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Specific PHGKB|Neurological Disorders PHGKB|PHGKB

Last Posted: Feb 03, 2023
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From precision diagnosis to precision treatment in epilepsy.
Katrine M Johannesen et al. Nature reviews. Neurology 2022 12

Technological advances over the past decade have made precision genetic diagnosis available to many patients. The findings of a new study demonstrate that genetic diagnosis in epilepsy can lead to changes in clinical management that manifest as positive outcomes for the patient. The results herald a new era in which precision diagnosis will lead to precision medicine.

Integrative genetic analysis illuminates ALS heritability and identifies risk genes.
Megat Salim et al. Nature communications 2023 1 (1) 342

We show that ALS heritability is enriched in splicing variants and in binding sites of 6 RNA-binding proteins including TDP-43 and FUS. A transcriptome wide association study (TWAS) identified 6 loci associated with ALS, including in NUP50 encoding for the nucleopore basket protein NUP50. Independently, rare variants in NUP50 were associated with ALS risk (P?=?3.71.10-03; odds ratio = 3.29; 95%CI, 1.37 to 7.87) in a cohort of 9,390 ALS/FTD patients and 4,594 controls.

Massive health-record review links viral illnesses to brain disease
M Koslov, Nature, January 23, 2023

An analysis of about 450,000 electronic health records has found a link between infections from influenza and other common viruses and an elevated risk of having a neurodegenerative condition such as Alzheimer’s or Parkinson’s disease later in life. But researchers caution that the data show only a possible connection, and that it’s still unclear how or whether the infections trigger disease onset.

Wearables and AI better predict the progression of muscular dystrophy
Nature Medicine, January 20, 2023

Clinical trials in neurological diseases often involve subjective, qualitative endpoints, such ‘by eye’ observations of movement. We developed an artificial intelligence–based method to analyze natural daily behavior data from people with Duchenne muscular dystrophy, using machine-learning algorithms to accurately predict their personal disease trajectories better than conventional clinical assessments.

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