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    Connaughton DM, et al. Monogenic causes of chronic kidney disease in adults. Kidney Int 2019; 95:914928. doi: 10.1016/j.kint.2018.10.031

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    Warejko JK, et al. Whole exome sequencing of patients with steroid-resistant nephrotic syndrome. Clin J Am Soc Nephrol 2018; 13:5362. doi: 10.2215/CJN.04120417

    • Crossref
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    Vivante A, et al. Exome sequencing discerns syndromes in patients from consanguineous families with congenital anomalies of the kidneys and uri-nary tract. J Am Soc Nephrol 2017; 28:6975. doi: 10.1681/ASN.2015080962

    • Crossref
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  • 7.

    Nestor JG. Assessing physician needs for the implementation of personalized care. Kidney Int Rep 2021; 6:243245. doi: 10.1016/j.ekir.2020.12.008

    • Crossref
    • Search Google Scholar
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    Nestor JG, et al. An electronic health record (EHR) log analysis shows limited clinician engagement with unsolicited genetic test results. JAMA Open 2021; 4:ooab014. doi: 10.1093/jamiaopen/ooab014

    • Crossref
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Personalized Nephrology: Genomic Implementation Tools Help Nephrologists Deliver on the Promises of Precision Nephrology

  • 1 Jordan G. Nestor, MD, specializes in precision medicine and the diagnosis and management of hereditary nephropathies. She is an Assistant Professor of Medicine and a Junior Investigator in the Division of Nephrology at Columbia University, New York, NY. Under the mentorship of Ali G. Gharavi, MD, and Chunhua Weng, PhD, her research focuses on facilitating broader genomic implementation in nephrology through the development of novel bioinformatic solutions. For questions or to share your interest in participating in genomic implementation initiatives at Columbia University, please email her at jgn2108@cumc.columbia.edu.
Full access

Creating personalized care plans through genomic implementation

Chronic kidney disease and kidney failure affect over 20 million Americans and confer substantial morbidity and mortality. Recent studies show that genomic sequencing approaches, such as exome sequencing, can identify a specific monogenic disease in 10% to 35% of kidney disease patients (16). Hereditary nephropathies are genotypically and phenotypically heterogenous and are often difficult to diagnose because of overlapping, nonspecific features (e.g., elevated serum creatinine, proteinuria, etc.). The establishment of a molecular diagnosis can support personalized nephrology care by informing targeted workup, disease prognosis, choice of therapy, and/or family counseling. However, genomic sequencing technologies are still emerging diagnostic tools, and despite their increased use in medicine subspecialties like nephrology, many physicians may lack the requisite knowledge and experience to apply genomic findings into clinical practice. This can be exhibited particularly if one is called upon to interpret unsolicited genomic findings, such as when patients undergo sequencing through their participation in genomic research, expanded carrier screening as part of family planning, or direct-to-consumer testing to learn about their ancestry. Overall, nephrologists' lack of familiarity in utilizing genomic data poses a signifi-cant barrier to their participation in precision medicine efforts and to broader implementation of genomics in routine nephrology care. However, these barriers can be overcome with customized tools tailored to nephrologists' needs (Figure 1).

Figure 1.
Figure 1.

User experience: needs and values

Citation: Kidney News 13, 9

Understanding the intended users' needs and values is essential for the development of EHR-integrated decision support tools that effectively enhance clinicians' use of genomic data.Figure adapted with permission from Peter Morville (2004).

The workflow and technology imperatives

Although consensus guidelines are available for the evaluation and/or management of some hereditary nephropathies (e.g., autosomal dominant polycystic kidney disease, Alport syndrome, etc.), these resources may be difficult to access in real time and at the point of care. Furthermore, they often require nephrologists to already suspect a hereditary etiology for an individual's kidney disease. Thus, there is great need for technologic solutions that support nephrologists' use of genomic data at the point of care, despite their level of expertise in clinical genomics. However, the development of novel, nephrology-tailored tools that clinicians will want to use, such as interactive electronic health record (EHR)-integrated, genome-informed clinical decision support tools, requires further study into the informational and workflow support needs of the intended user (7, 8). Insights into nephrologists' unmet needs will inform the design of tools that are versatile enough to be used across diverse practice settings, address specific knowledge gaps, and potentially increase users' willingness to deliver more personalized nephrology care. Development of these novel aids relies on nephrologists' participation in genomic implementation and bioinformatics research. For example, Columbia University needs US nephrologists, particularly those who practice outside of large academic institutions, to share their user experiences with existing decision aids and technology-based tools and to help us pilot preliminary decision support tools intended for the EHR. Technologic tools tailored to address nephrologists' needs will allow us to provide more personalized care, work toward improving long-term outcomes in our patients, and deliver on the promises of precision nephrology.

Acknowledgment:

The project was supported by grants from the US National Institutes of Health (KL-2TR001874) and the National Kidney Foundation.

References

  • 1.

    Groopman EE, et al. Diagnostic utility of exome sequencing for kidney disease. N Engl J Med 2019; 380:142151. doi: 10.1056/NEJMoa1806891

  • 2.

    Mann N, et al. Whole-exome sequencing enables a precision medicine approach for kidney transplant recipients. J Am Soc Nephrol 2019; 30:201215. doi: 10.1681/ASN.2018060575

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 3.

    Connaughton DM, et al. Monogenic causes of chronic kidney disease in adults. Kidney Int 2019; 95:914928. doi: 10.1016/j.kint.2018.10.031

  • 4.

    van der Ven AT, et al. Whole-exome sequencing identifies causative mutations in families with congenital anomalies of the kidney and urinary tract. J Am Soc Nephrol 2018; 29:23482361. doi: 10.1681/ASN.2017121265

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 5.

    Warejko JK, et al. Whole exome sequencing of patients with steroid-resistant nephrotic syndrome. Clin J Am Soc Nephrol 2018; 13:5362. doi: 10.2215/CJN.04120417

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 6.

    Vivante A, et al. Exome sequencing discerns syndromes in patients from consanguineous families with congenital anomalies of the kidneys and uri-nary tract. J Am Soc Nephrol 2017; 28:6975. doi: 10.1681/ASN.2015080962

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 7.

    Nestor JG. Assessing physician needs for the implementation of personalized care. Kidney Int Rep 2021; 6:243245. doi: 10.1016/j.ekir.2020.12.008

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 8.

    Nestor JG, et al. An electronic health record (EHR) log analysis shows limited clinician engagement with unsolicited genetic test results. JAMA Open 2021; 4:ooab014. doi: 10.1093/jamiaopen/ooab014

    • Crossref
    • Search Google Scholar
    • Export Citation
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