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Many Disease Genes are Sheep in Wolves' Clothing

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Everyone has heard about genetic mutations causing serious disease. Finding one in your genome was like getting a death sentence. Recently, however, geneticists have been surprised that many people with these mutations don't ever get sick.

You're probably among them. "Lurking in the genes of the average person are about 54 mutations that look as if they should sicken or even kill their bearer," says Erica Check Hayden in Nature. "But they don't." [Emphasis added.] And therein lies a scientific revolution. The growing realization that humans survive these mutations is leading to "a radical revision of human genetics," she says.

Few would have thought to ask such a question in years past, but medical genetics has been going through a bit of soul-searching. The fast pace of genomic research since the start of the twenty-first century has packed the literature with thousands of gene mutations associated with disease and disability. Many such associations are solid, but scores of mutations once suggested to be dangerous or even lethal are turning out to be innocuous. These sheep in wolves' clothing are being unmasked thanks to one of the largest genetics studies ever conducted: the Exome Aggregation Consortium, or ExAC.

We mentioned ExAC before, noting that a billion genes have failed to turn up any beneficial mutations. This time we look at the flip side; are "harmful" mutations really as deadly as we thought?

Part of the misdiagnosis problem came from a common statistical error, illustrated by an old joke: "Monday, Joe got drunk on gin and soda water. Tuesday, Joe got drunk on bourbon and soda water. Wednesday, Joe got drunk on vodka and soda water. Conclusion: soda water causes drunkenness." The mistake could have been prevented by comparing Joe to people who drank soda water alone or added it to non-alcoholic drinks.

Similarly, doctors and scientists can find a genetic variant in several individuals with fatal genetic diseases and rush to the conclusion that the common gene was the cause of the disease, before checking to see how widespread the variant is in the general population. Philosophers use illustrations like this to teach rules of logical inference.

The error can be forgiven in this case. Before now, scientists lacked enough data to compare genomes. ExAC is changing that. It's a welcome development. The editors of Nature want to accelerate the correction:

These conclusions have consequences for real people, and so researchers must go about this work differently. When they suspect that a variant is linked to disease, they should check to see how common it is in databases such as ExAC. Even better, they should hunt for evidence that the mutation has a functional role in disease before declaring that it is pathogenic. Let the reckoning begin.

ExAC is helping in more ways than correcting previous inferential mistakes. Hayden says it can be a tool for discovering function in genes and proteins:

ExAC is a simple idea. It combines sequences for the protein-coding region of the genome -- the exome -- from more than 60,000 people into one database, allowing scientists to compare them and understand how variable they are. But the resource is having tremendous impacts in biomedical research. As well as helping scientists to toss out spurious disease-gene links, it is generating new discoveries. By looking more closely at the frequency of mutations in different populations, researchers can gain insight into what many genes do and how their protein products function.

This is where the story gets interesting for intelligent design. Is it possible that variants thought of as mistakes could be functional? Or is there more room for neutral variation than expected? How does the body protect against variants? Is there such a thing as "the" human genome? Could natural variation be a mechanism for robustness against deleterious mutations?

ExAC has turned human genetics upside down, says geneticist David Goldstein of Columbia University in New York City. Instead of starting with a disease or trait and working backwards to find its genetic underpinnings, researchers can start with mutations that look like they should have an interesting effect and investigate what might be happening in the people who harbour them. "This really is a new way of working," he says.

Remember that the ID approach is to look for reasons for things. Mistakes surely occur when DNA is exposed to carcinogens or cosmic rays, but the rule of thumb for ID is, "If something works, it's not happening by accident." The fact that billions of people live healthy lives in spite of variants previously assumed to be fatal supports a new heuristic model: maybe we should expect a baseline of variability built into the normal, healthy human genome.

We have to be careful; we don't want to confuse tolerance to neutral mutations for function. Hayden's article, with a chart, shows that some mutations remain clearly associated with disease. But many others thought to be deadly have turned out to be common in the population, and thus must be benign. Some may increase risk of disease without causing it, or be expressed later in life. There are many pitfalls in associating variants with deleterious effects.

Later this month another version of ExAC will be released, increasing the data to 135,000 exomes and 15,000 whole-genome sequences. ExAC is a field to watch for design implications. Given that ExAC has already turned human genetics upside down, maybe design theorists can help find which way is up.

Querying the Rest of the Story

ExAC catalogs the exome, the coding parts of the genome. What about the non-coding parts? Efforts after ENCODE continue to query the non-coding portions, looking for reasons why they are there. One such effort was published recently in Science by Sanjana et al., "High-resolution interrogation of functional elements in the noncoding genome." Here's their design-friendly goal: they want to find causes for effects rather than dismiss the unknown as junk.

More than 98% of the human genome does not code for proteins; however, unlike for the coding genome, there exists no overarching framework to translate the noncoding genomic sequence into functional elements. Evidence from genome-wide association studies suggests that many noncoding regions are critical for human health. The implications of these associations, however, have been difficult to assess, in part because we lack the tools to determine which variants alter functional elements. Molecular hallmarks, such as epigenetic state, chromatin accessibility, transcription factor binding, and evolutionary conservation, correlate with putative functional elements in the noncoding genome and can predict regulatory function. However, these predictions largely bypass regions lacking hallmarks, and it is difficult to ascertain which hallmarks play a correlative or truly causal role in function or phenotype. Efforts to determine causality have used preselected DNA fragments, with expression serving as a proxy for function, but these methods lack the local chromatin context and broader regulatory interactions. Thus, there is a need for systematic approaches to sift through noncoding variants and determine whether and how they affect phenotypes in a native biological context.

It's exciting to be at the verge of a paradigm shift. This team (though still accepting the Darwinian view that the genome is a product of evolution) is beginning with the right attitude. They want to nail down the evidence for function. It appears Darwinian theory played no role in their research.

So here are two avenues of research for design theorists. We know that evolutionists have already made the mistake of dismissing parts of the genome they didn't understand as "junk." While we don't want to make the opposite mistake of assuming everything is functional, we can help apply a paradigmatic corrective that may very well lead to fundamental new discoveries. When studying an exon or non-coding region, perhaps we should let design be the default expectation until proven otherwise. After all, you could miss a function if you aren't looking for it. So as Nature's editors said, "Let the reckoning begin."

Photo: © Jeff Baumgart -- stock.adobe.com.