Background: Diagnostic pathways for patients presenting with cognitive complaints may vary across geographies. Objective: To describe diagnostic pathways of patients presenting with cognitive complaints across 6 countries. Methods: This real-world, cross-sectional study analyzed chart-extracted data from healthcare providers (HCPs) for 6,744 patients across China, France, Germany, Spain, UK, and the US. Results: Most common symptoms at presentation were cognitive (memory/amnestic; 89.86%), followed by physical/behavioral (87.13%). Clinical/cognitive tests were used in >  95%, with Mini-Mental State Examination being the most common cognitive test (79.0%). Blood tests for APOE ɛ4/other mutations, or to rule out treatable causes, were used in half of the patients. Clinical and cognitive tests were used at higher frequency at earlier visits, and amyloid PET/CSF biomarker testing at higher frequency at later visits. The latter were ordered at low rates even by specialists (across countries, 5.7% to 28.7% for amyloid PET and 5.0% to 27.3% for CSF testing). Approximately half the patients received a diagnosis (52.1% of which were Alzheimer’s disease [AD]). Factors that influenced risk of not receiving a diagnosis were HCP type (higher for primary care physicians versus specialists) and region (highest in China and Germany). Conclusion: These data highlight variability in AD diagnostic pathways across countries and provider types. About 45% of patients are referred/told to ‘watch and wait’. Improvements can be made in the use of amyloid PET and CSF testing. Efforts should focus on further defining biomarkers for those at risk for AD, and on dismantling barriers such low testing capacity and reimbursement challenges.

Brain-age can be inferred from structural neuroimaging and compared to chronological age (brain-age delta) as a marker of biological brain aging. Accelerated aging has been found in neurodegenerative disorders like Alzheimer's disease (AD), but its validation against markers of neurodegeneration and AD is lacking. Here, imaging-derived measures from the UK Biobank dataset (N=22,661) were used to predict brain-age in 2,314 cognitively unimpaired (CU) individuals at higher risk of AD and mild cognitive impaired (MCI) patients from four independent cohorts with available biomarker data: ALFA+, ADNI, EPAD and OASIS. Brain-age delta was associated with abnormal amyloid-b, more advanced stages (AT) of AD pathology and APOE-e4 status. Brain-age delta was positively associated with plasma neurofilament light, a marker of neurodegeneration, and sex differences in the brain effects of this marker were found. These results validate brain-age delta as a non-invasive marker of biological brain aging in non-demented individuals with abnormal levels of biomarkers of AD and axonal injury.

BackgroundAccurate and robust blood‐based biomarkers (BBBMs) of Alzheimer’s disease (AD) are required for identification of symptomatic patients with low likelihood of amyloid pathology before confirmatory diagnostic evaluation. Further evidence on the clinical performance and robustness of BBBMs is required to identify patients for clinical trials and in routine clinical practice. We evaluated the clinical performance and robustness of amyloid‐β 1–42 (Aβ42), amyloid‐β 1–40 (Aβ40), apolipoprotein E4 (ApoE4), phosphorylated‐tau 181 (pTau181), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NFL) as BBBMs of AD.MethodAnalyses were performed retrospectively using plasma samples from AIBL, BioFINDER, and CREAD cohorts, comprising cognitively normal individuals and patients with subjective/objective cognitive impairment, mild AD, or amyloid screen failure. BBBMs were measured at two laboratories using automated Elecsys® prototype immunoassays (cobas e 601 and e 411 analyzers; all Roche Diagnostics International Ltd). Clinical performance of single BBBMs and combinations of BBBMs (using logistic regression) was assessed using area under the receiver operating characteristic curve (AUC‐ROC) analysis. Negative percent agreement (NPA), prevalence‐adjusted negative and positive predictive values (NPV and PPV), and screen‐out rate were compared at 85% positive percent agreement (PPA). Robustness, defined as the change in clinical performance when adding ±10% bias and random variability, was calculated at 85% PPA.ResultAcross cohorts, the best performing single BBBM was pTau181 (AUC: 81.6–89.3). The best performing combined BBBM models across cohorts were pTau181+Aβ42 (AUC: 85.6–93.4), pTau181+ApoE4 (AUC: 83.7–91.8), and pTau181+Aβ40 (AUC: 84.8–90.2); clinical performance for these combined BBBM models in terms of NPV and PPV was comparable, providing high NPVs (>90%) and screen‐out rates (>50%). For combined BBBM models including Aβ42 or Aβ40, robustness at 85% PPA was lower compared with models not including Aβ42 or Aβ40 across cohorts. Considering both clinical performance and robustness, pTau181 and pTau181+ApoE4 were the best performing single and combined BBBM models, respectively, across cohorts.ConclusionAcross cohorts, pTau181+ApoE4 was the best performing BBBM model for detecting patients with low likelihood of amyloid pathology. These findings support the suitability of these BBBMs to inform diagnostic assessments for patients with low likelihood of AD.

BackgroundDiagnostic pathways from cognitive impairment (CI) to Alzheimer’s disease (AD) are complex and vary geographically. This study aimed to quantify and compare the current diagnostic pathways in six countries.MethodsA real‐world, cross‐sectional survey of 1,694 health care professionals (HCPs) was conducted in six countries (US, China, UK, France, Germany and Spain) from October to November 2021. HCPs provided data for 6,744 patients including patient demographics, presenting symptoms, and diagnostic tests and procedures. Descriptive analyses were conducted for all patients and further stratified by countries and HCP types (primary care physicians (PCP) versus specialists (geriatricians, neurologists and psychiatrists)).ResultsMost common presenting symptoms included problems with memory (89.9%), physical/behavioral (87.1%), executive functioning (72.2%) and language (71.4%). 42.1% of patients were presenting to HCPs the first time for their symptoms.96.0% of patients with data on diagnostic tests by country and specialty (n=6,525), underwent clinical and 95.5% cognitive tests, including tests at scheduled follow‐up visits. Mini‐Mental State Examination (MMSE) was the most frequently used cognitive test (n=5,141). About half the patients (n=3,329) received blood‐tests, mainly to rule out other causes of CI (n=2,687) (Table 1).Diagnostic test use varied by country and specialty. In China, cognitive tests, especially MMSE, were more commonly used by specialists (81.9%) than PCPs (41.6%). In the UK blood tests were more commonly used by PCPs (62.5%) than specialists (46.2%).ConclusionDiagnostic pathways varied largely by country and specialty. This study is relevant to populate diagnostic pathways, fill data gaps and advance patient care in AD by supporting future evidence generation, especially when new treatment options arrive.

BackgroundGene‐environment interactions are important in understanding Alzheimer’s disease (AD) etiology. Current research is limited, possibly due to weak effects of individual genetic variants. We analysed interaction between genetics of hippocampal volume, environmental exposures and levels of AD biomarkers in cognitively unimpaired individuals at increased risk of AD.MethodA total of 319 cognitively unimpaired, middle‐age participants from the Alzheimer’s and Families (ALFA) study with data for genotyping, environmental exposures, and cerebrospinal fluid (CSF) biomarkers were included. Genome‐wide genotyping was performed using Infinium Neuro Consortium (NeuroChip) Array. Genetic variants that passed a quality control/imputation procedure were used to calculate polygenic risk scores (PRS) using PRSice version 2. Land use regression estimated residential exposure to particulate matter (PM2.5, PM10), and nitrogen dioxide (NO2). NeuroToolKit robust prototype assays and Elecsys® immunoassays (both Roche Diagnostics International Ltd, Rotkreuz, Switzerland) were used to measure CSF biomarkers, and amyloid positivity was defined as amyloid‐beta(Aβ)42/40 ratio <0.071. Associations between PRSs and environmental factors were investigated and estimated using multiple logistic/linear regression models adjusted for age and sex; CSF biomarkers were included as outcomes.ResultPRS‐hippocampal volume (HV)×PM10 and PRS‐HV×NO2 were significantly associated with p‐tau (p = 0.045 and p = 0.025, respectively) (Figure 1). Individuals at high genetic predisposition for larger hippocampal volumes had lower levels of p‐tau at low levels of air pollution compared to individuals at low/null genetic predisposition; as the level of exposure to PM10 and NO2 increased, higher values of p‐tau were observed compared to low‐risk individuals.ConclusionOur results showed that air pollution may have a deleterious effect on biological mechanisms of AD, in cognitively unimpaired individuals with higher genetic liability for larger hippocampal volumes. Further research is needed to elucidate the biological mechanism involved in such associations.