key: cord-0786917-rb6ccdwm
authors: Soffer, Shelly; Glicksberg, Benjamin S; Zimlichman, Eyal; Efros, Orly; Levin, Matthew A; Freeman, Robert; Reich, David L; Klang, Eyal
title: The Association Between Obesity and Peak Antibody Titer Response in COVID‐19 Infection
date: 2021-05-04
journal: Obesity (Silver Spring)
DOI: 10.1002/oby.23208
sha: e6d497c320073a193c3d539c43d4022743f85514
doc_id: 786917
cord_uid: rb6ccdwm

OBJECTIVE: Obesity is associated with severe COVID‐19 infection. Disease severity is associated with a higher COVID‐19 antibody titer. We compared the COVID‐19 antibody titer response of patients with obesity versus patients without obesity. METHODS: We retrospectively retrieved data of individuals tested for COVID‐19 serology at the Mount Sinai Health System in New York City between March 1st, 2020, and December 14th, 2021. The primary outcome was peak antibody titer, assessed as a binary variable (1:2880, which was the highest detected titer, versus lower than 1:2880). In patients with positive serology test, peak titer rates were compared between BMI groups (<18.5, 18.5‐25, 25‐30, 30‐40, ≥40 kg/m(2)). A multivariable logistic regression model was used to analyze the independent association between different BMI groups and peak titer. RESULTS: Overall, 39,342 individuals underwent serology testing and had BMI measurements. Positive serology test was present in 12,314 patients. Peak titer rates were associated with obesity (<18.5:34.5%, 18.5‐25:29.2%, 25‐30:37.7%; 30‐40:44.7%; ≥40:52.0%, p<0.001). In multivariable analysis, severe obesity had the highest adjusted odds ratio for peak titer (aOR 2.5, 95% CI 2.1–3.0). CONCLUSION: COVID‐19 neutralizing antibody titer is associated with obesity. This has implications on the understanding of the role of obesity in COVID‐19 severity.

Obesity is an independent risk factor for severe illness, hospitalization, and mortality from coronavirus disease 2019 (COVID-19) (1, 2, 3, 4) . Several mechanisms have been proposed to explain the link between obesity and COVID-19 severity. Specifically, the impact of obesity on the immune response to COVID-19 has been a focus of interest. Prior knowledge of other viruses has shown that obesity is associated with an impaired immune response following infection or vaccination (5, 6, 7, 8, 9, 10) .

Antibody tests, also known as serology tests, can be utilized to assess the adaptive immune response following COVID-19 infection (11) . Studies have demonstrated that COVID-19 patients developed antibodies within 1-2 weeks after the onset of symptoms. These antibodies remain elevated for at least several months (12) . Several studies have shown that a higher neutralizing antibody titer is associated with disease severity (13, 14) .

The COVID-19 antibody profile in patients with obesity is poorly understood. This study aimed to compare the COVID-19 antibody titer response of patients with obesity versus patients without obesity.

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We retrospectively retrieved data of adult patients (age 18) who underwent COVID-19 serology testing and had available Body Mass Index (BMI) measurements from Electronic Health Record (EHR) of a large, diverse academic health system, the Mount Sinai Health System (MSHS) in New York City. MSHS encompasses the Icahn School of Medicine at Mount Sinai and eight hospital campuses in the New York metropolitan area and a large, regional ambulatory footprint.

The study time frame was between March 1st, 2020, and December 14, 2020. We have chosen this study end date to ensure there were no vaccinated patients included in the cohort, as the COVID-19 vaccinations were first introduced to New York on December 14, 2020. Structured patient data was retrieved from the EHR system (Epic, Epic Systems Corporation, Verona, WI). The Mount

Sinai Institutional Review Board approved this study prior to data collection.

Serology testing for severe acute respiratory syndrome coronavirus-2 (SARS CoV-2) was performed at the MSHS beginning in March 2020 (12) . The test uses enzyme-linked immunosorbent assay (ELISA), which has been extensively used in research (15, 16, 17, 18) . The test was established in Mount Sinai's center for clinical laboratories, where it received the New York State Department of Health (NYSDOH) and FDA emergency use authorization (EUA) (19, 20) . MSHS started to screen individuals for antibodies to SARS CoV-2 to recruit volunteers as donors for convalescent plasma therapy (21) . In addition, MSHS also offered the antibody test to MSHS employees and was available for clinical use. The ELISA set up results in a discrete titer at either <1:80, 1:80, 1:160, 1:320, 1:960, or 1:2880, which was the highest detected titer. A positive test was defined as a titer of 1:80 and above.

A minority of the cases had more than one serology test. For those individuals, we chose the first positive test, or in cases with only negative tests, the first negative test.

We queried the EHR for BMI measurements for all patients with serology testing. Only patients with a documented BMI measurement (height/weight 2 ) were included in the study. Patients with

This article is protected by copyright. All rights reserved missing BMI were excluded. The timestamp of the BMI recording was obtained and compared to the serology test timestamp.

Patients were clustered into five groups based on BMI measurements: <18.5, 18.5-25, 25-30, 30-40, and ≥40 kg/m 2 . The obesity group was defined as BMI 30-40 kg/m 2, and the severe obesity group was defined as BMI ≥40 kg/m 2 (22) .

We further obtained data of COVID-19 nasopharyngeal swab polymerase chain reaction (PCR) testing. When available, for each patient, we included the date of the first positive PCR test performed before the serology test. For all positive PCR cases, we have obtained records pertaining COVID-19 related hospital admission.

Other variables obtained for each patient included demographics (age, sex, race), comorbidities, and smoking status. Comorbidities were coded as International Classification of Diseases (ICD-10) records. The ICD codes were grouped using the diagnostic clinical classification software (CCS) (23). Smoking was defined as past or present smoking.

Categorical variables were compared using the chi-square test. Continuous variables were compared using either the unpaired t-test to compare two groups or one-way analysis of variance (ANOVA) to compare more than two groups. We compared titer levels between different BMI groups (<18.5, 18.5-25, 25-30, 30-40, and ≥40 kg/m 2 ). In order to segregate the group of patients with prior COVID-19 laboratory diagnosis, we performed sub-analyses for patients with and without a prior positive PCR. We also performed sub-analyses for individuals below and above 50 years of age (24) and patients with and without prior COVID-19 related hospital admission.

In patients with a positive titer, we used a multivariable logistic regression model to analyze the independent association between different BMI groups and peak titer (1:2880). Similarly to a previous study, peak titer was defined as the maximal serum dilution observed in our laboratory (1:2880) (25). BMI 18.5-25 kg/m 2 was used as the reference group. The model was adjusted for

This article is protected by copyright. All rights reserved demographics, comorbidities, and prior admission. A correlation matrix was constructed to assess the possible collinearity between covariates in the model, demonstrating that all correlations were below 0.52 ( Figure S1 ). Prior positive PCR was not included as a covariate as it had high collinearity (0.70) with prior admission. Adjusted odds ratios (aOR), 95% confidence intervals (CI), and p-values were calculated for the models' variables. All analyses were performed using Python (Python Software Foundation, version. 3.6.5. Available at http://www.python.org).

Overall, 63,988 individuals who underwent serology testing were identified. BMI recordings were available for 39,342 of those patients. Positive titer levels (≥1:80) were present in 12,314 patients ( Figure 1 ). The median time between BMI recordings and serology tests was 127 days (IQR 33 -245 days). 39.954.6 days, p = 0.002). BMI distributions in the sub-analyses groups are presented in Figure   S2 . 1387 patients with a positive serology test had a prior hospital admission with positive PCR.

Table S1 demonstrates the ten most common primary diagnoses in this group.

Peak titer levels were associated with obesity and severe obesity in the entire cohort (BMI <18. 

The association between obesity and peak titer rates was also observed after stratifying by positive PCR status (BMI <18. 5 

This article is protected by copyright. All rights reserved Figure S3 (A-F) .

Multivariable analysis (Figure 3 ) revealed that severe obesity had the highest adjusted odds ratio (aOR) for peak titers (aOR 2.5, 95% CI 2.1 -3.0, p<0.001). This was followed by BMI levels of 30 -40 kg/m 2 (aOR 1.8, 95% CI 1.6 -2.0, p<0.001). Other features positively associated with peak titer included BMI 25-30 kg/m 2 , previous COVID-19 related admission, age decile, CKD, CHF, and DM. White race was negatively associated with peak titers (aOR 0.7, 95% CI 0.7 -0.8, p<0.001).

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This retrospective study of a large urban cohort demonstrated that the magnitude of the neutralizing antibody response following COVID-19 infection is associated with obesity and severe obesity.

Previous research has shown that antibody titer level against COVID-19 is associated with disease severity (13, 14, 26) . Additionally, it was found that patients with obesity have an increased risk for severe COVID-19 illness (1, 24). Thus, our observation of a high titer among patients with obesity could be explained by their more severe illness. These results are particularly intriguing as it has been shown that patients with obesity develop poor seroconversion response after other disease infections such as influenza (27).

The higher titer values among COVID-19 patients with severe obesity may be an indication of a strong immune response. This could be a result of a severe infection that is more evident in patients with severe obesity (1, 2) . Alternatively, an activated immune system with high antibody formation may be the cause of severe symptoms. The latter explanation could be more applicable as the adipose abnormal cytokine production has been proposed as a key mediator of COVID-19 severity in patients with obesity(28, 29, 30).

We have also shown that the difference between the BMI groups for high peak titer was most prominent in the young population (age less than 50). This strengthens our earlier finding that obesity is a stronger predictor for severe disease and mortality among young COVID-19 patients (24) . The current results reinforce the significant role of severe obesity in COVID-19 pathogenesis in young patients.

When analyzing patients hospitalized due to COVID-19, there was no significant difference between BMI groups for high peak titer. This could be explained by the fact that inpatients due to COVID-19 experience severe disease requiring hospitalization. Of note, it was previously demonstrated that elevation of neutralizing antibodies among all hospitalized patients reaches 80% of maximal levels rapidly after symptom onset (26).

It was recently shown by Nilles et al., that the humoral response against COVID-19 is not adversely affected in patients with obesity (25). In contrast to our results, they did not detect a

This article is protected by copyright. All rights reserved difference in the antibody titers between the BMI groups. The difference in the studies populations could explain this. Their study included a limited number of individuals with seropositive tests, and among them, only five patients with severe obesity. Our study included more than 650 individuals with severe obesity and a positive antibody test.

Interestingly, a recent study evaluated the antibody titer response following two doses of the BNT162b2 mRNA COVID-19 vaccine according to different BMI groups (31). The researchers found that individuals with obesity had a less efficient humoral response compared to the normal- Our study has several limitations. This was an observational retrospective analysis. The time of disease onset is not available for all subjects and it has been shown that the antibody titer declines over time (11) . In our study, in cases where the PCR was available, the average time lapse between the PCR and the antibody test was greater among patients with obesity. Nevertheless, they presented with a higher antibody titer. Additionally, although we adjusted and performed subanalyses for previous COVID-19 admission and previous positive PCR, our study may have a selection bias. Furthermore, we excluded patients without available BMI records which could also lead to a selection bias. Moreover, the indication for serology testing was not available. There may also be a selective survival bias, whereby patients with a more severe disease died and did not have a titer antibody test. Although information related to medications used by the study Accepted Article participants would be informative, considering that certain drugs may alter COVID-19 infection rates, this data was not available. Lastly, data regarding disease severity was also not available.

In conclusion, COVID-19 neutralizing antibody titer is associated with BMI, with the highest titer in patients with severe obesity. This has implications on the understanding of the role of obesity in COVID-19 severity. Future studies should clarify the kinetics and activity of the antibody developed in individuals with obesity, as they are relevant to the protection against reinfection and vaccine response. Abbreviations: Interquartile range (IQR); Coronary artery disease (CAD); Congestive heart failure (CHF); Hypertension (HTN); Diabetes mellitus (DM); Body mass index (BMI); Chronic kidney disease (CKD).

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High prevalence of obesity in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) requiring invasive mechanical ventilation

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Accepted Article This article is protected by copyright. All rights reserved 9

Obesity is associated with impaired immune response to influenza vaccination in humans

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SARS-CoV-2 infection induces robust, neutralizing antibody responses that are stable for at least three months. medRxiv : the preprint server for health sciences

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Accepted Article This article is protected by copyright. All rights reserved 17

Asymptomatic seroconversion of immunoglobulins to SARS-CoV-2 in a pediatric dialysis unit

Seroconversion of a city: Longitudinal monitoring of SARS-CoV-2 seroprevalence in New York City. medRxiv : the preprint server for health sciences

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Data sharing statement -The data that support the findings of this study are available from the author EK upon reasonable request. The data are not publicly available due to information that could compromise the privacy of research participants.

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This article is protected by copyright. All rights reserved