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Dental cementum virtual histology of Neanderthal teeth from Krapina (Croatia, 130–120 kyr): an informed estimate of age, sex and adult stressors

Paola Cerrito

Paola Cerrito

Department of Anthropology, New York University, New York, NY, USA

New York Consortium in Evolutionary Primatology, New York, NY, USA

Department of Molecular Pathobiology, New York University College of Dentistry, New York, NY, USA

[email protected]

Contribution: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

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Alessia Nava

Alessia Nava

Skeletal Biology Research Centre, School of Anthropology and Conservation, University of Kent, Canterbury, UK

Contribution: Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Writing – review & editing

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Davorka Radovčić

Davorka Radovčić

Department of Geology and Paleontology, Croatian Natural History Museum, Zagreb, Croatia

Contribution: Data curation, Investigation, Resources, Writing – review & editing

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Dušan Borić

Dušan Borić

Dipartimento di Biologia Ambientale, Sapienza Università di Roma, Rome, Italy

Contribution: Resources, Writing – review & editing

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Leonardo Cerrito

Leonardo Cerrito

Istituto Nazionale di Fisica Nucelare, Rome, Italy

Contribution: Data curation, Formal analysis, Methodology, Software

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Tricia Basdeo

Tricia Basdeo

Department of Anthropology, Adelphi University, New York, NY, USA

Contribution: Data curation, Formal analysis

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Guido Ruggiero

Guido Ruggiero

Ruggiero-Piscopo Dental Practice, Naples, Italy

Molise Regional Health Authority, Venafro, Italy

Contribution: Resources, Writing – review & editing

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David W. Frayer

David W. Frayer

Department of Anthropology, University of Kansas, Lawrence, KS, USA

Contribution: Supervision, Writing – review & editing

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Alexander P. Kao

Alexander P. Kao

Elettra-Sincrotrone Trieste S.C.p.A., 34149 Basovizza, Trieste, Italy

Contribution: Data curation, Investigation, Methodology

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Luca Bondioli

Luca Bondioli

Department of Cultural Heritage, University of Padua, Padua, Italy

Contribution: Formal analysis, Investigation, Methodology, Project administration, Supervision, Writing – review & editing

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Lucia Mancini

Lucia Mancini

Elettra-Sincrotrone Trieste S.C.p.A., 34149 Basovizza, Trieste, Italy

Contribution: Data curation, Investigation, Methodology, Project administration, Supervision, Writing – review & editing

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Timothy G. Bromage

Timothy G. Bromage

Department of Anthropology, New York University, New York, NY, USA

New York Consortium in Evolutionary Primatology, New York, NY, USA

Department of Molecular Pathobiology, New York University College of Dentistry, New York, NY, USA

Contribution: Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Validation, Writing – review & editing

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Published:https://doi.org/10.1098/rsif.2021.0820

Abstract

The evolution of modern human reproductive scheduling is an aspect of our life history that remains vastly uncomprehended. The present work aims to address this gap by validating a non-destructive cutting-edge methodology to infer adult life-history events on modern teeth with known life history and then applying it to fossil specimens. We use phase-contrast synchrotron X-ray microtomography to visualize the dental cementum of 21 specimens: nine contemporary humans; 10 Neanderthals from Krapina (Croatia, 130–120 kyr); one Neolithic Homo sapiens from Ajmana (Serbia); and one Mesolithic H. sapiens from Vlasac (Serbia). We were able to correctly detect and time (root mean square error = 2.1 years; R2 = 0.98) all reproductive (menarche, parturition, menopause) and other physiologically impactful events in the modern sample. Nonetheless, we could not distinguish between the causes of the events detected. For the fossil specimens, we estimated age at death and age at occurrence of biologically significant events. Finally, we performed an exploratory analysis regarding possible sexual dimorphism in dental cementum microstructure, which allowed us to correctly infer the sex of the Neolithic specimen, for which the true value was known via DNA analysis.

1. Introduction

The factors that have shaped Homo sapiens' life history are largely still to be understood. Given our significant reliance on material culture and on (pro)social behaviour for the acquisition of energy, care of offspring and many other correlated aspects, it is likely that our life history, cultural and social evolution are intertwined [1]. Life-history variables (LHVs) are those variables that directly record the timing of the several major life-history events, such as gestation length, age at weaning, age at sexual maturity, age at first birth, interbirth intervals, age at menopause and longevity. Nonetheless, tracking the evolution of LHVs in the fossil record has proven to be a significant challenge as it is limited to what can be gleaned and inferred from teeth and bones [2,3]. The current knowledge regarding LHVs in the hominin fossil record is very scant, being limited to estimates of age at death [4], gestation length, onset of weaning [5] and physiological stress occurrence [6]. The present work aims to improve and enrich our understanding of some of the more elusive LHVs using a non-destructive cutting-edge methodology.

Human teeth permanently record physiologically impactful events during their formation, enabling the collection of data about stressors experienced during development in addition to the estimation of the age at death [7]. In Recording structures of mammals, Klevezal [8] thoroughly describes the different types of growth layers pertaining to the mineralized tissues of bone, dental enamel, dental cementum, horn and other mammalian mineralized tissues. All recording structures are periodically layered, and each layer is the visible result of changing micromorphology, which corresponds to changing physiological states of the organism [9]. These structures are extremely conserved across mammalian taxa, from cetaceans to cervids to primates. Recording structures can be categorized according to three parameters [8]: sensitivity, which relates to the frequency with which new layers are added and which can vary across the period of registration [10]; period of registration (when does the structure start and stop recording); and persistence of a record (for how long the recording structure is maintained unchanged) (table 1).

Table 1. The three fundamental parameters of the four different ‘recording structures' present in primates [8]. These parameters determine the suitability of each structure for the different questions in anthropological and primatological research.

structure sensitivity period of registration persistence of a record
bone multidien eighth week after conception to the end of life several years, but variable depending on bone and population
enamel circadian and multidien tooth initiation to tooth crown completion lifetime
dentine circadian and multidien tooth initiation to tooth completion lifetime
cementum annual tooth completion to death lifetime

Of the mineralized tissues present in primates, only cementum retains both the lifetime period of registration and lifetime persistence of the record, even if it is with a low sensitivity owing to its yearly periodicity and low growth rate [11]. Physiological events that are strong enough to produce a disruption of organismal mineral homeostasis or organic matrix synthesis leave marks in the corresponding position of the developing cementum, which are visible as changes in tissue refractive index [1215]. Previous studies already ascertained the possibility of using phase-contrast synchrotron X-ray microtomography (PC-SRµCT) for a non-destructive three-dimensional (3D) visualization of yearly incremental cementum bands in both modern human and fossil animal teeth [1619], which provide the basis for age-at-death estimation. Furthermore, recent work in classic histology [12,20] has provided evidence, in two distantly related species of primates (H. sapiens and Macaca mulatta), of changes in tissue microstructure in relation to pregnancies, cessation of fertility and illnesses. Fertility data derived from human teeth are scarce, constituting an almost unexplored area of research, particularly when dealing with hominin fossil teeth. The combination of age-at-death estimation provided by the yearly periodicity and the markers associated with physiological stressors can be used to determine their chronology, thus attempting a first informed estimate in fossil remains regarding the timing of possible parturitions [21]. Thus far, studies attempting to investigate them [12,21,22] have relied on destructive methods which are substantially prevented in palaeoanthropological specimens for obvious preservation reasons. To date, non-destructive virtual histology studies based on the use of PC-SRµCT techniques are increasing in number [2326] but remain scarce in the exploration of dental cementum and non-existent in the investigation of fossil hominin cementum.

Here, we report for the first time the application of this approach to the cementum of Neanderthal teeth, specifically from Krapina (Croatia, 130–120 kyr [27]). Using synchrotron-based high-resolution 3D imaging, we acquired data on 10 Neanderthal specimens, in addition to one Mesolithic, one Neolithic (both from the Danube Gorges area of Serbia) and nine known life-history contemporary humans. In addition to estimating the age at death following previously published methods [16,18], we attempt a first informed estimate of sex and reproductive events and/or other types of stressors for the fossil specimens.

2. Methods

2.1. Sample

A total of 21 permanent teeth (each with an approximate size of 1.5 cm × 0.8 cm × 0.8 cm) were selected for this study (table 2). All contemporary H. sapiens specimens were accompanied by age, sex, medical and life-history information. They were acquired by G.R. and were donated by patients who had them extracted for medical purposes. All patients signed an informed consent form. Specimens were fully anonymized by G.R. and there is no possibility of tracing back any identifying information about the participants. The research was carried out under the auspices of the College of Medicine Research and Ethics Committee (COMREC) (protocol no. P.05/06/373) of the New York University (NYU) College of Dentistry. All methods were carried out in accordance with relevant guidelines and regulations and all experimental protocols were approved by the NYU College of Dentistry. The Late Mesolithic (burial H326/7, ca 50 years old, Vlasac, Serbia [31]) and Early Neolithic (burial 6/A2309, Ajmana, Serbia [30,32]) specimens were known to be females through previously performed DNA analysis [28]. The Neanderthal specimens from Krapina had previously been studied by Wolpoff [29], who estimated their ages at death based on dental wear. Contemporary samples were chosen so that the following categories were represented: younger and older males, nulliparous and multiparous females, reproductive and post-reproductive females. Neanderthal teeth were chosen based on the dental wear and the Krapina Dental Person (KDP) assignation made by Wolpoff [29]. We selected the most worn teeth, presumably belonging to older individuals, and we chose more than one tooth from the same KDP. Macroscopically, all specimens showed good cementum preservation.

Table 2. Specimens analysed in the present study. For each species/population, we report whether sex and/or LHVs were known.

specimen tooth age sex species reliable cementum imaging
ARF36 URP3 36 F H. sapiens (contemporary) No
ARF45 ULP4 45 F H. sapiens (contemporary) Yes
ARF69 URM2 69 F H. sapiens (contemporary) Yes
ARF77_LLI2 LLI2 77 F H. sapiens (contemporary) Yes
ARF77_LLI1 LLI1 77 F H. sapiens (contemporary) Yes
ARF78 URC 78 F H. sapiens (contemporary) Yes
ARF67_UI2 UI2 67 F H. sapiens (contemporary) Yes
ARM63 URM3 63 M H. sapiens (contemporary) Yes
ARM47 LRC 47 M H. sapiens (contemporary) Yes
H327 LLM3 50a Fb H. sapiens (Mesolithic) No
A2309 LRM1 / Fb H. sapiens (Neolithic) Yes
KR1 LRM2 16a N/A Homo neanderthalensis No
KR7 LRM3 16a N/A H. neanderthalensis No
KR25 LRP3 16a N/A H. neanderthalensis No
KR27 LLP3 16a N/A H. neanderthalensis Yes
KR85 LLM3 16a N/A H. neanderthalensis Yes
KR176 ULM2 24a N/A H. neanderthalensis No
KR137 URM3 24a N/A H. neanderthalensis No
KR179 ULM3 19a N/A H. neanderthalensis Yes
KR162 URM3 25a N/A H. neanderthalensis Yes
KR172 URM2 25a N/A H. neanderthalensis Yes

aEstimates based on wear are from Wolpoff [29] for the Neanderthal specimens, Borić & Price [30] for the Neolithic individual and from Borić et al. [31] for the Mesolithic one. ARF and ARM = contemporary specimens with known life history.

bSex was estimated via DNA analysis [28].

2.2. Image acquisition and processing

The permanent tooth roots were measured via SRμCT at the SYRMEP beamline of the Elettra synchrotron facility (Basovizza, Trieste, Italy) in August 2020. The measurements were performed in propagation-based phase-contrast mode using a filtered white X-ray beam (filter = 1.5 mm Si + 1.0 mm Al) with a mean energy of 27 keV. After the alignment of the μCT set-up, a series of scout scans were first acquired on one of the samples in order to optimize the experimental conditions to be used for the high-resolution measurements. For each tomographic scan, 1800 sample radiographs were recorded during continuous rotation over a total scan angle of 180°. The sample-to-detector distance was set at 150 mm. Samples were imaged with a water-cooled, 16-bit scientific complementary metal–oxide–semiconductor (sCMOS) macroscope camera whose effective pixel size was set at 0.9 × 0.9 µm2, yielding a maximum field of view of about 1.85 × 1.85 mm2. The detector system is equipped with a motorized quadrupole hosting four different scintillator screens. A 17-μm-thick GGG:Eu scintillator screen (ESRF, Grenoble, France) was selected for our experiment. The exposure time/projection was 3.5 s. For each tooth, we imaged at least one region of interest (ROI) located at approximately one-third of the tooth root from the cervical enamel. We reconstructed the volumes using the filtered back-projection algorithm provided by the SYRMEP Tomo Project (STP) software [33]. Prior to slice reconstruction, a single-distance phase-retrieval algorithm [34] was applied to the sample projections with a d/b parameter (the ratio between the real and imaginary parts of the complex refraction index of the material) in the range of 10–17 depending on the specific sample features.

Of the 21 teeth imaged, one contemporary human (ARF36) and six Neanderthals (KR7, KR25, KR176, KR1, KR137 and KR176) did not present enough cementum preserved in the region selected to offer consistent LHV estimates. Moreover, PC-SRμCT data revealed that extensive diagenetic damage had clearly occurred to the cementum of the Mesolithic specimen (H326/7) so no further analyses were carried out on this tooth. Consequently, we carried out data analyses on the remaining 14 teeth: eight contemporary humans, five Neanderthals and one Neolithic individual (table 2).

Virtual two-dimensional (2D) sections were extracted from the reconstructed 3D volumes using the open-source FIJI ImageJ [35]. To ensure maximum visibility of the tooth cementum annulations (TCAs), using the reslice tool in FIJI ImageJ, the virtual sections were made perpendicular to the root surface [36], rather than to the tooth axis, as, in the latter case, the section would cut the cementum layers in an oblique fashion. To minimize the risk of analysing a non-representative area, and to factually sample in three dimensions, even if by discrete increments, we made five virtual sections for each tooth (figures 1 and 2). For each of the 70 2D virtual sections, we obtained (electronic supplementary material, script S1) between 15 and 25 linear plots (depending on the length of the cementum segment) of the grey-level value of pixels across the entire thickness of the cementum (see electronic supplementary material, methods for a more detailed description). Finally, we saved the data of the plots, with the x-axis representing the distance (in years) from the cementum–dentine junction (CDJ), which was manually identified, and the y-axis the grey-level pixel value [20].

Figure 1.

Figure 1. Schematic representation of the workflow (from left to right): five 2D virtual sections of approximately 1.85 mm2 were made for each tooth; from each section, we obtained between 14 and 25 (depending on the extension of the cementum) 1-pixel-thick linear plots of the grey-level value of pixels across the entire width of the cementum, starting from the CDJ outwards. Each line plot was acquired at a distance of three pixels from the previous one.

Figure 2.

Figure 2. Two-dimensional virtual section of (a) specimen ARF77 (a mandibular central incisor), contemporary H. sapiens; (b) the fossil specimen KR172 (a mandibular second molar), H. neanderthalensis. For each specimen, small square at top left: zoom-in on the ROI. Top right: plot of the grey-value of pixels (y-axis) along the cementum segment indicated by the solid yellow line. Bottom right: 3D surface plot of the thicker cementum segment indicated by the shaded yellow rectangle. The 3D surface plot is for illustrative purposes only; data were collected on a series of line scans, as shown by the plot at topright.

2.3. Data analysis

2.3.1. Age-at-death (or tooth extraction in contemporary individuals) estimation

We followed previously published methods [16,18] of TCA count on PC-SRμCT data with the variant of measuring increments on five sections per tooth, rather than just one (see §2.2). Images were assigned randomized numbers to prevent unconscious bias in increment count. At least 24 h elapsed between the first and the second time each observer measured the increments on each of the 30 micrographs (five micrographs for each of the five Neanderthal individuals and one Neolithic individual). In table 3, we report the number of increments counted on each micrograph by each of the four independent observers (P.C., T.B., A.N. and L.B.), as well as the average value across the five micrographs.

Table 3. Number of cementum annuli counted by each of the two observers (P.C. and T.B.) on each of the 30 virtual sections.

specimen tooth image no. PC1 counts PC2 counts TB1 counts TB2 counts AN1 counts AN2 counts LB1 counts LB2 counts constant addeda P.C., T.B., A.N., L.B. avg age age estimate from wearb
KR27 LP3 305 6 7 5 6 5 5 5 4
KR27 LP3 557 5 6 5 3 4 5 5 4
KR27 LP3 782 9 8 5 6 8 7 7 5
KR27 LP3 811 10 9 5 6 9 8 8 6
KR27 LP3 2035 6 7 3 3 6 5 6 5
KR27 LP3 avg 7.2 7.4 4.6 4.8 6.4 6 6.2 4.8 9.3 17.025 16
KR85 LM3 917 10 9 7 7 8 10 11 8
KR85 LM3 921 9 9 7 7 9 8 11 8
KR85 LM3 950 10 10 6 7 8 7 9 5
KR85 LM3 1080 9 8 6 8 7 7 10 7
KR85 LM3 1093 11 12 8 7 9 10 10 8
KR85 LM3 avg 9.8 9.6 6.8 7.2 8.2 8.4 10.2 7.2 16.3 24.725 16
KR162 UM3 206 9 12 10 8 11 10 9 10
KR162 UM3 363 11 9 7 7 10 8 9 9
KR162 UM3 796 9 8 6 6 9 8 9 10
KR162 UM3 907 13 11 12 11 11 13 10 10
KR162 UM3 935 10 13 7 9 10 12 11 9
KR162 UM3 avg 10.4 10.6 8.4 8.2 10.2 10.2 9.6 9.6 16.3 25.95 25
KR172 LM2 1714 15 15 14 14 14 14 13 13
KR172 LM2 1730 11 10 5 7 12 11 14 12
KR172 LM2 1772 14 13 11 10 13 14 14 12
KR172 LM2 1778 9 7 7 8 9 8 14 9
KR172 LM2 2048 12 13 11 11 13 13 13 11
KR172 LM2 avg 12.2 11.6 9.6 10 12.2 12 13.6 11.4 9.8 21.375 25
KR179 UM3 6 9 10 8 9 9 10 13 11
KR179 UM3 22 14 12 10 9 10 11 13 12
KR179 UM3 302 10 12 9 7 10 10 10 10
KR179 UM3 332 8 7 5 8 9 7 10 12
KR179 UM3 464 11 13 10 9 10 10 11 10
KR179 UM3 avg 10.4 10.8 8.4 8.4 9.6 9.6 11.4 11 16.3 26.25 19
A2309 UM2 224 7 8 5 5 6 6 5 6
A2309 UM2 664 8 7 5 5 6 5 6 6
A2309 UM2 965 9 9 9 8 8 7 7 7
A2309 UM2 1228 8 9 4 5 6 5 6 6
A2309 UM2 1339 9 9 7 7 7 7 8 7
A2309 UM2 avg 8.2 8.4 6 6 6.6 6 6.4 6.4 9.5 16.25

aThe constant added to calculate the estimated age at death is: for Neanderthals (KR specimens), the minimum age at gingival eruption reported by [29]; for the Neolithic human (A239), the values reported by [37] for age at two-thirds of root completion.

bAge estimates based on wear are from [29].

Age-at-death estimation based on TCA counts is performed by adding the age at which cementum deposition begins, which is the estimated age at eruption of the tooth, to the number of annuli counted. While this constant is debated even for modern human populations (see [16]), the question is even more complicated when dealing with fossil hominins for which data on tooth formation time are limited [3841] and cementum initiation is poorly documented. Ideally, one would want to add the age at which cementum begins being secreted specifically in the region of the tooth where one is measuring the increments. Since for Neanderthal teeth that information is not available, we added the minimum age at gingival emergence as estimated by Wolpoff [29]. For the H. sapiens specimens, we added the age at one-third of root completion reported by [37] for maxillary teeth (males and females are pooled together), by [42] for mandibular teeth excluding the third molar (estimates differ for males and females) and by [43] for the mandibular third molar (estimates differ for males and females).

All statistical analyses were performed in R (v. 4.0.2) language [44]. To assess the agreement between observers and between successive measurements made by the same observer (intraobserver error), we used the intraclass correlation coefficient (ICC) [45] as implemented through the R package psych [46]. For each of the four observers, we report (electronic supplementary material, table S1) the ICC estimated values together with their 95% confidence intervals and p-values using a two-way mixed effects model ICC (3, k), where the first number in brackets refers to the model (1, 2 or 3) and the second number refers to the type, which is either a single rater/measurement (1) or the mean of k raters/measurements (k) [47].

2.3.2. Sexual dimorphism

We undertook exploratory research on possible sexual dimorphism in cementum layering and collected several variables from the line profiles of each virtual section of the individuals for whom we knew the sex. The same variables were also collected on the fossil specimens: five Neanderthals and one Neolithic individual, who was treated as sex = NA even though the sex was known for the Neolithic specimen (see §1.1). First, each line profile was smoothed according to two different denoising thresholds, thus producing two datasets that were analysed independently. The variables we measured were: the standard deviation of the grey-level value of pixels; the average amplitude of the peaks; the frequency of both positive and negative peaks; the standard deviation of the area of the peaks; the average width of both positive and negative peaks. The values were then averaged across the several data files of each micrograph. On these data from the modern samples, we used the rpart function [48] in R to construct a classification tree with sex as the grouping variable. We used it with method = ‘class’ and rpart.control at default settings. Additionally, we conducted two-tailed (Bonferroni corrected) t-tests to determine whether there was a significant difference between males and females. Subsequently, we applied the parameter of the splitting criteria obtained from the supervised classification on the training datasets (modern specimens) to the fossil specimens. Finally, for the variables that showed a statistically significant difference between sexes in the modern specimens we observed and reported their values for the fossil specimens. Methods are described in greater detail in the electronic supplementary material.

2.3.3. Age at physiologically significant event occurrence

To determine the age at which physiologically significant events occurred (event detection is described below), we proceeded under the verified assumption [12,20] that cementum growth rate is roughly constant and that therefore proportional relationships can be made in the form of: total cementum thickness/total years of cementum deposition = x-value (in pixels, or micrometres) of event detected/age at event occurrence (in years).

For each line profile of each of the 70 virtual sections, we used proprietary algorithms (electronic supplementary material, scripts S4 and S5) to (i) denoise the signal; (ii) identify peaks as local maxima and minima (electronic supplementary material, figures S1 and S2); (iii) detect peaks that were consistent among most (greater than 40%) of the line profiles of the same virtual section; and (iv) identify those that were present at highest frequencies when grouping the output peaks of the several virtual sections of the same individual together. Step (iv) was carried out by imposing a cut-off threshold at either 30% or 40% of the maximum frequency to minimize false positives (30% threshold) and to minimize false negatives (40%). Results are reported for both settings. The value in years of each peak thus obtained was summed to the age at cementum initiation to produce the final estimate of age at event occurrence. Methods are described in greater detail in the electronic supplementary material.

For the modern teeth, we calculated the average absolute difference between known and inferred age, the percentage error of the inferred age, the root mean square error (RMSE), the coefficient of determination (R2) between the two, the false-positive rate and the false-negative rate.

3. Results

3.1. Age at death

Krapina Neanderthals: the cementum-based estimated ages at death are reported in table 3, together with the estimates made by Wolpoff [29] based on dental wear. For KR27 and KR162 cementum-based estimates are very close to those based on wear. However, our results do not match the individual assignation to a KDP made by Wolpoff, according to whom KR27 and KR85 belong to KDP23 while KR162 and KR172 belong to KDP25. Our age estimation is discordant between KR27 and KR85 (9.35 years difference) and between KR162 and KR172 (5.05 years difference), which could derive from the margin of error regarding age estimates based on TCA counts [16].

The results of the ICC (electronic supplementary material, table S1) indicate that the reliability is excellent for both observers (see [47] for ICC results interpretation), meaning that the intraobserver error is very low. Conversely, the results of the ICC on the four different observers indicate that interobserver agreement is lower (ICC = 0.71; 95% CI: 0.56 < ICC < 0.83). Specifically, the agreement between A.N. and L.B. is very good (ICC = 0.88; 95% CI: 0.76 < ICC < 0.94), while P.C. consistently overestimates A.N. and L.B. by an average of 0.8 years, while T.B. consistently underestimates them by an average of 1.5 years. We took the arithmetic average between the four observers as our final age estimate.

3.2. Sexual dimorphism

The results of the recursive partitioning (electronic supplementary material, figure S3) on the known-sex samples indicate that the average width of positive peaks is the best discriminating variable between the sexes regardless of noise threshold (0.3*Std or 1*Std). Based on this parameter, the misclassification rate for females is 4%, while for males it is 40% (electronic supplementary material, figure S4). This difference in misclassification rate is likely to be due to the larger number of female specimens than male specimens. For this variable, the range for females is 22.7–32.15, while for males it is 18.28–26.29 (figure 3). In addition, several other variables (electronic supplementary material, table S2) appear to be significantly different between the two sexes based on the results of the t-tests. Since some of the variables that were significant at 0.3*Std were not significant at 1*Std, we only use the ones significant in both settings to make our informed suggestions regarding the sex of the fossil specimens. We, therefore, used the areas of non-overlap in values between the male and female ranges (thus excluding the range of 22.7–26.29) to suggest a specimen as either male or female. The misclassification rate on the modern specimens based on non-overlapping ranges is 0% for both males and females, with 54.3% of the cases resulting in no estimate being made (electronic supplementary material, figure S5). By suggesting an estimation of sex only if the value fell within the exclusive (non-overlapped) range of either sex our results indicate that the Neanderthal fossils KR172 and KR179 might be females and the Neolithic specimen A2309 is female, while for the remaining three Neanderthal specimens we make no informed suggestion (table 4). Our analyses correctly predicted the sex of A2309.

Figure 3.

Figure 3. Boxplot of the average positive peak width for the contemporary known-sex females (F), contemporary known-sex males (M) and the six fossil specimens, of whom five Neanderthals were unknown sex (grey boxes) and one Neolithic H. sapiens (A2390) was known to be female from DNA analysis. Each data point represents the average positive peak width value for a single 2D virtual section; five 2D virtual sections were made per specimen. The boxes show the interquartile range (IQR); the line shows the median of the data; the whiskers add 1.5 times the IQR from the 75th percentile and subtract 1.5 times the IQR from the 25th percentile; the dots represent outliers. The sex of A2390 (Neolithic specimen) is known via DNA analysis and it was then correctly estimated via our analyses.

Table 4. Suggestions of sex of the fossil specimens based on the average width of positive peaks. We report the value for each specimen at two different noise thresholds. The partitioning value derived from the recursive partition is 23.13; the range for known-sex females is 22.70–32.15, while for males it is 18.28–26.29. The ranges of no overlap are 18.28–22.69 for males and 26.30–32.15 for females. For the Neolithic specimen, the sex was known through DNA analysis and our results correctly predict it. For specimens that had a value falling within the overlap male and female range no suggestion is made.

species specimen average width of positive peaks at 0.3 * Std average width of positive peaks at 1 * Std sex estimated based on range known sex
H. neanderthalensis KR162 25.834 25.834 / /
H. neanderthalensis KR172 27.394 27.394 F /
H. neanderthalensis KR179 34.486 34.486 F /
H. neanderthalensis KR27 25.872 25.872 / /
H. neanderthalensis KR85 25.268 25.268 / /
H. sapiens (Neolithic) A2309 27.038 27.038 F F

3.3. Age at event occurrence

We found that there is a strong and statistically significant positive correlation (R2 = 0.9874; p < 0.05) between known and inferred ages at physiological stressors (pregnancy, illness, etc.) in the modern reference samples. The inferred ages together with the known ages at event occurrence are reported in electronic supplementary material, table S3. The intercept value (y = 0.1063) of the equation of the regression line reported in figure 4 (y = 1.0034x + 0.1063) indicates that there is no systematic error towards over- or underestimating the ages at event occurrence. The average absolute difference between known and inferred ages in the estimates of all known events is 1.9 years; the RMSE is 2.1 years. The false-positive and false-negative rates differ considerably depending on the final parameter used in the analysis. With the cut-off threshold at 40% of the maximum frequency, the false-negative rate is 0%, meaning that all known events are detected; however, the false-positive rate is extremely high at 55.2%. When implementing a stricter cut on the final output (30% of the maximum frequency), the false-negative rate increases to 10.3% while the false-positive one logically decreases to 34.5% (table 5). The inferred ages at event occurrence for the fossil specimens are reported in table 6. Only one event was detected for each specimen.

Figure 4.

Figure 4. Plot of the inferred versus known age at event occurrence for all the known-event individuals included. The superimposed grey line represents the regression line with equation y = 1.0034x + 0.1063 (R2 = 0.98; p < 0.05). The data used for this plot are available in electronic supplementary material, table S3.

Table 5. For each of the two settings of the final event detection analysis (see Methods for details): the associated average absolute difference between known age at event occurrence; the RMSE; and the false-negative and false-positive rates.

setting avg absolute difference RMSE false negative (%) false positive (%)
30% of maximum frequency 1.93 2.13 0 55.17
40% of maximum frequency 1.91 2.1 10.34 34.48

Table 6. Results of the inferred ages at event occurrence for the fossil specimens (KR are the Krapina Neanderthals). Ages at cementum initiation and age at death are estimated (see §2.3.1) and reported in table 3. Suggested sex is reported as resulting from our analyses (table 4).

specimen age at event sex age at death
KR27 13.94 / 17.03
KR85 24.04 / 24.73
KR162 23.84 / 25.95
KR172 15.61 F 21.38
KR179 23.55 F 26.25
A2309 15.52 F 16.25

4. Discussion

Our age estimates match fairly well with those based on dental wear, even though there are some potential differences from the KDP assignation made by Wolpoff [29]. Nonetheless, as previously reported [16] there is a non-negligible margin of error regarding age estimates based on TCA counts. The difference between known and inferred age, for individuals less than 50 years of age, is reported to be between 6.8 and 6.5 years [16]. Future works could benefit from recently developed semi-automatic TCA count methods [49,50] in order to eliminate inter- and intraobserver error. Additionally, because of the inhomogeneous nature of cementum, tracking the growth increments via 3D virtual reconstruction could help reduce error in age estimates. The age at which cementum begins formation is another source of error, which in the future could be addressed by acquiring scans of whole teeth to enable precise measures of crown and root formation times. Hence, the results of our study are not conclusive enough to add meaningful information to the KDP assignation. It is worth noting that, although our sample size is small, there does not appear to be any systematic over- or underestimation of age, compared with the one derived from dental wear.

The exploratory research regarding sexual dimorphism in cementum microstructure has provided insights into a potentially novel area of research. Based on our small sample and preliminary observations, it appears that the width of peaks in the grey-level profile of cementum transects might be sexually dimorphic, with males presenting on average narrower event oscillations than females. This could reflect the rapidity (frequency of peaks also seems to be sexually dimorphic) in changes in tissue deposition and could be caused by underlying metabolic differences between the sexes, which in turn are likely to be correlated with body size sexual dimorphism since metabolic rate scales with body size [51]. Indeed, research has shown that inner fundamental metabolic rhythms reconcile and regulate tissue formation and organ masses across primates [52,53]. This is reflected, for example, in the sexually dimorphic periodicity of repeat intervals (RIs) in enamel formation such that the average Havers–Halberg oscillation RI values are lower (hence frequency is higher) for males than for females [54]. Accordingly, other works have demonstrated the presence of sexual dimorphism in bone accretion with an increased turnover in males, which suggests a higher metabolic activity in this sex [55,56]. Although our study has a small sample size, we were able to correctly estimate the sex of a Neolithic fossil tooth. Our preliminary results seem to confirm recent research [18], which has reported evidence of sexual dimorphism in the cementum of another primate species (M. mulatta). It is therefore likely that there is sexual dimorphism in the microstructure of this tissue, but systematic exploration on a larger sample is necessary in order to better understand it, especially across different taxa, which in turn have differing degrees and forms of sexual dimorphism (e.g. macaques have sexually dimorphic canines while humans do not).

While previous research has confirmed that physiologically impactful events, such as those relating to reproduction, are permanently recorded in cementum microstructure and can be accurately timed [1214,20], this is the first study to demonstrate that it is possible to obtain such information in a non-destructive manner. This is of tremendous importance for its applicability to fossil specimens. Indeed, the results of our analyses support the hypothesis that physiologically impactful events are detectable using the PC-SRµCT technique. However, the high false-positive rates of the known-event sample indicate that most events are detected but not all detected events are necessarily real. Nonetheless, it is important to note that we cannot be completely certain that false positives are not actually real events, which the anonymous participant omitted or forgot to include in their questionnaire, as documented by previous research that has addressed the problem of retrospective reporting [57,58]. Additionally, it is possible that events subjectively deemed insignificant and not directly related to health and reproduction (which is what our questionnaire assessed) actually have significant effects on cementum deposition. Indeed, recent research [59] has shown that in mandrills (Mandrillus sphinx) events such as changes of alpha male within a group correlate with an accentuated line in enamel.

When applying our event detection algorithms to our sample of fossils, our results (table 6) indicate only one physiologically impactful event per individual. While our known-event specimens had a high false-positive rate, they also had a 0% false-negative one, meaning that we should expect all known events to be detected. It is likely that the physiology of modern urban-dwelling people is more perturbed and less tightly correlated to seasonal rhythms than that of Neanderthals, leading to an increased amount of perturbations in the cementum that are not correlated to any known stressors. Additionally, the results of our sex, age and event estimations combined could suggest that the physiologically impactful events reported for A2309 (15.5 years) and KR172 (16.6 years) could reasonably relate to menarche, which in contemporary hunter–gatherer populations has a mean of 16.6 and a median of 17.1 years [60], and is expected to be earlier for Neanderthals, who had an overall accelerated life-history scheduling compared with H. sapiens. As for KR179, for whom we report only one physiologically significant event at 23.6 years, we are inclined to suggest the possibility of it relating to a reproductive event or severe illness. However, we lack an explanation for the absence of a menarche signal, if this is indeed a female.

However, it is necessary to acknowledge that all inferred events are between 0.7 and 5.4 years before death, making it possible that the physiologically stressful events detected close to death were possibly correlated to it. Notwithstanding, as already acknowledged by several recent works [12,21], it is not possible to infer the cause of stressor from the histological analyses of cementum alone. It is likely that elemental analyses would provide more event-specific information, in that each different type of stressor alters the mineral homeostatic balance in a different way. However, that type of data is not yet available using non-destructive methods. Future research aiming at collecting elemental data and teasing apart the cause of the stressor is necessary, such as synchrotron X-ray fluorescence mapping [61] on the cementum of fossil teeth having natural broken roots.

In conclusion, the present work provides tentative evidence that sex can be recovered from cementum microstructure, and robust evidence that the chronology of physiologically impactful events is both preserved in cementum microstructure and detectable using non-destructive 3D imaging methods. Future research will hopefully build on the present work and further advance our knowledge.

Ethics

The research was carried out under the auspices of the College of Medicine Research and Ethics Committee (COMREC) (protocol no. P.05/06/373). All methods were carried out in accordance with relevant guidelines and regulations and all experimental protocols were approved by the NYU College of Dentistry.

Data accessibility

The data are provided in the electronic supplementary material [62].

Authors' contributions

P.C.: conceptualization, data curation, formal analysis, funding acquisition, investigation, methodology, project administration, resources, software, validation, visualization, writin—original draft, writing—review and editing; A.N.: data curation, formal analysis, funding acquisition, investigation, methodology, project administration, writing—review and editing; D.R.: data curation, investigation, resources, writing—review and editing; D.B.: resources, writing—review and editing; L.C.: data curation, formal analysis, methodology, software; T.B.: data curation, formal analysis; G.R.: resources, writing—review and editing; D.W.F.: supervision, writing—review and editing; A.P.K.: data curation, investigation, methodology; L.B.: formal analysis, investigation, methodology, project administration, supervision, writing—review and editing; L.M.: data curation, investigation, methodology, project administration, supervision, writing—review and editing; T.G.B.: data curation, formal analysis, funding acquisition, investigation, methodology, project administration, supervision, validation, writing—review and editing.

All authors gave final approval for publication and agreed to be held accountable for the work performed herein.

Competing interests

We declare we have no competing interests.

Funding

The research was supported by a National Science Foundation Graduate Dissertation Research Improvement Grant (to P.C., grant no. 2018357), by the NYU MacCracken Fellowship (to P.C.) and by the Marie Skłodowska-Curie Actions Individual Fellowship (to A.N., grant no. H2020-MSCA-IF-2018-842812).

Acknowledgements

The authors acknowledge Elettra Sincrotrone Trieste for access to the SYRMEP beamline (proposal no. 20180099) and the SYRMEP beamline staff members for their assistance in data experiment set-up and data collection and to D.B. by the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 846856.

Footnotes

Electronic supplementary material is available online at https://doi.org/10.6084/m9.figshare.c.5849111.

Published by the Royal Society. All rights reserved.