scholarly journals New Diagnostic Approaches for Undiagnosed Rare Genetic Diseases

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.

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.


2021 ◽  
pp. 153537022110400
Author(s):  
Haseeb Nisar ◽  
Bilal Wajid ◽  
Samiah Shahid ◽  
Faria Anwar ◽  
Imran Wajid ◽  
...  

Rare diseases affect nearly 300 million people globally with most patients aged five or less. Traditional diagnostic approaches have provided much of the diagnosis; however, there are limitations. For instance, simply inadequate and untimely diagnosis adversely affects both the patient and their families. This review advocates the use of whole genome sequencing in clinical settings for diagnosis of rare genetic diseases by showcasing five case studies. These examples specifically describe the utilization of whole genome sequencing, which helped in providing relief to patients via correct diagnosis followed by use of precision medicine.


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.


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.


Author(s):  
Ol’ga V. Kirpichnik ◽  
Ol’ga A. Yekimchik

The paper discusses one of topical problems, connected to a distress of a child being diagnosed with a genetic disease situation – parents’ coping with that. An attempt was made to determine what strategies and resources not only contribute to the parental coping with the situation of the child’s diagnosis, but also the subjective well-being of the parents? The authors present the results of narratives of native parents of children with Down syndrome (received from charity societies and open sources; n = 52). The emotional aspect of parents’ experience, their difficulties at the stage of recognising the diagnosis, coping strategies and resources involved in accepting process, and the parents` subjective well-being at the stages of recognising the diagnosis and the stage of the interview (after 1—12 years) are analysed. The Ronald Fisher's multifunctional angular transformation was used for analysing the differences. Mothers and fathers show no differences in the perception and assessment of difficulties at the stages of recognition of the diagnosis and the moment of the interview, but there are significant differences in the resources and strategies for coping with these difficulties. Features of difficulties at different stages, differences in the structure of resources and the intensity of coping strategies (especially among mothers) indicate the dynamics of experiencing the situation and adapting to it.


2021 ◽  
Vol 40 (5) ◽  
pp. 291-301
Author(s):  
Milena Mariani ◽  
Paola Cianci ◽  
Anna Cereda ◽  
Silvia Maitz ◽  
Marzia Giagnacovo ◽  
...  

Availability of genetic tests has remarkably increased in the last few years. The new technologies offer clinicians new diagnostic opportunities that enable to save time and money in the diagnostic path of patients with possible genetic disease. Also from a patient’s perspective the application of the new tests significantly improves what has been called “diagnostic odyssey”. For all these reasons it is absolutely important that paediatricians become aware of what can be offered to their patients as well as of the increased diagnostic potentialities but also of the well-known limits and possible doubtful results of these tests.


2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Ayse B. Kolemen ◽  
Enes Akyuz ◽  
Ali Toprak ◽  
Erdem Deveci ◽  
Gozde Yesil

Abstract Background The diagnosis of the rare genetic diseases has great importance in treating multisystemic conditions, preventing potential complications, and estimating disease risk for family members. The duration of obtaining genetic test results is varies. The demand to learn the diagnosis of a possible untreatable illness involves a struggle between uncertainty and a lifetime chronic disease. The current uncertainty of their child's condition and the long wait for a diagnosis may increase the parents' anxiety level and cause difficulties in the continuation of diagnostic procedures in some families. This study aimed to investigate the prediagnosis and postdiagnosis anxiety levels of parents who have a child with a rare genetic disease. Method The parents in this study, mothers or fathers, admitted their children to the Bezmialem Vakıf University Medical Genetics Clinic due to a suspected rare genetic disease (n = 40). Researchers created “The Sociodemographic Questionnaire” and used it to analyze the parents' sociodemographic status. In addition, they used the State-Trait Anxiety Inventory (STAI) to determine the anxiety levels of the parents. Results The state anxiety levels of parents decreased significantly after learning the diagnosis. However, there was no statistically significant decrease observed in trait anxiety levels. Conclusion Data from this study revealed that informing parents about their child's disease and properly explaining to them the expected difficulties might help to reduce their anxiety levels. Psychological support for parents is necessary to reduce their long-term stress, thus increasing the patient's compliance with treatment.


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.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Claudia C. Y. Chung ◽  
Jasmine L. F. Fung ◽  
Adrian C. Y. Lui ◽  
Marcus C. Y. Chan ◽  
Yvette N. C. Ng ◽  
...  

AbstractThe measurement of costs is fundamental in healthcare decision-making, but it is often challenging. In particular, standardised methods have not been developed in the rare genetic disease population. A reliable and valid tool is critical for research to be locally meaningful yet internationally comparable. Herein, we sought to develop, contextualise, translate, and validate the Client Service Receipt Inventory for the RAre disease population (CSRI-Ra) to be used in cost-of-illness studies and economic evaluations for healthcare planning. Through expert panel discussions and focus group meetings involving 17 rare disease patients, carers, and healthcare and social care professionals from Hong Kong, we have developed the CSRI-Ra. Rounds of forward and backward translations were performed by bilingual researchers, and face validity and semantic equivalence were achieved through interviews and telephone communications with focus group participants and an additional of 13 healthcare professional and university students. Intra-class correlation coefficient (ICC) was used to assess criterion validity between CSRI-Ra and electronic patient record in a sample of 94 rare disease patients and carers, with overall ICC being 0.69 (95% CI 0.56–0.78), indicating moderate to good agreement. Following rounds of revision in the development, contextualisation, translation, and validation stages, the CSRI-Ra is ready for use in empirical research. The CSRI-Ra provides a sufficiently standardised yet adaptable method for collecting socio-economic data related to rare genetic diseases. This is important for near-term and long-term monitoring of the resource consequences of rare diseases, and it provides a tool for use in economic evaluations in the future, thereby helping to inform planning for efficient and effective healthcare. Adaptation of the CSRI-Ra to other populations would facilitate international research.


2021 ◽  
Author(s):  
Joanna Kaplanis ◽  
Benjamin Ide ◽  
Rashesh Sanghvi ◽  
Matthew Neville ◽  
Petr Danecek ◽  
...  

Mutation in the germline is the source of all evolutionary genetic variation and a cause of genetic disease. Previous studies have shown parental age to be the primary determinant of the number of new germline mutations seen in an individual's genome. Here we analysed the genome-wide sequences of 21,879 families with rare genetic diseases and identified 12 hypermutated individuals with between two and seven times more de novo single nucleotide variants (dnSNVs) than expected. In most of these families (9/12) the excess mutations could be attributed to the father. We determined that two of these families had genetic drivers of germline hypermutation, with the fathers carrying damaging genetic variation in known DNA repair genes, causing distinctive mutational signatures. For five families, by analysing clinical records and mutational signatures, we determined that paternal exposure to chemotherapeutic agents prior to conception was a key driver of hypermutation. Our results suggest that the germline is well protected from mutagenic effects, hypermutation is rare and relatively modest in degree and that most hypermutated individuals will not have a genetic disease.


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