Inequalities in vaccination coverage for young females whose parents are informal caregivers

The effects of caregiver strain and stress on preventive health service utilization among adult family members are well-established, but the effects of informal caregiving on children of caregivers are unknown. We aimed to assess whether inequalities in vaccination coverage (specifically human papillomavirus [HPV] and influenza) exist for females aged 9 to 17 years whose parents are informal caregivers (i.e., care providers for family members or others who are not functionally independent) compared with females whose parents are not informal caregivers. Data from the 2009 Behavioral Risk Factor Surveillance System were analyzed using Poisson regression with robust variance to estimate overall and subgroup-specific HPV and influenza vaccination prevalence ratios (PRs) and corresponding 95% confidence limits (CL) comparing females whose parents were informal caregivers with females whose parents were not informal caregivers. Our unweighted study populations comprised 1645 and 1279 females aged 9 to 17 years for the HPV and influenza vaccination analyses, respectively. Overall, both HPV and influenza vaccination coverage were lower among females whose parents were informal caregivers (HPV: PR = 0.72, 95% CL: 0.53, 0.97; Influenza: PR = 0.89, 95% CL: 0.66, 1.2). Our results suggest consistently lower HPV and influenza vaccination coverage for young females whose parents are informal caregivers. Our study provides new evidence about the potential implications of caregiving on the utilization of preventive health services among children of caregivers

Two Chromogranin A-Derived Peptides Induce Calcium Entry in Human Neutrophils by Calmodulin-Regulated Calcium Independent Phospholipase A2

Background: Antimicrobial peptides derived from the natural processing of chromogranin A (CgA) are co-secreted with catecholamines upon stimulation of chromaffin cells. Since PMNs play a central role in innate immunity, we examine responses by PMNs following stimulation by two antimicrobial CgA-derived peptides. Methodology/Principal Findings: PMNs were treated with different concentrations of CgA-derived peptides in presence of several drugs. Calcium mobilization was observed by using flow cytometry and calcium imaging experiments. Immunocytochemistry and confocal microscopy have shown the intracellular localization of the peptides. The calmodulin-binding and iPLA2 activating properties of the peptides were shown by Surface Plasmon Resonance and iPLA2 activity assays. Finally, a proteomic analysis of the material released after PMNs treatment with CgA-derived peptides was performed by using HPLC and Nano-LC MS-MS. By using flow cytometry we first observed that after 15 s, in presence of extracellular calcium, Chromofungin (CHR) or Catestatin (CAT) induce a concentration-dependent transient increase of intracellular calcium. In contrast, in absence of extra cellular calcium the peptides are unable to induce calcium depletion from the stores after 10 minutes exposure. Treatment with 2-APB (2-aminoethoxydiphenyl borate), a store operated channels (SOCs) blocker, inhibits completely the calcium entry, as shown by calcium imaging. We also showed that they activate iPLA2 as the two CaM-binding factors (W7 and CMZ) and that the two sequences can be aligned with the two CaMbinding domains reported for iPLA2. We finally analyzed by HPLC and Nano-LC MS-MS the material released by PMNs following stimulation by CHR and CAT. We characterized several factors important for inflammation and innate immunity. Conclusions/Significance: For the first time, we demonstrate that CHR and CAT, penetrate into PMNs, inducing extracellular calcium entry by a CaM-regulated iPLA2 pathway. Our study highlights the role of two CgA-derived peptides in the active communication between neuroendocrine and immune systems

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

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

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

Progress on human papillomavirus (HPV) infection and cervical cancer prevention in sub-Saharan Africa: Highlights of the 27th International Papillomavirus Conference in Berlin, 17–22 September 2011

Highlights of the International Papillomavirus Conference in Berlin, 17–22 September 2011

Younger age distribution of cervical cancer incidence among survivors of pediatric and young adult cancers

Background Pediatric and young adult (PAYA) cancer survivors may have an earlier onset of chronic diseases compared with the general population. We compared the age at cervical cancer diagnosis between PAYA cancer survivors and females in the general US population. Methods We used longitudinal data from 9 population-based registries of the Surveillance, Epidemiology, and End Results program collected between 1973 and 2010. PAYA cancer survivors were females diagnosed with any cancer before age 30 years, survived at least 5 years post-diagnosis, and were subsequently diagnosed with invasive cervical cancer (n = 46). The general US population comprised females who were diagnosed with invasive cervical cancer as the primary malignancy (n = 26,956). We estimated the difference in median age at diagnosis (ß50) and bootstrap 95% confidence limits (CL) of invasive cervical cancer after adjustment for year of diagnosis and race. Results The median age at diagnosis of invasive cervical cancer was 33 years for female PAYA cancer survivors and 40 years for females in the general US population (ß50 = - 7.0, 95% CL: - 11, - 3.2). Similar differences were observed across subgroups of stage and histologic subtype of invasive cervical cancer. Conclusion Our results suggest that PAYA cancer survivors are diagnosed with invasive cervical cancer at a substantially younger age compared with females without a prior cancer diagnosis in the general US population. This issue warrants further study, and could have implications for determining age at initiation or frequency of cervical cancer screening if younger age at diagnosis is attributable to an underlying biological phenomenon. © 2014 Elsevier Inc