Physical Activity Levels, Correlates, and All-Cause Mortality Risk in People Living With Different Health Conditions.

BACKGROUND: To better understand physical activity behavior and its health benefits in people living with health conditions, we studied people with and without 20 different self-reported health conditions with regard to (1) their physical activity levels, (2) factors correlated with these physical activity levels, and (3) the association between physical activity and all-cause mortality. METHODS: We used a subsample (n = 88,659) of the Lifelines cohort study from the Netherlands. For people living with and without 20 different self-reported health conditions, we studied the aforementioned factors in relation to physical activity. Physical activity was assessed with the Short Questionnaire to Assess Health-Enhancing Physical Activity Questionnaire, and mortality data were obtained from the Dutch death register. RESULTS: People with a reported health condition were less likely to meet physical activity guidelines than people without a reported health condition (odds ratios ranging from 0.55 to 0.89). Higher body mass index and sitting time, and lower self-rated health, physical functioning, and education levels were associated with lower odds of meeting physical activity guidelines across most health conditions. Finally, we found a protective association between physical activity and all-cause mortality in both people living with and without different health conditions. CONCLUSION: People living with different health conditions are generally less physically active compared with people living without a health condition. Both people living with and without self-reported health conditions share a number of key factors associated with physical activity levels. We also observed the expected protective association between physical activity and all-cause mortality.

Socioeconomic Inequalities in Type 2 Diabetes: Mediation Through Status Anxiety?

Objectives: While status anxiety has received attention as a potential mechanism generating health inequalities, empirical evidence is still limited. Studies have been ecological and have largely focused on mental and not physical health outcomes. Methods: We conducted individual-level analyses to assess status anxiety (feelings of inferiority resulting from social comparisons) and resources (financial difficulties) as mediators of the relationship between socioeconomic status (SES) (education/occupation/employment status) and type 2 diabetes (T2D). We used cross-sectional data of 21,150 participants (aged 18-70 years) from the Amsterdam-based HELIUS study. We estimated associations using logistic regression models and estimated mediated proportions using natural effect modelling. Results: Odds of status anxiety were higher among participants with a low SES [e.g., OR = 2.66 (95% CI: 2.06-3.45) for elementary versus academic occupation]. Odds of T2D were 1.49 (95% CI: 1.12-1.97) times higher among participants experiencing status anxiety. Proportion of the SES-T2D relationship mediated was 3.2% (95% CI: 1.5%-7.0%) through status anxiety and 10.9% (95% CI: 6.6%-18.0%) through financial difficulties. Conclusion: Status anxiety and financial difficulties played small but consistent mediating roles. These individual-level analyses underline status anxiety's importance and imply that status anxiety requires attention in efforts to reduce health inequalities.

Improved multimodal prediction of progression from MCI to Alzheimer's disease combining genetics with quantitative brain MRI and cognitive measures.

INTRODUCTION: There is a pressing need for non-invasive, cost-effective tools for early detection of Alzheimer's disease (AD). METHODS: Using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), Cox proportional models were conducted to develop a multimodal hazard score (MHS) combining age, a polygenic hazard score (PHS), brain atrophy, and memory to predict conversion from mild cognitive impairment (MCI) to dementia. Power calculations estimated required clinical trial sample sizes after hypothetical enrichment using the MHS. Cox regression determined predicted age of onset for AD pathology from the PHS. RESULTS: The MHS predicted conversion from MCI to dementia (hazard ratio for 80th versus 20th percentile: 27.03). Models suggest that application of the MHS could reduce clinical trial sample sizes by 67%. The PHS alone predicted age of onset of amyloid and tau. DISCUSSION: The MHS may improve early detection of AD for use in memory clinics or for clinical trial enrichment. HIGHLIGHTS: A multimodal hazard score (MHS) combined age, genetics, brain atrophy, and memory. The MHS predicted time to conversion from mild cognitive impairment to dementia. MHS reduced hypothetical Alzheimer's disease (AD) clinical trial sample sizes by 67%. A polygenic hazard score predicted age of onset of AD neuropathology.

Cardiovascular Risk Estimation Based on Country-of-Birth- and Country-of-Residence-Specific Scores among Migrants in the Netherlands: The HELIUS Study.

BACKGROUND: Regional and country-specific cardiovascular risk algorithms have been developed to improve CVD risk prediction. But it is unclear whether migrants' country-of-residence or country-of-birth algorithms agree in stratifying the CVD risk of these populations. We evaluated the risk stratification by the different algorithms, by comparing migrant country-of-residence-specific scores to migrant country-of-birth-specific scores for ethnic minority populations in the Netherlands. METHOD: data from the HELIUS study was used in estimating the CVD risk scores for participants using five laboratory-based (Framingham, Globorisk, Pool Cohort Equation II, SCORE II, and WHO II) and three nonlaboratory-based (Framingham, Globorisk, and WHO II) risk scores with the risk chart for the Netherlands. For the Globorisk, WHO II, and SCORE II risk scores, we also computed the risk scores using risk charts specified for the migrant home country. Risk categorization was first done according to the specification of the risk algorithm and then simplified to low (green), moderate (yellow and orange), and high risk (red). RESULTS: we observed differences in risk categorization for different risk algorithms ranging from 0% (Globorisk) to 13% (Framingham) for the high-risk category, as well as differences in the country-of-residence- and country-of-birth-specific scores. Agreement between different scores ranged from none to moderate. We observed a moderate agreement between the Netherlands-specific SCORE II and the country-of-birth SCORE II for the Turkish and a nonagreement for the Dutch Moroccan population. CONCLUSION: disparities exist in the use of the country-of-residence-specific, as compared to the country-of-birth, risk algorithms among ethnic minorities living in the Netherlands. Hence, there is a need for further validation of country-of-residence- and country-of-birth-adjusted scores to ascertain appropriateness and reliability.

Using Polygenic Hazard Scores to Predict Age at Onset of Alzheimer's Disease in Nordic Populations.

BACKGROUND: Polygenic hazard scores (PHS) estimate age-dependent genetic risk of late-onset Alzheimer's disease (AD), but there is limited information about the performance of PHS on real-world data where the population of interest differs from the model development population and part of the model genotypes are missing or need to be imputed. OBJECTIVE: The aim of this study was to estimate age-dependent risk of late-onset AD using polygenic predictors in Nordic populations. METHODS: We used Desikan PHS model, based on Cox proportional hazards assumption, to obtain age-dependent hazard scores for AD from individual genotypes in the Norwegian DemGene cohort (n = 2,772). We assessed the risk discrimination and calibration of Desikan model and extended it by adding new genotype markers (the Desikan Nordic model). Finally, we evaluated both Desikan and Desikan Nordic models in two independent Danish cohorts: The Copenhagen City Heart Study (CCHS) cohort (n = 7,643) and The Copenhagen General Population Study (CGPS) cohort (n = 10,886). RESULTS: We showed a robust prediction efficiency of Desikan model in stratifying AD risk groups in Nordic populations, even when some of the model SNPs were missing or imputed. We attempted to improve Desikan PHS model by adding new SNPs to it, but we still achieved similar risk discrimination and calibration with the extended model. CONCLUSION: PHS modeling has the potential to guide the timing of treatment initiation based on individual risk profiles and can help enrich clinical trials with people at high risk to AD in Nordic populations.

Diphtheria And Tetanus Vaccination History Is Associated With Lower Odds of COVID-19 Hospitalization.

Background: COVID-19 is characterized by strikingly large, mostly unexplained, interindividual variation in symptom severity: while some individuals remain nearly asymptomatic, others suffer from severe respiratory failure. Previous vaccinations for other pathogens, in particular tetanus, may partly explain this variation, possibly by readying the immune system. Methods: We made use of data on COVID-19 testing from 103,049 participants of the UK Biobank (mean age 71.5 years, 54.2% female), coupled to immunization records of the last ten years. Using logistic regression, covarying for age, sex, respiratory disease diagnosis, and socioeconomic status, we tested whether individuals vaccinated for tetanus, diphtheria or pertussis, differed from individuals that had only received other vaccinations on 1) undergoing a COVID-19 test, 2) being diagnosed with COVID-19, and 3) whether they developed severe COVID-19 symptoms. Results: We found that individuals with registered diphtheria or tetanus vaccinations are less likely to develop severe COVID-19 than people who had only received other vaccinations (diphtheria odds ratio (OR)=0.47, p-value=5.3*10-5; tetanus OR=0.52, p-value=1.2*10-4). Discussion: These results indicate that a history of diphtheria or tetanus vaccinations is associated with less severe manifestations of COVID-19. These vaccinations may protect against severe COVID-19 symptoms by stimulating the immune system. We note the correlational nature of these results, yet the possibility that these vaccinations may influence the severity of COVID-19 warrants follow-up investigations.

Vertex-wise multivariate genome-wide association study identifies 780 unique genetic loci associated with cortical morphology.

Brain morphology has been shown to be highly heritable, yet only a small portion of the heritability is explained by the genetic variants discovered so far. Here we extended the Multivariate Omnibus Statistical Test (MOSTest) and applied it to genome-wide association studies (GWAS) of vertex-wise structural magnetic resonance imaging (MRI) cortical measures from N=35,657 participants in the UK Biobank. We identified 695 loci for cortical surface area and 539 for cortical thickness, in total 780 unique genetic loci associated with cortical morphology robustly replicated in 8,060 children of mixed ethnicity from the Adolescent Brain Cognitive Development (ABCD) Study®. This reflects more than 8-fold increase in genetic discovery at no cost to generalizability compared to the commonly used univariate GWAS methods applied to region of interest (ROI) data. Functional follow up including gene-based analyses implicated 10% of all protein-coding genes and pointed towards pathways involved in neurogenesis and cell differentiation. Power analysis indicated that applying the MOSTest to vertex-wise structural MRI data triples the effective sample size compared to conventional univariate GWAS approaches. The large boost in power obtained with the vertex-wise MOSTest together with pronounced replication rates and highlighted biologically meaningful pathways underscores the advantage of multivariate approaches in the context of highly distributed polygenic architecture of the human brain.

Exercise self-efficacy is weakly related to engagement in physical activity in persons with long-standing spinal cord injury.

Aims: Many people with a long-standing spinal cord injury have an inactive lifestyle. Although exercise self-efficacy is considered a key determinant of engaging in exercise, the relationship between exercise self-efficacy and physical activity remains unclear. Therefore, this study examines the relationship between exercise self-efficacy and the amount of physical activity in persons with long-standing spinal cord injury.Methods: This cross-sectional study included 268 individuals (aged 28-65 years) with spinal cord injury ≥ 10 years and using a wheelchair. Physical activity was measured with the Physical Activity Scale for Individuals with Physical Disabilities. Exercise self-efficacy was assessed with the Spinal cord injury Exercise Self-Efficacy Scale. Univariate and multivariable regression analyses were performed to test for the association between exercise self-efficacy and physical activity, controlling for supposed confounders.Results: Univariate regression analysis revealed that exercise self-efficacy was significantly related to the level of daily physical activity (ß = 0.05; 95% CI 0.04-0.07; 15% explained variance; p < 0.001). In multivariable regression analysis exercise self-efficacy remained, explaining a significant additional amount of the variance (2%; p < 0.001) of physical activity.Conclusion: Exercise-self efficacy is a weak but independent explanatory factor of the level of physical activity among persons with long-standing spinal cord injury. Longitudinal trials are needed to study the impact of interventions targeting an increase of exercise self-efficacy on the amount of physical activity performed.Implications for rehabilitationPre-intervention levels of exercise-self-efficacy might mediate the effectiveness of interventions that aim at increasing physical activities in people with a long-standing spinal cord injury.Enhancing exercise-self efficacy may improve levels of physical activity, even in people with a long-standing spinal cord injury.When it comes to enhancing physical activity, efforts to enhance non-structured daily physical activities such as household activities and gardening might be as important as efforts to enhance sports and other physical exercise.

Family-Based Haplotype Estimation and Allele Dosage Correction for Polyploids Using Short Sequence Reads.

DNA sequence reads contain information about the genomic variants located on a single chromosome. By extracting and extending this information using the overlaps between the reads, the haplotypes of an individual can be obtained. Using parent-offspring relationships in a population can considerably improve the quality of the haplotypes obtained from short reads, as pedigree information can be used to correct for spurious overlaps (due to sequencing errors) and insufficient overlaps (due to short read lengths, low genomic variation and shallow coverage). We developed a novel method, PopPoly, to estimate polyploid haplotypes in an F1-population from short sequence data by taking into consideration the transmission of the haplotypes from the parents to the offspring. In addition, this information is employed to improve genotype dosage estimation and to call missing genotypes in the population. Through simulations, we compare PopPoly to other haplotyping methods and show its better performance. We evaluate PopPoly by applying it to a tetraploid potato cross at nine genomic regions involved in tuber formation.

TriPoly: haplotype estimation for polyploids using sequencing data of related individuals.

Motivation: Knowledge of haplotypes, i.e. phased and ordered marker alleles on a chromosome, is essential to answer many questions in genetics and genomics. By generating short pieces of DNA sequence, high-throughput modern sequencing technologies make estimation of haplotypes possible for single individuals. In polyploids, however, haplotype estimation methods usually require deep coverage to achieve sufficient accuracy. This often renders sequencing-based approaches too costly to be applied to large populations needed in studies of Quantitative Trait Loci. Results: We propose a novel haplotype estimation method for polyploids, TriPoly, that combines sequencing data with Mendelian inheritance rules to infer haplotypes in parent-offspring trios. Using realistic simulations of both short and long-read sequencing data for banana (Musa acuminata) and potato (Solanum tuberosum) trios, we show that TriPoly yields more accurate progeny haplotypes at low coverages compared to existing methods that work on single individuals. We also apply TriPoly to phase Single Nucleotide Polymorphisms on chromosome 5 for a family of tetraploid potato with 2 parents and 37 offspring sequenced with an RNA capture approach. We show that TriPoly haplotype estimates differ from those of the other methods mainly in regions with imperfect sequencing or mapping difficulties, as it does not rely solely on sequence reads and aims to avoid phasings that are not likely to have been passed from the parents to the offspring. Availability and implementation: TriPoly has been implemented in Python 3.5.2 (also compatible with Python 2.7.3 and higher) and can be freely downloaded at https://github.com/EhsanMotazedi/TriPoly. Supplementary information: Supplementary data are available at Bioinformatics online.

Exploiting next-generation sequencing to solve the haplotyping puzzle in polyploids: a simulation study.

Haplotypes are the units of inheritance in an organism, and many genetic analyses depend on their precise determination. Methods for haplotyping single individuals use the phasing information available in next-generation sequencing reads, by matching overlapping single-nucleotide polymorphisms while penalizing post hoc nucleotide corrections made. Haplotyping diploids is relatively easy, but the complexity of the problem increases drastically for polyploid genomes, which are found in both model organisms and in economically relevant plant and animal species. Although a number of tools are available for haplotyping polyploids, the effects of the genomic makeup and the sequencing strategy followed on the accuracy of these methods have hitherto not been thoroughly evaluated.We developed the simulation pipeline haplosim to evaluate the performance of three haplotype estimation algorithms for polyploids: HapCompass, HapTree and SDhaP, in settings varying in sequencing approach, ploidy levels and genomic diversity, using tetraploid potato as the model. Our results show that sequencing depth is the major determinant of haplotype estimation quality, that 1 kb PacBio circular consensus sequencing reads and Illumina reads with large insert-sizes are competitive and that all methods fail to produce good haplotypes when ploidy levels increase. Comparing the three methods, HapTree produces the most accurate estimates, but also consumes the most resources. There is clearly room for improvement in polyploid haplotyping algorithms.

A genome-wide approach to children's aggressive behavior: The EAGLE consortium.

Individual differences in aggressive behavior emerge in early childhood and predict persisting behavioral problems and disorders. Studies of antisocial and severe aggression in adulthood indicate substantial underlying biology. However, little attention has been given to genome-wide approaches of aggressive behavior in children. We analyzed data from nine population-based studies and assessed aggressive behavior using well-validated parent-reported questionnaires. This is the largest sample exploring children's aggressive behavior to date (N = 18,988), with measures in two developmental stages (N = 15,668 early childhood and N = 16,311 middle childhood/early adolescence). First, we estimated the additive genetic variance of children's aggressive behavior based on genome-wide SNP information, using genome-wide complex trait analysis (GCTA). Second, genetic associations within each study were assessed using a quasi-Poisson regression approach, capturing the highly right-skewed distribution of aggressive behavior. Third, we performed meta-analyses of genome-wide associations for both the total age-mixed sample and the two developmental stages. Finally, we performed a gene-based test using the summary statistics of the total sample. GCTA quantified variance tagged by common SNPs (10-54%). The meta-analysis of the total sample identified one region in chromosome 2 (2p12) at near genome-wide significance (top SNP rs11126630, P = 5.30 × 10(-8) ). The separate meta-analyses of the two developmental stages revealed suggestive evidence of association at the same locus. The gene-based analysis indicated association of variation within AVPR1A with aggressive behavior. We conclude that common variants at 2p12 show suggestive evidence for association with childhood aggression. Replication of these initial findings is needed, and further studies should clarify its biological meaning. © 2015 Wiley Periodicals, Inc.

ß-Amyloid Precursor Protein and Ubiquitin Immunohistochemistry Aid in the Evaluation of Infant Autopsy Eyes With Abusive Head Trauma.

PURPOSE: To investigate ß-amyloid precursor protein (ß-APP), ubiquitin, and glial fibrillary acid protein (GFAP) immunostaining as a diagnostic tool to aid in the discrimination between abusive head trauma and nonabusive head trauma in postmortem ocular histopathologic investigation. DESIGN: Retrospective cross-sectional study. METHODS: Seventy-four eyes of 37 infants were studied for hemorrhage and immunohistochemical expression of ß-APP, ubiquitin, and GFAP in the retina and optic nerve. Infants were assigned to abusive head trauma or control groups, according to published criteria. RESULTS: In the abusive head trauma group, positive ß-APP and ubiquitin immunostaining of the retina was significantly more likely to be found than in the control group, odds ratio (OR) 11.4, confidence interval (CI) 2.9-44.3; P < .001 and OR 8.8, CI 2.2-34.5; P = .002, respectively. Positive correlations were found between retinal expression of ß-APP and ubiquitin immunostaining and retinal hemorrhage. Vitreal hemorrhages, orbital fat hemorrhages, and macular folds could only be identified in abusive head trauma cases. Retinal hemorrhages were significantly more severe, occupied a larger proportion of the retina, and involved more retinal layers in abusive head trauma compared to controls (OR 2.7, CI 1.7-4.4; P < .001). CONCLUSIONS: This study shows correlations between positive retinal ß-APP and ubiquitin immunostaining as a sign of axonal injury in abusive head trauma. Axonal injury is a useful pathologic feature that can be demonstrated in postmortem ocular investigation of deceased children using immunohistochemical staining for ß-APP and ubiquitin with a high OR for abusive head trauma when compared to controls.

Low and high birth weight and the risk of child attention problems.

OBJECTIVE: To study the prospective association between birth weight and attention problems and to explore the role of maternal body mass index (BMI) in this association. STUDY DESIGN: In 6015 children of a population-based cohort (Rotterdam, The Netherlands, 2001-2005), information on birth weight was collected and gestational age-adjusted SDS were calculated. At age 6 years, parents assessed attention problems with the Child Behavior Checklist. We used linear regression to study the association of birth weight with attention problem score and examined the modification of this association by maternal early pregnancy BMI. RESULTS: The observed association between birth weight and attention problem score was curvilinear (adjusted ß per birth weight SDS(2): 0.02, 95% CI 0.00; 0.03, P = .008); the turning point equals 3.6 kg at term. In analyses of the extreme tails of the birth weight distribution, the associations with attention problem score disappeared after adjustment for socioeconomic confounders. Maternal early pregnancy BMI moderated the association of child birth weight with attention problem score (P interaction = .007, with curvilinear term in model). CONCLUSIONS: Higher birth weight was related to less attention problems but from a birth weight of about 3.6 kg or more, a higher birth weight did not reduce the risk of attention problems any further. However, in children of obese mothers (BMI >30 kg/m(2)), high birth weight may increase the risk of attention problems.