Symptoms and quality of life before, during, and after a SARS-CoV-2 PCR positive or negative test:data from Lifelines

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 &lt; 0.05), except fever. A higher symptom prevalence after versus before a test was also found for nearly all symptoms in negatives (p &lt; 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 &gt; 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.</p

Autosomal genetic variation is associated with DNA methylation in regions variably escaping X-chromosome inactivation

X-chromosome inactivation (XCI), i.e., the inactivation of one of the female X chromosomes, restores equal expression of X-chromosomal genes between females and males. However, ~10% of genes show variable degrees of escape from XCI between females, although little is known about the causes of variable XCI. Using a discovery data-set of 1867 females and 1398 males and a replication sample of 3351 females, we show that genetic variation at three autosomal loci is associated with female-specific changes in X-chromosome methylation. Through cis-eQTL expression analysis, we map these loci to the genes SMCHD1/METTL4, TRIM6/HBG2, and ZSCAN9. Low-expression alleles of the loci are predominantly associated with mild hypomethylation of CpG islands near genes known to variably escape XCI, implicating the autosomal genes in variable XCI. Together, these results suggest a genetic basis for variable escape from XCI and highlight the potential of a population genomics approach to identify genes involved in XCI

Refining Attention-Deficit/Hyperactivity Disorder and Autism Spectrum Disorder Genetic Loci by Integrating Summary Data From Genome-wide Association, Gene Expression, and DNA Methylation Studies

Background: Recent genome-wide association studies (GWASs) identified the first genetic loci associated with attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). The next step is to use these results to increase our understanding of the biological mechanisms involved. Most of the identified variants likely influence gene regulation. The aim of the current study is to shed light on the mechanisms underlying the genetic signals and prioritize genes by integrating GWAS results with gene expression and DNA methylation (DNAm) levels. Methods: We applied summary-data–based Mendelian randomization to integrate ADHD and ASD GWAS data with fetal brain expression and methylation quantitative trait loci, given the early onset of these disorders. We also analyzed expression and methylation quantitative trait loci datasets of adult brain and blood, as these provide increased statistical power. We subsequently used summary-data–based Mendelian randomization to investigate if the same variant influences both DNAm and gene expression levels. Results: We identified multiple gene expression and DNAm levels in fetal brain at chromosomes 1 and 17 that were associated with ADHD and ASD, respectively, through pleiotropy at shared genetic variants. The analyses in brain and blood showed additional associated gene expression and DNAm levels at the same and additional loci, likely because of increased statistical power. Several of the associated genes have not been identified in ADHD and ASD GWASs before. Conclusions: Our findings identified the genetic variants associated with ADHD and ASD that likely act through gene regulation. This facilitates prioritization of candidate genes for functional follow-up studies

Improving Phenotypic Prediction by Combining Genetic and Epigenetic Associations

We tested whether DNA-methylation profiles account for inter-individual variation in body mass index (BMI) and height and whether they predict these phenotypes over and above genetic factors. Genetic predictors were derived from published summary results from the largest genome-wide association studies on BMI (n ∼ 350,000) and height (n ∼ 250,000) to date. We derived methylation predictors by estimating probe-trait effects in discovery samples and tested them in external samples. Methylation profiles associated with BMI in older individuals from the Lothian Birth Cohorts (LBCs, n = 1,366) explained 4.9% of the variation in BMI in Dutch adults from the LifeLines DEEP study (n = 750) but did not account for any BMI variation in adolescents from the Brisbane Systems Genetic Study (BSGS, n = 403). Methylation profiles based on the Dutch sample explained 4.9% and 3.6% of the variation in BMI in the LBCs and BSGS, respectively. Methylation profiles predicted BMI independently of genetic profiles in an additive manner: 7%, 8%, and 14% of variance of BMI in the LBCs were explained by the methylation predictor, the genetic predictor, and a model containing both, respectively. The corresponding percentages for LifeLines DEEP were 5%, 9%, and 13%, respectively, suggesting that the methylation profiles represent environmental effects. The differential effects of the BMI methylation profiles by age support previous observations of age modulation of genetic contributions. In contrast, methylation profiles accounted for almost no variation in height, consistent with a mainly genetic contribution to inter-individual variation. The BMI results suggest that combining genetic and epigenetic information might have greater utility for complex-trait prediction

Traditional lifestyle factors partly mediate the association of socioeconomic position with intrahepatic lipid content:The Maastricht study

Background &amp; Aims: Recent studies have unveiled an association between socioeconomic position (SEP) and intrahepatic lipid (IHL) content. The aim of this study was to examine to what extent traditional lifestyle factors mediate the relationship between SEP and IHL content, independent of aetiology, and non-alcoholic fatty liver disease (NAFLD). Methods: We used cross-sectional data derived from The Maastricht Study (N = 4,001; mean age: 60 years, 49% women, 32% low education level, 21% diabetes, 21% NAFLD). Education, income, and occupation were used as indicators of SEP. Physical activity (accelerometer), intake of total energy, alcohol, saturated fat, protein, vitamin E, dietary fibre, and fructose from sugar-sweetened beverages (SSBs) and fruit juice (food frequency questionnaires) were potential mediators. IHL content was quantified by magnetic resonance imaging. Age, sex, and type 2 diabetes were covariates. Multiple parallel mediation analyses (bootstraps = 10,000) were performed. Results: Individuals with a low education level had a 1.056-fold higher IHL content (95% CI: 1.03–1.08) and a 44% greater NAFLD risk (OR:1.44; 95% CI:1.18–1.77) compared with those with higher education levels. Approximately 8.9% of educational disparity in risk of IHL content was attributable to moderate-to-vigorous physical activity; 6.3% to fructose intake from SSBs; 5.5% to dietary fibre; and -23% to alcohol. Approximately 8.7% of educational disparity in risk of NAFLD was attributable to moderate-to-vigorous physical activity; and 7.7% to fructose intake from SSBs. However, the indirect effect of these mediators was small (0.998 for IHL content and 1.045 for NAFLD) in comparison to the total effect. Similar results were found when income and occupation were used as SEP indicators. Conclusions: Societal measures may alleviate the burden of NAFLD and further studies that identify mediators other than traditional lifestyle factors are warranted to define the relationship underlying SEP and IHL content. Impact and implications: Individuals with a low or medium level of education, income, or occupational status had more fat accumulation in their livers than individuals with a higher education, income, or occupational status. This difference may be attributed to the influence of unhealthy lifestyle factors, such as reduced physical activity and a higher intake of sugar-sweetened beverages among individuals with lower socioeconomic position. Nevertheless, other yet unknown factors may also play a role

An interferon-related signature characterizes the whole blood transcriptome profile of insulin-resistant individuals-the CODAM study

BACKGROUND: Worldwide, the prevalence of obesity and insulin resistance has grown dramatically. Gene expression profiling in blood represents a powerful means to explore disease pathogenesis, but the potential impact of inter-individual differences in a cell-type profile is not always taken into account. The objective of this project was to investigate the whole blood transcriptome profile of insulin-resistant as compared to insulin-sensitive individuals independent of inter-individual differences in white blood cell profile. RESULTS: We report a 3% higher relative amount of monocytes in the insulin-resistant individuals. Furthermore, independent of their white blood cell profile, insulin-resistant participants had (i) higher expression of interferon-stimulated genes and (ii) lower expression of genes involved in cellular differentiation and remodeling of the actin cytoskeleton. CONCLUSIONS: We present an approach to investigate the whole blood transcriptome of insulin-resistant individuals, independent of their DNA methylation-derived white blood cell profile. An interferon-related signature characterizes the whole blood transcriptome profile of the insulin-resistant individuals, independent of their white blood cell profile. The observed signature indicates increased systemic inflammation possibly due to an innate immune response and whole-body insulin resistance, which can be a cause or a consequence of insulin resistance. Altered gene expression in specific organs may be reflected in whole blood; hence, our results may reflect obesity and/or insulin resistance-related organ dysfunction in the insulin-resistant individuals. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12263-021-00702-7