficulties in using whole-genome marker sets as high-dimensional NN input. In this note, we have developed an R package called snnR that could find an optimal sparse structure of a NN by minimizing the square error subject to a penalty on the L1-norm of the parameters (weights and biases), therefore solve the problem of over-parameterization in NN...
February 24, 2018: Journal of Animal Science
Thomas Parr, Geraint Rees, Karl J Friston
Computational theories of brain function have become very influential in neuroscience. They have facilitated the growth of formal approaches to disease, particularly in psychiatric research. In this paper, we provide a narrative review of the body of computational research addressing neuropsychological syndromes, and focus on those that employ Bayesian frameworks. Bayesian approaches to understanding brain function formulate perception and action as inferential processes. These inferences combine 'prior' beliefs with a generative (predictive) model to explain the causes of sensations...
2018: Frontiers in Human Neuroscience
Mangyuan Wang, Kai Chen, Xiao Chen, Liang Chen, Jiangping Song, ShengShou Hu
Arrhythmogenic right ventricular cardiomyopathy (ARVC) and dilated cardiomyopathy (DCM), despite being two dramatically different entities, have overlapping phenotypes. As it is easy to misdiagnose between ARVC and DCM, there is a need to establish a new differential diagnostic parameter to differentiate the two. We investigated the utility of endomyocardial biopsy (EMB) for the differential diagnosis, and our study had three aims. The first was to verify the EMB high diagnostic efficacy. The second was to investigate the EMB perforation risk at the right ventricle (RV) free wall of end-stage ARVC...
February 14, 2018: Cardiovascular Pathology: the Official Journal of the Society for Cardiovascular Pathology
Ibai Irastorza-Azcarate, Rafael D Acemel, Juan J Tena, Ignacio Maeso, José Luis Gómez-Skarmeta, Damien P Devos
The use of 3C-based methods has revealed the importance of the 3D organization of the chromatin for key aspects of genome biology. However, the different caveats of the variants of 3C techniques have limited their scope and the range of scientific fields that could benefit from these approaches. To address these limitations, we present 4Cin, a method to generate 3D models and derive virtual Hi-C (vHi-C) heat maps of genomic loci based on 4C-seq or any kind of 4C-seq-like data, such as those derived from NG Capture-C...
March 9, 2018: PLoS Computational Biology
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