SARS-CoV-2 positivity rates associated with circulating 25-hydroxyvitamin D levels.

Until treatment and vaccine for coronavirus disease-2019 (COVID-19) becomes widely available, other methods of reducing infection rates should be explored. This study used a retrospective, observational analysis of deidentified tests performed at a national clinical laboratory to determine if circulating 25-hydroxyvitamin D (25(OH)D) levels are associated with severe acute respiratory disease coronavirus 2 (SARS-CoV-2) positivity rates. Over 190,000 patients from all 50 states with SARS-CoV-2 results performed mid-March through mid-June, 2020 and matching 25(OH)D results from the preceding 12 months were included. Residential zip code data was required to match with US Census data and perform analyses of race/ethnicity proportions and latitude. A total of 191,779 patients were included (median age, 54 years [interquartile range 40.4-64.7]; 68% female. The SARS-CoV-2 positivity rate was 9.3% (95% C.I. 9.2-9.5%) and the mean seasonally adjusted 25(OH)D was 31.7 (SD 11.7). The SARS-CoV-2 positivity rate was higher in the 39,190 patients with "deficient" 25(OH)D values (<20 ng/mL) (12.5%, 95% C.I. 12.2-12.8%) than in the 27,870 patients with "adequate" values (30-34 ng/mL) (8.1%, 95% C.I. 7.8-8.4%) and the 12,321 patients with values ≥55 ng/mL (5.9%, 95% C.I. 5.5-6.4%). The association between 25(OH)D levels and SARS-CoV-2 positivity was best fitted by the weighted second-order polynomial regression, which indicated strong correlation in the total population (R2 = 0.96) and in analyses stratified by all studied demographic factors. The association between lower SARS-CoV-2 positivity rates and higher circulating 25(OH)D levels remained significant in a multivariable logistic model adjusting for all included demographic factors (adjusted odds ratio 0.984 per ng/mL increment, 95% C.I. 0.983-0.986; p<0.001). SARS-CoV-2 positivity is strongly and inversely associated with circulating 25(OH)D levels, a relationship that persists across latitudes, races/ethnicities, both sexes, and age ranges. Our findings provide impetus to explore the role of vitamin D supplementation in reducing the risk for SARS-CoV-2 infection and COVID-19 disease.

Introduction

Studies suggest an association between vitamin D deficiency and risk of viral upper respiratory tract infections and mortality from coronavirus disease-2019 (COVID-19) [1, 2]. This relationship is anticipated, given that vitamin D has numerous actions affecting the innate and adaptive immune systems. Respiratory monocytes/macrophages and epithelial cells constitutively express the vitamin D receptor. Acting through this receptor, vitamin D may be important in protection against respiratory infections [3]. In addition, an important action of vitamin D is suppressing excessive cytokine release that can present as a “cytokine storm,” a common cause of COVID-19-related morbidity and mortality [4]. The role of vitamin D supplementation in reducing the risk of infection by severe acute respiratory disease coronavirus-2 (SARS-CoV-2) has not been studied. Better understanding of the relation between vitamin D status and SARS-CoV-2 NAAT positivity rates is appropriate before evaluating this potential intervention.

Previous studies examined latitude-related differences in COVID-19 outcomes related to vitamin D [1, 5]. However, to our knowledge, only two studies investigated the direct relationship between vitamin D status and SARS-CoV-2 positivity, and these came to opposite conclusions [6, 7]. Both were based on small numbers of paired SARS-CoV-2 and 25(OH)D results, and neither involved US patients. In this study, we evaluated the association of circulating 25-hydroxyvitamin D [25(OH)D] levels, a measure of vitamin D status, with positivity for SARS-CoV-2 as assessed with nucleic acid amplification testing (NAAT).

Methods

Study population

In this retrospective, observational analysis of deidentified test results from a clinical laboratory, a Quest Diagnostics-wide unique patient identifier was used to match all results of SARS-CoV-2 testing performed March 9 through June 19, 2020, with 25(OH)D results from the preceding 12 months. Analysis was limited to one SARS-CoV-2 result per patient; patients were considered to have a positive SARS-CoV-2 result if any test result indicated positivity. When multiple 25(OH)D results were available, the most recent was selected. We excluded specimens with inconclusive results (one out of two SARS-CoV-2 targets detected) or missing residential zip code data, which are needed to assign race/ethnicity proportions and latitude.

Laboratory methods

All SARS-CoV-2 RNA NAATs were performed by Quest Diagnostics using one of four United States Food and Drug Administration (FDA) Emergency Use Authorized tests (Quest Diagnostics SARS-CoV-2 RNA [COVID-19], Qualitative NAAT; Hologic Panther Fusion SARS-CoV-2 assay; Roche Diagnostics cobas® SARS-CoV-2 test; or Hologic Aptima SARS-CoV-2 assay). We combined results from all four tests due to their very similar sensitivity and specificity [8-11]. Total 25(OH)D was measured using a chemiluminescent immunoassay (DiaSorin LIAISON® XL 25-hydroxyvitamin D, total) or a laboratory-developed test based on liquid chromatograph/tandem mass spectrometry. The laboratory categorizes 25(OH)D results <20 ng/mL as deficient, 20–29 ng/mL as suboptimal, and ≥30 ng/mL as optimal. The laboratory assays are standardized and performed identically throughout Quest Diagnostics.

Estimates by zip code

To analyze race/ethnicity, patient data were linked to estimated race/ethnicity proportions reported by zip code in the 2018 5-year American Community Survey (ACS) [12]. Zip codes with estimated proportions of black non-Hispanic population over 50% are referred to as “predominately black non-Hispanic.” The same pattern was followed for “predominantly Hispanic” and “predominantly white non-Hispanic” zip codes. Latitude for each zip code, acquired from SAS reference data, was stratified into three groups: >40 degrees (“northern”); 32–40 degrees (“central”); or <32 degrees (“southern”).

Vitamin D seasonality adjustment

We adjusted for vitamin D seasonality with a model based on a previous 25(OH)D3 study, utilizing Quest Diagnostics results that fit the present study data well [13].

Statistical analyses

Comparisons of proportions were analyzed using the chi-square test. Comparisons of means were analyzed using the t-test. Concentrations of circulating 25(OH)D are reported in ng/mL. Values <20 ng/mL or ≥60 ng/mL were assigned a value of 19 ng/mL or 60 ng/mL, respectively. Age was stratified into two groups: <60 years and ≥60 years for convenience. The correlation between 25(OH)D values and SARS-CoV-2 positivity were fitted the best by the weighted second-order polynomial regression. For regressions of predominately black non-Hispanic and Hispanic zip codes, 25(OH)D values were grouped into bins with two values from 20–29 (20–21, 22–23, etc.), and bins with 5 values thereafter (30–34, 35–39, etc.), because of the relatively low number of patients with 25(OH)D values ≥30. For all other polynomial regressions, 25(OH)D values were grouped into bins with two values. Multivariable logistic regression was performed using a stepwise entry criterion of p<0.05, after excluding patients with missing values for any included factor. Analyses were performed using SAS Studio 3.6 on SAS 9.4 (SAS Institute) and R, version 3.6.1 (R Project for Statistical Computing). HIPAA clearly defines research use of data as analyzed for this and numerous other studies based on the Quest Diagnostics Data Informatics Warehouse (45 CFR 164.501, 164.508, 164.512(i) (See also 45 CFR 164.514(e), 164.528, 164.532) Quest Diagnostics takes the additional step of having its process reviewed annual by the Western Institutional Review Board (Puyallup, Washington) who has determined the process is “deemed exempt.”

Results

Our potential cohort included 218,372 patients. After excluding patients with missing residential zip code data (n = 26,387) or inconclusive SARS-CoV-2 NAAT results (n = 206), results from 191,779 (87.8%) patients remained for analysis. This cohort comprised patients from all 50 states and the District of Columbia. The median age and sex distribution of included and excluded patients were nearly identical: age, 54.0 years, IQR 40.4–64.7, vs. 53.7 years, IQR 39.7–64.5, and female, 68% vs. 67%, respectively. SARS-CoV-2 positivity was lower among included (9.3%, 95% C.I. 9.2–9.5%) than excluded (10.1%, 95% C.I. 9.7–10.4%) patients (p<0.001). 98.8% of included patients had 25(OH)D levels assessed with immunoassay testing methodology.

There was an association between lower SARS-CoV-2 positivity rates and higher circulating 25(OH)D levels (unadjusted odds ratio 0.979 per 1 ng/mL increment, 95% C.I. 0.977–0.980). Regression analysis indicated strong correlation (R-squared = 0.96) between 25(OH)D levels and SARS-CoV-2 positivity in the total population (Fig 1) and in northern, central, and southern latitudes (Fig 2A). The decrease in positivity rate associated with 25(OH)D levels appeared to plateau as values approached 55 ng/mL; SARS-CoV-2 positivity rates were similar between the 4,016 patients with values 55–59 ng/mL (6.0%, 95% C.I. 5.2–6.7%) and the 8,305 patients with higher values (5.9%, 95% C.I. 5.4–6.4%). The SARS-CoV-2 positivity rate was lower in the 27,870 patients with “adequate” 25(OH)D values (30–34 ng/mL) (8.1%, 95% C.I. 7.8–8.4%) than in the 39,190 patients with “deficiency” (<20 ng/mL) (12.5%, 95% C.I. 12.2–12.8%) (difference 35%; p<0.001). Similarly, the SARS-CoV-2 positivity rate was lower in the 12,321 patients with 25(OH)D values ≥55 ng/mL (5.9%, 95% C.I. 5.5–6.4%) than in patients with adequate values (difference 27%; p<0.001).

Fig 1

SARS-CoV-2 NAAT positivity rates and circulating 25(OH)D levels in the total population.

Smooth line represents the weighted second order polynomial regression fit to the data associating circulating 25(OH)D levels (x) and SARS-CoV-2 positivity rates (y) where: y = 0.2029–0.0052*x + 4.8e-05*x2; R2 = 0.96. SI conversion factor: 1 ng/mL = 0.400641 nmol/L.

Fig 2

SARS-CoV-2 NAAT Positivity Rates and Circulating 25(OH)D Levels, (A) by Latitude Region and (B) Predominately Black non-Hispanic, Hispanic, and White non-Hispanic Zip Codes. Smooth lines represent the weighted second order polynomial regression fit to the data associating circulating 25(OH)D levels (x) and SARS-CoV-2 positivity rates (y) where: Northern: y = 0.2544–0.0055*x + 5.2e-05*x2; R2 = 0.94. Central: y = 0.1745–0.0049*x + 4.7e-05*x2; R2 = 0.94. Southern: y = 0.1693–0.0052*x + 5.2e-05*x2; R2 = 0.90. Black non-Hispanic: y = 0.2948–0.0067*x + 5.8e-05*x2; R2 = 0.87. Hispanic: y = 0.2873–0.0083*x + 8.5e-05*x2; R2 = 0.95. White non-Hispanic: y = 0.1219–0.0021*x + 1.5e-05*x2; R2 = 0.92. SI conversion factor: 1 ng/mL = 0.400641 nmol/L.

SARS-CoV-2 positivity rates were higher in the 9,529 patients from predominately black non-Hispanic zip codes (15.7%, 95% C.I. 15.0–16.4%) and the 26,242 patients from predominately Hispanic zip codes (12.8%, 95% C.I. 12.4–13.2%) than in the 112,281 patients from predominately white non-Hispanic zip codes (7.2%, 95% C.I. 7.1–7.4%; p<0.001 for both comparisons). Mean (±SD) 25(OH)D levels were also higher in patients from predominately white non-Hispanic zip codes (33.0±11.9 ng/mL; 1 ng/mL = 0.400641 nmol/L) than in patients from predominately black non-Hispanic (29.1±11.0 ng/mL; p<0.001) or Hispanic (28.8±10.7 ng/mL; p<0.001) zip codes. Regression analysis indicated strong correlation between 25(OH)D levels and SARS-CoV-2 positivity in each of these groups (Fig 2B).

Compared to the 67,667 patients age ≥60 years, the 120,362 younger patients had significantly higher SARS-CoV-2 positivity (10.2%, 95% C.I. 10.0–10.3%, vs. 7.7%, 95% C.I. 7.5–7.9%; p<0.001) and lower mean 25(OH)D levels (29.4±10.8 ng/mL vs. 35.4±12.1 ng/mL; p<0.001). Compared to the 130,473 female patients, the 61,305 male patients had higher SARS-CoV-2 positivity (10.7% 95% C.I. 10.5–11.0% vs. 8.7%, 95% C.I. 8.5%-8.8%; p<0.001) and lower mean 25(OH)D levels (31.3±11.4 ng/mL vs. 31.9±11.8 ng/mL; p<0.001). Regression analysis indicated strong correlation between 25(OH)D level and SARS-CoV-2 positivity in all these groups (Fig 3A and 3B).

Fig 3

SARS-CoV-2 NAAT Positivity Rates and Circulating 25(OH)D Levels by (A) Age Group and (B) Sex. Smooth lines represent the weighted second order polynomial regression fit to the data associating circulating 25(OH)D levels (x) and SARS-CoV-2 positivity rates (y) where: Age <60: y = 0.2161–0.0058*x + 5.6e-05*x2; R2 = 0.94. Age ≥60: y = 0.1515–0.0030*x + 2.4e-05*x2; R2 = 0.91. Female: y = 0.1837–0.0045*x + 3.9e-05*x2; R2 = 0.94. Male: y = 0.2445–0.0068*x + 6.9e-05*x2; R2 = 0.94. SI conversion factor: 1 ng/mL = 0.400641 nmol/L.

The association between lower SARS-CoV-2 positivity rates and higher circulating 25(OH)D levels per ng/mL remained significant in a multivariable logistic model (adjusted odds ratio 0.984, 95% C.I. 0.983–0.986; p<0.001). Other significant factors in both the adjusted and unadjusted models were male sex, northern and central latitudes, predominately black non-Hispanic zip codes, and predominately Hispanic zip codes (Table 1).

Table 1

Associations with SARS-CoV-2 positivity.

	Unadjusted Odds Ratio (95% C.I.)	Adjusted Odds Ratio (95% C.I.)
25(OH)D (per ng/mL increment)	0.979 (0.977–0.980)	0.984 (0.983–0.986)
Male	1.26 (1.22–1.31)	1.24 (1.20–1.28)
Female	reference	reference
Age ≥60 years	0.74 (0.71–0.76)	0.84 (0.81–0.87)
Age <60 years	reference	reference
Latitudes
Northern (>40 degrees)	2.43 (2.32–2.54)	2.66 (2.54–2.79)
Central (32–40 degrees)	1.17 (1.12–1.23)	1.22 (1.16–1.28)
Southern (<32 degrees)	reference	reference
Race/Ethnicity zip codes
Predominately black non-Hispanic	2.04 (1.93–2.17)	2.03 (1.91–2.15)
Predominately Hispanic	1.61 (1.54–1.67)	1.95 (1.87–2.04)
All other zip codes	reference	reference

Adjusted model H-L Fit: p = 0.003; R2 = 0.024. SI conversion factor: 1 ng/mL = 0.400641 nmol/L. Adjusted model included 188,028 patients with no missing values (98% of included patients).

Discussion

These results demonstrate an inverse relationship between circulating 25(OH)D levels and SARS-CoV-2 positivity. For the entire population those who had a circulating level of 25(OH)D <20 ng/mL had a 54% higher positivity rate compared to those who had a blood level of 30–34 ng/mL. The risk of SARS-CoV-2 positivity continued to decline until the serum levels reached 55 ng/mL. This finding is not surprising, given the established inverse relationship between risk of respiratory viral pathogens, including influenza, and 25(OH)D levels [14-16]. Vitamin D supplementation may reduce acute respiratory infections, especially in people with vitamin D deficiency [17]. A previous study found that each 4 ng/mL increase in circulating 25(OH)D levels was associated with a 7% decreased risk of seasonal infection, a decrement of approximately 1.75% per ng/mL [18]. This is remarkably similar to the 1.6% lower risk of SARS-CoV-2 positivity per ng/mL found in our adjusted multivariable model.

Patients with the lowest circulating levels of 25(OH)D had approximately 5–7% higher absolute SARS-CoV-2 positivity across northern, central, and southern latitudes. Indeed, Covid‐19 diagnoses and particularly mortality exhibit a decreasing worldwide North‐South latitude gradient [19]. The inverse relationship between SARS-CoV-2 positivity and 25(OH)D levels was most striking in predominately black non-Hispanic zip codes, followed by predominately Hispanic zip codes. Although 25(OH)D levels appeared to play a role for all race/ethnicities, patients from predominately black non-Hispanic zip codes had higher SASR-CoV-2 positivity than those from predominately white non-Hispanic zip codes at every 25(OH)D level. Other potential reasons including chronic diseases, occupations, housing, and lifetime risk exposures for the increased impact of COVID-19 on African Americans and Latinos have been published previously [20-22].

Northern and central latitudes, predominately Hispanic zip codes, predominately black non-Hispanic zip codes, age <60 years, and male sex were independently associated with both 25(OH)D levels and SARS-CoV-2 positivity. Yet, both in stratified analyses and in a model that controlled for all of these factors, the relationship between SARS-CoV-2 positivity and circulating 25(OH)D levels remained.

Limitations of this retrospective study include that testing for SARS-CoV-2 was based on selection factors, including presence and gravity of symptoms and exposure to infected individuals. High-risk groups, such as healthcare workers and first responders, are also more likely to be tested. Another limitation is that race/ethnicity estimates were based on aggregate U.S. Census proportions by zip code. There may be many other potentially confounding factors that were neither identified nor controlled for in this study. As expected, the multivariable model displayed poor overall fit and correlation statistics, given SARS-CoV-2 can infect anyone. The intent of the model was to determine whether circulating 25(OH)D levels remained significantly associated with SARS-CoV-2 positivity after adjustment for other identified factors.

The major strength of this study is the direct assessment of circulating 25(OH)D levels in a large cohort; this approach can more clearly elucidate the relationship of circulating 25(OH)D levels to SARS-CoV-2 positivity than is possible when using latitude as a surrogate for vitamin D status.

In conclusion, SARS-CoV-2 NAAT positivity is strongly and inversely associated with circulating 25(OH)D levels, a relationship that persists across latitudes, races/ethnicities, sexes, and age ranges. Our findings provide further rationale to explore the role of vitamin D supplementation in reducing the risk for SARS-CoV-2 infection and COVID-19 disease. If controlled trials find this relationship to be causative, the implications are vast and would present a cheap, readily-available method for helping prevent infection, especially for those with vitamin D deficiency. This could be of increased importance for the African American and Latinx community, who are disproportionately affected by both COVID-19 and vitamin D deficiency. In the interim, the authors recommend responsible vitamin D supplementation based on personal needs, risk factors, and advice from personal physicians in accordance with existing Endocrine Society Guidelines [23].

19 Aug 2020

PONE-D-20-23650

SARS-CoV-2 Positivity Rates Associated with Circulating 25-Hydroxyvitamin D Levels

PLOS ONE

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Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

ACADEMIC EDITOR:   The manuscript findings are interesting investigating the role of vitamin D supplementation in reducing the risk of SARS-CoV-2 infection. SARS-CoV-2 infection rate and vitamin D levels can be confounded by the assay method used.  Therefore, the authors should clarify the methods for sensitivity of assay and address the reviewers comments.

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Reviewer #1: In this manuscript, Kaufman, et al. examined the relationship between the SARS-CoV-2 positivity and circulating levels of 25-hydroxyvitamin D (25OHD). They analyzed the data of from over 190,000 patients and found strong inverse correlation between SARS-CoV-2 positivity and 25OHD levels, which persisted across latitudes, races/ethnicities, both sexes and age ranges. This paper may provide a rationale to investigate the role of vitamin D supplementation in reducing the risk of SARS-CoV-2 infection. The reviewer’s specific comments are described below.

Specific comments

1. Figures and line 112-113 in the text. To analyze the relationship between circulating 25OHD levels and SARS-CoV-2 positivity, the authors assigned the 25OHD values <20 ng/mL or ≥�60 ng/mL as 19 ng/mL or 60 ng/mL, respectively. However, since many subjects have 25OHD levels lower than 20 ng/mL in the United States, the authors should use the raw data of 25OHD for the analyses.

2. Lines 87-91. Four different assays were used as SARS-Cov-2 RNA NAATs. Please provide the information on the sensitivity of each assay.

3. Table 1. “Vitamin D” should be changed to “25OHD”.

Reviewer #2: Kaufman et al. implemented retrospective analytic methods to identify an association between vitamin D levels and SARS-CoV-2 infection rate. The results are potentially interesting due to the need for viable SARS-CoV-2 treatments and a greater understanding for SARS-CoV-2 infection pathology. he manuscript is well-written and the figures are clear. However, interpreting these results are difficult due these vitamin D detection methods. Here, vitamin D was measured using two techniques: (1) immunoassay and (2) LC-MS. While LC-MS is considered the gold standard due to both its sensitivity and reliability, it is readily established that vitamin D immunoassays frequently overestimate or underestimate 25(OH)D concentrations (Kocak et al., 2015; Holmes et al., 2013; Farrell et al., 2012). I acknowledge the authors' efforts to consider all potential confounding variables related to ethnicity, geographical location, sex, and age. Nevertheless,the authors do not consider the vitamin D detection method as a limitation. Therefore, the association between SARS-CoV-2 infection rate and vitamin D levels may be confounded by the detection method. The regression analysis in which infection rate was assessed as a function of vitamin D levels appear positively skewed towards extremely low vitamin D levels, which could be due to the method of vitamin D detection.

In order to properly assess SARS-CoV-2 infection rate as a function of vitamin D levels, I suggest the authors to conduct analyses by detection method.

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28 Aug 2020

I confirm the following proposed Data Availability statement is accurate and suitable to appear alongside our manuscript.

"Data underlying the study cannot be made publicly available due to ethical concerns about patient confidentiality. Data will be made available to qualified researchers on request to HealthTrends@QuestDiagnostics.com."

Sincerely yours,

Michael F Holick PhD MD

Thank you for submitting your manuscript entitled "SARS-CoV-2 Positivity Rates Associated with Circulating 25-Hydroxyvitamin D Levels" to PLOS ONE. Your manuscript files have been checked in-house but before we can proceed we need you to address the following issues:

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Authors’ Response: In accordance with Quest Diagnostics company policy on data security we are not able to upload the 191,000 rows of data to a public repository. We cannot violate HIPAA and open our Data Informatics Warehouse to external parties. This legal restriction applies to academic institutions as well as to our commercial organization.

Quest Diagnostics has previously published in PLoSONE:

https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0180840

https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0118108

https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0063416

https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0028201

In all prior circumstances as with this study, we have made data available to researchers upon request. We are eager to have others validate our analysis, suggest new ways to analyze and interpret our data, and explore how we can further understanding of health and disease. In recent months we have worked on other subjects with investigators from many outside organizations including the CDC, Boston University, Penn State University, the University of Alabama, the Alameda Health System, and many others. Requests for data and research collaborations can be sent to HealthTrends@QuestDiagnostics.com

(4) In the Methods section of your manuscript, please include the following statement: "HIPAA clearly defines research use of data as analyzed for this and numerous other studies based on the Quest Diagnostics Data Informatics Warehouse (45 CFR 164.501, 164.508, 164.512(i) (See also 45 CFR 164.514(e), 164.528, 164.532) Link: https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.hhs.gov%2Fhipaa%2Ffor-professionals%2Fspecial-topics%2Fresearch%2Findex.html&data=02%7C01%7CHarvey.W.Kaufman%40questdiagnostics.com%7C204b422f20524f74c4bd08d849bc2198%7Cb68c6481b22b46b38c4c0024bb9b9b1f%7C1%7C0%7C637340419657314405&sdata=R9Yjj38kKasss73QqHM0u2z16rLwk64VX3QAImAFrRg%3D&reserved=0 ). Quest Diagnostics takes the additional step of having its process reviewed annual by the Western Institutional Review Board who has determined the process is “deemed exempt."

Authors’ Response: We have added this statement to the methods section.

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Authors’ response: HIPAA clearly defines research use of data as analyzed for this and numerous other studies based on the Quest Diagnostics Data Informatics Warehouse (45 CFR 164.501, 164.508, 164.512(i) (See also 45 CFR 164.514(e), 164.528, 164.532) Link: https://www.hhs.gov/hipaa/for-professionals/special-topics/research/index.html ). Quest Diagnostics takes the additional step of having its process reviewed annual by the Western Institutional Review Board who has determined the process is “deemed exempt.” This statement is included in the manuscript text to assure the readers. Finally, patient privacy and adherence to HIPAA is of prime important to Quest Diagnostics to provide patients, healthcare providers, and the public trust in its operations ( https://www.questdiagnostics.com/home/privacy/ ).

3. Thank you for stating the following in the Competing Interests section:

'HWK, JKN, MHK, and CB are employees of Quest Diagnostics. HWK, MHK and CB

own stock in Quest Diagnostics. MFH is a consultant to Quest Diagnostics and was on the speakers’ bureau for Abbott Inc. and Hyatt Pharmaceutical Industries Company

PLC.'

We note that one or more of the authors are employed by a commercial company: Quest Diagnostics.

1. Please provide an amended Funding Statement declaring this commercial affiliation, as well as a statement regarding the Role of Funders in your study. If the funding organization did not play a role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript and only provided financial support in the form of authors' salaries and/or research materials, please review your statements relating to the author contributions, and ensure you have specifically and accurately indicated the role(s) that these authors had in your study. You can update author roles in the Author Contributions section of the online submission form.

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Authors’ Response: We added: “The funder provided support in the form of salaries for authors JKN, BC, MK, and HWK and consulting fees for MFH but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.”

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Reviewer #1: Partly

Reviewer #2: Partly

________________________________________

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Reviewer #1: No

Reviewer #2: No

________________________________________

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________________________________________

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Reviewer #1: In this manuscript, Kaufman, et al. examined the relationship between the SARS-CoV-2 positivity and circulating levels of 25-hydroxyvitamin D (25OHD). They analyzed the data of from over 190,000 patients and found strong inverse correlation between SARS-CoV-2 positivity and 25OHD levels, which persisted across latitudes, races/ethnicities, both sexes and age ranges. This paper may provide a rationale to investigate the role of vitamin D supplementation in reducing the risk of SARS-CoV-2 infection. The reviewer’s specific comments are described below.

Specific comments

1. Figures and line 112-113 in the text. To analyze the relationship between circulating 25OHD levels and SARS-CoV-2 positivity, the authors assigned the 25OHD values <20 ng/mL or ≥�60 ng/mL as 19 ng/mL or 60 ng/mL, respectively. However, since many subjects have 25OHD levels lower than 20 ng/mL in the United States, the authors should use the raw data of 25OHD for the analyses.

Authors’ Response: We chose the cutoff of <20 ng/mL to be more clinically relevant as it is in keeping with the definition of vitamin D deficiency. Given the small number of patients with extreme values, and our message that compares those with vitamin D deficiency to patients where the end of increasing benefits exists at 55 ng/mL we feel these cutoffs are appropriate. However, we acknowledge that most of the patients with vitamin D deficiency have values between 16-20 ng/mL, enough to be statistically relevant. If we were to analyze the data with the bottom bin at 15 ng/mL the following would happen:

The R-squared value in Figure 1 would increase from 0.96 to 0.97. The unadjusted odds ratio for 25(OH) would increase 0.001 from 0.979 (95% CI 0.977-0.980) to 0.980 (95% CI 0.978-0.981). The adjusted odds ratio for 25(OH) would also increase 0.001 from 0.984 (95% CI 0.983-0.986) to 0.985 (95% CI 0.984-0.986). All effect sizes of other factors in the multivariable model remain identical except the predominately black non-Hispanic ZIP codes, which would decrease 0.01. The mean 25(OH) level would fall from 31.7 (SD 11.7) to 31.2 (SD 12.3).

Given the lack of clinically significant impact on the main statistical outcomes, the clinical relevance gained by grouping all vitamin D deficient patients, and the urgent nature of the message this study contains (a major reason we chose to submit to PLOS ONE, expediency) we would greatly prefer to keep the groupings unchanged.

2. Lines 87-91. Four different assays were used as SARS-Cov-2 RNA NAATs. Please provide the information on the sensitivity of each assay.

Authors’ Response: We have added four FDA references for the four tests in question and added the following statement to the methods section: “We combined results from all four tests due to their very similar sensitivity and specificity.[8-11]”

3. Table 1. “Vitamin D” should be changed to “25OHD”.

Authors’ Response: We agree and have made this change. Thank you for catching this.

Reviewer #2: Kaufman et al. implemented retrospective analytic methods to identify an association between vitamin D levels and SARS-CoV-2 infection rate. The results are potentially interesting due to the need for viable SARS-CoV-2 treatments and a greater understanding for SARS-CoV-2 infection pathology. The manuscript is well-written and the figures are clear. However, interpreting these results are difficult due these vitamin D detection methods. Here, vitamin D was measured using two techniques: (1) immunoassay and (2) LC-MS. While LC-MS is considered the gold standard due to both its sensitivity and reliability, it is readily established that vitamin D immunoassays frequently overestimate or underestimate 25(OH)D concentrations (Kocak et al., 2015; Holmes et al., 2013; Farrell et al., 2012). I acknowledge the authors' efforts to consider all potential confounding variables related to ethnicity, geographical location, sex, and age. Nevertheless,the authors do not consider the vitamin D detection method as a limitation. Therefore, the association between SARS-CoV-2 infection rate and vitamin D levels may be confounded by the detection method. The regression analysis in which infection rate was assessed as a function of vitamin D levels appear positively skewed towards extremely low vitamin D levels, which could be due to the method of vitamin D detection.

In order to properly assess SARS-CoV-2 infection rate as a function of vitamin D levels, I suggest the authors to conduct analyses by detection method.

Authors’ Response: 98.8% of specimens were tested using immunoassay. In a company-wide analysis the immunoassay and LC/MS-MS methods obtain nearly identical values, with the immunoassay yielding values 1 to 2 ng/mL less, on average, than the LC/MS-MS methodology. In addition, the difference between the methods is tiny in comparison to the range of results and if it did have an effect, it would only diminish the statistical significance of results, not magnify the effect. In the regression analysis in which infection rate was assessed as a function of 25(OH)D levels the specimens tested by LC/MS-MS had an unadjusted odds ratio of 0.956 (95% CI 0.942-0.970), stronger than the unadjusted odds ratio for immunoassay tests 0.979 (95% CI 0.977-0.980) which is also the results for all specimens combined.

We have added the following sentence to the results: “98.8% of included patients had 25(OH)D levels assessed with immunoassay testing methodology.”

________________________________________

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Reviewer #2: No

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Submitted filename: Response to Editors 8.26.20.docx

Click here for additional data file.

3 Sep 2020

SARS-CoV-2 Positivity Rates Associated with Circulating 25-Hydroxyvitamin D Levels

PONE-D-20-23650R1

Dear Dr. Holick,

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.

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Reviewer #1: All comments have been addressed

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**********

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**********

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Reviewer #1: Yes

**********

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8 Sep 2020

PONE-D-20-23650R1

SARS-CoV-2 positivity rates associated with circulating 25-hydroxyvitamin D levels

Dear Dr. Holick:

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