Search

BackgroundGenome-wide Association Studies (GWAS) have reshaped our understanding of the genetic bases of complex diseases in general and neurodegenerative diseases in particular. Despite being a common disorder, dementia with Lewy bodies (DLB), which, together with Parkinson’s disease dementia (PDD), comprise the umbrella term Lewy body dementias (LBD), is far from being well-characterized genetically. This is primarily due to a lack of familial cases and difficulty recruiting large, deeply characterized cohorts, given the high rate of misdiagnosis. By performing the largest GWAS in DLB, we aimed to identify novel risk loci to gain a better understanding of this disease’s pathobiology.MethodsHere, we conducted the largest meta-analysis of genome-wide association studies performed in LBD, using a total of 5,119 cases and 20,988 controls, from five independent datasets, aggregating all previously published DLB genome-wide association results to date, as well as two previously undescribed cohorts. Additionally, we performed a sex stratified GWAS using the discovery datasets. We updated the heritability estimates for DLB and, to fine map these estimates, we used local heritability analysis. We calculated genetic correlation estimates between DLB and a range of other diseases and traits to identify potential pleiotropy. We also performed gene-set analysis to identify genes with excess burden of rare variability and pathway analysis. Lastly, we used the UK Biobank data to perform a PheWas using individuals at the extremes of genetic risk for DLB.FindingsBetween November 2018 and September 2022 we analyzed 8.6 million single nucleotide polymorphisms in 3293 DLB cases, 1826 LBD cases and 20,988 controls, as well as phenotypes from the UK Biobank dataset. Despite more than doubling the sample size from the previous GWAS in DLB, we did not identify significant loci in addition to those previously reported atGBA, SNCA, STX1B, andAPOE. However, the sex-stratified analysis revealed that theGBAandSNCAsignals are mainly driven by males, suggesting a sex-specific genetic architecture of disease. Using only clinical and neuropathologically diagnosed cases, we highlight four loci surpassing the significance threshold. Using the largest cohort of DLB we update our heritability estimates to 13% and fine map these results highlighting regions of the genome with high heritability but no genome-wide significant result so far.InterpretationThese data provide the most comprehensive analysis of genetic variability in DLB to date. The fact that no novel risk loci have been identified after doubling the cohort size indicates the potentially significant role of rare variants in the genetic architecture of DLB and stresses the urgent need for larger, well-characterized cohorts of this disease for genetic studies. The sex-stratified analysis shows that males and females have different signatures of genetic risk for DLB. These results have widespread implications for clinical practice and clinical trials’ design in DLB.

Background: Mild cognitive impairment (MCI) due to Alzheimer’s disease (AD) diagnosis is based on cerebrospinal fluid (CSF) or neuroimaging biomarkers. Currently, non-invasive and inexpensive blood-based biomarkers are being investigated, such as neuronal-derived plasma exosomes (NPEs). Neuroinflammation and early vascular changes have been described in AD pathogenesis and can be traced in plasma and NPEs. However, they have not been studied in early onset MCI (EOMCI). Objective: To describe the rationale, design, and baseline characteristics of the participants from the BIOFACE cohort, a two-year observational study on EOMCI conducted at Fundació ACE. The study goal is to characterize the different phenotypes from a clinical, neuropsychological, and biomarker point of view and to investigate the CSF and plasma proteomics as well as the role of NPEs as early biomarkers of AD. Methods: Participants underwent extended neurological and neuropsychological batteries, multimodal biomarkers including brain MRI, blood, saliva, CSF, anthropometric, and neuro-ophthalmological examinations. Results: Ninety-seven patients with EOMCI were recruited. 59.8%were women. Mean age at symptom onset was 57 years; mean MMSE was 28. First degree and presenile family history of dementia was present in 60.8%and 15.5%, respectively. Depressive and anxiety disorders along with vascular risk factors were the most frequent comorbidities. 29%of participants were APOE ɛ4 carriers, and 67%showed a CSF normal ATN profile. Conclusion: BIOFACE is a two-year study of clinical, cognition, and biomarkers that will shed light on the physiopathology and the potential utility of plasma and NPEs as non-invasive early diagnostic and prognostic biomarkers in people younger than 65 years.

Background FACEmemory® is the first computerized, self-administered verbal episodic memory test with voice recognition. It can be conducted under minimal supervision and contains an automatic scoring system to avoid administrator errors. Moreover, it is suitable for discriminating between cognitively healthy and amnestic mild cognitive impairment (MCI) individuals, and it is associated with Alzheimer’s disease (AD) cerebrospinal fluid (CSF) biomarkers. This study aimed to determine whether FACEmemory scoring is related to performance on classical memory tests and to AD biomarkers of brain magnetic resonance imaging (MRI) and CSF in patients with early-onset MCI (EOMCI). Methods Ninety-four patients with EOMCI from the BIOFACE study completed FACEmemory, classical memory tests (the Spanish version of the Word Free and Cued Selective Reminding Test -FCSRT-, the Word List from the Wechsler Memory Scale, third edition, and the Spanish version of the Rey–Osterrieth Complex Figure Test), and a brain MRI. Eighty-two individuals also underwent a lumbar puncture. Results FACEmemory scoring was moderately correlated with FCSRT scoring. With regard to neuroimaging MRI results, worse execution on FACEmemory was associated with lower cortical volume in the right prefrontal and inferior parietal areas, along with the left temporal and associative occipital areas. Moreover, the total FACEmemory score correlated with CSF AD biomarkers (Aβ1-42/Aβ1-40 ratio, p181-tau, and Aβ1-42/p181-tau ratio). When performance on FACEmemory was compared among the ATN classification groups, significant differences between the AD group and normal and SNAP groups were found. Conclusions FACEmemory is a promising tool for detecting memory deficits sensitive to early-onset AD, but it also allows the detection of memory-impaired cases due to other etiologies. Our findings suggest that FACEmemory scoring can detect the AD endophenotype and that it is also associated with AD-related changes in MRI and CSF in patients with EOMCI. The computerized FACEmemory tool might be an opportunity to facilitate early detection of MCI in younger people than 65, who have a growing interest in new technologies.

Background A low amount and extent of Aβ deposition at early stages of Alzheimer’s disease (AD) may limit the use of previously developed pathology-proven composite SUVR cutoffs. This study aims to characterize the population with earliest abnormal Aβ accumulation using 18F-florbetaben PET. Quantitative thresholds for the early (SUVRearly) and established (SUVRestab) Aβ deposition were developed, and the topography of early Aβ deposition was assessed. Subsequently, Aβ accumulation over time, progression from mild cognitive impairment (MCI) to AD dementia, and tau deposition were assessed in subjects with early and established Aβ deposition. Methods The study population consisted of 686 subjects (n = 287 (cognitively normal healthy controls), n = 166 (subjects with subjective cognitive decline (SCD)), n = 129 (subjects with MCI), and n = 101 (subjects with AD dementia)). Three categories in the Aβ-deposition continuum were defined based on the developed SUVR cutoffs: Aβ-negative subjects, subjects with early Aβ deposition (“gray zone”), and subjects with established Aβ pathology. Results SUVR using the whole cerebellum as the reference region and centiloid (CL) cutoffs for early and established amyloid pathology were 1.10 (13.5 CL) and 1.24 (35.7 CL), respectively. Cingulate cortices and precuneus, frontal, and inferior lateral temporal cortices were the regions showing the initial pathological tracer retention. Subjects in the “gray zone” or with established Aβ pathology accumulated more amyloid over time than Aβ-negative subjects. After a 4-year clinical follow-up, none of the Aβ-negative or the gray zone subjects progressed to AD dementia while 91% of the MCI subjects with established Aβ pathology progressed. Tau deposition was infrequent in those subjects without established Aβ pathology. Conclusions This study supports the utility of using two cutoffs for amyloid PET abnormality defining a “gray zone”: a lower cutoff of 13.5 CL indicating emerging Aβ pathology and a higher cutoff of 35.7 CL where amyloid burden levels correspond to established neuropathology findings. These cutoffs define a subset of subjects characterized by pre-AD dementia levels of amyloid burden that precede other biomarkers such as tau deposition or clinical symptoms and accelerated amyloid accumulation. The determination of different amyloid loads, particularly low amyloid levels, is useful in determining who will eventually progress to dementia. Quantitation of amyloid provides a sensitive measure in these low-load cases and may help to identify a group of subjects most likely to benefit from intervention. Trial registration Data used in this manuscript belong to clinical trials registered in ClinicalTrials.gov (NCT00928304, NCT00750282, NCT01138111, NCT02854033) and EudraCT (2014-000798-38).

Background A low amount and extent of Aβ deposition at early stages of Alzheimer’s disease (AD) may limit the use of previously developed pathology-proven composite SUVR cutoffs. This study aims to characterize the population with earliest abnormal Aβ accumulation using 18F-florbetaben PET. Quantitative thresholds for the early (SUVRearly) and established (SUVRestab) Aβ deposition were developed, and the topography of early Aβ deposition was assessed. Subsequently, Aβ accumulation over time, progression from mild cognitive impairment (MCI) to AD dementia, and tau deposition were assessed in subjects with early and established Aβ deposition. Methods The study population consisted of 686 subjects (n = 287 (cognitively normal healthy controls), n = 166 (subjects with subjective cognitive decline (SCD)), n = 129 (subjects with MCI), and n = 101 (subjects with AD dementia)). Three categories in the Aβ-deposition continuum were defined based on the developed SUVR cutoffs: Aβ-negative subjects, subjects with early Aβ deposition (“gray zone”), and subjects with established Aβ pathology. Results SUVR using the whole cerebellum as the reference region and centiloid (CL) cutoffs for early and established amyloid pathology were 1.10 (13.5 CL) and 1.24 (35.7 CL), respectively. Cingulate cortices and precuneus, frontal, and inferior lateral temporal cortices were the regions showing the initial pathological tracer retention. Subjects in the “gray zone” or with established Aβ pathology accumulated more amyloid over time than Aβ-negative subjects. After a 4-year clinical follow-up, none of the Aβ-negative or the gray zone subjects progressed to AD dementia while 91% of the MCI subjects with established Aβ pathology progressed. Tau deposition was infrequent in those subjects without established Aβ pathology. Conclusions This study supports the utility of using two cutoffs for amyloid PET abnormality defining a “gray zone”: a lower cutoff of 13.5 CL indicating emerging Aβ pathology and a higher cutoff of 35.7 CL where amyloid burden levels correspond to established neuropathology findings. These cutoffs define a subset of subjects characterized by pre-AD dementia levels of amyloid burden that precede other biomarkers such as tau deposition or clinical symptoms and accelerated amyloid accumulation. The determination of different amyloid loads, particularly low amyloid levels, is useful in determining who will eventually progress to dementia. Quantitation of amyloid provides a sensitive measure in these low-load cases and may help to identify a group of subjects most likely to benefit from intervention. Trial registration Data used in this manuscript belong to clinical trials registered in ClinicalTrials.gov (NCT00928304, NCT00750282, NCT01138111, NCT02854033) and EudraCT (2014-000798-38).

BACKGROUND Recruitment methods can determine sample characteristics in mild cognitive impairment and Alzheimer's disease dementia, but little is known about its influence in subjective cognitive decline (SCD). OBJECTIVE To determine the influence of two types of recruitment methods in the characteristics of individuals with SCD. METHODS We select and compare clinical and neuropsychological features, and frequency of APOE ɛ4 allele of 326 subjects with SCD from two cohorts: Open House Initiative (OHI) versus Memory Unit (MU). A logistic regression analysis (LRA), using gender and years of education as covariates, was used to examine the neuropsychological variables. RESULTS The OHI sample were mostly women (75.9% versus 64.5%, p

// Sonia Moreno-Grau 1 , Isabel Hernandez 1 , Stefanie Heilmann-Heimbach 2, 3 , Susana Ruiz 1 , Maitee Rosende-Roca 1 , Ana Mauleon 1 , Liliana Vargas 1 , Octavio Rodriguez-Gomez 1 , Montserrat Alegret 1 , Ana Espinosa 1 , Gemma Ortega 1 , Nuria Aguilera 1 , Carla Abdelnour 1 , Alzheimer’s Disease Neuroimaging Initiative * , Silvia Gil 1 , Wolfgang Maier 4, 5 , Oscar Sotolongo-Grau 1 , Lluis Tarraga 1 , Alfredo Ramirez 2, 4, 6 , Jesus Lopez-Arrrieta 7 , Carmen Antunez 8 , Manuel Serrano-Rios 9 , Merce Boada 1 and Agustin Ruiz 1 1 Research Center and Memory Clinic of Fundacio ACE, Institut Catala de Neurociencies Aplicades, Univesitat Internacional de Catalunya, Barcelona, Spain 2 Institute of Human Genetics, University of Bonn, Bonn, Germany 3 Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany 4 Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany 5 German Center for Neurodegenerative Diseases, DZNE, Bonn, Germany 6 Department of Psychiatry and Psychotherapy, University of Cologne, Cologne, Germany 7 Memory Unit, University Hospital La Paz-Cantoblanco, Madrid, Spain 8 Dementia Unit, University Hospital Virgen de la Arrixaca, Murcia, Spain 9 Centro de Investigacion Biomedica en Red de Diabetes y Enfermedades Metabolicas Asociadas, CIBERDEM, Spain, Hospital Clinico San Carlos, Madrid, Spain * Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or Provided data but did not participate in analysis or writing of this report Correspondence to: Agustin Ruiz, email: aruiz@fundacioace.com Keywords: late onset Alzheimer’s disease; ABCA7; APOE; CD33; linkage disequilibrium; Gerotarget Received: December 13, 2017 Accepted: March 22, 2018 Published: May 15, 2018 ABSTRACT The apolipoprotein E ( APOE ) gene on chromosome 19q13.32, was the first, and remains the strongest, genetic risk factor for Alzheimer’s disease (AD). Additional signals associated with AD have been located in chromosome 19, including ABCA7 (19p13.3) and CD33 (19q13.41). The ABCA7 gene has been replicated in most populations. However, the contribution to AD of other signals close to APOE gene remains controversial. Possible explanations for inconsistency between reports include long range linkage disequilibrium (LRLD). We analysed the contribution of ABCA7 and CD33 loci to AD risk and explore LRLD patterns across APOE region. To evaluate AD risk conferred by ABCA7 rs4147929:G>A and CD33 rs3865444:C>A, we used a large Spanish population (1796 AD cases, 2642 controls). The ABCA7 rs4147929:G>A SNP effect was nominally replicated in the Spanish cohort and reached genome-wide significance after meta-analysis (odds ratio (OR)=1.15, 95% confidence interval (95% CI)=1.12–1.19; P = 1.60 x 10 -19 ). CD33 rs3865444:C>A was not associated with AD in the dataset. The meta-analysis was also negative (OR=0.98, 95% CI=0.93–1.04; P =0.48). After exploring LRLD patterns between APOE and CD33 in several datasets, we found significant LD (D’ >0.20; P A in two of five datasets, suggesting the presence of a non-universal long range interaction between these loci affecting to some populations. In conclusion, we provide here evidence of genetic association of the ABCA7 locus in the Spanish population and also propose a plausible explanation for the controversy on the contribution of CD33 to AD susceptibility.

Background: Long-term longitudinal studies with multimodal biomarkers are needed to delve into the knowledge of preclinical AD. Subjective cognitive decline has been proposed as a risk factor for the development of cognitive impairment. Thus, including individuals with SCD in observational studies may be a cost-effective strategy to increase the prevalence of preclinical AD in the sample. Objectives: To describe the rationale, research protocols and baseline characteristics of participants in the Fundació ACE Healthy Brain Initiative (FACEHBI). Design: FACEHBI is a clinical trial (EudraCT: 2014-000798-38) embedded within a long-term observational study of individuals with SCD. Setting: Participants have been recruited at the memory clinic of Fundació ACE (Barcelona) from two different sources: patients referred by a general practitioner and individuals from an Open House Initiative. Participants: 200 individuals diagnosed with SCD with a strictly normal performance in a comprehensive neuropsychological battery. Measurements: Individuals will undergo an extensive neuropsychological protocol, risk factor assessment and a set of multimodal biomarkers including florbetaben PET, structural and functional MRI, diffusion tensor imaging, determination of amyloid species in plasma and neurophthalmologic assessment with optical coherence tomography. Results: Two hundred individuals have been recruited in 15 months. Mean age was 65.9 years; mean MMSE was 29.2 with a mean of 14.8 years of education. Conclusions: FACEHBI is a long-term study of cognition, biomarkers and lifestyle that has been designed upon an innovative symptom-based approach using SCD as target population. It will shed light on the pathophysiology of preclinical AD and the role of SCD as a risk marker for the development of cognitive impairment.

The Face-Name Associative Memory Exam (FNAME) is a paired associative memory test created to detect memory deficits in individuals with preclinical Alzheimer’s disease (AD). Worse performance on FNAME in cognitively healthy individuals were found related to higher amyloid beta (Aβ) burden measured with Positron-Emission-Tomography using 11C-PiB (PiB-PET). We previously reported normative data of a Spanish version of FNAME (S-FNAME) in cognitively healthy Spanish-speaking subjects. The aim of the present study was to determine whether performance on S-FNAME was associated with Aβ burden in subjective cognitive decline (SCD) individuals. 200 SCD subjects received neurological and neuropsychological assessments, including the S-FNAME and the Word List task from the Wechsler-Memory-Scale-III (WMS-III). Moreover, they received an MRI and (18)F-Florbetaben Positron-Emission-Tomography (FBB-PET) to measure Aβ burden. Three cognitive factor composites were derived for the episodic memory measures (face-name [SFN-N], face-occupation [SFN-O] and WMS-III) to determine whether episodic memory performance was related to Aβ deposition. Higher global Aβ deposition was significantly related to worse performance on SFN-N but not with SFN-O or WMS-III Composite. Moreover, worse SFN-N performance was significantly related to higher Aβ deposition in bilateral Posterior Cingulate Cortex. The S-FNAME may be a promising neuropsychological tool for detecting SCD individuals with preclinical AD.

Introduction Subjective cognitive decline (SCD) has been proposed as a potential preclinical stage of Alzheimer's disease (AD). Nevertheless, the genetic and biomarker profiles of SCD individuals remain mostly unexplored. Methods We evaluated apolipoprotein E ( APOE ) e4's effect in the risk of presenting SCD, using the Fundacio ACE Healthy Brain Initiative (FACEHBI) SCD cohort and Spanish controls, and performed a meta-analysis addressing the same question. We assessed the relationship between APOE dosage and brain amyloid burden in the FACEHBI SCD and Alzheimer's Disease Neuroimaging Initiative cohorts. Results Analysis of the FACEHBI cohort and the meta-analysis demonstrated SCD individuals presented higher allelic frequencies of APOE e4 with respect to controls. APOE dosage explained 9% (FACEHBI cohort) and 11% (FACEHBI and Alzheimer's Disease Neuroimaging Initiative cohorts) of the variance of cerebral amyloid levels. Discussion The FACEHBI sample presents APOE e4 enrichment, suggesting that a pool of AD patients is nested in our sample. Cerebral amyloid levels are partially explained by the APOE allele dosage, suggesting that other genetic or epigenetic factors are involved in this AD endophenotype.

SummaryGenetic studies suggest that hundreds of genes associated with stroke remain unidentified. Exome sequencing proves useful for finding new genes associated with stroke. We aimed to find new genetic risk factors for cardioembolic stroke by analysing exome sequence data using new strategies. For discovery, we analysed 42 cardioembolic stroke cases and controls with extreme phenotypes (cohort 1), and for replication, 32 cardioembolic stroke cases and controls (cohort 2) using the SeqCapExome capture kit. We then analysed the replicated genes in two new cohorts that comprised 834 cardioembolic strokes and controls (cohort 3) and 64,373 cardioembolic strokes and controls (cohort 4). Transcriptomic in-silico functional analyses were also performed. We found 26 coding regions with a higher frequency of mutations in cardioembolic strokes after correcting for the number of mutations found in the whole exome of every patient. The TRPV3 gene was associated with cardioembolic stroke after replication of exome sequencing analysis (p-value-discovery: 0.018, p-value-replication: 0.014). The analysis of the TRPV3 gene using polymorphisms in cohort 3 and 4 revealed two polymorphisms associated with cardioembolic stroke in both cohorts, the most significant polymorphism being rs151091899 (p-value: 3.1 × 10−05; odds ratio: 5.4) in cohort 3. The genotype of one polymorphism of TRPV3 was associated with a differential expression of genes linked to cardiac malformations. In conclusion, new strategies using exome sequence data have revealed TRPV3 as a new gene associated with cardioembolic stroke. This strategy among others might be useful in finding new genes associated with complex genetic diseases.

A dynamical system model for tumour-immune system interaction together with a method to mimic radiation therapy are proposed. A large population of virtual patients is simulated following an ideal radiation treatment. A characteristic parameter, the immune system-tumor efficiency ratio (ISTER) is introduced. ISTER dependence of treatment success and other features are studied. Radiotherapy treatment dose optimization, following ALARA (As Low As Reasonably Achievable) criterion, as well as a patient classification are drawn from the statistics results.

The objective of this study was to identify genetic variation in genes encoding death receptors and signals that modulate their activity. After conducting a meta-analysis with five previous genome-wide association studies and aggregated data, the most significant signals, (TNF locus: rs2395488, rs2534672, and rs9267445; and FASLG locus: rs730278), were replicated in 1,046 cases and 372 controls. The rs2395488 and rs2534672 markers showed a modest protective effect (OR = 0.849, p = 0.49780;OR= 0.687, p = 0.11335), in contrast to rs730278 marker (OR = 1.146, p = 0.17212), which did not follow the previous effect direction; in any case it reached the significance level. Final meta-analysis, adding the replication sample, confirmed these observations. We concluded that FASLG marker is not etiologically linked to Alzheimer’s disease. However, single nucleotide polymorphisms around TNF locus require further analyses in order to explain the association between Alzheimer’s disease and human leukocyte antigen.

Introduction The identification of early, preferably presymptomatic, biomarkers and true etiologic factors for Alzheimer’s disease (AD) is the first step toward establishing effective primary and secondary prevention programs. Consequently, the search for a relatively inexpensive and harmless biomarker for AD continues. Despite intensive research worldwide, to date there is no definitive plasma or blood biomarker indicating high or low risk of conversion to AD. Methods Magnetic resonance imaging and β-amyloid (Aβ) levels in three blood compartments (diluted in plasma, undiluted in plasma and cell-bound) were measured in 96 subjects (33 with mild cognitive impairment, 14 with AD and 49 healthy controls). Pearson correlations were completed between 113 regions of interest (ROIs) (45 subcortical and 68 cortical) and Aβ levels. Pearson correlation analyses adjusted for the covariates age, sex, apolipoprotein E (ApoE), education and creatinine levels showed neuroimaging ROIs were associated with Aβ levels. Two statistical methods were applied to study the major relationships identified: (1) Pearson correlation with phenotype added as a covariate and (2) a meta-analysis stratified by phenotype. Neuroimaging data and plasma Aβ measurements were taken from 630 Alzheimer’s Disease Neuroimaging Initiative (ADNI) subjects to be compared with our results. Results The left hippocampus was the brain region most correlated with Aβ(1–40) bound to blood cell pellets (partial correlation (pcor) = −0.37, P = 0.0007) after adjustment for the covariates age, gender and education, ApoE and creatinine levels. The correlation remained almost the same (pcor = −0.35, P = 0.002) if phenotype is also added as a covariate. The association between both measurements was independent of cognitive status. The left hemisphere entorhinal cortex also correlated with Aβ(1–40) cell-bound fraction. AB128 and ADNI plasma Aβ measurements were not related to any brain morphometric measurement. Conclusions Association of cell-bound Aβ(1–40) in blood with left hippocampal volume was much stronger than previously observed in Aβ plasma fractions. If confirmed, this observation will require careful interpretation and must be taken into account for blood amyloid-based biomarker development.

Transmembrane Protein 106B SNP rs1990622 was recently shown to modify the risk of frontotemporal lobar degeneration with TDP-43 inclusions (FTD-TDP). An independent replication study of this genetic variant was performed in 381 individuals from Catalonia (Spain). By applying a recessive model, a tendency toward an association with FTD risk was observed in our case-control study (age- and gender-adjusted odds ratio = 0.57; p = 0.082). Importantly, meta-analysis of available studies also supports a recessive effect for rs1990622 CC genotype (OR = 0.70; CI 95% [0.57-0.85]; p = 0.0003) and demonstrates the existence of statistical heterogeneity due to an inherent pathological heterogeneity between series (p = 0.00014). We conclude that TMEM106B is associated with FTD, although the extent of this effect is difficult to be estimated by using clinical FTD series.

Objective: Postmortem and genetic studies of clinically diagnosed Frontotemporal dementia (FTD) patients suggest that a number of clinically diagnosed FTD patients are actually "frontal variants" of Alzheimer's disease (fvAD). The purpose of this study was to evaluate this hypothesis by combining neuropathological data, genetic association studies of APOE, phenotype-APOE genotype correlations and discriminant analysis techniques. Methods: Neuropathological information on 24 FTD cases, genetic association studies of APOE (168 FTD, 3083 controls and 2528 AD), phenotypegenotype correlations and discriminant techniques (LDA, logistic regression and decision trees) were combined to identify fvAD patients within a clinical FTD series. Results: Four of 24 FTLD patients (16.6%) met criteria for definite AD. By comparing allele and genotype frequencies of APOE in controls, FTD and AD groups and by applying the Hardy- Weinberg equilibrium law (HWE), we inferred a consistent (17.2%) degree of AD contamination in clinical FTD. A penetrance analysis for APOE 4 genotype in the FTD series identified 14 features for discrimination analysis. These features were compared between clinical AD (n=332) and clinical FTD series (n=168) and classifiers were constructed usinglinear discriminant analysis logistic regression or decision tree techniques. The classifier had 92.8% sensitivity to FTD and 93.4% sensitivity to AD relative to neuropathology (global AUC=0.939, p<

A nonextensive survival fraction model is extended from single dose to fractionated radiotherapy treatments, ruled by an extensivity index and a critical annihilation dose. The expected effects of doses given simultaneously and separately in time, lead to the general expression for the survival fraction with both limits linked by a new parameter describing the evolution of tissue radioresistance. This parameter determines the critical dose per fraction needed to achieve total target annihilation. The conclusion is that as the extensivity index of the tissue characterises the primary response of the tissue to radiation, the success of fractionation depends only on this critical dose per fraction value.

The expression of survival factors for radiation damaged cells is currently based on probabilistic assumptions and experimentally fitted for each tumor, radiation, and conditions. Here, we show how the simplest of these radiobiological models can be derived from the maximum entropy principle of the classical Boltzmann-Gibbs expression. We extend this derivation using the Tsallis entropy and a cutoff hypothesis, motivated by clinical observations. The obtained expression shows a remarkable agreement with the experimental data found in the literature.

It is possible to find the optimized radiation dose per session for a radiotherapy (RT) treatment, using a population dynamics model. This has already been done in a previous work for a protocol with 30 sessions and a fixed dose per session. Extending this model to other protocols, with a variable number of sessions, we could change the radiation dosage while keeping the success probability of treatment at its maximum value. This could help the RT oncology service managers to plan the sequence of patients and treatments adapting it to the facilities of the oncology service. Besides, if tumor surrounding tissue is not able to afford a high dosage, it could be useful to extend the treatment to a higher number of low dose radiation sessions, keeping an optimal treatment.

A cytokine-based periodic immunotherapy treatment is included in a model of tumour growth with a delay. The effects of dose schedule are studied in the case of a weak immune system and a growing tumour. We find the existence of 'metastable' states (that may last for tens of years) induced by the treatment and also potentially adverse effects of the dosage frequency on the stabilization of the tumour. These two effects depend on the delay between the tumour growth and the immune system response, the cytokine dose burden, and other parameters considered in the model.

The effects of radiation on a tissue (being it healthy or cancerous) are well described by current linear-quadratic (LQ) radiobiological model for low absorbed doses around the 2 Gy often used in clinical fractionation. However, experimental data show a disagreement between the predicted and the observed effect of large doses. The Sotolongo et al. (2011) radiobiological (SRB) model, derived from Tsallis nonextensive entropy, has shown a good agreement with experiments for high absorbed doses, where LQ overestimates the dose required for a required effect. Other studies have reported a crossover in LQ model where its effects are underestimated for large doses. In this paper we develop a mechanistic version of the SRB model and show that it can reproduce both behaviors with a minimum set of assumptions. We compare the results of our simulations with some data reported in the literature. We also trivially adapt this model to fractionated radiotherapy and, in particular, to hypofractionation for which we draw some conclusions.

Se simuló computacionalmente un gran número de pacientes bajo tratamiento de radioterapia, mediante un sistema dinámico. De los resultados, se halló un método para cambiar el número de sesiones de radiación manteniendo óptimo el tratamiento. Además, se obtuvo que la relación entre la fracción sistema inmune-eficiencia tumoral para un paciente dado y la máxima probabilidad de éxito del tratamiento sigue una ley de potencias.

Several radiobiological models mimic the biologic effect of one single radiation dose on a living tissue. However, the actual fractionated radiotherapy requires accounting for a new magnitude, i.e., time. Here, we explore the biological consequences posed by the mathematical prolongation of a previous single radiation model to fractionated treatment. The survival fraction is obtained, together with the equivalent physical dose, in terms of a time dependent factor (similar to a repair coefficient) describing the tissue trend to recovering its radioresistance. The model describes how dose fractions add up to obtain the equivalent dose and how the repair coefficient poses a limit to reach an equivalent dose equal to the critical one that would completely annihilate the tumor. On the other hand, the surrounding healthy tissue is a limiting factor to treatment planning. This tissue has its own repair coefficient and thus should limit the equivalent dose of a treatment. Depending on the repair coefficient and the critical dose of each tissue, unexpected results (failure to fully remove the tumor) can be obtained. To illustrate these results and predictions, some realistic example calculations will be performed using parameter values within actual clinical ranges. In conclusion, the model warns about treatment limitations and proposes ways to overcome them.