Phenotypic variations of eye color, skin color, and iris surface features have been well-explored in certain populations. However, there has been comparatively little research on variations in these features in Pakistani population. The aim of this study is to discover phenotypic diversity and correlations of pigmented traits and iris surface features in Punjab and Khyber-Pakhtunkhwa (KPK) province of Pakistan. Digital images of eyes and skin were examined by investigators to determine color using Fitzpatrick Phototype Scale. Similarly, iris patterns were characterized by Edward iris feature software and association studies were conducted through SPSS program. Intermediate eye color was frequent in KPK (44%) while brown was higher in Punjab (47%). Contrarily, light to medium brown skin color was recurring (55%) in Punjab whereas lighter skin color prevailed in KPK (69%). Furthermore, Fuchs’ crypts were significantly correlated with contraction furrows in both populations. Likewise, crypts were significantly associated with Wolfflin nodules and furrows were significantly related to conjunctival melanosis and pigment spots in KPK sample set. Based on unique iris patterns, these phenotypic traits would be helpful for individuals’ discrimination in the population. In future, there is need to explore genetic associations and functional differences of these traits.

Materials and Methods

Sample Collection

After approval from Institutional Ethical Committee (letter no. D-1644-UZ), the study was conducted on 514 unrelated and healthy volunteers i.e., 334 males and 180 females from different regions of Punjab and KPK (Khyber Pakhtunkhwa) province of Pakistan. Among them 298 samples were from KPK and 216 from Punjabi population. All participants ranged in age between 10-85 years and they were asked to fill consent form and questionnaire detailing about gender, age, ethnic group and place of birth of ancestors.

Phenotyping

Digital captures of eyes and skin from the inner side of upper arm of each individual were recorded at a distance of 10 cm using 24.2-megapixel camera, Canon EOS 80D equipped with 18 -135mm lens. All images were taken thricely at a shutter speed of 1/100, ISO 200, ensuring equal distance and constant light conditions.

Sample Binning

Eye color was determined qualitatively according to Fitzpatrick Phototype Scale (Figure 1) [30]. For simplification purpose, images were grouped into three categories; 1: “blue” (equivalent to 1 and 2 in Fitzpatrick classification); 2: “intermediate” (equivalent to 3 in Fitzpatrick classification) where intermediate is combination of green, blue/green, brown/green pigments and 3: “brown” (equivalent to 4 and 5 in Fitzpatrick classification). Similarly, based on Fitzpatrick categorization system, three categories were used to classify skin color (Figure 2); 1: “white and beige skin color”; 2: “light brown to medium brown” and 3: “dark brown to black skin”  [31-33]. Eye and skin digital images were independently inspected by two different investigators under uniform environmental conditions. In order to avoid discrepancies, a further detailed analysis of all photographs was performed until consensus assignment of phenotype took place.

Characterization of Iris Patterns

Iris surface patterns were accurately characterized using a web-based application (http://iris.davidcha.ca/) designed by David Cha [30]. Account was set up on request. Following instructions and guidelines of the program, right eye of each individual was analyzed for presence of Fuchs’ crypts, pigment spots, melanosis, Wolfflin nodules and contraction furrows. After analysis of 514 irises, the program created an EXCEL spreadsheet providing complete information about the categories of all five surface features, the prevalence of these features in different quadrants and diameter of iris. Furthermore, accurate position and size of each of the pigment spots and crypts were also determined. Iris feature categorization system developed in a prior study was used to determine categories of iris textures in Pakistani population [30].

Statistical Analysis

Statistical analysis was conducted through IBM STATISTICS SPSS v. 22.0. Gamma statistic was used to determine correlations among iris features, eye and skin color. Both p-value and G-value were reported for each of the correlation. Eye features were considered to be correlated with each other or with eye and skin color if p <0.05. Moreover, ordinal regression was executed to explore associations between iris patterns and gender, eye color, skin color, iris diameter and age. Goodness of fit and proportional odds were also tested. Furthermore, chi-square test was carried out to highlight significant variations in iris features, eye color, skin color with respect to gender and age between provinces. Differences in iris diameter between two sample sets were evaluated with the help of one-way ANOVA. Before starting the statistical analysis, normality was checked by Q-Q plots.

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