Response to ”Understanding Familial Variability in ADPKD: a Comprehensive Approach Integrating Genetics, Hormones, and Lifestyle for Tailored Management”

To the Editor:

We thank Catania et al.¹ for their insightful response to our article.² We wholeheartedly agree with the points raised in the letter and would like to respond with the following. The study of the intrafamilial variability of Mendelian disorders, including autosomal dominant polycystic kidney disease (ADPKD), represents a clinical conundrum. We consider the factors influencing variability in disease progression as conglomerate lifetime traits (Figure 1). Therefore, to address the significant data-to-evidence gap, the emerging framework that influences the clinical course variability of patients with ADPKD should integrate genetic, phenotypic, and environmental factors, as Catania et al.¹ highlighted.

Figure 1.

Schematic illustration of genetic and nongenetic factors influencing the variability progression to kidney failure through lifetime. Trom bottom to the top: Kidney failure risk cumulates throughout the lifetime and is influenced by the specific types of ADPKD genetic variants (represented by KF slopes). The risk of KF peaks later in adulthood in individuals with typical ADPKD (blue slope): PKD1 truncating variants progress to KF earlier than those with PKD1 nontruncating and PKD2 variants. Rare cases with (very) early-onset ADPKD ([V] EO-ADPKD) result from complex genetic alterations, such as biallelic PKD1/PKD2 and monoallelic NEK8 variants, leading to KF at a young age (red slope). In contrast, late-onset ADPKD is associated with ADPKD-like variants and characterized by a slowly progressing phenotype in older patients (grey slope). However, the variability of disease progression within families can be explained by factors beyond the causal genetic variant shared by family members (as illustrated by the traffic-light gradient). Genomic determinants impact early phenotypic progression, potentially inherited from the other parent, involving modifier genetic factors and/or molecular risks that may accelerate or ameliorate disease progression. On the other hand, exposomic determinants encompass intrinsic factors, such as fetal and pregnancy-related factors like birth weight and nephron dosage, as well as extrinsic factors such as cardiometabolic burden, which influence phenotype expression. These determinants are likely to accumulate throughout life, thereby affecting the severity of phenotypes and the morbidity and mortality associated with diseases, despite the onset of their effects varying based on exposure. ADPKD, autosomal dominant polycystic kidney disease; KF, kidney failure.

Because familial members share numerous "fixed" elements, including the primary genetic variant and family environment, employing "omics-based" measurements can provide more accurate predictive models of familial variability.^3,S1^,S2 At first, the cumulative effect of rare disease-causing variants and rare risk variants have been demonstrated to impact the progression of chronic kidney disease; however, the role of genetic modifier effects in ADPKD remains to be systematically investigatedS3–S9. Further, the background impact of polygenic common variants has been reported to influence the risk of developing chronic kidney disease in ADPKD.S10 Epigenetic modulations are crucial in the progression of aging-related kidney diseases, such as ADPKD, by promoting kidney cyst growth and cardiovascular complications, such as hypertension.^4,S11–S13 This can result in identifying druggable targets, because cyst growth is an age-dependent feature in typical ADPKD.⁴ In addition, exposome-based approaches, which incorporate nongenetic factors that influence the progression of kidney disease, offer more precise methods that complement genetic factors to reveal environmental drivers that influence genetic susceptibility and treatment response throughout the lifespan.⁵ The analysis can be adjusted to account for the duration of exposure and desired outcomes, including factors such as intrauterine fetal health,S14 body mass index,S15,S16 hypertension,S17 diabetes,S18 smoking status,S19 sleep-related disorders,S20 and dietary habits.S21

In conclusion, the increasing interest in personalized medicine requires comprehensive genetic and nongenetic profiling of affected members with familial ADPKD, which serves as an accurate tool for studying the "effects" of disease and its outcomes.

Disclosure

EAEE reports funds from the Royal College of Surgeons in Ireland StAR PhD. GLC reports receipt of research funding from BioMarin. PJC reports HRCI-HRB research grants (Grant code: HRCI-HRB-2020-032) and funding from BioMarin Pharmaceutical.

Supplementary Material

Supplementary File (PDF)

Supplementary References.