Study could explain why some people are severely affected by Bardet-Biedl syndrome

Geneticists usually split disorders into “simple”, where disease is caused by a single gene mutation, or complex, where mutations in several genes contribute modest quantities. Now, according to a new study, the truth is somewhere in between.

For several years, researchers focused on patient genomes have captured glimpses of genetic “burden” or further genetic variation that contributes to the impact of disease-causing mutations and renders them more (or less) powerful.

In theory, a phenomenon like this can help explain why certain people are adversely affected by disease, while others are not. But the concept of genetic burden has been a debatable issue to a large extent, because it has been extremely hard to identify and interpret its properties.

Investigators from the Stanley Manne Children’s Research Institute at Ann & Robert H. Lurie Children’s Hospital of Chicago have now utilized a conglomerate of functional and genetic methods to show the prevalence of burden in diseases that are believed to be induced by a single gene.

The study, published in the Nature Genetics journal, assessed several hundred patients suffering from Bardet-Biedl syndrome (BBS)—a rare disorder that affects vision, cognitive function, body weight regulation, and renal function.

Most significantly, all these patients had previously been diagnosed genetically with BBS, that is, these individuals carried mutations in one of the 25 genes implicated in this disorder. In other words, the genetic diagnosis of these patients was completed, and they were believed to be “solved.”

But when the authors examined these patients for all known BBS genes, they discovered that three times more mutations were carried by these individuals in a pattern that is more reminiscent of the genetic layout of complex traits, like type II diabetes or Alzheimer’s disease.

In addition, the distribution pattern of such mutations was not arbitrary, but clustered around certain subsets of genes encoding two different complexes of protein. Such observations indicate that the impact of these extra genetic mutations was fueled by their number and also by their position in a “disease network.”

The research also holds implications about the kinds of genetics data that can be returned to patients in clinical settings.

It is imperative that we broaden our search for answers beyond the single causal gene. We have always known that disease causality was not binary, but a continuum, but we lacked the proof and the tools to detect it. To me, this is not too different from the development of tools that increased the magnification of telescopes.

Nico Katsanis, PhD, Director of the Advanced Center for Translational and Genetic Medicine, Manne Research Institute, Ann & Robert H. Lurie Children’s Hospital of Chicago

Dr Katsanis is also the study’s senior author and Professor of Pediatrics and Cell and Molecular Biology at Northwestern University Feinberg School of Medicine.

He added, “Now we can see deeper, better, and start making predictions about diseases: why they happen, why the progress the way they do. The work also gives us multiple potential entry points for therapies: some disease-causing genes are difficult to target—but their neighbors might be amenable.”

As a next step, the researchers are now applying these ideas to a range of other associated disorders, paying more attention to network mutations that not only exacerbate the severity of disease but also attenuate it.

It has taken us 20 years to get here. Now, I feel we have a new depth of resolution to understand the problem better.”

Nico Katsanis, PhD, Director of the Advanced Center for Translational and Genetic Medicine, Manne Research Institute, Ann & Robert H. Lurie Children’s Hospital of Chicago

Source:

Ann & Robert H. Lurie Children’s Hospital of Chicago

Journal reference:

Kousi, M., et al. (2020) Evidence for secondary-variant genetic burden and non-random distribution across biological modules in a recessive ciliopathy. Nature Genetics. doi.org/10.1038/s41588-020-0707-1.

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