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Abstract Cognitive dysfunction is common in Parkinson’s disease (PD). We developed and evaluated an EEG-based biomarker to index cognitive functions in PD from a few minutes of resting-state EEG. We hypothesized that synchronous changes in EEG across the power spectrum can measure cognition. We optimized a data-driven algorithm to efficiently capture these changes and index cognitive function in 100 PD and 49 control participants. We compared our EEG-based cognitive index with the Montreal cognitive assessment (MoCA) and cognitive tests across different domains from National Institutes of Health (NIH) Toolbox using cross-validations, regression models, and randomization tests. Finally, we externally validated our approach on 32 PD participants. We observed cognition-related changes in EEG over multiple spectral rhythms. Utilizing only 8 best-performing electrodes, our proposed index strongly correlated with cognition (MoCA: rho = 0.68, p value

Abstract Black patients are diagnosed with Parkinson’s disease (PD) at half the rate as White patients. The reasons for this large disparity are unknown. Here, we review evidence that practitioner bias may contribute. A key sign of PD is hypomimia or decreased facial expressivity. However, practitioner bias surrounding facial expressivity in Black people versus White people may lead practitioners to appraise Black patients with hypomimia as having higher levels of facial expressivity. Furthermore, practitioner bias may cause them to characterize reduced facial expressivity as being due to negative personality traits, as opposed to a medical sign, in Black patients with hypomimia. This racial bias in the evaluation of hypomimia in Black versus White patients could profoundly impact subsequent referral decisions and rates of diagnosis of PD. Therefore, exploring these differences is expected to facilitate addressing health care disparities through earlier and more accurate detection of PD in Black patients.

Parkinson’s disease (PD) is a neurodegenerative disease with cognitive as well as motor impairments. While much is known about the brain networks leading to motor impairments in PD, less is known about the brain networks contributing to cognitive impairments. Here, we leveraged resting-state functional magnetic resonance imaging (rs-fMRI) data from the Parkinson’s Progression Marker Initiative (PPMI) to examine network dysfunction in PD patients with cognitive impairment. We focus on canonical cortical networks linked to cognition, including the salience network (SAL), frontoparietal network (FPN), and default mode network (DMN), as well as a subcortical basal ganglia network (BGN). We used the Montreal Cognitive Assessment (MoCA) as a continuous index of coarse cognitive function in PD. In 82 PD patients, we found that lower MoCA scores were linked with lower intra-network connectivity of the FPN. We also found that lower MoCA scores were linked with lower inter-network connectivity between the SAL and the BGN, the SAL and the DMN, as well as the FPN and the DMN. These data elucidate the relationship of cortical and subcortical functional connectivity with cognitive impairments in PD.

Abstract Terazosin is an α1-adrenergic receptor antagonist that enhances glycolysis and increases cellular ATP by binding to the enzyme phosphoglycerate kinase 1 (PGK1). Recent work has shown that terazosin is protective against motor dysfunction in rodent models of Parkinson’s disease (PD) and is associated with slowed motor symptom progression in PD patients. However, PD is also characterized by profound cognitive symptoms. We tested the hypothesis that terazosin protects against cognitive symptoms associated with PD. We report two main results. First, in rodents with ventral tegmental area (VTA) dopamine depletion modeling aspects of PD-related cognitive dysfunction, we found that terazosin preserved cognitive function. Second, we found that after matching for demographics, comorbidities, and disease duration, PD patients newly started on terazosin, alfuzosin, or doxazosin had a lower hazard of being diagnosed with dementia compared to tamsulosin, an α1-adrenergic receptor antagonist that does not enhance glycolysis. Together, these findings suggest that in addition to slowing motor symptom progression, glycolysis-enhancing drugs protect against cognitive symptoms of PD.

Leucine-rich repeat kinase 2 (LRRK2) is a serine–threonine protein kinase belonging to the ROCO protein family. Within the kinase domain of LRRK2, a point mutation known as LRRK2 G2019S has emerged as the most prevalent variant associated with Parkinson’s disease. Recent clinical studies have indicated that G2019S carriers have an elevated risk of cancers, including colon cancer. Despite this observation, the underlying mechanisms linking LRRK2 G2019S to colon cancer remain elusive. In this study, employing a colitis-associated cancer (CAC) model and LRRK2 G2019S knock-in (KI) mouse model, we demonstrate that LRRK2 G2019S promotes the pathogenesis of colon cancer, characterized by increased tumor number and size in KI mice. Furthermore, LRRK2 G2019S enhances intestinal epithelial cell proliferation and inflammation within the tumor microenvironment. Mechanistically, KI mice exhibit heightened susceptibility to DSS-induced colitis, with inhibition of LRRK2 kinase activity ameliorating colitis severity and CAC progression. Our investigation also reveals that LRRK2 G2019S promotes inflammasome activation and exacerbates gut epithelium necrosis in the colitis model. Notably, GSDMD inhibitors attenuate colitis in LRRK2 G2019S KI mice. Taken together, our findings offer experimental evidence indicating that the gain-of-kinase activity in LRRK2 promotes colorectal tumorigenesis, suggesting LRRK2 as a potential therapeutic target in colon cancer patients exhibiting hyper LRRK2 kinase activity.

Abstract Brain rhythms are strongly linked with behavior, and abnormal rhythms can signify pathophysiology. For instance, the basal ganglia exhibit a wide range of low-frequency oscillations during movement, but pathological “beta” rhythms at ~ 20 Hz have been observed in Parkinson’s disease (PD) and in PD animal models. All brain rhythms have a frequency, which describes how often they oscillate, and a phase, which describes the precise time that peaks and troughs of brain rhythms occur. Although frequency has been extensively studied, the relevance of phase is unknown, in part because it is difficult to causally manipulate the instantaneous phase of ongoing brain rhythms. Here, we developed a phase-adaptive, real-time, closed-loop algorithm to deliver optogenetic stimulation at a specific phase with millisecond latency. We combined this Phase-Adaptive Brain STimulation (PABST) approach with cell-type-specific optogenetic methods to stimulate basal ganglia networks in dopamine-depleted mice that model motor aspects of human PD. We focused on striatal medium spiny neurons expressing D1-type dopamine receptors because these neurons can facilitate movement. We report three main results. First, we found that our approach delivered PABST within system latencies of 13 ms. Second, we report that closed-loop stimulation powerfully influenced the spike-field coherence of local brain rhythms within the dorsal striatum. Finally, we found that both 4 Hz PABST and 20 Hz PABST improved movement speed, but we found differences between phase only with 4 Hz PABST. These data provide causal evidence that phase is relevant for brain stimulation, which will allow for more precise, targeted, and individualized brain stimulation. Our findings are applicable to a broad range of preclinical brain stimulation approaches and could also inform circuit-specific neuromodulation treatments for human brain disease.

Abstract Patients with Parkinson’s disease (PD) can have significant cognitive dysfunction; however, the mechanisms for these cognitive symptoms are unknown. Here, we used scalp electroencephalography (EEG) to investigate the cortical basis for PD-related cognitive impairments during interval timing, which requires participants to estimate temporal intervals of several seconds. Time estimation is an ideal task demand for investigating cognition in PD because it is simple, requires medial frontal cortical areas, and recruits basic executive processes such as working memory and attention. However, interval timing has never been systematically studied in PD patients with cognitive impairments. We report three main findings. First, 71 PD patients had increased temporal variability compared to 37 demographically matched controls, and this variability correlated with cognitive dysfunction as measured by the Montreal Cognitive Assessment (MOCA). Second, PD patients had attenuated ~4 Hz EEG oscillatory activity at midfrontal electrodes in response to the interval-onset cue, which was also predictive of MOCA. Finally, trial-by-trial linear mixed-effects modeling demonstrated that cue-triggered ~4 Hz power predicted subsequent temporal estimates as a function of PD and MOCA. Our data suggest that impaired cue-evoked midfrontal ~4 Hz activity predicts increased timing variability that is indicative of cognitive dysfunction in PD. These findings link PD-related cognitive dysfunction with cortical mechanisms of cognitive control, which could advance novel biomarkers and neuromodulation for PD.

Voltage-gated Ca2+ channels are critical for the development and mature function of the nervous system. Variants in the CACNA2D4 gene encoding the α2δ-4 auxiliary subunit of these channels are associated with neuropsychiatric and neurodevelopmental disorders. α2δ-4 is prominently expressed in the retina and is crucial for vision, but extra-retinal functions of α2δ-4 have not been investigated. Here, we sought to fill this gap by analyzing the behavioral phenotypes of α2δ-4 knockout (KO) mice. α2δ-4 KO mice (both males and females) exhibited significant impairments in prepulse inhibition that were unlikely to result from the modestly elevated auditory brainstem response thresholds. Whereas α2δ-4 KO mice of both sexes were hyperactive in various assays, only females showed impaired motor coordination in the rotarod assay. α2δ-4 KO mice exhibited anxiolytic and anti-depressive behaviors in the elevated plus maze and tail suspension tests, respectively. Our results reveal an unexpected role for α2δ-4 in sensorimotor gating and motor function and identify α2δ-4 KO mice as a novel model for studying the pathophysiology associated with CACNA2D4 variants.

Introduction: Depression is a non-motor symptom of Parkinson’s disease (PD). PD-related depression is difficult to diagnose, and the neurophysiological basis is poorly understood. Depression can markedly affect cortical function, which suggests that scalp electroencephalography (EEG) may be able to distinguish depression in PD. We conducted a pilot study of depression and resting-state EEG in PD. Methods: We recruited 18 PD patients without depression, 18 PD patients with depression, and 12 demographically similar non-PD patients with clinical depression. All patients were on their usual medications. We collected resting-state EEG in all patients and compared cortical brain signal features between patients with and without depression. We used a machine learning algorithm that harnesses the entire power spectrum (linear predictive coding of EEG Algorithm for PD: LEAPD) to distinguish between groups. Results: We found differences between PD patients with and without depression in the alpha band (8–13 Hz) globally and in the beta (13–30 Hz) and gamma (30–50 Hz) bands in the central electrodes. From two minutes of resting-state EEG, we found that LEAPD-based machine learning could robustly distinguish between PD patients with and without depression with 97 % accuracy and between PD patients with depression and non-PD patients with depression with 100 % accuracy. We verified the robustness of our finding by confirming that the classification accuracy gracefully declines as data are randomly truncated. Conclusions: Our results suggest that resting-state EEG power spectral analysis has the potential to distinguish depression in PD accurately. We demonstrated the efficacy of the LEAPD algorithm in identifying PD patients with depression from PD patients without depression and controls with depression. Our data provide insight into cortical mechanisms of depression and could lead to novel neurophysiological markers for non-motor symptoms of PD.

In India, among various diseases that limit livestock production, Foot and Mouth Disease (FMD) stands first and affects thousands of animals every year. The estimation of loss due to FMD is of paramount importance for designing appropriate control plans. The economic impact studies on various livestock diseases including FMD are very minimal and hence this study assessed the economic loss due to FMD in cattle and buffaloes in few states and overall loss in the country. The total loss estimated comprise of milk yield reduction, unavailability of draught power, distress sale, treatment cost, mortality and opportunity cost of labour based on primary survey undertaken in 10 states and one Union territory. The results revealed that there was variation in loss levels between species and among the study states due to variation in disease incidence and severity levels, productive capacity of the animals, animal health infrastructure in the respective states, etc. The total estimated loss due to FMD in cattle and buffalo was INR 20,897 crore during 2013-14 with wide variation in magnitude across the states studied. The study provided empirical evidence of loss due to FMD in cattle and buffaloes in few states and overall loss in the country.

Parkinson's disease (PD) causes impaired movement and cognition. PD can involve profound changes in cortical and subcortical brain activity as measured by electroencephalography or intracranial recordings of local field potentials (LFP). Such signals can adaptively guide deep-brain stimulation (DBS) as part of PD therapy. However, adaptive DBS requires the identification of triggers of neuronal activity dependent on real time monitoring and analysis. Current methods do not always identify PD-related signals and can entail delays. We test an alternative approach based on linear predictive coding (LPC), which fits autoregressive (AR) models to time-series data. Parameters of these AR models can be calculated by fast algorithms in real time. We compare LFPs from the striatum in an animal model of PD with dopamine depletion in the absence and presence of the dopamine precursor levodopa, which is used to treat motor symptoms of PD. We show that in dopamine-depleted mice a first order AR model characterized by a single LPC parameter obtained by LFP sampling at 1 kHz for just 1 min can distinguish between levodopa-treated and saline-treated mice and outperform current methods. This suggests that LPC may be useful in online analysis of neuronal signals to guide DBS in real time and could contribute to DBS-based treatment of PD.

Parkinson’s disease dementia (PDD) and dementia with Lewy bodies (DLB) are common causes of dementia worldwide. Although considered separate entities based on the relative temporal onset of motor symptoms vs. diagnosis of dementia, it is unknown if these diseases truly have distinct cognitive profiles. We hypothesized that patients divided into PDD and DLB categories strictly by temporal criteria would have different neuropsychological profiles. We investigated this question via neuropsychological testing of PDD and DLB patients at the University of Iowa. We performed retrospective chart analysis and review of neuropsychological testing of clinically diagnosed patients with PDD or DLB, who had presented to University of Iowa’s dementia and movement disorder clinics. Forty-seven patients diagnosed by the treating neurologist as PDD or DLB were included. Neuropsychological performance was compared between groups, and as a function of the relative timing of the motor diagnosis vs. diagnosis of dementia. We found that both PDD and DLB patients showed severe deficits in executive function, visual–spatial processing, and verbal learning. However, we found no significant differences in neuropsychological performance between groups, and neuropsychological performance could not reliably account for the relative timing of motor diagnosis vs. diagnosis of dementia. Our data support the idea that DLB and PDD are on a neuropsychological spectrum.

Foot-and-mouth disease (FMD) is a highly contagious acute vesicular disease of the cloven-hoofed animals including cattle, buffalo, sheep, goats, pigs along with more than 70 wildlife species. During the year 2013, FMD outbreaks were recorded in the southern peninsular India comprising the states of Karnataka, Tamil Nadu, Kerala and Andhra Pradesh. Besides domestic livestock, captive elephants in Kerala were also affected by FMD. The suspected FMD outbreak in six elephants occurred in Neendoor of Kottayam district, Guruvayoor and Thrissur of Thrissur district in Kerala during November - December 2013. The first clinical signs recorded in the elephants were loss of appetite and lameness with mild fever. Frank lesions were grossly evident on the tongue, palate and inner mucous membrane of trunk with exudates from nostrils. There was copious salivation often appeared to be drooling. Severe lameness led to recumbency. Erosive lesions were also noticed in foot-slipper. The foot with blisters turned to open sores making the animals difficult to stand and walk. Clinical samples (foot/oral/tongue/trunk/nasal epithelium) from the FMD-suspected elephants were collected in 50% phosphate buffered saline/glycerol medium (pH-7.5). Supernatants of the homogenized clinical samples were used in a serotype differentiating antigen detection ELISA and samples found negative were further subjected to multiplex PCR. All clinical samples were found positive for FMD virus (FMDV) serotype O in antigen detection ELISA and in mPCR. The VP1 region based phylogenetic analysis indicated the involvement of O/Middle East-South Asia/Ind2001d sub-lineage of FMDV serotype O, which was also responsible for severe disease in domestic livestock in southern states of India during 2013.

The cognitive role of the cerebellum is critically tied to its distributed connections throughout the brain. Accumulating evidence from anatomical, structural and functional imaging, and lesion studies advocate a cognitive network involving indirect connections between the cerebellum and non-motor areas in the prefrontal cortex. Cerebellar stimulation dynamically influences activity in several regions of the frontal cortex and effectively improves cognition in schizophrenia. In this manuscript, we summarize current literature on the cingulocerebellar circuit and we introduce a method to interrogate this circuit combining opotogenetics, neuropharmacology, and electrophysiology in awake-behaving animals while minimizing incidental stimulation of neighboring cerebellar nuclei. We propose the novel hypothesis that optogenetic cerebellar stimulation can restore aberrant frontal activity and rescue impaired cognition in schizophrenia. We focus on how a known cognitive region in the frontal cortex, the anterior cingulate, is influenced by the cerebellum. This circuit is of particular interest because it has been confirmed using tracing studies, neuroimaging reveals its role in cognitive tasks, it is conserved from rodents to humans, and diseases such as schizophrenia and autism appear in its aberrancy. Novel tract tracing results presented here provide support for how these two areas communicate. The primary pathway involves a disynaptic connection between the cerebellar dentate nuclei and the anterior cingulate cortex. Secondarily, the pathway from cerebellar fastigial nuclei to the ventral tegmental area, which supplies dopamine to the prefrontal cortex, may play a role as schizophrenia characteristically involves dopamine deficiencies. We hope that the hypothesis described here will inspire new therapeutic strategies targeting currently untreatable cognitive impairments in schizophrenia.

Patients with Parkinson’s disease (PD) have deficits in perceptual timing, or the perception and estimation of time. PD patients can also have cognitive symptoms, including deficits in executive functions such as working memory, planning, and visuospatial attention. Here, we discuss how PD-related cognitive symptoms contribute to timing deficits. Timing is influenced by signaling of the neurotransmitter dopamine in the striatum. Timing also involves the frontal cortex, which is dysfunctional in PD. Frontal cortex impairments in PD may influence memory subsystems as well as decision processes during timing tasks. These data suggest that timing may be a type of executive function. As such, timing can be used to study the neural circuitry of cognitive symptoms of PD as they can be studied in animal models. Performance of timing tasks also maybe a useful clinical biomarker of frontal as well as striatal dysfunction in PD.

Working memory (WM) capacity and WM processing speed are simple cognitive measures that underlie human performance in complex processes such as reasoning and language comprehension. These cognitive measures have shown to be interrelated in behavioral studies, yet the neural mechanism behind this interdependence has not been elucidated. We have carried out two functional MRI studies to separately identify brain regions involved in capacity and speed. Experiment 1, using a block-design WM verbal task, identified increased WM capacity with increased activity in right prefrontal regions, and Experiment 2, using a single-trial WM verbal task, identified increased WM processing speed with increased activity in similar regions. Our results suggest that right prefrontal areas may be a common region interlinking these two cognitive measures. Moreover, an overlap analysis with regions associated with binding or chunking suggest that this strategic memory consolidation process may be the mechanism interlinking WM capacity and WM speed.

There is extensive evidence that glucocorticoid hormones enhance memory consolidation, helping to ensure that emotionally significant events are well remembered. Prior findings suggest that the anteroventral region of bed nuclei of the stria terminalis (avBST) regulates glucocorticoid release, suggesting the potential for avBST activity to influence memory consolidation following an emotionally arousing learning event. To investigate this issue, male Sprague-Dawley rats underwent inhibitory avoidance training and repeated measurement of stress hormones, immediately followed by optogenetic manipulations of either the avBST or its projections to downstream regions, and 48 h later were tested for retention. The results indicate that avBST inhibition augmented posttraining pituitary-adrenal output and enhanced the memory for inhibitory avoidance training. Pretreatment with a glucocorticoid synthesis inhibitor blocked the memory enhancement as well as the potentiated corticosterone response, indicating the dependence of the memory enhancement on glucocorticoid release during the immediate posttraining period. In contrast, posttraining avBST stimulation decreased retention yet had no effect on stress hormonal output. Subsequent experiments revealed that inhibition of avBST input to the paraventricular hypothalamus enhanced stress hormonal output and subsequent retention, whereas stimulation did not affect either. Conversely, stimulation-but not inhibition-of avBST input to the ventrolateral periaqueductal gray impaired consolidation, whereas neither manipulation affected glucocorticoid secretion. These findings indicate that divergent pathways from the avBST are responsible for the mnemonic effects of avBST inhibition versus stimulation and do so via glucocorticoid-dependent and -independent mechanisms, respectively.