Biology subjects

Berg, D.

Publications and source records attributed to Berg, D..

3 recordsLinked to original sources

bioRxiv2019

Gut microbiome signatures of risk and prodromal markers of Parkinson's disease

ObjectivesAlterations of the gut microbiome in Parkinsons disease (PD) have been repeatedly demonstrated. However, little is known about whether such alterations precede disease onset and how they may be related to risk and prodromal markers of PD. We investigated associations of these features with gut microbiome composition. MethodsEstablished risk and prodromal markers of PD as well as factors related to diet/lifestyle, bowel function and medication were studied in relation to bacterial -/{beta}-diversity, enterotypes, and taxonomic composition in stool samples of 666 elderly TREND study participants. ResultsAmong risk and prodromal markers, physical inactivity, constipation and age showed associations with - and {beta}-diversity, and for both measures subthreshold parkinsonism and physical inactivity showed interaction effects. Moreover, male sex, possible REM-sleep behavior disorder (RBD), smoking as well as body-mass-index, antidiabetic and urate-lowering medication were associated with {beta}-diversity. Physical inactivity and constipation severity were increased in individuals with the Firmicutes-enriched enterotype. Subthreshold parkinsonism was least frequently observed in individuals with the Prevotella-enriched enterotype. Differentially abundant taxa were linked to constipation, physical inactivity, possible RBD, and subthreshold parkinsonism. Substantia nigra hyperechogenicity, olfactory loss, depression, orthostatic hypotension, urinary/erectile dysfunction, PD family history and the overall prodromal PD probability showed no significant microbiome associations. InterpretationSeveral risk and prodromal markers of PD are associated with changes in gut microbiome composition. However, the impact of the gut microbiome on PD risk and potential microbiome-dependent subtypes in the prodrome of PD need further investigation based on prospective clinical and (multi)omics data in incident PD cases.

neuroscience↗

bioRxiv2019

Machine learning to detect Alzheimer’s disease from circulating non-coding RNAs

BackgroundTo develop therapeutics for Alzheimers disease, early detection of patients awakes new hope. Circulating small non-coding RNAs are among the prominent candidates for a blood-based diagnosis, requiring however growing cohort sizes.\n\nMethodsWe determined abundance levels of 21 known circulating microRNAs in 465 individuals encompassing Alzheimers patients and controls recruited in US and Germany. We computed models to assess the relation between microRNA-expression and phenotypes, gender, age and disease severity (Mini-Mental State Examination MMSE).\n\nResults20 of 21 miRNAs were consistently dys-regulated in the US and Germany. 18 were significantly correlated to neurodegeneration (adjusted p<0.05) with highest significance for miR-532-5p (adjusted p=4.8x10-30). Ten miRNAs were significantly correlated with MMSE, in particular miR-26a/26b-5p (adjusted p=0.0002). Machine learning models reached an AUC value of 87.6% in differentiating AD patients from controls.\n\nConclusionsOur data provide strong evidence for the relevance of circulating non-coding RNAs to detect Alzheimers from a blood sample.

bioinformatics↗

bioRxiv2018

Molecular Diversity of Intrinsically Photosensitive Ganglion Cells

Intrinsically photosensitive retinal ganglion cells (ipRGCs) are rare mammalian photoreceptors essential for non-image-forming vision functions, such as circadian photoentrainment and the pupillary light reflex. They comprise multiple subtypes distinguishable by morphology, physiology, projections, and levels of expression of melanopsin (Opn4), their photopigment. The molecular programs that differentiate ipRGCs from other ganglion cells and ipRGC subtypes from one another remain elusive. Here, we present comprehensive gene expression profiles of early postnatal and adult mouse ipRGCs purified from two lines of reporter mice marking different sets of ipRGC subtypes. We find dozens of novel genes highly enriched in ipRGCs. We reveal that Rasgrp1 and Tbx20 are selectively expressed in subsets of ipRGCs, though these molecularly defined groups imperfectly match established ipRGC subtypes. We demonstrate that the ipRGCs regulating circadian photoentrainment are unexpectedly diverse at the molecular level. Our findings reveal unexpected complexity in gene expression patterns across mammalian ipRGC subtypes.

neuroscience↗