Haplotype frequency estimation error analysis in the presence of missing genotype data

BACKGROUND: Increasingly researchers are turning to the use of haplotype analysis as a tool in population studies, the investigation of linkage disequilibrium, and candidate gene analysis. When the phase of the data is unknown, computational methods, in particular those employing the Expectation-Maximisation (EM) algorithm, are frequently used for estimating the phase and frequency of the underlying haplotypes. These methods have proved very successful, predicting the phase-known frequencies from data for which the phase is unknown with a high degree of accuracy. Recently there has been much speculation as to the effect of unknown, or missing allelic data – a common phenomenon even with modern automated DNA analysis techniques – on the performance of EM-based methods. To this end an EM-based program, modified to accommodate missing data, has been developed, incorporating non-parametric bootstrapping for the calculation of accurate confidence intervals. RESULTS: Here we present the results of the analyses of various data sets in which randomly selected known alleles have been relabelled as missing. Remarkably, we find that the absence of up to 30% of the data in both biallelic and multiallelic data sets with moderate to strong levels of linkage disequilibrium can be tolerated. Additionally, the frequencies of haplotypes which predominate in the complete data analysis remain essentially the same after the addition of the random noise caused by missing data. CONCLUSIONS: These findings have important implications for the area of data gathering. It may be concluded that small levels of drop out in the data do not affect the overall accuracy of haplotype analysis perceptibly, and that, given recent findings on the effect of inaccurate data, ambiguous data points are best treated as unknown

Combining Clinical With Cognitive or Magnetic Resonance Imaging Data for Predicting Transition to Psychosis in Ultra High-Risk Patients:Data From the PACE 400 Cohort

Background: Multimodal modeling that combines biological and clinical data shows promise in predicting transition to psychosis in individuals who are at ultra-high risk. Individuals who transition to psychosis are known to have deficits at baseline in cognitive function and reductions in gray matter volume in multiple brain regions identified by magnetic resonance imaging.Methods: In this study, we used Cox proportional hazards regression models to assess the additive predictive value of each modality—cognition, cortical structure information, and the neuroanatomical measure of brain age gap—to a previously developed clinical model using functioning and duration of symptoms prior to service entry as predictors in the Personal Assessment and Crisis Evaluation (PACE) 400 cohort. The PACE 400 study is a well-characterized cohort of Australian youths who were identified as ultra-high risk of transitioning to psychosis using the Comprehensive Assessment of At Risk Mental States (CAARMS) and followed for up to 18 years; it contains clinical data (from N = 416 participants), cognitive data (n = 213), and magnetic resonance imaging cortical parameters extracted using FreeSurfer (n = 231).Results: The results showed that neuroimaging, brain age gap, and cognition added marginal predictive information to the previously developed clinical model (fraction of new information: neuroimaging 0%–12%, brain age gap 7%, cognition 0%–16%).Conclusions: In summary, adding a second modality to a clinical risk model predicting the onset of a psychotic disorder in the PACE 400 cohort showed little improvement in the fit of the model for long-term prediction of transition to psychosis

CA 15-3 is predictive of response and disease recurrence following treatment in locally advanced breast cancer

BACKGROUND: Primary chemotherapy (PC) is used for down-staging locally advanced breast cancer (LABC). CA 15-3 measures the protein product of the MUC1 gene and is the most widely used serum marker in breast cancer. METHODS: We retrospectively investigated the role of CA 15-3 in conjunction with other clinico-pathological variables as a predictor of response and time to disease recurrence following treatment in LABC. Pre and post primary chemotherapy serum concentrations of CA 15-3 together with other variables were reviewed and related to four outcomes following primary chemotherapy (clinical response, pathological response, time to recurrence and time to progression). Persistently elevated CA 15-3 after PC was considered as consecutively high levels above the cut off point during and after PC. RESULTS: 73 patients were included in this study. Patients received PC (AC or AC-T regimen) for locally advanced breast cancer. 54 patients underwent surgery. The median follow up was 790 days. Patients with high concentrations of CA 15-3 before PC treatment had a poor clinical (p = 0.013) and pathological (p = 0.044) response. Together with Her-2/neu expression (p = 0.009) and tumour lympho-vascular space invasion (LVI) (p = 0.001), a persistently elevated CA 15-3 post PC (p = 0.007) was an independent predictive factor of recurrence following treatment in LABC. CONCLUSION: Elevated CA 15-3 level is predictive of a poor response to chemotherapy. In addition, persistently elevated CA 15-3 levels post chemotherapy in conjunction with lympho-vascular invasion and HER2 status predict a reduced disease free survival following treatment in locally advanced breast cancer

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

GWAS Meta-Analysis of Suicide Attempt: Identification of 12 Genome-Wide Significant Loci and Implication of Genetic Risks for Specific Health Factors

Objective: Suicidal behavior is heritable and is a major cause of death worldwide. Two large-scale genome-wide association studies (GWASs) recently discovered and crossvalidated genome-wide significant (GWS) loci for suicide attempt (SA). The present study leveraged the genetic cohorts from both studies to conduct the largest GWAS metaanalysis of SA to date. Multi-ancestry and admixture-specific meta-analyses were conducted within groups of significant African, East Asian, and European ancestry admixtures. Methods: This study comprised 22 cohorts, including 43,871 SA cases and 915,025 ancestry-matched controls. Analytical methods across multi-ancestry and individual ancestry admixtures included inverse variance-weighted fixed-effects meta-analyses, followed by gene, gene-set, tissue-set, and drug-target enrichment, as well as summary-data-based Mendelian randomization with brain expression quantitative trait loci data, phenome-wide genetic correlation, and genetic causal proportion analyses. Results: Multi-ancestry and European ancestry admixture GWAS meta-analyses identified 12 risk loci at p values &lt;5×10-8. These loci were mostly intergenic and implicated DRD2, SLC6A9, FURIN, NLGN1, SOX5, PDE4B, and CACNG2. The multi-ancestry SNP-based heritability estimate of SA was 5.7% on the liability scale (SE=0.003, p=5.7×10-80). Significant brain tissue gene expression and drug set enrichment were observed. There was shared genetic variation of SA with attention deficit hyperactivity disorder, smoking, and risk tolerance after conditioning SA on both major depressive disorder and posttraumatic stress disorder. Genetic causal proportion analyses implicated shared genetic risk for specific health factors. Conclusions: This multi-ancestry analysis of suicide attempt identified several loci contributing to risk and establishes significant shared genetic covariation with clinical phenotypes. These findings provide insight into genetic factors associated with suicide attempt across ancestry admixture populations, in veteran and civilian populations, and in attempt versus death.</p

Barriers and facilitators to Hepatitis C (HCV) Screening and Treatment – A Prisoners’ Perspective

Background: Hepatitis C Virus (HCV) infection is a global epidemic with an estimated 71 million people infected worldwide. People who inject drugs (PWID) are over represented in prison populations globally and have higher levels of HCV infection than the general population. Despite increased access to primary health care while in prison, many HCV infected prisoners do not engage with screening or treatment. With recent advances in treatment regimes, HCV in now a curable and preventable disease and prisons provide an ideal opportunity to engage this hard to reach population. Aim: To identify barriers and enablers to HCV screening and treatment in prisons Methods: A qualitative study of four prisoner focus groups (n=46) conducted at two prison settings in Dublin, Ireland. Results: The following barriers to HCV screening and treatment were identified, lack of knowledge, concerns regarding confidentiality and stigma experienced and inconsistent and delayed access to prison health services. Enablers identified included; access to health care, opt-out screening at committal, peer support, and stability of prison life which removed many of the competing priorities associated with life on the outside. Unique blocks and enablers to HCV treatment reported were, fear of treatment and having a liver biopsy, the requirement to go to hospital and in-reach hepatology services and fibroscaning. Conclusion; The many barriers and enablers to HCV screening and treatment reported by Irish prisoners will inform both national and international public health HCV elimination strategies. Incarceration provides a unique opportunity to upscale HCV treatment and linkage to the community would support effectiveness

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe

Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.Peer reviewe

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms