Hippocampal neuronal loss and cognitive decline in LATE‐NC and ADNC among community‐dwelling older persons
BACKGROUND The hippocampus, a region within the limbic lobe of the brain, plays an important role in maintaining cognitive function. Specifically, the CA1 and subiculum sub‐sectors within the hippocampus contribute to the maintenance of episodic memory. With aging, it is common and well known to observe some degree of neuronal loss in the hippocampus, often due to Alzheimer's disease (AD) and associated with memory deterioration. However, hippocampal neuronal loss (HNL) can be due to a variety of factors, potentially involving proteinopathies beyond AD. Recently the neuropathologic changes associated with limbic‐predominant age‐related TAR‐DNA binding protein of 43 kDa (TDP‐43) encephalopathy (LATE) have been increasingly recognized in the hippocampus with or without co‐existing Alzheimer's disease neuropathologic changes (ADNC) and is now referred to as LATE‐neuropathologic changes (LATE‐NC). In addition, LATE‐NC is associated with hippocampal sclerosis (HS), which refers to severe neuronal loss and astrogliosis in the CA1 and/or subiculum, suggesting that LATE‐NC may also be involved in hippocampal neurodegeneration in aging. , , Clinicopathological and imaging studies have also shown that both ADNC and LATE‐NC are associated with hippocampal atrophy and cognitive decline, , , yet their independent relationship with HNL in studies of humans remains unclear, specifically within the spectrum of LATE‐NC. Although, many studies have shown the deleterious associations of HNL with cognition, , few have integrated the recent knowledge of LATE‐NC, which creates further complexity. Therefore, it is important to examine the inter‐connected nature of these specific diseases defined by their distinct proteinopathies, HNL, and cognitive decline, especially memory loss. Using data from three ongoing epidemiologic clinical–pathologic studies of aging and dementia, this study aims to characterize the severity of HNL by establishing a semiquantitative grading system based on the histological changes observed on hematoxylin and eosin (H&E)–stained sections without including the severity of LATE‐NC and ADNC in the evaluation of HNL. Then we explore the associations of HNL with ADNC and LATE‐NC, and separately with cognitive decline, in subjects with varying degrees of HNL. Finally, the study examines the extent to which HNL accounts for the association of LATE‐NC and ADNC with cognitive decline. RESEARCH IN CONTEXT Systematic review : The authors reviewed the literature about the association of hippocampal neuronal loss (HNL) with cognitive decline and Alzheimer's disease neuropathologic changes (ADNC) and limbic‐predominant age‐related TDP‐43 encephalopathy neuropathologic changes (LATE‐NC). There are limited human‐based studies examining the relationship between HNL and longitudinal cognitive decline, and very little is known regarding the relationship between HNL, neurodegenerative pathologies, and cognition to understand how much the relationship between ADNC and LATE‐NC is mediated by HNL. Interpretation : This study demonstrates that HNL is an important driver of late‐life cognitive decline. Specifically, HNL was associated with a decline in global cognition and in domains of episodic, semantic, and working memory even in the subjects without hippocampal sclerosis (HS). HNL is a prominent feature of LATE‐NC and is less associated with ADNC. Further, findings highlight that HNL partially mediated the association of LATE‐NC with cognitive decline, whereas the association of ADNC with cognitive decline was mostly independent of HNL. Future directions : These findings highlight differential underlying mechanisms in the hippocampal degeneration associated with LATE‐NC versus ADNC and may have important implications for both treatment and prognosis.   Systematic review : The authors reviewed the literature about the association of hippocampal neuronal loss (HNL) with cognitive decline and Alzheimer's disease neuropathologic changes (ADNC) and limbic‐predominant age‐related TDP‐43 encephalopathy neuropathologic changes (LATE‐NC). There are limited human‐based studies examining the relationship between HNL and longitudinal cognitive decline, and very little is known regarding the relationship between HNL, neurodegenerative pathologies, and cognition to understand how much the relationship between ADNC and LATE‐NC is mediated by HNL. Interpretation : This study demonstrates that HNL is an important driver of late‐life cognitive decline. Specifically, HNL was associated with a decline in global cognition and in domains of episodic, semantic, and working memory even in the subjects without hippocampal sclerosis (HS). HNL is a prominent feature of LATE‐NC and is less associated with ADNC. Further, findings highlight that HNL partially mediated the association of LATE‐NC with cognitive decline, whereas the association of ADNC with cognitive decline was mostly independent of HNL. Future directions : These findings highlight differential underlying mechanisms in the hippocampal degeneration associated with LATE‐NC versus ADNC and may have important implications for both treatment and prognosis.   METHODS 2.1 Study subjects Participants were older adults enrolled from the Religious Orders Study (ROS), the Rush Memory and Aging Project (MAP), or the Minority Aging Research Study (MARS). , ROS recruits priests, nuns, and brothers from across the United States. MAP enrolls both non‐Latino White and Black participants, whereas MARS specifically focuses on non‐Latino Black participants from the Chicago metropolitan area. Eligibility in all three studies included age ≥65 years, no known dementia, and agreement to annual clinical evaluations. Each study was approved by a Rush University Medical Center Institutional Review Board. Participants from all three studies signed a written informed consent at the time of enrollment. Participants from ROS and MAP also signed an Anatomical Gift Act for required brain donation, whereas brain donation was optional for MARS participants. Follow‐up across all studies exceeds 88%, and autopsy rates exceed 91% for ROS and 84% for MAP. At the time of the analyses in June 2023, a total of 4630 ROS‐MAP‐MARS older participants completed baseline cognitive evaluations. Among these participants, 4059 had longitudinal cognition data with at least two follow‐up visits for cognitive assessments, 2371 older subjects died, 1912 were autopsied, and 1841 had a complete neuropathologic workup for diagnosis of neurodegenerative diseases. HNL data collection was started in mid‐2018 from a consecutive subset of autopsied subjects. At the time of analyses, 425 subjects with complete pathology data on HNL from 1841 participants were available for inclusion in this study (Figure ). We found no differences between 425 participants who had HNL data and participants who did not have HNL data ( n = 1416) for demographic, clinical, and neuropathologic characteristics (Table ). Age was determined by the date of birth and date of death. Sex and education (in years) were self‐reported at baseline. 2.2 Clinical evaluation All participants underwent annual uniform structured clinical examinations including a medical history, neuropsychological testing, and neurologic examination. All clinical tests were conducted by clinicians who were blinded to prior assessments. A uniform battery of 19 tests was used to assess cognitive function, which generated composite measures of global cognitive function and the five specific domains of episodic, semantic, and working memory; perceptual speed; and visuospatial ability. Composite measures of global cognitive function and of five cognitive domains were derived by averaging standardized scores of individual tests. 2.3 Neuropathology Brain autopsies were performed by trained staff, who were blinded to clinical data, following a standard protocol, as described previously. The median postmortem interval was 8 h (interquartile range [IQR] = 5.98–12.95h). After brain removal, the brain was bisected to separate the two hemispheres. One hemisphere was cut coronally into 1 cm slabs and frozen, and the other hemisphere was fixed in 4% paraformaldehyde solution for 30 days. After fixation, the hemisphere was cut into 1‐cm‐thick slabs, and tissue blocks from the hippocampus were obtained to assess HNL, and from other multiple brain regions for pathological assessments, as described below in sections from 2.3.1 to 2.3.7. 2.3.1 HNL HNL may not be uniform across the length of the hippocampus or consistent across hemispheres. We assessed the hippocampus using H&E‐stained CA1‐subiculum sectors from three locations of the hippocampus from each brain, including the mid‐hippocampus from one hemisphere, the ipsilateral anterior hippocampus, and the contralateral anterior hippocampus. Three raters with expertise in aging and dementia graded the severity of NL in all three locations using a 0 to 5 scale, where 0 indicated none or minimal NL (0%–5%); 1, mild (6%–25%); 2, mild–moderate (26%–50%); 3, moderate (51%–75%); 4, moderate‐to‐severe (76%–90%); and 5, severe NL (>90%). Note that, by definition, the participants with severe NL in one or more of the three hippocampal locations sampled (mid‐hippocampus and ipsilateral and contralateral anterior hippocampi) have a pathologic diagnosis of HS. We assessed interrater agreement of HNL ratings among the three raters for HNL using a generalized weighted kappa statistic. This assessment was carried out in 66 participants, selected to represent all levels of HNL severity. The generalized weighted kappa statistic was 0.81, which indicates that the three raters have excellent agreement in assessing HNL. Because all subjects had some degree of NL and it was moderately correlated among three brain regions (Spearman ρ ’s range from 0.55 to 0.77), we created a continuous measure of HNL severity score by averaging the scores from the three locations used for this measure in the analytical analyses. For descriptive statistics, the overall HNL severity was converted into a three‐level class variable predictor, with none–mild (0–2), moderate (3–4), and severe NL (5) (Figure ). 2.3.2 ADNC Modified Bielschowsky‐stained sections of midfrontal, middle temporal, inferior parietal, and entorhinal cortices and hippocampus was used to manually count the neuritic plaques and neurofibrillary tangles in an area of greatest density from each region to determine the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) score and Braak staging. The presence of amyloid beta (Aβ) plaques was examined from multiple brain regions (midfrontal, middle temporal, and inferior parietal cortices; hippocampus; basal ganglia; substantia nigra; and cerebellum) using Aβ immunohistochemistry (4G8 antibody; 1:9000; Covance Labs, Madison, WI) to determine the Thal stage. A pathologic diagnosis of ADNC was determined by using National Institute on Aging–Alzheimer's Association (NIA‐AA) criteria, which required either an intermediate or high likelihood of ADNC. 2.3.3 LATE‐NC and HS Phosphorylated transactive response DNA‐binding protein 43 (TDP‐43) associated with LATE‐NC was assessed by immunohistochemistry using a monoclonal antibody to phosphorylated TDP‐43 (pS409/410; 1:100) from eight brain regions: entorhinal cortex, anterior temporal pole, middle temporal gyrus, middle frontal gyrus, and inferior orbital frontal cortices, amygdala, and CA1 and dentate gyrus of hippocampus. Semi‐quantitative measures of phosphorylated TDP‐43 pathology were determined based on the number of pathogenic TDP‐43 cytoplasmic inclusions in a 0.25 mm 2 area of greatest density. Semi‐quantitative assessment of inclusions were also summarized as four distinct stages based on the distribution of phosphorylated TDP‐43 in the brain; stage 0 (no presence of TDP‐43), stage 1 (TDP‐43 localized to the amygdala only), stage 2 (extension of TDP‐43 to the hippocampus and/or entorhinal cortex), and stage 3 (extension of TDP‐43 into the neocortex). A dichotomous variable of none/low (stage 0 and 1) and advanced LATE‐NC (stage 2 and 3) was used for descriptive and analytical analyses. In addition, a grade of the severity of TDP‐43 cytoplasmic inclusions from the hippocampal region was also used to obtain hippocampal TDP‐43 burden. As previously defined, , , HS refers to severe NL and gliosis occurring in either the CA1 or subiculum regions of the hippocampus. In this study, HS were considered if any of the hippocampi (mid‐hippocampus and ipsilateral and contralateral anterior hippocampi) contained severe NL (with total or near total loss of neurons) and gliosis. 2.3.4 Hippocampal Aβ load Hippocampal Aβ was assessed by immunohistochemistry using one of the three monoclonal antibodies against Aβ: 4G8 (1:9000; Covance Labs, Madison, WI), 6F/3D (1:50; Dako North America Inc., Carpinteria, CA), and 10D5 (1:600; Elan Pharmaceuticals, San Francisco, CA) from the CA1/subiculum sector of the hippocampus. For quantification, before 2019, examiners outlined the cortex using Stereo Investigator software. The systematic random sampling (SRS) grid within the software was applied to the regions of interest (ROIs). Images at each sampling grid were manually taken, and the percentage of images positive for amyloid was calculated. Digital scanning of 4G8‐stained slides began in 2019, using the Aperio AT2 whole slide brightfield scanning system. Briefly, 4G8‐stained tissue slides were loaded into the Aperio AT2 scanner console and processed to generate digital whole slide images. The ROI (CA1 and subiculum) in the hippocampus was outlined manually (excluding meninges). Digital image analysis for Aβ pathology was quantified using the Aperio Image Analysis Toolbox Positive Pixel Count algorithm. Algorithm‐input parameters were optimized for Aβ‐staining intensity and applied to whole slide images from the hippocampus. Digital scores are the percentage of amyloid (after square root transformation) from the hippocampus. For analyses, we harmonized historical data with the new digital data for Aβ and used the digital scores for Aβ that reflect the percentage of total hippocampal Aβ load. 2.3.5 Hippocampal tau tangle density The hippocampus was immunostained with an antibody specific to phosphorylated tau: AT8 (1:2000, Thermo Fisher Scientific, Rockford, IL USA). Similar to the Aβ assessment, before 2019, a trained examiner blinded to Aβ data quantified tangle density per square millimeter by using a stereological mapping station as described previously. A digital scanning of AT8‐stained slides began in 2019. In brief, pathology slides were loaded into the Aperio AT2 scanner console and processed to generate whole digital slide images. An annotation was created and Aperio Image Analysis Toolbox Nuclear algorithm was applied to quantify tau tangles. Hippocampal tau‐tangle burden was calculated for each slide by adding up the nuclei with medium and strong threshold, and dividing by the analysis area, resulting in a value of nuclei in counts per mm 2 . Digital scores are reported as hippocampal tau‐tangle burden, after square root transformation. For descriptive and analytical analyses, we harmonized historical data with the new digital data for tau tangles and used the digital scores for hippocampal tau‐tangle burden. 2.3.6 Lewy body pathology Lewy body (LB) pathology was assessed by immunohistochemistry using monoclonal phosphorylated antibody to α‐synuclein (Zymed LB 509; 1:50; pSyn, 1:20 000; Wako Chemicals) from six brain regions and was computed as present or absent for analyses. 2.3.7 Cerebrovascular pathology Arteriolosclerosis was evaluated from the vessels of the anterior basal ganglia with a semiquantitative grading system (0–3) as described previously. Atherosclerosis was assessed on gross examination of the circle of Willis at the base of the brain including evaluation of anterior, middle, and posterior cerebral arteries and their proximal branches using a semiquantitative scale (0–3). Meningeal and parenchymal vessels from the midfrontal, middle temporal, inferior parietal, and calcarine cortices were assessed for cerebral amyloid angiopathy (CAA) as described previously. All three‐vessel disease pathologies were dichotomously used as none–mild versus moderate–severe for both descriptive and analytic analyses. Chronic infarcts were identified on macroscopic examination and their presence and age were confirmed by microscope. Chronic microinfarcts were identified by microscopy from a minimum set of brain regions; seven cortical, two subcortical, midbrain, and cerebellum. Total cerebral infarcts (both macroscopic and microscopic) were computed dichotomously as present or absent for analyses. 2.4 Statistical analyses We used a linear regression model to examine the associations of age‐at‐death, sex, and education with the degree of HNL. We augmented the model by including the terms for common age‐related pathologies to examine the associations of LATE‐NC and ADNC with HNL. We also compared the HNL level across four groups: (1) no ADNC or LATE‐NC, (2) ADNC without LATE‐NC, (3) LATE‐NC without ADNC, and (4) mixed AD and LATE‐NC via analysis of variance (ANOVA), and multiple comparisons correction was performed with Tukey's Kramer test to obtain an adjusted p ‐value. We also employed regression models to investigate the association between tau tangles, Aβ load, and TDP‐43 from the hippocampus to HNL. Next, we used linear mixed‐effects models to examine the association of HNL with change in global cognition. These models include a term for time in years before death whose coefficient estimates the mean annual rate of change in global cognition. The interaction term of time and HNL examines the association of the severity of HNL with the cognitive slope, such that a significant and negative coefficient suggests that more severe HNL is associated with faster decline in global cognition. We first controlled for age‐at‐death, sex, and education, and then in a separate model, we further controlled for ADNC, LATE‐NC, LBs, arteriolosclerosis, atherosclerosis, CAA, and cerebral infarcts. We then repeated the fully adjusted model to examine the associations of HNL with decline in five cognitive domains. We also repeated fully adjusted models to examine the association of LATE‐NC and ADNC with cognitive decline. We performed sensitivity analyses by excluding cases with HS to examine the association of HNL with LATE‐NC and ADNC, and separately with decline in global cognition and five cognitive domains. Finally, we performed a path analysis to assess the extent to which the associations of LATE‐NC and separately ADNC with decline in cognition can be attributable to HNL. The model partitioned the total association of LATE‐NC, and separately ADNC, with cognitive decline into a direct association and an indirect association through HNL, which were estimated by standardized path coefficients. All analyses were programmed in SAS/STAT software version 9.4 (SAS Institute Inc, Cary, NC). Statistical significance was determined at nominal α level 0.05.   Study subjects Participants were older adults enrolled from the Religious Orders Study (ROS), the Rush Memory and Aging Project (MAP), or the Minority Aging Research Study (MARS). , ROS recruits priests, nuns, and brothers from across the United States. MAP enrolls both non‐Latino White and Black participants, whereas MARS specifically focuses on non‐Latino Black participants from the Chicago metropolitan area. Eligibility in all three studies included age ≥65 years, no known dementia, and agreement to annual clinical evaluations. Each study was approved by a Rush University Medical Center Institutional Review Board. Participants from all three studies signed a written informed consent at the time of enrollment. Participants from ROS and MAP also signed an Anatomical Gift Act for required brain donation, whereas brain donation was optional for MARS participants. Follow‐up across all studies exceeds 88%, and autopsy rates exceed 91% for ROS and 84% for MAP. At the time of the analyses in June 2023, a total of 4630 ROS‐MAP‐MARS older participants completed baseline cognitive evaluations. Among these participants, 4059 had longitudinal cognition data with at least two follow‐up visits for cognitive assessments, 2371 older subjects died, 1912 were autopsied, and 1841 had a complete neuropathologic workup for diagnosis of neurodegenerative diseases. HNL data collection was started in mid‐2018 from a consecutive subset of autopsied subjects. At the time of analyses, 425 subjects with complete pathology data on HNL from 1841 participants were available for inclusion in this study (Figure ). We found no differences between 425 participants who had HNL data and participants who did not have HNL data ( n = 1416) for demographic, clinical, and neuropathologic characteristics (Table ). Age was determined by the date of birth and date of death. Sex and education (in years) were self‐reported at baseline.   Clinical evaluation All participants underwent annual uniform structured clinical examinations including a medical history, neuropsychological testing, and neurologic examination. All clinical tests were conducted by clinicians who were blinded to prior assessments. A uniform battery of 19 tests was used to assess cognitive function, which generated composite measures of global cognitive function and the five specific domains of episodic, semantic, and working memory; perceptual speed; and visuospatial ability. Composite measures of global cognitive function and of five cognitive domains were derived by averaging standardized scores of individual tests.   Neuropathology Brain autopsies were performed by trained staff, who were blinded to clinical data, following a standard protocol, as described previously. The median postmortem interval was 8 h (interquartile range [IQR] = 5.98–12.95h). After brain removal, the brain was bisected to separate the two hemispheres. One hemisphere was cut coronally into 1 cm slabs and frozen, and the other hemisphere was fixed in 4% paraformaldehyde solution for 30 days. After fixation, the hemisphere was cut into 1‐cm‐thick slabs, and tissue blocks from the hippocampus were obtained to assess HNL, and from other multiple brain regions for pathological assessments, as described below in sections from 2.3.1 to 2.3.7. 2.3.1 HNL HNL may not be uniform across the length of the hippocampus or consistent across hemispheres. We assessed the hippocampus using H&E‐stained CA1‐subiculum sectors from three locations of the hippocampus from each brain, including the mid‐hippocampus from one hemisphere, the ipsilateral anterior hippocampus, and the contralateral anterior hippocampus. Three raters with expertise in aging and dementia graded the severity of NL in all three locations using a 0 to 5 scale, where 0 indicated none or minimal NL (0%–5%); 1, mild (6%–25%); 2, mild–moderate (26%–50%); 3, moderate (51%–75%); 4, moderate‐to‐severe (76%–90%); and 5, severe NL (>90%). Note that, by definition, the participants with severe NL in one or more of the three hippocampal locations sampled (mid‐hippocampus and ipsilateral and contralateral anterior hippocampi) have a pathologic diagnosis of HS. We assessed interrater agreement of HNL ratings among the three raters for HNL using a generalized weighted kappa statistic. This assessment was carried out in 66 participants, selected to represent all levels of HNL severity. The generalized weighted kappa statistic was 0.81, which indicates that the three raters have excellent agreement in assessing HNL. Because all subjects had some degree of NL and it was moderately correlated among three brain regions (Spearman ρ ’s range from 0.55 to 0.77), we created a continuous measure of HNL severity score by averaging the scores from the three locations used for this measure in the analytical analyses. For descriptive statistics, the overall HNL severity was converted into a three‐level class variable predictor, with none–mild (0–2), moderate (3–4), and severe NL (5) (Figure ). 2.3.2 ADNC Modified Bielschowsky‐stained sections of midfrontal, middle temporal, inferior parietal, and entorhinal cortices and hippocampus was used to manually count the neuritic plaques and neurofibrillary tangles in an area of greatest density from each region to determine the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) score and Braak staging. The presence of amyloid beta (Aβ) plaques was examined from multiple brain regions (midfrontal, middle temporal, and inferior parietal cortices; hippocampus; basal ganglia; substantia nigra; and cerebellum) using Aβ immunohistochemistry (4G8 antibody; 1:9000; Covance Labs, Madison, WI) to determine the Thal stage. A pathologic diagnosis of ADNC was determined by using National Institute on Aging–Alzheimer's Association (NIA‐AA) criteria, which required either an intermediate or high likelihood of ADNC. 2.3.3 LATE‐NC and HS Phosphorylated transactive response DNA‐binding protein 43 (TDP‐43) associated with LATE‐NC was assessed by immunohistochemistry using a monoclonal antibody to phosphorylated TDP‐43 (pS409/410; 1:100) from eight brain regions: entorhinal cortex, anterior temporal pole, middle temporal gyrus, middle frontal gyrus, and inferior orbital frontal cortices, amygdala, and CA1 and dentate gyrus of hippocampus. Semi‐quantitative measures of phosphorylated TDP‐43 pathology were determined based on the number of pathogenic TDP‐43 cytoplasmic inclusions in a 0.25 mm 2 area of greatest density. Semi‐quantitative assessment of inclusions were also summarized as four distinct stages based on the distribution of phosphorylated TDP‐43 in the brain; stage 0 (no presence of TDP‐43), stage 1 (TDP‐43 localized to the amygdala only), stage 2 (extension of TDP‐43 to the hippocampus and/or entorhinal cortex), and stage 3 (extension of TDP‐43 into the neocortex). A dichotomous variable of none/low (stage 0 and 1) and advanced LATE‐NC (stage 2 and 3) was used for descriptive and analytical analyses. In addition, a grade of the severity of TDP‐43 cytoplasmic inclusions from the hippocampal region was also used to obtain hippocampal TDP‐43 burden. As previously defined, , , HS refers to severe NL and gliosis occurring in either the CA1 or subiculum regions of the hippocampus. In this study, HS were considered if any of the hippocampi (mid‐hippocampus and ipsilateral and contralateral anterior hippocampi) contained severe NL (with total or near total loss of neurons) and gliosis. 2.3.4 Hippocampal Aβ load Hippocampal Aβ was assessed by immunohistochemistry using one of the three monoclonal antibodies against Aβ: 4G8 (1:9000; Covance Labs, Madison, WI), 6F/3D (1:50; Dako North America Inc., Carpinteria, CA), and 10D5 (1:600; Elan Pharmaceuticals, San Francisco, CA) from the CA1/subiculum sector of the hippocampus. For quantification, before 2019, examiners outlined the cortex using Stereo Investigator software. The systematic random sampling (SRS) grid within the software was applied to the regions of interest (ROIs). Images at each sampling grid were manually taken, and the percentage of images positive for amyloid was calculated. Digital scanning of 4G8‐stained slides began in 2019, using the Aperio AT2 whole slide brightfield scanning system. Briefly, 4G8‐stained tissue slides were loaded into the Aperio AT2 scanner console and processed to generate digital whole slide images. The ROI (CA1 and subiculum) in the hippocampus was outlined manually (excluding meninges). Digital image analysis for Aβ pathology was quantified using the Aperio Image Analysis Toolbox Positive Pixel Count algorithm. Algorithm‐input parameters were optimized for Aβ‐staining intensity and applied to whole slide images from the hippocampus. Digital scores are the percentage of amyloid (after square root transformation) from the hippocampus. For analyses, we harmonized historical data with the new digital data for Aβ and used the digital scores for Aβ that reflect the percentage of total hippocampal Aβ load. 2.3.5 Hippocampal tau tangle density The hippocampus was immunostained with an antibody specific to phosphorylated tau: AT8 (1:2000, Thermo Fisher Scientific, Rockford, IL USA). Similar to the Aβ assessment, before 2019, a trained examiner blinded to Aβ data quantified tangle density per square millimeter by using a stereological mapping station as described previously. A digital scanning of AT8‐stained slides began in 2019. In brief, pathology slides were loaded into the Aperio AT2 scanner console and processed to generate whole digital slide images. An annotation was created and Aperio Image Analysis Toolbox Nuclear algorithm was applied to quantify tau tangles. Hippocampal tau‐tangle burden was calculated for each slide by adding up the nuclei with medium and strong threshold, and dividing by the analysis area, resulting in a value of nuclei in counts per mm 2 . Digital scores are reported as hippocampal tau‐tangle burden, after square root transformation. For descriptive and analytical analyses, we harmonized historical data with the new digital data for tau tangles and used the digital scores for hippocampal tau‐tangle burden. 2.3.6 Lewy body pathology Lewy body (LB) pathology was assessed by immunohistochemistry using monoclonal phosphorylated antibody to α‐synuclein (Zymed LB 509; 1:50; pSyn, 1:20 000; Wako Chemicals) from six brain regions and was computed as present or absent for analyses. 2.3.7 Cerebrovascular pathology Arteriolosclerosis was evaluated from the vessels of the anterior basal ganglia with a semiquantitative grading system (0–3) as described previously. Atherosclerosis was assessed on gross examination of the circle of Willis at the base of the brain including evaluation of anterior, middle, and posterior cerebral arteries and their proximal branches using a semiquantitative scale (0–3). Meningeal and parenchymal vessels from the midfrontal, middle temporal, inferior parietal, and calcarine cortices were assessed for cerebral amyloid angiopathy (CAA) as described previously. All three‐vessel disease pathologies were dichotomously used as none–mild versus moderate–severe for both descriptive and analytic analyses. Chronic infarcts were identified on macroscopic examination and their presence and age were confirmed by microscope. Chronic microinfarcts were identified by microscopy from a minimum set of brain regions; seven cortical, two subcortical, midbrain, and cerebellum. Total cerebral infarcts (both macroscopic and microscopic) were computed dichotomously as present or absent for analyses.   HNL HNL may not be uniform across the length of the hippocampus or consistent across hemispheres. We assessed the hippocampus using H&E‐stained CA1‐subiculum sectors from three locations of the hippocampus from each brain, including the mid‐hippocampus from one hemisphere, the ipsilateral anterior hippocampus, and the contralateral anterior hippocampus. Three raters with expertise in aging and dementia graded the severity of NL in all three locations using a 0 to 5 scale, where 0 indicated none or minimal NL (0%–5%); 1, mild (6%–25%); 2, mild–moderate (26%–50%); 3, moderate (51%–75%); 4, moderate‐to‐severe (76%–90%); and 5, severe NL (>90%). Note that, by definition, the participants with severe NL in one or more of the three hippocampal locations sampled (mid‐hippocampus and ipsilateral and contralateral anterior hippocampi) have a pathologic diagnosis of HS. We assessed interrater agreement of HNL ratings among the three raters for HNL using a generalized weighted kappa statistic. This assessment was carried out in 66 participants, selected to represent all levels of HNL severity. The generalized weighted kappa statistic was 0.81, which indicates that the three raters have excellent agreement in assessing HNL. Because all subjects had some degree of NL and it was moderately correlated among three brain regions (Spearman ρ ’s range from 0.55 to 0.77), we created a continuous measure of HNL severity score by averaging the scores from the three locations used for this measure in the analytical analyses. For descriptive statistics, the overall HNL severity was converted into a three‐level class variable predictor, with none–mild (0–2), moderate (3–4), and severe NL (5) (Figure ).   ADNC Modified Bielschowsky‐stained sections of midfrontal, middle temporal, inferior parietal, and entorhinal cortices and hippocampus was used to manually count the neuritic plaques and neurofibrillary tangles in an area of greatest density from each region to determine the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) score and Braak staging. The presence of amyloid beta (Aβ) plaques was examined from multiple brain regions (midfrontal, middle temporal, and inferior parietal cortices; hippocampus; basal ganglia; substantia nigra; and cerebellum) using Aβ immunohistochemistry (4G8 antibody; 1:9000; Covance Labs, Madison, WI) to determine the Thal stage. A pathologic diagnosis of ADNC was determined by using National Institute on Aging–Alzheimer's Association (NIA‐AA) criteria, which required either an intermediate or high likelihood of ADNC.   LATE‐NC and HS Phosphorylated transactive response DNA‐binding protein 43 (TDP‐43) associated with LATE‐NC was assessed by immunohistochemistry using a monoclonal antibody to phosphorylated TDP‐43 (pS409/410; 1:100) from eight brain regions: entorhinal cortex, anterior temporal pole, middle temporal gyrus, middle frontal gyrus, and inferior orbital frontal cortices, amygdala, and CA1 and dentate gyrus of hippocampus. Semi‐quantitative measures of phosphorylated TDP‐43 pathology were determined based on the number of pathogenic TDP‐43 cytoplasmic inclusions in a 0.25 mm 2 area of greatest density. Semi‐quantitative assessment of inclusions were also summarized as four distinct stages based on the distribution of phosphorylated TDP‐43 in the brain; stage 0 (no presence of TDP‐43), stage 1 (TDP‐43 localized to the amygdala only), stage 2 (extension of TDP‐43 to the hippocampus and/or entorhinal cortex), and stage 3 (extension of TDP‐43 into the neocortex). A dichotomous variable of none/low (stage 0 and 1) and advanced LATE‐NC (stage 2 and 3) was used for descriptive and analytical analyses. In addition, a grade of the severity of TDP‐43 cytoplasmic inclusions from the hippocampal region was also used to obtain hippocampal TDP‐43 burden. As previously defined, , , HS refers to severe NL and gliosis occurring in either the CA1 or subiculum regions of the hippocampus. In this study, HS were considered if any of the hippocampi (mid‐hippocampus and ipsilateral and contralateral anterior hippocampi) contained severe NL (with total or near total loss of neurons) and gliosis.   Hippocampal Aβ load Hippocampal Aβ was assessed by immunohistochemistry using one of the three monoclonal antibodies against Aβ: 4G8 (1:9000; Covance Labs, Madison, WI), 6F/3D (1:50; Dako North America Inc., Carpinteria, CA), and 10D5 (1:600; Elan Pharmaceuticals, San Francisco, CA) from the CA1/subiculum sector of the hippocampus. For quantification, before 2019, examiners outlined the cortex using Stereo Investigator software. The systematic random sampling (SRS) grid within the software was applied to the regions of interest (ROIs). Images at each sampling grid were manually taken, and the percentage of images positive for amyloid was calculated. Digital scanning of 4G8‐stained slides began in 2019, using the Aperio AT2 whole slide brightfield scanning system. Briefly, 4G8‐stained tissue slides were loaded into the Aperio AT2 scanner console and processed to generate digital whole slide images. The ROI (CA1 and subiculum) in the hippocampus was outlined manually (excluding meninges). Digital image analysis for Aβ pathology was quantified using the Aperio Image Analysis Toolbox Positive Pixel Count algorithm. Algorithm‐input parameters were optimized for Aβ‐staining intensity and applied to whole slide images from the hippocampus. Digital scores are the percentage of amyloid (after square root transformation) from the hippocampus. For analyses, we harmonized historical data with the new digital data for Aβ and used the digital scores for Aβ that reflect the percentage of total hippocampal Aβ load.   Hippocampal tau tangle density The hippocampus was immunostained with an antibody specific to phosphorylated tau: AT8 (1:2000, Thermo Fisher Scientific, Rockford, IL USA). Similar to the Aβ assessment, before 2019, a trained examiner blinded to Aβ data quantified tangle density per square millimeter by using a stereological mapping station as described previously. A digital scanning of AT8‐stained slides began in 2019. In brief, pathology slides were loaded into the Aperio AT2 scanner console and processed to generate whole digital slide images. An annotation was created and Aperio Image Analysis Toolbox Nuclear algorithm was applied to quantify tau tangles. Hippocampal tau‐tangle burden was calculated for each slide by adding up the nuclei with medium and strong threshold, and dividing by the analysis area, resulting in a value of nuclei in counts per mm 2 . Digital scores are reported as hippocampal tau‐tangle burden, after square root transformation. For descriptive and analytical analyses, we harmonized historical data with the new digital data for tau tangles and used the digital scores for hippocampal tau‐tangle burden.   Lewy body pathology Lewy body (LB) pathology was assessed by immunohistochemistry using monoclonal phosphorylated antibody to α‐synuclein (Zymed LB 509; 1:50; pSyn, 1:20 000; Wako Chemicals) from six brain regions and was computed as present or absent for analyses.   Cerebrovascular pathology Arteriolosclerosis was evaluated from the vessels of the anterior basal ganglia with a semiquantitative grading system (0–3) as described previously. Atherosclerosis was assessed on gross examination of the circle of Willis at the base of the brain including evaluation of anterior, middle, and posterior cerebral arteries and their proximal branches using a semiquantitative scale (0–3). Meningeal and parenchymal vessels from the midfrontal, middle temporal, inferior parietal, and calcarine cortices were assessed for cerebral amyloid angiopathy (CAA) as described previously. All three‐vessel disease pathologies were dichotomously used as none–mild versus moderate–severe for both descriptive and analytic analyses. Chronic infarcts were identified on macroscopic examination and their presence and age were confirmed by microscope. Chronic microinfarcts were identified by microscopy from a minimum set of brain regions; seven cortical, two subcortical, midbrain, and cerebellum. Total cerebral infarcts (both macroscopic and microscopic) were computed dichotomously as present or absent for analyses.   Statistical analyses We used a linear regression model to examine the associations of age‐at‐death, sex, and education with the degree of HNL. We augmented the model by including the terms for common age‐related pathologies to examine the associations of LATE‐NC and ADNC with HNL. We also compared the HNL level across four groups: (1) no ADNC or LATE‐NC, (2) ADNC without LATE‐NC, (3) LATE‐NC without ADNC, and (4) mixed AD and LATE‐NC via analysis of variance (ANOVA), and multiple comparisons correction was performed with Tukey's Kramer test to obtain an adjusted p ‐value. We also employed regression models to investigate the association between tau tangles, Aβ load, and TDP‐43 from the hippocampus to HNL. Next, we used linear mixed‐effects models to examine the association of HNL with change in global cognition. These models include a term for time in years before death whose coefficient estimates the mean annual rate of change in global cognition. The interaction term of time and HNL examines the association of the severity of HNL with the cognitive slope, such that a significant and negative coefficient suggests that more severe HNL is associated with faster decline in global cognition. We first controlled for age‐at‐death, sex, and education, and then in a separate model, we further controlled for ADNC, LATE‐NC, LBs, arteriolosclerosis, atherosclerosis, CAA, and cerebral infarcts. We then repeated the fully adjusted model to examine the associations of HNL with decline in five cognitive domains. We also repeated fully adjusted models to examine the association of LATE‐NC and ADNC with cognitive decline. We performed sensitivity analyses by excluding cases with HS to examine the association of HNL with LATE‐NC and ADNC, and separately with decline in global cognition and five cognitive domains. Finally, we performed a path analysis to assess the extent to which the associations of LATE‐NC and separately ADNC with decline in cognition can be attributable to HNL. The model partitioned the total association of LATE‐NC, and separately ADNC, with cognitive decline into a direct association and an indirect association through HNL, which were estimated by standardized path coefficients. All analyses were programmed in SAS/STAT software version 9.4 (SAS Institute Inc, Cary, NC). Statistical significance was determined at nominal α level 0.05.   RESULTS 3.1 Subjects A total of 425 participants were included in the analyses. Mean age‐at‐death was 91 years and 72% were female. Clinical and neuropathologic characteristics of participants are summarized in Table . HNL was common and similar across the three locations of the hippocampus. About 61% of participants ( n = 260) had mild HNL, 19% ( n = 78) had moderate, and 20% ( n = 87) had severe HNL. In a linear regression model that included age‐at‐death, sex, and education as predictors, we found that older age (odds ratio [OR] = 1.05, 95% confidence interval [CI] = 1.02–1.09, p < 0.001) and female sex (OR = 1.69, 95% CI = 1.08–2.66, p = 0.021) were associated with more severe HNL, whereas education was not significant ( p = 0.808). Of 78 participants with moderate HNL, only 12 (15.38%) had moderate HNL in all three hippocampal areas. Similarly, only 24 of 87 (28%) participants had severe HNL (HS) in all three hippocampal areas. Eighty‐seven participants had HS, of which, HS was mostly unilateral ( n = 57, 65%) and only bilateral in 30 (35%) of participants. The anatomic regions involved in HS varied: 34 participants had HS only in the anterior hippocampus and lacked in the mid‐hippocampus, whereas only a small number of participants had HS in the mid‐hippocampus without having it in the anterior hippocampus ( n =  5) (χ 2 = 155.50, df = 1, p = < 0.001). Table shows the distributions of neuronal loss severities in the anterior and mid‐hippocampal regions. 3.2 HNL, ADNC, and LATE‐NC Because both ADNC and LATE‐NC are commonly present in the hippocampus, we compared the severity of HNL across four groups: (1) no ADNC or LATE‐NC (reference group; n = 68, 16%), (2) ADNC without LATE‐NC ( n = 179, 42%), (3) LATE‐NC without ADNC ( n = 73, 17%), and (4) mixed AD and LATE‐NC ( n = 105, 25%) (Figure ). HNL differed across the four groups ( p < 0.001). Compared to the reference group, HNL was higher among LATE‐NC without ADNC ( t ‐value = −9.03, p < 0.001) and mixed AD and LATE‐NC groups ( t ‐value = −11.31, p < 0.001), but not ADNC without LATE‐NC ( t ‐value = −1.63, p = 0.361), suggesting heterogeneity in HNL across pathologic groups. Next, we examined the associations of LATE‐NC and ADNC with HNL. After controlling for demographics, ADNC, and other brain pathologies, LATE‐NC was associated with more HNL. The association remained significant after excluding the subjects with HS (Table ). In the same model, ADNC was not associated with HNL after controlling for demographics, LATE‐NC, and other brain pathologies. We also examined the associations of Thal phase, Braak stage, and CERAD score with HNL after controlling demographics and LATE‐NC. Similar to the findings for ADNC, no significant associations were observed between HNL and Thal phase (Est = 0.057, standard error [SE] = 0.042, p = 0.173), Braak stage (Est = 0.089, SE = 0.067, p = 0.186), and CERAD score (Est = 0.053, SE = 0.040, p = 0.196). However, a significant association became evident between the diagnosis of ADNC (Table ) and HNL as well as Braak stage (Est = 0.205, SE = 0.05, p < 0.001) and HNL after excluding subjects with HS. , To further understand this unexpected finding, we examined regional Aβ load, tau‐tangle density, and TDP‐43 to understand their associations with HNL. As observed in LATE‐NC, a higher burden of hippocampal TDP‐43 was associated with more severe HNL (Est = 0.380, SE = 0.029, p < 0.001). Hippocampal Aβ load was still not associated (Est = 0.147, SE = 0.108, p = 0.176), and unexpectedly, hippocampal tangles were negatively associated with HNL (Est = −0.083, SE = 0.030, p = 0.006). We hypothesized that this finding may be related to the severe loss of neurons in HS. To investigate this hypothesis, we first compared the distributions of hippocampal tangle and TDP‐43 levels across different grades of HNL. Scatter plots and Loess curve in Figure shows that the burden of hippocampal tangle is less in cases with more severe HNL, being particularly lower when HS is present, whereas hippocampal TDP‐43 levels were increased with more severe HNL and plateau at the end. Based on this finding, we repeated the analysis after excluding the participants with HS, and we observed a positive association between hippocampal tangle and HNL (Est = 0.047, SE = 0.016, p = 0.004). Furthermore, other brain pathologies including Lewy bodies, arteriolosclerosis, CAA, atherosclerosis, and cerebral infarcts were also not associated with HNL (data not shown, all p values > 0.058). 3.3 HNL and cognitive decline In the initial analysis adjusted for age‐at‐death, sex, and education, the severity of HNL was associated with a faster decline of 0.031 units per year in global cognition (SE = 0.003, p = < 0.001). After further adjustment for common neuropathologic diseases of ADNC, LATE‐NC, and other brain pathologies (LBs, atherosclerosis, arteriolosclerosis, CAA, and cerebral infarcts), more severe HNL was associated with a 0.023‐unit per year decline in global cognition ( p < 0.001, Table ). In addition, the severity of HNL was associated with a 0.028‐unit per year of decline in episodic memory, 0.024‐unit per year in semantic memory, 0.010‐unit in working memory, and 0.008‐unit in perceptual speed after adjusting for demographics and common age‐related pathologies (Table ). We did not observe an association of HNL with decline in visuospatial orientation. Figure shows the rates of decline in global cognition for subjects with moderate and severe HNL compared to those with mild HNL. Because HS is a potent driver for cognitive decline, , we examined whether the association of HNL with rates of decline in global cognition and five specific cognitive systems remained in the absence of HS. On exclusion of subjects with HS, we found that associations between HNL and faster rates of decline in global cognition and episodic memory, semantic memory, and working memory remained (Table ). Consistent with prior studies LATE‐NC (stage 2 and above) and ADNC were also associated with cognitive decline after controlling for demographics and other common brain pathologies (Table ). 3.4 Link between LATE‐NC, ADNC, HNL, and cognitive decline Given that HNL was associated with LATE‐NC, ADNC, and cognitive decline and separately LATE‐NC and ADNC were independently associated with cognitive decline, we examined whether HNL was a pathway for LATE‐NC and ADNC to cognitive decline. To examine the pathway, we used person‐specific slopes of change in cognition as an outcome, LATE‐NC and ADNC as predictors, and HNL as a potential mediator. The path analyses showed three significant pathways: (1) LATE‐NC to cognitive decline through HNL, (2) ADNC to cognitive decline without HNL, and (3) LATE‐NC to cognitive decline without HNL. Specifically, the total association of LATE‐NC to cognitive decline had a standardized coefficient of −0.284 (SE = 0.043, p < 0.001). Sixty‐one percent of this total association was attributable to HNL (estimate = −0.172; SE = 0.029, p = < 0.001) and the remaining 39% represented a direct association (estimate = −0.111; SE = 0.050, p = 0.027). In contrast, the total association of ADNC to cognitive decline had a standardized coefficient of −0.260 (SE = 0.043, p = < 0.001). About 95% of this total association represented a direct association of ADNC with cognitive decline (estimate = −0.248; SE = 0.041, p = < 0.001). The association of ADNC to cognitive decline through HNL was not significant (estimate = −0.011, SE = 0.013, p = 0.389) (Figure ).   Subjects A total of 425 participants were included in the analyses. Mean age‐at‐death was 91 years and 72% were female. Clinical and neuropathologic characteristics of participants are summarized in Table . HNL was common and similar across the three locations of the hippocampus. About 61% of participants ( n = 260) had mild HNL, 19% ( n = 78) had moderate, and 20% ( n = 87) had severe HNL. In a linear regression model that included age‐at‐death, sex, and education as predictors, we found that older age (odds ratio [OR] = 1.05, 95% confidence interval [CI] = 1.02–1.09, p < 0.001) and female sex (OR = 1.69, 95% CI = 1.08–2.66, p = 0.021) were associated with more severe HNL, whereas education was not significant ( p = 0.808). Of 78 participants with moderate HNL, only 12 (15.38%) had moderate HNL in all three hippocampal areas. Similarly, only 24 of 87 (28%) participants had severe HNL (HS) in all three hippocampal areas. Eighty‐seven participants had HS, of which, HS was mostly unilateral ( n = 57, 65%) and only bilateral in 30 (35%) of participants. The anatomic regions involved in HS varied: 34 participants had HS only in the anterior hippocampus and lacked in the mid‐hippocampus, whereas only a small number of participants had HS in the mid‐hippocampus without having it in the anterior hippocampus ( n =  5) (χ 2 = 155.50, df = 1, p = < 0.001). Table shows the distributions of neuronal loss severities in the anterior and mid‐hippocampal regions.   HNL, ADNC, and LATE‐NC Because both ADNC and LATE‐NC are commonly present in the hippocampus, we compared the severity of HNL across four groups: (1) no ADNC or LATE‐NC (reference group; n = 68, 16%), (2) ADNC without LATE‐NC ( n = 179, 42%), (3) LATE‐NC without ADNC ( n = 73, 17%), and (4) mixed AD and LATE‐NC ( n = 105, 25%) (Figure ). HNL differed across the four groups ( p < 0.001). Compared to the reference group, HNL was higher among LATE‐NC without ADNC ( t ‐value = −9.03, p < 0.001) and mixed AD and LATE‐NC groups ( t ‐value = −11.31, p < 0.001), but not ADNC without LATE‐NC ( t ‐value = −1.63, p = 0.361), suggesting heterogeneity in HNL across pathologic groups. Next, we examined the associations of LATE‐NC and ADNC with HNL. After controlling for demographics, ADNC, and other brain pathologies, LATE‐NC was associated with more HNL. The association remained significant after excluding the subjects with HS (Table ). In the same model, ADNC was not associated with HNL after controlling for demographics, LATE‐NC, and other brain pathologies. We also examined the associations of Thal phase, Braak stage, and CERAD score with HNL after controlling demographics and LATE‐NC. Similar to the findings for ADNC, no significant associations were observed between HNL and Thal phase (Est = 0.057, standard error [SE] = 0.042, p = 0.173), Braak stage (Est = 0.089, SE = 0.067, p = 0.186), and CERAD score (Est = 0.053, SE = 0.040, p = 0.196). However, a significant association became evident between the diagnosis of ADNC (Table ) and HNL as well as Braak stage (Est = 0.205, SE = 0.05, p < 0.001) and HNL after excluding subjects with HS. , To further understand this unexpected finding, we examined regional Aβ load, tau‐tangle density, and TDP‐43 to understand their associations with HNL. As observed in LATE‐NC, a higher burden of hippocampal TDP‐43 was associated with more severe HNL (Est = 0.380, SE = 0.029, p < 0.001). Hippocampal Aβ load was still not associated (Est = 0.147, SE = 0.108, p = 0.176), and unexpectedly, hippocampal tangles were negatively associated with HNL (Est = −0.083, SE = 0.030, p = 0.006). We hypothesized that this finding may be related to the severe loss of neurons in HS. To investigate this hypothesis, we first compared the distributions of hippocampal tangle and TDP‐43 levels across different grades of HNL. Scatter plots and Loess curve in Figure shows that the burden of hippocampal tangle is less in cases with more severe HNL, being particularly lower when HS is present, whereas hippocampal TDP‐43 levels were increased with more severe HNL and plateau at the end. Based on this finding, we repeated the analysis after excluding the participants with HS, and we observed a positive association between hippocampal tangle and HNL (Est = 0.047, SE = 0.016, p = 0.004). Furthermore, other brain pathologies including Lewy bodies, arteriolosclerosis, CAA, atherosclerosis, and cerebral infarcts were also not associated with HNL (data not shown, all p values > 0.058).   HNL and cognitive decline In the initial analysis adjusted for age‐at‐death, sex, and education, the severity of HNL was associated with a faster decline of 0.031 units per year in global cognition (SE = 0.003, p = < 0.001). After further adjustment for common neuropathologic diseases of ADNC, LATE‐NC, and other brain pathologies (LBs, atherosclerosis, arteriolosclerosis, CAA, and cerebral infarcts), more severe HNL was associated with a 0.023‐unit per year decline in global cognition ( p < 0.001, Table ). In addition, the severity of HNL was associated with a 0.028‐unit per year of decline in episodic memory, 0.024‐unit per year in semantic memory, 0.010‐unit in working memory, and 0.008‐unit in perceptual speed after adjusting for demographics and common age‐related pathologies (Table ). We did not observe an association of HNL with decline in visuospatial orientation. Figure shows the rates of decline in global cognition for subjects with moderate and severe HNL compared to those with mild HNL. Because HS is a potent driver for cognitive decline, , we examined whether the association of HNL with rates of decline in global cognition and five specific cognitive systems remained in the absence of HS. On exclusion of subjects with HS, we found that associations between HNL and faster rates of decline in global cognition and episodic memory, semantic memory, and working memory remained (Table ). Consistent with prior studies LATE‐NC (stage 2 and above) and ADNC were also associated with cognitive decline after controlling for demographics and other common brain pathologies (Table ).   Link between LATE‐NC, ADNC, HNL, and cognitive decline Given that HNL was associated with LATE‐NC, ADNC, and cognitive decline and separately LATE‐NC and ADNC were independently associated with cognitive decline, we examined whether HNL was a pathway for LATE‐NC and ADNC to cognitive decline. To examine the pathway, we used person‐specific slopes of change in cognition as an outcome, LATE‐NC and ADNC as predictors, and HNL as a potential mediator. The path analyses showed three significant pathways: (1) LATE‐NC to cognitive decline through HNL, (2) ADNC to cognitive decline without HNL, and (3) LATE‐NC to cognitive decline without HNL. Specifically, the total association of LATE‐NC to cognitive decline had a standardized coefficient of −0.284 (SE = 0.043, p < 0.001). Sixty‐one percent of this total association was attributable to HNL (estimate = −0.172; SE = 0.029, p = < 0.001) and the remaining 39% represented a direct association (estimate = −0.111; SE = 0.050, p = 0.027). In contrast, the total association of ADNC to cognitive decline had a standardized coefficient of −0.260 (SE = 0.043, p = < 0.001). About 95% of this total association represented a direct association of ADNC with cognitive decline (estimate = −0.248; SE = 0.041, p = < 0.001). The association of ADNC to cognitive decline through HNL was not significant (estimate = −0.011, SE = 0.013, p = 0.389) (Figure ).   DISCUSSION In this clinical‐pathologic investigation involving over 400 older subjects recruited from the community, we investigated the interconnected roles of HNL, LATE‐NC, and ADNC that lead to cognitive decline during aging. Our study reveals that HNL is common among older adults and exhibits independent associations with LATE‐NC, and to a lesser extent with ADNC specifically in individuals without HS. HNL emerges as an important driver of late‐life cognitive decline, above and beyond the presence of AD, LATE‐NC, and other brain pathologies. Specifically, we observed that HNL correlates with declines in overall cognitive function as well as in memory domains such as episodic memory, semantic memory, and working memory, even after excluding participants with HS. Moreover, we found that HNL contributed substantially to the association between LATE‐NC and cognitive decline, accounting for nearly two‐thirds of the total effect. However, the relationship between ADNC and cognitive decline was predominantly direct. These findings collectively provide compelling evidence that disparate pathological mechanisms within the hippocampus play a role in cognitive decline during the aging process. This study extends prior work in several ways. First, we show that LATE‐NC is independently related to HNL above and beyond AD and other brain pathologies. The association of HNL with LATE‐NC is much stronger than the association with ADNC. Many human studies , , have examined and reported the role of AD in association with HNL, but many of these studies were conducted before the recognition of LATE‐NC as a pathologic entity. In addition, extensive tangle pathology traditionally excludes a diagnosis of HS. However, in this study, our semiquantitative assessments of HNL were based on histological changes seen on H&E staining without regard to the presence or absence of TDP‐43 inclusions or AD pathology, which allowed us to then examine the association of these pathologies with HNL. Second, we unexpectedly observed a negative relationship between hippocampal tau tangles and the severity of HNL. Our data suggest that tangle development may be constrained or the ongoing NL may involve macrophage‐mediated uptake and clearance of the remaining neurofibrillary tangles, particularly in those cases where NL due to HS is pronounced. This hypothesis gains support from the fact that the negative association of HNL with hippocampal tangle was prominent when including individuals with HS but it is reversed when we excluded HS. Third, pathologic TDP‐43 accumulation occurs more frequently even in advanced HNL cases (HS), despite the loss of neurons, suggesting that TDP‐43 inclusions present in either residual neurons or glial cells have a significant role in HNL, whereas in ADNC specifically tangles may be related to significant cognitive dysfunction but through less NL. These differential findings of HNL with ADNC and LATE‐NC may have both mechanistic and treatment implications. In summary, our study not only underscores the potent influence of LATE‐NC on HNL in aging but also suggests that the contribution of ADNC to NL is weaker. The mechanism by which the pathological processes manifest NL in the hippocampus is still unclear. Whether these pathological processes interact with each other or whether pathologic factors separately trigger NL is still unclear. Many animals and in vivo studies have shown that pathologic aggregates can act as a stressor to induce a plethora of cytotoxic mechanisms including upregulation in reactive oxygen species level, synaptic dysfunction, inflammation, and mitochondrial dysfunction, ultimately terminating in neuronal cell death. Recently we showed an association of LATE‐NC and tangle with hippocampal microglia burden, suggesting that future studies examining the association of microglial inflammation with HNL in the context of LATE‐NC and ADNC will be important to understand this complex process. Consistent with other studies, , , we also found that HNL is an important process that contributes to cognitive impairment and is associated with a decline in global cognition and multiple cognitive domains in older subjects. We also expand the current literature by showing that the contribution of HNL to cognitive impairment is also independent of HS, suggesting that not only pronounced HNL, but even lesser loss of neurons has detrimental impacts on cognition in older individuals. This study also suggests that HNL mainly affects the memory domains compared to visuospatial orientation or perceptual speed domain. Many biological changes, including brain inflammation, oxidative stress, innate immunity response, or perhaps lifestyle factors, including unhealthy dietary intakes and impaired sleep, may influence HNL. More work is required to understand the relationship of HNL with these other biological changes. The impact of HNL as a pathway in LATE‐NC toward cognitive decline is largely unclear. This study demonstrates that nearly two‐thirds of the effect of LATE‐NC on cognitive decline operates through HNL and underscores the potential significance of HNL as a key indicator for LATE‐NC. Conversely, the results in the context of ADNC suggest that the impact of ADNC on cognitive decline is largely separate from HNL (see Figure ). This observation is somewhat surprising given that our prior study and other findings , report that ADNC significantly contributes to hippocampal atrophy, which is often used to represent neurodegeneration (N) in the ATN criteria. We postulate that alternative factors besides HNL, such as alterations in synaptic efficacy, reduced dendrites, cell shrinkage, or inflammation, , , may act as a pathway for hippocampal atrophy and subsequent cognitive decline in the context of ADNC. For example, one study found a correlation between frontal white matter signal increase and tangles in patients with clinical dementia and AD, suggesting that axonal degeneration follows hippocampal atrophy in ADNC. Understanding the contributions of HNL and other factors to hippocampal volume in the context of LATE‐NC and ADNC will provide important insight toward differential mechanism related with brain pathologies. HS in aging is recognized as the extreme feature of HNL, and it has been associated with cognitive decline and increased risk of dementia. , , However, the prevalence of HS widely varies from 0.4% to 25% in older adults, partly due to the inclusion of wide age ranges in studies, but also because of the diverse neuropathological definitions of HS. For instance, some studies consider HS present only if it occurs in both CA1 and the subiculum, , whereas others define it as occurring in either CA1 or the subiculum, , , or exclusively within CA1. We examined the hippocampi of both hemispheres to determine the frequency and the laterality of HS and found that the frequency of HS increased twofold after including the anterior hippocampus from both sides, as compared to our previous studies where only mid‐hippocampus was considered. , This finding may suggest that HS may have explained more variance of cognitive decline than reported in our previous study. Consistent with other studies, , we also found that HS was more frequently presented as unilateral, which underscores the need to examine both hippocampi for HS evaluation. However, some other studies have also described bilateral presentation of HS. , Finally, we also found that HS was more frequent at the anterior portion of the hippocampus than mid‐level. In addition, other studies have demonstrated that the anterior hippocampus exhibits more severe TDP‐43‐associated atrophy and tau burden. Our findings indicate that this anterior‐posterior gradient may also extend to HS. Overall, these findings suggest that anterior hippocampus is a key region and should be considered as a diagnostic region for the assessment of HS in aging. This study has a few limitations. First, most subjects in this study were non‐Latino Whites, so the findings cannot be generalized to other ethnic or racial groups. Second, this study included mainly highly educated healthy volunteers and their mean age at death was >90 years; therefore, our findings might not apply to subjects with less education or individuals who have a younger age at death. Third, this study utilized both semi‐quantitative and quantitative methods to assess various pathologies, which may have influenced the results, particularly regarding the sensitivity and specificity of the pathology assessments. Future research incorporating more standardized quantitative neuropathological assessments across different brain pathologies would be valuable in clarifying the complex associations, which may not be fully captured by semi‐quantitative approaches. Finally, pathway analysis in this study assumes temporal causation and thus is intended as an exploratory approach to examine complex interrelationships that might guide future longitudinal research. Countering these limitations, our study also had strengths including a large number of autopsies that came from community‐dwelling cohorts, and an extensive systematic histopathological evaluation of HNL performed by neuropathologists experienced in aging and dementia research who were blinded to LATE‐NC and ADNC findings and clinical information, representing an excellent and uniform setup to evaluate the HNL and other dementia‐related neuropathologies. As previous work showed that HS can be segmental, we evaluated HNL not only on a single coronal section of the mid‐hippocampus, but also from the anterior hippocampi of both hemispheres, which provided more accurate information on HNL and HS distribution. In summary, our findings show that HNL is a potent driver of cognitive decline. In addition, both LATE‐NC and ADNC are related to HNL, but HNL is a more prominent feature of LATE‐NC and is a major pathway for LATE‐NC toward cognitive decline. These findings highlight differential underlying mechanisms in the hippocampal degeneration associated with LATE‐NC versus ADNC and may have important implications for both treatment and prognosis.   S.A., L.Y., S.E.L., S.N., L.L.B., D.A.B. and J.A.S. have no relevant disclosures. Author disclosures are available in the .   All human subjects provided written informed consent.   Supporting Information Supporting Information   