My view of COVID from crisp, cold Helsinki (back to London - with PCR test - on Tue). TL;DR Omicron has thrown us back to a place of uncertainity; we have far more potent tools+understanding now but the trajectory will be mainly determined by the biological properties of Omicron
Context: I am expert in human genetics and computational biology. I know experts in viral genomics, infectious epidemiology, clinical trials and immunology. I have some conflicts of interest; I am paid consultant and shareholder of Oxford Nanopore and was on the Ox/Az trial.
Key background: COVID is a virus-triggered disease, with hallmarks of auto-immune disease, triggered by a novel, highly infectious Coronavirus, SARS-CoV-2. In naive populations many people would get this disease, many of those dieing, and healthcare would be overwhelmed
A great collaboration on direct RNA sequencing of SARS-CoV-2 transcripts using nanopore sequencing from Camilla Ugolini (Italian Institute of Technology) and colleagues, lead by Tomasso Leonardi (IIT) and Dave Matthews (Bristol) - I am a co-author. biorxiv.org/content/10.110…
(note; I and some other authors, eg, @AkesonUCSC have conflict of interests to declare as I am long standing consultant to Oxford Nanopore and shareholder).
Camilla looked at SARS-CoV-2 transcripts using a neat new protocol that both captures capped (full length) RNAs and can sequence through them, NRCseq, developed by @ettwiller (also a co-author). This means Camilla can distinguish full length from degraded transcripts.
A brief explainer thread on B.1.1.529, the latest SARS-CoV-2 variant which is throwing up concern after an excellent live streamed press conference from South Africa. TL;DR this variant both has many mutations but most importantly looks like it outcompeting delta in South Africa
Context: I am a expert in human genetics and computational biology; I know experts in viral genomics, infectious epidemiology, clinical trials and immunology. I have some conflicts of interest: I am longstanding consultant to Oxford Nanopore and was on the Ox/Az clincal trail
Background. The SARS-CoV-2 virus is made from RNA (its instruction set) wrapped in proteins. The RNA+proteins of the virus hijack our cells to make more of its RNA and proteins into a virus. This hijacking (infection) causes a response from our immune system.
In my voyages in maths with my daughter series - we've been discussing geometry (seed question - can you prove the (n-2)*180 for the interior angles of an n-sided polygon) and this threw up some interesting things.
First off, a discussion of 180 leading to radians + Pi. Thought experiment - if there was a planet of intelligent otters and they used a different number/angle system, they would no doubt not divide the circle into 360, but the concept of a circle, half circle, would be the same
(you might guess my daughter is a fan of otters. We decided they would likely work in base 7 I think due to their tails being the extra "unsymmetric" digit. Don't ask for more details).
Thoughts on COVID in Europe from a crisp morning in London; we understand this virus, its likely endpoint, but it is hard road to follow. Central/Northern Europe start a 4th nasty wave; South West Europe has vaccinated well, (currently) less of a wave; the UK remains a conundrum
Context: I am an expert in human genetics and computational biology. I know experts in infection biology, viral genomics, clinical trials. I have COIs - I am longstanding consultant to Oxford Nanopore (makes sequencing machines) and was on the Ox/Az trial.
Reminder: Assumming there is no major new SARS-CoV-2 variant, we have the measure of this virus and its horrible disease - it transmits rapidly between humans, causing a nasty, often lethal disease (COVID) in some (older, more overweight) people who are immunlogically naive.
Ethnicity, Ancestry Groups and Biology in humans; some thoughts triggered by @molly_przew threads and the recent Oxford paper on the likely mechanism of action for the COVID risk locus on chr3. TL;DR This is area is complex; racism +discrimination are real; biology is universal.
It's useful to remind yourself what some of these terms mean (or might mean). Ethnicity (also "Race" in US context) is usually defined via self identification - a person is given a number of options to tick, sometimes with hierarchy, and they tick one (or more) option.
Great to see this pre-print on rare-meets-common TYR/ human pigmentation genetics by Vincent Michaud (Bordeaux) and senior author Panagiotis (Panos) Sergouniotis (Manchester) - I am a co-author medrxiv.org/content/10.110…
One key thing is that it is a promoter variant which is associated with albinism and related eye phenotypes, not in fact as non-synonymous variant in LD (one needs to capture rare recombinations, and an example of needing deep phenotype positive ascertainmemt - case collections).
(The Promoter variant is the first SNP TYR c.-301C>T [rs4547091] - and it's LD NS proxy is c.575C>A (p.Ser192Tyr) [rs1042602] - by default, any program/analysis would have probably assigned function to the protein coding change)
A COVID viewpoint from increasingly cold London. TL;DR the world vaccination situation is improving, but there is a long way to go; Europe is entering a winter exit to endemicity surge; the UK is a leading country in this exit surge with internal angst, strife and screw ups
Context: I am an expert in human genetics and computational biology. I know experts in infectious disease epidemiology, viral genomics, immunology and clinical trials. I have COIs - I am consultant and shareholder of Oxford Nanopore and I was on the Ox/AZ trial.
Reminder: SARS-CoV-2 is now the fifth endemic coronavirus that infects humans, and by far the nastiest. For a subset (older, overweight, male) of people is causes a horrible disease, COVID, in which some people die, and many people have horrible time in hospital or longCOVID
COVID thoughts on an autumnal London day. TL;DR the developed vaccinated world has some tricky navigation, but is probably entering some endemic-ish state; the developed unvaccinated world is a bit mad and needs help; the rest of the world needs vaccines.
Context: I am an expert in genetics/genomics and computational biology. I know experts in infectious epidemiology, viral genomics, clinical trials and immunology. I have COIs; I am long established consultant to Oxford Nanopore and I was on the Ox/Az clinical trial.
Reminder: SARS-CoV-2 is an airborne virus. The latest variant, now globally dominant, transmits rapidly and all variants causes a horrible disease in subset of people - older, more overweight, male. Left unchecked many people would die and healthcare systems overwhelmed.
In general the response I think to the announcement of a polygenic-risk-score informed embryo selection has been right - one where the science is wrong, the clinical harm/benefit therefore also wrong, and one where ethical/societal considerations have to be folded in. However...
There are some people who say "but even if this is wrong now, it might not in the future" (true) and also "if genetics works, then this should work" often with some handwaving towards farm animal genetics/breeding/selection. In this twitter thread I'd like to tackle this.
(Context: I am a geneticist/genomicist. My two favourite organisms to study humans and Japanese rice paddy fish. I'm on the experiments/practical data science side, but have a pretty good understanding of the theory/stats side, partly because I've coded it myself/in my group)
A reminder; in the UK this process would clearly fall under HFEA, and applications to do this would almost certainly be rejected on ethical / societal grounds, on clinical harm to benefit and underlying scientific validity
I’m very positive about the use of genomics in healthcare - many diverse uses and its growing - but I am firmly against this use on ethics, clinical (I’m not an expert) and science (I am an expert). Blogged on this in 2019 ewanbirney.com/2019/05/why-em…
I think the imperial weights thing in the UK is silly (deeply silly) but I do think there was more method in "12" units (and for that matter, 60). 12 is a nice number for division (halves, thirds, quarters, sixths) and then the next nice number for division is 60 (fifths).
Of course the pounds to stone (14!) and then madness of Guineas (I still don't really understand) doesn't fit this. On historical numerology, I was reminded of the arcane voting system for the Dodge in Venice that involves 11, 13s and 17s as supposed "hard to game" prime numbers
As well as the measuring unit changing depending on what you were measuring (this is another moment of deep madness) I think this use of effectively base 12 might be more about early medieaval maths and plenty of mental arithmetic.
After a great workshop in Paris (and hopefully, testing being ok, I will be returning next week) I've been thinking about my travel in the new normal, thinking about green (lowering carbon)
This has been informed by conversations with colleagues such as @embl's green officer, @BrenRouseHD, faculty colleagues such as @Alexbateman1, @PaulFlicek and Deltev Arendt (many thanks); these are currently my thoughts on this (insight from colleagues; missteps from me!)
First off pre-pandmic science travel was useful but often mad; flying for single meetings (sometimes in windowless rooms) with fast turn arounds. Not only was it carbon expensive but it was also bad for family life and just plain health.
As we enter yet another period of COVID uncertainity over outcomes (due mainly to human behaviour - what does "baseline/new normal" contacts look like in an European Autumn/Winter) a reminder about models. There are at least 3 different types; explanatory, forecast and scenario.
Explanatory - usually retrospective data to fit an understanding of the world (say infection->hospitalistion/not->death/discharge) for time series. Examples: excess deaths attributable to COVID, vaccine efficacy models and biological properties of variants.
Forecast - fit an up to date time series to understand outcomes in the near future, sometimes just to understand "now" (hence "nowcasting"). Examples: R rate and near time extrapolation; hospitalisation capacity near term management (often not public).
My annual reminder; if you propose doing large scale data gathering and analysis, just a *one sentence* power calculation, or "we have confidence this approach can provide robust results due to similar work of XXX in system YYY with similar sample sizes".
Why is this important in a grant? As a reviewer wont be able to fully check your power calculation (usually) but I do want to see that you are honest with *yourself* about whether the stats are going to work out. Too few samples, expected weak effects => it's never going to work
If your power calculation (which will always be pulling numbers out of the air for effect size etc; such is science) says its very unlikely you will find a credible result then... you need to reset your goals.
COVID thoughts from London, after a yesterday's day of slow cricket; TL;DR - the pandemic is reasonably predictable except for human behaviour on contacts; Europe will be likely navigating a complex winter; US (still) needs to vaccinate; The world needs more vaccines.
Context: I am an expert in genetics and computational biology. I know experts in viral genomics, infectious epidemiology, immunology and clinical trials. I have some COIs - I am a longestablished consultant to Oxford Nanopore and was on the Ox/Az vaccine trial.
Reminder: SARS-CoV-2 is a respiratory human virus where a subset of people infected get a horrible disease, COVID, often leading to death. Left unchecked many people would die and healthcare systems would have overflowed.
COVID thoughts from London as back to school and work looms for England. TL;DR Vaccines work; Delta is our hardest test; the real question is how fast can we vaccinate the planet but many developed countries are running serious, largely avoidable, risks now and coming months
Context: I am genetics and computational biology expert. I know experts in viral genomics, infectious disease epidemiology, clinical trials and immunology. I have some COIs: I am a long standing consultat to Oxford Nanopore and was on the Ox/Az vaccine trial.
Reminder: SARS-CoV-2 is a respiratory virus, distributed by both droplets and floating aerosols, which sometimes causes a delibating disease, COVID, mainly in older and overweight people. If left unchecked, many people would die and many more suffer long term health issues.
Dear journalists / editors covering COVID / this delta wave. Some of you are ... great (genuinely) - its not easy out there crafting a path thru information, speculation+ crankiness. But others... time to up your game. Here are some rookie mistakes in describing what is going on:
1. Please please stop with the % vaccinated in hospital. This is genuinely a meaningless statistic. It is just bonkers wrong to quote it. Trivially if a population is 100% vaccinated then 100% of the people in that population's hospital will be vaccinated.
What you want is something surprisingly tricky to calculate; the counterfactual of how many people should be in hospital if no vaccine. Thankfully there is an easy way of doing this which is referring back to the Alpha wave (wave 2/3 depending on counting system in each country)
Had another moment of "well, yes, but people *are* different" and "you geneticists use continental groups in your analysis" as we skirted around discussions of ethnicity / race in health impacts. TL;DR Partially correct but the underlying mindset that ethnicity=genetics is wrong
Let's deal with the correct things first. Yes, people are different partly (sometimes mainly) due to genetics. Visibly, eg height, weight, hair colour, skin colour, smoking habits + invisibly, eg cholesterol levels, heart trabeculation levels, likelihood of getting breast cancer
Some of these visible differences we integrate into the gestalt assessment of ourselves and others for ethnicity, as represented by self identified ethnicity boxes which people tick, eg "Black British, White English, British Indian, British xxx", gloriously variable by society
Ah. I love the smell of freshly baked data/analysis, well controlled false discovery rate (QQ plot) and just ... so many results. Which of the thousands of beautiful stars in the sky does one pull out to discuss? Biology is so endless and wonderful in its detail...
... to alter (butcher?) a passage from a far far wiser and more thoughtful man than me....
It is interesting to contemplate a tangled set of genetic results, associated to both well known genes and entirely anonymous regions of the genome, stories from physiology of old and hints of new insights, and to reflect ...
Great history of the electric car / mobility - 1890s onwards. I really like switching sometimes to a historical perspective on science and technology; it reminds one of the unchanging nature of human foibles and drivers with "you know how the technology story turns out"
There is, for me, a similar history of technology / medicine about the complex introduction of Xrays into medicine (I blogged about this 6 years - (! 6 years!) ago - ewanbirney.com/2015/10/genomi…
The journey of Xrays from spanking new whizzy technology to routine part of medicine is surprisingly complex - it involves twists and turns, inappropriate use of technology "just for fun" (echos of 23andme), and non obvious advocates for the uptake of the technology.