Population-scale tissue transcriptomics maps long non-coding RNAs to complex disease.

Long non-coding RNA (lncRNA) genes have well-established and important impacts on molecular and cellular functions. However, among the thousands of lncRNA genes, it is still a major challenge to identify the subset with disease or trait relevance. To systematically characterize these lncRNA genes, we used Genotype Tissue Expression (GTEx) project v8 genetic and multi-tissue transcriptomic data to profile the expression, genetic regulation, cellular contexts, and trait associations of 14,100 lncRNA genes across 49 tissues for 101 distinct complex genetic traits. Using these approaches, we identified 1,432 lncRNA gene-trait associations, 800 of which were not explained by stronger effects of neighboring protein-coding genes. This included associations between lncRNA quantitative trait loci and inflammatory bowel disease, type 1 and type 2 diabetes, and coronary artery disease, as well as rare variant associations to body mass index.

Metabolomic identification of α-ketoglutaric acid elevation in pediatric chronic graft-versus-host disease.

Chronic graft-versus-host disease (cGVHD) is the most common cause for non-relapse mortality postallogeneic hematopoietic stem cell transplant (HSCT). However, there are no well-defined biomarkers for cGVHD or late acute GVHD (aGVHD). This study is a longitudinal evaluation of metabolomic patterns of cGVHD and late aGVHD in pediatric HSCT recipients. A quantitative analysis of plasma metabolites was performed on 222 evaluable pediatric subjects from the ABLE/PBMTC1202 study. We performed a risk-assignment analysis at day + 100 (D100) on subjects who later developed either cGVHD or late aGVHD after day 114 to non-cGVHD controls. A second analysis at diagnosis used fixed and mixed multiple regression to compare cGVHD at onset to time-matched non-cGVHD controls. A metabolomic biomarker was considered biologically relevant only if it met all 3 selection criteria: (1) P ≤ .05; (2) effect ratio of ≥1.3 or ≤0.75; and (3) receiver operator characteristic AUC ≥0.60. We found a consistent elevation in plasma α-ketoglutaric acid before (D100) and at the onset of cGVHD, not impacted by cGVHD severity, pubertal status, or previous aGVHD. In addition, late aGVHD had a unique metabolomic pattern at D100 compared with cGVHD. Additional metabolomic correlation patterns were seen with the clinical presentation of pulmonary, de novo, and progressive cGVHD. α-ketoglutaric acid emerged as the single most significant metabolite associated with cGVHD, both in the D100 risk-assignment and later diagnostic onset analysis. These distinctive metabolic patterns may lead to improved subclassification of cGVHD. Future validation of these exploratory results is needed. This trial was registered at www.clinicaltrials.gov as #NCT02067832.

Cascading epigenomic analysis for identifying disease genes from the regulatory landscape of GWAS variants.

The majority of genetic variants detected in genome wide association studies (GWAS) exert their effects on phenotypes through gene regulation. Motivated by this observation, we propose a multi-omic integration method that models the cascading effects of genetic variants from epigenome to transcriptome and eventually to the phenome in identifying target genes influenced by risk alleles. This cascading epigenomic analysis for GWAS, which we refer to as CEWAS, comprises two types of models: one for linking cis genetic effects to epigenomic variation and another for linking cis epigenomic variation to gene expression. Applying these models in cascade to GWAS summary statistics generates gene level statistics that reflect genetically-driven epigenomic effects. We show on sixteen brain-related GWAS that CEWAS provides higher gene detection rate than related methods, and finds disease relevant genes and gene sets that point toward less explored biological processes. CEWAS thus presents a novel means for exploring the regulatory landscape of GWAS variants in uncovering disease mechanisms.

CD56bright CD16- natural killer cells as an important regulatory mechanism in chronic graft-versus-host disease.

Chronic graft-versus-host disease (cGvHD) is a major cause of morbidity after hematopoietic stem cell transplantation (HSCT). In large patient populations, we have shown a CD56bright natural killer (NK) population to strongly associate with a lack of cGvHD and we hypothesize that these cells function to suppress cGvHD. We aimed to isolate and define the characteristics of regulatory NK (NKreg) cells associated with suppression of cGvHD. Immunophenotypic evaluation of a large pediatric population found the CD56bright NK population associated with a lack of cGvHD to be perforin-, Granzyme B-, and CD335+. Transcriptome analysis of a small patient cohort of CD56bright compared to CD56dim NK cells found the NKreg cells to also overexpress Granzyme K, IL-7R, GPR183, RANK, GM-CSFR, TCF7, and IL23A. Further analysis of this CD56bright NKreg population found a subpopulation that overexpressed IRF1, and TNF. We also found that viable NKreg cells may be isolated by sorting on CD56+ and CD16- NK cells, and this population can suppress allogeneic CD4+ T cells, but not Treg cells or CD8+ T cells through a non-cytolytic, cell-cell contact dependent mechanism. Suppression was not reliant upon the NKp44, NKp46, or GPR183 receptors. Additionally, NKreg cells do not kill leukemic cells. Moreover, this is the first paper to clearly establish that a CD56brightCD3-CD16-perforin- NKreg population associates with a lack of cGvHD and has several unique characteristics, including the suppression of helper T-cell function in vitro. With further investigation we may decipher the mechanism of NKreg suppression and operationalize expansion of NKreg cells associated with cGvHD suppression.

Deep learning of immune cell differentiation.

Although we know many sequence-specific transcription factors (TFs), how the DNA sequence of cis-regulatory elements is decoded and orchestrated on the genome scale to determine immune cell differentiation is beyond our grasp. Leveraging a granular atlas of chromatin accessibility across 81 immune cell types, we asked if a convolutional neural network (CNN) could learn to infer cell type-specific chromatin accessibility solely from regulatory DNA sequences. With a tailored architecture and an ensemble approach to CNN parameter interpretation, we show that our trained network ("AI-TAC") does so by rediscovering ab initio the binding motifs for known regulators and some unknown ones. Motifs whose importance is learned virtually as functionally important overlap strikingly well with positions determined by chromatin immunoprecipitation for several TFs. AI-TAC establishes a hierarchy of TFs and their interactions that drives lineage specification and also identifies stage-specific interactions, like Pax5/Ebf1 vs. Pax5/Prdm1, or the role of different NF-κB dimers in different cell types. AI-TAC assigns Spi1/Cebp and Pax5/Ebf1 as the drivers necessary for myeloid and B lineage fates, respectively, but no factors seemed as dominantly required for T cell differentiation, which may represent a fall-back pathway. Mouse-trained AI-TAC can parse human DNA, revealing a strikingly similar ranking of influential TFs and providing additional support that AI-TAC is a generalizable regulatory sequence decoder. Thus, deep learning can reveal the regulatory syntax predictive of the full differentiative complexity of the immune system.

Gene expression profiles complement the analysis of genomic modifiers of the clinical onset of Huntington disease.

Huntington disease (HD) is a neurodegenerative disorder that is caused by a CAG repeat expansion in HTT. The length of this repeat, however, only explains a proportion of the variability in age of onset in patients. Genome-wide association studies have identified modifiers that contribute toward a proportion of the observed variance. By incorporating tissue-specific transcriptomic information with these results, additional modifiers can be identified. We performed a transcriptome-wide association study assessing heritable differences in genetically determined expression in diverse tissues, with genome-wide data from over 4000 patients. Functional validation of prioritized genes was undertaken in isogenic HD stem cells and patient brains. Enrichment analyses were performed with biologically relevant gene sets to identify the core pathways. HD-associated gene coexpression modules were assessed for associations with neurological phenotypes in an independent cohort and to guide drug repurposing analyses. Transcriptomic analyses identified genes that were associated with age of HD onset and displayed colocalization with gene expression signals in brain tissue (FAN1, GPR161, PMS2, SUMF2), with supporting evidence from functional experiments. This included genes involved in DNA repair, as well as novel-candidate modifier genes that have been associated with other neurological conditions. Further, cortical coexpression modules were also associated with cognitive decline and HD-related traits in a longitudinal cohort. In summary, the combination of population-scale gene expression information with HD patient genomic data identified novel modifier genes for the disorder. Further, these analyses expanded the pathways potentially involved in modifying HD onset and prioritized candidate therapeutics for future study.

Using Transcriptomic Hidden Variables to Infer Context-Specific Genotype Effects in the Brain.

Deciphering the environmental contexts at which genetic effects are most prominent is central for making full use of GWAS results in follow-up experiment design and treatment development. However, measuring a large number of environmental factors at high granularity might not always be feasible. Instead, here we propose extracting cellular embedding of environmental factors from gene expression data by using latent variable (LV) analysis and taking these LVs as environmental proxies in detecting gene-by-environment (GxE) interaction effects on gene expression, i.e., GxE expression quantitative trait loci (eQTLs). Applying this approach to two largest brain eQTL datasets (n = 1,100), we show that LVs and GxE eQTLs in one dataset replicate well in the other dataset. Combining the two samples via meta-analysis, 895 GxE eQTLs are identified. On average, GxE effect explains an additional ∼4% variation in expression of each gene that displays a GxE effect. Ten of these 52 genes are associated with cell-type-specific eQTLs, and the remaining genes are multi-functional. Furthermore, after substituting LVs with expression of transcription factors (TF), we found 91 TF-specific eQTLs, which demonstrates an important use of our brain GxE eQTLs.

Risk of venous and arterial thromboembolism in patients with giant cell arteritis and/or polymyalgia rheumatica: A Veterans Health Administration population-based study in the United States.

BACKGROUND: Giant cell arteritis (GCA) and polymyalgia rheumatica (PMR) are systemic inflammatory diseases that primarily affect elderly women. OBJECTIVES: To compare the risk of thromboembolic events and retinal vascular occlusions in GCA and/or PMR with that in osteoarthritis (OA), evaluating a veteran-based population. METHODS: A total of 1535 patients with GCA, 10,265 with PMR, and 1203 with overlapping disease, as well as 39,009 age- and sex-matched patients with OA were identified in this retrospective study. The incidence rate ratios (IRRs) of pulmonary embolism (PE), deep venous thrombosis (DVT), arterial thromboembolism, central retinal artery occlusion, and central retinal vein occlusion were calculated and examined over time. The cumulative incidence was plotted and hazard ratios (HRs) of thromboembolic events were calculated, adjusting for independent risk factors of thromboembolism. RESULTS: Patients with GCA and overlapping disease exhibited higher IRRs for all thromboembolic events compared to patients with OA. Patients with GCA had a higher risk of developing DVT and retinal vascular occlusions than those with overlapping disease (HR: 2.01, 95% confidence interval [CI]: 1.35-2.99, p < 0.001; HR: 2.37, 95% CI: 1.23-4.53, p = 0.009, respectively) or PMR alone (HR: 1.89, 95% CI: 1.50-2.41, p < 0.001; HR: 4.68, 95% CI: 3.10-7.07, p < 0.001, respectively). Patients with GCA had a higher risk of developing PE than those with PMR (HR: 1.55, 95% CI: 1.1-2.18, p = 0.01). CONCLUSION: The risk of thromboembolic events differs between GCA, PMR, and overlapping diseases. Our findings may help predict the risk of thromboembolic events based on disease phenotype.

Immune profile differences between chronic GVHD and late acute GVHD: results of the ABLE/PBMTC 1202 studies.

Human graft-versus-host disease (GVHD) biology beyond 3 months after hematopoietic stem cell transplantation (HSCT) is complex. The Applied Biomarker in Late Effects of Childhood Cancer study (ABLE/PBMTC1202, NCT02067832) evaluated the immune profiles in chronic GVHD (cGVHD) and late acute GVHD (L-aGVHD). Peripheral blood immune cell and plasma markers were analyzed at day 100 post-HSCT and correlated with GVHD diagnosed according to the National Institutes of Health consensus criteria (NIH-CC) for cGVHD. Of 302 children enrolled, 241 were evaluable as L-aGVHD, cGVHD, active L-aGVHD or cGVHD, and no cGVHD/L-aGVHD. Significant marker differences, adjusted for major clinical factors, were defined as meeting all 3 criteria: receiver-operating characteristic area under the curve ≥0.60, P ≤ .05, and effect ratio ≥1.3 or ≤0.75. Patients with only distinctive features but determined as cGVHD by the adjudication committee (non-NIH-CC) had immune profiles similar to NIH-CC. Both cGVHD and L-aGVHD had decreased transitional B cells and increased cytolytic natural killer (NK) cells. cGVHD had additional abnormalities, with increased activated T cells, naive helper T (Th) and cytotoxic T cells, loss of CD56bright regulatory NK cells, and increased ST2 and soluble CD13. Active L-aGVHD before day 114 had additional abnormalities in naive Th, naive regulatory T (Treg) cell populations, and cytokines, and active cGVHD had an increase in PD-1- and a decrease in PD-1+ memory Treg cells. Unsupervised analysis appeared to show a progression of immune abnormalities from no cGVHD/L-aGVHD to L-aGVHD, with the most complex pattern in cGVHD. Comprehensive immune profiling will allow us to better understand how to minimize L-aGVHD and cGVHD. Further confirmation in adult and pediatric cohorts is needed.

Tumor necrosis factor inhibitor (TNFi) persistence and reasons for discontinuation in a predominantly male cohort with axial spondyloarthritis.

Although tumor necrosis factor inhibitors (TNFi) have favorably altered the treatment landscape for patients with axial spondyloarthritis (axSpA), there is limited data regarding TNFi persistence and reasons for discontinuation. This is an observational time-to-event study utilizing data collected for a prospective multiple-disease registry of US Veterans with axSpA treated with TNFi therapies and recruited over a 10 year period. Clinical, serological, and comorbid parameters were collected. Corporate Data Warehouse Pharmacy files provided courses of the 5 TNFi agents, and response to treatment was documented. Individual TNFi persistence was established utilizing univariate and multivariate Cox proportional models, and reasons for discontinuation were obtained by physician chart review. Two-hundred and fifty-five axSpA patients received 731 TNFi courses. A majority of patients (84.3%) had TNFi persistence at 12 months; 63.5% and 47.1% at 24 and 36 months, respectively. Compared to adalimumab, infliximab demonstrated greater persistence, certolizumab the least. Age, smoking status, BMI, comorbidity burden, inflammatory markers and HLA-B27 did not predict TNFi persistence or discontinuation. Stroke and peripheral arterial disease increased the probability of TNFi discontinuation. Secondary non-response (SNR) was the most common reason for discontinuation (46% of all courses); non-adherence (6%) and clinical remission (2%) were uncommon. Pain score at enrollment, myocardial infarction, African American race and inflammatory bowel disease (IBD) predicted TNFi response. While initial persistence of TNFi treatment was high, a large proportion of the patients discontinued initial TNFi therapy by 3 years, primarily due to loss of efficacy. While further research identifying potential predictors of TNFi discontinuation in axSpA is warranted, access to alternate disease-modifying therapies is needed.

Deconvolving the contributions of cell-type heterogeneity on cortical gene expression.

Complexity of cell-type composition has created much skepticism surrounding the interpretation of bulk tissue transcriptomic studies. Recent studies have shown that deconvolution algorithms can be applied to computationally estimate cell-type proportions from gene expression data of bulk blood samples, but their performance when applied to brain tissue is unclear. Here, we have generated an immunohistochemistry (IHC) dataset for five major cell-types from brain tissue of 70 individuals, who also have bulk cortical gene expression data. With the IHC data as the benchmark, this resource enables quantitative assessment of deconvolution algorithms for brain tissue. We apply existing deconvolution algorithms to brain tissue by using marker sets derived from human brain single cell and cell-sorted RNA-seq data. We show that these algorithms can indeed produce informative estimates of constituent cell-type proportions. In fact, neuronal subpopulations can also be estimated from bulk brain tissue samples. Further, we show that including the cell-type proportion estimates as confounding factors is important for reducing false associations between Alzheimer's disease phenotypes and gene expression. Lastly, we demonstrate that using more accurate marker sets can substantially improve statistical power in detecting cell-type specific expression quantitative trait loci (eQTLs).

Implications of the diagnostic criteria of idiopathic pulmonary fibrosis in clinical practice: Analysis from the Australian Idiopathic Pulmonary Fibrosis Registry.

BACKGROUND AND OBJECTIVE: Current guidelines for the diagnosis of idiopathic pulmonary fibrosis (IPF) provide specific criteria for diagnosis in the setting of multidisciplinary discussion (MDD). We evaluate the utility and reproducibility of these diagnostic guidelines, using clinical data from the Australian IPF Registry. METHODS: All patients enrolled in the registry undergo a diagnostic review whereby international IPF guidelines are applied via a registry MDD. We investigated the clinical applicability of these guidelines with regard to: (i) adherence to guidelines, (ii) Natural history of IPF diagnostic categories and (iii) Concordance for diagnostic features. RESULTS: A total of 417 participants (69% male, 70.6 ± 8.0 years) with a clinical diagnosis of IPF underwent MDD. The 23% of participants who did not meet IPF diagnostic criteria displayed identical disease behaviour to those with confirmed IPF. Honeycombing on radiology was associated with a worse prognosis and this translated into poorer prognosis in the 'definite' IPF group. While there was moderate agreement for IPF diagnostic categories, agreement for specific radiological features, other than honeycombing, was poor. CONCLUSION: In clinical practice, physicians do not always follow IPF diagnostic guidelines. We demonstrate a cohort of IPF patients who do not meet IPF diagnostic guideline criteria, based largely on their radiology and lack of lung biopsy, but who have outcomes identical to those with IPF.

The TLR9 agonist (GNKG168) induces a unique immune activation pattern in vivo in children with minimal residual disease positive acute leukemia: Results of the TACL T2009-008 phase I study.

Background: Preclinical studies show that TLR9 agonists can eradicate leukemia by induction of immune responses in vivo against AML and ALL. These studies demonstrated that TLR9 agonists induce an immediate NK response followed by adaptive T and B cells responses resulting in long term anti-leukemia immunity. Methods: The Therapeutic Advances in Childhood Leukemia and Lymphoma Phase I consortium performed a pilot study on 3 patients with MRD positive acute leukemia after an initial remission on conventional chemotherapy (TACL T2009-008) with the TLR 9 agonist (GNKG168). To guide future trial development, we evaluated the impact of GNKG168 by Nanostring on the expression 608 genes before and 8 days after initiation of GNKG168 therapy. Results: Twenty-three out of 578 markers on the nanostring panel showed significant difference (p ≤ 0.05). We focused on 8 markers that had the greatest differences with p < 0.01. Two genes were increased, promyelocytic leukemia protein (PML) and H-RAS, and 6 were decreased, Single Ig and TIR Domain containing (SIGIRR, IL1R8), interleukin 1 receptor 1 (IL1RL1, ST2), C-C Motif chemokine receptor 8 (CCR8), interleukin 7 R (IL7R), cluster of differentiation 8B (CD8B), and cluster of differentiation 3 (CD3D). Tumor inhibitory pathways were downregulated including the SIGIRR (IL1R8), important in IL-37 signaling and NK cell inhibition. TLR9 can induce IL-33, which is known to downregulate ST2 (IL1RL1) a receptor for IL-33. Conclusion: GNKG168 therapy is associated with immunologic changes in pediatric leukemia patients. Further work with a larger sample size is required to assess the impact of these changes on disease treatment and persistence of leukemia remission.

Overdominant Effect of a CHRNA4 Polymorphism on Cingulo-Opercular Network Activity and Cognitive Control.

The nicotinic system plays an important role in cognitive control and is implicated in several neuropsychiatric conditions. However, the contributions of genetic variability in this system to individuals' cognitive control abilities are poorly understood and the brain processes that mediate such genetic contributions remain largely unidentified. In this first large-scale neuroimaging genetics study of the human nicotinic receptor system (two cohorts, males and females, fMRI total N = 1586, behavioral total N = 3650), we investigated a common polymorphism of the high-affinity nicotinic receptor α4ß2 (rs1044396 on the CHRNA4 gene) previously implicated in behavioral and nicotine-related studies (albeit with inconsistent major/minor allele impacts). Based on our prior neuroimaging findings, we expected this polymorphism to affect neural activity in the cingulo-opercular (CO) network involved in core cognitive control processes including maintenance of alertness. Consistent across the cohorts, all cortical areas of the CO network showed higher activity in heterozygotes compared with both types of homozygotes during cognitive engagement. This inverted U-shaped relation reflects an overdominant effect; that is, allelic interaction (cumulative evidence p = 1.33 * 10-5). Furthermore, heterozygotes performed more accurately in behavioral tasks that primarily depend on sustained alertness. No effects were observed for haplotypes of the surrounding CHRNA4 region, supporting a true overdominant effect at rs1044396. As a possible mechanism, we observed that this polymorphism is an expression quantitative trait locus modulating CHRNA4 expression levels. This is the first report of overdominance in the nicotinic system. These findings connect CHRNA4 genotype, CO network activation, and sustained alertness, providing insights into how genetics shapes individuals' cognitive control abilities.SIGNIFICANCE STATEMENT The nicotinic acetylcholine system plays a central role in neuromodulatory regulation of cognitive control processes and is dysregulated in several neuropsychiatric disorders. Despite this functional importance, no large-scale neuroimaging genetics studies have targeted the contributions of genetic variability in this system to human brain activity. Here, we show the impact of a common polymorphism of the high-affinity nicotinic receptor α4ß2 that is consistent across brain activity and behavior in two large human cohorts. We report a hitherto unknown overdominant effect (allelic interaction) at this locus, where the heterozygotes show higher activity in the cingulo-opercular network underlying alertness maintenance and higher behavioral alertness performance than both homozygous groups. This gene-brain-behavior relationship informs about the biological basis of interindividual differences in cognitive control.

CD56bright natural killer regulatory cells in filgrastim primed donor blood or marrow products regulate chronic graft-versus-host disease: the Canadian Blood and Marrow Transplant Group randomized 0601 study results.

Randomized trials have conclusively shown higher rates of chronic graft-versus-host disease with filgrastim-stimulated apheresis peripheral blood as a donor source than unstimulated bone marrow. The Canadian Blood and Marrow Transplant Group conducted a phase 3 study of adults who received either filgrastim-stimulated apheresis peripheral blood or filgrastim-stimulated bone marrow from human leukocyte antigen-identical sibling donors. Because all donors received the identical filgrastim dosing schedule, this study allowed for a controlled evaluation of the impact of stem cell source on development of chronic graft-versus-host disease. One hundred and twenty-one evaluable filgrastim-stimulated apheresis peripheral blood and filgrastim-stimulated bone marrow patient donor products were immunologically characterized by flow cytometry and tested for their association with acute and chronic graft-versus-host disease within 2 years of transplantation. The immune populations evaluated included, regulatory T cells, central memory and effector T cells, interferon γ positive producing T cells, invariate natural killer T cells, regulatory natural killer cells, dendritic cell populations, macrophages, and activated B cells and memory B cells. When both filgrastim-stimulated apheresis peripheral blood and filgrastim-stimulated bone marrow were grouped together, a higher chronic graft-versus-host disease frequency was associated with lower proportions of CD56bright natural killer regulatory cells and interferon γ-producing T helper cells in the donor product. Lower CD56bright natural killer regulatory cells displayed differential impacts on the development of extensive chronic graft-versus-host disease between filgrastim-stimulated apheresis peripheral blood and filgrastim-stimulated bone marrow. In summary, while controlling for the potential impact of filgrastim on marrow, our studies demonstrated that CD56bright natural killer regulatory cells had a much stronger impact on filgrastim-stimulated apheresis peripheral blood than on filgrastim-stimulated bone marrow. This supports the conclusion that a lower proportion of CD56bright natural killer regulatory cells results in the high rate of chronic graft-versus-host disease seen in filgrastim-stimulated apheresis peripheral blood. clinicaltrials.gov Identifier: 00438958.

Identification of Mood-Relevant Brain Connections Using a Continuous, Subject-Driven Rumination Paradigm.

Rumination, an internal cognitive state characterized by recursive thinking of current self-distress and past negative events, has been found to correlate with the development of depressive disorders. Here, we investigated the feasibility of using connectivity for distinguishing different emotional states induced by a novel free-streaming, subject-driven experimental paradigm. Connectivity between 78 functional regions of interest (ROIs) within 14 large-scale networks and 6 structural ROIs particularly relevant to emotional processing were used for classifying 4 mental states in 19 healthy controls. The 4 mental states comprised: An unconstrained period of mind wandering; a ruminative mental state self-induced by recalling a time of personal disappointment; a euphoric mental state self-induced by recalling what brings the subject joy; and a sequential episodic recollection of the events of the day. A support vector machine achieved accuracies ranging from 89% to 94% in classifying pairs of different mental states. We reported the most significant brain connections that best discriminated these mental states. In particular, connectivity changes involving the amygdala were found to be important for distinguishing the rumination condition from the other mental states. Our results demonstrated that connectivity-based classification of subject-driven emotional states constitutes a novel and effective approach for studying ruminative behavior.

Regional brain hypometabolism is unrelated to regional amyloid plaque burden.

In its original form, the amyloid cascade hypothesis of Alzheimer's disease holds that fibrillar deposits of amyloid are an early, driving force in pathological events leading ultimately to neuronal death. Early clinicopathological investigations highlighted a number of inconsistencies leading to an updated hypothesis in which amyloid plaques give way to amyloid oligomers as the driving force in pathogenesis. Rather than focusing on the inconsistencies, amyloid imaging studies have tended to highlight the overlap between regions that show early amyloid plaque signal on positron emission tomography and that also happen to be affected early in Alzheimer's disease. Recent imaging studies investigating the regional dependency between metabolism and amyloid plaque deposition have arrived at conflicting results, with some showing regional associations and other not. We extracted multimodal neuroimaging data from the Alzheimer's disease neuroimaging database for 227 healthy controls and 434 subjects with mild cognitive impairment. We analysed regional patterns of amyloid deposition, regional glucose metabolism and regional atrophy using florbetapir ((18)F) positron emission tomography, (18)F-fluordeoxyglucose positron emission tomography and T1-weighted magnetic resonance imaging, respectively. Specifically, we derived grey matter density and standardized uptake value ratios for both positron emission tomography tracers in 404 functionally defined regions of interest. We examined the relation between regional glucose metabolism and amyloid plaques using linear models. For each region of interest, correcting for regional grey matter density, age, education and disease status, we tested the association of regional glucose metabolism with (i) cortex-wide florbetapir uptake; (ii) regional (i.e. in the same region of interest) florbetapir uptake; and (iii) regional florbetapir uptake while correcting in addition for cortex-wide florbetapir uptake. P-values for each setting were Bonferroni corrected for 404 tests. Regions showing significant hypometabolism with increasing cortex-wide amyloid burden were classic Alzheimer's disease-related regions: the medial and lateral parietal cortices. The associations between regional amyloid burden and regional metabolism were more heterogeneous: there were significant hypometabolic effects in posterior cingulate, precuneus, and parietal regions but also significant positive associations in bilateral hippocampus and entorhinal cortex. However, after correcting for global amyloid burden, few of the negative associations remained and the number of positive associations increased. Given the wide-spread distribution of amyloid plaques, if the canonical cascade hypothesis were true, we would expect wide-spread, cortical hypometabolism. Instead, cortical hypometabolism appears to be linked to global amyloid burden. Thus we conclude that regional fibrillar amyloid deposition has little to no association with regional hypometabolism.

Optimization of rs-fMRI Pre-processing for Enhanced Signal-Noise Separation, Test-Retest Reliability, and Group Discrimination.

Resting-state functional magnetic resonance imaging (rs-fMRI) has become an increasingly important tool in mapping the functional networks of the brain. This tool has been used to examine network changes induced by cognitive and emotional states, neurological traits, and neuropsychiatric disorders. However, noise that remains in the rs-fMRI data after preprocessing has limited the reliability of individual-subject results, wherein scanner artifacts, subject movements, and other noise sources induce non-neural temporal correlations in the blood oxygen level-dependent (BOLD) timeseries. Numerous preprocessing methods have been proposed to isolate and remove these confounds; however, the field has not coalesced around a standard preprocessing pipeline. In comparisons, these preprocessing methods are often assessed with only a single metric of rs-fMRI data quality, such as reliability, without considering other aspects in tandem, such as signal-to-noise ratio and group discriminability. The present study seeks to identify the data preprocessing pipeline that optimizes rs-fMRI data across multiple outcome measures. Specifically, we aim to minimize the noise in the data and maximize result reliability, while retaining the unique features that characterize distinct groups. We examine how these metrics are influenced by bandpass filter selection and noise regression in four datasets, totaling 181 rs-fMRI scans and 38 subject-driven memory scans. Additionally, we perform two different rs-fMRI analysis methods - dual regression and region-of-interest based functional connectivity - and highlight the preprocessing parameters that optimize both approaches. Our results expand upon previous reports of individual-scan reliability, and demonstrate that preprocessing parameter selection can significantly change the noisiness, reliability, and heterogeneity of rs-fMRI data. The application of our findings to rs-fMRI data analysis should improve the validity and reliability of rs-fMRI results, both at the individual-subject level and the group level.

Perioperative use of anti-rheumatic agents does not increase early postoperative infection risks: a Veteran Affairs' administrative database study.

The aim of this study was to validate a novel technique that predicts stopping of disease-modifying anti-rheumatic drugs (DMARDs) and biologic agents (BA) from the Veterans Affairs (VA) database and compare infection risks of rheumatoid arthritis patients who stopped versus continued DMARDs/BA perioperatively. We identified 6,024 patients on 1 DMARD or BA in the perioperative period between 1999 and 2009. Time gap between medication stop date and the next start date predicted drug stoppage (X). Time gap between surgery date and stop date predicted whether stoppage was before surgery (Y). Chart review from Houston VA was used for validation. ROC analyses were performed on chart review data to obtain X and Y cutoffs. The primary endpoints were wound infections and other infections within 30 days. ROC analyses found X ≥ 33 (AUC = 0.954) and Y ≥ -11 (AUC = 0.846). Risk of postoperative infections was not different when stopping and continuing DMARDs/BA preoperatively. Stopping BA after surgery was associated with higher odds of postoperative wound (OR 14.15, 95 % CI 1.76-113.76) and general infection (OR 9.2, 95 % CI 1.99-42.60) compared to not stopping. Stopping DMARDs after surgery was associated with increased risk of postoperative general infection (OR 1.84, 95 % CI 1.07-3.16) compared with not stopping. There was positive association between stopping DMARDs after surgery and postoperative wound infection but failed to achieve statistical significance (OR 1.67, 95 % CI 0.96-2.91). There was no significant difference in postoperative infection risk when stopping or continuing DMARD/BA. Our new validated method can be utilized in the VA and other databases to predict drug stoppage.

Environmental life cycle assessment of different domestic wastewater streams: policy effectiveness in a tropical urban environment.

To enhance local water security, the Singapore government promotes two water conservation policies: the use of eco-friendly toilets to reduce yellow water (YW) disposal and the installation of water efficient devices to minimize gray water (GW) discharge. The proposed water conservation policies have different impacts on the environmental performance of local wastewater management. The main purpose of this study is to examine and compare the impacts of different domestic wastewater streams and the effectiveness of two water conservation policies by means of life cycle assessment (LCA). LCA is used to compare three scenarios, including a baseline scenario (BL), YW-reduced scenario (YWR) and GW-reduced scenario (GWR). The BL is designed based on the current wastewater management system, whereas the latter two scenarios are constructed according to the two water conservation policies that are proposed by the Singapore government. The software SIMPARO 7.3 with local data and an eco-invent database is used to build up the model, and the functional unit is defined as the daily wastewater disposal of a Singapore resident. Due to local water supply characteristics, the system boundary is extended to include the sewage sludge management and tap water production processes. The characterization results indicate that the GWR has a significant impact reduction (22-25%) while the YWR has only a 2-4% impact reduction compared with the BL. The contribution analysis reveals that the GW dominates many impact categories except eutrophication potential. The tap water production is identified as the most influential process due to its high embodied energy demand in a local context. Life cycle costing analysis shows that both YWR and GWR are financially favorable. It is also revealed that the current water conservation policies could only achieve Singapore's short-term targets. Therefore, two additional strategies are recommended for achieving long-term goals. This study provides a comprehensive and reliable environmental profile of Singapore's wastewater management with the help of extended system boundary and local data. This work also fills the research gap of previous studies by identifying the contribution of different wastewater streams, which would serve as a good reference for source-separating sanitation system design.