Comparison of Skin Biomechanics and Skin Color in Puerto Rican and Non-Puerto Rican Women

Objective: Skin biomechanics are physical properties that protect the body from injury. Little is known about differences in skin biomechanics in racial/ethnic groups and the role of skin color in these differences. The purpose of this study was to determine the relationship between skin biomechanics (viscoelasticity, hydration) and skin color, when controlling for demographic and health-related variables in a sample of Puerto Rican and non-Puerto Rican women. Methods: We performed a secondary analysis of data from 545 women in a longitudinal, observational study of skin injury in Puerto Rico and the United States. Data included measures of skin viscoelasticity, skin hydration, skin color, demographic, and health-related variables. Skin color was measured by spectrophotometry (L* - lightness/darkness, a*- redness/greenness, b* - yellowness/blueness). The sample was 12.5% Puerto Rican, 27.3% non-Puerto Rican Latina, 28.8% Black, 28.6% White, and 2.8% Other. Results: Regression analyses showed that: 1) higher levels of skin viscoelasticity were associated with lower age, higher BMI, and identifying as non-Puerto Rican Latina as compared to Puerto Rican; (all p \u3c .001); and 2) higher levels of hydration were associated with lower L* values, higher health status, lower BMI, and identifying as non-Puerto Rican Latina, White, or Other as compared to Puerto Rican (all p \u3c .05). Conclusion: When adjusting for skin color, Puerto Rican women had lower viscoelasticity and hydration as compared to other groups. Puerto Rican women may be at long-term risk for skin alterations, including pressure injury, as they age or become chronically ill

Genome-wide analyses identify a role for SLC17A4 and AADAT in thyroid hormone regulation.

Thyroid dysfunction is an important public health problem, which affects 10% of the general population and increases the risk of cardiovascular morbidity and mortality. Many aspects of thyroid hormone regulation have only partly been elucidated, including its transport, metabolism, and genetic determinants. Here we report a large meta-analysis of genome-wide association studies for thyroid function and dysfunction, testing 8 million genetic variants in up to 72,167 individuals. One-hundred-and-nine independent genetic variants are associated with these traits. A genetic risk score, calculated to assess their combined effects on clinical end points, shows significant associations with increased risk of both overt (Graves' disease) and subclinical thyroid disease, as well as clinical complications. By functional follow-up on selected signals, we identify a novel thyroid hormone transporter (SLC17A4) and a metabolizing enzyme (AADAT). Together, these results provide new knowledge about thyroid hormone physiology and disease, opening new possibilities for therapeutic targets

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

Promiscuous antibodies characterised by their physico-chemical properties:From sequence to structure and back

AbstractHuman B cells produce antibodies, which bind to their cognate antigen based on distinct molecular properties of the antibody CDR loop. We have analysed a set of 10 antibodies showing a clear difference in their binding properties to a panel of antigens, resulting in two subsets of antibodies with a distinct binding phenotype. We call the observed binding multiplicity ‘promiscuous’ and selected physico-chemical CDRH3 characteristics and conformational preferences may characterise these promiscuous antibodies. To classify CDRH3 physico-chemical properties playing a role in their binding properties, we used statistical analyses of the sequences annotated by Kidera factors. To characterise structure-function requirements for antigen binding multiplicity we employed Molecular Modelling and Monte Carlo based coarse-grained simulations. The ability to predict the molecular causes of promiscuous, multi-binding behaviour would greatly improve the efficiency of the therapeutic antibody discovery process