Rare predicted loss-of-function variants of type I IFN immunity genes are associated with life-threatening COVID-19

BACKGROUND

We previously reported that impaired type I IFN activity, due to inborn errors of TLR3- and TLR7-dependent type I interferon (IFN) immunity or to autoantibodies against type I IFN, account for 15-20% of cases of life-threatening COVID-19 in unvaccinated patients. Therefore, the determinants of life-threatening COVID-19 remain to be identified in ~ 80% of cases.

METHODS

We report here a genome-wide rare variant burden association analysis in 3269 unvaccinated patients with life-threatening COVID-19, and 1373 unvaccinated SARS-CoV-2-infected individuals without pneumonia. Among the 928 patients tested for autoantibodies against type I IFN, a quarter (234) were positive and were excluded.

RESULTS

No gene reached genome-wide significance. Under a recessive model, the most significant gene with at-risk variants was TLR7, with an OR of 27.68 (95%CI 1.5-528.7, P = 1.1 × 10-4) for biochemically loss-of-function (bLOF) variants. We replicated the enrichment in rare predicted LOF (pLOF) variants at 13 influenza susceptibility loci involved in TLR3-dependent type I IFN immunity (OR = 3.70[95%CI 1.3-8.2], P = 2.1 × 10-4). This enrichment was further strengthened by (1) adding the recently reported TYK2 and TLR7 COVID-19 loci, particularly under a recessive model (OR = 19.65[95%CI 2.1-2635.4], P = 3.4 × 10-3), and (2) considering as pLOF branchpoint variants with potentially strong impacts on splicing among the 15 loci (OR = 4.40[9%CI 2.3-8.4], P = 7.7 × 10-8). Finally, the patients with pLOF/bLOF variants at these 15 loci were significantly younger (mean age [SD] = 43.3 [20.3] years) than the other patients (56.0 [17.3] years; P = 1.68 × 10-5).

CONCLUSIONS

Rare variants of TLR3- and TLR7-dependent type I IFN immunity genes can underlie life-threatening COVID-19, particularly with recessive inheritance, in patients under 60 years old.

SLC37A4-CDG: Second patient

Recently, a disorder caused by the heterozygous de novo c.1267C>T (p.R423*) substitution in SLC37A4 has been described. This causes mislocalization of the glucose-6-phosphate transporter to the Golgi leading to a congenital disorder of glycosylation type II (SLC37A4-CDG). Only one patient has been reported showing liver disease that improved with age and mild dysmorphism. Here we report the second patient with a type II CDG caused by the same heterozygous de novo c.1267C>T (p.R423*) mutation thereby confirming the pathogenicity of this variant and expanding the clinical picture with type 1 diabetes, severe scoliosis, and membranoproliferative glomerulonephritis. Additional clinical and biochemical data provide further insight into the mechanism and prognosis of SLC37A4-CDG.

From Sequence-Defined Macromolecules to Macromolecular Pin Codes

Dynamic sequence-defined oligomers carrying a chemically written pin code are obtained through a strategy combining multicomponent reactions with the thermoreversible addition of 1,2,4-triazoline-3,5-diones (TADs) to indole substrates. The precision oligomers are specifically designed to be encrypted upon heating as a result of the random reshuffling of the TAD-indole covalent bonds within the backbone, thereby resulting in the scrambling of the encoded information. The encrypted pin code can eventually be decrypted following a second heating step that enables the macromolecular pin code to be deciphered using 1D electrospray ionization-mass spectrometry (ESI-MS). The herein introduced concept of encryption/decryption represents a key advancement compared with current strategies that typically use uncontrolled degradation to erase and tandem mass spectrometry (MS/MS) to analyze, decipher, and read-out chemically encrypted information. Additionally, the synthesized macromolecules are coated onto a high-value polymer material, which demonstrates their potential application as coded product tags for anti-counterfeiting purposes.

Modeling the impact of liana infestation on the demography and carbon cycle of tropical forests

There is mounting empirical evidence that lianas affect the carbon cycle of tropical forests. However, no single vegetation model takes into account this growth form, although such efforts could greatly improve the predictions of carbon dynamics in tropical forests. In this study, we incorporated a novel mechanistic representation of lianas in a dynamic global vegetation model (the Ecosystem Demography Model). We developed a liana-specific plant functional type and mechanisms representing liana-tree interactions (such as light competition, liana-specific allometries, and attachment to host trees) and parameterized them according to a comprehensive literature meta-analysis. We tested the model for an old-growth forest (Paracou, French Guiana) and a secondary forest (Gigante Peninsula, Panama). The resulting model simulations captured many features of the two forests characterized by different levels of liana infestation as revealed by a systematic comparison of the model outputs with empirical data, including local census data from forest inventories, eddy flux tower data, and terrestrial laser scanner-derived forest vertical structure. The inclusion of lianas in the simulations reduced the secondary forest net productivity by up to 0.46 t_C  ha^-1  year^-1 , which corresponds to a limited relative reduction of 2.6% in comparison with a reference simulation without lianas. However, this resulted in significantly reduced accumulated above-ground biomass after 70 years of regrowth by up to 20 t_C /ha (19% of the reference simulation). Ultimately, the simulated negative impact of lianas on the total biomass was almost completely cancelled out when the forest reached an old-growth successional stage. Our findings suggest that lianas negatively influence the forest potential carbon sink strength, especially for young, disturbed, liana-rich sites. In light of the critical role that lianas play in the profound changes currently experienced by tropical forests, this new model provides a robust numerical tool to forecast the impact of lianas on tropical forest carbon sinks.

Interactive rhythms across species: the evolutionary biology of animal chorusing and turn-taking

The study of human language is progressively moving toward comparative and interactive frameworks, extending the concept of turn-taking to animal communication. While such an endeavor will help us understand the interactive origins of language, any theoretical account for cross-species turn-taking should consider three key points. First, animal turn-taking must incorporate biological studies on animal chorusing, namely how different species coordinate their signals over time. Second, while concepts employed in human communication and turn-taking, such as intentionality, are still debated in animal behavior, lower level mechanisms with clear neurobiological bases can explain much of animal interactive behavior. Third, social behavior, interactivity, and cooperation can be orthogonal, and the alternation of animal signals need not be cooperative. Considering turn-taking a subset of chorusing in the rhythmic dimension may avoid overinterpretation and enhance the comparability of future empirical work.

Structural variants identified by Oxford Nanopore PromethION sequencing of the human genome

We sequenced the genome of the Yoruban reference individual NA19240 on the long-read sequencing platform Oxford Nanopore PromethION for evaluation and benchmarking of recently published aligners and germline structural variant calling tools, as well as a comparison with the performance of structural variant calling from short-read sequencing data. The structural variant caller Sniffles after NGMLR or minimap2 alignment provides the most accurate results, but additional confidence or sensitivity can be obtained by a combination of multiple variant callers. Sensitive and fast results can be obtained by minimap2 for alignment and a combination of Sniffles and SVIM for variant identification. We describe a scalable workflow for identification, annotation, and characterization of tens of thousands of structural variants from long-read genome sequencing of an individual or population. By discussing the results of this well-characterized reference individual, we provide an approximation of what can be expected in future long-read sequencing studies aiming for structural variant identification.