*Important notice: Research Square publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.
In a recent study posted to the Research Square* preprint server, researchers analyzed polygenic risk scores in whole genome sequences obtained from blood samples of long coronavirus disease (long COVID) patients to determine genomic predictors of long COVID.
Background
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Emerging evidence strongly suggests that long COVID is prevalent among individuals who experienced severe coronavirus disease 2019 (COVID-19). The World Health Organization (WHO) estimates the number of long COVID patients in Europe and the United States (U.S.) alone to be around 40 million. Long COVID is characterized by persistent COVID-19-associated symptoms and newly emerging symptoms for months after recovering from the initial severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection.
The commonly reported symptoms include fever, headaches, debilitating fatigue, post-exertional malaise, dyspnea, loss of taste and smell, cognitive impairments such as difficulty concentrating, and other problems related to the cardiovascular, digestive, and renal systems. The U.S. Centers for Disease Control and Prevention (CDC) has expressed the importance of expanding our understanding of the demographic and genetic risk factors associated with long COVID. However, the genetic markers associated with long COVID risks and symptoms remain unclear.
About the study
In the present study, the researchers used low-coverage whole genome sequencing, which can affordably sequence various variants with 99% reliability, to determine the genetic risk factors of long COVID. Rigorous inclusion criteria comprising a prior antibody or ribonucleic acid (RNA) positive test for SARS-CoV-2 and the occurrence of five or more persistent signs or symptoms for more than six months were used to select long COVID patients to participate in the study.
Data on demographic characteristics, existing comorbidities, and date of onset of symptoms were collected. Patients with confounding conditions such as neurocognitive disorders, fibromyalgia, mental health disorders, and post-traumatic stress syndrome that present long COVID-like symptoms were excluded. Hospitalized patients were also excluded since their persistent symptoms could have been a part of an extended recovery from severe COVID-19.
Blood samples were collected and subjected to low-pass whole genome sequencing. The participant selection ensured that the patients were not related to one another and their ancestries were evaluated. A control group consisting of available genomes of subpopulations of Iberian Spanish ancestry was also included in the study.
Polygenic risk scores were calculated by dividing the cumulative effect weights of observed risk alleles by the total number of reported risk alleles for the test and control groups. Apart from the polygenic risk scores reported for breast cancer, coronary artery disease, and prostate cancer, the researchers also examined the long COVID symptoms to determine other potential polygenic risk scores that had recorded effect alleles, weights, and chromosome positions.
Results
The results suggested a significant genetic component in the susceptibility to long COVID symptoms, especially in individuals predisposed to fatigue or tiredness. Comparisons between the long COVID and control groups revealed that long COVID patients exhibiting polygenic risk score traits of fatigue or lethargy in the last two weeks had distributions of risk alleles significantly different from the normal control samples.
Furthermore, the distribution of depression-associated polygenic risk scores in the control samples showed a lower predisposition to suffer from depression than in the long COVID samples, indicating that depression was significant in predicting long COVID susceptibility.
Polygenic risk scores associated with other diseases or conditions such as dyslipidemia, endocrine disorders, migraine, neurological disorders, asthma, immunological disorders, venous thromboembolism, and hypothyroidism were not significantly different between the long COVID and control samples. Similarly, polygenic risk scores of breast cancer, prostate cancer, and cardiovascular diseases were also not distinctive in the long COVID samples.
Due to the small sample size and the predominance of females in the study population, the researchers could not make inferences about sex-related risk factors. They admit that a large number of female patients in the study could have influenced the results.
Conclusions
To summarize, the study evaluated polygenic risk scores across whole genome sequences obtained from blood samples of long COVID patients to determine a genetic predisposition to long COVID.
Overall, the results indicated that polygenic risk scores associated with tiredness suggested susceptibility to long COVID, while those related to depression were significant predictors. However, the polygenic risk scores of cardiovascular diseases, breast cancer, prostate cancer, and neurological, endocrine, and immunological disorders did not differ between the long COVID patients and controls.
*Important notice: Research Square 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.
- Preliminary scientific report. Corpas, M. et al. (2023) "Genomic Determinants of Long COVID". Research Square. doi: 10.21203/rs.3.rs-2530935/v1. https://www.researchsquare.com/article/rs-2530935/v1
Posted in: Genomics | Medical Science News | Medical Research News | Disease/Infection News
Tags: Antibody, Asthma, Blood, Breast Cancer, Cancer, Chromosome, Coronary Artery Disease, Coronavirus, Coronavirus Disease COVID-19, covid-19, Depression, Dyslipidemia, Dyspnea, Endocrine, Fatigue, Fever, Fibromyalgia, Genetic, Genome, Genomic, Hypothyroidism, Lethargy, Mental Health, Migraine, Prostate, Prostate Cancer, Research, Respiratory, Ribonucleic Acid, RNA, SARS, SARS-CoV-2, Severe Acute Respiratory, Severe Acute Respiratory Syndrome, Stress, Syndrome, Thromboembolism, Tiredness, Venous Thromboembolism, Whole Genome Sequencing
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Written by
Dr. Chinta Sidharthan
Chinta Sidharthan is a writer based in Bangalore, India. Her academic background is in evolutionary biology and genetics, and she has extensive experience in scientific research, teaching, science writing, and herpetology. Chinta holds a Ph.D. in evolutionary biology from the Indian Institute of Science and is passionate about science education, writing, animals, wildlife, and conservation. For her doctoral research, she explored the origins and diversification of blindsnakes in India, as a part of which she did extensive fieldwork in the jungles of southern India. She has received the Canadian Governor General’s bronze medal and Bangalore University gold medal for academic excellence and published her research in high-impact journals.
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