Gene-level association analysis of systemic sclerosis: A comparison of African-Americans and White populations

All authors: Olga Y. Gorlova , Yafang Li, Ivan Gorlov, Jun Ying, Wei V. Chen, Shervin Assassi, John D. Reveille, Frank C. Arnett, Xiaodong Zhou, Lara Bossini-Castillo, Elena Lopez-Isac, Marialbert Acosta-Herrera, Peter K. Gregersen, Annette T. Lee, Virginia D. Steen, Barri J. Fessler, Dinesh Khanna, Elena Schiopu, Richard M. Silver, Jerry A. Molitor, Daniel E. Furst, Suzanne Kafaja, Robert W. Simms, Robert A. Lafyatis, Patricia Carreira, Carmen Pilar Simeon, Ivan Castellvi, Emma Beltran, Norberto Ortego, Christopher I. Amos, Javier Martin, Maureen D. Mayes.Data Availability Statement: Genetic data is available from dbGaP repository (https://www.ncbi. nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_ id=phs000357.v1.p1).Gene-level analysis of ImmunoChip or genome-wide association studies (GWAS) data has not been previously reported for systemic sclerosis (SSc, scleroderma). The objective of this study was to analyze genetic susceptibility loci in SSc at the gene level and to determine if the detected associations were shared in African-American and White populations, using data from ImmunoChip and GWAS genotyping studies. The White sample included 1833 cases and 3466 controls (956 cases and 2741 controls from the US and 877 cases and 725 controls from Spain) and the African American sample, 291 cases and 260 controls. In both Whites and African Americans, we performed a gene-level analysis that integrates association statistics in a gene possibly harboring multiple SNPs with weak effect on disease risk, using Versatile Gene-based Association Study (VEGAS) software. The SNP-level analysis was performed using PLINK v.1.07. We identified 4 novel candidate genes (STAT1, FCGR2C, NIPSNAP3B, and SCT) significantly associated and 4 genes (SERBP1, PINX1, TMEM175 and EXOC2) suggestively associated with SSc in the gene level analysis in White patients. As an exploratory analysis we compared the results on Whites with those from African Americans. Of previously established susceptibility genes identified in Whites, only TNFAIP3 was significant at the nominal level (p = 6.13x10-3) in African Americans in the gene-level analysis of the ImmunoChip data. Among the top suggestive novel genes identified in Whites based on the ImmunoChip data, FCGR2C and PINX1 were only nominally significant in African Americans (p = 0.016 and p = 0.028, respectively), while among the top novel genes identified in the gene-level analysis in African Americans, UNC5C (p = 5.57x10-4) and CLEC16A (p = 0.0463) were also nominally significant in Whites. We also present the gene-level analysis of SSc clinical and autoantibody phenotypes among Whites. Our findings need to be validated by independent studies, particularly due to the limited sample size of African Americans.Funding was provided to MDM by the National Institutes of Health (NIH) the National Institute of Arthritis, Musculoskeletal and Skin Diseases (NIAMS https://www.niams.nih.gov/) Centers of Research Translation (CORT) P50-AR054144, NIH grant N01-AR-02251 and R01-AR-055258, and the Department of Defense (DD) Congressionally Directed Medical Research Program (http://cdmrp.army.mil/) W81XWH-07-1-011 and WX81XWH-13-1-0452 for the collection, analysis and interpretation of the data

Frequency binned distributions of the risk alleles for different common diseases.

<p>F—frequency of the risk-associated allele. Area under each curve equals 1. Black line shows the distribution expected under the assumption that the probability of the allele to be risk associated is independent of its frequency. a) Proportions of the risk alleles in the 5 frequency categories for diseases stratified by the ELI tertiles. b) Proportions of the risk alleles for 3 individual diseases from the first tertile (environment/lifestyle independent diseases). c) Distributions of risk alleles for 3 individual diseases from the third ELI tertile (environment/lifestyle dependent diseases). d) Proportions of the risk alleles averaged for the 3 environment/lifestyle dependent (red line) and 3 environment/lifestyle independent (blue line) diseases.</p

Allelic Spectra of Risk SNPs Are Different for Environment/Lifestyle Dependent versus Independent Diseases

<div><p>Genome-wide association studies (GWAS) have generated sufficient data to assess the role of selection in shaping allelic diversity of disease-associated SNPs. Negative selection against disease risk variants is expected to reduce their frequencies making them overrepresented in the group of minor (<50%) alleles. Indeed, we found that the overall proportion of risk alleles was higher among alleles with frequency <50% (minor alleles) compared to that in the group of major alleles. We hypothesized that negative selection may have different effects on environment (or lifestyle)-dependent versus environment (or lifestyle)-independent diseases. We used an environment/lifestyle index (ELI) to assess influence of environmental/lifestyle factors on disease etiology. ELI was defined as the number of publications mentioning “environment” or “lifestyle” AND disease per 1,000 disease-mentioning publications. We found that the frequency distributions of the risk alleles for the diseases with strong environmental/lifestyle components follow the distribution expected under a selectively neutral model, while frequency distributions of the risk alleles for the diseases with weak environmental/lifestyle influences is shifted to the lower values indicating effects of negative selection. We hypothesized that previously selectively neutral variants become risk alleles when environment changes. The hypothesis of ancestrally neutral, currently disadvantageous risk-associated alleles predicts that the distribution of risk alleles for the environment/lifestyle dependent diseases will follow a neutral model since natural selection has not had enough time to influence allele frequencies. The results of our analysis suggest that prediction of SNP functionality based on the level of evolutionary conservation may not be useful for SNPs associated with environment/lifestyle dependent diseases.</p></div

Environmental and lifestyle indexes (ELIs) for the GWAS-studied diseases.

<p>Environmental and lifestyle indexes (ELIs) for the GWAS-studied diseases.</p

Expected evolutionary dynamics of currently deleterious, recently neutral risk associated alleles.

<p>Upper panel shows the distribution of selection coefficients: negative values imply negative and positive values positive selection. A change in the environment or life style leads to changes in selective values of existing variants making some of previously neutral variants deleterious and others advantageous. The lower panel shows frequency distributions of risk alleles immediately after changes in environment/life style and after the negative selection took place.</p

Frequency binned distributions of the risk alleles for different common diseases.

<p>F—frequency of the risk-associated allele. Area under each curve equals 1. Black line shows the distribution expected under the assumption that the probability of the allele to be risk associated is independent of its frequency. a) Proportions of the risk alleles in the 5 frequency categories for diseases stratified by the ELI tertiles. b) Proportions of the risk alleles for 3 individual diseases from the first tertile (environment/lifestyle independent diseases). c) Distributions of risk alleles for 3 individual diseases from the third ELI tertile (environment/lifestyle dependent diseases). d) Proportions of the risk alleles averaged for the 3 environment/lifestyle dependent (red line) and 3 environment/lifestyle independent (blue line) diseases.</p

Proportions of minor risk alleles (MiRA) in GWAS studied diseases.

<p>Proportions of minor risk alleles (MiRA) in GWAS studied diseases.</p

The proportions of minor risk alleles (MiRA) in the first, second and third tertiles defined based on the environment/lifestyle index (ELI).

<p>The proportions of minor risk alleles (MiRA) in the first, second and third tertiles defined based on the environment/lifestyle index (ELI).</p

The estimates of model parameters, with asymptotic confidence intervals.

<p>*Assuming exponential tumor growth and the estimates of K and θ, the average tumor growth rate E(λ) corresponds to a doubling time of 55 to 60 days.</p

Proportions of SNPs with the signature of recent positive selection on the most commonly used genotyping platforms.

<p>The red horizontal line shows the proportion of SNPs with signature of recent positive selection among GWAS-detected SNPs associated with risk of common human diseases.</p