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Updates of DNA Variations in Evolution and Human Diseases
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Updates of DNA Variations in Evolution and Human Diseases

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 (10 November 2023) | Viewed by 3876

Special Issue Editors

Dr. Laura Crisponi

E-Mail Website
Guest Editor
CNR, Ist Ric Genet & Biomed, Cagliari, Italy
Interests: rare disease; medical genetics; molecular genetics; physiopathological mechanisms
Dr. Mara Marongiu

E-Mail Website
Guest Editor
The National Research Council (CNR), Institute for Genetic and Biomedical Research (IRGB), Monserrato, CA, Italy
Interests: medical genetics; molecular genomics; molecular pathways; transcriptomics
Dr. Manuela Uda

E-Mail Website
Guest Editor
The National Research Council (CNR), Institute for Genetic and Biomedical Research (IRGB), Monserrato, CA, Italy
Interests: human genetics; genetic disorders; molecular genomics; functional genetics

Special Issue Information

Dear Colleagues,

In recent years, progress in decoding the human genome has enabled us to understand genetic architecture and heritability, which provides valuable insights into human diseases. However, interpreting the relationships between genotypes/phenotypes is becoming more complex than expected, leading to the need for (r)evolutionary thinking. DNA variations are crucial for the evolutive process, with most of them producing traits that confer neither an advantage nor disadvantage, and the process of natural selection defines those more suited to a particular environment. Nonetheless, if the environment changes, then an evolutionary mismatch emerges, creating maladaptive conditions. This accounts for the prevalence of many common diseases in modern populations, such as obesity, diabetes, or heart disease affected by lifestyle changes and diet. Therefore, evolutionary medicine, studying modern diseases from an evolutionary perspective, has the power to identify novel mechanisms, pathways, and networks, enlightening us on how and why we get sick.

This Special Issue aims to provide “Updates on DNA Variations in Evolution and Human Diseases”; we welcome original articles, new methods, and reviews related to this issue topic, and we look forward to your valuable contributions.

“We must retrace steps already done, to repeat them, and to paint alongside new ways. You have to start the trip again. All the time.” (Jose Saramago)

Dr. Laura Crisponi
Dr. Mara Marongiu
Dr. Manuela Uda
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

  • human genome
  • genotype/phenotype relationships
  • DNA variations
  • human diseases
  • evolution
  • evolutionary mistmaches
  • evolutionary medicine

Published Papers (2 papers)

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Research

20 pages, 2230 KiB  
Article
Using Machine Learning to Explore Shared Genetic Pathways and Possible Endophenotypes in Autism Spectrum Disorder
by Daniele Di Giovanni, Roberto Enea, Valentina Di Micco, Arianna Benvenuto, Paolo Curatolo and Leonardo Emberti Gialloreti
Genes 2023, 14(2), 313; https://doi.org/10.3390/genes14020313 - 25 Jan 2023
Cited by 3 | Viewed by 1660
Abstract
Autism spectrum disorder (ASD) is a heterogeneous condition, characterized by complex genetic architectures and intertwined genetic/environmental interactions. Novel analysis approaches to disentangle its pathophysiology by computing large amounts of data are needed. We present an advanced machine learning technique, based on a clustering [...] Read more.
Autism spectrum disorder (ASD) is a heterogeneous condition, characterized by complex genetic architectures and intertwined genetic/environmental interactions. Novel analysis approaches to disentangle its pathophysiology by computing large amounts of data are needed. We present an advanced machine learning technique, based on a clustering analysis on genotypical/phenotypical embedding spaces, to identify biological processes that might act as pathophysiological substrates for ASD. This technique was applied to the VariCarta database, which contained 187,794 variant events retrieved from 15,189 individuals with ASD. Nine clusters of ASD-related genes were identified. The 3 largest clusters included 68.6% of all individuals, consisting of 1455 (38.0%), 841 (21.9%), and 336 (8.7%) persons, respectively. Enrichment analysis was applied to isolate clinically relevant ASD-associated biological processes. Two of the identified clusters were characterized by individuals with an increased presence of variants linked to biological processes and cellular components, such as axon growth and guidance, synaptic membrane components, or transmission. The study also suggested other clusters with possible genotype–phenotype associations. Innovative methodologies, including machine learning, can improve our understanding of the underlying biological processes and gene variant networks that undergo the etiology and pathogenic mechanisms of ASD. Future work to ascertain the reproducibility of the presented methodology is warranted. Full article
(This article belongs to the Special Issue Updates of DNA Variations in Evolution and Human Diseases)
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13 pages, 1154 KiB  
Article
Migration/Differentiation-Associated LncRNA SENCR rs12420823*C/T: A Novel Gene Variant Can Predict Survival and Recurrence in Patients with Breast Cancer
by Essam Al Ageeli, Samy M. Attallah, Marwa Hussein Mohamed, Amany I. Almars, Shahad W. Kattan, Eman A. Toraih, Manal S. Fawzy and Marwa K. Darwish
Genes 2022, 13(11), 1996; https://doi.org/10.3390/genes13111996 - 31 Oct 2022
Cited by 1 | Viewed by 1535
Abstract
Long non-coding RNAs (lncRNAs) have key roles in tumor development and the progress of many cancers, including breast cancer (BC). This study aimed to explore for the first time the association of the migration/differentiation-associated lncRNA SENCR rs12420823C/T variant with BC risk and prognosis. [...] Read more.
Long non-coding RNAs (lncRNAs) have key roles in tumor development and the progress of many cancers, including breast cancer (BC). This study aimed to explore for the first time the association of the migration/differentiation-associated lncRNA SENCR rs12420823C/T variant with BC risk and prognosis. Genotyping was carried out for 203 participants (110 patients and 93 controls) using the TaqMan allelic discrimination technique. The corresponding clinicopathological data, including the recurrence/survival times, were analyzed with the different genotypes. After adjustment by age and risk factors, the T/T genotype carrier patients were more likely to develop BC under homozygote comparison (T/T vs. C/C: OR = 8.33, 95% CI = 2.44–25.0, p = 0.001), dominant (T/T-C/T vs. C/C: OR = 3.70, 95% CI = 1.72–8.33, p = 0.027), and recessive (T/T vs. C/T-C/C: OR = 2.17, 95% CI = 1.08–4.55, p < 0.001) models. Multivariate logistic regression analysis showed that the T/T genotype carriers were more likely to be triple-negative sub-type (OR = 2.66, 95% CI = 1.02–6.95, p = 0.046), at a higher risk of recurrence (OR = 3.57, 95% CI = 1.33–9.59, p = 0.012), and had short survival times (OR = 3.9, 95% CI = 1.52–10.05, p = 0.005). Moreover, Cox regression analysis supported their twofold increased risk of recurrence (HR = 2.14, 95% CI = 1.27–3.59, p = 0.004). Furthermore, the predictive nomogram confirmed the high weight for SENCR rs12420823*T/T and C/T genotypes in predicting recurrence within the first year. The Kaplan–Meier survival curve demonstrated low disease-free survival (T/T: 12.5 ± 1.16 months and C/T: 15.9 ± 0.86 months versus C/C: 22.3 ± 0.61 months, p < 0.001). In conclusion, the LncRNA SENCR rs12420823*C/T may be associated with an increased risk of BC in women and could be a promising genetic variant for predicting recurrence and survival. Full article
(This article belongs to the Special Issue Updates of DNA Variations in Evolution and Human Diseases)
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