What is in your genome? – MyGenome’s WGS data reveals some interesting surprises but no immediate action needed.

Got my report from Vertias for the MyGenome analysis. What is it that is hiding between the words that come out of my mouth that get written down on this blog? Saliva was delivered into a tube, 3 months ago, and finally the data is starting to arrive.

What lays beneath the surface, may not stay beneath the surface.

If you are like me, you may think you are “healthy,” but we know what is highly likely – you will be a carrier for a disease and it’s also likely risk factors for other diseases will be identified in your genome. Note, 9 of 10 persons are carriers for rare disease, as previously addressed in a prior post. You will even have a low chance (~20%) for immediately actionable conditions that you can start to explore now and find mitigating options.

The Ticking Time Bomb

That last one is perhaps the most compelling reason to get your genome done – can you capture an impending time bomb of genetic disease before it has gone off! For pathogenic variants in the ACMG59 “secondary findings” genes, you stand a good chance of being able to diffuse the bomb before it is too late.

For my report, immediately actionable findings were not discovered. I am highly skeptical that we can say I am healthy and “free” of a genetic precondition. It is clear that researchers are only just now scratching the surface of this potential. The rare monogenic drivers of disease are somewhat understood, but the polygenic drivers are way more in their infancy.

What lies beneath might be two variations that, by themselves are not pathogenic, but together they can cause, or highly exasperate, a disease.

Think about the size of the problem from a theoretical aspect. There are roughly 7000 genes thought to be involved in rare disease. Some of the variants in these genes are monogenic and powerful enough by themselves to cause disease. But it is likely there are many more variants in these genes for which their contribution is not pathogenic by themselves and they need another variation somewhere else in the genome to enable manifestation of disease. Taking just the 7000 genes, the diagenic possibilities are 49 million. In fact, the remainder of the genome can be part of the diagenic, so the space may actually be near 400 million. Then what about 3 gene sympaticos – 8 trillion!! Thats a 1000x more than the number of the people on the planet! The only hope we have for predictive systems here is Big Data and AI options to help us gain sufficient understanding.

Heterogeneity and Homogeneity – the Advantage and Bane of Each.

To truly move to greater understanding of our genetic liabilities, we must move from qualitative (yes or no?) assessment to the quantitative (how much?) assessment. Knowing that a gene variant is 50% pathogenic in its potential can help us start to deconvolute the polygenic problem. When two 50% pathogenic variants in the same disease pathway are seen in the same individual, we have will have reached a threshold and the disease condition can manifest. With the amazing amount of heterogeneity in the human genome, analyzing patient derived tissue will be an extremely difficult approach for quantify pathogenic potential of a variant. Instead, it becomes highly desirable to use systems of high homogeneity. A uniform genetic background greatly simplifies the quantitation of disease contribution of a variant. Knowing the genetic background is the same, we can easily say that gene variant A is XX% stronger than gene variant B in regards to a pathogenic propensity, after deploying a range of function tests of deviant behavior for each of the variants.

Proxies of Disease Biology

The use of C. elegans has unique attributes that make it an ideal system for quantifying variant behavior. There is enough similarity of gene function between humans and the worm, that so far, 4 of 4 human gene insertions with observable sequence homology have been capable of rescue function as gene replacement of the ortholog gene in the worm. Of the many favorable features (speed to transgenics, microscopic size, high-throughput amenable, wide range of easily measured phenotypes, etc), the worm is a self fertilizing hermaphrodite. What this means is that when growth conditions are good, the animal clones copies of itself and can go from 1 animal to nearly 30 million near identical animals in just under 10 days. Only when conditions get stressful does the accident of spontaneous nondisjunction of sex chromosomes become more prevalent and males can form. Under these stress conditions, males go from being extremely rare to about 1 per 100 animals. So the worm has evolved to be highly tolerant of homogeneity and only needs to sample heterogeneity a small fraction of the time to maintain health of the species (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1462001).

Classical LOH – the Bane of Self-fertilization

The clonal nature is quite useful for getting large populations of nearly identical animals, but there is a flip side that creates problems. There is a phenomenon in genetics called Loss of Heterozygosity. Commonly applied to explain the evolution of cancer cell populations, the principle applied to population genetics in species is backcrossing will drive heterozygous conditions towards rarity. What this means for a self fertilizing hermaphrodite is that if the individual starts to self-propagate, and has one of their gene’s in a heterozygous conditions (A/B: variants A and B for a given gene),then half the progeny will be homozygous (either A/A or B/B) and the other half will be heterozygous (A/B). In the next generation, the prior homozygous remain homozygous (either A/A or B/B), but the hets generate another 50/50 split of homo and het. After 10 generations the het is nearly nonexistent in the population (<1%) . The population has bifringed to to A/A and B/B strains. If B/B is deleterious to life, then at 10 generations, most of the animals are A/A.

DNA replication is not perfect. As a clonal population expands, random mutations happen that essentially create heterozygous conditions at random genes (A/B scenarios). For the researcher maintaining strains, one of the biggest mistakes they can do is serially propagate the next generation plate by isolation of only 1 individual for the next population expansion. Since each clone progeny will have at least 4 de novo mutations in their genome from their parent, in just a few generations of this extreme selectivity, the population after 10 generations will have quite a few random and possibly pathogenic hits in quite a few genes and the animals of the serially-propagated strain will have drifted significantly in their genetics from the starting strain. Critical here for C. elegans is to occasionally access sexual reproduction to avoid Muller’s Ratchet.

Genetic drift is Unavoidable

To mitigate this, but not eliminate it, good practice is to transfer 10 to 20 animals for next generation of animals being maintained as a population. Even with this technique, fecundity compromised strains can quickly evolve new mutations that eliminate the starting phenotype and grow faster. So, add to a variety of other transgenerational silencing mechanism, the clonal propagation of a strain can lead to auto-selection of suppressors that effectively “silence” an engineered gene phenotype. Thankfully worms can be flash frozen shortly after making a transgenic line, so one can essentially have an endless supply of starting material. Genetic drift driving selection of gene silencing backgrounds can be avoided by going to a fresh thaw. As a result, high levels of homogenous backgrounds can be obtained for comparing the properties between two variants.

Anti-simpatico Creates More Complexity

Lets take the dialog back to the quantitation of pathogenicity in variants of human disease genes. There are almost certainly some variants in the genome that act to suppress a “monogenic” pathogenic variant. We can envision a negative pathogenicity value for these variants. And adding more complexity to this, is the fact that a variant can be pathogenic in one condition and be protective in another condition. The classic example is sickle-cell anemia and malaria. A person who is a carrier for a recessive pathogenic variation is protected from malaria infections. Yet for persons who are homozygous for the V6Q change in hemogobin, they will have a pathogenic condition that leads to quality of life issues and a reduced lifespan (https://www.cdc.gov/malaria/about/biology/#tabs-1-4). So, as Julie Eggington says, pathogenicity assessment must be made in a disease-specific context. As a result, calculating all of any one individual’s genetic liabilities is an exceedingly complex problem.

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