Mahdiar Sadeghi

Abstract Social distancing as a form of nonpharmaceutical intervention has been enacted in many countries as a form of mitigating the spread of COVID-19. There has been a large interest in mathematical modeling to aid in the prediction of both the total infected population and virus-related deaths, as well as to aid government agencies in decision making. As the virus continues to spread, there are both economic and sociological incentives to minimize time spent with strict distancing mandates enforced, and/or to adopt periodically relaxed distancing protocols, which allow for scheduled economic activity. The main objective of this study is to reduce the disease burden in a population, here measured as the peak of the infected population, while simultaneously minimizing the length of time the population is socially distanced, utilizing both a single period of social distancing as well as periodic relaxation. We derive a linear relationship among the optimal start time and duration of a single interval of social distancing from an approximation of the classic epidemic SIR model. Furthermore, we see a sharp phase transition region in start times for a single pulse of distancing, where the peak of the infected population changes rapidly; notably, this transition occurs well before one would intuitively expect. By numerical investigation of more sophisticated epidemiological models designed specifically to describe the COVID-19 pandemic, we see that all share remarkably similar dynamic characteristics when contact rates are subject to periodic or one-shot changes, and hence lead us to conclude that these features are universal in epidemic models. On the other hand, the nonlinearity of epidemic models leads to non-monotone behavior of the peak of infected population under periodic relaxation of social distancing policies. This observation led us to hypothesize that an additional single interval social distancing at a proper time can significantly decrease the infected peak of periodic policies, and we verified this improvement numerically. While synchronous quarantine and social distancing mandates across populations effectively minimize the spread of an epidemic over the world, relaxation decisions should not be enacted at the same time for different populations.

Social distance

Distancing

Epidemic model

10.1101/2020.06.21.163931

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Citations (13)

Microglia ferroptosis is prevalent in neurodegenerative disease and regulated by SEC24B

bioRxiv (Cold Spring Harbor Laboratory) (2021)

Sean K. Ryan Matija Zelic Yingnan Han Erin Teeple Luoman Chen

Abstract Iron dysregulation has been implicated in multiple neurodegenerative diseases, including Parkinson’s Disease (PD), Amyotrophic Lateral Sclerosis (ALS), and Multiple Sclerosis (MS). One prominent feature of affected brain regions are iron-loaded microglia, but how iron overload influences microglia physiology and disease response is poorly understood. Here we show that microglia are highly susceptible to ferroptosis, an iron-dependent form of cell death. In a tri-culture of human iPSC-derived neurons, astrocytes, and microglia, under ferroptosis-inducing conditions, microglia undergo a drastic shift in cell state, with increased ferritin levels, disrupted glutathione homeostasis, and altered cytokine signaling. Similar ferroptosis-associated signature (FAS) microglia were uncovered in PD, and the signature was also found in a large cohort of PD patient blood samples, raising the possibility that ferroptosis can be identified clinically. We performed a genome-wide CRISPR screen which revealed a novel regulator of ferroptosis, the vesicle trafficking gene SEC24B. A small molecule screen also nominated several candidates which blocked ferroptosis, some of which are already in clinical use. These data suggest that ferroptosis sits at the interface of cell death and inflammation, and inhibition of this process in microglia and other brain cells may provide new ways for treating neurodegenerative disease.

10.1101/2021.11.02.466996

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Network Analysis and Human Single Cell Brain Transcriptomics Reveal Novel Aspects of Alpha-Synuclein (SNCA) Biology

bioRxiv (Cold Spring Harbor Laboratory) (2020)

Erin Teeple Khushboo Jindal Beril Kiragasi Siddharth Annaldasula Annette T. Byrne

ABSTRACT Alpha-synuclein (SNCA) aggregates are pathological hallmarks of synucleinopathies, neurodegenerative disorders including Parkinson’s Disease (PD) and Lewy Body Dementia (LBD). Functional networks are not yet well-characterized for SNCA by CNS cell type. We investigated cell-specific differences in SNCA expression using Allen Brain Database single-nucleus RNA-seq data from human Middle Temporal Gyrus (MTG, 15,928 nuclei) and Anterior Cingulate Cortex (ACC, 7,258 nuclei). Weighted gene co-expression analysis (WGCNA) and hierarchical clustering identified a conserved SNCA co-expression module. Module genes were highly conserved (p < 10 −10 ) and most highly expressed in excitatory neurons versus inhibitory neurons and other glial cells. SNCA co-expression module genes from ACC and MTG regions were then used to construct a protein-protein interaction (PPI) network, with SNCA empirically top hub. Genes in the SNCA PPI network were compared with genes nearest single nucleotide polymorphisms linked with PD risk in genome-wide association studies. 16 genes in our PPI network are nearest genes to PD risk loci (p < 0.0006) and 55 genes map within 100kb. Selected SNCA PPI network genes nearest PD risk loci were disrupted by CRISPR knock out gene editing for validation of network functional significance; disruption of STK39, GBA, and MBNL2 resulted in significantly elevated intracellular SNCA expression.

Interactome

10.1101/2020.06.05.137166

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Genome-Wide Polygenic Risk Score Identifies Individuals at Elevated Parkinson’s Disease Risk (4286)

Neurology (2021)

Yingnan Han Erin Teeple Srinivas Shankara Mahdiar Sadeghi Cheng Zhu

Polygenic risk score

10.1212/wnl.96.15_supplement.4286

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Citations (2)

Virtual Source Model for Ray-Based Analysis of Focused Wave Scattering of a Penetrable Slab on PEC Ground Plane

Mahdiar Sadeghi Carey M. Rappaport

We develop a Virtual Source Model which is an intuitive, non-iterative, forward model to analyze the differential scattering of a dielectric covered conductive ground plane. This simple model is well suited for focused beam, nearfield mm-wave sensing of body-worn explosives for person scanning security systems. Ray analysis using the method of images for multiple interfaces yields good, experimentally-validated results.

Ground plane

Slab

10.1109/apusncursinrsm.2018.8609422

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Citations (9)

On the Periodic Gain of the Ribosome Flow Model

bioRxiv (Cold Spring Harbor Laboratory) (2018)

Mahdiar Sadeghi M. Ali Al-Radhawi Michael Margaliot Eduardo D. Sontag

We consider a compartmental model for ribosome flow during RNA translation called the RFM. This model includes a set of positive transition rates that control the flow from every site to the consecutive site. It has been shown that when these rates are time-varying and jointly T-periodic every solution of the RFM converges to a unique periodic solution with period T. In other words, the RFM entrains to the periodic excitation. In particular, the protein production rate converges to a unique T-periodic pattern. From a biological point of view, one may argue that the average of the periodic production rate, and not the instantaneous rate, is the relevant quantity. Here, we study a problem that can be roughly stated as: can periodic rates yield a higher average production rate than constant rates? We rigorously formulate this question and show via simulations, and rigorous analysis in one simple case, that the answer is no.

Constant (computer programming)

10.1101/507988

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Long-term regulation of prolonged epidemic outbreaks in large populations via adaptive control: a singular perturbation approach

arXiv (Cornell University) (2021)

M. Ali Al-Radhawi Mahdiar Sadeghi Eduardo D. Sontag

Initial hopes of quickly eradicating the COVID-19 pandemic proved futile, and the goal shifted to controlling the peak of the infection, so as to minimize the load on healthcare systems. To that end, public health authorities intervened aggressively to institute social distancing, lock-down policies, and other Non-Pharmaceutical Interventions (NPIs). Given the high social, educational, psychological, and economic costs of NPIs, authorities tune them, alternatively tightening up or relaxing rules, with the result that, in effect, a relatively flat infection rate results. For example, during the summer in parts of the United States, daily infection numbers dropped to a plateau. This paper approaches NPI tuning as a control-theoretic problem, starting from a simple dynamic model for social distancing based on the classical SIR epidemics model. Using a singular-perturbation approach, the plateau becomes a Quasi-Steady-State (QSS) of a reduced two-dimensional SIR model regulated by adaptive dynamic feedback. It is shown that the QSS can be assigned and it is globally asymptotically stable. Interestingly, the dynamic model for social distancing can be interpreted as a nonlinear integral controller. Problems of data fitting and parameter identifiability are also studied for this model. The paper also discusses how this simple model allows for meaningful study of the effect of population size, vaccinations, and the emergence of second waves.

Social distance

Epidemic model

Source

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Citations (1)

Accelerating Medicines Partnership: Parkinson's Disease. Genetic Resource

Movement Disorders (2021)

Hirotaka Iwaki Hampton L. Leonard Mary B. Makarious Matt Bookman Barry Landin

Abstract Background Whole‐genome sequencing data are available from several large studies across a variety of diseases and traits. However, massive storage and computation resources are required to use these data, and to achieve sufficient power for discoveries, harmonization of multiple cohorts is critical. Objectives The Accelerating Medicines Partnership Parkinson's Disease program has developed a research platform for Parkinson's disease (PD) that integrates the storage and analysis of whole‐genome sequencing data, RNA expression data, and clinical data, harmonized across multiple cohort studies. Methods The version 1 release contains whole‐genome sequencing data derived from 3941 participants from 4 cohorts. Samples underwent joint genotyping by the TOPMed Freeze 9 Variant Calling Pipeline. We performed descriptive analyses of these whole‐genome sequencing data using the Accelerating Medicines Partnership Parkinson's Disease platform. Results The clinical diagnosis of participants in version 1 release includes 2005 idiopathic PD patients, 963 healthy controls, 64 prodromal subjects, 62 clinically diagnosed PD subjects without evidence of dopamine deficit, and 705 participants of genetically enriched cohorts carrying PD risk‐associated GBA variants or LRRK2 variants, of whom 304 were affected. We did not observe significant enrichment of pathogenic variants in the idiopathic PD group, but the polygenic risk score was higher in PD both in nongenetically enriched cohorts and genetically enriched cohorts. The population analysis showed a correlation between genetically enriched cohorts and Ashkenazi Jewish ancestry. Conclusions We describe the genetic component of the Accelerating Medicines Partnership Parkinson's Disease platform, a solution to democratize data access and analysis for the PD research community. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article is a U.S. Government work and is in the public domain in the USA.

LRRK2

Genome-wide Association Study

10.1002/mds.28549

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Citations (90)

Determining the Dielectric Permittivity and Thickness of a Penetrable Slab Affixed to the Human Body Using Focused CW Mm-Wave Sensing

Mahdiar Sadeghi Elizabeth Wig Carey M. Rappaport

We propose a fast and accurate method of finding the thickness and dielectric permittivity of weak dielectric objects using a focused continuous-wave radar security scanning system, to characterize objects that may be explosive threats. Building on the previously developed ray-based Virtual Source model for sensing scattering from slabs, this work presents an inversion algorithm using two observable CW millimeter wave probe parameters by considering expected small variations of dielectric slab thickness over its surface. The determination works reasonably well with a simulated dielectric covered conductive ground plane as a representation of body worn explosives.

Slab

10.1109/apusncursinrsm.2018.8608861

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Citations (9)

Long-term regulation of prolonged epidemic outbreaks in large populations via adaptive control: a singular perturbation approach

arXiv (Cornell University) (2021)

M. Ali Al-Radhawi Mahdiar Sadeghi Eduardo D. Sontag

Initial hopes of quickly eradicating the COVID-19 pandemic proved futile, and the goal shifted to controlling the peak of the infection, so as to minimize the load on healthcare systems. To that end, public health authorities intervened aggressively to institute social distancing, lock-down policies, and other Non-Pharmaceutical Interventions (NPIs). Given the high social, educational, psychological, and economic costs of NPIs, authorities tune them, alternatively tightening up or relaxing rules, with the result that, in effect, a relatively flat infection rate results. For example, during the summer in parts of the United States, daily infection numbers dropped to a plateau. This paper approaches NPI tuning as a control-theoretic problem, starting from a simple dynamic model for social distancing based on the classical SIR epidemics model. Using a singular-perturbation approach, the plateau becomes a Quasi-Steady-State (QSS) of a reduced two-dimensional SIR model regulated by adaptive dynamic feedback. It is shown that the QSS can be assigned and it is globally asymptotically stable. Interestingly, the dynamic model for social distancing can be interpreted as a nonlinear integral controller. Problems of data fitting and parameter identifiability are also studied for this model. The paper also discusses how this simple model allows for meaningful study of the effect of population size, vaccinations, and the emergence of second waves.

Social distance

Epidemic model

10.48550/arxiv.2103.08488

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Mahdiar Sadeghi

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