Clinical exome sequencing is a powerful tool in the diagnostic flow of monogenic kidney diseases: an Italian experience.

BACKGROUND: A considerable minority of patients on waiting lists for kidney transplantation either have no diagnosis (and fall into the subset of undiagnosed cases) because kidney biopsy was not performed or histological findings were non-specific, or do not fall into any well-defined clinical category. Some of these patients might be affected by a previously unrecognised monogenic disease. METHODS: Through a multidisciplinary cooperative effort, we built an analytical pipeline to identify patients with chronic kidney disease (CKD) with a clinical suspicion of a monogenic condition or without a well-defined diagnosis. Following the stringent phenotypical and clinical characterization required by the flowchart, candidates meeting these criteria were further investigated by clinical exome sequencing followed by in silico analysis of 225 kidney-disease-related genes. RESULTS: By using an ad hoc web-based platform, we enrolled 160 patients from 13 different Nephrology and Genetics Units located across the Piedmont region over 15 months. A preliminary "remote" evaluation based on well-defined inclusion criteria allowed us to define eligibility for NGS analysis. Among the 138 recruited patients, 52 (37.7%) were children and 86 (62.3%) were adults. Up to 48% of them had a positive family history for kidney disease. Overall, applying this workflow led to the identification of genetic variants potentially explaining the phenotype in 78 (56.5%) cases. CONCLUSIONS: These results underline the importance of clinical exome sequencing as a versatile and highly useful, non-invasive tool for genetic diagnosis of kidney diseases. Identifying patients who can benefit from targeted therapies, and improving the management of organ transplantation are further expected applications.

Impact of type 2 diabetes mellitus on kidney transplant rates and clinical outcomes among waitlisted candidates in a single center European experience.

Despite type 2 diabetes mellitus (T2D) is commonly considered a detrimental factor in dialysis, its clear effect on morbidity and mortality on waitlisted patients for kidney transplant (KT) has never been completely elucidated. We performed a retrospective analysis on 714 patients admitted to wait-list (WL) for their first kidney transplant from 2005 to 2010. Clinical characteristics at registration in WL (age, body mass index -BMI-, duration and modality of dialysis, underlying nephropathy, coronary artery -CAD- and/or peripheral vascular disease), mortality rates, and effective time on WL were investigated and compared according to T2D status (presence/absence). Data about therapy and management of T2D were also considered. At the time of WL registration T2D patients (n = 86) were older than non-T2D (n = 628) (58.7 ± 8.6 years vs 51.3 ± 12.9) with higher BMI (26.2 ± 3.8 kg/m2 vs 23.8 ± 3.6), more frequent history of CAD (33.3% vs 9.8%) and peripheral vascular disease (25.3% vs 5.8%) (p < 0.001 for all analyses). Considering overall population, T2D patients had reduced survival vs non-T2D (p < 0.001). Transplanted patients showed better survival in both T2D and non-T2D groups despite transplant rate are lower in T2D (75.6% vs 85.8%, p < 0.001). T2D was also associated to similar waiting time but longer periods between dialysis start and registration in WL (1.6 years vs 1.2, p = 0.008), comorbidity-related suspension from WL (571 days vs 257, p = 0.002), and increased mortality rate (33.7% vs 13.9% in the overall population, p < 0.001). In T2D patients admitted to WL, an history of vascular disease was significantly associated to low patient survival (p = 0.019). In conclusion, T2D significantly affects survival also on waitlisted patients. Allocation policies in T2D patients may be adjusted according to increased risk of mortality and WL suspension due to comorbidities.