bioRxiv ScienceSearch

bioRxiv · 10.1101/2020.04.17.047290

Selective amplification of ipRGC signals accounts for interictal photophobia in migraine

Abstract

Second only to headache, photophobia is the most debilitating symptom reported by people with migraine. While the melanopsin-containing, intrinsically photosensitive retinal ganglion cells (ipRGCs) are thought to play a role, how cone and melanopsin signals are integrated in this pathway to produce visual discomfort is poorly understood. We studied 60 people: 20 without headache and 20 each with interictal photophobia from migraine with or without aura. Participants viewed pulses of spectral change that selectively targeted melanopsin, the cones, or both, and rated the degree of visual discomfort produced by these stimuli while we also recorded pupil responses. We examined the data within a model that describes how cone and melanopsin signals are weighted and combined at the level of the retina, and how this combined signal is transformed into a rating of discomfort or pupil response. Our results indicate that people with migraine do not differ from headache-free controls in the manner in which melanopsin and cone signals are combined. Instead, people with migraine demonstrate an amplification of integrated ipRGC signals for discomfort. This effect of migraine is selective for ratings of visual discomfort, in that an amplification of pupil responses was not seen in the migraine group, nor were group differences found in surveys of other behaviors putatively linked to ipRGC function (chronotype, seasonal sensitivity, presence of a photic sneeze reflex). By revealing a dissociation in the amplification of discomfort versus pupil response, our findings suggest a post-retinal alteration in processing of ipRGC signals for photophobia in migraine. SignificanceThe melanopsin-containing, intrinsically photosensitive retinal ganglion cells (ipRGCs) may contribute to photophobia in migraine. We measured visual discomfort and pupil responses to cone and melanopsin stimulation--the photoreceptor inputs to the ipRGCs--in people with and without migraine. We find that people with migraine do not differ from those without headaches in how cone and melanopsin signals are weighted and combined to produce visual discomfort. Instead, migraine is associated with an amplification of ipRGC signals for discomfort. This effect of migraine upon ipRGC signals is limited to photophobia, as we did not find an enhancement of pupil responses or a change in other behaviors linked to ipRGC function. Our findings suggest a post-retinal amplification of ipRGC signals for photophobia in migraine.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

McAdams, H. M., Kaiser, E. A., Igdalova, A., Haggerty, E. B., Cucchiara, B., Brainard, D. H., Aguirre, G. K.. 2020-04-18. Selective amplification of ipRGC signals accounts for interictal photophobia in migraine. https://doi.org/10.1101/2020.04.17.047290

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience