10.5061/DRYAD.SBCC2FR6N
Bashir, Saliha
0000-0003-0940-8793
University of the Punjab
Shafique, Muhammad
University of the Punjab
Shahzad, Muhammad
University of the Punjab
Anjum, Muhammad Sohail
University of the Punjab
Shahid, Ahmad Ali
University of the Punjab
Exploring phenotypic diversity of pigmented traits and iris features in
Pakistani population
Dryad
dataset
2021
FOS: Biological sciences
Natural Sciences and Engineering Research Council
https://ror.org/01h531d29
CGSD Award,Discovery Grant
Ontario Ministry of Training, Colleges and Universities
Ontario Graduate Scholarship
2021-07-08T00:00:00Z
2021-07-08T00:00:00Z
en
http://iris.davidcha.ca/
https://doi.org/10.1098/rsos.150424
https://www.ibm.com/analytics/spss-statistics-software
https://doi.org/10.5281/zenodo.4972208
3176392 bytes
7
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
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.
N/A