The underestimated topography of the fingertip: Finding a link towards a disrupted neurodevelopment.

The underestimated topography of the fingertip: Finding a link towards a disrupted neurodevelopment. | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 23 May 2025 V1 Latest version Share on The underestimated topography of the fingertip: Finding a link towards a disrupted neurodevelopment. Authors : Klaudia Kyselicová 0000-0002-5520-1657 [email protected] , Dóra Dukonyová , Dominika Sónak Ballová , Radoslav Beňuš , Katarína Polónyiová , and Michal Kuchař Authors Info & Affiliations https://doi.org/10.22541/au.174797283.33032327/v1 251 views 93 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract This study investigates the distribution of fingerprint minutiae types in boys with autism spectrum disorder (N = 48) compared to neurotypical controls (N = 46), with the aim of gaining insights into atypical developmental processes. The analysis focused on differences in the total number and types of minutiae across two areas of the fingerprint. Results showed no significant difference in the total number of minutiae across all fingers; however, notable differences were observed on the fourth finger (p = 0.001573) and in specific minutiae types. Boys with ASD showed a higher incidence of types like fragments, dots, and breaks in the central area (p < 0.00001), while neurotypical boys exhibited more enclosures. These findings suggest that the distribution and types of fingerprint minutiae could be potential markers for neurodevelopmental differences, as they indicate a disruption in the normal developmental pathways. The underestimated topography of the fingertip: Finding a link towards a disrupted neurodevelopment Short running title: not-yet-known not-yet-known not-yet-known unknown Fingerprint differences in autistic boys Author affiliations: Klaudia Kyselicová1, Dóra Dukonyová1, Dominika Sónak Ballová2, Radoslav Beňuš3, Katarína Polónyiová1, Michal Kuchař4 1 Academic Research Center for Autism, Institute of Physiology, Comenius University in Bratislava, Bratislava, Slovakia 2 Faculty of Civil Engineering, Slovak University of Technology in Bratislava, Bratislava, Slovakia 3 Department of Anthropology, Faculty of Natural Sciences, Comenius University in Bratislava, Bratislava, Slovakia 4Department of Anatomy, Faculty of Medicine in Hradec Králové, Hradec Králové, Czechia Corresponding author: not-yet-known not-yet-known not-yet-known unknown Klaudia Kyselicová not-yet-known not-yet-known not-yet-known unknown Academic Research Center for Autism Institute of Physiology, Faculty of Medicine Comenius University in Bratislava Sasinkova 4 813 72 Bratislava email: [email protected] ORCiD: 0000-0002-5520-1657 E-mail addresses: Dóra Dukonyová [email protected] Dominika Sónak Ballová [email protected] Radoslav Beňuš [email protected] Katarína Polónyiová [email protected] Michal Kuchař [email protected] Acknowledgments We thank to all participants enrolled in this study. This work was funded by the Slovak Research and Development Agency (grant number APVV20-0139) Declaration of interest statement None Data availability statement Raw data were generated at the Faculty of Medicine of the Comenius University in Bratislava (Slovakia). Derived data supporting the findings of this study are available from the corresponding author on request. Ethical consent Ethical approval for the study was obtained from the University Hospital and Faculty of Medicine Ethical Committee in Bratislava, Slovakia. Informed written consent was obtained from all individual participants enrolled in the study. The participants received the study information, and signed the study consent formed after being additionally verbally informed about the study details. All procedures of this study which involved human subjects were conducted according to the principles expressed in the Declaration of Helsinki. Informative title: The underestimated topography of the fingertip: Finding a link towards a disrupted neurodevelopment not-yet-known not-yet-known not-yet-known unknown Short running title: not-yet-known not-yet-known not-yet-known unknown Fingerprint differences in autistic boys Abstract This study investigates the distribution of fingerprint minutiae types in boys with autism spectrum disorder (N = 48) compared to neurotypical controls (N = 46), with the aim of gaining insights into atypical developmental processes. The analysis focused on differences in the total number and types of minutiae across two areas of the fingerprint. Results showed no significant difference in the total number of minutiae across all fingers; however, notable differences were observed on the fourth finger (p = 0.001573) and in specific minutiae types. Boys with ASD showed a higher incidence of types like fragments, dots, and breaks in the central area (p < 0.00001), while neurotypical boys exhibited more enclosures. These findings suggest that the distribution and types of fingerprint minutiae could be potential markers for neurodevelopmental differences, as they indicate a disruption in the normal developmental pathways. Key words: neurodevelopmental disorders, developmental instability, dermatoglyphics, volar pads, autism spectrum disorder Acknowledgments We thank to all participants enrolled in this study. This work was funded by the Slovak Research and Development Agency (grant number APVV 20-0070 and APVV20-0139) Declaration of interest statement None Data availability statement Raw data were generated at the Faculty of Medicine of the Comenius University in Bratislava (Slovakia). Derived data supporting the findings of this study are available from the corresponding author on request. Ethical consent Ethical approval for the study was obtained from the University Hospital and Faculty of Medicine Ethical Committee in Bratislava, Slovakia. Informed written consent was obtained from all individual participants enrolled in the study. The participants received the study information, and signed the study consent formed after being additionally verbally informed about the study details. All procedures of this study which involved human subjects were conducted according to the principles expressed in the Declaration of Helsinki. Introduction Fingerprint formation gained a lot of attention, since Li et al. defined specific genes responsible for the various processes involved not only in limb development but also in the ontogenesis of ridge formations (Li et al., 2022). This was followed by attempts of modelling the development of fingerprints, among which those of (Glover et al., 2023) contributed significantly in describing a cascade of genetic signaling. Naming specific genes and their involvement in the primary and secondary ridge formation on the fingertip. Nevertheless, these researches were never aimed on defining the atypical pathway of fingerprint formation, which would indicate a prenatal disturbance of the explored morphological processes. In this contribution we propose that the distribution of the different minutiae types within the fingerprint pattern may offer new insights into atypical developmental processes in individuals with a neurodevelopmental condition. Our hypothesis relies mostly on the topography and anatomical structure of the fingertip, but also on the sensoric specificities of the neuroepithelium in autistic children. The clinical significance of atypically formed fingerprints in different genetic conditions is undeniable (Trisomy 21, Boroffice, 1978; Trisomy 18, Uchida et al., 1962; Trisomy 13, Magenis et al., 1968; Cri-Du-Chat, Warburton & Miller., 1968; Klinefelter syndrome, Cushman & Soltan, 1969; Rubinstein-Taybi syndrome, Simpson & Brissenden, 1973). Even though these features are just listed among other morphological and anatomical deviations as part of the clinical phenotype, their value lies in something else – they open up new pathways for the research of the etiology of those conditions where the genetic background still remains somehow unseizable. As defined in The International Classification of Diseases, 11th Revision (ICD-11), autism spectrum disorder (ASD) is a neurodevelopmental disorder defined by persistent deficits in the ability to initiate and sustain reciprocal social interaction and communication, and by a range of restricted, repetitive, and inflexible patterns of behavior, interests, or activities (World Health Organisation, 2019). The genetic background relies upon thousands of possible genetic variants, and even de novo mutations (Sanders et al., 2015; Satterstrom et al., 2019), which hinder a solid prediction of the manifestation of the autistic phenotype or even the factors impacting the expression of these genes. Additionally, there aren´t any known morphological or anatomical features which would consistently correlate with ASD, indicating the absence of a universally defined ASD phenotype (Ozgen et al., 2011). This is true even for individuals with syndromic autism, where ASD symptoms are caused by other genetic syndromes such as Fragile X syndrome, Rett syndrome, and Phelan–McDermid syndrome (Fernandez & Scherer, 2017). As there are currently also no definitive biological markers available to confirm the diagnosis, the diagnostic process relies heavily on a combination of direct clinical observation (using standardized tools such as ADOS-2) and the assessment of core symptoms through a comprehensive developmental history analysis (with tools such as ADI-R). This is a lengthy and challenging process, especially due to waiting periods for diagnostic evaluations often being several months or even years due to a lack of specialized professionals and resources. Additionally, many parents may not recognize the early signs of autism in their child, and not even get them diagnosed soon enough. This happens because some behaviors associated with ASD, such as social withdrawal or delayed speech, can be subtle or attributed to other developmental delays (Mandell et al., 2005). Alternatively parents of children with Autism Spectrum Disorder (ASD) often exhibit subclinical traits associated with autism, known as the broader autism phenotype, which may impact their perceptions and interpretations of their child’s behaviors leading to a normalization of certain behaviors, potentially delaying the recognition and diagnosis of ASD in children (Rubenstein et al., 2019). Furthermore, the delay in recognizing symptoms is further compounded by the fact that teachers and healthcare providers often lack sufficient training in identifying early indicators of ASD (Zwaigenbaum et al., 2015). While behavioral markers will likely remain central to ASD diagnosis, the discovery of reliable biomarkers or other indicators could significantly reduce these diagnostic delays, improve accuracy, and ensure that children receive the appropriate support at the earliest possible age (Ritvo et al., 2011; Geschwind, 2011). Based on our previous research (Kyselicová et al., 2023), dermatoglyphic differences were detected in autistic boys when compared to age-matched peers. A higher frequency of ulnar loops and tented arches together with high pattern discordance could indicate a higher risk of being at the spectrum of autism. Our findings reveal the diagnostic potential of fingerprint patterns, but only if they can be supported by 2nd level details. In the previously published work, we also attempted to analyze the frequencies of second level details, but were limited by the sample size - the number of minutiae within a whorl was compared between ASD boys and typically developing boys, only for the fourth finger of the right hand. We compared 25 ring fingers from the ASD group with 20 ring fingers from the control group, but the number of second-level details did not differ significantly ( p = 0.65). We propose, that the key to understanding the etiology of neurodevelopmental disorders lies in detecting disrupting factors influencing mechanisms which underlie the formation of different types of minutiae (second level details) and impacts their frequency and distribution. Various theories concerning fingerprint formation have been published; among the most accepted are those that consider differential forces on the skin (mechanical theory) (Kücken & Newell, 2005; Hirsch & Schweighel, 1973); Kücken, 2007) and those having a genetic component (Cummins & Midlo, 1963; Kücken & Newell, 2005). From a mechanical point of view, it has been theorized that fingerprints are produced by the interaction of nonlinear elastic forces between the dermis and epidermis (Kücken, 2007). Each fingerprint is a papillary drawing composed by papillae and rete ridges (crests) (Bonnevie, 1924; Hale, 1949, 1952; Hirsch & Schweighel, 1973; Kücken & Newell, 2004, 2005). These crests are epidermal ridges having unique characteristics – minutiae (Kücken & Newell, 2005). We refer to these crests as papillary lines after taking the fingerprints onto a dactyloscopic card. Within these crests/lines, the second level details – minutiae could provide sufficient differences (e.g., in their frequency) to analyze the differences in the trajectory of normal vs. atypical fingerprint formation: The fingertips start to be defined from the seventh week onwards (Cummins & Midlo, 1963; Kücken & Newell, 2005) on the so-called volar pads. They continue to grow until about the 9th week and finally appear as high, rounded hillocks with a clearly defined base (Cummins, 1929). Indirectly, the selection of a particular fingerprint pattern (arch, loop, whorl), which will form the primary ridges, is influenced by genes. These genes exert an indirect effect on fingerprint pattern formation through their effects on digit length proportions and on the size and shape of the raised volar pads that are present from gestational weeks 9. – 15. There are several theories regarding the morphogenesis of primary ridges – they might form from pre-existing templates, intercellular signaling, or simple mechanical deformation of the epithelium (Kücken, 2007). A recent publication (Glover et al., 2023) showed, that fingerprint ridges undergo a truncated HF (hair follicle) developmental program and that the pattern is produced by a Turing reaction-diffusion system operating in several spreading waves, triggered at distinct initiation sites. The confluence of patterning waves initiated at these variable sites then determines the pattern type, which together with the inherent randomness of Turing systems delivers an individual uniqueness to each fingerprint. During fetal development of the hand the number of ridges increases to keep up with the hand’s growth (Hale, 1949; Babler, 1987). According to one theory, this process of ridge multiplication is believed to be responsible for the formation of the many small defects (minutiae) in fingerprint patterns. There are strong clues that the ridge system significantly changes until its final appearance because the number of minutiae increases significantly in this time (Hale, 1949). During the period of primary ridge growth, the finger rapidly expands, new primary ridges form and the existing primary ridges begin to divide. According to original theories on minutiae development, bifurcations are made by mechanical separation. New ridges pull away from existing primary ridges to fill in these divisions. Ridge endings are assembled when a developing ridge becomes barred between two settled ridges (Hale, 1952). The exact location of any particular bifurcation or ridge ending within the developing ridge field is directed by an accidental series of co-dependent forces acting across that particular area of skin at that critical moment. Differences in the physiological environment, mechanical stress or diversity in the timing of development could significantly influence the location of minutiae (Wertheim, 2014). It is noted that ridges tend to align perpendicularly to physical compression across a surface. Ridges form further transversely to the lines of growth stress in friction skin. Ridges commonly cover the volar surface transversely and the main growth of the hand is longitudinal (Wertheim, 2014). At the time of embryonic friction ridge formation, the central nervous and cardiovascular systems are in their critical developmental phase (Hirsch, 1964). Previous research has reported the appearance of nerve endings (innervation) at the sites of ridge formation immediately preceding the appearance of ridges, and suggests this could be the trigger mechanism for the onset of cell division (proliferation) (Bonnevie, 1924; Dell & Munger, 1986; Hirsch & Schweighel, 1973; Moore & Munger, 1989). Several researchers even postulated that the distribution of the capillary-nerve pairs at the junction of the epidermis and dermis directly influences the alignment of the primary ridges (Hirsch & Schweighel, 1973; Dell & Munger, 1986; Moore & Munger, 1989). Later discoveries confirm the neurological relation of spinal cord sections C-6, C-7, and C-8 to innervation of the fingers (Heimer, 1995). This offered some support to the link between innervation and volar patterning. Most likely, the alignment of the nerves and/or capillaries is directed by the same stresses and strains of the developing hand that establish ridge alignment (Smith & Holbrook, 1986). Among potential explanations for the different organization (frequency) of first (and as proved in this article, also second-) -level details in autistic individuals, is the primary function of fingerprints, which is sensation. In general, the skin is a highly sensitive organ responding to various mechanical and chemical stimuli through orchestrated cellular and molecular signals. Sensory issues are very common in people with ASD. About 90% of ASD individuals have atypical sensory experiences, described as both hyper- and hypo-reactivity, with abnormal responses to tactile stimulation (Marco et al., 2011). An in-depth analysis of somatosensory defects detected in mouse lines harboring mutations in ASD-relevant genes was published by (Balasco et al., 2020). But it still remains unclear whether underlying sensory mechanisms are altered, or it is the emotional response to sensory input that leads to issues in filtering of the signal resulting in hyper/hypo-responsiveness. Fingerprint formation finishes at about week 19 (Kücken, 2007). From this time on, the fingerprints stop changing for the rest of an individual’s lifetime. Materials and methods We investigated the fingerprints of 48 boys with autism spectrum disorder (ASD) aged between 2.75 and 12.92 years (SD = 2.56). All of the enrolled boys were of Slovak nationality and residents of the Slovak republic. In total, a set of 480 fingerprints of ASD boys were evaluated. Prior to this analysis 274 fingerprints belonging to 30 participants with ASD were rejected due to poor quality. The diagnosis of ASD was confirmed at the Academic Research Center for Autism (ARCA) at the Faculty of Medicine of the Comenius University in Bratislava, using Autism Diagnostic Observation Schedule, Second Edition (ADOS-2) (Lord et al., 2012) and Autism Diagnostic Interview-Revised (ADI-R) (Lord et al., 1994), which are considered the gold standard of autism diagnostics. ADI-R is a semi-structured interview conducted with the parents and consisting of 4 subscales: Qualitative Abnormalities in Reciprocal Social Interaction, Qualitative Abnormalities in Communication, Restricted, Repetitive, and Stereotyped Patterns of Behavior, and Abnormality of Development Evident at or Before 36 Months. ADOS-2 is a direct examination of the individual, consisting of 5 different modules, chosen based on the individual´s chronological age and level of expressive language proficiency. Module 1 includes individuals older than 31 months, with speech limited to using a few words. Module 2 is intended for children who communicate in simple phrases and sentences. Module 3 is used for individuals using fluent, grammatically correct speech. To enable comparison of the results of children from different modules, a calibrated score has been introduced. Overall ADOS-2 score is calculated as well as scores for two separate domains: Social affect and Restricted and repetitive behaviors. In our research sample, 20 children (43.75%) were administered Module 1, 8 children (16.66%) Module 2 and 11 (22.92%) belonged to the Module 3. Simultaneously, a control group of 46 neurotypical boys from the general population aged 2.75 - 12.33 years (SD = 2.88), was recruited. We collected their fingerprints among other biological/anthropological parameters due to their participation in another project aimed on monitoring the development of pre-school and school children in Slovakia. In this group, only boys without detected developmental abnormalities, syndromes and without learning disorders, were enrolled. This information was requested in accordance with the informed consent form signed by the parents or legal guardians. Fingerprints were obtained by the rolling method, which captures the complete papillary terrain, rolling the finger from the outer lateral edge to the inner medial edge. Prior to this, dactyloscopic dye was applied directly to the child’s hands by using the dactyloscopic roller Printmatic impregnated with black dye. This procedure was chosen because it was very effective and quick especially in cases where the child refused to cooperate. Individual fingers were printed two to three times onto a dactyloscopic card. Consequently, only best quality fingerprints were chosen for the analysis. Before processing, the prints were scanned at a resolution of 1200 dpi (dots per inch) and then analyzed using GIMP 2.10.22. The fingerprints were graphically divided and evaluated, based on three topographically distinct areas in a radius from: • the center of the pattern to the 6th papillary ridge, • from the 6th to the 12th papillary ridge, • from the center of the pattern to the 12th papillary ridge. The evaluated areas were determined by a circle with a radius from the center of the pattern to the 6th and 12th papillary ridge (Picture 1). This is a modification of the methodology described by Okajima (1970), which was adapted to the quality of the collected prints for the purposes of this research. Please insert Picture 1 and 2 The count of papillary ridges allowed us to establish the number and type frequencies of minutiae in two different topographic areas of the fingerprint. The number and type of minutia in the central area (from the center of the pattern to the 6th papillary ridge) and the “periphery” (from the 6th to the 12th papillary ridge). The diameter of the circle always cuts across 12 ridges to eliminate any possible differences caused by the size of the finger and the ridges. The classification by (Gutiérrez et al., 2007), a classification of second level details used by the Spanish police scientists was used. The different minutiae types were marked out manually and the colored minutiae/characteristic points were subsequently designated by the letters of the alphabet a – m. The number of individual minutiae and the number of papillary ridges were determined. Statistical processing was carried out using R Studio. The analyzed data are the number of minutia types of two groups - the group of boys with autism spectrum disorder (N = 48) and the group of neurotypical boys (N = 46). The data were organized into contingency tables to evaluate the presence of association between variables - group and minutiae type. For this purpose, we used and compared the results of two tests - the chi-square independence test and the Fisher exact test. The effect size for contingency tables was determined using Cramer’s V. We have used the tests multiple times, which can affect the alpha inflation. Therefore, when evaluating the results, we used the Bonferroni correction to evaluate the significance of the results of the tests. not-yet-known not-yet-known not-yet-known unknown Results In the first stage of the evaluation, the differences in the total number of minutiae on all five fingers and both hands between boys with ASD (N = 48) and between neurotypical individuals (N = 46) were compared. There is no statistically significant difference in the total number of minutiae of boys with ASD and the control group. When looking at individual fingers, there is a statistically significant difference in the total number of minutiae only on the fourth finger at the periphery of the fingerprint (p = 0.001573). Here there are statistically significantly more minutiae on the right hand for the ASD group while on the left hand it is statistically significantly more minutiae for the group of neurotypical boys (Table 1). In the next step, we looked at the differences with respect to individual types of minutiae. Those types of minutiae whose number was too small for both groups were excluded from the analyses (crossbar, opposite bifurcation, Y, dock, return). The reason for this is that the chi-square test assumes at least 5 expected values in the tested contingency tables. Differences were found in all the three observed areas of the fingerprint (i.e., in area of 6 papillary lines, from the 6th to 12th papillary line and in the whole area of fingerprints- 12 papillary lines). The following test results are also summarized in Tables 1 and 2 and Figure 1. If we first consider the center of the fingerprint, that is, 6 papillary lines, there is a statistically significant difference in the number of five types of minutiae between boys with ASD and neurotypical boys. For minutia types ending, fragment and dot their number is statistically significantly higher for the group of boys with ASD than for the group of neurotypical boys. On the contrary, types of minutiae break, and enclosure are statistically significantly more common for neurotypical boys. These results are also displayed in Figure 1, where we can see the types of significant minutiae and their contribution to the total chi-squared statistics. Blue color indicates a higher presence of minutiae in the given group, while red represents a lower number of minutiae. In the other part of the figure, the size and intensity of the color of the circles represents how each type of minutiae contributes to the overall chi-squared statistics. As we can see, minutia type enclosure contributes the most, while at least type overlap, for which the difference was not statistically significant. Please insert Figure 1 We also examined how these differences manifest themselves on the right and left hands separately. At this fingerprint level, minutia type fragment is on the right hand statistically significantly more frequent in the group of ASD boys than for neurotypical boys. There is no statistically significant difference in other types of minutiae on the right hand in the center area. On the left hand as well as in the results, regardless of which hand it was on, the statistically significant difference was in the higher presence of enclosure minutia for neurotypical boys (Table 2). Also, on the periphery of the fingerprint (6th- 12th papillary line), differences were found in five minutiae. But in this area minutiae dot, break, enclosure, and bridge were found statistically significantly more frequent for boys with ASD. Unlike the central area, in this area the number of minutiae ending is statistically significantly higher for the neurotypical boys. In the periphery of fingerprints of the right hand, we observe a statistically significantly higher incidence of minutiae dot, break, and bridge for boys with ASD. On the left hand, we similarly observe significantly higher occurrence of the following minutiae for ASD boys- break, enclosure, and overlap (Table 2). When we take the whole fingerprint, the difference between the groups is only in the minutia dot (Tab 1). This type of minutia is statistically significantly more present for the group of ASD boys. At this level, there is no statistically significant difference between other types of minutiae (Table 2). Considering the entire fingerprint area of the right hand, we observed a significantly higher number of dots as well as on the left hand for boys with ASD. The left hand also has a statistically significantly higher number of minutiae fragment among boys with ASD. In the next part of the study the number of minutiae on individual fingers were monitored. Again, we first investigated whether there was a statistically significant difference in the number of minutiae between the ASD and the control group, regardless of whether the given finger is on the right or left hand. Then we made the comparison between the groups for the right and left hand separately. It was also examined in the above three fingerprint areas for all the fingers. The following results are also summarized in Table 2. On the first finger, only the two separated areas (center and periphery) of the fingerprint showed a statistically significant difference, while the entire fingerprint area did not show significant difference between the groups (p = 0.6663). In the center and periphery of the fingerprint on this finger, a statistically significant difference was shown if we did not consider which hand, it was, i.e., for the total number of given minutiae in this area. In the center area it was statistically significantly higher number of enclosures for neurotypical boys (p = 0.0005422). The area between the 6th and 12th papillary lines has significantly higher occurrence of breaks for boys with ASD (p = 0.0000984). For the first finger of right hand the difference between ASD boys and neurotypical boys was found only at the periphery of the fingerprint (p = 0.001208). The difference consists in that neurotypical boys have statistically significantly higher number of endings in this area on the first finger of right hand than boys with ASD. On the left hand there exists a statistically significant difference in both areas between the two groups. At the center of the fingerprint the group of neurotypical boys has statistically significantly higher number of enclosures (p = 0.0000257). The periphery shows statistically significant difference in enclosure and break (p = 0.0008537). Their occurrence is higher in the ASD group. On the second finger, differences between groups were found as statistically significant only in the periphery of the left hand and in the periphery, regardless of which hand the finger is on. On the second finger on left hand of boys with ASD the number of enclosures is significantly higher than the number of enclosures of neurotypical boys (p = 0.0009081). Regardless of which hand the finger is located on, in addition to a higher number of enclosures, there are also more dots for the ASD group (p = 0.0009178). On the third finger on the periphery of this finger, regardless of which hand it was on, there is a statistically significant difference in the number of minutiae bridge (p = 0.0004952). The number of these minutiae is statistically significantly higher in this area for the ASD group. In addition, there is a difference between groups also on the left hand (p = 0.003948). The difference here is in the number of enclosures which is statistically significantly higher for boys with ASD. If we take the entire area of the fingerprint, there is also a difference regardless of which hand the finger is on (p = 0.001317). Boys with ASD have statistically significantly more dots in this area of the fingerprint. For the fourth finger, on 6 papillary lines, we found a statistically significant difference between ASD and controls on the left hand, and regardless of the hand on which the finger is located (p for the left hand is 0.001054, p regardless of the hand is 0.002492). In both cases, there are significantly more minutiae fragment on this finger in the group of boys with ASD. In addition, more enclosures were found on the left hand of neurotypical boys than in the group of ASD boys. Without considering the hand, boys with ASD also have statistically significantly higher number of dots. In the periphery of the fingerprint, the difference did not turn out to be statistically significant either on the left (p = 0.4858) or on the right hand (p = 0.05006), only if we take the total number of minutiae regardless of the hand (p = 0.005823). Here the groups differ in the number of enclosures, ASD boys have a higher number of these minutiae than neurotypical boys. In the case of the entire fingerprint, the difference between the groups is significant in case we do not distinguish which hand the finger is located on (p = 0.006093). On the entire surface of this fingerprint, ASD boys have a higher number of dots. Most differences were found when examining the number of minutiae on the fifth finger. In both the center and periphery, a statistically significant difference was shown between groups on the right hand as well as regardless of which hand the finger is located on (p for center of the right hand = 0.007259, p for the periphery of the right hand = 0.002014, p for center regardless the hand = 0.006239, p for periphery regardless the hand = 0.0001196). There are more overlaps for the ASD group on the periphery of the right finger fingerprint, while there are more fragments for the right fingerprint for the ASD group in the center of the fingerprint. Regardless of the hand, the differences are the same as the differences found on the right hand. If the entire surface of the fingerprint has been taken, then there is a difference for both the left hand (p = 0.0000378) and the right hand (p = 0.003768), and regardless of which hand the finger is located on (p = 0.000449). On the left hand of ASD boys there are more breaks and enclosures than for neurotypical boys. On the right hand, as well as regardless of the hand, boys with ASD have more overlaps. All these differences are statistically significant after correction for the significance level according to the Bonferroni method. This was used to adjust alpha inflation. The effect size was calculated using the Cramer’s coefficient V. In most of the tests this coefficient indicated a small association (with values from 0.1 to 0.15 and 1 degree of freedom) between the variables. Please insert Table 1 and Table 2 Discussion The present study aimed to explore minutiae types in the fingerprints of boys with Autism Spectrum Disorder (N = 48) compared to neurotypical boys (N = 46). The findings of the study suggest notable differences in the distribution of minutiae types between the compared groups, offering insights into the potential role of genetic and developmental factors in ASD. There is a strong correlation between ridge differentiation and limb embryogenesis as various developmental disorders are reflected in the ridges (Arrieta et al., 1990). So, the ridge pattern is impaired by certain abnormalities that mainly include genetic disorders. The formation of fingerprints may then be atypical, providing clues to the underlying genetic and mechanical developmental disruptions associated with these disorders. In recent years, scientific literature has explored how specific genetic mutations and conditions can impact fingerprint development. Unfortunately, studies that have examined the association between dermatoglyphic formation and autism spectrum disorder are significantly limited, not only in terms of the depth of the analysis but also in terms of the size of the studied population (see an overview of these studies in Table 3). Screening for dermatoglyphic abnormalities in ASD individuals has so far focused only on the frequency of first level details (pattern), ridge count and ATD angle, but rarely on second level details (minutiae). And none of the studies dealing with dermatoglyphs, consider the detailed topography of the fingertip. They do not distinguish between the center and the surrounding area or any other sub-regions within the fingertip surface. Please insert Table 3 Biomechanically, the fingertip behaves as an adaptive, ellipsoidal, quasi-static membrane under compressive forces. The subcutaneous matrix enables a nonlinear elastic response, which provides flexibility and absorbs impact while maintaining sensory feedback. In this area, the innervation is particularly dense (Serina et al., 1998). Mechanoreceptors, including Merkel cells, Meissner corpuscles, and Pacinian corpuscles, are embedded within the pulp, with higher concentrations in the central area – the fingerprint center. The vascularization is extensive, featuring finely branched networks. Proper digital arteries supply a dense capillary network within the pulp, with arteriovenous anastomoses and glomus bodies in the deep dermis and subcutaneous tissue that assists in thermoregulation. Perforating branches of the digital arteries supply the skin and subcutaneous tissues, maintaining tissue resilience under varying pressure conditions, especially during sustained grip or repeated contact. The epidermal ridges form the characteristic fingerprint patterns unique to each individual. These ridges are not uniformly distributed; central areas tend to have more densely packed ridges compared to the periphery. The ridge structure increases friction during object manipulation, improving grip and facilitating fine motor control. Differences in structure and function are notable across individual fingers. The thumb has a broader, more robust volar pad with a higher ridge breadth, optimized for opposition and pinch strength, essential for power grips. In contrast, the index finger has a thinner, more sensitive volar pad with a high ridge density and abundant sensory receptors, allowing for delicate tasks. The middle finger, with a thicker pad and broader ridges, contributes to grip stability and strength, while the little finger, with small, closely packed ridges, is suited for delicate object handling. Overall, the shape of the volar pad varies between different fingers, with the thumb having the largest pulp volume, followed by the middle finger, ring finger, index finger, and little finger. The order of decreasing ridge breadth is as follows: thumb – index – middle – little - ring (Serina et al., 1998; Králík & Novotný, 2003). Given the above-described differences in the ridge distribution on different fingers and within the fingertip itself (the center of the fingerprint versus it´s “surrounding”), the here presented study focused on describing the differences/deviations from normal fingerprint pattern formation in autistic individuals with regards to the topography of the fingerprint. Our study uncovered a striking pattern difference in minutiae types between the two groups, especially in the central and peripheral areas of the fingerprints. Specifically, ASD boys had a higher prevalence of certain minutiae types, including – ending, fragment, dot (p < 0.00001), particularly in the central region of the fingerprint (0 – 6 papillary line). Those are minutiae types which imply that they originate from some kind of “breaking of the papillary line, when the original line is “split” into smaller fragments. On the contrary, they had a higher frequency of minutia types – dot, break, enclose, bridge and overlap (p < 0.00001), in the “periphery) of the fingerprint, in either one of the hands, or in case of the minutiae “break” in both hands. The most important question here is – What is the mechanism behind the formation of minutiae types ending, fragment and dot? Dots are small, isolated ridges or spots that form as minor interruptions or breaks in the ridge system. These dots arise during the early phases of ridge formation when cellular events such as apoptosis (programmed cell death) or mechanical disturbances result in small, localized interruptions in ridge continuity. Dot formation is often associated with irregularities in the epidermal ridge structure, which may be caused by genetic or mechanical influences during fetal skin development. According to our results, we can suggest that the mentioned irregularities occur more often in autistic children. Similar to the formation of dots, fragments are small ridge segments that do not connect to the larger ridge system (they can be seen as longer dots). The formation of fragments is primarily attributed to incomplete or irregular ridge development. Recent studies have shown that fibroblast growth factors (FGFs) play an essential role in regulating the proliferation and differentiation of skin cells during ridge formation, and any disruption in these processes can lead to the formation of fragment minutiae. These disruptions may be the result of both genetic mutations and external mechanical factors, such as pressure or stretch forces acting on the skin during fetal movement. Ending ridges are points where a ridge abruptly ends within the fingerprint. The development of these minutiae is linked to the termination of epidermal ridges. Studies have shown that Wnt/β-catenin signaling plays a crucial role in regulating the formation of epidermal ridges and their eventual segmentation into distinct minutiae features, including ending ridges as the ridge pattern becomes established, local disruptions in ridge formation, influenced by both genetic and mechanical factors, result in the creation of ridges that end without continuing further. The establishment of these features has something in common – they are dependent (their frequency is dependent) upon local disruptions, irregularities in the formation and timing of their development and underline the importance of the fetal environment in which these molecular signaling pathways work. Therefore, we suggest that our results/ the differences found, may reflect variations in the underlying genetic and developmental processes that guide ridge formation, with potential contributions from Turing´s reaction-diffusion model of pattern formation. This model suggests that biological patterns such as ridges and minutiae emerge from the interaction of signaling molecules and local cellular processes during early development (Madzvamuse et al., 2003). Turing reaction explains that a spatial pattern is established by a Turing reaction-diffusion system, based on signaling between EDAR, WNT, and antagonistic BMP pathways. These signals resolve epithelial growth into bands of focalized proliferation under a precociously differentiated suprabasal layer. Ridge formation occurs as a set of waves spreading from variable initiation sites defined by the local signaling environments and anatomical intricacies of the digit, with the propagation and meeting of these waves determining the type of pattern that forms. When we take the whole fingerprint, the difference between the groups is only in the minutia dot. This type of minutia is statistically significantly more present for the group of ASD boys. At this level, there is no statistically significant difference between other types of minutiae. Therefore, we consider it of crucial importance to take into account splitting the fingerprint area into topographic subareas when studying the distribution of minutiae types, because the anatomy of the fingerprint may play a role as well. To further discuss the “anatomical intricacies of the digit „which may predefine the fingerprint formation, from a biomechanical perspective, the structure of the fingertip plays a crucial role in the formation of fingerprint patterns. The fingertip´s volar side is a highly specialized structure, optimized for both sensory perception and motor functions. The distinct topography of the fingertip, with its dense network of mechanoreceptors and collagen fibers, might influence the distribution of minutiae, particularly in the central versus peripheral regions. Hypothetically, differences in ridge formation could correlate with differences in sensory sensitivity and tactile functions, which are often altered in ASD individuals. This is particularly relevant when considering the observed higher frequency of „dot “, „ending „and „fragment“in ASD boys, which may reflect subtle alterations in sensory processing. One key observation was that statistically significant differences in minutiae on the fourth finger´s periphery. This suggests that specific fingers may be more susceptible to developmental variations in individuals with ASD. The discrepancy between the left and right hands further emphasizes the complexity of these patterns, which could be influenced by both genetic and environmental factors. Despite the novel contributions of this study, several limitations should be acknowledged. The relatively small sample size of boys with ASD limits the generalizability of the findings. Additionally, while the study observed significant differences in minutiae across various regions of the fingerprint, the underlying mechanisms driving these differences remain unclear. Further research should focus on larger, more diverse populations. Future studies could also expand on the analysis of minutiae in specific subtypes of ASD, as the heterogeneity of the disorder might lead to different dermatoglyphic profiles. Moreover, exploring the relationship between minutiae formation and sensory processing in ASD could yield important insights into the functional implications of these differences. Conclusion In conclusion, the present study highlights the potential of fingerprint minutiae as a tool for understanding ASD, specifically in the context of developmental and genetic factors. 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List of figures Figure 1: a) Mosaic plot of the dependence between the group and minutia types at the center of the fingerprint on both hands b) Corresponding relative contribution of each cell to the total Chi-square score. Supplementary Material File (table_1.docx) Download 14.28 KB File (table_2.docx) Download 14.58 KB File (table_3.docx) Download 18.10 KB Information & Authors Information Version history V1 Version 1 23 May 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords brain development developmental biology developmental neurobiology & genetics embryology tactile discrimination Authors Affiliations Klaudia Kyselicová 0000-0002-5520-1657 [email protected] Univerzita Komenskeho v Bratislave Lekarska fakulta View all articles by this author Dóra Dukonyová Univerzita Komenskeho v Bratislave Lekarska fakulta View all articles by this author Dominika Sónak Ballová Slovenska technicka univerzita v Bratislave Stavebna fakulta View all articles by this author Radoslav Beňuš Univerzita Komenskeho v Bratislave Prirodovedecka fakulta View all articles by this author Katarína Polónyiová Univerzita Komenskeho v Bratislave Lekarska fakulta View all articles by this author Michal Kuchař Univerzita Hradec Kralove View all articles by this author Metrics & Citations Metrics Article Usage 251 views 93 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Klaudia Kyselicová, Dóra Dukonyová, Dominika Sónak Ballová, et al. 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