Defining treatment regimens and lines of therapy using real-world data in oncology.

Retrospective observational research relies on databases that do not routinely record lines of therapy or reasons for treatment change. Standardized approaches to estimate lines of therapy were developed and evaluated in this study. A number of rules were developed, assumptions varied and macros developed to apply to large datasets. Results were investigated in an iterative process to refine line of therapy algorithms in three different cancers (lung, colorectal and gastric). Three primary factors were evaluated and included in the estimation of lines of therapy in oncology: defining a treatment regimen, addition/removal of drugs and gap periods. Algorithms and associated Statistical Analysis Software (SAS®) macros for line of therapy identification are provided to facilitate and standardize the use of real-world databases for oncology research.

Lay abstract Most, if not all, real-world healthcare databases do not contain data explaining treatment changes, requiring that rules be applied to estimate when treatment changes may reflect advancement of underlying disease. This study investigated three tumor types (lung, colorectal and gastric cancer) to develop and provide rules that researchers can apply to real-world databases. The resulting algorithms and associated SAS^® macros from this work are provided for use in the Supplementary data.

Hi-MC: a novel method for high-throughput mitochondrial haplogroup classification.

Effective approaches for assessing mitochondrial DNA (mtDNA) variation are important to multiple scientific disciplines. Mitochondrial haplogroups characterize branch points in the phylogeny of mtDNA. Several tools exist for mitochondrial haplogroup classification. However, most require full or partial mtDNA sequence which is often cost prohibitive for studies with large sample sizes. The purpose of this study was to develop Hi-MC, a high-throughput method for mitochondrial haplogroup classification that is cost effective and applicable to large sample sizes making mitochondrial analysis more accessible in genetic studies. Using rigorous selection criteria, we defined and validated a custom panel of mtDNA single nucleotide polymorphisms that allows for accurate classification of European, African, and Native American mitochondrial haplogroups at broad resolution with minimal genotyping and cost. We demonstrate that Hi-MC performs well in samples of European, African, and Native American ancestries, and that Hi-MC performs comparably to a commonly used classifier. Implementation as a software package in R enables users to download and run the program locally, grants greater flexibility in the number of samples that can be run, and allows for easy expansion in future revisions. Hi-MC is available in the CRAN repository and the source code is freely available at https://github.com/vserch/himc.

Safety profiles of non-small cell lung cancer patients treated with pemetrexed plus carboplatin: a real-world retrospective, observational, cohort study.

OBJECTIVE: Pemetrexed plus carboplatin (PCb) is a frequently used first-line treatment in advanced non-small cell lung cancer (NSCLC). This study examined the characteristics and safety profile of a NSCLC population treated with PCb area under the concentration-time curve 5 (PCb5) or 6 mg/mL•min (PCb6) under real-world conditions. RESEARCH DESIGN AND METHODS: A retrospective, observational, cohort study was conducted, utilizing data from the IMS Oncology US clinic-based, longitudinal, patient-level electronic medical records (EMR), including patients with NSCLC on PCb5 or PCb6 regimens initiated concomitantly on or after the diagnosis of lung cancer during 2004-2014. Patient characteristics and incidence of adverse events (AEs) were described for each cohort. Propensity scores were calculated based on baseline demographic and clinical factors. Propensity score stratification was used to further adjust for cohort differences. RESULTS: In total, 636 NSCLC patients receiving PCb5 (37% aged ≥70 years) and 184 patients receiving PCb6 (34% aged ≥70 years) who met the inclusion criteria were identified in the EMR. Patients with more comorbidities were more likely to have received PCb5. Overall incidence rates (IRs) per 100 person-years were similar for neutropenia in both cohorts, were numerically higher for anemia (IR = 43.6 vs 101.0) and thrombocytopenia (IR = 1.5 vs 17.9), and were numerically lower for nausea (IR = 14.4 vs 9.9) in the PCb6 vs PCb5 cohort. Within the PCb6 cohort, the IR per 100 person-years was higher for neutropenia for ≥70 year-old patients (IR = 41.1) compared to <70 year-old patients (IR = 14.5). After propensity score stratification, adjusted IRs showed similar patterns. LIMITATIONS: Limitations included lack of power for AEs other than anemia, given the nature of EMR. CONCLUSIONS: Results from this real-world analysis add to existing evidence from randomized clinical trials about PCb safety profiles in the overall NSCLC population and in elderly patients. These results may guide physicians when making treatment decisions.

Pleiotropic and sex-specific effects of cancer GWAS SNPs on melanoma risk in the population architecture using genomics and epidemiology (PAGE) study.

BACKGROUND: Several regions of the genome show pleiotropic associations with multiple cancers. We sought to evaluate whether 181 single-nucleotide polymorphisms previously associated with various cancers in genome-wide association studies were also associated with melanoma risk. METHODS: We evaluated 2,131 melanoma cases and 20,353 controls from three studies in the Population Architecture using Genomics and Epidemiology (PAGE) study (EAGLE-BioVU, MEC, WHI) and two collaborating studies (HPFS, NHS). Overall and sex-stratified analyses were performed across studies. RESULTS: We observed statistically significant associations with melanoma for two lung cancer SNPs in the TERT-CLPTM1L locus (Bonferroni-corrected p<2.8x10-4), replicating known pleiotropic effects at this locus. In sex-stratified analyses, we also observed a potential male-specific association between prostate cancer risk variant rs12418451 and melanoma risk (OR=1.22, p=8.0x10-4). No other variants in our study were associated with melanoma after multiple comparisons adjustment (p>2.8e-4). CONCLUSIONS: We provide confirmatory evidence of pleiotropic associations with melanoma for two SNPs previously associated with lung cancer, and provide suggestive evidence for a male-specific association with melanoma for prostate cancer variant rs12418451. This SNP is located near TPCN2, an ion transport gene containing SNPs which have been previously associated with hair pigmentation but not melanoma risk. Previous evidence provides biological plausibility for this association, and suggests a complex interplay between ion transport, pigmentation, and melanoma risk that may vary by sex. If confirmed, these pleiotropic relationships may help elucidate shared molecular pathways between cancers and related phenotypes.

Mitochondrial variation and the risk of age-related macular degeneration across diverse populations.

Substantial progress has been made in identifying susceptibility variants for age-related macular degeneration (AMD). The majority of research to identify genetic variants associated with AMD has focused on nuclear genetic variation. While there is some evidence that mitochondrial genetic variation contributes to AMD susceptibility, to date, these studies have been limited to populations of European descent resulting in a lack of data in diverse populations. A major goal of the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study is to describe the underlying genetic architecture of common, complex diseases across diverse populations. This present study sought to determine if mitochondrial genetic variation influences risk of AMD across diverse populations. We performed a genetic association study to investigate the contribution of mitochondrial DNA variation to AMD risk. We accessed samples from the National Health and Nutrition Examination Surveys, a U.S population-based, cross-sectional survey collected without regard to health status. AMD cases and controls were selected from the Third NHANES and NHANES 2007-2008 datasets which include non-Hispanic whites, non-Hispanic blacks, and Mexican Americans. AMD cases were defined as those > 60 years of age with early/late AMD, as determined by fundus photography. Targeted genotyping was performed for 63 mitochondrial SNPs and participants were then classified into mitochondrial haplogroups. We used logistic regression assuming a dominant genetic model adjusting for age, sex, body mass index, and smoking status (ever vs. never). Regressions and meta-analyses were performed for individual SNPs and mitochondrial haplogroups J, T, and U. We identified five SNPs associated with AMD in Mexican Americans at p < 0.05, including three located in the control region (mt16111, mt16362, and mt16319), one in MT-RNR2 (mt1736), and one in MT-ND4 (mt12007). No mitochondrial variant or haplogroup was significantly associated in non-Hispanic blacks or non- Hispanic whites in the final meta-analysis. This study provides further evidence that mitochondrial variation plays a role in susceptibility to AMD and contributes to the knowledge of the genetic architecture of AMD in Mexican Americans.

Electronic medical records and genomics (eMERGE) network exploration in cataract: several new potential susceptibility loci.

PURPOSE: Cataract is the leading cause of blindness in the world, and in the United States accounts for approximately 60% of Medicare costs related to vision. The purpose of this study was to identify genetic markers for age-related cataract through a genome-wide association study (GWAS). METHODS: In the electronic medical records and genomics (eMERGE) network, we ran an electronic phenotyping algorithm on individuals in each of five sites with electronic medical records linked to DNA biobanks. We performed a GWAS using 530,101 SNPs from the Illumina 660W-Quad in a total of 7,397 individuals (5,503 cases and 1,894 controls). We also performed an age-at-diagnosis case-only analysis. RESULTS: We identified several statistically significant associations with age-related cataract (45 SNPs) as well as age at diagnosis (44 SNPs). The 45 SNPs associated with cataract at p<1×10(-5) are in several interesting genes, including ALDOB, MAP3K1, and MEF2C. All have potential biologic relationships with cataracts. CONCLUSIONS: This is the first genome-wide association study of age-related cataract, and several regions of interest have been identified. The eMERGE network has pioneered the exploration of genomic associations in biobanks linked to electronic health records, and this study is another example of the utility of such resources. Explorations of age-related cataract including validation and replication of the association results identified herein are needed in future studies.

Association of cancer susceptibility variants with risk of multiple primary cancers: The population architecture using genomics and epidemiology study.

BACKGROUND: Multiple primary cancers account for approximately 16% of all incident cancers in the United States. Although genome-wide association studies (GWAS) have identified many common genetic variants associated with various cancer sites, no study has examined the association of these genetic variants with risk of multiple primary cancers (MPC). METHODS: As part of the National Human Genome Research Institute (NHGRI) Population Architecture using Genomics and Epidemiology (PAGE) study, we used data from the Multiethnic Cohort (MEC) and Women's Health Initiative (WHI). Incident MPC (IMPC) cases (n = 1,385) were defined as participants diagnosed with more than one incident cancer after cohort entry. Participants diagnosed with only one incident cancer after cohort entry with follow-up equal to or longer than IMPC cases served as controls (single-index cancer controls; n = 9,626). Fixed-effects meta-analyses of unconditional logistic regression analyses were used to evaluate the associations between 188 cancer risk variants and IMPC risk. To account for multiple comparisons, we used the false-positive report probability (FPRP) to determine statistical significance. RESULTS: A nicotine dependence-associated and lung cancer variant, CHRNA3 rs578776 [OR, 1.16; 95% confidence interval (CI), 1.05-1.26; P = 0.004], and two breast cancer variants, EMBP1 rs11249433 and TOX3 rs3803662 (OR, 1.16; 95% CI, 1.04-1.28; P = 0.005 and OR, 1.13; 95% CI, 1.03-1.23; P = 0.006), were significantly associated with risk of IMPC. The associations for rs578776 and rs11249433 remained (P < 0.05) after removing subjects who had lung or breast cancers, respectively (P ≤ 0.046). These associations did not show significant heterogeneity by smoking status (Pheterogeneity ≥ 0.53). CONCLUSIONS: Our study has identified rs578776 and rs11249433 as risk variants for IMPC. IMPACT: These findings may help to identify genetic regions associated with IMPC risk.

Gene-carbohydrate and gene-fiber interactions and type 2 diabetes in diverse populations from the National Health and Nutrition Examination Surveys (NHANES) as part of the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study.

BACKGROUND: Both environmental and genetic factors impact type 2 diabetes (T2D). To identify such modifiers, we genotyped 15 T2D-associated variants from genome-wide association studies (GWAS) in 6,414 non-Hispanic whites, 3,073 non-Hispanic blacks, and 3,633 Mexican American participants from the National Health and Nutrition Examination Surveys (NHANES) and evaluated interactions between these variants and carbohydrate intake and fiber intake. RESULTS: We calculated a genetic risk score (GRS) with the 15 SNPs. The odds ratio for T2D with each GRS point was 1.10 (95% CI: 1.05-1.14) for non-Hispanic whites, 1.07 (95% CI: 1.02-1.13) for non-Hispanic blacks, and 1.11 (95% CI: 1.06-1.17) for Mexican Americans. We identified two gene-carbohydrate interactions (P < 0.05) in non-Hispanic whites (with CDKAL1 rs471253 and FTO rs8050136), two in non-Hispanic blacks (with IGFBP2 rs4402960 and THADA rs7578597), and two in Mexican Americans (with NOTCH2 rs1092398 and TSPAN8-LGRS rs7961581). We found three gene-fiber interactions in non-Hispanic whites (with ADAMT59 rs4607103, CDKN2A/2B rs1801282, and FTO rs8050136), two in non-Hispanic blacks (with ADAMT59 rs4607103 and THADA rs7578597), and two in Mexican Americans (with THADA rs7578597 and TSPAN8-LGRS rs796158) at the P < 0.05 level. Interactions between the GRS and nutrients failed to reach significance in all the racial/ethnic groups. CONCLUSION: Our results suggest that dietary carbohydrates and fiber may modify T2D-associated variants, highlighting the importance of dietary nutrients in predicting T2D risk.

Investigating the relationship between mitochondrial genetic variation and cardiovascular-related traits to develop a framework for mitochondrial phenome-wide association studies.

BACKGROUND: Mitochondria play a critical role in the cell and have DNA independent of the nuclear genome. There is much evidence that mitochondrial DNA (mtDNA) variation plays a role in human health and disease, however, this area of investigation has lagged behind research into the role of nuclear genetic variation on complex traits and phenotypic outcomes. Phenome-wide association studies (PheWAS) investigate the association between a wide range of traits and genetic variation. To date, this approach has not been used to investigate the relationship between mtDNA variants and phenotypic variation. Herein, we describe the development of a PheWAS framework for mtDNA variants (mt-PheWAS). Using the Metabochip custom genotyping array, nuclear and mitochondrial DNA variants were genotyped in 11,519 African Americans from the Vanderbilt University biorepository, BioVU. We employed both polygenic modeling and association testing with mitochondrial single nucleotide polymorphisms (mtSNPs) to explore the relationship between mtDNA variants and a group of eight cardiovascular-related traits obtained from de-identified electronic medical records within BioVU. RESULTS: Using polygenic modeling we found evidence for an effect of mtDNA variation on total cholesterol and type 2 diabetes (T2D). After performing comprehensive mitochondrial single SNP associations, we identified an increased number of single mtSNP associations with total cholesterol and T2D compared to the other phenotypes examined, which did not have more significantly associated SNPs than would be expected by chance. Among the mtSNPs significantly associated with T2D we identified variant mt16189, an association previously reported only in Asian and European-descent populations. CONCLUSIONS: Our replication of previous findings and identification of novel associations from this initial study suggest that our mt-PheWAS approach is robust for investigating the relationship between mitochondrial genetic variation and a range of phenotypes, providing a framework for future mt-PheWAS.

Pleiotropic effects of genetic risk variants for other cancers on colorectal cancer risk: PAGE, GECCO and CCFR consortia.

OBJECTIVE: Genome-wide association studies have identified a large number of single nucleotide polymorphisms (SNPs) associated with a wide array of cancer sites. Several of these variants demonstrate associations with multiple cancers, suggesting pleiotropic effects and shared biological mechanisms across some cancers. We hypothesised that SNPs previously associated with other cancers may additionally be associated with colorectal cancer. In a large-scale study, we examined 171 SNPs previously associated with 18 different cancers for their associations with colorectal cancer. DESIGN: We examined 13 338 colorectal cancer cases and 40 967 controls from three consortia: Population Architecture using Genomics and Epidemiology (PAGE), Genetic Epidemiology of Colorectal Cancer (GECCO), and the Colon Cancer Family Registry (CCFR). Study-specific logistic regression results, adjusted for age, sex, principal components of genetic ancestry, and/or study specific factors (as relevant) were combined using fixed-effect meta-analyses to evaluate the association between each SNP and colorectal cancer risk. A Bonferroni-corrected p value of 2.92×10(-4) was used to determine statistical significance of the associations. RESULTS: Two correlated SNPs--rs10090154 and rs4242382--in Region 1 of chromosome 8q24, a prostate cancer susceptibility region, demonstrated statistically significant associations with colorectal cancer risk. The most significant association was observed with rs4242382 (meta-analysis OR=1.12; 95% CI 1.07 to 1.18; p=1.74×10(-5)), which also demonstrated similar associations across racial/ethnic populations and anatomical sub-sites. CONCLUSIONS: This is the first study to clearly demonstrate Region 1 of chromosome 8q24 as a susceptibility locus for colorectal cancer; thus, adding colorectal cancer to the list of cancer sites linked to this particular multicancer risk region at 8q24.

No evidence of interaction between known lipid-associated genetic variants and smoking in the multi-ethnic PAGE population.

Genome-wide association studies (GWAS) have identified many variants that influence high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and/or triglycerides. However, environmental modifiers, such as smoking, of these known genotype-phenotype associations are just recently emerging in the literature. We have tested for interactions between smoking and 49 GWAS-identified variants in over 41,000 racially/ethnically diverse samples with lipid levels from the Population Architecture Using Genomics and Epidemiology (PAGE) study. Despite their biological plausibility, we were unable to detect significant SNP × smoking interactions.

Post-genome-wide association study challenges for lipid traits: describing age as a modifier of gene-lipid associations in the Population Architecture using Genomics and Epidemiology (PAGE) study.

Numerous common genetic variants that influence plasma high-density lipoprotein cholesterol, low-density lipoprotein cholesterol (LDL-C), and triglyceride distributions have been identified via genome-wide association studies (GWAS). However, whether or not these associations are age-dependent has largely been overlooked. We conducted an association study and meta-analysis in more than 22,000 European Americans between 49 previously identified GWAS variants and the three lipid traits, stratified by age (males: <50 or ≥50 years of age; females: pre- or postmenopausal). For each variant, a test of heterogeneity was performed between the two age strata and significant Phet values were used as evidence of age-specific genetic effects. We identified seven associations in females and eight in males that displayed suggestive heterogeneity by age (Phet < 0.05). The association between rs174547 (FADS1) and LDL-C in males displayed the most evidence for heterogeneity between age groups (Phet = 1.74E-03, I(2) = 89.8), with a significant association in older males (P = 1.39E-06) but not younger males (P = 0.99). However, none of the suggestive modifying effects survived adjustment for multiple testing, highlighting the challenges of identifying modifiers of modest SNP-trait associations despite large sample sizes.

Association of the FTO obesity risk variant rs8050136 with percentage of energy intake from fat in multiple racial/ethnic populations: the PAGE study.

Common obesity risk variants have been associated with macronutrient intake; however, these associations' generalizability across populations has not been demonstrated. We investigated the associations between 6 obesity risk variants in (or near) the NEGR1, TMEM18, BDNF, FTO, MC4R, and KCTD15 genes and macronutrient intake (carbohydrate, protein, ethanol, and fat) in 3 Population Architecture using Genomics and Epidemiology (PAGE) studies: the Multiethnic Cohort Study (1993-2006) (n = 19,529), the Atherosclerosis Risk in Communities Study (1987-1989) (n = 11,114), and the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) Study, which accesses data from the Third National Health and Nutrition Examination Survey (1991-1994) (n = 6,347). We used linear regression, with adjustment for age, sex, and ethnicity, to estimate the associations between obesity risk genotypes and macronutrient intake. A fixed-effects meta-analysis model showed that the FTO rs8050136 A allele (n = 36,973) was positively associated with percentage of calories derived from fat (ßmeta = 0.2244 (standard error, 0.0548); P = 4 × 10(-5)) and inversely associated with percentage of calories derived from carbohydrate (ßmeta = -0.2796 (standard error, 0.0709); P = 8 × 10(-5)). In the Multiethnic Cohort Study, percentage of calories from fat assessed at baseline was a partial mediator of the rs8050136 effect on body mass index (weight (kg)/height (m)(2)) obtained at 10 years of follow-up (mediation of effect = 0.0823 kg/m(2), 95% confidence interval: 0.0559, 0.1128). Our data provide additional evidence that the association of FTO with obesity is partially mediated by dietary intake.

Genetic analysis of a population heavy drinking phenotype identifies risk variants in whites.

Genetic association studies thus far have used detailed diagnoses of alcoholism to identify loci associated with risk. This proof-of-concept analysis examined whether population data of lifetime heaviest alcohol consumption may be used to identify genetic loci that modulate risk. We conducted a genetic association study in European Americans between variants in approximately 2100 genes and alcohol consumption as part of the Candidate gene Association Resource project. We defined cases as individuals with a history of drinking 5 or more drinks per day almost every day of the week and controls as current light drinkers (1-5 drinks per week). We cross-validated identified single nucleotide polymorphisms in a meta-analysis of 2 cohorts of unrelated individuals--Atherosclerosis Risk in Communities (ARIC) and Cardiovascular Health Study (CHS)--and in a separate cohort of related individuals--Framingham Heart Study (FHS). The most significant variant in the meta-analysis of ARIC and CHS was rs6933598 in methylenetetrahydrofolate dehydrogenase (P = 7.46 × 10(-05)) with a P value in FHS of 0.042. The top variants in FHS were rs12249562 in cubulin (P = 3.03 × 10(-05)) and rs9839267 near cholecystokinin (P = 3.05 × 10(-05)) with a P value of 0.019 for rs9839267 in CHS. We have here shown feasibility in evaluating lifetime incidence of heavy alcohol drinking from population-based studies for the purpose of conducting genetic association analyses.

Consistent directions of effect for established type 2 diabetes risk variants across populations: the population architecture using Genomics and Epidemiology (PAGE) Consortium.

Common genetic risk variants for type 2 diabetes (T2D) have primarily been identified in populations of European and Asian ancestry. We tested whether the direction of association with 20 T2D risk variants generalizes across six major racial/ethnic groups in the U.S. as part of the Population Architecture using Genomics and Epidemiology Consortium (16,235 diabetes case and 46,122 control subjects of European American, African American, Hispanic, East Asian, American Indian, and Native Hawaiian ancestry). The percentage of positive (odds ratio [OR] >1 for putative risk allele) associations ranged from 69% in American Indians to 100% in European Americans. Of the nine variants where we observed significant heterogeneity of effect by racial/ethnic group (P(heterogeneity) < 0.05), eight were positively associated with risk (OR >1) in at least five groups. The marked directional consistency of association observed for most genetic variants across populations implies a shared functional common variant in each region. Fine-mapping of all loci will be required to reveal markers of risk that are important within and across populations.

Gene-centric analysis of serum cotinine levels in African and European American populations.

To date, most genetic association studies of tobacco use have been conducted in European American subjects using the phenotype of smoking quantity (cigarettes per day). However, smoking quantity is a very imprecise measure of exposure to tobacco smoke constituents. Analyses of alternate phenotypes and populations may improve our understanding of tobacco addiction genetics. Cotinine is the major metabolite of nicotine, and measuring serum cotinine levels in smokers provides a more objective measure of nicotine dose than smoking quantity. Previous genetic association studies of serum cotinine have focused on individual genes. We conducted a genetic association study of the biomarker in African American (N=365) and European American (N=315) subjects from the Coronary Artery Risk Development in Young Adults study using a chip containing densely-spaced tag SNPs in ∼2100 genes. We found that rs11187065, located in the non-coding region (intron 1) of insulin-degrading enzyme (IDE), was the most strongly associated SNP (p=8.91 × 10(-6)) in the African American cohort, whereas rs11763963, located on chromosome 7 outside of a gene transcript, was the most strongly associated SNP in European Americans (p=1.53 × 10(-6)). We then evaluated how the top variant association in each population performed in the other group. We found that the association of rs11187065 in IDE was also associated with the phenotype in European Americans (p=0.044). Our top SNP association in European Americans, rs11763963 was non-polymorphic in our African American sample. It has been previously shown that psychostimulant self-administration is reduced in animals with lower insulin because of interference with dopamine transmission in the brain reward centers. Our finding provides a platform for further investigation of this, or additional mechanisms, involving the relationship between insulin and self-administered nicotine dose.

Genetic variability of smoking persistence in African Americans.

To date, most genetic association analyses of smoking behaviors have been conducted in populations of European ancestry and many of these studies focused on the phenotype that measures smoking quantity, that is, cigarettes per day. Additional association studies in diverse populations with different linkage disequilibrium patterns and an alternate phenotype, such as total tobacco exposure which accounts for intermittent periods of smoking cessation within a larger smoking period as measured in large cardiovascular risk studies, can aid the search for variants relevant to smoking behavior. For these reasons, we undertook an association analysis by using a genotyping array that includes 2,100 genes to analyze smoking persistence in unrelated African American participants from the Atherosclerosis Risk in Communities study. A locus located approximately 4 kb downstream from the 3'-UTR of the brain-derived neurotrophic factor (BDNF) significantly influenced smoking persistence. In addition, independent variants rs12915366 and rs12914385 in the cluster of genes encoding nicotinic acetylcholine receptor subunits (CHRNA5-CHRNA3-CHRNB4) on 15q25.1 were also associated with the phenotype in this sample of African American subjects. To our knowledge, this is the first study to more extensively evaluate the genome in the African American population, as a limited number of previous studies of smoking behavior in this population included evaluations of only single genomic regions.

A candidate gene study of obstructive sleep apnea in European Americans and African Americans.

RATIONALE: Obstructive sleep apnea (OSA) is hypothesized to be influenced by genes within pathways involved with obesity, craniofacial development, inflammation, and ventilatory control. OBJECTIVES: We conducted the first candidate gene study of OSA using family data from European Americans and African Americans, selecting biologically plausible genes from within these pathways. METHODS: A total of 1,080 single nucleotide polymorphisms (SNPs) were genotyped in 729 African Americans and 505 SNPs were genotyped in 694 European Americans. Coding for SNPs additively, association testing on the apnea-hypopnea index (AHI) as a continuous trait, and OSA as a dichotomous trait (AHI ≥15) was conducted using methods that account for familial correlations in models adjusted for age, age-squared, and sex, with and without body mass index. MEASUREMENTS AND MAIN RESULTS: In European Americans, variants within C-reactive protein (CRP) and glial cell line-derived neurotrophic factor (GDNF) were associated with AHI (CRP: ß = 4.6; SE = 1.1; P = 0.0000402) (GDNF: ß = 4.3; SE = 1; P = 0.0000201) and with the dichotomous OSA trait (CRP: odds ratio = 2.4; 95% confidence interval, 1.5-3.9; P = 0.000170) (GDNF: odds ratio = 2; 95% confidence interval, 1.4-2.89; P = 0.0000433). In African Americans, rs9526240 within serotonin receptor 2a (HTR2A: odds ratio = 2.1; 95% confidence interval, 1.5-2.9; P = 0.00005233) was associated with OSA. CONCLUSIONS: This candidate gene analysis identified the potential role of genes operating through intermediate disease pathways to influence sleep apnea phenotypes, providing a framework for focusing future replication studies.

Multivariate association analysis of the components of metabolic syndrome from the Framingham Heart Study.

Metabolic syndrome, by definition, is the manifestation of multiple, correlated metabolic impairments. It is known to have both strong environmental and genetic contributions. However, isolating genetic variants predisposing to such a complex trait has limitations. Using pedigree data, when available, may well lead to increased ability to detect variants associated with such complex traits. The ability to incorporate multiple correlated traits into a joint analysis may also allow increased detection of associated genes. Therefore, to demonstrate the utility of both univariate and multivariate family-based association analysis and to identify possible genetic variants associated with metabolic syndrome, we performed a scan of the Affymetrix 50 k Human Gene Panel data using 1) each of the traits comprising metabolic syndrome: triglycerides, high-density lipoprotein, systolic blood pressure, diastolic blood pressure, blood glucose, and body mass index, and 2) a composite trait including all of the above, jointly. Two single-nucleotide polymorphisms within the cholesterol ester transfer protein (CETP) gene remained significant even after correcting for multiple testing in both the univariate (p < 5 x 10-7) and multivariate (p < 5 x 10-9) association analysis. Three genes met significance for multiple traits after correction for multiple testing in the univariate analysis, while five genes remained significant in the multivariate association. We conclude that while both univariate and multivariate family-based association analysis can identify genes of interest, our multivariate approach is less affected by multiple testing correction and yields more significant results.