DNA Dreams at Harvard

This is a panel discussion of the documentary film DNA Dreams (see below), about BGI and its Cognitive Genomics Lab.

DNA DREAMS

Moderator: Dr. Evelynn Hammonds, Director of the Project on Race & Gender in Science & Medicine, Hutchins Center for African & African American Research/Barbara Gutmann Rosenkrantz Professor of the History of Science

Panelists include: (L to R)
1. George Church, Robert Winthrop Professor of Genetics, Harvard Medical School
2. Bregjte van der Haak, Filmmaker
3. Arthur Kleinman, Director of the Harvard University Asia Center and Professor of Anthropology and Medical Anthropology at Harvard University
4. Peter Galison, Pellegrino University Professor, Director of the Collection of Historical Scientific Instruments, Harvard University

Peter Galison is dismissive of "single parameter" measures of cognitive ability. George Church replies quite effectively. Certainly anyone who has thought seriously about IQ or g knows that it is only a crude measure of (compressed approximation to) a multi-dimensional set of mental abilities. I wonder how Peter would react to learning that his grandchild would be born with a mutation depressing the meaningless "single parameter" in question to an SD below normal. Would he just shrug it off as unimportant?

I believe this is the entire documentary:

Value-Added College Rankings

New report from Brookings estimates value added (in terms of economic success) by university, controlling for input factors such as student quality and family income. This is just the first step toward outcomes-driven rankings of universities that will be far more useful than the existing rankings, which are largely based on prestige. Brief summary.

See also Defining Merit.

Brookings: The choice of whether and where to attend college is among the most important investment decisions individuals and families make, yet people know little about how institutions of higher learning compare along important dimensions of quality. This is especially true for the nearly 5,000 colleges granting credentials of two years or fewer, which together graduate nearly 2 million students annually, or about 39 percent of all postsecondary graduates. Moreover, popular rankings of college quality, such as those produced by U.S. News, Forbes, and Money, focus only on a small fraction of the nation’s four-year colleges and tend to reward highly selective institutions over those that contribute the most to student success.

Drawing on a variety of government and private data sources, this report presents a provisional analysis of college value-added with respect to the economic success of the college’s graduates, measured by the incomes graduates earn, the occupations in which they work, and their loan repayment rates. This is not an attempt to measure how much alumni earnings increase compared to forgoing a postsecondary education. Rather, as defined here, a college’s value-added measures the difference between actual alumni outcomes (like salaries) and predicted outcomes for institutions with similar characteristics and students. Value-added, in this sense, captures the benefits that accrue from both measurable aspects of college quality, such as graduation rates and the market value of the skills a college teaches, as well as unmeasurable “x factors,” like exceptional leadership or teaching, that contribute to student success.

While imperfect, the value-added measures introduced here improve on conventional rankings in several ways. They are available for a much larger number of postsecondary institutions; they focus on the factors that best predict objectively measured student economic outcomes; and their goal is to isolate the effect colleges themselves have on those outcomes, above and beyond what students’ backgrounds would predict.

Using a variety of private and public data sources, this analysis finds that:

Graduates of some colleges enjoy much more economic success than their characteristics at time of admission would suggest. Colleges with high value-added in terms of alumni earnings include not only nationally recognized universities such as Cal Tech, MIT, and Stanford, but also less well-known institutions such as Rose-Hulman Institute of Technology in Indiana, Colgate in upstate New York, and Carleton College in Minnesota. Two-year colleges with high-value added scores include the New Hampshire Technical Institute, Lee College near Houston, and Pearl River Community College in Mississippi. ...

On the quality of PayScale compensation figures used in the analysis:

...There are a number of ways one can assess whether or not PayScale accurately captures the earnings of graduates—or whether the sample is statistically biased by the voluntary nature of its data collection.

Broadly, PayScale earnings by major for U.S. residents with bachelor’s degrees can be compared to similar data from the ACS, which annually samples 1 percent of the U.S. population.30 The correlation between the two is what matters most for this analysis, since value-added calculations are based on relative differences between predicted and actual earnings.

The correlation between bachelor’s degree holders on PayScale and median salaries by major for workers in the labor force from the Census Bureau is 0.85 across 158 majors matched between the two databases.

Effects of student ability and family SES:

For each of the three post-attendance outcomes measured here—mid-career salary, loan repayment rate, and occupational earnings power—student test scores, math scores in particular, are highly correlated: 0.76 for mid-career salaries and 0.69 for student loan repayment and occupational earnings power (Figure 3). Other student characteristics, such as the percentage receiving Pell grants, also correlate highly with these outcomes, though not as highly as test scores.

Go Beavers! Note Caltech grads are also much more likely to win Nobel Prizes and be elected to the National Academy of Science or Engineering than graduates of any other university. Claims that a technical education bestows narrow technical skill without conveying deep ideas and teaching critical thinking are silly.

... Alumni from Cal Tech list the highest-value skills on their LinkedIn profiles (Table 3); their skills include algorithm development, machine learning, Python, C++, and startups (that is, starting a new business). Cal Tech is followed closely by Harvey Mudd and MIT. Babson College, also in the top 10, focuses on business rather than science; its course offerings teach many quantitative skills relevant for business-oriented STEM careers. Many graduates from the Air Force Academy are prepared for high-paying engineering jobs in the military and at large defense contractors. They list skills like aerospace and project planning.

Amusingly, you can see by looking at the tables of regression results that Asian share of enrollment is strongly positively correlated with mid-career earnings, whereas female share is negatively correlated. This is not surprising, given that STEM skills are big drivers of compensation.

Colgate's strong performance (and probably that of Carleton and some others) cannot be explained in terms of STEM skills -- see discussion and figure, on page 16.

CRISPR edits in human zygotes

Results such as these had been the subject of rumors for some time. Also covered in Nature News.

It is very early days for this technology -- the off-target rate can probably be reduced significantly using better methods. But in the near term, safety and efficacy issues make PGD a better technique for improving human reproduction. See, e.g., PGD in the US and Israel and Single Cell Sequencing in PGD.

CRISPR/Cas9-mediated gene editing in human tripronuclear zygotes
(Protein and Cell -- open access)

Genome editing tools such as the clustered regularly interspaced short palindromic repeat (CRISPR)-associated system (Cas) have been widely used to modify genes in model systems including animal zygotes and human cells, and hold tremendous promise for both basic research and clinical applications. To date, a serious knowledge gap remains in our understanding of DNA repair mechanisms in human early embryos, and in the efficiency and potential off-target effects of using technologies such as CRISPR/Cas9 in human pre-implantation embryos. In this report, we used tripronuclear (3PN) zygotes to further investigate CRISPR/Cas9-mediated gene editing in human cells. We found that CRISPR/Cas9 could effectively cleave the endogenous β-globin gene (HBB). However, the efficiency of homologous recombination directed repair (HDR) of HBB was low and the edited embryos were mosaic. Off-target cleavage was also apparent in these 3PN zygotes as revealed by the T7E1 assay and whole-exome sequencing. Furthermore, the endogenous delta-globin gene (HBD), which is homologous to HBB, competed with exogenous donor oligos to act as the repair template, leading to untoward mutations. Our data also indicated that repair of the HBB locus in these embryos occurred preferentially through the non-crossover HDR pathway. Taken together, our work highlights the pressing need to further improve the fidelity and specificity of the CRISPR/Cas9 platform, a prerequisite for any clinical applications of CRSIPR/Cas9-mediated editing.

The table below is from the Supplement.

Earnings by educational attainment 1990-2013

This graphic is from today's NYTimes: Why American Workers Without Much Education Are Being Hammered.

Aside from the human capital (education) point the figure makes, I'm a bit puzzled by the following: real per-capita GDP is probably up at least ~50% (e.g., ~2% x 23 years) over the 1990-2013 period. Where did those gains go? Into the pockets of a small invisible group that doesn't show up in the graph (note use of medians, not averages)? It seems that everyone except the members of this small group were "hammered" over the last two decades ...

Note added (with better data): This source has 2013 GDP at $16 trillion versus $9 trillion in 1990 (both figures in 2009 dollars). Total US population went up 26% (316 million from 249 million). The percentage of the population with college degrees went from about 20% to 30%. It still appears to me that much of GDP increase during the period did not go to workers or ordinary people.

If you annualize any of the real income changes in the graph over 23 years, the change is small -- less than 1% per year. Yet real GDP grew at about 3% per year on average during the period. The graph below (from this 2007 post) might shed some light on the mystery (even the top quintile saw little income appreciation):

More here.

China's Ideological Spectrum

These researchers identify a dominant principal component in the Chinese ideological spectrum. Discussed on Sinica podcast.

China's Ideological Spectrum

Jennifer Pan (Harvard University - Graduate School of Arts and Sciences)
Yiqing Xu (MIT - Department of Political Science)

We offer the first large scale empirical analysis of ideology in contemporary China to determine whether individuals fall along a discernible and coherent ideological spectrum, and whether there are regional and inter-group variations in ideological orientation. Using principal component analysis (PCA) on a survey of 171,830 individuals, we identify one dominant ideological dimension in China. Individuals who are politically conservative, who emphasize the supremacy of the state and nationalism, are also likely to be economically conservative, supporting a return to socialism and state-control of the economy, and culturally conservative, supporting traditional, Confucian values. In contrast, political liberals, supportive of constitutional democracy and individual liberty, are also likely to be economic liberals who support market-oriented reform and social liberals who support modern science and values such as sexual freedom. This uni-dimensionality of ideology is robust to a wide variety of diagnostics and checks. Using post-stratification based on census data, we find a strong relationship between liberal orientation and modernization -- provinces with higher levels of economic development, trade openness, urbanization are more liberal than their poor, rural counterparts, and individuals with higher levels of education and income and more liberal than their less educated and lower-income peers.

Warning: PCA is the tool of the devil ;-)

Ulam on physical intuition and visualization

The picture above is of von Neumann, Feynman, and Ulam. More Ulam. See also the nature of intuition and intuition and the two brains.

Adventures of a Mathematician: (p.147-148) ... the main ability to have was a visual, and also an almost tactile, way to imagine the physical situations, rather than a merely logical picture of the problems.

The feeling for problems in physics is quite different from purely theoretical mathematical thinking. It is hard to describe the kind of imagination that enables one to guess at or gauge the behavior of physical phenomena. Very few mathematicians seem to possess it to any great degree. Johnny [vN], for example, did not have to any extent the intuitive common sense and "gut" feeling or penchant for guessing what happens in given physical situations. His memory was mainly auditory, rather than visual.

Another thing that seems necessary is the knowledge of a dozen or so physical constants, not merely of their numerical value, but a real feeling for their relative orders of magnitude and interrelations, and, so to speak, an instinctive ability to "estimate."

I knew, of course, the values of constants like the velocity of light and maybe three or four other fundamental constants—the Planck constant h, a gas constant R, etc. Very soon I discovered that if one gets a feeling for no more than a dozen other radiation and nuclear constants, one can imagine the subatomic world almost tangibly, and manipulate the picture dimensionally and qualitatively, before calculating more precise relationships.

Most of the physics at Los Alamos could be reduced to the study of assemblies of particles interacting with each other, hitting each other, scattering, sometimes giving rise to new particles. Strangely enough, the actual working problems did not involve much of the mathematical apparatus of quantum theory although it lay at the base of the phenomena, but rather dynamics of a more classical kind—kinematics, statistical mechanics, large-scale motion problems, hydrodynamics, behavior of radiation, and the like. In fact, compared to quantum theory the project work was like applied mathematics as compared with abstract mathematics. If one is good at solving differential equations or using asymptotic series, one need not necessarily know the foundations of function space language. It is needed for a more fundamental understanding, of course. In the same way, quantum theory is necessary in many instances to explain the data and to explain the values of cross sections. But it was not crucial, once one understood the ideas and then the facts of events involving neutrons reacting with other nuclei.

This "dynamics of a more classical kind" did not require intuition for entanglement or high dimensional Hilbert spaces. But see von Neumann and the foundations of quantum statistical mechanics for examples of the latter.

Summer of '69

I love this video. The clothes, the hair, the faces -- they're all so familiar. Every person in the video looks like someone I grew up with in the midwest :-)

2:1 faculty preference for women on STEM tenure track (PNAS)

The results described below suggest that faculty evaluators of STEM job applicants tend to favor women over men. Certainly, most departments receive strong incentives and signals from above to increase numbers of women and underrepresented minorities among their faculty. Women could still face obstacles at other points in their careers, such as during promotion or merit reviews, or in the competition for resources such as grant funding or lab space. Nevertheless, I think gender discrimination has decreased significantly during my adult life.

This article is also discussed in Nature. See also STEM, Gender, and Leaky Pipelines and Gender differences in preferences, choices, and outcomes. Earlier blog posts citing research by Ceci and Williams.

National hiring experiments reveal 2:1 faculty preference for women on STEM tenure track (PNAS)

Wendy M. Williams and Stephen J. Ceci

National randomized experiments and validation studies were conducted on 873 tenure-track faculty (439 male, 434 female) from biology, engineering, economics, and psychology at 371 universities/colleges from 50 US states and the District of Columbia. In the main experiment, 363 faculty members evaluated narrative summaries describing hypothetical female and male applicants for tenure-track assistant professorships who shared the same lifestyle (e.g., single without children, married with children). Applicants' profiles were systematically varied to disguise identically rated scholarship; profiles were counterbalanced by gender across faculty to enable between-faculty comparisons of hiring preferences for identically qualified women versus men. Results revealed a 2:1 preference for women by faculty of both genders across both math-intensive and non–math-intensive fields, with the single exception of male economists, who showed no gender preference. Results were replicated using weighted analyses to control for national sample characteristics. In follow-up experiments, 144 faculty evaluated competing applicants with differing lifestyles (e.g., divorced mother vs. married father), and 204 faculty compared same-gender candidates with children, but differing in whether they took 1-y-parental leaves in graduate school. Women preferred divorced mothers to married fathers; men preferred mothers who took leaves to mothers who did not. In two validation studies, 35 engineering faculty provided rankings using full curricula vitae instead of narratives, and 127 faculty rated one applicant rather than choosing from a mixed-gender group; the same preference for women was shown by faculty of both genders. These results suggest it is a propitious time for women launching careers in academic science. Messages to the contrary may discourage women from applying for STEM (science, technology, engineering, mathematics) tenure-track assistant professorships.

IQ prediction from structural MRI

These authors use machine learning techniques to build sparse predictors based on grey/white matter volumes of specific regions. Correlations obtained are ~ 0.7 (see figure).

I predict that genomic estimators of this kind will be available once ~ 1 million genomes and cognitive scores are available for analysis. See also Myths, Sisyphus and g.

MRI-Based Intelligence Quotient (IQ) Estimation with Sparse Learning (PLOS)

In this paper, we propose a novel framework for IQ estimation using Magnetic Resonance Imaging (MRI) data. In particular, we devise a new feature selection method based on an extended dirty model for jointly considering both element-wise sparsity and group-wise sparsity. Meanwhile, due to the absence of large dataset with consistent scanning protocols for the IQ estimation, we integrate multiple datasets scanned from different sites with different scanning parameters and protocols. In this way, there is large variability in these different datasets. To address this issue, we design a two-step procedure for 1) first identifying the possible scanning site for each testing subject and 2) then estimating the testing subject’s IQ by using a specific estimator designed for that scanning site. We perform two experiments to test the performance of our method by using the MRI data collected from 164 typically developing children between 6 and 15 years old. In the first experiment, we use a multi-kernel Support Vector Regression (SVR) for estimating IQ values, and obtain an average correlation coefficient of 0.718 and also an average root mean square error of 8.695 between the true IQs and the estimated ones. In the second experiment, we use a single-kernel SVR for IQ estimation, and achieve an average correlation coefficient of 0.684 and an average root mean square error of 9.166. All these results show the effectiveness of using imaging data for IQ prediction, which is rarely done in the field according to our knowledge.

Training and testing of models was performed as described below. They had only 164 individuals in their sample, so IIUC the average correlation is computed on test samples of ~16 individuals. It would be good to see their predictors tested on larger data sets. I wonder how stable the predictor variables (feature coefficients) were across partitions.

We performed experiments with 10-fold cross-validations. Specifically, we randomly partitioned each dataset into 10 subsets with no replacement, and used 9 out of the 10 subsets for training and the remaining one for testing. To further avoid a possible bias during partitioning, we repeated the experiments 10 times.

Some background from the paper. Strangely, they don't cite the Thompson lab (UCLA) results on brain size and intelligence (21k individuals). IIRC from their results, brain size alone correlates 0.4 with IQ.

... Uncovering human intelligence has always been of major interest in cognitive neuroscience. With the advent of brain imaging, there have been efforts to investigate the relation between brain anatomy and intelligence [3,4], and substantial understanding has been achieved in the field. For example, Supekar et al. showed that the size and circuitry of certain parts of children’s brains could be a potential predictor for how well they would respond to intensive math tutoring [5]. Chen et al. [6] demonstrated that the volumetric analysis of gray matter (GM) from structural Magnetic Resonance Imaging (MRI) could be used to predict a subsequent decline in IQ in children with sickle cell disease. McDaniel et al. [3] found that the volume of the brain is positively correlated with IQ according to MRI-based experiments. Frangou et al. [7] reported positive correlations between IQ score and GM density of the orbitofrontal cortex, cingulate gyrus, cerebellum, and thalamus, but negative correlation between IQ score and the caudate nucleus. On the other hand, Navas-Sanchez et al. [8] investigated the relationship between IQ score and microstructure of white matter (WM) tracts using diffusion tensor imaging (DTI), and found that IQ score is positively correlated with fractional anisotropy (FA). Kim et al. [9] found that lower performance in verbal IQ score is correlated with the decrease of FA values. In another DTI-based study, Welcome et al. [10] discovered that the volume of WM fiber tracts is correlated with nonverbal IQ score. Inspired by these strong correlations between brain anatomy and IQ score, we propose, in this study, a novel framework to estimate IQ by using GM and WM features extracted from structural MRI. ...

Their results might give some indication as to which regions of the brain are responsible for most of the population variation in IQ. Below are the brain regions most commonly identified as "features" by sparse learning methods.

From the comments (55% of variance means a correlation just larger than 0.7):

There are lots of recent studies that have tried to estimate IQ from MRI or EEG readings (sometimes called "neurometric" IQ); many of the teams are based in South Korea and Malaysia. The Malaysian group, based at the MARA University of Technology, has published about a dozen papers over the past two years, involving hundreds of subjects. They can now use EEG readings to sort subjects into one of seven IQ ranges (e.g. 90-100, 120-130) with 83% accuracy; this figure jumps to 98% when subjects are sorted into one of three IQ ranges (low, medium, or high). The South Korean researchers, at Seoul National University, have been combining MRI and fMRI scans to predict IQ scores, and in late 2012 they were granted a patent for their "neurobiological method for measuring human intelligence," which can explain up to 55% of the variance between individual IQ scores. An example (from Dec 2013) is at http://ieeexplore.ieee.org/...

Additional links:
http://dx.doi.org/10.1016/j.cmpb.2014.01.016
http://www.google.com/patents/WO2008018763A1?cl=en

For this you went to Harvard?

Personal assistants of the world, unite!

Better to reign in Hell, than serve in Heaven  ;-)

Dissent Magazine: ... When I was an undergrad at Harvard, the English department produced fancy brochures about the opportunities available to its majors: teacher, editor, Rhodes scholar. Personal assistant was not listed. I hadn’t even heard of such positions until senior year, when older friends, artistically inclined friends, started snagging them. It’s the position I think I’ve heard most about now.

Nearly every exclusive field runs on assistants. The actor James Franco, like Buddha before him, had an assistant keep track of his meals and school assignments. The critic and writer Daphne Merkin has employed a steady stream of Ivy-educated elves. They’re tasked with everything from editing to returning dead houseplants. Bestselling novelist John Irving (The Cider House Rules, A Prayer for Owen Meany) has an assistant who types up his roughly twenty-five pages of handwritten manuscript a day. He recruits exclusively from liberal arts schools in cold climates like Middlebury and Vassar, to ensure his hires can survive the winter at his home in Dorset, Vermont. During the 2008 presidential season, recent Harvard grad Eric Lesser impressed senior advisor to the president, David Axelrod, with his color-coded system for tracking Obama’s campaign luggage. Lesser was taken on as Axelrod’s “special assistant,” assuming responsibility for everything from supervising his boss’s diet to organizing the first-ever presidential Seder.

Welcome to the main artery into creative or elite work—highly pressurized, poorly recompensed, sometimes exhilarating, sometimes menial secretarial assistance. From the confluence of two grand movements in American history—the continued flight of women out of the home and into the workplace, and the growing population of arts and politically oriented college graduates struggling to survive in urban epicenters that are increasingly ceded to bankers and consultants—the personal assistant is born. ...

... One of the most exceptional—and mysterious—personal assistantship programs is run by a hedge fund billionaire in New York. For years, his human resources staff used to tuck the same discreet, neatly boxed advertisement in alongside the dense criticism of the New Republic and the New York Review of Books, as well as in Ivy League alumni magazines:

RESEARCH ASSOCIATE/PERSONAL ASSISTANT New York City—Highly intelligent, resourceful individuals with exceptional communication skills sought to undertake research projects and administrative tasks for one of Wall Street’s most successful entrepreneurs. We welcome applications from writers, musicians, artists, or others who may be pursuing other professional goals in the balance of their time. $90-110k/yr to start (depending on qualifications). Resume to: gen8R@spsfind.com

The firm recruits and interviews year-round, whether there are openings or not. In addition to ads, the billionaire’s people email Phi Beta Kappa and summa students from top colleges about openings at the firm, though they are also likely scouting for assistants. “Although much of our work involves the use of advanced mathematical and computational techniques,” the email reads, “we are equally interested in speaking with brilliant liberal arts graduates, regardless of major, who are open to the possibility of a career they may never have previously considered.” It might be the only time in their lives that art students or English majors are courted by a potential employer. “The firm,” the email continues, “ . . . can give serious consideration only to individuals having extraordinary intellectual capabilities, communication skills, and general ‘real world’ competence.” Of the many who apply, a handful are called to New York, where their “real world competence” is quantified in no fewer than five management consulting-style interviews. Interviewees sign non-disclosure forms, and if hired as personal assistants, are essentially barred from saying where they work. When pressed, they might say they are writing books or “making music.” ...

Multigenerational mobility: does the Son Also Rise?

The working paper below on multigenerational mobility arrives at smaller intergenerational correlations than Greg Clark obtained (e.g., 0.4 vs 0.7). I found Clark's results hard to explain, at least in genetic terms, because estimates of assortativity in mating are much lower than required.

Related posts here and here. From the second link:

Correlations as high as 0.7 -- 0.8 are implausible from genetic factors alone without highly assortative mating. Traits such as height and IQ have narrow sense heritabilities as large as h2 ~ 0.6, so fraction of variance accounted for is ~ 60%, and midparent-child correlation as high as ~ 0.8, but under even somewhat random mating the parental midpoint is significantly closer to average than the phenotype of the more exceptional parent. This would cause children to regress to the mean much faster in height and IQ than in social status as indicated in Clark's data. It's also important to note that social status itself is only imperfectly correlated to observable phenotypes such as IQ, Conscientiousness or Extraversion. See Intergenerational mobility: Bowles, Gintis, Clark for more.

Solon's results seem to be consistent with Bowles and Gintis.

What Do We Know So Far about Multigenerational Mobility?

Gary Solon
Michigan State University

Abstract
“Multigenerational mobility” refers to the associations in socioeconomic status across three or more generations. This article begins by summarizing the longstanding but recently growing empirical literature on multigenerational mobility. It then discusses multiple theoretical interpretations of the empirical patterns, including the one recently proposed in Gregory Clark’s book The Son Also Rises.


... contrary to Clark’s prediction, most group-average studies other than his own – including the surnames-based work by Chetty et al. – have estimated much smaller intergenerational associations.

Clark was recently interviewed on KQED Forum. Michael Krasny was willing to entertain Clark's Social Darwinistic perspective ;-)

Income, wealth, and IQ

I'm occasionally asked about financial returns to cognitive ability. As a rough rule of thumb, judging from the graphs below (obtained here), I would say:

On average, an increase of IQ by one SD corresponds to  ~ $30k per annum of additional income. (Somewhat less than 1 SD in income; the distribution is far from normal.)

By early middle age, individuals > 90th percentile in IQ have, typically, more than twice the wealth of individuals who are of average IQ.

If you can find better data than what is shown below, please let me know. (How do bottom decile adults manage to earn ~ $40k per annum, on average? Does this include transfer payments?)

Of course, you can turn this around to estimate the increased (heritable) cognitive ability endowments of high income parents relative to average parents. That might help to clarify causality in results such as this one: "Studies show that children from low-income families have smaller brains and lower cognitive abilities." (Even Nature susceptible to faulty logic.)

Note, there is good evidence that positive returns to IQ persist above high thresholds (e.g., IQ=120, or even top 1 percent ability). See here and here.

Income mobility is strongly affected by IQ. In fact, IQ is a much stronger predictor variable than race for escaping the bottom quintile of income (Pew Trust report; NLSY again, AFQT=IQ scores):

This last figure is very problematic for the "Social Status/Wealth causes IQ" position. It seems to be the other way around: the kids escaping bottom quintile childhoods all experienced poverty, but the ones with higher cognitive ability were more likely to move up. (Recall that adopted children tend to resemble their biological parents much more than their adoptive ones; family environment has a limited effect on IQ, which is highly heritable.)

Pew: Individuals with higher test scores in adolescence are more likely to move out of the bottom quintile, and test scores can explain virtually the entire black-white mobility gap. Figure 13 plots the transition rates against percentiles of the AFQT test score distribution. The upward-sloping lines indicate that, as might be expected, individuals with higher test scores are much more likely to leave the bottom income quintile. For example, for whites, moving from the first percentile of the AFQT distribution to the median roughly doubles the likelihood from 42 percent to 81 percent. The comparable increase for blacks is even more dramatic, rising from 33 percent to 78 percent. Perhaps the most stunning finding is that once one accounts for the AFQT score, the entire racial gap in mobility is eliminated for a broad portion of the distribution. At the very bottom and in the top half of the distribution a small gap remains, but it is not statistically significant.

Gene drive

IIUC, there is a self-referential ("auto-catalyzing") aspect to this method which is very interesting. The Cas9 gene (payload) also encodes the guide RNA (target) information, which determines the location of the DNA cut.

Needless to say, this is a very powerful and potentially dangerous technology.

Enrico Fermi (speaking about atomic weapons): Once basic knowledge is acquired, any attempt at preventing its fruition would be as futile as hoping to stop the earth from revolving around the sun.

Biologists devise invasion plan for mutations (Science): On 28 December 2014, Valentino Gantz and Ethan Bier checked on the fruit flies that had just hatched in their lab at the University of California (UC), San Diego. By the classic rules of Mendelian genetics, only one out of four of the newborn flies should have shown the effects of the mutation their mothers carried, an X-linked recessive trait that causes a loss of pigmentation similar to albinism. Instead, nothing but pale yellow flies kept emerging. “We were stunned,” says Bier, who is Gantz's Ph.D. adviser. “It was like the sun rose in the west rather than the east.” They hammered out a paper and submitted it to Science 3 days later. [ Bier and Gantz Science paper ]

... George Church, a geneticist at Harvard Medical School in Boston who is a leader in the field, believes the new study should not have been published, because it does not include measures to restrain the spread of unintended mutations. “It is a step too far,” he says. ...

... Creating a gene drive system wasn't Gantz's original goal, Bier says. “We were just trying to solve a practical problem.” Gantz studies the development of fruit fly wing veins, for which he must create flies with multiple mutations. That's typically painstaking work, requiring large numbers of flies over many generations to create a single multimutant. Last summer, Gantz made a tweak to the CRISPR system, in which an engineered bacterial protein, Cas9, uses a string of RNA to find and delete, replace, or otherwise edit a target DNA sequence. By equipping the CRISPR gene cassette with DNA sequences flanking the targeted gene, Gantz hoped to create a mutation that would “auto-catalyze.” Once incorporated on one chromosome, it would produce new copies of the CRISPR complex that would target and edit the gene everywhere it appeared. ...

Similar demonstration in yeast by the Church lab:

... Because synthetic gene drives would alter the global environmental commons, the decision to deploy such a drive must be made collectively by society. ... Fortunately, a simple and costless precaution is both available and already utilized for different reasons by many laboratories: avoid delivering the Cas9 gene on a DNA cassette that also encodes a guide RNA. ...

See also Regulating Gene Drives (Science). More on how to avoid making a gene drive: http://biorxiv.org/content/early/2015/04/01/017384.


The following paper from Harvard's Wyss Institute (which also produced the video below) provides a nice overview of CRISPR gene drives. The paper appeared last summer.

Emerging technology: Concerning RNA-guided gene drives for the alteration of wild populations

Abstract: Gene drives may be capable of addressing ecological problems by altering entire populations of wild organisms, but their use has remained largely theoretical due to technical constraints. Here we consider the potential for RNA-guided gene drives based on the CRISPR nuclease Cas9 to serve as a general method for spreading altered traits through wild populations over many generations. We detail likely capabilities, discuss limitations, and provide novel precautionary strategies to control the spread of gene drives and reverse genomic changes. The ability to edit populations of sexual species would offer substantial benefits to humanity and the environment. For example, RNA-guided gene drives could potentially prevent the spread of disease, support agriculture by reversing pesticide and herbicide resistance in insects and weeds, and control damaging invasive species. However, the possibility of unwanted ecological effects and near-certainty of spread across political borders demand careful assessment of each potential application. We call for thoughtful, inclusive, and well-informed public discussions to explore the responsible use of this currently theoretical technology.


... We submit that Cas9 is highly likely to enable scientists to construct efficient RNA-guided gene drives not only in mosquitoes, but in many other species. In addition to altering populations of insects to prevent them from spreading disease (Curtis, 1968), this advance would represent an entirely new approach to ecological engineering with many potential applications relevant to human health, agriculture, biodiversity, and ecological science. ...