Semiautomated approach focused on new genomic information results in time and effort-efficient reannotation of negative exome data.

Most rare disease patients (75-50%) undergoing genomic sequencing remain unsolved, often due to lack of information about variants identified. Data review over time can leverage novel information regarding disease-causing variants and genes, increasing this diagnostic yield. However, time and resource constraints have limited reanalysis of genetic data in clinical laboratories setting. We developed RENEW, (REannotation of NEgative WES/WGS) an automated reannotation procedure that uses relevant new information in on-line genomic databases to enable rapid review of genomic findings. We tested RENEW in an unselected cohort of 1066 undiagnosed cases with a broad spectrum of phenotypes from the Mayo Clinic Center for Individualized Medicine using new information in ClinVar, HGMD and OMIM between the date of previous analysis/testing and April of 2022. 5741 variants prioritized by RENEW were rapidly reviewed by variant interpretation specialists. Mean analysis time was approximately 20 s per variant (32 h total time). Reviewed cases were classified as: 879 (93.0%) undiagnosed, 63 (6.6%) putatively diagnosed, and 4 (0.4%) definitively diagnosed. New strategies are needed to enable efficient review of genomic findings in unsolved cases. We report on a fast and practical approach to address this need and improve overall diagnostic success in patient testing through a recurrent reannotation process.

Clinical Trials for Special Populations: Children, Older Adults, and Rare Diseases.

Research cannot maximize population health unless it improves health for all members of the public, including special populations such as children, older adults, and people living with rare diseases. Each of these categories require special considerations when planning and performing clinical trials, and common threads of ethical conduct of research in vulnerable populations appear throughout. In this review, definitions of each of the three categories of special population (children, older adults, and rare diseases) are discussed in terms of US research regulations, the unique challenges to conducting clinical trials for these special populations, critical ethical issues, and opportunities for innovative ways to design and operationalize clinical trials in special populations. Additional critical attention is focused on factors that influence the generalizability of study results to reduce health disparities, as well as the importance of community engagement and advocacy groups that can help to educate potential trial participants of the benefits of clinical trial participation.

Most patients with disorders of gut-brain interaction receive pharmacotherapy with major or moderate drug-gene interactions.

BACKGROUND: How variations predicted by pharmacogenomic testing to alter drug metabolism and therapeutic response affect outcomes for patients with disorders of gut- brain interaction is unclear. AIMS: To assess the prevalence of pharmacogenomics-predicted drug-gene interactions and symptom outcomes for patients with disorders of gut-brain interaction. METHODS: Patients who were treated in our clinical practice for functional dyspepsia/bowel disorder underwent pharmacogenomic testing. The change in symptoms from baseline to 6 months was compared for patients with variations in CYP2D6 and CYP2C19, which metabolize neuromodulators, and SLC6A4, which encodes the sodium- dependent serotonin transporter. RESULTS: At baseline, 79 of 94 participants (84%) had at least one predicted major drug- gene interaction, and all 94 (100%) had at least one predicted moderate interaction. For the 44 participants who completed a survey of their symptoms at 6 months, the mean (SD) irritable bowel syndrome-symptom severity score decreased from 284 (71) at baseline to 231 (95) at 6 months (p < 0.001). Among patients taking selective serotonin reuptake inhibitors, the decrease in symptom severity (p = 0.03) and pain (p = 0.002) scores from baseline to 6 months was greater for patients with a homozygous SLC6A4 long/long genotype (n = 30) (ie, increased serotonin transporter activity) than for patients with homozygous short/short or heterozygous long/short genotypes (n = 64). Symptom outcomes were not affected by CYP2D6 or CYP2C19 variations. CONCLUSIONS: The homozygous SLC6A4 long/long genotype confers better symptom resolution for patients with disorders of gut-brain interaction who take selective serotonin reuptake inhibitors than do the homozygous short/short or heterozygous long/short genotypes.

IL-17 Signaling in Primary Sclerosing Cholangitis Patient-Derived Organoids.

The pathogenesis of primary sclerosing cholangitis (PSC) is unclear, although studies implicate IL-17A as an inflammatory mediator in this disease. However, a direct assessment of IL-17 signaling in PSC cholangiocytes is lacking. In this study we aimed to investigate the response of PSC extrahepatic cholangiocyte organoids (ECO) to IL-17A stimulation. Cholangiocytes obtained from PSC and non-PSC patients by endoscopic retrograde cholangiography (ERC) were cultured as ECO. The ECO were treated with vehicle or IL-17A and assessed by transcriptomics, secretome analysis, and genome sequencing (GS). Unsupervised clustering of all integrated scRNA-seq data identified 8 cholangiocyte clusters which did not differ between PSC and non-PSC ECO. However, PSC ECO cells demonstrated a robust response to IL-17 treatment, noted by an increased number of differentially expressed genes (DEG) by transcriptomics, and more abundant chemokine and cytokine expression and secretion. After rigorous filtering, GS identified candidate somatic variants shared among PSC ECO from unrelated individuals. However, no candidate rare variants in genes regulating the IL-17 pathway were identified, but rare variants regulating the MAPK signaling pathway were present in all PSC ECO. In conclusion, PSC and non-PSC patient derived ECO respond differently to IL-17 stimulation implicating this pathway in the pathogenesis of PSC.

Predicting cholangiocarcinoma in primary sclerosing cholangitis: using artificial intelligence, clinical and laboratory data.

BACKGROUND: Primary sclerosing cholangitis (PSC) patients have a risk of developing cholangiocarcinoma (CCA). Establishing predictive models for CCA in PSC is important. METHODS: In a large cohort of 1,459 PSC patients seen at Mayo Clinic (1993-2020), we quantified the impact of clinical/laboratory variables on CCA development using univariate and multivariate Cox models and predicted CCA using statistical and artificial intelligence (AI) approaches. We explored plasma bile acid (BA) levels' predictive power of CCA (subset of 300 patients, BA cohort). RESULTS: Eight significant risk factors (false discovery rate: 20%) were identified with univariate analysis; prolonged inflammatory bowel disease (IBD) was the most important one. IBD duration, PSC duration, and total bilirubin remained significant (p < 0.05) with multivariate analysis. Clinical/laboratory variables predicted CCA with cross-validated C-indexes of 0.68-0.71 at different time points of disease, significantly better compared to commonly used PSC risk scores. Lower chenodeoxycholic acid, higher conjugated fraction of lithocholic acid and hyodeoxycholic acid, and higher ratio of cholic acid to chenodeoxycholic acid were predictive of CCA. BAs predicted CCA with a cross-validated C-index of 0.66 (std: 0.11, BA cohort), similar to clinical/laboratory variables (C-index = 0.64, std: 0.11, BA cohort). Combining BAs with clinical/laboratory variables leads to the best average C-index of 0.67 (std: 0.13, BA cohort). CONCLUSIONS: In a large PSC cohort, we identified clinical and laboratory risk factors for CCA development and demonstrated the first AI based predictive models that performed significantly better than commonly used PSC risk scores. More predictive data modalities are needed for clinical adoption of these models.

The exposome and liver disease - how environmental factors affect liver health.

Since the initial development of the exposome concept, much effort has been devoted to the characterisation of the exposome through analytical, epidemiological, and toxicological/mechanistic studies. There is now an urgent need to link the exposome to human diseases and to include exposomics in the characterisation of environment-linked pathologies together with genomics and other omics. Liver diseases are particularly well suited for such studies since major functions of the liver include the detection, detoxification, and elimination of xenobiotics, as well as inflammatory responses. It is well known that several liver diseases are associated with i) addictive behaviours such as alcohol consumption, smoking, and to a certain extent dietary imbalance and obesity, ii) viral and parasitic infections, and iii) exposure to toxins and occupational chemicals. Recent studies indicate that environmental exposures are also significantly associated with liver diseases, and these include air pollution (particulate matter and volatile chemicals), contaminants such as polyaromatic hydrocarbons, bisphenol A and per-and poly-fluorinated substances, and physical stressors such as radiation. Furthermore, microbial metabolites and the "gut-liver" axis play a major role in liver diseases. Exposomics is poised to play a major role in the field of liver pathology. Methodological advances such as the exposomics-metabolomics framework, the determination of risk factors' genomic and epigenomic signatures, and cross-species biological pathway analysis should further delineate the impact of the exposome on the liver, opening the way for improved prevention, as well as the identification of new biomarkers of exposure and effects, and additional therapeutic targets.

Multitrait genome-wide analyses identify new susceptibility loci and candidate drugs to primary sclerosing cholangitis.

Primary sclerosing cholangitis (PSC) is a rare autoimmune bile duct disease that is strongly associated with immune-mediated disorders. In this study, we implemented multitrait joint analyses to genome-wide association summary statistics of PSC and numerous clinical and epidemiological traits to estimate the genetic contribution of each trait and genetic correlations between traits and to identify new lead PSC risk-associated loci. We identified seven new loci that have not been previously reported and one new independent lead variant in the previously reported locus. Functional annotation and fine-mapping nominated several potential susceptibility genes such as MANBA and IRF5. Network-based in silico drug efficacy screening provided candidate agents for further study of pharmacological effect in PSC.

Environmental chemicals and endogenous metabolites in bile of USA and Norway patients with primary sclerosing cholangitis.

Primary sclerosing cholangitis (PSC) is a complex bile duct disorder. Its etiology is incompletely understood, but environmental chemicals likely contribute to risk. Patients with PSC have an altered bile metabolome, which may be influenced by environmental chemicals. This novel study utilized state-of-the-art high-resolution mass spectrometry (HRMS) with bile samples to provide the first characterization of environmental chemicals and metabolomics (collectively, the exposome) in PSC patients located in the United States of America (USA) (n = 24) and Norway (n = 30). First, environmental chemical- and metabolome-wide association studies were conducted to assess geographic-based similarities and differences in the bile of PSC patients. Nine environmental chemicals (false discovery rate, FDR < 0.20) and 3143 metabolic features (FDR < 0.05) differed by site. Next, pathway analysis was performed to identify metabolomic pathways that were similarly and differentially enriched by the site. Fifteen pathways were differentially enriched (P < .05) in the categories of amino acid, glycan, carbohydrate, energy, and vitamin/cofactor metabolism. Finally, chemicals and pathways were integrated to derive exposure-effect correlation networks by site. These networks demonstrate the shared and differential chemical-metabolome associations by site and highlight important pathways that are likely relevant to PSC. The USA patients demonstrated higher environmental chemical bile content and increased associations between chemicals and metabolic pathways than those in Norway. Polychlorinated biphenyl (PCB)-118 and PCB-101 were identified as chemicals of interest for additional investigation in PSC given broad associations with metabolomic pathways in both the USA and Norway patients. Associated pathways include glycan degradation pathways, which play a key role in microbiome regulation and thus may be implicated in PSC pathophysiology.

Algebraic topology-based machine learning using MRI predicts outcomes in primary sclerosing cholangitis.

BACKGROUND: Primary sclerosing cholangitis (PSC) is a chronic cholestatic liver disease that can lead to cirrhosis and hepatic decompensation. However, predicting future outcomes in patients with PSC is challenging. Our aim was to extract magnetic resonance imaging (MRI) features that predict the development of hepatic decompensation by applying algebraic topology-based machine learning (ML). METHODS: We conducted a retrospective multicenter study among adults with large duct PSC who underwent MRI. A topological data analysis-inspired nonlinear framework was used to predict the risk of hepatic decompensation, which was motivated by algebraic topology theory-based ML. The topological representations (persistence images) were employed as input for classification to predict who developed early hepatic decompensation within one year after their baseline MRI. RESULTS: We reviewed 590 patients; 298 were excluded due to poor image quality or inadequate liver coverage, leaving 292 potentially eligible subjects, of which 169 subjects were included in the study. We trained our model using contrast-enhanced delayed phase T1-weighted images on a single center derivation cohort consisting of 54 patients (hepatic decompensation, n = 21; no hepatic decompensation, n = 33) and a multicenter independent validation cohort of 115 individuals (hepatic decompensation, n = 31; no hepatic decompensation, n = 84). When our model was applied in the independent validation cohort, it remained predictive of early hepatic decompensation (area under the receiver operating characteristic curve = 0.84). CONCLUSIONS: Algebraic topology-based ML is a methodological approach that can predict outcomes in patients with PSC and has the potential for application in other chronic liver diseases.

ACE2 and TMPRSS2 SARS-CoV-2 infectivity genes: deep mutational scanning and characterization of missense variants.

The human angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2) proteins play key roles in the cellular internalization of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the coronavirus responsible for the coronavirus disease of 2019 (COVID-19) pandemic. We set out to functionally characterize the ACE2 and TMPRSS2 protein abundance for variant alleles encoding these proteins that contained non-synonymous single-nucleotide polymorphisms (nsSNPs) in their open reading frames (ORFs). Specifically, a high-throughput assay, deep mutational scanning (DMS), was employed to test the functional implications of nsSNPs, which are variants of uncertain significance in these two genes. Specifically, we used a 'landing pad' system designed to quantify the protein expression for 433 nsSNPs that have been observed in the ACE2 and TMPRSS2 ORFs and found that 8 of 127 ACE2, 19 of 157 TMPRSS2 isoform 1 and 13 of 149 TMPRSS2 isoform 2 variant proteins displayed less than ~25% of the wild-type protein expression, whereas 4 ACE2 variants displayed 25% or greater increases in protein expression. As a result, we concluded that nsSNPs in genes encoding ACE2 and TMPRSS2 might potentially influence SARS-CoV-2 infectivity. These results can now be applied to DNA sequence data for patients infected with SARS-CoV-2 to determine the possible impact of patient-based DNA sequence variation on the clinical course of SARS-CoV-2 infection.

DNA methylation profile of liver tissue in end-stage cholestatic liver disease.

Aims: In this methylome-wide association study of cholestatic liver diseases (primary sclerosing cholangitis and primary biliary cholangitis), the authors aimed to elucidate changes in methylome and pathway enrichment to identify candidate genes. Patients & methods: Reduced representation bisulfite sequencing was performed on liver tissue from 58 patients with primary sclerosing cholangitis (n = 13), primary biliary cholangitis (n = 20), alcoholic liver disease (n = 21) and live liver donors (n = 4). Pathway enrichment and network analysis were used to explore key genes/pathways. Results: Both cholestatic liver diseases were characterized by global hypomethylation, with pathway enrichment demonstrating distinct genes and pathways associated with the methylome. Conclusions: This novel study demonstrated that differential methylation in cholestatic liver disease was associated with unique pathways, suggesting it may drive disease pathogenesis.

While DNA is the permanent code that defines each living being, the epigenome comprises sequences attached to DNA that can change with the environment. This means that abnormal changes to the epigenome may lead to disease and that finding and treating these abnormalities may in turn help treat disease. In this study of liver tissue from individuals with two rare liver diseases, primary sclerosing cholangitis and primary biliary cholangitis, the authors found that the epigenome of these two conditions is distinct, suggesting that the epigenome is linked to the development of these conditions and may be the key to treating them.

Implementation of preemptive DNA sequence-based pharmacogenomics testing across a large academic medical center: The Mayo-Baylor RIGHT 10K Study.

PURPOSE: The Mayo-Baylor RIGHT 10K Study enabled preemptive, sequence-based pharmacogenomics (PGx)-driven drug prescribing practices in routine clinical care within a large cohort. We also generated the tools and resources necessary for clinical PGx implementation and identified challenges that need to be overcome. Furthermore, we measured the frequency of both common genetic variation for which clinical guidelines already exist and rare variation that could be detected by DNA sequencing, rather than genotyping. METHODS: Targeted oligonucleotide-capture sequencing of 77 pharmacogenes was performed using DNA from 10,077 consented Mayo Clinic Biobank volunteers. The resulting predicted drug response-related phenotypes for 13 genes, including CYP2D6 and HLA, affecting 21 drug-gene pairs, were deposited preemptively in the Mayo electronic health record. RESULTS: For the 13 pharmacogenes of interest, the genomes of 79% of participants carried clinically actionable variants in 3 or more genes, and DNA sequencing identified an average of 3.3 additional conservatively predicted deleterious variants that would not have been evident using genotyping. CONCLUSION: Implementation of preemptive rather than reactive and sequence-based rather than genotype-based PGx prescribing revealed nearly universal patient applicability and required integrated institution-wide resources to fully realize individualized drug therapy and to show more efficient use of health care resources.

Induced Pluripotent Stem Cells From Subjects With Primary Sclerosing Cholangitis Develop a Senescence Phenotype Following Biliary Differentiation.

Primary sclerosing cholangitis (PSC) is a chronic fibroinflammatory disease of the biliary tract characterized by cellular senescence and periportal fibrogenesis. Specific disease features that are cell intrinsic and either genetically or epigenetically mediated remain unclear due in part to a lack of appropriate, patient-specific, in vitro models. Recently, our group developed systems to create induced pluripotent stem cell (iPSC)-derived cholangiocytes (iDCs) and biliary epithelial organoids (cholangioids). We use these models to investigate whether PSC cholangiocytes are intrinsically predisposed to cellular senescence. Skin fibroblasts from healthy controls and subjects with PSC were reprogrammed to pluripotency, differentiated to cholangiocytes, and subsequently grown in three-dimensional matrigel-based culture to induce formation of cholangioids. RNA sequencing (RNA-seq) on iDCs showed significant differences in gene expression patterns, including enrichment of pathways associated with cell cycle, senescence, and hepatic fibrosis, that correlate with PSC. These pathways also overlapped with RNA-seq analysis on isolated cholangiocytes from subjects with PSC. Exome sequencing on the subjects with PSC revealed genetic variants of unknown significance in the genes identified in these pathways. Three-dimensional culture revealed smaller size, lack of a central lumen, and increased cellular senescence in PSC-derived cholangioids. Congruent with this, PSC-derived iDCs showed increased secretion of the extracellular matrix molecule fibronectin as well as the inflammatory cytokines interleukin-6, and chemokine (C-C motif) ligand 2. Conditioned media (CM) from PSC-derived iDCs more potently activated hepatic stellate cells compared to control CM. Conclusion: We demonstrated efficient generation of iDCs and cholangioids from patients with PSC that show disease-specific features. PSC cholangiocytes are intrinsically predisposed to cellular senescence. These features are unmasked following biliary differentiation of pluripotent stem cells and have functional consequences in epithelial organoids.

Nine-gene pharmacogenomics profile service: The Mayo Clinic experience.

PURPOSE: The Pharmacogenomics (PGx) Profile Service was a proof-of-concept project to implement PGx in patient care at Mayo Clinic. METHODS: Eighty-two healthy individuals aged 18 and older underwent genotyping of CYP1A2, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, SLCO1B1, HLA-B*58:01, and VKORC1. A PGx pharmacist was involved in ordering, meeting with patients, interpreting, reviewing, and documenting results. RESULTS: Ninety three percent were CYP1A2 rapid metabolizers, 92% CYP3A4 normal metabolizers, and 88% CYP3A5 poor metabolizers; phenotype frequencies for CYP2C19 and CYP2D6 varied. Seventy-three percent had normal functioning SLCO1B1 transporter, 4% carried the HLA-B*58:01 risk variant, and 35% carried VKORC1 and CYP2C9 variants that increased warfarin sensitivity. CONCLUSION: Pre-emptive PGx testing offered medication improvement opportunity in 56% of participants for commonly used medications. A collaborative approach involving a PGx pharmacist integrated within a clinical practice with regards to utility of PGx results allowed for implementation of the PGx Profile Service. KEY POINTS: The Mayo Clinic PGx (PGx) Profile Service was a proof-of-concept project to utilize PGx testing as another clinical tool to enhance medication selection and decrease serious adverse reactions or medication failures. Over one-half of participants in the pilot using the PGx Profile Service were predicted to benefit from pre-emptive PGx testing to guide pharmacotherapy. PGx pharmacists played a crucial role in the PGx Profile Service by educating participants, identifying medication-gene interactions, and providing evidence-based (CPIC and DPWG) PGx recommendations for past, current, and future medication us.

Patients with Autoimmune Hepatitis Report Lower Lifetime Coffee Consumption.

BACKGROUND: Coffee drinking has been associated with decreased risk of some autoimmune diseases as well liver disease and outcomes. Environmental factors, such as coffee consumption, are yet to be assessed among patients with autoimmune hepatitis (AIH). AIM: We sought to investigate the relationship between coffee consumption and risk of AIH utilizing the Genetic Repository of Autoimmune Liver Disease and Contributing Exposures (GRACE) database. METHODS: Lifetime coffee drinking was collected from 358 AIH patients (cases) and 564 volunteers (controls) from primary care visits. Groups were compared utilizing the Wilcoxon rank sum test for continuous variables and the Chi-square test for discrete variables. Logistic regression was used to analyze the effects of different coffee parameters (time, frequency, and cups) after adjusting for age, sex, education, smoking status, BMI, and daily activity. RESULTS: 24.6% of AIH patients never drank coffee compared to 15.7% of controls (p < 0.001), and only 65.6% were current drinkers compared with 77% of controls (p < 0.001). Among "ever" coffee drinkers, AIH patients consumed fewer lifetime cups of coffee per month (45 vs. 47 for controls, p < 0.001) and spent less percentage of life drinking coffee (62.5% vs. 69.1% for controls, p < 0.001). Concurrent inflammatory bowel disease was higher among AIH patients than controls (5.7% vs. 1.2%, p < 0.001), yet did not significantly contribute to "never" coffee drinking status. The relationship between lower coffee consumption and AIH persisted even after controlling for covariates. CONCLUSIONS: Coffee consumption is lower among patients with AIH compared to controls.

High-Resolution Exposomics and Metabolomics Reveals Specific Associations in Cholestatic Liver Diseases.

Progress in development of prognostic and therapeutic options for the rare cholestatic liver diseases, primary sclerosing cholangitis (PSC) and primary biliary cholangitis (PBC), is hampered by limited knowledge of their pathogeneses. In particular, the potential role of hepatotoxic and/or metabolism-altering environmental chemicals in the pathogenesis of these diseases remains relatively unstudied. Moreover, the extent to which metabolic pathways are altered due to ongoing cholestasis and subsequent liver damage or possibly influenced by hepatotoxic chemicals is poorly understood. In this study, we applied a comprehensive exposomics-metabolomics approach to uncover potential pathogenic contributors to PSC and PBC. We used untargeted high-resolution mass spectrometry to characterize a wide range of exogenous chemicals and endogenous metabolites in plasma and tested them for association with disease. Exposome-wide association studies (EWAS) identified environmental chemicals, including pesticides, additives and persistent pollutants, that were associated with PSC and/or PBC, suggesting potential roles for these compounds in disease pathogenesis. Metabolome-wide association studies (MWAS) found disease-associated alterations to amino acid, eicosanoid, lipid, co-factor, nucleotide, mitochondrial and microbial metabolic pathways, many of which were shared between PSC and PBC. Notably, this analysis implicates a potential role of the 5-lipoxygenase pathway in the pathogenesis of these diseases. Finally, EWAS × MWAS network analysis uncovered linkages between environmental agents and disrupted metabolic pathways that provide insight into potential mechanisms for PSC and PBC. Conclusion: This study establishes combined exposomics-metabolomics as a generalizable approach to identify potentially pathogenic environmental agents and enumerate metabolic alterations that may impact PSC and PBC, providing a foundation for diagnostic and therapeutic strategies.

Genomics Integration Into Nephrology Practice.

RATIONALE & OBJECTIVE: The etiology of kidney disease remains unknown in many individuals with chronic kidney disease (CKD). We created the Mayo Clinic Nephrology Genomics Clinic to improve our ability to integrate genomic and clinical data to identify the etiology of unexplained CKD. STUDY DESIGN: Retrospective study. SETTING & PARTICIPANTS: An essential component of our program is the Nephrology Genomics Board which consists of nephrologists, geneticists, pathologists, translational omics scientists, and trainees who interpret the patient's clinical and genetic data. Since September 2016, the Board has reviewed 163 cases (15 cystic, 100 glomerular, 6 congenital anomalies of kidney and urinary tract (CAKUT), 20 stones, 15 tubulointerstitial, and 13 other). ANALYTICAL APPROACH: Testing was performed with targeted panels, single gene analysis, or analysis of kidney-related genes from exome sequencing. Variant classification was obtained based on the 2015 American College of Medical Genetics and Genomics and the Association for Molecular Pathology guidelines. RESULTS: A definitive genetic diagnosis was achieved for 50 families (30.7%). The highest diagnostic yield was obtained in individuals with tubulointerstitial diseases (53.3%), followed by congenital anomalies of the kidney and urological tract (33.3%), glomerular (31%), cysts (26.7%), stones (25%), and others (15.4%). A further 20 (12.3%) patients had variants of interest, and variant segregation, and research activities (exome, genome, or transcriptome sequencing) are ongoing for 44 (40%) unresolved families. LIMITATIONS: Possible overestimation of diagnostic rate due to inclusion of individuals with variants with evidence of pathogenicity but classified as of uncertain significance by the clinical laboratory. CONCLUSIONS: Integration of genomic and research testing and multidisciplinary evaluation in a nephrology cohort with CKD of unknown etiology or suspected monogenic disease provided a diagnosis in a third of families. These diagnoses had prognostic implications, and often changes in management were implemented.