Genetic modifiers of nutritional status in cystic fibrosis1–4
Gia M Bradley, Scott M Blackman, Christopher P Watson, Vishal K Doshi, and Garry R Cutting
Background: Improved nutrition early in life is associated with
better pulmonary function for patients with cystic fibrosis (CF).
However, nutritional status is poorly correlated with the CFTR ge-
Objective: We investigated the extent to which modifier genes in-
fluence nutrition in children with CF.
Design: BMI data were longitudinally collected from the CF Twin-
Sibling Study and Cystic Fibrosis Foundation Patient Registry for
twins and siblings from 2000 to 2010. A nutritional phenotype was
derived for 1124 subjects by calculating the average BMI z score
from 5–10 y of age (BMI-z5to10). The genetic contribution to the
variation in BMI-z5to10(ie, heritability) was estimated by comparing
the similarity of the phenotype in monozygous twins to that in di-
zygous twins and siblings. Linkage analysis identified potential
Results: The median BMI-z5to10was 20.07 (range: 23.89 to 2.30),
which corresponded to the 47th CDC percentile. BMI-z5to10was
negatively correlated with pancreatic insufficiency, history of me-
conium ileus, and female sex but positively correlated with later
birth cohorts and lung function. Monozygous twins showed greater
concordance for BMI-z5to10than did dizygous twins and siblings;
heritability estimates from same-sex twin-only analyses ranged
from 0.54 to 0.82. For 1010 subjects with pancreatic insufficiency,
genome-wide significant linkage was identified on chromosomes
1p36.1 [log of odds (LOD): 5.3] and 5q14 (LOD: 5.1). These loci
explained $16% and $15%, respectively, of the BMI variance.
Conclusions: The analysis of twins and siblings with CF indicates
a prominent role for genes other than CFTR to BMI variation. Spe-
cifically, regions on chromosomes 1 and 5 appear to harbor genetic
modifiers of substantial effect.
Am J Clin Nutr 2012;96:1299–
Cystic fibrosis (CF)5is an autosomal recessive disease that af-
fects w70,000 individuals worldwide and is caused by mutations
in the CFTR (cystic fibrosis transmembrane conductance regula-
tor) gene (1). It is marked by a progressive decline in lung function
and malnutrition, although improved nutrition early in life has
been associated with better pulmonary function later in life (2–5).
Nutritional status is not well correlated with the CFTR genotype
(6, 7), which suggests the additional influence of environmental,
genetic, or stochastic factors (8). Identified nongenetic influences
include the diagnosis of CF via a newborn screen (NBS) and
placement of a gastrostomy, which are both associated with im-
proved nutritional status (9, 10). Alternately, pancreatic insufficiency
(PI) and meconium ileus (MI) negatively influence nutrition and
growth in CF patients (11, 12). We also have previously shown that
genes independent of CFTR contribute to the average lifetime nu-
tritional status in CF (13). The identification of the extent to which
these modifier genes modulate nutritional status in children with CF
is important to elucidate the cause of poor nutrition in these patients
when they have otherwise been nutritionally optimized.
Twin studies allow for the estimation of the relative contri-
butions of genes and environment to an observed phenotype.
With the use of data from the CF Twin-Sibling Study (www.
clinicaltrials.gov; NCT00037778) (14), we investigated the in-
fluence of genetic and nongenetic factors on nutrition in young
CF patients who experience the greatest changes in growth rates.
In accordance with the recommendation of the Cystic Fibrosis
Foundation (CFF), BMI (in kg/m2) was used as the marker of
nutritional status (15). BMI percentiles more accurately predict
nutritional failure in CF patients than do conventional anthro-
pometric measures, including the height-for-age percentile,
weight-for-age percentile, and percentage of ideal body weight
(16, 17). Because BMI varies during childhood and adolescence,
we derived measures from a specific age range. The age range of
5–10 y was selected as a stable period in the disease process
1Fromthe Department of Pediatrics (GMB, SMB, and GRC) and McKu-
sick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Bal-
timore, MD (CPW, VKD, and GRC).
2GMBand SMB are joint first authors.
3Supportedby the NIH (grant 5 T32 HD44355-8; to GMB), the National
Institute of Diabetes and Digestive and Kidney Diseases (grant DK076446;
to SMB), and the National Heart, Lung, and Blood Institute (grant
HL068927; to GRC).
4Addressreprint requests and correspondence to GR Cutting, Institute of Ge-
netic Medicine, Johns Hopkins University, Broadway Research Building, 733
North Broadway, Suite 551, Baltimore, MD 21205. E-mail: firstname.lastname@example.org.
5Abbreviationsused: BMI-zadj, average BMI z score from 5 to 10 y of age
adjusted for female sex, birth cohort, pancreatic insufficiency, and history of
meconium ileus; BMI-zadjFEV, average BMI z score from 5 to 10 y of age
adjusted as for BMI-zadjplus for FEVq6to10; BMI-zadjFEV-F508del, BMI-zadjFEV
values with the inclusion of only subjects homozygous for F508del; BMI-zadj-
FEV-PI, BMI-zadjFEVvalues with the inclusion of only pancreatic-insufficient
subjects; BMI-zadj-F508del, BMI-zadjvalues with the inclusion of only subjects
homozygous for F508del; BMI-zadj-PI, BMI-zadjvalues with the inclusion of
only pancreatic-insufficient subjects; BMI-z5to10, average BMI z score from 5 to
10 y of age; CF, cystic fibrosis; CFF, Cystic Fibrosis Foundation; FEVq6to10,
average cystic fibrosis–specific forced expiratory volume in 1 s percentile for all
measures obtained from 6 to 10 y of age; height-z5to10, average height z score
from 5 to 10 y of age; LOD, log of odds; MI, meconium ileus; NBS,
newborn screen; PI, pancreatic insufficiency; weight-z5to10, average
weight z score from 5 to 10 y of age.
ReceivedMay 22, 2012. Accepted for publication September 20, 2012.
Firstpublished online November 7, 2012; doi: 10.3945/ajcn.112.043406.
Am J Clin Nutr 2012;96:1299–308. Printed in USA. ? 2012 American Society for Nutrition
by guest on November 26, 2015
Supplemental Material can be found at:
after the majority of patients have been diagnosed with CF but
before the onset of disease-related comorbidities, such as CF-
related diabetes (18, 19). We hypothesized that this BMI phe-
notype would be heritable (ie, within-pair similarity would be
greater for monozygous twins than for dizygous twins and sib-
lings) and could be used to identify modifier genes that con-
tribute to the variability in nutritional status of children with CF.
SUBJECTS AND METHODS
All subjects were part of the CF Twin-Sibling Study and
recruited on the basis of having a twin or sibling with CF. Family
members all shared the same CFTR genotype. Written consent or
assent was obtained from all subjects or guardians, and the study
was approved by the Johns Hopkins University Institutional
Review Board. The zygosity status of twins was confirmed by
short tandem repeat analysis with use of an AmpFLSTR Profiler
(Applied Biosystems). Clinical data were supplemented by using
data provided by the US CFF Data Registry.
Longitudinal height and weight data were collected from 2000
to 2010. The raw data were subjected to a cleaning process
whereby biologically implausible dates, ages, heights, and
weights were corrected or excluded. For each clinic visit, BMI
was calculated if the age of the subject age at the time of the visit
was $2 y and if both height and weight measurements were
available. z scores for height, weight, and BMI were generated
by using CDC reference equations (20). To reduce the possible
bias associated with more-frequent measurements taken during
times of sickness, average-per-quarter z scores were calculated
for each subject with a quarter being defined as a 3-mo period
beginning with the subject’s month of birth. For generation of
the longitudinal BMI phenotype used in our analysis, BMI z
scores were dropped if the subject’s age was ,5 or $11 y at the
time BMI was obtained. Exclusion criteria included the fol-
lowing: 1) having BMI data during ,2 quarters between 5 and
10 y of age, 2) being diagnosed with CF at .5 y of age, and 3)
half-siblings and twins of indeterminate zygosity. In addition,
individuals without a twin or sibling who remained in the study
sample after the exclusion criteria were applied were also ex-
cluded. For the remaining individuals, a phenotype was derived
by calculating the average of average-per-quarter BMI z scores
from 5 to 10 y of age (BMI-z5to10).
The following covariates have been previously shown to
confound nutritional status in CF so were evaluated for their
contributions to the variability in BMI-z5to10phenotype: sex (4),
birth cohort (19), age at CF diagnosis (y) (21), diagnosis by NBS
(9), homozygosity for the F508del CFTR mutation (21), severe
exocrine PI (12), history of MI (11), presence of a gastrostomy
(10), pulmonary function (forced expiratory volume in 1 s) (19),
and socioeconomic status (22). Birth cohorts of subjects were
defined according to the year in which subjects were born
by using the following intervals: ,1980 (1), 1980–1984 (2),
1985–1989 (3), 1990–1994 (4), 1995–1999 (5), and .1999 (6).
The CFTR genotype is known to be associated with the severity
of pancreatic exocrine disease in CF patients, which, in turn, is
correlated with nutritional status (23–26). Thus, pancreatic
sufficiency was defined as having at least one CFTR mutation
associated with pancreatic sufficiency, as described previously
(27, 28). In the 7% of cases in which the CFTR genotype was
missing or indeterminate, clinical data, including fecal elastase,
fecal fat, serum trypsin, and the use of pancreatic enzymes, re-
spectively, were used. To further control for the influence of
CFTR on nutritional status, we analyzed patients who were ho-
mozygous for the F508del mutation (w55% of the study pop-
ulation). Other CFTR genotypes were too infrequent to perform
statistically robust comparisons. Diagnostic criteria for MI were
previously defined (29); in addition, pancreatic-sufficient patients
with an unknown diagnosis of MI were considered to have no
history of MI. The presence of a gastrostomy was defined at the
time of enrollment in the study. Lung function was quantified by
calculating CF-specific percentiles for the best FEV measurement
during each quarter (14) between age 6 and age 10; each best-
per-quarter percentile was averaged to obtain a single value per
subject (FEVq6to10). FEVobtained at ,6 y of age were excluded
owing to lack of reference values (30). Insurance type, which
was defined as public or private on the basis of the most recent
CFF data, was selected as the marker of socioeconomic status
because it was previously shown to be associated with lower
lung function for patients in the CF Twin-Sibling Study (31).
Fisher’s exact test and 2-tailed t tests were used to compare
subjects stratified by zygosity. The association of covariates with
BMI-z5to10 was tested by using univariate linear regression.
Covariates that were significant (P , 0.05) in the univariate
analyses were included in multivariate regressions. Residuals
from multivariate models were used in heritability estimations
and linkage analyses. These analyses were also performed with
the inclusion of only subjects with PI and only F508del homo-
zygotes to control for the effect of CFTR on nutritional status.
To account for the possibility of changes in the mean BMI z
score across the 6-y window used to construct the BMI-z5to10
phenotype, a regression analysis was performed by using age
centered on 8 y as a covariate; a residual phenotype was gen-
erated from this regression and used in separate heritability and
linkage analyses. All linear regressions accounted for within-
family correlations by using a generalized estimating equations
methodology. Stata IC 11 software (StataCorp) was used for all
Estimation of heritability
Pearson’s correlation coefficient for BMI-z5to10and each re-
sidual phenotype was determined for monozygous twins, di-
zygous twins, same-sex dizygous twins, and a dizygous twin and
sibling group. The dizygous twin and sibling group included
same-sex dizygous twins and siblings born #3 y of each other;
this group was used as a proxy for dizygous twins because of the
limited number of pairs of dizygous twins. Heritability was
estimated by subtracting the correlation coefficient for dizygous
twins from the correlation coefficient for monozygous twins and
multiplying the difference by 2; estimates were also generated
BRADLEY ET AL
by guest on November 26, 2015
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