Spring is here! (almost) I have a piece in Slate in case you haven’t noticed. Sorry about the one day delay, but I left this in drafts and was busy with other things.
Google Trends Search Results for CRISPR
- Genesis, 3:5
Sometimes science surprises you. Many a time science seems like a slowly sluggish river, inexorable in its progress, but languid nonetheless, beset by turns and twists which delay its progress. Over the last year though I’ve been hearing people whisper in excited tones about something new, something special. And it’s about CRISPR. This may indeed be a world-turned-upside-down moment, and CRISPR may finally cash out the promise that biological science is going to result in a flowering of engineering analogous to what occurred during physics’ ‘atomic age.’
And now the excitement is percolating into the public spaces of the middle-brow media. The New York Times has now finally put CRISPR on the radar of the broader culture, in a rather long article, A Powerful New Way to Edit DNA. As they they, “read the whole thing,” but key in on this quote:
“It just completely changes the landscape,” Dr. Doudna said. Berkeley scientists used to farm out that work to specialized laboratories or companies. Now, she said, “people are able to make mice in their own labs.”
No, it complete creates a landscape. Theory becomes concrete, and the speculations and worries of bioethicists are challenged by the real present, not some vague future. Now a biologist can state, I am become life, creator of worlds. Whereas genetic engineering up to the present has been an almost artisanal act, CRISPR opens up the window into the possibilities of scalable industrialization. No doubt there will be Neo-Luddites demanding we smash the looms, but they will fail, as they always have.
There’s been a lot of talk on Twitter and the blogs about PLOS’ new data sharing policy. I don’t have much deep to say, except that I’m for it. I do think from what I can tell that there is a cultural element to the reaction, pro or con. People in genomics seem to be responding of the form “yes, of course.” On the other hand those in other fields have less positive reactions.
You can go elsewhere to hear “both sides.” I am confident that this will be the future, and the naysayers will have to deal. One of the major reasons that formalized data release is good is that in a field like genomics there is more data than people to analyze the data. By this, I mean that you can ask many different questions of data, but you may only be interested in a subset of those questions. Other people in your lab might have different questions, but ultimately you’re probably leaving avenues on the table because you don’t have the time or inclination. To give you a funny example, a few years ago I stumbled on the fact that Dan MacArthur probably has recent (>200 years) South Asian ancestry. As an academic genomicist Dan could have dug up this fact himself, but he has grants and papers to write, not to mention a non-scientific life. So it was left to me to stumble upon the fact. On the margin it’s not that useful to Dan, but it’s something. You never know what’s going to happen when you release data, because you can’t read the minds of others. And that sort of surprise is a good thing.
One of the greatest intellectual philanthropists in recent years has been Mait Metspalu. He has plenty of publications to his name, but he’s also generously released and assembled the data together in convenient form. This allows for easy reanalysis. A few days ago I noticed that he had put up a few more European populations, including understudied groups like Greeks. With the recent flair up on Ukraine I thought I would process some of the new data. I pruned the data set down to 230,000 high quality SNPs, and focused on a large and small data set respectively of 500 and 340 individuals.
A reader pointed me to a paper in The Proceedings of the Royal Society B, Was skin cancer a selective force for black pigmentation in early hominin evolution?. My initial reaction was to dismiss this argument, because cancer is obviously a late-in-life disease, and therefore it would not be a major selective hit. Rather, I found Nina Jablonski’s argument in Skin: A Natural History, persuasive. Basically she suggests that chemical processes triggered by ultraviolet radiation result in the destruction of folate, and this in turn leads to elevated miscarriage rates due neural tube defects. Anything that impacts direct female reproductive output is a candidate from strong natural selection, so the thesis was highly persuasive.
But after reading the paper I do think the argument that carcinomas can reduce the fitness of humans with light skin in the tropics has merit. The author uses the case histories of albinos in Africa, who tend to develop serious health issues by their twenties. Obviously white skin is not albinism, but if the suboptimal function and lethality for albinos is correct, I can’t but help think that light-skinned hunter-gatherers on the Malthusian margin would have an even tougher go.
We can frame evolutionary question with some molecular genetic inferences. It seems that strong constraint (selection) impacted the region around MC1R 1-2 million years. The model is that ancient hominins shifted toward the savanna, lost their fur due to thermo-regulation needs, and then evolved dark skin to protect themselves against the radiation. What I think needs to be acknowledged is that it could have been that multiple forces resulted in the shift toward dark skin, which probably occurred concomitantly with the loss of fur.
Yesterday I tweeted out Obesity Rate for Young Children Plummets 43% in a Decade. This is a big deal, and many people retweeted it. Here’s the summary in The New York Times:
But the figures on Tuesday showed a sharp fall in obesity rates among all 2- to 5-year-olds, offering the first clear evidence that America’s youngest children have turned a corner in the obesity epidemic. About 8 percent of 2- to 5-year-olds were obese in 2012, down from 14 percent in 2004.
They helpfully link to the paper in The Journal of the American Medical Association, Prevalence of Childhood and Adult Obesity in the United States, 2011-2012. And actually, if you read the paper the authors themselves seem very unsure about the robustness of this specific result. I quote from the paper:
…Tests for differences by age in children were evaluated with the following comparisons: aged 2 to 5 vs 6 to 11 years, 2 to 5 vs 12 to 19 years, and 6 to 11 vs 12 to 19 years. Similarly, in adults comparisons were made between aged 20 to 39 and 40 to 59 years, 20 to 39 and 60 years or older, and 40 to 59 and 60 years or older. P values for test results are shown in the text but not the tables. Adjustments were not made for multiple comparisons.
…Similarly, there was no significant change in obesity prevalence among adults between 2003-2004 and 2011-2012. In subgroup analyses, the prevalence of obesity among children aged 2 to 5 years decreased from 14% in 2003-2004 to just over 8% in 2011-2012, and the prevalence increased in women aged 60 years and older, from 31.5% to more than 38%. Because these age subgroup analyses and tests for significance did not adjust for multiple comparisons, these results should be interpreted with caution.
In the current analysis, trend tests were conducted on different age groups. When multiple statistical tests are undertaken, by chance some tests will be statistically significant (eg, 5% of the time using α of .05). In some cases, adjustments are made to account for these multiple comparisons, and a P value lower than .05 is used to determine statistical significance. In the current analysis, adjustments were not made for multiple comparisons, but the P value is presented.
The p-value here is 0.03 for the difference in question. That passes the conventional threshold of significance (0.05), but it is close enough to the border that I’m quite suspicious. Here is the full conclusion of the paper:
Overall, there have been no significant changes in obesity prevalence in youth or adults between 2003-2004 and 2011-2012. Obesity prevalence remains high and thus it is important to continue surveillance.
Granted, these may turn out to be real true results. And the age class that showed a decline in obesity is definitely one we should focus on. But public health is a serious matter, and therefore we shouldn’t get ahead of ourselves.
One hypothesis that presents itself in regards to this paper is that a reviewer asked explicitly about the multiple comparisons problem. The authors acknowledged the problem, without actually checking to see if the results hold after a correction, and then the editor let the paper through. Of course this is just a model. I haven’t tested it, so can’t even offer up a p-value, even if I was a frequentist.
Note: The raw data is here.
There seems to be a deep and ancient connection between the populations of Southeast and South Asia, most evident in the substrate of the Cambodians. In First Farmers the author relays an early report about a farming community in northern Vietnam where morphological and ancient DNA evidence both pointed to a stabilized coexistence between a classically East Asian majority population and another which he terms “Austro-Melanesian.” This latter group has been predominantly absorbed today, but seems to persist in isolated tribes such as the Senoi. But these are most certainly residual elements, near extinction, and it seems the dominant genetic heritage of major ethnicities such as the Khmer derives from agriculturalists who left southern China over 4,000 years ago. Only in eastern Indonesia does the Melanesian component of ancestry in Southeast Asia begin to increase to a non-trivial component, and this area is truly as much or more part of Oceania than maritime Southeast Asia.
The Indian subcontinent has also characterized by a synthesis between outsiders, who likely brought farming technologies, and the native inhabitants. These ancient populations had very distant connections to the ancestors of the hunter-gatherers of the Andaman Islands, and no doubt with the peoples of pre-agricultural Southeast Asia, and further on toward Oceania. This is not to say that the zone between the South China Sea and Indus was homogeneous. Rather, like Northeast and Northwest Eurasia, it was likely a region where peoples diversified from an original Pleistocene element which arrived ~50,000 years ago, and retained broad affinities through gene flow and common ancestry. But whereas the farmers in Southeast Asia came from the north, those in India came from the west. Additionally, it seems clear that the fraction of ‘indigenous’ ancestry is far higher in South Asia, on the order of ~50% across the subcontinent. The equivalent figure for Austronesians, Daic, Burman, and Austro-Asiatic populations of Southeast Asia of Pleistocene hunter-gatherer is probably closer to ~10% (higher in the Austro-Asiatic, least among the Daic).
So I have decided to offer up a hypothesis: the agricultural toolkit which West Asian farmers brought to the northwest fringe of the Indian subcontinent was far more constrained in its ability to expand than the equivalent for the rice farmers from southern China. Though there is still debate, it seems that the dominant Indian cultivar of rice has an East Asian origin. Though wheat plays an important role in Pakistan and northwest India, rice is the staple crop for the preponderance of the South Asian population. Though I hold to the proposition that the Austro-Asiatic populations of South Asia are recently intrusive (i.e., they are not the primal inhabitants as some would argue), for geographic reasons, it seems that east to west migration across the difficult north-south mountains separating South and Southeast Asia served as a check on migration from farmers in that zone. Ultimately it was South Asian rice farmers, a hybrid population, that pushed south and east and absorbed the tribal hunter-gatherers who remained in their fastness (the current Indian tribes are not descendants of the original hunter-gatherers, but admixed populations at the margins of Sanskritic civilization; both genetics and their mode of production suggest this). The long pause in the northwest due to the limitations of their agricultural toolkit may explain the difference between South and Southeast Asia in the completeness of their demographic assimilation. Where the rice farmers from southern China swept across all of Southeast Asia rapidly in a singular sweep, the West Asian farmers were halted for many generations at the limits of their ecological range, absorbing genes from the hunter-gatherers on their frontiers. The analogy here would be the Xhosa, Bantus at the edge of their range of expansion which have absorbed a great deal of genetic material (~25% of their ancestry) from Khoisan populations. Once the proto-Indians of the northwest had accumulated enough cultural adaptations their distinctive West Asian genetic signal may already have been substantially diluted by gene flow from the hunter-gatherers to the south and east. The subsequent expansion into the forest zones was likely a demographic disaster for the old natives, but the newcomers themselves were already partly cousins.
I purchased Greg Clark’s most recent book, The Son Also Rises: Surnames and the History of Social Mobility, and it was delivered to my Kindle on the money (I’d pre-ordered), but I don’t think I’ll be able to read it in the near future, as I’m quite busy. Luckily, Clark has written a nice precis in The New York Times. He notes the likely role of heritable variation in maintaining the status of particular lineages over hundreds of years. From an American perspective this is not a congenial outcome for any ideological camp. On the Right it discomfits those who hold that this is a meritocratic nation as typified by the heroes of Horatio Alger novels. But on the Left it should give pause to those who hold that increased redistributionist policies will quickly ameliorate heritable inequality.
If you don’t know what CRISPR is, you should. Two words: genetic engineering. And then you have cloning. I was talking to a friend of mine about the possibility of combining these two technologies, CRISPR and cloning. The basic intention here would be to recreate yourself, but superior. Edit out de novo mutations, and genetic load inherited from ancestors more generally. Perhaps substitute well known large effect alleles which have salubrious consequences. This is not totally abstract, as I’ve talked to many people who are interested in the idea of cloning.
For example, the economics blogger and professor Bryan Caplan has confessed that he would like to see what raising a clone would be like. Or as he states, “I want to experience the sublime bond I’m sure we’d share. I’m confident that he’d be delighted, too, because I would love to be raised by me. ” This may be correct. But now imagine that Caplan avails himself of the latest genetic engineering technology, in addition to cloning. Bryan Caplan version 2.0 is taller, better looking, smarter, more socially astute. In fact, from 2.0′s perspective the original Bryan Caplan may simply be an “alpha” version, before he was “perfected.” Perhaps 2.0 would love Caplan 1.0, but I suspect that this love would resemble Christianity’s love of its parent Judaism, which verges into patronizing condescension, as Christians believe their religion is a perfected completion of the Yahweh cult.
More farcically, consider how teenage rebellion would play out between a clone which is superior in every way to the parent. If a parent asks rhetorically “do you think you’re better than me?”, the clone would have to respond honestly, “Yes, and so do you.” The clone would be a better version of the parent, and likely this structural tension in the relationship would persist, as the original copies see themselves as they would wish to be, but never can be.
Addendum: Ted Kosmatka should write a short story based on this idea!
Over at Mother Jones Tasneem Raja and Chris Mooney have a rather alarming article up, How Many People Aren’t Vaccinating Their Kids in Your State? This is no joke. I’ve talked earlier about the fact that during my wife’s pregnancy we were confronted by rather strong anti-vaccination sentiments within the community. Because of our generally scientific bent it had no effect on us, but we saw how persuaded, or persuadable, many of our friends and acquaintances were. Without a scientific background people often rely on authorities, and those authorities can lead them astray.
One issue that has come up on occasion is the political orientation of the anti-vaccination movement. Many have assumed that it has a Left-liberal bias. I’m actually moderately skeptical of a strong political association (e.g., Michele Bachmann). But the map above suggested to me that we should test the proposition that there’s at least a state level correlation between exemptions and vote for Obama in 2012. The data was easy to get.
The raw Obama vote % and vaccination exemptions correlated at 0.08 (p-value 0.59). Pretty much nothing. But, I thought it might be more interesting to look at Obama vote for whites. Here the correlation was 0.25 (p-value 0.09). This is still a modest correlation, but it does suggest a political tinge. But rather than a standard Left-Right axis, I think we’re seeing a “crunchy counter-culture” sentiment. Here’s a scatterplot with state labels for what it’s worth….