SEARCH

SEARCH BY CITATION

Abstract

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. References

The contribution of hereditary and environmental factors to the pathogenesis of symptomatic gallstone disease is still unclear. We estimated the relative importance of genetic and environmental factors by analyzing a large population of twins. For this purpose, the Swedish Twin Registry was linked with the Swedish inpatient-discharge and causes of death registries for symptomatic gallstone disease and gallstone surgery–related diagnoses in 43,141 twin pairs born between 1900 and 1958. Concordance rates, correlations, and odds ratios were calculated for males, females, monozygotic, and dizygotic twins, respectively, as well as for twin pairs of opposite sex. Structural equation modeling techniques were used to estimate the contributions of genetic effects as well as shared and non-shared environmental factors to the development of symptomatic gallstone disease. We found that concordances and correlations were higher in monozygotic compared with dizygotic twins, both for males and females. Of note, there were no significant sex differences in heritability. In the full model, genetic effects accounted for 25% (95% CI, 9%–40%), shared environmental effects for 13% (95% CI, 1%–25%), and unique environmental effects for 62% (95% CI, 56%–68%) of the phenotypic variance among twins. In conclusion, our results show heritability to be a major susceptibility factor for symptomatic gallstone disease, consistent with results from previous, much smaller studies. (HEPATOLOGY 2005.)

Gallstone disease (GD) is likely to result from a complex interaction of environmental factors and the effects of multiple undetermined genes. Genetic factors that affect susceptibility to gallstone formation and gallbladder disease in humans are suggested by family clustering and ethnic differences in gallstone prevalence,1–6 and by very few unbiased small twin studies.7–11

In 1999, Duggirala et al.5 used pedigree data to explore the genetic susceptibility to symptomatic GD in a Mexican-American population of 32 families and estimated a heritability (i.e., the proportion of the phenotypic variance of the trait that is due to genetic effects) of 44%. However, this association study did not control for shared environmental effects.5 A recent family study from the United States performed a variance component analysis in 1,038 individuals taken from 358 families and calculated the heritability of symptomatic GD to be 29%.6

Twin studies have been a valuable source of information on the genetic epidemiology of complex traits. They can be used to dissect the complex genetics by analyzing the interaction of genotypes and phenotypes with sex, age, and lifestyle factors. In contrast to family studies, comparisons of the concordance rates of symptomatic GD between monozygotic (MZ) and dizygotic (DZ) pairs of twins provide information on whether the familial pattern is due to hereditary or environmental factors.12 Furthermore, twin studies not only have the ability to point to hereditary effects, but they also allow an estimation of the magnitude of genetic effects.

The initial stage of genetic analysis is to determine whether genetic influences are important for a disease. The simplest analysis computes concordance rates separately for MZ and DZ twins. If concordance is found to be significantly higher in MZ twins who share all their genes compared with DZ twins who share on average 50% of their segregated genes, then this is considered to be a rough indicator that genetic effects are likely to be important.13 Following on from this, the heritability can be estimated by structural equation modeling (SEM), which defines causal relationships between observed variables.14 Since genes can be functionally relevant at different time periods through a lifetime, age is of importance. Furthermore, the inclusion of opposite-sexed (OS) pairs offers the advantage of testing whether different genes or specific environmental factors are relevant for both sexes.

The specific aim of this study was to assess the relative importance of genetic and environmental factors for symptomatic gallstone disease by conducting a quantitative genetic analysis on a large twin population in Sweden.

Patients and Methods

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. References

Subjects.

The first two collected cohorts (C1, twins born between 1900 and 1938; and C2, twins born between 1939 and 1958) of the Swedish Twin Registry15 were linked to the inpatient-discharge and causes of death registries. We then screened the registries for gallstone disease and gallstone surgery–related diagnoses codes (International Classification of Diseases [ICD] by the Word Health Organization [WHO]), according to the following search-criteria: ICD-8: 574, 575, 576; ICD-9: 574.0-574.5, 576.0-576.9; and ICD-10: K563, K800-K805, K808, JKA20, JKA21, JKB11, JKE00, JKE02, JKE06, JKE12, JKE15, and JKF10. The total number of twin pairs screened was 43,141. Zygosity data were provided by the registry and were determined by a questionnaire that has been shown in validation studies to classify correctly more than 98% of pairs of twins.15 Twins with unknown zygosity were excluded.

The study was approved by the Ethics Committee of the Karolinska Institute and by the Swedish Twin Registry Board.

Statistics.

The probandwise concordance (C) was calculated as the proportion of all persons with symptomatic GD whose twins had symptomatic GD metachronously:

  • equation image

The 95% confidence intervals for C (CIc) were calculated as:

  • equation image

where p, proportion of concordance; z = 1.96, coefficient for a 95% confidence interval; and n, number of cases.

The relative risk for symptomatic GD for subjects whose twin had symptomatic GD compared with subjects whose twin did not was estimated as an odds ratio (OR) and was calculated as:

  • equation image

where a, number of concordant pairs; b and c, each half the number of discordant pairs; and d, number of pairs without disease.

The 95% confidence intervals for the risk (CIr) were estimated according to the Mantel-Haenszel method,14 using the SISA statistical program.16

SEM.

SEM, also known as covariance modeling, is a general approach for the analysis of variance and correlations. In SEM, genotypic and environmental effects are modeled as the contribution of unmeasured (latent) variables to the potentially multivariate phenotypic differences between individuals. The latent variables' contributions are estimated as regression coefficients in the linear regression of the observed variables on the latent variables by the maximum likelihood and weighted least squares.15 Data on all types of twins (male, female, MZ, DZ) are incorporated simultaneously and provide estimates of the variables. By including OS DZ twins one can compare phenotypic identity for symptomatic GD between twins of opposite sexes. To estimate the relative importance of genetic factors and to test whether these differ between men and women, models based on 2-by-2 contingency tables (twin A's status by twin B's status) on categorical data (dichotomous, i.e., disease or no disease) were constructed for MZ females, DZ females, MZ males, DZ females, and OS pairs. The software package used was Mx.17

In addition to concordance rates, tetrachoric correlations were calculated for MZ, DZ, and OS twin pairs. Tetrachoric correlations are calculated for two normally distributed phenotypic variables that are both expressed as a dichotomy (disease or no disease) and reflect the similarity of twin pairs. Thus, differences in correlations between various groups provide information about the presence of genetic effects. For example, if MZ twins display higher tetrachoric correlation coefficients than DZ twins, genetic effects are important.

The overall phenotypic variance (VP) is divided into (1) one component due to inherited genetic factors (G = A + D; additive A or non-additive/dominant D), (2) one component due to common environmental factors (C), and (3) another component due to environmental factors unique for each twin (E). Assuming heritability in the narrow sense (i.e., the absence of non-additive genetic variance {G = A]), the equation for variance (Vp) for one of the twins in a pair can be written as15:

  • equation image

Since heritability is not a universal factor but depends on the population, sex, and cohort being measured, we tested different models for males and females in two separate cohorts as well as both cohorts as a whole. An underlying normal distribution of susceptibility to the disease was assumed. A threshold value was defined as the sum of effects of many genetic and environmental factors that has to be exceeded for the disease to manifest itself. In the saturated model, the threshold value was calculated from the clinical prevalence. For model evaluation, a likelihood ratio test was used. The difference between twice the log-likelihood can be interpreted as a χ2 statistic. The principle of parsimony indicates that the model with fewer parameters to be estimated that still fits the data best is to be chosen.18

The usual assumptions for a twin study were made, i.e., no random mating (since we just aimed to study the influence of the genotype), no gene/environment interaction, in that MZs share their entire genome whereas DZ share 50% of their segregated genes, equivalent environments (including prenatal) for MZ and DZ twins, known zygosity as well as the assumption that the twins are representative of the general population.17

Results

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. References

From the total twin population of 43,141 pairs, 5,970 pairs of unknown zygosity consisting of 235 discordant, 40 concordant, and 5,677 healthy pairs were excluded from further calculations. The age range was 64 to 102 years in cohort 1 (C1) and 44 to 63 years in cohort 2 (C2). Among the 43,141 pairs evaluated in the whole cohort (C) we found a total of 4,394 individuals with symptomatic GD. The overall prevalence of symptomatic GD was 6.5% in C1 (7.3% and 6.8% for MZ and DZ females, 5.9% and 5.5% for MZ and DZ males, and 6.7% for OS twins, respectively), and 3.5% in C2 (5.2% and 4.7% for MZ and DZ females, 1.7% and 2.0% for MZ and DZ males, 3.5% for OS twins, respectively).

Table 1 displays the probandwise concordance rates for symptomatic GD in MZ and DZ twins of both sexes as well as of OS pairs. Concordance rates ranged from 6% for affected females in OS twin pairs to 24% for female MZ twins in C2. Concordance rates were higher for MZ compared with DZ twins, for both women and men. The differences between MZ and DZ twins were more pronounced in the younger cohort, C2. This result is also reflected by the odds ratios for symptomatic GD that ranged from 1.9 for OS twins in both cohorts to 17.6 for male MZ twins in the younger cohort 2 (Table 1).

Table 1. Concordance Rates for Symptomatic Gallstone Disease in Twins
CohortHealthy PairsDiscordant PairsConcordant PairsProbandwise Concordance Rate (95% CI)*Odds Ratio (95% CI)Tetrachoric Correlation (95% CI)
  • *

    Probandwise concordance rate = (number of affected twins in concordant pairs)/(total number of affected twins).

Females      
 C1      
  MZ3013410490.19 (0.16-0.23)3.5 (2.5-4.9)0.33 (0.23-0.42)
  DZ5529735630.15 (0.12-0.17)2.6 (1.9-3.4)0.24 (0.16-0.32)
 C2      
  MZ2378208320.24 (0.19-0.29)7.0 (4.5-10.9)0.48 (0.36-0.58)
  DZ3414305250.14 (0.11-0.18)3.7 (2.3-5.8)0.31 (0.19-0.42)
 C      
  MZ539161881  0.39 (0.32-0.46)
  DZ8943104088  0.26 (0.20-0.33)
Males      
 C1      
  MZ2498280240.15 (0.11-0.19)3.1 (1.9-4.9)0.28 (0.15-0.39)
  DZ4096456250.10 (0.08-0.13)2.0 (1.3-3.0)0.16 (0.05-0.27)
 C2      
  MZ21165870.19 (0.12-0.30)17.6 (7.1-43.5)0.56 (0.35-0.73)
  DZ340312480.11 (0.07-0.18)7.1 (3.3-15.4)0.39 (0.20-0.55)
 C      
  MZ461433831  0.37 (0.26-0.47)
  DZ749958033  0.24 (0.15-0.33)
Opposite-sexed twin pairs      
 C1      
  Female5217419470.12 (0.10-0.14)1.9 (1.4-2.7)0.16 (0.04-0.28)
  Male 293   0.17 (0.05-0.28)
 C2      
  Female7380389170.06 (0.04-0.09)1.9 (1.2-3.2)0.12 (0.04-0.28)
  Male 123   0.14 (0.01-0.29)
 C      
  Female1259780864  0.31 (0.20-0.40)
  Male 416   0.09 (0.01-0.18)

Tetrachoric Correlations.

The tetrachoric correlations (r) were calculated using Mx. Similar to the concordance rates, MZ similarity exceeded DZ similarity in all cases, indicating genetic effects (Table 1). The correlations were generally higher in the younger cohort, although there was still overlapping CI compared with C1. We found rMZ < 2 rDZ in all cases, which implies a better fit of the ACE than the ADE model according to the algorithms used in SEM.16 In practice, it indicates that shared environmental effects are of more importance than dominant genetic effects. Significant sex differences were not found.

Model Fitting.

In a first attempt at model fitting, the whole cohort was analyzed. We found a significant heritability both for females and males (25%, 95% CI, 9%-40%). The next step was to analyze the two cohorts separately with respect to females and males. When decomposing the phenotypic variance by SEM separately for both cohorts and both sexes, statistically significant effects of heritable factors were only observed for female twins in the younger cohort C2 (33%, 95% CI, 1%-58%). Heritability seems to be generally higher in the younger cohort, particularly for men in C2.

Table 2 presents statistics on model fitting and the estimates of variance components based on the best-fitting models. Two different assumptions were tested: When different estimates for A, C, and E were assumed for the model, Mx returned no significant differences in the estimated parameters between sexes (Table 2) with a good fit to the model. This was confirmed by remodeling with identical estimates for both sexes from the beginning (ACE2 model in Table 2), supporting the assumption of no difference in estimates between sexes. The ACE2 model represented the best fit according to Akaike's Information Criterion.12 Parameters in the best-fitting model ACE2 are estimated as follows: A, 25%; C, 13%; and E, 62%.

Table 2. Best-Fitting Model to Assess Variation of Genetic and Environmental Components for Symptomatic Gallstone Disease
ModelSexParameter EstimatesCohortFit of Model
A: Genetic Effects (95% CI)C: Shared Environmental Effects (95% CI)E: Unique Environmental Effects (95% CI)χ2DfProbabilityAIC
  1. NOTE. Analysis for men and women in each cohort given separately and for the whole cohort, assuming no sex differences. Model in bold type indicates the most suitable model according to the principle of parsimony. ACE2; different prevalences assumed, same estimates assumed for males and females. Abbreviations: C1, Cohort 1; C2, Cohort 2; C, whole cohort; df, degrees of freedom; AIC, Akaike Information Criterion (χ2 − 2 df).

ACEWomen0.17 (0-0.40)0.16 (0-0.32)0.67 (0.58-0.77)C12.25560.895−9.745
ACEMen0.23 (0-0.39)0.05 (0-0.27)0.73 (0.62-0.85)C1    
ACE2Women0.19 (0-0.37)0.12 (0-0.27)0.69 (0.62-0.77)C14.19680.839−11.804
ACE2Men0.19 (0-0.37)0.12 (0-0.27)0.69 (0.62-0.77)C1    
ACEWomen0.33 (0.01-0.58)0.14 (0-0.40)0.53 (0.42-0.64)C22.58960.858−9.411
ACEMen0.40 (0-0.74)0.18 (0-0.54)0.42 (0.26-0.63)C2    
ACE2Women0.33 (0.06-0.58)0.16 (0-0.38)0.50 (0.41-0.60)C23.87780.868−12.123
ACE2Men0.33 (0.06-0.58)0.16 (0-0.38)0.50 (0.41-0.60)C2    
ACEAll0.25 (0.09-0.40)0.13 (0.01-0.25)0.62 (0.56-0.68)C1.86880.985−14.132
AEAll0.41 (0.36-0.46)0.59 (0.54-0.64)C6.56490.682−11.436

We also tested the whole cohort for the ADE model, which was inferior to the ACE2 model (data not shown).

CIs were generally large and overlapping in C1 and C2, suggesting calculations to be performed for the cohort as a whole and with the assumption of no sex differences, as reasoned above. Calculations for the whole cohort were important in terms of statistical power, since the number of males is relatively small compared with females. The model was run for 4 and 6 groups, respectively, excluding or including OS twin pairs, once again showing no differences in results, although there was an unsatisfactory model fit for the 6 group model. Thus, all data are presented for the best-fitting models ACE and ACE2 using 4 groups.

Discussion

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. References

The present study estimated the impact of genetic and environmental factors on the development of symptomatic GD by linking the Swedish Twin Registry to symptomatic GD-related diagnoses from the Swedish inpatient-discharge and death registries.

An increased risk for symptomatic GD was found in the co-twins of affected individuals among the MZ twins of both sexes in the two study cohorts, C1 and C2. In all cases, correlations of MZ twins were greater than twice the correlations of DZ twins. From previous studies analyzing symptomatic GD in a total number of 148 twin pairs,7–11 concordance rates of 38% for the MZ and 8% for the DZ twins (i.e., a 5-fold difference) can be calculated. Our data derived from a nearly 30-fold larger cohort confirmed the higher concordance of symptomatic GD in MZ twins. However, the differences were found to be approximately only 2-fold, which points to the importance of environmental factors. Males were generally found to have higher odds ratios and higher correlations than females. However, the sex differences did not reach statistical significance. This finding is supported by the model for OS twins in the 2 separate cohorts, which showed no significant differences in the correlations for OS twin pairs.

We estimated a heritability of 25% (95% CI, 9%-40%) for symptomatic GD from a very large population sample. This is in accordance with the family study by Nakeeb et al. that shows a heritability of 29% based on a self-reported questionnaire.6 In contrast, Duggirala et al.5 reported a heritability of 44% for symptomatic GD, but their variance component linkage analysis did not discriminate common and non-shared environmental effects.

The major contribution to our current understanding of specific “lithogenic genes” is derived from animal studies, particularly cross-breeding experiments in inbred mouse strains that differ in genetic susceptibility to cholesterol gallstone formation (quantitative trait locus mapping).19 However, so far only few human genes have been repeatedly associated with gallstone formation in case-control and experimental studies. These include apolipoprotein E, the hepatic phospholipid transporter ABCB4 and the rate-limiting enzyme of bile salt synthesis CYP7A1.20 Although we expect additional genes related to gallbladder inflammation and hypomotility to be important,19, 20 the limited number of known human gallstone genes could at least in part demonstrate that genetic effects play a dominant role in defined subtypes of cholelithiasis—like patients with ABCB4 gene mutation-associated cholelithiasis21—but not in the majority of elderly gallstone carriers.

A major finding of the present study was the significant contribution of common environmental factors to symptomatic GD, by 13% (95% CI, 1%-25%). A “lithogenic” (gallstone-promoting) diet in childhood, weight changes through common dietary factors, biliary infections, perhaps by enterohepatic Helicobacter species,22 or other environmental factors could also contribute. Notwithstanding that the shared environment seems to be of some importance, non-shared environmental factors account for the largest proportion of the total trait variance (62%, 95% CI, 56%-68%). There are more discordant than concordant pairs in every group, supporting the postulation that non-shared environment plays a significant role in disease development as in many other complex traits.2 The best-known lifelong, sex-independent risk factor is the hypercaloric (“westernized”) diet, that is notoriously included among the common risk factors for symptomatic GD (i.e., “female, fertile, fat, and [age over] forty”). It is more likely that habits acquired later in life gain importance when the familial cluster is abandoned, and thus, familiality should be most obvious in the younger cohort C1, and in particular in MZ males. This in fact is the case as seen by the highest odds ratio of 17.2 for MZ males in C2. Power calculations computed separately for the significance of heritability, and the significance of the common environment did not allow the reduction to a simpler model where either genetic or shared environmental factors could be disregarded. The power for the significance of common environmental factors C was weak, which can be explained partly by the fact that studies of twins have limited power to detect common environmental effects in dichotomous phenotypes (disease or no disease).

The prevalence of symptomatic GD in twins was found to be 6.5% for the younger and 8.3% for the older cohort, which was expected for a late-onset symptomatic disease that peaks after the age of 60. Nevertheless, the data may surprise, because previous studies from Sweden indicated an overall prevalence of GD of approximately 15%.23, 24 The discrepancy may be because of insufficient sampling of GD codes in the registries; however, this is most likely due to the fact that our data included symptomatic GD only, whereas the two older studies included approximately 50% of asymptomatic gallstone patients who were diagnosed by ultrasound or X-ray investigations.23, 24 Considering this figure, “true” prevalences of 16.6% in C1 and 13.0% in C2 can be estimated from our data, which are consistent with previous data.23, 24 Although the prevalence of symptomatic GD is lower than that of asymptomatic GD, heritability for symptomatic GD seems to be higher than for asymptomatic GD, as was recently suggested by Duggirala et al.,24 rendering symptomatic cohorts more suitable for genetic analyses.

Family clustering in symptomatic GD seems to be the result of additive genetic factors, at least to some extent. However, these are difficult to distinguish from shared environmental factors, even in a large study like the present one. Obviously, there are different thresholds for the disease between sexes, but no differences in heritability. The similar correlations of OS pairs suggest that the same genes are operating in males and females, a result that is consistent with the hypothesis that an identical set of critical genes is rate-limiting across sexes and species.19 Since the age at diagnosis of symptomatic GD was not available, the two cohorts were applied as a rough indicator of age dependency. However, no significant differences could be seen or conclusions drawn about specific genes contributing to the trait at different ages, as model fitting can predict heritability but not gene-environment interactions.

In summary, we conclude this twin study establishes heritability as an important component (25%, 95% CI, 1%-40%) along with unique environmental factors (62%, 95% CI, 56%-68%) in symptomatic GD. Genetic determinants of GD indicate that epidemiological studies on GD might be confounded by different genetic backgrounds and that genetic factors need to be carefully controlled for in studies defining environmental risk factors for GD.

References

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. References
  • 1
    Van der Linden W. Genetic factors in gallstone disease. Clin Gastroenterol 1973; 2: 603614.
  • 2
    Paigen B, Carey MC. Gallstones. In: KingRA, RotterJI, MotulskyAG, eds. The Genetic Basis of Common Diseases. 2nd ed. New York: Oxford University Press, 2002: 298335.
  • 3
    Gilat T, Feldman C, Halpern Z, Dan M, Bar-Meir S. An increased familial frequency of gallstones. Gastroenterology 1983; 84: 242246
  • 4
    Sarin SK, Negi VS, Dewan R, Sasan S, Saraya A. High familial prevalence of gallstones in the first-degree relatives of gallstone patients. HEPATOLOGY 1995; 22: 138141.
  • 5
    Duggirala R, Mitchell BD, Blangero J, Stern MP. Genetic determinants of variation in gallbladder disease in the Mexican-American population. Genet Epidemiol 1999; 16: 191204.
  • 6
    Nakeeb A, Comuzzie AG, Martin L, Sonnenberg GE, Swartz-Basile D, Kissebah AH, et al. Gallstones: genetics versus environment. Ann Surg 2002; 235: 842849.
  • 7
    Duis BT. Catamneses of twins: clinical findings in follow-up examination of a free-choice selection of a series of twins. Acta Genet Med Gemellol 1956; 5: 15103.
  • 8
    Harvald B, Hauge M. A catamnestic investigation of Danish twins. A preliminary report. Dan Med Bull 1956; 3: 150158.
  • 9
    Doig RK. Illness in twins, III: cholelithiasis. Med J Aust 1957; 44: 716717.
  • 10
    Koch G. Results of a reexamination of the Berlin twin series after 20 and 25 years. Verh Dtsch Ges Inn Med 1959; 64: 273277.
  • 11
    Kesaniemi YA, Koskenvuo M, Vuoristo M, Miettinen TA. Biliary lipid composition in monozygotic and dizygotic pairs of twins. Gut 1989; 30: 17501756.
  • 12
    Neale MC, Cardon LR. Methodology for Genetic Studies of Twins and Families. Dordrecht, The Netherlands: Kluwer Academic Publishers, 1992.
  • 13
    Lichtenstein P, Holm NV, Verkasalo PK, Iliadou A, Kaprio J, Koskenvuo M, et al. Environmental and heritable factors in the causation of cancer—analyses of cohorts of twins from Sweden, Denmark, and Finland. N Engl J Med 2000; 343: 7885.
  • 14
    Kuritz SJ, Landis JR, Koch GG. A general overview of Mantel-Haenszel methods: applications and recent developments. Annu Rev Public Health 1988; 9: 123160.
  • 15
    Lichtenstein P, De Faire U, Floderus B, Svartengren M, Svedberg P, Pedersen NL. The Swedish Twin Registry: a unique resource for clinical, epidemiological and genetic studies. J Intern Med 2002; 252: 184205.
  • 16
    SISA Binomial [database online]. Hilversum, The Netherlands: Uitenbroek; 2005. Available at: http://home.clara.net/sisa/binomial.htm.
  • 17
    Neale MC. Mx: statistical modelling, 5th ed. Richmond, VA: Virginia Commonwealth University, 1999.
  • 18
    Iliadou A, Lichtenstein P, Morgenstern R, Forsberg L, Svensson R, de Faire U, et al. Repeated blood pressure measurements in a sample of Swedish twins: heritabilities and associations with polymorphisms in the renin-angiotensin-aldosterone system. J Hypertens 2002; 20: 15431550.
  • 19
    Lammert F, Carey MC, Paigen B. The chromosomal organization of candidate genes involved in cholesterol gallstone formation: a murine gallstone map. Gastroenterology 2001; 120: 221238.
  • 20
    Lammert F, Matern S. The genetic background of cholesterol gallstone formation: an inventory of human lithogenic genes. Curr Drug Targets 2005, in press.
  • 21
    Rosmorduc O, Hermelin B, Boelle PY, Parc R, Taboury J, Poupon R. ABCB4 gene mutation-associated cholelithiasis in adults. Gastroenterology 2003; 125: 452459.
  • 22
    Maurer KJ, Ihrig MM, Rogers AB, Ng V, Bouchard G, Leonard MR, et al. Identification of cholelithogenic enterohepatic Helicobacter species and their role in murine cholesterol gallstone formation. Gastroenterology 2005; 128, in press.
  • 23
    Muhrbeck O, Ahlberg J. Prevalence of gallstone disease in a Swedish population. Scand J Gastroenterol 1995; 30: 11251128.
  • 24
    Borch K, Jonsson KA, Zdolsek JM, Halldestam I, Kullman E. Prevalence of gallstone disease in a Swedish population sample. Relations to occupation, childbirth, health status, life style, medications and blood lipids. Scand J Gastroenterol 1998; 33: 12191225.
  • 25
    Duggirala R, Dodd GD, Fowler S, Schneider J, Arya R, Diehl AK, et al. A major susceptibility locus for gallbladder disease is on chromosome 11p in Mexican Americans. Am J Hum Genet 2003; 73(Suppl): A167.