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Abstract Number: 650

Parental Influence On Systemic Sclerosis

Tracy M. Frech1, Richard Pimentel2, Allen D. Sawitzke3, Gopi Penmetsa4 and Jathine Wong2, 1Internal Medicine, Salt Lake City VAMC, Salt Lake, UT, 2University of Utah, Salt Lake, UT, 3Rheumatology, University of Utah Medical Ctr, Salt Lake City, UT, 4Rheumatology Division, University Of Utah Hospital, Salt lake City, UT

Meeting: 2013 ACR/ARHP Annual Meeting

Keywords: epidemiologic methods and systemic sclerosis, Inheritance

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Session Information

Title: Systemic Sclerosis, Fibrosing Syndromes and Raynaud's I

Session Type: Abstract Submissions (ACR)

Background/Purpose: A genealogic resource, the Utah Population Database (UPDB) has successfully identified systemic sclerosis (SSc) pedigrees and hereditable risk for this disease (1).  We hypothesized that these pedigrees could be used to assess parental influence on a SSc proband by (a) examination of mitochondrial inheritance; (b) birth order (a possible surrogate marker for microchimerism); and (c) paternal age at conception (a possible surrogate marker for telomere erosion).

Methods: SSc was defined by ICD-9 710.1 and ICD-10 34.0, 34.1, and 34.9, and identified from statewide discharge data, the University of Utah Health Science Center Enterprise Data Warehouse, and death certificates and were linked to the UPDB for analysis. Mitochondrial inheritance was evaluated by familial standardized incidence ratio (FSIR). Chi squared test and logistic regression was used to evaluate birth order and maternal/paternal age at conception of the SSc proband.

Results: A software kinship analysis tool (KAT) was used to analyze 1949 unique SSc patients and 5 controls per case (9115), which were matched by birth year. Comparing the result of using mitochondrial pedigrees (MP) with autosomal pedigrees (AP), both pedigrees yield similar result in Cox proportional hazard regression model to predict relative risk as a function of fsir, lfsir log of ( 1+fsir), llfsir, log of (1+ log(1+ lfsir)), and eb empirical Bayes adjustment to llfsir (2). Both MP and AP have a RR of 1.00 for fsir. MP has a RR of 1.43 for eb, and AP has a similar RR of 1.37 for eb. MP has a very low population-attributable risk, PAR value, 0.03, where AP has a higher value of 0.11 to 0.13. It suggested approximately 3% of the population who has SSc could be from mitochondrial inheritance, whereas 13% of the population who has SSc are familial. Thus, there is no indication of SSc is caused by mitochondrial inheritance.

We compared the affected and the unaffected individuals in each birth order group, and the distribution showed from birth order group 1 to 9, they were almost evenly distributed, affected was approximately 16 to 17%, and the unaffected was approximately 83 to 84% of each of these birth order groups. Chi Square test result shows an insignificant p value of 0.738. Since some of the table cell expected values are below 5, we re-examined the dataset using a logistic regression generalized linear model which confirmed there were no differences in the birth order of the groups in the study.

A multivariate logistic regression model with 3 covariates, birth order, father’s age at conception, and mother’s age at conception indicate all 3 covariates do not increase the odds for having the disease.

Covariate

RR

Lower Level CI

Upper Level CI

P-value

Birth Order

1.03

0.98

1.08

0.246

Father’s age of conceived

0.998

0.951

1.05

0.939

Mother’s age of conceived

0.997

0.945

1.05

0.913

Conclusion:

The UPDB is a resource that allows for meaningful inheritance analysis. These data suggest that while increased inheritance of SSc is seen, patterns suggesting mitochondrial inheritance, birth order (microchimerism), and parental age at conception of a SSc proband are not likely responsible for pathogenesis.


Disclosure:

T. M. Frech,
None;

R. Pimentel,
None;

A. D. Sawitzke,
None;

G. Penmetsa,
None;

J. Wong,
None.

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