MMS19 and IFIH1 Host Genetic Variants Associate with SARS-CoV-2 Infection in Elderly Residents of Long-Term Care Facilities

1. Introduction

The elderly population is particularly vulnerable to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and severe coronavirus disease 2019 (COVID-19)[1]. Specifically, residents of long-term care facilities (LTCFs) are at a higher risk of SARS-CoV-2 transmission and infection [2,3]. LTCF population density may account for this increased risk of transmission. Described risk factors for infection and disease severity are sex, age, ethnicity, obesity, and cardiovascular and respiratory diseases. Current vaccines have successfully reduced both SARS-CoV-2 transmission and COVID-19 severity [4,5]. However, the development of new tools to predict virus transmission and disease burden may improve current and future treatments, as well as disease prevention strategies. Several large-scale genetic association studies have consistently identified human host single nucleotide polymorphisms (SNPs) that are implicated in the biology and epidemiology of COVID-19 [6,7,8,9,10,11]. These studies suggest different mechanisms to explain why some individuals are more prone to infection by SARS-CoV-2 or being more severely affected by the disease upon infection[12,13]. Host genetics can inform us about disease etiology and provide new means for patient management. Population-specific risk variants have also been reported [8,14,15]. Due to the extreme importance of age as a risk factor for severe COVID-19, age should be considered in genetic analyses [12]. In this study, we aimed to identify host genetic factors influencing susceptibility to SARS-CoV-2 infection in LTCF residents. Our study included individuals infected and uninfected with SARS-CoV-2 early in the pandemic before initiation of vaccination.

2. Materials and Methods

2.1. Study Participants

A total of 97 residents of three LTCFs located in the area of Barcelona, Spain, were randomly included in this prospective observational study (CoronAVI@S study). Plasma samples were collected before vaccination through September-November 2020[12]. SARS-CoV-2 serology was performed to sub-classify participants into infected and uninfected individuals depending on their PCR and serology status.

2.2. Ethics

The CoronAVI@S study was approved by the Ethics Board of the Institut Universitari d’Investigació en Atenció Primària Jordi Gol (20-116P). All participants provided written informed consent before inclusion.

2.3. Single Nucleotide Polymorphism Genotyping

Genomic DNA was extracted from peripheral blood mononuclear cells using Quick Extract DNA Extraction 1.0 solution (Epicentre/Lucigen) as described previously [16]. Two microliters of extracted DNA were used for SNP genotyping (Applied Biosystems). The reference numbers of the TaqMan assays used for genotyping on a Quantstudio 5.0 from Applied Biosystems were ADAR1/rs1127313, C_8724398_10; IFIH1/rs1990760, C_2780299_30; MMS19/rs2236575, C_1797584_30; OAS-1/rs4767027, C_28015278_10; OAS-1/ rs10774671, C_2567433_10; OAS-2/rs1293767, C_8920276_10; OAS-3/rs10735079, C_31831768_10; IFNL3/rs12979860, C_7820464_10; IFNAR2/rs2236757, C_11354003_30; and PNPLA3/rs738409, C_7241_10. The SNPs IFNL3/rs4803217 and TNFAIP8L1/rs1060555 were determined using IDT DNA assay Hs.GT.rs4803217.A.1 and Hs.GT.rs1060555.G.1, respectively, and also assayed by Quantstudio 5.0 (Applied Biosystems).

2.4. Statistical Analysis

Haplotype estimation and association with patient susceptibility to SARS-CoV-2 infection were achieved using Haploview 4.2 (Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA) and SNPSTATS [17]. To enhance the robustness of our findings, we performed a bootstrap resampling with 100 interactions, and calculated empirical p-values as the proportion of times the observed p-value was greater than the p-value derived from the bootstrap resampling. Risk factors were included in the genetic analysis to adjust the association of each SNP to infection susceptibility. Hardy-Weinberg equilibrium, minor allele frequency, and SNP linkage disequilibrium (LD) were also determined by Haploview 4.2. Mann Whitney t and chi-squared tests to compare infected and uninfected individuals were performed using GraphPad Prism 9.0 (GraphPad Software, San Diego, California, USA).

3. Results

Study participants were tested by PCR during SARS-CoV-2 outbreaks at their respective LTCFs between September and November 2020. During this period, 81 of the participants tested positive for SARS-CoV-2 (80% female, mean age 87 years) and 16 tested negative (Table 1). The number of females was significantly higher in the infected group than the uninfected group (p = 0.0104). Only three infected individuals required hospitalization after acute infection. Interestingly, the 16 uninfected individuals remained seronegative for antibodies against the virus nucleoprotein until vaccination (January and February 2021)[18]. Table 1 shows the clinical and biochemical characteristics of the study patients. Compared with SARS-CoV-2-infected individuals, uninfected individuals had significantly higher glucose levels (Table 1). The higher glucose level in the uninfected group may be due to the higher number of diabetic individuals in this group (n=8/16) compared with the infected group (n=17/81; p = 0.0153, chi-squared). No other differences were found between infected and uninfected individuals.

For the entire cohort of 97 individuals, we analyzed 12 SNPs from 7 host genes previously associated with the innate immune response [9,10,11,16,19] or essential host cofactors involved in SARS-CoV-2 replication[20,21]. The observed allele SNP frequencies were characteristic of southern European populations. All of the variants had a minor allele frequency >0.01 and were in Hardy–Weinberg equilibrium (Table 2). The four SNPs in the OAS gene were in high LD (R2 > 0.81). The SNPs in the IFNL3 gene were also in high LD (R2 = 0.94). No other significant LD was observed among the other study SNPs. For the association analyses for each SNP, we adjusted for sex and age, identifying genetic associations between susceptibility to SARS-CoV-2 infection and two SNPs: MMS19/rs2236575 in the dominant model (odds ratio [OR] 6.57, 95% CI 0.80-53.87, p = 0.029) and over dominant model (OR 3.60, 95% CI 0.97-13.30, p = 0.041), and IFIH1/rs1990760 in the over dominant model (OR 3.57, 95% CI 1.04-12.29, p = 0.034; Table 2). After adjusting for multiple comparisons, by means of bootstrap techniques, MMS19/rs2236575 and IFIH1/rs1990760 remained significantly associated with susceptibility to SARS-CoV-2 infection (Table 2). In the unadjusted analysis, MMS19/rs2236575 was the only variant related to susceptibility to SARS-CoV-2 infection in the dominant (p = 0.022) and over dominant (p = 0.049) models.

4. Discussion

In this study, we tested the association between host genetic polymorphisms and susceptibility to SARS-CoV-2 infection. After adjusting for sex and age, we found that residents of LTCFs carrying genetic variants in MMS19/rs2236575 and IFIH1/rs1990760 were more refractory to SARS-CoV-2 infection.

The IFIH1/rs1990760 TT variant was previously reported to confer resistance to SARS-CoV-2 infection and explain the epidemiological features of the pandemic in different countries [22]. Importantly, COVID-19 patients with the IFIH1/rs1990760 TT variant have an attenuated inflammatory response and better outcomes[23]. The human gene IFIH1 encodes a helicase, melanoma differentiation-associated gene-5, which acts as a cytoplasmic virus receptor and triggers the transcription of type-1 interferon genes and the systemic inflammatory response. IFIH1/rs1990760 has been previously linked to bowel disease, type 1 diabetes, vitiligo, and liver disease progression in HIV-1 patients [16], [24].

In contrast to the IFIH1/rs1990760 variant, we are the first to describe a possible implication of MMS19/rs2236575 variants in susceptibility to SARS-CoV-2 infection. MMS19 is a component of the cytosolic iron-sulfur protein assembly machinery that transfers Fe/S clusters to various DNA metabolism-associated Fe/S proteins [25]. Whether MMS19/rs2236575 associates with loss-of-function (LOF) of MMS19 remains to be clarified. This LOF would then likely reduce ability of the virus to replicate because of its dependence on MMS19 for acquisition of its required iron sulfur cofactors. MMS19 is implicated in DNA replication and repair, and its deregulation has been linked to numerous human diseases, including cancer[26]. MMS19 degradation and its downregulation is a common feature in cancer and genomic stability and is evolutionarily controlled [27]. MMS19/rs2236575 has been explored as a possible marker of advanced epithelial ovarian cancer[28]. Finally, the MMS19 protein has been described as a potential cofactor of the SARS-CoV-2 RNA-dependent RNA polymerase[20]. The virus helicase (nonstructural protein 3) has a Fe/S cluster that modulates its RNA-binding and unwinding activities[21].

Isoforms in the Neanderthal haplotype on chromosome 12 in the gene encoding oligoadenylate synthetase (OAS) play a protective role for individuals of European ancestry against COVID-19 susceptibility and severity [9,10,11]. An additional finding of our study is that we did not find support for a protective role of OAS after interaction with SARS-CoV-2.

Although our findings require validation in larger cohorts, we identified two host genetic variants associated with susceptibility to SARS-CoV-2 infection in an elderly population. Current SARS-CoV-2 variants tend to cause mild symptoms, with few hospitalizations and deaths [13,29,30]. Nevertheless, our findings can lead to better understanding of SARS-CoV-2 infections.