Peripheral Blood Cell Gene Expression Diagnostic for Identifying Symptomatic Transthyretin Amyloidosis Patients: Male and Female Specific Signatures

BACKGROUND: Early diagnosis of familial transthyretin (TTR) amyloid diseases remains challenging because of variable disease penetrance. Currently, patients must have an amyloid positive tissue biopsy to be eligible for disease-modifying therapies. Endomyocardial biopsies are typically amyloid positive when cardiomyopathy is suspected, but this disease manifestation is generally diagnosed late. Early diagnosis is often difficult because patients exhibit apparent symptoms of polyneuropathy, but have a negative amyloid biopsy. Thus, there is a pressing need for an additional early diagnostic strategy for TTR-aggregation-associated polyneuropathy and cardiomyopathy. METHODS AND FINDINGS: Global peripheral blood cell mRNA expression profiles from 263 tafamidis-treated and untreated V30M Familiar Amyloid Neuropathy patients, asymptomatic V30M carriers, and healthy, age- and sex-matched controls without TTR mutations were used to differentiate symptomatic from asymptomatic patients. We demonstrate that blood cell gene expression patterns reveal sex-independent, as well as male- and female-specific inflammatory signatures in symptomatic FAP patients, but not in asymptomatic carriers. These signatures differentiated symptomatic patients from asymptomatic V30M carriers with >80% accuracy. There was a global downregulation of the eIF2 pathway and its associated genes in all symptomatic FAP patients. We also demonstrated that the molecular scores based on these signatures significantly trended toward normalized values in an independent cohort of 46 FAP patients after only 3 months of tafamidis treatment. CONCLUSIONS: This study identifies novel molecular signatures that differentiate symptomatic FAP patients from asymptomatic V30M carriers as well as affected males and females. We envision using this approach, initially in parallel with amyloid biopsies, to identify individuals who are asymptomatic gene carriers that may convert to FAP patients. Upon further validation, peripheral blood cell mRNA expression profiling could become an independent early diagnostic. This quantitative gene expression signature for symptomatic FAP could also become a biomarker to demonstrate significant disease-modifying effects of drugs and drug candidates. For example, when new disease modifiers are being evaluated in a FAP clinical trial, such surrogate biomarkers have the potential to provide an objective, quantitative and mechanistic molecular diagnostic of disease response to therapy.We acknowledge the following sources of research funding: NIH U19 A1063603 (DRS, SMK), NIH DK46335 (JWK) and NIH R01AG19259 (JNB)info:eu-repo/semantics/publishedVersio

Locality-oblivious cache organization leveraging single-cycle multi-hop NoCs

Locality has always been a critical factor in on-chip data placement on CMPs as accessing further-away caches has in the past been more costly than accessing nearby ones. Substantial research on locality-aware designs have thus focused on keeping a copy of the data private. However, this complicatesthe problem of data tracking and search/invalidation; tracking the state of a line at all on-chip caches at a directory or performing full-chip broadcasts are both non-scalable and extremely expensive solutions. In this paper, we make the case for Locality-Oblivious Cache Organization (LOCO), a CMP cache organization that leverages the on-chip network to create virtual single-cycle paths between distant caches, thus redefining the notion of locality. LOCO is a clustered cache organization, supporting both homogeneous and heterogeneous cluster sizes, and provides near single-cycle accesses to data anywhere within the cluster, just like a private cache. Globally, LOCO dynamically creates a virtual mesh connecting all the clusters, and performs an efficient global data search and migration over this virtual mesh, without having to resort to full-chip broadcasts or perform expensive directory lookups. Trace-driven and full system simulations running SPLASH-2 and PARSEC benchmarks show that LOCO improves application run time by up to 44.5% over baseline private and shared cache.Semiconductor Research CorporationUnited States. Defense Advanced Research Projects Agency (Semiconductor Technology Advanced Research Network

Precision medicine for suicidality: from universality to subtypes and personalization

Suicide remains a clear, present and increasing public health problem, despite being a potentially preventable tragedy. Its incidence is particularly high in people with overt or un(der)diagnosed psychiatric disorders. Objective and precise identification of individuals at risk, ways of monitoring response to treatments and novel preventive therapeutics need to be discovered, employed and widely deployed. We sought to investigate whether blood gene expression biomarkers for suicide (that is, a ‘liquid biopsy’ approach) can be identified that are more universal in nature, working across psychiatric diagnoses and genders, using larger cohorts than in previous studies. Such markers may reflect and/or be a proxy for the core biology of suicide. We were successful in this endeavor, using a comprehensive stepwise approach, leading to a wealth of findings. Steps 1, 2 and 3 were discovery, prioritization and validation for tracking suicidality, resulting in a Top Dozen list of candidate biomarkers comprising the top biomarkers from each step, as well as a larger list of 148 candidate biomarkers that survived Bonferroni correction in the validation step. Step 4 was testing the Top Dozen list and Bonferroni biomarker list for predictive ability for suicidal ideation (SI) and for future hospitalizations for suicidality in independent cohorts, leading to the identification of completely novel predictive biomarkers (such as CLN5 and AK2), as well as reinforcement of ours and others previous findings in the field (such as SLC4A4 and SKA2). Additionally, we examined whether subtypes of suicidality can be identified based on mental state at the time of high SI and identified four potential subtypes: high anxiety, low mood, combined and non-affective (psychotic). Such subtypes may delineate groups of individuals that are more homogenous in terms of suicidality biology and behavior. We also studied a more personalized approach, by psychiatric diagnosis and gender, with a focus on bipolar males, the highest risk group. Such a personalized approach may be more sensitive to gender differences and to the impact of psychiatric co-morbidities and medications. We compared testing the universal biomarkers in everybody versus testing by subtypes versus personalized by gender and diagnosis, and show that the subtype and personalized approaches permit enhanced precision of predictions for different universal biomarkers. In particular, LHFP appears to be a strong predictor for suicidality in males with depression. We also directly examined whether biomarkers discovered using male bipolars only are better predictors in a male bipolar independent cohort than universal biomarkers and show evidence for a possible advantage of personalization. We identified completely novel biomarkers (such as SPTBN1 and C7orf73), and reinforced previously known biomarkers (such as PTEN and SAT1). For diagnostic ability testing purposes, we also examined as predictors phenotypic measures as apps (for suicide risk (CFI-S, Convergent Functional Information for Suicidality) and for anxiety and mood (SASS, Simplified Affective State Scale)) by themselves, as well as in combination with the top biomarkers (the combination being our a priori primary endpoint), to provide context and enhance precision of predictions. We obtained area under the curves of 90% for SI and 77% for future hospitalizations in independent cohorts. Step 5 was to look for mechanistic understanding, starting with examining evidence for the Top Dozen and Bonferroni biomarkers for involvement in other psychiatric and non-psychiatric disorders, as a mechanism for biological predisposition and vulnerability. The biomarkers we identified also provide a window towards understanding the biology of suicide, implicating biological pathways related to neurogenesis, programmed cell death and insulin signaling from the universal biomarkers, as well as mTOR signaling from the male bipolar biomarkers. In particular, HTR2A increase coupled with ARRB1 and GSK3B decreases in expression in suicidality may provide a synergistic mechanistical corrective target, as do SLC4A4 increase coupled with AHCYL1 and AHCYL2 decrease. Step 6 was to move beyond diagnostics and mechanistical risk assessment, towards providing a foundation for personalized therapeutics. Items scored positive in the CFI-S and subtypes identified by SASS in different individuals provide targets for personalized (psycho)therapy. Some individual biomarkers are targets of existing drugs used to treat mood disorders and suicidality (lithium, clozapine and omega-3 fatty acids), providing a means toward pharmacogenomics stratification of patients and monitoring of response to treatment. Such biomarkers merit evaluation in clinical trials. Bioinformatics drug repurposing analyses with the gene expression biosignatures of the Top Dozen and Bonferroni-validated universal biomarkers identified novel potential therapeutics for suicidality, such as ebselen (a lithium mimetic), piracetam (a nootropic), chlorogenic acid (a polyphenol) and metformin (an antidiabetic and possible longevity promoting drug). Finally, based on the totality of our data and of the evidence in the field to date, a convergent functional evidence score prioritizing biomarkers that have all around evidence (track suicidality, predict it, are reflective of biological predisposition and are potential drug targets) brought to the fore APOE and IL6 from among the universal biomarkers, suggesting an inflammatory/accelerated aging component that may be a targetable common denominator

Towards precision medicine for pain: diagnostic biomarkers and repurposed drugs

We endeavored to identify objective blood biomarkers for pain, a subjective sensation with a biological basis, using a stepwise discovery, prioritization, validation, and testing in independent cohorts design. We studied psychiatric patients, a high risk group for co-morbid pain disorders and increased perception of pain. For discovery, we used a powerful within-subject longitudinal design. We were successful in identifying blood gene expression biomarkers that were predictive of pain state, and of future emergency department (ED) visits for pain, more so when personalized by gender and diagnosis. MFAP3, which had no prior evidence in the literature for involvement in pain, had the most robust empirical evidence from our discovery and validation steps, and was a strong predictor for pain in the independent cohorts, particularly in females and males with PTSD. Other biomarkers with best overall convergent functional evidence for involvement in pain were GNG7, CNTN1, LY9, CCDC144B, and GBP1. Some of the individual biomarkers identified are targets of existing drugs. Moreover, the biomarker gene expression signatures were used for bioinformatic drug repurposing analyses, yielding leads for possible new drug candidates such as SC-560 (an NSAID), and amoxapine (an antidepressant), as well as natural compounds such as pyridoxine (vitamin B6), cyanocobalamin (vitamin B12), and apigenin (a plant flavonoid). Our work may help mitigate the diagnostic and treatment dilemmas that have contributed to the current opioid epidemic

Constitutive activation of the EGFR-STAT1 axis increases proliferation of meningioma tumor cells.

Background: Meningiomas are the most frequent primary brain tumors of the central nervous system. The standard of treatment is surgery and radiotherapy, but effective pharmacological options are not available yet. The well-characterized genetic background stratifies these tumors in several subgroups, thus increasing diversification. We identified epidermal growth factor receptor-signal transducer and activator of transcription 1 (EGFR-STAT1) overexpression and activation as a common identifier of these tumors. Methods: We analyzed STAT1 overexpression and phosphorylation in 131 meningiomas of different grades and locations by utilizing several techniques, including Western blots, qPCR, and immunocytochemistry. We also silenced and overexpressed wild-type and mutant forms of the gene to assess its biological function and its network. Results were further validated by drug testing. Results: STAT1 was found widely overexpressed in meningioma but not in the corresponding healthy controls. The protein showed constitutive phosphorylation not dependent on the JAK-STAT pathway. STAT1 knockdown resulted in a significant reduction of cellular proliferation and deactivation of AKT and ERK1/2. STAT1 is known to be activated by EGFR, so we investigated the tyrosine kinase and found that EGFR was also constitutively phosphorylated in meningioma and was responsible for the aberrant phosphorylation of STAT1. The pharmaceutical inhibition of EGFR caused a significant reduction in cellular proliferation and of overall levels of cyclin D1, pAKT, and pERK1/2. Conclusions: STAT1-EGFR-dependent constitutive phosphorylation is responsible for a positive feedback loop that causes its own overexpression and consequently an increased proliferation of the tumor cells. These findings provide the rationale for further studies aiming to identify effective therapeutic options in meningioma

Seasonal occurrence of anoxygenic photosynthesis in Tillari and Selaulim reservoirs, Western India

© The Author(s), 2012. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Biogeosciences 9 (2012): 2485-2495, doi:10.5194/bg-9-2485-2012.Phytoplankton and bacterial pigment compositions were determined by high performance liquid chromatography (HPLC) and liquid chromatography-mass spectrometry (LC-MS) in two freshwater reservoirs (Tillari Dam and Selaulim Dam), which are located at the foothills of the Western Ghats in India. These reservoirs experience anoxia in the hypolimnion during summer. Water samples were collected from both reservoirs during anoxic periods while one of them (Tillari Reservoir) was also sampled in winter, when convective mixing results in well-oxygenated conditions throughout the water column. During the period of anoxia (summer), bacteriochlorophyll (BChl) e isomers and isorenieratene, characteristic of brown sulfur bacteria, were dominant in the anoxic (sulfidic) layer of the Tillari Reservoir under low light intensities. The winter observations showed the dominance of small cells of Chlorophyll b-containing green algae and cyanobacteria, with minor presence of fucoxanthin-containing diatoms and peridinin-containing dinoflagellates. Using total BChl e concentration observed in June, the standing stock of brown sulfur bacteria carbon in the anoxic compartment of Tillari Reservoir was estimated to be 2.27 gC m−2, which is much higher than the similar estimate for carbon derived from oxygenic photosynthesis (0.82 gC m−2. The Selaulim Reservoir also displayed similar characteristics with the presence of BChl e isomers and isorenieratene in the anoxic hypolimnion during summer. Although sulfidic conditions prevailed in the water column below the thermocline, the occurrence of photo-autotrophic bacteria was restricted only to mid-depths (maximal concentration of BChl e isomers was detected at 0.2% of the surface incident light). This shows that the vertical distribution of photo-autotrophic sulfur bacteria is primarily controlled by light penetration in the water column where the presence of H2S provides a suitable biogeochemical environment for them to flourish.Financial support for this work was provided by the Council of Scientific & Industrial Research (CSIR) and Ministry of Earth Sciences (MoES). S. Kurian acknowledges POGO-SCOR for financial support to visit WHOI. R. Roy, G. Narvenkar and A. Sarkar received fellowship support from CSIR. D. Repeta acknowledges support from US National Science Foundation Center Award EF0424599 to the Center for Microbial Oceanography: Research and Education (C-MORE)

Yield of comparative genomic hybridization microarray in pediatric neurology practice

OBJECTIVE: The present study investigated the diagnostic yield of array comparative genomic hybridization (aCGH) in a large cohort of children with diverse neurologic disorders as seen in child neurology practice to test whether pathogenic copy number variants (CNVs) were more likely to be detected in specific neurologic phenotypes. METHODS: A retrospective cross-sectional analysis was performed on 555 children in whom a genetic etiology was suspected and who underwent whole-genome aCGH testing between 2006 and 2012. Neurologic phenotyping was performed using hospital medical records. An assessment of pathogenicity was made for each CNV, based on recent developments in the literature. RESULTS: Forty-seven patients were found to carry a pathogenic CNV, giving an overall diagnostic yield of 8.59%. Certain phenotypes predicted for the presence of a pathogenic CNV, including developmental delay (odds ratio [OR] 3.69 [1.30–10.51]), cortical visual impairment (OR 2.73 [1.18–6.28]), dysmorphism (OR 2.75 [1.38–5.50]), and microcephaly (OR 2.16 [1.01–4.61]). The combination of developmental delay/intellectual disability with dysmorphism and abnormal head circumference was also predictive for a pathogenic CNV (OR 2.86 [1.02–8.00]). For every additional clinical feature, there was an increased likelihood of detecting a pathogenic CNV (OR 1.18 [1.01–1.38]). CONCLUSIONS: the use of aCGH led to a pathogenic finding in 8.59% of patients. The results support the use of aCGH as a first tier investigation in children with diverse neurologic disorders, although whole-genome sequencing may replace aCGH as the detection method in the future. In particular, the yield was increased in children with developmental delay, dysmorphism, cortical visual impairment, and microcephaly

Hydrography and water masses in the southeastern Arabian Sea during March-June 2003

This paper describes the hydrographic observations in the southeastern Arabian Sea (SEAS) during two cruises carried out in March-June 2003 as part of the Arabian Sea Monsoon Experiment. The surface hydrography during March-April was dominated by the intrusion of low-salinity waters from the south; during May-June, the low-salinity waters were beginning to be replaced by the high-salinity waters from the north. There was considerable mixing at the bottom of the surface mixed layer, leading to interleaving of low-salinity and high-salinity layers. The flow paths constructed following the spatial patterns of salinity along the sections mimic those inferred from numerical models. Time-series measurements showed the presence of Persian Gulf and Red Sea Waters in the SEAS to be intermittent during both cruises: they appeared and disappeared during both the fortnight-long time series