A rare likely pathogenic HLA-DRB1 variant with compromised immunity in severe COVID-19 patient and in-hospital mortality

The severity of COVID-19 disease can vary greatly, influenced by genetic factors and comorbid conditions that may increase mortality. This study has examined potential genetic influences on the disease for a young adult aged 36 years with T2DM-CAD multi-morbidity with severe COVID-19 disease and in-hospital mortality using whole-exome sequencing. The patient exhibited a constellation of severe symptoms and abnormality in several biochemical markers associated with COVID-19 disease and comorbid conditions. A total of 756 variants were discovered in the patient, including several rare and novel variants associated with immune pathways. A set of 10 unique candidate variants in 10 distinct genes were identified with nine variants located within genes associated with the COVID-19 panel (HLA-DRB1, IL23R, PRKDC, RNF31, SLC37A4, TAP2, TCIRG1, TCN2, and TPP2), while one variant was found in a gene (PAX6) from Diabetes panel. Enrichment analysis showed that the top three enriched GO biological processes were a response to stimulus (<i>n</i> = 23, <i>p</i> = 6.8E-3), immune system process (<i>n</i> = 22, <i>p</i> = 3.6E-12), and regulation of immune system process (<i>n</i> = 19, <i>p</i> = 1.57E-11). The Maximal Clique Centrality algorithm identified HLA-DRB1 as a prominent hub gene and potential loss-of-function mutation in HLA-DRB1, suggests a compromised antigen presentation mechanism within this patient.

Authors

Institutions

Publication Details

Journal
Personalized Medicine
Published
2025-07-24
DOI
https://doi.org/10.1080/17410541.2025.2538424
Primary Topic
Diabetes and associated disorders
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A rare likely pathogenic HLA-DRB1 variant with compromised immunity in severe COVID-19 patient and in-hospital mortality

Badr Alsayed, Mohammad Fahad Ullah, Rashid Mir
Personalized Medicine
Diabetes and associated disorders
article

A rare likely pathogenic HLA-DRB1 variant with compromised immunity in severe COVID-19 patient and in-hospital mortality

Badr Alsayed, Mohammad Fahad Ullah, Rashid Mir
article en

Abstract

The severity of COVID-19 disease can vary greatly, influenced by genetic factors and comorbid conditions that may increase mortality. This study has examined potential genetic influences on the disease for a young adult aged 36 years with T2DM-CAD multi-morbidity with severe COVID-19 disease and in-hospital mortality using whole-exome sequencing. The patient exhibited a constellation of severe symptoms and abnormality in several biochemical markers associated with COVID-19 disease and comorbid conditions. A total of 756 variants were discovered in the patient, including several rare and novel variants associated with immune pathways. A set of 10 unique candidate variants in 10 distinct genes were identified with nine variants located within genes associated with the COVID-19 panel (HLA-DRB1, IL23R, PRKDC, RNF31, SLC37A4, TAP2, TCIRG1, TCN2, and TPP2), while one variant was found in a gene (PAX6) from Diabetes panel. Enrichment analysis showed that the top three enriched GO biological processes were a response to stimulus (<i>n</i> = 23, <i>p</i> = 6.8E-3), immune system process (<i>n</i> = 22, <i>p</i> = 3.6E-12), and regulation of immune system process (<i>n</i> = 19, <i>p</i> = 1.57E-11). The Maximal Clique Centrality algorithm identified HLA-DRB1 as a prominent hub gene and potential loss-of-function mutation in HLA-DRB1, suggests a compromised antigen presentation mechanism within this patient.

Personalized MedicineVol. 22(5)
Fahd bin Sultan University (SA), University of Tabuk (SA)
Good health and well-being
Openalex Percentile: Top 79%
Diabetes and associated disorders
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.