Incorporating Family History Research Articles

Leveraging family history in genetic association analyses of binary traits

BackgroundConsidering relatives’ health history in logistic regression for case–control genome-wide association studies (CC-GWAS) may provide new information that increases accuracy and power to detect disease associated genetic variants. We conducted simulations and analyzed type 2 diabetes (T2D) data from the Framingham Heart Study (FHS) to compare two methods, liability threshold model conditional on both case–control status and family history (LT-FH) and Fam-meta, which incorporate family history into CC-GWAS.ResultsIn our simulation scenario of trait with modest T2D heritability (h2 = 0.28), variant minor allele frequency ranging from 1% to 50%, and 1% of phenotype variance explained by the genetic variants, Fam-meta had the highest overall power, while both methods incorporating family history were more powerful than CC-GWAS. All three methods had controlled type I error rates, while LT-FH was the most conservative with a lower-than-expected error rate. In addition, we observed a substantial increase in power of the two familial history methods compared to CC-GWAS when the prevalence of the phenotype increased with age. Furthermore, we showed that, when only the phenotypes of more distant relatives were available, Fam-meta still remained more powerful than CC-GWAS, confirming that leveraging disease history of both close and distant relatives can increase power of association analyses. Using FHS data, we confirmed the well-known association of TCF7L2 region with T2D at the genome-wide threshold of P-value < 5 × 10–8, and both familial history methods increased the significance of the region compared to CC-GWAS. We identified two loci at 5q35 (ADAMTS2) and 5q23 (PRR16), not previously reported for T2D using CC-GWAS and Fam-meta; both genes play a role in cardiovascular diseases. Additionally, CC-GWAS detected one more significant locus at 13q31 (GPC6) reported associated with T2D-related traits.ConclusionsOverall, LT-FH and Fam-meta had higher power than CC-GWAS in simulations, especially using phenotypes that were more prevalent in older age groups, and both methods detected known genetic variants with lower P-values in real data application, highlighting the benefits of including family history in genetic association studies.

Predicting the Need for Biopsy to Detect Clinically Significant Prostate Cancer in Patients with a Magnetic Resonance Imaging–detected Prostate Imaging Reporting and Data System/Likert ≥3 Lesion: Development and Multinational External Validation of the Imperial Rapid Access to Prostate Imaging and Diagnosis Risk Score

BackgroundAlthough multiparametric magnetic resonance imaging (MRI) has high sensitivity, its lower specificity leads to a high prevalence of false-positive lesions requiring biopsy. ObjectiveTo develop and externally validate a scoring system for MRI-detected Prostate Imaging Reporting and Data System (PIRADS)/Likert ≥3 lesions containing clinically significant prostate cancer (csPCa). Design, setting, and participantsThe multicentre Rapid Access to Prostate Imaging and Diagnosis (RAPID) pathway included 1189 patients referred to urology due to elevated age-specific prostate-specific antigen (PSA) and/or abnormal digital rectal examination (DRE); April 27, 2017 to October 25, 2019. InterventionVisual-registration or image-fusion targeted and systematic transperineal biopsies for an MRI score of ≥4 or 3 + PSA density ≥0.12 ng/ml/ml. Outcome measurements and statistical analysisFourteen variables were used in multivariable logistic regression for Gleason ≥3 + 4 (primary) and Gleason ≥4 + 3, and PROMIS definition 1 (any ≥4 + 3 or ≥6 mm any grade; secondary). Nomograms were created and a decision curve analysis (DCA) was performed. Models with varying complexity were externally validated in 2374 patients from six international cohorts. Results and limitationsThe five-item Imperial RAPID risk score used age, PSA density, prior negative biopsy, prostate volume, and highest MRI score (corrected c-index for Gleason ≥3 + 4 of 0.82 and 0.80–0.86 externally). Incorporating family history, DRE, and Black ethnicity within the eight-item Imperial RAPID risk score provided similar outcomes. The DCA showed similar superiority of all models, with net benefit differences increasing in higher threshold probabilities. At 20%, 30%, and 40% of predicted Gleason ≥3 + 4 prostate cancer, the RAPID risk score was able to reduce, respectively, 11%, 21%, and 31% of biopsies against 1.8%, 6.2%, and 14% of missed csPCa (or 9.6%, 17%, and 26% of foregone biopsies, respectively). ConclusionsThe Imperial RAPID risk score provides a standardised tool for the prediction of csPCa in patients with an MRI-detected PIRADS/Likert ≥3 lesion and can support the decision for prostate biopsy. Patient summaryIn this multinational study, we developed a scoring system incorporating clinical and magnetic resonance imaging characteristics to predict which patients have prostate cancer requiring treatment and which patients can safely forego an invasive prostate biopsy. This model was validated in several other countries.

Incorporating family history of disease improves polygenic risk scores in diverse populations

SUMMARYPolygenic risk scores (PRSs) derived from genotype data and family history (FH) of disease provide valuable information for predicting disease risk, but PRSs perform poorly when applied to diverse populations. Here, we explore methods for combining both types of information (PRS-FH) in UK Biobank data. PRSs were trained using all British individuals (n = 409,000), and target samples consisted of unrelated non-British Europeans (n = 42,000), South Asians (n = 7,000), or Africans (n = 7,000). We evaluated PRS, FH, and PRS-FH using liability-scale R2, primarily focusing on 3 well-powered diseases (type 2 diabetes, hypertension, and depression). PRS attained average prediction R2s of 5.8%, 4.0%, and 0.53% in non-British Europeans, South Asians, and Africans, confirming poor cross-population transferability. In contrast, PRS-FH attained average prediction R2s of 13%, 12%, and 10%, respectively, representing a large improvement in Europeans and an extremely large improvement in Africans. In conclusion, including family history improves the accuracy of polygenic risk scores, particularly in diverse populations.

Multi-syndrome, multi-gene risk modeling for individuals with a family history of cancer with the novel R package PanelPRO.

Identifying individuals who are at high risk of cancer due to inherited germline mutations is critical for effective implementation of personalized prevention strategies. Most existing models focus on a few specific syndromes; however, recent evidence from multi-gene panel testing shows that many syndromes are overlapping, motivating the development of models that incorporate family history on several cancers and predict mutations for a comprehensive panel of genes.We present PanelPRO, a new, open-source R package providing a fast, flexible back-end for multi-gene, multi-cancer risk modeling with pedigree data. It includes a customizable database with default parameter values estimated from published studies and allows users to select any combinations of genes and cancers for their models, including well-established single syndrome BayesMendel models (BRCAPRO and MMRPRO). This leads to more accurate risk predictions and ultimately has a high impact on prevention strategies for cancer and clinical decision making. The package is available for download for research purposes at https://projects.iq.harvard.edu/bayesmendel/panelpro.

Exercise Testing, Family History, and Subclinical Atherosclerosis Markers for Cardiovascular Risk Reclassification in Middle-Aged Women

Background Cardiovascular diseases are the main cause of death in women and the accuracy of currently available risk scores is questionable. Objective To reclassify the risk estimated by the Framingham Risk Score (FRS) in asymptomatic middle-aged women by incorporating family history, exercise testing variables, and subclinical atherosclerosis markers. Methods This cross-sectional study included 509 women (age range, 46-65 years) without cardiovascular symptoms. Those at low or intermediate risk by the FRS were reclassified to a higher level considering premature [...]

Family history assessment significantly enhances delivery of precision medicine in the genomics era

BackgroundFamily history has traditionally been an essential part of clinical care to assess health risks. However, declining sequencing costs have precipitated a shift towards genomics-first approaches in population screening programs rendering the value of family history unknown. We evaluated the utility of incorporating family history information for genomic sequencing selection.MethodsTo ascertain the relationship between family histories on such population-level initiatives, we analysed whole genome sequences of 1750 research participants with no known pre-existing conditions, of which half received comprehensive family history assessment of up to four generations, focusing on 95 cancer genes.ResultsAmongst the 1750 participants, 866 (49.5%) had high-quality standardised family history available. Within this group, 73 (8.4%) participants had an increased family history risk of cancer (increased FH risk cohort) and 1 in 7 participants (n = 10/73) carried a clinically actionable variant inferring a sixfold increase compared with 1 in 47 participants (n = 17/793) assessed at average family history cancer risk (average FH risk cohort) (p = 0.00001) and a sevenfold increase compared to 1 in 52 participants (n = 17/884) where family history was not available (FH not available cohort) (p = 0.00001). The enrichment was further pronounced (up to 18-fold) when assessing only the 25 cancer genes in the American College of Medical Genetics (ACMG) Secondary Findings (SF) genes. Furthermore, 63 (7.3%) participants had an increased family history cancer risk in the absence of an apparent clinically actionable variant.ConclusionsThese findings demonstrate that the collection and analysis of comprehensive family history and genomic data are complementary and in combination can prioritise individuals for genomic analysis. Thus, family history remains a critical component of health risk assessment, providing important actionable data when implementing genomics screening programs.Trial registrationClinicalTrials.gov NCT02791152. Retrospectively registered on May 31, 2016.

Acceptability and potential impact on uptake of using different risk stratification approaches to determine eligibility for screening: A population-based survey.

BackgroundUsing risk stratification approaches to determine eligibility has the potential to improve efficiency of screening.ObjectivesTo compare the public acceptability and potential impact on uptake of using different approaches to determine eligibility for screening.DesignAn online population‐based survey of 668 adults in the UK aged 45‐79 including a series of scenarios in the context of a potential kidney cancer screening programme in which eligibility was determined by age, sex, age and sex combined, a simple risk score (age, sex, body mass index, smoking status), a complex risk score additionally incorporating family history and lifestyle, or a genetic risk score.Outcome measuresWe used multi‐level ordinal logistic regression to compare acceptability and potential uptake within individuals and multivariable ordinal logistic regression differences between individuals.ResultsUsing sex, age and sex, or the simple risk score were less acceptable than age (P < .0001). All approaches were less acceptable to women than men. Over 70% were comfortable waiting until they were older if the complex risk score or genetics indicated a low risk. If told they were high risk, 85% would be more likely to take up screening. Being told they were low risk had no overall influence on uptake.ConclusionsVarying the starting age of screening based on estimated risk from models incorporating phenotypic or genetic risk factors would be acceptable to most individuals and may increase uptake.Patient or Public ContributionTwo members of the public contributed to the development of the survey and have commented on this paper.

Genetic analysis of biobank data: Familial history aggregation‐based tests (FHAT) with application to Alzheimer's disease

AbstractBackgroundBiobanks provide great resources for genetic association analysis. To increase power of genetic association analysis, we propose a novel approach to exploit family history of disease that is often available in biobanks. While methods have been proposed to incorporate family history in single variant analysis, methods to incorporate this information in gene‐based tests, such as the Sequence kernel association test (SKAT), are not available. The goal of this project is to develop a familial history aggregation‐based test (FHAT) to improve power to detect rare variant associations in gene‐based tests, and to apply this method to detect genes associated with Alzheimer’s Disease (AD).MethodWe assume that participants’ genotypes, and phenotypes of participants’ and their relatives, such as parents, are available from a large cohort. We first assess the association between participants’ genotypes and their phenotypes. Then we evaluate the association between participants’ genotypes and a set of relatives’ disease status conditional on the participants’ disease status. We use a weighted meta‐analysis to combing the score statistics from probands and their relatives. We evaluate the FHAT in simulations, and we apply our novel method to detect associations of gene regions with Alzheimer’s Disease (AD) in the UK Biobank data incorporating parental disease history.ResultOur simulation results showed that the type I error of FHAT is well controlled with disease prevalence of 10% and 20%. We obtained corrected type I error rate at various alpha levels using 10,000 simulation replicates with a sample size of 5,000. Out of seven genes previously implicated in AD susceptibility, six showed evidence of association using FHAT in UK Biobank. These six genes had improved significance after incorporating parental phenotype information.ConclusionWe proposed a novel approach to include family history, as is often available from medical charts, and showed improved power to detect aggregates of rare variant genetic associations with AD in large cohorts or biobanks.

Association between having a family member with dementia and perceptions of dementia preventability

Background One’s experience with dementia may affect their perceptions about dementia preventability, which in turn could influence preventive health behaviors. We aimed to examine how having a family history of dementia and caregiving experience are associated with perceptions about and self-efficacy for dementia preventability. Methods Cross-sectional, self-administered survey. Participants reported whether they have had a family member with dementia and, among those who reported having a family member with dementia, whether they served as a caregiver. Outcomes were perceptions about the likelihood of dementia preventability, self-efficacy for dementia prevention, and benefits of specific dementia prevention strategies. Associations were assessed via partial proportional odds model for ordinal outcome variables and logistic regression for binary outcome variables. Results Of 1,575 respondents, 71% had a family member with dementia, of which 42% served as a caregiver. People with a family member with dementia were less likely to believe that dementia is preventable (aOR = 0.75, 95% CI: 0.58, 0.96) and had lower self-efficacy for dementia prevention (aOR = 0.71, 95% CI: 0.56, 0.90). The subgroup analysis among those with caregiving experience was consistent with the primary findings, showing less belief in the likelihood of dementia preventability (aOR = 0.69, 95% CI: 0.46, 1.03) and self-efficacy (aOR = 0.75, 95% CI: 0.56, 1.00). Conclusion Having a family member with dementia is associated with unfavorable perceptions about dementia preventability. Incorporating family history of dementia into communication efforts about dementia risk reduction may help address potential barriers to preventive health behaviors.

Familial Barrett’s Esophagus and Esophageal Adenocarcinoma

To examine the evidence for Familial Barrett’s Esophagus and Esophageal Adenocarcinoma and putative causative genes. Recent large population studies continue to provide evidence for Familial Barrett’s Esophagus and Esophageal Adenocarcinoma. Also, based on sequencing of two multigenerational families with Barrett’s esophagus and/or esophageal adenocarcinoma, two new possible causative gene variants have been identified including VSIG10L and MSX1. Familial Barrett’s esophagus and esophageal adenocarcinoma is increasingly becoming more recognized. Current guidelines also now incorporate family history as a risk factor for Barrett’s esophagus. Recent studies include DNA sequencing of multigenerational families in addition to previously performed GWAS studies. Several new gene variants now have been identified; however, phenotypic and mechanistic studies need to be performed to demonstrate their association with Barrett’s esophagus and esophageal adenocarcinoma.

Individual vulnerabilities to psychosis after antiepileptic drug administration

BackgroundPsychosis often develops after the administration of antiepileptic drugs (AEDs) in patients with epilepsy. However, the individual vulnerability and clinical condition of such patients have been rarely scrutinised. We investigated...

Liability threshold modeling of case-control status and family history of disease increases association power.

Family history of disease can provide valuable information in case-control association studies, but it is currently unclear how to best combine case-control status and family history of disease. We developed an association method based on posterior mean genetic liabilities under a liability threshold model, conditional on case-control status and family history (LT-FH). Analyzing 12 diseases from the UK Biobank (average N=350K), we compared LT-FH to genome-wide association without using family history (GWAS) and a previous proxy-based method incorporating family history (GWAX). LT-FH was +63% (s.e. 6%) more powerful than GWAS and +36% (s.e. 4%) more powerful than the trait-specific maximum of GWAS and GWAX, based on the number of independent genome-wide significant loci across all diseases (e.g. 690 loci for LT-FH vs. 423 for GWAS); relative improvements were similar when applying BOLT-LMM to GWAS, GWAX, LT-FH phenotypes. Thus, LT-FH greatly increases association power when family history of disease is available.

The Prevalence of Elevated Lipoprotein(a) in Patients Presenting With Coronary Artery Disease

Elevated lipoprotein(a) (Lp(a)) is an inherited lipid disorder and an independent risk factor for cardiovascular (CV) disease. Although its prevalence in the general population has been well-documented, the prevalence of elevated Lp(a) in patients with clinical coronary artery disease (CAD) is less clear. In this study, we hypothesised that there is an over-representation of elevated Lp(a) in patients with early-onset CAD compared to the general population. Between 6 February and 8 June 2018, we screened consecutive patients aged ≤70 years who presented to the Austin Hospital with any of the following criteria: (1) acute coronary syndrome (ACS); (2) percutaneous coronary intervention (PCI); or (3) coronary artery bypass grafting (CABG). Whilst examining a range of different Lp(a) levels, a dichotomous elevated Lp(a) was defined as concentrations ≥0.5 g/L. Other CV risk factors were documented including hypertension, type 2 diabetes mellitus, and familial hypercholesterolaemia (FH) using the Dutch Lipid Clinic Network Criteria (DLCNC), also incorporating family history and clinical examination. One hundred and fifty-eight (158) patients were screened; 63 (39.9%) were under 60 years of age. Overall, elevated Lp(a) ≥0.5 g/L was identified in 57 patients (36.1%). Of these, nine patients (15.8%) also had probable or definite FH. General population data was obtained from the Copenhagen General Population Study which studied 6,000 men and women and showed that the estimated prevalence of Lp(a) ≥0.5 g/L in the general population was 20%. Elevated Lp(a) is more prevalent in patients with relatively early-onset CAD compared to the general population and may contribute to previously unappreciated residual cardiovascular risk. Patients who present with early-onset CAD, should be routinely screened for elevated Lp(a).

A New Comprehensive Colorectal Cancer Risk Prediction Model Incorporating Family History, Personal Characteristics, and Environmental Factors.

Reducing colorectal cancer incidence and mortality through early detection would improve efficacy if targeted. We developed a colorectal cancer risk prediction model incorporating personal, family, genetic, and environmental risk factors to enhance prevention. A familial risk profile (FRP) was calculated to summarize individuals' risk based on detailed cancer family history (FH), family structure, probabilities of mutation in major colorectal cancer susceptibility genes, and a polygenic component. We developed risk models, including individuals' FRP or binary colorectal cancer FH, and colorectal cancer risk factors collected at enrollment using population-based colorectal cancer cases (N = 4,445) and controls (N = 3,967) recruited by the Colon Cancer Family Registry Cohort (CCFRC). Model validation used CCFRC follow-up data for population-based (N = 12,052) and clinic-based (N = 5,584) relatives with no cancer history at recruitment to assess model calibration [expected/observed rate ratio (E/O)] and discrimination [area under the receiver-operating-characteristic curve (AUC)]. The E/O [95% confidence interval (CI)] for FRP models for population-based relatives were 1.04 (0.74-1.45) for men and 0.86 (0.64-1.20) for women, and for clinic-based relatives were 1.15 (0.87-1.58) for men and 1.04 (0.76-1.45) for women. The age-adjusted AUCs (95% CI) for FRP models for population-based relatives were 0.69 (0.60-0.78) for men and 0.70 (0.62-0.77) for women, and for clinic-based relatives were 0.77 (0.69-0.84) for men and 0.68 (0.60-0.76) for women. The incremental values of AUC for FRP over FH models for population-based relatives were 0.08 (0.01-0.15) for men and 0.10 (0.04-0.16) for women, and for clinic-based relatives were 0.11 (0.05-0.17) for men and 0.11 (0.06-0.17) for women. Both models calibrated well. The FRP-based model provided better risk stratification and risk discrimination than the FH-based model. Our findings suggest detailed FH may be useful for targeted risk-based screening and clinical management.

Leveraging Family History in Case-Control Analyses of Rare Variation.

Standard methods for case-control association studies of rare variation often treat disease outcome as a dichotomous phenotype. However, both theoretical and experimental studies have demonstrated that subjects with a family history of disease can be enriched for risk variation relative to subjects without such history. Assuming family history information is available, this observation motivates the idea of replacing the standard dichotomous outcome variable used in case-control studies with a more informative ordinal outcome variable that distinguishes controls (0), sporadic cases (1), and cases with a family history (2), with the expectation that we should observe increasing number of risk variants with increasing category of the ordinal variable. To leverage this expectation, we propose a novel rare-variant association test that incorporates family history information based on our previous GAMuT framework for rare-variant association testing of multivariate phenotypes. We use simulated data to show that, when family history information is available, our new method outperforms standard rare-variant association methods, like burden and SKAT tests, that ignore family history. We further illustrate our method using a rare-variant study of cleft lip and palate.

Risk of breast or ovarian cancer in family members who do not carry the BRCA1 or BRCA2 family mutation: Findings from the EMBRACE study.

1558 Background: BRCA1/BRCA2 true-negatives are proven non-carriers of the BRCA mutation segregating within their family. Currently, there is no conclusive evidence on the risk of developing breast or ovarian cancer in these individuals, potentially leading to non-uniform clinical practices. The purpose of this study was to estimate breast and ovarian cancer risks for true-negatives from the EMBRACE prospective cohort study. Methods: Risks were calculated separately for incident invasive breast cancer and epithelial ovarian cancer (EOC). We used cohort analysis to estimate incidences, cumulative risks and standardised incidence ratios (SIRs). Results: A total of 1895 unaffected women were eligible for inclusion in the breast cancer analysis and 1736 for the ovarian cancer analysis. There were 23 incident invasive breast cancers and 2 EOCs diagnosed during follow-up. The cumulative risk of invasive breast cancer was 9.4% (95% CI 5.9%-15%) by the age of 85-years, whilst the corresponding risk of EOC was 0.6% (95% CI 0.2%-2.6%). The SIR for breast cancer was 0.93 (95% CI 0.62-1.40) in the overall cohort, 0.85 (95% CI 0.48-1.50) in non-carriers from BRCA1 families and 1.03 (95% CI 0.57-1.87) in non-carriers from BRCA2 families. The SIR for EOC was 0.79 (95% CI 0.20-3.17) in the overall cohort and 1.74 (95% CI 0.44-6.98) in non-carriers from BRCA2 families. Conclusions: This is the largest cohort to date of prospectively ascertained true-negatives from BRCA1/ BRCA2 families. Our results did not provide evidence for elevated risks of invasive breast cancer or EOC in proven non-carriers. Risk-reducing bilateral mastectomy and risk-reducing salpingo-oophorectomy may not be appropriate for these individuals. Female relatives of a known BRCA1/BRCA2 mutation carrier should be advised towards genetic testing to avoid unnecessary surgical procedures. However, we were not able to investigate variation in risks by cancer family history. Therefore, we cannot rule out that risks may be slightly higher for close relatives of affected mutation carriers. In such cases, model-based estimates incorporating family history, such as those given by BOADICEA, can be used in the counselling process.

Long-Term Risk of Atherosclerotic Cardiovascular Disease in US Adults With the Familial Hypercholesterolemia Phenotype.

Heterozygous familial hypercholesterolemia (FH) affects up to 1 in 200 individuals in the United States, but atherosclerotic cardiovascular disease (ASCVD) outcomes of FH in the general US population have not been described. We therefore sought to evaluate long-term coronary heart disease (CHD) and total ASCVD risks in US adults with an FH phenotype. Using individual pooled data from 6 large US epidemiological cohorts, we stratified participants by low-density lipoprotein cholesterol level at index ages from 20 to 79 years. For the primary analysis, low-density lipoprotein cholesterol levels ≥190 and <130 mg/dL defined the FH phenotype and referent, respectively. Sensitivity analyses evaluated the effects of varying the FH phenotype definition. We used Cox regression models to assess covariate-adjusted associations of the FH phenotype with 30-year hazards for CHD (CHD death or nonfatal myocardial infarction) and total ASCVD (CHD or stroke). We included 68 565 baseline person-examinations; 3850 (5.6%) had the FH phenotype by the primary definition. Follow-up across index ages ranged from 78 985 to 308 378 person-years. After covariate adjustment, the FH phenotype was associated with substantially elevated 30-year CHD risk, with hazard ratios up to 5.0 (95% confidence interval, 1.1-21.7). Across index ages, CHD risk was accelerated in those with the FH phenotype by 10 to 20 years in men and 20 to 30 years in women. Similar patterns of results were found for total ASCVD risk, with hazard ratios up to 4.1 (95% confidence interval, 1.2-13.4). Alternative FH phenotype definitions incorporating family history, more stringent age-based low-density lipoprotein cholesterol thresholds, or alternative lipid fractions decreased the FH phenotype prevalence to as low as 0.2% to 0.4% without materially affecting CHD risk estimates (hazard ratios up to 8.0; 95% confidence interval, 1.0-61.6). In the general US population, the long-term ASCVD burden related to phenotypic FH, defined by low-density lipoprotein cholesterol ≥190 mg/dL, is likely substantial. Our finding of CHD risk acceleration may aid efforts in risk communication.

Highlights of This Issue

The TMPRSS2:ERG gene fusion is the most common somatic event in prostate cancer. There is intriguing evidence that TMPRSS2:ERG represents a unique molecular subtype. Penney and colleagues examined the association of 39 prostate cancer genetic risk variants with TMPRSS2:ERG fusion positive and negative disease. Six of the variants were significantly differentially associated with fusion-positive versus fusion-negative disease. These findings suggest that the molecular events in prostate carcinogenesis may be distinct for men depending on their underlying genetic predisposition. When examining other risk factors for prostate cancer, the integration of molecular subtypes may improve understanding of the etiology of this disease.It is important to develop risk prediction models for individuals with Barrett's esophagus (BE) who are at increased risk of esophageal adenocarcinoma (EAC). Sun and colleagues developed a risk prediction model using singly ascertained BE pedigrees and multiplex BE pedigrees and incorporating family history and clinical risk factors. This study indicates that family information is valuable in predicting BE risk, and this new model will assist in both identifying high-risk individuals for BE screening and potentially reducing mortality from EAC.Little is known about the serostability of polyomaviruses (PyV) over time, or associations with cutaneous squamous cell carcinoma (SCC). In a case–control study, Gossai and colleagues measured antibody response against BK and JC. Among controls, BK and JC seroreactivity was stable over time, and there was little evidence of seroconversion following SCC diagnosis. JC seropositivity prior to diagnosis was associated with an elevated risk of SCC. A single measure of PyV seroreactivity appears a reliable indicator of long-term antibody status, and seropositivity to certain PyVs may be related to subsequent occurrence of SCC.Johnson and colleagues examined the effects of residential segregation and deprivation on treatment and survival in non–small cell lung cancer patients living in the state of Georgia. Living in areas with high levels of segregation was associated with decreased odds of receipt of surgery. Black patients living in high residential segregation/high deprivation were 31% more likely to die, even after surgery was controlled for. For white patients, economic deprivation was associated with decreased odds of surgery but not survival, and residential segregation had no effect. This study suggests differences in how black and white individuals experience segregation and poverty lead to differences in adverse health outcomes.

Predicting Barrett's Esophagus in Families: An Esophagus Translational Research Network (BETRNet) Model Fitting Clinical Data to a Familial Paradigm.

Barrett's esophagus is often asymptomatic and only a small portion of Barrett's esophagus patients are currently diagnosed and under surveillance. Therefore, it is important to develop risk prediction models to identify high-risk individuals with Barrett's esophagus. Familial aggregation of Barrett's esophagus and esophageal adenocarcinoma, and the increased risk of esophageal adenocarcinoma for individuals with a family history, raise the necessity of including genetic factors in the prediction model. Methods to determine risk prediction models using both risk covariates and ascertained family data are not well developed. We developed a Barrett's Esophagus Translational Research Network (BETRNet) risk prediction model from 787 singly ascertained Barrett's esophagus pedigrees and 92 multiplex Barrett's esophagus pedigrees, fitting a multivariate logistic model that incorporates family history and clinical risk factors. The eight risk factors, age, sex, education level, parental status, smoking, heartburn frequency, regurgitation frequency, and use of acid suppressant, were included in the model. The prediction accuracy was evaluated on the training dataset and an independent validation dataset of 643 multiplex Barrett's esophagus pedigrees. Our results indicate family information helps to predict Barrett's esophagus risk, and predicting in families improves both prediction calibration and discrimination accuracy. Our model can predict Barrett's esophagus risk for anyone with family members known to have, or not have, had Barrett's esophagus. It can predict risk for unrelated individuals without knowing any relatives' information. Our prediction model will shed light on effectively identifying high-risk individuals for Barrett's esophagus screening and surveillance, consequently allowing intervention at an early stage, and reducing mortality from esophageal adenocarcinoma. Cancer Epidemiol Biomarkers Prev; 25(5); 727-35. ©2016 AACR.

A systematic approach incorporating family history improves identification of cardiovascular disease risk.

Although family history (FH) is an independent predictor of cardiovascular disease (CVD) risk, traditional risk scores do not incorporate FH. Nurse practitioners routinely solicit FH but have no mechanism to incorporate the information into risk estimation. Underestimation of risk leaves clinicians misinformed and patients vulnerable to the CVD epidemic. We examined a systematic approach incorporating FH in CVD risk assessment, validating risk reclassification using carotid intima-media thickness (CIMT), a surrogate measure of atherosclerosis. Of 413 consecutive patients prospectively enrolled in the Integrative Cardiac Health Project Registry, a subgroup of 239 was low or intermediate risk by the Framingham Risk Score. A systematic approach for the assessment of FH was applied to this subgroup of the registry. A positive FH for premature CVD, defined as a first-degree relative having a CVD event before the age of 55 years in men and 65 years in women, conferred reclassification to high risk. Reclassification was validated with CIMT results. Chart audits revealed adherence to the systematic approach for FH assessment in 100% of cases. This systematic approach identified 115 of 239 (48%) patients as high risk because of positive FH. Of the reclassified patients, 75% had evidence of subclinical atherosclerosis by CIMT versus 55% in the patients not reclassified, P < 0.001. Logistic regression identified positive FH for premature CVD (odds ratio, 2.6; P = 0.001) among all variables, as the most significant predictor of abnormal CIMT, thus increasing risk for CVD. The Integrative Cardiac Health Project systematic approach incorporating FH into risk stratification enhances CVD risk assessment by identifying previously unrecognized high-risk patients, reduces variability in practice, and appropriately targets more stringent therapeutic goals for prevention.