Dementia: Biomarkers for Differential Diagnosis and Alzheimer's Disease Assessment
Dementia: Biomarkers for Differential Diagnosis and Alzheimer's Disease Assessment
This Clinical Focus describes the role that laboratory testing can play in diagnosing causes of mild cognitive impairment, dementia, and dementia-like symptoms.
Clinical Focus
Dementia
Biomarkers for Differential Diagnosis and Alzheimer's Disease Assessment
Clinical background [return to contents]
Dementia is becoming an increasing public health and economic burden for the United States as the population ages.1 Based on current incidence rates, the number of adults who will develop dementia each year is projected to approach about 1 million in 2060 compared with just over half that number in 2020.1 Women are at higher risk than men, and Black adults are at higher risk than White adults.1
Mitigation of some of the actionable risk factors for dementia may attenuate these projections. Dementia incidence in the United States is actually declining, possibly due to reduction of population-attributable risk factors over time, including higher education attainment and less smoking.2 Prevalence, in terms of the percentage of people with dementia for any given age group, appears to be similarly decreasing.3 Compared to preceding generations, younger cohorts have improved access to medication to control other dementia risk factors, which include high low-density lipoprotein levels, depression, and hypertension.3 Unfortunately, diabetes and obesity are dementia risk factors that continue to increase in the US population that may have dampened declines in dementia in the past and will continue to in the future.3
Dementia is a syndrome with a collection of symptoms that can be grouped into different etiologies, the most common of which is Alzheimer’s disease (AD). Some conditions have dementia-like symptoms, but are treatable and reversible; thus, identifying the cause of dementia is crucial for providing appropriate patient care.4
This Clinical Focus describes the role that laboratory testing can play in diagnosing mild cognitive impairment (MCI), dementia, and dementia-like symptoms caused by AD (vs other causes), excluding neuroimmune causes. (See Quest Diagnostics: Results for Recombx Progressive Dementia for testing for autoimmune rapidly progressing dementia.) Once a diagnosis is made, laboratory testing also plays a role in assessing prognosis and drug and clinical trial eligibility. This information is not intended as medical advice. Test selection and interpretation, diagnosis, and patient management decisions should be based on the physician’s education, clinical expertise, and assessment of the patient.
Dementia causes
AD causes 60% to 80% of dementia cases; according to the Alzheimer’s Association, an estimated 6.9 million people currently have AD, and the number is expected to rise to nearly 14 million by 2060.4 Other causes of dementia include, but are not limited to,4
- Cerebrovascular disease (5%-10% of cases)
- Lewy body disease (LBD, 5%)
- Parkinson disease (PD, 4%)
- Frontotemporal degeneration (FTD, 3% ≥65 years; 10% <65 years)
- Hippocampal sclerosis (HS, <2%)
Mixed pathologies cause >50% of dementia cases and are common in patients ≥85 years (eg, HS prevalence, which increases to 3%-13% as a mixed etiology).4 Although progress is being made in slowing disease progression with the approval and use of the first disease-modifying therapies in AD, most of these dementias are irreversible.
Causes of other non-AD dementias include Huntington disease, HIV infection, traumatic brain injury, substance use disorder, prion disease, and stroke.5 Neurocognitive symptoms may emerge after disease onset in most of these conditions as well as in PD.6 In contrast, cognitive and behavioral symptoms are the first manifestation of the disease in AD, cerebrovascular disease, LBD, and FTD.
Some conditions can cause dementia-like symptoms but are not considered dementia (See “Non-AD dementia and dementia-like symptoms” section below).4 These include depression, sleep apnea, delirium (eg, caused by drug side effects, substance intoxication or withdrawal), infection (eg, Lyme disease, syphilis), brain blood clots or tumors, thyroid disease, head injury, or certain vitamin deficiencies.4,7-10 Importantly, dementia-like symptoms may often be reversed with treatment once these causes are identified.
Dementia diagnosis
Dementia is diagnosed based on evidence of significant cognitive decline reported by the patient, an individual close to the patient, or their clinician, preferably documented through objective quantifiable clinical assessment.5,6 This decline is relative to the patient’s previous abilities in complex attention, executive function, learning and memory, or perceptual-motor or social cognition. For a diagnosis, these cognitive impairments must interfere with the patient’s independence in everyday activities, such that they minimally require assistance (eg, with paying bills and managing medications). Additionally, impairments cannot be attributed to delirium or other mental disorder (eg, major depressive disorder or schizophrenia).
Dementia is also defined as “a major neurocognitive disorder” by the Diagnostic and Statistical Manual of Mental Disorders DSM-5-TR.™5 The DSM-5-TR definition differs from the previous DSM-IV definition in that impairments in learning and memory are not necessary for diagnosis and that it is more inclusive for younger symptomatic patients.6
Mild cognitive impairment (MCI) diagnosis
DSM-5-TR was also revised to define “a mild neurocognitive disorder” with a very similar definition to “a major neurocognitive disorder” but with cognitive declines being qualitatively “modest.”5 DSM-5-TR defines these cognitive declines as not interfering in everyday activities (although more effort or accommodation is required) and being quantitively less (eg, 1-2 standard deviations [SD] below normative means for standardized cognitive tests vs >2 SD for dementia).5,6
Despite the DSM-5-TR definitions, the terms “dementia” and “MCI” are favored in the literature. Knowing whether a person with a mild neurocognitive disorder/MCI is at risk for developing AD can help patients and their families to better prepare for future care needs11 and enable clinical trial eligibility. Ruling out AD can prompt investigation of non-AD causes of MCI or dementia.7-9,11
Clinical trials for AD therapeutics have used various criteria to identify eligible patients with MCI.6,12-14 Bondi et al proposed neuropsychological criteria that (1) defined impairment as 1 SD below normative means to capture more individuals with suspected MCI, (2) required 2 impaired scores for a cognitive test to support a reliable observation, and (3) incorporated activities of daily living scores.15 The last criterion has been incorporated into the Clinical Dementia Rating (CDR® ) sum of boxes score, which is commonly used as a primary endpoint in many clinical trials.16 In head-to-head comparisons with other MCI criteria, a higher percentage of study participants who fulfilled the Bondi criteria progressed to dementia.15,17
Importantly, the Bondi criteria were also supported by significant associations with cerebrospinal fluid (CSF) AD biomarkers including beta-amyloid (1-42) (Aβ42), total tau, and hyperphosphorylated tau (see “CSF–based biomarkers” Section below),15 indicating that they may be better suited to identifying MCI–AD.
Given that different phenotypic presentations of AD are well known, biomarkers are important in diagnosis and monitoring, even in the prodromal stages of MCI-AD.18 Accordingly, the Alzheimer’s Association Workgroup revised the definition of AD from one based on clinical presentation to “a biological process that begins with the appearance of AD neuropathologic change.”18
Blood-based biomarkers
Compared with CSF and imaging biomarkers, blood-based biomarkers have emerging roles as less invasive and less expensive methods for characterizing MCI as a prodromal state of AD (Table 1),18-34 but they have been challenging to incorporate into clinical practice until recent years. Blood is a more complex matrix, and biomarker levels are much lower than in CSF.35 Fortunately, ultrasensitive methods have been developed that better quantify the blood-based biomarkers.21
Table 1. Select AD Biomarkers, Clinical Uses, Classification, and Test Codes [return to contents]
| Biomarker | Current clinical use(s) in AD | Core classification18,a | Test codes (see Table 2) | ||||
| Risk and/or diagnosis | Prognosis | Progression | Therapy selection | Monitoring therapy | |||
| Blood-based biomarkers | |||||||
| Aβ4219-21,b | • | 1 | 11786c | ||||
| 14258c | |||||||
| p-Tau21722-26 | • | • | • | 1 | 13825 | ||
| 14258 | |||||||
| p-Tau18127 | • | • | • | 1 | 13690 | ||
| NfL28,29 | • | • | Nonspecific | 13979 | |||
| GFAP27,30 | • | • | • | Nonspecific | 14319 | ||
| APOE4 | • | • | • | NA, genericd | 10642 | ||
| 12563 | |||||||
| CSF biomarkers | |||||||
| Aβ4218,31,32,b | • | • | 1 | 94627c | |||
| 94628c | |||||||
| p-Tau18 | • | 1 | 92433c | ||||
| Aβ4218 | • | 1 | 92433c | ||||
| APOE433,34 | • | • | • | NA, genericd | 94626 | ||
| 94628 | |||||||
| Aβ42/40, beta-amyloid (1-42)/beta-amyloid (1-40); AD, Alzheimer's disease; APOE4, APOE ε4 allele; CSF, cerebrospinal fluid; GFAP, glial fibrillary acidic protein; NA, not applicable; NfL, neurofilament light chain; p-tau, tau protein phosphorylated at amino acid residue 217 (or 181). | |
| a | Per Alzheimer's Association Workgroup,18 Core 1 biomarkers and hybrid ratios are sufficient for early detection of amyloid pathology and tau hyperphosphorylation in AD; nonspecific biomarkers are important in AD pathology but are not specific to AD. |
| b | Measuring Aβ42/40 provides greater assessment accuracy than measuring Aβ42 alone because it controls for the natural variance of β-amyloid production between patients.19 |
| c | Measured in a hybrid ratio of biomarkers.18 |
| d | Genotype can be determined from any generic matrix. |
A consensus statement provided by academicians and patient advocacy, pharmaceutical, diagnostic, and other private industry professionals (the Global CEO Initiative) has suggested acceptable performance characteristics for blood-based tests that assess amyloid pathology.36 Different thresholds for performance supporting clinical uses are proposed:
- For triaging followed by confirmation using positron emission tomography (PET) or CSF (depending on availability)
- Sensitivity ≥90%, specificity ≥85% (primary care)
- Sensitivity ≥90%, specificity ≥75% (secondary care)
- For confirmation without the need for follow-up testing (patient history and clinical and cognitive testing are still needed)
- Sensitivity and specificity ≥90%
According to the consensus statement, these thresholds should only be interpreted in clinical context including the predictive ability of the test for the population examined, which in turn depends upon the prevalence of amyloid pathology of the population being examined.36 For example, in a primary care setting, prevalence is likely to be closer to 20%,37 whereas in secondary care, it is likely to be higher (eg, 50%-80%), and follow-up is likely better supported by PET and CSF testing capabilites.36
The prevalence in combination with the sensitivity and specificity of the test determines the positive predictive value (PPV) and the negative predictive value (NPV). High PPV can be used to help “rule in,” and high NPV can be used to help “rule out,” a diagnosis based on a test result. For example, in a population with a 50% prevalence of PET positivity36
- For a confirmatory test, PPV and NPV should both be approximately 90%
- For a high-specificity triaging test, the PPV should be 86% and NPV should be 89%
- For a low-specificity triaging test, the PPV should be 78% and NPV should be 88%
To confirm or rule out amyloid pathology, these performance metrics can be achieved in 2 ways36:
- A single static threshold for the biomarker (ie, cutpoint value, such as a ratio or concentration, above or below which the required sensitivity and specificity is attained)
- A 2-value, dynamic high-low threshold approach (the lower cutpoint is set to achieve the desired sensitivity and upper cutpoint is set to achieve the desired specificity; ideally, this approach requires no more than 15% to 20% of patients obtaining an intermediate/indeterminate result with values between the high-low thresholds)
Revised criteria for diagnosis and staging of AD provided by the Alzheimer’s Association Workgroup18 cite the consensus statement in evaluating plasma assays. "Core 1" biomarkers are those that have sufficient performance to be used for early AD detection of amyloid pathology and tau hyperphosphorylation. Abnormal results for a Core 1 biomarker can be considered equivalent to CSF assays in detecting abnormality in PET in the intended use population (MCI and AD). Hybrid ratios of biomarkers can be interpreted similarly but represent the associated assay rather than the single biomarker.18
The Workgroup also provides 2 other categories of biomarkers. These include “Core 2” biomarkers, which can be used for evaluating later stages of the disease and providing prognostic information in AD assessment, but that are not stand-alone tests for AD diagnosis.18 When abnormal, Core 2 biomarkers, which currently include selected tau protein fragments, help assess the contribution of AD to patient symptoms. (These are not further discussed in this Clinical Focus.) The third category includes nonspecific biomarkers that are important in AD pathology but are not specific to AD (Table 1).
CSF–based biomarkers [H2]
CSF–based testing is considered a benchmark against which blood-based biomarker testing can be compared.18 Concentrations of biomarkers are much higher in CSF than in blood, and results correlate well with PET imaging analysis for Aβ.31,32 CSF biomarkers also provide cutpoints that better separate PET-positive vs PET-negative individuals and tend to be more robust, as assay imprecision and bias affect test results and patient classification to a lesser extent.32 CSF Aβ42, p-tau217, p-tau181, and p-tau231 are considered as Core 1 biomarkers for Aβ pathology by the Workgroup (Table 1).
Individuals suitable for testing [return to contents]
- Adults exhibiting signs and symptoms of MCI and dementia (per DSM-5-TR definitions of minor and major neurocognitive disorders)
Test availability [return to contents]
Quest Diagnostics offers tests and panels to help diagnose the cause(s) of MCI, dementia, and dementia-like symptoms (Table 2). For AD assessment, Quest offers tests employing liquid chromatography-tandem mass spectrometry (LC-MS/MS), immunoassays, or molecular methodology for various biomarkers and specimen types. Blood-based tests include Aβ42/40, p-tau217, and APOE4 offered singularly and in combination, as well as other tests for AD assessment. Where applicable, we provide performance characteristics of these tests in the context of the Global CEO Initiative statement as described below. CSF–based tests include single tests and combinations of biomarkers for AD risk assessment.
Table 2. Dementia Tests and Panels [return to contents]
| Test code | Test or panela name | Method | Clinical use |
AD-dementia Blood-based biomarkers |
|||
14258 |
AD-Detect™ ABeta 42/40 and p-tau217 Evaluation, Plasma Includes plasma Aβ42/40 ratio and p-tau217 and calculated probabilities for PET positivity. |
|
|
10642 |
ADmark® APOE Genotype Analysis and Interpretation (Symptomatic)b Includes detection of APOE2, E3, and E4 alleles. |
|
|
14319 |
Glial Fibrillary Acidic Protein (GFAP), Plasma |
|
|
13979 |
Neurofilament Light Chain (NfL), Plasmac |
|
|
12563 |
Quest AD-Detect® Apolipoprotein E (ApoE) Isoform, Plasmac |
|
|
11786 |
Quest AD-Detect® Beta-Amyloid 42/40 Ratio, Plasmac |
|
|
13690 |
Quest AD-Detect® Phosphorylated tau181 (p-tau181), Plasmac |
|
|
13825 |
Quest AD-Detect® Phosphorylated tau217(p-tau217), Plasmac |
|
|
| CSF–based biomarkers | |||
92433 |
ADmark® Phospho-Tau/Total-Tau/A Beta42, Analysis and Interp, CSF(Symptomatic)b |
|
|
94626 |
Apolipoprotein E (APOE) Isoform, CSFc |
|
|
94628 |
Beta-Amyloid 42/40 Ratio and Apolipoprotein E (APOE) Isoform Panel, CSFc Includes beta-amyloid 42/40 ratio, ApoE isoform, and total ApoE. |
|
|
94627 |
Beta-Amyloid 42/40 Ratio, CSFc |
|
|
Non-AD dementia |
|||
37989 |
14-3-3 Protein, CSF (Prion Disease)d |
|
|
91431 |
HIV-1/2 Antigen and Antibodies, Fourth Generation, with Reflexe Includes HIV-1/2 antigen and antibody with reflex to HIV-1/2 antibody differentiation; if differentiation test is indeterminate or negative, reflex to HIV-1 RNA. |
|
|
5042 |
Vitamin B1 (Thiamine), Blood, LC/MS/MS |
|
|
Dementia-like symptoms Non-infectious |
|||
34541 |
Dementia Panel, Secondary Causes Includes CBC (6399, including differential and platelets), comprehensive metabolic panel (including albumin [223], albumin/globulin ratio [calculated], alkaline phosphatase [234], ALT [823], AST [822], BUN/creatinine ratio [296], calcium [303], carbon dioxide [310], chloride [330], globulin [calculated], glucose [483], potassium [733], serum creatinine [375] with eGFR [calculated], sodium [836], total bilirubin [287], and total protein [754]), folate (466), TSH (899), and vitamin B12 (927). |
|
|
| Infectious | |||
4553 |
Culture, Fungus, other than Hair, Skin, Blood, with Fluorescent KOH |
|
|
30429 |
Cryptococcus Antibody |
|
|
34164 |
Cysticercus Antibody (IgG), ELISA, CSF |
|
|
34173 |
Cysticercus Antibody (IgG), ELISA, Serum |
||
6732 |
Cytomegalovirus Antibodies (IgG, IgM) |
|
|
8542 |
Herpes Simplex Virus 1/2 (IgG) Type Antibody, CSF |
|
|
34194 |
Lyme Disease Antibody Index for CNS Infection |
|
|
36126 |
RPR (Diagnosis) With Reflex to Titer and Treponema pallidum Antibody, IAe Includes RPR screen with reflex to titer and fluorescent treponemal antibody. |
|
|
10485 |
Toxoplasma gondii (IgG, IgM), ELISA, CSF |
|
|
| AD, Alzheimer's disease; CLIA, chemiluminescence IA; CNS, central nervous system; ECLIA, electrochemiluminescence IA; ELISA, enzyme-linked immunosorbent immunoassay; GFAP, glial fibrillary acidic protein; IA, immunoassay; LC-MS/MS, liquid chromatography-tandem mass spectrometry; MCI, mild cognitive impairment; PET, positron emission tomography; RFLP, restriction fragment length polymorphism. | |
| a | Panel components may be ordered separately. |
| b | This test was developed and its analytical performance characteristics have been determined by Athena Diagnostics. It has not been cleared or approved by FDA. This assay has been validated pursuant to the CLIA regulations and is used for clinical purposes. |
| c | This test was developed and its analytical performance characteristics have been determined by Quest Diagnostics. It has not been cleared or approved by the US Food and Drug Administration. This assay has been validated pursuant to the CLIA regulations and is used for clinical purposes. |
| d | These tests were developed and their performance characteristics determined by the National Prion Disease Pathology Surveillance Center (NPDPSC) and have not been cleared or approved by the FDA. These assays should be used in conjunction with other clinical, pathological, and laboratory findings. |
| e | Reflex testing performed at additional charge with an additional CPT® code. |
Test selection and interpretation [return to contents]
Blood-based tests
AD-Detect panels
AD-Detect™ ABeta 42/40 and p-tau217 Evaluation, Plasma (test code 14258) panel combines results for Aβ42/40 and p-tau217 into a model that generates a likelihood score for PET positivity.38 The model achieves the performance characteristics detailed by the Global CEO Initiative statement for a confirmatory Core 1 diagnostic test for Aβ pathology.36 The model was optimized by using 2 cutpoints, 1 for high and 1 for low risk of PET positivity, evaluated at ≥90% specificity and sensitivity.
The model was developed based on data from an ethnically diverse (54% Hispanic) population of 215 participants from a memory clinic (1Florida AD Research Center [ADRC]) with MCI or AD and a moderate prevalence of PET-positivity.38 Importantly, PET-positive and PET-negative patients were age-, sex-, ethnicity-, and years-of-education matched in contrast to recent studies.39,40
The model achieved an area under the receiver operating characteristic curve (AUC-ROC) of 0.929 with dual cutpoints at ≥90% sensitivity and specificity providing the following: high cutpoint, 87% PPV; low cutpoint, 91% NPV; 83% accuracy (both cutpoints) at the 46% prevalence of PET-positivity in the intended use population (MCI/AD). The dual cutpoint results in most patients receiving a “high” or “low” likelihood score for PET positivity with relatively few having an “indeterminate” result (15% in the ADRC cohort) within the recommended test specifications for ≤20% of patients obtaining an intermediate/indeterminate result.36
The model was further improved by adding APOE4 allele count, which has similar performance to the 2-marker model but with slightly higher accuracy and fewer indeterminate results (10% vs 15%, 7% in >4,000 patient specimens submitted for the 3 component tests).38 Quest will make a 3-marker model that includes APOE4 allele count available in an upcoming update; the test would be a confirmatory test for amyloid pathology without the need for follow-up testing (patient history and clinical and cognitive testing are still needed).36
Beta-amyloid 42/40 ratio
Quest AD-Detect® , Beta-Amyloid 42/40 Ratio, Plasma test (test code 11786) is an LC-MS/MS assay that helps initially assess whether AD pathology is present in the context of dementia. Aβ42 is a Core 1 biomarker in AD assessment and Aβ42/40 is considered a hybrid ratio.18 Measuring Aβ42/40 provides greater assessment accuracy than measuring Aβ42 alone because it controls for the natural variance of β-amyloid production between patients.19
LC-MS/MS is a preferred method for measuring Aβ42/40. A cross-sectional study assessed the diagnostic accuracy of 8 ultrasensitive Aβ42/40 plasma methods (4 immunoassays and 4 MS assays) among 286 individuals. This study included 104 with and 182 without MCI with presence/absence Aβ pathology previously determined using CSF Aβ42/40 by MS.21 Of these assays, an LC-MS/MS analysis-based assay demonstrated higher accuracy (AUC-ROC ≥0.84) than other assays that were standardized for high throughput (AUC-ROCs ranging from 0.60 to 0.80; P<.05).21
The Quest test achieves 91% sensitivity, 76% specificity at a single cutpoint of Aβ42/40=0.160.41 The test was developed using LC-MS/MS data for 250 specimens with associated data for amyloid PET imaging, diagnosis, and demographics. The risk for having AD pathology was projected onto the test results for 6,192 consecutive clinical specimens submitted for Aβ42/40 testing.41
High diagnostic sensitivity and negative predictive value (NPV) for Aβ-PET positivity were observed at a prevalence of 40% of PET positivity in the cohort, consistent with the clinical performance of other plasma LC-MS/MS assays, but with greater separation between Aβ42/40 values for individuals with positive vs negative Aβ-PET results. At the study prevalence of Aβ-PET positivity, a cutpoint (0.170) was identified with 99% NPV, which could help predict that AD is likely not the cause of a patient’s cognitive impairment and help reduce PET evaluations by about 40%.41
p-Tau181 and p-tau217
The Quest AD-Detect® Phosphorylated tau181 (p-tau181), Plasma (test code 13690) and Quest AD-Detect® Phosphorylated tau217 (p-tau217), Plasma (test code 13825) tests help assess whether MCI or dementia is caused by AD. Plasma levels of p-tau181 and p-tau217 are elevated in the MCI and dementia stages of AD and are associated with the presence of Aβ and tau pathology.22-26 Both are considered Core 1 biomarkers in AD assessment.18
Of the 2 biomarkers, p-tau181 has been more extensively studied with a meta-analysis of 18 studies demonstrating that measured blood levels reliably differentiate between Aβ-PET–positive vs Aβ-PET–negative individuals.42 However, plasma p-tau217 has a particularly strong association with Aβ pathology, which increases early in AD progression43 and typically outperforms p-tau181 in head-to-head comparisons according to the Alzheimer's Association Workgroup.18 Increased baseline plasma p-tau217 can predict progression of cognitive impairment, and longitudinal increases correlate with declining cognition.44,45 Increased plasma p-tau181 levels can also predict clinical progression to more severe cognitive impairment.46,47
Plasma levels of both p-tau181 and p-tau217 are dynamic and highly correlative biomarkers of AD pathology as assessed by PET and CSF.23,46-48 Levels increase longitudinally in Aβ-positive, but not Aβ-negative, individuals.24,44 Levels also increase across advancing stages of tau pathology.24,26 The markers can differentiate AD from many other neurodegenerative diseases, such as FTD, progressive supranuclear palsy, vascular dementia, and PD.22,25,46,48 In addition, both plasma p-tau-217 and p-tau181 are leading markers in monitoring AD pathology in response to anti-amyloid therapies targeting protofibrils (lecanemab), insoluble fibrils (donanemab), and plaques (aducanumab).27
The following results are inconsistent with MCI and dementia caused by AD, and further investigation of other causes of cognitive symptoms may be considered:
- Normal plasma p-tau217 levels (≤0.15 pg/mL)
- Normal plasma p-tau181 levels (≤0.86 pg/mL if age <55 years; ≤1.07 pg/mL if age ≥55 years)
The following results are consistent with MCI and dementia caused by AD, and follow-up assessment using PET or CSF analysis should be considered to confirm the presence of AD pathology:
- Higher than normal plasma p-tau217 levels (>0.15 pg/mL)
- Higher than normal plasma p-tau181 levels (>0.86 pg/mL if age <55 years; >1.07 pg/mL if age ≥55 years)
Importantly, both plasma p-tau181 and p-tau217 can also increase in those with chronic kidney disease or a history of myocardial infarction or stroke.23 Plasma p-tau181 can also be increased in patients with amyotrophic lateral sclerosis (ALS) and is associated with lower motor neuron disease.49 Consequently, the results of these assays should be considered in conjunction with the findings from medical and family history, nutritional deficiency biomarkers (See "Dementia-like symptoms" Section below), neuroimaging, and physical, neurological, and neuropsychological examination.
Neurofilament light chain (NfL)
The Neurofilament Light Chain (NfL), Plasma test (test code 13979) provides an accessible, minimally invasive option for assessing neurodegeneration or neuronal injury; NfL is considered a biomarker of nonspecific processes resulting from AD pathophysiology.18
NfL is a structural protein expressed exclusively in neurons. Upon neuronal degeneration or injury, NfL is released into extracellular space, resulting in increased concentrations in CSF and peripheral blood.50 Though NfL levels are lower in blood than in CSF, advancements in assay development have enabled the use of blood-based NfL as a more accessible biomarker of neuronal injury and/or neurodegeneration.50 NfL is generally useful for informing prognosis and monitoring disease progression, most commonly for multiple sclerosis but also for neurodegeneration in AD. Because elevated levels are associated with AD progression, NfL has emerged as a candidate biomarker in the biological definition of AD.28,29
Although lacking specificity for any given disease, NfL measurements can be useful for certain differential diagnoses. Levels are elevated in FTD vs psychiatric disorders, ALS vs motor neuron disease mimics, and atypical parkinsonian syndromes vs PD.50-54
Interpretation of plasma NfL test results depends on the clinical context:
- Normal plasma NfL levels are generally consistent with MCI or dementia not being caused by neuronal injury or neurodegeneration.
- Higher than normal NfL levels are consistent with MCI or dementia being caused by clinically relevant neuronal injury or neurodegeneration. In patients with a known neurologic condition, elevated NfL or increased levels from an established, patient-specific baseline may indicate poorer prognosis and/or disease progression.50 In patients with diagnostic uncertainty, elevated NfL may support differential diagnosis of a suspected neurologic condition.50
NfL levels can be influenced by many factors, including age, body mass index, kidney disease, and a history of diabetes or cardiovascular conditions.50 The results of this assay should be considered in conjunction with the findings from medical and family history, neuroimaging, and physical, neurological, and neuropsychological examination.
Glial fibrillary acidic protein (GFAP)
The Glial Fibrillary Acidic Protein (GFAP), Plasma test (test code 14319) is a tool for assessing AD progression and anti-amyloid therapy treatment response; GFAP is considered another biomarker of nonspecific processes involved in AD pathophysiology.18
GFAP is an intermediate filament protein found only in astrocytes and is a biomarker of neuronal injury (reactive astrogliosis) when released from the central nervous system.27,55 In contrast to most other AD biomarkers, GFAP performs better in plasma than CSF for distinguishing Aβ-PET–positive vs Aβ-PET–negative individuals.27 Meta-analysis of over 2,400 patients on the AD continuum (from cognitively unimpaired to MCI to AD) found that plasma GFAP concentrations increased with disease progression.30 Furthermore, GFAP has been found to be a consistent biomarker in clinical trials for anti-amyloid therapies; compared with baseline, treated patients had a 10% to 20% decrease in plasma GFAP levels compared with a 10% to 15% increase in patients receiving a placebo.27 The placebo-drug difference and effect size was similar to those observed for clinical trials that used plasma p-tau181.27
Interpretation of plasma GFAP test results depends on the clinical context:
- Normal plasma GFAP levels indicate that MCI or dementia does not involve active astrogliosis.
- Higher than normal plasma GFAP levels indicate that MCI or dementia involves active astrogliosis.
GFAP may also be elevated in mild traumatic brain injury, stroke, multiple sclerosis, neuromyelitis optica spectrum disorder, cardiovascular disease (cardiac arrest and atrial fibrillation), infection (West Nile and SARS-CoV-2), and sepsis-related encephalopathy.55 The results of this assay should be considered in conjunction with the findings from medical and family history, neuroimaging, and physical, neurological, and neuropsychological examination.
APOE genotypes and apolipoprotein E proteotypes
The Quest AD-Detect® Apolipoprotein E (ApoE) Isoform, Plasma test (test code 12563) is a tool for AD risk assessment. ApoE phenotypes are identified based on the detection of proteoform-specific peptide(s). Results of phenotyping are 100% concordant with APOE genotyping results.56
ApoE is the primary brain apolipoprotein and the most studied blood biomarker for AD. ApoE has 3 common proteoforms, E2, E3, and E4, which are encoded by the APOE gene ε2, ε3, or ε4 alleles, respectively. The 6 combinations of APOE alleles are ε2/ε2, ε2/ε3, ε2/ε4, ε3/ε3, ε3/ε4, and ε4/ε4; frequencies vary among racial and ethnic groups.4
Specific APOE alleles are associated with increased AD risk: the presence of an ε4 allele confers higher risk of AD compared with ε3 (the most common allele), whereas the ε2 allele confers a protective effect.34 However, patient sex, environment, race, and ethnicity as well as the presence of other risk alleles also contribute to AD risk associated with the APOE genotype.33,34
Establishing ApoE proteoform status (APOE genotype) is recommended for patients with early AD who are candidates for anti-amyloid monoclonal antibody therapy.57 Lecanemab, donanemab, and aducanumab are 3 monoclonal antibodies that target aggregated forms of beta-amyloid and have been approved by the US Food and Drug Administration (FDA)4—although aducanumab was recently withdrawn from the market as a “business decision” not related to safety or efficacy.58 Individuals receiving these therapies are at risk of developing amyloid-related imaging abnormalities (ARIAs) detected as edema (ARIA-E) or hemorrhagic changes (ARIA-H); ARIAs are mostly asymptomatic but occasionally may result in life-threatening symptoms.57 Risk of ARIA is increased in APOE ε4 carriers, especially APOE ε4 homozygotes.59 Therefore, testing for APOE ε4 status, either with genotyping or ApoE phenotyping, helps inform the discussion of treatment risk between the prescriber and patient.57,59
The presence of the ε4 allele is not necessary or sufficient to cause AD. People who are ε4 allele carriers may never develop AD, and over 30% of patients with AD are not carriers of the ε4 allele.4 Therefore, routine testing for ApoE proteoform status using this test or APOE genotype (test code 10642) alone is not recommended to predict AD risk.60,61 These tests can be ordered alongside other AD-Detect tests.
Compared to the most common combination of ApoE proteoforms (E3/E3 phenotype)
- E2/E2 and E2/E3 phenotypes (ε2/ε2 and ε2/ε3 genotypes) suggest lower-than-average AD risk
- E2/E4 and E3/E4 phenotypes (ε2/ε4 and ε3/ε4 genotypes) suggest higher-than-average AD risk
Compared with all other phenotypes, an E4/E4 (homozygous) phenotype (ε4/ ε4 genotype) may confer the highest AD risk; homozygosity has been suggested to be a genetically distinct form of AD.62
Risk for ARIA is higher in individuals who are receiving anti-amyloid monoclonal antibody therapy and have the ApoE4 proteoform-specific peptide, especially the E4/E4 phenotype.57
Phenotyping results should be considered knowing that patient sex, environment, race, and ethnicity, as well as the presence of other risk alleles, also contribute to AD risk associated with the ApoE phenotype/APOE genotype.33,34
CSF–based tests
Beta-amyloid 42/40 ratio and ApoE
The Beta-Amyloid 42/40 Ratio and Apolipoprotein E (ApoE) Isoform Panel, CSF (test code 94628), combines results for these biomarkers into a model to assess the risk for adults exhibiting signs of MCI or dementia having AD. Panel components can be ordered separately: Beta-Amyloid 42/40 Ratio, CSF (test code 94627) or Apolipoprotein E (APOE) Isoform, CSF (test code 94626). If only phenotyping or genotyping is required, consider plasma tests for less invasive specimen collection.
The clinical performance measures for Aβ42/40 ratio in CSF were developed using a population predominantly >50 years old, including individuals with AD (n=102), MCI (n=37), mixed LBD–AD dementia (n=9), LBD (n=10), FTD (n=7), progressive supranuclear palsy (n=3), corticobasal degeneration (n=1), and normal cognition (n=130).63 PET data were not available for all of these individuals, so performance relates to diagnosis rather than PET status.
An Aβ42/40 ratio cutoff of <0.16 had a clinical sensitivity of 78% for distinguishing patients with AD from those with non–AD dementia (clinical specificity, 91%) and from those with normal cognition (clinical specificity, 81%). The Aβ42/40 ratio decreased significantly (P <.001) with increasing dose of APOE4 alleles.63
Based on these data, a model was developed (test code 94628) to examine the biomarkers separately and combined into a risk score to determine the risk that a patient has AD (Table 3).
Table 3. CSF Biomarkers and Risk of Having AD [return to contents]
| Biomarker | AD likelihood |
||
| Lower | Average | Higher | |
ApoE proteoform |
E2a |
E3a |
E4 |
Aβ42/40 |
≥0.16 |
NAb |
<0.16 |
Risk assessment score |
<-0.918 |
-0.918 to 1.419 |
>1.419 |
| Aβ42/40, beta-amyloid (1-42)/beta-amyloid (1-40); ApoE, apolipoprotein; CSF, cerebral spinal fluid; NA, not applicable | |
| a | In the absence of E4. |
| b | As a single-cutpoint test, there is no average likelihood. |
p-tau/total-tau/Aβ42
The ADmark® Phospho-Tau/Total-Tau/A Beta42, Analysis and Interp, CSF (Symptomatic) test (test code 92433) uses immunoassay to correlate p-tau, total-tau, and Aβ42 levels in CSF.
Meta-analysis of 231 studies, comprising nearly 30,000 individuals, indicated that CSF from patients with AD has levels of p-tau about 1.9-times higher, total-tau 2.5-times higher, and Aβ42 0.56-times lower than CSF from healthy control individuals.64 These differences were similarly reflected in comparing individuals with MCI-AD vs stable MCI; p-tau levels were 1.7-fold higher, total-tau was 1.8-fold higher, and Aβ42 was 0.7-fold lower in CSF from patients with stable MCI.64
Importantly, racial differences have been observed, with lower tau CSF biomarkers in Black MCI patients compared with those in White MCI patients, which could affect their eligibility for clinical trial participation.65 Consequently, higher Aβ42 and lower tau cutoffs were proposed for Black vs White patients. Fortunately, CSF Aβ42/tau ratios appear less affected by race.65
The ADmark® test computes an amyloid tau index (ATI) using the CSF concentrations (pg/mL) of Aβ42 and total tau in CSF66 based in part on a model developed using a cohort of US and European patients with AD. The ATI normalizes Aβ42 concentration such that an ATI threshold <1.0 suggests the presence of AD.67 It provides a sensitivity of 85% for identifying AD-dementia and provides a specificity of 86% for distinguishing AD from non-AD disorders, 87% from healthy control individuals, and 58% from non-AD dementia.68
Non-AD dementia and dementia-like symptoms
Non-AD dementia and dementia-like symptoms can have several etiologies, some of which are treatable and reversible. US and European guidelines recommend laboratory testing to assess these conditions as well as comorbidities that often accompany dementia.8,9 Quest offers Dementia Panel, Secondary Causes (test code 34541) that includes recommended testing for folate, vitamin B12, thyroid-stimulating hormone, calcium, glucose, complete blood cell count, and renal and liver function tests.
Infectious disease testing is also recommended for atypical presentation or clinical features suggestive of syphilis (test code 36126), Lyme disease (test code 34194), or HIV infection (test code 91431).9 An algorithmic approach has been published for incorporating most of these tests in evaluation of suspected dementia.7 Tests are also available for other possible infectious disease causes of dementia, including prion disease (test code 37989),10 as described in Table 2.
References [return to contents]
- Fang M, Hu J, Weiss J, et al. Lifetime risk and projected burden of dementia. Nat Med. 2025;31(3):772-776. doi:10.1038/s41591-024-03340-9
- Mukadam N, Wolters FJ, Walsh S, et al. Changes in prevalence and incidence of dementia and risk factors for dementia: an analysis from cohort studies. Lancet Public Health. 2024;9(7):e443-e460. doi:10.1016/S2468-2667(24)00120-8
- Stallard PJE, Ukraintseva SV, Doraiswamy PM. Changing story of the dementia epidemic. JAMA. 2025:;333(18):1579-1580. doi:10.1001/jama.2025.1897
- 2024 Alzheimer's disease facts and figures. Alzheimers Dement. 2024;20(5):3708-3821. doi:10.1002/alz.13809
- American Psychiatric Association. Neurocognitive disorders. In:. Diagnostic and Statistical Manual of Mental Disorders Text Revision DSM-5-TR™. 5th ed. American Psychiatric Association Publishing; 2022:667-732. doi:10.1176/appi.books.9780890425787.x17_Neurocognitive_Disorders
- Sachdev PS, Blacker D, Blazer DG, et al. Classifying neurocognitive disorders: the DSM-5 approach. Nat Rev Neurol. 2014;10(11):634-642. doi:10.1038/nrneurol.2014.181
- Falk N, Cole A, Meredith TJ. Evaluation of suspected dementia. Am Fam Physician. 2018;97(6):398-405.
- Knopman DS, DeKosky ST, Cummings JL, et al. Practice parameter: diagnosis of dementia (an evidence-based review). Report of the quality standards subcommittee of the American Academy of Neurology. Neurology. 2001;56(9):1143-1153. doi:10.1212/wnl.56.9.1143
- Sorbi S, Hort J, Erkinjuntti T, et al. EFNS-ENS Guidelines on the diagnosis and management of disorders associated with dementia. Eur J Neurol. 2012;19(9):1159-1179. doi:10.1111/j.1468-1331.2012.03784.x
- Almeida OP, Lautenschlager NT. Dementia associated with infectious diseases. Int Psychogeriatr. 2005;17 Suppl 1:S65-77. doi:10.1017/s104161020500195x
- Morley JE, Morris JC, Berg-Weger M, et al. Brain health: the importance of recognizing cognitive impairment: an IAGG consensus conference. J Am Med Dir Assoc. 2015;16(9):731-739. doi:10.1016/j.jamda.2015.06.017
- Budd Haeberlein S, Aisen PS, Barkhof F, et al. Two randomized phase 3 studies of aducanumab in early Alzheimer's Disease. J Prev Alzheimers Dis. 2022;9(2):197-210. doi:10.14283/jpad.2022.30
- Albert MS, DeKosky ST, Dickson D, et al. 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. 2011;7(3):270-279. doi:10.1016/j.jalz.2011.03.008
- McKhann GM, Knopman DS, Chertkow H, et al. 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. 2011;7(3):263-269. doi:10.1016/j.jalz.2011.03.005
- Bondi MW, Edmonds EC, Jak AJ, et al. Neuropsychological criteria for mild cognitive impairment improves diagnostic precision, biomarker associations, and progression rates. J Alzheimers Dis. 2014;42(1):275-289. doi:10.3233/JAD-140276
- McDougall F, Edgar C, Mertes M, et al. Psychometric properties of the clinical dementia rating - sum of boxes and other cognitive and functional outcomes in a prodromal Alzheimer's disease population. J Prev Alzheimers Dis. 2021;8(2):151-160. doi:10.14283/jpad.2020.73
- Whitfield T, Chouliaras L, Morrell R, et al. The criteria used to rule out mild cognitive impairment impact dementia incidence rates in subjective cognitive decline. Alzheimers Res Ther. 2024;16(1):142. doi:10.1186/s13195-024-01516-6
- Jack CR, Jr., Andrews JS, Beach TG, et al. Revised criteria for diagnosis and staging of Alzheimer's disease: Alzheimer's Association Workgroup. Alzheimers Dement. 2024;20(8):5143-5169. doi:10.1002/alz.13859
- Lewczuk P, Matzen A, Blennow K, et al. Cerebrospinal fluid Aβ42/40 corresponds better than Aβ42 to amyloid PET in Alzheimer's disease. J Alzheimers Dis. 2017;55(2):813-822. doi:10.3233/JAD-160722
- Zetterberg H, Burnham SC. Blood-based molecular biomarkers for Alzheimer's disease. Mol Brain. 2019;12(1):26. doi:10.1186/s13041-019-0448-1
- Janelidze S, Teunissen CE, Zetterberg H, et al. Head-to-head comparison of 8 plasma amyloid-β 42/40 assays in Alzheimer disease. JAMA Neurol. 2021:e213180. doi:10.1001/jamaneurol.2021.3180
- Thijssen EH, Joie RL, Strom A, et al. Plasma phosphorylated tau 217 and phosphorylated tau 181 as biomarkers in Alzheimer's disease and frontotemporal lobar degeneration: a retrospective diagnostic performance study. The Lancet Neurology. 2021;20(9):739-752. doi:10.1016/s1474-4422(21)00214-3
- Mielke MM, Dage JL, Frank RD, et al. Performance of plasma phosphorylated tau 181 and 217 in the community. Nature Medicine. 2022;28(7):1398-1405. doi:10.1038/s41591-022-01822-2
- Ashton NJ, Brum WS, Molfetta GD, et al. Diagnostic accuracy of a plasma phosphorylated tau 217 immunoassay for Alzheimer disease pathology. JAMA Neurology. 2024;81(3):255-263. doi:10.1001/jamaneurol.2023.5319
- Palmqvist S, Janelidze S, Quiroz YT, et al. Discriminative accuracy of plasma phospho-tau217 for Alzheimer disease vs other neurodegenerative disorders. JAMA. 2020;324(8):772-781. doi:10.1001/jama.2020.12134
- Therriault J, Ashton NJ, Pola I, et al. Comparison of two plasma p-tau217 assays to detect and monitor Alzheimer’s pathology. eBioMedicine. 2024;102:105046. doi:10.1016/j.ebiom.2024.105046
- Hu Y, Cho M, Sachdev P, et al. Fluid biomarkers in the context of amyloid-targeting disease-modifying treatments in Alzheimer's disease. Med. 2024;5(10):1206-1226. doi:10.1016/j.medj.2024.08.004
- Jack CR, Bennett DA, Blennow K, et al. NIA-AA Research Framework: toward a biological definition of Alzheimer's disease. Alzheimers Dement. 2018;14(4):535-562. doi:10.1016/j.jalz.2018.02.018
- Mattsson N, Cullen NC, Andreasson U, et al. Association between longitudinal plasma neurofilament light and neurodegeneration in patients with Alzheimer disease. JAMA Neurology. 2019;76(7):791-799. doi:10.1001/jamaneurol.2019.0765
- Holper S, Loveland P, Churilov L, et al. Blood astrocyte biomarkers in Alzheimer disease: a systematic review and meta-analysis. Neurology. 2024;103(3):e209537. doi:10.1212/WNL.0000000000209537
- Nisenbaum L, Martone R, Chen T, et al. CSF biomarker concordance with amyloid PET in phase 3 studies of aducanumab. Alzheimers Dement. 2023;19(8):3379-3388. doi:10.1002/alz.12919
- Rabe C, Bittner T, Jethwa A, et al. Clinical performance and robustness evaluation of plasma amyloid-beta(42/40) prescreening. Alzheimers Dement. 2023;19(4):1393-1402. doi:10.1002/alz.12801
- Neu SC, Pa J, Kukull W, et al. Apolipoprotein E genotype and sex risk factors for Alzheimer Disease: a meta-analysis. JAMA Neurol. 2017;74(10):1178-1189. doi:10.1001/jamaneurol.2017.2188
- Reitz C, Pericak-Vance MA, Foroud T, et al. A global view of the genetic basis of Alzheimer disease. Nat Rev Neurol. 2023;19(5):261-277. doi:10.1038/s41582-023-00789-z
- Hampel H, O'Bryant SE, Molinuevo JL, et al. Blood-based biomarkers for Alzheimer disease: mapping the road to the clinic. Nat Rev Neurol. 2018;14(11):639-652. doi:10.1038/s41582-018-0079-7
- Schindler SE, Galasko D, Pereira AC, et al. Acceptable performance of blood biomarker tests of amyloid pathology - recommendations from the Global CEO Initiative on Alzheimer's Disease. Nat Rev Neurol. 2024;20(7):426-439. doi:10.1038/s41582-024-00977-5
- Roberts RO, Aakre JA, Kremers WK, et al. Prevalence and outcomes of amyloid positivity among persons without dementia in a longitudinal, population-based setting. JAMA Neurol. 2018;75(8):970-979. doi:10.1001/jamaneurol.2018.0629
- Weber DM, Stroh MA, Taylor SW, et al. Development and clinical validation of blood-based multibiomarker models for the evaluation of brain amyloid pathology. medRxiv. doi:10.1101/2025.02.27.25322892
- Figdore DJ, Griswold M, Bornhorst JA, et al. Optimizing cutpoints for clinical interpretation of brain amyloid status using plasma p-tau217 immunoassays. Alzheimers Dement. 2024;20(9):6506-6516. doi:10.1002/alz.14140
- Meyer MR, Kirmess KM, Eastwood S, et al. Clinical validation of the PrecivityAD2 blood test: a mass spectrometry-based test with algorithm combining %p-tau217 and Abeta42/40 ratio to identify presence of brain amyloid. Alzheimers Dement. 2024;20(5):3179-3192. doi:10.1002/alz.13764
- Weber DM, Taylor SW, Lagier RJ, et al. Clinical utility of plasma Aβ42/40 ratio by LC-MS/MS in Alzheimer’s disease assessment. Front Neurol. 2024;15:1364658. doi:10.3389/fneur.2024.1364658
- Antonioni A, Raho EM, Manzoli L, et al. Blood phosphorylated Tau181 reliably differentiates amyloid-positive from amyloid-negative subjects in the Alzheimer's disease continuum: a systematic review and meta-analysis. Alzheimers Dement (Amst). 2025;17(1):e70068. doi:10.1002/dad2.70068
- Therriault J, Vermeiren M, Servaes S, et al. Association of phosphorylated tau biomarkers with amyloid positron emission tomography vs tau positron emission tomography. JAMA Neurology. 2023;80(2):188-199. doi:10.1001/jamaneurol.2022.4485
- Mattsson-Carlgren N, Janelidze S, Palmqvist S, et al. Longitudinal plasma p-tau217 is increased in early stages of Alzheimer’s disease. Brain. 2020;143(11):3234-3241. doi:10.1093/brain/awaa286
- Palmqvist S, Tideman P, Cullen N, et al. Prediction of future Alzheimer’s disease dementia using plasma phospho-tau combined with other accessible measures. Nature Medicine. 2021;27(6):1034-1042. doi:10.1038/s41591-021-01348-z
- Janelidze S, Mattsson N, Palmqvist S, et al. Plasma p-tau181 in Alzheimer's disease: relationship to other biomarkers, differential diagnosis, neuropathology and longitudinal progression to Alzheimer's dementia. Nat Med. 2020;26(3):379-386. doi:10.1038/s41591-020-0755-1
- Palmqvist S, Stomrud E, Cullen N, et al. An accurate fully automated panel of plasma biomarkers for Alzheimer's disease. Alzheimers Dement. 2023;19(4):1204-1215. doi:10.1002/alz.12751
- Karikari TK, Pascoal TA, Ashton NJ, et al. Blood phosphorylated tau 181 as a biomarker for Alzheimer's disease: a diagnostic performance and prediction modelling study using data from four prospective cohorts. Lancet Neurol. 2020;19(5):422-433. doi:10.1016/S1474-4422(20)30071-5
- Vacchiano V, Mastrangelo A, Zenesini C, et al. Elevated plasma p-tau181 levels unrelated to Alzheimer's disease pathology in amyotrophic lateral sclerosis. J Neurol Neurosurg Psychiatry. 2023;94(6):428-435. doi:10.1136/jnnp-2022-330709
- Khalil M, Teunissen CE, Lehmann S, et al. Neurofilaments as biomarkers in neurological disorders — towards clinical application. Nature Reviews Neurology. 2024;20(5):269-287. doi:10.1038/s41582-024-00955-x
- Ashton NJ, Janelidze S, Khleifat AA, et al. A multicentre validation study of the diagnostic value of plasma neurofilament light. Nature Communications. 2021;12(1):3400. doi:10.1038/s41467-021-23620-z
- Ducharme S, Dols A, Laforce R, et al. Recommendations to distinguish behavioural variant frontotemporal dementia from psychiatric disorders. Brain. 2020;143(6):1632-1650. doi:10.1093/brain/awaa018
- Feneberg E, Oeckl P, Steinacker P, et al. Multicenter evaluation of neurofilaments in early symptom onset amyotrophic lateral sclerosis. Neurology. 2018;90(1):e22-e30. doi:10.1212/wnl.0000000000004761
- Angelopoulou E, Bougea A, Papadopoulos A, et al. CSF and circulating NfL as biomarkers for the discrimination of Parkinson disease from atypical parkinsonian syndromes. Neurology: Clinical Practice. 2021;11(6):e867-e875. doi:10.1212/cpj.0000000000001116
- Abdelhak A, Foschi M, Abu-Rumeileh S, et al. Blood GFAP as an emerging biomarker in brain and spinal cord disorders. Nat Rev Neurol. 2022;18(3):158-172. doi:10.1038/s41582-021-00616-3
- Weber DM, Kim JC, Goldman SM, et al. New plasma LC-MS/MS assays for the quantitation of beta-amyloid peptides and identification of apolipoprotein E proteoforms for Alzheimer's disease risk assessment. J Investig Med. 2024;72(5):465-474. doi:10.1177/10815589241246537
- Cummings J, Apostolova L, Rabinovici GD, et al. Lecanemab: appropriate use recommendations. J Prev Alzheimers Dis. 2023;10(3):362-377. doi:10.14283/jpad.2023.30
- Aducanumab discontinued as an Alzheimer's treatment. Alzheimer's Association. Accessed March 20, 2025. https://www.alz.org/alzheimers-dementia/treatments/aducanumab
- LEQEMBI® (lecanemab-irmb) injection. Prescribing information. Eisai Inc; July 2023. Accessed March 20, 2025. https://www.leqembi.com/-/media/Files/Leqembi/Prescribing-Information.pdf?hash=77aa4a86-b786-457a-b894-01de37199024
- Goldman JS, Hahn SE, Catania JW, et al. Genetic counseling and testing for Alzheimer disease: joint practice guidelines of the American College of Medical Genetics and the National Society of Genetic Counselors. Genet Med. 2011;13(6):597-605. doi:10.1097/GIM.0b013e31821d69b8
- Goldman JS, Hahn SE, Catania JW, et al. ADDENDUM: Genetic counseling and testing for Alzheimer disease: joint practice guidelines of the American College of Medical Genetics and the National Society of Genetic Counselors. Genet Med. 2019;21(10):2404. doi:10.1038/s41436-019-0559-1
- Fortea J, Pegueroles J, Alcolea D, et al. APOE4 homozygozity represents a distinct genetic form of Alzheimer's disease. Nat Med. 2024;30(5):1284-1291. doi:10.1038/s41591-024-02931-w
- Weber DM, Tran D, Goldman SM, et al. High-throughput mass spectrometry assay for quantifying β-amyloid 40 and 42 in cerebrospinal fluid. Clin Chem. 2019;65(12):1572-1580. doi:10.1373/clinchem.2018.300947
- Olsson B, Lautner R, Andreasson U, et al. CSF and blood biomarkers for the diagnosis of Alzheimer's disease: a systematic review and meta-analysis. Lancet Neurol. 2016;15(7):673-684. doi:10.1016/S1474-4422(16)00070-3
- Garrett SL, McDaniel D, Obideen M, et al. Racial disparity in cerebrospinal fluid amyloid and tau biomarkers and associated cutoffs for mild cognitive impairment. JAMA Netw Open. 2019;2(12):e1917363. doi:10.1001/jamanetworkopen.2019.17363
- Oboudiyat C, Gefen T, Varelas E, et al. Cerebrospinal fluid markers detect Alzheimer's disease in nonamnestic dementia. Alzheimers Dement. 2017;13(5):598-601. doi:10.1016/j.jalz.2017.01.006
- Tariciotti L, Casadei M, Honig LS, et al. Clinical experience with cerebrospinal fluid Abeta42, total and phosphorylated tau in the evaluation of 1,016 individuals for suspected dementia. J Alzheimers Dis. 2018;65(4):1417-1425. doi:10.3233/JAD-180548
- Hulstaert F, Blennow K, Ivanoiu A, et al. Improved discrimination of AD patients using beta-amyloid(1-42) and tau levels in CSF. Neurology. 1999;52(8):1555-1562. doi:10.1212/wnl.52.8.1555
Content reviewed 4/2025
This Clinical Focus describes the role that laboratory testing can play in diagnosing causes of mild cognitive impairment, dementia, and dementia-like symptoms.
Clinical Focus
Dementia
Biomarkers for Differential Diagnosis and Alzheimer's Disease Assessment
Clinical background [return to contents]
Dementia is becoming an increasing public health and economic burden for the United States as the population ages.1 Based on current incidence rates, the number of adults who will develop dementia each year is projected to approach about 1 million in 2060 compared with just over half that number in 2020.1 Women are at higher risk than men, and Black adults are at higher risk than White adults.1
Mitigation of some of the actionable risk factors for dementia may attenuate these projections. Dementia incidence in the United States is actually declining, possibly due to reduction of population-attributable risk factors over time, including higher education attainment and less smoking.2 Prevalence, in terms of the percentage of people with dementia for any given age group, appears to be similarly decreasing.3 Compared to preceding generations, younger cohorts have improved access to medication to control other dementia risk factors, which include high low-density lipoprotein levels, depression, and hypertension.3 Unfortunately, diabetes and obesity are dementia risk factors that continue to increase in the US population that may have dampened declines in dementia in the past and will continue to in the future.3
Dementia is a syndrome with a collection of symptoms that can be grouped into different etiologies, the most common of which is Alzheimer’s disease (AD). Some conditions have dementia-like symptoms, but are treatable and reversible; thus, identifying the cause of dementia is crucial for providing appropriate patient care.4
This Clinical Focus describes the role that laboratory testing can play in diagnosing mild cognitive impairment (MCI), dementia, and dementia-like symptoms caused by AD (vs other causes), excluding neuroimmune causes. (See Quest Diagnostics: Results for Recombx Progressive Dementia for testing for autoimmune rapidly progressing dementia.) Once a diagnosis is made, laboratory testing also plays a role in assessing prognosis and drug and clinical trial eligibility. This information is not intended as medical advice. Test selection and interpretation, diagnosis, and patient management decisions should be based on the physician’s education, clinical expertise, and assessment of the patient.
Dementia causes
AD causes 60% to 80% of dementia cases; according to the Alzheimer’s Association, an estimated 6.9 million people currently have AD, and the number is expected to rise to nearly 14 million by 2060.4 Other causes of dementia include, but are not limited to,4
- Cerebrovascular disease (5%-10% of cases)
- Lewy body disease (LBD, 5%)
- Parkinson disease (PD, 4%)
- Frontotemporal degeneration (FTD, 3% ≥65 years; 10% <65 years)
- Hippocampal sclerosis (HS, <2%)
Mixed pathologies cause >50% of dementia cases and are common in patients ≥85 years (eg, HS prevalence, which increases to 3%-13% as a mixed etiology).4 Although progress is being made in slowing disease progression with the approval and use of the first disease-modifying therapies in AD, most of these dementias are irreversible.
Causes of other non-AD dementias include Huntington disease, HIV infection, traumatic brain injury, substance use disorder, prion disease, and stroke.5 Neurocognitive symptoms may emerge after disease onset in most of these conditions as well as in PD.6 In contrast, cognitive and behavioral symptoms are the first manifestation of the disease in AD, cerebrovascular disease, LBD, and FTD.
Some conditions can cause dementia-like symptoms but are not considered dementia (See “Non-AD dementia and dementia-like symptoms” section below).4 These include depression, sleep apnea, delirium (eg, caused by drug side effects, substance intoxication or withdrawal), infection (eg, Lyme disease, syphilis), brain blood clots or tumors, thyroid disease, head injury, or certain vitamin deficiencies.4,7-10 Importantly, dementia-like symptoms may often be reversed with treatment once these causes are identified.
Dementia diagnosis
Dementia is diagnosed based on evidence of significant cognitive decline reported by the patient, an individual close to the patient, or their clinician, preferably documented through objective quantifiable clinical assessment.5,6 This decline is relative to the patient’s previous abilities in complex attention, executive function, learning and memory, or perceptual-motor or social cognition. For a diagnosis, these cognitive impairments must interfere with the patient’s independence in everyday activities, such that they minimally require assistance (eg, with paying bills and managing medications). Additionally, impairments cannot be attributed to delirium or other mental disorder (eg, major depressive disorder or schizophrenia).
Dementia is also defined as “a major neurocognitive disorder” by the Diagnostic and Statistical Manual of Mental Disorders DSM-5-TR.™5 The DSM-5-TR definition differs from the previous DSM-IV definition in that impairments in learning and memory are not necessary for diagnosis and that it is more inclusive for younger symptomatic patients.6
Mild cognitive impairment (MCI) diagnosis
DSM-5-TR was also revised to define “a mild neurocognitive disorder” with a very similar definition to “a major neurocognitive disorder” but with cognitive declines being qualitatively “modest.”5 DSM-5-TR defines these cognitive declines as not interfering in everyday activities (although more effort or accommodation is required) and being quantitively less (eg, 1-2 standard deviations [SD] below normative means for standardized cognitive tests vs >2 SD for dementia).5,6
Despite the DSM-5-TR definitions, the terms “dementia” and “MCI” are favored in the literature. Knowing whether a person with a mild neurocognitive disorder/MCI is at risk for developing AD can help patients and their families to better prepare for future care needs11 and enable clinical trial eligibility. Ruling out AD can prompt investigation of non-AD causes of MCI or dementia.7-9,11
Clinical trials for AD therapeutics have used various criteria to identify eligible patients with MCI.6,12-14 Bondi et al proposed neuropsychological criteria that (1) defined impairment as 1 SD below normative means to capture more individuals with suspected MCI, (2) required 2 impaired scores for a cognitive test to support a reliable observation, and (3) incorporated activities of daily living scores.15 The last criterion has been incorporated into the Clinical Dementia Rating (CDR® ) sum of boxes score, which is commonly used as a primary endpoint in many clinical trials.16 In head-to-head comparisons with other MCI criteria, a higher percentage of study participants who fulfilled the Bondi criteria progressed to dementia.15,17
Importantly, the Bondi criteria were also supported by significant associations with cerebrospinal fluid (CSF) AD biomarkers including beta-amyloid (1-42) (Aβ42), total tau, and hyperphosphorylated tau (see “CSF–based biomarkers” Section below),15 indicating that they may be better suited to identifying MCI–AD.
Given that different phenotypic presentations of AD are well known, biomarkers are important in diagnosis and monitoring, even in the prodromal stages of MCI-AD.18 Accordingly, the Alzheimer’s Association Workgroup revised the definition of AD from one based on clinical presentation to “a biological process that begins with the appearance of AD neuropathologic change.”18
Blood-based biomarkers
Compared with CSF and imaging biomarkers, blood-based biomarkers have emerging roles as less invasive and less expensive methods for characterizing MCI as a prodromal state of AD (Table 1),18-34 but they have been challenging to incorporate into clinical practice until recent years. Blood is a more complex matrix, and biomarker levels are much lower than in CSF.35 Fortunately, ultrasensitive methods have been developed that better quantify the blood-based biomarkers.21
Table 1. Select AD Biomarkers, Clinical Uses, Classification, and Test Codes [return to contents]
| Biomarker | Current clinical use(s) in AD | Core classification18,a | Test codes (see Table 2) | ||||
| Risk and/or diagnosis | Prognosis | Progression | Therapy selection | Monitoring therapy | |||
| Blood-based biomarkers | |||||||
| Aβ4219-21,b | • | 1 | 11786c | ||||
| 14258c | |||||||
| p-Tau21722-26 | • | • | • | 1 | 13825 | ||
| 14258 | |||||||
| p-Tau18127 | • | • | • | 1 | 13690 | ||
| NfL28,29 | • | • | Nonspecific | 13979 | |||
| GFAP27,30 | • | • | • | Nonspecific | 14319 | ||
| APOE4 | • | • | • | NA, genericd | 10642 | ||
| 12563 | |||||||
| CSF biomarkers | |||||||
| Aβ4218,31,32,b | • | • | 1 | 94627c | |||
| 94628c | |||||||
| p-Tau18 | • | 1 | 92433c | ||||
| Aβ4218 | • | 1 | 92433c | ||||
| APOE433,34 | • | • | • | NA, genericd | 94626 | ||
| 94628 | |||||||
| Aβ42/40, beta-amyloid (1-42)/beta-amyloid (1-40); AD, Alzheimer's disease; APOE4, APOE ε4 allele; CSF, cerebrospinal fluid; GFAP, glial fibrillary acidic protein; NA, not applicable; NfL, neurofilament light chain; p-tau, tau protein phosphorylated at amino acid residue 217 (or 181). | |
| a | Per Alzheimer's Association Workgroup,18 Core 1 biomarkers and hybrid ratios are sufficient for early detection of amyloid pathology and tau hyperphosphorylation in AD; nonspecific biomarkers are important in AD pathology but are not specific to AD. |
| b | Measuring Aβ42/40 provides greater assessment accuracy than measuring Aβ42 alone because it controls for the natural variance of β-amyloid production between patients.19 |
| c | Measured in a hybrid ratio of biomarkers.18 |
| d | Genotype can be determined from any generic matrix. |
A consensus statement provided by academicians and patient advocacy, pharmaceutical, diagnostic, and other private industry professionals (the Global CEO Initiative) has suggested acceptable performance characteristics for blood-based tests that assess amyloid pathology.36 Different thresholds for performance supporting clinical uses are proposed:
- For triaging followed by confirmation using positron emission tomography (PET) or CSF (depending on availability)
- Sensitivity ≥90%, specificity ≥85% (primary care)
- Sensitivity ≥90%, specificity ≥75% (secondary care)
- For confirmation without the need for follow-up testing (patient history and clinical and cognitive testing are still needed)
- Sensitivity and specificity ≥90%
According to the consensus statement, these thresholds should only be interpreted in clinical context including the predictive ability of the test for the population examined, which in turn depends upon the prevalence of amyloid pathology of the population being examined.36 For example, in a primary care setting, prevalence is likely to be closer to 20%,37 whereas in secondary care, it is likely to be higher (eg, 50%-80%), and follow-up is likely better supported by PET and CSF testing capabilites.36
The prevalence in combination with the sensitivity and specificity of the test determines the positive predictive value (PPV) and the negative predictive value (NPV). High PPV can be used to help “rule in,” and high NPV can be used to help “rule out,” a diagnosis based on a test result. For example, in a population with a 50% prevalence of PET positivity36
- For a confirmatory test, PPV and NPV should both be approximately 90%
- For a high-specificity triaging test, the PPV should be 86% and NPV should be 89%
- For a low-specificity triaging test, the PPV should be 78% and NPV should be 88%
To confirm or rule out amyloid pathology, these performance metrics can be achieved in 2 ways36:
- A single static threshold for the biomarker (ie, cutpoint value, such as a ratio or concentration, above or below which the required sensitivity and specificity is attained)
- A 2-value, dynamic high-low threshold approach (the lower cutpoint is set to achieve the desired sensitivity and upper cutpoint is set to achieve the desired specificity; ideally, this approach requires no more than 15% to 20% of patients obtaining an intermediate/indeterminate result with values between the high-low thresholds)
Revised criteria for diagnosis and staging of AD provided by the Alzheimer’s Association Workgroup18 cite the consensus statement in evaluating plasma assays. "Core 1" biomarkers are those that have sufficient performance to be used for early AD detection of amyloid pathology and tau hyperphosphorylation. Abnormal results for a Core 1 biomarker can be considered equivalent to CSF assays in detecting abnormality in PET in the intended use population (MCI and AD). Hybrid ratios of biomarkers can be interpreted similarly but represent the associated assay rather than the single biomarker.18
The Workgroup also provides 2 other categories of biomarkers. These include “Core 2” biomarkers, which can be used for evaluating later stages of the disease and providing prognostic information in AD assessment, but that are not stand-alone tests for AD diagnosis.18 When abnormal, Core 2 biomarkers, which currently include selected tau protein fragments, help assess the contribution of AD to patient symptoms. (These are not further discussed in this Clinical Focus.) The third category includes nonspecific biomarkers that are important in AD pathology but are not specific to AD (Table 1).
CSF–based biomarkers [H2]
CSF–based testing is considered a benchmark against which blood-based biomarker testing can be compared.18 Concentrations of biomarkers are much higher in CSF than in blood, and results correlate well with PET imaging analysis for Aβ.31,32 CSF biomarkers also provide cutpoints that better separate PET-positive vs PET-negative individuals and tend to be more robust, as assay imprecision and bias affect test results and patient classification to a lesser extent.32 CSF Aβ42, p-tau217, p-tau181, and p-tau231 are considered as Core 1 biomarkers for Aβ pathology by the Workgroup (Table 1).
Individuals suitable for testing [return to contents]
- Adults exhibiting signs and symptoms of MCI and dementia (per DSM-5-TR definitions of minor and major neurocognitive disorders)
Test availability [return to contents]
Quest Diagnostics offers tests and panels to help diagnose the cause(s) of MCI, dementia, and dementia-like symptoms (Table 2). For AD assessment, Quest offers tests employing liquid chromatography-tandem mass spectrometry (LC-MS/MS), immunoassays, or molecular methodology for various biomarkers and specimen types. Blood-based tests include Aβ42/40, p-tau217, and APOE4 offered singularly and in combination, as well as other tests for AD assessment. Where applicable, we provide performance characteristics of these tests in the context of the Global CEO Initiative statement as described below. CSF–based tests include single tests and combinations of biomarkers for AD risk assessment.
Table 2. Dementia Tests and Panels [return to contents]
| Test code | Test or panela name | Method | Clinical use |
AD-dementia Blood-based biomarkers |
|||
14258 |
AD-Detect™ ABeta 42/40 and p-tau217 Evaluation, Plasma Includes plasma Aβ42/40 ratio and p-tau217 and calculated probabilities for PET positivity. |
|
|
10642 |
ADmark® APOE Genotype Analysis and Interpretation (Symptomatic)b Includes detection of APOE2, E3, and E4 alleles. |
|
|
14319 |
Glial Fibrillary Acidic Protein (GFAP), Plasma |
|
|
13979 |
Neurofilament Light Chain (NfL), Plasmac |
|
|
12563 |
Quest AD-Detect® Apolipoprotein E (ApoE) Isoform, Plasmac |
|
|
11786 |
Quest AD-Detect® Beta-Amyloid 42/40 Ratio, Plasmac |
|
|
13690 |
Quest AD-Detect® Phosphorylated tau181 (p-tau181), Plasmac |
|
|
13825 |
Quest AD-Detect® Phosphorylated tau217(p-tau217), Plasmac |
|
|
| CSF–based biomarkers | |||
92433 |
ADmark® Phospho-Tau/Total-Tau/A Beta42, Analysis and Interp, CSF(Symptomatic)b |
|
|
94626 |
Apolipoprotein E (APOE) Isoform, CSFc |
|
|
94628 |
Beta-Amyloid 42/40 Ratio and Apolipoprotein E (APOE) Isoform Panel, CSFc Includes beta-amyloid 42/40 ratio, ApoE isoform, and total ApoE. |
|
|
94627 |
Beta-Amyloid 42/40 Ratio, CSFc |
|
|
Non-AD dementia |
|||
37989 |
14-3-3 Protein, CSF (Prion Disease)d |
|
|
91431 |
HIV-1/2 Antigen and Antibodies, Fourth Generation, with Reflexe Includes HIV-1/2 antigen and antibody with reflex to HIV-1/2 antibody differentiation; if differentiation test is indeterminate or negative, reflex to HIV-1 RNA. |
|
|
5042 |
Vitamin B1 (Thiamine), Blood, LC/MS/MS |
|
|
Dementia-like symptoms Non-infectious |
|||
34541 |
Dementia Panel, Secondary Causes Includes CBC (6399, including differential and platelets), comprehensive metabolic panel (including albumin [223], albumin/globulin ratio [calculated], alkaline phosphatase [234], ALT [823], AST [822], BUN/creatinine ratio [296], calcium [303], carbon dioxide [310], chloride [330], globulin [calculated], glucose [483], potassium [733], serum creatinine [375] with eGFR [calculated], sodium [836], total bilirubin [287], and total protein [754]), folate (466), TSH (899), and vitamin B12 (927). |
|
|
| Infectious | |||
4553 |
Culture, Fungus, other than Hair, Skin, Blood, with Fluorescent KOH |
|
|
30429 |
Cryptococcus Antibody |
|
|
34164 |
Cysticercus Antibody (IgG), ELISA, CSF |
|
|
34173 |
Cysticercus Antibody (IgG), ELISA, Serum |
||
6732 |
Cytomegalovirus Antibodies (IgG, IgM) |
|
|
8542 |
Herpes Simplex Virus 1/2 (IgG) Type Antibody, CSF |
|
|
34194 |
Lyme Disease Antibody Index for CNS Infection |
|
|
36126 |
RPR (Diagnosis) With Reflex to Titer and Treponema pallidum Antibody, IAe Includes RPR screen with reflex to titer and fluorescent treponemal antibody. |
|
|
10485 |
Toxoplasma gondii (IgG, IgM), ELISA, CSF |
|
|
| AD, Alzheimer's disease; CLIA, chemiluminescence IA; CNS, central nervous system; ECLIA, electrochemiluminescence IA; ELISA, enzyme-linked immunosorbent immunoassay; GFAP, glial fibrillary acidic protein; IA, immunoassay; LC-MS/MS, liquid chromatography-tandem mass spectrometry; MCI, mild cognitive impairment; PET, positron emission tomography; RFLP, restriction fragment length polymorphism. | |
| a | Panel components may be ordered separately. |
| b | This test was developed and its analytical performance characteristics have been determined by Athena Diagnostics. It has not been cleared or approved by FDA. This assay has been validated pursuant to the CLIA regulations and is used for clinical purposes. |
| c | This test was developed and its analytical performance characteristics have been determined by Quest Diagnostics. It has not been cleared or approved by the US Food and Drug Administration. This assay has been validated pursuant to the CLIA regulations and is used for clinical purposes. |
| d | These tests were developed and their performance characteristics determined by the National Prion Disease Pathology Surveillance Center (NPDPSC) and have not been cleared or approved by the FDA. These assays should be used in conjunction with other clinical, pathological, and laboratory findings. |
| e | Reflex testing performed at additional charge with an additional CPT® code. |
Test selection and interpretation [return to contents]
Blood-based tests
AD-Detect panels
AD-Detect™ ABeta 42/40 and p-tau217 Evaluation, Plasma (test code 14258) panel combines results for Aβ42/40 and p-tau217 into a model that generates a likelihood score for PET positivity.38 The model achieves the performance characteristics detailed by the Global CEO Initiative statement for a confirmatory Core 1 diagnostic test for Aβ pathology.36 The model was optimized by using 2 cutpoints, 1 for high and 1 for low risk of PET positivity, evaluated at ≥90% specificity and sensitivity.
The model was developed based on data from an ethnically diverse (54% Hispanic) population of 215 participants from a memory clinic (1Florida AD Research Center [ADRC]) with MCI or AD and a moderate prevalence of PET-positivity.38 Importantly, PET-positive and PET-negative patients were age-, sex-, ethnicity-, and years-of-education matched in contrast to recent studies.39,40
The model achieved an area under the receiver operating characteristic curve (AUC-ROC) of 0.929 with dual cutpoints at ≥90% sensitivity and specificity providing the following: high cutpoint, 87% PPV; low cutpoint, 91% NPV; 83% accuracy (both cutpoints) at the 46% prevalence of PET-positivity in the intended use population (MCI/AD). The dual cutpoint results in most patients receiving a “high” or “low” likelihood score for PET positivity with relatively few having an “indeterminate” result (15% in the ADRC cohort) within the recommended test specifications for ≤20% of patients obtaining an intermediate/indeterminate result.36
The model was further improved by adding APOE4 allele count, which has similar performance to the 2-marker model but with slightly higher accuracy and fewer indeterminate results (10% vs 15%, 7% in >4,000 patient specimens submitted for the 3 component tests).38 Quest will make a 3-marker model that includes APOE4 allele count available in an upcoming update; the test would be a confirmatory test for amyloid pathology without the need for follow-up testing (patient history and clinical and cognitive testing are still needed).36
Beta-amyloid 42/40 ratio
Quest AD-Detect® , Beta-Amyloid 42/40 Ratio, Plasma test (test code 11786) is an LC-MS/MS assay that helps initially assess whether AD pathology is present in the context of dementia. Aβ42 is a Core 1 biomarker in AD assessment and Aβ42/40 is considered a hybrid ratio.18 Measuring Aβ42/40 provides greater assessment accuracy than measuring Aβ42 alone because it controls for the natural variance of β-amyloid production between patients.19
LC-MS/MS is a preferred method for measuring Aβ42/40. A cross-sectional study assessed the diagnostic accuracy of 8 ultrasensitive Aβ42/40 plasma methods (4 immunoassays and 4 MS assays) among 286 individuals. This study included 104 with and 182 without MCI with presence/absence Aβ pathology previously determined using CSF Aβ42/40 by MS.21 Of these assays, an LC-MS/MS analysis-based assay demonstrated higher accuracy (AUC-ROC ≥0.84) than other assays that were standardized for high throughput (AUC-ROCs ranging from 0.60 to 0.80; P<.05).21
The Quest test achieves 91% sensitivity, 76% specificity at a single cutpoint of Aβ42/40=0.160.41 The test was developed using LC-MS/MS data for 250 specimens with associated data for amyloid PET imaging, diagnosis, and demographics. The risk for having AD pathology was projected onto the test results for 6,192 consecutive clinical specimens submitted for Aβ42/40 testing.41
High diagnostic sensitivity and negative predictive value (NPV) for Aβ-PET positivity were observed at a prevalence of 40% of PET positivity in the cohort, consistent with the clinical performance of other plasma LC-MS/MS assays, but with greater separation between Aβ42/40 values for individuals with positive vs negative Aβ-PET results. At the study prevalence of Aβ-PET positivity, a cutpoint (0.170) was identified with 99% NPV, which could help predict that AD is likely not the cause of a patient’s cognitive impairment and help reduce PET evaluations by about 40%.41
p-Tau181 and p-tau217
The Quest AD-Detect® Phosphorylated tau181 (p-tau181), Plasma (test code 13690) and Quest AD-Detect® Phosphorylated tau217 (p-tau217), Plasma (test code 13825) tests help assess whether MCI or dementia is caused by AD. Plasma levels of p-tau181 and p-tau217 are elevated in the MCI and dementia stages of AD and are associated with the presence of Aβ and tau pathology.22-26 Both are considered Core 1 biomarkers in AD assessment.18
Of the 2 biomarkers, p-tau181 has been more extensively studied with a meta-analysis of 18 studies demonstrating that measured blood levels reliably differentiate between Aβ-PET–positive vs Aβ-PET–negative individuals.42 However, plasma p-tau217 has a particularly strong association with Aβ pathology, which increases early in AD progression43 and typically outperforms p-tau181 in head-to-head comparisons according to the Alzheimer's Association Workgroup.18 Increased baseline plasma p-tau217 can predict progression of cognitive impairment, and longitudinal increases correlate with declining cognition.44,45 Increased plasma p-tau181 levels can also predict clinical progression to more severe cognitive impairment.46,47
Plasma levels of both p-tau181 and p-tau217 are dynamic and highly correlative biomarkers of AD pathology as assessed by PET and CSF.23,46-48 Levels increase longitudinally in Aβ-positive, but not Aβ-negative, individuals.24,44 Levels also increase across advancing stages of tau pathology.24,26 The markers can differentiate AD from many other neurodegenerative diseases, such as FTD, progressive supranuclear palsy, vascular dementia, and PD.22,25,46,48 In addition, both plasma p-tau-217 and p-tau181 are leading markers in monitoring AD pathology in response to anti-amyloid therapies targeting protofibrils (lecanemab), insoluble fibrils (donanemab), and plaques (aducanumab).27
The following results are inconsistent with MCI and dementia caused by AD, and further investigation of other causes of cognitive symptoms may be considered:
- Normal plasma p-tau217 levels (≤0.15 pg/mL)
- Normal plasma p-tau181 levels (≤0.86 pg/mL if age <55 years; ≤1.07 pg/mL if age ≥55 years)
The following results are consistent with MCI and dementia caused by AD, and follow-up assessment using PET or CSF analysis should be considered to confirm the presence of AD pathology:
- Higher than normal plasma p-tau217 levels (>0.15 pg/mL)
- Higher than normal plasma p-tau181 levels (>0.86 pg/mL if age <55 years; >1.07 pg/mL if age ≥55 years)
Importantly, both plasma p-tau181 and p-tau217 can also increase in those with chronic kidney disease or a history of myocardial infarction or stroke.23 Plasma p-tau181 can also be increased in patients with amyotrophic lateral sclerosis (ALS) and is associated with lower motor neuron disease.49 Consequently, the results of these assays should be considered in conjunction with the findings from medical and family history, nutritional deficiency biomarkers (See "Dementia-like symptoms" Section below), neuroimaging, and physical, neurological, and neuropsychological examination.
Neurofilament light chain (NfL)
The Neurofilament Light Chain (NfL), Plasma test (test code 13979) provides an accessible, minimally invasive option for assessing neurodegeneration or neuronal injury; NfL is considered a biomarker of nonspecific processes resulting from AD pathophysiology.18
NfL is a structural protein expressed exclusively in neurons. Upon neuronal degeneration or injury, NfL is released into extracellular space, resulting in increased concentrations in CSF and peripheral blood.50 Though NfL levels are lower in blood than in CSF, advancements in assay development have enabled the use of blood-based NfL as a more accessible biomarker of neuronal injury and/or neurodegeneration.50 NfL is generally useful for informing prognosis and monitoring disease progression, most commonly for multiple sclerosis but also for neurodegeneration in AD. Because elevated levels are associated with AD progression, NfL has emerged as a candidate biomarker in the biological definition of AD.28,29
Although lacking specificity for any given disease, NfL measurements can be useful for certain differential diagnoses. Levels are elevated in FTD vs psychiatric disorders, ALS vs motor neuron disease mimics, and atypical parkinsonian syndromes vs PD.50-54
Interpretation of plasma NfL test results depends on the clinical context:
- Normal plasma NfL levels are generally consistent with MCI or dementia not being caused by neuronal injury or neurodegeneration.
- Higher than normal NfL levels are consistent with MCI or dementia being caused by clinically relevant neuronal injury or neurodegeneration. In patients with a known neurologic condition, elevated NfL or increased levels from an established, patient-specific baseline may indicate poorer prognosis and/or disease progression.50 In patients with diagnostic uncertainty, elevated NfL may support differential diagnosis of a suspected neurologic condition.50
NfL levels can be influenced by many factors, including age, body mass index, kidney disease, and a history of diabetes or cardiovascular conditions.50 The results of this assay should be considered in conjunction with the findings from medical and family history, neuroimaging, and physical, neurological, and neuropsychological examination.
Glial fibrillary acidic protein (GFAP)
The Glial Fibrillary Acidic Protein (GFAP), Plasma test (test code 14319) is a tool for assessing AD progression and anti-amyloid therapy treatment response; GFAP is considered another biomarker of nonspecific processes involved in AD pathophysiology.18
GFAP is an intermediate filament protein found only in astrocytes and is a biomarker of neuronal injury (reactive astrogliosis) when released from the central nervous system.27,55 In contrast to most other AD biomarkers, GFAP performs better in plasma than CSF for distinguishing Aβ-PET–positive vs Aβ-PET–negative individuals.27 Meta-analysis of over 2,400 patients on the AD continuum (from cognitively unimpaired to MCI to AD) found that plasma GFAP concentrations increased with disease progression.30 Furthermore, GFAP has been found to be a consistent biomarker in clinical trials for anti-amyloid therapies; compared with baseline, treated patients had a 10% to 20% decrease in plasma GFAP levels compared with a 10% to 15% increase in patients receiving a placebo.27 The placebo-drug difference and effect size was similar to those observed for clinical trials that used plasma p-tau181.27
Interpretation of plasma GFAP test results depends on the clinical context:
- Normal plasma GFAP levels indicate that MCI or dementia does not involve active astrogliosis.
- Higher than normal plasma GFAP levels indicate that MCI or dementia involves active astrogliosis.
GFAP may also be elevated in mild traumatic brain injury, stroke, multiple sclerosis, neuromyelitis optica spectrum disorder, cardiovascular disease (cardiac arrest and atrial fibrillation), infection (West Nile and SARS-CoV-2), and sepsis-related encephalopathy.55 The results of this assay should be considered in conjunction with the findings from medical and family history, neuroimaging, and physical, neurological, and neuropsychological examination.
APOE genotypes and apolipoprotein E proteotypes
The Quest AD-Detect® Apolipoprotein E (ApoE) Isoform, Plasma test (test code 12563) is a tool for AD risk assessment. ApoE phenotypes are identified based on the detection of proteoform-specific peptide(s). Results of phenotyping are 100% concordant with APOE genotyping results.56
ApoE is the primary brain apolipoprotein and the most studied blood biomarker for AD. ApoE has 3 common proteoforms, E2, E3, and E4, which are encoded by the APOE gene ε2, ε3, or ε4 alleles, respectively. The 6 combinations of APOE alleles are ε2/ε2, ε2/ε3, ε2/ε4, ε3/ε3, ε3/ε4, and ε4/ε4; frequencies vary among racial and ethnic groups.4
Specific APOE alleles are associated with increased AD risk: the presence of an ε4 allele confers higher risk of AD compared with ε3 (the most common allele), whereas the ε2 allele confers a protective effect.34 However, patient sex, environment, race, and ethnicity as well as the presence of other risk alleles also contribute to AD risk associated with the APOE genotype.33,34
Establishing ApoE proteoform status (APOE genotype) is recommended for patients with early AD who are candidates for anti-amyloid monoclonal antibody therapy.57 Lecanemab, donanemab, and aducanumab are 3 monoclonal antibodies that target aggregated forms of beta-amyloid and have been approved by the US Food and Drug Administration (FDA)4—although aducanumab was recently withdrawn from the market as a “business decision” not related to safety or efficacy.58 Individuals receiving these therapies are at risk of developing amyloid-related imaging abnormalities (ARIAs) detected as edema (ARIA-E) or hemorrhagic changes (ARIA-H); ARIAs are mostly asymptomatic but occasionally may result in life-threatening symptoms.57 Risk of ARIA is increased in APOE ε4 carriers, especially APOE ε4 homozygotes.59 Therefore, testing for APOE ε4 status, either with genotyping or ApoE phenotyping, helps inform the discussion of treatment risk between the prescriber and patient.57,59
The presence of the ε4 allele is not necessary or sufficient to cause AD. People who are ε4 allele carriers may never develop AD, and over 30% of patients with AD are not carriers of the ε4 allele.4 Therefore, routine testing for ApoE proteoform status using this test or APOE genotype (test code 10642) alone is not recommended to predict AD risk.60,61 These tests can be ordered alongside other AD-Detect tests.
Compared to the most common combination of ApoE proteoforms (E3/E3 phenotype)
- E2/E2 and E2/E3 phenotypes (ε2/ε2 and ε2/ε3 genotypes) suggest lower-than-average AD risk
- E2/E4 and E3/E4 phenotypes (ε2/ε4 and ε3/ε4 genotypes) suggest higher-than-average AD risk
Compared with all other phenotypes, an E4/E4 (homozygous) phenotype (ε4/ ε4 genotype) may confer the highest AD risk; homozygosity has been suggested to be a genetically distinct form of AD.62
Risk for ARIA is higher in individuals who are receiving anti-amyloid monoclonal antibody therapy and have the ApoE4 proteoform-specific peptide, especially the E4/E4 phenotype.57
Phenotyping results should be considered knowing that patient sex, environment, race, and ethnicity, as well as the presence of other risk alleles, also contribute to AD risk associated with the ApoE phenotype/APOE genotype.33,34
CSF–based tests
Beta-amyloid 42/40 ratio and ApoE
The Beta-Amyloid 42/40 Ratio and Apolipoprotein E (ApoE) Isoform Panel, CSF (test code 94628), combines results for these biomarkers into a model to assess the risk for adults exhibiting signs of MCI or dementia having AD. Panel components can be ordered separately: Beta-Amyloid 42/40 Ratio, CSF (test code 94627) or Apolipoprotein E (APOE) Isoform, CSF (test code 94626). If only phenotyping or genotyping is required, consider plasma tests for less invasive specimen collection.
The clinical performance measures for Aβ42/40 ratio in CSF were developed using a population predominantly >50 years old, including individuals with AD (n=102), MCI (n=37), mixed LBD–AD dementia (n=9), LBD (n=10), FTD (n=7), progressive supranuclear palsy (n=3), corticobasal degeneration (n=1), and normal cognition (n=130).63 PET data were not available for all of these individuals, so performance relates to diagnosis rather than PET status.
An Aβ42/40 ratio cutoff of <0.16 had a clinical sensitivity of 78% for distinguishing patients with AD from those with non–AD dementia (clinical specificity, 91%) and from those with normal cognition (clinical specificity, 81%). The Aβ42/40 ratio decreased significantly (P <.001) with increasing dose of APOE4 alleles.63
Based on these data, a model was developed (test code 94628) to examine the biomarkers separately and combined into a risk score to determine the risk that a patient has AD (Table 3).
Table 3. CSF Biomarkers and Risk of Having AD [return to contents]
| Biomarker | AD likelihood |
||
| Lower | Average | Higher | |
ApoE proteoform |
E2a |
E3a |
E4 |
Aβ42/40 |
≥0.16 |
NAb |
<0.16 |
Risk assessment score |
<-0.918 |
-0.918 to 1.419 |
>1.419 |
| Aβ42/40, beta-amyloid (1-42)/beta-amyloid (1-40); ApoE, apolipoprotein; CSF, cerebral spinal fluid; NA, not applicable | |
| a | In the absence of E4. |
| b | As a single-cutpoint test, there is no average likelihood. |
p-tau/total-tau/Aβ42
The ADmark® Phospho-Tau/Total-Tau/A Beta42, Analysis and Interp, CSF (Symptomatic) test (test code 92433) uses immunoassay to correlate p-tau, total-tau, and Aβ42 levels in CSF.
Meta-analysis of 231 studies, comprising nearly 30,000 individuals, indicated that CSF from patients with AD has levels of p-tau about 1.9-times higher, total-tau 2.5-times higher, and Aβ42 0.56-times lower than CSF from healthy control individuals.64 These differences were similarly reflected in comparing individuals with MCI-AD vs stable MCI; p-tau levels were 1.7-fold higher, total-tau was 1.8-fold higher, and Aβ42 was 0.7-fold lower in CSF from patients with stable MCI.64
Importantly, racial differences have been observed, with lower tau CSF biomarkers in Black MCI patients compared with those in White MCI patients, which could affect their eligibility for clinical trial participation.65 Consequently, higher Aβ42 and lower tau cutoffs were proposed for Black vs White patients. Fortunately, CSF Aβ42/tau ratios appear less affected by race.65
The ADmark® test computes an amyloid tau index (ATI) using the CSF concentrations (pg/mL) of Aβ42 and total tau in CSF66 based in part on a model developed using a cohort of US and European patients with AD. The ATI normalizes Aβ42 concentration such that an ATI threshold <1.0 suggests the presence of AD.67 It provides a sensitivity of 85% for identifying AD-dementia and provides a specificity of 86% for distinguishing AD from non-AD disorders, 87% from healthy control individuals, and 58% from non-AD dementia.68
Non-AD dementia and dementia-like symptoms
Non-AD dementia and dementia-like symptoms can have several etiologies, some of which are treatable and reversible. US and European guidelines recommend laboratory testing to assess these conditions as well as comorbidities that often accompany dementia.8,9 Quest offers Dementia Panel, Secondary Causes (test code 34541) that includes recommended testing for folate, vitamin B12, thyroid-stimulating hormone, calcium, glucose, complete blood cell count, and renal and liver function tests.
Infectious disease testing is also recommended for atypical presentation or clinical features suggestive of syphilis (test code 36126), Lyme disease (test code 34194), or HIV infection (test code 91431).9 An algorithmic approach has been published for incorporating most of these tests in evaluation of suspected dementia.7 Tests are also available for other possible infectious disease causes of dementia, including prion disease (test code 37989),10 as described in Table 2.
References [return to contents]
- Fang M, Hu J, Weiss J, et al. Lifetime risk and projected burden of dementia. Nat Med. 2025;31(3):772-776. doi:10.1038/s41591-024-03340-9
- Mukadam N, Wolters FJ, Walsh S, et al. Changes in prevalence and incidence of dementia and risk factors for dementia: an analysis from cohort studies. Lancet Public Health. 2024;9(7):e443-e460. doi:10.1016/S2468-2667(24)00120-8
- Stallard PJE, Ukraintseva SV, Doraiswamy PM. Changing story of the dementia epidemic. JAMA. 2025:;333(18):1579-1580. doi:10.1001/jama.2025.1897
- 2024 Alzheimer's disease facts and figures. Alzheimers Dement. 2024;20(5):3708-3821. doi:10.1002/alz.13809
- American Psychiatric Association. Neurocognitive disorders. In:. Diagnostic and Statistical Manual of Mental Disorders Text Revision DSM-5-TR™. 5th ed. American Psychiatric Association Publishing; 2022:667-732. doi:10.1176/appi.books.9780890425787.x17_Neurocognitive_Disorders
- Sachdev PS, Blacker D, Blazer DG, et al. Classifying neurocognitive disorders: the DSM-5 approach. Nat Rev Neurol. 2014;10(11):634-642. doi:10.1038/nrneurol.2014.181
- Falk N, Cole A, Meredith TJ. Evaluation of suspected dementia. Am Fam Physician. 2018;97(6):398-405.
- Knopman DS, DeKosky ST, Cummings JL, et al. Practice parameter: diagnosis of dementia (an evidence-based review). Report of the quality standards subcommittee of the American Academy of Neurology. Neurology. 2001;56(9):1143-1153. doi:10.1212/wnl.56.9.1143
- Sorbi S, Hort J, Erkinjuntti T, et al. EFNS-ENS Guidelines on the diagnosis and management of disorders associated with dementia. Eur J Neurol. 2012;19(9):1159-1179. doi:10.1111/j.1468-1331.2012.03784.x
- Almeida OP, Lautenschlager NT. Dementia associated with infectious diseases. Int Psychogeriatr. 2005;17 Suppl 1:S65-77. doi:10.1017/s104161020500195x
- Morley JE, Morris JC, Berg-Weger M, et al. Brain health: the importance of recognizing cognitive impairment: an IAGG consensus conference. J Am Med Dir Assoc. 2015;16(9):731-739. doi:10.1016/j.jamda.2015.06.017
- Budd Haeberlein S, Aisen PS, Barkhof F, et al. Two randomized phase 3 studies of aducanumab in early Alzheimer's Disease. J Prev Alzheimers Dis. 2022;9(2):197-210. doi:10.14283/jpad.2022.30
- Albert MS, DeKosky ST, Dickson D, et al. 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. 2011;7(3):270-279. doi:10.1016/j.jalz.2011.03.008
- McKhann GM, Knopman DS, Chertkow H, et al. 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. 2011;7(3):263-269. doi:10.1016/j.jalz.2011.03.005
- Bondi MW, Edmonds EC, Jak AJ, et al. Neuropsychological criteria for mild cognitive impairment improves diagnostic precision, biomarker associations, and progression rates. J Alzheimers Dis. 2014;42(1):275-289. doi:10.3233/JAD-140276
- McDougall F, Edgar C, Mertes M, et al. Psychometric properties of the clinical dementia rating - sum of boxes and other cognitive and functional outcomes in a prodromal Alzheimer's disease population. J Prev Alzheimers Dis. 2021;8(2):151-160. doi:10.14283/jpad.2020.73
- Whitfield T, Chouliaras L, Morrell R, et al. The criteria used to rule out mild cognitive impairment impact dementia incidence rates in subjective cognitive decline. Alzheimers Res Ther. 2024;16(1):142. doi:10.1186/s13195-024-01516-6
- Jack CR, Jr., Andrews JS, Beach TG, et al. Revised criteria for diagnosis and staging of Alzheimer's disease: Alzheimer's Association Workgroup. Alzheimers Dement. 2024;20(8):5143-5169. doi:10.1002/alz.13859
- Lewczuk P, Matzen A, Blennow K, et al. Cerebrospinal fluid Aβ42/40 corresponds better than Aβ42 to amyloid PET in Alzheimer's disease. J Alzheimers Dis. 2017;55(2):813-822. doi:10.3233/JAD-160722
- Zetterberg H, Burnham SC. Blood-based molecular biomarkers for Alzheimer's disease. Mol Brain. 2019;12(1):26. doi:10.1186/s13041-019-0448-1
- Janelidze S, Teunissen CE, Zetterberg H, et al. Head-to-head comparison of 8 plasma amyloid-β 42/40 assays in Alzheimer disease. JAMA Neurol. 2021:e213180. doi:10.1001/jamaneurol.2021.3180
- Thijssen EH, Joie RL, Strom A, et al. Plasma phosphorylated tau 217 and phosphorylated tau 181 as biomarkers in Alzheimer's disease and frontotemporal lobar degeneration: a retrospective diagnostic performance study. The Lancet Neurology. 2021;20(9):739-752. doi:10.1016/s1474-4422(21)00214-3
- Mielke MM, Dage JL, Frank RD, et al. Performance of plasma phosphorylated tau 181 and 217 in the community. Nature Medicine. 2022;28(7):1398-1405. doi:10.1038/s41591-022-01822-2
- Ashton NJ, Brum WS, Molfetta GD, et al. Diagnostic accuracy of a plasma phosphorylated tau 217 immunoassay for Alzheimer disease pathology. JAMA Neurology. 2024;81(3):255-263. doi:10.1001/jamaneurol.2023.5319
- Palmqvist S, Janelidze S, Quiroz YT, et al. Discriminative accuracy of plasma phospho-tau217 for Alzheimer disease vs other neurodegenerative disorders. JAMA. 2020;324(8):772-781. doi:10.1001/jama.2020.12134
- Therriault J, Ashton NJ, Pola I, et al. Comparison of two plasma p-tau217 assays to detect and monitor Alzheimer’s pathology. eBioMedicine. 2024;102:105046. doi:10.1016/j.ebiom.2024.105046
- Hu Y, Cho M, Sachdev P, et al. Fluid biomarkers in the context of amyloid-targeting disease-modifying treatments in Alzheimer's disease. Med. 2024;5(10):1206-1226. doi:10.1016/j.medj.2024.08.004
- Jack CR, Bennett DA, Blennow K, et al. NIA-AA Research Framework: toward a biological definition of Alzheimer's disease. Alzheimers Dement. 2018;14(4):535-562. doi:10.1016/j.jalz.2018.02.018
- Mattsson N, Cullen NC, Andreasson U, et al. Association between longitudinal plasma neurofilament light and neurodegeneration in patients with Alzheimer disease. JAMA Neurology. 2019;76(7):791-799. doi:10.1001/jamaneurol.2019.0765
- Holper S, Loveland P, Churilov L, et al. Blood astrocyte biomarkers in Alzheimer disease: a systematic review and meta-analysis. Neurology. 2024;103(3):e209537. doi:10.1212/WNL.0000000000209537
- Nisenbaum L, Martone R, Chen T, et al. CSF biomarker concordance with amyloid PET in phase 3 studies of aducanumab. Alzheimers Dement. 2023;19(8):3379-3388. doi:10.1002/alz.12919
- Rabe C, Bittner T, Jethwa A, et al. Clinical performance and robustness evaluation of plasma amyloid-beta(42/40) prescreening. Alzheimers Dement. 2023;19(4):1393-1402. doi:10.1002/alz.12801
- Neu SC, Pa J, Kukull W, et al. Apolipoprotein E genotype and sex risk factors for Alzheimer Disease: a meta-analysis. JAMA Neurol. 2017;74(10):1178-1189. doi:10.1001/jamaneurol.2017.2188
- Reitz C, Pericak-Vance MA, Foroud T, et al. A global view of the genetic basis of Alzheimer disease. Nat Rev Neurol. 2023;19(5):261-277. doi:10.1038/s41582-023-00789-z
- Hampel H, O'Bryant SE, Molinuevo JL, et al. Blood-based biomarkers for Alzheimer disease: mapping the road to the clinic. Nat Rev Neurol. 2018;14(11):639-652. doi:10.1038/s41582-018-0079-7
- Schindler SE, Galasko D, Pereira AC, et al. Acceptable performance of blood biomarker tests of amyloid pathology - recommendations from the Global CEO Initiative on Alzheimer's Disease. Nat Rev Neurol. 2024;20(7):426-439. doi:10.1038/s41582-024-00977-5
- Roberts RO, Aakre JA, Kremers WK, et al. Prevalence and outcomes of amyloid positivity among persons without dementia in a longitudinal, population-based setting. JAMA Neurol. 2018;75(8):970-979. doi:10.1001/jamaneurol.2018.0629
- Weber DM, Stroh MA, Taylor SW, et al. Development and clinical validation of blood-based multibiomarker models for the evaluation of brain amyloid pathology. medRxiv. doi:10.1101/2025.02.27.25322892
- Figdore DJ, Griswold M, Bornhorst JA, et al. Optimizing cutpoints for clinical interpretation of brain amyloid status using plasma p-tau217 immunoassays. Alzheimers Dement. 2024;20(9):6506-6516. doi:10.1002/alz.14140
- Meyer MR, Kirmess KM, Eastwood S, et al. Clinical validation of the PrecivityAD2 blood test: a mass spectrometry-based test with algorithm combining %p-tau217 and Abeta42/40 ratio to identify presence of brain amyloid. Alzheimers Dement. 2024;20(5):3179-3192. doi:10.1002/alz.13764
- Weber DM, Taylor SW, Lagier RJ, et al. Clinical utility of plasma Aβ42/40 ratio by LC-MS/MS in Alzheimer’s disease assessment. Front Neurol. 2024;15:1364658. doi:10.3389/fneur.2024.1364658
- Antonioni A, Raho EM, Manzoli L, et al. Blood phosphorylated Tau181 reliably differentiates amyloid-positive from amyloid-negative subjects in the Alzheimer's disease continuum: a systematic review and meta-analysis. Alzheimers Dement (Amst). 2025;17(1):e70068. doi:10.1002/dad2.70068
- Therriault J, Vermeiren M, Servaes S, et al. Association of phosphorylated tau biomarkers with amyloid positron emission tomography vs tau positron emission tomography. JAMA Neurology. 2023;80(2):188-199. doi:10.1001/jamaneurol.2022.4485
- Mattsson-Carlgren N, Janelidze S, Palmqvist S, et al. Longitudinal plasma p-tau217 is increased in early stages of Alzheimer’s disease. Brain. 2020;143(11):3234-3241. doi:10.1093/brain/awaa286
- Palmqvist S, Tideman P, Cullen N, et al. Prediction of future Alzheimer’s disease dementia using plasma phospho-tau combined with other accessible measures. Nature Medicine. 2021;27(6):1034-1042. doi:10.1038/s41591-021-01348-z
- Janelidze S, Mattsson N, Palmqvist S, et al. Plasma p-tau181 in Alzheimer's disease: relationship to other biomarkers, differential diagnosis, neuropathology and longitudinal progression to Alzheimer's dementia. Nat Med. 2020;26(3):379-386. doi:10.1038/s41591-020-0755-1
- Palmqvist S, Stomrud E, Cullen N, et al. An accurate fully automated panel of plasma biomarkers for Alzheimer's disease. Alzheimers Dement. 2023;19(4):1204-1215. doi:10.1002/alz.12751
- Karikari TK, Pascoal TA, Ashton NJ, et al. Blood phosphorylated tau 181 as a biomarker for Alzheimer's disease: a diagnostic performance and prediction modelling study using data from four prospective cohorts. Lancet Neurol. 2020;19(5):422-433. doi:10.1016/S1474-4422(20)30071-5
- Vacchiano V, Mastrangelo A, Zenesini C, et al. Elevated plasma p-tau181 levels unrelated to Alzheimer's disease pathology in amyotrophic lateral sclerosis. J Neurol Neurosurg Psychiatry. 2023;94(6):428-435. doi:10.1136/jnnp-2022-330709
- Khalil M, Teunissen CE, Lehmann S, et al. Neurofilaments as biomarkers in neurological disorders — towards clinical application. Nature Reviews Neurology. 2024;20(5):269-287. doi:10.1038/s41582-024-00955-x
- Ashton NJ, Janelidze S, Khleifat AA, et al. A multicentre validation study of the diagnostic value of plasma neurofilament light. Nature Communications. 2021;12(1):3400. doi:10.1038/s41467-021-23620-z
- Ducharme S, Dols A, Laforce R, et al. Recommendations to distinguish behavioural variant frontotemporal dementia from psychiatric disorders. Brain. 2020;143(6):1632-1650. doi:10.1093/brain/awaa018
- Feneberg E, Oeckl P, Steinacker P, et al. Multicenter evaluation of neurofilaments in early symptom onset amyotrophic lateral sclerosis. Neurology. 2018;90(1):e22-e30. doi:10.1212/wnl.0000000000004761
- Angelopoulou E, Bougea A, Papadopoulos A, et al. CSF and circulating NfL as biomarkers for the discrimination of Parkinson disease from atypical parkinsonian syndromes. Neurology: Clinical Practice. 2021;11(6):e867-e875. doi:10.1212/cpj.0000000000001116
- Abdelhak A, Foschi M, Abu-Rumeileh S, et al. Blood GFAP as an emerging biomarker in brain and spinal cord disorders. Nat Rev Neurol. 2022;18(3):158-172. doi:10.1038/s41582-021-00616-3
- Weber DM, Kim JC, Goldman SM, et al. New plasma LC-MS/MS assays for the quantitation of beta-amyloid peptides and identification of apolipoprotein E proteoforms for Alzheimer's disease risk assessment. J Investig Med. 2024;72(5):465-474. doi:10.1177/10815589241246537
- Cummings J, Apostolova L, Rabinovici GD, et al. Lecanemab: appropriate use recommendations. J Prev Alzheimers Dis. 2023;10(3):362-377. doi:10.14283/jpad.2023.30
- Aducanumab discontinued as an Alzheimer's treatment. Alzheimer's Association. Accessed March 20, 2025. https://www.alz.org/alzheimers-dementia/treatments/aducanumab
- LEQEMBI® (lecanemab-irmb) injection. Prescribing information. Eisai Inc; July 2023. Accessed March 20, 2025. https://www.leqembi.com/-/media/Files/Leqembi/Prescribing-Information.pdf?hash=77aa4a86-b786-457a-b894-01de37199024
- Goldman JS, Hahn SE, Catania JW, et al. Genetic counseling and testing for Alzheimer disease: joint practice guidelines of the American College of Medical Genetics and the National Society of Genetic Counselors. Genet Med. 2011;13(6):597-605. doi:10.1097/GIM.0b013e31821d69b8
- Goldman JS, Hahn SE, Catania JW, et al. ADDENDUM: Genetic counseling and testing for Alzheimer disease: joint practice guidelines of the American College of Medical Genetics and the National Society of Genetic Counselors. Genet Med. 2019;21(10):2404. doi:10.1038/s41436-019-0559-1
- Fortea J, Pegueroles J, Alcolea D, et al. APOE4 homozygozity represents a distinct genetic form of Alzheimer's disease. Nat Med. 2024;30(5):1284-1291. doi:10.1038/s41591-024-02931-w
- Weber DM, Tran D, Goldman SM, et al. High-throughput mass spectrometry assay for quantifying β-amyloid 40 and 42 in cerebrospinal fluid. Clin Chem. 2019;65(12):1572-1580. doi:10.1373/clinchem.2018.300947
- Olsson B, Lautner R, Andreasson U, et al. CSF and blood biomarkers for the diagnosis of Alzheimer's disease: a systematic review and meta-analysis. Lancet Neurol. 2016;15(7):673-684. doi:10.1016/S1474-4422(16)00070-3
- Garrett SL, McDaniel D, Obideen M, et al. Racial disparity in cerebrospinal fluid amyloid and tau biomarkers and associated cutoffs for mild cognitive impairment. JAMA Netw Open. 2019;2(12):e1917363. doi:10.1001/jamanetworkopen.2019.17363
- Oboudiyat C, Gefen T, Varelas E, et al. Cerebrospinal fluid markers detect Alzheimer's disease in nonamnestic dementia. Alzheimers Dement. 2017;13(5):598-601. doi:10.1016/j.jalz.2017.01.006
- Tariciotti L, Casadei M, Honig LS, et al. Clinical experience with cerebrospinal fluid Abeta42, total and phosphorylated tau in the evaluation of 1,016 individuals for suspected dementia. J Alzheimers Dis. 2018;65(4):1417-1425. doi:10.3233/JAD-180548
- Hulstaert F, Blennow K, Ivanoiu A, et al. Improved discrimination of AD patients using beta-amyloid(1-42) and tau levels in CSF. Neurology. 1999;52(8):1555-1562. doi:10.1212/wnl.52.8.1555
Content reviewed 4/2025