scholarly journals ClinPhen extracts and prioritizes patient phenotypes directly from medical records to accelerate genetic disease diagnosis

2018 ◽  
Author(s):  
Cole A. Deisseroth ◽  
Johannes Birgmeier ◽  
Ethan E. Bodle ◽  
Jonathan A. Bernstein ◽  
Gill Bejerano

AbstractPurposeSevere genetic diseases affect 7 million births per year, worldwide. Diagnosing these diseases is necessary for optimal care, but it can involve the manual evaluation of hundreds of genetic variants per case, with many variants taking an hour to evaluate. Automatic gene-ranking approaches shorten this process by reporting which of the genes containing variants are most likely to be causing the patient’s symptoms. To use these tools, busy clinicians must manually encode patient phenotypes, which is a cumbersome and imprecise process. With 60 million patients expected to be sequenced in the next 7 years, a fast alternative to manual phenotype extraction from the clinical notes in patients’ medical records will become necessary.MethodsWe introduce ClinPhen: a fast, high-accuracy tool that automatically converts the clinical notes into a prioritized list of patient symptoms using HPO terms.ResultsClinPhen shows superior accuracy to existing phenotype extractors, and when paired with a gene-ranking tool it significantly improve the latter’s performance.ConclusionCompared to manual phenotype extraction, ClinPhen saves more than 5 hours per case in Mendelian diagnosis alone. Summing over millions of forthcoming cases whose medical notes await phenotype encoding, ClinPhen makes a substantial contribution towards ending all patients’ diagnostic odyssey.

2020 ◽  
Vol 21 (1) ◽  
pp. 351-372 ◽  
Author(s):  
Taila Hartley ◽  
Gabrielle Lemire ◽  
Kristin D. Kernohan ◽  
Heather E. Howley ◽  
David R. Adams ◽  
...  

Accurate diagnosis is the cornerstone of medicine; it is essential for informed care and promoting patient and family well-being. However, families with a rare genetic disease (RGD) often spend more than five years on a diagnostic odyssey of specialist visits and invasive testing that is lengthy, costly, and often futile, as 50% of patients do not receive a molecular diagnosis. The current diagnostic paradigm is not well designed for RGDs, especially for patients who remain undiagnosed after the initial set of investigations, and thus requires an expansion of approaches in the clinic. Leveraging opportunities to participate in research programs that utilize new technologies to understand RGDs is an important path forward for patients seeking a diagnosis. Given recent advancements in such technologies and international initiatives, the prospect of identifying a molecular diagnosis for all patients with RGDs has never been so attainable, but achieving this goal will require global cooperation at an unprecedented scale.


2018 ◽  
Vol 21 (7) ◽  
pp. 1585-1593 ◽  
Author(s):  
Cole A. Deisseroth ◽  
◽  
Johannes Birgmeier ◽  
Ethan E. Bodle ◽  
Jennefer N. Kohler ◽  
...  

2021 ◽  
Author(s):  
Francisco M. De La Vega ◽  
Shimul Chowdhury ◽  
Barry Moore ◽  
Erwin Frise ◽  
Jeanette McCarthy ◽  
...  

Clinical interpretation of genetic variants in the context of the patient's phenotype is becoming the largest component of cost and time expenditure for genome-based diagnosis of rare genetic diseases. Artificial intelligence (AI) holds promise to greatly simplify and speed interpretation by comprehensively evaluating genetic variants for pathogenicity in the context of the growing knowledge of genetic disease. We assess the diagnostic performance of GEM, a new, AI-based, clinical decision support tool, compared with expert manual interpretation. We benchmarked GEM in a retrospective cohort of 119 probands, mostly NICU infants, diagnosed with rare genetic diseases, who received whole genome sequencing (WGS) at Rady Children's Hospital. We also performed a replication study in a separate cohort of 60 cases diagnosed at five additional academic medical centers. For comparison, we also analyzed these cases with commonly used variant prioritization tools (Phevor, Exomiser, and VAAST). Included in the comparisons were WGS and whole exome sequencing (WES) as trios, duos, and singletons. Variants underpinning diagnoses spanned diverse modes of inheritance and types, including structural variants (SVs). Patient phenotypes were extracted either manually or by automated clinical natural language processing (CNLP) from clinical notes. Finally, 14 previously unsolved cases were re-analyzed. GEM ranked >90% of causal genes among the top or second candidate, using manually curated or CNLP derived phenotypes, and prioritized a median of 3 genes for review per case. Ranking of trios and duos was unchanged when analyzed as singletons. In 17 of 20 cases with diagnostic SVs, GEM identified the causal SVs as the top or second candidate irrespective of whether SV calls where provided or inferred ab initio by GEM when absent. Analysis of 14 previously unsolved cases provided novel findings in one, candidates ultimately not advanced in 3, and no new findings in 10, demonstrating the utility of GEM for reanalysis. GEM enables automated diagnostic interpretation of WES and WGS for all types of variants, including SVs, nominating a very short list of candidate genes and disorders for final review and reporting. In combination with deep phenotyping by CNLP, GEM enables substantial automation of genetic disease diagnosis, potentially decreasing the cost and speeding case review.


2020 ◽  
Vol 24 (1) ◽  
Author(s):  
Laura Helena Gerber Franciscatto ◽  
Mara Regina Santos da Silva ◽  
Alessandro Marques dos Santos ◽  
Adriane Maria Netto de Oliveira ◽  
Keterlin Salvador

Abstract Objective: To identify the trajectories and experiences of families of children with genetic diseases in health services. Method: A qualitative study, with data collected through interviews with 15 families and caregivers of children with Genetic Disease, living in the northern region of Rio Grande do Sul. Interviews were conducted from March to May 2018. Data analysis was based on thematic analysis. Results: A genetic disease diagnosis led to families' changes due to the demands of treatment, and also the needs of the child for being met by health services. To access specialized services, some families needed to travel to referral centers in larger cities. Families experienced difficulties such as unprepared health professionals, lack of organization of services, judicialization of resources, and need for structured Health Care Networks. Conclusion: The professional has the fundamental role of providing families with access to information and are responsible for decision making and for the organization and management of health and nursing services to meet the demands imposed on the individual and the family by the genetic disease.


2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Francisco M. De La Vega ◽  
Shimul Chowdhury ◽  
Barry Moore ◽  
Erwin Frise ◽  
Jeanette McCarthy ◽  
...  

Abstract Background Clinical interpretation of genetic variants in the context of the patient’s phenotype is becoming the largest component of cost and time expenditure for genome-based diagnosis of rare genetic diseases. Artificial intelligence (AI) holds promise to greatly simplify and speed genome interpretation by integrating predictive methods with the growing knowledge of genetic disease. Here we assess the diagnostic performance of Fabric GEM, a new, AI-based, clinical decision support tool for expediting genome interpretation. Methods We benchmarked GEM in a retrospective cohort of 119 probands, mostly NICU infants, diagnosed with rare genetic diseases, who received whole-genome or whole-exome sequencing (WGS, WES). We replicated our analyses in a separate cohort of 60 cases collected from five academic medical centers. For comparison, we also analyzed these cases with current state-of-the-art variant prioritization tools. Included in the comparisons were trio, duo, and singleton cases. Variants underpinning diagnoses spanned diverse modes of inheritance and types, including structural variants (SVs). Patient phenotypes were extracted from clinical notes by two means: manually and using an automated clinical natural language processing (CNLP) tool. Finally, 14 previously unsolved cases were reanalyzed. Results GEM ranked over 90% of the causal genes among the top or second candidate and prioritized for review a median of 3 candidate genes per case, using either manually curated or CNLP-derived phenotype descriptions. Ranking of trios and duos was unchanged when analyzed as singletons. In 17 of 20 cases with diagnostic SVs, GEM identified the causal SVs as the top candidate and in 19/20 within the top five, irrespective of whether SV calls were provided or inferred ab initio by GEM using its own internal SV detection algorithm. GEM showed similar performance in absence of parental genotypes. Analysis of 14 previously unsolved cases resulted in a novel finding for one case, candidates ultimately not advanced upon manual review for 3 cases, and no new findings for 10 cases. Conclusions GEM enabled diagnostic interpretation inclusive of all variant types through automated nomination of a very short list of candidate genes and disorders for final review and reporting. In combination with deep phenotyping by CNLP, GEM enables substantial automation of genetic disease diagnosis, potentially decreasing cost and expediting case review.


1995 ◽  
pp. 45-53
Author(s):  
Jaakko Ignatius

The frequency of marriages contracted between individuals with close consanguinity has traditionally been low in Finland. In the 19th and early 20th centuries only 0.1-0.3% of all marriages were contracted between first-cousins (average kinship coefficient 0.0001-0.0002). In genealogical search, however, a remote consanguinity (often beyond 3rd cousins) is frequently found especially in the rural areas and the true level of inbreeding is higher. In Finland, several autosomal recessive diseases are known to be enriched in the population. This unique spectrum of genetic diseases is sometimes called »the Finnish Disease Heritage». To study the implication of close consanguinity for these disorders, information on consanguineous marriages closer than second-cousins was collected from 808 families representing 24 different »Finnish» autosomal recessive disorders. The mean rate of first-cousin marriages was 1.6% (0-20%). Consanguinity (parents second-cousins or closer) was found in 4.2% of the families. For comparison, in 160 families representing three »non-Finnish» autosomal disorders the corresponding figures were 1.9% and 2.5%, respectively. Although these figures are high when compared to the general Finnish population, it can be concluded that close consanguinity is not a significant factor of Finnish genetic diseases.


2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Yuhai Zhao ◽  
Yuan Li ◽  
Ying Yin ◽  
Gang Sheng

Diagnostic genes are usually used to distinguish different disease phenotypes. Most existing methods for diagnostic genes finding are based on either the individual or combinatorial discriminative power of gene(s). However, they both ignore the common expression trends among genes. In this paper, we devise a novel sequence rule, namely, top-kirreducible covering contrast sequence rules (TopkIRs for short), which helps to build a sample classifier of high accuracy. Furthermore, we propose an algorithm called MineTopkIRs to efficiently discover TopkIRs. Extensive experiments conducted on synthetic and real datasets show that MineTopkIRs is significantly faster than the previous methods and is of a higher classification accuracy. Additionally, many diagnostic genes discovered provide a new insight into disease diagnosis.


Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 33-34
Author(s):  
Marwan Elbagoury ◽  
Ohoud F. Kashari

Rationale Around the globe, it is now understood that individuals with Rare genetic Diseases routinely face limitations to getting access to diagnosis. Plans have been created to improve the requirements of the patient's communities, including access to multidisciplinary care, and proposing new corrections or amendments to existing strategies. In the gulf region, numerous proposals have been established to tackle the diagnosis and management Rare genetic Diseases. Introduction and Background Rare genetic diseases are characterized as life-long, serious conditions that debilitate or compromise life. Almost 80% of Rare genetic diseases are diagnosed during the childhood. Absence of access to these assets affect patients and their families living with complex needs that may incorporate day in and day out observing, continuous serious physical and formative medicines, remaining in the training framework, and now and then costly strength meds1. The underlying etiology may stay obscure for many patients with rare genetic diseases despite multiple investigations. patients may be assigned an incorrect diagnosis and be referred to several specialties until a correct diagnosis can be made. A correct diagnosis of rare genetic diseases may impact not only the patient's care but may have further implications for management and/or counselling of family members as well2. Also, Early diagnosis leading to early treatment to prevent long-term damage. Global Landscape3 Rarity of diseases is most commonly defined based on prevalence and incidence within a jurisdiction, or in some cases by a combination of factors based on severity and the existence or feasibility of alternative therapeutic options. Globally, the following areas of focus aimed at improving the delivery of health care for the rare disease population: - Improve access to early diagnosis, timely intervention, coordinated care for rare genetic disease patients and developing referral pathways for rare genetic disease patients to facilitate efficient care deliver - Provide educational resources and knowledge exchange opportunities to health professionals to allow them to better identify, manage and treat rare disea - support integrated peer networks, patient organizations to ensure that rare disease patients, their family/caregivers and support them to make informed decisions about their condition. The importance of having working groups for Rare genetic Diseases in Gulf region 4 - Encourage improved coordination of care and access to particular information for rare genetic diseaseses. - Create a complete system services suppliers over Gulf states. Assets and Gaps analysis 1- Early Detection and Diagnostics 5 There are resources that assist the diagnostic capacity and early detection for rare genetic diseases. · Whole Exome sequencing are used mainly for research purposes, despite the fact that their use will reduced diagnostic odyssey. · Lack of the availability of testing is dependent on budget support in some hospitals. - Timely Access to Evidence-based care 6 - Family doctors may not be well equipped to meet the needs of patients with rare hematological genetic diseases, even after diagnosis. - Poor access supportive services for adult care. - Access to genetic counseling for patients and families outside major academic hospitals7. References 1. Sawyer, S. L. et al. Utility of whole-exome sequencing for those near the end of the diagnostic odyssey: time to address gaps in care. Clin. Genet.89, 275-284 (2016). 2. Undiagnosed Diseases Network Manual of Operations. (2018). 3. Richter, T. et al. Rare Disease Terminology and Definitions-A Systematic Global Review: Report of the ISPOR Rare Disease Special Interest Group. (2015). doi:10.1016/j.jval.2015.05.008 4. International Rare Disease Research Consortium& GUIDELINES Long version. (2013). 5. Clinical Handbook for Sickle Cell Disease Vaso-occlusive Crisis Provincial Council for Maternal and Child Health & Ministry of Health and Long-Term Care. (2017). 6. Therrell, B. L. et al. Current status of newborn screening worldwide: 2015. Seminars in Perinatology39, 171-187 (2015). 7. Stille, C. J. & Antonelli, R. C. Coordination of care for children with special health care needs. Current Opinion in Pediatrics16, 700-705 (2004). Figure Disclosures No relevant conflicts of interest to declare.


Author(s):  
Michael Snyder

What is a complex genetic disease? Although great strides have been made to identify single gene variants that have a strong causative effect for a particular disease (e.g., CFTR mutations for cystic fibrosis and HEXA mutations for Tay-Sachs disease), the...


1987 ◽  
Vol 21 (3) ◽  
pp. 592-608 ◽  
Author(s):  
Margaret I. Gradie ◽  
Danielle Gauvreau

This article examines the relationship between migration and genetic disease in the situation of the Saguenay region of Quέbec. This large population shows an elevated incidence of several genetic diseases. The process of migration, which created the population, is thought to be a major factor in determining the genetic structure of the contemporary population. Preliminary results suggest that although consanguineous marriages are not and never were frequent in the population, socially, kinship was important in determining migration and persistence, leading to a high level of genetic homogeneity today.


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