A mouse model of the schizophrenia-associated 1q21.1 microdeletion syndrome exhibits altered mesolimbic dopamine transmission

Abstract 1q21.1 hemizygous microdeletion is a copy number variant leading to eightfold increased risk of schizophrenia. In order to investigate biological alterations induced by this microdeletion, we generated a novel mouse model (Df(h1q21)/+) and characterized it in a broad test battery focusing on schizophrenia-related assays. Df(h1q21)/+ mice displayed increased hyperactivity in response to amphetamine challenge and increased sensitivity to the disruptive effects of amphetamine and phencyclidine hydrochloride (PCP) on prepulse inhibition. Probing of the direct dopamine (DA) pathway using the DA D1 receptor agonist SKF-81297 revealed no differences in induced locomotor activity compared to wild-type mice, but Df(h1q21)/+ mice showed increased sensitivity to the DA D2 receptor agonist quinpirole and the D1/D2 agonist apomorphine. Electrophysiological characterization of DA neuron firing in the ventral tegmental area revealed more spontaneously active DA neurons and increased firing variability in Df(h1q21)/+ mice, and decreased feedback reduction of DA neuron firing in response to amphetamine. In a range of other assays, Df(h1q21)/+ mice showed no difference from wild-type mice: gross brain morphology and basic functions such as reflexes, ASR, thermal pain sensitivity, and motor performance were unaltered. Similarly, anxiety related measures, baseline prepulse inhibition, and seizure threshold were unaltered. In addition to the central nervous system-related phenotypes, Df(h1q21)/+ mice exhibited reduced head-to tail length, which is reminiscent of the short stature reported in humans with 1q21.1 deletion. With aspects of both construct and face validity, the Df(h1q21)/+ model may be used to gain insight into schizophrenia-relevant alterations in dopaminergic transmission

Development and Function of CD94-Deficient Natural Killer Cells

The CD94 transmembrane-anchored glycoprotein forms disulfide-bonded heterodimers with the NKG2A subunit to form an inhibitory receptor or with the NKG2C or NKG2E subunits to assemble a receptor complex with activating DAP12 signaling proteins. CD94 receptors expressed on human and mouse NK cells and T cells have been proposed to be important in NK cell tolerance to self, play an important role in NK cell development, and contribute to NK cell-mediated immunity to certain infections including human cytomegalovirus. We generated a gene-targeted CD94-deficient mouse to understand the role of CD94 receptors in NK cell biology. CD94-deficient NK cells develop normally and efficiently kill NK cell-susceptible targets. Lack of these CD94 receptors does not alter control of mouse cytomegalovirus, lymphocytic choriomeningitis virus, vaccinia virus, or Listeria monocytogenes. Thus, the expression of CD94 and its associated NKG2A, NKG2C, and NKG2E subunits is dispensable for NK cell development, education, and many NK cell functions

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Longitudinal clinical and biomarker characteristics of non-manifesting LRRK2 G2019S carriers in the PPMI cohort

We examined 2-year longitudinal change in clinical features and biomarkers in LRRK2 non-manifesting carriers (NMCs) versus healthy controls (HCs) enrolled in the Parkinson’s Progression Markers Initiative (PPMI). We analyzed 2-year longitudinal data from 176 LRRK2 G2019S NMCs and 185 HCs. All participants were assessed annually with comprehensive motor and non-motor scales, dopamine transporter (DAT) imaging, and biofluid biomarkers. The latter included cerebrospinal fluid (CSF) Abeta, total tau and phospho-tau; serum urate and neurofilament light chain (NfL); and urine bis(monoacylglycerol) phosphate (BMP). At baseline, LRRK2 G2019S NMCs had a mean (SD) age of 62 (7.7) years and were 56% female. 13% had DAT deficit (defined as <65% of age/sex-expected lowest putamen SBR) and 11% had hyposmia (defined as ≤15th percentile for age and sex). Only 5 of 176 LRRK2 NMCs developed PD during follow-up. Although NMCs scored significantly worse on numerous clinical scales at baseline than HCs, there was no longitudinal change in any clinical measures over 2 years or in DAT binding. There were no longitudinal differences in CSF and serum biomarkers between NMCs and HCs. Urinary BMP was significantly elevated in NMCs at all time points but did not change longitudinally. Neither baseline biofluid biomarkers nor the presence of DAT deficit correlated with 2-year change in clinical outcomes. We observed no significant 2-year longitudinal change in clinical or biomarker measures in LRRK2 G2019S NMCs in this large, well-characterized cohort even in the participants with baseline DAT deficit. These findings highlight the essential need for further enrichment biomarker discovery in addition to DAT deficit and longer follow-up to enable the selection of NMCs at the highest risk for conversion to enable future prevention clinical trials

CSF1R inhibitor JNJ-40346527 attenuates microglial proliferation and neurodegeneration in P301S mice

Neuroinflammation and microglial activation are significant processes in Alzheimer’s disease pathology. Recent genome-wide association studies have highlighted multiple immune-related genes in association with Alzheimer’s disease, and experimental data have demonstrated microglial proliferation as a significant component of the neuropathology. In this study, we tested the efficacy of the selective CSF1R inhibitor JNJ-40346527 (JNJ-527) in the P301S mouse tauopathy model. We first demonstrated the anti-proliferative effects of JNJ-527 on microglia in the ME7 prion model, and its impact on the inflammatory profile, and provided potential CNS biomarkers for clinical investigation with the compound, including pharmacokinetic/pharmacodynamics and efficacy assessment by TSPO autoradiography and CSF proteomics. Then, we showed for the first time that blockade of microglial proliferation and modification of microglial phenotype leads to an attenuation of tau-induced neurodegeneration and results in functional improvement in P301S mice. Overall, this work strongly supports the potential for inhibition of CSF1R as a target for the treatment of Alzheimer’s disease and other tau-mediated neurodegenerative diseases

Inflammatory biomarkers in Alzheimer's disease plasma

Introduction:Plasma biomarkers for Alzheimer’s disease (AD) diagnosis/stratification are a“Holy Grail” of AD research and intensively sought; however, there are no well-established plasmamarkers.Methods:A hypothesis-led plasma biomarker search was conducted in the context of internationalmulticenter studies. The discovery phase measured 53 inflammatory proteins in elderly control (CTL;259), mild cognitive impairment (MCI; 199), and AD (262) subjects from AddNeuroMed.Results:Ten analytes showed significant intergroup differences. Logistic regression identified five(FB, FH, sCR1, MCP-1, eotaxin-1) that, age/APOε4 adjusted, optimally differentiated AD andCTL (AUC: 0.79), and three (sCR1, MCP-1, eotaxin-1) that optimally differentiated AD and MCI(AUC: 0.74). These models replicated in an independent cohort (EMIF; AUC 0.81 and 0.67). Twoanalytes (FB, FH) plus age predicted MCI progression to AD (AUC: 0.71).Discussion:Plasma markers of inflammation and complement dysregulation support diagnosis andoutcome prediction in AD and MCI. Further replication is needed before clinical translatio

Risk for cervical intraepithelial neoplasia grade 3 or worse in relation to smoking among women with persistent human papillomavirus infection

BACKGROUND: Smoking has been associated with cervical cancer. We examined whether smoking increases the risk for high-grade cervical lesions in women with high-risk human papillomavirus (HPV) infection. METHODS: In a population-based cohort study, 8,656 women underwent a structured interview, and subsequently cervical cells were obtained for HPV DNA testing. Women with high-risk HPV infection and no prevalent cervical disease at baseline (n=1,353) were followed through the Pathology Data Bank for cervical lesions for up to 13 years. Separate analyses of women with persistent high-risk HPV infection were also conducted. Hazard ratios (HRs) for a diagnosis of cervical intraepithelial neoplasia grade 3 or worse/high-grade squamous intraepithelial lesions or worse (CIN3+) and the corresponding 95% confidence intervals (CIs) were calculated in the 2 groups. RESULTS: Among high-risk HPV positive women an increased risk for CIN3+ was associated with long-term smoking (≥10 years) and heavy smoking (≥20 cigarettes/day). In the subgroup of women with persistent HPV infection heavy smoking was also associated with a statistically significantly higher risk for CIN3+ than never smoking (HR, 1.85; 95% CI, 1.05–3.22, adjusted for length of schooling, parity and HPV type at baseline). The average number of cervical cytology screening tests per year during follow-up did not explain the differences in risk in relation to smoking (p=0.4). CONCLUSIONS: Smoking is associated with an increased risk for subsequent high-grade cervical lesions in women with persistent high-risk HPV infection. IMPACT: Our study adds to the understanding of the role of smoking in the natural history of HPV and cervical carcinogenesis

Nonspecificity fingerprints for clinical-stage antibodies in solution.

Monoclonal antibodies (mAbs) have successfully been developed for the treatment of a wide range of diseases. The clinical success of mAbs does not solely rely on optimal potency and safety but also require good biophysical properties to ensure a high developability potential. In particular, nonspecific interactions are a key developability parameter to monitor during discovery and development. Despite an increased focus on the detection of nonspecific interactions, their underlying physicochemical origins remain poorly understood. Here, we employ solution-based microfluidic technologies to characterize a set of clinical-stage mAbs and their interactions with commonly used nonspecificity ligands to generate nonspecificity fingerprints, providing quantitative data on the underlying physical chemistry. Furthermore, the solution-based analysis enables us to measure binding affinities directly, and we evaluate the contribution of avidity in nonspecific binding by mAbs. We find that avidity can increase the apparent affinity by two orders of magnitude. Notably, we find that a subset of these highly developed mAbs show nonspecific electrostatic interactions, even at physiological pH and ionic strength, and that they can form microscale particles with charge-complementary polymers. The group of mAb constructs flagged here for nonspecificity are among the worst performers in independent reports of surface and column-based screens. The solution measurements improve on the state-of-the-art by providing a stand-alone result for individual mAbs without the need to benchmark against cohort data. Based on our findings, we propose a quantitative solution-based nonspecificity score, which can be integrated in the development workflow for biological therapeutics and more widely in protein engineering

Design of Biopharmaceutical Formulations Accelerated by Machine Learning

In addition to activity, successful biological drugs must exhibit a series of suitable developability properties, which depend on both protein sequence and buffer composition. In the context of this high-dimensional optimization problem, advanced algorithms from the domain of machine learning are highly beneficial in complementing analytical screening and rational design. Here, we propose a Bayesian optimization algorithm to accelerate the design of biopharmaceutical formulations. We demonstrate the power of this approach by identifying the formulation that optimizes the thermal stability of three tandem single-chain Fv variants within 25 experiments, a number which is less than one-third of the experiments that would be required by a classical DoE method and several orders of magnitude smaller compared to detailed experimental analysis of full combinatorial space. We further show the advantage of this method over conventional approaches to efficiently transfer historical information as prior knowledge for the development of new biologics or when new buffer agents are available. Moreover, we highlight the benefit of our technique in engineering multiple biophysical properties by simultaneously optimizing both thermal and interface stabilities. This optimization minimizes the amount of surfactant in the formulation, which is important to decrease the risks associated with corresponding degradation processes. Overall, this method can provide high speed of converging to optimal conditions, the ability to transfer prior knowledge, and the identification of new nonlinear combinations of excipients. We envision that these features can lead to a considerable acceleration in formulation design and to parallelization of operations during drug development.ISSN:1543-8384ISSN:1543-839