The Outcome of Patients with Amyloid-Negative Amnestic Mild Cognitive Impairment

Abstract

Background:

Patients with amnestic mild cognitive impairment (aMCI) are usually at an initial stage of Alzheimer’s disease (AD). However, some patients with aMCI do not present biomarkers of amyloid pathology characteristic of AD. The significance of amyloid-negative aMCI is not presently clear.

Objective:

To know the etiology and prognosis of amyloid-negative aMCI.

Methods:

Patients who fulfilled criteria for aMCI and were amyloid negative were selected from a large cohort of non-demented patients with cognitive complaints and were followed with clinical and neuropsychological assessments.

Results:

Few amyloid-negative aMCI had evidence of neurodegeneration at the baseline, as reflected in cerebrospinal fluid elevated tau protein levels. About half of the patients remained essentially stable for long periods of time. Others manifested a psychiatric disorder that was not apparent at baseline, namely major depression or bipolar disorder. Remarkably, about a quarter of patients developed neurodegenerative disorders other than AD, mostly frontotemporal dementia or Lewy body disease.

Conclusion:

Amyloid-negative aMCI is a heterogeneous condition. Many patients remain clinically stable, but others may later manifest psychiatric conditions or evolve to neurodegenerative disorders. Prudence is needed when communicating to the patient and family the results of biomarkers, and clinical follow-up should be advised.

Keywords

Amnestic mild cognitive impairment amyloid-beta amyloid-negative biomarkers dementia follow-up

INTRODUCTION

As a consequence of population aging, the number of people affected by neurodegenerative disorders, particularly Alzheimer’s disease (AD), is increasing dramatically worldwide, representing a major public health issue [1]. For many years, a transitional state in AD from normal cognitive aging to a full-blown dementia stage was anticipated [2]. The possibility of diagnosing consistently AD at an early phase emerged about two decades ago, when the Mayo Clinic group proposed the concept of amnestic mild cognitive impairment (aMCI), characterized by subjective memory complaints, objective memory deficit, normal general cognitive performance, and maintained activities of daily living [3]. Indeed, patients diagnosed with aMCI in a clinical setting have about 10% annual progression rate of conversion to dementia, usually AD [4]. The concept of aMCI as a surrogate for early AD, however, was not entirely satisfactory, since it was recognized that a proportion of patients with aMCI may remain cognitively and functionally stable for more than 10 years, which would be hardly compatible with a neurodegenerative condition [5].

In recent years, a major breakthrough was the possibility of diagnosing AD reliably in vivo in patients that present with aMCI. Different diagnostic criteria with slight differences were advanced, namely prodromal AD [6 –8] and mild cognitive impairment (MCI) due to AD [9], that rely on biomarkers reflecting pathological alterations of the AD continuum, namely the presence of amyloid in the brain [10], detected by measuring low amyloid Aβ_1-42 concentrations in the cerebrospinal fluid (CSF) [11], and/or identifying brain deposits of Aβ with amyloid positron emission tomography (PET) [12]. Interestingly, when applying the AD biomarkers in research and clinical settings [13], the existence of a subset of patients with aMCI who do not harbor amyloid pathology and thus do not have AD was confirmed [14].

The etiology and prognosis of aMCI patients without amyloid pathology are not presently clear. A previous study found that amyloid negative patients with aMCI do not show cognitive decline over a period of 3 years [15]. On the contrary, in a large multicentric study, as much as 24% of the amyloid negative aMCI cases progressed to dementia within 3 years [16]. In several studies, some patients with amyloid negative aMCI were proposed to be at an initial stage of a neurodegenerative disorder other than AD, like frontotemporal dementia, primary age-related tauopathy, or the Lewy body disease [17 –20]. Other patients may have masked depressive symptoms [21] or functional cognitive disorder [22] that might mimic the aMCI syndrome.

For sure, the absence of amyloid pathology is by no means a guarantee that patient with aMCI will not get worse and will not develop dementia in the future. As a consequence, the information that presently can be provided by the clinician to the individual patient and family is rather imprecise and certainly unsatisfactory. More should be known about the relevant and intriguing question of the etiology of aMCI cases that do not show AD pathology, and for this purpose a long follow-up might needed, so that to underlying clinical conditions might appear manifestly, and rates of progression might be estimated.

In the present study, we selected from a large cohort of non-demented patients with cognitive complaints those who fulfilled criteria for aMCI and were amyloid negative at the baseline and followed them up with clinical and neuropsychological assessments.

METHODS

Participants

Participants were selected from the Cognitive Complaints Cohort (CCC), established in a prospective study conducted at Faculdade de Medicina da Universidade de Lisboa, approved by the local ethics committee, conducted according to the declaration of Helsinki and requiring the participants’ informed consent [23]. The CCC aimed to investigate the cognitive stability or evolution to dementia in patients with cognitive complaints, recruiting nondemented patients with cognitive complaints who underwent a comprehensive neuropsychological evaluation, as well as clinical history, neurological examination, laboratory evaluation, and brain imaging (CT or MRI). Patients with neurological, psychiatric, or medical disorders that might induce cognitive deficits, history of alcohol or recurrent substance abuse, or with dementia were excluded. For the purpose of the present study, participants recruited from 2008 to 2018 were selected. Although patients were followed on a routine clinical basis, when preparing this work they were systematically contacted for follow-up.

Diagnostic criteria

Inclusion criteria

Diagnosis of amnestic MCI, adapted from Petersen [3].

Memory complaints present at the clinical interview.

Abnormal memory function. Performan-ces in at least two memory domain tests must fall 1.0 SD below norms for age and education, following the comprehensive criteria defined by Jak and coworkers [24].

Normal general cognitive function, determined by the Mini-Mental State Examination (MMSE) [25] within normal values for the Portuguese population [26].

No or a minimal impairment in activities of daily living, reflected in a score < 3 on the first part (items 1–8) of the Blessed Dementia Rating Scale (BDRS) [27].

Absence of brain amyloid pathology.

Exclusion criteria

The same exclusion criteria as used in the CCC (see above), that is, patients with neurological, psychiatric, or medical disorders that might induce cognitive deficits, history of alcohol or recurrent substance abuse, or with dementia were excluded.

Amyloid status

The absence of amyloid pathology was determined at baseline by measuring normal Aβ_1-42 concentrations in the CSF and/or the absence of brain deposits of Aβ with amyloid PET scan. Whenever possible, patients had both CSF biomarkers and amyloid PET performed. A high agreement between Aβ_1-42 concentrations in the CSF and amyloid PET scan findings was documented previously, supporting the strong correlation of these two measures [12].

Lumbar puncture and CSF handling followed established protocols [28]. The levels of Aβ_1–42, total tau, and hyperphosphorylated tau were mea-sured using commercially available enzyme-linked immunosorbent assays (INNOTEST® Aβ42, INNOTEST hTAU Ag, and INNOTEST PHOSPHO-TAU (181P); Innogenetics, Ghent, Belgium). The positivity was determined using locally available cut-off values.

Amyloid positron emission tomography (PET) scans used the Pittsburgh Compound B ([¹¹C]-PIB) and were performed in the same scanner (Philips PET/CT Gemini GXL), preceded by a low-dose brain computed tomography (CT) acquisition for attenuation correction (Institute of Nuclear Science Applied to Health, ICNAS, University of Coimbra). PiB-PET images were initially classified as amyloid positive or negative based on a support vector machines (SVM) local classifier, which uses the voxel wise brain grey matter standardized uptake value ratio (SUVR) and the cerebellar grey matter as reference region [29]. Final classification was confirmed by visual read from the same specialists, a nuclear medicine radiologist and a neurologist, experienced in the field.

Clinical diagnoses at follow-up

Clinical diagnoses at follow-up are based on international clinical criteria: 1) Presence of dementia according to the DSM-IV- TR [30]; 2) Alzheimer’s disease according to the Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease [31]; 3) Vascular dementia criteria of the National Institute of Neurological Disorders and Stroke (NINDS) and Association Internationale pour la Recherche et l’Enseignement en Neurosciences (AIREN) [32]; 4) Lewy body disease criteria by McKeith [33, 34]; 5) Dementia associated with Parkinson’s disease, criteria of the Movement Disorder Society [35]; 6) Frontotemporal dementia following Rascovsky [36]; 7) Primary progressive aphasia variants, criteria proposed by Gorno-Tempini [37]; 8) Major depressive disorder and bipolar disorder, according to the DSM-IV- TR [30].

Neuropsychological assessment

The baseline and follow-up comprehensive neuropsychological assessments were carried out by the same team of trained neuropsychologists, following a standard protocol and comprised the following instruments:

MMSE [25]. The MMSE is a brief screening instrument to assess global cognitive performance. The Portuguese version was applied, and normative data was > 27 for more than 11 years of education and > 22 for 11 or less years of education [26].

Battery of Lisbon for the Assessment of Dementia (BLAD) [38, 39]. The BLAD is a comprehensive neuropsychological battery that includes some tests from the Wechsler Memory Scale [40] and has been validated for the Portuguese population. This battery includes tests for the following cognitive domains: attention and executive functions (Cancellation Task, Digit Span Backward and Clock Draw); initiative (Semantic Fluency, Motor and Graphomotor initiatives); reasoning (Raven Colored Progressive Matrices and Interpretation of Proverbs); orientation (Personal, Spatial, and Temporal Orientation); calculation (Basic Written Calculation); visuo-constructional abilities (Cube Copy); language (Token Test); memory and learning (Visual Reproduction Test, Digit Span Forward, Word Recall, Logical Memory immediate and delayed recall, Verbal Paired-Associate Learning).

Trail Making Test (part A and part B) [41, 42]. This task measures sustained attention, visuomotor processing speed (part A), visuospatial working memory and cognitive flexibility (part B). Part A consists of 25 circles numbered 1–25 distributed over a sheet of paper and the patient should draw lines to connect the numbers in ascending order. In Part B there are 25 circles as well, but the circles include both numbers (1–13) and letters (A –M) and the patient has to draw lines to connect them all in an ascending pattern with the added task of alternating between the numbers and letters (i.e., 1-A-2-B-3-C, etc.).

California Verbal Learning Test (CVLT) [43, 44]. The CVLT measures verbal learning and assesses constructs such as repetition learning, serial position effects, semantic organization, intrusion, and proactive interference. The word lists (List A and List B) are made up of 16 items from 4 different categories of “shopping list” items. The trial of interest (better discriminating ability for different stages of cognitive decline) [45] considered for the present study was the total number of words from List A correctly recalled on the first 5 learning trials (CVLT 5 Trials Total Recall).

Geriatric Depression Rating Scale (GDS) –short version (15 items) [46 –48]. The GDS is a self-report instrument used specifically to identify depressive symptomatology in the elderly.

Subjective Memory Complaints Scale (SMC) [49, 50]. The SMC scale comprises 10 individual questions for the assessment of subjective memory complaints, with total scores ranging from 0 (absence of complaints) to 21 (maximal complaints score).

Blessed Dementia Rating Scale (BDRS) [51, 52]. The BDRS is a brief behavioral scale based on the interview of a close informant. This scale is composed of 22 items that address daily life activities, habits, and changes in personality. Changes in everyday activities and habits were assessed by the first part of the scale [27].

Statistical analysis

The neuropsychological assessments were standardized according to the age and education norms for the Portuguese population [26, 38], and z scores were calculated.

RESULTS

From the 79 amyloid-negative aMCI patients selected from the CCC as much as 39 were excluded for various reasons shown in Fig. 1. Demographic and clinical data of the 40 amyloid-negative aMCI patients that entered the study are reported in Table 1. The amyloid status was based on normal Aβ_1-42 concentrations in the CSF (13 patients), normal brain amyloid PET scan (9 patients), or both (18 patients). The values of CSF biomarkers were Aβ_1-42 883±224 pg/mL, total tau 277±119 pg/mL, and hyperphosphorylated tau 45±19 pg/mL (31 patients that underwent lumbar puncture).

Fig. 1

Flow-chart of patient selection for the study.

Table 1

Baseline demographic and clinical characteristics of patients with amyloid-negative aMCI

	amyloid- negative aMCI (n = 40)
Age at first assessment, y, mean (SD)	65.1 (9.7)
Formal education, y, mean (SD)	11.8 (3.8)
Gender, female/male, n	18/22
Follow-up time, y, mean (SD)	5.5 (3.3)
Time between onset of symptoms and baseline neuropsychological assessment, years, mean (SD)	2.4 (1.8)
Geriatric Depression Scale, mean (SD)	4.7 (2.7)
Subjective Memory Complaints Scale, mean (SD)	11.9 (2.6)
Blessed Dementia Rating Scale –total, mean (SD)	4.3 (1.6)
Blessed Dementia Rating Scale –1^st part, daily activities, mean (SD)	1.3 (0.7)
Mini-Mental State Examination, mean (SD)	27.6 (1.6)

The results of the baseline neuropsychological assessment are shown in Table 2. Patients were impaired (z score < –1) in measures of memory (Logical Memory), learning (CVLT) and orientation, as well as in executive functions (Trail Making Test B).

Table 2

Baseline neuropsychological performance of patients with amyloid-negative aMCI

Cognitive domain Neuropsychological Test	Amyloid-negative aMCI n = 40 z score, mean (SD)
Attention and executive functions
Cancellation Task	–0.07 (1.21)
Digit Span Backward	0.11 (1.27)
Clock Draw	0.35 (1.04)
Trail Making Test A	–0.75 (1.59)
Trail Making Test B	–1.84 (2.75)
Initiative
Semantic Fluency	–0.27(1.34)
Motor Initiative	–0.15 (1.60)
Graphomotor Initiative	0.62 (0.88)
Reasoning
Raven Colored Progressive Matrices	0.01 (1.17)
Interpretation of Proverbs	1.13 (1.39)
Orientation
Personal, Spatial and Temporal Orientation	–1.33 (2.42)
Calculation
Basic Written Calculation	0.11 (0.81)
Visuo-constructional abilities
Cube Copy	0.61 (1.11)
Language
Token Test	0.34 (0.32)
Memory and learning
Visual Reproduction	0.39 (1.78)
Digit Span Forward	0.38 (1.27)
Word Recall	–0.88 (1.37)
Logical Memory –immediate recall	–1.14 (0.98)
Logical Memory –delayed recall	–0.69 (1.08)
Verbal Paired-Associate Learning	–0.68 (1.29)
CVLT 5 Trials Total Recall	–2.55 (1.56)

Means of z scores calculated according to the equation [z = (x-mean)/SD]. z score values below 1 SD of the mean are marked in bold. CVLT, California Verbal Learning Test.

It was possible to obtain follow-up data in all but 2 patients. The global follow-up time was 5.5±3.3 years (Table 1), and 6.5±3.5 years in patients who remained stable during the study. The individual outcomes are detailed in Table 3, showing that amyloid-negative aMCI represents a rather heterogeneous group of patients. About half of the patients (#1 to #19) remained essentially stable for long periods of time. Of these, only one (#8) admitted to becoming free from memory complaints. Other patients (#20 to #24) manifested a psychiatric disorder that was not apparent at baseline, namely major depression or bipolar disorder, showing no evidence of cognitive decline. Importantly, about a quarter of the patients (#25 to #34) developed a neurodegenerative disorder other than AD, mostly frontotemporal dementia or Lewy body disease. Finally, some patients (#35 to #38) suffered from serious intercurrent medical disorders affecting cognition, as would be expected in this aged population (Table 3).

Table 3

Follow up of patients with amyloid-negative aMCI

Number	Age (y)	Gender	Education (y)	MMSE	Total tau	Follow-up time (y)	Outcome	Final diagnosis
Clinical stability
1	78	M	12	27	ND	5.3	Memory complaints, normal activities of daily life	MCI
2	64	M	16	30	N	10.0	Memory complaints, normal activities of daily life, stable NPS evaluation	MCI
3	72	F	12	29	ND	8.2	Memory complaints, normal activities of daily life, slight decline in learning tests	MCI
4	56	M	16	ND	ND	8.7	Memory complaints, normal activities of daily life, stable NPS evaluation	MCI
5	55	M	9	28	N	6.1	Improved after overcoming a stressful life situation, normal activities of daily life, slight decline in attention and memory tests	MCI
6	67	M	11	30	N	5.0	Memory complaints, normal activities of daily life, slight decline in memory tests	MCI
7	72	M	9	28	ND	3.3	Memory complaints, normal activities of daily life, stable NPS evaluation	MCI
8	64	M	17	24	ND	3.4	No memory complaints, normal activities of daily life	Normal
9	63	F	9	29	N	12.6	Memory complaints, normal activities of daily life, slight decline in attention, memory and verbal initiative	MCI
10	49	M	9	30	N	11.5	Memory complaints, normal activities of daily life, stable NPS evaluation	MCI
11	72	M	17	ND	N	11.3	Memory complaints, normal activities of daily life, difficulties caused by profound deafness	MCI
12	69	M	9	29	N	9.8	Attention complaints, normal activities of daily life	MCI
13	46	F	7	28	N	10.8	Memory complaints, normal activities of daily life, stable NPS evaluation	MCI
14	51	F	16	28	N	5.5	Memory complaints, normal activities of daily life, slight decline in attention and memory tests	MCI
15	44	F	16	30	N	5.3	Memory complaints, normal activities of daily life, stable NPS evaluation	MCI
16	64	F	6	25	N	3.3	Attention complaints, normal activities of daily life, stable NPS evaluation	MCI
17	74	F	16	28	N	2.4	Memory complaints, visual acuity deficits, normal activities of daily life	MCI
18	58	M	16	27	N	2.2	Memory complaints, normal activities of daily life, stable NPS evaluation	MCI
19	57	F	12	28	N	2.3	Memory complaints, normal activities of daily life, slight decline in attention and memory tests	MCI
Psychiatric disorder
20	64	F	4	28	N	5.4	Depressive episode, followed by psychiatrist	Major depression disorder
21	61	M	9	29	N	1.3	Episode of mania requiring hospital admission	Bipolar disorder
22	75	M	16	27	ND	4.3	Depressive episode, followed by psychiatrist	Major depression disorder
23	74	F	6	26	N	2.5	Depressive syndrome, stressful life situation, improved with antidepressant drugs, normal activities of daily life	Depressive syndrome
24	68	F	16	29	High	4.0	Depressive syndrome, stressful life situation, improved with antidepressant drugs, normal activities of daily life	Depressive syndrome
Neurodegenerative disorder
25	56	M	4	23	N	6.3	Progressive behavioral symptoms, cognitive and functional decline confirmed in the NPS evaluation	Frontotemporal dementia
26	71	F	9	28	N	3.5	Parkinsonian syndrome, NPS evaluation showed decline in memory tests	Lewy body disease
27	76	F	9	28	ND	5.7	Progressive cognitive and functional decline, confirmed in the NPS evaluation	Dementia not otherwise specified
28	82	F	4	28	N	10.5	Slow and progressive cognitive and functional decline confirmed in the NPS evaluation	Dementia not otherwise specified
29	56	F	9	ND	N	10.7	Recurrent absence seizures	Epilepsy
30	73	M	9	28	High	6.0	Parkinsonian syndrome, NPS evaluation showed mild cognitive decline, DaTscan positive	Lewy body disease
31	70	F	16	29	N	2.9	Progressive language and behavioral symptoms, marked cognitive and functional decline	Frontotemporal dementia
32	75	M	13	29	N	1.8	Parkinsonian syndrome, DaTscan positive	Lewy body disease
33	67	M	10	26	High	2.3	Parkinsonian syndrome, NPS evaluation showed slight cognitive decline	Lewy body disease
34	73	M	11	25	N	2.3	Parkinsonian syndrome, NPS evaluation showed generalized cognitive decline	Lewy body disease
Other medical disorders
35	71	F	16	25	ND	3.0	Developed metastatic breast cancer and had stroke	Stroke
36	78	M	16	30	ND	1.1	Died from heart attack	Heart attack
37	79	M	16	27	N	5.0	Prolonged hospitalization for pneumonia, septicemia, multiple organ dysfunction syndrome	Serious medical conditions
38	72	M	16	27	High	5.1	Ischemic stroke	Stroke
Lost to follow-up
39	63	M	14	27	N	NA	Lost to follow-up	NA
40	48	F	16	28	N	NA	Lost to follow-up	NA

F, female; M, male; DaTscan, single photon emission computed tomography with ioflupane; aMCI, amnestic mild cognitive impairment; MMSE, Mini-Mental State Examination; NPS evaluation, neuropsychological evaluation; N, normal; NA, not applicable; ND, not determined.

Regarding the 4 patients who had evidence of neurodegeneration at the baseline, as reflected in CSF elevated tau protein levels, one developed depressive syndrome, another was apparently cognitively stable suffering stroke a few years later, and the remaining two progressed to Lewy body disease (Table 3).

DISCUSSION

First, the majority of patients fulfilling criteria for aMCI who had biomarkers performed were amyloid positive, as would be expected from a condition designed to identify patients at early stages of AD. A second point is that, in patients with aMCI who were amyloid-negative, the review of the clinical files could often identify at the baseline a presumable cause for the memory deficits. Several patients were followed by the psychiatrist with the diagnosis of major depressive disorder, presenting concurrently substantial memory complaints. Others showed prominent behavioral symptoms suggestive of an initial phase of frontotemporal dementia, or language deficits indicating a primary progressive aphasia disorder. The patients where a presumable cause for memory decline might have been suspected at the baseline were excluded from the present study.

We observed that patients with amyloid-negative aMCI had deficits in memory, learning, and orientation tests at the baseline. Deficits in executive functions were also observed. Recent studies emphasized the presence of executive dysfunction in patients with aMCI [53], namely involving difficulties in inhibitory and interference control, cognitive control, and cognitive flexibility [54].

The main finding of the present study is that amyloid-negative aMCI represents a rather heterogeneous group of patients. As a consequence, classifying simply the patients with amyloid-negative aMCI as converters and non-converters [55] might conceal the diversity of distinct clinical entities. About half of the patients remained essentially stable, as found in previous studies [19, 56]. We now show that this stability may be observed for remarkably lengthy periods of time, more than a decade. Even though, cognitive complaints and memory deficits generally persisted. Although patients with high levels of depressive symptoms or psychiatric diagnoses were excluded, some manifested at the follow up a psychiatric disorder that was not apparent at baseline, namely major depressive disorder or bipolar disorder, showing no evidence of cognitive decline. In these cases, we may assume that the memory complaints and memory deficits observed at the baseline could be prodromal manifestations of an insidious psychiatric condition that would later become apparent. Other amyloid-negative aMCI patients developed a neurodegenerative disorder, mostly frontotemporal dementia or Lewy body disease, as reported by other authors [18 , 56]. Two patients progressed to a non-specified form of dementia.

Although it was proposed that declining amyloid-negative aMCI patients might develop AD [19, 56], this hypothesis does not seem plausible taking into account the very long preclinical phase of AD, amyloid biomarkers being present for about 20 years before symptoms appearance [57]. In other words, if the cognitive symptoms were due to AD, the biomarkers should be present at the baseline. According to the recent biological AT(N) definition of Alzheimer’s disease, amyloid-negative aMCI patients should be considered outside the AD continuum [10]. The possibility that some aMCI cases considered as amyloid-negative might show insufficient amyloid accumulation to be detected by PiB-PET or have borderline levels of CSF Aβ_1-42 might be considered. The use of CSF Aβ₄₂/Aβ₄₀ ratio was proposed as a normalization procedure and may provide a more accurate measure of the amyloid status in some patients [58]. In the present study, we would argue that the patients were truly amyloid negative, since the amyloid status was concordant between CSF measures and PiB-PET in all but two cases, that were excluded from the study. The clinical evolution of the amyloid-negative aMCI patients does not seem compatible with AD either, since the patients remained essentially stable or developed psychiatric or other neurodegenerative disorders. One might argue that the two cases that progressed to dementia not otherwise specified could have had AD to start with. This might be the case with #27, since the patient’s PET scan showed substantial PiB binding, although in an exclusively subcortical (nonspecific) topography. On the contrary, patient #28 had a completely normal value of CSF Aβ_1-42 (858 pg/mL) at the baseline. The possibility that these two cases might have Limbic Predominant Age-associated TDP-43 Encephalopathy (LATE) [59] might also be considered, but LATE is for the time being essentially a neuropathological diagnosis.

The presence of biomarkers for neurodegeneration was associated with progression to dementia in healthy people and in patients with cognitive decline [60]. A previous study reported that amyloid-negative aMCI patients with high CSF tau, as a biomarker of neuronal injury, may have a high risk of progressing to dementia [61]. On the contrary, other studies found that amyloid-negative and tau-positive aMCI patients have a low risk for progression [62, 63]. As a matter of fact, amyloid-negative and tau-positive MCI patients might be included in distinct but overlapping diagnostic categories, namely suspected non-Alzheimer’s pathophysiology (SNAP), primary age-related tauopathy (PART), or even other primary tauopathies [64]. In the present study, only few participants had abnormal CSF tau levels (both total tau and phospho-tau), and they did not show a particularly negative outcome.

The present study has limitations regarding the small number of participants, and replication of the present findings in future studies is needed. A further limitation to consider is that part of the cohort had no CSF or imaging biomarkers of neurodegeneration available. The lack of MRI data should also be recognized as a limitation. The major strengths of the present study are the long follow-up time, and the fact that only two patients were lost to follow-up. We anticipate that methodological issues, such as the specific clinical setting, the definition of aMCI, the extent of exclusion criteria, the use of CSF or PET measures to establish the amyloid status, and the selection of biomarkers of neurodegeneration might assume a critical relevance for the characterization and prognosis of amyloid-negative aMCI patients.

As practical consequences, when communicating to the patient with aMCI and the family the results of biomarkers, a negative amyloid status reflecting the absence of AD is usually acknowledged as good news [65] but must be moderated by the information that some cases may later manifest psychiatric conditions or evolve to neurodegenerative disorders. For sure, clinical follow-up should be advised.

The present study shows that it may not be possible to classify individuals based on cognitive performance at initial stages of the neurodegenerative disorder. This emphasizes the importance of continuing developing cognitive outcome measures that correlate with biomarkers of disease and neurodegeneration and that can detect changes at the MCI stage or even before. Future studies should focus on how to distinguish the different types of amyloid-negative aMCI and to provide reliable prognostic information to the individual patient. Adding advanced neuroimaging techniques, more extensive mood and personality assessments, and other CSF biomarkers like neurofilament light might be of interest. Large collaborative studies with amyloid-negative aMCI would allow the use of machine learning techniques, namely feature selection ensemble approaches, to automatically choose the best predictors of future outcome, as was already done for MCI patients without amyloid status information [66].

In conclusion, amyloid-negative aMCI is a heterogeneous condition, many patients remain clinically stable, but others may later manifest psychiatric conditions or evolve to neurodegenerative disorders, so that prudence is needed when communicating to the patient and family the results of biomarkers, and clinical follow-up should be advised.

Footnotes

ACKNOWLEDGMENTS

The authors thank Memoclínica for the facilities provided. This work was supported by a grant from Fundação para a Ciência e Tecnologia (FCT) - PTDC/MED-NEU/27946/2017.

Authors’ disclosures available online ().

References

World Health Organization (2021) Global status report on the public health response to dementia. https://www.who.int/en/news-room/fact-sheets/detail/dementia, Last updated 02 September 2021, Accessed on October 14, 2021.

Kral

(1958) Neuro-psychiatric observations in an old peoples home; studies of memory dysfunction in senescence. J Gerontol 13, 169–176.

Petersen

, Smith

, Waring

, Ivnik

, Tangalos

, Kokmen

(1999) Mild cognitive impairment: Clinical characterization and outcome. Arch Neurol 56, 303–308.

Mitchell

, Shiri-Feshki

(2009) Rate of progression of mild cognitive impairment to dementia-meta-analysis of 41 robust inception cohort studies. Acta Psychiatr Scand 119, 252–265.

Alves

, Cardoso

, Maroco

, de Mendonça

A¸

, Guerreiro

, Silva

(2018) Neuropsychological predictors of long-term (10 years) mild cognitive impairment stability. J Alzheimers Dis 62, 1703–1711.

Dubois

, Feldman

, Jacova

, Dekosky

, Barberger-Gateau

, Cummings

, Delacourte

, Galasko

, Gauthier

, Jicha

, Meguro

, O’brien

, Pasquier

, Robert

, Rossor

, Salloway

, Stern

, Visser

, Scheltens

(2007) Research criteria for the diagnosis of Alzheimer’s disease: Revising the NINCDS-ADRDA criteria. Lancet Neurol 6, 734–746.

Dubois

, Feldman

, Jacova

, Hampel

, Molinuevo

, Blennow

, DeKosky

, Gauthier

, Selkoe

, Bateman

, Cappa

, Crutch

, Engelborghs

, Frisoni

, Fox

, Galasko

, Habert

, Jicha

, Nordberg

, Pasquier

, Rabinovici

, Robert

, Rowe

, Salloway

, Sarazin

, Epelbaum

, de Souza

, Vellas

, Visser

, Schneider

, Stern

, Scheltens

, Cummings

(2014) Advancing research diagnostic criteria for Alzheimer’s disease: The IWG-2 criteria. Lancet Neurol 13, 614–629.

Dubois

, Villain

, Frisoni

, Rabinovici

, Sabbagh

, Cappa

, Bejanin

, Bombois

, Epelbaum

, Teichmann

, Habert

, Nordberg

, Blennow

, Galasko

, Stern

, Rowe

, Salloway

, Schneider

, Cummings

, Feldman

(2021) Clinical diagnosis of Alzheimer’s disease: Recommendations of the International Working Group. Lancet Neurol 20, 484–496.

Albert

, DeKosky

, Dickson

, Dubois

, Feldman

, Fox

, Gamst

, Holtzman

, Jagust

, Petersen

, Snyder

, Carrillo

, Thies

, Phelps

(2011) The diagnosis of mild cognitive impairment due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement 7, 270–279.

10.

Jack

Jr , Bennett

, Blennow

, Carrillo

, Dunn

, Haeberlein

, Holtzman

, Jagust

, Jessen

, Karlawish

, Liu

, Molinuevo

, Montine

, Phelps

, Rankin

, Rowe

, Scheltens

, Siemers

, Snyder

, Sperling

(2018) NIA-AA Research Framework: Toward a biological definition of Alzheimer’s disease. Alzheimers Dement 14, 535–562.

11.

Olsson

, Lautner

, Andreasson

, Öhrfelt

, Portelius

, Bjerke

, Hölttä

, Rosén

, Olsson

, Strobel

, Wu

, Dakin

, Petzold

, Blennow

, Zetterberg

(2016) CSF and blood biomarkers for the diagnosis of Alzheimer’s disease: A systematic review and meta-analysis. Lancet Neurol 15, 673–684.

12.

Leuzy

, Chiotis

, Hasselbalch

, Rinne

, de Mendonça

, Otto

, Lleó

, Castelo-Branco

, Santana

, Johansson

, Anderl-Straub

, von Arnim

, Beer

, Blesa

, Fortea

, Herukka

, Portelius

, Pannee

, Zetterberg

, Blennow

, Nordberg

(2016) Pittsburgh compound B imaging and cerebrospinal fluid amyloid-beta in a multicentre European memory clinic study. Brain 139, 2540–2553.

13.

Bocchetta

, Galluzzi

, Kehoe

, Aguera

, Bernabei

, Bullock

, Ceccaldi

, Dartigues

, de Mendonça

, Didic

, Eriksdotter

, Félician

, Frölich

, Gertz

, Hallikainen

, Hasselbalch

, Hausner

, Heuser

, Jessen

, Jones

, Kurz

, Lawlor

, Lleo

, Martinez-Lage

, Mecocci

, Mehrabian

, Monsch

, Nobili

, Nordberg

, Rikkert

, Orgogozo

, Pasquier

, Peters

, Salmon

, Sánchez-Castellano

, Santana

, Sarazin

, Traykov

, Tsolaki

, Visser

, Wallin

, Wilcock

, Wilkinson

, Wolf

, Yener

, Zekry

, Frisoni

(2015) The use of biomarkers for the etiologic diagnosis of MCI in Europe: An EADC survey. Alzheimers Dement 11, 195–206.

14.

Alves

, Cardoso

, Silva

, Mendes

, Maroco

, Nogueira

, Lima

, Tábuas-Pereira

, Baldeiras

, Santana

, de Mendonça

, Guerreiro

(2021) Neuropsychological profile of amyloid-positive versus amyloid-negative amnestic mild cognitive impairment. J Neuropsychol 15, 41–52.

15.

Lim

, Maruff

, Pietrzak

, Ames

, Ellis

, Harrington

, Lautenschlager

, Szoeke

, Martins

, Masters

, Villemagne

, Rowe

, for the AIBL Research Group (2014) Effect of amyloid on memory and non-memory decline from preclinical to clinical Alzheimer's disease. Brain 137(Pt 1), 221–231.

16.

Vos

, Verhey

, Frölich

, Kornhuber

, Wiltfang

, Maier

, Peters

, Rüther

, Nobili

, Morbelli

, Frisoni

, Drzezga

, Didic

, van Berckel

, Simmons

, Soininen

, Kłoszewska

, Mecocci

, Tsolaki

, Vellas

, Lovestone

, Muscio

, Herukka

, Salmon

, Bastin

, Wallin

, Nordlund

, de Mendonça

, Silva

, Santana

, Lemos

, Engelborghs

, Van der Mussele

; Alzheimer’s Disease Neuroimaging Initiative, Freund-Levi

, Wallin

ÅK

, Hampel

, van der Flier

, Scheltens

, Visser

(2015) Prevalence and prognosis of Alzheimer’s disease at the mild cognitive impairment stage. Brain 138, 1327–1338.

17.

Grimmer

, Wutz

, Drzezga

, Förster

, Förstl

, Ortner

, Perneczky

, Kurz

(2013) The usefulness of amyloid imaging in predicting the clinical outcome after two years in subjects with mild cognitive impairment. Curr Alzheimer Res 10, 82–85.

18.

, Kim

, Jung

, Lee

, Jang

, Yang

, Lee

, Vogel

, Na

, Seo

(2018) Longitudinal outcomes of amyloid positive versus negative amnestic mild cognitive impairments: A three-year longitudinal study. Sci Rep 8, 5557.

19.

Rosenberg

, Solomon

, Jelic

, Hagman

, Bogdanovic

, Kivipelto

(2019) Progression to dementia in memory clinic patients with mild cognitive impairment and normal beta-amyloid. Alzheimers Res Ther 11, 99.

20.

Teylan

, Mock

, Gauthreaux

, Chen

, Chan

, Hassenstab

, Besser

, Kukull

, Crary

(2020) Cognitive trajectory in mild cognitive impairment due to primary age-related tauopathy. Brain 143, 611–621.

21.

Bos

, Vos

, Frölich

, Kornhuber

, Wiltfang

, Maier

, Peters

, Rüther

, Engelborghs

, Niemantsverdriet

, De Roeck

, Tsolaki

, Freund-Levi

, Johannsen

, Vandenberghe

, Lleó

, Alcolea

, Frisoni

, Galluzzi

, Nobili

, Morbelli

, Drzezga

, Didic

, van Berckel

, Salmon

, Bastin

, Dauby

, Santana

, Baldeiras

, de Mendonça

, Silva

, Wallin

, Nordlund

, Coloma

, Wientzek

, Alexander

, Novak

, Gordon

; Alzheimer’s Disease Neuroimaging Initiative, Wallin

, Hampel

, Soininen

, Herukka

, Scheltens

, Verhey

, Visser

(2017) The frequency and influence of dementia risk factors in prodromal Alzheimer’s disease. Neurobiol Aging 56, 33–40.

22.

Ball

, McWhirter

, Ballard

, Bhome

, Blackburn

, Edwards

, Fleming

, Fox

, Howard

, Huntley

, Isaacs

, Larner

, Nicholson

, Pennington

, Poole

, Price

, Reuber

, Ritchie

, Rossor

, Schott

, Teodoro

, Venneri

, Stone

, Carson

(2020) Functional cognitive disorder: Dementia’s blind spot. Brain 143, 2895–2903.

23.

Maroco

, Silva

, Rodrigues

, Guerreiro

, Santana

, de Mendonça

(2011) Data mining methods in the prediction of dementia: A real-data comparison of the accuracy, sensitivity and specificity of linear discriminant analysis, logistic regression, neural networks, support vector machines, classification trees and random forests. BMC Res Notes 4, 299.

24.

Jak

, Bondi

, Delano-Wood

, Wierenga

, Corey-Bloom

, Salmon

, Delis

(2009) Quantification of five neuropsychological approaches to defining mild cognitive impairment. Am J Geriat Psychiatry 17, 368–375.

25.

Folstein

, Folstein

, McHugh

(1975) Mini-Mental State: A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 12, 189–198.

26.

Guerreiro

, Silva

, Botelho

, Leitão

, Castro-Caldas

, Garcia

(1994) Adaptação à população portuguesa da tradução do Mini Mental State Examination (MMSE). Rev Port Neurol 1, 9–10.

27.

Ribeiro

, de Mendonça

, Guerreiro

(2006) Mild cognitive impairment: Deficits in cognitive domains other than memory. Dement Geriatr Cogn Disord 21, 284–290.

28.

Teunissen

, Tumani

, Engelborghs

, Mollenhauer

(2014) Biobanking of CSF: International standardization to optimize biomarker development. Clin Biochem 47, 288–292.

29.

Oliveira

, Moreira

, de Mendonça

, Verdelho

, Xavier

, Barroca

, Rio

, Cardoso

, Cruz

, Abrunhosa

, Castelo-Branco

(2018) Can ¹¹C-PiB-PET relative delivery R1 or ¹¹C-PiB-PET perfusion replace ¹⁸F-FDG-PET in the assessment of brain neurodegeneration? J Alzheimers Dis 65, 89–97.

30.

American Psychiatric Association (2000) Diagnostic and statistical manual of mental disorders (DSM-IV), Washington, DC.

31.

McKhann

, Knopman

, Chertkow

, Hyman

, Jack

Jr , Kawas

, Klunk

, Koroshetz

, Manly

, Mayeux

, Mohs

, Morris

, Rossor

, Scheltens

, Carrillo

, Thies

, Weintraub

, Phelps

(2011) The diagnosis of dementia due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement 7, 263–269.

32.

Román

, Tatemichi

, Erkinjuntti

, Cummings

, Masdeu

, Garcia

, Amaducci

, Orgogozo

, Brun

, Hofman

, Moody

, O’Brien

, Yamaguchi

, Grafman

, Drayer

, Bennett

, Fisher

, Ogata

, Kokmen

, Bermejo

, Wolf

, Gorelick

, Bick

, Pajeau

, Bell

, DeCarli

, Culebras

, Korczyn

, Bogousslavsky

, Hartmann

, Scheinberg

(1993) Vascular dementia: Diagnostic criteria for research studies. Report of the NINDS-AIREN International Workshop. Neurology 43, 250–260.

33.

McKeith

, Boeve

, Dickson

, Halliday

, Taylor

, Weintraub

, Aarsland

, Galvin

, Attems

, Ballard

, Bayston

, Beach

, Blanc

, Bohnen

, Bonanni

, Bras

, Brundin

, Burn

, Chen-Plotkin

, Duda

, El-Agnaf

, Feldman

, Ferman

, Ffytche

, Fujishiro

, Galasko

, Goldman

, Gomperts

, Graff-Radford

, Honig

, Iranzo

, Kantarci

, Kaufer

, Kukull

, Lee

, Leverenz

, Lewis

, Lippa

, Lunde

, Masellis

, Masliah

, McLean

, Mollenhauer

, Montine

, Moreno

, Mori

, Murray

, O’Brien

, Orimo

, Postuma

, Ramaswamy

, Ross

, Salmon

, Singleton

, Taylor

, Thomas

, Tiraboschi

, Toledo

, Trojanowski

, Tsuang

, Walker

, Yamada

, Kosaka

(2017) Diagnosis and management of dementia with Lewy bodies: Fourth consensus report of the DLB Consortium. Neurology 89, 88–100.

34.

McKeith

, Ferman

, Thomas

, Blanc

, Boeve

, Fujishiro

, Kantarci

, Muscio

, O’Brien

, Postuma

, Aarsland

, Ballard

, Bonanni

, Donaghy

, Emre

, Galvin

, Galasko

, Goldman

, Gomperts

, Honig

, Ikeda

, Leverenz

, Lewis

, Marder

, Masellis

, Salmon

, Taylor

, Tsuang

, Walker

, Tiraboschi

; prodromal DLB Diagnostic Study Group (2020) Research criteria for the diagnosis of prodromal dementia with Lewy bodies. Neurology 94, 743–755.

35.

Emre

, Aarsland

, Brown

, Burn

, Duyckaerts

, Mizuno

, Broe

, Cummings

, Dickson

, Gauthier

, Goldman

, Goetz

, Korczyn

, Lees

, Levy

, Litvan

, McKeith

, Olanow

, Poewe

, Quinn

, Sampaio

, Tolosa

, Dubois

(2007) Clinical diagnostic criteria for dementia associated with Parkinson’s disease. Mov Disord 22, 1689–1707.

36.

Rascovsky

, Hodges

, Knopman

, Mendez

, Kramer

, Neuhaus

, van Swieten

, Seelaar

, Dopper

, Onyike

, Hillis

, Josephs

, Boeve

, Kertesz

, Seeley

, Rankin

, Johnson

, Gorno-Tempini

, Rosen

, Prioleau-Latham

, Lee

, Kipps

, Lillo

, Piguet

, Rohrer

, Rossor

, Warren

, Fox

, Galasko

, Salmon

, Black

, Mesulam

, Weintraub

, Dickerson

, Diehl-Schmid

, Pasquier

, Deramecourt

, Lebert

, Pijnenburg

, Chow

, Manes

, Grafman

, Cappa

, Freedman

, Grossman

, Miller

(2011) Sensitivity of revised diagnostic criteria for the behavioural variant of frontotemporal dementia. Brain 134, 2456–2477.

37.

Gorno-Tempini

, Hillis

, Weintraub

, Kertesz

, Mendez

, Cappa

, Ogar

, Rohrer

, Black

, Boeve

, Manes

, Dronkers

, Vandenberghe

, Rascovsky

, Patterson

, Miller

, Knopman

, Hodges

, Mesulam

, Grossman

(2011) Classification of primary progressive aphasia and its variants. Neurology 76, 1006–1014.

38.

Garcia

(1984) Doença de Alzheimer, problemas do diagnóstico clínico. Tese de Doutoramento. Faculdade de Medicina de Lisboa.

39.

Guerreiro

(1998) Contributo da Neuropsicologia para o Estudo das Demências. Dissertação de Doutoramento em Ciências Biomédicas. Faculdade de Medicina de Lisboa.

40.

Wechsler

(1945) Wechsler Memory Scale. Psychological Corporation, San Antonio, TX.

41.

Reitan

(1958) Validity of the Trail Making test as an indicator of organic brain damage. Percept Mot Skills 8, 271–276.

42.

Cavaco

, Gonçalves

, Pinto

, Almeida

, Gomes

, Moreira

, Fernandes

, Teixeira-Pinto

(2013) Trail Making Test: Regression-based norms for the Portuguese population. Arch Clin Neuropsychol 28, 189–198.

43.

Delis

, Kramer

, Kaplan

, Ober

(1987) California Verbal Learning Test: Adult version research edition manual. The Psychological Corporation, San Antonio, TX.

44.

Ribeiro

, Guerreiro

, de Mendonça

(2007) Verbal learning and memory deficits in Mild Cognitive Impairment. J Clin Exp Neuropsychol 29, 187–197.

45.

Greenaway

, Lacritz

, Binegar

, Weiner

, Lipton

, Munro Cullum

(2006) Patterns of verbal memory performance in mild cognitive impairment, Alzheimer disease, and normal aging. Cogn Behav Neurol 19, 79–84.

46.

Yesavage

, Brink

, Rose

, Lum

, Huang

, Adey

, Leirer

(1983) Development and validation of a geriatric depression screening scale: A preliminary report. J Psychiatr Res 17, 37–49.

47.

Sheikh

, Yeasavage

(1986) Geriatric Depression Scale (GDS): Recent evidence and development of a shorter version. In Clinical Gerontology: A guide to assessment and intervention, Brink TL, ed. The Harworth Press Inc., NY, pp. 165–173.

48.

Barreto

, Leuschner

, Santos

, Sobral

(2008) Geriatric Depression Scale (GDS). In Escalas e Testes na Demência, Mendonça A, Guerreiro M, eds. Grupo de Estudos de Envelhecimento Cerebral e Demência, 3rd edition, Lisboa, pp. 71–72.

49.

Schmand

, Jonker

, Hoojier

, Lindeboom

(1996) Subjective memory complaints may announce dementia. Neurology 46, 121–125.

50.

Ginó

, Guerreiro

, Garcia

(2008) Subjective Memory Complaints (QSM). In Escalas e Testes na Demência, de Mendonça A, Guerreiro M, eds. Grupo de Estudos de Envelhecimento Cerebral e Demência, 2nd edition, Lisbon, pp. 117–120.

51.

Blessed

, Tomlinson

, Roth

(1968) The association between quantitative measures of dementia and of senile change in the cerebral grey matter of elderly subjects. Br J Psychiatry 114, 797–811.

52.

Garcia

(2008) Blessed Dementia Rating Scale (BDRS). In Escalas e Testes na Demência, de Mendonça A, Guerreiro M, eds. Grupo de Estudos de Envelhecimento Cerebral e Demência, 3rd edition, Lisboa, pp. 105–106.

53.

Chehrehnegar

, Nejati

, Shati

, Rashedi

, Lotfi

, Adelirad

, Foroughan

(2020) Early detection of cognitive disturbances in mild cognitive impairment: A systematic review of observational studies. Psychogeriatrics 20, 212–228.

54.

Guarino

, Forte

, Giovannoli

, Casagrande

(2020) Executive functions in the elderly with mild cognitive impairment: A systematic review on motor and cognitive inhibition, conflict control and cognitive flexibility. Aging Ment Health 24, 1028–1045.

55.

Kim

, Lee

, Cheong

, Chung

, Jo

, Shim

, Hong

(2020) Elucidating the risk factors for progression from amyloid-negative amnestic mild cognitive impairment to dementia. Curr Alzheimer Res 17, 893–903.

56.

Kim

, Cheong

, Jo

, Lee

, Shim

, Kang

, Kwon

, Kim

, Lee

(2021) Early impairment in the ventral visual pathway can predict conversion to dementia in patients with amyloid-negative amnestic mild cognitive impairment. Alzheimer Dis Assoc Disord 35, 298–305.

57.

Jansen

, Ossenkoppele

, Knol

, Tijms

, Scheltens

, Verhey

, Visser

, the Amyloid Biomarker Study Group (2015) Prevalence of cerebral amyloid pathology in persons without dementia. A meta-analysis. JAMA 313, 1924–1938.

58.

Baldeiras

, Santana

, Leitão

, Gens

, Pascoal

, Tábuas-Pereira

, Beato-Coelho

, Duro

, Almeida

, Oliveira

(2018) Addition of the Aβ42/40 ratio to the cerebrospinal fluid biomarker profile increases the predictive value for underlying Alzheimer’s disease dementia in mild cognitive impairment. Alzheimers Res Ther 10, 33.

59.

Nelson

, Dickson

, Trojanowski

, Jack

, Boyle

, Arfanakis

, Rademakers

, Alafuzoff

, Attems

, Brayne

, Coyle-Gilchrist

ITS

, Chui

, Fardo

, Flanagan

, Halliday

, Hokkanen

SRK

, Hunter

, Jicha

, Katsumata

, Kawas

, Keene

, Kovacs

, Kukull

, Levey

, Makkinejad

, Montine

, Murayama

, Murray

, Nag

, Rissman

, Seeley

, Sperling

, White

3rd, Yu

, Schneider

(2019) Limbic-predominant age-related TDP-43 encephalopathy (LATE): Consensus working group report. Brain 142, 1503–1527.

60.

Jack

Jr , Knopman

, Chételat

, Dickson

, Fagan

, Frisoni

, Jagust , Mormino

, Petersen

, Sperling

, van der Flier

, Villemagne

, Visser

, Vos

(2016) Suspected non-Alzheimer disease pathophysiology-concept and controversy. Nat Rev Neurol 12, 117–124.

61.

Santana

, Baldeiras

, Santiago

, Duro

, Freitas

, Tábuas-Pereira

, Almeida

, Oliveira

(2018) Underlying biological processes in mild cognitive impairment: Amyloidosis versus neurodegeneration. J Alzheimers Dis 64(S1), S647–S657.

62.

Pascoal

, Mathotaarachchi

, Shin

, Benedet

, Mohades

, Wang

, Beaudry

, Kang

, Soucy

, Labbe

, Gauthier

, Rosa-Neto

; Alzheimer’s Disease Neuroimaging Initiative (2017) Synergistic interaction between amyloid and tau predicts the progression to dementia. Alzheimers Dement 13, 644–653.

63.

Ekman

, Ferreira

, Westman

(2018) The A/T/N biomarker scheme and patterns of brain atrophy assessed in mild cognitive impairment. Sci Rep 8, 8431.

64.

Yoon

, Guo

, Provost

, Korman

, Ward

, Landau

, Jagust

; Alzheimer’s Disease Neuroimaging Initiative (2022) Abnormal tau in amyloid PET negative individuals. Neurobiol Aging 109, 125–134.

65.

Silva

, Cardoso

, Guerreiro

, Maroco

, Mendes

, Alves

, Gerardo

, Lima

, Santana

, de Mendonça

(2020) Neuropsychological contribution to predict conversion to dementia in patients with mild cognitive impairment due to Alzheimer’s disease. J Alzheimers Dis 74, 785–796.

66.

Pereira

, Ferreira

, Cardoso

, Silva

, de Mendonça

, Guerreiro

, Madeira

; Alzheimer’s Disease Neuroimaging Initiative (2018) Neuropsychological predictors of conversion from mild cognitive impairment to Alzheimer’s disease: A feature selection ensemble combining stability and predictability. BMC Med Inform Decis Mak 18, 137.