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DNA Analysis and Facial Reconstruction of Human Skull

Paper Type: Free Essay Subject: Archaeology
Wordcount: 3537 words Published: 8th Feb 2020

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The mystery of box 9


Box 9 encompassed a complete skull, articulated pelvis and right femur, all from a single, unknown individual. Sex, age, ethnicity, height and pathology was determined using both metric and morphological forensic anthropological methods. Metric analysis is advantageous because it’s easier to learn and reproduce, relies on standard landmarks, and results in fewer indeterminate conclusions (Giles, 1970). However, disadvantages include the need for unfragmented bones and population-specific formulae. Therefore, if remains are burned or fragmented, a qualitative method is needed, however, these can be subjective and lack of consistency (Giles, 1970). Alongside this, facial reconstruction and DNA profiling provided further evidence to help identify this individual.

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Pathological conditions

Pathology is important to consider before determining sex, age and ethnicity to prevent bias. This individual has many common characteristics of acromegaly- a rare disorder caused by over-production of growth hormone from the pituitary gland, these include an enlarged skull, protruding mandible, mispositioned teeth and excessive bone outgrowth around sutures (Chapman, 2017). Although these features could also indicate gigantism, this individual’s pelvis and femur are within normal ranges, suggesting the condition was acquired in adulthood which only occurs in acromegaly patients (NIDDK, 2012). Acromegaly progression is often linked to type 2 diabetes, hypertension, osteoarthritis and severe muscle weakness, which, if left untreated, could lead to premature death- it may have also caused this individual to have a stooped posture and frequent cardiovascular complications (Chapman, 2017). As the pelvis and femur have no signs of disease or damage, it’s unlikely this individual had osteoarthritis, however, absence of organs and muscles means other conditions cannot be ruled out as cause of death.


Ferembach’s (1980) qualitative method for skull sex determination indicated most features were hyper-male (see figure 1), however, a rough but medium thickness zygomatic process and a somewhat flexed posterior border of the mandibular ramus showed neither male or female characteristics. Despite this, overall, one can predict that this individual was male.







Figure 1 shows features of the cranium and mandible that indicated hyper-male traits using Ferembach’s (1980) method. 1: prominent glabella, 2: vertical mastoid process, 3: blunted supraorbital ridges, 4: inclined forehead, 5: quadrectangular orbitals and 6: robust, broad mandible.

Alternatively, Giles and Elliot’s (1963) discrimination function is a quicker method with similar accuracy of 86.6%. Using formula 1, outlined in Appendix D, a value of 2994.9 is obtained, also suggesting this individual was male, increasing reliability of conclusions. Krogman (1962) found that sexing the skull alone is 90% accurate, however, sexing the skull and pelvis together is 98% accurate. Thus, to increase accuracy of final conclusions, the pelvis and femur need to be analysed too.

The pelvis is the best indicator of sex due to its adaptation for childbirth in females. Phenice’s (1969) morphological technique uses 3 pubis characteristics to determine sex- one of which is the ventral arc, said to be 96% accurate in determining sex (Sutherland and Suchey, 1991). Unfortunately, this technique produced mixed results for this pelvis, therefore, alternatively, Albanese’s (2003) metric analysis, outlined in Appendix B, uses the whole pelvis and femur to increase accuracy and reduce subjectivity of sex determination. Using model 1, which has 98% accuracy, a value of 0.26 is obtained, suggesting this individual was female. Yet, model 2 and 3, which have 97% and 96.3% accuracy respectively, obtain 0.62 and 0.94, clearly indicating male. Although model 2 and 3 have lower accuracy, their matching outcome increases confidence and validity, allowing one to conclude this individual was male.

Bass (1978) discovered that a femur head diameter >47.5mm indicates male while <42.5mm indicates female. Unfortunately, as this individual’s is only 44.85mm, sex cannot be determined. Nevertheless, height can be estimated using Trotter’s formula (1970) in figure 2. As femur length is 47.9cm, height is estimated at 175.4 cm ±3.27.

However, cranial suture closure is considered unreliable and inaccurate because it frequently under‐ages older adults and over‐ages sub-adults (Molleson and Cox 1993). Moreover, this individual’s acromegaly caused excessive outgrowth of bone around the sutures, potentially affecting their closure and, thus, impacting age determination. As a result, a more reliable method of ageing the skull involves looking at dentition.

Teeth are the least destructible part of the body, making them excellent for age estimation. No deciduous dentition and evidence of tooth 8 alveolar processes indicate this individual was at least 18 years old (Carr, 1962). Dental wear analysis provides more accurate age determination than those previously mentioned because it examines enamel which cannot be remodelled. A widely used method involves analysing of mandibular molar wear (Miles 1963), however, as shown in figure 5 and 6, excessive ante- and postmortem tooth loss means only two mandibular molars are present, preventing any valid age estimation.


Figure 5, photographs showing mandibular (A) and maxillary (B) dentition. 1) identifies the sites of postmortem tooth loss, 2) shows antemortem tooth loss, 3) indicates alveolar processes of molar 3 and 4) indicates areas of decay.

Figure 6, using the University of Sheffield dental chart, shows which teeth are present, which have been extracted and any fractures seen. It appears teeth 13, 15, 16, 24, 27, 31, 36, 42, and 46 were removed at a while before death as they have had time to heal over.

These forensic age estimation techniques conclude that this individual could be anywhere between 25 and 48.1 years old. However, after combining all results and analysing their accuracy and validity, it is likely that this individual is between 32 and 43 years old.

Facial reconstruction

During facial reconstruction, 16 osteometric points were measured and attached to the skull, then, facial muscles, features, fat and skin were created from wax to produce a potential antemortem model of this individual- see figure 7. After completion, it was clear that this individual was a male with a very prominent jaw and forehead which links to previous conclusions.




Figure 7 shows the stages of facial reconstruction. A) shows the skull with osteometric points in place, B) shows the addition of some facial muscles, eyeball and nose, and C) shows the final, completed facial reconstruction.

Despite this, as this is an artistic interpretation completed by a group of untrained individuals without any soft tissue or portrait to work alongside, this method is very subjective and therefore not very reliable at recreating an individual’s morphological traits for identification. Therefore, this could be improved using computerised 3D facial reconstruction.

DNA profiling

Amplified Fragment Length Polymorphism (AFLP), a highly reproducible DNA profiling technique, was carried out to identify the common D1S80 variable nucleotide tandem repeat within this individual’s DNA sample and compared to those of 7 missing people. However, absence of any bands in this individual’s DNA sample, shown in figure 10, prevents matching to known genotypes. This could be due to poor primer specificity or synthesis or inadequate, faulty DNA in the sample (McPherson, Quirke & Taylor, 1992).

Figure 10 shows the results from 2% agarose gel electrophoresis of the PCR products. Lane 1 and 12 – 100bp ladder; 2- water control; 3- DNA sample A; 4- DNA sample B; 5- DNA sample C; 6- this individuals DNA sample; 7- DNA sample D; 8- DNA sample E; 9- DNA sample F;   10- DNA sample G; 11- water.

Therefore, to find a match, AFLP should be repeated ensuring there is adequate, unfragmented DNA along with an appropriate, high specificity primer. Primer dimers at the bottom of lane 9 suggests the primer concentration was too high, therefore, to avoid allelic dropout which may assume homozygosity, lower concentrations should be used when repeating.

AFLP requires high quality and quantity of DNA to prevent allelic dropout, however, it’s likely that this cannot be achieved from this DNA sample. Therefore, DNA-17 may provide better results because it requires less DNA due to improved sensitivity and discrimination between profiles (Crown Prosecution Service, 2019).


After analysing all results, one can estimate this was a European male aged between 32 and 43 who was 174cm tall, living with acromegaly. The likely cause of death is co-morbidity associated with acromegaly progression. Unfortunately, these conclusions cannot be confirmed through DNA fingerprinting which reduces validation and reliability, therefore, further analysis to confirm this individual’s identity could include more reliable methods involving molecular biology and bone chemistry.


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Appendix A


Measurement (mm)

Cranial length


Cranial breadth


Basion-bregma height


Bizygomatic breadth


Basion prosthion length


Nasion-prosthion line


Maxillo-alveolar breadth


Height of the processus mastoideus


These measurements were then inputted into the formula below to determine sex from the skull.

Discriminant function formula (Giles & Elliot, 1963):

(Cranial length*3.107) + (Cranial breadth*-4.643) + (Basion-bregma height*5.786) + (bizygomatic breadth*14.821) + (Basion prosthion length*1.000) + (Nasion-prosthion line*2.714) + (Maxillo-alveolar breadth*-5.179) + (Height of the processus mastoideus*6.071)

If result is larger than 2676.39, the individual is male, if smaller than 2676.39, the individual is female.

Appendix B


Measurement (mm)

Hipbone height (A)


Iliac breadth (B)


Pubis length (C)


Ischium length (D)


Femur head diameter (E)


Epicondylar breadth of femur (F)


There measurements where then inputted into the formula below Albanese’s (2003) to determine sex from the pelvis and femur.

Probability M/F=1(1+eZ)

Model 1, Z = -61.5345 + (0.595*A) – (0.5192*B) – (1.1104*D) + (1.1696*E) + (0.5893*F)

Model 2, Z = -40.5313 + (0.2572*A) – (0.9852*C) + (0.7303*E) + (0.3177*F)

Model 3, Z = -30.359 + (0.4323*A) – (0.2217*B) – (0.7404*C) + (0.3412*D)

If P is greater than 0.5, the individual is male, if P is less than 0.5, the individual is female.

Appendix C

List of corresponding states and ages for each of the 7 acetabulum variables Rissech’s (2006)

  1. Acetabular groove
    • State 1 – predicted age: 41.6
  2. Acetabular rim shape
    • State 3 – predicted age: 45.9
  3. Acetabular rim porosity
    • State 2 – predicted age: 39
  4. Apex activity
    • State 1 – predicted age: 38.2
  5. Activity on the outer edge of the acetabular fossa
    • State 2 – predicted age: 32.3
  6. Activity of the acetabular fossa
    • State 3 – predicted age: 48.1
  7. Porosities of the acetabular fossa
    • State 2 – predicted age: 34.3


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