ReviewDeutsches Arzteblatt international2022
Genetic Predisposition and the Variable Course of Infectious Diseases.
Review in Deutsches Arzteblatt international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 11 citations in OpenAlex.
- Human Influenza Virus Infection: A Focus on Key Host Determinants Linked to Clinical Disease Severity.Viruses · 2026Review
- Rare genetic variant risks in patients with sepsis-associated acute respiratory distress syndrome.Respiratory research · 2026Article
- Article
- FURIN, IFNL4, and TLR2 gene polymorphisms in relation to COVID-19 severity: a case-control study in Egyptian patients.Infection · 2024Article
- Medical students' knowledge on cancer predisposition syndromes and attitude toward eHealth.Archives of gynecology and obstetrics · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundContact with a pathogen is followed by variable courses of infectious disease, which are only partly explicable by classical risk factors. The susceptibility to infection is variable, as is the course of disease after infection. In this review, we discuss the extent to which this variation is due to genetic factors of the affected individual (the host).
methodsSelective review of the literature on host genetics in infectious disease, with special attention to the pathogens SARSCoV- 2, influenza viruses, Mycobacterium tuberculosis, and human immunodeficiency virus (HIV).
resultsGenetic variants of the host contribute to the pathogenesis of infectious diseases. For example, in HIV infection, a relatively common variant leading to a loss of function of the HIV co-receptor CCR5 affects the course of the disease, as do variants in genes of the major histocompatibility complex (MHC) region. Rare monogenic variants of the interferon immune response system contribute to severe disease courses in COVID-19 and influenza (type I interferon in these two cases) and in tuberculosis (type II interferon). An estimated 1.8% of life-threatening courses of COVID-19 in men under age 60 are caused by a deficiency of toll-like receptor 7. The scientific understanding of host genetic factors has already been beneficial to the development of effective drugs. In a small number of cases, genetic information has also been used for individual therapeutic decision-making and for the identification of persons at elevated risk.
conclusionA comprehensive understanding of host genetics can improve the care of patients with infectious diseases. Until the present, the clinical utility of host genetics has been limited to rare cases; in the future, polygenic risk scores summarizing the relevant genetic variants in each patient will enable a wider benefit. To make this possible, multicenter studies are needed that will systematically integrate clinical and genetic data.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.