Biology subjects

Kogelman, L. J. A.

Publications and source records attributed to Kogelman, L. J. A..

3 recordsLinked to original sources

bioRxiv2026

Menstrual cycle phase length variation is associated with daily symptom burden

Menstrual symptoms vary across the cycle, yet most research assumes a normative 28-day cycle with fixed phase durations, obscuring the physiological relevance of natural cycle variation. Using the mcPHASES dataset, we characterised cycle and phase length variation across 96 menstrual cycles from 37 participants, with ovulation timing estimated from daily urinary luteinizing hormone measurements using a Bayesian hierarchical model, and examined associations with daily symptoms in a subset of 64 cycles from 35 participants with complete symptom data. Twelve physical, mental, and behavioural symptom domains were modelled using Bayesian ordinal regression, with posterior uncertainty in phase-length predictors propagated via a measurement error framework. Total cycle length was not associated with daily symptom burden, except sleep disturbances. By contrast, phase length decomposition revealed systematic associations across multiple domains: longer menstrual phase length was broadly associated with greater symptom intensity spanning physical, gastrointestinal, affective, and sleep domains; longer luteal phase duration was associated with greater fatigue and more frequent headaches, but lower sore breast intensity and lower stress; and longer follicular phase duration and later ovulation were each associated with greater sore breast intensity and more frequent mood swings. These associations require knowledge of actual ovulation timing and cannot be recovered from cycle length alone, indicating that the common assumption of a fixed 14-day luteal phase introduces systematic misclassification of hormonal exposure. Daily symptom intensity was also predominantly person-specific, with cycle phase explaining little of the between-person variance across most symptoms. These findings indicate that calendar-based phase assignment is insufficient for research and clinical assessment of hormone-sensitive conditions, and that person-specific baselines, rather than population-level phase averages, are needed for clinically meaningful symptom monitoring.

physiology↗

bioRxiv2020

Changes in the gene expression profile during spontaneous migraine attacks

ObjectiveMigraine occurs in clearly defined attacks and thus lends itself to investigate changes during and outside attack. Gene expression fluctuates according to environmental and endogenous events and therefore is likely to reveal changes during a migraine attack. We examined the hypothesis that changes in RNA expression during and outside of a spontaneous migraine attack exist which are specific to the migraine attack. MethodsWe collected blood samples from 27 migraine patients during an attack, two hours after treatment with subcutaneous sumatriptan, on a headache-free day and after a cold pressor test. All patients were deeply phenotyped, including headache characteristics and treatment effect during the sampling. RNA-Sequencing, genotyping, and steroid profiling was performed on all samples. RNA-Sequences were analyzed at gene level (differential expression analysis) and at network level, and we integrated transcriptomic and genomic data. ResultsWe found 29 differentially expressed (DE) genes between attack and after treatment, after subtracting non-migraine specific genes, i.e. genes related to a general pain/stress response. DE genes were functioning in fatty acid oxidation, signaling pathways and immune-related pathways. Network analysis revealed molecular mechanisms affected by change in gene interactions during the migraine attack, e.g. ion transmembrane transport and response to stress. Integration of genomic and transcriptomic data revealed pathways related to sumatriptan treatment, i.e. 5HT1 type receptor mediated signaling pathway. InterpretationUsing a paired-sample design, we uniquely investigated intra-individual changes in the gene expression during a migraine attack. We revealed both genes and pathway potentially involved in the pathophysiology of migraine.

genomics↗

bioRxiv2019

Genetic Identification of Cell Types Underlying Brain Complex Traits Yields Novel Insights Into the Etiology of Parkinson's Disease

Genome-wide association studies (GWAS) have discovered hundreds of loci associated with complex brain disorders, and provide the best current insights into the etiology of these idiopathic traits. However, it remains unclear in which cell types these variants may be active, which is essential for understanding disease etiology and for disease modelling. Here we integrate GWAS results with single-cell transcriptomic data from the entire nervous system to systematically identify cell types underlying psychiatric disorders, neurological conditions, and other brain complex traits. We show that psychiatric disorders are predominantly associated with excitatory neurons from the cortex/hippocampus, medium spiny neurons from the striatum, diverse sets of midbrain neurons, and inhibitory neurons from the cortex/hippocampus. Cognitive traits were generally associated with similar cell types but their associations were driven by different genes. Neurological disorders were associated with different cell types, consistent with other lines of evidence. Notably, we found that Parkinsons disease is not only genetically associated with dopaminergic neurons but also with serotonergic neurons and cells from the oligodendrocyte lineage. Using post-mortem brain transcriptomic data, we confirmed alterations in these cells, even at the earliest stages of disease progression. Altogether, our study provides a solid framework for understanding the cellular basis of complex brain disorders and reveals a new unexpected role of oligodendrocytes in Parkinsons disease.

genomics↗