The admixture maximum likelihood test to test for association between rare variants and disease phenotypes.

BACKGROUND: The development of genotyping arrays containing hundreds of thousands of rare variants across the genome and advances in high-throughput sequencing technologies have made feasible empirical genetic association studies to search for rare disease susceptibility alleles. As single variant testing is underpowered to detect associations, the development of statistical methods to combine analysis across variants - so-called "burden tests" - is an area of active research interest. We previously developed a method, the admixture maximum likelihood test, to test multiple, common variants for association with a trait of interest. We have extended this method, called the rare admixture maximum likelihood test (RAML), for the analysis of rare variants. In this paper we compare the performance of RAML with six other burden tests designed to test for association of rare variants. RESULTS: We used simulation testing over a range of scenarios to test the power of RAML compared to the other rare variant association testing methods. These scenarios modelled differences in effect variability, the average direction of effect and the proportion of associated variants. We evaluated the power for all the different scenarios. RAML tended to have the greatest power for most scenarios where the proportion of associated variants was small, whereas SKAT-O performed a little better for the scenarios with a higher proportion of associated variants. CONCLUSIONS: The RAML method makes no assumptions about the proportion of variants that are associated with the phenotype of interest or the magnitude and direction of their effect. The method is flexible and can be applied to both dichotomous and quantitative traits and allows for the inclusion of covariates in the underlying regression model. The RAML method performed well compared to the other methods over a wide range of scenarios. Generally power was moderate in most of the scenarios, underlying the need for large sample sizes in any form of association testing.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Evidence of a Causal Association Between Cancer and Alzheimer’s Disease: a Mendelian Randomization Analysis

Abstract: While limited observational evidence suggests that cancer survivors have a decreased risk of developing Alzheimer’s disease (AD), and vice versa, it is not clear whether this relationship is causal. Using a Mendelian randomization approach that provides evidence of causality, we found that genetically predicted lung cancer (OR 0.91, 95% CI 0.84–0.99, p = 0.019), leukemia (OR 0.98, 95% CI 0.96–0.995, p = 0.012), and breast cancer (OR 0.94, 95% CI 0.89–0.99, p = 0.028) were associated with 9.0%, 2.4%, and 5.9% lower odds of AD, respectively, per 1-unit higher log odds of cancer. When genetic predictors of all cancers were pooled, cancer was associated with 2.5% lower odds of AD (OR 0.98, 95% CI 0.96–0.988, p = 0.00027) per 1-unit higher log odds of cancer. Finally, genetically predicted smoking-related cancers showed a more robust inverse association with AD than non-smoking related cancers (OR 0.95, 95% CI 0.92–0.98, p = 0.0026, vs. OR 0.98, 95% CI 0.97–0.995, p = 0.0091)

Sociodemographic and lifestyle predictors of incident hospital admissions with multimorbidity in a general population, 1999-2019: the EPIC-Norfolk cohort.

BACKGROUND:The ageing population and prevalence of long-term disorders with multimorbidity are a major health challenge worldwide. The associations between comorbid conditions and mortality risk are well established; however, few prospective community-based studies have reported on prior risk factors for incident hospital admissions with multimorbidity. We aimed to explore the independent associations for a range of demographic, lifestyle and physiological determinants and the likelihood of subsequent hospital incident multimorbidity. METHODS:We examined incident hospital admissions with multimorbidity in 25 014 men and women aged 40-79 in a British prospective population-based study recruited in 1993-1997 and followed up until 2019. The determinants of incident multimorbidity, defined as Charlson Comorbidity Index ≥3, were investigated using multivariable logistic regression models for the 10-year period 1999-2009 and repeated with independent measurements in a second 10-year period 2009-2019. RESULTS:Between 1999 and 2009, 18 179 participants (73% of the population) had a hospital admission. Baseline 5-year and 10-year incident multimorbidities were observed in 6% and 12% of participants, respectively. Age per 10-year increase (OR 2.19, 95% CI 2.06 to 2.33) and male sex (OR 1.32, 95% CI 1.19 to 1.47) predicted incident multimorbidity over 10 years. In the subset free of the most serious diseases at baseline, current smoking (OR 1.86, 95% CI 1.60 to 2.15), body mass index >30 kg/m² (OR 1.48, 95% CI 1.30 to 1.70) and physical inactivity (OR 1.16, 95% CI 1.04 to 1.29) were positively associated and plasma vitamin C (a biomarker of plant food intake) per SD increase (OR 0.86, 95% CI 0.81 to 0.91) inversely associated with incident 10-year multimorbidity after multivariable adjustment for age, sex, social class, education, alcohol consumption, systolic blood pressure and cholesterol. Results were similar when re-examined for a further time period in 2009-2019. CONCLUSION:Age, male sex and potentially modifiable lifestyle behaviours including smoking, body mass index, physical inactivity and low fruit and vegetable intake were associated with increased risk of future incident hospital admissions with multimorbidity

Residential area deprivation and risk of subsequent hospital admission in a British population: the EPIC-Norfolk cohort.

OBJECTIVES:To investigate whether residential area deprivation index predicts subsequent admissions to hospital and time spent in hospital independently of individual social class and lifestyle factors. DESIGN:Prospective population-based study. SETTING:The European Prospective Investigation into Cancer in Norfolk (EPIC-Norfolk) study. PARTICIPANTS:11 214 men and 13 763 women in the general population, aged 40-79 years at recruitment (1993-1997), alive in 1999. MAIN OUTCOME MEASURE:Total admissions to hospital and time spent in hospital during a 19-year time period (1999-2018). RESULTS:Compared to those with residential Townsend Area Deprivation Index lower than the average for England and Wales, those with a higher than average deprivation index had a higher likelihood of spending >20 days in hospital multivariable adjusted OR 1.18 (95% CI 1.07 to 1.29) and having 7 or more admissions OR 1.11 (95% CI 1.02 to 1.22) after adjustment for age, sex, smoking status, education, social class and body mass index. Occupational social class and educational attainment modified the association between area deprivation and hospitalisation; those with manual social class and lower education level were at greater risk of hospitalisation when living in an area with higher deprivation index (p-interaction=0.025 and 0.020, respectively), while the risk for non-manual and more highly educated participants did not vary greatly by area of residence. CONCLUSION:Residential area deprivation predicts future hospitalisations, time spent in hospital and number of admissions, independently of individual social class and education level and other behavioural factors. There are significant interactions such that residential area deprivation has greater impact in those with low education level or manual social class. Conversely, higher education level and social class mitigated the association of area deprivation with hospital usage

Test-Retest Reliability of Self-Reported Sexual Behavior History in Urbanized Nigerian Women.

BACKGROUND: Studies assessing risk of sexual behavior and disease are often plagued by questions about the reliability of self-reported sexual behavior. In this study, we evaluated the reliability of self-reported sexual history among urbanized women in a prospective study of cervical HPV infections in Nigeria. METHODS: We examined test-retest reliability of sexual practices using questionnaires administered at study entry and at follow-up visits. We used the root mean squared approach to calculate within-person coefficient of variation (CVw) and calculated the intra-class correlation coefficient (ICC) using two way, mixed effects models for continuous variables and [Formula: see text] statistics for discrete variables. To evaluate the potential predictors of reliability, we used linear regression and log binomial regression models for the continuous and categorical variables, respectively. RESULTS: We found that self-reported sexual history was generally reliable, with overall ICC ranging from 0.7 to 0.9; however, the reliability varied by nature of sexual behavior evaluated. Frequency reports of non-vaginal sex (agreement = 63.9%, 95% CI: 47.5-77.6%) were more reliable than those of vaginal sex (agreement = 59.1%, 95% CI: 55.2-62.8%). Reports of time-invariant behaviors were also more reliable than frequency reports. The CVw for age at sexual debut was 10.7 (95% CI: 10.6-10.7) compared with the CVw for lifetime number of vaginal sex partners, which was 35.2 (95% CI: 35.1-35.3). The test-retest interval was an important predictor of reliability of responses, with longer intervals resulting in increased inconsistency (average change in unreliability for each 1 month increase = 0.04, 95% CI = 0.07-0.38, p = 0.005). CONCLUSION: Our findings suggest that overall, the self-reported sexual history among urbanized Nigeran women is reliable

Vaginal microbiota diversity and paucity of Lactobacillus species are associated with persistent hrHPV infection in HIV negative but not in HIV positive women.

Funder: Maryland Department of Health and Mental Hygiene; doi: http://dx.doi.org/10.13039/100006671The vaginal microbiota is thought to play a role in modulating risk of high-risk human papillomavirus (hrHPV) infection. We examined the relationship between the vaginal microbiota and persistent hrHPV infection in HIV-negative and HIV-positive women. We used 16S-rRNA sequencing to characterize the vaginal microbiota of two serial samples taken six months apart from 211 Nigerian women (67%, 142/211 HIV-positive and 33%, 69/211 HIV-negative) and evaluated the association between the vaginal microbiota and persistent hrHPV infection using generalized estimating equation logistic regression models and linear discriminant analysis effect size (LEfSe) algorithm to identify phylotypic biomarkers of persistent hrHPV infection. The high diversity microbiota, Community State Type IV-B, was the most prevalent in both HIV-negative (38% at baseline, 30% at the follow-up visit) and HIV-positive (27% at baseline, 35% at the follow-up visit) women. The relationship between the vaginal microbiota and persistent hrHPV was modified by HIV status. In HIV-negative women, women with Lactobacillus dominant microbiota had lower odds (OR: 0.35, 95% CI 0.14-0.89, p = 0.03) of persistent hrHPV compared to women with Lactobacillus deficient microbiota. While among HIV-positive women, the odds of being persistently infected with hrHPV was higher in women with Lactobacillus dominant microbiota (OR: 1.25, 95% CI 0.73-2.14 p = 0.41). This difference in effect estimates by HIV was statistically significant (p = 0.02). A high diversity vaginal microbial community with paucity of Lactobacillus species was associated with persistent hrHPV infection in HIV-negative women but not in HIV-positive women

Genomic risk prediction of coronary artery disease in women with breast cancer: a prospective cohort study.

Funder: Wellcome TrustBackgroundAdvancements in cancer therapeutics have resulted in increases in cancer-related survival; however, there is a growing clinical dilemma. The current balancing of survival benefits and future cardiotoxic harms of oncotherapies has resulted in an increased burden of cardiovascular disease in breast cancer survivors. Risk stratification may help address this clinical dilemma. This study is the first to assess the association between a coronary artery disease-specific polygenic risk score and incident coronary artery events in female breast cancer survivors.MethodsWe utilized the Studies in Epidemiology and Research in Cancer Heredity prospective cohort involving 12,413 women with breast cancer with genotype information and without a baseline history of cardiovascular disease. Cause-specific hazard ratios for association of the polygenic risk score and incident coronary artery disease (CAD) were obtained using left-truncated Cox regression adjusting for age, genotype array, conventional risk factors such as smoking and body mass index, as well as other sociodemographic, lifestyle, and medical variables.ResultsOver a median follow-up of 10.3 years (IQR: 16.8) years, 750 incident fatal or non-fatal coronary artery events were recorded. A 1 standard deviation higher polygenic risk score was associated with an adjusted hazard ratio of 1.33 (95% CI 1.20, 1.47) for incident CAD.ConclusionsThis study provides evidence that a coronary artery disease-specific polygenic risk score can risk-stratify breast cancer survivors independently of other established cardiovascular risk factors

Incorporating truncating variants in PALB2, CHEK2, and ATM into the BOADICEA breast cancer risk model.

PURPOSE: The proliferation of gene panel testing precipitates the need for a breast cancer (BC) risk model that incorporates the effects of mutations in several genes and family history (FH). We extended the BOADICEA model to incorporate the effects of truncating variants in PALB2, CHEK2, and ATM. METHODS: The BC incidence was modeled via the explicit effects of truncating variants in BRCA1/2, PALB2, CHEK2, and ATM and other unobserved genetic effects using segregation analysis methods. RESULTS: The predicted average BC risk by age 80 for an ATM mutation carrier is 28%, 30% for CHEK2, 50% for PALB2, and 74% for BRCA1 and BRCA2. However, the BC risks are predicted to increase with FH burden. In families with mutations, predicted risks for mutation-negative members depend on both FH and the specific mutation. The reduction in BC risk after negative predictive testing is greatest when a BRCA1 mutation is identified in the family, but for women whose relatives carry a CHEK2 or ATM mutation, the risks decrease slightly. CONCLUSIONS: The model may be a valuable tool for counseling women who have undergone gene panel testing for providing consistent risks and harmonizing their clinical management. A Web application can be used to obtain BC risks in clinical practice (http://ccge.medschl.cam.ac.uk/boadicea/).Genet Med 18 12, 1190-1198.This work was funded by Cancer Research UK Grants C12292/A11174 and C1287/A10118. ACA is a Cancer Research UK Senior Cancer Research Fellow. This work was supported by the Governement of Canada through Genome Canada and the Canadian Institutes of Health Research, and the Ministère de l'enseignement supérieur, de la recherche, de la science et de la technologie du Québec through Génome Québec.This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/gim.2016.3

Polygenic risk-tailored screening for prostate cancer: A benefit-harm and cost-effectiveness modelling study.

BACKGROUND: The United States Preventive Services Task Force supports individualised decision-making for prostate-specific antigen (PSA)-based screening in men aged 55-69. Knowing how the potential benefits and harms of screening vary by an individual's risk of developing prostate cancer could inform decision-making about screening at both an individual and population level. This modelling study examined the benefit-harm tradeoffs and the cost-effectiveness of a risk-tailored screening programme compared to age-based and no screening. METHODS AND FINDINGS: A life-table model, projecting age-specific prostate cancer incidence and mortality, was developed of a hypothetical cohort of 4.48 million men in England aged 55 to 69 years with follow-up to age 90. Risk thresholds were based on age and polygenic profile. We compared no screening, age-based screening (quadrennial PSA testing from 55 to 69), and risk-tailored screening (men aged 55 to 69 years with a 10-year absolute risk greater than a threshold receive quadrennial PSA testing from the age they reach the risk threshold). The analysis was undertaken from the health service perspective, including direct costs borne by the health system for risk assessment, screening, diagnosis, and treatment. We used probabilistic sensitivity analyses to account for parameter uncertainty and discounted future costs and benefits at 3.5% per year. Our analysis should be considered cautiously in light of limitations related to our model's cohort-based structure and the uncertainty of input parameters in mathematical models. Compared to no screening over 35 years follow-up, age-based screening prevented the most deaths from prostate cancer (39,272, 95% uncertainty interval [UI]: 16,792-59,685) at the expense of 94,831 (95% UI: 84,827-105,630) overdiagnosed cancers. Age-based screening was the least cost-effective strategy studied. The greatest number of quality-adjusted life-years (QALYs) was generated by risk-based screening at a 10-year absolute risk threshold of 4%. At this threshold, risk-based screening led to one-third fewer overdiagnosed cancers (64,384, 95% UI: 57,382-72,050) but averted 6.3% fewer (9,695, 95% UI: 2,853-15,851) deaths from prostate cancer by comparison with age-based screening. Relative to no screening, risk-based screening at a 4% 10-year absolute risk threshold was cost-effective in 48.4% and 57.4% of the simulations at willingness-to-pay thresholds of GBP£20,000 (US$26,000) and £30,000 ($39,386) per QALY, respectively. The cost-effectiveness of risk-tailored screening improved as the threshold rose. CONCLUSIONS: Based on the results of this modelling study, offering screening to men at higher risk could potentially reduce overdiagnosis and improve the benefit-harm tradeoff and the cost-effectiveness of a prostate cancer screening program. The optimal threshold will depend on societal judgements of the appropriate balance of benefits-harms and cost-effectiveness