Thank you to everyone who sent kind messages after I announced the end of MassGenomics earlier this month. Please rest assured that this website and all of its articles will remain online for the foreseeable future.

Also, I have an important announcement. Today is Rare Disease Day, an annual event that aims to raise awareness of rare diseases and the pressing need for more research. It’s the perfect occasion to announce KidsGenomics , my new blog about the genomics of rare diseases and pediatric cancer.

KidsGenomics

The format will be similar to MassGenomics, with posts every couple of weeks (sign up here for notifications). I’ll be expanding the content to include interviews with clinicians/researchers working on pediatric diseases, and patients/families affected by them. Head over to KidsGenomics.org to see my first two posts: a review of a paper about patients with multiple rare diseases in The New England Journal of Medicine, and an editorial on why rare disease research matters.

I started MassGenomics ten years ago, when so-called next-generation sequencing was still in its infancy. I’d joined the Genome Sequencing Center at Washington University, fulfilling a dream I had since high school. At the time, two NGS technologies had begun to emerge: 454 pyrosequencing and Solexa sequencing-by-synthesis.

Over the next several years, Solexa was acquired by Illumina and matured to become the workhorse of the genomic research community. 454 sequencing was applied to some innovative projects, but could not match the price or accuracy of Solexa. It was acquired by Roche but eventually faded to obscurity. ABI Life Sciences made a brief foray into next-gen sequencing with its much-hyped (ill-fated) SOLiD platform.

It was a thrill to be at a leading sequencing center during the rise of NGS. We sequenced the first cancer genome, and went on to characterize numerous common tumor types for The Cancer Genome Atlas. Whole-genome sequencing is now the mainstay of genetic research, and will help uncover the molecular basis of countless diseases in the years to come.

Unfortunately, it has become clear that I can no longer give MassGenomics the attention it deserves. I managed only 13 posts in 2017, a far cry from my typical frequency of 20-30 posts per year. There are three main reasons my attentions have been elsewhere:

1. Shift to Science Fiction

As you probably know, I do some writing outside the realm of science. Today marks the publication of The World Awakening, the third and final book in my series with HarperCollins about a Vegas magician who infiltrates a medieval world. There’s surprisingly little hard science in these novels, which has surprised some people. Let’s just say I’m saving the hard stuff for another project.

Speaking of which, I’m also spending more time on nonfiction aimed at writers. I’m currently editing Putting the Science in Fiction , a compendium of 60 articles on biology, chemistry, physics, engineering, and other subjects relevant to genre fiction. I have about 40 contributors to that volume, which is being published by Writer’s Digest Books in Fall 2018. It’s keeping me busy.

2. Less Large-Scale Sequencing

Another more practical reason that I’m not writing as much for MassGenomics is this: I no longer work at a large-scale genome center with the latest factory-scale sequencing system. In other words, Illumina is no longer taking my calls. (I’m kidding about this — the folks at Illumina are actually quite responsive, and I appreciate that a number of them read my blog).

There are others who are better informed about the state of large-scale genome sequencing. My friend Keith Robison of Omics! Omics!, for example, has never stopped in providing a cogent analysis of NGS technologies and applications.

3. A New Focus: Rare Diseases and Pediatric Cancers

I moved to Nationwide Children’s Hospital about a year and a half ago. Our mission at the Institute for Genomic Medicine is very different from that of a large-scale sequencing center. Our ultimate goal with NGS is to help individual patients, whether that’s providing a molecular diagnosis for a rare disorder, or searching for new treatment options in pediatric cancer patients.

That’s also where my passion lies, and so it makes sense for me to devote my energies there rather than to MassGenomics. I do have something else in the works, and plan to announce that on Rare Disease Day, February 28th.

I’ll end by saying THANK YOU to all of the readers who’ve followed MassGenomics over the past ten years. This blog has been an important part of my life, and I’m grateful for everyone who came along for the ride.

~Dan Koboldt, February 2018

In September of this year, genetic counselors from all over the United States descended on Columbus for the annual meeting of NSGC, the National Society of Genetic Counselors. One of the major outcomes of that meeting was the announcement that November 9th (today) would be Genetic Counselor Awareness Day .

genetic counselor day

I’m not a genetic counselor, nor do I claim to be an expert in their profession. However, in the year since I joined Nationwide Children’s Hospital and The Ohio State University, I’ve gotten to know quite a few of them. Too, I have an increasing appreciation for their vital roles in genetic research, laboratory testing, and clinical care.

Genetic Research

I’ve written in the past about the fact that, once NGS technologies became widely available to the research community, samples were the new commodity. In particular, we as researchers are expected to obtain large cohorts of well-phenotyped samples that have research value. A critical aspect of the cohort assembly is the informed consent that patients and/or their families must sign to participate in research. These documents are increasingly nuanced and complex with regard to the scope of use, privacy protections, and how data may be used or shared.

Like most legal documents, consents are complicated and somewhat-frightening to the average person. Most of the time, the time-consuming work of explaining and obtaining informed consent is done by a genetic counselor. Without consents, we have no usable samples, and without usable samples, we have no research study. It’s that simple.

Laboratory Testing

Our institution and many others like it also have laboratory genetic counselors who assist clinicians in ordering laboratory tests for the patients under their care. This is a challenging role to play, as the adoption and evolution of genetic testing often far outstrips the ability of clinicians to understand:

• The tests that are available, and what they involve
• Which tests are most appropriate for most patients
• The expectations and results for genetic tests

Lab GCs, according to what I understand, are the crucial layer between the clinical laboratory and the ordering physician. This role requires both extensive knowledge about genetics and laboratory testing, as well as basic communication/people skills. Those things don’t always segregate together in humans, as you probably know.

Patient Care and Advocacy

Genetic counselors are often involved in patient care, and here is where their diverse skill set is especially valuable. Genetic information is increasingly part of patient care in the Western world. It’s also a powerful tool, often allowing for rapid diagnosis of conditions that may not always be clinically obvious.

And yet, as much as it excites us, human genetics can be frightening to the average person. Daunting. Difficult to understand. There is also the quite real possibility of (for lack of a better term) genetic malpractice: inappropriate test orders, incorrect interpretation of results, unauthorized or unwanted use of samples for research purposes. As the bridge between patient families and laboratories/researchers, genetic counselors not only participate in patient care, but serve as their advocates when necessary. In other words, they take responsibility for protecting the patients privacy and well-being. And that may be the most important role of all.

Thank you, genetic counselors. We appreciate you!

I’m back and nearly recovered from the American Society of Human Genetics meeting in Orlando, Florida. The conference was well-covered on the #ASHG17 hashtag as usual, but I also compiled detailed notes that I’ll share here. The obvious theme of this meeting, from my point of view, was the rise of clinical genome sequencing in patients with inherited disease.

Genomes for breakfast with Karl Stefansson from deCODE

I heard a great talk by Karl Stefansson at one of the early-morning exhibitor events. He said that DeCODE has genotyped 425k individuals, performed WGS on 50k, and RNA-seq on 10k. Of particular interest was their work on de novo mutations in families. Some background:

• Each one of us born with ~70 de novo mutations
• 1/10 children born with LoF mutation in a gene
• 1/20 children born with LoF mutation in a gene expressed in brain

De novo mutations shared by siblings

Decode examined 1,010 sib pairs from 253 families:

• 447 autosomal de novo mutations shared by two or more siblings. (out of 17,710 per fam?, 2.5%)
• But notes use of strict filters: no reads showing mutation in parent selects against mosaic
• Age effect: the older the father, the fewer de novo mutations shared
• 70% of the diversity in de novo mutation rate is explained by paternal age. 2x mutations if 40 yo father vs 20 yo

Stefansson also relayed some interesting work on non-transmitted alleles in parents of children, finding that even when not passed on, many were significantly associated with the kids’ educational attainment, socioeconomic status, and other factors. He called it “genetic nurturing” and I love the concept. He also offered a few memorable quotes during his talk; my favorite was, "In human genetics, your competitor always becomes your collaborator."

Clinical WGS: One Test to Rule Them All

Much of the ASHG conversation of course, was driven by Illumina. At their lunch symposium, CSO Ryan Taft touted clinical WGS as “one test to rule them all” — a single assay for detecting SNPs, indels, repeat expansions (an area of active software development at the company, i.e. ExpansionHunter), and large structural/copy number variants. Although I’m personally dubious about the ultimate ability of short-read sequencing to fully characterize large repeat expansions like fragile X and C9orf72, Taft sounded optimistic. He also shared some vignettes from the iHope network, an initiative to provide clinical WGS pro bono to families who can’t afford genetic testing. Their 2017 cohort included 81 cases; I took some quick numbers down (note, not

• 62 trios, 14 duos, 5 quads
• 7% were already likely positives (VUS that later got bumped)
• 7% reached a partial explanation (some but not all of disease)
• 21 cases with likely causal variants; many of these involved CNVs
• Clinically signif. variant types: 48% SNVs, 4% indels 1-4 bp, 31% CNVs 19kb-15mbp, 4% gross abnormalities, 11% multiple variant types, 2% LOH/UPD

Taft described one case of a de novo deletion on 19q13 (KMT2B) in 9-yo male. Array results were “not accessible” at time of referral. Obviously such an alteration would have been detected by an array at a significantly lower cost. Taft said that the patient had gotten an array, but the results were “not available” when they decided to proceed with sequencing. Even so, WGS certainly does have an advantage over clinical arrays for detecting kilobase-scale CNVs. The challenge, of course, is the cost.

The Clinical benefit of WGS in 300 families

Peter Bauer from Centogene gave a nice summary of clinical WGS in 300 families. Their interpretation strategy, it must be said, is nevertheless very coding-centric: they focus on coding region +/- 10bp, examining deep intronic variants only if already described as pathogenic, in an established candidate gene, or a region of homozygosity. He also highlighted the importance of previous testing on clinical WGS yield: they saw a 26% diagnostic rate for cases without previous WES testing, compared to 18% for cases that had been through WES. Interestingly, 55% of their diagnosed cases had a positive family history. I interpreted that as an illustration of the power of family-based sequencing with multiple affected relatives. A breakdown of pathogenic variants:

• 29% splice site (wow!)
• 25% missense variants
• 22% nonsense variants
• 22% indels (20% frameshift, 2% inframe)
• 2% large deletions

Note the contrast with Illumina’s numbers, which featured CNVs much more prominently.

Mendelian Disease Updates

Here are some highlights across a number of talks about clinical/research sequencing in rare inherited disorders.

Posey on behalf of CMGs on clinical impact of gene discovery

Jennifer Posey gave a nice report on progress at the Centers for Mendelian Genomics, from the Baylor perspective. She reminded us that the CMGs post their candidate genes on a website, many before publication. Baylor alone has discovered 300+ disease genes; 14% of these have already led to a diagnosis in their clinical lab (accounting for 3-4% of positive reports). She also mentioned that clinically negative WES cases are referred to the research lab for further evaluation, and 51% (yes, HALF) of these ultimately get a candidate diagnosis. I asked a question about this, because the rescue rate seemed almost too good to be true. She said that many of those rescues were achieved after additional family samples sequenced, which allowed a more definitive interpretation of a VUS. However, sometimes new disease gene publications were the source.

Rare and Undiagnosed Diseases in Pediatrics Initiative in Japan

Japan’s initiative has a 32% diagnostic rate, 77.4% autosomal dominant (presumably de novo), 12% X-linked, 9.1% autosomal recessive. I think it’s valuable to include these numbers because they show similar trends to what we’ve seen in predominantly European ancestry cohorts: a 1-in-3 solve rate, and a majority of positive clinical reports due to de novo mutations.

The contribution of rare recessive coding variants to severe developmental disorders in DDD

Hilary Martin gave a nice talk about the DDD project, which has enrolled over 10,000 cases and already yielded some valuable insights into the genetics of developmental disorders. For example, de novo mutations account for 40-45% of cases. Their analysis framework for recessive variants suggests that parents show lower frequency of biallelic variants than expected by chance … because presumably lethal or disease-causing biallelic pairs are not in healthy parents. There are twice as many recessive genes as dominant ones, but even so, recessive genes account for only a fraction (~5%) of their mostly-European-ancestry cohort.

A Review of Clinical Exome and Genome Sequencing

Stephen Kingsmore from the Rady Institute presented a meta-analysis of exome/genome sequencing in 19,715 infants/children from 75 studies. It’s an impressive dataset, and I think the results are thus very compelling:

• Diagnostic sensitivity: 0.40 for WGS, 0.35 for WES, 0.09 for chromosomal microarray.
• Between 2013 and 2017, the rate of diagnosis increased 16% each year.
• Rate of consanguinity in study is inversely proportional to rate of pathogenic de novo mutations
• Odds of Dx by trio testing were TWICE that for singleton testing
• The diagnostic rate was higher at hospital labs (0.41) than reference labs (0.28?)
• In six 2017 studies, odds of Dx by WGS/WES were 8.3x higher than that for CMA

Kingsmore found only 2 small studies which compared diagnostic sensitivity of WES versus WGS; both reported no significant difference. He said “the literature needs to catch up,” which I take to mean that he thinks WGS has a clear diagnostic advantage.

Automated reanalysis of clinical exome data in a fee-for-service clinical Dx lab.

One of my favorite talks was from Sam Baker from CHOP on their pipeline for automated re-analysis of clinical exomes which were reported as negative (80% of their first 300 probands in the lab). They have an approach for mining weekly PubMed abstracts (from new papers) to see if they inform past exome cases. He described "Clinical correlation" (manual assessment of gene-disease phenotype overlap) as the most important and most time-consuming step. They have a

Phenotype terms retrieved from chart review were used with genotype data. Automated correlation comes from 3 filters:

1.) Patient phenotype to gene-disease compares gene symbols and phenotype terms in PubMed Abstracts/OMIM entries

2.) Filters based on variant characteristics, quality, MAF, effect

3.) Filter based on segregation / inheritance

Their reanalysis of 240 negative exomes revealed 27 novel diagnoses

• 17 new disease gene
• 6 classification update of previous VUSes
• 1 new phenotype described for a known disease gene
• 3 candidate genes that don’t meet lab’s diagnostic criteria but they think they have it
• The diagnostic yield went from 20% in the initial analysis to to 29% with automated reanalysis. Their pipelines have really whittled down the monthly re-analysis workload to make it feasible (it’s usually 1-5 variants per case per month).