The diagnostic yield of exome sequencing in liver diseases from a curated gene panel.

Exome sequencing (ES) has been used in a variety of clinical settings but there are limited data on its utility for diagnosis and/or prediction of monogenic liver diseases. We developed a curated list of 502 genes for monogenic disorders associated with liver phenotypes and analyzed ES data for these genes in 758 patients with chronic liver diseases (CLD). For comparison, we examined ES data in 7856 self-declared healthy controls (HC), and 2187 patients with chronic kidney disease (CKD). Candidate pathogenic (P) or likely pathogenic (LP) variants were initially identified in 19.9% of participants, most of which were attributable to previously reported pathogenic variants with implausibly high allele frequencies. After variant annotation and filtering based on population minor allele frequency (MAF ≤ 10-4 for dominant disorders and MAF ≤ 10-3 for recessive disorders), we detected a significant enrichment of P/LP variants in the CLD cohort compared to the HC cohort (X2 test OR 5.00, 95% CI 3.06-8.18, p value = 4.5e-12). A second-level manual annotation was necessary to capture true pathogenic variants that were removed by stringent allele frequency and quality filters. After these sequential steps, the diagnostic rate of monogenic disorders was 5.7% in the CLD cohort, attributable to P/LP variants in 25 genes. We also identified concordant liver disease phenotypes for 15/22 kidney disease patients with P/LP variants in liver genes, mostly associated with cystic liver disease phenotypes. Sequencing results had many implications for clinical management, including familial testing for early diagnosis and management, preventative screening for associated comorbidities, and in some cases for therapy. Exome sequencing provided a 5.7% diagnostic rate in CLD patients and required multiple rounds of review to reduce both false positive and false negative findings. The identification of concordant phenotypes in many patients with P/LP variants and no known liver disease also indicates a potential for predictive testing for selected monogenic liver disorders.

Beyond the exome: What's next in diagnostic testing for Mendelian conditions.

Despite advances in clinical genetic testing, including the introduction of exome sequencing (ES), more than 50% of individuals with a suspected Mendelian condition lack a precise molecular diagnosis. Clinical evaluation is increasingly undertaken by specialists outside of clinical genetics, often occurring in a tiered fashion and typically ending after ES. The current diagnostic rate reflects multiple factors, including technical limitations, incomplete understanding of variant pathogenicity, missing genotype-phenotype associations, complex gene-environment interactions, and reporting differences between clinical labs. Maintaining a clear understanding of the rapidly evolving landscape of diagnostic tests beyond ES, and their limitations, presents a challenge for non-genetics professionals. Newer tests, such as short-read genome or RNA sequencing, can be challenging to order, and emerging technologies, such as optical genome mapping and long-read DNA sequencing, are not available clinically. Furthermore, there is no clear guidance on the next best steps after inconclusive evaluation. Here, we review why a clinical genetic evaluation may be negative, discuss questions to be asked in this setting, and provide a framework for further investigation, including the advantages and disadvantages of new approaches that are nascent in the clinical sphere. We present a guide for the next best steps after inconclusive molecular testing based upon phenotype and prior evaluation, including when to consider referral to research consortia focused on elucidating the underlying cause of rare unsolved genetic disorders.

Beyond the exome: what's next in diagnostic testing for Mendelian conditions.

Despite advances in clinical genetic testing, including the introduction of exome sequencing (ES), more than 50% of individuals with a suspected Mendelian condition lack a precise molecular diagnosis. Clinical evaluation is increasingly undertaken by specialists outside of clinical genetics, often occurring in a tiered fashion and typically ending after ES. The current diagnostic rate reflects multiple factors, including technical limitations, incomplete understanding of variant pathogenicity, missing genotype-phenotype associations, complex gene-environment interactions, and reporting differences between clinical labs. Maintaining a clear understanding of the rapidly evolving landscape of diagnostic tests beyond ES, and their limitations, presents a challenge for non-genetics professionals. Newer tests, such as short-read genome or RNA sequencing, can be challenging to order and emerging technologies, such as optical genome mapping and long-read DNA or RNA sequencing, are not available clinically. Furthermore, there is no clear guidance on the next best steps after inconclusive evaluation. Here, we review why a clinical genetic evaluation may be negative, discuss questions to be asked in this setting, and provide a framework for further investigation, including the advantages and disadvantages of new approaches that are nascent in the clinical sphere. We present a guide for the next best steps after inconclusive molecular testing based upon phenotype and prior evaluation, including when to consider referral to a consortium such as GREGoR, which is focused on elucidating the underlying cause of rare unsolved genetic disorders.

Rare genetic causes of complex kidney and urological diseases.

Although often considered a single-entity, chronic kidney disease (CKD) comprises many pathophysiologically distinct disorders that result in persistently abnormal kidney structure and/or function, and encompass both monogenic and polygenic aetiologies. Rare inherited forms of CKD frequently span diverse phenotypes, reflecting genetic phenomena including pleiotropy, incomplete penetrance and variable expressivity. Use of chromosomal microarray and massively parallel sequencing technologies has revealed that genomic disorders and monogenic aetiologies contribute meaningfully to seemingly complex forms of CKD across different clinically defined subgroups and are characterized by high genetic and phenotypic heterogeneity. Investigations of prevalent genomic disorders in CKD have integrated genetic, bioinformatic and functional studies to pinpoint the genetic drivers underlying their renal and extra-renal manifestations, revealing both monogenic and polygenic mechanisms. Similarly, massively parallel sequencing-based analyses have identified gene- and allele-level variation that contribute to the clinically diverse phenotypes observed for many monogenic forms of nephropathy. Genome-wide sequencing studies suggest that dual genetic diagnoses are found in at least 5% of patients in whom a genetic cause of disease is identified, highlighting the fact that complex phenotypes can also arise from multilocus variation. A multifaceted approach that incorporates genetic and phenotypic data from large, diverse cohorts will help to elucidate the complex relationships between genotype and phenotype for different forms of CKD, supporting personalized medicine for individuals with kidney disease.

Genetic testing for kidney disease of unknown etiology.

In many cases of chronic kidney disease, the cause of disease remains unknown despite a thorough nephrologic workup. Genetic testing has revolutionized many areas of medicine and promises to empower diagnosis and targeted management of such cases of kidney disease of unknown etiology. Recent studies using genetic testing have demonstrated that Mendelian etiologies account for approximately 20% of cases of kidney disease of unknown etiology. Although genetic testing has significant benefits, including tailoring of therapy, informing targeted workup, detecting extrarenal disease, counseling patients and families, and redirecting care, it also has important limitations and risks that must be considered.

Pilot Study of Return of Genetic Results to Patients in Adult Nephrology.

BACKGROUND AND OBJECTIVES: Actionable genetic findings have implications for care of patients with kidney disease, and genetic testing is an emerging tool in nephrology practice. However, there are scarce data regarding best practices for return of results and clinical application of actionable genetic findings for kidney patients. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We developed a return of results workflow in collaborations with clinicians for the retrospective recontact of adult nephrology patients who had been recruited into a biobank research study for exome sequencing and were identified to have medically actionable genetic findings. RESULTS: Using this workflow, we attempted to recontact a diverse pilot cohort of 104 nephrology research participants with actionable genetic findings, encompassing 34 different monogenic etiologies of nephropathy and five single-gene disorders recommended by the American College of Medical Genetics and Genomics for return as medically actionable secondary findings. We successfully recontacted 64 (62%) participants and returned results to 41 (39%) individuals. In each case, the genetic diagnosis had meaningful implications for the patients' nephrology care. Through implementation efforts and qualitative interviews with providers, we identified over 20 key challenges associated with returning results to study participants, and found that physician knowledge gaps in genomics was a recurrent theme. We iteratively addressed these challenges to yield an optimized workflow, which included standardized consultation notes with tailored management recommendations, monthly educational conferences on core topics in genomics, and a curated list of expert clinicians for patients requiring extranephrologic referrals. CONCLUSIONS: Developing the infrastructure to support return of genetic results in nephrology was resource-intensive, but presented potential opportunities for improving patient care. PODCAST: This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2020_04_16_12481019.mp3.

Atlas-CNV: a validated approach to call single-exon CNVs in the eMERGESeq gene panel.

PURPOSE: To provide a validated method to confidently identify exon-containing copy-number variants (CNVs), with a low false discovery rate (FDR), in targeted sequencing data from a clinical laboratory with particular focus on single-exon CNVs. METHODS: DNA sequence coverage data are normalized within each sample and subsequently exonic CNVs are identified in a batch of samples, when the target log2 ratio of the sample to the batch median exceeds defined thresholds. The quality of exonic CNV calls is assessed by C-scores (Z-like scores) using thresholds derived from gold standard samples and simulation studies. We integrate an ExonQC threshold to lower FDR and compare performance with alternate software (VisCap). RESULTS: Thirteen CNVs were used as a truth set to validate Atlas-CNV and compared with VisCap. We demonstrated FDR reduction in validation, simulation, and 10,926 eMERGESeq samples without sensitivity loss. Sixty-four multiexon and 29 single-exon CNVs with high C-scores were assessed by Multiplex Ligation-dependent Probe Amplification (MLPA). CONCLUSION: Atlas-CNV is validated as a method to identify exonic CNVs in targeted sequencing data generated in the clinical laboratory. The ExonQC and C-score assignment can reduce FDR (identification of targets with high variance) and improve calling accuracy of single-exon CNVs respectively. We propose guidelines and criteria to identify high confidence single-exon CNVs.

Expanding opportunities and emerging challenges: broadening the scope of genetic testing in nephrology.

Massively parallel sequencing technologies such as exome sequencing are increasingly applied across medicine. Connaughton et al. report a high diagnostic yield of exome sequencing among adults with hereditary nephropathy or nephropathy of unknown cause. Their findings support broader use of genomic sequencing in nephrology and highlight key associated questions, including how to identify those patients for whom testing is indicated, pinpoint pathogenic variants, and balance the resultant health care benefits and clinical follow-up burden.

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.

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.).

Deep Phenotyping on Electronic Health Records Facilitates Genetic Diagnosis by Clinical Exomes.

Integration of detailed phenotype information with genetic data is well established to facilitate accurate diagnosis of hereditary disorders. As a rich source of phenotype information, electronic health records (EHRs) promise to empower diagnostic variant interpretation. However, how to accurately and efficiently extract phenotypes from heterogeneous EHR narratives remains a challenge. Here, we present EHR-Phenolyzer, a high-throughput EHR framework for extracting and analyzing phenotypes. EHR-Phenolyzer extracts and normalizes Human Phenotype Ontology (HPO) concepts from EHR narratives and then prioritizes genes with causal variants on the basis of the HPO-coded phenotype manifestations. We assessed EHR-Phenolyzer on 28 pediatric individuals with confirmed diagnoses of monogenic diseases and found that the genes with causal variants were ranked among the top 100 genes selected by EHR-Phenolyzer for 16/28 individuals (p < 2.2 × 10-16), supporting the value of phenotype-driven gene prioritization in diagnostic sequence interpretation. To assess the generalizability, we replicated this finding on an independent EHR dataset of ten individuals with a positive diagnosis from a different institution. We then assessed the broader utility by examining two additional EHR datasets, including 31 individuals who were suspected of having a Mendelian disease and underwent different types of genetic testing and 20 individuals with positive diagnoses of specific Mendelian etiologies of chronic kidney disease from exome sequencing. Finally, through several retrospective case studies, we demonstrated how combined analyses of genotype data and deep phenotype data from EHRs can expedite genetic diagnoses. In summary, EHR-Phenolyzer leverages EHR narratives to automate phenotype-driven analysis of clinical exomes or genomes, facilitating the broader implementation of genomic medicine.

Genomic medicine for kidney disease.

Technologies such as next-generation sequencing and chromosomal microarray have advanced the understanding of the molecular pathogenesis of a variety of renal disorders. Genetic findings are increasingly used to inform the clinical management of many nephropathies, enabling targeted disease surveillance, choice of therapy, and family counselling. Genetic analysis has excellent diagnostic utility in paediatric nephrology, as illustrated by sequencing studies of patients with congenital anomalies of the kidney and urinary tract and steroid-resistant nephrotic syndrome. Although additional investigation is needed, pilot studies suggest that genetic testing can also provide similar diagnostic insight among adult patients. Reaching a genetic diagnosis first involves choosing the appropriate testing modality, as guided by the clinical presentation of the patient and the number of potential genes associated with the suspected nephropathy. Genome-wide sequencing increases diagnostic sensitivity relative to targeted panels, but holds the challenges of identifying causal variants in the vast amount of data generated and interpreting secondary findings. In order to realize the promise of genomic medicine for kidney disease, many technical, logistical, and ethical questions that accompany the implementation of genetic testing in nephrology must be addressed. The creation of evidence-based guidelines for the utilization and implementation of genetic testing in nephrology will help to translate genetic knowledge into improved clinical outcomes for patients with kidney disease.

Towards precision nephrology: the opportunities and challenges of genomic medicine.

The expansion of genomic medicine is furthering our understanding of many human diseases. This is well illustrated in the field of nephrology, through the characterization, discovery, and growing insight into various renal diseases through use of Next Generation Sequencing (NGS) technologies. This review will provide an overview of the diagnostic opportunities of using genetic testing in the clinical setting by describing notable discoveries regarding inherited forms of renal disease that have advanced the field and by highlighting some of the potential benefits of establishing a molecular diagnosis in a clinical practice. In addition, it will discuss some of the challenges associated with the expansion of genetic testing into the clinical setting, including clinical variant interpretation and return of genetic results.

Genetic Evidence of Human Adaptation to a Cooked Diet.

Humans have been argued to be biologically adapted to a cooked diet, but this hypothesis has not been tested at the molecular level. Here, we combine controlled feeding experiments in mice with comparative primate genomics to show that consumption of a cooked diet influences gene expression and that affected genes bear signals of positive selection in the human lineage. Liver gene expression profiles in mice fed standardized diets of meat or tuber were affected by food type and cooking, but not by caloric intake or consumer energy balance. Genes affected by cooking were highly correlated with genes known to be differentially expressed in liver between humans and other primates, and more genes in this overlap set show signals of positive selection in humans than would be expected by chance. Sequence changes in the genes under selection appear before the split between modern humans and two archaic human groups, Neandertals and Denisovans, supporting the idea that human adaptation to a cooked diet had begun by at least 275,000 years ago.

Cooking increases net energy gain from a lipid-rich food.

Starch, protein, and lipid are three major sources of calories in the human diet. The unique and universal human practice of cooking has been demonstrated to increase the energy gained from foods rich in starch or protein. Yet no studies have tested whether cooking has equivalent effects on the energy gained from lipid-rich foods. Using mice as a model, we addressed this question by examining the impact of cooking on the energy gained from peanuts, a lipid-rich oilseed, and compared this impact against that of nonthermal processing (blending). We found that cooking consistently increased the energy gained per calorie, whereas blending had no detectable energetic benefits. Assessment of fecal fat excretion showed increases in lipid digestibility when peanuts were cooked, and examination of diet microstructure revealed concomitant alterations to the integrity of cell walls and the oleosin layer of proteins that otherwise shield lipids from digestive lipases. Both effects were consistent with the greater energy gain observed with cooking. Our findings highlight the importance of cooking in increasing dietary energy returns for humans, both past and present.