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Genetic and Neurodevelopmental Markers in Schizophrenia-Spectrum Disorders: Analysis of the Combined Role of the Gene and Dermatoglyphics.
Biomedicines
October 2024
FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Spain.
Article Synopsis
- The study investigates the link between dermatoglyphic patterns (fingerprint characteristics) and schizophrenia-spectrum disorders (SSD), suggesting these patterns may reflect neurodevelopmental vulnerabilities.
- Researchers analyzed the relationship between two genetic polymorphisms in the Cannabinoid Receptor 1 gene and three dermatoglyphic markers among 97 patients with SSD and 112 controls.
- Findings indicate that one genetic variant, rs2023239, modifies how dermatoglyphic pattern intensity relates to SSD risk, underscoring the potential role of the endocannabinoid system in neurodevelopment and highlighting the need for further research combining genetics and dermatoglyphics.
Unveiling intra-person fingerprint similarity via deep contrastive learning.
Sci Adv
January 2024
Department of Computer Science and Engineering, SUNY Buffalo, Buffalo, NY 14260, USA.
Fingerprint biometrics are integral to digital authentication and forensic science. However, they are based on the unproven assumption that no two fingerprints, even from different fingers of the same person, are alike. This renders them useless in scenarios where the presented fingerprints are from different fingers than those on record.
View Article and Find Full Text PDFFingerprint patterns in neuropsychological disorder depression among south Indian population.
Bioinformation
March 2023
Faculty of Allied Health Sciences, Chettinad Hospital and Research Institute, Chettinad Academy of Research and Education, Kelambakkam- 603103, Tamilnadu, India.
Depression is a pervasive mental health disorder characterized by persistent sadness and an inability to enjoy activities that were once enjoyable. This study compares the dermatoglyphic patterns of depressed patients with those of healthy, normal individuals in order to determine if dermatoglyphic patterns can be used as biomarkers for early diagnosis and prompt intervention of depression. A total of 100 depressive disorder patients of both sexes between the ages of 18 and 60 were selected for the study.
View Article and Find Full Text PDFBackground And Hypothesis: The existing developmental bond between fingerprint generation and growth of the central nervous system points to a potential use of fingerprints as risk markers in schizophrenia. However, the high complexity of fingerprints geometrical patterns may require flexible algorithms capable of characterizing such complexity.
Study Design: Based on an initial sample of scanned fingerprints from 612 patients with a diagnosis of non-affective psychosis and 844 healthy subjects, we have built deep learning classification algorithms based on convolutional neural networks.
Dermatoglypic patterns are extensively investigated to apply in disease-related risk assessment due to an obvious association between morphological and genetic characteristics. In the current study, we aimed to determine whether the fingerprint and palmar patterns vary between case population with schizophrenia and general population. A cross sectional study was conducted in people diagnosed with schizophrenia (cases) and a control population between 2016 and 2019.
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