Thursday, December 27, 2018

Genomic Prediction of Complex Disease Risk (bioRxiv)

Our new paper describes over a dozen genomic predictors for common disease risk, constructed via machine learning on hundreds of thousands of genotypes. The predictors use anywhere from a few tens (e.g., 20 or 50) to thousands of SNPs to compute the risk PGS (Poly-Genic Score) for a specific disease.

The figure above (Atrial Fibrillation) shows out-of-sample testing of risk prediction (black dots with error bars) compared to theoretical prediction (red line). The theoretical prediction uses the empirical fact that cases and controls are normally-distributed in PGS score, with the two distributions shifted relative to each other. Cases have, on average, higher risk scores, and come to dominate in high PGS percentile bins. So, conditional on a high PGS risk score (e.g., 99th percentile PGS), the probability of the condition can be significantly elevated (e.g., ~8 times typical probability of developing atrial fibrillation).

We can identify, from SNP genotype alone, a subset of the population with unusual risk for conditions like Atrial Fibrillation or Diabetes or Breast Cancer or Prostate Cancer.

Just a year or two ago this would have seemed like science fiction to biomedical researchers...

Empirical validation of risk is limited by availability of out-of-sample populations for whom we have genotype and disease status. However, it is clear from the results that the theoretical models do a good job of predicting odds ratios once the properties of the case and control normal distributions (mean and standard deviation of PGS) are known.

These predictors only require data from an inexpensive ~$50 SNP array. Once the ~1 million SNPs on the array are measured *all* of the disease risks can be computed for an individual patient. It is only a matter of time before genotyping of this kind becomes Standard of Care in health systems around the world.

In the paper we also analyze the rate of improvement of prediction AUC as training sample size increases. With more data these predictors will become significantly more accurate -- the relevant timescale is just a few years!

Genomic Prediction of Complex Disease Risk

Louis Lello, Timothy Raben, Soke Yuen Yong, Laurent CAM Tellier, Stephen D. H. Hsu

We construct risk predictors using polygenic scores (PGS) computed from common Single Nucleotide Polymorphisms (SNPs) for a number of complex disease conditions, using L1-penalized regression (also known as LASSO) on case-control data from UK Biobank. Among the disease conditions studied are Hypothyroidism, (Resistive) Hypertension, Type 1 and 2 Diabetes, Breast Cancer, Prostate Cancer, Testicular Cancer, Gallstones, Glaucoma, Gout, Atrial Fibrillation, High Cholesterol, Asthma, Basal Cell Carcinoma, Malignant Melanoma, and Heart Attack. We obtain values for the area under the receiver operating characteristic curves (AUC) in the range  0.58 - 0.71 using SNP data alone. Substantially higher predictor AUCs are obtained when incorporating additional variables such as age and sex. Some SNP predictors alone are sufficient to identify outliers (e.g., in the 99th percentile of PGS) with 3-8 times higher risk than typical individuals. We validate predictors out-of-sample using the eMERGE dataset, and also with different ancestry subgroups within the UK Biobank population. Our results indicate that substantial improvements in predictive power are attainable using training sets with larger case populations. We anticipate rapid improvement in genomic prediction as more case-control data become available for analysis.

Wednesday, December 26, 2018

Ghosts and Hybrids: Ancient DNA and Human Origins

Take a break from your holiday Netflix binge and learn something about recent breakthroughs in our understanding of human evolution from ancient DNA.

John Hawks (UW Madison) is an excellent speaker and this talk is for non-experts. Get the whole family together to watch -- it's a treat to learn from one of the leading researchers!

For more video of lectures at MSU, by our faculty and visitors, see this YouTube channel:

Dr. John Hawks delivers a lecture on Ancient DNA & Human Origins at Michigan State University on October 4, 2018.

The rapidly changing field of ancient DNA has settled into a kind of normal science, as several teams of researchers have coalesced around a set of approaches to discover the genetic relationships among ancient peoples.

Hawks is the Vilas-Borghesi Distinguished Achievement Professor of Anthropology at the University of Wisconsin - Madison. He is an anthropologist and studies the bones and genes of ancient humans. He's worked on almost every part of our evolutionary story, from the very origin of our lineage among the apes up to the last 10,000 years of our history.

Tuesday, December 25, 2018

Peace on Earth, Good Will to Men 2018

For years, when asked what I wanted for Christmas, I've been replying: Peace On Earth, Good Will To All Men :-)

No one ever seems to recognize that this comes from the bible, Luke 2.14 to be precise!

Linus said it best in A Charlie Brown Christmas:
And there were in the same country shepherds abiding in the field, keeping watch over their flock by night.

And, lo, the angel of the Lord came upon them, and the glory of the Lord shone round about them: and they were sore afraid.

And the angel said unto them, Fear not: for, behold, I bring you good tidings of great joy, which shall be to all people.

For unto you is born this day in the city of David a Saviour, which is Christ the Lord.

And this shall be a sign unto you; Ye shall find the babe wrapped in swaddling clothes, lying in a manger.

And suddenly there was with the angel a multitude of the heavenly host praising God, and saying,

Glory to God in the highest, and on earth peace, good will toward men.

Merry Christmas!

Three years ago today I shared the following story on this blog: Nativity 2050

For an update, see

The Future of IVF and Gene-Editing (Psychology Today interview)

Validation of simultaneous preimplantation genetic testing (PGT) for aneuploidy, monogenic, and polygenic disorders

The Future is Here: Genomic Prediction in MIT Technology Review

And the angel said unto them, Fear not: for, behold, I bring you good tidings of great joy, which shall be to all people.
Mary was born in the twenties, when the tests were new and still primitive. Her mother had frozen a dozen eggs, from which came Mary and her sister Elizabeth. Mary had her father's long frame, brown eyes, and friendly demeanor. She was clever, but Elizabeth was the really brainy one. Both were healthy and strong and free from inherited disease. All this her parents knew from the tests -- performed on DNA taken from a few cells of each embryo. The reports came via email, from GP Inc., by way of the fertility doctor. Dad used to joke that Mary and Elizabeth were the pick of the litter, but never mentioned what happened to the other fertilized eggs.

Now Mary and Joe were ready for their first child. The choices were dizzying. Fortunately, Elizabeth had been through the same process just the year before, and referred them to her genetic engineer, a friend from Harvard. Joe was a bit reluctant about bleeding edge edits, but Mary had a feeling the GP engineer was right -- their son had the potential to be truly special, with just the right tweaks ...
See also [1], [2], and [3].

Wednesday, December 19, 2018

IceCube: neutrino astronomy in Antarctica

Tyce DeYoung (MSU Department of Physics and Astronomy) colloquium on high-energy astrophysics and exploration of the high-energy universe with the IceCube neutrino detector at the South Pole. Several MSU professors are part of the IceCube collaboration.

I predict very exciting developments in neutrino astronomy in the coming decade ;-)

The situation is similar to that for LIGO a few years ago. Events of significant scientific interest have already been seen with the detector at small (here small means instrumenting a cubic kilometer of ice!) fiducial volume. At a higher volume (10x or more scale up in IceCube anticipated upgrade), we therefore expect a robust new kind of astronomy to emerge, using a never before available probe of the universe -- for IceCube, high energy neutrinos, for LIGO, gravity waves. In both cases new insights into astrophysical black holes (and perhaps other very exotic objects) are likely to emerge.

Note the scale of the experiment in the image below -- in units of Eiffel Towers :-)

Tuesday, December 18, 2018

A Realist Appraisal of US Foreign Policy

An evenhanded realist appraisal of US foreign policy going back to the end of the Cold War.

Topics addressed: Should we have extended NATO to the east of Germany, despite promises made to Gorbachev by GHWB? Should we have supported PRC WTO accession? Should we have invaded Iraq after 9/11? Hasn't Obama openly admitted that what we did in Libya and Syria (thanks, Hillary!) recently was a tragic disaster? Trump's trade war, Populism and Democracy, Why are our foreign policy elites so stupid -- is there no penalty for being wrong again and again? (He doesn't really answer the last question -- it's mine.)
Wikipedia: Stephen Martin Walt (born July 2, 1955) is an American professor of international affairs at Harvard University's John F. Kennedy School of Government. He belongs to the realist school of international relations.

Walt was born in Los Alamos, New Mexico, where his father, a physicist, worked at Los Alamos National Laboratory. ... Walt pursued his undergraduate studies at Stanford University.  ... After attaining his B.A., Walt began graduate work at UC Berkeley, graduating with a M.A. in Political Science in 1978, and a Ph.D. in Political Science in 1983.
Walt and University of Chicago political scientist Stephen Mearsheimer endured significant blowback for their too-realistic 2007 book The Israel Lobby and U.S. Foreign Policy.

Monday, December 17, 2018

Advances in Genomic Prediction: Breast Cancer Risk

This is a new paper on polygenic prediction for breast cancer by a large collaboration that has been working for many years on GWAS and, more recently, genomic risk prediction.

"The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%" !
Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes

Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57–1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628–0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.
Note 10-25x (ER-positive and -negative) range of risk between lowest and highest percentile PRS score.

One of the senior authors (Paul Pharoah of Cambridge) details the history of his work on genetics of breast cancer in a tweet thread. He describes historical progress from simple GWAS associations to full-blown genomic prediction:
1/n This paper has been many years in the making both conceptually and in terms of the time to generate the data. It has been part of almost all my scientific life (or at least since I started my PhD).


11/n This PRS is now being used in an EU funded trial of risk stratified screening. It is the culmination of many years of many people working together on samples donated by hundreds of thousands of patients.
My small team of physicists has constructed a breast cancer predictor of similar power using UKBB data and our own automated ML pipeline :-)

See earlier post Advances in Genomic Prediction.

Friday, December 14, 2018

The Future of the U.S. Aircraft Carrier: Fearsome Warship or Expensive Target? (Heritage Panel; video)

This is a Heritage Foundation panel on the future of the aircraft carrier. The discussion addresses, in part, the possibility that in a peer-competitor conflict aircraft carriers will have to operate 1000 miles offshore (range of the PRC DF21 anti-ship ballistic missile; the DF26 may have twice the reach), requiring a new class of (perhaps unmanned) aircraft with greater range than, e.g., the F35 fighter. The focus on ASBM like the DF21 might have been too narrow, as both PRC and Russia have equally dangerous ASCM (anti-ship cruise missle) capability.

The basic problem is that aircraft carriers are easy to detect (e.g., satellite imaging via optical or radar sensors) and missiles (especially those with maneuver capability) are very difficult to stop. Advances in AI / machine learning tend to favor missile targeting, not defense of carriers.

For previous discussion of these issues, see these posts.
The Future of the U.S. Aircraft Carrier: Fearsome Warship or Expensive Target?

Over 70 years ago, U.S. Navy aircraft carriers supplanted battleships as preeminent warship with their ability to strike enemy warships or land targets hundreds of miles away. Since World War II, U.S. aircraft carriers and the carrier air wing have operated relatively unthreatened, providing unrivaled air support and power projection capability in every U.S. conflict. Recently, an increasing number of critics are predicting the end of the aircraft carrier era. They cite the growing threats from anti-ship missiles, such as China’s DF-21D “carrier killer”; the proliferation of increasingly quieter attack submarines; and advanced integrated air and missile defense capabilities. They also argue that current carrier strike fighter aircraft and their weapons lack sufficient range to engage targets in a denied/degraded environment. Aircraft carrier proponents argue that a modern U.S. supercarrier uniquely provides a globally deployable U.S. airfield that can rapidly respond to emergent crises and does not depend the approval of any host nation. While they acknowledge the increased threats to the carrier strike group and its air wing, they argue that introduction of the fifth generation F-35, long-range unmanned carrier-based tankers, advanced weapons and electronic warfare systems, and the employment of new operational tactics will enable the aircraft carrier to remain relevant for the foreseeable future. Can the new USS FORD-class aircraft carrier and a modernized carrier air wing provide effective sea-based power projection against near-peer competitors like Russia and China, should the U.S. Navy develop smaller aircraft carriers with new weapons systems and carrier aircraft to meet these 21st Century threats, or should the U.S. move on from the aircraft carrier?

Monday, December 10, 2018

Music and Mathematics: Noam Elkies

Dinner with two old Harvard friends -- mathematician Noam Elkies and MSU physicist Dean Lee. Noam is in town this week to give a lecture, a colloquium, and perform a piano recital.

At 26 Noam became the youngest full professor in Harvard history, and the youngest to ever receive tenure. He has an amazing Wikipedia entry :-)
In 1981, at age 14, he was awarded a gold medal at the 22nd International Mathematical Olympiad, receiving a perfect score of 42 and becoming one of just 26 participants to attain this score,[3] and one of the youngest ever to do so. Elkies graduated from Stuyvesant High School in 1982[4][5] and went on to Columbia University, where he won the Putnam competition at the age of sixteen years and four months, making him one of the youngest Putnam Fellows in history.[6] He was a Putnam Fellow two more times during his undergraduate years. After graduating as valedictorian at age 18 with a summa cum laude in Mathematics and Music, he earned his Ph.D. at the age 20 under the supervision of Benedict Gross and Barry Mazur at Harvard University.[7]

From 1987 to 1990 he was a junior fellow of the Harvard Society of Fellows.[8]

In 1987, he proved that an elliptic curve over the rational numbers is supersingular at infinitely many primes. In 1988, he found a counterexample to Euler's sum of powers conjecture for fourth powers.[9] His work on these and other problems won him recognition and a position as an associate professor at Harvard in 1990.[4] In 1993, he was made a full, tenured professor at the age of 26. This made him the youngest full professor in the history of Harvard.[10] Along with A. O. L. Atkin he extended Schoof's algorithm to create the Schoof–Elkies–Atkin algorithm.
Noam, Dean, and I are all veterans of the Malkin Athletic Center weight room, when it was old-school and gritty :-)

Here's an earlier version of the talk Noam gave tonight. Video should start with him constructing a canon from thin air!

Sunday, December 09, 2018

Paris 2018: Global Capital and Its Discontents

Is she shooting video of the riot outside, or is she video chatting with a friend, oblivious? Did she just have the Royale with Cheese? :-)

My suggested title is Global Capital and Its Discontents.

Amazing work by this photographer.

Paris in happier times.
“If you are lucky enough to have lived in Paris as a young man, then wherever you go for the rest of your life, it stays with you, for Paris is a moveable feast.” ― Ernest Hemingway, A Moveable Feast

A meal by the Seine.

Les Deux Magots.

Le Louvre.

View from Sacre Coeur.

Friday, December 07, 2018

Crude Awakening: The Yuan, the Dollar, and the Battle for Global Supremacy

Yuan-Dollar-Oil discussion starts about 20min in. Any professionals want to weigh in?

In the past the main drivers of oil prices were supply-demand and dollar confidence (all transactions in dollars). Now you can add dollar-yuan fx factors... even gold.

Have idiots screaming about Khashoggi thought about what happens if Saudi starts accepting Yuan for oil, as Russia, Iran, and Venezuela do now?

See also On the military balance of power in the Western Pacific.

Wednesday, December 05, 2018

The Quantum Theory of Fields

Excerpt from Sidney Coleman's Erice lectures. The period he describes just predates my entry into physics.
This was a great time to be a high-energy theorist, the period of the famous triumph of quantum field theory. And what a triumph it was, in the old sense of the word: a glorious victory parade, full of wonderful things brought back from far places to make the spectator gasp with awe and laugh with joy. I hope some of that awe and joy has been captured here.
Physics students learn quantum mechanics and special relativity as undergraduates, but typically do not encounter a synthesis of the two until graduate school, in a course on quantum field theory. Undergraduate quantum mechanics focuses on non-relativistic particles, moving at much less than the speed of light (e.g., the electrons in atomic systems or ordinary matter). Special relativity, as first encountered by students, is a modification of Newtonian (classical) mechanics, and ignores quantum effects.

In quantum field theory (QFT), the wave function of quantum mechanics Ψ(x) becomes a wave functional Ψ[ Φ(x) ], valued over field configurations Φ(x) which are themselves functions of spacetime coordinates. Individual particles are excitations ("quanta") of quantum fields. I think it is fair to say that almost no student really gets a deep understanding of quantum field theory when they take it for the first time. It is simply too complex to digest quickly. QFT introduces new intuitive pictures, novel calculational tricks, strange physical and mathematical constructs.

And how could it be otherwise? All of these tools are necessary to make sense of the generalization of ordinary quantum mechanics (of a finite number of degrees of freedom) to a physical system with an infinite number of degrees of freedom.

I first took quantum field theory (Physics 205) in my last year at Caltech, taught by Fredrik Zachariasen. Zachariasen used Bjorken and Drell I and II and Ramond as the main textbooks. He was what Russian theorists sometimes refer to as a "strong calculator" -- he would fill the blackboard with equations as fast as we could note them down. However, I would say his approach to the subject was rather old-fashioned by that time, and while I learned a good bit about the Dirac equation, spinors, how to compute Feynman diagrams, and even about path integrals, my overall understanding of the subject was still lacking. If I had been there the following year I would have enjoyed John Preskill's version of 205 (see below), but alas I was already in graduate school by then.

I remember that I also studied Feynman's short volume (in the Frontiers in Physics series; not to be confused with his later popular book) Quantum Electrodynamics. I was very confused at the time about the relationship between particles and fields and about so-called Second Quantization.  Also, what happened to the Schrodinger equation? At no point did Zachariasen (nor, I think, do Bjorken and Drell) clarify that while Dirac deduced his equation via relativistic generalization of Schrodinger's, the two are not on the same logical footing.

It was only some years later that I realized that Feynman himself had been confused about these things when he wrote his early papers on the subject. (Feynman, when someone explained a creation operator and Fock space to him: "How can you create an electron? It disagrees with conservation of charge!") Do Feynman diagrams describe spacetime trajectories of particles? Or are they simply graphical representations of terms in a perturbative expansion that happen to correspond, intuitively but not exactly, to physical processes?

As a first year graduate student at Berkeley I took Physics 230 from Stanley Mandelstam, a true master of the subject. This course was far more theoretical than the one I had taken the previous year. Amazingly, Stanley taught without notes. The only day he brought a single page of paper to class was when he covered the BPHZ proof of renormalizability. (Or was it the day he derived the beta function for non-Abelian gauge theories? I might be conflating two different instances.) His lectures followed no specific textbook, although the recommended one was probably Itzykson and Zuber.

My final student encounter with a QFT course was as the grader for Physics 230, taught by Martin Halpern. (I am sad to discover, in finding this link, that Marty passed away earlier this year.) Marty was a high strung chain smoker, and I recall many hours in his office going over solutions to his homework problems. He was especially on edge that fall because Vaughan Jones from the math department (who was about to share the Fields Medal with Ed Witten!) had decided to learn QFT and was sitting in on the class. As might be expected, the mathematician's insistence on clarity and precision slowed Marty down significantly. This wasn't Marty's fault -- QFT has not, even today, been placed on a completely rigorous footing (at least, not to the satisfaction of mathematicians), even though it is (in the form of Quantum Electrodynamics and the Standard Model) the most precisely tested theoretical construct in science.

This post is long enough. Perhaps I will revisit the topic in the future with a discussion of Sidney Coleman's lectures on QFT at Harvard, where I went after graduate school. It's nice to see that these lectures have been rendered into a book by his former students. For many years one could check out videotapes (Sony Betamax!) of his lectures from the physics library at Harvard. This made me think, even then, that the future of many professors might someday be as glorified teaching assistants, helping to explain and clarify recorded or streamed lectures by the true masters.

If I have kindled your interest in the subject, I recommend my friend Tony Zee's book: Quantum Field Theory in a Nutshell. Also, John Preskill's fantastic lecture notes, covering basic as well as advanced topics. It took me some time to learn to decipher his handwriting, but it was worth it!

Let me end by noting that the physics students who took these classes with me are quite a remarkable group. Among them are a number of well-known theoretical physicists, as well as the odd startup founder, AI researcher, or hedge fund billionaire. You could do worse in this life than get to know some students of quantum field theory :-)

Trading Blows: The US-China Trade War (Yukon Huang)

Watch this at 1.5x speed so that the next time you discuss US-China competitive issues you won't say things that are factually incorrect. (Not that I agree with everything Huang says but overall content is good...)
Yukon Huang is a senior fellow with the Asia Program. He was formerly the World Bank’s country director for China and earlier director for Russia and the Former Soviet Union Republics. He is an adviser to the World Bank, Asian Development Bank, Asian Infrastructure Investment Bank, and various governments and corporations. His research focuses on China’s economy and its regional and global impact.

Huang has published widely on development issues in both professional journals and the public media. He is a featured commentator for the Financial Times on China, and his articles are seen frequently in the Wall Street Journal, Bloomberg, Foreign Affairs, the National Interest, and Caixin. His books include East Asia Visions, Reshaping Economic Geography in East Asia, and International Migration and Development in East Asia and the Pacific. His latest book, Cracking the China Conundrum: Why Conventional Economic Wisdom Is Wrong, was published by Oxford University Press (2017).

He has a PhD in economics from Princeton University and a BA from Yale University.

Monday, December 03, 2018

The Future of IVF and Gene-Editing (Psychology Today interview)

The excerpt below is from an interview with Psychology Today.
The Future of In-Vitro Fertilization and Gene Editing (Psychology Today)

"The Eminents" interview with Stephen Hsu.

MN: Would you explain polygenic complex traits embryo selection in more detail?

SH: Most human traits (e.g., height or cognitive ability) and most disease risks (e.g., for diabetes or heart disease) are polygenic -- they depend on many different genetic loci. For the first time, thanks to very large datasets and advances in AI / machine learning, we have genomic predictors for these traits. Our height predictor is accurate to a few cm! Individuals who are outliers for risk -- for example, have 5 or 10 times greater probability of heart disease than the typical person -- can now be identified using inexpensive genotyping.

Many although not all parents using IVF are confronted by an “embryo choice” problem: They have more viable embryos than they intend to use. For these parents, it is useful to have additional information about each embryo, such as whether it is at high risk for certain health conditions. Each year, a million embryos are genetically screened worldwide. Most of the time, this is just a screen for chromosomal normality (e.g., against Down’s Syndrome), but with better technology, we can screen against many mutations and complex disease risks.

MN: What ethical safeguards need to be in place before this kind of technology is put to use?

SH: The birth of the gene-edited baby girls has brought this issue to the forefront. While bioethicists and researchers have already thought through many of the ethical questions (the obvious criteria are safety, effectiveness, and benefit to the child, as well as implementation that would ensure net benefit to society, for example, the procedure’s cost being covered by health insurance provided to the poor), the average person has not. It seems important that there be a high level of public understanding of and consensus about these new technologies before widespread use.

However, It is probably too much to ask that each country come to the same conclusions as to what is permissible or best. Hence I think we will see a patchwork of legal and regulatory practices.

MN: Since this is Psychology Today I want to ask about cognitive ability and personality traits. Can we predict these from genotype? How will this be used in IVF?

SH: From genotype, we can predict cognitive ability (i.e., IQ) with correlation r ~ 0.3 to 0.4, which is as well as standardized tests like SAT or ACT predict college performance. This is nowhere near the accuracy of, for example, height prediction. However, despite the SAT's only moderate accuracy, it is easy to understand why colleges are reluctant to admit students with low (say, bottom 10%) scores, and generally very enthusiastic about students with high scores. It’s similar with the current genomic predictors. We can identify embryos that have unusually high risk of intellectual disability but we can’t reliably rank-order embryos that are in the normal range.

At the moment, the situation is even worse for predicting Big-5 personality traits, such as conscientiousness or extraversion, even though we know those traits are fairly heritable. I expect the situation for all psychological traits to improve drastically in the near future as more data become available.

At present, we can apply genomic prediction to cognitive traits in the same way we apply it to disease risk -- to warn parents about embryos that are outliers in risk. In the future, we may be able to rank-order embryos, although this would raise further important ethical issues that need to be explored. By comparison, we’ve found in our testing that we correctly predict height ordering between two same-sex siblings 80 to 90 percent of the time. I don’t see any reason we won’t get to this point with IQ, but it may take some years.

MN: Tell me something about yourself that people might find surprising.

SH: I’m a huge fan of Mixed Martial Arts (MMA) and jiujitsu. I learned judo growing up, and got into Brazilian jiujitsu and MMA in the early 1990s when the UFC first started. I trained pretty seriously in the US and Japan, including with some professional fighters. Jiujitsu is like chess with the human body -- move and countermove, dominate position, then force a submission.

Perhaps the most beautiful thing about jiujitsu is that one can submit the opponent without either getting hurt. It would be great if intellectual / scientific disagreements worked the same way :-)

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