Autoimmune diseases and female-specific cancer risk: A systematic review and meta-analysis.

OBJECTIVES: Among the over 80 different autoimmune diseases, psoriasis (PsO), rheumatoid arthritis (RA), and ankylosing spondylitis (AS) are common representatives. Previous studies indicated a potential link with cancer risk, but suffered often from low statistical power. Thus, we aimed to synthesize the evidence and quantify the association to different female-specific cancer sites. METHODS: The systematic review was performed according to PRISMA guidelines. A search string was developed for the databases PubMed, Web of Science, Cochrane Library and Embase. Results were screened independently by two investigators and the risk of bias was assessed using the ROBINS-E tool. Meta-analyses were performed using inverse variance weighted random-effects models. Statistical between-study heterogeneity was quantified by calculating Cochran's Q, τ2, and Higgins' I2 statistics. Sources of heterogeneity were analyzed and adjusted for within an intensive bias assessment in the form of meta-regression, outlier, influential, and subgroup analyses. A range of methods were used to test and adjust for publication bias. RESULTS: Of 10,096 records that were originally identified by the search strategy, 45 were included in the meta-analyses. RA was inversely associated with both breast and uterine cancer occurrence, while PsO was associated with a higher breast cancer risk. Outlier-adjusted estimates confirmed these findings. Bias assessment revealed differences in geographic regions, particularly in RA patients, with higher estimates among Asian studies. An additional analysis revealed no association between psoriatic arthritis and breast cancer. CONCLUSIONS: RA seems to reduce the risk of breast and uterine cancers, while PsO appears to increase breast cancer risk. Further large studies are required to investigate potential therapy-effects and detailed biological mechanisms.

Inflammation biomarkers in acute ischemic stroke according to different etiologies.

BACKGROUND: High throughput technologies provide new opportunities to further investigate the pathophysiology of ischemic strokes. The present cross-sectional study aimed to evaluate potential associations between the etiologic subtypes of ischemic stroke and blood-based proteins. METHODS: We investigated the associations between ischemic stroke subtypes and a panel of circulating inflammation biomarkers in 364 patients included in the Stroke Cohort Augsburg (SCHANA). Stroke etiologies were categorized according to the TOAST (Trial of Org 10172 in Acute Stroke Treatment) classification. Serum concentrations of 52 biomarkers were measured using the Bio-Plex Pro™ Human Cytokine Screening Panel, ICAM-1 set and VCAM-1 set, plus the Pro™ Human TH17 cytokine sCD40L set and IL31 set (all Bio-Rad, USA). Multivariable linear regression models were used to examine associations. Point estimates were calculated as the mean difference in σ -standardized cytokine levels on the log2 -scale. RESULTS: Stromal-cell-derived-factor 1 alpha (SDF-1a) showed significantly higher serum levels in cardioembolic compared with large vessel atherosclerotic stroke (ß = 0.48; 95% CI 0.22; 0.75; Padj = 0.036). Significantly lower levels of interleukin-6 (IL-6) (ß = -0.53; 95% CI -0.84; -0.23; Padj = 0.036) and macrophage migration inhibitory factor (MIF) (ß = -0.52; 95% CI -0.84; -0.21; Padj = 0.043) were found in the small vessel versus large vessel stroke subtype. CONCLUSIONS: Immune dysregulations observed in different stroke subtypes might help uncover pathophysiological mechanisms of the disease. Further studies are needed to validate identified biomarkers in diverse study populations before they can potentially be used in clinical practice to further improve stroke management and patient outcomes.

Differential association of dietary scores with the risk of type 2 diabetes by metabotype.

PURPOSE: We aimed to examine the association between dietary patterns and type 2 diabetes mellitus (T2DM) while considering the potential effect modification by metabolic phenotypes (metabotypes). Additionally, we aimed to explore the association between dietary scores and prediabetes. METHODS: A total of 1460 participants (11.8% with T2DM) from the cross-sectional population-based KORA FF4 study were included. Participants, classified into three metabotype subgroups, had both their FSAm-NPS dietary index (underpinning the Nutri-Score) and ultra-processed foods (UPF) intake (using NOVA classification) calculated. Glucose tolerance status was assessed via oral glucose tolerance tests (OGTT) in non-diabetic participants and was classified according to the American Diabetes Association criteria. Logistic regression models were used for both the overall and metabotype-stratified analyses of dietary scores' association with T2DM, and multinomial probit models for their association with prediabetes. RESULTS: Participants who had a diet with a higher FSAm-NPS dietary index (i.e., a lower diet quality) or a greater percentage of UPF consumption showed a positive association with T2DM. Stratified analyses demonstrated a strengthened association between UPF consumption and T2DM specifically in the metabolically most unfavorable metabotype (Odds Ratio, OR 1.92; 95% Confidence Interval, CI 1.35, 2.73). A diet with a higher FSAm-NPS dietary index was also positively associated with prediabetes (OR 1.19; 95% CI 1.04, 1.35). CONCLUSION: Our study suggests different associations between poorer diet quality and T2DM across individuals exhibiting diverse metabotypes, pointing to the option for stratified dietary interventions in diabetes prevention.

Symptom Clusters in Acute SARS-CoV-2 Infection and Long COVID Fatigue in Male and Female Outpatients.

(1) Background: After an acute SARS-CoV-2 infection, patients are at risk of developing Long COVID, with fatigue as a frequent and serious health problem. Objectives: To identify symptom clusters in acute SARS-CoV-2 infections and investigate their associations with the development of Long COVID fatigue, and to examine sex-specific differences. (2) Methods: The analysis included a total of 450 COVID-19 outpatients, of whom 54.4% were female. The median ages of the men and women were 51 years (IQR 36.0; 60.0) and 48 years (IQR 33.0; 57.0), respectively. Data collection took place between November 2020 and May 2021, with a median time between acute SARS-CoV-2 infection and examination in the study center of 240 days (IQR 133; 326). The Fatigue Assessment Scale (FAS) was used to identify fatigue and its severity. A multiple correspondence analysis was used to group forty-two COVID-19 symptoms into seven symptom clusters. Logistic and log-linear regressions were used to investigate associations between acute symptom clusters and Long COVID fatigue as dichotomous and continuous outcome, respectively. (3) Results: Fatigue occurred more frequently in women than in men (45% vs. 25%) and the median FAS score, indicating severity of fatigue, was higher in women than in men. The comparison between men and women revealed notable differences in four out of seven clusters. The strongest associations between symptom clusters in infection and Long COVID fatigue were identified for the cluster "cognitive and mental symptoms". In the log-linear regression model, each additional symptom in this cluster was associated with an increase of the FAS score by 5.13% (95% CI: [0.04; 0.07]; p < 0.001). The results of the logistic regression models supported this finding. Each additional symptom in this symptom cluster increased the odds of fatigue by 42% (95% CI: [1.23; 1.66]; p < 0.001). (4) Conclusions: In our study in COVID-19 outpatients, a strong association was observed between the number of symptoms in the cluster "cognitive and mental symptoms" during acute SARS-CoV-2 infection and the risk of developing fatigue months later. The consequent use of preventive and therapeutic strategies is necessary to decrease the burden of fatigue in the context of Long COVID.

Is the Habitual Dietary Intake of Foods of Plant or Animal Origin Associated with Circulating Hemostatic Factors?-Results of the Population-Based KORA-Fit Study.

Blood coagulation is a complex physiological process critical for maintaining hemostasis, and disruptions in this system can lead to various health complications. Since the effects of specific food groups on a series of circulating coagulation parameters in the population are not well established, this study examines such associations in the population-based KORA-Fit study. A total of 595 subjects (263 men and 332 women) born between 1945 and 1964 and living in the study region of Augsburg were included in the study. Habitual food intake was estimated based on a combination of repeated 24-h food lists (24HFLs) and a food frequency questionnaire (FFQ). Antithrombin III, D-dimers, factor VIII, fibrinogen, protein C, protein S, aPTT, Quick value and INR were measured in citrate plasma. Multivariable linear regression models were applied to investigate associations between the consumption of specific foods of plant or animal origin and hemostatic factors. We found that the consumption of plant-based food groups, including green leafy vegetables (rich in vitamin K1), were hardly associated with coagulation parameters. Surprisingly, a high consumption of dairy products and especially butter were associated with higher D-dimer concentrations. These findings need further evaluation in prospective studies.

Association Between Acute Myocardial Infarction Symptoms and Short- and Long-term Mortality After the Event.

BACKGROUND: In this study, we investigated various acute myocardial infarction (AMI) symptoms and their associations with short-term (28 day) and long-term mortality. METHODS: The analysis was based on 5900 patients, aged 25 to 84 years, with first-time AMI recorded by the population-based Myocardial Infarction Registry Augsburg between 2010 and 2017. Median follow-up time was 3.8 years (interquartile range: 1.1-6.3). As part of a face-to-face interview, the presence (yes/no) of 11 most common AMI symptoms at the acute event was assessed. Using multivariable-adjusted logistic regression and Cox regression models, the association between various symptoms and all-cause mortality was investigated. P values of the regression models were false discovery rate adjusted. RESULTS: Pain in various body parts (chest pain, left and right shoulder/arm/hand, between shoulder blades), sweating, nausea/vomiting, dizziness and fear of death/feeling of annihilation were significantly associated with a decreased 28-day mortality after AMI. The pain symptoms and sweating were also significantly associated with a decreased long-term mortality. Shortness of breath was significantly associated with a higher long-term mortality. CONCLUSIONS: The absence of several symptoms, including typical chest discomfort (chest pain or retrosternal pressure/tightness), is associated with unfavourable outcomes after AMI. This finding has implications for patient management and public health measures designed to encourage appropriate and prompt medical consultation of patients with atypical AMI symptoms.

Can inflammatory plasma proteins predict Long COVID or Fatigue severity after SARS-CoV-2 infection?

OBJECTIVE: To investigate whether specific immune response plasma proteins can predict an elevated risk of developing Long COVID symptoms or fatigue severity after SARS-CoV-2 infection. METHODS: This study was based on 257 outpatients with test-confirmed SARS-CoV-2 infection between February 2020 and January 2021. At least 12 weeks after the acute infection, 92 plasma proteins were measured using the Olink Target 96 immune response panel (median time between acute infection and venous blood sampling was 38.8 [IQR: 24.0-48.0] weeks). The presence of Long COVID symptoms and fatigue severity was assessed 115.8 [92.5-118.6] weeks after the acute infection by a follow-up postal survey. Long COVID (yes/no) was defined as having one or more of the following symptoms: fatigue, shortness of breath, concentration or memory problems. The severity of fatigue was assessed using the Fatigue Assessment Scale (FAS). In multivariable-adjusted logistic and linear regression models the associations between each plasma protein (exposure) and Long COVID (yes/no) or severity of fatigue were investigated. RESULTS: Nine plasma proteins were significantly associated with Long COVID before, but not after adjusting for multiple testing (FDR-adjustment): DFFA, TRIM5, TRIM21, HEXIM1, SRPK2, PRDX5, PIK3AP1, IFNLR1 and HCLS1. Moreover, a total of 10 proteins were significantly associated with severity of fatigue before FDR-adjustment: SRPK2, ITGA6, CLEC4G, HEXIM1, PPP1R9B, PLXNA4, PRDX5, DAPP1, STC1 and HCLS1. Only SRPK2 and ITGA6 remained significantly associated after FDR-adjustment. CONCLUSIONS: This study demonstrates that certain immune response plasma proteins might play an important role in the pathophysiology of Long COVID and severity of fatigue after SARS-CoV-2 infection.

Usual dietary intake and change in DNA methylation over years: EWAS in KORA FF4 and KORA fit.

Introduction: Changes in DNA methylation can increase or suppress the expression of health-relevant genes. We investigated for the first time the relationship between habitual food consumption and changes in DNA methylation. Methods: The German KORA FF4 and KORA Fit studies were used to study the change in methylation over a median follow-up of 4 years. Only subjects participating in both surveys and with available dietary and methylation data were included in the analysis (n = 465). DNA methylation was measured using the Infinium MethylationEPIC BeadChip (Illumina), resulting in 735,527 shared CpGs across both studies. Generalized estimating equation models with an interaction term of exposure and time point were used to analyze the association of 34 food groups, folic acid, and two dietary patterns with changes in DNA methylation over time. Results: The results were corrected for genomic inflation. Significant interaction terms indicate different effects between both time points. We observed only a few significant associations between food intake and change in DNA methylation, except for cream and spirit consumption. The annotated genes include CLN3, PROM1, DLEU7, TLL2, and UGT1A10. Discussion: We identified weak associations between food consumption and DNA methylation change. The differential results for cream and spirits, both consumed in low quantities, require replication in independent studies.