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Rapid advances in high-throughput DNA sequencing technologies have enabled the conduct of whole genome sequencing (WGS) studies, and several bioinformatics pipelines have become available. The aim of this study was the comparison of 6 WGS data pre-processing pipelines, involving two mapping and alignment approaches (GATK utilizing BWA-MEM2 2.2.1, and DRAGEN 3.8.4) and three variant calling pipelines (GATK 4.2.4.1, DRAGEN 3.8.4 and DeepVariant 1.1.0). We sequenced one genome in a bottle (GIAB) sample 70 times in different runs, and one GIAB trio in triplicate. The truth set of the GIABs was used for comparison, and performance was assessed by computation time, F 1 score, precision, and recall. In the mapping and alignment step, the DRAGEN pipeline was faster than the GATK with BWA-MEM2 pipeline. DRAGEN showed systematically higher F 1 score, precision, and recall values than GATK for single nucleotide variations (SNVs) and Indels in simple-to-map, complex-to-map, coding and non-coding regions. In the variant calling step, DRAGEN was fastest. In terms of accuracy, DRAGEN and DeepVariant performed similarly and both superior to GATK, with slight advantages for DRAGEN for Indels and for DeepVariant for SNVs. The DRAGEN pipeline showed the lowest Mendelian inheritance error fraction for the GIAB trios. Mapping and alignment played a key role in variant calling of WGS, with the DRAGEN outperforming GATK.

Background Venoarterial extracorporeal membrane oxygenation (VA-ECMO) is increasingly used in patients with critical cardiopulmonary failure. To investigate the association between hospital VA-ECMO procedure volume and outcomes in a large, nationwide registry. Methods By using administrative data from the German Federal Health Monitoring System, we analyzed all VA-ECMO procedures performed in Germany from 2013 to 2016 regarding the association of procedural volumes with outcomes and complications. Results During the study period, 10,207 VA-ECMO procedures were performed; mean age was 61 years, 43.4% had prior CPR, and 71.2% were male patients. Acute coronary syndrome was the primary diagnosis for VA-ECMO implantation ( n  = 6202, 60.8%). The majority of implantations ( n  = 5421) were performed at hospitals in the lowest volume category (≤ 50 implantations per year). There was a significant association between annualized volume of VA-ECMO procedures and 30-day in-hospital mortality for centers with lower vs. higher volume per year. Multivariable logistic regression showed an increased 30-day in-hospital mortality at hospitals with the lowest volume category (adjusted odds ratio 1.13, 95% confidence interval [CI] 1.01–1.27, p  = 0.034). Similarly, higher likelihood for complications was observed at hospitals with lower vs. higher annual VA-ECMO volume (adjusted odds ratio 1.46, 95% CI 1.29–1.66, p  = 0.001). Conclusions In this analysis of more than 10,000 VA-ECMO procedures for cardiogenic shock, the majority of implantations were performed at hospitals with the lowest annual volume. Thirty-day in-hospital mortality and likelihood for complications were higher at hospitals with the lowest annual VA-ECMO volume.

Inflammatory biomarkers are associated with severity of coronavirus disease 2019 (COVID-19). However, direct comparisons of their utility in COVID-19 versus other respiratory infections are largely missing. We aimed to investigate the prognostic utility of various inflammatory biomarkers in COVID-19 compared to patients with other respiratory infections. Patients presenting to the emergency department with symptoms suggestive of COVID-19 were prospectively enrolled. Levels of Interleukin-6 (IL-6), c-reactive protein (CRP), procalcitonin, ferritin, and leukocytes were compared between COVID-19, other viral respiratory infections, and bacterial pneumonia. Primary outcome was the need for hospitalisation, secondary outcome was the composite of intensive care unit (ICU) admission or death at 30 days. Among 514 patients with confirmed respiratory infections, 191 (37%) were diagnosed with COVID-19, 227 (44%) with another viral respiratory infection (viral controls), and 96 (19%) with bacterial pneumonia (bacterial controls). All inflammatory biomarkers differed significantly between diagnoses and were numerically higher in hospitalized patients, regardless of diagnoses. Discriminative accuracy for hospitalisation was highest for IL-6 and CRP in all three diagnoses (in COVID-19, area under the curve (AUC) for IL-6 0.899 [95%CI 0.850-0.948]; AUC for CRP 0.922 [95%CI 0.879-0.964]). Similarly, IL-6 and CRP ranged among the strongest predictors for ICU admission or death at 30 days in COVID-19 (AUC for IL-6 0.794 [95%CI 0.694-0.894]; AUC for CRP 0.807 [95%CI 0.721-0.893]) and both controls. Predictive values of inflammatory biomarkers were generally higher in COVID-19 than in controls. In patients with COVID-19 and other respiratory infections, inflammatory biomarkers harbour strong prognostic information, particularly IL-6 and CRP. Their routine use may support early management decisions.

•We related age-related cortical thickness differences with indices of brain network architecture in a surface-based spatial correlation analysis of a large population-based sample.•Age effects on cortical thickness were strongest in sensorimotor areas.•Regional age-related differences were strongly correlated within the structurally defined node neighborhood.•The overall pattern of thickness differences was found to be anchored in the functional network hierarchy as encoded by macroscale functional connectivity gradients.•Taken together, we demonstrate a link between functional and structural brain network topology and age effects on cortical morphology. Age-related cortical atrophy, approximated by cortical thickness measurements from magnetic resonance imaging, follows a characteristic pattern over the lifespan. Although its determinants remain unknown, mounting evidence demonstrates correspondence between the connectivity profiles of structural and functional brain networks and cortical atrophy in health and neurological disease. Here, we performed a cross-sectional multimodal neuroimaging analysis of 2633 individuals from a large population-based cohort to characterize the association between age-related differences in cortical thickness and functional as well as structural brain network topology. We identified a widespread pattern of age-related cortical thickness differences including “hotspots” of pronounced age effects in sensorimotor areas. Regional age-related differences were strongly correlated within the structurally defined node neighborhood. The overall pattern of thickness differences was found to be anchored in the functional network hierarchy as encoded by macroscale functional connectivity gradients. Lastly, the identified difference pattern covaried significantly with cognitive and motor performance. Our findings indicate that connectivity profiles of functional and structural brain networks act as organizing principles behind age-related cortical thinning as an imaging surrogate of cortical atrophy.

Coffee, next to water the most widespread beverage, is attributed both harmful and protective characteristics concerning cardiovascular health. This study aimed to evaluate associations of coffee consumption with cardiac biomarkers, echocardiographic, electrocardiographic parameters and major cardiovascular diseases. We performed a cross-sectional analysis of 9009 participants of the population-based Hamburg City Health Study (HCHS), enrolled between 2016 and 2018 median age 63 [IQR: 55; 69] years. Coffee consumption was classified into three groups: < 3 cups/day (low), 3–4 cups/day (moderate), > 4 cups/day (high). In linear regression analyses adjusted for age, sex, body mass index, diabetes, hypertension, smoking, and additives, high coffee consumption correlated with higher LDL-cholesterol (β = 5.92; 95% CI 2.95, 8.89; p < 0.001). Moderate and high coffee consumption correlated with lower systolic (β = − 1.91; 95% CI − 3.04, − 0.78; p = 0.001; high: β = − 3.06; 95% CI − 4.69, − 1.44; p < 0.001) and diastolic blood pressure (β = − 1.05; 95% CI − 1.67, − 0.43; p = 0.001; high: β = − 1.85; 95% CI − 2.74, − 0.96; p < 0.001). Different levels of coffee consumption did neither correlate with any investigated electrocardiographic or echocardiographic parameter nor with prevalent major cardiovascular diseases, including prior myocardial infarction and heart failure. In this cross-sectional analysis, high coffee consumption correlated with raised LDL-cholesterol levels and lower systolic and diastolic blood pressure. However, major cardiovascular diseases including heart failure and its diagnostic precursors were not associated with coffee consumption, connoting a neutral role of coffee in the context of cardiovascular health.

The link between metabolic syndrome (MetS) and neurodegenerative as well as cerebrovascular conditions holds substantial implications for brain health in at-risk populations. This study elucidates the complex relationship between MetS and brain health by conducting a comprehensive examination of cardiometabolic risk factors, brain morphology, and cognitive function in 40,087 individuals. Multivariate, data-driven statistics identified a latent dimension linking more severe MetS to widespread brain morphological abnormalities, accounting for up to 71% of shared variance in the data. This dimension was replicable across sub-samples. In a mediation analysis, we could demonstrate that MetS-related brain morphological abnormalities mediated the link between MetS severity and cognitive performance in multiple domains. Employing imaging transcriptomics and connectomics, our results also suggest that MetS-related morphological abnormalities are linked to the regional cellular composition and macroscopic brain network organization. By leveraging extensive, multi-domain data combined with a dimensional stratification approach, our analysis provides profound insights into the association of MetS and brain health. These findings can inform effective therapeutic and risk mitigation strategies aimed at maintaining brain integrity.

The early triage of patients toward rule-out and rule-in of acute myocardial infarction (AMI) is challenging. Therefore, we aimed to develop a 2-h algorithm that uses high-sensitivity cardiac troponin I (hs-cTnI). We prospectively enrolled 1435 (derivation cohort) and 1194 (external validation cohort) patients presenting with suspected AMI to the emergency department. The final diagnosis was adjudicated by 2 independent cardiologists. hs-cTnI was measured at presentation and after 2 h in a blinded fashion. We derived and validated a diagnostic algorithm incorporating hs-cTnI values at presentation and absolute changes within the first 2 h. AMI was the final diagnosis in 17% of patients in the derivation and 13% in the validation cohort. The 2-h algorithm developed in the derivation cohort classified 56% of patients as rule-out, 17% as rule-in, and 27% as observation. Resulting diagnostic sensitivity and negative predictive value (NPV) were 99.2% and 99.8% for rule-out; specificity and positive predictive value (PPV) were 95.2% and 75.8% for rule-in. Applying the 2-h algorithm in the external validation cohort, 60% of patients were classified as rule-out, 13% as rule-in, and 27% as observation. Diagnostic sensitivity and NPV were 98.7% and 99.7% for rule-out; specificity and PPV were 97.4% and 82.2% for rule-in. Thirty-day survival was 100% for rule-out patients in both cohorts. A simple algorithm incorporating hs-cTnI baseline values and absolute 2-h changes allowed a triage toward safe rule-out or accurate rule-in of AMI in the majority of patients.

Despite its high prevalence, the determinants of smelling impairment in COVID-19 remain not fully understood. In this work, we aimed to examine the association between olfactory bulb volume and the clinical trajectory of COVID-19-related smelling impairment in a large-scale magnetic resonance imaging (MRI) analysis. Data of non-vaccinated COVID-19 convalescents recruited within the framework of the prospective Hamburg City Health Study COVID Program between March and December 2020 were analyzed. At baseline, 233 participants underwent MRI and neuropsychological testing as well as a structured questionnaire for olfactory function. Between March and April 2022, olfactory function was assessed at follow-up including quantitative olfactometric testing with Sniffin’ Sticks. This study included 233 individuals recovered from mainly mild to moderate SARS-CoV-2 infections. Longitudinal assessment demonstrated a declining prevalence of self-reported olfactory dysfunction from 67.1% at acute infection, 21.0% at baseline examination and 17.5% at follow-up. Participants with post-acute self-reported olfactory dysfunction had a significantly lower olfactory bulb volume at baseline than normally smelling individuals. Olfactory bulb volume at baseline predicted olfactometric scores at follow-up. Performance in neuropsychological testing was not significantly associated with the olfactory bulb volume. Our work demonstrates an association of long-term self-reported smelling dysfunction and olfactory bulb integrity in a sample of individuals recovered from mainly mild to moderate COVID-19. Collectively, our results highlight olfactory bulb volume as a surrogate marker that may inform diagnosis and guide rehabilitation strategies in COVID-19.

Background Coronary heart disease (CHD) is the leading cause of death among adults in Germany. There is evidence that occupational exposure to particulate matter, noise, psychosocial stressors, shift work and high physical workload are associated with CHD. The aim of this study is to identify occupations that are associated with CHD and to elaborate on occupational exposures associated with CHD by using the job exposure matrix (JEM) BAuA-JEM ETB 2018 in a German study population. Methods Cross-sectional data from 8,070 participants, members of the first sub-cohort of the Hamburg City Health Study (HCHS), was used. To classify occupations, we rely on standard occupational titles (ISCO-08). The level of exposure is assigned to each job using a JEM. CHD is measured by self-reported diagnosis. Absolute and relative frequencies were calculated. Using logistic regression, the association of CHD and standard occupation titles via ISCO-08 and the association of CHD and occupational exposures via JEM were calculated and adjusted for potentially confounding covariates. Multiple imputations with chained equations (MICEs) were applied for missing values. Sensitivity analyses were performed. Results The CHD prevalence in the study population was 4.6% (95% CI 4.2–5.1). Occupations associated with CHD were Physical and Engineering Science Technicians , Other Health Associate Professionals , General Office Clerks , Secretaries (general) , Material Recording and Transport Clerks , Hairdressers , Beauticians and Related Workers , Electronics and Telecommunications Installers and Repairers , Other Craft and Related Workers , Car , Van and Motorcycle Drivers , Mobile Plant Operators and Domestic , Hotel and Office Cleaners and Helpers . Among occupational exposures retrieved from the JEM, Environmental Demands showed an association with CHD in the crude model but not after adjustment. The results remained robust in sensitivity analyses. Conclusions This study is the first to assess the association of a wide range of occupations and occupational exposures with CHD in a German study population. We found no association between occupational exposures and CHD after adjustment, but 11 occupations associated with CHD were identified. The results are limited by cross-sectional design, healthy worker effect (HWE), and small group sizes. Further studies with a larger sample and longitudinal design containing data on occupational history, occupational exposures and time of CHD diagnosis are needed.

With the emergence of new subvariants, the disease severity of Severe Acute Respiratory Syndrome Coronavirus-2 has attenuated. This study aimed to compare the disease severity in patients hospitalized with omicron variant infection to those with influenza infection. We compared data from the multicenter observational, prospective, epidemiological \"CORONA Germany\" (Clinical Outcome and Risk in hospitalized COVID-19 patients) study on patients infected with Severe Acute Respiratory Syndrome Coronavirus-2 to retrospective data on influenza infection cases from November 2016 to August 2022. Severe Acute Respiratory Syndrome Coronavirus-2 cases were classified as wild-type/delta variant before January 2022, or omicron variant from January 2022 onward. The primary outcome was in-hospital mortality, adjusted for age, gender, and comorbidities. The study included 35,806 patients from 53 hospitals in Germany, including 4,916 patients (13.7%) with influenza infection, 16,654 patients (46.5%) with wild-type/delta variant infection, and 14,236 patients (39.8%) with omicron variant infection. In-hospital mortality was highest in patients with wild-type/delta variant infection (16.8%), followed by patients with omicron variant infection (8.4%) and patients with influenza infection (4.7%). In the adjusted analysis, higher age was the strongest predictor for in-hospital mortality (age 80 years vs. age 50 years: OR 4.25, 95% CI 3.10-5.83). Both, patients with wild-type/delta variant infection (OR 3.54, 95% CI 3.02-4.15) and patients with omicron variant infection (OR 1.56, 95% CI 1.32-1.84) had a higher risk for in-hospital mortality than patients with influenza infection. After adjusting for age, gender and comorbidities, patients with wild-type/delta variant infection had the highest risk for in-hospital mortality compared to patients with influenza infection. Even for patients with omicron variant infection, the adjusted risk for in-hospital mortality was higher than for patients with influenza infection. The adjusted risk for in-hospital mortality showed a strong age dependency across all virus types and variants. NCT04659187.