Browsing by Author "Sack, Markus"

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    Big GABA II: Water-referenced edited MR spectroscopy at 25 research sites
    (Elsevier, 2019-05) Mikkelsen, Mark; Rimbault, Daniel L.; Barker, Peter B.; Bhattacharyya, Pallab K.; Brix, Maiken K.; Buur, Pieter F.; Cecil, Kim M.; Chan, Kimberly L.; Chen, David Y.-T.; Craven, Alexander R.; Cuypers, Koen; Dacko, Michael; Duncan, Niall W.; Dydak, Ulrike; Edmondson, David A.; Ende, Gabriele; Ersland, Lars; Forbes, Megan A.; Gao, Fei; Greenhouse, Ian; Harris, Ashley D.; He, Naying; Heba, Stefanie; Hoggard, Nigel; Hsu, Tun-Wei; Jansen, Jacobus F. A.; Kangarlu, Alayar; Lange, Thomas; Lebel, R. Marc; Li, Yan; Lin, Chien-Yuan E.; Liou, Jy-Kang; Lirng, Jiing-Feng; Liu, Feng; Long, Joanna R.; Ma, Ruoyun; Maes, Celine; Moreno-Ortega, Marta; Murray, Scott O.; Noah, Sean; Noeske, Ralph; Noseworthy, Michael D.; Oeltzschner, Georg; Porges, Eric C.; Prisciandaro, James J.; Puts, Nicolaas A.; Roberts, Timothy P. L.; Sack, Markus; Sailasuta, Napapon; Saleh, Muhammad G.; Schallmo, Michael-Paul; Simard, Nicholas; Stoffers, Diederick; Swinnen, Stephan P.; Tegenthoff, Martin; Truong, Peter; Wang, Guangbin; Wilkinson, Iain D.; Wittsack, Hans-Jörg; Woods, Adam J.; Xu, Hongmin; Yan, Fuhua; Zhang, Chencheng; Zipunnikov, Vadim; Zöllner, Helge J.; Edden, Richard A. E.; Radiology and Imaging Sciences, School of Medicine
    Accurate and reliable quantification of brain metabolites measured in vivo using 1H magnetic resonance spectroscopy (MRS) is a topic of continued interest. Aside from differences in the basic approach to quantification, the quantification of metabolite data acquired at different sites and on different platforms poses an additional methodological challenge. In this study, spectrally edited γ-aminobutyric acid (GABA) MRS data were analyzed and GABA levels were quantified relative to an internal tissue water reference. Data from 284 volunteers scanned across 25 research sites were collected using GABA+ (GABA + co-edited macromolecules (MM)) and MM-suppressed GABA editing. The unsuppressed water signal from the volume of interest was acquired for concentration referencing. Whole-brain T1-weighted structural images were acquired and segmented to determine gray matter, white matter and cerebrospinal fluid voxel tissue fractions. Water-referenced GABA measurements were fully corrected for tissue-dependent signal relaxation and water visibility effects. The cohort-wide coefficient of variation was 17% for the GABA + data and 29% for the MM-suppressed GABA data. The mean within-site coefficient of variation was 10% for the GABA + data and 19% for the MM-suppressed GABA data. Vendor differences contributed 53% to the total variance in the GABA + data, while the remaining variance was attributed to site- (11%) and participant-level (36%) effects. For the MM-suppressed data, 54% of the variance was attributed to site differences, while the remaining 46% was attributed to participant differences. Results from an exploratory analysis suggested that the vendor differences were related to the unsuppressed water signal acquisition. Discounting the observed vendor-specific effects, water-referenced GABA measurements exhibit similar levels of variance to creatine-referenced GABA measurements. It is concluded that quantification using internal tissue water referencing is a viable and reliable method for the quantification of in vivo GABA levels.
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    Comparison of Multivendor Single-Voxel MR Spectroscopy Data Acquired in Healthy Brain at 26 Sites
    (Radiological Society of North America, 2020-04) Považan, Michal; Mikkelsen, Mark; Berrington, Adam; Bhattacharyya, Pallab K.; Brix, Maiken K.; Buur, Pieter F.; Cecil, Kim M.; Chan, Kimberly L.; Chen, David Y.T.; Craven, Alexander R.; Cuypers, Koen; Dacko, Michael; Duncan, Niall W.; Dydak, Ulrike; Edmondson, David A.; Ende, Gabriele; Ersland, Lars; Forbes, Megan A.; Gao, Fei; Greenhouse, Ian; Harris, Ashley D.; He, Naying; Heba, Stefanie; Hoggard, Nigel; Hsu, Tun-Wei; Jansen, Jacobus F.A.; Kangarlu, Alayar; Lange, Thomas; Lebel, R. Marc; Li, Yan; Lin, Chien-Yuan E.; Liou, Jy-Kang; Lirng, Jiing-Feng; Liu, Feng; Long, Joanna R.; Ma, Ruoyun; Maes, Celine; Moreno-Ortega, Marta; Murray, Scott O.; Noah, Sean; Noeske, Ralph; Noseworthy, Michael D.; Oeltzschner, Georg; Porges, Eric C.; Prisciandaro, James J.; Puts, Nicolaas A.J.; Roberts, Timothy P.L.; Sack, Markus; Sailasuta, Napapon; Saleh, Muhammad G.; Schallmo, Michael-Paul; Simard, Nicholas; Stoffers, Diederick; Swinnen, Stephan P.; Tegenthoff, Martin; Truong, Peter; Wang, Guangbin; Wilkinson, Iain D.; Wittsack, Hans-Jörg; Woods, Adam J.; Xu, Hongmin; Yan, Fuhua; Zhang, Chencheng; Zipunnikov, Vadim; Zöllner, Helge J.; Edden, Richard A.E.; Barker, Peter B.; Radiology and Imaging Sciences, School of Medicine
    The hardware and software differences between MR vendors and individual sites influence the quantification of MR spectroscopy data. An analysis of a large data set may help to better understand sources of the total variance in quantified metabolite levels. Purpose To compare multisite quantitative brain MR spectroscopy data acquired in healthy participants at 26 sites by using the vendor-supplied single-voxel point-resolved spectroscopy (PRESS) sequence. Materials and Methods An MR spectroscopy protocol to acquire short-echo-time PRESS data from the midparietal region of the brain was disseminated to 26 research sites operating 3.0-T MR scanners from three different vendors. In this prospective study, healthy participants were scanned between July 2016 and December 2017. Data were analyzed by using software with simulated basis sets customized for each vendor implementation. The proportion of total variance attributed to vendor-, site-, and participant-related effects was estimated by using a linear mixed-effects model. P values were derived through parametric bootstrapping of the linear mixed-effects models (denoted Pboot). Results In total, 296 participants (mean age, 26 years ± 4.6; 155 women and 141 men) were scanned. Good-quality data were recorded from all sites, as evidenced by a consistent linewidth of N-acetylaspartate (range, 4.4-5.0 Hz), signal-to-noise ratio (range, 174-289), and low Cramér-Rao lower bounds (≤5%) for all of the major metabolites. Among the major metabolites, no vendor effects were found for levels of myo-inositol (Pboot > .90), N-acetylaspartate and N-acetylaspartylglutamate (Pboot = .13), or glutamate and glutamine (Pboot = .11). Among the smaller resonances, no vendor effects were found for ascorbate (Pboot = .08), aspartate (Pboot > .90), glutathione (Pboot > .90), or lactate (Pboot = .28). Conclusion Multisite multivendor single-voxel MR spectroscopy studies performed at 3.0 T can yield results that are coherent across vendors, provided that vendor differences in pulse sequence implementation are accounted for in data analysis. However, the site-related effects on variability were more profound and suggest the need for further standardization of spectroscopic protocols.
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    Differential resting-state patterns across networks are spatially associated with Comt and Trmt2a gene expression patterns in a mouse model of 22q11.2 deletion
    (Elsevier, 2021) Gass, Natalia; Peterson, Zeru; Reinwald, Jonathan; Sartorius, Alexander; Weber-Fahr, Wolfgang; Sack, Markus; Chen, Junfang; Cao, Han; Didriksen, Michael; Stensbøl, Tine Bryan; Klemme, Gabriele; Schwarz, Adam J.; Schwarz, Emanuel; Meyer-Lindenberg, Andreas; Nickl-Jockschat, Thomas; Radiology and Imaging Sciences, School of Medicine
    Copy number variations (CNV) involving multiple genes are ideal models to study polygenic neuropsychiatric disorders. Since 22q11.2 deletion is regarded as the most important single genetic risk factor for developing schizophrenia, characterizing the effects of this CNV on neural networks offers a unique avenue towards delineating polygenic interactions conferring risk for the disorder. We used a Df(h22q11)/+ mouse model of human 22q11.2 deletion to dissect gene expression patterns that would spatially overlap with differential resting-state functional connectivity (FC) patterns in this model (N = 12 Df(h22q11)/+ mice, N = 10 littermate controls). To confirm the translational relevance of our findings, we analyzed tissue samples from schizophrenia patients and healthy controls using machine learning to explore whether identified genes were co-expressed in humans. Additionally, we employed the STRING protein-protein interaction database to identify potential interactions between genes spatially associated with hypo- or hyper-FC. We found significant associations between differential resting-state connectivity and spatial gene expression patterns for both hypo- and hyper-FC. Two genes, Comt and Trmt2a, were consistently over-expressed across all networks. An analysis of human datasets pointed to a disrupted co-expression of these two genes in the brain in schizophrenia patients, but not in healthy controls. Our findings suggest that COMT and TRMT2A form a core genetic component implicated in differential resting-state connectivity patterns in the 22q11.2 deletion. A disruption of their co-expression in schizophrenia patients points out a prospective cause for the aberrance of brain networks communication in 22q11.2 deletion syndrome on a molecular level.
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    Plant cell packs: a scalable platform for recombinant protein production and metabolic engineering
    (Wiley, 2019) Rademacher, Thomas; Sack, Markus; Blessing, Daniel; Fischer, Rainer; Holland, Tanja; Buyel, Johannes; Chemistry and Chemical Biology, School of Science
    Industrial plant biotechnology applications include the production of sustainable fuels, complex metabolites and recombinant proteins, but process development can be impaired by a lack of reliable and scalable screening methods. Here, we describe a rapid and versatile expression system which involves the infusion of Agrobacterium tumefaciens into three‐dimensional, porous plant cell aggregates deprived of cultivation medium, which we have termed plant cell packs (PCPs). This approach is compatible with different plant species such as Nicotiana tabacum BY2, Nicotiana benthamiana or Daucus carota and 10‐times more effective than transient expression in liquid plant cell culture. We found that the expression of several proteins was similar in PCPs and intact plants, for example, 47 and 55 mg/kg for antibody 2G12 expressed in BY2 PCPs and N. tabacum plants respectively. Additionally, the expression of specific enzymes can either increase the content of natural plant metabolites or be used to synthesize novel small molecules in the PCPs. The PCP method is currently scalable from a microtiter plate format suitable for high‐throughput screening to 150‐mL columns suitable for initial product preparation. It therefore combined the speed of transient expression in plants with the throughput of microbial screening systems. Plant cell packs therefore provide a convenient new platform for synthetic biology approaches, metabolic engineering and conventional recombinant protein expression techniques that require the multiplex analysis of several dozen up to hundreds of constructs for efficient product and process development.