Trends in Immunology
Volume 34, Issue 3, March 2013, Pages 99-106
Journal home page for Trends in Immunology

Opinion
Understanding the immunological impact of the human mutation explosion

https://doi.org/10.1016/j.it.2012.12.001Get rights and content

The recent development of human exome sequencing technology has revealed that our immune system is riddled with more genetic defects than anyone imagined. As a legacy of the recent human population explosion, we each inherit hundreds of rare mutations that alter the sequence of proteins. This mutation load is ten times higher than that induced by experimental treatment of mice by ethylnitrosourea; a high fraction of which has substantial effects on immune function. This mutation burden is likely to be a major factor in the incidence of many human immune disorders, but understanding this at the level of individual patients will require new bioinformatics and experimental strategies to assess the impact of individual and combined mutations on immune response pathways.

Section snippets

The human mutation explosion

Locus-specific mutations that result in partial or complete loss of protein function have in the past been estimated to arise de novo in human gametes at an average rate of the order of ∼1 per 105 births per gene. Mutations that lead to X-linked diseases such as X-linked severe combined immunodeficiency (X-SCID) or X-linked agammaglobulinemia (XLA) have been inferred to arise in the population at a rate of 1.0 × 10−5–2.4 × 10−5 (see [1] and references therein) and similar rates have been observed

What is the immunological impact of unpurified heterozygous mutations?

The contribution that rare (MAF <1%), heterozygous, nonsynonymous variants make to human disease is a subject of vigorous investigation, now that the sequencing tools have become available to reveal them. Comparatively, the contribution of common variation (MAF >5%) in disease is vastly better understood and genome-wide association studies (GWASs) conducted over the past decade have been highly successful in detecting associations between human autoimmune and allergic diseases and common single

Bioinformatic prediction of the immunological impact of nonsynonymous mutations is a major challenge

Now that exome sequencing is revealing the load of rare nonsynonymous substitutions in important immune genes, interpreting these data becomes the pressing problem for our age. Although each mutation carrier will typically have a unique (e.g., family-specific) variant, statistical methods are emerging to collapse the carriers of these different substitutions and treat them as a group 45, 46, 47. However, to collapse people into carrier and noncarrier groups in this way, it will be important to

Experimental datasets of the immunological impact of nonsynonymous mutations

Addressing the gaps in knowledge outlined above will require systematic experimental analysis of the immunological consequences of de novo (unselected) nonsynonymous mutations and targeted mutations, in their heterozygous and homozygous states, especially when multiple heterozygous mutations are combined. Mice provide a critical experimental route, as discussed later, but it is well recognized that only 95% of genes are well conserved between humans and mice 58, 59. The rapidly evolving genes

Concluding remarks

A significant challenge for the very near future will be how to interpret human genetic variation in a clinical context, given that even healthy individuals harbor a considerable load of loss-of-function or gain-of-function heterozygous genetic variants. GWASs have been highly successful at indentifying loci that associate with human disease, but currently do not address a large portion of genetic variability that exists with a MAF <5%. It is yet wholly unanswered whether clinically important

Acknowledgments

The authors thank three anonymous reviewers and Teresa Neeman of the Statistical Consulting Unit at the Australian National University for statistical advice and help with Figure 1. The authors are supported by grants from the NHMRC, NIAID-NIH, Wellcome Trust, and by the Australian Government National Collaborative Research Infrastructure Scheme through the Australian Phenomics Network.

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