The evolutionary landscape of host immunity genes involved in respiratory and other immune-related diseases, and their association with severe COVID-19 outcomes

Background Given its high mortality and broad societal impacts, the COVID-19 pandemic is a particularly notable global outbreak of a respiratory illness in the 21st century. Although previous studies have identified several genes associated with COVID-19 susceptibility, relatively little is known about the genes contributing to severe COVID-19, including their evolutionary histories. In the current study, we analyzed IL-4, TLR2, CCL2, and SLC11A1—four immunity genes that have been implicated in severe COVID-19 and other immune-related diseases—in globally diverse populations from the 1000 Genomes Project. We also tested for associations between genetic variation in these genes and clinical COVID-19 phenotypes in more than 4,000 laboratory-confirmed COVID-19–positive individuals from Italy.

Based on our analyses, we identified 72 single nucleotide polymorphisms (SNPs) across these genes as targets of positive selection, including several derived alleles shared with archaic Neanderthal and/or Denisovan genomes—a finding not previously reported in the literature. Furthermore, we found that common SNPs—implicated in respiratory diseases such as tuberculosis and chronic obstructive pulmonary disorder—were also under selection. Functional predictions based on in silico analyses revealed that a subset of selected alleles map to transcription factor binding sites and are predicted to affect binding affinity. In addition, our genetic association analyses uncovered significant correlations between derived alleles in the coding region of TLR2 and COVID-19 severity. Interestingly, these candidate alleles occurred at relatively low frequency in western European and East Asian populations but were absent in populations of African and South Asian descent.

Overall, our study provides new insights into the evolution of biologically relevant immunity genes in the modern human lineage and highlights genetic variants that may underlie differential risk for severe COVID-19. Competing Interest Statement The authors have declared no competing interest. Funding Statement This work was supported by funds from the National Geographic Society [grant HJ-116ER-17] to C.N.C, the U.S. National Science Foundation (NSF) grant IOS-1355034, Howard University College of Medicine, and the District of Columbia Center for AIDS Research, an NIH funded program [P30AI117970] to T.H., as well as U.S. NSF grant BCS-2221924 and U.S. NSF grant BCS-2221920 to M.C.C. Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The genetic diversity data underlying this article are available in the 1000 Genomes Consortium Project at https://ftp.1000genomes.ebi.ac.uk/vol1/ftp/release/20130502/. The clinical datasets analyzed for the current study are available from GEN-COVID upon reasonable request. The GEN-COVID data were individual-level data that had been de-identified prior to use in the study. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Footnotes Figure 5 was revised, and the corresponding legend in the main manuscript was updated to clarify the figure; Table 1 was also revised along with the Table 1 legend in the main manuscript. Data availability The genetic diversity data underlying this article are available in the 1000 Genomes Consortium Project at https://ftp.1000genomes.ebi.ac.uk/vol1/ftp/release/20130502/. The clinical datasets analyzed for the current study are available from GEN-COVID upon reasonable request. Abbreviations - ACB - African Caribbeans in Barbados - ACE2 - Angiotensin-Converting Enzyme 2 - ANPEP - Alanyl Aminopeptidase - APC - Antigen-Presenting Cell - ARG - Ancestral Recombination Graph - ASW - African Ancestry in Southwest US - BEB - Bengali in Bangladesh - bp - Base Pair - CCL2 - C-C Motif Chemokine Ligand 2 - CCL3 - C-C Motif Chemokine Ligand 3 - CCBB - Center for Computational Biology and Bioinformatics - CDX - Chinese Dai in Xishuangbanna, China - CHB - Han Chinese in Beijing, China - CHS - Southern Han Chinese - CLUES2 - Composite Likelihood for Estimating Selection, version 2 - COVID-19 - Coronavirus Disease 2019 - CPAP - Continuous Positive Airway Pressure - CTSB - Cathepsin B - CTSL - Cathepsin L - CXCL10 - C-X-C Motif Chemokine Ligand 10 - DPP4 - Dipeptidyl Peptidase-4 - DNA - Deoxyribonucleic Acid - DT - Tajima’s D Statistic - EHH - Extended Haplotype Homozygosity - ER - Endoplasmic Reticulum - ESN - Esan in Nigeria - FIN - Finnish in Finland - FST - Fixation Index - FURIN - Furin Protease - GBR - British in England and Scotland - GEN-COVID - Genetic and Clinical Data Collection for COVID-19 - GIH - Gujarati Indian in Houston, Texas - GRCh37 - Genome Reference Consortium Human Build 37 - GRM - Genetic Relationship Matrix - GWD - Gambian in Western Division, The Gambia - H - Fay and Wu’s H Statistic - HBV - Hepatitis B Virus - HCV - Hepatitis C Virus - HIV - Human Immunodeficiency Virus - HLA - Human Leukocyte Antigen - IBD - Inflammatory Bowel Disease - IBS - Iberian population in Spain - ICU - Intensive Care Unit - IFN-α - Interferon-alpha - IFN-γ - Interferon-gamma - iHS - Integrated Haplotype Score - IL - Interleukin - IL-4 - Interleukin-4 - IL-6 - Interleukin-6 - IL-10 - Interleukin-10 - ITU - Indian Telugu in the UK - JPT - Japanese in Tokyo, Japan - KHV - Kinh in Ho Chi Minh City, Vietnam - LD - Linkage Disequilibrium - LWK - Luhya in Webuye, Kenya - MAF - Minor Allele Frequency - MSL - Mende in Sierra Leone - mRNA - Messenger RNA - nSL - Number of Segregating Sites by Length (haplotype-based test) - ORF - Open Reading Frame - PCA - Principal Component Analysis - PJL - Punjabi in Lahore, Pakistan - RNA - Ribonucleic Acid - SARS-CoV-2 - Severe Acute Respiratory Syndrome Coronavirus 2 - SLC11A1 - Solute Carrier Family 11 Member 1 - SNP - Single Nucleotide Polymorphism - SPA - Saddle Point Approximation - STU - Sri Lankan Tamil in the UK - TB - Tuberculosis - TF - Transcription Factor - TFBS - Transcription Factor Binding Site - TLR - Toll-like Receptor - TLR2 - Toll-like Receptor 2 - TMPRSS2 - Transmembrane Protease, Serine 2 - TMPRSS11D - Transmembrane Protease, Serine 11D - TSI - Toscani in Italy - UTR - Untranslated Region - VCF - Variant Call Format - YRI - Yoruba in Ibadan, Nigeria