Dr. Scott C. Ritchie

@sritchie73.bsky.social

British Heart Foundation Cambridge Centre for Research Excellence Fellow & Assistant Professor of Research in the Department of Public Health and Primary Care at the University of Cambridge https://scholar.google.com/citations?user=K8qTnLUAAA

We just introduced 14 new size-resolved #lipoprotein measures for the #Nightingale #Health platform and validated them using genetic associations #GWAS. pubs.acs.org/doi/full/10....

Size-Resolved Lipoprotein Fatty Acid Content as a Novel Nuclear Magnetic Resonance-Derived Trait Specifically Associates with Genetic Variants That Control Fatty Acid Metabolism

Population-level nuclear magnetic resonance (NMR)-based lipoprotein profiling is a key tool for investigating dysregulated lipoprotein metabolism and its role in cardiovascular disorders. However, associations with size-resolved lipoprotein composition readouts are difficult to dissect, as these traits are often highly correlated. Derived variables can therefore be more relevant to biological interpretation. Here, we show that the total fatty acid (FA) content of the lipoproteins derived from their lipid headgroup concentrations using the formula FA = 3TG + 2PL + CE strongly correlates (Spearman rho = 0.98) with the independently measured total fatty acid content. This observation is not self-evident since these variables are determined using different portions of the NMR spectrum. Using NMR data acquired on the Nightingale platform for 274,303 UK Biobank (UKB) participants and genetic associations as a readout, we then show that this relationship also holds at the size-resolved lipoprotein level. We identified eight gene loci where the proposed FA variables display a significantly stronger genetic association signal than that of the corresponding lipid headgroup variables. Five of these loci (LIPC, LIPG, PLB1, LPL, and APOC3) have a direct function in FA metabolism. Including computed size-resolved FA variables may therefore improve the biological interpretation of future studies based on Nightingale’s data.

pubs.acs.org

At #EASD and interested in learning about how polygenic risk scores can be use to improve prediction and prevention of type 2 diabetes? Come see my talk at 17:25 today in the Milan Hall as part of the EASD-ADA Joint Symposium. I'll also be around until Friday afternoon if anyone wants to chat.

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⏰ Last couple of days to apply to join my group @Cambridge as a postdoc and work on the environmental (un)sustainability of AI! ⏳ Closing September 16th. ✏️ Apply here: tinyurl.com/2ukkp8yx Or learn more about what we do at www.lannelongue-group.org Initial examples of research projects below 👇

Research Associate*/Research Assistant in Sustainability of AI (Fixed Term)

An exciting opportunity has arisen for a talented researcher to join our team as part of the Green Algorithms Initiative, one of the leading academic teams in the field of sustainable computing. The

cam.ac.uk

Excited to be tutoring at the Leena Peltonen School of Human Genetics on July 27-31, alongside a stellar crew. If you’re a late-stage or recently graduated PhD student this is an awesome opportunity to get 1:1 time with faculty at the cutting edge of genomics. Apply by March 7th at lpshg.com

Flyer for the LPSHG - details in the post