BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//SciLifeLab - ECPv6.15.20//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:SciLifeLab
X-ORIGINAL-URL:https://www.scilifelab.se
X-WR-CALDESC:Events for SciLifeLab
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Europe/Stockholm
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20250330T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20251026T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20260329T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20261025T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20270328T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20271031T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20260325T140000
DTEND;TZID=Europe/Stockholm:20260325T150000
DTSTAMP:20260510T230727
CREATED:20260318T102028Z
LAST-MODIFIED:20260318T102029Z
UID:196453-1774447200-1774450800@www.scilifelab.se
SUMMARY:What stories can metabolites tell? Exploring data from cohorts to the individual
DESCRIPTION:Gabi Kastenmüller\,  Computational Health Center / ICB\, Helmholtz Munich \n\n\n\nAbstract\n\n\n\nMetabolites provide a direct readout of biological processes and therefore offer unique opportunities to study metabolism across populations and within individuals. In this talk\, I will give examples on how analysis and integration of metabolomics data from large cohort studies as well as smaller\, more specific challenge studies can help uncover relationships between metabolism\, genetic risk\, environmental exposures\, and health. The presentation will highlight three complementary perspectives on human metabolomics studies\, using examples from our own research. First\, I will show how genetic variation influences metabolite levels and how shared metabolite signatures across diseases can point to common biological pathways\, providing a molecular\, mechanism-oriented view on disease. Next\, I will illustrate how combining metabolite and genetic information may help stratify patients in the context of Alzheimer’s disease and its prevention. Finally\, I will discuss the potential of longitudinal metabolite profiles to monitor health and capture individual metabolic changes over time. Rather than focusing on technical aspects\, the talk aims to inspire thinking about metabolomics data analysis as a helpful tool in exploring metabolism in health and disease. \n\n\n\nBiography\n\n\n\nDr. Gabi Kastenmüller is an expert in the analysis\, integration\, and interpretation of metabolomics data and is heading a research group on Systems Metabolomics at Helmholtz Munich\, Germany. Having a background in chemistry and computer science\, she moved into bioinformatics for her PhD\, which she received from the Technische Universität München\, Germany\, in 2009. During her postdoctoral training at Karsten Suhre’s lab and a four-months stay as a visiting scientist at Metabolon Inc.\, USA\, she found her passion in metabolomics and was involved in the analysis of one of the first mass spectrometry-based metabolomics studies at large scale in two population-based cohorts. Inspired by the substantial metabolic individuality uncovered in these studies\, she started her own lab in 2011 with the goal to understand the role of metabolism and metabolic individuality in the development\, treatment\, and prevention of complex human diseases\, including Alzheimer’s disease. Thereby\, her team is particularly interested in a detailed\, systems-level understanding of which factors\, such as genotype\, lifestyle\, and microbiome composition\, shape and influence one’s personal metabolome and its changes over time. To this end\, her group experienced in computational biology collaborates with epidemiologists\, clinicians\, nutrition and sports scientists. Leveraging and integrating large-scale omics data within these collaborations enabled characterization of the human metabolic individuality in many cohorts and conditions\, including individuality in the response to physiological stimuli such as exercise or intake of specific food. \n\n\n\n \n\n\n\nHost: Elena Dracheva\, NBIS (elena.dracheva@scilifelab.se) \n\n\n\nBroadcast link (live event):  https://umu.zoom.us/j/61077879409 \n\n\n\nThe talk is sponsored by the NBIS course Introduction to Metabolomics Data Analysis. \n\n\n\nA recording  will also be available on the NBIS YouTube channel.
URL:https://www.scilifelab.se/event/what-stories-can-metabolites-tell-exploring-data-from-cohorts-to-the-individual/
LOCATION:Online event via Zoom
CATEGORIES:Event
ORGANIZER;CN="BiG Talks":MAILTO:info@nbis.se
END:VEVENT
END:VCALENDAR