Biology subjects

Maier, C.

Publications and source records attributed to Maier, C..

7 recordsLinked to original sources

bioRxiv2024

Multi-omics analysis in mouse primary cortical neurons reveals complex positive and negative biological interactions between constituent compounds in Centella asiatica

BackgroundA water extract of the Ayurvedic plant Centella asiatica (CAW) improves cognitive function in mouse models of aging and Alzheimers disease, and affects dendritic arborization, mitochondrial activity and oxidative stress in mouse primary neurons. Triterpenes (TT) and caffeoylquinic acids (CQA) are constituents associated with these bioactivities of CAW although little is known about how interactions between these compounds contribute to the plants therapeutic benefit. MethodsMouse primary cortical neurons were treated with CAW, or equivalent concentrations of four TT combined, eight CQA combined, or these twelve compounds combined (TTCQA). Treatment effects on the cell transcriptome (18,491 genes) and metabolome (192 metabolites) relative to vehicle control were evaluated using RNAseq and metabolomic analyses respectively. ResultsExtensive differentially expressed genes (DEGs) were seen with all treatments, as well as evidence of interactions between compounds. Notably many DEGs seen with TT treatment were not observed in the TTCQA condition, possibly suggesting CQA reduced the effects of TT. Moreover, additional gene activity seen with CAW as compared to TTCQA indicate the presence of additional compounds in CAW that further modulate TTCQA interactions. Weighted Gene Correlation Network Analysis (WGCNA) identified 4 gene co-expression modules altered by treatments that were associated with extracellular matrix organization, fatty acid metabolism, cellular response to stress and stimuli, and immune function. Compound interaction patterns were seen at the eigengene level in these modules. Interestingly, in metabolomics analysis, the TTCQA treatment saw the highest number of changes in individual metabolites (20), followed by CQA (15), then TT (8) and finally CAW (3). WGCNA analysis found two metabolomics modules with significant eigenmetabolite differences for TT and CQA, and possible compound interactions at this level. ConclusionsFour gene expression modules and two metabolite modules were altered by the four types of treatments applied. This methodology demonstrated the existence of both negative and positive interactions between TT, CQA and additional compounds found in CAW on the transcriptome and metabolome of mouse primary cortical neurons.

neuroscience↗

bioRxiv2022

Reversing gut microbiome-driven adipose tissue inflammation alleviates metabolic syndrome

The gut microbiota contributes to macrophage-mediated inflammation in adipose tissue with consumption of an obesogenic diet, thus driving the development of metabolic syndrome. There is a need to identify and develop interventions that abrogate this condition. The hops-derived prenylated flavonoid xanthohumol (XN) and its semi-synthetic derivative tetrahydroxanthohumol (TXN) attenuate high-fat diet-induced obesity, hepatosteatosis and metabolic syndrome in C57Bl/6J mice. This coincides with a decrease in pro-inflammatory gene expression in the gut and adipose tissue, together with alterations in the gut microbiota and bile acid composition. In this study, we integrated and interrogated multi-omics data from different organs with fecal 16S sequences and systemic metabolic phenotypic data using a transkingdom network analysis. By incorporating cell type information from single cell RNA-seq data, we discovered TXN attenuates macrophage inflammatory processes in adipose tissue. TXN treatment also reversed levels of inflammation-inducing microbes, such as Oscillibacter valericigenes, that lead to adverse metabolic phenotypes. Furthermore, in vitro validation in macrophage cell lines and in vivo mouse supplementation showed addition of O. valericigenes supernatant induced the expression of metabolic macrophage signature genes that are downregulated by TXN in vivo. Our findings establish an important mechanism by which TXN mitigates adverse phenotypic outcomes from diet-induced obesity and metabolic syndrome. It primarily reduces the abundance of pro-inflammatory gut microbes that can otherwise promote macrophage-associated inflammation in adipose tissue.

systems biology↗

bioRxiv2022

An energy-saving glasshouse film reduces seasonal, and cultivar dependent Capsicum yield due to light limited photosynthesis

Glasshouse films can be used to reduce energy costs by limiting non-productive heat-generating radiation, but the impact on yield of greenhouse horticultural crops remains unknown. The effects of energy-saving film ULR-80 (referred to as Smart Glass; SG) designed to block long wavelength light that generates heat also reduced photosynthetically active radiation (PAR) consequently affecting crop morphology, photosynthesis, leaf pigments, and yield of two hydroponically grown capsicum (Capsicum annuum L.) cultivars (Red and Orange). The crops were grown in four high-tech glasshouse bays over two seasons of similar daily light integrals (DLI) during ascending (Autumn) and descending (Summer) photoperiods. The Red cultivar exhibited higher photosynthetic rates (light saturated - Asat and maximal - Amax) and yield than the Orange cultivar in control but displayed stronger reductions in modelled photosynthetic rates at growth light and yield in SG without changes in photosynthetic capacity. Foliar pigment ratios of chlorophyll a/b and carotenoid: chlorophyll remained unaffected by the SG during both seasons indicating that chloroplast homeostasis was similar between SG and control. The seasonal differences in photosynthetic pigments and xanthophyll de-epoxidation state (DPS) revealed that cultivars were able to sense the SG-altered light environment during the ascending, but not descending photoperiod. The descending photoperiod correlated with a lower daily light level and a substantial yield reduction of 29 % and 13 % in Red and Orange cultivars, respectively. Thus, SG-induced higher reductions in yield during the descending photoperiod indicate that SG may be more beneficial for capsicum crops planted during Autumn with an ascending photoperiod. HighlightsO_LIA potential energy saving SG film limited net photosynthesis of capsicum C_LIO_LIThe SG film reduced yield of two capsicum cultivars that can be mitigated by planting during the low light growth season with a shorter photoperiod C_LIO_LISG reduced genotype-dependent capsicum yield was associated with alterations in the level of foliar pigments required for photoprotection under adverse light conditions C_LI

plant biology↗

bioRxiv2019

The effect of sample size on polygenic hazard models for prostate cancer

We aimed to determine the effect of sample size on performance of polygenic hazard score (PHS) models in predicting the age at onset of prostate cancer. Age and genotypes were obtained for 40,861 men from the PRACTICAL consortium. The dataset included 201,590 SNPs per subject, and was split into training (34,444 samples) and testing (6,417 samples) sets. Two PHS model-building strategies were investigated. Established-SNP model considered 65 SNPs that had been associated with prostate cancer in the literature. A stepwise SNP selection was used to develop Discovery-SNP models. The performance of each PHS model was calculated for random sizes of the training set (1 to 30 thousand). The performance of a representative Established-SNP model was estimated for random sizes of the testing set (0.5 to 6 thousand). Mean HR98/50 (hazard ratio of top 2% to the average in the test set) of the Established-SNP model increased from 1.73[95%CI: 1.69-1.77] to 2.41[2.40-2.43] when the number of training samples was increased from 1 to 30 thousand. The corresponding HR98/50 of the Discovery-SNP model increased from 1.05[0.93-1.18] to 2.19[2.16-2.23]. HR98/50 of a representative Established-SNP model using testing set sample sizes of 0.6 and 6 thousand observations were 1.78[1.70-1.85] and 1.73[1.71-1.76], respectively. We estimate that a study population of 20 to 30 thousand men is required to develop Discovery-SNP PHS models for prostate cancer. The required sample size could be reduced to 10 thousand samples, if a set of SNPs associated with the disease has already been established.\n\nAuthor summaryPolygenic hazard scores represent a recent advancement in polygenic prediction to model the age of onset of various diseases, such as Alzheimers disease or prostate cancer. These scores accumulate small effect sizes from several tens of genetic variants and can be used to establish an individuals risk of experiencing an event relative to a control population across time. The largest barrier to the development of polygenic hazard scores is the large number of study subjects needed to develop the underlying models. We sought to understand the effect of varying the total number of samples on the performance of a polygenic hazard score in the context of prostate cancer. We found that the performance of the score did not appreciably change beyond 20 to 30 thousand observations when developing the model from scratch. However, when the discovery of the genetic variants can be borrowed from those already identified in the literature to be associated with the disease, the required number of samples is reduced to 10 thousand with no appreciable detriment in performance. We hope that these results can guide the design of future studies of polygenic scores in other diseases and demonstrate the importance of genome-wide association studies.

genetics↗

bioRxiv2019

A genetic hazard score to personalize prostate cancer screening, applied to population data

BackgroundGenetic risk stratification may inform decisions of whether--and when--a man should undergo prostate cancer (PCa) screening. We previously validated a polygenic hazard score (PHS), a weighted sum of 54 single-nucleotide polymorphism genotypes, for accurate prediction of age of onset of aggressive PCa and improved screening performance. We now assess the potential impact of PHS-informed screening.\n\nMethodsUnited Kingdom population data were fit to a continuous model of age-specific PCa incidence. Using hazard ratios estimated from ProtecT trial data, age-specific incidence rates were calculated for percentiles of genetic risk. Incidence of higher-grade PCa (Gleason[≥]7) was estimated from age-specific data from the linked CAP trial. PHS and incidence data were combined to give a risk-equivalent age, when a man with a given PHS percentile will have risk of higher-grade PCa equivalent to that of a typical man at age 50 (50-years standard). Positive predictive value (PPV) of PSA testing was calculated using PHS-adjusted (PCa-risk-equivalent age) groups identified from ProtecT.\n\nResultsExpected age of onset of higher-grade PCa is modulated by 19 years between the 1st and 99th PHS percentiles. A man with PHS in the 99th percentile reaches 50-years-standard risk at age 41; conversely, a man in the 1st percentile reaches this risk at age 60. PPV of PSA was higher for men with higher PHS-adjusted age.\n\nConclusionsPHS informs PCa screening strategies with individualized estimates of risk-equivalent age for higher-grade PCa. Screening initiation could be adjusted according to a mans genetic hazard score, improving PPV of PSA screening.

genetics↗

bioRxiv2018

T vector velocity: A new ECG biomarker for identifying drug effects on cardiac ventricular repolarization

We present a new family TrX of ECG biomarkers based on the T vector velocity (TVV) for assessing drug effects on ventricular repolarization. Assuming a link between the TVV and the instantaneous change of the cellular action potentials, drugs accelerating repolarization by blocking inward (depolarizing) ion currents cause a relative increase of the TVV, while drugs delaying repolarization by blocking outward ion currents cause a relative decrease of the TVV.\n\nEvaluating the published data from two FDA funded studies, the TrX effect profiles indicate increasingly delayed electrical activity over the entire repolarization process for drugs solely reducing outward potassium current (dofetilide, moxifloxacin). For drugs eliciting block of the inward sodium or calcium currents (mexiletine, lidocaine), the TrX effect profiles were consistent with accelerated electrical activity in the initial repolarization phase. For multichannel blocking drugs (ranolazine) or drug combinations blocking multiple ion currents (dofetilide + mexiletine, dofetilide + lidocaine), the overall TrX effect profiles indicate a superposition of the individual TrX effect profiles.\n\nThe parameter Tr40c allows separating pure potassium channel blocking drugs from multichannel blocking drugs with an area under the ROC curve (AUC) value of 0.90, CI = [0.88 to 0.92]. This is significantly larger than the performance of J-Tpeakc (0.81, CI = [0.78 to 0.84]) using the published data from the second FDA study. Further performance improvement was achieved by combining the ten parameters Tr10c to Tr100c in a logistic regression model, resulting in an AUC value of 0.94.\n\nThe TVV based approach substantially improves assessment of drug effects on cardiac repolarization, providing a plausible and improved mechanistic link between drug effects on ionic currents and overall ventricular repolarization reflected in the body surface ECG. TVV may contribute to a better assessment of the proarrhythmic risk of drugs beyond QTc prolongation and JTpeakc.

pharmacology and toxicology↗

bioRxiv2016

A genetic risk score to guide age-specific, personalized prostate cancer screening

BackgroundProstate-specific-antigen (PSA) screening resulted in reduced prostate cancer (PCa) mortality in a large clinical trial, but due to a high false-positive rate, among other concerns, many guidelines do not endorse universal screening and instead recommend an individualized decision based on each patients risk. Genetic risk may provide key information to guide the decisions of whether and at what age to screen an individual man for PCa.\n\nMethodsGenotype, PCa status, and age from 34,444 men of European ancestry from the PRACTICAL consortium database were analyzed to select single-nucleotide polymorphisms (SNPs) associated with prostate cancer diagnosis. These SNPs were then incorporated into a survival analysis to estimate their effects on age at PCa diagnosis. The resulting polygenic hazard score (PHS) is an assessment of individual genetic risk. The final model was validated in an independent dataset comprised of 6,417 men with screening PSA and genotype data. PHS was calculated for these men to test for prediction of PCa-free survival. PHS was also combined with age-specific PCa incidence data from the U.S. population to generate a PCa-Risk (PCaR) age that relates a given mans risk to that of the population average. PHS and PCaR age were evaluated for prediction of positive predictive value (PPV) of PSA screening.\n\nFindingsPHS calculated from 54 SNPs was very highly predictive of age at PCa diagnosis for men in the validation set (p =10-53). PPV of PSA screening varied from 0.18 to 0.52 for men with low and high genetic risk, respectively. PHS modulates PCa-free survival curves by an estimated 20 years between men in the 1st or 99th percentiles of genetic risk.\n\nInterpretationPolygenic hazard scores give personalized genetic risk estimates and can inform the decisions of whether and at what age to screen a man for PCa.\n\nFundingDepartment of Defense #W81XWH-13-1-0391

genetics↗