# Genomic Approaches for Monogenic Kidney Diseases:
## 3 Discussion  
This review highlights a heterogeneity of diagnostic performance within the single technologies, rendering any comparison of technologies difficult to make. A targeted gene panel is a convenient and largely available technology in the clinical setting. It is mainly used to evaluate patients who are clinically well characterized and can assess from 10 to over 2000 genes. The diagnostic yield of the targeted panel can reach 80% in ADPKD patients [26]. However, targeted panels can become quickly outdated as new genes linked to specific clinical presentation are continuously identified, especially in the case of heterogeneous or not well clinically defined phenotypes. Initial clinical indication is not always confirmed by genetic testing, and diagnoses are changed or reclassified after genetic testing in up to 45% of cases [22]. These limitations have encouraged numerous centers around the world to adopt the WES approach, filtering for genes of interest. This makes it possible to update the list of genes to be filtered or, when appropriate, to analyze in the future. However, WES technology has a low coverage in GC-rich and homology regions, requiring an adjustment of PCR conditions. WGS overcomes this limitation, identifying structural and non-coding variants. The employment of a single method to screen patientsfor single or copy number variations and structural variants on genes, such as MUC1 or HNF1b [81,86], enables the identification of the main causes of disease. However, the high costs of WGS technology and the difficulty of data analysis make it less likely to be adopted outside of research settings [87]. The adoption of genomic methods has significantly increased the number of variants to be evaluated, raising the issue of secondary findings [82]. Currently, there is no global consensus on the management of secondary findings. A feasible, current solution involves the inclusion of panels or virtual panels focused exclusively on known diagnosis-related genes. In the case of negative results, research can then be extended [35,56]. The integration of multiple analytical methods seems to show a better average yield (Figure 1). In the scenario of increasing prevalence and demand for genomic sequencing, the identification of the most efficient and cost-effective technology is pivotal. However, the heterogeneity of the studies and the absence of direct comparison between available technologies in similar study settings, limits comparative evaluations. Table 1 reports the range of diagnostic yields reported among studies included in this review. There are no correlations between the yield and the technology used or patient age. However, no formal statistical analysis could be performed, due to the important heterogeneity of the studies meeting our inclusion criteria, type of population tested and the number of cases. Among studies of direct comparison of two technologies, WES was superior to targeted panels. However, these data may be confounded by the use of inappropriately selected disease-specific panels. Had a much broader panel, including 2700 genes been used, misdiagnoses due to heterogeneous phenotypes, phenocopies or misclassification of pathology, may have been avoided [71]. Despite the high heterogeneity and inconclusive, single study comparison of two technologies, we hypothesize that the highest diagnostic yield can be found in a well selected targeted panel strategy adopted for patients with specific clinical presentation, such as ADPKD [20,26]. Conversely, in patients with non-ADPKD clinical presentation, such as renal stones and Bartter disease, the diagnostic yield is lower, ranging from 6.8% and 17.7% [27,28]. In the case of WES technology, the results are extremely variable. The diagnostic yield reaches 42% in pediatric/adult setting in a study of 102 patients affected by CKD [50], but it is only 9.3% in a study that involved 3315 adults [54].