The Application of Genetic Risk Scores in Rheumatic Diseases: A Perspective

Modest effect sizes have limited the clinical applicability of genetic associations with rheumatic diseases. Genetic risk scores (GRSs) have emerged as a promising solution to translate genetics into useful tools. In this review, we provide an overview of the recent literature on GRSs in rheumatic diseases. We describe six categories for which GRSs are used: (a) disease (outcome) prediction, (b) genetic commonalities between diseases, (c) disease differentiation, (d) interplay between genetics and environmental factors, (e) heritability and transferability, and (f) detecting causal relationships between traits. In our review of the literature, we identified current lacunas and opportunities for future work. First, the shortage of non-European genetic data restricts the application of many GRSs to European populations. Next, many GRSs are tested in settings enriched for cases that limit the transferability to real life. If intended for clinical application, GRSs are ideally tested in the relevant setting. Finally, there is much to elucidate regarding the co-occurrence of clinical traits to identify shared causal paths and elucidate relationships between the diseases. GRSs are useful instruments for this. Overall, the ever-continuing research on GRSs gives a hopeful outlook into the future of GRSs and indicates significant progress in their potential applications.

A partitioned 88-loci psoriasis genetic risk score reveals HLA and non-HLA contributions to clinical phenotypes in a Newfoundland psoriasis cohort

Psoriasis is an immune-mediated inflammatory skin disease typically characterized by erythematous and scaly plaques. It affects 3% of the Newfoundland population while only affecting 1.7% of the general Canadian population. Recent genome-wide association studies (GWAS) in psoriasis have identified more than 63 genetic susceptibility loci that individually have modest effects. Prior studies have shown that a genetic risk score (GRS) combining multiple loci can improve psoriasis disease prediction. However, these prior GRS studies have not fully explored the association of GRS with patient clinical characteristics. In this study, we calculated three types of GRS: one using all known GWAS SNPs (GRS-ALL), one using a subset of SNPs from the HLA region (GRS-HLA), and the last using non-HLA SNPs (GRS-noHLA). We examined the relationship between these GRS and a number of psoriasis features within a well characterized Newfoundland psoriasis cohort. We found that both GRS-ALL and GRS-HLA were significantly associated with early age of psoriasis onset, psoriasis severity, first presentation of psoriasis at the elbow or knee, and the total number of body locations affected, while only GRS-ALL was associated with a positive family history of psoriasis. GRS-noHLA was uniquely associated with genital psoriasis. These findings clarify the relationship of the HLA and non-HLA components of GRS with important clinical features of psoriasis.

Relationship Between a Vitamin D Genetic Risk Score and Autoantibodies Among First-Degree Relatives of Probands With Rheumatoid Arthritis and Systemic Lupus Erythematosus

Objective

Higher 25-hydroxyvitamin D (25(OH)D) levels have been associated with reduced risk for autoimmune diseases and are influenced by vitamin D metabolism genes. We estimated genetically-determined vitamin D levels by calculating a genetic risk score (GRS) and investigated whether the vitamin D GRS was associated with the presence of autoantibodies related to rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) in those at increased risk for developing RA and SLE, respectively.

Methods

In this cross-sectional study, we selected autoantibody positive (aAb+) and autoantibody negative (aAb-) individuals from the Studies of the Etiologies of Rheumatoid Arthritis (SERA), a cohort study of first-degree relatives (FDRs) of individuals with RA (189 RA aAb+, 181 RA aAb-), and the Lupus Family Registry and Repository (LFRR), a cohort study of FDRs of individuals with SLE (157 SLE aAb+, 185 SLE aAb-). Five SNPs known to be associated with serum 25(OH)D levels were analyzed individually as well as in a GRS: rs4588 (GC), rs12785878 (NADSYN1), rs10741657 (CYP2R1), rs6538691 (AMDHD1), and rs8018720 (SEC23A).

Results

Both cohorts had similar demographic characteristics, with significantly older and a higher proportion of males in the aAb+ FDRs. The vitamin D GRS was inversely associated with RA aAb+ (OR = 0.85, 95% CI = 0.74-0.99), suggesting a possible protective factor for RA aAb positivity in FDRs of RA probands. The vitamin D GRS was not associated with SLE aAb+ in the LFRR (OR = 1.09, 95% CI = 0.94-1.27). The SEC23A SNP was associated with RA aAb+ in SERA (OR = 0.65, 95% CI = 0.43-0.99); this SNP was not associated with SLE aAb+ in LFRR (OR = 1.41, 95% CI = 0.90 - 2.19).

Conclusion

Genes associated with vitamin D levels may play a protective role in the development of RA aAbs in FDRs of RA probands, perhaps through affecting lifelong vitamin D status. The GRS and the SEC23A SNP may be of interest for future investigation in pre-clinical RA. In contrast, these results do not support a similar association in SLE FDRs, suggesting other mechanisms involved in the relationship between vitamin D and SLE aAbs not assessed in this study.

Genetically-Guided Medical Nutrition Therapy in Type 2 Diabetes Mellitus and Pre-diabetes: A Series of n-of-1 Superiority Trials

Type 2 diabetes mellitus (T2DM) is a heterogeneous metabolic disorder of multifactorial etiology that includes genetic and dietary influences. By addressing the latter, medical nutrition therapy (MNT) contributes to the management of T2DM or pre-diabetes toward achieving glycaemic control and improved insulin sensitivity. However, the clinical outcomes of MNT vary and may further benefit from personalized nutritional plans that take into consideration genetic variations associated with individual responses to macronutrients. The aim of the present series of n-of-1 trials was to assess the effects of genetically-guided vs. conventional MNT on patients with pre-diabetes or T2DM. A quasi-experimental, cross-over design was adopted in three Caucasian adult men with either diagnosis. Complete diet, bioclinical and anthropometric assessment was performed and a conventional MNT, based on the clinical practice guidelines was applied for 8 weeks. After a week of “wash-out,” a precision MNT was prescribed for an additional 8-week period, based on the genetic characteristics of each patient. Outcomes of interest included changes in body weight (BW), fasting plasma glucose (FPG), and blood pressure (BP). Collectively, the trials indicated improvements in BW, FPG, BP, and glycosylated hemoglobin (HbA1c) following the genetically-guided precision MNT intervention. Moreover, both patients with pre-diabetes experienced remission of the condition. We conclude that improved BW loss and glycemic control can be achieved in patients with pre-diabetes/T2DM, by coupling MNT to their genetic makeup, guiding optimal diet, macronutrient composition, exercise and oral nutrient supplementation in a personalized manner.

Prognostic value of leukocyte telomere length in renal cell carcinoma patients

Telomeres play important roles in cancer initiation and progression. Leukocyte telomere length (LTL) can modulate cancer risk and outcome. We hypothesize that genetically predicted short LTL is associated with worse prognosis in renal cell carcinoma (RCC). A total of 1,086 histologically confirmed RCC patients were included in this study. A weighted genetic risk score (GRS) predictive of LTL was constructed using 10 confirmed LTL-associated single nucleotide polymorphisms (SNPs). The associations of individual SNPs and GRS with recurrence and survival were determined by multivariate Cox proportional hazards analysis. In individual SNP analysis, long LTL-associated allele of rs7675998 in NAF1 gene at chromosome 4 was significantly associated with a reduced risk of recurrence (HR=0.85, 95% CI, 0.73-0.99, P=0.043), while the long LTL-associated allele of rs10936599 in TERC at chromosome 3 conferred a reduced risk of death (HR=0.85, 95% CI, 0.73-1.00, P=0.047). More importantly, genetically predicted LTL was associated with both recurrence and survival. Dichotomized at the median value of GRS, patients with low GRS (indicating short LTL) exhibited significantly increased risks of recurrence (HR=1.26, 95% CI, 1.03-1.54, P=0.025) and death (HR=1.23, 95% CI, 1.00-1.50, P=0.045). Hence, we concluded that genetically predicted short LTL is associated with worse prognosis in RCC patients.

Multi-Locus Models to Address Hb F Variability in Portuguese β-Thalassemia Carriers

Hb F production is under the influence of major quantitative trait loci (QTL). The present study aims: i) to replicate the association with Hb F for representative genetic variants in the three major Hb F QTLs in a Portuguese sample of β-thalassemia (β-thal) carriers; and ii) to test different genetic multi-locus models to account for the genetic component of Hb F variation. A population sample of 79 Portuguese β-thal carriers (39 males, 40 females), aged between 2 to 70 years old, were genotyped for polymorphisms in the locus control region (LCR)-5' hypersensitive site 4 (5'HS4) rs16912979, XmnI-HBG2 rs7482144, BCL11A rs1427407 and HMIP rs66650371, using standard biomolecular procedures. Univariate linear regression models were used to test for genetic associations with Hb F. The minor alleles of the individual variants BCL11A rs1427407 (T) (0.165), HMIP rs66650371 (3 bp del) (0.247) and XmnI-HBG2 rs7482144 (T) (0.196), were found to be significantly associated with increased levels of Hb F (p = 0.029, p = 0.002 and p = 0.0004, respectively), explaining about 6.0, 12.0 and 15.0% of Hb F variation, respectively. In a multiple linear regression approach, the three loci accounted for about 30.0% of Hb F variance. Two genetic risk scores (GRS), rationalizing the number of minor alleles into a single genetic variable, explained about 30.0 and 32.0% of the Hb F variation. In conclusion, we replicated in β-thal carriers previously reported associations with Hb F. Multi-locus models combining three representative variants of Hb F influencing QTLs can explain a larger amount of Hb F variability.

Performance of FRAX in Predicting Fractures in US Postmenopausal Women with Varied Race and Genetic Profiles

BACKGROUND

Whether the Fracture Risk Assessment Tool (FRAX) performed differently in estimating the 10-year fracture probability in women of different genetic profiling and race remained unclear.

METHODS

The genomic data in the Women's Health Initiative (WHI) study was analyzed (n = 23,981). The genetic risk score (GRS) was calculated from 14 fracture-associated single nucleotide polymorphisms (SNPs) for each participant. FRAX without bone mineral density (BMD) was used to estimate fracture probability.

RESULTS

FRAX significantly overestimated the risk of major osteoporotic fracture (MOF) in the WHI study. The most significant overestimation was observed in women with low GRS (predicted/observed ratio (POR): 1.61, 95% CI: 1.45-1.79) specifically Asian women (POR: 3.5, 95% CI 2.48-4.81) and in African American women (POR: 2.59, 95% CI: 2.33-2.87). Compared to the low GRS group, the 10-year probability of MOF adjusted for the FRAX score was 21% and 30% higher in the median GRS group and high GRS group, respectively. Asian, African American, and Hispanic women respectively had a 78%, 76%, and 56% lower hazard than Caucasian women after the FRAX score was adjusted. The results were similar for hip fractures.

CONCLUSIONS

Our study suggested the FRAX performance varies significantly by both genetic profile and race in postmenopausal women.

Concept and benchmarks for assessing narrow-sense validity of genetic risk score values

BACKGROUND

While higher genetic risk score (GRS) has been statistically associated with increased disease risk (broad-sense validity), the concept and tools for assessing the validity of reported GRS values from tests (narrow-sense validity) are underdeveloped.

METHODS

We propose two benchmarks for assessing the narrow-sense validity of GRS. The baseline benchmark requires that the mean GRS value in a general population approximates 1.0. The calibration benchmark assesses the agreement between observed risks and estimated risks (GRS values). We assessed benchmark performance for three prostate cancer (PCa) GRS tests, derived from three SNP panels with increasing stringency of selection criteria, in a PCa chemoprevention trial where 714 of 3225 men were diagnosed with PCa during the 4-year follow-up.

RESULTS

GRS from Panels 1, 2, and 3 were all statistically associated with PCa risk; P = 5.58 × 10^-3 , P = 1 × 10^-3 , and P = 1.5 × 10^-13 , respectively (broad-sense validity). For narrow-sense validity, the mean GRS value among men without PCa was 1.33, 1.09, and 0.98 for Panels 1, 2, and 3, respectively (baseline benchmark). For assessing the calibration benchmark, observed risks were calculated for seven groups of men with GRS values <0.3, 0.3-0.79, 0.8-1.19, 1.2-1.49, 1.5-1.99, 2-2.99, and ≥3. The calibration slope (higher is better) was 0.15, 0.12, and 0.60, and the bias score (lower is better) between the observed risks and GRS values was 0.08, 0.08, and 0.02 for Panels 1, 2, and 3, respectively.

CONCLUSION

Performance differed considerably among GRS tests. We recommend that all GRS tests be evaluated using the two benchmarks before clinical implementation for individual risk assessment.

Modeling Gene-Environment Interaction for the Risk of Non-hodgkin Lymphoma

Background: Non-hodgkin lymphoma (NHL) is one of the most common and deadly cancers. There is limited analysis of gene-environment interactions for the risk of NHL. This study intends to explore the interactions between genetic variants and environmental factors, and how they contribute to NHL risk.

Methods: A case-control study was performed in Shanghai, China. The cases were diagnosed between 2003 and 2008 with patients aged 18 years or older. Samples and SNPs which did not satisfy quality control were excluded from the analysis. Weighted and unweighted genetic risk scores (GRS) and environmental risk scores were generated using clustering analysis algorithm. Univariate and multivariable logistic regression analyses were conducted. Moreover, genetics and environment interactions (G × E) were tested on the NHL cases and controls.

Results: After quality control, there are 22 SNPs, 11 environmental variables and 5 demographical variables to be explored. For logistic regression analyses, 5 SNPs (rs1800893, rs4251961, rs1800630, rs13306698, rs1799931) and environmental tobacco smoking showed statistically significant associations with the risk of NHL. Odds ratio (OR) and 95% confidence interval (CI) was 10.82 (4.34–28.88) for rs13306698, 2.84 (1.66–4.95) for rs1800893, and 2.54 (1.43–4.58) for rs4251961. For G × E analysis, the interaction between smoking and dichotomized weighted GRS showed statistically significant association with NHL (OR = 0.23, 95% CI = [0.09, 0.61]).

Conclusions: Several genetic and environmental risk factors and their interactions associated with the risk of NHL have been identified. Replication in other cohorts is needed to validate the results.

Genetic variants determining body fat distribution and sex hormone-binding globulin among Chinese female young adults

BACKGROUND

Measures of body fat distribution (i.e. waist : hip ratio [WHR]) are major risk factors for diabetes, independent of overall adiposity. The genetic variants related to body fat distribution show sexual dimorphism and particularly affect females. Substantial literature supports a role for sex hormone-binding globulin (SHBG) in the maintenance of glucose homeostasis. The aim of the present study was to examine the association of the genetic risk score of body fat distribution with SHBG levels and insulin resistance in young (14-30 years) Chinese females.

METHODS

In all, 675 young Chinese females were evaluated in the present study. A genetic risk score (GRS) was calculated on the basis of 12 established variants associated with body fat distribution. The main outcome variable was serum SHBG levels and homeostasis model assessment of insulin resistance (HOMA-IR).

RESULTS

The GRS of body fat distribution was significantly associated with decreasing serum SHBG levels (P = 0.018), independent of body mass index and WHR. In addition, the GRS and SHBG showed additive effects on HOMA-IR (P = 0.004).

CONCLUSIONS

The GRS of body fat distribution reflects serum SHBG levels, and the GRS and SHBG jointly influence the risk of insulin resistance.

Evaluation of genetic risk score models in the presence of interaction and linkage disequilibrium

In the area of genetic epidemiology, genetic risk predictive modeling is becoming an important area of translational success. As an increasing number of genetic variants are successfully discovered, the use of multiple genetic variants in constructing a genetic risk score (GRS) for modeling has been widely applied using a variety of approaches. Previously, we compared the performance of a simple, additive GRS with weighted GRS approaches, but our initial simulation experiment assumed very simple models without many of the complications found in real genetic studies. In particular, interactions between variants and linkage disequilibrium (LD) (indirect mapping) remain important and challenging problems for GRS modeling. In the present study, we applied two simulation strategies to mimic various types of epistasis to evaluate their impact on the performance of the GRS models. We simulated a range of models demonstrating statistical interaction and linkage disequilibrium. Three genetic risk models were compared in terms of power, type I error, C-statistic and AIC, including a simple count GRS (SC-GRS), an odds ratio weighted GRS (OR-GRS) and an explained variance weighted GRS (EV-GRS). Simulation factors of interest included allele frequencies, effect sizes, strengths of interaction, degrees of LD and heritability. We extensively examined the extent to how these interactions could influence the performance of genetic risk models. Our results show that the weighted methods outperform simple count method in general even if interaction or LD is present, with well controlled type I error.

Prediction of Colorectal Cancer Risk Using a Genetic Risk Score: The Korean Cancer Prevention Study-II (KCPS-II)

Colorectal cancer (CRC) is among the leading causes of cancer deaths and can be caused by environmental factors as well as genetic factors. Therefore, we developed a prediction model of CRC using genetic risk scores (GRS) and evaluated the effects of conventional risk factors, including family history of CRC, in combination with GRS on the risk of CRC in Koreans. This study included 187 cases (men, 133; women, 54) and 976 controls (men, 554; women, 422). GRS were calculated with most significantly associated single-nucleotide polymorphism with CRC through a genomewide association study. The area under the curve (AUC) increased by 0.5% to 5.2% when either counted or weighted GRS was added to a prediction model consisting of age alone (AUC 0.687 for men, 0.598 for women) or age and family history of CRC (AUC 0.692 for men, 0.603 for women) for both men and women. Furthermore, the risk of CRC significantly increased for individuals with a family history of CRC in the highest quartile of GRS when compared to subjects without a family history of CRC in the lowest quartile of GRS (counted GRS odds ratio [OR], 47.9; 95% confidence interval [CI], 4.9 to 471.8 for men; OR, 22.3; 95% CI, 1.4 to 344.2 for women) (weighted GRS OR, 35.9; 95% CI, 5.9 to 218.2 for men; OR, 18.1, 95% CI, 3.7 to 88.1 for women). Our findings suggest that in Koreans, especially in Korean men, GRS improve the prediction of CRC when considered in conjunction with age and family history of CRC.