scholarly journals Strategies to Uplift Novel Mendelian Gene Discovery for Improved Clinical Outcomes

2021 ◽  
Vol 12 ◽  
Author(s):  
Eleanor G. Seaby ◽  
Heidi L. Rehm ◽  
Anne O’Donnell-Luria
Keyword(s):  
Clinical Outcomes ◽  
Large Scale ◽  
Genetic Disorders ◽  
Clinical Care ◽  
Gene Discovery ◽  
Genomic Sequencing ◽  
Omics Data ◽  
Significant Morbidity ◽  
Genetic Etiology ◽  
Mendelian Gene

Rare genetic disorders, while individually rare, are collectively common. They represent some of the most severe disorders affecting patients worldwide with significant morbidity and mortality. Over the last decade, advances in genomic methods have significantly uplifted diagnostic rates for patients and facilitated novel and targeted therapies. However, many patients with rare genetic disorders still remain undiagnosed as the genetic etiology of only a proportion of Mendelian conditions has been discovered to date. This article explores existing strategies to identify novel Mendelian genes and how these discoveries impact clinical care and therapeutics. We discuss the importance of data sharing, phenotype-driven approaches, patient-led approaches, utilization of large-scale genomic sequencing projects, constraint-based methods, integration of multi-omics data, and gene-to-patient methods. We further consider the health economic advantages of novel gene discovery and speculate on potential future methods for improved clinical outcomes.

scholarly journals Findings from the Section on Bioinformatics and Translational Informatics

2017 ◽  
Vol 26 (01) ◽  
pp. 188-192 ◽  
Author(s):  
H. Dauchel ◽  
T. Lecroq
Keyword(s):  
Intelligent Systems ◽  
Large Scale ◽  
Cancer Genomics ◽  
Clinical Care ◽  
Evaluation Process ◽  
Omics Data ◽  
Health Domain ◽  
Medical Genomics ◽  
Research Activities ◽  
Translational Informatics

Summary Objective: To summarize excellent current research and propose a selection of best papers published in 2016 in the field of Bioinformatics and Translational Informatics with applications in the health domain and clinical care. Methods: We provide a synopsis of the articles selected for the IMIA Yearbook 2017, from which we attempt to derive a synthetic overview of current and future activities in the field. As in 2016, a first step of selection was performed by querying MEDLINE with a list of MeSH descriptors completed by a list of terms adapted to the section coverage. Each section editor evaluated separately the set of 951 articles returned and evaluation results were merged for retaining 15 candidate best papers for peer-review. Results: The selection and evaluation process of papers published in the Bioinformatics and Translational Informatics field yielded four excellent articles focusing this year on the secondary use and massive integration of multi-omics data for cancer genomics and non-cancer complex diseases. Papers present methods to study the functional impact of genetic variations, either at the level of the transcription or at the levels of pathway and network. Conclusions: Current research activities in Bioinformatics and Translational Informatics with applications in the health domain continue to explore new algorithms and statistical models to manage, integrate, and interpret large-scale genomic datasets. As addressed by some of the selected papers, future trends would include the question of the international collaborative sharing of clinical and omics data, and the implementation of intelligent systems to enhance routine medical genomics.

scholarly journals Findings from the Section on Bioinformatics and Translational Informatics

2017 ◽  
Vol 26 (01) ◽  
pp. 188-191
Author(s):  
H. Dauchel ◽  
T. Lecroq
Keyword(s):  
Intelligent Systems ◽  
Large Scale ◽  
Cancer Genomics ◽  
Clinical Care ◽  
Evaluation Process ◽  
Omics Data ◽  
Health Domain ◽  
Medical Genomics ◽  
Research Activities ◽  
Translational Informatics

Summary Objective: To summarize excellent current research and propose a selection of best papers published in 2016 in the field of Bioinformatics and Translational Informatics with applications in the health domain and clinical care. Methods: We provide a synopsis of the articles selected for the IMIA Yearbook 2017, from which we attempt to derive a synthetic overview of current and future activities in the field. As in 2016, a first step of selection was performed by querying MEDLINE with a list of MeSH descriptors completed by a list of terms adapted to the section coverage. Each section editor evaluated separately the set of 951 articles returned and evaluation results were merged for retaining 15 candidate best papers for peer-review. Results: The selection and evaluation process of papers published in the Bioinformatics and Translational Informatics field yielded four excellent articles focusing this year on the secondary use and massive integration of multi-omics data for cancer genomics and non-cancer complex diseases. Papers present methods to study the functional impact of genetic variations, either at the level of the transcription or at the levels of pathway and network. Conclusions: Current research activities in Bioinformatics and Translational Informatics with applications in the health domain continue to explore new algorithms and statistical models to manage, integrate, and interpret large-scale genomic datasets. As addressed by some of the selected papers, future trends would include the question of the international collaborative sharing of clinical and omics data, and the implementation of intelligent systems to enhance routine medical genomics.

scholarly journals Integration of enzyme constraints in a genome-scale metabolic model of Aspergillus niger improves phenotype predictions

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Jingru Zhou ◽  
Yingping Zhuang ◽  
Jianye Xia
Keyword(s):  
Aspergillus Niger ◽  
Large Scale ◽  
Measurement Techniques ◽  
Metabolic Model ◽  
System Level ◽  
Metabolic Phenotype ◽  
Omics Data ◽  
Prediction Ability ◽  
Phenotype Prediction ◽  
Genome Scale

Abstract Background Genome-scale metabolic model (GSMM) is a powerful tool for the study of cellular metabolic characteristics. With the development of multi-omics measurement techniques in recent years, new methods that integrating multi-omics data into the GSMM show promising effects on the predicted results. It does not only improve the accuracy of phenotype prediction but also enhances the reliability of the model for simulating complex biochemical phenomena, which can promote theoretical breakthroughs for specific gene target identification or better understanding the cell metabolism on the system level. Results Based on the basic GSMM model iHL1210 of Aspergillus niger, we integrated large-scale enzyme kinetics and proteomics data to establish a GSMM based on enzyme constraints, termed a GEM with Enzymatic Constraints using Kinetic and Omics data (GECKO). The results show that enzyme constraints effectively improve the model’s phenotype prediction ability, and extended the model’s potential to guide target gene identification through predicting metabolic phenotype changes of A. niger by simulating gene knockout. In addition, enzyme constraints significantly reduced the solution space of the model, i.e., flux variability over 40.10% metabolic reactions were significantly reduced. The new model showed also versatility in other aspects, like estimating large-scale $$k_{{cat}}$$ k cat values, predicting the differential expression of enzymes under different growth conditions. Conclusions This study shows that incorporating enzymes’ abundance information into GSMM is very effective for improving model performance with A. niger. Enzyme-constrained model can be used as a powerful tool for predicting the metabolic phenotype of A. niger by incorporating proteome data. In the foreseeable future, with the fast development of measurement techniques, and more precise and rich proteomics quantitative data being obtained for A. niger, the enzyme-constrained GSMM model will show greater application space on the system level.

scholarly journals Challenges and opportunities for ovarian cancer management in the epidemic of Covid-19: lessons learned from Wuhan, China

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Zhilan Chen ◽  
Chun Zhang ◽  
Jiu Yin ◽  
Xin Xin ◽  
Hemei Li ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Large Scale ◽  
Treatment Plan ◽  
Clinical Care ◽  
Gynecologic Cancer ◽  
Treatment Phase ◽  
Tumor Stage ◽  
Current Treatment ◽  
Lessons Learned ◽  
Cancer Management

AbstractChina and the rest of the world are experiencing an outbreak of the 2019 novel coronavirus disease (COVID-19). Patients with cancer are more susceptible to viral infection and are more likely to develop severe complications, as compared to healthy individuals. The growing spread of COVID-19 presents challenges for the clinical care of patients with gynecological malignancies. Ovarian debulking surgery combined with the frequent need for chemotherapy is most likely why ovarian cancer was rated as the gynecologic cancer most affected by COVID-19. Therefore, ovarian cancer presents a particular challenging task. Concerning the ovarian cancer studies with confirmed COVID-19 reported from large-scale general hospitals in Wuhan, we hold that the treatment plan was adjusted appropriately and an individualized remedy was implemented. The recommendations discussed here were developed mainly based on the experience from Wuhan. We advise that the management strategy for ovarian cancer patients should be adjusted in the light of the local epidemic situation and formulated according to the pathological type, tumor stage and the current treatment phase. Online medical service is an effective and convenient communication platform during the pandemic.

scholarly journals EyeHealer: A large-scale anterior eye segment dataset with eye structure and lesion annotations

2021 ◽  
Author(s):  
Wenjia Cai ◽  
Jie Xu ◽  
Ke Wang ◽  
Xiaohong Liu ◽  
Wenqin Xu ◽  
...  
Keyword(s):  
Deep Learning ◽  
Large Scale ◽  
Image Annotation ◽  
Clinical Care ◽  
Significant Proportion ◽  
Anterior Segment ◽  
Future Research ◽  
Learning Models ◽  
Anterior Eye Segment ◽  
Segmentation Models

Abstract Anterior segment eye diseases account for a significant proportion of presentations to eye clinics worldwide, including diseases associated with corneal pathologies, anterior chamber abnormalities (e.g. blood or inflammation) and lens diseases. The construction of an automatic tool for the segmentation of anterior segment eye lesions will greatly improve the efficiency of clinical care. With research on artificial intelligence progressing in recent years, deep learning models have shown their superiority in image classification and segmentation. The training and evaluation of deep learning models should be based on a large amount of data annotated with expertise, however, such data are relatively scarce in the domain of medicine. Herein, the authors developed a new medical image annotation system, called EyeHealer. It is a large-scale anterior eye segment dataset with both eye structures and lesions annotated at the pixel level. Comprehensive experiments were conducted to verify its performance in disease classification and eye lesion segmentation. The results showed that semantic segmentation models outperformed medical segmentation models. This paper describes the establishment of the system for automated classification and segmentation tasks. The dataset will be made publicly available to encourage future research in this area.

scholarly journals Perspectives and experiences of patients and healthcare professionals with geriatric assessment in chronic kidney disease: a qualitative study

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Carlijn G. N. Voorend ◽  
Noeleen C. Berkhout-Byrne ◽  
Yvette Meuleman ◽  
Simon P. Mooijaart ◽  
Willem Jan W. Bos ◽  
...  
Keyword(s):  
Kidney Disease ◽  
Qualitative Study ◽  
Clinical Outcomes ◽  
Geriatric Assessment ◽  
Clinical Care ◽  
Treatment Options ◽  
Routine Care ◽  
Treatment Team ◽  
Dutch Hospital ◽  
Additional Support

Abstract Background Older patients with end-stage kidney disease (ESKD) often live with unidentified frailty and multimorbidity. Despite guideline recommendations, geriatric assessment is not part of standard clinical care, resulting in a missed opportunity to enhance (clinical) outcomes including quality of life in these patients. To develop routine geriatric assessment programs for patients approaching ESKD, it is crucial to understand patients’ and professionals’ experiences with and perspectives about the benefits, facilitators and barriers for geriatric assessment. Methods In this qualitative study, semi-structured focus group discussions were conducted with ESKD patients, caregivers and professionals. Participants were purposively sampled from three Dutch hospital-based study- and routine care initiatives involving geriatric assessment for (pre-)ESKD care. Transcripts were analysed inductively using thematic analysis. Results In six focus-groups, participants (n = 47) demonstrated four major themes: (1) Perceived characteristics of the older (pre)ESKD patient group. Patients and professionals recognized increased vulnerability and (cognitive) comorbidity, which is often unrelated to calendar age. Both believed that often patients are in need of additional support in various geriatric domains. (2) Experiences with geriatric assessment. Patients regarded the content and the time spent on the geriatric assessment predominantly positive. Professionals emphasized that assessment creates awareness among the whole treatment team for cognitive and social problems, shifting the focus from mainly somatic to multidimensional problems. Outcomes of geriatric assessment were observed to enhance a dialogue on suitability of treatment options, (re)adjust treatment and provide/seek additional (social) support. (3) Barriers and facilitators for implementation of geriatric assessment in routine care. Discussed barriers included lack of communication about goals and interpretation of geriatric assessment, burden for patients, illiteracy, and organizational aspects. Major facilitators are good multidisciplinary cooperation, involvement of geriatrics and multidisciplinary team meetings. (4) Desired characteristics of a suitable geriatric assessment concerned the scope and use of tests and timing of assessment. Conclusions Patients and professionals were positive about using geriatric assessment in routine nephrology care. Implementation seems achievable, once barriers are overcome and facilitators are endorsed. Geriatric assessment in routine care appears promising to improve (clinical) outcomes in patients approaching ESKD.

scholarly journals COVID-19 public health measures: a reduction in hospital admissions for COPD exacerbations

Thorax ◽  
2020 ◽  
pp. thoraxjnl-2020-216083
Author(s):  
Jing Yuan Tan ◽  
Edwin Philip Conceicao ◽  
Liang En Wee ◽  
Xiang Ying Jean Sim ◽  
Indumathi Venkatachalam
Keyword(s):  
Public Health ◽  
Clinical Outcomes ◽  
Hospital Admissions ◽  
Viral Infections ◽  
Significant Morbidity ◽  
Common Cause ◽  
Copd Exacerbations ◽  
Health Measures ◽  
Acute Exacerbations ◽  
Respiratory Viral Infections

Hospitalisations for acute exacerbations of COPD (AECOPD) carry significant morbidity and mortality. Respiratory viral infections (RVIs) are the most common cause of AECOPD and are associated with worse clinical outcomes. During the COVID-19 pandemic, public health measures, such as social distancing and universal masking, were originally implemented to reduce transmission of SARS-CoV-2; these public health measures were subsequently also observed to reduce transmission of other common circulating RVIs. In this study, we report a significant and sustained decrease in hospital admissions for all AECOPD as well as RVI-associated AECOPD, which coincided with the introduction of public health measures during the COVID-19 pandemic.

Consumer Wearables for Patient Monitoring in Otolaryngology: A State of the Art Review

2021 ◽  
pp. 019459982110616
Author(s):  
Shaan N. Somani ◽  
Katherine M. Yu ◽  
Alexander G. Chiu ◽  
Kevin J. Sykes ◽  
Jennifer A. Villwock
Keyword(s):  
Health Care ◽  
Clinical Outcomes ◽  
Behavioral Interventions ◽  
Early Recognition ◽  
Clinical Care ◽  
The United States ◽  
Major Surgery ◽  
Inpatient Setting ◽  
Biometric Data ◽  
Pubmed Search

Objective Consumer wearables, such as the Apple Watch or Fitbit devices, have become increasingly commonplace over the past decade. The application of these devices to health care remains an area of significant yet ill-defined promise. This review aims to identify the potential role of consumer wearables for the monitoring of otolaryngology patients. Data Sources PubMed. Review Methods A PubMed search was conducted to identify the use of consumer wearables for the assessment of clinical outcomes relevant to otolaryngology. Articles were included if they described the use of wearables that were designed for continuous wear and were available for consumer purchase in the United States. Articles meeting inclusion criteria were synthesized into a final narrative review. Conclusions In the perioperative setting, consumer wearables could facilitate prehabilitation before major surgery and prediction of clinical outcomes. The use of consumer wearables in the inpatient setting could allow for early recognition of parameters suggestive of poor or declining health. The real-time feedback provided by these devices in the remote setting could be incorporated into behavioral interventions to promote patients’ engagement with healthy behaviors. Various concerns surrounding the privacy, ownership, and validity of wearable-derived data must be addressed before their widespread adoption in health care. Implications for Practice Understanding how to leverage the wealth of biometric data collected by consumer wearables to improve health outcomes will become a high-impact area of research and clinical care. Well-designed comparative studies that elucidate the value and clinical applicability of these data are needed.

NCOG-18. RELATIONSHIP BETWEEN RANO-PRO WORKING GROUP STANDARDIZED PRIORITY CONSTRUCTS AND DISEASE PROGRESSION AMONG MALIGNANT GLIOMA PATIENTS AS MEASURED THROUGH CLINICAL OUTCOMES ASSESSMENTS

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi155-vi156
Author(s):  
Elizabeth Vera ◽  
Tito Mendoza ◽  
Alvina Acquaye ◽  
Nicole Briceno ◽  
Anna Choi ◽  
...  
Keyword(s):  
Malignant Glioma ◽  
Disease Progression ◽  
Clinical Outcomes ◽  
Stable Disease ◽  
Working Group ◽  
Karnofsky Performance Status ◽  
Clinical Care ◽  
Self Care ◽  
Work Activity ◽  
Core Symptoms

Abstract Recognizing the importance of clinical outcomes assessments (COA), the RANO-PRO Working Group recommends inclusion of core symptoms/functions in clinical care/research for malignant glioma patients. This study evaluated the association between the recommended symptoms (pain, perceived cognition, seizures, aphasia, treatment-specific symptoms) and functions (physical: weakness, walking; and role/social: work, usual activities) and disease progression in these patients. MDASI-Brain Tumor and EQ-5D-3L scores, Karnofsky Performance Status (KPS), and Neurologic Function Score (NFS) were evaluated in relation to disease progression by chi-square tests, independent- and paired-samples t-tests, adjusted for multiple comparisons. Our sample included 336 patients with malignant glioma; 82% white, 64% male, median age=52 (21-79). Imaging study revealed disease progression for 46% of patients. All symptoms except seizures and difficulty concentrating were worse in the group whose imaging showed disease progression versus stable disease, as well as the functions of walking, work, activity, and self-care (0.8 < difference < 1.8). Patients with disease progression were 4 times more likely to have a poor KPS (≤ 80) and worse NFS. Among patients with disease progression (n=112), all symptoms, except seizures, worsened from first assessment to time of progression. Up to 22% of patients reported worsening mobility, self-care, and usual activity; 46% and 35% had worsened KPS and NFS, respectively. Seven symptoms and functions were each individually reported by at least 10% of patients as having worsened the most. Worsening of symptoms and functions was not observed among patients with stable disease, except in difficulty understanding. Identified core symptoms/functions worsen at the time of progression demonstrating the relationship between priority constructs and a traditional tumor response measure while highlighting the importance of longitudinal collection of COA. The pattern of worsening was observed via both patient- and clinician-reported outcomes, emphasizing the utility of COA in clinical care and clinical trials.

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