Loneliness and Deprivation: The Case of Roman Catholic Priests

Using Roman Catholic Priests as a test in order to control for deprivation in relationships of intimacy while maximizing the need for social network relationships, an examination was made of their differential experience of loneliness. The evidence suggested repeatedly that priests were more likely to experience loneliness as a serious problem when they perceived that the social network which they regarded as most significant in their lives (the Church) placed some kind of structural limitation on the extent of their involvement in it. Factors, for example, which help determine the individual priest\u27s place in the structure of the Church are: type of assignment, length of time ordained, and degree of integration into the network through mutual commitment; all of these factors correlate significantly with the experience of loneliness. For priests experiencing serious loneliness, there were further significant correlations with a perceived deficit in intimacy, an expressed need for sexual intimacy, a desire to marry, and more frequent dating behavior. While causal sequences could not be established with certainty, the use of Guttman scaling techniques and a logical ordering of the variables suggests strongly that an emotional response (in this case an exaggerated search for intimate relationships) may have been triggered by social deprivation (network exclusion) rather than by an emotional deprivation (in intimacy) as might have been expected. Such a possibility has far-reaching implications and calls for further research. If an exaggerated search for intimate relationships can be triggered by social network deprivation, that might shed light on a variety of other phenomena such as promiscuity and rape, especially in urban, industrialized societies whose character is such that secondary relationehips become more pervasive and achieve such great importance in the minds and daily lives of the people

Genome-Wide Association with Select Biomarker Traits in the Framingham Heart Study

BACKGROUND: Systemic biomarkers provide insights into disease pathogenesis, diagnosis, and risk stratification. Many systemic biomarker concentrations are heritable phenotypes. Genome-wide association studies (GWAS) provide mechanisms to investigate the genetic contributions to biomarker variability unconstrained by current knowledge of physiological relations. METHODS: We examined the association of Affymetrix 100K GeneChip single nucleotide polymorphisms (SNPs) to 22 systemic biomarker concentrations in 4 biological domains: inflammation/oxidative stress; natriuretic peptides; liver function; and vitamins. Related members of the Framingham Offspring cohort (n = 1012; mean age 59 ± 10 years, 51% women) had both phenotype and genotype data (minimum-maximum per phenotype n = 507–1008). We used Generalized Estimating Equations (GEE), Family Based Association Tests (FBAT) and variance components linkage to relate SNPs to multivariable-adjusted biomarker residuals. Autosomal SNPs (n = 70,987) meeting the following criteria were studied: minor allele frequency ≥ 10%, call rate ≥ 80% and Hardy-Weinberg equilibrium p ≥ 0.001. RESULTS: With GEE, 58 SNPs had p < 10-6: the top SNPs were rs2494250 (p = 1.00*10-14) and rs4128725 (p = 3.68*10-12) for monocyte chemoattractant protein-1 (MCP1), and rs2794520 (p = 2.83*10-8) and rs2808629 (p = 3.19*10-8) for C-reactive protein (CRP) averaged from 3 examinations (over about 20 years). With FBAT, 11 SNPs had p < 10-6: the top SNPs were the same for MCP1 (rs4128725, p = 3.28*10-8, and rs2494250, p = 3.55*10-8), and also included B-type natriuretic peptide (rs437021, p = 1.01*10-6) and Vitamin K percent undercarboxylated osteocalcin (rs2052028, p = 1.07*10-6). The peak LOD (logarithm of the odds) scores were for MCP1 (4.38, chromosome 1) and CRP (3.28, chromosome 1; previously described) concentrations; of note the 1.5 support interval included the MCP1 and CRP SNPs reported above (GEE model). Previous candidate SNP associations with circulating CRP concentrations were replicated at p < 0.05; the SNPs rs2794520 and rs2808629 are in linkage disequilibrium with previously reported SNPs. GEE, FBAT and linkage results are posted at . CONCLUSION: The Framingham GWAS represents a resource to describe potentially novel genetic influences on systemic biomarker variability. The newly described associations will need to be replicated in other studies.National Heart, Lung, and Blood Institute's Framingham Heart Study (N01-HC25195); National Institutes of Health National Center for Research Resources Shared Instrumentation grant (1S10RR163736-01A1); National Institutes of Health (HL064753, HL076784, AG028321, HL71039, 2 K24HL04334, 1K23 HL083102); Doris Duke Charitable Foundation; American Diabetes Association Career Developement Award; National Center for Research Resources (GCRC M01-RR01066); US Department of Agriculture Agricultural Research Service (58-1950-001, 58-1950-401); National Institute of Aging (AG14759

De novo assembly of the cattle reference genome with single-molecule sequencing.

BackgroundMajor advances in selection progress for cattle have been made following the introduction of genomic tools over the past 10-12 years. These tools depend upon the Bos taurus reference genome (UMD3.1.1), which was created using now-outdated technologies and is hindered by a variety of deficiencies and inaccuracies.ResultsWe present the new reference genome for cattle, ARS-UCD1.2, based on the same animal as the original to facilitate transfer and interpretation of results obtained from the earlier version, but applying a combination of modern technologies in a de novo assembly to increase continuity, accuracy, and completeness. The assembly includes 2.7 Gb and is &gt;250× more continuous than the original assembly, with contig N50 &gt;25 Mb and L50 of 32. We also greatly expanded supporting RNA-based data for annotation that identifies 30,396 total genes (21,039 protein coding). The new reference assembly is accessible in annotated form for public use.ConclusionsWe demonstrate that improved continuity of assembled sequence warrants the adoption of ARS-UCD1.2 as the new cattle reference genome and that increased assembly accuracy will benefit future research on this species

Breast Cancer Index is a predictive biomarker of treatment benefit and outcome from extended tamoxifen therapy: final analysis of the Trans-aTTom study

PURPOSE: The Breast Cancer Index (BCI) HOXB13/IL17BR (H/I) ratio predicts benefit from extended endocrine therapy in hormone receptor–positive (HR(+)) early-stage breast cancer. Here, we report the final analysis of the Trans-aTTom study examining BCI (H/I)'s predictive performance. EXPERIMENTAL DESIGN: BCI results were available for 2,445 aTTom trial patients. The primary endpoint of recurrence-free interval (RFI) and secondary endpoints of disease-free interval (DFI) and disease-free survival (DFS) were examined using Cox proportional hazards regression and log-rank test. RESULTS: Final analysis of the overall study population (N = 2,445) did not show a significant improvement in RFI with extended tamoxifen [HR, 0.90; 95% confidence interval (CI), 0.69–1.16; P = 0.401]. Both the overall study population and N0 group were underpowered due to the low event rate in the N0 group. In a pre-planned analysis of the N(+) subset (N = 789), BCI (H/I)-High patients derived significant benefit from extended tamoxifen (9.7% absolute benefit: HR, 0.33; 95% CI, 0.14–0.75; P = 0.016), whereas BCI (H/I)-Low patients did not (−1.2% absolute benefit; HR, 1.11; 95% CI, 0.76–1.64; P = 0.581). A significant treatment-to-biomarker interaction was demonstrated on the basis of RFI, DFI, and DFS (P = 0.037, 0.040, and 0.025, respectively). BCI (H/I)-High patients remained predictive of benefit from extended tamoxifen in the N(+)/HER2(−) subgroup (9.4% absolute benefit: HR, 0.35; 95% CI, 0.15–0.81; P = 0.047). A three-way interaction evaluating BCI (H/I), treatment, and HER2 status was not statistically significant (P = 0.849). CONCLUSIONS: Novel findings demonstrate that BCI (H/I) significantly predicts benefit from extended tamoxifen in HR(+) N(+) patients with HER2(−) disease. Moreover, BCI (H/I) demonstrates significant treatment to biomarker interaction across survival outcomes

Atherosclerotic Biomarkers and Aortic Atherosclerosis by Cardiovascular Magnetic Resonance Imaging in the Framingham Heart Study

Background: The relations between subclinical atherosclerosis and inflammatory biomarkers have generated intense interest but their significance remains unclear. We sought to determine the association between a panel of biomarkers and subclinical aortic atherosclerosis in a community‐based cohort. Methods and Results: We evaluated 1547 participants of the Framingham Heart Study Offspring cohort who attended the 7th examination cycle and underwent both cardiovascular magnetic resonance imaging (CMR) and assays for 10 biomarkers associated with atherosclerosis: high‐sensitivity C‐reactive protein, fibrinogen, intercellular adhesion molecule‐1, interleukin‐6, interleukin‐18, lipoprotein‐associated phospholipase‐A2 activity and mass, monocyte chemoattractant protein‐1, P‐selectin, and tumor necrosis factor receptor‐2. In logistic regression analysis, we found no significant association between the biomarker panel and the presence of aortic plaque (global P=0.53). Using Tobit regression with aortic plaque as a continuous variable, we noted a modest association between biomarker panel and aortic plaque volume in age‐ and sex‐adjusted analyses (P=0.003). However, this association was attenuated after further adjustment for clinical covariates (P=0.09). Conclusions: In our community‐based cohort, we found no significant association between our multibiomarker panel and aortic plaque. Our results underscore the strengths and limitations of the use of biomarkers for the identification of subclinical atherosclerosis and the importance of traditional risk factors

An assessment of population structure in eight breeds of cattle using a whole genome SNP panel

<p>Abstract</p> <p>Background</p> <p>Analyses of population structure and breed diversity have provided insight into the origin and evolution of cattle. Previously, these studies have used a low density of microsatellite markers, however, with the large number of single nucleotide polymorphism markers that are now available, it is possible to perform genome wide population genetic analyses in cattle. In this study, we used a high-density panel of SNP markers to examine population structure and diversity among eight cattle breeds sampled from <it>Bos indicus </it>and <it>Bos taurus</it>.</p> <p>Results</p> <p>Two thousand six hundred and forty one single nucleotide polymorphisms (SNPs) spanning all of the bovine autosomal genome were genotyped in Angus, Brahman, Charolais, Dutch Black and White Dairy, Holstein, Japanese Black, Limousin and Nelore cattle. Population structure was examined using the linkage model in the program STRUCTURE and Fst estimates were used to construct a neighbor-joining tree to represent the phylogenetic relationship among these breeds.</p> <p>Conclusion</p> <p>The whole-genome SNP panel identified several levels of population substructure in the set of examined cattle breeds. The greatest level of genetic differentiation was detected between the <it>Bos taurus </it>and <it>Bos indicus </it>breeds. When the <it>Bos indicus </it>breeds were excluded from the analysis, genetic differences among beef versus dairy and European versus Asian breeds were detected among the <it>Bos taurus </it>breeds. Exploration of the number of SNP loci required to differentiate between breeds showed that for 100 SNP loci, individuals could only be correctly clustered into breeds 50% of the time, thus a large number of SNP markers are required to replace the 30 microsatellite markers that are currently commonly used in genetic diversity studies.</p

Whole genome linkage disequilibrium maps in cattle

<p>Abstract</p> <p>Background</p> <p>Bovine whole genome linkage disequilibrium maps were constructed for eight breeds of cattle. These data provide fundamental information concerning bovine genome organization which will allow the design of studies to associate genetic variation with economically important traits and also provides background information concerning the extent of long range linkage disequilibrium in cattle.</p> <p>Results</p> <p>Linkage disequilibrium was assessed using r²among all pairs of syntenic markers within eight breeds of cattle from the <it>Bos taurus </it>and <it>Bos indicus </it>subspecies. <it>Bos taurus </it>breeds included Angus, Charolais, Dutch Black and White Dairy, Holstein, Japanese Black and Limousin while <it>Bos indicus </it>breeds included Brahman and Nelore. Approximately 2670 markers spanning the entire bovine autosomal genome were used to estimate pairwise r²values. We found that the extent of linkage disequilibrium is no more than 0.5 Mb in these eight breeds of cattle.</p> <p>Conclusion</p> <p>Linkage disequilibrium in cattle has previously been reported to extend several tens of centimorgans. Our results, based on a much larger sample of marker loci and across eight breeds of cattle indicate that in cattle linkage disequilibrium persists over much more limited distances. Our findings suggest that 30,000–50,000 loci will be needed to conduct whole genome association studies in cattle.</p

Comparison of Bayesian models to estimate direct genomic values in multi-breed commercial beef cattle

Background: While several studies have examined the accuracy of direct genomic breeding values (DGV) within and across purebred cattle populations, the accuracy of DGV in crossbred or multi-breed cattle populations has been less well examined. Interest in the use of genomic tools for both selection and management has increased within the hybrid seedstock and commercial cattle sectors and research is needed to determine their efficacy. We predicted DGV for six traits using training populations of various sizes and alternative Bayesian models for a population of 3240 crossbred animals. Our objective was to compare alternate models with different assumptions regarding the distributions of single nucleotide polymorphism (SNP) effects to determine the optimal model for enhancing feasibility of multi-breed DGV prediction for the commercial beef industry.Results: Realized accuracies ranged from 0.40 to 0.78. Randomly assigning 60 to 70% of animals to training (n is about 2000 records) yielded DGV accuracies with the smallest coefficients of variation. Mixture models (BayesB95, BayesC[pi]) and models that allow SNP effects to be sampled from distributions with unequal variances (BayesA, BayesB95) were advantageous for traits that appear or are known to be influenced by large-effect genes. For other traits, models differed little in prediction accuracy (~0.3 to 0.6%), suggesting that they are mainly controlled by small-effect loci.Conclusions: The proportion (60 to 70%) of data allocated to training that optimized DGV accuracy and minimized the coefficient of variation of accuracy was similar to large dairy populations. Larger effects were estimated for some SNPs using BayesA and BayesB95 models because they allow unequal SNP variances. This substantially increased DGV accuracy for Warner-Bratzler Shear Force, for which large-effect quantitative trait loci (QTL) are known, while no loss in accuracy was observed for traits that appear to follow the infinitesimal model. Large decreases in accuracy (up to 0.07) occurred when SNPs that presumably tag large-effect QTL were over-regressed towards the mean in BayesC0 analyses. The DGV accuracies achieved here indicate that genomic selection has predictive utility in the commercial beef industry and that using models that reflect the genomic architecture of the trait can have predictive advantages in multi-breed populations.Peer reviewedAnimal Scienc

Power poses – where do we stand?

<p>Dynamic results for Scenario 2.</p