Some of us are old enough to remember what was originally promised by genome-wide association studies (GWASs): we would finally discover the genes aetiologically involved in the conditions which till then we had been researching using a combination of linkage and candidate gene association studies. Clearly, this has not happened. With the benefit of hindsight and a myriad actual results we now clearly appreciate what perhaps we should always have realised, which is that common variants do not have substantial effects on phenotypes. GWASs yield complex, difficult to interpret findings which implicate variants but not genes and have not delivered the insights which we were promised they would.
The first GWAS of severe COVID-19 infection was published in the NEJM with the main hit at rs11385942 at locus 3p21.31, a region linked by the authors to LZTFL1. The GWAS catalogue points to MIP1B ( Macrophage Inflammatory Protein 1 beta, MIP-1b, CCL4) level that has been mapped there as well.
MIP-1B seems to be increased in patients with COVID-19 as a study showed that levels of various CCGFs, including PDGF-BB, CCL5/RANTES, CCL4/MIP-1β, IL-9, and TNF-β were upregulated in COVID-19 patients but negatively correlated to disease severity.
Another study measured also MIP-1B but no major effect
A recent Frontiers review discusses the relationship to the cytokine storm in fatal COVID-19 infection but again no isolated effect. Nevertheless I have a gut feeling from a 1995 Science paper that it could be relevant as it was identified as the major HIV-SF produced by CD8+ T cells (which are so important also in COVID-19 recovery).
This is not a joke – we can easily drop the last 3 or 4 nature genetics volumes for ignorance of basic facts. I have written here many times about the usefulness of current GWAs but missed the details of a Cell paper by McClellan & King that I am wholeheartedly supporting (although not all other science bloggers) Continue reading Drop the last 3 nature genetics volumes from the libraries
We had Aulchenko here a year a go or so – now here comes his new paper Predicting human height by Victorian and genomic methods
In a population-based study of 5748 people, we find that a 54-loci genomic profile explained 4â€“6% of the sex- and age-adjusted height variance, and had limited ability to discriminate tall/short people, as characterized by the area under the receiver-operating characteristic curve (AUC). In a family-based study of 550 people, with both parents having height measurements, we find that the Galtonian mid-parental prediction method explained 40% of the sex- and age-adjusted height variance.
While some of my earlier co-workers continue to praise the achievements of GWAs, some other earlier co-authors now show that the common variants thrown on the current GWA chips are leading to false associations (politely called “synthetic” associations)
We propose as an alternative explanation that variants much less common than the associated one may create â€œsynthetic associationsâ€ by occurring, stochastically, more often in association with one of the alleles at the common site versus the other allele. Although synthetic associations are an obvious theoretical possibility, they have never been systematically explored as a possible explanation for GWAS findings. Here, we use simple computer simulations to show the conditions under which such synthetic associations will arise and how they may be recognized. We show that they are not only possible, but inevitable…
The proof comes with a sickle cell anemia study Continue reading True, false, true, false, true, false, false
Having done lung function testing on hundreds, even thousands of children, I believe that this is not an easy task – it’s not only about abdominal mechanics and airway diameter but also about physical fitness – and let’s be cruel – also about intelligence. Even worse, I remember a long discussion how to adjust lung function parameter appropriately – should we use standing or sitting height? Two new papers large ignore these questions. But read first what the Charge consortium writes Continue reading On the tasseography of lung function genes