Neuropathological findings and in vivo imaging correlates of the red nucleus compared to those of the substantia nigra pars compacta in parkinsonisms.

INTRODUCTION: The substantia nigra pars compacta (SNc) is the key pathologic locus in neurodegenerative parkinsonian disorders. Recently, in vivo susceptibility MRI metrics were associated with postmortem glial cell density and tau burden in the SNc of parkinsonism subjects. This study investigated the red nucleus (RN), another iron-rich region adjacent to the SNc and a potential site of higher functionality in parkinsonisms. METHODS: In vivo MRI and postmortem data were obtained from 34 parkinsonism subjects and 3 controls. Neuron density, glial cell density, and percentages of area occupied by α-synuclein and tau were quantified using digitized midbrain slides. R2* and quantitative susceptibility mapping (QSM) metrics in the RN and SNc were derived from multi-gradient echo images. Histopathology data were compared between the RN and SNc using paired t-tests. MRI-histology associations were analyzed using partial Pearson correlations. RESULTS: The RN had greater neuron (t23 = 3.169, P = 0.004) and glial cell densities (t23 = 2.407, P = 0.025) than the SNc, whereas the SNc had greater α-synuclein (t28 = 4.614, P < 0.0001) and tau burden (t24 = 4.513, P = 0.0001). In both the RN (R2*: r = 0.47, P = 0.043; QSM: r = 0.52, P = 0.024) and SNc (R2*: r = 0.57, P = 0.01; QSM: r = 0.58, P = 0.009), MRI values were associated with glial cell density but not neuron density or α-synuclein (Ps > 0.092). QSM associated with tau burden (r = 0.49, P = 0.038) in the SNc, but not the RN. CONCLUSIONS: The RN is resilient to parkinsonian-related pathological processes compared to the SNc, and susceptibility MRI captured glial cell density in both regions. These findings help to further our understanding of the underlying pathophysiological processes in parkinsonisms.

Susceptibility Magnetic Resonance Imaging Correlates with Glial Density and Tau in the Substantia Nigra Pars Compacta.

BACKGROUND: Susceptibility magnetic resonance imaging (MRI) is sensitive to iron-related changes in the substantia nigra pars compacta (SNc), the key pathologic locus of parkinsonisms. It is unclear, however, if iron deposition in the SNc is associated with its neurodegeneration. OBJECTIVE: The objective of this study was to test whether susceptibility MRI metrics in parkinsonisms are associated with SNc neuropathologic features of dopaminergic neuron loss, gliosis, and α-synuclein and tau burden. METHODS: This retrospective study included 27 subjects with both in vivo MRI and postmortem data. Multigradient echo imaging was used to derive the apparent transverse relaxation rate (R2*) and quantitative susceptibility mapping (QSM) in the SNc. Archived midbrain slides that were stained with hematoxylin and eosin, anti-α-synuclein, and anti-tau were digitized to quantify neuromelanin-positive neuron density, glial density, and the percentages of area occupied by positive α-synuclein and tau staining. MRI-histology associations were examined using Pearson correlations and regression. RESULTS: Twenty-four subjects had postmortem parkinsonism diagnoses (Lewy body disorder, progressive supranuclear palsy, multiple system atrophy, and corticobasal degeneration), two had only Alzheimer's neuropathology, and one exhibited only mild atrophy. Among all subjects, both R2* and QSM were associated with glial density (r ≥ 0.67; P < 0.001) and log-transformed tau burden (r ≥ 0.53; P ≤ 0.007). Multiple linear regression identified glial density and log-transformed tau as determinants for both MRI metrics (R2 ≥ 0.580; P < 0.0001). Neither MRI metric was associated with neuron density or α-synuclein burden. CONCLUSIONS: R2* and QSM are associated with both glial density and tau burden, key neuropathologic features in the parkinsonism SNc. © 2023 International Parkinson and Movement Disorder Society.

Low plasma serotonin linked to higher nigral iron in Parkinson's disease.

A growing body of evidence suggests nigral iron accumulation plays an important role in the pathophysiology of Parkinson's disease (PD), contributing to dopaminergic neuron loss in the substantia nigra pars compacta (SNc). Converging evidence suggests this accumulation might be related to, or increased by, serotonergic dysfunction, a common, often early feature of the disease. We investigated whether lower plasma serotonin in PD is associated with higher nigral iron. We obtained plasma samples from 97 PD patients and 89 controls and MRI scans from a sub-cohort (62 PD, 70 controls). We measured serotonin concentrations using ultra-high performance liquid chromatography and regional iron content using MRI-based quantitative susceptibility mapping. PD patients had lower plasma serotonin (p < 0.0001) and higher nigral iron content (SNc: p < 0.001) overall. Exclusively in PD, lower plasma serotonin was correlated with higher nigral iron (SNc: r(58) = - 0.501, p < 0.001). This correlation was significant even in patients newly diagnosed (< 1 year) and stronger in the SNc than any other region examined. This study reveals an early, linear association between low serotonin and higher nigral iron in PD patients, which is absent in controls. This is consistent with a serotonin-iron relationship in the disease process, warranting further studies to determine its cause and directionality.

HFE H63D Limits Nigral Vulnerability to Paraquat in Agricultural Workers.

Paraquat is an herbicide whose use is associated with Parkinson's disease (PD), a neurodegenerative disorder marked by neuron loss in the substantia nigra pars compacta (SNc). We recently observed that the murine homolog to the human H63D variant of the homeostatic iron regulator (HFE) may decrease paraquat-associated nigral neurotoxicity in mice. The present study examined the potential influence of H63D on paraquat-associated neurotoxicity in humans. Twenty-eight paraquat-exposed workers were identified from exposure histories and compared with 41 unexposed controls. HFE genotypes, and serum iron and transferrin were measured from blood samples. MRI was used to assess the SNc transverse relaxation rate (R2*), a marker for iron, and diffusion tensor imaging scalars of fractional anisotropy (FA) and mean diffusivity, markers of microstructural integrity. Twenty-seven subjects (9 exposed and 18 controls) were H63D heterozygous. After adjusting for age and use of other PD-associated pesticides and solvents, serum iron and transferrin were higher in exposed H63D carriers than in unexposed carriers and HFE wildtypes. SNc R2* was lower in exposed H63D carriers than in unexposed carriers, whereas SNc FA was lower in exposed HFE wildtypes than in either unexposed HFE wildtypes or exposed H63D carriers. Serum iron and SNc FA measures correlated positively among exposed, but not unexposed, subjects. These data suggest that H63D heterozygosity is associated with lower neurotoxicity presumptively linked to paraquat. Future studies with larger cohorts are warranted to replicate these findings and examine potential underlying mechanisms, especially given the high prevalence of the H63D allele in humans.

Towards natural mimetics of metformin and rapamycin.

Aging is now at the forefront of major challenges faced globally, creating an immediate need for safe, widescale interventions to reduce the burden of chronic disease and extend human healthspan. Metformin and rapamycin are two FDA-approved mTOR inhibitors proposed for this purpose, exhibiting significant anti-cancer and anti-aging properties beyond their current clinical applications. However, each faces issues with approval for off-label, prophylactic use due to adverse effects. Here, we initiate an effort to identify nutraceuticals-safer, naturally-occurring compounds-that mimic the anti-aging effects of metformin and rapamycin without adverse effects. We applied several bioinformatic approaches and deep learning methods to the Library of Integrated Network-based Cellular Signatures (LINCS) dataset to map the gene- and pathway-level signatures of metformin and rapamycin and screen for matches among over 800 natural compounds. We then predicted the safety of each compound with an ensemble of deep neural network classifiers. The analysis revealed many novel candidate metformin and rapamycin mimetics, including allantoin and ginsenoside (metformin), epigallocatechin gallate and isoliquiritigenin (rapamycin), and withaferin A (both). Four relatively unexplored compounds also scored well with rapamycin. This work revealed promising candidates for future experimental validation while demonstrating the applications of powerful screening methods for this and similar endeavors.

Systems Genetics Analysis of Iron and Its Regulation in Brain and Periphery.

In this contribution, we demonstrate the utility of the systems genetics-systems biology approach to the study of iron regulation while employing a comprehensive database. We describe our work in iron regulation in the brain and periphery under normal iron and iron-restricted dietary conditions in the BXD family of recombinant inbred mouse strains. Using multiple measures, we showed wide variation among the strains in the effect of being fed an iron-restricted diet for 100 days in every measure from brain and from the periphery. All data were entered into GeneNetwork ( www.genenetwork.org ), a database that contains genotypic, phenotypic, and gene expression data (Rosen et al., Methods Mol Biol 401:287-303, 2007). Using this resource, we were able to ask the following four questions concerning possible candidate genes underlying our measures: (1) what is the range of response for each of the measures? (2) Does the pattern of variability show continuous (additive genetic) or discrete (Mendelian) distribution across strains? (3) Are there genetic markers that are associated with the variability in the measures? (4) Are there genes in near the markers that contain associated allelic differences, and whose expression is related to the variability in the measures? Other questions that we could address include: (5) what is the association among the measures between the sexes? (6) What is the association among the measures, e.g., is liver iron status under the diets related to brain iron? (7) What is the relationship between our measures and other phenotypic parameters-i.e., is there an association between our brain iron measures and neurochemical phenotypes extant in the database? And finally, (8) are there gene networks that underlie single or combined measures?

In search for geroprotectors: in silico screening and in vitro validation of signalome-level mimetics of young healthy state.

Populations in developed nations throughout the world are rapidly aging, and the search for geroprotectors, or anti-aging interventions, has never been more important. Yet while hundreds of geroprotectors have extended lifespan in animal models, none have yet been approved for widespread use in humans. GeroScope is a computational tool that can aid prediction of novel geroprotectors from existing human gene expression data. GeroScope maps expression differences between samples from young and old subjects to aging-related signaling pathways, then profiles pathway activation strength (PAS) for each condition. Known substances are then screened and ranked for those most likely to target differential pathways and mimic the young signalome. Here we used GeroScope and shortlisted ten substances, all of which have lifespan-extending effects in animal models, and tested 6 of them for geroprotective effects in senescent human fibroblast cultures. PD-98059, a highly selective MEK1 inhibitor, showed both life-prolonging and rejuvenating effects. Natural compounds like N-acetyl-L-cysteine, Myricetin and Epigallocatechin gallate also improved several senescence-associated properties and were further investigated with pathway analysis. This work not only highlights several potential geroprotectors for further study, but also serves as a proof-of-concept for GeroScope, Oncofinder and other PAS-based methods in streamlining drug prediction, repurposing and personalized medicine.

Aging Chart: a community resource for rapid exploratory pathway analysis of age-related processes.

Aging research is a multi-disciplinary field encompassing knowledge from many areas of basic, applied and clinical research. Age-related processes occur on molecular, cellular, tissue, organ, system, organismal and even psychological levels, trigger the onset of multiple debilitating diseases and lead to a loss of function, and there is a need for a unified knowledge repository designed to track, analyze and visualize the cause and effect relationships and interactions between the many elements and processes on all levels. Aging Chart (http://agingchart.org/) is a new, community-curated collection of aging pathways and knowledge that provides a platform for rapid exploratory analysis. Building on an initial content base constructed by a team of experts from peer-reviewed literature, users can integrate new data into biological pathway diagrams for a visible, intuitive, top-down framework of aging processes that fosters knowledge-building and collaboration. As the body of knowledge in aging research is rapidly increasing, an open visual encyclopedia of aging processes will be useful to both the new entrants and experts in the field.

Geroprotectors.org: a new, structured and curated database of current therapeutic interventions in aging and age-related disease.

As the level of interest in aging research increases, there is a growing number of geroprotectors, or therapeutic interventions that aim to extend the healthy lifespan and repair or reduce aging-related damage in model organisms and, eventually, in humans. There is a clear need for a manually-curated database of geroprotectors to compile and index their effects on aging and age-related diseases and link these effects to relevant studies and multiple biochemical and drug databases. Here, we introduce the first such resource, Geroprotectors (http://geroprotectors.org). Geroprotectors is a public, rapidly explorable database that catalogs over 250 experiments involving over 200 known or candidate geroprotectors that extend lifespan in model organisms. Each compound has a comprehensive profile complete with biochemistry, mechanisms, and lifespan effects in various model organisms, along with information ranging from chemical structure, side effects, and toxicity to FDA drug status. These are presented in a visually intuitive, efficient framework fit for casual browsing or in-depth research alike. Data are linked to the source studies or databases, providing quick and convenient access to original data. The Geroprotectors database facilitates cross-study, cross-organism, and cross-discipline analysis and saves countless hours of inefficient literature and web searching. Geroprotectors is a one-stop, knowledge-sharing, time-saving resource for researchers seeking healthy aging solutions.

A method for predicting target drug efficiency in cancer based on the analysis of signaling pathway activation.

A new generation of anticancer therapeutics called target drugs has quickly developed in the 21st century. These drugs are tailored to inhibit cancer cell growth, proliferation, and viability by specific interactions with one or a few target proteins. However, despite formally known molecular targets for every "target" drug, patient response to treatment remains largely individual and unpredictable. Choosing the most effective personalized treatment remains a major challenge in oncology and is still largely trial and error. Here we present a novel approach for predicting target drug efficacy based on the gene expression signature of the individual tumor sample(s). The enclosed bioinformatic algorithm detects activation of intracellular regulatory pathways in the tumor in comparison to the corresponding normal tissues. According to the nature of the molecular targets of a drug, it predicts whether the drug can prevent cancer growth and survival in each individual case by blocking the abnormally activated tumor-promoting pathways or by reinforcing internal tumor suppressor cascades. To validate the method, we compared the distribution of predicted drug efficacy scores for five drugs (Sorafenib, Bevacizumab, Cetuximab, Sorafenib, Imatinib, Sunitinib) and seven cancer types (Clear Cell Renal Cell Carcinoma, Colon cancer, Lung adenocarcinoma, non-Hodgkin Lymphoma, Thyroid cancer and Sarcoma) with the available clinical trials data for the respective cancer types and drugs. The percent of responders to a drug treatment correlated significantly (Pearson's correlation 0.77 p = 0.023) with the percent of tumors showing high drug scores calculated with the current algorithm.

Screening and personalizing nootropic drugs and cognitive modulator regimens in silico.

The go-to cognitive enhancers of today are those that are widely available rather than optimal for the user, including drugs typically prescribed for treatment of ADHD (e.g., methylphenidate) and sleep disturbances such as narcolepsy (modafinil). While highly effective in their intended therapeutic role, performance gains in healthy populations are modest at best and profoundly inconsistent across subgroups and individuals. We propose a method for in silico screening of possible novel cognitive enhancers followed by high-throughput in vivo and in vitro validation. The proposed method uses gene expression data to evaluate the the collection of activated or suppressed signaling pathways in tissues or neurons of the cognitively enhanced brain. An algorithm maps expression data onto signaling pathways and quantifies their individual activation strength. The collective pathways and their activation form what we term the signaling pathway cloud, a biological fingerprint of cognitive enhancement (or any other condition of interest). Drugs can then be screened and ranked based on their ability to minimize, mimic, or exaggerate pathway activation or suppression within that cloud. Using this approach, one may predict the efficacy of many drugs that may enhance various aspects of cognition before costly preclinical studies and clinical trials are undertaken.

Systems genetic analysis of the effects of iron deficiency in mouse brain.

Iron regulation in the brain is both necessary and highly complex. Too little or too much iron can compromise neurological function, yet we still do not know all of the regulatory processes. In our research, we seek to identify genes and gene networks underlying individual differences in brain iron regulation. To this end, we fed mice from 20+ inbred strains a diet low in iron from weaning to 4 months of age. At sacrifice, we measured iron content in the ventral midbrain (VMB). The VMB contains the substantia nigra, a region particularly vulnerable to iron imbalance. The results showed high, inter-strain variability in dietary iron reduction, from almost no loss to more than 40 % vs. control. When we performed quantitative trait loci (QTL) analysis, we observed a significant area on chromosome 2. Within this QTL, we selected glial high-affinity glutamate transporter 1 (Glt1) as the leading candidate. Expression of this gene is both correlated with VMB iron and is also cis-modulated by local sequence variants that segregate in the BXD family. VMB expression differences of Glt1 in six strains covary with differential susceptibility to VMB iron loss.

Systems genetic analysis of multivariate response to iron deficiency in mice.

The aim of this study was to identify genes that influence iron regulation under varying dietary iron availability. Male and female mice from 20+ BXD recombinant inbred strains were fed iron-poor or iron-adequate diets from weaning until 4 mo of age. At death, the spleen, liver, and blood were harvested for the measurement of hemoglobin, hematocrit, total iron binding capacity, transferrin saturation, and liver, spleen and plasma iron concentration. For each measure and diet, we found large, strain-related variability. A principal-components analysis (PCA) was performed on the strain means for the seven parameters under each dietary condition for each sex, followed by quantitative trait loci (QTL) analysis on the factors. Compared with the iron-adequate diet, iron deficiency altered the factor structure of the principal components. QTL analysis, combined with PosMed (a candidate gene searching system) published gene expression data and literature citations, identified seven candidate genes, Ptprd, Mdm1, Picalm, lip1, Tcerg1, Skp2, and Frzb based on PCA factor, diet, and sex. Expression of each of these is cis-regulated, significantly correlated with the corresponding PCA factor, and previously reported to regulate iron, directly or indirectly. We propose that polymorphisms in multiple genes underlie individual differences in iron regulation, especially in response to dietary iron challenge. This research shows that iron management is a highly complex trait, influenced by multiple genes. Systems genetics analysis of iron homeostasis holds promise for developing new methods for prevention and treatment of iron deficiency anemia and related diseases.

Genetic analysis of iron-deficiency effects on the mouse spleen.

Iron homeostasis is crucial to many biological functions in nearly all organisms, with roles ranging from oxygen transport to immune function. Disruption of iron homeostasis may result in iron overload or iron deficiency. Iron deficiency may have severe consequences, including anemia or changes in immune or neurotransmitter systems. Here we report on the variability of phenotypic iron tissue loss and splenomegaly and the associated quantitative trait loci (QTLs), polymorphic areas in the mouse genome that may contain one or more genes that play a role in spleen iron concentration or spleen weight under each dietary treatment. Mice from 26 BXD/Ty recombinant inbred strains, including the parent C57BL/6 and DBA/2 strains, were randomly assigned to adequate iron or iron-deficient diets at weaning. After 120 days, splenomegaly was measured by spleen weight, and spleen iron was assessed using a modified spectrophotometry technique. QTL analyses and gene expression comparisons were then conducted using the WebQTL GeneNetwork. We observed wide, genetic-based variability in splenomegaly and spleen iron loss in BXD/Ty recombinant inbred strains fed an iron-deficient diet. Moreover, we identified several suggestive QTLs. Matching our QTLs with gene expression data from the spleen revealed candidate genes. Our work shows that individual differences in splenomegaly response to iron deficiency are influenced at least partly by genetic constitution. We propose mechanistic hypotheses by which splenomegaly may result from iron deficiency.

Systems genetics analysis of iron regulation in the brain.

Iron imbalances in the brain, including excess accumulation and deficiency, are associated with neurological disease and dysfunction; yet, their origins are poorly understood. Using systems genetics analysis, we have learned that large individual differences exist in brain iron concentrations, even in the absence of neurological disease. Much of the individual differences can be tied to the genetic makeup of the individual. This genetic-based differential regulation can be modeled in genetic reference populations of rodents. The work in our laboratory centers on iron regulation in the brain and our animal model consists of 25 BXD/Ty recombinant inbred mouse strains. By studying naturally occurring variation in iron phenotypes, such as tissue iron concentration, we can tie that variability to one or more genes by way of quantitative trait loci (QTL) analysis. Moreover, we can conduct genetic correlation analyses between our phenotypes and others previously measured in the BXD/Ty strains. We have observed several suggestive QTL related to ventral midbrain iron content, including one on chromosome 17 that contains btbd9, a gene that in humans has been associated with restless legs syndrome and serum ferritin. We have also observed gene expression correlations with ventral midbrain iron, including btbd9 expression and dopamine receptor expression. In addition, we have observed significant correlations between ventral midbrain iron content and dopamine-related phenotypes. The following is a discussion of iron regulation in the brain and the contributions a systems genetics approach can make toward understanding the genetic underpinnings and relation to neurological disease.