29 Feb 2024

In the more than a decade since scientists at Washington University and the Mayo Clinic first proposed the now well-known curves of biomarker change over the course of Alzheimer's disease, researchers have filled in this framework with dozens of fluid and imaging biomarkers that reflect different aspects of AD progression. Data came mostly from cross-sectional, short-term, or familial AD cohorts. Now, two studies have deployed other methods to trace biomarkers longitudinally over the course of sporadic AD. They report surprisingly similar trajectories, which largely confirm prior analyses.

One, led by Suzanne Schindler at Washington University in St. Louis and published February 24 in the Annals of Neurology, used an “amyloid clock” she had previously developed to estimate years to symptom onset among almost 400 participants. With this proxy measure of time, the researchers charted the changes of multiple biomarkers reflecting amyloidosis, tauopathy, neuroinflammation, and neurodegeneration over a two-decade span.

The trajectories aligned closely with those among a large longitudinal cohort in China. That study, led by Jianping Jia at Capital Medical University in Beijing and published February 22 in the New England Journal of Medicine, tracked biomarker changes in some 1,700 people, nearly 700 of whom developed dementia over the 20+ year investigation, which began in 2000 with more than 50,000 people.

“These two papers describing the timeline of the trajectory from amyloid positivity to symptom onset are extremely important, with very practical implications for clinical trials and patient care,” commented Michael Weiner of the University of California, San Francisco. “What is so remarkable is how similar the results are in these two studies: a U.S., largely white population, and a Chinese population.”

Schindler’s study built upon previous work, in which her team identified a tipping point of amyloid accumulation—SUVR 1.2 according to PiB-PET, to be exact—beyond which amyloid accumulates with striking consistency across individuals (Sep 2021 news). A person’s age at this tipping point predicted at what subsequent age they would develop AD symptoms, allowing the scientists to use the so-called “amyloid clock” to tie plaque burden to estimated years from onset (EYO).  

In the current study, first author Yan Li and colleagues used this clock to place a slew of biomarkers along the amyloid-time trajectory. They included 395 participants who had undergone at least one amyloid-PET scan with a PiB tracer, of whom 118 had reached or surpassed the threshold for amyloid positivity. Volunteers averaged 70 years of age at the time of amyloid onset. Depending on the biomarker, between 40 and 60 participants had serial measurements over an average of five to seven years of follow-up. For each biomarker, the researchers tracked the difference in its levels between the amyloid-PET-negative and -positive groups, as a function of amyloid clock-based EYO.

Some key findings? First, at 19 to 15 years prior to symptoms, biomarkers reflecting amyloidosis changed. These included CSF and plasma Aβ42/40, CSF p-tau217/217, and amyloid-PET. Next, at 14 to 12 EYO, plasma p-tau217/217 rose, as did biomarkers of synaptic loss and neurodegeneration, such as CSF neurogranin, SNAP-25, and NfL. Neuroinflammation markers, including CSF sTREM2 and plasma GFAP, also ticked up at this time. Between nine to seven years before EYO, CSF p-tau205/205—thought to reflect tau pathology—started to climb, as did the neuroinflammatory indicator CSF YKL-40. Shortly thereafter, the hippocampus starting shrinking and cognitive scores faltered.

In their NEJM paper, Jia and colleagues made use of longitudinal data collected among participants in the China Cognition and Aging Study. COAST is an ambitious nationwide prospective cohort study that aims to amass data on dementia in China. It enrolled 52,000 participants in the first half of 2000. Of those, 32,061 met the eligibility requirements for this biomarker analysis; however, owing to drop-outs, deaths, and other factors, only 1,789 completed the requisite 15+ years of follow-up tests. Of those, 695 were diagnosed with AD, 1,094 remained cognitively normal at their last assessment. Overall, the participants were tracked for an average of 20 years, during which time they donated blood, CSF, and underwent brain scans and cognitive assessments several times. Alberto Lleó, Hospital de Sant Pau, Barcelona, Spain, called the study impressive. “The long follow-up and the large sample size help to shed light on the complex biology of the common form of AD,” he wrote to Alzforum (comment below)

What did this longitudinal data reveal? CSF Aβ42 was the first to change, becoming abnormal 18 years prior to diagnosis among those with AD. The ratio of Aβ42/40 changed 14 years prior to diagnosis, while CSF p-tau181 and total tau took off at 11 and 10 years out, respectively. CSF NfL started to rise nine years prior to diagnosis, followed closely by hippocampal shrinkage at seven and cognitive decline at six years.

Compared to Li et al, Jia et al. measured fewer biomarkers. Of those the two studies have in common, Li detected changes two to three years earlier. However, Jia plotted biomarker abnormality relative to actual AD diagnosis, not relative to EYO based on an amyloid clock. These different endpoints, in addition to assays used to measure the biomarkers, might explain some of the timing differences.

Even so, both studies tell a similar story, with biomarkers of amyloidosis followed by tauopathy, neurodegeneration, and cognitive decline. The number of biomarkers being studied in cohorts around the world is growing rapidly, hence more are going to be added to these diagrams before long.—Jessica Shugart

Comments

1. • Michael Weiner
     San Francisco Veterans Affairs Medical Center
   • Posted: 29 Feb 2024

   These two papers describing the timeline of the trajectory from amyloid positivity to symptom onset are extremely important, with very practical implications for clinical trials and patient care. What is so remarkable is how similar the results are in these two studies: a U.S., largely white population population and a Chinese population.

   We can expect that these results will lead to additional studies using plasma markers. In the long term, as more data becomes available, we can be hopeful that a “precision medicine” approach may be possible to inform individual patients about their relative risk and possible timeline for development of future symptoms.

   View all comments by Michael Weiner
2. • Alberto Lleó
     Hospital de Sant Pau
   • Posted: 29 Feb 2024

   This impressive study characterizes the longitudinal biomarker changes in sporadic AD. The pattern of changes in other forms of AD, such as autosomal-dominant AD (Bateman et al., 2012) or Down Syndrome AD (Fortea et al., 2020) have previously been reported. However, the course of sporadic AD has been less characterized. One of the challenges is that sporadic AD is highly heterogeneous in term of pathophysiology, with different underlying biological subtypes that lead to different progression rates (Tijms et al., 2020).

   In this study, Jia et al. confirm the long preclinical phase of the disease of sporadic AD; however, the exclusion of patients with positive family history makes it difficult to generalize the results to the bulk of patients seen in memory units or to patients enrolled in clinical trials. In any case, the long follow-up and the large sample size help to shed light on the complex biology of the common form of AD. 

   References:

   Bateman RJ, Xiong C, Benzinger TL, Fagan AM, Goate A, Fox NC, Marcus DS, Cairns NJ, Xie X, Blazey TM, Holtzman DM, Santacruz A, Buckles V, Oliver A, Moulder K, Aisen PS, Ghetti B, Klunk WE, McDade E, Martins RN, Masters CL, Mayeux R, Ringman JM, Rossor MN, Schofield PR, Sperling RA, Salloway S, Morris JC. Clinical and biomarker changes in dominantly inherited Alzheimer's disease. N Engl J Med. 2012 Aug 30;367(9):795-804. PubMed.

   Fortea J, Vilaplana E, Carmona-Iragui M, Benejam B, Videla L, Barroeta I, Fernández S, Altuna M, Pegueroles J, Montal V, Valldeneu S, Giménez S, González-Ortiz S, Muñoz L, Estellés T, Illán-Gala I, Belbin O, Camacho V, Wilson LR, Annus T, Osorio RS, Videla S, Lehmann S, Holland AJ, Alcolea D, Clarimón J, Zaman SH, Blesa R, Lleó A. Clinical and biomarker changes of Alzheimer's disease in adults with Down syndrome: a cross-sectional study. Lancet. 2020 Jun 27;395(10242):1988-1997. PubMed.

   Tijms BM, Gobom J, Reus L, Jansen I, Hong S, Dobricic V, Kilpert F, Ten Kate M, Barkhof F, Tsolaki M, Verhey FR, Popp J, Martinez-Lage P, Vandenberghe R, Lleó A, Molinuevo JL, Engelborghs S, Bertram L, Lovestone S, Streffer J, Vos S, Bos I, Alzheimer’s Disease Neuroimaging Initiative (ADNI), Blennow K, Scheltens P, Teunissen CE, Zetterberg H, Visser PJ. Pathophysiological subtypes of Alzheimer's disease based on cerebrospinal fluid proteomics. Brain. 2020 Dec 1;143(12):3776-3792. PubMed.

   View all comments by Alberto Lleó

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References

News Citations

1. Can a Single Amyloid PET Scan Predict Time to Symptom Onset? 28 Sep 2021

Further Reading

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