RELATIONSHIP BETWEEN DERMATOGLYPHICS AND SICKLE CELL ANAEMIA - - PowerPoint PPT Presentation

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
• ne’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.

4

To generate detailed baseline data to elucidate the possible diagnostic value and worth of dermatoglyphics for earlier detection

• f sickle cell anaemia.

5

AIM

SPECIFIC OBJECTIVES

To 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

7

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 10

MATERIALS AND METHODS

Total 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).

a a b b c

Figure 3: An illustration showing finger ridge counts; A- arch, B- loop and C-whorl (Source: Kahn et al., 2001).

11

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

12

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

13

A B C D A B C 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).

14

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 METHODS

PIC patterns

Figure 8: Photographs showing PIC patterns (X 0.2).

16

MATERIALS AND METHODS

PIC patterns

PIC 200 PIC 310 PIC 300 PIC 301 PIC 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)

17

400 1388 212 468 1297 235 200 400 600 800 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

18

14 53 333 1372 16 204 8 30 52 386 1284 13 213 22 200 400 600 800 1000 1200 1400 1600 CPW DLW PCW UL RL PA TA

FREQUENCY 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).

19

0.25 35 0.5 61.25 0.75 1.25 2.5 0.75 54.75 39.5 0.25 0.25 0.75 0.25 0.5 10 20 30 40 50 60 70 200 201 211 300 301 310 311 321 400 410 430 500 520

PERCENTAGE 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).

20

RESULTS AND DISCUSSIONS

New PIC’s patterns recorded

PIC 400 PIC 410 PIC 520 PIC 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.

21

• 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 DISCUSSION

Table 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

22

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 DISCUSSION

Table 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).

23

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 DISCUSSION

Table 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.

24

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 DISCUSSION

Table 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.

25

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

26

• 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

27

• 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

28

• 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.

REFERENCES

29

• Johnson, C. F. and Opitz E. (1971). Clinical review: the single palmar crease and its clinical significance

in a child development clinic observations and correlations. Clinical of pediatrics, 10: 392-403.

• Kahn, H. S., Ravindranath, R., Valdez, R. and Narayan, K. V

. (2001). Fingerprint ridge-Count difference between adjacent fingertips (dR45) predicts upper-Body tissue distribution: evidence for early gestational programming. Journal of Epidemiology, 153: 338-344.

• Kucken, M. and Newell, A. C. (2005). Fingerprint formation. Journal of Theoretical Biology, 235(1): 71-83.
• Li, H., Hou, J. and Yang, N. (2002). The molecular analysis of the Liujia. Guangxi University of National

Philosophy and Social Science), 24: 38-43.

• Margi, V

. D., Tripathi, S. R., Sharma, S., Nirali, J. K., Patel, A. and Roz, H. (2016). Co - Relational Scrutiny between Dermatoglyphics and Blood Group Patterns Revisited. International Journal of Trend in Research and Development, 3(1): 2394–9333.

REFERENCES

30

• Mensvoort, V

. M. (2009). Handprints: The hands of Albert Einstein! What the hands of Albert Einstein reveal about his independent personality his, his autism and his presumed left handedness? (Available Online). http:// www.handresearch.com. [Accessed 25th March, 2015 at 22:10 GMT].

• Oladipo, G. S., Olabiyi, O., Oremosu, A. A., Noronha, C. C., Okanlawon, A. O. and Paul, C. U.

(2007). Sickle cell anemia in Nigeria: dermatoglyphic analysis of 90 cases. African Journal of Biochemistry Research, 1(4): 54-59.

• Pagrut, K. and Chide, P

. (2017). Screening for the sickle cell gene in Yavatmal District, Maharashtra, India: An approach to a major public health problem. International Journal of Biomedical and Advance Research, 8(2): 50-53.

• Piel, F. B., Hay, S. I., Gupta, S., Weatherall, D. J. and Williams, T

. N. (2013). Global burden of sickle cell anemia in children under five, 2010-2050: modeling based on demographics, excess mortality and

• interventions. Plos Medicine, 10(7): 78-89.
• Ramesh, M., Geetha, K. K., Sudhakar, G. and Lakshmi, K. V

. (2011). A dermatoglyphic study on sickle cell anemia patients of north coastal Andhra Pradesh, south India. International Journal of Current Research, 3(8): 62-67.

REFERENCES

31

• Shetty, R. M. and Sarda, R. (2017). Dermatoglyphic Patterns in Sickle Cell Anaemia Patients of
• Chhattisgarh. Indian Journal of Dental Science, 2(4):2-6.
• Stevenson, R. E., Hane, B., Arena, J. F., May, M., Lawrence, L., Lubs, H. A. and Schwartz, C. E.

(1997). Arch finger prints, hypotonia and areflexia associated with x-linked mental retardation. Journal of Medical Genetics, 34 (6): 465-469.

• Sun, K. (2013). New insight into sickle cell disease. Current opinion in haematology, 20:215.
• Wadood, A. M. and Boskey, E. (2012). Sickle cell anemia. Healthline review, 44:1.
• Wethers, D.L. (2000). Sickle cell disease in childhood: Laboratory diagnosis, Pathophysiology and health
• maintenance. American Family Physcian, 62 (5): 1013-1027.
• WHO (2006). Sickle cell disease in the African region: Current situation and the way forward. Regional office

for Africa, 56: 1-2.

REFERENCES

32

THANK YOU