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Rare Disease PHGKB

Specific PHGKB|Rare Diseases PHGKB|PHGKB

Last Posted: Sep 22, 2022
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Correspondence on “Cost-effectiveness of exome and genome sequencing for children with rare and undiagnosed conditions”
SD Grosse et al, Genetics in Medicine, September 21, 2022

The relative cost-effectiveness of rES and rGS should be informed by up-to-date evidence on costs and diagnostic performance and reflect specific clinical settings, meeting the needs of decision-makers in those settings. Published economic evaluations of GS should distinguish between the price and cost (value of resources used) of sequencing and suggested that the use of microcosting data could improve the accuracy of cost-effectiveness analyses from either the societal or health care perspectives.

Neurofibromatosis Type 1 and Risk of Skin Cancer
J Trinh et al, JAMA Dermatology, August 24, 2022

This study found increased odds of melanoma, BCC, and SCC in patients with NF1. Whole-exome sequencing has established NF1 as the third most frequently mutated gene in melanomas.3 About 12% to 18% of melanomas and 45% to 93% of desmoplastic melanomas harbor NF1 alterations.

Prevalence of Fabry disease-causing variants in the UK Biobank.
Gilchrist Mark et al. Journal of medical genetics 2022 8

Fabry disease is an X-linked lysosomal storage disorder resulting from deficiency of the alpha-galactosidase A enzyme leading to accumulation of globotriaosylceramide in multiple organ sites with prominent cardiovascular and renal involvement. Global prevalence estimates of Fabry disease based on clinical ascertainment range from 1 in 40?000 to 1 in 170?000. We aimed to determine the prevalence of Fabry disease-causing variants in UK Biobank.

Discovering monogenic patients with a confirmed molecular diagnosis in millions of clinical notes with MonoMiner.
Wu David Wei et al. Genetics in medicine : official journal of the American College of Medical Genetics 2022 8

We define a subset (4461) of OMIM diseases that have at least 1 known monogenic causal gene. We then introduce MonoMiner, a natural language processing framework to identify molecularly confirmed monogenic patients from free-text clinical notes. We show that ICD-10-CM codes cover only a fraction of monogenic diseases and that even where available, ICD-10-CM code?based patient retrieval offers 0.14 precision. Searching by causal gene symbol offers great recall but has an even worse 0.07 precision. MonoMiner achieves 6 to 11 times higher precision (0.80), with 0.87 precision on disease diagnosis alone, tagging 4259 patients with 560 monogenic diseases and 534 causal genes, at 0.48 recall.


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Disclaimer: Articles listed in the Public Health Knowledge Base are selected by the CDC Office of Public Health Genomics to provide current awareness of the literature and news. Inclusion in the update does not necessarily represent the views of the Centers for Disease Control and Prevention nor does it imply endorsement of the article's methods or findings. CDC and DHHS assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by CDC or DHHS. Opinion, findings and conclusions expressed by the original authors of items included in the update, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of CDC or DHHS. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by CDC or DHHS.

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