relationship between neonatal fingerprint patterns … j... · 2019. 8. 16. · (ahmad and...
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RELATIONSHIP BETWEEN DERMATOGLYPHICS AND
SICKLE CELL ANAEMIA
JAMES NKETSIAH
1
Dermatoglyphics (fingerprint and palmprint).(Lakshmana et al., 2017).
Development of dermatoglyphics. (Bhat et al., 2014; Margi et al., 2016).
Characteristics of dermatoglyphics: genetic, unique, permanent. (Eboh, 2013; Bhat et al., 2014).
Uses of dermatoglyphics: identification, diagnosis, authentication, mirror of one’s potential and talent.
(Kucken and Newell, 2005; Offei et al., 2014; Atinga, 2017).
INTRODUCTION
Genetic blood disorder that affects the haemoglobin within the RBC. (Wadood et al., 2012).
300,000 infants are born each year worldwide. (WHO, 2006).
Prevalent in West Africa (2-5)% and 2% in Ghana. (WHO, 2006; Asare et al., 2018).
18,000 babies born each year with SCA in Ghana. (Dennis-Antwi, 2018).
Effects of sickle cell anaemia: Chronic anaemia and damage to body organs.(Johnson, 2005; Sun, 2013).
SICKLE-CELL ANAEMIA (SCA)
2
PRESENT STUDY
Solubility test and haemoglobin electrophoresis may give a false negative result when performed too early in infants.
(Wethers, 2000).
Infants less than 6 months possess predominantly foetal haemoglobin. (Piel, 2017).
Inaccuracy of diagnostic methods in babies less than 6 months.
(Pagrut and Chide, 2017).
Dermatoglyphics can be use to diagnose some genetic and non-genetic diseases.
(Andani et al., 2007). 3
PRESENT STUDY
Limited data correlating dermatoglyphics and SCA.
Limited dermatoglyphics parameters studied.
Ethnic and racial variations in dermatoglyphics.
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To generate detailed baseline data to elucidate the possible diagnostic value and worth of dermatoglyphics for earlier detection of sickle cell anaemia.
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AIM
SPECIFIC OBJECTIVESTo determine:
the distribution of fingerprint patterns between sickle cell anaemic (SCA) group and normal individuals.
finger ridge counts (TFRC and AFRC) between SCA and normal individuals.
palmar inter-digital ridge counts (A-B, B-C and C-D) between SCA and normal individuals.
the distribution of PIC patterns between SCA and normal individuals.
palmar ATD and ADT angles between SCA and normal individuals.6
Study design and location
• Cross sectional study.
• Sickle Cell Units of Komfo Anokye Teaching Hospital (KATH), Kumasi.
• School of Medicine and Dentistry- KNUST, Kumasi.
Duration: February, 2018 – April, 2019.
Informed participants’ consent and Ethical approval were sought from
KSMD/KATH Committee of Human Research, Publications and and
Ethics.
MATERIALS AND METHODS
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MATERIALS AND METHODS Sample size: 400
• 200 pre-diagnosed with SCA (SS) : 100 (50%) males and 100 (50%) females.
• 200 without SCA (AA) : 100 (50%) males and 100 (50%) females.
Inclusion criteria
• All ten fingers and palm intact.
• Exclusively either SS or AA genotypes.
Exclusion criteria
• Physical fingers and palm deformities due to injury and burns.
• Absent fingers, extra, webbed or worn out fingers.
Data Analysis
• SPSS version 23.0 (Inc., Chicago, IL, USA).8
MATERIALS AND METHODS
9
Data collection
Figure 1: Photographs illustrating method of taking (A) palmar and fingerprints and (B) thumb print using
CanoScan lide 120 scanner (X 0.2).
A B
MATERIALS AND METHODS
Figure 2: A schematic presentation showing the eight subdivisions of fingerprint patterns
(Stevenson et al., 2001).
Distribution of fingerprint patterns
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MATERIALS AND METHODSTotal Finger Ridge Count (TFRC) and Absolute Finger Ridge Count (AFRC)
TFRC : Addition of the finger ridge counts taking the highest count of a whorl
for all the ten fingers (Ahmad and Pimpalkar, 2017).
AFRC: Addition of the finger ridge counts of all the ten fingers taking into
consideration the presence of both count of a whorl (Ramesh et al., 2011).
aa
b b
c
Figure 3: An illustration showing finger ridge counts; A- arch, B- loop and C-whorl (Source: Kahn et al., 2001).
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PALMAR ATD, DAT AND ADT ANGLES
Figure 4: A photograph of the palm illustrating atd, dat and adt angles (X 0.2).
a
t
a
d
t
MATERIALS AND METHODS
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d
A-B, B-C AND C-D PALMAR INTER-DIGITAL RIDGE COUNTS
Figure 5: A photograph (A) and illustration (B) showing palmar inter-digital a-b, b-c and c-d ridge counts
(Source: Lakshmana et al., 2017).
MATERIALS AND METHODS
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A BC
DABC
D
A B
MATERIALS AND METHODS PIC model
• PIC 101
• PIC 200, 201
• PIC 210, 211
• PIC 300, 311, 310(Mensvoort, 2009; Atinga, 2017)
Distal transverse crease
Proximal transverse crease
Radial longitudinal crease
Figure 6: A photograph showing the Primary Palmar Creases (X 0.2).
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Figure 7: Cartoons showing PIC 101, PIC 200, PIC 201, PIC 211, PIC 300, PIC 311 and PIC 310 (Source: Mensvoort,
2009). 15
MATERIALS AND METHODSPIC patterns
Figure 8: Photographs showing PIC patterns (X 0.2).
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MATERIALS AND METHODSPIC patterns
PIC
200
PIC
310PIC
300
PIC
301PIC
310
PIC
300
PIC
201
Figure 9: A bar chat showing the distribution of the primary fingerprint patterns between the SCA and control groups.
RESULTS AND DISCUSSION
Consistent with: (Oladipo et al., 2007; Ramesh et al., 2011; Shetty and Sarda, 2017)
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400
1388
212
468
1297
235
0
200
400
600
800
1000
1200
1400
1600
WHORL LOOP ARCH
PRIMARY FINGERPRINT PATTERNS BETWEEN SCA AND CONTROL GROUPS
SCA CG
Figure 10: A bar chart showing the distribution of the subdivisions of fingerprints between the SCA and control groups.
SCA-Sickle Cell Anaemia; CG-Control Group; CPW- Central pocket whorl; DLW –Double loop whorl; PCW –Plain concentric whorl; RL- Radial loop; UL- Ulnar loop; PA- Plain arch; TA- Tented arch.
RESULTS AND DISCUSSION
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1453
333
1372
16
204
830 52
386
1284
13
213
220
200
400
600
800
1000
1200
1400
1600
CPW DLW PCW UL RL PA TA
FR
EQ
UE
NC
Y
SUB-DIVISION OF THE FINGERPRINT PATTERN BETWEEN THE SCA AND CONTROL GROUPS
SCA CG
RESULTS AND DISCUSSION
Figure 11: A bar chart showing the distribution of the PIC pattern between the SCA and Control groups.
SCA-Sickle Cell Anaemia; CG-Control Group; PIC- Primary crease, Intersections of primary crease and Complete transverse
crease.
PIC 310 and 300 dominate in the Ghanaian population (Offei et al., 2014; Atinga, 2017).
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0 0.25
35
0.5
61.25
0 0 0.75 1.25 0 0 02.5
0.75 0
54.75
0
39.5
0.25 0.25 0 0.75 0.25 0.50
10
20
30
40
50
60
70
200 201 211 300 301 310 311 321 400 410 430 500 520
PE
RC
EN
TA
GE
PIC PATTERN
DISTRIBUTION OF PIC PATTERN BETWEEN THE SCA AND CONTROL GROUPS
SCA CG
Figure 12: Photographs showing new PIC’s recorded in the study (X 0.2).
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RESULTS AND DISCUSSIONSNew PIC’s patterns recorded
PIC
400
PIC
410
PIC
520PIC
430
RESULTS AND DISCUSSION
Table 1: Comparison of palmar ‘atd’ angle between the SCA and control groups.
SD= standard deviation; t = test statistic and p-value- statistically significant at 0.05.
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Consistent with Oladipo et al. (2007); Shetty and Sarda (2017).
SICKLE CELL
ANAEMIA
CONTROL
GROUP
95% CI
Mean SD Mean SD lower Upper t p
43.62 5.92 41.61 5.26 0.442 3.65 2.542 0.015
RESULTS AND DISCUSSIONTable 2: Comparison of ‘adt’ angle between the SCA and control groups.
SD= standard deviation (SD); t = test statistic and p-value- statistically significant at 0.05.
Paucity of literature
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SICKLE CELL
ANAEMIA
CONTROL
GROUP
95% CI
Mean SD Mean SD lower Upper t p
60.35 5.52 62.11 5.62 -3.415 0.381 2.212 0.045
RESULTS AND DISCUSSIONTable 3: Comparison of total finger ridge count (TFRC) between SCA and control groups.
SD= standard deviation; t = test-statistic and p-value- statistically significant at 0.05.
Consistent with Ramesh et al. (2011).
SCA is inherited as monogenic trait (chromosome 11) (Koch et al., 2000)
FRC is inherited as a polygenic trait (chromosome 5 and 1: 5q14.1)(Medland et al., 2007).
Problematic ridge count method (Acree, 1999).
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TFRC
SIDE SCA CG 95% CI
Mean SD Mean SD Lower Upper t p
Right hand 38.12 52.34 42.31 51.74 -14.417 6.047 -0.804 0.422
Left hand 29.05 47.26 36.18 50.98 -16.793 2.533 -1.451 0.148
Both
hands
67.17 94.52 78.49 97.64 -15.605 4.290 -1.177 0.240
RESULTS AND DISCUSSIONTable 4: Comparison of absolute finger ridge count (AFRC) between the SCA and control groups.
SD= standard deviation; t = test statistic and p-value- statistically significant at 0.05.
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AFRC
SIDE SCA CG 95% CI
Mean SD Mean SD Lower Upper t p
Right hand 74.47 23.43 70.57 28.94 -1.276 9.076 1.481 0.139
Left hand 74.78 29.97 68.04 30.37 0.084 12.667 2.232 0.026
Both hands 149.25 50.71 138.61 57.26 -0.680 10.872 1.967 0.058
Inconsistent with Ramesh et al. (2011).
SCA is inherited as monogenic trait (chromosome 11) (Koch et al., 2000).
FRC is inherited as a polygenic trait (chromosome 5 and 1: 5q14.1)(Medland et al., 2007).
Significant association might : both genes might co-occur on the same chromosome.
RESULTS AND DISCUSSIONTable 5: Comparison of ‘A-B’, ‘B-C’ and ‘C-D’ palmar interdigital ridge counts between SCA and Control groups.
SD= standard deviation; t= test statistic and p-value- statistically significant at 0.05.
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PALMAR INTER-DIGITAL RIDGE COUNTS
SIDE SCA CG 95% CI
Mean SD Mean SD Lower Upper t p
A-B 36.28 5.67 38.97 5.65 -3.805 -1.576 -4.771 0.000
B-C 32.06 5.48 33.02 5.25 -2.630 1.000 -1.37 0.203
C-D 36.61 6.30 37.36 5.91 -4.956 -2.545 -6.127 0.000
TOTAL 104.95 17.45 109.35 16.81 -3.797 -2.561 -5.384 0.000
A-B and C-D inconsistent with Ramesh et al. (2011).
B-C consistent with Ramesh et al. (2011).
PIRC is inherited as a polygenic trait (Li et al., 2003)..
Significant association: genes for SCA and PIRC might co-occur
Ulnar loop dominated in both sickle cell anaemic and control groups with the sickle cell anaemic group recording the highest, this was not statistically significant.
For the absolute finger ridge count, there was a significant difference between the left hand of the sickle cell anaemic and control groups with the sickle cell anaemic group recording the highest.
Significant difference recorded between sickle cell anaemic and control groups for A-B and C-D palmar inter-digital ridge counts with the control group recording the highest in both.
CONCLUSION
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PIC 310 dominated in the sickle cell anaemic group whilst PIC 300 dominated in the control group, this was statistically significant.
• Recorded 5 unreported PIC’s ( PIC 400, PIC 410, PIC 430, PIC 500 and PIC 520) in Ghana.
Significant difference recorded between sickle cell anaemic group and control group for ATD and DAT angles.
• ATD angle recorded highest in the sickle cell anaemic group.
• DAT angle recorded highest in the control group.
This study has established that there is some significant relationship between
dermatoglyphics and sickle cell anaemia.
CONCLUSION
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Further analysis focusing on the minutiae or details of fingerprint (e.g. ridge dot, ridge ending, bifurcation, trifurcation, bridge, spur, enclosure, ridge crossing etc.)should be considered.
Finger ridge density between the sickle cell anaemic and control groups be studied rather than finger ridge count.
Method for finger ridge count should be reviewed because it is considered not being a true reflection of the total number of ridges present in a particular print.
RECOMMENDATIONS FOR FUTURE WORK
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Ahmad, M. and Pimpalkar, D. S. (2017). Study of Palmar Dermatoglyphics in Hypertension. International Journal of Science and Research, 6(3): 719-724.
Andani, R. H., Dharati, K., Ojaswini, M., Nagar, S. K., Kanan, U. and Bhaskar, P. (2012). Palmar dermatoglyphics in patients of thalassemia major. National Journal of Medical Research, 2(3): 287-290.
Bhat, G. M., Mukhdoomi, M. A., Shah, B. A. and Ittoo, M. S. (2014). Dermatoglyphics: in health and disease-a review. International Journal of Research in Medical Sciences, 2(1): 31-37.
Darekh, D. and Vig, R (2011). Review of Fingerprint classification methods based on Algorithmic flow. Journal of Biometrics, 2: 2.
Eboh, D. E. (2013). Fingerprint Patterns in relation to gender and blood group among students of Delta State University, Abraka, Nigeria. Journal of Experimental and Clinical Anatomy, 12(2): 83.
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