Absence of association between host genetic mutations in the ORAI1 gene and COVID-19 fatality.

The calcium ion channel ORAI1 has emerged as a promising therapeutic target for the Coronavirus Disease 19 (COVID-19)-associated pneumonia, and a pharmacological inhibitor of ORAI1 has now reached clinical trials for severe COVID-19 pneumonia. Whether ORAI1 itself is associated with an increased risk for severe COVID-19 presentation is still unknown. Here, we employed genetic association analysis to investigate the potential association of host genetic polymorphisms of ORAI1 with the risk of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection and its associated COVID-19 fatality in UK Biobank participants from white British background. The analysis showed no significant association between ORAI1 variants and COVID-19 positivity or fatality, despite the well-established roles of ORAI1 in immune response and inflammation and the success of ORAI1 inhibition in clinical trials. Our results suggest that the host genetic polymorphisms of ORAI1 are unlikely to be implicated in the broad variability in symptoms severity among afflicted patients.

Background

The emergence of a new, fast-spreading infectious respiratory disease outbreak, at the end of 2019 has presented a global threat to public health with its fast transmission and serious multi-organ complications. The disease is caused by a new virus from the coronavirus species, designated as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), and the disease is now known as Coronavirus Disease 19 (COVID-19) [1]. The worldwide confirmed COVID-19 cases, as of 23 November 2021, have exceeded 256 million cases and accounts for around 5.1 million deaths [2]. SARS-CoV-2 is a new strain of coronavirus species, similar to SARS-CoV and MERS-CoV that caused more limited outbreaks in 2002 and 2012, respectively. SARS-CoV-2, however, appears to be less deadly compared to SARS-CoV and MERS-CoV but is more transmissible. COVID-19 patients have presented with wide-range of severe symptoms both within and beyond the respiratory system, ranging from no or mild symptoms, to severe acute pneumonia, respiratory failure, and could be even life threatening. COVID-19 was also reported to be associated with non-respiratory complications, including myocardial injury, multisystem inflammatory syndrome, and haematological and thrombotic complications [3-5]. To this end, there has always been a question regarding the source of this large range of variation in symptoms severity. Failure to answer this question has hindered the true identification of individuals at high risk of serious illness, as well as those who are likely to be asymptomatic carriers and unknowingly spreading the virus. To date, the pathophysiology underlying this varied manifestation of the disease is still elusive. Age [6, 7], gender [8], obesity [9], and comorbid conditions [7, 10, 11] appeared to be risk factors associated with adverse COVID-19 outcomes. Nonetheless, severe illness was worryingly observed in young, otherwise healthy, individuals [12, 13]. Discrepancies in disease burden and the risk of infection was also observed among the different ethnic groups [14-16]. A possible explanation of the substantial variation in susceptibility to SARS-CoV-2 virus and the wide unpredictability in COVID-19 manifestation is the variability in the host genetic background. In fact, emerging genome-wide association [17, 18] and candidate gene association [19] studies have revealed an association between a host genetic risk factor and the severity of COVID-19 illness.

Here, we investigate the host genetic polymorphisms within the ORAI1 gene that could be implicated in the genetic risk for SARS-CoV-2 infection and for the severity of COVID-19 symptoms. The ORAI1 gene located at the long arm of Chr12 at 12q24.31 is a gene encoding for the calcium ion channel ORAI1, which is the de facto pore forming ion channel mediating store operated calcium entry (SOCE). ORAI1 is an interesting candidate gene in the context of COVID-19 as it is known to play a key role in the immune response, inflammation, platelet activation and thrombus formation. As innate immune cell over-activation, an exacerbated inflammatory response and thrombosis were linked with adverse COVID-19 outcome, ORAI1 could potentially play a role in this over-exuberant immune response, thrombotic state and adverse outcome in cases with serious symptoms and therefore could be a promising therapeutic target for COVID-19. This is not a new suggestion. The pharmacological ORAI1 inhibitor Auxora, produced by CalciMedica, has reached clinical trials for severe COVID-19 pneumonia [20]. In a 2:1 randomized, open label trial of patients with severe COVID-19 pneumonia, the intravenous administration of Auxora, showed promising safety profile and favourable outcomes in patients with severe COVID-19 pneumonia. Its therapeutic benefits are currently being further investigated in a randomized, placebo-controlled, double-blind study. Mutations within ORAI1 originally manifested as severe combined immune deficiency (SCID) [21]. It is however still unknown if ORAI1 small nucleotide polymorphisms (SNPs) could be implicated in an increased risk of SARS-CoV-2 infection or COVID-19-associated fatality. Our aim is to study the implications of host genetic polymorphisms within the ORAI1 gene in the genetic risk for SARS-CoV-2 infection and for the severity of COVID-19 symptoms. This information could help identify individuals at high risk of adverse COVID-19 outcomes and reveal potential therapeutic target. Therefore, this candidate gene association study investigates the potential associations of polymorphisms within the ORAI1 gene and the susceptibility to SARS-CoV-2 infection as well as COVID-19 fatality in UK Biobank dataset.

Methods

Participants

UK Biobank dataset of participants tested for COVID-19 (January 2021 release) was utilised under UK Biobank accession number 60315. UK Biobank received ethical approval from the North West Multi-Centre Research Ethics Committee and was conducted in accordance with the principles of the Declaration of Helsinki. No separate ethical approval was required. This dataset comprises 47,988 participants tested for COVID-19. As the majority of participants are from British decent, the analysis was restricted to this group. After applying the filtering parameters, among the 41,146 individuals from British ancestor, 7,462 (18.1%) were reported to have been diagnosed with COVID-19, and 33,684 (81.9%) were negative controls. The death records of COVID-19 positive cases showed 332 (4.4%) COVID-19 deaths and 7,130 (95.6%) COVID-19 survivals. Participants’ characteristics are summarised in Table 1.

Table 1

Basic characteristics of the study participants.

Characteristics	All	COVID-19 Positive	COVID-19 Negative	COVID-19 Fatalities	Non-fatal COVID-19
n *	41146	7462	33684	332	7130
Mean age, years ± SD **	68.8 ± 8	68.8 ± 8.1	68.7 ± 8	69.1 ± 8.4	68.8 ± 8.1
Gender
Female, n (%)	22076 (53.65%)	3978 (53.3%)	18098 (53.7%)	181 (54.52%)	3797 (53.25%)
Male, n (%)	19070 (46.35%)	3484 (46.7%)	15586 (46.27%)	151 (45.48%)	3333 (46.75%)
Co-morbidities
Stroke, n (%)	770 (1.87%)	149 (2.0%)	621 (1.84%)	11 (3.31%)	138 (1.94%)
Hypertension, n (%)	12788 (31.08%)	2018 (27.04%)	10770 (31.97)	163 (49.1%)	1855 (26.02%)
Diabetes, n (%)	2520 (6.12%)	417 (5.59%)	2103 (6.24%)	52 (15.66%)	365 (5.12%)
Asthma, n (%)	5562 (13.52%)	1020 (%)	4542 (13.48%)	34 (10.24%)	986 (13.83%)
Heart/cardiac problem, n (%)	210 (0.51%)	38 (13.67%)	172 (0.51%)	4 (1.20%)	34 (0.48%)
Myocardial infarction, n (%)	1364 (3.32%)	229 (3.07%)	1135 (3.37%)	26 (7.83%)	203 (2.85%)
Chronic Obstructive pulmonary disease, n (%)	213 (0.52%)	39 (0.52%)	174 (0.52%)	3 (0.90%)	36 (0.50%)

*n, number of individuals,

**SD, standard deviation.

Genetic association analysis

UK Biobank imputed genomic data of Chr12 were obtained and variants with imputation quality (Info score) < 0.4 were filtered out. Details about UK Biobank genome-wide genotyping and the genotypes imputation were previously described in [22, 23]. Quality measures were applied to exclude participants with more than 10% missing data, exclude variants with Hardy-Weinberg equilibrium (HWE) less than 1x10-6 and exclude variants with minor allele frequency (MAF) less than 5% for common variants or less than 1% for less frequent variants, using PLINK version 2.0 software [24]. After applying the filtering parameters, 7,462 COVID-19 positive cases and 33,684 control cases were retained and eligible for downstream analyses. Filtered variants spanning Chr12 (312,261 variants) were then examined for genetic association with COVID-19 positivity and fatality (Fig 1). The Manhattan pots were generated using the qqman R package and the regional association plots were generated using LocusZoom (http://locuszoom.sph.umich.edu) [25].

Fig 1

Flowchart of the analysis pipeline.

ORAI1 variants associations with SARS-CoV-2 infection and COVID-19 fatality were examined in British UK Biobank participants. There was no significant association observed between ORAI1 variants and COVID-19 positivity or fatality.

Statistics

After adjusting for effects of sex, age, and the first ten principal components that conveys variations in population structure, the associations of variants within ORAI1 (chr12:122,064,455–122,080,583, GRCh37/hg19) with COVID-19 positivity (7,462 cases and 33,684 controls) and fatality (332 deaths and 7,130 controls) were examined using logistic regression, conducted using PLINK version 2.0 [24]. Bonferroni correction was applied on the P-value to adjust for the number of variants tested. Bonferroni corrected P-value of 0.05 was used as a threshold to indicate statistical significance.

Results

Participants characteristics

Data collected from 41,146 participants of British ancestry, tested for COVID-19, were obtained from the UK Biobank (Fig 1). Table 1 shows the basic characteristics of the study participants. The study participants were 46% males (average age 69) and 54% females (average age 68.6), with overall mean age of 68.8 years (age range from 50 to 84 years). In total, 332 COVID-19 deaths were reported, with mean age of 69.1 years, of which 45.5% are males with mean age of 69.8, and 54.5% are females with mean age of 68.7. On the other hand, non-fatal COVID-19 cases were 47% males (average age 69 years), and 53% females (average age 68.7 years) and all non-fatal cases had an average age of 68.8 years. We did not observe substantial differences between the mean age of fatal (69.1 ± 8.4 years) and non-fatal (68.8 ± 8.1 years) COVID-19 cases, which could be attributed to the confined age range of the participants between 50 and 84 years. Therefore, the younger age group with a lower risk of serious COVID-19 illness was not captured in our analysis. As expected, the incidence of comorbid conditions associated with severe COVID-19 symptoms was more common among fatal compared to non-fatal COVID-19, with 49.1% of fatal, 26.02% of non-fatal COVID-19 cases had concomitant hypertension, 3.31% of fatal and 1.94% of non-fatal cases were diagnosed with previous stroke, 15.66% of fatal while 5.12% of non-fatal COVID-19 cases were diagnosed with diabetes, 10.24% of fatal and 13.83% of non-fatal COVID-19 cases were diagnosed with asthma, and 7.83% of fatal, while 2.85% of non-fatal COVID-19 cases were diagnosed with myocardial infarction (Table 1).

SARS-CoV-2 infection and COVID-19 fatality

The genetic variants within the ORAI1 gene were examined for association with COVID-19 positivity. There was no statistically significant association between SNPs within the ORAI1 locus and SARS-CoV-2 infection (Fig 2, Table 2). We then examined the association between ORAI1 variants and COVID-19 fatality. The analysis was performed in 332 fatal and 7130 non-fatal COVID-19 cases. There was also no significant association between ORAI1 variants and COVID-19 fatality (Fig 3, Table 3), despite its role in immune cell function and the promising outcome of ORAI1 inhibition in the randomized, controlled, open-label study conducted in patients with severe or critical COVID-19 pneumonia [20]. We did not observe significant association between common variants with MAF > 5% or less frequent variants with MAF > 1% in the ORAI1 gene with COVID-19 positivity or fatality in the examined participants.

Fig 2

Candidate gene association analysis of the ORAI1 locus in SARS-CoV-2 positive cases.

Manhattan plot showing the association of SNPs located within Chr12 with SARS-CoV-2 positivity. The red line indicates a P value of 0.05. Regional association plot at 12q24 showing the SNPs within the region comprising the ORAI1 locus. SNPs are plotted according to their chromosomal position on build GRCh37/hg19 displayed on the x-axis and the–log10 scale of the P-value of their association with SARS-CoV-2 positivity, plotted on the left y-axis. The right y-axis displays the recombination rate estimated from the 1000 Genomes European data.

Table 2

The association of common ORAI1 variants with MAF more than 5% with SARS-CoV-2 positivity.

SNP ID	REF	ALT	OR	LOG(OR)_SE	L95	U95	Z_STAT	P
rs7963749	C	G	1.04	0.04	0.96	1.12	0.97	0.33
rs6486786	T	C	1.02	0.02	0.98	1.05	0.87	0.38
rs6486787	G	C	0.99	0.02	0.94	1.03	-0.56	0.58
rs6486789	T	C	1.02	0.02	0.98	1.05	0.82	0.42
rs7135617	T	G	1.02	0.02	0.98	1.05	0.85	0.39
rs7484839	C	T	0.98	0.03	0.93	1.03	-0.91	0.36
rs7968061	T	C	0.98	0.03	0.93	1.03	-0.83	0.41
rs3892486	G	A	0.97	0.03	0.92	1.02	-1.08	0.28
rs7956644	G	A	0.99	0.02	0.94	1.03	-0.53	0.60
rs6486790	A	G	0.99	0.02	0.94	1.03	-0.52	0.61
rs7398511	C	A	0.98	0.02	0.94	1.03	-0.71	0.48
rs10522094	C	CAGGG	1.02	0.02	0.98	1.05	0.86	0.39
rs139720017	G	GT	1.03	0.03	0.97	1.10	1.02	0.31
rs12300327	A	G	0.99	0.02	0.94	1.03	-0.58	0.56
rs6486795	T	C	0.99	0.02	0.95	1.04	-0.38	0.70
rs11043296	C	T	0.98	0.03	0.93	1.03	-0.91	0.36
rs11043305	G	A	1.03	0.03	0.97	1.09	0.98	0.33
rs11043306	T	C	0.98	0.03	0.93	1.03	-0.91	0.36
rs3741595	C	T	0.99	0.02	0.94	1.03	-0.59	0.56
rs3825175	T	C	1.02	0.02	0.98	1.05	0.87	0.39
rs712853	A	G	1.03	0.02	0.99	1.08	1.61	0.11
rs35558190	A	AT	0.98	0.02	0.94	1.03	-0.66	0.51
rs1983268	G	A	1.03	0.02	0.99	1.08	1.56	0.12

REF, reference allele; ALT, alternative allele; OR, Odds Ratio; L95, lower 95% confidence interval; U95, upper 95% confidence interval.

Fig 3

Association analysis of variants within the ORAI1 locus with COVID-19 fatality.

Manhattan plot showing the association of SNPs located within Chr12 with COVID-19 fatality. The red line indicates a P-value of 0.05. Regional association plot at 12q24 showing the SNPs within the region comprising the ORAI1 locus. SNPs are plotted according to their chromosomal position on build GRCh37/hg19 displayed on the x-axis and the–log10 scale of the P-value of their association with COVID-19 fatality, plotted on the left y-axis. The right y-axis displays the recombination rate estimated from the 1000 Genomes European data.

Table 3

Non-significant association of common ORAI1 variants with MAF more than 5% with COVID-19 fatality.

SNP ID	REF	ALT	OR	LOG(OR)_SE	L95	U95	Z_STAT	P
rs7963749	C	G	1.09	0.17	0.79	1.52	0.54	0.59
rs6486786	T	C	0.91	0.08	0.78	1.07	-1.15	0.25
rs6486787	G	C	0.94	0.10	0.76	1.15	-0.60	0.55
rs6486789	T	C	0.92	0.08	0.78	1.08	-1.03	0.30
rs7135617	T	G	0.90	0.08	0.77	1.06	-1.25	0.21
rs7484839	C	T	0.97	0.12	0.77	1.22	-0.23	0.81
rs7968061	T	C	0.98	0.11	0.79	1.22	-0.18	0.86
rs3892486	G	A	0.99	0.11	0.79	1.23	-0.13	0.90
rs7956644	G	A	0.94	0.11	0.76	1.15	-0.60	0.55
rs6486790	A	G	0.94	0.11	0.76	1.15	-0.61	0.54
rs7398511	C	A	0.93	0.11	0.75	1.15	-0.65	0.51
rs10522094	C	CAGGG	0.92	0.08	0.79	1.09	-0.96	0.34
rs139720017	G	GT	1.14	0.13	0.89	1.47	1.03	0.30
rs12300327	A	G	0.94	0.10	0.76	1.15	-0.59	0.55
rs6486795	T	C	0.99	0.10	0.81	1.20	-0.10	0.92
rs11043296	C	T	0.97	0.12	0.77	1.22	-0.23	0.82
rs11043305	G	A	1.13	0.13	0.88	1.45	0.93	0.35
rs11043306	T	C	0.97	0.12	0.77	1.22	-0.23	0.82
rs3741595	C	T	0.93	0.11	0.75	1.16	-0.66	0.51
rs3825175	T	C	0.89	0.08	0.76	1.05	-1.42	0.16
rs712853	A	G	0.91	0.09	0.76	1.09	-1.03	0.30
rs35558190	A	AT	0.93	0.11	0.75	1.15	-0.68	0.49
rs1983268	G	A	0.90	0.10	0.75	1.09	-1.06	0.29

REF, reference allele; ALT, alternative allele; OR, Odds Ratio; L95, lower 95% confidence interval; U95, upper 95% confidence interval.

Discussion

Defining the host genetic polymorphisms that contributes to COVID-19 severity could help unravel causes of the observed inter-individual variability of COVID-19 symptoms and death. This could help aid genetic counselling for our afflicted patients and improve our preventative strategies. We investigated the potential association between polymorphisms within the candidate gene, ORAI1, with the susceptibility to SARS-CoV-2 infection and the disease-associated fatality in UK Biobank white British participants. We observed no significant association between ORAI1 variants and COVID-19 positivity or fatality in our examined population.

The human Chr12 harbours over 1,400 protein coding genes, and a number of them are implicated in immune response and inflammation, which are essential processes to fight any infection, including SARS-CoV-2 infection [26]. Among the genes located on Chr12 is the ORAI1 gene that encodes for the SOCE ORAI1 channel. The main reported clinical manifestation of the ORAI1 loss-of-function mutations in patients is immunodeficiency resulting from impaired T cell activation and cytokine production [21, 27, 28], which highlights the fundamental role of ORAI1 in immune response against pathogens. ORAI1 channel activity was also shown to be a major player in inflammation and cytokine production [29]. This implication of ORAI1 channels in inflammation was previously observed in pulmonary endothelial cell injury, increased pulmonary permeability and alveolar-vascular barrier dysfunction [30-32]. The linkage between ORAI1, the immune, and inflammatory responses, as well as the fact that strong evidence implicates a hyper-inflammatory state in the adverse COVID-19 outcome [33, 34], foreshadow a potential role of ORAI1 in the pro-inflammatory cytokine storm reported in severe COVID-19 illness. This is further supported by the positive outcomes observed in clinical trial of the ORAI1 inhibitor Auxora in patients with severe COVID-19 pneumonia [20].

The well-established roles of ORAI1 in immune response and inflammation rendered it as a promising candidate gene that could be implicated in an altered susceptibility to COVID-19 positivity and disease severity. This important role in immune cell function and inflammation motivated us to examine the potential association between ORAI1 polymorphisms and the severity of COVID-19 illness. Nonetheless, there was no significant association observed between ORAI1 variants and COVID-19 positivity or fatality in British UK Biobank participants, which could be attributed to the small number of cases in the study. The observed absence of genetic association between ORAI1 variants and COVID-19 fatality does not eliminate the possible implication of ORAI1 in disease pathogenesis through altered gene expression levels or channel activity and therefore it does not eliminate the potential usefulness of targeting ORAI1 as a therapeutic target for COVID-19. Our analysis was constrained to participants from white British (Caucasian) background, due to the small number of cases from other ethnic groups in this dataset. Therefore, an impact of ORAI1 variants on COVID-19 fatality in different ethnic groups cannot be ruled out. Further studies are needed to investigate whether ORAI1 polymorphisms influence the susceptibility to COVID-19 positivity or fatality in different ethnic populations. Additionally, the age range of the participants was confined to age 50–84 years and did not include the younger age group with the lower risk of adverse COVID-19 illness. Because of these geographical, ethnic and age limitations, our finding may not reflect the wider more diverse population. Our analysis was also limited by the lack of information about the vaccination status of the participants and about the prevalence of the SARS-CoV-2 variants of concern in the examined population. Further research is still needed to understand the role of ORAI1 in severe COVID-19 illness and to investigate the potential genetic association of ORAI1 variants and adverse COVID-19 outcome in different populations.

3 Nov 2021

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Reviewer #1: Study based on a biobank dataset to clarify the role of genetic variants within the ORAI1 gene with positivity and mortality for COVID-19. The study design is not clear, the authors do not accurately describe what the main objective is; these aspects should be better defined.

The results demonstrate that there is no significant association between ORAI1 variants and COVID-19 positivity or fatality in the study participants, despite the well-established roles of ORAI1 in immune response and inflammation and the successful inhibition of ORAI1 in clinical studies. Authors should explain the reason for this discrepancy in more detail than they have already done.

Reviewer #2: I am grateful for the chance to review this work by Heba and coworker. The authors retrospectively employed genetic association analysis to investigate the potential association of host genetic 18 polymorphisms of ORAI1 with the risk of developing COVID-19 with COVID-19 fatality in 41146 with British individuals. They found that there was no significant association observed between ORAI1 199 variants and COVID-19 positivity or fatality.

The research question is extremely appealing being the susceptibility to SARS-CoV-2 virus quite unpredictable and given the promising results of the ORAI1 inhibitor in patients with COVID-19. Since study aim is extremely relevant, methodological procedures are correct and statistical analysis is well described and convincing. Manuscript sections are well organized and clear.

I just have a few issues to address:

1) Introduction: in my opinion it should be shortened and focused on the research question.

2) Methods: the frequency of ORAI1 SNpolymorphism should be detailed and considered to estimate a sample large enough to test the research question.

3) Methods: did the authors collected data regarding SARS-CoV-2 major variants? If so, wouldn’t it be interesting to test whether an association with ORAI1 SNP could be find?

4) Methods: the authors should report the percentage of vaccinated people.

4) Results: it is surprising that COVID-19 fatal and non-fatal case have similar average age, gender distribution and hypertension rate. These data are in contrast with the great majority of results reported in literature and should be discussed in more details.

5) Results: Data regarding the prevalence of hearth problem in the COVID-19 fatality group should be checked (just 1 over 332?).

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Reviewer #1: No

Reviewer #2: No

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3 Dec 2021

Dear Dr Marchioni,

Thank you for allowing us to respond and provide a revised manuscript to PLOS ONE. We are grateful to Reviewer #1 and Reviewer #2 for the constructive comments, which after addressing, the quality of the manuscript has significantly improved. We have responded to each comment and submitted a tracked version of the manuscript.

Thank you once again for allowing us to resubmit this revised and improved manuscript.

Yours sincerely,

Heba Shawer on behalf of all authors

Editor

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming.

Response: The manuscript style requirements were reviewed in the manuscript.

2. In your Data Availability statement, you have not specified where the minimal data set underlying the results described in your manuscript can be found. PLOS defines a study's minimal data set as the underlying data used to reach the conclusions drawn in the manuscript and any additional data required to replicate the reported study findings in their entirety. All PLOS journals require that the minimal data set be made fully available. For more information about our data policy, please see http://journals.plos.org/plosone/s/data-availability

Response: Thanks for your comments. The following Data Availability Statement describes where the data set underlying the analysis can be found.

“The data underlying the results presented in the study are available from the UK Biobank on application via the UK Biobank online access management system (http://www.ukbiobank.ac.uk).”

3. Thank you for stating the following in the Acknowledgments Section of your manuscript: “This work was supported by British Heart Foundation fellowships to MAB and HS (FS/18/12/33270, FS/17/66/33480) and Leeds Cardiovascular Endowment support to CWC. This work was conducted using UK Biobank datasets. We thank the UK Biobank participants and staff. This work was undertaken on ARC3, part of the High-Performance Computing (HPC) facilities at the University of Leeds, UK.”

Response: We appreciate the comments. The funding statement is now removed from the Acknowledgments Section to be only stated in the Funding Section.

Reviewer #1

1. Study based on a biobank dataset to clarify the role of genetic variants within the ORAI1 gene with positivity and mortality for COVID-19. The study design is not clear, the authors do not accurately describe what the main objective is; these aspects should be better defined.

Response: We have more clearly defined the rationale for the study, the design and our objective on page 3, line 73-79, in the untracked version of the revised manuscript.

2. The results demonstrate that there is no significant association between ORAI1 variants and COVID-19 positivity or fatality in the study participants, despite the well-established roles of ORAI1 in immune response and inflammation and the successful inhibition of ORAI1 in clinical studies. Authors should explain the reason for this discrepancy in more detail than they have already done.

Response: We added the following clarification in the discussion to explain the potential reasons for not finding significant evidence that ORAI1 variants influence the susceptibility to COVID-19 positivity or fatality.

“This absence of genetic association between ORAI1 variants and COVID-19 fatality doesn’t eliminate the possible implication of ORAI1 in disease pathogenesis through altered gene expression levels or channel activity and therefore it does not eliminate the potential usefulness of targeting ORAI1 as a therapeutic target for COVID-19. Our analysis was constrained to participants from White British (Caucasian) background, due to the small number of cases from other ethnic groups in this data set, and therefore possible implication of ORAI1 variants in COVID-19 fatality in different ethnic groups couldn’t be ruled out. Further studies are needed to investigate whether ORAI1 polymorphisms influence the susceptibility to COVID19 positivity or fatality in different ethnic populations. Additionally, the age range of participants was confined to age 50–84 years and didn’t include the younger age group with the lower risk of adverse COVID-19 illness. Because of these geographical, ethnic and age limitations, our finding may not reflect the wider more diverse population.” Page 10-11, Line 199-211 in the untracked version of the revised manuscript.

Reviewer #2

1. Introduction: in my opinion it should be shortened and focused on the research question.

Response: We have now shorted the introduction for brevity.

2. Methods: the frequency of ORAI1 SNP polymorphism should be detailed and considered to estimate a sample large enough to test the research question.

Response: To evaluate the effect of the variants frequencies in this locus, we included in our analysis the ORAI1 common variants with minor allele frequency more than 5%, as well as the less frequent variants with minor allele frequency more than 1%. We found no significant evidence that either the common (MAF > 5%) or rare (MAF > 1%) variants influence the susceptibility to COVID-19 positivity or fatality. We have added the following remarks to the revised manuscript to highlight this point.

“We did not observe significant association between common variants with MAF > 5% or less frequent variants with MAF > 1% in the ORAI1 gene with COVID-19 positivity or fatality in the examined population.” Page 7, Lines 145-147 in the untracked version of the revised manuscript.

3. Methods: did the authors collected data regarding SARS-CoV-2 major variants? If so, wouldn’t it be interesting to test whether an association with ORAI1 SNP could be find?

Response: We appreciate reviewer’s suggestion. Although it is interesting to link ORAI1 SNPs with the major SARS-CoV-2 variants, these data are currently not available in the UK Biobank database. Therefore, studying the association between ORAI1 SNPs in this cohort and SARS-CoV-2 variants is currently not possible. We added the following remarks in the discussion to highlight this limitation in the revised manuscript.

“Our analysis was also limited by the lack of information about the vaccination status of the participants and about the prevalence of the SARS-CoV-2 variants of concern in the examined population.” Page 11, Lines 211-213 in the untracked version of the revised manuscript.

4. Methods: the authors should report the percentage of vaccinated people.

Response: This genetic data is approved and provided by Public Health England through UK Biobank. Unfortunately, the vaccination data is yet to be made available to the scientific community. We appreciate this could be a limitation in the study. This limitation is now highlighted in the manuscript. Page 11, Lines 211-213 in the untracked version of the revised manuscript.

5. Results: it is surprising that COVID-19 fatal and non-fatal case have similar average age, gender distribution and hypertension rate. These data are in contrast with the great majority of results reported in literature and should be discussed in more details.

Response: it is true that the age, gender and number of cases with hypertension were comparable in the COVID-19 fatal and non-fatal groups. This could be attributed to the fact that the UK Biobank dataset contains the genetic data for individuals aged between 50 to 84 and only a subset of COVID-19 data was released at the time of analysis. To clarify this and recognise the limitations, we added the following remarks to the revised manuscript.

“We did not observe substantial differences between the mean age of fatal (69.1 ± 8.4 years) and non-fatal (68.8 ± 8.1 years) COVID-19 cases, which could be attributed to the confined age range of the participants between 50 and 84 years. Therefore, the younger age group with a lower risk of serious COVID-19 illness was not captured in our analysis.”. Page 5, Lines 120-124 in the untracked version of the revised manuscript..

“The age range of participants was confined to age 50–84 years and didn’t include the younger age group with the low risk of adverse COVID-19 illness. Because of these geographical, ethnic and age limitations of the examined dataset, our finding may not reflect the wider more diverse population.” Page 11, Lines 208-211 in the untracked version of the revised manuscript.

6. Results: Data regarding the prevalence of hearth problem in the COVID-19 fatality group should be checked (just 1 over 332?).

Response: Thanks for your comment. We have noticed a calculation error that attributes to this low number of cases with heart problem. We took the opportunity to correct this error and further examine the prevalence of additional more specific and relevant co-morbidities (Myocardial infarction and Chronic Obstructive pulmonary disease) in the examined population. Table 1 with the basic characteristics of the study participants is now updated. Page 6-7 in the untracked version of the revised manuscript.

Table 1. Basic characteristics of the study participants

characteristic All COVID-19 Positive COVID-19 Negative COVID-19 Fatalities Non-fatal COVID-19

N* 41146 7462 33684 332 7130

Mean age, years ± SD** 68.8 ± 8 68.8 ± 8.1 68.7 ± 8 69.1 ± 8.4 68.8 ± 8.1

Gender

Female, n (%) 22076 (53.65%) 3978 (53.3%) 18098(53.7%) 181 (54.52%) 3797 (53.25%)

Male, n (%) 19070 (46.35%) 3484 (46.7%) 15586 (46.27%) 151 (45.48%) 3333 (46.75%)

Co-morbidities

Stroke, n (%) 770 (1.87%) 149 (2.0%) 621 (1.84%) 11 (3.31%) 138 (1.94%)

Hypertension, n (%) 12788 (31.08%) 2018 (27.04%) 10770 (31.97) 163 (49.1%) 1855 (26.02%)

Diabetes, n (%) 2520 (6.12%) 417 (5.59%) 2103 (6.24%) 52 (15.66%) 365 (5.12%)

Asthma, n (%) 5562 (13.52%) 1020 (%) 4542 (13.48%) 34 (10.24%) 986 (13.83%)

Heart/cardiac problem, n (%) 210 (0.51%) 38 (13.67%) 172 (0.51%) 4 (1.20%) 34 (0.48%)

Myocardial infarction, n (%) 1364 (3.32%) 229 (3.07%) 1135 (3.37%) 26 (7.83%) 203 (2.85%)

Chronic Obstructive pulmonary disease, n (%) 213 (0.52%) 39 (0.52%) 174 (0.52%) 3 (0.90%) 36 (0.50%)

*N, number of individuals, **SD, standard deviation

Submitted filename: Response to Reviewers_1.docx

Click here for additional data file.

17 Jan 2022

Absence of association between host genetic mutations in the ORAI1 gene and COVID-19 fatality

PONE-D-21-24713R1

Dear Dr. Bailey,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Alessandro Marchioni

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Dear Professor Bailey,

I am pleased to inform that your paper "Absence of association between host genetic mutations in the ORAI1 gene and COVID-19 fatality" has been revised and considered suitable for publication in PLOS ONE.

CRAC channels have a critical role in the activation of T lymphocytes, and mutations in either Orai1 or STIM1 are characterized by severe immunodeficiency (SCID)-like disease and autoimmunity. Therefore, considering severe COVID-19 the results of a immune response dysregulation, the potential association of genetic polymorphisms of ORAI1 with the risk of Severe Acute Respiratory Syndrome related to SARS-CoV-2 (CARDS) is a relevant topic. Although the authors results suggest that in COVID-19 the host genetic polymorphisms of ORAI1 are unlikely to be implicated in symptoms severity among afflicted patients, we think that the informations provided in the paper could increases the knowledge about this complex disease.

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: (No Response)

Reviewer #2: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors answered my queries. Even in the presence of significant limitations of the study, I have no other comments to make and it can be published in its current form.

Reviewer #2: I would like to thank the Authors for their responses to my comments. I have no more comments to make.

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Reviewer #1: No

Reviewer #2: Yes: Roberto Tonelli

27 Jan 2022

PONE-D-21-24713R1

Absence of association between host genetic mutations in the ORAI1 gene and COVID-19 fatality

Dear Dr. Bailey:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

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on behalf of

Dr. Alessandro Marchioni

Academic Editor

PLOS ONE