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Dermatoglyphic asymmetry and testosterone levels in normal males.

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AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 90:185-198 (1993)
Dermatoglyphic Asymmetry and Testosterone Levels
in Normal Males
CHERYL SORENSON JAMISON, ROBERT J. MEIER, AND
BENJAMIN C. CAMPBELL
Anthropology Department, Indiana University, Bloomington, Indiana
47405 (C.S.J., R.J.M.) and Anthropology Department, Haruard
University, Cambridge, Massachusetts 02138 (B.C.C.)
KEY WORDS
Finger prints, Palm prints, Salivary steroids,
Geschwind Hypothesis
ABSTRACT
Dermatoglyphic prints and salivary samples were taken on a
sample of 39 adult males. A statistical relationship between dermatoglyphic
asymmetry and adult testosterone levels as measured in saliva was examined
for seven dermatoglyphic variables by means of correlation, regression, and
analysis of covariance, controlling for age and stature when necessary. The
first two types of anlayses indicated a significant effect of testosterone level
upon the asymmetry of three dermatoglyphic variables: a-b ridge count, palmar pattern intensity, and the combined pattern intensity of palm and digits.
Analysis of covariance, which examined the effect of testosterone level as a
categorical variable, while holding age or stature constant, demonstrated the
asymmetry of five variables to be significantly affected by testosterone level:
radial digital count, digital pattern intensity, palmar pattern intensity, total
digital ridge count, and the combined palmar and digital intensity. Although
there is as yet only associational evidence linking levels of prenatal and
secondary testosterone, the results of the present study lend support to the
hypothesis that prenatal testosterone levels may have a significant effect on
the development of dermatoglyphics. 0 1993 Wiley-Liss, Inc
The search for the determinants of dermatoglyphic variation has identified a number of potential alternatives, many of which
could function interactively. Genetics, of
course, plays a major role (e.g., Holt, 1956;
Loesch et al., 1978), but the fact that even
monozygotic twins differ to some degree in
dermatoglyphic traits (e.g., Reed et al.,
1977) indicates a strong prenatal environmental component in the expression of dermatoglyphic variation.
Since dermatoglyphic characteristics are
established before the 19th week of gestation (Cummins, 1929; Hale, 1949, 1952;
Mulvihill and Smith, 1969; Babler, 1987),
whatever factors that are hypothesized to
affect ridge development must be in operation before or during this time period. After
the 19th week, epidermal ridge configurations are set; injury and caustic substances
0 1993 WILEY-LISS, INC.
may reduce the appearance of the ridges,
but unless the skin is destroyed to a depth of
at least one millimeter, the original pattern
will return (Cummins and Midlo, 1961).
A number of studies have elucidated the
effects of various environmental factors on
dermatoglyphic traits. Internal prenatal environment effects that have been investigated have included, for example: rubella
(Achs et al., 1966), alcohol (Qazi et al., 1980;
Dar and Jaffe, 19831, cytomegalovirus infec-.
tion (Wright et al., 1972), nonspecific intrauterine insult (Rose et al., 1972), and “maternal effects” (Reed et al., 1979). The
Received October 10,1991; accepted July 29,1992
Benjamin C. Campbell’s present address is Carolina Population Center, University of North Carolina, Chapel Hill, North
Carolina 27516.
186
C. SORENSON JAMISON ET AL.
external environment has also been hypothesized to have critical influence on epidermal features (e.g., Rosa, 1985; Loesch, 1986;
Blangero, 1988).
The present research follows a different
line of investigation from those previously
described. Here it is proposed that a critical
variable, such as the level of a circulating
hormone, specifically testosterone, has a genetic as well a s a prenatal environmental
component. The prenatal testosterone to
which a fetus is exposed arises from two
sources: the hormone that the fetus itself
produces has a (probably pleiotropic) genetic
basis, while the testosterone that originates
from the mother provides environmental exposure, as far a s the fetus is concerned. We
have earlier reported the rate of maturation
to be a determinant of dermatoglyphic variation (Meier et al., 1987; see also Livshits
and Kobyliansky, 19871, and that dyslexics,
who have been described as being late maturers, differ dermatoglyphically from a
sample of normal controls (Sorenson Jamison, 1988, 1990; Meier, 1990, and work in
progress). The Geschwind Hypothesis (Geschwind and Behan, 1982; Geschwind and
Galaburda, 1985) identifies a n excess of prenatal testosterone to be the central causative factor involved in the development of
dyslexia, a s well a s of a number of other
central nervous system disorders. The fact
that one of the effects of prenatal testosterone is the modification of developmental
rate (McEwen, 1981; MacLusky and Naftolin, 1981; Bardin and Catterall, 1981; Geschwind and Galaburda, 1985) ties the two
lines of investigation together. If dyslexics
and late maturers demonstrate significantly
different dermatoglyphic variation than
controls, and if testosterone has been related to both the development of dyslexia
and to slowed maturation, then the dermatoglyphic investigation of testosterone is
a logical next step.
It is not possible to test directly for the
differential dermatoglyphic effect of prenatal testosterone in humans because of the
ethical problems associated with such a n endeavor. However, indirect support for the
importance of testosterone to both the variation in dermatoglyphic traits and to the development of dyslexia might be gained if a
relationship between dermatoglyphic variation and secondary testosterone, which is
more easily and ethically measured, could
be demonstrated.
Testosterone secretion is not constant
throughout the life cycle (Lowrey, 1986;
Tanner, 1990). The male fetus secretes increasing amounts of testosterone from the
time of Leydig cell differentiation, a t approximately eight weeks, until midgestation
(George et al., 1981). From that point, the
testosterone level declines gradually until
by a few months following birth it has
reached the low level characterizing childhood. At puberty, testosterone secretion
once again increases and orchestrates the
development of secondary sexual characteristics. Testosterone levels do not remain constant during adulthood either: numerous
studies have documented a n age-related decline in testosterone starting in early adulthood (at least by the early thirties) in both
serum (Deslypere and Vermeulen, 1984;
Lewis et al., 1976; Pirke and Doerr, 1973;
Purifoy et al., 1981) and saliva (Read and
Walker, 1984; Campbell e t al., 1991).
While the relationship between prenatal
and secondary testosterone levels is not
presently known, evidence of a genetic influence on both pubertal and adult levels of
testosterone and other androgens has been
reported (Akamine et al., 1980; Meikle e t al.,
1982, 1988; Rotter et al., 1985). These studies do suggest a n association between a n individual’s prenatal and secondary testosterone levels. It would seem reasonable to
assume that the genetic effect on testosterone level would be greatest at the earliest
ages (when environmental effects have had
less chance to exert themselves) and would
then decrease over time. Since environmental influences on testosterone can only obscure a n association between prenatal and
postpubertal testosterone levels, a demonstrated relationship between secondary testosterone level and dermatoglyphic patterns
may be taken as indirect evidence for a n
association between prenatal testosterone
level and developing dermatoglyphic features.
The focus of the present study was the
investigation of the relationship between
secondary testosterone level and dermato-
DERMATOGLYPHICS AND TESTOSTERONE
glyphic asymmetry. Dermatoglyphic asymmetry variables were chosen for a number of
reasons. First, such asymmetry has been repeatedly indicated a s being related to developmental variation (e.g., Jantz and Webb,
1980; Livshits and Kobliansky, 1991). A second reason for the selection of asymmetry
was that a central prediction of the Geschwind Hypothesis is that a n excess of prenatal testosterone is expected to result in
greater morphological asymmetry. Additionally, one of the most significant findings
from the dyslexic study was that dyslexics
exhibited greater bimanual asymmetry
than the controls.
MATERIALS AND METHODS
The sample for this study included 39
healthy Caucasian male volunteers, between the ages of 18 and 45.Digital prints
were taken by C.S.J. with Hollister Footprinters and analyzed by R.J.M., and palm
prints were taken with graphite and tape
(Robertson-Neufeld and Murray, 1978) and
analyzed by C.S.J., using a modified version
of the Penrose-Loesch topological technique
(Loesch, 1983; Sorenson Jamison, 1988). Saliva specimens, for the testosterone analysis, were taken by R.J.M. on a second visit,
in order to ensure comparability of intervening variables. To control for the well documented diurnal variation in salivary testosterone (Walker et al., 1980a; Campbell e t al.,
1991; Magrini et al., 1986; Dabbs, 19901, all
subjects provided saliva specimens at the
same time of day (between 10 and 11in the
morning). To avoid any potential contamination of the saliva sample from food a n d o r
bleeding gums, subjects were requested not
to have eaten or brushed their teeth before
arriving. Furthermore, since acute rises in
testosterone levels may result from both exercise (Cumming et al., 1986) and sexual activity (Fox et al., 1972), subjects were asked
to refrain from these activities in the previous 24 hours. Prior to saliva collection, subjects were given a stick of gum (Carefree
Sugarless) to stimulate saliva flow, which,
according to Ellison (1988), has no effect on
accuracy of testosterone measurement. Saliva was collected into a test tube containing
sodium azide, an antibacterial agent.
187
Salivary testosterone was utilized because the methodology offers many advantages over plasma or urinary assays. This
method is noninvasive and nondisruptive,
the specimen is easy to collect and to store,
and furthermore, i t has been demonstrated
to reflect free, biologically active plasma testosterone levels (Ellison, 1988; Lipson and
Ellison, 1989; Wang et al., 1981; Schurmeyer and Nieschlag, 1982). Testosterone levels in the saliva were determined by BCC
with radioimmunoassay, using a specific antibody (No. 250, supplied by Gordon Niswender), as described in Ellison et al. (1989).
All samples were assayed in a single assay
with a n interassay variability of 9.0%. Salivary testosterone values ranged from 242
pmoVL to 701 pmoVL, within the normal
range reported for salivary testosterone of
adult males (Read and Walker, 1982;
Walker e t al., 1980b; Schurmeyer and Nieschlag, 1982; Campbell et al., 1991; for instance, Ellison et al., 1989 reported a normal
range for males in western population to
vary between 100 and 1,000 pmol/L).
Dermatoglyphic variables
and statistical analyses
All statistical analyses were run using
SPSSPC-t, version 4.01 (NorusidSPSS Inc.,
1990). Bimanual asymmetry variables were
computed (left minus right) from the following left and right original dermatoglyphic
variables: digital radial count, digital ulnar
count, palmar a-b count, digital pattern intensity, palmar pattern intensity, total digital ridge count, and combined digital and
palmar pattern intensity. The names and
definitions of the asymmetry variables examined in the present study are listed in
Table 1. These variables, as well as age and
TABLE I . List of dermatoglyphic asymmetry variables
used in the anaLyses
Variable name
Definition
~
RCASYM
UCASYM
ABASYM
DPIASYM
PPIASYM
TDRCASYM
COMPASYM
Digital radial count
Digital ulnar count
Palmar a-b count
Digital pattern intensity
Palmar pattern intensity
Total digital ridge count
Combined digital and palmar
pattern intensity
C. SORENSON JAMISON ET AL
188
TABLE 2. Descriptiue statistics for original dermatoglyphic variables and their Pearson correlations with testosterone
and age as well as partial correlation with testosterone leuel (after the effect of age has been removed)
Variable name
Mean
S.D.
r (Testos)
r (Age)
Left radial digital count
Right radial digital count
Left ulnar digital count
Right ulnar digital count
Left palmar a-b count
Right palmar a-b count
Left digital pattern intensity
Right digital pattern intensity
Left palmar pattern intensity
Right palmar pattern intensity
Left total digital ridge count
Right total digital ridge count
Left complex pattern intensity
Right comDlex Dattern intensitv
61.10
61.15
18.59
23.26
38.33
37.21
6.05
6.51
1.62
1.59
76.69
84.41
7.67
8.10
26.74
24.13
18.72
23.42
3.97
4.74
2.04
1.82
0.91
0.75
41.25
42.58
2.34
2.11
p.218
p.229
-.122
-.3572
p.027
p.227
-.122
-.327'
.3892
-.098
-.I97
- .32V
,045
-.3162
,283
,231
,094
.3642
.093
,233
,140
.314'
p.278
-.090
,226
.3312
.014
,238
__
Partial r
- ,090
p.133
-.087
p.215
.024
-.130
p.060
- .206
.300
p.167
p.098
p.194
,060
p.234
N = 39.
'Significant at the .05level
stature, were first analyzed with salivary
testosterone level using Pearson Product
Moment correlation. Regression analyses
were then run to examine the predictive effect of salivary testosterone level on dermatoglyphic asymmetry. Thirdly, Analysis
of Covariance using the W O V A program
was used to determine whether a significant
amount of variance in the dermatoglyphic
asymmetry variables could be explained by
high and low testosterone group membership.
RESULTS
Descriptive statistics for the original dermatoglyphic variables, from which the
asymmetry variables were computed, are
presented in Table 2 . On the right side of the
table are also found the correlations of the
TABLE 3 Pearson product moment correlation
coefficients and associated probability (two-tail) between
salivary testosterone levels and dermatoglyphic asymmetry
uariables, age, and stature
Variable
RCASYM
UCASYM
ABASYM
DPIASYM
PPUSYM
TDRCASYM
COMPASYM
AGE
STATURE
Entire sample'
r
P
-.0345
,3984
.2500
,2722
,3754
,3280
.4154
-.5061
.1571
=
r
P
,835
.I502
,420
,012
,125
,094
.019
.042
.009
,001
,340
,2307
,3975
,2827
,3967
-.1778
3830
,212
,027
,123
.027
,339
,033
' Entire sample, N
= 39.
Sample 25 years or younger, N
Age LE 25 yrs'
31.
::;;: ::;:
dermatoglyphic variables with testosterone
and age, and the partial correlation of the
variable with testosterone after controlling
for the effect of age.
The results of the correlation analysis between the dermatoglyphic asymmetry variables and testosterone can be seen in Table
3. It is immediately apparent that while
many of the asymmetry variables demonstrate a positive relationship with testosterone level, age is highly significantly correlated with testosterone as well.
Two possibilities presented themselves as
ways to deal with this relationship. One alternative would be to control for the effects
of age statistically while continuing to use
the entire sample, the other is to restrict the
analysis to a homogeneous age range. Examination of the frequencies for age (see Fig.
la) demonstrates that the first break in the
range appears at age 25, and this was the
break we decided to use in our analyses. A
scatterplot showing the distribution of testosterone level by age as well as grouped testosterone level frequencies for the entire
sample and the selected restricted age sample are also included in Figure 1 (b, c, and d,
Eespectively). The reduced variability apparent in testosterone level with age was
Fig. 1. Freauencies of age
- a n d testosterone. a: Age
for entire sample. b: Scatterplot of testosterone by age.
c: Testosterone levels for entire sample. d Testosterone
I
levels for restricted sample.
I
-
10
100-200
rFREQUENCY
12
10
301-400
401-500
501-600
TESTOSTERONE PMOL/L
201-300
601-701
Y
n
2-
4-
8-
6-
100-200
FREQUENCY
301-400
401-500
501-600
TESTOSTERONE PMOL/L
201-300
601-701
(AGE LE 25, N = 3 1 )
40
d. FREQUENCIES OF TESTOSTERONE LEVEL
30
.
(ENTIRE SAMPLE, N = 3 9 )
20
. . ..
'
c . FREQUENCIES OF TESTOSTERONE LEVELS
i
. .* . .
LEVEL
AGE
10
200
400
600
SALlVAFN TESTOSERONE
(ENTIRE SAMPLE, N = 3 9 )
b. SCATTERPLOT OF AGE AND TESTOSTERONE
AGE
11119 202 122 23 24 25 2827 2829 30 3132 3334 3536373839404 142 4344 45
a. FREQUENCIES OF AGES
(ENTIRE SAMPLE, N=39)
50
C. SORENSON JAMISON ET AL
190
TABLE 4a. Results of multiple regression analyses predicting dermatoglyphic asymmetry variables from stature and
saliuarv testosterone levels
Dermatoglyphic
variable
RCASYM
UCASYM
ABASYM
DPIASYM
PPIASYM
TDRCASYM
COMPASYM
t
Stature
P
B
t
Testosterone
P
B
-0.72
1.54
-0.16
-0.65
-0.18
0.93
-0.53
,480
,136
,875
,522
355
,362
.601
p.215
,716
-.018
- .024
p.007
,501
p.030
1.02
0.62
2.31
1.42
2.19
1.11
2.33
,315
,539
,029
,168
.037
,277
,028
,015
,027
,013
,003
,004
,029
,006
~~
-
Equation
R2
~
.04
.13
.15*
.07
.162
.ll
,172
‘Age 525, N = 31, none of the multiple regression equations were significant a t the .05 level.
“The hivariate regression, without controlling for stature, is significant at the .05level.
TABLE 46. Results of multiple regression analyses predicting dermatoglyphic asymmetry variables from age and
salivarv testosterone levels
Dermatoglyphic
variable
___
Testosterone
Age
P
-~
t
B
t
D
B
1.39
-1.94
-0.46
-0.63
0.21
-0.78
-0.32
,173
.061
.650
.535
.836
-439
,750
,426
p.851
-.057
-.025
.007
-.425
p.018
0.52
1.38
1.11
1.16
2.20
1.42
2.20
,606
.175
275
.256
.034
,166
,034
,006
.024
.005
,002
.003
.031
,005
Equation
R’
~
RCASYM
UCASYM
ABASYM
DPIASYM
PPIASYM
TDRCASYM
COMPASYM
.05
24’
-07
-08
.153
.12
,182.3
‘Entire sample, N = 39.
“he multiple regression equation IS significant at the .05 level.
3The hivariate regression, without controlling for age, is significant a t the .05level.
viewed a s offering further support for the
decisions to concentrate only on the homogeneous lower age group. However, it must be
emphasized that since the number of individuals in our sample over the age of 25 is so
small (eight), no valid conclusions can be
drawn concerning this age group from the
population.
There are valid arguments to both methods of dealing with the age effect. Loss of
information is always to be avoided, if possible; however, we felt that the problem of this
potential loss was overridden by a n additional problem of environmental noise that
is presumably introduced with increasing
age. Genetic influence on testosterone level
was assumed to decrease subsequent to the
prenatal period and to become increasingly
weaker with advancing age. Therefore, we
chose to restrict our analyses to a relatively
homogeneous age sample between 18 and 25
years. However, in order to allow readers to
form their own judgments about our data,
we do include the results of both types of
analyses (that is, entire sample versus restricted sample) for comparison purposes.
The correlation was run a second time,
after restricting the sample to those individuals 25 years old or younger (right side of
Table 3). Several of the dermatoglyphic variables continued to be correlated with testosterone in this sample, but age was no
longer significantly related to testosterone.
However, at this point, stature became important (P = ,033). On the basis of these results the decision was made to examine the
effect of stature, controlling for this variable
in the restricted sample.
The multiple regression results for the
age-restricted sample are presented in Table 4a. The effect of stature was not of even
borderline significance on any of the variables (column 21, while the effect of testosterone was significant for three variables,
ABASYM, PPIASYM, and COMPASYM,
even after controlling for the effect of stature
Fig. 2. Scattergrams illustrating significant bivariate relationships between testosterone level and asymmetry variables (N = 31, age 25). a: ABASYM. b: PPIASYM. c: COMPASYM.
a. TESTOSTERONE AND a
COUNT ASYMMETRY
10
-b
- b Count bymnwtry
I
1
b. TESTOSTERONE AND PALMAR
PATTERN INTENSITY ASYMMETRY
a
2
Palmer Pattern Inhnolty Aoynnnotry
9.-
+
--Q-
c. TESTOSTERONE AND COMBINED
PATTERN INTENSITY ASYMMETRY
C o m b l d PotMn lnhnrltv AIYrnnntrv
C. SORENSON JAMISON ET AL.
192
TABLE 5. Frequency distrlbution of saliuaq testosterone
; = 311
leuel (in pmollL; age ~ 2 . 5 N
Testosterone level
242
270
281
292
293
304
306
318
337
350
355
369
424
426
427
435
444
447
476
482
484
520
521
532
536
550
603
621
657
691
701
(column 5). Scattergrams for the three significant bivariate relationships (that is, regressions without controlling for stature)
are illustrated in Figure 2, with the regression lines indicated. Table 4b includes the
results from the multiple regression analyses on the entire sample, controlling for the
effect of age rather than stature.
To examine the effect of high versus low
testosterone level as a categorical variable,
subjects were divided into testosterone
groups on the basis of a frequency distribution (presented in Table 5). Testosterone
values ranged from a low of 242 pmoWL to a
high of 701 pmoWL, with a mean of 441.74
pmoWL. There was a level, above and below
400 pmoWL, which provided a reasonable
sectioning point between two clear clusters.
Although this division resulted in two
groups of unequal size, it was utilized because of the obvious gap between the values
of 369 pmoWL and 424 pmol/L. The low testosterone group (LE 369 pmol/L) included 12
subjects; the high testosterone group (GE
424 pmoWL) was composed of 19 individuals.
Using the SPSSPC + program MANOVA,
analyses of covariance were run with stature as a covariate. The results can be seen in
Table 6a. The effect of stature (presented
under the regression columns) was only of
borderline significance for the dermatoglyphic variable UCASYM (2' = ,0771,and of
no significance for any of the others. Testosterone was not significantly related to
UCASYM. However, for the remaining six
analyses, it can be seen that five of the variables are significantly affected by testosterone. While ABASYM was not significant (as
it had been in the regression analysis),
RCASYM, DPIASYM, and TDRCASYM
demonstrate significance along with the
continuing importance of PPIASYM and
COMPASYM. Again, the analyses were run
a second time on the entire sample, with age
rather than stature as the covariate, and the
results are presented in Table 6b.
The means and standard deviations for
the high and low testosterone groups are
presented in Table 7a. One very striking
finding that is apparent from this table is
that in the low testosterone group, all of the
dermatoglyphic asymmetry variable means
are negative and all of those in the high testosterone group are positive. Since the
asymmetry variables were calculated left
minus right, Table 7a indicates that for the
low testosterone groups, the right side value
was higher than that of the left, while for the
high testosterone groups, the left side value
was higher. Figure 3 graphically illustrates
the differences between the two groups for
each of the dermatoglyphic asymmetry variables. Table 7b includes the descriptive statistics for the entire sample divided into low
and high testosterone groups on the same
basis (LE 369 and GE 424 pmoWL). The positive and negative signs are the same as in
Table 7a with the single exception of
ABASYM in the low testosterone group.
DISCUSSION
These results lend strong support to our
hypothesis that testosterone level has a significant effect upon dermatoglyphic asymmetry. This is in agreement with a recent
general review of the subject of asymmetry
and developmental shift by Livshits and Kobyliansky (1991). Of the seven variables
studied, only one (UCASYM) failed to demonstrate a clearly significant relationship to
salivary testosterone in either the regression or analyses of covariance. This variable,
it may be remembered, was also the only one
to have a borderline significant relationship
to stature.
The regression analyses examined testosterone level as a continuous variable.
Three of the seven dermatoglyphic variables
demonstrated a significant relationship
(P < .05) to testosterone level. Two of these
variables, ABASYM and PPIASYM, are the
193
DERMATOGLYPHICS AND TESTOSTERONE
TABLE 6a. Results of analysis of couariance predicting dermatoglyphic variables from high and low testosterone groups,
with stature as a couariate
Dermatoglyphic
Regression2
RCASYM
UCASYM
ABASYM
DPIASYM
PPIASYM
TDRCASYM
COMPASYM
Constant
F
P
0.35
3.37
0.36
0.14
0.22
1.81
0.01
.560
.077
,555
,708
,640
.189
.935
variable
'Age 525. Total N = 31, high N = 19, low N
'Regression statistics refer to the covariate.
=
- -.
-
Testosterone
-
F
P
F
P
0.30
3.50
0.30
0.09
0.23
1.97
0.02
,590
,072
.591
,773
,635
,171
5.42
1.68
2.73
7.54
8.79
6.21
15.11
,027
,206
,110
,010
,006
,019
,001
.886
12
TABLE 6b. Results of analysis of couariance predicting dermatoglyphic variables from high and low testosterone groups,
with age as a couariate
Regression2
Dermatoglyphic
variable
RCASYM
UCASYM
ABASYM
DPIASYM
PPIASYM
TDRCASYM
COMPASYM
'Total N
=
39, high N
=
Constant
F
P
F
3.59
5.47
0.58
0.38
0.00
0 80
0 21
,066
3.51
3.02
1.28
0.00
0.00
0 16
0 00
21, low N
=
,025
,453
.540
,989
378
648
.. ..
Testosterone
._
.-
P
F
P
.069
.091
,265
,997
,972
693
984
3.26
2.66
1.04
5.00
9.56
5 76
13 75
,080
,112
,315
,032
,004
022
001
18.
a Regression statistics refer to the covariate
only two palmar traits included in the study;
the third significant variable, COMPASYM,
is a combination of the palmar and digital
pattern intensity. Examination of the unstandardized Betas from the regression
analyses (Table 4)indicated that they were
all positive (including those that were not
significant), suggesting that for every dermatoglyphic variable (but significantly so
for the palmar variables), a higher testosterone level is predictive of greater dermatoglyphic asymmetry.
The importance of salivary testosterone
when it is considered as a categorical variable is even more clearly demonstrated: the
high and low testosterone groups have significantly different ( P < .05) dermatoglyphic
asymmetry values for five of the seven variables investigated. Furthermore, the directional effects of the differences are striking:
individuals with high testosterone levels
have higher values, for every dermatoglyphic asymmetry variable, on the left
hand, while individuals with low testosterone levels have higher values on the right
hand. These analyses emphasize the rela-
tionship of digital variable asymmetry to
testosterone level, in contrast to the regression analyses which emphasized the palmar
variables. The asymmetry of the radial ridge
count, total ridge count, and digital pattern
intensity demonstrated significance along
with the combined pattern intensity and the
palmar pattern intensity. Thus, while both
palmar and digital variable asymmetries
are significantly affected by testosterone
levels, the effect of the hormone is demonstrated in different ways for the palms and
digits. There is some overlap in significant
variables, but perhaps the differences between the dermatoglyphic regions are more
interesting, particularly in relation to the
ridge count traits. Only palmar ridge counts
were found to be significantly affected by
testosterone in the regression analyses,
while only digital ridge counts (with sole exception of the ulnar count) were found to be
significantly affected in the analyses of covariance. Perhaps for the digital traits,
which develop at a different rate than the
palmar traits (Could, 19481,the influence of
testosterone is exerted a s a threshold effect,
194
C. SORENSON JAMISON ET AL.
TABLE 7a. Means and standard deviations for
dermatoglyphic asymmetry variables i n low and high
testosterone groups, used in analyses of covariance
(age S25, N = 31)
ance indicated higher values to be on the left
hand of the high testosterone group while
the opposite was true of the low testosterone
group
may be a reflection of the greater inLow testosterone
High testosterone
fluence of testosterone upon the left side of
group
group
the body. Additional support for this suppoMean
SD
Dermatoglyphic
Mean
SD
(N = 19)
variable
(N = 12)
sition may be found in the fact that the dys~.
lexic study demonstrated there to be more
1.684
8.453
9.166
RCASYM
-5.650
1.053
15.936
13.192
UCASYM
-6.750
left hand variables which differentiated sig2.211
4.131
-0,167
2.918
ABASYM
nificantly between dyslexics and controls
DPIASYM
-1,000
0.739
0.053
1.177
1.071
1.155
0.579
PPIASYM
-0.667
than right hand variables (Sorenson Jami2.737
15.779
16.223
TDRCASYM
-12.000
son, 1988).
0.632
1.535
-1.667
1.664
COMPASYM
Hence, one interpretation of the findings
of the present study is to suggest that the
relationship between salivary testosterone
TABLE 76. Means and standard deviations for
and dermatoglyphic asymmetry is a reflecdermatoglyphic asymmetry variables i n low and high
testosterone groups, used i n analyses of covariance
tion of the much earlier effect of prenatal
(entire s a m d e . N = 39)
testosterone upon developing dermatoLow testosterone
High testosterone
glyphic variation. The present research pergroup
group
mits no precise prediction of the relationship
Mean
SD
Mean
SD
Dermatoglyphic
between levels of prenatal and secondary
(N
= 18)
(N
= 21)
variable
- .. testosterone. However, prenatal testoster1.619
8.322
-2,000
10.655
RCASYM
one levels in the male fetus appear to be
0.529
15.276
13.132
UCASYM
-10.722
ABASYM
0.222
3.422
1.905
4.146
largely the result of fetal production, which
0.000
1.140
-1,000
1.237
DPIASYM
reaches adult male levels (Winter, 1987).
1.030
0.984
0.524
PPIASYM
-0.556
While the fetus is exposed to testosterone
2.143
15.519
16.613
TDRCASYM
-12.772
0.524
1.504
1.617
COMPASYM
-1.556
from maternal sources as well, maternal levels of “free testosterone” are so much lower
than those produced fetally (Rivarola e t al.,
while for the palmar traits there is a more 1968)that any normal variation in maternal
directly linear effect of the hormone upon levels (James, 1987a,b) would appear negligible when compared to potential variation
ridge formation.
Interpreting these results is somewhat in fetal testosterone. Thus prenatal tesdifficult. The Geschwind Hypothesis (Gesch- tosterone exposure and adult levels in norwind and Galaburda, 1985) predicts that an mal men represent testicular production a t
excess of prenatal testosterone results in the different points in the life cycle.
We hypothesize that in spite of the considslowed maturation of the left side of the
erable
intra-individual variation in the sebrain, with concomitant enhancement of the
right side (and thus, abilities associated creted amounts of both prenatal and secondwith left side dominance, such a s reading, ary testosterone (due to developmental and
are impaired, while those associated with cyclical variables), there is still a within-inright side dominance, such as music and dividual relationship between the average
mathematics, are augmented). Since prena- circulating levels of the two hormones. The
tal testosterone is hypothesized to disrupt dermatoglyphic data presented in this study
the characteristic asymmetry of the brain, it support this hypothesis.
would seem to be a reasonable extension of
the Geschwind Hypothesis to suggest that it
might also disrupt developing bilateral symmetry for those additional morphological deFig. 3. Summaries of statistical relationships bevelopments that are occurring when prenatween high a n d low testosterone groups (N = 31,
tal testosterone is circulating. A listing of age < 25). a: Means. b: Sta nda rd deviations. c: 95%
such features would include dermatoglyphic Confidence levels of low group. d 95%Confidence levels
traits. The fact that the analyses of covari- of high group.
-25
-15
-10
-20
-6
0
5
.-
-12
-10
-8
-8
-4
-
RwgyM
UC48YM
ABABYM
-
I
-
LO
=
T
Gfp H u n
I
,,I
I
EB ni Qrp uAn
ASYMMETRY VARIABLES
I
DPIASYM PPUB/MTDRUBYUCOMPMYM
-
I
0.
mHIatp8D
-
-
I
-
I
L
T
T
T
d. 95% CONFIDENCE INTERVALS OF
ASYMMETRY VARIABLES IN HIGH
TESTOSTERONE GROUP
mLoQtpS0
M Y MMETRY VARIABLES
b. STANDARD DEVIATIONS OF
VARIABLES OF HI AND LO TESTOSTERONE
GROUPS
5-
n
5
10
I5
-2
*O
0
I
2
4,
a. MEANS OF ASYMMETRY
VARIABLES OF HI AND LO TESTOSTERONE
GROUPS
196
C. SORENSON JAMISON ET AL
The precise nature of the relationship between levels of prenatal testosterone and
secondary testosterone cannot yet be defined. However, our results certainly can be
viewed as adding support to such a relationship, especially when combined with the
dermatoglyphic findings of early and late
maturers (Meier et al., 1987) and dyslexia
(Sorenson Jamison, 1988, 1990; Meier,
1990, and work in progress). There is some
supportive additional research emphasizing
the proposed relationship between prenatal
and secondary hormone levels. In a recent
study with sheep, the authors reported that
the timing of postnatal neuroendocrine maturation is a function of prenatal androgen
level (Wood et al., 1991). Additionally, a n
investigation of human lateralization (Tan,
1990) led to the conclusion that cerebral lateralization is a function of both prenatal and
secondary testosterone levels.
Although the likelihood of direct evidence
of the relationship between human prenatal
and secondary testosterone being demonstrated in the near future is not great (because of the associated ethical problems),
additional indirect evidence might be gained
from testing salivary testosterone levels
from individuals identified by the Geschwind Hypothesis as having been subjected
to a n excess of prenatal testosterone. Such
groups might include, for instance, dyslexics, stutterers, left-handers, individuals suffering from autoimmune disorders or migraine headaches, individuals who are
nearsighted, and individuals gifted in rightbrain abilities such a s mathematics, music,
or art.
A direct effect of prenatal testosterone
level upon dermatoglyphic traits cannot be
definitively stated as yet. But again, the results of this study offer considerable support
for the hypothesized effect. As has been explained more fully in earlier publications
(e.g., Sorenson Jamison, 1988, 1990), a
mechanism by which prenatal testosterone
could exert a n effect on dermatoglyphic
traits might exist in the fact that the hormone serves as a stimulus for both Nerve
Growth Factor and Epidermal Growth Factor. Furthermore, testosterone is circulating
within fetuses of both sexes during the time
period of dermatoglyphic formation (Wilson
et al., 1981; Zaaijer and Price, 19711, and
additional amounts are of placental and maternal origin (Geschwind and Galaburda,
1985). The earlier research with dyslexics
does not definitely associate their significant dermatoglyphic differences from controls with levels of prenatal testosterone,
but the present results clearly demonstrate
the significant dermatoglyphic effect of that
hormone, albeit a measure of secondary
rather than prenatal testosterone.
The direction of future research appears
to be obvious: to see if a definite relationship
between levels of prenatal testosterone and
dermatoglyphic variation can be determined. Since this type of research on humans is unethical a s well as impractical, the
next best approach would be to utilize already available, cage-reared, nonhuman
primates. Such a study is presently underway using dermatoglyphic data collected
from macaques a t the University of Wisconsin Regional Primate Research Center
(Meier et al., 1992).Monkeys whose mothers
were differentially injected with testosterone a t various points during pregnancy
serve as subjects and are compared to a suitable control group of like-aged macaques
from the Regional Primate Center.
ACKNOWLEDGMENTS
The authors gratefully acknowledge the
editorial and statistical help of Paul L. Jamison. We also very much appreciate the timeconsuming contribution made by our volunteer subjects and the use of equipment and
supplies from the Reproductive Ecology Lab,
Anthropology Department, Harvard University, Peter ellison, Director. The suggestions of three anonymous reviewers were
extremely valuable. This project was supported by grants received from the Biomedical Sciences Program, Indiana University,
and The National Science Foundation.
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