Making difficult health decisions: a motivated decision processing model

This study introduces and evaluates a model of motivated health decision processing. In this model, threatening health decision information is thought to lead to two potentially incompatible motivations in decision makers: the desire to process information in an effortful manner, and the desire to defend against threat. The model proposes that these dual motivations lead to biased but effortful processing of decision options. The model was tested empirically by experimentally manipulating exposure to threatening information and measuring decision information processing and decision strategy selection. Participants (N = 100; age 40+) were randomly assigned to one of two groups and exposed to either threatening or non-threatening information about skin cancer. They were asked to read about and choose from five skin cancer treatments; a computerized process-tracing tool recorded their pattern of information acquisition as they perused the information. Results showed that compared to participants in the low threat condition, participants in the high threat condition were more likely to avoid information about death and to use an attribute-based decision strategy. Participants in the high threat condition and participants who used an attribute-based decision strategy were also more likely to make an accurate decision. Post hoc analyses showed that participants in the high threat condition were more likely than participants in the low threat condition to use an effective lexicographic decision strategy, and that anxiety and impulsivity moderated the relationship between condition and decision strategy. The results of this study suggest that exposure to perceived threats can lead to patients' avoidance of frightening, but important, information about treatments and to the use of heuristic decision strategies while making treatment decisions

Is the association between optimistic cardiovascular risk perceptions and lower rates of cardiovascular disease mortality explained by biomarkers of systemic inflammation or endothelial function? A case-cohort study

<p>Abstract</p> <p>Background</p> <p>More optimistic perceptions of cardiovascular disease risk are associated with substantively lower rates of cardiovascular death among men. It remains unknown whether this association represents causality (i.e. perception leads to actions/conditions that influence cardiovascular disease occurrence) or residual confounding by unmeasured factors that associate with risk perceptions and with physiological processes that promote cardiovascular disease (i.e. inflammation or endothelial dysfunction).</p> <p>Purpose</p> <p>To evaluate whether previously unmeasured biological markers of inflammation or endothelial dysregulation confound the observed association between cardiovascular disease risk perceptions and cardiovascular disease outcomes;</p> <p>Methods</p> <p>We conducted a nested case-cohort study among community-dwelling men from Southeastern New England (USA) who were interviewed between 1989 and 1990 as part of the Pawtucket Heart Health Program. We measured C-reactive protein (CRP) and Vascular Endothelial Growth Factor (VEGF) levels from stored sera for a random sample of the parent cohort (control sample, n = 127) and all cases of cardiovascular death observed through 2005 (case sample, n = 44). We evaluated potential confounding using stratified analyses and logistic regression modeling.</p> <p>Results</p> <p>Optimistic ratings of risk associated with lower odds of dying from cardiovascular causes among men (OR = 0.39, 95% CI = 0.17, 0.91). Neither CRP nor VEGF confounded these findings.</p> <p>Conclusions</p> <p>The strong cardio-protective association between optimistic ratings of cardiovascular disease risk and lower rates of cardiovascular mortality among men is not confounded by baseline biomarkers of systemic inflammation or endothelial dysfunction.</p

Characterization of highly frequent epitope-specific CD45RA(+)/CCR7(+/- )T lymphocyte responses against p53-binding domains of the human polyomavirus BK large tumor antigen in HLA-A*0201+ BKV-seropositive donors

Human polyomavirus BK (BKV) has been implicated in oncogenic transformation. Its ability to replicate is determined by the binding of its large tumor antigen (LTag) to products of tumor-suppressor genes regulating cell cycle, as specifically p53. We investigated CD8+ T immune responses to BKV LTag portions involved in p53 binding in HLA-A*0201+ BKV LTag experienced individuals. Peptides selected from either p53-binding region (LTag(351–450 )and LTag(533–626)) by current algorithms and capacity to bind HLA-A*0201 molecule were used to stimulate CD8+ T responses, as assessed by IFN-γ gene expression ex vivo and detected by cytotoxicity assays following in vitro culture. We observed epitope-specific immune responses in all HLA-A*0201+ BKV LTag experienced individuals tested. At least one epitope, LTag(579–587); LLLIWFRPV, was naturally processed in non professional antigen presenting cells and induced cytotoxic responses with CTL precursor frequencies in the order of 1/20'000. Antigen specific CD8+ T cells were only detectable in the CD45RA+ subset, in both CCR7+ and CCR7- subpopulations. These data indicate that widespread cellular immune responses against epitopes within BKV LTag-p53 binding regions exist and question their roles in immunosurveillance against tumors possibly associated with BKV infection

Exchange hazards, relational reliability, and contracts in China: The contingent role of legal enforceability

Building on institutional and transaction cost economics, this article proposes that legal enforceability increases the use of contract over relational reliability (e.g., beliefs that the other party acts in a non-opportunistic manner) to safeguard market exchanges characterized by non-trivial hazards. The results of 399 buyer-supplier exchanges in China show that: (1) when managers perceive that the legal system can protect their firm's interests, they tend to use explicit contracts rather than relational reliability to safeguard transactions involving risks (i.e., asset specificity, environmental uncertainty, and behavioral uncertainty); and (2) when managers do not perceive the legal system as credible, they are less likely to use contracts, and instead rely on relational reliability to safeguard transactions associated with specialized assets and environmental uncertainty, but not those involving behavioral uncertainty. We further find that legal enforceability does not moderate the effect of relational reliability on contracts, but does weaken the effect of contracts on relational reliability. These results endorse the importance of prior experience (e.g., relational reliability) in supporting the use of explicit contracts, and alternatively suggest that, under conditions of greater legal enforceability, the contract signals less regarding one's intention to be trustworthy but more about the efficacy of sanctions. © 2010 Academy of International Business All rights reserved.postprin

Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use

Tobacco and alcohol use are leading causes of mortality that influence risk for many complex diseases and disorders 1 . They are heritable 2,3 and etiologically related 4,5 behaviors that have been resistant to gene discovery efforts 6–11 . In sample sizes up to 1.2 million individuals, we discovered 566 genetic variants in 406 loci associated with multiple stages of tobacco use (initiation, cessation, and heaviness) as well as alcohol use, with 150 loci evidencing pleiotropic association. Smoking phenotypes were positively genetically correlated with many health conditions, whereas alcohol use was negatively correlated with these conditions, such that increased genetic risk for alcohol use is associated with lower disease risk. We report evidence for the involvement of many systems in tobacco and alcohol use, including genes involved in nicotinic, dopaminergic, and glutamatergic neurotransmission. The results provide a solid starting point to evaluate the effects of these loci in model organisms and more precise substance use measures

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Abstract Background Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Funding GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska Läkaresällskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file 32: Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services.Peer reviewedPublisher PD

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Funding Information: GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska Läkaresällskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file : Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services. Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe