Abstract
Background
To improve research and care for patients with post-COVID-19 condition more insight into different subtypes of post-COVID-19 condition and their risk factors is urgently needed. ...We aimed to identify risk factors of post-COVID-19 condition in general and for specific symptom profiles.
Methods
This study is based on data collected within the Lifelines Coronavirus disease 2019 (COVID-19) cohort (N = 76 503). Mean pre- and post-SARS-CoV-2 infection symptom scores were compared to classify post-COVID-19 condition. Latent Profile Analysis was used to identify symptom profiles. Logistic and multinomial regression analyses were used to examine the association between demographic, lifestyle and health-related risk factors and post-COVID-19 condition, and symptom profiles, respectively.
Results
Of the 3465 participants having had COVID-19, 18.5% (n = 642) classified for post-COVID-19 condition. Four symptom profiles were identified: muscle pain, fatigue, cardiorespiratory and ageusia/anosmia. Female sex was a risk factor for the muscle pain and fatigue profiles. Being overweight or obese increased risk for all profiles, except the fatigue profile. Having a chronic disease increased the risk for all profiles except the ageusia/anosmia profile, with the cardiorespiratory profile being only significant in case of multimorbidity. Being unvaccinated increased risk of the ageusia/anosmia profile.
Conclusions
Findings from this study suggest that Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may trigger different pathophysiological mechanisms that may result in different subtypes of post-COVID-19 condition. These subtypes have shared and unique risk factors. Further characterization of symptom profiles and quantification of the individual and societal impact of specific symptom profiles are pressing challenges for future research.
Although age-dependent effects on blood pressure (BP) have been reported, they have not been systematically investigated in large-scale genome-wide association studies (GWASs). We leveraged the ...infrastructure of three well-established consortia (CHARGE, GBPgen, and ICBP) and a nonstandard approach (age stratification and metaregression) to conduct a genome-wide search of common variants with age-dependent effects on systolic (SBP), diastolic (DBP), mean arterial (MAP), and pulse (PP) pressure. In a two-staged design using 99,241 individuals of European ancestry, we identified 20 genome-wide significant (p <= 5 x 10(-8)) loci by using joint tests of the SNP main effect and SNP-age interaction. Nine of the significant loci demonstrated nominal evidence of age-dependent effects on BP by tests of the interactions alone. Index SNPs in the EHBP1L1 (DBP and MAP), CASZ1 (SBP and MAP), and GOSR2 (PP) loci exhibited the largest age interactions, with opposite directions of effect in the young versus the old. The changes in the genetic effects over time were small but nonnegligible (up to 1.58 mm Hg over 60 years). The EHBP1L1 locus was discovered through gene-age interactions only in whites but had DBP main effects replicated (p = 8.3 x 10(-4)) in 8,682 Asians from Singapore, indicating potential interethnic heterogeneity. A secondary analysis revealed 22 loci with evidence of age-specific effects (e.g., only in 20 to 29-year-olds). Age can be used to select samples with larger genetic effect sizes and more homogenous phenotypes, which may increase statistical power. Age-dependent effects identified through novel statistical approaches can provide insight into the biology and temporal regulation underlying BP associations.
Although age-dependent effects on blood pressure (BP) have been reported, they have not been systematically investigated in large-scale genome-wide association studies (GWASs). We leveraged the ...infrastructure of three well-established consortia (CHARGE, GBPgen, and ICBP) and a nonstandard approach (age stratification and metaregression) to conduct a genome-wide search of common variants with age-dependent effects on systolic (SBP), diastolic (DBP), mean arterial (MAP), and pulse (PP) pressure. In a two-staged design using 99,241 individuals of European ancestry, we identified 20 genome-wide significant (p <= 5 x 10(-8)) loci by using joint tests of the SNP main effect and SNP-age interaction. Nine of the significant loci demonstrated nominal evidence of age-dependent effects on BP by tests of the interactions alone. Index SNPs in the EHBP1L1 (DBP and MAP), CASZ1 (SBP and MAP), and GOSR2 (PP) loci exhibited the largest age interactions, with opposite directions of effect in the young versus the old. The changes in the genetic effects over time were small but nonnegligible (up to 1.58 mm Hg over 60 years). The EHBP1L1 locus was discovered through gene-age interactions only in whites but had DBP main effects replicated (p = 8.3 x 10(-4)) in 8,682 Asians from Singapore, indicating potential interethnic heterogeneity. A secondary analysis revealed 22 loci with evidence of age-specific effects (e.g., only in 20 to 29-year-olds). Age can be used to select samples with larger genetic effect sizes and more homogenous phenotypes, which may increase statistical power. Age-dependent effects identified through novel statistical approaches can provide insight into the biology and temporal regulation underlying BP associations.
This study evaluates to what extent symptoms are present before, during, and after a positive SARS-CoV-2 polymerase chain reaction (PCR) test, and to evaluate how the symptom burden and quality of ...Life (QoL) compares to those with a negative PCR test. Participants from the Dutch Lifelines COVID-19 Cohort Study filled-out as of March 2020 weekly, later bi-weekly and monthly, questions about demographics, COVID-19 diagnosis and severity, QoL, and symptoms. The study population included those with one positive or negative PCR test who filled out two questionnaires before and after the test, resulting in 996 SARS-CoV-2 PCR positive and 3978 negative participants. Nearly all symptoms were more often reported after a positive test versus the period before the test (p < 0.05), except fever. A higher symptom prevalence after versus before a test was also found for nearly all symptoms in negatives (p < 0.05). Before the test, symptoms were already partly present and reporting of nearly all symptoms before did not differ between positives and negatives (p > 0.05). QoL decreased around the test for positives and negatives, with a larger deterioration for positives. Not all symptoms after a positive SARS-CoV-2 PCR test might be attributable to the infection and symptoms were also common in negatives.
Individual differences in heart rate variability (HRV) can be partly attributed to genetic factors that may be more pronounced during stress. Using data from the Oman Family Study (OFS), we aimed to ...estimate and quantify the relative contribution of genes and environment to the variance of HRV at rest and during stress; calculate the overlap in genetic and environmental influences on HRV at rest and under stress using bivariate analyses of HRV parameters and heart rate (HR).
Time and frequency domain HRV variables and average HR were measured from beat-to-beat HR obtained from electrocardiogram recordings at rest and during two stress tests mental: Word Conflict Test (WCT) and physical: Cold Pressor Test (CPT) in the OFS - a multigenerational pedigree consisting of five large Arab families with a total of 1326 participants. SOLAR software was used to perform quantitative genetic modelling.
Heritability estimates for HRV and HR ranged from 0.11 to 0.31 for rest, 0.09-0.43 for WCT, and 0.07-0.36 for CPT. A large part of the genetic influences during rest and stress conditions were shared with genetic correlations ranging between 0.52 and 0.86 for rest-WCT and 0.60-0.92 for rest-CPT. Nonetheless, genetic rest-stress correlations for most traits were significantly smaller than 1 indicating some stress-specific genetic effects.
Genetic factors significantly influence HRV and HR at rest and under stress. Most of the genetic factors that influence HRV at rest also influence HRV during stress tests, although some unique genetic variance emerges during these challenging conditions.
Working from home during the COVID-19 pandemic has affected many workers' daily life and possibly their physical activity behavior. We studied the longitudinal association of working from home during ...the pandemic with physical activity and sedentary behavior.
Longitudinal data from 17 questionnaire rounds of the Lifelines COVID-19 cohort (March 2020-February 2021) were used. In total, 33 325 workers were included. In every round, participants reported their current work situation: location, home, or hybrid (working on location and from home). Physical activity levels and sedentary behavior before and during the pandemic were asked. Logistic generalized estimating equations adjusted for demographic/work/health covariates were used to study the association of work situation with physical activity and sedentary behavior.
Home workers were less likely to meet the recommended ≥150 minutes/week of moderate-to-vigorous-intensity activity during the pandemic than location workers odds ratio (OR) 0.93, 95% confidence interval (CI) 0.90-0.96 and more likely to be less physically active than before the pandemic (OR 1.09, 95% CI 1.04-1.14). Furthermore, compared to location workers, home and hybrid workers were more likely to be more sedentary (sitting ≥8 hours/day) on workdays during than before the pandemic (OR 1.51, 95% CI 1.39-1.64/1.36-1.68, respectively).
Compared to location workers, home workers (and to a lesser extent hybrid workers) were more often physically inactive and sedentary during than before the COVID-19 pandemic. As a substantial part of the working population may continue to work (partly) from home after the pandemic, workers should be supported to increase activity and reduce sitting while working from home.
Background
Frailty is associated with COVID-19 severity in clinical settings. No general population-based studies on the association between actual frailty status and COVID-19 hospitalization are ...available.
Aims
To investigate the association between frailty and the risk of COVID-19 hospitalization once infected.
Methods
440 older adults who participated in the Lifelines COVID-19 Cohort study in the Northern Netherlands and reported positive COVID-19 testing results (54.2% women, age 70 ± 4 years in 2021) were included in the analyses. COVID-19 hospitalization status was self-reported. The Groningen Frailty Indicator (GFI) was derived from 15 self-reported questionnaire items related to daily activities, health problems, and psychosocial functioning, with a score ≥ 4 indicating frailty. Both frailty and COVID-19 hospitalization were assessed in the same period. Poisson regression models with robust standard errors were used to analyze the associations between frailty and COVID-19 hospitalization.
Results
Of 440 older adults included, 42 were hospitalized because of COVID-19 infection. After adjusting for sociodemographic and lifestyle factors, a higher risk of COVID-19 hospitalization was observed for frail individuals (risk ratio (RR) 95% CI 1.97 1.06–3.67) compared to those classified as non-frail.
Discussion
Frailty was positively associated with COVID-19 hospitalization once infected, independent of sociodemographic and lifestyle factors. Future research on frailty and COVID-19 should consider biomarkers of aging and frailty to understand the pathophysiological mechanisms and manifestations between frailty and COVID-19 outcomes.
Conclusions
Frailty was positively associated with the risk of hospitalization among older adults that were infected with COVID-19. Public health strategies for frailty prevention in older adults need to be advocated, as it is helpful to reduce the burden of the healthcare system, particularly during a pandemic like COVID-19.
During the COVID-19 pandemic, many healthcare workers faced extreme working conditions and were at higher risk of infection with the coronavirus. These circumstances may have led to mental health ...problems, such as anxiety, among healthcare workers. Most studies that examined anxiety among healthcare workers during the COVID-19 pandemic were cross-sectional and focused on the first months of the pandemic only. Therefore, this study aimed to investigate the longitudinal association between working in healthcare and anxiety during a long-term period (i.e., 18 months) of the COVID-19 pandemic.
Data were used from online questionnaires of the Lifelines COVID-19 prospective cohort with 22 included time-points (March 2020-November 2021). In total, 2,750 healthcare workers and 9,335 non-healthcare workers were included. Anxiety was assessed with questions from the Mini-International Neuropsychiatric Interview, and an anxiety sum score (0-7) was calculated. Negative binomial generalized estimating equations (GEE), adjusted for demographic, work and health covariates, were used to examine the association between working in healthcare and anxiety.
Anxiety sum scores over time during the COVID-19 pandemic were similar for healthcare workers and non-healthcare workers. No differences between the anxiety sum scores of healthcare workers and non-healthcare workers were found incidence rate ratio (IRR) = 0.97, 95% CI = 0.91-1.04.
This study did not find differences between healthcare workers and non-healthcare in perceived anxiety during the COVID-19 pandemic.
Working from home during the COVID-19 pandemic has been associated both with physical inactivity and musculoskeletal pain. However, it has not been examined whether physical activity and sedentary ...behavior are underlying mechanisms in the association between working from home and musculoskeletal pain. Therefore, we examined their mediating role in this association.
Data were used from 24 questionnaire rounds of the Lifelines COVID-19 cohort (March 2020-January 2022). Longitudinal information on work situation (location, home, hybrid), physical activity, sedentary behavior, and musculoskeletal pain was collected among 28,586 workers. Analysis of physical activity/sedentary behavior as mediators of the association between working from home and musculoskeletal pain was performed using multilevel structural equation modeling.
Home workers more often had pain in the upper back odds ratio (OR) = 1.17, 95%-confidence interval (CI) = 1.02-1.34 and arm, neck, and/or shoulder (ANS) (OR = 1.32, 95%-CI = 1.19-1.47) than location workers. Furthermore, home workers were more often sedentary for >9 h per work day than location workers (OR = 2.82, 95%-CI = 2.56-3.09), and being more sedentary was associated with musculoskeletal pain (upper back: OR = 1.17, 95%-CI = 1.06-1.30; ANS: OR = 1.25, 95%-CI = 1.16-1.34). Corresponding indirect effects were OR = 1.18 (95%-CI = 1.04-1.33) and OR = 1.26 (95%-CI = 1.12-1.35). No indirect effect was found for physical activity. Similar indirect effects were observed for hybrid workers.
Home and hybrid workers were more likely to have pain in the upper musculoskeletal system during the COVID-19 pandemic than location workers, which was partly mediated by increased sedentary behavior, but not by reduced physical activity. Measures to reduce sedentary time in home workers may contribute to preventing musculoskeletal pain.
Evaluation of the IRF-2 Gene as a Candidate for PSORS3 Foerster, John; Nolte, Ilja; Schweiger, Susann ...
Journal of investigative dermatology,
January 2004, 2004-01-00, 2004, 2004-Jan, 20040101, Letnik:
122, Številka:
1
Journal Article
Recenzirano
Odprti dostop
Type 1 interferon can trigger flares of psoriasis. Hypersensitivity to type 1 interferon signaling causes a psoriasis-like skin disease in mice deficient for the transcription factor interferon ...regulatory factor 2 (IRF2). The human IRF2 gene is located at a previously identified candidate psoriasis susceptibility locus on chromosome 4q (PSORS3 at D4S1535). Therefore, we tested association of psoriasis with IRF2. We generated a sample consisting of 157 families with a total of 521 individuals. Five novel microsatellite markers were developed and typed, and complemented with three known markers to yield a set of eight markers spaced within 600 kb around the IRF2 gene, three of which are located in the gene. We detected association of IRF2 with type 1 psoriasis at two markers in the IRF2 gene. Haplotype sharing analysis confirmed association of IRF2 with type 1 psoriasis (p=0.0017; pcorr=0.03). The 921G/A SNP in exon 9 was found to obliterate a predicted exon splice enhancer in an allele-specific manner. There was a suggestive increase of homozygosity for the splicing-deficient allele in type 1 psoriasis patients. Our data identify IRF2 as a potential susceptibility gene for psoriasis.
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