A reduced level of consciousness affects non-conscious processes.

Being conscious is a profound aspect of human existence, and understanding its function and its inception is considered one of the truly grand scientific challenges. However, the nature of consciousness remains enigmatic, to a large part because "being conscious" can refer to both the content (phenomenology) and the level (arousal) of consciousness, and how these different aspects are related remains unclear. To empirically assess the relation between level and content of consciousness, we manipulated these two aspects by presenting stimuli consciously or non-consciously and by using Propofol sedation, while brain activity was measured using fMRI. We observed that sedation affected both conscious and non-conscious processes but at different hierarchical levels; while conscious processing was altered in higher-order regions (the intraparietal sulcus) and spared sensory areas, the opposite effect was observed for non-conscious processing. The observation that Propofol affected non-conscious processing calls for a reconsideration of what kind of information one can gain on "consciousness" from recording neural responses to sedation without considering both (content) conscious and (content) non-conscious processing.

Development of an ICU discharge instrument predicting psychological morbidity: a multinational study.

PURPOSE: To develop an instrument for use at ICU discharge for prediction of psychological problems in ICU survivors. METHODS: Multinational, prospective cohort study in ten general ICUs in secondary and tertiary care hospitals in Sweden, Denmark and the Netherlands. Adult patients with an ICU stay ≥ 12 h were eligible for inclusion. Patients in need of neurointensive care, with documented cognitive impairment, unable to communicate in the local language, without a home address or with more than one limitation of therapy were excluded. Primary outcome was psychological morbidity 3 months after ICU discharge, defined as Hospital Anxiety and Depression Scale (HADS) subscale score ≥ 11 or Post-traumatic Stress Symptoms Checklist-14 (PTSS-14) part B score > 45. RESULTS: A total of 572 patients were included and 78% of patients alive at follow-up responded to questionnaires. Twenty percent were classified as having psychological problems post-ICU. Of 18 potential risk factors, four were included in the final prediction model after multivariable logistic regression analysis: symptoms of depression [odds ratio (OR) 1.29, 95% confidence interval (CI) 1.10-1.50], traumatic memories (OR 1.44, 95% CI 1.13-1.82), lack of social support (OR 3.28, 95% CI 1.47-7.32) and age (age-dependent OR, peak risk at age 49-65 years). The area under the receiver operating characteristics curve (AUC) for the instrument was 0.76 (95% CI 0.70-0.81). CONCLUSIONS: We developed an instrument to predict individual patients' risk for psychological problems 3 months post-ICU, http://www.imm.ki.se/biostatistics/calculators/psychmorb/ . The instrument can be used for triage of patients for psychological ICU follow-up. TRIAL REGISTRATION: The study was registered at clinicaltrials.gov, NCT02679157.

Islet autoantibodies and residual beta cell function in type 1 diabetes children followed for 3-6 years.

AIMS: To test if islet autoantibodies at diagnosis of type 1 diabetes (T1DM) and after 3-6 years with T1D predict residual beta-cell function (RBF) after 3-6 years with T1D. METHODS: T1D children (n=260, median age at diagnosis 9.4, range 0.9-14.7 years) were tested for GAD65, IA-2, ZnT8R, ZnT8W and ZnT8Q autoantibodies (A) at diagnosis, and 3-6 years after diagnosis when also fasting and stimulated RBF were determined. RESULTS: For every 1-year increase in age at diagnosis of TID, the odds of detectable C-peptide increased 1.21 (1.09, 1.34) times for fasting C-peptide and 1.28 (1.15, 1.42) times for stimulated C-peptide. Based on a linear model for subjects with no change in IA-2A levels, the odds of detectable C-peptide were 35% higher than for subjects whose IA-2A levels decreased by half (OR=1.35 (1.09, 1.67), p=0.006); similarly for ZnT8WA (OR=1.39 (1.09, 1.77), p=0.008) and ZnT8QA (OR=1.55 (1.06, 2.26) p=0.024). Such relationship was not detected for GADA or ZnT8RA. All OR adjusted for confounders. CONCLUSIONS: Age at diagnosis with T1D was the major predictor of detectable C-peptide 3-6 years post-diagnosis. Decreases in IA-2A, and possibly ZnT8A, levels between diagnosis and post-diagnosis were associated with a reduction in RBF post-diagnosis.

Severe traumatic brain injury: consequences of early adverse events.

BACKGROUND: Several factors associated with an unfavourable outcome after severe traumatic brain injury (TBI) have been described: prolonged pre-hospital time, secondary referral to a level 1 trauma centre, the occurrence of secondary insults such as hypoxia, hypotension or low end-tidal carbon dioxide (ETCO(2)). To determine whether adverse events were linked to outcome, patients with severe TBI were studied before arrival at a level 1 trauma centre. METHODS: Prospective, observational study design. Patients with severe TBI (n = 48), admitted to Umeå University Hospital between January 2002 to December 2005 were included. All medical records from the site of the accident to arrival at the level 1 trauma centre were collected and evaluated. RESULTS: A pre-hospital time of >60 min, secondary referral to a level 1 trauma centre, documented hypoxia (oxygen saturation <95%), hypotension (systolic blood pressure <90 mmHg), hyperventilation (ETCO(2) <4.5 kPa) or tachycardia (heart rate >100 beats/min) at any time before arrival at a level 1 trauma centre were not significantly related to an unfavourable outcome (Glasgow Outcome Scale 1-3). CONCLUSION: Early adverse events before arrival at a level 1 trauma centre were without significance for outcome after severe TBI in the trauma system studied.

No association of the IRS1 and PAX4 genes with type I diabetes.

To reassess earlier suggested type I diabetes (T1D) associations of the insulin receptor substrate 1 (IRS1) and the paired domain 4 gene (PAX4) genes, the Type I Diabetes Genetics Consortium (T1DGC) evaluated single-nucleotide polymorphisms (SNPs) covering the two genomic regions. Sixteen SNPs were evaluated for IRS1 and 10 for PAX4. Both genes are biological candidate genes for T1D. Genotyping was performed in 2300 T1D families on both Illumina and Sequenom genotyping platforms. Data quality and concordance between the platforms were assessed for each SNP. Transmission disequilibrium testing neither show T1D association of SNPs in the two genes, nor did haplotype analysis. In conclusion, the earlier suggested associations of IRS1 and PAX4 to T1D were not supported, suggesting that they may have been false positive results. This highlights the importance of thorough quality control, selection of tagging SNPs, more than one genotyping platform in high throughput studies, and sufficient power to draw solid conclusions in genetic studies of human complex diseases.

Functional SOCS1 polymorphisms are associated with variation in obesity in whites.

AIMS/HYPOTHESIS: The suppressor of cytokine signalling 1 (SOCS1) is a natural inhibitor of cytokine and insulin signalling pathways and may also play a role in obesity. In addition, SOCS1 is considered a candidate gene in the pathogenesis of both type 1 diabetes (T1D) and type 2 diabetes (T2D). The objective was to perform mutation analysis of SOCS1 and to test the identified variations for association to T2D-related quantitative traits, T2D or T1D. METHODS: Mutation scanning was performed by direct sequencing in 27 white Danish subjects. Genotyping was carried out by TaqMan allelic discrimination. A total of more than 8100 individuals were genotyped. RESULTS: Eight variations were identified in the 5' untranslated region (UTR) region. Two of these had allele frequencies below 1% and were not further examined. The six other variants were analysed in groups of T1D families (n = 1461 subjects) and T2D patients (n = 1430), glucose tolerant first-degree relatives of T2D patients (n = 212) and normal glucose tolerant (NGT) subjects. The rs33977706 polymorphism (-820G > T) was associated with a lower body mass index (BMI) (p = 0.004). In a second study (n = 4625 NGT subjects), significant associations of both the rs33977706 and the rs243330 (-1656G > A) variants to obesity were found (p = 0.047 and p = 0.015) respectively. The rs33977706 affected both binding of a nuclear protein to and the transcriptional activity of the SOCS1 promoter, indicating a relationship between this polymorphism and gene regulation. CONCLUSIONS/INTERPRETATION: This study demonstrates that functional variations in the SOCS1 promoter may associate with alterations in BMI in the general white population.

Identification of T1D susceptibility genes within the MHC region by combining protein interaction networks and SNP genotyping data.

AIM: To develop novel methods for identifying new genes that contribute to the risk of developing type 1 diabetes within the Major Histocompatibility Complex (MHC) region on chromosome 6, independently of the known linkage disequilibrium (LD) between human leucocyte antigen (HLA)-DRB1, -DQA1, -DQB1 genes. METHODS: We have developed a novel method that combines single nucleotide polymorphism (SNP) genotyping data with protein-protein interaction (ppi) networks to identify disease-associated network modules enriched for proteins encoded from the MHC region. Approximately 2500 SNPs located in the 4 Mb MHC region were analysed in 1000 affected offspring trios generated by the Type 1 Diabetes Genetics Consortium (T1DGC). The most associated SNP in each gene was chosen and genes were mapped to ppi networks for identification of interaction partners. The association testing and resulting interacting protein modules were statistically evaluated using permutation. RESULTS: A total of 151 genes could be mapped to nodes within the protein interaction network and their interaction partners were identified. Five protein interaction modules reached statistical significance using this approach. The identified proteins are well known in the pathogenesis of T1D, but the modules also contain additional candidates that have been implicated in beta-cell development and diabetic complications. CONCLUSIONS: The extensive LD within the MHC region makes it important to develop new methods for analysing genotyping data for identification of additional risk genes for T1D. Combining genetic data with knowledge about functional pathways provides new insight into mechanisms underlying T1D.