Expressão de individualidade biológica na periodontite usando algorítmo específico e o Método Salus

Abstract

Periodontitis is a multifactorial inflammatory condition associated with the accumulation of dysbiotic biofilm and is highly prevalent among adults. It leads to the progressive destruction of periodontal tissues and may result in tooth loss. The Salus method employs Validated Computerized Dermatoglyphics (DIV) for biometric analysis of fingerprints through a specific algorithm within the Science software. This software has been used as a marker of biological individuality in various clinical conditions. This study aimed to determine dermatoglyphic patterns in individuals with a clinical diagnosis of periodontitis, applying a specific algorithm from the Science software. A total of 157 participants (30 females), aged between 30 and 64 years, were evaluated. The periodontitis group included 62 individuals (mean age: 53.7 years), while the control group, composed of healthy individuals, comprised 95 participants (55 females; mean age: 48.2 years). In the periodontitis group, clinical periodontal examination confirmed probing pocket depths of at least 4 mm (stages III and IV). In the control group, periodontal health was verified by the absence of periodontal pockets during probing. All participants underwent a digital fingerprint scan of all ten fingers using the Salus method to assess fingerprint pattern type and ridge count per finger. After fingerprint capture, the images were analyzed using the Science software algorithm, which included noise reduction, classification of fingerprint patterns, identification of cores and deltas, tracing of Galton lines, and ridge count processing. For the statistical analysis, the Kolmogorov-Smirnov, Student’s t-test, Mann-Whitney, and Fisher’s Exact tests were used. The significance level was set at 0.05. Comparative analysis between the groups with (n = 62) and without periodontitis (n = 95) showed similar demographic and anthropometric characteristics, except for age, which was significantly higher in the periodontitis group (p = 0.004). No significant differences were found in weight, height, or gender distribution, indicating homogeneity between the samples. Regarding qualitative dermatoglyphic patterns, the ulnar loop (LU) was the most frequent pattern across all fingers in both groups. The whorl (W) was the second most common pattern, with a frequency greater than 30% in specific fingers—MET2, MDT2, and MDT4 in the case group, and MET4, MDT2, and MDT4 in the control group. Other patterns, such as S-type whorl (WS), radial loop (LR), and arch (A), were infrequent. However, no statistically significant differences were observed in the distribution of fingerprint patterns between groups (p > 0.05), suggesting that periodontitis does not influence qualitative dermatoglyphic profiles. Quantitative analysis also showed similarities between groups. The average number of ridges per finger was comparable, with total ridge counts per hand and per individual nearly identical (113.7 in the periodontitis group and 112.6 in the control group). Delta distribution was also consistent with typical loop patterns, with one delta per finger being the most common. The mean number of deltas was 13.2 in the periodontitis group and 12.7 in the control group, with no statistically significant difference. The analysis of the total number of fingerprint patterns by type revealed similar distributions regarding medians and interquartile ranges, with no statistical differences across all categories assessed (W, WS, UL, RL, and A). Based on the methodology employed, it can be concluded that there is no significant association between dermatoglyphic patterns, both qualitative and quantitative, and the clinical presence of periodontitis. Despite the shared genetic origin between digital ridges and ectodermal structures, the data do not support the existence of a specific dermatoglyphic profile for individuals with periodontitis. The predominance of ulnar loop (UL) patterns and the similarity in ridge and delta counts between groups reinforce the absence of relevant phenotypic differences in digital patterns related to the disease. Thus, based on the evaluated sample and the method used, the validated computerized dermatoglyphics did not prove effective as a standalone biometric marker for identifying or screening individuals with periodontitis.