How can researchers profile post-COVID syndromes among distinct SARS-CoV-2 variants?

In a recent study posted to the medRxiv* preprint server, researchers profiled post-coronavirus disease (COVID) syndrome (PCS) throughout various severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. 

Background

SARS-CoV-2 is a rapidly evolving and highly contagious Coronavirus (CoV). It has infected over 572 million people worldwide since the initial human transmission cases over two years ago.

Self-reported symptom investigations significantly improved knowledge of SARS-CoV-2 throughout the pandemic and made it possible to follow COVID 2019 (COVID-19)'s long-term impacts beyond the hospital background. Characterizing how PCS manifests with varied patterns is essential to enable individualized therapy for the most impacted survivors.

According to the authors of the present investigation, no available research compares the symptom pattern of PCS among COVID-19 vaccination status and distinct SARS-CoV-2 variants. In addition, no studies sought to characterize the PCS by reporting the modeling of longitudinally acquired symptoms in a time-series data format.

About the study

The present study used an extensive sample with prospectively accumulated longitudinal self-reported COVID-19 symptoms to establish symptom patterns for PCS among the dominant SARS-CoV-2 variants in 2020 and 2021 and throughout vaccination status when infected. It aims to guide PCS prognostication and tailored management.

In the current prospective longitudinal cohort research, the investigators examined data from 336,652 participants who provided regular health reports using the COVID Symptom Study (CSS) mobile application. They used prospective self-reported data gathered throughout the pandemic from a notably large cohort in the United Kingdom (UK) to undertake an unsupervised clustering assessment of symptoms from community-based PCS patients.

The different symptom profiles for PCS patients across SARS-CoV-2 variants and vaccination status during infection time were identified using clustering assessment of time-series data. Subsequently, clusters were characterized by symptom duration, prevalence, demographics, and comorbidities or preceding conditions. Furthermore, the team looked into how PCS clusters influenced the lives of impacted individuals utilizing an independent research sample with supplementary data from 140 people.

Results

The study results revealed that the participants reported being physically fine approximately 30 days ahead they tested SARS-CoV-2-positive. Interestingly, 9,323 people later experienced Long-COVID, characterized by SARS-CoV-2 symptoms continuing for more than 28 days. Further, 1,459 developed PCS, regarded as having COVID-19 symptoms for above 12 weeks.

The study discovered three major symptom profiles for people who experienced COVID-19 symptoms for 12 weeks or longer. These profiles were consistent throughout the analyzed viral variants (Delta, Alpha, and wild-type) and according to vaccination status; the only differences were the proportion of people who experienced each pattern and the overall length of the symptoms. The authors found distinctive symptom patterns for PCS across and within SARS-CoV-2 variants. Moreover, four endotypes for infections caused by the SARS-CoV-2 wild-type strain, five for Delta, and seven for Alpha, were found.

A cardiorespiratory symptom cluster was discovered among all variants. Central neurological disorders were the subject of a second cluster, and instances with the most debilitating and severe multi-organ symptoms were associated with a third cluster. There were not more than two distinct phenotypes of gastrointestinal symptoms per virus strain. An independent research sample validated the existence of the three major clusters and evaluated their functional influence.

Symptoms associated with the central neurological cluster included dysosmia/anosmia, brain fog, fatigue, depression, headache, and delirium. This symptom profile matched the second-biggest wild-type variant cluster and the largest cluster for the Delta and Alpha variants. 

The second frequent cluster, the largest during the wild-type phase when no one was vaccinated, was linked to cardiorespiratory symptoms. This cluster might indicate lung damage, discovered in other analyses and suggested in the current research as chest pain and dyspnea. Finally, a third frequent cluster, found in all variants, was differentiated by myalgias, abdominal, and inflammatory/systemic symptoms, as documented in other PCS-focused research.

Conclusions

The researchers claimed that the current study was one of the initial large-scale investigations to establish a PCS symptom cluster among adults in an unsupervised manner.

The study findings demonstrated the existence of various PCSs, with shared characteristics across the SARS-CoV-2 variants in symptoms and the mechanism of their evolution during the disease course. The scientists described patient subgroups with particular post-COVID manifestations, which could signify various underpinning pathophysiological processes.

The study found unique self-reported symptom evolutions, or clusters, in those with 12 weeks or more of persistent symptoms following SARS CoV-2 infection, adopting a data-driven methodology. There were several clusters detected throughout the three viral variants examined. Nonetheless, three clusters predominately characterized by specific symptom groups (cardiorespiratory, central neurological, and inflammatory/systemic) emerged with shared characteristics.

The present study was pertinent for post-COVID prognostication, revealing how long specific symptoms endure due to the time-series element. These discoveries may help in the establishment of individualized diagnosis and therapy and the planning of care for PCS patients by policymakers. Further, the current classification may help understand the multiple PCS mechanisms and subgroups of people at risk for long-term debilitation.

*Important notice

medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Written by

Shanet Susan Alex

Shanet Susan Alex, a medical writer, based in Kerala, India, is a Doctor of Pharmacy graduate from Kerala University of Health Sciences. Her academic background is in clinical pharmacy and research, and she is passionate about medical writing. Shanet has published papers in the International Journal of Medical Science and Current Research (IJMSCR), the International Journal of Pharmacy (IJP), and the International Journal of Medical Science and Applied Research (IJMSAR). Apart from work, she enjoys listening to music and watching movies.