Rare Disease

Advancing Understanding
of Rare Disease

Annually, up to 10 percent of the nearly 4 million babies born in the US are hospitalized in an intensive care unit due to an underlying rare genetic disease. Without proper diagnosis and treatment, some such disorders can lead to permanent disability or even death.

Many rare genetic diseases are never seen by most physicians, as they affect very few children worldwide. This creates challenges in recognizing the condition and knowing how to treat it.

At RCIGM, we want to provide accurate information when a rare disorder is diagnosed to enable families and their healthcare teams to make informed decisions about treatment. 

Knowledge Generation

  • We identify new diseases.
  • We study the normal disease progression of the rare diseases we diagnose.
  • We evaluate treatments for rare disease, including trying medicines not previously used in children, and participating in research with drug companies to evaluate the efficacy of potential new therapies.

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Key Facts

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Publications

Orphanet J Rare Dis. 2021 Oct 23;16(1):446. doi: 10.1186/s13023-021-02048-0.

ABSTRACT

BACKGROUND: Extremely rare progressive diseases like Sedaghatian-type Spondylometaphyseal Dysplasia (SSMD) can be neonatally lethal and therefore go undiagnosed or are difficult to treat. Recent sequencing efforts have linked this disease to mutations in GPX4, with consequences in the resulting enzyme, glutathione peroxidase 4. This offers potential diagnostic and therapeutic avenues for those suffering from this disease, though the steps toward these treatments is often convoluted, expensive, and time-consuming.

MAIN BODY: The CureGPX4 organization was developed to promote awareness of GPX4-related diseases like SSMD, as well as support research that could lead to essential therapeutics for patients. We provide an overview of the 21 published SSMD cases and have compiled additional sequencing data for four previously unpublished individuals to illustrate the genetic component of SSMD, and the role of sequencing data in diagnosis. We outline in detail the steps CureGPX4 has taken to reach milestones of team creation, disease understanding, drug repurposing, and design of future studies.

CONCLUSION: The primary aim of this review is to provide a roadmap for therapy development for rare, ultra-rare, and difficult to diagnose diseases, as well as increase awareness of the genetic component of SSMD. This work will offer a better understanding of GPx4-related diseases, and help guide researchers, clinicians, and patients interested in other rare diseases find a path towards treatments.

PMID:34688299 | DOI:10.1186/s13023-021-02048-0

Genome Med. 2021 Oct 14;13(1):153. doi: 10.1186/s13073-021-00965-0.

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.

PMID:34645491 | DOI:10.1186/s13073-021-00965-0

Nat Commun. 2021 Sep 20;12(1):5529. doi: 10.1038/s41467-021-25515-5.

ABSTRACT

Inherited disorders of neurotransmitter metabolism are rare neurodevelopmental diseases presenting with movement disorders and global developmental delay. This study presents the results of the first standardized deep phenotyping approach and describes the clinical and biochemical presentation at disease onset as well as diagnostic approaches of 275 patients from the registry of the International Working Group on Neurotransmitter related Disorders. The results reveal an increased rate of prematurity, a high risk for being small for gestational age and for congenital microcephaly in some disorders. Age at diagnosis and the diagnostic delay are influenced by the diagnostic methods applied and by disease-specific symptoms. The timepoint of investigation was also a significant factor: delay to diagnosis has decreased in recent years, possibly due to novel diagnostic approaches or raised awareness. Although each disorder has a specific biochemical pattern, we observed confounding exceptions to the rule. The data provide comprehensive insights into the phenotypic spectrum of neurotransmitter disorders.

PMID:34545092 | DOI:10.1038/s41467-021-25515-5

J Pediatr. 2021 Sep 8:S0022-3476(21)00877-5. doi: 10.1016/j.jpeds.2021.09.005. Online ahead of print.

ABSTRACT

OBJECTIVES: To assess associations between maternal smoking and congenital heart defects (CHDs) in offspring.

STUDY DESIGN: We performed a retrospective case-control study using data for cases of CHD (n=8,339) and non-malformed controls (n=11,020) children from all years (1997-2011) of the National Birth Defects Prevention Study. Maternal self-reported smoking one month before through three months after conception was evaluated as a binary (none, any) and categorical (light, medium, heavy) exposure. Multivariable logistic regression was used to estimate adjusted odds ratios (aOR) and 95% confidence intervals. Stratified analyses were performed for septal defects according to maternal age, pre-pregnancy body mass index, and maternal race/ethnicity.

RESULTS: Multiple CHDs displayed modest associations with any level of maternal periconceptional smoking independent of potential confounders; the strongest associations were for aggregated septal defects (OR 1.5 [1.3-1.7]), tricuspid atresia (OR 1.7 [1.0-2.7]), and double outlet right ventricle (DORV) (1.5 [1.1-2.1]). TA and DORV also displayed dose-response relationships. Among heavy smokers, the highest odds were again observed for TA (aOR 3.0 [1.5-6.1]) and DORV (aOR 1.5 [1.1-2.2]). Heavy smokers ≥35 years old more frequently had a child with a septal defect when compared with similarly aged non-smokers (aOR 2.3 [1.4-3.9]).

CONCLUSIONS: Maternal periconceptional smoking is most strongly associated with septal defects, TA and DORV; the risk for septal defects is modified by maternal age.

PMID:34508749 | DOI:10.1016/j.jpeds.2021.09.005

Child Neurol Open. 2021 Aug 5;8:2329048X211030723. doi: 10.1177/2329048X211030723. eCollection 2021 Jan-Dec.

ABSTRACT

We present a case of a young child with a rare metabolic disorder whose clinical presentation resembled that of autoimmune myasthenia gravis. The differential diagnosis was expanded when autoantibody testing was negative and the patient did not respond to standard immunomodulatory therapies. Rapid whole genome sequencing identified 2 rare variants of uncertain significance in the SLC52A3 gene shown to be in compound heterozygous state after parental testing. Biallelic mutations in SLC52A3 are associated with Riboflavin Transporter Deficiency, which in its untreated form, results in progressive neurodegeneration and death. Supplementation with oral riboflavin has been shown to limit disease progression and improve symptoms in some patients. When the diagnosis is suspected, patients should be started on supplementation immediately while awaiting results from genetic studies.

PMID:34395718 | PMC:PMC8361551 | DOI:10.1177/2329048X211030723

Knowledge Generation

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Read more about this groundbreaking work.

Robert Wechler-Reva

PHD, Neuro-Oncology Program Director

Noted scientist Robert Wechsler-Reya, PhD, is also a professor and researcher at the Sanford Burnham Prebys Medical Discovery Institute (SBP) where he is focused on investigating the genes and nervous system signaling pathways that contribute to medulloblastoma, the most common malignant brain tumor in children.

News Features

October 22, 2020

Variety.com

Inside Our Child’s Battle With Mitochondrial Disease

“Despite a beautiful pregnancy and delivery with every prenatal screening and precaution taken, Evan was born with mitochondrial disease.” Lindzi Scharf shares a … Read More

October 14, 2020

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Lorem ipsum dolor sit amet, consectetur adipiscing elit. Praesent lobortis, est eget hendrerit rutrum, … Read More

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