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Background Copy number variants (CNVs) have been associated with the risk of schizophrenia, autism and intellectual disability. However, little is known about their spectrum of psychopathology in adulthood. Methods We investigated the psychiatric phenotypes of adult CNV carriers and compared probands, who were ascertained through clinical genetics services, with carriers who were not. One hundred twenty-four adult participants (age 18–76), each bearing one of 15 rare CNVs, were recruited through a variety of sources including clinical genetics services, charities for carriers of genetic variants, and online advertising. A battery of psychiatric assessments was used to determine psychopathology. Results The frequencies of psychopathology were consistently higher for the CNV group compared to general population rates. We found particularly high rates of neurodevelopmental disorders (NDDs) (48%), mood disorders (42%), anxiety disorders (47%) and personality disorders (73%) as well as high rates of psychiatric multimorbidity (median number of diagnoses: 2 in non-probands, 3 in probands). NDDs [odds ratio (OR) = 4.67, 95% confidence interval (CI) 1.32–16.51; p = 0.017) and psychotic disorders (OR = 6.8, 95% CI 1.3–36.3; p = 0.025) occurred significantly more frequently in probands (N = 45; NDD: 39[87%]; psychosis: 8[18%]) than non-probands (N = 79; NDD: 20 [25%]; psychosis: 3[4%]). Participants also had somatic diagnoses pertaining to all organ systems, particularly conotruncal cardiac malformations (in individuals with 22q11.2 deletion syndrome specifically), musculoskeletal, immunological, and endocrine diseases. Conclusions Adult CNV carriers had a markedly increased rate of anxiety and personality disorders not previously reported and high rates of psychiatric multimorbidity. Our findings support in-depth psychiatric and medical assessments of carriers of CNVs and the establishment of multidisciplinary clinical services.

Connected vehicle (CV) technology has the potential to greatly improve the safety, mobility, and environmental sustainability of traffic. Many CV applications require the vehicle position as input, which is primarily provided by global navigation satellite systems (GNSS). Although a large number of those applications (e.g., Intersection Movement Assist) require vehicle positioning to have lane-level accuracy, it has been shown that the type of positioning system typically used by CVs currently cannot provide consistent lane-level accuracy, even under open-sky conditions. In order to address this gap, we have evaluated an enhanced positioning system that adds little, if any, to the cost of the CV. It consists of a single-frequency real-time kinematic (RTK)-capable GNSS receiver onboard the vehicle, which utilizes Radio Technical Commission for Maritime Services (RTCM) differential corrections transmitted over dedicated short-range communications (DSRC) by the roadside infrastructure. Tests on a moving vehicle show that this system could provide lane-level accuracy over 95% of the time in open-sky conditions. These tests also show the DSRC to be an effective means of disseminating RTCM corrections, given the intersection spacings and communication ranges in the test. However, neither RTCM nor the more commonly used space-based augmentation system (SBAS) differential corrections appeared to improve the positioning accuracy of GNSS in urban canyons.

This essay radically re-conceptualises architecture as a psycho-social subject entwined with the psychology of its creators and inhabitants. Seeking to understand the psychology of architecture, it discusses innovative, transdisciplinary, practice-based methods derived from psycho-social studies, psychoanalysis, and conceptual art, to explore the consciousness and unconsciousness of buildings. It then tests those methods on a case-study example – Oscar Niemeyer’s Communist Party headquarters in Paris – to speculate how psychological profiling may lead to a deeper understanding of the entangled human/non-human relations within a building, while also revealing potentials for therapeutic adaptation or reuse.The essay’s principal contribution is the re-conceptualisation of architecture as having profound and active psychological dimensions – the awareness and management of which potentially impacts upon liveability and lifespan – aided by a set of methods with which to reveal those psychological dimensions. It thus expands the scope for processes of architectural practice and contributes to transdisciplinarity within conceptual art.

Background/Aims Interleukin-27 (IL-27) regulates adaptive immune responses and is critical for the timely resolution of inflammation to restore tissue homeostasis. Studies have highlighted roles for IL-27 in limiting immune cell effector function, stromal cell responses and erosive joint pathology in clinical rheumatoid arthritis and experimental models of the disease. In the murine antigen-induced arthritis (AIA) model, IL-27 receptor-deficient (Il27ra-/-) mice develop severe synovitis associated with increased infiltration of synovial CD4+ T cells, development of synovial ectopic lymphoid-like structures and exacerbated cartilage and bone erosion. Similarly, mice with collagen-induced arthritis (CIA) administered IL-27 show improved joint pathology and reduced serum IFN-γ and IL-17 levels. Identifying mechanisms by which IL-27 regulates arthritis progression is key to understanding its therapeutic potential. Using RNA-sequencing of synovial tissue and joint-infiltrating CD4+ T cells we reveal that IL-27 regulates the magnitude of synovitis and genes in CD4+ T cells central to neutrophil recruitment. Methods Antigen-induced arthritis (AIA) was established in Il27ra-/- and wild-type control mice. RNA-sequencing was performed on whole synovial tissue and joint-infiltrating CD4+ T cells during the peak of joint inflammation and during the resolution of synovitis. Differentially expressed genes were interrogated by molecular pathway analysis and gene set enrichment analysis. CD4+ T cell culture assays, qPCR and ELISA were used to test and validate genes under IL-27 regulation. Results RNA-sequencing of whole synovial tissue revealed that pathways relating to CD4+ T cell and Th17 biology were significantly overrepresented in Il27ra-/- mice with AIA, consistent with a pathogenic role for these cells in inflammatory arthritis. Genes associated with neutrophil effector function (e.g. Elane, Padi4, Prtn3) and recruitment (e.g. Cxcl1, Cxcr2) were also highly expressed in Il27ra-/- synovium and was reflected in the increased number of Ly6G+CD11b+ neutrophils recovered from the joints of Il27ra-/- mice. In contrast to the transcriptomic analysis of inflamed synovial tissue, surprisingly RNA-sequencing of joint-infiltrating CD4+ T cells revealed that the expression of signature Th17 genes (e.g. Il17a, Il17f, Rorc) was comparable between WT and Il27ra-/- T cells. This implies that IL-27 predominantly regulates the magnitude of the joint CD4+ T cell infiltrate more than the effector characteristics of the infiltrating T cells. Differential gene expression analysis revealed heightened Cxcl1 expression in both whole synovial tissue and joint-infiltrating CD4+ T cells recovered from Il27ra-/- mice with AIA. CD4+ T cell differentiation cultures confirmed upregulation of Cxcl1 following T cell receptor activation and under Th1 polarizing conditions. Here, IL-27 suppressed the expression of CXCL1 at the mRNA and protein level. Conclusion Together, our data reveals a role for IL-27 in limiting CXCL1 expression in activated and joint-infiltrating CD4+ T cells, highlighting a novel mechanism by which IL-27 may integrate innate and adaptive arms of the immune response to regulate arthritis progression. Disclosure I. Burridge: None. S. Eastham: None. D.G. Hill: None. R. Andrews: None. B. Szomolay: None. N. Williams: None. S.A. Jones: None. G.W. Jones: None.

Introduction Bile acid diarrhoea (BAD) can occur due to disruption to the enterohepatic circulation such as following cholecystectomy. However, the mechanism behind this is as yet unknown. The aim of this study was to determine the rate of post-cholecystectomy diarrhoea and to assess whether FGF19 within the gallbladder was associated with the development of BAD. Methods This was a prospective case-control study in which patients were assessed pre- and post- cholecystectomy (study group) and compared with patients also having laparoscopic surgery but not cholecystectomy (control group). Their bowel habits and a GIQLI questionnaire was performed to compare the pre- and post-operative condition of the two groups. Gallbladder tissue sample was tested for FGF19 and PPARα in the study group patients. A subset had serum lipid levels, FGF19 and C4 measurements. Results Gallbladder PPAR α was found to have a significant correlation with stool consistency, with the lower the PPARα concentration the higher the Bristol stool chart number (i.e. looser stool). There were no significant correlation when assessing the effect of gallbladder FGF19 concentration on bowel habit, stool consistency, lipid levels, BMI or smoking. The study group showed a significant increase in triglycerides post-operatively, however there were no changes in cholesterol, HDL and LDL levels. Correlation of the increased triglyceride levels with GIQLI, stool consistency and frequency showed no significant results. Discussion and conclusion While there is a general improvement in post operative quality of life, we did not find any direct evidence that FGF19 levels within the gallbladder impact the development of post-cholecystectomy diarrhoea. There was however a significant increase in triglycerides postoperatively. There was also no correlation with PPARα suggesting the observed rise is independent of this pathway. Further work is required particularly relating to the gut microbiome to further investigate this condition.

BackgroundPatients with Parkinson’s disease (PD) have variable rates of progression. More accurate prediction of progression could improve selection for clinical trials. Although some variance in clinical progression can be predicted by age at onset and phenotype, we hypothesise that this can be further improved by blood biomarkers.ObjectiveTo determine if blood biomarkers (serum neurofilament light (NfL) and genetic status (glucocerebrosidase,GBAand apolipoprotein E (APOE))) are useful in addition to clinical measures for prognostic modelling in PD.MethodsWe evaluated the relationship between serum NfL and baseline and longitudinal clinical measures as well as patients’ genetic (GBAandAPOE) status. We classified patients as having a favourable or an unfavourable outcome based on a previously validated model, and explored how blood biomarkers compared with clinical variables in distinguishing prognostic phenotypes .Results291 patients were assessed in this study. Baseline serum NfL was associated with baseline cognitive status. Nfl predicted a shorter time to dementia, postural instability and death (dementia—HR 2.64; postural instability—HR 1.32; mortality—HR 1.89) whereas APOEe4 status was associated with progression to dementia (dementia—HR 3.12, 95% CI 1.63 to 6.00). NfL levels and genetic variables predicted unfavourable progression to a similar extent as clinical predictors. The combination of clinical, NfL and genetic data produced a stronger prediction of unfavourable outcomes compared with age and gender (area under the curve: 0.74-age/gender vs 0.84-ALL p=0.0103).ConclusionsClinical trials of disease-modifying therapies might usefully stratify patients using clinical, genetic and NfL status at the time of recruitment.

Psychosis is an encumbering cluster of mental illnesses which has a significant impact on the daily life of individuals. Recovery from psychosis is a personalised process due to the unique nature of the lived experiences of these individuals. Although numerous research have been conducted, there exists a research gap in taking into consideration the perspectives of practitioners in treating the illness. This study aimed to identify the perspectives of psychologists on the impact of interpersonal and intrapersonal factors that impact recovery from psychosis. Five participants were interviewed to qualitatively explore this utilising Interpretative Phenomenological Analysis (IPA). Findings suggested that recovery from psychosis can occur on four different dimensions; Behavioural, Insight, Cognitive, and Social Recovery. There are several interpersonal and intrapersonal factors impacting these dimensions collaboratively. An Integrated Recovery Model was generated to summarise these findings which could potentially assist the recovery process of individuals. Limitations of the study and future implications were also addressed.

To date, numerous cooperative merging techniques have been developed, with multiple studies demonstrating their potential to improve traffic safety, efficiency, and environmental impact at merging points. However, many of these techniques make assumptions that will almost certainly be questionable in the real world, namely: 1) relative positioning between vehicles will be sufficiently accurate at all times; 2) the merging application-equipped vehicles will not change lanes before reaching the merge point, nor will other vehicles change lanes into their lane; and 3) vehicles with merging-assist technology will not mix with vehicles without the technology. This paper proposes a cooperative merging application which is capable of functioning even when the vehicles positioning accuracy is severely degraded and all vehicles are free to change lanes into and out of the merging traffic streams. Furthermore, our strategy demonstrates safety, efficiency, and environmental benefits for the overall traffic stream even with technology penetration rates as low as 20%.

Biomarkers to aid diagnosis and delineate the progression of Parkinson’s disease are vital for targeting treatment in the early phases of the disease. Here, we aim to discover a multi-protein panel representative of Parkinson’s and make mechanistic inferences from protein expression profiles within the broader objective of finding novel biomarkers. We used aptamer-based technology (SomaLogic®) to measure proteins in 1599 serum samples, 85 cerebrospinal fluid samples and 37 brain tissue samples collected from two observational longitudinal cohorts (the Oxford Parkinson’s Disease Centre and Tracking Parkinson’s) and the Parkinson’s Disease Brain Bank, respectively. Random forest machine learning was performed to discover new proteins related to disease status and generate multi-protein expression signatures with potential novel biomarkers. Differential regulation analysis and pathway analysis were performed to identify functional and mechanistic disease associations. The most consistent diagnostic classifier signature was tested across modalities [cerebrospinal fluid (area under curve) = 0.74, P = 0.0009; brain area under curve = 0.75, P = 0.006; serum area under curve = 0.66, P = 0.0002]. Focusing on serum samples and using only those with severe disease compared with controls increased the area under curve to 0.72 (P = 1.0 × 10−4). In the validation data set, we showed that the same classifiers were significantly related to disease status (P < 0.001). Differential expression analysis and weighted gene correlation network analysis highlighted key proteins and pathways with known relationships to Parkinson’s. Proteins from the complement and coagulation cascades suggest a disease relationship to immune response. The combined analytical approaches in a relatively large number of samples, across tissue types, with replication and validation, provide mechanistic insights into the disease as well as nominate a protein signature classifier that deserves further biomarker evaluation.

ObjectivesTo explore the genetics of four Parkinson’s disease (PD) subtypes that have been previously described in two large cohorts of patients with recently diagnosed PD. These subtypes came from a data-driven cluster analysis of phenotypic variables.MethodsWe looked at the frequency of genetic mutations in glucocerebrosidase (GBA) and leucine-rich repeat kinase 2 against our subtypes. Then we calculated Genetic Risk Scores (GRS) for PD, multiple system atrophy, progressive supranuclear palsy, Lewy body dementia, and Alzheimer’s disease. These GRSs were regressed against the probability of belonging to a subtype in the two independent cohorts and we calculated q-values as an adjustment for multiple testing across four subtypes. We also carried out a Genome-Wide Association Study (GWAS) of belonging to a subtype.ResultsA severe disease subtype had the highest rates of patients carrying GBA mutations while the mild disease subtype had the lowest rates (p=0.009). Using the GRS, we found a severe disease subtype had a reduced genetic risk of PD (p=0.004 and q=0.015). In our GWAS no individual variants met genome wide significance (ConclusionsWe have found that four previously defined PD subtypes have different genetic determinants which will help to inform future studies looking at underlying disease mechanisms and pathogenesis in these different subtypes of disease.

Children with rare neurodevelopmental genetic conditions (ND-GCs) are at high risk for a range of neuropsychiatric conditions. Sleep symptomatology may represent a transdiagnostic risk indicator within this patient group. Here we present data from 629 children with ND-GCs, recruited via the United Kingdom’s National Health Service medical genetic clinics. Sibling controls (183) were also invited to take part. Detailed assessments were conducted to characterise the sleep phenotype of children with ND-GCs in comparison to controls. Latent class analysis was conducted to derive subgroups of children with a ND-GC based on sleep symptomatology. Assessment of cognition and psychopathology allowed investigation of whether sleep phenotypic subgroup was associated with neuropsychiatric outcomes. We found that children with a ND-GC, when compared to control siblings, were at elevated risk of insomnia (ND-GC = 41% vs Controls = 17%, p

Many Connected Vehicle (CV) applications, including safety-critical ones such as collision warning, require lane-level positioning accuracy to function correctly. However, differential GNSS, the primary positioning method used by CVs in current deployments across the U.S., cannot always provide this level of accuracy. This is particularly true in urban environments. Alternative positioning methods or strategies must be developed to fill this gap. To determine what strategies are appropriate, we first identify the positioning requirements of each CV application listed in the USDOT?s Connected Vehicle Reference Implementation Architecture (CVRIA). These requirements include accuracy, integrity, update rate, and type of positioning (relative or absolute). Based on our overall analysis, we recommend two general positioning strategies: 1) utilize other sources of positioning information whenever possible (particularly at intersections), and 2) estimate the uncertainty of the positioning solution and use this uncertainty as an input to CV applications themselves.

This article investigates the similarities and differences for tangible and intangible elements (factors and language use) contributing to placemaking in Airbnb English language reviews in Paris (59,057 reviews), Barcelona (19,291 reviews) and London (30,403 reviews). This paper contributes to provide new insights on the narrative construction of reputational capital which is connected to placemaking strategies. A combined quantitative approach using large scale text analysis enabled the analysis of review content and style. Patterns in the words usage were identified. Findings suggest that tangible and intangible elements work together in the discourse, contributing to the place-narrative built on the host’s reputational capital. The host-guest interaction is the main aspect of the reviews, followed by the importance of transport and local amenities. Cities have different profiles in the composition of the word clusters which indicates differences in the guests’ perceived experience. Keywords: Hospitality; Sharing economy; Placemaking; Airbnb, Narrative, Reputational capital

Biomarkers to aid diagnosis and delineate progression of Parkinson’s Disease (PD) are vital for targeting treatment in the early phases of disease. Here, we aim to discover a multi-protein panel representative of PD and make mechanistic inferences from protein expression profiles within the broader objective of finding novel biomarkers.We used aptamer-based technology (SomaLogic®) to measure proteins in 1,599 serum samples, 85 CSF samples and 37 brain tissue samples collected from two observational longitudinal cohorts (Oxford Parkinson’s Disease Centre and Tracking Parkinson’s) and the PD Brain Bank, respectively. Random forest machine learning was performed to discover new proteins related to disease status and generate multi-protein expression signatures with potential novel biomarkers. Differential regulation analysis and pathway analysis was performed to identify functional and mechanistic disease associations.The most consistent diagnostic classifier signature was tested across modalities (CSF AUC = 0.74, p-value = 0.0009; brain AUC = 0.75, p-value = 0.006; serum AUC = 0.66, p-value = 0.0002). In the validation dataset we showed that the same classifiers were significantly related to disease status (p-values < 0.001). Differential expression analysis and Weighted Gene Correlation Network Analysis (WGCNA) highlighted key proteins and pathways with known relationships to PD. Proteins from the complement and coagulation cascades suggest a disease relationship to immune response.The combined analytical approaches in a relatively large number of samples, across tissue types, with replication and validation, provides mechanistic insights into the disease as well as nominating a protein signature classifier that deserves further biomarker evaluation.

BackgroundPatients with Parkinson’s disease (PD) have variable disease progression. More accurate prediction of progression could improve clinical trial design. Although some variance in clinical progression can be predicted by age at onset and phenotype, we hypothesise that this can be improved by blood biomarkers.ObjectiveTo determine if serum neurofilament light (NfL) is a useful biomarker for prognostic modelling in PD.MethodsWe evaluated the relationship between serum NfL and baseline and longitudinal clinical measures as well as patients’ genetic (GBA and APOE) status in a large clinical dataset. We classified patients as having a favourable or an unfavourable outcome based on a previously validated model and explored whether serum NfL could distinguish prognostic phenotypes. We compared NfL with baseline candidate predictor variables and studied the combination of clinical, serum and genetic data.ResultsSerum NfL was associated with patients’ cognitive status at baseline. Baseline NfL was associated with the progression of motor and functional impairment and with increased mortality (Survival HR 1.85, CI: 1.03-3.33, p=0.04). Baseline NfL levels predicted unfavourable progression to a similar extent as previously validated clinical predictors (AUC: 0.74 vs 0.78, p=0.22). The combination of clinical, genetic and biomarker data produced a strong predication of unfavourable outcomes as compared to age and gender alone (AUC: 0.71-age/gender vs 0.83-ALL p = 0.0076)ConclusionsBaseline serum NfL provides an objective measure of neurodegeneration in PD patients. Clinical trials of disease-modifying therapies might usefully stratify patients according using clinical, genetic and NfL status at the time of recruitment.

Surface transportation accounts for a large fraction of greenhouse gas emissions around the world. Vehicles powered by internal combustion engines are becoming increasingly fuel efficient and produce less emissions through a number of technological improvements. One technology category is providing real-time “eco-driving” feedback to drivers, so that they drive more efficiently. Since hard accelerations have a major effect on vehicle fuel consumption and emissions, some eco-driving systems have been developed to provide drivers with feedback through the accelerator pedal in order to mitigate these events. This study evaluates one such system called the Reactive Force Pedal (RFP) that provides different degrees of force feedback to the driver. This study examined two levels of force feedback (LOW and HIGH) that were applied to 40 drivers while driving on a prescribed route in Southern California. Detailed driving data (speed, acceleration, fuel consumption, etc.) were collected for baseline, LOW RFP, and HIGH RFP settings, and subsequently compared. The data were also used to compare different emission models in order to gain insight on future scenario estimation methods. The results show that there is 2% - 3% improvement in fuel economy with the LOW setting, and approximately 3% - 5% improvement with the HIGH setting, when consider positive acceleration events. The technology has different effects among different drivers.

While technologies such as adaptive cruise control and platooning can increase energy efficiency of freight trucks on highways, to date less attention has been given to technologies that can improve energy efficient of these trucks during their first-mile/last-mile operations. In this paper, we present a Connected Vehicle-based truck eco-driving system, called Eco-Drive, which uses Signal Phase and Timing (SPaT) information from the upcoming traffic signal along with the information about the equipped vehicle and preceding traffic to determine the most energy-efficient speed trajectory to pass through the intersection. The system is pre-calibrated using real-world acceleration and deceleration profile data to create a graph-based vehicle trajectory planning algorithm. A machine learning algorithm is then developed and trained to enable a fast and accurate determination of optimal vehicle trajectory. During the operation, the system uses real-time information about the host vehicle, SPaT, and preceding traffic to optimize vehicle trajectory for energy while ensuring a safe passage through the intersection. The system evaluation in traffic microsimulation environment shows that the proposed system provides statistically significant energy savings for the host vehicle, while maintaining similar travel time, as a result of reduced number of stops and milder acceleration/deceleration. The results presented are specific to the simulation settings used in this paper. More research is needed to better understand the levels of energy savings that the proposed system could provide under a wide variety of settings.

Background The length of the HTT CAG repeat explains around 60% of the variance in Huntington’s disease (HD) age at onset. Recently, genome-wide association studies (GWAS) of HD age at onset have identified multiple single nucleotide variants (SNVs) that influence onset, including an intronic SNV, rs79727797, in TCERG1 (p=3.76E-10). Aims Since the SNV does not modify the protein or appear to change gene expression, we tested whether the GWAS signal is due to genetic variation not present in the GWAS. Methods/Techniques We developed a novel method for calling perfect and imperfect short tandem repeats from whole exome sequencing (WES) data, and applied it to 610 WES samples from HD individuals with age at onset or cognitive test data discrepant from those predicted by their HTT CAG length. We identified an exonic (CAGGCC)n short tandem repeat in TCERG1 previously reported to be associated with altered HD age at onset. The reference allele is (CAGGCC)6. We identified 5 length alleles with 3 to 8 hexamer repeats. Results/Outcome Reduced repeat length is significantly associated with later HD age-at-onset (sum of repeat from both TCERG1 repeat alleles: p=6.51E-9). The (CAGGCC)3 allele (frequency 4.1%) is in linkage disequilibrium (r2=0.98) with the minor allele at rs79727797, associated with later onset in the GWAS. Conditioning the association of rs79727797 on TCERG1 (CAGGCC)n length reduces its significance from p=2.4E-6 to p=0.96, while STR length is still significantly associated with HD age at onset after conditioning on rs79727797 (p=3.9E-4). This indicates that the repeat, rather than rs79727797, is responsible for the association at this locus. Conclusion The GWAS signal in TCERG1 is attributable to a short tandem repeat, rather than SNVs. Further biological study of the mechanism by which it alters HD age at onset is warranted.

Introduction Bile acid diarrhoea (BAD) can occur due to disruption to the enterohepatic circulation, e.g. following cholecystectomy. Post-cholecystectomy diarrhoea has been reported in 2.1–57.2% of patients; however, this is not necessarily due to BAD. The aim of this study was to determine the rates of bile acid diarrhoea diagnosis after cholecystectomy and to consider investigation practices. Methods A retrospective analysis of electronic databases from five large centres detailing patients who underwent laparoscopic cholecystectomy between 2013 and 2017 was cross-referenced with a list of patients who underwent 75SeHCAT testing. A 7-day retention time of p Results A total of 9439 patients underwent a laparoscopic cholecystectomy between 1 January 2013 and 31 December 2017 in the five centres. In total, 202 patients (2.1%) underwent investigation for diarrhoea via 75SeHCAT, of which 64 patients (31.6%) had a 75SeHCAT test result of >15%, while 62.8% of those investigated were diagnosed with bile acid diarrhoea (BAD). In total, 133 (65.8%) patients also underwent endoscopy and 74 (36.6%) patients had a CT scan. Median time from surgery to 75SeHCAT test was 672 days (SD ± 482 days). Discussion/Conclusion Only a small proportion of patients, post-cholecystectomy, were investigated for diarrhoea with significant time delay to diagnosis. The true prevalence of BAD after cholecystectomy may be much higher, and clinicians need to have an increased awareness of this condition due to its amenability to treatment. 75SeHCAT is a useful tool for diagnosis of bile acid diarrhoea.

BackgroundHuntington’s disease is caused by an expanded CAG tract in HTT. The length of the CAG tract accounts for over half the variance in age at onset of disease, and is influenced by other genetic factors, mostly implicating the DNA maintenance machinery. We examined a single nucleotide variant, rs79727797, on chromosome 5 in the TCERG1 gene, previously reported to be associated with Huntington’s disease and a quasi-tandem repeat (QTR) hexamer in exon 4 of TCERG1 with a central pure repeat.MethodsWe developed a novel method for calling perfect and imperfect repeats from exome sequencing data, and tested association between the QTR in TCERG1 and residual age at motor onset (after correcting for the effects of CAG length in the HTT gene) in 610 individuals with Huntington’s disease via regression analysis.ResultsWe found a significant association between age at onset and the sum of the repeat lengths from both alleles of the QTR (p = 2.1×10−9), with each added repeat hexamer reducing age at onset by one year (95% confidence interval [0.7, 1.4]). This association explained that previously observed with rs79727797.ConclusionsThe association with age at onset in the genome-wide association study is due to a QTR hexamer in TCERG1, translated to a glutamine/alanine tract in the protein. We could not distinguish whether this was due to cis-effects of the hexamer repeat on gene expression or of the encoded glutamine/alanine tract in the protein. These results motivate further study of the mechanisms by which TCERG1 modifies onset of HD.

The CNS has traditionally been considered an immune privileged site, but is now understood to have a system of immune surveillance, predominantly involving CD4+ T-cells. Identifying functional differences between CNS and blood CD4+ T-cells, therefore, have relevance to CNS immune surveillance as well as to neurological conditions, such as multiple sclerosis, in which CD4+ T-cells play a central role. Here, CD4+ T-cells were purified from CSF and blood from 21 patients with newly diagnosed treatment-naïve multiple sclerosis and 20 individuals with non-inflammatory disorders using fluorescence-activated cell sorting, and their transcriptomes were profiled by RNA sequencing. Paired comparisons between CD4+ T-cells from CSF and blood identified 5156 differentially expressed genes in controls and 4263 differentially expressed in multiple sclerosis patients at false discovery rate, Hrastelj et al. report the largest transcriptomic comparison of CSF and blood CD4+ T-cells to date. The study identifies thousands of significant genes, implicating cellular migration and cholesterol metabolism, as well as Th1, Th17 and effector memory function in immune surveillance of the CNS in multiple sclerosis and controls., Graphical Abstract Graphical Abstract