Using lifetime risk estimates in personal genomic profiles: estimation of uncertainty

PheSeq, a Bayesian deep learning model to enhance and interpret the gene-disease association studies

Despite the abundance of genotype-phenotype association studies, the resulting association outcomes often lack robustness and interpretations. To address these challenges, we introduce PheSeq, a Bayesian deep learning model that enhances and interprets association studies through the integration and perception of phenotype descriptions. By implementing the PheSeq model in three case studies on Alzheimer's disease, breast cancer, and lung cancer, we identify 1024 priority genes for Alzheimer's disease and 818 and 566 genes for breast cancer and lung cancer, respectively. Benefiting from data fusion, these findings represent moderate positive rates, high recall rates, and interpretation in gene-disease association studies.

The importance of increasing population diversity in genetic studies of type 2 diabetes and related glycaemic traits

Type 2 diabetes has a global prevalence, with epidemiological data suggesting that some populations have a higher risk of developing this disease. However, to date, most genetic studies of type 2 diabetes and related glycaemic traits have been performed in individuals of European ancestry. The same is true for most other complex diseases, largely due to use of 'convenience samples'. Rapid genotyping of large population cohorts and case-control studies from existing collections was performed when the genome-wide association study (GWAS) 'revolution' began, back in 2005. Although global representation has increased in the intervening 15 years, further expansion and inclusion of diverse populations in genetic and genomic studies is still needed. In this review, I discuss the progress made in incorporating multi-ancestry participants in genetic analyses of type 2 diabetes and related glycaemic traits, and associated opportunities and challenges. I also discuss how increased representation of global diversity in genetic and genomic studies is required to fulfil the promise of precision medicine for all.

Role of a p53 polymorphism in the development of nonfunctional pituitary adenomas

Non-functional pituitary adenomas (NFPAs) are among the commonest intracranial neoplasms. While histologically benign, NFPAs sometimes become large enough to limit therapeutic options and reduce quality of life. Investigations of the molecular etiology of NFPAs have failed to identify prevalent genetic changes and, while a role for p53 has been suggested, TP53 gene alterations have yet to be described in NFPAs. We found that the polymorphism rs1042522:C > G in codon 72 of exon 4 of the TP53 gene, whose C variant produces a proline and is more common in most ethnicities, has a G variant producing an arginine in 79.8% of NFPAs (n = 42; p < 1.411 × 10^-18 vs. 1000 Genomes database), causing patients to present a decade earlier with symptomatic NFPAs. In cultured NFPA cells, transfection with the rs1042522 G variant versus the C variant reduced expression of cell arrest gene p21 and increased proliferation. These findings suggest that this TP53 polymorphism influences NFPA growth.

Genetic-based prediction of disease traits: prediction is very difficult, especially about the future

Translation of results from genetic findings to inform medical practice is a highly anticipated goal of human genetics. The aim of this paper is to review and discuss the role of genetics in medically-relevant prediction. Germline genetics presages disease onset and therefore can contribute prognostic signals that augment laboratory tests and clinical features. As such, the impact of genetic-based predictive models on clinical decisions and therapy choice could be profound. However, given that (i) medical traits result from a complex interplay between genetic and environmental factors, (ii) the underlying genetic architectures for susceptibility to common diseases are not well-understood, and (iii) replicable susceptibility alleles, in combination, account for only a moderate amount of disease heritability, there are substantial challenges to constructing and implementing genetic risk prediction models with high utility. In spite of these challenges, concerted progress has continued in this area with an ongoing accumulation of studies that identify disease predisposing genotypes. Several statistical approaches with the aim of predicting disease have been published. Here we summarize the current state of disease susceptibility mapping and pharmacogenetics efforts for risk prediction, describe methods used to construct and evaluate genetic-based predictive models, and discuss applications.

Are health professionals ready for direct-to-consumer genetic and genomic testing?

Direct-to-consumer genetic and genomic tests have been offered for over a decade. With the reduction in the cost of sequencing, the options for consumers will increase, with subsequent pressure on health services to interpret data and integrate the results into healthcare management. However, indications are that health professionals are grossly unprepared to deal with requests for support from those who have undertaken direct-to-consumer genetic or genomic tests. While benefits may be derived from patient-driven investigations, distinction needs to be made between the mostly uncertain clinical utility of susceptibility testing and the potential benefits of a reliably interpreted sequencing result. It is essential that we develop strategies, including enhanced professional education, to cope with the potential impact on the health services, rather than ignoring these developments. There may also be implications for the future of genetic counseling, with potential changes in the current paradigm.

Public knowledge of and attitudes toward genetics and genetic testing

BACKGROUND

Variable health literacy and genetic knowledge may pose significant challenges to engaging the general public in personal genomics, specifically with respect to promoting risk comprehension and healthy behaviors.

METHODS

We are conducting a multistage study of individual responses to genomic risk information for Type 2 diabetes mellitus. A total of 300 individuals were recruited from the general public in Durham, North Carolina: 60% self-identified as White; 70% female; and 65% have a college degree. As part of the baseline survey, we assessed genetic knowledge and attitudes toward genetic testing.

RESULTS

Scores of factual knowledge of genetics ranged from 50% to 100% (average=84%), with significant differences in relation to racial groups, the education level, and age. Scores were significantly higher on questions pertaining to the inheritance and causes of disease (mean score 90%) compared to scientific questions (mean score 77.4%). Scores on the knowledge survey were significantly higher than scores from European populations. Participants' perceived knowledge of the social consequences of genetic testing was significantly lower than their perceived knowledge of the medical uses of testing. More than half agreed with the statement that testing may affect a person's ability to obtain health insurance (51.3%) and 16% were worried about the consequences of testing for chances of finding a job.

CONCLUSIONS

Despite the relatively high educational status and genetic knowledge of the study population, we find an imbalance of knowledge between scientific and medical concepts related to genetics as well as between the medical applications and societal consequences of testing, suggesting that more effort is needed to present the benefits, risks, and limitations of genetic testing, particularly, at the social and personal levels, to ensure informed decision making.

Murine double minute clone 2,309T/G and 285G/C promoter single nucleotide polymorphism as a risk factor for breast cancer: a Polish experience

BACKGROUND

Breast cancer is a multifactorial disease caused by complex interactions between genetic and environmental factors. Recently, a functional polymorphism, MDM2 285G>C (rs117039649), has been discovered. This polymorphism antagonizes the effect of the 309T>G (rs2279744) polymorphism on the same gene, resulting in decreased MDM2 transcription.

METHODS

The MDM2 285G>C and 309T>G polymorphisms were identified by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and sequencing analysis in women with breast cancer (n=468) and controls (n=550).

RESULTS

The odds ratio (OR) for breast cancer patients with the MDM2 285C/C and 285G/C genotypes was 0.4768 (95% confidence interval [CI] 0.2906-0.7824; p=0.0033, pcorr=0.0066). We also found a significantly lower frequency of the MDM2 285C allele in patients with breast cancer than in controls: the OR for the C allele in patients with breast cancer was 0.4930 (95% CI=0.3059-0.7947, p=0.0031, pcorr=0.0062). The p value of the chi-square test for the trend observed for the MDM2 285G>C polymorphism was statistically significant (ptrend=0.0036). The statistical power of this study amounted to 85% for the G/C or C/C genotypes and 85% for the C allele. However, we did not observe significant differences between the distribution of MDM2 309T>G genotypes and alleles in patients with breast cancer and healthy controls.

CONCLUSION

In a sample of the Polish population, we observed that the MDM2 285C gene variant may be a significant protective factor against breast cancer.

Perception of direct-to-consumer genetic testing and direct-to-consumer advertising of genetic tests among members of a large managed care organization

This small qualitative study was designed to determine possible attitudes toward and understanding of direct-to-consumer (DTC) genetic testing among members of a large managed care organization, and whether differences might exist between population groups. Ten focus groups were conducted by population type (high risk, White, African American, Hispanic/Latino) to determine knowledge, attitudes and beliefs about DTC genetics. Focus group transcripts were coded for attitudes toward and framing of the issue. Study results found participants were negative towards DTC genetic testing but they also found some aspects useful. Participants framed the issue mainly in terms of disease prevention and uncertainty of reaction to results, with some variation between population types. The concept of an "Informed Consumer," or process to seek information when the issue becomes personally relevant, emerged. This concept suggests that individuals may seek additional assistance to make personally-appropriate choices when faced with a DTC advertisement or genetic test.

Consistency of genome-wide associations across major ancestral groups

It is not well known whether genetic markers identified through genome-wide association studies (GWAS) confer similar or different risks across people of different ancestry. We screened a regularly updated catalog of all published GWAS curated at the NHGRI website for GWAS-identified associations that had reached genome-wide significance (p ≤ 5 × 10(-8)) in at least one major ancestry group (European, Asian, African) and for which replication data were available for comparison in at least two different major ancestry groups. These groups were compared for the correlation between and differences in risk allele frequencies and genetic effects' estimates. Data on 108 eligible GWAS-identified associations with a total of 900 datasets (European, n = 624; Asian, n = 217; African, n = 60) were analyzed. Risk-allele frequencies were modestly correlated between ancestry groups, with >10% absolute differences in 75-89% of the three pairwise comparisons of ancestry groups. Genetic effect (odds ratio) point estimates between ancestry groups correlated modestly (pairwise comparisons' correlation coefficients: 0.20-0.33) and point estimates of risks were opposite in direction or differed more than twofold in 57%, 79%, and 89% of the European versus Asian, European versus African, and Asian versus African comparisons, respectively. The modest correlations, differing risk estimates, and considerable between-association heterogeneity suggest that differential ancestral effects can be anticipated and genomic risk markers may need separate further evaluation in different ancestry groups.

Genotype-informed estimation of risk of coronary heart disease based on genome-wide association data linked to the electronic medical record

Background

Susceptibility variants identified by genome-wide association studies (GWAS) have modest effect sizes. Whether such variants provide incremental information in assessing risk for common 'complex' diseases is unclear. We investigated whether measured and imputed genotypes from a GWAS dataset linked to the electronic medical record alter estimates of coronary heart disease (CHD) risk.

Methods

Study participants (n = 1243) had no known cardiovascular disease and were considered to be at high, intermediate, or low 10-year risk of CHD based on the Framingham risk score (FRS) which includes age, sex, total and HDL cholesterol, blood pressure, diabetes, and smoking status. Of twelve SNPs identified in prior GWAS to be associated with CHD, four were genotyped in the participants as part of a GWAS. Genotypes for seven SNPs were imputed from HapMap CEU population using the program MACH. We calculated a multiplex genetic risk score for each patient based on the odds ratios of the susceptibility SNPs and incorporated this into the FRS.

Results

The mean (SD) number of risk alleles was 12.31 (1.95), range 6-18. The mean (SD) of the weighted genetic risk score was 12.64 (2.05), range 5.75-18.20. The CHD genetic risk score was not correlated with the FRS (P = 0.78). After incorporating the genetic risk score into the FRS, a total of 380 individuals (30.6%) were reclassified into higher-(188) or lower-risk groups (192).

Conclusion

A genetic risk score based on measured/imputed genotypes at 11 susceptibility SNPs, led to significant reclassification in the 10-y CHD risk categories. Additional prospective studies are needed to assess accuracy and clinical utility of such reclassification.

APOE and Alzheimer disease: a major gene with semi-dominant inheritance

Apolipoprotein E (APOE) dependent lifetime risks (LTRs) for Alzheimer Disease (AD) are currently not accurately known and odds ratios alone are insufficient to assess these risks. We calculated AD LTR in 7351 cases and 10 132 controls from Caucasian ancestry using Rochester (USA) incidence data. At the age of 85 the LTR of AD without reference to APOE genotype was 11% in males and 14% in females. At the same age, this risk ranged from 51% for APOE44 male carriers to 60% for APOE44 female carriers, and from 23% for APOE34 male carriers to 30% for APOE34 female carriers, consistent with semi-dominant inheritance of a moderately penetrant gene. Using PAQUID (France) incidence data, estimates were globally similar except that at age 85 the LTRs reached 68 and 35% for APOE 44 and APOE 34 female carriers, respectively. These risks are more similar to those of major genes in Mendelian diseases, such as BRCA1 in breast cancer, than those of low-risk common alleles identified by recent GWAS in complex diseases. In addition, stratification of our data by age groups clearly demonstrates that APOE4 is a risk factor not only for late-onset but for early-onset AD as well. Together, these results urge a reappraisal of the impact of APOE in Alzheimer disease.

Regulating direct-to-consumer genetic tests: what is all the fuss about?

The number of genetic tests available direct-to-consumer has burgeoned over the last few years, prompting numerous calls for tighter regulation of these services. However, there is a lack of consensus about the most appropriate and achievable level of regulation, particularly given the global nature of the market. By consideration of potential for direct and indirect harms caused by genetic susceptibility or genomic profiling tests, in this study we offer an overarching framework that we believe to be feasible for the regulation of direct-to-consumer genetic tests and likely to be relevant to other forms of predictive testing. We suggest that just five key requirements would adequately protect the consumer: a proportionate set of consent procedures; formal laboratory accreditation; evidence of a valid gene-disease association; appropriately qualified staff to interpret the test result; and consumer protection legislation to prevent false or misleading claims.

Annotating individual human genomes

Advances in DNA sequencing technologies have made it possible to rapidly, accurately and affordably sequence entire individual human genomes. As impressive as this ability seems, however, it will not likely amount to much if one cannot extract meaningful information from individual sequence data. Annotating variations within individual genomes and providing information about their biological or phenotypic impact will thus be crucially important in moving individual sequencing projects forward, especially in the context of the clinical use of sequence information. In this paper we consider the various ways in which one might annotate individual sequence variations and point out limitations in the available methods for doing so. It is arguable that, in the foreseeable future, DNA sequencing of individual genomes will become routine for clinical, research, forensic, and personal purposes. We therefore also consider directions and areas for further research in annotating genomic variants.

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.

The MDM2 promoter SNP285C/309G haplotype diminishes Sp1 transcription factor binding and reduces risk for breast and ovarian cancer in Caucasians

MDM2 plays a key role in modulating p53 function. The MDM2 SNP309T > G promoter polymorphism enhances Sp1 binding and has been linked to cancer risk and young age at diagnosis although with conflicting evidence. We report a second MDM2 promoter polymorphism, SNP285G > C, residing on the SNP309G allele. SNP285C occurs in Caucasians only, where 7.7% (95% CI 7.6%-7.8%) of healthy individuals carry the SNP285C/309G haplotype. In vitro analyses reveals that SNP309G enhances but SNP285C strongly reduces Sp1 promoter binding. Comparing MDM2 promoter status among different cohorts of ovarian (n = 1993) and breast (n = 1973) cancer patients versus healthy controls (n = 3646), SNP285C reduced the risk of both ovarian (OR 0.74; CI 0.58-0.94) and breast cancer (OR 0.79; CI 0.62-1.00) among SNP309G carriers.

CoAIMs: a cost-effective panel of ancestry informative markers for determining continental origins

Background

Genetic ancestry is known to impact outcomes of genotype-phenotype studies that are designed to identify risk for common diseases in human populations. Failure to control for population stratification due to genetic ancestry can significantly confound results of disease association studies. Moreover, ancestry is a critical factor in assessing lifetime risk of disease, and can play an important role in optimizing treatment. As modern medicine moves towards using personal genetic information for clinical applications, it is important to determine genetic ancestry in an accurate, cost-effective and efficient manner. Self-identified race is a common method used to track and control for population stratification; however, social constructs of race are not necessarily informative for genetic applications. The use of ancestry informative markers (AIMs) is a more accurate method for determining genetic ancestry for the purposes of population stratification.

Methodology/Principal Findings

Here we introduce a novel panel of 36 microsatellite (MSAT) AIMs that determines continental admixture proportions. This panel, which we have named Continental Ancestry Informative Markers or CoAIMs, consists of MSAT AIMs that were chosen based upon their measure of genetic variance (F_st), allele frequencies and their suitability for efficient genotyping. Genotype analysis using CoAIMs along with a Bayesian clustering method (STRUCTURE) is able to discern continental origins including Europe/Middle East (Caucasians), East Asia, Africa, Native America, and Oceania. In addition to determining continental ancestry for individuals without significant admixture, we applied CoAIMs to ascertain admixture proportions of individuals of self declared race.

Conclusion/Significance

CoAIMs can be used to efficiently and effectively determine continental admixture proportions in a sample set. The CoAIMs panel is a valuable resource for genetic researchers performing case-control genetic association studies, as it can control for the confounding effects of population stratification. The MSAT-based approach used here has potential for broad applicability as a cost effective tool toward determining admixture proportions.

The emergence of translational epidemiology: from scientific discovery to population health impact

Recent emphasis on translational research (TR) is highlighting the role of epidemiology in translating scientific discoveries into population health impact. The authors present applications of epidemiology in TR through 4 phases designated T1-T4, illustrated by examples from human genomics. In T1, epidemiology explores the role of a basic scientific discovery (e.g., a disease risk factor or biomarker) in developing a "candidate application" for use in practice (e.g., a test used to guide interventions). In T2, epidemiology can help to evaluate the efficacy of a candidate application by using observational studies and randomized controlled trials. In T3, epidemiology can help to assess facilitators and barriers for uptake and implementation of candidate applications in practice. In T4, epidemiology can help to assess the impact of using candidate applications on population health outcomes. Epidemiology also has a leading role in knowledge synthesis, especially using quantitative methods (e.g., meta-analysis). To explore the emergence of TR in epidemiology, the authors compared articles published in selected issues of the Journal in 1999 and 2009. The proportion of articles identified as translational doubled from 16% (11/69) in 1999 to 33% (22/66) in 2009 (P = 0.02). Epidemiology is increasingly recognized as an important component of TR. By quantifying and integrating knowledge across disciplines, epidemiology provides crucial methods and tools for TR.

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.

Extending comprehensive cancer center expertise in clinical cancer genetics and genomics to diverse communities: the power of partnership

Rapidly evolving genetic and genomic technologies for genetic cancer risk assessment (GCRA) are revolutionizing the approach to targeted therapy and cancer screening and prevention, heralding the era of personalized medicine. Although many academic medical centers provide GCRA services, most people receive their medical care in the community setting. However, few community clinicians have the knowledge or time needed to adequately select, apply, and interpret genetic/genomic tests. This article describes alternative approaches to the delivery of GCRA services, profiling the City of Hope Cancer Screening & Prevention Program Network (CSPPN) academic and community-based health center partnership as a model for the delivery of the highest-quality evidence-based GCRA services while promoting research participation in the community setting. Growth of the CSPPN was enabled by information technology, with videoconferencing for telemedicine and Web conferencing for remote participation in interdisciplinary genetics tumor boards. Grant support facilitated the establishment of an underserved minority outreach clinic in the regional County hospital. Innovative clinician education, technology, and collaboration are powerful tools to extend GCRA expertise from a National Cancer Institute-designated Comprehensive Cancer Center, enabling diffusion of evidenced-base genetic/genomic information and best practice into the community setting.