Use of genomic panels to determine risk of developing type 2 diabetes in the general population: a targeted evidence-based review

Rates and Correlates of Incident Type 2 Diabetes Mellitus Among Persons Living With HIV-1 Infection

The prevalence of various comorbidities continue to rise in aging persons living with HIV-1 infection (PLWH), and our study here aimed to assess the rates and correlates of incident type 2 diabetes mellitus (T2DM) in PLWH from a retrospective, southeastern U.S. cohort. Based on electronic health records, we examined patient demographics, body mass index (BMI), HIV-1-related outcomes, hepatitis C virus co-infection, common comorbidities (e.g. shingles and asthma), usage of protease inhibitors, and usage of statins as potential correlates for T2DM occurrence. Among 3,975 PLWH with ≥12 months of follow-up between January 1999 and March 2018, the overall rate of incident T2DM was 135 per 10,000 person-years, almost 2-fold higher than the rate reported for the general U.S. population. In multivariable models (354 T2DM patients and 3,617 control subjects), sex, BMI, nadir CD4⁺ T-cell count, HIV-1 viral load (VL) and duration of statin use were independent correlates of incident T2DM (adjusted P <0.05 for all), with clear consistency in several sensitivity analyses. The strongest associations (adjusted odds ratio/OR >2.0 and P <0.0001) were noted for: i) statin use for ≥6 months (OR = 10.2), ii) BMI ≥30 kg/m² (OR = 3.4), and iii) plasma VL ≥200 copies/ml (OR = 2.2). Their collective predictive value was substantial: the C-statistic for area under the receiver operating characteristics curve was 0.87 (95% CI = 0.84-0.91), showing close similarity between two major racial groups (C-statistic = 0.87 for African Americans and 0.91 for European Americans). Overall, these findings not only establish a promising algorithm for predicting incident T2DM in PLWH but also suggest that patients who are obese and use statins should require special consideration for T2DM diagnosis and prevention.

Polymorphism of the Transcription Factor 7-Like 2 Gene (TCF7L2) Interacts with Obesity on Type-2 Diabetes in the PREDIMED Study Emphasizing the Heterogeneity of Genetic Variants in Type-2 Diabetes Risk Prediction: Time for Obesity-Specific Genetic Risk Scores

Nutrigenetic studies analyzing gene-diet interactions of the TCF7L2-rs7903146 C > T polymorphism on type-2 diabetes (T2D) have shown controversial results. A reason contributing to this may be the additional modulation by obesity. Moreover, TCF7L2-rs7903146 is one of the most influential variants in T2D-genetic risk scores (GRS). Therefore, to increase the predictive value (PV) of GRS it is necessary to first see whether the included polymorphisms have heterogeneous effects. We comprehensively investigated gene-obesity interactions between the TCF7L2-rs7903146 C > T polymorphism on T2D (prevalence and incidence) and analyzed other T2D-polymorphisms in a sub-sample. We studied 7018 PREDIMED participants at baseline and longitudinally (8.7 years maximum follow-up). Obesity significantly interacted with the TCF7L2-rs7903146 on T2D prevalence, associations being greater in non-obese subjects. Accordingly, we prospectively observed in non-T2D subjects (n = 3607) that its association with T2D incidence was stronger in non-obese (HR: 1.81; 95% CI: 1.13-2.92, p = 0.013 for TT versus CC) than in obese subjects (HR: 1.01; 95% CI: 0.61-1.66; p = 0.979; p-interaction = 0.048). Accordingly, TCF7L2-PV was higher in non-obese subjects. Additionally, we created obesity-specific GRS with ten T2D-polymorphisms and demonstrated for the first time their higher strata-specific PV. In conclusion, we provide strong evidence supporting the need for considering obesity when analyzing the TCF7L2 effects and propose the use of obesity-specific GRS for T2D.

The Application of Genomics in Diabetes: Barriers to Discovery and Implementation

The emerging availability of genomic and electronic health data in large populations is a powerful tool for research that has drawn interest in bringing precision medicine to diabetes. In this article, we discuss the potential application of genomics to the prediction, prevention, and treatment of diabetes, and we use examples from other areas of medicine to illustrate some of the challenges involved in conducting genomics research in human populations and implementing findings in practice. At this time, a major barrier to the application of genomics in diabetes care is the lack of actionable genomic findings. Whether genomic information should be used in clinical practice requires a framework for evaluating the validity and clinical utility of this approach, an improved integration of genomic data into electronic health records, and the clinical decision support and educational resources for clinicians to use these data. Efforts to identify optimal approaches in all of these domains are in progress and may help to bring diabetes into the era of genomic medicine.

Internet-Based Direct-to-Consumer Genetic Testing: A Systematic Review

Background

Direct-to-consumer genetic tests (DTC-GT) are easily purchased through the Internet, independent of a physician referral or approval for testing, allowing the retrieval of genetic information outside the clinical context. There is a broad debate about the testing validity, their impact on individuals, and what people know and perceive about them.

Objective

The aim of this review was to collect evidence on DTC-GT from a comprehensive perspective that unravels the complexity of the phenomenon.

Methods

A systematic search was carried out through PubMed, Web of Knowledge, and Embase, in addition to Google Scholar according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist with the key term “Direct-to-consumer genetic test.”

Results

In the final sample, 118 articles were identified. Articles were summarized in five categories according to their focus on (1) knowledge of, attitude toward use of, and perception of DTC-GT (n=37), (2) the impact of genetic risk information on users (n=37), (3) the opinion of health professionals (n=20), (4) the content of websites selling DTC-GT (n=16), and (5) the scientific evidence and clinical utility of the tests (n=14). Most of the articles analyzed the attitude, knowledge, and perception of DTC-GT, highlighting an interest in using DTC-GT, along with the need for a health care professional to help interpret the results. The articles investigating the content analysis of the websites selling these tests are in agreement that the information provided by the companies about genetic testing is not completely comprehensive for the consumer. Given that risk information can modify consumers’ health behavior, there are surprisingly few studies carried out on actual consumers and they do not confirm the overall concerns on the possible impact of DTC-GT. Data from studies that investigate the quality of the tests offered confirm that they are not informative, have little predictive power, and do not measure genetic risk appropriately.

Conclusions

The impact of DTC-GT on consumers’ health perceptions and behaviors is an emerging concern. However, negative effects on consumers or health benefits have yet to be observed. Nevertheless, since the online market of DTC-GT is expected to grow, it is important to remain aware of a possible impact.

Sequence and analysis of a whole genome from Kuwaiti population subgroup of Persian ancestry

Background

The 1000 Genome project paved the way for sequencing diverse human populations. New genome projects are being established to sequence underrepresented populations helping in understanding human genetic diversity. The Kuwait Genome Project an initiative to sequence individual genomes from the three subgroups of Kuwaiti population namely, Saudi Arabian tribe; “tent-dwelling” Bedouin; and Persian, attributing their ancestry to different regions in Arabian Peninsula and to modern-day Iran (West Asia). These subgroups were in line with settlement history and are confirmed by genetic studies. In this work, we report whole genome sequence of a Kuwaiti native from Persian subgroup at >37X coverage.

Results

We document 3,573,824 SNPs, 404,090 insertions/deletions, and 11,138 structural variations. Out of the reported SNPs and indels, 85,939 are novel. We identify 295 ‘loss-of-function’ and 2,314 ’deleterious’ coding variants, some of which carry homozygous genotypes in the sequenced genome; the associated phenotypes include pharmacogenomic traits such as greater triglyceride lowering ability with fenofibrate treatment, and requirement of high warfarin dosage to elicit anticoagulation response. 6,328 non-coding SNPs associate with 811 phenotype traits: in congruence with medical history of the participant for Type 2 diabetes and β-Thalassemia, and of participant’s family for migraine, 72 (of 159 known) Type 2 diabetes, 3 (of 4) β-Thalassemia, and 76 (of 169) migraine variants are seen in the genome. Intergenome comparisons based on shared disease-causing variants, positions the sequenced genome between Asian and European genomes in congruence with geographical location of the region. On comparison, bead arrays perform better than sequencing platforms in correctly calling genotypes in low-coverage sequenced genome regions however in the event of novel SNP or indel near genotype calling position can lead to false calls using bead arrays.

Conclusions

We report, for the first time, reference genome resource for the population of Persian ancestry. The resource provides a starting point for designing large-scale genetic studies in Peninsula including Kuwait, and Persian population. Such efforts on populations under-represented in global genome variation surveys help augment current knowledge on human genome diversity.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1233-x) contains supplementary material, which is available to authorized users.

Information-seeking and sharing behavior following genomic testing for diabetes risk

As the practice of medicine has become more patient-driven, patients are increasingly seeking health information within and outside of their doctor's office. Patients looking for information and support are often turning to the Internet as well as family and friends. As part of a study to understand the impact of delivery method of genomic testing for type 2 diabetes risk on comprehension and health-related behaviors, we assessed participants' information-seeking and sharing behaviors after receiving their results in-person with a genetic counselor or online through the testing company's website. We found that 32.6 % of participants sought information after receiving the genomic test results for T2DM; 80.8 % of those that did seek information turned to the Internet. Eighty-eight percent of participants reported that they shared their T2DM risk results, primarily with their spouse/partner (65 %) and other family members (57 %) and children (19 %); 14 % reported sharing results with their health provider. Sharing was significantly increased in those who received results in-person from the genetic counselor (p = 0.0001). Understanding patients' interests and needs for additional information after genomic testing and with whom they share details of their health is important as more information and clinical services are available and accessed outside the clinician's office. Genetic counselors' expertise and experience in creating educational materials and promoting sharing of genetic information can facilitate patient engagement and education.

Recommendations from the EGAPP Working Group: does genomic profiling to assess type 2 diabetes risk improve health outcomes?

SUMMARY OF RECOMMENDATIONS

The Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group (EWG) found insufficient evidence to recommend testing for predictive variants in 28 variants (listed in Table 1) to assess risk for type 2 diabetes in the general population, on the basis of studies in populations of northern European descent. The EWG found that the magnitude of net health benefit from the use of any of these tests alone or in combination is close to zero. The EWG discourages clinical use unless further evidence supports improved clinical outcomes.The EWG found insufficient evidence to recommend testing for the TCF7L2 gene to assess risk for type 2 diabetes in high-risk individuals. The EWG found that the magnitude of net health benefit from the use of this test is close to zero. The EWG discourages clinical use unless further evidence supports improved clinical outcomes.On the basis of the available evidence for both the scenarios, the overall certainty of net health benefit is deemed "low."

RATIONALE

It has been suggested that genomic profiling in the general population or in high-risk populations for type 2 diabetes might lead to management changes (e.g., earlier initiation or higher rates of medical interventions, or targeted recommendations for behavioral change) that improve type 2 diabetes outcomes or prevent type 2 diabetes. The EWG found no direct evidence to support this possibility; therefore, this review sought indirect evidence aimed at documenting the extent to which genomic profiling alters type 2 diabetes risk estimation, alone and in combination with traditional risk factors, and the extent to which risk classification improves health outcomes.

ANALYTIC VALIDITY

Assay-related evidence on available genomic profiling tests was deemed inadequate. However, on the basis of existing technologies that have been or may be used, the analytic sensitivity and specificity of tests for individual gene variants might be at least satisfactory.

CLINICAL VALIDITY

Twenty-eight candidate markers were evaluated in the general population. Evidence on clinical validity was rated inadequate for 24 of these associations (86%) and adequate for 4 (14%). Inadequate grades were based on limited evidence, poor replication, existence of possible biases, or combinations of these factors. Type 2 diabetes genomic profiling provided areas under the receiver operator characteristics curve of 55%-57%, with 4, 8, and 28 genes. Only TCF7L2 had convincing evidence of an association with type 2 diabetes with an odds ratio of 1.39 (95% confidence interval: 1.33-1.46).TCF7L2 was evaluated for high-risk populations, and the overall odds ratio was 1.66 (95% confidence interval: 1.22-2.27) for association with progression to type 2 diabetes.

CLINICAL UTILITY

No studies were available to provide direct evidence on the balance of benefits and harms for genetic profiling for type 2 diabetes alone or in addition to traditional risk factors in the general population.Evidence for high-risk populations and TCF7L2 was inadequate on the basis of two identified studies. These studies found close to zero additional benefit with the addition of genomic markers to traditional risk factors (diet, body mass index, and glucose tolerance).

CONTEXTUAL ISSUES

Prevention of type 2 diabetes is a public health priority. Improvements in the outcomes associated with genomic profiling could have important impacts. Traditional risk factors (e.g., body mass index, weight, fat mass, and exercise) have an advantage in clinical screening and risk assessment strategies because they measure the actual targets for therapy (e.g., fasting plasma glucose and medical interventions). To be useful in predicting disease risk, genomic testing should improve the predictive value of these traditional risk factors. Some issues important for clinical utility remain unknown, such as the level of risk that changes intervention, whether long-term disease outcomes will improve, how individuals being tested will understand/respond to test results and interact with the health-care system, and whether testing will motivate behavior change or amplify potential harms.