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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Arthritis Rheum. Author manuscript; available in PMC Jul 1, 2011.
Published in final edited form as:
PMCID: PMC2956122
NIHMSID: NIHMS211096

Heritability of Vasculopathy, Autoimmune Disease, and Fibrosis: A Population-Based Study of Systemic Sclerosis

Abstract

Objective

This study looks at the familiality of systemic sclerosis (SSc) in relation to Raynaud's phenomenon (RP) a marker of vasculopathy, other autoimmune inflammatory disease (AD), and fibrotic interstitial lung disease (ILD).

Methods

A genealogic resource, the Utah Population Database (UPDB), was used to test heritability of RP, AD, and ILD. Diseases were defined by ICD-9 codes and identified from statewide discharge data, the University of Utah Health Science Center Enterprise Data Warehouse, and death certificates and linked to the UPDB for analysis. Familial Standardize Incidence Ratio (FSIR); relative risks (RR) to first, second, third, and fourth degree relatives for cases of SSc, RP, AD and ILD; and Population Attributable Risk (PAR) were calculated.

Results

A software kinship analysis tool was used to analyze 1037 unique SSc patients. Fifty significant SSc families had FSIRs ranging from 2.07 to 17.60. The adjusted PAR is about 8%. The RRs were significant for AD in the first (2.49, CI: 1.99-3.41, p: 2.42e-15) and second degree relatives (1.48, CI 1.34-2.39, p: 0.002); for RP in first (6.38, CI: 3.44 - 11.83, p: 4.04e-09) and second degree relatives (2.39, CI: 1.21 - 4.74, p: 0.012); and for ILD in first (1.53, CI: 1.04-2.26, p: 0.03), third (1.47, 1.18-1.82, p: 0004), and fourth degree relatives (1.2, CI: 1.06-1.35, p: 0.004).

Conclusion

This data suggests that SSc pedigrees include more RP, AD, and ILD than expected by chance. In SSc pedigrees, genetic predisposition to vasculopathy is the most important risk for first-degree relatives.

Systemic sclerosis (SSc) is a heterogeneous chronic illness with variability in clinical manifestations, internal organ involvement, and outcome, due to a complex interplay of inflammation, fibrosis, and vasculopathy. Genetic predispositions to SSc have been described, but the exact underpinnings that may predispose to specific disease presentations are unknown. Although the etiopathogenesis of this disease is not yet identified, autoimmunity has been thought to be the root cause of SSc (1). As such, permissive genetic background is thought to be essential to the development of this condition. Genetic susceptibility likely involves a combination of polymorphisms at multiple genes, particularly those regulating immune response and/or fibrotic mechanisms. The genes possibly work in epistatic pleiotrophy for different phenotypic expression.

Immune dysregulation is thought to play a key role in the initiation and perpetuation of vascular dysfunction and fibrosis seen in SSc (2). Despite its phenotypic complexity, almost all patients with SSc have Raynaud's phenomenon (RP) with capillary nailbed changes, which is a marker of the vasculopathy. The leading cause of mortality in this population is interstitial lung disease (ILD), a fibrotic process similar to that observed in the skin of SSc patients. Of interest, RP and ILD are not unique to systemic sclerosis and are observed in other autoimmune conditions, including systemic lupus erythematous (SLE), Sjogrens (SjS), dermatomyositis (DM), rheumatoid arthritis (RA), and unspecified connective tissue disease (UCTD) (3). Thus, it is the fibrotic and/or vasculopathic skin manifestations and SSc-specific serologies that generally help differentiate patients with SSc from other connective tissue disease (4).

A large cohort study in white and black adults in the US has estimated the prevalence and incidence of SSc as 24.2 per 100,000/year and 1.93 per 100,000/year adults, respectively (5). Higher prevalence is reported in the Oklahoma Choctaw Indians, with 66.0 cases per 100,000, suggesting either a higher genetic risk and/or common environmental exposure in this ethnic group (6, 7). Familial aggregation and twin studies in SSc support a genetic basis for the disease (8). In a twin study of 42 pairs, including 24 monozygotic pairs, there was a reported 4.7% concordance for disease expression (9). Based on three large cohorts with a total of 701 affected scleroderma cases, a positive family history of SSc is thought to represent the largest risk factor for this disease, though the absolute risk factor for each family member was reported at < 1%, the familial relative risk (RR) was approximately 15-fold higher for siblings, 13-fold higher for first-degree relatives, and it recurred in 1.6% of the SSc families (10). In another study of 710 proband cases, 10 cases of SSc occurred in first-degree relatives (11). Recently the familial risk of rheumatoid arthritis with SSc (standard incidence ratio 1.65 in offspring of proband) has been described in a study population of 447,704 patients (12). This supports the shared autoimmunity component to SSc and RA.

SSc vasculopathy, characterized by both noninflammatory macrovascular and microvascular changes, has been linked to genetic abnormalities in the expression of type 1 interferon (IFN) and regulator of G protein signaling 5 (RGS5), two molecules associated with vascular rarefaction (13). Thus, a genetic predisposition to abnormal endothelial cell senescence and apoptosis may be important to the pathogenesis of vasculopathy in SSc. Studies have shown an increase mRNA and protein levels of IFNs and several interferon stimulated genes in cells and tissues from SSc patients (14). IFNs are well-known immunomodulators and inhibitors of collagen production, thus in addition to a role in vasculopathy they may also play a role in the inflammatory and fibrosis aspect of SSc.

Population-level studies, however, are important in studying complex autoimmune diseases in order to estimate the likelihood of identifying candidate genes, such as those associated with IFN pathways (15). A valid assessment of familial relative risk may have important clinical utility in triaging persons for more involved screening and informing family members about potential risks (16).

This study looks at the familiality of the three important aspects of SSc: vasculopathy, altered immunity, and fibrosis in founder families of SSc patients. It is hypothesized that the relative contributions of these components to the pathophysiology may be determined by examining their compared heritability in a population based ascertainment model.

Methods and Study Population

Study population

A unique genealogic resource, the Utah Population Database (UPDB) was used to examine heritability using records from more than 7.0 million individuals. This resource links the medical records of an individual to their family or pedigree structure; the family history information begins about 1800 A.D. and many families have as many as eleven generations (17). It provides a valid resource for identifying founder mutations and assessing familial components to diseases and has been described in other studies (18-21). The Utah population is genetically representative of northern Europe and has low inbreeding levels, similar to other areas of the United States (22, 23).

For this study, diagnoses were defined using ICD-9 and ICD-10 codes; SSc (710.1) systemic lupus erythematous (SLE, 710.0), Sjögren's (SjS, 710.2), dermatomyositis (DM, 710.3), rheumatoid arthritis (RA, 714.0), and unspecified connective tissue disease (UCTD, 710.9). Records were collected from any of three sources a) statewide death certificates, b) University of Utah Health Science Center Enterprise Data Warehouse (UUHSC), which includes inpatient and outpatient records, or c) state-wide hospital discharge data. The SSc, RP, ILD, SLE, SjS, DM, and UCTD capture dates for the state-wide inpatient data ranged from January 1996 to December 2007; for UUHSC outpatients from May 1990 to May 2007; and for death certificates from January 1979 to December 1998 for ICD9 codes and to December 2007 for ICD10 codes. There is a disproportionate length of time between the different data bases and the incidence reported in this study is based on the date of first encounter within the respective data systems. The hospital discharge data system is a database containing statewide, population-based healthcare information associated with all hospitals in a state. In Utah 53 hospitals have submitted their discharge data to the Utah Department of Health. These data include principal diagnosis and up to eight other diagnosis. The UUHSC data includes information on more than 1.8 million patient records hospitals and outpatients clinics associated with the University of Utah. There were 21520 unique patients in the inpatient discharge data, 20561 unique patients in the UUHSC data, and 809 unique patients in the death certificates for all captured diagnoses. The distributions for these ICD codes from each data source are given in Table 1.

Table 1
Distribution of ICD9 codes by Diagnoses and Data Source

Cases of SSc were mapped to pedigrees of the UPDB for analysis. To be included in this pedigree analysis, the proband had to have parents and/or children with accessible medical records. The total number of SSc patient records used in this study from the combined datasets was 1589. There were 621 unique patients identified from the inpatient data, 833 from the UUHSC data, and 135 from death certificates. However some patients were identified from more than one source. For example, 244 of the 833 UUHSC patients were also found in the inpatient discharge data. From 1589 records, we found 1316 unique patients (Table 1). Of these patients, 1037 had either a parent or child or both in the UPDB and could be used by our software in the analysis. Ten matched controls were selected from the statewide UPDB population file without replacement in a Monte Carlo method to simulate random sampling. The controls were matched on sex, birth year, and whether they were born in Utah or not. The controls had to be living at the time of their matched case's diagnosis and had not been diagnosed with SSc, RP, SLE, SjS, DM, RA, UCTD, or ILD from any of the three data sources used.

The use of this data resource for this study has been approved by the University of Utah Institutional Review Board and by the Utah Resource for Genetic and Epidemiology Research (17).

Statistical analysis

The 1037 distinct SSc patients identified in the statewide population file with accessible genealogic records were used with kinship analysis software tools (KAT) to compute the Familial Standardized Incidence Ratio (FSIR) and Population Attributable Risk (PAR). The 50 families showing highest risk for SSc were identified for pedigree analysis by first filtering out families who did not have a p value of 0.05 or less for SSc and then sorting by Familial Standardized Incidence Ratio (FSIR) for special analysis.

We additionally computed the relative risk (RR) for SSc, RP, ILD, and other autoimmune disease (AD), including SLE, SjS, DM, UCTD, and RA, to specific kinship classes of the 1037 SSc patients: first degree relatives, second degree relatives, first cousins (third degree), and second cousins (fourth degree). For these calculations the numerator is risk of the designated type of disease (SSc, RP, ILD, or AD) among specific kinship classes of the cases, and denominator the risk of the same type of disease among kinship classes of the control group. We only used cousins for third and fourth degree relatives because they are in the same cohort as the probands and within the narrow range of years covered by electronic medical records. Hence, they have higher probability of being included in the records.

The key measures for this study are the population attributable risk (PAR), relative risk (RR), and familial standardized incidence ratio (FSIR). The PAR estimates the proportion of disease in a population attributable to familial factors, while the RR is used to compare the risk of SSc among family members of an individual with SSc to risk of SSc among the matched controls. The FSIR computes an individual family's risk for SSc, accounting for the number of biological relatives, their degree of relatedness to the proband, and their time at risk (24). It is calculated by the ratio of observed to expected numbers for SSc among family members, weighting the contribution of each member by the probability that member shares an allele by common descent. Two refinements of FSIR were used in this analysis. The first uses the natural logarithm of the FSIR, log(1+FSIR), to improve its behavior as a covariate in the conditional logistic regression model. The second transformation is an empirical-Bayes (EB) adjustment for uncertainty (25). A standard error was computed for each FSIR as a function of both the variation in risk among relatives in a family and the number of family members observed. EB was used to adjust for measurement error by moving the individual FSIR estimates closer to the mean in proportion to the magnitude of the standard error using the expectation-maximization method described by Dempster (26). The PAR was calculated using a method described by Bruzzi (27). Using conditional logistic regression to predict RR as a function of FSIR, individual probabilities of causation (PAC) for each case are computed as PAC = (RR − 1)/RR. The PAR is calculated as the mean of the PAC across all cases. The raw PAR uses the log of the FSIR to compute RR and the adjusted PAR uses the EB adjusted FSIR to compute the RR. We used the adjusted PAR because it accounts for the missing observations due to lack of family or follow up data as mentioned above.

KAT was also used to find the families that contained more SSc than expected by chance. This tool controls for the proportion of Type I errors adaptively, utilizing correlation and distribution characteristics of the observed data. We define family founders as oldest ancestors in a familial line in the UPDB for whom we have no record of parents. We also compared the RR for RP in relatives of patients with SSc and their controls in order to assess the heritability of this marker for vasculopathy. Similarly, to study the autoimmune or inflammatory aspect of SSc was examined by the RR of developing AD in relatives of patients with SSc to controls. Lastly, to study the hereditability of fibrosis in the context of SSc, we compared the RR of ILD in relatives of patients with SSc and their controls.

Results

The cumulative incidence and mortality rate for SSc was examined using the appropriate data source and number of years for each source. The mortality rate was 1.5 per 100,000 person-years in death certificates group and incidence rate was 3.3 per 100,000 person-years in the inpatient data and 2.8 per 100,000 person-years in the UUHSC group. The UUHSC data includes outpatient data and may be the best estimate of the population incidence rate.

KAT was applied to the 1037 patients with a parent, child, or both in the UPDB genealogic records in order to find the families that contained more SSc than expected by chance. The 50 statistically significant SSc families (number affected >= 4; p value <= 0.05) had FSIRs ranging from 2.066 to 17.60. In other words, these families had from 2 to 17 times as many members with SSc than would be predicted by a uniform distribution corrected for age, sex, and demographics. They ranged in size from 1840 family members to 80,787 and the number of affected descendants (i.e. diagnosed with SSC) ranged from 4 to 24. The adjusted PAR, which is a measure of familial risk to a specific disease, and accounts for missing observations, appears to be 8%. This is a measure of the familial contribution to risk for SSc accounting for degree of relatedness and length of time at risk. The familial contribution can be inherited or environmental.

Risk by relatedness

The increased RRs for systemic sclerosis were significant for all kinship classes examined except for second cousins (Table 2). The RRs do not follow the expected trend from first to fourth degree relatives because the RR for second degree relatives is higher than for first degree relatives. This is probably an artifact caused by the small number of affected individuals. The confidence intervals for first and second degree relatives almost completely overlap rendering the RRs statistically indistinguishable. In other words, the RRs are significant within their kinship classes but not between them.

Table 2
Relative Risk for Systemic Sclerosis to Specific Kinship Class

Risk of vasculopathy

When we compared the RR of RP in relatives of patients with SSc and their controls, we looked at first through fourth degree relatives and first and second degree relatives had a significant increase in risk. First degree relatives are 6 times more likely to have RP than first degree relatives of the controls and second degree relatives are twice as likely to have RP (Table 3).

Table 3
Relative Risk for Raynauds Phenomenon to Specific Kinship Classes of Patients with Systemic Sclerosis and their Control Families

Risk of altered immunity as determined by having an AD

When we compared the relative risk for overlapping autoimmune conditions in relatives of patients with SSc to controls, first and second degree relatives had a significant increase in risk (Table 4). First degree relatives are 2.5 times more likely to have another autoimmune disease than first degree relatives of the controls. Second degree relatives are 1.5 times more at risk for an overlapping condition.

Table 4
Relative Risk for Other Autoimmune Diseases to Specific Kinship Classes of Patients with Systemic Sclerosis and their Control Families

Risk of Fibrotic disease

Lastly, we compared the RR for ILD in relatives of patients with SSc and their controls (Table 5). First, third, and fourth degree relatives had significantly elevated relative risks for ILD. Excluding second degree relatives, the relative risks to the other kinship classes follow the expected decreasing trend for inherited risk.

Table 5
Relative Risk for ILD to Specific Kinship Classes of Patients with Systemic Sclerosis and their Control Families

Seven SSc pedigrees were compiled from UPDB for further analysis. Their founders were among the 50 highest risk families we found and were chosen because they had p < 0.05 for RP, ILD, and AD. The number of their descendants ranged from 1804 to 9151 and their number of generations ranged from five to seven. One particular founder family with 3720 descendants demonstrates the power of the UPDB as a resource for finding multiplex families. It reveals the presence of RP, ILD, and AD in multiple family members, and demonstrates how a pedigree can link seemly sporadic disease together into a familial syndrome (Figure 1). This pedigree was trimmed to only show the descendant paths that lead to affected individuals.

Figure 1
Systemic Sclerosis Pedigree

Discussion

This population-based study examines the familiality of SSc in the setting of a family history of vasculopathy (RP), autoimmune inflammatory diseases (SLE, SjS, DM, UCTD, and RA), and fibrosis (ILD) in order to examine the relative genetic influence of these components of SSc pathophysiology. In the UPDB, which is linked to over 7 million individuals, 1316 distinct SSc patients and 50 SSc families with the highest FSIR were examined in detail. These families were 2 to 17 times as affected with SSc as would be predicted by a uniform distribution corrected for age, sex, and demographics and had excess RP, autoimmunity (as represented by AD) and fibrosis (as represented by ILD). The PAR, a measure of the familial predisposition to SSc, appears to be 8%. This study is genetically representative of northern Europe with low inbreeding levels (22, 23). This has important implication when counseling SSc patients about familial risk. The cumulative incidence rate was 3.3 per 100,000 person-years in the inpatient data and 2.8 per 100,000 person-years in the UUHSC group which is higher, but close to the confidence interval of 1.9 per 100,000/yr (95% CI 1.24-3.02) previously reported in the large cohort study done in the Detroit tri-county area (5). Our reported higher incidence could be due to the fact that localized scleroderma (morphea and linear disease), were excluded in the Mayes study, but these entities could have possibly been coded in our data sources under ICD-9 710.1.

The exact genetic contribution to vasculopathy, inflammation, and fibrosis in SSc remains unknown. When KAT was used to find the relative risks to SSc families for RP (to represent vasculopathy), ILD (fibrosis), and overlapping autoimmune diseases (inflammatory diseases; SLE, SjS, DM, UCTD, RA), the risk for each of these conditions was increased in first degree relatives. First degree relatives were 6 times more likely to have RP than controls. Risk for RP was also significantly increased in second degree relatives, through the risk tended to decrease with more distant relationship as expected for heritable conditions. The presence of RP in a SSc family member seems to imply that there may by increased risk for SSc, consistent with the hypothesis that places vascular injury at the center of the pathogenesis SSc (13). Additionally, this supports the importance of the clinical finding of capillaroscopy, which examines the vascular nailbed changes in the setting of RP, as an important diagnostic test for SSc, which has a reported sensitivity of 100%, specificity of 81%, and a positive predictive value of 90% (28). This is an important tool for screening for and diagnosing SSc (29).

Only first and second degree relatives of SSc patients had a statistically significant increase in risk for other autoimmune diseases. First degree relatives were 3 times more likely to have an AD than first degree relatives of the controls. Second degree relatives were 1.8 times more at risk for an overlapping condition. This finding is consistent with other data that immune dysregulation, possibly related to highly pleiotropic cytokines, also has a heritable component (30).

With exception of second degree relatives, the relative risk of ILD to the other kinship classes also follows the expected decreasing trend for inherited risk. First degree relatives were 1.5 times more likely to have ILD. These results suggest that in the clinical setting, screening questions for the presence of RP, ILD, or another autoimmune condition in a first degree relative is important when considering the diagnosis of SSc. Additionally, these results attest to the important role of RP in the pathophysiology of SSc. Improved inpatient coding for RP may be warranted. Institution of potent therapies aimed at patients with RP could lower the risk for development of systemic sclerosis a proposition that remains untested.

There are limitations to this population database approach. The study population was primarily of Northern European descent and should be generalized to only other populations of similar origin. Nonetheless this study does suggest a genetic contribution to vasculopathy, immune dysfunction, and fibrosis, and provides the background for additional studies. The identification of the cases is based on billing codes which may include some misclassification. Due to the de-identified nature of the data we were unable to validate the diagnoses. However, this approach allows the estimates of familial risk to be more valid as they are not based on self reports by patients. Every patient with SSc did not have RP as a co-diagnosis although it is almost universally present in this condition (31). This suggests that perhaps only the most severe aspect of the disease was recorded. There may have been biases of ascertainment for each disease that was captured. It is possible that a relative of someone with SSc is more likely to be evaluated if they have RP or pulmonary complaints. The ICD-9 code for post-inflammatory disease/pulmonary fibrosis may not capture all cases of ILD. Additionally, we could have looked at other fibrotic and vasculopathy aspects of SSc, such as primary biliary cirrhosis or pulmonary hypertension. Similarly, we could have looked at other more common autoimmune inflammatory conditions, such as thyroid disease. It is likely that the cases with SSc were accurately diagnosed based on its unique physical properties, while less accuracy is expected with the autoimmune disorders. We pooled them in order to mitigate any effect this lower accuracy of specific diagnosis might have instilled. Analysis of each autoimmune disease separately may have better characterize the genetic component of each disease, but was not done to allow large enough numbers for calculation of RR.

In summary, this study uses the unique UPDB resource to examine the familial nature of SSc. Through its use, we have estimated RRs in SSc relatives, with a focus on RP, ILD, and other autoimmune diseases. We have shown that the presence of SSc in a first degree relative confers a significantly increased risk of SSc, RP, ILD, and other autoimmune diseases. Further, it suggests vasculopathy is the most important heritable component and fibrosis is less polygenic. This finding warrants attention for screening strategies aimed at early identification of SSc, with a focus on a personal and family history of RP and ILD. Further, studies performed on the high-risk pedigrees that have been identified in the UPDB could allow increased understanding of the specifics of these three components to SSc predisposition. Additionally, studying outpatient records for the presence of RP and subsequently examining cases of SSc might better clarify the risk that RP imparts on familial risk of developing SSc.

Acknowledgment

Partial support for all datasets within the Utah Population Database is provided by Huntsman Cancer Institute, University of Utah. The Skaggs Family Foundation provided funding for this project.

Dr. D. Khanna was supported by a National Institutes of Health Award (NIAMS K23 AR053858-03) and the Scleroderma Foundation (New Investigator Award).

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