Publications by authors named "J H Ranson"

Abstract: Recent clinical trials on slowing dementia progression have led to renewed focus on finding safer, more effective treatments. One approach to identify plausible candidates is to assess whether existing medications for other conditions may affect dementia risk. We conducted a systematic review to identify studies adopting a data-driven approach to investigate the association between a wide range of prescribed medications and dementia risk.

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Introduction: Neurofilament light chain (NfL) is a specific biomarker of neuroaxonal damage and related neurodegenerative diseases. Aging acceleration, which reflects the impact of modifiable factors on the aging process, is increasingly recognized for its relevance. While normal aging is known to contribute substantially to neuroaxonal damage and many neurodegenerative diseases, the effects of aging acceleration warrant further investigation.

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Importance: An accessible marker of both biological age and dementia risk is crucial to advancing dementia prevention and treatment strategies. Although frailty is a candidate for that role, the nature of the relationship between frailty and dementia is not well understood.

Objective: To clarify the temporal relationship between frailty and incident dementia by investigating frailty trajectories in the years preceding dementia onset.

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Background:  Mendelian mutations in the Prothrombin gene () and the factor V Leiden gene () genes are established risk factors for venous thromboembolism (VTE). Walking pace is associated with the risk of coronary artery diseases, but no study has investigated its association with VTE. This study aimed to investigate the association and causality between walking pace and VTE, compare its population risk with established Mendelian mutations, and determine if blood biomarkers mediate its effect.

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Article Synopsis
  • This study explores genetic associations related to amyotrophic lateral sclerosis (ALS) and aims to provide insights into potential treatments and risk prediction.
  • The researchers identified 118 genes linked to ALS using advanced statistical methods and discovered possible repurposing opportunities for six drugs, noting varying impacts of drug classes on ALS risk.
  • The results suggest that new genetic analyses can enhance understanding of ALS mechanisms and improve predictions of disease risk and patient outcomes.
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