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DOE OSTI2022

Multimodal parameter spaces of a complex multi-channel neuron model

One of the most common types of models that helps us to understand neuron behavior is based on the Hodgkin–Huxley ion channel formulation (HH model). A major challenge with inferring parameters in HH models is non-uniqueness: many different sets of ion channel parameter values produce similar outputs for the same input stimulus. Such phenomena result in an objective function that exhibits multiple modes (i.e., multiple local minima). This non-uniqueness of local optimality poses challenges for parameter estimation with many algorithmic optimization techniques. HH models additionally have severe non-linearities resulting in further challenges for inferring parameters in an algorithmic fashion. To address these challenges with a tractable method in high-dimensional parameter spaces, we propose using a particular Markov chain Monte Carlo (MCMC) algorithm, which has the advantage of inferring parameters in a Bayesian framework. The Bayesian approach is designed to be suitable for multimodal solutions to inverse problems. We introduce and demonstrate the method using a three-channel HH model. We then focus on the inference of nine parameters in an eight-channel HH model, which we analyze in detail. We explore how the MCMC algorithm can uncover complex relationships between inferred parameters using five injected current levels. The MCMC method provides as a result a nine-dimensional posterior distribution, which we analyze visually with solution maps or landscapes of the possible parameter sets. The visualized solution maps show new complex structures of the multimodal posteriors, and they allow for selection of locally and globally optimal value sets, and they visually expose parameter sensitivities and regions of higher model robustness. We envision these solution maps as enabling experimentalists to improve the design of future experiments, increase scientific productivity and improve on model structure and ideation when the MCMC algorithm is applied to experimental data.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Verbal Learning and Memory Deficits across Neurological and Neuropsychiatric Disorders: Insights from an ENIGMA Mega Analysis

Deficits in memory performance have been linked to a wide range of neurological and neuropsychiatric conditions. While many studies have assessed the memory impacts of individual conditions, this study considers a broader perspective by evaluating how memory recall is differentially associated with nine common neuropsychiatric conditions using data drawn from 55 international studies, aggregating 15,883 unique participants aged 15–90. The effects of dementia, mild cognitive impairment, Parkinson’s disease, traumatic brain injury, stroke, depression, attention-deficit/hyperactivity disorder (ADHD), schizophrenia, and bipolar disorder on immediate, short-, and long-delay verbal learning and memory (VLM) scores were estimated relative to matched healthy individuals. Random forest models identified age, years of education, and site as important VLM covariates. A Bayesian harmonization approach was used to isolate and remove site effects. Regression estimated the adjusted association of each clinical group with VLM scores. Memory deficits were strongly associated with dementia and schizophrenia (p < 0.001), while neither depression nor ADHD showed consistent associations with VLM scores (p > 0.05). Differences associated with clinical conditions were larger for longer delayed recall duration items. By comparing VLM across clinical conditions, this study provides a foundation for enhanced diagnostic precision and offers new insights into disease management of comorbid disorders.

Neurosciences & Neurology↗

DOE OSTI2021

Altered microRNA expression in animal models of Huntington’s disease and potential therapeutic strategies

A review of recent animal models of Huntington’s disease showed many microRNAs had altered expression levels in the striatum and cerebral cortex, and which were mostly downregulated. Among the altered microRNAs were miR-9/9*, miR-29b, miR-124a, miR-132, miR-128, miR-139, miR-122, miR-138, miR-23b, miR-135b, miR-181 (all downregulated) and miR-448 (upregulated), and similar changes had been previously found in Huntington’s disease patients. In the animal cell studies, the altered microRNAs included miR-9, miR-9*, miR-135b, miR-222 (all downregulated) and miR-214 (upregulated). In the animal models, overexpression of miR-155 and miR-196a caused a decrease in mutant huntingtin mRNA and protein level, lowered the mutant huntingtin aggregates in striatum and cortex, and improved performance in behavioral tests. Improved performance in behavioral tests also occurred with overexpression of miR-132 and miR-124. In the animal cell models, overexpression of miR-22 increased the viability of rat primary cortical and striatal neurons infected with mutant huntingtin and decreased huntingtin -enriched foci of ≥ 2 µm. Also, overexpression of miR-22 enhanced the survival of rat primary striatal neurons treated with 3-nitropropionic acid. Exogenous expression of miR-214, miR-146a, miR-150, and miR-125b decreased endogenous expression of huntingtin mRNA and protein in Hdh Q111 /Hdh Q111 cells. Further studies with animal models of Huntington’s disease are warranted to validate these findings and identify specific microRNAs whose overexpression inhibits the production of mutant huntingtin protein and other harmful processes and may provide a more effective means of treating Huntington’s disease in patients and slowing its progression.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

MicroRNA expression in animal models of amyotrophic lateral sclerosis and potential therapeutic approaches

A review of recent animal models of amyotrophic lateral sclerosis showed a large number of miRNAs had altered levels of expression in the brain and spinal cord, motor neurons of spinal cord and brainstem, and hypoglossal, facial, and red motor nuclei and were mostly upregulated. Among the miRNAs found to be upregulated in two of the studies were miR-21, miR-155, miR-125b, miR-146a, miR-124, miR-9, and miR-19b, while those downregulated in two of the studies included miR-146a, miR-29, miR-9, and miR-125b. A change of direction in miRNA expression occurred in some tissues when compared (e.g., miR-29b-3p in cerebellum and spinal cord of wobbler mice at 40 days), or at different disease stages (e.g., miR-200a in spinal cord of SOD1(G93A) mice at 95 days vs. 108 and 112 days). In the animal models, suppression of miR-129-5p resulted in increased lifespan, improved muscle strength, reduced neuromuscular junction degeneration, and tended to improve motor neuron survival in the SOD1(G93A) mouse model. Suppression of miR-155 was also associated with increased lifespan, while lowering of miR-29a tended to improve lifespan in males and increase muscle strength in SOD1(G93A) mice. Overexpression of members of miR-17~92 cluster improved motor neuron survival in SOD1(G93A) mice. Treatment with an artificial miRNA designed to target hSOD1 increased lifespan and improved muscle strength in SOD1(G93A) animals. Further studies with animal models of amyotrophic lateral sclerosis are warranted to validate these findings and identify specific miRNAs whose suppression or directed against hSOD1 results in increased lifespan, improved muscle strength, reduced neuromuscular junction degeneration, and improved motor neuron survival in SOD1(G93A) animals.

59 BASIC BIOLOGICAL SCIENCES↗