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  3. Analysis of genetic diversity in patients with major psychiatric disorders versus healthy controls: A molecular-genetic study of 1698 subjects genotyped for 100 candidate genes (549 SNPs).
 

Analysis of genetic diversity in patients with major psychiatric disorders versus healthy controls: A molecular-genetic study of 1698 subjects genotyped for 100 candidate genes (549 SNPs).

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BORIS DOI
10.48350/191646
Publisher DOI
10.1016/j.psychres.2024.115720
PubMed ID
38224633
Description
BACKGROUND

This study analyzed the extent to which irregularities in genetic diversity separate psychiatric patients from healthy controls.

METHODS

Genetic diversity was quantified through multidimensional "gene vectors" assembled from 4 to 8 polymorphic SNPs located within each of 100 candidate genes. The number of different genotypic patterns observed per gene was called the gene's "diversity index".

RESULTS

The diversity indices were found to be only weakly correlated with their constituent number of SNPs (20.5 % explained variance), thus suggesting that genetic diversity is an intrinsic gene property that has evolved over the course of evolution. Significant deviations from "normal" diversity values were found for (1) major depression; (2) Alzheimer's disease; and (3) schizoaffective disorders. Almost one third of the genes were correlated with each other, with correlations ranging from 0.0303 to 0.7245. The central finding of this study was the discovery of "singular genes" characterized by distinctive genotypic patterns that appeared exclusively in patients but not in healthy controls. Neural Nets yielded nonlinear classifiers that correctly identified up to 90 % of patients. Overlaps between diagnostic subgroups on the genotype level suggested that (1) diagnoses-crossing vulnerabilities are likely involved in the pathogenesis of major psychiatric disorders; (2) clinically defined diagnoses may not constitute etiological entities.

CONCLUSION

Detailed analyses of the variation of genotypic patterns in genes along with the correlation between genes lead to nonlinear classifiers that enable very robust separation between psychiatric patients and healthy controls on the genotype level.
Date of Publication
2024-03
Publication Type
Article
Subject(s)
600 Technology > 610 Medicine & health
Keyword(s)
Alzheimer's disease Artificial intelligence Bipolar illness Classifiers Depression Gene vectors Neural nets Resilience Schizoaffective disorders Schizophrenia Singular genes Vulnerability
Language(s)
en
Contributor(s)
Stassen, H H
Bachmann, S
Bridler, R
Cattapan-Ludewig, Katja
Zentrum für Translationale Forschung der Universitätsklinik für Psychiatrie und Psychotherapie
Hartmann, A M
Rujescu, D
Seifritz, E
Weisbrod, M
Scharfetter, Chr
Additional Credits
Zentrum für Translationale Forschung der Universitätsklinik für Psychiatrie und Psychotherapie
Series
Psychiatry research
Publisher
Elsevier
ISSN
1872-7123
Access(Rights)
open.access
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