Purpose Pharmacogenomic (PGx) variation affects drug metabolism and adverse drug reaction (ADR) risk. While the Clinical Pharmacogenetics Implementation Consortium (CPIC) lists 573 actionable gene-drug pairs, large-scale evaluation of PGx-related ADRs remains limited. We performed a retrospective genomic-first analysis on genetic and electronic health record (EHR) data to assess PGx impact on ADR risk. Methods We analyzed 226,053 individuals in the Geisinger MyCode cohort for 58 CPIC high-risk gene-drug associations spanning 11 genes. Genetic findings were linked to EHR allergy and medication discontinuation records. Results Most individuals (211,920/226,053, 93.7%) had at least one actionable PGx phenotype and 44.4% (100,402/226,053) had an actionable phenotype conferring ADR risk and were prescribed a relevant medication. As individuals accumulate medication exposures, ADR incidence increases (Pearson’s correlation=0.50, P<0.001). Individuals with risk phenotypes were more likely to have a documented allergy or ADR-related medication discontinuation (P<0.001, OR=1.4), and 3.9% (8,913/226,053) exhibited an ADR associated with personal PGx risk. We observed 36,194 ADRs across 27,546 individuals (12.2% of cohort); 10,719/36,194 (29.6%) occurred in individuals with relevant PGx phenotypes. Conclusion Individuals exposed to more medications exhibit increased ADR rates. PGx further compounds ADR risk, and a portion of population ADR burden could possibly have been prevented through PGx-guided therapy.

Abstract As population DNA sequencing becomes more common, genomic-first approaches are increasingly used to identify individuals with possible rare genetic disorders. To accurately estimate prevalence and penetrance, these studies often confirm manifestation of the disorder using electronic health records (EHRs). Multiple strategies exist to search the EHR for diagnoses of rare disorders, however, each has its limitations. We have developed a portable, ensemble tool, DxFit, that mines EHR data (ICD codes and structured diagnosis descriptions from billing code and problem list tables) for a diagnosis consistent with a given rare genetic disorder. DxFit combines evidence across four strategies: (1) gene name searches in diagnosis descriptions and notes, (2) ICD conversion to Mondo rare disorder ontology to find exact and nearby matches, (3) word embedding similarity searches, and (4) Jaccard similarity matches. DxFit prioritizes the match type and outputs the most confident match for each participant-disorder pair. On a cohort of 350 participants with a known positive result from diagnostic genetic testing for developmental disorders, DxFit had a sensitivity of 88.7% and specificity of 86.2% using default parameters. Adjusting the linguistic scoring thresholds from 0.8 to 0.7 and allowing for synonymous matches yielded a sensitivity of 92.7% and specificity of 84.5%. Partitioning EHR evidence into windows before and after genetic testing demonstrates, as expected, that the overall DxFit rates increase after testing and the match types become more confident. DxFit is available to the public and has extensive customization options to support a wide range of uses. Graphical Abstract

A challenge for clinical exome and genome sequencing (ES/GS) analysis is correlating the clinical presentation of the cases being tested with known gene-phenotype associations (GPAs). We developed Multiscore, a gene prioritization tool, to facilitate gene-level predictions of phenotypic fit. Multiscore combines data inputs and algorithms to generate similarity subscores that feed a random forest (RF) classifier trained to predict the probability of association between the patient's clinical features and the gene. The reference GPAs are extracted from: (1) OMIM, (2) patient descriptions in the literature, and (3) GeneDx (GDx) clinical data. We used 9,989 ES/GS cases to assess performance of the tool in combination with genotype filtering. Genotype filters rendered an average of 173 genes with variants requiring clinical review. Multiscore prioritized the reported positive gene with a median rank of 3 and mean rank of 6.35. The average recall (sensitivity) of Multiscore was 33% in the top 1, 69% in the top 5, 83% in the top 10, and 93% in the top 20 ranked genes. Multiscore was able to handle non-exact HPO term matches allowing the use of real-world clinical data. 74 genes lacking OMIM entries were prioritized using only the GDx and literature datasets. Multiscore allows the phenotype review to prioritize the most relevant genes, increasing case throughput and broadening access to diagnoses for patients.

OBJECTIVE:Vacuoles, E1-ubiquitin-activating enzyme, X-linked, autoinflammatory, somatic (VEXAS) syndrome is a progressive systemic autoinflammatory disorder caused by somatic variants in UBA1 in blood. Previous analyses have shown discordant disease penetrance. In this study, we examine the associations between demographic features and UBA1 variant allele frequency (VAF) with disease manifestations. METHODS:Whole exome sequencing data from 192,584 participants from Geisinger MyCode Community Health Initiative and Mount Sinai BioMe Biobank were analyzed for disease-causing variants in UBA1. Clinical manifestations were analyzed across individuals with the UBA1 variant. RESULTS:Nine UBA1 variants (VAF range 2.9%-79%) in 23 participants (69.6% men) were identified. Cases with high VAF (>20%) developed macrocytic anemia more often (87.5%) than patients with low VAF (≤20%) variants (27%; P = 0.009). Specifically, at the time of genetic testing, 87.5% of high VAF cases had macrocytic anemia compared with 13.3% of low VAF cases (P = 0.001). However, there was no significant difference in the development of anemia or thrombocytopenia (P = 0.53). In two high VAF cases, macrocytosis developed more than five years before the time of sample collection, followed by anemia approximately at the time of sample collection. In one low VAF case with other inflammatory symptoms, macrocytic anemia did not develop until five years after sample collection. CONCLUSION:VEXAS syndrome disease severity and penetrance increase at higher VAFs. Low VAF cases demonstrate incomplete penetrance, and the disease tends to be milder in those with it. Female individuals are enriched in lower VAFs and have milder symptoms, suggesting a protective role against disease severity. Low VAF cases, especially ≤10%, can be initially asymptomatic and later develop disease.

ImportanceThe feasibility of implementing genome sequencing as an adjunct to traditional newborn screening (NBS) in newborns of different racial and ethnic groups is not well understood.ObjectiveTo report interim results of acceptability, feasibility, and outcomes of an ongoing genomic NBS study in a diverse population in New York City within the context of the New York State Department of Health Newborn Screening Program.Design, Setting, and ParticipantsThe Genomic Uniform-screening Against Rare Disease in All Newborns (GUARDIAN) study was a multisite, single-group, prospective, observational investigation of supplemental newborn genome screening with a planned enrollment of 100 000 participants. Parent-reported race and ethnicity were recorded at the time of recruitment. Results of the first 4000 newborns enrolled in 6 New York City hospitals between September 2022 and July 2023 are reported here as part of a prespecified interim analysis.ExposureSequencing of 156 early-onset genetic conditions with established interventions selected by the investigators were screened in all participants and 99 neurodevelopmental disorders associated with seizures were optional.Main Outcomes and MeasuresThe primary outcome was screen-positive rate. Additional outcomes included enrollment rate and successful completion of sequencing.ResultsOver 11 months, 5555 families were approached and 4000 (72.0%) consented to participate. Enrolled participants reflected a diverse group by parent-reported race (American Indian or Alaska Native, 0.5%; Asian, 16.5%; Black, 25.1%; Native Hawaiian or Other Pacific Islander, 0.1%; White, 44.7%; 2 or more races, 13.0%) and ethnicity (Hispanic, 44.0%; not Hispanic, 56.0%). The majority of families consented to screening of both groups of conditions (both groups, 90.6%; disorders with established interventions only, 9.4%). Testing was successfully completed for 99.6% of cases. The screen-positive rate was 3.7%, including treatable conditions that are not currently included in NBS.Conclusions and RelevanceThese interim findings demonstrate the feasibility of targeted interpretation of a predefined set of genes from genome sequencing in a population of different racial and ethnic groups. DNA sequencing offers an additional method to improve screening for conditions already included in NBS and to add those that cannot be readily screened because there is no biomarker currently detectable in dried blood spots. Additional studies are required to understand if these findings are generalizable to populations of different racial and ethnic groups and whether introduction of sequencing leads to changes in management and improved health outcomes.Trial RegistrationClinicalTrials.gov Identifier: NCT05990179

Chronic kidney disease (CKD) affects approximately 9% of the global population, leading to increased risks of end-stage kidney disease (ESKD), cardiovascular disease (CVD), and mortality. Patients with CKD are a huge burden on health care resources globally. CKD is a complex condition influenced by a combination of genetic, environmental, and traditional risk factors. Family studies have suggested heritability rates for CKD ranging from 30% to 75%, and large genomic biobank studies have proven essential in identifying genes with substantial effects on CKD risk and in capturing cumulative genetic risk through polygenic risk scores. These biobanks are crucial for discovering new genes associated with kidney health and disease, and their growing size enhances the power to detect novel genetic associations. Integrating multi-omics technologies such as transcriptomics, metabolomics, and proteomics further enriches our understanding of CKD, while advanced computational tools continue to expand our insights into genetic data. Polygenic risk scores, derived from hundreds of genetic variants with small effect sizes, can help identify individuals at high risk of CKD. Genomic biobanks offer valuable opportunities for early identification and personalized treatment of monogenic kidney disorders, such as autosomal dominant polycystic kidney disease and Alport syndrome. These biobanks help fill knowledge gaps, particularly in individuals with milder or asymptomatic presentations who are often underrepresented in traditional studies. Expanding genomic biobank efforts globally, especially in diverse populations, is vital to enhancing our understanding of the genetic underpinnings of kidney disease. This review highlights the significant contributions of genomic biobanks to advancing our comprehension of the genetics of CKD.

Purpose: Prior studies investigating the genetic architecture of pediatric motor speech disorders (MSDs) have been limited by small sample sizes and an exclusive focus on apraxia. We aimed to identify pathogenic genomic variants associated with MSDs in a large pediatric population referred for exome sequencing (ES). Methods: We identified pediatric patients with MSDs who had clinical ES between 2012 and 2022. The rate of pathogenic/likely pathogenic (P/LP) findings considered causative of the MSD phenotype was determined and delineated by sex and neurodevelopmental comorbidity. Gene- based burden testing compared the rate of P/LP variants in each gene in MSD cases with a comparison clinical ES cohort. Results: Positive diagnostic results were detected in 527 of 2004 (26.3%) patients with MSDs, with higher diagnostic rates in females and individuals with neurodevelopmental comorbidities. P/LP sequence variants were detected in 262 genes. Gene-based case-referent burden analysis revealed that 30 genes were nominally associated with MSDs, 2 of which (SETBP1 and ADCY5) survived exome-wide correction. Conclusion: Over 25% of patients with MSDs were found to harbor P/LP variants in 262 genes, many of which have not previously been associated with MSDs. Potential clinical implications include early implementation of intensive speech therapy for children diagnosed with mono- genic causes of MSDs. (c) 2025 The Authors. Published by Elsevier Inc. on behalf of American College of Medical Genetics and Genomics. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

(Abstracted from JAMA 2025;333(3):232–240 Newborn screening (NBS) checks for congenital conditions that can be treated before symptoms start and lead to irreversible effects; these include conditions such as metabolic disease, cystic fibrosis, hearing impairment, endocrine disorders, hemoglobinopathies, severe combined immunodeficiency, and other conditions that are often genetic. Genetic sequencing is typically second-tier in terms of NBS, being used chiefly to identify genes involved in a condition such as cystic fibrosis.

Our understanding of rare genetic disorders (RGDs) comes largely from clinically ascertained individuals. Genomic-first ascertainment, however, can identify individuals with monogenic RGDs who were not ascertained clinically and enhance our understanding of the phenotypic spectrum, penetrance, and prevalence of RGDs. Although genomic ascertainment of RGDs at scale presents several challenges, it offers the potential for earlier and more precise diagnosis, improved management and treatment, and a more accurate description of the phenotypic spectrum of RGDs, which could all contribute to improved outcomes in RGDs. Therefore, we curated a list of 2,701 high-confidence, single-disorder-associated genes that are not routinely screened. Next, we created a sustainable strategy for identifying disease-causing variants across this gene list in 218,680 healthcare-population participants in Geisinger's MyCode Community Health Initiative. We developed and applied automated methods for assessing the fit of participants' genomic findings to existing clinical diagnoses. Our strategy identified 2.5% of participants (N = 5,484) with a high-confidence positive molecular finding in 490 RGD-associated genes. An additional 0.7% (N = 1,455) had possible molecular findings from compound-heterozygous or novel loss-of-function variants. Of the high-confidence molecular positives, 15.0%-21.1% had evidence of a corresponding clinical fit from existing diagnosis codes. The remainder lacked a corresponding clinical diagnosis code, suggesting that genomic ascertainment of RGDs may be more sensitive than clinical ascertainment and that penetrance for RGDs may be overestimated. This low rate of correspondence highlights the potential clinical value of a genomic-first approach to RGD ascertainment and the need for further population-based study of RGDs.

Access to a precise genetic diagnosis (PrGD) in critically ill newborns is limited and inequitable because the complex inclusion criteria used to prioritize testing eligibility omit many patients at high risk for a genetic condition. SeqFirst-neo is a program to test whether a genotype-driven workflow using simple, broad exclusion criteria to assess eligibility for rapid genome sequencing (rGS) increases access to a PrGD in critically ill newborns. All 408 newborns admitted to a neonatal intensive care unit between January 2021 and February 2022 were assessed, and of 240 eligible infants, 126 were offered rGS (i.e., intervention group [IG]) and compared to 114 infants who received conventional care in parallel (i.e., conventional care group [CCG]). A PrGD was made in 62/126 (49.2%) IG neonates compared to 11/114 (9.7%) CCG infants. The odds of receiving a PrGD were ∼9 times greater in the IG vs. the CCG, and this difference was maintained at 12 months follow-up. Access to a PrGD in the IG vs. CCG differed significantly between infants identified as non-White (34/74, 45.9% vs. 6/29, 20.7%; p = 0.024) and Black (8/10, 80.0% vs. 0/4; p = 0.015). Neonatologists were significantly less successful at predicting a PrGD in non-White than non-Hispanic White infants. The use of a standard workflow in the IG with a PrGD revealed that a PrGD would have been missed in 26/62 (42%) infants. The use of simple, broad exclusion criteria that increase access to genetic testing significantly increases access to a PrGD, improves access equity, and results in fewer missed diagnoses.

Historically, clinical genomics has been driven by a phenotype-first approach. However, many genomic conditions remain under-diagnosed due to both potential under-ascertainment and challenges in accessing expert care and testing. The Geisinger MyCode Community Health Initiative, an unselected healthcare-based population with >170,000 patient-participants with exome sequencing and linked electronic health records (EHR), is uniquely positioned to pursue a genotype-first approach to disease diagnosis to expand our understanding of the penetrance, phenotypic spectrum, and progression of genomic conditions.

Autosomal recessive coding variants are well-known causes of rare disorders. We quantified the contribution of these variants to developmental disorders in a large, ancestrally diverse cohort comprising 29,745 trios, of whom 20.4% had genetically inferred non-European ancestries. The estimated fraction of patients attributable to exome-wide autosomal recessive coding variants ranged from ~2-19% across genetically inferred ancestry groups and was significantly correlated with average autozygosity. Established autosomal recessive developmental disorder-associated (ARDD) genes explained 84.0% of the total autosomal recessive coding burden, and 34.4% of the burden in these established genes was explained by variants not already reported as pathogenic in ClinVar. Statistical analyses identified two novel ARDD genes: KBTBD2 and ZDHHC16. This study expands our understanding of the genetic architecture of developmental disorders across diverse genetically inferred ancestry groups and suggests that improving strategies for interpreting missense variants in known ARDD genes may help diagnose more patients than discovering the remaining genes.

You have accessJournal of UrologyStone Disease: Epidemiology & Evaluation II (MP45)1 May 2024MP45-12 PREVALENCE OF MONOGENIC NEPHROLITHIASIS GENE ALTERATIONS IN A REGIONAL HEALTH CARE SYSTEM Jasmine Kashkoush, Karyn Murphy, Ion Dan Bucaloiu, Steven Scheinman, Kyle Retterer, Alexander Chang, and Heinric Williams Jasmine KashkoushJasmine Kashkoush , Karyn MurphyKaryn Murphy , Ion Dan BucaloiuIon Dan Bucaloiu , Steven ScheinmanSteven Scheinman , Kyle RettererKyle Retterer , Alexander ChangAlexander Chang , and Heinric WilliamsHeinric Williams View All Author Informationhttps://doi.org/10.1097/01.JU.0001008764.86460.8e.12AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Genetic and environmental factors contribute to the development of nephrolithiasis (NL). Hereditability explains at least 45% of this disease and monogenic causes have been identified in a number of known NL genes. In this study, we assessed the prevalence of germline mutations in 34 known NL genes from the United Kingdom NHS Genomic Medicine Service NL PanelApp (UK PanelApp) in our study population. METHODS: Electronic health records (EHR) of individuals with and without a ICD diagnosis of NL participating in the Geisinger MyCode® (DNA exome sequencing program) from 2014 to December 2022 were reviewed. Through the DiscovEHR program which links DNA exome sequencing data with EHR data, we assess NL burden in the MyCode® cohort and the prevalence of all ClinVar pathogenic (P) or likely pathogenic (LP) variants in the 34 genes were assessed among NL patients aged>18 years versus matched variant-negative controls. RESULTS: Among a population of 170,729 MyCode® participants≥18 years old, we identified 10,621 adults (6.2%) with NL related ICD codes in their EHR confirmed on imaging and/or stone analysis. Mean age of stone formers was 59.2 years, 45.8% were male and 99% non-Hispanic white. Heterozygous or homozygous variants in any of the 34 genes were found in 5.9% (631/10,621) of NL population. Compared to variant-negative controls, unique LP/P variants were found in 25/34 genes (73.5%) among NL patients. The SLC7A9 gene (n=115) was most frequently mutated followed by CYP24A1 (n=92) and SLC3A1 (n=92). The percentage of variant carriers with NL for each of the 25 genes is provided. CONCLUSIONS: Our study provides a real-world prevalence of monogenic causes of stone disease in individuals from a regional healthcare system. Source of Funding: None © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e747 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Jasmine Kashkoush More articles by this author Karyn Murphy More articles by this author Ion Dan Bucaloiu More articles by this author Steven Scheinman More articles by this author Kyle Retterer More articles by this author Alexander Chang More articles by this author Heinric Williams More articles by this author Expand All Advertisement PDF downloadLoading ...

Introduction:Our knowledge of X-linked Alport Syndrome [AS] comes mostly from selected cohorts with more severe disease. Methods:We examined the phenotypic spectrum of X-linked AS in males and females with a genotype-based approach using data from the Geisinger MyCode DiscovEHR study, an unselected health system-based cohort with exome sequencing and electronic health records. Patients with COL4A5 variants reported as pathogenic (P) or likely pathogenic (LP) in ClinVar, or protein-truncating variants (PTVs), were each matched with up to 5 controls without COL4A3/4/5 variants by sociodemographics, diabetes diagnosis, and year of first outpatient encounter. AS-related phenotypes included dipstick hematuria, bilateral sensorineural hearing loss (BSHL), proteinuria, decreased eGFR, and ESKD. Results:Out of 170,856 patients, there were 29 hemizygous males (mean age 52.0 y [SD 20.0]) and 55 heterozygous females (mean age 59.3 y [SD 18.8]) with a COL4A5 P/LP variant, including 48 with the hypomorphic variant p.Gly624Asp. Overall, penetrance (having any AS phenotypic feature) was highest for non-p.Gly624Asp P/LP variants (males: 94%, females: 85%), intermediate for p.Gly624Asp (males: 77%, females: 69%), compared to controls (males: 32%; females: 50%). The proportion with ESKD was highest for males with P/LP variants (44%), intermediate for males with p.Gly624Asp (15%) and females with P/LP variants (10%), compared to controls (males: 3%, females 2%). Only 47% of individuals with COL4A5 had completed albuminuria screening, and a minority were taking renin-angiotensin aldosterone system (RAAS) inhibitors. Only 38% of males and 16% of females had a known diagnosis of Alport syndrome or thin basement membrane disease. Conclusion:In an unselected cohort, we show increased risks of AS-related phenotypes in men and women compared to matched controls, while showing a wider spectrum of severity than has been described previously and variability by genotype. Future studies are needed to determine whether early genetic diagnosis can improve outcomes in Alport Syndrome.

Alport Syndrome (AS), particularly autosomal dominant AS, can range in severity from microscopic hematuria to end-stage kidney disease (ESKD), and often goes undiagnosed. With increased availability of genetic testing and recognition of the importance of AS in chronic kidney disease (CKD), there is a need to understand the molecular diagnostic yield across various phenotypes and settings. We hypothesized that the molecular diagnostic yield would be lower in largely unselected health system cohorts compared to a multidisciplinary renal genetics cohort.

Protein-truncating variants (PTVs) near the 30 end of genes may escape nonsense-mediated decay (NMD). PTVs in the NMD-escape region (PTVescs) can cause Mendelian disease but are difficult to interpret given their varying impact on protein function. Previously, PTVesc burden was assessed in an epilepsy cohort, but no large-scale analysis has systematically evaluated these variants in rare disease. We performed a retrospective analysis of 29,031 neurodevelopmental disorder (NDD) parent -offspring trios referred for clinical exome sequencing to identify PTVesc de novo mutations (DNMs). We identified 1,376 PTVesc DNMs and 133 genes that were significantly enriched (binomial p < 0.001). The PTVesc-enriched genes included those with PTVescs previously described to cause dominant Mendelian disease (e.g., SEMA6B, PPM1D, and DAGLA). We annotated ClinVar variants for PTVescs and identified 948 genes with at least one highconfidence pathogenic variant. Twenty-two known Mendelian PTVesc-enriched genes had no prior evidence of PTVesc-associated disease. We found 22 additional PTVesc-enriched genes that are not well established to be associated with Mendelian disease, several of which showed phenotypic similarity between individuals harboring PTVesc variants in the same gene. Four individuals with PTVesc mutations in RAB1A had similar phenotypes including NDD and spasticity. PTVesc mutations in IRF2BP1 were found in two individuals who each had severe immunodeficiency manifesting in NDD. Three individuals with PTVesc mutations in LDB1 all had NDD and multiple congenital anomalies. Using a large-scale, systematic analysis of DNMs, we extend the mutation spectrum for known Mendelian disease -associated genes and identify potentially novel disease -associated genes.