Pathway Analysis for Plasma β-Amyloid, Tau and Neurofilament Light (ATN) in World Trade Center Responders at Midlife

The World Trade Center (WTC) responders who aided in the search, rescue and recovery operations during and after the terrorist attacks of September 11, 2001, endured extraordinarily stressful experiences. Our work has demonstrated that these exposures resulted in high levels of chronic post-traumatic stress disorder (PTSD) in WTC responders that were associated with increased incidence of cognitive impairment (CI) [1‐8], which can be prodromal to Alzheimer’s disease (AD) [9‐11].

AD is the sixth most common underlying cause of death [12]. AD has a long prodromal phase, with molecular, structural and functional changes commencing decades prior to the onset of observable symptoms. According to the recent National Institute on Aging–Alzheimer’s Association (NIA-AA) framework [9‐11], AD is characterized by progressive accumulation of an underlying neuropathological cascade commencing with β-amyloid deposition (A) [13], followed by tauopathy (T) [14] and neurodegeneration (N) [9], the extent and stage of which can be diagnosed by changes in A, T and N (Fig. 1).

The preclinical phase of AD is characterized by cognitive decline and commences in midlife up to 20 years before clinical diagnosis [15, 16]. However, whilst neuroimaging studies are propelling AD research forward [11], they are nevertheless limited in the number of ways that they can examine A, T or N, given that such studies are costly and thus employ relatively small samples of older adults who are willing and able to undergo neuroimaging scans subject to radiation exposure from positron emission tomography (PET) radioligands. The recruitment of smaller and older age groups limits the collection and analysis of important information about critical time points for intervention. In addition, imaging studies are further limited by necessary exclusion criteria such as anxiety and/or claustrophobia, unsafe metal implants, or high body mass. Moreover, whilst imaging studies are able to identify A, T or N, they are unable to differentiate between the two main Aβ subtypes (Aβ₄₀ and Aβ₄₂) known to be implicated in AD. These important limitations highlight the need for implementing cost-effective and larger-sampled investigative modalities that can replicate imaging studies to better address the etiology and neuropathology depicted in the ATN model for AD.

As a solution to the above limitations, recent work supports the use of plasma-based measures for measuring A, T and N, utilizing protein distribution levels of Aβ₄₂, Aβ₄₀ [17, 18], total tau for T [19, 20] and neurofilament-light (NfL) for N [21‐24]. The main objective of this study was to determine the extent to which plasma-based measures for A₄₂, A₄₀ T and N support the existing ATN model of AD neuropathological changes in a larger, age-heterogeneous World Trade Center (WTC) responder sample of men and women at midlife [25]. Additionally, since little is known about the role of Aβ₄₀ in A, a second aim of this effort was to further characterize the extent to which Aβ₄₀ is involved in the ATN model.

Sample characteristics are described in Table 1. Responders were predominantly male and on average at midlife when blood samples were collected. Approximately 13% of responders in this sample had CI (Table 1). Stratification by age groups further revealed significant linear trends between each age group mean from left to right order for every variable under investigation (Fig. 2). Stratification by biological sex revealed that T (pg/ml) was significantly higher in females 0.49 (SE = 0.152) than males, p = 0.001, which survived FDR (Fig. 3). Stratification by cognitive status revealed that responders with CI had (1) higher age (years): +3.09, SED = 1.21, p = 0.011, q = 0.011; (2) lower Aβ₄₂ (pg/ml): −1.08, SED = 0.385, p =0.005, q = 0.010; (3) higher Aβ₄₀:Aβ₄₂: +9, SED = 3.26, p = 0.0175, q = 0.010; and (4) higher N (pg/ml): +1.53, SED = 0.788, p = 0.054, q = 0.042, all of which survived FDR set at Q = 5% (Fig. 4).

The AIC and BIC were minimized for the model commencing with Aβ₄₂ but flowing through Aβ₄₀ (Table 2). Results from the best-fitting model suggest that age played an independent role in predicting Aβ₄₀, Aβ₄₂, T and N distribution and that female responders had higher levels of T. Our results support the proposed ATN framework view insofar as Aβ₄₂ → T → N; however, our findings suggest a more intricate process indicating that Aβ₄₀ independently played a central, if late, role in linking T and N (Fig. 3). Examining the utility of demographic factors (age/sex), Aβ₄₀, Aβ₄₂, T and N as predictors of CI in these data revealed that age, Aβ₄₂ and T were independently associated with risk of CI (Fig. 3). Effect size calculations suggested that the risk of CI in responders increased by 30% per standard deviation (SD) reduction in Aβ₄₂ (aRR = 1.30, [1.11–1.53]), and by 24% per SD increase in T (aRR = 1.24 [1.05–1.49]). The likelihood ratio test showed no loss of information in the model presented here as compared with the saturated model (\(\chi_{9}^{2}\) = −9.90, p = 1.000) (Fig. 5).

In this study, we examined the AD pathological ATN framework cascade utilizing novel high-sensitivity plasma-based measures of neuropathology collected in a sample of WTC responders. Demographic correlations were interesting, as CI strongly associated with age, but more so that women may be at increased risk of T. There is currently sparse prior work to suggest that sex should act as a predictive element for the distribution and accumulation of tau, other than a neuroimaging study showing elevated T in female APOE4 carriers [36].

An important goal of this study was to disentangle how the two β-amyloid subtypes, Aβ₄₂ and Aβ₄₀, flow through the ATN model; thus we examined a more refined Aβ₄₀, Aβ₄₂, T and N cascade model of AD. Our findings provide strong support for the Aβ₄₂ → T → N model, with biological sex differences indicating that the pathogenesis of T differs among female responders and that Aβ₄₂ is associated with an increased risk of CI, which supports the translocation theory of A₄₂ from the periphery into the brain [37], as responders with CI had lower raw mean plasma levels. However, we also report that Aβ₄₀ offers an intermediary role linking the proliferation of T with changes in N, which suggests that different types of amyloid may play different roles in the progression of AD. We further report an elevated Aβ₄₀:Aβ₄₂ ratio in responders with CI, which is in agreement with previous reports for individuals at risk for AD [29, 37, 38], which is in agreement with previous observations for AD pathogenesis [21].

Prior studies have noted that T incompletely follows A [25], and we suggest that one reason for this mismatch is due to β-amyloid subtypes (Aβ₄₀ and Aβ₄₂) differentially regulating the course of T and N neuropathology. Notably, our responder sample demonstrated associations for Aβ₄₂ with CI and N, Aβ₄₀ with T and N, T with CI, and Aβ₄₂ with Aβ₄₀. The fact that Aβ₄₂ and Aβ₄₀ have these differential roles in the ATN model underscores a possible explanation for the previously reported mismatches between A and T seen in imaging studies of AD. Indeed, from studies of histopathology, we see that Aβ₄₀ plays a critical role in modulating dense-core plaque formation, which is critical in AD pathogenesis [39], and Aβ₄₂, more commonly present in diffuse plaques [40], are often collocated with T [41], and more commonly evident in the occipital lobe [42] in later stages of sporadic AD [43]. Furthermore, in neuroimaging studies, we see dense-core Aβ₄₀ plaques that tend to be smaller but denser than Aβ₄₂ diffuse plaques [42]. Therefore, the two subtypes of β-amyloid, though highly inter-related, could result in both Aβ₄₂-related cognitive changes, with a potentially slower onset of CI via changes in T through Aβ₄₀ and N. This further highlights the temporal elements underscoring the ATN model, where in certain cases Aβ₄₀ may be more prominent in leading towards T and N, in the absence of pronounced Aβ₄₂ accumulation. Indeed, studies have demonstrated inverse associations between plasma Aβ₄₂/Aβ₄₀ ratios and high cortical A burden [29], which taken together with our report highlights the role for Aβ₄₀ in the ATN model. Interestingly, prior work from our lab demonstrated that in WTC responders with PTSD, Aβ₄₂/Aβ₄₀ ratios were higher [44], suggesting a leading elevation in Aβ₄₂ when applying the ATN model to WTC-PTSD.

This is the first study to apply the ATN research framework using an ultrasensitive multiplex array of plasma-based neuropathological biomarkers in a large, well-characterized sample of individuals at midlife—the WTC responder cohort. In addition, while prior imaging studies are able to identify ATN, they lack specificity in their ability to differentiate between Aβ₄₀ and Aβ₄₂, which this study accomplishes. Furthermore, the GSEM analytical approach used to determine and examine plasma ATN in WTC responders allows for examination of associations of predictors with non-normal distributions, thus enabling us to fully characterize the peripheral distribution of Aβ₄₀, Aβ₄₂, T and N.

Nevertheless, this study lacked an external control group with which to compare peripheral levels of ATN. Since the present report was an initial and exploratory application of the ATN research framework for these blood-based biomarkers in a population of WTC responders with a spectrum of cognitive impairment, we propose that future such investigations with this cohort employ an external control group in order for the findings to be more generalizable. Furthermore, this study focused on an occupational population of adults exposed to the unique events of the WTC attacks and the chronic aftermath of recovery efforts within New York City, a geographic region where responders also resided. Though the use of GSEM represents a notable strength of this study, it nevertheless does not permit the calculation of a fit statistic (RMSEA) that is commonly employed in SEM. Finally, we measured plasma total tau as a marker for T and not plasma phospho-tau181. Whilst both have been demonstrated to effectively distinguish between AD and cognitively normal subjects in a clinical setting, pTau181 has been reported to be a more sensitive and specific predictor of elevated brain Aβ and was associated with tau PET, whereas total tau was associated with cortical thickness in AD signature regions [45], which is an association that applies to our finding of reduced cortical thickness in the WTC responder population [46]. Therefore, future pathway analyses and considerations of the ATN model in AD pathogenesis should not only account for both subtypes of β-amyloid, but should also take into account both isoforms of plasma tau. These factors limit the generalizability of the findings in our study. However, prior studies in our group with the WTC responder population have provided extensive characterizations for the role of neuro-behavioral symptoms of PTSD and major depressive disorder (MDD) and their associations with CI [2, 6, 8, 28, 47]. Therefore, we encourage future studies that aim to examine the neurobiology of such neurobehavioral disorders in WTC responders to employ the ATN research framework and novel modeling approaches we report here.

The current ATN model of AD does not specify the subtype of β-amyloid to be considered. Here, we demonstrate that Aβ₄₀ levels are important indicators for T and N, and although Aβ₄₀ and Aβ₄₂ were strongly interrelated, they do not co-occur uniformly, such that some individuals may develop Aβ₄₂ but not Aβ₄₀, or the inverse. If so, then there may be adults who appear A+ on a neuroimaging scan but never develop Aβ₄₀ dense-core plaques. Conversely, some individuals with rapid Aβ₄₀ may not attain the levels of global β-amyloid deposition necessary to be considered A+, potentially earning the diagnosis of primary age-related tauopathy (PART) [48] or suspected non-Alzheimer’s disease pathophysiology (SNAP) [49]. Therefore, the present study suggests that when considering the current ATN model of AD in a clinical setting, we may be overlooking the differential roles that the two β-amyloid subtypes play in the pathological cascade. Furthermore, the present report highlights the applicability and utility of employing analysis of peripheral ATN biomarkers to study and further understand the underlying neurobiological etiology for the CI observed in this population. Combined with molecular imaging methodologies that directly interrogate levels of cortical ATN, future investigations utilizing a concurrent imaging and peripheral ATN investigation offer a powerful arsenal of useful biomarkers to help better understand the observed CI in this population.