Round-up Feb 1 – Feb 18


  • An opinion piece in STAT by Michael Joyner and Nigel Paneth against the genetic reductionism of precision medicine: “We are calling for an open debate, in all centers of biomedical research, about the best way forward, and about whether precision medicine is really the most promising avenue for progress. It is time for precision medicine supporters to engage in debate — to go beyond asserting the truism that all individuals are unique, and that the increase in the volume of health data and measurements combined with the decline in the cost of studying the genome constitute sufficient argument for the adoption of the precision medicine program.” Their piece references a 1999 lecture from Francis Collins. He explains the background to the Human Genome Project (“a public science initiative focused so sharply on the molecular essence of humankind was too intriguing and too promising to forgo”) and then lays out his vision for what we now call Personalized Medicine, including an imagined 2010 encounter where a young soker learns of his increased risk of lung cancer, which “provides the key motivation for him to join a support group of persons at genetically high risk for serious complications of smoking, and he successfully kicks the habit.”


  • Race as a biological variable. A paper that finds differences in Alzheimer biomarkers between African-Americans and non-Hispanic whites: lower cerebrospinal fluid concentrations of tau, with results varying by APOE status. In addition to a race-by-biomarker interaction, this is a race-by-genotype interaction. They argue that these uncovered links mean that a) any attempts to use biomarkers in diagnosis should adjust for race, and b) hope for better treatment based on incorporating “race dependent biological mechanisms”.
  • A review of polygenic risk scores in psychiatry. Reviews use of GWAS for “increasingly informative individual-level genetic risk prediction” for psychiatric disorders, which are not yet ready for the clinic. Does a nice job of showing that the idea of summing up the effects of many genetic variants to explain a continuous phenotype goes back to the very beginning of the study of hereditary. “ To understand how to incorporate PRS into clinical practice for patients with heritable psychiatric disorders, studies will need to assess health outcomes for various behavioral interventions, treatment regimens, and/or differential diagnoses” They make an interesting observation as regards height: “prediction accuracy is not distributed evenly; it performs particularly poorly at the extreme short end of the height distribution, indicating a larger contribution of environmental factors, large-effect rare variants, and/or other factors in these individuals”
  • Polygenic scores are trained on cohorts of diagnosed individuals. A Danish study shows that polygenic scores for depression are also predictive in a general cohort. A score of one standard deviation above the mean gives a 30% increased chance of a diagnosis of depression.


  • A look at how consumer genetic testing companies market testing for Native American ancestry, focusing on the claimed links to identity. They wonder, whilst acknowledging it is beyond the scope of their paper, “Are companies changing consumer behavior, or are consumers already coming in with certain expectations of verifying tribal ancestry and using the results as a means to accomplish this goal?” (See this paper for qualitative interviews with 100 people looking at this question). The paper references that the US government required tribes in 1934 to have a minimum “blood quantum” for enrollment. There is clear, and problematic, precedent for the use of genetics/blood to define identities. Rewind the clock to 2013, and in giving the majority opinion against a Native American father in a complicated court case, Justice Alito choose to start with “This case is about a little girl (Baby Girl) who is classified as an Indian because she is 1.2% (3/256) Cherokee.”, seemingly drawing attention to the genetic component of her Indian-ness, and in particular that it was only 1.2% (I recommend the More Perfect podcast episode about this case). Reading more about these considerations convinces me of just how counterproductive it was for Elizabeth Warren to act upon Trump’s goad to be genetically tested to proof her claims of Native ancestry.
  • A piece on SpectrumNews, about the benefits of genetic testing. I was struck by this quote from the mother of a child who received a pathogenic finding when her daughter was an adolescent: “Instead of trying to change her behaviors, we’re modifying how we take care of her… It has given me a lot of relief knowing where her autism comes from, and that there was nothing I could have done differently.” Her daughter was the “way she is because of biology”. Routine genetic testing, if it had been available at the time could have saved her ”years of worry and guilt”.  
  • Antonio Regalado reports on a start-up working towards designer babies. One of the founders “is skeptical of the role regulations can play—a lesson he says he learned working with Bitcoin, a digital currency outside the control of any central bank.” I was alarmed at this: “Bishop told me none of the ethicists he e-mailed had ever gotten back to him.”
  • The FBI can now send a sample to FamilyTree, and they will sequence it and see if it matches anything in their database:
  • Speaking of polygenic scores, did you see that the Scripps has an App for that?
  • Some lovely visual explainers of the difference between NGS and genotyping from NYT.


  • Designing babies with high IQs may be far off, but selecting between embryos based on polygenic scores for IQ is more or less upon us (witness Genomic Prediction). Erik Parens, Paul Appelbaum, and Wendy Chung argue that profiling embryos for IQ would be unethical. Parents have two competing ethical obligations: to accept their children as they are, and to shape their children. The market is producing a “grotesque” pull towards the latter. “Placing limits on the genetic selection of embryos is one small way for our society to affirm the importance of achieving a balance between the ethical obligations to shape our children and to accept them as they are — and the importance of closing, rather than widening, the gap between the rich and the poor.” They argue for regulation, pointing out that the UK manages to do just that.
  • Ethics dumping? The Economist asks whether Deem — the American scientist who was He’s thesis advisor and who had same role in the notorious experiments — is guilty.

The Backstreet Boys have a new album called DNA. Why? Watch this cringeworthy explainer.

Round-up Jan 16th- 31st

Updates to the human germline editing saga


  • In a long piece in the New York Times Magazine on paleogenomics, takehomes here,  Gideon Lewis-Kraus points to the field’s major and recent successes, but also highlights how some archeologists fear that it traffics in “grand intellectual narratives” that history warns us against. This is an indication of culture wars between geneticists and others.


  • A study that doubled the number of microbial genomes available (150,000) by producing data from metagenomic studies including those covering non-Westernized countries. They grouped their ~150,000 new sequences in to 5000 “species bins”, 77% of which were novel. The new sequences dramatically increase the mappability of samples to 87%.
  • A fine grained (682bp) map of where crossovers occur on chromosomes, from Decode. The CEO of Decode, and author, Dr Stefansson (source): “The classic premise of evolution is that it is powered first by random genetic change. But we see here in great detail how this process is in fact systematically regulated – by the genome itself and by the fact that recombination and de novo mutation are linked. We have identified 35 sequence variants affecting recombination rate and location, and show that de novo mutations are more than fifty times more likely at recombination sites than elsewhere in the genome. Furthermore, women contribute far more to recombination and men to de novo mutation, and it is the latter that comprise a major source of rare diseases of childhood. What we see here is that the genome is an engine for generating diversity within certain bounds. This is clearly beneficial to the success of our species but at great cost to some individuals with rare diseases, which are therefore a collective responsibility we must strive to address”
  • Polygenic score for lifespan, explaining 1% of the phenotypic variance, which is 5% of the heritability. Those in the top 10% of the score can expect, on average, to live 5 years longer than those in the bottom 10%.
  • GWAS for risk tolerance and risky behaviors, with genetic overlaps found between different “risky” phenotypes, and with various personality traits.



  • More powers for DNA forensics. As of the beginning of January, the Rapid DNA Act comes into force. Rapid DNA machines sitting inside police stations allow police officers to obtain sequence results in 90 minutes. The Act allows for police to upload this data to CODIS, the National DNA database, and look for matches to e.g. previous crime scenes.

In other news: The preprint server for biology BioRxiv, just turned five. In 2018, about 1711 preprints were posted per month, and in October there were over 1 million downloads. A project called the Rxvist allows users to see which preprints are generating the most twitter attention. I have added this to my bookmarks, and will be using it to help inform this round-up from henceforth!

Round-up Dec 22 2018 – Jan 15 2019

Focus on polygenic risk scores

First, let’s look at a paradigmatic example of a polygenic score publication. Inouye et al constructed a Polygenic Risk Score for CAD, gaining a hazard ratio of 4.17 for those in the top 20% compared to bottom 20% of their score. It is better as a single predictor (based on Area Under ROC curve, also known as C-statistic) than any one of smoking, diabetes, hypertension, body mass index, self-reported high cholesterol, and family history (it does not do as well as all of them put together). They conclude that their score “strengthens the concept of using genomic information to stratify individuals for CAD risk in general populations and demonstrates the potential for genomic screening in early life to complement conventional risk prediction.”

In reaction to articles such as this, several clear lines of criticism have emerged

  1. The scores are only applicable in the ancestral population that they were developed in. Combine this with the well publicised fact that almost all studies are on Caucasian populations (reviewed here), and that the assays used are SNP chips whose genetic variants were chosen based on frequencies of variants within European populations, and several issues are immediately apparent. As an alternative to producing scores separately for each ancestral population, a suggestion that studies based on African populations would be less biased and more generalizable to other populations. It is  based on the simple fact that non-African populations have been subject to more genetic drift – i.e. change in genetic variant frequency because of small population sizes. It is also the case that there are hazards aplenty in using differences between populations to infer anything about genetics, and particularly about natural selection (see g.g. this article).
  2. Hazard ratios have to be very high to be useful as screening tools. In an article that has been well circulated on twitter, “The illusion of polygenic disease risk prediction”, the authors point out that “the paradox is largely explained by the fact that odds ratios or hazard ratios typically compare risks in the tails of a single risk distribution, but these ratios ignore the proportions of individuals who will or will not develop the disease that fall in the region between the tails of the distribution”. The first author, Nicholas Wald, has been pointing this out for a long time. Note that this does not just apply to genomics, in his 1999 paper Wald takes as its case study cholesterol levels for heart disease, and shows how poor a screening test this is. (They state that no future polygenic risk score will produce a high enough relative risk — it would be good to check this, based on a score that captured the full heritability estimates for a given trait.) This argument ought not to be news. I enjoyed this slide deck by epidemiologist Cecile Janssens that traces the history of the prospect of predictive genomic tests, and some of the known pitfalls.
  3. The role of the environment means that genetics is often not as useful as these scores would suggest. If the environment changes, e.g. all people stop smoking, then the polygenic scores change too. If the genetics is mediated by an independently measurable and modifiable intermediate phenotype, e.g. cholesterol levels, then it is much less useful to know the genetics. Though see the Inouye paper showing that their score is relatively independent of other known risk factors.

These skeptical voices are not preventing a full-scale rush to applications. Color announced a 100,000 person initiative to use low throughput whole genome data to provide individuals with polygenic scores.



Science and Applications

  • Antonio Regalado has summed up the top advances in Genetics from 2018 — seeing it all in one place is definitely impressive.
  • The latest chapter on heritability, from a study of Aetna’s database of insurance claims covering about 45m individuals. Their dataset has over 56,000 pairs of twins born since 1985, and over 700,000 sibling pairs. They connect zipcodes to environmental factors of interest — SES, air pollution and weather/climate. They found that variance from these measures was much lower than from genetics and shared environment, with obesity being the phenotype with the strongest link to SES (var=0.027). Monthly cost of data was estimated at 29% heritable and 30% due to shared environment. The respective figures for co-morbidities were 43% and 24%.
  • There is often concern that receiving ambiguous results can lead to increased worry for individuals. But a new study based on a sample of over 5000 women receiving HBOC genetic risk testing fond that receiving uncertain results did not increase worry among women compared to a negative result.
  • The BabySeq project reports on results of exome sequencing of 159 newborns (127 healthy and 32 in the NICU). Of these 15 (9.4%) had genetic variants associated with a disease that could be managed in childhood. Genomic sequencing for newborns remains a contentious area.
  • An AP poll found 70% of Americans supportive of genetic editing “to prevent an incurable or fatal disease a child otherwise would inherit, such as cystic fibrosis or Huntington’s disease”, about two thirds to “prevent a child from inheriting a non-fatal condition such as blindness, and even to reduce the risk of diseases that might develop later in life, such as cancers”, and about 70% oppose “using gene editing to alter capabilities such as intelligence or athletic talent, and to alter physical features such as eye color or height.” I can’t find any original data, just reports e.g. here.
  • I thought this was an interesting story about how much of an impact the classification of a disease can make — in this case, the efforts to have schizophrenia classified as a brain disease so that it was covered by a new CDC program. Why does this matter? Mental conditions receive less funding and health insurance is often less generous. Strong echoes of dualism here.


Round-up Nov 11 – Dec 21


  • The major news was the report of the birth of the first children genetically modified as embryos. I report on that separately here.
  • The question of whether those who receive a genetic diagnosis have a duty to tell their family members is working its way through the UK courts. A man who received a genetic diagnosis of Huntington’s asked the hospital not to tell his daughter, who was pregnant at the time, because he feared she would abort the baby. The daughter has since been found to have the genetic variant associated with Huntington’s is now suing the hospital. Bioethicist Anna Middleton told the Guardian “This could really change the way we do medicine, because it is about the duty that doctors have to share genetic test results with relatives and whether the duty exists in law.”
  • UCL launched an inquiry into their past ties with eugenics, including to Galton. This was motivated by a series of secretive eugenics meetings that an academic of theirs was recently involved with.


  • PsychENCODE, a large consortium looking at functional genomics in over 2000 developing and adult brains, has published 10 papers. To focus on one paper, they found that differences in gene expression between individuals are mostly explained by differences in fractions of cell types, and that some disorders and aging are associated with changes in these proportions. For schizophrenia, they found 321 genes associated with GWAS loci, and then did some fancy machine learning to predict phenotype from genotypes and from expression. This model did much better than a genotype polygenic score alone, and still did better when the expression data was imputed (i.e. not actually experimentally measured), “highlighting the value of having just a small amount of transcriptome data for disease prediction.”
  • Large study of the genetics of ADHD finds reproducible loci. A polygenic score predicts 5.5% of the variance (for an odds ratio of 1.56). The study presents evidence that ADHD should be considered the end of a distribution: “Strong concordance with GWAS of quantitative population measures of ADHD symptoms supports that clinical diagnosis of ADHD is an extreme expression of continuous heritable traits.”
  • A much smaller fraction of developmental disorders (DDs) are explained by recessive variation in protein-coding genes than previously thought: ~3.6% in non-consanguineous populations, compared to 31% in consanguineous populations. Compare to 50% of DDs caused by de novo mutations. This work, from Hilary Martin et al appearing in Science, is based on a burden analysis approach in over 6000 exomes from the Deciphering Developmental Disorders study. “The high proportion of unexplained patients even amongst those with affected siblings or high consanguinity suggests that future studies should investigate a wide range of modes of inheritance including oligogenic and polygenic inheritance as well as noncoding recessive variants.”
  • “Just thinking you have poor endurance genes changes your body” – individuals were told a test had revealed they had one or another version of the gene CREB1, which affects how easily one tires, and were then set to run on a treadmill. Those who were told they had the version would meant they would tire more easily did indeed tire more easily. In fact, the participants had been randomized. Likewise for FTO, which can affect how full you feel, participants who were told they had the “less hungry” version of the gene reported feeling less hungry, and had higher levels of a hormone associated with feeling full. This would be a type of placebo effect for genetic information: “The results suggest that if a person just thinks they are at high risk for, say, obesity, it could change their physiology in a way that makes them more prone to the condition, Turnwald says.” (Paper here). “If simply conveying genetic risk information can alter actual risk, clinicians and ethicists should wrestle with appropriate thresholds for when revealing genetic risk is warranted.”
  • Calico and have teamed up to show that longevity is <10% genetic. Using a single pedigree of over 400 million individuals, they were able to show that previous estimates (about 15-30%) overestimated genetic inheritance because they were confounded by non-genetic inheritance showing up via the effects of assortative mating.
  • Mitochondria can be inherited from both parents in humans. The inheritance appears to be autosomal.
  • We’ve known for a long time that there is a lot of undiscovered genetic diversity in African populations, and that use of the reference genome is rife with problems. Sequencing of 910 African genomes has showed just how large the problem is: at least 10% of reads failed to align to the reference genome, but were alignable to constructed pan-African contigs.
  • A polygenic score for schizophrenia explained some of the variance in response to antipsychotics.
  • In a severe reminder that polygenic scores cannot be used in ancestral populations not included in their construction, also using the polygenic score for schizophrenia from the Psychiatric Genetics Consortium, it was shown that the mean difference between Europeans and Africans was ten times as great as the mean difference between the European cases and controls.
  • I missed this in my last round-up. At ASHG researchers in GeneRisk, from Finland, presented data on over 7000 individuals who were given cardiac risk information, some including their polygenic cardiac risk score. Those identified at higher risk, particularly if genetic, did well at making lifestyle changes.
  • Mendelian Randomization is the idea that because genetics at birth is randomized and not altered by environmental confounders, considering some gene X, one can see whether gene X is subject to Loss or Gain of Function variants in the disease of interest. If it is, then Gene X is s good drug candidate – many high cost drug trials could have been avoided if MR had been performed. The technique can also be used to distinguish between correlation and causation, for example in showing that the correlation between obesity and depression is at least partially explained by obesity causing depression (depression odds ratio of 1.18 for 1 SD higher genetic risk score for high BMI). There are many improvements to the most basic MR model, see e.g. correcting for genetic correlations with shared etiology.
  • As an alternative to Mendelian Randomization posted to bioarxix, BADGERS (Biobank-wide Association Discovery using GEnetic Risk Scores), designed to identify associations between a disease and hundreds to thousands genetically-predicted complex traits (using polygenic scores). Variants can be reclassified.
  • A study has shown that over 30% of patients had their variants reclassified within a five year time period. “The findings of this study suggest that pediatric patients with epilepsy and previous genomic test results should have their test results reinterpreted at least every 2 years and before further genetic testing.”
  • A nice review of the genetic variation relevant to immunotherapy, written by one of my former colleagues, Eric Kofman.



  • The UN’s Convention on Biological Diversity considered, and rejected, a ban on gene drives. Both those working on gene drive technology and those campaigning against it called the result a win. They state the need for informed consent, but it is not clear what this means: “who gets to decide when the African people have consented — and how unanimous a decision you need when millions of lives are on the line”
  • China has cracked down on companies that have sequenced Chinese individuals and then exported the data. Adam Minter argues that this view of chinese genetic data as a national security matter is in keeping with other chinese policies on e.g. the internet. Ultimately, a lack of openness will damage science, and chinese science in particular.
  • In April 2018 the FDA issued guidance on the use of databases in genomic testing. Applying that guidance, they have approved use of ClinGen’s Expert Curated Human Genetic Data as clinical evidence in approval submissions for tests. The data covers over 10,000 variants (ClinVar review status (“reviewed by expert panel”or “practice guideline”).
  • LunaDNA received SEC approval to sell shares to customers, part of its business plan to incentivize individuals to share their genomic data. It currently values a whole genome at $21.

Lulu and Nana: the children who will help change our morals

I first learnt about Lulu and Nana by watching the video that Chinese scientist He Jiankiu published explaining why he had edited embryos leading to the births of the first genetically modified babies. This is strongly recommended viewing. You can read the story, as broken by the AP, here. His claims have yet to be verified.

It was anticipated that the first International Summit on Human Gene Editing, held three years ago, would result in a consensus statement calling for a moratorium on genetically modified babies. There was no call for a moratorium. Since then, others have failed to call for a moratorium. Including the US’s National Academies report (which I covered here) which instead produced a checklist for when editing could be performed (p132), and the UK’s Nuffield Council report.

He published this video on November 25th, timed just before the Second International Summit on Human Gene Editing. He referenced the NASAM report in justifying his work. (Note also that He has engaged with several bioethicists over the years.) Some, e.g. Paul Knoepfler, argue that the failure to call for a moratorium “left the door too open” for his work. The second summit also did not call for a moratorium (their consensus statement).

There has been much criticism of He, for example Oxford’s Julian Savulescu, famous for arguing that we have a moral imperative to have the best children possible, described the work as “monstrous”; Penn’s Dr Kiran Musunuru described it as “unconscionable” (link). These voices included Chinese: Qiu Renzong, bioethicist and emeritus professor at the Chinese Academy of Social Science in Beijing, stated that the work was clearly not ethical, and a fraud (link).

While most have strongly condemned He’s work, some have taken a less accusatory stance. At the summit, Dr. George Daley, dean of Harvard Medical School, characterized He’s work as a “misstep” and argues “It is time to move forward from [debates about] ethical permissibility to outline the path to clinical translation … in order to bring this technology forward.” (link). George Church states “I feel an obligation to be balanced.”, calling the criticisms of He bullying.

Should the scientific community have acted differently? David Baltimore, the convener of the Second Summit, (reported by STAT) states that “I think there has been a failure of self-regulation by the scientific community because of the lack of transparency.” Scott Gottlieb, FDA Commissioner, goes further and says that the scientific community should not have given He a platform to self promote his work. “The response from the scientific community has been far too slow and far too tepid, and the credibility of the community to self-police has already been damaged… Governments will now have to react, and that reaction may have to take consideration of the fact that the scientific community failed to convincingly assert, in this case, that certain conduct must simply be judged as over the line” (reported in BioCentury). The work would have been illegal in the US. It also likely contravened Chinese laws (link). Lawyer Glenn Cohen questions that there could be a complicit scientific community, “it seems to me that the community is acting exactly as it should when one of its members breaks the covenant” (link).

The details of the research help highlight some open ethical issues. The aim of this research was to disable the CCR5 gene, a mutation that some people (though not Han Chinese) naturally have that is protective against HIV infection. The choice seems motivated to be a CRISPR first, rather than a pressing therapeutic need. Disabling a gene is much easier than precisely tweaking a “broken” gene to be functional. The desire for fame, to have a first, was a clear motivating factor for the research: the team wrote in their submitted ethics statement “In this ever more competitive global pursuit of applications for gene editing, we hope to be a stand-out”. Potential parents were only eligible for the study if the father had HIV. Infertile women are not eligible for IVF if their partner has HIV (link). The research is thus particularly question worthy as it a) blurred the lines between research, which is supposed to recruit individuals whose main aim is to contribute to scientific knowledge, and clinical application, where direct benefit is expected, b) edited healthy embryos, rather than seeking to “fix” those who would otherwise go on to develop a serious condition, c) individuals with the introduced edit have a higher chance of infection with the West Nile virus, and a higher chance of dying from influenza; as a protective mutation, d) the edit blurs the enhancement/therapy line, e) one of the embryos was known heterozygous (and hence would not have had the protective benefits) pre-implantation; whether the prospective parents could give true informed consent has been questioned. For the very real risk of off target effects, the consent form stated that “the project team is not responsible for the risk.” The case highlights just how ambiguous language is: An item on NASAM’s checklist was that editing be done for an “unmet” medical need. As Church points out, there is no cure or vaccine for HIV. On the other hand, HIV is both preventable and treatable.

What happens next? There are decisions ahead for any editor who receives the work to review. Francis Collins, who heads the NIH, has called for a “binding international consensus”. An editorial in Nature calls for a global registry of work genetically modifying human embryos. Carl Zimmer, writing in the New York Times, draws the parallel to babies born via mitochondrial replacement therapy, and the example of how the UK has made this legal within a highly regulated environment. Throughout this debacle, two reference cases have been given. The first is to Louise Brown, the first baby born by IVF. In the years around her birth, public opinion changed from being opposed to interfering with nature in this way, to being supportive of IVF (see Table 2 here). The second is to Jesse Gelsinger, who died in 1999 after receiving an experimental gene therapy. His death seems largely creditable to hastiness around excitement of a new technology. As George Church states, it is too early to tell whether Lulu and Nana will be Louise Browns or Jesse Gelsingers. But note that, post Jesse’s death, gene therapy is once again being pursued with gusto.

Why China? While international science incentives “firsts”, this may be acutely felt in China. As Jing-Bao Nie argues, “China’s science schemes have much to do with the developing mentality that ethics is merely secondary and instrumental for cutting-edge scientific investigation and technological invention”. Additionally, Chinese society places less emphasis on the individual: As Antonio Regalado reports here, “A person who knows He said his scientific ambitions appear to be in line with prevailing social attitudes in China, including the idea that the larger communal good transcends individual ethics and even international guidelines.” Indeed, He commissioned an opinion poll that found majority support of the Chinese public for therapeutic genetic modification (this is inline with polls in the US).

I think we will see public acceptance of genetic modification of embryos, first in the therapeutic setting, and probably first in a country such as China. As we have learnt time and again from the Assisted Reproductive Technologies space, technology does change morals.

Round-up Oct 1 – Nov 10

I continue to struggle to find a format for these round-ups. I am finding the division Science/Applications/Regulation useful, but there a few stories that never quite fit that pattern. I realized that these are mostly the controversial ones, and so I have carved off a section dedicated to the eyebrow raising.


  • Elizabeth Warren underwent genetic ancestry testing, in order to prove a genetic connection to her claim of Native American ancestor. Her move has been widely covered, and criticised. It throws light on the connection between genetics and identity. Here is an interesting piece comparing the relationship between genetics and cultural identity in the aboriginal populations of Australia and the US.
  • Nature News reports on the The approach to predictive medicine that is taking genomics research by storm. One of the leading scientists behind polygenic scores, Peter Visscher, a geneticist at the University of Queensland, states that “I’m absolutely convinced this is going to come sooner than we think.” Myriad has begun including a polygenic score for breast cancer on its reports, in something that is rather convenient for sales, “One of the strengths of these scores is that they provide a result for everyone, says Jerry Lanchbury, Myriad’s chief scientific officer.”
  • Genomic Prediction launched their Expanded Pre-implantation Genomic Testing in September. It covers many single gene disorders and uses polygenic scoring for complex disorders (Type 1 Diabetes, Type 2 Diabetes, Coronary Artery Disease, Atrial Fibrillation, Breast Cancer, Hypothyroidism, Mental Disability, Idiopathic Short Stature, Inflammatory Bowel Disease). They are working on height. The cost will be $400 per embryo (source). From the same source, the CSO, who has Type 1 Diabetes, explains that the company wants to move on to genome editing “If his own parents had that option, “they could have potentially edited out my diabetes and it would have been a cure,” he said. “I would have been here without diabetes.” The irony is, if his parents had access to their PGD product, he would probably never have been born.
  • In a striking example of the misuse of genetics, an image of white supremacists chugging milk has been doing the rounds. The act goes with the message that those who can’t digest milk should “go home”. Those of caucasian ancestry, and inconveniently for the supremacists, also those of East-African ancestry, tend to have the ability to digest lactose. The report by Amy Harmon in the NYT states plainly some of the problems with addressing this: “Many geneticists at the top of their field say they do not have the ability to communicate to a general audience on such a complicated and fraught topic. Some suggest journalists might take up the task. Several declined to speak on the record for this article. And with much still unknown, some scientists worry that rebutting basic misconceptions without being able to provide definitive answers could do more harm than good. “There are often many layers of uncertainties in our findings,” said Anna Di Rienzo, a human genetics professor at the University of Chicago. “Being able to communicate that level of uncertainty to a public that often just sees things in black and white is very, very difficult.” The ASHG released a statement condemning this use of genetics, saying that concept of “racial purity” was scientifically meaningless.
  • Robert Plomin’s book Blueprint, which is newly released in the UK, is already stirring controversy. One commentator notes “Yet in the end with Blueprint, there exists a risk that readers end up impressed by Plomin’s account of his science without being aware of the racial and social implications of his theory. And in the context of a resurgent right wing across the world looking for “scientific” reasons to elevate race in public policy, this seems profoundly irresponsible.”



  • Economic researchers applied the score in combination with economic data (working paper). The results? As one of the authors reported to the Post, “If you don’t have the family resources, even the bright kids — the kids who are naturally gifted — are going to have to face uphill battles.”
  • A twin study based on UK individuals on the genetics of university success produced heritability estimates for: entrance exam achievement (57%), the choice to study at university (51%), the quality of university attended (57%) and achievement at university (46%). (Numbers are the proportion of variance in the trait explained by inherited factors). The Educational Achievement polygenic score, which captures 11-13% of variance in number of years of education, captured 4%, 5%, 2%, 7% of this variation respectively.
  • This was a piece I started to read not expecting a connection to genomics: the story of the placebo effect, and attempts to unpick its biochemistry. Researchers formed a hypothesis that variation that affected the levels of COMT, an enzyme that helps determine levels of dopamine and its relatives. They have indeed found evidence of this. The suggestion is that somehow the caring involved in a patient-physician interaction stimulates the same biochemical pathway that many drugs use. This suggests that the blinded placebo trial may be inappropriate: “the placebo effect is not just some constant to be subtracted from the drug effect but an intrinsic part of a complex interaction among genes, drugs and mind.” And of course “The [pharma]industry would be delighted if it were able to identify placebo responders — say, by their genome — and exclude them from clinical trials.” Thinking beyond trials to the administration of medicine, “Should medical rituals be doled out according to genotype, with warmth and caring withheld in order to clear the way for the drugs?”
  • I had previously missed this: a European initiative to overcome data silos and privacy concerns to assemble a million genomes by 2022.
  • A new study from Calico and estimates the heritability of lifespan to be under 10%. It was previously believed to be higher, but they think that this was inflated due to the effects of assortative mating.
  • The largest ever genetic study from China of over 140,000 Chinese individuals has been reported. It was based on blood processed for Non-invasive prenatal testing of pregnant women.
  • The Garvan Institute in Australia has sequenced the genomes of 4000 healthy elderly individuals. I remember when 4000 sounded enormous…
  • In more new datasets, about 2000 genomes of individuals from rural Uganda, and genotype results from thousands of other across Africa. This is beginning to help us unpick the early starts of human population structure.
  • Gout was previously thought to be associated with diet. But a new study of ~17,000 individuals finds that the effects of diet are very minimal, whereas genetics plays a large role, explaining ~24% of the variance.
  • A new version of CRISPR, CRISPR-GO can alter the genome’s organization.





Catch-up June 28th – Sept 30th

Another major gap from me as my travels have continued…

A major theme that emerges for me over the past few months is on non-medical uses of genetics, made possible by 1) Continued growth of Direct to Consumer (DTC) testing, 2) large scale studies of non-health traits, and 3) increased acceptance of polygenic risk scores, whereby an aggregate score for a given trait is made from small contributions from many genetic markers. This is something we need to talk about.

1) Millions of DTC tests have been sold in the US (over 12 million, according to one estimate from February). A poll found that “Some 17 percent of Americans already have undergone at least one kind of DNA test, and 52 percent of the remainder say they’d like to.”

2) In the last few months, there have been large scale studies of neuroticism, intelligence, social mobility, and on social traits including loneliness. A lot of research into such “social” traits is performed under a health mandate, as many such traits correlate with health outcomes.

3) Polygenic risk scores can be much better at identifying those at risk of serious conditions. That’s the conclusion of a paper and the basis for a new tool that will ingest e.g. 23andMe data and give you a score. From the paper: “The approach identifies 8.0, 6.1, 3.5, 3.2, and 1.5% of the population at greater than threefold increased risk for coronary artery disease, atrial fibrillation, type 2 diabetes, inflammatory bowel disease, and breast cancer, respectively.” These successes, combined with the type of studies I listed above, lead to, for example, educational achievement and cognitive performance polygenic risk scores, explaining 11-13% of variance, 7-10% of variance respectively. Such scores have already make it into DTC tests, for example educational achievement markers are available from Helix.

Needless to say, such scores have the potential for large social implications. The educational achievement study has appeared all over the press, but I have found good critique of possible implications scant. This piece is an exception, one example:

“There’s as much to be learned about the nature of our educational system as about the nature of the individual in this data,” said Mary Helen Immordino-Yang, professor of education, psychology, and neuroscience at the University of Southern California. Specifically, if certain genetic variants are associated with better educational outcomes, then there might be something about the structure of our educational system that’s favoring people with these variants. For example, if the variants were involved in language comprehension, that could tell educators that current teaching methods aren’t working for students who process language differently. That means they should be designing new interventions to accommodate that variation, Belsky said.”

Such reflection is critical. Contrast this with the authors of a paper titled “The stability of educational achievement across school years is largely explained by genetic factors”,  state the motivations and consequences of their work are that “we could use DNA tests at birth to identify children at genetic risk for developing reading problems, and give them early intervention.”

Separately, additional potential downsides of the DTC genomics movement have been in the news. I highlight three:

  • What happens when DTC tests reveal unexpected family secrets? The Atlantic has a piece on a facebook group, with over 1000 members, that allows individuals affected to vent emotions and plan next steps. Meanwhile in the UK, the fertility regulator has called for genetic testing companies to better highlight chances of uncovering family secrets, additionally saying that anonymity for sperm/egg donors is a thing of the past.
  • In the light of and Spotify teaming up to offer playlists based on your results, a critique of how genetic ancestry testing, who focus on the fact your DNA reveals something meaningful about you. This runs from “conflating DNA and cultural identity” (routing for a World Cup team based on results) to “game programs set up to address past injustices” (using results to prove Native American or African ancestry), to reifying race as a meaningful category (citing a study that showed reading about these tests increased beliefs in racial differences).
  • A report on four cases of families who act on information obtained from raw data provided by DTC tests. In these cases, none of the SNPs reported turned out to be present. Another story of a discordant 23andMe and Ancestry result over a very worrying variant.

I think it is worth highlighting what we have learnt about consumer preferences

  • The Associated Press reports a poll of 1109 adults it performed on questions related to genetic testing (also refed above on number of people interested in genetic testing). On whether people would want to know if DNA showed they had a genetic variant associated with an incurable disease. 60% said Yes, for under 30s the number was 78%. Most (but not all) would tell family members). The poll also asked about the use of DNA by the Feds — “Half of people think genetic data should be used to help solve crimes only with the consent of the person tested, a third think it’s OK without that consent — and 13 percent don’t think law enforcement should use it at all.”
  • A Pew poll found majority support for gene editing for babies for health reasons. Men and more supportive; religious people are less supportive. If the intervention relies on testing embryos, most are opposed.
  • A U of Michigan study on patient attitudes to their biobank samples being commercialized. “67 percent of participants agreed that clear notification of potential commercialization of biospecimens is warranted, but only 23 percent were comfortable with such use. Sixty-two percent believed that profits should be used only to support future research, and 41 percent supported sharing profits with the public.”
  • STAT reports on consumer adoption of genetics in China. Those in the space refer to a particular emphasis on a Chinese fascination of how genetics affects identity and destiny, and, for the generations born under the one child policy, with finding family. Routine newborn genome sequencing is on the cards within the next five years (Veritas already has a product in pilot out there). Because there isn’t an entrenched medical genetics profession, there will be less paternalism about results.

It strikes me that the academic literature is all about efforts to ensure that people’s informed choices are respected. A lot of this type of work, which looks at what those choices are likely to be, happens outside the academic mainstream. This is an observation I intend to check.




And finally, a nice piece from science historian Oren Harman on use of the term “gene” — historically and in the future. And another lovely piece about how some of the genes got their names, including the background to “Pray for Elves”, which I learnt originates with someone I used to work with, Prof Mark Yandell.