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GWAS on Special Human Phenotypes
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GWAS on Special Human Phenotypes

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Human Genomics and Genetic Diseases".

Deadline for manuscript submissions: closed (20 December 2021) | Viewed by 8080

Special Issue Editors

Dr. Holger Kirsten

E-Mail Website
Guest Editor
Institute for Medical Informatics, Statistics and Epidemiology (IMISE), Universität Leipzig, 04109 Leipzig, Saxony, Germany
Interests: analysis of high-dimensional molecular genetic data; population genetics and integrative genome analyses including expression data and metabolomics; statistical/continuous modelling of diseases and physiological processes
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Markus Scholz

E-Mail Website
Guest Editor
Institute for Medical Informatics, Statistics and Epidemiology (IMISE), Universität Leipzig, 04103 Leipzig, Saxony, Germany
Interests: analysis of high-dimensional molecular genetic data; population genetics and integrative genome analyses including expression data and metabolomics; statistical/continuous modelling of diseases and physiological processes
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Recent years showed a dramatic increase in our insights into the pathomechanisms of human diseases and physiological processes, an increase driven by genome-wide association analysis. In particular, the analysis of ultra-large cohort studies and meta-analysis of multiple studies have dominated recent studies on human genetics of common diseases.
However, there are many traits and diseases where certain phenotypes are still not available in large numbers, making large-scale replication or meta-analysis an unachievable goal. This hampers the communication of important findings and the emergence of follow-up studies for rare phenotypes. However, novel statistical techniques integrating evidence from external data sources are available and can provide additional functional evidence for identified genetic associations.

In this Special Issue, we welcome reviews, new methods, and original articles covering genetic analyses on phenotypes related to traits or diseases that are not available in very large numbers. We consider a study size of >1000 as a minimum. To support the validity of identified genetic associations, a replication cohort is not considered mandatory, as we encourage the integration of supportive external data for validation purposes. Such secondary analyses include but are not limited to integration of expression, proteomics, or metabolomics data or genetic analysis of related phenotypes. We are looking forward to your contributions.

Dr. Holger Kirsten
Prof. Dr. Markus Scholz
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Genes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • GWAS 
  • Data integration 
  • Integrative analysis 
  • External validation 
  • Multi-omics 
  • Human infrequent phenotypes

Published Papers (3 papers)

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Research

13 pages, 901 KiB  
Article
Genetic Regulation of Cytokine Response in Patients with Acute Community-Acquired Pneumonia
by Andreas Kühnapfel, Katrin Horn, Ulrike Klotz, Michael Kiehntopf, Maciej Rosolowski, Markus Loeffler, Peter Ahnert, Norbert Suttorp, Martin Witzenrath and Markus Scholz
Genes 2022, 13(1), 111; https://0-doi-org.brum.beds.ac.uk/10.3390/genes13010111 - 06 Jan 2022
Cited by 2 | Viewed by 1724
Abstract
Background: Community-acquired pneumonia (CAP) is an acute disease condition with a high risk of rapid deteriorations. We analysed the influence of genetics on cytokine regulation to obtain a better understanding of patient’s heterogeneity. Methods: For up to N = 389 genotyped participants of [...] Read more.
Background: Community-acquired pneumonia (CAP) is an acute disease condition with a high risk of rapid deteriorations. We analysed the influence of genetics on cytokine regulation to obtain a better understanding of patient’s heterogeneity. Methods: For up to N = 389 genotyped participants of the PROGRESS study of hospitalised CAP patients, we performed a genome-wide association study of ten cytokines IL-1β, IL-6, IL-8, IL-10, IL-12, MCP-1 (MCAF), MIP-1α (CCL3), VEGF, VCAM-1, and ICAM-1. Consecutive secondary analyses were performed to identify independent hits and corresponding causal variants. Results: 102 SNPs from 14 loci showed genome-wide significant associations with five of the cytokines. The most interesting associations were found at 6p21.1 for VEGF (p = 1.58 × 10−20), at 17q21.32 (p = 1.51 × 10−9) and at 10p12.1 (p = 2.76 × 10−9) for IL-1β, at 10p13 for MIP-1α (CCL3) (p = 2.28 × 10−9), and at 9q34.12 for IL-10 (p = 4.52 × 10−8). Functionally plausible genes could be assigned to the majority of loci including genes involved in cytokine secretion, granulocyte function, and cilial kinetics. Conclusion: This is the first context-specific genetic association study of blood cytokine concentrations in CAP patients revealing numerous biologically plausible candidate genes. Two of the loci were also associated with atherosclerosis with probable common or consecutive pathomechanisms. Full article
(This article belongs to the Special Issue GWAS on Special Human Phenotypes)
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27 pages, 3229 KiB  
Article
Thousands of CpGs Show DNA Methylation Differences in ACPA-Positive Individuals
by Yixiao Zeng, Kaiqiong Zhao, Kathleen Oros Klein, Xiaojian Shao, Marvin J. Fritzler, Marie Hudson, Inés Colmegna, Tomi Pastinen, Sasha Bernatsky and Celia M. T. Greenwood
Genes 2021, 12(9), 1349; https://0-doi-org.brum.beds.ac.uk/10.3390/genes12091349 - 29 Aug 2021
Cited by 2 | Viewed by 2031
Abstract
High levels of anti-citrullinated protein antibodies (ACPA) are often observed prior to a diagnosis of rheumatoid arthritis (RA). We undertook a replication study to confirm CpG sites showing evidence of differential methylation in subjects positive vs. negative for ACPA, in a new subset [...] Read more.
High levels of anti-citrullinated protein antibodies (ACPA) are often observed prior to a diagnosis of rheumatoid arthritis (RA). We undertook a replication study to confirm CpG sites showing evidence of differential methylation in subjects positive vs. negative for ACPA, in a new subset of 112 individuals sampled from the population cohort and biobank CARTaGENE in Quebec, Canada. Targeted custom capture bisulfite sequencing was conducted at approximately 5.3 million CpGs located in regulatory or hypomethylated regions from whole blood; library and protocol improvements had been instituted between the original and this replication study, enabling better coverage and additional identification of differentially methylated regions (DMRs). Using binomial regression models, we identified 19,472 ACPA-associated differentially methylated cytosines (DMCs), of which 430 overlapped with the 1909 DMCs reported by the original study; 814 DMRs of relevance were clustered by grouping adjacent DMCs into regions. Furthermore, we performed an additional integrative analysis by looking at the DMRs that overlap with RA related loci published in the GWAS Catalog, and protein-coding genes associated with these DMRs were enriched in the biological process of cell adhesion and involved in immune-related pathways. Full article
(This article belongs to the Special Issue GWAS on Special Human Phenotypes)
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13 pages, 1536 KiB  
Article
Genomic Association vs. Serological Determination of ABO Blood Types in a Chinese Cohort, with Application in Mendelian Randomization
by Mengqiao Wang, Jiaqi Gao, Jin Liu, Xing Zhao and Yi Lei
Genes 2021, 12(7), 959; https://0-doi-org.brum.beds.ac.uk/10.3390/genes12070959 - 24 Jun 2021
Cited by 3 | Viewed by 3430
Abstract
ABO blood system is an inborn trait determined by the ABO gene. The genetic-phenotypic mechanism underneath the four mutually exclusive and collectively exhaustive types of O, A, B and AB could theoretically be elucidated. However, genetic polymorphisms in the human populations render the [...] Read more.
ABO blood system is an inborn trait determined by the ABO gene. The genetic-phenotypic mechanism underneath the four mutually exclusive and collectively exhaustive types of O, A, B and AB could theoretically be elucidated. However, genetic polymorphisms in the human populations render the link elusive, and importantly, past studies using genetically determined rather than biochemically determined ABO types were not and could not be evaluated for the inference errors. Upon both blood-typing and genotyping a cohort of 1008 people of the Han Chinese population, we conducted a genome-wide association study in parallel with both binomial and multinomial log-linear models. Significant genetic variants are all mapped to the ABO gene, and are quantitatively evaluated for binary and multi-class classification performances. Three single nucleotide polymorphisms of rs8176719, rs635634 and rs7030248 would together be sufficient to establish a multinomial predictive model that achieves high accuracy (0.98) and F1 scores (micro 0.99 and macro 0.97). Using the set of identified ABO-associated genetic variants as instrumental variables, we demonstrate the application in causal analysis by Mendelian randomization (MR) studies on blood pressures (one-sample MR) and severe COVID-19 with respiratory failure (two-sample MR). Full article
(This article belongs to the Special Issue GWAS on Special Human Phenotypes)
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