Automated prioritization of sick newborns for whole genome sequencing using clinical natural language processing and machine learning

Peterson, Bennet; Hernández, Edgar Javier; Hobbs, Charlotte A.; Jenkins, Sabrina Malone; Moore, Barry; Rosales, Edwin; Zoucha, Samuel; Sanford, Erica; Bainbridge, Matthew N.; Frise, Erwin; Oriol, Albert; Brunelli, Luca; Yandell, Mark

doi:10.1186/s13073-023-01166-7

Cited by 11 publications

(9 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…If this gap is not overcome, it will further deepen the inequities in access to NBS between different regions worldwide. Genetic studies are essential for the adequate diagnosis, management (i.e., selection of patients for specific treatment), and prognosis of IEiM patients, especially in the pediatric population and even more so in critically ill patients, allowing personalized medicine approaches [ 67 , 68 ]. These studies are also helpful for the establishment of the prognosis of those cases of MAA where different forms (mut 0 and mut - ) of the disease differently impact the patient survival [ 69 , 70 ].…”

Section: Discussionmentioning

confidence: 99%

A Review of Disparities and Unmet Newborn Screening Needs over 33 Years in a Cohort of Mexican Patients with Inborn Errors of Intermediary Metabolism

Ibarra-González,

Fernández-Lainez,

Vela-Amieva

et al. 2023

IJNS

View full text Add to dashboard Cite

Advances in an early diagnosis by expanded newborn screening (NBS) have been achieved mainly in developed countries, while populations of middle- and low-income countries have poor access, leading to disparities. Expanded NBS in Mexico is not mandatory. Herein, we present an overview of the differences and unmet NBS needs of a group of Mexican patients with inborn errors of intermediary metabolism (IEiM), emphasizing the odyssey experienced to reach a diagnosis. We conducted a retrospective observational study of a historical cohort of patients with IEiM from a national reference center. A total of 924 patients with IEiM were included. Although 72.5% of the diseases identified are detectable by expanded NBS, only 35.4% of the patients were screened. The mortality in the unscreened group was almost two-fold higher than that in the screened group. Patients experienced a median diagnostic delay of 4 months, which is unacceptably long considering that to prevent disability and death, these disorders must be treated in the first days of life. Patients had to travel long distances to our reference center, contributing to their unacceptable diagnostic odyssey. This study highlights the urgent need to have an updated, expanded NBS program with adequate follow up in Mexico and promote the creation of regional medical care centers. We also provide compelling evidence that could prove valuable to decision makers overseeing public health initiatives for individuals impacted by IEiM from middle- and low-income countries.

show abstract

Section: Discussionmentioning

confidence: 99%

A Review of Disparities and Unmet Newborn Screening Needs over 33 Years in a Cohort of Mexican Patients with Inborn Errors of Intermediary Metabolism

Ibarra-González,

Fernández-Lainez,

Vela-Amieva

et al. 2023

IJNS

View full text Add to dashboard Cite

show abstract

“…A recent study by Kingsmore et al . (31) showed that more HPO terms may not increase diagnostic yield, but that a more focused list of key terms may support analysis more effectively.…”

Section: Discussionmentioning

confidence: 99%

A panel-agnostic strategy ‘HiPPo’ improves diagnostic efficiency in the UK Genome Medicine Service

Seaby

Thomas

Hunt

et al. 2023

Preprint

View full text Add to dashboard Cite

Genome sequencing is now available as a clinical test on the National Health Service (NHS) through the Genome Medicine Service (GMS). The GMS have set out an analytical strategy that predominantly filters genome data on a pre-selected gene panel(s). Whilst this approach reduces the number of variants requiring assessment by reporting laboratories, pathogenic variants outside of the gene panel applied may be missed, and candidate variants in novel genes are largely ignored. This study sought to compare a research exome analysis to an independent clinical genome analysis performed through the NHS for the same group of patients. When analysing the exome data, we applied a panel agnostic approach filtering for variants with High Pathogenic Potential (HiPPo) using ClinVar, allele frequency, and in silico prediction tools. We then compared this gene agnostic analysis to the panel-based approach as applied by the GMS to genome data. Later we restricted HiPPo variants to a panel of the Gene Curation Coalition (GenCC) morbid genes and compared the diagnostic yield with the variants filtered using the GMS strategy. 24 patients from 8 families underwent parallel research exome sequencing and GMS genome sequencing. HiPPo analysis applied to research exome data identified a similar number of variants as the gene panel-based approach applied by the GMS. GMS clinical genome analysis identified and returned 2 pathogenic variants and 3 variants of uncertain significance. HiPPo research exome analysis identified the same variants plus an additional pathogenic variant and a further 3 de novo variants of uncertain significance in novel genes, where case series and functional studies are underway. When HiPPo was restricted to GenCC disease genes (strong or definitive), the same pathogenic variants were identified yet statistically fewer variants required assessment to identify more diagnostic variants than reported by the GMS genome strategy. This gave a diagnostic rate per variant assessed of 20% for HiPPo restricted to GenCC versus 3% for the GMS panel-based approach. With plans to sequence 5 million more NHS patients, strategies are needed to optimise the full potential of genome data beyond gene panels whilst minimising the burden of variants that require clinical assessment.

show abstract

“…Finally, AI can be used to automate the identification of patients who are likely to benefit from URGS, RGS, or RES. Machine learning, together with NLP of the EHR, has been used to develop classifiers that distinguish between NICU infants who have or have not historically received URGS, RGS, or RES 166 . As URGS, RGS, and RES are implemented in NICUs without prior experience, such tools will be important in achievement of high diagnostic rates.…”

Section: Increasing Use Of Artificial Intelligence (Ai) In Urgsmentioning

confidence: 99%

Rapid genomic sequencing for genetic disease diagnosis and therapy in intensive care units: a review

Kingsmore,

Nofsinger,

Ellsworth

2024

npj Genom. Med.

Self Cite

View full text Add to dashboard Cite

Single locus (Mendelian) diseases are a leading cause of childhood hospitalization, intensive care unit (ICU) admission, mortality, and healthcare cost. Rapid genome sequencing (RGS), ultra-rapid genome sequencing (URGS), and rapid exome sequencing (RES) are diagnostic tests for genetic diseases for ICU patients. In 44 studies of children in ICUs with diseases of unknown etiology, 37% received a genetic diagnosis, 26% had consequent changes in management, and net healthcare costs were reduced by $14,265 per child tested by URGS, RGS, or RES. URGS outperformed RGS and RES with faster time to diagnosis, and higher rate of diagnosis and clinical utility. Diagnostic and clinical outcomes will improve as methods evolve, costs decrease, and testing is implemented within precision medicine delivery systems attuned to ICU needs. URGS, RGS, and RES are currently performed in <5% of the ~200,000 children likely to benefit annually due to lack of payor coverage, inadequate reimbursement, hospital policies, hospitalist unfamiliarity, under-recognition of possible genetic diseases, and current formatting as tests rather than as a rapid precision medicine delivery system. The gap between actual and optimal outcomes in children in ICUs is currently increasing since expanded use of URGS, RGS, and RES lags growth in those likely to benefit through new therapies. There is sufficient evidence to conclude that URGS, RGS, or RES should be considered in all children with diseases of uncertain etiology at ICU admission. Minimally, diagnostic URGS, RGS, or RES should be ordered early during admissions of critically ill infants and children with suspected genetic diseases.

show abstract

Automated prioritization of sick newborns for whole genome sequencing using clinical natural language processing and machine learning

Cited by 11 publications

References 24 publications

A Review of Disparities and Unmet Newborn Screening Needs over 33 Years in a Cohort of Mexican Patients with Inborn Errors of Intermediary Metabolism

A Review of Disparities and Unmet Newborn Screening Needs over 33 Years in a Cohort of Mexican Patients with Inborn Errors of Intermediary Metabolism

A panel-agnostic strategy ‘HiPPo’ improves diagnostic efficiency in the UK Genome Medicine Service

Rapid genomic sequencing for genetic disease diagnosis and therapy in intensive care units: a review

Contact Info

Product

Resources

About