The utility of the National Alzheimer’s Coordinating Center’s database for the rapid assessment of evolving neuropathologic conditions

Abstract

The field of dementia research is rapidly evolving, especially with regards to our understanding of the diversity of neuropathologic changes that underlie cognitive decline. Definitions and criteria for known conditions are being periodically revised and refined, and new findings are being made about neuropathologic features associated with dementia status. The database maintained by the National Alzheimer’s Coordinating Center (NACC) offer researchers a robust, rapid, and statistically well-powered method to evaluate the implications of newly identified neuropathologic conditions with regards to comorbidities, demographic associations, cognitive status, neuropsychologic tests, radiographic findings, and genetics. NACC data derive from dozens of excellent U.S. Alzheimer’s disease research centers, which collectively follow thousands of research volunteers longitudinally. Many of the research participants are autopsied using state-of-the-art methods. In this article, we describe the NACC database and give examples of its use in evaluating recently revised neuropathologic diagnoses, including primary age-related tauopathy (PART), limbic predominant age-related TDP-43 encephalopathy (LATE), and the pre-clinical stage of Alzheimer’s disease neuropathologic change, based on the National Institute on Aging – Alzheimer’s Association consensus guidelines. The dementia research community is encouraged to make use of this readily available database as new neuropathologic changes are recognized and defined in this rapidly evolving field.

INTRODUCTION

Due to increased public support, increased funding, and advancing technologies, the field of dementia research is rapidly evolving, especially with regards to our understanding of the diversity of neuropathologic changes that underlie cognitive decline. Neuropathologic classifications are being meaningfully updated by groups of experts reflecting new consensus about terminology and diagnostic concepts. Some of the diseases where recent consensus working groups recommended new diagnostic guidelines were primary age-related tauopathy (PART) and limbic predominant age-related TDP-43 encephalopathy (LATE).^1,2 Previous definitions and criteria for widely recognized conditions are also continuing to be revised and refined, as was the case for the National Institute on Aging – Alzheimer’s Association (NIA-AA) guidelines for definition of Alzheimer’s disease neuropathologic change (ADNC).³

Along with changes in neuropathologic categorizations come the need to understand how these changes are associated with cognitive status, other neuropathologic entities, comorbid clinical conditions, biomarkers, genetics, drug exposures, and other risk factors. Among the possible approaches, researchers can review their own individual institution’s data. Likewise, researchers can undertake new epidemiologic, clinical, and neuropathologic studies, all of which require substantial time and resources.

In this review paper, we would like to raise awareness in the dementia research community of the availability of an existing, standardized, multi-institutional database that can be easily accessed and rapidly used to study newly defined and recently revised neuropathologic phenomena. This database is maintained and actively curated by the National Alzheimer’s Coordinating Center (NACC). In this article, we describe the NACC database and give several examples of its use in evaluating the associated features and cognitive implications of recently described neuropathologic changes.

NATIONAL ALZHEIMER’S COORDINATING CENTER DATABASE

NACC is the repository for data collected at past and present Alzheimer’s Disease Centers (ADCs) funded by the National Institute on Aging (NIA) and located at medical institutions across the United States. The ADCs contribute data to the two main data sets that comprise the overall NACC database. They contribute standardized clinical data to the Uniform Data Set (UDS) and neuropathological evaluations obtained at autopsy to the Neuropathology (NP) Data Set.

The NIA ADC program began in 1984 but it was not until 1997 that the ADCs began to share retrospectively abstracted “minimal” data (about 55 data elements) pooled across ADCs. These data were passed to NACC when it began in 1999. They included demographics, clinical diagnoses, and neuropathologic diagnoses if available, along with some other descriptive items. In 2002, NACC worked with the Neuropathology Core Leaders to establish a neuropathology data form based on a relatively standard examination and definitions of neuropathologic features. An ADC Clinical Task Force (John Morris MD, Chair) was established by NIA in 2002 for the purpose of creating a standardized clinical exam including neuropsychological test battery and other data collection that could be applied at all ADCs for all of their Clinical Core participants—the UDS was implemented by NACC at all ADCs in 2005. These data were collected following an annual return visit protocol. The current UDS version 3 began in 2015. It collects data on: participant (subject) demographics, family history, medications, co-existing medical conditions, physical examination (both general and neurological), several scales (e.g. Clinical Dementia Rating - CDR® Dementia Staging Instrument, Geriatric Depression Scale), clinical assessment of symptoms and clinical diagnosis, and a battery of 12 neuropsychological tests across 4 domains (attention/working memory, episodic memory, language, executive function) (Table 1).

Table 1.

Data available in the National Alzheimer’s Coordinating Center (NACC) database

Data set	Form or other detail	Type of data	Number of participants, as of Dec 2019 data freeze
Uniform Data Set (UDS)			42,022
	A1	Participant demographics
	A2	Co-participant demographics
	A3	Participant family history
	A4	Participant medications
	B1	Physical examination
	B4	CDR® Dementia Staging Instrument
	B5	Neuropsychiatric inventory questionnaire
	B6	Geriatric depression scale
	B7	Functional assessment scale
	B8	Neurological examination findings
	B9	Clinician judgement of symptoms
	C2	Neuropsychological battery scores:  • Montreal Cognitive Assessment (MoCA)  • Benson Complex Figure Copy and Recall  • Craft Story 21 Recall (immediate, delayed)  • Number Span Tests (forward, backward)  • Trail Making Tests (A, B)  • Category fluency (Animals, Vegetables)  • Multilingual Naming Test (MINT)  • Verbal fluency (F and L words)
	D1	Clinician diagnosis
	D2	Clinician-assessed medical conditions
Neuropathology (NP) Data Set		91 neuropathology parameters involving:  • Alzheimer’s disease  • Cerebrovascular disease  • Lewy body and substantia nigra pathology  • Hippocampal sclerosis  • FTLD, other tauopathies and TDP-43 pathology	6,056
Additional data	MRI	Scans	5,269
	MRI	Calculated volumes	2,068
	β-amyloid PET	Scans	455
	CSF biomarkers	β-amyloid, tau	1,211
Additional modules	FTLD module		2,756
	LBD module		104
Linkages to other databases	ADGC, NIAGADS	Genetics data	16,877

Note. Numbering of forms is not continuous due to discontinued older forms.

ADGC: Alzheimer’s Disease Genetic Consortium;

CSF: Cerebrospinal fluid;

FTLD: frontotemporal lobar degeneration;

LBD: Lewy body disease;

MRI: magnetic resonance imaging;

NIAGADS: National Institute on Aging Genetics of Alzheimer’s Disease Data Storage Site;

PET: positron emission tomography

Beginning in 1984, a limited amount of autopsy data were gathered on some participants. More comprehensive data gathering started in 2002, utilizing a formal neuropathologic protocol as part of the “NP form.” Since 2005, NP data have been linked with UDS data. The NP form (and related sampling and staining protocols) has been updated periodically. The most recent version (NP version 10) began in 2014, incorporating the recently released NIA-AA guidelines for the evaluation of AD neuropathologic change (ADNC), as well as the recently categorized FTLD neuropathologic changes. There are 85 neuropathology parameters recorded per case.

As of December 2019, 6,056 of the 42,022 UDS participants have NP data. 28,519 (68%) of UDS participants have longitudinal data (2 or more visits). Participants with NP data had a range of cognitive statuses at the last clinic visit prior to death: 661 cognitively normal, 499 mild cognitive impairment (MCI), 86 impaired (non-MCI), and 4,810 dementia.

Subsets of UDS participants have other data voluntarily shared with NACC, including magnetic resonance imaging (MRI) scans and calculated brain volumes, β-amyloid positron emission tomography (PET) scans, cerebrospinal fluid (CSF) biomarker data, and additional modules on participants with frontotemporal lobar degeneration (FTLD) and Lewy body disease (LBD) (Table 1). The two data sets (UDS and NP Data Set) together with the additional modules and additional biomarker and imaging data comprise the NACC database. There is also the ability to link UDS data to genetic data (housed at the Alzheimer’s Disease Genetic Consortium – ADGC and National Institute on Aging Genetics of Alzheimer’s Disease Data Storage Site - NIAGADS) and DNA samples (housed at National Centralized Repository for Alzheimer’s Disease and Related Dementias - NCRAD).

More detailed information on UDS and NP has been provided in other publications.^4–8 NACC data are freely available to researchers. Requests may be submitted at https://www.alz.washington.edu. To date, approximately 650 peer reviewed publications have used data from the NACC database.

EXAMPLES

Below we provide three prime examples of studies demonstrating the benefits and fitting use of the NACC database: PART, LATE, and pre-clinical AD. For these conditions, the NP Data Set was used to identify participants who had newly defined (or newly recategorized) neuropathologic change. NP data were used to identify and stratify participants, and evaluate associations using the clinical data, including co-morbid conditions, neuropsychologic test score results, neuroimaging, and other data from the UDS database.

Primary Age-Related Tauopathy (PART)

PART is defined as the presence of neurofibrillary tangles (NFT) composed of tau protein in regions comparable to early- to moderate-stage ADNC, without detected β-amyloid plaque deposition. While some controversy remains,⁹ PART is increasingly recognized as a separate neuropathological entity from ADNC. Clinicopathologic designations, such as “tangle-only dementia” and “tangle-predominant senile dementia” had been in use for several decades. However, the term PART and related definitions were established in a 2014 consensus paper.¹ Along with a critical review of the previous literature relevant to this entity, the consensus paper presented a set of diagnostic recommendations, distinguishing definite PART (NFTs and no β-amyloid) and possible PART (NFTs and sparse β-amyloid plaques). Data from NACC (UDS and NP) were used to demonstrate for the first time the associations of the new neuropathologic definitions with demographic characteristics, distribution of Braak NFT stage, cognition (in the form of Mini Mental State Examination scores), and APOE ε4 allele status.¹

After the new criteria had been proposed, there was controversy as to whether consideration of PART as a distinct entity was scientifically valid.^10,11There was an urgent need to better understand the extent to which PART caused dementia without β-amyloid and whether there are differences in the clinical presentations of and cognitive trajectories between PART and ADNC. The NACC data were ideally suited to retrospective studies addressing clinical presentations, cognitive profiles, and trajectories in PART and especially to focus on people who had PART demonstrated at autopsy but who did not have cognitive symptoms during life. This provided validation of the 2014 study’s finding of the differences of definite PART and possible PART, with participants with the latter condition having a higher percentage of people with higher Braak neocortical stage. Participants with possible PART were also more likely to express cognitive symptoms on their last UDS visit prior to death (80% having CDR greater than 0) compared with definite PART (42%). The two groups also presented differently in terms of the predictors of being symptomatic. Although both had Braak NFT stage as a predictor, within the definite PART group, independent predictors included depression and history of a stroke, whereas, for the possible PART group, independent predictors included lower education and presence of cerebral β-amyloid angiopathy.¹²

The above study used a broad measure of cognition (CDR global score). This prompted us to look at more specific neuropsychological measures. We compared the entire battery of UDS neuropsychological test scores (12 tests across 4 domains, as noted above and in Table 1) at the last visit for participants who subsequently had definite PART confirmed at autopsy to participants who had ADNC confirmed at autopsy. For both groups, participants were limited to those who had their last UDS visit within 2 years of their deaths. A consistent finding at all levels of cognitive dysfunction (CDR 0.5 to 3) was the relative sparing of semantic memory / language in definite PART participants compared to participants with ADNC. This pertained component tests of the language domain (animal, vegetable, and Boston naming tests). These results suggest that cognitive dysfunction due to PART is unlikely to be merely slow AD, but rather has its own separate profile.¹³

Thus far, PART is only a neuropathologic entity, recognized at autopsy. Given that PART is a milder disease with a different prognosis compared to AD, it would be desirable to be able to diagnose it during life, in order to be able to more accurately advise patients and families on the expected prognosis. In order to work towards that goal, we undertook two additional analyses using NACC data: a description of the diagnoses assigned to living people who subsequently had PART at autopsy; and an assessment of in vivo MRI findings of people who subsequently were found to have PART at autopsy.

For participants with definite PART at autopsy who had MCI at their last UDS visit, more than half (57%) were diagnosed as having clinical AD, which was slightly less than for participants with underlying ADNC, of whom 69% were diagnosed with clinical AD while alive. For participants with PART who had dementia at their last UDS visit, just about half (52%) were diagnosed as having clinical AD, again lower than for participants with underlying ADNC, of whom 86% were diagnosed with clinical AD while alive. This suggests that clinicians may recognize differences between the clinical symptoms associated with PART and ADNC, diagnosing clinical AD less frequently in those with definite PART. Nonetheless, clinical AD was diagnosed greater than 50% of the time in definite PART participants with MCI or dementia (Table 2). Clearly, ante-mortem clinical criteria for the diagnosis of PART and related diagnostic methods (e.g. biomarkers) need to be established.¹⁴

Table 2.

Five leading primary clinical diagnoses at last visit before death in symptomatic individuals with primary-age related tauopathy (PART) vs. Alzheimer’s disease neuropathologic change (ADNC)

Primary clinical diagnosisa	MCI diagnosis at last visit		Dementia diagnosis at last visit
	PART n=49	ADNC n=75	PART n=112	ADNC n=1,118
AD	28 (57.1%)	52 (69.3%)	58 (51.8%)	959 (85.8%)
PPA or bvFTD	2 (4.1%)	0 (0.0%)	14 (12.5%)	62 (5.6%)
Vascular brain injury/dementia	4 (8.2%)	13 (17.3%)	19 (17.0%)	25 (2.2%)
ALS	3 (6.1%)	1 (1.3%)	2 (1.8%)	1 (0.1%)
MSA	3 (6.1%)	0 (0.0%)	0 (0.0%)	0 (0.0%)

^aEach participant has only one primary diagnosis. Diagnosis listed for any category for which there were more than 5% of cases for PART for MCI or dementia. PART includes only PART-definite, defined as no neuritic plaques. ADNC defined as moderate to frequent neuritic plaques.

Data from reference¹⁴

AD: Alzheimer’s disease;

PPA: primary progressive aphasia;

bvFTD: behavioral variant frontotemporal dementia;

ALS: amyotrophic lateral sclerosis;

MSA: multiple system atrophy

MRI is one of the main diagnostic modalities used by neurologists in the clinical setting for differential diagnosis of cognitive impairment. It would be topical to understand the utility of MRI in diagnoses of individuals with eventual autopsy-confirmed PART. Hence, we took a preliminary step in investigating MRI findings in PART. We identified 26 PART cases in the NACC NP Data Set who had in vivo MRIs performed. We then studied the imaging characteristics of PART. Applying a previously validated multiregion visual atrophy scale, we found increased atrophy in the medial temporal region with increasing Braak NFT stage. In addition, anterior temporal lobe atrophy was associated with decreased semantic memory/language scores (from the UDS neuropsychology battery). Although there are still no criteria for in vivo diagnosis of PART using MRI, these findings begin to provide some understanding of the radiologic patterns observed in people who go on to have PART confirmed at autopsy.¹⁵

Limbic Predominant Age-Related TDP-43 Encephalopathy (LATE)

LATE neuropathologic change (LATE-NC) is defined “by a sterotypical TDP-43 proteinopathy in older adults, with or without coexisting hippocampal sclerosis pathology.”² TDP-43 is transactive response DNA binding protein 43 kDa. LATE-NC can co-exist with other neuropathologic entities. In 2006, abnormally phosphorylated TDP-43 was first discovered in ubiquitylated inclusions that are hallmarks of amyotrophic lateral sclerosis (ALS) and of many cases of FTLD, now known as FTLD-TDP.^16,17 There was a growing realization of the potential connections between TDP-43 proteinopathy and hippocampal sclerosis in the years after that.¹⁸ In 2014, the evaluation of TDP-43 proteinopathy was added as a standard data element in the NACC NP version 10 data set. As of 2018, there were 929 participants with available TDP-43 data. An analysis of these data described the distribution of TDP-43 in different brain regions and noted its association with comorbid hippocampal sclerosis, severe ADNC, and brain arteriolosclerosis.¹⁹

The term LATE and related definitions were established in a 2019 consensus statement by a multinational working group of subject experts.² This consensus statement extensively evaluated the existing literature on age-related TDP-43 proteinopathy. It derived consensus-based nomenclature, diagnostic criteria, and guidelines for staging, creating a hierarchical staging, that reflects a hypothetical spatiotemporal development of TDP-43 proteinopathy in the brain: first affecting amygdala (stage 1), then hippocampus (stage 2), followed by middle frontal gyrus (stage 3) and other brain areas. The overall pattern was described initially by Josephs et al²⁰ and was later found in a separate cohort by Nag et al²¹, although the specific staging schemes by Josephs et al (6 stages) and Nag et al (5 stages) were more granular. The consensus statement used NACC data to demonstrate the prevalence of LATE-NC stages with increasing age.²

Shortly after release of the consensus statement, NACC data were used to investigate implications and clinical correlates of LATE-NC. One study assessed the demographic, clinical, and neuropathologic correlates of LATE-NC. This study especially sought to evaluate potential interactions between LATE-NC and other brain pathologies. Multivariable models showed higher odds of LATE-NC with arteriosclerosis, ADNC, hippocampal sclerosis, and one (but not other) Lewy body subtypes: limbic / amygdala-predominant Lewy body disease.²²

Another study sought to identify commonalities and distinguishing features between ADNC, LATE-NC, FTLD-TDP and low-pathology controls, in terms of cognition (using the neuropsychological test scores in UDS), neuropsychiatric and motor symptoms, and primary progressive aphasia. Cognitive impairment was common to all three neuropathologies. Neuropsychiatric symptoms (e.g. agitation, psychotic symptoms) and motor disturbance were increased in severe ADNC. Primary progressive aphasia, apathy, and appetite disturbances were increased in FTLD-TDP. Cases with autopsy-proven LATE-NC tended to have some degree of disinhibition, as did FTLD-TDP cases. This study has thus provided some information that might ultimately be useful for distinguishing among syndromes caused by these neuropathologic substrates.²³

Early Stages of Alzheimer’s Disease

In 2012, a consensus group of experts sponsored by the NIA, in collaboration with the Alzheimer’s Association, released updated criteria for the neuropathologic definition and staging of ADNC.³ This coincided with and helped to facilitate increased attention to the preclinical stages of ADNC.²⁴ Classification schemes for ADNC have changed frequently over the years. Prior schemes (such as NIA-Reagan and CERAD) had included the presence of clinical symptoms along with AD neuropathologic features in order to assign a likelihood that the neuropathologic changes contributed to the clinical symptoms, thus discounting the presence of pathology in preclinical stages.^25,26 The 2012 NIA-AA guidelines dissociated the clinical syndrome of dementia of the Alzheimer type from the underlying ADNC. The new neuropathologic definitions presented an opportunity to better define and characterize persons with ADNC who had not yet developed cognitive symptoms. NACC data were used in these guidelines to demonstrate the frequency of cases based on the new proposed staging.³

Shortly after the release of the NIA-AA guidelines, and in similar fashion to the study of the asymptomatic stages of PART described above, NACC and ADC collaborators utilized these guidelines to identify a group of people in the NP Data Set who had ADNC at autopsy but who had no documented cognitive symptoms while alive. A goal was to compare these presumed presymptomatic individuals with symptomatic people with ADNC of similar severity. One problem that had to be confronted was that the NIA-AA guidelines incorporated Thal Aβ phase, which was not to be included in the NACC NP Data Set until Version 10 in 2014. In order to be able to identify a group of participants in existing NP data who had early stage ADNC, we used any detected diffuse plaques as a surrogate parameter for Thal Aβ phase of 1 or higher.²⁷

In the comparison of symptomatic vs. asymptomatic persons with underlying ADNC, as expected, degree of neuropathology, as reflected by CERAD score and Braak NFT stage, was strongly associated with expression of cognitive symptoms (CDR global score of 0.5 or higher). However, the association was not complete. There were several participants with low CERAD and Braak NFT stage who had cognitive symptoms. Likewise, there were several participants with high CERAD and Braak NFT stages who were asymptomatic. In multivariable analysis, Braak NFT stage persisted as a determinant of cognitive symptoms, along with several other features, including age, Hachinski ischemic score, APOE ε4 status, and depression. This represented one of the first uses of the NIA-AA guidelines.²⁷

The finding that APOE ε4 allele status remained associated with cognitive status even after adjusting for the extent of ADNC prompted the team to look further into the potential genetic factors influencing expression of cognitive symptoms. As with the above study, we identified a group of participants in the NP Data Set who had ADNC and who also had genotype data in the ADGC, some of whom were asymptomatic (CDR = 0) and some of whom were symptomatic (CDR > 0). ADGC provided us with the data on the alleles for the 22 genes that had been associated with late-onset AD at that point. Intriguingly, four of the genes showed an association with outcome (CDR > 0), some in the whole participant group and some only in participants with at least one APOE ε4 allele. The single-nucleotide polymorphism (SNP) mostly strongly associated with cognitive status is located in the extended MAPT locus (Table 3).²⁸

Table 3.

Summary of main findings from study on genetic profile associated with expression of cognitive symptoms in presence of AD neuropathologic change.

Gene	SNP	AOR	AOR in APOE ε4 carriers	OR in APOE ε4 non-carriers
CD2AP	rs10948363	0.73 (0.50,1.09)	0.35 (0.16,0.75)	0.99 (0.62,1.61)
ABCA7	rs4147929	1.66 (1.00,2.76)	1.25 (0.52,3.02)	1.81 (0.97,3.40)
ZCWPW1	rs1476679	1.31 (0.87,1.96)	2.98 (1.33,6.69)	1.04 (0.63,1.70)
MAPT	rs393152	2.18 (1.26,3.75)	3.73 (1.27,10.97)	1.77 (0.93,3.40)

Data show odds ratio (adjusted for age and sex) for being symptomatic (Clinical Dementia Rating global score greater than 0) for each SNP. Adjusted odds ratios shown with 95% confidence intervals. Odds ratios whose 95% confidence intervals exclude 1 are bolded.

AOR: adjusted odds ratio; SNP, single-nucleotide polymorphism.

Data from reference:²⁸

The ability to identify a cohort of participants who had ADNC, but who had not expressed cognitive symptoms also allowed us to look for subtle changes in neuropsychological tests that might not yet have been reflected in the clinical status designation (normal vs MCI vs dementia). The UDS has extensive longitudinal data related to neuropsychological test scores. For participants who have had more than one UDS visit, we are able to evaluate cognitive trajectories (or changes over time), which are more sensitive at detecting change than one-time comparisons to norms or other groups. We evaluated the differences in trajectories of the neuropsychological test scores, comparing asymptomatic (CDR = 0) participants who were eventually were shown to have ADNC at autopsy to asymptomatic participants who did not have ADNC at autopsy. Participants with ADNC had worsened decline in one domain (attention / working memory) than participants without ADNC.²⁹ This corroborated a previous body of evidence on this topic. Episodic memory is typically considered one of the first neuropsychological domains to decline in people who have symptomatic AD. However, our study, along with a few others, indicated that the situation is different among people who are beginning to decline, but not yet noticeably enough to be diagnosed as having MCI. In these people, subtle changes in attention / working memory appear to be an early cognitive marker of ADNC.^30–33

Finally, as noted above, Thal Aβ phase data were not in the NP Data Set until 2014. Hence, for the pre-2014 data, we used surrogate parameters, i.e. the presence of any diffuse plaque, as equivalent to Thal Aβ phase > 0. Now that Thal Aβ phase data are available, we have been able to evaluate the appropriateness of our retrofit method. It turned out to be highly (98.4%) accurate. Out of the 2647 people in the NACC NP 10 data set, 84.96% had agreement in positive categorization (any diffuse plaque and Thal Aβ phase of 1 or higher) and 13.37% had agreement in negative categorization (no diffuse plaques and Thal Aβ phase of 0). There was discordance only in 1.06% (who had no diffuse plaques noted, but Thal Aβ phase of 1 or higher) and 0.60% (who had diffuse plaques and Thal Aβ phase of 0).

CONCLUSIONS: LESSONS LEARNED AND FUTURE DIRECTIONS

The three above examples show the utility of the NACC database to rapidly evaluate the implications of newly identified or newly revised neuropathologic conditions as regards to comorbidities (neuropathologic changes as well as other clinical comorbidities), demographic associations, and cognitive status (Figure 1). The NACC data are available to be used as soon as definitions are solidified. In the case of PART and LATE, NACC data were critical components of the consensus statements that defined these entities.^1,2 The studies on PART and LATE involved applying new neuropathologic definitions. For ADNC, the newly revised definitions contained in the 2012 NIA-AA guidelines were applied.

Figure 1.

Example of timeline of use of National Alzheimer’s Coordinating Center (NACC) database to evaluate newly described neuropathologic (NP) conditions.

Each of the three cases described above involved somewhat different uses of the NP Data Set. The data elements needed for definition of PART (Braak NFT stage and absence of CERAD plaques) had been present since the inception of the NP Data Set. Hence, the entirety of the NP Data Set could be immediately used as soon as the definitions of PART were derived.¹ For LATE, TDP-43 had been collected optionally up until 2014, after which it became standard. During the ensuing years, NACC data helped to explore the consequences of TDP-43¹⁹ and sufficient cases had accumulated to be utilized in the consensus statement that defined LATE in 2019.²

For the study of early-stage ADNC, the NP Data Set did not contain the Thal phases needed to apply the NIA-AA guidelines for assessment of ADNC when they were released in 2012. However, it was possible to approximate the presence of Thal phase > 1 by using the variable “any diffuse plaque”. Subsequent comparison of Thal phase data and the “any diffuse plaque” variable in the NP version 10 data set revealed the accuracy of this retrofit of the data prior to 2014. Hence, one can anticipate that the NACC NP Data Set will allow similar flexibility to address new neuropathologic conditions as they are recognized and defined. In addition to the data housed at NACC, there is the possibility for researchers to identify cases of interest through NACC and then contact ADCs directly to see if there might be more detailed neuropathologic data, such as tau tangle burden, or other types of more refined data that the ADC is able to share.

The linkage of all cases in the NP Data Set to the detailed clinical data in the UDS allows in-depth exploration of demographic, clinical, and cognitive features. Especially detailed are the results of the 4 scales (e.g. CDR, Geriatric Depression Scale) and the 12 neuropsychological tests encompassing 4 cognitive domains. Moreover, these data are available for repeated (usually annual) measures over time, allowing study of trajectories. This is notable because changes over time in the neuropsychological test scores for an individual are more sensitive to underlying cognitive change than comparisons of cross sectional data to population norms or other comparison groups.^34,35

UDS and NP also link to the ADGC and NIAGADS databases for a substantial number of participants. As of December 2019, over 3,000 of NP participants have available genetics data, allowing us to include genetic profiles in the assessment of determinants of expression of cognitive symptoms.

There are growing capabilities of the NACC database that are increasingly allowing added dimensions to what can be explored for new neuropathologic conditions. In 2014, NACC started collecting MRI data, both full scans and volumetric data. These data allowed us to undertake one of the first evaluations of antemortem MRI findings in persons who were subsequently confirmed to have PART at autopsy.¹⁴ Other capabilities that were recently developed and for which data are now accumulating include β-amyloid PET scans and CSF biomarker values. On the horizon, NACC will likely be able to include quantitative digital measures of specific neuropathologist features.

The diversity of data may require a corresponding set of multidisciplinary teams for appropriate analytic approaches. The above examples involved experts from multiple disciplines, including biostatistics, epidemiology, neurology, neuropathology, neuropsychology and, as needed, genetics and radiology. Sometimes individual centers may have all of the expertise needed. In addition, NACC has a history of connecting individuals requesting the data to experts at the ADCs in order to collaborate on these types of studies, as needed.

NACC data will continue to useful for rapid evaluation of neuropathologic conditions, as they are discovered or as their criteria are revised. It is assumed that the practice of neuropathology, and the clinical study of brain aging, will continue to evolve. There are numerous other examples of this paradigm. In 2016, different consensus statements defined new neuropathologic criteria for the diagnosis of chronic traumatic encephalopathy (CTE)³⁶ and laid out suggested neuropathologic criteria for the evaluation of aging-related tau astrogliopathy (ARTAG).³⁷ Study of both conditions could be aided by use of the NACC database.

Similarly, the breadth of data in NACC allows researchers to go beyond consensus diagnoses. There is an increasing awareness in the research community that pathologies are often mixed (e.g., ADNC with some Lewy body pathologies³⁸; ADNC comorbid with vascular pathologies). These data allow researchers the opportunity to investigate pathology across a wide spectrum of disease, or in concert with other comorbidities. Finally, a dominant future direction for all dementia research is genetics. Genetics can be used to learn more about the etiology of disease, identify potential biomarkers, identify putative therapeutic targets, and help advance personalized medicine initiatives.^39,40 NACC data, together with genetic data from the ADGC, have played major parts in past efforts of studying the genetics of neuropathology and will continue to play major parts moving forward.⁴¹ These genomic data are publicly available (by qualified access), and are a valuable resource for the dementia research community.

In conclusion, the NACC data sets (NP and UDS), along with the databases to which they link (e.g. ADGC and NIAGADS), are robust, flexible, and rapidly available tools to understand the pathologic and clinical associations of newly derived neuropathologic conditions. The database is constantly being curated, updated, and improved. The database also accumulates sample sizes faster than for single centers or single studies. These are resources that are appropriate both for hypothesis testing and also for generating new hypotheses using open-ended study designs. The dementia research community is strongly encouraged to make use of this easily available database as new neuropathologic changes continue to be recognized and defined in this rapidly evolving field.