The First Anniversary: Stress, Well-Being, and Optimism in Older Widows

The first anniversary for older widows (n = 47) has been explored during Months 11, 12, and 13. Concurrent correlations show that optimism inversely correlates with psychological (intrusion and avoidance) stress as measured with the Impact of Event Scale (r = —.52 to —.66, p \u3c .005) and positively correlates with well-being (physical: r = .36 to .46, p \u3c .025; psychosocial: r = .58 to .72, p \u3c .005; spiritual: r = .50 to .69, p \u3c .005). Lagged correlation patterns suggest that higher levels of optimism at a given time are associated with higher life satisfaction and spiritual well-being at later times. Psychological stress is higher at Month 12 when compared to Month 13, t(43) = 2.54, p = .01, but not when compared to Month 11, t(43) = 1.49, p \u3e .10. There are no significant differences in physiologic stress (salivary cortisol) or well-being during the first anniversary of spousal bereavement

A Systematic Review of Genetic Influence on Psychological Resilience

When exposed to adversity, some individuals are at an increased risk of posttraumatic stress disorder, experiencing persistent biopsychosocial disturbances, whereas others adapt well, described as resilience. Resilience is a complex biopsychosocial phenomenon conceptualized as adaptation to adversity influenced by an individual’s genetic variants, epistasis, epigenetics, and gene-by-environment interactions. Studies on psychological resilience have focused on behavioral and psychosocial variables with far less examination of the genetic contributions. The purpose of this review is to identify specific genetic variants contributing to the biological capacity for psychological resilience. PubMed and PsycINFO were searched using the following key words: psychological resilience AND genotype(s). Additional articles were identified from the Human Genome Epidemiology Navigator using the term resilience, psychological. Ten studies met the criteria. Six genes were empirically associated with psychological resilience: serotonin-transporter-linked polymorphic region (5-HTTLPR), dopamine receptor D4, brain-derived neurotrophic factor (BDNF), corticotropin-releasing hormone receptor 1, oxytocin receptor and regulator of G-protein signaling 2. The findings of this systematic review suggest that the L/L or L′/L′ genotype of 5-HTTLPR and rs25531 in children/adolescents and the S/S or S′/S′ genotype in adults are most frequently related to resilience. Additionally, the Val/Val genotype of rs6265 in BDNF in Caucasians was also associated with resilience. There are numerous factors contributing to the complexity of determining the genetic influence on resilience including analysis of rs25531, assumptions of the mode of inheritance, operationalization of resilience, demographic and population characteristics, sample size, and other types of genetic influence including epistasis and epigenetics. While current evidence is supportive, further investigation of the genetic influence on resilience is required

Ultra-Efficient PrPSc Amplification Highlights Potentialities and Pitfalls of PMCA Technology

In order to investigate the potential of voles to reproduce in vitro the efficiency of prion replication previously observed in vivo, we seeded protein misfolding cyclic amplification (PMCA) reactions with either rodent-adapted Transmissible Spongiform Encephalopathy (TSE) strains or natural TSE isolates. Vole brain homogenates were shown to be a powerful substrate for both homologous or heterologous PMCA, sustaining the efficient amplification of prions from all the prion sources tested. However, after a few serial automated PMCA (saPMCA) rounds, we also observed the appearance of PK-resistant PrPSc in samples containing exclusively unseeded substrate (negative controls), suggesting the possible spontaneous generation of infectious prions during PMCA reactions. As we could not definitively rule out cross-contamination through a posteriori biochemical and biological analyses of de novo generated prions, we decided to replicate the experiments in a different laboratory. Under rigorous prion-free conditions, we did not observe de novo appearance of PrPSc in unseeded samples of M109M and I109I vole substrates, even after many consecutive rounds of saPMCA and working in different PMCA settings. Furthermore, when positive and negative samples were processed together, the appearance of spurious PrPSc in unseeded negative controls suggested that the most likely explanation for the appearance of de novo PrPSc was the occurrence of cross-contamination during saPMCA. Careful analysis of the PMCA process allowed us to identify critical points which are potentially responsible for contamination events. Appropriate technical improvements made it possible to overcome PMCA pitfalls, allowing PrPSc to be reliably amplified up to extremely low dilutions of infected brain homogenate without any false positive results even after many consecutive rounds. Our findings underline the potential drawback of ultrasensitive in vitro prion replication and warn on cautious interpretation when assessing the spontaneous appearance of prions in vitro

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)

Large-scale genome-wide analysis identifies genetic variants associated with cardiac structure and function

BACKGROUND: Understanding the genetic architecture of cardiac structure and function may help to prevent and treat heart disease. This investigation sought to identify common genetic variations associated with inter-individual variability in cardiac structure and function. METHODS: A GWAS meta-analysis of echocardiographic traits was performed, including 46,533 individuals from 30 studies (EchoGen consortium). The analysis included 16 traits of left ventricular (LV) structure, and systolic and diastolic function. RESULTS: The discovery analysis included 21 cohorts for structural and systolic function traits (n = 32,212) and 17 cohorts for diastolic function traits (n = 21,852). Replication was performed in 5 cohorts (n = 14,321) and 6 cohorts (n = 16,308), respectively. Besides 5 previously reported loci, the combined meta-analysis identified 10 additional genome-wide significant SNPs: rs12541595 near MTSS1 and rs10774625 in ATXN2 for LV end-diastolic internal dimension; rs806322 near KCNRG, rs4765663 in CACNA1C, rs6702619 near PALMD, rs7127129 in TMEM16A, rs11207426 near FGGY, rs17608766 in GOSR2, and rs17696696 in CFDP1 for aortic root diameter; and rs12440869 in IQCH for Doppler transmitral A-wave peak velocity. Findings were in part validated in other cohorts and in GWAS of related disease traits. The genetic loci showed associations with putative signaling pathways, and with gene expression in whole blood, monocytes, and myocardial tissue. CONCLUSION: The additional genetic loci identified in this large meta-analysis of cardiac structure and function provide insights into the underlying genetic architecture of cardiac structure and warrant follow-up in future functional studies. FUNDING: For detailed information per study, see Acknowledgments.This work was supported by a grant from the US National Heart, Lung, and Blood Institute (N01-HL-25195; R01HL 093328 to RSV), a MAIFOR grant from the University Medical Center Mainz, Germany (to PSW), the Center for Translational Vascular Biology (CTVB) of the Johannes Gutenberg-University of Mainz, and the Federal Ministry of Research and Education, Germany (BMBF 01EO1003 to PSW). This work was also supported by the research project Greifswald Approach to Individualized Medicine (GANI_MED). GANI_MED was funded by the Federal Ministry of Education and Research and the Ministry of Cultural Affairs of the Federal State of Mecklenburg, West Pomerania (contract 03IS2061A). We thank all study participants, and the colleagues and coworkers from all cohorts and sites who were involved in the generation of data or in the analysis. We especially thank Andrew Johnson (FHS) for generation of the gene annotation database used for analysis. We thank the German Center for Cardiovascular Research (DZHK e.V.) for supporting the analysis and publication of this project. RSV is a member of the Scientific Advisory Board of the DZHK. Data on CAD and MI were contributed by CARDIoGRAMplusC4D investigators. See Supplemental Acknowledgments for consortium details. PSW, JFF, AS, AT, TZ, RSV, and MD had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis

A Systematic Review of Genetic Influence on Psychological Resilience

When exposed to adversity, some individuals are at an increased risk of posttraumatic stress disorder, experiencing persistent biopsychosocial disturbances, whereas others adapt well, described as resilience. Resilience is a complex biopsychosocial phenomenon conceptualized as adaptation to adversity influenced by an individual’s genetic variants, epistasis, epigenetics, and gene-by-environment interactions. Studies on psychological resilience have focused on behavioral and psychosocial variables with far less examination of the genetic contributions. The purpose of this review is to identify specific genetic variants contributing to the biological capacity for psychological resilience. PubMed and PsycINFO were searched using the following key words: psychological resilience AND genotype(s). Additional articles were identified from the Human Genome Epidemiology Navigator using the term resilience, psychological. Ten studies met the criteria. Six genes were empirically associated with psychological resilience: serotonin-transporter-linked polymorphic region (5-HTTLPR), dopamine receptor D4, brain-derived neurotrophic factor (BDNF), corticotropin-releasing hormone receptor 1, oxytocin receptor and regulator of G-protein signaling 2. The findings of this systematic review suggest that the L/L or L′/L′ genotype of 5-HTTLPR and rs25531 in children/adolescents and the S/S or S′/S′ genotype in adults are most frequently related to resilience. Additionally, the Val/Val genotype of rs6265 in BDNF in Caucasians was also associated with resilience. There are numerous factors contributing to the complexity of determining the genetic influence on resilience including analysis of rs25531, assumptions of the mode of inheritance, operationalization of resilience, demographic and population characteristics, sample size, and other types of genetic influence including epistasis and epigenetics. While current evidence is supportive, further investigation of the genetic influence on resilience is required

A Concept Analysis of Resilience Integrating Genetics

Although clinicians and researchers are interested in the phenomenon of resilience, there is no agreed-upon definition of resilience. Scientific evidence suggests that resilience is influenced by intrapersonal (e.g., personality traits) and environmental (e.g., social support) variables. A concept analysis was conducted to better understand the meaning of resilience. In this analysis, the antecedent of resilience was a potentially traumatic event; the defining attributes were ego-resiliency, emotion regulation, social support, and heredity; and the consequences were none to mild psychopathological symptoms and positive adaptation. This analysis can help nurses better understand resilience and its relationships to both intrapersonal and environmental variables