PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Prog Neurobiol. Author manuscript; available in PMC 2012 December 1.
Published in final edited form as:
PMCID: PMC3173583
NIHMSID: NIHMS293089

Biomarkers in Frontotemporal Lobar Degenerations – Progress and Challenges

William T. Hu, MD, PhD,1 John Q. Trojanowski, MD, PhD,2 and Leslie M. Shaw, PhD2

Abstract

Neuronal and glial changes associated with tau, TAR DNA binding protein of ~43 kD (TDP-43), and fused in sarcoma (FUS) together constitute the pathologic spectrum of frontotemporal lobar degeneration (FTLD). Most patients with FTLD present with prominent behavior or language changes, sometimes accompanied by extrapyramidal symptoms or motor neuron disease. Identification of FTLD patients with mutations in genes for tau, TDP-43, and FUS lends strong support for their pathogenic roles in FTLD, and elucidation of their dysfunction will pave the way for development of substrate specific therapy. However, there remains no reliable biomarker for early detection of FTLD or prediction of underlying FTLD pathologic change. Clinical syndromes usually reflects the earliest affected brain regions where atrophy can be visualized on structural MRI, but neither clinical nor structural imaging-based biomarkers has been accurately correlated with underlying pathology on the individual patient level. Biochemical markers in the cerebrospinal fluid (CSF) have also been investigated in FTLD and related disorders, including amyotrophic lateral sclerosis (ALS) and progressive supranuclear palsy (PSP). However, their accuracy and pathologic significance need to be confirmed in future multi-center studies. Here we review the progress made in FTLD biomarkers, including clinical phenotype/feature characterization, neuropsychological analysis, CSF and plasma analytes, and patterns of brain atrophy and network dysfunction detectable on brain imaging. Given the pathologic overlap of FTLD with ALS and PSP, collaboration with specialists in those fields will be essential in the translation of promising FTLD biomarkers into clinical practice.

Keywords: Biomarker, diagnosis, frontotemporal dementia, tau, tauopathy, TDP-43

1. Introduction

Frontotemporal lobar degeneration (FTLD) represents a group of clinically and pathologically heterogeneous disorders, with an estimated prevalence of 3-15/100,000 in adults under the age of 65.(Ratnavalli et al., 2002; Rosso et al., 2003) Traditionally, clinical descriptions of FTLD have largely been restricted to patients with prominent behavior or language disorders. With evolving terminology, these patients have been referred to as having frontotemporal dementia (FTD),(Neary et al., 1998) behavior variant of FTD (bv-FTD),(McKhann et al., 2001; Rascovsky et al., 2007a) primary progressive aphasia (PPA),(Grossman, 2010; Mesulam, 1982, 2001) or language variant of FTD (lv-FTD).(McKhann et al., 2001) The rendering of a specific syndromic diagnosis can be challenging due to the sometimes mixed nature of language and behavioral symptoms in these patients, which is only made more difficult with the recognition that the cognitive FTLD patients can develop additional symptoms in keeping with motor neuron disease or parkinsonian disorders.(Josephs, 2008) The emergence of these non-cognitive symptoms should not come as a surprise, as work in motor neuron disease and movement disorders has independently identified cognitive symptoms in patients with established amyotrophic lateral sclerosis (ALS),(Hu et al., 2009b; Lomen-Hoerth et al., 2002; Strong et al., 2003) corticobasal degeneration (CBD),(Bak et al., 2005; Kertesz et al., 2000; Murray et al., 2007) and progressive supranuclear palsy (PSP)(Bak et al., 2005; Esmonde et al., 1996; Kertesz and McMonagle, 2010) to be similar to those seen in FTLD patients with cognitive-only or cognitive-predominant features. The behavior-language-motor connection in FTLD patients is further strengthened by the observation that patients belonging to the same clinical spectrum tend to share the same pathologic substrate: abnormal accumulation of hyperphosphorylated tau in those with cognitive symptoms and CBD/PSP,(Josephs et al., 2006b; Murray et al., 2007) and abnormal accumulation of hyperphosphorylated and ubiquitinated TAR DNA binding protein of 43 kD (TDP-43) in those with cognitive symptoms and ALS.(Hu et al., 2009b; Josephs et al., 2006b; Neumann et al., 2006) FTLD-TDP and FTLD-Tau each contains multiple subtypes, including subtyping according to patterns of TDP-immunoreactive lesions in FTLD-TDP(Mackenzie et al., 2009; Neumann et al., 2006) and according to predominant tau isoform inclusion and/or affected cellular (neuronal vs. glial) population.(Mackenzie et al., 2009) Even though details on how the different subtypes differ biochemically and clinically from each other within FTLD-TDP or FTLD-Tau still need clarification, the diagnostic groupings of FTLD-TDP and FTLD-Tau account for the majority of patients who present with prominent behavior, language, or motor symptoms who do not have atypical Alzheimer’s disease (AD) or dementia with Lewy bodies (DLB), while a small proportion of FTLD patients without characteristic Tau or TDP-43 immunoreactive changes have pathology associated with fused in sarcoma (FUS).(Urwin et al., 2010)

The relatively recent identification of one protein (TDP-43 or Tau) as the common denominator in a spectrum disorder raises the possibility that the characteristic protein is a late-stage epiphenomenon that likely does not carry pathogenic significance. Evidence against this has come from genetic cases of FTLD in whom the TARDBP (Benajiba et al., 2009; Borroni et al., 2009; Corrado et al., 2009; Kabashi et al., 2008; Kuhnlein et al., 2008; Sreedharan et al., 2008), MAPT(Hutton, 2001), or FUS(Kwiatkowski et al., 2009; Vance et al., 2009) gene is itself mutated. Such cases of FTLD often have cognitive PLUS additional symptoms, such as ALS in families with TARDBP mutations and prominent parkinsonism in patients with MAPT mutations (otherwise referred to as frontotemporal dementia with parkinsonism linked to chromosome 17, or FTDP-17). FTLD cases with mutations in these or other genes invariably have FTLD pathology corresponding to the mutation, although such straightforward clinicopathologic correlation does not exist for most of the sporadic FTLD cases without known mutations. In addition, for reasons that remain enigmatic, familial FTLD caused by mutations in the progranulin gene (PGRN) have TDP-43 inclusions as the underlying neuropathology.(Mackenzie, 2007; Mackenzie et al., 2006) Thus, in elucidating disease mechanisms that link abnormal protein deposition to progressive dementing syndromes with hopes of developing substrate-specific therapies targeting tau or TDP-43, accurate prediction of underlying FTLD pathology is essential for human studies similar to those ongoing in AD(Petersen et al., ; Shaw et al., 2009; Trojanowski et al., 2010b) or Parkinson’s disease (PD)(MJFF, 2010) including but beyond those cases with known mutations. Such a search for pathologic predictors, or diagnostic biomarkers, in FTLD has followed more established directions laid out in AD biomarker research, although no putative FTLD biomarker (for TDP or tau) is currently as reliable as cerebrospinal fluid (CSF) levels of pathology-related proteins(Shaw et al., 2007; Shaw et al., 2009) or even hippocampal volume(Schuff et al., 2009) in AD. Thus, to facilitate our efforts and those of others to confirm and explore the utility of single and combinatorial biomarkers for FTLD diagnosis and prognosis, here we review the recent advances in FTLD biomarker development in terms of clinical, biochemical, and imaging based strategies. As there are few studies on FUS-related biomarkers,(Josephs et al., 2010b) we will focus primarily on biomarkers related to FTLD-TDP and FLTD-Tau.

2. Clinical FTLD biomarkers

Several well-executed surveys on the pathologic substrates for cognitive forms of FTLD have led to generalization on the correlation between clinical syndromes (or phenotypes) and pathologic substrate.(Forman et al., 2006; Hodges et al., 2004; Josephs et al., 2006b; Kertesz et al., 2005) Cases usually come from tertiary referral centers with expertise in cognitive forms of FTLD and associated motor neuron/parkinsonian disorders, although the composition of the autopsy cohort can significantly differ due to referral bias among other reasons. Bias aside, these studies showed a general pathologic predilection for certain subtypes of clinical syndromes (Table 1): patients with progressive non-fluent aphasia (PNFA, also referred to as agrammatic/non-fluent form of PPA) are more likely to have FTLD-Tau than FTLD-TDP, patients with semantic dementia (SD or SemD) or the semantic variant (SV) of PPA often have FTLD-TDP instead of FTLD-Tau, and patients with bv-FTD are as likely to have FTLD-TDP as the cause of their clinical symptoms as FLTD-Tau. While these findings continue to be replicated in most independent clinicopathologic series, it is often challenging to translate these population-level probabilities into clinical practice for the individual patient. For example, while FTLD-Tau is the most common cause for PNFA, atypical AD and FTLD-TDP can also account for significant proportions of patients with agrammatic/non-fluent speech.(Alladi et al., 2007; Forman et al., 2006; Hu et al., 2010e; Mesulam et al., 2008) Further characterization of their non-fluency through detailed language examinations can identify patients who are more likely to have underlying pathology of AD rather than a FTLD,(Gorno-Tempini et al., 2008; Hu et al., 2010e) but such strategy creates another category of heterogeneous pathology.(Mesulam et al., 2008) Importantly, while syndrome-based diagnosis is crucial in the understanding of pathology-behavior relationship,(Gunawardena et al., 2010) assignment of a clinical syndrome does not seem to improve the overall diagnostic accuracy when it comes to pathologic prediction.

Table 1
Clinical syndromes associated with FTLD; pathologic causes shown in decreasing prevalence within each clinical syndrome.

Beyond cognitive forms of FTLD, similar diagnostic challenges have been plaguing clinicopathologic work of CBD which is often viewed as a FTLD spectrum disorder. CBD, as a pathologic diagnosis,(Dickson et al., 2002) was originally hoped to have strong correlations with the clinical syndrome carrying the same name.(Boeve et al., 2003; Litvan et al., 1996) However, even when strict diagnostic criteria are applied, clinical prediction for CBD is poorly sensitive and specific for pathologic changes diagnostic for CBD.(Boeve et al., 1999) In fact, CBD may represent a minor cause of clinically diagnosed cases of corticobasal syndrome (CBS) with a recent study showing a positive predictive value under 25% for the clinical diagnosis.(Ling et al., 2010) These findings have led to a recent re-evaluation of diagnostic criteria for CBD, and it remains unclear if a standard set of clinical criteria can be successfully formulated in spectrum disorders such as CBD. This is best illustrated by examples in the most common form of tau-negative FTLD, i.e. FTLD-TDP. In FTLD-TDP, patients can develop cognitive symptoms of FTLD, motor neuron disease (ALS or primary lateral sclerosis), or both.(Geser et al., 2008; Josephs et al., 2006b; Lomen-Hoerth et al., 2002; Neumann et al., 2006) In patients with cognitive only or cognitive predominant FTLD, strict criteria for ALS (such as modified El Escorial criteria)(Brooks et al., 2000) will not be met for nearly all bv-FTD and SD, including sometimes in cases with pathologic motor neuron involvement.(Josephs et al., 2006a) Similarly, in patients with ALS in whom up to 50% may have minor cognitive symptoms (including 15% with dementia,(Hu et al., 2009b; Lomen-Hoerth et al., 2002), severity of dementia or aphasia may be difficult to determine due to functional impairments from motor deficits.(Geser et al., 2008) Therefore, while additional symptoms in keeping with ALS (such as single limb involvement, prominent fasciculations) or CBD/PSP (apraxia, supranuclear palsy) may be very useful in the prediction of underlying FTLD pathology, a criteria-based approach may leave many patients with otherwise predictable pathology in a category of diagnostic uncertainty.

An extension of feature-based characterization in predicting underlying FTLD pathology involves detailed neuropsychological analysis of patients.(Libon et al., 2007b) While neuropsychological evaluation is commonplace in patients with mild cognitive impairment (MCI) or early AD, (Loewenstein et al., 2006; Petersen et al., 2010) its use in FTLD is more variable(Collette et al., 2007; Hutchinson and Mathias, 2007; Libon et al., 2007a; Libon et al., 2007b; Rogers et al., 2006; Rosen et al., 2004) and few studies have incorporated neuropathologic evaluation as the “gold standard” in pathologic prediction.(Grossman et al., 2008; Rascovsky et al., 2007b) The development and validation of a neuropsychological biomarker (for FTLD-TDP or FTLD-Tau) can be quite discouraging for multiple reasons. First, multiple cognitive domains are often involved in clinical syndromes involving behavior or language impairments (for example, naming and speech praxis in non-fluent speech), and limited standardized batteries are available for these functions in isolation. Second, the main differences between two pathologic groups can be biased by uneven distribution of certain syndromes in each pathologic group. For example, if the FTLD-TDP group has a high number of SD cases, confrontation naming can emerge as a predictor for FTLD-TDP even though confrontation naming is often preserved in bv-FTD due to FTLD-TDP and SD cases account for a small proportion of all FTLD-TDP cases. (Grossman et al., 2007; Grossman et al., 2004) Lastly, multiple autopsy-confirmed studies have shown that patients with the same clinical phenotype can have very similar neuropsychological profiles in terms of absolute impairments that reflect the characteristic deficits for the clinical diagnosis (for example, impairment in praxis or visual-spatial function in CBS, or fluency in PNFA)(Hu et al., 2010e; Hu et al., 2009a; Vanvoorst et al., 2008). While these studies may be discouraging, two observations have revived interests in the development of a neuropsychological biomarker to predict underlying FTLD pathology. First, in one series of autopsy-confirmed cases of FTLD-TDP and FTLD-Tau, it appeared that the relative performance of paired neuropsychological tests can be related to the underlying FTLD pathology: FTLD-TDP patients had more impaired confrontation naming and category fluency than visual spatial function, while FTLD-Tau patients have the opposite pattern.(Grossman et al., 2008) Second, work on structural and functional brain imaging has revealed possible networks of distant brain regions that are preferentially affected by FTLDs.(Listerud et al., 2009; Seeley et al., 2009) When examined together, these two observations raise the possibility that there exist regions in the brain commonly affected by FTLD-TDP or FTLD-Tau irrespective of the clinical phenotype, and neuropsychological evaluation of network-level brain functions can allow for the differentiation between FTLD-TDP and FTLD-Tau.(Listerud et al., 2009) We recently demonstrated the potential of such a comparison when we examined the relative performance on letter-guided fluency and confrontation naming in patients with non-fluent speech and autopsy or CSF AD biomarker confirmation.(Hu et al., 2010e) Whereas direct comparison of cognitive performance did not reveal any difference between those with FTLD vs. AD, we were able to predict underlying AD pathology based on worse relative performance in confrontation naming compared to letter-guided fluency with moderate accuracy. This relative pattern of impairment was subsequently found in patients with CBS due to FTLD or AD,(Gross et al., 2010) which demonstrates preliminary evidence for the syndrome-independent nature of such a neuropsychological biomarker. While the relative performance of paired neuropsychological subtests has not been prospectively tested in FTLD, better characterization of jointly impaired cognitive domains may provide better understanding of FTLD pathology-specific large scale brain networks.

While a phenotype-based diagnostic algorithm has limited sensitivity or specificity for FTLD pathologic prediction, useful information such as prognosis can still be gleaned from a syndromic diagnosis.(Xiong et al., 2010) For example, patients with SD and FTLD-TDP often have longer survival and lower chances of developing motor neuron symptoms than FTLD-TDP patients presenting with bv-FTD.(Hodges et al., 2010; Seeley et al., 2005) These differences may reflect the specific FTLD subtyping, as neurites immunoreactive to TDP-43 are more common in SD than bv-FTD,(Grossman et al., 2007; Hodges et al., 2010). Similarly, survival in patients with ALS (with or without cognitive impairment) is often shorter than those with bv-FTD due to FTLD-TDP, and there continues to be speculation whether prognosis is determined by pathology, clinical syndrome, or both. Given all the possible combinations of clinical syndrome and FTLD pathology, we propose that FTLD patients be not labeled by their presenting phenotype alone. Instead, each patient should be classified according to their main pathologic substrate, possibly through biochemical biomarkers for AD and FTLD, other investigations suggestive of pathology (such as abnormal electromyography for co-existing subclinical ALS), or future biomarker/ technology as they become available, along with their presenting phenotype for monitoring of disease progression.

3. Biochemical FTLD biomarkers

A limited number of biochemical biomarkers have been investigated in cognitive forms of FTLD (Table 2), although many have been identified in related disorders such as ALS and PSP. The earliest attempts to predict underlying FTLD pathology followed strategies proven successful in AD. As tau hyperphosphorylation is a common feature between AD and FTLD-Tau, tau-related AD biomarkers – elevated levels of total tau and hyperphosphorylated tau at threonine 181 (p-tau181) – were examined as potential FTLD biomarkers. In a group of clinically characterized FTLD patients, p-tau181 levels were decreased in these patients compared to control subjects and AD patients.(Vanmechelen et al., 2000) In another group of FTLD patients with detailed neuropathologic analysis, normal levels of CSF tau and p-tau181 levels were again found in patients with FTLD-Tau compared with control subjects, and there was even a trend that total tau levels were decreased in FTLD-Tau cases compared to tau-negative FTLD cases.(Bian et al., 2008) When this was expanded to a larger living cohort (no autopsy confirmation) divided according to likelihood of FTLD-Tau vs. FTLD-TDP based on clinical syndromic diagnosis, the trend persisted but remained non-significant.(Hu & Grossman, unpublished data) Thus, among patients with a FTLD-related clinical syndrome, a normal CSF AD biomarker profile is suggestive of underlying FTLD by ruling out AD pathology. While we and others have employed such approaches to determine group-level differences in hopes of a more homogeneous cohort of FTLD patients than patients classified by clinical syndromes only,(Hu et al., 2010e; Hu et al., 2010f) the occasional detection of altered AD biomarker levels in CSF of patients with clinically unambiguous ALS or genetic cases of FTLD strongly reflects the presence of AD co-pathology in some FTLD cases. Thus, a biomarker positively predictive of FTLD (rather than the absence of a positive biomarker for AD) is essential in a CSF diagnostic algorithm of FTLD. Along that line, levels of structural proteins such as neurofilament heavy and light chains have been found to be elevated in FTLD compared to AD and control subjects at the group level,(Petzold et al., 2007) but its ability to distinguish between potential etiologies at the individual levels remains uncertain.

Table 2
Potential biochemical biomarkers for FTLD or FTLD subtypes. See text for specific references.

Following the identification of TDP-43 as a main ubiquitinated protein in FTLD-TDP, TDP-43 itself has become a target of biomarker discovery. In plasma samples from clinically characterized patients, about half of patients with bv-FTD and a quarter of patients with AD have elevated TDP-43 levels but with significant overlap between the two groups.(Foulds et al., 2008) In clinically defined patients with ALS (with and without dementia), CSF levels of TDP-43 were also elevated at the group level with significant overlap with neurologically healthy control subjects.(Kasai et al., 2009; Steinacker et al., 2008) The low absolute levels of TDP-43 detected also raised questions regarding assay robustness, sensitivity and specificity.(Kasai et al., 2009) To-date, it remains unclear whether plasma or CSF levels of total TDP-43 differ between cases with autopsy confirmation, although highly sensitive measures for phosphorylated species of TDP-43 may yet yield useful findings.

As a major cause for familial FTLD-TDP, progranulin levels have been directly measured in patients with clinical syndromes associated with FTLD as PGRN mutations results in a protein haploinsufficiency.(Baker et al., 2006; Gass et al., 2006) In familial FTLD cases with PGRN mutations, plasma progranulin levels were decreased compared to control subjects.(Finch et al., 2009) This finding has been further extended to cognitively impaired patients homozygous for the T allele of PGRN rs5848, a group of subjects suspected of having increased risks of developing FTLD-TDP.(Hsiung et al., 2010; Rademakers et al., 2008) However, while plasma progranulin levels are decreased in FTLD patients and asymptomatic family members carrying the mutation, progranulin levels in patients with FTLD-related disorders without PGRN mutations remain indistinguishable from control subjects,(Finch et al., 2009) limiting the application of this biomarker in most cases of FTLD-TDP.

We and others have taken more unbiased approaches towards novel biomarker discovery in FTLD (Table 2). Using small groups of clinically characterized FTLD patients without neuropathologic confirmation, putative biomarkers for FTLD have been identified, including granin-like neuroendocrine precursor, apoliprotein E, pigment epithelium derived growth factor, retinol-binding protein, and haptoglobin in one study (with RBP, apoE, and haptoglobin also altered in AD);(Davidsson et al., 2002a; Davidsson et al., 2002b) neurosecretory VGF, cystatin C, transthyretin, and chromogranin B.(Ruetschi et al., 2005) Among these, retinol-binding protein, apoliprotein E, haptoglobin, VGF, and transthyretin were also altered in AD in similar directions, even though VGF was identified in a separate study to be altered in ALS.(Pasinetti et al., 2006) Chromogranin B is a potential marker for FTLD-TDP as it is associated with increased risk for ALS, (Gros-Louis et al., 2009) and cystatin C showed the most promise in being specific to FTLD (or a FTLD subtype) with an opposite direction of change from AD patients.(Ruetschi et al., 2005) As part of a larger targeted proteomic study,(Hu et al., 2010b) we measured CSF levels of 151 proteins in multiplexed immunoassays in 23 patients with autopsy-confirmed FTLD-TDP or FTLD-Tau, along with 80 living patients with a clinical syndrome suggestive of underlying FTLD pathology (bv-FTD, PPA, CBS) whose CSF levels of AD-biomarkers are not suggestive of AD pathology. (Hu et al., 2010d) Similar to the prior study, we did not see a significant difference in total tau levels between autopsy-confirmed cases of FTLD-TDP and FTLD-Tau despite a similar trend. At the same time, levels of a number of proteins differed between the two main pathologic FTLD groups, including neuropeptides (agouti-related peptide, adrenocorticotropic hormone), members of the apoptotic pathways (Fas, TRAIL-R3), inflammatory chemokines (macrophage derived chemokine, IL-17, IL-23), structural protein (S100b), and apolipoprotein B. Whereas patterns of tau and Aβ42 change in AD likely reflect the early pathogenic processes (soluble tau release and Aβ42 deposition), some alterations we observed in FTLD may instead reflect downstream effects of disease. This hypothesis is based on the observation that many of these altered peptides derive from similar biological pathways, such as the agouti-related peptide pathway (AgRP, ACTH) and the IL-17 releasing T-cell pathway (IL-17, IL-23). Using random forests analysis, we were able to achieve moderate sensitivity (86%) and specificity (78%) in the distinction between FTLD-TDP and FTLD-Tau cases. We were also able to classify patients with clinical FTLD syndromes into those likely to have FTLD-TDP or FTLD-Tau, with a trend that is consistent with the probabilistic model from previous clinicopathologic studies (SD having the highest percentage of patients predicted to have FTLD-TDP, and PNFA and CBS having the smallest percentage of patients predicted to have FTLD-TDP). While this panel of diagnostic biomarkers awaits validation in a larger cohort to be recruited and characterized in a multi-center design to begin in 2011, this panel perhaps represents a more mature CSF-based diagnostic biomarker combination for pathologic FTLD subtyping. If successful, plasma-based biomarkers to distinguish between FTLD-TDP and FTLD-Tau can then be developed using patients with CSF suggestive of one or the other FTLD subtype.

CSF biomarkers have also been examined in disorders related to FTLD-Tau (PSP) or FTLD-TDP (ALS). There are fewer studies of CSF biomarkers for PSP, possibly due to the relatively high clinical diagnostic accuracy for PSP compared to other FTLD spectrum disorders.(Josephs and Dickson, 2003; Josephs et al., 2006b; Litvan et al., 1996) Among available studies, one initially promising biomarker in PSP, complement factor 4d, was also found to be elevated in ALS.(Tsuboi and Yamada, 1994; Yamada et al., 1994) A subsequent study on PSP (including 21 clinical PSP and 20 CBS cases) showed a decreased ratio of the truncated form of tau to full length tau in PSP only (but not in CBS).(Borroni et al., 2008) This and FTLD-Tau. As discussed above, IL-17 is released by T-cells whose differentiation from immature T-cells depended on IL-23, and paralleled changes in IL-17 and IL-23 in CSF of FTLD-TDP strongly suggests this to be a pathway likely common to the FTLD-ALS spectrum of TDP-43 proteinopathy. In terms of MCP-1, its levels significantly correlated with Fas levels in the CSF which differed between the two main FTLD subtypes.(Hu et al., 2010d) Thus, similar to what we observed in a targeted proteomic AD biomarker study,(Hu et al., 2010c) certain diagnostic analytes (biomarkers) may serve as proxy for pathways specifically altered in one or more types of neurodegenerative disorders. Comparison of different biomarker studies should then incorporate pathway analysis for proteins of known function for agreement across studies. Furthermore, changes in biologically active processes or pathways – suggested by parallel changes in analytes from the same pathways – may complement pathologic prediction based purely on combinations of functionally unrelated analytes.

Unbiased evaluation of total proteomes from model systems over-expressing TDP-43 or human tissues has also identified potential biomarkers for FTLD. In an in vitro model expressing TDP-43, two clusters of proteins – those involved in nuclear RNA splicing and those involved in cytoplasmic translation initiation and elongation – were found to be interacting directly with TDP-43.(Freibaum et al., 2010) Some of these proteins have been implicated in human leukoencephalopathies, and may represent the missing link between abnormal TDP-43 accumulation and aspects of large scale brain dysfunction. In another study using post-mortem human brain tissues, direct comparison of 10,000 proteins using mass spectrometry revealed over 200 proteins that differed in levels between FTLD-TDP and FTLD-Tau (unpublished data, Gozal YM, Seyfriend NT, et al.). The identification of these proteins will undoubtedly improve our understanding of the pathogenic processes involved in FTLD-TDP and FTLD-Tau. Some cytoplasmic proteins may also be released into the CSF during early neuronal dysfunction or upon yielded a sensitivity of 87% and specificity of 86% for the CSF diagnosis of PSP. However, as PSP is a common pathologic cause for clinically diagnosed cases of bv-FTD and CBS,(Forman et al., 2006; Josephs et al., 2006b) this finding may reflect differential neuroanatomic involvement in motor-predominant forms of PSP rather than a molecular signature of PSP pathology, and this finding was not replicated in another independent cohort of PSP subjects.(Kuiperij and Verbeek, 2010) Another promising biomarker may be CSF orexin, as its levels were found to be decreased in clinical cases of both PSP and CBS compared to control subjects and patients with PD,(Yasui et al., 2006) and no different between ALS patients and control subjects.(Van Rooij et al., 2009) While orexin levels have not been examined directly in patients with more cognitive-predominant forms of FTLD-TDP or FLTD-Tau, it likely deserves attention in follow-up studies given the paucity of potential biomarkers for tauopathies.

In contrast to PSP, a larger numbers of potential CSF biomarkers have been identified for ALS, including inflammatory proteins (GM-CSF,(Mitchell et al., 2009) G-CSF,(Mitchell et al., 2009) MCP-1,(Kuhle et al., 2009; Mitchell et al., 2009) MIP-1a/b,(Mitchell et al., 2009) interferon γ, IL-2, IL-6, IL-8, IL-10, IL-15, and IL-17(Kuhle et al., 2009; Mitchell et al., 2009)), axonal structural proteins (neurofilament light chain(Zetterberg et al., 2007)), growth factors (FGF basic protein and VEGF(Mitchell et al., 2009)), cystatin C,(Pasinetti et al., 2006) insulin-like growth factor 1,(Bilic et al., 2006) erythropoietin,(Brettschneider et al., 2006) and angiotensin II.(Kawajiri et al., 2009) Few of these analytes have been tested in a multi-group basis to include other neurodegenerative disorders such as AD, PD, or DLB, and thus their specificity in predicting TDP-43 proteinopathy remains uncertain. At the same time, some interesting trends emerged when we analyzed together findings from multiple proteomic studies of clinical FTD or pathologic FTLD cases. Among potential TDP-43 biomarkers identified from ALS cohorts, IL-17 and to a lesser degree MCP-1 were found to differ between FTLD-TDP neuronal death to serve as useful biomarkers. Alternatively, direct unbiased proteomic characterization of CSF from patients with known FTLD-TDP (such as ALS with dementia) or FTLD-Tau (such as genetically confirmed cases of FTDP-17) can yield practical CSF biomarkers whose pathologic significance may be less well characterized. The potential utility of such approaches has been demonstrated in animal and human models of familial ALS which yielded galectin-3 as a potential biomarker in ALS,(Zhou et al., 2010b) and may complement targeted proteomic approaches for soluble CSF proteins without an insoluble brain component.

While promising, the characterization of biochemical FTLD biomarkers – identified through hypothesis driven, targeted proteomic, or unbiased proteomic studies – should follow procedures similar to those used in the validation and standardization of AD CSF biomarkers for investigators to realize these potential biomarkers’ clinical application.(Bjerke et al., 2010; Trojanowski et al., 2010b) For each analyte or analyte combination, these include determining the effect of collection tube material,(Andreasen et al., 1999) post-lumbar puncture centrifugation,(Bjerke et al., 2010) storage temperature (room temperature, 4°C, −20°C, −80°C),(Bjerke et al., 2010; Mattsson et al., 2009) repeated freeze-thawing cycles, immunoassay specificity and reproducibility within and across assay runs (Trojanowski et al., 2010b) in addition to factors including age, gender, and genetic influences (such as TMEM106b genotype).(Van Deerlin et al., 2010; Vass et al., 2010) Beyond AD, such effort has begun to take place in ALS,(Wuolikainen et al., 2009) but not in FTLD itself. As we and our collaborators aim to validate the robustness, sensitivity, and specificity of immunoassays for promising CSF-based FTLD biomarkers, these factors must be addressed empirically. Specifically, a multi-center standardization effort will be necessary for assay reproducibility, preferably using aliquots from pooled human samples from subjects with different neurodegenerative disorders. In the multi-center Alzheimer’s Disease Neuroimaging Initiative (ADNI), such work involving seven centers showed coefficients of variation (CVs) of 5.3% for CSF Aβ1-42, 6.7% for t-tau, and 10.8% for p-tau181 within centers; and 17.9% for Aβ42, 13.1% for t-tau, and 14.6% for p-tau181 across centers.(Shaw et al., 2011) In the world wide multicenter standardization effort, inter-center CVs were 21% for Aβ1-42, 15% for t-tau, and 9% for p-tau.(Verwey et al., 2009) While system-based standardization efforts are underway in multiple collaborative studies to further reduce these CVs,(Mattsson et al., 2010; Verwey et al., 2009) values shown from the seven-center ADNI round robin set the benchmark for biomarker assay reproducibility. As summarized recently,(Poste, 2011) assay standardization is especially important as biochemical markers become routinely used as entry criteria or end points for substrate-specific therapeutic trials. As we and others have discovered, multiple pre-analytical and analytical factors can affect the reproducibility of immunoassays for candidate biomarkers, including freeze-thawing cycles, thawing condition (time, room temperature vs. 4°C), extent of handling (including vortexing and centrifugation), strict adherence to the methodologic protocol, dilutional nonlinearity, pipetting equipment and technique, and incubation time, temperature, and buffer.(Mattsson et al., 2010; Shaw et al., 2011) While some of these factors may be chosen out of convenience, an empirical approach may be necessary to identify reproducible biomarker assays for translation into clinical use.

4. Imaging FTLD biomarkers

Early work in imaging studies of FTLD began after the observation that patients with bv-FTD often have prominent atrophy in the frontal or temporal lobar regions. This is thought to be sufficiently distinct from AD to be in clinical use as a practical predictor of FTLD-related dementias. However, clinicopathologic studies have subsequently shown that while such differences can be consistently demonstrated on the group level, it often is unreliable on an individual level for syndromic or pathologic prediction even by experienced radiologists.(Mendez et al., 2007; Suarez et al., 2009) This may be due to inclusion of slowly progressive forms of FTD,(Davies et al., 2006) the occasional finding of no obvious atrophy on MRI,(Kipps et al., 2007; Koedam et al., 2010) or the overlap between atrophy in FTLD and atrophy in normal aging.(Chow et al., 2008) Thus, there has been escalating effort to identify a more reliable imaging measure of FTLD pathology using available imaging modalities beyond visual evidence of frontotemporal atrophy.

Patterns of structural atrophy in FTLD have been examined both in terms of clinical syndromes and pathologic substrates. Along syndromic divisions, atrophy is generally observed in regions associated with the most prominent clinical feature, such as atrophy in the right dorsolateral prefrontal cortex,(Rosen et al., 2002a) anterior cingulate cortex, and insula in bv-FTD (Table 3). Certain behavioral characteristics common in bv-FTD can be referred to these regions, such as disinhibition with orbitofrontal and right medial temporal limbic structure atrophy,(Zamboni et al., 2008) apathy with dorso-lateral pre-frontal atrophy (Zamboni et al., 2008), and poor emotional comprehension with right amygdala and orbitofrontal atrophy. (Rosen et al., 2002b) At the same time, frontal atrophy is often found in cognitively normal control subjects, and right frontal lobe atrophy may lack sufficient specificity for bv-FTD.(Chow et al., 2008) Similar patterns of group-level atrophy along clinical FTLD syndromes have been reported, including left or bilateral anterior temporal atrophy in SD, left-perisylvian region for PNFA, left temporal parietal junction for logopenic progressive aphasia (LPA),(Gorno-Tempini et al., 2008; Hu et al., 2010e; Mesulam et al., 2008) right or bilateral parietal atrophy in CBS,(Josephs et al., 2004) and brainstem atrophy in PSP.(Josephs et al., 2008) Comparison of atrophic patterns between different pathologic FTLD groups is more challenging, as most studies had consecutive or convenient case combinations of FTLD-TDP and FTLD-Tau cases which can be biased towards local clinical expertise or patient subgroups with higher autopsy rates. Findings from these studies also reflected more the most prevalent clinical syndrome within each pathologic group, and may be difficult to be generalized to a structural signature for a given FTLD pathology.

Table 3
Regions of brain atrophy associated with FTLD and behavioral alteration(s) correlated with each region. See text for specific references.

A few studies have focused on different atrophic patterns among patients with similar clinical syndromes along pathologic diagnoses. Compared to patients with pathologic AD, autopsy-confirmed cases of FTLD had more atrophy in frontal lobar regions, anterior cingulate gyri, and the insula.(Rabinovici et al., 2007) When cases of FTLD-TDP and FTLD-Tau – both clinically characterized by prominent behavior symptoms – were directly compared in two separate studies, no significant pattern of atrophy was sufficient to differentiate between the two pathologic groups.(Kim et al., 2007; Whitwell et al., 2004) However, when each specific pathologic diagnosis was examined individually, certain patterns were identified: atrophy in the bilateral orbitofrontal cortices, posterior superior temporal lobes, and posterior fusiform gyri in FTLD-TDP; bilateral dorsolateral prefrontal atrophy in Pick’s disease with Pick bodies; right temporal and orbitofrontal atrophy in FTDP-17; frontoparietal cortical regions and subcortical nuclei in CBD; and brainstem, cortical, and adjacent white matter atrophy in PSP.(Whitwell et al., 2007; Whitwell et al., 2005) Whether these findings can be replicated in independent series and whether the group-level difference can be translated into diagnostic biomarkers at the individual level remain to be determined, although such analyses within, instead of across, clinical syndromes can circumvent certain false discoveries associated with syndromic diagnoses. For example, when patients with non-fluent PPA were examined according to autopsy- or CSF AD biomarker information, patients with AD had more posterior atrophy along the peri-sylvian region and patients with FTLD had more anterior atrophy.(Hu et al., 2010e) Similarly, when patients with CBS were examined according to autopsy information, patients with CBS due to CBD and AD both had atrophy in the basal ganglia, but patients with CBS due to AD had more temporal and inferior parietal atrophy.(Josephs et al., 2010a) Within certain clinical syndromes, patterns and severity of atrophy can differentiate between different FTLD pathologic types. Alternatively, comparisons can be made between clinical syndromes sharing the same pattern of dominant lobar atrophy. In one study including 20 patients with right temporal variant of FTD, all 8 patients with bv-FTD had FTLD-Tau, and all 12 patients with SD had FTLD-TDP.(Josephs et al., 2009) This strategy is intriguing since other potential areas of focal atrophy can be preferentially associated with certain clinical syndromes, including left temporal atrophy for SD and bv-FTD, left parietal atrophy for PPA and CBS, and right parietal atrophy for CBS and PCA. Future studies will be necessary for further understanding of such atrophy-syndrome pairing.

Significant progress has been made in other imaging modalities, including functional imaging such as positron emission tomography (PET) using 18F fluorodeoxyglucose (FDG),(Foster et al., 2007; Ishii et al., 1998) single-photon emission computed tomography (SPECT),(McMurtray et al., 2006; McNeill et al., 2007) diffusion tensor imaging (DTI),(Asmuth et al., 2008; Borroni et al., 2007; Whitwell et al., 2010; Zhang et al., 2009) and arterial spin labeling (ASL)(Alsop et al., 2000; Hu et al., 2010f) in the differential diagnosis of FTLD. Most of these studies have compared patients with FTLD against patients with AD, and the advancement in AD CSF biomarkers has allowed for more ante-mortem studies using the most modern imaging techniques. According to CSF AD biomarker profiles (Aβ42, tau, p-tau181) consistent with AD or suggestive of a non-AD disorder, investigators can now derive group-level differences between pathologic cases of AD or non-AD disorders with similar clinical syndromes. This has been used in deriving an imaging signature of FTLD in ASL (frontal hypoperfusion with parietal hyperperfusion),(Hu et al., 2010f) and DTI studies are underway.(Hu et al., 2010g) Similar strategies are underway to identify functional or structural imaging signatures of FTLD-TDP or FTLD-Tau. In the meantime, the most promising use of structural imaging biomarkers (and possibly functional imaging biomarker) may be in disease staging, especially if biochemical biomarkers of FTLD demonstrate a threshold-type phenomenon similar to CSF levels of Aβ42 in MCI and AD. Using boundary shift analysis, a study using serial structural imaging in autopsy-confirmed cases of FTLD showed different rates of atrophy over time among the different FTLD pathologic subyptes, with CBD and FTLD-TDP cases having the greatest longitudinal change, and PSP and DLB having the least.(Whitwell et al., 2007) While the rate of change may be influenced by pathology, the region of longitudinal atrophy may also be influenced by the clinical syndrome. For example, frontal insular network may be affected early in bv-FTD, while neorcortical atrophy can be found in mild disease and regions more associated with AD (parietal cortex, hippocampus) are affected late in the course.(Seeley et al., 2008) A similar technique showed correlation between MRI rates of atrophy and common clinical measures including scores on Mini-Mental Status Examination, Clinical Dementia Rating, and Frontal Assessment Battery in 32 clinically defined FTD patients.(Gordon et al., 2010) Taking advantage of the within-individual rate of volume change (even when insufficiently sensitive or specific to syndrome or pathology), serial measurements of brain volume can be a potential biomarker of response in therapeutic trials once patients are categorized according to clinical syndrome, most dominant region of atrophy, biochemical biomarkers, or a combination of these factors.(Knopman et al., 2009; Knopman et al., 2008) This approach is similar to the observations by ADNI investigators,(Jack et al., 2010) where CSF-based Aβ biomarkers become abnormal first to possibly identify subjects most at risk for future development of AD, followed by changes in neurodegenerative biomarkers (e.g. CSF total tau and p-tau181, atrophy on MRI) and clinical symptoms that are better suited to follow the progression of disease.

No survey of FTLD imaging biomarkers would be complete without discussion on two recent technological advances: substrate-specific imaging and network based imaging. Substrate-specific imaging has generated much enthusiasm in biomarker research given its non-invasive nature and the ability to topographically characterize pathologic deposition. Most of the recent success in substrate-specific imaging related to neurodegenerative disorders has come from studies using ligands that bind to extracellular amyloid deposits in AD, including 11C-Pittsburgh Compound B (11C-PIB)(Mormino et al., 2009; Wang et al., 2002) and 18F-AV-45 (florbetapir).(Choi et al., 2009; Wong et al., 2010) While their use in the differential diagnosis of AD and mild cognitive impairment is discussed elsewhere in this issue, amyloid imaging has been increasingly used in the differential diagnosis of FTLD, sometimes in lieu of CSF biomarkers. In one series of clinically characterized AD and FTD syndromes, 11C-PIB imaging revealed presence of amyloid deposition in 7 out of 7 AD cases and 4 out of 12 clinical FTD cases.(Rabinovici et al., 2007) While there was no autopsy information available on these patients, diagnostic prediction using FDG-PET scan provided complementary information. Importantly, in 3 out of 4 patients (2 bv-FTD, 2 SD) in whom diagnostic outcomes (AD or FTLD) differed between metabolic and amyloid imaging, 18F-FDG showed patterns consistent with FTLD despite the presence of amyloid deposition by 11C-PIB. When such studies were performed in clinical series of PPA(Rabinovici et al., 2008) and CBS(Lee et al., 2010) using amyloid imaging, results were found to mirror those reported in autopsy- or CSF AD biomarker-based studies.(Gross et al., 2010; Hu et al., 2010e; Josephs et al., 2010a; Mesulam et al., 2008) While direct comparison of CSF AD biomarkers and amyloid imaging compounds is not yet available, the use of “amyloid presence” as an exclusion criterion for FTLD pathology will invariably generate a suboptimal sensitivity in detecting all patients with FTLD pathology. This can be a particular concern as patients with autopsy-confirmed cases of FTLD (such as those reported in our autopsy-based multiplex biomarker studies(Hu et al., 2010b)) can have minor AD co-pathology reflected through positive AD biomarkers (CSF or imaging), and patients with genetic cases of FTLD (such as those with PGRN mutations(Mukherjee et al., 2006)) plus AD co-pathology can be misidentified as having AD. Therefore, the need for an imaging biomarker with positive predictive value for FTLD beyond the absence of amyloid deposition is as important in imaging-based differential diagnosis of neurodegenerative disorders as it is in CSF- or plasma-based diagnostic algorithms. As FTLD disorders lack a clear extracellular target for ligand binding, receptor binding according to misregulated membrane-bound receptors (such as sortilin)(Hu et al., 2010a) or recruited cellular population may prove to be more useful than TDP-43 or tau binding ligands.

Finally, network based imaging analysis – examining correlated structural or functional changes across topographically distant brain regions – provided a new dimension of FTLD biomarker investigation. As multiple previous syndrome-based imaging have shown, each classic FTLD-related phenotype seems to be correlated with a network of atrophic brain regions (Table 3). When a region-of-interest approach was used to examine these connected regions in healthy control subjects, a strong network-specific correlation was found in terms of resting functional MRI activation pattern and volume variance.(Seeley et al., 2009) This finding supports the hypothesis that some of the seeming unrelated clinical symptoms (for example, language disorder and alien limb phenomenon in CBS) can be due to a network-level vulnerability that impairs distant rather than adjacent brain regions after disease onset. The proximity of some adjacent nodes belonging to very distinct networks can also potentially account for the various pathologic substrates for similar clinical FTLD syndromes (such as AD and FTLD both causing non-fluent PPA(Hu et al., 2010e)). An examination of the network-level imaging biomarker in future FTLD work can be fruitful in predicting underlying pathologic FTLD or FTLD subtypes, in addition to more conventional strategies such as single region structural or substrate-specific imaging approaches.(Zhou et al., 2010a)

5. Future challenges

As we reviewed here, significant progress has been made in the understanding of clinical, genetic, biochemical, pathologic, and radiologic characterization of FTLD related disorders despite the significant clinical heterogeneity and pathologic overlap. While studies on FTLD often lump patients into hypothesis-driven or convenient categories for the sake of power or simplicity, most FTLD investigators now share a certain degree of comfort in maneuvering through the maze of syndromic-pathologic admixture. Work centered around clinical syndromes (with or without pathologic correlation) has yielded useful information on brain-behavioral relationship and symptomatic progression of FTLD.(Gorno-Tempini et al., 2004; Grossman, 2010; Josephs, 2008; McKhann et al., 2001; Mesulam, 1982; Neary et al., 1998; Pick, 1892; Rascovsky et al., 2007a) Some of the biochemical studies suffer from small sample size and bias, although rigorous validation studies are underway. With progress in biomarker development for disorders such as AD in ADNI serving as a blueprint for FTLD biomarker studies (Table 4), the expanded use of ante-mortem biomarkers will likely herald the next chapter of FTLD investigation to allow for early detection of pathologic FTLD substrate. Reliable biomarkers may accurately identify prodromal subjects with familial FTLD with or without known mutations, and allow for better and timely recruitment of patients with known pathologic FTLD substrates for natural history studies, therapeutic trials, and other associated lines of investigation. Parallel to emerging technology for biomarker detection (analyte levels in biofluids, gray matter volume, white matter integrity, large scale network connectivity), novel analytical strategies on single time point classification and multiple time point correlation will also be necessary to elucidate meaningful biological relationships that would otherwise escape conventional statistical approaches. This may be especially relevant if there is discordance among biomarkers,(Rabinovici et al., 2007; Zhou et al., 2010a) and such discordance may need to be reconciled by yet more sophisticated algorithms beyond simple linear combinations. It may be only fitting that a network approach – be it biochemical analytes(Hu et al., 2010c; Hu et al., 2010d) or brain structures(Zhou et al., 2010a) – through collaboration with specialists in complex applied mathematics and statistics would be the most suitable strategy to decode a family of disorders that defy the one syndrome-one pathology rule. If successful, these bodies of work can then be further developed beyond the first level TDP vs. Tau comparison. These can include biomarker discovery for those with FTLD subtypes (e.g., Type 1 pathology for FTLD-TDP, CBD instead of FTLD-Tau), tau and TDP-43-negative FTLDs such as FLTD with FUS,(Urwin et al., 2010) and FTLD of the same pathologic subtype but different prognosis.(Hu et al., 2009b)

Table 4
Multi-modal biomarker combinations for AD and FTLD.

An even greater barrier to progress of FTLD biology may be the separation of patients with the same disease in different subspecialty clinics (such as FTD-PSP patients in Cognitive Neurology or Movement Disorders clinics) based entirely on convention or reimbursement. As it is well recognized that FTLD continues to be a relatively uncommon disorder even when including those with ALS and PSP/CBS patients without dementia, the success of having a critical mass of FTLD patients at any level depends heavily on breaking down traditional administrative barriers that separate patients with dementia from those with other forms of neurodegenerative disorders. Similar to the depth associated with the creation of a comprehensive Alzheimer’s disease center to involve radiologists, neuropsychologists, basic scientists, and clinical pharmacists among others,(Trojanowski et al., 2010a) the breadth of a comprehensive neurodegenerative research center must involve the talent and effort from Cognitive/Behavioral Neurology, Movement Disorders, and ALS/MND sections. As there is significant clinical, biochemical, pathologic, and radiologic overlap between cognitive-predominant forms of FTLD and the other disorders, future therapeutic strategies based on common pathologic substrates (TDP-43, tau, FUS) or susceptible regions (frontal-subcortical network, basal ganglia, motor neurons) will likely benefit more from cross pollination than continued separation. Effort to extend single center findings to a multi-center stage (demonstrated by ADNI) is also crucial beyond discovery and validation, as each stage of such multi-center studies promotes the harmonization of local approaches to the clinical, biochemical, pathologic, and radiologic characterization of FTLD.

6. Acknowledgement

The authors would like to acknowledge their collaborators in work on clinical, biochemical, and imaging biomarkers of FTLD, including Alice Chen-Plotkin, MD, Murray Grossman, MD, Steven E. Arnold, MD, PhD, Christopher M. Clark, MD, Leo McCluskey, MD, MBE, Lauren Elman, MD, Jason Karlawish, MD, Howard I. Hurtig, MD, Andrew Siderowf, MD, Virginia M.-Y. Lee, PhD, MBA, Holly Soares, PhD, David Libon, PhD, Yair Gozal, MD, PhD, Nick Seyfried, DPhil, James Lah, MD, PhD, Allan Levey, MD, PhD, Jonathan Glass, MD, Marla Gearing, PhD, and Keith Josephs, MST, MD. This work has been supported by Viretta Brady Discovery Fund at Emory University School of Medicine and AG10124, AG17586, and the Penn-Pfizer Alliance at the University of Pennsylvania.

Abbreviation List

AD
Alzheimer’s disease
ALS/MND
Amyotrophic lateral sclerosis/motor neuron disease
ASL
Arterial spin labeling
CBS
Corticobasal syndrome
CBD
Corticobasal degeneration
CSF
Cerebrospinal fluid
DLB
Dementia with Lewy bodies
DTI
Diffusion tensor imaging
FTDP-17
Frontotemporal dementia with parkinsonism linked to chromosome 17
FTLD
Frontotemporal lobar degeneration
FTLD-Tau
Frontotemporal lobar degeneration with tau-immunoreactive lesions
FTLD-TDP
Frontotemporal lobar degeneration with TDP-immunoreactive lesions
FUS
fused-in-sarcoma
MRI
Magnetic resonance imaging
PD
Parkinson’s disease
PNFA
Progressive non-fluent aphasia
PPA
Primary progressive aphasia
PSP
Progressive supranuclear palsy
SD/SV-PPA
Semantic dementia/semantic variant of primary progressive aphasia

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

REFERENCE

  • Alladi S, Xuereb J, Bak T, Nestor P, Knibb J, Patterson K, Hodges JR. Focal cortical presentations of Alzheimer’s disease. Brain. 2007;130:2636–2645. [PubMed]
  • Alsop DC, Detre JA, Grossman M. Assessment of cerebral blood flow in Alzheimer’s disease by spin-labeled magnetic resonance imaging. Annals of neurology. 2000;47:93–100. [PubMed]
  • Andreasen N, Hesse C, Davidsson P, Minthon L, Wallin A, Winblad B, Vanderstichele H, Vanmechelen E, Blennow K. Cerebrospinal fluid beta-amyloid(1-42) in Alzheimer disease: differences between early- and late-onset Alzheimer disease and stability during the course of disease. Archives of neurology. 1999;56:673–680. [PubMed]
  • Asmuth J, Zhang H, Grossman M. DTI analysis of white matter deficits in frontotemporal lobar dementia. Neurology. 2008;70:A452.
  • Bak TH, Crawford LM, Hearn VC, Mathuranath PS, Hodges JR. Subcortical dementia revisited: similarities and differences in cognitive function between progressive supranuclear palsy (PSP), corticobasal degeneration (CBD) and multiple system atrophy (MSA) Neurocase. 2005;11:268–273. [PubMed]
  • Baker M, Mackenzie IR, Pickering-Brown SM, Gass J, Rademakers R, Lindholm C, Snowden J, Adamson J, Sadovnick AD, Rollinson S, Cannon A, Dwosh E, Neary D, Melquist S, Richardson A, Dickson D, Berger Z, Eriksen J, Robinson T, Zehr C, Dickey CA, Crook R, McGowan E, Mann D, Boeve B, Feldman H, Hutton M. Mutations in progranulin cause tau-negative frontotemporal dementia linked to chromosome 17. Nature. 2006;442:916–919. [PubMed]
  • Benajiba L, Le Ber I, Camuzat A, Lacoste M, Thomas-Anterion C, Couratier P, Legallic S, Salachas F, Hannequin D, Decousus M, Lacomblez L, Guedj E, Golfier V, Camu W, Dubois B, Campion D, Meininger V, Brice A. TARDBP mutations in motoneuron disease with frontotemporal lobar degeneration. Annals of neurology. 2009;65:470–473. [PubMed]
  • Bian H, Van Swieten JC, Leight S, Massimo L, Wood E, Forman M, Moore P, de Koning I, Clark CM, Rosso S, Trojanowski J, Lee VM, Grossman M. CSF biomarkers in frontotemporal lobar degeneration with known pathology. Neurology. 2008;70:1827–1835. [PMC free article] [PubMed]
  • Bilic E, Bilic E, Rudan I, Kusec V, Zurak N, Delimar D, Zagar M. Comparison of the growth hormone, IGF-1 and insulin in cerebrospinal fluid and serum between patients with motor neuron disease and healthy controls. Eur J Neurol. 2006;13:1340–1345. [PubMed]
  • Bjerke M, Portelius E, Minthon L, Wallin A, Anckarsater H, Anckarsater R, Andreasen N, Zetterberg H, Andreasson U, Blennow K. Confounding factors influencing amyloid Beta concentration in cerebrospinal fluid. International journal of Alzheimer’s disease. 2010;2010 [PMC free article] [PubMed]
  • Boeve BF, Lang AE, Litvan I. Corticobasal degeneration and its relationship to progressive supranuclear palsy and frontotemporal dementia. Annals of neurology. 2003;54(Suppl 5):S15–19. [PubMed]
  • Boeve BF, Maraganore DM, Parisi JE, Ahlskog JE, Graff-Radford N, Caselli RJ, Dickson DW, Kokmen E, Petersen RC. Pathologic heterogeneity in clinically diagnosed corticobasal degeneration. Neurology. 1999;53:795–800. [PubMed]
  • Borroni B, Bonvicini C, Alberici A, Buratti E, Agosti C, Archetti S, Papetti A, Stuani C, Di Luca M, Gennarelli M, Padovani A. Mutation within TARDBP leads to frontotemporal dementia without motor neuron disease. Human mutation. 2009;30:E974–983. [PubMed]
  • Borroni B, Brambati SM, Agosti C, Gipponi S, Bellelli G, Gasparotti R, Garibotto V, Di Luca M, Scifo P, Perani D, Padovani A. Evidence of white matter changes on diffusion tensor imaging in frontotemporal dementia. Archives of neurology. 2007;64:246–251. [PubMed]
  • Borroni B, Malinverno M, Gardoni F, Alberici A, Parnetti L, Premi E, Bonuccelli U, Grassi M, Perani D, Calabresi P, Di Luca M, Padovani A. Tau forms in CSF as a reliable biomarker for progressive supranuclear palsy. Neurology. 2008;71:1796–1803. [PubMed]
  • Brettschneider J, Widl K, Ehrenreich H, Riepe M, Tumani H. Erythropoietin in the cerebrospinal fluid in neurodegenerative diseases. Neuroscience letters. 2006;404:347–351. [PubMed]
  • Brooks BR, Miller RG, Swash M, Munsat TL. El Escorial revisited: revised criteria for the diagnosis of amyotrophic lateral sclerosis. Amyotroph Lateral Scler Other Motor Neuron Disord. 2000;1:293–299. [PubMed]
  • Choi SR, Golding G, Zhuang Z, Zhang W, Lim N, Hefti F, Benedum TE, Kilbourn MR, Skovronsky D, Kung HF. Preclinical properties of 18F-AV-45: a PET agent for Abeta plaques in the brain. J Nucl Med. 2009;50:1887–1894. [PMC free article] [PubMed]
  • Chow TW, Binns MA, Freedman M, Stuss DT, Ramirez J, Scott CJ, Black S. Overlap in frontotemporal atrophy between normal aging and patients with frontotemporal dementias. Alzheimer disease and associated disorders. 2008;22:327–335. [PubMed]
  • Collette F, Amieva H, Adam S, Hogge M, Van der Linden M, Fabrigoule C, Salmon E. Comparison of inhibitory functioning in mild Alzheimer’s disease and frontotemporal dementia. Cortex; a journal devoted to the study of the nervous system and behavior. 2007;43:866–874. [PubMed]
  • Corrado L, Ratti A, Gellera C, Buratti E, Castellotti B, Carlomagno Y, Ticozzi N, Mazzini L, Testa L, Taroni F, Baralle FE, Silani V, D’Alfonso S. High frequency of TARDBP gene mutations in Italian patients with amyotrophic lateral sclerosis. Human mutation. 2009;30:688–694. [PubMed]
  • Davidsson P, Sjogren M, Andreasen N, Lindbjer M, Nilsson CL, Westman-Brinkmalm A, Blennow K. Studies of the pathophysiological mechanisms in frontotemporal dementia by proteome analysis of CSF proteins. Brain research. 2002a;109:128–133. [PubMed]
  • Davidsson P, Westman-Brinkmalm A, Nilsson CL, Lindbjer M, Paulson L, Andreasen N, Sjogren M, Blennow K. Proteome analysis of cerebrospinal fluid proteins in Alzheimer patients. Neuroreport. 2002b;13:611–615. [PubMed]
  • Davies RR, Kipps CM, Mitchell J, Kril JJ, Halliday GM, Hodges JR. Progression in frontotemporal dementia: identifying a benign behavioral variant by magnetic resonance imaging. Archives of neurology. 2006;63:1627–1631. [PubMed]
  • Dickson DW, Bergeron C, Chin SS, Duyckaerts C, Horoupian D, Ikeda K, Jellinger K, Lantos PL, Lippa CF, Mirra SS, Tabaton M, Vonsattel JP, Wakabayashi K, Litvan I. Office of Rare Diseases neuropathologic criteria for corticobasal degeneration. Journal of neuropathology and experimental neurology. 2002;61:935–946. [PubMed]
  • Esmonde T, Giles E, Gibson M, Hodges JR. Neuropsychological performance, disease severity, and depression in progressive supranuclear palsy. Journal of neurology. 1996;243:638–643. [PubMed]
  • Finch N, Baker M, Crook R, Swanson K, Kuntz K, Surtees R, Bisceglio G, Rovelet-Lecrux A, Boeve B, Petersen RC, Dickson DW, Younkin SG, Deramecourt V, Crook J, Graff-Radford NR, Rademakers R. Plasma progranulin levels predict progranulin mutation status in frontotemporal dementia patients and asymptomatic family members. Brain. 2009;132:583–591. [PMC free article] [PubMed]
  • Forman MS, Farmer J, Johnson JK, Clark CM, Arnold SE, Coslett HB, Chatterjee A, Hurtig HI, Karlawish JH, Rosen HJ, Van Deerlin V, Lee VM, Miller BL, Trojanowski JQ, Grossman M. Frontotemporal dementia: clinicopathological correlations. Annals of neurology. 2006;59:952–962. [PMC free article] [PubMed]
  • Foster NL, Heidebrink JL, Clark CM, Jagust WJ, Arnold SE, Barbas NR, DeCarli CS, Turner RS, Koeppe RA, Higdon R, Minoshima S. FDG-PET improves accuracy in distinguishing frontotemporal dementia and Alzheimer’s disease. Brain. 2007;130:2616–2635. [PubMed]
  • Foulds P, McAuley E, Gibbons L, Davidson Y, Pickering-Brown SM, Neary D, Snowden JS, Allsop D, Mann DM. TDP-43 protein in plasma may index TDP-43 brain pathology in Alzheimer’s disease and frontotemporal lobar degeneration. Acta neuropathologica. 2008;116:141–146. [PMC free article] [PubMed]
  • Freibaum BD, Chitta RK, High AA, Taylor JP. Global analysis of TDP-43 interacting proteins reveals strong association with RNA splicing and translation machinery. Journal of proteome research. 2010;9:1104–1120. [PMC free article] [PubMed]
  • Gass J, Cannon A, Mackenzie IR, Boeve B, Baker M, Adamson J, Crook R, Melquist S, Kuntz K, Petersen R, Josephs K, Pickering-Brown SM, Graff-Radford N, Uitti R, Dickson D, Wszolek Z, Gonzalez J, Beach TG, Bigio E, Johnson N, Weintraub S, Mesulam M, White CL, 3rd, Woodruff B, Caselli R, Hsiung GY, Feldman H, Knopman D, Hutton M, Rademakers R. Mutations in progranulin are a major cause of ubiquitin-positive frontotemporal lobar degeneration. Human molecular genetics. 2006;15:2988–3001. [PubMed]
  • Geser F, Brandmeir NJ, Kwong LK, Martinez-Lage M, Elman L, McCluskey L, Xie SX, Lee VM, Trojanowski JQ. Evidence of multisystem disorder in whole-brain map of pathological TDP-43 in amyotrophic lateral sclerosis. Archives of neurology. 2008;65:636–641. [PubMed]
  • Gordon E, Rohrer JD, Kim LG, Omar R, Rossor MN, Fox NC, Warren JD. Measuring disease progression in frontotemporal lobar degeneration: a clinical and MRI study. Neurology. 2010;74:666–673. [PMC free article] [PubMed]
  • Gorno-Tempini ML, Brambati SM, Ginex V, Ogar J, Dronkers NF, Marcone A, Perani D, Garibotto V, Cappa SF, Miller BL. The logopenic/phonological variant of primary progressive aphasia. Neurology. 2008;71:1227–1234. [PMC free article] [PubMed]
  • Gorno-Tempini ML, Dronkers NF, Rankin KP, Ogar JM, Phengrasamy L, Rosen HJ, Johnson JK, Weiner MW, Miller BL. Cognition and anatomy in three variants of primary progressive aphasia. Annals of neurology. 2004;55:335–346. [PMC free article] [PubMed]
  • Gros-Louis F, Andersen PM, Dupre N, Urushitani M, Dion P, Souchon F, D’Amour M, Camu W, Meininger V, Bouchard JP, Rouleau GA, Julien JP. Chromogranin B P413L variant as risk factor and modifier of disease onset for amyotrophic lateral sclerosis. Proceedings of the National Academy of Sciences of the United States of America. 2009;106:21777–21782. [PubMed]
  • Gross RG, Hu WT, McMillan CT, Gunawardena D, Lee VM, Trojanowski JQ, Grossman M. Prediction of underlying Alzheimer’s disease in corticobasal syndrome; American Academy of Neurology Annual Meeting; Toronto. 2010.
  • Grossman M. Primary progressive aphasia: clinicopathological correlations. Nat Rev Neurol. 2010;6:88–97. [PubMed]
  • Grossman M, Libon DJ, Forman MS, Massimo L, Wood E, Moore P, Anderson C, Farmer J, Chatterjee A, Clark CM, Coslett HB, Hurtig HI, Lee VM, Trojanowski JQ. Distinct antemortem profiles in patients with pathologically defined frontotemporal dementia. Archives of neurology. 2007;64:1601–1609. [PubMed]
  • Grossman M, McMillan C, Moore P, Ding L, Glosser G, Work M, Gee J. What’s in a name: voxel-based morphometric analyses of MRI and naming difficulty in Alzheimer’s disease, frontotemporal dementia and corticobasal degeneration. Brain. 2004;127:628–649. [PubMed]
  • Grossman M, Xie SX, Libon DJ, Wang X, Massimo L, Moore P, Vesely L, Berkowitz R, Chatterjee A, Coslett HB, Hurtig HI, Forman MS, Lee VM, Trojanowski JQ. Longitudinal decline in autopsy-defined frontotemporal lobar degeneration. Neurology. 2008;70:2036–2045. [PMC free article] [PubMed]
  • Gunawardena D, Ash S, McMillan C, Avants B, Gee J, Grossman M. Why are patients with progressive nonfluent aphasia nonfluent? Neurology. 2010;75:588–594. [PMC free article] [PubMed]
  • Hodges JR, Davies RR, Xuereb JH, Casey B, Broe M, Bak TH, Kril JJ, Halliday GM. Clinicopathological correlates in frontotemporal dementia. Annals of neurology. 2004;56:399–406. [PubMed]
  • Hodges JR, Mitchell J, Dawson K, Spillantini MG, Xuereb JH, McMonagle P, Nestor PJ, Patterson K. Semantic dementia: demography, familial factors and survival in a consecutive series of 100 cases. Brain. 2010;133:300–306. [PubMed]
  • Hsiung GY, Fok A, Feldman HH, Rademakers R, Mackenzie IR. rs5848 polymorphism and serum progranulin level. Journal of the neurological sciences. 2010 [PMC free article] [PubMed]
  • Hu F, Padukkavidana T, Vaegter CB, Brady OA, Zheng Y, Mackenzie IR, Feldman HH, Nykjaer A, Strittmatter SM. Sortilin-mediated endocytosis determines levels of the frontotemporal dementia protein, progranulin. Neuron. 2010a;68:654–667. [PMC free article] [PubMed]
  • Hu WT, Chen-Plotkin A, Arnold SE, Grossman M, Clark CM, Shaw LM, McCluskey L, Elman L, Karlawish J, Hurtig HI, Siderowf A, Lee VM, Soares H, Trojanowski JQ. Biomarker discovery for Alzheimer’s disease, frontotemporal lobar degeneration, and Parkinson’s disease. Acta neuropathologica. 2010b;120:385–399. [PMC free article] [PubMed]
  • Hu WT, Chen-Plotkin A, Arnold SE, Grossman M, Clark CM, Shaw LM, Pickering E, Kuhn M, Chen Y, McCluskey L, Elman L, Karlawish J, Hurtig HI, Siderowf A, Lee VM, Soares H, Trojanowski JQ. Novel CSF biomarkers for Alzheimer’s disease and mild cognitive impairment. Acta neuropathologica. 2010c;119:669–678. [PMC free article] [PubMed]
  • Hu WT, Chen-Plotkin A, Grossman M, Arnold SE, Clark CM, Shaw LM, McCluskey L, Elman L, Hurtig HI, Siderowf A, Lee VM, Soares H, Trojanowski JQ. Novel CSF biomarkers for frontotemporal lobar degenerations. Neurology. 2010d [PMC free article] [PubMed]
  • Hu WT, McMillan C, Libon DJ, Leight S, Forman MS, Lee VM, Trojanowski JQ, Grossman M. Multi-modal predictors for Alzheimer’s disease in non-fluent primary progressive aphasia. Neurology. 2010e;75:595–602. [PMC free article] [PubMed]
  • Hu WT, Rippon GW, Boeve BF, Knopman DS, Petersen RC, Parisi JE, Josephs KA. Alzheimer’s disease and corticobasal degeneration presenting as corticobasal syndrome. Mov Disord. 2009a;24:1375–1379. [PubMed]
  • Hu WT, Seelaar H, Josephs KA, Knopman DS, Boeve BF, Sorenson EJ, McCluskey L, Elman L, Schelhaas HJ, Parisi JE, Kuesters B, Lee VM, Trojanowski JQ, Petersen RC, van Swieten JC, Grossman M. Survival profiles of patients with frontotemporal dementia and motor neuron disease. Archives of neurology. 2009b;66:1359–1364. [PMC free article] [PubMed]
  • Hu WT, Wang Z, Lee VM, Trojanowski JQ, Detre JA, Grossman M. Distinct cerebral perfusion patterns in FTLD and AD. Neurology. 2010f;75:881–888. [PMC free article] [PubMed]
  • Hu WT, Zhang H, McMillan C, Lee VM, Trojanowski JQ, Grossman M. Distinct white matter tract changes in frontotemporal dementia associated with FTLD and Alzheimer’s disease pathology or CSF biomarkers; American Academy of Neurology Annual Meeting; Toronto. 2010g.
  • Hutchinson AD, Mathias JL. Neuropsychological deficits in frontotemporal dementia and Alzheimer’s disease: a meta-analytic review. Journal of neurology, neurosurgery, and psychiatry. 2007;78:917–928. [PMC free article] [PubMed]
  • Hutton M. Missense and splice site mutations in tau associated with FTDP-17: multiple pathogenic mechanisms. Neurology. 2001;56:S21–25. [PubMed]
  • Ishii K, Sakamoto S, Sasaki M, Kitagaki H, Yamaji S, Hashimoto M, Imamura T, Shimomura T, Hirono N, Mori E. Cerebral glucose metabolism in patients with frontotemporal dementia. J Nucl Med. 1998;39:1875–1878. [PubMed]
  • Jack CR, Jr., Knopman DS, Jagust WJ, Shaw LM, Aisen PS, Weiner MW, Petersen RC, Trojanowski JQ. Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade. Lancet neurology. 2010;9:119–128. [PMC free article] [PubMed]
  • Josephs KA. Frontotemporal dementia and related disorders: deciphering the enigma. Annals of neurology. 2008;64:4–14. [PubMed]
  • Josephs KA, Dickson DW. Diagnostic accuracy of progressive supranuclear palsy in the Society for Progressive Supranuclear Palsy brain bank. Mov Disord. 2003;18:1018–1026. [PubMed]
  • Josephs KA, Parisi JE, Knopman DS, Boeve BF, Petersen RC, Dickson DW. Clinically undetected motor neuron disease in pathologically proven frontotemporal lobar degeneration with motor neuron disease. Archives of neurology. 2006a;63:506–512. [PubMed]
  • Josephs KA, Petersen RC, Knopman DS, Boeve BF, Whitwell JL, Duffy JR, Parisi JE, Dickson DW. Clinicopathologic analysis of frontotemporal and corticobasal degenerations and PSP. Neurology. 2006b;66:41–48. [PubMed]
  • Josephs KA, Tang-Wai DF, Edland SD, Knopman DS, Dickson DW, Parisi JE, Petersen RC, Jack CR, Jr., Boeve BF. Correlation between antemortem magnetic resonance imaging findings and pathologically confirmed corticobasal degeneration. Archives of neurology. 2004;61:1881–1884. [PubMed]
  • Josephs KA, Whitwell JL, Boeve BF, Knopman DS, Petersen RC, Hu WT, Parisi JE, Dickson DW, Jack CR., Jr. Anatomical differences between CBS-corticobasal degeneration and CBS-Alzheimer’s disease. Mov Disord. 2010a;25:1246–1252. [PMC free article] [PubMed]
  • Josephs KA, Whitwell JL, Dickson DW, Boeve BF, Knopman DS, Petersen RC, Parisi JE, Jack CR., Jr. Voxel-based morphometry in autopsy proven PSP and CBD. Neurobiology of aging. 2008;29:280–289. [PMC free article] [PubMed]
  • Josephs KA, Whitwell JL, Knopman DS, Boeve BF, Vemuri P, Senjem ML, Parisi JE, Ivnik RJ, Dickson DW, Petersen RC, Jack CR., Jr. Two distinct subtypes of right temporal variant frontotemporal dementia. Neurology. 2009;73:1443–1450. [PMC free article] [PubMed]
  • Josephs KA, Whitwell JL, Parisi JE, Petersen RC, Boeve BF, Jack CR, Jr., Dickson DW. Caudate atrophy on MRI is a characteristic feature of FTLD-FUS. Eur J Neurol. 2010b;17:969–975. [PMC free article] [PubMed]
  • Kabashi E, Valdmanis PN, Dion P, Spiegelman D, McConkey BJ, Vande Velde C, Bouchard JP, Lacomblez L, Pochigaeva K, Salachas F, Pradat PF, Camu W, Meininger V, Dupre N, Rouleau GA. TARDBP mutations in individuals with sporadic and familial amyotrophic lateral sclerosis. Nature genetics. 2008;40:572–574. [PubMed]
  • Kasai T, Tokuda T, Ishigami N, Sasayama H, Foulds P, Mitchell DJ, Mann DM, Allsop D, Nakagawa M. Increased TDP-43 protein in cerebrospinal fluid of patients with amyotrophic lateral sclerosis. Acta neuropathologica. 2009;117:55–62. [PubMed]
  • Kawajiri M, Mogi M, Higaki N, Tateishi T, Ohyagi Y, Horiuchi M, Miki T, Kira JI. Reduced angiotensin II levels in the cerebrospinal fluid of patients with amyotrophic lateral sclerosis. Acta neurologica Scandinavica. 2009;119:341–344. [PubMed]
  • Kertesz A, Martinez-Lage P, Davidson W, Munoz DG. The corticobasal degeneration syndrome overlaps progressive aphasia and frontotemporal dementia. Neurology. 2000;55:1368–1375. [PubMed]
  • Kertesz A, McMonagle P. Behavior and cognition in corticobasal degeneration and progressive supranuclear palsy. Journal of the neurological sciences. 2010;289:138–143. [PubMed]
  • Kertesz A, McMonagle P, Blair M, Davidson W, Munoz DG. The evolution and pathology of frontotemporal dementia. Brain. 2005;128:1996–2005. [PubMed]
  • Kim EJ, Rabinovici GD, Seeley WW, Halabi C, Shu H, Weiner MW, DeArmond SJ, Trojanowski JQ, Gorno-Tempini ML, Miller BL, Rosen HJ. Patterns of MRI atrophy in tau positive and ubiquitin positive frontotemporal lobar degeneration. Journal of neurology, neurosurgery, and psychiatry. 2007;78:1375–1378. [PMC free article] [PubMed]
  • Kipps CM, Davies RR, Mitchell J, Kril JJ, Halliday GM, Hodges JR. Clinical significance of lobar atrophy in frontotemporal dementia: application of an MRI visual rating scale. Dementia and geriatric cognitive disorders. 2007;23:334–342. [PubMed]
  • Knopman DS, Jack CR, Jr., Kramer JH, Boeve BF, Caselli RJ, Graff-Radford NR, Mendez MF, Miller BL, Mercaldo ND. Brain and ventricular volumetric changes in frontotemporal lobar degeneration over 1 year. Neurology. 2009;72:1843–1849. [PMC free article] [PubMed]
  • Knopman DS, Kramer JH, Boeve BF, Caselli RJ, Graff-Radford NR, Mendez MF, Miller BL, Mercaldo N. Development of methodology for conducting clinical trials in frontotemporal lobar degeneration. Brain. 2008 [PMC free article] [PubMed]
  • Koedam EL, Van der Flier WM, Barkhof F, Koene T, Scheltens P, Pijnenburg YA. Clinical characteristics of patients with frontotemporal dementia with and without lobar atrophy on MRI. Alzheimer disease and associated disorders. 2010;24:242–247. [PubMed]
  • Kuhle J, Lindberg RL, Regeniter A, Mehling M, Steck AJ, Kappos L, Czaplinski A. Increased levels of inflammatory chemokines in amyotrophic lateral sclerosis. Eur J Neurol. 2009;16:771–774. [PubMed]
  • Kuhnlein P, Sperfeld AD, Vanmassenhove B, Van Deerlin V, Lee VM, Trojanowski JQ, Kretzschmar HA, Ludolph AC, Neumann M. Two German kindreds with familial amyotrophic lateral sclerosis due to TARDBP mutations. Archives of neurology. 2008;65:1185–1189. [PMC free article] [PubMed]
  • Kuiperij HB, Verbeek MM. Diagnosis of progressive supranuclear palsy: can measurement of tau forms help? Neurobiology of aging. 2010 [PubMed]
  • Kwiatkowski TJ, Jr., Bosco DA, Leclerc AL, Tamrazian E, Vanderburg CR, Russ C, Davis A, Gilchrist J, Kasarskis EJ, Munsat T, Valdmanis P, Rouleau GA, Hosler BA, Cortelli P, de Jong PJ, Yoshinaga Y, Haines JL, Pericak-Vance MA, Yan J, Ticozzi N, Siddique T, McKenna-Yasek D, Sapp PC, Horvitz HR, Landers JE, Brown RH., Jr. Mutations in the FUS/TLS gene on chromosome 16 cause familial amyotrophic lateral sclerosis. Science (New York, N.Y. 2009;323:1205–1208. [PubMed]
  • Lee SE, Seeley WW, Wilson S, Growdon M, Jang J, Rankin KP, Jagust WJ, Weiner MW, Gorno-Tempini ML, Miller BL, Rabinovici GD. Correlates of Alzheimer’s pathology in corticobasal syndrome; American Academy of Neurology Annual Meeting; Toronto. 2010.
  • Libon DJ, Massimo L, Moore P, Coslett HB, Chatterjee A, Aguirre GK, Rice A, Vesely L, Grossman M. Screening for frontotemporal dementias and Alzheimer’s disease with the Philadelphia Brief Assessment of Cognition: a preliminary analysis. Dementia and geriatric cognitive disorders. 2007a;24:441–447. [PubMed]
  • Libon DJ, Xie SX, Moore P, Farmer J, Antani S, McCawley G, Cross K, Grossman M. Patterns of neuropsychological impairment in frontotemporal dementia. Neurology. 2007b;68:369–375. [PubMed]
  • Ling H, O’Sullivan SS, Holton JL, Revesz T, Massey LA, Williams DR, Paviour DC, Lees AJ. Does corticobasal degeneration exist? A clinicopathological re-evaluation. Brain. 2010;133:2045–2057. [PubMed]
  • Listerud J, Powers C, Moore P, Libon DJ, Grossman M. Neuropsychological patterns in magnetic resonance imaging-defined subgroups of patients with degenerative dementia. J Int Neuropsychol Soc. 2009;15:459–470. [PMC free article] [PubMed]
  • Litvan I, Agid Y, Jankovic J, Goetz C, Brandel JP, Lai EC, Wenning G, D’Olhaberriague L, Verny M, Chaudhuri KR, McKee A, Jellinger K, Bartko JJ, Mangone CA, Pearce RK. Accuracy of clinical criteria for the diagnosis of progressive supranuclear palsy (Steele-Richardson-Olszewski syndrome) Neurology. 1996;46:922–930. [PubMed]
  • Loewenstein DA, Acevedo A, Ownby R, Agron J, Barker WW, Isaacson R, Strauman S, Duara R. Using different memory cutoffs to assess mild cognitive impairment. Am J Geriatr Psychiatry. 2006;14:911–919. [PubMed]
  • Lomen-Hoerth C, Anderson T, Miller B. The overlap of amyotrophic lateral sclerosis and frontotemporal dementia. Neurology. 2002;59:1077–1079. [PubMed]
  • Mackenzie IR. The neuropathology and clinical phenotype of FTD with progranulin mutations. Acta neuropathologica. 2007;114:49–54. [PubMed]
  • Mackenzie IR, Baker M, Pickering-Brown S, Hsiung GY, Lindholm C, Dwosh E, Gass J, Cannon A, Rademakers R, Hutton M, Feldman HH. The neuropathology of frontotemporal lobar degeneration caused by mutations in the progranulin gene. Brain. 2006;129:3081–3090. [PubMed]
  • Mackenzie IR, Neumann M, Bigio EH, Cairns NJ, Alafuzoff I, Kril J, Kovacs GG, Ghetti B, Halliday G, Holm IE, Ince PG, Kamphorst W, Revesz T, Rozemuller AJ, Kumar-Singh S, Akiyama H, Baborie A, Spina S, Dickson DW, Trojanowski JQ, Mann DM. Nomenclature for neuropathologic subtypes of frontotemporal lobar degeneration: consensus recommendations. Acta neuropathologica. 2009;117:15–18. [PMC free article] [PubMed]
  • Mattsson N, Blennow K, Zetterberg H. Inter-laboratory variation in cerebrospinal fluid biomarkers for Alzheimer’s disease: united we stand, divided we fall. Clin Chem Lab Med. 2010;48:603–607. [PubMed]
  • Mattsson N, Zetterberg H, Hansson O, Andreasen N, Parnetti L, Jonsson M, Herukka SK, van der Flier WM, Blankenstein MA, Ewers M, Rich K, Kaiser E, Verbeek M, Tsolaki M, Mulugeta E, Rosen E, Aarsland D, Visser PJ, Schroder J, Marcusson J, de Leon M, Hampel H, Scheltens P, Pirttila T, Wallin A, Jonhagen ME, Minthon L, Winblad B, Blennow K. CSF biomarkers and incipient Alzheimer disease in patients with mild cognitive impairment. Jama. 2009;302:385–393. [PubMed]
  • McKhann GM, Albert MS, Grossman M, Miller B, Dickson D, Trojanowski JQ. Clinical and pathological diagnosis of frontotemporal dementia: report of the Work Group on Frontotemporal Dementia and Pick’s Disease. Archives of neurology. 2001;58:1803–1809. [PubMed]
  • McMurtray AM, Chen AK, Shapira JS, Chow TW, Mishkin F, Miller BL, Mendez MF. Variations in regional SPECT hypoperfusion and clinical features in frontotemporal dementia. Neurology. 2006;66:517–522. [PubMed]
  • McNeill R, Sare GM, Manoharan M, Testa HJ, Mann DM, Neary D, Snowden JS, Varma AR. Accuracy of single-photon emission computed tomography in differentiating frontotemporal dementia from Alzheimer’s disease. Journal of neurology, neurosurgery, and psychiatry. 2007;78:350–355. [PMC free article] [PubMed]
  • Mendez MF, Shapira JS, McMurtray A, Licht E, Miller BL. Accuracy of the clinical evaluation for frontotemporal dementia. Archives of neurology. 2007;64:830–835. [PubMed]
  • Mesulam M, Wicklund A, Johnson N, Rogalski E, Leger GC, Rademaker A, Weintraub S, Bigio EH. Alzheimer and frontotemporal pathology in subsets of primary progressive aphasia. Annals of neurology. 2008;63:709–719. [PMC free article] [PubMed]
  • Mesulam MM. Slowly progressive aphasia without generalized dementia. Annals of neurology. 1982;11:592–598. [PubMed]
  • Mesulam MM. Primary progressive aphasia. Annals of neurology. 2001;49:425–432. [PubMed]
  • Mitchell RM, Freeman WM, Randazzo WT, Stephens HE, Beard JL, Simmons Z, Connor JR. A CSF biomarker panel for identification of patients with amyotrophic lateral sclerosis. Neurology. 2009;72:14–19. [PubMed]
  • MJFF The Michael J. Fox Foundation for Parkinson’s Research: Parkinson’s Progression Markers Initiative. 2010.
  • Mormino EC, Kluth JT, Madison CM, Rabinovici GD, Baker SL, Miller BL, Koeppe RA, Mathis CA, Weiner MW, Jagust WJ. Episodic memory loss is related to hippocampal-mediated beta-amyloid deposition in elderly subjects. Brain. 2009;132:1310–1323. [PMC free article] [PubMed]
  • Mukherjee O, Pastor P, Cairns NJ, Chakraverty S, Kauwe JS, Shears S, Behrens MI, Budde J, Hinrichs AL, Norton J, Levitch D, Taylor-Reinwald L, Gitcho M, Tu PH, Grinberg L. Tenenholz, Liscic RM, Armendariz J, Morris JC, Goate AM. HDDD2 is a familial frontotemporal lobar degeneration with ubiquitin-positive, tau-negative inclusions caused by a missense mutation in the signal peptide of progranulin. Annals of neurology. 2006;60:314–322. [PMC free article] [PubMed]
  • Murray R, Neumann M, Forman MS, Farmer J, Massimo L, Rice A, Miller BL, Johnson JK, Clark CM, Hurtig HI, Gorno-Tempini ML, Lee VM, Trojanowski JQ, Grossman M. Cognitive and motor assessment in autopsy-proven corticobasal degeneration. Neurology. 2007;68:1274–1283. [PubMed]
  • Neary D, Snowden JS, Gustafson L, Passant U, Stuss D, Black S, Freedman M, Kertesz A, Robert PH, Albert M, Boone K, Miller BL, Cummings J, Benson DF. Frontotemporal lobar degeneration: a consensus on clinical diagnostic criteria. Neurology. 1998;51:1546–1554. [PubMed]
  • Neumann M, Sampathu DM, Kwong LK, Truax AC, Micsenyi MC, Chou TT, Bruce J, Schuck T, Grossman M, Clark CM, McCluskey LF, Miller BL, Masliah E, Mackenzie IR, Feldman H, Feiden W, Kretzschmar HA, Trojanowski JQ, Lee VM. Ubiquitinated TDP-43 in frontotemporal lobar degeneration and amyotrophic lateral sclerosis. Science (New York, N.Y. 2006;314:130–133. [PubMed]
  • Pasinetti GM, Ungar LH, Lange DJ, Yemul S, Deng H, Yuan X, Brown RH, Cudkowicz ME, Newhall K, Peskind E, Marcus S, Ho L. Identification of potential CSF biomarkers in ALS. Neurology. 2006;66:1218–1222. [PubMed]
  • Petersen RC, Aisen PS, Beckett LA, Donohue MC, Gamst AC, Harvey DJ, Jack CR, Jr., Jagust WJ, Shaw LM, Toga AW, Trojanowski JQ, Weiner MW. Alzheimer’s Disease Neuroimaging Initiative (ADNI): clinical characterization. Neurology. 74:201–209. [PMC free article] [PubMed]
  • Petersen RC, Aisen PS, Beckett LA, Donohue MC, Gamst AC, Harvey DJ, Jack CR, Jr., Jagust WJ, Shaw LM, Toga AW, Trojanowski JQ, Weiner MW. Alzheimer’s Disease Neuroimaging Initiative (ADNI): clinical characterization. Neurology. 2010;74:201–209. [PMC free article] [PubMed]
  • Petzold A, Keir G, Warren J, Fox N, Rossor MN. A systematic review and meta-analysis of CSF neurofilament protein levels as biomarkers in dementia. Neuro-degenerative diseases. 2007;4:185–194. [PubMed]
  • Pick A. Uber die Beziehungen der senilen Hirnatrophie zur Aphasie. Prager medicinische Wochenschrift. 1892:165–167.
  • Poste G. Bring on the biomarkers. Nature. 2011;469:156–157. [PubMed]
  • Rabinovici GD, Furst AJ, O’Neil JP, Racine CA, Mormino EC, Baker SL, Chetty S, Patel P, Pagliaro TA, Klunk WE, Mathis CA, Rosen HJ, Miller BL, Jagust WJ. 11C-PIB PET imaging in Alzheimer disease and frontotemporal lobar degeneration. Neurology. 2007;68:1205–1212. [PubMed]
  • Rabinovici GD, Jagust WJ, Furst AJ, Ogar JM, Racine CA, Mormino EC, O’Neil JP, Lal RA, Dronkers NF, Miller BL, Gorno-Tempini ML. Abeta amyloid and glucose metabolism in three variants of primary progressive aphasia. Annals of neurology. 2008;64:388–401. [PMC free article] [PubMed]
  • Rademakers R, Eriksen JL, Baker M, Robinson T, Ahmed Z, Lincoln SJ, Finch N, Rutherford NJ, Crook RJ, Josephs KA, Boeve BF, Knopman DS, Petersen RC, Parisi JE, Caselli RJ, Wszolek ZK, Uitti RJ, Feldman H, Hutton ML, Mackenzie IR, Graff-Radford NR, Dickson DW. Common variation in the miR-659 binding-site of GRN is a major risk factor for TDP43-positive frontotemporal dementia. Human molecular genetics. 2008;17:3631–3642. [PubMed]
  • Rascovsky K, Hodges JR, Kipps CM, Johnson JK, Seeley WW, Mendez MF, Knopman D, Kertesz A, Mesulam M, Salmon DP, Galasko D, Chow TW, Decarli C, Hillis A, Josephs K, Kramer JH, Weintraub S, Grossman M, Gorno-Tempini ML, Miller BM. Diagnostic criteria for the behavioral variant of frontotemporal dementia (bvFTD): current limitations and future directions. Alzheimer disease and associated disorders. 2007a;21:S14–18. [PubMed]
  • Rascovsky K, Salmon DP, Hansen LA, Thal LJ, Galasko D. Disparate letter and semantic category fluency deficits in autopsy-confirmed frontotemporal dementia and Alzheimer’s disease. Neuropsychology. 2007b;21:20–30. [PubMed]
  • Ratnavalli E, Brayne C, Dawson K, Hodges JR. The prevalence of frontotemporal dementia. Neurology. 2002;58:1615–1621. [PubMed]
  • Rogers TT, Ivanoiu A, Patterson K, Hodges JR. Semantic memory in Alzheimer’s disease and the frontotemporal dementias: a longitudinal study of 236 patients. Neuropsychology. 2006;20:319–335. [PubMed]
  • Rosen HJ, Gorno-Tempini ML, Goldman WP, Perry RJ, Schuff N, Weiner M, Feiwell R, Kramer JH, Miller BL. Patterns of brain atrophy in frontotemporal dementia and semantic dementia. Neurology. 2002a;58:198–208. [PubMed]
  • Rosen HJ, Narvaez JM, Hallam B, Kramer JH, Wyss-Coray C, Gearhart R, Johnson JK, Miller BL. Neuropsychological and functional measures of severity in Alzheimer disease, frontotemporal dementia, and semantic dementia. Alzheimer disease and associated disorders. 2004;18:202–207. [PubMed]
  • Rosen HJ, Perry RJ, Murphy J, Kramer JH, Mychack P, Schuff N, Weiner M, Levenson RW, Miller BL. Emotion comprehension in the temporal variant of frontotemporal dementia. Brain. 2002b;125:2286–2295. [PubMed]
  • Rosso SM, Kaat L. Donker, Baks T, Joosse M, de Koning I, Pijnenburg Y, de Jong D, Dooijes D, Kamphorst W, Ravid R, Niermeijer MF, Verheij F, Kremer HP, Scheltens P, van Duijn CM, Heutink P, van Swieten JC. Frontotemporal dementia in The Netherlands: patient characteristics and prevalence estimates from a population-based study. Brain. 2003;126:2016–2022. [PubMed]
  • Ruetschi U, Zetterberg H, Podust VN, Gottfries J, Li S, Simonsen A. Hviid, McGuire J, Karlsson M, Rymo L, Davies H, Minthon L, Blennow K. Identification of CSF biomarkers for frontotemporal dementia using SELDI-TOF. Experimental neurology. 2005;196:273–281. [PubMed]
  • Schuff N, Woerner N, Boreta L, Kornfield T, Shaw LM, Trojanowski JQ, Thompson PM, Jack CR, Jr., Weiner MW. MRI of hippocampal volume loss in early Alzheimer’s disease in relation to ApoE genotype and biomarkers. Brain. 2009;132:1067–1077. [PMC free article] [PubMed]
  • Seeley WW, Bauer AM, Miller BL, Gorno-Tempini ML, Kramer JH, Weiner M, Rosen HJ. The natural history of temporal variant frontotemporal dementia. Neurology. 2005;64:1384–1390. [PMC free article] [PubMed]
  • Seeley WW, Crawford R, Rascovsky K, Kramer JH, Weiner M, Miller BL, Gorno-Tempini ML. Frontal paralimbic network atrophy in very mild behavioral variant frontotemporal dementia. Archives of neurology. 2008;65:249–255. [PMC free article] [PubMed]
  • Seeley WW, Crawford RK, Zhou J, Miller BL, Greicius MD. Neurodegenerative diseases target large-scale human brain networks. Neuron. 2009;62:42–52. [PMC free article] [PubMed]
  • Shaw LM, Korecka M, Clark CM, Lee VM, Trojanowski JQ. Biomarkers of neurodegeneration for diagnosis and monitoring therapeutics. Nature reviews. 2007;6:295–303. [PubMed]
  • Shaw LM, Vanderstichele H, Knapik-Czajka M, Clark CM, Aisen PS, Petersen RC, Blennow K, Soares H, Simon A, Lewczuk P, Dean R, Siemers E, Potter W, Lee VM, Trojanowski JQ. Cerebrospinal fluid biomarker signature in Alzheimer’s disease neuroimaging initiative subjects. Annals of neurology. 2009;65:403–413. [PMC free article] [PubMed]
  • Shaw LM, Vanderstichele H, Knapik-Czajka M, Figurski M, Coart E, Blennow K, Soares H, Simon AJ, Lewczuk P, Dean RA, Siemers E, Potter W, Lee VM, Trojanowski JQ. Qualification of the analytical and clinical performance of CSF biomarker analyses in ADNI. Acta neuropathologica. 2011 [PMC free article] [PubMed]
  • Sreedharan J, Blair IP, Tripathi VB, Hu X, Vance C, Rogelj B, Ackerley S, Durnall JC, Williams KL, Buratti E, Baralle F, de Belleroche J, Mitchell JD, Leigh PN, Al-Chalabi A, Miller CC, Nicholson G, Shaw CE. TDP-43 mutations in familial and sporadic amyotrophic lateral sclerosis. Science (New York, N.Y. 2008;319:1668–1672. [PubMed]
  • Steinacker P, Hendrich C, Sperfeld AD, Jesse S, von Arnim CA, Lehnert S, Pabst A, Uttner I, Tumani H, Lee VM, Trojanowski JQ, Kretzschmar HA, Ludolph A, Neumann M, Otto M. TDP-43 in cerebrospinal fluid of patients with frontotemporal lobar degeneration and amyotrophic lateral sclerosis. Archives of neurology. 2008;65:1481–1487. [PMC free article] [PubMed]
  • Strong MJ, Lomen-Hoerth C, Caselli RJ, Bigio EH, Yang W. Cognitive impairment, frontotemporal dementia, and the motor neuron diseases. Annals of neurology. 2003;54(Suppl 5):S20–23. [PubMed]
  • Suarez J, Tartaglia MC, Vitali P, Erbetta A, Neuhaus J, Laluz V, Miller BL. Characterizing radiology reports in patients with frontotemporal dementia. Neurology. 2009;73:1073–1074. [PMC free article] [PubMed]
  • Trojanowski JQ, Arnold SE, Karlawish JH, Brunden K, Cary M, Davatzikos C, Detre J, Gaulton G, Grossman M, Hurtig H, Jedrziewski K, McCluskey L, Naylor M, Polsky D, Schellenberg GD, Siderowf A, Shaw LM, Van Deerlin V, Wang LS, Werner R, Xie SX, Lee VM. Design of comprehensive Alzheimer’s disease centers to address unmet national needs. Alzheimers Dement. 2010a;6:150–155. [PMC free article] [PubMed]
  • Trojanowski JQ, Vandeerstichele H, Korecka M, Clark CM, Aisen PS, Petersen RC, Blennow K, Soares H, Simon A, Lewczuk P, Dean R, Siemers E, Potter WZ, Weiner MW, Jack CR, Jr., Jagust W, Toga AW, Lee VM, Shaw LM. Update on the biomarker core of the Alzheimer’s Disease Neuroimaging Initiative subjects. Alzheimers Dement. 2010b;6:230–238. [PMC free article] [PubMed]
  • Tsuboi Y, Yamada T. Increased concentration of C4d complement protein in CSF in amyotrophic lateral sclerosis. Journal of neurology, neurosurgery, and psychiatry. 1994;57:859–861. [PMC free article] [PubMed]
  • Urwin H, Josephs KA, Rohrer JD, Mackenzie IR, Neumann M, Authier A, Seelaar H, Van Swieten JC, Brown JM, Johannsen P, Nielsen JE, Holm IE, Dickson DW, Rademakers R, Graff-Radford NR, Parisi JE, Petersen RC, Hatanpaa KJ, White CL, 3rd, Weiner MF, Geser F, Van Deerlin VM, Trojanowski JQ, Miller BL, Seeley WW, van der Zee J, Kumar-Singh S, Engelborghs S, De Deyn PP, Van Broeckhoven C, Bigio EH, Deng HX, Halliday GM, Kril JJ, Munoz DG, Mann DM, Pickering-Brown SM, Doodeman V, Adamson G, Ghazi-Noori S, Fisher EM, Holton JL, Revesz T, Rossor MN, Collinge J, Mead S, Isaacs AM. FUS pathology defines the majority of tau- and TDP-43-negative frontotemporal lobar degeneration. Acta neuropathologica. 2010;120:33–41. [PMC free article] [PubMed]
  • Van Deerlin VM, Sleiman PM, Martinez-Lage M, Chen-Plotkin A, Wang LS, Graff-Radford NR, Dickson DW, Rademakers R, Boeve BF, Grossman M, Arnold SE, Mann DM, Pickering-Brown SM, Seelaar H, Heutink P, van Swieten JC, Murrell JR, Ghetti B, Spina S, Grafman J, Hodges J, Spillantini MG, Gilman S, Lieberman AP, Kaye JA, Woltjer RL, Bigio EH, Mesulam M, Al-Sarraj S, Troakes C, Rosenberg RN, White CL, 3rd, Ferrer I, Llado A, Neumann M, Kretzschmar HA, Hulette CM, Welsh-Bohmer KA, Miller BL, Alzualde A, de Munain AL, McKee AC, Gearing M, Levey AI, Lah JJ, Hardy J, Rohrer JD, Lashley T, Mackenzie IR, Feldman HH, Hamilton RL, Dekosky ST, van der Zee J, Kumar-Singh S, Van Broeckhoven C, Mayeux R, Vonsattel JP, Troncoso JC, Kril JJ, Kwok JB, Halliday GM, Bird TD, Ince PG, Shaw PJ, Cairns NJ, Morris JC, McLean CA, DeCarli C, Ellis WG, Freeman SH, Frosch MP, Growdon JH, Perl DP, Sano M, Bennett DA, Schneider JA, Beach TG, Reiman EM, Woodruff BK, Cummings J, Vinters HV, Miller CA, Chui HC, Alafuzoff I, Hartikainen P, Seilhean D, Galasko D, Masliah E, Cotman CW, Tunon MT, Martinez MC, Munoz DG, Carroll SL, Marson D, Riederer PF, Bogdanovic N, Schellenberg GD, Hakonarson H, Trojanowski JQ, Lee VM. Common variants at 7p21 are associated with frontotemporal lobar degeneration with TDP-43 inclusions. Nature genetics. 2010;42:234–239. [PMC free article] [PubMed]
  • Van Rooij FG, Schelhaas HJ, Lammers GJ, Verbeek MM, Overeem S. CSF hypocretin-1 levels are normal in patients with amyotrophic lateral sclerosis. Amyotroph Lateral Scler. 2009;10:487–489. [PubMed]
  • Vance C, Rogelj B, Hortobagyi T, De Vos KJ, Nishimura AL, Sreedharan J, Hu X, Smith B, Ruddy D, Wright P, Ganesalingam J, Williams KL, Tripathi V, Al-Saraj S, Al-Chalabi A, Leigh PN, Blair IP, Nicholson G, de Belleroche J, Gallo JM, Miller CC, Shaw CE. Mutations in FUS, an RNA processing protein, cause familial amyotrophic lateral sclerosis type 6. Science (New York, N.Y. 2009;323:1208–1211. [PubMed]
  • Vanmechelen E, Vanderstichele H, Davidsson P, Van Kerschaver E, Van Der Perre B, Sjogren M, Andreasen N, Blennow K. Quantification of tau phosphorylated at threonine 181 in human cerebrospinal fluid: a sandwich ELISA with a synthetic phosphopeptide for standardization. Neuroscience letters. 2000;285:49–52. [PubMed]
  • Vanvoorst WA, Greenaway MC, Boeve BF, Ivnik RJ, Parisi JE, Ahlskog J. Eric, Knopman DS, Dickson DW, Petersen RC, Smith GE, Josephs KA. Neuropsychological findings in clinically atypical autopsy confirmed corticobasal degeneration and progressive supranuclear palsy. Parkinsonism & related disorders. 2008;14:376–378. [PMC free article] [PubMed]
  • Vass R, Ashbridge E, Geser F, Hu WT, Grossman M, Clay-Falcone D, Elman L, McCluskey L, Lee VM, Van Deerlin VM, Trojanowski JQ, Chen-Plotkin AS. Risk genotypes at TMEM106B are associated with cognitive impairment in amyotrophic lateral sclerosis. Acta neuropathologica. 2010 [PMC free article] [PubMed]
  • Verwey NA, van der Flier WM, Blennow K, Clark C, Sokolow S, De Deyn PP, Galasko D, Hampel H, Hartmann T, Kapaki E, Lannfelt L, Mehta PD, Parnetti L, Petzold A, Pirttila T, Saleh L, Skinningsrud A, Swieten JC, Verbeek MM, Wiltfang J, Younkin S, Scheltens P, Blankenstein MA. A worldwide multicentre comparison of assays for cerebrospinal fluid biomarkers in Alzheimer’s disease. Annals of clinical biochemistry. 2009;46:235–240. [PubMed]
  • Wang Y, Klunk WE, Huang GF, Debnath ML, Holt DP, Mathis CA. Synthesis and evaluation of 2-(3′-iodo-4′-aminophenyl)-6-hydroxybenzothiazole for in vivo quantitation of amyloid deposits in Alzheimer’s disease. J Mol Neurosci. 2002;19:11–16. [PubMed]
  • Whitwell JL, Avula R, Senjem ML, Kantarci K, Weigand SD, Samikoglu A, Edmonson HA, Vemuri P, Knopman DS, Boeve BF, Petersen RC, Josephs KA, Jack CR., Jr. Gray and white matter water diffusion in the syndromic variants of frontotemporal dementia. Neurology. 2010;74:1279–1287. [PMC free article] [PubMed]
  • Whitwell JL, Jack CR, Jr., Parisi JE, Knopman DS, Boeve BF, Petersen RC, Ferman TJ, Dickson DW, Josephs KA. Rates of cerebral atrophy differ in different degenerative pathologies. Brain. 2007;130:1148–1158. [PMC free article] [PubMed]
  • Whitwell JL, Josephs KA, Rossor MN, Stevens JM, Revesz T, Holton JL, Al-Sarraj S, Godbolt AK, Fox NC, Warren JD. Magnetic resonance imaging signatures of tissue pathology in frontotemporal dementia. Archives of neurology. 2005;62:1402–1408. [PubMed]
  • Whitwell JL, Warren JD, Josephs KA, Godbolt AK, Revesz T, Fox NC, Rossor MN. Voxel-based morphometry in tau-positive and tau-negative frontotemporal lobar degenerations. Neuro-degenerative diseases. 2004;1:225–230. [PubMed]
  • Wong DF, Rosenberg PB, Zhou Y, Kumar A, Raymont V, Ravert HT, Dannals RF, Nandi A, Brasic JR, Ye W, Hilton J, Lyketsos C, Kung HF, Joshi AD, Skovronsky DM, Pontecorvo MJ. In vivo imaging of amyloid deposition in Alzheimer disease using the radioligand 18F-AV-45 (florbetapir [corrected] F 18) J Nucl Med. 2010;51:913–920. [PMC free article] [PubMed]
  • Wuolikainen A, Hedenstrom M, Moritz T, Marklund SL, Antti H, Andersen PM. Optimization of procedures for collecting and storing of CSF for studying the metabolome in ALS. Amyotroph Lateral Scler. 2009;10:229–236. [PubMed]
  • Xiong L, Xuereb JH, Spillantini MG, Patterson K, Hodges JR, Nestor PJ. Clinical comparison of progressive aphasia associated with Alzheimer versus FTD-spectrum pathology. Journal of neurology, neurosurgery, and psychiatry. 2010 [PubMed]
  • Yamada T, Moroo I, Koguchi Y, Asahina M, Hirayama K. Increased concentration of C4d complement protein in the cerebrospinal fluids in progressive supranuclear palsy. Acta neurologica Scandinavica. 1994;89:42–46. [PubMed]
  • Yasui K, Inoue Y, Kanbayashi T, Nomura T, Kusumi M, Nakashima K. CSF orexin levels of Parkinson’s disease, dementia with Lewy bodies, progressive supranuclear palsy and corticobasal degeneration. Journal of the neurological sciences. 2006;250:120–123. [PubMed]
  • Zamboni G, Huey ED, Krueger F, Nichelli PF, Grafman J. Apathy and disinhibition in frontotemporal dementia: Insights into their neural correlates. Neurology. 2008;71:736–742. [PMC free article] [PubMed]
  • Zetterberg H, Jacobsson J, Rosengren L, Blennow K, Andersen PM. Cerebrospinal fluid neurofilament light levels in amyotrophic lateral sclerosis: impact of SOD1 genotype. Eur J Neurol. 2007;14:1329–1333. [PubMed]
  • Zhang Y, Schuff N, Du AT, Rosen HJ, Kramer JH, Gorno-Tempini ML, Miller BL, Weiner MW. White matter damage in frontotemporal dementia and Alzheimer’s disease measured by diffusion MRI. Brain. 2009;132:2579–2592. [PMC free article] [PubMed]
  • Zhou J, Greicius MD, Gennatas ED, Growdon ME, Jang JY, Rabinovici GD, Kramer JH, Weiner M, Miller BL, Seeley WW. Divergent network connectivity changes in behavioural variant frontotemporal dementia and Alzheimer’s disease. Brain. 2010a;133:1352–1367. [PMC free article] [PubMed]
  • Zhou JY, Afjehi-Sadat L, Asress S, Duong DM, Cudkowicz M, Glass JD, Peng J. Galectin-3 is a candidate biomarker for amyotrophic lateral sclerosis: discovery by a proteomics approach. Journal of proteome research. 2010b;9:5133–5141. [PMC free article] [PubMed]