An elevated NLR, serving as an indicator of peripheral inflammation, has been implicated in AD pathology (19-22, 26). However, an elevated NLR has also been implicated in various other diseases and conditions, including those that are risk factors for AD, such as diabetes, hypertension, and obesity, raising questions as to whether the association with AD is simply a manifestation of underlying comorbidities (27-40). Further, the shortcoming of the NLR as a tool for the differential diagnosis with other dementias, due to its lack of specificity, has recently been highlighted (51). Therefore, the need for an investigation into the NLR in specific relation to Aβ and tau biomarkers, while accounting for comorbidities, has become apparent, particularly within the A/T/N framework. In this study, we report significant associations between the NLR and CSF Aβ42 in the CU ADNI cohort, as well as between the NLR and CSF p-tau181 and t-tau in the CU NYU cohort. These associations were observed before and after adjusting for sociodemographic information, APOE4, and common comorbidities (diabetes, hypertension, BMI).
The associations we report between the NLR and A/T/N characteristics in each cohort could be partially explained by recent research focused on neutrophil involvement in AD pathology. Neutrophils, the predominant form of leukocytes, play an important role in innate immunity by defending against pathogens and clearing cellular debris. However, their pro-inflammatory nature, including the release of reactive oxygen species (ROS), lytic enzymes, and neutrophil extracellular traps (NETs), can cause tissue damage through sustained exposure, largely explaining their implication in many inflammatory diseases (52-55). Although the brain was once considered an immune-privileged site, neutrophils and NETs have been shown to aggregate in the cerebral small vessels of AD patients, particularly near Aβ plaques and tau tangles (7, 8, 56). This phenomenon has been attributed to disruption of the blood-brain barrier (BBB) and the release of cytokines and chemokines by microglia in response to local amyloid plaques, leading to the recruitment of neutrophils into the brain parenchyma to help clear the misfolded protein aggregates (8, 56, 57). Indeed, the chronic presence of these neutrophils in the brain can lead to sustained neuroinflammation, which is pertinent considering hyperactive and advanced adhesive phenotypes such as elevated expression of the CD11b adhesion molecule have been observed in the neutrophils of AD patients (7, 8, 58, 59). Moreover, aging, which remains the greatest risk factor for AD, has been associated with neutrophil abnormalities including impaired chemotaxis and increased ROS release (60-62). Zanero et al. even reported an Aβ-induced transition of the neutrophil-arresting LFA-1 integrin to a higher affinity state, thereby perpetuating neutrophil adhesion in amyloid-rich regions (8). In the same studies, a reduction in cognitive impairment was reported after neutrophils were depleted or neutrophil trafficking was inhibited via LFA-1 integrin blockade. Taken together, these reports may support our findings, particularly in the ADNI cohort where an elevated NLR associated with Aβ brain deposition, and subjects in the upper median NLR at baseline demonstrated greater prevalence of subsequent cognitive decline. Previous research has also shown that pro-inflammatory cytokines released by activated microglia near amyloid plaques, including TNFα, IFNγ, and IL-1β, can increase Aβ peptide levels and decrease amyloid plaque clearance (63-66), promoting a positive feedback cycle between amyloid plaque deposition, microglial activation, neutrophil/immune cell recruitment, and neuroinflammation, which may further support our findings. The Aβ-induced microglial release of IL-1β, which is involved in neutrophil recruitment, has also been linked with increased BBB disruption and tau pathology in murine models (66-69), which may partially support our findings in the NYU cohort, where the NLR associated with both neurodegeneration and tau pathology. In addition to their recruitment into the brain, elevated levels and phenotypic changes of neutrophils in the peripheral blood of AD patients have been reported (9, 59), which may also support our findings in both cohorts. However, the discrepancies we report in specific associations between cohorts suggest the involvement of additional factors, and the role of lymphocytes is also relevant when considering the NLR in relation to AD and A/T/N.
Previous literature surrounding lymphocytes, leukocytes involved in the adaptive immune response, has highlighted their contribution to the pro-inflammatory milieu outlined above. Similar to neutrophils, lymphocytes, particularly CD4+ and CD8+ T-cells, have been observed in the brains of AD patients near microglia, suggesting dynamic cross-talk and interdependence on microglial phenotype, T-cell differentiation, and pro-inflammatory outcomes (10, 12, 13, 15). In general, CD4+ T-cells exhibit diverse roles in modulating microglia, with regulatory T-cells (Tregs) secreting anti-inflammatory cytokines and effector T-cells (Teffs) secreting pro-inflammatory cytokines. Although the anti-inflammatory benefits of Tregs in AD and their role in Aβ clearance has been highlighted (70), Teffs have been shown to progress AD pathology and even downregulate Tregs in later disease stages in murine models (71). Pro-inflammatory CD8+ T-cells have generally been observed in close proximity to tau aggregates in the AD brain, and their involvement in tauopathy has been suggested (10, 72). Although our study did not differentiate lymphocyte subsets, this may support our findings in the NYU cohort linking the NLR with tau pathology. Additionally, the pro-inflammatory response from T-cell activation in the brain has been linked with compromised BBB integrity and peripheral immune cell influx (73), with a study by Yang et al. suggesting an Aβ-induced release of TNFα by microglia to promote T-cell recruitment to the brain in AD (74), further feeding in to the aforementioned positive feedback loop. Contrarily, a study by Chen et al. demonstrated that microglial recruitment of T-cells in response to tauopathy, but not amyloid deposition, leads to neurodegeneration in AD (72), and a study by Merlini et al. reported CD3+ T-cells, most of which were CD8+, to correlate with tau, but not amyloid, pathology in the AD brain (10). Taken together, these studies may further support our findings in the NYU cohort which demonstrated associations between the NLR and both tau pathology and neurodegeneration, but not Aβ. Relevant to our findings in both cohorts, many studies have reported a decrease in the total count of lymphocytes in the peripheral blood in AD (although conflicting findings have also been reported), with mechanisms being attributed to influx in the CNS as well as susceptibility to ROS, which is pertinent given the observed increase in ROS released by neutrophils in AD as mentioned above. Regardless, an increase in the proportion of activated HLA-DR+ CD4+ and CD8+ T-cells has been observed in the peripheral blood of AD patients, even in studies which observed no difference in the total count (14, 75, 76).
These pathophysiological changes in AD in the context of both neutrophils and lymphocytes may partially explain why an elevated NLR has been associated with cortical Aβ deposition, as determined by PET and CSF Aβ measures, and a greater risk of cognitive decline in AD cohorts (19-22, 26). The associations we report between the NLR and decreased CSF Aβ42 in the ADNI cohort support these previous studies and suggests the associations are not simply an artifact of comorbidities that raise the NLR and pose as risk factors for AD. In particular, our results in the ADNI cohort support the study by Hou et al. which reported an association between the NLR and lower CSF Aβ42 in CU participants within the ADNI after adjusting for sociodemographics and APOE4 alone (26). Another study conducted in the ADNI cohort, by Mehta et al., that included MCI and AD participants in the analysis, reported an elevated NLR to associate with greater PET measures of Aβ, but not tau, as well as with longitudinal cognitive decline determine by the Alzheimer’s Disease Assessment Scale Cognitive Subscale (ADAS-Cog) (22). Our study supports these findings, demonstrating that the association between the NLR and Aβ deposition are present even within the strictly CU population in the ADNI cohort. Likewise, although we defined cognitive decline as the transition from CU to a clinical diagnosis of MCI or AD throughout follow-up visits, rather than by changes in the ADAS-Cog score alone, the increased incidence of cognitive decline that we report in the ADNI subjects who were in the upper median NLR at baseline supports the reported study. This association between the NLR and longitudinal cognitive decline also supports the study of Ramos-Cejudo et al. who found an increased NLR to associate with a greater risk of incident dementia in the elderly population after comprehensive adjustment (23). However, the associations between the NLR and p-tau and t-tau, but not Aβ42, that we report in the NYU cohort, which displayed a younger aging profile, may suggest the NLR associates with tau pathology and neurodegeneration, but not amyloid deposition, in earlier stages of the disease process.
Further, our results in the NYU cohort suggest the association between the NLR, tau pathology, and neurodegeneration may be greater in participants who are amyloid-positive. This may be due to greater BBB disruption resulting in increased immune cell recruitment into the CNS by microglia-released pro-inflammatory cytokines, whether neutrophil recruitment via IL-1β or T-cell recruitment via TNFα, as outlined in the studies mentioned above. This may also be supported by the findings of Zhang et al. who demonstrated increased T-cell recruitment into the brain parenchyma as a result of BBB disruption in Aβ-induced AD rats (73). Another possible mechanism may be explained by Man et al. who suggested amyloid-induced overexpression of macrophage inflammatory protein-1 alpha (MIP-1α) in peripheral T-cells of AD patients to promote their migration across the BBB (77). Regardless of mechanism, our findings of potential amyloid-mediated associations between the NLR, tau pathology, and neurodegeneration may be supported by Ising et al. who demonstrated that activation of the NLRP3 inflammasome mediates Aβ-induced tau pathology in the AD mouse model (69). Additionally, Bellaver et al. reported Aβ-positivity to associate with tau tangle accumulation in CU individuals only if they were positive for astrocyte reactivity based on their plasma glial fibrillary acidic protein (GFAP) levels (78). Future studies could therefore benefit from incorporating GFAP data in addition to the NLR to explore potential interplay in amyloid and tau outcomes. Another study by Rabin et al. reported that cerebral amyloid angiopathy interacted with neuritic Aβ plaques to promote cognitive decline, and this interaction was mediated by tau, which may support our findings of a dynamic interplay between peripheral inflammation, amyloid burden, and tau pathology (79). Lastly, Milà-Alomà et al. reported that changes in CSF p-tau and t-tau were associated with age in Aβ+ subjects only (80). Although our study suggests changes in CSF t-tau are associated with the NLR, not age, in these subjects, it supports the notion that Aβ-induced changes in tau pathology (41-43, 78, 80, 81) are mediated by additional factors. To our knowledge, we are the first to report an association between the NLR and CSF measures of t-tau and p-tau in the preclinical setting, a dynamic relationship between peripheral immunity, tau pathology, and neurodegeneration that may be more pronounced in the presence of amyloid deposition.
In understanding the disparities in specific biomarker associations between cohorts, the statistically significant variations in cohort characteristics, including age, amyloid burden, hypertensive histories, and BMIs are likely contributors. With the older ADNI cohort demonstrating a greater presence of age-related conditions, our results suggest that the general influence of aging on the immune system, or immunosenescence, may contribute to the varied predictive capabilities of the NLR across cohorts of distinct immune profiles. Propensity score matching between the two groups could not be conducted to address these considerations due to the relatively small sample sizes and drastic cohort differences leading to inadequate match results. Similarly, although the meta analysis encompassing both cohorts showed associations between an elevated NLR and increases in both t-tau and p-tau after adjustment, further suggesting an association between the NLR and both tau pathology and neurodegeneration, associations between the NLR and Aβ42 could not be adequately assessed due to directional differences in the β coefficients between cohorts, once again highlighting the variability of specific associations between the NLR and A/T/N markers dependent on immunity and aging profiles. Therefore, future studies could benefit from conducting an extensive longitudinal analysis encompassing the age ranges of both cohorts in our study to investigate how age plays a factor in the interplay between the NLR and these CSF markers, and how associations with specific markers in the A/T/N framework may change as a result of immunosenescence.
In the same light, additional comorbidities which have been shown to increase the NLR, such as depression, cancer, and cardiovascular diseases, may be confounders (82-86), and a limitation of our study was the inability to account for these variables due to the absence of data and sample size limitations. Future studies conducting similar investigations should consider adjusting for these additional comorbidities as well. Future studies should also consider assessing the NLR as a risk factor for cognitive decline to AD or MCI due to AD by means of survival analysis, an analysis we could not explore due to sample size limitations and the absence of longitudinal CBC data in the ADNI. Although we report greater prevalence of cognitive decline in the ADNI subjects within the upper median NLR at baseline, a survival analysis leveraging longitudinal NLR, comorbidity, and A/T/N framework data could be more beneficial in highlighting specific pathways in disease progression. Another limitation of our study was that we investigated associations with AD biomarkers in the CSF in order to maximize sample size, but future studies could benefit from incorporating PET and MRI data, which may be more accurate at assessing structural and functional changes within the A/T/N and I/V/S frameworks. In fact, the absence of associations between the NLR and t-tau or p-tau among Aβ+ subjects in the ADNI cohort may be partially explained by the findings of Reimand et al. who reported that participants in the ADNI who met the Aβ-positivity threshold in both the CSF and PET had substantially greater levels of tau after 5 years when compared to those who met the Aβ-positivity threshold in the CSF but not PET (87). Therefore, a limitation of our study was defining Aβ-positivity by CSF levels, which may define an earlier and less understood level of amyloid deposition, and future studies could benefit from conducting the same analysis using the amyloid PET cutoff threshold instead. Future studies could also benefit from incorporating p-tau231 and p-tau217 measures, as they have been more closely associated with Aβ deposition in previous studies, compared to p-tau181, even in early stages prior to significant Aβ plaque buildup (80, 81). Lastly, a limitation of our study included differences in variable determination and collection procedures between cohorts. For example, only the NYU cohort included the documented use of hypertensive medications as a requirement in defining history of hypertension, so future studies could benefit from incorporating a standardized definition or raw blood pressure data.