When "loss-of-function" means proteostasis burden: Thinking again about coding DNA variants

Abstract

Each human genome has approximately 5 million DNA variants. Even for complete loss-of-function variants causing inherited, monogenic diseases, current understanding based on gene-specific molecular function does not adequately predict variability observed between people with identical mutations or fluctuating disease trajectories. We present a parallel paradigm for loss-of-function variants based on broader consequences to the cell when aberrant polypeptide chains of amino acids are translated from mutant RNA to generate mutated proteins. Missense variants that modify primary amino acid sequence, and nonsense/frameshift variants that generate premature termination codons (PTCs), are placed in context alongside emergent themes of chaperone binding, protein quality control capacity, and cellular adaptation to stress. Relatively stable proteostasis burdens are contrasted with rapid changes after induction of gene expression, or stress responses that suppress nonsense mediated decay (NMD) leading to higher PTC transcript levels where mutant proteins can augment cellular stress. For known disease-causal mutations, an adjunctive variant categorization system enhances clinical predictive power and precision therapeutic opportunities. Additionally, with typically more than 100 nonsense and frameshift variants, and ∼10,000 missense variants per human DNA, the paradigm focuses attention on all protein-coding DNA variants, and their potential contributions to multimorbid states beyond classically designated inherited diseases. Experimental testing in clinically relevant systems is encouraged to augment current atlases of protein expression at single-cell resolution, and high-throughput experimental data and deep-learning models that predict which amino acid substitutions generate enhanced degradative burdens. Incorporating additional dimensions such as pan-proteome competition for chaperones, and age-related loss of proteostasis capacity, should further accelerate health impacts.