European Journal of Cardiovascular Medicine

The identification of individuals, whether living or deceased, is a cornerstone of forensic science. This process relies heavily on the analysis of unique physical and mental attributes, which serve as critical tools in forensic investigations. One of the foundational principles in forensic science is Locard's exchange principle, which posits that whenever two objects come into contact, there is an exchange of materials between them [1]. This principle underscores the importance of trace evidence in criminal investigations. For instance, a perpetrator may inadvertently leave behind traces of their presence at a crime scene, such as fingerprints or blood stains, while also carrying away traces from the scene. These exchanged materials can provide invaluable forensic evidence, aiding in the identification of suspects or victims [1]. Among the various forms of trace evidence, fingerprints have emerged as one of the most reliable and widely used tools for personal identification. The scientific study of fingerprints, known as dermatoglyphics, focuses on the naturally occurring epidermal ridges found on the fingers, palms, and soles, as well as the flexion creases and secondary folds. The term "dermatoglyphics" was introduced by anatomist Harold Cummins in 1926, who discovered that the patterns of these ridges are influenced by both genetic factors and environmental conditions during fetal development [2]. The formation of these ridges begins during the early stages of intrauterine life, with the proliferation of the corium (dermis) leading to the development of papillary projections into the epidermis. These projections eventually form the unique patterns of papillary ridges, which are fully established between the 11th and 24th weeks of gestation [3]. Once formed, these patterns remain unchanged throughout an individual's life, except for proportional growth to accommodate physical development [4]. This permanence and uniqueness make fingerprints an invaluable tool for identification. Fingerprint analysis, or dactylography, has been a cornerstone of forensic science for over 150 years. It is widely used for security, authentication, and personal identification purposes across the globe. Dermatoglyphics has also proven to be a valuable tool in various fields, including biology, medicine, genetics, and evolutionary studies, due to its ability to provide insights into human development and heredity [5,6]. Even in cases of monozygotic twins, who share identical genetic material, dermatoglyphic patterns remain distinct and unique, further highlighting their reliability as identifiers [5]. Fingerprints are not only permanent but also highly detailed, making them nearly impossible to alter or replicate. This makes them an ideal biometric marker for identification purposes. Similarly, blood groups, which are determined by the presence or absence of specific antigens on the surface of red blood cells, are another biological characteristic that remains constant throughout an individual's life [7]. The combination of fingerprints and blood group analysis can provide a robust framework for personal identification in forensic investigations. In forensic science, identification methods are broadly categorized into two types: (a) possession-based identification, which relies on objects or information owned by an individual, such as keys or login credentials, and (b) biometric identification, which is based on physical or behavioral characteristics, such as fingerprints, voice patterns, or signatures [8]. Among these, biometric methods, particularly those involving fingerprints and blood groups, are considered more reliable and secure because they are inherently linked to an individual's biology and cannot be easily forged or duplicated [8]. This makes them indispensable tools in criminal investigations, where the accuracy and authenticity of identification are paramount. Despite advancements in forensic technology, the early identification of perpetrators remains a significant challenge in criminal investigations. Often, the only evidence available at a crime scene consists of fingerprints and bloodstains. These traces can provide critical clues for identifying both victims and suspects. The present study seeks to explore the potential relationship between primary fingerprint patterns, gender, and ABO and Rh blood groups. By investigating these associations, the study aims to enhance the utility of fingerprints in forensic investigations, enabling more accurate determination of gender and blood group from fingerprint analysis and vice versa. This could significantly improve the efficiency and reliability of criminal investigations, aiding in the identification of both perpetrators and victims. The study was conducted among healthcare workers at a tertiary care teaching institute in Eastern India. The primary objectives were to identify the predominant fingerprint patterns in this population and to examine their correlation with gender and blood groups. The findings of this study could have far-reaching implications, not only for forensic science but also for the development of local biometric databases. Such databases could serve as valuable resources for law enforcement agencies, particularly in regions where research on fingerprint patterns is limited. By addressing the current paucity of data on fingerprint patterns in this region, the study aims to contribute to a deeper understanding of dermatoglyphics and its applications in forensic science.

This cross-sectional observational study was conducted on 200 medical students studying in the Indira Gandhi Institute of Medical Sciences (IGIMS), Patna, Bihar (India).

Inclusion Criteria:

1. Age Group: Participants aged 18 years and above were included in the study. This age group was chosen to ensure that fingerprint patterns were fully developed and stable, as dermatoglyphic patterns are established by the 24th week of gestation and remain unchanged throughout life [3,4].
2. Voluntary Participation: Only individuals who provided informed consent to participate in the study were included. Written consent was obtained from all participants after explaining the purpose and methodology of the study.
3. Availability of Blood Group Data: Participants with known ABO and Rh blood group information, either through previous medical records or voluntary testing during the study, were included. This was essential for analyzing the relationship between fingerprint patterns and blood groups.
4. Clear and Legible Fingerprints: Individuals with clear, legible, and complete fingerprints on all ten digits were included. This ensured accurate classification and analysis of fingerprint patterns.

Exclusion Criteria:

1. Age Below 18 Years: Individuals below 18 years of age were excluded to avoid the inclusion of minors and to ensure that fingerprint patterns were fully developed and stable.
2. Presence of Skin Conditions or Injuries: Participants with skin conditions such as eczema, psoriasis, or burns, or those with injuries, scars, or deformities on their fingertips that could alter or obscure fingerprint patterns, were excluded. Such conditions could interfere with the accurate recording and analysis of dermatoglyphic patterns.
3. Unwillingness to Participate: Individuals who did not provide informed consent or were unwilling to participate in the study were excluded.
4. Incomplete or Unclear Fingerprints: Participants with smudged, incomplete, or unclear fingerprints that could not be accurately classified were excluded from the study.
5. Unknown Blood Group: Individuals who did not know their ABO and Rh blood group and were unwilling to undergo blood group testing during the study were excluded.
6. Systemic Diseases Affecting Dermatoglyphics: Participants with systemic diseases or genetic conditions known to affect dermatoglyphic patterns, such as Down syndrome or other chromosomal abnormalities, were excluded. These conditions can alter fingerprint patterns, potentially skewing the study results [2,3].

The study employed a universal sampling technique to enroll participants, ensuring that all eligible individuals within the target population had an equal opportunity to participate. This approach was chosen to achieve a representative sample of healthcare workers at the tertiary care institute in Bihar. The methodology for collecting and analyzing fingerprint patterns was meticulously designed to ensure accuracy and reliability, drawing on established techniques in dermatoglyphics and forensic science.

Fingerprint Collection Process:

1. Preparation of Materials: A proforma was printed on thick white A4-size paper to record the fingerprints and demographic details of the participants. The materials used for fingerprint collection included:
   • A Faber-Castell blue ink pad, chosen for its consistent and clear imprint quality.
   • White A4-size paper for recording fingerprints.
   • Cardboard to provide a firm surface for imprinting.
   • Gauze pads for cleaning the ink pad and participants' fingers.
   • A magnifying lens for detailed examination of fingerprint patterns.
   • A pencil and pen for documenting participant information and observations.

2. Informed Consent and Demographic Data Collection: Each participant was provided with a detailed explanation of the study's purpose and methodology. After obtaining informed consent, basic demographic information such as name, gender, age, religion, and blood group was recorded on the proforma. For participants who did not know their blood group, the ABO and Rh blood grouping process was conducted using Karl Landsteiner's conventional method [10].

3. Hand Preparation: Participants were asked to wash their hands thoroughly with soap and water to remove any dirt, oil, or residue that could interfere with the quality of the fingerprints. After washing, their hands were dried using a clean towel to ensure no moisture remained on the fingertips

4. Fingerprint Imprinting: The INK method, originally demonstrated by Cummins and Mildo in 1961 [9], was used to capture the fingerprints. This method involves the following steps:
   • Each fingertip of the right and left hand was pressed onto the ink pad to ensure even ink coverage.
   • The inked fingertip was then firmly pressed onto the white A4-size proforma, ensuring clear and complete imprints.
   • This process was repeated for all ten digits, with care taken to avoid smudging or overlapping of prints.

5. Evaluation of Fingerprint Patterns: The collected fingerprints were immediately evaluated using a powerful magnifying lens to identify and classify the patterns. Fingerprint patterns were categorized into three primary types:
   • Loops: Ridges that enter from one side of the finger, curve around, and exit from the same side.
   • Whorls: Circular or spiral patterns with at least one ridge making a complete circuit.
   • Arches: Ridges that enter from one side of the finger, rise in the center, and exit from the opposite side.

The classification of fingerprint patterns was based on Michael Kuchen's fingerprint classification system [11], which provides a standardized framework for analyzing and documenting dermatoglyphic patterns.

Blood Group Determination:

For participants with unknown blood groups, the ABO and Rh blood grouping process was conducted using Karl Landsteiner's conventional method [10]. This involved:

• A small blood sample from the participant.
• Testing the sample with anti-A, anti-B, and anti-D sera to determine the ABO and Rh blood group.
• Record the blood group on the proforma alongside the participant's demographic details and fingerprint patterns.

Documentation and Analysis: Each proforma contained the following information:

• The participant's name, gender, age, religion, and blood group.
• Fingerprint patterns of all ten digits, classified as loops, whorls, or arches.
• Observations and notes regarding the clarity and quality of the fingerprints.

The collected data were systematically documented and analyzed to identify important associations between fingerprint patterns, gender, and blood groups. The use of standardized methods and tools ensured the findings' reliability and reproducibility.

Statistical Analysis: The collected data was organized into a table using Microsoft Excel 2019. Subsequently, the data was transferred to GraphPad version 8.4.3 for further statistical analysis. Continuous data were expressed as mean with standard deviations, and discrete data were expressed as frequencies and percentages. Chi-square/Fisher exact tests were used to compare two or more proportions. The level of significance was set as p-value < 0.05.

Among the 200 study participants, 108 were male (54%), and 92 were female (46%). Blood group B +ve was the most prevalent, represented by 72 participants (36%), including 37 males (34.26%) and 35 females (38.04%). Blood group O +ve was also common, with 56 participants (28%), comprising 30 males (27.78%) and 26 females (28.26%). Blood group A +ve included 45 participants (22.5%), with 25 males (23.15%) and 20 females (21.74%). The AB +ve blood group was observed in 16 participants (8%), of whom 10 were males (9.26%) and 6 were females (6.52%). Blood group B -ve was noted in 5 participants (2.5%), with 2 males (1.85%) and 3 females (3.26%). The O -ve blood group had 4 participants (2%), including 3 males (2.78%) and 1 female (1.09%). The A -ve blood group was the least common, seen in only 2 participants (1%), with 1 male (0.92%) and 1 female (1.09%). Notably, no participants had the AB -ve blood group. Overall, blood group B +ve was the most common, accounting for 36% of the total participants, while A -ve was the rarest at just 1% (Table 1).

Table 1: Showing the distribution of study participants based on blood group and gender

The analysis of primary fingerprint patterns among males and females revealed that loops were the most prevalent pattern, observed in 55.65% of males and 55.98% of females, with an overall prevalence of 55.8%. Whorls were the second most common pattern, identified in 35.65% of males and 33.48% of females, accounting for a combined prevalence of 34.65%. Arches were less frequently observed, appearing in 5.65% of males and 6.41% of females, with a combined prevalence of 6%. Composites were the least common pattern, found in 3.05% of males and 4.13% of females, contributing to 3.55% of the total sample. Overall, the distribution of fingerprint patterns was remarkably similar between males and females, with loops being the most common, followed by whorls, arches, and composites. The difference in fingerprint patterns between the genders was not statistically significant, as evidenced by a chi-square value of 2.79 and a p-value of 0.42 (Table 2).

Table 2: Showing the distribution of primary fingerprint patterns in all fingers of both hands in both genders

The distribution of fingerprint patterns across all fingers was analyzed in relation to Rh blood groups, as shown in Table 3. Among individuals with Rh-positive blood groups, loops were the most prevalent pattern, accounting for 55.61% of the total observations, while in Rh-negative individuals, loops were even more common, representing 61.82% of the cases. Whorls were the second most frequent pattern, observed in 35.08% of Rh-positive individuals and 26.36% of Rh-negative individuals. Arches were less common, appearing in 5.98% of Rh-positive individuals and 10% of Rh-negative individuals. Composites were the least frequent pattern, identified in 3.33% of Rh-positive individuals and 1.82% of Rh-negative individuals. The chi-square test yielded a value of 6.44 with a p-value of 0.09, indicating that the differences in fingerprint pattern distribution between Rh-positive and Rh-negative blood groups were not statistically significant.

Table 3: Showing the distribution of fingerprint patterns in all fingers by Rh blood group

The distribution of primary fingerprint patterns across all fingers was analyzed in relation to ABO blood groups, as presented in Table 4. Among individuals with blood group A, loops were the most prevalent pattern, constituting 58.72% of the total observations. Similarly, loops were the dominant pattern in blood group B (52.34%), blood group O (56%), and blood group AB (61.25%). Whorls were the second most common pattern, observed in 33.83% of blood group A, 37.53% of blood group B, 33% of blood group O, and 30.63% of blood group AB individuals. Arches were less frequent, appearing in 4.68% of blood group A, 6.88% of blood group B, 6.33% of blood group O, and 5% of blood group AB individuals. Composites were the least common pattern, identified in 2.77% of blood group A, 3.25% of blood group B, 4.67% of blood group O, and 3.12% of blood group AB individuals. The chi-square test yielded a value of 12.29 with a p-value of 0.20, indicating that the differences in fingerprint pattern distribution across the ABO blood groups were not statistically significant.

Table 4: Showing the distribution of primary fingerprints patterns in all fingers by ABO blood group

The distribution of primary fingerprint patterns across all fingers was analyzed in relation to ABO and Rh blood groups (Table 5). Loops were the most common pattern across all groups, with the highest prevalence in Rh-negative blood group A (65%) and Rh-positive blood group AB (61.25%). Whorls were the second most frequent, while arches and composites were less common. However, in none of the ABO blood groups, the difference in the fingerprint pattern between the Rh +ve and Rh-ve individuals was found to be significant (p>0.05).

Table 5: Showing the distribution of primary fingerprint patterns in all fingers of both hands by ABO and Rh blood groups

Fingerprints, the distinctive patterns created by the small ridges on fingertips, are highly individualized and serve a crucial function in forensic identification, especially in criminal investigations and mass disaster victim identification [12]. The existing categorization system, derived from Sir Francis Galton's research and refined by Sir Edward Henry, is referred to as the Henry-Galton technique or Henry's classification system. This methodology is the most precise and extensively utilized approach for fingerprint categorization [13]. This study, involving 200 medical students at the Indira Gandhi Institute of Medical Sciences (IGIMS) in Patna, Bihar, sought to examine fingerprint patterns and investigate their possible correlation with gender and blood group. Establishing a correlation among fingerprint patterns, gender, and blood group could substantially improve biometric technology, providing wider applications in personal identity, medical diagnostics, and forensic medicine. This study revealed that the predominant gender among participants was male (54%), with blood group B being the most prevalent, followed by groups O, A, and AB, consistent across both sexes. The results correspond with research conducted by Patil et al. [14] in Navi Mumbai, Thakur et al. [15] in Bhopal, Mehta et al. [16] in Nagpur, and Bhavana et al. [17] in Hubli-Dharwad, Karnataka, all of which identified blood group B as the most common. Comparable patterns were noted in research conducted in Pakistan [18] and Iran [19]. Nevertheless, other research from Northern and Southern India, including works by Bharadwaja et al. [20], Rastogi and Pillai [21], Garg et al. [22], Joshi et al. [23], and Manikandan et al. [24], along with studies from Nepal [25, 26] and Libya [27], identified blood group O as the predominant type. These regional variances may indicate disparities in genetic and demographic characteristics among populations. The proportion of Rh-positive persons (94.5%) in our study was markedly greater than that of Rh-negative individuals (5.5%), aligning with results from studies conducted in India [14-17, 20-23], Pakistan [18], Iran [19], Nepal [25, 26], Libya [27], Nigeria [28], and Iraq [29]. This indicates a worldwide trend of increased Rh positive, probably attributable to the hereditary predominance of the Rh factor. Regarding fingerprint patterns, loops were the predominant kind (55.8%), followed by whorls (34.65%), arches (6%), and composites (3.55%). This finding aligns with earlier studies from India [14-17, 20-24], which similarly identified loops as the prevailing pattern. Loops were similarly common in males (55.65%) and females (55.98%), exhibiting no significant gender differences, a finding supported by Nithin et al. [30] and Kc et al. [26]. Rastogi and Pillai [21] observed a greater prevalence of whorls in males and loops in females, indicating possible regional or population-specific discrepancies. In terms of Rh blood groups, loops occurred more frequently in Rh-negative persons (61.82%) than in Rh-positive individuals (55.61%), but whorls were more prevalent in Rh-positive individuals (35.08%) compared to Rh-negative individuals (26.36%). Nonetheless, these discrepancies lacked statistical significance, a conclusion corroborated by Patil et al. [14], Thakur et al. [15], and Kc et al. [26]. This indicates that fingerprint patterns may not be significantly affected by Rh blood group status. Within the framework of ABO blood types, loops were most frequently observed in blood group AB (61.25%) and least frequently in blood group B (52.34%), whereas whorls were predominantly found in blood group B (37.53%) and little in blood group AB (30.63%). These results correspond with the research conducted by Patil et al. [14], Mehta et al. [16], Bhavana et al. [17], and Kc et al. [26]. Our investigation identified a statistically significant correlation between fingerprint patterns and ABO blood groups, corroborated by research conducted in India [14, 20-24] and Libya [27]. Nevertheless, research conducted in Nepal [25, 26] indicated no significant correlation, potentially because to variations in study populations or sample sizes. In the analysis of the combined ABO and Rh blood types, loops emerged as the predominant pattern in all groups, exhibiting the highest incidence in Rh-negative blood group A (65%) and Rh-positive blood group AB (61.25%). Whorls were predominantly observed in the Rh-positive blood type B (37.64%). No substantial changes in fingerprint patterns were detected between Rh-positive and Rh-negative individuals across any ABO blood type. Bhavana et al. [17] and Kc et al. [26] reported analogous findings; however, Fayrouz et al. [27] observed a greater prevalence of loops in Rh-positive blood types O and A, which contradicts our results.

Clinical Significance and Applications: The findings of this study hold significant implications for forensic science, anthropology, and medical genetics. The consistent prevalence of loops across genders and blood groups underscores their utility as a reliable biometric marker. The observed association between fingerprint patterns and ABO blood groups, though not universally significant, suggests potential genetic linkages that warrant further investigation. Such insights could enhance the accuracy of biometric identification systems, particularly in forensic investigations and disaster victim identification. Additionally, understanding the relationship between dermatoglyphics and blood groups could contribute to advancements in personalized medicine, where fingerprint patterns might serve as non-invasive markers for genetic predispositions or disease risks.

Limitations of the study: The limited sample size and disproportionate sex distribution were the primary limitations of this study. Further studies should be performed on a bigger sample with balanced gender representation from this region to more accurately ascertain the association between dermatoglyphic patterns and gender as well as ABO and Rh blood groups.

Loops are the most common fingerprint pattern among both males and females, followed by whorls, with composite patterns being the least common in the population of Eastern India. This study concludes that the distribution of primary fingerprint patterns is related to the ABO blood group but not to gender or the Rh blood group. The fingerprint pattern of an individual may be used to predict their ABO blood group and vice versa, which can aid in the accurate identification of both living and deceased individuals. As fingerprints will continue to be a key component of biometric-based identification solutions in the coming years, the relationship between fingerprint patterns and the ABO blood group offers additional data that can be used for personal identification purposes.

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