Genetic Knowledge Among Participants in the Coriell Personalized Medicine Collaborative.

Genetic literacy is essential for the effective integration of genomic information into healthcare; yet few recent studies have been conducted to assess the current state of this knowledge base. Participants in the Coriell Personalized Medicine Collaborative (CPMC), a prospective study assessing the impact of personalized genetic risk reports for complex diseases and drug response on behavior and health outcomes, completed genetic knowledge questionnaires and other surveys through an online portal. To assess the association between genetic knowledge and genetic education background, multivariate linear regression was performed. 4 062 participants completed a genetic knowledge and genetic education background questionnaire. Most were older (mean age: 50), Caucasian (90 %), female (59 %), highly educated (69 % bachelor's or higher), with annual household income over $100 000 (49 %). Mean percent correct was 76 %. Controlling for demographics revealed that health care providers, participants previously exposed to genetics, and participants with 'better than most' self-rated knowledge were significantly more likely to have a higher knowledge score (p < 0.001). Overall, genetic knowledge was high with previous genetic education experience predictive of higher genetic knowledge score. Education is likely to improve genetic literacy, an important component to expanded use of genomics in personalized medicine.

Using the Coriell Personalized Medicine Collaborative Data to conduct a genome-wide association study of sleep duration.

Sleep is critical to health and functionality, and several studies have investigated the inherited component of insomnia and other sleep disorders using genome-wide association studies (GWAS). However, genome-wide studies focused on sleep duration are less common. Here, we used data from participants in the Coriell Personalized Medicine Collaborative (CPMC) (n = 4,401) to examine putative associations between self-reported sleep duration, demographic and lifestyle variables, and genome-wide single nucleotide polymorphism (SNP) data to better understand genetic contributions to variation in sleep duration. We employed stepwise ordered logistic regression to select our model and retained the following predictive variables: age, gender, weight, physical activity, physical activity at work, smoking status, alcohol consumption, ethnicity, and ancestry (as measured by principal components analysis) in our association testing. Several of our strongest candidate genes were previously identified in GWAS related to sleep duration (TSHZ2, ABCC9, FBXO15) and narcolepsy (NFATC2, SALL4). In addition, we have identified novel candidate genes for involvement in sleep duration including SORCS1 and ELOVL2. Our results demonstrate that the self-reported data collected through the CPMC are robust, and our genome-wide association analysis has identified novel candidate genes involved in sleep duration. More generally, this study contributes to a better understanding of the complexity of human sleep.

ursaPGx: a new R package to annotate pharmacogenetic star alleles using phased whole-genome sequencing data.

Long-read sequencing technologies offer new opportunities to generate high-confidence phased whole-genome sequencing data for robust pharmacogenetic annotation. Here, we describe a new user-friendly R package, ursaPGx, designed to accept multi-sample phased whole-genome sequencing data VCF input files and output star allele annotations for pharmacogenes annotated in PharmVar.

Genetic risk estimation in the Coriell Personalized Medicine Collaborative.

PURPOSE: Recent genome wide-association studies have identified hundreds of single nucleotide polymorphisms associated with common complex diseases. With the momentum of these discoveries comes a need to communicate this information to individuals. METHODS: The Coriell Personalized Medicine Collaborative is an observational research study designed to evaluate the utility of personalized genomic information in health care. Participants provide saliva samples for genotyping and complete extensive on-line medical history, family history, and lifestyle questionnaires. Only results for diseases deemed potentially actionable by an independent advisory board are reported. RESULTS: We present our methodology for developing personalized reports containing risks for both genetic and nongenetic factors. Risk estimates are given as relative risk, derived or reported from representative peer-reviewed publications. Estimates of disease prevalence are also provided. Presenting risk as relative risk allows for consistent reporting across multiple diseases and across genetic and nongenetic factors. Using this approach eliminates the need for assumptions regarding population lifetime risk estimates. Publications used for risk reporting are selected based on the strength of the design and study quality. CONCLUSION: Coriell Personalized Medicine Collaborative risk reports demonstrate an approach to communicating risk of complex disease via the web that encompasses risks due to genetic variants along with risks caused by family history and lifestyle factors.

Common Treatment, Common Variant: Evolutionary Prediction of Functional Pharmacogenomic Variants.

Pharmacogenomics holds the promise of personalized drug efficacy optimization and drug toxicity minimization. Much of the research conducted to date, however, suffers from an ascertainment bias towards European participants. Here, we leverage publicly available, whole genome sequencing data collected from global populations, evolutionary characteristics, and annotated protein features to construct a new in silico machine learning pharmacogenetic identification method called XGB-PGX. When applied to pharmacogenetic data, XGB-PGX outperformed all existing prediction methods and identified over 2000 new pharmacogenetic variants. While there are modest pharmacogenetic allele frequency distribution differences across global population samples, the most striking distinction is between the relatively rare putatively neutral pharmacogene variants and the relatively common established and newly predicted functional pharamacogenetic variants. Our findings therefore support a focus on individual patient pharmacogenetic testing rather than on clinical presumptions about patient race, ethnicity, or ancestral geographic residence. We further encourage more attention be given to the impact of common variation on drug response and propose a new 'common treatment, common variant' perspective for pharmacogenetic prediction that is distinct from the types of variation that underlie complex and Mendelian disease. XGB-PGX has identified many new pharmacovariants that are present across all global communities; however, communities that have been underrepresented in genomic research are likely to benefit the most from XGB-PGX's in silico predictions.

An expanded pharmacogenomics warfarin dosing table with utility in generalised dosing guidance.

Pharmacogenomics (PGx) guided warfarin dosing, using a comprehensive dosing algorithm, is expected to improve dose optimisation and lower the risk of adverse drug reactions. As a complementary tool, a simple genotype-dosing table, such as in the US Food and Drug Administration (FDA) Coumadin drug label, may be utilised for general risk assessment of likely over- or under-anticoagulation on a standard dose of warfarin. This tool may be used as part of the clinical decision support for the interpretation of genetic data, serving as a first step in the anticoagulation therapy decision making process. Here we used a publicly available warfarin dosing calculator (www.warfarindosing.org) to create an expanded gene-based warfarin dosing table, the CPMC-WD table that includes nine genetic variants in CYP2C9, VKORC1, and CYP4F2. Using two datasets, a European American cohort (EUA, n=73) and the Quebec Warfarin Cohort (QWC, n=769), we show that the CPMC-WD table more accurately predicts therapeutic dose than the FDA table (51 % vs 33 %, respectively, in the EUA, McNemar's two-sided p=0.02; 52 % vs 37 % in the QWC, p<1×10(-6)). It also outperforms both the standard of care 5 mg/day dosing (51 % vs 34 % in the EUA, p=0.04; 52 % vs 31 % in the QWC, p<1×10(-6)) as well as a clinical-only algorithm (51 % vs 38 % in the EUA, trend p=0.11; 52 % vs 45 % in the QWC, p=0.003). This table offers a valuable update to the PGx dosing guideline in the drug label.

Analysis of multiple data sets reveals no association between the insulin gene variable number tandem repeat element and polycystic ovary syndrome or related traits.

CONTEXT: Variation at the insulin gene VNTR (variable number tandem repeat) minisatellite has been reported to be associated with polycystic ovary syndrome (PCOS), but findings have been inconsistent and all studies have featured small sample sizes. OBJECTIVE: To gain a robust understanding of the role of the INS-VNTR in PCOS susceptibility. DESIGN: Case-control, family-based association and quantitative trait analyses. SETTING AND PARTICIPANTS: A UK population comprising 255 parent-offspring trios, 185 additional cases, and 1062 control subjects (cases and controls all British/Irish) as well as 1599 women from a northern Finland population-based birth cohort characterized for PCO symptomatology and testosterone levels. VNTR class was inferred from genotyping of the -23HphI variant. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): INS-VNTR genotype frequencies between subject groups, body mass index, and testosterone levels by genotype. RESULTS: Case-control analyses in both UK and Finnish samples failed to confirm previously reported class III allele associations with PCOS (UK, P = 0.43, Finnish, P = 0.31; Kruskal-Wallis chi2). Transmission analysis in trios showed no excess transmission of either allele (P = 0.62), regardless of parent of origin (maternal: P = 0.73; paternal: P = 0.66). No association between genotype and testosterone levels was seen in any sample (UK PCOS subjects, P = 0.95; Finnish symptomatic cases, P = 0.38; Finnish control women, P = 0.58). CONCLUSIONS: Despite the strong biological candidacy and supportive data from previous studies, we conclude that variation at the INS-VNTR has no major role in the development of PCOS.

Remapping the insulin gene/IDDM2 locus in type 1 diabetes.

Type 1 diabetes susceptibility at the IDDM2 locus was previously mapped to a variable number tandem repeat (VNTR) 5' of the insulin gene (INS). However, the observation of associated markers outside a 4.1-kb interval, previously considered to define the limits of IDDM2 association, raised the possibility that the VNTR association might result from linkage disequilibrium (LD) with an unknown polymorphism. We therefore identified a total of 177 polymorphisms and obtained genotypes for 75 of these in up to 434 pedigrees. We found that, whereas disease susceptibility did map to within the 4.1-kb region, there were two equally likely candidates for the causal variant, -23HphI and +1140A/C, in addition to the VNTR. Further analyses in 2,960 pedigrees did not support the difference in association between VNTR lineages that had previously enabled the exclusion of these two polymorphisms. Therefore, we were unable to rule out -23HphI and +1140A/C having an etiological effect. Our mapping results using robust regression methods show how precisely a variant for a common disease can be mapped, even within a region of strong LD, and specifically that IDDM2 maps to one or more of three common variants in a approximately 2-kb region of chromosome 11p15.

Three autism candidate genes: a synthesis of human genetic analysis with other disciplines.

Autism is a particularly complex disorder when considered from virtually any methodological framework, including the perspective of human genetics. We first present a review of the genetic analysis principles relevant for discussing autism genetics research. From this body of work we highlight results from three candidate genes, REELIN (RELN), SEROTONIN TRANSPORTER (5HTT), and ENGRAILED 2 (EN2) and discuss the relevant neuroscience, molecular genetics, and statistical results that suggest involvement of these genes in autism susceptibility. As will be shown, the statistical results from genetic analysis, when considered alone, are in apparent conflict across research groups. We use these three candidate genes to illustrate different problems in synthesizing results from non-overlapping research groups examining the same problem. However, when basic genetic principles and results from other scientific disciplines are incorporated into a unified theoretical framework, at least some of the difficulties with interpreting results can be understood and potentially overcome as more data becomes available to the field of autism research. Integrating results from several scientific frameworks provides new hypotheses and alternative data collection strategies for future work.

Common genetic risk for melanoma encourages preventive behavior change.

There is currently great interest in using genetic risk estimates for common disease in personalized healthcare. Here we assess melanoma risk-related preventive behavioral change in the context of the Coriell Personalized Medicine Collaborative (CPMC). As part of on-going reporting activities within the project, participants received a personalized risk assessment including information related to their own self-reported family history of melanoma and a genetic risk variant showing a moderate effect size (1.7, 3.0 respectively for heterozygous and homozygous individuals). Participants who opted to view their report were sent an optional outcome survey assessing risk perception and behavioral change in the months that followed. Participants that report family history risk, genetic risk, or both risk factors for melanoma were significantly more likely to increase skin cancer preventive behaviors when compared to participants with neither risk factor (ORs = 2.04, 2.79, 4.06 and p-values = 0.02, 2.86 × 10-5, 4.67 × 10-5, respectively), and we found the relationship between risk information and behavior to be partially mediated by anxiety. Genomic risk assessments appear to encourage positive behavioral change in a manner that is complementary to family history risk information and therefore may represent a useful addition to standard of care for melanoma prevention.

Variation within the type 2 diabetes susceptibility gene calpain-10 and polycystic ovary syndrome.

Variation within the calpain-10 gene (CAPN10) has been proposed to account for linkage to type 2 diabetes on chromosome 2q in Mexican-Americans, and associations with diabetes have been reported in several other populations. Given the epidemiological, physiological, and genetic overlap between type 2 diabetes and polycystic ovary syndrome (PCOS), CAPN10 represents a strong candidate gene for a role in PCOS susceptibility. Using both family based and case-control association resources (146 parent-offspring trios; 185 additional PCOS cases; 525 control subjects, all of European ancestry), we sought association between CAPN10 variation and PCOS, focusing on four single nucleotide polymorphism (SNP) variants (SNP-44, SNP-43; SNP-19; SNP-63). On single-locus transmission disequilibrium analysis in the 146 trios, there was nominal evidence (P = 0.03) of excess transmission of the more common allele at SNP-63. This association was not, however, replicated in the case-control analysis. No other significant associations were observed at the single-locus or haplotype level in either the transmission-disequilibrium or case-control analyses. The relative risk for the high-risk diabetes susceptibility 112/121 genotype (SNPs 43-19-63) was 0.84 (95% confidence intervals, 0.40-1.71). No associations were seen with intermediate traits of relevance to diabetes and PCOS pathogenesis. We have found no evidence from these analyses that CAPN10 gene variation influences susceptibility to PCOS.

Large-scale analysis of the relationship between CYP11A promoter variation, polycystic ovarian syndrome, and serum testosterone.

CYP11A, the gene encoding p450scc, a key enzyme in steroid biosynthesis, is a strong biological candidate for polycystic ovary syndrome (PCOS) susceptibility. Four of the five published studies that have examined CYP11A for evidence of linkage and/or association have reported significant relationships with polycystic ovary (PCO) status and/or serum testosterone levels. However, study sizes have been modest, and the current study aimed to reevaluate these findings using significantly larger clinical resources. A pair of CYP11A promoter microsatellites, including the pentanucleotide (D15S520) previously implicated in trait susceptibility, were genotyped in 371 PCOS patients of United Kingdom origin, using both case-control and family-based association methods, and in 1589 women from a population-based birth cohort from Finland characterized for PCO symptomatology and testosterone levels. Although nominally significant differences in allele and genotype frequencies at both loci were observed in the United Kingdom case-control study (for example, an excess of the pentanucleotide four-repeat allele in cases, P = 0.005), these findings were not substantiated in the other analyses, and no discernable relationship was seen between variation at these loci and serum testosterone levels. These studies indicate that the strength of, and indeed the existence of, associations between CYP11A promoter variation and androgen-related phenotypes has been substantially overestimated in previous studies.

The Coriell personalized medicine collaborative pharmacogenomics appraisal, evidence scoring and interpretation system.

Implementation of pharmacogenomics (PGx) in clinical care can lead to improved drug efficacy and reduced adverse drug reactions. However, there has been a lag in adoption of PGx tests in clinical practice. This is due in part to a paucity of rigorous systems for translating published clinical and scientific data into standardized diagnostic tests with clear therapeutic recommendations. Here we describe the Pharmacogenomics Appraisal, Evidence Scoring and Interpretation System (PhAESIS), developed as part of the Coriell Personalized Medicine Collaborative research study, and its application to seven commonly prescribed drugs.

Coriell Personalized Medicine Collaborative®: a prospective study of the utility of personalized medicine.

There is a dearth of large prospective studies to determine if genetic risk factors are useful predictors of health outcomes and if reporting them to individuals or physicians changes health behavior. The Coriell Personalized Medicine Collaborative® (CPMC, NJ, USA) is a prospective observational study with three cohorts - community, cancer and chronic disease cohorts. Participants provide detailed medical history through a dynamic internet-based portal. DNA is tested and personalized risk reports are provided for potentially actionable health conditions. To date, the community cohort has enrolled 4372 participants. The internet-based portal supplies educational content, captures phenotypic data and delivers customized risk reports. The Informed Cohort Oversight Board has approved 16 health conditions to date, and risk reports with genetic and nongenetic risks for six conditions have been released. The majority (87%) of participants who completed requisite questionnaires viewed at least one report. The CPMC is a cohort study delivering customized risk reports for actionable conditions using a web interface and measuring outcomes longitudinally.

Autism-associated haplotype affects the regulation of the homeobox gene, ENGRAILED 2.

BACKGROUND: Association analysis identified the homeobox transcription factor, ENGRAILED 2 (EN2), as a possible autism spectrum disorder (ASD) susceptibility gene (ASD [MIM 608636]; EN2 [MIM 131310]). The common alleles (underlined) of two intronic single nucleotide polymorphisms (SNPs), rs1861972 (A/G) and rs1861973 (C/T), are over-transmitted to affected individuals both singly and as a haplotype in three separate datasets (518 families total, haplotype p = .00000035). METHODS: Further support that EN2 is a possible ASD susceptibility gene requires the identification of a risk allele, a DNA variant that is consistently associated with ASD but is also functional. To identify possible risk alleles, additional association analysis and linkage disequilibrium (LD) mapping were performed. Candidate polymorphisms were then tested for functional differences by luciferase (Luc) reporter transfections and electrophoretic mobility shift assays (EMSAs). RESULTS: Association analysis of additional EN2 polymorphisms and LD mapping with Hapmap SNPs identified the rs1861972-rs1861973 haplotype as the most appropriate candidate to test for functional differences. Luciferase reporters for the two common rs1861972-rs1861973 haplotypes (A-C and G-T) were then transfected into human and rat cell lines as well as primary mouse neuronal cultures. In all cases the A-C haplotype resulted in a significant increase in Luc levels (p < .005). The EMSAs were then performed, and nuclear factors were bound specifically to the A and C alleles of both SNPs. CONCLUSIONS: These data indicate that the A-C haplotype is functional and, together with the association and LD mapping results, supports EN2 as a likely ASD susceptibility gene and the A-C haplotype as a possible risk allele.

Cognitive traits link to human chromosomal regions.

: Human cognition in normal and disease states is both environmentally and genetically mediated. Except for measures of language-specific abilities, however, few cognitive measures have been associated with specific genes or chromosomal regions. We performed genome-wide linkage analysis of five neuropsychological tests in the Collaborative Study on Genetics of Alcoholism sample. The sample included 1579 individuals (53% female, 76% White Non-Hispanic) in 217 families. There were 390 markers with mean inter-marker distance of 9.6 cM. Performance on the Digit Symbol Substitution Test, a component of the Wechsler Adult Intelligence Scale-R, showed significant linkage to 14q11.2 and suggestive linkage to 14q 24.2. This test of sustained visual attention also involves visual-motor coordination and executive functions. Performance on the WAIS-R Digit Span Test of immediate memory and mental flexibility showed suggestive linkage to 11q 25. Although the validity of these results beyond populations with a susceptibility for alcohol dependence is unclear, these results are among the first linkage results for non-language components of cognition.

Support for the homeobox transcription factor gene ENGRAILED 2 as an autism spectrum disorder susceptibility locus.

Our previous research involving 167 nuclear families from the Autism Genetic Resource Exchange (AGRE) demonstrated that two intronic SNPs, rs1861972 and rs1861973, in the homeodomain transcription factor gene ENGRAILED 2 (EN2) are significantly associated with autism spectrum disorder (ASD). In this study, significant replication of association for rs1861972 and rs1861973 is reported for two additional data sets: an independent set of 222 AGRE families (rs1861972-rs1861973 haplotype, P=.0016) and a separate sample of 129 National Institutes of Mental Health families (rs1861972-rs1861973 haplotype, P=.0431). Association analysis of the haplotype in the combined sample of both AGRE data sets (389 families) produced a P value of .0000033, whereas combining all three data sets (518 families) produced a P value of .00000035. Population-attributable risk calculations for the associated haplotype, performed using the entire sample of 518 families, determined that the risk allele contributes to as many as 40% of ASD cases in the general population. Linkage disequilibrium (LD) mapping with the use of polymorphisms distributed throughout the gene has shown that only intronic SNPs are in strong LD with rs1861972 and rs1861973. Resequencing and association analysis of all intronic SNPs have identified alleles associated with ASD, which makes them candidates for future functional analysis. Finally, to begin defining the function of EN2 during development, mouse En2 was ectopically expressed in cortical precursors. Fewer En2-transfected cells than controls displayed a differentiated phenotype. Together, these data provide further genetic evidence that EN2 might act as an ASD susceptibility locus, and they suggest that a risk allele that perturbs the spatial/temporal expression of EN2 could significantly alter normal brain development.

Pathogenesis of polycystic ovary syndrome: evidence for a genetically determined disorder of ovarian androgen production.

Polycystic ovary syndrome (PCOS) is the commonest endocrine disorder in women of reproductive age. It is the major cause of anovulatory infertility and of hirsutism but its aetiology remains uncertain. The most consistent biochemical abnormality is hypersecretion of androgens. In this review, evidence is presented to support the view that a genetically determined abnormality of ovarian androgen secretion is the primary cause of the syndrome. Molecular genetic studies have demonstrated that CYP11a, the gene encoding P450 cholesterol side chain cleavage, is a major susceptibility locus for development of hyperandrogenism in PCOS.

Estimation and testing of parent-of-origin effects for quantitative traits.

Recent progress in developing family-based association methods has extended their use to the analysis of quantitative traits in the offspring and to the estimation, for dichotomous traits, of the relative contribution of genetic and environmental mechanisms for parent-of-origin effects. However, many traits of interest are not naturally measured on a binary scale yet are suspected or known to be influenced by imprinted genes, and there is consequent interest in seeking evidence for parent-of-origin effects at these loci. Here we show how simple linear models can be used to estimate these parent-of-origin effects for a broad class of phenotypes; in particular, normally distributed quantitative traits are easily dealt with.