Diabetes mellitus, prediabetes and the risk of Parkinson’s disease: a systematic review and meta-analysis of 15 cohort studies with 29.9 million participants and 86,345 cases

A diagnosis of diabetes mellitus and prediabetes has been associated with increased risk of Parkinson’s disease (PD) in several studies, but results have not been entirely consistent. We conducted a systematic review and meta-analysis of cohort studies on diabetes mellitus, prediabetes and the risk of PD to provide an up-to-date assessment of the evidence. PubMed and Embase databases were searched for relevant studies up to 6th of February 2022. Cohort studies reporting adjusted relative risk (RR) estimates and 95% confidence intervals (CIs) for the association between diabetes, prediabetes and Parkinson’s disease were included. Summary RRs (95% CIs) were calculated using a random effects model. Fifteen cohort studies (29.9 million participants, 86,345 cases) were included in the meta-analysis. The summary RR (95% CI) of PD for persons with diabetes compared to persons without diabetes was 1.27 (1.20–1.35, I2 = 82%). There was no indication of publication bias, based on Egger’s test (p = 0.41), Begg’s test (p = 0.99), and inspection of the funnel plot. The association was consistent across geographic regions, by sex, and across several other subgroup and sensitivity analyses. There was some suggestion of a stronger association for diabetes patients reporting diabetes complications than for diabetes patients without complications (RR = 1.54, 1.32–1.80 [n = 3] vs. 1.26, 1.16–1.38 [n = 3]), vs. those without diabetes (pheterogeneity=0.18). The summary RR for prediabetes was 1.04 (95% CI: 1.02–1.07, I2 = 0%, n = 2). Our results suggest that patients with diabetes have a 27% increased relative risk of developing PD compared to persons without diabetes, and persons with prediabetes have a 4% increase in RR compared to persons with normal blood glucose. Further studies are warranted to clarify the specific role age of onset or duration of diabetes, diabetic complications, glycaemic level and its long-term variability and management may play in relation to PD risk

Clinical reporting following the quantification of cerebrospinal fluid biomarkers in Alzheimer's disease: An international overview

Introduction: The current practice of quantifying cerebrospinal fluid (CSF) biomarkers as an aid in the diagnosis of Alzheimer's disease (AD) varies from center to center. For a same biochemical profile, interpretation and reporting of results may differ, which can lead to misunderstandings and raises questions about the commutability of tests. Methods: We obtained a description of (pre-)analytical protocols and sample reports from 40 centers worldwide. A consensus approach allowed us to propose harmonized comments corresponding to the different CSF biomarker profiles observed in patients. Results: The (pre-)analytical procedures were similar between centers. There was considerable heterogeneity in cutoff definitions and report comments. We therefore identified and selected by consensus the most accurate and informative comments regarding the interpretation of CSF biomarkers in the context of AD diagnosis. Discussion: This is the first time that harmonized reports are proposed across worldwide specialized laboratories involved in the biochemical diagnosis of AD

The 2022 symposium on dementia and brain aging in low- and middle-income countries: Highlights on research, diagnosis, care, and impact

\ua9 2024 The Authors. Alzheimer\u27s & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer\u27s Association.Two of every three persons living with dementia reside in low- and middle-income countries (LMICs). The projected increase in global dementia rates is expected to affect LMICs disproportionately. However, the majority of global dementia care costs occur in high-income countries (HICs), with dementia research predominantly focusing on HICs. This imbalance necessitates LMIC-focused research to ensure that characterization of dementia accurately reflects the involvement and specificities of diverse populations. Development of effective preventive, diagnostic, and therapeutic approaches for dementia in LMICs requires targeted, personalized, and harmonized efforts. Our article represents timely discussions at the 2022 Symposium on Dementia and Brain Aging in LMICs that identified the foremost opportunities to advance dementia research, differential diagnosis, use of neuropsychometric tools, awareness, and treatment options. We highlight key topics discussed at the meeting and provide future recommendations to foster a more equitable landscape for dementia prevention, diagnosis, care, policy, and management in LMICs. Highlights: Two-thirds of persons with dementia live in LMICs, yet research and costs are skewed toward HICs. LMICs expect dementia prevalence to more than double, accompanied by socioeconomic disparities. The 2022 Symposium on Dementia in LMICs addressed advances in research, diagnosis, prevention, and policy. The Nairobi Declaration urges global action to enhance dementia outcomes in LMICs

Perspective: Clinical relevance of the dichotomous classification of Alzheimer’s disease biomarkers: Should there be a “grey zone”?

The 2018 National Institute on Aging and the Alzheimer's Association (NIA-AA) research framework recently redefined Alzheimer's disease (AD) as a biological construct, based on in vivo biomarkers reflecting key neuropathologic features. Combinations of normal/abnormal levels of three biomarker categories, based on single thresholds, form the AD signature profile that defines the biological disease state as a continuum, independent of clinical symptomatology. While single thresholds may be useful in defining the biological signature profile, we provide evidence that their use in studies with cognitive outcomes merits further consideration. Using data from the Alzheimer's Disease Neuroimaging Initiative with a focus on cortical amyloid binding, we discuss the limitations of applying the biological definition of disease status as a tool to define the increased likelihood of the onset of the Alzheimer's clinical syndrome and the effects that this may have on trial study design. We also suggest potential research objectives going forward and what the related data requirements would be