Familial Hypercholesterolemia and Type 2 Diabetes in the Old Order Amish


Familial Hypercholesterolemia and Type 2 Diabetes
in the Old Order Amish
Huichun Xu,1 Kathleen A. Ryan,1 Thomas J. Jaworek,1 Lorraine Southam,2,3 Jeffrey G. Reid,4

John D. Overton,4 Aris Baras,4 Marja K. Puurunen,4 Eleftheria Zeggini,3 Simeon I. Taylor,1

Alan R. Shuldiner,4 and Braxton D. Mitchell1,5

Diabetes 2017;66:2054–2058 | https://doi.org/10.2337/db17-0173

Alleles associated with lower levels of LDL cholesterol
(LDL-C) have recently been associated with an increased
risk of type 2 diabetes (T2D), highlighting the complex
relationship between LDL-C and diabetes. This observa-
tion begs the question of whether LDL-C–raising alleles
are associated with a decreased risk of T2D. This issue
was recently addressed in a large familial hypercholester-
olemia (FH) screening study, which reported a lower prev-
alence of self-reported diabetes in FH subjects than in
age-matched relatives without FH. To extend this obser-
vation, we tested the association of FH with diabetes sta-
tus and glycemia in a large Amish population enriched
for the FH-associated APOB R3527Q variant that in-
cluded 640 APOB R3527Q carriers and 4,683 noncarriers.
Each copy of the R3527Q T allele was associated with a
74.9 mg/dL increase in LDL-C. There was little difference
in T2D prevalence between subjects with (5.2%) and with-
out (4.5%) the R3527Q allele (P = 0.23), and there was no
association between R3527Q variant and impaired fasting
glucose, fasting glucose or insulin, or oral glucose tolerance
test–derived measures. Our data provide no evidence
supporting an association between the APOB R3527Q var-
iant and T2D or glycemia and highlight the asymmetry of
the LDL-C–T2D relationship and/or the gene/variant-
dependent specificity of the LDL-C–T2D association.

The observation that treatment of hypercholesterolemia
with statins to reduce LDL cholesterol (LDL-C) levels leads
to an ;9% increased risk of type 2 diabetes (T2D) (1) has
generated a large dialogue on the relation of LDL-C low-
ering and T2D. Studies showing that LDL-C–lowering

variants in HMGCR, the gene encoding HMG-CoA reductase
and the molecular target of statins, are also associated with
increased risk of T2D (2) implicated the gene itself as the
driver for the increased T2D risk rather than an off-target
effect of statins. Subsequent studies have since shown LDL-
C–lowering alleles at other genes also to be associated with
increased risk of T2D, further suggesting that the LDL low-
ering itself is related somehow to increased T2D risk. An
intriguing recent finding is the appearance of heterogeneity
among LDL-C–lowering variants in different genes of the
degree to which they increase T2D risk. For example, recent
meta-analyses have revealed that LDL-C–lowering alleles at
PCSK9 and LDLR are associated with a small (19%, P = 0.03,
and 13%, P = 0.05, respectively) increased risk of T2D per
LDL-C reduction of 1 mmol/L (38.7 mg/dL), while LDL-C–
lowering alleles at NPC1L1 appear to impose a greater T2D
risk (142%, P , 0.001) per LDL-C reduction of 1 mmol/L
(3). These observations and others (4,5) suggest that mech-
anisms both dependent and independent of LDL-C may be
associated with increased T2D risk. Uncovering these mech-
anisms may reveal potentially targetable pathways for di-
abetes prevention or treatment.

The fact that LDL-C–lowering alleles are associated with
an increase in T2D risk begs the question as to whether
LDL-C–raising alleles are associated with a decrease in T2D
risk. This hypothesis was recently tested by Besseling et al.
(6) in familial hypercholesterolemia (FH) cases identified
from the national Dutch FH screening program. FH is as-
sociated with extremely high levels of LDL-C due to muta-
tions in the LDL receptor (LDLR) pathway, with mutations
occurring mainly in APOB, LDLR, and PCSK9. In the study

1Program in Personalized and Genomic Medicine, and Division of Endocrinology,
Diabetes & Nutrition, Department of Medicine, University of Maryland School of
Medicine, Baltimore, MD
2Wellcome Trust Sanger Institute, Hinxton, U.K.
3Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, U.K.
4Regeneron Genetics Center, Regeneron Pharmaceuticals, Inc., Tarrytown, NY
5Geriatrics Research and Education Clinical Center, Baltimore VA Medical Center,
Baltimore, MD

Corresponding author: Braxton D. Mitchell, bmitchel@som.umaryland.edu.

Received 10 February 2017 and accepted 15 April 2017.

© 2017 by the American Diabetes Association. Readers may use this article as
long as the work is properly cited, the use is educational and not for profit, and the
work is not altered. More information is available at http://www.diabetesjournals
.org/content/license.

2054 Diabetes Volume 66, July 2017

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https://doi.org/10.2337/db17-0173
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by Besseling et al. (6), there was a 44% lower rate of (self-
reported) T2D in FH cases (adjusted prevalence 1.44%)
compared with unaffected relatives (adjusted prevalence
3.26%). In subanalyses, the relative protection against T2D
was observed in patients with either the LDLR or APOB
mutations, with the strongest effect in those with LDLR
null mutations, which are more severe in disturbing LDL-C
metabolism.

Because of inherent biases in using self-reported diabetes
history and the potential for differential preventive care
given to subjects already known to have a lipid disorder, we
sought to evaluate the association of FH with T2D and
glycemia in a well-phenotyped cohort. Our analyses were
carried out in 5,323 Old Order Amish (OOA) individuals
from Lancaster County, Pennsylvania, a population enriched
for one of the known FH mutations, the R3527Q variant in
the APOB gene (rs5742904). We have previously reported
that LDL-C levels are increased by 58 mg/dL per copy of the
APOB R3527Q allele in the OOA (7). This mutation is more
common in the OOA population than in other Caucasian
populations because of a founder effect. Our sample in-
cluded 640 APOB R3527Q carriers, a number far larger
than the 84 APOB mutation carriers reported in the Dutch
study. We compared across APOB R3527Q genotypes T2D
prevalence and mean levels of glycemia-related traits, in-
cluding glucose and insulin values measured during oral
glucose tolerance tests (OGTTs) in a subset of subjects.
We found no evidence supporting an association between
the APOB R3527Q variant and T2D or glycemia.

RESEARCH DESIGN AND METHODS

All 5,323 subjects included in this study were phenotyped
for one or more of the study outcomes (diabetes, fasting
glucose, and/or HbA1c) and genotyped for APOB R3527Q by
either the Illumina HumanExome BeadChip or by whole-
exome sequencing. Paired-end 75 bp exome sequencing
was performed by the Regeneron Genetics Center as pre-
viously described (8) but using xGen (Integrated DNA Tech-
nologies) capture followed by sequencing on the Illumina
HiSeq 2500 System with v4 chemistry. For samples with
both exome sequence and chip genotype data (n = 2,695),
the concordance rate for the R3527Q variant was 99.85%.
All study subjects had participated in at least one of the
community-based studies our group had carried out in this
population over the past 20 years as part of our Amish
Complex Disease Research Program (9–13). Among these
were 640 subjects heterozygous (n = 625) or homozygous
(n = 15) for APOB R3527Q, corresponding to an allele
frequency of 6% and carrier frequency of 12%, consistent
with what we have previously reported (7).

For the analyses described in this report, T2D was diag-
nosed according to American Diabetes Association criteria
of fasting glucose .7 mmol/L (126 mg/dL) or HbA1c $6.5%
(if available). Subjects reporting current use of antidiabetes
medications (n = 86) were also considered to have diabetes
regardless of glucose testing. A 3-h OGTT was administered

to 723 individuals who had previously participated in the
Amish Family Diabetes Study (9), and subjects having a 2-h
glucose level .11.1 mmol/L (200 mg/dL) were also consid-
ered to have T2D. Impaired fasting glucose was defined in
individuals without diabetes as a glucose level between 5.6
and 6.9 mmol/L (100 and 125 mg/dL). Fasting glucose was
measured by a Beckman glucose analyzer using the glu-
cose oxidase method or the spectrophotometry method as
implemented by Quest Diagnostics, fasting insulin by radio-
immunoassay (Linco Research, Inc., St. Charles, MO), and
HbA1c by immunoturbidimetry (Quest Diagnostics, Hor-
sham, PA). HOMA of insulin resistance (HOMA-IR) was
defined as HOMA-IR = [fasting insulin (mU/L) 3 fasting
glucose (mmol/L)]/22.5. Area under the curve (AUC) in
OGTT was computed using the trapezoid rule. We tested
the association of glucose and HbA1c levels with APOB
R3527Q genotype using a mixed model that accounts for
relatedness among individuals as a random effect. Age and
sex were included as covariates. Analyses were carried out
under an additive genetic model using the MMAP software
program (14). Logistic regression was used to test the as-
sociation of T2D with genotype.

RESULTS

In the sample described in this report, each copy of the
APOB R3527Q T allele was associated with a 74.9 mg/dL
increase in LDL-C levels (95% CI 71.7–78.1), a slightly
higher estimate than the 58 mg/dL per allele effect size
we have reported previously in a smaller sample size (7).
This effect size was present across all ages studied (i.e., ages
20 years and older). The overall prevalence of T2D in the
sample was 4.6%, and there was virtually no difference by
R3527Q genotype (wild type 4.5%, heterozygotes 5.1%, and
homozygotes 6.7% across genotypes, P = 0.236) (Table 1).
In fact, the R3527Q T allele was associated with an in-
creased, not decreased, risk of T2D (per allele odds ratio
[OR] 1.27 [95% CI 0.85–1.85] for additive model; per
allele OR 1.41 [95% CI 0.07–8.08] for dominant model),
although in both models the CIs were wide and included 1.
Further analyses revealed no evidence for genotype ∗ age or
genotype ∗ BMI interactions.

Results of the 3-h OGTTs are shown in Fig. 1 for the
subset of 723 subjects who underwent this procedure, and
as indicated, the response profiles, measured as AUC for
glucose and insulin changes following glucose challenge,
were virtually indistinguishable across genotypes (P = 0.73
and 0.42, respectively). Table 2 compares prevalence of im-
paired fasting glucose and mean values of fasting glucose,
fasting insulin, and HbA1c as well as HOMA-IR in individ-
uals without diabetes according to genotype. These results
also reveal little differences between genotypes (P = 0.42–
0.73).

DISCUSSION

Our study is unique in its large sample size of FH subjects
(n = 640) carrying a single APOB mutation who were

diabetes.diabetesjournals.org Xu and Associates 2055



recruited as part of a community-based population survey
and tested for diabetes. Our data provide no evidence
supporting an association (protective or otherwise) of
the APOB R3527Q variant with either T2D or any other
glycemia-related trait. Notably, the 95% CI surrounding our
estimate of the T2D–APOB R3527Q association (0.85–1.85)
is not consistent with a 35% reduced odds of having T2D as
reported by Besseling et al. (6) but could be associated
with as much as a 15% decreased odds of T2D or as
much as a 85% increased odds. Our analysis is also con-
sistent with the lack of association reported for this var-
iant with T2D from the GoT2D Consortium (OR 1.69,
P = 0.17) based on 76 allele carriers and .75,000 noncar-
riers (http://www.type2diabetesgenetics.org). The absence
of association observed in our study (and GoT2D) contrasts
with the results obtained by Besseling at al. (6) that were
based on self-reported diabetes history in the Netherlands
FH registry. The protective association of FH with T2D
reported in the Dutch study was present for both LDLR
and APOB mutations; notably, the R3527Q variant present
in the Amish also appears to be the predominate APOB
variant observed in the Netherlands study (15). A possible
explanation for this discrepancy is that heightened surveil-
lance of FH cases and carriers in the Netherlands FH reg-
istry may have altered behaviors related to T2D risk, while
this was unlikely to be the case for Amish APOB R3527Q
carriers as subjects were unaware of their genotypes at the
time of subject enrollment and few Amish seek primary
care; in fact, only 3.1% of our Amish FH subjects reported
taking lipid-lowering medications.

The absence of an association observed in our study
between the R3527Q variant and T2D contrasts with the
increased risk of T2D that has been reported in Mendelian
randomization studies of HMGCR, PCSK9, NPC1L1, and
LDLR. One speculation is that the critical determinant of
lipid-associated T2D risk is more closely tied to an LDL
receptor–regulated mechanism than to an upstream defect
affecting the quality of the APOB ligand. As elucidated in
the pioneering research of Brown and Goldstein (16), a
dimeric complex between SREBPF chaperone (SCAP) and
insulin-induced genes (INSIG1 and INSIG2) functions as
an intracellular receptor for cholesterol. Together, these
proteins mediate effects of cholesterol on SREBP pathway–
mediated regulation of gene expression. It is plausible that
this SREBP pathway might mediate some of the observed
associations between LDL-C and the risk of diabetes. Be-
cause the INSIG/SCAP/SREBP pathway is regulated by in-
tracellular levels of cholesterol, this raises the question of
whether the R3527Q alters the rate at which LDL-C enters
cells. Boren et al. (17) reported that the R3527Q substitu-
tion decreases the affinity of APOB for the LDL receptor
by ;6.4-fold, suggesting that a ;6.4-fold higher concentra-
tion of Q3527-APOB would compensate for the lower bind-
ing affinity as compared with R3527-APOB. In this study,
we report an ;2.4-fold increase in LDL-C level, which is less
than the theoretical prediction of a 6.4-fold increase in the
concentration of APOB. At least two biological factors may

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2056 FH and T2D in the Old Order Amish Diabetes Volume 66, July 2017

http://www.type2diabetesgenetics.org


contribute to the apparent discrepancy. First, it is possible
that the ratio of APOB:LDL-C may be higher in individuals
who are homozygous for Q3527-APOB. Second, a decrease
in LDL receptor occupancy would be predicted to induce
upregulation of the number of LDL receptors on the cell
surface by decreasing the rate of ligand-induced receptor
degradation (18). Taken together, an increase in the num-
ber of LDL receptors and an increase in the concentration
of APOB would be predicted to preserve relatively normal
levels of receptor-mediated endocytosis.

Several limitations of our study should be acknowledged.
First, the Amish subjects included in our study were
relatively young (mean age 43 years), and some subjects
destined for future T2D may not have developed it yet.
Second, our sample included only 245 subjects with T2D,
and the minimal detectable OR at 80% power in our sample
is only 0.61. However, this estimate is approximately iden-
tical to the OR of 0.62 reported by Besseling et al. (6).
Moreover, our sample provides .90% power to detect a
significant association of the R3527Q variant with fasting
glucose if this variant accounted for as little as 0.4% of
the variation in fasting glucose levels, corresponding to a
change of ,1 mg/dL in glucose levels. Thus, our sample
size is well powered for detecting associations between the
R3527Q variant and glycemic traits.

The lack of association of this FH mutation with T2D
adds to the complexity of the LDL-C–T2D relationship.
While LDL-C–lowering alleles appear to be associated with
a modest increase in T2D risk, recent studies also indicate
that the increased T2D risk is not necessarily correlated
with the magnitude of the LDL-C–lowering effect. Our
study adds to this story by considering a single LDL-C–
raising variant, albeit one leading to a very large increase
in LDL-C. Notably, we find no association with either
T2D or any other glucose parameter. In contrast, other
FH-associated variants, including some in APOB, have
been associated with self-reported diabetes. These discrep-
ancies could reflect an asymmetry in the LDL-C–T2D re-
lationship, with T2D risk increasing with lower LDL-C levels
but unchanged with markedly higher LDL-C levels, or these
discrepancies could highlight a gene (or variant)-dependent
specificity of the LDL-C–T2D association similar to the het-
erogeneous effect shown by Lotta et al. (3). Given these
possibilities, Mendelian randomization studies that have
shown genetic risk scores for high LDL-C to be inversely
correlated with T2D risk (2,19,20) should be interpreted
cautiously, as the risk score–driving risk alleles included in
these analyses typically fall in a range of different genes and
their effects on T2D risk may represent widely varying
mechanisms rather than a single unified one. Sorting out

Table 2—Fasting and OGTT-derived measurements in individuals without diabetes
Trait All subjects CC TC TT b P

Impaired fasting
glucose (%) 7.1 (359/5,046) 7.1 (316/4,442) 6.9 (41/590) 14.2 (2/14) 0.120† 0.47

Glucose (mg/dL) 85.6 6 0.1 (n = 5,046) 85.6 6 0.1 (n = 4,442) 85.9 6 0.4 (n = 590) 86.4 6 3.3 (n = 14) 0.256 0.52

Insulin (mU/L, ln) 2.22 [1.95, 2.49] (n = 2,468) 2.22 [1.96, 2.50] (n = 2,171) 2.18 [1.92, 2.48] (n = 291) 2.41 [2.25, 2.50] (n = 6) 0.016 0.61

HOMA-IR 0.69 [0.38, 1.01] (n = 2,274) 0.68 [0.40, 1.01] (n = 2,001) 0.66 [0.33, 1.02] (n = 267) 0.95 [0.80, 1.16] (n = 6) 0.018 0.55

HbA1c (%, ln) 1.69 [1.63, 1.74] (n = 2,743) 1.69 [1.63, 1.74] (n = 2,417) 1.71 [1.63, 1.74] (n = 313) 1.69 [1.65, 1.74] (n = 13) 0.003 0.49

OGTT-derived
measures

Glucose AUC 389.3 6 4.7 (n = 723) 374.5 6 3.4 (n = 641) 387.5 6 12.3 (n = 80) 403.8 (n = 2) 3.250 0.73
Insulin AUC 129.6 6 2.4 (n = 717) 130.3 6 3.1 (n = 637) 133.6 6 10.7 (n = 78) 85.8 (n = 2) 6.930 0.42

Data are mean 6 SD except for insulin, HOMA-IR, and HbA1c (median [Q1, Q3]) unless otherwise indicated. SD not presented for glucose
and insulin AUC in the TT genotype group because of the small number of subjects. ln, natural logarithm. †OR 1.17 (95% CI 0.80–1.56).

Figure 1—Glucose and insulin response to a 3-h OGTT by APOB R3527Q (rs5742904) genotype.

diabetes.diabetesjournals.org Xu and Associates 2057



the mechanisms and pathways involved may reveal impor-
tant insights for diabetes prevention and treatment.

Funding. This study was supported by National Institutes of Health grants R01
DK54261, R01 AG18728, R01 HL69313, U01 HL072515, U01 GM074518, R01
HL088119, and P30 DK072488 and by the Wellcome Trust (WT098051).
Duality of Interest. No potential conflicts of interest relevant to this article
were reported.
Author Contributions. H.X. and B.D.M. contributed to study design and
management. L.S., J.D.O., and E.Z. contributed to genotyping. A.R.S. and B.D.M.
contributed to subject recruitment. H.X., K.A.R., and T.J.J. analyzed data. H.X., J.G.R.,
A.B., E.Z., S.I.T., A.R.S., and B.D.M. interpreted the results. H.X., K.A.R., S.I.T., and
B.D.M. drafted the manuscript. H.X., K.A.R., T.J.J., L.S., J.G.R., J.D.O., A.B., M.K.P.,
E.Z., S.I.T., A.R.S., and B.D.M. critically reviewed the manuscript. B.D.M. is the
guarantor of this work and, as such, had full access to all the data in the study
and takes responsibility for the integrity of the data and the accuracy of the data
analysis.

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2058 FH and T2D in the Old Order Amish Diabetes Volume 66, July 2017

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