Batch correction and harmonization of –Omics datasets with a tunable median polish of ratio

Large scale −omics datasets can provide new insights into normal and disease-related biology when analyzed through a systems biology framework. However, technical artefacts present in most −omics datasets due to variations in sample preparation, batching, platform settings, personnel, and other experimental procedures prevent useful analyses of such data without prior adjustment for these technical factors. Here, we demonstrate a tunable median polish of ratio (TAMPOR) approach for batch effect correction and agglomeration of multiple, multi-batch, site-specific cohorts into a single analyte abundance data matrix that is suitable for systems biology analyses. We illustrate the utility and versatility of TAMPOR through four distinct use cases where the method has been applied to different proteomic datasets, some of which contain a specific defect that must be addressed prior to analysis. We compare quality control metrics and sources of variance before and after application of TAMPOR to show that TAMPOR is effective at removing batch effects and other unwanted sources of variance in −omics data. We also show how TAMPOR can be used to harmonize −omics datasets even when the data are acquired using different analytical approaches. TAMPOR is a powerful and flexible approach for cleaning and harmonization of −omics data prior to downstream systems biology analysis

Genetic background influences the 5XFAD Alzheimer\u27s disease mouse model brain proteome.

There is an urgent need to improve the translational validity of Alzheimer’s disease (AD) mouse models. Introducing genetic background diversity in AD mouse models has been proposed as a way to increase validity and enable the discovery of previously uncharacterized genetic contributions to AD susceptibility or resilience. However, the extent to which genetic background influences the mouse brain proteome and its perturbation in AD mouse models is unknown. In this study, we crossed the 5XFAD AD mouse model on a C57BL/6J (B6) inbred background with the DBA/2J (D2) inbred background and analyzed the effects of genetic background variation on the brain proteome in F1 progeny. Both genetic background and 5XFAD transgene insertion strongly affected protein variance in the hippocampus and cortex (n = 3,368 proteins). Protein co-expression network analysis identified 16 modules of highly co-expressed proteins common across the hippocampus and cortex in 5XFAD and non- transgenic mice. Among the modules strongly influenced by genetic background were those related to small molecule metabolism and ion transport. Modules strongly influenced by the 5XFAD transgene were related to lysosome/stress responses and neuronal synapse/signaling. The modules with the strongest relationship to human disease—neuronal synapse/signaling and lysosome/stress response—were not significantly influenced by genetic background. However, other modules in 5XFAD that were related to human disease, such as GABA synaptic signaling and mitochondrial membrane modules, were influenced by genetic background. Most disease-related modules were more strongly correlated with AD genotype in the hippocampus compared with the cortex. Our findings suggest that the genetic diversity introduced by crossing B6 and D2 inbred backgrounds influences proteomic changes related to disease in the 5XFAD model, and that proteomic analysis of other genetic backgrounds in transgenic and knock-in AD mouse models is warranted to capture the full range of molecular heterogeneity in genetically diverse models of AD

Low HDL Cholesterol is Associated with Lower Gray Matter Volume in Cognitively Healthy Adults

Dyslipidemia is common in adults and contributes to high rates of cardiovascular disease and may be linked to subsequent neurodegenerative and neurovascular diseases. This study examined whether lower brain volumes and cognition associated with dyslipidemia could be observed in cognitively healthy adults, and whether apolipoprotein E (APOE) genotype or family history of Alzheimer's disease (FHAD) alters this effect. T1-weighted magnetic resonance imaging was used to examine regional brain gray matter (GM) and white matter (WM) in 183 individuals (58.4 ± 8.0 years) using voxel-based morphometry. A non-parametric multiple linear regression model was used to assess the effect of high-density lipoprotein (HDL) and non-HDL cholesterol, APOE, and FHAD on regional GM and WM volume. A post hoc analysis was used to assess whether any significant correlations found within the volumetric analysis had an effect on cognition. HDL was positively correlated with GM volume in the bilateral temporal poles, middle temporal gyri, temporo-occipital gyri, and left superior temporal gyrus and parahippocampal region. This effect was independent of APOE and FHAD. A significant association between HDL and the Brief Visuospatial Memory Test was found. Additionally, GM volume within the right middle temporal gyrus, the region most affected by HDL, was significantly associated with the Controlled Oral Word Association Test and the Center for Epidemiological Studies Depression Scale. These findings suggest that adults with decreased levels of HDL cholesterol may be experiencing cognitive changes and GM reductions in regions associated with neurodegenerative disease and therefore, may be at greater risk for future cognitive decline

Discovery of a Gas-Rich Companion to the Extremely Metal-Poor Galaxy DDO 68

We present HI spectral-line imaging of the extremely metal-poor galaxy DDO 68. This system has a nebular oxygen abundance of only 3% Z$_{\odot}$, making it one of the most metal-deficient galaxies known in the local volume. Surprisingly, DDO 68 is a relatively massive and luminous galaxy for its metal content, making it a significant outlier in the mass-metallicity and luminosity-metallicity relationships. The origin of such a low oxygen abundance in DDO 68 presents a challenge for models of the chemical evolution of galaxies. One possible solution to this problem is the infall of pristine neutral gas, potentially initiated during a gravitational interaction. Using archival HI spectral-line imaging obtained with the Karl G. Jansky Very Large Array, we have discovered a previously unknown companion of DDO 68. This low-mass (M$_{\rm HI}$ $=$ 2.8$\times$10$^{7}$ M$_{\odot}$), recently star-forming (SFR$_{\rm FUV}$ $=$ 1.4$\times$10$^{-3}$ M$_{\odot}$ yr$^{-1}$, SFR$_{\rm H\alpha}$ $<$ 7$\times$10$^{-5}$ M$_{\odot}$ yr$^{-1}$) companion has the same systemic velocity as DDO 68 (V$_{\rm sys}$ $=$ 506 km s$^{-1}$; D $=$ 12.74$\pm$0.27 Mpc) and is located at a projected distance of 42 kpc. New HI maps obtained with the 100m Robert C. Byrd Green Bank Telescope provide evidence that DDO 68 and this companion are gravitationally interacting at the present time. Low surface brightness HI gas forms a bridge between these objects.Comment: Accepted for publication in the Astrophysical Journal Letter

Cerebrospinal fluid proteomics define the natural history of autosomal dominant Alzheimer\u27s disease

Alzheimer\u27s disease (AD) pathology develops many years before the onset of cognitive symptoms. Two pathological processes-aggregation of the amyloid-β (Aβ) peptide into plaques and the microtubule protein tau into neurofibrillary tangles (NFTs)-are hallmarks of the disease. However, other pathological brain processes are thought to be key disease mediators of Aβ plaque and NFT pathology. How these additional pathologies evolve over the course of the disease is currently unknown. Here we show that proteomic measurements in autosomal dominant AD cerebrospinal fluid (CSF) linked to brain protein coexpression can be used to characterize the evolution of AD pathology over a timescale spanning six decades. SMOC1 and SPON1 proteins associated with Aβ plaques were elevated in AD CSF nearly 30 years before the onset of symptoms, followed by changes in synaptic proteins, metabolic proteins, axonal proteins, inflammatory proteins and finally decreases in neurosecretory proteins. The proteome discriminated mutation carriers from noncarriers before symptom onset as well or better than Aβ and tau measures. Our results highlight the multifaceted landscape of AD pathophysiology and its temporal evolution. Such knowledge will be critical for developing precision therapeutic interventions and biomarkers for AD beyond those associated with Aβ and tau

Circularity in fisheries data weakens real world prediction

The systematic substitution of direct observational data with synthesized data derived from models during the stock assessment process has emerged as a low-cost alternative to direct data collection efforts. What is not widely appreciated, however, is how the use of such synthesized data can overestimate predictive skill when forecasting recruitment is part of the assessment process. Using a global database of stock assessments, we show that Standard Fisheries Models (SFMs) can successfully predict synthesized data based on presumed stock-recruitment relationships, however, they are generally less skillful at predicting observational data that are either raw or minimally filtered (denoised without using explicit stock-recruitment models). Additionally, we find that an equation-free approach that does not presume a specific stock-recruitment relationship is better than SFMs at predicting synthesized data, and moreover it can also predict observational recruitment data very well. Thus, while synthesized datasets are cheaper in the short term, they carry costs that can limit their utility in predicting real world recruitment.https://www.nature.com/articles/s41598-020-63773-3Published versio

Two New Long-Period Giant Planets from the McDonald Observatory Planet Search and Two Stars with Long-Period Radial Velocity Signals Related to Stellar Activity Cycles

We report the detection of two new long-period giant planets orbiting the stars HD 95872 and HD 162004 (ψ^1 Dra B) by the McDonald Observatory planet search. The planet HD 95872b has a minimum mass of 4.6 M_(Jup) and an orbital semimajor axis of 5.2 AU. The giant planet ψ^1 Dra Bb has a minimum mass of 1.5 M_(Jup) and an orbital semimajor axis of 4.4 AU. Both of these planets qualify as Jupiter analogs. These results are based on over one and a half decades of precise radial velocity (RV) measurements collected by our program using the McDonald Observatory Tull Coude spectrograph at the 2.7 m Harlan J. Smith Telescope. In the case of ψ^1 Dra B we also detect a long-term nonlinear trend in our data that indicates the presence of an additional giant planet, similar to the Jupiter–Saturn pair. The primary of the binary star system, ψ^1 Dra A, exhibits a very large amplitude RV variation due to another stellar companion. We detect this additional member using speckle imaging. We also report two cases—HD 10086 and HD 102870 (β Virginis)—of significant RV variation consistent with the presence of a planet, but that are probably caused by stellar activity, rather than reflexive Keplerian motion. These two cases stress the importance of monitoring the magnetic activity level of a target star, as long-term activity cycles can mimic the presence of a Jupiter-analog planet

Error-analysis and comparison to analytical models of numerical waveforms produced by the NRAR Collaboration

The Numerical-Relativity-Analytical-Relativity (NRAR) collaboration is a joint effort between members of the numerical relativity, analytical relativity and gravitational-wave data analysis communities. The goal of the NRAR collaboration is to produce numerical-relativity simulations of compact binaries and use them to develop accurate analytical templates for the LIGO/Virgo Collaboration to use in detecting gravitational-wave signals and extracting astrophysical information from them. We describe the results of the first stage of the NRAR project, which focused on producing an initial set of numerical waveforms from binary black holes with moderate mass ratios and spins, as well as one non-spinning binary configuration which has a mass ratio of 10. All of the numerical waveforms are analysed in a uniform and consistent manner, with numerical errors evaluated using an analysis code created by members of the NRAR collaboration. We compare previously-calibrated, non-precessing analytical waveforms, notably the effective-one-body (EOB) and phenomenological template families, to the newly-produced numerical waveforms. We find that when the binary's total mass is ~100-200 solar masses, current EOB and phenomenological models of spinning, non-precessing binary waveforms have overlaps above 99% (for advanced LIGO) with all of the non-precessing-binary numerical waveforms with mass ratios <= 4, when maximizing over binary parameters. This implies that the loss of event rate due to modelling error is below 3%. Moreover, the non-spinning EOB waveforms previously calibrated to five non-spinning waveforms with mass ratio smaller than 6 have overlaps above 99.7% with the numerical waveform with a mass ratio of 10, without even maximizing on the binary parameters.Comment: 51 pages, 10 figures; published versio

Effects of APOE Genotype on Brain Proteomic Network and Cell Type Changes in Alzheimer's Disease

Polymorphic alleles in the apolipoprotein E (APOE) gene are the main genetic determinants of late-onset Alzheimer's disease (AD) risk. Individuals carrying the APOE E4 allele are at increased risk to develop AD compared to those carrying the more common E3 allele, whereas those carrying the E2 allele are at decreased risk for developing AD. How ApoE isoforms influence risk for AD remains unclear. To help fill this gap in knowledge, we performed a comparative unbiased mass spectrometry-based proteomic analysis of post-mortem brain cortical tissues from pathologically-defined AD or control cases of different APOE genotypes. Control cases (n = 10) were homozygous for the common E3 allele, whereas AD cases (n = 24) were equally distributed among E2/3, E3/3, and E4/4 genotypes. We used differential protein expression and co-expression analytical approaches to assess how changes in the brain proteome are related to APOE genotype. We observed similar levels of amyloid-β, but reduced levels of neurofibrillary tau, in E2/3 brains compared to E3/3 and E4/4 AD brains. Weighted co-expression network analysis revealed 33 modules of co-expressed proteins, 12 of which were significantly different by APOE genotype in AD. The modules that were significantly different by APOE genotype were associated with synaptic transmission and inflammation, among other biological processes. Deconvolution and analysis of brain cell type changes revealed that the E2 allele suppressed homeostatic and disease-associated cell type changes in astrocytes, microglia, oligodendroglia, and endothelia. The E2 allele-specific effect on brain cell type changes was validated in a separate cohort of 130 brains. Our systems-level proteomic analyses of AD brain reveal alterations in the brain proteome and brain cell types associated with allelic variants in APOE, and suggest further areas for investigation into the upstream mechanisms that drive ApoE-associated risk for AD