Closing the CKD diagnosis gap: What to know about genetic testing for chronic kidney disease

In the United States alone, more than one in seven adults has chronic kidney disease (CKD), yet as many as nine in 10 people with CKD are unaware they have it. Early-stage CKD is often asymptomatic, meaning most patients show no obvious signs until the disease has advanced significantly, when interventions like dialysis or transplantation may be the only remaining options.

The burden of education, prevention and management largely falls on primary care providers. Primary care doctors understand the high stakes of early detection, as catching CKD sooner can help prevent serious comorbidities, such as heart attacks and strokes. However, with typical 15-minute office visits, limited routine screening and a lack of efficient clinical support tools, identifying and addressing CKD early remains extremely difficult. This combination of silent progression and practical diagnostic challenges exacerbates poor outcomes for millions of patients.

Genomic sequencing, paired with proper interpretation tools, offers valuable support for primary care physicians by helping flag potential CKD before it becomes symptomatic, particularly in cases with unclear etiology, family history or atypical features. Advances in genetic testing (such as next-generation sequencing [NGS] panels or exome/genome approaches) can identify monogenic causes in a meaningful proportion of patients with CKD, help refine diagnoses and guide personalized management. However, broader integration of genomic sequencing into routine primary care still faces barriers, such as familiarity and workflow constraints.

Increased prevalence of genomic sequencing in kidney disease

Following similar patterns in cardiovascular disease and rare diseases protocols, NGS continues to gain prevalence among patients with kidney disease and the primary care physicians who treat them, paving a genetics-first care pathway. To meet this increased demand, options for genetic testing have grown over the years.

With the influx of testing tools, the primary barrier to adoption of NGS as a standard practice of care has shifted from sequencing to interpretation at scale. There is increasing demand for platforms that standardize variant interpretation and reduce the need for specialist bioinformatics teams to make genetic testing accessible in real-world workflows, especially for primary care physicians. Understandably, for many primary care settings, an in-house bioinformatics team remains rare and infeasible. In practice, doctors may order NGS sequencing but may not have the time, expertise or support to convert this genomic information into actionable treatment options.

Results buried under data influx

While kidney genetic testing is clinically valuable, interpretation remains inconsistent. For example, in the National Institutes of Health’s ClinVar database, which connects human genetic variants and phenotypes, many renal disease variants face challenges: underrepresentation, conflicting classifications or a lack of specific clinical context. This leads to reporting uncertainty, slower turnaround times, and a heavy reliance on manual expert curation for phenotype matching, an unfair task for primary care physicians who already often have full caseloads and face burnout.

In this regard, certain automated genomic reporting can help doctors. For example, some genomic tools can standardize renal reporting and reduce manual curation demands on physicians. Further, by providing actionable clinical insights even when public databases are limited, some platforms support faster and more accurate diagnosis, leading to improved disease management.

Assessing kidney germline data effectively

With a plethora of NGS tools, primary care physicians are able to select the one that best fits their needs after assessing for completeness of recommendations, turnaround time and cost.

For example, some tools offer integrated kidney germline workflows that convert raw DNA sequencing data into ready-to-use, structured renal gene panel clinical reports. When ClinVar evidence is incomplete or conflicting, genomic platforms provide primary care physicians assistance by consolidating updated available sources, including existing submissions, published associations and variant consequence data, to generate a clinician-friendly summary. Primary care physicians can benefit from such interpretable guidance rather than an unknown output from a standard genomic report.

In addition, primary care physicians have options in terms of what turnaround times they prefer when choosing a genomic platform. Solutions can range from multiple days to under 48 hours for modern whole-genome pipelines to run, a mere four hours for somatic or germline analysis, or just 30 minutes for pharmacogenomic analysis. For some primary care physicians, the shortest timeline might best support therapeutic adjustments in the time it takes for a patient to visit the doctor’s office.

Like any technology, costs vary. Doctors can look for versions that cost under $100 per whole-genome sequence, or explore options that might cost in the thousands. Depending on the features that best support their needs, doctors can choose the pipeline that works best for them.

The future is promising, as primary care physicians have multiple options for analyzing germline and somatic mutations in kidney diseases. Doctors and the patients they serve stand to benefit.

Ben Stansfield, Ph.D. candidate, is the director of computational biology at UGenome, a biotechnology company focusing on developing genomics, multiomics and bioinformatics software for personalized medicine with both research and clinical applications. He is a doctoral candidate in genetics at the University of Arizona.

Zachary S. Brooks, Ph.D., EMBA, is CEO at UGenome, a biotechnology company focusing on developing genomics, multiomics and bioinformatics for personalized medicine with both research and clinical applications.