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Effect of Disclosing Genetic Risk for Coronary Heart Disease on Information Seeking and SharingCLINICAL PERSPECTIVE: The MI-GENES Study (Myocardial Infarction Genes)
Abstract
Background:
Whether disclosing genetic risk for coronary heart disease (CHD) to individuals influences information seeking and information sharing is not known. We hypothesized that disclosing genetic risk for CHD to individuals influences information seeking and sharing.
Methods and results:
The MI-GENES study (Myocardial Infarction Genes) randomized participants (n=203) aged 45 to 65 years who were at intermediate CHD risk based on conventional risk factors and not on statins to receive their conventional risk score alone or also a genetic risk score based on 28 variants. CHD risk was disclosed by a genetic counselor and then discussed with a physician. Surveys assessing information seeking were completed before and after risk disclosure. Information sharing was assessed post-disclosure. Six-month post-disclosure, genetic risk score participants were more likely than conventional risk score participants to visit a website to learn about CHD (odds ratio [OR], 4.88 [confidence interval (CI), 1.55-19.13]; P=0.01), use the internet for information about how genetic factors affect CHD risk (OR, 2.11 [CI, 1.03-4.47]; P=0.04), access their CHD risk via a patient portal (OR, 2.99 [CI, 1.35-7.04]; P=0.01), and discuss their CHD risk with others (OR, 3.13 [CI, 1.41-7.47]; P=0.01), particularly their siblings (OR, 1.92 [CI, 1.06-3.51]; P=0.03), extended family (OR, 3.8 [CI, 1.37-12.38]; P=0.01), coworkers (OR, 2.42 [CI, 1.09-5.76]; P=0.03), and primary care provider (PCP; OR, 2.00 [CI, 1.08-3.75]; P=0.03).
Conclusions:
Disclosure of a genetic risk score for CHD increased information seeking and sharing.
Clinical trial registration:
URL: https://clinicaltrials.gov/. Unique identifier: NCT01936675.
... High genetic risk and low levels of physical activity volume and intensity were associated with large increases in incident CAD. This study showed physical activity is beneficial regardless of an individual's underlying genetic risk and that genetic risk does not determine an individual's fate regarding CAD [49]. This has important public health implications because it suggests that older adults have a significant ability to decrease their risk of CAD by engaging in more-and particularly more intense-physical activity. ...
Previous research demonstrates the joint association of self-reported physical activity and genotype with coronary artery disease. However, an existing research gap is whether accelerometer-measured overall physical activity or physical activity intensity can offset genetic predisposition to coronary artery disease. This study explores the independent and joint associations of accelerometer-measured physical activity and genetic predisposition with incident coronary artery disease. Incident coronary artery disease based on hospital inpatient records and death register data serves as the outcome of this study. Polygenic risk score and overall physical activity, measured as Euclidean Norm Minus One, and intensity, measured as minutes per day of moderate-to-vigorous intensity physical activity (MVPA), are examined both linearly and by decile. The UK Biobank population-based cohort recruited over 500,000 individuals aged 40 to 69 between 2006 and 2010, with 103,712 volunteers participating in a weeklong wrist-worn accelerometer study from 2013 to 2015. Individuals of White British ancestry (n = 65,079) meeting the genotyping and accelerometer-based inclusion criteria and with no missing covariates were included in the analytic sample. In the sample of 65,079 individuals, the mean (SD) age was 62.51 (7.76) and 61% were female. During a median follow-up of 6.8 years, 1,382 cases of coronary artery disease developed. At the same genetic risk, physical activity intensity had a hazard ratio (HR) of 0.41 (95% CI: 0.29–0.60) at the 90th compared to 10th percentile, equivalent to 31.68 and 120.96 minutes of moderate-to-vigorous physical activity per day, respectively, versus an HR of 0.61 (95% CI: 0.52–0.72) for overall physical activity. The combination of high genetic risk and low physical activity intensity showed the greatest risk, with an individual at the 10th percentile of genetic risk and 90th percentile of intensity facing an HR of 0.14 (95% CI: 0.09–0.21) compared to an individual at the 90th percentile of genetic risk and 10th percentile of intensity. Physical activity, especially physical activity intensity, is associated with an attenuation of some of the risk of coronary artery disease but this pattern does not vary by genetic risk. This accelerometer-based study provides the clearest evidence to date regarding the joint influence of genetics, overall physical activity, and physical activity intensity on coronary artery disease.
... Surveys show that the majority of internet users in the United States use online sources as their primary source of health information. 23,24 However, the lack of reliable information has been well documented, sowing distrust among users. 25 Authoritative print, video, and internet multimedia developed by universities, hospitals, and science centers can help to address the communication gap between research/medical communities and the general public. ...
Polygenic risk scores (PRS) have potential to improve healthcare by identifying individuals at elevated risk for common complex conditions. Use of PRS in clinical practice, however, requires careful assessment of the needs and capabilities of patients, providers, and healthcare systems. The electronic Medical Records and Genomics (eMERGE) Network is conducting a collaborative study which will return PRS to 25,000 pediatric and adult participants. All participants will receive a risk report, potentially classifying them as high risk (∼2-10% per condition) for one or more of 10 conditions based on PRS. The study population is enriched by participants from racial and ethnic minority populations, underserved populations, and populations who experience poorer medical outcomes. All ten eMERGE clinical sites conducted focus groups, interviews, and/or surveys to understand educational needs among key stakeholders - participants, providers, and/or study staff. Together, these studies highlighted the need for tools that address the perceived benefit/value of PRS, types of education/support needed, accessibility, and PRS-related knowledge and understanding. Based on findings from these preliminary studies, the network harmonized training initiatives and formal/informal educational resources. This paper summarizes eMERGE's collective approach to assessing educational needs and developing educational approaches for primary stakeholders. It discusses challenges encountered and solutions provided.
... They are most likely to be first used in clinical practice to add information to currently used risk scores, for example in cardiovascular risk prediction models [17][18][19]. Ongoing research aims to ascertain whether framing clinical risk discussions in the context of genetic risk is acceptable to patients and clinicians, and whether it changes risk behaviours and outcomes [20]. In some individuals, their genetic risk may push them into a higher risk category than traditional risk factors, for example with cardiovascular disease estimation, and therefore might modify their management plans [21]. ...
Multimorbidity has increased in prevalence world-wide. It is anticipated to affect over 1 in 6 of the UK population by 2035 and is now recognised as a global priority for health research. Genomic medicine has rapidly advanced over the last 20 years from the first sequencing of the human genome to integration into clinical care for rarer conditions. Genetic studies help identify new disease mechanisms as they are less susceptible to the bias and confounding that affects epidemiological studies, as genetics are assigned from conception. There is also genetic variation in the efficacy of medications and the risk of side effects, pharmacogenetics. Genomic approaches offer the potential to improve our understanding of mechanisms underpinning multiple long-term conditions/multimorbidity and guide precision approaches to risk, diagnosis and optimisation of management. In this commentary as part of the Age and Ageing 50th anniversary commentary series, we summarise genomics and the potential utility of genomics in multimorbidity.
... There is still limited data on whether disclosure of PRS information motivates health behavior changes across a spectrum of common diseases, but emerging evidence suggests a potentially beneficial behavioral impact for CAD risk. Studies of disclosure of CAD PRSs found increased perception of personal control and increased information seeking 30 , favorable health behaviors 31 , and increased shared decision-making resulting in more statin prescriptions 32 . Nonetheless, given that multiple factors besides the disclosure of genetic risk can impact health behaviors 29 , future disease risk communication strategies should carefully consider the relative and combined effects of all relevant types of information. ...
Polygenic risk scores (PRSs) aggregate the many small effects of alleles across the human genome to estimate the risk of a disease or disease-related trait for an individual. The potential benefits of PRSs include cost-effective enhancement of primary disease prevention, more refined diagnoses and improved precision when prescribing medicines. However, these must be weighed against the potential risks, such as uncertainties and biases in PRS performance, as well as potential misunderstanding and misuse of these within medical practice and in wider society. By addressing key issues including gaps in best practices, risk communication and regulatory frameworks, PRSs can be used responsibly to improve human health. Here, the International Common Disease Alliance’s PRS Task Force, a multidisciplinary group comprising expertise in genetics, law, ethics, behavioral science and more, highlights recent research to provide a comprehensive summary of the state of polygenic score research, as well as the needs and challenges as PRSs move closer to widespread use in the clinic. As polygenic risk scores move closer to widespread clinical use, this Perspective summarizes the benefits, risks and challenges to be overcome.
... Smaller-sized studies, including a few hundred participants, have previously reported that disclosure of PRS for coronary heart disease associates with increased perception of personal control 15 , in addition to increased information seeking and sharing 16 . In accordance with these findings our study further adds that receiving personal genome-based disease risk information motivates individuals at elevated disease risk more than others, and show that a substantial proportion of individuals at high risk also undertake relevant actions to promote their health. ...
Background. Algorithms including both traditional risk factors and polygenic risk scores (PRS) can significantly improve prediction of atherosclerotic cardiovascular disease (ASCVD). However, the clinical benefit of adding PRS to clinical risk evaluation remains unclear.
Objectives. The study evaluated the attitudes of 7,342 individuals (64% women, mean age 56 yrs) upon receiving personal genome-enhanced ASCVD risk information, and prospectively assessed the impact on the participants' health behavior.
Methods. The participant's 10-year risk for ASCVD was estimated using both a traditional clinical risk score and a PRS-enhanced score, and both scores were communicated directly to study participants with an interactive web-tool.
Results. When reassessed after 1.5 years by a clinical visit and questionnaires, 20.8% of individuals at high (>10%) ASCVD risk had seen a doctor, 12.4% reported weight loss, 14.2% of smokers had quit smoking, and 15.4% had signed up for health coaching online. Altogether, 42.6% of individuals at high risk had made some health behavioral change compared to 33.5% of persons at low/average risk such that a higher baseline risk predicted a favorable change (p<0.001), with both clinical (p<0.001) and genomic factors (p=0.003) contributing independently. Seeing a doctor and weight loss both resulted in clinically significant improvement of lipid profiles (lower LDL-cholesterol and triglycerides) and lower systolic blood pressure (p<0.01).
Conclusions. Web-based communication of personal ASCVD risk-data including polygenic risk to middle-aged persons can motivate positive changes in health behavior. It supports integration of genomic information into clinical risk calculators as a feasible approach to enhance disease prevention.
Background
Millions of cancer survivors are at risk of cardiovascular diseases, a leading cause of morbidity and mortality. Tools to potentially facilitate implementation of cardiology guidelines, consensus recommendations, and scientific statements to prevent atherosclerotic cardiovascular disease (ASCVD) and other cardiovascular diseases are limited. Thus, inadequate utilization of cardiovascular medications and imaging is widespread, including significantly lower rates of statin use among cancer survivors for whom statin therapy is indicated.
Methods
In this methodological study, we leveraged published guidelines documents to create a rules-based tool to include guidelines, expert consensus, and medical society scientific statements relevant to point of care cardiovascular disease prevention in the cardiovascular care of cancer survivors. Any overlap, redundancy, or ambiguous recommendations were identified and eliminated across all converted sources of knowledge. The integrity of the tool was assessed with use case examples and review of subsequent care suggestions.
Results
An initial selection of 10 guidelines, expert consensus, and medical society scientific statements was made for this study. Then 7 were kept owing to overlap and revisions in society recommendations over recent years. Extensive formulae were employed to translate the recommendations of 7 selected guidelines into rules and proposed action measures. Patient suitability and care suggestions were assessed for several use case examples.
Conclusion
A simple rules-based application was designed to provide a potential format to deliver critical cardiovascular disease best-practice prevention recommendations at the point of care for cancer survivors. A version of this tool may potentially facilitate implementing these guidelines across clinics, payers, and health systems for preventing cardiovascular diseases in cancer survivors.
Trial Registration
ClinicalTrials.Gov Identifier: NCT05377320.
Background
Genetic factors are not included in prediction models for coronary heart disease (CHD).
Objectives
The authors assessed the predictive utility of a polygenic risk score (PRS) for CHD (defined as myocardial infarction, coronary revascularization, or cardiovascular death) and whether the risks due to monogenic familial hypercholesterolemia (FH) and family history (FamHx) are independent of and additive to the PRS.
Methods
In UK-biobank participants, PRSCHD was calculated using metaGRS, and 10-year risk for incident CHD was estimated using the pooled cohort equations (PCE). The area under the curve (AUC) of the receiver operator curve and net reclassification improvement (NRI) were assessed. FH was defined as the presence of a pathogenic or likely pathogenic variant in LDLR, APOB, or PCSK9. FamHx was defined as a diagnosis of CHD in first-degree relatives. Independent and additive effects of PRSCHD, FH, and FamHx were evaluated in stratified analyses.
Results
In 323,373 participants with genotype data, the addition of PRSCHD to PCE increased the AUC from 0.759 (95% CI: 0.755-0.763) to 0.773 (95% CI: 0.769-0.777). The AUC and NRIEvent for PRSCHD were higher before the age of 55 years. Of 199,997 participants with exome sequence data, 10,000 had a PRSCHD ≥95th percentile (PRSP95), 673 had FH, and 46,163 had FamHx. The CHD risk associated with PRSP95 was independent of FH and FamHx. The risks associated with combinations of PRSCHD, FH, and FamHx were additive and comprehensive estimates could be obtained by multiplying the risk from each genetic factor.
Conclusions
Incorporating PRSCHD into the PCE improves risk prediction for CHD, especially at younger ages. The associations of PRSCHD, FH, and FamHx with CHD were independent and additive.
Background
The many improvements in cancer therapies have led to an increased number of survivors, which comes with a greater risk of consequent/subsequent cardiovascular disease. Identifying effective management strategies that can mitigate this risk of cardiovascular complications is vital. Therefore, developing computer-driven and personalized clinical decision aid interventions that can provide early detection of patients at risk, stratify that risk, and recommend specific cardio-oncology management guidelines and expert consensus recommendations is critically important.
Objectives
To assess the feasibility, acceptability, and utility of the use of an artificial intelligence (AI)-powered clinical decision aid tool in shared decision making between the cancer survivor patient and the cardiologist regarding prevention of cardiovascular disease.
Design
This is a single-center, double-arm, open-label, randomized interventional feasibility study. Our cardio-oncology cohort of > 4000 individuals from our Clinical Research Data Warehouse will be queried to identify at least 200 adult cancer survivors who meet the eligibility criteria. Study participants will be randomized into either the Clinical Decision Aid Group (where patients will use the clinical decision aid in addition to current practice) or the Control Group (current practice). The primary endpoint of this study is to assess for each patient encounter whether cardiovascular medications and imaging pursued were consistent with current medical society recommendations. Additionally, the perceptions of using the clinical decision tool will be evaluated based on patient and physician feedback through surveys and focus groups.
Summary
This trial will determine whether a clinical decision aid tool improves cancer survivors’ medication use and imaging surveillance recommendations aligned with current medical guidelines.
Trial registration
ClinicalTrials.Gov Identifier: NCT05377320
Purpose of review:
Recent advances in genetics have facilitated the calculation of polygenic risk scores (PRSs) based on common genetic risk variants of coronary artery disease (CAD). Here, we provide an explanation of the genetic basis for PRSs and review recent literature investigating PRSs and the clinical utility for different aspects of CAD.
Recent findings:
CAD-based PRSs are strongly associated with atherosclerosis burden in the coronary arteries and other vascular beds. In multiple studies, PRSs have proven to be a measure of CAD risk, more powerful than most established risk factors alone, that can be used from early life to stratify individuals into varying trajectories of lifetime risk. When implemented in risk stratification models for primary prevention of cardiovascular disease, PRSs provide modest improvements in discrimination (C-index generally increasing 0-4% points) and reclassification, but yield significant clinical benefit as a risk enhancer. Additionally, data suggest possible value of PRSs for aiding decisions in other aspects of diagnostics and treatment in CAD.
Summary:
Once genotyped, the genetic information may be used to calculate an infinite number of PRSs and contribute to personalize medicine providing clinical value for risk stratification, diagnostics and treatment in CAD as well as in other diseases.
Recent discoveries from the past 15 years of human genetic association studies have provided new insights into the common genetic basis of coronary artery disease and its risk factors including molecular traits like circulating lipid/lipoprotein levels. Polygenic risk scores, which aggregate findings from these large genetic studies, have been developed to predict clinical disease and stratify treatment response in clinical trials. In this review, we describe common methods for calculating polygenic risk scores, highlight examples related to coronary artery disease and lipid traits, and discuss opportunities and challenges for clinical implementation.
Background:
Prediction tools that combine polygenic risk scores with clinical factors provide a new opportunity for improved prediction and prevention of atherosclerotic cardiovascular disease, but the clinical utility of polygenic risk score has remained unclear.
Methods:
We collected a prospective cohort of 7342 individuals (64% women, mean age 56 years) and estimated their 10-year risk for atherosclerotic cardiovascular disease both by a traditional risk score and a composite score combining the effect of a polygenic risk score and clinical risk factors. We then tested how returning the personal risk information with an interactive web-tool impacted on the participants' health behavior.
Results:
When reassessed after 1.5 years by a clinical visit and questionnaires, 20.8% of individuals at high (>10%) 10-year atherosclerotic cardiovascular disease risk had seen a doctor, 12.4% reported weight loss, 14.2% of smokers had quit smoking, and 15.4% had signed up for health coaching online. Altogether, 42.6% of persons at high risk had made one or more health behavioral changes versus 33.5% of persons at low/average risk such that higher baseline risk predicted a favorable change (OR [CI], 1.53 [1.37-1.72] for persons at high risk versus the rest, P<0.001), with both high clinical (P<0.001) and genomic risk (OR [CI], 1.10 [1.03-1.17], P=0.003) contributing independently.
Conclusions:
Web-based communication of personal atherosclerotic cardiovascular disease risk-data including polygenic risk to middle-aged persons motivates positive changes in health behavior and the propensity to seek care. It supports integration of genomic information into clinical risk calculators as a feasible approach to enhance disease prevention.
Over the past decade, substantial progress has been made in the discovery of alleles contributing to the risk of coronary artery disease. In addition to providing causal insights into disease, these endeavours have yielded and enabled the refinement of polygenic risk scores. These scores can be used to predict incident coronary artery disease in multiple cohorts and indicate the clinical response to some preventive therapies in post hoc analyses of clinical trials. These observations and the widespread ability to calculate polygenic risk scores from direct-to-consumer and health-care-associated biobanks have raised many questions about responsible clinical adoption. In this Review, we describe technical and downstream considerations for the derivation and validation of polygenic risk scores and current evidence for their efficacy and safety. We discuss the implementation of these scores in clinical medicine for uses including risk prediction and screening algorithms for coronary artery disease, prioritization of patient subgroups that are likely to derive benefit from treatment, and efficient prospective clinical trial designs.
Genetic testing for cardiovascular (CV) disease has had a profound impact on the diagnosis and evaluation of monogenic causes of CV disease, such as hypertrophic and familial cardiomyopathies, long QT syndrome, and familial hypercholesterolemia (FH). The success in genetic testing for monogenic diseases has prompted special interest in utilizing genetic information in the risk assessment of more common diseases such as atherosclerotic cardiovascular disease (ASCVD). Polygenic risk scores (PRS) have been developed to assess the risk of coronary artery disease (CAD) that now include millions of single-nucleotide polymorphisms (SNPs) that have been identified through genome-wide association studies (GWAS). While these PRS have demonstrated a strong association with CAD in large cross-sectional population studies, there remains intense debate regarding the added value that PRS contribute to existing clinical risk prediction models such as the pooled cohort equations (PCEs). In this review, we provide a brief background of genetic testing for monogenic drivers of CV disease and then focus on the recent developments in genetic risk assessment of ASCVD, including the use of PRS. We outline the genetic testing that is currently available to all cardiologists in the clinic and discuss the evolving sphere of specialized cardiovascular genetics programs (CVGPs) that integrate the expertise of cardiologists, geneticists, and genetic counselors. Finally, we review the possible implications that PRS and pharmacogenomic data may soon have on clinical practice in the care for patients with or at risk of developing ASCVD.
Because polygenic risk scores (PRSs) for coronary heart disease (CHD) are derived from mainly European ancestry (EA) cohorts, their validity in African ancestry (AA) and Hispanic ethnicity (HE) individuals is unclear. We investigated associations of “restricted” and genome-wide PRSs with CHD in three major racial and ethnic groups in the U.S. The eMERGE cohort (mean age 48 ± 14 years, 58% female) included 45,645 EA, 7,597 AA, and 2,493 HE individuals. We assessed two restricted PRSs (PRSTikkanen and PRSTada; 28 and 50 variants, respectively) and two genome-wide PRSs (PRSmetaGRS and PRSLDPred; 1.7 M and 6.6 M variants, respectively) derived from EA cohorts. Over a median follow-up of 11.1 years, 2,652 incident CHD events occurred. Hazard and odds ratios for the association of PRSs with CHD were similar in EA and HE cohorts but lower in AA cohorts. Genome-wide PRSs were more strongly associated with CHD than restricted PRSs were. PRSmetaGRS, the best performing PRS, was associated with CHD in all three cohorts; hazard ratios (95% CI) per 1 SD increase were 1.53 (1.46–1.60), 1.53 (1.23–1.90), and 1.27 (1.13–1.43) for incident CHD in EA, HE, and AA individuals, respectively. The hazard ratios were comparable in the EA and HE cohorts (pinteraction = 0.77) but were significantly attenuated in AA individuals (pinteraction= 2.9 × 10⁻³). These results highlight the potential clinical utility of PRSs for CHD as well as the need to assemble diverse cohorts to generate ancestry- and ethnicity PRSs.
Evidence of the effects of genetic risk score (GRS) on secondary prevention is scarce and mixed. We investigated whether coronary artery disease (CAD) susceptible loci can be used to predict the risk of major adverse cardiovascular events (MACE) in a cohort with acute coronary syndromes (ACS). A total of 1667 patients hospitalized with ACS were enrolled and prospectively followed for a median of 2 years. We constructed a weighted GRS comprising 79 CAD risk variants and investigated the association between GRS and MACE using a multivariable cox proportional hazards regression model. The incremental value of adding GRS into the prediction model was assessed by integrated discrimination improvement (IDI) and decision curve analysis (DCA). In the age- and sex-adjusted model, each increase in standard deviation in the GRS was associated with a 33% increased risk of MACE (HR: 1.33, 95% CI: 1.10-1.61; P = 0.003), with this association not attenuating after further adjustment for traditional cardiovascular risk factors. Addition of GRS to a prediction model of seven clinical risk factors and EPICOR prognostic model slightly improved risk stratification for MACE as calculated by IDI (+1.7%, P = 0.006; +0.3%, P = 0.024, respectively). DCA demonstrated positive net benefits by adding GRS to other models. GRS was associated with MACE after multivariable adjustment in a cohort comprising Chinese ACS patients. Future studies are needed to validate our results and further evaluate the predictive value of GRS in secondary prevention.
Purpose of Review
The genetic counseling profession is growing rapidly, as is its presence in cardiology. In this review, we will survey recent innovations and research in cardiovascular genetic counseling, as well as findings from the broader genetic counseling field that are relevant to cardiovascular genetic counseling.
Recent Findings
Research into the structure of services finds that genetic counselors are increasingly being embedded within cardiology departments and that cardiologists value their expertise and contributions. Findings from other genetic counseling subspecialties and from clinical psychology suggest this trend toward moving genetic counselors into the cardiology clinic will increase access, timeliness, and uptake of genetics services. Studies on the selection and interpretation of genetic tests in cardiology have shown that there is a need for specialized expertise in these areas. This has led clinical genetic counselors, in collaboration with their physician colleagues, to take a more active role in assessing whether genetic variants contribute to disease. Evidence on the psychological and behavioral impact of cardiovascular genetic counseling is beginning to emerge with several non-randomized and one randomized study showing benefit. As investigators, genetic counselors are leading studies that generate practice-shaping insights into inherited cardiovascular disease, including the genetic underpinnings of disease, natural history, prognosis, psychological impact, and genetic test interpretation.
Summary
Genetic counseling is in its early days as an academic and scientific discipline, yet there are, nonetheless, several notable recent findings that are shaping the field.
Background
Recent GWAS studies have identified more than 300 SNPs associated with variation in blood pressure. We investigated whether a genetic risk score constructed from these variants is associated with burden of coronary heart disease.
Methods
From 2010–2014, 4,809 individuals admitted to coronary angiography in Capital Region of Copenhagen were genotyped. We calculated hypertension GRS comprised of GWAS identified SNPs associated with blood pressure. We performed logistic regression analyses to estimate the risk of hypertension and prevalent CHD. We also assessed the severity of CHD associated with the GRS. The analyses were performed using GRS quartiles. We used the Inter99 cohort to validate our results and to investigate for possible pleiotropy for the GRS with other CHD risk factors.
Results
In COGEN, adjusted odds ratios comparing the 2nd, 3rd and 4th cumulative GRS quartiles with the reference were 1.12(95% CI 0.95–1.33), 1.35(95% CI 1.14–1.59) and 1.29(95% CI 1.09–1.53) respectively, for prevalent CHD. The adjusted multinomial logistic regression showed that 3rd and 4th GRS quartiles were associated with increased odds of developing two(OR 1.33, 95% CI 1.04–1.71 and OR 1.36, 95% CI 1.06–1.75, respectively) and three coronary vessel disease(OR 1.77, 95% CI 1.36–2.30 and OR 1.65, 95% CI 1.26–2.15, respectively). Similar results for incident CHD were observed in the Inter99 cohort. The hypertension GRS did not associate with type 2 diabetes, smoking, BMI or hyperlipidemia.
Conclusion
Hypertension GRS quartiles were associated with an increased risk of hypertension, prevalent CHD, and burden of coronary vessel disease in a dose-response pattern. We showed no evidence for pleiotropy with other risk factors for CHD.
Dyslipidaemias encompass about two dozen relatively rare monogenic disorders and syndromes for which the genetic basis has largely been defined. In addition, the complex polygenic basis of disturbed lipids and lipoproteins has been characterised in many patients, and has been shown to result from accumulation of many common polymorphisms with small effects on lipids. Genetic technologies, including dedicated genotyping and sequencing methods can detect both rare and common DNA variants underlying dyslipidaemias. Some dyslipidaemias may be clinically silent for years, but early diagnosis, including genetic diagnosis, may permit early intervention to prevent or delay deleterious downstream clinical consequences, such as premature vascular disease or acute pancreatitis. The potential clinical utility of genetic testing for familial hypercholesterolaemia, familial chylomicronaemia syndrome, lysosomal acid lipase deficiency and some others will increase demand for reliable genetic diagnostic methods. We review some current technologies, such as targeted next-generation sequencing that seem to be helpful with DNA diagnosis of dyslipidaemias. We also address technical, biological and clinical limitations of genetic testing in dyslipidaemias. Finally, genetic counselling issues, the potential impact of results on patients and health care providers, current gaps and future directions will be discussed.
Initial genomewide association studies were exceptional owing to an ability to yield novel and reliable evidence for heritable contributions to complex disease and phenotype. However the top results alone were certainly not responsible for a wave of new predictive tools. Despite this, even studies small by contemporary standards were able to provide estimates of the relative contribution of all recorded genetic variants to outcome. Sparking efforts to quantify heritability, these results also provided the material for genomewide prediction. A fantastic growth in the performance of human genetic studies has only served to improve the potential of these complex, but potentially informative predictors. Prompted by these conditions and recent work, this letter explores the likely utility of these predictors, considers how clinical practice might be altered through their use, how to measure the efficacy of this and some of the potential ethical issues involved. Ultimately we suggest that for common genetic variation at least, the future should contain an acceptance of complexity in genetic architecture and the possibility of useful prediction even if only to shift the way we interact with clinical service providers.
Importance
Genetic and lifestyle factors both contribute to the risk of developing cardiovascular disease, but whether poor health behaviors are associated with similar increases in risk among individuals with low, intermediate, or high genetic risk is unknown.
Objective
To investigate the association of combined health behaviors and factors within genetic risk groups with coronary artery disease, atrial fibrillation, stroke, hypertension, and type 2 diabetes as well as to investigate the interactions between genetic risk and lifestyle.
Design, Setting, and Participants
The UK Biobank cohort study includes more than 500 000 participants aged 40 to 70 years who were recruited from 22 assessment centers across the United Kingdom from 2006 to 2010. A total of 339 003 unrelated individuals of white British descent with available genotype and matching genetic data and reported sex were included in this study from the UK Biobank population-based sample. Individuals were included in the analyses of 1 or more new-onset diseases. Data were analyzed from April 2006 to March 2015.
Main Outcomes and Measures
Risks of new-onset cardiovascular disease and diabetes associated with genetic risk and combined health behaviors and factors. Genetic risk was categorized as low (quintile 1), intermediate (quintiles 2-4), or high (quintile 5). Within each genetic risk group, the risks of incident events associated with ideal, intermediate, or poor combined health behaviors and factors were investigated and compared with low genetic risk and ideal lifestyle.
Results
Of 339 003 individuals, 181 702 (53.6%) were female, and the mean (SD) age was 56.86 (7.99) years. During follow-up, 9771 of 325 133 participants (3.0%) developed coronary artery disease, 7095 of 333 637 (2.1%) developed atrial fibrillation, 3145 of 332 971 (0.9%) developed stroke, 11 358 of 234 651 (4.8%) developed hypertension, and 4379 of 322 014 (1.4%) developed diabetes. Genetic risk and lifestyle were independent predictors of incident events, and there were no interactions for any outcome. Compared with ideal lifestyle in the low genetic risk group, poor lifestyle was associated with a hazard ratio of up to 4.54 (95% CI, 3.72-5.54) for coronary artery disease, 5.41 (95% CI, 4.29-6.81) for atrial fibrillation, 4.68 (95% CI, 3.85-5.69) for hypertension, 2.26 (95% CI, 1.63-3.14) for stroke, and 15.46 (95% CI, 10.82-22.08) for diabetes in the high genetic risk group.
Conclusions and Relevance
In this large contemporary population, genetic composition and combined health behaviors and factors had a log-additive effect on the risk of developing cardiovascular disease. The relative effects of poor lifestyle were comparable between genetic risk groups. Behavioral lifestyle changes should be encouraged for all through comprehensive, multifactorial approaches, although high-risk individuals may be selected based on the genetic risk.
Precision medicine strives to delineate disease using multiple data sources—from genomics to digital health metrics—in order to be more precise and accurate in our diagnoses, definitions, and treatments of disease subtypes. By defining disease at a deeper level, we can treat patients based on an understanding of the molecular underpinnings of their presentations, rather than grouping patients into broad categories with one-size-fits-all treatments. In this review, the authors examine how precision medicine, specifically that surrounding genetic testing and genetic therapeutics, has begun to make strides in both common and rare cardiovascular diseases in the clinic and the laboratory, and how these advances are beginning to enable us to more effectively define risk, diagnose disease, and deliver therapeutics for each individual patient.
The first human genome project, completed in 2003, uncovered the genetic building blocks of humankind. Painstakingly cataloguing the basic constituents of our DNA (‘genome sequencing’) took ten years, over three billion dollars and was a multinational collaboration. Since then, our ability to sequence genomes has been finessed so much that by 2018 it is possible to explore the 20,000 or so human genes for under £1000, in a matter of days. Such testing offers clues to our past, present and future health, as well as information about how we respond to medications so that truly ‘personalised medicine’ is now moving closer to a reality.
The impact of such a ‘genomic era’ is likely to have some level of impact on an increasingly large number of us, even if we are not directly using healthcare services ourselves. We explore how advancements in genetics are likely to be experienced by people, as patients, consumers and citizens; and urge policy makers to take stock of the pervasive nature of the technology as well as the human response to it.
The first human genome project, completed in 2003, uncovered the genetic building blocks of humankind. Painstakingly cataloguing the basic constituents of our DNA (‘genome sequencing’) took ten years, over three billion dollars and was a multinational collaboration. Since then, our ability to sequence genomes has been finessed so much that by 2017 it is possible to explore the 20,000 or so human genes for under £1000, in a matter of days. Such testing offers clues to our past, present and future health, as well as information about how we respond to medications so that truly ‘personalised medicine’ is now a reality.
The impact of such a ‘genomic era’ is likely to have some level of impact on all of us, even if we are not directly using healthcare services ourselves. We explore how advancements in genetics are likely to be experienced by people, as patients, consumers and citizens; and urge policy makers to take stock of the pervasive nature of the technology as well as the human response to it.
Background
Both genetic and lifestyle factors contribute to individual-level risk of coronary artery disease. The extent to which increased genetic risk can be offset by a healthy lifestyle is unknown.
Methods
Using a polygenic score of DNA sequence polymorphisms, we quantified genetic risk for coronary artery disease in three prospective cohorts — 7814 participants in the Atherosclerosis Risk in Communities (ARIC) study, 21,222 in the Women’s Genome Health Study (WGHS), and 22,389 in the Malmö Diet and Cancer Study (MDCS) — and in 4260 participants in the cross-sectional BioImage Study for whom genotype and covariate data were available. We also determined adherence to a healthy lifestyle among the participants using a scoring system consisting of four factors: no current smoking, no obesity, regular physical activity, and a healthy diet.
Results
The relative risk of incident coronary events was 91% higher among participants at high genetic risk (top quintile of polygenic scores) than among those at low genetic risk (bottom quintile of polygenic scores) (hazard ratio, 1.91; 95% confidence interval [CI], 1.75 to 2.09). A favorable lifestyle (defined as at least three of the four healthy lifestyle factors) was associated with a substantially lower risk of coronary events than an unfavorable lifestyle (defined as no or only one healthy lifestyle factor), regardless of the genetic risk category. Among participants at high genetic risk, a favorable lifestyle was associated with a 46% lower relative risk of coronary events than an unfavorable lifestyle (hazard ratio, 0.54; 95% CI, 0.47 to 0.63). This finding corresponded to a reduction in the standardized 10-year incidence of coronary events from 10.7% for an unfavorable lifestyle to 5.1% for a favorable lifestyle in ARIC, from 4.6% to 2.0% in WGHS, and from 8.2% to 5.3% in MDCS. In the BioImage Study, a favorable lifestyle was associated with significantly less coronary-artery calcification within each genetic risk category.
Conclusions
Across four studies involving 55,685 participants, genetic and lifestyle factors were independently associated with susceptibility to coronary artery disease. Among participants at high genetic risk, a favorable lifestyle was associated with a nearly 50% lower relative risk of coronary artery disease than was an unfavorable lifestyle. (Funded by the National Institutes of Health and others.)
Precision medicine focuses on understanding individual variability in disease prevention, care, and treatment. The Precision Medicine Initiative, launched by President Obama in early 2015, aims to bring this approach to all areas of health care. However, few consumer-friendly resources exist for the public to learn about precision medicine and the conditions that could be affected by this approach to care. Genetics Home Reference, a website from the US National Library of Medicine, seeks to support precision medicine education by providing the public with summaries of genetic conditions and their associated genes, as well as information about issues related to precision medicine such as disease risk and pharmacogenomics. With the advance of precision medicine, consumer-focused resources like Genetics Home Reference can be foundational in providing context for public understanding of the increasing amount of data that will become available.
Background
New avenues of data collection such as eHealth and mobile technology have the potential to revolutionize the way large populations can be assessed and managed outside of standard research and clinical settings.
Methods and Results
A digital connectedness survey was administered within the Framingham Heart Study from 2014 to 2015. The exposure was usage of the Internet, email, cell phones, and smartphones in relation to demographic and cardiovascular disease risk factors; all results were adjusted for age and sex. Among 8096 living study participants, 6503 (80.3%) completed the digital survey. Among survey responders, 5678 (87.4%) reported regular Internet use. Participants reporting regular Internet use were younger (aged 59.1 versus 76.5 years, P<0.0001), were more likely to be employed (70.3% versus 23.7%, P=0.002), and had more favorable cardiovascular disease risk factors than those who did not use the Internet (all P≤0.05). Overall, 5946 (92.1%) responders reported using cell phones. Among cell phone users, 3907 (67.8%) had smartphones. Smartphone users were younger (aged 55.4 versus 68.5 years, P<0.0001), more likely to be employed (81.1% versus 43.9%, P<0.0001) and to have a college education, and less likely to have hypertension (27.9% versus 55.7%, P=0.0002) than those who did not use smartphones.
Conclusions
Digital connectedness varies substantially by age; connected persons tend to be younger and better educated and to have more favorable cardiovascular disease risk factor profiles. Less than two‐thirds of study participants who completed the survey had a smartphone. The generalizability of studies focused on digitally connected persons may have limitations.
Objective:
To assess the impact of communicating DNA based disease risk estimates on risk-reducing health behaviours and motivation to engage in such behaviours.
Design:
Systematic review with meta-analysis, using Cochrane methods.
Data sources:
Medline, Embase, PsycINFO, CINAHL, and the Cochrane Central Register of Controlled Trials up to 25 February 2015. Backward and forward citation searches were also conducted.
Study selection:
Randomised and quasi-randomised controlled trials involving adults in which one group received personalised DNA based estimates of disease risk for conditions where risk could be reduced by behaviour change. Eligible studies included a measure of risk-reducing behaviour.
Results:
We examined 10,515 abstracts and included 18 studies that reported on seven behavioural outcomes, including smoking cessation (six studies; n=2663), diet (seven studies; n=1784), and physical activity (six studies; n=1704). Meta-analysis revealed no significant effects of communicating DNA based risk estimates on smoking cessation (odds ratio 0.92, 95% confidence interval 0.63 to 1.35, P=0.67), diet (standardised mean difference 0.12, 95% confidence interval -0.00 to 0.24, P=0.05), or physical activity (standardised mean difference -0.03, 95% confidence interval -0.13 to 0.08, P=0.62). There were also no effects on any other behaviours (alcohol use, medication use, sun protection behaviours, and attendance at screening or behavioural support programmes) or on motivation to change behaviour, and no adverse effects, such as depression and anxiety. Subgroup analyses provided no clear evidence that communication of a risk-conferring genotype affected behaviour more than communication of the absence of such a genotype. However, studies were predominantly at high or unclear risk of bias, and evidence was typically of low quality.
Conclusions:
Expectations that communicating DNA based risk estimates changes behaviour is not supported by existing evidence. These results do not support use of genetic testing or the search for risk-conferring gene variants for common complex diseases on the basis that they motivate risk-reducing behaviour.
Systematic review registration:
This is a revised and updated version of a Cochrane review from 2010, adding 11 studies to the seven previously identified.
Information scanning, or attention to information via incidental or routine exposure or browsing, is relatively less understood than information seeking. To 1) provide a more theoretical understanding of information scanning and 2) extend existing information seeking theory to information scanning, the current study used data from the National Cancer Institute’s Health Information National Trends Survey (HINTS) to examine cancer information scanning using the comprehensive model of information seeking (CMIS). Consistent with the CMIS, health-related factors were associated with the information-carrier factor of trust, and health-related factors and trust were associated with attention to information sources. Some of these associations differed between entertainment-oriented sources, information-oriented sources, and the Internet. The current findings provide a clearer picture of information scanning and suggest future avenues of research and practice using the CMIS.
Patient engagement has become a major focus of health reform. However, there is limited evidence showing that increases in patient engagement are associated with improved health outcomes or lower costs. We examined the extent to which a single assessment of engagement, the Patient Activation Measure, was associated with health outcomes and costs over time, and whether changes in assessed activation were related to expected changes in outcomes and costs. We used data on adult primary care patients from a single large health care system where the Patient Activation Measure is routinely used. We found that results indicating higher activation in 2010 were associated with nine out of thirteen better health outcomes-including better clinical indicators, more healthy behaviors, and greater use of women's preventive screening tests-as well as with lower costs two years later. Changes in activation level were associated with changes in over half of the health outcomes examined, as well as costs, in the expected directions. These findings suggest that efforts to increase patient activation may help achieve key goals of health reform and that further research is warranted to examine whether the observed associations are causal.
Project HOPE—The People-to-People Health Foundation, Inc.
The demonstrated benefits of information seeking for cancer patients, coupled with increases in information availability, underscore the importance of monitoring patient information seeking experiences over time. We compared information seeking among cancer survivors to those with a family history of cancer and those with no history of cancer. We identified characteristics associated with greater information seeking among cancer survivors, key sources of cancer-related information, and changes in information source use over time. Data from five iterations of the Health Information National Trends Survey (HINTS) spanning 2003 to 2013 were merged and analyzed. Frequencies, cross-tabulations, multivariate logistic regression, and multinomial regression analyses were conducted. All data were weighted to provide representative estimates of the adult US population. Cancer information seeking was reported most frequently by cancer survivors (69.8 %). The percentage of cancer survivors who reported information seeking increased from 66.8 % in 2003 to 80.8 % in 2013. Cancer information seeking was independently associated with age, education, and income; seeking was less likely among older adults, those with less education, and those with lower incomes. Compared to respondents in 2003, those in 2005 (odds ratio (OR) = 0.40, 95 % confidence interval (CI) = 0.24-0.65) and 2008 (OR = .43, 95 % CI = 0.26-0.70) were about half as likely to use the Internet as the first source of cancer information compared to a healthcare provider. Despite overall increases in cancer information seeking and access to health information from a variety of sources, healthcare providers remain a key source of health information for cancer survivors.
Following in the path of feminists and civil rights leaders, informed patients are building a progressive social movement to improve medical care. Dave deBronkart says medicine should let patients help improve care, share responsibility, and think for themselves
Although growth in U.S. consumers' overall use of e-health is strong, it is being driven by only a portion of the e-health services that are offered through online health portals. Fine-grained, longitudinal analysis of three representative e-health services shows that, while online communication with medical personnel has grown consistently between 2003 and 2012, the purchase of health supplies online plateaued by 2007, and participation in online support groups has been flat since 2003. Socioeconomic factors of income and education level continue to have an impact on consumers' use of e-health; however, differences based on age, sex, and race/ethnicity are trending lower during this period. The findings caution against the common practice of studying e-health adoption principally at the level of online health portals, which can mask substantial variation in adoption trends among the underlying e-health services, and suggest that it is important to update trend studies on a regular basis to maintain currency.
Background:
Little is known about patients' online health information seeking after a primary care or specialist medical visit.
Objectives:
To examine predictors of patients' post-visit online health information seeking, reasons for seeking information and information sources used.
Methods:
Survey of online support group members (N = 311) with a recent medical visit. Measures included eHealth literacy, patient-centred communication (PCC), post-visit changes in worry, online health information seeking and reasons for seeking information. Analyses were based on descriptive statistics and logistic regression.
Results:
Eighty per cent of patients went online post-visit. The most common source used was others' forum posts (91%). The most common reason was curiosity (68%). Dissatisfaction with the physician's performance motivated information seeking for 40% of respondents. In a multivariate analysis, post-visit online health information seeking was highest among patients who were more eHealth literate [odds ratio (OR) = 1.73 (95% confidence interval (CI): 1.11, 2.71), P = 0.016], gave lower PCC ratings to their providers [OR = 0.45 (0.22, 0.90), P = 0.024] and experienced increased worry due to the visit [OR = 5.19 (1.36, 19.82), P = 0.016]. eHealth literate patients made greater use of specialized medical information (e.g. online medical journal articles) than less literate patients. Primary care physicians were rated as more patient centred than specialists. Visit-induced worry led to greater use of interpersonal channels (e.g. e-mailing other forum members). Patients who saw their doctor as less patient-centred were more likely to go online due to dissatisfaction with doctor performance.
Conclusion:
Online support forum members often turn to the Internet for health information following their medical visits. Their information seeking is shaped by patient, relational and visit factors.
Background
The need to understand preferred sources of health information remains important to providing patient-centered care. The Internet remains a popular resource for health information, but more traditional sources may still be valid for patients during a recent health need. This study sought to understand the characteristics of patients that turn to their doctor or healthcare provider first for a recent health or medical information need.
Methods
Using the national cross-sectional survey, Health Information National Trend Study [HINTS], characteristics of those who sought a doctor or healthcare provider for a recent health information need were compared to other sources. Weighted survey responses from Cycle 1 and Cycle 2 of the HINTS survey were used for multivariable logistic regression.
Results
A total 5,307 patient responses were analyzed. Overall, those who seek a doctor or healthcare provider first for a health need are female, 46–64 years, White non-Hispanic, educated, in good health and users of the Internet. Yet, adjusted logistic regressions showed that those who sought a doctor or healthcare provider first during a recent health information need compared to other sources were most likely to be 65+ years, in poor health, less educated and have health insurance.
Conclusions
Patients who seek their doctor or healthcare provider first for health information rather than other sources of information represent a unique population. Doctors or healthcare providers remain an important resource for these patients during recent needs, despite the wide use of the Internet as a source of health information.
This study retested PRISM, a model of risk information seeking, and found that it is applicable to the context of cancer risk communication. The study, which used an online sample of 928 U.S. adults, also tested the effect of additional variables on that model and found that the original model better fit the data. Among the strongest predictors of cancer information seeking were seeking-related subjective norms, attitude toward seeking, perceived knowledge insufficiency, and affective risk response. Furthermore, risk perception was a strong predictor of an affective risk response. The authors suggest that, given the robustness across studies, the path between seeking-related subjective norms and seeking intention is ready to be implemented in communication practice.
First published in JMIR Research Protocols. Link to original article: http://www.researchprotocols.org/2013/2/e33/
Creative Commons copyright and license information:https://creativecommons.org/licenses/by/2.0/
Abstract:
People of South Asian origin suffer a high burden of premature myocardial infarction (MI). South Asians form a growing proportion of the Canadian population and preventive strategies to mitigate the risk of MI in this group are needed. Prior studies have shown that multimedia interventions are effective and feasible in inducing health behavior changes among the obese, smokers, and among those who are sedentary.
Among at-risk South Asians living in Canada, our objectives are to determine: (1) the feasibility of a culturally tailored multimedia intervention to induce positive behavioral changes associated with reduced MI risk factors, and (2) the effectiveness and acceptability of information communicated by individualized MI and genetic risk score (GRS) reports.
The South Asian HeArt Risk Assessment (SAHARA) pilot study enrolled 367 individuals of South Asian origin recruited from places of worship and community centers in Ontario, Canada. MI risk factors including the 9p21 genetic variant status were provided to all participants after the baseline visit. Participants were randomly allocated to receive a multimedia intervention or control. The intervention group selected health goals and received personalized health messages to promote adherence to their selected goals. After 6 months, all participants had their MI risk factors repeated. The methods and results of this study are reported based on the CONSORT-EHEALTH guidelines.
The mean age of participants was 53.8 years (SD 11.4), 52.0% (191/367) were women, and 97.5% (358/367) were immigrants to Canada. The mean INTERHEART risk score was 13.0 (SD 5.8) and 73.3% (269/367) had one or two copies of the risk allele for the 9p21 genetic variant. Both the intervention and control groups made some progress in health behavior changes related to diet and physical activity over 6 months. Participants reported that their risk score reports motivated behavioral changes, although half of the participants could not recall their risk scores at the end of study evaluation. Some components of the multimedia intervention were not widely used such as logging onto the website to set new health goals, and participants requested having more personal interactions with the study team.
Some, but not all, components of the multimedia intervention are feasible and have the potential to induce positive health behavior changes. MI and GRS reports are desired by participants although their impact on inducing sustained health behavior change requires further evaluation. Information generated from this pilot study has directly informed the design of another randomized trial designed to reduce MI risk among South Asians.
ClinicalTrials.gov NCT01577719; http://clinicaltrials.gov/ct2/show/NCT01577719 (Archived by WebCite at http://www.webcitation.org/6J11uYXgJ).
With the increasing availability of the Internet in the United States, patients are more frequently seeking medical information online. Oftentimes, the medical information that patients find on traditional websites is unreliable. It is a physician's duty to ensure that patients are being educated properly. Providing sound medical information through social media websites is one way in which physicians may accomplish this goal, while also improving clinic reputation, patient volume, and doctor-patient communication.
More accurate coronary heart disease (CHD) prediction, specifically in middle-aged men, is needed to reduce the burden of disease more effectively. We hypothesised that a multilocus genetic risk score could refine CHD prediction beyond classic risk scores and obtain more precise risk estimates using a prospective cohort design.
Using data from nine prospective European cohorts, including 26,221 men, we selected in a case-cohort setting 4,818 healthy men at baseline, and used Cox proportional hazards models to examine associations between CHD and risk scores based on genetic variants representing 13 genomic regions. Over follow-up (range: 5-18 years), 1,736 incident CHD events occurred. Genetic risk scores were validated in men with at least 10 years of follow-up (632 cases, 1361 non-cases). Genetic risk score 1 (GRS1) combined 11 SNPs and two haplotypes, with effect estimates from previous genome-wide association studies. GRS2 combined 11 SNPs plus 4 SNPs from the haplotypes with coefficients estimated from these prospective cohorts using 10-fold cross-validation. Scores were added to a model adjusted for classic risk factors comprising the Framingham risk score and 10-year risks were derived.
Both scores improved net reclassification (NRI) over the Framingham score (7.5%, p = 0.017 for GRS1, 6.5%, p = 0.044 for GRS2) but GRS2 also improved discrimination (c-index improvement 1.11%, p = 0.048). Subgroup analysis on men aged 50-59 (436 cases, 603 non-cases) improved net reclassification for GRS1 (13.8%) and GRS2 (12.5%). Net reclassification improvement remained significant for both scores when family history of CHD was added to the baseline model for this male subgroup improving prediction of early onset CHD events.
Genetic risk scores add precision to risk estimates for CHD and improve prediction beyond classic risk factors, particularly for middle aged men.
Multiple studies have identified single-nucleotide polymorphisms (SNPs) that are associated with coronary heart disease (CHD). We examined whether SNPs selected based on predefined criteria will improve CHD risk prediction when added to traditional risk factors (TRFs).
SNPs were selected from the literature based on association with CHD, lack of association with a known CHD risk factor, and successful replication. A genetic risk score (GRS) was constructed based on these SNPs. Cox proportional hazards model was used to calculate CHD risk based on the Atherosclerosis Risk in Communities (ARIC) and Framingham CHD risk scores with and without the GRS.
The GRS was associated with risk for CHD (hazard ratio [HR] = 1.10; 95% confidence interval [CI]: 1.07-1.13). Addition of the GRS to the ARIC risk score significantly improved discrimination, reclassification, and calibration beyond that afforded by TRFs alone in non-Hispanic whites in the ARIC study. The area under the receiver operating characteristic curve (AUC) increased from 0.742 to 0.749 (Δ = 0.007; 95% CI, 0.004-0.013), and the net reclassification index (NRI) was 6.3%. Although the risk estimates for CHD in the Framingham Offspring (HR = 1.12; 95% CI: 1.10-1.14) and Rotterdam (HR = 1.08; 95% CI: 1.02-1.14) Studies were significantly improved by adding the GRS to TRFs, improvements in AUC and NRI were modest.
Addition of a GRS based on direct associations with CHD to TRFs significantly improved discrimination and reclassification in white participants of the ARIC Study, with no significant improvement in the Rotterdam and Framingham Offspring Studies.
Little is known about access, sources, and trust of cancer-related information, or factors that facilitate or hinder communication on a populationwide basis. Through a careful developmental process involving extensive input from many individuals and organizations, the National Cancer Institute (NCI) developed the Health Information National Trends Survey (HINTS) to help fill this gap. This nationally representative telephone survey of 6,369 persons aged !18 years among the general population was first conducted in 2002–2003, and will be repeated biennially depending on avail-ability of funding. The purpose of creating a population survey to be repeated on a cyclical basis is to track trends in the public's rapidly changing use of new The authors gratefully acknowledge the contributions of, without whom launching a new survey program would not have been possible.
This paper presents an outline of models of information seeking and other aspects of information behaviour, showing the relationship between communication and information behaviour in general with information seeking and information searching in information retrieval systems. It is suggested that these models address issues at various levels of information behaviour and that they can be related by envisaging a 'nesting' of models. It is also suggested that, within both information seeking research and information searching research, alternative models address similar issues in related ways and that the models are complementary rather than conflicting. Finally, an alternative, problem-solving model is presented, which, it is suggested, provides a basis for relating the models in appropriate research strategies.
Purpose:
Examination of patients' responses to direct-to-consumer genetic susceptibility tests is needed to inform clinical practice. This study examined patients' recall and interpretation of, and responses to, genetic susceptibility test results provided directly by mail.
Methods:
This observational study had three prospective assessments (before testing, 10 days after receiving results, and 3 months later). Participants were 199 patients aged 25-40 years who received free genetic susceptibility testing for eight common health conditions.
Results:
More than 80% of the patients correctly recalled their results for the eight health conditions. Patients were unlikely to interpret genetic results as deterministic of health outcomes (mean = 6.0, s.d. = 0.8 on a scale of 1-7, 1 indicating strongly deterministic). In multivariate analysis, patients with the least deterministic interpretations were white (P = 0.0098), more educated (P = 0.0093), and least confused by results (P = 0.001). Only 1% talked about their results with a provider.
Conclusion:
Findings suggest that most patients will correctly recall their results and will not interpret genetics as the sole cause of diseases. The subset of those confused by results could benefit from consultation with a health-care provider, which could emphasize that health habits currently are the best predictors of risk. Providers could leverage patients' interest in genetic tests to encourage behavior changes to reduce disease risk.
Diabetes self-management is essential for diabetes control, yet little is known about patient preferences for sources of health information or about the extent to which information is sought directly or received passively through various media sources. The aim of this qualitative study was to identify how individuals with diabetes seek and use health care information.
Using a health information model to guide our research, we conducted 9 focus groups with 46 adults with a diagnosis of diabetes and then analyzed the transcripts and notes from these focus groups.
Five themes emerged: (1) passive receipt of health information about diabetes is an important aspect of health information behavior; (2) patients weave their own information web depending on their disease trajectory; (3) patients' personal relationships help them understand and use this information; (4) a relationship with a health care professional is needed to cope with complicated and sometimes conflicting information; and (5) health literacy makes a difference in patients' ability to understand and use information.
Patients make decisions about diabetes self-management depending on their current needs, seeking and incorporating diverse information sources not traditionally viewed as providing health information. Based on our findings, we have developed a new health information model that reflects both the nonlinear nature of health information-seeking behavior and the interplay of both active information seeking and passive receipt of information.
The prevalence of overweight among children worldwide is growing at an alarming rate. Social relationships may contribute to the development of obesity through the interaction of biological, behavioral, and environmental factors. Although there is evidence that early environment influences the expression of obesity, very little research elucidates the social context of obesity among children or adolescents. Social network approaches can contribute to research on the role of social environments in overweight and obesity and strengthen interventions to prevent disease and promote health. By capitalizing on the structure of the network system, a targeted intervention that uses social relationships in families, schools, neighborhoods, and communities may be successful in encouraging healthful behaviors among children and their families.
Established in 1975, the National Cancer Institute's (NCI's) Cancer Information Service (CIS) is a national information and education network that serves the nation by providing the latest scientific cancer information to the American public. The purpose of this study was to determine the public's awareness of the CIS and other national cancer and health organizations by analyzing data from the NCI's Health Information National Trends Survey (HINTS 200310.
National Cancer Institute . ( 2003 ). Cancer health disparities: Fact sheet. Retrieved May 12, 2005, from http://www.cancer.gov/newscenter/healthdisparities View all references). This study also examined sociodemographic, health, and communication correlates of awareness of CIS and other national health organizations: American Cancer Society (ACS), National Institutes of Health (NIH), and NCI. Results indicated that awareness of the CIS was low (32.8%). Some subgroups were more likely to be aware of the CIS than others. When comparing awareness levels of the four national health organizations, marked differences in patterns of awareness among specific subgroups emerged for many sociodemographic variables. For example, minority groups were significantly more aware of the CIS than Whites; however, for all three other organizations a greater percentage of Whites were aware of each organization. For the NIH, NCI, and ACS, respondents in the highest income group were most aware of each organization and, as income level increased awareness also increased. The CIS, respondents with the lowest income levels, however, were more aware of the CIS compared with middle- and high-income groups. A similar pattern was found for other sociodemographic variables. Results of this study will guide the development of a targeted promotional campaign for the CIS.
Whether disclosure of genetic risk for coronary heart disease (CHD) influences shared decision-making (SDM) regarding use of statins to reduce CHD risk is unknown. We randomized 207 patients, age 45-65 years, at intermediate CHD risk, and not on statins, to receive the 10-year risk of CHD based on conventional risk factors alone (n=103) or in combination with a genetic risk score (n=104). A genetic counselor disclosed this information followed by a physician visit for SDM regarding statin therapy. A novel decision aid was used in both encounters to disclose the CHD risk estimates and facilitate SDM regarding statin use. Patients reported their decision quality and physician visit satisfaction using validated surveys. There were no statistically significant differences between the two groups in the SDM score, satisfaction with the clinical encounter, perception of the quality of the discussion or of participation in decision-making and physician visit satisfaction scores. Quantitative analyses of a random subset of 80 video-recorded encounters using the OPTION5 scale also showed no significant difference in SDM between the two groups. Disclosure of CHD genetic risk using an electronic health record-linked decision aid did not adversely affect SDM or patients' satisfaction with the clinical encounter.
Trial registration number:
NCT01936675; Results.
Background:
-We evaluated whether including multi-locus genetic risk scores (GRS's) into the Framingham Risk Equation improves the predictive capacity, discrimination and reclassification of asymptomatic individuals with respect to coronary heart disease (CHD) risk.
Methods and results:
-We performed a cohort study among 51,954 European-ancestry members of a Northern California integrated health care system (67% female; mean age 59) free of CHD at baseline (2007-08). Four GRS's were constructed using between 8 and 51 previously identified genetic variants. After a mean (± SD) follow-up of 5.9 (± 1.5) years, 1,864 incident CHD events were documented. All GRS's were linearly associated with CHD in a model adjusted by individual risk factors: HR [95%CI] per SD unit: 1.21 [1.15-1.26] for GRS_8, 1.20 [1.15-1.26] for GRS_12, 1.23 [1.17-1.28] for GRS_36 and 1.23 [1.17-1.28] for GRS_51. Inclusion of the GRS's improved the C-statistic (Δc-statistic=0.008 for GRS_8 and GRS_36; 0.007 for GRS_12; and 0.009 for GRS_51; all p<0.001). The net reclassification improvement (NRI) was 5% for GRS_8, GRS_12 and GRS_36 and 4% for GRS_51 in the entire cohort, and was (after correcting for bias) 9% for GRS_8 and GRS_12, and 7% for GRS_36 and GRS_51 when analyzing those classified as intermediate Framingham risk (10-20%). The number required to treat to prevent 1 CHD after selectively treating with statins up-reclassified subjects on the basis of genetic information was 36 for GRS_8 and GRS_12, 41 for GRS_36 and 43 for GRS_51.
Conclusions:
-Our results demonstrate significant and clinically relevant incremental discriminative/predictive capability of four multi-locus GRS's for incident CHD among subjects of European ancestry.
Genetic test results have medical implications beyond the patient that extend to biological family members. We examined psychosocial and clinical factors associated with communication of genetic test results within families. Women (N = 1080) diagnosed with breast cancer at age 40 or younger completed an online survey; 920 women that reported prior cancer genetic testing were included in analysis. We examined the proportion of immediate family members to whom they communicated genetic test results, and built multivariable regression models to examine clinical and psychosocial variables associated with the proportion score. Participants were most likely to communicate test results to their mother (83 %) and least likely to their son (45 %). Participants who carried a BRCA mutation (OR = 1.34; 95 % CI = 1.06, 1.70), had higher interest in genomic information (OR = 1.55; 95 % CI = 1.26, 1.91) and lower genetic worry (OR = 0.91; 95 % CI = 0.86, 0.96) communicated genetic test results to a greater proportion of their immediate family members. Participants with a BRCA1/2 mutation shared their genetic test results with more male family members (OR = 1.72; 95 % CI = 1.02, 2.89). Our findings suggest that patients with high worry about genetic risks, low interest in genomic information, or receive a negative genetic test result will likely need additional support to encourage family communication.
Background:
-Whether knowledge of genetic risk for coronary heart disease (CHD) affects health-related outcomes is unknown. We investigated whether incorporating a genetic risk score (GRS) in CHD risk estimates lowers low-density lipoprotein cholesterol (LDL-C) levels.
Methods and results:
-Participants (n=203, 45-65 years old, at intermediate risk for CHD, and not on statins) were randomized to receive their 10-year probability of CHD based either on a conventional risk score (CRS) or CRS + GRS ((+)GRS). Participants in the (+)GRS group were stratified as having high ((+)H-GRS) or average/low ((+)L-GRS) GRS. Risk was disclosed by a genetic counselor followed by shared decision-making regarding statin therapy with a physician. We compared the primary endpoint of LDL-C levels at 6 months and assessed whether any differences were due to changes in dietary fat intake, physical activity levels or statin use. Participants (mean age 59.4±5 years, 48% men, mean 10-year CHD risk 8.5±4.1%) were allocated to receive either CRS (n=100) or +GRS (n=103). At the end of the study period, the (+)GRS group had a lower LDL-C than the CRS group (96.5±32.7 vs. 105.9±33.3 mg/dL; P=0.04). (+)H-GRS participants had lower LDL-C levels (92.3±32.9 mg/dL) than CRS participants (P=0.02) but not (+)L-GRS participants (100.9±32.2 mg/dL; P=0.18). Statins were initiated more often in the (+)GRS group than in the CRS group (39% vs. 22%, P<0.01). No significant differences in dietary fat intake and physical activity levels were noted.
Conclusions:
-Disclosure of CHD risk estimates that incorporated genetic risk information led to lower LDL-C levels than disclosure of CHD risk based on conventional risk factors alone. Clinical Trial Registration Information-ClinicalTrials.gov. Identifier: NCT01936675.
Information and behaviour can spread through interpersonal ties. By targeting influential individuals, health interventions that harness the distributive properties of social networks could be made more effective and efficient than those that do not. Our aim was to assess which targeting methods produce the greatest cascades or spillover effects and hence maximise population-level behaviour change.
In this cluster randomised trial, participants were recruited from villages of the Department of Lempira, Honduras. We blocked villages on the basis of network size, socioeconomic status, and baseline rates of water purification, for delivery of two public health interventions: chlorine for water purification and multivitamins for micronutrient deficiencies. We then randomised villages, separately for each intervention, to one of three targeting methods, introducing the interventions to 5% samples composed of either: randomly selected villagers (n=9 villages for each intervention); villagers with the most social ties (n=9); or nominated friends of random villagers (n=9; the last strategy exploiting the so-called friendship paradox of social networks). Participants and data collectors were not aware of the targeting methods. Primary endpoints were the proportions of available products redeemed by the entire population under each targeting method. This trial is registered with ClinicalTrials.gov, number NCT01672580.
Between Aug 4, and Aug 14, 2012, 32 villages in rural Honduras (25-541 participants each; total study population of 5773) received public health interventions. For each intervention, nine villages (each with 1-20 initial target individuals) were randomised, using a blocked design, to each of the three targeting methods. In nomination-targeted villages, 951 (74·3%) of 1280 available multivitamin tickets were redeemed compared with 940 (66·2%) of 1420 in randomly targeted villages and 744 (61·0%) of 1220 in indegree-targeted villages. All pairwise differences in redemption rates were significant (p<0·01) after correction for multiple comparisons. Targeting nominated friends increased adoption of the nutritional intervention by 12·2% compared with random targeting (95% CI 6·9-17·9). Targeting the most highly connected individuals, by contrast, produced no greater adoption of either intervention, compared with random targeting.
Introduction of a health intervention to the nominated friends of random individuals can enhance that intervention's diffusion by exploiting intrinsic properties of human social networks. This method has the additional advantage of scalability because it can be implemented without mapping the network. Deployment of certain types of health interventions via network targeting, without increasing the number of individuals targeted or the resources used, could enhance the adoption and efficiency of those interventions, thereby improving population health.
National Institutes of Health, The Bill & Melinda Gates Foundation, Star Family Foundation, and the Canadian Institutes of Health Research.
Copyright © 2015 Elsevier Ltd. All rights reserved.
Genetic variants have been associated with the risk of coronary heart disease. In this study, we tested whether or not a composite of these variants could ascertain the risk of both incident and recurrent coronary heart disease events and identify those individuals who derive greater clinical benefit from statin therapy.
A community-based cohort study (the Malmo Diet and Cancer Study) and four randomised controlled trials of both primary prevention (JUPITER and ASCOT) and secondary prevention (CARE and PROVE IT-TIMI 22) with statin therapy, comprising a total of 48 421 individuals and 3477 events, were included in these analyses. We studied the association of a genetic risk score based on 27 genetic variants with incident or recurrent coronary heart disease, adjusting for traditional clinical risk factors. We then investigated the relative and absolute risk reductions in coronary heart disease events with statin therapy stratified by genetic risk. We combined data from the different studies using a meta-analysis.
When individuals were divided into low (quintile 1), intermediate (quintiles 2-4), and high (quintile 5) genetic risk categories, a significant gradient in risk for incident or recurrent coronary heart disease was shown. Compared with the low genetic risk category, the multivariable-adjusted hazard ratio for coronary heart disease for the intermediate genetic risk category was 1·34 (95% CI 1·22-1·47, p<0·0001) and that for the high genetic risk category was 1·72 (1·55-1·92, p<0·0001). In terms of the benefit of statin therapy in the four randomised trials, we noted a significant gradient (p=0·0277) of increasing relative risk reductions across the low (13%), intermediate (29%), and high (48%) genetic risk categories. Similarly, we noted greater absolute risk reductions in those individuals in higher genetic risk categories (p=0·0101), resulting in a roughly threefold decrease in the number needed to treat to prevent one coronary heart disease event in the primary prevention trials. Specifically, in the primary prevention trials, the number needed to treat to prevent one such event in 10 years was 66 in people at low genetic risk, 42 in those at intermediate genetic risk, and 25 in those at high genetic risk in JUPITER, and 57, 47, and 20, respectively, in ASCOT.
A genetic risk score identified individuals at increased risk for both incident and recurrent coronary heart disease events. People with the highest burden of genetic risk derived the largest relative and absolute clinical benefit from statin therapy.
National Institutes of Health.
Copyright © 2015 Elsevier Ltd. All rights reserved.
Using 1940 and 1950 census data on marital status by age, this paper presents estimated mean ages at first marriage for white males and females in the United States and discusses briefly the pattern of change over the decade. While age at marriage declined in all educational groups, the amount of the decline was greatest (two years or more) among men and women who had completed either college or high school.
Although the majority of US adults has Internet access and gathers health information online, the Internet does not replace clinicians. People rate health professionals as their top source for technical questions such as diagnosis and treatment, but nonprofessionals (eg, friends and family) are rated higher for emotional support and quick remedies. For their most recent health issue, 21% of adults say they turned to others who have the same health condition; evidence of people's interest in connecting with and learning from each other. People living with chronic diseases (and their caregivers) are especially likely to say they look online for peer advice. They are pioneering new ways of pursuing health by banding together and sharing knowledge; so-called peer-to-peer health care. Practical tips from fellow patients and caregivers can have far-reaching implications for clinical outcomes. As a parent of a chronically ill child observed: "We all work collaboratively, but I notice that my doctor doesn't. After I've talked with my community online, I go back to him and ask, 'What do your colleagues say about this issue?' And it's clear it didn't occur to him to ask them." Clinicians might do well to look into online patient communities and consider recommending them as resources for their patients. Clinicians might look at patient networks as a model for their own collaborative learning process as well. Linking the expertise of patients, families, and clinicians holds promise for further improving care and outcomes.
People are increasingly using the Internet to access health information and the information obtained has an impact on their healthcare outcomes. This paper examines the impacts of IT enablers and health motivators on peoples' online health information search behavior. We characterize users' online health information search behavior along three dimensions: the frequency of online health information search, the diversity of online health information usage, and the preference of the Internet for initial search. Using the 2003 Health Information National Trends Survey (HINTS) data on cancer, we find that ease of access to Internet services and trust in online health information could affect the three dimensional search behavior listed above. While perceived quality of communication with doctors has an impact on diversity of use and preference of use, we surprisingly do not find an impact on the frequency of search for online health information. In addition, our results find that perceived health status could affect both frequency and diversity of search for online health information. But we do not find evidence that perceived health status could lead to a preference for using the Internet as a source for health information.
Healthcare is undergoing a profound revolution as a consequence of three contemporary thrusts: systems medicine [1-4], big data and patient involvement in their own health through social networks. This convergence is leading to a medicine that is predictive, preventive, personalized and participatory (P4) [4-7]. The first three Ps, predictive, preventive and personalized, were delineated in the early 2000s [1,2], whereas the fourth P, participatory, was added later. To achieve a participatory healthcare system, major technical and societal challenges will need to be overcome, and this will require close integration with systems medicine and big data. Before commenting further on participatory medicine, let us first delineate the essence of systems medicine and big data and their implications for P4 medicine.
Systems medicine, the application of systems biology approaches to disease [3,4,6,8,9], is already changing how healthcare is practiced (Table 1). We predict that in 5 to 10 years each patient will be surrounded by a virtual cloud of billions of data points - molecular, clinical chemistries, cellular, organ, phenotypic, imaging, social networks, and so on. We also predict that we will have the analytical tools to reduce this big data cloud to simple models that will guide improvements in health and minimize disease. This requires addressing two grand challenges: the signal-to-noise issues intrinsic to big data and integration of multi-scale data into predictive models.
Table 1
How systems medicine is transforming healthcare
In addition, for each individual patient we foresee that we will be able to integrate an individual’s genetic, molecular, cellular, organ and social networks into an overall 'network of networks’ [10]. Disease leads to the perturbation of the network of networks and this alters the information the network manages. The availability of a personal data cloud will allow one to characterize an individual’s network of networks in its normal or disease-perturbed states. This altered, disease-perturbed information will provide deep insights into disease mechanisms, new approaches to diagnostics and therapeutics, and a platform for participatory medicine.
Objective:
Current guidelines do not support the use of genetic profiles in risk assessment of coronary heart disease (CHD). However, new single nucleotide polymorphisms associated with CHD and intermediate cardiovascular traits have recently been discovered. We aimed to compare several multilocus genetic risk score (MGRS) in terms of association with CHD and to evaluate clinical use.
Approach and results:
We investigated 6 Swedish prospective cohort studies with 10 612 participants free of CHD at baseline. We developed 1 overall MGRS based on 395 single nucleotide polymorphisms reported as being associated with cardiovascular traits, 1 CHD-specific MGRS, including 46 single nucleotide polymorphisms, and 6 trait-specific MGRS for each established CHD risk factors. Both the overall and the CHD-specific MGRS were significantly associated with CHD risk (781 incident events; hazard ratios for fourth versus first quartile, 1.54 and 1.52; P<0.001) and improved risk classification beyond established risk factors (net reclassification improvement, 4.2% and 4.9%; P=0.006 and 0.017). Discrimination improvement was modest (C-index improvement, 0.004). A polygene MGRS performed worse than the CHD-specific MGRS. We estimate that 1 additional CHD event for every 318 people screened at intermediate risk could be saved by measuring the CHD-specific genetic score in addition to the established risk factors.
Conclusions:
Our results indicate that genetic information could be of some clinical value for prediction of CHD, although further studies are needed to address aspects, such as feasibility, ethics, and cost efficiency of genetic profiling in the primary prevention setting.
Objective:
Genome-wide association studies have identified several genetic variants associated with coronary heart disease (CHD). The aim of this study was to evaluate the genetic risk discrimination and reclassification and apply the results for a 2-stage population risk screening strategy for CHD.
Approach and results:
We genotyped 28 genetic variants in 24 124 participants in 4 Finnish population-based, prospective cohorts (recruitment years 1992-2002). We constructed a multilocus genetic risk score and evaluated its association with incident cardiovascular disease events. During the median follow-up time of 12 years (interquartile range 8.75-15.25 years), we observed 1093 CHD, 1552 cardiovascular disease, and 731 acute coronary syndrome events. Adding genetic information to conventional risk factors and family history improved risk discrimination of CHD (C-index 0.856 versus 0.851; P=0.0002) and other end points (cardiovascular disease: C-index 0.840 versus 0.837, P=0.0004; acute coronary syndrome: C-index 0.859 versus 0.855, P=0.001). In a standard population of 100 000 individuals, additional genetic screening of subjects at intermediate risk for CHD would reclassify 2144 subjects (12%) into high-risk category. Statin allocation for these subjects is estimated to prevent 135 CHD cases over 14 years. Similar results were obtained by external validation, where the effects were estimated from a training data set and applied for a test data set.
Conclusions:
Genetic risk score improves risk prediction of CHD and helps to identify individuals at high risk for the first CHD event. Genetic screening for individuals at intermediate cardiovascular risk could help to prevent future cases through better targeting of statins.
The relationship between patients and doctors is at the core of medical ethics, anchoring many important debates in the field. Over the past several decades, this relationship has evolved along three axes — as it is defined in clinical care, research, and society.
To illustrate the problem of generalizability of epidemiological findings derived from a single population using data from the Rochester Epidemiology Project and from the US Census.
We compared the characteristics of the Olmsted County, Minnesota, population with the characteristics of populations residing in the state of Minnesota, the Upper Midwest, and the entire United States.
Age, sex, and ethnic characteristics of Olmsted County were similar to those of the state of Minnesota and the Upper Midwest from 1970 to 2000. However, Olmsted County was less ethnically diverse than the entire US population (90.3% vs 75.1% white), more highly educated (91.1% vs 80.4% high school graduates), and wealthier ($51,316 vs $41,994 median household income; 2000 US Census data). Age- and sex-specific mortality rates were similar for Olmsted County, the state of Minnesota, and the entire United States.
We provide an example of analyses and comparisons that may guide the generalization of epidemiological findings from a single population to other populations or to the entire United States.
Limited data exist regarding the use of a genetic risk score (GRS) for predicting risk of incident cardiovascular disease (CVD) in US-based samples.
By using findings from recent genome-wide association studies, we constructed GRSs composed of 13 genetic variants associated with myocardial infarction or other manifestations of coronary heart disease (CHD) and 102 genetic variants associated with CHD or its major risk factors. We also updated the 13 single-nucleotide polymorphism (SNP) GRSs with 16 SNPs recently discovered by genome-wide association studies. We estimated the association, discrimination, and risk reclassification of each GRS for incident cardiovascular events and prevalent coronary artery calcium (CAC). In analyses adjusted for age, sex, CVD risk factors, and parental history of CVD, the 13 SNP GRSs were significantly associated with incident hard CHD (hazard ratio, 1.07; 95% CI, 1.00-1.15; P=0.04), CVD (hazard ratio per allele, 1.05; 95% CI, 1.01-1.09; P=0.03), and high CAC (defined as >75(th) age- and sex-specific percentile; odds ratio per allele, 1.18; 95% CI, 1.11-1.26; P=3.4×10(-7)). The GRS did not improve discrimination for incident CHD or CVD but led to modest improvements in risk reclassification. However, significant improvements in discrimination and risk reclassification were observed for the prediction of high CAC. The addition of 16 newly discovered SNPs to the 13 SNP GRSs did not significantly modify these results.
A GRS composed of 13 SNPs associated with coronary disease is an independent predictor of cardiovascular events and of high CAC, modestly improves risk reclassification for incident CHD, and significantly improves discrimination for high CAC. The addition of recently discovered SNPs did not significantly improve the performance of this GRS.
The Internet holds great potential to support information gathering and decision making surrounding health education and self-care. Older adults, however, underutilize the Internet for health information searches relative to younger adults. The goal of the present study was to examine age differences in the role of trust and ease of search in predicting whether or not individuals use (adopters) or do notuse (nonadopters) the Internet to search for health information.
We used logistic regressions todetermine whether there were age differences in the extent to which trust and ease of search predicted online health information searches within a nationally-representative sample of 3796 adults from the Health Information National Trends Survey (HINTS).
Adopters were more trusting of Internet health informationthan nonadopters. However, a significant age by trust interaction indicated that this difference increased in magnitude with age, a pattern that held even after controlling for demographic and health variables.
Older adults may benefit from special instructions designed to boost Internet trust, for example, learning how to distinguish between high and low quality health-related websites.
Comparison of patients with coronary heart disease and controls in genome-wide association studies has revealed several single nucleotide polymorphisms (SNPs) associated with coronary heart disease. We aimed to establish the external validity of these findings and to obtain more precise risk estimates using a prospective cohort design.
We tested 13 recently discovered SNPs for association with coronary heart disease in a case-control design including participants differing from those in the discovery samples (3829 participants with prevalent coronary heart disease and 48,897 controls free of the disease) and a prospective cohort design including 30,725 participants free of cardiovascular disease from Finland and Sweden. We modelled the 13 SNPs as a multilocus genetic risk score and used Cox proportional hazards models to estimate the association of genetic risk score with incident coronary heart disease. For case-control analyses we analysed associations between individual SNPs and quintiles of genetic risk score using logistic regression.
In prospective cohort analyses, 1264 participants had a first coronary heart disease event during a median 10·7 years' follow-up (IQR 6·7-13·6). Genetic risk score was associated with a first coronary heart disease event. When compared with the bottom quintile of genetic risk score, participants in the top quintile were at 1·66-times increased risk of coronary heart disease in a model adjusting for traditional risk factors (95% CI 1·35-2·04, p value for linear trend=7·3×10(-10)). Adjustment for family history did not change these estimates. Genetic risk score did not improve C index over traditional risk factors and family history (p=0·19), nor did it have a significant effect on net reclassification improvement (2·2%, p=0·18); however, it did have a small effect on integrated discrimination index (0·004, p=0·0006). Results of the case-control analyses were similar to those of the prospective cohort analyses.
Using a genetic risk score based on 13 SNPs associated with coronary heart disease, we can identify the 20% of individuals of European ancestry who are at roughly 70% increased risk of a first coronary heart disease event. The potential clinical use of this panel of SNPs remains to be defined.
The Wellcome Trust; Academy of Finland Center of Excellence for Complex Disease Genetics; US National Institutes of Health; the Donovan Family Foundation.
This report describes the use of information emerging from genetic discovery to motivate risk-reducing health behaviors. Most research to date has evaluated the effects of information related to rare genetic variants on screening behaviors, in which genetic risk feedback has been associated consistently with improved screening adherence. The limited research with common genetic variants suggests that genetic information, when based on single-gene variants with low-risk probabilities, has little impact on behavior. The effect on behavioral outcomes of more realistic testing scenarios in which genetic risk is based on numerous genetic variants is largely unexplored. Little attention has been directed to matching genetic information to the literacy levels of target audiences. Another promising area for research is consideration of using genetic information to identify risk shared within kinship networks and to expand the influence of behavior change beyond the individual.
A periodic column from the Center for Reducing Risks in Vulnerable Populations, College of Nursing, University of Illinois at Chicago.
Research electronic data capture (REDCap) is a novel workflow methodology and software solution designed for rapid development and deployment of electronic data capture tools to support clinical and translational research. We present: (1) a brief description of the REDCap metadata-driven software toolset; (2) detail concerning the capture and use of study-related metadata from scientific research teams; (3) measures of impact for REDCap; (4) details concerning a consortium network of domestic and international institutions collaborating on the project; and (5) strengths and limitations of the REDCap system. REDCap is currently supporting 286 translational research projects in a growing collaborative network including 27 active partner institutions.
This report presents data from the Current Population Surveys conducted in March 1986 and 1987. Tables present data on years of school completed by persons 15 and older by age, sex, race, Hispanic origin, type of residence, religion, occupation, marital status, and education of spouse. Summary data are also presented for the 15 largest states and metropolitan areas. Some highlights of the data follow. 1) Educational attainment in 1987 reached a peak level for the entire population, as well as for both sexes, Whites, and Hispanics. The attainment for Blacks was not statistically different from the 1986 level, but both the 1986 and 1987 figures were higher than in previous years. 2) 75.6% of all adults aged 25 or older had completed at least 4 years of high school, the highest level measured in the history of the survey. 3) 1 in 5 persons aged 25+ has completed 4 or more years of college; this figure has doubled in the past 20 years. 4) 76% of adult men completed high school as compared to 75.3% of women; as recently as 1969 the proportion of female high school graduates exceeded the male proportion. 23.6% of men have 4 or more years of college as compared to 16.5% of women, a ratio of 1.4. In 1967, the ratio of the proportions of men and women who had completed 4 or more years of college was about 1.7. 5) 77% of Whites have completed high school, as compared to 63.4% of Blacks. Though this gap has narrowed considerably, it is still large. 20.5% of Whites and 10.7% of Blacks have completed 4 or more years of college. 33.4% of adults of other races have completed 4 or more years of college. 50.9% of Hispanics aged 25 or older have completed high school, and 8.6% have finished 4 or more years of college.
This trial tests the hypothesis that confirming a clinical diagnosis of familial hypercholesterolemia (FH) by finding a genetic mutation reduces patients' perceptions of control over the disease and adherence to risk-reducing behaviors. Three hundred forty-one families, comprising 341 hypercholesterolemia probands and 128 adult relatives, were randomized to one of two groups: (a) routine clinical diagnosis; (b) routine clinical diagnosis plus genetic testing (mutation searching in probands and direct gene testing in relatives). The main outcome measures were perceptions of control over hypercholesterolemia, adherence to cholesterol-lowering medication, diet, physical activity, and smoking. There was no support for the main hypothesis: finding a mutation had no impact on perceived control or adherence to risk-reducing behavior (all P-values > 0.10). While all groups believed that lowering cholesterol was an effective way of reducing the risk of a heart attack, participants in whom a mutation was found believed less strongly in the efficacy of diet in reducing their cholesterol level (P = 0.02 at 6 months) and showed a trend in believing more strongly in the efficacy of cholesterol-lowering medication (P = 0.06 at 6 months). In conclusion, finding a mutation to confirm a clinical diagnosis of FH in a previously aware population does not reduce perceptions of control or adherence to risk-reducing behaviors. The pattern of findings leads to the new hypothesis that genetic testing does not affect the extent to which people feel they have control over a condition, but does affect their perceptions of how control is most effectively achieved. Further work is needed to determine whether similar results will be obtained in populations with little previous awareness of their risks.
Despite substantial evidence that the public wants access to Internet-based communication with health care providers, online patient-provider communication remains relatively uncommon, and few studies have examined sociodemographic and health-related factors associated with the use of online communication with health care providers at a population level.
The aim of the study was to use nationally representative data to report on the prevalence of and changes in use of online patient-provider communication in 2003 and 2005 and to describe sociodemographic and health-related factors associated with its use.
Data for this study are from two iterations of the Health Information National Trends Survey (HINTS 2003, HINTS 2005). In both years, respondents were asked whether they had ever used email or the Internet to communicate with a doctor or a doctor's office. Adult Internet users in 2003 (n = 3982) and 2005 (n = 3244) were included in the present study. Multivariate logistic regression analysis was conducted to identify predictors for electronic communication with health care providers.
In 2003, 7% of Internet users had communicated online with an health care provider; this prevalence significantly increased to 10% in 2005. In multivariate analyses, Internet users with more years of education, who lived in a metro area, who reported poorer health status or who had a personal history of cancer were more likely to have used online patient-provider communication.
Despite wide diffusion of the Internet, online patient-provider communication remains uncommon but is slowly increasing. Policy-level changes are needed to maximize the availability and effectiveness of online patient-provider communication for health care consumers and health care providers. Internet access remains a significant barrier to online patient-provider communication.
Clinical genetic testing can help direct cancer screening for members of Lynch syndrome families; however, there is limited information about family communication of genetic test results.
A total of 174 probands who had genetic testing for Lynch syndrome were enrolled through 4 US cancer genetics clinics. Subjects were asked whether they had disclosed their genetic test results to first-, second-, and third-degree relatives. Univariate and multivariate analyses were used to identify clinical and demographic factors associated with informing immediate and extended family of genetic test results.
One hundred seventy-one of 174 probands (98%; 95% confidence interval, 95%-100%) reported that they had disclosed their genetic test result to a first-degree relative. Communication of test results to other relatives occurred significantly less often, with only 109 of 162 (67%; 95% confidence interval, 59%-74%) subjects with second- or third-degree relatives sharing their results. Individuals with a pathogenic mutation were significantly more likely to inform distant relatives than were subjects with a negative or indeterminate test result (odds ratio, 2.49; 95% confidence interval, 1.14-5.40). Probands' age, sex, and cancer status did not influence communication of genetic test results. Lack of closeness and concerns that relatives would worry or not understand the implications of test results were the primary reasons for not sharing genetic test results.
Most individuals who undergo genetic testing for Lynch syndrome share their test results with first-degree family members; however, these results reach more distant relatives significantly less often. Interventions to improve communication of genetic test results to members of the extended family are necessary to provide optimal cancer prevention care to at-risk families.
Adolescent obesity and social networks.
- Koehly LM
Koehly LM, Loscalzo A. Adolescent obesity and social networks. Prev
Chronic Dis. 2009;6:A99.