Personalized medicine in chronic kidney disease by detection of monogenic mutations

Abstract

A large fraction of early-onset chronic kidney disease (CKD) is known to be monogenic in origin. To date, ∼450 monogenic (synonymous with single-gene disorders) genes, if mutated, are known to cause CKD, explaining ∼30% of cases in pediatric cohorts and ∼5-30% in adult cohorts. However, there are likely hundreds of additional monogenic nephropathy genes that may be revealed by whole-exome or -genome sequencing. Although the discovery of novel CKD-causing genes has accelerated, significant challenges in adult populations remain due to broad phenotypic heterogeneity together with variable expressivity, incomplete penetrance or age-related penetrance of these genes. Here we give an overview of the currently known monogenic causes for human CKD. We also describe how next-generation sequencing facilitates rapid molecular genetic diagnostics in individuals with suspected genetic kidney disease. In an era of precision medicine, understanding the utility of genetic testing in individuals with a suspected inherited nephropathy has important diagnostic and prognostic implications. Detection of monogenic causes of CKD permits molecular genetic diagnosis for patients and families and opens avenues for personalized treatment strategies for CKD. As an example, detection of a pathogenic mutation in the gene HNF1B not only allows for the formal diagnosis of CKD, but can also facilitate screening for additional extrarenal manifestations of disease, such as maturity-onset diabetes of youth, subclinical abnormal liver function tests, neonatal cholestasis and pancreatic hypoplasia. It also provides the driving force towards a better understanding of disease pathogenesis, potentially facilitating targeted new therapies for individuals with CKD.

Keywords: Mendelian renal disease; familial nephropathy; genetic kidney disease; monogenic disease; single-gene disorders.

FIGURE 1

Disease causation hypothesis. Disease causation is displayed ranging from almost exclusive genetic causes in the case of single-gene disorders (monogenic, recessive and dominant; top left corner, red), to diseases with a strong genetic component (metabolic, developmental, polygenic), to damage that is primarily inflicted by the environment with some component of genetic susceptibility (degenerative, infectious, toxic and trauma; bottom right corner, blue).

FIGURE 2

Age-related penetrance of monogenic alleles (mutations). The x-axis shows the age of disease manifestation in years. Characteristic features of age-related penetrance are shown for AR versus AD CKD genes. For example, the median age of onset for a homozygous truncating mutation (‘strong allele’) in an AR gene may occur at 10 years of age (dark blue curve). For another individual with a homozygous missense mutation in the same disease gene (‘mild allele’), the age-of-onset curve may be skewed to a later median age of onset (light blue curve). Similar to AR genes, AD genes show age-related penetrance. As a tendency, AD disease genes manifest later in life. In addition, AD disease genes feature effects such as incomplete penetrance (i.e. a mutation carrier never manifesting with disease) and variable expressivity (i.e. varied organ involvement between carriers of an identical mutation), which are usually not seen in AR acting genes. Exposure to environmental risk factors can hasten disease onset (red arrow), while treatment or prophylaxis can delay the onset of disease (green arrow).

FIGURE 3

Diagnostic yield from reported studies using molecular genetic analysis in each disease subgroup comparing childhood-onset (<18 years) versus adult-onset (≥18 years) CKD. Molecular genetic analysis was performed by WES or gene panel sequencing. For disease subgroups with more than two studies, the median diagnostic yield is reported. For disease subgroups with two or fewer studies, the average diagnostic yield is calculated as a marker of the median. Median, median diagnostic yield across all reported studies for each specific disease subcategory; NA, not available. Note: n indicates the number of families included in the study. If the number of families was not available, then the number of unrelated patients was included. ^†Indicates the diagnostic rate varied depending on the age of onset of disease. *Indicates results are quoted including and excluding the Snoek et al. study [23]. ^aMost adult cohorts analyzed to date have been enriched for familial cases of CKD, therefore diagnostic yield is likely higher compared with the general CKD population; ^b[9]; ^c[10]; ^d[11]; ^e[12]; ^f[13]; ^g[14], ^h[15]; ⁱ[16]; ^j[17]; ^k[18]; ^l[19]; ^m[20]; ⁿ[21]; ^o[22]; ^p[23]; ^q[24]; ^r[25]; ^s[26]; ^t[27]; ^u[28]; ^v[29] and ^w[30].