Evidence of epistasis in regions of long-range linkage disequilibrium across five complex diseases in the UK Biobank and eMERGE datasets.

Leveraging linkage disequilibrium (LD) patterns as representative of population substructure enables the discovery of additive association signals in genome-wide association studies (GWASs). Standard GWASs are well-powered to interrogate additive models; however, new approaches are required for invesigating other modes of inheritance such as dominance and epistasis. Epistasis, or non-additive interaction between genes, exists across the genome but often goes undetected because of a lack of statistical power. Furthermore, the adoption of LD pruning as customary in standard GWASs excludes detection of sites that are in LD but might underlie the genetic architecture of complex traits. We hypothesize that uncovering long-range interactions between loci with strong LD due to epistatic selection can elucidate genetic mechanisms underlying common diseases. To investigate this hypothesis, we tested for associations between 23 common diseases and 5,625,845 epistatic SNP-SNP pairs (determined by Ohta's D statistics) in long-range LD (>0.25 cM). Across five disease phenotypes, we identified one significant and four near-significant associations that replicated in two large genotype-phenotype datasets (UK Biobank and eMERGE). The genes that were most likely involved in the replicated associations were (1) members of highly conserved gene families with complex roles in multiple pathways, (2) essential genes, and/or (3) genes that were associated in the literature with complex traits that display variable expressivity. These results support the highly pleiotropic and conserved nature of variants in long-range LD under epistatic selection. Our work supports the hypothesis that epistatic interactions regulate diverse clinical mechanisms and might especially be driving factors in conditions with a wide range of phenotypic outcomes.

Do research participants share genomic screening results with family members?

The public health impact of genomic screening can be enhanced by cascade testing. However, cascade testing depends on communication of results to family members. While the barriers and facilitators of family communication have been researched following clinical genetic testing, the factors impacting the dissemination of genomic screening results are unknown. Using the pragmatic Electronic Medical Records and Genomics Network-3 (eMERGE-3) study, we explored the reported sharing practices of participants who underwent genomic screening across the United States. Six eMERGE-3 sites returned genomic screening results for mostly dominant medically actionable disorders and surveyed adult participants regarding communication of results with first-degree relatives. Across the sites, 279 participants completed a 1-month and/or 6-month post-results survey. By 6 months, only 34% of the 156 respondents shared their results with all first-degree relatives and 4% did not share with any. Over a third (39%) first-degree relatives were not notified of the results. Half (53%) of participants who received their results from a genetics provider shared them with all first-degree relatives compared with 11% of participants who received their results from a non-genetics provider. The most frequent reasons for sharing were a feeling of obligation (72%) and that the information could help family members make medical decisions (72%). The most common reasons indicated for not sharing were that the family members were too young (38%), or they were not in contact (25%) or not close to them (25%). These data indicate that the professional returning the results may impact sharing patterns, suggesting that there is a need to continue to educate healthcare providers regarding approaches to facilitate sharing of genetic results within families. Finally, these data suggest that interventions to increase sharing may be universally effective regardless of the origin of the genetic result.

Generalizability of Polygenic Risk Scores for Breast Cancer Among Women With European, African, and Latinx Ancestry.

Importance: Multiple polygenic risk scores (PRSs) for breast cancer have been developed from large research consortia; however, their generalizability to diverse clinical settings is unknown. Objective: To examine the performance of previously developed breast cancer PRSs in a clinical setting for women of European, African, and Latinx ancestry. Design, Setting, and Participants: This cohort study using the Electronic Medical Records and Genomics (eMERGE) network data set included 39 591 women from 9 contributing medical centers in the US that had electronic medical records (EMR) linked to genotype data. Breast cancer cases and controls were identified through a validated EMR phenotyping algorithm. Main Outcomes and Measures: Multivariable logistic regression was used to assess the association between breast cancer risk and 7 previously developed PRSs, adjusting for age, study site, breast cancer family history, and first 3 ancestry informative principal components. Results: This study included 39 591 women: 33 594 with European, 3801 with African, and 2196 with Latinx ancestry. The mean (SD) age at breast cancer diagnosis was 60.7 (13.0), 58.8 (12.5), and 60.1 (13.0) years for women with European, African, and Latinx ancestry, respectively. PRSs derived from women with European ancestry were associated with breast cancer risk in women with European ancestry (highest odds ratio [OR] per 1-SD increase, 1.46; 95% CI, 1.41-1.51), women with Latinx ancestry (highest OR, 1.31; 95% CI, 1.09-1.58), and women with African ancestry (OR, 1.19; 95% CI, 1.05-1.35). For women with European ancestry, this association with breast cancer risk was largest in the extremes of the PRS distribution, with ORs ranging from 2.19 (95% CI, 1.84-2.53) to 2.48 (95% CI, 1.89-3.25) for the 3 different PRSs examined for those in the highest 1% of the PRS compared with those in the middle quantile. Among women with Latinx and African ancestries at the extremes of the PRS distribution, there were no statistically significant associations. Conclusions and Relevance: This cohort study found that PRS models derived from women with European ancestry for breast cancer risk generalized well for women with European, Latinx, and African ancestries across different clinical settings, although the effect sizes for women with African ancestry were smaller, likely because of differences in risk allele frequencies and linkage disequilibrium patterns. These results highlight the need to improve representation of diverse population groups, particularly women with African ancestry, in genomic research cohorts.

Genomic considerations for FHIR®; eMERGE implementation lessons.

Structured representation of clinical genetic results is necessary for advancing precision medicine. The Electronic Medical Records and Genomics (eMERGE) Network's Phase III program initially used a commercially developed XML message format for standardized and structured representation of genetic results for electronic health record (EHR) integration. In a desire to move towards a standard representation, the network created a new standardized format based upon Health Level Seven Fast Healthcare Interoperability Resources (HL7® FHIR®), to represent clinical genomics results. These new standards improve the utility of HL7® FHIR® as an international healthcare interoperability standard for management of genetic data from patients. This work advances the establishment of standards that are being designed for broad adoption in the current health information technology landscape.

Medical records-based chronic kidney disease phenotype for clinical care and "big data" observational and genetic studies.

Chronic Kidney Disease (CKD) represents a slowly progressive disorder that is typically silent until late stages, but early intervention can significantly delay its progression. We designed a portable and scalable electronic CKD phenotype to facilitate early disease recognition and empower large-scale observational and genetic studies of kidney traits. The algorithm uses a combination of rule-based and machine-learning methods to automatically place patients on the staging grid of albuminuria by glomerular filtration rate ("A-by-G" grid). We manually validated the algorithm by 451 chart reviews across three medical systems, demonstrating overall positive predictive value of 95% for CKD cases and 97% for healthy controls. Independent case-control validation using 2350 patient records demonstrated diagnostic specificity of 97% and sensitivity of 87%. Application of the phenotype to 1.3 million patients demonstrated that over 80% of CKD cases are undetected using ICD codes alone. We also demonstrated several large-scale applications of the phenotype, including identifying stage-specific kidney disease comorbidities, in silico estimation of kidney trait heritability in thousands of pedigrees reconstructed from medical records, and biobank-based multicenter genome-wide and phenome-wide association studies.

An electronic health record (EHR) log analysis shows limited clinician engagement with unsolicited genetic test results.

How clinicians utilize medically actionable genomic information, displayed in the electronic health record (EHR), in medical decision-making remains unknown. Participating sites of the Electronic Medical Records and Genomics (eMERGE) Network have invested resources into EHR integration efforts to enable the display of genetic testing data across heterogeneous EHR systems. To assess clinicians' engagement with unsolicited EHR-integrated genetic test results of eMERGE participants within a large tertiary care academic medical center, we analyzed automatically generated EHR access log data. We found that clinicians viewed only 1% of all the eMERGE genetic test results integrated in the EHR. Using a cluster analysis, we also identified different user traits associated with varying degrees of engagement with the EHR-integrated genomic data. These data contribute important empirical knowledge about clinicians limited and brief engagements with unsolicited EHR-integrated genetic test results of eMERGE participants. Appreciation for user-specific roles provide additional context for why certain users were more or less engaged with the unsolicited results. This study highlights opportunities to use EHR log data as a performance metric to more precisely inform ongoing EHR-integration efforts and decisions about the allocation of informatics resources in genomic research.

Copy Number Variant Analysis and Genome-wide Association Study Identify Loci with Large Effect for Vesicoureteral Reflux.

BACKGROUND: Vesicoureteral reflux (VUR) is a common, familial genitourinary disorder, and a major cause of pediatric urinary tract infection (UTI) and kidney failure. The genetic basis of VUR is not well understood. METHODS: A diagnostic analysis sought rare, pathogenic copy number variant (CNV) disorders among 1737 patients with VUR. A GWAS was performed in 1395 patients and 5366 controls, of European ancestry. RESULTS: Altogether, 3% of VUR patients harbored an undiagnosed rare CNV disorder, such as the 1q21.1, 16p11.2, 22q11.21, and triple X syndromes ((OR, 3.12; 95% CI, 2.10 to 4.54; P=6.35×10-8) The GWAS identified three study-wide significant and five suggestive loci with large effects (ORs, 1.41-6.9), containing canonical developmental genes expressed in the developing urinary tract (WDPCP, OTX1, BMP5, VANGL1, and WNT5A). In particular, 3.3% of VUR patients were homozygous for an intronic variant in WDPCP (rs13013890; OR, 3.65; 95% CI, 2.39 to 5.56; P=1.86×10-9). This locus was associated with multiple genitourinary phenotypes in the UK Biobank and eMERGE studies. Analysis of Wnt5a mutant mice confirmed the role of Wnt5a signaling in bladder and ureteric morphogenesis. CONCLUSIONS: These data demonstrate the genetic heterogeneity of VUR. Altogether, 6% of patients with VUR harbored a rare CNV or a common variant genotype conferring an OR >3. Identification of these genetic risk factors has multiple implications for clinical care and for analysis of outcomes in VUR.

Loci identified by a genome-wide association study of carotid artery stenosis in the eMERGE network.

Carotid artery atherosclerotic disease (CAAD) is a risk factor for stroke. We used a genome-wide association (GWAS) approach to discover genetic variants associated with CAAD in participants in the electronic Medical Records and Genomics (eMERGE) Network. We identified adult CAAD cases with unilateral or bilateral carotid artery stenosis and controls without evidence of stenosis from electronic health records at eight eMERGE sites. We performed GWAS with a model adjusting for age, sex, study site, and genetic principal components of ancestry. In eMERGE we found 1793 CAAD cases and 17,958 controls. Two loci reached genome-wide significance, on chr6 in LPA (rs10455872, odds ratio [OR] (95% confidence interval [CI]) = 1.50 (1.30-1.73), p = 2.1 × 10-8 ) and on chr7, an intergenic single nucleotide variant (SNV; rs6952610, OR (95% CI) = 1.25 (1.16-1.36), p = 4.3 × 10-8 ). The chr7 association remained significant in the presence of the LPA SNV as a covariate. The LPA SNV was also associated with coronary heart disease (CHD; 4199 cases and 11,679 controls) in this study (OR (95% CI) = 1.27 (1.13-1.43), p = 5 × 10-5 ) but the chr7 SNV was not (OR (95% CI) = 1.03 (0.97-1.09), p = .37). Both variants replicated in UK Biobank. Elevated lipoprotein(a) concentrations ([Lp(a)]) and LPA variants associated with elevated [Lp(a)] have previously been associated with CAAD and CHD, including rs10455872. With electronic health record phenotypes in eMERGE and UKB, we replicated a previously known association and identified a novel locus associated with CAAD.

GeneLiFT: A novel test to facilitate rapid screening of genetic literacy in a diverse population undergoing genetic testing.

With the broader introduction of genomic medicine in research and clinical care, an increasing number of persons are offered genetic testing. Many factors, including genetic literacy, may impact the utilization of genetic results by patients and their families. We developed a rapid, self-administered measure of genetic literacy, called Genetic Literacy Fast Test (GeneLiFT). We next evaluated the association of GeneLiFT scores with the comprehension of limitations of genomic medicine in participants undergoing genetic testing in the NIH-sponsored eMERGE III study at Columbia University Irving Medical Center, New York. All participants underwent genetic screening for variants in 74 actionable genes associated with adult-onset disorders. A diverse cohort of 724 participants completed the survey (60% women, 45% less than 40 years old, and 53% self-reported White non-Hispanic ancestry). The GeneLiFT was validated using known group differences based on education, health literacy, and numeracy, and with questions assessing genetic knowledge. GeneLiFT identified multiple standard genetics terms, that is, jargon, not recognized by more than 50% of participants (including actionability and pathogenicity). Low genetic literacy, identified in 210 participants (29%), was significantly associated with poor understanding of the limitations of genetic testing (p-values < 10-9 ). This association was independent of education, health literacy, and numeracy levels, highlighting the importance of directly measuring genetic literacy. Low genetic literacy was also associated with low satisfaction with the informed consent process. GeneLiFT is a practical tool for rapid assessment of genetic literacy in large studies or clinical care. GeneLiFT will allow future research to efficiently assess the role of genetic literacy on the clinical impact of genetic testing.

Rapid exome sequencing in PICU patients with new-onset metabolic or neurological disorders.

BACKGROUND: Genomic assessment previously took months to result and was unable to impact clinical care in the pediatric intensive care unit (PICU). The advent of rapid exome sequencing potentially changes this. We investigated the impact of rapid exome sequencing in a pilot study on pediatric patients admitted to a single PICU with new-onset metabolic/neurologic disease. METHODS: Rapid exome sequencing (7 days to verbal result) was performed on (n = 10) PICU patients age < 6 years admitted with new-onset metabolic/neurologic disease. The primary outcome of interest was inpatient LOS, which served as a proxy for inpatient cost. RESULTS: A significant reduction in median LOS was identified when comparing PICU patients who underwent rapid exome sequencing to historical controls. From those patients who underwent rapid sequencing, five had likely pathogenic variants. In three cases with diagnostic genetic results, there was a modification to clinical care attributable to information provided by exome sequencing. CONCLUSIONS: This pilot study demonstrates that rapid exome sequencing is feasible to do in the PICU, that genetic results can be returned quickly enough to impact critical care decision-making and management. In a select population of PICU patients, this technology may contribute to a decrease in hospital length of stay. IMPACT: Ten prospectively enrolled PICU patients with defined clinical criteria and their parents underwent rapid exome sequencing. Fifty percent received a genetic diagnosis, and medical management was affected for 60% of those patients. Median hospital LOS was significantly decreased in this selective subset of PICU patients. Genetic disorders and congenital anomalies are a leading cause of pediatric mortality. Genomic assessment previously took weeks to months for results and was therefore unable to acutely impact clinical care in the pediatric intensive care unit (PICU). The recent advent of rapid exome sequencing changes this in selected patients. Rapid exome sequencing is feasible to do in a PICU. Genetic results can be returned quickly enough to impact critical care decision-making. When done in a carefully selected subset of pediatric patients, rapid exome sequencing can potentially decrease hospital LOS.

Correction: Evaluation of the cost and effectiveness of diverse recruitment methods for a genetic screening study.

The original version of this Article contained an error in the undergraduate degree awarded to the author Ian Halim, which was incorrectly given as BS. This has now been corrected to BA in both the PDF and HTML versions of the Article.

Evaluation of the cost and effectiveness of diverse recruitment methods for a genetic screening study.

PURPOSE: Recruitment of participants from diverse backgrounds is crucial to the generalizability of genetic research, but has proven challenging. We retrospectively evaluated recruitment methods used for a study on return of genetic results. METHODS: The costs of study design, development, and participant enrollment were calculated, and the characteristics of the participants enrolled through the seven recruitment methods were examined. RESULTS: A total of 1118 participants provided consent, a blood sample, and questionnaire data. The estimated cost across recruitment methods ranged from $579 to $1666 per participant and required a large recruitment team. Recruitment methods using flyers and staff networks were the most cost-efficient and resulted in the highest completion rate. Targeted sampling that emphasized the importance of Latino/a participation, utilization of translated materials, and in-person recruitments contributed to enrolling a demographically diverse sample. CONCLUSIONS: Although all methods were deployed in the same hospital or neighborhood and shared the same staff, each recruitment method was different in terms of cost and characteristics of the enrolled participants, suggesting the importance of carefully choosing the recruitment methods based on the desired composition of the final study sample. This analysis provides information about the effectiveness and cost of different methods to recruit adults for genetic research.

Detecting potential pleiotropy across cardiovascular and neurological diseases using univariate, bivariate, and multivariate methods on 43,870 individuals from the eMERGE network.

The link between cardiovascular diseases and neurological disorders has been widely observed in the aging population. Disease prevention and treatment rely on understanding the potential genetic nexus of multiple diseases in these categories. In this study, we were interested in detecting pleiotropy, or the phenomenon in which a genetic variant influences more than one phenotype. Marker-phenotype association approaches can be grouped into univariate, bivariate, and multivariate categories based on the number of phenotypes considered at one time. Here we applied one statistical method per category followed by an eQTL colocalization analysis to identify potential pleiotropic variants that contribute to the link between cardiovascular and neurological diseases. We performed our analyses on ~530,000 common SNPs coupled with 65 electronic health record (EHR)-based phenotypes in 43,870 unrelated European adults from the Electronic Medical Records and Genomics (eMERGE) network. There were 31 variants identified by all three methods that showed significant associations across late onset cardiac- and neurologic- diseases. We further investigated functional implications of gene expression on the detected "lead SNPs" via colocalization analysis, providing a deeper understanding of the discovered associations. In summary, we present the framework and landscape for detecting potential pleiotropy using univariate, bivariate, multivariate, and colocalization methods. Further exploration of these potentially pleiotropic genetic variants will work toward understanding disease causing mechanisms across cardiovascular and neurological diseases and may assist in considering disease prevention as well as drug repositioning in future research.

Author Correction: The copy number variation landscape of congenital anomalies of the kidney and urinary tract.

In the version of this article initially published, affiliation 38 incorrectly read "ICNU-Nephrology and Urology Department, Barcelona, Spain"; "Renal Division, Hospital Clinic, IDIBAPS, University of Barcelona, Barcelona, Spain" is the correct affiliation. The error has been corrected in the HTML and PDF versions of the article.

Association of Thyroid Function Genetic Predictors With Atrial Fibrillation: A Phenome-Wide Association Study and Inverse-Variance Weighted Average Meta-analysis.

Importance: Thyroid hormone levels are tightly regulated through feedback inhibition by thyrotropin, produced by the pituitary gland. Hyperthyroidism is overwhelmingly due to thyroid disorders and is well recognized to contribute to a wide spectrum of cardiovascular morbidity, particularly the increasingly common arrhythmia atrial fibrillation (AF). Objective: To determine the association between genetically determined thyrotropin levels and AF. Design, Setting, and Participants: This phenome-wide association study scanned 1318 phenotypes associated with a polygenic predictor of thyrotropin levels identified by a previously published genome-wide association study that included participants of European ancestry. North American individuals of European ancestry with longitudinal electronic health records were analyzed from May 2008 to November 2016. Analysis began March 2018. Main Outcomes and Measures: Clinical diagnoses associated with a polygenic predictor of thyrotropin levels. Exposures: Genetically determined thyrotropin levels. Results: Of 37 154 individuals, 19 330 (52%) were men. The thyrotropin polygenic predictor was positively associated with hypothyroidism (odds ratio [OR], 1.10; 95% CI, 1.07-1.14; P = 5 × 10-11) and inversely associated with diagnoses related to hyperthyroidism (OR, 0.64; 95% CI, 0.54-0.74; P = 2 × 10-8 for toxic multinodular goiter). Among nonthyroid associations, the top association was AF/flutter (OR, 0.93; 95% CI, 0.9-0.95; P = 9 × 10-7). When the analyses were repeated excluding 9801 individuals with any diagnoses of a thyroid-related disease, the AF association persisted (OR, 0.91; 95% CI, 0.88-0.95; P = 2.9 × 10-6). To replicate this association, we conducted an inverse-variance weighted average meta-analysis using AF single-nucleotide variant weights from a genome-wide association study of 17 931 AF cases and 115 142 controls. As in the discovery analyses, each SD increase in predicted thyrotropin was associated with a decreased risk of AF (OR, 0.86; 95% CI, 0.79-0.93; P = 4.7 × 10-4). In a set of AF cases (n = 745) and controls (n = 1680) older than 55 years, directly measured thyrotropin levels that fell within the normal range were inversely associated with AF risk (OR, 0.91; 95% CI, 0.83-0.99; P = .04). Conclusions and Relevance: This study suggests a role for genetically determined variation in thyroid function within a physiologically accepted normal range as a risk factor for AF. The clinical decision to treat subclinical thyroid disease should incorporate the risk for AF as antithyroid medications to treat hyperthyroidism may reduce AF risk and thyroid hormone replacement for hypothyroidism may increase AF risk.

The Burden of Candidate Pathogenic Variants for Kidney and Genitourinary Disorders Emerging From Exome Sequencing.

Background: Exome sequencing is increasingly being used for clinical diagnostics, with an impetus to expand reporting of incidental findings across a wide range of disorders. Analysis of population cohorts can help reduce risk for genetic variant misclassification and resultant unnecessary referrals to subspecialists. Objective: To examine the burden of candidate pathogenic variants for kidney and genitourinary disorders emerging from exome sequencing. Design: Secondary analysis of genetic data. Setting: A tertiary care academic medical center. Patients: A convenience sample of exome sequence data from 7974 self-declared healthy adults. Measurements: Assessment of the prevalence of candidate pathogenic variants in 625 genes associated with Mendelian kidney and genitourinary disorders. Results: Of all participants, 23.3% carried a candidate pathogenic variant, most of which were attributable to previously reported variants that had implausibly high allele frequencies. In particular, 25 genes (discovered before the creation of the Exome Aggregation Consortium, a genetic database comprising data from a large control population) accounted for 67.7% of persons with candidate pathogenic variants. After stringent filtering based on allele frequency, 1.4% of persons still had a candidate pathogenic variant, an excessive rate given the prevalence of monogenic kidney and genitourinary disorders. Manual annotation of a subset of variants showed that the majority would be classified as nonbenign under current guidelines for clinical sequence interpretation and could prompt subspecialty referrals if returned. Limitation: Limited access to health record data prevented comprehensive assessment of the phenotypic concordance with genetic diagnoses. Conclusion: Widespread reporting of incidental genetic findings related to kidney and genitourinary disorders will require stringent curation of clinical variant databases and detailed case-level review to avoid genetic misdiagnosis and unnecessary referrals. These findings motivate similar analyses for genes relevant to other medical subspecialties. Primary Funding Source: National Institute of Diabetes and Digestive and Kidney Diseases and National Human Genome Research Institute.

The copy number variation landscape of congenital anomalies of the kidney and urinary tract.

Congenital anomalies of the kidney and urinary tract (CAKUT) are a major cause of pediatric kidney failure. We performed a genome-wide analysis of copy number variants (CNVs) in 2,824 cases and 21,498 controls. Affected individuals carried a significant burden of rare exonic (that is, affecting coding regions) CNVs and were enriched for known genomic disorders (GD). Kidney anomaly (KA) cases were most enriched for exonic CNVs, encompassing GD-CNVs and novel deletions; obstructive uropathy (OU) had a lower CNV burden and an intermediate prevalence of GD-CNVs; and vesicoureteral reflux (VUR) had the fewest GD-CNVs but was enriched for novel exonic CNVs, particularly duplications. Six loci (1q21, 4p16.1-p16.3, 16p11.2, 16p13.11, 17q12 and 22q11.2) accounted for 65% of patients with GD-CNVs. Deletions at 17q12, 4p16.1-p16.3 and 22q11.2 were specific for KA; the 16p11.2 locus showed extensive pleiotropy. Using a multidisciplinary approach, we identified TBX6 as a driver for the CAKUT subphenotypes in the 16p11.2 microdeletion syndrome.

Diagnostic Utility of Exome Sequencing for Kidney Disease.

BACKGROUND: Exome sequencing is emerging as a first-line diagnostic method in some clinical disciplines, but its usefulness has yet to be examined for most constitutional disorders in adults, including chronic kidney disease, which affects more than 1 in 10 persons globally. METHODS: We conducted exome sequencing and diagnostic analysis in two cohorts totaling 3315 patients with chronic kidney disease. We assessed the diagnostic yield and, among the patients for whom detailed clinical data were available, the clinical implications of diagnostic and other medically relevant findings. RESULTS: In all, 3037 patients (91.6%) were over 21 years of age, and 1179 (35.6%) were of self-identified non-European ancestry. We detected diagnostic variants in 307 of the 3315 patients (9.3%), encompassing 66 different monogenic disorders. Of the disorders detected, 39 (59%) were found in only a single patient. Diagnostic variants were detected across all clinically defined categories, including congenital or cystic renal disease (127 of 531 patients [23.9%]) and nephropathy of unknown origin (48 of 281 patients [17.1%]). Of the 2187 patients assessed, 34 (1.6%) had genetic findings for medically actionable disorders that, although unrelated to their nephropathy, would also lead to subspecialty referral and inform renal management. CONCLUSIONS: Exome sequencing in a combined cohort of more than 3000 patients with chronic kidney disease yielded a genetic diagnosis in just under 10% of cases. (Funded by the National Institutes of Health and others.).

Whole-Exome Sequencing in Adults With Chronic Kidney Disease: A Pilot Study.

Background: The utility of whole-exome sequencing (WES) for the diagnosis and management of adult-onset constitutional disorders has not been adequately studied. Genetic diagnostics may be advantageous in adults with chronic kidney disease (CKD), in whom the cause of kidney failure often remains unknown. Objective: To study the diagnostic utility of WES in a selected referral population of adults with CKD. Design: Observational cohort. Setting: A major academic medical center. Patients: 92 adults with CKD of unknown cause or familial nephropathy or hypertension. Measurements: The diagnostic yield of WES and its potential effect on clinical management. Results: Whole-exome sequencing provided a diagnosis in 22 of 92 patients (24%), including 9 probands with CKD of unknown cause and encompassing 13 distinct genetic disorders. Among these, loss-of-function mutations were identified in PARN in 2 probands with tubulointerstitial fibrosis. PARN mutations have been implicated in a short telomere syndrome characterized by lung, bone marrow, and liver fibrosis; these findings extend the phenotype of PARN mutations to renal fibrosis. In addition, review of the American College of Medical Genetics actionable genes identified a pathogenic BRCA2 mutation in a proband who was diagnosed with breast cancer on follow-up. The results affected clinical management in most identified cases, including initiation of targeted surveillance, familial screening to guide donor selection for transplantation, and changes in therapy. Limitation: The small sample size and recruitment at a tertiary care academic center limit generalizability of findings among the broader CKD population. Conclusion: Whole-exome sequencing identified diagnostic mutations in a substantial number of adults with CKD of many causes. Further study of the utility of WES in the evaluation and care of patients with CKD in additional settings is warranted. Primary Funding Source: New York State Empire Clinical Research Investigator Program, Renal Research Institute, and National Human Genome Research Institute of the National Institutes of Health.