Sunday, May 29, 2022

Genomic Prediction in Bloomberg

A nice article in Bloomberg describing polygenic embryo selection in IVF: DNA Testing for Embryos Promises to Predict Genetic Diseases, by Carey Goldberg.
Bloomberg: Simone Collins knew she was pregnant the moment she answered the phone. ... Embryo 3, the fertilized egg that Collins and her husband, Malcolm, had picked, could soon be their daughter—a little girl with, according to their tests, an unusually good chance of avoiding heart disease, cancer, diabetes, and schizophrenia. 
This isn’t a story about Gattaca-style designer babies. No genes were edited in the creation of Collins’s embryo. The promise, from dozens of fertility clinics around the world, is just that the new DNA tests they’re using can assess, in unprecedented detail, whether one embryo is more likely than the next to develop a range of illnesses long thought to be beyond DNA-based predictions. It’s a new twist on the industry-standard testing known as preimplantation genetic testing, which for decades has checked embryos for rare diseases, such as cystic fibrosis, that are caused by a single gene. 
One challenge with leading killers like cancer and heart disease is that they’re usually polygenic: linked to many different genes with complex interactions. Patients such as Collins can now take tests that assess thousands of DNA data points to decode these complexities and compute the disease risks. Genomic Prediction, the five-year-old New Jersey company that handled the tests for her fertility clinic, generates polygenic risk scores, predicting in percentage terms each embryo’s chances of contracting each disease in the panel, plus a composite score for overall health. Parents with multiple embryos can then weigh the scores when deciding which one to implant. 
This new form of genetic embryo testing appears to move humanity one step closer to control of its evolution. The $14 billion IVF industry brings more than 500,000 babies into the world each year, and with infertility rates rising, the market is expected to more than double this decade. Companies including Genomic Prediction bet many going into that process have seen enough loved ones suffer from a polygenic disease to want risk scoring. 
[ Note I think the number of IVF babies born worldwide each year is more like 1 million, but there is some uncertainty in estimates. ] 
In December, Genomic Prediction doubled its venture funding to about $25 million and says it will use the cash to expand and add to its testing panel. Boston IVF, one of the biggest fertility networks in the US, recently started offering Genomic Prediction’s polygenic testing to its patients, says CEO David Stern. “Like anything else, you have early adopters,” he says. “We have had patients who worked in the biotech field or the Harvard milieu who came in and asked for it.” Stern predicts that, like egg freezing, polygenic embryo testing will grow slowly at first, but steadily, and eventually demand will reflect the powerful appeal of lowering a child’s odds for disease. 
Believers such as Collins and her husband support government subsidies for fertility and parenthood but aren’t interested in any conversation about slowing down. “This is about the people who care about giving their children every opportunity,” she says. “I do not believe that law or social norms are going to stop parents from giving their kids advantages.”

This article is well-written and informative. It covers polygenic screening from multiple perspectives: the parents who want a healthy child, the IVF doctors and genetic counselors who help the parents toward that goal, the scientists who study polygenic prediction and its ability to differentiate risk among siblings (i.e., embryos), the bioethicists who worry about a slippery slope to GATTACA.

An important point that is not discussed in the article (understandable, given the complexity of the topics listed above), is that precise genotyping of embryos leads to higher success rates in IVF.

... improved success rates resulting from higher accuracy in aneuploidy screening of embryos will affect millions of families around the world, and over 60% of all IVF families in the US.  
The SNP array platform allows very accurate genotyping of each embryo at ~1 million locations in the genome, and the subsequent bioinformatic analysis produces a much more accurate prediction of chromosomal normality than the older methods. 
Millions of embryos are screened each year using PGT-A, about 60% of all IVF embryos in the US. 
Klaus Wiemer is the laborator director for Poma Fertility near Seattle. He conducted this study independently, without informing Genomic Prediction. 
There are ~3000 embryos in the dataset, all biopsied at Poma and samples allocated to three testing labs A,B,C using the two different methods. The family demographics (e.g., maternal age) were similar in all three groups. Lab B is Genomic Prediction and A,C are two of the largest IVF testing labs in the world, using NGS. 
The results imply lower false-positive rates, lower false-negative rates, and higher accuracy overall from our methods. These lead to a significantly higher pregnancy success rate. 
The new technology has the potential to help millions of families all over the world.

This increase in pregnancy success rates was not something we directly aimed for -- rather, we were simply trying to get the most accurate characterization of chromosomal abnormality (aneuploidy) using the high precision genotype from our platform. After Dr. Wiemer surprised us with these results, it became plausible that significant increases in success rates per IVF cycle could still exist as low-hanging fruit. The ~3k embryos used in his study are considered a big sample size in fertility research, whereas in genomics today a big sample is hundreds of thousands or a million individuals. 

Prioritizing research in IVF using large sample sizes could plausibly raise success rates per cycle to, e.g., ~80%. The qualitative experience of parents using IVF will improve with average success rates, perhaps relieving much of the angst and uncertainty.

Thursday, May 19, 2022

Theodore A. Postol: Nuclear Weapons, Missile Technology, and U.S. Diplomacy — Manifold #12

Theodore A. Postol is professor emeritus of Science, Technology, and International Security at the Massachusetts Institute of Technology. He is widely known as an expert on nuclear weapons and missile technology. 

Educated in physics and nuclear engineering at MIT, he was a researcher at Argonne National Lab, worked at the Congressional Office of Technology Assessment, and was scientific advisor to the Chief of Naval Operations. 

After leaving the Pentagon, Postol helped to build a program at Stanford University to train mid-career scientists to study weapons technology in relation to defense and arms control policy. 

He has received numerous awards, including the Leo Szilard Prize from the American Physical Society for "incisive technical analysis of national security issues that [have] been vital for informing the public policy debate", the Norbert Wiener Award from Computer Professionals for Social Responsibility for "uncovering numerous and important false claims about missile defenses", and the Richard L. Garwin Award "that recognizes an individual who, through exceptional achievement in science and technology, has made an outstanding contribution toward the benefit of mankind." 

Steve and Ted discuss: 

0:00 Introduction 
2:02 Early life in Brooklyn, education at MIT, work at the Pentagon 
20:27 Reagan’s “Star Wars” defense plan 
28:26 U.S. influence on Russia and China’s second-strike capabilities 
54:41 Missile defense: vs nuclear weapons, scuds, anti-ship missiles (aircraft carriers), hypersonics 
1:11:42 Nuclear escalation and the status of mutually assured destruction 
1:32:24 Analysis of claims the Syrian government used chemical agents against their own people 
1:44:45 Media skepticism 


Theodore Postol at MIT 

A Flawed and Dangerous US Missile Defense Plan, G. Lewis and T. Postol, Arms Control Today 

Review Cites Flaws in US Antimissile Program, NY Times May 17 2010 

Improving US Ballistic Missile Defense Policy, G. Lewis and F. von Hippel, Arms Control Today, May 2018 

Whose Sarin? by Seymour Hersh (2013) 

Here is an excerpt from the transcript: 
Ted Postol: ... So, you've got to listen to Putin's voice dispassionately. And when you listen to him, he makes it clear numerous times, numerous times that he doesn't think American missile defense is a worth anything, but he also is worried about an American president who might believe otherwise, and who might take steps against Russia, that would then lead to an action-reaction cycle that would get us, get us all killed. 
In other words, he's not just worried about the system, whether it can work, he's worried about American political leadership and what they think, or if they think, or if they know. And that was, you know, I was very receptive to understanding that because that's exactly what I went through, you know, 30 years earlier when I was at the Pentagon, looking at this dog of a missile defense. 
And so, the Chinese look at this, they know the Americans are lying to them all the time. I could give you a good story about South Korea and the way we lied to the South Koreans and lied to the Chinese. 
I was really furious with that. That was under Secretary of State Hillary Clinton. And my view is... 
Steve: THAAD? 
Ted Postol: THAAD, right. THAAD in South Korea
And my view is if you're lying to an ally and you're lying, you know, I have very good friends. I'm very, very proud to say I have some very good friends who are high-level diplomats, and I've asked every one of them, would you lie in a negotiation? And every one of them has said, no. In other words, your credibility depends on your honesty. You might not say something that, you know, could be relevant to a negotiation relevant to your adversary's thinking, but you would never lie because your credibility will, you'll never be believed again. That's their view of this. 
And here we were under Hillary Clinton lying to an ally and lying to the Chinese, who I knew through my personal contacts, understood that we were lying to them. I know from personal contacts with the Chinese.  
So, how do you expect people to treat you when they know you're a liar? To me, it's just simple human relations. And, and I now understand that because I have friends who are both diplomats and soldiers, and I know, if you have to lie to make a point there's something wrong and you're, you're jeopardizing your credibility with other professionals if, if you do that. 
So, we should not be surprised that the Chinese are increasing their forces. 
And when Putin marched out this horrifying Poseidon underwater torpedo, could potentially carry a hundred megaton warhead. It's nuclear-powered. It can travel at some very high speed, 50, 60 knots or more, and then it can go quiet, sneak into a Harbor, know coastal Harbor and detonate underwater, and destroy out to 30 or 40 kilometers, a complete area, urban area. And he has this weapon. He made it obvious that he had it. He showed plans for it. 
Ted Postol: Well, what he was doing is he was saying to an American president who knows nothing. All right, assuming that the president knows nothing, that your missile defenses will not do anything about this weapon. That's what he did it for. He was an insurance policy toward bad decision-making by American political leadership. That's why he built that weapon. That's why he ordered that weapon built. 
So not because, I mean, he may be a monster. That's another issue, but it's not because he was a monster, it's because he made a strategic calculation that that kind of weapon would cause any person, even if they were totally without knowledge and thought of how missile defense could work, to understand that you will not escape retribution if you attack Russia. That's why that weapon was built.

Tuesday, May 17, 2022

Seminar on Black Hole Information and Quantum Hair, Yangzhou University (video)


Center for Gravitation and Cosmology, Yangzhou University (May 16 2022) 

There were several good questions at the end, and a discussion of the following rather fundamental topic.

In the conventional description of quantum measurement a pure state evolves into a mixed state, with probabilities of distinct outcomes (non-unitary von Neumann projection). 

See, e.g., 

Against Measurement (John Bell)

What Hawking suggested is that a black hole (i.e., gravity) causes pure states to evolve into mixed states. But if pure states already evolve into mixed states in ordinary quantum mechanics, why is it problematic for black hole physics (gravity) to have this effect? 

Title: Quantum Hair and Black Hole Information 

Abstract: I discuss recent results concerning the quantum state of the gravitational field of a compact matter source such as a black hole. These results demonstrate the existence of quantum hair, violating the classical No Hair Theorems. I then discuss how this quantum hair affects Hawking radiation, allowing unitary evaporation of black holes. Small corrections to leading order Hawking radiation amplitudes, with weak dependence on the external graviton state, are sufficient to produce a pure final radiation state. The radiation state violates the factorization assumption made in standard formulations of the information paradox. These conclusions are consequences of long wavelength properties of quantum gravity: no special assumptions are made concerning short distance (Planckian) physics.

Wednesday, May 11, 2022

Quantum Hair and Black Hole Information -- Quantum Gravity and All of That seminar series (video)


May 5 2022 talk in the international seminar series Quantum Gravity and All of That

The talk is pitched at a slightly more expert audience than previous versions I have given. 

There are interesting comments by and discussions with G. Veneziano, V. Rubakov, Suvrat Raju and others during the seminar. 

The Zoom client on ChromeOS does not allow me to see others in the meeting when I share my slides fullscreen. So at times I was not sure whose questions I was responding to! 

Title: Quantum Hair and Black Hole Information 
Abstract: I discuss recent results concerning the quantum state of the gravitational field of a compact matter source such as a black hole. These results demonstrate the existence of quantum hair, violating the classical No Hair Theorems. I then discuss how this quantum hair affects Hawking radiation, allowing unitary evaporation of black holes. Small corrections to leading order Hawking radiation amplitudes, with weak dependence on the external graviton state, are sufficient to produce a pure final radiation state. The radiation state violates the factorization assumption made in standard formulations of the information paradox. These conclusions are consequences of long wavelength properties of quantum gravity: no special assumptions are made concerning short distance (Planckian) physics.

Thursday, May 05, 2022

Raghuveer Parthasarathy: Four Physical Principles and Biophysics -- Manifold podcast #11


Raghu Parthasarathy is the Alec and Kay Keith Professor of Physics at the University of Oregon. His research focuses on biophysics, exploring systems in which the complex interactions between individual components, such as biomolecules or cells, can give rise to simple and robust physical patterns. 

Raghu is the author of a recent popular science book, So Simple a Beginning: How Four Physical Principles Shape Our Living World. 

Steve and Raghu discuss: 

0:00 Introduction 

1:34 Early life, transition from Physics to Biophysics 

20:15 So Simple a Beginning: discussion of the Four Physical Principles in the title, which govern biological systems 

26:06 DNA prediction 

37:46 Machine learning / causality in science 

46:23 Scaling (the fourth physical principle) 

54:12 Who the book is for and what high schoolers are learning in their bio and physics classes 

1:05:41 Science funding, grants, running a research lab 

1:09:12 Scientific careers and radical sub-optimality of the existing system 


Raghuveer Parthasarathy's lab at the University of Oregon - 
Raghuveer Parthasarathy's blog the Eighteenth Elephant -

Added from comments:
key holez • 2 days ago 
It was a fascinating episode, and I immediately went out and ordered the book! One question that came to mind: given how much of the human genome is dedicated to complex regulatory mechanisms and not proteins as such, it seems unintuitive to me that so much of heritability seems to be additive. I would have thought that in a system with lots of complicated,messy on/off switches, small genetic differences would often lead to large phenotype differences -- but if what I've heard about polygenic prediction is right, then, empirically, assuming everything is linear seems to work just fine (outside of rare variants, maybe). Is there a clear explanation for how complex feedback patterns give rise to linearity in the end? Is it just another manifestation of the central limit theorem...?
steve hsu 
This is an active area of research. It is somewhat surprising even to me how well linearity / additivity holds in human genetics. Searches for non-linear effects on complex traits have been largely unsuccessful -- i.e., in the sense that most of the variance seems to be controlled by additive effects. By now this has been investigated for large numbers of traits including major diseases, quantitive traits such as blood biomarkers, height, cognitive ability, etc. 
One possible explanation is that because humans are so similar to each other, and have passed through tight evolutionary bottlenecks, *individual differences* between humans are mainly due to small additive effects, located both in regulatory and coding regions. 
To genetically edit a human into a frog presumably requires many changes in loci with big nonlinear effects. However, it may be the case that almost all such genetic variants are *fixed* in the human population: what makes two individuals different from each other is mainly small additive effects. 
Zooming out slightly, the implications for human genetic engineering are very positive. Vast pools of additive variance means that multiplex gene editing will not be impossibly hard...
This topic is discussed further in the review article:

Tuesday, May 03, 2022

How We Learned, Then Forgot, About Human Intelligence... And Witnessing the Live Breakdown of Academia (podcast interview with Cactus Chu)

This is a long interview I did recently with Cactus Chu, a math prodigy turned political theorist and podcaster. (Unfortunately I can't embed the podcast here.)

3:24 Interview Starts  
15:49 Cactus' Experience with High Math People 
19:49 High School Sports 
21:26 Comparison to Intelligence 
26:29 Is Lack of Understanding due to Denial or Ignorance? 
29:29 The Past and Present of Selection in Academia 
37:02 How Universities Look from the Inside 
44:19 Informal Networks Replacing Credentials 
48:37 Capture of Research Positions 
50:24 Progressivism as Demagoguery Against the Self-Made 
55:31 Innumeracy is Common 
1:06:53 Understanding Innumerate People 
1:13:53 Skill Alignment at Cactus' High School 
1:18:12 Free Speech in Academia 
1:21:00 You Shouldn't Fire Exceptional People 
1:23:03 The Anti-Excellence Progressives 
1:28:42 Rawls, Nozick, and Technology 
1:34:00 Freedom = Variance = Inequality 
1:37:58 Dating Apps 
1:41:27 Jumping Into Social Problems From a Technical Background 
1:41:50 Steve's High School Pranks 
1:46:43 996 and Cactus' High School 
1:50:26 The Vietnam War and Social Change 
1:53:07 Are Podcasts the Future? 
1:59:37 The Power of New Things 
2:02:56 The Birth of Twitter 
2:07:27 Selection Creates Quality 
2:10:21 Incentives of University Departments 
2:16:29 Woke Bureaucrats 
2:27:59 Building a New University 
2:30:42 What needs more order? 
2:31:56 What needs more chaos?

An automated (i.e., imperfect) transcript of our discussion.

Here's an excerpt from the podcast:

Sunday, May 01, 2022

Complex Trait Prediction: Methods and Protocols (Springer 2022)

My research group contributed a chapter to this new book on Complex Trait Prediction (see below). The book is somewhat unique, covering applications to humans, plants, and animals all in a single volume. 
Complex Trait Prediction: Methods and Protocols (Springer Nature) 
Nourollah Ahmadi and Jérôme Bartholomé 
CIRAD, UMR AGAP Institut, Montpellier, France


About this book 
This volume explores the conceptual framework and the practical issues related to genomic prediction of complex traits in human medicine and in animal and plant breeding. The book is organized into five parts. Part One reminds molecular genetics approaches intending to predict phenotypic variations. Part Two presents the principles of genomic prediction of complex traits, and reviews factors that affect its reliability. Part Three describes genomic prediction methods, including machine-learning approaches, accounting for different degree of biological complexity, and reviews the associated computer-packages. Part Four reports on emerging trends such as phenomic prediction and incorporation into genomic prediction models of “omics” data and crop growth models. Part Five is dedicated to lessons learned from case studies in the fields of human health and animal and plant breeding, and to methods for analysis of the economic effectiveness of genomic prediction. 
Written in the highly successful Methods in Molecular Biology series format, the book provides theoretical bases and practical guidelines for an informed decision making of practitioners and identifies pertinent routes for further methodological researches. Cutting-edge and thorough, Complex Trait Predictions: Methods and Protocols is a valuable resource for scientists and researchers who are interested in learning more about this important and developing field.
Our article (pp 421–446):
From Genotype to Phenotype: Polygenic Prediction of Complex Human Traits 
T. Raben, L. Lello, E. Widen, and S. Hsu 
Decoding the genome confers the capability to predict characteristics of the organism (phenotype) from DNA (genotype). We describe the present status and future prospects of genomic prediction of complex traits in humans. Some highly heritable complex phenotypes such as height and other quantitative traits can already be predicted with reasonable accuracy from DNA alone. For many diseases, including important common conditions such as coronary artery disease, breast cancer, type I and II diabetes, individuals with outlier polygenic scores (e.g., top few percent) have been shown to have 5 or even 10 times higher risk than average. Several psychiatric conditions such as schizophrenia and autism also fall into this category. We discuss related topics such as the genetic architecture of complex traits, sibling validation of polygenic scores, and applications to adult health, in vitro fertilization (embryo selection), and genetic engineering.
Ungated arXiv version.

Previous discussion: 

See also Big Chickens.

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