Large-scale assessment of physical activity in a population using high-resolution hip-worn accelerometry: the German National Cohort (NAKO).

Large population-based cohort studies utilizing device-based measures of physical activity are crucial to close important research gaps regarding the potential protective effects of physical activity on chronic diseases. The present study details the quality control processes and the derivation of physical activity metrics from 100 Hz accelerometer data collected in the German National Cohort (NAKO). During the 2014 to 2019 baseline assessment, a subsample of NAKO participants wore a triaxial ActiGraph accelerometer on their right hip for seven consecutive days. Auto-calibration, signal feature calculations including Euclidean Norm Minus One (ENMO) and Mean Amplitude Deviation (MAD), identification of non-wear time, and imputation, were conducted using the R package GGIR version 2.10-3. A total of 73,334 participants contributed data for accelerometry analysis, of whom 63,236 provided valid data. The average ENMO was 11.7 ± 3.7 mg (milli gravitational acceleration) and the average MAD was 19.9 ± 6.1 mg. Notably, acceleration summary metrics were higher in men than women and diminished with increasing age. Work generated in the present study will facilitate harmonized analysis, reproducibility, and utilization of NAKO accelerometry data. The NAKO accelerometry dataset represents a valuable asset for physical activity research and will be accessible through a specified application process.

Associations of Migration, Socioeconomic Position and Social Relations With Depressive Symptoms - Analyses of the German National Cohort Baseline Data.

Objectives: We analyze whether the prevalence of depressive symptoms differs among various migrant and non-migrant populations in Germany and to what extent these differences can be attributed to socioeconomic position (SEP) and social relations. Methods: The German National Cohort health study (NAKO) is a prospective multicenter cohort study (N = 204,878). Migration background (assessed based on citizenship and country of birth of both participant and parents) was used as independent variable, age, sex, Social Network Index, the availability of emotional support, SEP (relative income position and educational status) and employment status were introduced as covariates and depressive symptoms (PHQ-9) as dependent variable in logistic regression models. Results: Increased odds ratios of depressive symptoms were found in all migrant subgroups compared to non-migrants and varied regarding regions of origins. Elevated odds ratios decreased when SEP and social relations were included. Attenuations varied across migrant subgroups. Conclusion: The gap in depressive symptoms can partly be attributed to SEP and social relations, with variations between migrant subgroups. The integration paradox is likely to contribute to the explanation of the results. Future studies need to consider heterogeneity among migrant subgroups whenever possible.

Suitability and user acceptance of the eResearch system "Prospective Monitoring and Management App (PIA)"-The example of an epidemiological study on infectious diseases.

BACKGROUND: The eResearch system "Prospective Monitoring and Management App (PIA)" allows researchers to implement questionnaires on any topic and to manage biosamples. Currently, we use PIA in the longitudinal study ZIFCO (Integrated DZIF Infection Cohort within the German National Cohort) in Hannover (Germany) to investigate e.g. associations of risk factors and infectious diseases. Our aim was to assess user acceptance and compliance to determine suitability of PIA for epidemiological research on transient infectious diseases. METHODS: ZIFCO participants used PIA to answer weekly questionnaires on health status and report spontaneous onset of symptoms. In case of symptoms of a respiratory infection, the app requested participants to self-sample a nasal swab for viral analysis. To assess user acceptance, we implemented the System Usability Scale (SUS) and fitted a linear regression model on the resulting score. For investigation of compliance with submitting the weekly health questionnaires, we used a logistic regression model with binomial response. RESULTS: We analyzed data of 313 participants (median age 52.5 years, 52.4% women). An average SUS of 72.0 reveals good acceptance of PIA. Participants with a higher technology readiness score at the beginning of study participation also reported higher user acceptance. Overall compliance with submitting the weekly health questionnaires showed a median of 55.7%. Being female, of younger age and being enrolled for a longer time decreased the odds to respond. However, women over 60 had a higher chance to respond than women under 60, while men under 40 had the highest chance to respond. Compliance with nasal swab self-sampling was 77.2%. DISCUSSION: Our findings show that PIA is suitable for the use in epidemiologic studies with regular short questionnaires. Still, we will focus on user engagement and gamification for the further development of PIA to help incentivize regular and long-term participation.

Authors' response: Occupation and SARS-CoV-2 infection risk among workers during the first pandemic wave in Germany: potential for bias.

We thank van Tongeren et al for responding to our study on occupational disparities in SARS-CoV-2 infection risks during the first pandemic wave in Germany (1). The authors address the potential for bias resulting from differential testing between occupational groups and propose an alternative analytical strategy for dealing with selective testing. In the following, we want to discuss two aspects of this issue, namely (i) the extent and reasons of differential testing in our cohort and (ii) the advantages and disadvantages of different analytical approaches to study risk factors for SARS-CoV-2 infection. Our study relied on nationwide prospective cohort data including more than 100 000 workers in order to compare the incidence of infections between different occupations and occupational status positions. We found elevated infection risks in personal services and business administration, in essential occupations (including health care) and among people in higher occupational status positions (ie, managers and highly skilled workers) during the first pandemic wave in Germany (2). Van Tongeren's et al main concern is that the correlations found could be affected by a systematic bias because people in healthcare professions get tested more often than employees in other professions. A second argument is that better-off people could be more likely to use testing as they are less affected by direct costs (prices for testing) and the economic hardship associated with a positive test result (eg, loss of earnings in the event of sick leave). We share the authors' view that differential testing must be considered when analysing and interpreting the data. Thus, in our study, we examined the proportion of tests conducted in each occupational group as part of the sensitivity analyses (see supplementary figure S1, accessible at www.sjweh.fi/article/4037). As expected, testing proportions were exceptionally high in medical occupations (due to employer requirements). However, we did not observe systematic differences among non-medical occupations or when categorising by skill-level or managerial responsibility. This might be explained by several reasons. First, SARS-CoV-2 testing was free of charge during the first pandemic wave in Germany, but reporting a risk contact or having symptoms was a necessary condition for testing ( https://www.bundesgesundheitsministerium.de/coronavirus/chronik-coronavirus.html (accessed 5 September 2022). The newspaper article cited by van Tongeren et al is misleading as it refers to a calendar date after our study period. Second, different motivation for testing due to economic hardship in case of a positive test result is an unlikely explanation, because Germany has a universal healthcare system, including paid sick leave and sickness benefits for all workers (3). Self-employed people carry greater financial risks in case of sickness. We therefore included self-employment in the multivariable analyses to address this potential source of bias. While the observed inverse social gradient may be surprising, it actually matches with findings of ecological studies from Germany (4, 5), the United States (6, 7) as well as Spain, Portugal, Sweden, The Netherlands, Israel, and Hong Kong (8), all of which observed higher infection rates in wealthier neighbourhoods during the initial outbreak phase of the pandemic. One possible explanation is the higher mobility of managers and better educated workers, who are more likely to participate in meetings and engage in business travel and holiday trips like skiing. Given the increasing number of studies providing evidence for this hypothesis, we conclude that the inverse social gradient in our study likely reflects different exposure probabilities and is not a result of systematic bias. This also holds true for the elevated infection risks in essential workers, which is actually corroborated by a large body of research (9-11). Regarding differential likelihood of testing, van Tongeren et al state that "[i]t is relatively simple to address this problem by using a test-negative design" (1). As van Tongeren et al describe, this is a case-control approach only including individuals who were tested (without considering those who were not tested). However, the proposed analytical strategy can lead to another (more serious) selection bias if testing proportions and/or testing criteria differ between groups (12). This can be easily illustrated when comparing the results based on a time-incidence design with those obtained by a test-negative design as shown in table 1 (see PDF). Both approaches show similar results in terms of vertical occupational differences. Infection was more common if individuals had a high skill level or had a managerial position, but associations were stronger in the time-incidence design and did not reach statistical significance in the test-negative design (as indicated by the confidence intervals overlapping "1"). Unfortunately, the test-negative approach relies on a strongly reduced sample size and thus results in greater statistical uncertainty and loss of statistical power (13). In contrast, the test-negative design yields a different picture when estimating the association between essential occupation and infection risk: In this analysis, essential workers did not differ from non-essential workers in their chance of being infected with SARS-CoV-2 (the test-negative design even exhibits a lower chance for essential workers). This is rather counter-intuitive and is not in accordance with what we know about the occupational hazards of healthcare workers during the pandemic (14). The main problem is that proportions of positive tests are highly unreliable when testing proportions and/or testing criteria differ between groups. As essential workers were tested more often without being symptomatic (due to employer requirements), a lower proportion of positive tests in this group does not necessarily correspond to a lower risk of infection. Consequently, we are not convinced that the test-negative design should be the 'gold standard' for studying risk factors for SARS-CoV-2 infections (15). Especially problematic is the loss of statistical power (increasing the probability of a type II error) and the low validity of the test-positivity when test criteria and/or test proportions differ between groups. References 1. van Tongeren M, Rhodes S, Pearce N. Occupation and SARS-CoV-2 infection risk among workers during the first pandemic wave in Germany: potential for bias. Scand J Work Environ Health 2022;48(7):586-587. https://doi.org/10.5271/sjweh.4052. 2. Reuter M, Rigó M, Formazin M, Liebers F, Latza U, Castell S, et al. Occupation and SARS-CoV-2 infection risk among 108 960 workers during the first pandemic wave in Germany. Scand J Work Environ Health 2022;48:446-56. https://doi.org/10.5271/sjweh.4037. 3. Busse R, Blümel M, Knieps F, Bärnighausen T. Statutory health insurance in Germany: a health system shaped by 135 years of solidarity, self-governance, and competition. Lancet 2017;390:882-97. https://doi.org/10.1016/S0140-6736(17)31280-1. 4. Wachtler B, Michalski N, Nowossadeck E, Diercke M, Wahrendorf M, Santos-Hövener C, et al. Socioeconomic inequalities in the risk of SARS-CoV-2 infection - First results from an analysis of surveillance data from Germany. J Heal Monit 2020;5:18-29. https://doi.org/10.25646/7057. 5. Plümper T, Neumayer E. The pandemic predominantly hits poor neighbourhoods? SARS-CoV-2 infections and COVID-19 fatalities in German districts. Eur J Public Health 2020;30:1176-80. https://doi.org/10.1093/eurpub/ckaa168. 6. Abedi V, Olulana O, Avula V, Chaudhary D, Khan A, Shahjouei S, et al. Racial, Economic, and Health Inequality and COVID-19 Infection in the United States. J Racial Ethn Heal Disparities 2021;8:732-42. https://doi.org/10.1007/s40615-020-00833-4. 7. Mukherji N. The Social and Economic Factors Underlying the Incidence of COVID-19 Cases and Deaths in US Counties During the Initial Outbreak Phase. Rev Reg Stud 2022;52. https://doi.org/10.52324/001c.35255. 8. Beese F, Waldhauer J, Wollgast L, Pförtner T, Wahrendorf M, Haller S, et al. Temporal Dynamics of Socioeconomic Inequalities in COVID-19 Outcomes Over the Course of the Pandemic-A Scoping Review. Int J Public Health 2022;67:1-14. https://doi.org/10.3389/ijph.2022.1605128. 9. Nguyen LH, Drew DA, Graham MS, Joshi AD, Guo C-G, Ma W, et al. Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study. Lancet Public Heal 2020;5:e475-83. https://doi.org/10.1016/S2468-2667(20)30164-X. 10. Chou R, Dana T, Buckley DI, Selph S, Fu R, Totten AM. Epidemiology of and Risk Factors for Coronavirus Infection in Health Care Workers. Ann Intern Med 2020;173:120-36. https://doi.org/10.7326/M20-1632. 11. Stringhini S, Zaballa M-E, Pullen N, de Mestral C, Perez-Saez J, Dumont R, et al. Large variation in anti-SARS-CoV-2 antibody prevalence among essential workers in Geneva, Switzerland. Nat Commun 2021;12:3455. https://doi.org/10.1038/s41467-021-23796-4. 12. Accorsi EK, Qiu X, Rumpler E, Kennedy-Shaffer L, Kahn R, Joshi K, et al. How to detect and reduce potential sources of biases in studies of SARS-CoV-2 and COVID-19. Eur J Epidemiol 2021;36:179-96. https://doi.org/10.1007/s10654-021-00727-7. 13. Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2nd Editio. New York: Routledge; 2013. https://doi.org/10.4324/9780203771587. 14. The Lancet. The plight of essential workers during the COVID-19 pandemic. Lancet 2020;395:1587. https://doi.org/10.1016/S0140-6736(20)31200-9. 15. Vandenbroucke JP, Brickley EB, Pearce N, Vandenbroucke-Grauls CMJE. The Evolving Usefulness of the Test-negative Design in Studying Risk Factors for COVID-19. Epidemiology 2022;33:e7-8. https://doi.org/10.1097/EDE.0000000000001438.

Epidemiology of Lyme borreliosis based on outpatient claims data of all people with statutory health insurance, Germany, 2019.

IntroductionEvidence of nationwide and regional morbidity of Lyme borreliosis (LB) in Germany is lacking.AimsWe calculated the total number of incident LB cases in Germany in 2019, compared regional variations, investigated the extent of possible under-reporting in notification data and examined the association between high incidence areas and land cover composition.MethodsWe used outpatient claims data comprising information for people with statutory health insurance who visited a physician at least once between 2010 and 2019 in Germany (n = 71,411,504). The ICD-10 code A69.2 was used to identify incident LB patients. Spatial variations of LB were assessed by means of Global and Local Moran's Index at district level. Notification data were obtained for nine federal states with mandatory notification from the Robert Koch Institute (RKI).ResultsOf all insured, 128,177 were diagnosed with LB in 2019, corresponding to an incidence of 179 per 100,000 insured. The incidence varied across districts by a factor of 16 (range: 40-646 per 100,000). We identified four spatial clusters with high incidences. These clusters were associated with a significantly larger proportion of forests and agricultural areas than low incidence clusters. In 2019, 12,264 LB cases were reported to the RKI from nine federal states, while 69,623 patients with LB were found in claims data for those states. This difference varied considerably across districts.ConclusionsThese findings serve as a solid basis for regionally tailored population-based intervention programmes and can support modelling studies assessing the development of LB epidemiology under various climate change scenarios.

Providing laypeople with results from dynamic infectious disease modelling studies affects their allocation preference for scarce medical resources-a factorial experiment.

BACKGROUND: Allocation of scarce medical resources can be based on different principles. It has not yet been investigated which allocation schemes are preferred by medical laypeople in a particular situation of medical scarcity like an emerging infectious disease and how the choices are affected by providing information about expected population-level effects of the allocation scheme based on modelling studies. We investigated the potential benefit of strategic communication of infectious disease modelling results. METHODS: In a two-way factorial experiment (n = 878 participants), we investigated if prognosis of the disease or information about expected effects on mortality at population-level (based on dynamic infectious disease modelling studies) influenced the choice of preferred allocation schemes for prevention and treatment of an unspecified sexually transmitted infection. A qualitative analysis of the reasons for choosing specific allocation schemes supplements our results. RESULTS: Presence of the factor "information about the population-level effects of the allocation scheme" substantially increased the probability of choosing a resource allocation system that minimized overall harm among the population, while prognosis did not affect allocation choices. The main reasons for choosing an allocation scheme differed among schemes, but did not differ among those who received additional model-based information on expected population-level effects and those who did not. CONCLUSIONS: Providing information on the expected population-level effects from dynamic infectious disease modelling studies resulted in a substantially different choice of allocation schemes. This finding supports the importance of incorporating model-based information in decision-making processes and communication strategies.

[Assessment of self-reported cardiovascular and metabolic diseases in the German National Cohort (GNC, NAKO Gesundheitsstudie): methods and initial results]. / Erfassung selbst berichteter kardiovaskulärer und metabolischer Erkrankungen in der NAKO Gesundheitsstudie: Methoden und erste Ergebnisse.

BACKGROUND: Data on self-reported cardiovascular and metabolic diseases are available for the first 100,000 participants of the population-based German National Cohort (GNC, NAKO Gesundheitsstudie). OBJECTIVES: To describe assessment methods and the frequency of self-reported cardiovascular and metabolic diseases in the German National Cohort. MATERIALS AND METHODS: Using a computer-based, standardized personal interview, 101,806 participants (20-75 years, 46% men) from 18 nationwide study centres were asked to use a predefined list to report medical conditions ever diagnosed by a physician, including cardiovascular or metabolic diseases. For the latter, we calculated sex-stratified relative frequencies and compared these with reference data. RESULTS: With regard to cardiovascular diseases, 3.5% of men and 0.8% of women reported to have ever been diagnosed with a myocardial infarction, 4.8% and 1.5% with angina pectoris, 3.5% and 2.5% with heart failure, 10.1% and 10.4% with cardiac arrhythmia, 2.7% and 1.8% with claudicatio intermittens, and 34.6% and 27.0% with arterial hypertension. The frequencies of self-reported diagnosed metabolic diseases were 8.1% and 5.8% for diabetes mellitus, 28.6% and 24.5% for hyperlipidaemia, 7.9% and 2.4% for gout, and 10.1% and 34.3% for thyroid diseases. Observed disease frequencies were lower than reference data for Germany. CONCLUSIONS: In the German National Cohort, self-reported cardiovascular and metabolic diseases diagnosed by a physician are assessed from all participants, therefore representing a data source for future cardio-metabolic research in this cohort.

[Persons with migration background in the German National Cohort (NAKO)-sociodemographic characteristics and comparisons with the German autochthonous population]. / Personen mit Migrationshintergrund in der NAKO Gesundheitsstudie ­ soziodemografische Merkmale und Vergleiche mit der autochthonen deutschen Bevölkerung.

BACKGROUND: Persons with a migration background (PmM) as a population group usually differ from the autochthonous population in terms of morbidity, mortality, and use of the health care system, but they participate less frequently in health studies. The PmM group is very heterogeneous, which has hardly been taken into account in studies so far. OBJECTIVES: Sociodemographic characteristics of PmM in the NAKO health study (age, sex, time since migration, education) are presented. In addition, it is examined through an example whether migration background is related to the use of cancer screening for colorectal cancer (hemoccult test). METHODS: Data of the first 101,816 persons of the NAKO were analyzed descriptively and cartographically. The migration background was assigned on the basis of the definition of the Federal Statistical Office, based on nationality, country of birth, year of entry, and country of birth of the parents. RESULTS: Overall, the PmM proportion is 16.0%. The distribution across the 18 study centers varies considerably between 6% (Neubrandenburg) and 33% (Düsseldorf). With 153 countries of origin, most countries are represented in the NAKO. All variables show clear differences between the different regions of origin. In the hemoccult test, persons of Turkish origin (OR = 0.67) and resettlers (OR = 0.60) have a lower participation rate. PmM born in Germany do not differ in this respect from the autochthonous population (OR = 0.99). CONCLUSION: PmM in the NAKO are a very heterogeneous group. However, due to the sample size, individual subgroups of migrants can be studied separately with respect to region of origin.

[Socio-demographic and employment-related factors in the German National Cohort (GNC; NAKO Gesundheitsstudie)]. / Soziodemografische und erwerbsbezogene Merkmale in der NAKO Gesundheitsstudie.

BACKGROUND: In epidemiologic studies, standardised measurement of socio-demographic and employment-related factors is becoming increasingly important, as variables such as gender, age, education or employment status are factors influencing health and disease risks. AIMS: The article gives an overview of the scientific background and assessment of socio-demographic factors in the German National Cohort Study. In addition, the distribution of individual characteristics in the cohort as well as relationships with health-related measures are presented by way of example. MATERIAL AND METHODS: The analysis is based on the data of the first half of the baseline survey (n = 101,724). On this basis, we present the distribution of key socio-demographic characteristics and analyse relationships with exemplary selected health indicators (body mass index, self-reported health) to assess the validity of socio-demographic data measurements. RESULTS: On average, study participants were 52.0 years old (SD = 12.4). Of the participants, 53.6% were women, 54.3% had high education, 60.1% were married and 72% were employed while 3.4% were unemployed. Well-established correlations between socio-demographic factors and health could be reproduced with the German National Cohort data. For example, low education, old age and unemployment were associated with an increased prevalence of obesity and poor self-reported health. DISCUSSION: The German National Cohort provides a comprehensive measurement of socio-demographic characteristics. Combined with a wide range of health data and the longitudinal measurements available in the future, this opens up new opportunities for health science and social epidemiological research in Germany.

[Physical activity in the German National Cohort (NAKO): use of multiple assessment tools and initial results]. / Körperliche Aktivität in der NAKO Gesundheitsstudie: erste Ergebnisse des multimodalen Erhebungskonzepts.

BACKGROUND: Physical activity is a complex behavior that is difficult to measure validly and reliably in large, population-based studies. Data on physical activity are available for the initial 100,000 participants of the German National Cohort. OBJECTIVES: To describe the baseline physical activity assessment in the cohort and to present initial descriptive results. MATERIAL AND METHODS: Physical activity was assessed using a combination of tools, including two self-administered questionnaires, the Questionnaire on Annual Physical Activity Pattern (QUAP) and the Global Physical Activity Questionnaire (GPAQ); a computer-based 24­h physical activity recall (cpar24); and 7­day accelerometry (Actigraph GT3X/+; ActiGraph, Pensacola, FL, USA). RESULTS: The availability of data varied between assessment instruments (QUAP: n = 16,372; GPAQ: n = 90,900; cpar24: n = 23,989; accelerometry: n = 35,218). Analyses across measurement tools showed that on average, women spent 75 to 216 min/d, and men spent 73 to 224 min/d in moderate or higher intensity total physical activity. Persons aged 20-39 years spent 66 to 200 min/d, and persons aged 40-69 years spent 78 to 244 min/d in moderate or higher intensity total physical activity. CONCLUSIONS: Initial baseline analyses of physical activity in this cohort show the value of using a combination of questionnaires, 24­h recalls, and a movement sensor. The comprehensive data collection represents a valuable resource for future analyses and will improve our understanding of the association between physical activity and disease prevention.

[The baseline assessment of the German National Cohort (NAKO Gesundheitsstudie): participation in the examination modules, quality assurance, and the use of secondary data]. / Die Basiserhebung der NAKO Gesundheitsstudie: Teilnahme an den Untersuchungsmodulen, Qualitätssicherung und Nutzung von Sekundärdaten.

BACKGROUND: The German National Cohort (NAKO) is an interdisciplinary health study aimed at elucidating causes for common chronic diseases and detecting their preclinical stages. This article provides an overview of design, methods, participation in the examinations, and their quality assurance based on the midterm baseline dataset (MBD) of the recruitment. METHODS: More than 200,000 women and men aged 20-69 years derived from random samples of the German general population were recruited in 18 study centers (2014-2019). The data collection comprised physical examinations, standardized interviews and questionnaires, and the collection of biomedical samples for all participants (level 1). At least 20% of all participants received additional in-depth examinations (level 2), and 30,000 received whole-body magnet resonance imaging (MRI). Additional information will be collected through secondary data sources such as medical registries, health insurances, and pension funds. This overview is based on the MBD, which included 101,839 participants, of whom 11,371 received an MRI. RESULTS: The mean response proportion was 18%. The participation in the examinations was high with most of the modules performed by over 95%. Among MRI participants, 96% completed all 12 MRI sequences. More than 90% of the participants agreed to the use of complementary secondary and registry data. DISCUSSION: Individuals selected for the NAKO were willing to participate in all examinations despite the time-consuming program. The NAKO provides a central resource for population-based epidemiologic research and will contribute to developing innovative strategies for prevention, screening and prediction of chronic diseases.

Tuberculosis: cost of illness in Germany.

4,444 new cases of tuberculosis (TB) were reported in Germany in 2009; of those, the proportion of multidrug-resistant (MDR)-TB cases increased to 2.1% (63 cases). On the basis of the therapy guidelines of the German Central Committee against Tuberculosis and the new World Health Organization guidelines, this study estimates the mean direct outpatient and combined in- and outpatient costs of TB, together with other attributable costs of the disease on the basis of the most recent German official health statistics and scientific literature. According to this, the mean outpatient costs (rounded) per case were €1,197 (adults) and €1,006 (children) for standard therapy, but €36,543 for treatment of MDR-TB. The mean combined in-patient/outpatient costs were €7,364 (adults) and €7,300 (children), respectively; the combined costs for treatment of MDR-TB amounted to €52,259. Including MDR-TB cases the mean costs of treatment per TB case were €7,931. These are joined by the mean costs due to loss of productivity (€2,313), costs per case for rehabilitation (€74) and contact tracing (€922), adding up to €11,240. When considering the probability of increasing numbers of MDR-TB cases in the near future, TB is still a disease of significant economic impact in Germany.

Serial analysis of gene expression identifies metallothionein-II as major neuroprotective gene in mouse focal cerebral ischemia.

We applied serial analysis of gene expression (SAGE) to study differentially expressed genes in mouse brain 14 hr after the induction of focal cerebral ischemia. Analysis of >60,000 transcripts revealed 83 upregulated and 94 downregulated transcripts (more than or equal to eightfold). Reproducibility was demonstrated by performing SAGE in duplicate on the same starting material. Metallothionein-II (MT-II) was the most significantly upregulated transcript in the ischemic hemisphere. MT-I and MT-II are assumed to be induced by metals, glucocorticoids, and inflammatory signals in a coordinated manner, yet their function remains elusive. Upregulation of both MT-I and MT-II was confirmed by Northern blotting. MT-I and MT-II mRNA expression increased as early as 2 hr after 2 hr of transient ischemia, with a maximum after 16 hr. Western blotting and immunohistochemistry revealed MT-I/-II upregulation in the ischemic hemisphere, whereas double labeling demonstrated the colocalization of MT with markers for astrocytes as well as for monocytes/macrophages. MT-I- and MT-II-deficient mice developed approximately threefold larger infarcts than wild-type mice and a significantly worse neurological outcome. For the first time we make available a comprehensive data set on brain ischemic gene expression and underscore the important protective role of metallothioneins in ischemic damage of the brain. Our results demonstrate the usefulness of SAGE to screen functionally relevant genes and the power of knock-out models in linking function to expression data generated by high throughput techniques.