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Apoe 2-4 genotype is a possible risk factor for primary progressive aphasia.

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Table. Apolipoprotein E Allele and Genotype Frequencies in Patients Affected by FTD and PPA and in Age-Matched Controls
FTD vs Controls
Frequency
ε2 allele frequency
ε3 allele frequency
ε4 allele frequency
ε2ε2 genotype
frequency
ε2ε3 genotype
frequency
ε2ε4 genotype
frequency
ε3ε3 genotype
frequency
ε3ε4 genotype
frequency
ε4ε4 genotype
frequency
Controls
FTD
␹2
p
PPA vs Controls
OR (95% CI)
PPA
␹2
p
OR (95% CI)
5.2%
85.6%
9.2%
0.0%
14.1%
4.09
0.0430
62.5%
13.93
0.0002
23.4%
7.17
0.0074
0.0% Fisher’s test ⬎0.9999
3.00 (1.13–7.94)
0.28 (0.14–0.54)
3.02 (1.39–6.55)
20.0%
6.23
0.0126
50.0%
18.41
⬍0.0001
30.0%
8.46
0.0036
0.0% Fisher’s test ⬎0.9999
4.85 (1.50–14.02)
0.17 (0.07–0.38)
4.23 (1.66–10.78)
9.2%
15.6% Fisher’s test ⬎0.9999
1.83 (0.55–6.07)
13.3% Fisher’s test ⬎0.9999
1.52 (0.29–7.96)
1.1%
12.5% Fisher’s test
0.018
72.4%
40.6%
8.91
0.0028
0.26 (0.11–0.61)
26.7% Fisher’s test
17.2%
28.1%
1.11
0.2917
1.88 (0.73–4.86)
33.3% Fisher’s test ⬎0.9999
0.0%
3.1% Fisher’s test
12.29 (1.32–114.53) 26.7% Fisher’s test
0.001
31.27 (3.20–300.56)
0.001
0.14 (0.04–0.48)
2.40 (0.72–8.04)
0.0% Fisher’s test ⬎0.9999
0.2690
There were 87 control subjects (mean age ⫾ SD, 62.6 ⫾ 4.7 yr), 32 FTD subjects (mean age ⫾ SD, 63.9 ⫾ 6.6 yr), and 15 PPA subjects
(mean age ⫾ SD, 63.4 ⫾ 6.5).
FTD ⫽ frontotemporal dementia; PPA ⫽ primary progressive aphasia; SD ⫽ standard deviation; OR ⫽ odd ratio; CI ⫽ confidence interval.
APOE ␧2-␧4 Genotype Is a Possible Risk Factor
for Primary Progressive Aphasia
Adele Acciarri, MD,1 Carlo Masullo, MD,1
Alessandra Bizzarro, MD,1 Alessandro Valenza, MD,1
Davide Quaranta, MD,1 Camillo Marra, MD, PhD,1
Francesco D. Tiziano, MD,2 Christina Brahe, PhD,2
Davide Seripa, PhD,3 Maria G. Matera, PhD,3
Vito M. Fazio, MD,4 Guido Gainotti, MD,1 and
Antonio Daniele, MD, PhD1
Although the pathogenic mechanisms involved in frontotemporal dementia (FTD) are poorly known, the frequent occurrence of familial cases suggests the importance of genetic
factors. The role of apolipoprotein E (ApoE) in FTD is controversial.1 An increased frequency of ApoE ε4 allele in patients with FTD and primary progressive aphasia (PPA) was
reported in some studies, but not in others. An increased
frequency of ε2 allele was detected in FTD, at variance with
other investigations.1 Homozygosity for ε2ε2 genotype was
also proposed as a risk factor for FTD.2
We examined 32 patients with a clinical diagnosis of
probable FTD,3 including 15 patients with PPA,4 and 87
age-matched non-demented controls. Patients and controls
were white, with Central Italian ancestry. ApoE genotyping
was performed as previously described.1
As compared with controls (Table), in the FTD group
and the PPA subgroup, there was a significant increase of ε2
and ε4 allele frequencies and a highly significant decrease of
ε3 allele frequency. As compared with controls (Table), we
observed in FTD group and the PPA subgroup a significant
increase of ε2ε4 genotype frequency and a significant decrease of ε3ε3 genotype. All four FTD patients carrying the
ε2ε4 genotype were affected by PPA.
This study of a relatively large series of patients with a
clinical diagnosis of FTD suggests that ApoE ε2ε4 genotype
might represent a genetic risk factor for PPA, whereas ε2 and
ε4 alleles might be risk factors for FTD and PPA. Con-
436
Annals of Neurology
Vol 59
No 2
February 2006
versely, ε3ε3 genotype and ε3 allele might have protective
effects for FTD and PPA.
At variance with the protective role of ε2 allele in Alzheimer’s disease (AD), this allele might play a pathogenic role in
FTD and other neurodegenerative conditions, because it may
increase the risk of Parkinson’s disease (PD) and the risk of
dementia in PD. The pathogenic role of ε4 allele in FTD
must be supported by neuropathologically confirmed studies,
because an increased ε4 frequency might be caused by the
inadvertent inclusion of patients with misdiagnosed AD. Although the association of ε2ε4 heterozygosity and PPA
might be because of insufficient size or unknown specific features of our sample, such association may be explained by
molecular heterosis, because subjects heterozygous for a genetic polymorphism may show a significantly greater effect
(positive heterosis) for a quantitative or dichotomous trait
than homozygotes for either allele.5 Further investigations on
larger samples are required to clarify the role of ApoE ε2ε4
genotype in PPA and FTD and to elucidate the possible
pathogenic mechanisms of risk and protection related to
ApoE in these conditions.
1
Institute of Neurology, 2Institute of Medical Genetics,
Catholic University School of Medicine, Rome, Italy,
3
Pathology of Aging Research Unit, I.R.C.C.S. “Casa Sollievo
della Sofferenza,” S. Giovanni Rotondo, FG, Italy, and
4
Laboratory of Molecular Medicine and Biotechnology,
Campus Bio-Medico University School of Medicine,
Rome, Italy
References
1. Masullo C, Daniele A, Fazio VM, et al. The apolipoprotein E
genotype in patients affected by syndromes with focal cortical
atrophy. Neurosci Lett 2001;303:87–90.
2. Verpillat P, Camuzat A, Hannequin D, et al. Apolipoprotein E
gene in frontotemporal dementia: an association study and metaanalysis. Eur J Hum Genet 2002;10:399 – 405.
3. McKhann GM, Albert MS, Grossman M, et al. Clinical and
pathological diagnosis of frontotemporal dementia: report of the
Work Group on Frontotemporal Dementia and Pick’s Disease.
Arch Neurol 2001;58:1803–1809.
4. Mesulam MM. Primary progressive aphasia. Ann Neurol 2001;
49:425– 432.
5. Comings DE, MacMurray JP. Molecular heterosis: a review. Mol
Genet Metab 2000;71:19 –31.
DOI: 10.1002/ana.20780
Can We Identify a CT-based Tissue Window for
Thrombolysis Without CTP?
Imanuel Dzialowski,1,2 Andrew Demchuk,1
Shelagh Coutts,1 Michael Hill,1 Marc Hudon,1
Ting-Yim Lee,3 and Ruediger Von Kummer3
Our congratulations to Parsons and colleagues for their novel
work on qualitative computed tomography perfusion (CTP)
imaging using the Alberta Stroke Program Early CT Score
(ASPECTS).1
In patients presenting with acute anterior circulation
stroke within 6 hours from symptom onset, the authors
showed that scoring ASPECTS on CTP parameter images
improves prediction of final infarct and outcome as compared with noncontrast CT (NCCT) or CT angiography
source-images (CTA-SI). In addition, their work contributes to increasing evidence that infarct core as well as tissue
at risk might be reliably identified by CTP (Murphy et al.
personal communication).2 However, we would like to discuss with the authors two issues that might contribute to
further understanding and development of this technique.
First, the authors did not mention which thresholds they
used to determine abnormal ASPECTS regions on parametric maps for relative cerebral blood flow (rCBF), cerebral
blood volume (rCBV), and mean transit time (rMTT). Depending on window and leveling, “dark blue or black” regions might represent different relative perfusion thresholds,
for example, 0.2 versus 0.3 for rCBF. With this information
lacking, results might be difficult to reproduce among different perfusion software and hardware manufacturers. Furthermore, it would be interesting to learn about incidence and
tissue outcome of ASPECTS regions with reduced rCBF but
increased rCBV.
Second, based on our ASPECTS analysis in a similar cohort studying patients with middle cerebral artery occlusions within 6 hours from symptom onset,3 we are currently testing the hypothesis that a favorable NCCT scan
(ASPECTS ⱖ6) in the presence of intracranial arterial occlusion predicts benefit from thrombolysis in a greater than
3-hour time window. NCCT (or CTA-SI) ASPECTS estimates infarct core, and intracranial occlusion on CT angiography or transcranial Doppler sonography acts as surrogate marker for large perfusion deficit. This approach
would be rapid and practical especially for stroke physicians
lacking advanced CT technology. To learn more about the
additional value of CTP compared with our approach, we
would like to ask the authors the following: did a rCBVASPECTS ⬎ rCBF-ASPECTS mismatch occur in patients
without demonstrable arterial occlusion? Which proportion
of patients with and without ASPECTS ⱖ6 and proximal
occlusion (M1 and ICA) showed this mismatch and how
did this proportion differ from patients with distal (M2)
occlusions?
We are looking forward to studying more data on this
important and evolving technology.
1
University of Calgary, Clinical Neurosciences, Calgary,
Alberta, Canada; 2University of Dresden, Department of
Neuroradiology, Dresden, Germany; and 3University of
Western Ontario, Robarts Research Institute, London,
Ontario, Canada
References
1. Parsons MW, Pepper EM, Chan V, et al. Perfusion computed
tomography: prediction of final infarct extent and stroke outcome. Ann Neurol 2005;58:672– 679.
2. Wintermark M, Reichhart M, Thiran JP, et al. Prognostic accuracy of cerebral blood flow measurement by perfusion computed
tomography, at the time of emergency room admission, in acute
stroke patients. Ann Neurol 2002;51:417– 432
3. Hill MD, Rowley HA, Adler F, et al. Selection of acute ischemic
stroke patients for intra-arterial thrombolysis with pro-urokinase
by using ASPECTS. Stroke 2003;34:1925–1931.
DOI: 10.1002/ana.20782
Annals of Neurology
Vol 59
No 1
January 2006
437
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