Differentiation of African Components of Ancestry
to Stratify Groups in a Case–Control Study
of a Brazilian Urban Population
Vivian N. Silbiger,1,2Mario H. Hirata,1Andre D. Luchessi,1Fabiana D.V. Genvigir,1Alvaro Cerda,1Alice C.
Rodrigues,1Maria A.V. Willrich,1Simone S. Arazi,1Egidio L. Dorea,3Marcia M.S. Bernik,3Andre A. Faludi,4
Marcelo C. Bertolami,4Carla Santos,5,6A´ngel Carracedo,6Antonio Salas,6Ana Freire,6Maria Victoria Lareu,6
Christopher Phillips,6Liliana Porras-Hurtado,6Manuel Fondevila,6and Rosario D.C. Hirata1
Background: Balancing the subject composition of case and control groups to create homogenous ancestries
between each group is essential for medical association studies. Methods: We explored the applicability of single-
tube 34-plex ancestry informative markers (AIM) single nucleotide polymorphisms (SNPs) to estimate the Af-
rican Component of Ancestry (ACA) to design a future case–control association study of a Brazilian urban
sample. Results: One hundred eighty individuals (107 case group; 73 control group) self-described as white,
brown-intermediate or black were selected. The proportions of the relative contribution of a variable number of
ancestral population components were similar between case and control groups. Moreover, the case and control
groups demonstrated similar distributions for ACA <0.25 and >0.50 categories. Notably a high number of
outlier values (23 samples) were observed among individuals with ACA <0.25. These individuals presented a
high probability of Native American and East Asian ancestral components; however, no individuals originally
giving these self-described ancestries were observed in this study. Conclusions: The strategy proposed for the
assessment of ancestry and adjustment of case and control groups for an association study is an important step
for the proper construction of the study, particularly when subjects are taken from a complex urban population.
This can be achieved using a straight forward multiplexed AIM-SNPs assay of highly discriminatory ancestry
tween Europeans, Africans, and Native Americans. European-
American admixture started soon after the arrival of the
first Portuguese colonizers in 1500, followed by *3.5 million
as forced labor in gold and diamond mines or sugarcane
and coffee plantations (Pimenta et al., 2006). At the end of the
19th century immigration, mainly by Portuguese colonizers,
was expanded to four million individuals from several other
regions, especially from Italy, Spain, Germany, and Japan
(Schwingel et al., 2007).
Web site; www.ibge.gov.br/home/estatistica/populacao/
razil has one of the most heterogeneous populations in
the world, resulting from five centuries of admixture be-
censo2006), 49.8% of Brazilians described themselves by a
simple skin color designation as white; 43.2% as brown-inter-
mediate; 6.3% as black; and 0.7% as other categories, such as
Amerindian/Native American or East Asian origin. However
as a consequence of extensive admixture over the last five
centuries ethnic/racial/color categories arepoordescriptorsof
the genetic diversity among modern Brazilian populations
(Suarez-Kurtz et al., 2007a). Therefore ancestral origin repre-
(e.g., case–control)genetic association studies. The problem
arises if case and control groups have different proportions of
ancestry in addition to the phenotypes of interest such as dis-
ease risk, drug response, or drug metabolism, especially when
the phenotypes themselves differ markedly in frequency
among populations from diverse ancestral origins (Pritchard
and Rosenberg, 1999; Enoch et al., 2006).
1Faculty of Pharmaceutical Sciences, University of Sao Paulo, Sa ˜o Paulo, Brazil.
2Department of Clinical and Toxicologic Analyses, Federal University of Rio Grande do Norte, Natal, Brazil.
3University Hospital, University of Sao Paulo, Sa ˜o Paulo, Brazil.
4Institute Dante Pazzanese of Cardiology, Sa ˜o Paulo, Brazil.
5Department of Biology, University of Aveiro, Aveiro, Portugal.
6Forensic Genetics Unit, Institute of Legal Medicine, University of Santiago de Compostela, Galicia, Spain.
GENETIC TESTING AND MOLECULAR BIOMARKERS
Volume 16, Number 6, 2012
ª Mary Ann Liebert, Inc.
A Brazilian pharmacogenomics study showed that the
CYP3A5*3A allele is associated with reduced cholesterol-low-
ering response to atorvastatin in non-African individuals from
the most populous city in Brazil, Sao Paulo (South-Eastern
region) (Willrich et al., 2008). Another study suggested that the
ACE indel polymorphism is associated with hypertension, and
the APOB EcoRI single nucleotide polymorphism (SNP) is
associated with low-density lipoprotein cholesterol level in
Afro-Brazilians (Sakuma et al., 2004). However, these studies
classified the ancestral origin of individuals by self-description
of skin color, and are likely to lack precise estimates of the
ancestral composition of the case and control groups in each
Autosomal polymorphisms have emerged as valuable an-
cestry-informative markers (Price et al., 2007) due to their
stability, density of distribution, and full range of allele fre-
quency patterns among populations (Phillips et al., 2007). This
approach was recently used to evaluate the ancestral com-
ponents related with SLCO1B1 c.463C>A variants in a Bra-
zilian sample using a single-tube 34-plex assay of ancestry
informative markers (AIM), SNPs, to obtain estimates of the
African Component of Ancestry (ACA) and then classify the
population sample into quartiles. Consequently c.463C>A
SNP showed a trend for decreasing the frequency of c.463A
variant from low ACA values (<25%) to high ACA values
(<75%) (Rodrigues et al., 2011). Estimation of the ACA is
especially important in case–control association studies of
subjects from heterogeneous populations where it may be
necessary to correct for stratification within one or both study
equivalent ancestry component frequencies (Zembrzuski
et al., 2006).
Phillips and colleagues developed an efficient and practical
single-tube 34-plex AIM-SNPs assay for the assignment of
ancestral origin by selecting markers with highly contrasting
allele frequency distributions among the major population
groups: European, African, East Asian, and native Amerin-
dian (Phillips et al., 2007). We have explored the ancestral
origin and ACA classification of individuals self-declared
from Sao Paulo City using the 34-plex AIM-SNPs assay to
evaluate the relative contribution of ancestral origin in a
typical case–control association study.
Materials and Methods
Peripheral blood samples of 180 Brazilian volunteers who
are permanent inhabitants in Sao Paulo city, Brazil (BRA)
of Sao Paulo. These individuals were grouped as hyper-
cholesterolemic (case group, n=107) and normolipidemic
(control group, n=73), as previously reported (Genvigir et al.,
2008). In all cases informed consent was obtained. The
ancestry of individuals was attributed according to the self-
description of skin color, as reported by the most recent
Brazilian IBGE consensus (IBGE Web site). Anthropometric,
demographic, and clinical results of the studied group are
shown in Supplementary Table S1 in online Supplementary
Data; Supplementary Data are available online at www
.liebertonline.com/gtmb. As expected, concentrations of se-
rum lipids were higher in case than in control patients
(p<0.001), with the exception of high-density lipoprotein
cholesterol and apoAI that were not significantly different
between these two groups (Supplementary Table S1). The
apoB/apoAI in the control group was lower than in case
We used genotype data from the H971 CEPH Human
Genome Diversity Panel (HGDP-CEPH) comprising 1265 in-
dividuals from 51 geographically diverse populations using
theSPSmartSNPbrowser(http:/ /spsmart.cesga.es) totestthe
ancestral classification performance of the BRA sample. This
panel represents African (AFR), East Asian (E ASN), Euro-
pean (EUR), andAmerican populations (AME). There arealso
individuals from the Middle East and Central South Asia
(mainly N Pakistan) who are usually included with Europe-
ans in a transcontinental Eurasian meta-population (Cann
et al., 2002).
SNPs genotyping assay
a salting-out method (Salazar et al., 1998). SNPs were geno-
typed by multiplex-PCR followed by 34-plex SNaPshot?
primer extension reactions (Applied Biosystems, Foster City,
CA). Extension products were separated by capillary elec-
trophoresis (3130 Analyzer; Applied Biosystems) and POP6?
polymer. Details of the SNPlex (primers, reactions, cycling,
and extension product sizes) were described elsewhere
(Phillips et al., 2007).
Data and statistical analyses
BRA and CEPH-HGDP AIM-SNPs were simultaneously
analyzed using the estimated relative contribution of a vari-
able number of ancestral population STRUCTURE v.2.2
(Pritchard and Rosenberg, 1999) based on a maximum likeli-
hood approach to assigning group membership of unknown
samples together with reference samples of confirmed ances-
try. The multi-local genotypes were used to allocate ancestry
proportions of the sample populations in different clusters.
Runs consisted of 200,000 Markov Chain Monte Carlo steps
after a burn-in of length 200,000; analyses performed with K
varying between 2 and 6. When all individuals of CEPH-
HGDP panel were grouped together, the likelihood values
demonstrated that the population structure of the group was
explained by four distinct clusters (K=4; ln Prob= -38529.5).
Therefore this structure was used to evaluate the ancestral
component of BRA and its behavior according to the distri-
bution of references populations from CEPH-HGDP.
The ACA of the BRA sample was estimated and catego-
rized into four ancestral categories (<0.25; 0.25–0.50; 0.50–
0.75;>0.75)according tothe relativecontribution ofa variable
number of African ancestral population and compared with
the self-description of skin color (Suarez-Kurtz et al., 2007b).
Principal components analysis (PCA) was performed using
Partek Genomics Suite software v.6.3 (Partek, St. Louis, MO)
after data transformation by SNPassoc software v.1.5-3 (Gon-
zalez et al., 2007). Statistical analyses were carried out using
SPSS v.15.0 software (SPSS Inc., Madrid, Spain). The distribu-
tion of ancestral components of the contributing population
groups was evaluated by v2and t-tests. The outlier individuals
were detected by the Tukey test with the criterion for signifi-
cance set at p<0.05 throughout to ensure homogeneity
ACA TO STRATIFY GROUPS IN CASE–CONTROL STUDY 525
between case and control group according to the ancestral
Table 1 shows the membership of Brazilian and reference
populations to the distinct clusters estimated by STRUCTURE
analysis. The highest membership values were as follows:
3—AME (0.73–0.33); and cluster 4—E ASN (0.91–0.12). The
BRA sample was predominantly grouped in clusters 1 (EUR:
0.58–0.32) and 2 (AFR: 0.29–0.29). Much lower membership
contributions of the BRA sample used in this study.
The triangle plot representations of the ancestry assign-
ment probability from the 34 SNPs in the reference and study
populations are shown in Figure 1A. Brazilian ancestry as-
signment data are dispersed between African and European
extremities, with Europe the dominant ancestry component.
The PCA results shown in Supplementary Figure S1 con-
firmed that this Brazilian sample is dispersedly plotted
between EUR and AFR populations demonstrating recent
active population admixture.
Case and controls groups presented similar distributions in
EUR (cases: 0.59–0.33; controls: 0.58–0.32), AFR (cases:
0.28–0.29; controls: 0.31–0.29), AME (cases: 0.09–0.13; con-
trols: 0.06–0.08) and E ASN (cases: 0.05–0.09; controls:
0.05–0.09) ancestral clusters (Table 1). The triangular plot
representations of identified population stratification in this
case–control study are outlined in Figure 1B.
Self-categorization and ACA
In this study 62.8% of the BRA individuals self-declared as
white (n=113), 13.9% as brown-intermediate (n=25), and
18.9% as black (n=34). Eight individuals declined to describe
their skin color (4.4%), and individuals self-declared as Asian
or Amerindian/native American was not observed.
The individual ACA values across the study population
ranged from 0.003 to 0.99. ACA mean values in self-reported
white, brown-intermediate, and black subjects were, respec-
tively, 0.15–0.19, 0.40–0.15 and 0.69–0.24. The distributions
Table 1. Membership Proportions in Brazilian and Reference Populations in a Population
Structure Analysis Based on a 34 Single Nucleotide Polymorphism Plex and Using Four-Cluster Grouping
Cluster 1Cluster 2 Cluster 3 Cluster 4
Groups MeanSD MeanSDMeanSD MeanSDn
Values are presented as mean–SD. In bold the high value of distribution observed in each four-cluster grouping.
ap<0.001 comparing BRA with each reference population using t-test.
AFR, African; AME, Amerindian; E ASN, East Asian; BRA, Brazilian; EUR, European.
tification of population stratification in a case–control study: 107 cases and 73 controls, using STRUCTURE for a grouping
value of K=3. Triangle vertices represent an assignment probability of 1 and opposite sides 0. The dots represent Brazilian
samples, African (AFR), American (AME), East Asian (E ASN), and European (EUR).
(A) Triangular plot of ancestry assignment probability of BRA and CEPH-HGDP reference populations. (B) Iden-
526SILBIGER ET AL.
white BRA individuals, ACA of 0.25–0.50 was found in 0.82
brown-intermediate individuals, and ACA >0.50 was present
in 0.82 of black individuals (Table 2). The frequencies of indi-
viduals in ACA categories were similar between case and con-
trol groups (v2=4.712, 3 degrees of freedom, p=0.19) (Table 2).
The PCA plot also showed similar distribution of an-
cestral components between case and control groups, and
inside of each ACA category was observed a homogenous
distribution (Fig. 2).
The Tukey box plot (Fig. 3) was applied to compare pro-
portions of ancestral components in the BRA sample among
the ACA categories to ensure homogeneity and detect indi-
vidual outliers showing extreme values.
Cluster 2, representing mainly proportions of African an-
cestral component, did not show clearly detectable outliers
because the ACA categories were determinate for this cluster
dispersion. On the other hand, clusters 3 and 4 showed high
numbers of outlier data (18 and 24 samples, respectively) that
may result from the lower relative contribution of AME or E
ASN ancestral components when compared with those of
Africa (cluster 2) and Europe (cluster 1) in the BRA study
population. Mostly these outliers were observed in the group
of individuals with less relative contribution of African an-
The relative contribution of the European component
found in our study group of 0.58 is greater than that based on
mtDNA markers of 0.39 (Alves-Silva et al., 2000), but lower
than estimates based on Y-chromosome markers of 0.97
(Carvalho-Silva et al., 2001) and autosomal short tandem re-
peats (STRs) of 0.79 (Ferreira et al., 2006) in the Brazilian
population. The African component in our BRA sample of
0.29 is higher than the one based on STRs of 0.14 (Ferreira
et al., 2006). However significantly the degree of admixture
detected varied depending on the geographical region of
Brazil analyzed and the genetic markers used. (Alves-Silva
et al., 2000; Carvalho-Silva et al., 2001; Ferreira et al., 2006).
Our sample population revealed a small American contri-
bution (0.07), which is similar to that observed in a white
population from the State of Parana ´ (Southern region of Bra-
zil) using human leucocyte antigen polymorphisms (0.07)
(Probst et al., 2000) and in a sample population from the State
of Sa ˜o Paulo using 10 STR AIMs (0.07) (Ferreira et al., 2006). A
genome-wide study of admixed populations from different
American countries showed that frequencies of the Native
American component were significantly lower in Brazilians
(0.18) and Colombians (0.19) compared with Latino Ameri-
cans from Los Angeles (0.45) and Mexico City (0.44) (Price
et al., 2007).
reduced from two million people present at the time of the
arrival of the first European colonizers to *700,000 individ-
uals, according to the IBGE census database. Further the
distribution is uneven with the majority of Native American
populations found in the Northern and Central-West regions
Our study is the first to evaluate the East Asian component
in a Brazilian sample from Sao Paulo. The East Asian com-
ponent, as Native American component, has lower relative
contribution (0.05) than African (0.29) and European (0.58)
components. However, a few samples presented a higher
relative contribution of East Asian and American ancestry
components than the mean of the BRA sample, even though
no individuals self-described as East Asian were observed
alongside Native Americans.
It may be critical to exclude possible outliers or to create a
new subgroup of individuals with a predominant relative
contribution of East Asian and Native American ancestry
living in Sao Paulo, even though these two ancestral compo-
nents had similar relative frequencies between case and con-
trol groups in this study. It is also important to consider that it
is difficult to distinguish the ancestral origin between the
East Asian and Native American populations by 34-plex
Table 2. Relative Distribution of the Ethnic
Self-Categorization and Study Groups According
to the African Component of Ancestry
in the Brazilian Sample
Number of individuals in parenthesis.
Frequencies of ACA categories between case and control groups
were similar (w2=4.712, 3 degrees of freedom, p=0.19).
ACA, African Component of Ancestry; W, White; BI, Brown-
Intermediate; BL, Black; ND, no-declared.
nucleotide polymorphisms from the BRA case group
(n=107—octahedron) and BRA control group (n=73—
sphere) according to the ACA categories. ACA estimated by
a relative contribution of African ancestral component. ACA,
African Component of Ancestry; PCA, Principal components
Three-dimensional PCA plot of 34-plex single
ACA TO STRATIFY GROUPS IN CASE–CONTROL STUDY 527
cluster (K=4) for case and control Brazilian groups. Cluster 1, meanly proportion of European ancestral component; cluster 2,
meanly proportion of African ancestral component; cluster 3, meanly proportion of American ancestral component; cluster 4,
meanly proportion of East Asian ancestral components. The boundaries of the boxes are Tukey’s hinges. The mean value is
identified by the line inside the box. The length of the box is the inter-quartile range (IQR) computed from Tukey’s hinges.
Values higher than three IQR’s are labeled as extreme, denoted with an asterisk (*). Values higher than 1.5 IQR’s but <3 IQR’s
are labeled as outliers (B). The numbers indicate the individuals from each group.
Box plot of ACA categories by relative contribution of ancestral references populations explained by four distinct
528 SILBIGER ET AL.
AIM-SNP, because of their close genetic affinities (Phillips
et al., 2007).
The ACA categorization of our samples a better strategy to
evaluate African ancestral than self-identified color categories.
This is particularly evident in the brown-intermediate group
(ACA 0.25–0.50), which presented a high relative contribution
of ACA (0.65), an observation previously reported by other
et al., 2008) of Brazilians. The 34-plex AIM-SNPs used provide
a simple but effective means to determine the proportion of
ACA in our sample population in a statistically secure way. It
is also possible to apply the ACA values as a continuous
variable in the genetic associated study analysis, and this
would still allow the identification of outliers.
The PCA results based on ACA categories underline the
need to stratify the sample population in case–control studies
based on complex populations such as the study population
of Sao Paulo used here. Although the distribution of indi-
viduals in each ACA category was homogeneous in the case
and control groups, it is possible to segregate the data in
subgroups by ACA. Even though the proportions of ancestral
components and ACA categories were similar between case
and control groups, the outlier analysis showed a different
strategy allowed the investigation of relative component
proportions, that is, whether individuals with low African
component (ACA <0.25) showed a high proportion of the
other three ancestral components. The Tukey Box Plot suc-
cessfully detected outliers that could be used to stratify the
sample population; however our sample size is limited for
The strategy of using a highly discriminatory 34-plex AIM-
SNP panel to construct ACA categories and perform Tukey
Box plot analyses is a simple but effective approach to eval-
uate the ancestral origin and stratify case and control groups
accordingly. Although an urban population sample from Sao
Paulo city represents a challenge in terms of likely patterns of
admixture, these were efficiently analyzed to allow rebalan-
cing of the study groups when necessary.
This study was financially supported by grants from FA-
PESP (Projects 2000/12224-0 and 2003/02086-8). We thank
Claudia Villazon and Raquel de Oliveira for the excellent
support during patient selection. V.N. Silbiger, M.A.V. Will-
rich, F.D.V. Genvigir, S.S. Arazi, and A.C. Rodrigues are re-
cipients of fellowships from FAPESP, Sa ˜o Paulo, SP, Brazil. A.
Cerda is a recipient of fellowship from CONECYT, Chile.
M.H. Hirata, R.D.C. Hirata, and A.D. Luchessi are recipients
of fellowships from CNPq, Brasilia, DF, Brazil.
No competing financial interests exist.
Alves-Silva J, da Silva Santos M, Guimaraes PE, Ferreira AC,
Bandelt HJ, Pena SD, et al. (2000) The ancestry of Brazilian
mtDNA lineages. Am J Hum Genet 67:444–461.
Cann HM, de Toma C, Cazes L, Legrand MF, Morel V, Piouffre
L, et al. (2002) A human genome diversity cell line panel.
Carvalho-Silva DR, Santos FR, Rocha J, Pena SD (2001) The
phylogeography of Brazilian Y-chromosome lineages. Am J
Hum Genet 68:281–286.
Enoch MA, Shen PH, Xu K, Hodgkinson C, Goldman D (2006)
Using ancestry-informative markers to define populations and
detect population stratification. J Psychopharmacol 20:19–26.
Ferreira LB, Mendes-Junior CT, Wiezel CE, Luizon MR,
Simoes AL (2006) Genomic ancestry of a sample population
from the state of Sao Paulo, Brazil. Am J Hum Biol 18:
Genvigir FD, Soares SA, Hirata MH, Willrich MA, Arazi SS,
Rebecchi IM, et al. (2008) Effects of ABCA1 SNPs, including
the C-105T novel variant, on serum lipids of Brazilian indi-
viduals. Clin Chim Acta 389:79–86.
Gonzalez JR, Armengol L, Sole X, Guino E, Mercader JM,
Estivill X, et al. (2007) SNPassoc: an R package to per-
form whole genome association studies. Bioinformatics 23:
Phillips C, Salas A, Sanchez JJ, Fondevila M, Gomez-Tato A,
Alvarez-Dios J, et al. (2007) Inferring ancestral origin using a
single multiplex assay of ancestry-informative marker SNPs.
Forensic Sci Int Genet 1:273–280.
Pimenta JR, Zuccherato LW, Debes AA, Maselli L, Soares RP,
Moura-Neto RS, et al. (2006) Color and genomic ancestry in
Brazilians: a study with forensic microsatellites. Hum Hered
Price AL, Patterson N, Yu F, Cox DR, Waliszewska A, McDo-
nald GJ, et al. (2007) A genomewide admixture map for Latino
populations. Am J Hum Genet 80:1024–1036.
Pritchard JK, Rosenberg NA (1999) Use of unlinked genetic
markers to detect population stratification in association
studies. Am J Hum Genet 65:220–228.
Probst CM, Bompeixe EP, Pereira NF, de ODMM, Visentainer JE,
Tsuneto LT, et al. (2000) HLA polymorphism and evaluation of
European, African, and Amerindian contribution to the white
and mulatto populations from Parana, Brazil. Hum Biol
Rodrigues AC, Perin PM, Purim SG, Silbiger VN, Genvigir FD,
Willrich MA, Arazi SS, Luchessi AD, Hirata MH, Bernik MM,
Dorea EL, Santos C, Faludi AA, Bertolami MC, Salas A, Freire
A, Lareu MV, Phillips C, Porras-Hurtado L, Fondevila M,
Carracedo A, Hirata RD (2011) Pharmacogenetics of OATP
transporters reveals that SLCO1B1 c.388A >G variant is
determinant of increased atorvastatin response. Int J Mol Sci
Sakuma T, Hirata RD, Hirata MH (2004) Five polymorphisms in
gene candidates for cardiovascular disease in Afro-Brazilian
individuals. J Clin Lab Anal 18:309–316.
Salazar LA, Hirata MH, Cavalli SA, Machado MO, Hirata RD
(1998) Optimized procedure for DNA isolation from fresh and
cryopreserved clotted human blood useful in clinical molec-
ular testing. Clin Chem 44:1748–1750.
Schwingel A, Nakata Y, Ito LS, Chodzko-Zajko WJ, Shigematsu
R, Erb CT, et al. (2007) Lower HDL-cholesterol among healthy
middle-aged Japanese-Brazilians in Sao Paulo compared to
Natives and Japanese-Brazilians in Japan. Eur J Epidemiol
Suarez-Kurtz G, Perini JA, Bastos-Rodrigues L, Pena SD, Stru-
chiner C (2007a) Impact of population admixture on the dis-
tribution of the CYP3A5*3 polymorphism. Pharmacogenomics
ACA TO STRATIFY GROUPS IN CASE–CONTROL STUDY529
Suarez-Kurtz G, Vargens DD, Struchiner CJ, Bastos-Rodrigues L, Download full-text
Pena SD (2007b) Self-reported skin color, genomic ancestry
and the distribution of GST polymorphisms. Pharmacogenet
Willrich MA, Hirata MH, Genvigir FD, Arazi SS, Rebecchi IM,
Rodrigues AC, et al. (2008) CYP3A53A allele is associ-
ated with reduced lowering-lipid response to atorvastatin in
individuals with hypercholesterolemia. Clin Chim Acta 398:
Zembrzuski VM, Callegari-Jacques SM, Hutz MH (2006) Ap-
plication of an African Ancestry Index as a genomic control
approach in a Brazilian population. Ann Hum Genet 70:822–
Address correspondence to:
Vivian N. Silbiger, Ph.D.
Department of Clinical and Toxicologic Analyses
Federal University of Rio Grande do Norte
Av. General Cordeiro de Faria s/n
E-mail: email@example.com; firstname.lastname@example.org
530 SILBIGER ET AL.