Generating genetic risk scores from intermediate phenotypes for use in association studies of clinically significant endpoints

Pathway-Specific Polygenic Risk Scores Identify Obstructive Sleep Apnea-Related Pathways Differentially Moderating Genetic Susceptibility to Coronary Artery Disease

BACKGROUND

Obstructive sleep apnea (OSA) and its features, such as chronic intermittent hypoxia, may differentially affect specific molecular pathways and processes in the pathogenesis of coronary artery disease (CAD) and influence the subsequent risk and severity of CAD events. In particular, competing adverse (eg, inflammatory) and protective (eg, increased coronary collateral blood flow) mechanisms may operate, but remain poorly understood. We hypothesize that common genetic variation in selected molecular pathways influences the likelihood of CAD events differently in individuals with and without OSA, in a pathway-dependent manner.

METHODS

We selected a cross-sectional sample of 471 877 participants from the UK Biobank, with 4974 ascertained to have OSA, 25 988 to have CAD, and 711 to have both. We calculated pathway-specific polygenic risk scores for CAD, based on 6.6 million common variants evaluated in the CARDIoGRAMplusC4D genome-wide association study (Coronary ARtery DIsease Genome wide Replication and Meta-analysis [CARDIoGRAM] plus The Coronary Artery Disease [C4D] Genetics), annotated to specific genes and pathways using functional genomics databases. Based on prior evidence of involvement with intermittent hypoxia and CAD, we tested pathway-specific polygenic risk scores for the HIF1 (hypoxia-inducible factor 1), VEGF (vascular endothelial growth factor), NFκB (nuclear factor kappa-light-chain-enhancer of activated B cells) and TNF (tumor necrosis factor) signaling pathways.

RESULTS

In a multivariable-adjusted logistic generalized additive model, elevated pathway-specific polygenic risk scores for the Kyoto Encyclopedia of Genes and Genomes VEGF pathway (39 genes) associated with protection for CAD in OSA (interaction odds ratio 0.86, P=6×10-4). By contrast, the genome-wide CAD PRS did not show evidence of statistical interaction with OSA.

CONCLUSIONS

We find evidence that pathway-specific genetic risk of CAD differs between individuals with and without OSA in a qualitatively pathway-dependent manner. These results provide evidence that gene-by-environment interaction influences CAD risk in certain pathways among people with OSA, an effect that is not well-captured by the genome-wide PRS. This invites further study of how OSA interacts with genetic risk at the molecular level and suggests eventual personalization of OSA treatment to reduce CAD risk according to individual pathway-specific genetic risk profiles.

Chronic air pollution-induced subclinical airway inflammation and polygenic susceptibility

Background

Air pollutants can activate low-grade subclinical inflammation which further impairs respiratory health. We aimed to investigate the role of polygenic susceptibility to chronic air pollution-induced subclinical airway inflammation.

Methods

We used data from 296 women (69–79 years) enrolled in the population-based SALIA cohort (Study on the influence of Air pollution on Lung function, Inflammation and Aging). Biomarkers of airway inflammation were measured in induced-sputum samples at follow-up investigation in 2007–2010. Chronic air pollution exposures at residential addresses within 15 years prior to the biomarker assessments were used to estimate main environmental effects on subclinical airway inflammation. Furthermore, we calculated internally weighted polygenic risk scores based on genome-wide derived single nucleotide polymorphisms. Polygenic main and gene-environment interaction (GxE) effects were investigated by adjusted linear regression models.

Results

Higher exposures to nitrogen dioxide (NO₂), nitrogen oxides (NO_x), particulate matter with aerodynamic diameters of ≤ 2.5 μm, ≤ 10 μm, and 2.5–10 µm significantly increased the levels of leukotriene (LT)B₄ by 19.7% (p-value = 0.005), 20.9% (p = 0.002), 22.1% (p = 0.004), 17.4% (p = 0.004), and 23.4% (p = 0.001), respectively. We found significant effects of NO₂ (25.9%, p = 0.008) and NO_x (25.9%, p-value = 0.004) on the total number of cells. No significant GxE effects were observed. The trends were mostly robust in sensitivity analyses.

Conclusions

While this study confirms that higher chronic exposures to air pollution increase the risk of subclinical airway inflammation in elderly women, we could not demonstrate a significant role of polygenic susceptibility on this pathway. Further studies are required to investigate the role of polygenic susceptibility.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-022-02179-3.

Genetic Risk Score for Coronary Heart Disease: Review

The present review deals with the stages of creation, methods of calculation, and the use of a genetic risk score for coronary heart disease in various populations. The concept of risk factors is generally recognized on the basis of the results of epidemiological studies in the 20th century; according to this concept, the high prevalence of diseases of the circulatory system is due to lifestyle characteristics and associated risk factors. An important and relevant task for the healthcare system is to identify the population segments most susceptible to cardiovascular diseases (CVDs). The level of individual risk of an unfavorable cardiovascular prognosis is determined by genetic factors in addition to lifestyle factors.

Cumulative Influence of Inflammatory Response Genetic Variation on Long-Term Neurobehavioral Outcomes after Pediatric Traumatic Brain Injury Relative to Orthopedic Injury: An Exploratory Polygenic Risk Score

The addition of genetic factors to prognostic models of neurobehavioral recovery following pediatric traumatic brain injury (TBI) may account for unexplained heterogeneity in outcomes. The present study examined the cumulative influence of candidate genes involved in the inflammatory response on long-term neurobehavioral recovery in children with early childhood TBI relative to children with orthopedic injuries (OI). Participants were drawn from a prospective, longitudinal study evaluating outcomes of children who sustained TBI (n = 67) or OI (n = 68) between the ages of 3 and 7 years. Parents completed ratings of child executive function and behavior at an average of 6.8 years after injury. Exploratory unweighted and weighted polygenic risk scores (PRS) were constructed from single nucleotide polymorphisms (SNPs) across candidate inflammatory response genes (i.e., angiotensin converting enzyme [ACE], brain-derived neurotrophic factor [BDNF], interleukin-1 receptor antagonist [IL1RN], and 5'-ectonucleotidase [NT5E]) that showed nominal (p ≤ 0.20) associations with outcomes in the TBI group. Linear regression models tested the PRS × injury group (TBI vs. OI) interaction term and post-hoc analyses examined the effect of PRS within each injury group. Higher inflammatory response PRS were associated with more executive dysfunction and behavior problems in children with TBI but not in children with OI. The cumulative influence of inflammatory response genes as measured by PRS explained additional variance in long-term neurobehavioral outcomes, over and above well-established predictors and single candidate SNPs tested individually. The results suggest that some of the unexplained heterogeneity in long-term neurobehavioral outcomes following pediatric TBI may be attributable to a child's genetic predisposition to a greater or lesser inflammatory response to TBI.

The impact of phenotype, ethnicity and genotype on progression of type 2 diabetes mellitus

AIM

To conduct a comprehensive review of studies of glycaemic deterioration in type 2 diabetes and identify the major factors influencing progression.

METHODS

We conducted a systematic literature search with terms linked to type 2 diabetes progression. All the included studies were summarized based upon the factors associated with diabetes progression and how the diabetes progression was defined.

RESULTS

Our search yielded 2785 articles; based on title, abstract and full-text review, we included 61 studies in the review. We identified seven criteria for diabetes progression: 'Initiation of insulin', 'Initiation of oral antidiabetic drug', 'treatment intensification', 'antidiabetic therapy failure', 'glycaemic deterioration', 'decline in beta-cell function' and 'change in insulin dose'. The determinants of diabetes progression were grouped into phenotypic, ethnicity and genotypic factors. Younger age, poorer glycaemia and higher body mass index at diabetes diagnosis were the main phenotypic factors associated with rapid progression. The effect of genotypic factors on progression was assessed using polygenic risk scores (PRS); a PRS constructed from the genetic variants linked to insulin resistance was associated with rapid glycaemic deterioration. The evidence of impact of ethnicity on progression was inconclusive due to the small number of multi-ethnic studies.

CONCLUSION

We have identified the major determinants of diabetes progression-younger age, higher BMI, higher HbA1c and genetic insulin resistance. The impact of ethnicity is uncertain; there is a clear need for more large-scale studies of diabetes progression in different ethnic groups.

Identification of female-specific genetic variants for metabolic syndrome and its component traits to improve the prediction of metabolic syndrome in females

Background

Metabolic syndrome (MetS), defined as a cluster of metabolic risk factors including dyslipidemia, insulin-resistance, and elevated blood pressure, has been known as partly heritable. MetS effects the lives of many people worldwide, yet females have been reported to be more vulnerable to this cluster of risks.

Methods

To elucidate genetic variants underlying MetS specifically in females, we performed a genome-wide association study (GWAS) for MetS as well as its component traits in a total of 9932 Korean female subjects (including 2276 MetS cases and 1692 controls). To facilitate the prediction of MetS in females, we calculated a genetic risk score (GRS) combining 14 SNPs detected in our GWA analyses specific for MetS.

Results

GWA analyses identified 14 moderate signals (P_meta < 5X10^− 5) specific to females for MetS. In addition, two genome-wide significant female-specific associations (P_meta < 5X10^− 8) were detected for rs455489 in DSCAM for fasting plasma glucose (FPG) and for rs7115583 in SIK3 for high-density lipoprotein cholesterol (HDLC). Logistic regression analyses (adjusted for area and age) between the GRS and MetS in females indicated that the GRS was associated with increased prevalence of MetS in females (P = 5.28 × 10^− 14), but not in males (P = 3.27 × 10^− 1). Furthermore, in the MetS prediction models using GRS, the area under the curve (AUC) of the receiver operating characteristics (ROC) curve was higher in females (AUC = 0.85) than in males (AUC = 0.57).

Conclusion

This study highlights new female-specific genetic variants associated with MetS and its component traits and suggests that the GRS of MetS variants is a likely useful predictor of MetS in females.

Electronic supplementary material

The online version of this article (10.1186/s12881-019-0830-y) contains supplementary material, which is available to authorized users.

Assessing the Genetic Correlations Between Blood Plasma Proteins and Osteoporosis: A Polygenic Risk Score Analysis

Osteoporosis is a common metabolic bone disease. The impact of global blood plasma proteins on the risk of osteoporosis remains elusive now. We performed a large-scale polygenic risk score (PRS) analysis to evaluate the potential effects of blood plasma proteins on the development of osteoporosis in 2286 Caucasians, including 558 males and 1728 females. Bone mineral density (BMD) and bone areas at ulna & radius, hip, and spine were measured using Hologic 4500W DXA. BMD/bone areas values were adjusted for age, sex, height, and weight as covariates. Genome-wide SNP genotyping of 2286 Caucasian subjects was performed using Affymetrix Human SNP Array 6.0. The 267 blood plasma proteins-associated SNP loci and their genetic effects were obtained from recently published genome-wide association study (GWAS) using a highly multiplexed aptamer-based affinity proteomics platform. The polygenetic risk score (PRS) of study subjects for each blood plasma protein was calculated from the genotypes data of the 2286 Caucasian subjects by PLINK software. Pearson correlation analysis of individual PRS values and BMD/bone area value was performed using R. Additionally, gender-specific analysis also was performed by Pearson correlation analysis. 267 blood plasma proteins were analyzed in this study. For BMD, we observed association signals between 41 proteins and BMD, mainly including whole body total BMD versus Factor H (p value = 9.00 × 10^-3), whole body total BMD versus BGH3 (p value = 1.40 × 10^-2), spine total BMD versus IGF-I (p value = 2.15 × 10^-2), and spine total BMD versus SAP (p value = 3.90 × 10^-2). As for bone areas, association evidence was observed between 45 blood plasma proteins and bone areas, such as ferritin versus spine area (p value = 1.90 × 10^-2), C4 versus hip area (p value = 1.25 × 10^-2), and hemoglobin versus right ulna and radius area (p value = 2.70 × 10^-2). Our study results suggest the modest impact of blood plasma proteins on the variations of BMD/bone areas, and identify several candidate blood plasma proteins for osteoporosis.

Abruptio placentae risk and genetic variations in mitochondrial biogenesis and oxidative phosphorylation: replication of a candidate gene association study

BACKGROUND

Abruptio placentae is a complex multifactorial disease that is associated with maternal and neonatal death and morbidity. Abruptio placentae's high recurrence rate, high prevalence of heritable thrombophilia among women with abruptio placentae, and aggregation of cases in families of women with the disease support the possibility of a genetic predisposition. Previous genome-wide and candidate gene association studies have identified single nucleotide polymorphisms in mitochondrial biogenesis and oxidative phosphorylation genes that potentially are associated with abruptio placentae risk. Perturbations in mitochondrial biogenesis and oxidative phosphorylation, which results in mitochondrial dysfunction, can lead to the impairment of differentiation and invasion of the trophoblast and to several obstetrics complications that include abruptio placentae.

OBJECTIVE

The purpose of this study was to determine whether the results of a candidate genetic association study that indicated a link between DNA variants (implicated in mitochondrial biogenesis and oxidative phosphorylation) and abruptio placentae could be replicated.

STUDY DESIGN

The study was conducted among participants (507 abruptio placentae cases and 1090 control subjects) of the Placental Abruption Genetic Epidemiology study. Weighted genetic risk scores were calculated with the use of abruptio placentae risk-increasing alleles of 11 single nucleotide polymorphisms in 9 mitochondrial biogenesis and oxidative phosphorylation genes (CAMK2B, NR1H3, PPARG, PRKCA, THRB, COX5A, NDUFA10, NDUFA12, and NDUFC2), which previously was reported in the Peruvian Abruptio Placentae Epidemiology study, a study with similar design and study population to the Placental Abruption Genetic Epidemiology study. Logistic regression models were fit to examine associations of weighted genetic risk scores (quartile 1, <25th percentile; quartile 2, 25-50th percentile; quartile 3, 50-70th percentile, and quartile 4, >75th percentile) with risk of abruptio placentae, adjusted for population admixture (the first 4 principal components), maternal age, infant sex, and preeclampsia. The weighted genetic risk score was also modeled as a continuous predictor. To assess potential effect modification, analyses were repeated among strata that were defined by preeclampsia status, maternal age (≥35 vs 18-34 years), and infant sex.

RESULTS

Abruptio placentae cases were more likely to have preeclampsia, shorter gestational age, and lower infant birthweight. Participants in quartile 2 (score, 12.6-13.8), quartile 3 (score, 13.9-15.0) and quartile 4 (score, ≥15.1) had a genetic risk score of 1.45-fold (95% confidence interval, 1.04-2.02; P=.03), a 1.42-fold (95% confidence interval, 1.02-1.98; P=.04), and a 1.75-fold (95% confidence interval, 1.27-2.42; P=7.0E-04) higher odds of abruptio placentae, respectively, compared with those in quartile 1 (score,<12.6; P-for trend=.0003). The risk of abruptio placentae was 1.12-fold (95% confidence interval, 1.05-1.19; P=3.0×10⁰⁴) higher per 1-unit increase in the score. Among women with preeclampsia, those in quartile 4 had a 3.92-fold (95% confidence interval, 1.48-10.36; P=.01) higher odds of abruptio placentae compared with women in quartile 1. Among normotensive women, women in quartile 4 had a 1.57-fold (95% confidence interval, 1.11-2.21; P=.01) higher odds of abruptio placentae compared with those in quartile 1 (P-for interaction=.12). We did not observe differences in associations among strata defined by maternal age or infant sex.

CONCLUSION

In this study, we replicated previous findings and provide strong evidence for DNA variants that encode for genes that are involved in mitochondrial biogenesis and oxidative phosphorylation pathways, which confers risk for abruptio placentae. These results shed light on the mechanisms that implicate DNA variants that encode for proteins in mitochondrial function that are responsible for abruptio placentae risk. Therapeutic efforts to reduce risk of abruptio placentae can be enhanced by improved biologic understanding of maternal mitochondrial biogenesis/oxidative phosphorylation pathways and identification of women who would be at high risk for abruptio placentae.

Pre-pregnancy or first-trimester risk scoring to identify women at high risk of preterm birth

Objective To develop a pre-pregnancy or first-trimester risk score to identify women at high risk of preterm birth. Study design In this retrospective cohort analysis, the sample was drawn from California singleton livebirths from 2007 to 2012 with linked birth certificate and hospital discharge records. The dataset was divided into a training (2/3 of sample) and a testing (1/3 of sample) set for discovery and validation. Predictive models for preterm birth using pre-pregnancy or first-trimester maternal factors were developed using backward stepwise logistic regression on a training dataset. A risk score for preterm birth was created for each pregnancy using beta-coefficients for each maternal factor remaining in the final multivariable model. Risk score utility was replicated in a testing dataset and by race/ethnicity and payer for prenatal care. Results The sample included 2,339,696 pregnancies divided into training and testing datasets. Twenty-three maternal risk factors were identified including several that were associated with a two or more increased odds of preterm birth (preexisting diabetes, preexisting hypertension, sickle cell anemia, and previous preterm birth). Approximately 40% of women with a risk score ≥ 3.0 in the training and testing samples delivered preterm (40.6% and 40.8%, respectively) compared to 3.1-3.3% of women with a risk score of 0.0 [odds ratio (OR) 13.0, 95% confidence interval (CI) 10.7-15.8, training; OR 12.2, 95% CI 9.4-15.9, testing). Additionally, over 18% of women with a risk score ≥ 3.0 had an adverse outcome other than preterm birth. Conclusion Maternal factors that are identifiable prior to pregnancy or during the first-trimester can be used create a cumulative risk score to identify women at the lowest and highest risk for preterm birth regardless of race/ethnicity or socioeconomic status. Further, we found that this cumulative risk score could also identify women at risk for other adverse outcomes who did not have a preterm birth. The risk score is not an effective screening test, but does identify women at very high risk of a preterm birth.

A computational framework for predicting obesity risk based on optimizing and integrating genetic risk score and gene expression profiles

Recent large-scale genome-wide association studies have identified tens of genetic loci robustly associated with Body Mass Index (BMI). Gene expression profiles were also found to be associated with BMI. However, accurate prediction of obesity risk utilizing genetic data remains challenging. In a cohort of 75 individuals, we integrated 27 BMI-associated SNPs and obesity-associated gene expression profiles. Genetic risk score was computed by adding BMI-increasing alleles. The genetic risk score was significantly correlated with BMI when an optimization algorithm was used that excluded some SNPs. Linear regression and support vector machine models were built to predict obesity risk using gene expression profiles and the genetic risk score. An adjusted R2 of 0.556 and accuracy of 76% was achieved for the linear regression and support vector machine models, respectively. In this paper, we report a new mathematical method to predict obesity genetic risk. We constructed obesity prediction models based on genetic information for a small cohort. Our computational framework serves as an example for using genetic information to predict obesity risk for specific cohorts.

Modeling the Causal Role of DNA Methylation in the Association Between Cigarette Smoking and Inflammation in African Americans: A 2-Step Epigenetic Mendelian Randomization Study

The association between cigarette smoking and inflammation is well known. However, the biological mechanisms behind the association are not fully understood, particularly the role of DNA methylation, which is known to be affected by smoking. Using 2-step epigenetic Mendelian randomization, we investigated the role of DNA methylation in the association between cigarette smoking and inflammation. In 822 African Americans from the Genetic Epidemiology Network of Arteriopathy, phase 2 (Jackson, Mississippi; 2000-2005), study population, we examined the association of cigarette smoking with DNA methylation using single nucleotide polymorphisms identified in previous genome-wide association studies of cigarette smoking. We then investigated the association of DNA methylation with levels of inflammatory markers using cis-methylation quantitative trait loci single nucleotide polymorphisms. We found that current smoking status was associated with the DNA methylation levels (M values) of cg03636183 in the coagulation factor II (thrombin) receptor-like 3 gene (F2RL3) (M = -0.64, 95% confidence interval (CI): -0.84, -0.45) and of cg19859270 in the G protein-coupled receptor 15 gene (GPR15) (M = -0.21, 95% CI: -0.27, -0.15). The DNA methylation levels of cg03636183 in F2RL3 were associated with interleukin-18 concentration (-0.11 pg/mL, 95% CI: -0.19, -0.04). These combined negative effects suggest that cigarette smoking increases interleukin-18 levels through the decrease in DNA methylation levels of cg03636183 in F2RL3.

Home Environmental and Behavioral Risk Indices for Reading Achievement

The goal of this study was to identify home environmental and temperament/behavior variables that best predict standardized reading comprehension scores among school-aged children. Data from 269 children aged 9-16 (M = 12.08; SD = 1.62) were used in discriminant function analyses to create the Home and Behavior indices. Family income was controlled in each index. The final Home and Behavior models each classified around 75% of cases correctly (reading comprehension at grade level vs. not). Each index was then used to predict other outcomes related to reading. Results showed that Home and/or Behavior accounted for 4-7% of the variance in reading fluency and spelling and 20-35% of the variance in parent-rated problems in math, social anxiety, and other dimensions. These metrics show promise as environmental and temperament/behavior risk scores that could be used to predict and potentially screen for further assessment of reading related problems.

Genetic variations related to maternal whole blood mitochondrial DNA copy number: a genome-wide and candidate gene study

We conducted genome-wide (GWAS) and candidate gene association studies of maternal mitochondrial DNA copy number. Maternal peripheral blood was collected during labor and delivery admission from 471 participants of a placental abruption case-control study conducted in Lima, Peru. Single nucleotide polymorphism (SNP) genotyping was performed using the Illumina Cardio-Metabo Chip. Whole blood mitochondrial DNA (mtDNA) copy number was measured using qRT-PCR techniques. We evaluated 119,629 SNPs in the GWAS and 161 SNPs (in 29 mitochondrial biogenesis and oxidative phosphorylation genes) in the candidate association study. Top hits from GWAS and the candidate gene study were selected to compute weighted genetic risk scores (wGRS). Linear regression models were used to calculate effect size estimates and related nominal p values. The top hit in our GWAS was chr19:51063065 in FOXA3 (empirical p values = 2.20e - 6). A total of 134 SNPs had p values < 0.001 including rs17111633 in CNNM1 (p values = 6.32e - 6) and chr19:51083059 in MYPOP (p values = 3.23e - 5). In the candidate association study, several SNPs in PPARG, PRKCA, SP1 and THRB were associated with mtDNA copy number (p values < 0.05). mtDNA copy number was significantly associated with wGRS based on top GWAS hits (β = 0.49, 95% CI:0.38-0.60, p < 0.001). Variations in nuclear DNA are potentially associated with maternal mtDNA copy number.

Placental genetic variations in vitamin D metabolism and birthweight

INTRODUCTION

Vitamin D has pleiotropic functions that regulate fetal growth and development. We investigated associations of common placental genetic variations in vitamin D metabolism with birthweight.

METHODS

The study was conducted among participants (506 maternal-infant pairs) of a pregnancy cohort study. Data were collected using interviewer-administered questionnaires and post-delivery medical record abstraction. DNA, extracted from placental samples collected at delivery, was genotyped for eight single nucleotide polymorphisms (SNPs) in five vitamin D metabolism genes (CUBN, LRP2, VDR, GC, and CYP2R1). Linear and logistic regression models were used to evaluate associations of SNPs with birthweight and risk of low birthweight, respectively. Effect modification of associations by infant sex was examined using stratified analyses and interaction terms in regression models.

RESULTS

Mean (standard-deviation) birthweight among all, male, and female infants was 3482.1 (549.9), 3544.6 (579.0) and 3419.2 (512.5) grams, respectively. Each copy of the minor allele of rs2282679 (GC) was associated with a 68.6 g (95%CI:3.1134.7 g) increase in birthweight overall. Sex-specific associations were observed for SNP rs4667591 (LRP2) (p-value for interaction < 0.001). Each copy of the minor allele of rs4667591 was associated with a 124.7 g (95%CI:20.1229.0 g) increase in birthweight among female infants, and a suggested 81.6 g decrease in birthweight among male infants (95%CI:-183.7,20.5 g).

DISCUSSION

Our study identified overall and sex-specific associations between placental genetic variations in vitamin D metabolism and birthweight. If confirmed by larger replication studies, observed associations may provide insight into mechanistic underpinnings of the relationships between placental vitamin D metabolism and birth size.

Weighted Genetic Risk Scores and Prediction of Weight Gain in Solid Organ Transplant Populations

Background

Polygenic obesity in Solid Organ Transplant (SOT) populations is considered a risk factor for the development of metabolic abnormalities and graft survival. Few studies to date have studied the genetics of weight gain in SOT recipients. We aimed to determine whether weighted genetic risk scores (w-GRS) integrating genetic polymorphisms from GWAS studies (SNP group#1 and SNP group#2) and from Candidate Gene studies (SNP group#3) influence BMI in SOT populations and if they predict ≥10% weight gain (WG) one year after transplantation. To do so, two samples (n_A = 995, n_B = 156) were obtained from naturalistic studies and three w-GRS were constructed and tested for association with BMI over time. Prediction of 10% WG at one year after transplantation was assessed with models containing genetic and clinical factors.

Results

w-GRS were associated with BMI in sample A and B combined (BMI increased by 0.14 and 0.11 units per additional risk allele in SNP group#1 and #2, respectively, p-values<0.008). w-GRS of SNP group#3 showed an effect of 0.01 kg/m² per additional risk allele when combining sample A and B (p-value 0.04). Models with genetic factors performed better than models without in predicting 10% WG at one year after transplantation.

Conclusions

This is the first study in SOT evaluating extensively the association of w-GRS with BMI and the influence of clinical and genetic factors on 10% of WG one year after transplantation, showing the importance of integrating genetic factors in the final model. Genetics of obesity among SOT recipients remains an important issue and can contribute to treatment personalization and prediction of WG after transplantation.

Assessing the Causality between Blood Pressure and Retinal Vascular Caliber through Mendelian Randomisation

We aimed to determine the association between blood pressure (BP) and retinal vascular caliber changes that were free from confounders and reverse causation by using Mendelian randomisation. A total of 6528 participants from a multi-ethnic cohort (Chinese, Malays, and Indians) in Singapore were included in this study. Retinal arteriolar and venular caliber was measured by a semi-automated computer program. Genotyping was done using Illumina 610-quad chips. Meta-analysis of association between BP, and retinal arteriolar and venular caliber across three ethnic groups was performed both in conventional linear regression and Mendelian randomisation framework with a genetic risk score of BP as an instrumental variable. In multiple linear regression models, each 10 mm Hg increase in systolic BP, diastolic BP, and mean arterial BP (MAP) was associated with significant decreases in retinal arteriolar caliber of a 1.4, 3.0, and 2.6 μm, and significant decreases in retinal venular caliber of a 0.6, 0.7, and 0.9 μm, respectively. In a Mendelian randomisation model, only associations between DBP and MAP and retinal arteriolar narrowing remained yet its significance was greatly reduced. Our data showed weak evidence of a causal relationship between elevated BP and retinal arteriolar narrowing.

Improved prediction of complex diseases by common genetic markers: state of the art and further perspectives

Reliable risk assessment of frequent, but treatable diseases and disorders has considerable clinical and socio-economic relevance. However, as these conditions usually originate from a complex interplay between genetic and environmental factors, precise prediction remains a considerable challenge. The current progress in genotyping technology has resulted in a substantial increase of knowledge regarding the genetic basis of such diseases and disorders. Consequently, common genetic risk variants are increasingly being included in epidemiological models to improve risk prediction. This work reviews recent high-quality publications targeting the prediction of common complex diseases. To be included in this review, articles had to report both, numerical measures of prediction performance based on traditional (non-genetic) risk factors, as well as measures of prediction performance when adding common genetic variants to the model. Systematic PubMed-based search finally identified 55 eligible studies. These studies were compared with respect to the chosen approach and methodology as well as results and clinical impact. Phenotypes analysed included tumours, diabetes mellitus, and cardiovascular diseases. All studies applied one or more statistical measures reporting on calibration, discrimination, or reclassification to quantify the benefit of including SNPs, but differed substantially regarding the methodological details that were reported. Several examples for improved risk assessments by considering disease-related SNPs were identified. Although the add-on benefit of including SNP genotyping data was mostly moderate, the strategy can be of clinical relevance and may, when being paralleled by an even deeper understanding of disease-related genetics, further explain the development of enhanced predictive and diagnostic strategies for complex diseases.

Evaluation of genetic risk scores for prediction of dichotomous outcomes

Substantial uncertainty exists as to whether combining multiple disease-associated single nucleotide polymorphisms (SNPs) into a genotype risk score (GRS) can improve the ability to predict the risk of disease in a clinically relevant way. We calculated the ability of a simple count GRS to predict the risk of a dichotomous outcome under both multiplicative and additive models of combined effects. We then compared the results of these simulations with the observed results of published GRS measured within multiple epidemiologic cohorts. If the combined effect of each disease-associated SNP included in a GRS is multiplicative on the risk scale, then a count GRS score should be useful for risk prediction with as few as 10-20 SNPs. Adding additional SNPs to the GRS under this model dramatically improves risk prediction. By contrast, if the combined effect of each SNP included in a GRS is linearly additive on the risk scale, a simple count GRS is unlikely to provide clinically useful risk prediction. Adding additional SNPs to the GRS under this model does not improve risk prediction. The combined effect of SNPs included in several published GRS measured in several well-phenotyped epidemiologic cohort studies appears to be more consistent with a linearly additive effect. A simple count GRS is unlikely to be clinically useful for predicting the risk of a dichotomous outcome. Alternative methods for constructing GRS that attempt to identify and include SNPs that demonstrate multiplicative gene-gene or gene-environment interactive effects are needed.

Big data challenges in bone research: genome-wide association studies and next-generation sequencing

Genome-wide association studies (GWAS) have been developed as a practical method to identify genetic loci associated with disease by scanning multiple markers across the genome. Significant advances in the genetics of complex diseases have been made owing to advances in genotyping technologies, the progress of projects such as HapMap and 1000G and the emergence of genetics as a collaborative discipline. Because of its great potential to be used in parallel by multiple collaborators, it is important to adhere to strict protocols assuring data quality and analyses. Quality control analyses must be applied to each sample and each single-nucleotide polymorphism (SNP). The software package PLINK is capable of performing the whole range of necessary quality control tests. Genotype imputation has also been developed to substantially increase the power of GWAS methodology. Imputation permits the investigation of associations at genetic markers that are not directly genotyped. Results of individual GWAS reports can be combined through meta-analysis. Finally, next-generation sequencing (NGS) has gained popularity in recent years through its capacity to analyse a much greater number of markers across the genome. Although NGS platforms are capable of examining a higher number of SNPs compared with GWA studies, the results obtained by NGS require careful interpretation, as their biological correlation is incompletely understood. In this article, we will discuss the basic features of such protocols.

A genetic risk tool for obesity predisposition assessment and personalized nutrition implementation based on macronutrient intake

There is little evidence about genetic risk score (GRS)-diet interactions in order to provide personalized nutrition based on the genotype. The aim of the study was to assess the value of a GRS on obesity prediction and to further evaluate the interactions between the GRS and dietary intake on obesity. A total of 711 seekers of a Nutrigenetic Service were examined for anthropometric and body composition measurements and also for dietary habits and physical activity. Oral epithelial cells were collected for the identification of 16 SNPs (related with obesity or lipid metabolism) using DNA zip-coded beads. Genotypes were coded as 0, 1 or 2 according to the number of risk alleles, and the GRS was calculated by adding risk alleles with such a criterion. After being adjusted for gender, age, physical activity and energy intake, the GRS demonstrated that individuals carrying >7 risk alleles had in average 0.93 kg/m(2) of BMI, 1.69 % of body fat mass, 1.94 cm of waist circumference and 0.01 waist-to-height ratio more than the individuals with ≤7 risk alleles. Significant interactions for GRS and the consumption of energy, total protein, animal protein, vegetable protein, total fat, saturated fatty acids, polyunsaturated fatty acids, total carbohydrates, complex carbohydrates and fiber intake on adiposity traits were found after adjusted for confounders variables. The GRS confirmed that the high genetic risk group showed greater values of adiposity than the low risk group and demonstrated that macronutrient intake modifies the GRS association with adiposity traits.

A genetic risk score for hypertension associates with the risk of ischemic stroke in a Swedish case-control study

Genetic risk scores (GRS), summing up the total effect of several single-nucleotide polymorphisms (SNPs) in genes associated with either coronary risk or cardiovascular risk factors, have been tested for association with ischemic stroke with conflicting results. Recently an association was found between a GRS based on 29 SNPs discovered by genome-wide association studies and hypertension. The aim of our study was to investigate the possible association of the same GRS with ischemic stroke on top of other 'traditional risk factors', also testing its potential improvement in indices of discrimination and reclassification, in a Swedish case-control study. Twenty-nine SNPs were genotyped in 3677 stroke cases and 2415 controls included in the Lund Stroke Register (LSR), the Malmö Diet and Cancer (MDC) study and the Sahlgrenska Academy Study on Ischemic Stroke (SAHLSIS). The analysis was conducted in the combined sample, and separately for the three studies. After adjustment for hypertension, diabetes mellitus and smoking habits, the GRS was associated with ischemic stroke in the combined sample (OR (95% CI) 1.086 (1.029-1.147) per SD increase in the GRS P=0.003) with similar trends in all three samples: LSR (1.050 (0.967-1.140); P=0.25), MDC (1.168 (1.060-1.288); P=0.002) and SAHLSIS (1.124 (0.997-1.267); P=0.055). Measures of risk discrimination and reclassification improved marginally using the GRS. A blood pressure GRS is independently associated with ischemic stroke risk in three Swedish case-control studies, however, the effect size is low and adds marginally to prediction of stroke on top of traditional risk factors including hypertension.

Genetics, environment, and gene-environment interactions in the development of systemic rheumatic diseases

Rheumatic diseases offer distinct challenges to researchers because of heterogeneity in disease phenotypes, low disease incidence, and geographic variation in genetic and environmental factors. Emerging research areas, including epigenetics, metabolomics, and the microbiome, may provide additional links between genetic and environmental risk factors in the pathogenesis of rheumatic disease. This article reviews the methods used to establish genetic and environmental risk factors and studies gene-environment interactions in rheumatic diseases, and provides specific examples of successes and challenges in identifying gene-environment interactions in rheumatoid arthritis, systemic lupus erythematosus, and ankylosing spondylitis. Emerging research strategies and future challenges are discussed.

Common genetic loci influencing plasma homocysteine concentrations and their effect on risk of coronary artery disease

BACKGROUND

The strong observational association between total homocysteine (tHcy) concentrations and risk of coronary artery disease (CAD) and the null associations in the homocysteine-lowering trials have prompted the need to identify genetic variants associated with homocysteine concentrations and risk of CAD.

OBJECTIVE

We tested whether common genetic polymorphisms associated with variation in tHcy are also associated with CAD.

DESIGN

We conducted a meta-analysis of genome-wide association studies (GWAS) on tHcy concentrations in 44,147 individuals of European descent. Polymorphisms associated with tHcy (P < 10(⁻⁸) were tested for association with CAD in 31,400 cases and 92,927 controls.

RESULTS

Common variants at 13 loci, explaining 5.9% of the variation in tHcy, were associated with tHcy concentrations, including 6 novel loci in or near MMACHC (2.1 × 10⁻⁹), SLC17A3 (1.0 × 10⁻⁸), GTPB10 (1.7 × 10⁻⁸), CUBN (7.5 × 10⁻¹⁰), HNF1A (1.2 × 10⁻¹²)), and FUT2 (6.6 × 10⁻⁹), and variants previously reported at or near the MTHFR, MTR, CPS1, MUT, NOX4, DPEP1, and CBS genes. Individuals within the highest 10% of the genotype risk score (GRS) had 3-μmol/L higher mean tHcy concentrations than did those within the lowest 10% of the GRS (P = 1 × 10⁻³⁶). The GRS was not associated with risk of CAD (OR: 1.01; 95% CI: 0.98, 1.04; P = 0.49).

CONCLUSIONS

We identified several novel loci that influence plasma tHcy concentrations. Overall, common genetic variants that influence plasma tHcy concentrations are not associated with risk of CAD in white populations, which further refutes the causal relevance of moderately elevated tHcy concentrations and tHcy-related pathways for CAD.

Development and evaluation of a genetic risk score for obesity

Multi-locus profiles of genetic risk, so-called "genetic risk scores," can be used to translate discoveries from genome-wide association studies into tools for population health research. We developed a genetic risk score for obesity from results of 16 published genome-wide association studies of obesity phenotypes in European-descent samples. We then evaluated this genetic risk score using data from the Atherosclerosis Risk in Communities (ARIC) cohort GWAS sample (N = 10,745, 55% female, 77% white, 23% African American). Our 32-locus GRS was a statistically significant predictor of body mass index (BMI) and obesity among ARIC whites [for BMI, r = 0.13, p<1 × 10(-30); for obesity, area under the receiver operating characteristic curve (AUC) = 0.57 (95% CI 0.55-0.58)]. The GRS predicted differences in obesity risk net of demographic, geographic, and socioeconomic information. The GRS performed less well among African Americans. The genetic risk score we derived from GWAS provides a molecular measurement of genetic predisposition to elevated BMI and obesity.[Supplemental materials are available for this article. Go to the publisher's online edition of Biodemography and Social Biology for the following resource: Supplement to Development & Evaluation of a Genetic Risk Score for Obesity.].

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.

Genetic variants and blood pressure in a population-based cohort: the Cardiovascular Risk in Young Finns study

Clinical relevance of a genetic predisposition to elevated blood pressure was quantified during the transition from childhood to adulthood in a population-based Finnish cohort (N=2357). Blood pressure was measured at baseline in 1980 (age 3-18 years) and in follow-ups in 1983, 1986, 2001, and 2007. Thirteen single nucleotide polymorphisms associated with blood pressure were genotyped, and 3 genetic risk scores associated with systolic and diastolic blood pressures and their combination were derived for all of the participants. Effects of the genetic risk score were 0.47 mm Hg for systolic and 0.53 mm Hg for diastolic blood pressures (both P<0.01). The combination genetic risk score was associated with diastolic blood pressure from age 9 years onward (β=0.68 mm Hg; P=0.015). Replications in 1194 participants of the Bogalusa Heart Study showed essentially similar results. The participants in the highest quintile of the combination genetic risk score had a 1.82-fold risk of hypertension in adulthood (P<0.0001) compared with the lowest quintile, independent of a family history of premature hypertension. These findings show that genetic variants are associated with preclinical blood pressure traits in childhood; individuals with several susceptibility alleles have, on average, a 0.5-mm Hg higher blood pressure, and this trajectory continues from childhood to adulthood.

Evaluation of genetic susceptibility to childhood allergy and asthma in an African American urban population

BACKGROUND

Asthma and allergy represent complex phenotypes, which disproportionately burden ethnic minorities in the United States. Strong evidence for genomic factors predisposing subjects to asthma/allergy is available. However, methods to utilize this information to identify high risk groups are variable and replication of genetic associations in African Americans is warranted.

METHODS

We evaluated 41 single nucleotide polymorphisms (SNP) and a deletion corresponding to 11 genes demonstrating association with asthma in the literature, for association with asthma, atopy, testing positive for food allergens, eosinophilia, and total serum IgE among 141 African American children living in Detroit, Michigan. Independent SNP and haplotype associations were investigated for association with each trait, and subsequently assessed in concert using a genetic risk score (GRS).

RESULTS

Statistically significant associations with asthma were observed for SNPs in GSTM1, MS4A2, and GSTP1 genes, after correction for multiple testing. Chromosome 11 haplotype CTACGAGGCC (corresponding to MS4A2 rs574700, rs1441586, rs556917, rs502581, rs502419 and GSTP1 rs6591256, rs17593068, rs1695, rs1871042, rs947895) was associated with a nearly five-fold increase in the odds of asthma (Odds Ratio (OR) = 4.8, p = 0.007). The GRS was significantly associated with a higher odds of asthma (OR = 1.61, 95% Confidence Interval = 1.21, 2.13; p = 0.001).

CONCLUSIONS

Variation in genes associated with asthma in predominantly non-African ethnic groups contributed to increased odds of asthma in this African American study population. Evaluating all significant variants in concert helped to identify the highest risk subset of this group.

Joint effects of common genetic variants from multiple genes and pathways on the risk of premature coronary artery disease

OBJECTIVE

The aim of this study is to discover common variants in 6 lipid metabolic genes and construct and validate a genetic risk score (GRS) based on the joint effects of genetic variants in multiple genes from lipid and other pathobiologic pathways.

BACKGROUND

Explaining the genetic basis of coronary artery disease (CAD) is incomplete. Discovery and aggregation of genetic variants from multiple pathways may advance this objective.

METHODS

Premature CAD cases (n = 1,947) and CAD-free controls (n = 1,036) were selected from our angiographic registry. In a discovery phase, single nucleotide polymorphisms (SNPs) at 56 loci from internal discovery and external reports were tested for associations with biomarkers and CAD: 28 promising SNPs were then tested jointly for CAD associations, and a GRS consisting of SNPs contributing independently was constructed and validated in a replication set of familial cases and population-based controls (n = 1,320).

RESULTS

Five variants contributed jointly to CAD prediction in a multigenic GRS model: odds ratio 1.24 (95% CI 1.16-1.33) per risk allele, P = 8.2 x 10(-11), adjusted OR 2.03 (1.53-2.70), fourth versus first quartile. 5-SNP genetic risk score had minor impact on area under the receiver operating characteristic curve (P > .05) but resulted in substantial net reclassification improvement: 0.16 overall, 0.28 in intermediate-risk patients (both P < .0001). GRS(5) predicted familial CAD with similar magnitude in the validation set.

CONCLUSIONS

The Intermountain Healthcare's Coronary Genetics study demonstrates the ability of a multigenic, multipathway GRS to improve discrimination of angiographic CAD. Genetic risk scores promise to increase understanding of the genetic basis of CAD and improve identification of individuals at increased CAD risk.

Evaluation of genetic risk scores for lipid levels using genome-wide markers in the Framingham Heart Study

BACKGROUND

Multiple single-nucleotide polymorphisms have been associated with low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglyceride (TG) levels. In this paper, we evaluate a weighted and an unweighted approach for estimating the combined effect of multiple markers (using genotypes and haplotypes) on lipid levels for a given individual.

METHODS

Using data from the Framingham Heart Study SHARe genome-wide association study, we tested genome-wide genotypes and haplotypes for association with lipid levels and constructed genetic risk scores (GRS) based on multiple markers that were weighted according to their estimated effects on LDL-C, HDL-C, and TG. These scores (GRS-LDL, GRS-HDL, and GRS-TG) were then evaluated for associations with LDL-C, HDL-C, and TG, and compared with results of an unweighted method based on risk-allele counts. For comparability of metrics, GRS variables were divided into quartiles.

RESULTS

GRS-LDL quartiles were associated with LDL-C levels (p = 2.1 x 10-24), GRS-HDL quartiles with HDL-C (p = 5.9 x 10-22), and GRS-TG quartiles with TG (p = 5.4 x 10-25). In comparison, these p-values were considerably lower than those for the associations of the unweighted GRS quartiles for LDL-C (p = 3.6 x 10-7), HDL-C (p = 6.4 x 10-16), and TG (p = 4.1 x 10-10).

CONCLUSION

GRS variables were highly predictive of LDL-C, HDL-C, and TG measurements, especially when weighted based on each marker's individual association with those intermediate risk phenotypes. The allele-count GRS approach that does not weight the GRS by individual marker associations was considerably less predictive of lipid and lipoprotein measures when the same genetic markers were utilized, suggesting that substantially more risk-associated genetic marker information is encapsulated by the weighted GRS variables.

Genetic variants in the cell cycle control pathways contribute to early onset colorectal cancer in Lynch syndrome

PURPOSE

Lynch syndrome is an autosomal dominant syndrome of familial malignancies resulting from germ line mutations in DNA mismatch repair (MMR) genes. Our goal was to take a pathway-based approach to investigate the influence of polymorphisms in cell cycle-related genes on age of onset for Lynch syndrome using a tree model.

EXPERIMENTAL DESIGN

We evaluated polymorphisms in a panel of cell cycle-related genes (AURKA, CDKN2A, TP53, E2F2, CCND1, TP73, MDM2, IGF1, and CDKN2B) in 220 MMR gene mutation carriers from 129 families. We applied a novel statistical approach, tree modeling (Classification and Regression Tree), to the analysis of data on patients with Lynch syndrome to identify individuals with a higher probability of developing colorectal cancer at an early age and explore the gene-gene interactions between polymorphisms in cell cycle genes.

RESULTS

We found that the subgroup with CDKN2A C580T wild-type genotype, IGF1 CA-repeats >or=19, E2F2 variant genotype, AURKA wild-type genotype, and CCND1 variant genotype had the youngest age of onset, with a 45-year median onset age, while the subgroup with CDKN2A C580T wild-type genotype, IGF1 CA-repeats >or=19, E2F2 wild-type genotype, and AURKA variant genotype had the latest median age of onset, which was 70 years. Furthermore, we found evidence of a possible gene-gene interaction between E2F2 and AURKA genes related to CRC age of onset.

CONCLUSIONS

Polymorphisms in these cell cycle-related genes work together to modify the age at the onset of CRC in patients with Lynch syndrome. These studies provide an important part of the foundation for development of a model for stratifying age of onset risk among those with Lynch syndrome.

Bladder cancer predisposition: a multigenic approach to DNA-repair and cell-cycle-control genes

The candidate-gene approach in association studies of polygenic diseases has often yielded conflicting results. In this hospital-based case-control study with 696 white patients newly diagnosed with bladder cancer and 629 unaffected white controls, we applied a multigenic approach to examine the associations with bladder cancer risk of a comprehensive panel of 44 selected polymorphisms in two pathways, DNA repair and cell-cycle control, and to evaluate higher-order gene-gene interactions, using classification and regression tree (CART) analysis. Individually, only XPD Asp312Asn, RAG1 Lys820Arg, and a p53 intronic SNP exhibited statistically significant main effects. However, we found a significant gene-dosage effect for increasing numbers of potential high-risk alleles in DNA-repair and cell-cycle pathways separately and combined. For the nucleotide-excision repair pathway, compared with the referent group (fewer than four adverse alleles), individuals with four (odds ratio [OR] = 1.52, 95% CI 1.05-2.20), five to six (OR = 1.81, 95% CI 1.31-2.50), and seven or more adverse alleles (OR = 2.50, 95% CI 1.69-3.70) had increasingly elevated risks of bladder cancer (P for trend <.001). Each additional adverse allele was associated with a 1.21-fold increase in risk (95% CI 1.12-1.29). For the combined analysis of DNA-repair and cell-cycle SNPs, compared with the referent group (<13 adverse alleles), the ORs for individuals with 13-15, 16-17, and >or=18 adverse alleles were 1.22 (95% CI 0.84-1.76), 1.57 (95% CI 1.05-2.35), and 1.77 (95% CI 1.19-2.63), respectively (P for trend = .002). Each additional high-risk allele was associated with a 1.07-fold significant increase in risk. In addition, we found that smoking had a significant multiplicative interaction with SNPs in the combined DNA-repair and cell-cycle-control pathways (P<.01). All genetic effects were evident only in "ever smokers" (persons who had smoked >or=100 cigarettes) and not in "never smokers." A cross-validation statistical method developed in this study confirmed the above observations. CART analysis revealed potential higher-order gene-gene and gene-smoking interactions and categorized a few higher-risk subgroups for bladder cancer. Moreover, subgroups identified with higher cancer risk also exhibited higher levels of induced genetic damage than did subgroups with lower risk. There was a significant trend of higher numbers of bleomycin- and benzo[a]pyrene diol-epoxide (BPDE)-induced chromatid breaks (by mutagen-sensitivity assay) and DNA damage (by comet assay) for individuals in higher-risk subgroups among cases of bladder cancer in smokers. The P for the trend was .0348 for bleomycin-induced chromosome breaks, .0036 for BPDE-induced chromosome breaks, and .0397 for BPDE-induced DNA damage, indicating that these higher-order gene-gene and gene-smoking interactions included SNPs that modulated repair and resulted in diminished DNA-repair capacity. Thus, genotype/phenotype analyses support findings from CART analyses. This is the first comprehensive study to use a multigenic analysis for bladder cancer, and the data suggest that individuals with a higher number of genetic variations in DNA-repair and cell-cycle-control genes are at an increased risk for bladder cancer, confirming the importance of taking a multigenic pathway-based approach to risk assessment.