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1.
Dtsch Arztebl Int ; 119(11): 179-187, 2022 03 18.
Article in English | MEDLINE | ID: covidwho-1879446

ABSTRACT

BACKGROUND: Numerous studies have reported an increase in mental disorders during the COVID-19 pandemic, but the exact reasons for this development are not well understood. In this study we investigate whether pandemic-related occupational and financial changes (e.g., reduced working hours, working from home, financial losses) were associated with increased symptoms of depression and anxiety compared with the situation before the pandemic. METHODS: We analyzed data from the German National Cohort (NAKO) Study. Between May and November 2020, 161 849 study participants answered questions on their mental state and social circumstances. Their responses were compared with data from the baseline survey before the pandemic (2014-2019). Linear fixed-effects models were used to determine whether individual changes in the severity of symptoms of depression (PHQ-9) or anxiety (GAD-7) were associated with occupational/ financial changes (controlling for various covariates). RESULTS: The prevalence of moderate or severe symptoms of depression and anxiety increased by 2.4% and 1.5%, respectively, during the COVID-19 pandemic compared with the preceding years. The mean severity of the symptoms rose slightly. A pronounced increase in symptoms was observed among those who became unemployed during the pandemic (+ 1.16 points on the depression scale, 95% confidence interval [0.91; 1.41], range 0-27). Increases were also seen for reduced working hours with no short-time allowance, increased working hours, working from home, insecurity regarding employment, and financial strain. The deterioration in mental health was largely statistically explained by the occupational and financial changes investigated in the model. CONCLUSION: Depressive symptoms and anxiety disorders increased slightly in the study population during the first year of the COVID-19 pandemic. Occupational and financial difficulties were an essential contributory factor. These strains should be taken into account both in the care of individual patients and in the planning of targeted prevention measures.


Subject(s)
COVID-19 , Mental Disorders , Anxiety/epidemiology , COVID-19/epidemiology , Depression/diagnosis , Depression/epidemiology , Humans , Mental Disorders/epidemiology , Pandemics , SARS-CoV-2
2.
Elife ; 112022 01 13.
Article in English | MEDLINE | ID: covidwho-1677761

ABSTRACT

Protein biomarkers have been identified across many age-related morbidities. However, characterising epigenetic influences could further inform disease predictions. Here, we leverage epigenome-wide data to study links between the DNA methylation (DNAm) signatures of the circulating proteome and incident diseases. Using data from four cohorts, we trained and tested epigenetic scores (EpiScores) for 953 plasma proteins, identifying 109 scores that explained between 1% and 58% of the variance in protein levels after adjusting for known protein quantitative trait loci (pQTL) genetic effects. By projecting these EpiScores into an independent sample (Generation Scotland; n = 9537) and relating them to incident morbidities over a follow-up of 14 years, we uncovered 137 EpiScore-disease associations. These associations were largely independent of immune cell proportions, common lifestyle and health factors, and biological aging. Notably, we found that our diabetes-associated EpiScores highlighted previous top biomarker associations from proteome-wide assessments of diabetes. These EpiScores for protein levels can therefore be a valuable resource for disease prediction and risk stratification.


Although our genetic code does not change throughout our lives, our genes can be turned on and off as a result of epigenetics. Epigenetics can track how the environment and even certain behaviors add or remove small chemical markers to the DNA that makes up the genome. The type and location of these markers may affect whether genes are active or silent, this is, whether the protein coded for by that gene is being produced or not. One common epigenetic marker is known as DNA methylation. DNA methylation has been linked to the levels of a range of proteins in our cells and the risk people have of developing chronic diseases. Blood samples can be used to determine the epigenetic markers a person has on their genome and to study the abundance of many proteins. Gadd, Hillary, McCartney, Zaghlool et al. studied the relationships between DNA methylation and the abundance of 953 different proteins in blood samples from individuals in the German KORA cohort and the Scottish Lothian Birth Cohort 1936. They then used machine learning to analyze the relationship between epigenetic markers found in people's blood and the abundance of proteins, obtaining epigenetic scores or 'EpiScores' for each protein. They found 109 proteins for which DNA methylation patterns explained between at least 1% and up to 58% of the variation in protein levels. Integrating the 'EpiScores' with 14 years of medical records for more than 9000 individuals from the Generation Scotland study revealed 137 connections between EpiScores for proteins and a future diagnosis of common adverse health outcomes. These included diabetes, stroke, depression, Alzheimer's dementia, various cancers, and inflammatory conditions such as rheumatoid arthritis and inflammatory bowel disease. Age-related chronic diseases are a growing issue worldwide and place pressure on healthcare systems. They also severely reduce quality of life for individuals over many years. This work shows how epigenetic scores based on protein levels in the blood could predict a person's risk of several of these diseases. In the case of type 2 diabetes, the EpiScore results replicated previous research linking protein levels in the blood to future diagnosis of diabetes. Protein EpiScores could therefore allow researchers to identify people with the highest risk of disease, making it possible to intervene early and prevent these people from developing chronic conditions as they age.


Subject(s)
Cardiovascular Diseases/diagnosis , DNA Methylation/genetics , Diabetes Mellitus/diagnosis , Epigenomics/methods , Neoplasms/diagnosis , Proteome/genetics , Adolescent , Adult , Aged , Aged, 80 and over , Aging , Biomarkers , Epigenesis, Genetic , Female , Humans , Life Style , Male , Middle Aged , Risk Factors , Scotland , Young Adult
4.
Dtsch Arztebl Int ; 117(50): 861-867, 2020 12 11.
Article in English | MEDLINE | ID: covidwho-968708

ABSTRACT

BACKGROUND: The pandemic caused by the coronavirus SARS-CoV-2 and the countermeasures taken to protect the public are having a substantial effect on the health of the population. In Germany, nationwide protective measures to halt the spread of the virus were implemented in mid-March for 6 weeks. METHODS: In May, the impact of the pandemic was assessed in the German National Cohort (NAKO). A total of 113 928 men and women aged 20 to 74 years at the time of the baseline examination conducted 1 to 5 years earlier (53%) answered, within a 30-day period, a follow-up questionnaire on SARS-CoV-2 test status, COVID-19- associated symptoms, and self-perceived health status. RESULTS: The self-reported SARS-CoV-2 test frequency among the probands was 4.6%, and 344 participants (0.3%) reported a positive test result. Depressive and anxiety-related symptoms increased relative to baseline only in participants under 60 years of age, particularly in young women. The rate of moderate to severe depressive symptoms increased from 6.4% to 8.8%. Perceived stress increased in all age groups and both sexes, especially in the young. The scores for mental state and self-rated health worsened in participants tested for SARS-CoV-2 compared with those who were not tested. In 32% of the participants, however, self-rated health improved. CONCLUSION: The COVID-19 pandemic and the protective measures during the first wave had effects on mental health and on self-rated general health.


Subject(s)
COVID-19/epidemiology , Health Status , Mental Health , Pandemics , Adult , Aged , Anxiety , Depression , Female , Germany/epidemiology , Humans , Male , Middle Aged , Self Report , Stress, Psychological , Young Adult
6.
Environ Int ; 146: 106272, 2021 01.
Article in English | MEDLINE | ID: covidwho-943095

ABSTRACT

The outbreak of COVID-19 raised numerous questions on the interactions between the occurrence of new infections, the environment, climate and health. The European Union requested the H2020 HERA project which aims at setting priorities in research on environment, climate and health, to identify relevant research needs regarding Covid-19. The emergence and spread of SARS-CoV-2 appears to be related to urbanization, habitat destruction, live animal trade, intensive livestock farming and global travel. The contribution of climate and air pollution requires additional studies. Importantly, the severity of COVID-19 depends on the interactions between the viral infection, ageing and chronic diseases such as metabolic, respiratory and cardiovascular diseases and obesity which are themselves influenced by environmental stressors. The mechanisms of these interactions deserve additional scrutiny. Both the pandemic and the social response to the disease have elicited an array of behavioural and societal changes that may remain long after the pandemic and that may have long term health effects including on mental health. Recovery plans are currently being discussed or implemented and the environmental and health impacts of those plans are not clearly foreseen. Clearly, COVID-19 will have a long-lasting impact on the environmental health field and will open new research perspectives and policy needs.


Subject(s)
Air Pollution , COVID-19 , Animals , Climate , Humans , Pandemics , SARS-CoV-2
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