Exome Sequencing Identifies Genes and Gene Sets Contributing to Severe Childhood Obesity, Linking PHIP Variants to Repressed POMC Transcription
Marenne, G., Hendricks, A., Perdikari, A., Bounds, R., Payne, F., Keogh, J., Lelliott, C., Henning, E., Pathan, S., Ashford, S., Bochukova, E., Mistry, V., Daly, A., Hayward, C., Wareham, N., O’Rahilly, S., Langenberg, C., Wheeler, E., Zeggini, E., Farooqi, I. and Barroso, I.
2 June 2020
Obesity is genetically heterogeneous with monogenic and complex polygenic forms. Using exome and targeted sequencing in 2,737 severely obese cases and 6,704 controls, the researchers identified three genes (PHIP, DGKI, and ZMYM4) with an excess burden of very rare predicted deleterious variants in cases.
In cells, they showed that PHIP is involved in human energy homeostasis, which has potential diagnostic and therapeutic implications for patients with obesity and developmental delay.
Additionally, they found an excess burden of predicted deleterious variants involving genes nearest to loci from obesity genome-wide association studies.
Genes and gene sets influencing obesity with variable penetrance provide compelling evidence for a continuum of causality in the genetic architecture of obesity, and explain some of its missing heritability.View publication
Maria Herrero-Zazo, Tomas Fitzgerald, Vince Taylor, Helen Street, Afzal N. Chaudhry, John R. Bradley, Ewan Birney, Victoria L. Keevil
20 January 2023
- Time-series blood test & vital sign data from older inpatients were presented to HMM (Hidden Markov Models)
- Hidden clinically interpretable states were extracted, linked with diagnoses and death
- States modeled inpatient trajectories, differentiating risk from admission-discharge
- The clinical interpretation of HMM states helped explain how ML models organise data
Publication: Nature Nanotechnology
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16 January 2023
Respiratory infections are the major cause of death from infectious disease worldwide. Multiplexed diagnostic approaches are essential as many respiratory viruses have indistinguishable symptoms.
We created self-assembled DNA nanobait that can simultaneously identify multiple short RNA targets. The nanobait approach relies on specific target selection via toehold-mediated strand displacement and rapid read-out via nanopore sensing. Here, we show this platform can concurrently identify several common respiratory viruses, detecting a panel of short targets of viral nucleic acids from multiple viruses.
Our nanobait can be easily reprogrammed to discriminate viral variants, as we demonstrated for several key SARS-CoV-2 variants with single-nucleotide resolution. Lastly, we show that nanobait discriminates
between samples extracted from oropharyngeal swabs from negative and positive SARS-CoV-2 patients
Our system allows for multiplexed identification of native RNA molecules, providing a new scalable approach for diagnostics of multiple respiratory viruses in a single assay.View publication
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