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			by Erika Check Hayden12 October 2016
 from 
			Nature Website
 
			
			Spanish version 
			
 
			  
			
  
 
			  
			Why many 'deadly' gene 
			mutations
 
			are turning out to be harmless.
 
			
 Lurking in the genes of the average person are about 54 mutations 
			that look as if they should sicken or even kill their bearer. But 
			they don't. Sonia Vallabh hoped that D178N (PrP 
			gene) was one such 
			mutation.
 
 In 2010, Vallabh had watched her mother die from a mysterious 
			illness called 'fatal familial insomnia,' in which misfolded
			
			prion 
			proteins cluster together and destroy the brain.
 
			  
			The following year, Sonia was tested and 
			found that she had a copy of the 
			
			prion-protein gene, PRNP, with the 
			same genetic glitch - D178N - that had probably caused her mother's 
			illness. It was a veritable death sentence: the average age of onset 
			is 50, and the disease progresses quickly.  
			  
			But it was not a sentence that Vallabh, 
			then 26, was going to accept without a fight.  
			  
			So she and her husband, Eric Minikel, 
			quit their respective careers in law and transportation consulting 
			to become graduate students in biology.  
			  
			They aimed to learn everything they 
			could about fatal familial insomnia and what, if anything, might be 
			done to stop it. One of the most important tasks was to determine 
			whether or not the D178N mutation definitively caused the disease.
 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. 
			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.
 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 harbor them.  
				
				"This really is a new way of 
				working," he says. 
			ExAC is also providing
			
			better information for families facing genetic diagnoses. 
			   
			D178N, for example, was strongly 
			suspected of causing prion disease because it had been seen in 
			several people with the condition and seldom elsewhere. But before 
			ExAC, no one really had the power to see just how rare it was.
			   
			If it shows up in people more frequently 
			than prion disease does, that would mean Vallabh's risk of getting 
			the disease is much lower than predicted. 
				
				"We needed to find out if this 
				mutation had ever been seen in a healthy population," Minikel 
				says.       
			Data gathering  
			ExAC was born of frustration. 
			 
			  
			In 2012, 
			geneticist Daniel MacArthur was starting his first 
			laboratory, at Massachusetts General Hospital (MGH) in Boston.
			   
			He wanted to find genetic mutations that 
			caused rare muscle diseases, and needed two things:  
				
			 
			If a mutation was more common in people 
			with a disorder than in healthy controls, it stood to reason that 
			the mutation was a likely cause.   
			The problem was that MacArthur couldn't 
			find enough sequences from unaffected people. He needed lots of exomes, and although researchers had been sequencing them by the 
			thousands, existing data sets weren't large enough.    
			No one had pulled enough together into 
			one combined, standardized resource. 
			  
			  
				
					
						| 
			
					
					 
					Daniel 
					MacArthur convinced researchers  
					to share 
					genetic data on tens of thousands of people. 
					Sam Goresh 
					for Nature |      
			So MacArthur started asking his 
			colleagues to share their data with him.    
			He was well suited to the task: 
			 
				
				an early adopter of social media, 
				his lively blog posts and acerbic Twitter feed had made him 
				unusually popular and authoritative for a young scientist.
				 
			He also had a position with the 
			
			Broad 
			Institute in Cambridge, Massachusetts, a genome-sequencing 
			powerhouse.    
			MacArthur convinced researchers to share 
			data from tens of thousands of exomes with him; most were in some 
			way connected to the Broad. 
			  
			All that remained was to analyze the 
			data, but that was no trivial task. Although the genes had been 
			sequenced, the raw data had been analyzed using different types of 
			software - including some that were out of date.   
			If one individual in the collection 
			showed a rare mutation, it could be real - or it could be an 
			artifact of how different programs 'called' the bases within, 
			judging whether they were, 
				
			 
			MacArthur needed something that would 
			standardize this gigantic data set. The Broad had developed 
			genome-calling software, but it wasn't up to the task of churning 
			through the tremendous amount of data included in ExAC.    
			So MacArthur's team worked closely with 
			the Broad programmers to test the software and scale up its 
			abilities.  
				
				"That was a pretty horrific 18 
				months," MacArthur recalls. "We ran into every obstacle 
				imaginable and had nothing to show for it."       
			Personal stake  
			While this was going on, in April 2013, 
			Vallabh was learning how to work with stem cells at MGH while
			
			Minikel studied bioinformatics.    
			Minikel met MacArthur for lunch and 
			explained his and Vallabh's curiosity about whether D178N existed in 
			healthy people. He admits to being a bit star-struck by MacArthur's 
			reputation.  
				
				"I thought if I could get him to 
				think about my problem for half an hour, that would probably be 
				the most important thing that happened in my whole month," 
				Minikel says.  
			The pair went upstairs to MacArthur's 
			lab, where bioinformatician Monkol Lek ran a search on the ExAC data 
			that had been analyzed so far - about 20,000 exomes.    
			They didn't see Vallabh's mutation. That 
			wasn't good news, but, optimistic about exploring the data further, 
			Minikel joined MacArthur's lab.   
			By June 2014, MacArthur's team and its 
			collaborators had a data set that they were confident in - exomes 
			from 60,706 individuals representing various ethnic groups, who met 
			certain thresholds for health and consent.    
			They released ExAC that October at the 
			annual meeting of the American Society of Human Genetics (ASHG), in 
			San Diego, California. Immediately, researchers and physicians 
			recognized that the data could help to recast their understanding of 
			genetic risks.   
			Many disease-association studies, 
			particularly in recent years, have identified mutations as 
			pathogenic simply because scientists performing analyses on a group 
			of people with a disorder found mutations that looked like the 
			culprit, but didn't see them in healthy people.    
			But it's possible that
			
			they weren't looking hard enough, or in the right populations. 
			Baseline 'healthy' genetic data has tended to come mainly from 
			people of European descent, which can skew results.   
			In August this year, MacArthur's group 
			published 1 its analysis of ExAC data in Nature, 
			revealing that many mutations thought to be harmful are probably 
			not.    
			In one analysis, the group identified 
			192 variants that had previously been thought to be pathogenic, but 
			turned out to be relatively common. The scientists reviewed papers 
			about these variants, looking for plausible evidence that they 
			actually caused disease, but could find solid evidence for only nine 
			of them.    
			Most are actually benign, according to 
			standards set by the American College of Medical Genetics and 
			Genomics (ACGM), and many have now been reclassified as such.   
			Similar work promises to have direct 
			impacts on medical practice.    
			In a companion paper, 2 
			geneticist Hugh Watkins of the University of Oxford, UK, 
			looked at genes associated with certain types of cardiomyopathy that 
			cause gradual weakening of the heart muscle.    
			Undetected, they can lead to sudden 
			death, and it has become fairly common to check relatives of people 
			with the conditions for genetic mutations associated with them.
			   
			Those found to have a genetic risk are 
			sometimes counseled to get an implanted defibrillator, which 
			delivers electrical shocks to the heart if it seems to be beating 
			abnormally.    
			Watkins checked the ExAC database for 
			information on genes that have been associated with these heart 
			conditions, and found that many mutations are much too common among 
			healthy people to be pathogenic.    
			About 60 genes had been implicated as 
			harboring pathogenic mutations that cause one form of the disease; 
			Watkins' analysis revealed that 40 of these probably bear no link.   
			This was troubling.  
				
				"If you have a genetic risk that you 
				believe is predicting disease but isn't, you can end up doing 
				drastic things that can harm someone," says Watkins. 
			Even some of the mutations that seem to 
			be reliably linked to disease aren't a sure bet - such as those in
			PRNP.    
			There are definitely mutations in the 
			gene that cause the disease, but some variants might not be 
			pathogenic or might elevate the risk only slightly (see
			'The Deadly Mutations that Weren't').    
			To find out the status of D178N, Vallabh 
			and Minikel gathered genetic data from more than 16,000 people who 
			had been diagnosed with prion diseases, and compared them with data 
			from almost 600,000 others, including the ExAC participants. 
			3 
			  
			  
			
			 
			  
			  
			The pair found that 52 people in ExAC 
			had PRNP mutations that have been linked to prion diseases, 
			but based on the prevalence of the disease, they would have expected 
			to see maybe two.    
			Minikel calculated that some of these 
			supposedly lethal mutations elevated a person's risk of prion 
			disease slightly; some seemed not to be linked to prion disease at 
			all.   
			This work provided insight for people 
			such as Alice Uflacker.    
			In 2011, Uflacker's father, Renan, died 
			from 
			
			Creutzfeldt-Jakob disease, a prion illness that causes rapid 
			mental and physical deterioration. He was 62. Alice found out that 
			she carried a mutation in PRNP called V210I, which had been 
			linked to her father's disease in previous studies.    
			Three years later, she learned from 
			Minikel that the mutation confers, at most, a small risk of disease. 
			The information was helpful, and the result made sense; her 
			grandmother had lived to 93 despite having the same mutation.   
			Vallabh and Minikel would find no such 
			relief, however. D178N was absent from the other genomes they looked 
			at, and is still highly likely to cause prion disease.    
			Minikel and Vallabh had already begun to 
			suspect as much, as Minikel dug into the data.  
				
				"All along the way was gradual 
				confirmation of what we were assuming anyway," Minikel says. 
				"There wasn't any moment where we said, 'Ah, this is the worst 
				news.' We'd already gotten the worst news."       
			Human knockouts  
			ExAC is revealing a lot about genes 
			through the frequency of mutations.    
			MacArthur and his team found 1 
			3,200 genes that are almost never severely mutated in any of the 
			ExAC genomes - a signal that these genes are important. And yet 72% 
			of them have never before been linked to disease. Researchers are 
			eager to study whether some of these genes play unappreciated parts 
			in illness.   
			Conversely, the group has found nearly 
			180,000 instances of mutations so severe that they should render 
			their protein products completely inactive. Scientists have long 
			studied genes by knocking them out in animals such as mice, so that 
			they don't work.    
			By looking at the symptoms that develop, 
			they can study what the genes do. But that has never been possible 
			in humans.    
			Now, researchers are eager to study 
			these natural human knockouts to understand what they can reveal 
			about how diseases develop or may be cured. MacArthur and other 
			researchers are gearing up to prioritize which human knockout genes 
			to study and how best to contact the people carrying them for 
			further study.   
				
				But it will have to wait until he 
				completes the second phase of ExAC.    
				Due to be unveiled at the ASHG 
				meeting in Vancouver, Canada, this month, it will double the 
				data set's size to 135,000 exomes and include some 15,000 
				whole-genome sequences, which should allow researchers to 
				explore mutations in regulatory regions of the genome that are 
				not captured by exome sequencing.   
				ExAC is quietly becoming a standard 
				tool in medical genetics.  
				  
				Clinical labs around the world now 
				check it before telling a patient that a particular glitch in 
				their genome might be making them ill. If the mutation is common 
				in ExAC, it's unlikely to be harmful.    
				Geneticist Leslie Biesecker 
				at the US National Human Genome Research Institute in Bethesda, 
				Maryland, says that his lab uses ExAC daily in patient care.
				 
					
					"It's a critical factor that we 
					take into consideration for every variant," he says. 
					 
				He and other geneticists are now 
				embarking on a
				
				painstaking reckoning with the genetics literature that will 
				probably take years.   
				ExAC has also driven home a point 
				that Goldstein and other researchers have made repeatedly:  
					
					that 
				failing to include people from Asian, African, Latino and other 
				non-European ancestries is holding back understanding of how 
				genes influence disease by
					
					limiting the view of human genetic diversity. 
					 
				There is now a fresh impetus to 
				include under-represented groups in planned studies linking 
				genetics and health information on large numbers of people, such 
				as the
				
				US Precision Medicine Initiative.   
				For Vallabh and Minikel, ExAC 
				provided a disheartening confirmation, but also some promising 
				insight.    
				Minikel's studies have identified 
				3 three people in ExAC with mutations that should 
				silence one of the two copies of the prion protein gene. If they 
				can live with a limited amount of functioning protein, perhaps a 
				drug could be made that would silence the defective protein in 
				Vallabh, preventing prion aggregation and disease progression 
				without dangerous side effects.    
				Minikel got in touch with one of the 
				individuals, a man in Sweden, who agreed to donate some cells 
				for research.  
				  
				Minikel and Vallabh have now joined the lab of 
				biochemist Stuart Schreiber at the Broad Institute, where they 
				are working full-time to find candidate drugs to treat prion 
				disease.   
				The couple exemplifies the challenge 
				of translating ExAC data into real medical benefits.  
					
					"We can't go back from this," 
					Vallabh says. "We have to go through it."  
				Their situation couldn't be more 
				illustrative of what is at stake: Vallabh is now 32 - just 20 
				years younger than her mother was when she died.    
				She has no time to waste.       
				References
 
				
				1. Lek, M. et al. Nature 536, 
				285-291 (2016) -
				
				Analysis of Protein-Coding Genetic 
				Variation in 60,706 Humans.
 2. Walsh, R. et al. Genet. Med. (2016) -
				
				Reassessment of Mendelian Gene 
				Pathogenicity Using 7,855 Cardiomyopathy Cases and 60,706 
				Reference Samples.
 
 3. Minikel, E. V. et al. Sci. Transl. Med. 8, 322ra9 (2016) -
				
				Quantifying Prion Disease Penetrance Using 
				Large Population Control Cohorts.
 
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