Personalized Approaches to the Diagnosis and Treatment of Chronic Kidney Disease

Recent publications using whole exome sequencing (WES) in chronic kidney disease (CKD) patients place nephrology squarely in the cusp of a major advance in the diagnosis and treatment of CKD1-4. Patients with any form of CKD could benefit, but especially those with a strong family history of CKD with no obvious cause.

WES will become a central part of our work-up of patients, as it is currently for patients with cancer. Moreover, as WES becomes a mainstay in the work-up of patients with CKD we will all need to know more about WES: who should be tested and what should we do with the information?

WES has its origins with traditional genetic sequencing (the Sanger method, named for Frederick Sanger), using gels that were expensive, laborious to work with, and inefficient. Automation speeded up sequencing, but it still required years to sequence a person’s whole genome. Because only 1% of the genome comprises the protein-coding sequences (the exons), it soon became clear that using next generation sequencing such as WES to sequence all of the exons (collectively known as the exome), most variations in the protein coding regions could be detected. WES both increased efficiency and reduced cost. However, a key disadvantage of sequencing the whole exome rather than the whole genome is that valuable information that might reside in non-coding sequences (introns) could be lost. Still, for clinical diagnostic purposes rather than research efficiency, cost and speed has won over comprehensiveness.

A recent potentially landmark paper published in the New England Journal of Medicine by Groopman and colleagues from Columbia University1 is really well done and represents a huge advance in the work-up and treatment of CKD.

The authors conducted WES in two cohorts (n= 3315). About one-third  of the patients (1128 hemodialysis patients) were from the A Study to Evaluate the Use of Rosuvastatin in Subjects on Regular Hemodialysis: An Assessment of Survival and Cardiovascular Events (AURORA), and about two-thirds (2187 patients mostly with parenchymal kidney disease) from a bio bank established by the Columbia University Medical Center (CUMC) Genetic Studies of Chronic Kidney Disease. The key characteristics of the cohort were that patients were mostly adults (91.6% >21 years of age), with one-third of non-European ancestry. All of the major categories of nephropathy were represented, including approximately 9% with nephropathy of unknown origin. Nearly two-thirds of the cohort had end-stage renal disease. The investigators only had family history available in the CUMC cohort, and nearly 30% were positive for a family history of kidney disease.

The key findings were that diagnostic variants were detected in 9.3% of patients. Nearly two-thirds of patients had an autosomal dominant disease encompassing 66 distinct monogenic disorders. Among these 66 monogenic disorders, autosomal dominant polycystic kidney disease (ADPKD) due to mutations in PKD1 or PKD2; glomerulopathy due to mutations in COL4A3, COL4A4, or COL4; and UMOD-associated tubulointerstitial disease were the most frequent culprits.

Diagnostic yield for WES was greatest for patients with a clinical diagnosis of congenital or cystic renal disease (~24%) and patients with nephropathy of unknown origin (~17%). The APOL1 risk genotype was detected in~29% of black patients and 7% of Hispanic patients. The APOL1 risk genotypes were also detected in patients with glomerulopathy (22%), particularly those with a diagnosis of focal segmental glomerulosclerosis (48%), hypertensive nephropathy (23%), or nephropathy of unknown origin.

The study supported three important conclusions:

  1. In many patients, particularly from the better-characterized CUMC cohort, genetic diagnosis using WES provided new clinical insight, including more precise diagnosis, the potential for better estimation of the risk of nephropathy progression, and guidance for donor selection for transplantation.
  2. WES enabled identification of a specific underlying cause among those with CKD—by pinpointing the precise genetic subtype of focal segmental glomerulosclerosis or cystic disease, for example—allowing for either better classification or even reclassification of disease.
  3. WES helped distinguish patients with CKD from genetic causes that result in structural changes to the glomerular barrier versus from causes that might have acquired immunological etiology, the latter potentially being more amenable to targeted immunosuppression—sparing some patients the unnecessary risk of toxicity from powerful immunosuppressive medications that might not work.

The take home message is that personalized approaches in CKD diagnosis and management are now at our doorstep and we had better take notice.


1. Groopman EE, Marasa M, Cameron-Christie S, et al. Diagnostic Utility of Exome Sequencing for Kidney Disease. N Engl J Med. 2019 Jan 10;380(2):142-151. Epub 2018 Dec 26.

2. Connaughton DM, Hildebrandt F. Personalized medicine in chronic kidney disease by detection of monogenic mutations. Nephrol Dial Transplant. 2019 Feb 26.

3. Connaughton DM, Kennedy C, Shril S, et al. Monogenic causes of chronic kidney disease in adults. Kidney Int. 2019 Feb 12. pii: S0085-2538(18)30839-1. doi: 10.1016/j.kint.2018.10.031. [Epub ahead of print].

4. Lata S, Marasa M, Li Y, et al. Whole-Exome Sequencing in Adults With Chronic Kidney Disease: A Pilot Study. Ann Intern Med. 2018 Jan16;168(2):100-109. doi: 10.7326/M17-1319. Epub 2017 Dec 5. Erratum in: Ann Intern Med. 2018 Feb 20;168(4):308.