With more than six thousand in attendance, the meeting featured just about every pioneer and cutting-edge research topic that I could think of. Simply put, there was far too much content to blog about, or even remember, individual talks.
ASHG is the kind of meeting where you can’t even make all of the talks that you’d like to hear. Most of the invited platform talks are 15 minutes long, and the venue was simply too spread out to facilitate easy hops between sessions. I tried to hear a little bit of everything — rare and common diseases, statistical genetics, cancer genomics, clinical testing. And with this esoteric approach, certain themes began to emerge.
Exome Sequencing for Rare DisordersBoth researchers and clinicians are routinely applying exome sequencing to rare inherited disorders. We’re reminded that for all its caveats, exome sequencing is a powerful tool. The NIH, the Mendelian centers, and numerous other groups are seeing hundreds of cases:
- At least half are pediatric cases. This is both sad and good news, sad because you hate to think about children with genetic diseases, but good because it means that a diagnosis might provide early intervention options while avoiding a life-long diagnostic odyssey.
- Neurological disorders predominate. As many as 70-80% of referrals have an apparent neurological disorder. Granted, that’s a broad category but I still find it interesting.
- Recessive diseases are by far the easiest to solve, followed by dominant, followed by “unknown” inheritance.
- The solve rate is ~30%. This holds true across many groups and disease types.
Rare Variants in Common DiseaseThere has long been a debate about the contribution of rare versus common variants to human disease, and each side of the argument seems to have conceded the somewhat unsurprising idea that both are important. The challenge with rare variants is mainly a statistical issue: When a variant is present in one out of every 1,000 individuals, establishing that it’s significantly more frequent in cases versus controls is a tall order.
Combined Super CohortsOne solution to this problem is to simply examine a crapload of samples. Many groups have taken the admirable step of combining their datasets, and the resulting numbers are impressive. My friend Daniel MacArthur described a combined dataset — with contributions from many consortia — encompassing 60,000 exome sequences. These super-cohorts will tell us a great deal about rare variation and may even provide the power for robust studies of genetic association.
Sequencing Isolated PopulationsIsolated population cohorts offer another approach to studying rare genetic variation. The founder effect in isolated populations — such as those found in North Finland or in Mediterranean islands like Sardinia — allowed many otherwise rare variants to achieve appreciable frequencies. This lets us ask, for example, whether homozygosity for certain very rare coding mutations would be lethal to humans because such homozygotes can (theoretically) be found in isolates. When coupled with phenotype data, such cohorts also provide greater power to study rare, deleterious variants in populations enriched for them.
Wide Gene/Locus/Disease HeterogeneityThe more we think we know about what causes a genetic disease, the more we seem to find exceptions to that rule. Even among classic monogenic Mendelian diseases, there’s a surprising amount of heterogeneity in terms of causal mutations, causal genes, inheritance patterns, and clinical presentation. Take dominant retinitis pigmentosa, for example: mutations in 23 different genes (many from different pathways) cause the same disease. Screening for common mutations in these genes only explains about 60% of cases, so there are many more, likely small-contribution genes to uncover.
There is increasing evidence that those “difficult” variants — indels, structural variants, CNVs — contribute even to Mendelian disorders. The fact that these are often refractory to detection by exome or whole-genome sequencing makes it important to consider other technologies, such as exon arrays, as well as new analysis techniques. And if it wasn’t hard enough, I heard more reports of somatic mosaicism (mutations present only in certain cell or tissue types) underlying disease susceptibility, meaning that DNA from blood cells may not be informative in some patients for some diseases.
Translational Challenges for Next-Gen SequencingNGS has provided us an incredibly useful research tool, but we all know that it may have even greater potential in the clinic. Still, diagnostic and prognostic tools must overcome a number of logistical, financial, and other hurdles before they see routine use. There’s the classic “panel versus exome versus whole genome” debate. There’s the question of what to do about return of information, especially for incidental/secondary findings that may come up when a broad assay (e.g. exome) is applied. Exome sequencing is beginning to show both cost and speed advantages over many established diagnostic tests; it’s only a matter of time until it supplants them.
The issue of returning information to patients is a tricky one. As a geneticist, it’s hard not to see the genetic counseling, family planning, and simple this-is-what-you-have advantages of reporting back to patients (through their clinicians or counselors, of course). As scientists and/or clinicians, we want to make sure that we get it right. As Americans, we also don’t want to get sued. The sad truth is that these two concerns may restrict how much information is returned to patients for a long, long time.
The Future of Human GeneticsIt is clear that while we have made incredible — and I do mean incredible — progress in the field of human genetics and genomics, there are still many unanswered questions. For one thing, there’s a pressing need for functional validation of statistical/genetic findings that come out of these studies. The literature is afloat in “little hits” from GWAS and/or exome sequencing studies. Someone on the Twitter feed rightfully reminded us that GWAS hits should generally not be reported along with the “nearest gene” — a trend that tends to pollute the scientific literature. An associated variant near a gene may have nothing to do with that gene. Chromatin interactions, trans-regulatory events, and distal enhancers are just some of the mechanisms by which elements in the genome can modulate distant genes.
The Need for Functional ValidationAs most of us know already, top-tier journals are usually dissatisfied with purely genetic/statistical findings. They want independent replication and functional validation. Both of these are time-consuming and expensive propositions. This will require bringing together the functional experts (molecular biology, model organisms, and reverse genetics) with the “gene hunters” as well as a serious commitment from funding agencies. The journals want this sort of thing, the scientific community needs it, so the granting agencies should fund it.
The Need for CollaborationAnother theme of the meeting, one I highlighted at the end of my own platform talk, is that we all need to work together and share resources — samples, knowledge, tools, etc. — if we are to find success in our work. The lone PI, working independently and aloof from other groups, is doomed to fail in this modern world of high-throughput, big data science. I find it encouraging that many investigators and consortia seem to have recognized this, and are pooling their cohorts for the greater good.
Improving Human LivesASHG president Jeff Murray gave a stirring address to open the meeting. Some of the things he said really resonated with me. Many years ago, his brother (a trisomy 21 carrier) suffered under the medical regime. He spent most of his life in an institution, and never had the chance at the treatment or understanding that we might be able to offer today. Medicine certainly has come a long way since then, but Murray reminded us that “Discovery should always be complemented by working to prevent or treat those entities that we have the tools — but sometimes not the will — to address today.”
He encouraged us to spend a little bit of time thinking about how we might do that, how we might pause after finding that hot new disease gene and try to think of ways to help the patients (rather than just racing on to the next one).
Finally, Dr. Murray proclaimed that there’s no better career than to be involved in genetics research. And if you’ve read this far, you know that he’s right.