Biology subjects

Gehrman, P. R.

Publications and source records attributed to Gehrman, P. R..

8 recordsLinked to original sources

bioRxiv2025

Cross-species variant-to-function analyses implicate MEIS1 in conferring sleep abnormalities and impaired cerebellar development

Genome wide association study (GWAS) reports substantially outpace subsequent functional characterization. Pinpointing the causal effector gene(s) at GWAS loci remains challenging given the non-coding genomic residency of >98% of these signals. We previously implicated effector genes at GWAS loci for the complex and polygenic disorder of human insomnia using a high-resolution cell-specific, chromatin capture-based variant-to-gene mapping protocol, paired with sleep phenotyping in Drosophila. In this study, we leveraged a diurnal vertebrate model with higher genomic conservation, namely zebrafish, to screen our six highest confidence candidate genes and identify those whose loss-of-function impaired sleep characteristics related to human insomnia-like behaviors. Of these genes, we observed that CRISPR-mediated deletion of the zebrafish ortholog of MEIS1 produced nighttime specific sleep fragmentation and increased latency to sleep, pointing to a conserved role for MEIS1 in sleep maintenance. Comparing our human cell-based chromatin accessibility and contact maps with publicly available zebrafish spatial genomic data revealed highly conserved genomic architecture harboring the insomnia GWAS variant of interest. Notably, this genomic conservation was selective for the zebrafish ortholog which contributed to the sleep phenotype, meis1b, while the duplicated ohnolog meis1a proved dispensable. Motivated by this, we characterized the spatio-temporal expression of meis1b in zebrafish, showing it is comparable to human with respect to cerebellar granule progenitors. Ultimately, we found that loss of meis1b impairs cerebellar development. Together, our work provides a powerful model for screening human disorder risk genes for sleep fragmentation using a tractable vertebrate and supports a conserved cerebellar role for MEIS1 in sleep disturbance.

neuroscience↗

bioRxiv2025

An open, fully-processed data resource for studying mood and sleep variability in the developing brain

Brain development during adolescence and early adulthood coincides with shifts in emotion regulation and sleep. Despite this, few existing datasets simultaneously characterize affective dynamics, sleep variation, and multimodal measures of brain development. Here, we describe the study protocol and initial release (n = 10) of an open data resource of neuroimaging paired with densely sampled behavioral measures in adolescents and young adults. All participants complete multi-echo functional MRI, compressed-sensing diffusion MRI, and advanced arterial spin-labeled MRI. Behavioral measures include ecological momentary assessment, actigraphy, extensive cognitive assessments, and detailed clinical phenotyping focused on emotion regulation. Raw and processed data are openly available without a data use agreement and will be regularly updated as accrual continues. Together, this resource will accelerate research on the links between mood, sleep, and brain development.

neuroscience↗

bioRxiv2023

Perturbation of the insomnia WDR90 GWAS locus pinpoints rs3752495 as a causal variant influencing distal expression of neighboring gene, PIG-Q

Although genome wide association studies (GWAS) have been crucial for the identification of loci associated with sleep traits and disorders, the method itself does not directly uncover the underlying causal variants and corresponding effector genes. The overwhelming majority of such variants reside in non-coding regions and are therefore presumed to impact the activity of cis-regulatory elements, such as enhancers. Our previously reported variant-to-gene mapping effort in human induced pluripotent stem cell (iPSC)-derived neural progenitor cells (NPCs), combined with validation in both Drosophila and zebrafish, implicated PIG-Q as a functionally relevant gene at the insomnia WDR90 locus. However, importantly that effort did not characterize the corresponding underlying causal variant at this GWAS signal. Specifically, our genome-wide ATAC-seq and high-resolution promoter-focused Capture C datasets generated in this cell setting brought our attention to a shortlist of three tightly neighboring single nucleotide polymorphisms (SNPs) in strong linkage disequilibrium in a candidate intronic enhancer region of WDR90 that contacted the open PIG-Q promoter. The objective of this study was to investigate the influence of the proxy SNPs collectively and then individually on PIG-Q modulation and to pinpoint the causal "regulatory" variant among the three SNPs. Starting at a gross level perturbation, deletion of the entire region harboring all three SNPs in human iPSC-derived neural progenitor cells via CRISPR-Cas9 editing and subsequent RNA sequencing revealed expression changes in specific PIG-Q transcripts. Results from more refined individual luciferase reporter assays for each of the three SNPs in iPSCs revealed that the intronic region with the rs3752495 risk allele induced a [~]2.5-fold increase in luciferase expression (n=10). Importantly, rs3752495 also exhibited an allele specific effect, with the risk allele increasing the luciferase expression by [~]2-fold compared to the non-risk allele. In conclusion, our variant-to-function approach and subsequent in vitro validation implicates rs3752495 as a causal insomnia risk variant embedded at the WDR90-PIG-Q locus.

genomics↗

bioRxiv2022

Zebrafish screen of high-confidence targets at insomnia GWAS loci implicates MEIS1, SKIV2L, and ARFGAP2 as conserved regulators of sleep-wake behaviors

Recent large-scale human genome-wide association studies (GWAS) for insomnia have identified more than 200 significant loci. The functional relevance of these loci to the pathogenesis of insomnia is largely unknown. GWAS signals are typically non-coding variants, which are often arbitrarily annotated to the nearest protein-coding gene; however, due to 3D chromatin structure, variants can interact with more distal genes driving their function. The distal gene may, therefore, represent the true causal gene influencing the phenotype. By integrating our high-resolution chromatin interaction maps from neural progenitor cells with phenotypic data from a Drosophila RNAi screen, we prioritized candidate genes that we hypothesized would have deep phylogenetic conservation of sleep function. To determine the conservation of these candidate genes in the context of vertebrate sleep and their relevance to insomnia-like behaviors, we performed CRISPR-Cas9 mutagenesis in larval zebrafish for six highly conserved candidate genes and examined sleep-wake behaviors using automated video-tracking. CRISPR mutation of zebrafish orthologs of MEIS1 and SKIV2L produced insomnia-like behaviors, while mutation of ARFGAP2 impaired activity and development in our larval zebrafish model, demonstrating the importance of performing functional validation of GWAS-implicated effector genes to reveal genes influencing disease-relevant mechanisms.

genetics↗

bioRxiv2021

Variant-to-gene-mapping followed by cross-species genetic screening identifies GPI-anchor biosynthesis as novel regulator of sleep

Sleep is nearly ubiquitous throughout the animal kingdom, with deficiencies in sleep having been linked to a wide range of human disorders and diseases. While genome wide association studies (GWAS) in humans have identified loci robustly associated with several heritable diseases or traits, little is known about the functional roles of the underlying causal variants in regulating sleep duration or quality. We applied an ATAC-seq/promoter focused Capture C strategy in human iPSC-derived neural progenitors to carry out a variant-to-gene mapping campaign that identified 88 candidate sleep effector genes connected to relevant GWAS signals. To functionally validate the role of the implicated effector genes in sleep regulation, we performed a neuron-specific RNAi screen in the fruit fly, Drosophila melanogaster. This approach identified a number of genes that regulated sleep, including phosphatidylinositol N-acetylglucosaminyltransferase subunit Q (PIG-Q), a gene that encodes an enzyme involved in the first step of glycosylphosphatidylinositol (GPI)- anchor biosynthesis. We show that flies deficient for PIG-Q have longer sleep during both day and night due to an increase in the total number of sleep bouts. Subsequent systematic investigation of other PIG-family genes identified increased sleep in flies for multiple different genes within the PIG pathway. We then mutated the PIG-Q locus in zebrafish and identified similar increases in sleep to those observed in Drosophila, confirming deep homology of PIG-Q mediated sleep regulation. These results provide the first physical variant-to-gene mapping of human sleep genes followed by a model organism-based prioritization, revealing a novel and conserved role for GPI-anchor biosynthesis in sleep regulation.

genetics↗

bioRxiv2018

PennZzz - an algorithm for estimating behavioral states from wrist-worn accelerometery

Sleep is a heterogeneous behavioral state comprised of different stages and interspersed with episodes of wakefulness. Sleep/wake states can be monitored in the sleep laboratory by polysomnography (PSG). However, sleep studies are intrusive, laborious and expensive, and are usually performed over a single night. In contrast, wrist-worn activity-tracking devices (actimeters) are inexpensive, unobtrusive, and can be used to estimate sleep and wake patterns over multiple nights. We designed the PennZzz algorithm to estimate sleep and wake from actimetry data. Results obtained by actimetry-based monitoring in 26 subjects were compared to stages of sleep and wakefulness detected by simultaneous polysomnography. We found that our algorithm identifies PSG-defined wake episodes with a high accuracy (336/431 - 76% of algorithm wake events correspond to true wakefulness). Furthermore, we find that the algorithm is sensitive enough to detect the majority (258/431 - 59%) of true wake episodes occurring after the first NREM1 to NREM2 transition. With correction, algorithm outputs can be used to estimate the total amount of time awake after sleep onset. We further refined this program for application in a high-throughput manner to assess the total amount of sleep, wake, and non-wear during longer recording periods.

physiology↗

bioRxiv2018

Genome-wide association analyses of chronotype in 697,828 individuals provides new insights into circadian rhythms in humans and links to disease

Using genome-wide data from 697,828 research participants from 23andMe and UK Biobank, we increase the number of identified loci associated with being a morning person, a behavioural indicator of a persons underlying circadian rhythm, from 24 to 351. Using data from 85,760 individuals with activity-monitor derived measures of sleep timing we show that the chronotype loci influence sleep timing: the mean sleep timing of the 5% of individuals carrying the most "morningness" alleles was 25 minutes earlier than the 5% carrying the fewest. The loci were enriched for genes involved in circadian regulation, cAMP, glutamate and insulin signalling pathways, and those expressed in the retina, hindbrain, hypothalamus, and pituitary. We provide evidence that being a morning person is causally associated with better mental health but does not appear to affect BMI or Type 2 diabetes. This study offers new insights into the biology of circadian rhythms and links to disease in humans.

genetics↗

bioRxiv2018

Estimating sleep parameters using an accelerometer without sleep diary

Wrist worn raw-data accelerometers are used increasingly in large scale population research. We examined whether sleep parameters can be estimated from these data in the absence of sleep diaries. Our heuristic algorithm uses the variance in estimated z-axis angle and makes basic assumptions about sleep interruptions. Detected sleep period time window (SPT-window), was compared against sleep diary in 3752 participants (range=60-82years) and polysomnography in sleep clinic patients (N=28) and in healthy good sleepers (N=22). The SPT-window derived from the algorithm was 10.9 and 2.9 minutes longer compared with sleep diary in men and women, respectively. Mean C-statistic to detect the SPT-window compared to polysomnography was 0.86 and 0.83 in clinic-based and healthy sleepers, respectively. We demonstrated the accuracy of our algorithm to detect the SPT-window. The value of this algorithm lies in studies such as UK Biobank where a sleep diary was not used.

epidemiology↗