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

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.

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.
For three thousand years literature has attested to the ideal of an earth without infant mortality or parental grief 1 .However, infant mortality remains unacceptably high in the United States (5.6 deaths per 1000 births in 2022) 2 .Indeed, the US ranked thirty seventh in infant mortality among Organization for Economic Cooperation and Development countries in 2021 3 .While infant mortality was a little lower in San Diego County, California (3.7 deaths per 1000 births in 2022), genome sequencing showed that single locus (Mendelian) genetic diseases were associated with 41% of infant deaths between 2015 and 2022 in that county 4 .Furthermore, 31% of those genetic diseases had effective therapies 4 .Had those genetic diseases been diagnosed at birth and indicated treatments been initiated, infant mortality may have been decreased-by up to 17% in that setting.If the estimate that 5.3% of 3.7 million United States newborns will suffer from a genetic disorder is correct, genome sequencing has the potential to change outcomes of many infants 5,6 .

Background
First described twelve years ago, ultra-rapid genome sequencing (URGS) is a purpose-developed, clinical method for timely (2 day) diagnosis of genetic diseases in neonatal, pediatric, and cardiovascular intensive care units (NICU, PICU, CVICU) 7 .Since then, URGS has evolved into a scalable delivery system for molecular diagnosis of genetic diseases, metagenomic identification of pathogens, and therapeutic intervention in inpatient children (Fig. 1) [6][7][8][9][10][11][12][13][14][15] .Rapid genome and exome sequencing (RGS, RES) are variations of URGS, but with time-to-result of ten to fourteen days and, for the latter, sequencing limited to the ~1% of the genome that is exons of genes.Subsequent studies have shown that URGS, RGS, and RES are effective, universal, agnostic methods for single locus (Mendelian) genetic disease diagnosis [reviewed in 6].When timely diagnosis is combined with targeted therapeutic interventions, URGS, RGS, and RES are associated with changes in outcome for 18% of NICU and PICU children 6 .Herein we review progress in URGS over the first twelve years and explore prospects for genome-informed healthcare for children with genetic diseases.This review is intended to be complementary to a recent review of the role of genome sequencing in NICUs 6 .

Diversity of genetic diseases
As of January 2024, Online Mendelian Inheritance in Man (OMIM) listed 7476 single locus (Mendelian) diseases that are causally associated with 4876 genes 16 .This number increases by ~530 disease-gene dyads per year (Fig. 2) 17 .At that time, dbVar listed 27,109 distinct pathogenic or likely pathogenic structural genomic variations (SV, variants of length greater than 50 nucleotides) 18 .This number increases by ~3400 per year.The total number of unique genetic disorders represented by SV is not known.For example, dbVar lists 1088 pathogenic or likely pathogenic SV associated with Duchenne Muscular Dystrophy 19 .However, most ClinVar pathogenic and likely pathogenic SV lack sufficient phenotype information to be mapped to syndromes, precluding enumeration of associated disorders.Furthermore, ClinVar, dbVar, and OMIM overlap by listing classical chromosomal anomalies (Fig. 3).
Strictly speaking, not all of these are single locus disorders since our current representations of SV are simplified.They are informed by technologies such as short read sequencing, chromosomal microarrays, karyotyping, and fluorescent in situ hybridization.Newer technologies, such as long-read sequencing and optical mapping, are demonstrating that many SV are more complex than hitherto recognized 20,21 .Nevertheless, we distinguish these "single event", uncommon genetic diseases from common, complex disorders which etiologically reflect the aggregate of many common and rare variants together with other risk factors.Furthermore, not all single locus genetic diseases have Mendelian inheritance.The most common occurrence of genetic diseases in the US is de novoarising either in gametes or early in embryogenesis 22 .Single locus genetic disorders also include other non-Mendelian inheritance mechanisms such as imprinting disorders, mitochondrial genome disorders, retrotransposition, gene conversion events, and repeat expansion disorders [23][24][25] .

Estimated incidence of genetic diseases
The aggregate birth incidence and childhood prevalence of single locus genetic diseases is not definitively known.Verma and Puri suggest the aggregate incidence to be 5.3% 5 .They note that the aggregate incidence varies by race, ethnicity, and geography 5 .The incidence of recessive disorders is higher in cultures with frequent consanguineous marriages 26 .Two of the most common types of genetic disease, hemoglobinopathies and glucose-6-phosphate dehydrogenase deficiency, have a higher incidence in individuals whose ancestry is from regions affected in the past by severe falciparum malaria 26,27 .An alternative method for estimating the minimal prevalence of genetic diseases is the prevalence of clinically actionable secondary findings of genome or exome sequencing using the American College of Medical Genetics recommended lists.These range between 2% and 3%, albeit these prevalence estimates will increase as the recommended secondary findings list expands over time [28][29][30][31] .Data from two clinical studies suggests the incidence of single locus genetic diseases in regional NICUs to be ~15% 32,33 .Healthcare costs of children with genetic diseases are ~5 fold higher than other chronic diseases 34 .There are ~400,000 US NICU admissions per annum, costing over $17 billion per annum [35][36][37] .By extrapolation from California Department of Health statistics, there are ~200,000 US PICU admissions per annum.The incidence of genetic diseases in NICU, PICU and CVICU admissions is almost certainly higher than current estimates, since almost all published studies of URGS, RGS and RES have been limited to infants and children with suspected genetic diseases and to phenotype-related diagnostic findings.Further studies are needed to understand the true incidence of genetic diseaseswhich will inform the optimal scope of testingparticularly in NICU, PICU and CVICU patients who are not currently suspected of having genetic diseases.

Diagnostic ultra-rapid genome sequencing
Here we define diagnostic URGS and RGS as clinical-grade methods that identify all major types of DNA variation in at least 90% of the nucleotides of an affected patient with at least 95% accuracy.URGS corresponds to methods that consistently return a diagnostic result within 3 days of sample receipt, and RGS and RES within 10 days.RES differs in that DNA variation identification is limited to exons and nucleotides near exon-intron boundaries, leading to a slightly lower diagnostic yield 38,39 .The introduction of new sequencing and informatic technologies has enabled the speed record for URGS to decrease with time, from 48 h in 2012 to 7 h in 2022, albeit such records featured research rather than clinical methods (Fig. 2) 7,9,12,14,[40][41][42] .URGS has very recently become technically possible in 90 min, albeit limited to tumor classification 43 .The median time for return of a provisional diagnostic result of URGS in routine clinical operation is tracked monthly at our Institute, and averages ~36 h.

URGS methods
Clinical diagnostic URGS and RGS currently have seven steps 12,14 .First, high molecular weight genomic DNA is isolated from proband and parental samples, if the latter are available and provide consent.While many sample types are amenable to URGS, blood and dried blood spots are the two most common types.Genomic DNA includes both the nuclear genome, mitochondrial genome, andif the newborn has suspected sepsispathogen genomes.The second step is conversion of genomic DNA into a format compatible with sequencing (library preparation).This involves random fragmentation of DNA, end-repair, and ligation of adapter sequences.In URGS these steps may be combined and take about 1 h 14 .Third, nextgeneration sequencing is performed.Currently most URGS uses Illumina "short read" (SR) sequencing-by-synthesis (SBS, Illumina, 11-24 h) although nanopore "long read" (LR) strand sequencing (Oxford Nanopore) is starting to be used because it enables real-time sequence analysis, generates much longer contiguous haplotypes, and detects 5-methyl cytosine ("methylation status", which is relevant for diagnosis of imprinting disorders or detection of specific DNA methylation episignatures of genetic diseases) 12,14,[40][41][42][43][44][45][46] .Fourth the sequence fragments (reads) are mapped to a reference human genome and ~5 million variants are identified and genotyped (30 min).For metagenomic pathogen detection, reads are also mapped to a collection of pathogen genomes 13,47,48 .Fifth, each variant is annotated with results of a batch of over twenty automated software tools and variants (or variant diplotypes) are rank ordered in terms of predicted pathogenicity (20 min) 12,14 .Sixth, the phenotypes observed in the affected child are matched to those of all known genetic diseases and a comprehensive, rank ordered differential diagnosis is determined 12,14 .Seventh, the results are interpreted according to guidelines developed by professional societies (such as the American College of Medical Genetics and Genomics, ACMG).This is performed manually by experts (up to 100 variants per case, 10 h), with artificial intelligence (no variant limit, 40 min), or with both.When available, trio evaluation enables facile identification of variants that occurred de novo and, in recessive disorders, whether heterozygous variants are in cis or in trans in probands which results in a slightly higher diagnostic yield when trios are available 49 .
Effective use of URGS, RGS, and RES in critically ill children requires numerous pre-test and post-test steps, leading to the use of the term Rapid Precision Medicine to describe the healthcare delivery system of which URGS, RGS, or RES are a part 6,14 .

Diagnostic utility of URGS
Since the initial description of URGS in 2012, more than 44 studies of the diagnostic utility of URGS, RGS, or RES have been published (Table 1) 7,12,31,32,38,39,48, . Thesestudies were performed in 12 countries and in 3609 infants and children.The enrollment criteria for these studies varied (Table 1).Almost all were critically ill inpatient children.Most were NICU infants or older PICU children.Almost all were suspected of having genetic diseases or had diseases of unknown etiology at time of test order.A suspected genetic disease is defined as symptoms, signs, or abnormal laboratory tests observed in an affected individual that matches one or more genetic diseases.A disease of unknown etiology is defined as symptoms, signs, or abnormal laboratory tests observed in an affected individual for which the root cause, such as a molecular diagnosis, is unknown.The definition of genetic disease diagnosis was almost always in agreement with professional society guidelines, although a few studies included suspicious variants of uncertain significance (those for which the associated disorder was a good fit with the child's observed phenotypes) 72,84 .The weighted average diagnostic rate was 37% (range 19%-83%, Table 1).The study designs varied widely.Most were prospective research cohort studies.One study aligned RGS reads to reference pathogen genomes as well as the reference human genome, enabling metagenomic diagnosis of infectious diseases 38 .As has been observed in case reports, pathogens were identified in 6 (3%) of 202 infants, each of whom had symptoms of sepsis, and guided antibiotic treatment 13,38,47 .Since sepsis is suspected in many NICU infants at time of admission, the addition of this simple additional bioinformatic step is likely to become generally adopted.
Two studies were randomized controlled trials (RCT) 32,52,70,71 .The Newborn Sequencing in Genomic Medicine and Public Health (NSIGHT) RCT compared rapid genome sequencing (RGS) with standard of care testing in NICU and PICU infants aged <4 months with suspected genetic diseases 52 .The primary endpoint (rate of genetic diagnosis within 28 days of enrollment) was met, with 31% in RGS group and 3% in controls.The median age at diagnosis was less in the RGS group (25 days) than in controls (130 days), and median time to diagnosis was less in the RGS group (13 days) than in controls (107 days).The study was terminated early due to loss of equipoise.A meta-analysis published in 2018 reported diagnostic genome sequencing [(41% diagnosis) and exome sequencing (36% diagnosis) to be superior to chromosomal microarrays (10% diagnosis) 49].Meta-analysis also showed that the likelihood of diagnosis was significantly greater for trio testing than singletons (odds ratio 2.04) 49 .A second metaanalysis of the utility of RGS and RES in 2022 reported diagnostic rates of 37% and 50%, respectively 86 .The NSIGHT2 RCT compared RGS with RES in infants in ICUs with disorders of unknown etiology 32,70,71 .Forty six percent of NICU admissions were eligible for enrollment in NSIGHT2, a much greater proportion than in other studies.As a result, however, the diagnostic rate was less ( ~20%) and the study was underpowered to test the hypothesis that RGS was associated with a higher rate of genetic disease diagnosis than RES.
Two studies had crossover designs in which all enrolled infants received two interventions.In GEMINI, infants received both RGS and a rapid gene panel test 72,83 .In the China Neonatal Genomes Project, infants received both RGS and RES tests 38 .RGS demonstrated superiority in both studies.The diagnostic yield of RGS in GEMINI was 49%, compared with 27% with the rapid gene panel test 83 .In the Chinese study, the diagnostic yield of trio-RGS was higher than that of proband-only clinical RES (36.6% vs 20.3%, respectively), and the median turnaround time for trio-RGS (7 days) was faster than that of proband-only clinical RES (20 days) 38 .
With the cutoff of 3-day time to result, only seven studies evaluated the diagnostic utility of URGS 7,12,67,69,73,78,85 .In 356 children it was 48%, which was higher than the remaining studies of RGS or RES (36%).There are two likely reasons for this difference.Firstly, URGS is reserved for infants and children with the most severe illnesses and in whom there is greater likelihood that results will inform substantial changes in caresuch as severe metabolic derangement, cardiac dysrhythmias, hypotonia, and drugresistant seizureswhich may have higher diagnostic yield.Secondly, URGS is more likely to be used as a first-tier test which also increases diagnostic yield compared with use after, for example, a negative chromosomal microarray or gene panel test.

Clinical utility of URGS
Thirty nine of the 44 studies of the diagnostic utility of RGS, URGS, or RES also evaluated the proportion of children who received changes in management upon return of results (Table 1) 12,32,38,48,[50][51][52][53][54][55][56][57][58][59][60][61][62][63]65,[67][68][69][70][71][72][73][74][75][76]78,79,[81][82][83][84][85] . Definitions of changs in management varied between studies, but were usually changes in surgical, dietary, drug, and device interventions.Inclusion of changes in diagnostic testing and subspeciality consultation were variable.Changes in genetic counseling were not included.In 2,858 infants and children the weighted average rate of change in management was 26% (range 7% − 63%).With the cutoff of 3-day time to result, six studies evaluated the clinical utility of URGS (Table 1).In 352 children it was 37%, which was higher than the remaining studies of RGS or RES (25%).This was in accord with the reasoning mentioned above for a higher diagnostic rate for URGS.In addition, it is particularly impactful in terms of clinical management to have results returned to the ordering physician prior to patient discharge as discharge prior to diagnosis will result in some patients lost to follow-up and all patients' future clinical engagements to be delayed.
URGS is predicated on the assumption that the clinical utility of a genetic disease diagnosis during an ICU admission is inversely proportional to the time to result.URGS is associated with a greater proportion of results returned before NICU discharge or death than RES or RGS 32 .Sixty days after enrollment, one study found that twice as many infants who received clinical genome sequencing results in 15 days (early) had changes in management relative to those who received results in 60 days 76 .
Several studies measured rates of change in management following negative results, in addition to positive results.NSIGHT2 found that clinicians perceived negative results to be useful or very useful in 72% of cases (versus 93% with positive results) 70,71 .That study also found that negative tests changed management in 16% of cases (versus 63% with positive results).The Australian Genomics Acute Care (AGAC) study reported that 11% of negative results influenced clinical management (versus 76% with positive results) 67 .Why negative results change management requires an explanation.Children with a suspected genetic disease may have had additional tests ordered or may have had decisions with regard to interventions that are impacted by that disease.While a negative result cannot completely rule out a genetic disorder it does greatly reduce its likelihood.A negative comprehensive genetic test, like URGS, decreases the likelihood of having any genetic disorder that is within the differential diagnosis.An example from our experience was a child with end-stage cardiomyopathy in whom a negative URGS led to listing for heart transplant.Prior to testing there was concern that a genetic cause of heart failure may have contraindicated transplant.Furthermore, Reanalysis of URGS, RGS, and RES is starting to occur commonly in patients with negative results or with findings that do not fully explain a child's illness.Reanalysis is typically performed upon the appearance of new disease features or when sufficient time has elapsed for enhancements in diagnostic sensitivity to have occurred.The incremental yield of reanalysis is 1-15% and annual reanalysis has been suggested as a possible best practice in consenting patients [87][88][89][90] .
Three studies reported implementation research.AGAC reported implementation of ultra-RES (3-day time to results) in 108 critically ill children with suspected monogenic conditions in 12 hospitals 67 .The diagnostic rate was 51% and management was influenced by results in 44%.Project Baby Bear was a payor funded, prospective, real-world, quality improvement project of URGS in the regional ICUs of five California tertiary care children's hospitals 73 .The participants were 184 acutely ill Medicaid beneficiaries aged <1 year and within one week of hospitalization, or who had just developed an abnormal response to therapy.Most infants were from underserved populations.URGS (3-day time to results) met two prespecified primary outcomes-changes in medical care reported by physicians and changes in the cost of care.A molecular diagnosis was made in 40% of infants and results led to changes in care in 32% 73 .Project Baby Deer evaluated implementation of URGS in 89 children in NICUs and

Cost and cost effectiveness of URGS
While the cost of research grade genome sequencing consumables at highest batching and throughput has declined to as little as $200 per 30-fold genome sequence (Fig. 2), the cost of diagnostic URGS and RGS has decreased only threefold in that period (to ~$7000 for a singleton, 3-day clinical test).As of December 2023, the cost of URGS consumables remains ~$1800 per genome because they are optimized for speed.The consumables used for RGS are less expensive (~$750 per sample) but have longer run time and require sample batching.A delay of several days to accrue a batch of samples is incompatible with URGS.Consumable cost of URGS and RGS are about to change since multiple new sequencing platforms were introduced in 2022-2024 that are less costly, optimized for speed, and do not require batching delays.Expert manpower is the largest component of current URGS, RGS, and RES cost, particularly for bioinformatics, software engineering, interpretation, reporting, quality assurance and regulatory compliance.The cost of interpretation does not differ for singleton and trio testing, nor for URGS and RGS.Obviously, consumable cost is three-fold higher for trio than singleton testing.Software and computation cost for URGS is ~$500 per family.Diagnostic URGS and RGS are currently performed at low volumes (less than 1000 families per year per center).As a result, they have not yet benefitted from scaling efficiencies.The falling cost of consumables, gradual replacement of manual interpretation with artificial intelligence, and scaling efficiencies following from broader adoption in light of reimbursement by payors will decrease the cost of URGS and RGS 12,14,91,92 .However, broad use of artificial intelligence and ascent of the adoption curve will likely take 3 years, at which time a cost of diagnostic URGS-as currently performedof ~$2500 is likely.As noted below, however, there is much potential for technological improvement in URGS that will both lead to increased diagnostic yield and rate of change in management and to cost.Ten studies have evaluated the cost effectiveness of URGS and RGS, of which nine with similar methodology are shown in Table 2 6,53,73,80,82,83,[93][94][95] .Based on a median cost per proband tested of $9239 (range $6300-$16,063), the cost per diagnosis was $23,602 (median, range $14,082-$37,480).Assuming the current cost of URGS test ($7,000), the cost per diagnosis would be $17,500.The final study, which used different methods based on population estimates, found a similar cost per diagnosis of $24,873 (based on an RGS cost of $12,188) 96 .The cost per diagnosis was also evaluated by two control methods (Table 2).It was $14,515 per diagnosis by chromosomal microarray and karyotyping ($1888 cost per proband) and $24,074 per diagnosis by a next-generation sequencing-based panel test ($6,500 per proband) 80,83,97 .It should be noted that while chromosomal microarray and karyotyping are less expensive per diagnosis than URGS or RGS, the associated rate of change in management was one fifth that of URGS or RGS (Table 2).
Eight of the nine studies used specific disease case-based modeling of actual cost versus counterfactual cost 6,53,73,80,82,[93][94][95] .The median cost savings per child tested, net of test cost, was $14,265.One of these studies compared cost in a cohort receiving RGS with a cohort receiving chromosomal microarray and karyotyping, was an outlier with $100,440 net savings per child tested 80 .Assuming the current cost of URGS test ($7000), the median cost savings per child tested was $16,504.Two of the studies were implementation research undertaken to inform policy 73,82 .Project Baby Bear, discussed above, found that URGS in 184 Medicaid infants in California Children's Services accredited level four NICUs was associated with $6294 net savings per child tested 73 .Project Baby Deer, also discussed above, found that RGS in in NICUs and PICUs of five community hospitals and two children's hospitals in Michigan was associated with $4,155 savings per child tested 82 .Three studies that evaluated URGS found median net cost savings of $17,243 per child tested 73,94,95 .Given the increasing per diem costs of care in NICUs and PICUs, it is likely that current cost savings per child tested are greater than these estimates.
As noted above, the clinical utility of a genetic disease diagnosis during an ICU admission has been reported to be inversely proportional to the time to result 32,76 .Three studies modeled the impact of time to result of URGS on cost effectiveness 6,73,95 .Maximal cost savings were apparent with 3-day time to result.Cost savings were less at 7-days, and less again with 14-day time to result.Efficacy of URGS or RGS varies with time from admission to test order and from order to reporting as well as by presentation, disease severity, and rate of progression.Time to result is inversely proportional to test cost, while length of an ICU stay is directly proportional to healthcare expenditures.As supported by the findings of the NSIGHT RCT (32) and Project Baby Bear (73), it is reasonable to expect more rapid diagnostic results to have higher impact on improving both clinical outcomes while simultaneously reducing overall healthcare costs.Accordingly, further studies are needed to define the ideal cost:speed ratio of URGS in high acuity patients to optimize for both outcome improvements and healthcare expenditures.

Guidelines for clinical use of URGS in the molecular diagnosis of genetic diseases
Diagnostic URGS is performed in the US in genetic laboratories accredited under the Clinical Laboratory Improvement Amendments (CLIA, 1988)  and by the College of American Pathologists (CAP) and individual states.CAP performs proficiency testing of laboratories performing URGS.No US Food and Drug Administration-approved tests for RGS or URGS are available currently.CAP, ACMG and the Association for Molecular Pathology (AMP) have issued detailed guidance to diagnostic laboratories regarding genome sequencing, bioinformatics, and interpretation and reporting of single and polynucleotide substitution and insertions and deletion variants, copy number variants, and structural variants identified by genome or exome sequencing [98][99][100][101][102] .
The ACMG issued a 2021 practice guideline in 2021 recommending firstor second-tier diagnostic genome or exome sequencing for all individuals with congenital anomalies, developmental delay, or intellectual disability 103 .The National Society of Genetic Counselors issued a practice guideline in 2022, recommending first-tier diagnostic genome or exome sequencing for all individuals with unexplained epilepsy 104 .As yet there are no professional society practice guidelines for URGS, RGS, or RES for inpatient children.

URGS coverage policies and test reimbursement
The United Kingdom (UK) released a coverage policy for rapid diagnostic genome sequencing in all inpatient children with suspected genetic diseases in 2019 6 .Pediatricians in the National Health Service (NHS) in England and Wales can order a rapid diagnostic genome for any child that they suspect may benefit.The NHS plans to supplement this with URGS in selected children.
Blue Shield of California was the initial US payer with a coverage policy and reimbursement rate for URGS and RGS in NICU and PICU children in 2019 105 .It has since been endorsed by the Blue Cross Blue Shield Association and adopted by plans federally and in Hawaii, Louisiana, Michigan, Mississippi, Western and Northeastern New York, Idaho, Florida, and New Jersey [106][107][108][109][110][111][112][113][114] .Recently United Health Group and Cigna have issued coverage policies for RGS, but their application in the inpatient setting has not yet been demonstrated 115,116 .
In 2021, Michigan was the initial state with a Medicaid coverage policy and reimbursement rate for inpatient RGS separate from the Diagnosis Related Group (DRG) payment using Current Procedural Terminology (CPT) codes [81,425 and 81,426 ($4166 singleton, $8652 trio) and 0094U ($6278 singleton, $10,764 trio) 117,118].In large measure this policy was issued in response to the results of the previously described project Baby Deer 82 .In 2022 − 2024, Louisiana, Minnesota, Florida, Arizona, Utah, and Georgia issued similar coverage policies and reimbursement 117,118 .In 2022, California, Oregon, and Maryland issued similar coverage policies but without reimbursement separate from the DRG [119][120][121] .California's policy followed legislative action in response to the results of project Baby Bear 73 .Since DRG-related Medicaid payments to hospitals generally cover 90% − 93% of costs, the absence of a payment apart from the DRG in California has not led to an increase in clinical use of URGS and RGS 122 .
These coverage policies have identified the indications for URGS and RGS in inpatient children.The policies differ regarding whether infants or all children are covered beneficiaries and whether they must be in a NICU, PICU, or inpatient.In general, however, they are aligned.The Michigan Medicaid policy states that RWGS (or URGS) is medically necessary when all the following apply 123,124

Future prospects for URGS
URGS has evolved rapidly in the twelve years since its initial description.Several recent advances have the potential to increase the diagnostic and clinical utility of URGS in addition to reducing cost and turnaround time.

New URGS platforms and innovations
Paired, short-read (100 or 150 nucleotides (nt)) RGS and URGS (PSRGS), using sequencing-by-synthesis (SBS, Illumina) has been the mainstay technology for diagnostic URGS worldwide since initial description in 2012 7 .SBS was initially performed on the HiSeq 2500 in rapid run mode, followed by SP, S1, and S2 flowcells on the NovaSeq 6000 instrument with fastest time of 13.5 h (Fig. 2) 7,9,12,14,40 .During the last twelve months, however, the landscape of URGS technology has been transformed.In SBS, basecalling occurs after the URGS run ends (~20 h).In contrast, URGS with the Oxford Nanopore Promethion calls bases "live" during runs, as DNA molecules pass through nanopores at a speed of 400 nt/sec.By performing URGS on 48 Promethion flowcells simultaneously, diagnostic URGS can be performed in 7 h (Fig. 2) 41,42,125,126 .The most recent Illumina SBS platform, the NovaSeq X Plus, together with new SBS chemistry and 10B flowcells enables 20 URGS per 24-h run at a singleton, 40X consumable cost of $364 per individual.At the same time, Complete Genomics introduced the DNBSEQ-T7 instrument that enables 48 40X URGS in 24 h at a consumable cost of $200 and with similar sequence quality as SBS.New genome sequencing platforms from Ultima Genomics, Singular Genomics, and Element Biosciences have similar potential to reduce the cost or improve the scalability of URGS.For example, the Element Biosciences AVITI platform enables two 40X RGS in 38 h at a consumable cost of $240.
New bioinformatics pipelines and reference human genome sequences also have the potential to increase the diagnostic yield of URGS.The new human reference GRCh38 corrects ~1.5% of SNV and ~2.0% of indels that are incorrectly identified in GRCh37 since they lie within complex, discordant regions (DISCREPs) containing segmental duplications, patch sequences, and 109 Mb of alternate haplotypes [127][128][129] .GRCh37 DISCREPS include eight genes that cause Mendelian diseases.A recent telomere-totelomere reference genome, CHM13, has further quality improvements that reduce SNV, indel and SV errors in 22 Mb of GRC38 DISCREPS, including ~270 complex medically relevant genes [130][131][132][133] .The full potential of these https://doi.org/10.1038/s41525-024-00404-0Review article npj Genomic Medicine | (2024) 9:17 reference genomes to increase diagnostic yield requires use of the latest generation of read alignment and variant identification software, such as the Illumina DRAGEN v4.2, which uses machine learning and graph theory to map reads to alternate haplotypes in GRCh38 that differ in minority populations 127,128 .
One shortcoming of Oxford Nanopore LRGS is imprecision in identification of homopolymer insertion-deletion nucleotide variants (indels).Whereas PSRGS has indel F1 scores of 99.7%, that of Oxford Nanopore LRGS is 87.8%.Accurate identification of indels is critical for URGS and RGS, since these variants often lead to frame shifts at translation that are disease-causing.Excluding homopolymer indels, however, Oxford Nanopore LRGS has an F1 score of 98.9%.
It should be noted that these new platforms and capabilities, while very exciting, remain limited to research studies.In contrast to paired, short read, URGS and RGS, they have not yet been validated for clinical use in CLIA/ CAP accredited diagnostic laboratories.

Increasing use of artificial intelligence (AI) in URGS
AI is gaining broad interest for medical interpretation in areas as diverse as nuclear medicine imaging, echocardiography, ultrasonography, retinal imaging, dermatology, and histopathology [144][145][146][147][148][149][150][151][152][153] .AI provides information collection, integration, analysis, and interpretation capabilities that are many orders of magnitude greater than the human brain.With appropriate training, AI applications can attain performance in specialized interpretive tasks that equals that of medical specialists with decades of experience.Furthermore, AI can provide greater standardization and reproducibility than human experts.
URGS is well suited for AI since inputs and outputs are digitized (genotypes, phenotypes, gene-disorder dyads, diagnostic findings), large training datasets are becoming available, and variant interpretation has been codified as Boolean operators 12,14,91,154,155 .The initial applications of AI in URGSbasecalling, alignment, and variant identification (primary and secondary analysis)are now well validated and universally employed 12,14,91,154,155 .Further gains in these AI applications are anticipated, both to improve performance, particularly for newer sequencing platforms, and to incorporate pangenome references and genome assemblies 133,156,157 .Four recent additional applications of AI in URGS will be briefly reviewed.The first is Natural Language Processing (NLP) of Electronic Medical Records (EMR) to provide deep phenotypes to broaden the scope of diagnostic interpretation of URGS 12 .EMRs, when extracted in controlled vocabularies, provide digital phenotype information.Traditionally, diagnostic interpretation of URGS was limited to a few patient phenotypes that were manually entered at time of order as Human Phenotype Ontology terms.The depth of phenotype entry varied between physicians and phenotype choice was biased by physician assessment of their clinical importance and relevance to a working differential diagnosis.Such sparse phenotyping limited the scope of analysis and interpretation since primary findings are genotypes that map to disorders that partially match the entered phenotypes, and diagnostic test reports are necessarily incomplete with regard to secondary or incidental findings.In one recent study of URGS, NLP identified 27-fold more phenotypic features than manual entry, including 5 times as many phenotypes that matched the diagnosed disorder in affected children than the phenotypes used in manual interpretation 12 .We recently found that NLP increased the analytic performance of phenotype extraction fivefold (from an F 1 score of 16% by manual entry to 75%).The full capabilities of NLP are only starting to be examined in URGS.NLP can also identify negated phenotypes (which is important for pathognomonic clinical features of disorders), quantitative phenotype modifiers (e.g.phenotype frequency or severity), and longitudinal dynamics of phenotypes (for assessment of causality).Furthermore, NLP can explore the context of phenotypes within the EMR, which can help disambiguate meaning.For example, it is important to distinguish phenotypes mentioned in past medical history from those mentioned in family history.In newborns it is important to distinguish maternal and infant phenotypes.In the future, NLP can be utilized together with Boolean operators or AI to optimize quantitative comparisons of the goodness of fit of observed and expected phenotypes specifically for URGS in critically ill inpatient children.
The second application of AI in URGS is to automate routine diagnostic interpretation 12,14,91,92,154,155,[158][159][160] .Current manual interpretation software systems provide over twenty annotations for each variant.Several of these annotations are already based on machine learning tools.In addition, annotated variants (or variant diplotypes) are rank ordered by machine learning for predicted pathogenicity.Furthermore, the entered phenotypes are matched to those of all known genetic diseases using machine learning to https://doi.org/10.1038/s41525-024-00404-0Review article npj Genomic Medicine | (2024) 9:17 yield a comprehensive, rank ordered differential diagnosis.AI-based diagnostic interpretation goes one step further, performing additional Bayesian inference to associate each diplotype with a diagnostic score.One such tool (GEM, Fabric Genomics) correctly ranked over 90% of the causal genes among the top or second candidate and prioritized for review a median of 3 candidate genes per NICU infant diagnosed with a genetic disease 91 .Another tool correctly selected the causal diplotype in 97% of manually analyzed positive cases 158 .The initial use of AI-based interpretation of URGS will be to minimize laboratory director manual effort in ~90% of cases by short-listing the top candidate diagnoses together with the supporting evidence.In such cases it is possible to reduce laboratory director effort about tenfold 14,40,91,92 .In the remaining outlier or edge cases, manual interpretation will continue to be required.
The true positive and negative predictive value (PPV, NPV) of URGS, RGS, and RES results have not yet been adequately studied.Such studies are technically difficult since they require long-term follow up of cases.In the future, studies by the Undiagnosed Diseases Network (UDN) and increasing use of other 'omics platforms for functional confirmation of molecular diagnoses should be informative 161,162 .Prior studies by the UDN have not addressed this question since their experience predates broad use of URGS, RGS and RES.It will also be important to compare the PPV and NPV of manual and AI-assisted interpretation.One challenge the AI field has struggled with is gold standard comparisons.Prospective comparisons of AI and manual methods are particularly needed.
The third application of AI in URGS is clinical decision support for therapeutic interventions following return of a likely genetic disease diagnosis 14,163,164 .Currently management guidance requires subspecialist or superspecialist consultation, which invokes delays in implementation.This is particularly true for ultra-rare genetic diseases.A barrier to implementation of precision medicine for genetic diseases is that evidence for effectiveness of most therapeutic interventions is largely limited to case reports and small case series.As URGS becomes more widely used, results will increasingly be returned to hospitals lacking a full complement of pediatric subspecialists, genetic counselors, and to pediatricians who are unfamiliar with the diagnosed disorders, invoking increased delays.This gap in physician knowledge is also increasing because of a rapid increase in the number of investigational new drug applications and approvals for new gene-based therapeutics (Fig. 2) 165 .Recently several groups have described AI-assisted clinical decision support tools for therapeutic interventions for rare genetic diseases 14,165 .
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.With appropriate training, generative AI can also be used to alleviate the burden of pre-and post-test genetic counseling 167,168 .Further work is needed to define best practices for genetic counseling in high acuity settings.
As noted for sequencing technology innovations, the clinical utility of these AI tools has not been broadly evaluated in prospective clinical studies.Considerable further comparative studies of AI and manual methods are needed.In summary, however, the use of AI has the potential to improve scalability and standardization of URGS and genome-informed care and to reduce cost, time-to-intervention, and geographic disparities 169 .

Conclusion
There are ~10,000 currently known single locus (Mendelian) genetic diseases.Collectively they are a leading cause of hospitalization, ICU admission, mortality, and healthcare cost in infants and children.However, the true incidence of genetic diseases among infants and children admitted to intensive care units remains unknown.Initially described in 2012, URGS is a purpose-developed, clinical method for timely diagnosis of almost all genetic diseases in high acuity NICU, PICU and, CVICU patients.In 44 studies of rapid genomic sequencing, 37% of children in ICUs with diseases of unknown etiology or with suspected genetic disorders received a genetic disease diagnosis.In 39 clinical utility studies, rapid genomic sequencing changed management in 26% of children tested.In nine cost effectiveness studies, rapid genome sequencing led to $14,265 in net cost savings per child tested.URGS outperformed rapid genome or exome sequencing in these studies with 49% rate of diagnosis and 37% clinical utility.These metrics are expected to improve as URGS methods evolve, test costs decrease, and testing is implemented within precision medicine delivery systems attuned to the needs of neonatologists and intensivists.The evidence for clinical utility and cost effectiveness is adequate to conclude that diagnostic URGS should be considered in all infants and children with diseases of uncertain etiology at time of ICU admission.Clinical URGS is currently performed in less than 5% of the ~200,000 infants and children who fit the enrollment criteria of these research studies.The major barriers to broad implementation of diagnostic URGS are under-recognition of the possibility of genetic diseases by physicians, limited or absent reimbursement, inpatient barriers to test ordering, and current formatting of URGS as a test rather than within a rapid precision medicine delivery system attuned to the needs of hospital physicians, such as neonatologists and intensivists.Little implementation science has yet been done to optimize the clinical utility or outcomes associated with URGS.The gap between actual and optimal outcomes in critically ill children with genetic diseases is currently increasing since growth in testing lags growth in the number of children who would benefit because of newly approved therapies for these diseases.In five years, it is anticipated that there will be effective treatments for at least 1000 genetic diseases and diagnosis by URGS will be available within one day nationwide at a cost of $2500.It is also anticipated that URGS has the potential to reduce childhood mortality in the US significantly within 5 years.
The true incidence of genetic diseases among infants and children admitted to ICUs remains unclear.Therefore, the optimal breadth of use of URGS is uncertain.For example, there is a need for clinical utility and cost effectiveness studies of URGS in community hospital ICUs, in general beds in children's hospitals, and in critically ill children who are not suspected of having a genetic disease.
The maximal diagnostic yield and clinical utility of URGS are uncertain.Technical advances in URGS, some of which were reviewed here, have the potential to double the rate of diagnosis.A significant unknown is the added value of combining URGS with equally rapid functional 'omic assays, such as transcriptome sequencing, metabolomics, and proteomics using readily available biological samples.As our knowledge of variant pathogenicity increases it is anticipated that the frustrating term variant of uncertain significance will become a historical artifact.
Little work has yet been done to optimize the clinical utility or outcomes associated with URGS.There is considerable need for implementation science and process engineering to transform testing into generalizable rapid precision medicine delivery systems.Significant gains in the rate of change in management following URGS are possible.
Long term trends suggest that in five years there will be effective treatments for at least 1,000 genetic diseases and that diagnosis by URGS will be available within a day nationwide at a cost of ~$2,500 (Fig. 2).In five years there is the potential for infant and childhood mortality in the US and UK to have been reduced by several percent through use of URGS as a first-tier, standard of care test for children in ICUs with diseases of uncertain etiology.

Fig. 1 |Fig. 2 |Fig. 3 |
Fig. 1 | Timeline and process flow graph demonstrating that for clinical URGS to improve outcomes in children admitted to ICUs it must be incorporated within a multi-disciplinary healthcare delivery system.While clinical grade URGS can be in performed in as little as 20 h, it typically takes at least 36 h.However, time-todiagnosis by URGS is dependent upon four antecedent steps that typically take at least 24 h.Furthermore, improvements in outcome only start to occur upon implementation of precision dietary, drug, device, or surgical interventions.While almost every molecular diagnosis changes management, very few genetic diseases currently have curative treatments.Rx treatment, ID identification, EHR electronic health record.Icons: manual operation; decision; predefined process; data; extract; multidocument; summing junction; or;terminator.

Table 1 |
Studies of the diagnostic performance, change in management and outcome, and time to result (TAT) of URGS, RGS and RES in seriously ill children in intensive care units npj Genomic Medicine | (2024) 9:17

Table 1 (
continued) | Studies of the diagnostic performance, change in management and outcome, and time to result (TAT) of URGS, RGS and RES in seriously ill children in intensive care units size refers to the number of probands.Studies are listed from oldest to newest.Ref. reference, Δ Change, Dx diagnosis, Mx management, TAT turnaround time, n.d.not done, d days, RCT Randomized Controlled Trial, SOC standard of care, Implem implementation science design, RTDCT randomized time delayed clinical trial, Crossover Patients received both interventions, Dis.disease, Susp.suspected, Aust Australia, UAE United Arab Emirates.
82udy npj Genomic Medicine | (2024) 9:17PICUs of five community hospitals and two children's hospitals in Michigan82.The rate of diagnosis was 39% and results changed management in 27%.Further studies are needed to determine how clinical utility of URGS, RGS and RES vary with time from admission to sample receipt, with rapid versus ultra-rapid testing, and by presentation, disease severity, and rate of progression.Addressing these gaps would inform implementation.

Table 2 |
Studies of the cost effectiveness of URGS and RGS in seriously ill children in intensive care units Δ change, Dx diagnosis, Mx management, n.d.not done, TAT turnaround time.https://doi.org/10.1038/s41525-024-00404-0Review article npj Genomic Medicine | (2024) 9:17 The beneficiary's signs/symptoms suggest a broad, differential diagnosis that could require multiple genetic tests if RGS was not performed; 3. Timely identification of a molecular diagnosis is necessary to guide clinical decision making, and the RGS results will guide the treatment and/or management of the beneficiary's condition; and 4. At least one of the following clinical criteria apply: : 1. Signs/symptoms suggest a rare genetic condition that cannot be diagnosed by a standard clinical work-up;2.