Reduced HDL-cholesterol in long COVID-19: A key metabolic risk factor tied to disease severity

Abstract

This controlled study investigated metabolic changes in non-vaccinated individuals with Long-COVID-19, along with their connection to the severity of the disease. The study involved 88 patients who experienced varying levels of initial disease severity (mild, moderate, and severe), and a control group of 29 healthy individuals. Metabolic risk markers from fasting blood samples were analyzed, and data regarding disease severity indicators were collected. Findings indicated significant metabolic shifts in severe Long-COVID-19 cases, mainly a marked drop in HDL-C levels and a doubled increase in ferritin levels and insulin resistance compared to the mild cases and controls. HDL-C and ferritin were identified as the leading factors predicted by disease severity. In conclusion, the decline in HDL-C levels and rise in ferritin levels seen in Long-COVID-19 individuals, largely influenced by the severity of the initial infection, could potentially play a role in the persistence and progression of Long-COVID-19. Hence, these markers could be considered as possible therapeutic targets, and help shape preventive strategies to reduce the long-term impacts of the disease.

Full text

Original articles
Reduced HDL-cholesterol in long COVID-19: A key metabolic risk factor tied
to disease severity
Jamila Al-Zadjali
a,1
, Amal Al-Lawati
b,1
,Nafila Al Riyami
c
, Koukab Al Farsi
c
, Najwa Al Jarradi
c
,
Ammar Boudaka
a
, Ali Al Barhoumi
a
, Mohsen Al Lawati
a
, Amani Al Khaifi
a
, Asma Musleh
a
,
Prisca Gebrayel
d
, Sophie Vaulont
e,f
, Carole Peyssonnaux
e,f
, Marvin Edeas
e,f,
*, Jumana Saleh
c
a
Sultan Qaboos University, Muscat, Oman
b
Oman Medical College, National University, Muscat, Oman
c
Sultan Qaboos University Hospital, Muscat, Oman
d
International Society of Microbiota, Tokyo, Japan
e
Universit
e de Paris, Institut Cochin, INSERM, CNRS, F-75014, Paris, France
f
Laboratory of Excellence GR-Ex, Paris, France
HIGHLIGHTS
Low HDL-C and high ferritin are linked to increased Long-COVID-19 severity.
Changes in HDL-C levels, significantly impact Long-COVID-19 progression.
Ferritin may exacerbate disease progression by increasing oxidative stress.
HDL-C and ferritin levels may serve as markers and therapeutic targets for Long-COVID-19.
ARTICLE INFO ABSTRACT
This controlled study investigated metabolic changes in non-vaccinated individuals with Long-COVID-19, along
with their connection to the severity of the disease. The study involved 88 patients who experienced varying lev-
els of initial disease severity (mild, moderate, and severe), and a control group of 29 healthy individuals. Meta-
bolic risk markers from fasting blood samples were analyzed, and data regarding disease severity indicators were
collected. Findings indicated significant metabolic shifts in severe Long-COVID-19 cases, mainly a marked drop in
HDL-C levels and a doubled increase in ferritin levels and insulin resistance compared to the mild cases and con-
trols. HDL-C and ferritin were identified as the leading factors predicted by disease severity. In conclusion, the
decline in HDL-C levels and rise in ferritin levels seen in Long-COVID-19 individuals, largely influenced by the
severity of the initial infection, could potentially play a role in the persistence and progression of Long-COVID-19.
Hence, these markers could be considered as possible therapeutic targets, and help shape preventive strategies to
reduce the long-term impacts of the disease.
Keywords:
Long-COVID-19
HDL-cholesterol
Iron
Ferritin
Metabolic changes
Disease severity
Introduction
Long-lasting effects of COVID-19, known as Long-COVID-19 (LC),
have been increasingly recognized. Long-COVID-19 syndrome refers to
the persistence of symptoms beyond three weeks after the initial diagno-
sis of COVID-19. The incidence of Long-COVID-19 is higher in cases
where the disease is more severe.
26
The severity of COVID-19 is associ-
ated with various multisystem pathologies affecting cardiovascular, gas-
trointestinal, nervous, and immunologic systems, which are distinct
from previous SARS strains.
42,12
The widespread binding of the SARS-CoV-2 virus to the ACE2 recep-
tor in different tissues and organs contributes to the systemic spread of
infection.
36
The persistence of inflammation, often characterized by a
cytokine storm,
42,19
can lead to organ damage and disease progression,
potentially causing long-term complications.
30
Reports have emerged
linking COVID-19 infection to cerebrovascular disease and recurrent
vascular events,
4,18
indicating the prolonged effects and Long-COVID-19
symptoms of the disease may be responsible for these cardiovascular
issues.
38,5
*Corresponding author.
E-mail address: marvin.edeas@inserm.fr (M. Edeas).
1
Jamila Al-Zadjali and Amal Al-Lawati contributed equally to this work.
https://doi.org/10.1016/j.clinsp.2024.100344
Received 3 August 2023; Revised 17 January 2024; Accepted 3 March 2024
1807-5932/© 2024 HCFMUSP. Published by Elsevier España, S.L.U. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/
licenses/by-nc-nd/4.0/)
Clinics 79 (2024) 100344
journal homepage: https://www.journals.elsevier.com/clinics

Notably, cardiovascular complications such as acute myocardial
infarction and stroke can be triggered by several acute respiratory viral
infections, including the influenza virus. However, patients with COVID-
19 are more likely to develop serious complications that endure for an
extended period. This is reflected in studies that showed that the inci-
dence of myocardial infarction increased 5 times within the first 14 days
post-COVID-19 acute infection,
25,35
and that COVID-19 patients are 7-
fold more likely to have a stroke than patients with influenza. In addi-
tion, the risk for both acute myocardial infarction and stroke remains
high for up to 1 year after infection. COVID-19 disease was associated
with increased incidence and prevalence of Acute Coronary Syndrome
(ACS) events. Reports showed that ACS cases increased from an inci-
dence of 1.01 %in 2019 to 3.31 %in 2020. Adverse cardiovascular
events in COVID-19 disease are reportedly attributed to factors including
the marked inflammatory response, blood clotting, endothelial dysfunc-
tion and viral entry.
14
Although metabolic alterations are acknowledged in acute COVID-19
disease, their role in Long-COVID-19 as risk factors remains underex-
plored in the existing literature. This prompted this study to investigate
metabolic changes in Long-COVID-19 patients, particularly in associa-
tion with disease severity, duration, prognostic and predictive value.
The authors specifically focused on established acute phase measures
that constitute major metabolic risk indicators, including cholesterol
and glycemic profiles, as well as factors associated with oxidative stress.
It is crucial to emphasize that these measures ought not to be exclusively
perceived as markers indicative of the acute phase; rather, their inherent
functional roles and predictive capacities in terms of disease progression
should be acknowledged.
This study aims to investigate the metabolic changes in a specific
group of Long-COVID-19 individuals who were affected by the original
alpha strain and were unvaccinated. By examining mild/moderate and
severe cases, the authors’aim is to determine the biochemical changes
occurring after recovery from the initial acute infection during the Long-
COVID-19 phase and their link to disease severity. Understanding these
metabolic alterations in Long-COVID-19 patients can provide insights
into the potential mechanisms behind the disease’s long-term effects and
identify metabolic markers that could be targeted for therapeutic inter-
ventions and preventive strategies to mitigate the long-term impact of
Long-COVID-19.
Materials and methods
This prospective study received ethical approval from the Ethics
Committee of Sultan Qaboos University, Muscat, Oman (SAU-EC /360/
2020, MREC # 2241) on November 22, 2020.
Population and sample collection
Between January 2021 and April 2021, blood samples were collected
from 88 unvaccinated Long-COVID-19 patients who had previously com-
pleted the quarantine period. Additionally, 29 healthy individuals who
had neither been affected by coronavirus nor vaccinated were included
as controls. Participants with a history of diabetes, cardiovascular dis-
ease, or lipid-lowering medications were excluded from the study. A
detailed electronic questionnaire was administered to gather informa-
tion on persistent symptoms, illness severity during the acute infection,
medications, and medical history. Prior to sample collection, Long-
COVID-19 patients had to meet the de-isolation criteria set by the Oman
Ministry of Health, which included being asymptomatic for 72 h without
medications and completing a 14-day period from the onset of symp-
toms.
2
All participants fasted for approximately 7‒8 h before blood col-
lection, and the collected blood samples were stored at −30 °C until
analysis.
The subjects were divided into three groups based on disease sever-
ity: mild, moderate, and severe. The classification followed the specifica-
tions provided by the World Health Organization (WHO) in their
Clinical Management of COVID-19: Interim Guidance, 27 May 2020.
1
The criteria for each group are described in Table 1. The study included
29 controls, 55 mild/moderate cases, and 33 severe cases. The mild and
moderate cases were combined into one group to avoid overlap due to
the lack of objective assessment tools. The differentiation between
mild/moderate and severe cases was based on factors such as respiratory
rate (>30 breaths/min), severe dyspnea, or SpO
2
<90 %. Metabolic
parameters were compared between the mild/moderate and severe
Long-COVID-19 groups. The parameters were also analyzed based on
the duration of Long-COVID-19, which was categorized as <4 months,
4‒6 months, and >6 months. Commercial kits, clinical chemistry ana-
lyzers, and manual methods were used to measure the metabolic param-
eters according to established procedures.
Metabolic risk parameters tested
Metabolic parameters were examined to assess differences in disease
severity and duration after recovery in Long-COVID-19 patients. The
parameters included total cholesterol, Low-Density Lipoprotein Choles-
terol (LDL-C), High-Density Lipoprotein Cholesterol (HDL-C), Apolipo-
protein B (ApoB), oxidized LDL, fasting glucose, as well as serum iron
parameters (transferrin and serum iron). Measurements were performed
using the Cobas 6000 analyzer (c-501, Roche Diagnostic). Insulin and
ferritin levels were measured using the Cobas 6000 analyzer (e-601,
Roche Diagnostic). Homeostatic Model Assessment for Insulin Resis-
tance (HOMA-IR), an estimate of insulin resistance, was calculated as
described previously.
37
Glycated Hemoglobin (HbA1c) was measured
using the Cobas Integra (400 plus, Roche Diagnostic) autoanalyzer. Oxi-
dized LDL was measured using an Oxidized LDL Assay Kit (MDA-LDL,
Human) ELISA Kit (ab242302).
Analysis and statistical tests
Statistical Package for the Social Sciences (SPSS), version 28, was
used for data analysis. Differences between the mild/moderate and
severe groups were analyzed using multivariate analysis, adjusting for
Long-COVID-19 duration, age, and gender. Eta squared was calculated
as a measure of effect size to determine the strength of the association.
Spearman correlation analysis was performed to investigate associations
between non-parametric continuous variables.
Results
Survey results and persistence of symptoms
The study included males and females from 88 Long-COVID-19
patients with an age range (20‒66 years), as well as a control group
with an age range (22‒54 years). The cases that participated in the study
are detailed in Table 2.
Table 3 presents the percentage of patients enduring persistent symp-
toms in the Long-COVID-19 population after recovery. From the data
collected, it can be observed that a range of symptoms persisted in
patients with Long-COVID-19 after recovery. The percentages indicate
the occurrence of each symptom in the mild/moderate and severe cases.
Notable findings included loss of taste and smell which surprisingly
Table 1
Definition of different COVID-19 severities.
Disease severity Definition
Mild Symptomatic patients with common COVID-19 symptoms but
without evidence of severe pneumonia.
Moderate Clinical signs of pneumonia without severe pneumonia or low
oxygen saturation.
Severe Clinical signs of severe pneumonia with respiratory distress or
low oxygen saturation.
2
J. Al-Zadjali et al. Clinics 79 (2024) 100344

showed a markedly higher percentage in the mild/moderate group com-
pared to the severe group. A higher percentage of Long-COVID-19
patients from the severe group experienced mood swings and weight
loss compared to the mild/moderate group, Fatigue was substantial in
both groups, while other symptoms persisted to varying degrees in
mild/moderate and severe cases.
Metabolic symptoms in long-COVID-19 patient groups
As shown in Table 4, there was a significant increase in insulin and
Insulin Resistance (HOMA-IR) in the severe group compared with con-
trols and the mild/moderate groups. In addition, HbA1c levels showed
an increased trend in the severe cases compared to the mild/moderate
and control groups. In addition, HDL-C levels were found to be signifi-
cantly lower in the severe Long-COVID-19 group compared to the mild/
moderate and control groups. There was also a significant difference in
HDL-C levels between the mild/moderate and control groups.
The data showed a significant twofold increase in ferritin levels in
the severe cases compared with the mild/moderate and control groups.
On the other hand, iron levels showed a decreasing trend in the severe
group compared with the mild/moderate Long-COVID-19 cases. All the
other acute phase metabolic parameters measured in this study
described in Table 4 did not show significant differences between mild/
moderate, severe, and control groups.
Correlation between disease severity and metabolic parameters in long-
COVID-19
The effect of severity on all measured metabolic parameters Long-
COVID-19 was examined by multivariate analysis that was adjusted for
gender and age represented by partial Eta square. The results in Table 5
show that level of severity determines 36 %of the variation in HDL-C
and 33 %in ferritin levels.
Spearman correlation of HDL-C with different metabolic parameters
The correlation of HDL-C, with severity-linked metabolic parameters,
showed that the strongest correlation was with ferritin (r=−0.32,
p= 0.003), followed by HOMA-IR (r=−0.226, p= 0.012). Notably,
no significant correlations were found between HDL-C and other iron
parameters.
Association between Long-COVID-19 duration and metabolic param-
eters in Long-COVID-19 overall, the study found that patients with
Long-COVID-19 experienced persistent symptoms and metabolic
changes. The severity of the disease was associated with significant
alterations in metabolic parameters including insulin, HOMA-IR, HDL-C,
and ferritin levels. The duration of Long-COVID-19 also had an impact
on HDL-C, ferritin, insulin, and HOMA-IR levels which are mostly appar-
ent in severe cases.
Table 6 shows the effect of Long-COVID-19 time duration on various
metabolic parameters. In the mild/moderate Long-COVID-19 cases,
there were no significant differences in metabolic parameters in the dif-
ferent time durations after recovery as shown in Table 6 (A). Remark-
ably, the results in Table 6 (B) showed that in severe Long-COVID-19
cases, HDL-C levels were significantly lower up to four months after
infection, and only slightly increased during the 6-month duration, but
remained lower than the mild/moderate cases and controls. Ferritin,
HOMA-IR and HbA1c, all remained higher than the mild cases and con-
trols at 6 months.
Discussion
Population studies continue to reveal the association of clinical
symptoms with Long-COVID-19.
29,20
Surprisingly, even patients with
mild infections who did not require hospitalization could experience
long-term medical complications.
40
The investigation into the underly-
ing causes of persistent Long-COVID-19 symptoms following infection
has become a critical area of focus. The aim of these ongoing studies is
to identify effective therapeutic and management strategies to address
this ongoing disease. Recent reports highlighted that crushing fatigue is
one of the most disabling symptoms of long COVID.
8
In this study, the
Table 2
Gender and age demographics of the Long-COVID-19 and patient
groups.
Gender Status Number Mean Age ±Std Deviation
Male Long-COVID-19 52 40.4 ±11.3
Control 13 37.0 ±11.8
Female Long-COVID-19 36 38.6 ±10.5
Control 16 39.2 ±9.7
Table 3
Percentage of patients enduring persistent symptoms in the
Long-COVID-19 population after recovery.
Complications long recovery Mild/Moderate ( %) Severe ( %)
Problems with appetite 20.0 15.2
Loss of taste and smell 27.3 6.1
Thyroid problems 5.5 3.0
Fatigue 34.5 45.5
Mood changes 27.3 36.4
Joint pain 25.5 33.3
Weight loss 10.9 27.3
Weight gain 16.4 9.1
Table 4
Multivariate comparison between severe, mild/moderate, and controls for the
different metabolic parameters in LC patients.
Metabolic
Parameters
Control (n= 29) Mild/Moderate
(n= 55)
Severe (n= 33)
Sugar Profile
Fasting blood glucose
(FBG) (mmoL/L)
5.1 ±0.5 5.5 ±0.1 5.9 ±0.9
Insulin (mIU/L) 14.2 ±12.8 14.7 ±8.5 24.2 ±15.9
a,d
HOMA-IR 3.4 ±3.5 3.8 ±2.8 6.5 ±4.5
a,d
HbA1c %5.2 ±0.39 5.4 ±0.6 5.7 ±0.8
Lipid Profile
Total Cholesterol
(TC) (mmoL/L)
5.2 ±1.0 5.1 ±1.1 5.3 ±1.1
ApoB (mmoL/L) 0.9 ±0.3 0.96 ±0.28 1.1 ±0.3
HDL-C (mmoL/L) 1.5 ±0.5 1.3 ±0.4
a
1.1 ±0.2
b,c
LDL-C (mmoL/L) 3.1 ±0.9 3.0 ±1.0 3.4 ±1.0
Oxidized LDL (μg/
dL)
1.7 ±0.28 1.5 ±0.14 1.9 ±0.3
Iron Profile
Ferritin (μg/L) 108.0 ±150.5 110 ±117.6 207.3 ±156.0
b
Transferrin (g/L) 2.8 ±0.5 2.8 ±0.5 2.7 ±0.5
Iron (μmoL/L) 14.9 ±6.6 15.8 ±6.0 15.1 ±5.3
a
p<0.05.
b
p<0.001, Compared to Controls.
c
p<0.05.
d
p<0.02.
Table 5
The effect of COVID-19 severity on different meta-
bolic parameters LC.
Metabolic parameter Partial Eta square p-value
HDL-C 0.36 <0.001
Ferritin 0.33 <0.001
Fasting blood glucose 0.169 0.009
HOMA-IR 0.15 0.013
3
J. Al-Zadjali et al. Clinics 79 (2024) 100344

questionnaire-based data highlighted that fatigue and joint pain are the
most prevalent symptoms in Long-COVID-19 patients. Mood swings and
weight loss were more frequently reported in severe cases, while loss of
taste and smell were more common in mild cases. The distribution of
other symptoms was similar between mild/moderate and severe cases
(Table 3).
While recognizing and understanding the symptoms of Long-COVID-
19, it is highly crucial to explore the realm of serum biochemical indica-
tors for an objective and quantitative measure of the underlying physio-
logical changes associated with the disease. These laboratory
parameters serve as invaluable tools, aiding clinicians in diagnosis, mon-
itoring progression, and tailoring precise treatment strategies and tar-
geted interventions.
Concerning the metabolic biochemical alterations in Long-COVID-
19, the existing evidence regarding persistent metabolic changes beyond
the hospitalization duration and completion of the quarantine period is
both scarce and inconclusive. This is primarily due to the limited avail-
ability of reliable evidence, influenced by vaccination interference and
the emergence of various strains subsequent to the initial occurrences.
In this study, the authors managed to overcome this limitation by con-
ducting a controlled approach focused exclusively on unvaccinated indi-
viduals who were most likely infected with the SARS-CoV-2 Alpha
variant.
Notably, this study revealed marked biochemical shifts in markers
linked to disease severity and metabolic complications in Long-COVID-
19 patients. These metabolic profiles include iron, glycemic, and lipid
risk markers as shown in Table 4. As for the iron profile, a significant
two-fold increase in ferritin levels was found in the severe group com-
pared to the mild/moderate and control groups, and this increase
persisted for up to six months. Similar findings were reported in a recent
meta-analysis, which identified high ferritin levels as one of the persis-
tent abnormal parameters in 5 %‒15 %of recovered COVID-19
patients.
29
The association of ferritin with disease severity was signifi-
cant and demonstrated major dynamic changes compared to transferrin
and iron. Despite transferrin’s predictive value in the acute phase shown
previously,
10
in this study exploring Long-COVID-19, transferrin, and
iron levels did not exhibit significant differences related to severity and
time after the initial infection. These findings align with the authors’
recent study, emphasizing a robust strong association between elevated
ferritin and CRP levels consistent with the heightened COVID-19 inflam-
matory state in COVID-19. In contrast, transferrin levels, classified as an
acute-phase negative reactant, displayed a non-significant decline when
compared to the mild/moderate groups.
10
Regarding glycemic meta-
bolic risk factors, a significant increase in insulin levels and Insulin
Resistance (HOMA-IR) was found in severe cases compared to mild/
moderate cases and the control group (Table 4). These findings align
with previous studies that reported elevated fasting insulin levels and
HOMA-IR in both COVID-19 patients and recovered COVID-19 cases
when compared to healthy individuals.
27
The elevated insulin levels
observed in this study suggest that Long-COVID-19 patients did not ini-
tially experience pancreatic damage, which is in contrast to studies
showing pancreatic β-cell damage in non-survivors.
35,9
HbA1C showed
a mild increase that was not significant in the severe Long-COVID-19
group.
Concerning the lipid profile parameters, significantly lower levels of
HDL-C were found in the severe group, while no significant differences
were observed in other measured lipid markers, including LDL-C, Apo B,
and oxidized LDL indicating that these parameters had normalized after
Table 6
The effect of LC duration on different metabolic parameters.
A: Mild/moderate
Metabolic parameters <4-months Duration 1 (n= 18) 4‒6 months Duration 2 (n= 25) >6-months Duration 3 (n= 17)
Sugar profile
Fasting blood glucose (FBG) (mmoL/L) 5.3 ±0.6 5.9 ±1.2 5.4 ±1.0
Insulin (mIU/L) 12.8 ±6.6 15.1 ±8.6 16.1 ±10.1
HOMA-IR 3.0 ±1.6 4.2 ±3.1 4.2 ±3.2
HbA1c %5.2 ±0.5 5.5 ±0.7 5.5 ±0.6
Lipid Profile
Total Cholesterol (TC) (mmoL/L) 5.2 ±1.3 5.2 ±1.1 4.8 ±0.9
ApoB (mmoL/L) 1.0 ±0.4 1.0 ±0.2 0.9 ±0.2
HDL-C (mmoL/L) 1.4 ±0.5 1.3 ±0.3 1.3 ±0.3
LDL-C (mmoL/L) 3.0 ±1.2 3.0 ±0.8 3.0 ±0.9
Oxidized LDL (μg/dL) 1.6 ±0.3 1.4 ±0.2 1.5 ±0.2
Iron Profile
Ferritin (μg/L) 148.8 ±136.3 78.3 ±80.3 105.8 ±127.7
Transferrin (g/L) 2.8 ±0.6 2.8 ±0.4 2.8 ±0.4
Iron (μmole/L) 16.1 ±6.5 16.0 ±5.6 15.2 ±6.1
B: Severe
Metabolic parameters <4-months Duration 1 (n= 14) 4‒6 months Duration 2 (n= 14) >6-months Duration 3 (n=5)
Sugar profile
Fasting blood glucose (FBG) (mmoL/L) 5.8 ±0.6 6.3 ±1.1 5.9 ±0.9
Insulin (mIU/L) 26.1 ±16.0 23.3 ±13.0 22.5 ±19.5
HOMA-IR 6.9 ±4.7 6.6 ±4.0 5.9 ±5.0
HbA1c %5.5 ±0.6 5.7 ±1.1 5.9 ±0.7
Lipid Profile
Total Cholesterol (TC) (mmoL/L) 5.2 ±1.1 5.3 ±1.5 5.3 ±0.9
ApoB (mmoL/L) 1.1 ±0.3 1.1 ±0.4 1.1 ±0.2
HDL-C (mmoL/L) 1.0 ±0.2 1.1 ±0.2 1.2 ±0.2
a
LDL-C (mmoL/L) 3.2 ±1.0 3.5 ±1.2 3.5 ±0.8
Oxidized LDL (μg/dL) 2.0 ±0.6 1.8 ±0.3 1.7 ±0.7
Iron Profile
Ferritin (μg/L) 222.5 ±183.7 200.5 ±175.5 194.2 ±100.2
Transferrin (g/L) 2.7 ±0.7 2.8 ±0.3 2.5 ±0.4
Iron (μmole/L) 13.5 ±4.9 14.6 ±6.9 17.7 ±3.4
a
p= 0.02: Compared to duration 1.
4
J. Al-Zadjali et al. Clinics 79 (2024) 100344

recovery from acute COVID-19. The combination of markedly elevated
insulin levels and decreased HDL-C levels, along with unchanged LDL-C
and Apo B levels, corresponds to signs of metabolic syndrome, which is
marked by insulin resistance, and often associated with cardiovascular
risk. The present findings reflect the persistence of these systemic altera-
tions with time particularly in severe Long-COVID-19 patients. Consider-
ing different time durations, Table 6 shows that the decrease in HDL-C
levels, along with the significant increase in insulin, HOMA-IR, and ferri-
tin, persisted across the time durations beyond 6 months apparent in the
severe cases (Table 6B), compared to the mild/moderate cases
(Table 6A) and controls. HbA1c levels demonstrated an upward trend
with time in severe Long-COVID-19 cases (Table 6B), reflecting a cumu-
lative glycemic history.
The major finding in this study was the significant association
between disease severity and HDL-C, as well as ferritin, highlighting
them as the main indicators linked to severity among Long-COVID-19
patients. Approximately 36 %decrease in HDL-C and 33 %increase in
ferritin levels were predicted by disease severity, surpassing the associa-
tion with all measured metabolic markers (Table 5). Importantly also,
HDL-C levels were significantly, negatively correlated with ferritin levels
(p= 0.003) and insulin resistance (p= 0.012) while no significant cor-
relation was found with other severity indicators or other iron profile
parameters.
While it is well-established that HDL plays an essential role in reverse
cholesterol transport, studies have also demonstrated its significant anti-
inflammatory and anti-atherogenic effects,
27,3,6,16
contributing sub-
stantially to cardiovascular protection.
13
Furthermore, HDL also exhibits
antioxidant functions, facilitating the removal of oxidized lipids and
neutralization of oxidative mediators, thus complementing the anti-
inflammatory response.
23,39
Additionally, with regard to the protective
function of HDL, recent research has indicated that reduced levels of
serum sphingosine-1-phosphate carried by HDL could potentially be a
predictive factor for the severity of COVID-19 consequences.
32,34,22
Therefore, exploring the role of HDL in counteracting tissue damage is
crucial for understanding its significance in long-term COVID-19 and
associated complications.
The link to ferritin resides in earlier studies that have indicated that
dysregulation of iron storage in Long-COVID-19 might contribute to fer-
roptosis as a result of lipid oxidation and impaired iron
homeostasis.
10,15
This feature is characterized by an excessive accumula-
tion of stored iron in the form of ferritin, and lipid oxidation products,
predisposing tissue damage. The significant negative correlation
between HDL-C and ferritin levels, particularly in the context of their
association with disease severity, supports the notion that the marked
reduction in HDL-C levels associated with disease severity, coupled with
elevated ferritin levels, could potentially lead to additional tissue dam-
age due to the compromised protective function of HDL-C.
15
In this
study, the higher trend seen in oxidized LDL levels in severe Long-
COVID-19 patients compared to the mild/moderate cases may be partly
explained by losing the protective effects of HDL in severe cases; how-
ever, normalization of LDL-C levels after an acute infection may explain
why the differences in oxidized LDL did not reach significance.
Another key aspect that highlights the originality of the findings is
the comparison with two recent Long-COVID-19 studies. The first study
by Xu et al., conducted on a large cohort reported that dyslipidemia,
characterized by increased total cholesterol, triglycerides, LDL-C, and
lower HDL-C compared to controls, was associated with the severity of
the acute phase of COVID-19 infection. That study’s limitations included
a predominantly white male participant group, the inclusion of individu-
als using lipid-lowering drugs, and a lack of information about the vacci-
nation status of those with Long-COVID-19. Notably, concerning the
present findings, their study did not establish a connection with iron sta-
tus, which constitutes an important acute phase response element.
41
The
second study was conducted on unvaccinated young adults aged 18‒
30 years, from the Swiss Armed Forces suggested an increased risk of
developing metabolic disorders, including dyslipidemia, 180-days after
SARS-CoV-2 diagnosis. The study revealed increased total cholesterol
and LDL-C levels, with no differences in HDL-C between Long-COVID-19
participants and controls. Variations in virus strains, young age, predom-
inantly male participants, and genetic predisposition may have contrib-
uted to the discrepancies regarding HDL-C variations compared to the
present study.
11
Several studies have indicated a connection between
COVID-19 infection and dyslipidemia, emphasizing decreased levels of
HDL-C and variations in other lipid markers.
However, it’s important to note that these studies were confined to
the acute phase of the infection and variations in these studies were
attributed to differences in genetic phenotypes, underlying diseases, and
medications. Unveiling long-term metabolic disturbances beyond recov-
ery from the acute COVID-19 infection amid the growing concern about
Long-COVID-19 pathological outcomes is crucial to be able to develop
effective therapeutic and long-term care strategies. It’s essential to
emphasize that the research conducted was limited to the acute phase of
the infection,
33,21,28
and the differences observed in these studies were
linked to genetic variations, underlying medical conditions, and medica-
tion use.
43
However, it is crucial to identify metabolic disruptions that
persist beyond the recovery phase of acute COVID-19 infection, espe-
cially in light of the growing concerns about Long-COVID-19 pathologi-
cal outcomes and the need to create effective therapeutic and long-term
care strategies.
In light of the notable metabolic changes observed in Long-COVID-
19, especially with regard to HDL-C as a primary factor linked to sever-
ity, there is a critical need to further investigate the potential therapeutic
effectiveness of interventions dedicated to lipid management, with a
specific focus on HDL and its potential anti-inflammatory and antioxi-
dant effects. For example, niacin, recognized for its role in lipid manage-
ment, may increase HDL-C up to 25 %.
17,24,7
Despite mixed results in
preventing cardiovascular outcomes, the widespread use of niacin per-
sists, highlighting its established effectiveness in enhancing HDL-C lev-
els. Which was shown to be superior, at a recommended dose, compared
to gemfibrozil, a fibrate, in increasing HDL-C, suggesting the potential
applicability of niacin in addressing metabolic alterations associated
with viral infections.
12,31
Nonetheless, fibrates, including gemfibrozil,
known for their ability to raise HDL-C levels and reduce major coronary
events with minimal toxicity, may further contribute to the therapeutic
strategies.
36
Additionally, the emergence of Cholesteryl Ester Transfer
Protein inhibitors as a novel drug class provides additional avenues for
intervention in the context of altered lipid metabolism associated with
viral infections and their complications.
19
Importantly, however, there is growing support for targeting HDL
functionality that could be more relevant to clinical outcomes. Measures
associated with HDL such as ApoA-I and HDL particle concentration and
sphingosine-1-p as specified earlier
31
are considered more robust indica-
tors of HDL function. Future research should explore therapies targeting
HDL function and investigate whether improvements in these parame-
ters translate into clinical benefits, the emerging HDL function hypothe-
sis shows promise in reducing cardiovascular risk.
31
This discussion
emphasizes the need for personalized therapeutic approaches in manag-
ing metabolic changes during severe viral infections. Tailoring treat-
ments to individual patient profiles, including specific dietary changes
and education about metabolic health, is recommended to optimize
HDL-C management.
It is important to acknowledge the limitations of this study, which
include the relatively small sample size attributed to the limited time for
recruitment of unvaccinated individuals amidst emerging viral strains
and launching vaccination campaigns. Additionally, self-reported symp-
toms may have introduced bias into the findings.
Conclusion
This study provides biochemical and metabolic changes associated
with Long-COVID-19 and their link to disease severity. It highlights
major alterations in serum HDL-C and ferritin levels in severe COVID-19
5
J. Al-Zadjali et al. Clinics 79 (2024) 100344

cases. The metabolic changes observed in severe cases closely resemble
the alterations found in the metabolic syndrome, which is characterized
by reduced serum HDL-C levels as a major component and poses a risk
to cardiovascular health.
This study highlights that HDL-C is negatively associated with ferri-
tin, and that HDL-C and ferritin levels are the main factors predicted by
disease severity compared to other metabolic or acute phase markers.
Furthermore, these metabolic shifts, along with other changes in
metabolic risk factors, persist for several months post-COVID-19 in
severe cases, differentiating them from mild cases and controls. This per-
sistence suggests a potential role for these metabolic changes in exacer-
bating the severity and progression of Long-COVID-19.
The decline in serum HDL-C levels, which are typically protective
against cardiovascular disease, coupled with an increase in ferritin,
known for its role in oxidative stress, may be crucial in the progression
of long COVID’s adverse effects.
These findings are of significant interest and may contribute to the
identification of potential markers for disease severity and progression
in Long-COVID-19. Additionally, they may offer insights into therapeu-
tic targets, aiding in the development of treatments and preventive
measures for COVID-19 and its prolonged symptoms. This research is a
step forward in understanding the complex effects of COVID-19 and
managing its long-term impacts.
Data availability statement
Not applicable.
Ethics approval and consent to participate
This prospective study was approved by the Sultan Qaboos Univer-
sity ethics committee (SAU-EC/360/2020,MREC # 2241) on November
22, 2020.
Conflicts of interest
The authors declare no conflicts of interest.
CRediT authorship contribution statement
Jamila Al-Zadjali: Data curation, Formal analysis, Methodology.
Amal Al-Lawati: Data curation, Formal analysis. Nafila Al Riyami:
Data curation, Formal analysis, Investigation. Koukab Al Farsi: Data
curation, Formal analysis. Najwa Al Jarradi: Data curation, Formal
analysis. Ammar Boudaka: Data curation, Formal analysis, Methodol-
ogy. Ali Al Barhoumi: Data curation, Formal analysis, Methodology.
Mohsen Al Lawati: Data curation, Formal analysis. Amani Al Khaifi:
Data curation, Formal analysis. Asma Musleh: Data curation, Formal
analysis. Prisca Gebrayel: Formal analysis, Investigation, Writing –
review & editing. Sophie Vaulont: Formal analysis, Investigation, Writ-
ing –review & editing. Carole Peyssonnaux: Formal analysis, Investiga-
tion, Writing –review & editing. Marvin Edeas: Conceptualization, Data
curation, Formal analysis, Investigation, Writing –review & editing.
Jumana Saleh: Conceptualization, Data curation, Formal analysis,
Investigation, Methodology, Writing –review & editing.
Funding
The project was funded by Sultan Qaboos University.
Acknowledgments
The authors thank the nurses at SQU hospital blood bank and the
Long-COVID-19 patient volunteers who contributed to the study.
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