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Review
. 2023 Jul 31;30(1):58.
doi: 10.1186/s12929-023-00959-7.

Phenotypic heterogeneity in human genetic diseases: ultrasensitivity-mediated threshold effects as a unifying molecular mechanism

Y Henry Sun  1   2 , Yueh-Lin Wu  3   4   5   6   7 , Ben-Yang Liao  8
Affiliations
Review

Phenotypic heterogeneity in human genetic diseases: ultrasensitivity-mediated threshold effects as a unifying molecular mechanism

Y Henry Sun et al. J Biomed Sci. .

Abstract

Phenotypic heterogeneity is very common in genetic systems and in human diseases and has important consequences for disease diagnosis and treatment. In addition to the many genetic and non-genetic (e.g., epigenetic, environmental) factors reported to account for part of the heterogeneity, we stress the importance of stochastic fluctuation and regulatory network topology in contributing to phenotypic heterogeneity. We argue that a threshold effect is a unifying principle to explain the phenomenon; that ultrasensitivity is the molecular mechanism for this threshold effect; and discuss the three conditions for phenotypic heterogeneity to occur. We suggest that threshold effects occur not only at the cellular level, but also at the organ level. We stress the importance of context-dependence and its relationship to pleiotropy and edgetic mutations. Based on this model, we provide practical strategies to study human genetic diseases. By understanding the network mechanism for ultrasensitivity and identifying the critical factor, we may manipulate the weak spot to gently nudge the system from an ultrasensitive state to a stable non-disease state. Our analysis provides a new insight into the prevention and treatment of genetic diseases.

Keywords: Edgetic mutation; Expressivity; Network; Penetrance; Phenotypic heterogeneity; Pleiotropy; Stochasticity; Threshold; Ultrasensitive response motif (URM); Ultrasensitivity.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Genotype–phenotype correlations.Penetrance is the percentage of individuals carrying a particular genotype (e.g., a mutation) that exhibits certain detectable phenotypic traits (clinical manifestation). A complete penetrance means that 100% genotype–phenotype correlation. Expressivity is the degree of phenotypic severity in an individual that exhibits detectable mutant phenotype. Pleiotropy means a gene, when mutated, is linked to multiple phenotypic defect, often in multiple tissues or organs
Fig. 2
Fig. 2
Threshold determines penetrance. We use a hypothetical case to illustrate the conceptual relationship between threshold and penetrance. Consider a hypomorphic allele m of a gene X. The X-axis is the level or activity of X. The Y-axis is the number of individuals with a particular [X]. Due to many factors, the [X] displays a distribution curve. A hypothetical threshold for [X] is drawn. If [X] falls below the threshold, the individual will exhibit the clinical phenotype. If [X] is above the threshold, the individuals will be phenotypically normal. In this hypothetical example, the m variant is recessive, because all m/ + individuals will be above threshold. The m variant is incompletely penetrant, because only a fraction of m/m individuals will be below threshold and exhibit phenotypes. If the threshold shifts to the right, the penetrance will become higher, i.e., more individuals are below threshold. If the threshold shifts to the left, then less individuals are below threshold, hence a lower penetrance
Fig. 3
Fig. 3
A sigmoidal curve illustrates the threshold effect. The phenotypic severity (Y-axis) is plotted with the level or activity of factor X (denoted [X]) in the X-axis. In a sigmoidal curve of such “dose–response” curve, when [X] is at its normal dosage (high), the system is at its normal (wildtype) state. When [X] is reduced due to a low level, e.g., due to a null mutation in X, the system exhibits the mutant phenotype with complete penetrance. At these two states, small perturbations in [X] do not cause any changes in the phenotypic output. However, at near the inflection point of the curve, small changes in [X] will cause large changes in the phenotypic outcome. Therefore, the system is ultrasensitive to changes in [X]
Fig. 4
Fig. 4
Stochastic variation in input causes heterogeneous output. (Left) A fixed [X] would generate a fixed output in phenotypic severity. (Right) Stochastic fluctuation in [X] generates different [X] in different individuals or cells, thereby generating a range of phenotypic output in different individuals
Fig. 5
Fig. 5
Threshold can shift. The hemoglobin-oxygen binding is a classic example of positive cooperativity and exhibits a sigmoidal curve (red curve). The curve can be shifted rightward (blue curve), representing reduced affinity for oxygen, by elevated temperature, CO2, and 2,3-diphosphoglycerate (DPG), and reduced pH, resulting in increased threshold. Sickle cell hemoglobin (HbSS) and sulfhemoglobin (Sulf-Hb) have reduced affinity to oxygen, so exhibits right-shifted curve. The curve can be shifted leftward (green curve), representing increased affinity for oxygen, by reduced temperature, CO2, and DPG, and elevated pH. Methemoglobinemia (metHb), fetal hemoglobin and CO-bound Hb (CO-Hb) have higher affinity to oxygen, so exhibit leftward curve. These examples demonstrate that the threshold can be shifted by environmental or physiological factors, as well as by changes in the protein structure. Adapted from [128]
Fig. 6
Fig. 6
The three conditions for threshold effect. First, an ultrasensitivity module need to be embedded in the gene regulatory network. The system is normally in a stable (homeostatic) state, i.e., the wildtype state, and is robust to small fluctuations. Second, the occurrence of a primary (driver) mutation shifts the system to a state that is ultrasensitive to changes in the concentration/activity of factor X ([X]). If [X] does not fluctuate, then the system would have a fixed [X] and a fixed outcome. Third, fluctuations in [X] would cause the system to produce heterogeneous phenotypic outputs
Fig. 7
Fig. 7
ELT-2 regulation as an example of the three requirements for phenotypic heterogeneity due to ultrasensitivity mediated threshold response. In Skn-1 mutants, the ELT-2 positive feedback is weakened due to absence of END-3 and reduced END-1. The ELT-2 level may fall below its functional threshold in some individuals, causing a failure in in C. elegans intestinal development. Modified from [56]
Fig. 8
Fig. 8
Protein interactions affected by different types of mutations. The dots represent proteins and lines (edges) connecting dots represent their interactions. Different types of mutation may affect the node or the edges. Modified from [89]
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