scholarly journals Type 2 Diabetes as a Determinant of Parkinson's Disease Risk and Progression

2021 ◽  
Author(s):  
Harneek Chohan ◽  
Konstantin Senkevich ◽  
Radhika K. Patel ◽  
Jonathan P. Bestwick ◽  
Benjamin M. Jacobs ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Disease Risk

scholarly journals Predicting the efficacy of exenatide in Parkinson’s disease using genetics – a Mendelian randomization study

2020 ◽  
Author(s):  
Catherine S. Storm ◽  
Demis A. Kia ◽  
Mona Almramhi ◽  
Dilan Athauda ◽  
Stephen Burgess ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Type 2 Diabetes Mellitus ◽  
Brain Tissue ◽  
Mendelian Randomization ◽  
Disease Risk ◽  
Age At Onset

AbstractBackgroundExenatide is a glucagon-like peptide 1 receptor (GLP1R) agonist used in type 2 diabetes mellitus that has shown promise for Parkinson’s disease in a phase II clinical trial. Drugs with genetic evidence are more likely to be successful in clinical trials. In this study we investigated whether the genetic technique Mendelian randomization (MR) can “rediscover” the effects of exenatide on diabetes and weight, and predict its efficacy for Parkinson’s disease.MethodsWe used genetic variants associated with increased expression of GLP1R in blood to proxy exenatide, as well as variants associated with expression of DPP4, TLR4 and 15 genes thought to act downstream of GLP1R or mimicking alternative actions of GLP-1 in blood and brain tissue. Using an MR approach, we predict the effect of exenatide on type 2 diabetes risk, body mass index (BMI), Parkinson’s disease risk and several Parkinson’s disease progression markers.ResultsWe found that genetically-raised GLP1R expression in blood was associated with lower BMI and possibly type 2 diabetes mellitus risk, but not Parkinson’s disease risk, age at onset or progression. Reduced DPP4 expression in brain tissue was significantly associated with increased Parkinson’s disease risk.ConclusionsWe demonstrate the usefulness of MR using expression data in predicting the efficacy of a drug and exploring its mechanism of action. Our data suggest that GLP-1 mimetics like exenatide, if ultimately proven to be effective in Parkinson’s disease, will be through a mechanism that is independent of GLP1R in blood.

scholarly journals Type 2 Diabetes and the Risk of Parkinson's Disease

Diabetes Care ◽  
2007 ◽  
Vol 30 (4) ◽  
pp. 842-847 ◽  
Author(s):  
G. Hu ◽  
P. Jousilahti ◽  
S. Bidel ◽  
R. Antikainen ◽  
J. Tuomilehto
Keyword(s):  
Type 2 Diabetes ◽  
Parkinson’S Disease ◽  
Parkinson's Disease

scholarly journals The impact of Type 2 diabetes in Parkinson's disease

2021 ◽  
Author(s):  
Dilan Athauda ◽  
James Evans ◽  
Anna Wernick ◽  
Gurvir Virdi ◽  
Minee Liane-Choi ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Disease Progression ◽  
Independent Predictor ◽  
Motor Symptoms ◽  
Severity Scores ◽  
The Impact ◽  
Over Time

Importance: Type 2 diabetes (T2DM) is an established risk factor for developing Parkinson's disease (PD) but its effect on disease progression is not well understood. Objective: To examine the effects of co-morbid T2DM on Parkinson's disease progression and quality of life. Design: We analysed data from the Tracking Parkinson's study, a large multi-centre prospective study in the UK. Participants: The study included 1930 adults with recent onset PD, recruited between February 2012 and May 2014, and followed up regularly thereafter. Exposure: A diagnosis of pre-existing T2DM was based on self-report at baseline. After controlling for confounders, an evaluation of how T2DM affects PD was performed by comparing symptom severity scores; and analyses using multivariable mixed models was used to determine the effects of T2DM on Parkinson's disease progression. Main Outcomes and Measures: The impact of T2DM on Parkinsons disease severity was derived from scores collected using the Movement Disorders Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS), Non-Motor Symptoms Scale (NMSS), Montreal Cognitive Assessment (MoCA), Questionnaire for impulsive-compulsive disorders in PD (QUIP), Leeds Anxiety and Depression Scale (LADS), and Schwab and England ADL scale. Results: We identified 167 (8.7%) patients with PD and T2DM (PD+T2DM) and 1763 (91.3%) with PD without T2DM (PD). Patients with T2DM had more severe motor symptoms, as assessed by MDS-UPDS III 25.8 (0.9) vs 22.5 (0.3) p=0.002, had significantly faster motor symptom progression over time (p=0.012), and T2DM was an independent predictor for the development of substantial gait impairment (HR 1.55, CI 1.07-2.23, p=0.020). Patients were more likely to have loss of independence (OR 2.08, CI 1.34-3.25, p=0.001); and depression (OR 1.62, CI 1.10-2.39, p=0.015), and developed worsening mood (p=0.041) over time compared to the PD group. T2DM was also an independent predictor for the development mild cognitive impairment (HR 1.7, CI 1.24-2.51, p=0.002) over time Conclusions and relevance: T2DM is associated with faster disease progression in PD, highlighting an interaction between these two diseases. As it is a potentially modifiable, metabolic state, with multiple peripheral and central targets for intervention, it may represent a target for ameliorating parkinsonian symptoms, and progression to disability and dementia.

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