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Genetic heritage of the Old Order Mennonites of southeastern Pennsylvania.

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American Journal of Medical Genetics Part C (Semin. Med. Genet.) 121C:18 – 31 (2003)
A R T I C L E
Genetic Heritage of the Old Order Mennonites of
Southeastern Pennsylvania
E.G. PUFFENBERGER*
The Old Order Mennonites of southeastern Pennsylvania are a religious isolate with origins in 16th-century
Switzerland. The Swiss Mennonites immigrated to Pennsylvania over a 50-year period in the early 18th century. The
history of this population in the United States provides insight into the increased incidence of several genetic diseases,
most notably maple syrup urine disease (MSUD), Hirschsprung disease (HSCR), and congenital nephrotic syndrome.
A comparison between the Old Order Mennonites and the Old Order Amish demonstrates the unique genetic heritage
of each group despite a common religious and geographic history. Unexpectedly, several diseases in both groups
demonstrate allelic and/or locus heterogeneity. The population genetics of the 1312T ! A BCKDHA gene mutation,
which causes classical MSUD, are presented in detail. The incidence of MSUD in the Old Order Mennonites is estimated
to be 1/358 births, yielding a corrected carrier frequency of 7.96% and a mutation allele frequency of 4.15%. Analysis
of the population demonstrates that repeated cycles of sampling effects, population bottlenecks, and subsequent
genetic drift were important in shaping the current allele frequencies. A linkage disequilibrium analysis of 1312T ! A
mutation haplotypes is provided and discussed in the context of the known genealogical history of the population.
Finally, data from microsatellite marker genotyping within the Old Order Mennonite population are provided that show
a significant but modest decrease in genetic diversity and elevated levels of background linkage disequilibrium.
ß 2003 Wiley-Liss, Inc.
KEY WORDS: Old Order Mennonite; Old Order Amish; maple syrup urine disease; founder effect; genetic drift; linkage disequilibrium
INTRODUCTION
The terms Mennonite, Amish, and especially Anabaptist as used in genetic
studies are often too broad to be meaningful. These terms denote shared
social history that does not necessarily
imply shared ancestry. The genealogical
histories of many of these Plain sects
are complex. Even within Pennsylvania, genealogical (and thus genetic)
differences exist between neighboring groups of the same religious sect.
The Clinic for Special Children, a
nonprofit pediatric metabolic disease
center, has patients from no fewer than
E.G. Puffenberger, Ph.D., is Laboratory
Director at the Clinic for Special Children,
with special interest in molecular biology and
population genetics.
*Correspondence to: E.G. Puffenberger,
Clinic for Special Children, 535 Bunker Hill
Rd., Strasburg, PA 17579. E-mail:
epuffenberger@clinicforspecialchildren.org
DOI 10.1002/ajmg.c.20003
ß 2003 Wiley-Liss, Inc.
The terms Mennonite,
Amish, and especially
Anabaptist as used in genetic
studies are often too broad to be
meaningful. These terms
denote shared social history that
does not necessarily imply
shared ancestry.
six different genetic isolates in Pennsylvania and Maryland; three are Old
Order Amish and three are Old Order
Mennonite. In some cases, these groups
have distant genealogical ties to one
another, but the proportion of shared
ancestry varies widely. This paper
will focus on the Old Order Mennonites
of southeastern Pennsylvania and
their derivative settlements in other
states, with occasional reference to the
Old Order Amish for comparative
purposes.
History of the Old
Order Mennonites of
Southeastern Pennsylvania
The Old Order Mennonites of southeastern Pennsylvania are a religious
isolate with origins in 16th-century
Switzerland. In 1525, a small group
of Protestants founded the Anabaptist
movement. A major point of contention
for these followers was the belief in adult
baptism, a practice not followed by the
Roman Catholic Church or the emerging Protestant churches. They held that
baptism should be the voluntary act of
an adult believer. In addition, they believed strongly in the separation of
church and state. These and other theological issues placed the Anabaptists in
direct conflict with both the church and
state leaders [Redekop, 1989]. In the
1640s, forced exile from Canton Zurich
and Schaffhausen resulted in the relocation of many Anabaptists to Canton
Bern and Alsace. By the 1650s, many
Anabaptists were moving into the Palatinate from Alsace and the cantons of
Switzerland. By the 1670s, refugees
ARTICLE
from Bern were joining their brethren
in the Palatinate [Davis, 1995, 1997].
Although the Palatinate provided a
certain degree of tolerance, there were
still restrictions placed upon the Anabaptists, including excessive taxes and
limitations on worship and population
size.
The Anabaptist leaders of the time
were searching for a place where they
could live and worship freely. In the late
17th century, William Penn actively
recruited Germanic peoples to immigrate to the New World. The first
Germanic settlers arrived in Germantown, Pennsylvania, in 1683. During
1707–1757, a large migration of Swiss
Mennonites took place [Redekop,
1989]. This included the ancestors of
the present-day Old Order Mennonites
of southeastern Pennsylvania.
In the early years of the Swiss Mennonite migrations, individuals settled
in the counties adjacent to Philadelphia,
especially Bucks and Montgomery
Counties. These Mennonites formed
the core population of the Franconia
Conference Mennonites. As tillable land
became more scarce, immigrants progressively began settling farther west.
The first Mennonite settlers in presentday Lancaster County (then known as
the Conestoga settlement) arrived in
1710 [Davis, 1995]. Although no specific Mennonite census records exist for
this period, it is estimated that several
hundred Mennonite families settled in
Lancaster County prior to the Revolutionary War. The Mennonite churches
of the county were organized into districts under the leadership of a single
governing body, the Lancaster Conference [Ruth, 2001]. Over the next
150 years, most growth in these communities was through reproduction, not
migration, so many of these districts
became isolated.
The late 19th century was a turbulent time in Mennonite history. Mennonite conferences in several states were
experiencing discontent among the laity.
Several issues, such as increased evangelism, missionary work, Sunday school,
English services, and higher education
were polarizing Mennonite communities. This discontent culminated in
AMERICAN JOURNAL OF MEDICAL GENETICS (SEMIN. MED. GENET.)
schisms within several Mennonite conferences. The adherents to the old ways
split away from the larger conference
bodies and formed new Old Order
conferences. This movement occurred
first in Indiana and Ohio in 1872,
followed by a schism in Ontario,
Canada, in 1889. Eventually, this movement spread to the Lancaster Conference, the largest Old Mennonite
Conference in the United States at
the time.
The schism in Lancaster County
was principally led by Bishop Jonas
Martin. The main issues were the increasing use of Sunday schools, English
singing and preaching, and the marriage
of couples who were not both members
of the church. These changes were opposed by the conservative members of
the Lancaster Conference. These troubles culminated at the fall conference
of Lancaster bishops in 1893. Bishop
Jonas Martin unambiguously expressed
his opinion of the contentious issues.
The other seven bishops conferred and
decided that Bishop Martin had been
too harsh and critical of the Lancaster
Conference. They demanded that
Bishop Martin recant, which he refused
to do. In response, the bishops revoked
his ministry and suspended his membership in the Lancaster Conference [Ruth,
2001]. Bishop Martin then established
a new Old Order group called the
Weaverland Conference.
Following this 1893 split, the new
Weaverland Conference Mennonites
enjoyed an era of peace and growth.
However, the introduction of the telephone, the automobile, and electricity
strained the fledgling conference. The
more conservative-minded members
wished to ban automobile use, but there
were an equal number who disagreed. In
1927, the Weaverland Conference officially split into the Weaverland and
Groffdale Conferences. The former permitted the use of automobiles (blackbumper1 Old Order Mennonites), and
the latter did not (horse-and-buggy Old
Order Mennonites) [Scott, 1996].
1
The term black bumper is used because the
chrome trim of automobiles was considered an
unnecessary adornment and was therefore painted
black.
19
Old Order Mennonite
Population Size and Growth
Approximately 8,000 persons of SwissSouth German Mennonite background
crossed the Atlantic from 1683–1880.
This number includes about 3,000–
5,000 Swiss Mennonites who immigrated to Pennsylvania from 1707–1756
[Redekop, 1989]. As shown in Figure 1,
a small percentage (probably several
hundred) of these immigrants settled in
Lancaster County. This provided the
first significant bottleneck for the eventual Old Order Mennonites. For nearly
150 years, the church districts grew
modestly in size, but regional genetic
isolation arose due to low migration
rates. The Lancaster Conference Mennonite population demonstrated steady
growth during the latter half of the 18th
century and the 19th century. By 1880,
the Mennonite membership in the Lancaster Conference was estimated at
3,300 [Kraybill, 1987], and in 1892,
the membership count was estimated at
6,500 [Ruth, 2001]. While neither
number is wholly accurate, it is assumed
that there were approximately 5,000
baptized members (adults) in the Lancaster Conference during this era.
The Old Order movement in Lancaster County resulted in the formation
of the Weaverland Conference in 1893.
An estimate of the number of members
who left the Lancaster Conference with
Bishop Jonas Martin can be derived from
the genealogies. By analyzing over 500
genealogies of extant members of the
Weaverland and Groffdale Old Order
Mennonites, it is estimated that about
125 families contributed most of the
genetic diversity to the Weaverland Conference, half of which is attributable to
30 nuclear families. The newly formed
conference was not a random sampling
from the larger population. Bishop
Martin and his followers were clustered
in three adjoining church districts in
northeastern Lancaster County, namely
Bowmansville, Churchtown, and Groffdale. This is significant in that many of
Bishop Martin’s followers were related
due to regional and religious isolation.
This nonrandom sampling of the Lancaster Conference resulted in another
20
AMERICAN JOURNAL OF MEDICAL GENETICS (SEMIN. MED. GENET.)
ARTICLE
Figure 1. Flow diagram depicting a brief population history of the Old Order Mennonites of southeastern Pennsylvania.
bottleneck for the Old Order Mennonite population.
As noted above, the Groffdale Conference split from the Weaverland Conference in 1927. This split was roughly
even, although exact population numbers are not known. By 1940, there were
roughly 1,078 members of the Weaverland Conference [A.B. Hoover, personal
communication]. If estimates of the
1927 split are accurate, the total adult
membership in 1940 for both conferences was about 2,160. Both conferences flourished in the 20th century.
The Weaverland Mennonites established new settlements in five other
states (Virginia, Missouri, New York,
Wisconsin, and Iowa). The Groffdale
Mennonites formed derivative settlements in Iowa, Ohio, New York,
Missouri, Wisconsin, Michigan, Indiana, and Kentucky. Based on the
Groffdale [Shirk and Shirk, 2002] and
Weaverland [Wise and Martin, 2000]
Conference directories, it is estimated
that there are 26,500 Old Order Mennonites in Lancaster County and the
distant settlements.
Many late 17th- and 18th-century
Mennonite settlements elsewhere in
the United States were established by
individuals migrating from established Mennonite settlements and Europe.
Thus, these communities must be viewed as unique genetic isolates. The Old
Order Mennonites in southeastern
Pennsylvania comprise the oldest and
largest Old Order Mennonite settlement in the country. It has been relatively immune to immigration and
emigration for nearly 250 years. However, as the population in Lancaster
County increased, families did migrate
westward. During the mid and latter
half of the 20th century, several new
settlements were established exclusively by the Weaverland and Groffdale
Mennonites. These new settlements
had little or no admixture with other
Mennonite demes. They were established in distant states (see above) and
were formed by the movement of a
large group of Old Order Mennonite
families from the Lancaster area. Due
to sampling effects and drift, these derivative settlements may experience
different frequencies of genetic disease
than the parent population.
The Old Order Mennonites of the
Weaverland and Groffdale Conferences
are themselves not a homogeneous
population. The Groffdale Conference
membership directory includes a settlement in Indiana that is genetically and/
or genealogically distinct from the rest
of the conference membership. This
settlement contains the remains of the
Ohio-Indiana Old Order Mennonites
who split from their parent conference
in 1872. Subsequently, a more conservative branch split off in 1907 under the
leadership of Bishop John W. Martin. By
1970, the Ohio groups were extinct. In
1973, the remaining Indiana members
officially merged with the Groffdale
Conference, but still remain geographically and genetically isolated from the
rest of the Groffdale Conference. There
are subpopulations of individuals derived from the Weaverland and Groffdale
Conferences, who have separated from
the larger group. One notable example
of this separation in Lancaster County
is the Reidenbach Mennonites. Owing
to disputes over the use of new technology and participation in Civilian
Public Service camps during World
War II, a conservative group of 35
individuals from the Groffdale Conference organized a separate church in
1946. In the mid-1990s, the group was
estimated to contain 300 members
[Scott, 1996].
ARTICLE
Genetic Research in
Isolated Populations
Although the history of these groups is
complex, an understanding of the structure of the population facilitates research
into genetic diseases in these groups. The
genetic mapping of disease loci within
isolated populations offers many advantages not found in outbred populations,
notably small population sizes that allow
efficient data and sample collection as
well as nearly complete ascertainment.
The genetic mapping
of disease loci within isolated
populations offers many
advantages not found
in outbred populations, notably
small population sizes
that allow efficient data
and sample collection
as well as nearly complete
ascertainment.
Large nuclear families are frequent,
which provides adequate numbers of
affected and unaffected siblings within a
sibship for sampling. Many isolates
also keep excellent historical and genealogical records. Due to their sociologic
and/or geographic isolation, there is
usually little or no migration into the
group. Finally, the members of the
group exhibit relatively homogeneous
lifestyles.
The primary genetic advantage,
however, results from the interaction of
two overlapping phenomena: the founder effect and inbreeding. The genesis of
an isolated population frequently entails
a severe reduction in size, otherwise
known as a bottleneck. Genetic drift
may increase the frequency of one or
more mutations introduced into the
population by heterozygous founders.
These phenomena, a population bottleneck accompanied by random genetic
drift, are known as the founder effect.
The founder effect is the major factor
responsible for the relatively high inci-
AMERICAN JOURNAL OF MEDICAL GENETICS (SEMIN. MED. GENET.)
dence of genetic disease in isolated
populations. This effect is exacerbated
by inbreeding, which is an unintended
consequence of genetic isolation. Many
successful mapping studies have been
performed in isolated and semi-isolated
populations throughout the world.
Some of the most well-known examples
include both religious isolates, such as
the Old Order Amish, Hutterites, and
Ashkenazi Jews [Arcos-Burgos and
Muenke, 2002], and geographic isolates,
such as the populations of Finland [de la
Chapelle and Wright, 1998; Peltonen
et al., 1999] and Iceland [Jorde et al.,
1982].
Genetic Research in the Old
Order Mennonites of
Southeastern Pennsylvania
Although the Old Order Mennonites of
southeastern Pennsylvania are not as well
known as the Old Order Amish, they
have similar population structures and
genetic disease incidences. Early studies
had identified an increased incidence
of maple syrup urine disease (MSUD)
[Marshall and DiGeorge, 1981] and
Hirschsprung disease (HSCR) [Cohen
and Gadd, 1982] in this population. The
first mutation identified in this population was the 1312T !A mutation in the
BCKDHA gene causing MSUD [Zhang
et al., 1989]. This was followed by the
mutations for HSCR [Puffenberger
et al., 1994a], glycogen storage disease
type 6 [Chang et al., 1998], and congenital nephrotic syndrome [Bolk et al.,
1999]. Over the past several years, the
Clinic for Special Children has elucidated the molecular basis of additional
metabolic disorders and conducted research to better understand the behavior
of these mutations in isolated populations such as the Plain sects of southeastern Pennsylvania.
MATERIALS AND
METHODS
Samples
All samples used for sequencing and
microsatellite marker analyses were ac-
21
quired from patients and their families
at the Clinic for Special Children. The
clinic follows 56 Mennonite MSUD
patients (44 Old Order Mennonites). In
order to perform the microsatellite
marker studies, DNA samples were
collected from 24 Old Order Mennonite
probands from 24 separate sibships. In
addition, 27 unrelated (greater than
second-degree relatives to probands)
1312T !A heterozygotes were also
genotyped. In order to set phase and
provide control (i.e., untransmitted or
U) allele frequencies, at least one parent was genotyped for all affected and
heterozygous individuals. We have ascertained several Old Order Mennonite
probands in Ontario, Canada, a settlement founded by multiple migrations
from Lancaster, Bucks, Berks, and
Montgomery Counties in Pennsylvania
[Bergey, 1992]. One affected MSUD
individual from this group was included
in our analysis.
Genealogies
Detailed genealogies for all mutation
heterozygotes and homozygotes were
prepared from private and published
family records. The initial genealogical
research was performed utilizing telephone interviews and several exhaustive family histories. Additional research
was performed at the Lancaster Mennonite Historical Society, Lancaster, PA.
All genealogical data were entered into
the MennGen database, which utilizes
the computer program Reunion 7.0
(Leister Productions, Inc.). This database was part of the effort to map the
gene(s) for HSCR in the Old Order
Mennonites [Puffenberger et al., 1994a,
1994b] and originally contained about
8,000 Old Order Mennonite individuals. The database has been expanded to include all individuals in the
latest editions of the Weaverland and
Groffdale Conference directories [Wise
and Martin, 2000; Shirk and Shirk,
2002] and the Stauffer Mennonites
[Sensenig and Sensenig, 1998] and
now contains over 90,000 individuals.
Data were exported to a HewlettPackard workstation for statistical
manipulations.
22
AMERICAN JOURNAL OF MEDICAL GENETICS (SEMIN. MED. GENET.)
ARTICLE
Genotyping
Sequencing
Genomic DNA was extracted from 13 ml of whole blood using the Puregene
DNA Isolation Kit (Gentra Systems).
Microsatellite marker loci were amplified by polymerase chain reaction (PCR)
using 30–50 ng of DNA and fluorescently labeled forward primers. Reaction
volumes were 10 ml and included 1 unit
of Taq polymerase (Qiagen), 200 mM
each of dATP, dCTP, dGTP, and dTTP,
and 1 ml of 10 incubation buffer.
Samples were amplified in a PerkinElmer 480 thermocycler for 30 cycles
(30 sec at 968C, 10 sec at 558C, 30 sec at
728C), followed by an 8-min incubation
at 728C. Genotypes were determined
using an ABI 310 Genetic Analyzer and
the GeneScan software package. Allele
sizes were determined from Centre
d’Etudes du Polymorphisme Humaine
(CEPH) control individual 1347-02
(when genotype known) and GeneScan-500 DNA size standards.
Mutation analysis was performed for the
following candidate genes: ACADM,
HPD, HSD3B2, MTHFR, MVK, PAH,
PCCB, SLC3A1, SLC7A9, and TJP2.
Targeted mutation detection was performed for all other mutations listed in
Tables I and II. The exons of the target
genes were amplified by PCR using
specific oligonucleotide primers and
30–50 ng of genomic DNA. Reaction
volumes were 25 ml and included 1 unit
of Taq polymerase (Qiagen), 200 mM
each of dATP, dCTP, dGTP, and dTTP,
and 2.5 ml of 10 incubation buffer.
Samples were amplified in a PerkinElmer 480 thermocycler for 30 cycles
(30 sec at 968C, 10 sec at 608C, 30 sec at
728C) followed by an 8-min incubation
at 728C. The PCR products were then
sequenced using a fluorescence-based
cycle sequencing protocol (BigDye
Terminator, Applied Biosystems). The
extension products were subsequently
size-fractionated on an ABI 310 Genetic
Analyzer. The sample sequence was
compared to the normal mRNA and
genomic sequence for each gene from
GenBank in order to identify sequence
variants. For this analysis, exonic sequence (from the initiator codon to
the termination codon) as well as the
splice donor, splice acceptor, and branch
point sites were screened for mutations.
These analyses did not screen for mutations in the promoter region, the 30
untranslated region, or the introns of
these genes (except as described above).
Assessment of
Linkage Disequilibrium
In this inbred Mennonite pedigree, it is
difficult to accurately assess the control
allele frequencies for the population, and
the allele frequencies in Genome Database (GDB) (http://www.gdb.org/)
may not be applicable. The presumably
TABLE I. Molecular Lesions Identified in the Old Order Mennonites of Southeastern PA
Disease
Congenital nephrotic syndrome
Cystinuria
Crigler-Najjar syndrome
Fragile X syndrome
Glycogen storage disease, type 6
Hirschsprung disease
Maple syrup urine disease
Medium chain dehydrogenase
deficiency
Mevalonate kinase deficiency
Phenylketonuria
Propionic acidemia
Spinal muscular atrophy
Tyrosinemia, type 3
3-methylcrotonylglycinuria
a
Gene
Mutation
Mutation reference
ID in Mennonitesa
NPHS1
NPHS1
SLC3A1
SLC3A1
SLC7A9
SLC7A9
UGT1A1
FMR1
PYGL
EDNRB
BCKDHA
ACADM
1481delC
3250delG
IVS6 þ 2T ! C
1354C ! T
200C ! T
1166C ! T
222C ! A
(CGG)n expansion
IVS13 þ 1G ! A
828G ! T
1312T !A
985A ! G
Bolk et al. [1999]
Bolk et al. [1999]
Novel mutation
Endsley et al. [1997]
Putative mutation?
Novel mutation
Kadakol et al. [2000]
Fu et al. [1991]
Chang et al. [1998]
Puffenberger et al. [1994a]
Zhang et al. [1989]
Matsubara et al. [1990]
Sameb
Sameb
Clinic for Special Children
Clinic for Special Children
Clinic for Special Children
Clinic for Special Children
Clinic for Special Children
Clinic for Special Children
Sameb
Same
Same
Clinic for Special Children
ACADM
MVK
MVK
PAH
PAH
PCCB
SMN1
HPD
MCCB
IVS4-30A ! G
803T ! C
1174G ! A
782G ! A
IVS10-11G ! A
1606A ! G
exon 7 deletion
85G ! A
518insT
Novel mutation
Hinson et al. [1999]
Novel mutation
Abadie et al. [1989]
Dworniczak et al. [1991]
Gravel et al. [1994]
Lefebvre et al. [1995]
Novel mutation
Baumgartner et al. [2001]
Clinic for Special Children
Sameb
Clinic for Special Children
Clinic for Special Children
Clinic for Special Children
Clinic for Special Children
Clinic for Special Children
Clinic for Special Children
Sameb
Mutation identification and/or verification in the Old Order Mennonites of southeastern Pennsylvania.
Collaborative study with the Clinic for Special Children, Strasburg, PA.
b
ARTICLE
AMERICAN JOURNAL OF MEDICAL GENETICS (SEMIN. MED. GENET.)
23
TABLE II. Molecular Lesions Identified in Old Order Amish Demes of Pennsylvania
Disease
Aldosterone deficiency
Amish microcephaly
Byler diseasec
Cartilage-hair hypoplasia
Crigler-Najjar syndrome
Ellis-van Creveld syndrome
Familial hypercholanemia
Galactosemiad
Gutaric aciduria, type 1
Homocystinuria
McKusick-Kauffman syndrome
Nemaline rod myopathy
Osteogenesis imperfecta
Phenylketonuria
Propionic acidemiae
Pyruvate kinase deficiencye
Sitosterolemia
3-ß-OH-steroid dehydrogenase
deficiency
3-methylcrotonylglycinuria
Gene
Mutation
ID in Amisha
Mutation reference
CYP11B2
SLC25A19
ATP8B1
RMRP
UGT1A1
EVC
TJP2
BAAT
GALT
GCDH
MTHFR
MKKS
TNNT1
COL1A2
PAH
PAH
PCCB
PKLR
ABCG8
HSD3B2
5 bp deletion
530G ! C
923G ! T
70A ! G
222C ! A
IVS13 þ 5G ! T
143T ! C
226A ! G
563A ! G
1262C ! T
1129C ! T
[250C ! T þ 724G ! T]
505G ! T
2098G ! T
280-282delATC
782G ! A
1606A ! G
1436G ! A
1720G ! A
35G ! A
Mitsuuchi et al. [1993]
Rosenberg et al. [2002]
Bull et al. [1998]
Ridanpaa et al. [2001]
Kadakol et al. [2000]
Ruiz-Perez et al. [2000]
Carlton et al. [2003]
Carlton et al. [2003]
Reichardt et al. [1991]
Biery et al. [1996]
Goyette et al. [1996]
Stone et al. [2000]
Johnston et al. [2000]
McBride et al. [2002]
Caillaud et al. [1991]
Abadie et al. [1989]
Gravel et al. [1994]
Kanno et al. [1994]
Berge et al. [2000]
Novel mutation
Sameb
Sameb
Sameb
Clinic for
Clinic for
Same
Sameb
Sameb
NeoGen
Sameb
Clinic for
Same
Sameb
Same
Clinic for
Clinic for
Clinic for
Same
Same
Clinic for
MCCB
295G ! C
Baumgartner et al. [2001]
Sameb
Special Children
Special Children
Special Children
Special Children
Special Children
Special Children
Special Children
a
Mutation identification and/or verification in Old Order Amish demes of Pennsylvania.
Collaborative study with the Clinic for Special Children, Strasburg, PA.
c
Patients identified in the Old Order Amish of Lancaster County, PA and the Old Order Amish of Mifflin and Juniata Counties, PA.
d
No mutation homozygotes identified yet.
e
Patients identified in the Old Order Amish of Mifflin and Juniata Counties, PA.
b
normal, untransmitted parental chromosomes were used as controls. To test for
linkage disequilibrium arising from
descent from a common ancestor, we
determined whether marker alleles had a
higher frequency on mutant gene-bearing (transmitted, T) chromosomes vs.
normal (untransmitted, U) parental
chromosomes. A 2 2 contingency X2
statistic was employed to test the null
hypothesis of equal allele frequency on T
and U chromosomes for each allele at a
marker, as previously described (Puffenberger et al., 1994a, 1994b). For estimating the average number of ancestral
recombinants (y) between a mutation
and marker locus, we assume that marker
haplotypes evolve by recombination. If
the frequency of the associated allele
(AA) is y on mutant (T) chromosomes
and x on normal (U) chromosomes, and
a is the proportion of mutant chromo-
somes attributable to a specific mutation,
then
y ¼ x þ að1xÞey
The average number (y) is estimated
from this equation by using the estimated values of y and x and assuming
homogeneity (all mutations at a locus of
single origin, a ¼ 1); conversely, for
tight linkage (y ¼ 0), a can be estimated.
The number of generations from the
common founder (g) was estimated using
a modified version of the previous
formula:
y ¼ x þ að1xÞð1yÞg
The recombination fraction (y)
for the estimation of g was based on
the Marshfield integrated genetic map
of chromosome 19 (http://research.
marshfieldclinic.org/genetics/). Estimates of the distance from the mutation
(in megabases, Mb) for each marker were
derived from contig physical maps at
National Center for Biotechnology
Information (NCBI) (http://www.ncbi.
nlm.nih.gov/) and the University of
California, Santa Cruz (UCSC) Genome Builds (http://genome.ucsc.edu/).
In addition to allele frequency data,
haplotypes were constructed and haplotype frequencies were compared
between affected individuals and untransmitted haplotypes from their parents. The association tests for allele and
haplotype frequency distortions were
performed on genotype data from either
one homozygote or one heterozygote
per nuclear family. In multicase families,
only one affected individual was utilized
in the enumeration of alleles and haplotypes. This procedure was implemented
to avoid allele and haplotype frequency
inflation. All allele and haplotype
24
AMERICAN JOURNAL OF MEDICAL GENETICS (SEMIN. MED. GENET.)
analyses were performed on a Power
Macintosh G3 using the custom
program MacAllele (developed by
Kashuk, Puffenberger, and Chakravarti,
1994).
RESULTS AND DISCUSSION
Molecular Lesions in the Old
Order Mennonites of
Southeastern Pennsylvania
As described elsewhere in this issue, the
Clinic for Special Children has been
serving the Old Order Amish and Old
Order Mennonite communities since
1989. Recently, the clinic has developed
a program to identify mutations segregating in these populations for use in
diagnostic and carrier testing. Collaborative efforts between the clinic and
other researchers have led to the identification of 12 mutations segregating in
these two isolated populations [Biery
et al., 1996; Bull et al., 1998; Chang et al.,
1998; Bolk et al., 1999; Hinson et al.,
1999; Johnston et al., 2000; Baumgartner et al., 2001; Rosenberg et al., 2002;
Carlton et al., 2003]. In addition, the
clinic has independently identified 7
novel mutations and 20 previously
published mutations in 20 additional
disorders found in the Plain sects of
Pennsylvania (Tables I and II).
It is commonly assumed that small
genetic isolates have little or no mutation
heterogeneity. Due to the founder effect,
a single mutation is postulated to segregate in the population and account
for the increased incidence of disease.
As Tables I and II demonstrate, molecular data show that this may not be
correct. Five of 14 disorders in the
Old Order Mennonites show mutation heterogeneity (Table I). This is
Five of 14 disorders in the
Old Order Mennonites
show mutation heterogeneity.
most striking for cystinuria, where allelic
and locus heterogeneity has been identified by sequencing the SLC3A1 and
SLC7A9 genes in five patients. In the
Old Order Amish, two disorders
demonstrate mutation heterogeneity,
one of which also demonstrates locus
heterogeneity. The assumption of mutation homogeneity can hinder mapping
studies of disease loci. While attempting
to identify the gene for HSCR among
the Old Order Mennonites, we identified a cluster of HSCR cases in an
associated Mennonite settlement in
Ontario, Canada [Puffenberger et al.,
1994a]. This group, the MarkhamWaterloo Conference Mennonites, was
formed by multiple migrations from
Lancaster, Montgomery, and Bucks
Counties, Pennsylvania, during the early
19th century. We surmised that the
gene(s) for HSCR would be the same
in both groups owing to shared ancestry.
However, upon identification of the
causative mutation, it was found that
the Canadian patients did not harbor the
same mutation as the Weaverland and
Groffdale Mennonites. Genealogical
analysis of this Canadian group shows
that the genetic contribution from the
Lancaster Mennonites was about 40%.
The molecular basis of four genetic
diseases that occur in both Old Order
Amish and Old Order Mennonites has
been elucidated. Prior to identification
of the causative mutation, it was widely
believed that these disorders would have
a common origin in the two populations.
This was based on the knowledge that
the Old Order Amish were a splinter
group from the Swiss Mennonites and
shared some ancestors with the Old
Order Mennonites. This was partially
correct as Crigler-Najjar syndrome and
propionic acidemia are caused by the
same mutation in both populations.
In contrast, 3-methylcrotonylglycinuria
involves a different mutation for each
group. Finally, phenylketonuria is common to both groups with one shared
mutation and two population-specific
mutations.
The identification of causative mutations in these populations does not
imply that the mutation is in high frequency. Most of the early mapping
studies focused on disorders that demonstrated a high incidence in these populations. In recent years, the Clinic for
Special Children has attempted to define
ARTICLE
the molecular bases of disease in these
populations regardless of the frequency.
Thus, some mutations are represented
by a single patient, as is the case for
tyrosinemia type 3. Pennsylvania state
newborn screening identified the patient, who subsequently was seen at our
clinic at 26 days of age. Amino acid
analysis confirmed the diagnosis of tyrosinemia, although the biochemical and
clinical phenotype was inconsistent with
type 1 or type 2 disease. By sequencing
genomic DNA, the patient was found
to be homozygous for a novel mutation
in the HPD gene. The identification of
these mutations regardless of their frequency permits the effective use of diagnostic molecular genetic testing in these
populations. For several of these disorders, the differential diagnosis is large,
requiring expensive testing and sometimes hospitalization. The ability to accurately diagnose the patient in a timely
manner is invaluable for preventing the
devastating effects of metabolic disease.
Population Genetics of MSUD
MSUD was the first published disease
phenotype reported in the Old Order
Mennonites of southeastern Pennsylvania [Marshall and DiGeorge, 1981].
Eight years later, the causative mutation,
1312T !A, was identified [Zhang et al.,
1989]. The unique features of the Old
Order Mennonite population, the high
disease incidence, and the extensive
carrier testing performed at the Clinic
for Special Children afforded the opportunity to study the population genetics
of the mutation in detail.
Although disease incidence and
mutation allele frequency are correlated,
the mechanism(s) by which mutation
frequencies change may be obscure.
Figure 2 presents a flowchart of the
MSUD mutation allele frequency in
the parental Swiss-German population,
the founding Mennonite population,
and the extant Old Order Mennonite
population. As the first panel demonstrates, the estimated incidence of MSUD
in the general population is 1/200,000
births, yielding a heterozygote frequency of roughly 1/225 and a mutation
allele frequency of 0.22%.
ARTICLE
AMERICAN JOURNAL OF MEDICAL GENETICS (SEMIN. MED. GENET.)
Figure 2. Flow diagram depicting historical phenomena that influenced the
1312T !A mutation allele frequency in the Old Order Mennonites of southeastern
Pennsylvania.
It is hypothesized that two related
events affected the MSUD mutation
allele frequency in the fledgling Lancaster Mennonite settlement. First, a
random sampling effect increased the
mutation allele frequency relative to
the parental population. This occurred
through the introduction of a single, rare
mutation by a heterozygous ancestor
into the small founder group. Second,
the sampling effect dramatically decreased mutation heterogeneity such that
only one MSUD mutation (1312T !A)
was found in the derivative group.
It is widely believed that the phenomenon with the greatest effect on the
mutation allele frequency in small genetic isolates is the founder effect. The
effects of genetic drift are most dramatic
when the population is small. As the
population size increases, the ability of
genetic drift to affect mutation allele
frequency diminishes. Thus, the first few
generations of Mennonites in Lancaster
County likely experienced the greatest
changes in mutation allele frequency.
Importantly, the Old Order Mennonite
population has experienced several significant bottlenecks in the past 300 years
(Fig. 1). Thus, repeated cycles of sampling effects, population bottlenecks,
and subsequent genetic drift were undoubtedly important in shaping the
current allele frequencies within the
population.
Incidence of MSUD
The Clinic for Special Children undertook an effort to update and confirm the
reported incidence of MSUD in the
Old Order Mennonites for the period
25
1985–1994. During this 10-year interval, there were 6,810 total Old Order
Mennonite births. Among this cohort,
there were 19 MSUD children born.
This yielded an incidence of 19/6,810
(0.28%), or 1/358. Interestingly, the
incidence of MSUD in the two conferences differs. Of the 19 MSUD children
enumerated above, 15 were Groffdale
Mennonites and 4 were Weaverland
Mennonites. This yields conferencespecific MSUD incidence rates of 1/
271 and 1/686, respectively.
These estimates were calculated
from the birth records for the entire
Weaverland and Groffdale Conference
populations. There were seven additional cases of MSUD in Mennonite
children during this period, but they
were excluded because their families
belong to Mennonite conferences where
population size, birth rates, and admixture are unknown. In some derivative
Weaverland and Groffdale settlements,
the incidence may be higher or lower
based on sampling effects and genetic
drift. An example is the Missouri settlements, where the incidence was 4/603
births or 0.66% [Love-Gregory et al.,
2002].
This population-based estimate is
less than a previous calculation by a
factor of two [Marshall and DiGeorge,
1981]. However, this earlier calculation
was performed before conference directories were available, thus making it
difficult to assess the total population size
or the birth rate. It is also probable that
some Mennonite patients were enumerated whose families are not, or never
have been, members of the Old Order
churches. We are aware of at least 16
additional Mennonite MSUD patients
whose families are not affiliated with the
Old Order Mennonite churches.
Allelic and Genotypic Frequencies
of the 1312T !A Mutation
By using the Hardy-Weinberg equilibrium and the incidence estimate, we
can calculate the mutation and carrier
frequency in this population. The mutation allele frequency in this population
(q) is estimated from the square root of
the incidence (q2). Thus, the 1312T !A
26
AMERICAN JOURNAL OF MEDICAL GENETICS (SEMIN. MED. GENET.)
allele frequency is approximately 5.28%.
The heterozygote (i.e., carrier) frequency is then easily calculated as
2(1q)(q), which yields an estimate of
10.01%.
This estimate of the heterozygote
frequency assumes random mating and
no inbreeding within the population.
However, pedigree analysis of Old
Order Mennonite families clearly demonstrates significant levels of inbreeding. The principal consequence of
inbreeding within a population is to
increase the proportion of homozygous
genotypes and reduce the fraction of
heterozygous genotypes. Thus, the heterozygote frequency within an inbred
population will be lower than the
heterozygote frequency in a population
with the same disease incidence, but
no inbreeding. Thus, the previous calculation of the 1312T !A heterozygote frequency is undoubtedly an
overestimate.
Based on the MSUD incidence and
the average inbreeding coefficient for
MSUD families, a more precise estimate
of the 1312T !A heterozygote frequency in the Old Order Mennonites
can be derived. Genotype frequencies in
the presence of inbreeding [Wright,
1921] were calculated based on the
formulas in Table III. Although a
population-wide average inbreeding
coefficient has not been calculated for
the Old Order Mennonites, inbreeding coefficients were calculated for all
Old Order Mennonite MSUD sibships.
The average inbreeding coefficient was
2.19%.
Although a population-wide
average inbreeding
coefficient has not been
calculated for the Old Order
Mennonites, inbreeding
coefficients were calculated for
all Old Order Mennonite
MSUD sibships. The average
inbreeding coefficient
was 2.19%.
ARTICLE
TABLE III. Effect of Inbreeding (F) on the 1312T !A Mutation
Frequency Estimate
F¼0
Mutation homozygotes
Mutation heterozygotes
Wild-type homozygotes
Mutation allele frequency
2
q
2pq
2
ppffiffiffiffiffi
q2
0.28%
10.01%
89.71%
5.28%
F ¼ 2.19%
2
q (1F) þ qF
2pq (1F)
2
p
(1F) þ pF ffi
pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
q2 ð1FÞ þ qF
0.28%
7.96%
91.87%
4.15%
For the period 1985–1994, there were 19 Old Order Mennonite children born with
maple syrup urine disease. The total number of Old Order Mennonite births for this same
period was 6810; thus, the incidence of MSUD was 19/6810 ¼ 0.2790% (or roughly 1/
358 births).
This inbreeding coefficient is a reasonable approximation for the Old
Order Mennonite population as a whole.
By using this approximation of inbreeding, the corrected population heterozygote frequency was 7.96%.
Genetic Drift Analogy:
Surname Frequency Distribution
Table III presents an example of random
genetic drift in the Old Order Mennonite population. A surname frequency
distribution was assembled using the two
conference directories. The most common surname in both conferences is
Martin, comprising 20% of Old Order
Mennonite households. There is no
known selective advantage to carrying
this surname, but its frequency has risen
from about 1–2% in the early 18th
century. The surname distribution further illustrates the differential effects of
random genetic drift in the two conferences. The second most common
surname, Zimmerman, demonstrates a
striking frequency difference between
the two conferences. This difference
may have occurred through random
genetic drift, nonrandom segregation
of the surname during the 1927 split, or a
combination of the two factors. The
distribution of several genetic diseases
within the two conferences demonstrates this phenomenon as well. In
addition to MSUD, the incidence of
congenital nephrotic syndrome is decidedly unequal between the two conferences. The incidence in the Groffdale
Mennonites is roughly 1/500 [Bolk
et al., 1999]. To date, only one affected
child has been born in the Weaverland
Mennonites. Although separated for
only three generations and similar genealogically, random sampling and genetic
drift have operated differently in each
subpopulation. These data show that the
incidence of a trait (i.e., surname) may
increase in the absence of inbreeding
(Table IV). However, within natural
populations, random genetic drift and
inbreeding are overlapping phenomena
that act together to cause the increased
disease incidence in genetic isolates.
Random genetic drift may lead to
an increased mutation allele frequency
within a population, as shown for
MSUD in the Old Order Mennonites;
conversely, it is equally probable for
an allele to decrease in frequency or
become extinct. Within the Old Order
Mennonites, no cases of cystic fibrosis
(CF) have ever been reported. In a
population of 27,000, we would
expect to find roughly 11 CF patients
based on an incidence of 1/2,500 births.
There are three possible explanations
for this deficiency: 1) mutations in
CFTR may never have been introduced into the population, 2) genetic drift
has resulted in the extinction of any
CFTR mutations, or 3) the frequency
of CFTR mutations is so low that
affected individuals have not been
ascertained.
Genealogical Analysis of
the 1312T !A Mutation
The MennGen genealogical database
(see Materials and Methods) was used
ARTICLE
AMERICAN JOURNAL OF MEDICAL GENETICS (SEMIN. MED. GENET.)
TABLE IV. Surname Distribution in the Weaverland and Groffdale
Conference Mennonites
Surname
Total
Weaverland
Groffdale
Martin
Zimmerman
Hoover
Nolt
Weaver
19.6%
14.1%
7.1%
6.0%
5.9%
20.0%
9.5%
5.8%
4.8%
6.7%
19.3%
17.8%
8.0%
7.0%
5.2%
The top five surnames account for 52.7% of households. There were 92 additional
surnames with frequencies <5.0%. Totals were based on head-of-household counts from
the Weaverland [Wise and Martin, 2000] and Groffdale [Shirk and Shirk, 2002]
Conference Directories.
to perform pedigree analysis of 366
Mennonite 1312T !A heterozygotes
to identify the putative common ancestor. Two ancestral couples were identified: Abraham Herr (1672–1725) and
his wife, Anna Bear, and Hans Groff
(1661–1746) and his wife, Susanna
Kendig. Assuming a single origin for
the mutation in this population, one of
these four individuals was the original
carrier of the 1312T !A mutation. It is
remarkable that analysis of 366 separate
pedigrees does not allow conclusive
identification of the common ancestor
for the MSUD mutation. This underscores the interrelatedness of extant Old
Order Mennonites.
Linkage Disequilibrium Analysis
of the 1312T !A Mutation
Most genetic mapping studies rely on
linkage analysis to localize the altered
gene. This parametric approach is particularly useful when mapping rare diseases in unrelated, outbred families.
Since mutation heterogeneity is nearly
certain, this method is preferred. It provides the ability to analyze cosegregation
of marker alleles with the phenotype
within sibships and calculate a test statistic based on the cumulative contribution
of each family. In isolated populations,
an alternative method is linkage disequilibrium analysis. This nonparametric
technique involves the assessment of
association between a phenotype and
alleles or haplotypes at genetic marker
loci. Association analysis detects those
genomic regions that are identical by
descent in affected individuals due to
common ancestry and is ideally suited
to mapping studies in genetic isolates.
It is also technically and computationally
simpler than linkage analysis. Ironically,
the merits of linkage disequilibrium analysis have been touted for years, yet only
two published mapping studies performed in the Old Order Amish and
Old Order Mennonite populations from
Lancaster County have utilized this
technique [Puffenberger et al., 1994a,
1994b; Carlton et al., 1995].
Linkage disequilibrium analysis can
also provide information about the
behavior of mutations within populations. It can be used to examine the
age of mutations within a population,
the evolution of haplotypes, and the
segregation of those haplotypes in the
population. The haplotypes provide a
historical record of recombinational
events and thus provide interesting data
on population age and structure. In
order to examine these issues, a study
of linkage disequilibrium surrounding the 1312T !A mutation in the
Old Order Mennonite population was
performed.
Twelve microsatellite markers flanking the BCKDHA locus on human
chromosome 19q13 were chosen for
their proximity to the gene and heterozygosity values. Twenty-six separate
mutation homozygotes and 25 heterozygotes were genotyped. When avail-
27
able, one or more parents were also
genotyped in order to set phase and
provide necessary population-specific
allele frequencies. Multiple sampling of
nearly identical haplotypes was minimized by analyzing one 1312T !A
haplotype per sibship (n ¼ 51). The total
number of independent haplotypes
sampled was 77. While none of the
haplotypes were truly independent due
to identity by descent for the 1312T !A
mutation, samples were excluded from
analysis when a first- or second-degree
relative of the proband or their parents
was already present in the genotyping
panel. A recent analysis determined the
frequency of alleles for 5 microsatellite
markers on 46 Old Order Mennonite
and 10 non-Mennonite 1312T !A
haplotpyes [Love-Gregory et al.,
2002]. Unfortunately, these data suffer
from multiple sampling, predominantly from only four sibships, of identical
or nearly identical haplotypes. Thus,
those allele or haplotype frequencies
could not be used for this study of linkage disequilibrium.
To analyze linkage disequilibrium,
it was determined whether alleles on the
transmitted, mutation-bearing haplotypes (T) were present at higher frequency than on presumably normal,
untransmitted haplotypes (U) in the
parents, as previously described [Puffenberger et al., 1994a, 1994b]. A Chisquare test was employed to test the null
hypothesis of equal allele frequencies on
T and U chromosomes for each allele at
the microsatellite marker locus.
The associated allele (AA) at each
marker locus is presented with the
corresponding frequency on T and U
chromosomes (Table V). As expected,
the markers physically closest to the
BCKDHA gene demonstrated the
greatest association, and D19S198 was
the only locus where no recombinants
were detected. This marker locus is
physically the closest to the 1312T !A
mutation, roughly 426 kb distal to
BCKDHA. Although no recombinants
were detected with the 145-bp allele
at this locus on 77 mutant haplotypes,
that allele is the most common allele
in control chromosomes as well. Thus,
historical recombinational events may
28
AMERICAN JOURNAL OF MEDICAL GENETICS (SEMIN. MED. GENET.)
ARTICLE
TABLE V. Association of Chromosome 19q13 Markers and the BCKDHA 1312T !A Mutation on Old Order
Mennonite Haplotypes
Marker
D19S431
D19S248
D19S713
D19S421
D19S718
D19S223
D19S400
1312T !A
D19S198
D19S420
D19S178
APOC2
D19S246
AA (bp)
T%
U%
T(n)
U(n)
X2
y
Mb
g
cM
g
292
129
218
187
368
233
188
A
145
261
152
147
231
82
62
72
88
94
95
93
100
100
99
77
74
61
52
3
16
56
16
0
3
0
34
31
7
15
36
76
71
74
73
72
73
76
77
77
67
74
70
36
80
69
80
71
76
77
78
82
80
64
76
68
14
14.8
55.4
48.1
17.6
92.1
134.8
127.5
159.0
77.0
65.7
77.7
49.5
2.6
0.491
0.497
0.219
0.332
0.068
0.056
0.070
0.000
0.000
0.022
0.278
0.359
0.929
9.60
7.95
4.14
3.06
0.55
0.51
0.38
0
0.25
1.91
2.51
3.55
8.94
4.9
6.0
5.2
10.7
12.5
11.0
18.5
0.0
0.0
1.1
10.9
9.9
9.9
10.66
6.65
2.24
3.22
1.33
1.18
0.64
0
0.43
0.96
2.74
4.16
12.74
4.4
7.2
9.7
10.1
5.1
4.7
10.8
0.0
0.0
2.3
10.0
8.5
6.8
have occurred, but these events had a
33.8% chance of replacing the 145-bp
allele with another 145-bp allele.
The data demonstrate the recombinational decay of the ancestral haplotype.
As distance from the mutation increases,
association with a particular allele at each
marker locus decreases. However, the
size of the region that demonstrates
statistically significant linkage disequilibrium is large, spanning roughly 14.8 cM
around the 1312T !A mutation. A
prior study of HSCR in the Old Order
Mennonites identified a similarly sized
region of 12.9 cM on chromosome 13
[Puffenberger et al., 1994a]. Allelic
associations were detected over large
genomic regions because the Old Order
Mennonite population is relatively
young. The extant population can trace
their genealogies back to a small group
of founding families roughly 10–12
generations ago. If this population
were older (e.g., 50 generations), the
shared region would be considerably
smaller.
The microsatellite marker data provide a related insight into allelic associations (Table V). The greatest statistical
significance occurs when the AA is in
high frequency on transmitted haplotypes (T) and low frequency on untransmitted haplotypes (U). The most
extreme example of this phenomenon
is the mutation itself, where the fre-
quency is 100% on T chromosomes (by
definition) and 0% on U chromosomes.
The microstallite marker D19S223 is
remarkable in that the associated 233-bp
allele is found on 94.5% of T chromosomes, but was not detected on any
U chromosomes. A similar association
between this microsatellite marker and
1312T !A mutation haplotypes was
shown previously [Love-Gregory et al.,
2002].
These data allow us to calculate the
average number of recombinational
events (y) that have occurred between
the mutation and the marker locus since
the introduction of the mutation into the
population. This estimate is based on
the frequency of the AA on T and
U chromosomes (see Materials and
Methods). This calculation estimates
the average number of recombinational
events that likely occurred to produce
the allele frequency distribution observed on T and U chromosomes. It
accounts for the fact that the identical
allele might occasionally be transferred
through recombination onto the haplotype. This occurs with a frequency equal
to the allele frequency on U chromosomes. This estimation of q provides a
relative measure of the distance between
the genetic marker and the mutation. A
close examination of the data in Table V
shows a discrepancy between the orders
of the markers. The physical map places
D19S713 proximal to D19S421, while
the genetic map has the order reversed.
The estimation of y is in agreement with
that of the genetic map.
When the allele frequencies for T
and U chromosomes as well as the
distance from the mutation are known,
the average number of generations back
to the common ancestor can be calculated. This calculation was performed
using the T and U AA frequencies and
the distance between the marker and the
mutation. This was calculated for both
physical distance (Mb) and genetic
distance (cM). Using the physical distances (Mb), the estimation of g for each
locus yields an average of 9.2 generations for all nonzero g values. The same
estimate using the genetic distances (cM)
yields a generation time of 7.2. These
estimates are slightly low, but are not
inconsistent with the known population
history. This low estimate probably arose
due to the occurrence of a bottleneck
since the founding of the Mennonite
settlement in Lancaster County. The
1893 Old Order schism likely reduced
the diversity of recombinant 1312T !A
mutation-bearing haplotypes in the
derivative Old Order population. This
sampling effect would provide an underestimate of the generation time to the
common ancestor since some rare recombinants would not be found in the
splinter group.
ARTICLE
The 1312T !A Mutation in
Non-Old Order Mennonite MSUD
The Clinic for Special Children has been
performing MSUD mutation identification as a clinical service for several years.
We have sequenced the BCKDHA,
BCKDHB, and/or DBT genes in 22
MSUD patients and have identified the
causative mutation on 43 of 44 alleles.
We have found two patients who were
heterozygous for the 1312T !A mutation in BCKDHA on chromosome
19q13. This yields a 1312T !A allele
frequency of 4.5% for non-Old Order
Mennonite MSUD (2/44).
In these two 1312T !A heterozygotes, we confirmed a common origin
for the 1312T !A mutation. By direct
sequencing of the BCKDHA gene,
we identified and analyzed 19 intragenic single nucleotide polymorphisms
(SNPs). These SNPs revealed identical
intragenic haplotypes for the 1312T !A
mutation in homozygous Old Order
Mennonite patients and the two heterozygous non-Mennonite patients (data
not shown). In order to estimate the
generation time from the common
ancestor for the 1312T !A mutation
for non-Old Order Mennonite patients,
we calculated g using our two patients
and the eight probands from the article
by Love-Gregory et al. [2002]. The
estimate of g is based on only two
microsatellite markers that were genotyped in both data sets, D19S223 and
D19S178. However, both loci demonstrated significant linkage disequilibrium in our study, and the AA
was in low frequency on control (U)
chromosomes.
The combined data for D19S223
and D19S178 revealed an AA frequency
of 41.7% for both loci (5/12) on nonOld Order Mennonite haplotypes. The
estimates of g using D19S223 were
171.6 and 73.5 generations (average ¼
122.6) for physical and genetic distances,
respectively. Likewise, the estimates for
D19S178 were 38.6 and 35.3 generations (average ¼ 37.0). While the sample
sizes are small, these data are consistent
with a common ancestor for non-Old
Order Mennonite haplotypes that predates the formation of the Lancaster
AMERICAN JOURNAL OF MEDICAL GENETICS (SEMIN. MED. GENET.)
Mennonite settlement. This does not
preclude the possibility that one or more
of these haplotypes were derived from
Mennonite ancestors, but the majority
of these haplotypes demonstrate recombination events consistent with a deeper
pedigree than the Lancaster Mennonite
population can provide.
Genetic Diversity
There is widespread expectation that
genetic variation is reduced in any genetically isolated population, particularly
those of recent origins such as the Old
Order Mennonites. One measure of
genetic diversity was studied in Old
Order Mennonite families with children
affected with HSCR by analysis of 515
autosomal and 24 X-linked microsatellite markers in 40 chromosomes
[Chakravarti et al., 1997]. These data
were compared to 40 chromosomes
from the Utah set of CEPH families for
control purposes.
Genetic variation, as measured
by heterozygosity (h) at microsatellite
marker loci, is significantly reduced in
the Old Order Mennonites on autosomes (Mennonite h ¼ 74.9% 0.4%
vs. CEPH h ¼ 76.8% 0.4%), but not
on the X chromosome (Mennonite
h ¼ 78.2% 1.6% vs. CEPH h ¼
77.4% 1.9%). This represents a 1.9%
reduction in heterozygosity for microsatellite markers on Old Order Mennonite autosomes. This figure closely
approximates the calculated inbreeding
coefficient for Old Order Mennonite
HSCR families (1.2%). Since inbreeding creates a fractional reduction in
heterozygous genotypes within a population, the correlation between the
reduction in heterozygosity and inbreeding was anticipated. The additional
reduction in heterozygosity is likely due
to random genetic drift, which has
undoubtedly led to the extinction of
some alleles in the population. The loss
of these alleles resulted in less diversity
and lower heterozygosity values. Although the reduction in heterozygosity
is statistically significant, the decrease
in genetic variation was modest, and
thus the population remains genetically
diverse.
29
CONCLUSIONS
The history of Old Order Mennonites
of southeastern Pennsylvania provides
insight into the increased incidence of
genetic disease within isolated populations. It is commonly assumed that
genetic isolates are founded by a small
number of individuals and the population size increases over subsequent generations with few perturbations. The
population history of the Old Order
Mennonites does not fit such a simple
model. An analysis of their history
It is commonly assumed
that genetic isolates are founded
by a small number of
individuals and the population
size increases over subsequent
generations with few
perturbations. The population
history of the Old Order
Mennonites does not fit such
a simple model.
in the United States indicates multiple population bottlenecks, long-term
genetic and geographic isolation, and
uneven growth over the past 250 years
(see Fig. 1).
Due to the small number of founders and the rarity of most genetic
diseases, it was assumed that isolated
populations would show mutation
homogeneity. The data presented here
indicate that this assumption is not valid.
This has important implications for
the mapping of complex traits in isolated populations: the allelic diversity of
these populations should not be underestimated.
Although genetic drift and inbreeding are overlapping phenomena that
increase the frequency of genetic disease,
it is a common and popular belief that
inbreeding is the major reason for elevated levels of genetic disease in isolated
populations. The data on the 1312T !A
mutation and the Old Order Mennonite
surname distribution show that random
30
AMERICAN JOURNAL OF MEDICAL GENETICS (SEMIN. MED. GENET.)
genetic drift had a major effect on the
incidence of genetic disease. Inbreeding
The data on the 1312T !A
mutation and the Old
Order Mennonite surname
distribution show that random
genetic drift had a
major effect on the incidence
of genetic disease.
exacerbated this phenomenon by decreasing the frequency of heterozygous
genotypes (and increasing homozygous
genotypes). These two factors worked
in concert to produce the increased incidence of specific diseases.
While genetic diversity is postulated
to be dramatically reduced in genetic
isolates, the genotype data show that
the reduction was modest. Much of the
decrease in heterozygosity within the
population can be explained by inbreeding. Since inbreeding only affects genotype frequencies, the allelic diversity is
not truly lost, but rather partitioned into
homozygous genotypes at the expense
of heterozygous genotypes.
Finally, the utility of linkage disequilibrium analyses to detect disease
genes in isolated populations has been
affirmed by this work. It was possible to
detect association between a phenotype
and marker alleles over large genomic
regions in a young genetic isolate such as
the Old Order Mennonites. This nonparametric technique is computationally
simple, requires no assumptions about
mode of inheritance, and obviates the
need for detailed and comprehensive
genealogical analyses.
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