Dr. Scott C. Ritchie

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.

⏰ 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 👇

prcomp() uses BLAS, which depending on the BLAS library and how R was compiled against it when R was installed will default to using all available cores.

Try adding the following code before your call to prcomp():

library(RhpcBLASctl)
blas_set_num_threads(1)
omp_set_num_threads(1)

Reminds me of this classic tweet:

Super excited to see beginning integration of PredictDB into OmicsPred!

We've annotated/deposited the GTExV8 gene expression predictors so they are now available alongside all the other multi-omic predictors at www.omicspred.org

More on its way... a wonderful collab with @hakyim.bsky.social & co!

Has Antony Green called the Eurovision winner yet? #eurovision #auspol #stillwaitingfortheprepolls

Estonia hands down

Feeling mildly emotional that this is Green’s last election coverage. He’s covered every Aus election I’ve ever seen, it won’t be the same without him #auspol

Genetic memory Genetic memory is the collection of memories of one's ancestors[1] that are passed down into subsequent generations through DNA. It enables instinctive skills in animals, and acted as an archive of hi...

GPT has consumed too much assassins creed lore: assassinscreed.fandom.com/wiki/Genetic...

Metabolic reaction fluxes as amplifiers and buffers of risk alleles for coronary artery disease | Molecular Systems Biology imageimageUsing genetically predicted metabolic reaction fluxes, the authors identify reactions that can amplify or buffer the effect of coronary artery disease (CAD) risk alleles on disease susceptib...

Our work on metabolic reaction fluxes as amplifiers and buffers of risk alleles for coronary artery disease is finally out in @molsystbiol.org !
www.embopress.org/doi/full/10....
A short thread on our key findings 🧵👇

📣 New from the lab: The contribution of genetic determinants of blood gene expression and splicing to molecular phenotypes and health outcomes www.nature.com/articles/s41...

Check out the INTERVAL RNAseq portal www.intervalrna.org.uk

Led by @alextokolyi.bsky.social & Elodie Persyn!

Wonderful to see our collaboration @astrazeneca.bsky.social @dphpc.bsky.social out! Identification of plasma proteomic markers underlying polygenic risk of T2D and related comorbidities @naturecomms.bsky.social www.nature.com/articles/s41...

Well done Doug Loesch, Dirk Paul, Abhishek Nag and co!

Human genetics suggests differing causal pathways from HMGCR inhibition to coronary artery disease and type 2 diabetes Background: Statins lower low-density lipoprotein cholesterol (LDL-C) and reduce the risk of coronary artery disease (CAD). However, they also increase the risk of type 2 diabetes (T2D). Methods: We c...

New pre-print led by @hwang_seongwon: "Human genetics suggests differing causal pathways from HMGCR inhibition to coronary artery disease and type 2 diabetes": www.medrxiv.org/content/10.1.... Brief thread follows:

Comparative Analysis Between Olink‐PEA and Alamar‐NULISA Proteomic Technologies Applied to a Critically Ill COVID‐19 Cohort We aim to verify and validate low-abundant plasma proteins from severe COVID-19 cases and controls through a comparative analysis between Olink and Alamar performances. Eighty-three severe cases and ....

Our latest Study just went online:

Comparative Analysis Between Olink-PEA and Alamar-NULISA Proteomic Technologies Applied to a Critically Ill COVID-19 Cohort

analyticalsciencejournals.onlinelibrary.wiley.com/doi/10.1002/...

A screenshot of a search for the NCBI gene website on the internet wayback machine showing snapshot archives available between 2008 and January 2025

Now's a good time for a reminder about the internet wayback machine: web.archive.org

Introducing a major upgrade to OmicsPred platform (www.omicspred.org) — a resource to enhance the accessibility and usability of genetic scores for multi-omic traits and their phenotypic associations. (1/N)

With accompanying editorial piece summarising and contextualising these findings written by myself: www.nature.com/articles/s44...

Large-scale multi-omics identifies drug targets for heart failure with reduced and preserved ejection fraction - Nature Cardiovascular Research Combining human proteome and transcriptome analyses and Mendelian randomization on a large genetic dataset of HFpEF and HFrEF cases, Rasooly et al. identified 58 potential therapeutic targets specific...

Out today in Nature Cardiovascular Research, Rasooly and colleagues utilise multiple sources of multi-omic evidence to identify new drug targets for heart failure with reduced and preserved ejection fraction: www.nature.com/articles/s44...

Clinical utility and implementation of polygenic risk scores for predicting cardiovascular disease: A clinical consensus statement of the ESC Council on Cardiovascular Genomics, the ESC Cardiovascular... Abstract. Genome-wide association studies have revealed hundreds of genetic variants associated with cardiovascular diseases (CVD). Polygenic risk scores (

Clinical utility and implementation of polygenic risk scores for predicting cardiovascular disease academic.oup.com/eurheartj/ad...

A clinical consensus statement of the ESC Council on Cardiovascular Genomics, ESC Cardiovascular Risk Collaboration and European Association of Preventive Cardiology

A platform for the biomedical application of large language models https://www.nature.com/articles/s41587-024-02534-3 (read free: https://rdcu.be/d68Ih) MIT licensed https://github.com/biocypher/biochatter 🧬🖥️🧪

Flyer for the LPSHG - details in the post

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

at first glance this just looks like ggplot but 's/geom/add/' 🤔

⏳ Just one more week to apply! 5 roles open in my group working on the Green Algorithms project: 3 research, a Software Engineer Lead and a Community manager/project coordinator
🌱 More details and links to all adverts there: www.green-algorithms.org/join-us/

Closing 25/11

#AcademicSky #SciSky

scPrediXcan integrates advances in deep learning and single-cell data into a powerful cell-type–specific transcriptome-wide association study framework Transcriptome-wide association studies (TWAS) help identify disease causing genes, but often fail to pinpoint disease mechanisms at the cellular level because of the limited sample sizes and sparsity ...

check out our new preprint led by Charles Zhou and supervised by Mengjie Chen and me doi.org/10.1101/2024... where we present scPrediXcan which integrates deep learning and single cell expression data into a powerful cell type specific TWAS framework

ukbnmr: Removal of Unwanted Technical Variation from UK Biobank NMR Metabolomics Biomarker Data A suite of utilities for working with the UK Biobank &lt;<a href="https://www.ukbiobank.ac.uk/" target="_top">https://www.ukbiobank.ac.uk/</a>&gt; Nuclear Magnetic Resonance spectroscopy (NMR) metabol...

Announcing version 3.2.0 of the ukbnmr R package now available on CRAN: cran.r-project.org/web/packages...

This is a major update that makes the package compatible with the UK Biobank Research Analysis Platform and shows removal of technical variation on the full NMR data release coming Jan 2025

Figure 4 from the preprint

Modelling the impact of these in the wider UK population, we show that supplementing screening with conventional risk factors (i.e. SCORE2) with targeted follow-up with NMR scores and PRSs could increase the # of CVD events prevented from 201 to 370 per 100K screened

Thread 3/3

Figure 3 from the preprint

Using the latest UK Biobank data, we show that:

- Integrating NMR scores and PRSs with SCORE2 can moderately improve 10-year CVD risk prediction (by up to 9%)

- Risk stratification is also improved when using ESC 2021 guideline-recommended risk categorisation

Thread 2/3

For my debut to bluesky, I am pleased to announce a new preprint:

medrxiv.org/content/10.1...

Here, we show that NMR biomarker scores combined with PRSs and SCORE2 may have moderate population health benefits for 10-year CVD risk prediction prevention

Thread 1/3: